Posts Tagged ‘enzymes’

Effect of mitochondrial stress on epigenetic modifiers

Larry H. Bernstein, MD, FCAP, Curator



Early Mitochondrial Stress Alters Epigenetics, Secures Lifelong Health Benefits

GEN 5/3/2016

A little adversity builds character, or so the saying goes. True or not, the saying does seem an apt description of a developmental phenomenon that shapes gene expression. While it knows nothing of character, the gene expression apparatus appears to respond well to short-term mitochondrial stress that occurs early in development. In fact, transient stress seems to result in lasting benefits. These benefits, which include improved metabolic function and increased longevity, have been observed in both worms and mice, and may even occur—or be made to occur—in humans.

Gene expression is known to be subject to reprogramming by epigenetic modifiers, but such modifiers generally affect metabolism or lifespan, not both. A new set of epigenetic modifiers, however, has been found to trigger changes that do just that—both improve metabolism and extend lifespan.

Scientists based at the University of California, Berkeley, and the École Polytechnique Fédérale de Lausanne (EPFL) have discovered enzymes that are ramped up after mild stress during early development and continue to affect the expression of genes throughout the animal’s life. When the scientists looked at strains of inbred mice that have radically different lifespans, those with the longest lifespans had significantly higher expression of these enzymes than did the short-lived mice.

“Two of the enzymes we discovered are highly, highly correlated with lifespan; it is the biggest genetic correlation that has ever been found for lifespan in mice, and they’re both naturally occurring variants,” said Andrew Dillin, a UC Berkeley professor of molecular and cell biology. “Based on what we see in worms, boosting these enzymes could reprogram your metabolism to create better health, with a possible side effect of altering lifespan.”

Details of the work, which appeared online April 29 in the journal Cell, are presented in a pair of papers. One paper (“Two Conserved Histone Demethylases Regulate Mitochondrial Stress-Induced Longevity”) resulted from an effort led by Dillin and the EPFL’s Johan Auwerx. The other paper (“Mitochondrial Stress Induces Chromatin Reorganization to Promote Longevity and UPRmt”) resulted from an effort led by Dillin and his UC Berkeley colleague Barbara Meyer.

According to these papers, mitochondrial stress activates enzymes in the brain that affect DNA folding, exposing a segment of DNA that contains the 1500 genes involved in the work of the mitochondria. A second set of enzymes then tags these genes, affecting their activation for much or all of the lifetime of the animal and causing permanent changes in how the mitochondria generates energy.

The first set of enzymes—methylases, in particular LIN-65—add methyl groups to the DNA, which can silence promoters and thus suppress gene expression. By also opening up the mitochondrial genes, these methylases set the stage for the second set of enzymes—demethylases, in this case jmjd-1.2 and jmjd-3.1—to ramp up transcription of the mitochondrial genes. When the researchers artificially increased production of the demethylases in worms, all the worms lived longer, a result identical to what is observed after mitochondrial stress.

“By changing the epigenetic state, these enzymes are able to switch genes on and off,” Dillin noted. This happens only in the brain of the worm, however, in areas that sense hunger or satiety. “These genes are expressed in neurons that are sensing the nutritional status of the animal, and these signals emanate out to the periphery to change peripheral metabolism,” he continued.

When the scientists profiled enzymes in short- and long-lived mice, they found upregulation of these genes in the brains of long-lived mice, but not in other tissues or in the brains of short-lived mice. “These genes are expressed in the hypothalamus, exactly where, when you eat, the signals are generated that tell you that you are full. And when you are hungry, signals in that region tell you to go and eat,” Dillin explained said. “These genes are all involved in peripheral feedback.”

Among the mitochondrial genes activated by these enzymes are those involved in the body’s response to proteins that unfold, which is a sign of stress. Increased activity of the proteins that refold other proteins is another hallmark of longer life.

These observations suggest that the reversal of aging by epigenetic enzymes could also take place in humans.

“It seems that, while extreme metabolic stress can lead to problems later in life, mild stress early in development says to the body, ‘Whoa, things are a little bit off-kilter here, let’s try to repair this and make it better.’ These epigenetic switches keep this up for the rest of the animal’s life,” Dillin stated.


Two Conserved Histone Demethylases Regulate Mitochondrial Stress-Induced Longevity

Carsten Merkwirth6, Virginija Jovaisaite6, Jenni Durieux,…., Reuben J. Shaw, Johan Auwerx, Andrew Dillin

  • H3K27 demethylases jmjd-1.2 and jmjd-3.1 are required for ETC-mediated longevity
  • jmjd-1.2 and jmjd-3.1 extend lifespan and are sufficient for UPRmt activation
  • UPRmt is required for increased lifespan due to jmjd-1.2 or jmjd-3.1 overexpression
  • JMJD expression is correlated with UPRmt and murine lifespan in inbred BXD lines

Across eukaryotic species, mild mitochondrial stress can have beneficial effects on the lifespan of organisms. Mitochondrial dysfunction activates an unfolded protein response (UPRmt), a stress signaling mechanism designed to ensure mitochondrial homeostasis. Perturbation of mitochondria during larval development in C. elegans not only delays aging but also maintains UPRmt signaling, suggesting an epigenetic mechanism that modulates both longevity and mitochondrial proteostasis throughout life. We identify the conserved histone lysine demethylases jmjd-1.2/PHF8 and jmjd-3.1/JMJD3 as positive regulators of lifespan in response to mitochondrial dysfunction across species. Reduction of function of the demethylases potently suppresses longevity and UPRmt induction, while gain of function is sufficient to extend lifespan in a UPRmt-dependent manner. A systems genetics approach in the BXD mouse reference population further indicates conserved roles of the mammalian orthologs in longevity and UPRmt signaling. These findings illustrate an evolutionary conserved epigenetic mechanism that determines the rate of aging downstream of mitochondrial perturbations.

Figure thumbnail fx1


Mitochondrial Stress Induces Chromatin Reorganization to Promote Longevity and UPRmt
Ye Tian, Gilberto Garcia, Qian Bian, Kristan K. Steffen, Larry Joe, Suzanne Wolff, Barbara J. Meyer, Andrew Dillincorrespondence             Publication stage: In Press Corrected Proof
  • LIN-65 accumulates in the nucleus in response to mitochondrial stress
  • Mitochondrial stress-induced chromatin changes depend on MET-2 and LIN-65
  • LIN-65 and DVE-1 exhibit interdependence in nuclear accumulation
  • met-2 and atfs-1 act in parallel to affect mitochondrial stress-induced longevity

Organisms respond to mitochondrial stress through the upregulation of an array of protective genes, often perpetuating an early response to metabolic dysfunction across a lifetime. We find that mitochondrial stress causes widespread changes in chromatin structure through histone H3K9 di-methylation marks traditionally associated with gene silencing. Mitochondrial stress response activation requires the di-methylation of histone H3K9 through the activity of the histone methyltransferase met-2 and the nuclear co-factor lin-65. While globally the chromatin becomes silenced by these marks, remaining portions of the chromatin open up, at which point the binding of canonical stress responsive factors such as DVE-1 occurs. Thus, a metabolic stress response is established and propagated into adulthood of animals through specific epigenetic modifications that allow for selective gene expression and lifespan extension

 Siddharta Mukherjee’s Writing Career Just Got Dealt a Sucker Punch
Author: Theral Timpson

Siddharha Mukherjee won the 2011 Pulitzer Prize in non-fiction for his book, The Emperor of All Maladies.  The book has received widespread acclaim among lay audience, physicians, and scientists alike.  Last year the book was turned into a special PBS series.  But, according to a slew of scientists, we should all be skeptical of his next book scheduled to hit book shelves this month, The Gene, An Intimate History.

Publishing an article on epigenetics in the New Yorker this week–perhaps a selection from his new book–Mukherjee has waltzed into one of the most active scientific debates in all of biology: that of gene regulation, or epigenetics.

Jerry Coyne, the evolutionary biologist known for keeping journalists honest, has published a two part critique of Mukherjee’s New Yorker piece.  The first part–wildly tweeted yesterday–is a list of quotes from Coyne’s colleagues and those who have written in to the New Yorker, including two Nobel prize winners, Wally Gilbert and Sidney Altman, offering some very unfriendly sentences.

Wally Gilbert: “The New Yorker article is so wildly wrong that it defies rational analysis.”

Sidney Altman:  “I am not aware that there is such a thing as an epigenetic code.  It is unfortunate to inflict this article, without proper scientific review, on the audience of the New Yorker.”

The second part is a thorough scientific rebuttal of the Mukherjee piece.  It all serves as a great drama about one of the most contested ideas in biology and also as a cautionary tale to journalists, even experienced writers such as Mukherjee, about the dangers of wading into scientific arguments.  Readers may remember that a few years ago, science writer, David Dobbs, similarly skated into the same topic with his piece, Die, Selfish Gene, Die, and which raised a similar shitstorm, much of it from Coyne.

Mukherjee’s mistake is in giving credence to only one side of a very fierce debate–that the environment causes changes in the genome which can be passed on; another kind of evolution–as though it were settled science.   Either Mukherjee, a physicisan coming off from a successful book and PBS miniseries on cancer, is setting himself up as a scientist, or he has been a truly naive science reporter.   If he got this chapter so wrong, what does it mean about an entire book on the gene?

Coyne quotes one of his colleagues who raised some questions about the New Yorker’s science reporting, one particular question we’ve been asking here at Mendelspod.  How do we know what we know?  Does science now have an edge on any other discipline for being able to create knowledge?

Coyne’s colleague is troubled by science coverage in the New Yorker, and goes so far as to write that the New Yorker has been waging a “war on behalf of cultural critics and literary intellectuals against scientists and technologists.”

From my experience, it’s not quite that tidy.  First of all, the New Yorker is the best writing I read each week.  Period.  Second, I haven’t found their science writing to have the slant claimed in the quote above.  For example, most other mainstream outlets–including the New York Times with the Amy Harmon pieces–have given the anti-GMO crowd an equal say in the mistaken search for a “balance” on whether GMOs are harmful.  (Remember John Stewart’s criticism of Fox News?  That they give a false equivalent between two sides even when there is no equivalent on the other side?)

But the New Yorker has not fallen into this trap on GMOs and most of their pieces on the topic–mainly by Michael Specter–have been decidedly pro science and therefore decided pro GMO.

So what led Mukherjee to play scientist as well as journalist?  There’s no question about whether I enjoy his prose.  His writing beautifully whisks me away so that I don’t feel that I’m really working to understand.  There is a poetic complexity that constantly brings different threads effortlessly together, weaving them into the same light.  At one point he uses the metaphor of a web for the genome, with the epigenome being the stuff that sticks to the web.  He borrows the metaphor from the Hindu notion of “being”, or jaal.

“Genes form the threads of the web; the detritus that adheres to it transforms every web into a singular being.”

There have been a few writers on Twitter defending Mukherjee’s piece.  Tech Review’s Antonio Regalado called Coyne and his colleagues “tedious literalists” who have an “issue with epigenetic poetry.”

At his best, Mukherjee can take us down the sweet alleys of his metaphors and family stories with a new curiosity for the scientific truth.  He can hold a mirror up to scientists, or put the spotlight on their work.   At their worst, Coyne and his scientific colleagues can reek of a fear of language and therefore metaphor.  The always outspoken scientist and author, Richard Dawkins, who made his name by personifying the gene, was quick to personify epigentics in a tweet:   “It’s high time the 15 minutes of underserved fame for “epigenetics” came to an overdue end.”  Dawkins is that rare scientist who has consistently been as comfortable with rhetoric and language as he is with data.

Hats off to Coyne who reminds us that a metaphor–however lovely–does not some science make. If Mukherjee wants to play scientist, let him create and gather data. If it’s the role of science journalist he wants, let him collect all the science he can before he begins to pour it into his poetry.


Same but Different  

How epigenetics can blur the line between nature and nurture.

Annals of Science MAY 2, 2016 ISSUE     BY

The author’s mother (right) and her twin are a study in difference and identity. CREDIT: PHOTOGRAPH BY DAYANITA SINGH FOR THE NEW YORKER

October 6, 1942, my mother was born twice in Delhi. Bulu, her identical twin, came first, placid and beautiful. My mother, Tulu, emerged several minutes later, squirming and squalling. The midwife must have known enough about infants to recognize that the beautiful are often the damned: the quiet twin, on the edge of listlessness, was severely undernourished and had to be swaddled in blankets and revived.

The first few days of my aunt’s life were the most tenuous. She could not suckle at the breast, the story runs, and there were no infant bottles to be found in Delhi in the forties, so she was fed through a cotton wick dipped in milk, and then from a cowrie shell shaped like a spoon. When the breast milk began to run dry, at seven months, my mother was quickly weaned so that her sister could have the last remnants.
Tulu and Bulu grew up looking strikingly similar: they had the same freckled skin, almond-shaped face, and high cheekbones, unusual among Bengalis, and a slight downward tilt of the outer edge of the eye, something that Italian painters used to make Madonnas exude a mysterious empathy. They shared an inner language, as so often happens with twins; they had jokes that only the other twin understood. They even smelled the same: when I was four or five and Bulu came to visit us, my mother, in a bait-and-switch trick that amused her endlessly, would send her sister to put me to bed; eventually, searching in the half-light for identity and difference—for the precise map of freckles on her face—I would realize that I had been fooled.

But the differences were striking, too. My mother was boisterous. She had a mercurial temper that rose fast and died suddenly, like a gust of wind in a tunnel. Bulu was physically timid yet intellectually more adventurous. Her mind was more agile, her tongue sharper, her wit more lancing. Tulu was gregarious. She made friends easily. She was impervious to insults. Bulu was reserved, quieter, and more brittle. Tulu liked theatre and dancing. Bulu was a poet, a writer, a dreamer.

….. more

Why are identical twins alike? In the late nineteen-seventies, a team of scientists in Minnesota set out to determine how much these similarities arose from genes, rather than environments—from “nature,” rather than “nurture.” Scouring thousands of adoption records and news clips, the researchers gleaned a rare cohort of fifty-six identical twins who had been separated at birth. Reared in different families and different cities, often in vastly dissimilar circumstances, these twins shared only their genomes. Yet on tests designed to measure personality, attitudes, temperaments, and anxieties, they converged astonishingly. Social and political attitudes were powerfully correlated: liberals clustered with liberals, and orthodoxy was twinned with orthodoxy. The same went for religiosity (or its absence), even for the ability to be transported by an aesthetic experience. Two brothers, separated by geographic and economic continents, might be brought to tears by the same Chopin nocturne, as if responding to some subtle, common chord struck by their genomes.

