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Periodic table of protein complexes, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Periodic table of protein complexes

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Periodic Table of Protein Complexes

http://www.technologynetworks.com/Proteomics/news.aspx?ID=186248

New tool helps to visualise, understand and predict how proteins combine to drive biological processes

A new ‘periodic table’ of protein complexes has been developed that provides a unified way to classify and visualise protein complexes, providing a valuable tool for biotechnology and the engineering of novel complexes.

This study also provides insights into evolutionary distribution of different types of existing protein complexes.

The Periodic Table of Protein Complexes offers a new way of looking at the enormous variety of structures that proteins can build in nature, which ones might be discovered next, and predicting how entirely novel structures could be engineered. Created by an interdisciplinary team led by researchers at the Wellcome Genome Campus and the University of Cambridge, the Table provides a valuable tool for research into evolution and protein engineering.

Almost every biological process depends on proteins interacting and assembling into complexes in a specific way, and many diseases are associated with problems in complex assembly. The principles underpinning this organisation are not yet fully understood, but by defining the fundamental steps in the evolution of protein complexes, the new ‘periodic table’ presents a systematic, ordered view on protein assembly, providing a visual tool for understanding biological function.

“Evolution has given rise to a huge variety of protein complexes, and it can seem a bit chaotic. But if you break down the steps proteins take to become complexes, there are some basic rules that can explain almost all of the assemblies people have observed so far.”

 

Dr Joe Marsh, formerly of the Wellcome Genome Campus and now of the MRC Human Genetics Unit at the University of Edinburgh.

Different ballroom dances can be seen as an endless combination of a small number of basic steps. Similarly, the ‘dance’ of protein complex assembly can be seen as endless variations on dimerization (one doubles, and becomes two), cyclisation (one forms a ring of three or more) and subunit addition (two different proteins bind to each other). Because these happen in a fairly predictable way, it’s not as hard as you might think to predict how a novel protein would form.

“We’re bringing a lot of order into the messy world of protein complexes. Proteins can keep go through several iterations of these simple steps, adding more and more levels of complexity and resulting in a huge variety of structures. What we’ve made is a classification based on these underlying principles that helps people get a handle on the complexity.”

Dr Sebastian Ahnert of the Cavendish Laboratory at the University of Cambridge

The exceptions to the rule are interesting in their own right, as are the subject of on-going studies.

“By analysing the tens of thousands of protein complexes for which three-dimensional structures have already been experimentally determined, we could see repeating patterns in the assembly transitions that occur – and with new data from mass spectrometry we could start to see the bigger picture.”

Dr Joe Marsh

“The core work for this study is in theoretical physics and computational biology, but it couldn’t have been done without the mass spectrometry work by our colleagues at Oxford University. This is yet another excellent example of how extremely valuable interdisciplinary research can be.”

Dr Sarah Teichmann, Research Group Leader at the Wellcome Trust Sanger Institute and the European Bioinformatics Institute (EMBL-EBI)

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Rhodopsin role in ciliary trafficking

Jillian N Pearring
Department of Ophthalmology, Duke University School of Medicine, Durham, United States
No competing interests declared

” data-author-inst=”DukeUniversitySchoolofMedicineUnitedStates”>Jillian N Pearring

William J Spencer
Department of Ophthalmology, Duke University School of Medicine, Durham, United States
No competing interests declared

” data-author-inst=”DukeUniversitySchoolofMedicineUnitedStates”>William J Spencer

Eric C Lieu
Department of Ophthalmology, Duke University School of Medicine, Durham, United States
No competing interests declared

” data-author-inst=”DukeUniversitySchoolofMedicineUnitedStates”>Eric C Lieu, 

Vadim Y Arshavsky
Department of Ophthalmology, Duke University School of Medicine, Durham, United States
For correspondence: vadim.arshavsky@duke.edu
No competing interests declared

” data-author-inst=”DukeUniversitySchoolofMedicineUnitedStates”>Vadim Y Arshavsky
eLife 2015;10.7554/eLife.12058   http://dx.doi.org/10.7554/eLife.12058

Sensory cilia are populated by a select group of signaling proteins that detect environmental stimuli. How these molecules are delivered to the sensory cilium and whether they rely on one another for specific transport remains poorly understood. Here, we investigated whether the visual pigment, rhodopsin, is critical for delivering other signaling proteins to the sensory cilium of photoreceptor cells, the outer segment. Rhodopsin is the most abundant outer segment protein and its proper transport is essential for formation of this organelle, suggesting that such a dependency might exist. Indeed, we demonstrated that guanylate cyclase-1, producing the cGMP second messenger in photoreceptors, requires rhodopsin for intracellular stability and outer segment delivery. We elucidated this dependency by showing that guanylate cyclase-1 is a novel rhodopsin-binding protein. These findings expand rhodopsin’s role in vision from being a visual pigment and major outer segment building block to directing trafficking of another key signaling protein.

 

Photoreceptor cells transform information entering the eye as photons into patterns of neuronal electrical activity. This transformation takes place in the sensory cilium organelle, the outer segment. Outer segments are built from a relatively small set of structural and signaling proteins, including components of the classical GPCR phototransduction cascade. Such a distinct functional and morphological specialization allow outer segments to serve as a nearly unmatched model system for studying general principles of GPCR signaling (Arshavsky et al., 2002) and, in more recent years, a model for ciliary trafficking (Garcia-Gonzalo and Reiter, 2012; Nemet et al., 2015; Pearring et al., 2013; Schou et al., 2015; Wang and Deretic, 2014). Despite our deep understanding of visual signal transduction, little is known how the outer segment is populated by proteins performing this function. Indeed, nearly all mechanistic studies of outer segment protein trafficking were devoted to rhodopsin (Nemet et al., 2015; Wang and Deretic, 2014), which is a GPCR visual pigment comprising the majority of the outer segment membrane protein mass (Palczewski, 2006). The mechanisms responsible for outer segment delivery of other transmembrane proteins remain essentially unknown. Some of them contain short outer segment targeting signals, which can be identified through site-specific mutagenesis (Deretic et al., 1998; Li et al., 1996; Pearring et al., 2014; Salinas et al., 2013; Sung et al., 1994; Tam et al., 2000; Tam et al., 2004). A documented exception is retinal guanylate cyclase 1 (GC-1), whose exhaustive mutagenesis did not yield a distinct outer segment targeting motif (Karan et al., 2011).

GC-1 is a critical component of the phototransduction machinery responsible for synthesizing the second messenger, cGMP (Wen et al., 2014). GC-1 is the only guanylate cyclase isoform expressed in the outer segments of cones and the predominant isoform in rods (Baehr et al., 2007; Yang et al., 1999). GC-1 knockout in mice is characterized by severe degeneration of cones and abnormal light-response recovery kinetics in rods (Yang et al., 1999). Furthermore, a very large number of GC-1 mutations found in human patients cause one of the most severe forms of early onset retinal dystrophy, called Leber’s congenital amaurosis (Boye, 2014; Kitiratschky et al., 2008). Many of these mutations are located outside the catalytic site of GC-1, which raises great interest to understanding the mechanisms of its intracellular processing and trafficking.

In this study, we demonstrate that, rather than relying on its own targeting motif, GC-1 is transported to the outer segment in a complex with rhodopsin. We conducted a comprehensive screen of outer segment protein localization in rod photoreceptors of rhodopsin knockout (Rho-/- ) mice and found that GC-1 was the only protein severely affected by this knockout. We next showed that this unique property of GC-1 is explained by its interaction with rhodopsin, which likely initiates in the biosynthetic membranes and supports both intracellular stability and outer segment delivery of this enzyme. These findings explain how GC-1 reaches its specific intracellular destination and also expand the role of rhodopsin in supporting normal vision by showing that it guides trafficking of another key phototransduction protein.

 

GC-1 is the outer segment-resident protein severely down-regulated in rhodopsin knockout rods

GC-1 stability and trafficking require the transmembrane core of rhodopsin but not its outer 119 segment targeting domain

GC-1 is a rhodopsin-interacting protein

 

The findings reported in this study expand our understanding of how the photoreceptor’s sensory cilium is populated by its specific membrane proteins. We have found that rhodopsin serves as an interacting partner and a vehicle for ciliary delivery of a key phototransduction protein, GC-1. This previously unknown function adds to the well-established roles of rhodopsin as a GPCR visual pigment and a major building block of photoreceptor membranes. We further showed that GC-1 is unique in its reliance on rhodopsin, as the other nine proteins tested in this study were expressed in significant amounts and faithfully localized to rod outer segments in the absence of rhodopsin.

Our data consolidate a number of previously published observations, including a major puzzle related to GC-1: the lack of a distinct ciliary targeting motif encoded in its sequence. The shortest recombinant fragment of GC-1 which localized specifically to the outer segment was found to be very large and contain both transmembrane and cytoplasmic domains (Karan et al., 2011). Our study shows that GC-1 delivery requires rhodopsin and, therefore, can rely on specific targeting information encoded in the rhodopsin molecule. Interestingly, we also found that this information can be replaced by an alternative ciliary targeting sequence from a GPCR not endogenous to photoreceptors. This suggests that the functions of binding/stabilization of GC-1 and ciliary targeting are performed by different parts of the rhodopsin molecule. Our findings also shed new light on the report that both rhodopsin and GC-1 utilize intraflagellar transport (IFT) for their ciliary trafficking and co-precipitate with IFT proteins (Bhowmick et al., 2009). The authors hypothesized that GC-1 plays a primary role in assembling cargo for the IFT particle bound for ciliary delivery. Our data suggest that it is rhodopsin that drives this complex, at least in photoreceptor cells where these proteins are specifically expressed. Unlike GC-1’s reliance on rhodopsin for its intracellular stability or outer segment trafficking, rhodopsin does not require GC-1 as its expression level and localization remain normal in rods of GC-1 knockout mice ((Baehr et al., 2007) and this study). The outer segment trafficking of cone opsins is not affected by the lack of GC-1 either (Baehr et al., 2007; Karan et al., 2008), although GC-1 knockout cones undergo rapid degeneration, likely because they do not express GC-2 – an enzyme with redundant function. The primary role of rhodopsin in guiding GC-1 to the outer segment is further consistent with rhodopsin directly interacting with IFT20, a mobile component of the IFT complex responsible for recruiting IFT cargo at the Golgi network (Crouse et al., 2014; Keady et al., 2011).

It was also reported that GC-1 trafficking requires participation of chaperone proteins, most importantly DnaJB6 (Bhowmick et al., 2009). Our data suggest that GC-1 interaction with DnaJB6 is transient, most likely in route to the outer segment, since we were not able to co-precipitate DnaJB6 with GC-1 from whole retina lysates (Figure 5). In contrast, the majority of GC-1 co-precipitates with rhodopsin from these same lysates, suggesting that these proteins remain in a complex after being delivered to the outer segment. Although our data do not exclude that the mature GC-1-rhodopsin complex may contain additional protein component(s), our attempts to identify such components by mass spectrometry have not yielded potential candidates.

Interestingly, GC-1 was previously shown to stably express in cell culture where it localizes to either ciliary or intracellular membranes (Bhowmick et al., 2009; Peshenko et al., 2015). This strikes at the difference between the composition of cellular components supporting membrane protein stabilization and transport in cell culture models versus functional photoreceptors. The goal of future experiments is to determine whether these protein localization patterns would be affected by co-expressing GC-1 with rhodopsin, thereby gaining further insight into the underlying intracellular trafficking mechanisms.

Finally, GC-1 trafficking was reported to depend on the small protein, RD3, thought to stabilize both guanylate cyclase isoforms, GC-1 and GC-2, in biosynthetic membranes (Azadi et al., 2010; Zulliger et al., 2015). In the case of GC-1, this stabilization would be complementary to that by rhodopsin and potentially could take place at different stages of GC-1 maturation and trafficking in photoreceptors. Another proposed function of RD3 is to inhibit the activity of guanylate cyclase isoforms outside the outer segment in order to prevent undesirable cGMP synthesis in other cellular compartments (Peshenko et al., 2011a).

In summary, this study explains how GC-1 reaches its intracellular destination without containing a dedicated targeting motif, expands our understanding of the role of rhodopsin in photoreceptor biology and extends the diversity of signaling proteins found in GPCR complexes to a member of the guanylate cyclase family. Provided that the cilium is a critical site of GPCR signaling in numerous cell types (Schou et al., 2015), it would be interesting to learn whether other ciliary GPCRs share rhodopsin’s ability to stabilize and deliver fellow members of their signaling pathways

 

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brown adipocyte protein CIDEA promotes lipid droplet fusion

brown adipocyte protein CIDEA promotes lipid droplet fusion

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

 

 

The brown adipocyte protein CIDEA promotes lipid droplet fusion via a phosphatidic acid-binding

Parker, Nicholas T Ktistakis, Ann M Dixon, Judith Klein-Seetharaman, Susan Henry, Mark Christian Dirk Dormann, Gil-Soo Han, Stephen A Jesch, George M Carman, Valerian Kagan, et al.

eLife 2015;10.7554/eLife.07485     http://dx.doi.org/10.7554/eLife.07485

 

Maintenance of energy homeostasis depends on the highly regulated storage and release of triacylglycerol primarily in adipose tissue and excessive storage is a feature of common metabolic disorders. CIDEA is a lipid droplet (LD)-protein enriched in brown adipocytes promoting the enlargement of LDs which are dynamic, ubiquitous organelles specialized for storing neutral lipids. We demonstrate an essential role in this process for an amphipathic helix in CIDEA, which facilitates embedding in the LD phospholipid monolayer and binds phosphatidic acid (PA). LD pairs are docked by CIDEA trans-complexes through contributions of the N-terminal domain and a C-terminal dimerization region. These complexes, enriched at the LD-LD contact site, interact with the cone-shaped phospholipid PA and likely increase phospholipid barrier permeability, promoting LD fusion by transference of lipids. This physiological process is essential in adipocyte differentiation as well as serving to facilitate the tight coupling of lipolysis and lipogenesis in activated brown fat.

 

Evolutionary pressures for survival in fluctuating environments that expose organisms to times of both feast and famine have selected for the ability to efficiently store and release energy in the form of triacyclglycerol (TAG). However, excessive or defective lipid storage is a key feature of common diseases such as diabetes, atherosclerosis and the metabolic syndrome (1). The organelles that are essential for storing and mobilizing intracellular fat are lipid droplets (LDs) (2). They constitute a unique cellular structure where a core of neutral lipids is stabilized in the hydrophilic cytosol by a phospholipid monolayer embedding LD-proteins. While most mammalian 46 cells present small LDs (<1 Pm) (3), white (unilocular) adipocytes contain a single giant LD occupying most of their cell volume. In contrast, brown (multilocular) adipocytes hold multiple LDs of lesser size, increasing the LD surface/volume ratio which facilitates the rapid consumption of lipids for adaptive thermogenesis (4).

The exploration of new approaches for the treatment of metabolic disorders has been stimulated by the rediscovery of active brown adipose tissue (BAT) in adult humans (5, 6) and by the induction of multilocular brown-like cells in white adipose tissue (WAT) (7). The multilocular morphology of brown adipocytes is a defining characteristic of these cells along with expression of genes such as Ucp1. The acquisition of a unilocular or multilocular phenotype is likely to be controlled by the regulation of LD growth. Two related proteins, CIDEA and CIDEC promote LD enlargement in adipocytes (8-10), with CIDEA being specifically found in BAT. Together with CIDEB, they form the CIDE (cell death-inducing DFF45-like effector) family of LD-proteins, which have emerged as important metabolic regulators (11).

Different mechanisms have been proposed for LD enlargement, including in situ neutral lipid synthesis, lipid uptake and LD-LD coalescence (12-14). The study of CIDE 62 proteins has revealed a critical role in the LD fusion process in which a donor LD progressively transfers its content to an acceptor LD until it is completely absorbed (15). However, the underlying mechanism by which CIDEC and CIDEA facilitate the interchange of triacylglycerol (TAG) molecules between LDs is not understood. In the present study, we have obtained a detailed picture of the different steps driving this LD enlargement process, which involves the stabilization of LD pairs, phospholipid binding, and the permeabilization of the LD monolayer to allow the transference of lipids.

 

CIDEA expression mimics the LD dynamics observed during the differentiation of brown adipocytes

Phases of CIDEA activity: LD targeting, LD-LD docking and LD growth

A cationic amphipathic helix in C-term drives LD targeting

The amphipathic helix is essential for LD enlargement

LD-LD docking is induced by the formation of CIDEA complexes

CIDEC differs from CIDEA in its dependence on the N-term domain

CIDEA interacts with Phosphatidic Acid

PA is required for LD enlargement

 

The Cidea gene is highly expressed in BAT, induced in WAT following cold exposure (46), and is widely used by researchers as a defining marker to discriminate brown or brite adipocytes from white adipocytes (7, 28). As evidence indicated a key role in the LD biology (47) we have characterized the mechanism by which CIDEA promotes LD enlargement, which involves the targeting of LDs, the docking of LD pairs and the transference of lipids between them. The lipid transfer step requires the interaction of CIDEA and PA through a cationic amphipathic helix. Independently of PA-binding, this helix is also responsible for anchoring CIDEA in the LD membrane. Finally, we demonstrate that the docking of LD pairs is driven by the formation of CIDEA complexes involving the N-term domain and a C-term interaction site.

CIDE proteins appeared during vertebrate evolution by the combination of an ancestor N-term domain and a LD-binding C-term domain (35). In spite of this, the full process of LD enlargement can be induced in yeast by the sole exogenous expression of 395 CIDEA, indicating that in contrast to SNARE-triggered vesicle fusion, LD fusion by lipid transference does not require the coordination of multiple specific proteins (48). Whereas vesicle fusion implicates an intricate restructuring of the phospholipid bilayers, LD fusion is a spontaneous process that the cell has to prevent by tightly controlling their phospholipid composition (23). However, although phospholipid-modifying enzymes have been linked with the biogenesis of LDs (49, 50), the implication of phospholipids in physiologic LD fusion processes has not been previously described.

Complete LD fusion by lipid transfer can last several hours, during which the participating LDs remain in contact. Our results indicate that both the N-term domain and a C-term dimerization site (aa 126-155) independently participate in the docking of LD pairs by forming trans interactions (Fig. 7). Certain mutations in the dimerization sites that do not eliminate the interaction result in a decrease on the TAG transference efficiency, reflected on the presence of small LDs docked to enlarged LDs. This suggests that in addition to stabilizing the LD-LD interaction, the correct conformation of the 409 CIDEA complexes is necessary for optimal TAG transfer. Furthermore, the formation of stable LD pairs is not sufficient to trigger LD fusion by lipid transfer. In fact, although LDs can be tightly packed in cultured adipocytes, no TAG transference across neighbour LDs is observed in the absence of CIDE proteins (15), showing that the phospholipid monolayer acts as a barrier impermeable to TAG. Our CG-MD simulations indicate that certain TAG molecules can escape the neutral lipid core of the LD and be integrated within the aliphatic chains of the phospholipid monolayer. This could be a transition state 416 prior to the TAG transference and our data indicates that the docking of the amphipathic helix in the LD membrane could facilitate this process. However, the infiltrated TAGs in LD membranes in the presence of mutant helices, or even in the absence of docking, suggests that this is not enough to complete the TAG transference.

To be transferred to the adjacent LD, the TAGs integrated in the hydrophobic region of the LD membrane should cross the energy barrier defined by the phospholipid polar heads, and the interaction of CIDEA with PA could play a role in this process, as suggested by the disruption of LD enlargement by the mutations preventing PA-binding (K167E/R171E/R175E) and the inhibition of CIDEA after PA depletion. The minor effects observed with more conservative substitutions in the helix, suggests that the presence of positive charges is sufficient to induce TAG transference by attracting anionic phospholipids present in the LD membrane. PA, which requirement is indicated by our PA-depletion experiments, is a cone-shaped anionic phospholipid which could locally destabilize the LD monolayer by favoring a negative membrane curvature incompatible with the spherical LD morphology (51). Interestingly, while the zwitterion PC, the main component of the monolayer, stabilizes the LD structure (23), the negatively charged PA promote their coalescence (29). This is supported by our CD-MD results which resulted in a deformation of the LD shape by the addition of PA. We propose a model in which the C-term amphipathic helix positions itself in the LD monolayer and interacts with PA molecules in its vicinity, which might include trans interactions with PA in the adjacent LD. The interaction with PA disturbs the integrity of the phospholipid barrier at the LD-LD interface, allowing the LD to LD transference of TAG molecules integrated in the LD membrane (Fig. 7). Additional alterations in the LD composition could be facilitating TAG transference, as differentiating adipocytes experience a reduction in saturated fatty acids in the LD phospholipids (52), and in their PC/PE ratio (53) which could increase the permeability of the LD membranes, and we previously observed that a change in the molecular structures of TAG results in an altered migration pattern to the LD surface (32).

During LD fusion by lipid transfer, the pressure gradient experienced by LDs favors TAG flux from small to large LDs (15). However, the implication of PA, a minor component of the LD membrane, could represent a control mechanism, as it is plausible that the cell could actively influence the TAG flux direction by differently regulating the levels of PA in large and small LDs, which could be controlled by the activity of enzymes such as AGPAT3 and LIPIN-1J (13, 30). This is a remarkable possibility, as a switch in the favored TAG flux direction could promote the acquisition of a multilocular phenotype and facilitate the browning of WAT (24). Interestingly, Cidea mRNA is the LD protein- encoding transcript that experiences the greatest increase during the cold-induced process by which multilocular BAT-like cells appear in WAT (24). Furthermore, in BAT, cold exposure instigates a profound increase in CIDEA protein levels that is independent of transcriptional regulation (54). The profound increase in CIDEA is coincident with elevated lipolysis and de novo lipogenesis that occurs in both brown and white adipose tissues after E-adrenergic receptor activation (55). It is likely that CIDEA has a central role in coupling these processes to package newly synthesized TAG in LDs for subsequent lipolysis and fatty acid oxidation. Importantly, BAT displays high levels of glycerol kinase activity (56, 57) that facilitates glycerol recycling rather than release into the blood stream, following induction of lipolysis (58), which occurs in WAT. Hence, the reported elevated glycerol released from cells depleted of CIDEA (28) is likely to be a result of decoupling lipolysis from the ability to efficiently store the products of lipogenesis in LDs and therefore producing a net increase in detected extracellular glycerol. This important role of CIDEA is supported by the marked depletion of TAG in the BAT of Cidea null mice following overnight exposure to 4 °C (28) and our findings that CIDEA-dependent LD enlargement is maintained in a lipase negative yeast strain.

Cidea and the genes that are required to facilitate high rates of lipolysis and lipogenesis are associated with the “browning” of white fat either following cold exposure (46) or in genetic models such as RIP140 knockout WAT (59). The induction of a brown- like phenotype in WAT has potential benefits in the treatment and prevention of metabolic disorders (60). Differences in the activity and regulation of CIDEC and CIDEA could also be responsible for the adoption of unilocular or multilocular phenotypes. In addition to their differential interaction with PLIN1 and 5, we have observed that CIDEC is more resilient to the deletion of the N-term than CIDEA, indicating that it may be less sensitive to regulatory posttranslational modifications of this domain. This robustness of CIDEC activity together with its potentiation by PLIN1, could facilitate the continuity of the LD enlargement in white adipocytes until the unilocular phenotype is achieved. In contrast, in brown adipocytes expressing CIDEA the process would be stopped at the multilocular stage for example due to post-translational modifications that modulate the function or stability of the protein or alteration of the PA levels in LDs.

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Complexity of Protein-Protein Interactions

Complexity of Protein-Protein Interactions, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 1: Next Generation Sequencing (NGS)

Complexity of Protein-Protein Interactions

Curator: Larry H. Bernstein, MD, FCAP

Cracking the Complex

Using mass spec to study protein-protein interactions

By Jeffrey M. Perkel | November 1, 2015

http://www.the-scientist.com//?articles.view/articleNo/44317/title/Cracking-the-Complex/

http://www.the-scientist.com/November2015/LT_1.jpg

Mass spectrometry is a proteomics workhorse. By precisely measuring polypeptide masses, researchers can identify and sequence those molecules, and characterize whether and how they have been chemically modified. To twist a phrase, by their masses you shall know them.

But many proteins do not act in isolation. Critical biological processes such as DNA replication, transcription, translation, cell division, and energy generation rely on the action of massive protein assemblies, many of which comprise dozens of subunits. While these clusters are ripe for study, few traditional mass spectrometric methods can handle them.

Indeed, protein complexes are unwieldy for many types of analysis, says Philip Compton, director of instrumentation at the Proteomics Center of Excellence at Northwestern University in Evanston, Illinois. Most complexes are held together by noncovalent interactions, assemble only transiently, or are located in the cell membrane—all of which complicate sample preparation, he explains. Also, while some complexes are relatively abundant, others are rare, further thwarting detection and analysis.

For mass spectrometry specifically, however, the problem with analyzing protein complexes, which can weigh in at 500 kDa, is size. “In a mass spec, things of that size have traditionally been fairly difficult to handle,” Compton says. Even if you can deliver them into the spectrometer itself, you need a way to figure out which proteins are present, and in what stoichiometry. Plus, normal sample preparation procedures tend to denature proteins, ripping complexes apart.

Still, researchers are increasingly keen to train their mass specs on intact protein assemblies. The Scientistasked four protein-complex experts about the approaches they use in their own labs. This is what they said.

Determining subunit composition 

http://www.the-scientist.com/November2015/LT1_2.jpg

GETTING TOGETHER: Lactate dehydrogenase from human skeletal muscle comprises four identical M subunits, shown here in different colors.  FVASCONCELLOS/WIKIMEDIA COMMONS

RESEARCHER: Philip Compton, Director of Instrumentation, Proteomics Center of Excellence, Northwestern University

PROJECT: High-throughput top-down proteomics

SOLUTION: If protein complexes are onions, Compton needs a way to iteratively peel off the layers to see what’s inside. Working with researchers at Thermo Fisher Scientific, Compton is developing an Orbitrap-based mass spectrometer that can do just that, or perform what is called an MS3 study.

Basically, an MS3 experiment involves weighing all the complexes in a sample fraction—there could be as many as 10 or 15 at a time—grabbing one, smashing it into inert-gas molecules to eject a subunit, weighing and sequencing the cast-off piece, and then repeating the process.

That’s the goal, but because that instrument is not yet built, Compton must temporarily content himself with what he calls a “pseudo-MS3” experiment. Basically, instead of one seamless workflow, the instrument shatters the complex, weighs the pieces that come off it, and then repeats the process, only this time capturing and fragmenting those ejected pieces for subsequent analysis (Anal Chem, 85:11163-73, 2013). “We’re kind of splitting it into these two different steps; that accomplishes essentially the same thing,” Compton says.

Compton and his team are still ironing out the kinks, but they have begun applying the approach to protein complexes involved in metabolism. One of these, lactate dehydrogenase (LDH), is a 145-kDa tetramer comprising M (muscle) and H (heart) subunits that can exist in any of five configurations (MMMM, MMMH, MMHH, MHHH, and HHHH). Using the MS3 workflow, Compton says he can differentiate these “multiproteoform assemblies,” as well as any posttranslational modifications those subunits may bear, and determine the abundance of each. Now he hopes to apply the approach to quantify LDH differences between cell and tissue types.

From Protein Complexes to Subunit Backbone Fragments: A Multi-stage Approach to Native Mass Spectrometry

Thermo Fisher Scientific, 28199 Bremen, Germany
Northwestern University, Evanston, Illinois 60208, United States
Anal. Chem., 2013, 85 (23), pp 11163–11173    DOI: http://dx.doi.org:/10.1021/ac4029328
Publication Date (Web): November 15, 2013   Copyright © 2013 American Chemical Society
Abstract Image
http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/ancham/2013/ancham.2013.85.issue-23/ac4029328/production/images/medium/ac-2013-029328_0009.gif
Native mass spectrometry (MS) is becoming an important integral part of structural proteomics and system biology research. The approach holds great promise for elucidating higher levels of protein structure: from primary to quaternary. This requires the most efficient use of tandem MS, which is the cornerstone of MS-based approaches. In this work, we advance a two-step fragmentation approach, or (pseudo)-MS3, from native protein complexes to a set of constituent fragment ions. Using an efficient desolvation approach and quadrupole selection in the extended mass-to-charge (m/z) range, we have accomplished sequential dissociation of large protein complexes, such as phosporylase B (194 kDa), pyruvate kinase (232 kDa), and GroEL (801 kDa), to highly charged monomers which were then dissociated to a set of multiply charged fragmentation products. Fragment ion signals were acquired with a high resolution, high mass accuracy Orbitrap instrument that enabled highly confident identifications of the precursor monomer subunits. The developed approach is expected to enable characterization of stoichiometry and composition of endogenous native protein complexes at an unprecedented level of detail.

EXTEND YOUR RANGE: Compton’s team uses a souped-up version of Thermo Fisher’s Orbitrap-based Q Exactive HF mass spectrometer, which among other things features a fourfold wider mass range. Other researchers can perform similar work using Thermo’s Exactive Plus EMR Orbitrap system, an off-the-shelf, “extended mass range” instrument. But, because the EMR lacks the “high-mass isolation capabilities” of Compton’s bespoke hardware, the application range is more limited, he says. “You can still do a similar experiment to us, provided that you have one clean [purified] complex.”

Mapping protein-protein interaction interfaces
RESEARCHER: Igor Kaltashov, Professor of Chemistry, University of Massachusetts Amherst

PROJECT: Probing the interactions of candidate protein therapeutics with their molecular targets

SOLUTION: Most attempts at studying protein complexes deliver them to the mass spec intact. Kaltashov takes a different approach, using a technique called hydrogen-deuterium exchange (HDX).

It works like this: proteins (like other molecules) pass hydrogen atoms back and forth with the solvent that surrounds them. Normally, one hydrogen is simply swapped for another, and nobody is the wiser. But in deuterated (“heavy”) water, as hydrogens are swapped at the protein surface, the protein gets slightly heavier as deuterium molecules replace some of the hydrogens. This allows researchers to probe how accessible different pieces of the protein are to the solvent, based on how much deuterium they pick up from the buffer, and how quickly they do so.

As Kaltashov explains, HDX can be used to study any event that might alter the accessibility of different protein regions to the solvent that surrounds them. Those events include protein folding and aggregation, but also protein-protein interactions. “Once two proteins bind to each other, solvent would be excluded from the interface, and that would be reflected in the hydrogen-deuterium exchange kinetics,” he says. That change is evident when compared to the proteins in isolation.

In a 2009 review, Kaltashov demonstrated the process with transferrin, an iron transport protein, and its receptor. After undergoing the exchange reaction, the proteins were fragmented to peptides and analyzed piecemeal. Some peptides exhibited no hydrogen-deuterium exchange, he says. That suggests they were never exposed to solvent because they were buried inside the protein core. Other peptides exchanged hydrogens with the solvent at the same rate regardless of receptor binding, indicating they are not part of the protein-receptor interface. A third set of peptides, though, exhibited clear differences in the presence and absence of receptor, marking those as elements of the protein-protein interaction domain (Anal Chem, 81:7892-99, 2009).

“You can actually localize these sites and obtain information both on the strength of the binding [interactions] and the structural characteristics of the interface region,” Kaltashov says.

H/D exchange and mass spectrometry in the studies of protein conformation and dynamics: Is there a need for a top-down approach?

Hydrogen/deuterium exchange (HDX) combined with mass spectrometry (MS) detection has matured in recent years to become a powerful tool in structural biology and biophysics. Several limitations of this technique can and will be addressed by tapping into ever expanding arsenal of methods to manipulate ions in the gas phase offered by mass spectrometry.

Keywords: hydrogen/deuterium exchange (HDX), mass spectrometry (MS), protein ion fragmentation, collision-induced dissociation (CAD), electron-capture dissociation (ECD), electron-transfer dissociation (ETD), protein conformation, protein dynamics

Introduction: HDX MS in the context of structural proteomics

The spectacular successes of proteomics and bioinformatics in the past decade have resulted in an explosive growth of information on the composition of complex networks of proteins interacting at the cellular level and beyond. However, a simple inventory of interacting proteins is insufficient for understanding how the components of sophisticated biological machinery work together. Protein interactions with each other, small ligands and other biopolymers are governed by their higher order structure, whose determination on a genome scale is a focus of structural proteomics. Realization that “the structures of individual macromolecules are often uninformative about function if taken out of context”1 is shifting the focus of the inquiry from comprehensive characterization of individual protein structures to structural analysis of protein complexes.

X-ray crystallography remains the mainstay in this field, and high resolution structures of proteins and protein complexes often provide important clues as to how they carry out their diverse functions in vivo. However, individual proteins are not static objects, and their behavior cannot be adequately described based solely on information derived from static snapshots and without taking into consideration their dynamic character.2Conformation and dynamics of small proteins can be probed at high spatial resolution on a variety of time scales using NMR spectroscopy; however, rather unforgiving molecular weight limitations make this technique less suited for the studies of larger proteins and protein complexes.

Mass spectrometry (MS) is playing an increasingly visible role in this field, as it can provide information on protein dynamics on a variety of levels, ranging from interactions with their physiological partners by forming dynamic assemblies3 to large-scale conformational transitions within individual subunits.4 Perhaps one of the most powerful MS-based tools to characterize protein conformation and dynamics is HDX MS, a technique that combined hydrogen/deuterium exchange in solution5 with MS detection of the progress of exchange reactions.6 This technique is certainly not new,7 and in fact already made lasting impact in diverse fields ranging from structural proteomics8 to analysis of biopharmaceutical products.9 Nevertheless, HDX MS methodology is still in a phase where dramatic progress is made, fed by the continued expansion of the experimental armamentarium offered by MS. In particular, better integration of new methods of manipulating ions in the gas phase into HDX MS routine is likely to result in truly transformative changes. This sea change in HDX MS methodology will transform it to a potent tool rivaling NMR in terms of resolution, but without suffering the limitations of this technique.

What information can be deduced from HDX MS measurements? The classic “bottom-up” approach, its challenges and limitations

While the concept of HDX experiment may appear rather transparent (Figure 1), interpretation of the results is usually not. The backbone protection measured in a typical HDX MS experiment is a combination of several factors, as the exchange reaction of each labile hydrogen atom is a convolution of two processes.5The first is a protein motion that makes a particular hydrogen atom exposed to solvent and therefore available for the exchange. This could be a small-scale event, such as relatively frequent local structural fluctuations transiently exposing hydrogen atoms residing close to the protein surface, or a rare global unfolding event exposing atoms sequestered from the solvent in the protein core. The second process is a chemical reaction of exchanging the unprotected labile hydrogen atom with the solvent. The kinetics of this reaction (intrinsic exchange rate) strongly depends on solution temperature and pH (with a minimum at pH 2.5-3 for backbone amides), parameters that obviously have a great influence on the protein dynamics as well.

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Schematic representation of HDX MS experiments: bottom-up (A) and top-down (B) HDX MS.

Since the majority of HDX MS studies target protein dynamics under near-native conditions, the experiments are typically carried out at physiological pH, where the progress of the exchange is followed by monitoring the protein mass change. The direct infusion scheme offers the simplest way to carry out such measurements, either in real time7 or by using on-line rapid mixing.10 However, in many cases these straightforward approaches cannot be used, as they limit the choice of exchange buffer systems to those compatible with electrospray ionization (ESI). To avoid this, HDX can be carried out in any suitable buffer followed by rapid quenching (lowering pH to 2.5-3 and temperature to near 0°C). Dramatic deceleration of the intrinsic exchange rate for backbone amides under these conditions allows the protein solution to be de-salted prior to MS analysis. Additionally, the slow exchange conditions denature most proteins, resulting in facile removal of various binding partners, ranging from small ligands to receptors (their binding to the protein of interest inevitably complicates the HDX MS data interpretation by making accurate mass measurements in the gas phase less straightforward).

An example of such experiments is shown in Figure 2, where HDX is used to probe the higher order structure and conformational dynamics of metal transporter transferrin (Fe2Tf) alone and in the receptor-bound form. Both Tf-metal and Tf-receptor complexes dissociate under the slow exchange conditions prior to MS analysis; therefore, the protein mass evolution in each case reflects solely deuterium uptake in the course of exchange in solution. The extra protection afforded by the receptor binding to Tf persists over an extended period of time, and it may be tempting to assign it to shielding of labile hydrogen atoms at the protein-receptor interface. However, this view is overly simplistic, as the conformational effects of protein binding are frequently felt well beyond the interface region. The difference in the backbone protection levels of receptor-free and receptor-bound forms of Fe2Tf appears to grow during the initial hour of the exchange (Figure 2), reflecting significant stabilization of Fe2Tf higher order structure by the receptor binding. Indeed, while the fast phase of HDX is typically ascribed to frequent local fluctuations (transient perturbations of higher order structure) affecting relatively small protein segments, the slower phases of HDX usually reflect relatively rare, large-scale conformational transitions (transient partial or complete unfolding). This is why global HDX MS measurements similar to those presented in Figure 2 are can be used to obtain quantitative thermodynamic characteristics for protein interaction with a variety of ligands, ranging from metal ions11 and small organic molecules 12 to other proteins13 and oligonucleotides.14

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HDX MS of Fe2Tf in the presence (blue) and the absence (red) of the cognate receptor. The exchange was carried out by diluting the protein stock solution 1:10 in exchange solution (100 mM NH4HCO3 in D2O, pH adjusted to 7.4) and incubating for a certain period of time as indicated on each diagram followed by rapid quenching (lowering pH to 2.5 and temperature to near 0°C). The black trace shows unlabeled protein.

While global HDX MS measurements under near-native conditions provide valuable thermodynamic information on proteins and their interaction with binding partners, structural studies (e.g., localizing the changes in Tf that occur as a result of receptor binding) must rely on the knowledge of exchange kinetics at the local level. This is typically accomplished by carrying out proteolysis under the slow exchange conditions following the quench of HDX.6 Here we will refer to this approach as “bottom-up” HDX MS, by drawing analogy to a bottom-up approach to obtain sequence information.15 An example is shown in Figure 3, where Fe2Tf undergoes exchange in solution in the absence and in the presence of the receptor, followed by rapid quenching of HDX reactions, protein reduction and digestion with pepsin and LC/MS analysis of the deuterium content of individual proteolytic peptides.

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Localizing the influence of the receptor binding on backbone protection of Fe2Tf using bottom-up HDX MS on the physiologically relevant time scale. The panels show isotopic distributions of representative peptic fragments derived from the protein subjected to HDX in the presence (blue) and the absence (red) of the receptor and followed by rapid quenching. Dotted lines indicate deuterium content of unlabeled and fully exchanged peptides. Colored segments within the Fe2Tf/receptor complex show location of the peptic fragments.

Evolution of deuterium content of various peptic fragments in Figure 3 reveals a wide spectrum of protection, which is clearly distributed very unevenly across the protein sequence. While some peptides exhibit nearly complete protection of backbone amides (e.g., segment [396-408] sequestered in the core of the protein C-lobe), exchange in some other segments is fast (e.g., peptide [612-621] in the solvent-exposed loop of the C-lobe). The influence of the receptor binding on the backbone protection is also highly localized. While many segments appear to be unaffected by the receptor binding, there are a few regions where exchange kinetics noticeably decelerates (e.g., segment [71-81] of the N-lobe, which contains several amino acid residues that form Tf/receptor interface according to the available model of the complex based on low-resolution cryo-EM data16).

Although the increased protection of backbone amides proximal to the protein/receptor binding interface is hardly surprising, HDX MS data also reveal a less trivial trend, acceleration of exchange kinetics in some segments of the protein as a result of receptor binding (such behavior is illustrated in Figure 3 with segment [113-134], a part of the N-lobe that is distal to the receptor). Therefore, in addition to mapping binding interface regions, HDX MS also provides a means to localize the protein segments that are affected by the binding indirectly via allosteric mechanisms. However, this example also highlights one of the limitations of HDX MS, namely inadequate spatial resolution. This peptic fragment spans several distinct regions of the protein (an α-helical segment, a β-strand, and two loops). The moderate level of protection observed in this segment in the absence of the receptor binding (fast exchange of three protons followed by slow exchange of the rest) is likely to be a result of averaging out very uneven protection patterns across this peptide. Even smaller peptides may comprise two or more distinct structural elements, such as segment [71-81] spanning three distinct regions of the protein (an α-helical segment, a β-strand, and a loop connecting them).

In some favorable cases spatial resolution in HDX MS of small proteins (<15 kDa) may be enhanced up to a single residue level by analyzing deuterium content of a set of overlapping proteolytic fragments.17However, single-residue resolution has never been demonstrated in HDX MS studies of proteins falling out of the mass range routinely accessible by NMR, although overlapping peptic fragments frequently provide moderate improvement of spatial resolution.

In addition to limited spatial resolution, the “classic” HDX MS scheme frequently suffers from incomplete sequence coverage, especially when applied to larger and extensively glycosylated proteins. Proteins with multiple disulfide bonds constitute another class of targets for which adequate sequence coverage is difficult to achieve, although certain changes in experimental protocol can alleviate this problem, at least for smaller proteins.18 Typically, an 80% level of sequence coverage is considered good, although significantly lower levels may also be adequate, depending on the context of the study.

Protein processing in HDX MS experiments is carried out under the conditions that minimize the exchange rates for backbone amides. Since these slow exchange conditions are highly denaturing for most proteins, both intact protein and its proteolytic fragments lack any protection and inevitably begin to lose their labile isotopic labels, despite low (but finite) intrinsic exchange rates.19 This phenomenon, known as “back-exchange,” may be accelerated during various stages of protein processing, e.g. during the chromatographic step.20 Although back-exchange was frequently evaluated in early HDX MS studies using unstructured model peptides, the utility of this procedure is questionable, since the intrinsic exchange rates are highly sequence-dependent. In many instances, back-exchange may be estimated using algorithms based on context-specific kinetics data (e.g., http://hx2.med.upenn.edu/download.html); it may also be determined experimentally for each proteolytic fragment by processing a fully labeled protein using a series of steps that precisely reproduce those used in HDX MS measurements.9 Typical back-exchange levels reported in recent literature range from 10% to 50%, although significantly higher numbers have also been reported. Even if back-exchange can be accounted for, it nonetheless has very detrimental influence on the quality of HDX MS measurements by reducing the available dynamic range.

Finally, the classic HDX MS scheme is poorly suited for measurements that are carried out under conditions favoring correlated exchange, when HDX kinetics follows the so-called EX1 regime, leading to appearance of bimodal and convoluted multi-modal isotopic distributions of protein ions.21 Carrying out HDX MS measurements under these conditions provides a unique opportunity to visualize and characterize distinct conformational states, which can be populated either transiently10 or at equilibrium.22 The distinction among such states can be made based on the differences in their deuterium contents. However, proteolysis in solution almost always leads to a loss of correlation between the deuterium content of fragment peptides and specific conformers with distinct levels of backbone protection. Therefore, the classic HDX MS scheme does not allow protein higher order structure and dynamics to be characterized in a conformer-specific fashion.

“Top-down” HDX MS: tandem MS allows protein structure to be probed in the conformer-specific fashion but raises the specter of hydrogen scrambling

The problem of characterizing protein conformation and dynamics in a conformer-specific fashion can be addressed using methods of tandem mass spectrometry (the so-called “top-down” HDX MS). Indeed, replacement of proteolysis in solution with protein ion fragmentation in the gas phase following mass selection of precursor ions provides a means to obtain fragment ions originating from a particular conformer with a specific level of deuterium incorporation. Deuterium content of fragment ions would then provide a measure of local protection patterns, assuming there is no internal re-arrangement of labile hydrogen and deuterium atoms during ion activation (vide infra). Although the idea to use polypeptide ion dissociation in the gas phase as an alternative to proteolysis was originally proposed in early 1990s,23 its implementation for proteins only became possible24 following dramatic improvements in FTMS and hybrid TOF analyzers in the late 1990s.

An example of conformer-specific characterization of protein higher order structure using a top-down HDX MS approach is illustrated in Figure 4. The isotopic profile of a fully deuterated 18 kDa protein wt*-CRABPI is recorded following its brief exposure to the 1H-based exchange buffer. The bimodal appearance of the isotopic distribution of the molecular ion (top trace in Figure 4A) clearly indicates the presence of at least two conformers with different levels of backbone protection. Collisional activation of the entire protein ion population generates a set of fragment ions with convoluted isotopic distributions (top trace in Figure 4B). However, mass selection of precursor ions with a specific level of deuterium content allows the top-down HDX MS measurements to be carried out in a conformation-specific fashion, taking full advantage of the HDX MS ability to detect distinct conformers. For example, selective fragmentation of protein ions representing a highly protected conformation is achieved by mass-selecting a narrow population of intact protein ions with high level of retained deuterium (the blue trace in Figure 4A). Mass-selection and subsequent fragmentation of a narrow population of protein ions with significantly lower deuterium content (the red trace in Figure 4A) generates a set of fragment ions whose isotopic distributions provide information on backbone protection within non-native protein states. For example, the data presented in Figure 4 clearly indicate that the C-terminal segment of the protein represented by the y172+ ions retains significant structure even within the partially unfolded conformers: the amount of retained deuterium atoms reduces by only 30% as a result of switching from the precursor ion from highly protected (blue) to less protected (red). At the same time, selection of the precursor ion has a much more dramatic effect on the protection levels exhibited by the N-terminal segment (represented by the b425+ ion), where more than a two-fold decrease in the amount of retained deuterium atoms is observed. Extending this analysis to other protein fragments may allow detailed backbone protection maps to be created for each protein conformer, provided there is no hydrogen scrambling prior to protein ion fragmentation (vide infra).

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Characterization of local dynamics in wt*-CRABP I in a conformer-specific fashion using top-down HDX MS (fully deuterated protein was exposed to 1H2O/CH3CO2N1H4 at pH 3.1 for 10 min; the gray trace at the bottom corresponds to HDX end-point). A: mass selection of precursor ions for subsequent CAD (from top to bottom): broad-band selection of the entire ionic population (not conformer-specific); highly protected conformers; narrow population of less protected conformers; HDX end-point. B: isotopic distributions of two representative fragment ions generated by CAD of precursor ions shown in panel A. Selection of different ion populations as precursor ions for subsequent fragmentation was achieved by varying the width of a mass selection window of a quadrupole filter (Q) in a hybrid quadrupole/time-of-flight mass spectrometer (Qq-TOF MS).

The example shown above illustrates a great promise of top-down HDX MS as a technique uniquely capable of probing structure and dynamics of populations of protein conformers coexisting in solution with high selectivity. Furthermore, this approach often allows one to avoid protein handling under the slow exchange conditions prior to MS analysis, thereby eliminating back-exchange as a factor adversely influencing the quality of measurements. Nonetheless, applications of top-down HDX MS have been limited due to concerns over the possibility of hydrogen scrambling accompanying collision-activated dissociation (CAD) of protein ions. Indeed, several reports pointed out that proton mobility in the gas phase may under certain conditions influence the outcome of top-down HDX MS measurements when CAD is employed to fragment protein ions.25, 26

The occurrence (or the absence) of hydrogen scrambling in the gas phase can be reliably detected by using built-in scrambling indicators. One particularly convenient indicator is a Histag, a 6-30 residues long, histidine-rich segment appended to wild-type sequences to facilitate protein purification on metal affinity columns. Such segments are fully unstructured in solution and, therefore, should lack any backbone protection.27 Alternatively, intrinsic scrambling indicators (e.g., internal flexible loops26), as well as other approaches25 can be used to detect occurrence of scrambling. The available experimental evidence suggests that slow protein ion activation (e.g., SORI CAD) always leads to hydrogen scrambling, while fast activation allows it to be minimized or eliminated in top-down HDX MS experiments.26

Another shortcoming of top-down HDX MS schemes utilizing CAD is the limited extent of protein ion fragmentation, which may lead to sizeable gaps in sequence coverage, particularly for larger proteins,28 and insufficient level of spatial resolution (even for smaller proteins29). Our earlier attempts to solve this problem by employing multi-stage CAD (MSn) were unsuccessful due to massive hydrogen scrambling exhibited by the second generation of fragments.

Electron-induced ion fragmentation in top-down schemes: keeping hydrogen scrambling at bay while enhancing sequence coverage and spatial resolution

Some time ago we suggested that the specter of hydrogen scrambling in top-down HDX MS measurements may be alleviated by using non-ergodic fragmentation processes, where dissociation is induced by ion-electron interaction, rather than collisional activation.30 Indeed, the results of earlier work combining hydrogen exchange of polypeptide ions in the gas phase and electron capture dissociation (ECD) were consistent with the notion of intramolecular rearrangement of hydrogen atoms occurring on a slower time scale compared to ion dissociation.31 A recent study demonstrated that the extent of scrambling was indeed negligible when ECD was used as a means to obtain fragment ions in top-down HDX MS characterization of a small protein ubiquitin.32

Our own recent work suggests that hydrogen scrambling can be avoided when top-down HDX MS employs ECD in characterizing higher order structure of larger proteins (approaching 20 kDa), although experimental conditions must be carefully controlled to minimize proton mobility induced by ion-molecule collisions in the ESI interface. The point in question is illustrated in Figure 5, which shows the results of top-down HDX MS analysis of higher order structure of wt*-CRABP I. The protein retains a significant proportion of labile deuterium label following its complete deuteration and then brief exposure to the 1H-based exchange buffer, as indicated by the isotopic distribution of the surviving molecular ions (red and blue traces in Figure 5A). However, the deuterium content of fragment ions derived from the 21-residue long His-tag region of the protein (e.g., c22 in Figure 5B) is indistinguishable from that of the exchange reaction endpoint, as long as moderate ion desolvation conditions are kept in the ESI interface. This clearly signals that hydrogen scrambling does not affect the outcome of local HDX MS measurements. However, once collision-assisted desolvation of protein ions is attempted in the ESI interface, the appearance of isotopic distributions of larger fragment ions derived from the His-tag region (e.g., c22, red trace in Figure 5B) shifts, indicating apparent deuterium retention and signaling the occurrence of limited hydrogen scrambling. We also demonstrated that deuterium distribution across the protein backbone is preserved when another recently introduced fragmentation technique based on cation-electron interactions, electron transfer dissociation (ETD), is used in top-down HDX MS schemes.33

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Top-down HDX MS of wt*-CRABP I using ECD of the entire protein ion population (fully deuterated protein was exposed to1H2O/CH3CO2N1H4 at pH 3.5 for varying time periods); the black trace at the bottom of corresponds to HDX end-point). A: isotopic distributions of surviving intact protein ions. B: two representative c-ions. Minimal collision-and temperature-induced desolvation was used for acquisition of all mass spectra, except the one top (red trace).

In addition to allowing scrambling to be easily eliminated in top-down HDX MS experiments, both ECD and ETD appear to be superior to CAD in terms of sequence coverage, at least for the proteins in the 20 kDa range. Unlike CAD, protein backbone cleavage in ECD and ETD is less specific,34 leading to a higher number of fragment ions. This translates not only to improved sequence coverage, but also enhanced spatial resolution. Indeed, in some cases it becomes possible to generate patterns of deuterium distribution across the protein backbone down to the single residue level.

One example of such work is shown in Figure 6, where ETD was used as a protein ion fragmentation tool in top-down HDX MS characterization of a 16 kDa variant of CRABP I. The bar graph shows the levels of deuterium retention in a series of c-ions derived from the N-terminal segment of the protein. The bar height at position n in this diagram shows mass difference between two cn-1 fragments, one derived from the fully deuterated protein that was exposed to the protiated exchange buffer at pH 7 for 5 min and then placed under the slow exchange conditions for the duration of the data acquisition cycle, and another one representing the HDX endpoint (raw data for bars at n=14 and 35 are shown in Figure 7). Unchanged height between two adjacent bars at residues n and n+1 indicates no difference in deuterium content of cn-1 and cn fragments, signaling no backbone amide deuterium retention at residue n+1, while bar height increase by one unit indicates complete retention of deuterium at the nth amide.

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Backbone protection pattern of CRABPI mutant (without N-terminal His-tag) obtained from top-down HDX MS measurements using ETD of the entire protein ion population. HDX was initiated by exposing the fully deuterated protein to 1H2O/CH3CO2N1H4 at pH 3.5 for 5 min followed by rapid quenching.

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An example of raw HDX MS data used to generate the protection plot shown in Figure 6. Isotopic distributions of c13 and c34 fragments derived from protein subjected to 5 min HDX exchange in solution (red trace) and protein at the HDX end-point (blue trace) were used to calculate the bar heights at n=12 and 35.

The resulting backbone protection pattern in Figure 6 shows clear correlation with the known higher order structure of the protein (the amino acid sequence and the secondary structure assignment are shown at the top of the graph). Furthermore, the diagram clearly shows uneven distribution of backbone protection even within single structural elements (e.g., lower protection at the fringes vs. the middle of helix α1), as well as unequal protection of similar structural elements participating in the same structural motif (e.g., lower protection of helix α2 vs. helix α1, consistent with the available NMR data). A comparable level of spatial resolution can be achieved with ECD, as shown recently in top-down HDX MS analysis of higher order structure of myoglobin.35

The ability to characterize protein conformation and dynamics at the single residue level is certainly very exciting; however, it comes at a price. Since the protein fragmentation is carried out entirely in the gas phase, no fragment separation can be done prior to mass analysis. A large number of fragment ions with different masses and charges are usually confined to a relatively narrow m/z region, leading to inevitable overlaps of fragment ion isotopic distributions (Figure 7). This places rather stringent requirements on the resolving power of the mass analyzer, effectively narrowing the selection of mass spectrometers suitable for this work to FTMS.

Meeting in the middle: integration of top-down strategies into bottom-up HDX MS schemes

The top-down approach to HDX MS measurements clearly shows a promise to solve many problems that mar the commonly employed bottom-up methodology. The fragmentation efficiency afforded by ECD and ETD provides better spatial resolution, at least for proteins in the 20 kDa range, and this number is likely to grow as there are numerous examples of successful use of these fragmentation techniques to obtain sequence information on significantly larger proteins.36 Unlike the classic bottom-up approach, top-down HDX MS provides an elegant solution to the problem of characterizing higher order structure and dynamics in a conformer-specific fashion (see Figure 4 and discussion in the text). Finally, back-exchange can be eliminated, as outsourcing protein fragmentation to the gas phase often eliminates the need to manipulate the protein in solution under the slow exchange conditions prior to MS analysis.

The top-down/bottom-up dichotomy in HDX MS should not be viewed through the “eitheror” prism. In fact, gas phase fragmentation can enhance the quality of HDX MS data derived from experiments that are built around the bottom-up approach. The suggestion to supplement proteolysis in solution with peptide ion fragmentation in the gas phase to achieve better spatial resolution was made over 10 years ago.37 However, earlier attempts to implement this idea using CAD on a variety of platforms yielded mixed results due to apparent scrambling in some (but not all) fragment ions.37, 38 Later reports showed even more extensive scrambling in small peptide ions subjected to collisional activation,39 an obvious anathema to the proposed marriage of CAD and bottom-up HDX MS. Nonetheless, continued search for a scrambling-free solution to this problem has yielded very encouraging results, with both ECD and ETD showing minimal scrambling when applied to short peptides under carefully controlled conditions40, 41 and feasibility of supplementing proteolytic fragmentation in solution with ETD in the gas phase was recently demonstrated using a small model protein.42 Although these initial steps are relatively modest, they certainly warrant further work in this field.

The two complementary approaches to HDX MS measurements share a set of common challenges that inevitably arise as these techniques gain popularity and the scope of their applications expands. One such challenge is presented by membrane proteins, a notoriously difficult class of biological objects. HDX MS has been shown to have a great potential in this field.43 Interestingly, some initial work in this field was done nearly ten years ago using then-infant top-down HDX MS technique,44 while more recent work in this field utilizes both bottomup18 and top-down45 approaches. Another challenge faced by HDX MS is presented by highly heterogeneous proteins, such as proteins conjugated to other biopolymers and/or synthetic polymers, which constitute a significant fraction of the next generation of biopharmaceuticals. Presently, there are no biophysical techniques capable of characterizing conformation and dynamics of these systems, and there is an urgent need to fill this gap. Finally, nearly all HDX MS work reported to date was carried out in vitro under conditions that some regard as “reductionist.” Although initial HDX work with living objects was carried out over 75 years ago,46 as the years passed only one report on in vivo HDX MS studies was published.47 As mass spectrometry at large is being increasingly used in both in vivo and ex vivo studies, there is a growing pressure on HDX MS to follow the trend, although it remains to be seen how this will be done.

It probably is not an exaggeration to say that we are witnessing a renaissance of HDX MS, with the emergence of the top-down approach not only expanding our experimental arsenal by offering new capabilities, but also serving as a catalyst in enhancing the classic bottom-up methodology. The two techniques are highly complementary, and their synergism will certainly bring about new exciting discoveries and accelerate our progress in solving a variety of problems ranging from very fundamental questions in biophysics to applied problems in drug design.

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WATCH OUT FOR DISULFIDES: If you’re going to try bottom-up HDX experiments, be careful of disulfide bonds, Kaltashov says. Pepsin is one of the very few proteinases that can efficiently digest a protein into its composite peptides under HDX experimental conditions, but it struggles when multiple disulfide bonds are present. In 2014, Kaltashov’s lab published two solutions to that problem. The first employs a fragmentation technique called electron capture dissociation (ECD) to break the disulfide linkage in the mass spec (Anal Chem, 86:5225-31, 2014); the second skips the pepsin digestion altogether—a strategy called top-down analysis (Anal Chem, 86:7293-98, 2014).

