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Two research groups from Harvard Medical School based at Dana Faber Cancer Institute have discovered a genetic mechanism in a cancer cells that influence whether they respond or resist to immunotherapy drugs, otherwise called as checkpoint inhibitors. The results are published in Science as part of two articles. One article is focused on clinical trial patients with advanced kidney cancer treated with checkpoint inhibitors comes from Eliezer van Allen’s group at Dana Farber Cancer Institute and Toni Choueiri group at Lank Center for Genitourinary Oncology at Dana Farber. The second articles is focused on identifying the immunotherapy resistance mechanism in melanoma cells comes from Kai Wucherpfennig at Dana-Farber and Shirley Liu at Dana -Farber. The two groups joined on that the resistance to immune checkpoint blockade is critically controlled by changes in a group of proteins that regulate how DNA is packaged in cells. The assortment of proteins, called a chromatin remodeling complex, is known as SWI/SNF. Its components are encoded by different genes, among them ARID2, PBRM1 and BRD7. SWI/SNF’s job is to open up stretches of tightly wound DNA so that its blueprints can be read by the cell to activate certain genes to make proteins.
Scientists led by Van Allen and Choueiri wanted a clarification for why some patients with a form of metastatic kidney cancer, clear cell renal carcinoma (ccRCC) gain clinical benefit from treatment with immune checkpoint inhibitors that block the PD-1 checkpoint while others patients don’t. The researchers use whole exome DNA sequencing to analyze tumor samples from 35 patients treated in a clinical trial with Opdivo, a checkpoint blocker nivolumab to search for other characteristics of ccRCC tumors that influence immunotherapy response and/or resistance. The scientist discovered that patients from the trial benefited from the immunotherapy treatment with longer survival and progression free survival were those whose tumors lacked a functioning PRBM1 gene. Loss of PRBM1 gene function caused cancer cells to have increased expression of other genes including those in the gene pathway known as IL6/JAK-STAT3, which is involved in immune system stimulation.
When the PBRM1 gene was knocked out in experiments, the melanoma cells became more sensitive to interferon gamma produced by T cells and, in response, produced signaling molecules that recruited more tumor-fighting T cells into the tumor. The two other genes in the PBAF complex—ARID2 and BRD7—are also found mutated in some cancers, according to the researchers, and those cancers, like the melanoma lacking ARID2 function, may also respond better to checkpoint blockade. According to the researchers, finding ways to alter those target molecules “will be important to extend the benefit of immunotherapy to larger patient populations, including cancers that thus far are refractory to immunotherapy.”
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
We here move on to a number of specific, key published work on signaling, and look at the possible therapeutic applications to disease states.
Scripps Research Professor Wolfram Ruf and colleagues have identified a key connection between
the signaling pathways and the immune system spiraling out of control involving
the coagulation system and vascular endothelium that,
if disrupted may be a target for sepsis. (Science Daily, Feb 29, 2008).
It may be caused by a bacterial infection that enters the bloodstream, but
we now recognize the same cascade not triggered by bacterial invasion.
The acute respiratory distress syndrome (ARDS) has been defined as
a severe form of acute lung injury featuring
pulmonary inflammation and increased capillary leak.
ARDS is associated with a high mortality rate and accounts for 100,000 deaths annually in the United States. ARDS may arise in a number of clinical situations, especially in patients with sepsis. A well-described pathophysiological model of ARDS is one form of
the acute lung inflammation mediated by
neutrophils,
cytokines, and
oxidant stress.
Neutrophils are major effect cells at the frontier of
innate immune responses, and they play
a critical role in host defense against invading microorganisms.
The tissue injury appears to be related to
proteases and toxic reactive oxygen radicals
released from activated neutrophils.
In addition, neutrophils can produce cytokines and chemokines that
enhance the acute inflammatory response.
Neutrophil accumulation in the lung plays a pivotal role in the pathogenesis of acute lung injury during sepsis. Directed movement of neutrophils is
mediated by a group of chemoattractants,
especially CXC chemokines.
Local lung production of CXC chemokines is intensified during experimental sepsis induced by cecal ligation and puncture (CLP).
Sepsis, Multi-organ Dysfunction Syndrome, and Septic Shock: A Conundrum of Signaling Pathways Cascading Out of Control
Schematic of the ‘focal adhesion clutch’ on stiff (a) versus soft (b) extracellular matrix (ECM). In all cases, integrins are coupled to F-actin via linker proteins (for example, talin and vinculin). The linker proteins move backwards (as indicated by the small arrows) as F-actin also moves backwards, under pushing forces from actin polymerization and/or pulling forces from myosin II activity. This mechanism transfers force from actin to integrins, which pull on the ECM. A stiff ECM (a) resists this force so that the bound integrins remain immobile. A compliant matrix (b) deforms under this force (as indicated by the compressed ECM labelled as deformed matrix) so that the bound integrins can also move backwards. Their movement reduces the net loading rate on all the force-bearing elements, which results in altered cellular responses
The ECM is a complex mixture of matrix molecules, including –
and nonmatrix proteins, – including growth factors
The integrin receptor formed from the binding of α and β subunits is
shaped like a globular head supported by two rod-like legs (Figure 1).
Most of the contact between the two subunits occurs in the head region, with
the intracellular tails of the subunits forming the legs of the receptor.
Integrin recognition of ligands is not constitutive but
is regulated by alteration of integrin affinity for ligand binding.
For integrin binding to ligands to occur
the integrin must be primed and activated, both of which involve
conformational changes to the receptor.
Linking integrin conformation to function
Figure Integrin binding to extracellular matrix (ECM). Conformational changes to integrin structure and clustering of subunits which allow enhanced function of the receptor.
Integrins work alongside other proteins such as
cadherins,
immunoglobulin superfamily
cell adhesion molecules,
selectins, and
syndecans
to mediate
cell–cell and
cell–matrix interactions and communication.
Activation of adhesion receptors triggers the formation of matrix contacts in which
bound matrix components,
adhesion receptors,
and associated intracellular cytoskeletal and signaling molecules
form large functional, localized multiprotein complexes.
Cell–matrix contacts are important in a variety of different cell and
tissue properties including
1.embryonic development,
2.inflammatory responses,
3.wound healing,
4.and adult tissue homeostasis.
Integrin extracellular binding activity is regulated from inside the cell and binding to the ECM induces signals that are transmitted into the cell. This bidirectional signaling requires
dynamic,
spatially, and
temporally regulated formation and
disassembly of multiprotein complexes that
form around the short cytoplasmic tails of integrins.
Ligand binding to integrin family members leads to clustering of integrin molecules in the plasma membrane and recruitment of actin filaments and intracellular signaling molecules to the cytoplasmic domain of the integrins. This forms focal adhesion complexes which are able to maintain
not only adhesion to the ECM
but are involved in complex signaling pathways
which include establishing
1.cell polarity,
2.directed cell migration, and
3.maintaining cell growth and survival.
Initial activation through integrin adhesion to matrix recruits up to around 50 diverse signaling molecules
to assemble the focal adhesion complex
which is capable of responding to environmental stimuli efficiently.
Mapping of the integrin
adhesome binding and signaling interactions
a network of 156 components linked together which can be modified by 690 interactions.
Genetic programming occurs with the binding of integrins to the ECM
Signal transduction pathway activation arising from integrin-ECM binding results in
changes in gene expression of cells and
leads to alterations in cell and tissue function.
Various different effects can arise depending on the
1.cell type,
2.matrix composition, and
3.integrins activated
It has been suggested that integrin-type I collagen interaction is necessary for
the phosphorylation and activation of osteoblast-specific transcription factors
present in committed osteoprogenitor cells.
During mechanical loading/stimulation of chondrocytes there is an
influx of ions across the cell membrane resulting from
activation of mechanosensitive ion channels
which can be inhibited by subunit-specific anti-integrin blocking antibodies or RGD peptides.
Using these strategies it was identified that
α5β1 integrin is a major mechanoreceptor in articular chondrocyte
responses to mechanical loading/stimulation.
Osteoarthritic chondrocytes show a depolarization response to 0.33 Hz stimulation
in contrast to the hyperpolarization response of normal chondrocytes.
The mechanotransduction pathway in chondrocytes derived from normal and osteoarthritic cartilage
both involve recognition of the mechanical stimulus
by integrin receptors resulting in
the activation of integrin signaling pathways
leading to the generation of a cytokine loop.
Normal and osteoarthritic chondrocytes show differences
at multiple stages of the mechanotransduction cascade.
inhibiting tension through interference with Rho signaling,
similar to the case of the immediate and early responses, but it was also prevented by
blocking mechanosensitive ion channels or
by inhibiting Src tyrosine kinases.
All adaptive responses were suppressed by cooling cells to 4°C to slow biochemical remodeling. Thus, cells use multiple mechanisms to sense and respond to static and dynamic changes in the level of mechanical stress applied to integrins.
Microtubule-Stimulated ADP Release, ATP Binding, and Force Generation In Transport Kinesins
All three classes of molecular motor proteins are now known to be
large protein families with diverse cellular functions.
Both the kinesin family and the myosin family have been defined and their proteins grouped into subfamilies. Finally, the elusive cytoplasmic version of dynein was identified and a multigene family of flagellar and cytoplasmic dyneins defined. Members of a given motor protein family share
significant homology in their motor domains with the defining member,
kinesin, dynein or myosin; but they also contain
unique protein domains that are specialized for interaction with different cargoes.
This large number of motor proteins may reflect
the number of cellular functions that require force generation or movement,
ranging from mitosis to morphogenesis to transport of vesicles.
Kinesins are a large family of microtubule (MT)-based motors that play important roles in many cellular activities including
mitosis,
motility, and
intracellular transport
Their involvement in a range of pathological processes
also highlights their significance as therapeutic targets and
the importance of understanding the molecular basis of their function
They are defined by their motor domains that contain both
the microtubule (MT) and
ATP binding sites.
Three ATP binding motifs—
the P-loop,
switch I,
switch II–
are highly conserved among
kinesins,
myosin motors, and
small GTPases.
They share a conserved mode of MT binding such that
MT binding,
ATP binding, and
hydrolysis
are functionally coupled for efficient MT-based work.
The interior of a cell is a hive of activity, filled with
proteins and other items moving from one location to another.
A network of filaments called microtubules forms tracks
along which so-called motor proteins carry these items.
Kinesins are one group of motor proteins, and a typical kinesin protein has
one end (called the ‘motor domain’) that can attach itself to the microtubules.
The other end links to the cargo being carried, and a ‘neck’ connects the two. When two of these proteins work together,
flexible regions of the neck allow the two motor domains to move past one another,
which enable the kinesin to essentially walk along a microtubule in a stepwise manner.
Although the two kinesins have been thought to move along the microtubule tracks in different ways, Atherton et al. find that the core mechanism used by their motor domains is the same.
When a motor domain binds to the microtubule, its shape changes,
first stimulating release of the breakdown products of ATP from the previous cycle.
This release makes room for a new ATP molecule to bind. The structural changes caused by ATP binding
produce larger changes in the flexible neck region that
enable individual motor domains within a kinesin pair to
co-ordinate their movement and move in a consistent direction.
The major and largely invariant point of contact between kinesin motor domains and the MT is helix-α4,
which lies at the tubulin intradimer interface.
The conformational changes in functionally important regions of each motor domain are described,
starting with the nucleotide-binding site,
from which all other conformational changes emanate.
The nucleotide-binding site (Figure 2) has three major elements:
(1) the P-loop (brown) is visible in all our reconstructions;
(2) loop9 (yellow, contains switch I) undergoes major conformational changes through the ATPase cycle; and
(3) loop11 (red, contains switch II) that connects strand-β7 to helix-α4, the conformation and flexibility of which is
determined by MT binding and motor nucleotide state.
Movement and extension of helix-α6 controls neck linker docking
the N-terminus of helix-α6 is closely associated with elements of the nucleotide binding site suggesting that
its conformation alters in response to different nucleotide states.
Further,
because the orientation of helix-α6 with respect to helix-α4 controls neck linker docking and
because helix-α4 is held against the MT during the ATPase cycle,
conformational changes in helix-α6 control movement of the neck linker.
Mechanical amplification and force generation involves conformational changes across the motor domain
A key conformational change in the motor domain following Mg-ATP binding is
peeling of the central β-sheet from the C-terminus of helix-α4 increasing their separation;
this is required to accommodate rotation of helix-α6 and consequent neck linker docking
ATP binding draws loop11 and loop9 closer together; causing
(1) tilting of most of the motor domain not contacting the MT towards the nucleotide-binding site,
(2) rotation, translation, and extension of helix-α6 which we propose contributes to force generation, and
(3) allows neck linker docking and biases movement of the 2nd head towards the MT plus end.
In both motors, microtubule binding promotes
ordered conformations of conserved loops that
stimulate ADP release,
enhance microtubule affinity and
prime the catalytic site for ATP binding.
ATP binding causes only small shifts of these nucleotide-coordinating loops but induces
large conformational changes elsewhere that
allow force generation and
neck linker docking towards the microtubule plus end.
The study presents evidence provide evidence for a conserved ATP-driven
mechanism for kinesins and
reveals the critical mechanistic contribution of the microtubule interface.
Phosphorylation at endothelial cell–cell junctions: Implications for VE-cadherin function
This review summarizes the role of VE-cadherin phosphorylation in the regulation of endothelial cell–cell junctions and highlights how this affects vascular permeability and leukocyte extravasation.
The vascular endothelium is the inner lining of blood vessels and
forms a physical barrier between the vessel lumen and surrounding tissue;
controlling the extravasation of fluids,
plasma proteins and leukocytes.
Changes in the permeability of the endothelium are tightly regulated. Under basal physiological conditions, there is a continuous transfer of substances across the capillary beds. In addition the endothelium can mediate inducible,
transient hyperpermeability
in response to stimulation with inflammatory mediators,
which takes place primarily in post-capillary venules
However, when severe, inflammation may result in dysfunction of the endothelial barrier
in various parts of the vascular tree, including large veins, arterioles and capillaries.
Dysregulated permeability is observed in various pathological conditions, such as
tumor-induced angiogenesis,
cerebrovascular accident and
atherosclerosis.
Two fundamentally different pathways regulate endothelial permeability,
the transcellular and
paracellular pathways.
Solutes and cells can pass through the body of endothelial cells via the transcellular pathway, which includes
vesicular transport systems,
fenestrae, and
biochemical transporters.
The paracellular route is controlled by
the coordinated opening and closing of endothelial junctions and
thereby regulates traffic across the intercellular spaces between endothelial cells.
Endothelial cells are connected by
tight, gap and
adherens junctions,
of which the latter, and particularly the adherens junction component,
vascular endothelial (VE)-cadherin,
are of central importance for the initiation and stabilization of cell–cell contacts.
Although multiple adhesion molecules are localized at endothelial junctions,
blocking the adhesive function of VE-cadherin using antibodies
is sufficient to disrupt endothelial junctions and
to increase endothelial monolayer permeability both in vitro and in vivo.
Like other cadherins, VE-cadherin mediates adhesion via
homophilic, calcium-dependent interactions.
This cell–cell adhesion
is strengthened by binding of cytoplasmic proteins, the catenins,
to the C-terminus of VE-cadherin.
VE-cadherin can directly bind
β-catenin and plakoglobin, which
both associate with the actin binding protein α-catenin.
Initially, α-catenin was thought to directly anchor cadherins to the actin cytoskeleton, but recently it became clear that
α-catenin cannot bind to both β-catenin and actin simultaneously.
Numerous lines of evidence indicate that p120-catenin
promotes VE-cadherin surface expression and stability at the plasma membrane.
Different models are proposed that describe how
p120-catenin regulates cadherin membrane dynamics, including the hypothesis
that p120-catenin functions as a ‘cap’ that prevents the interaction of VE-cadherin
with the endocytic membrane trafficking machinery.
In addition, p120-catenin might regulate VE-cadherin internalization
through interactions with small GTPases.
Cytoplasmic p120-catenin, which is not bound to VE-cadherin, has been shown to
decrease RhoA activity,
elevate active Rac1 and Cdc42, and thereby is thought
to regulate actin cytoskeleton organization and membrane trafficking.
The intact cadherin-catenin complex is required for proper functioning of the adherens junction.
Several mechanisms may be involved in the
regulation of the organization and function of the cadherin–catenin complex, including
endocytosis of the complex,
VE-cadherin cleavage and
actin cytoskeleton reorganization.
The remainder of this review primarily focuses on the
role of tyrosine phosphorylation in the control of VE-cadherin-mediated cell–cell adhesion.
Regulation of the adhesive function of VE-cadherin by tyrosine phosphorylation
It is a widely accepted concept that tyrosine phosphorylation of
components of the VE–cadherin-catenin complex
Correlates with the weakening of cell–cell adhesion.
A general idea has emerged that
tyrosine phosphorylation of the VE-cadherin complex
leads to the uncoupling of VE-cadherin from the actin cytoskeleton
through dissociation of catenins from the cadherin.
However, tyrosine phosphorylation of VE-cadherin
is required for efficient transmigration of leukocytes.
This suggests that VE-cadherin-mediated cell–cell contacts
1.are not just pushed open by the migrating leukocytes, but play
2.a more active role in the transmigration process.
A schematic overview of leukocyte adhesion-induced signals leading to VE-cadherin phosphorylation
Regulation of the integrity of endothelial cell–cell contacts by phosphorylation of VE-cadherin.
Regulation of the integrity of endothelial cell–cell contacts by phosphorylation of VE-cadherin
N-glycosylation status of E-cadherin controls cytoskeletal dynamics through the organization of distinct β-catenin- and γ-catenin-containing AJs
N-glycosylation of E-cadherin has been shown to inhibit cell–cell adhesion.
Specifically, our recent studies have provided evidence that
the reduction of E-cadherin N-glycosylation
promoted the recruitment of stabilizing components,
vinculin and serine/ threonine protein phosphatase 2A (PP2A), to adherens junctions (AJs)
and enhanced the association of AJs with the actin cytoskeleton.
Here, we examined the details of how
N-glycosylation of E-cadherin affected the molecular organization of AJs and their cytoskeletal interactions.
Using the hypoglycosylated E-cadherin variant, V13, we show that
V13/β-catenin complexes preferentially interacted with PP2A and with the microtubule motor protein dynein.
This correlated with dephosphorylation of the microtubule-associated protein tau, suggesting that
increased association of PP2A with V13-containing AJs promoted their tethering to microtubules.
These studies provide the first mechanistic insights into how N-glycosylation of E-cadherin drives changes in AJ composition through
the assembly of distinct β-catenin- and γ-catenin-containing scaffolds that impact the interaction with different cytoskeletal components
Cytoskeletal Basis of Ion Channel Function in Cardiac Muscle
MacKinnon. Fig 1 Ion channels exhibit three basic properties
In order to contract and accommodate the repetitive morphological changes induced by the cardiac cycle, cardiomyocytes
depend on their highly evolved and specialized cytoskeletal apparatus.
Defects in components of the cytoskeleton, in the long term,
affect the ability of the cell to compensate at both functional and structural levels.
In addition to the structural remodeling,
the myocardium becomes increasingly susceptible to altered electrical activity leading to arrhythmogenesis.
The development of arrhythmias secondary to structural remodeling defects has been noted, although the detailed molecular mechanisms are still elusive.
subjects with severe left ventricular chamber dilation such as in DCM can have left bundle branch block (LBBB), while right bundle branch block (RBBB) is more characteristic of right ventricular failure. LBBB and RBBB have both been repeatedly associated with AV block in heart failure.
The impact of volume overload on structural and electro-cardiographic alterations has been noted in cardiomyopathy patients treated with left ventricular assist device (LVAD) therapy, which puts the heart at mechanical rest.
In LVAD-treated subjects,
QRS- and both QT- and QTc duration decreased,
suggesting that QRS- and QT-duration are significantly influenced by mechanical load and
that the shortening of the action potential duration contributes to the improved contractile performance after LVAD support.
An early postoperative period study after cardiac unloading therapy in 17 HF patients showed that in the first two weeks after LVAD implantation,
HF was associated with a relatively high incidence of ventricular arrhythmias associated with QTc interval prolongation.
In addition, a recent retrospective study of 100 adult patients with advanced HF, treated with an axial-flow HeartMate LVAD suggested that
the rate of new-onset monomorphic ventricular tachycardia (MVT) was increased in LVAD treated patients compared to patients given only medical treatment,
The myocardium is exposed to severe and continuous biomechanical stress during each contraction-relaxation cycle. When fiber tension remains uncompensated or simply unbalanced,
it may represent a trigger for arrhythmogenesis caused by cytoskeletal stretching,
which ultimately leads to altered ion channel localization, and subsequent action potential and conduction alterations.
Cytoskeletal proteins not only provide the backbone of the cellular structure, but they also
maintain the shape and flexibility of the different sub-cellular compartments, including the
1.plasma membrane,
2.the double lipid layer, which defines the boundaries of the cell and where
ion channels are mainly localized.
The interaction between the sarcomere, which is the basic for the passive force during diastole and for the restoring force during systole.
Sarcomeric Proteins and Ion Channels
besides fiber stretch associated with mechanical and hemodynamic impairment, cytoskeletal alterations due to primary genetic defects or indirectly to alterations in response to cellular injury can potentially
1.affect ion channel anchoring, and trafficking, as well as
2.functional regulation by second messenger pathways,
3.causing an imbalance in cardiac ionic homeostasis that will trigger arrhythmogenesis.
Intense investigation of
the sarcomeric actin network,
the Z-line structure, and
chaperone molecules docking in the plasma membrane,
has shed new light on the molecular basis of
cytoskeletal interactions in regulating ion channels
Actin disruption using cytochalasin D, an agent that interferes with actin polymerization, increased Na+ channel activity in 90% of excised patches tested within 2 min, which indicated that
the integrity of the filamentous actin (F-actin) network was essential for the maintenance of normal Na+ channel function
These data were the first to support a role for the cytoskeleton in cardiac arrhythmias.
Molecular interactions between the cytoskeleton and ion channels
The figure illustrates the interactions between the ion channels on the sarcolemma, and the sarcomere in cardiac myocytes. Note that the Z-line is connected to the cardiac T-tubules. The diagram illustrates the complex protein-protein interactions that occur between structural components of the cytoskeleton and ion channels. The cytoskeleton is involved in regulating the metabolism of ion channels, modifying their expression, localization, and electrical properties.
sarcomere structure
It is important to be aware of the enormous variety of clinical presentations that derive from distinct variants in the same pool of genetic factors. Knowledge of these variants could facilitate tailoring the therapy of choice for each patient. In particular,
the recent findings of structural and functional links between
the cytoskeleton and ion channels
could expand the therapeutic interventions in
arrhythmia management in structurally abnormal myocardium, where aberrant binding
between cytoskeletal proteins can directly or indirectly alter ion channel function.
In the imtroduction to this series of discussions I pointed out JEDS Rosalino’s observation about the construction of a complex molecule of acetyl coenzyme A, and the amount of genetic coding that had to go into it. Furthermore, he observes – Millions of years later, or as soon as, the information of interaction leading to activity and regulation could be found in RNA, proteins like reverse transcriptase move this information to a more stable form (DNA). In this way it is easier to understand the use of CoA to make two carbon molecules more reactive.
acetylCoA
In the tutorial that follows we find support for the view that mechanisms and examples from the current literature, which give insight into the developments in cell metabolism, are achieving a separation from inconsistent views introduced by the classical model of molecular biology and genomics, toward a more functional cellular dynamics that is not dependent on the classic view. The classical view fits a rigid framework that is to genomics and metabolomics as Mendelian genetics if to multidimentional, multifactorial genetics. The inherent difficulty lies in two places:
Interactions between differently weighted determinants
A large part of the genome is concerned with regulatory function, not expression of the code
The goal of the tutorial was to achieve an understanding of how cell signaling occurs in a cell. Completion of the tutorial would provide
a basic understanding signal transduction and
the role of phosphorylation in signal transduction.
Regulation of the integrity of endothelial cell–cell contacts by phosphorylation of VE-cadherin
In addition – detailed knowledge of –
the role of Tyrosine kinases and
G protein-coupled receptors in cell signaling.
serine
threonine
protein kinase
We are constantly receiving and interpreting signals from our environment, which can come
in the form of light, heat, odors, touch or sound.
The cells of our bodies are also
constantly receiving signals from other cells.
These signals are important to
keep cells alive and functioning as well as
to stimulate important events such as
cell division and differentiation.
Signals are most often chemicals that can be found
in the extracellular fluid around cells.
These chemicals can come
from distant locations in the body (endocrine signaling by hormones), from
nearby cells (paracrine signaling) or can even
be secreted by the same cell (autocrine signaling).
Signaling molecules may trigger any number of cellular responses, including
changing the metabolism of the cell receiving the signal or
result in a change in gene expression (transcription) within the nucleus of the cell or both.
controlling the output of ribosomes.
To which I would now add..
result in either an inhibitory or a stimulatory effect
The three stages of cell signaling are:
Cell signaling can be divided into 3 stages:
Reception: A cell detects a signaling molecule from the outside of the cell.
Transduction: When the signaling molecule binds the receptor it changes the receptor protein in some way. This change initiates the process of transduction. Signal transduction is usually a pathway of several steps. Each relay molecule in the signal transduction pathway changes the next molecule in the pathway.
Response: Finally, the signal triggers a specific cellular response.
Signal Transduction – ligand binds to surface receptor
Membrane receptors function by binding the signal molecule (ligand) and causing the production of a second signal (also known as a second messenger) that then causes a cellular response. These types of receptors transmit information from the extracellular environment to the inside of the cell.
by changing shape or
by joining with another protein
once a specific ligand binds to it.
Examples of membrane receptors include
G Protein-Coupled Receptors and
Understanding these receptors and identifying their ligands and the resulting signal transduction pathways represent a major conceptual advance.
Intracellular receptors are found inside the cell, either in the cytopolasm or in the nucleus of the target cell (the cell receiving the signal).
Note that though change in gene expression is stated, the change in gene expression does not here imply a change in the genetic information – such as – mutation. That does not have to be the case in the normal homeostatic case.
This point is the differentiating case between what JEDS Roselino has referred as
a fast, adaptive reaction, that is the feature of protein molecules, and distinguishes this interaction from
a one-to-one transcription of the genetic code.
The rate of transcription can be controlled, or it can be blocked. This is in large part in response to the metabolites in the immediate interstitium.
This might only be
a change in the rate of a transcription or a suppression of expression through RNA.
Or through a conformational change in an enzyme
Swinging domains in HECT E3 enzymes
Since signaling systems need to be
responsive to small concentrations of chemical signals and act quickly,
cells often use a multi-step pathway that transmits the signal quickly,
while amplifying the signal to numerous molecules at each step.
Signal transduction pathways are shown (simplified):
Signal Transduction
Signal transduction occurs when an
extracellular signaling molecule activates a specific receptor located on the cell surface or inside the cell.
In turn, this receptor triggers a biochemical chain of events inside the cell, creating a response.
Depending on the cell, the response alters the cell’s metabolism, shape, gene expression, or ability to divide.
The signal can be amplified at any step. Thus, one signaling molecule can cause many responses.
In 1970, Martin Rodbell examined the effects of glucagon on a rat’s liver cell membrane receptor. He noted that guanosine triphosphate disassociated glucagon from this receptor and stimulated the G-protein, which strongly influenced the cell’s metabolism. Thus, he deduced that the G-protein is a transducer that accepts glucagon molecules and affects the cell. For this, he shared the 1994 Nobel Prize in Physiology or Medicine with Alfred G. Gilman.