One pair of twins both suffered crippling migraines, owned dogs that they had named Toy, married women named Linda, and had sons named James Allan (although one spelled the middle name with a single “l”). Another pair—one brought up Jewish, in Trinidad, and the other Catholic, in Nazi Germany, where he joined the Hitler Youth—wore blue shirts with epaulets and four pockets, and shared peculiar obsessive behaviors, such as flushing the toilet before using it. Both had invented fake sneezes to diffuse tense moments. Two sisters—separated long before the development of language—had invented the same word to describe the way they scrunched up their noses: “squidging.” Another pair confessed that they had been haunted by nightmares of being suffocated by various metallic objects—doorknobs, fishhooks, and the like.

The Minnesota twin study raised questions about the depth and pervasiveness of qualities specified by genes: Where in the genome, exactly, might one find the locus of recurrent nightmares or of fake sneezes? Yet it provoked an equally puzzling converse question: Why are identical twins different? Because, you might answer, fate impinges differently on their bodies. One twin falls down the crumbling stairs of her Calcutta house and breaks her ankle; the other scalds her thigh on a tipped cup of coffee in a European station. Each acquires the wounds, calluses, and memories of chance and fate. But how are these changes recorded, so that they persist over the years? We know that the genome can manufacture identity; the trickier question is how it gives rise to difference.

….. more

But what turns those genes on and off, and keeps them turned on or off? Why doesn’t a liver cell wake up one morning and find itself transformed into a neuron? Allis unpacked the problem further: suppose he could find an organism with two distinct sets of genes—an active set and an inactive set—between which it regularly toggled. If he could identify the molecular switches that maintain one state, or toggle between the two states, he might be able to identify the mechanism responsible for cellular memory. “What I really needed, then, was a cell with these properties,” he recalled when we spoke at his office a few weeks ago. “Two sets of genes, turned ‘on’ or ‘off’ by some signal.”


“Histones had been known as part of the inner scaffold for DNA for decades,” Allis went on. “But most biologists thought of these proteins merely as packaging, or stuffing, for genes.” When Allis gave scientific seminars in the early nineties, he recalled, skeptics asked him why he was so obsessed with the packing material, the stuff in between the DNA.  …. A skein of silk tangled into a ball has very different properties from that same skein extended; might the coiling or uncoiling of DNA change the activity of genes?

In 1996, Allis and his research group deepened this theory with a seminal discovery. “We became interested in the process of histone modification,” he said. “What is the signal that changes the structure of the histone so that DNA can be packed into such radically different states? We finally found a protein that makes a specific chemical change in the histone, possibly forcing the DNA coil to open. And when we studied the properties of this protein it became quite clear that it was also changing the activity of genes.” The coils of DNA seemed to open and close in response to histone modifications—inhaling, exhaling, inhaling, like life.

Allis walked me to his lab, a fluorescent-lit space overlooking the East River, divided by wide, polished-stone benches. A mechanical stirrer, whirring in a corner, clinked on the edge of a glass beaker. “Two features of histone modifications are notable,” Allis said. “First, changing histones can change the activity of a gene without affecting the sequence of the DNA.” It is, in short, formally epi-genetic, just as Waddington had imagined. “And, second, the histone modifications are passed from a parent cell to its daughter cells when cells divide. A cell can thus record ‘memory,’ and not just for itself but for all its daughter cells.”




The New Yorker screws up big time with science: researchers criticize the Mukherjee piece on epigenetics

Jerry Coyne

Abstract: This is a two part-post about a science piece on gene regulation that just appeared in the New Yorker. Today I give quotes from scientists criticizing that piece; tomorrow I’ll present a semi-formal critique of the piece by two experts in the field.

esterday I gave readers an assignment: read the new New Yorkerpiece by Siddhartha Mukherjee about epigenetics. The piece, called “Same but different” (subtitle: “How epigenetics can blur the line between nature and nurture”) was brought to my attention by two readers, both of whom praised it.  Mukherjee, a physician, is well known for writing the Pulitzer-Prize-winning book (2011) The Emperor of All Maladies: A Biography of Cancer. (I haven’t read it yet, but it’s on my list.)  Mukherjee has a new book that will be published in May: The Gene: An Intimate History. As I haven’t seen it, the New Yorker piece may be an excerpt from this book.

Everyone I know who has read The Emperor of All Maladies gives it high praise. I wish I could say the same for Mukherjee’s New Yorker piece. When I read it at the behest of the two readers, I found his analysis of gene regulation incomplete and superficial. Although I’m not an expert in that area, I knew that there was a lot of evidence that regulatory proteins called “transcription factors”, and not “epigenetic markers” (see discussion of this term tomorrow) or modified histones—the factors emphasized by Mukherjee—played hugely important roles in gene regulation. The speculations at the end of the piece about “Lamarckian evolution” via environmentally induced epigenetic changes in the genome were also unfounded, for we have no evidence for that kind of adaptive evolution. Mukherjee does, however, mention that lack of evidence, though I wish he’d done so more strongly given that environmental modification of DNA bases is constantly touted as an important and neglected factor in evolution.

Unbeknownst to me, there was a bit of a kerfuffle going on in the community of scientists who study gene regulation, with many of them finding serious mistakes and omissions in Mukherjee’s piece.  There appears to have been some back-and-forth emailing among them, and several wrote letters to the New Yorker, urging them to correct the misconceptions, omissions, and scientific errors in “Same but different.” As I understand it, both Mukherjee and the New Yorker simply batted these criticisms away, and, as far as I know, will not publish any corrections.  So today and tomorrow I’ll present the criticisms here, just so they’ll be on the record.

Because Mukherjee writes very well, and because even educated laypeople won’t know the story of gene regulation revealed over the last few decades,  they may not see the big lacunae in his piece. It is, then,  important to set matters straight, for at least we should know what science has told us about how genes are turned on and off. The criticism of Mukherjee’s piece, coming from scientists who really are experts in gene regulation, shows a lack of care on the part of Mukherjee and theNew Yorker: both a superficial and misleading treatment of the state of the science, and a failure of the magazine to properly vet this piece (I have no idea whether they had it “refereed” not just by editors but by scientists not mentioned in the piece).

Let me add one thing about science and the New Yorker. I believe I’ve said this before, but the way the New Yorker treats science is symptomatic of the “two cultures” problem. This is summarized in an email sent me a while back by a colleague, which I quote with permission:

The New Yorker is fine with science that either serves a literary purpose (doctors’ portraits of interesting patients) or a political purpose (environmental writing with its implicit critique of modern technology and capitalism). But the subtext of most of its coverage (there are exceptions) is that scientists are just a self-interested tribe with their own narrative and no claim to finding the truth, and that science must concede the supremacy of literary culture when it comes to anything human, and never try to submit human affairs to quantification or consilience with biology. Because the magazine is undoubtedly sophisticated in its writing and editing they don’t flaunt their postmodernism or their literary-intellectual proprietariness, but once you notice it you can make sense of a lot of their material.

. . . Obviously there are exceptions – Atul Gawande is consistently superb – but as soon as you notice it, their guild war on behalf of cultural critics and literary intellectuals against scientists, technologists, and analytic scholars becomes apparent.

…. more

Researchers criticize the Mukherjee piece on epigenetics: Part 2

Trigger warning: Long science post!

Yesterday I provided a bunch of scientists’ reactions—and these were big names in the field of gene regulation—to Siddhartha Mukherjee’s ill-informed piece in The New Yorker, “Same but different” (subtitle: “How epigenetics can blur the line between nature and nurture”). Today, in part 2, I provide a sentence-by-sentence analysis and reaction by two renowned researchers in that area. We’ll start with a set of definitions (provided by the authors) that we need to understand the debate, and then proceed to the critique.

Let me add one thing to avoid confusion: everything below the line, including the definition (except for my one comment at the end) was written by Ptashne and Greally.

by Mark Ptashne and John Greally


Ptashne is The Ludwig Professor of Molecular Biology at the Memorial Sloan Kettering Cancer Center in New York. He wrote A Genetic Switch, now in its third edition, which describes the principles of gene regulation and the workings of a ‘switch’; and, with Alex Gann, Genes and Signals, which extends these principles and ideas to higher organisms and to other cellular processes as well.  John Greally is the Director of the Center for Epigenomics at the Albert Einstein College of Medicine in New York.


The New Yorker  (May 2, 2016) published an article entitled “Same But Different” written by Siddhartha Mukherjee.  As readers will have gathered from the letters posted yesterday, there is a concern that the article is misleading, especially for a non-scientific audience. The issue concerns our current understanding of “gene regulation” and how that understanding has been arrived at.

First some definitions/concepts:

Gene regulation refers to the “turning on and off of genes”.  The primary event in turning a gene “on” is to transcribe (copy) it into messenger RNA (mRNA). That mRNA is then decoded, usually, into a specific protein.  Genes are transcribed by the enzyme called RNA polymerase.

Development:  the process in which a fertilized egg (e.g., a human egg) divides many times and eventually forms an organism.  During this process, many of the roughly 23,000 genes of a human are turned “on” or “off” in different combinations, at different times and places in the developing organism. The process produces many different cell types in different organs (e.g. liver and brain), but all retain the original set of genes.

Transcription factors: proteins that bind to specific DNA sequences near specific genes and turn transcription of those genes on and off. A transcriptional ‘activator’, for example, bears two surfaces: one binds a specific sequence in DNA, and the other binds to, and thereby recruits to the gene, protein complexes that include RNA polymerase. It is widely acknowledged that the identity of a cell in the body depends on the array of transcription factors present in the cell, and the cell’s history.  RNA molecules can also recognize specific genomic sequences, and they too sometimes work as regulators.  Neither transcription factors nor these kinds of RNA molecules – the fundamental regulators of gene expression and development – are mentioned in the New Yorker article.

Signals:  these come in many forms (small molecules like estrogen, larger molecules (often proteins such as cytokines) that determine the ability of transcription factors to work.  For example, estrogen binds directly to a transcription factor (the estrogen receptor) and, by changing its shape, permits it to bind DNA and activate transcription.

Memory”:  a dividing cell can (often does) produce daughters that are identical, and that express identical genes as does the mother cell.  This occurs because the transcription factors present in the mother cell are passively transmitted to the daughters as the cell divides, and they go to work in their new contexts as before.  To make two different daughters, the cell must distribute its transcription factors asymmetrically.

Positive Feedback: An activator can maintain its own expression by  positive feedback.  This requires, simply, that a copy of the DNA sequence to which the activator binds is  present  near its own gene. Expression of the activator  then becomes self-perpetuating.  The activator (of which there now are many copies in the cell) activates  other target genes as it maintains its own expression. This kind of ‘memory circuit’, first described  in  bacteria, is found in higher organisms as well.  Positive feedback can explain how a fully differentiated cell (that is, a cell that has reached its developmental endpoint) maintains its identity.

Nucleosomes:  DNA in higher organisms (eukaryotes) is wrapped, like beads on a string, around certain proteins (called histones), to form nucleosomes.  The histones are subject to enzymatic modifications: e.g., acetyl, methyl, phosphate, etc. groups can be added to these structures. In bacteria there are no nucleosomes, and the DNA is more or less ‘naked’.

“Epigenetic modifications: please don’t worry about the word ”epigenetic”; it is misused in any case. What Mukherjee refers to by this term are the histone modifications mentioned above, and a modification to DNA itself: the addition of methyl groups. Keep in mind that the organisms that have taught us the most about development – flies (Drosophila) and worms (C. elegans)—do not have the enzymes required for DNA methylation. That does not mean that DNA methylation cannot do interesting things in humans, for example, but it is obviously not at the heart of gene regulation.

Specificity Development requires the highly specific sequential turning on and off of sets of genes.  Transcription factors and RNA supply this specificity, but   enzymes that impart modifications to histones  cannot: every nucleosome (and hence every gene) appears the same to the enzyme.  Thus such enzymes cannot pick out particular nucleosomes associated with particular genes to modify.  Histone modifications might be imagined to convey ‘memory’ as cells divide – but there are no convincing indications that this happens, nor are there molecular models that might explain why they would have the imputed effects.

Analysis and critique of Mukherjee’s article

The picture we have just sketched has taken the combined efforts of many scientists over 50 years to develop.  So what, then, is the problem with the New Yorker article?

There are two: first, the picture we have just sketched, emphasizing the primary role of transcription factors and RNA, is absent.  Second, that picture is replaced by highly dubious speculations, some of which don’t make sense, and none of which has been shown to work as imagined in the article.

(Quotes from the Mukherjee article are indented and in plain text; they are followed by comments, flush left and in bold, by Ptashne and Greally.)

In 1978, having obtained a Ph.D. in biology at Indiana University, Allis began to tackle a problem that had long troubled geneticists and cell biologists: if all the cells in the body have the same genome, how does one become a nerve cell, say, and another a blood cell, which looks and functions very differently?

The problems referred to were recognized long before 1978.  In fact, these were exactly the problems that the great French scientists François Jacob and Jacques Monod took on in the 1950s-60s.  In a series of brilliant experiments, Jacob and Monod showed that in bacteria, certain genes encode products that regulate (turn on and off) specific other genes.  Those regulatory molecules turned out to be proteins, some of which respond to signals from the environment.  Much of the story of modern biology has been figuring out how these proteins – in bacteria and in higher organisms  – bind to and regulate specific genes.  Of note is that in higher organisms, the regulatory proteins look and act like those in bacteria, despite the fact that eukaryotic DNA is wrapped in nucleosomes  whereas bacterial DNA is not.   We have also learned that certain RNA molecules can play a regulatory role, a phenomenon made possible by the fact that RNA molecules, like regulatory proteins, can recognize specific genomic sequences.

In the nineteen-forties, Conrad Waddington, an English embryologist, had proposed an ingenious answer: cells acquired their identities just as humans do—by letting nurture (environmental signals) modify nature (genes). For that to happen, Waddington concluded, an additional layer of information must exist within a cell—a layer that hovered, ghostlike, above the genome. This layer would carry the “memory” of the cell, recording its past and establishing its future, marking its identity and its destiny but permitting that identity to be changed, if needed. He termed the phenomenon “epigenetics”—“above genetics.”

