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Posts Tagged ‘Autophagy’


Targeted Liposome Based Delivery System to Present HLA Class I Antigens to Tumor Cells: Two papers

Reporter: Stephen J. Williams, Ph.D.

 

Abstract

Cell-mediated immunotherapies have potential as stand-alone and adjuvant therapies for cancer. However, most current protocols suffer from one or more of three major issues: cost, safety, or efficacy. Here we present a nanoparticle delivery system that facilitates presentation of an immunogenic measles antigen specifically in cancer cells. The delivery system does not contain viral particles, toxins, or biologically derived material. Treatment with this system facilitates activation of a secondary immune response against cancer cells, bypassing the need to identify tumor-associated antigens or educate the immune system through a primary immune response. The delivery system consists of a stealth liposome displaying a cancer-specific targeting peptide, named H1299.3, on its exterior surface and encapsulating H250, an immunogenic human leukocyte antigen class 1 restricted peptide. This targeted-nanoparticle facilitates presentation of the H250 peptide in major histocompatibility complex class I molecules. Activation is dependent on the targeting peptide, previous antigen exposure, and utilizes a novel autophagy-mediated mechanism to facilitate presentation. Treatment with this liposome results in a significant reduction of tumor growth using an aggressive LLC1 model in vaccinated C57BL/6 mice. These data provide proof-of-principle for a novel cell-mediated immunotherapy that is scalable, contains no biologically derived material, and is an efficacious cancer therapy.

Introduction

Cell-mediated (CM) immunotherapies for cancer treatment are designed to activate the body’s adaptive immune responses against a malignant growth.1,2 Generally, the goal of a CM response is to activate a cytotoxic T-cell response against a tumor to eliminate cancer cells. The principle of these treatments is straightforward, yet current work studying the complexity of the tumor micro-environment2,3 as well as methods that attempt to directly activate T cells against tumor antigens4,5,6 demonstrate the difficulty associated generating an immune response against a tumor.

Several CM cancer immunotherapies exist today. Major examples include PD-1 inhibitors, injection of live virus or viral particles into tumors, and adoptive T-cell therapies.1,6,7,8 However, concerns regarding efficacy, safety, and/or cost have limited the use of many of these treatments. To address these concerns, we sought to develop a novel treatment based on developing a fully synthetic, minimal delivery system that facilitates presentation of human leukocyte antigen (HLA) class I restricted immunogenic peptides specifically on cancer cells without using live virus, viral subunits, or biologically derived material.

Based on these requirements, we developed a liposomal based agent consisting of a neutral, stealth liposome that encapsulates a synthetically manufactured immunogenic HLA class I restricted peptide derived from measles virus.1,2,9 In addition, the liposome has a targeting peptide on the external surface that both specifically accumulates in cancer cells and facilitates presentation of the immunogenic peptide in HLA class I molecules (Figure 1a). Thus, this treatment is designed to generate a secondary CM immune response specifically against the tumor if the patient was previously vaccinated against or infected with measles.

Figure 1

The minimal antigen delivery system consists of three components. (a) PEGylated stealth liposomes are loaded with an immunogenic human leukocyte antigen (HLA) class 1 restricted peptide derived from measles virus, named H250. The surface of the liposome

In this proof-of-concept study, we synthesized a liposome that encapsulates H250,1 an immunogenic HLA class 1 restricted peptide identified from measles hemagglutinin protein. The liposome is designed to specifically internalize in cancer cells by displaying the recently identified targeting peptide H1299.3 on the exterior surface (Figure 1b).10 H1299.3 is a 20mer, cancer-specific targeting peptide that was recently identified by our group. The peptide was identified using a novel phage display technique that allows for selection of cancer-specific targeting peptides that preferentially internalize in cancer cells via a defined mechanism of endocytosis. This peptide was dimerized on a lysine core and is fully functional outside the context of the phage particle. The H1299.3 peptide accumulates specifically in a panel of non-small cell lung cancer (NSCLC) cell lines compared to a normal bronchial epithelial cell control cell line via a clathrin-dependent mechanism of endocytosis. In this study, we demonstrate that H1299.3 facilitates functional presentation of an immunogenic antigen in both major histocompatibility complex (MHC) and HLA class I molecules as indicated by CD8+-specific interferon (IFN)γ secretion. In addition, H1299.3 facilitated presentation utilizes an autophagy-dependent mechanism. Finally, treatment with H1299.3 targeted liposomes containing H250 substantially reduces the growth rate of subcutaneous LLC1 tumors implanted in vaccinated C57BL/6 mice compared to treatment with vehicle control.

Result summarized:

  1. The H1299.3 targeting ligand specifically accumulates in cancer and facilitates HLA class I presentation: H250 is an immunogenic peptide identified from sequencing peptides present in HLA A*0201 molecules following measles infection. identified two donors that were HLA A*02 positive and had previously been vaccinated against measles virus (the human NSCLC cell line, H1993, which we determined to be HLA A*02 positive)
  2. identified three different cancer-specific targeting peptides that internalize into H1993 that have been previously published: H1299.2, H2009.1, and H1299.3. Each of these peptides specifically internalize in NSCLC cell lines compared to normal bronchial epithelial cells
  3. H1299.3 facilitated HLA class I presentation requires autophagy. H1299.3 peptide colocalizes with Lamp-1 which is a marker of both lysosomes and autolysosomes, therefore it was possible autophagy involved and shown that H1299.3 colocalizes with autophagosomes.  Chlorpromazine, which inhibits clathrin coated mediatated endocytosis, decreased the HLA1 presentation of H250.
  4. H1299.3-targeted liposomes encapsulating H250 reduce tumor burden in vivo. Mice were first vaccinated against H250.  The J1299.3 targeted liposome encapsulation H250 reduced tumor growth of LLC1 s.c. xenograpfts  by 50%.
J Transl Med. 2011 Mar 31;9:34. doi: 10.1186/1479-5876-9-34.

Enhanced presentation of MHC class Ia, Ib and class II-restricted peptides encapsulated in biodegradable nanoparticles: a promising strategy for tumor immunotherapy.

Abstract

BACKGROUND:

Many peptide-based cancer vaccines have been tested in clinical trials with a limited success, mostly due to difficulties associated with peptide stability and delivery, resulting in inefficient antigen presentation. Therefore, the development of suitable and efficient vaccine carrier systems remains a major challenge.

METHODS:

To address this issue, we have engineered polylactic-co-glycolic acid (PLGA) nanoparticles incorporating: (i) two MHC class I-restricted clinically-relevant peptides, (ii) a MHC class II-binding peptide, and (iii) a non-classical MHC class I-binding peptide. We formulated the nanoparticles utilizing a double emulsion-solvent evaporation technique and characterized their surface morphology, size, zeta potential and peptide content. We also loaded human and murine dendritic cells (DC) with the peptide-containing nanoparticles and determined their ability to present the encapsulated peptide antigens and to induce tumor-specific cytotoxic T lymphocytes (CTL) in vitro.

RESULTS:

We confirmed that the nanoparticles are not toxic to either mouse or human dendritic cells, and do not have any effect on the DC maturation. We also demonstrated a significantly enhanced presentation of the encapsulated peptides upon internalization of the nanoparticles by DC, and confirmed that the improved peptide presentation is actually associated with more efficient generation of peptide-specific CTL and T helper cell responses.

CONCLUSION:

Encapsulating antigens in PLGA nanoparticles offers unique advantages such as higher efficiency of antigen loading, prolonged presentation of the antigens, prevention of peptide degradation, specific targeting of antigens to antigen presenting cells, improved shelf life of the antigens, and easy scale up for pharmaceutical production. Therefore, these findings are highly significant to the development of synthetic vaccines, and the induction of CTL for adoptive immunotherapy.

[PubMed – indexed for MEDLINE]

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microglia and brain maintenance

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Mapping mosaicism: Tracing subtle mutations in our brains

Posted on January 14, 2015 by Nancy Fliesler

Posted in All PostsInformation technology

More On: brain developmentDNA sequencinggeneticsmosaicismneurosciencesomatic mutations

DNA sequences were once thought to be the same in every cell, but the story is now known to be more complicated than that. The brain is a case in point: Mutations can arise at different times in brain development and affect only a percentage of neurons, forming a mosaic pattern.

Now, thanks to new technology described last week in Neuron, these subtle “somatic” brain mutations can be mapped spatially across the brain and even have their ancestry traced.

Like my family, who lived in Eastern Europe, migrated to lower Manhattan and branched off to Boston, California and elsewhere, brain mutations can be followed from the original mutant cells as they divide and migrate to their various brain destinations, carrying their altered DNA with them.

“Some mutations may occur on one side of the brain and not the other,” says Christopher Walsh, MD, PhD, chief of Genetics and Genomics at Boston Children’s Hospital and co-senior author on the paper. “Some may be ‘clumped,’ affecting just one gyrus [fold] of the brain, disrupting just a little part of the cortex at a time.”

This tracking capability represents a significant advance for genetics research. And for neuroscientists, it provides a new way to study both the normal brain and brain disorders like epilepsy, autism and intellectual disability.

Walsh and colleagues studied normal brain tissue from a teenage boy who had passed away from other causes. Sampling in more than 30 brain locations, they used deep, highly sensitive, whole-genome sequencing of one neuron at a time—unlike usual methods, which sequence thousands or millions of cells mixed together and simply read out an average.

http://vectorblog.org/wp-content/uploads/2015/01/Walsh-figure3B-v2-1024×735.jpg

The blue and green boxes indicate different degrees of mosaicism (based on proportion of cells affected) in the left half of this teen’s normal brain. The blue shaded area indicates that retrotransposon mutation #1 (blue boxes) is limited to a focal area in the middle frontal gyrus. The empty boxes indicate areas where mutation #1 was not detected. (Courtesy Gilad Evrony, PhD, Boston Children’s Hospital)

Next, using technology developed by Alice (Eunjung) Lee in the lab of Peter Park, PhD, at Harvard Medical School’s Center for Biomedical Informatics, they zeroed in on inserted bits of DNA caused by retrotransposons, one type of mutation that can arise as the brain develops. These essentially served as markers that allowed cell lineages to be traced.

“Our findings are intriguing because they suggest that every normal brain may in fact be a mosaic patchwork of focal somatic mutations, though in normal individuals most are likely silent or harmless,” says Gilad Evrony, PhD, in the Walsh Lab.

http://vectorblog.org/wp-content/uploads/2015/01/Walsh-figure5-1024×509.jpg

This model illustrates the origins of two somatic retrotransposon mutations during prenatal development and their subsequent dissemination in the brain. Insertion #2 (in green) occurred soon after conception; #1 (in blue) happened sometime later during brain development. The ‘pie slices’ show a closeup of the layers of the cerebral cortex. Later in development, additional somatic mutations occurred inside insertions #1 and #2, creating new, smaller sublineages of cells. (Courtesy Gilad Evrony, PhD)

A parallel study from Walsh’s lab in 2014 used single-neuron sequencing to find copy number variants— a different type of mutation affecting the number of copies of chromosomes or chromosome fragments. It, too, found the mutations to be present in normal brains as well as neurologically diseased brains.

Walsh and others speculate that some somatic brain mutations might play a role in autism, epilepsy, schizophrenia and other unsolved neuropsychiatric diseases whose causes are mostly still a mystery.

“It is possible that a whole new class of brain disorders may exist that has not been previously recognized,” says Evrony. “In such disorders, a somatic mutation may subtly affect only one small part of the brain involved in a specific ability, for example language, while sparing the rest of the brain.”

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Tracking subtle brain mutations, systematicallyTool can trace and spatially map “mosaic” mutations in the brain

http://www.prnewswire.com/news-releases/tracking-subtle-brain-mutations-systematically-300017369.html

BOSTON, Jan. 7, 2015 /PRNewswire-USNewswire/ — DNA sequences were once thought to be identical from cell to cell, but it’s increasingly understood that mutations can arise during brain development that affect only certain groups of brain cells. A technique developed at Boston Children’s Hospital allows these subtle mutation patterns to be traced and mapped spatially for the first time. This capability is a significant advance for genetics research and provides a new way to study both the normal brain and brain disorders such as epilepsy and autism.

Described in the January 7th issue of Neuron, the technique uses “deep,” highly sensitive whole-genome sequencing of single neurons and a new technology that identifies inserted bits of DNA caused by retrotransposons, one of several kinds of so-called somatic mutations that can arise as the brain develops.

The technique picks up somatic mutations that affect just a fraction of the brain’s cells, in a “mosaic” pattern. It also allows “lineage tracing,” showing when during brain development the mutations arise and how they spread through brain tissue as the mutated cells grow, replicate and migrate, carrying the mutation with them.

“There is a lot of genetic diversity from one neuron to the other, and this work gets at how somatic mutations are distributed in the brain,” says Christopher Walsh, MD, PhD, chief of Genetics and Genomics at Boston Children’s and co-senior author on the paper. “Some mutations may occur on one side of the brain and not the other. Some may be ‘clumped,’ affecting just one gyrus [fold] of the brain, disrupting just a little part of the cortex at a time.”

The study examined brain tissue from a deceased 17-year-old who had been neurologically normal, sampling in more than 30 brain locations. It builds on work published by the Walsh lab in 2012, which developed methods to sequence the genomes of single neurons, and represents the first time single neurons have been sequenced in their entirety. The single-cell technique is better at detecting subtle mosaicism than usual DNA sequencing methods, which sequence many thousands or millions of cells mixed together and read out an average for the sample.

Somatic brain mutations, affecting just pockets of cells, can be harmful, and have been suggested as a possible cause of neurodevelopmental disorders such as autism, epilepsy or intellectual disability (see this review article for further background). But they also can be completely benign or have just a subtle effect.

“Our findings are intriguing because they suggest that every normal brain may in fact be a mosaic patchwork of focal somatic mutations, though in normal individuals most are likely silent or harmless,” says Gilad Evrony, PhD, in the Walsh Lab, co-first author on the Neuron paper. “These same technologies can now be used to study the brains of people who died from unexplained neuropsychiatric diseases to determine whether somatic mutations may be the cause.”

Finally, says Evrony, the findings provide a proof-of-principle for a systematic way of studying how brain cells disperse and migrate during development, “something that has not been possible to do before in humans,” he says.

Co-first author Alice Eunjung Lee, PhD, from the lab of Peter Park, PhD, at the Center for Biomedical Informatics at Harvard Medical School, developed the study’s retrotransposon analysis tool, which detects somatic retrotransposon mutations in single-cell sequencing data.

Mirroring these findings, study published by Walsh’s lab in 2014 used single-neuron sequencing to detect copy number variants—another type of mutation affecting the number of copies of chromosomes or chromosome fragments. The study found that these mutations can occur in both normal and neurologically diseased brains.

Evrony and Lee are first authors on the Neuron paper; Walsh and Park are senior authors. The research was supported by the National Institutes of Health (MSTP grant T32GM007753), the National Institute of Neurological Disorders and Stroke (R01 NS079277 and R01 NS032457), the Louis Lange III Scholarship in Translational Research, the Eleanor and Miles Shore Fellowship, the Research Connection and the Manton Center for Orphan Disease Research at Boston Children’s Hospital, the Paul G. Allen Family Foundation and the Howard Hughes Medical Institute.

SOURCE Boston Children’s Hospital

 

Beth Stevens: A transformative thinker in neuroscience

Posted on September 29, 2015 by Nancy Fliesler

Posted in All PostsDrug discoveryProfiles

 

More On: Alzheimer’s diseaseautismFM Kirby Neurobiology Centerglial cellsneurosciencesynapse development

http://vector.childrenshospital.org/2015/09/beth-stevens-a-transformative-thinker-in-neuroscience/

https://youtu.be/6DOYTpXkLOY

When 2015 MacArthur “genius” grant winner Beth Stevens, PhD, began studying the role of glia in the brain in the 1990s, these cells—“glue” from the Greek—weren’t given much thought. Traditionally, glia were thought to merely protect and support neurons, the brain’s real players.

But Stevens, from the Department of Neurology and the F.M. Kirby Neurobiology Center at Boston Children’s Hospital, has made the case that glia are key actors in the brain, not just caretakers. Her work—at the interface between the nervous and immune systems—is helping transform how neurologic disorders like autism, amyotrophic lateral sclerosis (ALS), Alzheimer’s disease and schizophrenia are viewed.

Soon after college graduation in 1993, without prior experience in neuroscience, she helped discoveran interplay between neurons and glial cells known as Schwann cells that controlled production of the nerve insulation known as myelin It was one of the early pieces of evidence that glia and neurons talk to each other.

In 2007, while still a postdoctoral fellow, Stevens showed how star-shaped glial cells called astrocytes influence the development of synapses, or brain connections. Studying neurons, her lab showed that a gene called C1q was markedly more active when astrocytes were present. C1q is an immune gene, one nobody had expected to see in a normal brain. In the context of disease, it initiates the complement cascade, an immunologic pathway for tagging unwanted cells and debris for clearance by other immune cells.

But in healthy developing brains, Stevens showed, C1q was concentrated at developing synapses, or brain connections, apparently marking certain synapses for pruning.

Then in 2012, the Stevens lab showed that microglia—another type of glia usually thought of as immune cells themselves—actively sculpt the brain’s wiring. They literally trim away unwanted, inappropriate synapses by eating them—in the same way they’d engulf and destroy invading bacteria.

http://19g6dy4by8jx1b5cx74fh0f2.wpengine.netdna-cdn.com/wp-content/uploads/2012/06/Microglial-cell.jpg

That paper was cited by the journal Neuron as the year’s most influential paper.

The same year, she received a Presidential Early Career Award for Scientists and Engineers, honoring her innovative research and scientific leadership.

Stevens’s current investigations are looking at synapse loss—a hallmark of neurodegenerative conditions such as Alzheimer’s—and trying to understand why it occurs. Her lab’s recent work suggests that normal pruning mechanisms that are active during early brain development get re-activated later in life. Intervening with this activation could lead to a new treatment approach, she believes.

Stevens isn’t the only brain researcher at Boston Children’s to become a MacArthur fellow. Neurosurgeon Benjamin Warf, MD, received the honor in 2012.

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Immune cells “sculpt” brain circuits — by eating excess connections

Posted on June 5, 2012 by Nancy Fliesler

Posted in All PostsDrug discoveryPediatrics

More On: ALSAlzheimer’s diseaseautismbrain developmentepilepsyglaucomaHuntington’s diseaseLou Gehrig’s disease,Parkinson’s diseasesynapse development

https://youtu.be/wb8UAyf8Nhw

The above movie shows an immune cell caught in the act of tending the brain—it’s just eaten away unnecessary connections, or synapses, between neurons.

That’s not something these cells, known as microglia, were previously thought to do. As immune cells, it was thought that their job was to rid the body of unwanted pathogens and debris, by engulfing and digesting them.

The involvement of microglia in the brain’s development has started to be recognized only recently. The latest research finds that microglia tune into the brain’s cues, akin to the way they survey their environment for invading microbes, and get rid of excess synapses the same way they’d dispatch these invaders—by eating them.

It’s a whole other way of understanding how the healthy brain develops—at the hands of cells that were once thought to be merely nerve “glue” (the literal meaning of “glia” from the Greek), playing a protective role to neurons, say investigators Beth Stevens, PhD, and Dori Schafer, PhD, of the F.M. Kirby Neurobiology Center at Boston Children’s Hospital.

“In the field of neuroscience, glia have often been ignored,” says Stevens. “But glia aren’t the nerve glue, they’re actively communicating with neurons. People have gotten a new respect for glia and are hungry to know more about them.”

Such knowledge could eventually shed light on brain disorders ranging from autism to Alzheimer’s.

The “eat me” sign

We’re all born with more brain connections than we need. As we begin to encounter our world, they’re trimmed back to fine-tune our circuitry. It’s a bit of an oversimplification, but Stevens and Schafer demonstrated last week in the journal Neuron that when two neurons start talking to each other less – because their connection is no longer important to our lives– the microglia notice that and prune the synapse away.

To study microglia’s pruning activity, Stevens and Schafer used a time-honored model: the visual system. When you cover one eye soon after birth, you force the brain to rewire: Brain connections with the covered eye weaken and those synapses eventually get eliminated.

Using this model, Stevens and Schafer showed that microglia take their cues from a set of signals also used by the immune system, known as the complement cascade. Specifically, microglia carry receptors that recognize the complement protein C3—the same protein found on synapses that are destined for elimination.

“We think that weaker synapses are being tagged with C3, and that microglia are eliminating them just as macrophages would eliminate bacteria,” says Schafer.  “C3 is like an ‘eat me’ signal.”

As a postdoctoral fellow in 2007, Stevens showed that neurons are loaded with complement proteins soon after birth, just when pruning is at its peak. In the new study, she and Schafer deliberately disrupted complement signaling in mice—stripping the microglia of C3 receptors, or blocking those receptors with a drug. When they did so, pruning of irrelevant synapses didn’t occur.

Stevens thinks their findings might have relevance for brain disorders. Developmental brain disorders such as autism, epilepsy or schizophrenia are increasingly seen as disorders of synapse development, and some data suggest that microglia and/or the complement cascade are involved.

At the other end of the spectrum, scientists have noted that microglia—normally in a resting state in adults—are activated in neurodegenerative diseases like glaucoma, Alzheimer’s disease, Lou Gehrig’s disease, Huntington’s disease and Parkinson’s disease. Subtle changes have been found in synapses that might cause them to be targeted for elimination.

So could targeting microglia or the complement cascade prevent synapse loss or alter pruning in these diseases?  “All this is still very speculative,” Stevens cautions. “We first need to understand normal brain development.”

 

Beth Stevens

Neuroscientist

Assistant Professor of Neurology, F. M. Kirby Neurobiology Center, Boston Children’s Hospital

Department of Neurology, Harvard Medical School

Boston, Massachusetts

Age: 45

Published September 28, 2015

https://www.macfound.org/fellows/946/#sthash.GpHuiEC6.dpuf

Beth Stevens is a neuroscientist whose research on microglial cells is prompting a significant shift in thinking about neuron communication in the healthy brain and the origins of adult neurological diseases. Until recently, it was believed that the primary function of microglia was immunological; they protected the brain by reducing inflammation and removing foreign bodies.

Stevens identified an additional, yet critical, role: the microglia are responsible for the “pruning” or removal of synaptic cells during brain development. Synapses form the connections, or means of communication, between nerve cells, and these pathways are the basis for all functions or jobs the brain performs. Using a novel model system that allows direct visualization of synapse pruning at various stages of brain development, Stevens demonstrated that the microglia’s pruning depends on the level of activity of neural pathways. She identified immune proteins called complement that “tag” (or bind) excess synapses with an “eat me” signal in the healthy developing brain. Through a process of phagocytosis, the microglia engulf or “eat” the synapses identified for elimination. This pruning optimizes the brain’s synaptic arrangements, ensuring that it has the most efficient “wiring.”

Stevens’s discoveries indicate that our adult neural circuitry is determined not only by the nerve cells but also by the brain’s immune cells. Her work suggests that adult diseases caused by deficient neural architecture (such as autism and schizophrenia) or states of neurodegeneration (such as Alzheimer’s or Huntington’s disease) may be the result of impaired microglial function and abnormal activation of this pruning pathway. Stevens is redefining our understanding of how the wiring in the brain occurs and changes in early life and shedding new light on how the nervous and immune systems interact in the brain, both in health and disease.

Beth Stevens received B.S. (1993) from Northeastern University and a Ph.D. (2003) from the University of Maryland. She was a postdoctoral fellow (2005–2008) at Stanford University and is currently an assistant professor in the Department of Neurology at Harvard Medical School and the F. M. Kirby Neurobiology Center at Boston Children’s Hospital. She is also an Institute Member of the Broad Institute of MIT and Harvard. Her scientific papers have appeared in such journals as NeuronScienceProceedings of the National Academy of Sciences, and Nature Neuroscience, among others.

– See more at: https://www.macfound.org/fellows/946/#sthash.GpHuiEC6.dpuf

Portraits of scientists who are making a mark on autism research.

http://spectrumnews.org/news/profiles/beth-stevens-casting-immune-cells-as-brain-sculptors/

Beth Stevens: Casting immune cells as brain sculptors

BY NICHOLETTE ZELIADT  /  24 SEPTEMBER 2015

Shortly after Beth Stevens launched her lab at Boston Children’s Hospital in 2008, she invited students from the Newton Montessori School, in a nearby suburb, to come for a visit. The children peered at mouse and rat brains bobbing in fluid-filled jars. They also learned how to position delicate slices of brain tissue on glass slides and inspect them with a microscope.

This visit sparked a running relationship with the school, with a steady stream of students visiting the growing lab each year. Soon it became too complicated to bring so many children to the lab, so Stevens decided to take her neuroscience lessons on the road, visiting a number of local elementary schools each year. Last year, she dropped in on the classrooms of her 5- and 8-year-old daughters, Zoe and Riley.

“The kids got really excited,” Stevens says. “It’s become such a thing that the principal wants me to come back for the whole school.”

Stevens’ enthusiasm for science has left a lasting impression on researchers, too. Her pioneering work points to a surprise role in brain development formicroglia, a type of cell once considered to simply be the brain’s immune defense system, cleaning up cellular debris, damaged tissue and pathogens. But thanks to Stevens, researchers now appreciate that these non-neuronal cells also play a critical role in shaping brain circuits.

In a 2012 discovery that created a buzz among autism researchers, Stevens and her colleagues discovered that microglia prune neuronal connections, calledsynapses, in the developing mouse brain. The trimming of synapses is thought to go awry in autism. And indeed, emerging work from Stevens’ lab hints at a role for microglia in the disorder.

Stevens has already earned praise and several prizes for her work. In 2012, shereceived the Presidential Early Career Award for Scientists and Engineers, the most prestigious award that the U.S. government bestows on young scientists. And in October, she’ll deliver one of four presidential lectures at the world’s largest gathering of neuroscientists — the annual meeting of the Society for Neuroscience — an honor she shares with three neuroscience heavyweights, including two Nobel laureates.

“The field is probably expecting a lot from Beth,” says Jonathan Kipnis, professor of neuroscience at the University of Virginia. Stevens has put microglia at the forefront, Kipnis says. “What used to be a stepchild of neuroscience research is now getting a lot of attention, and I think in part it’s due to her research.”

Curious mind:

Stevens was born in 1970 in Brockton, Massachusetts, where her mother taught elementary school and her father was the school’s principal. As a child, she was deeply inquisitive, eager to understand how things work. She enjoyed collecting bugs and worms, and would analyze these precious specimens in makeshift labs in her backyard.

But a career in science wasn’t on her radar until high school, when she took a biology class with an inspiring teacher named Anthony Cabral. “He totally made me realize that this could be a career, that I could be a scientist,” Stevens says. “It was that one class that changed it, and I’m like, ‘Okay, I’m going to do this.’”

In 1988, she began studying biology at Northeastern University in Boston, which offered an unusual opportunity. It had a unique cooperative education program that allowed Stevens to spend several semesters working full time in medical labs after finishing her coursework.

After that experience, Stevens knew she wanted to find a job in a research lab. After graduating in 1993, she joined her then-boyfriend Rob Graham, now her husband, in Washington, D.C., where he had landed a job in the U.S. Senate. Stevens headed to the National Institutes of Health (NIH) in Rockville, Maryland, to apply for a job as a research assistant.

At around the same time, neuroscientist R. Douglas Fields was launching his lab at the NIH. He studied how neural impulses influence glia — a class of non-neuronal cells that includes microglia — and shape the structure of the developing brain. Fields readily hired Stevens despite her lack of expertise in neuroscience. “I was impressed with her work ethic, energy and drive,” he says.

Stimulating research:

In Fields’ lab, Stevens used a multi-compartment cell culture system to investigate whether stimulating neurons influences the activity of Schwann cells, glial cells that produce a fatty substance called myelin, which insulates nerves1. She discovered that patterns of neural impulses similar to those that occur during early development influence the maturation of Schwann cells and the production of myelin.

The findings added to mounting evidence that glia and neurons communicate with each other, a newly emerging concept at the time.

“What I loved about the glia research was that there were so few neuroscientists studying it; it was such a mysterious part of neuroscience,” Stevens says. “Those years in Doug’s lab were really exciting because it was a new field.”

Stevens spent five years in Fields’ lab. “She was doing extraordinary work,” Fields says. “She had the potential and the interest to do neuroscience research, and I recommended that she should consider going to graduate school.”

But Stevens didn’t want to give up her position in the lab, and at that time, the NIH did not allow its researchers to have graduate students. So she and Fields convinced the University of Maryland, College Park, just 10 miles away, to allow her to take graduate courses in neuroscience while completing the necessary research for her Ph.D. in Fields’ lab.

In 2000, less than two years after starting graduate school, Stevens published a paper in Science showing that nerves in the peripheral nervous system (located outside the brain and spinal cord) use chemical signals to communicate with Schwann cells2. Two years later, she reported in Neuron that a similar form of communication occurs in the brain, between neurons and oligodendrocytes, the myelin-producing cells in the brain3.

As she was closing in on her Ph.D., Stevens sought career advice from Story Landis, then-director of the National Institute of Neurological Disorders and Stroke. Landis turned Stevens on to the possibility of starting her own lab one day. “I convinced her that she really had the abilities and energy and intelligence to run an independent research program,” Landis says.

In 2004, Stevens sought a postdoctoral fellowship with neurobiologist Ben Barres at Stanford University. “She was already seen as a leading researcher in the glial field,” recalls Barres, who promptly hired her. “She had done all sorts of beautiful work on glia.”

In Barres’ lab, Stevens continued to explore the dialogue between neurons and glia, turning her attention to star-shaped glia called astrocytes. Barres and his team had discovered that astrocytes help neurons form synapses4. To get a better handle on this process, Stevens examined how astrocytes influence gene expression in neurons in the developing mouse brain.

To her surprise, she found that astrocytes trigger neurons to produce a ‘complement’ protein that is best known for its role in the immune system. There, the protein serves as an ‘eat me’ signal, flagging pathogens and debris for removal. She found that neurons deposit this tag around immature synapses, but not mature ones, in mouse brain tissue, and mice that lack this protein have too many immature synapses. The findings suggested that astrocytes might help eliminate synapses by triggering the complement cascade5.

 

http://spectrumnews.org/wp-content/uploads/2015/09/20150929ProfileBethStevensChild350.jpg

Young recruit: Beth Stevens’ daughter Riley inspects brain tissue during a visit to her mother’s lab. | Courtesy of Beth Stevens

But it was still unclear exactly how the tagged synapses are cleared. The prime suspects were microglia, the only cells in the brain known to have the receptor for the ‘eat me’ signal.

Stevens set out to test this hypothesis in her own lab: After four years as a postdoc, she had decided to branch out on her own. In 2008, neuroscientist Michael Greenberg — chair of the neurobiology department at Harvard — recruited her to the Harvard-affiliated Boston Children’s Hospital. Even when her lab was in its infancy, she had little trouble convincing new staff to join her.

“A lot of people might be a little hesitant to join a new lab,” says Dorothy Schafer, a former postdoctoral fellow in Stevens’ lab who is now assistant professor of neurobiology at the University of Massachusetts-Worcester. “But I was so excited by the research, and she was so energetic and extremely positive, and just seemed like a very nice person.”

One decision Stevens made early on was to continue to studying microglia in mice rather than experiment with new model systems. “You’ll never see her working on songbirds, because she has this aversion to birds,” Schafer says. “I think they think her curly blond hair is a nest or something, and she’s had really bad experiences with many types of birds dive-bombing her head.”

Just four years into her foray as an independent researcher, Stevens found the proof she had been looking for. In 2012, her team published evidence that microglia eat synapses, especially those that are weak and unused6.

The findings pinned down a new role for microglia in wiring the brain. They also helped to explain how the brain, which starts out with a surplus of neurons, trims some of the excess away. Neuron named the paper its most influential publication of 2012.

Stevens continues to study the function of microglia in the healthy brain, most recently uncovering preliminary evidence that a certain protein serves as a ‘don’t eat me’ tag that protects synapses from being engulfed by microglia. She is also exploring the role of microglia in disorders such as autism.

Several studies suggest that microglia are more active and more numerous in the brains of people with autism than in controls. Stevens and her team are looking at whether the activity of microglia is altered during brain development in mouse models of autism.

 

Immunodulatory Thalidomides in ~ conjugants unleash proteasome degradation on ~ oncoproteins with distinct mechanisms- BRD4,MYC & PIM1 & little collteral damage to 7429 other proteins!

Imagine being able to specifically target a cancer protein for immediate destruction, slipping Robert Louis Stevenson’s notorious black spot into a crevice in the secondary structure and spelling imminent death. Well, this is what Winter et al. (2015) describe in a recent drug discovery report for Science.1 Using phthalimide conjugation, the researchers not only specifically marked BRD4, a transcriptional coactivator important in MYC oncogene upregulation, for proteasomal degradation, but also achieved reduced tumor burdens in vivo.

The research team combined two drugs, thalidomide and JQ1, exploiting the properties of each to create a bifunctional compound, dBET1, that drives the proteasomal degradation of BRD4. JQ1, which in itself is anti-oncogenic, selectively binds BET bromodomains on the transcription factor, thus competitively inhibiting BRD4 activity on chromatin. Thalidomide, a phthalimide-based drug with immunomodulatory properties, binds cereblon (CRBN) in the cullin-RING ubiquitin ligase (CRL) complex, which is important in proteasomal protein degradation.

After confirming that the new phthalimide conjugate, dBET1, retained affinity for BRD4 and that this binding was specific, the team used a human acute myelocytic leukemia (AML) cell line, MV4;11, to show that treatment with the conjugate over 18 hours reduced BRD4 abundance. The researchers also found this with dBET1 treatment of other human cancer cell lines (SUM159, MOLM13). Following this, Winter et al. investigated the mechanisms by which dBET1 inhibits BRD4. By focusing primarily on proteasome function, the researchers determined that the reduction in BRD4 abundance in MV4;11 cells is proteasomal and dependent on CRBN binding activity.

Having established targeted proteasomal degradation using the dBET1 conjugate, Winter et al. then investigated the proteomic consequences of treatment in MV4;11 cells. Scientists at the Thermo Fisher Scientific Center for Multiplexed Proteomics (Harvard Medical School) used quantitative proteomics analysis with an isobaric tagging approach to compare the immediate effects of dBET1 treatment following two hours of incubation with the responses to JQ1 and vehicle control. Spectral data analysis identified 7,429 proteins with few differences in response to either treatment. JQ1 treatment reduced levels of MYC and oncoprotein PIM1 similarly to the response following dBET1 incubation. However, treatment with the latter also reduced BRD2, BRD3 and BRD4 abundance, findings that the research team confirmed with specific immunoblotting. Measuring expression of mRNA showed that both treatments reduced levels of MYC and PIM1 abundance. However, Winter et al. found no difference in BRD3 and BRD4, suggesting that dBET1 reduces the protein levels by post-transcriptional regulation.

Investigating the antiproliferative potential of the phthalimide conjugate, dBET1, Winter and coauthors examined apoptotic response in both MV4;11 and DHL4 lymphoma cells, and in primary human AML blast cultures. Compared to JQ1 treatment, dBET1 stimulated a profound and prolonged apoptotic response in both cell lines, suggesting that targeted degradation could be a more effective treatment than target inhibition.

shapes of proteins as they shift from one stable shape to a different, folded one Protein-structural-changes

shapes of proteins as they shift from one stable shape to a different, folded one Protein-structural-changes

Orchestrating the unfolded protein response in health and disease

Randal J. Kaufman Department of Biological Chemistry,
Howard Hughes Medical Institute, University of Michigan Medical Center, Ann Arbor, Michigan, USA J. Clin. Invest. 110:1389–1398 (2002).   http://dx.doi.org:/10.1172/JCI200216886

The endoplasmic reticulum (ER), the entrance site for proteins destined to reside in the secretory pathway or the extracellular environment, is also the site of biosynthesis for steroids and for cholesterol and many lipids. Given the considerable number of resident structural proteins and biosynthetic enzymes and the high expression of many secreted proteins, the total concentration of proteins in the this organelle can reach 100 mg/ml. The ER relies on an efficient system of protein chaperones that prevent the accumulation of unfolded or aggregated proteins and correct misfolded proteins that are caught in low-energy kinetic traps (see Horwich, this Perspective series, ref. 1).

These chaperone-mediated processes expend metabolic energy to ensure high-fidelity protein folding in the lumen of the ER. For example, the most abundant ER chaperone, BiP/GRP78, uses the energy from ATP hydrolysis to promote folding and prevent aggregation of proteins within the ER. In addition, the oxidizing environment of the ER creates a constant demand for cellular protein disulfide isomerases to catalyze and monitor disulfide bond formation in a regulated and ordered manner. Operating in parallel with chaperone dependent protein folding are several “quality control” mechanisms, which ensure that, of all proteins translocated into the ER lumen, only those that are properly folded transit to the Golgi compartment. Proteins that are misfolded in the ER are retained until they reach their native conformation or are retrotranslocated back into the cytosol for degradation by the 26S proteasome. The ER has evolved highly specific signaling pathways to ensure that its protein-folding capacity is not overwhelmed. These pathways, collectively termed the unfolded protein response (UPR), are required if the cell is to survive the ER stress (see Ron, this Perspective series, ref. 2) that can result from perturbation in calcium homeostasis or redox status, elevated secretory protein synthesis, expression of misfolded proteins, sugar/glucose deprivation, or altered glycosylation. Upon accumulation of unfolded proteins in the ER lumen, the UPR is activated, reducing the amount of new protein translocated into the ER lumen, increasing retrotranslocation and degradation of ER-localized proteins, and bolstering the protein-folding capacity of the ER. The UPR is orchestrated by the coordinate transcriptional activation of multiple genes, a general decrease in translation initiation, and a concomitant shift in the mRNAs that are translated.

The recent discovery of the mechanisms of ER stress signaling, coupled with the ability to genetically engineer model organisms, has led to major new insights into the diverse cellular and physiological processes that are regulated by the UPR. Here, I summarize current discoveries that have offered insights into the complex regulation of the UPR and its relevance to human physiology and disease.

Glucose and protein folding Early studies demonstrated that both viral transformation and glucose depletion induce transcription of a set of related genes that were termed glucose-regulated proteins (GRPs) (3). Since viral transformation increases both the cellular metabolic rate and ATP utilization, it became evident that, in both cases, this signal emanates from the ER as a consequence of energy deprivation. Because proteins have different ATP requirements for protein folding prior to export, it has been proposed that the threshold for UPR activation might differ among various cell types, depending on their energy stores and the amount and nature of the secretory proteins they produce (4). Glucose not only provides the metabolic energy needed by cells but also participates directly in glycoprotein folding as a component of oligosaccharide structures.

The recognition and modification of oligosaccharide structures in the lumen of the ER is intimately coupled to polypeptide folding (5). As the growing nascent chain is translocated into the lumen of the ER, a 14-oligosaccharide core (GlcNAc2Man9Glc3) is added to consensus asparagine residues. Immediately after the addition of this core, the three terminal glucose residues are cleaved by the sequential action of glucosidases I and II to yield a GlcNAc2Man9 structure. If the polypeptide is not folded properly, a UDP-glucose:glycoprotein glucosyltransferase (UGGT) recognizes the unfolded nature of the glycoprotein and reglucosylates the core structure to re-establish the glucose-α(1, 3)–mannose glycosidic linkage. Monoglucosylated oligosaccharides containing this bond bind to the ER-resident protein chaperones calnexin and calreticulin.

This quality control process ensures that unfolded glycoproteins do not exit the ER. Treatment of cells with castanospermine, a transition-state analogue inhibitor of glucosidases I and II, inhibits this monoglucosylation cycle, prevents interaction of unfolded glycoproteins with calnexin and calreticulin, and activates the UPR. Genetic alterations that reduce the nucleotide sugar precursor pool or glycosyltransferase reactions likewise activate the UPR (6). Therefore, the recognition of altered carbohydrate structures is in some manner linked to UPR activation.

The UPR in yeast and higher eukaryotes On a cellular level, the accumulation of unfolded proteins in the ER lumen induces the transcription of a large set of genes whose products increase the ER’s volume or its capacity for protein folding or promote the degradation of misfolded proteins through the process of ER-associated protein degradation (ERAD) (7). For example, transcription of the ER protein chaperone BiP is a classical marker for UPR activation in yeast and mammalian cells (8). BiP binds hydrophobic exposed patches on the surfaces of unfolded proteins and interactive sites on unassembled protein subunits, and it releases its polypeptide substrates upon ATP binding.