Enhancing the Quality of H/D Exchange Measurements with Mass Spectrometry Detection in Disulfide-Rich Proteins Using Electron Capture Dissociation

Anal Chem. 2014 Jun 3; 86(11): 5225–5231.   Published online 2014 May 12. doi:  10.1021/ac500904p
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Hydrogen/deuterium exchange (HDX) mass spectrometry (MS) has become a potent technique to probe higher-order structures, dynamics, and interactions of proteins. While the range of proteins amenable to interrogation by HDX MS continues to expand at an accelerating pace, there are still a few classes of proteins whose analysis with this technique remains challenging. Disulfide-rich proteins constitute one of such groups: since the reduction of thiol–thiol bonds must be carried out under suboptimal conditions (to minimize the back-exchange), it frequently results in incomplete dissociation of disulfide bridges prior to MS analysis, leading to a loss of signal, inadequate sequence coverage, and a dramatic increase in the difficulty of data analysis. In this work, the dissociation of disulfide-linked peptide dimers produced by peptic digestion of the 80 kDa glycoprotein transferrin in the course of HDX MS experiments is carried out using electron capture dissociation (ECD). ECD results in efficient cleavage of the thiol–thiol bonds in the gas phase on the fast LC time scale and allows the deuterium content of the monomeric constituents of the peptide dimers to be measured individually. The measurements appear to be unaffected by hydrogen scrambling, even when high collisional energies are utilized. This technique will benefit HDX MS measurements for any protein that contains one or more disulfides and the potential gain in sequence coverage and spatial resolution would increase with disulfide bond number.
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Hydrogen/deuterium exchange (HDX) with mass spectrometry (MS) detection has evolved in the past two decades into a powerful tool that is now used to decipher intimate details of processes as diverse as protein folding, recognition and binding, and enzyme catalysis.1,2 While initially being a tool that was used exclusively in fundamental studies, HDX MS is now becoming an indispensable part of the analytical arsenal in the biopharmaceutical sector, where it is utilized increasingly in all stages of protein drug development from discovery to quality control.35 Despite this progress, several areas remain where the application of HDX MS has met with only limited success. Disulfide-rich proteins constitute one such group, where characterization of higher-order structure and dynamics is particularly difficult, because of the suboptimal conditions used for reduction of thiol–thiol bonds following a quench of the exchange reactions. Proteins containing disulfide bonds are encountered very rarely in the protein folding studies where the most popular targets are small proteins lacking cysteine residues (with a notable exception of the oxidative folding studies), as well as in many other fundamental studies focusing on proteins of prokaryotic origin. However, disulfide-rich proteins are encountered very frequently in eukaryotic proteomes6 and constitute a large segment of the biopharmaceutical products,7 where the thiol–thiol bonds are critical elements defining conformation of protein drugs, and also play an important role in stabilizing proteins by endowing them with protease resistance.

While disulfide bond reduction is a relatively trivial task that can be readily accomplished at neutral pH using a variety of reagents, the acidic, low-temperature environment where proteins are placed to quench HDX narrows down the choice to a single reducing agent, TCEP.8 However, the alkaline pH for optimal disulfide reduction by TCEP is substantially higher, compared to the acidic environment of typical “slow exchange conditions” commonly employed to minimize back exchange within proteins and their peptic fragments prior to MS analysis.9 Furthermore, disulfide reduction in HDX MS measurements is usually carried out within a relatively short period of time (a few minutes) and at low temperature (0–4 °C) to limit the extent of the back-exchange, which in many situations does not allow the complete dissociation of thiol–thiol linkages of individual peptic fragments to be achieved in solution prior to LC separation and MS analysis of their deuterium content. Incomplete reduction of disulfide bonds dramatically increases the pool of candidate peptides that should be considered when analyzing proteolytic fragments in HDX MS measurements and frequently reduces sequence coverage and/or spatial resolution. While the former problem can be solved by employing more powerful and robust search engines for peptide identification, the latter one is more difficult to circumvent and can be very detrimental for the quality of HDX MS data and may require significant changes in experimental protocols. Indeed, a complete failure to reduce a certain disulfide bond in a protein will give rise to a thiol–thiol linked peptide dimer, whose constituent monomers do not necessarily represent a contiguous segment of the protein and may have vastly different conformational and dynamic properties. The total deuterium content of the entire dimer (measured by HDX MS) would not provide any meaningful information under these conditions, thereby effectively reducing the sequence coverage in the corresponding segments of the protein.
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Disulfide-rich proteins have traditionally been challenging targets for HDX MS studies, because of incomplete reduction of thiol–thiol linkages, which is a consequence of the quench conditions used to minimize amide back-exchange in peptides prior to MS analysis of their deuterium content: limited time, low temperature, and low pH. Traditionally, the principal strategy to address difficult-to-reduce or high-density disulfides in the HDX MS workflow is a brute force approach utilizing high concentrations of reductant and denaturant prior to (or even in combination with) digestion. The effectiveness of this approach is protein-dependent and extended incubation times frequently employed to enhance exposure to reductant invariably result in an undesirable increase in H/D back exchange. More recently, a novel electrochemical approach to reduce disulfides in solution under quench conditions prior to LC-MS has been reported for insulin.32 While electrochemical reduction shows promise, several limitations were identified, an apparent requirement for low-salt conditions, a higher-than-optimal temperature (10 °C), and a current cell pressure limit of 50 bar. In this work, electron capture dissociation (ECD) was used to circumvent the disulfide problem, since it effectively cleaves external disulfide bonds. Dissociation of the disulfide-linked peptide dimers can be accomplished on the fast LC time scale and produces abundant signals for monomeric subunits without interchain hydrogen scrambling, even when collisional activation of ions is applied prior to ion selection and ECD fragmentation. Inclusion of ECD in the HDX MS workflow results in increased sequence coverage and spatial resolution and provides an attractive alternative to extensive chemical reduction of disulfide-rich proteins.

see more at   http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4051250/

Approach to Characterization of the Higher Order Structure of Disulfide-Containing Proteins Using Hydrogen/Deuterium Exchange and Top-Down Mass Spectrometry

Guanbo Wang† and Igor A. Kaltashov*
http://www.chem.umass.edu/people/kaltashovlab/papers/Approach.pdf

Top-down hydrogen/deuterium exchange (HDX) with mass spectrometric (MS) detection has recently matured to become a potent biophysical tool capable of providing valuable information on higher order structure and conformational dynamics of proteins at an unprecedented level of structural detail. However, the scope of the proteins amenable to the analysis by top-down HDX MS still remains limited, with the protein size and the presence of disulfide bonds being the two most important limiting factors. While the limitations imposed by the physical size of the proteins gradually become more relaxed as the sensitivity, resolution and dynamic range of modern MS instrumentation continue to improve at an ever accelerating pace, the presence of the disulfide linkages remains a much less forgiving limitation even for the proteins of relatively modest size. To circumvent this problem, we introduce an online chemical reduction step following completion and quenching of the HDX reactions and prior to the top-down MS measurements of deuterium occupancy of individual backbone amides. Application of the new methodology to the top-down HDX MS characterization of a small (99 residue long) disulfide-containing protein β2- microglobulin allowed the backbone amide protection to be probed with nearly a single-residue resolution across the entire sequence. The high-resolution backbone protection pattern deduced from the top-down HDX MS measurements carried out under native conditions is in excellent agreement with the crystal structure of the protein and high-resolution NMR data, suggesting that introduction of the chemical reduction step to the top-down routine does not trigger hydrogen scrambling either during the electrospray ionization process or in the gas phase prior to the protein ion dissociation.

Since its initial introduction in the late 1990s,1−3 top-down hydrogen/deuterium exchange (HDX) with mass spectrometric (MS) detection evolved to become a potent biophysical tool capable of providing valuable information on higher order structure and conformational dynamics of proteins at an unprecedented level of structural detail. Among the many advantages offered by top-down HDX MS compared to conventional (bottom-up) measurements are significant reduction or indeed complete elimination of the back exchange,4 high spatial resolution,5,6 and the ability to study conformational dynamics in the conformer-specific fashion.7,8 However, despite the spectacular recent advances and the broader acceptance of this technique, the scope of the proteins amenable to the analysis by top-down HDX MS remains limited, with the protein size and the presence of disulfide bonds being the two most important limiting factors. The limitations imposed by the physical size of the proteins gradually become more relaxed as the sensitivity, resolution, and dynamic range of modern MS instrumentation continue to improve at an ever accelerating pace. However, the presence of disulfides remains a much less forgiving limitation even for the proteins of relatively modest size.

In this work we demonstrated feasibility of applying top-down HDX MS measurements to characterize higher order structure and conformational dynamics of disulfide-containing proteins, which have been out of the reach of this technique so far. Use of a moderate amount of a reducing agent TCEP is compatible with the ESI process, while allowing a fraction of the protein molecules to be reduced in solution thereby enabling nearcomplete sequence coverage at high resolution. The agreement between the top-down HDX MS and NMR data sets demonstrate that the new experimental approach is capable of capturing the dynamic picture of protein conformation at high spatial resolution without compromising the quality of the data by triggering hydrogen scrambling in the gas phase. Despite its modest size, β2m is known to be able to populate a non-native state,35 which might be a key player in a variety of processes, including amyloidosis. However, the structure of this non-native state of β2m remains elusive since this conformer exists in dynamic equilibrium with the native state of the protein.36,37 Recently we demonstrated that top-down HDX MS provides an elegant way to selectively probe structure of protein states coexisting in solution at equilibrium;8 however, β2m remained out of reach of this technique until recently due to the presence of a disulfide bond. The ability to expand the scope of top-down HDX MS to disulfide-containing proteins opens up a host of exciting possibilities to explore the structure of β2m, interferon, lysozyme, and a variety of other disulfidecontaining proteins in a conformer-specific fashion, where physiologically important non-native states may play important roles in processes as diverse as folding, recognition, signaling, and amyloidosis. ■ ASSOCIATED CONTENT *S Supporting Information Representative examples of isotopic distributions of fragment ions that have (Supplementary Figure 1) and have not (Supplementary Figure 2) been used to calculate the deuterium occupancy at individual backbone amides of β2m in top-down HDX MS measurements. This material is available free of charge via the Internet at http://pubs.acs.org.

Determining surface topology of protein complexes

http://www.the-scientist.com/November2015/MS-surface-topology.jpg

SUSSING OUT THE SURFACE: Protein topology can be probed by firing low-energy electrons (white circles) at intact protein complexes within a high-resolution mass spectrometer. That reaction, called electron capture dissociation, causes the protein complex to fracture on its surface, revealing the exposed amino acid residues.     COURTESY OF PIRIYA WONGKONGKATHEP AND HUILIN LI, UCLA

RESEARCHER: Joseph Loo, Professor of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles)

PROJECT: Studying protein-ligand and protein-protein interactions

SOLUTION: Loo is less interested in complex identification than in how the protein subunits assemble. Specifically, he wants to know which amino acid residues lie on the complex’s surface and which are buried inside or interacting with ligands.

It’s a question of structural biology, he explains: “How is this thing folded in a way that these residues are on the outside?”

To work that out, Loo combines high-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR) with electron-capture dissociation (ECD), a mass spec fragmentation method in which an ion in the mass spectrometer interacts with free electrons, causing the protein to fracture along its peptide backbone. By measuring the mass of those fragments with high precision, researchers can determine the protein’s amino acid sequence.

In Loo’s case, though, that fragmentation is not uniform along the length of the protein. Proteins usually are denatured for mass spectrometry analysis, but the protein complexes in his studies are intact—a process called native mass spectrometry. Fragmentation thus occurs preferentially on the surface of the complex, like the cracks in the shell of a hard-boiled egg. “You get limited sequence information, but that sequence information comes from regions that are specific to its 3-D structure,” he says (Anal Chem, 86:317-20, 2014).

Native Top-Down ESI-MS of 158 kDa Protein Complex by High Resolution Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) delivers high resolving power, mass measurement accuracy, and the capabilities for unambiguously sequencing by a top-down MS approach. Here, we report isotopic resolution of a 158 kDa protein complex – tetrameric aldolase with an average absolute deviation of 0.36 ppm and an average resolving power of ~520,000 at m/z 6033 for the 26+ charge state in magnitude mode. Phase correction further improves the resolving power and average absolute deviation by 1.3 fold. Furthermore, native top-down electron capture dissociation (ECD) enables the sequencing of 149 C-terminal amino acid (AA) residues out of 463 total AAs. Combining the data from top-down MS of native and denatured aldolase complexes, a total of 58% of the backbone cleavages efficiency is achieved. The observation of complementary product ion pairs confirms the correctness of the sequence and also the accuracy of the mass fitting of the isotopic distribution of the aldolase tetramer. Top-down MS of the native protein provides complementary sequence information to top-down ECD and CAD MS of the denatured protein. Moreover, native top-down ECD of aldolase tetramer reveals that ECD fragmentation is not limited only to the flexible regions of protein complexes and that regions located on the surface topology are prone to ECD cleavage.

“Native” mass spectrometry (MS) is an emerging technique that has been successfully used to characterize intact, noncovalently-bound protein complexes, providing stoichiometry and structural information that is complementary to data supplied by conventional structural biology techniques.13 To confidently characterize protein complexes, electrospray ionization (ESI)-MS measurements acquired with isotopic resolving power (RP) and high mass accuracy and capabilities for deriving primary structure, i.e., sequence, information would be ideal. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) is prominent for its superior resolving power and mass accuracy and its utility for tandem MS (MS/MS) with a variety of fragmentation techniques; FT-ICR MS is noted for characterizating posttranslational modifications (PTMs) and protein-ligand and protein-protein interactions.49 However, it remains challenging to isotopically resolving large biomolecules over 100 kDa due to sample heterogeneity, cation/solvent/buffer addition, space charge effects, and electric and magnetic field inhomogeneity (for FT-ICR).1013 Unit mass resolution has been achieved for a few denatured proteins, including a 112 kDa protein with 3 Da mass error using a 9.4 T FT-ICR MS,14 a 115 kDa protein by a 7 T instrument with a mass error of 5 ppm,4 and a 148 kDa protein with a mass error of 1 Da by a 9.4 T FTMS.10

Compared to denatured proteins, it is more difficult to achieve isotopic resolution for inherently lower charged (and thus, higher m/z) native protein complexes because (1) the peak height is proportional to its charge state, (2) the resolving power is inversely proportional to mass-to-charge ratio for FT-ICR MS, and (3) the broader isotope distribution of large biomolecules reduces overall signal-to-noise ratio.15 However, the introduction of a new FT-ICR analyzer cell – the ParaCell, by Nikolaev and coworkers has significantly increased the resolving power of FT-ICR MS.16, 17 By dynamically harmonizing the electric field potential at any radius of cyclotron motion in the entire cell volume, a resolving power of 39 M has been achieved for the alkaloid, resperine (m/z 609), using a 7 T system.18 In addition, a few native protein complexes, including enolase dimer (93 kDa, RP ~ 800,000 at m/z 4250), alcohol dehydrogenase tetramer (147 kDa, RP ~ 500,000 at m/z 5465), and enolase tetramer (186 kDa), have been isotopically resolved with a 12 T FT-ICR system with the new ICR cell.18 Although Mitchell and Smith reported that cyclotron phase locking due to Coulombic interactions limits the highest mass that unit mass resolution can be achieved by FT-ICR MS (Mmax ≈ 1×104B, where B is magnetic field strength),19 the ParaCell has made it significantly easier and promising to measure high resolution mass spectra for large native protein complexes.

……

Native top-down CAD and ISD were performed for the aldolase tetramer; dissociation of the tetramer to yield monomer was observed in both approaches and no sequence information was obtained. The cleavage sites from ECD (colored in red) and CAD (colored in green) of the denatured aldolase monomer (26+) are overlaid with the native ECD results for aldolase tetramer (Figure 2B). As shown in Figure 2B, in contrast to the limited number of c-ion fragments observed in the ECD of aldolase tetramer, ECD of denatured aldolase monomer induces extensive c-ion fragments in the N-terminal region and enables the assignment of first 156 N-terminal AA residues. Surprisingly, the number of z-ions observed from ECD of the denatured aldolase monomer is much less compared to the ECD of the native aldolase tetramer. Although it may be possible that the z-ions may undergo secondary fragmentation due to excess available energy, electrons, or long ion-electron reaction times during the ECD experiment, ECD experiments with reduced reaction time and bias voltages were performed and the results argue against this assumption. Overall, 58% of the total number of backbone bonds are cleaved from combining top-down MS of native aldolase complex and denatured aldolase monomer (20% for native ECD of aldolase tetramer, 37% for ECD of denatured aldolase, and 5% for CAD of denatured aldolase).

The three dimensional structure of the aldolase tetramer is shown in Figure 3. To compare the flexibility of the structure to the data from ECD of the aldolase tetramer, one of the subunits (B-chain) is presented as B-factor putty and the D-chain is shown with its native ECD backbone cleavage regions colored in red. The remaining A- and C-chains are shown in grey. Although the C-terminal region (AA 340–363) of each subunit is highly flexible based on the crystallography B-factor (see B-chain in Figure 3A), only 4 out of 75 backbone cleavage sites are from the AA 340–363 region. Instead, the native ECD fragments largely originate from surface regions of the protein structure (see D-chain in Figure 3A). The N-terminal regions are not directly involved in the interfaces between subunits, but they are located in regions that are partially buried, which is consistent with the limited c-ions observed. To better show the native ECD backbone cleavage regions, the D-chain is rotated 90 degrees clockwise (Figure 3B). It is clear that, although protein structure flexibility might play a role in the native top-down ECD fragmentation pattern, for aldolase the ECD cleavage sites are not limited to the flexible region. In addition, backbone cleavage regions from CAD (yellow) and ECD (cyan) of denatured aldolase are complementary with the native ECD results.

An external file that holds a picture, illustration, etc. Object name is nihms548404f3.jpg

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3908771/bin/nihms548404f3.jpg

A) Structure of tetrameric aldolase (1ZAH)29. A- and C-chains are shown as grey ribbons, the B-chain is shown in B-factor putty, and the D-chain is in cartoon with native ECD cleavage sites colored in red, CAD cleavage sites of denatured aldolase in yellow, and ECD cleavage sites of the N-terminal region from ECD of denatured aldolase in cyan. B) The D-chain is rotated 90 degrees clockwise to show the outer surface region of the subunit structure.

Also evident in such data sets are protein–small molecule interactions. As the proteins break apart, Loo explains, ligands often remain attached to the polypeptide shards that are produced. In one recent publication, for instance, his team mapped zinc binding sites in eukaryotic alcohol dehydrogenase, a 147-kDa tetrameric complex (J Am Soc Mass Spectrom, 25:2060-8, 2014).

Revealing Ligand Binding Sites and Quantifying Subunit Variants of Non-Covalent Protein Complexes in a Single Native Top-Down FTICR MS Experiment

“Native” mass spectrometry (MS) has been proven increasingly useful for structural biology studies of macromolecular assemblies. Using horse liver alcohol dehydrogenase (hADH) and yeast alcohol dehydrogenase (yADH) as examples, we demonstrate that rich information can be obtained in a single native top-down MS experiment using Fourier transform ion cyclotron mass spectrometry (FTICR MS). Beyond measuring the molecular weights of the protein complexes, isotopic mass resolution was achieved for yeast ADH tetramer (147 kDa) with an average resolving power of 412,700 at m/z 5466 in absorption mode and the mass reflects that each subunit binds to two zinc atoms. The N-terminal 89 amino acid residues were sequenced in a top-down electron capture dissociation (ECD) experiment, along with the identifications of the zinc binding site at Cys46 and a point mutation (V58T). With the combination of various activation/dissociation techniques, including ECD, in-source dissociation (ISD), collisionally activated dissociation (CAD), and infrared multiphoton dissociation (IRMPD), 40% of the yADH sequence was derived directly from the native tetramer complex. For hADH, native top-down ECD-MS shows that both E and S subunits are present in the hADH sample, with a relative ratio of 4:1. Native top-down ISD MS hADH dimer shows that each subunit (E and S chain) binds not only to two zinc atoms, but also the NAD+/NADH ligand, with a higher NAD+/NADH binding preference for the S chain relative to the E chain. In total, 32% sequence coverage was achieved for both E and S chains.

Studying how proteins interact with one another and assemble on a structural basis is key to understanding biological processes and their function. As a complementary technique to conventional technologies used in structural biology, such as nuclear magnetic resonance (NMR) spectroscopy, X-ray crystallography, and electron microscopy, “native” mass spectrometry (MS) has established its crucial role in the characterization of intact noncovalently-bound protein complexes, revealing the composition, stoichiometry, dynamics, stability, and also spatial information of subunit arrangements in protein assemblies [111]. To date, most native MS studies of protein complexes have been performed using quadrupole time-of-flight (Q-TOF) MS instruments with electrospray ionization (ESI). Because of the efficient transmission of high mass and highm/z ions using TOF analyzers, large proteins with molecular weights up to 18 MDa have been studied [12,13]. The coupling of ion mobility spectrometry (IMS) with mass spectrometry provides a new dimension to the analysis of biomolecules [14]. With IMS, ions are separated based on size and shape, and the IMS-derived collision cross-section information can be used to understand the topological properties of gas phase protein complexes. Surface induced dissociation (SID) has been recently added for the purposes of disassembling protein complexes into sub-complexes that appear to better reflect the structure of the solution phase complexes [1517]. The capability of Orbitrap MS has been extended significantly for the analysis of macromolecules, with greatly improved mass (and m/z) range and resolving power to measure the binding of ADP and ATP to the 800 kDa GroEL complex [18].

Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) is known for its superior resolving power and mass accuracy and its capabilities for tandem MS (MS/MS) with a variety of fragmentation techniques. Particularly, after the introduction of electron capture dissociation (ECD) [19], FTICR MS quickly established its utility for protein top-down protein sequencing, post-translational modification characterization, and protein gas phase studies [2034]. Polypeptide backbone bonds are cleaved by ECD, but non-covalent interactions are preserved, which therefore makes the native top-down MS study of the non-covalent interaction sites of protein-ligands complexes more feasible. Our group and others have successfully applied top-down ECD-MS to pinpoint the interaction sites of several protein-ligand system [3538], and this can be enhanced by “supercharging” [35]. An early attempt of applying ECD-MS to the study of large protein complexes was made by Heeren and Heck, but little topology and sequence information was derived [39]. However, the Gross group starting in 2010 made the first breakthrough for the study of large protein complexes using native top-down ECD with FTICR MS. Besides obtaining molecular weight, sequence, and metal-binding site information in a single MS experiment, they correlated the origins of ECD product ions to the flexible regions of proteins as determined by the “B-factor” from the X-ray crystal structures of protein complexes [40, 41]. Therefore, native top-down ECD has been proposed as a tool to probe the flexible regions of protein complexes. Our group recently also demonstrated the capability of obtaining sequence information and isotopic mass resolution of a noncovalently-bound protein complex of 158 kDa using native top-down FTICR MS, and most importantly, we found that the origin of ECD fragments is not limited only to the flexible region of the protein complex (e.g., tetrameric aldolase), but also largely from the surface of the complex [42].

The application of FTICR MS for native top-down interrogation of large non-covalent bound protein complexes is still in its infancy. Here, for the purpose of further exploring the capability of FTICR MS in the analysis of large protein complexes, various fragmentation techniques including in-source dissociation (ISD), collisionally activated dissociation (CAD), ECD, and infrared multiphoton dissociation (IRMPD) were applied in the native top-down MS studies of a 80 kDa dimeric protein complex and a 147 kDa tetrameric protein complex. The results demonstrate that with the superior resolving power, mass accuracy, and versatile fragmentation techniques of FTICR MS, rich information, including isotopic mass resolution, amino acid sequence, point mutations, metal/ligand binding sites, and identification and quantification of subunit variants can be accomplished in a single native top-down FTICR MS experiment.

see more at   http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4444062/

Still, Loo admits, the technique “is not really ready for prime time.” His team is collecting ECD data on a bank of proteins of known structure to ensure the data they collect really do reflect protein topology. In the meantime, they are working to extend the size of the complexes they can analyze. The technique’s current limit is 800 kDa.

GO NATIONAL: FTICR mass spectrometers offer top-of-the-line accuracy and resolution, with price tags to match. Few researchers have direct access to them, Loo says, but they can always try the national laboratories. Both the National High Magnetic Field Laboratory at Florida State University and the Environmental Molecular Sciences Laboratory at the Pacific Northwest National Laboratory have user facilities open to worthy projects.

Determining the architecture of protein complexes

RESEARCHER: Vicki Wysocki, Ohio Eminent Scholar and Professor of Chemistry and Biochemistry, Ohio State University

PROJECT: Instrumentation development for whole-complex analysis

SOLUTION: An analytical chemist by training, Wysocki focuses on instrumentation development for protein-complex analysis. Among the discoveries in her lab is a method called surface-induced dissociation (SID).

http://www.the-scientist.com/November2015/LT1_last.jpg

HIT THE WALL, JACK: When it comes to molecular collision in a mass spectrometer, size matters. Collide a complex with small gas molecules, and proteins in the complex will simply unravel (top). By smacking them into a “wall”—a process called surface-induced dissociation—the complex dissociates to reveal its underlying architecture.  COURTESY OF VICKI WYSOCKI

Like many other fragmentation approaches, SID works by forcing an ion in the mass spectrometer to collide with another object. Usually that object is a small gas molecule, with the energy of collision sufficient to crack the peptide backbone. But for large protein complexes, bigger is better, and the collision partner in SID is as big as it can get: the method slams protein ions of interest into a nonreactive surface inside the instrument—essentially, a wall—causing complexes to fracture into subcomplexes that reveal the assembly’s inner architecture.

Wysocki combined this approach with ion-mobility separation—a kind of gas-phase electrophoresis that resolves molecules by their size and shape—to dissect an enzyme involved in antibiotic production. The enzyme, they found, has two copies each of three subunits, alpha, beta, and gamma, arranged as a pair of triads sitting on top of one another, with the alpha and beta subunits of one triad linked more tightly to each other than either is to gamma (Anal Chem, 83:2862-65, 2011).

Such information can be valuable to protein engineers, Wysocki says, especially as this particular complex otherwise falls into a structural biology knowledge gap: “It doesn’t crystallize, and it’s too small for the cryoEM and a little bit large for NMR,” she says. “And so, mass spec turned out to be a great tool.”

Revealing the Quaternary Structure of a Heterogeneous Noncovalent Protein Complex through Surface-Induced Dissociation

Anne E. Blackwell, Eric D. Dodds,† Vahe Bandarian, and Vicki H. Wysocki*
https://research.cbc.osu.edu/wysocki.11/wp-content/uploads/2012/09/Blackwell-2011-Revealing-the-Quater.pdf

As scientists begin to appreciate the extent to which quaternary structure facilitates protein function, determination of the subunit arrangement within noncovalent protein complexes is increasingly important. While native mass spectrometry shows promise for the study of noncovalent complexes, few developments have been made toward the determination of subunit architecture, and no mass spectrometry activation method yields complete topology information. Here, we illustrate the surface-induced dissociation of a heterohexamer, toyocamycin nitrile hydratase, directly into its constituent trimers. We propose that the single-step nature of this activation in combination with high energy deposition allows for dissociation prior to significant unfolding or other large-scale rearrangement. This method can potentially allow for dissociation of a protein complex into subcomplexes, facilitating the mapping of subunit contacts and thus determination of quaternary structure of protein complexes.

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http://pubs.acs.org/appl/literatum/publisher/achs/journals/content/ancham/2011/ancham.2011.83.issue-8/ac200452b/production/pdfimages_v02/normal.img-000.jpg

The majority of proteins exist and perform their functions as multimers of varing stoichiometries and architecture.1 However, very few methods are available that can provide insights into subunit interactions. Native mass spectrometry (MS) is increasingly being used to study noncovalent protein complexes, as many structural features found in solution may be maintained in the gas phase.2,3 While subunit stoichiometries are readily obtainable by mass measurement alone, the determination of subunit arrangement within protein complexes remains a significant challenge. This is particularly true for heterogeneous complexes with multiple types of subunits. Considerable progress has been made using solution-phase disruption to divide the original protein complex into smaller subcomplexes, which may be readily measured by MS.4,5 The composition of the stable subcomplexes provides insight on the topology of the protein complex. However, MS activation methods used to date have fallen short of providing subunit topology. Here, we present the first evidence for subunit arrangement obtained directly from gas-phase experiments on a heterogeneous complex via surfaceinduced dissociation (SID). We have demonstrated previously the ability of SID to yield unique dissociation pathways for protein complexes, resulting in complementary information to collision-induced dissociation (CID).68 While the SID process is not yet well understood for macromolecules, there is a large body of work concerning SID of small molecules; influential factors such as collision energy, surface composition, and translational-to-vibrational energy conversion have been well-studied.911 The higher effective mass of a surface relative to that of neutral gas atoms used in CID (typically argon) results in significantly higher energy deposited through a single surface collision.9 As SID is a single-collision activation process, rather than activation via thousands of less energetic collisions as in CID, dissociation pathways other than those of the lowest energies become accessible

……

This is the only study to date demonstrating an ion activation method capable of yielding extensive dissociation, as well as the release of intact subcomplexes, thus providing relevant substructure information on a noncovalent, hetero-oligomeric protein complex. The capacity to produce intact, charge-symmetric subcomplexes suggests that dissociation occurs faster than subunit unfolding and that a significant degree of secondary and tertiary structure is maintained up to the point of dissociation and for some period of time afterward. Identification of trimeric substructure in TNH provides insight into a protein with little previous structural characterization and indicates a promising advancement of MS as a tool for structural biology.

Such information can be valuable to protein engineers, Wysocki says, especially as this particular complex otherwise falls into a structural biology knowledge gap: “It doesn’t crystallize, and it’s too small for the cryoEM and a little bit large for NMR,” she says. “And so, mass spec turned out to be a great tool.”

CHOOSE MASS: Mass spec may not be the only method for quickly working out protein structure, but it surely is the fastest, Wysocki says. She recalls one instance when a colleague sent over a complex that his group couldn’t crack. “In one afternoon, my student gave them a prediction of the structure: this one’s a heptamer, with a large subunit sitting atop a hexameric ring.” Even if the experiment doesn’t work, she adds, that fast turnaround time can be a boon, as collaborators can get rapid feedback for tweaking their experimental conditions. “Mass is a great thing.”

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Irreconciliable Dissonance in Physical Space and Cellular Metabolic Conception

Irreconciliable Dissonance in Physical Space and Cellular Metabolic Conception

Curator: Larry H. Bernstein, MD, FCAP

Pasteur Effect – Warburg Effect – What its history can teach us today. 

José Eduardo de Salles Roselino

The Warburg effect, in reality the “Pasteur-effect” was the first example of metabolic regulation described. A decrease in the carbon flux originated at the sugar molecule towards the end of the catabolic pathway, with ethanol and carbon dioxide observed when yeast cells were transferred from an anaerobic environmental condition to an aerobic one. In Pasteur´s studies, sugar metabolism was measured mainly by the decrease of sugar concentration in the yeast growth media observed after a measured period of time. The decrease of the sugar concentration in the media occurs at great speed in yeast grown in anaerobiosis (oxygen deficient) and its speed was greatly reduced by the transfer of the yeast culture to an aerobic condition. This finding was very important for the wine industry of France in Pasteur’s time, since most of the undesirable outcomes in the industrial use of yeast were perceived when yeasts cells took a very long time to create, a rather selective anaerobic condition. This selective culture media was characterized by the higher carbon dioxide levels produced by fast growing yeast cells and by a higher alcohol content in the yeast culture media.

However, in biochemical terms, this finding was required to understand Lavoisier’s results indicating that chemical and biological oxidation of sugars produced the same calorimetric (heat generation) results. This observation requires a control mechanism (metabolic regulation) to avoid burning living cells by fast heat released by the sugar biological oxidative processes (metabolism). In addition, Lavoisier´s results were the first indications that both processes happened inside similar thermodynamics limits. In much resumed form, these observations indicate the major reasons that led Warburg to test failure in control mechanisms in cancer cells in comparison with the ones observed in normal cells.

[It might be added that the availability of O2 and CO2 and climatic conditions over 750 million years that included volcanic activity, tectonic movements of the earth crust, and glaciation, and more recently the use of carbon fuels and the extensive deforestation of our land masses have had a large role in determining the biological speciation over time, in sea and on land. O2 is generated by plants utilizing energy from the sun and conversion of CO2. Remove the plants and we tip the balance. A large source of CO2 is from beneath the earth’s surface.]

Biology inside classical thermodynamics places some challenges to scientists. For instance, all classical thermodynamics must be measured in reversible thermodynamic conditions. In an isolated system, increase in P (pressure) leads to increase in V (volume), all this occurring in a condition in which infinitesimal changes in one affects in the same way the other, a continuum response. Not even a quantic amount of energy will stand beyond those parameters.

In a reversible system, a decrease in V, under same condition, will led to an increase in P. In biochemistry, reversible usually indicates a reaction that easily goes either from A to B or B to A. For instance, when it was required to search for an anti-ischemic effect of Chlorpromazine in an extra hepatic obstructed liver, it was necessary to use an adequate system of increased biliary system pressure in a reversible manner to exclude a direct effect of this drug over the biological system pressure inducer (bile secretion) in Braz. J. Med. Biol. Res 1989; 22: 889-893. Frequently, these details are jumped over by those who read biology in ATGC letters.

Very important observations can be made in this regard, when neutral mutations are taken into consideration since, after several mutations (not affecting previous activity and function), a last mutant may provide a new transcript RNA for a protein and elicit a new function. For an example, consider a Prion C from lamb getting similar to bovine Prion C while preserving  its normal role in the lamb when its ability to change Human Prion C is considered (Stanley Prusiner).

This observation is good enough, to confirm one of the most important contributions of Erwin Schrodinger in his What is Life:

“This little book arose from a course of public lectures, delivered by a theoretical physicist to an audience of about four hundred which did not substantially dwindle, though warned at the outset that the subject matter was a difficult one and that the lectures could not be termed popular, even though the physicist’s most dreaded weapon, mathematical deduction, would hardly be utilized. The reason for this was not that the subject was simple enough to be explained without mathematics, but rather that it was much too involved to be fully accessible to mathematics.”

After Hans Krebs, description of the cyclic nature of the citrate metabolism and after its followers described its requirement for aerobic catabolism two major lines of research started the search for the understanding of the mechanism of energy transfer that explains how ADP is converted into ATP. One followed the organic chemistry line of reasoning and therefore, searched for a mechanism that could explain how the breakdown of carbon-carbon link could have its energy transferred to ATP synthesis. One of the major leaders of this research line was Britton Chance. He took into account that relatively earlier in the series of Krebs cycle reactions, two carbon atoms of acetyl were released as carbon dioxide ( In fact, not the real acetyl carbons but those on the opposite side of citrate molecule). In stoichiometric terms, it was not important whether the released carbons were or were not exactly those originated from glucose carbons. His research aimed at to find out an intermediate proteinaceous intermediary that could act as an energy reservoir. The intermediary could store in a phosphorylated amino acid the energy of carbon-carbon bond breakdown. This activated amino acid could transfer its phosphate group to ADP producing ATP. A key intermediate involved in the transfer was identified by Kaplan and Lipmann at John Hopkins as acetyl coenzyme A, for which Fritz Lipmann received a Nobel Prize.

Alternatively, under possible influence of the excellent results of Hodgkin and Huxley a second line of research appears. The work of Hodgkin & Huxley indicated that the storage of electrical potential energy in transmembrane ionic asymmetries and presented the explanation for the change from resting to action potential in excitable cells. This second line of research, under the leadership of Peter Mitchell postulated a mechanism for the transfer of oxide/reductive power of organic molecules oxidation through electron transfer as the key for the energetic transfer mechanism required for ATP synthesis.
This diverted the attention from high energy (~P) phosphate bond to the transfer of electrons. During most of the time the harsh period of the two confronting points of view, Paul Boyer and followers attempted to act as a conciliatory third party, without getting good results, according to personal accounts (in L. A. or Latin America) heard from those few of our scientists who were able to follow the major scientific events held in USA, and who could present to us later. Paul  Boyer could present how the energy was transduced by a molecular machine that changes in conformation in a series of 3 steps while rotating in one direction in order to produce ATP and in opposite direction in order to produce ADP plus Pi from ATP (reversibility).

However, earlier, a victorious Peter Mitchell obtained the result in the conceptual dispute, over the Britton Chance point of view, after he used E. Coli mutants to show H+ gradients in the cell membrane and its use as energy source, for which he received a Nobel Prize. Somehow, this outcome represents such a blow to Chance’s previous work that somehow it seems to have cast a shadow over very important findings obtained during his earlier career that should not be affected by one or another form of energy transfer mechanism.  For instance, Britton Chance got the simple and rapid polarographic assay method of oxidative phosphorylation and the idea of control of energy metabolism that brings us back to Pasteur.

This metabolic alternative result seems to have been neglected in the recent years of obesity epidemics, which led to a search for a single molecular mechanism required for the understanding of the accumulation of chemical (adipose tissue) reserve in our body. It does not mean that here the role of central nervous system is neglected. In short, in respiring mitochondria the rate of electron transport linked to the rate of ATP production is determined primarily by the relative concentrations of ADP, ATP and phosphate in the external media (cytosol) and not by the concentration of respiratory substrate as pyruvate. Therefore, when the yield of ATP is high as it is in aerobiosis and the cellular use of ATP is not changed, the oxidation of pyruvate and therefore of glycolysis is quickly (without change in gene expression), throttled down to the resting state. The dependence of respiratory rate on ADP concentration is also seen in intact cells. A muscle at rest and using no ATP has a very low respiratory rate.   [When skeletal muscle is stressed by high exertion, lactic acid produced is released into the circulation and is metabolized aerobically by the heart at the end of the activity].

This respiratory control of metabolism will lead to preservation of body carbon reserves and in case of high caloric intake in a diet, also shows increase in fat reserves essential for our biological ancestors survival (Today for our obesity epidemics). No matter how important this observation is, it is only one focal point of metabolic control. We cannot reduce the problem of obesity to the existence of metabolic control. There are numerous other factors but on the other hand, we cannot neglect or remove this vital process in order to correct obesity. However, we cannot explain obesity ignoring this metabolic control. This topic is so neglected in modern times that we cannot follow major research lines of the past that were interrupted by the emerging molecular biology techniques and the vain belief that a dogmatic vision of biology could replace all previous knowledge by a new one based upon ATGC readings. For instance, in order to display bad consequences derived from the ignorance of these old scientific facts, we can take into account, for instance, how ion movements across membranes affects membrane protein conformation and therefore contradicts the wrong central dogma of molecular biology. This change in protein conformation (with unchanged amino acid sequence) and/or the lack of change in protein conformation is linked to the factors that affect vital processes as the heart beats. This modern ignorance could also explain some major pitfalls seen in new drugs clinical trials and in a small scale on bad medical practices.

The work of Britton Chance and of Peter Mitchell have deep and sound scientific roots that were made with excellent scientific techniques, supported by excellent scientific reasoning and that were produced in a large series of very important intermediary scientific results. Their sole difference was to aim at very different scientific explanations as their goals (They have different Teleology in their minds made by their previous experiences). When, with the use of mutants obtained in microorganisms P Mitchell´s goal was found to survive and B Chance to succumb to the experimental evidence, all those excellent findings of B Chance and followers were directed to the dustbin of scientific history as an example of lack of scientific consideration.  [On the one hand, the Mitchell model used a unicellular organism; on the other, Chance’s work was with eukaryotic cells, quite relevant to the discussion.]

We can resume the challenge faced by these two great scientists in the following form: The first conceptual unification in bioenergetics, achieved in the 1940s, is inextricably bound up with the name of Fritz Lipmann. Its central feature was the recognition that adenosine triphosphate, ATP, serves as a universal energy  “currency” much as money serves as economic currency. In a nutshell, the purpose of metabolism is to support the synthesis of ATP. In microorganisms, this is perfect! In humans or mammals, or vertebrates, by the same reason that we cannot consider that gene expression is equivalent to protein function (an acceptable error in the case of microorganisms) this oversimplifies the metabolic requirement with a huge error. However, in case our concern is ATP chemistry only, the metabolism produces ATP and the hydrolysis of ATP pays for the performance of almost, all kinds of works. It is possible to presume that to find out how the flow of metabolism (carbon flow) led to ATP production must be considered a major focal point of research of the two contenders. Consequently, what could be a minor fall of one of the contenders, in case we take into account all that was found during their entire life of research, the real failure in B Chance’s final goal was amplified far beyond what may be considered by reason!

Another aspect that must be taken into account: Both contenders have in the scientific past a very sound root. Metabolism may produce two forms of energy currency (I personally don´t like this expression*) and I use it here because it was used by both groups in order to express their findings. Together with simplistic thermodynamics, this expression conveys wrong ideas): The second kind of energy currency is the current of ions passing from one side of a membrane to the other. The P. Mitchell scientific root undoubtedly have the work of Hodgkin & Huxley, Huxley &  Huxley, Huxley & Simmons

*ATP is produced under the guidance of cell needs and not by its yield. When glucose yields only 2 ATPs per molecule it is oxidized at very high speed (anaerobiosis) as is required to match cellular needs. On the other hand, when it may yield (thermodynamic terms) 38 ATP the same molecule is oxidized at low speed. It would be similar to an investor choice its least money yield form for its investment (1940s to 1972) as a solid support. B. Chance had the enzymologists involved in clarifying how ATP could be produced directly from NADH + H+ oxidative reductive metabolic reactions or from the hydrolysis of an enolpyruvate intermediary. Both competitors had their work supported by different but, sound scientific roots and have produced very important scientific results while trying to present their hypothetical point of view.

Before the winning results of P. Mitchell were displayed, one line of defense used by B. Chance followers was to create a conflict between what would be expected by a restrictive role of proteins through its specificity ionic interactions and the general ability of ionic asymmetries that could be associated with mitochondrial ATP production. Chemical catalyzed protein activities do not have perfect specificity but an outstanding degree of selective interaction was presented by the lock and key model of enzyme interaction. A large group of outstanding “mitochondriologists” were able to show ATP synthesis associated with Na+, K+, Ca2+… asymmetries on mitochondrial membranes and any time they did this, P. Mitchell have to display the existence of antiporters that exchange X for hydrogen as the final common source of chemiosmotic energy used by mitochondria for ATP synthesis.

This conceptual battle has generated an enormous knowledge that was laid to rest, somehow discontinued in the form of scientific research, when the final E. Coli mutant studies presented the convincing final evidence in favor of P. Mitchell point of view.

Not surprisingly, a “wise anonymous” later, pointed out: “No matter what you are doing, you will always be better off in case you have a mutant”

(Principles of Medical Genetics T D Gelehrter & F.S. Collins chapter 7, 1990).

However, let’s take the example of a mechanical wristwatch. It clearly indicates when the watch is working in an acceptable way, that its normal functioning condition is not the result of one of its isolated components – or something that can be shown by a reductionist molecular view.  Usually it will be considered that it is working in an acceptable way, in case it is found that its accuracy falls inside a normal functional range, for instance, one or two standard deviations bellow or above the mean value for normal function, what depends upon the rigor wisely adopted. While, only when it has a faulty component (a genetic inborn error) we can indicate a single isolated piece as the cause of its failure (a reductionist molecular view).

We need to teach in medicine, first the major reasons why the watch works fine (not saying it is “automatic”). The functions may cross the reversible to irreversible regulatory limit change, faster than what we can imagine. Latter, when these ideas about normal are held very clear in the mind set of medical doctors (not medical technicians) we may address the inborn errors and what we may have learn from it. A modern medical technician may cause admiration when he uses an “innocent” virus to correct for a faulty gene (a rather impressive technological advance). However, in case the virus, later shows signals that indicate that it was not so innocent, a real medical doctor will be called upon to put things in correct place again.

Among the missing parts of normal evolution in biochemistry a lot about ion fluxes can be found. Even those oscillatory changes in Ca2+ that were shown to affect gene expression (C. De Duve) were laid to rest since, they clearly indicate a source of biological information that despite the fact that it does not change nucleotides order in the DNA, it shows an opposing flux of biological information against the dogma (DNA to RNA to proteins). Another, line has shown a hierarchy, on the use of mitochondrial membrane potential: First the potential is used for Ca2+ uptake and only afterwards, the potential is used for ADP conversion into ATP (A. L. Lehninger). In fact, the real idea of A. L. Lehninger was by far, more complex since according to him, mitochondria works like a buffer for intracellular calcium releasing it to outside in case of a deep decrease in cytosol levels or capturing it from cytosol when facing transient increase in Ca2+ load. As some of Krebs cycle dehydrogenases were activated by Ca2+, this finding was used to propose a new control factor in addition to the one of ADP (B. Chance). All this was discontinued with the wrong use of calculus (today we could indicate bioinformatics in a similar role) in biochemistry that has established less importance to a mitochondrial role after comparative kinetics that today are seen as faulty.

It is important to combat dogmatic reasoning and restore sound scientific foundations in basic medical courses that must urgently reverse the faulty trend that tries to impose a view that goes from the detail towards generalization instead of the correct form that goes from the general finding well understood towards its molecular details. The view that led to curious subjects as bioinformatics in medical courses as training in sequence finding activities can only be explained by its commercial value. The usual form of scientific thinking respects the limits of our ability to grasp new knowledge and relies on reproducibility of scientific results as a form to surpass lack of mathematical equation that defines relationship of variables and the determination of its functional domains. It also uses old scientific roots, as its sound support never replaces existing knowledge by dogmatic and/or wishful thinking. When the sequence of DNA was found as a technical advance to find amino acid sequence in proteins it was just a technical advance. This technical advance by no means could be considered a scientific result presented as an indication that DNA sequences alone have replaced the need to study protein chemistry, its responses to microenvironmental changes in order to understand its multiple conformations, changes in activities and function. As E. Schrodinger correctly describes the chemical structure responsible for the coded form stored of genetic information must have minimal interaction with its microenvironment in order to endure hundreds and hundreds years as seen in Hapsburg’s lips. Only magical reasoning assumes that it is possible to find out in non-reactive chemical structures the properties of the reactive ones.

For instance, knowledge of the reactions of the Krebs cycle clearly indicate a role for solvent that no longer could be considered to be an inert bath for catalytic activity of the enzymes when the transfer of energy include a role for hydrogen transport. The great increase in understanding this change on chemical reaction arrived from conformational energy.

Again, even a rather simplistic view of this atomic property (Conformational energy) is enough to confirm once more, one of the most important contribution of E. Schrodinger in his What is Life:

“This little book arose from a course of public lectures, delivered by a theoretical physicist to an audience of about four hundred which did not substantially dwindle, though warned at the outset that the subject matter was a difficult one and that the lectures could not be termed popular, even though the physicist’s most dreaded weapon, mathematical deduction, would hardly be utilized. The reason for this was not that the subject was simple enough to be explained without mathematics, but rather that it was much too involved to be fully accessible to mathematics.”

In a very simplistic view, while energy manifests itself by the ability to perform work conformational energy as a property derived from our atomic structure can be neutral, positive or negative (no effect, increased or decreased reactivity upon any chemistry reactivity measured as work)

Also:

“I mean the fact that we, whose total being is entirely based on a marvelous interplay of this very kind, yet if all possess the power of acquiring considerable knowledge about it. I think it possible that this knowledge may advance to little just a short of a complete understanding -of the first marvel. The second may well be beyond human understanding.”

In fact, scientific knowledge allows us to understand how biological evolution may have occurred or have not occurred and yet does not present a proof about how it would have being occurred. It will be always be an indication of possible against highly unlike and never a scientific proven fact about the real form of its occurrence.

As was the case of B. Chance in its bioenergetics findings, we may get very important findings that indicates wrong directions in the future as was his case, or directed toward our past.

The Skeleton of Physical Time – Quantum Energies in Relative Space of S-labs

By Radoslav S. Bozov  Independent Researcher

WSEAS, Biology and BioSystems of Biomedicine

Space does not equate to distance, displacement of an object by classically defined forces – electromagnetic, gravity or inertia. In perceiving quantum open systems, a quanta, a package of energy, displaces properties of wave interference and statistical outcomes of sums of paths of particles detected by a design of S-labs.

The notion of S-labs, space labs, deals with inherent problems of operational module, R(i+1), where an imagination number ‘struggles’ to work under roots of a negative sign, a reflection of an observable set of sums reaching out of the limits of the human being organ, an eye or other foundational signal processing system.

While heavenly bodies, planets, star systems, and other exotic forms of light reflecting and/or emitting objects, observable via naked eye have been deduced to operate under numerical systems that calculate a periodic displacement of one relative to another, atomic clocks of nanospace open our eyes to ever expanding energy spaces, where matrices of interactive variables point to the problem of infinity of variations in scalar spaces, however, defining properties of minute universes as a mirror image of an astronomical system. The first and furthermost problem is essentially the same as those mathematical methodologies deduced by Isaac Newton and Albert Einstein for processing a surface. I will introduce you to a surface interference method by describing undetermined objective space in terms of determined subjective time.

Therefore, the moment will be an outcome of statistical sums of a numerical system extending from near zero to near one. Three strings hold down a dual system entangled via interference of two waves, where a single wave is a product of three particles (today named accordingly to either weak or strong interactions) momentum.

The above described system emerges from duality into trinity the objective space value of physical realities. The triangle of physical observables – charge, gravity and electromagnetism, is an outcome of interference of particles, strings and waves, where particles are not particles, or are strings strings, or  are waves waves of an infinite character in an open system which we attempt to define to predict outcomes of tomorrow’s parameters, either dependent or independent as well as both subjective to time simulations.

We now know that aging of a biological organism cannot be defined within singularity. Thereafter, clocks are subjective to apparatuses measuring oscillation of defined parameters which enable us to calculate both amplitude and a period, which we know to be dependent on phase transitions.

The problem of phase was solved by the applicability of carbon relative systems. A piece of diamond does not get wet, yet it holds water’s light entangled property. Water is the dark force of light. To formulate such statement, we have been searching truth by examining cooling objects where the Maxwell demon is translated into information, a data complex system.

Modern perspectives in computing quantum based matrices, 0+1 =1 and/or 0+0=1, and/or 1+1 =0, will be reduced by applying a conceptual frame of Aladdin’s flying anti-gravity carpet, unwrapping both past and future by sending a photon to both, placing present always near zero. Thus, each parallel quantum computation of a natural system approaching the limit of a vibration of a string defining 0 does not equal 0, and 1 does not equal 1. In any case, if our method 1+1 = 1, yet, 1 is not 1 at time i+1. This will set the fundamentals of an operational module, called labris operator or in simplicity S-labs. Note, that 1 as a result is an event predictable to future, while interacting parameters of addition 1+1 may be both, 1 as an observable past, and 1 as an imaginary system, or 1+1 displaced interactive parameters of past observable events. This is the foundation of Future Quantum Relative Systems Interference (QRSI), taking analytical technologies of future as a result of data matrices compressing principle relative to carbon as a reference matter rational to water based properties.

Goedel’s concept of loops exist therefore only upon discrete relative space uniting to parallel absolute continuity of time ‘lags’. ( Goedel, Escher and Bach: An Eternal Golden Braid. A Metaphorical Fugue on Minds and Machines in the Spirit of Lewis Carroll. D Hofstadter.  Chapter XX: Strange Loops, Or Tangled Hierarchies. A grand windup of many of the ideas about hierarchical systems and self-reference. It is concerned with the snarls which arise when systems turn back on themselves-for example, science probing science, government investigating governmental wrongdoing, art violating the rules of art, and finally, humans thinking about their own brains and minds. Does Gödel’s Theorem have anything to say about this last “snarl”? Are free will and the sensation of consciousness connected to Gödel’s Theorem? The Chapter ends by tying Gödel, Escher, and Bach together once again.)  The fight struggle in-between time creates dark spaces within which strings manage to obey light properties – entangled bozons of information carrying future outcomes of a systems processing consciousness. Therefore, Albert Einstein was correct in his quantum time realities by rejecting a resolving cube of sugar within a cup of tea (Henri Bergson 19th century philosopher. Bergson’s concept of multiplicity attempts to unify in a consistent way two contradictory features: heterogeneity and continuity. Many philosophers today think that this concept of multiplicity, despite its difficulty, is revolutionary.) However, the unity of time and space could not be achieved by deducing time to charge, gravity and electromagnetic properties of energy and mass.

Charge is further deduced to interference of particles/strings/waves, contrary to the Hawking idea of irreducibility of chemical energy carrying ‘units’, and gravity is accounted for by intrinsic properties of   anti-gravity carbon systems processing light, an electromagnetic force, that I have deduced towards ever expanding discrete energy space-energies rational to compressing mass/time. The role of loops seems to operate to control formalities where boundaries of space fluctuate as a result of what we called above – dark time-spaces.

Indeed, the concept of horizon is a constant due to ever expanding observables. Thus, it fails to acquire a rational approach towards space-time issues.

Richard Feynman has touched on issues of touching of space, sums of paths of particle traveling through time. In a way he has resolved an important paradigm, storing information and possibly studying it by opening a black box. Schroedinger’s cat is alive again, but incapable of climbing a tree when chased by a dog. Every time a cat climbs a garden tree, a fruit falls on hedgehogs carried away parallel to living wormholes whose purpose of generating information lies upon carbon units resolving light.

In order to deal with such a paradigm, we will introduce i+1 under square root in relativity, therefore taking negative one ( -1 = sqrt (i+1), an operational module R dealing with Wheelers foam squeezed by light, releasing water – dark spaces. Thousand words down!

What is a number? Is that a name or some kind of language or both? Is the issue of number theory possibly accountable to the value of the concept of entropic timing? Light penetrating a pyramid holding bean seeds on a piece of paper and a piece of slice of bread, a triple set, where a church mouse has taken a drop of tear, but a blood drop. What an amazing physics! The magic of biology lies above egoism, above pride, and below Saints.

We will set up the twelve parameters seen through 3+1 in classic realities:

–              discrete absolute energies/forces – no contradiction for now between Newtonian and Albert Einstein mechanics

–              mass absolute continuity – conservational law of physics in accordance to weak and strong forces

–              quantum relative spaces – issuing a paradox of Albert Einstein’s space-time resolved by the uncertainty principle

–              parallel continuity of multiple time/universes – resolving uncertainty of united space and energy through evolving statistical concepts of scalar relative space expansion and vector quantum energies by compressing relative continuity of matter in it, ever compressing flat surfaces – finding the inverse link between deterministic mechanics of displacement and imaginary space, where spheres fit within surface of triangles as time unwraps past by pulling strings from future.

To us, common human beings, with an extra curiosity overloaded by real dreams, value happens to play in the intricate foundation of life – the garden of love, its carbon management in mind, collecting pieces of squeezed cooling time.

The infinite interference of each operational module to another composing ever emerging time constrains unified by the Solar system, objective to humanity, perhaps answers that a drop of blood and a drop of tear is united by a droplet of a substance separating negative entropy to time courses of a physical realities as defined by an open algorithm where chasing power subdue to space becomes an issue of time.

Jose Eduardo de Salles Roselino

Some small errors: For intance an increase i P leads to a decrease in V ( not an increase in V)..

 

Radoslav S. Bozov  Independent Researcher

If we were to use a preventative measures of medical science, instruments of medical science must predict future outcomes based on observable parameters of history….. There are several key issues arising: 1. Despite pinning a difference on genomic scale , say pieces of information, we do not know how to have changed that – that is shift methylome occupying genome surfaces , in a precise manner.. 2. Living systems operational quo DO NOT work as by vector gravity physics of ‘building blocks. That is projecting a delusional concept of a masonry trick, who has not worked by corner stones and ever shifting momenta … Assuming genomic assembling worked, that is dealing with inferences through data mining and annotation, we are not in a position to read future in real time, and we will never be, because of the rtPCR technology self restriction into data -time processing .. We know of existing post translational modalities… 3. We don’t know what we don’t know, and that foundational to future medicine – that is dealing with biological clocks, behavior, and various daily life inputs ranging from radiation to water systems, food quality, drugs…

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Development of Chemoresistance to Targeted Therapies: Alterations of Cell Signaling & the Kinome

Development of Chemoresistance to Targeted Therapies: Alterations of Cell Signaling, & the Kinome [11.4.1.2]

 

Curator, Reporter: Stephen J. Williams, Ph.D.

The advent of molecular targeted therapies like Imatinib (Gleevec), and other tyrosine kinase inhibitors (TKI) has been transformative to cancer therapy. However, as with all chemotherapeutics, including radiation therapy, the development of chemo-resistance toward personalized, molecular therapies has been disastrous to the successful treatment of cancer. The fact that chemo-resistance develops to personalized therapies was a serious disappointment to clinicians (although most expected this to be the case) but more surprisingly it was the rapidity of onset and speed of early reported cases which may have been the biggest shocker.

A post on resistance to other TKIs (to EGFR and ALK) can be seen here: http://pharmaceuticalintelligence.com/2013/11/01/resistance-to-receptor-of-tyrosine-kinase/

History of Development of Resistance to Imatinib (Gleevec)

The Melo group published a paper in Blood showing that short exposure to STI571 (imatinib; trade name Gleevec®) could result in drug resistant clones

Selection and characterization of BCR-ABL positive cell lines with differential sensitivity to the tyrosine kinase inhibitor STI571: diverse mechanisms of resistance. Blood. 2000 Aug 1;96(3):1070-9.