This description greatly misrepresents the original concept.  Waddington argued that development proceeds not by the loss (or gain) of genes, which would be a “genetic” process, but rather that some genes would be selectively expressed in specific and complex cellular patterns as development proceeds.  He referred to this intersection of embryology (then called “epigenesis”) and genetics as “epigenetic”.We now understand that regulatory proteins work in combinations to turn on and off genes, including their own genes, and that sometimes the regulatory proteins respond to signals sent by other cells.  It should be emphasized that Waddington never proposed any “ghost-like” layer of additional information hovering above the gene.  This is a later misinterpretation of a literal translation of the term epigenetics, with “epi-“ meaning “above/upon” the genetic information encoded in DNA sequence.  Unfortunately, this new and pervasive definition encompasses all of transcriptional regulation and is of no practical value.


By 2000, Allis and his colleagues around the world had identified a gamut of proteins that could modify histones, and so modulate the activity of genes. Other systems, too, that could scratch different kinds of code on the genome were identified (some of these discoveries predating the identification of histone modifications). One involved the addition of a chemical side chain, called a methyl group, to DNA. The methyl groups hang off the DNA string like Christmas ornaments, and specific proteins add and remove the ornaments, in effect “decorating” the genome. The most heavily methylated parts of the genome tend to be dampened in their activity.

It is true that enzymes that modify histones have been found—lots of them.  A striking problem is that, after all this time, it is not at all clear what the vast majority of these modifications do.  When these enzymatic activities are eliminated by mutation of their active sites (a task substantially easier to accomplish in yeast than in higher organisms) they mostly have little or no effect on transcription.  It is not even clear that histones are the biologically relevant substrates of most of these enzymes.  

 In the ensuing decade, Allis wrote enormous, magisterial papers in which a rich cast of histone-modifying proteins appear and reappear through various roles, mapping out a hatchwork of complexity. . . These protein systems, overlaying information on the genome, interacted with one another, reinforcing or attenuating their signals. Together, they generated the bewildering intricacy necessary for a cell to build a constellation of other cells out of the same genes, and for the cells to add “memories” to their genomes and transmit these memories to their progeny. “There’s an epigenetic code, just like there’s a genetic code,” Allis said. “There are codes to make parts of the genome more active, and codes to make them inactive.”

By ‘epigenetic code’ the author seems to mean specific arrays of nucleosome modifications, imparted over time and cell divisions, marking genes for expression.  This idea has been tested in many experiments and has been found not to hold.

….. and more


Larry H. Bernstein, MD, FCAP

I hope that this piece brings greater clarity to the discussion.  I have heard the use of the term “epigenetics” for over a decade.  The term was never so clear.  I think that the New Yorker article was a reasonable article for the intended audience.  It was not intended to clarify debates about a mechanism for epigenetic based changes in evolutionary science.  I think it actually punctures the “classic model” of the cell depending only on double stranded DNA and transcription, which deflates our concept of the living cell.  The concept of epigenetics was never really formulated as far as I have seen, and I have done serious work in enzymology and proteins at a time that we did not have the technology that exists today.  I have considered with the critics that protein folding, protein misfolding, protein interactions with proximity of polar and nonpolar groups, and the regulatory role of microRNAs that are not involved in translation, and the evolving concept of what is “dark (noncoding) DNA” lend credence to the complexity of this discussion.  Even more interesting is the fact that enzymes (and isoforms of enzymes) have a huge role in cellular metabolic differences and in the function of metabolic pathways.  What is less understood is the extremely fast reactions involved in these cellular reactions.  These reactions are in my view critical drivers.  This is brought out by Erwin Schroedinger in the book What is Life? which infers that there can be no mathematical expression of life processes.





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Protein profiling in cancer and metabolic diseases

Larry H. Bernstein, MD, FCAP, Curator



Deep Protein Profiling Key

Company has encouraged by two recent reports that emphasise the importance of protein profiling to improve outcomes in cancer treatment.

Proteome Sciences plc has strongly encouraged by two recent reports that emphasise the importance of protein profiling to improve outcomes in cancer treatment. These highlight the growing need for more detailed, personal assessment of protein profiles to improve the management of cancer treatment.

In the first study two groups from University College London and Cancer Research UK demonstrated that genetic mutations in cancer can lead to changes in the proteins on the cell surface1. These are new sequences which are seen as foreign by the body’s immune system and, with appropriate immunotherapy, the level of response in lung cancer was greatly enhanced.

However many of the patients with these types of mutations unfortunately still did not respond which highlighted the need for deeper analysis of the protein expression in tumours in order to better appreciate the mechanisms that contribute to treatment failure.

The second study, led by Professor Nigel Bundred of Manchester University, reported that use of two drugs that act on the same breast cancer target, an over-expressing protein called Her-2, were able to eradicate detectable tumours in around 10% of those treated in just 11 days, with 87% of those treated having a proteomic change indicating cells had stopped growing and/or cell death had increased2.

Whilst these results appear very promising it is worth noting that the over-expressing Her-2 target is only present in about 20% of breast tumours meaning this combination therapy was successful in clearing tumours in just 2% of the total breast cancer population.

Dr. Ian Pike, Chief Operating Officer of Proteome Sciences commented, “Both these recent studies should rightly be recognised as important steps forward towards better cancer treatment. However, in order to overcome the limitations of current drug therapy programs, a much deeper and more comprehensive analysis of the complex protein networks that regulate tumour growth and survival is required and will be essential to achieve a major advance in the battle to treat cancer.

“Our SysQuant® workflows provide that solution. As an example, in pancreatic cancer3 we have successfully mapped the complex network of regulatory processes and demonstrate the ability to devise personalised treatment combinations on an individual basis for each patient. A retrospective study with SysQuant® to predict response to the targeted drug Sorafenib in liver cancer is in process and we are planning further prospective trials to guide personalised treatment selection in liver cancer.

“We are already delivering systems-wide biology solutions through SysQuant® and TMTcalibrator™ programs to our clients that are generating novel biological data and results using more sensitive profiling that are helping them to better understand their drug development programs and to provide new biomarkers for tracking patient response in clinical trials.

“We are strongly positioned to deliver more comprehensive analysis of proteins and cellular pathways across other areas of disease and in particular to extend the use of SysQuant® with other leading cancer research groups in liver and other cancers.”

Proteome Sciences has also expanded its offering in personalised medicine through the use of its TMTcalibrator™ technology to uniquely identify protein biomarkers that reveal active cancer and other disease processes in body fluid samples. The importance of these ‘mechanistic’ biomarkers is that they are essential to monitor that drugs are being effective and that they can be used as early biomarkers of disease recurrence.

Using SysQuant® and TMTcalibrator™, Proteome Sciences can deliver more comprehensive analysis and provide unparalleled levels of sensitivity and breadth of coverage of the proteome, enabling faster, more efficient drug development and more accurate disease diagnosis.


Discovering ‘Outlier’ Enzymes

Researchers at TSRI and Salk Institute have discovered ‘Outlier’ enzymes that could offer new targets to treat type 2 diabetes and inflammatory disorders.

A team led by scientists at The Scripps Research Institute (TSRI) and the Salk Institute for Biological Studies have discovered two enzymes that appear to play a role in metabolism and inflammation—and might someday be targeted with drugs to treat type 2 diabetes and inflammatory disorders. The discovery is unusual because the enzymes do not bear a resemblance—in their structures or amino-acid sequences—to any known class of enzymes.

The team of scientists nevertheless identified them as “outlier” members of the serine/threonine hydrolase class, using newer techniques that detect biochemical activity. “A huge fraction of the human ‘proteome’ remains uncharacterized, and this paper shows how chemical approaches can be used to uncover proteins of a given functionality that have eluded classification based on sequence or predicted structure,” said co-senior author Benjamin F. Cravatt, chair of TSRI’s Department of Chemical Physiology.

“In this study, we found two genes that control levels of lipids with anti-diabetic and anti-inflammatory activity, suggesting exciting targets for diabetes and inflammatory diseases,” said co-senior author Alan Saghatelian, who holds the Dr. Frederik Paulsen Chair at the Salk Institute. The study, which appeared as a Nature Chemical Biology Advance Online Publication on March 28, 2016, began as an effort in the Cravatt laboratory to discover and characterize new serine/threonine hydrolases using fluorophosphonate (FP) probes—molecules that selectively bind and, in effect, label the active sites of these enzymes.

Pulling FP-binding proteins out of the entire proteome of test cells and identifying them using mass spectrometry techniques, the team matched nearly all to known hydrolases. The major outlier was a protein called androgen-induced gene 1 protein (AIG1). The only other one was a distant cousin in terms of sequence, a protein called ADTRP. “Neither of these proteins had been characterized as an enzyme; in fact, there had been little functional characterization of them at all,” said William H. Parsons, a research associate in the Cravatt laboratory who was co-first author of the study.

Experiments on AIG1 and ADTRP revealed that they do their enzymatic work in a unique way. “It looks like they have an active site that is novel—it had never been described in the literature,” said Parsons. Initial tests with panels of different enzyme inhibitors showed that AIG1 and ADTRP are moderately inhibited by inhibitors of lipases—enzymes that break down fats and other lipids. But on what specific lipids do these newly discovered outlier enzymes normally work?

At the Salk Institute, the Saghatelian laboratory was investigating a class of lipids it had discovered in 2014. Known as fatty acid esters of hydroxy fatty acids (FAHFAs), these molecules showed strong therapeutic potential. Saghatelian and his colleagues had found that boosting the levels of one key FAHFA lipid normalizes glucose levels in diabetic mice and also reduces inflammation.

“[Ben Cravatt’s] lab was screening panels of lipids to find the ones that their new enzymes work on,” said Saghatelian, who is a former research associate in the Cravatt laboratory. “We suggested they throw FAHFAs in there—and these turned out to be very good substrates.” The Cravatt laboratory soon developed powerful inhibitors of the newly discovered enzymes, and the two labs began working together, using the inhibitors and genetic techniques to explore the enzymes’ functions in vitro and in cultured cells.

Co-first author Matthew J. Kolar, an MD-PhD student, performed most of the experiments in the Saghatelian lab. The team concluded that AIG1 and ADTRP, at least in the cell types tested, appear to work mainly to break down FAHFAs and not any other major class of lipid. In principle, inhibitors of AIG1 and ADTRP could be developed into FAHFA-boosting therapies.

“Our prediction,” said Saghatelian, “is that if FAHFAs do what we think they’re doing, then using an enzyme inhibitor to block their degradation would make FAHFA levels go up and should thus reduce inflammation as well as improve glucose levels and insulin sensitivity.” The two labs are now collaborating on further studies of the new enzymes—and the potential benefits of inhibiting them—in mouse models of diabetes, inflammation and autoimmune disease.

“One of the neat things this study shows,” said Cravatt, “is that even for enzyme classes as well studied as the hydrolases, there may still be hidden members that, presumably by convergent evolution, arrived at that basic enzyme mechanism despite sharing no sequence or structural homology.”

Other co-authors of the study, “AIG1 and ADTRP are atypical integral membrane hydrolases that degrade bioactive FAHFAs,” were Siddhesh S. Kamat, Armand B. Cognetta III, Jonathan J. Hulce and Enrique Saez, of TSRI; and co-senior author Barbara B. Kahn of Beth Israel Deaconess Medical Center and Harvard Medical School


New Weapon Against Breast Cancer

Molecular marker in healthy tissue can predict a woman’s risk of getting the disease, research says.

Harvard Stem Cell Institute (HSCI) researchers at Dana-Farber Cancer Institute (DFCI) and collaborators at Brigham and Women’s Hospital (BWH) have identified a molecular marker in normal breast tissue that can predict a woman’s risk for developing breast cancer, the leading cause of death in women with cancer worldwide.

The work, led by HSCI principal faculty member Kornelia Polyak and Rulla Tamimi of BWH, was published in an early online release and in the April 1 issue of Cancer Research.

The study builds on Polyak’s earlier research finding that women already identified as having a high risk of developing cancer — namely those with a mutation called BRCA1 or BRCA2 — or women who did not give birth before their 30s had a higher number of mammary gland progenitor cells.

In the latest study, Polyak, Tamimi, and their colleagues examined biopsies, some taken as many as four decades ago, from 302 participants in the Nurses’ Health Study and the Nurses’ Health Study II who had been diagnosed with benign breast disease. The researchers compared tissue from the 69 women who later developed cancer to the tissue from the 233 women who did not. They found that women were five times as likely to develop cancer if they had a higher percentage of Ki67, a molecular marker that identifies proliferating cells, in the cells that line the mammary ducts and milk-producing lobules. These cells, called the mammary epithelium, undergo drastic changes throughout a woman’s life, and the majority of breast cancers originate in these tissues.

Doctors already test breast tumors for Ki67 levels, which can inform decisions about treatment, but this is the first time scientists have been able to link Ki67 to precancerous tissue and use it as a predictive tool.

“Instead of only telling women that they don’t have cancer, we could test the biopsies and tell women if they were at high risk or low risk for developing breast cancer in the future,” said Polyak, a breast cancer researcher at Dana-Farber and co-senior author of the paper.

“Currently, we are not able to do a very good job at distinguishing women at high and low risk of breast cancer,” added co-senior author Tamimi, an associate professor at the Harvard T.H. Chan School of Public Health and Harvard Medical School. “By identifying women at high risk of breast cancer, we can better develop individualized screening and also target risk reducing strategies.”

To date, mammograms are the best tool for the early detection, but there are risks associated with screening. False positive and negative results and over-diagnosis could cause psychological distress, delay treatment, or lead to overtreatment, according to the National Cancer Institute (NCI).

Mammography machines also use low doses of radiation. While a single mammogram is unlikely to cause harm, repeated screening can potentially cause cancer, though the NCI writes that the benefits “nearly always outweigh the risks.”

“If we can minimize unnecessary radiation for women at low risk, that would be good,” said Tamimi.

Screening for Ki67 levels would “be easy to apply in the current setting,” said Polyak, though the researchers first want to reproduce the results in an independent cohort of women.