In parallel, as Ron (this Perspective series, ref. 2) details in his accompanying article, translation is attenuated to decrease the protein-folding load. The complex network of physiological responses to ER stress is regulated by only a few ER transmembrane proteins: IRE1, PERK, and ATF6 (9). IRE1, PERK, and ATF6 are proximal sensors that regulate the production and/or quality of basic leucine zipper–containing (bZIP-containing) transcription factors that may form homo- and heterodimers. Combinatorial interactions of these factors generate diversity in responses for different subsets of UPRresponsive genes. In multicellular organisms, if these adaptive responses are not sufficient to relieve ER stress, the cell dies through apoptosis or necrosis.

IRE1-dependent splicing The UPR-signaling pathway was first described less than ten years ago in the budding yeast Saccharomyces cerevisiae. Elegant studies identified IRE1 as the sensor of unfolded proteins in the ER lumen. IRE1 is a type 1 transmembrane Ser/Thr protein kinase that also has a site-specific endoribonuclease (RNase) activity. The presence of unfolded proteins in the ER lumen promotes dimerization and trans-autophosphorylation, rendering IRE1 active as an RNase, and allowing it to cleave a 252-base intron from the mRNA encoding the transcription factor HAC1 (10). The 5′ and 3′ ends of HAC1 mRNA are spliced together by tRNA ligase in a process that is independent of the spliceosome and the usual intranuclear machinery for mRNA splicing. Splicing of HAC1 mRNA increases its translational efficiency and alters sequence of the encoded HAC1 protein, yielding a potent transcriptional activator (11) that can bind and activate the UPR elements (UPREs) upstream of many UPR-inducible genes. In S. cerevisiae, the UPR activates transcription of approximately 381 genes (7).

All eukaryotic cells appear to have maintained the essential and unique properties of the UPR present in S. cerevisiae, but higher eukaryotes possess additional sensors that generate diverse, coordinately regulated responses that promote stress adaptation or cell death. The mammalian genome contains two homologues of yeast IRE1 — IRE1α and IRE1β. Whereas IRE1α is expressed in most cells and tissues, with high-level expression in the pancreas and placenta (12), IRE1β expression is prominent only in intestinal epithelial cells (13). Both IRE1 molecules respond to the accumulation of unfolded proteins in the ER, which activate their kinase and, thereby, their RNase activities. The cleavage specificities of IRE1α and IRE1β are similar, if not identical, suggesting that they do not recognize different sets of substrates but rather generate temporally specific and tissue-specific expression (14, 15).

Searching for transcription factors that mediate the UPR, Yoshida et al. defined a mammalian ER stress response element [ERSEI; CCAAT(N9)CCACG] that is necessary and sufficient for UPR gene activation. Using a yeast one-hybrid screen, these authors isolated XBP1, a bZIP transcription factor X-box DNA binding protein (16). Subsequently, several groups demonstrated that XBP1 mRNA is a substrate for mammalian IRE1, much as the HAC1 mRNA in S. cerevisiae is processed by the yeast IRE1; this pathway is also conserved in Caenorhabditis elegans (17–20). On activation of the UPR, XBP1 mRNA is cleaved by IRE1 to remove a 26-nucleotide intron and generate a translational frameshift. As expected given the precedent of HAC1 regulation in yeast, the resulting processed mRNA encodes a protein with a novel carboxy-terminus that acts as a potent transcriptional activator.

Overexpression of either IRE1α or IRE1β is sufficient to activate transcription from a BiP promoter reporter construct (15). Analysis of a minimal UPRE motif (TGACGTGC/A) (21) uncovered a transcriptional defect in IRE1α-null mouse embryo fibroblasts that could be complemented by expression of spliced XBP1 mRNA (20), and Yoshida et al. (unpublished data) recently identified a UPR-inducible gene that uniquely requires IRE1α-mediated splicing of XBP1 mRNA. However, neither IRE1α nor IRE1β is necessary for transcriptional activation of the BiP gene, as judged by the phenotype of IRE1α/β–deleted murine cells (20, 22, 23). These results indicate that a subset of UPR targets require IRE1 but that at least one IRE1-independent pathway exists for UPR-mediated transcriptional induction. Deletion of IRE1α causes embryonic lethality at embryonic day 10.5 (E10.5) (20, 22, 23). Therefore, although IRE1α is not required for the UPR, it is clearly required for mammalian embryogenesis. XBP1 deletion also causes embryonic lethality, but the mutant embryos can survive up to day E14.5, consistent with the notion that XBP1 acts downstream of IRE1α. XBP1 deletion causes cardiomyopathy and liver hypoplasia (24, 25). In contrast, IRE1β-null mice develop normally but exhibit increased susceptibility to experimentally induced colitis, a phenotype that is consistent with the specific expression of this kinase in the intestinal epithelium (26).

Activation of ATF6 and PERK by ER stress The activating transcription factor ATF6 (16) has been identified as another regulatory protein that, like XBP1, can bind ERSEI elements in the promoters of UPRresponsive genes. There are two forms of ATF6, both synthesized as ER transmembrane proteins. ATF6α (90 kDa) and ATF6β (110 kDa, also known as CREB-RP) both require the presence of the transcription factor CBF (also called NF-Y) to bind ERSEI (27–30).

On activation of the UPR, both forms of ATF6 are processed to generate 50- to 60-kDa cytosolic, bZIP containing transcription factors that migrate to the nucleus (27). Processing of ATF6 by site-1 protease (S1P) and site-2 protease (S2P) occurs within the transmembrane segment and at an adjacent site exposed to the ER lumen. S1P and S2P are the processing enzymes that cleave the ER-associated transmembrane sterolresponse element–binding protein (SREBP) upon cholesterol deprivation (31). The cytosolic fragment of cleaved SREBP migrates to the nucleus to activate transcription of genes required for sterol biosynthesis. Interestingly, although the mechanism regulating ATF6 processing is similar to that regulating SREBP processing (32), the UPR only elicits ATF6 processing, whereas sterol deprivation alone induces SREBP processing. The SREBP cleavage–activating protein (SCAP) confers specificity for SREBP transport to the Golgi compartment, and consequently cleavage in response to sterol deprivation (33). It is unknown whether another cleavage-activating protein, analogous to SCAP but active only following induction of the UPR, promotes the specific cleavage and activation of ATF6 by S1P and S2P.

Transcription of UPR-responsive genes is induced when the cleaved form of ATF6 activates the XBP1 promoter. Therefore, signaling through ATF6 and IRE1 merges to induce XBP1 transcription and mRNA splicing, respectively (Figure 1, a and b). ATF6 increases XBP1 transcription to produce more substrate for IRE1- mediated splicing that generates more active XBP1, providing a positive feedback for UPR activation. However, cells that lack either IRE1α or ATF6 cleavage can induce XBP1 mRNA (20). These two pathways may thus provide parallel signaling pathways for XBP1 transcriptional induction. Alternatively, another pathway — possibly mediated by the ER-localized protein kinase PERK (see Ron, this Perspective series, ref. 2) — may also contribute to induction of XBP1 mRNA. The binding specificities of XBP1 and ATF6 are similar, although ATF6 binding requires CBF binding to an adjacent site, whereas XBP1 binds independently (17, 20, 21, 34). These binding specificities provide another avenue for complementary interaction between the IRE1-XBP1 and ATF6 pathways at the level of transcriptional activation. In addition, these transcription factors might regulate transcription from a second ERSE (ERSEII), which also contains a CCACG motif (35).

In parallel with the activation of ATF6 processing and the consequent changes in gene transcription, the accumulation of unfolded proteins in the ER also alters cellular patterns of translation. The protein kinase PERK has been implicated in this aspect of the ER stress response (see Ron, this Perspective series, ref. 2). Activated PERK phosphorylates the α subunit of eukaryotic translation initiation factor 2 (eIF2α) and attenuates general protein synthesis. Inactivation of the PERK-eIF2α phosphorylation pathway decreases cells’ ability to survive ER stress (36, 37). The PERK pathway promotes cell survival not only by limiting the protein-folding load on the ER, but also by inducing transcription of UPR- activated genes, one-third of which require phosphorylation of eIF2α for their induction (36). Preferential translation of the transcription factor ATF4 allows for continued activation of these genes under conditions of stress, when general protein synthesis is inhibited (36, 37).

A coordinated mechanism for activation One puzzling question about the UPR is how three independent sensors are activated by a common stimulus, the accumulation of unfolded proteins in the ER lumen. BiP, which negatively regulates the UPR, interacts with all three sensors, IRE1, PERK, and ATF6, under nonstressed conditions and may indeed be the master regulator of UPR activation.

Upon accumulation of unfolded proteins in the ER, BiP is released from IRE1, PERK, and ATF6. It is believed that the unfolded proteins bind BiP and sequester it from interacting with IRE1, PERK, and ATF6 to elicit their activation. In this manner, BiP senses both the level of unfolded proteins and the energy (ATP) level in the cell in regulating the UPR. Following release from BiP, IRE1 and PERK are each free to undergo spontaneous homodimerization mediated by their lumenal domains and to become phosphorylated by their endogenous kinase activities (38, 39). BiP interaction with ATF6 prevents trafficking of ATF6 to the Golgi compartment. For this reason, BiP release permits ATF6 transport to the Golgi compartment, where it gains access to S1P and S2P proteases (32). The regulation of signaling through the free level of BiP is an attractive hypothesis providing a direct mechanism by which all three ER stress sensors could be activated by the same stimulus. In addition, the increase in BiP during the UPR would provide a negative feedback to turn off UPR signaling. However, in certain cells, different stress conditions can selectively activate only one or two of the ER stress sensors. For example, in pancreatic β cells, glucose limitation appears to activate PERK prior to activation of IRE1 (D. Scheuner and R.J. Kaufman, unpublished results). It will be important to elucidate how general BiP repression permits the selective activation of individual components of the UPR that mediate various downstream effects.

Signaling the UPR in eukaryotes

Signaling the UPR in eukaryotes

Figure 1 Signaling the UPR in eukaryotes.

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Three proximal sensors, IRE1, PERK, and ATF6, coordinately regulate the UPR through their various signaling pathways. Whereas IRE1 and PERK are dispensable for many aspects of the response, ATF6 cleavage is required for UPR transcriptional induction and appears to be the most significant of these effectors in mammalian cells. BiP negatively regulates these pathways. BiP interacts with ATF6 to prevent its transport to the Golgi compartment (a). BiP binds to the lumenal domains of IRE1 (b) and PERK (c) to prevent their dimerization. As unfolded proteins accumulate, they bind BiP and reduce the amount of BiP available to bind and inhibit activation of IRE1, PERK, and ATF6. (a) BiP release from ATF6 permits transport to the Golgi compartment. In the Golgi, ATF6 is cleaved by S1P and S2P proteases to yield a cytosolic fragment that migrates to the nucleus to activate transcription of responsive genes, including XBP1. (b) BiP release from IRE1 permits dimerization to activate its kinase and RNase activities to initiate XBP1 mRNA splicing. XBP1 splicing removes a 26-base intron, creating a translational frameshift to yield a more potent transcriptional activator. (c) BiP release permits PERK dimerization and activation to phosphorylate Ser51 on eIF2α to reduce the frequency of AUG initiation codon recognition. As eIF2α phosphorylation reduces the functional level of eIF2, the general rate of translation initiation is reduced. However, selective mRNAs, such as ATF4 mRNA, are preferentially translated under these conditions, possibly by the presence of open reading frames within the 5′ untranslated region of the mRNA. Upon recovery from the UPR, GADD34 targets PP1 to dephosphorylate eIF2α and increase protein translation.

The UPR as a mediator of programmed cell death In contrast to UPR-signaling adaptation in response to ER stress, prolonged UPR activation leads to apoptotic cell death (Figure 2). The roles of several death-promoting signaling pathways have been shown by analysis of specific gene-deleted cells. Activated IRE1 recruits c-Jun-N-terminal inhibitory kinase (JIK) and the cytosolic adaptor TRAF2 to the ER membrane (22, 40). TRAF2 activates the apoptosis-signaling kinase 1 (ASK1), a mitogen-activated protein kinase kinase kinase (MAPKKK) (41). Activated ASK1 leads to activation of the JNK protein kinase and mitochondriadependent caspase activation (40–42).

ER insults lead to caspase activation by mitochondria/APAF-1–dependent and –independent pathways. ER stress promotes cytochrome c release from mitochondria, possibly by c-ABL kinase (43) or calcium (44). However, APAF1–/– cells are susceptible to ER stress–induced apoptosis, indicating that the mitochondrial pathway is not essential (45). Caspase-12 is an ER-associated proximal effector in the caspase activation cascade, and cells lacking this enzyme are partially resistant to inducers of ER stress (46). ER stress induces TRAF2 release from procaspase 12, allowing it to bind activated IRE1. As shown in Figure 2, release of TRAF2 permits clustering of procaspase-12 at the ER membrane, leading to its activation (40). Caspase-12 can activate caspase-9, which in turn activates caspase- 3 (47). Procaspase-12 can also be activated by m-calpain in response to calcium release from the ER, although the physiological significance of this pathway is not known (48). In addition, upon ER stress, procaspase-7 is activated and recruited to the ER membrane (49). These findings support the notion that ER stress leads to several redundant pathways for caspase activation.

A second death-signaling pathway activated by ER stress is mediated by transcriptional activation of genes encoding proapoptotic functions. Activation of UPR sensor IRE1, PERK, or ATF6 leads to transcriptional activation of CHOP/GADD153, a bZIP transcription factor that potentiates apoptosis (see Ron, this Perspective series, ref. 2).

The UPR in health and disease Primary amino acid sequence contains all the information for a protein to attain its final folded conformation. However, many folding intermediates exist along the folding pathway (see Horwich, this Perspective series, ref. 1), and some of these intermediates can become irreversibly trapped in low-energy states and activate the UPR. Clearance of such misfolded species requires a functional ER-associated degradation (ERAD) pathway, which is regulated by the UPR. Proteasomal degradation of ER-associated misfolded proteins is required to protect from UPR activation. Proteasomal inhibition is sufficient to activate the UPR, and, in turn, genes encoding several components of ERAD are transcriptionally induced by the UPR (7). Therefore, it is to be expected that UPR activation and impaired ERAD function might contribute to a variety of diseases and that polymorphisms affecting the UPR and ERAD responses could modify disease progression. The following examples provide the best available evidence linking the UPR pathway to the natural history of human diseases and animal models of these diseases.

The UPR and ERAD in genetic disease Many recessive inherited genetic diseases are due to loss  of-function mutations that disturb productive folding and that produce proteins that are either not secreted or not functional. In other cases, protein-folding mutations can interfere with cellular processes, resulting in a gain of function and a dominant pattern of inheritance. In several instances, UPR activation by the accumulation of unfolded proteins in the ER is known to contribute to disease progression. The distinction between these two classes of genetic disease is important, because gain-of-function protein-misfolding mutations will be less amenable to treatment by gene therapy to deliver a wild-type copy of the mutant gene.

One well-characterized protein-folding defect results from a mutation that leads to type 1 diabetes. The Akita mouse has a gain-of-function Cys96Tyr mutation in the proinsulin 2 (Ins2) gene; this mutation disrupts proinsulin folding. The mutant protein is retained in the ER of the pancreatic β cell and activates the UPR. Crucially, the progressive development of diabetes in this model is not solely due to the lack of insulin but is rather a consequence of the misfolded protein accumulation, UPR activation, and β cell death. When bred into a Chop–/–background, the Akita mutation causes a lesser degree of β cell death and delayed onset of diabetes (50), indicating that the loss of at least one downstream signaling component of the UPR can ameliorate pathogenesis in this setting.

Signaling UPR-mediated cell death

Signaling UPR-mediated cell death

Figure 2 Signaling UPR-mediated cell death.

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The activation of procaspase-12 is likely the major pathway that induces apoptosis in response to ER stress. Upon activation of the UPR, c-Jun-N-terminal inhibitory kinase (JIK) release from procaspase-12 permits clustering and activation of procaspase-12. Caspase-12 activates procaspase-9 to activate procaspase-3, the executioner of cell death. In addition, activated IRE1 binds JIK and recruits TRAF2, which signals through apoptosis-signaling kinase 1 (ASK1) and JNK to promote mitochondria-dependent apoptosis. In addition, in vitro studies suggest that localized calcium release from the ER activates m-calpain to cleave and activate procaspase-12. Upon UPR activation, procaspase-7 is activated and recruited to the ER membrane. Finally, IRE1, PERK, and ATF6 induce transcription of several genes encoding apoptotic functions, including CHOP/GADD153. CSP, caspase; pCSP, procaspase.

Deficiency in α1-proteinase inhibitor (α1-PI, also known as α1-antitrypsin) results in emphysema and destructive lung disease in one out of 1,800 births. However, a subgroup of affected individuals develop chronic liver disease and hepatocellular carcinoma as a consequence of a secretion defect in the misfolded protein at the site of synthesis, the hepatocyte. This is the most common genetic cause of liver disease in children. The Z allele of the α1 gene PI (Glu342Lys mutation) produces a protein that polymerizes and is retained in the ER for degradation by the proteasome (see Lomas and Mahadeva, this Perspective series, ref. 51; and Perlmutter, this series, ref. 52). While α1-PI Z neither binds BiP nor activates the UPR, analysis of fibroblasts obtained from these patients demonstrates that individuals susceptible to liver disease have inherited a second trait that slows degradation of the misfolded protein in the ER (53), consistent with the idea that polymorphisms that reduce ERAD function can exacerbate pathogenesis of certain diseases.

There are numerous additional genetic misfolding diseases that are also likely influenced by UPR signaling. Because BiP release from IRE1, PERK, or ATF6 can activate the UPR, the expression of any wild-type or mutant protein that binds BiP can have a similar effect. In contrast, misfolded proteins that do not bind BiP are unlikely to activate the UPR. For example, cystic fibrosis is due to mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) protein. Approximately 70% of patients with this disease carry a common mutation, deletion of Phe508, that results in a molecule that is retained in the ER and eventually degraded by the proteosome (see Gelman and Kopito, this Perspective series, ref. 54). Although expression of ∆508 CFTR does not activate the UPR in cultured cells, the protein does interact with calnexin, as well as HSP70, and requires ERAD function for cell survival.

Osteogenesis imperfecta (OI) results from misfolding mutations in procollagen that produce molecules that bind BiP and activate the UPR (55). Interestingly, Wolcott-Rallison syndrome is due to inactivating mutations in the PERK gene. Affected individuals, as well as mice with deletions in Perk, display osteoporosis and deficient mineralization throughout the skeletal system (56, 57), the same defects that are observed in OI. Procollagen type I accumulates to high levels and mature collagen is not detected in bone and osteoblasts from PERKnull mice. Osteoblasts from PERK-null humans and mice display fragmented and distended ER that is filled with electron-dense material (56, 57). These observations suggest that procollagen type 1 uniquely requires PERK function to maintain its transport out of the ER, processing, and secretion In this case, PERK may be required to limit procollagen synthesis so that it does not saturate the ER protein-folding capacity.

The UPR and ERAD in conformational diseases Diseases caused by expansion of polyglutamine repeats and neurodegenerative diseases, such as Alzheimer disease and Parkinson disease, represent a large class of conformational diseases associated with accumulation of abnormal protein aggregates in and around affected neurons. Recent evidence indicates that the pathogenesis of these diseases is due to a defect in proteasomal function that results in UPR activation, leading to cell death. The protein aggregates in these diseases are localized to the nucleus or the cytoplasm and would not be predicted to disturb ER function directly. Nevertheless, they have been found in some cases to activate the UPR and to promote cell death. Analysis of the polyglutamine repeat associated with the spinocerebrocellular atrophy protein (SCA3) in Machado-Joseph disease suggests that cytoplasmic accumulation of the SCA3 aggregate can inhibit proteasome function, thereby interfering with ERAD to induce the UPR and elicit caspase-12 activation (41, 58). These findings support the idea that the UPR can signal the accumulation of unfolded proteins in the cytosol via proteasomal inhibition and disruption of ERAD function.

Parkinson disease is the most common movement disorder, affecting about 1% of individuals 65 years of age or older. Autosomal recessive juvenile parkinsonism (AR-JP) results from defects in the Parkin gene (59), which encodes a ubiquitin protein ligase (E3) that functions with ubiquitin-conjugating enzyme UbcH7 or UbcH8 to tag proteins for degradation. Overexpression of Parkin suppresses cell death associated with ER stress (60). Inherited Parkinson disease is associated with the accumulation in the ER of dopaminergic neurons of PAEL-R, a putative transmembrane receptor protein that is detected in an insoluble form in the brains of AR-JP patients (61). The accumulation of PAEL-R results from defective Parkin that does not maintain the proteasome-degrading activity necessary to maintain ER function (62). Other, still-unidentified substrates of the Parkin E3 ligase may also be relevant to the pathogenesis of AR-JP.

The UPR in diabetes The metabolism of glucose is tightly controlled at the levels of synthesis and utilization through hormonal regulation. The most dramatic phenotype in Wolcott-Rallison syndrome is pancreatic β cell death with infancy onset diabetes (56). A similar defect is observed in PERK-null mice; this defect also correlated with increased apoptosis of β cells (57, 63). In addition, mice with a homozygous Ser51Ala mutation at the PERK phosphorylation site in eIF2α display an even greater β cell loss that appears in utero (36). Therefore, translational control through PERK-mediated phosphorylation of eIF2α is required to maintain β cell survival (see Ron, this Perspective series, ref. 2). The more severe β cell loss in mice harboring the Ser51Ala eIF2α mutation suggests that additional eIF2α kinases partially complement the requirement for PERK in β cell function (36)

Glucose not only promotes the secretion of insulin but also stimulates insulin transcription and translation (64–66). Our group has proposed that glucose stimulated proinsulin mRNA translation is regulated by PERK-mediated phosphorylation of eIF2α in response to UPR activation 36). As blood glucose declines, energy may become limiting for protein folding in the ER and therefore activate the UPR to promote PERK-mediated phosphorylation of eIF2α. Conversely, a rise in blood glucose would turn off the UPR so that translation would accelerate, allowing entry of new preproinsulin into the ER. In this manner, PERK mediated phosphorylation of eIF2α provides a brake on protein synthesis, including proinsulin translation. Continual elevation of blood glucose may also prolong elevated proinsulin translation, eventually activating the UPR as the secretion capacity of the ER is overwhelmed. Therefore, a delicate balance between glucose levels and eIF2α phosphorylation needs to be maintained: Disturbances in either direction may lead to excessive UPR activation, with eventual β cell death.

The insulin resistance and hyperglycemia associated with type 2 diabetes is accommodated by an increase in proinsulin translation. Under these conditions the UPR is activated to compensate for the increased protein-folding requirement in the ER. Prolonged activation of the UPR could contribute to the β cell death associated with insulin resistance. Thus, the signaling mechanisms that β cells use for sensing glucose levels, triggering insulin secretion, and rapidly controlling insulin biosynthesis may have coevolved with ER signaling pathways to support these specialized functions. Pancreatic β cells are exquisitely sensitive to physiological fluctuations in blood glucose, because, in contrast to other cell types, they lack hexokinase, an enzyme with a low affinity but a high capacity for binding glucose. Therefore, in β cells, the production of glucose 6-phosphate and the production of ATP through glycolysis are controlled by glucokinase (67), and the ratio of ATP to ADP correlates directly with the blood glucose level. Periodic decreases in blood glucose level (as occurs between meals) would decrease the ATP/ADP ratio and compromise protein folding in the ER so that the UPR may be frequently activated in these cells. Hence, when glucose levels vary within the normal physiological range, the ER compartment of the β cell may be exposed to greater energy fluctuations than is the ER of other cell types, making the β cell uniquely dependent on the UPR for survival during intermittent decreases in blood glucose levels, as happens between meals. Additionally, the high-level expression of PERK and IRE1α in the pancreas may predispose these kinases to dimerization and activation in response to intermittent stress.

The UPR in organelle expansion The UPR is required for ER expansion that occurs upon differentiation of highly specialized secretory cells, but ER membrane expansion can also proceed independently of UPR activation. Overexpression of membrane proteins, such as HMG CoA reductase or the peroxisomal protein Pex15, promotes the expansion of smooth membranes without UPR activation (68, 69), as does overexpression of the p180 ribosome acceptor in the rough ER membrane (70). Conversely, protein overexpression, even under circumstances in which secretory capacity is unchanged (as occurs following the induction of high levels of cytochrome p450), can activate the UPR to induce ER chaperone levels to match the expanded membrane area (71, 72).

During the terminal differentiation of certain secretory cells, such as those in the pancreas or liver, membrane expansion is accompanied by a dramatic increase in protein secretion. Likewise, upon B cell maturation into high-level antibody-secreting plasma cells, the ER compartment expands approximately fivefold to accommodate the large increase in Ig synthesis. The requirement for the UPR in this latter process has been demonstrated in XBP1–/– cells. Since deletion of XBP1 produces an embryonic-lethal phenotype at day E14.5, the role of XBP1 in B and T cell development had to be studied in immunoincompetent RAG1–/– mice reconstituted with XBP1–/– embryonic stem cells (73). Work in these chimeric mice demonstrated that XBP1 is required for high-level Ig production. Interestingly, the induction of Ig heavy-chain and light-chain gene rearrangement and the assembly and transport of Igµ to the surface of the B cells occurred normally. However, plasma cells were not detected, suggesting a role for XBP1 in plasma cell differentiation or survival.

These findings support the hypothesis that induction of Ig synthesis activates the UPR to induce ER expansion to accommodate the high-level antibody expression. Alternatively, activation of the UPR may be part of the differentiation program that occurs prior to induction of high-level antibody synthesis. Plasma cell differentiation is stimulated in vivo by treatment with LPS or by ligation of CD40 receptors, treatments that activate the innate immune response and have been shown to induce XBP1 mRNA splicing (19). Thus, the UPR may contribute to a programmed response to signals that increase a cell’s protein-secretory demand.

The UPR in hyperhomocysteinemia. The association between high levels of serum homocysteine and the development of ischemic heart disease and stroke is supported by substantial epidemiological data. Unfortunately, it is not known whether homocysteine is the underlying cause of atherosclerosis and thrombosis. Severe hyperhomocysteinemia is caused by mutation in the cystathionine β-synthase (CBS) gene, whose product is a vitamin B6–dependent enzyme required for the conversion of homocysteine to cysteine. Elevated homocysteine is also associated with vitamin B deficiency. In cultured vascular endothelial cells, homocysteine induces protein misfolding in the ER by interfering with disulfide bond formation, and it activates the UPR to induce expression of several ER stress response proteins, such as BiP, GRP94, CHOP, and HERP (74–76). Homocysteine also activates apoptosis in a manner that requires an intact IRE1-signaling pathway (76).

These findings suggest that homocysteine acts intracellularly to disrupt ER homoeostasis. Indeed, recent studies confirm that induction of hyperhomocysteinemia elicits UPR activation in the livers of normal or Cbs+/– mice (77). In addition, hyperhomocysteinemia activates SREBP cleavage, leading to intracellular accumulation of cholesterol (77). Increased cholesterol biosynthesis may explain the hepatic steatosis and possibly the atherosclerotic lesions associated with hyperhomocysteinemia. Finally, hyperhomocysteinemia accelerates atherosclerosis in ApoE–/– mice (78, 79), although the molecular mechanisms remain to be elucidated.

Hyperhomocysteinemia is also associated with increased amyloid production and increased amyloid-mediated neuronal death in animal models of Alzheimer disease (80). These observations suggest that the UPR may link the disease etiologies of hyperhomocysteinemia and Alzheimer disease. HERP, a homocysteine-induced ER stress–responsive gene, appears to be involved in amyloid β-protein (Aβ) accumulation, including the formation of senile plaques and vascular Aβ deposits (81), and that it interacts with both presenilin-1 (PS1) and presenilin-2 (PS2), thus regulating presenilin-mediated Aβ generation. Immunohistochemical analysis of brains from patients with Alzheimer disease reveals intense HERP staining in activated microglia in senile plaques.

The UPR in cancer Hypoxia is a common feature of solid tumors that display increased malignancy, resistance to therapy, and poor prognosis. Hypoxia in the tumor results from increased demand due to dysregulated cell growth and from vascular abnormalities associated with cancerous tissue. The importance of hypoxia has been seen in the clinic, since it predicts for poor outcome of treatments, independent of treatment modality. Hypoxia activates the UPR, whose downstream signaling events can undermine the efficacy of treatment. Tumor cells need to adapt to the increasingly hypoxic environment that surrounds them as they grow, and the induction of the UPR is key to this response. Induction of the ER stress response genes, for example BiP and GRP94, in cancerous tissue correlates with malignancy, consistent with their antiapoptotic function (82). In addition, the UPR confers resistance to topoisomerase inhibitors, such as etoposide, and some UPR-induced genes directly mediate drug resistance via the multi-drug-resistance gene MDR. Therefore, approaches to prevent UPR activation in cancerous cells may significantly improve treatment outcome.

The proteasome inhibitor PS-341 is now in earlyphase clinical evaluation for the treatment of multiple myeloma, a clonal B cell tumor of differentiated plasma cells (83). The mechanism of PS-341 function is thought to be inhibition of IκB degradation, which prevents activation of the antiapoptotic transcription factor NF-κB. However, proteasomal inhibition would also prevent ERAD. As high-level heavy- or light-chain Ig production is likely associated with a certain degree of protein misfolding, it is possible that inhibition of ERAD function may be selectively toxic to B cell myelomas through activation of the UPR and apoptosis.

The UPR and viral pathogenesis The two major mediators of the IFN-induced arm of the innate immune response are evolutionarily related to IRE1 and PERK. The kinase/endoribonuclease domain of IRE1 is homologous to RNaseL, and the protein kinase domain of PERK is related to the double-stranded RNA–activated (dsRNA-activated) eIF2α protein kinase PKR. RNase L and PKR mediate the IFN induced antiviral response of the host, which is required to limit viral protein synthesis and pathogenesis. As part of the innate immune response to viral infection, RNase L and PKR are activated by dsRNAs produced as intermediates in viral replication. In contrast to activation by dsRNA, IRE1 and PERK are activated by ER stress, which can be induced by high-level viral glycoprotein expression. All enveloped viruses produce excess glycoproteins that could elicit PERK and IRE1 activation to meet the need for increased folding and secretory capacity. More studies will be required to elucidate the role of the UPR in various viral diseases.

Hepatitis C virus (HCV) is a positive-stranded RNA virus encoding a single polyprotein. Polyprotein cleavage generates at least ten polypeptides, including two glycoproteins, E1 and E2. A large amount of E1 forms disulfide–cross-linked aggregates with E2 in the ER (84). Since the accumulation of misfolded α1-PI elicits UPR activation, with subsequent hepatocyte death and hepatocellular carcinoma, it is possible that the aggregated E1/E2 complexes in the HCV-infected hepatocyte also contribute to hepatitis and hepatocellular carcinoma. Future studies should identify whether these glycoprotein aggregates activate the UPR to mediate the hepatocyte cell death and transformation associated with the pathogenesis of HCV infection.

The UPR in tissue ischemia Finally, neuronal death due to reperfusion after ischemic injury is associated with activation of the UPR (85, 86). Immediately after reperfusion, protein synthesis is inhibited, due at least in part to phosphorylation of eIF2α; this inhibition may represent a protective mechanism to prevent further neuron damage. Recent studies support the idea that eIF2α phosphorylation in response to reperfusion injury is mediated by PERK and hence that it depends on the UPR (87). If so, UPR activation prior to ischemic injury might protect the brain and other tissues from cell death during periods of reperfusion.

Summary A variety of approaches have been employed to identify the UPR signaling components, their function, and their physiological role. Yeast genetics allowed the definition of the basic ER stress–signaling pathway. The identification of homologous and parallel signaling pathways in higher eukaryotes has produced a mechanistic framework the cell uses to sense and compensate for ER over-load and stress. The high-level tissue-specific expression patterns of several ER stress–signaling molecules indicated the pancreas and intestine as organs that require UPR for physiological function. Analysis of UPR-induced gene expression established that protein degradation is required to reduce the stress of unfolded protein accumulation in the ER. Major advances in identifying UPR function and rele vance to disease were derived from mutation of UPR signaling components in model organisms and the identification of mutations in humans.

Despite tremendous progress, our knowledge of the UPR pathway remains incomplete. Further studies promise to expand our understanding of how ER stress impacts the other cellular signaling pathways. It will be very exciting and informative to understand how the UPR varies when critical components are genetically manipulated by deletion or other types of mutations. In addition, although the accumulation of unfolded protein in the ER is now known to contribute to pathogenesis in a variety of diseases, there are still few therapeutic approaches that target these events. With a greater understanding of protein-folding processes, pharmacological intervention with chemical chaperones to promote proper folding becomes feasible, as observed with sodium phenylbutyrate for ∆508 CFTR (see Gelman and Kopito, this Perspective series, ref. 53). Future intervention should consider activation of different subpathways of the UPR or overexpression of appropriate protein chaperones, as in the case of overexpression of the J domain of cytosolic HSP70, which suppresses polyglutamine toxicity in flies (88). Treatments that activate the ERAD response may also ameliorate pathogenesis in a number of the conformational diseases.

Over the past ten years, tremendous progress has been made in understanding the mechanisms and physiological significance of the UPR. The processes of protein folding and secretion, transcriptional and translational activation, and protein degradation are intimately interconnected to maintain homeostasis in the ER. A variety of environmental insults, genetic disease, and underlying genetic modifiers of UPR function contribute to the pathogenesis of different disease states. As we gain a greater understanding of the mechanisms that control UPR activation, it should be possible to discover methods to activate or inhibit the UPR as desired for therapeutic benefit.

  1. Horwich, A. 2002. Protein aggregation in disease: a role for folding intermediates forming specific multimeric interactions. J. Clin. Invest. 110:1221–1232. doi:10.1172/JCI200216781.
  2. Ron, D. 2002. Translational control in the endoplasmic reticulum stress response. J. Clin. Invest. 110:1383–1388. doi:10.1172/JCI200216784.
  3. Lee, A.S. 1992. Mammalian stress response: induction of the glucose-regulated protein family. Curr. Opin. Cell Biol. 4:267–273.
  4. Kaufman, R.J., et al. 2002. The unfolded protein response in nutrient sensing and differentiation. Nat. Rev. Mol. Cell Biol. 3:411–421.
  5. Ellgaard, L., and Helenius, A. 2001. ER quality control: towards an understanding at the molecular level. Curr. Opin. Cell Biol. 13:431–437.
  6. Jakob, C.A., Burda, P., Te Heesen, S., Aebi, M., and Roth, J. 1998. Genetic tailoring of N-linked oligosaccharides: the role of glucose residues in glycoprotein processing of Saccharomyces cerevisiae in vivo. Glycobiology. 8:155–164.
  7. Travers, K.J., et al. 2000. Functional and genomic analyses reveal an essential coordination between the unfolded protein response and ER-associated degradation. Cell. 101:249–258.
    ……

 

Citation: Cell Death and Disease (2014) 5, e1578; doi:10.1038/cddis.2014.539
Published online 18 December 2014

An activated unfolded protein response promotes retinal degeneration and triggers an inflammatory response in the mouse retina
http://www.nature.com/cddis/journal/v5/n12/full/cddis2014539a.html

T Rana1, V M Shinde1, C R Starr1, A A Kruglov1, E R Boitet1, P Kotla1, S Zolotukhin2, A K Gross1 and M S Gorbatyuk1

  1. 1Department of Vision Sciences, University of Alabama at Birmingham, AL, USA
  2. 2Department of Pediatrics, University of Florida, FL, USA

Correspondence: M Gorbatyuk, Department of Vision Sciences, University of Alabama at Birmingham, 1670 University Boulevard, Birmingham, 35233 AL, USA. Tel: +1 205 934 6762; Fax: +1 205 934 3425; E-mail:mgortk@uab.edu

Received 20 July 2014; Revised 23 October 2014; Accepted 27 November 2014

Edited by P Ekert

Recent studies on the endoplasmic reticulum stress have shown that the unfolded protein response (UPR) is involved in the pathogenesis of inherited retinal degeneration caused by mutant rhodopsin. However, the main question of whether UPR activation actually triggers retinal degeneration remains to be addressed. Thus, in this study, we created a mouse model for retinal degeneration caused by a persistently activated UPR to assess the physiological and morphological parameters associated with this disease state and to highlight a potential mechanism by which the UPR can promote retinal degeneration. We performed an intraocular injection in C57BL6 mice with a known unfolded protein response (UPR) inducer, tunicamycin (Tn) and examined animals by electroretinography (ERG), spectral domain optical coherence tomography (SD-OCT) and histological analyses. We detected a significant loss of photoreceptor function (over 60%) and retinal structure (35%) 30 days post treatment. Analysis of retinal protein extracts demonstrated a significant upregulation of inflammatory markers including interleukin-1β (IL-1β), IL-6, tumor necrosis factor-α (TNF), monocyte chemoattractant protein-1 (MCP-1) and IBA1. Similarly, we detected a strong inflammatory response in mice expressing either Ter349Glu or T17M rhodopsin (RHO). These mutant rhodopsin species induce severe retinal degeneration and T17M rhodopsin elicits UPR activation when expressed in mice. RNA and protein analysis revealed a significant upregulation of pro- and anti-inflammatory markers such as IL-1β, IL-6, p65 nuclear factor kappa B (NF-kB) and MCP-1, as well as activation of F4/80 and IBA1 microglial markers in both the retinas expressing mutant rhodopsins. We then assessed if the Tn-induced inflammatory marker IL-1β was capable of inducing retinal degeneration by injecting C57BL6 mice with a recombinant IL-1β. We observed ~19%reduction in ERG a-wave amplitudes and a 29% loss of photoreceptor cells compared with control retinas, suggesting a potential link between pro-inflammatory cytokines and retinal pathophysiological effects. Our work demonstrates that in the context of an established animal model for ocular disease, the persistent activation of the UPR could be responsible for promoting retinal degeneration via the UPR-induced pro-inflammatory cytokine IL-1β.

Abbreviations: 

ERG, electroretinography; SD-OCT, spectral domain optical coherence tomography; UPR, unfolded protein response; IL-1β, Interleukin-1β; TNF-α, tumor necrosis factor-α; MCP-1, monocyte chemoattractant protein-1; NF-kB, ; nuclear factor kappa B, ; ER, endoplasmic reticulum; ADRP, autosomal dominant retinitis pigmentosa; RHO, rhodopsin; ERAI, ER stress activated indicator; Tn, tunicamycin; ONL, outer nuclear layer; H&E, hematoxylin and eosin; ONH, optic nerve head

 

ER stress and neuroinflammation: connecting the unfolded protein response to JAK/STAT signaling (P5196)

Gordon Meares,1 and Etty Benveniste1

1Department of Cell, Developmental and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL

J Immunol May 2013 190 (Meeting Abstract Supplement) 198.5

http://www.jimmunol.org/cgi/content/meeting_abstract/190/1_MeetingAbstracts/198.5

Neuroinflammation and endoplasmic reticulum (ER) stress are associated with many neurological diseases. ER stress is brought on by misfolded proteins. In turn, cells respond with activation of the unfolded protein response (UPR). The UPR is a highly conserved pathway that transmits both adaptive and apoptotic signals to restore homeostasis or eliminate the irreparably damaged cell. Recent evidence indicates that ER stress and inflammation are linked. In this study, we have examined the interaction between ER stress and JAK/STAT-dependent inflammation in astrocytes. The JAK/STAT pathway mediates the biological actions of many cytokines and growth factors. We have found that ER stress leads to the activation of STAT3 in a JAK1-dependent fashion. ER stress-induced activation of the JAK1/STAT3 axis leads to expression of IL-6 and several chemokines. The activation of STAT3 signaling is dependent on the protein kinase PERK, a central component of the UPR. Knockdown of PERK abrogates ER stress-induced activation of STAT3 and overexpression of PERK is sufficient to activate STAT3. Additionally, ER stressed astrocytes, via paracrine signaling, can stimulate activation of microglia leading to production of oncostatin M (OSM). OSM can then synergize with ER stress in astrocytes to drive inflammation. Together, this work describes a new PERK-JAK1-STAT3 signaling pathway that may elicit a feed-forward inflammatory loop involving astrocytes and microglia to drive neuroinflammation.