Mahon FX1, Deininger MW, Schultheis B, Chabrol J, Reiffers J, Goldman JM, Melo JV.

Abstract

Targeting the tyrosine kinase activity of Bcr-Abl with STI571 is an attractive therapeutic strategy in chronic myelogenous leukemia (CML). A few CML cell lines and primary progenitors are, however, resistant to this compound. We investigated the mechanism of this resistance in clones of the murine BaF/3 cells transfected with BCR-ABL and in 4 human cell lines from which sensitive (s) and resistant (r) clones were generated by various methods. Although the resistant cells were able to survive in the presence of STI571, their proliferation was approximately 30% lower than that of their sensitive counterparts in the absence of the compound. The concentration of STI571 needed for a 50% reduction in viable cells after a 3-day exposure was on average 10 times higher in the resistant (2-3 micromol/L) than in the sensitive (0.2-0.25 micromol/L) clones. The mechanism of resistance to STI571 varied among the cell lines. Thus, in Baf/BCR-ABL-r, LAMA84-r, and AR230-r, there was up-regulation of the Bcr-Abl protein associated with amplification of the BCR-ABL gene. In K562-r, there was no Bcr-Abl overexpression, but the IC(50) for the inhibition of Bcr-Abl autophosphorylation was increased in the resistant clones. Sequencing of the Abl kinase domain revealed no mutations. The multidrug resistance P-glycoprotein (Pgp) was overexpressed in LAMA84-r, indicating that at least 2 mechanisms of resistance operate in this cell line. KCL22-r showed neither Bcr-Abl up-regulation nor a higher threshold for tyrosine kinase inhibition by STI571. We conclude that BCR-ABL-positive cells can evade the inhibitory effect of STI571 by different mechanisms, such as Bcr-Abl overexpression, reduced intake mediated by Pgp, and, possibly, acquisition of compensatory mutations in genes other than BCR-ABL.

mellobcrablresistamplification

FISH analysis of AR230 and LAMA84 sensitive and resistant clones, with probes for the ABL (red signal) and theBCR (green signal) genes. BCR-ABL is identified as a red–green or yellow fused signal. Adapted from Mahon et al., Blood 2000; 96(3):1070-9.

This rapid onset of imatinib resistance also see in the clinic and more prominent in advance disease

From NCCN 2nd Annual Congress: Hematologic Malignancies – Update on Primary Therapy, Second-Line Therapy, and New Agents for Chronic Myelogenous Leukemia (Slides with Transcript)

http://www.medscape.org/viewarticle/564097

There is some evidence that even looking earlier makes some sense in determining what the prognosis is. This is from Timothy Hughes’ group in Adelaide, and he is looking at an earlier molecular time point, 3 months after initiation of therapy. And what you have done here is you have taken the 3-month mark and you have said, “Well, based on your response at 3 months, what is your likelihood that in the future you will either get a major molecular response or become resistant?”

3monthimitanibresist

If you look at the accumulation of imatinib resistance to find if it is either initially not responding or becoming resistant after a good response, it goes up with type of disease and phase of disease. So if you look at patients who have early chronic phase disease — that is, they start getting imatinib less than a year from the diagnosis — their chance of failure is pretty low. With later disease — they are in a chronic phase but they have had disease more than a year before they get imatinib — it is higher. If you see patients with accelerated phase or blast crisis, the chances are that they will fail sometime in the future.

speed of imitinib resistance

Therefore, because not all resistant samples show gene amplification of Bcr/Abl and the rapidity of onset of resistance, many feel that there are other mechanisms of resistance at play, like kinome plasticity.

Kinome Plasticity Contributes to TKI resistance

Beyond gene amplification, other mechanisms of imitanib and other tyrosine kinase inhibitors (TKI) include alterations in compensatory signaling pathways. This can be referred to as kinome plasticity and is explained in the following abstracts from the AACR 2015 meeting.

Systems-pharmacology dissection of a drug synergy in imatinib-resistant CML

Georg E Winter, Uwe Rix, Scott M Carlson, Karoline V Gleixner, Florian Grebien, Manuela Gridling, André C Müller, Florian P Breitwieser, Martin Bilban, Jacques Colinge, Peter Valent, Keiryn L Bennett, Forest M White & Giulio Superti-Furga. Nature Chemical Biology 8,905–912(2012)

Occurrence of the BCR-ABLT315I gatekeeper mutation is among the most pressing challenges in the therapy of chronic myeloid leukemia (CML). Several BCR-ABL inhibitors have multiple targets and pleiotropic effects that could be exploited for their synergistic potential. Testing combinations of such kinase inhibitors identified a strong synergy between danusertib and bosutinib that exclusively affected CML cells harboring BCR-ABLT315I. To elucidate the underlying mechanisms, we applied a systems-level approach comprising phosphoproteomics, transcriptomics and chemical proteomics. Data integration revealed that both compounds targeted Mapk pathways downstream of BCR-ABL, resulting in impaired activity of c-Myc. Using pharmacological validation, we assessed that the relative contributions of danusertib and bosutinib could be mimicked individually by Mapk inhibitors and collectively by downregulation of c-Myc through Brd4 inhibition. Thus, integration of genome- and proteome-wide technologies enabled the elucidation of the mechanism by which a new drug synergy targets the dependency of BCR-ABLT315I CML cells on c-Myc through nonobvious off targets.

nchembio.1085-F2kinomegleevecresistance

Please see VIDEO and SLIDESHARE of a roundtable Expert Discussion on CML

A Video Viewpoint: Expert Discussions on CML Clinical Debates from Institute For Medical Education and Research (IMER)

Curated Content From the 2015 AACR National Meeting on Drug Resistance Mechanisms and tyrosine kinase inhibitors

Session Title: Mechanisms of Resistance: From Signaling Pathways to Stem Cells
Session Type: Major Symposium
Session Start/End Time: Tuesday, Apr 21, 2015, 10:30 AM -12:30 PM
Location: Terrace Ballroom II-III (400 Level), Pennsylvania Convention Center
CME: CME-Designated
CME/CE Hours: 2
Session Description: Even the most effective cancer therapies are limited due to the development of one or more resistance mechanisms. Acquired resistance to targeted therapies can, in some cases, be attributed to the selective propagation of a small population of intrinsically resistant cells. However, there is also evidence that cancer drugs themselves can drive resistance by triggering the biochemical- or genetic-reprogramming of cells within the tumor or its microenvironment. Therefore, understanding drug resistance at the molecular and biological levels may enable the selection of specific drug combinations to counteract these adaptive responses. This symposium will explore some of the recent advances addressing the molecular basis of cancer cell drug resistance. We will address how tumor cell signaling pathways become rewired to facilitate tumor cell survival in the face of some of our most promising cancer drugs. Another topic to be discussed involves how drugs select for or induce the reprogramming of tumor cells toward a stem-like, drug resistant fate. By targeting the molecular driver(s) of rewired signaling pathways and/or cancer stemness it may be possible to select drug combinations that prevent the reprogramming of tumors and thereby delay or eliminate the onset of drug resistance.
Presentations:
Chairperson
Tuesday, Apr 21, 2015, 10:30 AM -12:30 PM
David A. Cheresh. UCSD Moores Cancer Center, La Jolla, CA
Introduction
Tuesday, Apr 21, 2015, 10:30 AM -10:40 AM
Resistance to tyrosine kinase inhibitors: Heterogeneity and therapeutic strategies.
Tuesday, Apr 21, 2015, 10:40 AM -10:55 AM
Jeffrey A. Engelman. Massachusetts General Hospital, Boston, MA
Discussion
Tuesday, Apr 21, 2015, 10:55 AM -11:00 AM
NG04: Clinical acquired resistance to RAF inhibitor combinations in BRAF mutant colorectal cancer through MAPK pathway alterations
Tuesday, Apr 21, 2015, 11:00 AM -11:15 AM
Ryan B. Corcoran, Leanne G. Ahronian, Eliezer Van Allen, Erin M. Coffee, Nikhil Wagle, Eunice L. Kwak, Jason E. Faris, A. John Iafrate, Levi A. Garraway, Jeffrey A. Engelman. Massachusetts General Hospital Cancer Center, Boston, MA, Dana-Farber Cancer Institute, Boston, MA
Discussion
Tuesday, Apr 21, 2015, 11:15 AM -11:20 AM
SY27-02: Tumour heterogeneity and therapy resistance in melanoma
Tuesday, Apr 21, 2015, 11:20 AM -11:35 AM
Claudia Wellbrock. Univ. of Manchester, Manchester, United Kingdom
Discussion
Tuesday, Apr 21, 2015, 11:35 AM -11:40 AM
SY27-03: Breast cancer stem cell state transitions mediate therapeutic resistance
Tuesday, Apr 21, 2015, 11:40 AM -11:55 AM
Max S. Wicha. University of Michigan, Comprehensive Cancer Center, Ann Arbor, MI
Discussion
Tuesday, Apr 21, 2015, 11:55 AM -12:00 PM
SY27-04: Induction of cancer stemness and drug resistance by EGFR blockade
Tuesday, Apr 21, 2015, 12:00 PM -12:15 PM
David A. Cheresh. UCSD Moores Cancer Center, La Jolla, CA
Discussion
Tuesday, Apr 21, 2015, 12:15 PM -12:20 PM
General Discussion
Tuesday, Apr 21, 2015, 12:20 PM -12:30 PM

Targeting Macromolecular Signaling Complexes 
Room 115, Pennsylvania Convention Center

Drug Resistance 
Hall A (200 Level), Pennsylvania Convention Center
Resistance to Pathway-Targeted Therapeutics 1 
Section 33

Molecular Mechanisms of Sensitivity or Resistance to Pathway-Targeted Agents 
Room 118, Pennsylvania Convention Center

Targeting Signaling Pathways in Cancer 
Room 204, Pennsylvania Convention Center
Exploiting the MAPK Pathway in Cancer 
Room 115, Pennsylvania Convention Center

PLEASE see the attached WORD file which includes ALL abstracts, posters, and talks on this subject from the AACR 2015 national meeting BELOW

 AACR2015resistancekinome

Other posts related to, Cancer, Chemotherapy, Gleevec and Resistance on this Open Access Journal Include

Imatinib (Gleevec) May Help Treat Aggressive Lymphoma: Chronic Lymphocytic Leukemia (CLL)

Treatments for Acute Leukemias [2.4.4A]

Therapeutic Implications for Targeted Therapy from the Resurgence of Warburg ‘Hypothesis’

Hematologic Malignancies [6.2]

Overview of Posttranslational Modification (PTM)

Novel Modeling Methods for Genomic Data Analysis & Evolutionary Systems Biology to Design Dosing Regimens to Minimize Resistance

Mechanisms of Drug Resistance

Using RNA-seq and targeted nucleases to identify mechanisms of drug resistance in acute myeloid leukemia

An alternative approach to overcoming the apoptotic resistance of pancreatic cancer

Resistance to Receptor of Tyrosine Kinase

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Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle

Reporter: Stephen S Williams, PhD

Article ID #180: Metabolic Genomics and Pharmaceutics, Vol. 1 of BioMed Series D available on Amazon Kindle. Published on 8/15/2015

WordCloud Image Produced by Adam Tubman

Leaders in Pharmaceutical Business Intelligence would like to announce the First volume of their BioMedical E-Book Series D:

Metabolic Genomics & Pharmaceutics, Vol. I

SACHS FLYER 2014 Metabolomics SeriesDindividualred-page2

which is now available on Amazon Kindle at

http://www.amazon.com/dp/B012BB0ZF0.

This e-Book is a comprehensive review of recent Original Research on  METABOLOMICS and related opportunities for Targeted Therapy written by Experts, Authors, Writers. This is the first volume of the Series D: e-Books on BioMedicine – Metabolomics, Immunology, Infectious Diseases.  It is written for comprehension at the third year medical student level, or as a reference for licensing board exams, but it is also written for the education of a first time baccalaureate degree reader in the biological sciences.  Hopefully, it can be read with great interest by the undergraduate student who is undecided in the choice of a career. The results of Original Research are gaining value added for the e-Reader by the Methodology of Curation. The e-Book’s articles have been published on the Open Access Online Scientific Journal, since April 2012.  All new articles on this subject, will continue to be incorporated, as published with periodical updates.

We invite e-Readers to write an Article Reviews on Amazon for this e-Book on Amazon.

All forthcoming BioMed e-Book Titles can be viewed at:

http://pharmaceuticalintelligence.com/biomed-e-books/

Leaders in Pharmaceutical Business Intelligence, launched in April 2012 an Open Access Online Scientific Journal is a scientific, medical and business multi expert authoring environment in several domains of  life sciences, pharmaceutical, healthcare & medicine industries. The venture operates as an online scientific intellectual exchange at their website http://pharmaceuticalintelligence.com and for curation and reporting on frontiers in biomedical, biological sciences, healthcare economics, pharmacology, pharmaceuticals & medicine. In addition the venture publishes a Medical E-book Series available on Amazon’s Kindle platform.

Analyzing and sharing the vast and rapidly expanding volume of scientific knowledge has never been so crucial to innovation in the medical field. WE are addressing need of overcoming this scientific information overload by:

This curation offers better organization and visibility to the critical information useful for the next innovations in academic, clinical, and industrial research by providing these hybrid networks.

Table of Contents for Metabolic Genomics & Pharmaceutics, Vol. I

Chapter 1: Metabolic Pathways

Chapter 2: Lipid Metabolism

Chapter 3: Cell Signaling

Chapter 4: Protein Synthesis and Degradation

Chapter 5: Sub-cellular Structure

Chapter 6: Proteomics

Chapter 7: Metabolomics

Chapter 8:  Impairments in Pathological States: Endocrine Disorders; Stress

                   Hypermetabolism and Cancer

Chapter 9: Genomic Expression in Health and Disease 

 

Summary 

Epilogue

 

 

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Chromatin Remodeling Enzymes: The Human Protein Methyltransferases

Chromatin Remodeling Enzymes: The Human Protein Methyltransferases

Reporter: Aviva Lev-Ari, PhD, RN

 

 

 

 

 

Methyltransferases are enzymes that facilitate the transfer of a methyl (-CH3) group to specific nucleophilic sites on proteins, nucleic acids or other biomolecules. They share a reaction mechanism in which the nucleophilic acceptor site attacks the electrophilic carbon of S-adenosyl-L-methionine (SAM) in an SN2 displacement reaction that produces a methylated biomolecule and S-adenosyl-L-homocysteine (SAH) as a byproduct. Methylation reactions are essential transformations in small-molecule metabolism, and methylation is a common modification of DNA and RNA. The recent discovery of dynamic and reversible methylation of amino acid side chains of chromatin proteins, particularly within the N-terminal tail of histone proteins, has revealed the importance of methyl ‘marks’ as regulators of gene expression. Human protein methyltransferases (PMTs) fall into two major families – protein lysine methyltransferases (PKMTs) and protein arginine methyltransferases (PRMTs) – that are distinguishable by the amino acid that accepts the methyl group and by the conserved sequences of their respective catalytic domains. Given their involvement in many cellular processes, PMTs have attracted attention as potential drug targets, spurring the search for small-molecule PMT inhibitors. Several classes of inhibitors have been identified, but new specific chemical probes that are active in cells will be required to elucidate the biological roles of PMTs and serve as potent leads for PMT-focused drug development.

 

Protein lysine methyltransferases (PKMTs)

The phylogenetic tree shows 51 genes predicted to encode PKMTs, which are positioned in the tree on the basis of the similarities of their amino acid sequences. This tree excludes one validated PKMT, DOT1L, which lacks a SET domain – the catalytic domain conserved in this family – and clusters more closely with the PRMTs. The tree has four major branches, and each branch contains enzymes with validated methyltransferase activity (highlighted in red). Some PKMTs add a single methyl group, resulting in a mono-methylated product (Kme), whereas others produce di-(Kme2) or tri-methylated (Kme3) lysine modifications. Many of the validated PKMTs methylate lysines on histones, though nonhistone substrates have also been identified.

 

Protein arginine methyltransferases (PRMTs)

The human PRMT phylogenetic tree comprises 45 predicted enzymes including the PKMT DOT1L. There are two major types of PRMTs; both catalyze the formation of mono-methylarginine (Rme1) but distinct reaction mechanisms yield symmetric (Rme2s) or asymmetric (Rme2a) dimethylarginine. A small number of predicted PRMTs have validated activity (highlighted in blue). In addition to PRMTs, this tree includes validated RNA methyltransferases (highlighted in green) and biosynthetic enzymes (highlighted in violet). It remains uncertain whether these latter enzymes have PRMT activity, despite their shared structural features. Substrates for the enzymes shown include RNA, metabolites, histones and RNA-binding and spiceosomal proteins.

 

More info: http://www.epizyme.com/epigenetics/about-epigenetics/chromatin-modifying-enzymes/

Sourced through Scoop.it from: www.genautica.com

See on Scoop.itCardiovascular and vascular imaging

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Protein-binding, Protein-Protein interactions & Therapeutic Implications [7.3]

Protein-binding, Protein-Protein interactions & Therapeutic Implications

Writer and Curator: Larry H. Bernstein, MD, FCAP 

7.3  Protein-binding, Protein-Protein interactions & Therapeutic Implications

7.3.1 Action at a Distance. Allostery_Delabarre_allostery review

7.3.2 Chemical proteomics approaches to examine novel histone modifications

7.3.3 Misfolded Proteins – from Little Villains to Little Helpers… Against Cancer

7.3.4 Endoplasmic reticulum protein 29 (ERp29) in epithelial cancer

7.3.5 Putting together structures of epidermal growth factor receptors

7.3.6 Complex Relationship between Ligand Binding and Dimerization in the Epidermal Growth Factor Receptor

7.3.7 IGFBP-2.PTEN- A critical interaction for tumors and for general physiology

7.3.8 Emerging-roles-for-the-Ph-sensing-G-protein-coupled-receptor

7.3.9 Protein amino-terminal modifications and proteomic approaches for N-terminal profiling

7.3.10 Protein homeostasis networks in physiology and disease

7.3.11 Proteome sequencing goes deep

7.3.1 Action at a Distance. Allostery_Delabarre_allostery review

DeLaBarre B1Hurov J1Cianchetta G1Murray S1Dang L2.
Chem Biol. 2014 Sep 18; 21(9):1143-61
http://dx.doi.org:/10.1016/j.chembiol.2014.08.007

Cancer cells must carefully regulate their metabolism to maintain growth and division under varying nutrient and oxygen levels. Compelling data support the investigation of numerous enzymes as therapeutic targets to exploit metabolic vulnerabilities common to several cancer types. We discuss the rationale for developing such drugs and review three targets with central roles in metabolic pathways crucial for cancer cell growth: pyruvate kinase muscle isozyme splice variant 2 (PKM2) in glycolysis, glutaminase in glutaminolysis, and mutations in isocitrate dehydrogenase 1 and 2 isozymes (IDH1/2) in the tricarboxylic acid cycle. These targets exemplify the drugging approach to cancer metabolism, with allosteric modulation being the common theme. The first glutaminase and mutant IDH1/2 inhibitors have entered clinical testing, and early data are promising. Cancer metabolism provides a wealth of novel targets, and targeting allosteric sites promises to yield selective drugs with the potential to transform clinical outcomes across many cancer types.

Based on knowledge acquired to date, there is no doubt that cancer metabolism provides a wealth of novel therapeutic targets and multiple innovative ways in which to exploit metabolic vulnerabilities for therapeutic benefit. More comprehensive reviews cover the breadth of metabolic targets that are currently under investigation (Stine and Dang, 2013; Vander Heiden, 2011). The following sections of this review focus on PKM2, glutaminase, and mutated IDH1/2 as exemplary metabolism targets under investigation for development of cancer therapies.
Drugging Glycolysis: Targeting Pyruvate Kinase Muscle Isozyme Alternative Splice Variant 2 PK catalyzes the last step of glycolysis, converting phosphoenolpyruvate (PEP) to pyruvate, while producing one molecule of ATP. The reaction encompasses two chemical steps: the first involves a phosphoryl transfer from PEP to ADP, forming an enolate intermediate and ATP, and the second involves protonation of the enolate intermediate, forming pyruvate (Robinson and Rose, 1972). PKM2 is one of four PK isoforms in humans. PKM1 and PKM2 result from the alternative splicing of exons 9 and 10 of the PKM gene, which encode a stretch of amino acids that differ at 23 positions between PKM1 and PKM2. PKM1 is constitutively active in skeletal muscle and brain tissue, but is not allosterically regulated. PKM2 is expressed in fetal and proliferating tissues, has low basal activity compared with PKM1, and is allosterically regulated. R-type pyruvate kinase (PKR) and L-type pyruvate kinase (PKL) are transcribed via different promoters from the PKLR gene. PKR is expressed in erythrocytes and PKL in the liver. PKR, PKL, and PKM1 exist as stable tetramers,whereas PKM2 forms tetramers (high activity form), dimers (low activity form), and monomers (Mazurek, 2011).

Figure 1. Central Metabolic Pathways Utilized by Cancer Cells *denotes mutated isoenzyme.

Pyruvate Kinase Muscle Isozyme Alternative Splice Variant 2 in Cancer Cell Metabolism Cancer cells predominantly express PKM2, which can be downregulated by tyrosine kinase growth factor signaling pathways, allowing metabolic flexibility. Phosphotyrosine peptides have been shown to suppress PKM2 activity by binding tightly to PKM2, thereby catalyzing the release of fructose 1,6-bisphosphate (FBP), resulting in a switch to the low activity dimer state (Christofk et al., 2008b; Hitosugi et al., 2009). This downregulation is thought to support tumor growth and proliferation by allowing for the shunting of glycolytic intermediates toward other biosynthetic pathways (i.e., pentose phosphate and serine pathways). In keeping with this model, the activation of PKM2 in cancer cells using small molecule agonists resulted in serine auxotrophy (Kung et al., 2012). Consistent with the hypothesis that PKM2 is a critical metabolic switch, there is growing evidence that, depending on the cellular stress environment, PKM2activity canberegulated byposttranslational modification such as acetylation (Lv et al., 2011), phosphorylation (Hitosugi et al., 2009), cysteine oxidation (Anastasiou et al., 2011), and proline hydroxylation (Luo et al., 2011). The utility of PKM2 activators in the clinic has yet to be determined, but recent work with tumor xenografts with a PKM2 activator suggests that this may be a viable approach (Parnell et al., 2013). As PKM2 tetramers show greater than 50-fold higher activity than PKM2 monomers (Anastasiou et al., 2012), one consideration when designing drugs to activate PKM2 for therapeutic means would be the need for small-molecule ligands capable of driving the enzyme toward its optimally active tetrameric form, thus forcing cancer cells into a less flexible metabolic state.

Structure of Pyruvate Kinase Muscle Isozyme Alternative Splice Variant 2 The structure of the PKM2 tetramer is summarized in Figure 2A. PKM2 is allosterically activated in a ‘‘feedforward’’ manner by the upstream glycolytic metabolite, FBP, which induces a shift to the active tetrameric conformation (Christofk et al., 2008b; Dombrauckas et al., 2005). PKM2 can be independently allosterically activated by serine (Chaneton et al., 2012), which binds in a distinct pocket that can also accommodate the inhibitor phenylalanine (Protein Data Bank [PDB] ID: 4FXJ). The binding of phenylalanine results in a tetrameric form distinct from the active conformer (Morgan et al., 2013). It is not clear how the change from serine to phenylalanine elicits such a dramatic change in protein behavior, or whether there is any biological interaction between serine activation and phenylalanine inhibition of PKM2 in cancer cells. Of note, PKM1 and PKL/R are not activated by serine, despite the conservation of the serine binding site in all PK isoforms.
Figure 2. Three Different Metabolic Enzymes and Their Allosteric Inhibitors Protomers are depicted as cartoon ribbons in blue, green, yellow, and cyan. Synthetic allostery is depicted in stick format with red highlight. (A) Structure of tetrameric PKM2:AGI-980 (4:2 complex) from PDB 4G1N. AGI-980 is shown in stick rendering near the center of tetramer. Each PK monomer consists of four domains, usually designated A, B, C, and N (Dombrauckas et al., 2005). The tetramer is a dimer-of-dimers with approximate D2 symmetry. The dimer is formed between the A domains of each monomer, while the tetramer is formed via dimerization along the C subunit interfaces of each dimer. The active site of PKM2 lies within a cleft between the A and B domain, illustrated by a PEP analog (red spheres). The FBP binding pocket is located entirely within the C domain (pink spheres). The natural allosteric site of serine is also shown (black spheres). (B)Tetrameric GAC:BPTES (4:2 complex) from PDB 3UO9. Glutamate molecules are shown as spheres. (C) Dimeric IDH2R140Q:AGI-6780 (2:1 complex) from PDB 4JA8 (Wang et al., 2013). NADP molecules are shown as spheres.
Discovery of Allosteric Activators of Pyruvate Kinase Muscle Isozyme Alternative Splice Variant 2 A number of small molecules that potently activate PKM2 have been discovered by various groups (Table 1). Interestingly, all seven X-rayco-complexescurrentlyavailableshowcompoundsbound at a novel binding pocket distinct from the FBP and serine binding sites, which would otherwise allow cells to overcome negative regulation by phosphotyrosines (Kung et al., 2012). The compounds found in structures 3GQY, 3GR4 (Boxer et al., 2010), 3H6O (Jiang et al., 2010), 3ME3, and 3U2Z (Anastasiou et al., 2012) were identified by screening the NIH Small Molecule Repository, and can be classified into two distinct chemical series, both of which establish very similar interactions with PKM2 (Table 1). Analogues in these two classes selectively activated PKM2 allosterically with good selectivity against PKM1, PKL, and PKR (Anastasiou et al., 2012; Boxer et al., 2010; Jiang et al., 2010). The molecule found in the structure 4JPG (Guo et al., 2013) is similar to the two series described above, where the pyrimidone ring is found between the two Phe26 residues (Table 1). Interestingly, the activator found in the 4G1N structure (Kung et al., 2012) sits in the same pocket as the NIH compounds. However, the interactions are quite different, with the side chains of the two Phe26 that line the pocket assuming distinct conformations. This activator wraps around the two aromatic residues, which pushes it closer to the walls of the pocket, allowing for a richer series of interactions with PKM2 (Table 1). There are two additional series of PKM2 activators that have been reported for which no structural information is available (Table 1)(Parnell et al., 2013; Xu et al., 2014; Yacovan et al., 2012). Members of this series were shown to have an activation level comparable to that of FBP, with selectivity for PKM2 over PKL, PKR, and PKM1. PKM2 offers a very interesting example of an allosterically regulated enzyme. Different allosteric sites have so far been identified for three different types of activator (FBP, serine, and small-molecule ligands) and all activate PKM2 by stabilizing the tetrameric form. It is remarkable that molecules as small as serine can dramatically alter this protein’s conformational landscape and aggregation state and lead to an active enzyme. This unusual allosteric site revealed by the small-molecule ligands is of particular curiosity, largely because neither its function nor its native ligands are known. All of the drug-like activators described above bind at the dimer–dimer interface and seem to act by displacing water from the mainly apolar pocket, thus contributing to the stabilization of the tetramer. While these PKM2 activators show promising preclinical data, none have yet entered clinical development.

Table 1. Biochemical Properties of Small Molecule PKM2 Inhibitors Series PDB ID Ligand Reference Binding Characteristics

Substituted N,N’diarylsulfonamide 3GQY (Boxer et al., 2010)

  1. 3GR4 (Boxer et al., 2010) 3ME3 (Anastasiou et al., 2012)
  2. Thieno[3,2-b]pyrrole [3,2-d]pyridazinone 3H6O (Jiang et al., 2010)
  3. 3U2Z (Anastasiou et al., 2012)
  4. 2-((1H-benzo[d]imidazol1-yl)methyl)-4H-pyrido [1,2-a]pyrimidin-4-ones
  5. 4JPG (Guo et al., 2013)

Quinolone sulfonamides 4G1N (Kung et al., 2012)

3-(trifluoromethyl)-1Hpyrazole-5-carboxamide (Parnell et al., 2013; Xu et al., 2014)

5-((2,3-dihydrobenzo[b] [1,4]dioxin-6-yl)sulfonyl)-2methyl-1-(methylsulfonyl) indoline scaffold (Yacovan et al., 2012)

Drugging Glutaminolysis: Targeting the Glutaminase C Variant Glutaminase catalyzes the conversion of glutamine to glutamate and ammonia. Glutamate can be oxidized to a-ketoglutarate (aKG), which then anaplerotically feeds into the TCA cycle as a means of providing proliferating cells with biosynthetic intermediates and ATP (Figure 1); glutamate is also used as a substrate for the generation of glutathione, which provides protection from redox stress (Hensley et al., 2013; Shanware et al., 2011). The ammonia produced during the reaction can be used in certain tissues like the kidney to provide pH homeostasis, and nitrogen derived from glutamine is utilized in nucleotide biosynthetic and glycosylation pathways.

Table 2. Characteristics of Small Molecule Glutaminase Inhibitors

BPTES N-(5–[1,3,4]thiadiazol-2yl)-2-phenylacetamide 6 (Shukla et al., 2012)

CB-839 (Calithera) (Gross et al., 2014)

Dibenzophenanthridines Compound 968 (Katt et al., 2012; Wang et al., 2010)

There are three isoforms of IDH. IDH1 is located in both the peroxisome and the cytosol, whereas IDH2 and IDH3 are located in mitochondria. It is unclear what the relative contributions of the IDH2 and IDH3 isoforms are to overall mitochondrial TCA function. IDH1 and IDH2 are both obligatory homodimeric proteins and use NADP+ as a cofactor, whereas IDH3 uses NAD+ as a cofactor and is a heterotrimeric protein comprising alpha, beta, and gamma subunits. All three isozymes require either Mg2+ or Mn2+ asdivalent metal cofactors for catalysis.The dimeric structure of IDH2 is shown in Figure 2C.

Mutant Isocitrate Dehydrogenase in Cancer Cell Metabolism The role of IDH mutations in cancer metabolism was recognized following the observation of frequent and recurrent mutations of IDH1 and IDH2 in patients with glioma and AML, initially identified by genomic deep sequencing and subsequent comparative genetic analyses (Parsons et al., 2008; Yan et al., 2009). These mutations were originally characterized as loss of function (Mardis etal.,2009; Parsonsetal.,2008; Yanet al.,2009), suggesting that mutated IDH acts as a tumor suppressor due to the loss of catalytic conversion of isocitrate to aKG (Zhaoetal., 2009). However, with the exception of cases of haploinsufficiency, the heterozygous mutation pattern of IDH is more consistent with an oncogene role. Subsequently, IDH mutations were shown to possess the neomorphic activity to generate the oncometabolite, 2-hydroxyglutarate (2HG) (Dang et al., 2009; Gross et al., 2010; Ward et al., 2010). With a single codon substitution, the kinetic properties of the mutant IDH isozyme are significantly altered, resulting in an obligatory sequential ordered reaction in the reverse direction (Rendina et al., 2013). Indeed, the critical kinetic observation of mutant IDH was not only the loss of affinity for isocitrate, but also a dramatic increase in NADPH affinity by three orders of magnitude (Dang et al.,2009), suggesting a substantial change in protein dynamics imparted by the mutation. The only known homeostatic 2HG clearance mechanism is the relatively inefficient reconversion of 2HG back to aKG by D-2hydroxyglutarate dehydrogenase. Therefore, 2HG accumulates when over-produced by mutant IDH. 2HG itself has been shown to be sufficient to drive the malignant phenotype (Rakheja et al., 2013). Abnormally high 2HG levels impair aKG-dependent dioxygenases through competitive inhibition, including those that modify DNA and histones (i.e., Jumonji domain-containing histone demethylases and the ten-eleven translocation (TET) family of 50-methylcytosine hydroxylases) (Chowdhury et al., 2011; Figueroa et al., 2010), as well as EglN prolyl hydroxylase in regulating hypoxia-inducible factor (Losman et al., 2013). This results in altered epigenetic status that blocks cell differentiation. These findings, combined with the inhibitory effects of fumarate and succinate on the same families of aKG-dependent enzymes, highlight a critical and fascinatingnetwork that ties together central metabolic pathways and epigenetic control. Remarkably, mutations in TET2 are mutually exclusive with IDH mutations in AML, strongly suggesting that, in this context, the tumorigenic effects of 2HG are at least in part driven by inhibition of TET2. The precise targets of IDH mutations with associated 2HG production (and TET2 mutations) that promote tumorigenesis are currentlyunknown;however,itisclearthatIDH1/2andTET2mutations lead to a block in hematopoietic cell differentiation (Figueroa et al., 2010; Lu et al., 2012; Moran-Crusio et al., 2011; Wang et al., 2013). To date, no IDH3 mutation associated with cancer has been reported (Krell et al., 2011; Reitman and Yan, 2010), suggesting that the role of IDH1/2 has a greater impact on tumorigenesis. Targeting mutated isoforms of IDH1/2 therefore presents a logical approach to cancer therapy. A consideration in designing suchdrugsistheheterozygoussomaticnatureoftheIDH1/2mutation, which likely yields a mixture of homo- and heterodimers; statistically, heterodimers should be the major species in vivo. Mutant homodimers and wild-type-mutant heterodimers both efficiently catalyze the production of 2HG from aKG (Dang et al., 2009; Rendina et al., 2013). However, the heterodimer is potentially more oncogenic, as it is more efficient at producing 2HG than homodimeric mutants (Pietrak et al., 2011) due to an increased local concentration of substrate while conserving NADPH. The heterodimer as a molecular target therefore becomes an important consideration in this scenario.

Structure of Isocitrate Dehydrogenase Structurally, both IDH1 and IDH2 comprise three main domains: the large domain, the small domain, and the clasp region (Yang et al., 2010). A simplified description of protein motion is provided in Figure 3 (Rendina et al., 2013; Xu et al., 2004). The dynamic of motion may differ slightly between IDH1 and IDH2 mutants. IDH1 mutants appear to open wider than IDH2 mutants to the point of unwinding a helix termed ‘‘seg2’’ (Yang et al., 2010). In contrast, the open form of IDH2 does not involve the melting of any secondary structure, and as a consequence has a much narrower range of motion (Taylor et al., 2008; Wang et al., 2013). This differential in protein dynamics could possibly explain the differential responses of IDH1 and IDH2 to inhibitors. X-ray structures of IDH3 have not yet been reported, but it appears to be distinct from IDH1 and IDH2 in terms of primary sequence and predicted quaternary organization (Kim et al., 1995; Ramachandran and Colman, 1980). There are three arginine residues in the enzyme active site that are predicted to play a central role in electrostatic stabilization and proper geometric orientation of isocitrate via its acidic moieties as the substrate binds in the active site. With the exception of the novel G97D or G97N codon mutation (Ward et al., 2012), virtually all confirmed IDH mutations that generate high levels of 2HG occur in one of these arginines (i.e., IDH1-R132 and IDH2-R172/R140) (Losman and Kaelin, 2013) and have in common a substitution of one of the diffuse positive charges of the respective arginine’s guanidinium moiety.
Discovery of Inhibitors against Mutated Isocitrate Dehydrogenase Several inhibitors of mutant IDH isoforms that block 2HG production in vitro and in vivo have been recently described. The first potent and specific IDH1 inhibitors reported were the phenylglycine series, specifically AGI-5198 (Popovici-Muller et al., 2012; Rohle et al., 2013) and subsequently ML309 (Davis et al., 2014)(Table 3), which were shown to be rapid-equilibrium inhibitors specific for IDH1-R132-codon mutations. These compounds inhibited IDH1-R132H competitively with respect to aKG and uncompetitively with respect to NADPH, suggesting that they preferably bind to the enzyme-NADPH ternary complex. Notably, they do not appreciably cross-react against the IDH2-R140Q mutant isozyme, suggesting a unique binding mode in IDH1-R132 that does not favorably exist in IDH2R140. Because no X-ray co-complex has been reported for this series, the exact mode of binding cannot be ascertained at this time. Preclinical data indicated 2HG inhibition and antitumor effects in vitro and in vivo (Table 3). These phenylglycine compounds appear to be excellent chemical tools for tumor biology investigation, but optimization of their properties is likely required for further therapeutic development. Co-complexes of IDH1-R132H with two different 1-hydroxypyridin-2-one inhibitors have been reported (Zheng et al., 2013), but the quality of the crystal structure data supporting the mechanism of inhibition is poor. AG-120, a selective, potent inhibitor of mutated IDH1, is currently in clinical development for the treatment of cancers with IDH1 mutations (Table 3), but there is currently no published information on this inhibitor. Another inhibitor of mutated IDH1 has been reported recently (Table 3) (Deng et al., 2014). Co-complex X-ray studies revealed that Compound1 binds mutated IDH1 allosterically at the dimer interface resulting in an asymmetric open conformation. Distinctively, Compound 1 displaces the conserved catalytic Tyr139 and further disrupts the Mg2+ binding network, consistent with kinetic results of competitive inhibition with respect to Mg2+, but not with aKG substrate. Others have reported modeling of inhibitors into the active site of IDH1, but experimental evidence is lacking (Chaturvedi et al., 2013; Davis et al., 2014). The first reported potent and selective IDH2 inhibitor was the urea-sulfonamide series, AGI-6780 (Wang et al., 2013), a timedependent slow-tight binder to IDH2-R140Q exhibiting noncompetitive inhibition with respect to substrate and uncompetitive inhibition with respect to NADPH, and nanomolar potency for 2HG inhibition (Table 3). This compound showed good inhibitory selectivity for IDH2-R140Q, with no effect on the closely related IDH1 and IDH1-R132H isozymes. At doses that effectively blocked 2HG to basal levels, AGI-6780 induced differentiation of TF-1 erythroleukemia and primary human AML cells in vitro, suggesting potential to reverse leukemic phenotype in AML tumors harboring the IDH2 mutation. Unlike the case of IDH1 above, the published structure of AGI-6780 co-complexed with IDH2-R140Q allows for detailed analysis of its inhibitory mechanism (Wang et al., 2013). In the X-ray structure, a single molecule
of AGI-6780 binds at the interface of two protomers (Figure 2C). The allosteric inhibition appears to arise from the ability of AGI6780 to keep the IDH2-R140Q mutant enzyme in an open orientation, thereby preventing the NADPH cofactor and substrate aKG from coming close to the catalytic Mg2+ binding site (see Figure 3). The highly symmetric AGI-6780 binding pocket extends deep into the protein interface and is closed over by loops composed of residues 152–167, which also fold over the binding pocket, providing anexplanation for the time-dependent inhibition kinetics. AGI-6780 makes several direct H-bond interactions from its urea group and amide nitrogen to Gln316, but a significant amount of binding energy arises from van der Waals contacts between the protein and hydrophobic surfaces of AGI-6780. The in vivo potential for this compound is not known, since its pharmacokinetic properties were not reported. Nevertheless, this effective mode of inhibition serves as an important molecular model for the design of bioisosteric compounds. OtherIDH2inhibitorsareunderdevelopment,notablyAG-221, a first-in-class, orally available inhibitor (Table 3) which demonstrated a survival advantage in a preclinical study of a primary human IDH2 mutant AML xenograft mouse model (Yen et al., 2013). Early phase I clinical trial data for AG-221 show promise, with meaningful clinical responses in evaluable AML patients harboring IDH2 mutations (Stein et al., 2014). To date, there is no published example of a molecule that inhibits both IDH1 and IDH2 mutant isoforms with equipotency.

Table 3.Characteristics of Small Molecule Inhibitors of Mutant IDH

PhenylglycineAGI-5198 (Popovici-Mulleretal., 2012; Rohleetal.,2013)
N-cyclohexyl-2-(N-(3-fluorophenyl)-2(2-methyl-1H-imidazol-1-yl)acetamido)2-(o-tolyl)acetamide IDH1-R132H

ML309 (Davis et al.,2014)
2-(2-(1H-benzo[d]imidazol-1-yl)-N-(3fluorophenyl)acetamido)-N-cyclopentyl2-o-tolylacetamide IDH1-R132H IDH1-R132C dIC50=68nM(R132H)

Undisclosed
AG-120 (Agios)
Undisclosed
IDH1

Allostery as an Approach to Drugging Metabolic Enzymes Is Important in Cancer All enzymes discussed in this article are allosterically targeted by small molecule modulators. With the exception of the enzymes of lipid metabolism, it is striking that there are very few examples of the regulation of metabolic enzymes by drug-like molecules at the catalytic site. We believe that this observation will hold true for the wider set of metabolic enzymes. Metabolic pathways are typically regulated by upstream and downstream metabolites through feedforward and feedback mechanisms. This regulation occurs typically through binding at allosteric sites, which have distinctly different properties relative to active sites. Therefore regulation can come from effectors that may have very different properties to the substrate. This review describes the potential therapeutic impact of specific allosteric regulators of PKM2, glutaminase, and IDH. Additionally, preclinical studies of tool compounds demonstrated that allosteric regulators of other enzymes involved in cancer cell metabolism could provide more therapeutic opportunities (Table 4). Substrates and products of metabolic enzymes tend to be small and very polar, and often include crucial metal ions and their ligands, so it is likely that targeting their catalytic pockets will yield molecules with similar properties. From a drug-discovery point of view, targeting allosteric sites is appealing as hydrophilic substrate-binding sites are generally not hospitable to strong interactions with small molecule drugs, which gain potency to a large extent through hydrophobic interactions. In addition, as activity of most metabolic enzymes is regulated by multimerization, the formation of multimers provides opportunity for binding sites to form at protein–protein interfaces.

Table 4. Examples of Allostery in Cancer Cell Metabolism

TH           Tyrosine hydroxylase         Haloperidol                                           Activator             Catecholamine metabolism               (Casu and Gale, 1981)
PDK1      Pyruvate dehydrogenase
kinase isozyme1                  3,5-diphenylpent-2-enoicacids                         Activator             TCAcycle                                                (Stroba et al., 2009)
BCKDK  Branched chain keto acid
dehydrogenase kinase   (S)-a-chloro-phenylpropionicacid[(S)-CPP]     Inhibitor              Branch-chain amino acid                   (Tso et al., 2013)
ACACA   Acetyl-CoA carboxylase
alpha                                 5-tetradecyloxy-2-furoicacid (TOFA)                  Inhibitor              Fatty acid  synthesis                            (Wang et al.,2009)

FBP1     Fructose-1,6
bisphosphatase1               Benzoxazole benzene sulfonamide1                    Inhibitor              Glycolysis                                        (von Geldern et al., 2006)
ALADA minolevulinate
dehydratase                     wALAD in1 benzimidazoles                                     Inhibitor              Haem synthesis                                    (Lentz et al., 2014)
TYR       Tyrosinase         2,3-dithiopropanol                                                   Inhibitor              Melanin metabolism                    (Wood and Schallreuter, 1991)
DBHD  opamine beta
hydroxylase-2H-phthalazinehydrazone (hydralazine;HYD)
2-1H-pyridinonehydrazone (2-hydrazinopyridine;HP)
2-quinoline-carboxylicacid (QCA)
1H-imidazole-4-aceticacid (imidazole-4-aceticacid;IAA)                             Inhibitor         Neurotransmitter synthesis                    (Townes et al.,1990)
DCTD   dCMP
deaminase        5-iodo-2’-deoxyuridine5’-triphosphate                                 Inhibitor          Nucleotide metabolism                      (Prusoff and Chang, 1968)
TYMP  Thymidine
phosphorylase     5’-O-tritylinosine (KIN59)                                                    Inhibitor          Nucleotide metabolism                         (Casanova et al.,2006)
TYMS Thymidylate
synthase         1,3-propanediphosphonicacid (PDPA)                                     Inhibitor          Nucleotide   metabolism                        (Lovelace et al.,2007)

Figure 3. Simplified Description of IDH Protein Motion The large domain (residues 1–103 and 286–414) forms nearly all of the NADPH cofactor binding residues and roughly half of the substrate binding residues.The small domain(residues 104–136 and 186–285) contains the remaining substrate binding residues and the metal binding residues. The interface between the two protomers is formed by both the small domain and the clasp region (residues 137–185). The large domain moves away from the small domain to facilitate NADPH cofactor exchange and substrate binding. The large domain then closes up against the small domain, thereby completing the substrate binding pocket and bringing the cofactor, substrate, and metal into close contact with each other and with the key catalytic residues to facilitate hydride transfer between substrate and cofactor and enzyme-assisted carboxylation/decarboxylation. Subsequent opening of the large domain from the small domain would enable product release and cofactor exchange to complete the catalytic cycle (Rendina et al., 2013; Xu et al., 2004).

7.3.2 Chemical proteomics approaches to examine novel histone modifications

Xin LiXiang David Li
Current Opinion in Chemical Biology Feb 2015; 24:80–90
http://dx.doi.org/10.1016/j.cbpa.2014.10.015

Highlights

Histone posttranslational modifications (PTMs) play key roles in the regulation of many fundamental cellular processes, such as gene transcription, DNA damage repair and chromosome segregation. Significant progress has been made on the detection of a large variety of PTMs on histones. However, the identification of these PTMs’ regulating enzymes (i.e. ‘writers’ and ‘erasers’) and functional binding partners (i.e. ‘readers’) have been a relatively slow-paced process. As a result, cellular functions and regulatory mechanisms of many histone PTMs, particularly the newly identified ones, remain poorly understood. This review focuses on the recent progress in developing chemical proteomics approaches to profile readers, erasers and writers of histone PTMs. One of such efforts involves the development of the Cross-Linking-Assisted and SILAC-based Protein Identification (CLASPI) approach to examine PTM-mediated protein–protein interactions.

Table 1    Novel histone PTMs                      functions
1             Lysine formylation             Arising from oxidative damage of DNA modification sites overlap with lysine acetylation and methylation, potentially interfere with normal regulation of these PTMs

2      Lysine propionylation  p300,c CREB-binding protein,c Sirt1,c Sirt2,c Sirt3c
Structurally similar with lysine acetylation, regulated by same set of enzymes, H3K23pr may be regulatory for cell metabolism
3    Lysine butyrylation       p300,c CREB-binding protein,c Sirt1,c Sirt2,c Sirt3c
Structurally similar with lysine acetylation, regulated by same set of enzymes
4    Lysine malonylation    Sirt5c
Changing the positively charged lysine to negatively charged residue, likely to affect the chromatin structure
5   Lysine succinylation    Sirt5c
A  mutation to mimic crotonyl lysine that changes lysine to glutamic acid of histone H4K31, reduces cell viability
6  Lysine crotonylation   Sirt1,c Sirt2,c Sirt3
Enriched at active gene promoters potential enhancers in mammalian genomes, male germ cell differentiation
7 Lysine 2-hydroxyiso
butyrylation                     HDAC1-3c
Associated with gene transcription
8  Lysine 4-oxononoylation    Modified by 4-oxo-2-nonenal, generated under oxidative stress, prevents nucleosome assembly in vitro
9 Lysine 5-hydroxylation   JMJD6
suppress lysine acetylation and methylation
10 Glutamine methylation   Nop1  (yeast), fibrillarin (huma)
human histone H2AQ105
11 Serine and
threonine GlcNAcylation  O-GlcNAc transferase
H2BS112 GlcNAcylation promotes K120 monoubiquitination, H3S10 GlcNAcylation suppresses phosphorylation of site
12 Serine and threonine acetylation
13 Serine palmitoylation   Lpcat1
catalyzed H4S47 palmitoylation, Ca2+-dependent, regulates global RNA synthesis
14  Cysteine glutathionylation
H3.2 and H3.3
conserved cysteine, but not H3.1, destabilize the nucleosomal structure
15 Cysteine fatty-acylation
H3.2 C110
16 Tyrosine hydroxylation

Fig. 1. Schematic description of a MS-based method for the identification of novel histone PTMs.

http://ars.els-cdn.com/content/image/1-s2.0-S1367593114001562-gr1.sml

Fig. 2. Chemical proteomics approaches to profile readers and erasers of histone PTMs.
(a) Photo-cross-linking strategy to capture proteins recognizing histone PTMs.
(b) Chemical structure of photoaffinity peptide probes.
Modifications of interest were labeled in green; photo-cross-linkers were labeled in red; chemical handles (alkyne) were labeled in blue; the sequence of probe C and probes 1–5 were derived from the
histone H3 1–15 amino acids residues, the sequence of probe 6 was derived from the histone H4 1–19 amino acids residues.
(c) Schematic for the CLASPI strategy to profile proteins that bind certain histone mark in whole-cell proteomes

http://ars.els-cdn.com/content/image/1-s2.0-S1367593114001562-gr2.sml

Consistent with our findings, Tate and coworkers [57] recently reported the development of a photoaffinity probe based on a succinylated glutamate dehydrogenase (GDH) peptide for capturing Sirt5
as the corresponding desuccinylase. In addition to the application of photo-cross-linking strategy for examining the histone PTMs with known erasers, we recently used CLASPI with a photoaffinity
probe (probe 5, Figure 2b) to profile proteins that recognize a novel histone mark, crotonylation at histone H3K4 (H3K4cr, Table 1, Entry 6) [25], whose erasers were unknown. This study revealed,
for the first time, that Sirt3 can recognize the H3K4cr mark and efficiently catalyze the removal of histone crotonylation marks. More importantly, Sirt3 was found to regulate histone Kcr level in
cells and may potentially modulate gene transcription through its decrotonylase activity [58]. By converting bisubstrate inhibitors of HATs (histone peptides with certain lysine residues covalently
attached to Ac-CoA) to clickable photoaffinity probes (for example, probe 6, Figure 2b), they carried out the first systematic profiling of HATs in whole-cell proteomes [59].  We  anticipate  that  similar methods can be used to search for writers of novel histone PTMs such as Kmal, Ksucc, Kcr and Khib (Table 1) since the corresponding acyl-CoAs are presumed to be the acyl donors.

We have shown, in this review, the applications and recent advances of chemical tools, in combination with MS-based proteomics approaches, for the detection and characterization of histone
PTMs and their readers, erasers and writers.

This article belongs to a special issue

Omics Edited By Benjamin F Cravatt and Thomas Kodadek

Editorial overview: Omics: Methods to monitor and manipulate biological systems: recent advances in ‘omics’

Benjamin F Cravatt, Thomas Kodadek
Current Opinion in Chemical Biology Feb 2015; 24:v–vii
http://dx.doi.org/10.1016/j.cbpa.2014.12.023

7.3.3 Misfolded Proteins – from Little Villains to Little Helpers… Against Cancer

Ansgar Brüning1,* and Julia Jückstock
Front Oncol. 2015; 5: 47
http://dx.doi.org/10.3389.2Ffonc.2015.00047

The application of cytostatic drugs targeting the high proliferation rates of cancer cells is currently the most commonly used treatment option in cancer chemotherapy. However, severe side effects and resistance mechanisms may occur as a result of such treatment, possibly limiting the therapeutic efficacy of these agents. In recent years, several therapeutic strategies have been developed that aim at targeting not the genomic integrity and replication machinery of cancer cells but instead their protein homeostasis. During malignant transformation, the cancer cell proteome develops vast aberrations in the expression of mutated proteins, oncoproteins, drug- and apoptosis-resistance proteins, etc. A complex network of protein quality-control mechanisms, including chaperoning by heat shock proteins (HSPs), not only is essential for maintaining the extravagant proteomic lifestyle of cancer cells but also represents an ideal cancer-specific target to be tackled. Furthermore, the high rate of protein synthesis and turnover in certain types of cancer cells can be specifically directed by interfering with the proteasomal and autophagosomal protein recycling and degradation machinery, as evidenced by the clinical application of proteasome inhibitors. Since proteins with loss of their native conformation are prone to unspecific aggregations and have proved to be detrimental to normal cellular function, specific induction of misfolded proteins by HSP inhibitors, proteasome inhibitors, hyperthermia, or inducers of endoplasmic reticulum stress represents a new method of cancer cell killing exploitable for therapeutic purposes. This review describes drugs – approved, repurposed, or under investigation – that can be used to accumulate misfolded proteins in cancer cells, and particularly focuses on the molecular aspects that lead to the cytotoxicity of misfolded proteins in cancer cells.

Introduction:

How Do Proteins Fold and What Makes Misfolded Proteins Dangerous?

For an understanding of misfolded proteins, it is necessary to understand how cellular proteins attain and then further maintain their native conformation and how mature proteins and unfolded proteins are generated and converted into each other.

The principles and mechanisms of protein folding were one of the major research topics and achievements of biochemical research in the last century. For decades, Anfinsen’s model, which explained protein structure by thermodynamic principles applying to the polypeptide’s inherent amino acid sequence (1), was to be found in the introductory sections of all textbooks in protein biochemistry. According to Anfinsen’s thermodynamic hypothesis, the structure with the lowest conformational Gibbs free energy was finally taken by each single polypeptide due to a thermodynamic and stereochemical selection for side chain relations that form most stable and effective enzymes or structural proteins (1). Beyond this individual selection for the energetically most optimized conformation, evolution also selected for amino acid sequences that energetically allowed the smoothest and most “frustration-free” folding processes via a thermodynamic “folding funnel” (1–3).

Whereas Anfinsen’s model preferred the side chain elements as preferential organizing structures, recent hypotheses have inversely proposed the backbone hydrogen bonds as the driving force behind protein folding (4). According to the former theory, the finally folded protein was assumed to attain a single defined structure and shape (1, 4), and the unfolded conditions were described as being represented by a structureless statistical coil with nearly indefinite conformations – a so-called “featureless energy landscape” (4). The latter model assumes that a protein selects during its folding process from a limited repertoire of stable scaffolds of backbone hydrogen bond-satisfied α-helices and β-strands (4). This also implies that unfolded proteins are not structureless, shoelace-like linear amino acid alignments as often depicted in cartoons for graphical reasons, but actually, at least in part, retain discrete and stable scaffolds.

Once the protein has attained its final conformation, the problem of stabilizing this structure arises. Hydrophobic interactions that press non-polar side chains into the center of the protein are assumed to be a major force in protein stabilization (5, 6). At the protein surface, polar interactions, mainly by hydrogen bonds of polar side chains and backbone structure, are assumed to be of similar importance (6). Salt bridges and covalent disulfide bonds were identified as further forces supporting the stability of proteins (6). Accordingly, all conditions that interfere with these stabilizing forces, including extreme temperature, salt concentrations, and redox conditions, may lead to protein misfolding.

Another aspect that must be taken into account when studying protein folding relates to the very different conditions found in viable cells when compared to test tube conditions. Considering the life-cycle of a protein, each protein begins as a growing polypeptide chain protruding from the ribosomal exit tunnel and with several of its future interacting amino acid binding partners not even yet attached to the growing chain of the nascent polymer. In these ribosomal exit tunnels, first molecular interactions and helical structures are formed, and evidence exists to support the notion that the speed of translation is regulated by slow translating codon sequences just to optimize these first folding processes (7). After leaving the ribosomal tunnel, nascent polypeptides are also directly welcomed by chaperoning protein complexes, which facilitate and further guide the folding process of newly synthesized proteins (8). It is believed that a high percentage of nascent proteins are subject to immediate degradation due to early folding errors (9). Since many nascent proteins are synthesized in parallel at polysomes, the temporal and spatial proximity of unfolded peptides brings the additional risk of protein aggregation (10). Moreover, as mentioned above, even incomplete folding intermediates and partially folded states may form energetically but not physiologically active metastable structures (11, 12). An immediate, perinatal guidance and chaperoning of newborn proteins is therefore essential to creating functional, integrative proteins and to avoiding misfolded, function-less polypeptides with potentially cytotoxic features.

Since protein structure and function are coupled, misfolded proteins are, at first, loss-of-function proteins that might reduce cell viability, in particular when generated in larger quantities. A more dangerous feature of misfolded proteins, however, lies in their strong tendency toward abnormal protein–protein interactions or aggregations, which is reflected by the involvement of misfolded proteins and their aggregates in several amyloidotic diseases, including neurodegenerative syndromes such as Alzheimer’s disease and Parkinson’s disease (13, 14). The fact that several of these intracellular and extracellular protein aggregates contain β-sheet-like structures and form filamentous structures also supports the notion that misfolded proteins are not necessarily structureless protein coils or unspecific aggregates, at least when they are formed by homogenous proteins as in the case of several neurodegenerative diseases (13). Paradoxically, these larger aggregates appear to reflect a cell protective mechanism so as to sequester or segregate smaller, but highly reactive, nucleation cores of condensing protein aggregates (13).

Unspecific hydrophobic interactions, in particular, have been held responsible for protein aggregations that form when terminally folded proteins lose their native conformation and expose buried hydrophobic side chains on their surface (15, 16). These hydrophobic interactions are also believed to be the most problematic issues with newly synthesized polypeptides on single ribosomes or polysomes (12). Once exposed to the surface, the hydrophobic structures will quickly find possible interaction partners. The intracellular milieu can be regarded as a “crowded environment” (17), fully packed with proteins in close contact and near to their solubility limit (8, 12). Thus, misfolded proteins not only aggregate among each other but may also attach to normal native proteins and inhibit their function and activity. Since such misfolding effects and interactions can also include nuclear DNA replication and repair enzymes (18), misfolded proteins may not only exert proteotoxic but also genotoxic effects, thereby endangering the entire cellular “interactome” (19) by interfering both with the integrity of the proteome (proteostasis) and the genome. Therefore, a misfolded protein is not simply a loss-of-function protein but also a promiscuous little villain that might act like a free radical, exerting uncontrolled danger to the cell.