Guanosine monophosphate structure
In 2007, a total of 48,377 scientific papers—including 11,211 e-review papers—were published on the subject. The term first appeared in a paper’s title in 1979. Widespread use of the term has been traced to a 1980 review article by Rodbell: Research papers focusing on signal transduction first appeared in large numbers in the late 1980s and early 1990s.
Signal transduction involves the binding of extracellular signaling molecules and ligands to cell-surface receptors that trigger events inside the cell. The combination of messenger with receptor causes a change in the conformation of the receptor, known as receptor activation.
This activation is always the initial step (the cause) leading to the cell’s ultimate responses (effect) to the messenger. Despite the myriad of these ultimate responses, they are all directly due to changes in particular cell proteins. Intracellular signaling cascades can be started through cell-substratum interactions; examples are the integrin that binds ligands in the extracellular matrix and steroids.
Integrin
Most steroid hormones have receptors within the cytoplasm and act by stimulating the binding of their receptors to the promoter region of steroid-responsive genes.
steroid hormone receptor
Various environmental stimuli exist that initiate signal transmission processes in multicellular organisms; examples include photons hitting cells in the retina of the eye, and odorants binding to odorant receptors in the nasal epithelium. Certain microbial molecules, such as viral nucleotides and protein antigens, can elicit an immune system response against invading pathogens mediated by signal transduction processes. This may occur independent of signal transduction stimulation by other molecules, as is the case for the toll-like receptor. It may occur with help from stimulatory molecules located at the cell surface of other cells, as with T-cell receptor signaling. Receptors can be roughly divided into two major classes: intracellular receptors and extracellular receptors.
Signal transduction cascades amplify the signal output
Signal transduction cascades amplify the signal output
G protein-coupled receptors (GPCRs) are a family of integral transmembrane proteins that possess seven transmembrane domains and are linked to a heterotrimeric G protein. Many receptors are in this family, including adrenergic receptors and chemokine receptors.
Arrestin binding to active GPCR kinase (GRK)-phosphorylated GPCRs blocks G protein coupling
signal transduction pathways
Arrestin binding to active GPCR kinase (GRK)-phosphorylated GPCRs blocks G protein coupling
Signal transduction by a GPCR begins with an inactive G protein coupled to the receptor; it exists as a heterotrimer consisting of Gα, Gβ, and Gγ. Once the GPCR recognizes a ligand, the conformation of the receptor changes to activate the G protein, causing Gα to bind a molecule of GTP and dissociate from the other two G-protein subunits.
The dissociation exposes sites on the subunits that can interact with other molecules. The activated G protein subunits detach from the receptor and initiate signaling from many downstream effector proteins such as phospholipases and ion channels, the latter permitting the release of second messenger molecules.
Receptor tyrosine kinases (RTKs) are transmembrane proteins with an intracellular kinase domain and an extracellular domain that binds ligands; examples include growth factor receptors such as the insulin receptor.
insulin receptor and and insulin receptor signaling pathway (IRS)
To perform signal transduction, RTKs need to form dimers in the plasma membrane; the dimer is stabilized by ligands binding to the receptor.
RTKs
The interaction between the cytoplasmic domains stimulates the autophosphorylation of tyrosines within the domains of the RTKs, causing conformational changes.
Subsequent to this, the receptors’ kinase domains are activated, initiating phosphorylation signaling cascades of downstream cytoplasmic molecules that facilitate various cellular processes such as cell differentiation and metabolism.
Signal-Transduction-Pathway
As is the case with GPCRs, proteins that bind GTP play a major role in signal transduction from the activated RTK into the cell. In this case, the G proteins are
members of the Ras, Rho, and Raf families, referred to collectively as small G proteins.
They act as molecular switches usually
tethered to membranes by isoprenyl groups linked to their carboxyl ends.
Upon activation, they assign proteins to specific membrane subdomains where they participate in signaling. Activated RTKs in turn activate
small G proteins that activate guanine nucleotide exchange factors such as SOS1.
Once activated, these exchange factors can activate more small G proteins, thus
amplifying the receptor’s initial signal.
The mutation of certain RTK genes, as with that of GPCRs, can result in the expression of receptors that exist in a constitutively activate state; such mutated genes may act as oncogenes.
Integrin
Integrin
Integrin-mediated signal transduction
An overview of integrin-mediated signal transduction, adapted from Hehlgens et al. (2007).
Integrins are produced by a wide variety of cells; they play a role in
cell attachment to other cells and the extracellular matrix and
in the transduction of signals from extracellular matrix components such as fibronectin and collagen.
Ligand binding to the extracellular domain of integrins
changes the protein’s conformation,
clustering it at the cell membrane to
initiate signal transduction.
Integrins lack kinase activity; hence, integrin-mediated signal transduction is achieved through a variety of intracellular protein kinases and adaptor molecules, the main coordinator being integrin-linked kinase.
As shown in the picture, cooperative integrin-RTK signaling determines the
timing of cellular survival,
apoptosis,
proliferation, and
differentiation.
integrin-mediated signal transduction
Integrin signaling
ion channel
A ligand-gated ion channel, upon binding with a ligand, changes conformation
to open a channel in the cell membrane
through which ions relaying signals can pass.
An example of this mechanism is found in the receiving cell of a neural synapse. The influx of ions that occurs in response to the opening of these channels
induces action potentials, such as those that travel along nerves,
by depolarizing the membrane of post-synaptic cells,
resulting in the opening of voltage-gated ion channels.
RyR and Ca+ release from SR
An example of an ion allowed into the cell during a ligand-gated ion channel opening is Ca2+;
it acts as a second messenger
initiating signal transduction cascades and
altering the physiology of the responding cell.
This results in amplification of the synapse response between synaptic cells
by remodelling the dendritic spines involved in the synapse.
In eukaryotic cells, most intracellular proteins activated by a ligand/receptor interaction possess an enzymatic activity; examples include tyrosine kinase and phosphatases. Some of them create second messengers such as cyclic AMP and IP3,
cAMP
Inositol_1,4,5-trisphosphate.svg
the latter controlling the release of intracellular calcium stores into the cytoplasm.
Many adaptor proteins and enzymes activated as part of signal transduction possess specialized protein domains that bind to specific secondary messenger molecules. For example,
calcium ions bind to the EF hand domains of calmodulin,
allowing it to bind and activate calmodulin-dependent kinase.
calcium movement and RyR2 receptor
PIP3 and other phosphoinositides do the same thing to the Pleckstrin homology domains of proteins such as the kinase protein AKT.
Signals can be generated within organelles, such as chloroplasts and mitochondria, modulating the nuclear
gene expression in a process called retrograde signaling.
Recently, integrative genomics approaches, in which correlation analysis has been applied on transcript and metabolite profiling data of Arabidopsis thaliana, revealed the identification of metabolites which are putatively acting as mediators of nuclear gene expression.
Omega-3 (ω-3) fatty acids are one of the two main families of long chain polyunsaturated fatty acids (PUFA). The main omega-3 fatty acids in the mammalian body are
α-linolenic acid (ALA), docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA).
Central nervous tissues of vertebrates are characterized by a high concentration of omega-3 fatty acids. Moreover, in the human brain,
DHA is considered as the main structural omega-3 fatty acid, which comprises about 40% of the PUFAs in total.
DHA deficiency may be the cause of many disorders such as depression, inability to concentrate, excessive mood swings, anxiety, cardiovascular disease, type 2 diabetes, dry skin and so on.
On the other hand,
zinc is the most abundant trace metal in the human brain.
There are many scientific studies linking zinc, especially
excess amounts of free zinc, to cellular death.
Neurodegenerative diseases, such as Alzheimer’s disease, are characterized by altered zinc metabolism. Both animal model studies and human cell culture studies have shown a possible link between
omega-3 fatty acids, zinc transporter levels and
free zinc availability at cellular levels.
Many other studies have also suggested a possible
omega-3 and zinc effect on neurodegeneration and cellular death.
Therefore, in this review, we will examine
the effect of omega-3 fatty acids on zinc transporters and
the importance of free zinc for human neuronal cells.
Moreover, we will evaluate the collective understanding of
mechanism(s) for the interaction of these elements in neuronal research and their
significance for the diagnosis and treatment of neurodegeneration.
Epidemiological studies have linked high intake of fish and shellfish as part of the daily diet to
reduction of the incidence and/or severity of Alzheimer’s disease (AD) and senile mental decline in
Omega-3 fatty acids are one of the two main families of a broader group of fatty acids referred to as polyunsaturated fatty acids (PUFAs). The other main family of PUFAs encompasses the omega-6 fatty acids. In general, PUFAs are essential in many biochemical events, especially in early post-natal development processes such as
cellular differentiation,
photoreceptor membrane biogenesis and
active synaptogenesis.
Despite the significance of these
two families, mammals cannot synthesize PUFA de novo, so they must be ingested from dietary sources. Though belonging to the same family, both
omega-3 and omega-6 fatty acids are metabolically and functionally distinct and have
opposing physiological effects. In the human body,
high concentrations of omega-6 fatty acids are known to increase the formation of prostaglandins and
thereby increase inflammatory processes [10].
the reverse process can be seen with increased omega-3 fatty acids in the body.
Many other factors, such as
thromboxane A2 (TXA2),
leukotriene
B4 (LTB4),
IL-1,
IL-6,
tumor necrosis factor (TNF) and
C-reactive protein,
which are implicated in various health conditions, have been shown to be increased with high omega-6 fatty acids but decreased with omega-3 fatty acids in the human body.
Dietary fatty acids have been identified as protective factors in coronary heart disease, and PUFA levels are known to play a critical role in
immune responses,
gene expression and
intercellular communications.
omega-3 fatty acids are known to be vital in
the prevention of fatal ventricular arrhythmias, and
are also known to reduce thrombus formation propensity by decreasing platelet aggregation, blood viscosity and fibrinogen levels
.Since omega-3 fatty acids are prevalent in the nervous system, it seems logical that a deficiency may result in neuronal problems, and this is indeed what has been identified and reported.
The main
In another study conducted with individuals of 65 years of age or older (n = 6158), it was found that
only high fish consumption, but
not dietary omega-3 acid intake,
had a protective effect on cognitive decline
In 2005, based on a meta-analysis of the available epidemiology and preclinical studies, clinical trials were conducted to assess the effects of omega-3 fatty acids on cognitive protection. Four of the trials completed have shown
a protective effect of omega-3 fatty acids only among those with mild cognitive impairment conditions.
A trial of subjects with mild memory complaints demonstrated
an improvement with 900 mg of DHA.
We review key findings on
the effect of the omega-3 fatty acid DHA on zinc transporters and the
importance of free zinc to human neuronal cells.
DHA is the most abundant fatty acid in neural membranes, imparting appropriate
fluidity and other properties,
and is thus considered as the most important fatty acid in neuronal studies. DHA is well conserved throughout the mammalian species despite their dietary differences. It is mainly concentrated
in membrane phospholipids at synapses and
in retinal photoreceptors and
also in the testis and sperm.
In adult rats’ brain, DHA comprises approximately
17% of the total fatty acid weight, and
in the retina it is as high as 33%.
DHA is believed to have played a major role in the evolution of the modern human –
in particular the well-developed brain.
Premature babies fed on DHA-rich formula show improvements in vocabulary and motor performance.
Analysis of human cadaver brains have shown that
people with AD have less DHA in their frontal lobe
and hippocampus compared with unaffected individuals
Furthermore, studies in mice have increased support for the
protective role of omega-3 fatty acids.
Mice administrated with a dietary intake of DHA showed
an increase in DHA levels in the hippocampus.
Errors in memory were decreased in these mice and they demonstrated
reduced peroxide and free radical levels,
suggesting a role in antioxidant defense.
Another study conducted with a Tg2576 mouse model of AD demonstrated that dietary
DHA supplementation had a protective effect against reduction in
drebrin (actin associated protein), elevated oxidation, and to some extent, apoptosis via
decreased caspase activity.
Zinc
Zinc is a trace element, which is indispensable for life, and it is the second most abundant trace element in the body. It is known to be related to
growth,
development,
differentiation,
immune response,
receptor activity,
DNA synthesis,
gene expression,
neuro-transmission,
enzymatic catalysis,
hormonal storage and release,
tissue repair,
memory,
the visual process
and many other cellular functions. Moreover, the indispensability of zinc to the body can be discussed in many other aspects, as
a component of over 300 different enzymes
an integral component of a metallothioneins
a gene regulatory protein.
Approximately 3% of all proteins contain
zinc binding motifs .
The broad biological functionality of zinc is thought to be due to its stable chemical and physical properties. Zinc is considered to have three different functions in enzymes;
catalytic,
coactive and
Indeed, it is the only metal found in all six different subclasses
of enzymes. The essential nature of zinc to the human body can be clearly displayed by studying the wide range of pathological effects of zinc deficiency. Anorexia, embryonic and post-natal growth retardation, alopecia, skin lesions, difficulties in wound healing, increased hemorrhage tendency and severe reproductive abnormalities, emotional instability, irritability and depression are just some of the detrimental effects of zinc deficiency.
Proper development and function of the central nervous system (CNS) is highly dependent on zinc levels. In the mammalian organs, zinc is mainly concentrated in the brain at around 150 μm. However, free zinc in the mammalian brain is calculated to be around 10 to 20 nm and the rest exists in either protein-, enzyme- or nucleotide bound form. The brain and zinc relationship is thought to be mediated
through glutamate receptors, and
it inhibits excitatory and inhibitory receptors.
Vesicular localization of zinc in pre-synaptic terminals is a characteristic feature of brain-localized zinc, and
its release is dependent on neural activity.
Retardation of the growth and development of CNS tissues have been linked to low zinc levels. Peripheral neuropathy, spina bifida, hydrocephalus, anencephalus, epilepsy and Pick’s disease have been linked to zinc deficiency. However, the body cannot tolerate excessive amounts of zinc.
The relationship between zinc and neurodegeneration, specifically AD, has been interpreted in several ways. One study has proposed that β-amyloid has a greater propensity to
form insoluble amyloid in the presence of
high physiological levels of zinc.
Insoluble amyloid is thought to
aggregate to form plaques,
which is a main pathological feature of AD. Further studies have shown that
chelation of zinc ions can deform and disaggregate plaques.
In AD, the most prominent injuries are found in
hippocampal pyramidal neurons, acetylcholine-containing neurons in the basal forebrain, and in
somatostatin-containing neurons in the forebrain.
All of these neurons are known to favor
rapid and direct entry of zinc in high concentration
leaving neurons frequently exposed to high dosages of zinc.
This is thought to promote neuronal cell damage through oxidative stress and mitochondrial dysfunction. Excessive levels of zinc are also capable of
inhibiting Ca2+ and Na+ voltage gated channels
and up-regulating the cellular levels of reactive oxygen species (ROS).
High levels of zinc are found in Alzheimer’s brains indicating a possible zinc related neurodegeneration. A study conducted with mouse neuronal cells has shown that even a 24-h exposure to high levels of zinc (40 μm) is sufficient to degenerate cells.
If the human diet is deficient in zinc, the body
efficiently conserves zinc at the tissue level by compensating other cellular mechanisms
to delay the dietary deficiency effects of zinc. These include reduction of cellular growth rate and zinc excretion levels, and
redistribution of available zinc to more zinc dependent cells or organs.
A novel method of measuring metallothionein (MT) levels was introduced as a biomarker for the
assessment of the zinc status of individuals and populations.
In humans, erythrocyte metallothionein (E-MT) levels may be considered as an indicator of zinc depletion and repletion, as E-MT levels are sensitive to dietary zinc intake. It should be noted here that MT plays an important role in zinc homeostasis by acting
as a target for zinc ion binding and thus
assisting in the trafficking of zinc ions through the cell,
which may be similar to that of zinc transporters
Zinc Transporters
Deficient or excess amounts of zinc in the body can be catastrophic to the integrity of cellular biochemical and biological systems. The gastrointestinal system controls the absorption, excretion and the distribution of zinc, although the hydrophilic and high-charge molecular characteristics of zinc are not favorable for passive diffusion across the cell membranes. Zinc movement is known to occur
via intermembrane proteins and zinc transporter (ZnT) proteins
These transporters are mainly categorized under two metal transporter families; Zip (ZRT, IRT like proteins) and CDF/ZnT (Cation Diffusion Facilitator), also known as SLC (Solute Linked Carrier) gene families: Zip (SLC-39) and ZnT (SLC-30). More than 20 zinc transporters have been identified and characterized over the last two decades (14 Zips and 8 ZnTs).
Members of the SLC39 family have been identified as the putative facilitators of zinc influx into the cytosol, either from the extracellular environment or from intracellular compartments (Figure 1).
The identification of this transporter family was a result of gene sequencing of known Zip1 protein transporters in plants, yeast and human cells. In contrast to the SLC39 family, the SLC30 family facilitates the opposite process, namely zinc efflux from the cytosol to the extracellular environment or into luminal compartments such as secretory granules, endosomes and synaptic vesicles; thus decreasing intracellular zinc availability (Figure 1). ZnT3 is the most important in the brain where
it is responsible for the transport of zinc into the synaptic vesicles of
glutamatergic neurons in the hippocampus and neocortex,
Figure 1: Subcellular localization and direction of transport of the zinc transporter families, ZnT and ZIP. Arrows show the direction of zinc mobilization for the ZnT (green) and ZIP (red) proteins. A net gain in cytosolic zinc is achieved by the transportation of zinc from the extracellular region and organelles such as the endoplasmic reticulum (ER) and Golgi apparatus by the ZIP transporters. Cytosolic zinc is mobilized into early secretory compartments such as the ER and Golgi apparatus by the ZnT transporters. Figures were produced using Servier Medical Art, http://www.servier.com/. http://www.hindawi.com/journals/jnme/2012/173712.fig.001.jpg
Figure 2: Early zinc signaling (EZS) and late zinc signaling (LZS). EZS involves transcription-independent mechanisms where an extracellular stimulus directly induces an increase in zinc levels within several minutes by releasing zinc from intracellular stores (e.g., endoplasmic reticulum). LSZ is induced several hours after an external stimulus and is dependent on transcriptional changes in zinc transporter expression. Components of this figure were produced using Servier Medical Art, http://www.servier.com/ and adapted from Fukada et al. [30].
omega-3 fatty acids in the mammalian body are
α-linolenic acid (ALA),
docosahexenoic acid (DHA) and
eicosapentaenoic acid (EPA).
In general, seafood is rich in omega-3 fatty acids, more specifically DHA and EPA (Table 1). Thus far, there are nine separate epidemiological studies that suggest a possible link between
increased fish consumption and reduced risk of AD
and eight out of ten studies have reported a link between higher blood omega-3 levels
DHA and Zinc Homeostasis
Many studies have identified possible associations between DHA levels, zinc homeostasis, neuroprotection and neurodegeneration. Dietary DHA deficiency resulted in
increased zinc levels in the hippocampus and
elevated expression of the putative zinc transporter, ZnT3, in the rat brain.
Altered zinc metabolism in neuronal cells has been linked to neurodegenerative conditions such as AD. A study conducted with transgenic mice has shown a significant link between ZnT3 transporter levels and cerebral amyloid plaque pathology. When the ZnT3 transporter was silenced in transgenic mice expressing cerebral amyloid plaque pathology,
a significant reduction in plaque load
and the presence of insoluble amyloid were observed.
In addition to the decrease in plaque load, ZnT3 silenced mice also exhibited a significant
reduction in free zinc availability in the hippocampus
and cerebral cortex.
Collectively, the findings from this study are very interesting and indicate a clear connection between
zinc availability and amyloid plaque formation,
thus indicating a possible link to AD.
DHA supplementation has also been reported to limit the following:
amyloid presence,
synaptic marker loss,
hyper-phosphorylation of Tau,
oxidative damage and
cognitive deficits in transgenic mouse model of AD.
In addition, studies by Stoltenberg, Flinn and colleagues report on the modulation of zinc and the effect in transgenic mouse models of AD. Given that all of these are classic pathological features of AD, and considering the limiting nature of DHA in these processes, it can be argued that DHA is a key candidate in preventing or even curing this debilitating disease.
In order to better understand the possible links and pathways of zinc and DHA with neurodegeneration, we designed a study that incorporates all three of these aspects, to study their effects at the cellular level. In this study, we were able to demonstrate a possible link between omega-3 fatty acid (DHA) concentration, zinc availability and zinc transporter expression levels in cultured human neuronal cells.
When treated with DHA over 48 h, ZnT3 levels were markedly reduced in the human neuroblastoma M17 cell line. Moreover, in the same study, we were able to propose a possible
neuroprotective mechanism of DHA,
which we believe is exerted through
a reduction in cellular zinc levels (through altering zinc transporter expression levels)
that in turn inhibits apoptosis.
DHA supplemented M17 cells also showed a marked depletion of zinc uptake (up to 30%), and
free zinc levels in the cytosol were significantly low compared to the control
This reduction in free zinc availability was specific to DHA; cells treated with EPA had no significant change in free zinc levels (unpublished data). Moreover, DHA-repleted cells had
low levels of active caspase-3 and
high Bcl-2 levels compared to the control treatment.
These findings are consistent with previous published data and further strengthen the possible
correlation between zinc, DHA and neurodegeneration.
On the other hand, recent studies using ZnT3 knockout (ZnT3KO) mice have shown the importance of
ZnT3 in memory and AD pathology.
For example, Sindreu and colleagues have used ZnT3KO mice to establish the important role of
ZnT3 in zinc homeostasis that modulates presynaptic MAPK signaling
required for hippocampus-dependent memory
Results from these studies indicate a possible zinc-transporter-expression-level-dependent mechanism for DHA neuroprotection.
We have laid down a basic structure and foundation for the remaining presentations. It was essential to begin with the genome, which changed the course of teaching of biology and medicine in the 20th century, and introduced a central dogma of translation by transcription. Nevertheless, there were significant inconsistencies and unanswered questions entering the twenty first century, accompanied by vast improvements in technical advances to clarify these issues. We have covered carbohydrate, protein, and lipid metabolism, which function in concert with the development of cellular structure, organ system development, and physiology. To be sure, the progress in the study of the microscopic and particulate can’t be divorced from the observation of the whole. We were left in the not so distant past with the impression of the Sufi story of the elephant and the three blind men, who one at a time held the tail, the trunk, and the ear, each proclaiming that it was the elephant.
I introduce here a story from the Brazilian biochemist, Jose
Eduardo des Salles Rosalino, on a formativr experience he had with the Nobelist, Luis Leloir.
Just at the beginning, when phosphorylation of proteins is presented, I assume you must mention that some proteins are activated by phosphorylation. This is fundamental in order to present self –organization reflex upon fast regulatory mechanisms. Even from an historical point of view. The first observation arrived from a sample due to be studied on the following day of glycogen synthetase. It was unintended left overnight out of the refrigerator. The result was it has changed from active form of the previous day to a non-active form. The story could have being finished here, if the researcher did not decide to spent this day increasing substrate levels (it could be a simple case of denaturation of proteins that changes its conformation despite the same order of amino acids). He kept on trying and found restoration of maximal activity. This assay was repeated with glycogen phosphorylase and the result was the opposite – it increases its activity. This led to the discovery
of cAMP activated protein kinase and
the assembly of a very complex system in the glycogen granule
that is not a simple carbohydrate polymer.
Instead, it has several proteins assembled and
preserves the capacity to receive from a single event (rise in cAMP)
two opposing signals with maximal efficiency,
stops glycogen synthesis,
as long as levels of glucose 6 phosphate are low
and increases glycogen phosphorylation as long as AMP levels are high).
I did everything I was able to do by the end of 1970 in order to repeat the assays with PK I, PKII and PKIII of M. Rouxii and using the Sutherland route to cAMP failed in this case. I then asked Leloir to suggest to my chief (SP) the idea of AA, AB, BB subunits as was observed in lactic dehydrogenase (tetramer) indicating this as his idea. The reason was my “chief”(SP) more than once, had said to me: “Leave these great ideas for the Houssay, Leloir etc…We must do our career with small things.” However, as she also had a faulty ability for recollection she also used to arrive some time later, with the very same idea but in that case, as her idea.
Leloir, said to me: I will not offer your interpretation to her as mine. I think it is not phosphorylation, however I think it is glycosylation that explains the changes in the isoenzymes with the same molecular weight preserved. This dialogue explains why during the reading and discussing “What is life” with him he asked me if as a biochemist in exile, talking to another biochemist, I expressed myself fully. I had considered that Schrödinger would not have confronted Darlington & Haldane because he was in U.K. in exile. This might explain why Leloir could have answered a bad telephone call from P. Boyer, Editor of The Enzymes, in a way that suggested that the pattern could be of covalent changes over a protein. Our FEBS and Eur J. Biochemistry papers on pyruvate kinase of M. Rouxii is wrongly quoted in this way on his review about pyruvate kinase of that year (1971).
Another aspect I think you must call attention to the following. Show in detail with different colors what carbons belongs to CoA, a huge molecule in comparison with the single two carbons of acetate that will produce the enormous jump in energy yield
in comparison with anaerobic glycolysis.
The idea is
how much must have been spent in DNA sequences to build that molecule in order to use only two atoms of carbon.
Very limited aspects of biology could be explained in this way. In case we follow an alternative way of thinking, it becomes clearer that proteins were made more stable by interaction with other molecules (great and small). Afterwards, it’s rather easy to understand how the stability of protein-RNA complexes where transmitted to RNA (vibrational +solvational reactivity stability pair of conformational energy).
Millions of years later, or as soon as, the information of interaction leading to activity and regulation could be found in RNA, proteins like reverse transcriptase move this information to a more stable form (DNA). In this way it is easier to understand the use of CoA to make two carbon molecules more reactive.
The discussions that follow are concerned with protein interactions and signaling.
Preface to Metabolomics as a Discipline in Medicine
Author: Larry H. Bernstein, MD, FCAP
The family of ‘omics fields has rapidly outpaced its siblings over the decade since
the completion of the Human Genome Project. It has derived much benefit from
the development of Proteomics, which has recently completed a first draft of the
human proteome. Since genomics, transcriptomics, and proteomics, have matured
considerably, it has become apparent that the search for a driver or drivers of cellular signaling and metabolic pathways could not depend on a full clarity of the genome. There have been unresolved issues, that are not solely comprehended from assumptions about mutations.
The most common diseases affecting mankind are derangements in metabolic
pathways, develop at specific ages periods, and often in adulthood or in the
geriatric period, and are at the intersection of signaling pathways. Moreover,
the organs involved and systemic features are heavily influenced by physical
activity, and by the air we breathe and the water we drink.
The emergence of the new science is also driven by a large body of work
on protein structure, mechanisms of enzyme action, the modulation of gene
expression, the pH dependent effects on protein binding and conformation.
Beyond what has just been said, a significant portion of DNA has been
designated as “dark matter”. It turns out to have enormous importance in
gene regulation, even though it is not transcriptional, effected in a
modulatory way by “noncoding RNAs. Metabolomics is the comprehensive
analysis of small molecule metabolites. These might be substrates of
sequenced enzyme reactions, or they might be “inhibiting” RNAs just
mentioned. In either case, they occur in the substructures of the cell
called organelles, the cytoplasm, and in the cytoskeleton.
The reactions are orchestrated, and they can be modified with respect to
the flow of metabolites based on pH, temperature, membrane structural
modifications, and modulators. Since most metabolites are generated by
enzymatic proteins that result from gene expression, and metabolites give
organisms their biochemical characteristics, the metabolome links
genotype with phenotype.