 

Neural Plasticity
Volume 2014 (2014), Article ID 610343, 15 pages
http://dx.doi.org/10.1155/2014/610343

Review Article

Surveillance, Phagocytosis, and Inflammation: How Never-Resting Microglia Influence Adult Hippocampal Neurogenesis

Amanda Sierra,1,2,3 Sol Beccari,2,3 Irune Diaz-Aparicio,2,3 Juan M. Encinas,1,2,3 Samuel Comeau,4,5 and Marie-Ève Tremblay4,5

1Ikerbasque Foundation, 48011 Bilbao, Spain
2Achucarro Basque Center for Neuroscience, Bizkaia Science and Technology Park, 48170 Zamudio, Spain
3Department of Neurosciences, University of the Basque Country, 48940 Leioa, Spain
4Centre de Recherche du CHU de Québec, Axe Neurosciences, Canada G1P 4C7
5Département de Médecine Moléculaire, Université Laval, Canada G1V 4G2

Received 10 December 2013; Accepted 11 February 2014; Published 19 March 2014

Academic Editor: Carlos Fitzsimons

http://www.hindawi.com/journals/np/2014/610343/

Microglia cells are the major orchestrator of the brain inflammatory response. As such, they are traditionally studied in various contexts of trauma, injury, and disease, where they are well-known for regulating a wide range of physiological processes by their release of proinflammatory cytokines, reactive oxygen species, and trophic factors, among other crucial mediators. In the last few years, however, this classical view of microglia was challenged by a series of discoveries showing their active and positive contribution to normal brain functions. In light of these discoveries, surveillant microglia are now emerging as an important effector of cellular plasticity in the healthy brain, alongside astrocytes and other types of inflammatory cells. Here, we will review the roles of microglia in adult hippocampal neurogenesis and their regulation by inflammation during chronic stress, aging, and neurodegenerative diseases, with a particular emphasis on their underlying molecular mechanisms and their functional consequences for learning and memory.

  1. Microglia: The Resident Immune Cells of the Brain

Microglia were first described in 1919 by the Spanish neuroanatomist Pío del Río Hortega, a disciple of the renowned Santiago Ramón y Cajal, almost half a century later than neurons and astrocytes and just before oligodendrocytes [1]. This delayed appearance into the neuroscience arena is still apparent today, as microglia remain one of the least understood cell types of the brain. Traditionally, microglia were simply considered as “brain macrophages” controlling the inflammatory response during acute insults and neurodegenerative conditions, and only recently was their unique origin revealed. Indeed, microglia were shown to derive from primitive myeloid progenitors of the yolk sac that invade the central nervous system (CNS) during early embryonic development (reviewed in [2]). In contrast, circulating monocytes and lymphocytes, as well as most tissue macrophages, derive from hematopoietic stem cells located initially in the foetal liver and later in the bone marrow [3]. In the adult brain, the microglial population is maintained exclusively by self-renewal during normal physiological conditions [2]. As a consequence, microglia are the only immune cells which permanently reside in the CNS parenchyma, alongside neural tube-derived neurons, astrocytes, and oligodendrocytes.

These past few years, unprecedented insights were also provided into their extreme dynamism and functional behaviour, in health as much as in disease. Indeed, microglia were revealed to be exceptional sensors of their environment, responding on a time scale of minutes to even subtle variations of their milieu, by undergoing concerted changes in morphology and gene expression [45]. During pathological insults, “activated” microglia were particularly shown to thicken and retract their processes, extend filopodia, proliferate and migrate, release factors and compounds influencing neuronal survival (such as proinflammatory cytokines, trophic factors, reactive oxygen species (ROS), etc.), and phagocytose pathogens, degenerating cells and debris, thus providing better understanding of their roles in orchestrating the inflammatory response [6]. These abilities as immune cells are also recruited during normal physiological conditions, where “surveillant” microglia further participate in the remodeling of neuronal circuits by their phagocytic elimination of synapses and their regulation of glutamatergic receptors maturation and synaptic transmission, among other previously unexpected roles [79], in addition to their crucial involvement in the phagocytic elimination of newborn cells in the context of adult neurogenesis [10].

Our review will discuss the emerging roles of microglia in adult hippocampal neurogenesis and their regulation by inflammation during chronic stress, aging, and neurodegenerative diseases, with a particular emphasis on their underlying molecular mechanisms and their functional consequences for learning and memory (Figure 1).

 

http://www.hindawi.com/journals/np/2014/floats/610343/thumbnails/610343.fig.001_th.jpg

Figure 1: The effects of surveillant and inflammatory microglia on the adult hippocampal neurogenic cascade. During physiological conditions, surveillant microglia effectively phagocytose the excess of apoptotic newborn cells and may release antineurogenic factors such as TGF. This anti-inflammatory state is maintained by neuronal (tethered or released) fractalkine. Enriched environment drives microglia towards a phenotype supportive of neurogenesis, via the production of IGF-1. In contrast, inflammatory challenge triggered by LPS, irradiation, aging, or AD induces the production of proinflammatory cytokines such as IL-1, TNF, and IL-6 by microglia as well as resident astrocytes and infiltrating monocytes, neutrophils, and lymphocytes. These cytokines have profound detrimental effects on adult neurogenesis by reducing the proliferation, survival, integration, and differentiation of the newborn neurons and decreasing their recall during learning and memory paradigms.

  1. A Brief Overview of Adult Hippocampal Neurogenesis

Adult hippocampal neurogenesis is continuously maintained by the proliferation of neural stem cells located in the subgranular zone (SGZ) [1113]. These neuroprogenitors have been named “radial glia-like cells” (rNSCs), or type 1 cells, since they morphologically and functionally resemble the embryonic radial glia. They have also been defined as “quiescent neuroprogenitors” because only a small percentage of the population is actively dividing during normal physiological conditions. The lineage of these cells is frequently traced by using analogs of the nucleotide thymidine, such as bromodeoxyuridine (BrdU) which gets incorporated into the DNA of dividing cells during the S phase and can be detected by immunofluorescence. Alternatively, their lineage can be traced by labeling with fluorescent reporters which are delivered to dividing cells by retroviral vectors or expressed by specific cell type promoters via inducible transgenic mice (for a review of the methods commonly used to study adult neurogenesis, see [14]). The daughter cells of rNSCs, also called type 2 cells or amplifying neuroprogenitors (ANPs), rapidly expand their pool by proliferating before becoming postmitotic neuroblasts. Within a month, these neuroblasts differentiate and integrate as mature neurons into the hippocampal circuitry [15]. They however display unique electrophysiological characteristics during several months, being more excitable than mature neurons [16], and constitute a special cell population that is particularly inclined to undergo synaptic remodeling and activity-dependent plasticity [17].

These unique properties of the newborn neurons and the neurogenic cascade in general suggested that adult hippocampal neurogenesis could play an important role in hippocampal-dependent functions that require extensive neuroplasticity such as learning and memory. Indeed, activity-dependent plasticity and learning are long known for modulating adult neurogenesis in a complex, yet specific manner, with adult hippocampal neurogenesis being influenced by learning tasks which depend on the hippocampus [4445]. For instance, hippocampal-dependent learning paradigms were found to regulate the survival of newborn neurons, in a positive manner that depends on the timing between their birth and the phases of learning [4647]. Young (1.5–2 months old) newborn neurons were also shown to be preferentially activated during memory recall in a water maze task, compared to mature neurons, as determined by colabeling of BrdU with immediate early genes such as c-Fos and Arc, in which expression correlates with neuronal firing [48]. Nonetheless, it has only been in the last few years that loss-of-function and gain-of-function approaches with inducible transgenic mice were able to confirm that adult hippocampal neurogenesis is necessary for synaptic transmission and plasticity, including the induction of long-term potentiation (LTP) and long-term depression [49], as well as trace learning in conditioned protocols [50], memory retention in spatial learning tasks [5152], and encoding of overlapping input patterns, that is, pattern separation [53].

Adult hippocampal neurogenesis and its functional implications for learning and memory are however influenced negatively by a variety of conditions that are commonly associated with microglial activation and inflammation in the brain, such as chronic stress, aging, and neurodegenerative diseases, as we will review herein. Indeed, inflammation caused by irradiation produces a sustained inhibition of neurogenesis, notably by decreasing the proliferation and neuronal differentiation of the progenitors, and therefore, exposure to therapeutic doses of cranial irradiation has been widely used for modulating neurogenesis experimentally before the development of more specific approaches [54].

  1. Regulation of Adult Hippocampal Neurogenesis by Inflammation

Inflammation is a natural bodily response to damage or infection that is generally mediated by proinflammatory cytokines such as interleukin 1 beta (IL-1), interleukin 6 (IL-6), and tumour necrosis factor alpha (TNF), in addition to lipidic mediators such as prostaglandins and leukotrienes. Oftentimes, it is associated with an increased production of ROS, as well as nitric oxide (NO). Together, these proinflammatory mediators lead to an increase in local blood flow, adhesion, and extravasation of circulating monocytes, neutrophils, and lymphocytes [55]. In the brain, microglia are the main orchestrator of the neuroinflammatory response, but other resident cell types, including astrocytes, endothelial cells, mast cells, perivascular and meningeal macrophages, and even neurons, can produce proinflammatory mediators, though perhaps not to the same extent as microglia [56]. In addition, peripheral immune cells invading the CNS during inflammation can further produce proinflammatory mediators, but the respective contribution of microglia versus other cell types in the inflammatory response of the brain is poorly understood.

The harmful effects of inflammation are also widely determined by the actual levels of proinflammatory mediators released, rather than the occurrence or absence of an inflammatory response in itself. For instance, TNF regulates synaptic plasticity by potentiating the cell surface expression of AMPA glutamatergic receptors, thus resulting in a homeostatic scaling following prolonged blockage of neuronal activity during visual system development [57]. However, TNF also produces differential effects at higher concentrations,ranging from an inhibition of long-term potentiation to an enhancement of glutamate-mediated excitotoxicityin vitro [58]. Inflammation induced by chronic ventricular infusion of bacterial lipopolysaccharides (LPS; a main component of the outer membrane of Gram-negative bacteria), that is, the most widely used method for inducing an inflammatory challenge, also increases ex vivo the hippocampal levels of TNF and IL-1, thereby impairing novel place recognition, spatial learning, and memory formation, but all these cognitive deficits can be restored by pharmacological treatment with a TNF protein synthesis inhibitor, a novel analog of thalidomide, 3,6′-dithiothalidomide [59].

The impact of inflammation on adult hippocampal neurogenesis was originally discovered by Olle Lindvall and Theo Palmer’s groups in 2003, showing that systemic or intrahippocampal administration of LPS reduces the formation of newborn neurons in the adult hippocampus, an effect that is prevented by indomethacin, a nonsteroidal anti-inflammatory drug (NSAID) which inhibits the synthesis of proinflammatory prostaglandins [6061]. Similarly, inflammation can determine the increase in neurogenesis that is driven by seizures, a context in which neurogenesis can be prevented by LPS and increased by the anti-inflammatory antibiotic minocycline [60]. In these studies, hippocampal proliferation remained unaffected by LPS or minocycline and thus it is likely that inflammation targeted the survival of newborn cells [6061], as LPS is known to increase SGZ apoptosis [62]. Inflammation also has further downstream effects on the neurogenic cascade. For instance, LPS increases the number of thin dendritic spines and the expression of the excitatory synapses marker “postsynaptic density protein of 95kDa” (PSD95) in newborn neurons. LPS in addition increases the expression of GABAA receptors at early stages of synapse formation, leading to suggesting a possible imbalance of excitatory and inhibitory neurotransmission in these young neurons [63]. Finally, LPS also prevents the integration of newborn neurons into behaviourally relevant networks, including most notably their activation during spatial exploration, as determined by the percentage of BrdU cells colabeled with the immediate early gene Arc [64].

Importantly, none of these manipulations is specific to microglia and may directly or indirectly affect other brain cells involved in the inflammatory response of the brain. For instance, both LPS and minocycline affect astrocytic function in vitro and in vivo [6569]. Furthermore, LPS is known to drive infiltration of monocytes and neutrophils into the brain parenchyma [70]. Monocytes and neutrophils produce major proinflammatory mediators and could therefore act on the neurogenic cascade as well. The implication of microglia in LPS-induced decrease in neurogenesis is nonetheless supported in vivo by the negative correlation between the number of newborn neurons (BrdU+, NeuN+ cells) and the number of “activated” microglia (i.e., expressing ED1) [60]. ED1, also called CD68 or macrosialin, is a lysosomal protein which is overexpressed during inflammatory challenge. While the location of ED1 previously suggested its involvement in phagocytosis, its loss of function did not result in phagocytosis deficits and thus, its function still remains unknown (reviewed in [10]). The number of ED1-positive microglia also negatively correlates with neurogenesis during inflammation provoked by cranial irradiation [61]. While correlation does not involve causation, nor can pinpoint to the underlying mechanism, these experiments were the first to reveal a potential role for “activated” microglia in the regulation of adult hippocampal neurogenesis. More direct evidence of microglial mediation in LPS deleterious effects was obtained from in vitro experiments, as it was shown that conditioned media from LPS-challenged microglia contained IL-6, which in turn caused apoptosis of neuroblasts [61]. Nonetheless, astrocytes can also release IL-6 when stimulated with TNF or IL-1 [71] and chronic astrocytic release of IL-6 in transgenic mice reduced proliferation, survival, and differentiation of newborn cells, thus resulting in a net decrease in neurogenesis [72]. In summary, while the detrimental impact of inflammation on neurogenesis is well established, more work is needed to define the specific roles played by the various inflammatory cells populating the brain.

  1. Inflammation Associated with Chronic Stress

Across health and disease, the most prevalent condition that is associated with neuroinflammation is “chronic stress,” which commonly refers to the repeated or sustained inability to cope with stressful environmental, social, and psychological constraints. Chronic stress is characterized by an imbalanced secretion of glucocorticoids by the hypothalamic-pituitary-adrenal (HPA) axis (most notably cortisol in humans and corticosterone in rodents), which leads to an altered brain remodeling, massive loss of synapses, and compromised cognitive function [73]. In particular, an impairment of spatial learning, working memory, novelty seeking, and decision making has been associated with chronic stress [74]. Glucocorticoids are well known for their anti-inflammatory properties, as they interfere with NF-B-mediated cytokine transcription, ultimately delaying wound healing [75]. They are also potent anti-inflammatory mediators in vivo [76] and in purified microglia cultures [77]. Recently, repeated administration of high doses of glucocorticoids by intraperitoneal injection, to mimic their release by chronic stress, was also shown to induce a loss of dendritic spines in the motor cortex, while impairing learning of a motor task. A transcription-dependent pathway acting downstream of the glucocorticoid receptor GR was proposed [7879] but the particular cell types involved were not identified.

Microglia are considered to be a direct target of the glucocorticoids, as they were shown to express GR during normal physiological conditions in vivo [77]. In fact, transgenic mice lacking GR in microglia and macrophages show an increased production of proinflammatory mediators (including TNF and IL-1) and greater neuronal damage in response to an intraparenchymal injection of LPS, compared to wild-type mice [80]. In contrast, glucocorticoids are considered to be proinflammatory in the chronically stressed brain [81], where among other changes they can promote inflammation, oxidative stress, neurodegeneration, and microglial activation [82]. For example, repeated restraint stress induces microglial proliferation and morphological changes, including a hyperramification of their processes in the adult hippocampus following restraint stress [83], but a nearly complete loss of processes in the context of social defeat [84]. Prenatal restraint stress also causes an increase in the basal levels of TNF and IL-1, while increasing the proportion of microglia showing a reactive morphology in the adult hippocampus [85]. Similarly, social defeat leads to an enhanced response to the inflammatory challenge induced by intraperitoneal injection of LPS, including an increased production of TNF and IL-1, and expression of inducible NO synthase (iNOS) by microglia, accompanied by an increased infiltration of circulating monocytes [8486]. Therefore, microglia are a strong candidate for mediating some of the effects of stress on adult neurogenesis, as will be discussed below, in synergy with other types of inflammatory cells.

Chronic stress is well known for its negative effects on hippocampal neurogenesis (reviewed in [8788]), although not all stress paradigms are equally effective [89]. Several stress paradigms can decrease neuroprogenitors proliferation in the tree shrew [90] and in mice [9192], although this effect seems to be compensated by an increased survival of newborn neurons [92] and whether stress results in a net increase or decrease in neurogenesis remains controversial (reviewed in [8788]). The effects of stress on adult neurogenesis seem to be mediated at least partially by glucocorticoids, because mice lacking a single copy of the GR gene show behavioural symptoms of depression including learned helplessness, neuroendocrine alterations of the HPA axis, and impaired neurogenesis [93]. In parallel, chronic stress is associated with an increased inflammatory response, which may inhibit neurogenesis as well. For instance, serum levels of IL-1and IL-6 are significantly increased in depressed patients [94]. In mice, restraint stress leads to a widespread activation of NF-B in the hippocampus, including at the level of neuroprogenitors [95] and increased protein levels of IL-1 [96]. In addition to the direct role of glucocorticoids, IL-1 also seems to mediate some of the effects of mild chronic stress, because in vivo manipulations that block IL-1 (either pharmacologically or in null transgenic mice) prevent the anhedonic stress response and the antineurogenic effect of stress [9196]. Moreover, the corticoids and IL-1 pathways may regulate each other in a bidirectional manner because the administration of a GR antagonist can blunt the LPS-induced production of hippocampal IL-1 in stressed mice [97], whereas mice knockout for the IL-1 receptor (IL-1R1) fail to display the characteristic elevation of corticosterone induced by mild chronic stress [96]. Another stress-related cytokine, IL-6, induces depressive phenotypes and prevents the antidepressant actions of fluoxetine when administered to mice in vivo [98]. So far the effects of stress on neurogenesis via corticosteroids and inflammation have been assumed to be cell autonomous, as neuroprogenitors express both GR [99] and IL-1R1 [95]. The potential participation of microglia is yet to be determined, but there are some reports of a direct effect of stress on microglial activation. For instance, microglia acutely isolated from mice subjected to acute stress (by inescapable tail shock) showed a primed response to LPS challenge by producing higher levels of IL-1 mRNA ex vivo [100], and the specific loss of expression of GR in microglia leads to a blunted inflammatory response in vitro and to a decreased neuronal damage in vivo in response to LPS [80]. In stress paradigms, these enhanced responses of microglia to inflammatory challenges are similar to their age-related “priming” which has been associated with and is possibly due to an increased basal production of proinflammatory mediators. However, whether microglia express increased levels of IL-1 and other proinflammatory cytokines in response to stressful events is presently unclear [101]. It is thus possible that some of the antineurogenic effects of stress are exerted by means of microglial-dependent inflammation, but this hypothesis remains to be experimentally tested.

  1. Inflammation Associated with Aging and Neurodegenerative Diseases

Inflammation is also commonly associated with normal aging and neurodegenerative diseases and, therefore, could represent a putative underlying mechanism that explains their decrease in hippocampal neurogenesis. Nonetheless, inflammation is also associated with neurological diseases, such as epilepsy or stroke, where neurogenesis is thought to be increased, although the data from rodents and humans is somewhat conflictive [102]. Neurogenesis is well known to decline throughout adulthood and normal aging in rodents and humans [103104], but the decay is more pronounced and occurs later in life in mice than in humans [105]. The aging-associated decrease in neurogenesis has been shown to occur mainly as a consequence of exhaustion of the rNSC population which, after being recruited and activated, undergo three rounds of mitosis in average and then terminally differentiate into astrocytes [12106]. In addition, a reduced mitotic capacity of the neuroprogenitors could further contribute to decreasing neurogenesis [106], and moreover, an age-related increase in the levels of proinflammatory cytokines could also hinder neurogenesis in the aging brain. Serum levels of IL-1, IL-6, and TNF are elevated in elderly patients [107108]. Aged microglia express higher levels of these proinflammatory cytokines and show a greater response to LPS inflammatory challenge, that is, a “primed” response, than their younger counterparts [109]. The origin of this low-grade age-related inflammation (“inflamm-aging” [110]) remains unknown and may be related to both aging and damage to the surrounding neurons, as well as aging of the immune system per se.

At the cellular level, stress to the endoplasmic reticulum (ER) caused by various perturbations, such as nutrient depletion, disturbances in calcium or redox status, or increased levels of misfolded proteins, can induce a cell-autonomous inflammatory response to neurons. Stress to the ER, a multifunctional organelle which is involved in protein folding, lipid biosynthesis, and calcium storage triggers a homeostatic response mechanism named the unfolding protein response (UPR), aiming to clear the unfolded proteins in order to restore normal ER homeostasis [111]. However, if the ER stress cannot be resolved, the UPR also initiates inflammatory and apoptotic pathways via activation of the transcription factor NF-B which controls the expression of most proinflammatory cytokines [112]. In the brain, ER stress is often initiated by the formation of abnormal protein aggregates in several neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), amyotrophic lateral sclerosis (ALS), Huntington’s disease (HD), and prion-related disorders [113]. This neurodegeneration-associated ER stress is assumed to occur mostly in neurons, but there are some examples of microglial protein misfolding as well. For instance, both microglia and neurons overexpress CHOP (C/EBP homologous protein), a transcription factor which is activated during ER stress in human patients and mouse models of ALS [114]. Inflammation has been speculated to be a main negative contributor to the pathology of ALS [115], but a direct microglial involvement in mediating the inflammatory response to abnormal protein aggregation in ALS and other neurodegenerative conditions remains to be tested. Finally, ER stress has been linked to a variety of inflammatory conditions [116117], including chronic stress, diet-induced obesity, and drug abuse, as well as atherosclerosis and arthritis [118120]. During normal aging, a progressive decline in expression and activity of key ER molecular chaperones and folding enzymes could also compromise the adaptive response of the UPR, thereby contributing to the age-associated decline in cellular functions [118]. Therefore, aging is strongly associated with a chronic ER stress which leads to increased activation of NF-B [112]; however, the contribution of the different brain cell types to “inflamm-aging” is still poorly understood. The detrimental effects on neurogenesis of increased proinflammatory cytokines in the aging brain are not necessarily related to microglia, but also to stressed neurons. Furthermore, ER stress may also cause a cell-autonomous response in neural stem cells [121], although its impact on neurogenesis remains to be experimentally determined.

In addition, aging is accompanied by an increased level of mitochondrial oxidative stress, which in turn activates the “Inflammasome” [122], a group of multimeric proteins comprising the interleukin 1 converting enzyme (ICE, caspase 1) which serves to release the active form of the cytokine [123]. IL-1 may act directly on rNSCs (visualised by labeling with the Sox2 marker), as they express IL-1R1 in the adult hippocampus [91]. Treatment with IL-1 decreases hippocampal proliferation in young mice [91] and pharmacological inhibition of ICE partially restores the number of newborn neurons in aged mice without significantly affecting their differentiation rate [124]. Transgenic IL-1 overexpression results in chronic inflammation and depletion of doublecortin-labeled neuroblasts, thus mimicking the aging-associated depletion of neurogenesis [125]. The actual mechanism of action of IL-1 on neurogenesis in aged mice, including decreased proliferation of rNSCs/ANPs and survival of newborn neurons, remains undetermined. Microglia are a main source of IL-1in the aging brain, but the hypothesis that microglia-derived IL-1 is responsible for depleting neurogenesis in the aging brain remains to be directly tested.

The regulation of neurogenesis by IL-1 in the aging brain has been further linked to the activity of another cytokine, the chemokine fractalkine, or CX3CL1. Fractalkine has soluble and membrane-tethered forms and is exclusively expressed by neurons, while the fractalkine receptor (CX3CR1) is expressed in the brain by microglia alone [126]. This module forms a unique neuron-microglia signalling unit that controls the extent of microglial inflammation in several neurodegenerative conditions including PD, ALS [127], or AD [128]. In fact, CX3CR1 blocking antibodies increase the production of hippocampal IL-1 when administered to young adult rats [129]. Importantly, chronic treatment with fractalkine increases hippocampal proliferation and the number of neuroblasts in aged (22 months old) but not young (3 months old) or middle-aged rats (12 months old), whereas an antagonists of CX3CR1 has the opposite effects in young, but not in middle-aged nor old rats [129]. Since fractalkine expression is decreased during aging [129], a reduced neuron-microglia signalling might be releasing the brake on microglial contribution to inflammatory responses, although increased levels of fractalkine were instead reported in aged rat hippocampus by other studies [68]. Additional insights into the role of fractalkine signalling come from knock-in mice in which the endogenous CX3CR1 locus is replaced by the fluorescent reporter GFP [126]. The initial studies suggested that  (i.e., ) mice have no significant differences in brain development and functions [130], but more systematic investigations recently revealed a long list of hippocampal-dependent changes in young (3 months old)  and  mice compared to wild-type mice. These changes notably included decreased neuroprogenitors proliferation and neuroblasts number, impaired LTP, performance in contextual fear conditioning and water maze spatial learning and memory, and, importantly, increased IL-1 protein levels [131]. The signalling pathway of fractalkine-IL-1 is functionally relevant, because IL-1R1 antagonists rescued LTP and cognitive function in  mice [131]. In sum, even though neuronal fractalkine seems to be sufficient for restraining the inflammatory activity of microglia in young rats, its downregulation during aging could activate the microglial inflammatory response and thereby subsequently reduce the proliferation of remaining neuroprogenitors.

In AD, inflammatory cytokines such as IL-1 are overexpressed in the microglia associated with the amyloid beta (A) plaques of postmortem samples [132] and in transgenic mice modeling the disease [133]. The loss of synapses (from hippocampus to frontal cortex) is one of the main pathological substrates in this disease, but adult neurogenesis is also severely reduced in most mouse models of AD, possibly due to a decreased proliferation of neuroprogenitors and a decreased survival of newborn cells, even though the putative changes in the neurogenic cascade in postmortem samples remain controversial (reviewed in [102]). This lack of agreement is possibly explained by the fact that the vast majority of AD cases have a late onset over 65 years of age, when little neurogenesis remains. In contrast, in most transgenic AD mouse models, the Aaccumulation, cognitive deficits, and changes in neurogenesis are already detectable in young animals (2-3 months old). The study of AD is further hindered by the difficulty in comparing the time course and pathology across different mouse models. For instance, early treatment with minocycline can improve cognition and reduce A burden in mice expressing the human amyloid precursor protein (APP) [134]. In contrast, in mice expressing APP and a mutated form of presenilin 1 (PS1), which is part of the  secretase pathway that cleaves A, inflammation is reduced without any detectable changes in A plaques deposition [135]. Concomitantly with a decrease in tissue inflammatory cytokines and number of microglial cells, minocycline restores neurogenesis and hippocampus-dependent memory deficits in these APP/PS1 mice [135], indirectly suggesting that cognitive decay in AD may be at least in part related to a detrimental effect of inflammation on hippocampal neurogenesis. Direct evidence that neurogenesis is associated with the cognitive performance in AD is still lacking. Further research is also necessary to determine the neurogenic targets of AD-related inflammation. One central open question for future therapies aiming at increasing neurogenesis and cognition in AD is whether neuroprogenitors are spared or whether their age-induced loss becomes accelerated. Rather than increasing the proliferation and neurogenic output of the few rNSCs remaining in an old AD brain, it may be more relevant to develop strategies that prevent the age-related loss of neuroprogenitors in presymptomatic patients.

In summary, inflammation associated with a wide variety of experimental models of disease produces strong detrimental effects on hippocampal neurogenesis. These effects on human neurogenesis are however not so well described and, in vitro, IL-1 increases the proliferation of hippocampal embryonic neuroprogenitors but decreases their differentiation into neurons [136]. Novel methods to assess hippocampal neurogenesis in the living human brain, from metabolomics of neuroprogenitors to hippocampal blood brain volume (reviewed in [102]), will help to determine the contribution of inflammation to adult neurogenesis in the healthy and diseased human brain during aging.

  1. Normal Physiological Conditions

In the healthy mature brain, microglia are an essential component of the neurogenic SGZ niche, where they physically intermingle with neuroprogenitors, neuroblasts, and newborn neurons [62]. Here, surveillant microglia effectively and rapidly phagocytose the excess of newborn cells undergoing apoptosis [62]. Importantly, microglial phagocytosis in the adult SGZ is not disturbed by inflammation associated with aging or by LPS challenge, as the phagocytic index (i.e., the proportion of apoptotic cells completely engulfed by microglia) is maintained over 90% in these conditions [62]. Nonetheless, the consequences of microglial phagocytosis on adult hippocampal neurogenesis remain elusive. Treatment of mice with annexin V, which binds to the phosphatidylserine (PS) receptor and prevents the recognition of PS on the surface of apoptotic cells, presumably blocking phagocytosis, increases the number of apoptotic cells in the SGZ [40]. Concomitantly, annexin V reduces neurogenesis by decreasing the survival of neuroblasts without affecting neuroprogenitors proliferation [40]. Similar results were obtained in transgenic mice knock-out for ELMO1, a cytoplasm protein which promotes the internalization of apoptotic cells, although the effects on neurogenesis were ascribed to a decreased phagocytic activity of neuroblasts [40]. The actual phagocytic target of the neuroblasts remains undetermined, but the newborn apoptotic cells in the adult SGZ are exclusively phagocytosed by microglia, at least in physiological conditions [62]. Nevertheless, none of the above manipulations has specifically tested the role of microglial phagocytosis in hippocampal-dependent learning and memory and thus, the functional impact of microglial phagocytosis in adult neurogenic niches during normal physiological conditions remains to be elucidated.

Microglial phagocytosis of apoptotic cells is actively anti-inflammatory, at least in vitro, and thus it has been hypothesized that anti-inflammatory cytokines produced by phagocytic microglia may further regulate neurogenesis [10]. For instance, transforming growth factor beta (TGF), which is produced by phagocytic microglia in vitro [137], inhibits the proliferation of SGZ neuroprogenitors [138]. Microglia are further able to produce proneurogenic factors in vitro [139]. When primed with cytokines associated with T helper cells such as interleukin 4 (IL-4) or low doses of interferon gamma (IFN), cultured microglia support neurogenesis and oligodendrogenesis through decreased production of TNF and increased production of insulin-like growth factor 1 (IGF-1) [139], an inducer of neuroprogenitor proliferation [26]. A list of potential factors produced by microglia and known to act on neuroprogenitor proliferation can be found in Table 1. In addition, recent observations suggest that neuroprogenitor cells may not only regulate their own environment, but also influence microglial functions. For instance, vascular endothelial growth factor (VEGF) produced by cultured neuroprecursor cells directly affects microglial proliferation, migration, and phagocytosis [20]. More potential factors produced by neuroprogenitors shown to be influencing microglial activity and function can be found in Table 2. However, it has to be taken into account that most of these observations were obtained in culture and that further research is needed in order to elucidate whether those factors are also secreted and have the same regulatory responses in vivo.

Table 1: Summary of factors secreted by microglia and the potential effect they have on neuroprogenitors in vitro.
Microglia secreted
factors
Reference Modulation of neural progenitor cells Reference
BDNF [18] Differentiation [19]
EGF [20] Survival, expansion, proliferation, differentiation [21]
FGF [22] Survival and expansion [23]
GDNF [24] Survival, migration, and differentiation [25]
IGF-1 [21] Proliferation [26]
IL-1 [27] Reduction in migration [27]
IL-6 [28] Inhibition of neurogenesis [29]
IL-7 [20] Differentiation [30]
IL-11 [20] Differentiation [30]
NT-4 [24] Differentiation [31]
PDGF [32] Expansion and differentiation [33]
TGF [34] Inhibition of proliferation [19]

 

Table 1: Summary of factors secreted by microglia and the potential effect they have on neuroprogenitors in vitro.

http://www.hindawi.com/journals/np/2014/610343/tab1/

 

 

Table 2: Summary of factors secreted by neuroprogenitors and the potential effect they have on microglia in vitro.

NPC secreted factors Reference Modulation of microglia Reference
BDNF [18] Proliferation and induction of phagocytic activity [35]
Haptoglobin [24] Neuroprotection [36]
IL-1 [37] Intracellular Ca+2 elevation and proliferation [22]
IL-6 [37] Increase in proliferation [38]
M-CSF [20] Mitogen [39]
NGF [40] Decrease in LPS-induced NO [41]
TGF [37] Inhibition of TNF secretion [42]
TNF [37] Upregulation of IL-10 secretion [43]
VEGF [20] Induction of chemotaxis and proliferation [20]

http://www.hindawi.com/journals/np/2014/floats/610343/thumbnails/610343.tab2_th.jpg

Table 2: Summary of factors secreted by neuroprogenitors and the potential effect they have on microglia in vitro.

In addition, microglial capacity to remodel and eliminate synaptic structures during normal physiological conditions has suggested that microglia could also control the synaptic integration of the newborn neurons generated during adult hippocampal neurogenesis [140]. Three main mechanisms were proposed: (1) the phagocytic elimination of nonapoptotic axon terminals and dendritic spines, (2) the proteolytic remodeling of the perisynaptic environment, and (3) the concomitant structural remodeling of dendritic spines [7140]. Indeed, microglial contacts with synaptic elements are frequently observed in the cortex during normal physiological conditions, sometimes accompanied by their engulfment and phagocytic elimination [141143], as in the developing retinogeniculate system [144]. Microglial cells are distinctively surrounded by pockets of extracellular space, contrarily to all the other cellular elements [142], suggesting that microglia could remodel the volume and geometry of the extracellular space, and thus the concentration of various ions, neurotransmitters, and signalling molecules in the synaptic environment. Whether microglia create the pockets of extracellular space themselves or not remains unknown, but these pockets could result from microglial release of extracellular proteases such as metalloproteinases and cathepsins [145], which are well known for influencing the formation, structural remodeling, and elimination of dendritic spines in situ and also experience-dependent plasticity in vivo [7146]. More recently, microglial phagocytosis of synaptic components was also observed in the developing hippocampus, in the unique time window of synaptogenesis, a process which is notably regulated by fractalkine-CX3CR1 signalling [147]. Therefore, the attractive hypothesis that microglial sculpts the circuitry of newborn cells in the adult hippocampus deserves further attention.

Lastly, microglia were also involved in increasing adult hippocampal neurogenesis in the enriched environment (EE) experimental paradigm. EE is a paradigm mimicking some features of the normal living circumstances of wild animals, as it gives them access to social interactions, toys, running wheels, and edible treats. EE has long been known to enhance neurogenesis by acting on newborn cells survival, resulting ultimately in an enlargement of the dentate gyrus [148]. Functionally, these changes are accompanied by enhanced spatial learning and memory formation with the water maze paradigm [149]. Similar increases in neurogenesis are obtained by subjecting mice to voluntary running paradigms, although in this case the effect is mediated by increased neuroprogenitor proliferation [150]. During inflammatory conditions, EE is antiapoptotic and neuroprotective [151] and it limits the hippocampal response to LPS challenge by decreasing the expression of several cytokines and chemokines, including IL1- and TNF [152]. In fact, EE is believed to counteract the inflammatory environment and rescue the decreased number of neuroblasts in mice compared to wild-type mice [153]. The effects of EE are independent of the IL-1 signalling pathway, as it increases neurogenesis in mice that are null for IL-1R1 [154]. EE also induces microglial proliferation and expression of the proneurogenic IGF-1 [155], but the full phenotype of microglia in EE compared to standard housing and its impact on the neurogenic cascade remains to be determined.

The mechanisms behind the anti-inflammatory actions of EE are unknown, but they were suggested to involve microglial interactions with T lymphocytes through an increased expression of the major histocompatibility complex of class II (MHC-II) during EE [155]. MHC-II is responsible for presenting the phagocytosed and degraded antigens to the antibodies expressed on the surface of a subtype of T lymphocytes (T helper or CD4+ cells), thus initiating their activation and production of antigen-specific antibodies. Severe combined immunodeficient (SCID) mice lacking either T and B lymphocytes or nude mice lacking only T cells have impaired proliferation and neurogenesis in normal and EE housing compared to wild-type mice [155], as well as impaired performance in the water maze [156]. Similarly, antibody-based depletion of T helper lymphocytes impairs basal and exercise-induced proliferation and neurogenesis [157]. Furthermore, a genetic study in heterogeneous stock mice, which descend from eight inbred progenitor strains, has found a significant positive correlation between genetic loci associated to hippocampal proliferation and to the proportion of CD4+ cells among blood CD3+ lymphocytes [158]. Additional experiments are needed to fully determine the possible interactions between microglia and T cells in neurogenesis, because, at least in normal physiological conditions, (1) T cell surveillance of the brain parenchyma is minimal, (2) microglia are poor antigen presenting cells, and (3) antigen presentation by means of MHC-II family of molecules is thought to occur outside the brain, that is, in the meninges and choroid plexus [159]. In fact, during voluntary exercise, there are no significant changes in T cell surveillance of the hippocampus, nor a direct interaction between T cells and microglia, nor any changes in the gene expression profile of microglia, including that of IGF-1, IL-1, and TNF [160]. The number of microglia is also inversely correlated with the number of hippocampal proliferating cells, rNSCs, and neuroblasts in aged (8 months) mice subjected to voluntary running, as well asin vitro cocultures of microglia and neuroprogenitors, which has been interpreted as resulting from an overall inhibitory effect of microglia on adult neurogenesis [161]. Even though EE is clearly a more complex environmental factor than voluntary running, further research is necessary to disregard nonspecific or indirect effects of genetic or antibody-based T cells depletion on microglia and other brain cell populations, including rNSCs. For instance, adoptive transfer of T helper cells treated with glatiramer acetate, a synthetic analog of myelin basic protein (MBP) approved for the treatment of multiple sclerosis, produces a bystander effect on resident astrocytes and microglia by increasing their expression of anti-inflammatory cytokines such as TGF[162]. Alternatively, it has been suggested that T cells may mediate an indirect effect on adult hippocampal neurogenesis by increasing the production of brain-derived neurotrophic factor (BDNF) [157], which is involved in the proneurogenic actions of EE [163]. Whether BDNF can counteract the detrimental effects of T cell depletion on neurogenesis remains unknown. Overall, the roles of microglia in EE and running-induced neurogenesis are unclear and have to be addressed with more precise experimental designs. In summary, surveillant microglia are part of the physical niche surrounding the neural stem cells and newborn neurons of the mature hippocampus, where they continuously phagocytose the excess of newborn cells. Microglia were also linked to the proneurogenic and anti-inflammatory effects of voluntary running and EE, but direct evidence is missing. The overall contribution of microglia to neurogenesis and learning and memory in normal physiological conditions remains largely unexplored at this early stage in the field.

  1. Conclusion

In light of these observations, microglia are now emerging as important effector cells during normal brain development and functions, including adult hippocampal neurogenesis. Microglia can exert a positive or negative influence on the proliferation, survival, or differentiation of newborn cells, depending on the inflammatory context. For instance, microglia can compromise the neurogenic cascade during chronic stress, aging, and neurodegenerative diseases, by their release of proinflammatory cytokines such as IL-1, IL-6, and TNF. A reduced fractalkine signalling between neurons and microglia could also be involved during normal aging. However, microglia are not necessarily the only cell type implicated because astrocytes, endothelial cells, mast cells, perivascular and meningeal macrophages, and to a lesser extent neurons and invading peripheral immune cells could further contribute by releasing proinflammatory mediators.

Additionally, microglia were shown to phagocytose the excess of newborn neurons undergoing apoptosis in the hippocampal neurogenic niche during normal physiological conditions, while a similar role in the synaptic integration of newborn cells was also proposed in light of their capacity to phagocytose synaptic elements. Lastly, microglial interactions with T cells, leading to the release of anti-inflammatory cytokines, neurotrophic factors, and other proneurogenic mediators (notably during EE and voluntary running), could counteract the detrimental effects of inflammation on adult hippocampal neurogenesis and their functional implications for learning and memory.

However, further research is necessary to assess the relative contribution of microglia versus other types of resident and infiltrating inflammatory cells and to determine the nature of the effector cytokines and other inflammatory mediators involved, as well as their cellular and molecular targets in the neurogenic cascade. Such research will undoubtedly help to develop novel strategies aiming at protecting the neurogenic potential and ultimately its essential contribution to learning and memory.