The way in which cells deal with misfolded proteins strongly depends on the nature, strength, length, and location of the damage induced by the various insults. Management of misfolded proteins can be achieved by heat shock protein (HSP)-mediated protein renaturation (repair); proteasomal, lysosomal, or autophagosomal degradation (recycling); intracellular disposal (aggregation); or – in its last consequence if overwhelmed – by programed cell death (despair). In the following paragraphs, the cellular management of misfolded proteins is described and therapeutic options to induce misfolded proteins in cancer cells are presented.

Hsp90 and Hsp90 Inhibitors

The best-known and evolutionarily most-conserved mechanism to protect against protein misfolding is the binding and refolding process mediated by so-called heat shock proteins (HSPs). HSPs recognize unfolded or misfolded proteins and facilitate their restructuring in either an ATP-dependent (large HSPs) or energy-independent manner (low weight HSPs). HSP of 90 kDa (hsp90) is a constitutively expressed HSP and is regarded as the most common and abundantly expressed HSP in eukaryotic cells (20, 21). Although commonly referred to as hsp90, it consists of a variety of isoforms that are encoding for cytosolic (hsp90α1, α2, β), mitochondrial (TRAP1), or endoplasmic reticulum (ER)-resident (GRP94) forms. Its primary function is less that of a stress response protein and more to bind to a certain group of client proteins unable to maintain a stable configuration without being assisted by hsp90 (20, 22, 23). Steroid hormone receptors (estrogen receptor, glucocorticoid receptor), cell cycle regulatory proteins (CDK4, cyclin D, polo-like kinase), and growth factor receptors and their downstream targets (epidermal growth factor receptor 1, HER2, AKT) are among the best-studied client proteins of hsp90 (20–22). Also, several cancer-specific mutations generating otherwise instable oncoproteins, such as mutant p53 or bcr-abl, rely on hsp90 chaperoning to keep them in a soluble form, thereby facilitating the extravagant but vulnerable “malignant lifestyle” of hsp90-addicted cancer cells (21, 24). Accordingly, hsp90 has been assumed to be a prominent target, in particular for hormone-responsive and growth factor receptor amplification-dependent cancer types.

The microbial antibiotics geldanamycin and radicicol are the prototypes of hsp90 inhibitors. Based on intolerable toxicity, these molecules had to be chemically modified for application in humans, and most of the ongoing clinical studies with hsp90 inhibitors are aimed at identifying semi-synthetic derivatives of these lead compounds with an acceptable risk profile. Unfortunately, most recent studies using geldanamycin derivatives have provided disappointing results because of toxicities and insufficient efficacy (22, 25–27). Studies with radicicol (resorcinol) derivatives, in particular with ganetespib, appear to be more promising because of fewer adverse effects (22, 25–27). Liver and ocular (retinal) toxicities have been described as main adverse effects of hsp90 inhibition, and appeared to be experienced less with ganetespib than with most of the first generation hsp90 inhibitors (28).

Since both geldanamycin and radicicol target the highly conserved and unique ATP-binding domain of hsp90, new synthetic inhibitors have also been generated by rational drug design (22, 25–27). However, none of the various natural or synthetic hsp90 inhibitors under investigation have yet provided convincing clinical data, and future studies will show whether hsp90 can eventually be added to the list of effective cancer targets.

Hsp70, Hsp40, Hsp27, and HSF1

Hsp90 is assisted by several other HSPs and non-chaperoning co-factors, finally forming a large protein complex that recruits and releases client proteins in an energy-dependent manner (21, 22, 29). Client proteins for hsp90 are first bound to hsp70, which transfers the prospective client to hsp90 through the mediating help of an hsp70–hsp90 organizing protein (HOP). Binding of potential hsp90 client proteins to hsp70 is facilitated by its co-chaperone hsp40 (23, 30). Exposed hydrophobic amino acids, the typical feature of misfolded proteins, have been described as the main recognition signal for hsp70 proteins (15, 16, 31). Hsp70 proteins are not only supporter proteins for hsp90 but also represent a large chaperone family capable of acting independently of hsp90 and that can be found in all cellular compartments, including cytosol and nucleus (hsp70, hsp72, hsc70), mitochondria (GRP75 = mortalin), and the ER (GRP78 = BiP). Hsp70 chaperones may act on misfolded or nascent proteins either as “holders” or “folders” (31), which means that they prevent protein aggregation either by sheltering these aggregation-prone protein intermediates or by allowing these proteins to fold/refold into their native form in an assisted mechanism within a protected environment (31). Hsc70 (HSPA8) is a constitutively expressed major hsp70 isoform that is an essential factor for normal protein homeostasis even in unstressed cells (16). Misfolded proteins can also be destined by hsp70 proteins for their ultimate degradation. Proteins that expose KFERQ amino acid motifs on their surface during their unfolding process are preferentially bound by hsc70 and can be directed to lysosomes in a process called chaperone-mediated autophagy (CMA) (32, 33). In another mechanism of targeted protein degradation, interaction of hsc70 with the E3 ubiquitin ligase CHIP (carboxyl terminus of Hsc70-interacting protein) leads to ubiquitination of misfolded proteins and thus their destination of the ubiquitin-proteasome protein degradation pathway (34, 35). Since hsc70 is essential for normal protein homeostasis and its knock-out is lethal in mice (16, 36), hsc70 inhibition might not be an optimal target for cancer-specific induction of misfolded proteins. This contrasts with the inducible forms of hsp70 such as hsp72 (HSPA1), which are upregulated in a cell stress-specific manner and are often found to be constitutively overexpressed in cancer tissues (16, 36). Transcriptional activation of these inducible HSPs is mediated by the heat shock factor 1 (HSF1), which also regulates expression of hsp40 and the small HSP hsp27 by sharing a common promoter consensus sequence (heat shock response element) for HSF1 binding (37). HSF1 was also found to be constitutively activated in cancer tissues, modulating several cell cycle- and apoptosis-related pathways via its target genes (38–40). HSF1 itself is kept inactive in the cytosol by binding to hsp90, and the recruitment of hsp90 to misfolded proteins is considered a main activation mechanism to release monomeric HSF1 for its subsequent trimerization, post-translational activation, and nuclear translocation (24, 41). Also, since hsp90 inhibition causes hsp70 induction by HSF1 activation as a compensatory feed-back mechanism (24), combined inhibition of hsp90 and hsp70, or of hsp90 and HSF1 might be a more effective therapeutic approach for cancer treatment than single HSP targeting alone.

Indeed, several small-molecule inhibitors and aptamers for hsp70, hsp40, and hsp27 have been designed (16, 42–44), but most of them remain in pre-clinical development, or are either not applicable in humans or associated with intolerable side effects (16, 42–44). Notably, the natural bioflavonoid quercetin was shown to inhibit phosphorylation and transcriptional activity of the heat shock transcription factor HSF1, thus reducing HSP expression at its most basal level (45–48). This HSP and HSF1 inhibition may also contribute to the observed cancer-preventing effects of a flavonoid-rich diet, which includes fruits and vegetables. However, due to their low bioavailability, the concentrations of flavonoids needed to induce direct cytotoxic effects in cancer cells for (chemo-)therapeutic reasons are obviously not achievable in humans, even when applied as nutritional supplements (49). More effective and clinically more easily applicable inhibitors of HSF1 are therefore urgently sought. Promising HSF1 targeting strategies are currently under development, although are apparently not yet suited for clinical applications (24, 50, 51).

SP Williams Comment:

There is a new hsp90- inhibitor, ganetespib, which is active against ovarian cancer in vitro and in vivo. Clinical trials are looking at this in cisplatin refractory cases. This was identified by a network analysis from a previous siRNA screen on ovarian cancer cells for pathways related to growth inhibition in an effort to find possible targets against CP resistance. The reference ishttp://www.researchgate.net/publication/253647952_Network_analysis_identifies_an_HSP90-central_hub_susceptible_in_ovarian_cancer

Protein Ubiquitination and Proteasomal Degradation

Ubiquitin is a 76 amino acid polypeptide that can covalently be attached via its carboxy-terminus to free (lysyl) amino groups of proteins. Ubiquitination of proteins generates a cellular recognition motif that is involved in various functions ranging from transcription factor and protein kinase activation to DNA repair and protein degradation – depending on the extent and exact location of this post-translational modification (52, 53). Monoubiquitination of peptides of more than 20 amino acids was found to be a minimal requirement for protein degradation, but the canonical fourfold (poly-)ubiquitination with three further lysine (K48) side chain-linked ubiquitins appears to be most apt for an effective and rapid substrate recognition by the proteasome (54). This canonical polyubiquitin structure, as well as several other mixed polyubiquitin structures, can be recognized by the external 19S subunits of the 26S proteasome complex (54, 55). Prior to degradation of ubiquitinated proteins by the proteasomal 20S core subunit, the attached ubiquitin chains are released by the external 19S subunits for recycling, although they can also be co-degraded by the proteasome (56). After first passing the 19S subunit, the proteasomal target proteins are then unfolded in an energy-dependent manner and introduced into the narrow enzymatic cavity of proteasome for degradation. The barrel-shaped 20S proteasomal core complex contains three different proteolytic activities in duplicate (β1: caspase-like-, β2: tryptic-, and β5: chymotryptic activity), which initiate an efficient cleavage of the proteasomal target proteins into smaller peptides (57).

It is important to note that specific ubiquitination and ensuing proteasomal degradation is not an exclusive degradation mechanism of misfolded proteins but is also used to regulate the expression level of several native cell cycle regulatory proteins [cyclins, proliferating cell nuclear antigen (PCNA), p53], signaling pathway molecules (β-catenin, IκB), and survival factors (mcl-1) during the course of normal protein homeostasis and cell cycle progression (53, 55, 57, 58). Moreover, proteasomes are involved in protein maturation, including the processing and maturation of the NF-κB transcription factor subunit p50 and the drug-resistant protein MDR1 (57). Therefore, targeting proteasomal activity has not only been of interest for the generation of misfolded, cytotoxic proteins but also for interfering with the expression of proteins involved in several hallmarks of cancer, including cell cycle progression, signal transduction, and apoptosis.

Proteasome Inhibitors

Bortezomib (PS-341, Velcade ™) has long been known as a paragon of a clinically applicable proteasome inhibitor. Bortezomib has been approved for the treatment of multiple myeloma and mantle cell lymphoma (55, 59, 60). The great expectations of transferring the success of bortezomib to non-hematological solid cancer types have unfortunately not yet been fulfilled. It has been suggested that the high antibody-producing capacity of myeloma cells and thus the need for an efficient proteasomal degradation system to cope with the recycling process of misfolded ER-generated antibodies [ER-associated degradation process (ERAD); see below] might contribute to the high sensitivity of myeloma cells to bortezomib (9, 60, 61). Originally, bortezomib was developed to inhibit the proteasomal degradation of the NF-κB inhibitor IκB, thus targeting the pro-inflammatory, but also cancer-promoting, effect of the NF-κB transcription factor (55, 60, 62). Recent insights indicate that the anti-tumoral effect of bortezomib is not only mediated by its NF-κB inhibitory activity but also by its ability to induce accumulation of misfolded proteins in the cytosol and the ER (60, 62–65). However, the use of bortezomib, even for highly sensitive multiple myeloma, is limited by its strong tendency to induce a proteasome inhibition-independent peripheral neuropathy by acting on neuronal mitochondria (61). Since neurodegenerative diseases are associated with protein misfolding and aggregation, the neuropathological effects of bortezomib might also be assumed to be mediated by the possible proteotoxic effects of bortezomib in neuronal cells. However, although proteasome inhibitor-induced neurodegeneration and inclusion body formation have been described in animal models, similarities between proteasome inhibitor-induced neurodegeneration and Parkinson’s disease-like histopathological features could not be established (66).

Table 1 Drugs described in this review and their mechanism of action (MOA), status of approval, and main adverse effects.

Aggresome Formation and Re-Solubilization: Role of HDAC6

As depicted above, proteasome and HSP inhibition will eventually lead to the accumulation of misfolded and polyubiquitinated proteins. Based on their inherent cohesive properties mediated by their exposed hydrophobic surfaces, both ubiquitinated and non-ubiquitinated misfolded proteins tend to adhere as small aggregates (Figure ​(Figure1).1). Individual ubiquitinated proteins and small ubiquitinated aggregates can be recognized by specific ubiquitin-binding proteins such as HDAC6 via its zinc finger ubiquitin-binding domain. HDAC6 is an unusual histone deacetylase located in the cytosol that regulates microtubule acetylation and is also able to bind ubiquitinated proteins. Based on HDAC6’s additional ability to bind to microtubule motor protein dynein, these aggregates are actively transported along the microtubular system into perinuclear aggregates around the microtubule organizing center (MTOC) (108384). Recognition of small, scattered ubiquitinated aggregates by HDAC6 has been described as being mediated by unanchored ubiquitin chains, which are generated by aggregate-attached ubiquitin ligase ataxin-3 (85). Whereas proteasomal target proteins are primarily tagged by K-48 (lysine-48) linked ubiquitins; K-63 linked ubiquitin chains appear to be a preferential modification for aggresomal targeting by HDAC6 and were assumed to mediate a redirection from proteasomal degradation to aggresome formation in the case of proteasomal inhibition or overload (86). Accordingly, aggresome formation is not an unspecific protein aggregation but a specific, ubiquitin-controlled sorting process. Furthermore, these aggresomes consist not only of misfolded and deposited proteins but have also been shown to contain a large amount of associated HSPs and ubiquitin-binding proteins, including HDAC6 [Figure ​[Figure1;1; (108384)]. Aggresomes contain, and are also surrounded by, large numbers of proteasomes (108384), which help to resolubilize these aggregates not only through their intrinsic proteasomal digestion but also by generating unanchored K63-branched polyubiquitin chains, which then stimulate HDAC6-mediated autophagy, another cellular disposal mechanism in involving HDAC6 (87). Notably, HDAC6 has also been shown to control further maturation of autophagic vesicles by stimulating autophagosome–lysosome fusion (Figure ​(Figure1)1) in a manner different from the normal autophagosome–lysosome fusion process (88).

Figure 1

Drugs that inhibit folding or disposal of misfolded proteins. Native mature proteins, nascent proteins, or misfolded proteins can be prevented from folding or refolding by small and large heat shock protein inhibitors, of which the hsp90 inhibitors based 

The HDAC6 multitalent also exerts its deacetylase activity on hsp90 and modifies hsp90 client binding by facilitating its chaperoning of steroid hormone receptors and HSF1 (8991). Recruitment of HDAC6 to ubiquitinated proteins leads to the dissociation of the repressive HDAC6/hsp90/HSF1 complex (91) and allows the release of transcriptionally active HSF1 to the nucleus. The engagement of HDAC6 at the aggresome–autophagy pathway hence also indirectly facilitates HSF1 activity. p97/VCP (valosin-containing protein), another binding partner of HDAC6 and itself a multi-interactive, ATP-dependent chaperone (9294), is assumed to be involved not only in the specific separation of hsp90 and HSF1 by its “segregase” activity but also in the binding and remodeling of polyubiquitinated proteins before their delivery to the proteasome (9395). Additionally, p97/VCP dissociates polyubiquitinated proteins bound to HDAC6 (91). Accumulation of polyubiquitinated proteins thus leads to HDAC6-dependent HSF1 activation and HSP induction, p97/VCP-dependent recruitment and “preparation” of polyubiquitinated proteins to proteasomes, and, in the case of pharmacological proteasome inhibition or physiological overload, to an HDAC6-dependent detoxification of polyubiquitinated proteins by the aggresome/autophagy pathway.

Pharmacological Inhibition of Aggresome Formation: HDAC6 Inhibitors

The central involvement of HDAC6 in aggresome formation and clearance makes HDAC6 one of the most interesting druggable targets for the induction of proteotoxicity in cancer cells. Also, HDAC6 has been found to be overexpressed in various cancer tissues, associated with advanced cancer stages and increased neoplastic transformation (96). Several pan-histone deacetylase inhibitors have been developed and tested in clinical studies for a variety of diseases, including different types of cancer (9798). Although hematological malignancies responded best to most of the already clinically tested pan-histone deacetylase inhibitors, the efficacy on solid cancer types was disappointingly poor and also associated with intolerable side effects (98). The unforeseeable pleiotropic epigenetic mechanism caused by non-specific (nuclear) histone deacetylase inhibitors may also limit their application for use in cancer treatment or HDAC6 inhibition, and has led to the search for selective HDAC6 inhibitors with no inhibitory effects on transcription modifying histone deacetylases. Through screening of small molecules under the rationale of selecting for tubulin deacetylase inhibitors with no cross-reactive histone deacetylase activity, the HDAC6 inhibitor tubacin was identified, and suggested for use in the treatment of neurodegenerative diseases or to reduce cancer cell migration and angiogenesis (99). Hideshima et al. then proved the hypothesis that the combined use of bortezomib with tubacin leads to an accumulation of non-disposed cytotoxic proteins and aggregates in cancer cells (100). Indeed, a synergistic effect of these two drugs against multiple myeloma cells could be observed with no detectable toxic effect on peripheral blood mononuclear cells (100). This and follow-up studies also revealed the efficacy of tubacin as a single agent against leukemia cells (100101) and a chemo-sensitizing effect on cytotoxic drugs in breast- and prostate-cancer cells (102).

Endoplasmic Reticulum Stress

Besides the cytosol, the ER is a major site for protein synthesis, in particular for those proteins destined for extracellular secretion, the cell membrane, or their retention within the endomembrane system. At the rough ER, nascent proteins are co-translationally transported across the ER membrane into the ER lumen (107), where they immediately encounter ER-resident chaperones, most prominently represented by hsp70 family member BiP/GRP78 and hsp90 family member GRP94 to help proper protein folding (15108). Most of these proteins also undergo post-translational modifications, including N- or O-linked glycosylation or protein disulfide bridge-building (109110), thereby adding further mechanisms of protein stabilization but also challenges for proper protein folding.

Similar to the situation in cytosolic protein biosynthesis, a large proportion of nascent proteins in the ER are assumed to misfold and to go “off-pathway” even under normal physiological conditions. Furthermore, the ER lumen, narrowly sandwiched between two phospholipid membranes, has been described as an even more densely crowded environment than the cytosol, additionally facilitating unspecific protein attachments and aggregations (15). Since, with the exception of bulk reticulophagy, the lumen of the ER contains no endogenous protein degradation system, and the anterograde transport of ER proteins to the Golgi, lysosomes, endosomes, or the extracellular environment requires properly folded proteins, a retrograde transport of ER proteins into the cytosol remains the only possible mechanism of preventing misfolded protein accumulation within the ER. In this ERAD, misfolded proteins are re-exported across the ER membrane by a specific multi protein complex, ubiquitinated by ER membrane-integrated ubiquitin ligases, and finally become degraded by cytosolic proteasomes (111112). Notably, association of the cytosolic p97/VCP protein, an important interacting partner with HDAC6, has also been described as being an essential factor for driving the luminal proteins through the ER membrane pore complex into the cytosol (92,112).

Accordingly, all agents and conditions that interfere with these folding, maturation, and retranslocation processes can lead to protein misfolding and aggregation within this sensitive organelle. Chemicals that act as glycosylation inhibitors (tunicamycin), calcium ionophore inhibitors (A23187, thapsigargin), heavy metal ions (cadmium, lead), reducing agents (dithiothreitol), as well as conditions like hypoxia or oxidative stress, all lead to a phenomenon called ER stress (113116). In the ER-stress response, a triad of ER membrane-resident signaling receptors and transducers, IRE1, ATF6, and PERK1, become activated and lead to the transcriptional activation of cytosolic and ER-resident chaperones to cope with the increasing number of misfolded proteins. Induction of autophagy (reticulophagy; ER-phagy) may also occur and supports the removal of damaged regions of the ER (117). Under very intensive or even unmanageable ER-stress conditions, a variety of pro-apoptotic pathways ensue, including CHOP induction, c-JUN-kinase activation, and caspase cleavage (118120), which eventually prevails over the cytoprotective arm of the ER-stress response and may lead to apoptosis. Targeting of protein folding within the ER is therefore a very promising strategy to induce apoptosis in cancer cells, in particular in those cancer cells characterized by an unphysiologically high protein secretion rate, such as, for example, multiple myeloma cells. Whereas the above-mentioned drugs such as tunicamycin or thapsigargin are valuable tools for cell biology studies, they display unacceptable toxicities in humans and are not suited for therapeutic applications. Interestingly, several already established drugs used for non-cancerous diseases have been described as inducing ER stress at pharmacologically relevant concentrations in humans as an off-target effect (113116). The non-steroidal anti-inflammatory COX-2 inhibitor celecoxib is an approved drug to treat various forms of arthritis and pain, but has also been described as exerting ER stress by functioning as a SERCA (sarco/ER Ca2+ ATPase) inhibitor (113116). However, although well tolerated in humans, the ER-stress-inducing ability of celecoxib seems to be weaker than that of direct SERCA inhibitors such as thapsigargin, and the usefulness of celecoxib against advanced cancer has been questioned (116). Various HIV protease inhibitors have been described as inducing ER stress in human tissue cells as a side effect (121123). In particular the HIV drugs lopinavir, saquinavir, and nelfinavir appear to be potent inducers of the ER-stress reaction, leading to a focused interest in these drugs for the induction of ER stress and apoptosis in cancer cells (116124128). In fact, with currently over 27 clinical studies in cancer patients2, nelfinavir, either used as a single agent or in combination therapy, is on the list of the most promising prospective candidates to induce selective proteotoxicity in cancer cells at pharmacologically relevant concentrations. Although the exact mechanism by which nelfinavir induces ER stress is not yet clear, it was shown that nelfinavir causes the upregulation of cytosolic and ER-resident HSPs, and induces apoptosis in cancer cells associated with caspase activation and induction of the pro-apoptotic transcription factor CHOP (125126). Nelfinavir was also shown to be combinable with bortezomib to enhance its activity on cancer cells (129). Since the retrograde transport of misfolded ER proteins is inhibited by the p97/VCP inhibitor eeyarestatin (130131), we recently tested the combination of eeyarestatin with nelfinavir but found no synergistic effect between these two agents in cervical cancer cells (132). In contrast, eeyarestatin markedly sensitized cervical cancer cells to bortezomib treatment (132), which was also observed in preceding studies in which eeyarestatin was used to augment the ER-stress-inducing ability of bortezomib in leukemia cells (131).

Induction of proteotoxicity through the accumulation of misfolded proteins has evolved as a new treatment modality in the fight against cancer. Clinically approved drugs such as bortezomib and carfilzomib provide evidence of the functionality of this approach. Newly developed agents like the HDAC6 inhibitor ACY-1215 or repurposed drugs like nelfinavir or disulfiram are currently being tested in clinical trials with cancer patients and will hopefully further broaden our arsenal of anti-cancer drugs. Notably, most proteotoxic agents that have been approved or are in clinical trials target the ubiquitin-proteasome-system (UPS) and are mainly effective in multiple myeloma cells, which rely on a functional ER/ERAD/UPS for excessive and proper antibody production. Similarly, it can be assumed that other cancer cell types with a marked secretory phenotype may also be affected by ER/ERAD/UPS inhibitors. In accordance with this notion, a recent dose-escalating Phase Ia study with nelfinavir as a single agent, that covered a large variety of solid cancer entities, revealed response rates primarily in patients with neuroendocrine tumors (140). In most other solid cancer types, however, the chemo-sensitizing or combination effects of proteotoxic drugs may prevail, and have become the focus of an increasing number of very promising clinical and pre-clinical studies.

7.3.4 Endoplasmic reticulum protein 29 (ERp29) in epithelial cancer

Friend or Foe: Endoplasmic reticulum protein 29 (ERp29) in epithelial cancer

Chen S1Zhang D2

FEBS Open Bio. 2015 Jan 30; 5:91-8
http://dx.doi.org:/10.1016/j.fob.2015.01.004

The endoplasmic reticulum (ER) protein 29 (ERp29) is a molecular chaperone that plays a critical role in protein secretion from the ER in eukaryotic cells. Recent studies have also shown that ERp29 plays a role in cancer. It has been demonstrated that ERp29 is inversely associated with primary tumor development and functions as a tumor suppressor by inducing cell growth arrest in breast cancer. However, ERp29 has also been reported to promote epithelial cell morphogenesis, cell survival against genotoxic stress and distant metastasis. In this review, we summarize the current understanding on the biological and pathological functions of ERp29 in cancer and discuss the pivotal aspects of ERp29 as “friend or foe” in epithelial cancer.

The endoplasmic reticulum (ER) is found in all eukaryotic cells and is complex membrane system constituting of an extensively interlinked network of membranous tubules, sacs and cisternae. It is the main subcellular organelle that transports different molecules to their subcellular destinations or to the cell surface [10,85].

The ER contains a number of molecular chaperones involved in protein synthesis and maturation. Of the ER chaperones, protein disulfide isomerase (PDI)-like proteins are characterized by the presence of a thioredoxin domain and function as oxido-reductases, isomerases and chaperones [33]. ERp29 lacks the active-site double-cysteine (CxxC) motif and does not belong to the redox-active PDIs [5,47]. ERp29 is recognized as a characterized resident of the cellular ER, and it is expressed ubiquitously and abundantly in mammalian tissues [50]. Protein structural analysis showed that ERp29 consists of N-terminal and C-terminal domains [5]: N-terminal domain involves dimerization whereas the C-terminal domain is essential for substrate binding and secretion [78]. The biological function of ERp29 in protein secretion has been well established in cells [8,63,67].

ERp29 is proposed to be involved in the unfolded protein response (UPR) as a factor facilitating transport of synthesized secretory proteins from the ER to Golgi [83]. The expression of ERp29 was demonstrated to be increased in cells exposed to radiation [108], sperm cells undergoing maturation [42,107], and in certain cell types both under the pharmacologically induced UPR and under the physiological conditions (e.g., lactation, differentiation of thyroid cells) [66,82]. Under ER stress, ERp29 translocates the precursor protein p90ATF6 from the ER to Golgi where it is cleaved to be a mature and active form p50ATF by protease (S1P and S2P) [48]. In most cases, ERp29 interacts with BiP/GRP78 to exert its function under ER stress [65].

ERp29 is considered to be a key player in both viral unfolding and secretion [63,67,77,78] Recent studies have also demonstrated that ERp29 is involved in intercellular communication by stabilizing the monomeric gap junction protein connexin43 [27] and trafficking of cystic fibrosis transmembrane conductance regulator to the plasma membrane in cystic fibrosis and non-cystic fibrosis epithelial cells [90]. It was recently reported that ERp29 directs epithelial Na(+) channel (ENaC) toward the Golgi, where it undergoes cleavage during its biogenesis and trafficking to the apical membrane [40]. ERp29 expression protects axotomized neurons from apoptosis and promotes neuronal regeneration [111]. These studies indicate a broad biological function of ERp29 in cells.

Recent studies demonstrated a tumor suppressive function of ERp29 in cancer. It was found that ERp29 expression inhibited tumor formation in mice [4,87] and the level of ERp29 in primary tumors is inversely associated with tumor development in breast, lung and gallbladder cancer [4,29].

However, its expression is also responsible for cancer cell survival against genotoxic stress induced by doxorubicin and radiation [34,76,109]. The most recent studies demonstrate other important roles of ERp29 in cancer cells such as the induction of mesenchymal–epithelial transition (MET) and epithelial morphogenesis [3,4]. MET is considered as an important process of transdifferentiation and restoration of epithelial phenotype during distant metastasis [23,52]. These findings implicate ERp29 in promoting the survival of cancer cells and also metastasis. Hence, the current review focuses on the novel functions of ERp29 and discusses its pathological importance as a “friend or foe” in epithelial cancer.

2. ERp29 regulates mesenchymal–epithelial transition

2.1. Epithelial–mesenchymal transition (EMT) and MET

The EMT is an essential process during embryogenesis [6] and tumor development [43,96]. The pathological conditions such as inflammation, organ fibrosis and cancer progression facilitate EMT [16]. The epithelial cells after undergoing EMT show typical features characterized as: (1) loss of adherens junctions (AJs) and tight junctions (TJs) and apical–basal polarity; (2) cytoskeletal reorganization and distribution; and (3) gain of aggressive phenotype of migration and invasion [98]. Therefore, EMT has been considered to be an important process in cancer progression and its pathological activation during tumor development induces primary tumor cells to metastasize [95]. However, recent studies showed that the EMT status was not unanimously correlated with poorer survival in cancer patients examined [92].

In addition to EMT in epithelial cells, mesenchymal-like cells have capability to regain a fully differentiated epithelial phenotype via the MET [6,35]. The key feature of MET is defined as a process of transdifferentiation of mesenchymal-like cells to polarized epithelial-like cells [23,52] and mediates the establishment of distant metastatic tumors at secondary sites [22]. Recent studies demonstrated that distant metastases in breast cancer expressed an equal or stronger E-cadherin signal than the respective primary tumors and the re-expression of E-cadherin was independent of the E-cadherin status of the primary tumors [58]. Similarly, it was found that E-cadherin is re-expressed in bone metastasis or distant metastatic tumors arising from E-cadherin-negative poorly differentiated primary breast carcinoma [81], or from E-cadherin-low primary tumors [25]. In prostate and bladder cancer cells, the nonmetastatic mesenchymal-like cells were interacted with metastatic epithelial-like cells to accelerate their metastatic colonization [20]. It is, therefore, suggested that the EMT/MET work co-operatively in driving metastasis.

2.2. Molecular regulation of EMT/MET

E-cadherin is considered to be a key molecule that provides the physical structure for both cell–cell attachment and recruitment of signaling complexes [75]. Loss of E-cadherin is a hallmark of EMT [53]. Therefore, characterizing transcriptional regulators of E-cadherin expression during EMT/MET has provided important insights into the molecular mechanisms underlying the loss of cell–cell adhesion and the acquisition of migratory properties during carcinoma progression [73].

Several known signaling pathways, such as those involving transforming growth factor-β (TGF-β), Notch, fibroblast growth factor and Wnt signaling pathways, have been shown to trigger epithelial dedifferentiation and EMT [28,97,110]. These signals repress transcription of epithelial genes, such as those encoding E-cadherin and cytokeratins, or activate transcription programs that facilitate fibroblast-like motility and invasion [73,97].

The involvement of microRNAs (miRNAs) in controlling EMT has been emphasized [11,12,18]. MiRNAs are small non-coding RNAs (∼23 nt) that silence gene expression by pairing to the 3′UTR of target mRNAs to cause their posttranscriptional repression [7]. MiRNAs can be characterized as “mesenchymal miRNA” and “epithelial miRNA” [68]. The “mesenchymal miRNA” plays an oncogenic role by promoting EMT in cancer cells. For instance, the well-known miR-21, miR-103/107 are EMT inducer by repressing Dicer and PTEN [44].

The miR-200 family has been shown to be major “epithelial miRNA” that regulate MET through silencing the EMT-transcriptional inducers ZEB1 and ZEB2 [13,17]. MiRNAs from this family are considered to be predisposing factors for cancer cell metastasis. For instance, the elevated levels of the epithelial miR-200 family in primary breast tumors associate with poorer outcomes and metastasis [57]. These findings support a potential role of “epithelial miRNAs” in MET to promote metastatic colonization [15].

2.3. ERp29 promotes MET in breast cancer

The role of ERp29 in regulating MET has been established in basal-like MDA-MB-231 breast cancer cells. It is known that myosin light chain (MLC) phosphorylation initiates to myosin-driven contraction, leading to reorganization of the actin cytoskeleton and formation of stress fibers [55,56]. ERp29 expression in this type of cells markedly reduced the level of phosphorylated MLC [3]. These results indicate that ERp29 regulates cortical actin formation through a mechanism involved in MLC phosphorylation (Fig. 1). In addition to the phenotypic change, ERp29 expression leads to: expression and membranous localization of epithelial cell marker E-cadherin; expression of epithelial differentiation marker cytokeratin 19; and loss of the mesenchymal cell marker vimentin and fibronectin [3] (Fig. 1). In contrast, knockdown of ERp29 in epithelial MCF-7 cells promotes acquisition of EMT traits including fibroblast-like phenotype, enhanced cell spreading, decreased expression of E-cadherin and increased expression of vimentin [3,4]. These findings further substantiate a role of ERp29 in modulating MET in breast cancer cells.

Fig. 1  ERp29 triggers mesenchymal–epithelial transition. Exogenous expression of ERp29 in mesenchymal MDA-MB-231 breast cancer cells inhibits stress fiber formation by suppressing MLC phosphorylation. In addition, the overexpressed ERp29 decreases the 

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2.4. ERp29 targets E-cadherin transcription repressors

The transcription repressors such as Snai1, Slug, ZEB1/2 and Twist have been considered to be the main regulators for E-cadherin expression [19,26,32]. Mechanistic studies revealed that ERp29 expression significantly down-regulated transcription of these repressors, leading to their reduced nuclear expression in MDA-MB-231 cells [3,4] (Fig. 2). Consistent with this, the extracellular signal-regulated kinase (ERK) pathway which is an important up-stream regulator of Slug and Ets1 was highly inhibited [4]. Apparently, ERp29 up-regulates the expressions of E-cadherin transcription repressors through repressing ERK pathway. Interestingly, ERp29 over-expression in basal-like BT549 cells resulted in incomplete MET and did not significantly affect the mRNA or protein expression of Snai1, ZEB2 and Twist, but increased the protein expression of Slug [3]. The differential regulation of these transcriptional repressors of E-cadherin by ERp29 in these two cell-types may occur in a cell-context-dependent manner.

Fig. 2  ERp29 decreases the expression of EMT inducers to promote MET. Exogenous expression of ERp29 in mesenchymal MDA-MB-231 breast cancer cells suppresses transcription and protein expression of E-cadherin transcription repressors (e.g., ZEB2, SNAI1 and Twist), ..

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2.5. ERp29 antagonizes Wnt/ β-catenin signaling

Wnt proteins are a family of highly conserved secreted cysteine-rich glycoproteins. The Wnt pathway is activated via a binding of a family member to a frizzled receptor (Fzd) and the LDL-Receptor-related protein co-receptor (LRP5/6). There are three different cascades that are activated by Wnt proteins: namely canonical/β-catenin-dependent pathway and two non-canonical/β-catenin-independent pathways that include Wnt/Ca2+ and planar cell polarity [84]. Of note, the Wnt/β-catenin pathway has been extensively studied, due to its important role in cancer initiation and progression [79]. The presence of Wnt promotes formation of a Wnt–Fzd–LRP complex, recruitment of the cytoplasmic protein Disheveled (Dvl) to Fzd and the LRP phosphorylation-dependent recruitment of Axin to the membrane, thereby leading to release of β-catenin from membrane and accumulation in cytoplasm and nuclei. Nuclear β-catenin replaces TLE/Groucho co-repressors and recruits co-activators to activate expression of Wnt target genes. The most important genes regulated are those related to proliferation, such as Cyclin D1 and c-Myc [46,94], which are over-expressed in most β-catenin-dependent tumors. When β-catenin is absent in nucleus, the transcription factors T-cell factor/lymphoid enhancer factors (TCF/LEF) recruits co-repressors of the TLE/Groucho family and function as transcriptional repressors.

β-catenin is highly expressed in the nucleus of mesenchymal MDA-MB-231 cells. ERp29 over-expression in this type of cells led to translocation of nuclear β-catenin to membrane where it forms complex with E-cadherin [3] (Fig. 3). This causes a disruption of β-catenin/TCF/LEF complex and abolishes its transcription activity. Indeed, ERp29 significantly decreased the expression of cyclin D1/D2 [36], one of the downstream targets of activated Wnt/β-catenin signaling [94], indicating an inhibitory effect of ERp29 on this pathway. Meanwhile, expression of ERp29 in this cell type increased the nuclear expression of TCF3, a transcription factor regulating cancer cell differentiation while inhibiting self-renewal of cancer stem cells [102,106]. Hence, ERp29 may play dual functions in mesenchymal MDA-MB-231 breast cancer cells by: (1) suppressing activated Wnt/β-catenin signaling via β-catenin translocation; and (2) promoting cell differentiation via activating TCF3 (Fig. 3). Because β-catenin serves as a signaling hub for the Wnt pathway, it is particularly important to focus on β-catenin as the target of choice in Wnt-driven cancers. Though the mechanism by which ERp29 expression promotes the disassociation of β-catenin/TCF/LEF complex in MDA-MB-231 cells remains elusive, activating ERp29 expression may exert an inhibitory effect on the poorly differentiated, Wnt-driven tumors.

Fig. 3  ERp29 over-expression “turns-off” activated Wnt/β-catenin signaling. In mesenchymal MDA-MB-231 cells, high expression of nuclear β-catenin activates its downstream signaling involved in cell cycles and cancer stem cell 

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3. ERp29 regulates epithelial cell integrity

3.1. Cell adherens and tight junctions

Adherens junctions (AJs) and tight junctions (TJs) are composed of transmembrane proteins that adhere to similar proteins in the adjacent cell [69]. The transmembrane region of the TJs is composed mainly of claudins, tetraspan proteins with two extracellular loops [1]. AJs are mediated by Ca2+-dependent homophilic interactions of cadherins [71] which interact with cytoplasmic catenins that link the cadherin/catenin complex to the actin cytoskeleton [74].

The cytoplasmic domain of claudins in TJs interacts with occludin and several zona occludens proteins (ZO1-3) to form the plaque that associates with the cytoskeleton [99]. The AJs form and maintain intercellular adhesion, whereas the TJs serve as a diffusion barrier for solutes and define the boundary between apical and basolateral membrane domains [21]. The AJs and TJs are required for integrity of the epithelial phenotype, as well as for epithelial cells to function as a tissue [75].

The TJs are closely linked to the proper polarization of cells for the establishment of epithelial architecture[86]. During cancer development, epithelial cells lose the capability to form TJs and correct apico–basal polarity [59]. This subsequently causes the loss of contact inhibition of cell growth [91]. In addition, reduction of ZO-1 and occludin were found to be correlated with poorly defined differentiation, higher metastatic frequency and lower survival rates [49,64]. Hence, TJs proteins have a tumor suppressive function in cancer formation and progression.

3.2. Apical–basal cell polarity

The apical–basal polarity of epithelial cells in an epithelium is characterized by the presence of two specialized plasma membrane domains: namely, the apical surface and basolateral surface [30]. In general, the epithelial cell polarity is determined by three core complexes. These protein complexes include: (1) the partitioning-defective (PAR) complex; (2) the Crumbs (CRB) complex; and (3) the Scribble complex[2,30,45,51]. PAR complex is composed of two scaffold proteins (PAR6 and PAR3) and an atypical protein kinase C (aPKC) and is localized to the apical junction domain for the assembly of TJs [31,39]. The Crumbs complex is formed by the transmembrane protein Crumbs and the cytoplasmic scaffolding proteins such as the homologue of Drosophila Stardust (Pals1) and Pals-associated tight junction protein (Patj) and localizes to the apical [38]. The Scribble complex is comprised of three proteins, Scribble, Disc large (Dlg) and Lethal giant larvae (Lgl) and is localized in the basolateral domain of epithelial cells [100].

Fig. 4  ERp29 regulates epithelial cell morphogenesis. Over-expression of ERp29 in breast cancer cells induces the transition from a mesenchymal-like to epithelial-like phenotype and the restoration of tight junctions and cell polarity. Up-regulation and membrane 

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The current data from breast cancer cells supports the idea that ERp29 can function as a tumor suppressive protein, in terms of suppression of cell growth and primary tumor formation and inhibition of signaling pathways that facilitate EMT. Nevertheless, the significant role of ERp29 in cell survival against drugs, induction of cell differentiation and potential promotion of MET-related metastasis may lead us to re-assess its function in cancer progression, particularly in distant metastasis. Hence, it is important to explore in detail the ERp29’s role in cancer as a “friend or foe” and to elucidate its clinical significance in breast cancer and other epithelial cancers. Targeting ERp29 and/or its downstream molecules might be an alternative molecular therapeutic approach for chemo/radio-resistant metastatic cancer treatment

7.3.5 Putting together structures of epidermal growth factor receptors

Bessman NJ, Freed DM, Lemmon MA
Curr Opin Struct Biol. 2014 Dec; 29:95-101
http://dx.doi.org:/10.1016/j.sbi.2014.10.002

Highlights

Numerous crystal structures have been reported for the isolated extracellular region and tyrosine kinase domain of the epidermal growth factor receptor (EGFR) and its relatives, in different states of activation and bound to a variety of inhibitors used in cancer therapy. The next challenge is to put these structures together accurately in functional models of the intact receptor in its membrane environment. The intact EGFR has been studied using electron microscopy, chemical biology methods, biochemically, and computationally. The distinct approaches yield different impressions about the structural modes of communication between extracellular and intracellular regions. They highlight possible differences between ligands, and also underline the need to understand how the receptor interacts with the membrane itself.

http://ars.els-cdn.com/content/image/1-s2.0-S0959440X14001304-gr1.sml

http://ars.els-cdn.com/content/image/1-s2.0-S0959440X14001304-gr2.sml

Growth factor receptor tyrosine kinases (RTKs) such as the epidermal growth factor receptor (EGFR) have been the subjects of intense study for many years [1,2]. There are 58 RTKs in the deduced human
proteome, and all play key roles in regulating cellular processes such as proliferation, differentiation, cell survival and metabolism, cell migration, and cell cycle control [3].  Importantly, aberrant activation
of RTK signaling by mutation, gene amplification, gene translocation or other mechanisms has been causally linked to cancers, diabetes, inflammation, and other diseases. These observations have prompted
the development of many targeted therapies that inhibit RTKs such as EGFR [4], Kit, VEGFR, or their ligands — typically employing therapeutic antibodies [5] or small molecule tyrosine kinase inhibitors [6].
Following the initial discoveries for EGFR [7] and the platelet-derived growth factor receptor (PDGFR) [8] that ligand-stabilized dimers are essential for RTK signaling, structural studies over the past decade
or so have guided development of quite sophisticated mechanistic views[1]. Each RTK has a ligand-binding extracellular region (ECR) that is linked by a single transmembrane a-helix to an intracellular
tyrosine kinase domain (TKD). Structures of the isolated ECRs and TKDs from several RTKs point to surprising mechanistic diversity across the larger family [1]. Unliganded RTKs exist as an equilibrium
mixture of inactive monomers, inactive dimers and active dimers (Figure 1), except for the extreme case of the insulin receptor (IR), which is covalently dimerized [9]. Extracellular ligand can bind to monomers,
to inactive dimers, or to active dimers — in each case pushing the equilibria shown in Figure 1 towards the central ligand-bound active dimer. Thus, ligand binding can drive receptor dimerization (Figure 1,
upper), or can promote inactive-to-active conformational transitions in dimers (Figure 1, lower). Regardless of pathway, the intracellular TKD of the ligand-stabilized dimer becomes activated either through
trans-autophosphorylation or through induced allosteric changes [1,10]. Roles for other parts of the receptor in RTK activation, including the juxtamembrane (JM) and transmembrane (TM) segments, have
also become clearer. The key current challenge for the field is to assemble data from many studies of isolated RTK parts into coherent views of how the intact receptors are regulated in their native membranes.
We will focus here on recent efforts to do this for the EGFR (or ErbB receptor) family. The missing links in intact RTKs: flexible or rigid? A central goal in extrapolating to the intact RTKs from studies of
isolated soluble domains is to understand how the individual parts of the receptor communicate with one another. The methods that have been used to produce and study the isolated domains inevitably
yield the impression that inter-domain linkers are flexible and disordered. For example, extracellular juxtamembrane regions have typically only been observed as C-terminal extensions of  the soluble ECR.
Similarly, intracellular juxtamembrane regions have been encountered predominantly as N-terminal extensions of TKD constructs, or as short peptides. In each of these contexts, the JM regions are incomplete,
and may appear disordered and flexible simply because key structural restraints have been removed. Nonetheless, this possible artifact has strongly influenced thinking about linkages between the extracellular
and intracellular regions [11], and in turn about mechanisms of RTK signaling. Highly flexible linkages between extracellular and intracellular regions of RTKs are fully consistent with simpler ligand-induced
dimerization models for transmembrane signaling by RTKs. It is more difficult, however, to understand how subtle allosteric communication across the membrane could be achieved if the linkages are truly
flexible. For example, since flexible linkage implies structural independence of the extracellular and intracellular regions, it is difficult to envision how a transition from inactive to active dimer in Figure 1
could be controlled precisely by ligand without more rigid (or restricted) connections.

Recent experimental studies with intact — or nearly intact — EGFR differ in the impressions they provide about how flexibly or rigidly the extracellular and intracellular regions are linked. Springer’s laboratory used cysteine crosslinking and mutagenesis approaches to investigate this issue for EGFR expressed in Ba/F3 cells [12]. They were unable to identify any specific JM or TM region interfaces
that were required for EGFR signaling, leading them to argue that the linkage across the membrane is too flexible to transmit a specific orientation between the extracellular and intracellular regions.
Consistent with this, negative-stain electron microscopy studies of (nearly) full-length EGFR in dodecylmaltoside micelles showed that a given extracellular dimer can be linked to several different
arrangements of the intracellular kinase domain [13,14]. Similarly, dimers driven by inhibitor binding to the intracellular TKD could couple to multiple different ECR conformations [13]. Biochemical
studies are also consistent with such structural independence of the extracellular and intracellular  regions [15,16]. Contrasting with these observations, however, Schepartz and colleagues have
reported that different precise conformations within the EGFR intracellular region can be induced by distinct activating ligands [17]. They used a method called bipartite tetracysteine display that
reports on formation of a chemically detectable tetracysteine motif when two cysteine pairs come together at  the dimer  interface. EGF activation of the receptor led to formation of a  tetracysteine
motif that requires the intracellular JM helix  [18] shown in Figure 2a to form antiparallel coiled-coil dimers  (Figure 2b/c) as proposed by Kuriyan and colleagues [19,20]. Surprisingly, transforming
growth factor-a (TGFa),which also activates EGFR, did not bring these two cysteine pairs together in the same way — arguing that TGFa does not induce formation of the same intracellular antiparallel
coiled-coil. Instead, activation of EGFR with TGFa (but not EGF) stabilized an alternative tetracysteine motif, consistent with a different intracellular JM structure. Evidence for ‘inside-out’ signaling
in EGFR has also been reported, where alterations in the intracellular JM region directly influence allosteric EGF binding to the ECR of the intact receptor analyzed in CHO cells [21–23]. The contradictory
views of flexibility versus rigidity  in linkages between the domains leave the path to understanding the intact receptor unclear, although it seems  reasonable doubt that  the inactive dimers known to
form in the absence of ligand [24–26] could be regulated by extracellular ligand if all linkages are always highly flexible.
Does the membrane hold the key?
All of the studies that support direct conformational communication between the extracellular and intracellular regions of EGFR were performed in cells [17,21,22]. By contrast, most of those that
explicitly suggest otherwise were performed in detergent micelles [13,14,15] — where the potentially important influences of specific membrane lipids (or membrane geometry) are absent. Studies of intact  EGFR in liposomes with defined lipid compositions [27] have shown that the ganglioside GM3 inhibits ligand-independent activation (and dimerization) of the receptor, apparently through interactions with a  site in its extracellular JM region. McLaughlin and colleagues [28,29] also proposed a model in which interaction of the intracellular JM region (and TKD) with anionic phospholipids in the inner leaflet of  the plasma membrane (notably PtdIns(4,5)P2) exerts an inhibitory effect that must be overcome in order for EGFR to signal. Association of the JM and TM regions with specific membrane lipids is likely to  define specific structures in the linkages between the EGFR extracellular and intracellular regions that are more well-defined (and potentially rigid) than is typically appreciated. Recent studies have begun to  shed some structural light on how membrane interactions with the intracellular JM region of EGFR might influence the signaling mechanism. Endres et al. [20] found that simply tethering the complete  intracellular region of EGFR to the inner leaflet of the plasma membrane maintains the TKD in a largely monomeric state and inhibits its kinase activity. Parallel computational studies [30] suggest that this  results from the previously proposed [29] inhibitory interaction of the JM and TKD regions of EGFR with the negatively charged membrane surface. The data of Endres et al. [20] further indicated that TM-mediated dimerization reverses this inhibitory effect. Moreover, NMR studies of a 60-residue peptide containing the TM and part of  the JM region solubilized in lipid bicelles led them to conclude that specific  TM dimerization through an N terminal GxxxG motif stabilizes formation of an antiparallel coiled-coil between the two JM fragments in the dimer — the same JM coiled-coil shown in Figure 2b/c that was  investigated in the bipartite tetracysteine display studies of  intact EGF-bound EGFR described above [17,19]. Independent solid-state NMR studies of a similar TM-JM peptide from the EGFR relative
ErbB2 in vesicles containing acidic phospholipids [31] further suggested that an activating mutation in the TM domain leads to release of  the JM region from the anionic membrane surface. Collectively,
these data suggest that ligand-induced dimerization of the receptor (or reorientation of receptors within a dimer) may engage the TM domain in a specific dimer that promotes both the formation of activating
interactions in the JM region and the disruption of inhibitory interactions between the JM region (and possibly TKD) and the membrane surface.

Negative cooperativity 
A key characteristic of ligand binding at the cell surface to EGFR [36], IR [37], and other receptors [38] is negative cooperativity — which is lost when soluble forms of the ECR from human EGFR [39]
or IR [40] are studied in isolation. Several studies have shown that intracellular and/or transmembrane regions are required for this negative cooperativity to be manifest [21,22,40,41], implying that
these parts of the receptor contribute to breaking the symmetry of the dimer — as required for the two sites to have distinct binding properties [42]. Such propagation of dimer asymmetry across the
membrane would surely require defined structures in the regions that connect extracellular and intracellular regions, and is difficult to reconcile with highly flexible JM linkers.
In brief, binding of one ligand stabilizes a singly-liganded asymmetric dimer in which the unoccupied ligand-binding site is compromised [43]. The binding affinity of the second ligand is thus reduced,
constituting a half-of-the-sites mode of negative cooperativity [44]. Leahy’s group has provided important evidence consistent with a similar mechanism in the cases of human EGFR and ErbB4 [16].
By comparing human ErbB receptor ECR dimer crystal structures with different bound ligands, Leahy and colleagues went on to identify two types of dimer interface [16], a ‘flush’ interface that resembles
the asymmetric (singly-liganded) dimer seen for the Drosophila EGFR [43] and a ‘staggered’ interface seen in the ECRs from EGFR (with bound EGF [12]) and ErbB4 (with bound neuregulin1b[16]).
These observations suggest that the ‘flush’ interface drives the most  stable dimers, which are singly liganded (Figure 2b). Binding of the second ligand is weaker, and also forces the dimer interface
into the less stable ‘staggered’ conformation (Figure 2c). Taken together, these findings suggest both a structural basis for negative cooperativity and a possible structural distinction between singly-liganded
and doubly-liganded ErbB receptor dimers.

A model for EGFR activation
The model shown in Figure 2 summarizes key proposed steps in the activation of human EGFR. In the absence of ligand, the ECR exists in a tethered conformation with the domain II ‘dimerization
arm’ engaged in an intramolecular interaction with domain IV that occludes the dimer interface [49]. The TKDs and the N-terminal portions of each intracellular JM region are thought to be engaged
in autoinhibitory interactions with the membrane surface [20,28,29,30].

Figure 2. More detailed view of EGF-induced activation of EGFR, as described in the text.
In the absence of ligand (a), the ECR adopts a tethered conformation, with an autoinhibitory tether interaction between domains II and IV. The TKD and JM regions lie against the membrane, making what
are believed to be additional autoinhibitory interactions. Domains I and III of the ECR are colored red, and domains II and IV are green. The JM helix is shown as a short cylinder and labeled in magenta.
The N-lobes and C-lobes of the kinase are also labeled, and both helix aC (blue) and the short helix in the activation loop (green) that interacts with aC to inhibit the TKD [50] are shown. The C-tail is
also depicted as a curve bearing 5 tyrosines. As described in the text, binding of a single ligand (b) induces formation of a singly-liganded dimer with a ‘flush’ (presumed asymmetric) ECR dimer interface.
The JM region forms an anti-parallel helix, as labeled in magenta, and the TKDs form an asymmetric dimer in which the activator (grey) allosterically activates the receiver (shown with an amber N-lobe).
It is not clear how the extracellular and intracellular asymmetry is structurally related, if at all. Finally, a second ligand binds to yield a more symmetric dimer with the ‘staggered’ ECR interface (c) described
in the text.

Conclusions Our mechanistic understanding of EGFR and its relatives has advanced dramatically in recent years, and the past year or two has seen substantial progress in putting the results of studies
with isolated domains together into initial views of how the intact receptor works. New insights into the origin of allosteric regulation of EGFR have been gained through a combination of innovative
structural, biochemical, cellular, and computational studies. A self-consistent picture is beginning to emerge. Two key issues remain unclear, however, and represent the current frontiers in studies of EGFR.
The first — for which we describe progress in this review — centers on the influence of specific interactions of the receptor with membrane lipids, which seem likely to define the structural ‘connections’
between extracellular and intracellular regions of the receptor. The second centers on the role of the carboxy-terminal 230 amino acids, which is believed to play a regulatory role for which little detail has
so far been defined [55].
(10PRE4140108).
DMF
is
supported
by

7.3.6 Complex Relationship between Ligand Binding and Dimerization in the Epidermal Growth Factor Receptor

Bessman NJ1Bagchi A2Ferguson KM2Lemmon MA3.
Cell Rep. 2014 Nov 20; 9(4):1306-17.
http://dx.doi.org/10.1016/j.celrep.2014.10.010

Highlights

The epidermal growth factor receptor (EGFR) plays pivotal roles in development and is mutated or overexpressed in several cancers. Despite recent advances, the complex allosteric regulation of EGFR remains incompletely understood. Through efforts to understand why the negative cooperativity observed for intact EGFR is lost in studies of its isolated extracellular region (ECR), we uncovered unexpected relationships between ligand binding and receptor dimerization. The two processes appear to compete. Surprisingly, dimerization does not enhance ligand binding (although ligand binding promotes dimerization). We further show that simply forcing EGFR ECRs into preformed dimers without ligand yields ill-defined, heterogeneous structures. Finally, we demonstrate that extracellular EGFR-activating mutations in glioblastoma enhance ligand-binding affinity without directly promoting EGFR dimerization, suggesting that these oncogenic mutations alter the allosteric linkage between dimerization and ligand binding. Our findings have important implications for understanding how EGFR and its relatives are activated by specific ligands and pathological mutations.

http://www.cell.com/cms/attachment/2020816777/2040986303/fx1.jpg

X-ray crystal structures from 2002 and 2003 (Burgess et al., 2003) yielded the scheme for ligand-induced epidermal growth factor receptor (EGFR) dimerization shown in Figure 1. Binding of a single ligand to domains I and III within the same extracellular region (ECR) stabilizes an “extended” conformation and exposes a dimerization interface in domain II, promoting self-association with a KD in the micromolar range (Burgess et al., 2003, Dawson et al., 2005, Dawson et al., 2007). Although this model satisfyingly explains ligand-induced EGFR dimerization, it fails to capture the complex ligand-binding characteristics seen for cell-surface EGFR, with concave-up Scatchard plots indicating either negative cooperativity (De Meyts, 2008, Macdonald and Pike, 2008) or distinct affinity classes of EGF-binding site with high-affinity sites responsible for EGFR signaling (Defize et al., 1989). This cooperativity or heterogeneity is lost when the ECR from EGFR is studied in isolation, as also described for the insulin receptor (De Meyts, 2008).

Figure 1

Structural View of Ligand-Induced Dimerization of the hEGFR ECR

(A) Surface representation of tethered, unliganded, sEGFR from Protein Data Bank entry 1NQL (Ferguson et al., 2003). Ligand-binding domains I and III are green and cysteine-rich domains II and IV are cyan. The intramolecular domain II/IV tether is circled in red.

(B) Hypothetical model for an extended EGF-bound sEGFR monomer based on SAXS studies of an EGF-bound dimerization-defective sEGFR variant (Dawson et al., 2007) from PDB entry 3NJP (Lu et al., 2012). EGF is blue, and the red boundary represents the primary dimerization interface.

(C) 2:2 (EGF/sEGFR) dimer, from PDB entry 3NJP (Lu et al., 2012), colored as in (B). Dimerization arm contacts are circled in red.

http://www.cell.com/cms/attachment/2020816777/2040986313/gr1.sml

Here, we describe studies of an artificially dimerized ECR from hEGFR that yield useful insight into the heterogeneous nature of preformed ECR dimers and into the origins of negative cooperativity. Our data also argue that extracellular structures induced by ligand binding are not “optimized” for dimerization and conversely that dimerization does not optimize the ligand-binding sites. We also analyzed the effects of oncogenic mutations found in glioblastoma patients (Lee et al., 2006), revealing that they affect allosteric linkage between ligand binding and dimerization rather than simply promoting EGFR dimerization. These studies have important implications for understanding extracellular activating mutations found in EGFR/ErbB family receptors in glioblastoma and other cancers and also for understanding specificity of ligand-induced ErbB receptor heterodimerization

Predimerizing the EGFR ECR Has Modest Effects on EGF Binding

To access preformed dimers of the hEGFR ECR (sEGFR) experimentally, we C-terminally fused (to residue 621 of the mature protein) either a dimerizing Fc domain (creating sEGFR-Fc) or the dimeric leucine zipper from S. cerevisiae GCN4 (creating sEGFR-Zip). Size exclusion chromatography (SEC) and/or sedimentation equilibrium analytical ultracentrifugation (AUC) confirmed that the resulting purified sEGFR fusion proteins are dimeric (Figure S1). To measure KD values for ligand binding to sEGFR-Fc and sEGFR-Zip, we labeled EGF with Alexa-488 and monitored binding in fluorescence anisotropy (FA) assays. As shown in Figure 2A, EGF binds approximately 10-fold more tightly to the dimeric sEGFR-Fc or sEGFR-Zip proteins than to monomeric sEGFR (Table 1). The curves obtained for EGF binding to sEGFR-Fc and sEGFR-Zip showed no signs of negative cooperativity, with sEGFR-Zip actually requiring a Hill coefficient (nH) greater than 1 for a good fit (nH = 1 for both sEGFRWT and sEGFR-Fc). Thus, our initial studies argued that simply dimerizing human sEGFR fails to restore the negatively cooperative ligand binding seen for the intact receptor in cells.