Metabolomics is still developing, and the continued development has
relied on two major events. The first is chromatographic separation and
mass spectroscopy (MS), MS/MS, as well as advances in fluorescence
ultrasensitive optical photonic methods, and the second, as crucial,
is the developments in computational biology. The continuation of
this trend brings expectations of an impact on pharmaceutical and
on neutraceutical developments, which will have an impact on medical
practice. What has lagged behind, and may continue to contribute to the
lag is the failure to develop a suitable electronic medical record to
assist the physician in decisions confronted with so much as yet,
hidden data, the ready availability of which could guide more effective
diagnosis and management of the patient. Put all of this together, and
we can meet series challenges as the research community
interprets and integrates the complex data they are acquiring.
This is the final article in a robust series on metabolism, metabolomics, and the “-OMICS-“ biological synthesis that is creating a more holistic and interoperable view of natural sciences, including the biological disciplines, climate science, physics, chemistry, toxicology, pharmacology, and pathophysiology with as yet unforeseen consequences.
There have been impressive advances already in the research into developmental biology, plant sciences, microbiology, mycology, and human diseases, most notably, cancer, metabolic , and infectious, as well as neurodegenerative diseases.
Acknowledgements:
I write this article in honor of my first mentor, Harry Maisel, Professor and Emeritus Chairman of Anatomy, Wayne State University, Detroit, MI and to my stimulating mentors, students, fellows, and associates over many years:
Masahiro Chiga, MD, PhD, Averill A Liebow, MD, Nathan O Kaplan, PhD, Johannes Everse, PhD, Norio Shioura, PhD, Abraham Braude, MD, Percy J Russell, PhD, Debby Peters, Walter D Foster, PhD, Herschel Sidransky, MD, Sherman Bloom, MD, Matthew Grisham, PhD, Christos Tsokos, PhD, IJ Good, PhD, Distinguished Professor, Raool Banagale, MD, Gustavo Reynoso, MD,Gustave Davis, MD, Marguerite M Pinto, MD, Walter Pleban, MD, Marion Feietelson-Winkler, RD, PhD, John Adan,MD, Joseph Babb, MD, Stuart Zarich, MD, Inder Mayall, MD, A Qamar, MD, Yves Ingenbleek, MD, PhD, Emeritus Professor, Bette Seamonds, PhD, Larry Kaplan, PhD, Pauline Y Lau, PhD, Gil David, PhD, Ronald Coifman, PhD, Emeritus Professor, Linda Brugler, RD, MBA, James Rucinski, MD, Gitta Pancer, Ester Engelman, Farhana Hoque, Mohammed Alam, Michael Zions, William Fleischman, MD, Salman Haq, MD, Jerard Kneifati-Hayek, Madeleine Schleffer, John F Heitner, MD, Arun Devakonda,MD, Liziamma George,MD, Suhail Raoof, MD, Charles Oribabor,MD, Anthony Tortolani, MD, Prof and Chairman, JRDS Rosalino, PhD, Aviva Lev Ari, PhD, RN, Rosser Rudolph, MD, PhD, Eugene Rypka, PhD, Jay Magidson, PhD, Izaak Mayzlin, PhD, Maurice Bernstein, PhD, Richard Bing, Eli Kaplan, PhD, Maurice Bernstein, PhD.
This article has EIGHT parts, as follows:
Part 1
Metabolomics Continues Auspicious Climb
Part 2
Biologists Find ‘Missing Link’ in the Production of Protein Factories in Cells
Part 3
Neuroscience
Part 4
Cancer Research
Part 5
Metabolic Syndrome
Part 6
Biomarkers
Part 7
Epigenetics and Drug Metabolism
Part 8
Pictorial
genome cartoon
iron metabolism
personalized reference range within population range
Part 1. MetabolomicsSurge
metagraph _OMICS
Metabolomics Continues Auspicious Climb
Jeffery Herman, Ph.D.
GEN May 1, 2012 (Vol. 32, No. 9)
Aberrant biochemical and metabolite signaling plays an important role in
the development and progression of diseased tissue.
This concept has been studied by the science community for decades. However, with relatively
recent advances in analytical technology and bioinformatics as well as
the development of the Human Metabolome Database (HMDB),
metabolomics has become an invaluable field of research.
At the “International Conference and Exhibition on Metabolomics & Systems Biology” held recently in San Francisco, researchers and industry leaders discussed how
the underlying cellular biochemical/metabolite fingerprint in response to
a specific disease state,
toxin exposure, or
pharmaceutical compound
is useful in clinical diagnosis and biomarker discovery and
in understanding disease development and progression.
Developed by BASF, MetaMap® Tox is
a database that helps identify in vivo systemic effects of a tested compound, including
targeted organs,
mechanism of action, and
adverse events.
Based on 28-day systemic rat toxicity studies, MetaMap Tox is composed of
differential plasma metabolite profiles of rats
after exposure to a large variety of chemical toxins and pharmaceutical compounds.
“Using the reference data,
we have developed more than 110 patterns of metabolite changes, which are
specific and predictive for certain toxicological modes of action,”
said Hennicke Kamp, Ph.D., group leader, department of experimental toxicology and ecology at BASF.
With MetaMap Tox, a potential drug candidate
can be compared to a similar reference compound
using statistical correlation algorithms,
which allow for the creation of a toxicity and mechanism of action profile.
“MetaMap Tox, in the context of early pre-clinical safety enablement in pharmaceutical development,” continued Dr. Kamp,
has been independently validated “
by an industry consortium (Drug Safety Executive Council) of 12 leading biopharmaceutical companies.”
Dr. Kamp added that this technology may prove invaluable
allowing for quick and accurate decisions and
for high-throughput drug candidate screening, in evaluation
on the safety and efficacy of compounds
during early and preclinical toxicological studies,
by comparing a lead compound to a variety of molecular derivatives, and
the rapid identification of the most optimal molecular structure
with the best efficacy and safety profiles might be streamlined.
Dynamic Construct of the –Omics
Targeted Tandem Mass Spectrometry
Biocrates Life Sciences focuses on targeted metabolomics, an important approach for
the accurate quantification of known metabolites within a biological sample.
Originally used for the clinical screening of inherent metabolic disorders from dried blood-spots of newborn children, Biocrates has developed
a tandem mass spectrometry (MS/MS) platform, which allows for
the identification,
quantification, and
mapping of more than 800 metabolites to specific cellular pathways.
It is based on flow injection analysis and high-performance liquid chromatography MS/MS.
common drug targets
The MetaDisIDQ® Kit is a
“multiparamatic” diagnostic assay designed for the “comprehensive assessment of a person’s metabolic state” and
the early determination of pathophysiological events with regards to a specific disease.
MetaDisIDQ is designed to quantify
a diverse range of 181 metabolites involved in major metabolic pathways
from a small amount of human serum (10 µL) using isotopically labeled internal standards,
This kit has been demonstrated to detect changes in metabolites that are commonly associated with the development of
metabolic syndrome, type 2 diabetes, and diabetic nephropathy,
Dr. Dallman reports that data generated with the MetaDisIDQ kit correlates strongly with
routine chemical analyses of common metabolites including glucose and creatinine
Biocrates has also developed the MS/MS-based AbsoluteIDQ® kits, which are
an “easy-to-use” biomarker analysis tool for laboratory research.
The kit functions on MS machines from a variety of vendors, and allows for the quantification of 150-180 metabolites.
The SteroIDQ® kit is a high-throughput standardized MS/MS diagnostic assay,
validated in human serum, for the rapid and accurate clinical determination of 16 known steroids.
Initially focusing on the analysis of steroid ranges for use in hormone replacement therapy, the SteroIDQ Kit is expected to have a wide clinical application.
Hormone-Resistant Breast Cancer
Scientists at Georgetown University have shown that
breast cancer cells can functionally coordinate cell-survival and cell-proliferation mechanisms,
while maintaining a certain degree of cellular metabolism.
To grow, cells need energy, and energy is a product of cellular metabolism. For nearly a century, it was thought that
the uncoupling of glycolysis from the mitochondria,
leading to the inefficient but rapid metabolism of glucose and
the formation of lactic acid (the Warburg effect), was
the major and only metabolism driving force for unchecked proliferation and tumorigenesis of cancer cells.
Other aspects of metabolism were often overlooked.
“.. we understand now that
cellular metabolism is a lot more than just metabolizing glucose,”
said Robert Clarke, Ph.D., professor of oncology and physiology and biophysics at Georgetown University. Dr. Clarke, in collaboration with the Waters Center for Innovation at Georgetown University (led by Albert J. Fornace, Jr., M.D.), obtained
the metabolomic profile of hormone-sensitive and -resistant breast cancer cells through the use of UPLC-MS.
They demonstrated that breast cancer cells, through a rather complex and not yet completely understood process,
can functionally coordinate cell-survival and cell-proliferation mechanisms,
while maintaining a certain degree of cellular metabolism.
This is at least partly accomplished through the upregulation of important pro-survival mechanisms; including
the unfolded protein response;
a regulator of endoplasmic reticulum stress and
initiator of autophagy.
Normally, during a stressful situation, a cell may
enter a state of quiescence and undergo autophagy,
a process by which a cell can recycle organelles
in order to maintain enough energy to survive during a stressful situation or,
if the stress is too great,
undergo apoptosis.
By integrating cell-survival mechanisms and cellular metabolism
advanced ER+ hormone-resistant breast cancer cells
can maintain a low level of autophagy
to adapt and resist hormone/chemotherapy treatment.
This adaptation allows cells
to reallocate important metabolites recovered from organelle degradation and
provide enough energy to also promote proliferation.
With further research, we can gain a better understanding of the underlying causes of hormone-resistant breast cancer, with
the overall goal of developing effective diagnostic, prognostic, and therapeutic tools.
NMR
Over the last two decades, NMR has established itself as a major tool for metabolomics analysis. It is especially adept at testing biological fluids. [Bruker BioSpin]
Historically, nuclear magnetic resonance spectroscopy (NMR) has been used for structural elucidation of pure molecular compounds. However, in the last two decades, NMR has established itself as a major tool for metabolomics analysis. Since
the integral of an NMR signal is directly proportional to
the molar concentration throughout the dynamic range of a sample,
“the simultaneous quantification of compounds is possible
without the need for specific reference standards or calibration curves,” according to Lea Heintz of Bruker BioSpin.
NMR is adept at testing biological fluids because of
high reproducibility,
standardized protocols,
low sample manipulation, and
the production of a large subset of data,
Bruker BioSpin is presently involved in a project for the screening of inborn errors of metabolism in newborn children from Turkey, based on their urine NMR profiles. More than 20 clinics are participating to the project that is coordinated by INFAI, a specialist in the transfer of advanced analytical technology into medical diagnostics. The construction of statistical models are being developed
for the detection of deviations from normality, as well as
automatic quantification methods for indicative metabolites
Bruker BioSpin recently installed high-resolution magic angle spinning NMR (HRMAS-NMR) systems that can rapidly analyze tissue biopsies. The main objective for HRMAS-NMR is to establish a rapid and effective clinical method to assess tumor grade and other important aspects of cancer during surgery.
Combined NMR and Mass Spec
There is increasing interest in combining NMR and MS, two of the main analytical assays in metabolomic research, as a means
to improve data sensitivity and to
fully elucidate the complex metabolome within a given biological sample.
to realize a potential for cancer biomarker discovery in the realms of diagnosis, prognosis, and treatment.
.
Using combined NMR and MS to measure the levels of nearly 250 separate metabolites in the patient’s blood, Dr. Weljie and other researchers at the University of Calgary were able to rapidly determine the malignancy of a pancreatic lesion (in 10–15% of the cases, it is difficult to discern between benign and malignant), while avoiding unnecessary surgery in patients with benign lesions.
When performing NMR and MS on a single biological fluid, ultimately “we are,” noted Dr. Weljie,
“splitting up information content, processing, and introducing a lot of background noise and error and
then trying to reintegrate the data…
It’s like taking a complex item, with multiple pieces, out of an IKEA box and trying to repackage it perfectly into another box.”
By improving the workflow between the initial splitting of the sample, they improved endpoint data integration, proving that
a streamlined approach to combined NMR/MS can be achieved,
leading to a very strong, robust and precise metabolomics toolset.
Metabolomics Research Picks Up Speed
Field Advances in Quest to Improve Disease Diagnosis and Predict Drug Response
John Morrow Jr., Ph.D.
GEN May 1, 2011 (Vol. 31, No. 9)
As an important discipline within systems biology, metabolomics is being explored by a number of laboratories for
its potential in pharmaceutical development.
Studying metabolites can offer insights into the relationships between genotype and phenotype, as well as between genotype and environment. In addition, there is plenty to work with—there are estimated to be some 2,900 detectable metabolites in the human body, of which
309 have been identified in cerebrospinal fluid,
1,122 in serum,
458 in urine, and
roughly 300 in other compartments.
Guowang Xu, Ph.D., a researcher at the Dalian Institute of Chemical Physics. is investigating the causes of death in China,
and how they have been changing over the years as the country has become a more industrialized nation.
the increase in the incidence of metabolic disorders such as diabetes has grown to affect 9.7% of the Chinese population.
Dr. Xu, collaborating with Rainer Lehman, Ph.D., of the University of Tübingen, Germany, compared urinary metabolites in samples from healthy individuals with samples taken from prediabetic, insulin-resistant subjects. Using mass spectrometry coupled with electrospray ionization in the positive mode, they observed striking dissimilarities in levels of various metabolites in the two groups.
“When we performed a comprehensive two-dimensional gas chromatography, time-of-flight mass spectrometry analysis of our samples, we observed several metabolites, including
2-hydroxybutyric acid in plasma,
as potential diabetes biomarkers,” Dr. Xu explains.
In other, unrelated studies, Dr. Xu and the German researchers used a metabolomics approach to investigate the changes in plasma metabolite profiles immediately after exercise and following a 3-hour and 24-hour period of recovery. They found that
medium-chain acylcarnitines were the most distinctive exercise biomarkers, and
they are released as intermediates of partial beta oxidation in human myotubes and mouse muscle tissue.
Dr. Xu says. “The traditional approach of assessment based on a singular biomarker is being superseded by the introduction of multiple marker profiles.”
Typical of the studies under way by Dr. Kaddurah-Daouk and her colleaguesat Duke University
is a recently published investigation highlighting the role of an SNP variant in
the glycine dehydrogenase gene on individual response to antidepressants.
patients who do not respond to the selective serotonin uptake inhibitors citalopram and escitalopram
carried a particular single nucleotide polymorphism in the GD gene.
“These results allow us to pinpoint a possible
role for glycine in selective serotonin reuptake inhibitor response and
illustrate the use of pharmacometabolomics to inform pharmacogenomics.
These discoveries give us the tools for prognostics and diagnostics so that
we can predict what conditions will respond to treatment.
“This approach to defining health or disease in terms of metabolic states opens a whole new paradigm.
By screening hundreds of thousands of molecules, we can understand
the relationship between human genetic variability and the metabolome.”
Dr. Kaddurah-Daouk talks about statins as a current
model of metabolomics investigations.
It is now known that the statins have widespread effects, altering a range of metabolites. To sort out these changes and develop recommendations for which individuals should be receiving statins will require substantial investments of energy and resources into defining the complex web of biochemical changes that these drugs initiate.
Furthermore, Dr. Kaddurah-Daouk asserts that,
“genetics only encodes part of the phenotypic response.
One needs to take into account the
net environment contribution in order to determine
how both factors guide the changes in our metabolic state that determine the phenotype.”
Interactive Metabolomics
Researchers at the University of Nottingham use diffusion-edited nuclear magnetic resonance spectroscopy to assess the effects of a biological matrix on metabolites. Diffusion-edited NMR experiments provide a way to
separate the different compounds in a mixture
based on the differing translational diffusion coefficients (which reflect the size and shape of the molecule).
The measurements are carried out by observing
the attenuation of the NMR signals during a pulsed field gradient experiment.
Clare Daykin, Ph.D., is a lecturer at the University of Nottingham, U.K. Her field of investigation encompasses “interactive metabolomics,”which she defines as
“the study of the interactions between low molecular weight biochemicals and macromolecules in biological samples ..
without preselection of the components of interest.
“Blood plasma is a heterogeneous mixture of molecules that
undergo a variety of interactions including metal complexation,
chemical exchange processes,
micellar compartmentation,
enzyme-mediated biotransformations, and
small molecule–macromolecular binding.”
Many low molecular weight compounds can exist
freely in solution,
bound to proteins, or
within organized aggregates such as lipoprotein complexes.
Therefore, quantitative comparison of plasma composition from
diseased individuals compared to matched controls provides an incomplete insight to plasma metabolism.
“It is not simply the concentrations of metabolites that must be investigated,
but their interactions with the proteins and lipoproteins within this complex web.
Rather than targeting specific metabolites of interest, Dr. Daykin’s metabolite–protein binding studies aim to study
the interactions of all detectable metabolites within the macromolecular sample.
Such activities can be studied through the use of diffusion-edited nuclear magnetic resonance (NMR) spectroscopy, in which one can assess
the effects of the biological matrix on the metabolites.
“This can lead to a more relevant and exact interpretation
for systems where metabolite–macromolecule interactions occur.”
Diffusion-edited NMR experiments provide a way to separate the different compounds in a mixture based on
the differing translational diffusion coefficients (which reflect the size and shape of the molecule).
The measurements are carried out by observing
the attenuation of the NMR signals during a pulsed field gradient experiment.
Pushing the Limits
It is widely recognized that many drug candidates fail during development due to ancillary toxicity. Uwe Sauer, Ph.D., professor, and Nicola Zamboni, Ph.D., researcher, both at the Eidgenössische Technische Hochschule, Zürich (ETH Zürich), are applying
high-throughput intracellular metabolomics to understand
the basis of these unfortunate events and
head them off early in the course of drug discovery.
“Since metabolism is at the core of drug toxicity, we developed a platform for
measurement of 50–100 targeted metabolites by
a high-throughput system consisting of flow injection
coupled to tandem mass spectrometry.”
Using this approach, Dr. Sauer’s team focused on
the central metabolism of the yeast Saccharomyces cerevisiae, reasoning that
this core network would be most susceptible to potential drug toxicity.
Screening approximately 41 drugs that were administered at seven concentrations over three orders of magnitude, they observed changes in metabolome patterns at much lower drug concentrations without attendant physiological toxicity.
The group carried out statistical modeling of about
60 metabolite profiles for each drug they evaluated.
This data allowed the construction of a “profile effect map” in which
the influence of each drug on metabolite levels can be followed, including off-target effects, which
provide an indirect measure of the possible side effects of the various drugs.
Dr. Sauer says.“We have found that this approach is
at least 100 times as fast as other omics screening platforms,”
“Some drugs, including many anticancer agents,
disrupt metabolism long before affecting growth.”
killing cancer cells
Furthermore, they used the principle of 13C-based flux analysis, in which
metabolites labeled with 13C are used to follow the utilization of metabolic pathways in the cell.
These 13C-determined intracellular responses of metabolic fluxes to drug treatment demonstrate
the functional performance of the network to be rather robust,
conformational changes leading to substrate efflux.
leading Dr. Sauer to the conclusion that
the phenotypic vigor he observes to drug challenges
is achieved by a flexible make up of the metabolome.
Dr. Sauer is confident that it will be possible to expand the scope of these investigations to hundreds of thousands of samples per study. This will allow answers to the questions of
how cells establish a stable functioning network in the face of inevitable concentration fluctuations.
Is Now the Hour?
There is great enthusiasm and agitation within the biotech community for
metabolomics approaches as a means of reversing the dismal record of drug discovery
that has accumulated in the last decade.
While the concept clearly makes sense and is being widely applied today, there are many reasons why drugs fail in development, and metabolomics will not be a panacea for resolving all of these questions. It is too early at this point to recognize a trend or a track record, and it will take some time to see how this approach can aid in drug discovery and shorten the timeline for the introduction of new pharmaceutical agents.
Degree of binding correlated with function
Diagram_of_a_two-photon_excitation_microscope_
Part 2. Biologists Find ‘Missing Link’ in the Production of Protein Factories in Cells
Biologists at UC San Diego have found
the “missing link” in the chemical system that
enables animal cells to produce ribosomes
—the thousands of protein “factories” contained within each cell that
manufacture all of the proteins needed to build tissue and sustain life.
‘Missing Link’
Their discovery, detailed in the June 23 issue of the journal Genes & Development, will not only force
a revision of basic textbooks on molecular biology, but also
provide scientists with a better understanding of
how to limit uncontrolled cell growth, such as cancer,
that might be regulated by controlling the output of ribosomes.
Ribosomes are responsible for the production of the wide variety of proteins that include
enzymes;
structural molecules, such as hair,
skin and bones;
hormones like insulin; and
components of our immune system such as antibodies.
Regarded as life’s most important molecular machine, ribosomes have been intensively studied by scientists (the 2009 Nobel Prize in Chemistry, for example, was awarded for studies of its structure and function). But until now researchers had not uncovered all of the details of how the proteins that are used to construct ribosomes are themselves produced.
In multicellular animals such as humans,
ribosomes are made up of about 80 different proteins
(humans have 79 while some other animals have a slightly different number) as well as
four different kinds of RNA molecules.
In 1969, scientists discovered that
the synthesis of the ribosomal RNAs is carried out by specialized systems using two key enzymes:
RNA polymerase I and RNA polymerase III.
But until now, scientists were unsure if a complementary system was also responsible for
the production of the 80 proteins that make up the ribosome.
That’s essentially what the UC San Diego researchers headed by Jim Kadonaga, a professor of biology, set out to examine. What they found was the missing link—the specialized
system that allows ribosomal proteins themselves to be synthesized by the cell.
Kadonaga says that he and coworkers found that ribosomal proteins are synthesized via
a novel regulatory system with the enzyme RNA polymerase II and
a factor termed TRF2,”
“For the production of most proteins,
RNA polymerase II functions with
a factor termed TBP,
but for the synthesis of ribosomal proteins, it uses TRF2.”
this specialized TRF2-based system for ribosome biogenesis
provides a new avenue for the study of ribosomes and
its control of cell growth, and
“it should lead to a better understanding and potential treatment of diseases such as cancer.”
Coordination of the transcriptome and metabolome
the potential advantages conferred by distal-site protein synthesis
Other authors of the paper were UC San Diego biologists Yuan-Liang Wang, Sascha Duttke and George Kassavetis, and Kai Chen, Jeff Johnston, and Julia Zeitlinger of the Stowers Institute for Medical Research in Kansas City, Missouri. Their research was supported by two grants from the National Institutes of Health (1DP2OD004561-01 and R01 GM041249).
Turning Off a Powerful Cancer Protein
Scientists have discovered how to shut down a master regulatory transcription factor that is
key to the survival of a majority of aggressive lymphomas,
which arise from the B cells of the immune system.
The protein, Bcl6, has long been considered too complex to target with a drug since it is also crucial
to the healthy functioning of many immune cells in the body, not just B cells gone bad.
The researchers at Weill Cornell Medical College report that it is possible
to shut down Bcl6 in diffuse large B-cell lymphoma (DLBCL)
while not affecting its vital function in T cells and macrophages
that are needed to support a healthy immune system.
If Bcl6 is completely inhibited, patients might suffer from systemic inflammation and atherosclerosis. The team conducted this new study to help clarify possible risks, as well as to understand
how Bcl6 controls the various aspects of the immune system.
The findings in this study were inspired from
preclinical testing of two Bcl6-targeting agents that Dr. Melnick and his Weill Cornell colleagues have developed
to treat DLBCLs.
These experimental drugs are
RI-BPI, a peptide mimic, and
the small molecule agent 79-6.
“This means the drugs we have developed against Bcl6 are more likely to be
significantly less toxic and safer for patients with this cancer than we realized,”
says Ari Melnick, M.D., professor of hematology/oncology and a hematologist-oncologist at NewYork-Presbyterian Hospital/Weill Cornell Medical Center.
Dr. Melnick says the discovery that
a master regulatory transcription factor can be targeted
offers implications beyond just treating DLBCL.
Recent studies from Dr. Melnick and others have revealed that
Bcl6 plays a key role in the most aggressive forms of acute leukemia, as well as certain solid tumors.
Bcl6 can control the type of immune cell that develops in the bone marrow—playing many roles
in the development of B cells, T cells, macrophages, and other cells—including a primary and essential role in
enabling B-cells to generate specific antibodies against pathogens.
According to Dr. Melnick, “When cells lose control of Bcl6,
lymphomas develop in the immune system.
Lymphomas are ‘addicted’ to Bcl6, and therefore
Bcl6 inhibitors powerfully and quickly destroy lymphoma cells,” .
The big surprise in the current study is that rather than functioning as a single molecular machine,
Bcl6 functions like a Swiss Army knife,
using different tools to control different cell types.
This multifunction paradigm could represent a general model for the functioning of other master regulatory transcription factors.
“In this analogy, the Swiss Army knife, or transcription factor, keeps most of its tools folded,
opening only the one it needs in any given cell type,”
He makes the following analogy:
“For B cells, it might open and use the knife tool;
for T cells, the cork screw;
for macrophages, the scissors.”
“this means that you only need to prevent the master regulator from using certain tools to treat cancer. You don’t need to eliminate the whole knife,” . “In fact, we show that taking out the whole knife is harmful since
the transcription factor has many other vital functions that other cells in the body need.”
Prior to these study results, it was not known that a master regulator could separate its functions so precisely. Researchers hope this will be a major benefit to the treatment of DLBCL and perhaps other disorders that are influenced by Bcl6 and other master regulatory transcription factors.
The study is published in the journal Nature Immunology, in a paper titled “Lineage-specific functions of Bcl-6 in immunity and inflammation are mediated by distinct biochemical mechanisms”.
Neurons (blue) which have absorbed exosomes (green) have increased levels of the enzyme catalase (red), which helps protect them against peroxides.
Neurons (blue) which have absorbed exosomes (green) have increased levels of the enzyme catalase (red), which helps protect them against peroxides.
Tiny vesicles containing protective substances
which they transmit to nerve cells apparently
play an important role in the functioning of neurons.
As cell biologists at Johannes Gutenberg University Mainz (JGU) have discovered,
nerve cells can enlist the aid of mini-vesicles of neighboring glial cells
to defend themselves against stress and other potentially detrimental factors.
These vesicles, called exosomes, appear to stimulate the neurons on various levels:
they influence electrical stimulus conduction,
biochemical signal transfer, and
gene regulation.
Exosomes are thus multifunctional signal emitters
that can have a significant effect in the brain.
Exosome
The researchers in Mainz already observed in a previous study that
oligodendrocytes release exosomes on exposure to neuronal stimuli.
these are absorbed by the neurons and improve neuronal stress tolerance.
Oligodendrocytes, a type of glial cell, form an
insulating myelin sheath around the axons of neurons.
The exosomes transport protective proteins such as
heat shock proteins,
glycolytic enzymes, and
enzymes that reduce oxidative stress from one cell type to another,
but also transmit genetic information in the form of ribonucleic acids.
“As we have now discovered in cell cultures, exosomes seem to have a whole range of functions,” explained Dr. Eva-Maria Krmer-Albers. By means of their transmission activity, the small bubbles that are the vesicles
not only promote electrical activity in the nerve cells, but also
influence them on the biochemical and gene regulatory level.