Abbreviations

AD: Alzheimer’s disease
ANPs: Amplifying neuroprogenitors
APP: Amyloid precursor protein
A: Amyloid beta
BDNF: Brain-derived neurotrophic factor
BrdU: 5-Bromo-2′-Deoxyuridine
CX3CL1: Fractalkine
CX3CR1: Fractalkine receptor
EAE: Experimental acute encephalomyelitis
EE: Enriched environment
EGF: Epidermal growth factor
FGFb: Basic fibroblast growth factor
GDNF: Glial cell line-derived neurotrophic factor
GFAP: Glial fibrillary acidic protein
GR: Glucocorticoid receptor
HPA: Hypothalamic-pituitary-adrenal axis
ICE: Interleukin 1 converting enzyme
IL-1: Interleukin 1 beta
IL-1R1: Interleukin 1 beta receptor
IL-4: Interleukin 4
IL-6: Interleukin 6
IL-7: Interleukin 7
IL-11: Interleukin 11
IFN: Interferon gamma
IGF-1: Insulin-like growth factor 1
iNOS: Inducible nitric oxide synthase
LPS: Bacterial lipopolysaccharides
LTP: Long term potentiation
M-CSF: Macrophage colony-stimulating factor
MBP: Myelin basic protein
MHC-II: Major histocompatibility complex class II
MOG: Myelin oligodendrocyte glycoprotein
NF-B: Nuclear factor kappa-light-chain-enhancer of activated B cells
NGF: Nerve growth factor
NO: Nitric oxide
NSAID: Nonsteroidal anti-inflammatory drug
NT-4: Neurotrophin-4
PDGF: Platelet-derived growth factor
PS: Phosphatidylserine
PS1: Presenilin 1
ROS: Radical oxygen species
SCID: Severe combined immunodeficiency
SGZ: Subgranular zone
TGF: Transforming growth factor beta
TNF: Tumor necrosis factor alpha
VEGF: Vascular endothelial growth factor.

Conflict of Interests

The authors declare that there is no conflict of interests regarding the publication of this paper.

Acknowledgments

This work was supported by grants from the Spanish Ministry of Economy and Competitiveness to Amanda Sierra (BFU2012-32089) and Juan M. Encinas (SAF2012-40085), from Basque Government (Saiotek S-PC 12UN014) and Ikerbasque start-up funds to Juan M. Encinas and Amanda Sierra, and from The Banting Research Foundation, the Scottish Rite Charitable Foundation of Canada, and start-up funds from Université Laval and Centre de recherche du CHU de Québec to Marie-Ève Tremblay.

References

  1. P. Rezaie and D. Male, “Mesoglia and microglia—a historical review of the concept of mononuclear phagocytes within the central nervous system,” Journal of the History of the Neurosciences, vol. 11, no. 4, pp. 325–374, 2002. View at Publisher · View at Google Scholar · View at Scopus
  2. F. Ginhoux, S. Lim, G. Hoeffel, D. Low, and T. Huber, “Origin and differentiation of microglia,”Frontiers in Cellular Neuroscience, vol. 7, article 45, 2013. View at Publisher · View at Google Scholar
  3. E. Gomez Perdiguero, C. Schulz, and F. Geissmann, “Development and homeostasis of “resident” myeloid cells: the case of the microglia,” GLIA, vol. 61, no. 1, pp. 112–120, 2013. View at Publisher ·View at Google Scholar
  4. H. Kettenmann, F. Kirchhoff, and A. Verkhratsky, “Microglia: new roles for the synaptic stripper,”Neuron, vol. 77, no. 1, pp. 10–18, 2013. View at Publisher · View at Google Scholar
  5. A. Aguzzi, B. A. Barres, and M. L. Bennett, “Microglia: scapegoat, saboteur, or something else?” Science, vol. 339, no. 6116, pp. 156–161, 2013. View at Publisher · View at Google Scholar
  6. K. Helmut, U. K. Hanisch, M. Noda, and A. Verkhratsky, “Physiology of microglia,” Physiological Reviews, vol. 91, no. 2, pp. 461–553, 2011. View at Publisher · View at Google Scholar · View at Scopus
  7. M. È. Tremblay, B. Stevens, A. Sierra, H. Wake, A. Bessis, and A. Nimmerjahn, “The role of microglia in the healthy brain,” Journal of Neuroscience, vol. 31, no. 45, pp. 16064–16069, 2011. View at Publisher ·View at Google Scholar · View at Scopus
  8. A. Miyamoto, H. Wake, A. J. Moorhouse, and J. Nabekura, “Microglia and synapse interactions: fine tuaning neural circuits and candidate molecules,” Frontiers in Cellular Neuroscience, vol. 7, article 70, 2013. View at Publisher · View at Google Scholar
  9. C. Bechade, Y. Cantaut-Belarif, and A. Bessis, “Microglial control of neuronal activity,” Frontiers in Cellular Neuroscience, vol. 7, article 32, 2013. View at Publisher · View at Google Scholar
  10. A. Sierra, O. Abiega, A. Shahraz, and H. Neumann, “Janus-faced microglia: beneficial and detrimental consequences of microglial phagocytosis,” Frontiers in Cellular Neuroscience, vol. 7, article 6, 2013. View at Publisher · View at Google Scholar
  11. G. Kempermann, S. Jessberger, B. Steiner, and G. Kronenberg, “Milestones of neuronal development in the adult hippocampus,” Trends in Neurosciences, vol. 27, no. 8, pp. 447–452, 2004. View at Publisher ·View at Google Scholar · View at Scopus
  12. J. M. Encinas, T. V. Michurina, N. Peunova et al., “Division-coupled astrocytic differentiation and age-related depletion of neural stem cells in the adult hippocampus,” Cell Stem Cell, vol. 8, no. 5, pp. 566–579, 2011. View at Publisher · View at Google Scholar · View at Scopus
  13. M. A. Bonaguidi, M. A. Wheeler, J. S. Shapiro et al., “In vivo clonal analysis reveals self-renewing and multipotent adult neural stem cell characteristics,” Cell, vol. 145, no. 7, pp. 1142–1155, 2011. View at Publisher · View at Google Scholar · View at Scopus
  14. J. J. Breunig, J. I. Arellano, J. D. Macklis, and P. Rakic, “Everything that glitters isn’t gold: a critical review of postnatal neural precursor analyses,” Cell Stem Cell, vol. 1, no. 6, pp. 612–627, 2007. View at Publisher · View at Google Scholar · View at Scopus
  15. L. S. Overstreet-Wadiche and G. L. Westbrook, “Functional maturation of adult-generated granule cells,” Hippocampus, vol. 16, no. 3, pp. 208–215, 2006. View at Publisher · View at Google Scholar · View at Scopus

……………….

 

Review

Nature Reviews Molecular Cell Biology 8, 519-529 (July 2007) | doi:10.1038/nrm2199

Signal integration in the endoplasmic reticulum unfolded protein response

David Ron & Peter Walter

http://www.nature.com/nrm/journal/v8/n7/full/nrm2199.html

The endoplasmic reticulum (ER) responds to the accumulation of unfolded proteins in its lumen (ER stress) by activating intracellular signal transduction pathways — cumulatively called the unfolded protein response (UPR). Together, at least three mechanistically distinct arms of the UPR regulate the expression of numerous genes that function within the secretory pathway but also affect broad aspects of cell fate and the metabolism of proteins, amino acids and lipids. The arms of the UPR are integrated to provide a response that remodels the secretory apparatus and aligns cellular physiology to the demands imposed by ER stress.

 

Figure 1: The unfolded protein response (UPR) signalling pathways.

FromThe impact of the endoplasmic reticulum protein-folding environment on cancer development

Nature Reviews Cancer 14, 581–597 (2014)  http://dx.doi.org:/10.1038/nrc3800

(UPR) signalling pathways

(UPR) signalling pathways

http://www.nature.com/nrc/journal/v14/n9/images/nrc3800-f1.jpg

Upon endoplasmic reticulum (ER) stress, unfolded and misfolded proteins bind and sequester immunoglobulin heavy-chain binding protein (BIP), thereby activating the UPR. The UPR comprises three parallel signalling branches: PRKR-like ER kinase (PERK)–eukaryotic translation initiation factor 2α (eIF2α), inositol-requiring protein 1α (IRE1α)–X-box binding protein 1 (XBP1) and activating transcription factor 6α (ATF6α). The outcome of UPR activation increases protein folding, transport and ER-associated protein degradation (ERAD), while attenuating protein synthesis. If protein misfolding is not resolved, cells enter apoptosis. CHOP, C/EBP homologous protein; GADD34, growth arrest and DNA damage-inducible protein 34; JNK, JUN N-terminal kinase; P, phosphorylation; RIDD, regulated IRE1-dependent decay; ROS, reactive oxygen species; XBP1s, transcriptionally active XBP1; XBP1u, unspliced XBP1.

Figure 3: The unfolded protein response (UPR) and inflammation.

(UPR) and inflammation

(UPR) and inflammation

http://www.nature.com/nrc/journal/v14/n9/images/nrc3800-f3.jpg

The three UPR pathways augment the production of reactive oxygen species (ROS) and activate nuclear factor-κB (NF-κB) and activator protein 1 (AP1) pathways, thereby leading to inflammation. NF-κB, which is a master transcriptional regulator of pro-inflammatory pathways, can be activated through binding to the inositol-requiring protein 1α (IRE1α)–TNF receptor-associated factor 2 (TRAF2) complex in response to endoplasmic reticulum (ER) stress, leading to recruitment of the IκB kinase (IKK), IκB phosphorylation (P) and degradation, and nuclear translocation of NF-κB196. Moreover, the IRE1α–TRAF2 complex can recruit apoptosis signal-regulating kinase 1 (ASK1) and activate JUN N-terminal kinase (JNK), increasing the expression of pro-inflammatory genes through enhanced AP1 activity197. The PRKR-like ER kinase (PERK)–eukaryotic translation initiation factor 2α (eIF2α) and activating transcription factor 6α (ATF6α) branches of the UPR activate NF-κB through different mechanisms. Engaging PERK–eIF2α signalling halts overall protein synthesis and increases the ratio of NF-κB to IκB, owing to the short half-life of IκB, thereby freeing NF-κB for nuclear translocation198199. ATF6α activation following exposure to the bacterial subtilase cytotoxin that cleaves immunoglobulin heavy-chain binding protein (BIP) leads to AKT phosphorylation and consequent NF-κB activation109200.

 

 

Figure 4

The cancer-supporting role of the unfolded protein response (UPR).

http://www.nature.com/nrc/journal/v14/n9/images/nrc3800-f4.jpg

cancer-supporting role of the unfolded protein response

cancer-supporting role of the unfolded protein response

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Autophagy

Writer and Curator: Larry H Bernstein, MD, FCAP

2.1.6      Autophagy

2.1.6.1 Cepharanthine induces apoptosis through reactive oxygen species

Hua P, Sun M, Zhang G, Zhang Y, Tian X, Li X, Cui R, Zhang X
Biochem Biophys Res Commun. 2015 Mar 5. pii: S0006-291X(15)00378-2
http://dx.doi.org/10.1016/j.bbrc.2015.02.131

Cepharanthine is a medicinal plant-derived natural compound which possesses potent anti-cancer properties. However, there is little report about its effects on lung cancer cells. In this study, we investigated the effects of cepharanthine on the cell viability and apoptosis in human non-small-cell lung cancer H1299 and A549 cells. It was found that cepharanthine inhibited the growth of H1299 and A549 cells in a dose-dependent manner which was associated with the generation of reactive oxygen species (ROS) and the dissipation of mitochondrial membrane potential (Δψm). These effects were markedly abrogated when cells were pretreated with N-acetylcysteine (NAC), a specific ROS inhibitor, indicating that the apoptosis-inducing effect of cepharanthine in lung cancer cells was mediated by ROS. In addition, cepharanthine triggered apoptosis in non-small lung cancer cells via the upregulation of Bax, downregulation of Bcl-2 and significant activation of caspase-3 and PARP. These results provide the rationale for further research and preclinical investigation of cepharanthine’s anti-tumor effect against human non-small-cell lung cancer.

2.1.6.2 Mitochondrial Shape Governs BAX-Induced membrane permeabilization and apoptosis

Renault TT, Floros KV, Elkholi R, Corrigan KA, Kushnareva Y, Wieder SY, et al.
Mol Cell. 2015 Jan 8;57(1):69-82
http://dx.doi.org/10.1016/j.molcel.2014.10.028.

Highlights

  • A proapoptotic BCL-2 repertoire containing BIM, PUMA, and BAX initiates MOMP
    • BAX-dependent membrane permeabilization exhibits mitochondrial size requirements
    • Mitochondrial membrane shape directly regulates BAX alpha helix 9 to induce MOMP
    • Mitochondrial hyperfission can be pharmacologically reversed to promote apoptosis

Proapoptotic BCL-2 proteins converge upon the outer mitochondrial membrane (OMM) to promote mitochondrial outer membrane permeabilization (MOMP) and apoptosis. Here we investigated the mechanistic relationship between mitochondrial shape and MOMP and provide evidence that BAX requires a distinct mitochondrial size to induce MOMP. We utilized the terminal unfolded protein response pathway to systematically define proapoptotic BCL-2 protein composition after stress and then directly interrogated their requirement for a productive mitochondrial size. Complementary biochemical, cellular, in vivo, and ex vivo studies reveal that Mfn1, a GTPase involved in mitochondrial fusion, establishes a mitochondrial size that is permissive for proapoptotic BCL-2 family function. Cells with hyperfragmented mitochondria, along with size-restricted OMM model systems, fail to support BAX-dependent membrane association and permeabilization due to an inability to stabilize BAXα9·membrane interactions. This work identifies a mechanistic contribution of mitochondrial size in dictating BAX activation, MOMP, and apoptosis.

http://www.cell.com/cms/attachment/2023304675/2043672113/fx1.jpg

Figure 1. Terminal UPR Requires BAX

(A–D) WT and Bak/Bax/ MEFs were treated with b-ME (A), DTT (B), Tg (C), or Tun (D) for 18 hr. (E) WT, Bak/, and Bax/ MEFs were treated with b-ME (15 mM), DTT (5 mM), Tg (1.5 mM), or Tun (2.5 mg/ml) for 18 hr. (F) Lysates from ER stress-treated WT, Bak/, and Bax/ MEFs in (E) were analyzed by western blot. (G) CHAPS lysates from ER stress-treated WT MEFs (highest doses at 18hr) were subjected to 6A7 IP and western blot. Total cell lysates (5%) were analyzed as a loading control. (H) HM fractions isolated from ER stress-treated WT MEFs (highest doses at 18hr) were subjected to trypsinization and analyzed by western blot.Total cell lysates (5%) were analyzed as a loading control for BAX; VDAC is a pretrypsinization mitochondrial loading control. (I) WT and Bid/Bim/ MEFs were treated with DTT for 18 hr. (J) HM fractions isolated from ER stress-treated WT MEFs (highest doses at 18 hr) were analyzed by western blot. (K) HM fractions from ER stress-treated WT MEFs (highest doses at 18 hr) were incubated with ABT-737 (1 mM) for 30 min at 37 C, centrifuged, and the supernatants were analyzed by western blot. CHAPS (0.25%) lysed mitochondria indicates total cyto c within each lane. *Nonspecific band. (L) Same as in (J), but probed for PUMA and SMAC. (M) WT and Puma/ MEFs were treated with b-ME for 18 hr. (N) Puma/ MEFs were pretreated either with ABT-737 (1 mM) for 1 hr and then b-ME for 18 hr or with b-ME for 18 hr and then ABT-737 for an additional 6 hr. (O)A summary schematic of BCL-2 family interactions required for apoptosis to proceed.All data are representative of at least triplicate experiments and reported as ±SD, as required. See also Figures S1–S3.

Figure 3. Mitochondrial Network Shape Regulates tUPR (A) WT and Mfn1/ MEFs were treated with DTT for 18 hr. (B) WT, Mfn2/, and Mfn1/ MEFs were loaded with MitoTracker Green (50 nM) and Hoechst 33342 (20 mM) before imaging (4003). (C) Mfn1/ MEFs were treated with mDIVI-1 (25 mM) for 2 hr before imaging (4003). Further magnified regions (2.53) are shown in white boxes. The average length of 200 mitochondria is shown. (D) Mfn1/ MEFs were pretreated with mDIVI-1 (25 mM) for 2 or 8 hr and then DTT for 18 hr. (E and F) Mfn1/ MEFs were pretreated with mDIVI-1 (25 mM) for 8 hr, then Tg (0.25 mM) (E) or Tun (0.5 mg/ml) (F) for 18 hr. (G) Mfn1/ MEFs were pretreated with mDIVI-1 (25 mM) for 8 hr, then TNFa and CHX (10 mg/ml) for 18 hr. (H) HM fractions from ER stress-treated Mfn1/ MEFs were analyzed by western blot. (I) Mfn1/MEFs were pretreated withmDIVI-1 (25mM) for 2hr and ER stress agents for 18hr,and mitochondria were isolated and analyzed by western blot. High molecular weight complexes of BAX are indicated (*). VDAC is a loading control. (J) Mfn1/ MEFs were treated with mDIVI-1 (25 mM) for 8 hr, and lysates were analyzed by western blot. (K) WT MEFs were pretreated with mDIVI-1 (25 mM) for 8 hr and ER stress agents for 18 hr. (L) Mfn1/ MEFs were pretreated with mDIVI-1 (25 mM) for 8 hr and Paclitaxel or cisplatin for 18 hr. (M) Same as in (L), but A375. (N) Same as in (C), but A375.

Figure 4. Mitochondrial Size Dictates Sensitivity to BAX-Dependent MOMP (A) Schematic representation of measuring D(DcM) to detect MOMP. (BandC) Digitonin-permeabilized, JC-1-loaded Mfn1/MEFs (pretreated with 25mM mDIVI-1, or DMSO, for 8hr) were incubated with BAX (0.25mM) or OG-BAX (0.25 mM), and mitochondrial depolarization (DcM) was determined. Kinetic and endpoint measurements are shown in (B) and (C), respectively. (D and E) Same as in (B), but with BIM-S (25 nM). Kinetic and endpoint measurements are shown in (D) and (E), respectively. (F) JC-1-loaded WT liver mitochondria were fractionated by size, and the relationships between 0.5 and 0.05 mm LUVs are indicated on the same graph. (G and H) Larger (>0.5 mm; fractions 6–8) and smaller (<0.5 mm; fractions 11–15) WT mitochondria were treated with BAX (100 nM) or OG-BAX (100 nM) for 1 hr at 37oC. Kinetic and endpoint measurements are shown in (G) and (H), respectively. (I) JC-1-loaded Bak/ liver mitochondria were fractionated by size. (J and K) Larger (>0.5 mm; fractions 8–10) and smaller (<0.5 mm; fractions 12–16) Bak/ mitochondria were treated with BAX (20 nM) ± BIM-S (20 nM) for 1 hr. Kinetic and endpoint measurements are shown in (J) and (K), respectively. All data are representative of at least triplicate experiments and reported as ±SD, as required. See also Figure S5.

Figure 5. BAX Preferentially Permeabilizes OMVs with Diameters Similar to Those of WT Mitochondria (A) Schematic representation of OMVs. (B) Unextruded OMVs were combined with BAX (40 nM) and N/C-BID (20 nM) or BIM BH3 peptide (2.5 mM) for 30 min at 37 C. (C) Kinetic traces of unextruded OMV permeabilization with BAX (40 nM) and BID (25 nM) or BIM BH3 (2.5 mM) for 30 min at 37 C. Triton X-100 solubilizes OMVs and establishes 100% release. An anti-FITC antibody is used to quench the FITC-dextran released during permeabilization. (D–F) DLS analyses of extruded (1, 0.2, and 0.05 mm) OMVs. The major peak was calculated as the area under the curve and is reported as a percentage. (G) OMVs were combined with BAX (0.25 mM) for 10 or 30 min. (H) OMVs were combined with BAX (40 nM) and BIM BH3 (2.5 mM) for 10 or 30 min. (I) Same as in (H), but with N/C-BID (20 nM). (J) OMVs were combined with BAX (40 nM), BIM BH3 (2.5 mM), BCL-xLDC (300 nM), and PUMA BH3 (5 mM) for 30 min. All data are representative of at least triplicate experiments and reported as ±SD, as required. See also Figure S6.

Figure 6. BAX Preferentially Permeabilizes LUVs with Diameters Similar to Those of WT Mitochondria (A) Schematic representation of LUVs. (B) Standard LUVs (1 mm) were combined with BAX (100 nM) and N/C-BID (20 nM) or BIM BH3 (2.5 mM) for 1 hr at 37oC. (C–E) DLS analyses of LUVs extruded 1 (C), 0.2 (D), and 0.05 (E) mm. (F) LUVs were combined with BAX (0.25 and 0.75 mM) for 1 hr. (G) LUVs were combined with BAX (75 and 100 nM) and BIM BH3 (2.5 mM) for 1 hr. (H) Same as in (G), but with N/C-BID (20 nM). (I) LUVs were combined with BAX (100 nM) and N/C-BID (20 nM) or BIM BH3 (2.5 mM) for 30minat 37oC prior to centrifugation, solubilization, and western blot for associated BAX. (J) LUVs were combined with BAX (100nM), BIMBH3 (2.5mM), BCL-xLDC (300nM), and PUMABH3 (5mM) for 1 hr. All data are representative of at least triplicate experiments and reported as ±SD, as required. See also Figure S7.

Figure 7. BAX a9 Displays Requirements for Membrane Shape (A) LUVs were combined with BAX or BAXOG (0.25 mM) for 15 min at 37oC. (B) BAX (100 ng) was incubated in the presence of BIM BH3 (2.5 mM) and LUVs for 30 min prior to 6A7 IP and western blot. (C) LUVs were combined with BAXWT or BAXDC (0.25 mM) for 1 hr at 37oC. The required incubation time is longer for BAXDC compared to BAXWT, which increases BAXWT activity. (D) LUVs were combined with BAXWT or BAXS184A for 30 min at 37oC. (E) Same as in (D), but with BIM BH3 (2.5 mM). (F) LUVs were combined with BAXWT or BAXS184A (100 nM) for 30 min at 37oC prior to centrifugation, solubilization, and western blot for associated BAX. (G) NBD-BAXWT or NBD-BAXS184A was incubated with 1 mm LUVs for 5 min ± BIMBH3 (2.5 mM). An increase in NBD fluorescence indicates BAX$LUV interactions and is reported as fold increase compared to NBD-BAXWT + LUVs. (H) LUVs (1 mm) were combined with BAXWT or BAXS184A (50, 75, 100 nM) with BIM BH3 (2.5 mM) for 30 min at 37oC. (I) LUVs were combined with BAXWT or BAXS184A (50 nM) with BIM BH3 (2.5 mM) for 30 min at 37oC. (J) OMVs were combined with BAXWT or BAXS184A (50 nM) and BIM BH3 (2.5 mM) for 30 min at 37oC. (K) NBD-BAXWT or NBD-BAXS184A ± BIM BH3 (2.5 mM) was incubated with OMVs for 30 min at 37oC. The interaction between NBD-BAXWT + BIM BH3 with 1 mm OMVs is reported as 100%. (L) Digitonin-permeabilized, JC-1-loaded Mfn1/ MEFs were incubated with BIM BH3 (0.1 mM), BAXWT (50 nM), and BAXS184A (50 nM), and DDcM was determined. (M) Mfn1/ MEFs expressing shBax were reconstituted with human BAXWT or BAXS184A and treated with DTT (1.5 mM), and the kinetics of tUPR were evaluated by IncuCyte. (N) A schematic summarizing the relationship between BAX, mitochondrial shape, and apoptosis. All data are representative of at least triplicate experiments and reported as ±SD, as required. See also Figure S7.

2.1.6.3 Stress-Independent Activation of XBP1s and/or ATF6 Reveals Three Functionally Diverse ER Proteostasis Environments

MD Shoulders, LM Ryno, JC Genereux, JJ Moresco, PG Tu, et al.
Cell Reports 25 Apr 2013; 3(4):1279–1292
http://dx.doi.org:/10.1016/j.celrep.2013.03.024

Highlights

► Orthogonal, ligand-dependent control of XBP1s and/or ATF6 in a single cell ► Proteomic and transcriptomic characterization of XBP1s and/or ATF6 activation ► XBP1s and/or ATF6 influences pathogenic protein fates, but not the endogenous proteome ► Arm-selective UPR activation reduces secretion of destabilized transthyretin variants

The unfolded protein response (UPR) maintains endoplasmic reticulum (ER) proteostasis through the activation of transcription factors such as XBP1s and ATF6. The functional consequences of these transcription factors for ER proteostasis remain poorly defined. Here, we describe methodology that enables orthogonal, small-molecule-mediated activation of the UPR-associated transcription factors XBP1s and/or ATF6 in the same cell independent of stress. We employ transcriptomics and quantitative proteomics to evaluate ER proteostasis network remodeling owing to the XBP1s and/or ATF6 transcriptional programs. Furthermore, we demonstrate that the three ER proteostasis environments accessible by activating XBP1s and/or ATF6 differentially influence the folding, trafficking, and degradation of destabilized ER client proteins without globally affecting the endogenous proteome. Our data reveal how the ER proteostasis network is remodeled by the XBP1s and/or ATF6 transcriptional programs at the molecular level and demonstrate the potential for selective restoration of aberrant ER proteostasis of pathologic, destabilized proteins through arm-selective UPR activation.

3 proteostasis envronments

3 proteostasis envronments

http://ars.els-cdn.com/content/image/1-s2.0-S2211124713001319-fx1.jpg

One-third of the human proteome is directed to the endoplasmic reticulum (ER) for partitioning between folding and trafficking versus ER-associated degradation (ERAD), a decision primarily dictated by the exact composition of the ER protein homeostasis (or proteostasis) network (Balch et al., 2008Braakman and Bulleid, 2011Hartl et al., 2011McClellan et al., 2005). This partitioning protects the integrity of downstream proteomes by ensuring that only folded, functional proteins are trafficked from the ER (Brodsky and Skach, 2011Smith et al., 2011bWiseman et al., 2007).

The folding, trafficking, and degradation capacity of the ER is dynamically adjusted to meet demand by the unfolded protein response (UPR)—a stress-responsive signaling pathway comprising three integrated signaling cascades emanating from the ER transmembrane proteins IRE1, ATF6, and PERK (Schröder and Kaufman, 2005Walter and Ron, 2011). UPR signaling is activated by the accumulation of misfolded or aggregated proteins within the ER lumen. UPR activation causes transient, PERK-mediated translational attenuation and activation of the basic leucine zipper transcription factors ATF4, XBP1s, and the cleaved N-terminal fragment of ATF6 downstream of the ER stress sensors PERK, IRE1, and full-length ATF6, respectively. These transcription factors increase expression of distinct but overlapping sets of genes comprising both ER-specific and general cellular proteostasis pathways (Adachi et al., 2008Lee et al., 2003Okada et al., 2002Yamamoto et al., 20042007). The three mechanistically distinct arms of the metazoan UPR presumably evolved to provide cells with flexibility to adapt to tissue-specific environmental and metabolic demands, creating a mechanism to restore ER proteostasis in response to a wide array of cellular insults (Gass et al., 2008Harding et al., 2001Kaser et al., 2008Wu et al., 2007).

Pharmacologic activation of the UPR offers the potential to adapt ER proteostasis and rescue misfolded, aberrantly degraded, or aggregation-prone ER client proteins without significantly affecting the healthy, wild-type proteome (Balch et al., 2008Walter and Ron, 2011). For example, activation of a UPR signaling pathway that increases ER protein folding capacity could decrease the aberrant ERAD and increase the ER folding and export of destabilized, mutant proteins, thereby ameliorating loss-of-function diseases such as cystic fibrosis or lysosomal storage diseases (Chiang et al., 2012Mu et al., 2008Wang et al., 2006). Alternatively, increasing ERAD activity could attenuate the secretion of destabilized, aggregation-prone proteins that undergo concentration-dependent extracellular aggregation into amorphous aggregates and amyloid fibrils (Braakman and Bulleid, 2011Brodsky and Skach, 2011Luheshi and Dobson, 2009Sitia and Braakman, 2003), providing a potential strategy to ameliorate amyloid disease pathology.

Concomitant pharmacologic activation of the PERK, IRE1, and ATF6 UPR arms can be achieved by the application of toxic small molecules such as tunicamycin (Tm; inhibits protein N-glycosylation) or thapsigargin (Tg; disrupts ER calcium homeostasis) that induce ER protein misfolding and aggregation, ultimately causing apoptosis (Schröder and Kaufman, 2005Walter and Ron, 2011). These global UPR activators have proven useful for delineating the molecular underpinnings of UPR signaling pathways. Unfortunately, the pleiotropic effects and acute toxicity of global UPR activation complicate studies focused on understanding how UPR activation (either global or arm selective) remodels the ER proteostasis network in the absence of an acute ER stress or how the partitioning between folding and trafficking versus degradation of ER client proteins can be influenced by arm-selective UPR activation. Thus, despite the considerable effort focused on understanding the signaling mechanisms of IRE1, ATF6, and PERK activation, the functional implications of activating these pathways on ER proteostasis pathway composition and function remain poorly defined.

Herein, we introduce small molecule-regulated, genetically encoded transcription factors that enable orthogonal activation of UPR transcriptional programs in the same cell. Using our methodology, we characterize the three distinct ER proteostasis environments accessible by activating XBP1s and/or ATF6 to physiologically relevant levels in the absence of stress. We also evaluate the functional consequences of activating XBP1s and/or ATF6 on the folding and trafficking versus degradation of destabilized ER client proteins, including transthyretin (TTR). Ultimately, we demonstrate that arm-selective UPR activation selectively reduces secretion of a destabilized, aggregation-prone TTR variant without affecting the analogous wild-type protein and without globally altering the endogenous intracellular or secreted proteomes. Our results demonstrate, in molecular detail, how the XBP1s and/or ATF6 transcriptional programs integrate to adapt ER proteostasis pathways and highlight the capacity of functionally distinct ER proteostasis environments accessed by arm-selective UPR activation to restore the aberrant ER proteostasis of destabilized protein variants.

To characterize the ER proteostasis environments accessible by the selective or combined activity of the UPR-associated transcription factors XBP1s and ATF6, we required methodology for the small molecule-mediated, orthogonal regulation of two transcription factors in the same cell. Tetracycline (tet)-repressor technology can be applied to allow doxycycline (dox)-dependent control of XBP1s levels in the physiologic range (Lee et al., 2003). However, we have found that tet-repressor regulation of ATF6 activity within the physiologically relevant range is difficult. Even after careful optimization and single-colony stable cell selection of HEK293T-REx cells expressing constitutively active ATF6(1–373) (henceforth termed ATF6) under the tet repressor, we observed nonphysiologic levels of ATF6 target gene expression and significant off-target effects including strong upregulation of established XBP1s target genes, following ATF6 induction at all permissive dox doses (Figures S1A and S1B). We required, therefore, an alternative strategy to regulate the ATF6 transcription factor that would be dosable and orthogonal to tet-repressor technology.

Figure S1. Development and Characterization of HEK293DAX and HEK293DYG Cell Lines, Related to Figure 1

(A) qPCR analysis of clonal HEK293T-REx cells stably expressing dox-inducible ATF6 treated for 12 hr with vehicle, or 1 μg/mL dox. The effects of activating the global unfolded protein response with tunicamycin (Tm; 10 μg/mL for 6 h) or thapsigargin (Tg; 10 μM for 2 h) in HEK293T-REx cells expressing DHFR.YFP are shown for comparison. The dox-inducible ATF6 cell line was carefully selected for the lowest levels of ATF6 expression across multiple isolated single colonies. Note the non-physiologic levels of Hyou1 and HerpUD induction and the upregulation of the established XBP1s-selective target Erdj4 following dox-dependent ATF6 activation. qPCR data are reported relative to appropriate clonal HEK293T-REx cell lines stably expressing dox-inducible eGFP or DHFR.YFP. qPCR data are reported as the mean ± 95% confidence interval.

(B) qPCR analysis of HerpUD mRNA levels in clonal HEK293T-REx cells expressing dox-inducible ATF6 treated for 12 hr with increasing concentrations of dox. Note the lack of dox dose-dependence of HerpUD upregulation in these cells. qPCR data are reported as the mean ± 95% confidence interval.

(C) Time course for induction of HerpUD in HEK293T-REx cells expressing DHFR.ATF6 or tet-inducible ATF6 and treated with 10 μM TMP or 1 μg/mL dox, respectively. Data are presented as percentage of maximal induction and calculated relative to vehicle-treated DHFR.YFP- or eGFP-expressing cells. qPCR data are reported as the mean ± 95% confidence interval.

(D) Immunoblot of nuclear (top) and post-nuclear (bottom) fractions from HEK293DAX and HEK293DYG cells treated 12 hr with dox (1 μg/mL), TMP (10 μM) or both. The immunoblot of matrin-3 shows the efficiency of the nuclear extraction.

(E) qPCR analysis of ATF6 and XBP1s target genes in HEK293DAX cells following 12 hr activation of XBP1s (dox; 1 μg/mL), DHFR.ATF6 (TMP; 10 μM), or both. qPCR data are reported relative to vehicle-treated HEK293DYG cells. qPCR data are reported as the mean ± 95% confidence interval.

(F) Representative autoradiogram of cell lysates prepared from HEK293DAX cells pretreated for 12 hr with dox (1 μg/mL), TMP (10 μM), or both. Following activation, cells were labeled with [35S]-methionine/cysteine for 30 min then chased in non-radioactive media for 0 or 4 hr, as indicated. These lysates are prepared from the same experiments described in Figure 2J.

(G) Quantification of cell lysate autoradiograms prepared from [35S]-labeled HEK293DAX cells following a 12 hr activation of XBP1s and/or ATF6 as described in Figure S1F. The quantified results reflect the amount of [35S] incorporated into the cellular proteome directly following a 30 min labeling period. Error bars indicate the standard error from biological replicates (n = 3).

(H) Immunoblot of lysates prepared from HEK293DAX cells treated with dox (1 μg/mL), TMP (10 μM), or both for the indicated time. Tg (1 μg/mL) was added for 2 hr as a control.

(I) HEK293DAX cells were plated at 5,000 cells/well in a translucent, flat-bottomed 96 well plate, and treated for 15 hr with vehicle, 10 μM TMP or 1 μg/mL dox. 2 hr before cell metabolic activity was assessed, Tg (10 μM) was added to untreated cells. Cell metabolic activity was measured using the 7-hydroxy-3H-phenoxazin-3-one 10-oxide (resazurin) assay, which reports on mitochondrial redox potential. Cells were incubated with a final concentration of 50 μM resazurin for 2 hr at 37°C, The fluorescence signal, which is proportional to cell metabolism and viability, was then measured (excitation wavelength 530 nm, emission wavelength 590 nm). Error bars indicate standard error from biological replicates (n = 3). ∗∗ indicates p-value < 0.01.

We envisioned that destabilized domain (DD) technology (Figure 1A) (Banaszynski et al., 2006Iwamoto et al., 2010) could be adapted to prepare a dose-dependent, ligand-regulated ATF6 transcription factor whose activity would be inducible to levels more consistent with those observed in human physiology. We fused a destabilized variant of E. coli dihydrofolate reductase (DHFR) to the N terminus of ATF6 via a short Gly-Ser linker. The poorly folded DHFR domain directs the entire constitutively expressed DHFR.ATF6 fusion protein to rapid proteasomal degradation. Administration of the DHFR-specific pharmacologic chaperone, trimethoprim (TMP), stabilizes the folded DHFR conformation, increasing the initially poorly populated folded DHFR population, attenuating proteasomal degradation, and inducing the ATF6 transcriptional program ( Figure 1A).

Figure 1. Orthogonal, Ligand-Dependent Control of XBP1s and ATF6 Transcriptional Activity

(A) Model illustrating the TMP-mediated, posttranslational regulation of DHFR.ATF6.

(B) Immunoblot of nuclear (top) and postnuclear (bottom) fractions from HEK293T-REx cells expressing DHFR.YFP or DHFR.ATF6 treated 12 hr with TMP (10 μM). The immunoblot of matrin-3 shows the efficiency of the nuclear extraction.

(C) qPCR analysis of Hyou1HerpUD, and Erdj4 in HEK293T-REx cells expressing DHFR.YFP or DHFR.ATF6 following a 12 hr treatment with TMP (10 μM) or a 6 hr treatment with Tm (10 μg/ml). qPCR data are reported relative to vehicle-treated cells expressing DHFR.YFP. qPCR data are reported as the mean ± 95% confidence interval.

(D) TMP dose dependence of HerpUD upregulation in HEK293T-REx cells expressing DHFR.ATF6 (12 hr treatments with TMP). qPCR data are reported as the mean ± 95% confidence interval.

(E) qPCR analysis of the ATF6 target gene BiP in HepG2, Huh7, or primary fibroblast cells transiently transduced with DHFR.YFP- or DHFR.ATF6-expressing adenoviruses and treated for 12 hr with 100 μM TMP or vehicle. qPCR data are reported relative to the corresponding vehicle-treated cells. qPCR data are reported as the mean ± 95% confidence interval.

(F) qPCR analysis of BiP and Erdj4 in HEK293DAX cells following a 12 hr activation of XBP1s (dox; 1 μg/ml), DHFR.ATF6 (TMP; 10 μM), or both. qPCR data are reported relative to vehicle-treated HEK293DYG cells. qPCR data are reported as the mean ± 95% confidence interval.

See also Figure S1 and Table S4.

The addition of TMP stabilizes DHFR.ATF6 in nuclear fractions isolated from HEK293T-REx cells expressing DHFR.ATF6 (Figure 1B). DHFR.ATF6 is not detected in the absence of TMP. Furthermore, TMP induces expression of the ATF6 target genes HerpUD and Hyou1 ( Adachi et al., 2008) in cells expressing DHFR.ATF6 to levels consistent with those observed following global UPR-dependent activation induced by Tm ( Figure 1C). We observe no increased expression of these genes in untreated cells expressing DHFR.ATF6 or TMP-treated cells expressing DHFR.YFP. The TMP-dependent activation of DHFR.ATF6 is rapid, causing significant upregulation of HerpUD in <2 hr ( Figure S1C). Importantly, TMP treatment does not induce expression of the XBP1s-selective target gene Erdj4 ( Lee et al., 2003) (Figure 1C). Increasing concentrations of TMP reveal a linear dose-dependent upregulation of ATF6 target genes, demonstrating a significant dynamic range for activation of DHFR.ATF6 by TMP ( Figure 1D). Because DHFR.ATF6 is a single gene product, it similarly enables the straightforward, ligand-dependent activation of the ATF6 transcriptional program at physiologic levels in a wide variety of other cellular model systems ( Figure 1E).

In order to activate both XBP1s and ATF6 in the same cell, we incorporated DHFR.ATF6 and tet-inducible XBP1s into a HEK293T-REx cell line stably expressing the tet repressor. Selection of a single colony resulted in the HEK293DAX cell line in which XBP1s is induced by dox, and DHFR.ATF6 is activated by TMP (TMP-dependent DHFR.ATF6 activation in HEK293DAX cells will henceforth be referred to as ATF6 activation for simplicity). We confirmed ligand-dependent regulation of XBP1s and ATF6 by immunoblotting (Figure S1D). qPCR analysis of HEK293DAX cells demonstrates the orthogonal, ligand-dependent activation of the XBP1s and/or ATF6 transcriptional programs (Figures 1F and S1E) (Lee et al., 2003). An analogous HEK293DYG control cell line expressing tet-inducible EGFP and DHFR.YFP was also prepared as a control (Figure S1D).

The addition of activating ligands to HEK293DAX cells neither alters the incorporation of [35S]-labeled methionine into the cellular proteome (Figures S1F and S1G) nor increases eIF2α phosphorylation (Figure S1H), demonstrating that selective XBP1s and/or ATF6 activation within the physiologically relevant regime does not cause PERK-mediated translational attenuation through stress-induced global UPR activation. Independent activation of XBP1s or ATF6 also does not significantly reduce cellular viability (unlike global UPR activators such as Tm or Tg; Figure S1I). Thus, HEK293DAX cells enable orthogonal control of the transcriptional programs regulated by XBP1s and ATF6 in the same cell independent of stress.