One surprise from these data was that forced sEGFR dimerization has only a modest (≤10-fold) effect on EGF-binding affinity. Under the conditions of the FA experiments, isolated sEGFR (without zipper or Fc fusion) remains monomeric; the FA assay contains just 60 nM EGF, so the maximum concentration of EGF-bound sEGFR is also limited to 60 nM, which is over 20-fold lower than the KD for dimerization of the EGF/sEGFR complex (Dawson et al., 2005, Lemmon et al., 1997). This ≤10-fold difference in affinity for dimeric and monomeric sEGFR seems small in light of the strict dependence of sEGFR dimerization on ligand binding (Dawson et al., 2005,Lax et al., 1991, Lemmon et al., 1997). Unliganded sEGFR does not dimerize detectably even at millimolar concentrations, whereas liganded sEGFR dimerizes with KD ∼1 μM, suggesting that ligand enhances dimerization by at least 104– to 106-fold. Straightforward linkage of dimerization and binding equilibria should stabilize EGF binding to dimeric sEGFR similarly (by 5.5–8.0 kcal/mol). The modest difference in EGF-binding affinity for dimeric and monomeric sEGFR is also significantly smaller than the 40- to 100-fold difference typically reported between high-affinity and low-affinity EGF binding on the cell surface when data are fit to two affinity classes of binding site (Burgess et al., 2003, Magun et al., 1980).

Mutations that Prevent sEGFR Dimerization Do Not Significantly Reduce Ligand-Binding Affinity

The fact that predimerizing sEGFR only modestly increased ligand-binding affinity led us to question the extent to which domain II-mediated sEGFR dimerization is linked to ligand binding. It is typically assumed that the domain II conformation stabilized upon forming the sEGFR dimer in Figure 1C optimizes the domain I and III positions for EGF binding. To test this hypothesis, we introduced a well-characterized pair of domain II mutations into sEGFRs that block dimerization: one at the tip of the dimerization arm (Y251A) and one at its “docking site” on the adjacent molecule in a dimer (R285S). The resulting (Y251A/R285S) mutation abolishes sEGFR dimerization and EGFR signaling (Dawson et al., 2005, Ogiso et al., 2002). Importantly, we chose isothermal titration calorimetry (ITC) for these studies, where all interacting components are free in solution. Previous surface plasmon resonance (SPR) studies have indicated that dimerization-defective sEGFR variants bind immobilized EGF with reduced affinity (Dawson et al., 2005), and we were concerned that this reflects avidity artifacts, where dimeric sEGFR binds more avidly than monomeric sEGFR to sensor chip-immobilized EGF.

Surprisingly, our ITC studies showed that the Y251A/R285S mutation has no significant effect on ligand-binding affinity for sEGFR in solution (Table 1). These experiments employed sEGFR (with no Fc fusion) at 10 μM—ten times higher than KD for dimerization of ligand-saturated WT sEGFR (sEGFRWT) (KD ∼1 μM). Dimerization of sEGFRWT should therefore be complete under these conditions, whereas the Y251A/R285S-mutated variant (sEGFRY251A/R285S) does not dimerize at all (Dawson et al., 2005). The KD value for EGF binding to dimeric sEGFRWT was essentially the same (within 2-fold) as that for sEGFRY251A/R285S (Figures 2B and 2C; Table 1), arguing that the favorable Gibbs free energy (ΔG) of liganded sEGFR dimerization (−5.5 to −8 kcal/mol) does not contribute significantly (<0.4 kcal/mol) to enhanced ligand binding. …

Thermodynamics of EGF Binding to sEGFR-Fc

If there is no discernible positive linkage between sEGFR dimerization and EGF binding, why do sEGFR-Fc and sEGFR-Zip bind EGF ∼10-fold more strongly than wild-type sEGFR? To investigate this, we used ITC to compare EGF binding to sEGFR-Fc and sEGFR-Zip (Figures 3A and 3B ) with binding to isolated (nonfusion) sEGFRWT. As shown in Table 1, the positive (unfavorable) ΔH for EGF binding is further elevated in predimerized sEGFR compared with sEGFRWT, suggesting that enforced dimerization may actually impair ligand/receptor interactions such as hydrogen bonds and salt bridges. The increased ΔH is more than compensated for, however, by a favorable increase in TΔS. This favorable entropic effect may reflect an “ordering” imposed on unliganded sEGFR when it is predimerized, such that it exhibits fewer degrees of freedom compared with monomeric sEGFR. In particular, since EGF binding does induce sEGFR dimerization, it is clear that predimerization will reduce the entropic cost of bringing two sEGFR molecules into a dimer upon ligand binding, possibly underlying this effect.

Possible Heterogeneity of Binding Sites in sEGFR-Fc

Close inspection of EGF/sEGFR-Fc titrations such as that in Figure 3A suggested some heterogeneity of sites, as evidenced by the slope in the early part of the experiment. To investigate this possibility further, we repeated titrations over a range of temperatures. We reasoned that if there are two different types of EGF-binding sites in an sEGFR-Fc dimer, they might have different values for heat capacity change (ΔCp), with differences that might become more evident at higher (or lower) temperatures. Indeed, ΔCp values correlate with the nonpolar surface area buried upon binding (Livingstone et al., 1991), and we know that this differs for the two Spitz-binding sites in the asymmetric Drosophila EGFR dimer (Alvarado et al., 2010). As shown in Figure 3C, the heterogeneity was indeed clearer at higher temperatures for sEGFR-Fc—especially at 25°C and 30°C—suggesting the possible presence of distinct classes of binding sites in the sEGFR-Fc dimer. We were not able to fit the two KD values (or ΔH values) uniquely with any precision because the experiment has insufficient information for unique fitting to a model with four variables. Whereas binding to sEGFRWT could be fit confidently with a single-site binding model throughout the temperature range, enforced sEGFR dimerization (by Fc fusion) creates apparent heterogeneity in binding sites, which may reflect negative cooperativity of the sort seen with dEGFR. …

Ligand Binding Is Required for Well-Defined Dimerization of the EGFR ECR

To investigate the structural nature of the preformed sEGFR-Fc dimer, we used negative stain electron microscopy (EM). We hypothesized that enforced dimerization might cause the unliganded ECR to form the same type of loose domain II-mediated dimer seen in crystals of unliganded Drosophila sEGFR (Alvarado et al., 2009). When bound to ligand (Figure 4A), the Fc-fused ECR clearly formed the characteristic heart-shape dimer seen by crystallography and EM (Lu et al., 2010, Mi et al., 2011). Figure 4B presents a structural model of an Fc-fused liganded sEGFR dimer, and Figure 4C shows a calculated 12 Å resolution projection of this model. The class averages for sEGFR-Fc plus EGF (Figure 4A) closely resemble this model, yielding clear densities for all four receptor domains, arranged as expected for the EGF-induced domain II-mediated back-to-back extracellular dimer shown in Figure 1 (Garrett et al., 2002, Lu et al., 2010). In a subset of classes, the Fc domain also appeared well resolved, indicating that these particular arrangements of the Fc domain relative to the ECR represent highly populated states, with the Fc domains occupying similar positions to those of the kinase domain in detergent-solubilized intact receptors (Mi et al., 2011). …

Our results and those of Lu et al. (2012)) argue that preformed extracellular dimers of hEGFR do not contain a well-defined domain II-mediated interface. Rather, the ECRs in these dimers likely sample a broad range of positions (and possibly conformations). This conclusion argues against recent suggestions that stable unliganded extracellular dimers “disfavor activation in preformed dimers by assuming conformations inconsistent with” productive dimerization of the rest of the receptor (Arkhipov et al., 2013). The ligand-free inactive dimeric ECR species modeled by Arkhipov et al. (2013) in their computational studies of the intact receptor do not appear to be stable. The isolated ECR from EGFR has a very low propensity for self-association without ligand, with KD in the millimolar range (or higher). Moreover, sEGFR does not form a defined structure even when forced to dimerize by Fc fusion. It is therefore difficult to envision how it might assume any particular autoinhibitory dimeric conformation in preformed dimers. …

Extracellular Oncogenic Mutations Observed in Glioblastoma May Alter Linkage between Ligand Binding and sEGFR Dimerization

Missense mutations in the hEGFR ECR were discovered in several human glioblastoma multiforme samples or cell lines and occur in 10%–15% of glioblastoma cases (Brennan et al., 2013, Lee et al., 2006). Several elevate basal receptor phosphorylation and cause EGFR to transform NIH 3T3 cells in the absence of EGF (Lee et al., 2006). Thus, these are constitutively activating oncogenic mutations, although the mutated receptors can be activated further by ligand (Lee et al., 2006, Vivanco et al., 2012). Two of the most commonly mutated sites in glioblastoma, R84 and A265 (R108 and A289 in pro-EGFR), are in domains I and II of the ECR, respectively, and contribute directly in inactive sEGFR to intramolecular interactions between these domains that are thought to be autoinhibitory (Figure 5). Domains I and II become separated from one another in this region upon ligand binding to EGFR (Alvarado et al., 2009), as illustrated in the lower part of Figure 5. Interestingly, analogous mutations in the EGFR relative ErbB3 were also found in colon and gastric cancers (Jaiswal et al., 2013).

We hypothesized that domain I/II interface mutations might activate EGFR by disrupting autoinhibitory interactions between these two domains, possibly promoting a domain II conformation that drives dimerization even in the absence of ligand. In contrast, however, sedimentation equilibrium AUC showed that sEGFR variants harboring R84K, A265D, or A265V mutations all remained completely monomeric in the absence of ligand (Figure 6A) at a concentration of 10 μM, which is similar to that experienced at the cell surface (Lemmon et al., 1997). As with WT sEGFR, however, addition of ligand promoted dimerization of each mutated sEGFR variant, with KD values that were indistinguishable from those of WT. Thus, extracellular EGFR mutations seen in glioblastoma do not simply promote ligand-independent ECR dimerization, consistent with our finding that even dimerized sEGFR-Fc requires ligand binding in order to form the characteristic heart-shaped dimer. …

We suggest that domain I is normally restrained by domain I/II interactions so that its orientation with respect to the ligand is compromised. When the domain I/II interface is weakened with mutations, this effect is mitigated. If this results simply in increased ligand-binding affinity of the monomeric receptor, the biological consequence might be to sensitize cells to lower concentrations of EGF or TGF-α (or other agonists). However, cellular studies of EGFR with glioblastoma-derived mutations (Lee et al., 2006, Vivanco et al., 2012) clearly show ligand-independent activation, arguing that this is not the key mechanism. The domain I/II interface mutations may also reduce restraints on domain II so as to permit dimerization of a small proportion of intact receptor, driven by the documented interactions that promote self-association of the transmembrane, juxtamembrane, and intracellular regions of EGFR (Endres et al., 2013, Lemmon et al., 2014, Red Brewer et al., 2009).

Setting out to test the hypothesis that simply dimerizing the EGFR ECR is sufficient to recover the negative cooperativity lost when it is removed from the intact receptor, we were led to revisit several central assumptions about this receptor. Our findings suggest three main conclusions. First, we find that enforcing dimerization of the hEGFR ECR does not drive formation of a well-defined domain II-mediated dimer that resembles ligand-bound ECRs or the unliganded ECR from Drosophila EGFR. Our EM and SAXS data show that ligand binding is necessary for formation of well-defined heart-shaped domain II-mediated dimers. This result argues that the unliganded extracellular dimers modeled by Arkhipov et al. (2013)) are not stable and that it is improbable that stable conformations of preformed extracellular dimers disfavor receptor activation by assuming conformations that counter activating dimerization of the rest of the receptor. Recent work from the Springer laboratory employing kinase inhibitors to drive dimerization of hEGFR (Lu et al., 2012) also showed that EGF binding is required to form heart-shaped ECR dimers. These findings leave open the question of the nature of the ECR in preformed EGFR dimers but certainly argue that it is unlikely to resemble the crystallographic dimer seen for unligandedDrosophila EGFR (Alvarado et al., 2009) or that suggested by computational studies (Arkhipov et al., 2013).

This result argues that ligand binding is required to permit dimerization but that domain II-mediated dimerization may compromise, rather than enhance, ligand binding. Assuming flexibility in domain II, we suggest that this domain serves to link dimerization and ligand binding allosterically. Optimal ligand binding may stabilize one conformation of domain II in the scheme shown in Figure 1 that is then distorted upon dimerization of the ECR, in turn reducing the strength of interactions with the ligand. Such a mechanism would give the appearance of a lack of positive linkage between ligand binding and ECR dimerization, and a good test of this model would be to determine the high-resolution structure of a liganded sEGFR monomer (which we expect to differ from a half dimer). This model also suggests a mechanism for selective heterodimerization over homodimerization of certain ErbB receptors. If a ligand-bound EGFR monomer has a domain II conformation that heterodimerizes with ErbB2 in preference to forming EGFR homodimers, this could explain several important observations. It could explain reports that ErbB2 is a preferred heterodimerization partner of EGFR (Graus-Porta et al., 1997) and might also explain why EGF binds more tightly to EGFR in cells where it can form heterodimers with ErbB2 than in cells lacking ErbB2, where only EGFR homodimers can form (Li et al., 2012).

7.3.7 IGFBP-2/PTEN: A critical interaction for tumours and for general physiology?

IGFBP-2
The insulin-like growth factor family of proteins, together with insulin, form an evolutionarily conserved system that helps to coordinate the metabolic status and activity of organisms with their nutritional environment. When food is abundant, the IGF/insulin signalling pathway is switched on and cell proliferation and other activities are enhanced; while when food is limited, such activities are suppressed to conserve energy and resources [1,2]. The IGF axis consists of two ligands IGF-I and -II, a series of heterotetrameric tyrosine kinase receptors and six high affinity binding proteins IGFBP-1 to-6. These IGFBPs not only regulate the reservoir, availability and functions of IGFs but also have direct actions upon cell behaviour that are independent of IGF-binding [3]. The six IGFBPs are conserved in all placental mammals having evolved from serial duplication of genes that were present throughout vertebrate evolution [4]. Each of the six IGFBPs has evolved unique functions that presumably have conferred some evolutionary advantage and hence have been conserved across mammalian evolution. After IGFBP-3, IGFBP-2 is the second most abundant binding protein in the circulation throughout adult life in humans. While circulating IGFBP-3 levels peak during puberty and decrease thereafter, IGFBP-2 levels are highest in infancy and old age. Together with the other five IGFBPs, IGFBP-2 regulates IGF availability and actions and has pleiotropic effects on normal and neoplastic tissues [3]. One of the clear distinctive structural features of IGFBP-2 is that it contains an Arg-Gly-Asp (RGD) sequence that enables functional interactions with integrin receptors [4]. This structural element is only present in one of the other IGFBPs, IGFBP-1. Although the RGD sequence was only acquired in IGFBP-1 during mammalian evolution it was present within IGFBP-2 from early vertebrate evolution indicating that it has been a long retained functional characteristic of IGFBP-2 [4]. The integrin receptors are critical for the anchorage of cells to the extracellular matrix (ECM) within tissues and hence for maintaining tissue architecture [5,6]. In solid tissue an important safeguard is imposed by linking normal cell functions and proliferation to appropriate cues from the ECM that are mediated by signals from attachment receptors such as the integrin receptors. Anchoragedependent growth is a common feature of normal cells and loss of attachment results in a form of apoptosis called anoikis. The integrin receptors interact with growth factor receptors in an ancillary and permissive manner to ensure that the signals for growth and survival occur in the appropriate setting and not inappropriately in detached cells. It has also become clear that integrin receptors serve many other roles in regulating cell functions and integrating cues from the surrounding ECM [5,6]. Over the last few decades, as the role of IGFBPs as extracellular modulators of IGF-availability and actions has emerged, there has also been a gradual characterization of the intracellular counter-regulatory components that modulate the signals initiated by IGF-receptor activation. There has been considerable progress in charting the signalling cascades initiated from these receptors but it is evident that the reason needs to be mechanisms for inactivating the pathways in intervening periods in preparation for subsequent activation. Throughout the canonical kinase cascades, activated by receptor ligation, at each node there is a corresponding phosphatase that returns the pathway to the inactive state and modulates the signal. The extracellular regulators of these phosphatases have however received much less attention than the activating kinases. That the extracellular counter-regulators may act in synchrony and be linked to the intracellular counter-regulators has only recently started to be revealed. Transgenic over-expression of IGFBP-2 at supra-physiological levels in mice results in reduced somatic growth [7] and this growth deficit is more pronounced when these mice were crossed with mice with raised growth hormone/IGF-I [8] implying that the growth inhibitory effect was due to sequestration of IGF-I. As with most of the IGFBP-family [3], there are also however multiple lines of evidence that IGFBP-2 has cellular actions that are independent of its ability to bind IGFs. There is evidence that IGFBP-2 initiates intrinsic cellular signalling through specific binding of its RGD-motif to integrin receptors, particularly the α5β1 integrin.In addition IGFBP-2 appears to modulate IGF and epidermal growth factor signalling through interactions with α5β3 integrins [9]. A heparin binding domain also exists in IGFBP-2 and it has been shown to bind to glycosaminoglycans [10], heparin [11], and other proteoglycans such as the receptor protein tyrosine phosphatase-β (RPTPβ) [12,13]. In addition,IGFBP-2has been reported to be localized on the cell surface, in the cytoplasm and on the nuclear membrane[14]. Several groups have now reported nuclear localization of IGFBP-2 [15–17]. A functional nuclear localization sequence in the central domain of IGFBP-2 has been reported that appears to interact with importin-α [18]. In the nucleus IGFBP-2 has been reported to regulate the expression of vascular endothelial growth factor [19].
IGFBP-2 and metabolic regulation
Epidemiological studies of human populations have indicated that IGFBP-2 levels are reduced in obesity, metabolic syndrome and type 2 diabetes and are inversely correlated with insulin sensitivity [20]. That these associations were due to a metabolic role for IGFBP-2, rather thanitjustbeingamarkerofdisturbance,hasbeenconfirmedinanumber of animal models. Using a transgenic IGFBP-2 over-expressing mouse model, Wheatcroft and coworkers found that IGFBP-2 was able to protect mice from high-fat/high-energy induced obesity and insulin resistance, and also protected the mice from the age-related development of glucose intolerance and hypertension [21]. Over-expression of IGFBP-2 induced by Leptin in wild type or obese mice similarly resulted in reduced plasma glucose and insulin levels [22]. All these data indicate a metabolic role for IGFBP-2 in glucose homeostasis.
IGFBP-2 and cancer
As indicated above, the early reports had implied that IGFBP-2 was generally a negative regulator of IGF-activity; the systemic growth restriction observed in transgenic mice over-expressing IGFBP-2 was followed by observations that chemically induced colorectal cancers were inhibited in this model [23]. Despite this there has been an accumulation of evidence indicating that IGFBP-2 is positively associated with the malignant progression of a wide range of cancers, as has been reviewed previously [24]. Raised serum levels of IGFBP-2 have been reported and positive associations between tumor IGFBP-2 expression and malignancy or metastasis have been observed for a variety of cancers, including glioma [25], breast [26], prostate [27], lung [28], colon [29] and lymphoid tumor [30]. Subsequent work has generally been consistent with this association between IGFBP-2 and cancer progression. In view of the majority of evidence, indicating that IGFBP-2 interacting with IGFs generally inhibited cell growth, it was suggested thatIGF-independentactionswereprobablyresponsibleforpositiveassociations between IGFBP-2 and tumourgrowth and progression [24]. The explanation for the increased expression of IGFBP-2 that has beenreportedformanydifferentcancersappearstocomefromthefactorsthat have been shown to regulate IGFBP-2 expression.The tumor suppressor gene p53, which is the most mutated gene in many human cancers, has been reported to transcriptionally regulate IGFBP-2 [31].

There also appears to again be reciprocal feedback as p53 mRNA in the breast cancer cell line Hs578T increased significantly after treatment with human recombinant IGFBP-2, suggesting a close interaction between IGFBP-2 and p53 [14]. A number of hormonal regulators of IGFBP-2 expression have been described including hCG, FSH, TGF-β, IL1, estradiol, glucocorticoids, EGF, IGF-I, IGF-II and insulin [24]. The stimulation of IGFBP-2 expression by EGF, IGF-I, IGF-II and insulin has been shown to be via the PI3K/AKT/mTOR pathway in breast cancer cells [32] and in adipocytes [33]. This is one of the most well characterisedsignallingpathwaysactivatedbyinsulinandIGFs.Inaddition the critical counter-regulatory phosphatase that deactivates this pathway the phosphatase and tensin homologue PTEN has been shown to downregulate the expression of IGFBP-2 [34]. This suggests another autoregulatory loop in which activation of the PI3K/AKT/mTOR pathway by IGFs induces the expression of IGFBP-2 that then sequesters the IGFs and modulates the signal. As activating mutations in the PI3K pathway or loss of PTEN are very common across a variety of human cancers, this plus the effect of p53, probably accounts for the common dysregulation of IGFBP-2 observed across many cancers. Using prostate cancer cell lines it has also been shown that local IGFBP-2 expression is metabolically regulated; IGFBP-2 expression was increased in hyperglycemic conditions through acetylation of histones H3 and H4 associated with the IGFBP-2 promoter, furthermore this up-regulation of IGFBP-2 mediated hyperglycemia-induced chemo-resistance [35].

PI3K
The signaling kinase PI3K plays a fundamental role that has been maintained throughout most of evolution. The ability to control growth and development according to the availability of nutrients provides a survival advantage and therefore has been selectively retained throughout evolution. Evidence has accumulated to indicate that the PI3K pathway provides this control in all species from yeast to mammals.Various forms of the PI3K enzyme exist that are classified into three groups (classes I, II, and III). Only one of these forms is present in yeast and is equivalent to mammalian class III PI3K: this acts as a nutrient sensor and is directly activated by the availability of amino acids and then itself activates mTOR/S6K1 to regulate cell growth and development [36]. In mammals class 1API3K has evolved: this form is not directly activated by nutrients but consists of heterodimers comprising a catalytic p110 subunit and a regulatory p85 subunit that enables the enzyme to be controlled by receptor tyrosine kinases, classically the insulin and insulin-like growth factor receptors (IR and IGF-IR) [37]. This enables the regulation of PI3K by social nutritionally dependent signals rather than by nutrients directly. It is not by chance that the insulin/IGF/PI3K pathway plays a fundamental role in regulating both metabolism and growth as it clearly is an advantage to synchronize the set processes and this synchronized control has been maintained throughout evolution.

Phosphatase and tensin homolog (PTEN)
Of all the intracellular counter-regulators of the IGF-pathway the one that has received the most attention in relation to cancer is PTEN. PTEN is a lipid tyrosine phosphatase that negatively regulates the Akt/ PKB signaling pathway by specifically dephosphorylating phosphatidylinositol (3,4,5)-trisphosphate and thereby reduces AKT activation to reduce signals for cell metabolism, proliferation and survival [37]. PTEN is the second most often mutated tumor suppressor in human cancers, after p53[38]. Aberrant PTEN activity occurs due to mutation, homozygous deletion, loss of heterozygosity, or epigenetic silencing. Lost or reduced activity of PTEN has been observed in a great variety of cancers, including breast [39], prostate [40,41], colorectal [42], lung[43], glioblastoma [44], endometrial [45], etc. It has been demonstrated that deregulation of PTEN is involved in tumorigenesis, tumor progression and also the predisposition of many cancers [46]. AsPI3K/Akt signaling is critical for the metabolic effects of insulin. It is clear that PTEN will also play a role in modulating the metabolic actions of insulin. Consistent with this mice genetically modified to have haploinsufficiency of PTEN were observed to be hypersensitive to insulin [47]. Similarly humans with haplo-insufficiency due to mutations in PTEN were found to have enhanced insulin sensitivity [48]. Recently an increase in insulin sensitivity due to suppression of PTEN has been described in grizzly bears in preparation for hibernation, indicating that this is a mechanism for physiological adaptation [49]. Although the genetic defects resulting in PTEN loss in cancers and the intrinsic mechanisms for regulation of PTEN have been well characterised; there have been relatively few reports of external cell regulators. Of interest one of the few extrinsic regulators that has been described is IGF-II [50]. IGF-II is the most abundant growth factor present in most human tissues and activates the PI3K/AKT/mTOR pathway. Just as the induction of IGFBP-2 by activation of the PI3K pathway suggests an autoregulatory feedback loop extrinsic to the cell;the induction of PTEN by IGF-II via PI3K suggests an additional feedback loop that is intrinsic within the cell (Fig. 1). Activation of the pathway by IGF-II induces expression of PTEN that then attenuates the signal; conversely when the pathway is not activated then PTEN expression is reduced making the cell more responsive for when an activation signal is next received.One of the mechanisms that has emerged,to explain this feedback loop, indicates that the signaling output of the PI3K/PTEN pathway is balanced by asynchronous regulation of the activity of both PI3K and PTEN. The p85α regulatory subunit of PI3K that binds to and represses the activity of the p110 catalytic subunit also binds directly to PTEN at a regulatory site within PTEN where serine/threonine phosphorylation occurs to inactivatePTEN.The p85α subunit binds to unphosphorylated PTEN at this site and enhances its lipid phosphatase activity 3-fold [51]. The nature of this feedback loop has been further extended by reports that PTEN can suppress the expression of IGF-II [52,53]. As IGF-II induces PTEN, the ability of PTEN to subsequently reduce IGF-II expression may enable the cell to protect itself from over-stimulation. In contrast loss of PTEN may increase the expression of IGF-II resulting inactivation of the PI3K/AKT/mTOR pathway that is then unopposed.

PTEN/IGFBP-2 interactions
In view of the recognized importance of loss of PTEN for a variety of cancers there has been considerable interest in identifying biomarkers that could be used clinically to indicate loss of PTEN within tumors. An unbiased screen of human prostate cancer xenografts and human glioblastoma samples using microarray-based expression profiling found that the most significant gene was IGFBP-2 and it was confirmed in experimental models that IGFBP-2 was inversely regulated by PTEN [54]. This was consistent with all of the subsequent studies indicating that the expression of IGFBP-2 was regulated by the PI3K/AKT/mTOR pathway. An increase in tumor IGFBP-2 has also been associated with loss of PTEN in human breast cancer samples[55]. In the same year that a screen revealed IGFBP-2 as the best marker for loss of PTEN; the nature of the interaction between these two proteins was extended by the demonstration that at the cellular level IGFBP-2 can inversely regulate PTEN. With human breast cancer cells it was confirmed that IGF-II stimulated PTEN expression and that this was modulated by the binding of IGF-II to IGFBP-2, but when IGFBP-2 was not bound to IGF-II it was able to suppress PTEN via an interaction with cell surface integrin receptors (Fig. 1) [56]. Subsequent work with human prostate cancer cells indicated that the interaction of IGFBP-2 with integrin receptors could also result in PTEN inactivation via increasing its phosphorylation [57].

Fig.1. A proposed autoregulatory feedback loop of IGFBP-2/PTEN interaction. Binding of IGF-II to the IGF-IR activates the PI3K pathway. Induction of PI3K activates Akt and mTOR signaling and leads to cell proliferation and cell survival. The regulatory subunit of PI3K,p85, also binds and activates PTEN through dephosphorylation. This increased PTEN subsequently blocks IGFII production to avoid overstimulation. On the other hand, activated PI3K pathway induces IGFBP-2 expression, which when unbound to IGF-II, suppresses PTEN via an interaction with integrin receptors and/or the receptor protein tyrosine phosphatase β(RPTPβ). Thus the negative control of PTEN on PI3K signaling is counteracted. These feedback loops enable the extrinsic balance between IGF-II and IGFBP-2 to be tightly integrated to the intrinsic balance between PI3K and PTEN.

The ability of IGFBP-2 to regulate PTEN, originally observed in human cancer cell lines has subsequently been confirmed in a variety of normal cell types from different tissues. In IGFBP-2 knock-out mice a decrease in hematopoietic stem cell survival and cycling has been associated with an increase in PTEN and this appeared to be mediated by the heparin binding domain (HBD) within IGFBP-2 as the administration of a peptide analogue could restore the deficit [58]. Similarly a decrease in bone mass in the IGFBP-2 knock-out mice has been attributed to an increase in PTEN and again the use of a peptide analogue appeared to implicate the IGFBP-2HBD [59]. It was subsequently reported that the IGFBP-2HBD mediated an interaction with the RPTPβ resulting in dimerization and consequent inactivation of RPTPβ and that this reduction in phosphatase activity cooperated with IGF-I activation of the IGF-IR to enhance the phosphorylation and inactivation of PTEN [12]. Recently IGFBP-2 has been reported to also suppress PTEN in human skeletal muscle cells [60] and human visceral adipocytes [61] by interacting with integrin receptors. A similar association between IGFBP-2 and PTEN has been implicated as playing a role in murine skeletal muscle cell differentiation, although the functional regulation was not directly investigated in that study [62].

Summary
Evidence from a variety of different sources have indicated a close regulatory feedback loop between IGFBP-2 and PTEN. Work using a variety of different cell types from different tissues and different species has indicated that IGFBP-2 inversely regulates PTEN. There are reports that this is mediated via the IGFBP-2 RGD domain interacting with integrin receptors and by the IGFBP-2 HBD interacting with proteoglycans; the relative involvement of each of these domains and their functional interactions will require further work to elucidate. These studies however suggest a general mechanism that plays a role in a variety of normal physiological processes in addition to having important implications for the progression of many different cancers. The phosphatase PTEN has an important role in determining insulin sensitivity and the extent that IGFBP-2 exerts a metabolic role in regulating PTEN to determine insulin-sensitivity is yet to be examined. The extracellular balance between IGF-II and IGFBP-2 seems tightly linked with the intracellular balance between PI3K and PTEN (Fig. 1). When driving, in order to move forward there is a synchronous application of the accelerator and a removal of the brake. It appears that the cell also synchronizes activation of an essential regulatory pathway with the removal of the tightly linked inactivation pathway.

References
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7.3.8 Emerging roles for the pH-sensing G protein-coupled receptors in response to acidotic stress

Edward J Sanderlin, Calvin R Justus, Elizabeth A Krewson, Li V Yang
Cell Health & Cytoskel Mar 2015; 2015(7): 99—109
http://www.dovepress.com/emerging-roles-for-the-ph-sensing-g-protein-coupled-receptors-in-respo-peer-reviewed-article-CHC#

Protons (hydrogen ions) are the simplest form of ions universally produced by cellular metabolism including aerobic respiration and glycolysis. Export of protons out of cells by a number of acid transporters is essential to maintain a stable intracellular pH that is critical for normal cell function. Acid products in the tissue interstitium are removed by blood perfusion and excreted from the body through the respiratory and renal systems. However, the pH homeostasis in tissues is frequently disrupted in many pathophysiologic conditions such as in ischemic tissues and tumors where protons are overproduced and blood perfusion is compromised. Consequently, accumulation of protons causes acidosis in the affected tissue. Although acidosis has profound effects on cell function and disease progression, little is known about the molecular mechanisms by which cells sense and respond to acidotic stress. Recently a family of pH-sensing G protein-coupled receptors (GPCRs), including GPR4, GPR65 (TDAG8), and GPR68 (OGR1), has been identified and characterized. These GPCRs can be activated by extracellular acidic pH through the protonation of histidine residues of the receptors. Upon activation by acidosis the pH-sensing GPCRs can transduce several downstream G protein pathways such as the Gs, Gq/11, and G12/13 pathways to regulate cell behavior. Studies have revealed the biological roles of the pH-sensing GPCRs in the immune, cardiovascular, respiratory, renal, skeletal, endocrine, and nervous systems, as well as the involvement of these receptors in a variety of pathological conditions such as cancer, inflammation, pain, and cardiovascular disease. As GPCRs are important drug targets, small molecule modulators of the pH-sensing GPCRs are being developed and evaluated for potential therapeutic applications in disease treatment.

Cellular metabolism produces acid as a byproduct. Metabolism of each glucose molecule by glycolysis generates two pyruvate molecules. Under anaerobic conditions the metabolism of pyruvate results in the production of the glycolytic end product lactic acid, which has a pKa of 3.9. Lactic acid is deprotonated at the carboxyl group and results in one lactate ion and one proton at the physiological pH. Under aerobic conditions pyruvate is converted into acetyl-CoA and CO2 in the mitochondria. CO2in water forms a chemical equilibrium of carbonic acid and bicarbonate, an important physiological pH buffering system. The body must maintain suitable pH for proper physiological functions. Some regulatory mechanisms to control systemic pH are respiration, renal excretion, bone buffering, and metabolism.14 The respiratory system can buffer the blood by excreting carbonic acid as CO2 while the kidney responds to decreased circulatory pH by excreting protons and electrolytes to stabilize the physiological pH. Bone buffering helps maintain systemic pH by Ca2+ reabsorption and mineral dissolution. Collectively, it is clear that several biological systems require tight regulation to maintain pH for normal physiological functions. Cells utilize vast varieties of acid-base transporters for proper pH homeostasis within each biological context.58 Some such transporters are H+-ATPase, Na+/H+exchanger, Na+-dependent HCO3/C1 exchanger, Na+-independent anion exchanger, and monocarboxylate transporters. Cells can also maintain short-term pH homeostasis of the intracellular pH by rapid H+ consuming mechanisms. Some such mechanisms utilize metabolic conversions that move acids from the cytosol into organelles. Despite these cellular mechanisms that tightly maintain proper pH homeostasis, there are many diseases whereby pH homeostasis is disrupted. These pathological conditions are characterized by either local or systemic acidosis. Systemic acidosis can occur from respiratory, renal, and metabolic diseases and septic shock.14,9 Additionally, local acidosis is characterized in ischemic tissues, tumors, and chronically inflamed conditions such as in asthma and arthritis caused by deregulated metabolism and hypoxia.1015

Acidosis is a stress for the cell. The ability of the cell to sense and modulate activity for adaptation to the stressful environment is critical. There are several mechanisms whereby cells sense acidosis and modulate cellular functions to facilitate adaptation. Cells can detect extracellular pH changes by acid sensing ion channels (ASICs) and transient receptor potential (TRP) channels.16 Apart from ASIC and TRP channels, extracellular acidic pH was shown to stimulate inositol polyphosphate formation and calcium efflux.17,18 This suggested the presence of an unknown cell surface receptor that may be activated by a certain functional group, namely the imidazole of a histidine residue. The identity of the acid-activated receptor was later unmasked by Ludwig et al as a family of proton-sensing G protein-coupled receptors (GPCRs). This group identified human ovarian cancer GPCR 1 (OGR1) which upon activation will produce inositol phosphate and calcium efflux through the Gq pathway.19 These pH-sensing GPCR family members, including GPR4, GPR65 (TDAG8), and GPR68 (OGR1), will be discussed in this review (Figure 1). The proton-sensing GPCRs sense extracellular pH by protonation of several histidine residues on their extracellular domain. The activation of these proton-sensing GPCRs facilitates the downstream signaling through the Gq/11, Gs, and G12/13 pathways. Their expression varies in different cell types and play critical roles in sensing extracellular acidity and modulating cellular functions in several biological systems.

Figure 1 Biological roles and G protein coupling of the pH-sensing GPCRs.
Abbreviation: GPCRs, G protein-coupled receptors.

Role for the pH-sensing GPCRs in the immune system and inflammation

Acidic pH is a main characteristic of the inflammatory loci.14,20,21 The acidic microenvironment in inflamed tissue is predominately due to the increased metabolic demand from infiltrating immune cells, such as the neutrophil. These immune cells increase oxygen consumption and glucose uptake for glycolysis and oxidative phosphorylation. When oxygen availability is limited, cells often undergo anaerobic glycolysis. This process generates increasing amounts of lactic acid, thereby creating a local acidic microenvironment within the inflammatory loci.22 This presents a role for the pH-sensing GPCR GPR65 (TDAG8) in inflammation and immune cell function.23 TDAG8 was originally identified by cloning as an orphan GPCR which was observed to be upregulated during thymocyte apoptosis.24,25GPR65 (TDAG8) is predominately expressed in lymphoid tissues such as the spleen, lymph nodes, thymus, and leukocytes.2426 It was demonstrated that GPR65 inhibited pro-inflammatory cytokine secretion, which includes IL-6 and TNF-α, in mouse peritoneal macrophages upon activation by extracellular acidification. This cytokine inhibition was shown to occur through the Gs-cAMP-protein kinase A (PKA) signaling pathway.23,27 Treatment with dexamethasone, a potent glucocorticoid, increased GPR65 expression in peritoneal macrophages. Following dexamethasone treatment, there was an inhibition of TNF-α secretion in a manner dependent on increased expression of GPR65.28Another report provides an anti-inflammatory role for GPR65 in arthritis.29 Type II collagen-induced arthritis was increased in GPR65-null mice in comparison to wild-type mice. These studies taken together suggest GPR65 serves as a negative regulator in inflammation.30 However, one study provided a function for GPR65 as a positive modulator in inflammation.31 GPR65 was reported to increase eosinophil viability in the acidic microenvironment by reducing apoptosis through the cAMP pathway. As eosinophils are central in asthmatic inflammation and allergic airway disease, GPR65 may play a role in increasing asthmatic inflammation.31 On the other hand, GPR65 has shown little involvement in immune cell development. One report indicates that GPR65 knockout mice had normal immune development and function.26 Modulation of inflammation by GPR65 is complex and must be examined within each specific pathology.23

In addition to GPR65, GPR4 is also involved in the inflammatory response. Endothelial cells compose blood vessels that often penetrate acidic tissue microenvironments such as the inflammatory loci. Among the pH-sensing GPCR family, GPR4 has the highest expression in endothelial cells. Response to inflammation by vascular endothelial cells facilitates the induction of inflammatory cytokines that are involved in the recruitment of leukocytes for adherence and transmigration into inflamed tissues. Activation of GPR4 by acidosis in human umbilical vein endothelial cells, among other endothelial cell types, increased the expression of a broad range of pro-inflammatory genes including chemokines, cytokines, PTGS2, NF-κB pathway genes, and adhesion molecules.32 Moreover, human umbilical vein endothelial cells, when treated with acidic pH, increased GPR4-mediated endothelial adhesion to leukocytes.32,33 Altogether, GPR65 and GPR4 provide differential regulation of the inflammatory response through their acid sensing capabilities. GPR65 predominately demonstrates function in the inhibition of the inflammatory response whereas GPR4 activation exacerbates inflammation.

Role for the pH-sensing GPCRs in the cardiovascular system

Taken together, both GPR4 and GPR68 play roles in regulating the function of the cardiovascular system. GPR4 regulates blood vessel stability and endothelial cell function and GPR68 increases cardiomyogenic and pro-survival gene expression while also mediating aortic smooth muscle cell gene expression.

Role for the pH-sensing GPCRs in the renal system

GPR4 is expressed in the kidney cortex, isolated kidney collecting ducts, inner and outer medulla, and in cultured inner and outer medullary collecting duct cells.59 In mice deficient for GPR4, renal acid excretion and the ability to respond to metabolic acidosis was reduced.59 In response to acidosis, inner and outer medullary collecting duct cells produced cAMP, a second messenger for the Gs G-protein pathway, through the GPR4 receptor.59 In renal HEK293 epithelial cells GPR4 overexpression was found to increase the activity of PKA.60 In addition, the protein expression of H+-K+-ATPase α-subunit (HKα2) was increased following GPR4 overexpression dependent on increased PKA activity.60

GPR68 has also been reported to alter proton export of HEK293 cells by stimulating the Na+/H+exchanger and H+-ATPase.58 The activation of GPR68 by acidosis was found to stimulate this effect through a cluster of extracellular histidine residues and the Gq/PKC signaling pathway.58 In GPR68-null mice the expression of the pH-sensitive kinase Pyk2 in the kidney proximal tubules was upregulated which might compensate for GPR68 deficiency.58 Taken together, GPR4 and GPR68 may both be necessary for successful systemic pH buffering by controlling renal acid excretion.

Role for the pH-sensing GPCRs in the respiratory system

Aoki et al demonstrated that GPR68-deficient mice were resistant to asthma along with inhibiting Th2 cytokine and immunoglobulin E production.68 This study concludes that GPR68 in dendritic cells is crucial for the onset of asthmatic responses.68 Moreover, GPR65 has been implicated as having a role in respiratory disorders as it is highly expressed in eosinophils, hallmark cells for asthmatic inflammation.69 Kottyan et al showed that GPR65 increased the viability of eosinophils within an acidic environment through the cAMP pathway in murine asthma models.31 In summary, GPR68 and GPR65 play important roles in the respiratory system and asthma. GPR68 regulates gene expression in airway epithelial, smooth muscle and immune cells while GPR65 enhances the survival of airway eosinophils in response to acidosis.

Role for the pH-sensing GPCRs in the skeletal system

GPR65 has also been reported as a pH sensor in bone. GPR65 is expressed in osteoclasts and its activity may inhibit Ca2+ resorption.81 Disruption of GPR65 gene exacerbated osteoclastic bone resorption in ovariectomized mice.81 The relative bone density of GPR65-null mice was less than control mice.81 In cultured osteoclast cells from mice deficient for GPR65, the normal inhibition of osteoclast formation in response to acidosis was abrogated.81 Taken together, this data suggest that the activation of GPR65 may enhance bone density, thus the GPR65 signaling may be important for disease processes such as osteoporosis and other bone density disorders.

Role for the pH-sensing GPCRs in the endocrine system

GPR68 has also been found to modify insulin production and secretion. In GPR68 knockout mice insulin secretion in response to glucose administration was reduced when compared to wild-type mice although blood glucose was not significantly altered.84 GPR68 deficiency in this respect may reduce insulin secretion but at the same time increase insulin sensitivity. In addition, stimulation of GPR68 in islet cells by acidosis increased the secretion of insulin through the Gq/11 G-protein signaling.84

Role for the pH-sensing GPCRs in the nervous system and nociception

Acidosis causes pain by exciting nociceptors located in sensory neurons. Several types of ion channels and receptors, such as ASICs, TRPV1, and proton-sensing GPCRs, have been identified as nociceptors in response to acidosis. ASICs and TRPV act as proton-gated membrane-bound channels, which are activated by acidic pH and mediate multimodal sensory perception including nociception.8688  GPR65 activation sensitized the response of TRPV1 to capsaicin. The results suggest high accumulation of protons post inflammation may not only stimulate nociceptive ion channels such as TRPV1 to trigger pain, but also activate proton-sensing GPCRs to regulate heightened sensitivity to pain.89 Furthermore, Hang et al demonstrated GPR65 activation elicited cancer-related bone pain through the PKA and phosphorylated CREB (pCREB) signaling pathway in the rat model.90 Collectively, GPR4, GPR65, and GPR68 are all expressed in the dorsal root ganglia; GPR65 is a functional receptor involved in nociception and the nervous system by sensitizing inflammatory pain and the evocation of cancer-related bone pain.

Role for the pH-sensing GPCRs in tumor biology

The tumor microenvironment is highly heterogeneous. Hypoxia, acidosis, inflammation, defective vasculature, poor blood perfusion, and deregulated cancer cell metabolism are hallmarks of the tumor microenvironment.9193 The acidity in the tumor microenvironment is owing to the altered cancer cell metabolism termed the “Warburg Effect”. This metabolic phenotype allows the cancer cells to preferentially utilize glycolysis over oxidative phosphorylation as a primary means of energy production.94 This process occurs even in normoxic tissue environments where sufficient oxygen is available. Due to this phenomenon, the Warburg Effect is often termed “aerobic glycolysis”. This unique metabolic phenotype produces vast quantities of lactic acid, which serve as a proton source for acidification. Upon disassociation of lactic acid to one lactate molecule and one proton, the monocarboxylate transporter and proton transporters export lactate and protons into the extracellular tumor microenvironment.95 The proton-sensing GPCRs are activated by acidic pH and facilitate tumor cell modulation in response to extracellular acidification. GPR4, GPR65, and GPR68 play roles in tumor cell apoptosis, proliferation, metastasis, angiogenesis, and immune cell function.19,27,32,33,44,45,96,97

GPR4 has had conflicting reports in terms of tumor suppressing or promoting activities. One study demonstrated that GPR4 could act as a tumor metastasis suppressor, when overexpressed and activated by acidic pH in B16F10 melanoma cells, by impeding migration and invasion of tumor cells.45 GPR4 overexpression also significantly inhibited the lung metastasis of B16F10 melanoma cells in mice.45 Another study utilizing the B16F10 melanoma cell line which overexpressed GPR4 showed an increase in mitochondrial surface area and a significant reduction in membrane protrusions by quantification of 3D morphology.98 These data point to a decrease in cancer cell migration when GPR4 is overexpressed and provides another example of GPR4 as exhibiting tumor metastasis suppressor function.98 However, in another report GPR4 malignantly transformed immortalized NIH3T3 fibroblasts.99 This presents GPR4 with tumor-promoting capabilities. The conflicting reports seem to indicate the functional ability of GPR4 to act as a tumor promoter and a tumor suppressor depending on the context of certain cell types and biological systems.

Reports with GPR65 involvement in cancer cells provide evidence in favor for cancer cell survival; however, opposing evidences suggest GPR65 functions as a tumor suppressor. In the same report suggesting GPR4 is oncogenic due to GPR4 transforming immortalized NIH3T3 fibroblasts, GPR65 overexpression was able to transform the mouse NMuMG mammary epithelial cell line.99 Another group demonstrated in NCI-H460 human non-small cell lung cancer cells that GPR65 promotes cancer cell survival in an acidic microenvironment.100 Conversely, a recent study showed that GPR65 inhibited c-Myc oncogene expression in human lymphoma cells.101 Furthermore, GPR65 messenger ribonucleic acid expression was reduced by more than 50% in a variety of human lymphoma samples when compared to normal lymphoid tissues, therefore implying GPR65 has a tumor suppressor function in lymphoma.101 GPR65 has also been shown to increase glucocorticoid-induced apoptosis in murine lymphoma cells.102 These reports highlight cell type dependency and biological context for GPR65 activity as a tumor suppressor or promoter.

GPR68 also has roles in tumor biology as a potential tumor suppressor or a tumor promoter. Reports have shown that GPR68 can inhibit cancer metastasis, reduce cancer cell proliferation, and inhibit migration. One study showed that when GPR68 was overexpressed in prostate cancer cells, metastasis to the lungs, diaphragm, and spleen was inhibited.97 When GPR68 was overexpressed in ovarian cancer (HEY) cells, cellular proliferation and migration were significantly reduced, and cell adhesion to the extracellular matrix was increased.96 Another study reported GPR68 expression was critical for the tumor cell induced immunosuppression in myeloid-derived cells. This study proposed that GPR68 promotes M2 macrophage development and inhibits T-cell infiltration, and thereby facilitates tumor development.103 In summary, the biological roles of GPR4, GPR65, and GPR68 in tumor biology are complex and both tumor-suppressing and tumor-promoting functions have been reported, primarily dependent on cell type and biological milieu.

Development of small molecule modulators of the pH-sensing GPCRs

GPCRs are critical receptors for the regulation of many physiological operations. It is of little surprise that GPCRs have become a central focus of pharmaceutical development. In fact, 30%–50% of therapeutics focuses on modulating GPCR activity.104,105 In view of the diverse roles of the pH-sensing GPCRs in the context of multiple biological systems, targeting these receptors with small molecules and other modulators could serve as potential therapeutics for diseases associated with deregulated pH homeostasis. There have been recent developments in the characterization of GPR4 antagonists along with agonists for GPR65 and GPR68.29,32,50,106 The GPR4 antagonist demonstrated effectiveness in vitro to reduce the GPR4-mediated inflammatory response to acidosis in endothelial cells.32 The GPR65 agonist, BTB09089, showed in vitro effects in GPR65 activation of immune cells to inhibit inflammatory response; however, the activity of BTB09089 was not strong enough for the use in animal models in vivo.29 The GPR68 agonist, lsx, exhibited pro-neurogenic activity and induced hippocampal neurogenesis in young mice.107 It was also demonstrated that lsx suppressed the proliferation of malignant astrocytes.108 To date, however, much advancement needs to be done in development of efficacious agonists and antagonists of the pH-sensing GPCRs coupled with a capacity to target specific tissue dysfunction in the midst of systemic drug administration to optimize therapeutic effects and minimize potential adverse effects.

Concluding remarks

Cells encounter acidotic stress in many pathophysiologic conditions such as inflammation, cancer, and ischemia. Intricate molecular mechanisms, including a large array of acid/base transporters and acid sensors, have evolved for cells to sense and respond to acidotic stress. Emerging evidence has demonstrated that a family of the pH-sensing GPCRs can be activated by extracellular acidotic stress and regulate the function of multiple physiological systems (Table 1). The pH-sensing GPCRs also play important roles in various pathological disorders. Agonists, antagonists and other modulators of the pH-sensing GPCRs are being actively developed and evaluated as potential novel treatment for acidosis-related diseases.

Table 1 The main biological functions of the pH-sensing GPCRs

7.3.9 Protein amino-terminal modifications and proteomic approaches for N-terminal profiling

Lai ZW1, Petrera A2, Schilling O3.
Curr Opin Chem Biol. 2015 Feb; 24:71-9
http://dx.doi.org:/10.1016/j.cbpa.2014.10.026

Amino-/N-terminal processing is a crucial post-translational modification affecting almost all proteins. In addition to altering the chemical properties of the N-terminus, these modifications affect protein activation, conversion, and degradation, which subsequently lead to diversified biological functions. The study of N-terminal modifications is of increasing interest; especially since modifications such as proteolytic truncation or pyroglutamate formation have been linked to disease processes. During the past decade, mass spectrometry has played an important role in facilitating the investigation of N-terminal modifications. Continuous progress is being made in the development and application of robust methods for the dedicated analysis of native and modified protein N-termini in a proteome-wide manner. Here we highlight recent progress in our understanding of protein N-terminal biology as well as outlining present enrichment strategies for mass spectrometry-based studies of protein N-termini.

Highlights

    • N-terminal acetylation, pyroglutamate formation, N-degrons and proteolysis are reviewed.• N-terminomics provide comprehensive profiling of modification at protein N-termini in a proteome-wide manner.• We outline a number of established methodologies for the enrichment of protein N-termini through positive and negative selection strategies.• Peptidomics-based approach is beneficial for the study of post-translational processing of protein N-termini.

 Introduction The life of every protein begins at the amino-terminus, also known as the N-terminus. During the initiation of mRNA translation into proteins or polypeptides, newly synthesized amino
acid chains form the N-termini and are the first to exit the ribosomes into the cytosol or the endoplasmic reticulum. The N-termini of these proteins or protein precursors often contain a signaling peptide
sequence proximal to the N-terminus, which may function as a ‘zip-code’ to direct the delivery of a protein to a cellular compartment as well as orchestrating protein maturation via different post-translational
modifications (PTMs) such as acetylation or proteolysis. These modifications often determine protein activity or stability; thus being crucial for the tight regulation of cellular homeostasis (Figure 1).
Mass spectrometry (MS) based analyses of protein N-termini, termed N-terminomics, is a promising tool to tackle these problems. In the past decade, we have witnessed significant progress in the
area of mass spectrometric investigation of post-translational modifications such as phosphorylation or glycosylation [1].  Similarly, MS-based studies of protein N-termini are gaining momentum.
Recent progress in positional proteomics using advanced MS platforms combined with a number of effective enrichment strategies has reinforced significant interest in N-terminomics.
Here we outline some of the most current highlights on proteomics-based studies on N-terminal modifications, including N-acetylation, pyroglutamate formation, proteolysis, and N-terminal degrons
(Figure 2). We also present a number of recent N-terminomic methodologies for the study of protein N-termini.

Acetylation of protein N-termini represents an abundant post-translational modification in eukaryotes, affecting nearly all cytoplasmic proteins. This  modification is catalyzed by the N-terminal
acetyltransferase (Nat) enzyme complex, which transfers an acetyl group to the N-termini of newly synthesized proteins during translation (Figure 2). Initial findings highlighted that N-terminal
acetylation protects proteins from degradation [2–4]. Recent studies however yield a more diverse picture. N-terminal acetylation may also play a role in protein delivery and localization [5–7],
protein complex formation and generation of specific degradation signals in cellular proteins via the N-degron pathway [9,10]. Loss of N-terminal acetylation through inactive acetyltransferases leads to
smaller aggregates of prion proteins [11]. In addition, N-terminal acetyltransferases have been described to also function as N-terminal proprionyltransferases [12].  Genetic mutation in the Naa10 gene,
encoding the NatA catalytic subunit, is known to cause N-terminal acetyltransferase deficient phenotypes. This genetic mutation has also been linked to X-linked disorder of infancy, causing lethality in
male infants[13]. The multifunctional roles of N-acetyltransferases as well as the importance of  N-terminal acetylation have been previously reviewed in [14]. Few MS-based studies have emerged that
specifically investigate acetylated N-termini in a proteome wide manner. The structural and functional integrity of actomyosin fibers depends on active NatB. A novel methodology determines the
extent of N-terminal acetylation in vivo through chemical, stable-isotope coded acetylation of proteins before their mass spectrometric analysis [16].

Pyroglutamate conversion of N-terminal glutamate and glutamine Many proteins and biologically active peptides exhibit an N-terminal pyroglutamic acid (pGlu) residue. This post
translational modification originates from the conversion of N-terminal glutamate and glutamine into pyroglutamic acid by glutaminyl cyclase or isoglutaminyl cyclase (Figure 2). N-terminal
pGlu influences structural stability as well as biological activity of peptides and proteins [17]. pGlu protects proteins from degradation by aminopeptidases [18] as well as regulating the
biological activity of peptide hormones, neuropeptides or chemokines [19]. Examples include thyrotropin releasing hormone (TRH), gonadotropin-releasing hormone, and the human
chemokines MCP-1 and 2. The presence of N-terminal pGlu in some amyloidogenic peptides, such as amyloid-b peptides, increases their hydrophobicity, resulting in an accelerated
aggregation [20]. Modulating the extent of N-terminal pGlu formation through pharmaceutical inhibition of glutaminyl cyclase is considered a promising strategy, for example, to
increase the degradation of inflammatory and neurotoxic peptides. Inhibition of glutaminyl cyclase has alleviated liver inflammation by destabilizing the chemokine MCP1 (CCL2) [21].
Proteolytic degradation of this promigratory chemokine by inhibiting glutaminyl cyclase was also proposed as an attractive novel strategy in preventing thyroid cancer metastasis [22].
Given the functional relevance of N-terminal pGlu in pathological conditions, an MS-based approach to profile this modification may be particularly useful.

N-terminal degrons N-terminal residues have a strong impact on protein stability and half-life. Firstly described in 1986 by Varshavsky and colleagues [25], the N-end rule pathway
has been identified in a broad range of species, from mammals to bacteria, and from yeast to plants [26]. This control of protein degradation in eukaryotes and bacteria is governed
by the formation and recognition of specific sequences at protein N-termini, called N-degrons. The main determinant of an N-degron is an N-terminal destabilizing residue. In eukaryotes,
two N-end rule pathways are being distinguished: the Ac/N-end rule pathway targets proteins through their N-terminally acetylated residues while the Arg/N-rule pathway targets
unacetylated N-terminal residues and involves N-terminal arginylation [26]. Proteolytic processing leading to new protein N-termini is increasingly recognized to play an important
role in the formation of N-degrons. In eukaryotes, N-degron mediated protein degradation occurs through the  ubiquitin–proteasome system. N degrons are recognized by E3
ubiquitin ligases called N-recognins, which induce protein ubiquitylation. Recent studies showed that the N-end rule pathway can be regulated by various mechanisms [26].
Hemin, the ferric (Fe3+) counterpart of heme, and short peptides can bind to components of the N-end rule pathway and impede their functionality [26]. Although the N-end rule
pathway has been molecularly dissected in great detail, numbers of identified physiological substrates undergoing N-end rule degradation have remained limited. A recent study
has expanded the range of substrates targeted by the Arg/N-end rule. Kim and colleagues have shown that N terminal Met followed by a hydrophobic residue functions as an N-degron
[27]. N-terminal Met followed by a small residue is typically removed by aminopeptidases in a cotranslational manner (Figure 2). However, approximately 15% of the genes in mammals
or yeast encode for an N-terminal Met followed by a larger hydrophobic residue. This specific N-degron is targeted by the Ac/N-end rule pathway when the N-terminal Met is acetylated.
The Arg/N-end rule acts instead on the non-acetylated N-terminal Met. As previously mentioned, novel N-degrons can be generated by preceding proteolysis. Piatkov and colleagues
investigated this concept for proteolytic cleavage products that occur during apoptosis [28]. They find that numerous proapoptotic fragments are short lived substrates of Arg/N-end
rule pathway, attributing to this pathway an anti-apoptotic role. Notably, the corresponding N-degron sequences are evolutionary conserved.