“The extent of activities of the exosomes is impressive,” added Krmer-Albers. The researchers hope that the understanding of these processes will contribute to the development of new strategies for the treatment of neuronal diseases. Their next aim is to uncover how vesicles actually function in the brains of living organisms.
Neuroscientists use snail research to help explain “chemo brain”
10/08/2014
It is estimated that as many as half of patients taking cancer drugs experience a decrease in mental sharpness. While there have been many theories, what causes “chemo brain” has eluded scientists.
In an effort to solve this mystery, neuroscientists at The University of Texas Health Science Center at Houston (UTHealth) conducted an experiment in an animal memory model and their results point to a possible explanation. Findings appeared in The Journal of Neuroscience.
In the study involving a sea snail that shares many of the same memory mechanisms as humans and a drug used to treat a variety of cancers, the scientists identified
memory mechanisms blocked by the drug.
Then, they were able to counteract or
unblock the mechanisms by administering another agent.
“Our research has implications in the care of people given to cognitive deficits following drug treatment for cancer,” said John H. “Jack” Byrne, Ph.D., senior author, holder of the June and Virgil Waggoner Chair and Chairman of the Department of Neurobiology and Anatomy at the UTHealth Medical School. “There is no satisfactory treatment at this time.”
Byrne’s laboratory is known for its use of a large snail called Aplysia californica to further the understanding of the biochemical signaling among nerve cells (neurons). The snails have large neurons that relay information much like those in humans.
When Byrne’s team compared cell cultures taken from normal snails to
those administered a dose of a cancer drug called doxorubicin,
the investigators pinpointed a neuronal pathway
that was no longer passing along information properly.
With the aid of an experimental drug,
the scientists were able to reopen the pathway.
Unfortunately, this drug would not be appropriate for humans, Byrne said. “We want to identify other drugs that can rescue these memory mechanisms,” he added.
According the American Cancer Society, some of the distressing mental changes cancer patients experience may last a short time or go on for years.
Byrne’s UT Health research team includes co-lead authors Rong-Yu Liu, Ph.D., and Yili Zhang, Ph.D., as well as Brittany Coughlin and Leonard J. Cleary, Ph.D. All are affiliated with the W.M. Keck Center for the Neurobiology of Learning and Memory.
Byrne and Cleary also are on the faculty of The University of Texas Graduate School of Biomedical Sciences at Houston. Coughlin is a student at the school, which is jointly operated by UT Health and The University of Texas MD Anderson Cancer Center.
The study titled “Doxorubicin Attenuates Serotonin-Induced Long-Term Synaptic Facilitation by Phosphorylation of p38 Mitogen-Activated Protein Kinase” received support from National Institutes of Health grant (NS019895) and the Zilkha Family Discovery Fellowship.
Doxorubicin Attenuates Serotonin-Induced Long-Term Synaptic Facilitation by Phosphorylation of p38 Mitogen-Activated Protein Kinase
Source: Univ. of Texas Health Science Center at Houston
Doxorubicin Attenuates Serotonin-Induced Long-Term Synaptic Facilitation by Phosphorylation of p38 Mitogen-Activated Protein Kinase
Rong-Yu Liu*, Yili Zhang*, Brittany L. Coughlin, Leonard J. Cleary, and John H. Byrne +Show Affiliations
The Journal of Neuroscience, 1 Oct 2014, 34(40): 13289-13300; http://dx.doi.org:/10.1523/JNEUROSCI.0538-14.2014
Doxorubicin (DOX) is an anthracycline used widely for cancer chemotherapy. Its primary mode of action appears to be
topoisomerase II inhibition, DNA cleavage, and free radical generation.
However, in non-neuronal cells, DOX also inhibits the expression of
dual-specificity phosphatases (also referred to as MAPK phosphatases) and thereby
inhibits the dephosphorylation of extracellular signal-regulated kinase (ERK) and
p38 mitogen-activated protein kinase (p38 MAPK),
two MAPK isoforms important for long-term memory (LTM) formation.
Activation of these kinases by DOX in neurons, if present,
could have secondary effects on cognitive functions, such as learning and memory.
The present study used cultures of rat cortical neurons and sensory neurons (SNs) of Aplysia
to examine the effects of DOX on levels of phosphorylated ERK (pERK) and
phosphorylated p38 (p-p38) MAPK.
In addition, Aplysia neurons were used to examine the effects of DOX on
long-term enhanced excitability, long-term synaptic facilitation (LTF), and
long-term synaptic depression (LTD).
DOX treatment led to elevated levels of
pERK and p-p38 MAPK in SNs and cortical neurons.
In addition, it increased phosphorylation of
the downstream transcriptional repressor cAMP response element-binding protein 2 in SNs.
DOX treatment blocked serotonin-induced LTF and enhanced LTD induced by the neuropeptide Phe-Met-Arg-Phe-NH2. The block of LTF appeared to be attributable to
overriding inhibitory effects of p-p38 MAPK, because
LTF was rescued in the presence of an inhibitor of p38 MAPK
(SB203580 [4-(4-fluorophenyl)-2-(4-methylsulfinylphenyl)-5-(4-pyridyl)-1H-imidazole]) .
These results suggest that acute application of DOX might impair the formation of LTM via the p38 MAPK pathway.
Terms: Aplysia chemotherapy ERK p38 MAPK serotonin synaptic plasticity
Technology that controls brain cells with radio waves earns early BRAIN grant
10/08/2014
bright spots = cells with increased calcium after treatment with radio waves, allows neurons to fire
BRAIN control: The new technology uses radio waves to activate or silence cells remotely. The bright spots above represent cells with increased calcium after treatment with radio waves, a change that would allow neurons to fire.
A proposal to develop a new way to
remotely control brain cells
from Sarah Stanley, a research associate in Rockefeller University’s Laboratory of Molecular Genetics, headed by Jeffrey M. Friedman, is
among the first to receive funding from U.S. President Barack Obama’s BRAIN initiative.
The project will make use of a technique called
radiogenetics that combines the use of radio waves or magnetic fields with
nanoparticles to turn neurons on or off.
The National Institutes of Health is one of four federal agencies involved in the BRAIN (Brain Research through Advancing Innovative Neurotechnologies) initiative. Following in the ambitious footsteps of the Human Genome Project, the BRAIN initiative seeks
to create a dynamic map of the brain in action,
a goal that requires the development of new technologies. The BRAIN initiative working group, which outlined the broad scope of the ambitious project, was co-chaired by Rockefeller’s Cori Bargmann, head of the Laboratory of Neural Circuits and Behavior.
Stanley’s grant, for $1.26 million over three years, is one of 58 projects to get BRAIN grants, the NIH announced. The NIH’s plan for its part of this national project, which has been pitched as “America’s next moonshot,” calls for $4.5 billion in federal funds over 12 years.
The technology Stanley is developing would
enable researchers to manipulate the activity of neurons, as well as other cell types,
in freely moving animals in order to better understand what these cells do.
Other techniques for controlling selected groups of neurons exist, but her new nanoparticle-based technique has a
unique combination of features that may enable new types of experimentation.
it would allow researchers to rapidly activate or silence neurons within a small area of the brain or
dispersed across a larger region, including those in difficult-to-access locations.
Stanley also plans to explore the potential this method has for use treating patients.
“Francis Collins, director of the NIH, has discussed
Why do some cancers spread while others don’t? Scientists have now demonstrated that
metastatic incompetent cancers actually “poison the soil”
by generating a micro-environment that blocks cancer cells
from settling and growing in distant organs.
The “seed and the soil” hypothesis proposed by Stephen Paget in 1889 is now widely accepted to explain how
cancer cells (seeds) are able to generate fertile soil (the micro-environment)
in distant organs that promotes cancer’s spread.
However, this concept had not explained why some tumors do not spread or metastasize.
The researchers, from Weill Cornell Medical College, found that
two key proteins involved in this process work by
dramatically suppressing cancer’s spread.
The study offers hope that a drug based on these
potentially therapeutic proteins, prosaposin and Thrombospondin 1 (Tsp-1),
might help keep human cancer at bay and from metastasizing.
Scientists don’t understand why some tumors wouldn’t “want” to spread. It goes against their “job description,” says the study’s senior investigator, Vivek Mittal, Ph.D., an associate professor of cell and developmental biology in cardiothoracic surgery and director of the Neuberger Berman Foundation Lung Cancer Laboratory at Weill Cornell Medical College. He theorizes that metastasis occurs when
the barriers that the body throws up to protect itself against cancer fail.
But there are some tumors in which some of the barriers may still be intact. “So that suggests
those primary tumors will continue to grow, but that
an innate protective barrier still exists that prevents them from spreading and invading other organs,”
The researchers found that, like typical tumors,
metastasis-incompetent tumors also send out signaling molecules
that establish what is known as the “premetastatic niche” in distant organs.
These niches composed of bone marrow cells and various growth factors have been described previously by others including Dr. Mittal as the fertile “soil” that the disseminated cancer cell “seeds” grow in.
Weill Cornell’s Raúl Catena, Ph.D., a postdoctoral fellow in Dr. Mittal’s laboratory, found an important difference between the tumor types. Metastatic-incompetent tumors
systemically increased expression of Tsp-1, a molecule known to fight cancer growth.
increased Tsp-1 production was found specifically in the bone marrow myeloid cells
that comprise the metastatic niche.
These results were striking, because for the first time Dr. Mittal says
the bone marrow-derived myeloid cells were implicated as
the main producers of Tsp-1,.
In addition, Weill Cornell and Harvard researchers found that
prosaposin secreted predominantly by the metastatic-incompetent tumors
increased expression of Tsp-1 in the premetastatic lungs.
Thus, Dr. Mittal posits that prosaposin works in combination with Tsp-1
to convert pro-metastatic bone marrow myeloid cells in the niche
into cells that are not hospitable to cancer cells that spread from a primary tumor.
“The very same myeloid cells in the niche that we know can promote metastasis
can also be induced under the command of the metastatic incompetent primary tumor to inhibit metastasis,”
The research team found that
the Tsp-1–inducing activity of prosaposin
was contained in only a 5-amino acid peptide region of the protein, and
this peptide alone induced Tsp-1 in the bone marrow cells and
effectively suppressed metastatic spread in the lungs
in mouse models of breast and prostate cancer.
This 5-amino acid peptide with Tsp-1–inducing activity
has the potential to be used as a therapeutic agent against metastatic cancer,
The scientists have begun to test prosaposin in other tumor types or metastatic sites.
Dr. Mittal says that “The clinical implications of the study are:
“Not only is it theoretically possible to design a prosaposin-based drug or drugs
that induce Tsp-1 to block cancer spread, but
you could potentially create noninvasive prognostic tests
to predict whether a cancer will metastasize.”
The study was reported in the April 30 issue of Cancer Discovery, in a paper titled “Bone Marrow-Derived Gr1+ Cells Can Generate a Metastasis-Resistant Microenvironment Via Induced Secretion of Thrombospondin-1”.
Knocking out a single enzyme dramatically cripples the ability of aggressive cancer cells to spread and grow tumors.
The paper, published in the journal Proceedings of the National Academy of Sciences, sheds new light on the importance of lipids, a group of molecules that includes fatty acids and cholesterol, in the development of cancer.
Researchers have long known that cancer cells metabolize lipids differently than normal cells. Levels of ether lipids – a class of lipids that are harder to break down – are particularly elevated in highly malignant tumors.
“Cancer cells make and use a lot of fat and lipids, and that makes sense because cancer cells divide and proliferate at an accelerated rate, and to do that,
they need lipids, which make up the membranes of the cell,”
said study principal investigator Daniel Nomura, assistant professor in UC Berkeley’s Department of Nutritional Sciences and Toxicology. “Lipids have a variety of uses for cellular structure, but what we’re showing with our study is that
lipids can send signals that fuel cancer growth.”
In the study, Nomura and his team tested the effects of reducing ether lipids on human skin cancer cells and primary breast tumors. They targeted an enzyme,
alkylglycerone phosphate synthase, or AGPS,
known to be critical to the formation of ether lipids.
The researchers confirmed that
AGPS expression increased when normal cells turned cancerous.
inactivating AGPS substantially reduced the aggressiveness of the cancer cells.
“The cancer cells were less able to move and invade,” said Nomura.
The researchers also compared the impact of
disabling the AGPS enzyme in mice that had been injected with cancer cells.
Nomura. observes -“Among the mice that had the AGPS enzyme inactivated,
the tumors were nonexistent,”
“The mice that did not have this enzyme
disabled rapidly developed tumors.”
The researchers determined that
inhibiting AGPS expression depleted the cancer cells of ether lipids.
AGPS altered levels of other types of lipids important to the ability of the cancer cells to survive and spread, including
prostaglandins and acyl phospholipids.
“What makes AGPS stand out as a treatment target is that the enzyme seems to simultaneously
regulate multiple aspects of lipid metabolism
important for tumor growth and malignancy.”
Future steps include the
development of AGPS inhibitors for use in cancer therapy,
“This study sheds considerable light on the important role that AGPS plays in ether lipid metabolism in cancer cells, and it suggests that
inhibitors of this enzyme could impair tumor formation,”
said Benjamin Cravatt, Professor and Chair of Chemical Physiology at The Scripps Research Institute, who is not part of the UC.
Agilent Technologies Thought Leader Award Supports Translational Research Program
Published: Mon, March 04, 2013
The award will support Dr DePinho’s research into
metabolic reprogramming in the earliest stages of cancer.
Agilent Technologies Inc. announces that Dr. Ronald A. DePinho, a world-renowned oncologist and researcher, has received an Agilent Thought Leader Award.
DePinho is president of the University of Texas MD Anderson Cancer Center. DePinho and his team hope to discover and characterize
alterations in metabolic flux during tumor initiation and maintenance, and to identify biomarkers for early detection of pancreatic cancer together with
novel therapeutic targets.
Researchers on his team will work with scientists from the university’s newly formed Institute of Applied Cancer Sciences.
The Agilent Thought Leader Award provides funds to support personnel as well as a state-of-the-art Agilent 6550 iFunnel Q-TOF LC/MS system.
“I am extremely pleased to receive this award for metabolomics research, as the survival rates for pancreatic cancer have not significantly improved over the past 20 years,” DePinho said. “This technology will allow us to
rapidly identify new targets that drive the formation, progression and maintenance of pancreatic cancer.
Discoveries from this research will also lead to
the development of effective early detection biomarkers and novel therapeutic interventions.”
“We are proud to support Dr. DePinho’s exciting translational research program, which will make use of
metabolomics and integrated biology workflows and solutions in biomarker discovery,”
said Patrick Kaltenbach, Agilent vice president, general manager of the Liquid Phase Division, and the executive sponsor of this award.
The Agilent Thought Leader Program promotes fundamental scientific advances by support of influential thought leaders in the life sciences and chemical analysis fields.
The covalent modifier Nedd8 is critical for the activation of Smurf1 ubiquitin ligase in tumorigenesis
Figure 1: Smurf1 expression is elevated in colorectal cancer tissues.
Smurf1 expression is elevated in colorectal cancer tissues.
(a) Smurf1 expression scores are shown as box plots, with the horizontal lines representing the median; the bottom and top of the boxes representing the 25th and 75th percentiles, respectively; and the vertical bars representing the ra
Figure 2: Positive correlation of Smurf1 expression with Nedd8 and its interacting enzymes in colorectal cancer.
Positive correlation of Smurf1 expression with Nedd8 and its interacting enzymes in colorectal cancer
(a) Representative images from immunohistochemical staining of Smurf1, Ubc12, NAE1 and Nedd8 in the same colorectal cancer tumour. Scale bars, 100 μm. (b–d) The expression scores of Nedd8 (b, n=283 ), NAE1 (c, n=281) and Ubc12 (d, n=19…
Figure 3: Smurf1 interacts with Ubc12.
Smurf1 interacts with Ubc12
(a) GST pull-down assay of Smurf1 with Ubc12. Both input and pull-down samples were subjected to immunoblotting with anti-His and anti-GST antibodies. Smurf1 interacted with Ubc12 and UbcH5c, but not with Ubc9. (b) Mapping the regions…
Figure 4: Nedd8 is attached to Smurf1through C426-catalysed autoneddylation.
Nedd8 is attached to Smurf1through C426-catalysed autoneddylation
(a) Covalent neddylation of Smurf1 in vitro.Purified His-Smurf1-WT or C699A proteins were incubated with Nedd8 and Nedd8-E1/E2. Reactions were performed as described in the Methods section. Samples were analysed by western blotting wi…
Figure 5: Neddylation of Smurf1 activates its ubiquitin ligase activity.
Neddylation of Smurf1 activates its ubiquitin ligase activity.
(a) In vivo Smurf1 ubiquitylation assay. Nedd8 was co-expressed with Smurf1 WT or C699A in HCT116 cells (left panels). Twenty-four hours post transfection, cells were treated with MG132 (20 μM, 8 h). HCT116 cells were transfected with…
12-LO enzyme promotes the obesity-induced oxidative stress in the pancreatic cells.
An enzyme called 12-LO promotes the obesity-induced oxidative stress in the pancreatic cells that leads
to pre-diabetes, and diabetes.
12-LO’s enzymatic action is the last step in
the production of certain small molecules that harm the cell,
according to a team from Indiana University School of Medicine, Indianapolis.
The findings will enable the development of drugs that can interfere with this enzyme, preventing or even reversing diabetes. The research is published ahead of print in the journal Molecular and Cellular Biology.
In earlier studies, these researchers and their collaborators at Eastern Virginia Medical School showed that
12-LO (which stands for 12-lipoxygenase) is present in these cells
only in people who become overweight.
The harmful small molecules resulting from 12-LO’s enzymatic action are known as HETEs, short for hydroxyeicosatetraenoic acid.
HETEs harm the mitochondria, which then
fail to produce sufficient energy to enable
the pancreatic cells to manufacture the necessary quantities of insulin.
For the study, the investigators genetically engineered mice that
lacked the gene for 12-LO exclusively in their pancreas cells.
Mice were either fed a low-fat or high-fat diet.
Both the control mice and the knockout mice on the high fat diet
developed obesity and insulin resistance.
The investigators also examined the pancreatic beta cells of both knockout and control mice, using both microscopic studies and molecular analysis. Those from the knockout mice were intact and healthy, while
those from the control mice showed oxidative damage,
demonstrating that 12-LO and the resulting HETEs
caused the beta cell failure.
Mirmira notes that fatty diet used in the study was the Western Diet, which comprises mostly saturated-“bad”-fats. Based partly on a recent study of related metabolic pathways, he says that
the unsaturated and mono-unsaturated fats-which comprise most fats in the healthy,
relatively high fat Mediterranean diet-are unlikely to have the same effects.
“Our research is the first to show that 12-LO in the beta cell
is the culprit in the development of pre-diabetes, following high fat diets,” says Mirmira.
“Our work also lends important credence to the notion that
the beta cell is the primary defective cell in virtually all forms of diabetes and pre-diabetes.”
Specially engineered mice gained no weight, and normal counterparts became obese
on the same high-fat, obesity-inducing Western diet.
Specially engineered mice that lacked a particular gene did not gain weight
when fed a typical high-fat, obesity-inducing Western diet.
Yet, these mice ate the same amount as their normal counterparts that became obese.
The mice were engineered with fat cells that lacked a gene called SEL1L,
known to be involved in the clearance of mis-folded proteins
in the cell’s protein making machinery called the endoplasmic reticulum (ER).
When mis-folded proteins are not cleared but accumulate,
they destroy the cell and contribute to such diseases as
mad cow disease,
Type 1 diabetes and
cystic fibrosis.
“The million-dollar question is why don’t these mice gain weight? Is this related to its inability to clear mis-folded proteins in the ER?” said Ling Qi, associate professor of molecular and biochemical nutrition and senior author of the study published online July 24 in Cell Metabolism. Haibo Sha, a research associate in Qi’s lab, is the paper’s lead author.
Interestingly, the experimental mice developed a host of other problems, including
postprandial hypertriglyceridemia,
and fatty livers.
“Although we are yet to find out whether these conditions contribute to the lean phenotype, we found that
there was a lipid partitioning defect in the mice lacking SEL1L in fat cells,
where fat cells cannot store fat [lipids], and consequently
fat goes to the liver.
During the investigation of possible underlying mechanisms, we discovered
a novel function for SEL1L as a regulator of lipid metabolism,” said Qi.
Sha said “We were very excited to find that
SEL1L is required for the intracellular trafficking of
lipoprotein lipase (LPL), acting as a chaperone,” .
and added that “Using several tissue-specific knockout mouse models,
we showed that this is a general phenomenon,”
Without LPL, lipids remain in the circulation;
fat and muscle cells cannot absorb fat molecules for storage and energy combustion,
People with LPL mutations develop
postprandial hypertriglyceridemia similar to
conditions found in fat cell-specific SEL1L-deficient mice, said Qi.
Future work will investigate the
role of SEL1L in human patients carrying LPL mutations and
determine why fat cell-specific SEL1L-deficient mice remain lean under Western diets, said Sha.
Co-authors include researchers from Cedars-Sinai Medical Center in Los Angeles; Wageningen University in the Netherlands; Georgia State University; University of California, Los Angeles; and the Medical College of Soochow University in China.
The study was funded by the U.S. National Institutes of Health, the Netherlands Organization for Health Research and Development National Institutes of Health, the Cedars-Sinai Medical Center, Chinese National Science Foundation, the American Diabetes Association, Cornell’s Center for Vertebrate Genomics and the Howard Hughes Medical Institute.
While work with biomarkers continues to grow, scientists are also grappling with research-related bottlenecks, such as
affinity reagent development,
platform reproducibility, and
sensitivity.
Biomarkers by definition indicate some state or process that generally occurs
at a spatial or temporal distance from the marker itself, and
it would not be an exaggeration to say that biomedicine has become infatuated with them:
where to find them,
when they may appear,
what form they may take, and
how they can be used to diagnose a condition or
predict whether a therapy may be successful.
Biomarkers are on the agenda of many if not most industry gatherings, and in cases such as Oxford Global’s recent “Biomarker Congress” and the GTC “Biomarker Summit”, they hold the naming rights. There, some basic principles were built upon, amended, and sometimes challenged.
In oncology, for example, biomarker discovery is often predicated on the premise that
proteins shed from a tumor will traverse to and persist in, and be detectable in, the circulation.
By quantifying these proteins—singularly or as part of a larger “signature”—the hope is
to garner information about the molecular characteristics of the cancer
that will help with cancer detection and
personalization of the treatment strategy.
Yet this approach has not yet turned into the panacea that was hoped for. Bottlenecks exist in
affinity reagent development,
platform reproducibility, and
sensitivity.
There is also a dearth of understanding of some of the
fundamental principles of biomarker biology that we need to know the answers to,
said Parag Mallick, Ph.D., whose lab at Stanford University is “working on trying to understand where biomarkers come from.”
There are dogmas saying that
circulating biomarkers come solely from secreted proteins.
But Dr. Mallick’s studies indicate that fully
50% of circulating proteins may come from intracellular sources or
proteins that are annotated as such.
“We don’t understand the processes governing
which tumor-derived proteins end up in the blood.”
Other questions include “how does the size of a tumor affect how much of a given protein will be in the blood?”—perhaps
the tumor is necrotic at the center, or
it’s hypervascular or hypovascular.
He points out “The problem is that these are highly nonlinear processes at work, and
there is a large number of factors that might affect the answer to that question,” .
Their research focuses on using
mass spectrometry and
computational analysis
to characterize the biophysical properties of the circulating proteome, and
relate these to measurements made of the tumor itself.
Furthermore, he said – “We’ve observed that the proteins that are likely to
first show up and persist in the circulation, ..
are more stable than proteins that don’t,”
“we can quantify how significant the effect is.”
The goal is ultimately to be able to
build rigorous, formal mathematical models that will allow something measured in the blood
to be tied back to the molecular biology taking place in the tumor.
And conversely, to use those models
to predict from a tumor what will be found in the circulation.
“Ultimately, the models will allow you to connect the dots between
what you measure in the blood and the biology of the tumor.”
Bound for Affinity Arrays
Affinity reagents are the main tools for large-scale protein biomarker discovery. And while this has tended to mean antibodies (or their derivatives), other affinity reagents are demanding a place in the toolbox.
Affimers, a type of affinity reagent being developed by Avacta, consist of
a biologically inert, biophysically stable protein scaffold
containing three variable regions into which
distinct peptides are inserted.
The resulting three-dimensional surface formed by these peptides
interacts and binds to proteins and other molecules in solution,
much like the antigen-binding site of antibodies.
Unlike antibodies, Affimers are relatively small (13 KDa),
non-post-translationally modified proteins
that can readily be expressed in bacterial culture.
They may be made to bind surfaces through unique residues
engineered onto the opposite face of the Affimer,
allowing the binding site to be exposed to the target in solution.
“We don’t seem to see in what we’ve done so far
any real loss of activity or functionality of Affimers when bound to surfaces—
they’re very robust,” said CEO Alastair Smith, Ph.D.
Avacta is taking advantage of this stability and its large libraries of Affimers to develop
very large affinity microarrays for
drug and biomarker discovery.
To date they have printed arrays with around 20–25,000 features, and Dr. Smith is “sure that we can get toward about 50,000 on a slide,” he said. “There’s no real impediment to us doing that other than us expressing the proteins and getting on with it.”
Customers will be provided with these large, complex “naïve” discovery arrays, readable with standard equipment. The plan is for the company to then “support our customers by providing smaller arrays with
the Affimers that are binding targets of interest to them,” Dr. Smith foretold.
And since the intellectual property rights are unencumbered,
Affimers in those arrays can be licensed to the end users
to develop diagnostics that can be validated as time goes on.
Around 20,000-Affimer discovery arrays were recently tested by collaborator Professor Ann Morgan of the University of Leeds with pools of unfractionated serum from patients with symptoms of inflammatory disease. The arrays
“rediscovered” elevated C-reactive protein (CRP, the clinical gold standard marker)
as well as uncovered an additional 22 candidate biomarkers.
other candidates combined with CRP, appear able to distinguish between different diseases such as
rheumatoid arthritis,
psoriatic arthritis,
SLE, or
giant cell arteritis.
Epigenetic Biomarkers
Sometimes biomarkers are used not to find disease but
to distinguish healthy human cell types, with
examples being found in flow cytometry and immunohistochemistry.
These widespread applications, however, are difficult to standardize, being
subject to arbitrary or subjective gating protocols and other imprecise criteria.
Epiontis instead uses an epigenetic approach. “What we need is a unique marker that is
demethylated only in one cell type and
methylated in all the other cell types,”
Each cell of the right cell type will have
two demethylated copies of a certain gene locus,
allowing them to be enumerated by quantitative PCR.
The biggest challenge is finding that unique epigenetic marker. To do so they look through the literature for proteins and genes described as playing a role in the cell type’s biology, and then
look at the methylation patterns to see if one can be used as a marker,
They also “use customized Affymetrix chips to look at the
differential epigenetic status of different cell types on a genomewide scale.”
explained CBO and founder Ulrich Hoffmueller, Ph.D.
The company currently has a panel of 12 assays for 12 immune cell types. Among these is an assay for
regulatory T (Treg) cells that queries the Foxp3 gene—which is uniquely demethylated in Treg
even though it is transiently expressed in activated T cells of other subtypes.
Also assayed are Th17 cells, difficult to detect by flow cytometry because
“the cells have to be stimulated in vitro,” he pointed out.