The activation of XBP1s or ATF6 results in the upregulation of overlapping but divergent gene sets (Figure 2A), reflecting two distinct ER proteostasis environments accessible by activating these transcription factors independently. The transcriptional targets induced by XBP1s or ATF6 largely overlap with those previously identified by Adachi et al. (2008)Lee et al. (2003)Okada et al. (2002), andYamamoto et al., 2004 and Yamamoto et al., 2007. Interestingly, activating both XBP1s and ATF6 affords a third, previously inaccessible, ER proteostasis environment that is not simply the sum of the transcriptional consequences of activating XBP1s or ATF6 independently. This third ER proteostasis environment includes genes upregulated to similar levels by activating either XBP1s or ATF6 in comparison to the combination (Figure 2B, red and blue, respectively). In addition, 31 genes display cooperative upregulation owing to combined XBP1s and ATF6 activation (Figure 2B, green). We have validated the cooperative induction of several of these genes by qPCR (Figure 2C). This cooperative induction likely reflects the binding of both XBP1s and ATF6 to promoter regions or the preferential binding of XBP1s/ATF6 heterodimers to select promoters (Yamamoto et al., 2007) and represents a unique transcriptional profile only accessible by our ability to activate both XBP1s and ATF6 in the same cell independent of stress.

Integration of Transcriptomics and Proteomics Reveals Three Distinct ER Proteostasis Environments

Integration of Transcriptomics and Proteomics Reveals Three Distinct ER Proteostasis Environments

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Integration of Transcriptomics and Proteomics Reveals Three Distinct ER Proteostasis Environments Accessible upon Activation of XBP1s and/or ATF6

Our transcriptional and proteomic profiling of HEK293DAX cells reveals how the composition of the ER proteostasis network is differentially remodeled by activation of the XBP1s and/or ATF6 transcriptional programs (Figure 3). Consistent with the IRE1-XBP1s signaling cascade being the only UPR pathway conserved from yeast to humans, XBP1s activation has a broader impact on the composition of ER proteostasis pathways than does ATF6. XBP1s activation upregulates entire ER proteostasis pathways, including those involved in ER protein import, N-linked glycosylation, and anterograde/retrograde vesicular trafficking (Figure 3, red). The induction of these pathways is similarly observed by enrichment analysis (Table S2). In contrast, although ATF6 is responsible for upregulating only a select subset of ER proteostasis network proteins, these ATF6-selective targets represent critical hub proteins in the ER proteostasis network, including BiP, Sel1L, and calreticulin (Figure 3, blue).

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Figure 3. Predictive Pathway Analysis for Stress-Independent XBP1s- and/or ATF6-Mediated Remodeling of the ER Proteostasis Network

Cartoon depicting the impact of activating XBP1s, ATF6, or both XBP1s and ATF6 on the composition of ER proteostasis pathways obtained by integrating transcriptional, proteomic, and biochemical results. XBP1s (red) and ATF6 (blue)-selective genes are genes where activating either XBP1s (but not ATF6) or ATF6 (but not XBP1s) independently results in >75% of the induction observed when both XBP1s and ATF6 are activated (“max induction”). Genes induced >75% of the max induction by activating XBP1s in isolation and induced >75% of the max induction by activating ATF6 in isolation (i.e., lacking selectivity) are colored purple. Genes cooperatively induced >1.33-fold upon activation of both XBP1s and ATF6 relative to the activation of either transcription factor alone are colored green. Plain type indicates results from array data. Italicized type indicates results from proteomics data. Underlined type indicates results confirmed at both the transcript and the protein levels. Thresholds for transcriptional analyses were set at a FDR of <0.05. Thresholds for proteomic analyses were set at a FDR of 0.1.

Some proteins are upregulated to similar levels by activating XBP1s in isolation, ATF6 in isolation, or both XBP1s and ATF6 (Figure 3, purple). Alternatively, a number of proteins primarily involved in ER quality control and degradation are cooperatively upregulated when both XBP1s and ATF6 are activated (Figure 3, green). These results are consistent with the biological pathways predicted to be transcriptionally enhanced by XBP1s:ATF6 heterodimers (Yamamoto et al., 2007) and clearly demonstrate that the impact of the combined activation of XBP1s and ATF6 on the composition of the ER proteostasis network is greater than the sum of activating XBP1s or ATF6 individually.

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Figure 4. XBP1s and/or ATF6 Activation Differentially Influences the Degradation of NHK-A1AT and NHK-A1ATQQQ

(A) Representative autoradiogram of [35S]-labeled NHK-A1AT immunopurified from transfected HEK293DAX cells following a 15 hr preactivation of XBP1s (dox; 1 μg/ml), DHFR.ATF6 (TMP; 10 μM), or both. The metabolic-labeling protocol employed is shown.

(B) Quantification of autoradiograms in (A) monitoring the degradation of [35S]-labeled NHK-A1AT. The fraction of NHK-A1AT remaining was calculated by normalizing the recovered [35S] signal to the total amount of labeling observed at 0 hr. Error bars represent SE from biological replicates (n = 18).

(C) Bar graph depicting the normalized fraction of NHK-A1AT remaining at 3 hr calculated as in (B).

(D) Representative autoradiogram of [35S]-labeled NHK-A1ATQQQ immunopurified from transfected HEK293DAX cells following a 15 hr preactivation of XBP1s (dox; 1 μg/ml), DHFR.ATF6 (TMP; 10 μM), or both. The metabolic-labeling protocol employed is shown.

(E) Quantification of autoradiograms in (D) monitoring the degradation of [35S]-labeled NHK-A1ATQQQ. The fraction of NHK-A1ATQQQ remaining was calculated as in (B). Error bars represent SE from biological replicates (n = 6).

(F) Bar graph depicting the normalized fraction of NHK-A1ATQQQ remaining at 4.5 hr calculated as in (B).

p < 0.05, ∗∗p < 0.01, and ∗∗∗p < 0.001. See also Figure S3.

Influence of Dox and-or TMP Treatment on NHK-A1AT and NHK-A1ATQQQ Degradation in HEK293DAX and HEK293DYG Cells, Related to Figure 4

Influence of Dox and-or TMP Treatment on NHK-A1AT and NHK-A1ATQQQ Degradation in HEK293DAX and HEK293DYG Cells, Related to Figure 4

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Figure S3. Influence of Dox and/or TMP Treatment on NHK-A1AT and NHK-A1ATQQQ Degradation in HEK293DAX and HEK293DYG Cells, Related to Figure 4

(A) Quantification of immunoblots of lysates prepared from HEK293DAX cells transfected with NHK-A1AT and treated for 15 hr with vehicle or TMP (10 μM; activates DHFR.ATF6). Cycloheximide (CHX, 50 μg/mL) was applied for the indicated time prior to harvest. Total NHK-A1AT at each CHX time point was normalized to the amount of NHK-A1AT observed in the absence of CHX. Error bars indicate the standard error from biological replicates (n = 4).

(B) Quantification of autoradiograms monitoring the degradation of [35S]-labeled, NHK-A1AT in transfected HEK293DYG cells following a 15 hr induction of GFP (dox; 1 μg/mL), DHFR.YFP (TMP; 10 μM), or both. The metabolic labeling protocol employed is identical to that used in Figure 4A. Fraction remaining was calculated as in Figure 4B. Error bars indicate the standard error from biological replicates (n = 3).

(C) Quantification of autoradiograms monitoring the degradation of [35S]-labeled NHK-A1ATQQQ in transfected HEK293DYG cells following a 15 hr induction of GFP (dox; 1 μg/mL), DHFR.YFP (TMP; 10 μM) or both. The metabolic labeling protocol employed is identical to that used in Figure 4D. Fraction remaining was calculated as in Figure 4E. Error bars indicate the standard error from biological replicates (n = 3).

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Figure 5. ATF6 Activation Selectively Attenuates the Secretion of Amyloidogenic TTR

(A) Autoradiogram of [35S]-labeled FTTTRA25T immunopurified from media and lysates collected from transfected HEK293DAX cells following a 15 hr preactivation of XBP1s (dox; 1 μg/ml), DHFR.ATF6 (TMP; 10 μM), or both. The metabolic-labeling protocol employed is shown.

(B) Quantification of autoradiograms as shown in (A). Fraction secreted was calculated as previously described by Sekijima et al. (2005). Error bars represent SE from biological replicates (n = 4).

(C) Graph depicting the normalized fraction secreted of [35S]-labeled FTTTRWT (white bars) or FTTTRA25T (orange bars) at 4 hr following a 15 hr preactivation of DHFR.ATF6 (TMP; 10 μM) in HEK293DAX cells. Error bars represent SE from biological replicates (n = 8 for FTTTRA25T, and n = 9 for FTTTRWT).

(D) Graph depicting the total [35S]-labeled FTTTRA25T remaining in HEK293DAX cells (combined media and lysate protein levels as in A). The fraction remaining was calculated as reported previously by Sekijima et al. (2005). Error bars represent SE from biological replicates (n = 8).

(E) Graph depicting the normalized fraction secreted of [35S]-labeled FTTTRA25T (orange bars) at 4 hr following preactivation of DHFR.ATF6 (TMP; 10 μM; 15 hr) in the presence or absence of tafamidis (10 μM; 15 hr) in HEK293DAX cells. Error bars represent SE from biological replicates (n = 4).

(F) Bar graph depicting the normalized fraction secreted of FTTTRA25T and endogenous TTRWT at 4 hr following a 13 hr pretreatment with TMP (100 μM) in HepG2 cells stably expressing DHFR.ATF6. Error bars represent SE from biological replicates (n = 4).

(G) Bar graph depicting the normalized fraction secreted of [35S]-labeled FTTTRD18G at 4 hr following a 15 hr pretreatment with TMP (10 μM) from HEK293DAX cells transfected with both FTTTRD18G and TTRWT. Error bars represent SE from biological replicates (n = 4).

(H) Immunoblot of α-FLAG M1 FTTTRA25T immunoisolations from DSP-crosslinked lysates prepared from HEK293DAX cells expressing FTTTRA25T following 15 hr activation of XBP1s (dox; 1 μg/ml), DHFR.ATF6 (TMP; 10 μM), or both. HEK293DAX cells expressing GFP are shown as a negative control (Mock). The KDEL immunoblot shows BiP.

p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.005. See also Figure S4.

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Figure S4.  ATF6 Activation Selectively Attenuates the Secretion of Amyloidogenic Transthyretin, Related to Figure 5

(A) Quantification of immunoblots measuring FTTTRA25T and FTTTRWT secreted into the media from transfected HEK293DAX cells during a 15 hr activation of XBP1s (dox; 1 μg/mL), DHFR.ATF6 (TMP; 10 μM), or both. Error bars indicate standard error from biologic replicates (n = 10 for FTTTRA25T and n = 7 for FTTTRWT).

(B) Quantification of autoradiograms monitoring [35S]-labeled FTTTRA25T secreted from transfected HEK293DYG cells following a 15 hr induction of GFP (dox; 1 μg/mL), DHFR.YFP (TMP; 10 μM) or both. The metabolic labeling protocol employed is identical to that used in Figure 5A. Fraction secreted was calculated as in Figure 5B. Error bars indicate the standard error from biological replicates (n = 3).

(C) Bar graph depicting the normalized fraction secreted of [35S]-labeled FTTTRA25T and FTTTRWT at t = 4 hr following a 15 hr preactivation of DHFR.ATF6 (TMP; 10 μM) or global UPR activation by treatment with Tg (500 nM). Normalized fraction secreted was calculated as in Figure 5C and a representative autoradiogram is shown. The error bars represent standard error from biological replicates (n = 2).

(D) Concentration-dependent kinetics of recombinant TTRA25T aggregation at pH 6.0 as monitored by turbidity at 400 nm. TTR was purified by gel filtration immediately prior to use. 150 μl of TTR in 10 mM phosphate buffer pH 7.0, 100 mM KCl, 1 mM EDTA, was added to 750 μl of 0.1 M citrate-phosphate buffer pH 6.0 in a plastic cuvette to yield final concentrations as indicated. The samples were incubated at 37°C without stirring, and agitated prior to transmittance measurement. Higher concentrations yield a higher extent and rate of TTR aggregation. Error bars indicate standard error from biologic replicates (n = 3).

(E) Representative immunoblot depicting detergent-soluble and insoluble FTTTRA25T isolated from HEK293DAX cells treated for 15 hr with vehicle or TMP (10 μM) and separated by SDS-PAGE. Detergent-insoluble protein was recovered by incubating the washed pellet from RIPA-lysed cells in 8 M urea in 50 mM Tris pH 8.0 at 4°C overnight, followed by shearing, dilution in RIPA, and centrifugation at 16000 × g for 15 min. The error bars represent standard error from biological replicates (n = 3).

(F) Representative autoradiogram and bar graph depicting the total [35S]-labeled FTTTRD18G remaining in HEK293DAX cells following 15 hr TMP (10 μM) pretreatment. The fraction remaining of FTTTRD18G following a 90 min chase was calculated as inFigure 5D. The error bars represent standard error from biological replicates (n = 4). indicates p-value < 0.05.

(G) Representative immunoblot and quantification of FTTTRD18G protein levels in HEK293DAX cells following a 15 hr incubation with TMP (10 μM) and/or MG-132 (10 μM). The error bars represent standard error from biological replicates (n = 9). ∗∗indicates a p-value < 0.05

(H) Representative immunoblot and quantification of media collected from equal numbers of HEK293DAX cells transiently transfected with FTTTRA25T and pretreated with TMP (10 μM) and/or tafamidis (10 μM) for 15 hr, as indicated. The error bars represent standard error from biological replicates (n = 4). ∗∗∗ indicates p-value < 0.01.

(I) Representative autoradiogram of [35S]-labeled FTTTRA25T in the media and lysates of HEK293DAX cells treated with TMP (10 μM) and/or tafamidis (10 μM) for 15 hr, as indicated, and used to prepare Figure 5E. Cells were metabolically labeled using an identical protocol to that shown in Figure 5A. The bar graph shows the quantification of normalized total [35S]-labeled FTTTRA25Tremaining from autoradiograms as shown above. Error bars represent standard error from biological replicates (n = 4).

(J) qPCR analysis of clonal HepG2T-REx cells stably expressing DHFR.ATF6 treated overnight with vehicle or 100 μM TMP. TMP treatment leads to substantial expression of the ATF6 target BiP, but not the XBP1s target ERdj4, demonstrating the selective activation of the ATF6 transcriptional program in these cells. qPCR data are reported as the mean ± 95% confidence interval.

(K) Representative autoradiogram of [35S]-labeled FTTTRA25T and endogenous TTRWT isolated from HepG2T-REx cells stably-expressing DHFR.ATF6 and pretreated with TMP (100 μM; 15 h). The cells were metabolically labeled using an identical approach to that shown in Figure 5A. FTTTRA25T was immunopurified using the anti-Flag M1 antibody. Endogenous TTRWT was immunopurified using an anti-TTR rabbit polyclonal antibody (Sekijima et al., 2005).

(L) Representative autoradiogram of [35S]-labeled FTTTRD18G isolated from HEK293DAX cells transiently transfected withFTTTRD18G and TTRWT. Cells were treated with TMP (10 μM; 14 h), as indicated. TTR was immunopurified from these cells using either the anti-Flag M1 antibody that selectively recognizes FTTTRD18G (n = 2) or the anti-TTR rabbit polyclonal antibody, which immunopurifies both FTTTRD18G and TTRWT (n = 2). The arrows indicate FTTTRD18G and TTRWT, which are separated by SDS-PAGE. It is important to note that anti-Flag M1 immunoisolation of FTTTRD18G co-purifies TTRWT, reflecting efficient formation of heterotetrameric TTR containing both FTTTRD18G and TTRWT subunits.

Herein, we establish methodology that allows for the orthogonal, small molecule-mediated regulation of the UPR-associated transcription factors XBP1s and/or ATF6 in the same cell independent of stress. We employ our methodology to reveal the molecular composition of the three distinct ER proteostasis environments accessible by activating the XBP1s and/or ATF6 transcriptional programs. Furthermore, we show that selectively activating XBP1s and/or ATF6 differentially influences the ER partitioning of destabilized protein variants between folding and trafficking versus degradation. Our results provide molecular insights into how the XBP1s and/or ATF6 transcriptional programs remodel the ER proteostasis environment and demonstrate the potential to influence the ER proteostasis of destabilized protein variants via physiologic levels of arm-selective UPR activation.

Our quantitative transcriptional and proteomic profiling of HEK293DAX cells provides an experimentally validated, conceptual framework to identify specific ER proteins and/or pathways that can be adapted to alter the fate of disease-associated ER client proteins (Figure 3). Critical pathways directly responsible for the partitioning of ER client proteins between folding and trafficking versus degradation are differentially impacted by XBP1s and/or ATF6 activation. For example, the levels of BiP and BiP cochaperones, which are known to modulate folding versus degradation decisions of client proteins in the ER lumen, are differentially influenced by XBP1s and/or ATF6 activation (Figure 3) (Kampinga and Craig, 2010). Considering the importance of BiP cochaperones in defining BiP function, these findings suggest that the fates of BiP clients are distinctly influenced by XBP1s and ATF6 activation. Consistent with this prediction, we show that BiP and HYOU1 have increased association with TTRA25T only when ATF6 is activated, even though HYOU1 is also upregulated by XBP1s (Table 1).

Analogously, XBP1s- or ATF6-dependent remodeling of ER client protein folding pathways can be deconvoluted from our bioinformatic characterization of HEK293DAX cells. For example, XBP1s-selective transcriptional upregulation of the ERAD-associated proteins ERMan1, ERdj5, and EDEM-3 may explain the enhanced degradation of NHK-A1AT upon XBP1s activation because overexpression of these three proteins enhances NHK-A1AT ERAD (Hosokawa et al., 20032006Ushioda et al., 2008). Alternatively, ATF6 selectively enhances the expression of the ERAD-associated protein Sel1L, which when overexpressed, accelerates degradation of the nonglycosylated protein NHK-A1ATQQQ (Iida et al., 2011). Thus, our transcriptional and proteomic profiles of cells remodeled by XBP1s and/or ATF6 activation enable hypothesis generation to dissect the contributions of ER proteostasis proteins and/or pathways involved in altering the folding, trafficking, or degradation of ER client proteins.

We used HEK293DAX cells to explore the potential for ER proteostasis environments accessed through arm-selective UPR activation to reduce the secretion of a destabilized, amyloidogenic TTR variant. We found that ATF6 activation selectively reduces secretion of the destabilized, aggregation-prone TTRA25T, but not the secretion of TTRWT or the global endogenous secreted proteome. Previously, we and others have demonstrated that the efficient secretion of destabilized TTR variants through the hepatic secretory pathway is a contributing factor to the extracellular aggregation and distal deposition of TTR as amyloid in the pathology of numerous TTR amyloid diseases (Hammarström et al., 20022003aHolmgren et al., 1993Sekijima et al., 20032005Suhr et al., 2000Susuki et al., 2009Tan et al., 1995). Thus, our discovery that ATF6-dependent remodeling of the ER proteostasis environment selectively reduces secretion of destabilized TTRA25T reveals a potential mechanism to attenuate the secretion and subsequent pathologic extracellular aggregation of the >100 destabilized TTR variants involved in TTR amyloid diseases (Sekijima et al., 2008). Furthermore, the establishment and characterization of the DHFR.ATF6 construct (which we demonstrate can be rapidly incorporated into any cellular model) and the HEK293DAX cell line provide invaluable resources to evaluate the functional impact of arm-selective UPR activation to physiologic levels on the aberrant ER proteostasis of destabilized mutant proteins involved in the pathology of many other protein misfolding-related diseases. Consistent with the potential to correct pathologic imbalances in destabilized protein ER proteostasis, recent studies that employ global UPR activation using toxic small molecules or the unregulated overexpression of XBP1s or ATF6 have suggested that remodeling ER proteostasis pathways through arm-selective UPR activation could correct the aberrant ER proteostasis of pathologic destabilized protein mutants involved in protein misfolding diseases (Chiang et al., 2012Mu et al., 2008Smith et al., 2011a).

Finally, we note that despite clear functional roles for XBP1s and ATF6 in adapting the composition of ER proteostasis pathways highlighted herein, organisms have distinct dependencies on these transcription factors. XBP1s is critical for biological processes including plasma cell differentiation and development (XBP1s knockout mice are not viable; Reimold et al., 2000). Alternatively, mice lacking ATF6α, the primary ATF6 homolog involved in UPR-dependent remodeling of the ER proteostasis environment, develop normally, although deletion of both mammalian ATF6 homologs, ATF6α and ATF6β, is embryonic lethal (Adachi et al., 2008Wu et al., 2007Yamamoto et al., 2007). Thus, whereas XBP1s is required for organismal development, our results suggest that functional roles for ATF6 in remodeling the ER proteostasis environment are adaptive—adjusting ER proteostasis capacity to match demand under conditions of cellular or organismal stress. Therefore, modulation of ATF6 may provide a unique opportunity to sensitively “tune” the ER proteostasis environment without globally influencing the folding, trafficking, or degradation of the secreted proteome.

In summary, we show that the application of DD methodology to control ATF6 transcriptional activity provides an experimental strategy to characterize the impact of stress-independent activation of XBP1s and/or ATF6 on ER proteostasis pathway composition and ER function. Adapting the underlying biology of the proteostasis network through the activation of specific UPR transcriptional programs reveals emergent functions of the proteostasis network, including a window to alter the ER proteostasis of destabilized mutant proteins without significantly affecting the proteostasis of the vast majority of the endogenous, wild-type proteome. Our transcriptional, proteomic, and functional characterization of the ER proteostasis environments accessible by activating XBP1s and/or ATF6 in a single cell validates targeting specific pathways within the proteostasis network as a potential therapeutic approach for adapting the aberrant ER proteostasis associated with numerous protein misfolding diseases, strongly motivating the development of arm-selective small molecule activators of the UPR.

2.1.6.4 Modeling general proteostasis – proteome balance in health and disease

Roth, D. M., Balch, William E.
Current Opinion in Cell Biology 2011; 23(2): 126-134
http://vivo.scripps.edu/individual/endnote128101
http://dx.doi.org:/10.1016/j.ceb.2010.11.001

Protein function is generated and maintained by the proteostasis network (PN) (Balch et al. (2008) Science, 319:916). The PN is a modular, yet integrated system unique to each cell type that is sensitive to signaling pathways that direct development and aging, and respond to folding stress. Mismanagement of protein folding and function triggered by genetic, epigenetic and environmental causes poses a major challenge to human health and lifespan. Herein, we address the impact of proteostasis defined by the FoldFx model on our understanding of protein folding and function in biology. FoldFx describes how general proteostasis control (GPC) enables the polypeptide chain sequence to achieve functional balance in the context of the cellular proteome. By linking together the chemical and energetic properties of the protein fold with the composition of the PN we discuss the principle of the proteostasis boundary (PB) as a key component of GPC. The curved surface of the PB observed in 3-dimensional space suggests that the polypeptide chain sequence and the PN operate as an evolutionarily conserved functional unit to generate and sustain protein dynamics required for biology. Modeling general proteostasis provides a rational basis for tackling some of the most challenging diseases facing mankind in the 21st century.

Newly synthesized proteins must fold into a unique three-dimensional (3D) structure to become functionally active. We now appreciate that all proteins likely require the assistance of the “proteostasis network” (PN) to generate and maintain function. The PN comprises not less than a 1000 factors that regulate protein synthesis, folding, function, and degradation [13] (FIG. 1). These form the Yin and Yang environment that promotes what we have referred to recently as proteome balance in health [4]. Importantly, the composition of the PN is dynamically regulated by a variety of signaling pathways [5,6], and in response to developmental cues, genetic changes, epigenetic marks, environmental stress and aging; challenges that all cells encounter during their lifespan to maintain normal organismal physiology [3,7,8]. Of importance, is that a very large number of inherited diseases are caused by mutations in the sequence of a polypeptide chain, leading to loss of protein stability, misfolding and disease. While genetic changes often severely challenge the dynamics of proteostasis to retain proteome balance, the response of the PN to mutation can significantly contribute to organismal evolution [9]. Given the multiplicity of cellular PN stress responses, it is not surprising that the PN has evolved to be highly versatile in its capacity to maintain proteome balance. Herein, we discuss the role of protein energetics and kinetics in generating and maintaining proteome balance through the activity of the PN. We explore how modeling of proteostasis opens new avenues to the management of human health and disease.

The PN

The PN

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3077458/bin/nihms258064f1.jpg

The PN

Shown are the interactions that comprise the PN, the composition of which is responsible for generating and maintaining the biological protein fold. Components comprising the PN outlined in the inner-most layer (in blue font) involve the synthesis module, the folding/unfolding module, and the degradation module (the GPC triad). A second layer shows the signaling transcriptional pathways (in green font) that influence the level and activity of the triad found in the innermost layer. The third layer (in red font) includes modifiers that influence and/or integrate the activities defined by the second and first layers. Modifiers and signaling pathways from both cell autonomous and cell non-autonomous origin. Modified figure reproduced with permission from Elsevier Press [2].

While small, single domain proteins can fold efficiently in the test tube, we now appreciate that these and multi-domain proteins generated in the crowded environment of the cell often fail to do so. This is because there are energy barriers in the landscape model (Fig. 2a, peaks and troughs) [10,11], that dictate the kinetics and thermodynamics of folding intermediates in the path(s) required to achieve the native folded state (Fig. 2a, red circles and ‘N’ in figure). The native state here is defined as the state with the lowest energy- which may or may not be the biologically important state [4]. To avoid off-pathway misfolding, degradation and/or aggregation that can occur during progress through intermediate folding steps in biology (Fig. 2a, red circles and white arrows), PN components are thought to interact with the polypeptide chain to generate and protect biological function (Fig. 2a, black and gray arrows) [1,2].

Coupling of the folding energy landscape with the PN

Coupling of the folding energy landscape with the PN

Figure 2 Coupling of the folding energy landscape with the PN

(a) Illustrated is a bumpy energy landscape funnel (http://www.dillgroup.ucsf.edu/) in which an unfolded protein proceeds along various intermediate steps (red circles) that can pose energetic barriers to achieve the native state (N) at the base of the funnel. The white arrows indicate potential pathways through various folding intermediates that the nascent protein may take to reach the native state. The solid black and blue (synthesis and folding modules) and the dashed gray (degradative module) arrows illustrate how different components of the PN may influence pathway choice. The dashed oval indicates that all intermediates are potential steps in which a protein can be targeted for degradation. Hsp90 is thought to principally facilitate late folding events (solid blue lines). (b) The energy landscape (a slice through the funnel illustrated in panel a) illustrates the central role of the ATPase cycle in synthesis, folding and degradative modules in managing the biology of the protein structure in the cell to achieve function. By coupling the energy of ATP hydrolysis (X-axis) by PN ATPase machines with the energetics imparted in the chemistry of the amino acid sequence of the polypeptide chain (Y-axis), PN ATPases maintain the protein fold in a dynamic state- essential for biology. Right side of panel illustrates energy barriers necessary to achieve a functional fold (black arrow) relative to the energetics associated with misfolding (red and orange arrows). The additional energetic demands challenging GPC through misfolding (red line) or aggregation (short orange line) are illustrated. Purple arrows indicate potential steps for GPC to alter folding kinetics and energetics to promote proteome balance and cell health. Abbreviations: sHsp (small heat shock proteins); TRiC (TCP1-ring complex)

The PN is an integrated system consisting of chaperones, folding enzymes, degradation components, and regulatory pathways that control the composition and concentration of the general proteostasis system [5,12] (Fig. 1). PN components include the molecular chaperones/co-chaperones belonging to the Hsc/Hsp (Hsc/p) 70 and 90 families [13], the GroEL/TCP1-ring complex (TRiC)/chaperonin family of folding machines [14], tetratricopeptide repeat (TRP)-domain containing proteins, proteins that modulate oxidative folding (e.g., protein disulfide isomerases [15]), and degradation components comprising both the cytosolic ubiquitin-proteasome and membrane-linked autophagy-lysosome systems [6,16] (Fig. 1). Some PN components are highly abundant (e.g., ribosome, Hsc/p70-Hsp90, proteasome/lysosome) and provide a cellular ‘buffer’ for synthesis, folding and/or degradation [12]. Most others function as specialists, either alone or together with the Hsc/p70 and Hsp90 systems, to synthesize and/or maintain specific folds for the highly evolved dynamic functions dictating extant organismal physiology. Regulation of the composition of the PN occurs through a number of signaling pathways including the unfolded protein response (UPR) [17], the heat shock response (HSR) [7,18,19], oxidative stress pathways [20], and growth factor and diet sensitive pathways [13], among others. A simplistic view of the PN is that components directing synthesis, (un)folding, and degradation could be considered as a triad of modules (Fig. 1, dark black lines). Triad modules recognize the chemical properties of polypeptide folding intermediates (Fig. 2), yet are integrated by the overall composition of the PN to maintain normal biological function.

It is important to recognize that the PN is unique for each type of cell and the numerous subcellular compartments within a eukaryotic cell. These environments change differentially during development, aging and in response to physiological stress [2,21]. Moreover, the PN is constantly challenged by changes in the composition of the amino acid pool, metabolites/co-factors, ion balance, genetic-epigenetic-environmental triggers, and viral/bacterial pathogens. These factors not only affect the inherited capacity of the proteostasis program, but are readily sensed by the above regulatory signaling pathways that attempt to rebalance the proteome to preserve healthspan [1,3,4]. Thus, the PN is dynamically tuned to cellular function as prescribed by cell autonomous processes and cell non-autonomous signals that optimize folding for function in complex organismal environments [7,19].

Role of ATP in maintaining proteome balance

The capacity of the PN to maintain proteome balance in the cytosol and exocytic/endocytic trafficking compartments, that is, the Yin-Yang relationship between generating and maintaining a functional fold or targeting a protein for degradation [4], is referred here as general proteostasis control (GPC). GPC emphasizes that function of a polypeptide chain is tightly linked to the local composition of the PN triad- the environment being the ultimate arbitrator of biological folding for function. What is a wild-type protein fold in one PN environment becomes a ‘mutant’ in another and can be removed and/or challenge the health status of the cell. The former is evident in the cyclical stability of proteins during cell cycle, or the transient stability observed in developmental programs. The latter is observed in, for example, numerous sporadic aggregation diseases, type II diabetes and cancer [2].

Both subtle and global challenges to protein folding energetics directly challenge the dynamics of the kinetics of protein folding and its thermodynamic stability. Thus, there is a close link between PN folding for function (Fig. 2a) and ATP-based proteostasis machines that manipulate the energy landscape dictated by the unique chemistries of amino acid sequence of each polypeptide chain (Fig. 2b). For example, during protein biogenesis, newly synthesized polypeptides are generated by the ribosome at a very high energy cost and in response to protein specific translational control programs. They emerge from the ribosome with exposed hydrophobic residues that are recognized by the folding module of the PN to prevent protein aggregation. This first step of GPC faced by nascent proteins is often regulated by members of the Hsc/p70 family [12] and/or the TRiC/chaperonin ATPase machines [22]. While TRiC ATPases appear to be dedicated to folding, the Hsc/p70 ATPases function to either promote folding/assembly of newly synthesized proteins or direct ‘non-native’ polypeptides to degradation [23], serving as a key linker between the various PN modules (Fig. 1). Thus, the Hsc/p70 system plays a critical role in proteome balance in response to energetics of the polypeptide chain [4].

Hsc/p70 family of chaperones, utilize ATP-dependent cycles of client binding and release in response to a plethora of accessory proteins, called co-chaperones. In the case of Hsc/p70 these include nucleotide exchange factors (NEFs) composed by the Bag (BCL2 associated athanogene) family of proteins, which facilitate ADP release and ATP binding to promote Hsc/p70 client substrate release, and a large Hsp40/DnaJ family of co-chaperones that stimulate the ATPase activity of Hsc/p70 and stabilize protein client-chaperone interactions [24]. Thus, Hsc/p70 co-chaperones will not only fine-tune Hsc/p70 client substrate specificity but dictate the cellular fate of the protein client [13,25,26].

Proteins that interact with the Hsc/p70 arm of GPC are in many cases subject to a second level of maintenance by the Hsp90 system [27]. The Hsp90 ATPase machinery appears to recognize dynamic facets of more folded substrates to modulate their activity(s) (Fig. 2a, blue lines), [27,28] (www.picard.ch/downloads/Hsp90interactors.pdf). As is seen for the Hsc/p70 system, a unique collection of co-chaperones also regulate Hsp90 ATPase activity. Hsp90 co-chaperones include the ATPase activator Aha1 and the ATPase inhibitor p23, as well as Cdc37, HOP, protein-disulfide isomerases (PPIases), and a large family of TRP-domain containing proteins. Depending on the local activity/composition of the co-chaperone environment, Hsp90 can promote either protein stability or degradation of folding intermediates- dynamically altering the proteome balance [4] (Fig. 2b).

Like the folding GPC module (Fig. 1), the degradation module involving the proteasome and the autophagy-lysosome pathways are intensely ATP-dependent [29]. While many of the regulatory factors that control function of these degradative machines remain to be determined, client targeting to multiple degradative pathways is generally regulated by the ubiquitin/sumoylation system. Targeting for degradation utilizes a highly diverse (>300) set of client specific ligases that utilize the energy of ATP to prime polypeptide targets for destruction [23]. Thus, ATP-dependent cycling of synthesis, folding, and degradation modules provides an energetic link between the functional and degradation prone states of a target protein in biology.

While GPC has a universal high level of energy demand, it is important to realize that folding/function is highly compartmentalized. For example, the cytosol is a reducing environment maintaining folded proteins in the absence of disulfide bonding. In contrast, the endoplasmic reticulum (ER), the first step in the secretory pathway, is an oxidative environment where protein folding is driven by an evolutionarily related, but distinct set of luminal PN folding components. The folding module in the ER is tightly coupled by membrane translocation pathways to the reducing cytosolic proteasomal degradation module [23,30,31]. Recent studies [32] have shown that cytosolic GPC components important for generation of newly synthesized transmembrane polypeptides in the ER also modulate protein stability at the cell surface. Likewise, the lysosome not only handles internalized cargoes from the cell surface, but is a critical partner of the autophagosome pathway that engulfs a wide range of misfolded cytosolic proteins and dysfunctional organelles [29,33]. These results suggest the importance of as yet unknown cellular proteostasis sensors that unify and balance folding throughout the cell.

In summary, it is now clear that GPC may define energetic standards for each cell type that is linked in as yet to be determined ways by the activity of PN-linked ATPase machines. By coupling the chemistry of the polypeptide chain sequence and its associated folding energetics with the ATPase activity of PN modules (Fig. 2b), a biologically dynamic GPC standard generates the proper balance between the triad of synthesis, (un)folding, and degradation modules (Fig. 1). This standard defines the proteome balance in a healthy cell and its response to stress, disease, injury and aging programs.

Modeling proteostasis

An understanding of the rules guiding GPC to achieve protein function involves integrating the chemistry of the polypeptide sequence with the activity of PN components (Fig. 2). For this purpose, we applied Michaelis-Menten formalism in the FoldEx model to describe how the inherent chemistry and energetics of the polypeptide chain can be read and manipulated by the PN for proteins trafficking through the exocytic pathway [34]. The concepts stemming from the FoldEx model were extended to describe a more encompassing model of how folding energetics and the PN work together. We refer to this new model asFoldFx [2]. FoldFx is applicable to folding of proteins in all compartments of the cell and the extracellular space in response to the composition of the local PN (Fig. 1). In FoldFx, the operational goal of the triad of protein synthesis, (un)folding, and degradation modules through GPC is to achieve ‘function’.

A key feature of the FoldFx model which rigorously defines the activity of GPC is the concept of the ‘proteostasis boundary’ or PB [2] (Fig. 3a). The PB can be used to define the minimal energetic properties that a protein must have to achieve normal function in response to the local PN. The PB is best illustrated in a 3-dimentsional (3D) space diagram as a curved surface. The position of a protein in 3D is determined by its inherent folding kinetics, misfolding kinetics, and thermodynamics (Fig. 3a). The curved shape of the PB is dictated by the variable concentration of proteostasis components. These are, in turn, defined by the genetic, epigenetic, and intrinsic and extrinsic factors that regulate PN pathways and thereby tune the PN for specific client functionality. Beneath the boundary is a normal biological network, defined by nodes (the proteins) and edges (their links to other proteins within the network) (Fig. 3a). Each node is positioned according to its folding energetics (its unique folding and misfolding rate and stability). In a healthy cell, each node and its link (the edges in Fig. 3a) are embraced by the curved space of the PB, indicating that the PN is sufficient to maintain normal function (Fig. 3a). In disease, a node falls outside the embrace of the PB, resulting in misfolding, aggregation and/or degradation (Fig. 3b).

proteostasis boundary (PB)

proteostasis boundary (PB)

Fig 3. The proteostasis boundary (PB)

The position of each node (protein) relative to the PB (curved surface) responsible for biological function is defined by a protein’s folding properties: folding kinetics (Z-axis), misfolding kinetics (Y-axis) and thermodynamic stability (X-axis). Each line defines a physical or functional interaction between two proteins in the system. The location of the PB in 3D space is established by the composition of the PN and modulated by the GPC triad. (a) All of the nodes are within the PB boundary in a healthy cell. (b) Mutations or aberrant post-translational modifications can alter folding kinetics and energetics, making their corresponding nodes and edges fall outside (above the curved surface) of the PB. This space in the 3D plot does not support function of the energetically destabilized variant and can lead to either degradation (red node) or protein aggregation (black node). The loss of connectivity to proteins within the embrace of the PB can challenge the entire PN leading to cell, tissue, and organismal disease. Reproduced with permission from Elsevier Press [2].

Yin-Yang of proteome balance

Yin-Yang of proteome balance

Figure 4 Modeling the Yin-Yang of proteome balance in health, disease, and in response to proteostasis therapeutics

(Panel a) Proteome balance [4] in a healthy cell is determined by the composition of the synthesis and folding modules (FM) (the Yang on the left side of diagram) and degradative module (DM) (the Yin on the right side of diagram). GPC1 determines the position of the PB (the S-shaped curve) and healthspan. The dashed lines illustrate that misfolding and aging can challenge the position of the PB. (Panel b) Aging and unfolding move the PB to the left resulting in compromised proteostasis function (GPC2) and an unhealthy cell by triggering increased degradation and/or accumulation of protein aggregates. (Panel c) Biological signaling pathways including the HSR (HSF1 and IGF1-R/FOXO pathways), UPR, oxidative stress response (OSR), diet, IGF1-R and/or proteostasis targeted therapeutics can move the Yin-Yang balance defined by the PB to the right generating GPC3. GPC3 provides an environment that protects the cell from physiological stress, misfolding and aging, allowing the cell to return to GPC1.

Therapeutics in modeling of the GPC triad

Multiple lines of evidence suggest that protection to misfolding disease and aging can be boasted through multiple pathways that regulate the expression of PN components (e.g., HSR, IGF1-R signaling, diet restriction and pathways that protect against oxidative stress mentioned above) [1,3] (Fig. 1Fig. 4c -GPC3). Modulation of components of the PN biologically by targeting individual PN components with siRNA implicated in these pathways can dramatically affect the outcome of disease. For example, depletion of Aha1 (an Hsp90 ATPase regulator) or E3ligase RMA1/CHIP, partially restores functionality in cystic fibrosis (CF) models [40,41]. These represent changes in distinct arms of the Yin-Yang balancing act, involving both cytosolic and exocytic/endocytic membrane trafficking pathways managed by the GPC triad (Fig. 4c). Moreover, overexpression of Hsc/p70 and its co-chaperones has been shown to reduce aggregation and toxicity in models of neurodegenerative/misfolding diseases, such as AD [42], prion disease [43], and HD [24]. Overexpression of Hsp40 reduces polyQ inclusion formation and toxicity [24] while the co-chaperone CHIP suppresses the toxicity of α-synuclein and polyQ proteins [44], and reduces accumulation of tau and Aβ [45], possibly through removal of aggregated misfolded proteins via the proteasome. The cofactor Bag1 also has been shown to reduce toxicity caused by polyQ Huntington aggregates [46]. Indeed, the FoldFx model predicts that bolstering the operation of the PN along specific axis’s is likely to not only improve healthspan, but also simultaneously improve longevity- the ultimate test of a therapeutic approach [1,2,7,8,47].