Figure 1 Protein N-termini are susceptible to various post-translational modification.
For a more comprehensive overview of all possible N terminal modification, see [60].

Figure 2 Examples of N-terminal mofications: acetylation, pyroglutamate conversion, proteolysis and N-degron processing via deamidation and amino acid conjugation.

Proteolytic processing of N-termini Proteolysis has long been regarded a degradation process. It is now increasingly recognized as an important posttranslational modification
with an array of proteases mediating cellular signaling via the precise processing of bioactive proteins and peptides. The study of cleavage events using N-terminomics is particularly
useful for the identification of proteolytic substrates. Proteolytic cleavage of proteins and polypeptides results in the generation of cleavage fragments with new N-termini and
C-termini. Numerous recent proteomic studies highlighted differential regulation of proteases in different disease settings. MALDI-TOF in combination with enzymatic assays
established reduced levels of dipeptidyl-peptidase (DPP)4 in the serum of patients suffering from metastatic prostate cancer [31]. Another proteomic based study,  using isotope
coded affinity tag (ICAT) labeling showed bacterial leucine aminopeptidase from Plasmodium chabaudi to be significantly upregulated in periodontal disease [32]. Mass spectrometry
was also used for the functional characterization of proteases.

7.3.10 Protein homeostasis networks in physiology and disease

Although most text books of biochemistry describe the process of protein folding to a three dimensional native state as an intrinsic property of the primary sequence, it is becoming increasingly clear that this process can go wrong in an almost infinite number of ways. In fact, many different diseases are caused by the misfolding and aggregation of certain proteins without genetic mutations in the primary sequence. An integrative view of the mechanisms that maintain protein folding homeostasis is emerging, which could be thought as a balanced and dynamic network of interconnected processes tightly regulated by a series of quality control mechanisms. This protein homeostasis network involves families of folding catalysts, co-factors under specific environmental and metabolic conditions. Maintaining protein homeostasis is particularly challenging in specialized secretory cells where the high demand for protein synthesis generates a constant source of stress that could lead to proteotoxicity.

Protein folding is assisted and monitored by diverse interconnected processes that follow a sequential pattern over time. The calnexin/calreticulin cycle ensures the proper folding of glycosylated proteins through the secretory pathway, which establishes the final pattern of disulfide bond formation through interactions with the disulfide isomerase ERp57. Coupled to this cycle is the ER-associated degradation (ERAD) pathway, which translocates terminally misfolded proteins to the cytosol for degradation by proteasomes. In addition, macroautophagy is becoming a relevant mechanism for the clearance of damaged proteins and abnormal protein aggregates through lysosomal hydrolysis, a process also referred to as ERAD-II. The folding status at the ER is constantly monitored by the Unfolded Protein Response (UPR), a specialized signaling pathway initiated by the activation of three types of stress sensors. The process underlying the surveillance of protein folding stress by the UPR is not fully understood, but it may require coupling to key folding mediators such as BiP or the direct recognition of the misfolded peptides by stress sensors. The UPR regulates genes and processs related to almost every folding step in the secretory pathway to reduce the load of misfolded proteins, including protein translation into the ER, translocation, folding, quality control, ERAD, the redox status, and many other related functions. Protein folding stress is observed in many disease conditions such as cancer, diabetes, and neurodegeneration. For example, abnormal protein aggregation and the accumulation of protein inclusions is associated with Parkinson’s and Alzheimer’s Disease, and amyotrophic lateral sclerosis. In those diseases and many others, neuronal dysfunction and disease progression correlates with the presence of a strong ER stress response; however, the direct in vivo role of the UPR in the disease process has been experimentally defined in only a few cases. Therapeutic strategies are currently being developed to increase protein folding and clearance of misfolded proteins, with the goal of alleviating ER stress.

In this issue of Current Opinion in Cell Biology we present a series of focused reviews from recognized experts in the field, that provide an overview of mechanisms underlying protein folding and quality control, and how balance of protein homeostasis is maintained in physiology and deregulated in diseases. Daniela Roth and William Balch integrate the concept of protein homeostasis networks into an interesting model termed FoldFx, showing how the interconnection between different pathways in the context of the cellular proteome determines the energetic barrier required to generate a functional folded peptide. The authors have previously proposed the term Proteostasis to refer to the set of interacting activities that maintain the health of the proteome and the organism (protein homeostasis). The ER is a central subcellular compartment for protein synthesis and quality control in the secretory pathway. Yukio Kimata and Kenji Kohno give an overview of the signaling pathways that control adaptation to ER stress and maintenance of protein folding homeostasis. The authors summarize the models proposed so far for the activation of UPR stress sensors, and discuss how this directly or indirectly relates to the accumulation of unfolded proteins in the ER lumen. Chronic or irreversible ER stress triggers cell death by apoptosis. Gordon Shore, Feroz Papa, and Scott Oakes summarize the complex signaling pathways initiating apoptosis by ER stress, where cross talk between the ER and the mitochondria play a central role. The authors focus on addressing the role of the BCL-2 protein family on the activation of intrinsic mitochondrial apoptosis pathways, highlighting different cytosolic and transcriptional events that determine the transition between adaptive responses to apoptosis programmed by the UPR to eliminate irreversibly injured cells.

Although diverse families of chaperones, foldases and co-factors are expressed at the ER, only a few protein folding networks have been well defined. However, molecular explanations for specific substrate recognition and quality control mechanisms are poorly defined. Here we present a series of reviews covering different aspects of protein maturation. Amy Lee summarizes what is known about the biology of the key ER folding chaperone BiP/Grp78, and its emerging role in diverse pathological conditions including cancer. In two reviews, David B. Williams and Linda M. Hendershot describe the best characterized mechanism of protein quality control at the ER, the calnexin cycle. In addition, they give an overview of the function of a family of ER foldases, the protein disulfide isomerases (PDIs), in folding, quality control and degradation of abnormally folded proteins. PDIs are also becoming key factors in establishing the redox tone of the ER. Riccardo Bernasconi and Maurizio Molinari overview the ERAD process and how this pathway affects the efficiency of the protein folding process at the ER and its relation to pathological conditions.

Lysosomal-mediated degradation is becoming a fundamental process for the control of the haft-life of proteins and the degradation of misfolded, aggregate prone proteins. Ana Maria Cuervo reviews the relevance of Chaperone-mediated autophagy in the selective degradation of soluble cytosolic proteins in lysosomes, and also points out a key role for Chaperone-mediated autophagy in the cellular defense against proteotoxicity. David Rubinsztein and Guido Kroemer present two reviews highlighting the emerging relevance of macroautophagy in maintaining the homeostasis of the nervous system. They also discuss the actual impact of macroautophagy in the clearance of protein aggregates related to neurodegenerative diseases, including Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease among others. In addition, recent evidence suggesting an actual impairment of macroautophagy as a causative factor in aging-related disorders is also discussed.

Alterations in protein homeostasis underlie the etiology of many diseases affecting the nervous system, in addition to cancer and diabetes. Fumiko Urano summarizes the impact of ER stress in β cell dysfunction and death during the progression of type 1 and type 2 diabetes, as well as in genetic forms of diabetes such as Wolfram syndrome. The occurrence of basal ER stress is observed in specialized secretory cells and organs, including plasma B cells. Roberto Sitia covers several aspects of how proteotoxic stresses physiologically contribute to regulate the biogenesis, function and lifespan of B cells, and speculates about the possible impact of ER stress in the treatment of multiple myeloma. Claudio Soto describes the specific role of calcineurin, a key phosphatase in the brain, in the occurrence of synaptic dysfunction and neuronal death in prion-related disorders. We also present provide a review summarizing the emerging role of ER stress and the UPR in most neurodegenerative diseases related to protein misfolding. We also discuss the particular mechanisms currently proposed to be involved in the generation of protein folding stress at the ER in these pathologies, and speculate about possible therapeutic interventions to treat neurodegenerative diseases.

Strategies to increase the efficiency of quality control mechanisms, to reduce protein aggregation and to enhance folding are suggested to be beneficial in the setting of diseases associated with the disruption of protein homeostasis. Finally, Jeffery Kelly overviews recent chemical and biological therapeutic strategies to restore protein homeostasis, which could be achieved by enhancing the biological capacity of the proteostasis network or through small molecule to stabilize misfolding-prone proteins. In summary, this volume ofCurrent Opinion in Cell Biology compiles the most recent advances in understanding the impact of protein folding stress in physiology and disease, and integrates a variety of complex mechanisms that evolved to maintain protein homeostasis in a dynamic way in the context of a changing environment. The biomedical applications of developing strategies to cope with protein folding stress have profound implications for the treatment of the most prevalent diseases in the human population.

7.3.11 Proteome sequencing goes deep
Advances in mass spectrometry (MS) have transformed the scope and impact of protein characterization efforts. Identifying hundreds of proteins from rather simple biological matrices, such as yeast, was a daunting task just a few decades ago. Now, expression of more than half of the estimated ∼20,000 human protein coding genes can be confirmed in record time and from minute sample quantities. Access to proteomic information at such unprecedented depths has been fueled by strides in every stage of the shotgun proteomics workflow-from sample processing to data analysis-and promises to revolutionize our understanding of the causes and consequences of proteome variation.
Highlights
    • Recent MS advances have transformed the depth of coverage of the human proteome.• Expression of half the estimated human protein coding genes can be verified by MS.• MS sample preparation, instrumentation, and data analysis techniques are highlighted.

http://ars.els-cdn.com/content/image/1-s2.0-S1367593114001586-gr1.sml

Mammalian proteomes  are complex [3]. The human proteome contains ~20,300 protein-coding genes; however, non-synonymous single nucleotide polymorphisms (nsSNPs), alternative
splicing events, and post-translational modifications (PTMs) all occur and exponentially increase the number of distinct proteoforms [4–6]. Detection of 5000 proteins in a proteomic
experiment was a considerable achievement just a few years ago [7–9]. More recently, two groups identified over 10,000 protein groups in a single experiment. Through extensive protein
and peptide fractionation (72 fractions) and digestion with multiple enzymes, Nagaraj et al. identified 10,255 protein groups from HeLa cells over 288 hours of instrument analysis [10].
A comparison with paired RNA-Seq data revealed nearly complete overlap between the detected proteins and the expressed transcripts. In that same year, a similar strategy enabled
the identification of 10,006 proteins from the U2OS cell line [11]. Kim and co-workers analyzed 30 human tissues and primary cells over 2000 LC–MS/MS experiments, resulting
in the detection of 293,000 peptides with unique amino acid sequences and evidence for 17,294 gene products [16]. Wilhelm et al. amassed a total of 16,857 LC–MS/MS experiments
from human cell lines, tissues, and body fluids. These experiments produced 946,000 unique peptides, which map to 18,097 protein coding genes [17]. Together, these two studies
provide direct evidence for protein translation of over 90% of  human genes (Figure 2). New developments in mass spectrometer technology have increased the rate at which proteomes
can be analyzed. We describe developments in sample preparation, MS instrumentation, and bioinformatics that have been key to obtaining comprehensive proteomic coverage.
Further, we consider how access to such proteomic detail will impact genomic  research.

Aurelian Udristioiu

Aurelian

Aurelian Udristioiu

Lab Director at Emergency County Hospital Targu Jiu

Mg²+ is critical for maintaining the positional integrity of closely clustered phosphate groups. These clusters appear in numerous and distinct parts of the cell nucleus and cytoplasm. The Mg²+ ion maintains the integrity of nucleic acids, ribosomes and proteins. In addition, this ion acts as an oligo-element with role in energy catalysis. Biological cell membranes and cell walls exhibit poly-anionic charges on the surface. This finding has important implications for the transport of ions, particularly because different membranes preferentially bind different ions. Both Mg²+ and Ca²+ regularly stabilize membranes by cross-linking the carboxylated and phosphorylated head groups of lipids.

Notable document –

Theor Biol Med Model. 2010 Jun 9;7:19.
Native aggregation as a cause of origin of temporary cellular structures needed for all forms of cellular activity, signaling and transformations.
Matveev VV1.
Cell physiologist at Institute of Cytology, Russian Academy of Sciences

According to the hypothesis explored in this paper, native aggregation is genetically controlled (programmed) reversible aggregation that occurs when interacting proteins form new temporary structures through highly specific interactions. It is assumed that Anfinsen’s dogma may be extended to protein aggregation: composition and amino acid sequence determine not only the secondary and tertiary structure of single protein, but also the structure of protein aggregates (associates). Cell function is considered as a transition between two states (two states model), the resting state and state of activity (this applies to the cell as a whole and to its individual structures). In the resting state, the key proteins are found in the following inactive forms: natively unfolded and globular. When the cell is activated, secondary structures appear in natively unfolded proteins (including unfolded regions in other proteins), and globular proteins begin to melt and their secondary structures become available for interaction with the secondary structures of other proteins. These temporary secondary structures provide a means for highly specific interactions between proteins. As a result, native aggregation creates temporary structures necessary for cell activity.”One of the principal objects of theoretical research in any department of knowledge is to find the point of view from which the subject appears in its greatest simplicity.”Josiah Willard Gibbs (1839-1903).

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To date, numerous mechanisms, signal pathways, and different factors have been found in the cell. Researchers are naturally eager to find commonalities in the mechanisms of cellular regulation. I would like to propose a substantial approach to problems of cell physiology – the structural ground that produces signals and underlies the diversity of cellular mechanisms.

The methodological basis for the proposed hypothesis results from studies by the scientific schools of Dmitrii Nasonov [1] and Gilbert Ling [26], which have gained new appreciation over the last 20-30 years owing to advances in protein physics [7] in the study of properties of globular proteins, their unfolding and folding, as well as the discovery of novel states of the protein molecule: the natively unfolded and the molten globule. The key statement for the rationale of the present paper is that the specificity of interactions of polypeptide chains with each other (at the intra- and inter-molecular levels) can be provided only by their secondary structures, primarily α-helices and β-sheets.

Nasonov’s school discovered and studied a fundamental phenomenon — the nonspecific reaction of the cell to external actions [1], while works by Ling [5] and his followers allow the mechanisms of this phenomenon to be understood.

The above-mentioned cell reaction has been called nonspecific because diverse physical and chemical factors produce the same complex of structural changes in the cell: an increase in the turbidity and macroscopic viscosity of the cytoplasm and in the adsorption of hydrophobic substances by cytoplasmic proteins. It is of primary importance that the same changes also occur in the cell during its transition into the active state: muscle contraction, action potential, enhancement of secretory activity (for details, see [8]). Hence, from the point of view of structural changes, there is no fundamental difference between the result of action on the cell of hydrostatic pressure and, for instance, muscle contraction. In both cases, proteins are aggregated.

Nasonov called the cause of these changes the stages of cell protein denaturation, as the changes of properties of isolated proteins during denaturation are very similar to the changes in the cytoplasm during the nonspecific reaction. As a result, the denaturational theory of cell excitation and damage was created [1]. The structural changes of protein denaturation were unclear in Nasonov’s time. Nowadays, it is assumed that the denaturation is the destruction of the tertiary and secondary structure of a protein. Below I give two definitions, for the denaturation of natively folded (globular) proteins and for natively unfolded proteins.

A key notion in physiology is the resting state of the cell. This is implicit in the concept of the threshold character of the action of stimuli on the cell, which has played a historical role in the development of physiological science. It is the threshold that is the boundary between two states — rest and activity. But in effect, all our knowledge about cells concerns active cells, not cells in the resting state. It is in the active cell that variable changes occur that can be recorded. Nothing happens in the resting cell, so there is nothing to be recorded in it. Nevertheless, it is obvious that the resting state is the initial cell state, the starting point for all changes occurring in the cell.

What characterizes the structural aspect of the cell in the state of rest? It is only in Ling’s work [5] that I have found a clear answer to this question. The answer can be interpreted as follows: if all resting cell proteins were arranged in one line, it would turn out that most of the peptide bonds in this superpolypeptide would be accessible to solvent (water), while only a few would be included in secondary structures. When the cell is activated, the ratio between the unfolded and folded areas is changed sharply to the opposite: the proportion of peptide bonds accessible to solvent decreases markedly, whereas the proportion included in secondary structures rises significantly. These two extreme states of cell proteins, suggested by Ling, provide a basis for further consideration.

If Ling’s approach is combined with Nasonov’s theory, we obtain several interesting consequences. First of all, it is clear that proteins with maximally unfolded structures form the structural basis of resting cells because they are inactive, i.e., do not interact with other proteins or other macromolecules. The situation changes when an action on the cell exceeds the threshold: completely or partially unfolded key proteins begin to fold when new secondary protein structures are formed. Owing to these new secondary structures, the proteins become capable of reacting, i.e., intramolecular aggregation (folding of individual polypeptides into globules) and intermolecular aggregation (interaction of some proteins with others) begin. A distinguishing feature of these aggregational processes is their absolutely specific character, which is ensured by the amino acid composition, shape, and size of the secondary structures. The structures appearing have physiological meaning, so such aggregation is native and the secondary structures causing it are centers of native aggregation. Another source of secondary structures necessary for native aggregation is the molten globule.

The ability of cells to return to the initial state, the state of rest, means that native aggregation is completely reversible, and the structures appearing in the course of native aggregation are temporary and are disassembled as soon as they cease to be necessary. Native aggregation can involve both the whole cell and individual organelles, compartments, and structures, and activation of proteins is of a threshold rather than a spontaneous character.

The meaning of the proposed hypothesis of native aggregation is that the primary cause of any functional changes in cell is the appearance, as a result of native aggregation, of temporary structures, continually appearing and disintegrating during the life of the cell. Since native aggregation is initiated by external stimuli or regulatory processes and the structures appearing have a temporary character, these structures can be called signal structures.

Signal structures can have different properties: (i) they can be centers of binding of ions, molecules (solutes), and proteins; (ii) they can have enzymatic activity; (iii) they can form channels and intercellular contacts; (iv) they can serve as matrices organizing the interactions of molecules in synthetic and transport processes; (iv) they can serve as receptors for signal molecules; (v) they can serve as the basis for constructing even more complex supramolecular structures. These structures “flash” in the cell space like signal lights, perform their role, and disappear, to appear in another place and at another time. The meaning of the existence of the structural “flashes” is that during transition into the active state the cell needs new resources, functions, mechanisms, regulators, and signals. As soon as the cell changes to the resting state, the need for these structures disappears, and they are disassembled. Extreme examples of native aggregation are muscle contraction, condensation of chromosomes, the appearance of the division spindle, and interactions of ligands with receptors.

Thus, the present paper will consider the meaning and significance of native aggregation as the universal structural basis of the active cell. The basis of pathological states is the inability of the cell to return to the resting state and errors in the formation of signal structures. The presentation of native aggregation is based on three pillars: (i) reversible protein aggregation is a structural basis of cell activity (Nasonov’s School); (ii) the operation of the living cell or its individual structures can be regarded as a repetitive sequence of transitions between two states (active and resting), a key role in which belongs to natively unfolded proteins (Ling’s approach); (iii) the specificity of interactions of separate parts of a single polypeptide chain with each other (folding) or the interaction of separate polypeptide chains among themselves (self-assembly, aggregation) can be provided only by protein secondary structures.

The goal of this paper is the enunciation of principles, rather than a review of facts corresponding to these principles.

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Hypoxia Inducible Factor 1 (HIF-1)[7.9]

Hypoxia Inducible Factor 1 (HIF-1)

Writer and Curator: Larry H Bernstein, MD, FCAP

7.9  Hypoxia Inducible Factor 1 (HIF-1)

7.9.1 Hypoxia and mitochondrial oxidative metabolism

7.9.2 Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability

7.9.3 Hypoxia-Inducible Factors in Physiology and Medicine

7.9.4 Hypoxia-inducible factor 1. Regulator of mitochondrial metabolism and mediator of ischemic preconditioning

7.9.5 Regulation of cancer cell metabolism by hypoxia-inducible factor 1

7.9.6 Coming up for air. HIF-1 and mitochondrial oxygen consumption

7.9.7 HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption

7.9.8 HIF-1. upstream and downstream of cancer metabolism

7.9.9 In Vivo HIF-Mediated Reductive Carboxylation

7.9.10 Evaluation of HIF-1 inhibitors as anticancer agents

 

 

7.9.1 Hypoxia and mitochondrial oxidative metabolism

Solaini G1Baracca ALenaz GSgarbi G.
Biochim Biophys Acta. 2010 Jun-Jul; 1797(6-7):1171-7
http://dx.doi.org/10.1016/j.bbabio.2010.02.011

It is now clear that mitochondrial defects are associated with a large variety of clinical phenotypes. This is the result of the mitochondria’s central role in energy production, reactive oxygen species homeostasis, and cell death. These processes are interdependent and may occur under various stressing conditions, among which low oxygen levels (hypoxia) are certainly prominent. Cells exposed to hypoxia respond acutely with endogenous metabolites and proteins promptly regulating metabolic pathways, but if low oxygen levels are prolonged, cells activate adapting mechanisms, the master switch being the hypoxia-inducible factor 1 (HIF-1). Activation of this factor is strictly bound to the mitochondrial function, which in turn is related with the oxygen level. Therefore in hypoxia, mitochondria act as [O2] sensors, convey signals to HIF-1directly or indirectly, and contribute to the cell redox potential, ion homeostasis, and energy production. Although over the last two decades cellular responses to low oxygen tension have been studied extensively, mechanisms underlying these functions are still indefinite. Here we review current knowledge of the mitochondrial role in hypoxia, focusing mainly on their role in cellular energy and reactive oxygen species homeostasis in relation with HIF-1 stabilization. In addition, we address the involvement of HIF-1 and the inhibitor protein of F1F0 ATPase in the hypoxia-induced mitochondrial autophagy.

Over the last two decades a defective mitochondrial function associated with hypoxia has been invoked in many diverse complex disorders, such as type 2 diabetes [1] and [2], Alzheimer’s disease [3] and [4], cardiac ischemia/reperfusion injury [5] and [6], tissue inflammation [7], and cancer [8][9][10],[11] and [12].

The [O2] in air-saturated aqueous buffer at 37 °C is approx. 200 μM [13]; however, mitochondria in vivo are exposed to a considerably lower [O2] that varies with tissue and physiological state. Under physiological conditions, most human resting cells experience some 5% oxygen tension, however the [O2] gradient occurring between the extracellular environment and mitochondria, where oxygen is consumed by cytochrome c oxidase, results in a significantly lower [O2] exposition of mitochondria. Below this oxygen level, most mammalian tissues are exposed to hypoxic conditions  [14]. These may arise in normal development, or as a consequence of pathophysiological conditions where there is a reduced oxygen supply due to a respiratory insufficiency or to a defective vasculature. Such conditions include inflammatory diseases, diabetes, ischemic disorders (cerebral or cardiovascular), and solid tumors. Mitochondria consume the greatest amount (some 85–90%) of oxygen in cells to allow oxidative phosphorylation (OXPHOS), which is the primary metabolic pathway for ATP production. Therefore hypoxia will hamper this metabolic pathway, and if the oxygen level is very low, insufficient ATP availability might result in cell death [15].

When cells are exposed to an atmosphere with reduced oxygen concentration, cells readily “respond” by inducing adaptive reactions for their survival through the AMP-activated protein kinase (AMPK) pathway (see for a recent review [16]) which inter alia increases glycolysis driven by enhanced catalytic efficiency of some enzymes, including phosphofructokinase-1 and pyruvate kinase (of note, this oxidative flux is thermodynamically allowed due to both reduced phosphorylation potential [ATP]/([ADP][Pi]) and the physiological redox state of the cell). However, this is particularly efficient only in the short term, therefore cells respond to prolonged hypoxia also by stimulation of hypoxia-inducible factors (HIFs: HIF-1 being the mostly studied), which are heterodimeric transcription factors composed of α and β subunits, first described by Semenza and Wang [17]. These HIFs in the presence of hypoxic oxygen levels are activated through a complex mechanism in which the oxygen tension is critical (see below). Afterwards HIFs bind to hypoxia-responsive elements, activating the transcription of more than two hundred genes that allow cells to adapt to the hypoxic environment [18] and [19].

Several excellent reviews appeared in the last few years describing the array of changes induced by oxygen deficiency in both isolated cells and animal tissues. In in vivo models, a coordinated regulation of tissue perfusion through vasoactive molecules such as nitric oxide and the action of carotid bodies rapidly respond to changes in oxygen demand [20][21][22][23] and [24]. Within isolated cells, hypoxia induces significant metabolic changes due to both variation of metabolites level and activation/inhibition of enzymes and transporters; the most important intracellular effects induced by different pathways are expertly described elsewhere (for recent reviews, see [25][26] and [27]). It is reasonable to suppose that the type of cells and both the severity and duration of hypoxia may determine which pathways are activated/depressed and their timing of onset [3][6][10][12][23] and [28]. These pathways will eventually lead to preferential translation of key proteins required for adaptation and survival to hypoxic stress. Although in the past two decades, the discovery of HIF-1 by Gregg Semenza et al. provided a molecular platform to investigate the mechanism underlying responses to oxygen deprivation, the molecular and cellular biology of hypoxia has still to be completely elucidated. This review summarizes recent experimental data concerned with mitochondrial structure and function adaptation to hypoxia and evaluates it in light of the main structural and functional parameters defining the mitochondrial bioenergetics. Since mitochondria contain an inhibitor protein, IF1, whose action on the F1F0 ATPase has been considered for decades of critical importance in hypoxia/ischemia, particular notice will be dedicated to analyze molecular aspects of IF1 regulation of the enzyme and its possible role in the metabolic changes induced by low oxygen levels in cells.

Mechanism(s) of HIF-1 activation

HIF-1 consists of an oxygen-sensitive HIF-1α subunit that heterodimerizes with the HIF-1β subunit to bind DNA. In high O2 tension, HIF-1α is oxidized (hydroxylated) by prolyl hydroxylases (PHDs) using α-ketoglutarate derived from the tricarboxylic acid (TCA) cycle. The hydroxylated HIF-1α subunit interacts with the von Hippel–Lindau protein, a critical member of an E3 ubiquitin ligase complex that polyubiquitylates HIF. This is then catabolized by proteasomes, such that HIF-1α is continuously synthesized and degraded under normoxic conditions [18]. Under hypoxia, HIF-1α hydroxylation does not occur, thereby stabilizing HIF-1 (Fig. 1). The active HIF-1 complex in turn binds to a core hypoxia response element in a wide array of genes involved in a diversity of biological processes, and directly transactivates glycolytic enzyme genes [29]. Notably, O2 concentration, multiple mitochondrial products, including the TCA cycle intermediates and reactive oxygen species, can coordinate PHD activity, HIF stabilization, hence the cellular responses to O2 depletion [30] and [31]. Incidentally, impaired TCA cycle flux, particularly if it is caused by succinate dehydrogenase dysfunction, results in decreased or loss of energy production from both the electron-transport chain and the Krebs cycle, and also in overproduction of free radicals [32]. This leads to severe early-onset neurodegeneration or, as it occurs in individuals carrying mutations in the non-catalytic subunits of the same enzyme, to tumors such as phaeochromocytoma and paraganglioma. However, impairment of the TCA cycle may be relevant also for the metabolic changes occurring in mitochondria exposed to hypoxia, since accumulation of succinate has been reported to inhibit PHDs [33]. It has to be noticed that some authors believe reactive oxygen species (ROS) to be essential to activate HIF-1 [34], but others challenge this idea [35], therefore the role of mitochondrial ROS in the regulation of HIF-1 under hypoxia is still controversial [36]. Moreover, the contribution of functional mitochondria to HIF-1 regulation has also been questioned by others [37][38] and [39].

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Major mitochondrial changes in hypoxia

Major mitochondrial changes in hypoxia

Fig. 1. Major mitochondrial changes in hypoxia. Hypoxia could decrease electron-transport rate determining Δψm reduction, increased ROS generation, and enhanced NO synthase. One (or more) of these factors likely contributes to HIF stabilization, that in turn induces metabolic adaptation of both hypoxic cells and mitophagy. The decreased Δψm could also induce an active binding of IF1, which might change mitochondrial morphology and/or dynamics, and inhibit mitophagy. Solid lines indicate well established hypoxic changes in cells, whilst dotted lines indicate changes not yet stated. Inset, relationships between extracellular O2concentration and oxygen tension.

Oxygen is a major determinant of cell metabolism and gene expression, and as cellular O2 levels decrease, either during isolated hypoxia or ischemia-associated hypoxia, metabolism and gene expression profiles in the cells are significantly altered. Low oxygen reduces OXPHOS and Krebs cycle rates, and participates in the generation of nitric oxide (NO), which also contributes to decrease respiration rate [23] and [40]. However, oxygen is also central in the generation of reactive oxygen species, which can participate in cell signaling processes or can induce irreversible cellular damage and death [41].

As specified above, cells adapt to oxygen reduction by inducing active HIF, whose major effect on cells energy homeostasis is the inactivation of anabolism, activation of anaerobic glycolysis, and inhibition of the mitochondrial aerobic metabolism: the TCA cycle, and OXPHOS. Since OXPHOS supplies the majority of ATP required for cellular processes, low oxygen tension will severely reduce cell energy availability. This occurs through several mechanisms: first, reduced oxygen tension decreases the respiration rate, due first to nonsaturating substrate for cytochrome c oxidase (COX), secondarily, to allosteric modulation of COX[42]. As a consequence, the phosphorylation potential decreases, with enhancement of the glycolysis rate primarily due to allosteric increase of phosphofructokinase activity; glycolysis however is poorly efficient and produces lactate in proportion of 0.5 mol/mol ATP, which eventually drops cellular pH if cells are not well perfused, as it occurs under defective vasculature or ischemic conditions  [6]. Besides this “spontaneous” (thermodynamically-driven) shift from aerobic to anaerobic metabolism which is mediated by the kinetic changes of most enzymes, the HIF-1 factor activates transcription of genes encoding glucose transporters and glycolytic enzymes to further increase flux of reducing equivalents from glucose to lactate[43] and [44]. Second, HIF-1 coordinates two different actions on the mitochondrial phase of glucose oxidation: it activates transcription of the PDK1 gene encoding a kinase that phosphorylates and inactivates pyruvate dehydrogenase, thereby shunting away pyruvate from the mitochondria by preventing its oxidative decarboxylation to acetyl-CoA [45] and [46]. Moreover, HIF-1 induces a switch in the composition of cytochrome c oxidase from COX4-1 to COX4-2 isoform, which enhances the specific activity of the enzyme. As a result, both respiration rate and ATP level of hypoxic cells carrying the COX4-2 isoform of cytochrome c oxidase were found significantly increased with respect to the same cells carrying the COX4-1 isoform [47]. Incidentally, HIF-1 can also increase the expression of carbonic anhydrase 9, which catalyses the reversible hydration of CO2 to HCO3 and H+, therefore contributing to pH regulation.

Effects of hypoxia on mitochondrial structure and dynamics

Mitochondria form a highly dynamic tubular network, the morphology of which is regulated by frequent fission and fusion events. The fusion/fission machineries are modulated in response to changes in the metabolic conditions of the cell, therefore one should expect that hypoxia affect mitochondrial dynamics. Oxygen availability to cells decreases glucose oxidation, whereas oxygen shortage consumes glucose faster in an attempt to produce ATP via the less efficient anaerobic glycolysis to lactate (Pasteur effect). Under these conditions, mitochondria are not fueled with substrates (acetyl-CoA and O2), inducing major changes of structure, function, and dynamics (for a recent review see [48]). Concerning structure and dynamics, one of the first correlates that emerge is that impairment of mitochondrial fusion leads to mitochondrial depolarization, loss of mtDNA that may be accompanied by altered respiration rate, and impaired distribution of the mitochondria within cells [49][50] and [51]. Indeed, exposure of cortical neurons to moderate hypoxic conditions for several hours, significantly altered mitochondrial morphology, decreased mitochondrial size and reduced mitochondrial mean velocity. Since these effects were either prevented by exposing the neurons to inhibitors of nitric oxide synthase or mimicked by NO donors in normoxia, the involvement of an NO-mediated pathway was suggested [52]. Mitochondrial motility was also found inhibited and controlled locally by the [ADP]/[ATP] ratio [53]. Interestingly, the author used an original approach in which mitochondria were visualized using tetramethylrhodamineethylester and their movements were followed by applying single-particle tracking.

Of notice in this chapter is that enzymes controlling mitochondrial morphology regulators provide a platform through which cellular signals are transduced within the cell in order to affect mitochondrial function [54]. Accordingly, one might expect that besides other mitochondrial factors [30] and [55] playing roles in HIF stabilization, also mitochondrial morphology might reasonably be associated with HIF stabilization. In order to better define the mechanisms involved in the morphology changes of mitochondria and in their dynamics when cells experience hypoxic conditions, these pioneering studies should be corroborated by and extended to observations on other types of cells focusing also on single proteins involved in both mitochondrial fusion/fission and motion.

Effects of hypoxia on the respiratory chain complexes

O2 is the terminal acceptor of electrons from cytochrome c oxidase (Complex IV), which has a very high affinity for it, being the oxygen concentration for half-maximal respiratory rate at pH 7.4 approximately 0.7 µM [56]. Measurements of mitochondrial oxidative phosphorylation indicated that it is not dependent on oxygen concentration up to at least 20 µM at pH 7.0 and the oxygen dependence becomes markedly greater as the pH is more alkaline [56]. Similarly, Moncada et al. [57] found that the rate of O2 consumption remained constant until [O2] fell below 15 µM. Accordingly, most reports in the literature consider hypoxic conditions occurring in cells at 5–0.5% O2, a range corresponding to 46–4.6 µM O2 in the cells culture medium (see Fig. 1 inset). Since between the extracellular environment and mitochondria an oxygen pressure gradient is established [58], the O2 concentration experienced by Complex IV falls in the range affecting its kinetics, as reported above.

Under these conditions, a number of changes on the OXPHOS machinery components, mostly mediated by HIF-1 have been found. Thus, Semenza et al. [59] and others thereafter [46] reported that activation of HIF-1α induces pyruvate dehydrogenase kinase, which inhibits pyruvate dehydrogenase, suggesting that respiration is decreased by substrate limitation. Besides, other HIF-1 dependent mechanisms capable to affect respiration rate have been reported. First, the subunit composition of COX is altered in hypoxic cells by increased degradation of the COX4-1 subunit, which optimizes COX activity under aerobic conditions, and increased expression of the COX4-2 subunit, which optimizes COX activity under hypoxic conditions [29]. On the other hand, direct assay of respiration rate in cells exposed to hypoxia resulted in a significant reduction of respiration [60]. According with the evidence of Zhang et al., the respiration rate decrease has to be ascribed to mitochondrial autophagy, due to HIF-1-mediated expression of BNIP3. This interpretation is in line with preliminary results obtained in our laboratory where the assay of the citrate synthase activity of cells exposed to different oxygen tensions was performed. Fig. 2 shows the citrate synthase activity, which is taken as an index of the mitochondrial mass [11], with respect to oxygen tension: [O2] and mitochondrial mass are directly linked.

Citrate synthase activity

Citrate synthase activity

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Fig. 2. Citrate synthase activity. Human primary fibroblasts, obtained from skin biopsies of 5 healthy donors, were seeded at a density of 8,000 cells/cm2 in high glucose Dulbecco’s Modified Eagle Medium, DMEM (25 mM glucose, 110 mg/l pyruvate, and 4 mM glutamine) supplemented with 15% Foetal Bovine Serum (FBS). 18 h later, cell culture dishes were washed once with Hank’s Balanced Salt Solution (HBSS) and the medium was replaced with DMEM containing 5 mM glucose, 110 mg/l pyruvate, and 4 mM glutamine supplemented with 15% FBS. Cell culture dishes were then placed into an INVIVO2 humidified hypoxia workstation (Ruskinn Technologies, Bridgend, UK) for 72 h changing the medium at 48 h, and oxygen partial pressure (tension) conditions were: 20%, 4%, 2%, 1% and 0.5%. Cells were subsequently collected within the workstation with trypsin-EDTA (0.25%), washed with PBS and resuspended in a buffer containing 10 mM Tris/HCl, 0.1 M KCl, 5 mM KH2PO4, 1 mM EGTA, 3 mM EDTA, and 2 mM MgCl2 pH 7.4 (all the solutions were preconditioned to the appropriate oxygen tension condition). The citrate synthase activity was assayed essentially by incubating 40 µg of cells with 0.02% Triton X-100, and monitoring the reaction by measuring spectrophotometrically the rate of free coenzyme A released, as described in [90]. Enzymatic activity was expressed as nmol/min/mg of protein. Three independent experiments were carried out and assays were performed in either duplicate or triplicate.

However, the observations of Semenza et al. must be seen in relation with data reported by Moncada et al.[57] and confirmed by others [61] in which it is clearly shown that when cells (various cell lines) experience hypoxic conditions, nitric oxide synthases (NOSs) are activated, therefore NO is released. As already mentioned above, NO is a strong competitor of O2 for cytochrome c oxidase, whose apparent Km results increased, hence reduction of mitochondrial cytochromes and all the other redox centres of the respiratory chain occurs. In addition, very recent data indicate a potential de-activation of Complex I when oxygen is lacking, as it occurs in prolonged hypoxia [62]. According to Hagen et al. [63] the NO-dependent inhibition of cytochrome c oxidase should allow “saved” O2 to redistribute within the cell to be used by other enzymes, including PHDs which inactivate HIF. Therefore, unless NO inhibition of cytochrome c oxidase occurs only when [O2] is very low, inhibition of mitochondrial oxygen consumption creates the paradox of a situation in which the cell may fail to register hypoxia. It has been tempted to solve this paradox, but to date only hypotheses have been proposed [23] and [26]. Interestingly, recent observations on yeast cells exposed to hypoxia revealed abnormal protein carbonylation and protein tyrosine nitration that were ascribed to increased mitochondrially generated superoxide radicals and NO, two species typically produced at low oxygen levels, that combine to form ONOO [64]. Based on these studies a possible explanation has been proposed for the above paradox.

Finally, it has to be noticed that the mitochondrial respiratory deficiency observed in cardiomyocytes of dogs in which experimental heart failure had been induced lies in the supermolecular assembly rather than in the individual components of the electron-transport chain [65]. This observation is particularly intriguing since loss of respirasomes is thought to facilitate ROS generation in mitochondria [66], therefore supercomplexes disassembly might explain the paradox of reduced [O2] and the enhanced ROS found in hypoxic cells. Specifically, hypoxia could reduce mitochondrial fusion by impairing mitochondrial membrane potential, which in turn could induce supercomplexes disassembly, increasing ROS production[11].

Complex III and ROS production

It has been estimated that, under normoxic physiological conditions, 1–2% of electron flow through the mitochondrial respiratory chain gives rise to ROS [67] and [68]. It is now recognized that the major sites of ROS production are within Complexes I and III, being prevalent the contribution of Complex I [69] (Fig. 3). It might be expected that hypoxia would decrease ROS production, due to the low level of O2 and to the diminished mitochondrial respiration [6] and [46], but ROS level is paradoxically increased. Indeed, about a decade ago, Chandel et al. [70] provided good evidence that mitochondrial reactive oxygen species trigger hypoxia-induced transcription, and a few years later the same group [71] showed that ROS generated at Complex III of the mitochondrial respiratory chain stabilize HIF-1α during hypoxia (Fig. 1 and Fig. 3). Although others have proposed mechanisms indicating a key role of mitochondria in HIF-1α regulation during hypoxia (for reviews see [64] and [72]), the contribution of mitochondria to HIF-1 regulation has been questioned by others [35][36] and [37]. Results of Gong and Agani [35] for instance show that inhibition of electron-transport Complexes I, III, and IV, as well as inhibition of mitochondrial F0F1 ATPase, prevents HIF-1α expression and that mitochondrial reactive oxygen species are not involved in HIF-1α regulation during hypoxia. Concurrently, Tuttle et al. [73], by means of a non invasive, spectroscopic approach, could find no evidence to suggest that ROS, produced by mitochondria, are needed to stabilize HIF-1α under moderate hypoxia. The same authors found the levels of HIF-1α comparable in both normal and ρ0 cells (i.e. cells lacking mitochondrial DNA). On the contrary, experiments carried out on genetic models consisting of either cells lacking cytochrome c or ρ0 cells both could evidence the essential role of mitochondrial respiration to stabilize HIF-1α [74]. Thus, cytochrome c null cells, being incapable to respire, exposed to moderate hypoxia (1.5% O2) prevented oxidation of ubiquinol and generation of the ubisemiquinone radical, thus eliminating superoxide formation at Complex III [71]. Concurrently, ρ0 cells lacking electron transport, exposed 4 h to moderate hypoxia failed to stabilize HIF-1α, suggesting the essential role of the respiratory chain for the cellular sensing of low O2 levels. In addition, recent evidence obtained on genetic manipulated cells (i.e. cytochrome b deficient cybrids) showed increased ROS levels and stabilized HIF-1α protein during hypoxia [75]. Moreover, RNA interference of the Complex III subunit Rieske iron sulfur protein in the cytochrome b deficient cells, abolished ROS generation at the Qo site of Complex III, preventing HIF-1α stabilization. These observations, substantiated by experiments with MitoQ, an efficient mitochondria-targeted antioxidant, strongly support the involvement of mitochondrial ROS in regulating HIF-1α. Nonetheless, collectively, the available data do not allow to definitely state the precise role of mitochondrial ROS in regulating HIF-1α, but the pathway stabilizing HIF-1α appears undoubtedly mitochondria-dependent [30].

Overview of mitochondrial electron and proton flux in hypoxia

Overview of mitochondrial electron and proton flux in hypoxia

Overview of mitochondrial electron and proton flux in hypoxia

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Fig. 3. Overview of mitochondrial electron and proton flux in hypoxia. Electrons released from reduced cofactors (NADH and FADH2) under normoxia flow through the redox centres of the respiratory chain (r.c.) to molecular oxygen (blue dotted line), to which a proton flux from the mitochondrial matrix to the intermembrane space is coupled (blue arrows). Protons then flow back to the matrix through the F0 sector of the ATP synthase complex, driving ATP synthesis. ATP is carried to the cell cytosol by the adenine nucleotide translocator (blue arrows). Under moderate to severe hypoxia, electrons escape the r.c. redox centres and reduce molecular oxygen to the superoxide anion radical before reaching the cytochrome c (red arrow). Under these conditions, to maintain an appropriate Δψm, ATP produced by cytosolic glycolysis enters the mitochondria where it is hydrolyzed by the F1F0ATPase with extrusion of protons from the mitochondrial matrix (red arrows).

Hypoxia and ATP synthase

The F1F0 ATPase (ATP synthase) is the enzyme responsible of catalysing ADP phosphorylation as the last step of OXPHOS. It is a rotary motor using the proton motive force across the mitochondrial inner membrane to drive the synthesis of ATP [76]. It is a reversible enzyme with ATP synthesis or hydrolysis taking place in the F1 sector at the matrix side of the membrane, chemical catalysis being coupled to H+transport through the transmembrane F0 sector.

Under normoxia the enzyme synthesizes ATP, but when mitochondria experience hypoxic conditions the mitochondrial membrane potential (Δψm) decreases below its endogenous steady-state level (some 140 mV, negative inside the matrix [77]) and the F1F0 ATPase may work in the reversal mode: it hydrolyses ATP (produced by anaerobic glycolysis) and uses the energy released to pump protons from the mitochondrial matrix to the intermembrane space, concurring with the adenine nucleotide translocator (i.e. in hypoxia it exchanges cytosolic ATP4− for matrix ADP3−) to maintain the physiological Δψm ( Fig. 3). Since under conditions of limited oxygen availability the decline in cytoplasmic high energy phosphates is mainly due to hydrolysis by the ATP synthase working in reverse [6] and [78], the enzyme must be strictly regulated in order to avoid ATP dissipation. This is achieved by a natural protein, the H+ψm-dependent IF1, that binds to the catalytic F1 sector at low pH and low Δψm (such as it occurs in hypoxia/ischemia) [79]. IF1 binding to the ATP synthase results in a rapid and reversible inhibition of the enzyme [80], which could reach about 50% of maximal activity (for recent reviews see [6] and [81]).

Besides this widely studied effect, IF1 appears to be associated with ROS production and mitochondrial autophagy (mitophagy). This is a mechanism involving the catabolic degradation of macromolecules and organelles via the lysosomal pathway that contributes to housekeeping and regenerate metabolites. Autophagic degradation is involved in the regulation of the ageing process and in several human diseases, such as myocardial ischemia/reperfusion [82], Alzheimer’s Disease, Huntington diseases, and inflammatory diseases (for recent reviews see [83] and [84], and, as mentioned above, it promotes cell survival by reducing ROS and mtDNA damage under hypoxic conditions.

Campanella et al. [81] reported that, in HeLa cells under normoxic conditions, basal autophagic activity varies in relation to the expression levels of IF1. Accordingly, cells overexpressing IF1 result in ROS production similar to controls, conversely cells in which IF1 expression is suppressed show an enhanced ROS production. In parallel, the latter cells show activation of the mitophagy pathway (Fig. 1), therefore suggesting that variations in IF1 expression level may play a significant role in defining two particularly important parameters in the context of the current review: rates of ROS generation and mitophagy. Thus, the hypoxia-induced enhanced expression level of IF1[81] should be associated with a decrease of both ROS production and autophagy, which is in apparent conflict with the hypoxia-induced ROS increase and with the HIF-1-dependent mitochondrial autophagy shown by Zhang et al. [60] as an adaptive metabolic response to hypoxia. However, in the experiments of Zhang et al. the cells were exposed to hypoxia for 48 h, whereas the F1F0-ATPase inhibitor exerts a prompt action on the enzyme and to our knowledge, it has never been reported whether its action persists during prolonged hypoxic expositions. Pertinent with this problem is the very recent observation that IEX-1 (immediate early response gene X-1), a stress-inducible gene that suppresses production of ROS and protects cells from apoptosis [85], targets the mitochondrial F1F0-ATPase inhibitor for degradation, reducing ROS by decreasing Δψm. It has to be noticed that the experiments described were carried out under normal oxygen availability, but it does not seem reasonable to rule out IEX-1 from playing a role under stress conditions as those induced by hypoxia in cells, therefore this issue might deserve an investigation also at low oxygen levels.

In conclusion, data are still emerging regarding the regulation of mitochondrial function by the F1F0 ATPase within hypoxic responses in different cellular and physiological contexts. Given the broad pathophysiological role of hypoxic cellular modulation, an understanding of the subtle tuning among different effectors of the ATP synthase is desirable to eventually target future therapeutics most effectively. Our laboratory is actually involved in carrying out investigations to clarify this context.

Conclusions and perspectives

The mitochondria are important cellular platforms that both propagate and initiate intracellular signals that lead to overall cellular and metabolic responses. During the last decades, a significant amount of relevant data has been obtained on the identification of mechanisms of cellular adaptation to hypoxia. In hypoxic cells there is an enhanced transcription and synthesis of several glycolytic pathway enzymes/transporters and reduction of synthesis of proteins involved in mitochondrial catabolism. Although well defined kinetic parameters of reactions in hypoxia are lacking, it is usually assumed that these transcriptional changes lead to metabolic flux modification. The required biochemical experimentation has been scarcely addressed until now and only in few of the molecular and cellular biology studies the transporter and enzyme kinetic parameters and flux rate have been determined, leaving some uncertainties.

Central to mitochondrial function and ROS generation is an electrochemical proton gradient across the mitochondrial inner membrane that is established by the proton pumping activity of the respiratory chain, and that is strictly linked to the F1F0-ATPase function. Evaluation of the mitochondrial membrane potential in hypoxia has only been studied using semiquantitative methods based on measurements of the fluorescence intensity of probes taken up by cells experiencing normal or hypoxic conditions. However, this approach is intrinsically incorrect due to the different capability that molecular oxygen has to quench fluorescence [86] and [87] and to the uncertain concentration the probe attains within mitochondria, whose mass may be reduced by a half in hypoxia [60]. In addition, the uncertainty about measurement of mitochondrial superoxide radical and H2O2 formation in vivo [88] hampers studies on the role of mitochondrial ROS in hypoxic oxidative damage, redox signaling, and HIF-1 stabilization.

The duration and severity of hypoxic stress differentially activate the responses discussed throughout and lead to substantial phenotypic variations amongst tissues and cell models, which are not consistently and definitely known. Certainly, understanding whether a hierarchy among hypoxia response mechanisms exists and which are the precise timing and conditions of each mechanism to activate, will improve our knowledge of the biochemical mechanisms underlying hypoxia in cells, which eventually may contribute to define therapeutic targets in hypoxia-associated diseases. To this aim it might be worth investigating the hypoxia-induced structural organization of both the respiratory chain enzymes in supramolecular complexes and the assembly of the ATP synthase to form oligomers affecting ROS production [65] and inner mitochondrial membrane structure [89], respectively.

7.9.2 Hypoxia promotes isocitrate dehydrogenase-dependent carboxylation of α-ketoglutarate to citrate to support cell growth and viability

DR WisePS WardJES ShayJR CrossJJ Gruber, UM Sachdeva, et al.
Proc Nat Acad Sci Oct 27, 2011; 108(49):19611–19616
http://dx.doi.org:/10.1073/pnas.1117773108

Citrate is a critical metabolite required to support both mitochondrial bioenergetics and cytosolic macromolecular synthesis. When cells proliferate under normoxic conditions, glucose provides the acetyl-CoA that condenses with oxaloacetate to support citrate production. Tricarboxylic acid (TCA) cycle anaplerosis is maintained primarily by glutamine. Here we report that some hypoxic cells are able to maintain cell proliferation despite a profound reduction in glucose-dependent citrate production. In these hypoxic cells, glutamine becomes a major source of citrate. Glutamine-derived α-ketoglutarate is reductively carboxylated by the NADPH-linked mitochondrial isocitrate dehydrogenase (IDH2) to form isocitrate, which can then be isomerized to citrate. The increased IDH2-dependent carboxylation of glutamine-derived α-ketoglutarate in hypoxia is associated with a concomitant increased synthesis of 2-hydroxyglutarate (2HG) in cells with wild-type IDH1 and IDH2. When either starved of glutamine or rendered IDH2-deficient by RNAi, hypoxic cells are unable to proliferate. The reductive carboxylation of glutamine is part of the metabolic reprogramming associated with hypoxia-inducible factor 1 (HIF1), as constitutive activation of HIF1 recapitulates the preferential reductive metabolism of glutamine-derived α-ketoglutarate even in normoxic conditions. These data support a role for glutamine carboxylation in maintaining citrate synthesis and cell growth under hypoxic conditions.

Citrate plays a critical role at the center of cancer cell metabolism. It provides the cell with a source of carbon for fatty acid and cholesterol synthesis (1). The breakdown of citrate by ATP-citrate lyase is a primary source of acetyl-CoA for protein acetylation (2). Metabolism of cytosolic citrate by aconitase and IDH1 can also provide the cell with a source of NADPH for redox regulation and anabolic synthesis. Mammalian cells depend on the catabolism of glucose and glutamine to fuel proliferation (3). In cancer cells cultured at atmospheric oxygen tension (21% O2), glucose and glutamine have both been shown to contribute to the cellular citrate pool, with glutamine providing the major source of the four-carbon molecule oxaloacetate and glucose providing the major source of the two-carbon molecule acetyl-CoA (45). The condensation of oxaloacetate and acetyl-CoA via citrate synthase generates the 6 carbon citrate molecule. However, both the conversion of glucose-derived pyruvate to acetyl-CoA by pyruvate dehydrogenase (PDH) and the conversion of glutamine to oxaloacetate through the TCA cycle depend on NAD+, which can be compromised under hypoxic conditions. This raises the question of how cells that can proliferate in hypoxia continue to synthesize the citrate required for macromolecular synthesis.

This question is particularly important given that many cancers and stem/progenitor cells can continue proliferating in the setting of limited oxygen availability (67). Louis Pasteur first highlighted the impact of hypoxia on nutrient metabolism based on his observation that hypoxic yeast cells preferred to convert glucose into lactic acid rather than burning it in an oxidative fashion. The molecular basis for this shift in mammalian cells has been linked to the activity of the transcription factor HIF1 (810). Stabilization of the labile HIF1α subunit occurs in hypoxia. It can also occur in normoxia through several mechanisms including loss of the von Hippel-Lindau tumor suppressor (VHL), a common occurrence in renal carcinoma (11). Although hypoxia and/or HIF1α stabilization is a common feature of multiple cancers, to date the source of citrate in the setting of hypoxia or HIF activation has not been determined.

Here, we study the sources of hypoxic citrate synthesis in a glioblastoma cell line that proliferates in profound hypoxia (0.5% O2). Glucose uptake and conversion to lactic acid increased in hypoxia. However, glucose conversion into citrate dramatically declined. Glutamine consumption remained constant in hypoxia, and hypoxic cells were addicted to the use of glutamine in hypoxia as a source of α-ketoglutarate. Glutamine provided the major carbon source for citrate synthesis during hypoxia. However, the TCA cycle-dependent conversion of glutamine into citric acid was significantly suppressed. In contrast, there was a relative increase in glutamine-dependent citrate production in hypoxia that resulted from carboxylation of α-ketoglutarate. This reductive synthesis required the presence of mitochondrial isocitrate dehydrogenase 2 (IDH2). In confirmation of the reverse flux through IDH2, the increased reductive metabolism of glutamine-derived α-ketoglutarate in hypoxia was associated with increased synthesis of 2HG. Finally, constitutive HIF1α-expressing cells also demonstrated significant reductive-carboxylation-dependent synthesis of citrate in normoxia and a relative defect in the oxidative conversion of glutamine into citrate. Collectively, the data demonstrate that mitochondrial glutamine metabolism can be rerouted through IDH2-dependent citrate synthesis in support of hypoxic cell growth.

Some Cancer Cells Can Proliferate at 0.5% O2 Despite a Sharp Decline in Glucose-Dependent Citrate Synthesis.

At 21% O2, cancer cells have been shown to synthesize citrate by condensing glucose-derived acetyl-CoA with glutamine-derived oxaloacetate through the activity of the canonical TCA cycle enzyme citrate synthase (4). In contrast, less is known regarding the synthesis of citrate by cells that can continue proliferating in hypoxia. The glioblastoma cell line SF188 is able to proliferate at 0.5% O2 (Fig. 1A), a level of hypoxia that is sufficient to stabilize HIF1α (Fig. 1B) and predicted to limit respiration (1213). Consistent with previous observations in hypoxic cells, we found that SF188 cells demonstrated increased lactate production when incubated in hypoxia (Fig. 1C), and the ratio of lactate produced to glucose consumed increased demonstrating an increase in the rate of anaerobic glycolysis. When glucose-derived carbon in the form of pyruvate is converted to lactate, it is diverted away from subsequent metabolism that can contribute to citrate production. However, we observed that SF188 cells incubated in hypoxia maintain their intracellular citrate to ∼75% of the level maintained under normoxia (Fig. 1D). This prompted an investigation of how proliferating cells maintain citrate production under hypoxia.

SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis.

SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis.

http://www.pnas.org/content/108/49/19611/F1.medium.gif

Fig. 1. SF188 glioblastoma cells proliferate at 0.5% O2 despite a profound reduction in glucose-dependent citrate synthesis. (A) SF188 cells were plated in complete medium equilibrated with 21% O2 (Normoxia) or 0.5% O2 (Hypoxia), total viable cells were counted 24 h and 48 h later (Day 1 and Day 2), and population doublings were calculated. Data are the mean ± SEM of four independent experiments. (B) Western blot demonstrates stabilized HIF1α protein in cells cultured in hypoxia compared with normoxia. (C) Cells were grown in normoxia or hypoxia for 24 h, after which culture medium was collected. Medium glucose and lactate levels were measured and compared with the levels in fresh medium. (D) Cells were cultured for 24 h as in C. Intracellular metabolism was then quenched with 80% MeOH prechilled to −80 °C that was spiked with a 13C-labeled citrate as an internal standard. Metabolites were then extracted, and intracellular citrate levels were analyzed with GC-MS and normalized to cell number. Data for C and D are the mean ± SEM of three independent experiments. (E) Model depicting the pathway for cit+2 production from [U-13C]glucose. Glucose uniformly 13C-labeled will generate pyruvate+3. Pyruvate+3 can be oxidatively decarboxylated by PDH to produce acetyl-CoA+2, which can condense with unlabeled oxaloacetate to produce cit+2. (F) Cells were cultured for 24 h as in C and D, followed by an additional 4 h of culture in glucose-deficient medium supplemented with 10 mM [U-13C]glucose. Intracellular metabolites were then extracted, and 13C-enrichment in cellular citrate was analyzed by GC-MS and normalized to the total citrate pool size. Data are the mean ± SD of three independent cultures from a representative of two independent experiments. *P < 0.05, ***P < 0.001.