Developing New Assays for Cancer Biomarkers
Researchers at Myriad RBM and the Cancer Prevention Research Institute of Texas are collaborating to develop
new assays for cancer biomarkers on the Myriad RBM Multi-Analyte Profile (MAP) platform.
The release of OncologyMAP 2.0 expanded Myriad RBM’s biomarker menu to over 250 analytes, which can be measured from a small single sample, according to the company. Using this menu, L. Stephen et al., published a poster, “Analysis of Protein Biomarkers in Prostate and Colorectal Tumor Lysates,” which showed the results of
a survey of proteins relevant to colorectal (CRC) and prostate (PC) tumors
to identify potential proteins of interest for cancer research.
The study looked at CRC and PC tumor lysates and found that 102 of the 115 proteins showed levels above the lower limit of quantification.
Four markers were significantly higher in PC and 10 were greater in CRC.
For most of the analytes, duplicate sections of the tumor were similar, although some analytes did show differences. In four of the CRC analytes, tumor number four showed differences for CEA and tumor number 2 for uPA.
Thirty analytes were shown to be
different in CRC tumor compared to its adjacent tissue.
Ten of the analytes were higher in adjacent tissue compared to CRC.
Eighteen of the markers examined demonstrated —-
significant correlations of CRC tumor concentration to serum levels.
“This suggests.. that the Oncology MAP 2.0 platform “provides a good method for studying changes in tumor levels because many proteins can be assessed with a very small sample.”
Clinical Test Development with MALDI-ToF
While there have been many attempts to translate results from early discovery work on the serum proteome into clinical practice, few of these efforts have progressed past the discovery phase.
Matrix-assisted laser desorption/ionization-time of flight (MALDI-ToF) mass spectrometry on unfractionated serum/plasma samples offers many practical advantages over alternative techniques, and does not require
a shift from discovery to development and commercialization platforms.
Biodesix claims it has been able to develop the technology into
a reproducible, high-throughput tool to
routinely measure protein abundance from serum/plasma samples.
“.. we improved data-analysis algorithms to
reproducibly obtain quantitative measurements of relative protein abundance from MALDI-ToF mass spectra.
Heinrich Röder, CTO points out that the MALDI-ToF measurements
are combined with clinical outcome data using
modern learning theory techniques
to define specific disease states
based on a patient’s serum protein content,”
The clinical utility of the identification of these disease states can be investigated through a retrospective analysis of differing sample sets. For example, Biodesix clinically validated its first commercialized serum proteomic test, VeriStrat®, in 85 different retrospective sample sets.
Röder adds that “It is becoming increasingly clear that
the patients whose serum is characterized as VeriStrat Poor show
consistently poor outcomes irrespective of
tumor type,
histology, or
molecular tumor characteristics,”
MALDI-ToF mass spectrometry, in its standard implementation,
allows for the observation of around 100 mostly high-abundant serum proteins.
Further, “while this does not limit the usefulness of tests developed from differential expression of these proteins,
the discovery potential would be greatly enhanced
if we could probe deeper into the proteome
while not giving up the advantages of the MALDI-ToF approach,”
Biodesix reports that its new MALDI approach, Deep MALDI™, can perform
simultaneous quantitative measurement of more than 1,000 serum protein features (or peaks) from 10 µL of serum in a high-throughput manner.
it increases the observable signal noise ratio from a few hundred to over 50,000,
resulting in the observation of many lower-abundance serum proteins.
Breast cancer, a disease now considered to be a collection of many complexes of symptoms and signatures—the dominant ones are labeled Luminal A, Luminal B, Her2, and Basal— which suggests different prognose, and
these labels are considered too simplistic for understanding and managing a woman’s cancer.
Studies published in the past year have looked at
somatic mutations,
gene copy number aberrations,
gene expression abnormalities,
protein and miRNA expression, and
DNA methylation,
coming up with a list of significantly mutated genes—hot spots—in different categories of breast cancers. Targeting these will inevitably be the focus of much coming research.
“We’ve been taking these large trials and profiling these on a variety of array or sequence platforms. We think we’ll get
prognostic drivers
predictive markers for taxanes and
monoclonal antibodies and
tamoxifen and aromatase inhibitors,”
explained Brian Leyland-Jones, Ph.D., director of Edith Sanford Breast Cancer Research. “We will end up with 20–40 different diseases, maybe more.”
Edith Sanford Breast Cancer Research is undertaking a pilot study in collaboration with The Scripps Research Institute, using a variety of tests on 25 patients to see how the information they provide complements each other, the overall flow, and the time required to get and compile results.
Laser-captured tumor samples will be subjected to low passage whole-genome, exome, and RNA sequencing (with targeted resequencing done in parallel), and reverse-phase protein and phosphorylation arrays, with circulating nucleic acids and circulating tumor cells being queried as well. “After that we hope to do a 100- or 150-patient trial when we have some idea of the best techniques,” he said.
Dr. Leyland-Jones predicted that ultimately most tumors will be found
to have multiple drivers,
with most patients receiving a combination of two, three, or perhaps four different targeted therapies.
Reduce to Practice
According to Randox, the evidence Investigator is a sophisticated semi-automated biochip system designed for research, clinical, forensic, and veterinary applications.
Once biomarkers that may have an impact on therapy are discovered, it is not always routine to get them into clinical practice. Leaving regulatory and financial, intellectual property and cultural issues aside, developing a diagnostic based on a biomarker often requires expertise or patience that its discoverer may not possess.
Andrew Gribben is a clinical assay and development scientist at Randox Laboratories, based in Northern Ireland, U.K. The company utilizes academic and industrial collaborators together with in-house discovery platforms to identify biomarkers that are
augmented or diminished in a particular pathology
relative to appropriate control populations.
Biomarkers can be developed to be run individually or
combined into panels of immunoassays on its multiplex biochip array technology.
Specificity can also be gained—or lost—by the affinity of reagents in an assay. The diagnostic potential of Heart-type fatty acid binding protein (H-FABP) abundantly expressed in human myocardial cells was recognized by Jan Glatz of Maastricht University, The Netherlands, back in 1988. Levels rise quickly within 30 minutes after a myocardial infarction, peaking at 6–8 hours and return to normal within 24–30 hours. Yet at the time it was not known that H-FABP was a member of a multiprotein family, with which the polyclonal antibodies being used in development of an assay were cross-reacting, Gribben related.
Randox developed monoclonal antibodies specific to H-FABP, funded trials investigating its use alone, and multiplexed with cardiac biomarker assays, and, more than 30 years after the biomarker was identified, in 2011, released a validated assay for H-FABP as a biomarker for early detection of acute myocardial infarction.
Ultrasensitive Immunoassays for Biomarker Development
Research has shown that detection and monitoring of biomarker concentrations can provide
insights into disease risk and progression.
Cytokines have become attractive biomarkers and candidates
for targeted therapies for a number of autoimmune diseases, including rheumatoid arthritis (RA), Crohn’s disease, and psoriasis, among others.
However, due to the low-abundance of circulating cytokines, such as IL-17A, obtaining robust measurements in clinical samples has been difficult.
Singulex reports that its digital single-molecule counting technology provides
increased precision and detection sensitivity over traditional ELISA techniques,
helping to shed light on biomarker verification and validation programs.
The company’s Erenna® immunoassay system, which includes optimized immunoassays, offers LLoQ to femtogram levels per mL resolution—even in healthy populations, at an improvement of 1-3 fold over standard ELISAs or any conventional technology and with a dynamic range of up to 4-logs, according to a Singulex official, who adds that
this sensitivity improvement helps minimize undetectable samples that
could otherwise delay or derail clinical studies.
The official also explains that the Singulex solution includes an array of products and services that are being applied to a number of programs and have enabled the development of clinically relevant biomarkers, allowing translation from discovery to the clinic.
In a poster entitled “Advanced Single Molecule Detection: Accelerating Biomarker Development Utilizing Cytokines through Ultrasensitive Immunoassays,” a case study was presented of work performed by Jeff Greenberg of NYU to show how the use of the Erenna system can provide insights toward
improving the clinical utility of biomarkers and
accelerating the development of novel therapies for treating inflammatory diseases.
A panel of inflammatory biomarkers was examined in DMARD (disease modifying antirheumatic drugs)-naïve RA (rheumatoid arthritis) vs. knee OA (osteoarthritis) patient cohorts. Markers that exhibited significant differences in plasma concentrations between the two cohorts included
CRP, IL-6R alpha, IL-6, IL-1 RA, VEGF, TNF-RII, and IL-17A, IL-17F, and IL-17A/F.
Among the three tested isoforms of IL-17,
the magnitude of elevation for IL-17F in RA patients was the highest.
“Singulex provides high-resolution monitoring of baseline IL-17A concentrations that are present at low levels,” concluded the researchers. “The technology also enabled quantification of other IL-17 isoforms in RA patients, which have not been well characterized before.”
The Singulex Erenna System has also been applied to cardiovascular disease research, for which its
cardiac troponin I (cTnI) digital assay can be used to measure circulating
levels of cTnI undetectable by other commercial assays.
Recently presented data from Brigham and Women’s Hospital and the TIMI-22 study showed that
using the Singulex test to serially monitor cTnI helps
stratify risk in post-acute coronary syndrome patients and
can identify patients with elevated cTnI
who have the most to gain from intensive vs. moderate-dose statin therapy,
according to the scientists involved in the research.
The study poster, “Prognostic Performance of Serial High Sensitivity Cardiac Troponin Determination in Stable Ischemic Heart Disease: Analysis From PROVE IT-TIMI 22,” was presented at the 2013 American College of Cardiology (ACC) Annual Scientific Session & Expo by R. O’Malley et al.
Biomarkers Changing Clinical Medicine
Better Diagnosis, Prognosis, and Drug Targeting Are among Potential Benefits
John Morrow Jr., Ph.D.
Researchers at EMD Chemicals are developing biomarker immunoassays
to monitor drug-induced toxicity including kidney damage.
The pace of biomarker development is accelerating as investigators report new studies on cancer, diabetes, Alzheimer disease, and other conditions in which the evaluation and isolation of workable markers is prominently featured.
Wei Zheng, Ph.D., leader of the R&D immunoassay group at EMD Chemicals, is overseeing a program to develop biomarker immunoassays to
monitor drug-induced toxicity, including kidney damage.
“One of the principle reasons for drugs failing during development is because of organ toxicity,” says Dr. Zheng.
“proteins liberated into the serum and urine can serve as biomarkers of adverse response to drugs, as well as disease states.”
Through collaborative programs with Rules-Based Medicine (RBM), the EMD group has released panels for the profiling of human renal impairment and renal toxicity. These urinary biomarker based products fit the FDA and EMEA guidelines for assessment of drug-induced kidney damage in rats.
The group recently performed a screen for potential protein biomarkers in relation to
kidney toxicity/damage on a set of urine and plasma samples
from patients with documented renal damage.
Additionally, Dr. Zheng is directing efforts to move forward with the multiplexed analysis of
organ and cellular toxicity.
Diseases thought to involve compromised oxidative phosphorylation include
diabetes, Parkinson and Alzheimer diseases, cancer, and the aging process itself.
Good biomarkers allow Dr. Zheng to follow the mantra, “fail early, fail fast.” With robust, multiplexible biomarkers, EMD can detect bad drugs early and kill them before they move into costly large animal studies and clinical trials. “Recognizing the severe liability that toxicity presents, we can modify the structure of the candidate molecule and then rapidly reassess its performance.”
Scientists at Oncogene Science a division of Siemens Healthcare Diagnostics, are also focused on biomarkers. “We are working on a number of antibody-based tests for various cancers, including a test for the Ca-9 CAIX protein, also referred to as carbonic anhydrase,” Walter Carney, Ph.D., head of the division, states.
CAIX is a transmembrane protein that is
overexpressed in a number of cancers, and, like Herceptin and the Her-2 gene,
can serve as an effective and specific marker for both diagnostic and therapeutic purposes.
It is liberated into the circulation in proportion to the tumor burden.
Dr. Carney and his colleagues are evaluating patients after tumor removal for the presence of the Ca-9 CAIX protein. If
the levels of the protein in serum increase over time,
this suggests that not all the tumor cells were removed and the tumor has metastasized.
Dr. Carney and his team have developed both an immuno-histochemistry and an ELISA test that could be used as companion diagnostics in clinical trials of CAIX-targeted drugs.
The ELISA for the Ca-9 CAIX protein will be used in conjunction with Wilex’ Rencarex®, which is currently in a
Phase III trial as an adjuvant therapy for non-metastatic clear cell renal cancer.
Additionally, Oncogene Science has in its portfolio an FDA-approved test for the Her-2 marker. Originally approved for Her-2/Neu-positive breast cancer, its indications have been expanded over time, and was approved
for the treatment of gastric cancer last year.
It is normally present on breast cancer epithelia but
overexpressed in some breast cancer tumors.
“Our products are designed to be used in conjunction with targeted therapies,” says Dr. Carney. “We are working with companies that are developing technology around proteins that are
overexpressed in cancerous tissues and can be both diagnostic and therapeutic targets.”
The long-term goal of these studies is to develop individualized therapies, tailored for the patient. Since the therapies are expensive, accurate diagnostics are critical to avoid wasting resources on patients who clearly will not respond (or could be harmed) by the particular drug.
“At this time the rate of response to antibody-based therapies may be very poor, as
they are often employed late in the course of the disease, and patients are in such a debilitated state
that they lack the capacity to react positively to the treatment,” Dr. Carney explains.
Nanoscale Real-Time Proteomics
Stanford University School of Medicine researchers, working with Cell BioSciences, have developed a
nanofluidic proteomic immunoassay that measures protein charge,
similar to immunoblots, mass spectrometry, or flow cytometry.
unlike these platforms, this approach can measure the amount of individual isoforms,
specifically, phosphorylated molecules.
“We have developed a nanoscale device for protein measurement, which I believe could be useful for clinical analysis,” says Dean W. Felsher, M.D., Ph.D., associate professor at Stanford University School of Medicine.
Critical oncogenic transformations involving
the activation of the signal-related kinases ERK-1 and ERK-2 can now be followed with ease.
“The fact that we measure nanoquantities with accuracy means that
we can interrogate proteomic profiles in clinical patients,
by drawing tiny needle aspirates from tumors over the course of time,” he explains.
“This allows us to observe the evolution of tumor cells and
their response to therapy
from a baseline of the normal tissue as a standard of comparison.”
According to Dr. Felsher, 20 cells is a large enough sample to obtain a detailed description. The technology is easy to automate, which allows
the inclusion of hundreds of assays.
Contrasting this technology platform with proteomic analysis using microarrays, Dr. Felsher notes that the latter is not yet workable for revealing reliable markers.
Dr. Felsher and his group published a description of this technology in Nature Medicine. “We demonstrated that we could take a set of human lymphomas and distinguish them from both normal tissue and other tumor types. We can
quantify changes in total protein, protein activation, and relative abundance of specific phospho-isoforms
from leukemia and lymphoma patients receiving targeted therapy.
Even with very small numbers of cells, we are able to show that the results are consistent, and
our sample is a random profile of the tumor.”
Splice Variant Peptides
“Aberrations in alternative splicing may generate
much of the variation we see in cancer cells,”
says Gilbert Omenn, Ph.D., director of the center for computational medicine and bioinformatics at the University of Michigan School of Medicine. Dr. Omenn and his colleague, Rajasree Menon, are
using this variability as a key to new biomarker identification.
It is becoming evident that splice variants play a significant role in the properties of cancer cells, including
initiation, progression, cell motility, invasiveness, and metastasis.
Alternative splicing occurs through multiple mechanisms
when the exons or coding regions of the DNA transcribe mRNA,
generating initiation sites and connecting exons in protein products.
Their translation into protein can result in numerous protein isoforms, and
these isoforms may reflect a diseased or cancerous state.
Regulatory elements within the DNA are responsible for selecting different alternatives; thus
the splice variants are tempting targets for exploitation as biomarkers.
Analyses of the splice-site mutation
Despite the many questions raised by these observations, splice variation in tumor material has not been widely studied. Cancer cells are known for their tremendous variability, which allows them to
grow rapidly, metastasize, and develop resistance to anticancer drugs.
Dr. Omenn and his collaborators used
mass spec data to interrogate a custom-built database of all potential mRNA sequences
to find alternative splice variants.
When they compared normal and malignant mammary gland tissue from a mouse model of Her2/Neu human breast cancers, they identified a vast number (608) of splice variant proteins, of which
peptides from 216 were found only in the tumor sample.
“These novel and known alternative splice isoforms
are detectable both in tumor specimens and in plasma and
represent potential biomarker candidates,” Dr. Omenn adds.
Dr. Omenn’s observations and those of his colleague Lewis Cantley, Ph.D., have also
shed light on the origins of the classic Warburg effect,
the shift to anaerobic glycolysis in tumor cells.
The novel splice variant M2, of muscle pyruvate kinase,
is observed in embryonic and tumor tissue.
It is associated with this shift, the result of
the expression of a peptide splice variant sequence.
It is remarkable how many different areas of the life sciences are tied into the phenomenon of splice variation. The changes in the genetic material can be much greater than point mutations, which have been traditionally considered to be the prime source of genetic variability.
“We now have powerful methods available to uncover a whole new category of variation,” Dr. Omenn says. “High-throughput RNA sequencing and proteomics will be complementary in discovery studies of splice variants.”
Splice variation may play an important role in rapid evolutionary changes, of the sort discussed by Susumu Ohno and Stephen J. Gould decades ago. They, and other evolutionary biologists, argued that
gene duplication, combined with rapid variability, could fuel major evolutionary jumps.
At the time, the molecular mechanisms of variation were poorly understood, but today
the tools are available to rigorously evaluate the role of
splice variation and other contributors to evolutionary change.
“Biomarkers derived from studies of splice variants, could, in the future, be exploited
both for diagnosis and prognosis and
for drug targeting of biological networks,
in situations such as the Her-2/Neu breast cancers,” Dr. Omenn says.
Aminopeptidase Activities
“By correlating the proteolytic patterns with disease groups and controls, we have shown that
exopeptidase activities contribute to the generation of not only cancer-specific
but also cancer type specific serum peptides.
according to Paul Tempst, Ph.D., professor and director of the Protein Center at the Memorial Sloan-Kettering Cancer Center.
So there is a direct link between peptide marker profiles of disease and differential protease activity.” For this reason Dr. Tempst argues that “the patterns we describe may have value as surrogate markers for detection and classification of cancer.”
To investigate this avenue, Dr. Tempst and his colleagues have followed
the relationship between exopeptidase activities and metastatic disease.
“We monitored controlled, de novo peptide breakdown in large numbers of biological samples using mass spectrometry, with relative quantitation of the metabolites,” Dr. Tempst explains. This entailed the use of magnetic, reverse-phase beads for analyte capture and a MALDI-TOF MS read-out.
“In biomarker discovery programs, functional proteomics is usually not pursued,” says Dr. Tempst. “For putative biomarkers, one may observe no difference in quantitative levels of proteins, while at the same time, there may be substantial differences in enzymatic activity.”
In a preliminary prostate cancer study, the team found a significant difference
in activity levels of exopeptidases in serum from patients with metastatic prostate cancer
as compared to primary tumor-bearing individuals and normal healthy controls.
However, there were no differences in amounts of the target protein, and this potential biomarker would have been missed if quantitative levels of protein had been the only criterion of selection.
It is frequently stated that “practical fusion energy is 30 years in the future and always will be.” The same might be said of functional, practical biomarkers that can pass muster with the FDA. But splice variation represents a new handle on this vexing problem. It appears that we are seeing the emergence of a new approach that may finally yield definitive diagnostic tests, detectable in serum and urine samples.
Part 7. Epigenetics and Drug Metabolism
DNA Methylation Rules: Studying Epigenetics with New Tools
The tools to unravel the epigenetic control mechanisms that influence how cells control access of transcriptional proteins to DNA are just beginning to emerge.
New tools may help move the field of epigenetic analysis forward and potentially unveil novel biomarkers for cellular development, differentiation, and disease.
DNA sequencing has had the power of technology behind it as novel platforms to produce more sequencing faster and at lower cost have been introduced. But the tools to unravel the epigenetic control mechanisms that influence how cells control access of transcriptional proteins to DNA are just beginning to emerge.
Among these mechanisms, DNA methylation, or the enzymatically mediated addition of a methyl group to cytosine or adenine dinucleotides,
serves as an inherited epigenetic modification that
stably modifies gene expression in dividing cells.
The unique methylomes are largely maintained in differentiated cell types, making them critical to understanding the differentiation potential of the cell.
In the DNA methylation process, cytosine residues in the genome are enzymatically modified to 5-methylcytosine,
which participates in transcriptional repression of genes during development and disease progression.
5-methylcytosine can be further enzymatically modified to 5-hydroxymethylcytosine by the TET family of methylcytosine dioxygenases. DNA methylation affects gene transcription by physically
interfering with the binding of proteins involved in gene transcription.
Methylated DNA may be bound by methyl-CpG-binding domain proteins (MBDs) that can
then recruit additional proteins. Some of these include histone deacetylases and other chromatin remodeling proteins that modify histones, thereby
forming compact, inactive chromatin, or heterochromatin.
While DNA methylation doesn’t change the genetic code,
it influences chromosomal stability and gene expression.
Epigenetics and Cancer Biomarkers
multistage chemical carcinogenesis
And because of the increasing recognition that DNA methylation changes are involved in human cancers, scientists have suggested that these epigenetic markers may provide biological markers for cancer cells, and eventually point toward new diagnostic and therapeutic targets. Cancer cell genomes display genome-wide abnormalities in DNA methylation patterns,
some of which are oncogenic and contribute to genome instability.
In particular, de novo methylation of tumor suppressor gene promoters
occurs frequently in cancers, thereby silencing them and promoting transformation.
Cytosine hydroxymethylation (5-hydroxymethylcytosine, or 5hmC), the aforementioned DNA modification resulting from the enzymatic conversion of 5mC into 5-hydroxymethylcytosine by the TET family of oxygenases, has been identified
as another key epigenetic modification marking genes important for
pluripotency in embryonic stem cells (ES), as well as in cancer cells.
The base 5-hydroxymethylcytosine was recently identified as an oxidation product of 5-methylcytosine in mammalian DNA. In 2011, using sensitive and quantitative methods to assess levels of 5-hydroxymethyl-2′-deoxycytidine (5hmdC) and 5-methyl-2′-deoxycytidine (5mdC) in genomic DNA, scientists at the Department of Cancer Biology, Beckman Research Institute of the City of Hope, Duarte, California investigated
whether levels of 5hmC can distinguish normal tissue from tumor tissue.
They showed that in squamous cell lung cancers, levels of 5hmdC showed
up to five-fold reduction compared with normal lung tissue.
In brain tumors,5hmdC showed an even more drastic reduction
with levels up to more than 30-fold lower than in normal brain,
but 5hmdC levels were independent of mutations in isocitrate dehydrogenase-1, the enzyme that converts 5hmC to 5hmdC.
Immunohistochemical analysis indicated that 5hmC is “remarkably depleted” in many types of human cancer.
there was an inverse relationship between 5hmC levels and cell proliferation with lack of 5hmC in proliferating cells.
Their data suggest that 5hmdC is strongly depleted in human malignant tumors,
a finding that adds another layer of complexity to the aberrant epigenome found in cancer tissue.
In addition, a lack of 5hmC may become a useful biomarker for cancer diagnosis.
Enzymatic Mapping
But according to New England Biolabs’ Sriharsa Pradhan, Ph.D., methods for distinguishing 5mC from 5hmC and analyzing and quantitating the cell’s entire “methylome” and “hydroxymethylome” remain less than optimal.
The protocol for bisulphite conversion to detect methylation remains the “gold standard” for DNA methylation analysis. This method is generally followed by PCR analysis for single nucleotide resolution to determine methylation across the DNA molecule. According to Dr. Pradhan, “.. bisulphite conversion does not distinguish 5mC and 5hmC,”
Recently we found an enzyme, a unique DNA modification-dependent restriction endonuclease, AbaSI, which can
decode the hydryoxmethylome of the mammalian genome.
You easily can find out where the hydroxymethyl regions are.”
AbaSI, recognizes 5-glucosylatedmethylcytosine (5gmC) with high specificity when compared to 5mC and 5hmC, and
cleaves at narrow range of distances away from the recognized modified cytosine.
By mapping the cleaved ends, the exact 5hmC location can, the investigators reported, be determined.
Dr. Pradhan and his colleagues at NEB; the Department of Biochemistry, Emory University School of Medicine, Atlanta; and the New England Biolabs Shanghai R&D Center described use of this technique in a paper published in Cell Reports this month, in which they described high-resolution enzymatic mapping of genomic hydroxymethylcytosine in mouse ES cells.
In the current report, the authors used the enzyme technology for the genome-wide high-resolution hydroxymethylome, describing simple library construction even with a low amount of input DNA (50 ng) and the ability to readily detect 5hmC sites with low occupancy.
As a result of their studies, they propose that
factors affecting the local 5mC accessibility to TET enzymes play important roles in the 5hmC deposition
including include chromatin compaction, nucleosome positioning, or TF binding.
the regularly oscillating 5hmC profile around the CTCF-binding sites, suggests 5hmC ‘‘writers’’ may be sensitive to the nucleosomal environment.
some transiently stable 5hmCs may indicate a poised epigenetic state or demethylation intermediate, whereas others may suggest a locally accessible chromosomal environment for the TET enzymatic apparatus.
“We were able to do complete mapping in mouse embryonic cells and are pleased about what this enzyme can do and how it works,” Dr. Pradhan said.
And the availability of novel tools that make analysis of the methylome and hypomethylome more accessible will move the field of epigenetic analysis forward and potentially novel biomarkers for cellular development, differentiation, and disease.
Patricia Fitzpatrick Dimond, Ph.D. (pdimond@genengnews.com), is technical editor at Genetic Engineering & Biotechnology News.
Epigenetic Regulation of ADME-Related Genes: Focus on Drug Metabolism and Transport
Published: Sep 23, 2013
Epigenetic regulation of gene expression refers to heritable factors that are functionally relevant genomic modifications but that do not involve changes in DNA sequence.
Examples of such modifications include
DNA methylation, histone modifications, noncoding RNAs, and chromatin architecture.
Epigenetic modifications are crucial for
packaging and interpreting the genome, and they have fundamental functions in regulating gene expression and activity under the influence of physiologic and environmental factors.
In this issue of Drug Metabolism and Disposition, a series of articles is presented to demonstrate the role of epigenetic factors in regulating
the expression of genes involved in drug absorption, distribution, metabolism, and excretion in organ development, tissue-specific gene expression, sexual dimorphism, and in the adaptive response to xenobiotic exposure, both therapeutic and toxic.
The articles also demonstrate that, in addition to genetic polymorphisms, epigenetics may also contribute to wide inter-individual variations in drug metabolism and transport. Identification of functionally relevant epigenetic biomarkers in human specimens has the potential to improve prediction of drug responses based on patient’s epigenetic profiles.
Metabolic models can provide a mechanistic framework
to analyze information-rich omics data sets, and are
increasingly being used to investigate metabolic alternations in human diseases.
An expression of the altered metabolic pathway utilization is the selection of metabolites consumed and released by cells. However, methods for the
inference of intracellular metabolic states from extracellular measurements in the context of metabolic models remain underdeveloped compared to methods for other omics data.
Herein, we describe a workflow for such an integrative analysis
emphasizing on extracellular metabolomics data.