An increasing number of small molecules are now recognized to impact these pathways and provide protective function to human disease [4,48,49] (Fig. 4c). For example, the inhibition of the proteasome arrests myeloma disease [50], kinetic stabilizers arrest onset of TTR [51], histone deacetylases function to correct CF [52], Friedreich Ataxia [53], HD [54] and poly-glutamine (polyQ) disease [26] and have a strong like to GPC [18].

It is now clear that the ultimate goal for FoldFx modeling will be to utilize it as framework for further understanding of human biology and for development of small molecule therapeutics that manipulate GPC triad to maintain and restore human health.

2.1.6.5 To Be or Not to Be. How Selective Autophagy and Cell Death Govern Cell Fate

Douglas R. GreenBeth Levine
Cell    Mar 2014; 157(1):65–75
http://dx.doi.org:/10.1016/j.cell.2014.02.049

The health of metazoan organisms requires an effective response to organellar and cellular damage either by repair of such damage and/or by elimination of the damaged parts of the cells or the damaged cell in its entirety. Here, we consider the progress that has been made in the last few decades in determining the fates of damaged organelles and damaged cells through discrete, but genetically overlapping, pathways involving the selective autophagy and cell death machinery. We further discuss the ways in which the autophagy machinery may impact the clearance and consequences of dying cells for host physiology. Failure in the proper removal of damaged organelles and/or damaged cells by selective autophagy and cell death processes is likely to contribute to developmental abnormalities, cancer, aging, inflammation, and other diseases.

As in all living things, each of our cells suffers the slings and arrows of outrageous fortune, facing damage from without and within. And, like the Prince of Denmark, each decides whether to be or not to be. To be, the cell must monitor and repair the damage. If not, it will “melt, thaw, and resolve itself into a dew,” dying and cleared from the body by other cells (with apologies to Shakespeare for scrambling his immortal words).

Here, we consider how the molecular pathways of autophagy and cell death and, ultimately the clearance of dying cells, function in this crucial decision. Although autophagy and cell death occur in response to a wide variety of metabolic and other cues, our focus is restricted here to those aspects of each that are directly concerned with the quality control of cells—the “garbage” (cellular or organellar) that must be managed for organismal function. And although there are many important functions of quality control mechanisms (e.g., DNA and membrane repair, cell growth and cell-cycle control, unfolded protein and endoplasmic reticulum (ER) stress responses, innate and adaptive immunity, and tumor suppression), our discussion is limited to the selective disposal of damaged or otherwise unwanted organelles and, when necessary, damaged or excess cells and how the autophagic and cell death mechanisms function in these processes. Overall, we focus on the overriding theme of waste management, but as we will see, many of the links between these elements remain largely unexplored. Further, although a great deal of what we know was delineated in yeast and invertebrate model systems, we largely restrict our consideration to what is known in mammals.

Engaging Autophagy

The process of macroautophagy (herein, autophagy) is best understood in the context of nutrient starvation (Kroemer et al., 2010 and Mizushima and Komatsu, 2011). When energy in the form of ATP is limiting, AMP kinase (AMPK) becomes active, and this can drive autophagy. Similarly, deprivation from growth factors and/or amino acids leads to the inhibition of TORC1, which, when active, represses conventional autophagy. As a result of AMPK induction and/or TORC1 inhibition, autophagy is engaged, although other signals may bypass AMPK and TORC1 to engage autophagy (Figure 1).

general-autophagy-pathway

general-autophagy-pathway

http://ars.els-cdn.com/content/image/1-s2.0-S0092867414002943-gr1.jpg

Figure 1. Overview of the General Autophagy Pathway

Cellular events and selected aspects of the molecular regulation involved in the lysosomal degradation pathway of autophagy in mammalian cells are shown. Several membrane sources may serve as the origin of the autophagosome and/or contribute to its expansion. A “preinitiation” complex (also called the ULK complex) is negatively and positively regulated by upstream kinases that sense cellular nutrient and energy status, resulting in inhibitory and stimulatory phosphorylations on ULK1/2 proteins. In addition to nutrient-sensing kinases shown here, other signals involved in autophagy induction may also regulate the activity of the ULK complex. The preinitiation complex activates the “initiation complex” (also called the Class III PI3K complex) through ULK-dependent phosphorylation of key components and, likely, other mechanisms. Activation of the Class III PI3K complex requires the disruption of binding of Bcl-2 antiapoptotic proteins to Beclin 1 and is also regulated by AMPK and a variety of other proteins not shown in the figure. The Class III PI3K complex generates PI3P at the site of nucleation of the isolation membrane (also known as the phagophore), which leads to the binding of PI3P-binding proteins (such as WIPI/II) and the subsequent recruitment of proteins involved in the “elongation reaction” (also called the ubiquitin-like protein conjugation systems) to the isolation membrane. These proteins contribute to membrane expansion, resulting in the formation of a closed double-membrane structure, the autophagosome, which surrounds cargo destined for degradation. The phosphatidylethanolamine-conjugated form of the LC3 (LC3-PE), generated by the ATG4-dependent proteolytic cleavage of LC3, and the action of the E1 ligase, ATG7, the E2 ligase, ATG3, and the E3 ligase complex, ATG12/ATG5/ATG16L, is the only autophagy protein that stably associates with the mature autophagosome. The autophagosome fuses with a lysosome to form an autolysosome; inside the autolysosome, the sequestered contents are degraded and released into the cytoplasm for recycling. Late endosomes or multivesicular bodies can also fuse with autophagosomes, generating intermediate structures known as amphisomes, and they also contribute to the formation of mature lysosomes. Additional proteins (not depicted in diagram) function in the fusion of autophagosomes and lysosomes. The general autophagy pathway has numerous functions in cellular homeostasis (examples listed in box labeled “physiological functions”), which contribute to the role of autophagy in development and protection against different diseases.

The “goal” of the autophagy machinery is to deliver cytosolic materials to the interior of the lysosomes for degradation, thereby recovering sources of metabolic energy and requisite metabolites in times of starvation (general autophagy). Autophagy can similarly function to target damaged or otherwise unwanted organelles to lysosomes for removal (selective autophagy). Although we focus here primarily on selective autophagy, it is useful to also consider general autophagy to highlight similarities and distinctions between the two processes.

In both cases a double-membrane structure, the autophagosome, fuses with lysosomes to deliver the contents for degradation, and this involves a proteolipid molecule, LC3-II, a component of the autophagosome composed of a protein, LC3, and a lipid, phosphatidylethanolamine. LC3-II is generated by a process resembling ubiquitination, involving E1, E2, and E3 ligases (Figure 1). The parent molecule, LC3-I, is generated by the action of a protease, ATG4, which cleaves LC3 to produce LC3-I. This is bound by the E1, ATG7, and transferred to the E2, ATG3. The E3 ligase is a complex composed of ATG16L and ATG12-5; the latter is produced by another reaction in which ATG12 is bound by the E1, ATG7, transferred to a different E2, ATG10, and from there to ATG5. The process by which ATG12-5 is formed—and, subsequently, LC3-II (also known as LC3-PE) is generated—is referred to as the elongation reaction and is required for the formation of the autophagosome.

As discussed in the Introduction, autophagy can function to remove damaged or otherwise unwanted organelles in a cell. By “unwanted,” we mean organelles that are removed during differentiation (e.g., in maturing erythrocytes) or when environmental factors (e.g., hypoxia) disfavor some organelles in the cell. We refer to this process as selective autophagy. When considering selective autophagy, we are faced with two problems. First, how does the process “know” which structures or organelles to target for removal? And second, how does this occur even when the conventional autophagy machinery is suppressed (at least partially), such as in nutrient-rich conditions? With regard to the latter, the problem is confounded by the simple fact that lysosomal digestion of organelles will itself provide amino acids and other metabolites, presumably activating TORC1 and suppressing AMPK. As we have seen, such conditions inhibit the function of the preinitiation complex. Nevertheless, animals lacking Ulk1 display a defect in at least one selective autophagic process, that of efficient removal of mitochondria during erythrocyte development (Kundu et al., 2008). Presumably, there are ways to bypass conventional inhibitory mechanisms to engage Ulk1 activity and promote selective autophagy in some settings. Alternatively, the preinitiation complex may be bypassed in some situations. We will not fully resolve this paradox here but perhaps provide clues as we consider the first problem—how specific cargoes are marked for clearance.

Before considering this issue, it may be useful to note that, even in nutrient-starved conditions, autophagy may be selective. Ribosomes represent a major portion of the biomass of many cells, and upon starvation, these are more rapidly removed than other structures in the cell (Cebollero et al., 2012). Similarly, there appears to be selective removal of peroxisomes during starvation (Hara-Kuge and Fujiki, 2008). The same may be the case for ER (reticulophagy), although it remains possible that, in this case, this is a consequence of developing the requisite autophagosomes for nutritional supplementation using the ER membrane (see above). Another possible selection during starvation is the preservation of functional mitochondria; because these are necessary for the catabolism of free fatty acids or amino acids and for the optimal generation of energy from glucose (all generated by lysosomal digestion), it simply does not make sense that inadvertent removal of mitochondria during starvation would be permitted. Such possible “antiselection,” however, has not been fully documented or adequately explored.

Targeting in selective organellar autophagy is perhaps best analyzed in the clearance of mitochondria (mitophagy) and peroxisomes (pexophagy). Tissues or cells lacking requisite components of the autophagy elongation machinery (e.g., ATG5 and ATG7) often display greatly increased numbers of apparently damaged mitochondria (Mizushima and Levine, 2010) and peroxisomes (Till et al., 2012). That said, there is evidence that, even in the absence of ATG5 and ATG7, some selective mitophagy continues via unknown mechanisms, perhaps via vesicular trafficking between mitochondria and lysosomes (Soubannier et al., 2012). Nevertheless, accumulated observations indicate that the autophagy elongation machinery and autophagosome formation are important for selective autophagy of damaged or otherwise unwanted organelles.

One way in which damaged mitochondria are removed by autophagy involves the action of two proteins, PINK1 and Parkin (Figure 2). PINK1 is a kinase that is constitutively imported into functional mitochondria and degraded by the rhomboid protease, PARL. As with most mitochondrial import, this requires the transmembrane potential of the inner mitochondrial membrane, ΔΨm. Loss of this potential, which can occur when the electron transport chain is damaged or if protons are allowed to pass freely across the inner membrane (i.e., due to the expression of uncoupler protein [UCP], presence of environmental protonophores, or as a consequence of the mitochondrial permeability transition) causes active PINK1 to accumulate on the cytosolic face of the outer mitochondrial membrane. This then recruits and activates Parkin, which is a ubiquitin E3-ligase, which then ubiquitinates proteins on the mitochondria.

roles-of-autophagy-proteins-in-the-removal-of-unwanted-organelles-and-in-the-removal-of-cell

roles-of-autophagy-proteins-in-the-removal-of-unwanted-organelles-and-in-the-removal-of-cell

http://ars.els-cdn.com/content/image/1-s2.0-S0092867414002943-gr2.jpg

Figure 2. Roles of Autophagy Proteins in the Removal of Unwanted Organelles and in the Removal of Cells

The left panel shows Parkin-dependent and Parkin-independent mechanisms involved in the selective degradation of mitochondria by autophagy (mitophagy). In Parkin-dependent mitophagy, mitochondrial damage and loss of mitochondrial membrane potential (ΔΨm) lead to localization of the kinase, PINK1, on the cytoplasmic surface of the mitochondria, resulting in recruitment of the E3 ubiquitin ligase, Parkin, to the mitochondria, followed by the ubiquitination of mitochondrial proteins and the formation of an isolation membrane that surrounds the damaged mitochondria. In Parkin-independent mitophagy, proteins such as Nix (shown in figure), BNIP3, and FUNDC1 (not shown in the figure) bind to LC3. Other autophagy proteins may be involved in Parkin-dependent and Parkin-independent mitophagy (discussed in the text). The precise details of how an isolation membrane is formed around specific mitochondria earmarked for degradation are unclear. Other damaged/unwanted organelles such as ER, peroxisomes, and lipid droplets can also be degraded by selective autophagy; the molecular mechanisms of these forms of selective autophagy are not well understood in mammalian cells. The right panel depicts roles of LAP of apoptotic corpses and of live cells (entosis). In LAP, components of the autophagy initiation complex (Beclin 1 and VPS34) are recruited to the phagosome, which leads to recruitment of LC3-PE and facilitation of phagolyosomal fusion. This process requires other components of the elongation machinery, but—in contrast to general autophagy or selective autophagy—proceeds independently of the ULK preinitiation complex.

It is self-evident that the selective removal of damaged or excess organelles is a critical homeostatic process, but beyond this, our information on what happens when this goes wrong is somewhat limited. There is an accumulation of damaged organelles (including mitochondria, perixosomes, and ER) and organ degeneration in mice with tissue-specific knockout of core autophagy genes such as Atg5 and Atg7in liver, neurons, heart, pancreatic acinar cells, muscle, podocytes, adipocytes, and hematopoietic stem cells ( Mizushima and Levine, 2010). Although it may not be possible to dissociate the effects of general autophagy from those of selective autophagy, it is reasonable to postulate that these phenotypes are partly related to defects in selective organellar autophagy, and at a minimum, such studies unequivocally establish a role for autophagy genes in the removal of damaged organelles in vivo.

The proper removal of excess or unwanted mitochondria is likely necessary for certain key aspects in development. As discussed above, the mitophagy factor Nix is required for mitochondrial clearance during erythroid maturation in vivo (Sandoval et al., 2008), and mouse erythrocytes lacking general autophagy factors such as Ulk1 and Atg7 fail to clear mitochondria ( Kundu et al., 2008 and Mortensen et al., 2010). Reduction in mitochondrial number may also contribute to the role of core autophagy genes, such as Atg7, in white adipocyte differentiation ( Zhang et al., 2009). An intriguing question is whether selective mitophagy—of paternal mitochondria—during embryonic development underlies mammalian maternal mitochondrial DNA (mtDNA) inheritance ( Levine and Elazar, 2011). In C. elegans, several studies showed that paternal mitochondria and mtDNA are eliminated from the fertilized oocyte by autophagy (with surrounding membranous organelles, but not the mitochondria themselves, marked by ubiquitin) ( Al Rawi et al., 2011Sato and Sato, 2011 and Zhou et al., 2011). In one of these studies ( Al Rawi et al., 2011), p62 and LC3 were also found to colocalize with sperm mitochondria after fertilization in mice. However, a more recent study confirmed that sperm mitochondria colocalized with p62 and LC3 in mouse embryos but concluded that this was not involved in their degradation ( Luo et al., 2013). Thus, the question of whether selective mitophagy explains why our mitochondrial DNA comes mainly from our mothers remains to be resolved.

An emerging far-reaching biomedical paradigm is that defects in mitophagy—presumably through resulting abnormal mitochondrial function, abnormal mitochondrial biogenesis, and/or increased mitochondrial generation of reactive oxygen species (leading to genomic instability and enhanced proinflammatory signaling) —contribute to cancer, neurodegenerative diseases, myopathies, aging, and inflammatory disorders (reviewed in Ding and Yin, 2012Green et al., 2011Lu et al., 2013 and Narendra and Youle, 2011). This paradigm intuitively makes sense and is consistent with a large body of literature in autophagy-deficient mice. Yet, it is difficult to establish a direct causal relationship between mitophagy defects and disease in mice lacking general autophagy factors. Presumably, phenotypes observed in mice lacking selective mitophagy factors may be more informative. For example, Parkin-deficient mice have cancer-prone phenotypes, including accelerated intestinal adenoma development (in the background ofApc mutation) ( Poulogiannis et al., 2010) and the development of hepatocellular carcinoma ( Fujiwara et al., 2008). However, these studies also do not provide direct evidence that Parkin-mediated mitophagy, rather than other potential effects of Parkin, contribute to its role in tumor suppression. Moreover, mice lacking Ulk1 ( Kundu et al., 2008) or Nix ( Sandoval et al., 2008) have progressive anemia with mature erythrocytes containing mitochondria but no other obvious cancer-prone defects. In addition, Parkin-null mice clear defective mitochondria normally in dopaminergic neurons in the substantia nigra ( Sterky et al., 2011), even though PARKIN and PINK1 mutations in humans lead to overt degeneration of these neurons and Parkinson’s disease. It is not unlikely that there are several overlapping mechanisms for selective autophagy that compensate for such deficiencies. Another possible explanation for the lack of more striking phenotypes in mice lacking selective autophagy factors is that other processes help to mediate the damage that should accrue when damaged organelles are not effectively cleared from cells, including perhaps the removal of the cells themselves.

cell-death-pathways-engaged-by-cellular-damage

cell-death-pathways-engaged-by-cellular-damage

Figure 3. Cell Death Pathways Engaged by Cellular Damage

Cellular damage induces cell death by inducing expression and/or modification of proapoptotic BH3-only proteins of the Bcl-2 family (inset), which engage the mitochondrial pathway of apoptosis, in which MOMP releases proteins of the mitochondrial intermembrane space. Among these is cytochrome c, which activates APAF1 to form a caspase-activation platform (the apoptosome) that binds and activates caspase-9. This then cleaves and thereby activates executioner caspases to promote apoptosis. Cellular damage can also induce the expression of death ligands of the TNF family, which bind their receptors to promote the activation of caspase-8 by FADD. The latter is antagonized by expression of c-FLIPL, and the caspase-8-FLIP heterodimer does not promote apoptosis but instead blocks another cell death pathway engaged by death receptors, necroptosis. Necroptosis involves the activation of RIPK1 and RIPK3, resulting in phosphorylation and activation of the pseudokinase, MLKL, which promotes an active necrotic cell death.

Noncanonical Autophagy Pathway and Clearance of Dying Cells

When dying cells are engulfed by a macrophage or other cell, the corpse-containing phagosome is rapidly decorated with the autophagic protein, LC3, which facilitates fusion with lysosomes and destruction of the cargo (Sanjuan et al., 2009). This LC3-associated phagocytosis (LAP) is dependent on the Beclin 1-VPS34 complex and the elongation machinery, but rather than generating a double-membrane autophagosome, LC3-II is generated on the single-membrane phagosome itself (Figure 2). In contrast to general or selective organellar autophagy, however, LAP appears to proceed independently of the ULK1 preinitiation complex in mammalian cells (Henault et al., 2012). If LAP is defective (due, for example, to lack of the requisite autophagy machinery), the corpse is not digested, and macrophages produce high levels of proinflammatory cytokines (Martinez et al., 2011). This may have implications for disease. For example, systemic lupus erythematosis is often characterized by circulation of “LE cells,” which have been identified as macrophages containing an undigested corpse. It is possible that proinflammatory signals emitted by such macrophages contribute to the disease.

The Interface of Autophagy and Cell Death in Tissue Homeostasis

LAP (see above) may also represent a link between autophagy components and a cell death process (and not only the clearance of dying cells), as engulfment of cells may restrict oncogenesis naturally. Immortalized mammary epithelial cells, upon loss of anchorage to basement membranes, engulf each other in a process called “entosis” (Florey et al., 2010). The engulfed cell dies by apoptosis due to nutrient deprivation. If the cell expresses an antiapoptotic signal, such as Bcl-2, it is nevertheless killed as LAP in the engulfing cell promotes fusion with lysosomes (Figure 2). However, if cells resist apoptosis and fail to engage LAP (e.g., due to ablation of the autophagic machinery), such immortalized cells escape entosis and grow in an anchorage-independent manner. The implications of such an interplay between apoptosis and autophagy at the cellular level has obvious consequences for understanding oncogenesis.

In thinking about general autophagy (in response to metabolic stress), selective autophagy (in response to damaged organelles), and cell death (as a consequence of excessive damage), it is obvious that the pathways crosstalk at a superficial level. That is, a cell that is defective for autophagy will necessarily be more prone to die if faced with nutrient deprivation. Cells lacking selective autophagy will accumulate damaged organelles such as mitochondria, which can generate signals (e.g., ROS) that promote further damage and ultimately cell death. If cell death does not occur, the ensuing dysfunction may promote severe effects in the form of oncogenesis. And, of course, a cell that engages death pathways will circumvent any benefit that might arise from autophagy. In a recent study, the extent of autophagy of individual cells in a population inversely correlated with the likelihood that a cell would die in response to engagement of the death receptor pathway of apoptosis (Gump et al., 2014).

There are more fundamental molecular interactions between these pathways, but it is difficult to parse how specific interactions contribute to cross-regulation in the face of the overarching effect of apoptotic defects on cellular health. For example, Beclin 1 is bound and inhibited by the antiapoptotic Bcl-2 proteins (Pattingre et al., 2005), and proapoptotic BH3-only proteins appear to be capable of disrupting this interaction to promote autophagy (Maiuri et al., 2007). Other autophagy components also interact with apoptotic players, but again, it is unclear whether these interactions, per se, influence cell fate.

We began our discussion with what may be the most fundamental dichotomy in biology, to be or not to be. At the cellular level, the question might be less elegantly posed along these lines: should we (the cell) be functional or, if not, die? Or, if we are dysfunctional and survive, do we risk compromising the life of the organism? Do we unite the fundamental pathways of garbage disposal, selective autophagy, and active cell death through complex (and largely unexplored) molecular interactions, or do we let the thresholds of damage dictate which pathway holds sway against the thousand natural shocks that flesh is heir to (again, with apologies to the Bard)? Those are the questions.

 

2.1.6.6 Signaling cell death from the endoplasmic reticulum stress response

Shore GC, Papa FR, Oakes SA.
Curr Opin Cell Biol. 2011 Apr; 23(2):143-9
http://dx.doi.org:/10.1016/j.ceb.2010.11.003

Inability to meet protein folding demands within the endoplasmic reticulum (ER) activates the unfolded protein response (UPR), a signaling pathway with both adaptive and apoptotic outputs. While some secretory cell types have a remarkable ability to increase protein folding capacity, their upper limits can be reached when pathological conditions overwhelm the fidelity and/or output of the secretory pathway. Irremediable ‘ER stress’ induces apoptosis and contributes to cell loss in several common human diseases, including type 2 diabetes and neurodegeneration. Researchers have begun to elucidate the molecular switches that determine when ER stress is too great to repair and the signals that are then sent from the UPR to execute the cell.

Connections from the UPR to the Mitochondrial Apoptotic Pathway

Connections from the UPR to the Mitochondrial Apoptotic Pathway

Connections from the UPR to the Mitochondrial Apoptotic Pathway

Under excessive ER stress, the ER transmembrane sensors IRE1α and PERK send signals through the BCL-2 family of proteins to activate the mitochondrial apoptotic pathway. In response to unfolded proteins, IRE1α oligomerizes and induces endonucleolytic decay of hundreds of ER-localized mRNAs, depleting ER protein folding components and leading to worsening ER stress. Phosphorylated IRE1α also recruits TNF receptor-associated factor 2 (TRAF2) and activates apoptosis signaling kinase 1 (ASK1) and its downstream target c-Jun NH2-terminal kinase (JNK). JNK then activates pro-apoptotic BIM and inhibits anti-apoptotic BCL-2. These conditions result in dimerization of PERK and activation of its kinase domain to phosphorylate eukaryotic translation initiation factor 2α (eIF2α), which causes selective translation of activating transcription factor-4 (ATF4). ATF4 upregulates expression of the CHOP/GADD153 transcription factor, which inhibits the gene encoding anti-apoptotic BCL-2 while inducing expression of pro-apoptotic BIM. ER stress also promotes p53-dependent transcriptional upregulation of Noxa and Puma, two additional pro-apoptotic BH3-only proteins. Furthermore, high levels of UPR signaling induce initiator caspase-2 to proteolytically cleave and activate pro-apoptotic BID upstream of the mitochondrion. In addition to antagonizing pro-survival BCL-2 members, cleaved BID, BIM and PUMA activate Bax and/or Bak. Hence, in response to excessive UPR signaling, the balance of BCL-2 family proteins shifts in the direction of apoptosis and leads to the oligomerization of BAX and BAK, two multi-domain pro-apoptotic BCL-2 family proteins that then drive the permeabilization of the outer mitochondrial membrane, apoptosome formation and activation of executioner caspases such as Caspase-3. Figure adapted with permission from the Journal of Cell Science [58].

The lumen of the ER is a unique cellular environment optimized to carry out the three primary tasks of this organelle: calcium storage and release, protein folding and secretion, and lipid biogenesis [1]. A range of cellular disturbances lead to accumulation of misfolded proteins in the ER, including point mutations in secreted proteins that disrupt their proper folding, sustained secretory demands on endocrine cells, viral infection with ER overload of virus-encoding protein, and loss of calcium homeostasis with detrimental effects on ER-resident calcium-dependent chaperones [24]. The tripartite UPR consists of three ER transmembrane proteins (IRE1α, PERK, ATF6) that alert the cell to the presence of misfolded proteins in the ER and attempt to restore homeostasis in this organelle through increasing ER biogenesis, decreasing the influx of new proteins into the ER, promoting the transport of damaged proteins from the ER to the cytosol for degradation, and upregulating protein folding chaperones [5]. The adaptive responses of the UPR can markedly expand the protein folding capacity of the cell and restore ER homeostasis [6]. However, if these adaptive outputs fail to compensate because ER stress is excessive or prolonged, the UPR induces cell death. The cell death pathways collectively triggered by the UPR include both caspase-dependent apoptosis and caspase-independent necrosis. While many details remain unknown, we are beginning to understand how cells determine when ER stress is beyond repair and communicate this information to the cell death machinery. For the purposes of this review, we focus on the apoptotic outputs trigged by the UPR under irremediable ER stress. While the ER contains numerous additional signaling platforms and targets that respond to diverse apoptotic stimuli (eg., those associated with the Bap31 complex [7,8]), their formal link to UPR-driven apoptosis remains to be determined.

The proximal unfolded protein response sensors

UPR signaling is initiated by three ER transmembrane proteins: IRE1α, PERK, and ATF6. The most ancient ER stress sensor, IRE1α, contains an ER lumenal domain, a cytosolic kinase domain and a cytosolic RNase domain [9,10]. In the presence of unfolded proteins, IRE1α’s ER lumenal domains homo-oligomerize, leading first to kinase trans-autophosphorylation and subsequent RNase activation. Dissociation of the ER chaperone BiP from IRE1α’s lumenal domain in order to engage unfolded proteins may facilitate IRE1α oligomerization [11]; alternatively, the lumenal domain may bind unfolded proteins directly [12]. PERK’s ER lumenal domain is thought to be activated similarly [13,14]. The ATF6 activation mechanism is less clear. Under ER stress, ATF6 translocates to the Golgi and is cleaved by Site-1 and Site-2 proteases to generate the ATF6(N) transcription factor [15].

All three UPR sensors have outputs that attempt to tilt protein folding demand and capacity back into homeostasis. PERK contains a cytosolic kinase that phosphorylates eukaryotic translation initiation factor 2α (eIF2α), which impedes translation initiation to reduce the protein load on the ER [16]. IRE1α splices XBP1mRNA, to produce the homeostatic transcription factor XBP1s [17,18]. Together with ATF6(N), XBP1s increases transcription of genes that augment ER size and function[19]. When eIF2α is phosphorylated, the translation of the activating transcription factor-4 (ATF4) is actively promoted and leads to the transcription of many pro-survival genes [20]. Together, these transcriptional events act as homeostatic feedback loops to reduce ER stress. If successful in reducing the amount of unfolded proteins, the UPR attenuates.

However, when these adaptive responses prove insufficient, the UPR switches into an alternate mode that promotes apoptosis. Under irremediable ER stress, PERK signaling can induce ATF-4-dependent upregulation of the CHOP/GADD153 transcription factor, which inhibits expression of the gene encoding anti-apoptotic BCL-2 while upregulating the expression of oxidase ERO1α to induce damaging ER oxidation [21,22]. Sustained IRE1α oligomerization leads to activation of apoptosis signal-regulating kinase 1 (ASK1) and its downstream target c-Jun NH2-terminal kinase (JNK) [23,24]. Phosphorylation by JNK has been reported to both activate pro-apoptotic BIM and inhibit anti-apoptotic BCL-2 (see below). Small molecule modulators of ASK1 have been shown to protect cultured cells against ER stress-induced apoptosis, emphasizing the importance of the IRE1α-ASK1-JNK output as a death signal in this pathway [25]. In response to sustained oligomerization, the IRE1α RNase also causes endonucleolytic decay of hundreds of ER-localized mRNAs [26]. By depleting ER cargo and protein folding components, IRE1α-mediated mRNA decay may worsen ER stress, and could be a key aspect of IRE1α’s pro-apoptotic program [27]. Recently, inhibitors of IRE1α’s kinase pocket have been shown to conformationally activate its adjacent RNase domain in a manner that enforces homeostatic XBP1s without causing destructive mRNA decay [27], a potentially exciting strategy for preventing ER stress-induced cell loss.

When deciding whether to switch into apoptotic mode, cells might use one or more “timers” to indicate if UPR signaling remains continuously active under high or chronic ER stress. For example, sustained PERK activity could result in protracted translation attenuation, which should be incompatible with survival, as well as high levels of pro-apoptotic CHOP. Similarly, high-level mRNA degradation mediated by IRE1α may deplete ER protein folding capacity further, and along with JNK signaling push the cell towards apoptosis. Thus, the continuous activation of the proximal sensors IRE1α and PERK may constitute a “timer” that triggers the switch to apoptosis under irremediable ER stress. Moreover, the ultimate response may depend on cell context. For example, the ability of IRE1α to complex with regulators such as BAX/BAK and Bax Inhibitor 1 (BI-1) at the ER may influence its ability to remediate ER stress and/or potentially signal apoptosis [28,29].

The BCL-2 family and the Mitochondrial Apoptotic Pathway

A wealth of genetic and biochemical data argues that the intrinsic (mitochondrial) apoptotic pathway is the major cell death pathway induced by the UPR, at least in most cell types. This apoptotic pathway is set in motion when several toxic proteins (e.g., cytochrome c, Smac/Diablo) are released from mitochondria into the cytosol where they lead to activation of downstream effector caspases (e.g., Caspase-3) [30]. The BCL-2 family, a large class of both pro- and anti- survival proteins, tightly regulates the intrinsic apoptotic pathway by controlling the integrity of the outer mitochondrial membrane [31]. This pathway is set in motion when cell injury leads to the transcriptional and/or post-translational activation of one or more BH3-only proteins, a structurally diverse class of pro-apoptotic BCL-2 proteins that share sequence similarity only in a short alpha helix (~9–12 a.a.) known as the Bcl-2 homology 3 (BH3) domain [32]. Once activated, BH3-only proteins lead to loss of mitochondrial integrity by disabling mitochondrial protecting proteins (e.g., BCL-2, BCL-XL, MCL-1) and (for a subset) directly triggering the oligomerization of the multidomain pro-apoptotic BAX and BAK proteins that drive the permeabilization of the outer mitochondrial membrane.

ER stress has been reported to activate at least four distinct BH3-only proteins (BID, BIM, NOXA, PUMA) that then signal the mitochondrial apoptotic machinery (i.e., BAX/BAK) [3335]. Each of these BH3-only proteins is activated by ER stress in a unique way. For example, BID is proteolytically cleaved at a caspase recognition site into a potent apoptotic signal [33]. The Bim gene is transcriptionally upregulated and its protein product stabilized through dephosphorylation in response to ER stress [34]. Cells individually deficient in any of these BH3-only proteins are modestly protected against ER stress-inducing agents, but not nearly as resistant as cells null for their common downstream targets BAX and BAK [36]—the essential gatekeepers to the mitochondrial apoptotic pathway. Moreover, cells genetically deficient in both Bim andPuma are more protected against ER stress-induced apoptosis than Bim or Puma single knockout cells [37], arguing that several BH3-only proteins are necessary for efficient activation of BAX/BAK-dependent apoptosis under conditions of irremediable ER stress.

The ER stress sensor that signals these BH3-only proteins is known in a few cases (i.e., BIM is downstream of PERK); however, we do not yet understand how the UPR communicates with most of the BH3-only proteins. Moreover, it is not known if all of the above BH3-only proteins are simultaneously set in motion by all forms of ER stress or if a subset is activated under specific pathological stimuli that injure this organelle. Understanding the molecular details of how ER damage is communicated to the mitochondrial apoptotic machinery is critical if we want to target disease specific apoptotic signals sent from the ER.

Initiator and Executor Caspases

Caspases, or cysteine-dependent aspartate-directed proteases, play essential roles in both initiating apoptotic signaling (initiator caspases- 2, 4, 8, 12) and executing the final stages of cell demise (executioner caspases- 3, 7, 9) [38]. The executioner caspases are proteolytically activated through either mitochondrial-dependent apoptosome formation or death receptor activation of upstream initiator caspases (i.e., caspase- 8, 10). Given the promiment role of the mitochondrial apoptotic pathway in ER stress-induced death, it is not surprising that the executioner caspases (casp-3,7,9) are critical for cell death resulting from damage to this organelle. On the other hand, there has been much controversy regarding the role of initiator caspases in ER stress-induced apoptosis. Caspase 12 was the first caspase reported to localize to the ER and become activated by UPR signaling in murine cells [39]. However, Caspase 12 was subsequently shown to be downstream of BAX/BAK-dependent mitochondrial permeabilization and executioner caspase activation in this pathway [40], arguing that its role is probably limited to amplifying rather than initiating ER stress-induced apoptosis. Moreover, most humans fail to express a functional CASP12 due to a polymorphism that creates a nonsense mutation in the coding region [41], which rules out an essential role for this protease in human ER stress signaling. More recently, caspase-2 was found to be the premitochondrial protease that proteolytically cleaves and activates the BH3-only protein BID in response to ER stress [33]. Genetic knockdown or pharmacological inhibition of caspase-2 confers resistance to ER stress-induced apoptosis [42]. How the UPR activates caspase-2 and whether other initiator caspases, such as caspase 4, are also involved remains to be determined.

Calcium and Cell Death

Although an extreme depletion of ER luminal Ca2+ concentrations is a well-documented initiator of the UPR and ER stress-induced apoptosis or necrosis, it represents a relatively non-physiological stimulus. Given that Ca2+ signaling from the ER is likely coupled to most pathways leading to apoptosis, however, it is not surprising that this also extends to UPR overload. For example, recent evidence in macrophages indicates that UPR-induced activation of ERO1-α via CHOP results in stimulation of inositol 1,4,5-triphosphate receptor (IP3R) [43], the major release channel for luminal Ca2+ from the ER. Although pathways may exist for ER Ca2+ release independently of IP3 receptors, many seemingly disparate pathways appear to converge on the IP3R platform. Consistent with this, all three sub-groups of the Bcl-2 family at the ER regulate IP3R activity. Mechanistically, this might ultimately result from titrations of pro-survival Bcl-XL, Bcl-2, and Mcl-1 that physically associate with IP3R [44]. Release of ER Ca2+ via IP3R into the cytoplasm could of course influence multiple pathways upstream of the core apoptosis machinery. However, a significant fraction of IP3R is a constituent of highly specialized tethers that physically attach ER cisternae to mitochondria (mitochondrial-associated membrane) and regulate local Ca2+ dynamics at the ER-mitochondrion interface [4546]. This results in propagation of privileged IP3R-mediated Ca2+ oscillations into mitochondria, which can influence cell survival in multiple ways. In an extreme scenario, massive transmission of Ca2+ into mitochondria results in Ca2+ overload and cell death by caspase-dependent and –independent means [46], particularly via the pathway involving the permeability transition pore/cyclophilin D complex [47]. More refined transmission regulated by the Bcl-2 axis at the ER can influence cristae junctions and the availability of cytochrome c for its release across the outer mitochondrial membrane [48]. Finally, such regulated Ca2+transmission to mitochondria is a key determinant of mitochondrial bioenergetics, which is linked not only to potential apoptotic responses, but importantly to survival/death mechanisms dependent on macroautophagy [49].

ER Stress-Induced Cell Loss and Disease

Mounting evidence suggests that ER stress-induced apoptosis contributes to a range of human diseases of cell loss, including diabetes, neurodegeneration, stroke, and heart disease, to name a few (reviewed in REF [50]). The cause of ER stress in these distinct diseases varies depending on the cell type affected and the intracellular and/or extracellular conditions that disrupt proteostasis. For example, some cases of inherited amyotrophic lateral sclerosis (ALS) are caused by toxic, gain-of-function point mutations in superoxide dismutase-1 (SOD1). Other neurodegenerative diseases, such as Huntington, result from mutant proteins (e.g., huntingtin) containing expanded glutamate repeat sequences. Both mutant SOD1 and mutant huntingtin proteins aggregate, exhaust proteasome activity, and result in secondary accumulations of misfolded proteins in the ER [5152]. In the early stages of type 2 diabetes, peripheral insulin resistance challenges pancreatic beta cells to secrete greater amounts of insulin in order to maintain euglycemia. This increased secretory demand can lead to ER stress, beta cell loss, and hyperglycemia [53]. Mutations in PERK result in massive pancreatic beta cell death and infant-onset diabetes in patients with Wolcott-Rallison syndrome [54], an autosomal recessive inherited disorder that illustrates the importance of a properly functioning UPR for beta cell health. An association between ER stress and heart disease has been implicated on a number of levels. Oxidative stress, high levels of cholesterol, and fatty acids can all cause ER stress-induced apoptosis of macrophages and endothelial cells associated with atherosclerotic plaques, leading to progression of atherosclerosis [55]. Myocardial infarction activates the UPR in cardiac myocytes; and Ask1−/− mice show preservation of left ventricular function compared to wild-type controls after coronary artery ligation [56]. Stroke (ischemia-reperfusion injury) has also been shown to induce ER stress-induced apoptosis, and Chop−/− mice are partly protected from neuronal loss after stroke injury [57].

While by no means exhaustive, these examples illustrate the therapeutic potential for novel drugs that block ER stress-induced apoptosis. While chronic UPR-targeted therapies may be problematic for the many tissues that require this pathway to maintain proteastasis, acute modulation of the UPR during stroke or myocardial infarction could be an effective strategy to prevent cell loss. In the case of IRE1α, it may be possible to use kinase inhibitors to activate its cytoprotective signaling and shut down its apoptotic outputs [27]. Whether similar strategies will work for PERK and/or ATF6 remains to be seen. Alternatively, blocking the specific apoptotic signals that emerge from the UPR is perhaps a more straightforward strategy to prevent ER stress-induced cell loss. To this end, small molecular inhibitors of ASK and JNK are currently being tested in a variety preclinical models of ER stress [5253,5657]. This is just the beginning, and much work needs to be done to validate the best drugs targets in the ER stress pathway.

Conclusions

The UPR is a highly complex signaling pathway activated by ER stress that sends out both adaptive and apoptotic signals. All three transmembrane ER stress sensors (IRE1α, PERK, AFT6) have outputs that initially decrease the load and increase capacity of the ER secretory pathway in an effort to restore ER homeostasis. However, under extreme ER stress, continuous engagement of IRE1α and PERK results in events that simultaneously exacerbate protein misfolding and signal death, the latter involving caspase-dependent apoptosis and caspase-independent necrosis. Advances in our molecular understanding of how these stress sensors switch from life to death signaling will hopefully lead to new strategies to prevent diseases caused by ER stress-induced cell loss.

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Introduction to Subcellular Structure

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

 

 

The following chapter of the metabolism/transcriptomics/proteomics/metabolomics series deals with the subcellular structure of the cell.  This would have to include the cytoskeleton, which has a key role in substrate and ion efflux and influx, and in cell movement mediated by tubulins.  It has been extensively covered already.  Much of the contributions here are concerned with the mitochondrion, which is also covered in metabolic pathways.  The ribosome is the organelle that we have discussed with respect to the transcription and translation of the genetic code through mRNA and tRNA, and the therapeutic implications of SiRNA as well as the chromatin regulation of lncRNA.

We have also encountered the mitochondrion and the lysosome in the discussion of apoptosis and autophagy, maintaining the balance between cell regeneration and cell death.