AIG1 and ADTRP are atypical integral membrane hydrolases that degrade bioactive FAHFAs

William H ParsonsMatthew J Kolar, …., Barbara B KahnAlan Saghatelian & Benjamin F Cravatt

Nature Chemical Biology 28 March 2016          

Enzyme classes may contain outlier members that share mechanistic, but not sequence or structural, relatedness with more common representatives. The functional annotation of such exceptional proteins can be challenging. Here, we use activity-based profiling to discover that the poorly characterized multipass transmembrane proteins AIG1 and ADTRP are atypical hydrolytic enzymes that depend on conserved threonine and histidine residues for catalysis. Both AIG1 and ADTRP hydrolyze bioactive fatty acid esters of hydroxy fatty acids (FAHFAs) but not other major classes of lipids. We identify multiple cell-active, covalent inhibitors of AIG1 and show that these agents block FAHFA hydrolysis in mammalian cells. These results indicate that AIG1 and ADTRP are founding members of an evolutionarily conserved class of transmembrane threonine hydrolases involved in bioactive lipid metabolism. More generally, our findings demonstrate how chemical proteomics can excavate potential cases of convergent or parallel protein evolution that defy conventional sequence- and structure-based predictions.

Figure 1: Discovery and characterization of AIG1 and ADTRP as FP-reactive proteins in the human proteome.

(a) Competitive ABPP-SILAC analysis to identify FP-alkyne-inhibited proteins, in which protein enrichment and inhibition were measured in proteomic lysates from SKOV3 cells treated with FP-alkyne (20 μM, 1 h) or DMSO using the FP-biotin…


  1. Willems, L.I., Overkleeft, H.S. & van Kasteren, S.I. Current developments in activity-based protein profiling. Bioconjug. Chem. 25, 11811191 (2014).
  2. Niphakis, M.J. & Cravatt, B.F. Enzyme inhibitor discovery by activity-based protein profiling.Annu. Rev. Biochem. 83, 341377 (2014).
  3. Berger, A.B., Vitorino, P.M. & Bogyo, M. Activity-based protein profiling: applications to biomarker discovery, in vivo imaging and drug discovery. Am. J. Pharmacogenomics 4,371381 (2004).
  4. Liu, Y., Patricelli, M.P. & Cravatt, B.F. Activity-based protein profiling: the serine hydrolases.Proc. Natl. Acad. Sci. USA 96, 1469414699 (1999).
  5. Simon, G.M. & Cravatt, B.F. Activity-based proteomics of enzyme superfamilies: serine hydrolases as a case study. J. Biol. Chem. 285, 1105111055 (2010).
  6. Bachovchin, D.A. et al. Superfamily-wide portrait of serine hydrolase inhibition achieved by library-versus-library screening. Proc. Natl. Acad. Sci. USA 107, 2094120946 (2010).
  7. Jessani, N. et al. A streamlined platform for high-content functional proteomics of primary human specimens. Nat. Methods 2, 691697 (2005).
  8. Higa, H.H., Diaz, S. & Varki, A. Biochemical and genetic evidence for distinct membrane-bound and cytosolic sialic acid O-acetyl-esterases: serine-active-site enzymes. Biochem. Biophys. Res. Commun. 144, 10991108 (1987).

Academic cross-fertilization by public screening yields a remarkable class of protein phosphatase methylesteras-1 inhibitors

Proc Natl Acad Sci U S A. 2011 Apr 26; 108(17): 6811–6816.    doi:  10.1073/pnas.1015248108
National Institutes of Health (NIH)-sponsored screening centers provide academic researchers with a special opportunity to pursue small-molecule probes for protein targets that are outside the current interest of, or beyond the standard technologies employed by, the pharmaceutical industry. Here, we describe the outcome of an inhibitor screen for one such target, the enzyme protein phosphatase methylesterase-1 (PME-1), which regulates the methylesterification state of protein phosphatase 2A (PP2A) and is implicated in cancer and neurodegeneration. Inhibitors of PME-1 have not yet been described, which we attribute, at least in part, to a dearth of substrate assays compatible with high-throughput screening. We show that PME-1 is assayable by fluorescence polarization-activity-based protein profiling (fluopol-ABPP) and use this platform to screen the 300,000+ member NIH small-molecule library. This screen identified an unusual class of compounds, the aza-β-lactams (ABLs), as potent (IC50 values of approximately 10 nM), covalent PME-1 inhibitors. Interestingly, ABLs did not derive from a commercial vendor but rather an academic contribution to the public library. We show using competitive-ABPP that ABLs are exquisitely selective for PME-1 in living cells and mice, where enzyme inactivation leads to substantial reductions in demethylated PP2A. In summary, we have combined advanced synthetic and chemoproteomic methods to discover a class of ABL inhibitors that can be used to selectively perturb PME-1 activity in diverse biological systems. More generally, these results illustrate how public screening centers can serve as hubs to create spontaneous collaborative opportunities between synthetic chemistry and chemical biology labs interested in creating first-in-class pharmacological probes for challenging protein targets.

Protein phosphorylation is a pervasive and dynamic posttranslational protein modification in eukaryotic cells. In mammals, more than 500 protein kinases catalyze the phosphorylation of serine, threonine, and tyrosine residues on proteins (1). A much more limited number of phosphatases are responsible for reversing these phosphorylation events (2). For instance, protein phosphatase 2A (PP2A) and PP1 are thought to be responsible together for > 90% of the total serine/threonine phosphatase activity in mammalian cells (3). Specificity is imparted on PP2A activity by multiple mechanisms, including dynamic interactions between the catalytic subunit (C) and different protein-binding partners (B subunits), as well as a variety of posttranslational chemical modifications (2, 4). Within the latter category is an unusual methylesterification event found at the C terminus of the catalytic subunit of PP2A that is introduced and removed by a specific methyltransferase (leucine carbxoylmethyltransferase-1 or LCMT1) (5, 6) and methylesterase (protein phosphatase methylesterase-1 or PME-1) (7), respectively (Fig. 1A). PP2A carboxymethylation (hereafter referred to as “methylation”) has been proposed to regulate PP2A activity, at least in part, by modulating the binding interaction of the C subunit with various regulatory B subunits (810). A predicted outcome of these shifts in subunit association is the targeting of PP2A to different protein substrates in cells. PME-1 has also been hypothesized to stabilize inactive forms of nuclear PP2A (11), and recent structural studies have shed light on the physical interactions between PME-1 and the PP2A holoenzyme (12).

There were several keys to the success of our probe development effort. First, screening for inhibitors of PME-1 benefited from the fluopol-ABPP technology, which circumvented the limited throughput of previously described substrate assays for this enzyme. Second, we were fortunate that the NIH compound library contained several members of the ABL class of small molecules. These chiral compounds, which represent an academic contribution to the NIH library, occupy an unusual portion of structural space that is poorly accessed by commercial compound collections. Although at the time of their original synthesis (23) it may not have been possible to predict whether these ABLs would show specific biological activity, their incorporation into the NIH library provided a forum for screening against many proteins and cellular targets, culminating in their identification as PME-1 inhibitors. We then used advanced chemoproteomic assays to confirm the remarkable selectivity displayed by ABLs for PME-1 across (and beyond) the serine hydrolase superfamily. That the mechanism for PME-1 inhibition involves acylation of the enzyme’s conserved serine nucleophile (Fig. 3) suggests that exploration of a more structurally diverse set of ABLs might uncover inhibitors for other serine hydrolases. In this way, the chemical information gained from a single high-throughput screen may be leveraged to initiate probe development programs for additional enzyme targets.

Projecting forward, this research provides an example of how public small-molecule screening centers can serve as a portal for spawning academic collaborations between chemical biology and synthetic chemistry labs. By continuing to develop versatile high-throughput screens and combining them with a small-molecule library of expanding structural diversity conferred by advanced synthetic methodologies, academic biologists and chemists are well-positioned to collaboratively deliver pharmacological probes for a wide range of proteins and pathways in cell biology.


New weapon against breast cancer

Molecular marker in healthy tissue can predict a woman’s risk of getting the disease, research says

April 6, 2016 | Popular


New Group of Aging-Related Proteins Discovered

Scientists have discovered a group of six proteins that may help to divulge secrets of how we age, potentially unlocking new insights into diabetes, Alzheimer’s, cancer, and other aging-related diseases.

The proteins appear to play several roles in our bodies’ cells, from decreasing the amount of damaging free radicals and controlling the rate at which cells die to boosting metabolism and helping tissues throughout the body respond better to insulin. The naturally occurring amounts of each protein decrease with age, leading investigators to believe that they play an important role in the aging process and the onset of diseases linked to older age.

The research team led by Pinchas Cohen, M.D., dean and professor of the University of Southern California Leonard Davis School of Gerontology, identified the proteins and observed their origin from mitochondria and their game-changing roles in metabolism and cell survival. This latest finding builds upon prior research by Dr. Cohen and his team that uncovered two significant proteins, humanin and MOTS-c, hormones that appear to have significant roles in metabolism and diseases of aging.

Unlike most other proteins, humanin and MOTS-c are encoded in mitochondria. Dr. Cohen’s team used computer analysis to see if the part of the mitochondrial genome that provides the code for humanin was coding for other proteins as well. The analysis uncovered the genes for six new proteins, which were dubbed small humanin-like peptides, or SHLPs, 1 through 6 (pronounced “schlep”).

After identifying the six SHLPs and successfully developing antibodies to test for several of them, the team examined both mouse tissues and human cells to determine their abundance in different organs as well as their functions. The proteins were distributed quite differently among organs, which suggests that the proteins have varying functions based on where they are in the body. Of particular interest is SHLP 2, according to Dr. Cohen.  The protein appears to have insulin-sensitizing, antidiabetic effects as well as neuroprotective activity that may emerge as a strategy to combat Alzheimer’s disease. He added that SHLP 6 is also intriguing, with a unique ability to promote cancer cell death and thus potentially target malignant diseases.

Proteins That May Protect Against Age Related Illnesses Discovered


The cell proliferation antigen Ki-67 organises heterochromatin

 Michal Sobecki, 

Antigen Ki-67 is a nuclear protein expressed in proliferating mammalian cells. It is widely used in cancer histopathology but its functions remain unclear. Here, we show that Ki-67 controls heterochromatin organisation. Altering Ki-67 expression levels did not significantly affect cell proliferation in vivo. Ki-67 mutant mice developed normally and cells lacking Ki-67 proliferated efficiently. Conversely, upregulation of Ki-67 expression in differentiated tissues did not prevent cell cycle arrest. Ki-67 interactors included proteins involved in nucleolar processes and chromatin regulators. Ki-67 depletion disrupted nucleologenesis but did not inhibit pre-rRNA processing. In contrast, it altered gene expression. Ki-67 silencing also had wide-ranging effects on chromatin organisation, disrupting heterochromatin compaction and long-range genomic interactions. Trimethylation of histone H3K9 and H4K20 was relocalised within the nucleus. Finally, overexpression of human or Xenopus Ki-67 induced ectopic heterochromatin formation. Altogether, our results suggest that Ki-67 expression in proliferating cells spatially organises heterochromatin, thereby controlling gene expression.


A protein called Ki-67 is only produced in actively dividing cells, where it is located in the nucleus – the structure that contains most of the cell’s DNA. Researchers often use Ki-67 as a marker to identify which cells are actively dividing in tissue samples from cancer patients, and previous studies indicated that Ki-67 is needed for cells to divide. However, the exact role of this protein was not clear. Before cells can divide they need to make large amounts of new proteins using molecular machines called ribosomes and it has been suggested that Ki-67 helps to produce ribosomes.

Now, Sobecki et al. used genetic techniques to study the role of Ki-67 in mice. The experiments show that Ki-67 is not required for cells to divide in the laboratory or to make ribosomes. Instead, Ki-67 alters the way that DNA is packaged in the nucleus. Loss of Ki-67 from mice cells resulted in DNA becoming less compact, which in turn altered the activity of genes in those cells.

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The Colors of Respiration and Electron Transport

Reporter & Curator: Larry H. Bernstein, MD, FCAP 



Molecular Biology of the Cell. 4th edition

Electron-Transport Chains and Their Proton Pumps

Having considered in general terms how a mitochondrion uses electron
transport to create an electrochemical proton gradient, we need to
examine the mechanisms that underlie this membrane-based energy-conversion process. In doing so, we also accomplish a larger purpose.
As emphasized at the beginning of this chapter, very similar chemi-
osmotic mechanisms are used by mitochondria, chloroplasts, archea,
and bacteria. In fact, these mechanisms underlie the function of nearly
all living organisms— including anaerobes that derive all their energy
from electron transfers between two inorganic molecules. It is therefore
rather humbling for scientists to remind themselves that the existence
of chemiosmosis has been recognized for only about 40 years.




Overview of The Electron Transport Chain

Overview of The Electron Transport Chain

We begin with a look at some of the principles that underlie the electron-transport process, with the aim of explaining how it can pump protons
across a membrane.

Although protons resemble other positive ions such as Na+ and K+
in their movement across membranes, in some respects they are unique.
Hydrogen atoms are by far the most abundant type of atom in living
organisms; they are plentiful not only in all carbon-containing
biological molecules, but also in the water molecules that surround
them. The protons in water are highly mobile, flickering through the
hydrogen-bonded network of water molecules by rapidly
dissociating from one water molecule to associate with its neighbor,
as illustrated in Figure 14-20A. Protons are thought to move across a
protein pump embedded in a lipid bilayer in a similar way: they
transfer from one amino acid side chain to another, following a
special channel through the protein.

Protons are also special with respect to electron transport. Whenever
a molecule is reduced by acquiring an electron, the electron (e -) brings
with it a negative charge. In many cases, this charge is rapidly
neutralized by the addition of a proton (H+) from water, so that
the net effect of the reduction is to transfer an entire hydrogen atom,
H+ + e – (Figure 14-20B). Similarly, when a molecule is oxidized,
a hydrogen atom removed from it can be readily dissociated into
its constituent electron and proton—allowing the electron to
be transferred separately to a molecule that accepts electrons,
while the proton is passed to the water. Therefore, in a membrane
in which electrons are being passed along an electron-transport
chain, pumping protons from one side of the membrane to
another can be relatively simple. The electron carrier merely
needs to be arranged in the membrane in a way that causes it to
pick up a proton from one side of the membrane when it accepts
an electron, and to release the proton on the other side of the
membrane as the electron is passed to the next carrier molecule
in the chain (Figure 14-21).

protons pumped across membranes ch14f21

protons pumped across membranes ch14f21

Figure 14-21

How protons can be pumped across membranes. As an electron
passes along an electron-transport chain embedded in a lipid-bilayer
membrane, it can bind and release a proton at each step.
In this diagram, electron carrier B picks up a proton (H+)
from one (more…)



The Redox Potential Is a Measure of Electron Affinities

In biochemical reactions, any electrons removed from one
molecule are always passed to another, so that whenever one
molecule is oxidized, another is reduced. Like any other chemical r
eaction, the tendency of such oxidation-reduction reactions, or
redox reactions, to proceed spontaneously depends on the free-
energy change (ΔG) for the electron transfer, which in turn
depends on the relative affinities of the two molecules for electrons.