Increased glucose uptake and glycolytic metabolism are critical elements of the metabolic response to hypoxia. To evaluate the contributions made by glucose to the citrate pool under normoxia or hypoxia, SF188 cells incubated in normoxia or hypoxia were cultured in medium containing 10 mM [U-13C]glucose. Following a 4-h labeling period, cellular metabolites were extracted and analyzed for isotopic enrichment by gas chromatography-mass spectrometry (GC-MS). In normoxia, the major 13C-enriched citrate species found was citrate enriched with two 13C atoms (cit+2), which can arise from the NAD+-dependent decarboxylation of pyruvate+3 to acetyl-CoA+2 by PDH, followed by the condensation of acetyl-CoA+2 with unenriched oxaloacetate (Fig. 1 E and F). Compared with the accumulation of cit+2, we observed minimal accumulation of cit+3 and cit+5 under normoxia. Cit+3 arises from pyruvate carboxylase (PC)-dependent conversion of pyruvate+3 to oxaloacetate+3, followed by the condensation of oxaloacetate+3 with unenriched acetyl-CoA. Cit+5 arises when PC-generated oxaloacetate+3 condenses with PDH-generated acetyl-CoA+2. The lack of cit+3 and cit+5 accumulation is consistent with PC activity not playing a major role in citrate production in normoxic SF188 cells, as reported (4).

In hypoxic cells, the major citrate species observed was unenriched. Cit+2, cit+3, and cit+5 all constituted minor fractions of the total citrate pool, consistent with glucose carbon not being incorporated into citrate through either PDH or PC-mediated metabolism under hypoxic conditions (Fig. 1F). These data demonstrate that in contrast to normoxic cells, where a large percentage of citrate production depends on glucose-derived carbon, hypoxic cells significantly reduce their rate of citrate production from glucose.

Glutamine Carbon Metabolism Is Required for Viability in Hypoxia.

In addition to glucose, we have previously reported that glutamine can contribute to citrate production during cell growth under normoxic conditions (4). Surprisingly, under hypoxic conditions, we observed that SF188 cells retained their high rate of glutamine consumption (Fig. 2A). Moreover, hypoxic cells cultured in glutamine-deficient medium displayed a significant loss of viability (Fig. 2B). In normoxia, the requirement for glutamine to maintain viability of SF188 cells can be satisfied by α-ketoglutarate, the downstream metabolite of glutamine that is devoid of nitrogenous groups (14). α-ketoglutarate cannot fulfill glutamine’s roles as a nitrogen source for nonessential amino acid synthesis or as an amide donor for nucleotide or hexosamine synthesis, but can be metabolized through the oxidative TCA cycle to regenerate oxaloacetate, and subsequently condense with glucose-derived acetyl-CoA to produce citrate. To test whether the restoration of carbon from glutamine metabolism in the form of α-ketoglutarate could rescue the viability defect of glutamine-starved SF188 cells even under hypoxia, SF188 cells incubated in hypoxia were cultured in glutamine-deficient medium supplemented with a cell-penetrant form of α-ketoglutarate (dimethyl α-ketoglutarate). The addition of dimethyl α-ketoglutarate rescued the defect in cell viability observed upon glutamine withdrawal (Fig. 2B). These data demonstrate that, even under hypoxic conditions, when the ability of glutamine to replenish oxaloacetate through oxidative TCA cycle metabolism is diminished, SF188 cells retain their requirement for glutamine as the carbon backbone for α-ketoglutarate. This result raised the possibility that glutamine could be the carbon source for citrate production through an alternative, nonoxidative, pathway in hypoxia.

Glutamine carbon is required for hypoxic cell viability

Glutamine carbon is required for hypoxic cell viability

Glutamine carbon is required for hypoxic cell viability

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Fig. 2. Glutamine carbon is required for hypoxic cell viability and contributes to increased citrate production through reductive carboxylation relative to oxidative metabolism in hypoxia. (A) SF188 cells were cultured for 24 h in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2(Hypoxia). Culture medium was then removed from cells and analyzed for glutamine levels which were compared with the glutamine levels in fresh medium. Data are the mean ± SEM of three independent experiments. (B) The requirement for glutamine to maintain hypoxic cell viability can be satisfied by α-ketoglutarate. Cells were cultured in complete medium equilibrated with 0.5% O2 for 24 h, followed by an additional 48 h at 0.5% O2 in either complete medium (+Gln), glutamine-deficient medium (−Gln), or glutamine-deficient medium supplemented with 7 mM dimethyl α-ketoglutarate (−Gln +αKG). All medium was preconditioned in 0.5% O2. Cell viability was determined by trypan blue dye exclusion. Data are the mean and range from two independent experiments. (C) Model depicting the pathways for cit+4 and cit+5 production from [U-13C]glutamine (glutamine+5). Glutamine+5 is catabolized to α-ketoglutarate+5, which can then contribute to citrate production by two divergent pathways. Oxidative metabolism produces oxaloacetate+4, which can condense with unlabeled acetyl-CoA to produce cit+4. Alternatively, reductive carboxylation produces isocitrate+5, which can isomerize to cit+5. (D) Glutamine contributes to citrate production through increased reductive carboxylation relative to oxidative metabolism in hypoxic proliferating cancer cells. Cells were cultured for 24 h as in A, followed by 4 h of culture in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. 13C enrichment in cellular citrate was quantitated with GC-MS. Data are the mean ± SD of three independent cultures from a representative of three independent experiments. **P < 0.01.

Cells Proliferating in Hypoxia Maintain Levels of Additional Metabolites Through Reductive Carboxylation.

Previous work has documented that, in normoxic conditions, SF188 cells use glutamine as the primary anaplerotic substrate, maintaining the pool sizes of TCA cycle intermediates through oxidative metabolism (4). Surprisingly, we found that, when incubated in hypoxia, SF188 cells largely maintained their levels of aspartate (in equilibrium with oxaloacetate), malate, and fumarate (Fig. 3A). To distinguish how glutamine carbon contributes to these metabolites in normoxia and hypoxia, SF188 cells incubated in normoxia or hypoxia were cultured in medium containing 4 mM [U-13C]glutamine. After a 4-h labeling period, metabolites were extracted and the intracellular pools of aspartate, malate, and fumarate were analyzed by GC-MS.

In normoxia, the majority of the enriched intracellular asparatate, malate, and fumarate were the +4 species, which arise through oxidative metabolism of glutamine-derived α-ketoglutarate (Fig. 3 B and C). The +3 species, which can be derived from the citrate generated by the reductive carboxylation of glutamine-derived α-ketoglutarate, constituted a significantly lower percentage of the total aspartate, malate, and fumarate pools. By contrast, in hypoxia, the +3 species constituted a larger percentage of the total aspartate, malate, and fumarate pools than they did in normoxia. These data demonstrate that, in addition to citrate, hypoxic cells preferentially synthesize oxaloacetate, malate, and fumarate through the pathway of reductive carboxylation rather than the oxidative TCA cycle.

IDH2 Is Critical in Hypoxia for Reductive Metabolism of Glutamine and for Cell Proliferation.

We hypothesized that the relative increase in reductive carboxylation we observed in hypoxia could arise from the suppression of α-ketoglutarate oxidation through the TCA cycle. Consistent with this, we found that α-ketoglutarate levels increased in SF188 cells following 24 h in hypoxia (Fig. 4A). Surprisingly, we also found that levels of the closely related metabolite 2-hydroxyglutarate (2HG) increased in hypoxia, concomitant with the increase in α-ketoglutarate under these conditions. 2HG can arise from the noncarboxylating reduction of α-ketoglutarate (Fig. 4B). Recent work has found that specific cancer-associated mutations in the active sites of either IDH1 or IDH2 lead to a 10- to 100-fold enhancement in this activity facilitating 2HG production (1517), but SF188 cells lack IDH1/2 mutations. However, 2HG levels are also substantially elevated in the inborn error of metabolism 2HG aciduria, and the majority of patients with this disease lack IDH1/2 mutations. As 2HG has been demonstrated to arise in these patients from mitochondrial α-ketoglutarate (18), we hypothesized that both the increased reductive carboxylation of glutamine-derived α-ketoglutarate to citrate and the increased 2HG accumulation we observed in hypoxia could arise from increased reductive metabolism by wild-type IDH2 in the mitochondria.

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2

http://www.pnas.org/content/108/49/19611/F4.medium.gif

Fig. 4. Reductive carboxylation of glutamine-derived α-ketoglutarate to citrate in hypoxic cancer cells is dependent on mitochondrial IDH2. (A) α-ketoglutarate and 2HG increase in hypoxia. SF188 cells were cultured in complete medium equilibrated with either 21% O2 (Normoxia) or 0.5% O2 (Hypoxia) for 24 h. Intracellular metabolites were then extracted, cell extracts spiked with a 13C-labeled citrate as an internal standard, and intracellular α-ketoglutarate and 2HG levels were analyzed with GC-MS. Data shown are the mean ± SEM of three independent experiments. (B) Model for reductive metabolism from glutamine-derived α-ketoglutarate. Glutamine+5 is catabolized to α-ketoglutarate+5. Carboxylation of α-ketoglutarate+5 followed by reduction of the carboxylated intermediate (reductive carboxylation) will produce isocitrate+5, which can then isomerize to cit+5. In contrast, reductive activity on α-ketoglutarate+5 that is uncoupled from carboxylation will produce 2HG+5. (C) IDH2 is required for reductive metabolism of glutamine-derived α-ketoglutarate in hypoxia. SF188 cells transfected with a siRNA against IDH2 (siIDH2) or nontargeting negative control (siCTRL) were cultured for 2 d in complete medium equilibrated with 0.5% O2. (Upper) Cells were then cultured at 0.5% O2 for an additional 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. 13C enrichment in intracellular citrate and 2HG was determined and normalized to the relevant metabolite total pool size. (Lower) Cells transfected and cultured in parallel at 0.5% O2 were counted by hemacytometer (excluding nonviable cells with trypan blue staining) or harvested for protein to assess IDH2 expression by Western blot. Data shown for GC-MS and cell counts are the mean ± SD of three independent cultures from a representative experiment. **P < 0.01, ***P < 0.001.

In an experiment to test this hypothesis, SF188 cells were transfected with either siRNA directed against mitochondrial IDH2 (siIDH2) or nontargeting control, incubated in hypoxia for 2 d, and then cultured for another 4 h in hypoxia in media containing 4 mM [U-13C]glutamine. After the labeling period, metabolites were extracted and analyzed by GC-MS (Fig. 4C). Hypoxic SF188 cells transfected with siIDH2 displayed a decreased contribution of cit+5 to the total citrate pool, supporting an important role for IDH2 in the reductive carboxylation of glutamine-derived α-ketoglutarate in hypoxic conditions. The contribution of cit+4 to the total citrate pool did not decrease with siIDH2 treatment, consistent with IDH2 knockdown specifically affecting the pathway of reductive carboxylation and not other fundamental TCA cycle-regulating processes. In confirmation of reverse flux occurring through IDH2, the contribution of 2HG+5 to the total 2HG pool decreased in siIDH2-treated cells. Supporting the importance of citrate production by IDH2-mediated reductive carboxylation for hypoxic cell proliferation, siIDH2-transfected SF188 cells displayed a defect in cellular accumulation in hypoxia. Decreased expression of IDH2 protein following siIDH2 transfection was confirmed by Western blot. Collectively, these data point to the importance of mitochondrial IDH2 for the increase in reductive carboxylation flux of glutamine-derived α-ketoglutarate to maintain citrate levels in hypoxia, and to the importance of this reductive pathway for hypoxic cell proliferation.

Reprogramming of Metabolism by HIF1 in the Absence of Hypoxia Is Sufficient to Induce Increased Citrate Synthesis by Reductive Carboxylation Relative to Oxidative Metabolism.

The relative increase in the reductive metabolism of glutamine-derived α-ketoglutarate at 0.5% O2 may be explained by the decreased ability to carry out oxidative NAD+-dependent reactions as respiration is inhibited (1213). However, a shift to preferential reductive glutamine metabolism could also result from the active reprogramming of cellular metabolism by HIF1 (810), which inhibits the generation of mitochondrial acetyl-CoA necessary for the synthesis of citrate by oxidative glucose and glutamine metabolism (Fig. 5A). To better understand the role of HIF1 in reductive glutamine metabolism, we used VHL-deficient RCC4 cells, which display constitutive expression of HIF1α under normoxia (Fig. 5B). RCC4 cells expressing either a nontargeting control shRNA (shCTRL) or an shRNA directed at HIF1α (shHIF1α) were incubated in normoxia and cultured in medium with 4 mM [U-13C]glutamine. Following a 4-h labeling period, metabolites were extracted and the cellular citrate pool was analyzed by GC-MS. In shCTRL cells, which have constitutive HIF1α expression despite incubation in normoxia, the majority of the total citrate pool was constituted by the cit+5 species, with low levels of all other species including cit+4 (Fig. 5C). By contrast, in HIF1α-deficient cells the contribution of cit+5 to the total citrate pool was greatly decreased, whereas the contribution of cit+4 to the total citrate pool increased and was the most abundant citrate species. These data demonstrate that the relative enhancement of the reductive carboxylation pathway for citrate synthesis can be recapitulated by constitutive HIF1 activation in normoxia.

Reprogramming of metabolism by HIF1 in the absence of hypoxia

Reprogramming of metabolism by HIF1 in the absence of hypoxia

http://www.pnas.org/content/108/49/19611/F5.medium.gif

Reprogramming of metabolism by HIF1 in the absence of hypoxia is sufficient to induce reductive carboxylation of glutamine-derived α-ketoglutarate.

Fig. 5. Reprogramming of metabolism by HIF1 in the absence of hypoxia is sufficient to induce reductive carboxylation of glutamine-derived α-ketoglutarate. (A) Model depicting how HIF1 signaling’s inhibition of pyruvate dehydrogenase (PDH) activity and promotion of lactate dehydrogenase-A (LDH-A) activity can block the generation of mitochondrial acetyl-CoA from glucose-derived pyruvate, thereby favoring citrate synthesis from reductive carboxylation of glutamine-derived α-ketoglutarate. (B) Western blot demonstrating HIF1α protein in RCC4 VHL−/− cells in normoxia with a nontargeting shRNA (shCTRL), and the decrease in HIF1α protein in RCC4 VHL−/− cells stably expressing HIF1α shRNA (shHIF1α). (C) HIF1-induced reprogramming of glutamine metabolism. Cells from B at 21% O2 were cultured for 4 h in glutamine-deficient medium supplemented with 4 mM [U-13C]glutamine. Intracellular metabolites were then extracted, and 13C enrichment in cellular citrate was determined by GC-MS. Data shown are the mean ± SD of three independent cultures from a representative of three independent experiments. ***P < 0.001.

Compared with glucose metabolism, much less is known regarding how glutamine metabolism is altered under hypoxia. It has also remained unclear how hypoxic cells can maintain the citrate production necessary for macromolecular biosynthesis. In this report, we demonstrate that in contrast to cells at 21% O2, where citrate is predominantly synthesized through oxidative metabolism of both glucose and glutamine, reductive carboxylation of glutamine carbon becomes the major pathway of citrate synthesis in cells that can effectively proliferate at 0.5% O2. Moreover, we show that in these hypoxic cells, reductive carboxylation of glutamine-derived α-ketoglutarate is dependent on mitochondrial IDH2. Although others have previously suggested the existence of reductive carboxylation in cancer cells (1920), these studies failed to demonstrate the intracellular localization or specific IDH isoform responsible for the reductive carboxylation flux. Recently, we identified IDH2 as an isoform that contributes to reductive carboxylation in cancer cells incubated at 21% O2 (16), but remaining unclear were the physiological importance and regulation of this pathway relative to oxidative metabolism, as well as the conditions where this reductive pathway might be advantageous for proliferating cells.

Here we report that IDH2-mediated reductive carboxylation of glutamine-derived α-ketoglutarate to citrate is an important feature of cells proliferating in hypoxia. Moreover, the reliance on reductive glutamine metabolism can be recapitulated in normoxia by constitutive HIF1 activation in cells with loss of VHL. The mitochondrial NADPH/NADP+ ratio required to fuel the reductive reaction through IDH2 can arise from the increased NADH/NAD+ ratio existing in the mitochondria under hypoxic conditions (2122), with the transfer of electrons from NADH to NADP+ to generate NADPH occurring through the activity of the mitochondrial transhydrogenase (23). Our data do not exclude a complementary role for cytosolic IDH1 in impacting reductive glutamine metabolism, potentially through its oxidative function in an IDH2/IDH1 shuttle that transfers high energy electrons in the form of NADPH from mitochondria to cytosol (1624).

In further support of the increased mitochondrial reductive glutamine metabolism that we observe in hypoxia, we report here that incubation in hypoxia can lead to elevated 2HG levels in cells lacking IDH1/2 mutations. 2HG production from glutamine-derived α-ketoglutarate significantly decreased with knockdown of IDH2, supporting the conclusion that 2HG is produced in hypoxia by enhanced reverse flux of α-ketoglutarate through IDH2 in a truncated, noncarboxylating reductive reaction. However, other mechanisms may also contribute to 2HG elevation in hypoxia. These include diminished oxidative activity and/or enhanced reductive activity of the 2HG dehydrogenase, a mitochondrial enzyme that normally functions to oxidize 2HG back to α-ketoglutarate (25). The level of 2HG elevation we observe in hypoxic cells is associated with a concomitant increase in α-ketoglutarate, and is modest relative to that observed in cancers with IDH1/2 gain-of-function mutations. Nonetheless, 2HG elevation resulting from hypoxia in cells with wild-type IDH1/2 may hold promise as a cellular or serum biomarker for tissues undergoing chronic hypoxia and/or excessive glutamine metabolism.

The IDH2-dependent reductive carboxylation pathway that we propose in this report allows for continued citrate production from glutamine carbon when hypoxia and/or HIF1 activation prevents glucose carbon from contributing to citrate synthesis. Moreover, as opposed to continued oxidative TCA cycle functioning in hypoxia which can increase reactive oxygen species (ROS), reductive carboxylation of α-ketoglutarate in the mitochondria may serve as an electron sink that decreases the generation of ROS. HIF1 activity is not limited to the setting of hypoxia, as a common feature of several cancers is the normoxic stabilization of HIF1α through loss of the VHL tumor suppressor or other mechanisms. We demonstrate here that altered glutamine metabolism through a mitochondrial reductive pathway is a central aspect of hypoxic proliferating cell metabolism and HIF1-induced metabolic reprogramming. These findings are relevant for the understanding of numerous constitutive HIF1-expressing malignancies, as well as for populations, such as stem progenitor cells, which frequently proliferate in hypoxic conditions.

7.9.3 Hypoxia-Inducible Factors in Physiology and Medicine

Gregg L. Semenza
Cell. 2012 Feb 3; 148(3): 399–408.
http://dx.doi.org/10.1016%2Fj.cell.2012.01.021

Oxygen homeostasis represents an organizing principle for understanding metazoan evolution, development, physiology, and pathobiology. The hypoxia-inducible factors (HIFs) are transcriptional activators that function as master regulators of oxygen homeostasis in all metazoan species. Rapid progress is being made in elucidating homeostatic roles of HIFs in many physiological systems, determining pathological consequences of HIF dysregulation in chronic diseases, and investigating potential targeting of HIFs for therapeutic purposes. Oxygen homeostasis represents an organizing principle for understanding metazoan evolution, development, physiology, and pathobiology. The hypoxia-inducible factors (HIFs) are transcriptional activators that function as master regulators of oxygen homeostasis in all metazoan species. Rapid progress is being made in elucidating homeostatic roles of HIFs in many physiological systems, determining pathological consequences of HIF dysregulation in chronic diseases, and investigating potential targeting of HIFs for therapeutic purposes.

 

Oxygen is central to biology because of its utilization in the process of respiration. O2 serves as the final electron acceptor in oxidative phosphorylation, which carries with it the risk of generating reactive oxygen species (ROS) that react with cellular macromolecules and alter their biochemical or physical properties, resulting in cell dysfunction or death. As a consequence, metazoan organisms have evolved elaborate cellular metabolic and systemic physiological systems that are designed to maintain oxygen homeostasis. This review will focus on the role of hypoxia-inducible factors (HIFs) as master regulators of oxygen homeostasis and, in particular, on recent advances in understanding their roles in physiology and medicine. Due to space limitations and the remarkably pleiotropic effects of HIFs, the description of such roles will be illustrative rather than comprehensive.

O2 and Evolution, Part 1

Accumulation of O2 in Earth’s atmosphere starting ~2.5 billion years ago led to evolution of the extraordinarily efficient system of oxidative phosphorylation that transfers chemical energy stored in carbon bonds of organic molecules to the high-energy phosphate bond in ATP, which is used to power physicochemical reactions in living cells. Energy produced by mitochondrial respiration is sufficient to power the development and maintenance of multicellular organisms, which could not be sustained by energy produced by glycolysis alone (Lane and Martin, 2010). The modest dimensions of primitive metazoan species were such that O2 could diffuse from the atmosphere to all of the organism’s thousand cells, as is the case for the worm Caenorhabditis elegans. To escape the constraints placed on organismal growth by diffusion, systems designed to conduct air to cells deep within the body evolved and were sufficient for O2delivery to organisms with hundreds of thousands of cells, such as the fly Drosophila melanogaster. The final leap in body scale occurred in vertebrates and was associated with the evolution of complex respiratory, circulatory, and nervous systems designed to efficiently capture and distribute O2 to hundreds of millions of millions of cells in the case of the adult Homo sapiens.

Hypoxia-Inducible Factors

Hypoxia-inducible factor 1 (HIF-1) is expressed by all extant metazoan species analyzed (Loenarz et al., 2011). HIF-1 consists of HIF-1α and HIF-1β subunits, which each contain basic helix-loop-helix-PAS (bHLH-PAS) domains (Wang et al., 1995) that mediate heterodimerization and DNA binding (Jiang et al., 1996a). HIF-1β heterodimerizes with other bHLH-PAS proteins and is present in excess, such that HIF-1α protein levels determine HIF-1 transcriptional activity (Semenza et al., 1996).

Under well-oxygenated conditions, HIF-1α is bound by the von Hippel-Lindau (VHL) protein, which recruits an ubiquitin ligase that targets HIF-1α for proteasomal degradation (Kaelin and Ratcliffe, 2008). VHL binding is dependent upon hydroxylation of a specific proline residue in HIF-1α by the prolyl hydroxylase PHD2, which uses O2 as a substrate such that its activity is inhibited under hypoxic conditions (Epstein et al., 2001). In the reaction, one oxygen atom is inserted into the prolyl residue and the other atom is inserted into the co-substrate α-ketoglutarate, splitting it into CO2 and succinate (Kaelin and Ratcliffe, 2008). Factor inhibiting HIF-1 (FIH-1) represses HIF-1α transactivation function (Mahon et al., 2001) by hydroxylating an asparaginyl residue, using O2 and α-ketoglutarate as substrates, thereby blocking the association of HIF-1α with the p300 coactivator protein (Lando et al., 2002). Dimethyloxalylglycine (DMOG), a competitive antagonist of α-ketoglutarate, inhibits the hydroxylases and induces HIF-1-dependent transcription (Epstein et al., 2001). HIF-1 activity is also induced by iron chelators (such as desferrioxamine) and cobalt chloride, which inhibit hydroxylases by displacing Fe(II) from the catalytic center (Epstein et al., 2001).

Studies in cultured cells (Jiang et al., 1996b) and isolated, perfused, and ventilated lung preparations (Yu et al., 1998) revealed an exponential increase in HIF-1α levels at O2 concentrations less than 6% (~40 mm Hg), which is not explained by known biochemical properties of the hydroxylases. In most adult tissues, O2concentrations are in the range of 3-5% and any decrease occurs along the steep portion of the dose-response curve, allowing a graded response to hypoxia. Analyses of cultured human cells have revealed that expression of hundreds of genes was increased in response to hypoxia in a HIF-1-dependent manner (as determined by RNA interference) with direct binding of HIF-1 to the gene (as determined by chromatin immunoprecipitation [ChIP] assays); in addition, the expression of hundreds of genes was decreased in response to hypoxia in a HIF-1-dependent manner but binding of HIF-1 to these genes was not detected (Mole et al., 2009), indicating that HIF-dependent repression occurs via indirect mechanisms, which include HIF-1-dependent expression of transcriptional repressors (Yun et al., 2002) and microRNAs (Kulshreshtha et al., 2007). ChIP-seq studies have revealed that only 40% of HIF-1 binding sites are located within 2.5 kb of the transcription start site (Schödel et al., 2011).

In vertebrates, HIF-2α is a HIF-1α paralog that is also regulated by prolyl and asparaginyl hydroxylation and dimerizes with HIF-1β, but is expressed in a cell-restricted manner and plays important roles in erythropoiesis, vascularization, and pulmonary development, as described below. In D. melanogaster, the gene encoding the HIF-1α ortholog is designated similar and its paralog is designated trachealess because inactivating mutations result in defective development of the tracheal tubes (Wilk et al., 1996). In contrast, C. elegans has only a single HIF-1α homolog (Epstein et al., 2001). Thus, in both invertebrates and vertebrates, evolution of specialized systems for O2 delivery was associated with the appearance of a HIF-1α paralog.

O2 and Metabolism

The regulation of metabolism is a principal and primordial function of HIF-1. Under hypoxic conditions, HIF-1 mediates a transition from oxidative to glycolytic metabolism through its regulation of: PDK1, encoding pyruvate dehydrogenase (PDH) kinase 1, which phosphorylates and inactivates PDH, thereby inhibiting the conversion of pyruvate to acetyl coenzyme A for entry into the tricarboxylic acid cycle (Kim et al., 2006Papandreou et al., 2006); LDHA, encoding lactate dehydrogenase A, which converts pyruvate to lactate (Semenza et al. 1996); and BNIP3 (Zhang et al. 2008) and BNIP3L (Bellot et al., 2009), which mediate selective mitochondrial autophagy (Figure 1). HIF-1 also mediates a subunit switch in cytochrome coxidase that improves the efficiency of electron transfer under hypoxic conditions (Fukuda et al., 2007). An analogous subunit switch is also observed in Saccharomyces cerevisiae, although it is mediated by a completely different mechanism (yeast lack HIF-1), suggesting that it may represent a fundamental response of eukaryotic cells to hypoxia.

Regulation of Glucose Metabolism nihms-350382-f0001

Regulation of Glucose Metabolism nihms-350382-f0001

Regulation of Glucose Metabolism

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3437543/bin/nihms-350382-f0001.gif
Figure 1
Regulation of Glucose Metabolism

It is conventional wisdom that cells switch to glycolysis when O2 becomes limiting for mitochondrial ATP production. Yet, HIF-1α-null mouse embryo fibroblasts, which do not down-regulate respiration under hypoxic conditions, have higher ATP levels at 1% O2 than wild-type cells at 20% O2, demonstrating that under these conditions O2 is not limiting for ATP production (Zhang et al., 2008). However, the HIF-1α-null cells die under prolonged hypoxic conditions due to ROS toxicity (Kim et al. 2006Zhang et al., 2008). These studies have led to a paradigm shift with regard to our understanding of the regulation of cellular metabolism (Semenza, 2011): the purpose of this switch is to prevent excess mitochondrial generation of ROS that would otherwise occur due to the reduced efficiency of electron transfer under hypoxic conditions (Chandel et al., 1998). This may be particularly important in stem cells, in which avoidance of DNA damage is critical (Suda et al., 2011).

Role of HIFs in Development

Much of mammalian embryogenesis occurs at O2 concentrations of 1-5% and O2 functions as a morphogen (through HIFs) in many developmental systems (Dunwoodie, 2009). Mice that are homozygous for a null allele at the locus encoding HIF-1α die by embryonic day 10.5 with cardiac malformations, vascular defects, and impaired erythropoiesis, indicating that all three components of the circulatory system are dependent upon HIF-1 for normal development (Iyer et al., 1998Yoon et al., 2011). Depending on the genetic background, mice lacking HIF-2α: die by embryonic day 12.5 with vascular defects (Peng et al., 2000) or bradycardia due to deficient catecholamine production (Tian et al., 1998); die as neonates due to impaired lung maturation (Compernolle et al., 2002); or die several months after birth due to ROS-mediated multi-organ failure (Scortegagna et al., 2003). Thus, while vertebrate evolution was associated with concomitant appearance of the circulatory system and HIF-2α, both HIF-1 and HIF-2 have important roles in circulatory system development. Conditional knockout of HIF-1α in specific cell types has demonstrated important roles in chondrogenesis (Schipani et al., 2001), adipogenesis (Yun et al., 2002), B-lymphocyte development (Kojima et al., 2002), osteogenesis (Wang et al., 2007), hematopoiesis (Takubo et al., 2010), T-lymphocyte differentiation (Dang et al., 2011), and innate immunity (Zinkernagel et al., 2007). While knockout mouse experiments point to the adverse effects of HIF-1 loss-of-function on development, it is also possible that increased HIF-1 activity, induced by hypoxia in embryonic tissues as a result of abnormalities in placental blood flow, may also dysregulate development and result in congenital malformations. For example, HIF-1α has been shown to interact with, and stimulate the transcriptional activity of, Notch, which plays a key role in many developmental pathways (Gustafsson et al., 2005).

Translational Prospects

Drug discovery programs have been initiated at many pharmaceutical and biotech companies to develop prolyl hydroxylase inhibitors (PHIs) that, as described above for DMOG, induce HIF activity for treatment of disorders in which HIF mediates protective physiological responses. Local and/or short term induction of HIF activity by PHIs, gene therapy, or other means are likely to be useful novel therapies for many of the diseases described above. In the case of ischemic cardiovascular disease, local therapy is needed to provide homing signals for the recruitment of BMDACs. Chronic systemic use of PHIs must be approached with great caution: individuals with genetic mutations that constitutively activate the HIF pathway (described below) have increased incidence of cardiovascular disease and mortality (Yoon et al., 2011). On the other hand, the profound inhibition of HIF activity and vascular responses to ischemia that are associated with aging suggest that systemic replacement therapy might be contemplated as a preventive measure for subjects in whom impaired HIF responses to hypoxia can be documented. In C. elegans, VHL loss-of-function increases lifespan in a HIF-1-dependent manner (Mehta et al., 2009), providing further evidence for a mutually antagonistic relationship between HIF-1 and aging.

Cancer

Cancers contain hypoxic regions as a result of high rates of cell proliferation coupled with the formation of vasculature that is structurally and functionally abnormal. Increased HIF-1α and/or HIF-2α levels in diagnostic tumor biopsies are associated with increased risk of mortality in cancers of the bladder, brain, breast, colon, cervix, endometrium, head/neck, lung, ovary, pancreas, prostate, rectum, and stomach; these results are complemented by experimental studies, which demonstrate that genetic manipulations that increase HIF-1α expression result in increased tumor growth, whereas loss of HIF activity results in decreased tumor growth (Semenza, 2010). HIFs are also activated by genetic alterations, most notably, VHL loss of function in clear cell renal carcinoma (Majmunder et al., 2010). HIFs activate transcription of genes that play key roles in critical aspects of cancer biology, including stem cell maintenance (Wang et al., 2011), cell immortalization, epithelial-mesenchymal transition (Mak et al., 2010), genetic instability (Huang et al., 2007), vascularization (Liao and Johnson, 2007), glucose metabolism (Luo et al., 2011), pH regulation (Swietach et al., 2007), immune evasion (Lukashev et al., 2007), invasion and metastasis (Chan and Giaccia, 2007), and radiation resistance (Moeller et al., 2007). Given the extensive validation of HIF-1 as a potential therapeutic target, drugs that inhibit HIF-1 have been identified and shown to have anti-cancer effects in xenograft models (Table 1Semenza, 2010).

Table 1  Drugs that Inhibit HIF-1

Process Inhibited Drug Class Prototype
HIF-1 α synthesis Cardiac glycosidemTOR inhibitorMicrotubule targeting agent

Topoisomerase I inhibitor

DigoxinRapamycin2-Methoxyestradiol

Topotecan

HIF-1 α protein stability HDAC inhibitorHSP90 inhibitorCalcineurin inhibitor

Guanylate cyclase activator

LAQ82417-AAGCyclosporine

YC-1

Heterodimerization Antimicrobial agent Acriflavine
DNA binding AnthracyclineQuinoxaline antibiotic DoxorubicinEchinomycin
Transactivation Proteasome inhibitorAntifungal agent BortezomibAmphotericin B
Signal transduction BCR-ABL inhibitorCyclooxygenase inhibitorEGFR inhibitor

HER2 inhibitor

ImatinibIbuprofenErlotinib, Gefitinib

Trastuzumab

Over 100 women die every day of breast cancer in the U.S. The mean PO2 is 10 mm Hg in breast cancer as compared to > 60 mm Hg in normal breast tissue and cancers with PO2 < 10 mm Hg are associated with increased risk of metastasis and patient mortality (Vaupel et al., 2004). Increased HIF-1α protein levels, as identified by immunohistochemical analysis of tumor biopsies, are associated with increased risk of metastasis and/or patient mortality in unselected breast cancer patients and in lymph node-positive, lymph node-negative, HER2+, or estrogen receptor+ subpopulations (Semenza, 2011). Metastasis is responsible for > 90% of breast cancer mortality. The requirement for HIF-1 in breast cancer metastasis has been demonstrated for both autochthonous tumors in transgenic mice (Liao et al., 2007) and orthotopic transplants in immunodeficient mice (Zhang et al., 2011Wong et al., 2011). Primary tumors direct the recruitment of bone marrow-derived cells to the lungs and other sites of metastasis (Kaplan et al., 2005). In breast cancer, hypoxia induces the expression of lysyl oxidase (LOX), a secreted protein that remodels collagen at sites of metastatic niche formation (Erler et al., 2009). In addition to LOX, breast cancers also express LOX-like proteins 2 and 4. LOX, LOXL2, and LOXL4 are all HIF-1-regulated genes and HIF-1 inhibition blocks metastatic niche formation regardless of which LOX/LOXL protein is expressed, whereas available LOX inhibitors are not effective against all LOXL proteins (Wong et al., 2011), again illustrating the role of HIF-1 as a master regulator that controls the expression of multiple genes involved in a single (patho)physiological process.

Translational Prospects

Small molecule inhibitors of HIF activity that have anti-cancer effects in mouse models have been identified (Table 1). Inhibition of HIF impairs both vascular and metabolic adaptations to hypoxia, which may decrease O2 delivery and increase O2 utilization. These drugs are likely to be useful (as components of multidrug regimens) in the treatment of a subset of cancer patients in whom high HIF activity is driving progression. As with all novel cancer therapeutics, successful translation will require the development of methods for identifying the appropriate patient cohort. Effects of combination drug therapy also need to be considered. VEGF receptor tyrosine kinase inhibitors, which induce tumor hypoxia by blocking vascularization, have been reported to increase metastasis in mouse models (Ebos et al., 2009), which may be mediated by HIF-1; if so, combined use of HIF-1 inhibitors with these drugs may prevent unintended counter-therapeutic effects.

HIF inhibitors may also be useful in the treatment of other diseases in which dysregulated HIF activity is pathogenic. Proof of principle has been established in mouse models of ocular neovascularization, a major cause of blindness in the developed world, in which systemic or intraocular injection of the HIF-1 inhibitor digoxin is therapeutic (Yoshida et al., 2010). Systemic administration of HIF inhibitors for cancer therapy would be contraindicated in patients who also have ischemic cardiovascular disease, in which HIF activity is protective. The analysis of SNPs at the HIF1A locus described above suggests that the population may include HIF hypo-responders, who are at increased risk of severe ischemic cardiovascular disease. It is also possible that HIF hyper-responders, such as individuals with hereditary erythrocytosis, are at increased risk of particularly aggressive cancer.

O2 and Evolution, Part 2

When lowlanders sojourn to high altitude, hypobaric hypoxia induces erythropoiesis, which is a relatively ineffective response because the problem is not insufficient red cells, but rather insufficient ambient O2. Chronic erythrocytosis increases the risk of heart attack, stroke, and fetal loss during pregnancy. Many high-altitude Tibetans maintain the same hemoglobin concentration as lowlanders and yet, despite severe hypoxemia, they also maintain aerobic metabolism. The basis for this remarkable evolutionary adaptation appears to have involved the selection of genetic variants at multiple loci encoding components of the oxygen sensing system, particularly HIF-2α (Beall et al., 2010Simonson et al., 2010Yi et al., 2010). Given that hereditary erythrocytosis is associated with modest HIF-2α gain-of-function, the Tibetan genotype associated with absence of an erythrocytotic response to hypoxia may encode reduced HIF-2α activity along with other alterations that increase metabolic efficiency. Delineating the molecular mechanisms underlying these metabolic adaptations may lead to novel therapies for ischemic disorders, illustrating the importance of oxygen homeostasis as a nexus where evolution, biology, and medicine converge.

7.9.4 Hypoxia-inducible factor 1. Regulator of mitochondrial metabolism and mediator of ischemic preconditioning

Semenza GL1.
Biochim Biophys Acta. 2011 Jul; 1813(7):1263-8.
http://dx.doi.org/10.1016%2Fj.bbamcr.2010.08.006

Hypoxia-inducible factor 1 (HIF-1) mediates adaptive responses to reduced oxygen availability by regulating gene expression. A critical cell-autonomous adaptive response to chronic hypoxia controlled by HIF-1 is reduced mitochondrial mass and/or metabolism. Exposure of HIF-1-deficient fibroblasts to chronic hypoxia results in cell death due to excessive levels of reactive oxygen species (ROS). HIF-1 reduces ROS production under hypoxic conditions by multiple mechanisms including: a subunit switch in cytochrome c oxidase from the COX4-1 to COX4-2 regulatory subunit that increases the efficiency of complex IV; induction of pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; induction of BNIP3, which triggers mitochondrial selective autophagy; and induction of microRNA-210, which blocks assembly of Fe/S clusters that are required for oxidative phosphorylation. HIF-1 is also required for ischemic preconditioning and this effect may be due in part to its induction of CD73, the enzyme that produces adenosine. HIF-1-dependent regulation of mitochondrial metabolism may also contribute to the protective effects of ischemic preconditioning.

The story of life on Earth is a tale of oxygen production and utilization. Approximately 3 billion years ago, primitive single-celled organisms evolved the capacity for photosynthesis, a biochemical process in which photons of solar energy are captured by chlorophyll and used to power the reaction of CO2 and H2O to form glucose and O2. The subsequent rise in the atmospheric O2 concentration over the next billion years set the stage for the ascendance of organisms with the capacity for respiration, a process that consumes glucose and O2 and generates CO2, H2O, and energy in the form of ATP. Some of these single-celled organisms eventually took up residence within the cytoplasm of other cells and devoted all of their effort to energy production as mitochondria. Compared to the conversion of glucose to lactate by glycolysis, the complete oxidation of glucose by respiration provided such a large increase in energy production that it made possible the evolution of multicellular organisms. Among metazoan organisms, the progressive increase in body size during evolution was accompanied by progressively more complex anatomic structures that function to ensure the adequate delivery of O2 to all cells, ultimately resulting in the sophisticated circulatory and respiratory systems of vertebrates.

All metazoan cells can sense and respond to reduced O2 availability (hypoxia). Adaptive responses to hypoxia can be cell autonomous, such as the alterations in mitochondrial metabolism that are described below, or non-cell-autonomous, such as changes in tissue vascularization (reviewed in ref. 1). Primary responses to hypoxia need to be distinguished from secondary responses to sequelae of hypoxia, such as the adaptive responses to ATP depletion that are mediated by AMP kinase (reviewed in ref 2). In contrast, recent data suggest that O2 and redox homeostasis are inextricably linked and that changes in oxygenation are inevitably associated with changes in the levels of reactive oxygen species (ROS), as will be discussed below.

HIF-1 Regulates Oxygen Homeostasis in All Metazoan Species

A key regulator of the developmental and physiological networks required for the maintenance of O2homeostasis is hypoxia-inducible factor 1 (HIF-1). HIF-1 is a heterodimeric transcription factor that is composed of an O2-regulated HIF-1α subunit and a constitutively expressed HIF-1β subunit [3,4]. HIF-1 regulates the expression of hundreds of genes through several major mechanisms. First, HIF-1 binds directly to hypoxia response elements, which are cis-acting DNA sequences located within target genes [5]. The binding of HIF-1 results in the recruitment of co-activator proteins that activate gene transcription (Fig. 1A). Only rarely does HIF-1 binding result in transcriptional repression [6]. Instead, HIF-1 represses gene expression by indirect mechanisms, which are described below. Second, among the genes activated by HIF-1 are many that encode transcription factors [7], which when synthesized can bind to and regulate (either positively or negatively) secondary batteries of target genes (Fig. 1B). Third, another group of HIF-1 target genes encode members of the Jumonji domain family of histone demethylases [8,9], which regulate gene expression by modifying chromatin structure (Fig. 1C). Fourth, HIF-1 can activate the transcription of genes encoding microRNAs [10], which bind to specific mRNA molecules and either block their translation or mediate their degradation (Fig. 1D). Fifth, the isolated HIF-1α subunit can bind to other transcription factors [11,12] and inhibit (Fig. 1E) or potentiate (Fig. 1F) their activity.

Mechanisms by which HIF-1 regulates gene expression. nihms232046f1

Mechanisms by which HIF-1 regulates gene expression. nihms232046f1

Mechanisms by which HIF-1 regulates gene expression.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3010308/bin/nihms232046f1.gif

Fig. 1 Mechanisms by which HIF-1 regulates gene expression. (A) Top: HIF-1 binds directly to target genes at a cis-acting hypoxia response element (HRE) and recruits coactivator proteins such as p300 to increase gene transcription.

HIF-1α and HIF-1β are present in all metazoan species, including the simple roundworm Caenorhabitis elegans [13], which consists of ~103 cells and has no specialized systems for O2 delivery. The fruit flyDrosophila melanogaster evolved tracheal tubes, which conduct air into the interior of the body from which it diffuses to surrounding cells. In vertebrates, the development of the circulatory and respiratory systems was accompanied by the appearance of HIF-2α, which is also O2-regulated and heterodimerizes with HIF-1β [14] but is only expressed in a restricted number of cell types [15], whereas HIF-1α and HIF-1β are expressed in all human and mouse tissues [16]. In Drosophila, the ubiquitiously expressed HIF-1α ortholog is designatedSimilar [17] and the paralogous gene that is expressed specifically in tracheal tubes is designated Trachealess[18].

HIF-1 Activity is Regulated by Oxygen

In the presence of O2, HIF-1α and HIF-2α are subjected to hydroxylation by prolyl-4-hydroxylase domain proteins (PHDs) that use O2 and α-ketoglutarate as substrates and generate CO2 and succinate as by-products [19]. Prolyl hydroxylation is required for binding of the von Hipple-Lindau protein, which recruits a ubiquitin-protein ligase that targets HIF-1α and HIF-2α for proteasomal degradation (Fig. 2). Under hypoxic conditions, the rate of hydroxylation declines and the non-hydroxylated proteins accumulate. HIF-1α transactivation domain function is also O2-regulated [20,21]. Factor inhibiting HIF-1 (FIH-1) represses transactivation domain function [22] by hydroxylating asparagine residue 803 in HIF-1α, thereby blocking the binding of the co-activators p300 and CBP [23].

Negative regulation of HIF-1 activity by oxygen nihms232046f2

Negative regulation of HIF-1 activity by oxygen nihms232046f2

Negative regulation of HIF-1 activity by oxygen

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3010308/bin/nihms232046f2.gif

Fig. 2 Negative regulation of HIF-1 activity by oxygen. Top: In the presence of O2: prolyl hydroxylation of HIF-1a leads to binding of the von Hippel-Lindau protein (VHL), which recruits a ubiquitin protein-ligase that targets HIF-1a for proteasomal degradation;

When cells are acutely exposed to hypoxic conditions, the generation of ROS at complex III of the mitochondrial electron transport chain (ETC) increases and is required for the induction of HIF-1α protein levels [24]. More than a decade after these observations were first made, the precise mechanism by which hypoxia increases ROS generation and by which ROS induces HIF-1α accumulation remain unknown. However, the prolyl and asparaginyl hydroxylases contain Fe2+ in their active site and oxidation to Fe3+would block their catalytic activity. Since O2 is a substrate for the hydroxylation reaction, anoxia also results in a loss of enzyme activity. However, the concentration at which O2 becomes limiting for prolyl or asparaginyl hydroxylase activity in vivo is not known.

HIF-1 Regulates the Balance Between Oxidative and Glycolytic Metabolism

All metazoan organisms depend on mitochondrial respiration as the primary mechanism for generating sufficient amounts of ATP to maintain cellular and systemic homeostasis. Respiration, in turn, is dependent on an adequate supply of O2 to serve as the final electron acceptor in the ETC. In this process, electrons are transferred from complex I (or complex II) to complex III, then to complex IV, and finally to O2, which is reduced to water. This orderly transfer of electrons generates a proton gradient across the inner mitochondrial membrane that is used to drive the synthesis of ATP. At each step of this process, some electrons combine with O2 prematurely, resulting in the production of superoxide anion, which is reduced to hydrogen peroxide through the activity of mitochondrial superoxide dismutase. The efficiency of electron transport appears to be optimized to the physiological range of O2 concentrations, such that ATP is produced without the production of excess superoxide, hydrogen peroxide, and other ROS at levels that would result in the increased oxidation of cellular macromolecules and subsequent cellular dysfunction or death. In contrast, when O2levels are acutely increased or decreased, an imbalance between O2 and electron flow occurs, which results in increased ROS production.

MEFs require HIF-1 activity to make two critical metabolic adaptations to chronic hypoxia. First, HIF-1 activates the gene encoding pyruvate dehydrogenase (PDH) kinase 1 (PDK1), which phosphorylates and inactivates the catalytic subunit of PDH, the enzyme that converts pyruvate to acetyl coenzyme A (AcCoA) for entry into the mitochondrial tricarboxylic acid (TCA) cycle [25]. Second, HIF-1 activates the gene encoding BNIP3, a member of the Bcl-2 family of mitochondrial proteins, which triggers selective mitochondrial autophagy [26]. Interference with the induction of either of these proteins in hypoxic cells results in increased ROS production and increased cell death. Overexpression of either PDK1 or BNIP3 rescues HIF-1α-null MEFs. By shunting pyruvate away from the mitochondria, PDK1 decreases flux through the ETC and thereby counteracts the reduced efficiency of electron transport under hypoxic conditions, which would otherwise increase ROS production. PDK1 functions cooperatively with the product of another HIF-1 target gene, LDHA [27], which converts pyruvate to lactate, thereby further reducing available substrate for the PDH reaction.

PDK1 effectively reduces flux through the TCA cycle and thereby reduces flux through the ETC in cells that primarily utilize glucose as a substrate for oxidative phosphorylation. However, PDK1 is predicted to have little effect on ROS generation in cells that utilize fatty acid oxidation as their source of AcCoA. Hence another strategy to reduce ROS generation under hypoxic conditions is selective mitochondrial autophagy [26]. MEFs reduce their mitochondrial mass and O2 consumption by >50% after only two days at 1% O2. BNIP3 competes with Beclin-1 for binding to Bcl-2, thereby freeing Beclin-1 to activate autophagy. Using short hairpin RNAs to knockdown expression of BNIP3, Beclin-1, or Atg5 (another component of the autophagy machinery) phenocopied HIF-1α-null cells by preventing hypoxia-induced reductions in mitochondrial mass and O2 consumption as a result of failure to induce autophagy [26]. HIF-1-regulated expression of BNIP3L also contributes to hypoxia-induced autophagy [28]. Remarkably, mice heterozygous for the HIF-1α KO allele have a significantly increased ratio of mitochondrial:nuclear DNA in their lungs (even though this is the organ that is exposed to the highest O2 concentrations), indicating that HIF-1 regulates mitochondrial mass under physiological conditions in vivo [26]. In contrast to the selective mitochondrial autophagy that is induced in response to hypoxia as described above, autophagy (of unspecified cellular components) induced by anoxia does not require HIF-1, BNIP3, or BNIP3L, but is instead regulated by AMP kinase [29].

The multiplicity of HIF-1-mediated mechanisms identified so far by which cells regulate mitochondrial metabolism in response to changes in cellular O2 concentration (Fig. 3) suggests that this is a critical adaptive response to hypoxia. The fundamental nature of this physiological response is underscored by the fact that yeast also switch COX4 subunits in an O2-dependent manner but do so by an entirely different molecular mechanism [33], since yeast do not have a HIF-1α homologue. Thus, it appears that by convergent evolution both unicellular and multicellular eukaryotes possess mechanisms by which they modulate mitochondrial metabolism to maintain redox homeostasis despite changes in O2 availability. Indeed, it is the balance between energy, oxygen, and redox homeostasis that represents the key to life with oxygen.

Regulation of mitochondrial metabolism by HIF-1  nihms232046f3

Regulation of mitochondrial metabolism by HIF-1 nihms232046f3

Regulation of mitochondrial metabolism by HIF-1α

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Fig. 3 Regulation of mitochondrial metabolism by HIF-1α. Acute hypoxia leads to increased mitochondrial generation of reactive oxygen species (ROS). Decreased O2 and increased ROS levels lead to decreased HIF-1α hydroxylation (see Fig. 2) and increased HIF-1-dependent 

 

7.9.5 Regulation of cancer cell metabolism by hypoxia-inducible factor 1

Semenza GL1.
Semin Cancer Biol. 2009 Feb; 19(1):12-6.

The Warburg Effect: The Re-discovery of the Importance of Aerobic Glycolysis in Tumor Cells
http://dx.doi.org:/10.1016/j.semcancer.2008.11.009

The induction of hypoxia-inducible factor 1 (HIF-1) activity, either as a result of intratumoral hypoxia or loss-of-function mutations in the VHL gene, leads to a dramatic reprogramming of cancer cell metabolism involving increased glucose transport into the cell, increased conversion of glucose to pyruvate, and a concomitant decrease in mitochondrial metabolism and mitochondrial mass. Blocking these adaptive metabolic responses to hypoxia leads to cell death due to toxic levels of reactive oxygen species. Targeting HIF-1 or metabolic enzymes encoded by HIF-1 target genes may represent a novel therapeutic approach to cancer.

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7.9.6 Coming up for air. HIF-1 and mitochondrial oxygen consumption

Simon MC1.
Cell Metab. 2006 Mar;3(3):150-1.
http://dx.doi.org/10.1016/j.cmet.2006.02.007

Hypoxic cells induce glycolytic enzymes; this HIF-1-mediated metabolic adaptation increases glucose flux to pyruvate and produces glycolytic ATP. Two papers in this issue of Cell Metabolism (Kim et al., 2006; Papandreou et al., 2006) demonstrate that HIF-1 also influences mitochondrial function, suppressing both the TCA cycle and respiration by inducing pyruvate dehydrogenase kinase 1 (PDK1). PDK1 regulation in hypoxic cells promotes cell survival.

Comment on

Oxygen deprivation (hypoxia) occurs in tissues when O2 supply via the cardiovascular system fails to meet the demand of O2-consuming cells. Hypoxia occurs naturally in physiological settings (e.g., embryonic development and exercising muscle), as well as in pathophysiological conditions (e.g., myocardial infarction, inflammation, and solid tumor formation). For over a century, it has been appreciated that O2-deprived cells exhibit increased conversion of glucose to lactate (the “Pasteur effect”). Activation of the Pasteur effect during hypoxia in mammalian cells is facilitated by HIF-1, which mediates the upregulation of glycolytic enzymes that support an increase in glycolytic ATP production as mitochondria become starved for O2, the substrate for oxidative phosphorylation (Seagroves et al., 2001). Thus, mitochondrial respiration passively decreases due to O2 depletion in hypoxic tissues. However, reports by Kim et al. (2006) and Papandreou et al. (2006) in this issue of Cell Metabolism demonstrate that this critical metabolic adaptation is more complex and includes an active suppression of mitochondrial pyruvate catabolism and O2consumption by HIF-1.

Mitochondrial oxidative phosphorylation is regulated by multiple mechanisms, including substrate availability. Major substrates include O2 (the terminal electron acceptor) and pyruvate (the primary carbon source). Pyruvate, as the end product of glycolysis, is converted to acetyl-CoA by the pyruvate dehydrogenase enzymatic complex and enters the tricarboxylic acid (TCA) cycle. Pyruvate conversion into acetyl-CoA is irreversible; this therefore represents an important regulatory point in cellular energy metabolism. Pyruvate dehydrogenase kinase (PDK) inhibits pyruvate dehydrogenase activity by phosphorylating its E1 subunit (Sugden and Holness, 2003). In the manuscripts by Kim et al. (2006) and Papandreou et al. (2006), the authors find that PDK1 is a HIF-1 target gene that actively regulates mitochondrial respiration by limiting pyruvate entry into the TCA cycle. By excluding pyruvate from mitochondrial metabolism, hypoxic cells accumulate pyruvate, which is then converted into lactate via lactate dehydrogenase (LDH), another HIF-1-regulated enzyme. Lactate in turn is released into the extracellular space, regenerating NAD+ for continued glycolysis by O2-starved cells (see Figure 1). This HIF-1-dependent block to mitochondrial O2 consumption promotes cell survival, especially when O2 deprivation is severe and prolonged.

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multiple-hypoxia-induced-cellular-metabolic-changes-are-regulated-by-hif-1

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Figure 1. Multiple hypoxia-induced cellular metabolic changes are regulated by HIF-1

By stimulating the expression of glucose transporters and glycolytic enzymes, HIF-1 promotes glycolysis to generate increased levels of pyruvate. In addition, HIF-1 promotes pyruvate reduction to lactate by activating lactate dehydrogenase (LDH). Pyruvate reduction to lactate regenerates NAD+, which permits continued glycolysis and ATP production by hypoxic cells. Furthermore, HIF-1 induces pyruvate dehydrogenase kinase 1 (PDK1), which inhibits pyruvate dehydrogenase and blocks conversion of pyruvate to acetyl CoA, resulting in decreased flux through the tricarboxylic acid (TCA) cycle. Decreased TCA cycle activity results in attenuation of oxidative phosphorylation and excessive mitochondrial reactive oxygen species (ROS) production. Because hypoxic cells already exhibit increased ROS, which have been shown to promote HIF-1 accumulation, the induction of PDK1 prevents the persistence of potentially harmful ROS levels.

Papandreou et al. demonstrate that hypoxic regulation of PDK has important implications for antitumor therapies. Recent interest has focused on cytotoxins that target hypoxic cells in tumor microenvironments, such as the drug tirapazamine (TPZ). Because intracellular O2 concentrations are decreased by mitochondrial O2 consumption, HIF-1 could protect tumor cells from TPZ-mediated cell death by maintaining intracellular O2 levels. Indeed, Papandreou et al. show that HIF-1-deficient cells grown at 2% O2 exhibit increased sensitivity to TPZ relative to wild-type cells, presumably due to higher rates of mitochondrial O2 consumption. HIF-1 inhibition in hypoxic tumor cells should have multiple therapeutic benefits, but the use of HIF-1 inhibitors in conjunction with other treatments has to be carefully evaluated for the most effective combination and sequence of drug delivery. One result of HIF-1 inhibition would be a relative decrease in intracellular O2 levels, making hypoxic cytotoxins such as TPZ more potent antitumor agents. Because PDK expression has been detected in multiple human tumor samples and appears to be induced by hypoxia (Koukourakis et al., 2005), small molecule inhibitors of HIF-1 combined with TPZ represent an attractive therapeutic approach for future clinical studies.

Hypoxic regulation of PDK1 has other important implications for cell survival during O2 depletion. Because the TCA cycle is coupled to electron transport, Kim et al. suggest that induction of the pyruvate dehydrogenase complex by PDK1 attenuates not only mitochondrial respiration but also the production of mitochondrial reactive oxygen species (ROS) in hypoxic cells. ROS are a byproduct of electron transfer to O2, and cells cultured at 1 to 5% O2 generate increased mitochondrial ROS relative to those cultured at 21% O2 (Chandel et al., 1998 and Guzy et al., 2005). In fact, hypoxia-induced mitochondrial ROS have also been shown to be necessary for the stabilization of HIF-1 in hypoxic cells (Brunelle et al., 2005Guzy et al., 2005 and Mansfield et al., 2005). However, the persistence of ROS could ultimately be lethal to tissues during chronic O2 deprivation, and PDK1 induction by HIF-1 should promote cell viability during long-term hypoxia. Kim et al. present evidence that HIF-1-deficient cells exhibit increased apoptosis after 72 hr of culture at 0.5% O2 compared to wild-type cells and that cell survival is rescued by enforced expression of exogenous PDK1. Furthermore, PDK1 reduces ROS production by the HIF-1 null cells. These findings support a novel prosurvival dimension of cellular hypoxic adaptation where PDK1 inhibits the TCA cycle, mitochondrial respiration, and chronic ROS production.

The HIF-1-mediated block to mitochondrial O2 consumption via PDK1 regulation also has implications for O2-sensing pathways by hypoxic cells. One school of thought suggests that perturbing mitochondrial O2consumption increases intracellular O2 concentrations and suppresses HIF-1 induction by promoting the activity of HIF prolyl hydroxylases, the O2-dependent enzymes that regulate HIF-1 stability (Hagen et al., 2003 and Doege et al., 2005). This model suggests that mitochondria function as “O2 sinks.” Although Papandreou et al. demonstrate that increased mitochondrial respiration due to PDK1 depletion results in decreased intracellular O2 levels (based on pimonidazole staining), these changes failed to reduce HIF-1 levels in hypoxic cells. Another model for hypoxic activation of HIF-1 describes a critical role for mitochondrial ROS in prolyl hydroxylase inhibition and HIF-1 stabilization in O2-starved cells (Brunelle et al., 2005Guzy et al., 2005 and Mansfield et al., 2005) (see Figure 1). The mitochondrial “O2 sink” hypothesis can account for some observations in the literature but fails to explain the inhibition of HIF-1 stabilization by ROS scavengers (Chandel et al., 1998Brunelle et al., 2005Guzy et al., 2005 and Sanjuán-Pla et al., 2005). While the relationship between HIF-1 stability, mitochondrial metabolism, ROS, and intracellular O2 redistribution will continue to be debated for some time, these most recent findings shed new light on findings by Louis Pasteur over a century ago.