I here list the organelles:

  1. Nucleus
  2. Centrosome
  3. Nuclear Membrane
  4. Ribososome
  5. Endoplasmic Reticulum
  6. Mitochondria
  7. Lysosome
  8. Cytoskeleton
  9. Golgi apparatus
  10. Cytoplasm
cell_organelle_quiz

cell_organelle_quiz

http://www.youtube.com/watch?feature=player_embedded&v=JufLDxmCwB0

http://www.youtube.com/watch?feature=player_embedded&v=FFrKN7hJm64

Golgi Apparatus

Found within the cytoplasm of both plant and animal cells, the Golgi is composed of stacks of membrane-bound structures known as cisternae (singular: cisterna). An individual stack is sometimes called a dictyosome (from Greek dictyon: net + soma: body), especially in plant cells. A mammalian cell typically contains 40 to 100 stacks. Between four and eight cisternae are usually present in a stack; however, in some protists as many as sixty have been observed. Each cisterna comprises a flat, membrane-enclosed disc that includes special Golgi enzymes which modify or help to modify cargo proteins that travel through it.

The cisternae stack has four functional regions: the cis-Golgi network, medial-Golgi, endo-Golgi, and trans-Golgi network. Vesicles from the endoplasmic reticulum (via the vesicular-tubular clusters) fuse with the network and subsequently progress through the stack to the trans-Golgi network, where they are packaged and sent to their destination.

The Golgi apparatus is integral in modifying, sorting, and packaging these macromolecules for cell secretion (exocytosis) or use within the cell. It primarily modifies proteins delivered from the rough endoplasmic reticulum, but is also involved in the transport of lipids around the cell, and the creation of lysosomes.  Enzymes within the cisternae are able to modify the proteins by addition of carbohydrates (glycosylation) and phosphates (phosphorylation). In order to do so, the Golgi imports substances such as nucleotide sugars from the cytosol. These modifications may also form a signal sequence which determines the final destination of the protein. For example, the Golgi apparatus adds a mannose-6-phosphate label to proteins destined for lysosomes.

The Golgi plays an important role in the synthesis of proteoglycans, which are molecules present in the extracellular matrix of animals. It is also a major site of carbohydrate synthesis. This includes the production of glycosaminoglycans (GAGs), long unbranched polysaccharides which the Golgi then attaches to a protein synthesised in the endoplasmic reticulum to form proteoglycans. Enzymes in the Golgi polymerize several of these GAGs via a xylose link onto the core protein. Another task of the Golgi involves the sulfation of certain molecules passing through its lumen via sulfotranferases that gain their sulfur molecule from a donor called PAPS. This process occurs on the GAGs of proteoglycans as well as on the core protein. Sulfation is generally performed in the trans-Golgi network. The level of sulfation is very important to the proteoglycans’ signalling abilities, as well as giving the proteoglycan its overall negative charge.

The phosphorylation of molecules requires that ATP is imported into the lumen of the Golgi and utilised by resident kinases such as casein kinase 1 and casein kinase 2. One molecule that is phosphorylated in the Golgi is apolipoprotein, which forms a molecule known as VLDL that is found in plasma. It is thought that the phosphorylation of these molecules labels them for secretion into the blood.

The Golgi has a putative role in apoptosis, with several Bcl-2 family members localised there, as well as to the mitochondria. A newly characterized protein, GAAP (Golgi anti-apoptotic protein), almost exclusively resides in the Golgi and protects cells from apoptosis by an as-yet undefined mechanism.

The vesicles that leave the rough endoplasmic reticulum are transported to the cis face of the Golgi apparatus, where they fuse with the Golgi membrane and empty their contents into the lumen. Once inside the lumen, the molecules are modified, then sorted for transport to their next destinations. The Golgi apparatus tends to be larger and more numerous in cells that synthesize and secrete large amounts of substances; for example, the plasma B cells and the antibody-secreting cells of the immune system have prominent Golgi complexes.

Those proteins destined for areas of the cell other than either the endoplasmic reticulum or Golgi apparatus are moved towards the trans face, to a complex network of membranes and associated vesicles known as the trans-Golgi network (TGN). This area of the Golgi is the point at which proteins are sorted and shipped to their intended destinations by their placement into one of at least three different types of vesicles, depending upon the molecular marker they carry.

Nucleus_ER_golgi

Nucleus_ER_golgi

Diagram of secretory process from endoplasmic reticulum (orange) to Golgi apparatus (pink). 1. Nuclear membrane; 2. Nuclear pore; 3. Rough endoplasmic reticulum (RER); 4. Smooth endoplasmic reticulum (SER); 5. Ribosome attached to RER; 6. Macromolecules; 7. Transport vesicles; 8. Golgi apparatus; 9. Cis face of Golgi apparatus; 10. Trans face of Golgi apparatus; 11. Cisternae of the Golgi Apparatus

Exocytotic vesicles

After packaging, the vesicles bud off and immediately move towards the plasma membrane, where they fuse and release the contents into the extracellular space in a process known as constitutive secretion. (Antibody release by activated plasma B cells)

Secretory vesicles

After packaging, the vesicles bud off and are stored in the cell until a signal is given for their release. When the appropriate signal is received they move towards the membrane and fuse to release their contents. This process is known as regulated secretion. (Neurotransmitter release from neurons)

Lysosomal vesicles

Vesicle contains proteins and ribosomes destined for the lysosome, an organelle of degradation containing many acid hydrolases, or to lysosome-like storage organelles. These proteins include both digestive enzymes and membrane proteins. The vesicle first fuses with the late endosome, and the contents are then transferred to the lysosome via unknown mechanisms.

http://en.wikipedia.org/wiki/Golgi_apparatus

Lysosome (derived from the Greek words lysis, meaning “to loosen”, and soma, “body”) is a membrane-bound cell organelle found in animal cells (they are absent in red blood cells). They are structurally and chemically spherical vesicles containing hydrolytic enzymes, which are capable of breaking down virtually all kinds of biomolecules, including proteins, nucleic acids, carbohydrates, lipids, and cellular debris.  Lysosomes are responsible for cellular homeostasis for their involvements in secretion, plasma membrane repair, cell signalling and energy metabolism, which are related to health and diseases. Depending on their functional activity their sizes can be very different, as the biggest ones can be more than 10 times bigger than the smallest ones. They were discovered and named by Belgian biologist Christian de Duve, who eventually received the Nobel Prize in Physiology or Medicine in 1974.

Enzymes of the lysosomes are synthesised in the rough endoplasmic reticulum. The enzymes are released from Golgi apparatus in small vesicles which ultimately fuse with acidic vesicles called endosomes, thus becoming full lysosomes. In the process the enzymes are specifically tagged with mannose 6-phosphate to differentiate them from other enzymes. Lysosomes are interlinked with three intracellular processes namely phagocytosis, endocytosis and autophagy. Extracellular materials such as microorganisms taken up by phagocytosis, macromolecules by endocytosis, and unwanted cell organelles are fused with lysosomes in which they are broken down to their basic molecules. Thus lysosomes are the recycling units of a cell.

http://en.wikipedia.org/wiki/Lysosome

The endoplasmic reticulum (ER) is a type of organelle in the cells of eukaryotic organisms that forms an interconnected network of flattened, membrane-enclosed sacs or tubes known as cisternae. The membranes of the ER are continuous with the outer membrane of the nuclear envelope. Endoplasmic reticulum occurs in most types of eukaryotic cells, including the most primitive Giardia, but is absent from red blood cells and spermatozoa. There are two types of endoplasmic reticulum, rough endoplasmic reticulum (RER) and smooth endoplasmic reticulum (SER). The outer (cytosolic) face of the rough endoplasmic reticulum is studded with ribosomes that are the sites of protein synthesis. The rough endoplasmic reticulum is especially prominent in cells such as hepatocytes where active smooth endoplasmic reticulum lacks ribosomes and functions in lipid metabolism, carbohydrate metabolism, and detoxification and is especially abundant in mammalian liver and gonad cells. The lacey membranes of the endoplasmic reticulum were first seen in 1945 by Keith R. Porter, Albert Claude, Brody Meskers and Ernest F. Fullam, using electron microscopy.

http://en.wikipedia.org/wiki/Endoplasmic_reticulum

endoplasmic_reticulum

endoplasmic_reticulum

https://2cslacardano.wikispaces.com/file/view/Cell7.png/338811858/408×313/Cell7.png

Cytoskeleton

The Effects of Actomyosin Tension on Nuclear Pore Transport
Rachel Sammons
Undergraduate Honors Thesis
Spring 2011

The cytoskeleton maintains cellular structure and tension through a force balance with the nucleus, where actomyosin is anchored to the nuclear envelope by nesprin integral proteins. It is hypothesized that the presence or absence of this tension alters the transport of molecules through the nuclear pore complex. We tested the effects of cytoskeletal tension on nuclear transport in human umbilical vein endothelial cells (HUVECs) by performing fluorescence recovery after photo-bleaching (FRAP) experiments on the nuclei to monitor the passive transport of the molecules through nuclear pores.

Using myosin inhibitors, as well as siRNA transfections to reduce the expression of nesprin-1, we altered the nucleo-cytoskeletal force balance and monitored the effect of each on the nuclear pore. FRAP data was fit to a diffusion model by assuming pseudo-steady state inside the nuclear pore, perfect mixing within both the cytoplasm and the nucleus, and no intracellular binding of the fluorescent probes. From these results and a model from the current literature relating diffusion rate constants to nuclear pore radii, we were able to determine that changing cytoskeletal tension alters nuclear pore size and passive transport.

nuclear pores in nuclear envelope

nuclear pores in nuclear envelope

image of nuclear pores on the external surface of the nuclear envelope

nuclear envelope and FG filaments

nuclear envelope and FG filaments

nuclear envelope and FG filaments

Figure 1: The structure and location of the nuclear pore, shown by (a) AFM image of nuclear pores on the external surface of the nuclear envelope[5] and (b) computer model cross-section. The nuclear envelope is shown in cyan, and FG filaments in blue can be seen throughout the channel. The nuclear basket extends into the nucleoplasm.

Fusion-pore expansion during syncytium formation is restricted by an actin network

A Chen, E Leikina, K Melikov, B Podbilewicz, MM. Kozlov and LV. Chernomordik,*
J Cell Sci 1 Nov 2008;121: 3619-3628. http://dx.doi.org:/10.1242/​jcs.032169

Effects of actin-modifying agents indicate that the actin cortex slows down pore expansion. We propose that the growth of the strongly bent fusion-pore rim is restricted by a dynamic resistance of the actin network and driven by membrane-bending proteins that are involved in the generation of highly curved intracellular membrane compartments.

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Metabolomics Summary and Perspective


Metabolomics Summary and Perspective

Author and Curator: Larry H Bernstein, MD, FCAP 

 

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

genome cartoon

 iron metabolism

iron metabolism

personalized reference range within population range

personalized reference range within population range

Part 1.  MetabolomicsSurge

metagraph  _OMICS

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

  1. recent advances in analytical technology and bioinformatics as well as
  2. 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
  1. a specific disease state,
  2. toxin exposure, or
  3. 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
  1. targeted organs,
  2. mechanism of action, and
  3. 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
  1. on the safety and efficacy of compounds
  2. during early and preclinical toxicological studies,
  3. 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

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
  1. the identification,
  2. quantification, and
  3. mapping of more than 800 metabolites to specific cellular pathways.

It is based on flow injection analysis and high-performance liquid chromatography MS/MS.

Clarification of Pathway-Specific Inhibition by Fourier Transform Ion Cyclotron Resonance.Mass Spectrometry-Based Metabolic Phenotyping Studies F5.large

common drug targets

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

  1. the uncoupling of glycolysis from the mitochondria,
  2. leading to the inefficient but rapid metabolism of glucose and
  3. 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,

  1. can functionally coordinate cell-survival and cell-proliferation mechanisms,
  2. 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

  1.  high reproducibility,
  2. standardized protocols,
  3. low sample manipulation, and
  4. 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,

  1. “splitting up information content, processing, and introducing a lot of background noise and error and
  2. 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

  1. 309 have been identified in cerebrospinal fluid,
  2. 1,122 in serum,
  3. 458 in urine, and
  4. 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

  1. undergo a variety of interactions including metal complexation,
  2. chemical exchange processes,
  3. micellar compartmentation,
  4. enzyme-mediated biotransformations, and
  5. 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

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.

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

Degree of binding correlated with function

Diagram_of_a_two-photon_excitation_microscope_

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’

‘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

  1. enzymes;
  2. structural molecules, such as hair,
  3. skin and bones;
  4. hormones like insulin; and
  5. 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,

  1. RNA polymerase II functions with
  2. a factor termed TBP,
  3. 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

Coordination of the transcriptome and metabolome

the potential advantages conferred by distal-site protein synthesis

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”.

Part 3. Neuroscience

Vesicles influence function of nerve cells 
Oct, 06 2014        source: http://feeds.sciencedaily.com

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.

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

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.

http://labroots.com/user/news/article/id/217438/title/vesicles-influence-function-of-nerve-cells

The above story is based on materials provided by Universitt Mainz.

Universitt Mainz. “Vesicles influence function of nerve cells.” ScienceDaily. ScienceDaily, 6 October 2014. www.sciencedaily.com/releases/2014/10/141006174214.htm

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

http://www.rdmag.com/news/2014/10/neuroscientists-use-snail-research-help-explain-E2_9_Cchemo-brain

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
  1. inhibits the dephosphorylation of extracellular signal-regulated kinase (ERK) and
  2. p38 mitogen-activated protein kinase (p38 MAPK),
  3. 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

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

  • the need for studying the circuitry of the brain,
  • which is formed by interconnected neurons.

Our remote-control technology may provide a tool with which researchers can ask new questions about the roles of complex circuits in regulating behavior,” Stanley says.
Rockefeller University’s Laboratory of Molecular Genetics
Source: Rockefeller Univ.

Part 4.  Cancer

Two Proteins Found to Block Cancer Metastasis

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”.

Disabling Enzyme Cripples Tumors, Cancer Cells

First Step of Metastasis

First Step of Metastasis

Published: Sep 05, 2013  http://www.technologynetworks.com/Metabolomics/news.aspx?id=157138

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

  1. AGPS expression increased when normal cells turned cancerous.
  2. 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

Ping Xie, Minghua Zhang, Shan He, Kefeng Lu, Yuhan Chen, Guichun Xing, et al.
Nature Communications
  2014; 5(3733).  http://dx.doi.org:/10.1038/ncomms4733

Neddylation, the covalent attachment of ubiquitin-like protein Nedd8, of the Cullin-RING E3 ligase family

  • regulates their ubiquitylation activity.

However, regulation of HECT ligases by neddylation has not been reported to date. Here we show that

  • the C2-WW-HECT ligase Smurf1 is activated by neddylation.

Smurf1 physically interacts with

  1. Nedd8 and Ubc12,
  2. forms a Nedd8-thioester intermediate, and then
  3. catalyses its own neddylation on multiple lysine residues.

Intriguingly, this autoneddylation needs

  • an active site at C426 in the HECT N-lobe.

Neddylation of Smurf1 potently enhances

  • ubiquitin E2 recruitment and
  • augments the ubiquitin ligase activity of Smurf1.

The regulatory role of neddylation

  • is conserved in human Smurf1 and yeast Rsp5.

Furthermore, in human colorectal cancers,

  • the elevated expression of Smurf1, Nedd8, NAE1 and Ubc12
  • correlates with cancer progression and poor prognosis.

These findings provide evidence that

  • neddylation is important in HECT ubiquitin ligase activation and
  • shed new light on the tumour-promoting role of Smurf1.
 Swinging domains in HECT E3

Swinging domains in HECT E3

Subject terms: Biological sciences Cancer Cell biology

Figure 1: Smurf1 expression is elevated in colorectal cancer tissues.

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

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. (bd) 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

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

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.

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…

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The deubiquitylase USP33 discriminates between RALB functions in autophagy and innate immune response

M Simicek, S Lievens, M Laga, D Guzenko, VN. Aushev, et al.
Nature Cell Biology 2013; 15, 1220–1230    http://dx.doi.org:/10.1038/ncb2847

The RAS-like GTPase RALB mediates cellular responses to nutrient availability or viral infection by respectively

  • engaging two components of the exocyst complex, EXO84 and SEC5.
  1. RALB employs SEC5 to trigger innate immunity signalling, whereas
  2. RALB–EXO84 interaction induces autophagocytosis.

How this differential interaction is achieved molecularly by the RAL GTPase remains unknown.

We found that whereas GTP binding

  • turns on RALB activity,

ubiquitylation of RALB at Lys 47

  • tunes its activity towards a particular effector.

Specifically, ubiquitylation at Lys 47

  • sterically inhibits RALB binding to EXO84, while
  • facilitating its interaction with SEC5.

Double-stranded RNA promotes

  • RALB ubiquitylation and
  • SEC5–TBK1 complex formation.

In contrast, nutrient starvation

  • induces RALB deubiquitylation
  • by accumulation and relocalization of the deubiquitylase USP33
  • to RALB-positive vesicles.

Deubiquitylated RALB

  • promotes the assembly of the RALB–EXO84–beclin-1 complexes
  • driving autophagosome formation. Thus,
  • ubiquitylation within the effector-binding domain
  • provides the switch for the dual functions of RALB in
    • autophagy and innate immune responses.

Part 5. Metabolic Syndrome

Single Enzyme is Necessary for Development of Diabetes

Published: Aug 20, 2014 http://www.technologynetworks.com/Metabolomics/news.aspx?ID=169416

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.

  1. HETEs harm the mitochondria, which then
  2. fail to produce sufficient energy to enable
  3. 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.”

A New Player in Lipid Metabolism Discovered

Published: Aug18, 2014  http://www.technologynetworks.com/Metabolomics/news.aspx?ID=169356

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
  1. mad cow disease,
  2. Type 1 diabetes and
  3. 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.

Part 6. Biomarkers

Biomarkers Take Center Stage

Josh P. Roberts
GEN May 1, 2013 (Vol. 33, No. 9)  http://www.genengnews.com/

While work with biomarkers continues to grow, scientists are also grappling with research-related bottlenecks, such as

  1. affinity reagent development,
  2. platform reproducibility, and
  3. 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:

  1. where to find them,
  2. when they may appear,
  3. what form they may take, and
  4. how they can be used to diagnose a condition or
  5. 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

  1. to garner information about the molecular characteristics of the cancer
  2. that will help with cancer detection and
  3. 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

  1. mass spectrometry and
  2. 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

  1. build rigorous, formal mathematical models that will allow something measured in the blood
  2. 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

  1. a biologically inert, biophysically stable protein scaffold
  2. containing three variable regions into which
  3. 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
  1. rheumatoid arthritis,
  2. psoriatic arthritis,
  3. SLE, or
  4. giant cell arteritis.

Epigenetic Biomarkers

Methylation of adenine

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
  1. tumor type,
  2. histology, or
  3. 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

  1. somatic mutations,
  2. gene copy number aberrations,
  3. gene expression abnormalities,
  4. protein and miRNA expression, and
  5. 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

  1. prognostic drivers
  2. predictive markers for taxanes and
  3. monoclonal antibodies and
  4. 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

  1. 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

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.

Patricia Fitzpatrick Dimond, Ph.D.

http://www.genengnews.com/media/images/AnalysisAndInsight/Feb7_2013_24454248_GreenPurpleDNA_EpigeneticsToolsII3576166141.jpg

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

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.

http://www.technologynetworks.com/Metabolomics/news.aspx?ID=157804

This study is published online in Drug Metabolism and Disposition

Part 8.  Pictorial Maps

 Prediction of intracellular metabolic states from extracellular metabolomic data

MK Aurich, G Paglia, Ottar Rolfsson, S Hrafnsdottir, M Magnusdottir, MM Stefaniak, BØ Palsson, RMT Fleming &

Ines Thiele

Metabolomics Aug 14, 2014;

http://dx.doi.org:/10.1007/s11306-014-0721-3

http://link.springer.com/article/10.1007/s11306-014-0721-3/fulltext.html#Sec1

http://link.springer.com/static-content/images/404/art%253A10.1007%252Fs11306-014-0721-3/MediaObjects/11306_2014_721_Fig1_HTML.gif

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.

Keywords Constraint-based modeling _ Metabolomics _ Multi-omics _ Metabolic network _ Transcriptomics

1 Introduction

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

  1. enterocytes (Sahoo and Thiele2013),
  2. macrophages (Bordbar et al. 2010),
  3. adipocytes (Mardinoglu et al. 2013),
  4. 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

  1. cancer metabolism (Jerby and Ruppin, 2012).
  2. 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

Modes of transcriptional regulation during the YMC

Such analyses have also been used to reveal the effects of

  1. enzymopathies on red blood cells (Price et al. 2004),
  2. to study effects of diet on diabetes (Thiele et al. 2005) and
  3. 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.

Our modeling yields meaningful predictions regarding

  • metabolic differences between two lymphoblastic leukemia cell lines (Fig. 1A).

Fig. 1

metabol leukem cell lines11306_2014_721_Fig1_HTML

metabol leukem cell lines11306_2014_721_Fig1_HTML

A Combined experimental and computational pipeline to study human metabolism.

  1. Experimental work and omics data analysis steps precede computational modeling.
  2. Model predictions are validated based on targeted experimental data.
  3. Metabolomic and transcriptomic data are used for model refinement and submodel extraction.
  4. Functional analysis methods are used to characterize the metabolism of the cell-line models and compare it to additional experimental data.
  5. 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.
  1. A number of metabolite exchanges mapped to the model were unique to one cell line.
  2. 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:

  1. data acquisition,
  2. data analysis,
  3. metabolic modeling and
  4. 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

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

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

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

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

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).

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

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

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 pathways 1476-4598-10-70-1

Metabolic Systems Research Team fig2

Metabolic Systems Research Team fig2

Metabolic control analysis of respiration in human cancer tissue. fphys-04-00151-g001

Metabolic control analysis of respiration in human cancer tissue. fphys-04-00151-g001

Metabolome Informatics Research fig1

Metabolome Informatics Research fig1

Modelling of Central Metabolism network3

Modelling of Central Metabolism network3

N. gaditana metabolic pathway map ncomms1688-f4

N. gaditana metabolic pathway map ncomms1688-f4

protein changes in biological mechanisms

protein changes in biological mechanisms

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Ubiquitin Pathway Involved in Neurodegenerative Diseases

Larry H Bernstein, MD,  FCAP

 

PINK1 and Parkin and Parkinson’s Disease

Studies of the familial Parkinson disease-related proteins PINK1 and Parkin have demonstrated that these factors promote the fragmentation and turnover of mitochondria following treatment of cultured cells with mitochondrial depolarizing agents. Whether PINK1 or Parkin influence mitochondrial quality control under normal physiological conditions in dopaminergic neurons, a principal cell type that degenerates in Parkinson disease, remains unclear. To address this matter, we developed a method to purify and characterize neural subtypes of interest from the adult Drosophila brain.

Using this method, we find that dopaminergic neurons from Drosophila parkin mutants accumulate enlarged, depolarized mitochondria, and that genetic perturbations that promote mitochondrial fragmentation and turnover rescue the mitochondrial depolarization and neurodegenerative phenotypes of parkin mutants. In contrast, cholinergic neurons from parkin mutants accumulate enlarged depolarized mitochondria to a lesser extent than dopaminergic neurons, suggesting that a higher rate of mitochondrial damage, or a deficiency in alternative mechanisms to repair or eliminate damaged mitochondria explains the selective vulnerability of dopaminergic neurons in Parkinson disease.

Our study validates key tenets of the model that PINK1 and Parkin promote the fragmentation and turnover of depolarized mitochondria in dopaminergic neurons. Moreover, our neural purification method provides a foundation to further explore the pathogenesis of Parkinson disease, and to address other neurobiological questions requiring the analysis of defined neural cell types.

Burmana JL, Yua S, Poole AC, Decala RB , Pallanck L. Analysis of neural subtypes reveals selective mitochondrial dysfunction in dopaminergic neurons from parkin mutants.

Autophagy in Parkinson’s Disease.

Parkinson’s disease is a common neurodegenerative disease in the elderly. To explore the specific role of autophagy and the ubiquitin-proteasome pathway in apoptosis, a specific proteasome inhibitor and macroautophagy inhibitor and stimulator were selected to investigate pheochromocytoma (PC12) cell lines transfected with human mutant (A30P) and wildtype (WT) -synuclein.

The apoptosis ratio was assessed by flow cytometry. LC3, heat shock protein 70 (hsp70) and caspase-3 expression in cell culture were determined by Western blot. The hallmarks of apoptosis and autophagy were assessed with transmission electron microscopy. Compared to the control group or the rapamycin (autophagy stimulator) group, the apoptosis ratio in A30P and WT cells was significantly higher after treatment with inhibitors of the proteasome and macroautophagy. The results of Western blots for caspase-3 expression were similar to those of flow cytometry; hsp70 protein was significantly higher in the proteasome inhibitor group than in control, but in the autophagy inhibitor and stimulator groups, hsp70 was similar to control. These findings show that inhibition of the proteasome and autophagy promotes apoptosis, and the macroautophagy stimulator rapamycin reduces the apoptosis ratio. And inhibiting or stimulating autophagy has less impact on hsp70 than the proteasome pathway.

In conclusion, either stimulation or inhibition of macroautophagy, has less impact on hsp70 than on the proteasome pathway. This study found that rapamycin decreased apoptotic cells in A30P cells independent of caspase-3 activity. Although several lines of evidence recently demonstrated crosstalk between autophagy and caspase-independent apoptosis, we could not confirm that autophagy activation protects cells from caspase-independent cell death. Undoubtedly, there are multiple connections between the apoptotic and autophagic processes.

Inhibition of autophagy may subvert the capacity of cells to remove damaged organelles or to remove misfolded proteins, which would favor apoptosis. However, proteasome inhibition activated macroautophagy and accelerated apoptosis. A likely explanation is inhibition of the proteasome favors oxidative reactions that trigger apoptosis, presumably through

  • a direct effect on mitochondria, and
  • the absence of NADPH2 and ATP

which may deinhibit the activation of caspase-2 or MOMP. Another possibility is that aggregated proteins induced by proteasome inhibition increase apoptosis.

Yang F, Yanga YP, Maoa CJ, Caoa BY, et al. Role of autophagy and proteasome degradation pathways in apoptosis of PC12 cells overexpressing human -synuclein. Neuroscience Letters 2009; 454:203–208. doi:10.1016/j.neulet.2009.03.027. www.elsevier.com/locate/neulet   http://neurosciletters.com/ Role_of_autophagy_and_proteasome_degradation_pathways_in_apoptosis_of_PC12_cells_
overexpressing_human –synuclein/

Parkin-dependent Ubiquitination of Endogenous Bax

Autosomal recessive loss-of-function mutations within the PARK2 gene functionally inactivate the E3 ubiquitin ligase parkin, resulting in neurodegeneration of catecholaminergic neurons and a familial form of Parkinson disease. Current evidence suggests both a mitochondrial function for parkin and a neuroprotective role, which may in fact be interrelated. The antiapoptotic effects of Parkin have been widely reported, and may involve fundamental changes in the threshold for apoptotic cytochrome c release, but the substrate(s) involved in Parkin dependent protection had not been identified. Here, we demonstrate the Parkin-dependent ubiquitination of endogenous Bax comparing primary cultured neurons from WT and Parkin KO mice and using multiple Parkin-overexpressing cell culture systems. The direct ubiquitination of purified Bax was also observed in vitro following incubation with recombinant parkin. The authors found that Parkin prevented basal and apoptotic stress induced translocation of Bax to the mitochondria. Moreover, an engineered ubiquitination-resistant form of Bax retained its apoptotic function, but Bax KO cells complemented with lysine-mutant Bax did not manifest the antiapoptotic effects of Parkin that were observed in cells expressing WT Bax. These data suggest that Bax is the primary substrate responsible for the antiapoptotic effects of Parkin, and provide mechanistic insight into at least a subset of the mitochondrial effects of Parkin.

Johnson BN, Berger AK, Cortese GP, and LaVoie MJ. The ubiquitin E3 ligase Parkin regulates the proapoptotic function of Bax. PNAS 2012, pp 6. www.pnas.org/cgi/doi/10.1073/pnas.1113248109
http://
PNAS.org/ The_ubiquitin_E3_ligase_Parkin_regulates_the_proapoptotic_function_of_Bax

Parkin Promotes Mitochondrial Loss in Autophagy

Parkin, an E3 ubiquitin ligase implicated in Parkinson’s disease, promotes degradation of dysfunctional mitochondria by autophagy. Using proteomic and cellular approaches, we show that upon translocation to mitochondria, Parkin activates the ubiquitin–proteasome system (UPS) for widespread degradation of outer membrane proteins. This is evidenced by an increase in K48-linked polyubiquitin on mitochondria, recruitment of the 26S proteasome and rapid degradation of multiple outer membrane proteins. The degradation of proteins by the UPS occurs independently of the autophagy pathway, and inhibition of the 26S proteasome completely abrogates Parkin-mediated mitophagy in HeLa, SH-SY5Y and mouse cells. Although the mitofusins Mfn1 and Mfn2 are rapid degradation targets of Parkin, degradation of additional targets is essential for mitophagy. These results indicate that remodeling of the mitochondrial outer membrane proteome is important for mitophagy, and reveal a causal link between the UPS and autophagy, the major pathways for degradation of intracellular substrates.

Chan NC, Salazar AM, Pham AH, Sweredoski MJ, et al. Broad activation of the ubiquitin–proteasome system by Parkin is critical for mitophagy. Human Molecular Genetics 2011; 20(9): 1726–1737. doi:10.1093/hmg/ddr048.  http://HumMolecGenetics.com/ Broad_activation_of_the_ubiquitin–proteasome_system_by_Parkin_is_critical_for_mitophagy/

Interactome Networks and Protein Expression

Aloy P. Shaping the future of interactome networks. (A report of the third Interactome Networks Conference, Hinxton, UK, 29 August-1 September 2007). Genome Biology 2007; 8:316 (doi:10.1186/gb-2007-8-10-316)

Complex systems are often networked, and biology is no exception. Following on from the genome sequencing projects, experiments show that proteins in living organisms are highly connected, which helps to explain how such great complexity can be achieved by a comparatively small set of gene products. At a recent conference on interactome networks held outside Cambridge, UK, the most recent advances in research on cellular networks were discussed. This year’s conference focused on identifying the strengths and weaknesses of currently resolved interaction networks and the techniques used to determine them – reflecting the fact that the field of mapping interaction networks is maturing.

Peroutka RJ, Orcutt SJ, Strickler JE, and Butt TR. SUMO Fusion Technology for Enhanced Protein Expression and Purification in Prokaryotes and Eukaryotes. Chapter 2. in T.C. Evans, M.-Q. Xu (eds.), Heterologous Gene Expression in E. coli, Methods in Molecular Biology 705:15-29. DOI 10.1007/978-1-61737-967-3_2, © Springer Science+Business Media, LLC 2011

The preparation of sufficient amounts of high-quality protein samples is the major bottleneck for structural proteomics. The use of recombinant proteins has increased significantly during the past decades. The most commonly used host, Escherichia coli, presents many challenges including protein misfolding, protein degradation, and low solubility. A novel SUMO fusion technology appears to enhance protein expression and solubility (www.lifesensors.com). Efficient removal of the SUMO tag by SUMO protease in vitro facilitates the generation of target protein with a native N-terminus. In addition to its physiological relevance in eukaryotes, SUMO can be used as a powerful biotechnology tool forenhanced functional protein expression in prokaryotes and eukaryotes.

IL-6 regulation on mitochondrial remodeling/dysfunction

Muscle protein turnover regulation during cancer cachexia is being rapidly defined, and skeletal muscle mitochondria function appears coupled to processes regulating muscle wasting. Skeletal muscle oxidative capacity and the expression of proteins regulating mitochondrial biogenesis and dynamics are disrupted in severely cachectic ApcMin/+ mice. It has not been determined if these changes occur at the onset of cachexia and are necessary for the progression of muscle wasting. Exercise and anti-cytokine therapies have proven effective in preventing cachexia development in tumor bearing mice, while their effect on mitochondrial content, biogenesis and dynamics is not well understood.

The purposes of this study were to

1) determine IL-6 regulation on mitochondrial remodeling/dysfunction during the progression of cancer cachexia and

2) to determine if exercise training can attenuate mitochondrial dysfunction and the induction of proteolytic pathways during IL-6 induced cancer cachexia.

ApcMin/+ mice were examined during the progression of cachexia, after systemic interleukin (IL)-6r antibody treatment, or after IL-6 over-expression with or without exercise. Direct effects of IL-6 on mitochondrial remodeling were examined in cultured C2C12 myoblasts.

  • Mitochondrial content was not reduced during the initial development of cachexia, while muscle PGC-1α and fusion (Mfn1, Mfn2) protein expression was repressed.
  • With progressive weight loss mitochondrial content decreased, PGC-1α and fusion proteins were further suppressed, and fission protein (FIS1) was induced.

IL-6 receptor antibody administration after the onset of cachexia improved mitochondrial content,

  • PGC-1α,
  • Mfn1/Mfn2 and
  • FIS1 protein expression.

IL-6 over-expression in pre-cachectic mice accelerated body weight loss and muscle wasting, without reducing mitochondrial content, while PGC-1α and Mfn1/Mfn2 protein expression was suppressed and FIS1 protein expression induced. Exercise normalized these IL-6 induced effects. C2C12 myotubes administered IL-6 had

  • increased FIS1 protein expression,
  • increased oxidative stress, and
  • reduced PGC-1α gene expression
  • without altered mitochondrial protein expression.

Altered expression of proteins regulating mitochondrial biogenesis and fusion are early events in the initiation of cachexia regulated by IL-6, which precede the loss of muscle mitochondrial content. Furthermore, IL-6 induced mitochondrial remodeling and proteolysis can be rescued with moderate exercise training even in the presence of high circulating IL-6 levels.

White JP, Puppa MJ, Sato S, Gao S. IL-6 regulation on skeletal muscle mitochondrial remodeling during cancer cachexia in the ApcMin/+ mouse. Skeletal Muscle 2012; 2:14-30.
http://www.skeletalmusclejournal.com/content/2/1/14

Starvation-induced Autophagy

Upon starvation cells undergo autophagy, a cellular degradation pathway important in the turnover of whole organelles and long lived proteins. Starvation-induced protein degradation has been regarded as an unspecific bulk degradation process. We studied global protein dynamics during amino acid starvation-induced autophagy by quantitative mass spectrometry and were able to record nearly 1500 protein profiles during 36 h of starvation. Cluster analysis of the recorded protein profiles revealed that cytosolic proteins were degraded rapidly, whereas proteins annotated to various complexes and organelles were degraded later at different time periods. Inhibition of protein degradation pathways identified the lysosomal/autophagosomal system as the main degradative route.

Thus, starvation induces degradation via autophagy, which appears to be selective and to degrade proteins in an ordered fashion and not completely arbitrarily as anticipated so far.

Kristensen AR, Schandorff S, Høyer-Hansen M, Nielsen MO, et al. Ordered Organelle Degradation during Starvation-induced Autophagy. Molecular & Cellular Proteomics 2008; 7:2419–2428.
http://MolecCellProteomics.com/Ordered_Organelle_Degradation_during_Starvation-induced_Autophagy/

Skeletal Muscle Macroautophagy

Skeletal muscles are the agent of motion and one of the most important tissues responsible for the control of metabolism. Coordinated movements are allowed by the highly organized structure of the cytosol of muscle fibers (or myofibers), the multinucleated and highly specialized cells of skeletal muscles involved in contraction. Contractile proteins are assembled into repetitive structures, the basal unit of which is the sarcomere, that are well packed into the myofiber cytosol. Myonuclei are located at the edge of the myofibers, whereas the various organelles such as mitochondria and sarcoplasmic reticulum are embedded among the myofibrils. Many different changes take place in the cytosol of myofibers during catabolic conditions:

  • proteins are mobilized
  • organelles networks are reorganized for energy needs
  • the setting of myonuclei can be modified.

Further,

  • strenuous physical activity,
  • improper dietary regimens and
  • aging

lead to mechanical and metabolic damages of

  • myofiber organelles,
  • especially mitochondria, and
  • contractile proteins.

During aging the protein turnover is slowed down, therefore it is easier to accumulate aggregates of dysfunctional proteins. Therefore, a highly dynamic tissue such as skeletal muscle requires a rapid and efficient system for the removal of altered organelles, the elimination of protein aggregates, and the disposal of toxic products.

The two major proteolytic systems in muscle are the ubiquitin-proteasome and the autophagy-lysosome pathways. The proteasome system requires

  • the transcription of the two ubiquitin ligases (atrogin-1 and MuRF1) and
  • the ubiquitination of the substrates.

Therefore, the ubiquitin-proteasome system can provide the rapid elimination of single proteins or small aggregates. Conversely, the autophagic system is able to degrade entire organelles and large proteins aggregates. In the autophagy-lysosome system, double-membrane vesicles named autophagosomes are able to engulf a portion of the cytosol and fuse with lysosomes, where their content is completely degraded by lytic enzymes.

The autophagy flux can be biochemicaly monitored following LC3 lipidation and p62 degradation. LC3 is the mammalian homolog of the yeast Atg8 gene, which is lipidated when recruited for the double-membrane commitment and growth. p62 (SQSTM-1) is a polyubiquitin-binding protein involved in the proteasome system and that can either reside free in the cytosol and nucleus or occur within autophagosomes and lysosomes. The GFP-LC3 transgenic mouse model allows easy detection of autophagosomes by simply monitoring the presence of bright GFP-positive puncta inside the myofibrils and beneath the plasma membrane of the myofibers, thus investigate the activation of autophagy in skeletal muscles with different contents of slow and fast-twitching myofibers and in response to stimuli such as fasting. For example, in the fast-twiching extensor digitorum longus muscle few GFP-LC3 dots were observed before starvation, while many small GFP-LC3 puncta appeared between myofibrils and in the perinuclear regions after 24 h starvation. Conversely, in the slow-twitching soleus muscle, autophagic puncta were almost absent in standard condition and scarcely induced after 24 h starvation.

Autophagy in Muscle Homeostasis

The autophagic flux was found to be increased during certain catabolic conditions, such as fasting, atrophy , and denervation , thus contributing to protein breakdown. Food deprivation is one of the strongest stimuli known to induce autophagy in muscle. Indeed skeletal muscle, after the liver, is the most responsive tissue to autophagy activation during food deprivation. Since muscles are the biggest reserve of amino acids in the body, during fasting autophagy has the vital role to maintain the amino acid pool by digesting muscular protein and organelles. In mammalian cells, mTORC1, which consists of

  • mTOR and
  • Raptor,

is the nutrient sensor that negatively regulates autophagy.

During atrophy, protein breakdown is mediated by atrogenes, which are under the forkhead box O (FoxO) transcription factors control, and activation of autophagy seems to aggravate muscle loss during atrophy. In vivo and in vitro studies demonstrated that several genes coding for components of the autophagic machinery, such as

  • LC3,
  • GABARAP,
  • Vps34,
  • Atg12 and
  • Bnip3,

are controlled by FoxO3 transcription factor. FoxO3 is able to regulate independently

  1. the ubiquitin-proteasome system and
  2. the autophagy-lysosome machinery in vivo and in vitro.

Denervation is also able to induce autophagy in skeletal muscle, although at a slower rate than fasting. This effect is mediated by RUNX1, a transcription factor upregulated during autophagy; the lack of RUNX1 results in

  • excessive autophagic flux in denervated muscle and leads to atrophy.

The generation of Atg5 and Atg7 muscle-specific knockout mice have shown that

  • with suppression of autophagy both models display muscle weakness and atrophy and
  • a significant reduction of weight, which is
  • correlated with the important loss of muscle tissue due to an atrophic condition.

An unbalanced autophagy flux is highly detrimental for muscle, as too much induces atrophy whereas too little leads to muscle weakness and degeneration. Muscle wasting associated with autophagy inhibition becomes evident and symptomatic only after a number of altered proteins and dysfunctional organelles are accumulated, a condition that becomes evident after months or even years. On the other hand, the excessive increase of autophagy flux is able to induce a rapid loss of muscle mass (within days or weeks).  Alterations of autophagy are involved in the pathogenesis of several myopathies and dystrophies.

The maintenance of muscle homeostasis is finely regulated by the balance between catabolic and anabolic process. Macroautophagy (or autophagy) is a catabolic process that provides the degradation of protein aggregation and damaged organelles through the fusion between autophagosomes and lysosomes. Proper regulation of the autophagy flux is fundamental for

  • the homeostasis of skeletal muscles during physiological situations and
  • in response to stress.

Defective as well as excessive autophagy is harmful for muscle health and has a pathogenic role in several forms of muscle diseases.