Because electron transfers provide most of the energy for living
things, it is worth spending the time to understand them. Many
readers are already familiar with acids and bases, which donate
and accept protons (see Panel 2-2, pp. 112–113). Acids and bases
exist in conjugate acid-base pairs, in which the acid is readily
converted into the base by the loss of a proton. For example,
acetic acid (CH3COOH) is converted into its conjugate base
(CH3COO-) in the reaction:

Image ch14e3.jpg

In exactly the same way, pairs of compounds such as NADH and
NAD+ are called redox pairs, since NADH is converted to NAD+
by the loss of electrons in the reaction:

Image ch14e4.jpg



NADH is a strong electron donor: because its electrons are held
in a high-energy linkage, the free-energy change for passing its
electrons to many other molecules is favorable (see Figure 14-9).
It is difficult to form a high-energy linkage. Therefore its redox
partner, NAD+, is of necessity a weak electron acceptor.

The tendency to transfer electrons from any redox pair can be
measured experimentally. All that is required is the formation
of an electrical circuit linking a 1:1 (equimolar) mixture of the
redox pair to a second redox pair that has been arbitrarily selected
as a reference standard, so the voltage difference can be measured
between them (Panel 14-1, p. 784). This voltage difference is
defined as the redox potential; as defined, electrons move
spontaneously from a redox pair like NADH/NAD+ with a low
redox potential (a low affinity for electrons) to a redox pair like
O2/H2O with a high redox potential (a high affinity for electrons).
Thus, NADH is a good molecule for donating electrons to the
respiratory chain, while O2 is well suited to act as the “sink” for
electrons at the end of the pathway. As explained in Panel 14-1,
the difference in redox potential, ΔE0′, is a direct measure of
the standard free-energy change (ΔG°) for the transfer of an
electron from one molecule to another.

Proteins of inner space

Proteins of inner space



Box Icon

Panel 14-1

Redox Potentials.

Electron Transfers Release Large Amounts of Energy

As just discussed, those pairs of compounds that have the most negative
redox potentials have the weakest affinity for electrons and therefore
contain carriers with the strongest tendency to donate electrons.
Conversely, those pairs that have the most positive redox potentials
have the strongest affinity for electrons and therefore contain carriers
with the strongest tendency to accept electrons. A 1:1 mixture of NADH
and NAD+ has a redox potential of -320 mV, indicating that NADH has
a strong tendency to donate electrons; a 1:1 mixture of H2O and ½O2
has a redox potential of +820 mV, indicating that O2 has a strong
tendency to accept electrons. The difference in redox potential is
1.14 volts (1140 mV), which means that the transfer of each electron
from NADH to O2 under these standard conditions is enormously
favorable, where ΔG° = -26.2 kcal/mole (-52.4 kcal/mole for the two
electrons transferred per NADH molecule; see Panel 14-1). If we
compare this free-energy change with that for the formation of the
phosphoanhydride bonds in ATP (ΔG° = -7.3 kcal/mole, see Figure 2-75), we see that more than enough energy is released by the oxidization
of one NADH molecule to synthesize several molecules of ATP from
ADP and Pi.

 Phosphate dependence of pyruvate oxidation

Phosphate dependence of pyruvate oxidation

Living systems could certainly have evolved enzymes that would
allow NADH to donate electrons directly to O2 to make water in the reaction:

Image ch14e5.jpg

But because of the huge free-energy drop, this reaction would proceed
with almost explosive force and nearly all of the energy would be released
as heat. Cells do perform this reaction, but they make it proceed much
more gradually by passing the high-energy electrons from NADH to
O2 via the many electron carriers in the electron-transport chain.
Since each successive carrier in the chain holds its electrons more
tightly, the highly energetically favorable reaction 2H+ + 2e – + ½O2
→ H2O is made to occur in many small steps. This enables nearly half
of the released energy to be stored, instead of being lost to the
environment as heat.

Spectroscopic Methods Have Been Used to Identify Many Electron
Carriers in the Respiratory Chain

Many of the electron carriers in the respiratory chain absorb visible
light and change color when they are oxidized or reduced. In general,
each has an absorption spectrum and reactivity that are distinct enough
to allow its behavior to be traced spectroscopically, even in crude mixtures.
It was therefore possible to purify these components long before their
exact functions were known. Thus, the cytochromes were discovered
in 1925 as compounds that undergo rapid oxidation and reduction in
living organisms as disparate as bacteria, yeasts, and insects. By observing
cells and tissues with a spectroscope, three types of cytochromes were
identified by their distinctive absorption spectra and designated
cytochromes a, b, and c. This nomenclature has survived, even though
cells are now known to contain several cytochromes of each type and
the classification into types is not functionally important.

The cytochromes constitute a family of colored proteins that are
related by the presence of a bound heme group, whose iron atom
changes from the ferric oxidation state (Fe3+) to the ferrous oxidation
state (Fe2+) whenever it accepts an electron. The heme group consists
of a porphyrin ring with a tightly bound iron atom held by four nitrogen
atoms at the corners of a square (Figure 14-22). A similar porphyrin ring
is responsible for the red color of blood and for the green color of
leaves, being bound to iron in hemoglobin and to magnesium in
chlorophyll, respectively.

The structure of the heme group attached covalently to cytochrome c ch14f22

The structure of the heme group attached covalently to cytochrome c ch14f22

Figure 14-22. The structure of the heme group attached covalently
to cytochrome c.

Figure 14-22

The structure of the heme group attached covalently to cytochrome c.
The porphyrin ring is shown in blue. There are five different
cytochromes in the respiratory chain. Because the hemes in different
cytochromes have slightly different structures and (more…)

Iron-sulfur proteins are a second major family of electron carriers. In these
proteins, either two or four iron atoms are bound to an equal number of
sulfur atoms and to cysteine side chains, forming an iron-sulfur center
on the protein (Figure 14-23). There are more iron-sulfur centers than
cytochromes in the respiratory chain. But their spectroscopic detection
requires electron spin resonance (ESR) spectroscopy, and they are less
completely characterized. Like the cytochromes, these centers carry one
electron at a time.

structure of iron sulfur centers ch14f23

structure of iron sulfur centers ch14f23

Figure 14-23. The structures of two types of iron-sulfur centers.

Figure 14-23

The structures of two types of iron-sulfur centers. (A) A center of the
2Fe2S type. (B) A center of the 4Fe4S type. Although they contain
multiple iron atoms, each iron-sulfur center can carry only one
electron at a time. There are more than seven different (more…)

The simplest of the electron carriers in the respiratory chain—and
the only one that is not part of a protein—is a small hydrophobic
molecule that is freely mobile in the lipid bilayer known as ubiquinone,
or coenzyme Q. A quinone (Q) can pick up or donate either one or
two electrons; upon reduction, it picks up a proton from the medium
along with each electron it carries (Figure 14-24).

quinone electron carriers ch14f24

quinone electron carriers ch14f24

Figure 14-24. Quinone electron carriers.

Figure 14-24

Quinone electron carriers. Ubiquinone in the respiratory chain picks
up one H+ from the aqueous environment for every electron it accepts,
and it can carry either one or two electrons as part of a hydrogen atom
(yellow). When reduced ubiquinone donates (more…)

In addition to six different hemes linked to cytochromes, more than
seven iron-sulfur centers, and ubiquinone, there are also two copper
atoms and a flavin serving as electron carriers tightly bound to respiratory-chain proteins in the pathway from NADH to oxygen. This pathway
involves more than 60 different proteins in all.

As one would expect, the electron carriers have higher and higher
affinities for electrons (greater redox potentials) as one moves along
the respiratory chain. The redox potentials have been fine-tuned
during evolution by the binding of each electron carrier in a particular
protein context, which can alter its normal affinity for electrons. However,
because iron-sulfur centers have a relatively low affinity for electrons,
they predominate in the early part of the respiratory chain; in contrast,
the cytochromes predominate further down the chain, where a higher
affinity for electrons is required.

The order of the individual electron carriers in the chain was
determined by sophisticated spectroscopic measurements (Figure 14-25),
and many of the proteins were initially isolated and characterized as
individual polypeptides. A major advance in understanding the
respiratory chain, however, was the later realization that most of
the proteins are organized into three large enzyme complexes.

path of electrons ch14f25

path of electrons ch14f25

Figure 14-25. The general methods used to determine the path of
electrons along an electron-transport chain.

Figure 14-25

The general methods used to determine the path of electrons along
an electron-transport chain. The extent of oxidation of electron
carriers a, b, c, and d is continuously monitored by following their
distinct spectra, which differ in their oxidized and (more…)

The Respiratory Chain Includes Three Large Enzyme Complexes
Embedded in the Inner Membrane

Membrane proteins are difficult to purify as intact complexes
because they are insoluble in aqueous solutions, and some of
the detergents required to solubilize them can destroy normal
protein-protein interactions. In the early 1960s, however, it
was found that relatively mild ionic detergents, such as deoxycholate,
can solubilize selected components of the inner mitochondrial
membrane in their native form. This permitted the identification
and purification of the three major membrane-bound respiratory
enzyme complexes in the pathway from NADH to oxygen (Figure 14-26).
As we shall see in this section, each of these complexes acts as an
electron-transport-driven H+ pump; however, they were
initially characterized in terms of the electron carriers that
they interact with and contain:

mitochondrial oxidative phosphorylation

mitochondrial oxidative phosphorylation

Figure 14-26. The path of electrons through the three respiratory
enzyme complexes.

Figure 14-26

The path of electrons through the three respiratory enzyme complexes.
The relative size and shape of each complex are shown. During the
transfer of electrons from NADH to oxygen (red lines), ubiquinone
and cytochrome c serve as mobile carriers that ferry (more…)

The NADH dehydrogenase complex (generally known as complex I)
is the largest of the respiratory enzyme complexes, containing more
than 40 polypeptide chains. It accepts electrons from NADH and
passes them through a flavin and at least seven iron-sulfur centers
to ubiquinone. Ubiquinone then transfers its electrons to a second
respiratory enzyme complex, the cytochrome b-c1 complex.

The cytochrome b-c1 complex contains at least 11 different
polypeptide chains and functions as a dimer. Each monomer
contains three hemes bound to cytochromes and an iron-sulfur
protein. The complex accepts electrons from ubiquinone
and passes them on to cytochrome c, which carries its electron
to the cytochrome oxidase complex.

The cytochrome oxidase complex also functions as a dimer; each
monomer contains 13 different polypeptide chains, including two
cytochromes and two copper atoms. The complex accepts one electron
at a time from cytochrome c and passes them four at a time to oxygen.

The cytochromes, iron-sulfur centers, and copper atoms can carry
only one electron at a time. Yet each NADH donates two electrons,
and each O2 molecule must receive four electrons to produce water.
There are several electron-collecting and electron-dispersing points
along the electron-transport chain where these changes in electron
number are accommodated. The most obvious of these is cytochrome

An Iron-Copper Center in Cytochrome Oxidase Catalyzes Efficient
O2 Reduction

Because oxygen has a high affinity for electrons, it releases a
large amount of free energy when it is reduced to form water.
Thus, the evolution of cellular respiration, in which O2 is
converted to water, enabled organisms to harness much more
energy than can be derived from anaerobic metabolism. This
is presumably why all higher organisms respire. The ability of
biological systems to use O2 in this way, however, requires a
very sophisticated chemistry. We can tolerate O2 in the air we
breathe because it has trouble picking up its first electron; this
fact allows its initial reaction in cells to be controlled closely by
enzymatic catalysis. But once a molecule of O2 has picked up one
electron to form a superoxide radical (O2 -), it becomes dangerously
reactive and rapidly takes up an additional three electrons wherever
it can find them. The cell can use O2 for respiration only because
cytochrome oxidase holds onto oxygen at a special bimetallic
center, where it remains clamped between a heme-linked iron
atom and a copper atom until it has picked up a total of four electrons.
Only then can the two oxygen atoms of the oxygen molecule be
safely released as two molecules of water (Figure 14-27).

Figure 14-27. The reaction of O2 with electrons in cytochrome oxidase.

Figure 14-27

The reaction of O2 with electrons in cytochrome oxidase. As indicated,
the iron atom in heme a serves as an electron queuing point; this
heme feeds four electrons into an O2 molecule held at the bimetallic
center active site, which is formed by the other (more…)

The cytochrome oxidase reaction is estimated to account for 90%
of the total oxygen uptake in most cells. This protein complex is
therefore crucial for all aerobic life. Cyanide and azide are extremely
toxic because they bind tightly to the cell’s cytochrome oxidase
complexes to stop electron transport, thereby greatly reducing
ATP production.

Although the cytochrome oxidase in mammals contains 13
different protein subunits, most of these seem to have a subsidiary
role, helping to regulate either the activity or the assembly of the
three subunits that form the core of the enzyme. The complete
structure of this large enzyme complex has recently been determined
by x-ray crystallography, as illustrated in Figure 14-28. The atomic
resolution structures, combined with mechanistic studies of the effect
of precisely tailored mutations introduced into the enzyme by genetic
engineering of the yeast and bacterial proteins, are revealing the
detailed mechanisms of this finely tuned protein machine.

Figure 14-28. The molecular structure of cytochrome oxidase.

Figure 14-28

The molecular structure of cytochrome oxidase. This protein
is a dimer formed from a monomer with 13 different protein
subunits (monomer mass of 204,000 daltons). The three colored
subunits are encoded by the mitochondrial genome, and they
form the functional (more…)

Electron Transfers Are Mediated by Random Collisions in
the Inner Mitochondrial Membrane

The two components that carry electrons between the three
major enzyme complexes of the respiratory chain—ubiquinone
and cytochrome c—diffuse rapidly in the plane of the inner
mitochondrial membrane. The expected rate of random collisions
between these mobile carriers and the more slowly diffusing
enzyme complexes can account for the observed rates of electron
transfer (each complex donates and receives an electron about
once every 5–20 milliseconds). Thus, there is no need to postulate
a structurally ordered chain of electron-transfer proteins in the
lipid bilayer; indeed, the three enzyme complexes seem to exist as
independent entities in the plane of the inner membrane, being
present in different ratios in different mitochondria.