We demonstrate,
using the lymphoblastic leukemia cell lines Molt-4 and CCRF-CEM,
how our methods can reveal differences in cell metabolism. Our models explain metabolite uptake and secretion by predicting
a more glycolytic phenotype for the CCRF-CEM model and
a more oxidative phenotype for the Molt-4 model,
which was supported by our experimental data.
Gene expression analysis revealed altered expression of gene products at
key regulatory steps in those central metabolic pathways, and
literature query emphasized the role of these genes in cancer metabolism.
Moreover, in silico gene knock-outs identified unique
control points for each cell line model, e.g., phosphoglycerate dehydrogenase for the Molt-4 model.
Thus, our workflow is well suited to the characterization of cellular metabolic traits based on
-extracellular metabolomic data, and it allows the integration of multiple omics data sets
into a cohesive picture based on a defined model context.
Modern high-throughput techniques have increased the pace of biological data generation. Also referred to as the ‘‘omics avalanche’’, this wealth of data provides great opportunities for metabolic discovery. Omics data sets
contain a snapshot of almost the entire repertoire of mRNA, protein, or metabolites at a given time point or
under a particular set of experimental conditions. Because of the high complexity of the data sets,
computational modeling is essential for their integrative analysis.
Currently, such data analysis is a bottleneck in the research process and methods are needed to facilitate the use of these data sets, e.g., through meta-analysis of data available in public databases [e.g., the human protein atlas (Uhlen et al. 2010) or the gene expression omnibus (Barrett et al. 2011)], and to increase the accessibility of valuable information for the biomedical research community.
Constraint-based modeling and analysis (COBRA) is
a computational approach that has been successfully used to
investigate and engineer microbial metabolism through the prediction of steady-states (Durot et al.2009).
The basis of COBRA is network reconstruction: networks are assembled in a bottom-up fashion based on
genomic data and extensive
organism-specific information from the literature.
Metabolic reconstructions capture information on the
known biochemical transformations taking place in a target organism
to generate a biochemical, genetic and genomic knowledge base (Reed et al. 2006).
Once assembled, a
metabolic reconstruction can be converted into a mathematical model (Thiele and Palsson 2010), and
model properties can be interrogated using a great variety of methods (Schellenberger et al. 2011).
The ability of COBRA models
to represent genotype–phenotype and environment–phenotype relationships arises
through the imposition of constraints, which
limit the system to a subset of possible network states (Lewis et al. 2012).
Currently, COBRA models exist for more than 100 organisms, including humans (Duarte et al. 2007; Thiele et al. 2013).
Since the first human metabolic reconstruction was described [Recon 1 (Duarte et al. 2007)],
biomedical applications of COBRA have increased (Bordbar and Palsson 2012).
One way to contextualize networks is to
define their system boundaries according to the metabolic states of the system, e.g., disease or dietary regimes.
The consequences of the applied constraints can
then be assessed for the entire network (Sahoo and Thiele 2013).
Additionally, omics data sets have frequently been used
to generate cell-type or condition-specific metabolic models.
Models exist for specific cell types, such as
enterocytes (Sahoo and Thiele2013),
macrophages (Bordbar et al. 2010),
adipocytes (Mardinoglu et al. 2013),
even multi-cell assemblies that represent the interactions of brain cells (Lewis et al. 2010).
All of these cell type specific models, except the enterocyte reconstruction
were generated based on omics data sets.
Cell-type-specific models have been used to study
diverse human disease conditions.
For example, an adipocyte model was generated using
transcriptomic, proteomic, and metabolomics data.
This model was subsequently used to investigate metabolic alternations in adipocytes
that would allow for the stratification of obese patients (Mardinoglu et al. 2013).
The biomedical applications of COBRA have been
cancer metabolism (Jerby and Ruppin, 2012).
predicting drug targets (Folger et al. 2011; Jerby et al. 2012).
A cancer model was generated using
multiple gene expression data sets and subsequently used
to predict synthetic lethal gene pairs as potential drug targets
selective for the cancer model, but non-toxic to the global model (Recon 1),
a consequence of the reduced redundancy in the cancer specific model (Folger et al. 2011).
In a follow up study, lethal synergy between FH and enzymes of the heme metabolic pathway
were experimentally validated and resolved the mechanism by which FH deficient cells,
e.g., in renal-cell cancer cells survive a non-functional TCA cycle (Frezza et al. 2011).
Contextualized models, which contain only the subset of reactions active in a particular tissue (or cell-) type,
can be generated in different ways (Becker and Palsson, 2008; Jerby et al. 2010).
However, the existing algorithms mainly consider
gene expression and proteomic data
to define the reaction sets that comprise the contextualized metabolic models.
These subset of reactions are usually defined
based on the expression or absence of expression of the genes or proteins (present and absent calls),
or inferred from expression values or differential gene expression.
Comprehensive reviews of the methods are available (Blazier and Papin, 2012; Hyduke et al. 2013). Only the compilation of a large set of omics data sets
can result in a tissue (or cell-type) specific metabolic model, whereas
the representation of one particular experimental condition is achieved
through the integration of omics data set generated from one experiment only (condition-specific cell line model).
Recently, metabolomic data sets have become more comprehensive and
using these data sets allow direct determination of the metabolic network components (the metabolites).
Additionally, metabolomics has proven to be stable, relatively inexpensive, and highly reproducible (Antonucci et al. 2012). These factors make metabolomic data sets particularly valuable for
interrogation of metabolic phenotypes.
Thus, the integration of these data sets is now an active field of research (Li et al. 2013; Mo et al. 2009; Paglia et al. 2012b; Schmidt et al. 2013).
Generally, metabolomic data can be incorporated into metabolic networks as
qualitative, quantitative, and thermodynamic constraints (Fleming et al. 2009; Mo et al. 2009).
Mo et al. used metabolites detected in the
spent medium of yeast cells to determine intracellular flux states through a sampling analysis (Mo et al. 2009),
which allowed unbiased interrogation of the possible network states (Schellenberger and Palsson 2009) and
prediction of internal pathway use.
Modes of transcriptional regulation during the YMC
Such analyses have also been used to reveal the effects of
enzymopathies on red blood cells (Price et al. 2004),
to study effects of diet on diabetes (Thiele et al. 2005) and
to define macrophage metabolic states (Bordbar et al. 2010).
This type of analysis is available as a function in the COBRA toolbox (Schellenberger et al. 2011).
In this study, we established a workflow
for the generation and analysis of condition-specific metabolic cell line models
that can facilitate the interpretation of metabolomic data.
metabolic differences between two lymphoblastic leukemia cell lines (Fig. 1A).
Fig. 1
metabol leukem cell lines11306_2014_721_Fig1_HTML
A Combined experimental and computational pipeline to study human metabolism.
Experimental work and omics data analysis steps precede computational modeling.
Model predictions are validated based on targeted experimental data.
Metabolomic and transcriptomic data are used for model refinement and submodel extraction.
Functional analysis methods are used to characterize the metabolism of the cell-line models and compare it to additional experimental data.
The validated models are subsequently used for the prediction of drug targets.
B Uptake and secretion pattern of model metabolites. All metabolite uptakes and secretions that were mapped during model generation are shown.
Metabolite uptakes are depicted on the left, and
secreted metabolites are shown on the right.
A number of metabolite exchanges mapped to the model were unique to one cell line.
Differences between cell lines were used to set quantitative constraints for the sampling analysis.
C Statistics about the cell line-specific network generation.
D Quantitative constraints.
For the sampling analysis, an additional set of constraints was imposed on the cell line specific models,
emphasizing the differences in metabolite uptake and secretion between cell lines.
Higher uptake of a metabolite was allowed
in the model of the cell line that consumed more of the metabolite in vitro, whereas
the supply was restricted for the model with lower in vitro uptake.
This was done by establishing the same ratio between the models bounds as detected in vitro.
X denotes the factor (slope ratio) that distinguishes the bounds, and
which was individual for each metabolite.
(a) The uptake of a metabolite could be x times higher in CCRF-CEM cells,
(b) the metabolite uptake could be x times higher in Molt-4,
(c) metabolite secretion could be x times higher in CCRF-CEM, or
(d) metabolite secretion could be x times higher in Molt-4 cells.LOD limit of detection.
The consequence of the adjustment was, in case of uptake, that one model was constrained to a lower metabolite uptake (A, B), and the difference depended on the ratio detected in vitro. In case of secretion, one model
had to secrete more of the metabolite, and again
the difference depended on the experimental difference detected between the cell lines
2 Results
We set up a pipeline that could be used to infer intracellular metabolic states
from semi-quantitative data regarding metabolites exchanged between cells and their environment.
Our pipeline combined the following four steps:
data acquisition,
data analysis,
metabolic modeling and
experimental validation of the model predictions (Fig. 1A).
We demonstrated the pipeline and the predictive potential to predict metabolic alternations in diseases such as cancer based on
^two lymphoblastic leukemia cell lines.
The resulting Molt-4 and CCRF-CEM condition-specific cell line models could explain
^ metabolite uptake and secretion ^ by predicting the distinct utilization of central metabolic pathways by the two cell lines. ^ the CCRF-CEM model resembled more a glycolytic, commonly referred to as ‘Warburg’ phenotype, ^ our model predicted a more respiratory phenotype for the Molt-4 model.
We found these predictions to be in agreement with measured gene expression differences
at key regulatory steps in the central metabolic pathways, and they were also
consistent with additional experimental data regarding the energy and redox states of the cells.
After a brief discussion of the data generation and analysis steps, the results derived from model generation and analysis will be described in detail.
2.1 Pipeline for generation of condition-specific metabolic cell line models
integration of exometabolomic (EM) data
2.1.1 Generation of experimental data
We monitored the growth and viability of lymphoblastic leukemia cell lines in serum-free medium (File S2, Fig. S1). Multiple omics data sets were derived from these cells.Extracellular metabolomics (exo-metabolomic) data,
integration of exometabolomic (EM) data
^ comprising measurements of the metabolites in the spent medium of the cell cultures (Paglia et al. 2012a), ^ were collected along with transcriptomic data, and these data sets were used to construct the models.
2.1.4 Condition-specific models for CCRF-CEM and Molt-4 cells
To determine whether we had obtained two distinct models, we evaluated the reactions, metabolites, and genes of the two models. Both the Molt-4 and CCRF-CEM models contained approximately half of the reactions and metabolites present in the global model (Fig. 1C). They were very similar to each other in terms of their reactions, metabolites, and genes (File S1, Table S5A–C).
(1) The Molt-4 model contained seven reactions that were not present in the CCRF-CEM model (Co-A biosynthesis pathway and exchange reactions).
(2) The CCRF-CEM contained 31 unique reactions (arginine and proline metabolism, vitamin B6 metabolism, fatty acid activation, transport, and exchange reactions).
(3) There were 2 and 15 unique metabolites in the Molt-4 and CCRF-CEM models, respectively (File S1, Table S5B).
(4) Approximately three quarters of the global model genes remained in the condition-specific cell line models (Fig. 1C).
(5) The Molt-4 model contained 15 unique genes, and the CCRF-CEM model had 4 unique genes (File S1, Table S5C).
(6) Both models lacked NADH dehydrogenase (complex I of the electron transport chain—ETC), which was determined by the absence of expression of a mandatory subunit (NDUFB3, Entrez gene ID 4709).
Rather, the ETC was fueled by FADH2 originating from succinate dehydrogenase and from fatty acid oxidation, which through flavoprotein electron transfer
FADH2
could contribute to the same ubiquinone pool as complex I and complex II (succinate dehydrogenase).
Despite their different in vitro growth rates (which differed by 11 %, see File S2, Fig. S1) and
^^^ differences in exo-metabolomic data (Fig. 1B) and transcriptomic data,
^^^ the internal networks were largely conserved in the two condition-specific cell line models.
2.1.5 Condition-specific cell line models predict distinct metabolic strategies
Despite the overall similarity of the metabolic models, differences in their cellular uptake and secretion patterns suggested distinct metabolic states in the two cell lines (Fig. 1B and see “Materials and methods” section for more detail). To interrogate the metabolic differences, we sampled the solution space of each model using an Artificial Centering Hit-and-Run (ACHR) sampler (Thiele et al. 2005). For this analysis, additional constraints were applied, emphasizing the quantitative differences in commonly uptaken and secreted metabolites. The maximum possible uptake and maximum possible secretion flux rates were reduced
^^^ according to the measured relative differences between the cell lines (Fig. 1D, see “Materials and methods” section).
We plotted the number of sample points containing a particular flux rate for each reaction. The resulting binned histograms can be understood as representing the probability that a particular reaction can have a certain flux value.
A comparison of the sample points obtained for the Molt-4 and CCRF-CEM models revealed
a considerable shift in the distributions, suggesting a higher utilization of glycolysis by the CCRF-CEM model
(File S2, Fig. S2).
This result was further supported by differences in medians calculated from sampling points (File S1, Table S6).
The shift persisted throughout all reactions of the pathway and was induced by the higher glucose uptake (34 %) from the extracellular medium in CCRF-CEM cells.
The sampling median for glucose uptake was 34 % higher in the CCRF-CEM model than in Molt-4 model (File S2, Fig. S2).
The usage of the TCA cycle was also distinct in the two condition-specific cell-line models (Fig. 2). Interestingly, the models used succinate dehydrogenase differently (Figs. 2, 3).
TCA_reactions
The Molt-4 model utilized an associated reaction to generate FADH2, whereas
in the CCRF-CEM model, the histogram was shifted in the opposite direction,
toward the generation of succinate.
Additionally, there was a higher efflux of citrate toward amino acid and lipid metabolism in the CCRF-CEM model (Fig. 2). There was higher flux through anaplerotic and cataplerotic reactions in the CCRF-CEM model than in the Molt-4 model (Fig. 2); these reactions include
(1) the efflux of citrate through ATP-citrate lyase,
(2) uptake of glutamine,
(3) generation of glutamate from glutamine,
(4) transamination of pyruvate and glutamate to alanine and to 2-oxoglutarate,
(5) secretion of nitrogen, and
(6) secretion of alanine.
energetics-of-cellular-respiration
The Molt-4 model showed higher utilization of oxidative phosphorylation (Fig. 3), again supported by elevated median flux through ATP synthase (36 %) and other enzymes, which contributed to higher oxidative metabolism. The sampling analysis therefore revealed different usage of central metabolic pathways by the condition-specific models.
Fig. 2
Differences in the use of the TCA cycle by the CCRF-CEM model (red) and the Molt-4 model (blue).
Differences in the use of the TCA cycle by the CCRF-CEM model (red) and the Molt-4 model (blue).
The table provides the median values of the sampling results. Negative values in histograms and in the table describe reversible reactions with flux in the reverse direction. There are multiple reversible reactions for the transformation of isocitrate and α-ketoglutarate, malate and fumarate, and succinyl-CoA and succinate. These reactions are unbounded, and therefore histograms are not shown. The details of participating cofactors have been removed.
Figure 3.
Molt-4 has higher median flux through ETC reactions II–IV 11306_2014_721_Fig3_HTML
Atp ATP, cit citrate, adp ADP, pi phosphate, oaa oxaloacetate, accoa acetyl-CoA, coa coenzyme-A, icit isocitrate, αkg α-ketoglutarate, succ-coa succinyl-CoA, succ succinate, fumfumarate, mal malate, oxa oxaloacetate,
pyr pyruvate, lac lactate, ala alanine, gln glutamine, ETC electron transport chain
Ingenuity network analysis showing up (red) and downregulation (green) of miRNAs involved in PC and their target genes
metabolic pathways 1476-4598-10-70-1
Metabolic Systems Research Team fig2
Metabolic control analysis of respiration in human cancer tissue. fphys-04-00151-g001
with contributions from JEDS Rosalis, Brazil
and Radislov Rosov, Univ of Virginia, VA, USA
A Brief Curation of Proteomics, Metabolomics, and Metabolism
This article is a continuation of a series of elaborations of the recent and
accelerated scientific discoveries that are enlarging the scope of and
integration of biological and medical knowledge leading to new drug
discoveries. The work that has led us to this point actually has roots
that go back 150 years. The roots go back to studies in the mid-nineteenth century, with the emergence of microbiology, physiology,
pathology, botany, chemistry and physics, and the laying down of a
mechanistic approach divergent from descriptive observation in the
twentieth century. Medicine took on the obligation to renew the method
of training physicians after the Flexner Report (The Flexner Report of
1910 transformed the nature and process of medical education in America
with a resulting elimination of proprietary schools), funded by the Carnegie
Foundation. Johns Hopkins University Medical School became the first to
adopt the model, as did Harvard, Yale, University of Chicago, and others.
The advances in biochemistry, genetics and genomics, were large, as was
structural organic chemistry in the remainder of the centrury. The advances
in applied mathematics and in instrumental analysis opened a new gateway
into the 21st century with the Human Genome Project, the Proteome Library,
Signaling Pathways, and the Metabolomes – human, microbial, and plants.
shall elaborate on how the key processes of life are being elucidated as
these interrelated disciplines converge. I shall not be covering in great
detail the contribution of the genetic code and transcripton because they
have been covered at great length in this series.
Part I. The foundation for the emergence of a revitalized molecular
biology and biochemistry.
In a series of discussions with Jose des Salles Roselino (Brazil) over a
period of months we have come to an important line of reasoning. DNA
to protein link goes from triplet sequence to amino acid sequence. The
realm of genetics. Further, protein conformation, activity and function
requires that environmental and microenvironmental factors should be
considered (Biochemistry). This has been opened in several articles
preceding this.
In the cAMP coupled hormonal response the transfer of conformation
from protein to protein is paramount. For instance, if your scheme goes
beyond cAMP, it will show an effect over a self-assembly (inhibitor
protein and protein kinase). Therefore, sequence alone does not
explain conformation, activity and function of regulatory proteins.
Recall that sequence is primar structure, determined by the translation
of the code, but secondary structure is determined by disulfide bonds.
There is another level of structure, tertiary structure, that is molded by
steric influences of near neighbors and by noncovalent attractions
and repulsions.
A few comments ( contributed by Assoc. Prof. JEDS Roselino) are in
order to stress the importance of self-assembly (Prigogine, R. A
Marcus, conformation energy) in a subject that is the best for this
connection. We have to stress again that in the cAMP
coupled hormonal response the transfer of conformation from
protein to protein is paramount. For instance, in case the
reaction sequence follows beyond the production of the
second messenger, as in the case of cAMP, this second
messenger will remove a self-assembly of inhibitor protein
with the enzyme protein kinase. Therefore, sequence alone
does not explain conformation, activity and function of
regulatory proteins. In this case, if this important mechanism
was not ignored, the work of Stanley Prusiner would most
certainly have been recognized earlier, and “rogue” proteins
would not have been seen as so rogue as some assumed.
For the general idea of importance of self-assembly versus
change in covalent modification of proteins (see R. A Kahn
and A. G Gilman (1984) J. Biol. Chem. 259(10), pp 6235-
6240. In this case, trimeric or dimeric G does not matter.
“Signaling transduction tutorial”.
G proteins in the G protein coupled-receptor proteins are
presented following a unidirectional series of arrows.
This is adequate to convey the idea of information being
transferred from outside the cell towards cell´s interior
(therefore, against the dogma that says all information
moves from DNA to RNA to protein. It is important to
consider the following: The entire process is driven by
a very delicate equilibrium between possible conform-
ational states of the proteins. Empty receptors have very
low affinity for G proteins. On the other hand, hormone
bound receptors have a change in conformation that
allows increasing the affinity for the G-trimer. When
hormone receptors bind to G-trimers two things happen:
Receptors transfer conformation information to
the G-triplex and
the G-triplex transfers information back to the
complex hormone-receptor.
In the first case , the dissociated G protein exchanges
GDP for GTP and has its affinity for the cyclase increased,
while by the same interaction receptor releases the
hormone which then places the first required step for the
signal. After this first interaction step, on the second and
final transduction system step is represented by an
opposite arrow. When, the G-protein + GTP complex
interacts with the cyclase two things happen:
It changes the cyclase to an active conformation starting the production of cAMP as the single
arrow of the scheme. However, the interaction
also causes a backward effect.
It activates the GTPase activity of this subunit
and the breakdown of GTP to GDP moves this subunit back to the initial trimeric inactive
state of G complex.
This was very well studied when the actions of cholera toxin
required better understanding. Cholera toxin changes the
GTPase subunit by ADP-ribosilation (a covalent and far more
stable change in proteins) producing a permanent conformation
of GTP bound G subunit. This keeps the cyclase in permanent
active conformation because ADP-ribosilation inhibits GTPase
activity required to put an end in the hormonal signal.
The study made while G-proteins were considered a dimer still
holds despite its limited vision of the real complexity of the
transduction system. It was also possible to get this very same
“freezing” in the active state using GTP stable analogues. This
transduction system is one of the best examples of the delicate
mechanisms of conformational interaction of proteins. Further-
more, this system also shows on the opposite side of our
reasoning scheme, how covalent changes are adequate for
more stable changes than those mediated by Van der Wall’s
forces between proteins. Yet, these delicate forces are the
same involved when Sc-Prion transfers its rogue
conformation to c-Prion proteins and other similar events. The Jacob-Monod Model
A combination of genetic and biochemical experiments in
bacteria led to the initial recognition of
protein-binding regulatory sequences associated with genes and
proteins whose binding to a gene’s regulatory sequences
either activate or repress its transcription.
These key components underlie the ability of both prokaryotic and
eukaryotic cells to turn genes on and off. The experimental findings lead to a general model of bacterial transcription control.
Gene control serves to allow a single cell to adjust to changes in its
nutritional environment so that its growth and division can be optimized.
Thus, the prime focus of research has been on genes that encode inducible proteins whose production varies depending on the nutritional
status of the cells. Its most characteristic and biologically far-reaching
purpose in eukaryotes, distinctive from single cell organisms is the
regulation of a genetic program that underlies embryological development and tissue differentiation.
The principles of transcription have already been described in this
series under the translation of the genetic code into amino acids
that are the building blocks for proteins.
E.coli can use either glucose or other sugars such as the disaccharide lactose as the sole source of carbon and energy.
When E. coli cells are grown in a glucose-containing medium,
the activity of the enzymes needed to metabolize lactose is
very low. When these cells are switched to a medium
containing lactose but no glucose, the activities of the lactose-metabolizing enzymes increase. Early studies showed that the
increase in the activity of these enzymes resulted from the
synthesis of new enzyme molecules, a phenomenon termed induction. The enzymes induced in the presence of lactose
are encoded by the lacoperon, which includes two genes, Z
and Y, that are required for metabolism of lactose and a third gene. The lac Y gene encodes lactose permease, which spans the E. coli cell membrane and uses the energy available from
the electrochemical gradient across the membrane to pump
lactose into the cell. The lac Z gene encodes β-galactosidase,
which splits the disaccharide lactose into the monosaccharides
glucose and galactose, which are further metabolized through
the action of enzymes encoded in other operons. The third
gene encodes thiogalactoside transacetylase.
Synthesis of all three enzymes encoded in the lacoperon is rapidly
induced when E. coli cells are placed in a medium containing lactose
as the only carbon source and repressed when the cells are switched
to a medium without lactose. Thus all three genes of the lac operon
are coordinately regulated. The lac operon in E. coli provides one
of the earliest and still best-understood examples of gene control.
Much of the pioneering research on the lac operon was conducted by
Francois Jacob, Jacques Monod, and their colleagues in the 1960s.
Some molecules similar in structure to lactose can induce expression
of the lac–operon genes even though they cannot be hydrolyzed by β-galactosidase. Such small molecules (i.e., smaller than proteins) are
called inducers. One of these, isopropyl-β-D-thiogalactoside,
abbreviated IPTG,is particularly useful in genetic studies of the lac
operon, because it can diffuse into cells and, it is not metabolized.
Insight into the mechanisms controlling synthesis of β-galactosidase
and lactose permease came from the study of mutants in which control
of β-galactosidase expression was abnormal and used a colorimetric
assay for β-galactosidase.
When the cells are exposed to chemical mutagens before plating on
X-gal/glucose plates, rare blue colonies appear, but when cells
from these blue colonies are recovered and grown in media containing
glucose, they overexpress all the genes of the lacoperon. These cells
are called constitutive mutants because they fail to repress the lac
operon in media lacking lactose and instead continuously express the
enzymes, and the genes were mapped to a region on the E. coli
chromosome. This led to the conclusion that these cells had a defect
in a protein that normally repressed expression of the lac operon in
the absence of lactose, and that it blocks transcription by binding to
a site on the E. coli genome where transcription of the lac operon is
initiated. In addition, it binds to the lac repressor in the lactose
medium and decreases its affinity for the repressor-binding site
on the DNA causing the repressor to unbind the DNA. Thereby,
transcription of the lac operon is initiated, leading to synthesis of
β-galactosidase, lactose permease, and thiogalactoside
transacetylase.
Jacob and Monod model of transcriptional regulation of the lac operon
Next, Jacob and Monod isolated mutants that expressed the lac operon
constitutively even when two copies of the wild-type lacI gene
encoding the lac repressor were present in the same cell, and the
constitutive mutations mapped to one end of the lac operon, as the
model predicted. Further, there are rare cells that carry a mutation
located at the region, promoter, that block initiation of transcription by
RNA polymerase.
lac I+ gene is trans-acting, & encodes a protein, which
binds to a lac operator
They further demonstrated that the two types of mutations lac I– and lac I+, were cis- and trans-acting, the latter encoding a protein that
binds to the lac operator. The cis-acting Oc mutations prevent
binding of the lac repressor to the operator, and mutations in the
lac promoter are cis-acting, since they alter the binding site for RNA
polymerase. In general, trans-acting genes that regulate expression
of genes on other DNA molecules encode diffusible products. In
most cases these are proteins, but in some cases RNA molecules
can act in trans to regulate gene expression.
According to the Jacob and Monod model of transcriptional control, transcription of the lacoperon, which encodes three inducible
proteins, is repressed by binding of lac repressor protein to the operator sequence.
In the presence of lactose or other inducer, this repression is
relieved and the lacoperon is transcribed.
Mutations in a promotersequence, which affect the affinity of RNA polymerase binding, can either decrease (down-mutation)
or increase (up-mutation) transcription.
(Section 10.1Bacterial Gene Control: The Jacob-Monod Model.) This book is accessible by the search feature.
Comment: This seminal work was done a half century ago. It was a
decade after the Watson-Crick model for DNA. The model is
elaborated for the Eukaryote in the examples that follow.
(The next two articles were called to my attention by R. Bosov at
University of Virginia).
An acetate switch regulates stress erythropoiesis
M Xu, JS Nagati, Ji Xie, J Li, H Walters, Young-Ah Moon, et al.
Nature Medicine 10 Aug 2014(20): 1018–1026. http://dx.doi.org:/10.1038/nm.3587
The hormone erythropoietin (EPO), synthesized in the kidney or liver
of adult mammals, controls erythrocyte production and is regulated by
the stress-responsive transcription factor hypoxia-inducible factor-2
(HIF-2).HIF–α acetylation and efficient HIF-2–dependent EPO
induction during hypoxia requires the lysine acetyltransferase CREB-binding protein (CBP) . These processes require acetate-dependent
acetyl CoA synthetase 2 (ACSS2) as follows.Acetate levels rise and ACSS2 is required for HIF-2α acetylation, CBP–HIF-2α complex
formation, CBP–HIF-2α recruitment to the EPO enhancer and induction
of EPO gene expression in human Hep3B hepatoma cells and in EPO-generating organs of hypoxic or acutely anemic mice. In acutely anemic
mice, acetate supplementation augments stress erythropoiesis in an ACSS2-dependent manner. Moreover, in acquired and inherited
chronic anemia mouse models, acetate supplementation increases
EPO expression and the resting hematocrit. Thus, a mammalian
stress-responsive acetate switch controls HIF-2 signaling and EPO
induction during pathophysiological states marked by tissue hypoxia.