Grumati P, Bonaldo P. Autophagy in Skeletal Muscle Homeostasis and in Muscular Dystrophies. Cells 2012, 1, 325-345; doi:10.3390/cells1030325. ISSN 2073-4409. www.mdpi.com/journal/cells
http://cell.com/ Autophagy in Skeletal Muscle Homeostasis and in Muscular Dystrophies/

Parkinson’s Disease Mutations

Mutations in parkin, a ubiquitin ligase, cause early-onset familial Parkinson’s disease (AR-JP). How Parkin suppresses Parkinsonism remains unknown. Parkin was recently shown to promote the clearance of impaired mitochondria by autophagy, termed mitophagy. Here, we show that Parkin promotes mitophagy by catalyzing mitochondrial ubiquitination, which in turn recruits ubiquitin-binding autophagic components, HDAC6 and p62, leading to mitochondrial clearance.

During the process, juxtanuclear mitochondrial aggregates resembling a protein aggregate-induced aggresome are formed. The formation of these “mito-aggresome” structures requires microtubule motor-dependent transport and is essential for efficient mitophagy. Importantly, we show that AR-JP–causing Parkin mutations are defective in supporting mitophagy due to distinct defects at

  • recognition,
  • transportation, or
  • ubiquitination of impaired mitochondria,

thereby implicating mitophagy defects in the development of Parkinsonism. Our results show that impaired mitochondria and protein aggregates are processed by common ubiquitin-selective autophagy machinery connected to the aggresomal pathway, thus identifying a mechanistic basis for the prevalence of these toxic entities in Parkinson’s disease.

Lee JY,Nagano Y, Taylor JP,Lim KL, and Yao TP. Disease-causing mutations in Parkin impair mitochondrial ubiquitination, aggregation, and HDAC6-dependent mitophagy. J Cell Biol 2010; 189(4):671-679. www.jcb.org/cgi/doi/10.1083/jcb.201001039
http://JCellBiol.com/Disease-causing_mutations_in_Parkin_impair_mitochondrial_ubiquitination_ aggregation_and_HDAC6-dependent_mitophagy/

Drosophila Parkin Requires PINK1

Loss of the E3 ubiquitin ligase Parkin causes early onset Parkinson’s disease, a neurodegenerative disorder of unknown etiology.  Parkin has been linked to multiple cellular processes including

  • protein degradation,
  • mitochondrial homeostasis, and
  • autophagy;

however, its precise role in pathogenesis is unclear. Recent evidence suggests that Parkin is recruited to damaged mitochondria, possibly affecting

  • mitochondrial fission and/or fusion,
  • to mediate their autophagic turnover.

The precise mechanism of recruitment and the ubiquitination target are unclear. Here we show in Drosophila cells that PINK1 is required to recruit Parkin to dysfunctional mitochondria and promote their degradation. Furthermore, PINK1 and Parkin mediate the ubiquitination of the profusion factor Mfn on the outer surface of mitochondria. Loss of Drosophila PINK1 or parkin causes an increase in Mfn abundance in vivo and concomitant elongation of mitochondria. These findings provide a molecular mechanism by which the PINK1/Parkin pathway affects mitochondrial fission/fusion as suggested by previous genetic interaction studies. We hypothesize that Mfn ubiquitination may provide a mechanism by which terminally damaged mitochondria are labeled and sequestered for degradation by autophagy.

Ziviani E, Tao RN, and Whitworth AJ. Drosophila Parkin requires PINK1 for mitochondrial translocation and ubiquitinates Mitofusin. PNAS 2010. Pp6 www.pnas.org/cgi/doi/10.1073/pnas.0913485107
http://PNAS.org/ Drosophila_Parkin_requires_PINK1_for_ mitochondrial_translocation_and_ubiquitinates_Mitofusin

Dynamin-related protein 1 (Drp1) in Parkinson’s

Mutations in Parkin, an E3 ubiquitin ligase that regulates protein turnover, represent one of the major causes of familial Parkinson’s disease (PD), a neurodegenerative disorder characterized by the loss of dopaminergic neurons and impaired mitochondrial functions. The underlying mechanism by which pathogenic parkin mutations induce mitochondrial abnormality is not fully understood. Here we demonstrate that Parkin interacts with and subsequently ubiquitinates dynamin-related protein 1 (Drp1), for promoting its proteasome-dependent degradation. Pathogenic mutation or knockdown of Parkin inhibits the ubiquitination and degradation of Drp1, leading to an increased level of Drp1 for mitochondrial fragmentation. These results identify Drp1 as a novel substrate of Parkin and suggest a potential mechanism linking abnormal Parkin expression to mitochondrial dysfunction in the pathogenesis of PD.

Wang H, Song P, Du L, Tian W. Parkin ubiquitinates Drp1 for proteasome-dependent degradation: implication of dysregulated mitochondrial dynamics in Parkinson’s disease.

JBC Papers in Press. Published on February 3, 2011 as Manuscript M110.144238. http://www.jbc.org/cgi/doi/10.1074/jbc.M110.144238
http://JBC.org/ Parkin_ubiquitinates_Drp1_for_proteasome-dependent_degradation_implication_of_ dysregulated_mitochondrial_dynamics_in_Parkinson’s_disease

Pink1, Parkin, and DJ-1 Form a Complex

Mutations in the genes PTEN-induced putative kinase 1 (PINK1), PARKIN, and DJ-1 cause autosomal recessive forms of Parkinson disease (PD), and the Pink1/Parkin pathway regulates mitochondrial integrity and function. An important question is whether the proteins encoded by these genes function to regulate activities of other cellular compartments. A study in mice, reported by Xiong et al. in this issue of the JCI, demonstrates that Pink1, Parkin, and DJ-1 can form a complex in the cytoplasm, with Pink1 and DJ-1 promoting the E3 ubiquitin ligase activity of Parkin to degrade substrates via the proteasome (see the related article, doi:10.1172/ JCI37617).

This protein complex in the cytosol may or may not be related to the role of these proteins in regulating mitochondrial function or oxidative stress in vivo. Three models for the role of the PPD complex. In this issue of the JCI, Xiong et al. report that Pink1, Parkin, and DJ-1 bind to each other and form a PPD E3 ligase complex in which Pink1 and DJ-1 modulate Parkin-dependent ubiquitination and subsequent degradation of substrates via the proteasome. Previous work suggests that the Pink1/Parkin pathway regulates mitochondrial integrity and promotes mitochondrial fission in Drosophila.

(A) Parkin and DJ-1 may be recruited to the mitochondrial outer membrane during stress and interact with Pink1. These interactions may facilitate the ligase activity of Parkin, thereby facilitating the turnover of molecules that regulate mitochondrial dynamics and mitophagy. The PPD complex may have other roles in the cytosol that result in degradative ubiquitination and/or relay information from mitochondria to other cellular compartments.

(B) Alternatively, Pink1 may be released from mitochondria after cleavage to interact with DJ-1 and Parkin in the cytosol.

A and B differ in the site of action of the PPD complex and the cleavage status of Pink1.

The complex forms on the mitochondrial outer membrane potentially containing full-length Pink1 in A, and in the cytosol with cleaved Pink1 in B.

Lack of DJ-1 function results in phenotypes that are distinct from the mitochondrial phenotypes observed in null mutants of Pink1 or Parkin in Drosophila. Thus, although the PPD complex is illustrated here as regulating mitochondrial fission, the role of DJ-1 in vivo remains to be clarified.

(C) It is also possible that the action occurs in the cytosol and is independent of the function of Pink1/Parkin in regulating mitochondrial integrity and function.

The Xiong et al. study offers an entry point for explorations of the role of Pink1, Parkin, and DJ-1 in the cytoplasm. It remains to be shown whether Parkin, in complex with Pink1 and DJ-1, carries out protein degradation in vivo.

Li H, and Guo M. Protein degradation in Parkinson disease revisited: it’s complex. commentaries. J Clin Invest.  doi:10.1172/JCI38619. http://www.jci.org
http://JCI.org/ Protein_degradation_in_Parkinson_disease_revisited_it’s_complex/

Xiong, H., et al. Parkin, PINK1, and DJ-1 form a ubiquitin E3 ligase complex promoting unfolded protein degradation. J. Clin. Invest. 2009; 119:650–660.
http://JCI.org/ Parkin_PINK1_DJ1_form_ubiquitin_E3_ligase_complex_promoting_unfolded_protein_degradation/

Mitochondrial Ubiquitin Ligase, MITOL, protects neuronal cells

Nitric oxide (NO) is implicated in neuronal cell survival. However, excessive NO production mediates neuronal cell death, in part via mitochondrial dysfunction. Here, we report that the mitochondrial ubiquitin ligase, MITOL, protects neuronal cells from mitochondrial damage caused by accumulation of S-nitrosylated microtubule associated protein 1B-light chain 1 (LC1). S-nitrosylation of LC1 induces a conformational change that serves both to activate LC1 and to promote its ubiquination by MITOL, indicating that microtubule stabilization by LC1 is regulated through its interaction with MITOL. Excessive NO production can inhibit MITOL, and MITOL inhibition resulted in accumulation of S-nitrosylated LC1 following stimulation of NO production by calcimycin and N-methyl-D-aspartate. LC1 accumulation under these conditions resulted in mitochondrial dysfunction and neuronal cell death. Thus, the balance between LC1 activation by S-nitrosylation and down-regulation by MITOL is critical for neuronal cell survival. Our findings may contribute significantly to an understanding of the mechanisms of neurological diseases caused by nitrosative stress-mediated mitochondrial dysfunction.

Yonashiro R, Kimijima Y, Shimura T, Kawaguchi K, et al. Mitochondrial ubiquitin ligase MITOL blocks S-nitrosylated MAP1B-light chain 1-mediated mitochondrial dysfunction and neuronal cell death. PNAS; 2012. pp 6. www.pnas.org/cgi/doi/10.1073/pnas.1114985109

Ubiquitin–Proteasome System in Neurodegeneration

A common histopathological hallmark of most neurodegenerative diseases is the presence of aberrant proteinaceous inclusions inside affected neurons. Because these protein aggregates are detected using antibodies against components of the ubiquitin–proteasome system (UPS), impairment of this machinery for regulated proteolysis has been suggested to be at the root of neurodegeneration. This hypothesis has been difficult to prove in vivo owing to the lack of appropriate tools. The recent report of transgenic mice with ubiquitous expression of a UPS-reporter protein should finally make it possible to test in vivo the role of the UPS in neurodegeneration.

Hernandez F, Dıaz-Hernandez M, Avila J and Lucas JJ. Testing the ubiquitin–proteasome hypothesis of neurodegeneration in vivo. TRENDS in Neurosciences 2004; 27(2): 66-68.

ALP in Parkinson’s

The ubiquitin-proteasome system (UPS) and autophagy-lysosome pathway (ALP) are the two most important mechanisms that normally repair or remove abnormal proteins. Alterations in the function of these systems to degrade misfolded and aggregated proteins are being increasingly recognized as playing a pivotal role in the pathogenesis of many neurodegenerative disorders such as Parkinson’s disease. Dysfunction of the UPS has been already strongly implicated in the pathogenesis of this disease and, more recently, growing interest has been shown in identifying the role of ALP in neurodegeneration. Mutations of a-synuclein and the increase of intracellular concentrations of non-mutant a-synuclein have been associated with Parkinson’s disease phenotype.

The demonstration that a-synuclein is degraded by both proteasome and autophagy indicates a possible linkage between the dysfunction of the UPS or ALP and the occurrence of this disorder.The fact that mutant a-synucleins inhibit ALP functioning by tightly binding to the receptor on the lysosomal membrane for autophagy pathway further supports the assumption that impairment of the ALP may be related to the development of Parkinson’s disease.  In this review, we summarize the recent findings related to this topic and discuss the unique role of the ALP in this neurogenerative disorder and the putative therapeutic potential through ALP enhancement.

Pan Y, Kondo S, Le W, Jankovic J. The role of autophagy-lysosome pathway in neurodegeneration associated with Parkinson’s disease. Brain 2008; 131: 1969-1978. doi:10.1093/brain/awm318.

Ubiquitin-Proteasome System in Parkinson’s

There is growing evidence that dysfunction of the mitochondrial respiratory chain and failure of the cellular protein degradation machinery, specifically the ubiquitin-proteasome system, play an important role in the pathogenesis of Parkinson’s disease. We now show that the corresponding pathways of these two systems are linked at the transcriptomic level in Parkinsonian substantia nigra. We examined gene expression in medial and lateral substantia nigra (SN) as well as in frontal cortex using whole genome DNA oligonucleotide microarrays. In this study, we use a hypothesis-driven approach in analysing microarray data to describe the expression of mitochondrial and ubiquitin-proteasomal system (UPS) genes in Parkinson’s disease (PD).

Although a number of genes showed up-regulation, we found an overall decrease in expression affecting the majority of mitochondrial and UPS sequences. The down-regulated genes include genes that encode subunits of complex I and the Parkinson’s-disease-linked UCHL1. The observed changes in expression were very similar for both medial and lateral SN and also affected the PD cerebral cortex. As revealed by “gene shaving” clustering analysis, there was a very significant correlation between the transcriptomic profiles of both systems including in control brains.

Therefore, the mitochondria and the proteasome form a higher-order gene regulatory network that is severely perturbed in Parkinson’s disease. Our quantitative results also suggest that Parkinson’s disease is a disease of more than one cell class, i.e. that it goes beyond the catecholaminergic neuron and involves glia as well.

Duke DC, Moran LB, Kalaitzakis ME, Deprez M, et al. Transcriptome analysis reveals link between proteasomal and mitochondrial pathways in Parkinson’s disease. Neurogenetics 2006; 7:139-148.

The causes of various neurodegenerative diseases, particularly sporadic cases, remain unknown, but increasing evidence suggests that these diseases may share similar molecular and cellular mechanisms of pathogenesis. One prominent feature common to most neurodegenerative diseases is the accumulation of misfolded proteins in the form of insoluble protein aggregates or inclusion bodies. Although these aggregates have different protein compositions, they all contain ubiquitin and proteasome subunits, implying a failure of the ubiquitin-proteasome system (UPS) in the removal of misfolded proteins.

A direct link between UPS dysfunction and neurodegeneration has been provided by recent findings that genetic mutations in UPS components cause several rare, familial forms of neurodegenerative diseases. Furthermore, it is becoming increasingly clear that oxidative stress, which results from aging or exposure to environmental toxins, can directly damage UPS components, thereby contributing to the pathogenesis of sporadic forms of neurodegenerative diseases.

Aberrations in the UPS often result in defective proteasome-mediated protein degradation, leading to accumulation of toxic proteins and eventually to neuronal cell death. Interestingly, emerging evidence has begun to suggest that impairment in substrate-specific components of the UPS, such as E3 ubiquitin-protein ligases, may cause aberrant ubiquitination and neurodegeneration in a proteasome-independent manner. This provides an overview of the molecular components of the UPS and their impairment in familial and sporadic forms of neurodegenerative diseases, and summarizes present knowledge about the pathogenic mechanisms of UPS dysfunction in neurodegeneration.

Molecular mechanisms of protein ubiquitination and degradation by the UPS. Ubiquitination involves a highly specific enzyme cascade in which

  • ubiquitin (Ub) is first activated by the ubiquitinactivating enzyme (E1),
  • then transferred to an ubiquitin-conjugating enzyme (E2), and
  • finally covalently attached to the substrate by an ubiquitin-protein ligase (E3).

Ubiquitination is a reversible posttranslational modification in which the removal of Ub is mediated by a deubiquitinating enzyme (DUB).

  • Substrate proteins can be either monoubiquitinated or polyubiquitinated through successive conjugation of Ub moieties to an internal lysine residue in Ub.
  • K48-linked poly-Ub chains are recognized by the 26S proteasome, resulting in degradation of the substrate and recycling of Ub.

Monoubiquitination or K63-linked polyubiquitination plays a number of regulatory roles in cells that are proteasome-independent.

Parkin

Loss-of-function mutations in parkin, a 465-amino-acid RING-type E3 ligase, were first identified as the cause for autosomal recessive juvenile Parkinsonism (AR-JP) and subsequently found to account for ~50% of all recessively transmitted early-onset PD cases. Interestingly, patients with parkin mutations do not exhibit Lewy body pathology.

Possible pathogenic mechanisms by which impaired UPS components cause neurodegeneration. Genetic mutations or oxidative stress from aging and/or exposure to environmental toxins have been shown to impair the ubiquitination machinery (particularly E3 ubiquitin-protein ligases) and deubiquitinating enzymes (DUBs), resulting in abnormal ubiquitination. Depending on the type of ubiquitination affected, the impairment could cause neurodegeneration through two different mechanisms.

  1. aberrant K48-linked polyubiquitination resulting from impaired E3s or DUBs alters protein degradation by the proteasome, leading to accumulation of toxic proteins and subsequent neurodegeneration. The proteasomes could be directly damaged by oxidative stress or might be inhibited by protein aggregation, which exacerbates the neurotoxicity.
  2. aberrant monoubiquitination or K63-linked polyubiquitination resulting from impaired E3s or DUBs alters crucial non-proteasomal functions, such as gene transcription and protein trafficking, thereby causing neurodegeneration without protein aggregation.

These two models are not mutually exclusive because a single E3 or DUB enzyme, such as parkin or UCH-L1, could regulate more than one type of ubiquitination. In addition, abnormal ubiquitination and neurodegeneration could also result from mutation or oxidative stress-induced structural changes in the protein substrates that alter their recognition and degradation by the UPS.

Lian Li and Chin LS. IMPAIRMENT OF THE UBIQUITIN-PROTEASOME SYSTEM: A COMMON PATHOGENIC MECHANISM IN NEURODEGENERATIVE DISORDERS. In The Ubiquitin Proteasome System…Chapter 23. (Eds: Eds: Mario Di Napoli and Cezary Wojcik) 553-577 © 2007 Nova Science Publishers, Inc. ISBN 978-1-60021-749-4.

filedesc Schematic diagram of the ubiquitylation system. Created by Roger B. Dodd (Photo credit: Wikipedia)

Current Noteworthy Work

Statins inhibit HMG-CoA reductase, a key enzyme in cholesterol synthesis, and are widely used to treat hypercholesterolemia.

These drugs can lead to a number of side effects in muscle, including muscle fiber breakdown; however, the mechanisms of muscle injury by statins are poorly understood. We report that lovastatin induced the expression of atrogin-1, a key gene involved in skeletal muscle atrophy, in humans with statin myopathy, in zebrafish embryos, and in vitro in murine skeletal muscle cells. In cultured mouse myotubes, atrogin-1 induction following lovastatin treatment was accompanied by distinct morphological changes, largely absent in atrogin-1 null cells. In zebrafish embryos, lovastatin promoted muscle fiber damage, an effect that was closely mimicked by knockdown of zebrafish HMG-CoA reductase. Moreover, atrogin-1 knockdown in zebrafish embryos prevented lovastatin-induced muscle injury. Finally, overexpression of PGC-1α, a transcriptional coactivator that induces mitochondrial biogenesis and protects against the development of muscle atrophy, dramatically prevented lovastatin-induced muscle damage and abrogated atrogin-1 induction both in fish and in cultured mouse myotubes. Collectively, our human, animal, and in vitro findings shed light on the molecular mechanism of statin-induced myopathy and suggest that atrogin-1 may be a critical mediator of the muscle damage induced by statins.

Inami Y, Waguri S, Sakamoto A, Kouno T, et al.  Persistent activation of Nrf2 through p62 in hepatocellular carcinoma cells. J. Cell Biol. 2011; 193(2): 275–284. www.jcb.org/cgi/doi/10.1083/jcb.201102031

Macroautophagy (hereafter referred to as autophagy) is a cellular degradation system in which cytoplasmic components, including organelles, are sequestered by double membrane structures called autophagosomes and the sequestered materials are degraded by lysosomal hydrolases for supply of amino acids and for cellular homeostasis. Although autophagy has generally been considered nonselective, recent studies have shed light on another indispensable role for basal autophagy in cellular homeostasis, which is mediated by selective degradation of a specific substrate(s).  p62 is a ubiquitously expressed cellular protein that is conserved in metazoa but not in plants and fungi, and recently it has been known as one of the selective substrates for autophagy.

This protein is localized at the autophagosome formation site and directly interacts with LC3, an autophagosome localizing protein . Subsequently, the p62 is incorporated into the autophagosome and then degraded. Therefore, impaired autophagy is accompanied by accumulation of p62 followed by the formation of p62 and ubiquitinated protein aggregates because of the nature of both self- oligomerization and ubiquitin binding of p62.

Epicrisis

This extensive review leaves little left unopened. We have seen the central role that the UPS system plays in normal organelle proteolysis in concert with autophagy. Impaired ubiquitination occurs from aging, and/or toxins, under oxidative stress involving E3s or DUBs.

This leads to altered gene transcripton, altered protein trafficking, and plays a role in neurodegenative disease, and muscle malfunction.

English: A cartoon representation of a lysine 48-linked diubiquitin molecule. The two ubiquitin chains are shown as green cartoons with each chain labelled. The components of the linkage are indicated and shown as orange sticks. Image was created using PyMOL from PDB id 1aar. (Photo credit: Wikipedia)

Different forms of protein ubiquitylation (Photo credit: Wikipedia)

 

                              nature10774-f6.2 (1)  tetra-ubiquitin chain conjugated to the undtructured initiation region of a substrate and bound to the ubiquitin receptor Rpn13. substrate poised for deubiquination by Rpn11

filedesc Schematic diagram of the ubiquitylati...

filedesc Schematic diagram of the ubiquitylation system. Created by Roger B. Dodd (Photo credit: Wikipedia)

Autophagy

Autophagy (Photo credit: Wikipedia)

English: Structure of the PARK2 protein. Based...

English: Structure of the PARK2 protein. Based on PyMOL rendering of PDB 1iyf. (Photo credit: Wikipedia)

Comparison of the process of macroautophagy ve...

Comparison of the process of macroautophagy versus microautophagy. (Photo credit: Wikipedia)

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Reporter: Aviral Vatsa PhD, MBBS

Osteocytes are the professional mechanosensors of bone. They modulate bone remodelling in accordance with external mechanical loads by orchestrating the activity of one forming osteoblasts and bone resorbing osteoclasts. Osteocytes are at the heart of bone metabolism. They constitute >95% of bone cells. They are terminally differentiated cells and reside in the hard mineralised matrix of bone, thus making it difficult to study them in situ. However, recent developments in imaging and tissue processing have made it possible to study osteocytes in their natural milieu. Moreover, increasing number of studies have highlighted the fact that a multifaceted approach from various domains of science such as biomechanics, cell biology, bioengineering, biophysics, biomaterials, computational modelling, endocrinology, and orthopaedics is essential to further our understanding of the intricate processes involved in bone remodelling and the central role of osteocytes in maintaining bone mass and architecture.

In this post a variety of reviews from an upcoming special issue on osteocytes in the journal Bone are highlighted that help us add few more pieces of knowledge to the ever growing eclaircissements on the subject.

1. Measurement and estimation of osteocyte mechanical strain

Review Article
Amber Rath Stern, Daniel P. Nicolella

Abstract

Osteocytes are the most abundant cell type in bone and are responsible for sensing mechanical strain and signaling bone (re)modeling, making them the primary mechanosensors within the bone. Under aging and osteoporotic conditions, bone is known to be less responsive to loading (exercise), but it is unclear why. Perhaps, the levels of mechanical strain required to initiate these biological events are not perceived by the osteocytes embedded within the bone tissue. In this review we examine the methods used to measure and estimate the strains experienced by osteocytes in vivo as well as the results of related published experiments. Although the physiological levels of strain experienced by osteocytes in vivo are still under investigation, through computational modeling and laboratory experiments, it has been shown that there is significant amplification of average bone strain at the level of the osteocyte lacunae. It has also been proposed that the material properties of the perilacunar region surrounding the osteocyte can have significant effects of the strain perceived by the embedded osteocyte. These facts have profound implications for studies involving osteoporotic bone where the material properties are known to become stiffer.

2. Glucocorticoids and Osteocyte Autophagy

Review Article
Wei Yao, Weiwei Dai, Jean X. Jiang, Nancy E. Lane

Abstract

Glucocorticoids are used for the treatment of inflammatory and autoimmune diseases. While they are effective therapy, bone loss and incident fracture risk is high. While previous studies have found GC effects on both osteoclasts and oteoblasts, our work has focused on the effects of GCs on osteocytes. Osteocytes exposed to low dose GCs undergo autophagy while osteocytes exposed to high doses of GCs or for a prolonged period of time undergo apoptosis. This paper will review the data to support the role of GCs in osteocyte autophagy.

3. Osteocytes remove and replace perilacunar mineral during reproductive cycles

Review Article
John J. Wysolmerski

Abstract

Lactation is associated with an increased demand for calcium and is accompanied by a remarkable cycle of bone loss and recovery that helps to supply calcium and phosphorus for milk production. Bone loss is the result of increased bone resorption that is due, in part, to increased levels of PTHrP and decreased levels of estrogen. However, the regulation of bone turnover during this time is not fully understood. In the 1960s and 1970s many observations were made to suggest that osteocytes could resorb bone and increase the size of their lacunae. This concept became known as osteocytic osteolysis and studies suggested that it occurred in response to parathyroid hormone and/or an increased systemic demand for calcium. However, this concept fell out of favor in the late 1970s when it was established that osteoclasts were the principal bone-resorbing cells. Given that lactation is associated with increased PTHrP levels and negative calcium balance, we recently examined whether osteocytes contribute to bone loss during this time. Our findings suggest that osteocytes can remodel their perilacunar and pericanalicular matrix and that they participate in the liberation of skeletal calcium stores during reproductive cycles. These findings raise new questions about the role of osteocytes in coordinating bone and mineral metabolism during lactation as well as the recovery of bone mass after weaning. It is also interesting to consider whether osteocyte lacunar and canalicular remodeling contribute more broadly to the maintenance of skeletal and mineral homeostasis.

4. Studying osteocytes within their environment

Review Article
Duncan J. Webster, Philipp Schneider, Sarah L. Dallas, Ralph Müller

Abstract

It is widely hypothesized that osteocytes are the mechano-sensors residing in the bone’s mineralized matrix which control load induced bone adaptation. Owing to their inaccessibility it has proved challenging to generate quantitative in vivo experimental data which supports this hypothesis. Recent advances in in situ imaging, both in non-living and living specimens, have provided new insights into the role of osteocytes in the skeleton. Combined with the retrieval of biochemical information from mechanically stimulated osteocytes using in vivo models, quantitative experimental data is now becoming available which is leading to a more accurate understanding of osteocyte function. With this in mind, here we review i) state of the art ex vivo imaging modalities which are able to precisely capture osteocyte structure in 3D, ii) live cell imaging techniques which are able to track structural morphology and cellular differentiation in both space and time, and iii) in vivo models which when combined with the latest biochemical assays and microfluidic imaging techniques can provide further insight on the biological function of osteocytes.

5. Osteocyte apoptosis

Review Article
Robert L. Jilka, Brendon Noble, Robert S. Weinstein

Abstract

Apoptotic death of osteocytes was recognized over 15 years ago, but its significance for bone homeostasis has remained elusive. A new paradigm has emerged that invokes osteocyte apoptosis as a critical event in the recruitment of osteoclasts to a specific site in response to skeletal unloading, fatigue damage, estrogen deficiency and perhaps in other states where bone must be removed. This is accomplished by yet to be defined signals emanating from dying osteocytes, which stimulate neighboring viable osteocytes to produce osteoclastogenic cytokines. The osteocyte apoptosis caused by chronic glucocorticoid administration does not increase osteoclasts; however, it does negatively impact maintenance of bone hydration, vascularity, and strength.

6. Emerging role of primary cilia as mechanosensors in osteocytes

Review Article
An M. Nguyen, Christopher R. Jacobs

Abstract

The primary cilium is a solitary, immotile microtubule-based extension present on nearly every mammalian cell. This organelle has established mechanosensory roles in several contexts including kidney, liver, and the embryonic node. Mechanical load deflects the cilium, triggering biochemical responses. Defects in cilium function have been associated with numerous human diseases. Recent research has implicated the primary cilium as a mechanosensor in bone. In this review, we discuss the cilium, the growing evidence for its mechanosensory role in bone, and areas of future study.

7. Mechanosensation and transduction in osteocytes

Review Article
Jenneke Klein-Nulend, Astrid D. Bakker, Rommel G. Bacabac, Aviral Vatsa, Sheldon Weinbaum

Abstract

The human skeleton is a miracle of engineering, combining both toughness and light weight. It does so because bones possess cellular mechanisms wherein external mechanical loads are sensed. These mechanical loads are transformed into biological signals, which ultimately direct bone formation and/or bone resorption. Osteocytes, since they are ubiquitous in the mineralized matrix, are the cells that sense mechanical loads and transduce the mechanical signals into a chemical response. The osteocytes then release signaling molecules, which orchestrate the recruitment and activity of osteoblasts or osteoclasts, resulting in the adaptation of bone mass and structure. In this review, we highlight current insights in bone adaptation to external mechanical loading, with an emphasis on how a mechanical load placed on whole bones is translated and amplified into a mechanical signal that is subsequently sensed by the osteocytes.

8. The osteocyte in CKD: New concepts regarding the role of FGF23 in mineral metabolism and systemic complications

Review Article
Katherine Wesseling-Perry, Harald Jüppner

Abstract

The identification of elevated circulating levels of the osteocytic protein fibroblast growth factor 23 (FGF23) in patients with chronic kidney disease (CKD), along with recent data linking these values to the pathogenesis of secondary hyperparathyroidism and to systemic complications, has changed the approach to the pathophysiology and treatment of disordered bone and mineral metabolism in renal failure. It now appears that osteocyte biology is altered very early in the course of CKD and these changes have implications for bone biology, as well as for progressive cardiovascular and renal disease. Since circulating FGF23 values are influenced by therapies used to treat secondary hyperparathyroidism, the effects of different therapeutic paradigms on FGF23 have important implications for mineral metabolism as well as for morbidity and mortality. Further studies are critically needed to identify the initial trigger for abnormalities of skeletal mineralization and turnover as well as the potential effects that current therapeutic options may have on osteocyte biology.

9. Vitamin D signaling in osteocytes: Effects on bone and mineral homeostasis

Review Article
Liesbet Lieben, Geert Carmeliet

Abstract

The active form of vitamin D [1,25(OH)2D] is an important regulator of calcium and bone homeostasis, as evidenced by the consequences of 1,25(OH)2D inactivity in man and mice, which include hypocalcemia, hypophosphatemia, secondary hyperparathyroidism and bone abnormalities. The recent generation of tissue-specific (intestine, osteoblast/osteocyte, chondrocyte) vitamin D receptor (Vdr) null mice has provided mechanistic insight in the cell-specific actions of 1,25(OH)2D and their contribution to the integrative physiology of VDR signaling that controls bone and mineral metabolism. These studies have demonstrated that even with normal dietary calcium intake, 1,25(OH)2D is crucial to maintain normal calcium and bone homeostasis and accomplishes this through this primarily through stimulation of intestinal calcium transport. When, moreover, insufficient calcium is acquired from the diet (severe dietary calcium restriction, lack of intestinal VDR activity), 1,25(OH)2D levels will increase and will directly act on osteoblasts and osteocytes to enhance bone resorption and to suppress bone matrix mineralization. Although this system is essential to maintain normal calcium levels in blood during a negative calcium balance, the consequences for bone are disastrous and generate an increased fracture risk. These findings evidently demonstrate that preservation of serum calcium levels has priority over skeletal integrity. Since vitamin D supplementation is an essential part of anti-osteoporotic therapy, mechanistic insight in vitamin D actions is required to define the optimal therapeutic regimen, taking into account the amount of dietary calcium supply, in order to maximize the targeted outcome and to avoid side-effects. We will review the current understanding concerning the functions of osteoblastic/osteocytic VDR signaling which not only include the regulation of bone metabolism, but also comprise the control of calcium and phosphate homeostasis via fibroblast growth factor (FGF) 23 secretion and the maintenance of the hematopoeitic stem cell (HSC) niche, with special focus on the experimental data obtained from systemic and osteoblast/osteocyte-specific Vdr null mice.

10. In vitro and in vivo approaches to study osteocyte biology

Review Article
Ivo Kalajzic, Brya G. Matthews, Elena Torreggiani, Marie A. Harris, Paola Divieti Pajevic, Stephen E. Harris

Abstract

Osteocytes, the most abundant cell population of the bone lineage, have been a major focus in the bone research field in recent years. This population of cells that resides within mineralized matrix is now thought to be the mechanosensory cell in bone and plays major roles in the regulation of bone formation and resorption. Studies of osteocytes had been impaired by their location, resulting in numerous attempts to isolate primary osteocytes and to generate cell lines representative of the osteocytic phenotype. Progress has been achieved in recent years by utilizing in vivo genetic technology and generation of osteocyte directed transgenic and gene deficiency mouse models.

We will provide an overview of the current in vitro and in vivo models utilized to study osteocyte biology. We discuss generation of osteocyte-like cell lines and isolation of primary osteocytes and summarize studies that have utilized these cellular models to understand the functional role of osteocytes. Approaches that attempt to selectively identify and isolate osteocytes using fluorescent protein reporters driven by regulatory elements of genes that are highly expressed in osteocytes will be discussed.

In addition, recent in vivo studies utilizing overexpression or conditional deletion of various genes using dentin matrix protein (Dmp1) directed Cre recombinase are outlined. In conclusion, evaluation of the benefits and deficiencies of currently used cell lines/genetic models in understanding osteocyte biology underlines the current progress in this field. The future efforts will be directed towards developing novel in vitro and in vivo models that would additionally facilitate in understanding the multiple roles of osteocytes.

11. Gap junction and hemichannel functions in osteocytes

Review Article
Alayna E. Loiselle, Jean X. Jiang, Henry J. Donahue

Abstract

Cell-to-cell and cell-to-matrix communication in bone cells mediated by gap junctions and hemichannels, respectively, maintains bone homeostasis. Gap junctional communication between cells permits the passage of small molecules including calcium and cyclic AMP. This cell-to-cell communication occurs between bone cells including osteoblasts, osteoclasts and osteocytes, and is important in both bone formation and bone resorption. Connexin (Cx) 43 is the predominant gap junction protein in bone cells, and facilitates the communication of cellular signals either through docking of gap junctions between two cells, or through the formation of un-paired hemichannels. Systemic deletion of Cx43 results in perinatal lethality, so conditional deletion models are necessary to study the postnatal role of gap junctions in bone. These models provide the opportunity to determine the role of gap junctions in specific bone cells, notably the osteocyte. In this review, we summarize the key roles that gap junctions and hemichannels in osteocytes play in bone cell response to many stimuli including mechanical loading, intracellular and extracellular stimuli, such as parathyroid hormone, PGE2, plasma calcium levels and pH, as well as in maintaining osteocyte survival.

12. Effects of PTH on osteocyte function

Review Article
Teresita Bellido, Vaibhav Saini, Paola Divieti Pajevic

Abstract

Osteocytes are ideally positioned to detect and respond to mechanical and hormonal stimuli and to coordinate the function of osteoblasts and osteoclasts. However, evidence supporting the involvement of osteocytes in specific aspects of skeletal biology has been limited mainly due to the lack of suitable experimental approaches. Few crucial advances in the field in the past several years have markedly increased our understanding of the function of osteocytes. The development of osteocytic cell lines initiated a plethora of in vitro studies that have provided insights into the unique biology of osteocytes and continue to generate novel hypotheses. Genetic approaches using promoter fragments that direct gene expression to osteocytes allowed the generation of mice with gain or loss of function of particular genes revealing their role in osteocyte function. Furthermore, evidence that Sost/sclerostin is expressed primarily in osteocytes and inhibits bone formation by osteoblasts, fueled research attempting to identify regulators of this gene as well as other osteocyte products that impact the function of osteoblasts and osteoclasts. The discovery that parathyroid hormone (PTH), a central regulator of bone homeostasis, inhibits sclerostin expression generated a cascade of studies that revealed that osteocytes are crucial target cells of the actions of PTH. This review highlights these investigations and discusses their significance for advancing our understanding of the mechanisms by which osteocytes regulate bone homeostasis and for developing therapies for bone diseases targeting osteocytes.

13. For whom the bell tolls: Distress signals from long-lived osteocytes and the pathogenesis of metabolic bone diseases

Review Article
Stavros C. Manolagas, A. Michael Parfitt

Abstract

Osteocytes are long-lived and far more numerous than the short-lived osteoblasts and osteoclasts. Immured within the lacunar–canalicular system and mineralized matrix, osteocytes are ideally located throughout the bone to detect the need for, and accordingly choreograph, the bone regeneration process by independently controlling rate limiting steps of bone resorption and formation. Consistent with this role, emerging evidence indicates that signals arising from apoptotic and old/or dysfunctional osteocytes are seminal culprits in the pathogenesis of involutional, post-menopausal, steroid-, and immobilization-induced osteoporosis. Osteocyte-originated signals may also contribute to the increased bone fragility associated with bone matrix disorders like osteogenesis imperfecta, and perhaps the rapid reversal of bone turnover above baseline following discontinuation of anti-resorptive treatments, like denosumab.

14. Osteocyte control of osteoclastogenesis

Review Article
Charles A. O’Brien, Tomoki Nakashima, Hiroshi Takayanagi

Abstract

Multiple lines of evidence support the idea that osteocytes act as mechanosensors in bone and that they control bone formation, in part, by expressing the Wnt antagonist sclerostin. However, the role of osteocytes in the control of bone resorption has been less clear. Recent studies have demonstrated that osteocytes are the major source of the cytokine RANKL involved in osteoclast formation in cancellous bone. The goal of this review is to discuss these and other studies that reveal mechanisms whereby osteocytes control osteoclast formation and thus bone resorption.

References

  1. A. R. Stern and D. P. Nicolella, “Measurement and estimation of osteocyte mechanical strain,” Bone.
  2. W. Yao, W. Dai, J. X. Jiang, and N. E. Lane, “Glucocorticoids and Osteocyte Autophagy,” Bone.
  3. J. J. Wysolmerski, “Osteocytes remove and replace perilacunar mineral during reproductive cycles,” Bone.
  4. D. J. Webster, P. Schneider, S. L. Dallas, and R. Müller, “Studying osteocytes within their environment,” Bone.
  5. R. L. Jilka, B. Noble, and R. S. Weinstein, “Osteocyte apoptosis,” Bone.
  6. A. M. Nguyen and C. R. Jacobs, “Emerging role of primary cilia as mechanosensors in osteocytes,” Bone.
  7. J. Klein-Nulend, A. D. Bakker, R. G. Bacabac, A. Vatsa, and S. Weinbaum, “Mechanosensation and transduction in osteocytes,” Bone.
  8. K. Wesseling-Perry and H. Jüppner, “The osteocyte in CKD: New concepts regarding the role of FGF23 in mineral metabolism and systemic complications,” Bone.
  9. L. Lieben and G. Carmeliet, “Vitamin D signaling in osteocytes: Effects on bone and mineral homeostasis,” Bone.
  10. I. Kalajzic, B. G. Matthews, E. Torreggiani, M. A. Harris, P. Divieti Pajevic, and S. E. Harris, “In vitro and in vivo approaches to study osteocyte biology,” Bone.
  11. A. E. Loiselle, J. X. Jiang, and H. J. Donahue, “Gap junction and hemichannel functions in osteocytes,” Bone.
  12. T. Bellido, V. Saini, and P. D. Pajevic, “Effects of PTH on osteocyte function,” Bone.
  13. S. C. Manolagas and A. M. Parfitt, “For whom the bell tolls: Distress signals from long-lived osteocytes and the pathogenesis of metabolic bone diseases,” Bone
  14. C. A. O’Brien, T. Nakashima, and H. Takayanagi, “Osteocyte control of osteoclastogenesis,” Bone.
  15. Bone remodelling in a nutshel June 22, 2012 by aviralvatsa
  16. Isolation of primary osteocytes from skeletally mature mice bones: Reoprt on “Isolation and culture of primary osteocytes from the long bones of skeletally mature and aged mice” (BioTechniques 52:361-373 ( June 2012) doi 10.2144/0000113876 )
  17. Nitric Oxide in bone metabolism July 16, 2012 by aviralvatsa

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