The ordered transfer of electrons along the respiratory chain
is due entirely to the specificity of the functional interactions
between the components of the chain: each electron carrier is
able to interact only with the carrier adjacent to it in the sequence
shown in Figure 14-26, with no short circuits.

Electrons move between the molecules that carry them in
biological systems not only by moving along covalent bonds
within a molecule, but also by jumping across a gap as large
as 2 nm. The jumps occur by electron “tunneling,” a quantum-
mechanical property that is critical for the processes we are
discussing. Insulation is needed to prevent short circuits that
would otherwise occur when an electron carrier with a low redox
potential collides with a carrier with a high redox potential. This
insulation seems to be provided by carrying an electron deep
enough inside a protein to prevent its tunneling interactions
with an inappropriate partner.

How the changes in redox potential from one electron carrier
to the next are harnessed to pump protons out of the mitochondrial
matrix is the topic we discuss next.

A Large Drop in Redox Potential Across Each of the Three Respiratory
Enzyme Complexes Provides the Energy for H+ Pumping

We have previously discussed how the redox potential reflects
electron affinities (see p. 783). An outline of the redox potentials
measured along the respiratory chain is shown in Figure 14-29.
These potentials drop in three large steps, one across each major
respiratory complex. The change in redox potential between any
two electron carriers is directly proportional to the free energy
released when an electron transfers between them. Each enzyme
complex acts as an energy-conversion device by harnessing some
of this free-energy change to pump H+ across the inner membrane,
thereby creating an electrochemical proton gradient as electrons
pass through that complex. This conversion can be demonstrated
by purifying each respiratory enzyme complex and incorporating
it separately into liposomes: when an appropriate electron donor
and acceptor are added so that electrons can pass through the complex,
H+ is translocated across the liposome membrane.

Figure 14-29. Redox potential changes along the mitochondrial
electron-transport chain.

Figure 14-29

Redox potential changes along the mitochondrial electron-transport
chain. The redox potential (designated E′0) increases as electrons
flow down the respiratory chain to oxygen. The standard free-energy
change, ΔG°, for the transfer (more…)

The Mechanism of H+ Pumping Will Soon Be Understood in
Atomic Detail

Some respiratory enzyme complexes pump one H+ per electron
across the inner mitochondrial membrane, whereas others pump
two. The detailed mechanism by which electron transport is coupled
to H+ pumping is different for the three different enzyme complexes.
In the cytochrome b-c1 complex, the quinones clearly have a role.
As mentioned previously, a quinone picks up a H+ from the aqueous
medium along with each electron it carries and liberates it when it
releases the electron (see Figure 14-24). Since ubiquinone is freely
mobile in the lipid bilayer, it could accept electrons near the inside
surface of the membrane and donate them to the cytochrome b-c1
complex near the outside surface, thereby transferring one H+
across the bilayer for every electron transported. Two protons are
pumped per electron in the cytochrome b-c1 complex, however, and
there is good evidence for a so-called Q-cycle, in which ubiquinone
is recycled through the complex in an ordered way that makes this
two-for-one transfer possible. Exactly how this occurs can now be
worked out at the atomic level, because the complete structure of
the cytochrome b-c1 complex has been determined by x-ray
crystallography (Figure 14-30).

Figure 14-30. The atomic structure of cytochrome b-c 1.

Figure 14-30

The atomic structure of cytochrome b-c 1. This protein is a dimer.
The 240,000-dalton monomer is composed of 11 different protein
molecules in mammals. The three colored proteins form the
functional core of the enzyme: cytochrome b (green), cytochrome (more…)

Allosteric changes in protein conformations driven by electron
transport can also pump H+, just as H+ is pumped when ATP
is hydrolyzed by the ATP synthase running in reverse. For both the
NADH dehydrogenase complex and the cytochrome oxidase complex,
it seems likely that electron transport drives sequential allosteric
changes in protein conformation that cause a portion of the protein
to pump H+ across the mitochondrial inner membrane. A general
mechanism for this type of H+ pumping is presented in Figure 14-31.

Figure 14-31. A general model for H+ pumping.

Figure 14-31

A general model for H+ pumping. This model for H+ pumping
by a transmembrane protein is based on mechanisms that are
thought to be used by both cytochrome oxidase and the light-driven
procaryotic proton pump, bacteriorhodopsin. The protein
is driven through (more…)

H+ Ionophores Uncouple Electron Transport from ATP Synthesis

Since the 1940s, several substances—such as 2,4-dinitrophenol—
have been known to act as uncoupling agents, uncoupling electron
transport from ATP synthesis. The addition of these low-molecular-weight organic compounds to cells stops ATP synthesis by mitochondria
without blocking their uptake of oxygen. In the presence of an
uncoupling agent, electron transport and H+ pumping continue at
a rapid rate, but no H+ gradient is generated. The explanation for
this effect is both simple and elegant: uncoupling agents are lipid-
soluble weak acids that act as H+ carriers (H+ ionophores), and
they provide a pathway for the flow of H+ across the inner mitochondrial
membrane that bypasses the ATP synthase. As a result of this short-
circuiting, the proton-motive force is dissipated completely, and
ATP can no longer be made.

Respiratory Control Normally Restrains Electron Flow
Through the Chain

When an uncoupler such as dinitrophenol is added to cells,
mitochondria increase their oxygen uptake substantially because
of an increased rate of electron transport. This increase reflects
the existence of respiratory control. The control is thought to
act via a direct inhibitory influence of the electrochemical proton
gradient on the rate of electron transport. When the gradient is
collapsed by an uncoupler, electron transport is free to run unchecked
at the maximal rate. As the gradient increases, electron transport
becomes more difficult, and the process slows. Moreover, if an
artificially large electrochemical proton gradient is experimentally
created across the inner membrane, normal electron transport
stops completely, and a reverse electron flow can be detected in
some sections of the respiratory chain. This observation suggests
that respiratory control reflects a simple balance between the
free-energy change for electron-transport-linked proton pumping
and the free-energy change for electron transport—that is, the
magnitude of the electrochemical proton gradient affects both
the rate and the direction of electron transport, just as it affects
the directionality of the ATP synthase (see Figure 14-19).

Respiratory control is just one part of an elaborate interlocking
system of feedback controls that coordinate the rates of glycolysis,
fatty acid breakdown, the citric acid cycle, and electron transport.
The rates of all of these processes are adjusted to the ATP:ADP ratio,
increasing whenever an increased utilization of ATP causes the ratio
to fall. The ATP synthase in the inner mitochondrial membrane,
for example, works faster as the concentrations of its substrates
ADP and Pi increase. As it speeds up, the enzyme lets more H+ flow
into the matrix and thereby dissipates the electrochemical proton
gradient more rapidly. The falling gradient, in turn, enhances the
rate of electron transport.

Similar controls, including feedback inhibition of several key enzymes
by ATP, act to adjust the rates of NADH production to the rate of
NADH utilization by the respiratory chain, and so on. As a result of
these many control mechanisms, the body oxidizes fats and sugars
5–10 times more rapidly during a period of strenuous exercise than
during a period of rest.

Natural Uncouplers Convert the Mitochondria in Brown Fat into
Heat-generating Machines

In some specialized fat cells, mitochondrial respiration is normally
uncoupled from ATP synthesis. In these cells, known as brown fat
cells, most of the energy of oxidation is dissipated as heat rather
than being converted into ATP. The inner membranes of the large
mitochondria in these cells contain a special transport protein that
allows protons to move down their electrochemical gradient, by-
passing ATP synthase. As a result, the cells oxidize their fat stores
at a rapid rate and produce more heat than ATP. Tissues containing
brown fat serve as “heating pads,” helping to revive hibernating animals
and to protect sensitive areas of newborn human babies from the cold.

Bacteria Also Exploit Chemiosmotic Mechanisms to Harness Energy

Bacteria use enormously diverse energy sources. Some, like animal
cells, are aerobic; they synthesize ATP from sugars they oxidize to
CO2 and H2O by glycolysis, the citric acid cycle, and a respiratory
chain in their plasma membrane that is similar to the one in the
inner mitochondrial membrane. Others are strict anaerobes, deriving
their energy either from glycolysis alone (by fermentation) or from an
electron-transport chain that employs a molecule other than oxygen
as the final electron acceptor. The alternative electron acceptor can
be a nitrogen compound (nitrate or nitrite), a sulfur compound
(sulfate or sulfite), or a carbon compound (fumarate or carbonate),
for example. The electrons are transferred to these acceptors by a
series of electron carriers in the plasma membrane that are comparable
to those in mitochondrial respiratory chains.

Despite this diversity, the plasma membrane of the vast majority of
bacteria contains an ATP synthase that is very similar to the one in
mitochondria. In bacteria that use an electron-transport chain to
harvest energy, the electron-transport pumps H+ out of the cell and
thereby establishes a proton-motive force across the plasma membrane
that drives the ATP synthase to make ATP. In other bacteria, the
ATP synthase works in reverse, using the ATP produced by glycolysis
to pump H+ and establish a proton gradient across the plasma
membrane. The ATP used for this process is generated by
fermentation processes (discussed in Chapter 2).

Thus, most bacteria, including the strict anaerobes, maintain a proton
gradient across their plasma membrane. It can be harnessed to drive
a flagellar motor, and it is used to pump Na+ out of the bacterium via
a Na+-H+ antiporter that takes the place of the Na+-K+ pump of
eucaryotic cells. This gradient is also used for the active inward transport
of nutrients, such as most amino acids and many sugars: each nutrient is
dragged into the cell along with one or more H+ through a specific symporter
(Figure 14-32). In animal cells, by contrast, most inward transport across
the plasma membrane is driven by the Na+ gradient that is established by the
Na+-K+ pump.

Figure 14-32. The importance of H+-driven transport in bacteria.

Figure 14-32

The importance of H+-driven transport in bacteria. A proton-motive force
generated across the plasma membrane pumps nutrients into the cell and
expels Na+. (A) In an aerobic bacterium, an electrochemical proton gradient
across the plasma membrane is produced (more…)

Some unusual bacteria have adapted to live in a very alkaline
environment and yet must maintain their cytoplasm at a physiological
pH. For these cells, any attempt to generate an electrochemical H+
gradient would be opposed by a large H+ concentration gradient in
the wrong direction (H+ higher inside than outside). Presumably for
this reason, some of these bacteria substitute Na+ for H+ in all of their
chemiosmotic mechanisms. The respiratory chain pumps Na+ out of
the cell, the transport systems and flagellar motor are driven by an
inward flux of Na+, and a Na+-driven ATP synthase synthesizes
ATP. The existence of such bacteria demonstrates that the principle
of chemiosmosis is more fundamental than the proton-motive force
on which it is normally based.


The respiratory chain in the inner mitochondrial membrane contains
three respiratory enzyme complexes through which electrons pass on
their way from NADH to O2.

Each of these can be purified, inserted into synthetic lipid vesicles,
and then shown to pump H+ when electrons are transported through it.
In the intact membrane, the mobile electron carriers ubiquinone and
cytochrome c complete the electron-transport chain by shuttling between
the enzyme complexes. The path of electron flow is NADH → NADH
dehydrogenase complex → ubiquinone → cytochrome b-c1 complex →
cytochrome c → cytochrome oxidase complex → molecular oxygen (O2).

The respiratory enzyme complexes couple the energetically favorable
transport of electrons to the pumping of H+ out of the matrix. The
resulting electrochemical proton gradient is harnessed to make ATP
by another transmembrane protein complex, ATP synthase, through
which H+ flows back into the matrix. The ATP synthase is a reversible
coupling device that normally converts a backflow of H+ into ATP
phosphate bond energy by catalyzing the reaction ADP + Pi → ATP,
but it can also work in the opposite direction and hydrolyze ATP to
pump H+ if the electrochemical proton gradient is sufficiently reduced.
Its universal presence in mitochondria, chloroplasts, and procaryotes
testifies to the central importance of chemiosmotic mechanisms in cells.

By agreement with the publisher, this book is accessible by the search
feature, but cannot be browsed.

Copyright © 2002, Bruce Alberts, Alexander Johnson, Julian Lewis,
Martin Raff, Keith Roberts, and Peter Walter; Copyright © 1983, 1989,
1994, Bruce Alberts, Dennis Bray, Julian Lewis, Martin Raff, Keith
Roberts, and James D. Watson .

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Summary of Proteomics

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


We have completed a series of discussions on proteomics, a scientific endeavor that is essentially 15 years old.   It is quite remarkable what has been accomplished in that time.  The interest is abetted by the understanding of the limitations of the genomic venture that has preceded it.  The thorough, yet incomplete knowledge of the genome, has led to the clarification of its limits.  It is the coding for all that lives, but all that lives has evolved to meet a demanding and changing environment with respect to

  1. availability of nutrients
  2. salinity
  3. temperature
  4. radiation exposure
  5. toxicities in the air, water, and food
  6. stresses – both internal and external

We have seen how both transcription and translation of the code results in a protein, lipoprotein, or other complex than the initial transcript that was modeled from tRNA. What you see in the DNA is not what you get in the functioning cell, organ, or organism.  There are comparabilities as well as significant differences between plants, prokaryotes, and eukaryotes.  There is extensive variation.  The variation goes beyond genomic expression, and includes the functioning cell, organ type, and species.

Here, I return to the introductory discussion.  Proteomics is a goal directed, sophisticated science that uses a combination of methods to find the answers to biological questions. Graves PR and Haystead TAJ.  Molecular Biologist’s Guide to Proteomics.
Microbiol Mol Biol Rev. Mar 2002; 66(1): 39–63.

Peptide mass tag searching

Peptide mass tag searching

Peptide mass tag searching. Shown is a schematic of how information from an unknown peptide (top) is matched to a peptide sequence in a database (bottom) for protein identification. The partial amino acid sequence or “tag” obtained by MS/MS is combined with the peptide mass (parent mass), the mass of the peptide at the start of the sequence (mass tag 1), and the mass of the peptide at the end of the sequence (mass tag 2). The specificity of the protease used (trypsin is shown) can also be included in the search.

ICAT method for measuring differential protein expression

ICAT method for measuring differential protein expression

The ICAT method for measuring differential protein expression. (A) Structure of the ICAT reagent. ICAT consists of a biotin affinity group, a linker region that can incorporate heavy (deuterium) or light (hydrogen) atoms, and a thiol-reactive end group for linkage to cysteines. (B) ICAT strategy. Proteins are harvested from two different cell states and labeled on cysteine residues with either the light or heavy form of the ICAT reagent. Following labeling, the two protein samples are mixed and digested with a protease such as trypsin. Peptides labeled with the ICAT reagent can be purified by virtue of the biotin tag by using avidin chromatography. Following purification, ICAT-labeled peptides can be analyzed by MS to quantitate the peak ratios and proteins can be identified by sequencing the peptides with MS/MS.