Figure 1: Acss2 controls HIF-2 signaling in hypoxic cells.
Time course of endogenous HIF-2α acetylation during hypoxia following
immunoprecipitation (IP) of HIF-2α from whole-cell extracts and detection
of acetylated lysines by immunoblotting (IB). http://www.nature.com/nm/journal/v20/n9/carousel/nm.3587-F1.jpg
Figure 4: An acetate switch regulates Cbp–HIF-2 interactions in cells.
(a) HIF-2α acetylation following immunoprecipitation of endogenous
HIF-2α and detection by immunoblotting with antibodies to acetylated
lysine or HIF-2α. http://www.nature.com/nm/journal/v20/n9/carousel/nm.3587-F4.jpg
Figure 6: Acetate facilitates recovery from anemia.
Acetate facilitates recovery from anemia
(a) Serial hematocrits of CD1 wild-type female mice after PHZ treatment, followed
by once daily per os (p.o.) supplementation with water vehicle (Veh; n = 7 mice),
GTA (n = 6 mice), GTB (n = 8 mice) or GTP (n = 7 mice) (single measurem…
see also-.
1. Bunn, H.F. & Poyton, R.O. Oxygen sensing and molecular adaptation to
hypoxia. Physiol. Rev. 76, 839–885 (1996).
.Richalet, J.P. Oxygen sensors in the organism: examples of regulation
under altitude hypoxia in mammals. Comp. Biochem. Physiol. A Physiol.
118, 9–14 (1997).
.Koury, M.J. Erythropoietin: the story of hypoxia and a finely regulated
hematopoietic hormone. Exp. Hematol. 33, 1263–1270 (2005).
Wang, G.L., Jiang, B.H., Rue, E.A. & Semenza, G.L. Hypoxia-inducible
factor 1 is a basic-helix-loop-helix-PAS heterodimer regulated
by cellular O2 tension. Proc. Natl. Acad. Sci. USA92, 5510–5514 (1995).
Chen, R. et al. The acetylase/deacetylase couple CREB-binding
protein/sirtuin 1 controls hypoxia-inducible factor 2 signaling. J. Biol.
Chem. 287, 30800–30811 (2012).
.Papandreou, I., Cairns, R.A., Fontana, L., Lim, A.L. & Denko, N.C.
HIF-1 mediates adaptation to hypoxia by actively down-regulating
mitochondrial oxygen consumption. Cell Metab. 3,187–197 (2006).
14. Kim, J.W., Tchernyshyov, I., Semenza, G.L. & Dang, C.V. HIF-1-
mediated expression of pyruvate dehydrogenase kinase: a metabolic
switch required for cellular adaptation to hypoxia. Cell Metab. 3,
177–185 (2006).
16. Fujino, T., Kondo, J., Ishikawa, M., Morikawa, K. & Yamamoto, T.T.
Acetyl-CoA synthetase 2, a mitochondrial matrix enzyme involved in the
oxidation of acetate. J. Biol. Chem. 276,11420–11426 (2001).
17..Luong, A., Hannah, V.C., Brown, M.S. & Goldstein, J.L. Molecular
characterization of human acetyl-CoA synthetase, an enzyme regulated
by sterol regulatory element-binding proteins. J. Biol. Chem. 275,
26458–26466 (2000).
20 .Wellen, K.E. et al. ATP-citrate lyase links cellular metabolism to
histone acetylation. Science324, 1076–1080 (2009).
24. McBrian, M.A. et al. Histone acetylation regulates intracellular pH.
Mol. Cell 49, 310–321(2013).
Asymmetric mRNA localization contributes to fidelity and sensitivity
of spatially localized systems
Although many proteins are localized after translation, asymmetric
protein distribution is also achieved by translation after mRNA localization.
Why are certain mRNA transported to a distal location and translated
on-site? Here we undertake a systematic, genome-scale study of
asymmetrically distributed protein and mRNA in mammalian cells.
Our findings suggest that asymmetric protein distribution by mRNA
localization enhances interaction fidelity and signaling sensitivity.
Proteins synthesized at distal locations frequently contain intrinsically
disordered segments. These regions are generally rich in assembly-
promoting modules and are often regulated by post-translational
modifications. Such proteins are tightly regulated but display distinct
temporal dynamics upon stimulation with growth factors. Thus, proteins
synthesized on-site may rapidly alter proteome composition and
act as dynamically regulated scaffolds to promote the formation
of reversible cellular assemblies. Our observations are consistent
across multiple mammalian species, cell types and developmental stages,
suggesting that localized translation is a recurring feature of cell
signaling and regulation.
Figure 1: Classification and characterization of TAS and DSS proteins.
The two major mechanisms for localizing proteins to distal sites in the cell
(a)The two major mechanisms for localizing proteins to distal sites in the cell.
(b) Data sets used to identify groups of DSS and TAS transcripts, as well as
DSS and TAS proteins in mouse neuroblastoma cells
Figure 2: Structural analysis of DSS proteins reveals an enrichment
in disordered regions.
Distributions of the various structural properties of the DSS and TAS proteins of the mouse neuroblastoma data sets
(a,b) Distributions of the various structural properties of the DSS and TAS
proteins of the mouse neuroblastoma data sets (a), the mouse pseudopodia,
the rat embryonic sensory neuron data set and the adult sensory neuron data set (b).…
Figure 3: Analysis of DSS proteins reveals an enrichment for linear motifs, phase-
transition (i.e., higher-order assembly) promoting segments and PTM sites that act
as molecular switches.
Figure 4: Dynamic regulation of DSS transcripts and proteins.
Dynamic regulation of DSS transcripts and proteins
Genome-wide quantitative measurements of gene expression of DSS (n = 289)
and TAS (n = 1,292) proteins in mouse fibroblast cells. DSS transcripts and
proteins have a lower abundance and shorter half-lives
Figure 5: An overview of the potential advantages conferred by distal-site protein
synthesis, inferred from our analysis.
An overview of the potential advantages conferred by distal-site protein synthesis, inferred from our analysis
Turquoise and red filled circle represents off-target and correct interaction partners,
respectively. Wavy lines – a disordered region within a distal site synthesis protein.
The identification of asymmetrically localized proteins and transcripts.
The identification of asymmetrically localized proteins and transcripts
An illustrative explanation of the resolution of the study and the concept of asymmetric
localization of proteins and mRNA. In this example, on the left a neuron is divided into
its cell body and axon terminal, and transcriptome/proteo…
Graphs and boxplots of functional and structural properties for distal site synthesis
(DSS) proteins (red) and transport after synthesis (TAS) proteins (gray).
See Online Methods for details and legend of Figure 2 for a description of boxplots
and statistical tests. http://www.nature.com/nsmb/journal/v21/n9/carousel/nsmb.2876-SF2.jpg
See also –
1. Martin, K.C. & Ephrussi, A. mRNA localization: gene expression in the spatial
dimension. Cell136, 719–730 (2009).
Scott, J.D. & Pawson, T. Cell signaling in space and time: where proteins come
together and when they’re apart. Science 326, 1220–1224 (2009).
4..Holt, C.E. & Bullock, S.L. Subcellular mRNA localization in animal cells
and why it matters.Science 326, 1212–1216 (2009).
Jung, H., Gkogkas, C.G., Sonenberg, N. & Holt, C.E. Remote control of
gene function by local translation. Cell 157, 26–40 (2014).
The maintenance of oxygen homeostasis is critical for survival, and the
master regulator of this process in metazoan species is hypoxia-inducible
factor 1 (HIF-1), which
controls both O(2) delivery and utilization.
Under conditions of reduced O(2) availability,
HIF-1 activates the transcription of genes, whose protein products
mediate a switch from oxidative to glycolytic metabolism.
HIF-1 is activated in cancer cells as a result of intratumoral hypoxia
and/or genetic alterations.
In cancer cells, metabolism is reprogrammed to
favor glycolysis even under aerobic conditions.
Pyruvate kinase M2 (PKM2) has been implicated in cancer growth and
metabolism, although the mechanism by which it exerts these effects is
unclear. Recent studies indicate that
PKM2 interacts with HIF-1α physically and functionally to
stimulate the binding of HIF-1 at target genes,
the recruitment of coactivators,
histone acetylation, and
gene transcription.
Interaction with HIF-1α is facilitated by
hydroxylation of PKM2 at proline-403 and -408 by PHD3.
Knockdown of PHD3
decreases glucose transporter 1, lactate dehydrogenase A, and
pyruvate dehydrogenase kinase 1 expression;
decreases glucose uptake and lactate production; and
increases O(2) consumption.
The effect of PKM2/PHD3 is not limited to genes encoding metabolic
enzymes because VEGF is similarly regulated.
These results provide a mechanism by which PKM2
promotes metabolic reprogramming and
suggest that it plays a broader role in cancer progression than has
previously been appreciated. PMID: 21785006
Cadherins
Cadherins are thought to be the primary mediators of adhesion
between the cells of vertebrate animals, and also function in cell
adhesion in many invertebrates. The expression of numerous cadherins
during development is highly regulated, and the precise pattern of
cadherin expression plays a pivotal role in the morphogenesis of tissues
and organs. The cadherins are also important in the continued maintenance
of tissue structure and integrity. The loss of cadherin expression appears
to be highly correlated with the invasiveness of some types of tumors. Cadherin adhesion is also dependent on the presence of calcium ions
in the extracellular milieu.
The cadherin protein superfamily, defined as proteins containing a
cadherin-like domain, can be divided into several sub-groups. These include
the classical (type I) cadherins, which mediate adhesion at adherens junctions;
the highly-related type II cadherins;
the desmosomal cadherins found in desmosome junctions;
protocadherins, expressed only in the nervous system; and
ERK1/2-dependent phosphorylation and nuclear translocation of
PKM2 promotes the Warburg effect
W Yang, Y Zheng, Y Xia, Ha Ji, X Chen, F Guo, CA Lyssiotis, & Zhimin Lu
Nature Cell Biology 2012 (27 June 2014); 14: 1295–1304
Corrigendum (January, 2013) http://dx.doi.org:/10.1038/ncb2629
Pyruvate kinase M2 (PKM2) is upregulated in multiple cancer types and
contributes to the Warburg. We demonstrate that
EGFR-activated ERK2 binds directly to PKM2 Ile 429/Leu 431
through the ERK2 docking groove
and phosphorylates PKM2 at Ser 37, but
does not phosphorylate PKM1.
Phosphorylated PKM2 Ser 37
recruits PIN1 for cis–trans isomerization of PKM2, which
promotes PKM2 binding to importin α5
and PKM2 translocates to the nucleus.
Nuclear PKM2 acts as
a coactivator of β-catenin to
induce c-Myc expression,
This is followed by
the upregulation of GLUT1, LDHA and,
in a positive feedback loop,
PTB-dependent PKM2 expression.
Replacement of wild-type PKM2 with
a nuclear translocation-deficient mutant (S37A)
blocks the EGFR-promoted Warburg effect
and brain tumour development in mice.
In addition, levels of PKM2 Ser 37 phosphorylation
correlate with EGFR and ERK1/2 activity
in human glioblastoma specimens.
Our findings highlight the importance of
nuclear functions of PKM2 in the Warburg effect
and tumorigenesis.
TEPP-46 and DASA-58 isoform specificity in vitro and in cells.
TEPP-46 and DASA-58 isoform specificity in vitro and in cells.
(a) Structures of the PKM2 activators TEPP-46 and DASA-58. (b) Pyruvate kinase (PK) activity in purified recombinant human
PKM1 or PKM2 expressed in bacteria in the presence of increasing
concentrations of TEPP-46 or DASA-58. M1, PKM1;… http://www.nature.com/nchembio/journal/v8/n10/carousel/nchembio.1060-F2.jpg
Activators promote PKM2 tetramer formation and prevent
inhibition by phosphotyrosine signaling.
Activators promote PKM2 tetramer formation and prevent inhibition by phosphotyrosine signaling.
Figure 5: Metabolic effects of cell treatment with PKM2 activators.
(a) Effects of TEPP-46, DASA-58 (both used at 30 μM) or PKM1
expression on the doubling time of H1299 cells under normoxia
(21% O2) or hypoxia (1% O2). (b) Effects of DASA-58 on lactate
production from glucose. The P value shown was ca… http://www.nature.com/nchembio/journal/v8/n10/carousel/nchembio.1060-F5.jpg
EGFR has a tumour-promoting role in liver macrophages during
hepatocellular carcinoma formation
H Lanaya, A Natarajan, K Komposch, L Li, N Amberg, …, & Maria Sibilia
Nature Cell Biology 31 Aug 2014 http://dx.doi.org:/10.1038/ncb3031
Tumorigenesis has been linked with macrophage-mediated chronic
inflammation and diverse signaling pathways, including the epidermal
growth factor receptor (EGFR) pathway. EGFR is expressed in liver
macrophages in both human HCC and in a mouse HCC model. Mice lacking EGFR in macrophages show impaired hepatocarcinogenesis,
Mice lacking EGFR in hepatocytes develop HCC owing to increased
hepatocyte damage and compensatory proliferation. EGFR is required
in liver macrophages to transcriptionally induce interleukin-6 following
interleukin-1 stimulation, which triggers hepatocyte proliferation and HCC.
Importantly, the presence of EGFR-positive liver macrophages in HCC
patients is associated with poor survival. This study demonstrates a
tumour-promoting mechanism for EGFR in non-tumour cells,
which could lead to more effective precision medicine strategies.
Hypoxia-inducible factor 1 activation by aerobic glycolysis implicates
the Warburg effect in carcinogenesis.
Lu H1, Forbes RA, Verma A.
J Biol Chem. 2002 Jun 28;277(26):23111-5. Epub 2002 Apr 9
Cancer cells display high rates of aerobic glycolysis, a phenomenon
known historically as the Warburg effect. Lactate and pyruvate, the end
products of glycolysis, are highly produced by cancer cells even in the
presence of oxygen.
Hypoxia-induced gene expression in cancer cells
has been linked to malignant transformation.
Here we provide evidence that lactate and pyruvate
regulate hypoxia-inducible gene expression
independently of hypoxia
by stimulating the accumulation of hypoxia-inducible Factor 1alpha
(HIF-1alpha).
In human gliomas and other cancer cell lines,
the accumulation of HIF-1alpha protein under aerobic conditions
requires the metabolism of glucose to pyruvate that
prevents the aerobic degradation of HIF-1alpha protein,
activates HIF-1 DNA binding activity, and
enhances the expression of several HIF-1-activated genes
erythropoietin,
vascular endothelial growth factor,
glucose transporter 3, and
aldolase A.
Our findings support a novel role for pyruvate in metabolic signaling
and suggest a mechanism by which
high rates of aerobic glycolysis
can promote the malignant transformation and
survival of cancer cells.PMID: 11943784
Part IV. Transcription control and innate immunity
c-Myc-induced transcription factor AP4 is required for
host protection mediated by CD8+ T cells
C Chou, AK Pinto, JD Curtis, SP Persaud, M Cella, Chih-Chung Lin, … & T Egawa Nature Immunology 17 Jun 2014; http://dx.doi.org:/10.1038/ni.2943
The transcription factor c-Myc is essential for
the establishment of a metabolically active and proliferative state
in T cells after priming,
We identified AP4 as the transcription factor
that was induced by c-Myc and
sustained activation of antigen-specific CD8+ T cells.
Despite normal priming,
AP4-deficient CD8+ T cells
failed to continue transcription of a broad range of
c-Myc-dependent targets.
Mice lacking AP4 specifically in CD8+ T cells showed
enhanced susceptibility to infection with West Nile virus.
AP4 is regulated post-transcriptionally in CD8+ T cells.
Microarray analysis of transcription factor–encoding genes with a difference
in expression of >1.8-fold in activated CD8+ T cells treated for 12 h with
IL-2 (100 U/ml; + IL-2) relative to their expression in activated CD8+ T cells… http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F1.jpg
2. AP4 is required for the population expansion of antigen specific
CD8+ T cells following infection with LCMV-Arm.
Expression of CD4, CD8α and KLRG1 (a) and binding of an
H-2Db–gp(33–41) tetramer and expression of CD8α, KLRG1 and
CD62L (b) in splenocytes from wild-type (WT) and Tfap4−/− mice,
assessed by flow cytometry 8 d after infection http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F2.jpg
AP4 is essential for the sustained expression of genes that are targets of c-Myc.
Normalized signal intensity (NSI) of endogenous transcripts in
Tfap4+/+ and Tfap4−/− OT-I donor T cells adoptively transferred into
host mice and assessed on day 4 after infection of the host with LM-OVA
(top), and that of ERCC controls http://www.nature.com/ni/journal/vaop/ncurrent/carousel/ni.2943-F6.jpg
The presence of immune memory at pathogen-entry sites is a prerequisite
for protection. We show that the non-classical major histocompatibility
complex (MHC) class I molecule
thymus leukemia antigen (TL),
induced on dendritic cells interacting with CD8αα on activated CD8αβ+ T cells,
mediated affinity-based selection of memory precursor cells.
Furthermore, constitutive expression of TL on epithelial cells
led to continued selection of mature CD8αβ+ memory T cells.
The memory process driven by TL and CD8αα
was essential for the generation of CD8αβ+ memory T cells in the intestine and
the accumulation of highly antigen-sensitive CD8αβ+ memory T cells
that form the first line of defense at the largest entry port for pathogens.
The metabolic checkpoint kinase mTOR is essential for IL-15 signaling during the development and activation of NK cells.
Marçais A, Cherfils-Vicini J, Viant C, Degouve S, Viel S, Fenis A, Rabilloud J,
Mayol K, Tavares A, Bienvenu J, Gangloff YG, Gilson E, Vivier E,Walzer T.
Nat Immunol. 2014 Aug; 15(8):749-757. Epub 2014 Jun 29 http://dx.doi.org:/10.1038/ni.2936 . PMID: 24973821
Interleukin 15 (IL-15) controls
both the homeostasis and the peripheral activation of natural killer (NK) cells.
We found that the metabolic checkpoint kinase
mTOR was activated and boosted bioenergetic metabolism
after exposure of NK cells to high concentrations of IL-15,
whereas low doses of IL-15 triggered
only phosphorylation of the transcription factor STAT5.
mTOR
stimulated the growth and nutrient uptake of NK cells and
positively fed back on the receptor for IL-15.
This process was essential for
sustaining NK cell proliferation during development and
the acquisition of cytolytic potential during inflammation
or viral infection.
The mTORC1 inhibitor rapamycin
inhibited NK cell cytotoxicity both in mice and humans;
this probably contributes to the immunosuppressive
activity of this drug in different clinical settings.
Natural killer (NK) cells were so named for their uniqueness in killing
certain tumor and virus-infected cells without prior sensitization.
Their functions are modulated in vivo by several soluble immune mediators;
interleukin-15 (IL-15) being the most potent among them in
enabling NK cell homeostasis, maturation, and activation.
During microbial infections,
NK cells stimulated with IL-15 display enhanced cytokine responses.
This priming effect has previously been shown with respect to increased
IFN-γ production in NK cells
upon IL-12 and IL-15/IL-2 co-stimulation.
we explored if this effect of IL-15 priming
can be extended to various other cytokines and
observed enhanced NK cell responses to stimulation
with IL-4, IL-21, IFN-α, and IL-2 in addition to IL-12.
we also observed elevated IFN-γ production in primed NK cells
Currently, the fundamental processes required for priming and
whether these signaling pathways work collaboratively or
independently
for NK cell functions are poorly understood.
We examined IL-15 effects on NK cells in which
the pathways emanating from IL-15 receptor activation
were blocked with specific inhibitors
To identify the key signaling events for NK cell priming,
Our results demonstrate that
the PI3K-AKT-mTOR pathway is critical for cytokine responses
in IL-15 primed NK cells.
This pathway is also implicated in a broad range of
IL-15-induced NK cell effector functions such as
proliferation and cytotoxicity.
Likewise, NK cells from mice
treated with rapamycin to block the mTOR pathway
displayed defects in proliferation, and IFN-γ and granzyme B productions
resulting in elevated viral burdens upon murine cytomegalovirus infection.
Taken together, our data demonstrate
the requirement of PI3K-mTOR pathway
for enhanced NK cell functions by IL-15, thereby
coupling the metabolic sensor mTOR to NK cell anti-viral responses.
Researchers at the Univ. of Michigan have described a new approach to
discovering potential cancer treatments that
requires a fraction of the time needed for more traditional methods.
They used the platform to identify
a novel antibody that is undergoing further investigation as a potential
treatment for breast, ovarian and other cancers.
In research published online in the Proceedings of the National Academy
of Sciences, researchers in the laboratory of Stephen Weiss at the U-M Life
Sciences Institute detail an approach
that replicates the native environment of cancer cells and
increases the likelihood that drugs effective against the growth of
tumor cells in test tube models
will also stop cancer from growing in humans.
The researchers have used their method
to identify an antibody that stops breast cancer tumor growth in animal models, and
they are investigating the antibody as a potential treatment in humans.
“Discovering new targets for cancer therapeutics is a long and tedious undertaking, and
identifying and developing a potential drug to specifically hit that
target without harming healthy cells is a daunting task,” Weiss said.
“Our approach allows us to identify potential therapeutics
in a fraction of the time that traditional methods require.”
The researchers began by
creating a 3-D “matrix” of collagen, a connective tissue molecule very similar to that found
surrounding breast cancer cells in human patients.
They then embedded breast cancer cells into the collagen matrix,
where the cells grew as they would in human tissue.
The investigators then injected the cancer-collagen tissue composites into mice that then
recognize the human cancer cells as foreign tissue.
Much in the way that our immune system generates antibodies
to fight infection,
the mice began to generate thousands of antibodies directed against
the human cancer cells.
These antibodies were then tested for the ability to stop the growth
of the human tumor cells.
“We create an environment in which cells cultured in the laboratory ‘think’
they are growing in the body and then
rapidly screen large numbers of antibodies to see if any exert
anti-cancer effects,” Weiss said.
“This allows us to select promising antibodies very quickly and then
They discovered a particular antibody, 4C3, which was able to
almost completely stop the proliferation of the breast cancer cells.
They then identified the molecule on the cancer cells that the antibody targets.
The antibody can be further engineered to generate
humanized monoclonal antibodies for use in patients
“We still need to do a lot more work to determine how effective 4C3 might be as a
treatment for breast and other cancers, on its own or in conjunction with other
therapies,” Weiss said. “But we have enough data to warrant further pursuit,
and are expanding our efforts to use this discovery platform to find similarly promising antibodies.”
Larry,
I think you have made a great effort in order to connect basic ideas of metabolic regulation with those of gene expression control “modern” mechanisms.
Yet, I do not think that at this stage it will be clear for all readers. At least, for the great majority of the readers. The most important factor I my opinion, is derived from the fact that modern readers considers that metabolic regulation deals with so called “housekeeping activities” of the cell. Something that is of secondary, tertiary or even less level of relevance.
My idea, that you have mentioned in the text when you write at the beginning, the word biochemistry, in order to resume it, derives from the reading of What is life together with Prof. Leloir . For me and also, for him, biochemistry comprises a set of techniques and also a framework of reasoning about scientific results. As a set of techniques, Schrodinger has considered that it will lead to better understanding of genetics and of physiology as a two legs structure supporting the future progress related to his time (mid-forties). For Leloir, the key was the understanding of chemical reactivity and I agree with him. However, as I was able to talk and discuss it with him in detail, we should also take into account levels of stabilities of macromolecules and above all, regulation of activities and function (this is where) Pasteur effect that I was studying in Leloir´s lab at that time, 1970-72, gets into the general picture.
Regulation for complex living beings , that also have cancer cell as a great topic of research problem can be understood through the understanding of two quite different results when opposition with lack of regulation is taken into account or experimentally elicited. The most clearly line of experiments can follow the Pasteur Effect as the intracellular result best seen when aerobiosis is compared with anaerobiosis as conditions in which maintenance of ATP levels and required metabolic regulation (Energy charge D.E, Atkinson etc) is studied. Another line of experiments is one that takes into account the extracellular result or for instance the homeostatic regulation of blood glucose levels. The blood glucose level is the most conspicuous and related to Pasteur Effect regulatory event that can be studied in the liver taking into account both final results tested or compared regarding its regulation, ATP levels maintenance (intracellular) and blood glucose maintenance (extracellular).
My key idea is to consider that the same factors that elicits fast regulatory responses also elicits the slow energetic expensive regulatory responses. The biologic logic behind this common root is the ATP economy. In case, the regulatory stimulus fades out quickly the fast regulatory responses are good enough to maintain life and the time requiring, energetic costly responses will soon be stopped cutting short the ATP expenditure. In case, the stimulus last for long periods of time the fast responses are replaced by adaptive responses that in general will follow the line of cell differentiation mechanisms with changes in gene expression etc.
The change from fast response mechanisms to long lasting developmentally linked ones is not sharp. Therefore, somehow, cancer cells becomes trapped into a metastable regulatory mechanism that prevents cell differentiation and reinforces those mechanisms linked to its internal regulatory goals. This metastable mechanism takes advantage from the fact that other cells, tissues and organs will take good care of homeostatic mechanisms that provide for their nutritional needs. In the case of my Hepatology work you will see a Piruvate kinase that does not responds to homeostatic signals .
This portion of the discussion is a series of articles on signaling and signaling pathways. Many of the protein-protein interactions or protein-membrane interactions and associated regulatory features have been referred to previously, but the focus of the discussion or points made were different. I considered placing this after the discussion of proteins and how they play out their essential role, but this is quite a suitable place for a progression to what follows. This is introduced by material taken from Wikipedia, which will be followed by a series of mechanisms and examples from the current literature, which give insight into the developments in cell metabolism, with the later goal of separating views introduced by molecular biology and genomics from functional cellular dynamics that are not dependent on the classic view. The work is vast, and this discussion does not attempt to cover it in great depth. It is the first in a series.
Signaling and signaling pathways
Signaling transduction tutorial.
Carbohydrate metabolism
Lipid metabolism
Protein synthesis and degradation
Subcellular structure
Impairments in pathological states: endocrine disorders; stress hypermetabolism; cancer.
Signal transduction occurs when an extracellular signaling[1] molecule activates a specific receptor located on the cell surface or inside the cell. In turn, this receptor triggers a biochemical chain of events inside the cell, creating a response.[2] Depending on the cell, the response alters the cell’s metabolism, shape, gene expression, or ability to divide.[3] The signal can be amplified at any step. Thus, one signaling molecule can cause many responses.[4]
In 1970, Martin Rodbell examined the effects of glucagon on a rat’s liver cell membrane receptor. He noted that guanosine triphosphate disassociated glucagon from this receptor and stimulated the G-protein, which strongly influenced the cell’s metabolism. Thus, he deduced that the G-protein is a transducer that accepts glucagon molecules and affects the cell.[5] For this, he shared the 1994 Nobel Prize in Physiology or Medicine with Alfred G. Gilman.