Selected reading

Brunelle et al., 2005

J.K. Brunelle, E.L. Bell, N.M. Quesada, K. Vercauteren, V. Tiranti, M. Zeviani, R.C. Scarpulla, N.S. Chandel

Cell Metab., 1 (2005), pp. 409–414

Article  PDF (324 K) View Record in Scopus Citing articles (357)

Chandel et al., 1998

N.S. Chandel, E. Maltepe, E. Goldwasser, C.E. Mathieu, M.C. Simon, P.T. Schumacker

Proc. Natl. Acad. Sci. USA, 95 (1998), pp. 11715–11720

View Record in Scopus Full Text via CrossRef Citing articles (973)

Doege et al., 2005Doege, S. Heine, I. Jensen, W. Jelkmann, E. Metzen

Blood, 106 (2005), pp. 2311–2317

View Record in Scopus Full Text via CrossRef Citing articles (84)

Guzy et al., 2005

R.D. Guzy, B. Hoyos, E. Robin, H. Chen, L. Liu, K.D. Mansfield, M.C. Simon, U. Hammerling, P.T. Schumacker

Cell Metab., 1 (2005), pp. 401–408

Article  PDF (510 K) View Record in Scopus Citing articles (593)

Hagen et al., 2003

Hagen, C.T. Taylor, F. Lam, S. Moncada

Science, 302 (2003), pp. 1975–1978

View Record in Scopus Full Text via CrossRef Citing articles (450)

7.9.7 HIF-1 mediates adaptation to hypoxia by actively downregulating mitochondrial oxygen consumption

Papandreou I1Cairns RAFontana LLim ALDenko NC.
Cell Metab. 2006 Mar; 3(3):187-97.
http://dx.doi.org/10.1016/j.cmet.2006.01.012

The HIF-1 transcription factor drives hypoxic gene expression changes that are thought to be adaptive for cells exposed to a reduced-oxygen environment. For example, HIF-1 induces the expression of glycolytic genes. It is presumed that increased glycolysis is necessary to produce energy when low oxygen will not support oxidative phosphorylation at the mitochondria. However, we find that while HIF-1 stimulates glycolysis, it also actively represses mitochondrial function and oxygen consumption by inducing pyruvate dehydrogenase kinase 1 (PDK1). PDK1 phosphorylates and inhibits pyruvate dehydrogenase from using pyruvate to fuel the mitochondrial TCA cycle. This causes a drop in mitochondrial oxygen consumption and results in a relative increase in intracellular oxygen tension. We show by genetic means that HIF-1-dependent block to oxygen utilization results in increased oxygen availability, decreased cell death when total oxygen is limiting, and reduced cell death in response to the hypoxic cytotoxin tirapazamine.

Comment in

Tissue hypoxia results when supply of oxygen from the bloodstream does not meet demand from the cells in the tissue. Such a supply-demand mismatch can occur in physiologic conditions such as the exercising muscle, in the pathologic condition such as the ischemic heart, or in the tumor microenvironment (Hockel and Vaupel, 2001 and Semenza, 2004). In either the physiologic circumstance or pathologic conditions, there is a molecular response from the cell in which a program of gene expression changes is initiated by the hypoxia-inducible factor-1 (HIF-1) transcription factor. This program of gene expression changes is thought to help the cells adapt to the stressful environment. For example, HIF-1-dependent expression of erythropoietin and angiogenic compounds results in increased blood vessel formation for delivery of a richer supply of oxygenated blood to the hypoxic tissue. Additionally, HIF-1 induction of glycolytic enzymes allows for production of energy when the mitochondria are starved of oxygen as a substrate for oxidative phosphorylation. We now find that this metabolic adaptation is more complex, with HIF-1 not only regulating the supply of oxygen from the bloodstream, but also actively regulating the oxygen demand of the tissue by reducing the activity of the major cellular consumer of oxygen, the mitochondria.

Perhaps the best-studied example of chronic hypoxia is the hypoxia associated with the tumor microenvironment (Brown and Giaccia, 1998). The tumor suffers from poor oxygen supply through a chaotic jumble of blood vessels that are unable to adequately perfuse the tumor cells. The oxygen tension within the tumor is also a function of the demand within the tissue, with oxygen consumption influencing the extent of tumor hypoxia (Gulledge and Dewhirst, 1996 and Papandreou et al., 2005b). The net result is that a large fraction of the tumor cells are hypoxic. Oxygen tensions within the tumor range from near normal at the capillary wall, to near zero in the perinecrotic regions. This perfusion-limited hypoxia is a potent microenvironmental stress during tumor evolution (Graeber et al., 1996 and Hockel and Vaupel, 2001) and an important variable capable of predicting for poor patient outcome. (Brizel et al., 1996Cairns and Hill, 2004Hockel et al., 1996 and Nordsmark and Overgaard, 2004).

The HIF-1 transcription factor was first identified based on its ability to activate the erythropoetin gene in response to hypoxia (Wang and Semenza, 1993). Since then, it is has been shown to be activated by hypoxia in many cells and tissues, where it can induce hypoxia-responsive target genes such as VEGF and Glut1 (Airley et al., 2001 and Kimura et al., 2004). The connection between HIF-regulation and human cancer was directly linked when it was discovered that the VHL tumor suppressor gene was part of the molecular complex responsible for the oxic degradation of HIF-1α (Maxwell et al., 1999). In normoxia, a family of prolyl hydroxylase enzymes uses molecular oxygen as a substrate and modifies HIF-1α and HIF2α by hydroxylation of prolines 564 and 402 (Bruick and McKnight, 2001 and Epstein et al., 2001). VHL then recognizes the modified HIF-α proteins, acts as an E3-type of ubiquitin ligase, and along with elongins B and C is responsible for the polyubiquitination of HIF-αs and their proteosomal degradation (Bruick and McKnight, 2001Chan et al., 2002Ivan et al., 2001 and Jaakkola et al., 2001). Mutations in VHL lead to constitutive HIF-1 gene expression, and predispose humans to cancer. The ability to recognize modified HIF-αs is at least partly responsible for VHL activity as a tumor suppressor, as introduction of nondegradable HIF-2α is capable of overcoming the growth–inhibitory activity of wild-type (wt) VHL in renal cancer cells (Kondo et al., 2003).

Mitochondrial function can be regulated by PDK1 expression. Mitochondrial oxidative phosphorylation (OXPHOS) is regulated by several mechanisms, including substrate availability (Brown, 1992). The major substrates for OXPHOS are oxygen, which is the terminal electron acceptor, and pyruvate, which is the primary carbon source. Pyruvate is the end product of glycolysis and is converted to acetyl-CoA through the activity of the pyruvate dehydrogenase complex of enzymes. The acetyl-CoA then directly enters the TCA cycle at citrate synthase where it is combined with oxaloacetate to generate citrate. In metazoans, the conversion of pyruvate to acetyl-CoA is irreversible and therefore represents a critical regulatory point in cellular energy metabolism. Pyruvate dehydrogenase is regulated by three known mechanisms: it is inhibited by acetyl-CoA and NADH, it is stimulated by reduced energy in the cell, and it is inhibited by regulatory phosphorylation of its E1 subunit by pyruvate dehydrogenase kinase (PDK) (Holness and Sugden, 2003 and Sugden and Holness, 2003). There are four members of the PDK family in vertebrates, each with specific tissue distributions (Roche et al., 2001). PDK expression has been observed in human tumor biopsies (Koukourakis et al., 2005), and we have reported that PDK3 is hypoxia-inducible in some cell types (Denko et al., 2003). In this manuscript, we find that PDK1 is also a hypoxia-responsive protein that actively regulates the function of the mitochondria under hypoxic conditions by reducing pyruvate entry into the TCA cycle. By excluding pyruvate from mitochondrial consumption, PDK1 induction may increase the conversion of pyruvate to lactate, which is in turn shunted to the extracellular space, regenerating NAD for continued glycolysis.

Identification of HIF-dependent mitochondrial proteins through genomic and bioinformatics approaches

In order to help elucidate the role of HIF-1α in regulating metabolism, we undertook a genomic search for genes that were regulated by HIF-1 in tumor cells exposed to hypoxia in vitro. We used genetically matched human RCC4 cells that had lost VHL during tumorigenesis and displayed constitutive HIF-1 activity, and a cell line engineered to re-express VHL to establish hypoxia-dependent HIF activation. These cells were treated with 18 hr of stringent hypoxia (<0.01% oxygen), and microarray analysis performed. Using a strict 2.5-fold elevation as our cutoff, we identified 173 genes that were regulated by hypoxia and/or VHL status (Table S1 in the Supplemental Data available with this article online). We used the pattern of expression in these experiments to identify putative HIF-regulated genes—ones that were constitutively elevated in the parent RCC4s independent of hypoxia, downregulated in the RCC4VHL cells under normoxia, and elevated in response to hypoxia. Of the 173 hypoxia and VHL-regulated genes, 74 fit the putative HIF-1 target pattern. The open reading frames of these genes were run through a pair of bioinformatics engines in order to predict subcellular localization, and 10 proteins scored as mitochondrial on at least one engine. The genes, fold induction, and mitochondrial scores are listed in Table 1.

HIF-1 downregulates mitochondrial oxygen consumption

Having identified several putative HIF-1 responsive gene products that had the potential to regulate mitochondrial function, we then directly measured mitochondrial oxygen consumption in cells exposed to long-term hypoxia. While other groups have studied mitochondrial function under acute hypoxia (Chandel et al., 1997), this is one of the first descriptions of mitochondrial function after long-term hypoxia where there have been extensive hypoxia-induced gene expression changes. Figure 1A is an example of the primary oxygen trace from a Clark electrode showing a drop in oxygen concentration in cell suspensions of primary fibroblasts taken from normoxic and hypoxic cultures. The slope of the curve is a direct measure of the total cellular oxygen consumption rate. Exposure of either primary human or immortalized mouse fibroblasts to 24 hr of hypoxia resulted in a reduction of this rate by approximately 50% (Figures 1A and 1B). In these experiments, the oxygen consumption can be stimulated with the mitochondrial uncoupling agent CCCP (carbonyl cyanide 3-chloro phenylhydrazone) and was completely inhibited by 2 mM potassium cyanide. We determined that the change in total cellular oxygen consumption was due to changes in mitochondrial activity by the use of the cell-permeable poison of mitochondrial complex 3, Antimycin A. Figure 1C shows that the difference in the normoxic and hypoxic oxygen consumption in murine fibroblasts is entirely due to the Antimycin-sensitive mitochondrial consumption. The kinetics with which mitochondrial function slows in hypoxic tumor cells also suggests that it is due to gene expression changes because it takes over 6 hr to achieve maximal reduction, and the reversal of this repression requires at least another 6 hr of reoxygenation (Figure 1D). These effects are not likely due to proliferation or toxicity of the treatments as these conditions are not growth inhibitory or toxic to the cells (Papandreou et al., 2005a).

Since we had predicted from the gene expression data that the mitochondrial oxygen consumption changes were due to HIF-1-mediated expression changes, we tested several genetically matched systems to determine what role HIF-1 played in the process (Figure 2). We first tested the cell lines that had been used for microarray analysis and found that the parental RCC4 cells had reduced mitochondrial oxygen consumption when compared to the VHL-reintroduced cells. Oxygen consumption in the parental cells was insensitive to hypoxia, while it was reduced by hypoxia in the wild-type VHL-transfected cell lines. Interestingly, stable introduction of a tumor-derived mutant VHL (Y98H) that cannot degrade HIF was also unable to restore oxygen consumption. These results indicate that increased expression of HIF-1 is sufficient to reduce oxygen consumption (Figure 2A). We also investigated whether HIF-1 induction was required for the observed reduction in oxygen consumption in hypoxia using two genetically matched systems. We measured normoxic and hypoxic oxygen consumption in murine fibroblasts derived from wild-type or HIF-1α null embryos (Figure 2B) and from human RKO tumor cells and RKO cells constitutively expressing ShRNAs directed against the HIF-1α gene (Figures 2C and 4C). Neither of the HIF-deficient cell systems was able to reduce oxygen consumption in response to hypoxia. These data from the HIF-overexpressing RCC cells and the HIF-deficient cells indicate that HIF-1 is both necessary and sufficient for reducing mitochondrial oxygen consumption in hypoxia.

HIF-dependent mitochondrial changes are functional, not structural

Because addition of CCCP could increase oxygen consumption even in the hypoxia-treated cells, we hypothesized that the hypoxic inhibition was a regulated activity, not a structural change in the mitochondria in response to hypoxic stress. We confirmed this interpretation by examining several additional mitochondrial characteristics in hypoxic cells such as mitochondrial morphology, quantity, and membrane potential. We examined morphology by visual inspection of both the transiently transfected mitochondrially localized DsRed protein and the endogenous mitochondrial protein cytochrome C. Both markers were indistinguishable in the parental RCC4 and the RCC4VHL cells (Figure 3A). Likewise, we measured the mitochondrial membrane potential with the functional dye rhodamine 123 and found that it was identical in the matched RCC4 cells and the matched HIF wt and knockout (KO) cells when cultured in normoxia or hypoxia (Figure 3B). Finally, we determined that the quantity of mitochondria per cell was not altered in response to HIF or hypoxia by showing that the amount of the mitochondrial marker protein HSP60 was identical in the RCC4 and HIF cell lines (Figure 3C)

PDK1 is a HIF-1 inducible target protein

After examination of the list of putative HIF-regulated mitochondrial target genes, we hypothesized that PDK1 could mediate the functional changes that we observed in hypoxia. We therefore investigated PDK1 protein expression in response to HIF and hypoxia in the genetically matched cell systems. Figure 4A shows that in the RCC4 cells PDK1 and the HIF-target gene BNip3 (Greijer et al., 2005 and Papandreou et al., 2005a) were both induced by hypoxia in a VHL-dependent manner, with the expression of PDK1 inversely matching the oxygen consumption measured in Figure 1 above. Likewise, the HIF wt MEFs show oxygen-dependent induction of PDK1 and BNip3, while the HIF KO MEFs did not show any expression of either of these proteins under any oxygen conditions (Figure 4B). Finally, the parental RKO cells were able to induce PDK1 and the HIF target gene BNip3L in response to hypoxia, while the HIF-depleted ShRNA RKO cells could not induce either protein (Figure 4C). Therefore, in all three cell types, the HIF-1-dependent regulation of oxygen consumption seen in Figure 2, corresponds to the HIF-1-dependent induction of PDK1 seen in Figure 4.

In order to determine if PDK1 was a direct HIF-1 target gene, we analyzed the genomic sequence flanking the 5′ end of the gene for possible HIF-1 binding sites based on the consensus core HRE element (A/G)CGTG (Caro, 2001). Several such sites exist within the first 400 bases upstream, so we generated reporter constructs by fusing the genomic sequence from −400 to +30 of the start site of transcription to the firefly luciferase gene. In transfection experiments, the chimeric construct showed significant induction by either cotransfection with a constitutively active HIF proline mutant (P402A/P564G) (Chan et al., 2002) or exposure of the transfected cells to 0.5% oxygen (Figure 4D). Most noteworthy, when the reporter gene was transfected into the HIF-1α null cells, it did not show induction when the cells were cultured in hypoxia, but it did show induction when cotransfected with expression HIF-1α plasmid. We then generated deletions down to the first 36 bases upstream of transcription and found that even this short sequence was responsive to HIF-1 (Figure 4D). Analysis of this small fragment showed only one consensus HRE site located in an inverted orientation in the 5′ untranslated region. We synthesized and cloned a mutant promoter fragment in which the core element ACGTG was replaced with AAAAG, and this construct lost over 90% of its hypoxic induction. These experiments suggest that it is this HRE within the proximal 5′ UTR that HIF-1 uses to transactivate the endogenous PDK1 gene in response to hypoxia.

PDK1 is responsible for the HIF-dependent mitochondrial oxygen consumption changes

In order to directly test if PDK1 was the HIF-1 target gene responsible for the hypoxic reduction in mitochondrial oxygen consumption, we generated RKO cell lines with either knockdown or overexpression of PDK1 and measured the oxygen consumption in these derivatives. The PDK1 ShRNA stable knockdown line was generated as a pool of clones cotransfected with pSUPER ShPDK1 and pTK-hygro resistance gene. After selection for growth in hygromycin, the cells were tested by Western blot for the level of PDK1 protein expression. We found that normoxic PDK1 is reduced by 75%, however, there was measurable expression of PDK1 in these cells in response to hypoxia (Figure 5A). When we measured the corresponding oxygen consumption in these cells, we found a change commensurate with the level of PDK1. The knockdown cells show elevated baseline oxygen consumption, and partial reduction in this activity in response to hypoxia. Therefore, reduction of PDK1 expression by genetic means increased mitochondrial oxygen consumption in both normoxic and hypoxic conditions. Interestingly, these cells still induced HIF-1α (Figure 5A) and HIF-1 target genes such as BNip3L in response to hypoxia (data not shown), suggesting that altered PDK1 levels do not alter HIF-1α function.

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PDK1 expression directly regulates cellular oxygen consumption rate

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Figure 5. PDK1 expression directly regulates cellular oxygen consumption rate

  1. A)Western blot of RKO cell and ShRNAPDK1RKO cell lysates after exposure to 24 hr of normoxia or 0.5% O2. Blots were probed for HIF 1α, PDK1, and tubulin as a loading control.
  2. B)Oxygen consumption rate in RKO and ShRNAPDK1RKO cells after exposure to 24 hr of normoxia or 0.5% O2.
  3. C)Western blot of RKOiresGUS cell and RKOiresPDK1 cell lysates after exposure to 24 hr of normoxia or 0.5% O2. Blots were probed for HIF 1α, PDK1, and tubulin as a loading control.
  4. D)Oxygen consumption rate in RKOiresGUS and RKOiresPDK1 cells after exposure to 24 hr of normoxia or 0.5% O2.
  5. E)Model describing the interconnected effects of HIF-1 target gene activation on hypoxic cell metabolism. Reduced oxygen conditions causes HIF-1 to coordinately induce the enzymes shown in boxes. HIF-1 activation results in increased glucose transporter expression to increase intracellular glucose flux, induction of glycolytic enzymes increases the conversion of glucose to pyruvate generating energy and NADH, induction of PDK1 decreases mitochondrial utilization of pyruvate and oxygen, and induction of LDH increases the removal of excess pyruvate as lactate and also regenerates NAD+ for increased glycolysis.

For all graphs, the error bars represent the standard error of the mean.

We also determined if overexpression of PDK1 could lead to reduced mitochondrial oxygen consumption. A separate culture of RKO cells was transfected with a PDK1-IRES-puro expression plasmid and selected for resistance to puromycin. The pool of puromycin resistant cells was tested for PDK1 expression by Western blot. These cells showed a modest increase in PDK1 expression under control conditions when compared to the cells transfected with GUS-IRES-puro, with an additional increase in PDK1 protein in response to hypoxia (Figure 5C). The corresponding oxygen consumption measurements showed that the mitochondria is very sensitive to changes in the levels of PDK1, as even this slight increase was able to significantly reduce oxygen consumption in the normoxic PDK1-puro cultures. Further increase in PDK1 levels with hypoxia further reduced oxygen consumption in both cultures (Figure 5D). The model describing the relationship between hypoxia, HIF-1, PDK1, and intermediate metabolism is described inFigure 5E.

Altering oxygen consumption alters intracellular oxygen tension and sensitivity to hypoxia-dependent cell killing

The intracellular concentration of oxygen is a net result of the rate at which oxygen diffuses into the cell and the rate at which it is consumed. We hypothesized that the rate at which oxygen was consumed within the cell would significantly affect its steady-state intracellular concentrations. We tested this hypothesis in vitro using the hypoxic marker drug pimonidazole (Bennewith and Durand, 2004). We plated high density cultures of HIF wild-type and HIF knockout cells and placed these cultures in normoxic, 2% oxygen, and anoxic incubators for overnight treatment. The overnight treatment gives the cells time to adapt to the hypoxic conditions and establish altered oxygen consumption profiles. Pimonidozole was then added for the last 4 hr of the growth of the culture. Pimonidazole binding was detected after fixation of the cells using an FITC labeled anti-pimonidazole antibody and it was quantitated by flow cytometry. The quantity of the bound drug is a direct indication of the oxygen concentration within the cell (Bennewith and Durand, 2004). The histograms in Figure 6A show that the HIF-1 knockout and wild-type cells show similar staining in the cells grown in 0% oxygen. However, the cells treated with 2% oxygen show the consequence of the genetic removal of HIF-1. The HIF-proficient cells showed relatively less pimonidazole binding at 2% when compared to the 0% culture, while the HIF-deficient cells showed identical binding between the cells at 2% and those at 0%. We interpret these results to mean that the HIF-deficient cells have greater oxygen consumption, and this has lowered the intracellular oxygenation from the ambient 2% to close to zero intracellularly. The HIF-proficient cells reduced their oxygen consumption rate so that the rate of diffusion into the cell is greater than the rate of consumption.

Figure 6. HIF-dependent decrease in oxygen consumption raises intracellular oxygen concentration, protects when oxygen is limiting, and decreases sensitivity to tirapazamine in vitro

  1. A)Pimonidazole was used to determine the intracellular oxygen concentration of cells in culture. HIF wt and HIF KO MEFs were grown at high density and exposed to 2% O2or anoxia for 24 hr in glass dishes. For the last 4 hr of treatment, cells were exposed to 60 μg/ml pimonidazole. Pimonidazole binding was quantitated by flow cytometry after binding of an FITC conjugated anti-pimo mAb. Results are representative of two independent experiments.
  2. B)HIF1α reduces oxygen consumption and protects cells when total oxygen is limited. HIF wt and HIF KO cells were plated at high density and sealed in aluminum jigs at <0.02% oxygen. At the indicated times, cells were harvested, and dead cells were quantitated by trypan blue exclusion. Note both cell lines are equally sensitive to anoxia-induced apoptosis, so the death of the HIF null cells indicates that the increased oxygen consumption removed any residual oxygen in the jig and resulted in anoxia-induced death.
  3. C)PDK1 is responsible for HIF-1’s adaptive response when oxygen is limiting. A similar jig experiment was performed to measure survival in the parental RKO, the RKO ShRNAHIF1α, and the RKOShPDK1 cells. Cell death by trypan blue uptake was measured 48 hr after the jigs were sealed.
  4. D)HIF status alters sensitivity to TPZ in vitro. HIF wt and HIF KO MEFs were grown at high density in glass dishes and exposed to 21%, 2%, and <0.01% O2conditions for 18 hr in the presence of varying concentrations of Tirapazamine. After exposure, cells were harvested and replated under normoxia to determine clonogenic viability. Survival is calculated relative to the plating efficiency of cells exposed to 0 μM TPZ for each oxygen concentration.
  5. E)Cell density alters sensitivity to TPZ. HIF wt and HIF KO MEFs were grown at varying cell densities in glass dishes and exposed to 2% O2in the presence of 10 μM TPZ for 18 hr. After the exposure, survival was determined as described in (C).

For all graphs, the error bars represent the standard error of the mean.

HIF-induced PDK1 can reduce the total amount of oxygen consumed per cell. The reduction in the amount of oxygen consumed could be significant if there is a finite amount of oxygen available, as would be the case in the hours following a blood vessel occlusion. The tissue that is fed by the vessel would benefit from being economical with the oxygen that is present. We experimentally modeled such an event using aluminum jigs that could be sealed with defined amounts of cells and oxygen present (Siim et al., 1996). We placed 10 × 106 wild-type or HIF null cells in the sealed jig at 0.02% oxygen, waited for the cells to consume the remaining oxygen, and measured cell viability. We have previously shown that these two cell types are resistant to mild hypoxia and equally sensitive to anoxia-induced apoptosis (Papandreou et al., 2005a). Therefore, any death in this experiment would be the result of the cells consuming the small amount of remaining oxygen and dying in response to anoxia. We found that in sealed jigs, the wild-type cells are more able to adapt to the limited oxygen supply by reducing consumption. The HIF null cells continued to consume oxygen, reached anoxic levels, and started to lose viability within 36 hr (Figure 6B). This is a secondary adaptive effect of HIF1. We confirmed that PDK1 was responsible for this difference by performing a similar experiment using the parental RKO cells, the RKOShRNAHIF1α and the RKOShRNAPDK1 cells. We found similar results in which both the cells with HIF1α knockdown and PDK1 knockdown were sensitive to the long-term effects of being sealed in a jig with a defined amount of oxygen (Figure 6c). Note that the RKOShPDK1 cells are even more sensitive than the RKOShHIF1α cells, presumably because they have higher basal oxygen consumption rates (Figure 5B).

Because HIF-1 can help cells adapt to hypoxia and maintain some intracellular oxygen level, it may also protect tumor cells from killing by the hypoxic cytotoxin tirapazamine (TPZ). TPZ toxicity is very oxygen dependent, especially at oxygen levels between 1%–4% (Koch, 1993). We therefore tested the relative sensitivity of the HIF wt and HIF KO cells to TPZ killing in high density cultures (Figure 6D). We exposed the cells to the indicated concentrations of drug and oxygen concentrations overnight. The cells were then harvested and replated to determine reproductive viability by colony formation. Both cell types were equally resistant to TPZ at 21% oxygen, while both cell types are equally sensitive to TPZ in anoxic conditions where intracellular oxygen levels are equivalent (Figure 6A). The identical sensitivity of both cell types in anoxia indicates that both cell types are equally competent in repairing the TPZ-induced DNA damage that is presumed to be responsible for its toxicity. However, in 2% oxygen cultures, the HIF null cells displayed a significantly greater sensitivity to the drug than the wild-type cells. This suggests that the increased oxygen consumption rate in the HIF-deficient cells is sufficient to lower the intracellular oxygen concentration relative to that in the HIF-proficient cells. The lower oxygen level is significant enough to dramatically sensitize these cells to killing by TPZ.

If the increased sensitivity to TPZ in the HIF ko cells is determined by intracellular oxygen consumption differences, then this effect should also be cell-density dependent. We showed that this is indeed the case in Figure 6E where oxygen and TPZ concentrations were held constant, and increased cell density lead to increased TPZ toxicity. The effect was much more pronounced in the HIF KO cells, although the HIF wt cells showed some increased toxicity in the highest density cultures, consistent with the fact they were still consuming some oxygen, even with HIF present (Figure 1). The in vitro TPZ survival data is therefore consistent with our hypothesis that control of oxygen consumption can regulate intracellular oxygen concentration, and suggests that increased oxygen consumption could sensitize cells to hypoxia-dependent therapy.

Discussion

The findings presented here show that HIF-1 is actively responsible for regulating energy production in hypoxic cells by an additional, previously unrecognized mechanism. It has been shown that HIF-1 induces the enzymes responsible for glycolysis when it was presumed that low oxygen did not support efficient oxidative phosphorylation (Iyer et al., 1998 and Seagroves et al., 2001). The use of glucose to generate ATP is capable of satisfying the energy requirements of a cell if glucose is in excess (Papandreou et al., 2005a). We now find that at the same time that glycolysis is increasing, mitochondrial respiration is decreasing. However, the decreased respiration is not because there is not enough oxygen present to act as a substrate for oxidative phosphorylation, but because the flow of pyruvate into the TCA cycle has been reduced by the activity of pyruvate dehydrogenase kinase. Other reports have suggested that oxygen utilization is shifted in cells exposed to hypoxia, but these reports have focused on other regulators such as nitric oxide synthase (Hagen et al., 2003). NO can reduce oxygen consumption through direct inhibition of cytochrome oxidase, but this effect seems to be more significant at physiologic oxygen concentrations, not at severe levels seen in the tumor (Palacios-Callender et al., 2004).

7.9.8 HIF-1. upstream and downstream of cancer metabolism

Semenza GL1.
Curr Opin Genet Dev. 2010 Feb; 20(1):51-6
http://dx.doi.org/10.1016%2Fj.gde.2009.10.009

Hypoxia-inducible factor 1 (HIF-1) plays a key role in the reprogramming of cancer metabolism by activating transcription of genes encoding glucose transporters and glycolytic enzymes, which take up glucose and convert it to lactate; pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; and BNIP3, which triggers selective mitochondrial autophagy. The shift from oxidative to glycolytic metabolism allows maintenance of redox homeostasis and cell survival under conditions of prolonged hypoxia. Many metabolic abnormalities in cancer cells increase HIF-1 activity. As a result, a feed-forward mechanism can be activated that drives HIF-1 activation and may promote tumor progression. Hypoxia-inducible factor 1 (HIF-1) plays a key role in the reprogramming of cancer metabolism by activating transcription of genes encoding glucose transporters and glycolytic enzymes, which take up glucose and convert it to lactate; pyruvate dehydrogenase kinase 1, which shunts pyruvate away from the mitochondria; and BNIP3, which triggers selective mitochondrial autophagy. The shift from oxidative to glycolytic metabolism allows maintenance of redox homeostasis and cell survival under conditions of prolonged hypoxia. Many metabolic abnormalities in cancer cells increase HIF-1 activity. As a result, a feed-forward mechanism can be activated that drives HIF-1 activation and may promote tumor progression.

Metastatic cancer is characterized by reprogramming of cellular metabolism leading to increased uptake of glucose for use as both an anabolic and catabolic substrate. Increased glucose uptake is such a reliable feature that it is utilized clinically to detect metastases by positron emission tomography using 18F-fluorodeoxyglucose (FDG-PET) with a sensitivity of ~90% [1]. As with all aspects of cancer biology, the details of metabolic reprogramming differ widely among individual tumors. However, the role of specific signaling pathways and transcription factors in this process is now understood in considerable detail. This review will focus on the involvement of hypoxia-inducible factor 1 (HIF-1) in both mediating metabolic reprogramming and responding to metabolic alterations. The placement of HIF-1 both upstream and downstream of cancer metabolism results in a feed-forward mechanism that may play a major role in the development of the invasive, metastatic, and lethal cancer phenotype.

O2 concentrations are significantly reduced in many human cancers compared to the surrounding normal tissue. The median PO2 in breast cancers is ~10 mm Hg, as compared to ~65 mm Hg in normal breast tissue [2]. Reduced O2 availability induces HIF-1, which regulates the transcription of hundreds of genes [3*,4*] that encode proteins involved in every aspect of cancer biology, including: cell immortalization and stem cell maintenance; genetic instability; glucose and energy metabolism; vascularization; autocrine growth factor signaling; invasion and metastasis; immune evasion; and resistance to chemotherapy and radiation therapy [5].

HIF-1 is a transcription factor that consists of an O2-regulated HIF-1α and a constitutively expressed HIF-1β subunit [6]. In well-oxygenated cells, HIF-1α is hydroxylated on proline residue 402 (Pro-402) and/or Pro-564 by prolyl hydroxylase domain protein 2 (PHD2), which uses O2 and α-ketoglutarate as substrates in a reaction that generates CO2 and succinate as byproducts [7]. Prolyl-hydroxylated HIF-1α is bound by the von Hippel-Lindau tumor suppressor protein (VHL), which recruits an E3-ubiquitin ligase that targets HIF-1α for proteasomal degradation (Figure 1A). Asparagine 803 in the transactivation domain is hydroxylated in well-oxygenated cells by factor inhibiting HIF-1 (FIH-1), which blocks the binding of the coactivators p300 and CBP [7]. Under hypoxic conditions, the prolyl and asparaginyl hydroxylation reactions are inhibited by substrate (O2) deprivation and/or the mitochondrial generation of reactive oxygen species (ROS), which may oxidize Fe(II) present in the catalytic center of the hydroxylases [8].

HIF-1 and metabolism  nihms156580f1

HIF-1 and metabolism nihms156580f1

HIF-1 and metabolism

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2822127/bin/nihms156580f1.gif

Figure 1 HIF-1 and metabolism. (A) Regulation of HIF-1α protein synthesis and stability and HIF-1-dependent metabolic reprogramming. The rate of translation of HIF-1α mRNA into protein in cancer cells is dependent upon the activity of the mammalian 

The finding that acute changes in PO2 increase mitochondrial ROS production suggests that cellular respiration is optimized at physiological PO2 to limit ROS generation and that any deviation in PO2 — up or down — results in increased ROS generation. If hypoxia persists, induction of HIF-1 leads to adaptive mechanisms to reduce ROS and re-establish homeostasis, as described below. Prolyl and asparaginyl hydroxylation provide a molecular mechanism by which changes in cellular oxygenation can be transduced to the nucleus as changes in HIF-1 activity. This review will focus on recent advances in our understanding of the role of HIF-1 in controlling glucose and energy metabolism, but it should be appreciated that any increase in HIF-1 activity that leads to changes in cell metabolism will also affect many other critical aspects of cancer biology [5] that will not be addressed here.

HIF-1 target genes involved in glucose and energy metabolism

HIF-1 activates the transcription of SLC2A1 and SLC2A3, which encode the glucose transporters GLUT1 and GLUT3, respectively, as well as HK1 and HK2, which encode hexokinase, the first enzyme of the Embden-Meyerhoff (glycolytic) pathway [9]. Once taken up by GLUT and phosphorylated by HK, FDG cannot be metabolized further; thus, FDG-PET signal is determined by FDG delivery to tissue (i.e. perfusion) and GLUT/HK expression/activity. Unlike FDG, glucose is further metabolized to pyruvate by the action of the glycolytic enzymes, which are all encoded by HIF-1 target genes (Figure 1A). Glycolytic intermediates are also utilized for nucleotide and lipid synthesis [10]. Lactate dehydrogenase A (LDHA), which converts pyruvate to lactate, and monocarboxylate transporter 4 (MCT4), which transports lactate out of the cell (Figure 1B), are also regulated by HIF-1 [9,11]. Remarkably, lactate produced by hypoxic cancer cells can be taken up by non-hypoxic cells and used as a respiratory substrate [12**].

Pyruvate represents a critical metabolic control point, as it can be converted to acetyl coenzyme A (AcCoA) by pyruvate dehydrogenase (PDH) for entry into the tricarboxylic acid (TCA) cycle or it can be converted to lactate by LDHA (Figure 1B). Pyruvate dehydrogenase kinase (PDK), which phosphorylates and inactivates the catalytic domain of PDH, is encoded by four genes and PDK1 is activated by HIF-1 [13,14]. (Further studies are required to determine whether PDK2PDK3, or PDK4 is regulated by HIF-1.) As a result of PDK1 activation, pyruvate is actively shunted away from the mitochondria, which reduces flux through the TCA cycle, thereby reducing delivery of NADH and FADH2 to the electron transport chain. This is a critical adaptive response to hypoxia, because in HIF-1α–null mouse embryo fibroblasts (MEFs), PDK1 expression is not induced by hypoxia and the cells die due to excess ROS production, which can be ameliorated by forced expression of PDK1 [13]. MYC, which is activated in ~40% of human cancers, cooperates with HIF-1 to activate transcription of PDK1, thereby amplifying the hypoxic response [15]. Pharmacological inhibition of HIF-1 or PDK1 activity increases O2 consumption by cancer cells and increases the efficacy of a hypoxia-specific cytotoxin [16].

Hypoxia also induces mitochondrial autophagy in many human cancer cell lines through HIF-1-dependent expression of BNIP3 and a related BH3 domain protein, BNIP3L [19**]. Autocrine signaling through the platelet-derived growth factor receptor in cancer cells increases HIF-1 activity and thereby increases autophagy and cell survival under hypoxic conditions [21]. Autophagy may also occur in a HIF-1-independent manner in response to other physiological stimuli that are associated with hypoxic conditions, such as a decrease in the cellular ATP:AMP ratio, which activates AMP kinase signaling [22].

In clear cell renal carcinoma, VHL loss of function (LoF) results in constitutive HIF-1 activation, which is associated with impaired mitochondrial biogenesis that results from HIF-1-dependent expression of MXI1, which blocks MYC-dependent expression of PGC-1β, a coactivator that is required for mitochondrial biogenesis [23]. Inhibition of wild type MYC activity in renal cell carcinoma contrasts with the synergistic effect of HIF-1 and oncogenic MYC in activating PDK1 transcription [24].

Genetic and metabolic activators of HIF-1

Hypoxia plays a critical role in cancer progression [2,5] but not all cancer cells are hypoxic and a growing number of O2-independent mechanisms have been identified by which HIF-1 is induced [5]. Several mechanisms that are particularly relevant to cancer metabolism are described below.

Activation of mTOR

Alterations in mitochondrial metabolism

NAD+ levels

It is of interest that the NAD+-dependent deacetylase sirtuin 1 (SIRT1) was found to bind to, deacetylate, and increase transcriptional activation by HIF-2α but not HIF-1α [42**]. Another NAD+-dependent enzyme is poly(ADP-ribose) polymerase 1 (PARP1), which was recently shown to bind to HIF-1α and promote transactivation through a mechanism that required the enzymatic activity of PARP1 [43]. Thus, transactivation mediated by both HIF-1α and HIF-2α can be modulated according to NAD+ levels.

Nitric oxide

Increased expression of nitric oxide (NO) synthase isoforms and increased levels of NO have been shown to increase HIF-1α protein stability in human oral squamous cell carcinoma [44]. In prostate cancer, nuclear co-localization of endothelial NO synthase, estrogen receptor β, HIF-1α, and HIF-2α was associated with aggressive disease and the proteins were found to form chromatin complexes on the promoter of TERT gene encoding telomerase [45**]. The NOS2 gene encoding inducible NO synthase is HIF-1 regulated [5], suggesting another possible feed-forward mechanism.

7.9.9 In Vivo HIF-Mediated Reductive Carboxylation

Gameiro PA1Yang JMetelo AMPérez-Carro R, et al.
Cell Metab. 2013 Mar 5; 17(3):372-85.
http://dx.doi.org/10.1016%2Fj.cmet.2013.02.002

Hypoxic and VHL-deficient cells use glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate. To gain insights into the role of HIF and the molecular mechanisms underlying RC, we took advantage of a panel of disease-associated VHL mutants and showed that HIF expression is necessary and sufficient for the induction of RC in human renal cell carcinoma (RCC) cells. HIF expression drastically reduced intracellular citrate levels. Feeding VHL-deficient RCC cells with acetate or citrate or knocking down PDK-1 and ACLY restored citrate levels and suppressed RC. These data suggest that HIF-induced low intracellular citrate levels promote the reductive flux by mass action to maintain lipogenesis. Using [1–13C] glutamine, we demonstrated in vivo RC activity in VHL-deficient tumors growing as xenografts in mice. Lastly, HIF rendered VHL-deficient cells sensitive to glutamine deprivation in vitro, and systemic administration of glutaminase inhibitors suppressed the growth of RCC cells as mice xenografts.

Cancer cells undergo fundamental changes in their metabolism to support rapid growth, adapt to limited nutrient resources, and compete for these supplies with surrounding normal cells. One of the metabolic hallmarks of cancer is the activation of glycolysis and lactate production even in the presence of adequate oxygen. This is termed the Warburg effect, and efforts in cancer biology have revealed some of the molecular mechanisms responsible for this phenotype (Cairns et al., 2011). More recently, 13C isotopic studies have elucidated the complementary switch of glutamine metabolism that supports efficient carbon utilization for anabolism and growth (DeBerardinis and Cheng, 2010). Acetyl-CoA is a central biosynthetic precursor for lipid synthesis, being generated from glucose-derived citrate in well-oxygenated cells (Hatzivassiliou et al., 2005). Warburg-like cells, and those exposed to hypoxia, divert glucose to lactate, raising the question of how the tricarboxylic acid (TCA) cycle is supplied with acetyl-CoA to support lipogenesis. We and others demonstrated, using 13C isotopic tracers, that cells under hypoxic conditions or defective mitochondria primarily utilize glutamine to generate citrate and lipids through reductive carboxylation (RC) of α-ketoglutarate by isocitrate dehydrogenase 1 (IDH1) or 2 (IDH2) (Filipp et al., 2012Metallo et al., 2012;Mullen et al., 2012Wise et al., 2011).

The transcription factors hypoxia inducible factors 1α and 2α (HIF-1α, HIF-2α) have been established as master regulators of the hypoxic program and tumor phenotype (Gordan and Simon, 2007Semenza, 2010). In addition to tumor-associated hypoxia, HIF can be directly activated by cancer-associated mutations. The von Hippel-Lindau (VHL) tumor suppressor is inactivated in the majority of sporadic clear-cell renal carcinomas (RCC), with VHL-deficient RCC cells exhibiting constitutive HIF-1α and/or HIF-2α activity irrespective of oxygen availability (Kim and Kaelin, 2003). Previously, we showed that VHL-deficient cells also relied on RC for lipid synthesis even under normoxia. Moreover, metabolic profiling of two isogenic clones that differ in pVHL expression (WT8 and PRC3) suggested that reintroduction of wild-type VHL can restore glucose utilization for lipogenesis (Metallo et al., 2012). The VHL tumor suppressor protein (pVHL) has been reported to have several functions other than the well-studied targeting of HIF. Specifically, it has been reported that pVHL regulates the large subunit of RNA polymerase (Pol) II (Mikhaylova et al., 2008), p53 (Roe et al., 2006), and the Wnt signaling regulator Jade-1. VHL has also been implicated in regulation of NF-κB signaling, tubulin polymerization, cilia biogenesis, and proper assembly of extracellular fibronectin (Chitalia et al., 2008Kim and Kaelin, 2003Ohh et al., 1998Thoma et al., 2007Yang et al., 2007). Hypoxia inactivates the α-ketoglutarate-dependent HIF prolyl hydroxylases, leading to stabilization of HIF. In addition to this well-established function, oxygen tension regulates a larger family of α-ketoglutarate-dependent cellular oxygenases, leading to posttranslational modification of several substrates, among which are chromatin modifiers (Melvin and Rocha, 2012). It is therefore conceivable that the effect of hypoxia on RC that was reported previously may be mediated by signaling mechanisms independent of the disruption of the pVHL-HIF interaction. Here we (1) demonstrate that HIF is necessary and sufficient for RC, (2) provide insights into the molecular mechanisms that link HIF to RC, (3) detected RC activity in vivo in human VHL-deficient RCC cells growing as tumors in nude mice, (4) provide evidence that the reductive phenotype ofVHL-deficient cells renders them sensitive to glutamine restriction in vitro, and (5) show that inhibition of glutaminase suppresses growth of VHL-deficient cells in nude mice. These observations lay the ground for metabolism-based therapeutic strategies for targeting HIF-driven tumors (such as RCC) and possibly the hypoxic compartment of solid tumors in general.

Functional Interaction between pVHL and HIF Is Necessary to Inhibit RC

Figure 1  HIF Inactivation Is Necessary for Downregulation of Reductive Carboxylation by pVHL

We observed a concurrent regulation in glucose metabolism in the different VHL mutants. Reintroduction of wild-type or type 2C pVHL mutant, which can meditate HIF-α destruction, stimulated glucose oxidation via pyruvate dehydrogenase (PDH), as determined by the degree of 13C-labeled TCA cycle metabolites (M2 enrichment) (Figures 1D and 1E). In contrast, reintroduction of an HIF nonbinding Type 2B pVHL mutant failed to stimulate glucose oxidation, resembling the phenotype observed in VHL-deficient cells (Figures 1D and 1E). Additional evidence for the overall glucose utilization was obtained from the enrichment of M3 isotopomers using [U13-C6]glucose (Figure S1A), which shows a lower contribution of glucose-derived carbons to the TCA cycle in VHL-deficient RCC cells (via pyruvate carboxylase and/or continued TCA cycling).

To test the effect of HIF activation on the overall glutamine incorporation in the TCA cycle, we labeled an isogenic pair of VHL-deficient and VHL-reconstituted UMRC2 cells with [U-13C5]glutamine, which generates M4 fumarate, M4 malate, M4 aspartate, and M4 citrate isotopomers through glutamine oxidation. As seen in Figure S1BVHL-deficient/VHL-positive UMRC2 cells exhibit similar enrichment of M4 fumarate, M4 malate, and M4 asparate (but not citrate) showing that VHL-deficient cells upregulate reductive carboxylation without compromising oxidative metabolism from glutamine. …  Labeled carbon derived from [5-13C1]glutamine can be incorporated into fatty acids exclusively through RC, and the labeled carbon cannot be transferred to palmitate through the oxidative TCA cycle (Figure 1B, red carbons). Tracer incorporation from [5-13C1]glutamine occurs in the one carbon (C1) of acetyl-CoA, which results in labeling of palmitate at M1, M2, M3, M4, M5, M6, M7, and M8 mass isotopomers. In contrast, lipogenic acetyl-CoA molecules originating from [U-13C6]glucose are fully labeled, and the labeled palmitate is represented by M2, M4, M6, M8, M10, M12, M14, and M16 mass isotopomers.

Figure 2 HIF Inactivation Is Necessary for Downregulation of Reductive Lipogenesis by pVHL

To determine the specific contribution from glucose oxidation or glutamine reduction to lipogenic acetyl-CoA, we performed isotopomer spectral analysis (ISA) of palmitate labeling patterns. ISA indicates that wild-type pVHL or pVHL L188V mutant-reconstituted UMRC2 cells relied mainly on glucose oxidation to produce lipogenic acetyl-CoA, while UMRC2 cells reconstituted with a pVHL mutant defective in HIF inactivation (Y112N or Y98N) primarily employed RC. Upon disruption of the pVHL-HIF interaction, glutamine becomes the preferred substrate for lipogenesis, supplying 70%–80% of the lipogenic acetyl-CoA (Figure 2C). This is not a cell-line-specific phenomenon, but it applies to VHL-deficient human RCC cells in general; the same changes are observed in 786-O cells reconstituted with wild-type pVHL or mutant pVHL or infected with vector only as control (Figure S2).

HIF Is Sufficient to Induce RC (reductive carboxylation) from Glutamine in RCC Cells

As shown in Figure 3C, reintroduction of wild-type VHLinto 786-O cells suppressed RC, whereas the expression of the constitutively active HIF-2α mutant was sufficient to stimulate this reaction, restoring the M1 enrichment of TCA cycle metabolites observed in VHL-deficient 786-O cells. Expression of HIF-2α P-A also led to a concomitant decrease in glucose oxidation, corroborating the metabolic alterations observed in glutamine metabolism (Figures 3D and 3E).

Figure 3 Expression of HIF-2α Is Sufficient to Induce Reductive Carboxylation and Lipogenesis from Glutamine in RCC Cells

Expression of HIF-2α P-A in 786-O cells phenocopied the loss-of-VHL with regards to glutamine reduction for lipogenesis (Figure 3G), suggesting that HIF-2α can induce the glutamine-to-lipid pathway in RCC cells per se. Although reintroduction of wild-type VHL restored glucose oxidation in UMRC2 and UMRC3 cells (Figures S3B–S3I), HIF-2α P-A expression did not measurably affect the contribution of each substrate to the TCA cycle or lipid synthesis in these RCC cells (data not shown). UMRC2 and UMRC3 cells endogenously express both HIF-1α and HIF-2α, whereas 786-O cells exclusively express HIF-2α. There is compelling evidence suggesting, at least in RCC cells, that HIF-α isoforms have overlapping—but also distinct—functions and their roles in regulating bioenergetic processes remain an area of active investigation. Overall, HIF-1α has an antiproliferative effect, and its expression in vitro leads to rapid death of RCC cells while HIF-2α promotes tumor growth (Keith et al., 2011Raval et al., 2005).

Metabolic Flux Analysis Shows Net Reversion of the IDH Flux upon HIF Activation

To determine absolute fluxes in RCC cells, we employed 13C metabolic flux analysis (MFA) as previously described (Metallo et al., 2012). Herein, we performed MFA using a combined model of [U-13C6]glucose and [1-13C1]glutamine tracer data sets from the 786-O derived isogenic clones PRC3 (VHL−/ −)/WT8 (VHL+) cells, which show a robust metabolic regulation by reintroduction of pVHL. To this end, we first determined specific glucose/glutamine consumption and lactate/glutamate secretion rates. As expected, PRC3 exhibited increased glucose consumption and lactate production when compared to WT8 counterparts (Figure 4A). While PRC3 exhibited both higher glutamine consumption and glutamate production rates than WT8 (Figure 4A), the net carbon influx was higher in PRC3 cells (Figure 4B). Importantly, the fitted data show that the flux of citrate to α-ketoglutarate was negative in PRC3 cells (Figure 4C). This indicates that the net (forward plus reverse) flux of isocitrate dehydrogenase and aconitase (IDH + ACO) is toward citrate production. The exchange flux was also higher in PRC3 than WT8 cells, whereas the PDH flux was lower in PRC3 cells. In agreement with the tracer data, these MFA results strongly suggest that the reverse IDH + ACO fluxes surpass the forward flux in VHL-deficient cells. The estimated ATP citrate lyase (ACLY) flux was also lower in PRC3 than in WT8 cells. Furthermore, the malate dehydrogenase (MDH) flux was negative, reflecting a net conversion of oxaloacetate into malate in VHL-deficient cells (Figure 4C). This indicates an increased flux through the reductive pathway downstream of IDH, ACO, and ACLY. Additionally, some TCA cycle flux estimates downstream of α-ketoglutarate were not significantly different between PRC and WT8 (Table S1). This shows that VHL-deficient cells maintain glutamine oxidation while upregulating reductive carboxylation (Figure S1B). This finding is in agreement with the higher glutamine uptake observed in VHL-deficient cells. Table S1 shows the metabolic network and complete MFA results. …

Addition of citrate in the medium, in contrast to acetate, led to an increase in the citrate-to-α-ketoglutarate ratio (Figure 5L) and absolute citrate levels (Figure S4H) not only in VHL-deficient but alsoVHL-reconstituted cells. The ability of exogenous citrate, but not acetate, to also affect RC in VHL-reconstituted cells may be explained by compartmentalization differences or by allosteric inhibition of citrate synthase (Lehninger, 2005); that is, the ability of acetate to raise the intracellular levels of citrate may be limited in (VHL-reconstituted) cells that exhibit high endogenous levels of citrate. Whatever the mechanism, the results imply that increasing the pools of intracellular citrate has a direct biochemical effect in cells with regards to their reliance on RC. Finally, we assayed the transcript and protein levels of enzymes involved in the reductive utilization of glutamine and did not observe significant differences between VHL-deficient andVHL-reconstituted UMRC2 cells (Figures S4I and S4J), suggesting that HIF does not promote RC by direct transactivation of these enzymes. The IDH1/IDH2 equilibrium is defined as follows:

[α−ketoglutrate][NADPH][CO2]/[Isocitrate][NADP+]=K(IDH)

Figure 5 Regulation of HIF-Mediated Reductive Carboxylation by Citrate Levels

We sought to investigate whether HIF could affect the driving force of the IDH reaction by also enhancing NADPH production. We did not observe a significant alteration of the NADP+/NADPH ratio between VHL-deficient and VHL-positive cells in the cell lysate (Figure S4I). Yet, we determined the ratio of the free dinucleotides using the measured ratios of suitable oxidized (α-ketoglutarate) and reduced (isocitrate/citrate) metabolites that are linked to the NADP-dependent IDH enzymes. The determined ratios (Figure S4J) are in close agreement with the values initially reported by the Krebs lab (Veech et al., 1969) and showed that HIF-expressing UMRC2 cells exhibit a higher NADP+/NADPH ratio. Collectively, these data strongly suggest that HIF-regulated citrate levels modulate the reductive flux to maintain adequate lipogenesis.

Reductive Carboxylation from Glutamine Is Detectable In Vivo

Figure 6 Evidence for Reductive Carboxylation Activity In Vivo

Loss of VHL Renders RCC Cells Sensitive to Glutamine Deprivation

We hypothesized that VHL deficiency results in cell addiction to glutamine for proliferation. We treated the isogenic clones PRC3 (VHL-deficient cells) and WT8 (VHL-reconstituted cells) with the glutaminase inhibitor 968 (Wang et al., 2010a). VHL-deficient PRC3 cells were more sensitive to treatment with 968, compared to the VHL-reconstituted WT8 cells (Figure 7A). To confirm that this is not only a cell-line-specific phenomenon, we also cultured UMRC2 cells in the presence of 968 or diluent control and showed selective sensitivity of VHL-deficient cells (Figure 7B).

Figure 7 VHL-Deficient Cells and Tumors Are Sensitive to Glutamine Deprivation

(A–E) Cell proliferation is normalized to the corresponding cell type grown in 1 mM glutamine-containing medium. Effect of treatment with glutaminase (GLS) inhibitor 968 in PRC3/WT8 (A) and UMRC2 cells (B). Rescue of GLS inhibition with dimethyl alpha-ketoglutarate (DM-Akg; 4 mM) or acetate (4 mM) in PRC3/WT8 clonal cells (C) and polyclonal 786-O cells (D). Effect of GLS inhibitor BPTES in UMRC2 cells (E). Student’s t test compares VHL-reconstituted cells to control cells in (A), (B), and (E) and DM-Akg or acetate-rescued cells to correspondent control cells treated with 968 only in (C) and (D) (asterisk in parenthesis indicates comparison between VHL-reconstituted to control cells). Error bars represent SEM.

(F) GLS inhibitor BPTES suppresses growth of human UMRC3 RCC cells as xenografts in nu/nu mice. When the tumors reached 100mm3, injections with BPTES or vehicle control were carried out daily for 14 days (n = 12). BPTES treatment decreases tumor size and mass (see insert). Student’s t test compares control to BPTES-treated mice (F). Error bars represent SEM.

(G) Diagram showing the regulation of reductive carboxylation by HIF.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4003458/bin/nihms449661f7.jpg

In summary, our findings show that HIF is necessary and sufficient to promote RC from glutamine. By inhibiting glucose oxidation in the TCA cycle and reducing citrate levels, HIF shifts the IDH reaction toward RC to support citrate production and lipogenesis (Figure 7G). The reductive flux is active in vivo, fuels tumor growth, and can potentially be targeted pharmacologically. Understanding the significance of reductive glutamine metabolism in tumors may lead to metabolism-based therapeutic strategies.

Along with others, we reported that hypoxia and loss of VHL engage cells in reductive carboxylation (RC) from glutamine to support citrate and lipid synthesis (Filipp et al., 2012Metallo et al., 2012Wise et al., 2011). Wise et al. (2011) suggested that inactivation of HIF in VHL-deficient cells leads to reduction of RC. These observations raise the hypothesis that HIF, which is induced by hypoxia and is constitutively active inVHL-deficient cells, mediates RC. In our current work, we provide mechanistic insights that link HIF to RC. First, we demonstrate that polyclonal reconstitution of VHL in several human VHL-deficient RCC cell lines inhibits RC and restores glucose oxidation. Second, the VHL mutational analysis demonstrates that the ability of pVHL to mitigate reductive lipogenesis is mediated by HIF and is not the outcome of previously reported, HIF-independent pVHL function(s). Third, to prove our hypothesis we showed that constitutive expression of a VHL-independent HIF mutant is sufficient to phenocopy the reductive phenotype observed in VHL-deficient cells. In addition, we showed that RC is not a mere in vitro phenomenon, but it can be detected in vivo in human tumors growing as mouse xenografts. Lastly, treatment of VHL-deficient human xenografts with glutaminase inhibitors led to suppression of their growth as tumors.

7.9.10 Evaluation of HIF-1 inhibitors as anticancer agents

Semenza GL1.
Drug Discov Today. 2007 Oct; 12(19-20):853-9
http://dx.doi.org/10.1016/j.drudis.2007.08.006

Hypoxia-inducible factor 1 (HIF-1) regulates the transcription of many genes involved in key aspects of cancer biology, including immortalization, maintenance of stem cell pools, cellular dedifferentiation, genetic instability, vascularization, metabolic reprogramming, autocrine growth factor signaling, invasion/metastasis, and treatment failure. In animal models, HIF-1 overexpression is associated with increased tumor growth, vascularization, and metastasis, whereas HIF-1 loss-of-function has the opposite effect, thus validating HIF-1 as a target. In further support of this conclusion, immunohistochemical detection of HIF-1α overexpression in biopsy sections is a prognostic factor in many cancers. A growing number of novel anticancer agents have been shown to inhibit HIF-1 through a variety of molecular mechanisms. Determining which combination of drugs to administer to any given patient remains a major obstacle to improving cancer treatment outcomes.

Aurelian Udristioiu

Aurelian

Aurelian Udristioiu

Lab Director at Emergency County Hospital Targu Jiu

Mechanisms that control T cell metabolic reprogramming are now coming to light, and many of the same oncogenes importance in cancer metabolism are also crucial to drive T cell metabolic transformations, most notably Myc, hypoxia inducible factor (HIF)1a, estrogen-related receptor (ERR) a, and the mTOR pathway.
The proto-oncogenic transcription factor, Myc, is known to promote transcription of genes for the cell cycle, as well as aerobic glycolysis and glutamine metabolism. Recently, Myc has been shown to play an essential role in inducing the expression of glycolytic and glutamine metabolism genes in the initial hours of T cell activation. In a similar fashion, the transcription factor (HIF)1a can up-regulate glycolytic genes to allow cancer cells to survive under hypoxic conditions

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