Strategies for determination of phosphorylation sites in proteins

Strategies for determination of phosphorylation sites in proteins

Strategies for determination of phosphorylation sites in proteins. Proteins phosphorylated in vitro or in vivo can be isolated by protein electrophoresis and analyzed by MS. (A) Identification of phosphopeptides by peptide mass fingerprinting. In this method, phosphopeptides are identified by comparing the mass spectrum of an untreated sample to that of a sample treated with phosphatase. In the phosphatase-treated sample, potential phosphopeptides are identified by a decrease in mass due to loss of a phosphate group (80 Da). (B) Phosphorylation sites can be identified by peptide sequencing using MS/MS. (C) Edman degradation can be used to monitor the release of inorganic 32P to provide information about phosphorylation sites in peptides.

protein mining strategy

protein mining strategy

Proteome-mining strategy. Proteins are isolated on affinity column arrays from a cell line, organ, or animal source and purified to remove nonspecific adherents. Then, compound libraries are passed over the array and the proteins eluted are analyzed by protein electrophoresis. Protein information obtained by MS or Edman degradation is then used to search DNA and protein databases. If a relevant target is identified, a sublibrary of compounds can be evaluated to refine the lead. From this method a protein target and a drug lead can be simultaneously identified.

Although the technology for the analysis of proteins is rapidly progressing, it is still not feasible to study proteins on a scale equivalent to that of the nucleic acids. Most of proteomics relies on methods, such as protein purification or PAGE, that are not high-throughput methods. Even performing MS can require considerable time in either data acquisition or analysis. Although hundreds of proteins can be analyzed quickly and in an automated fashion by a MALDI-TOF mass spectrometer, the quality of data is sacrificed and many proteins cannot be identified. Much higher quality data can be obtained for protein identification by MS/MS, but this method requires considerable time in data interpretation. In our opinion, new computer algorithms are needed to allow more accurate interpretation of mass spectra without operator intervention. In addition, to access unannotated DNA databases across species, these algorithms should be error tolerant to allow for sequencing errors, polymorphisms, and conservative substitutions. New technologies will have to emerge before protein analysis on a large-scale (such as mapping the human proteome) becomes a reality.

Another major challenge for proteomics is the study of low-abundance proteins. In some eukaryotic cells, the amounts of the most abundant proteins can be 106-fold greater than those of the low-abundance proteins. Many important classes of proteins (that may be important drug targets) such as transcription factors, protein kinases, and regulatory proteins are low-copy proteins. These low-copy proteins will not be observed in the analysis of crude cell lysates without some purification. Therefore, new methods must be devised for subproteome isolation.

Tissue Proteomics for the Next Decade?  Towards a Molecular Dimension in Histology

R Longuespe´e, M Fle´ron, C Pottier, F Quesada-Calvo, Marie-Alice Meuwis, et al.
OMICS A Journal of Integrative Biology 2014; 18: 9.

The concept of tissues appeared more than 200 years ago, since textures and attendant differences were described within the whole organism components. Instrumental developments in optics and biochemistry subsequently paved the way to transition from classical to molecular histology in order to decipher the molecular contexts associated with physiological or pathological development or function of a tissue. In 1941, Coons and colleagues performed the first systematic integrated examination of classical histology and biochemistry when his team localized pneumonia antigens in infected tissue sections. Most recently, in the early 21st century, mass spectrometry (MS) has progressively become one of the most valuable tools to analyze biomolecular compounds. Currently, sampling methods, biochemical procedures, and MS instrumentations
allow scientists to perform ‘‘in depth’’ analysis of the protein content of any type of tissue of interest. This article reviews the salient issues in proteomics analysis of tissues. We first outline technical and analytical considerations for sampling and biochemical processing of tissues and subsequently the instrumental possibilities for proteomics analysis such as shotgun proteomics in an anatomical context. Specific attention concerns formalin fixed and paraffin embedded (FFPE) tissues that are potential ‘‘gold mines’’ for histopathological investigations. In all, the matrix assisted laser desorption/ionization (MALDI) MS imaging, which allows for differential mapping of hundreds of compounds on a tissue section, is currently the most striking evidence of linkage and transition between ‘‘classical’’ and ‘‘molecular’’ histology. Tissue proteomics represents a veritable field of research and investment activity for modern biomarker discovery and development for the next decade.

Progressively, tissue analyses evolved towards the description of the whole molecular content of a given sample. Currently, mass spectrometry (MS) is the most versatile
analytical tool for protein identification and has proven its great potential for biological and clinical applications. ‘‘Omics’’ fields, and especially proteomics, are of particular
interest since they allow the analysis of a biomolecular picture associated with a given physiological or pathological state. Biochemical techniques were then adapted for an optimal extraction of several biocompounds classes from tissues of different natures.

Laser capture microdissection (LCM) is used to select and isolate tissue areas of interest for further analysis. The developments of MS instrumentations have then definitively transformed the scientific scene, pushing back more and more detection and identification limits. Since a few decades, new approaches of analyses appeared, involving the use of tissue sections dropped on glass slides as starting material. Two types of analyses can then be applied on tissue sections: shotgun proteomics and the very promising MS imaging (MSI) using Matrix Assisted Laser Desorption/Ionization (MALDI) sources. Also known as ‘‘molecular histology,’’ MSI is the most striking hyphen between histology and molecular analysis. In practice, this method allows visualization of the spatial distribution of proteins, peptides, drugs, or others analytes directly on tissue sections. This technique paved new ways of research, especially in the field of histopathology, since this approach appeared to be complementary to conventional histology.

Tissue processing workflows for molecular analyses

Tissue processing workflows for molecular analyses

Tissue processing workflows for molecular analyses. Tissues can either be processed in solution or directly on tissue sections. In solution, processing involves protein
extraction from tissue pieces in order to perform 2D gel separation and identification of proteins, shotgun proteomics, or MALDI analyses. Extracts can also be obtained from
tissues area selection and protein extraction after laser micro dissection or on-tissue processing. Imaging techniques are dedicated to the morphological characterization or molecular mapping of tissue sections. Histology can either be conducted by hematoxylin/eosin staining or by molecular mapping using antibodies with IHC. Finally, mass spectrometry imaging allows the cartography of numerous compounds in a single analysis. This approach is a modern form of ‘‘molecular histology’’ as it grafts, with the use of mathematical calculations, a molecular dimension to classical histology. (AR, antigen retrieval; FFPE, formalin fixed and paraffin embedded; fr/fr, fresh frozen; IHC, immunohistochemistry; LCM, laser capture microdissection; MALDI, matrix assisted laser desorption/ionization; MSI, mass spectrometry imaging; PTM, post translational modification.)

Analysis of tissue proteomes has greatly evolved with separation methods and mass spectrometry instrumentation. The choice of the workflow strongly depends on whether a bottom-up or a top-down analysis has to be performed downstream. In-gel or off-gel proteomics principally differentiates proteomic workflows. The almost simultaneous discoveries of the MS ionization sources (Nobel Prize awarded) MALDI (Hillenkamp and Karas, 1990; Tanaka et al., 1988) and electrospray ionization (ESI) (Fenn et al., 1989) have paved the way for analysis of intact proteins and peptides. Separation methods such as two-dimension electrophoresis (2DE) (Fey and Larsen, 2001) and nanoscale reverse phase liquid chromatography (nanoRP-LC) (Deterding et al., 1991) lead to efficient preparation of proteins for respectively topdown and bottom-up strategies. A huge panel of developments was then achieved mostly for LC-MS based proteomics in order to improve ion fragmentation approaches and peptide
identification throughput relying on database interrogation. Moreover, approaches were developed to analyze post translational modifications (PTM) such as phosphorylations (Ficarro et al., 2002; Oda et al., 2001; Zhou et al., 2001) or glycosylations (Zhang et al., 2003), proposing as well different quantification procedures. Regarding instrumentation, the most cutting edge improvements are the gain of mass accuracy for an optimal detection of the eluted peptides during LC-MS runs (Mann and Kelleher, 2008; Michalski et al., 2011) and the increase in scanning speed, for example with the use of Orbitrap analyzers (Hardman and Makarov, 2003; Makarov et al., 2006; Makarov et al., 2009; Olsen et al., 2009). Ion transfer efficiency was also drastically improved with the conception of ion funnels that homogenize the ion transmission
capacities through m/z ranges (Kelly et al., 2010; Kim et al., 2000; Page et al., 2006; Shaffer et al., 1998) or by performing electrospray ionization within low vacuum (Marginean et al., 2010; Page et al., 2008; Tang et al., 2011). Beside collision induced dissociation (CID) that is proposed for many applications (Li et al., 2009; Wells and McLuckey, 2005), new fragmentation methods were investigated, such as higher-energy collisional dissociation (HCD) especially for phosphoproteomic
applications (Nagaraj et al., 2010), and electron transfer dissociation (ETD) and electron capture dissociation (ECD) that are suited for phospho- and glycoproteomics (An
et al., 2009; Boersema et al., 2009; Wiesner et al., 2008). Methods for data-independent MS2 analysis based on peptide fragmentation in given m/z windows without precursor selection neither information knowledge, also improves identification throughput (Panchaud et al., 2009; Venable et al., 2004), especially with the use of MS instruments with high resolution and high mass accuracy specifications (Panchaud et al., 2011). Gas fractionation methods such as ion mobility (IM) can also be used as a supplementary separation dimension which enable more efficient peptide identifications (Masselon et al., 2000; Shvartsburg et al., 2013; Shvartsburg et al., 2011).

Microdissection relies on a laser ablation principle. The tissue section is dropped on a plastic membrane covering a glass slide. The preparation is then placed into a microscope
equipped with a laser. A highly focused beam will then be guided by the user at the external limit of the area of interest. This area composed by the plastic membrane, and the tissue section will then be ejected from the glass slide and collected into a tube cap for further processing. This mode of microdissection is the most widely used due to its ease of handling and the large panels of devices proposed by constructors. Indeed, Leica microsystem proposed the Leica LMD system (Kolble, 2000), Molecular Machine and Industries, the MMI laser microdissection system Microcut, which was used in combination with IHC (Buckanovich et al., 2006), Applied Biosystems developed the Arcturus
microdissection System, and Carl Zeiss patented P.A.L.M. MicroBeam technology (Braakman et al., 2011; Espina et al., 2006a; Espina et al., 2006b; Liu et al., 2012; Micke
et al., 2005). LCM represents a very adequate link between classical histology and sampling methods for molecular analyses as it is a simple customized microscope. Indeed,
optical lenses of different magnification can be used and the method is compatible with classical IHC (Buckanovich et al., 2006). Only the laser and the tube holder need to be
added to the instrumentation.

After microdissection, the tissue pieces can be processed for analyses using different available MS devices and strategies. The simplest one consists in the direct analysis of the
protein profiles by MALDI-TOF-MS (MALDI-time of flight-MS). The microdissected tissues are dropped on a MALDI target and directly covered by the MALDI matrix (Palmer-Toy et al., 2000; Xu et al., 2002). This approach was already used in order to classify breast cancer tumor types (Sanders et al., 2008), identify intestinal neoplasia protein biomarkers (Xu et al., 2009), and to determine differential profiles in glomerulosclerosis (Xu et al., 2005).

Currently the most common proteomic approach for LCM tissue analysis is LC-MS/MS. Label free LC-MS approaches have been used to study several cancers like head and neck squamous cell carcinomas (Baker et al., 2005), esophageal cancer (Hatakeyama et al., 2006), dysplasic cervical cells (Gu et al., 2007), breast carcinoma tumors (Hill et al., 2011; Johann et al., 2009), tamoxifen-resistant breast cancer cells (Umar et al., 2009), ER + / – breast cancer cells (Rezaul et al., 2010), Barretts esophagus (Stingl et al., 2011), and ovarian endometrioid cancer (Alkhas et al., 2011). Different isotope labeling methods have been used in order to compare proteins expression. ICAT was first used to investigate proteomes of hepatocellular carcinoma (Li et al., 2004; 2008). The O16/O18 isotopic labeling was then used for proteomic analysis of ductal carcinoma of the breast (Zang et al., 2004).

Currently, the lowest amount of collected cells for a relevant single analysis using fr/fr breast cancer tissues was 3000–4000 (Braakman et al., 2012; Liu et al., 2012; Umar et al., 2007). With a Q-Exactive (Thermo, Waltham) mass spectrometer coupled to LC, Braakman was able to identify up to 1800 proteins from 4000 cells. Processing
of FFPE microdissected tissues of limited sizes still remains an issue which is being addressed by our team.

Among direct tissue analyses modes, two categories of investigations can be done. MALDI profiling consists in the study of molecular localization of compounds and can be
combined with parallel shotgun proteomic methods. Imaging methods give less detailed molecular information, but is more focused on the accurate mapping of the detected compounds through tissue area. In 2007, a concept of direct tissue proteomics (DTP) was proposed for high-throughput examination of tissue microarray samples. However, contrary to the classical workflow, tissue section chemical treatment involved a first step of scrapping each FFPE tissue spot with a razor blade from the glass slide. The tissues were then transferred into a tube and processed with RIPA buffer and finally submitted to boiling as an AR step (Hwang et al., 2007). Afterward, several teams proved that it was possible to perform the AR directly on tissue sections. These applications were mainly dedicated to MALDI imaging analyses (Bonnel et al., 2011; Casadonte and Caprioli, 2011; Gustafsson et al., 2010). However, more recently, Longuespe´e used citric acid antigen retrieval (CAAR) before shotgun proteomics associated to global profiling proteomics (Longuespee et al., 2013).

MALDI imaging workflow

MALDI imaging workflow

MALDI imaging workflow. For MALDI imaging experiments, tissue sections are dropped on conductive glass slides. Sample preparations are then adapted depending on the nature of the tissue sample (FFPE or fr/fr). Then, matrix is uniformly deposited on the tissue section using dedicated devices. A laser beam subsequently irradiates the preparation following a given step length and a MALDI spectrum is acquired for each position. Using adapted software, the different detected ions are then mapped through the tissue section, in function of their differential intensities. The ‘‘molecular maps’’ are called images. (FFPE, formalin fixed and paraffin embedded; fr/fr, fresh frozen; MALDI, matrix assisted laser desorption ionization.)