Signal_transduction_publications_graph
The earliest MEDLINE entry for “signal transduction” dates from 1972.[6] Some early articles used the terms signal transmission and sensory transduction.[7][8] In 2007, a total of 48,377 scientific papers—including 11,211 e review papers—were published on the subject. The term first appeared in a paper’s title in 1979.[9][10] Widespread use of the term has been traced to a 1980 review article by Rodbell:[5][11] Research papers focusing on signal transduction first appeared in large numbers in the late 1980s and early 1990s.[12]
Notch-mediated juxtacrine signal between adjacent cells.
Signal transduction involves the binding of extracellular signaling molecules and ligands to cell-surface receptors that trigger events inside the cell. The combination of messenger with receptor causes a change in the conformation of the receptor, known as receptor activation. This activation is always the initial step (the cause) leading to the cell’s ultimate responses (effect) to the messenger. Despite the myriad of these ultimate responses, they are all directly due to changes in particular cell proteins. Intracellular signaling cascades can be started through cell-substratum interactions; examples are the integrin that binds ligands in the extracellular matrix and steroids.[13] Most steroid hormones have receptors within the cytoplasm and act by stimulating the binding of their receptors to the promoter region of steroid-responsive genes.[14] Examples of signaling molecules include the hormone melatonin,[15] the neurotransmitter acetylcholine[16] and the cytokineinterferon γ.[17]
Signal transduction cascades amplify the signal output
Various environmental stimuli exist that initiate signal transmission processes in multicellular organisms; examples include photons hitting cells in the retina of the eye,[20] and odorants binding to odorant receptors in the nasal epithelium.[21] Certain microbial molecules, such as viral nucleotides and protein antigens, can elicit an immune system response against invading pathogens mediated by signal transduction processes. This may occur independent of signal transduction stimulation by other molecules, as is the case for the toll-like receptor. It may occur with help from stimulatory molecules located at the cell surface of other cells, as with T-cell receptor signaling. Unicellular organisms may respond to environmental stimuli through the activation of signal transduction pathways. For example, slime molds secrete cyclic adenosine monophosphate upon starvation, stimulating individual cells in the immediate environment to aggregate,[22] and yeast cells use mating factors to determine the mating types of other cells and to participate in sexual reproduction.[23] Receptors can be roughly divided into two major classes: intracellular receptors and extracellular receptors.
Extracellular
Extracellular receptors are integral transmembrane proteins and make up most receptors. They span the plasma membrane of the cell, with one part of the receptor on the outside of the cell and the other on the inside. Signal transduction occurs as a result of a ligand binding to the outside; the molecule does not pass through the membrane. This binding stimulates a series of events inside the cell; different types of receptor stimulate different responses and receptors typically respond to only the binding of a specific ligand. Upon binding, the ligand induces a change in the conformation of the inside part of the receptor.[24] These result in either the activation of an enzyme in the receptor or the exposure of a binding site for other intracellular signaling proteins within the cell, eventually propagating the signal through the cytoplasm.
In eukaryotic cells, most intracellular proteins activated by a ligand/receptor interaction possess an enzymatic activity; examples include tyrosine kinase and phosphatases. Some of them create second messengers such as cyclic AMP and IP3, the latter controlling the release of intracellular calcium stores into the cytoplasm. Other activated proteins interact with adaptor proteins that facilitate signalling protein interactions and coordination of signalling complexes necessary to respond to a particular stimulus. Enzymes and adaptor proteins are both responsive to various second messenger molecules.
Many adaptor proteins and enzymes activated as part of signal transduction possess specialized protein domains that bind to specific secondary messenger molecules. For example, calcium ions bind to the EF hand domains of calmodulin, allowing it to bind and activate calmodulin-dependent kinase. PIP3 and other phosphoinositides do the same thing to the Pleckstrin homology domains of proteins such as the kinase protein AKT.
G protein-coupled
G protein-coupled receptors (GPCRs) are a family of integral transmembrane proteins that possess seven transmembrane domains and are linked to a heterotrimeric G protein. Many receptors are in this family, including adrenergic receptors and chemokine receptors.
Arrestin binding to active GPCR kinase (GRK)-phosphorylated GPCRs blocks G protein coupling
Signal transduction by a GPCR begins with an inactive G protein coupled to the receptor; it exists as a heterotrimer consisting of Gα, Gβ, and Gγ.[25] Once the GPCR recognizes a ligand, the conformation of the receptor changes to activate the G protein, causing Gα to bind a molecule of GTP and dissociate from the other two G-protein subunits. The dissociation exposes sites on the subunits that can interact with other molecules.[26] The activated G protein subunits detach from the receptor and initiate signaling from many downstream effector proteins such as phospholipases and ion channels, the latter permitting the release of second messenger molecules.[27] The total strength of signal amplification by a GPCR is determined by the lifetimes of the ligand-receptor complex and receptor-effector protein complex and the deactivation time of the activated receptor and effectors through intrinsic enzymatic activity.
A study was conducted where a point mutation was inserted into the gene encoding the chemokine receptor CXCR2; mutated cells underwent a malignant transformation due to the expression of CXCR2 in an active conformation despite the absence of chemokine-binding. This meant that chemokine receptors can contribute to cancer development.[28]
Tyrosine and histidine kinase
Receptor tyrosine kinases (RTKs) are transmembrane proteins with an intracellular kinase domain and an extracellular domain that binds ligands; examples include growth factor receptors such as the insulin receptor.[29] To perform signal transduction, RTKs need to form dimers in the plasma membrane;[30] the dimer is stabilized by ligands binding to the receptor. The interaction between the cytoplasmic domains stimulates the autophosphorylation of tyrosines within the domains of the RTKs, causing conformational changes. Subsequent to this, the receptors’ kinase domains are activated, initiating phosphorylation signaling cascades of downstream cytoplasmic molecules that facilitate various cellular processes such as cell differentiation and metabolism.[29]
As is the case with GPCRs, proteins that bind GTP play a major role in signal transduction from the activated RTK into the cell. In this case, the G proteins are members of the Ras, Rho, and Raf families, referred to collectively as small G proteins. They act as molecular switches usually tethered to membranes by isoprenyl groups linked to their carboxyl ends. Upon activation, they assign proteins to specific membrane subdomains where they participate in signaling. Activated RTKs in turn activate small G proteins that activate guanine nucleotide exchange factors such as SOS1. Once activated, these exchange factors can activate more small G proteins, thus amplifying the receptor’s initial signal. The mutation of certain RTK genes, as with that of GPCRs, can result in the expression of receptors that exist in a constitutively activate state; such mutated genes may act as oncogenes.[31]
Histidine-specific protein kinases are structurally distinct from other protein kinases and are found in prokaryotes, fungi, and plants as part of a two-component signal transduction mechanism: a phosphate group from ATP is first added to a histidine residue within the kinase, then transferred to an aspartate residue on a receiver domain on a different protein or the kinase itself, thus activating the aspartate residue.[32]
Integrin
integrin-mediated signal transduction
An overview of integrin-mediated signal transduction, adapted from Hehlgens et al. (2007).[33]
Integrins are produced by a wide variety of cells; they play a role in cell attachment to other cells and the extracellular matrix and in the transduction of signals from extracellular matrix components such as fibronectin and collagen. Ligand binding to the extracellular domain of integrins changes the protein’s conformation, clustering it at the cell membrane to initiate signal transduction. Integrins lack kinase activity; hence, integrin-mediated signal transduction is achieved through a variety of intracellular protein kinases and adaptor molecules, the main coordinator being integrin-linked kinase.[33] As shown in the picture to the right, cooperative integrin-RTK signalling determines the timing of cellular survival, apoptosis, proliferation, and differentiation.
Important differences exist between integrin-signalling in circulating blood cells and non-circulating cells such as epithelial cells; integrins of circulating cells are normally inactive. For example, cell membrane integrins on circulating leukocytes are maintained in an inactive state to avoid epithelial cell attachment; they are activated only in response to stimuli such as those received at the site of an inflammatory response. In a similar manner, integrins at the cell membrane of circulating platelets are normally kept inactive to avoid thrombosis. Epithelial cells (which are non-circulating) normally have active integrins at their cell membrane, helping maintain their stable adhesion to underlying stromal cells that provide signals to maintain normal functioning.[34]
Toll gate
When activated, toll-like receptors (TLRs) take adapter molecules within the cytoplasm of cells in order to propagate a signal. Four adaptor molecules are known to be involved in signaling, which are Myd88, TIRAP, TRIF, and TRAM.[35][36][37] These adapters activate other intracellular molecules such as IRAK1, IRAK4, TBK1[disambiguation needed], and IKKi that amplify the signal, eventually leading to the induction or suppression of genes that cause certain responses. Thousands of genes are activated by TLR signaling, implying that this method constitutes an important gateway for gene modulation.
Ligand-gated ion channel
A ligand-gated ion channel, upon binding with a ligand, changes conformation to open a channel in the cell membrane through which ions relaying signals can pass. An example of this mechanism is found in the receiving cell of a neural synapse. The influx of ions that occurs in response to the opening of these channels induces action potentials, such as those that travel along nerves, by depolarizing the membrane of post-synaptic cells, resulting in the opening of voltage-gated ion channels.
An example of an ion allowed into the cell during a ligand-gated ion channel opening is Ca2+; it acts as a second messenger initiating signal transduction cascades and altering the physiology of the responding cell. This results in amplification of the synapse response between synaptic cells by remodelling the dendritic spines involved in the synapse.
Ion transporters and channels in mammalian choroidal epithelium
Intracellular
Extracellular receptors are integral transmembrane proteins and make up most receptors. They span the plasma membrane of the cell, with one part of the receptor on the outside of the cell and the other on the inside. Signal transduction occurs as a result of a ligand binding to the outside; the molecule does not pass through the membrane. This binding stimulates a series of events inside the cell; different types of receptor stimulate different responses and receptors typically respond to only the binding of a specific ligand. Upon binding, the ligand induces a change in the conformation of the inside part of the receptor.[24] These result in either the activation of an enzyme in the receptor or the exposure of a binding site for other intracellular signaling proteins within the cell, eventually propagating the signal through the cytoplasm.
Understanding these receptors and identifying their ligands and the resulting signal transduction pathways represent a major conceptual advance
intercellular signaling
conformational-rearrangements
membrane protein receptor binds with hormone
The multiple protein-dependent steps in signal transduction
In eukaryotic cells, most intracellular proteins activated by a ligand/receptor interaction possess an enzymatic activity; examples include tyrosine kinase and phosphatases. Some of them create second messengers such as cyclic AMP and IP3, the latter controlling the release of intracellular calcium stores into the cytoplasm. Other activated proteins interact with adaptor proteins that facilitate signalling protein interactions and coordination of signalling complexes necessary to respond to a particular stimulus. Enzymes and adaptor proteins are both responsive to various second messenger molecules.
Ca++ exchange
Many adaptor proteins and enzymes activated as part of signal transduction possess specialized protein domains that bind to specific secondary messenger molecules. For example, calcium ions bind to the EF hand domains of calmodulin, allowing it to bind and activate calmodulin-dependent kinase. PIP3 and other phosphoinositides do the same thing to the Pleckstrin homology domains of proteins such as the kinase protein AKT.
G protein-coupled
G protein-coupled receptors (GPCRs) are a family of integral transmembrane proteins that possess seven transmembrane domains and are linked to a heterotrimeric G protein. Many receptors are in this family, including adrenergic receptors and chemokine receptors.
membrane_receptor_g protein
intracellular_receptor_steroid
Signal transduction by a GPCR begins with an inactive G protein coupled to the receptor; it exists as a heterotrimer consisting of Gα, Gβ, and Gγ.[25] Once the GPCR recognizes a ligand, the conformation of the receptor changes to activate the G protein, causing Gα to bind a molecule of GTP and dissociate from the other two G-protein subunits. The dissociation exposes sites on the subunits that can interact with other molecules.[26] The activated G protein subunits detach from the receptor and initiate signaling from many downstream effector proteins such as phospholipases and ion channels, the latter permitting the release of second messenger molecules.[27] The total strength of signal amplification by a GPCR is determined by the lifetimes of the ligand-receptor complex and receptor-effector protein complex and the deactivation time of the activated receptor and effectors through intrinsic enzymatic activity.
A study was conducted where a point mutation was inserted into the gene encoding the chemokine receptor CXCR2; mutated cells underwent a malignant transformation due to the expression of CXCR2 in an active conformation despite the absence of chemokine-binding. This meant that chemokine receptors can contribute to cancer development.[28]
Tyrosine and histidine kinase
Receptor tyrosine kinases (RTKs) are transmembrane proteins with an intracellular kinase domain and an extracellular domain that binds ligands; examples include growth factor receptors such as the insulin receptor.[29] To perform signal transduction, RTKs need to form dimers in the plasma membrane;[30] the dimer is stabilized by ligands binding to the receptor. The interaction between the cytoplasmic domains stimulates the autophosphorylation of tyrosines within the domains of the RTKs, causing conformational changes. Subsequent to this, the receptors’ kinase domains are activated, initiating phosphorylation signaling cascades of downstream cytoplasmic molecules that facilitate various cellular processes such as cell differentiation and metabolism.[29]
As is the case with GPCRs, proteins that bind GTP play a major role in signal transduction from the activated RTK into the cell. In this case, the G proteins are members of the Ras, Rho, and Raf families, referred to collectively as small G proteins. They act as molecular switches usually tethered to membranes by isoprenyl groups linked to their carboxyl ends. Upon activation, they assign proteins to specific membrane subdomains where they participate in signaling. Activated RTKs in turn activate small G proteins that activate guanine nucleotide exchange factors such as SOS1. Once activated, these exchange factors can activate more small G proteins, thus amplifying the receptor’s initial signal. The mutation of certain RTK genes, as with that of GPCRs, can result in the expression of receptors that exist in a constitutively activate state; such mutated genes may act as oncogenes.[31]
Histidine-specific protein kinases are structurally distinct from other protein kinases and are found in prokaryotes, fungi, and plants as part of a two-component signal transduction mechanism: a phosphate group from ATP is first added to a histidine residue within the kinase, then transferred to an aspartate residue on a receiver domain on a different protein or the kinase itself, thus activating the aspartate residue.[32]
Integrin
integrin-mediated signal transduction
An overview of integrin-mediated signal transduction, adapted from Hehlgens et al. (2007).[33]
Integrins are produced by a wide variety of cells; they play a role in cell attachment to other cells and the extracellular matrix and in the transduction of signals from extracellular matrix components such as fibronectin and collagen. Ligand binding to the extracellular domain of integrins changes the protein’s conformation, clustering it at the cell membrane to initiate signal transduction. Integrins lack kinase activity; hence, integrin-mediated signal transduction is achieved through a variety of intracellular protein kinases and adaptor molecules, the main coordinator being integrin-linked kinase.[33] As shown in the picture to the right, cooperative integrin-RTK signalling determines the timing of cellular survival, apoptosis, proliferation, and differentiation.
Platelet signaling pathways
Protein ubiquitylation
ubiquitylation-is-a-multistep-reaction.
Important differences exist between integrin-signaling in circulating blood cells and non-circulating cells such as epithelial cells; integrins of circulating cells are normally inactive. For example, cell membrane integrins on circulating leukocytes are maintained in an inactive state to avoid epithelial cell attachment; they are activated only in response to stimuli such as those received at the site of an inflammatory response. In a similar manner, integrins at the cell membrane of circulating platelets are normally kept inactive to avoid thrombosis. Epithelial cells (which are non-circulating) normally have active integrins at their cell membrane, helping maintain their stable adhesion to underlying stromal cells that provide signals to maintain normal functioning.[34]
Toll gate
When activated, toll-like receptors (TLRs) take adapter molecules within the cytoplasm of cells in order to propagate a signal. Four adaptor molecules are known to be involved in signaling, which are Myd88, TIRAP, TRIF, and TRAM.[35][36][37] These adapters activate other intracellular molecules such as IRAK1, IRAK4, TBK1[disambiguation needed], and IKKi that amplify the signal, eventually leading to the induction or suppression of genes that cause certain responses. Thousands of genes are activated by TLR signaling, implying that this method constitutes an important gateway for gene modulation.
SignalTrans
Ligand-gated ion channel
A ligand-gated ion channel, upon binding with a ligand, changes conformation to open a channel in the cell membrane through which ions relaying signals can pass. An example of this mechanism is found in the receiving cell of a neural synapse. The influx of ions that occurs in response to the opening of these channels induces action potentials, such as those that travel along nerves, by depolarizing the membrane of post-synaptic cells, resulting in the opening of voltage-gated ion channels.
An example of an ion allowed into the cell during a ligand-gated ion channel opening is Ca2+; it acts as a second messenger initiating signal transduction cascades and altering the physiology of the responding cell. This results in amplification of the synapse response between synaptic cells by remodelling the dendritic spines involved in the synapse.
Ion transporters and channels in mammalian choroidal epithelium
Intracellular
Intracellular receptors, such as nuclear receptors and cytoplasmic receptors, are soluble proteins localized within their respective areas. The typical ligands for nuclear receptors are lipophilic hormones like the steroid hormones testosterone and progesterone and derivatives of vitamins A and D. To initiate signal transduction, the ligand must pass through the plasma membrane by passive diffusion. On binding with the receptor, the ligands pass through the nuclear membrane into the nucleus, enabling gene transcription and protein production.
Signal Transduction
Activated nuclear receptors attach to the DNA at receptor-specific hormone-responsive element (HRE) sequences, located in the promoter region of the genes activated by the hormone-receptor complex. Due to their enabling gene transcription, they are alternatively called inductors of gene expression. All hormones that act by regulation of gene expression have two consequences in their mechanism of action; their effects are produced after a characteristically long period of time and their effects persist for another long period of time, even after their concentration has been reduced to zero, due to a relatively slow turnover of most enzymes and proteins that would either deactivate or terminate ligand binding onto the receptor.
Signal transduction via these receptors involves little proteins, but the details of gene regulation by this method are not well-understood. Nucleic receptors have DNA-binding domains containing zinc fingers and a ligand-binding domain; the zinc fingers stabilize DNA binding by holding its phosphate backbone. DNA sequences that match the receptor are usually hexameric repeats of any kind; the sequences are similar but their orientation and distance differentiate them. The ligand-binding domain is additionally responsible for dimerization of nucleic receptors prior to binding and providing structures for transactivation used for communication with the translational apparatus.
signal-transduction-in-protease-signaling-
protein changes in biological mechanisms
Steroid receptors are a subclass of nuclear receptors located primarily within the cytosol; in the absence of steroids, they cling together in an aporeceptor complex containing chaperone or heatshock proteins (HSPs). The HSPs are necessary to activate the receptor by assisting the protein to fold in a way such that the signal sequence enabling its passage into the nucleus is accessible. Steroid receptors, on the other hand, may be repressive on gene expression when their transactivation domain is hidden; activity can be enhanced by phosphorylation of serine residues at their N-terminal as a result of another signal transduction pathway, a process called crosstalk.
Structure of the N-terminal domain of the yeast Hsp90 chaperone
Pincer movement of Hsp90 coupled to the ATPase cycle. NTD = N-terminal domain, MD = middle domain, CTD = C-terminal domain.
Retinoic acid receptors are another subset of nuclear receptors. They can be activated by an endocrine-synthesized ligand that entered the cell by diffusion, a ligand synthesised from a precursor like retinol brought to the cell through the bloodstream or a completely intracellularly synthesised ligand like prostaglandin. These receptors are located in the nucleus and are not accompanied by HSPs; they repress their gene by binding to their specific DNA sequence when no ligand binds to them, and vice versa.
Certain intracellular receptors of the immune system are cytoplasmic receptors; recently identified NOD-like receptors (NLRs) reside in the cytoplasm of some eukaryotic cells and interact with ligands using a leucine-rich repeat (LRR) motif similar to TLRs. Some of these molecules like NOD2 interact with RIP2 kinase that activates NF-κB signaling, whereas others like NALP3 interact with inflammatory caspases and initiate processing of particular cytokines like interleukin-1β.[38][39]
Cell signaling
signaling pathjways map
Cell signalling is part of a complex system of communication that governs basic cellular activities and coordinates cell actions. The ability of cells to perceive and correctly respond to their microenvironment is the basis of development, tissue repair, and immunity as well as normal tissue homeostasis. Errors in cellular information processing are responsible for diseases such as cancer, autoimmunity, and diabetes. By understanding cell signalling, diseases may be treated effectively and, theoretically, artificial tissues may be created.
Traditional work in biology has focused on studying individual parts of cell signaling pathways. Systems biology research helps us to understand the underlying structure of cell signaling networks and how changes in these networks may affect the transmission and flow of information. Such networks are complex systems in their organization and may exhibit a number of emergent properties. Long-range allostery is often a significant component of cell signaling events.[1]
Enzyme_Model allosterism
Classification
Signaling within, between, and among cells is subdivided into the following classifications:
Intracrine signals are produced by the target cell that stay within the target cell.
Autocrine signals are produced by the target cell, are secreted, and effect the target cell itself via receptors. Sometimes autocrine cells can target cells close by if they are the same type of cell as the emitting cell. An example of this are immune cells.
Juxtacrine signals target adjacent (touching) cells. These signals are transmitted along cell membranes via protein or lipid components integral to the membrane and are capable of affecting either the emitting cell or cells immediately adjacent.
Paracrine signals target cells in the vicinity of the emitting cell. Neurotransmitters represent an example.
Endocrine signals target distant cells. Endocrine cells produce hormones that travel through the blood to reach all parts of the body.
Notch-mediated juxtacrine signal between adjacent cells.
Notch-mediated juxtacrine signal between adjacent cells.
Some cell–cell communication requires direct cell–cell contact. Some cells can form gap junctions that connect their cytoplasm to the cytoplasm of adjacent cells. In cardiac muscle, gap junctions between adjacent cells allows for action potential propagation from the cardiac pacemaker region of the heart to spread and coordinately cause contraction of the heart.
The notch signaling mechanism is an example of juxtacrine signaling (also known as contact-dependent signaling) in which two adjacent cells must make physical contact in order to communicate. This requirement for direct contact allows for very precise control of cell differentiation during embryonic development. In the worm Caenorhabditis elegans, two cells of the developing gonad each have an equal chance of terminally differentiating or becoming a uterine precursor cell that continues to divide. The choice of which cell continues to divide is controlled by competition of cell surface signals. One cell will happen to produce more of a cell surface protein that activates the Notch receptor on the adjacent cell. This activates a feedback loop or system that reduces Notch expression in the cell that will differentiate and that increases Notch on the surface of the cell that continues as a stem cell.[5]
Many cell signals are carried by molecules that are released by one cell and move to make contact with another cell. Endocrine signals are called hormones. Hormones are produced by endocrine cells and they travel through the blood to reach all parts of the body. Specificity of signaling can be controlled if only some cells can respond to a particular hormone. Paracrine signals such as retinoic acid target only cells in the vicinity of the emitting cell.[6]Neurotransmitters represent another example of a paracrine signal. Some signaling molecules can function as both a hormone and a neurotransmitter. For example, epinephrine and norepinephrine can function as hormones when released from the adrenal gland and are transported to the heart by way of the blood stream. Norepinephrine can also be produced by neurons to function as a neurotransmitter within the brain.[7]Estrogen can be released by the ovary and function as a hormone or act locally via paracrine or autocrine signaling.[8] Active species of oxygen and nitric oxide can also act as cellular messengers. This process is dubbed redox signaling.
Signaling Pathways
Cell Signaling Biology
Michael J. Berridge
Module 2
Cell Signaling Pathways
The nine membrane-bound adenylyl cyclases (AC1–AC9) have a similar domain structure. The single polypeptide has a tandem repeat of six transmembrane domains (TM) with TM1- -TM6 in one repeat and TM7- -TM12 in the other. Each TM cassette is followed by large cytoplasmic domains (C1 and C2), which contain the catalytic regions that convert ATP into cyclic AMP. As shown in the lower panel, the C1 and C2 domains come together to form a heterodimer. The ATP-binding site is located at the interface between these two domains. The soluble AC10 isoform lacks the transmembrane regions, but it retains the C1 and C2 domains that are responsible for catalysis www.cellsignallingbiology.orghttp://www.biochemj.org/csb/002/csb002.pdf
Resources:
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DiscoveRx® offers a comprehensive collection of cell-based pathway indicator assays designed to detect activation or inhibition of complex signal transduction pathways in response to compound treatment. Based on the proven PathHunter® technology, These biosensor cell lines allow you to measure distinct events within a variety of pathways involved in compound toxicity, cholesterol metabolism, antioxidant function, DNA damage and ER stress. – See more at: http://www.discoverx.com/targets/signaling-pathways#sthash.ZTb5UXVO.dpuf
inhibitors of signal transduction pathway
Inhibitors of MAPK Signaling Pathway
jak-stat
Nrf2 signaling in ARE-mediated coordinated activation of defensive genes
Larry,
I think you have made a great effort in order to connect basic ideas of metabolic regulation with those of gene expression control “modern” mechanisms.
Yet, I do not think that at this stage it will be clear for all readers. At least, for the great majority of the readers. The most important factor I my opinion, is derived from the fact that modern readers considers that metabolic regulation deals with so called “housekeeping activities” of the cell. Something that is of secondary, tertiary or even less level of relevance.
My idea, that you have mentioned in the text when you write at the beginning, the word biochemistry, in order to resume it, derives from the reading of What is life together with Prof. Leloir . For me and also, for him, biochemistry comprises a set of techniques and also a framework of reasoning about scientific results. As a set of techniques, Schrodinger has considered that it will lead to better understanding of genetics and of physiology as a two legs structure supporting the future progress related to his time (mid-forties). For Leloir, the key was the understanding of chemical reactivity and I agree with him. However, as I was able to talk and discuss it with him in detail, we should also take into account levels of stabilities of macromolecules and above all, regulation of activities and function (this is where) Pasteur effect that I was studying in Leloir´s lab at that time, 1970-72, gets into the general picture.
Regulation for complex living beings , that also have cancer cell as a great topic of research problem can be understood through the understanding of two quite different results when opposition with lack of regulation is taken into account or experimentally elicited. The most clearly line of experiments can follow the Pasteur Effect as the intracellular result best seen when aerobiosis is compared with anaerobiosis as conditions in which maintenance of ATP levels and required metabolic regulation (Energy charge D.E, Atkinson etc) is studied. Another line of experiments is one that takes into account the extracellular result or for instance the homeostatic regulation of blood glucose levels. The blood glucose level is the most conspicuous and related to Pasteur Effect regulatory event that can be studied in the liver taking into account both final results tested or compared regarding its regulation, ATP levels maintenance (intracellular) and blood glucose maintenance (extracellular).
My key idea is to consider that the same factors that elicits fast regulatory responses also elicits the slow energetic expensive regulatory responses. The biologic logic behind this common root is the ATP economy. In case, the regulatory stimulus fades out quickly the fast regulatory responses are good enough to maintain life and the time requiring, energetic costly responses will soon be stopped cutting short the ATP expenditure. In case, the stimulus last for long periods of time the fast responses are replaced by adaptive responses that in general will follow the line of cell differentiation mechanisms with changes in gene expression etc.
The change from fast response mechanisms to long lasting developmentally linked ones is not sharp. Therefore, somehow, cancer cells becomes trapped into a metastable regulatory mechanism that prevents cell differentiation and reinforces those mechanisms linked to its internal regulatory goals. This metastable mechanism takes advantage from the fact that other cells, tissues and organs will take good care of homeostatic mechanisms that provide for their nutritional needs. In the case of my Hepatology work you will see a Piruvate kinase that does not responds to homeostatic signals .