Proteomics instrumentations, specific biochemical preparations, and sampling methods such as LCM altogether allow for the deep exploration and comparison of different proteomes between regions of interest in tissues with up to 104 detected proteins. MALDI MS imaging that allows for differential mapping of hundreds of compounds on a tissue section is currently the most striking illustration of association between ‘‘classical’’ and ‘‘molecular’’ histology.

Novel serum protein biomarker panel revealed by mass spectrometry and its prognostic value in breast cancer

L Chung, K Moore, L Phillips, FM Boyle, DJ Marsh and RC Baxter*  Breast Cancer Research 2014, 16:R63

Introduction: Serum profiling using proteomic techniques has great potential to detect biomarkers that might improve diagnosis and predict outcome for breast cancer patients (BC). This study used surface-enhanced laser desorption/ionization time-of-flight (SELDI-TOF) mass spectrometry (MS) to identify differentially expressed proteins in sera from BC and healthy volunteers (HV), with the goal of developing a new prognostic biomarker panel.
Methods: Training set serum samples from 99 BC and 51 HV subjects were applied to four adsorptive chip surfaces (anion-exchange, cation-exchange, hydrophobic, and metal affinity) and analyzed by time-of-flight MS. For validation, 100 independent BC serum samples and 70 HV samples were analyzed similarly. Cluster analysis of protein spectra was performed to identify protein patterns related to BC and HV groups. Univariate and multivariate statistical analyses were used to develop a protein panel to distinguish breast cancer sera from healthy sera, and its prognostic potential was evaluated.
Results: From 51 protein peaks that were significantly up- or downregulated in BC patients by univariate analysis, binary logistic regression yielded five protein peaks that together classified BC and HV with a receiver operating characteristic (ROC) area-under-the-curve value of 0.961. Validation on an independent patient cohort confirmed
the five-protein parameter (ROC value 0.939). The five-protein parameter showed positive association with large tumor size (P = 0.018) and lymph node involvement (P = 0.016). By matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS, immunoprecipitation and western blotting the proteins were identified as a fragment
of apolipoprotein H (ApoH), ApoCI, complement C3a, transthyretin, and ApoAI. Kaplan-Meier analysis on 181 subjects after median follow-up of >5 years demonstrated that the panel significantly predicted disease-free survival (P = 0.005), its efficacy apparently greater in women with estrogen receptor (ER)-negative tumors (n = 50, P = 0.003) compared to ER-positive (n = 131, P = 0.161), although the influence of ER status needs to be confirmed after longer follow-up.
Conclusions: Protein mass profiling by MS has revealed five serum proteins which, in combination, can distinguish between serum from women with breast cancer and healthy control subjects with high sensitivity and specificity. The five-protein panel significantly predicts recurrence-free survival in women with ER-negative tumors and may have value in the management of these patients.

Cellular prion protein is required for neuritogenesis: fine-tuning of multiple signaling pathways involved in focal adhesions and actin cytoskeleton dynamics

Aurélie Alleaume-Butaux, et al.   Cell Health and Cytoskeleton 2013:5 1–12

Neuritogenesis is a dynamic phenomenon associated with neuronal differentiation that allows a rather spherical neuronal stem cell to develop dendrites and axon, a prerequisite for the integration and transmission of signals. The acquisition of neuronal polarity occurs in three steps:

(1) neurite sprouting, which consists of the formation of buds emerging from the postmitotic neuronal soma;

(2) neurite outgrowth, which represents the conversion of buds into neurites, their elongation and evolution into axon or dendrites; and

(3) the stability and plasticity of neuronal polarity.

In neuronal stem cells, remodeling and activation of focal adhesions (FAs)

  • associated with deep modifications of the actin cytoskeleton is
  • a prerequisite for neurite sprouting and subsequent neurite outgrowth.

A multiple set of growth factors and interactors located in

  • the extracellular matrix and the plasma membrane orchestrate neuritogenesis
  • by acting on intracellular signaling effectors, notably small G proteins such as RhoA, Rac, and Cdc42,
  • which are involved in actin turnover and the dynamics of FAs.

The cellular prion protein (PrPC), a glycosylphosphatidylinositol (GPI)-anchored membrane protein

  • mainly known for its role in a group of fatal neurodegenerative diseases,
  • has emerged as a central player in neuritogenesis.

Here, we review the contribution of PrPC to neuronal polarization and

  • detail the current knowledge on the signaling pathways fine-tuned
  • by PrPC to promote neurite sprouting, outgrowth, and maintenance.

We emphasize that PrPC-dependent neurite sprouting is a process in which

  • PrPC governs the dynamics of FAs and the actin cytoskeleton via β1 integrin signaling.

The presence of PrPC is necessary to render neuronal stem cells

  • competent to respond to neuronal inducers and to develop neurites.

In differentiating neurons, PrPC exerts a facilitator role towards neurite elongation.

This function relies on the interaction of PrPC with a set of diverse partners such as

  1. elements of the extracellular matrix,
  2. plasma membrane receptors,
  3. adhesion molecules, and
  4. soluble factors that control actin cytoskeleton turnover
  • through Rho-GTPase signaling.

Once neurons have reached their terminal stage of differentiation and

  • acquired their polarized morphology,
  • PrPC also takes part in the maintenance of neurites.

By acting on tissue nonspecific alkaline phosphatase, or matrix metalloproteinase type 9,

  • PrPC stabilizes interactions between neurites and the extracellular matrix.

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

Andrew Chen et al., Journal of Cell Science 121, 3619-3628.

Cell-cell fusion in animal development and in pathophysiology

  • involves expansion of nascent fusion pores formed by protein fusogens
  • to yield an open lumen of cell-size diameter.

Here we explored the enlargement of micron-scale pores in syncytium formation,

  • which was initiated by a well-characterized fusogen baculovirus gp64.

Radial expansion of a single or, more often, of multiple fusion pores

  • proceeds without loss of membrane material in the tight contact zone.

Pore growth requires cell metabolism and is

  • accompanied by a local disassembly of the actin cortex under the pores.

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

  1. is restricted by a dynamic resistance of the actin network and
  2. driven by membrane-bending proteins that are involved in
  3. the generation of highly curved intracellular membrane compartments.

Pak1 Is Required to Maintain Ventricular Ca2+ Homeostasis and Electrophysiological Stability Through SERCA2a Regulation in Mice

Yanwen Wang, et al.  Circ Arrhythm Electrophysiol. 2014;7:00-00.

Impaired sarcoplasmic reticular Ca2+ uptake resulting from

  • decreased sarcoplasmic reticulum Ca2+-ATPase type 2a (SERCA2a) expression or activity
  • is a characteristic of heart failure with its associated ventricular arrhythmias.

Recent attempts at gene therapy of these conditions explored strategies

  • enhancing SERCA2a expression and the activity as novel approaches to heart failure management.

We here explore the role of Pak1 in maintaining ventricular Ca2+ homeostasis and electrophysiological stability

  • under both normal physiological and acute and chronic β-adrenergic stress conditions.

Methods and Results—Mice with a cardiomyocyte-specific Pak1 deletion (Pak1cko), but not controls (Pak1f/f), showed

  • high incidences of ventricular arrhythmias and electrophysiological instability
  • during either acute β-adrenergic or chronic β-adrenergic stress leading to hypertrophy,
  • induced by isoproterenol.

Isolated Pak1cko ventricular myocytes correspondingly showed

  • aberrant cellular Ca2+ homeostasis.

Pak1cko hearts showed an associated impairment of SERCA2a function and

  • downregulation of SERCA2a mRNA and protein expression.

Further explorations of the mechanisms underlying the altered transcriptional regulation

  • demonstrated that exposure to control Ad-shC2 virus infection
  • increased SERCA2a protein and mRNA levels after
  • phenylephrine stress in cultured neonatal rat cardiomyocytes.

This was abolished by the

  • Pak1-knockdown in Ad-shPak1–infected neonatal rat cardiomyocytes and
  • increased by constitutive overexpression of active Pak1 (Ad-CAPak1).

We then implicated activation of serum response factor, a transcriptional factor well known for

  • its vital role in the regulation of cardiogenesis genes in the Pak1-dependent regulation of SERCA2a.

Conclusions—These findings indicate that

Pak1 is required to maintain ventricular Ca2+ homeostasis and electrophysiological stability

  • and implicate Pak1 as a novel regulator of cardiac SERCA2a through
  • a transcriptional mechanism

fusion in animal development and in pathophysiology involves expansion of nascent fusion pores

  • formed by protein fusogens to yield an open lumen of cell-size diameter.

Here we explored the enlargement of micron-scale pores in syncytium formation,

  • which was initiated by a well-characterized fusogen baculovirus gp64.

Radial expansion of a single or, more often, of multiple fusion pores proceeds

  • without loss of membrane material in the tight contact zone.

Pore growth requires cell metabolism and is accompanied by

  • a local disassembly of the actin cortex under the pores.

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.

Role of forkhead box protein A3 in age-associated metabolic decline

Xinran Maa,1, Lingyan Xua,1, Oksana Gavrilovab, and Elisabetta Muellera,2
PNAS Sep 30, 2014 | 111 | 39 | 14289–14294

This paper reports that the transcription factor forkhead box protein A3 (Foxa3) is

  • directly involved in the development of age-associated obesity and insulin resistance.

Mice that lack the Foxa3 gene

  1. remodel their fat tissues,
  2. store less fat, and
  3. burn more energy as they age.

These mice also live significantly longer.

We show that Foxa3 suppresses a key metabolic cofactor, PGC1α,

  • which is involved in the gene programs that turn on energy expenditure in adipose tissues.

Overall, these findings suggest that Foxa3 contributes to the increased adiposity observed during aging,

  • and that it can be a possible target for the treatment of metabolic disorders.

Aging is associated with increased adiposity and diminished thermogenesis, but

  • the critical transcription factors influencing these metabolic changes late in life are poorly understood.

We recently demonstrated that the winged helix factor forkhead box protein A3 (Foxa3)

  • regulates the expansion of visceral adipose tissue in high-fat diet regimens; however,
  • whether Foxa3 also contributes to the increase in adiposity and the decrease in brown fat activity
  • observed during the normal aging process is currently unknown.

Here we report that during aging, levels of Foxa3 are significantly and selectively

  • up-regulated in brown and inguinal white fat depots, and that
  • midage Foxa3-null mice have increased white fat browning and thermogenic capacity,
  1. decreased adipose tissue expansion,
  2. improved insulin sensitivity, and
  3. increased longevity.

Foxa3 gain-of-function and loss-of-function studies in inguinal adipose depots demonstrated

  • a cell-autonomous function for Foxa3 in white fat tissue browning.

The mechanisms of Foxa3 modulation of brown fat gene programs involve

  • the suppression of peroxisome proliferator activated receptor γ coactivtor 1 α (PGC1α) levels
  • through interference with cAMP responsive element binding protein 1-mediated
  • transcriptional regulation of the PGC1α promoter.

Our data demonstrate a role for Foxa3 in energy expenditure and in age-associated metabolic disorders.

Control of Mitochondrial pH by Uncoupling Protein 4 in Astrocytes Promotes Neuronal Survival

HP Lambert, M Zenger, G Azarias, Jean-Yves Chatton, PJ. Magistretti,§, S Lengacher
JBC (in press) M114.570879

Background: Role of uncoupling proteins (UCP) in the brain is unclear.
Results: UCP, present in astrocytes, mediate the intra-mitochondrial acidification leading to a decrease in mitochondrial ATP production.
Conclusion: Astrocyte pH regulation promotes ATP synthesis by glycolysis whose final product, lactate, increases neuronal survival.
Significance: We describe a new role for a brain uncoupling protein.

Brain activity is energetically costly and requires a steady and

  • highly regulated flow of energy equivalents between neural cells.

It is believed that a substantial share of cerebral glucose, the major source of energy of the brain,

  • will preferentially be metabolized in astrocytes via aerobic glycolysis.

The aim of this study was to evaluate whether uncoupling proteins (UCPs),

  • located in the inner membrane of mitochondria,
  • play a role in setting up the metabolic response pattern of astrocytes.

UCPs are believed to mediate the transmembrane transfer of protons

  • resulting in the uncoupling of oxidative phosphorylation from ATP production.

UCPs are therefore potentially important regulators of energy fluxes. The main UCP isoforms

  • expressed in the brain are UCP2, UCP4, and UCP5.

We examined in particular the role of UCP4 in neuron-astrocyte metabolic coupling

  • and measured a range of functional metabolic parameters
  • including mitochondrial electrical potential and pH,
  1. reactive oxygen species production,
  2. NAD/NADH ratio,
  3. ATP/ADP ratio,
  4. CO2 and lactate production, and
  5. oxygen consumption rate (OCR).

In brief, we found that UCP4 regulates the intra-mitochondrial pH of astrocytes

  • which acidifies as a consequence of glutamate uptake,
  • with the main consequence of reducing efficiency of mitochondrial ATP production.
  • the diminished ATP production is effectively compensated by enhancement of glycolysis.
  • this non-oxidative production of energy is not associated with deleterious H2O2 production.

We show that astrocytes expressing more UCP4 produced more lactate,

  • used as energy source by neurons, and had the ability to enhance neuronal survival.

Jose Eduardo des Salles Roselino

The problem with genomics was it was set as explanation for everything. In fact, when something is genetic in nature the genomic reasoning works fine. However, this means whenever an inborn error is found and only in this case the genomic knowledge afterwards may indicate what is wrong and not the completely way to put biology upside down by reading everything in the DNA genetic as well as non-genetic problems.

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Functional Correlates of Signaling Pathways

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


We here move on to a number of specific, key published work on signaling, and look at the possible therapeutic applications to disease states.

Scripps Research Professor Wolfram Ruf and colleagues have identified a key connection between

  • the signaling pathways and the immune system spiraling out of control involving
  • the coagulation system and vascular endothelium that,
  • if disrupted may be a target for sepsis. (Science Daily, Feb 29, 2008).

It may be caused by a bacterial infection that enters the bloodstream, but

  • we now recognize the same cascade not triggered by bacterial invasion.

The acute respiratory distress syndrome (ARDS) has been defined as

  • a severe form of acute lung injury featuring
  • pulmonary inflammation and increased capillary leak.

ARDS is associated with a high mortality rate and accounts for 100,000 deaths annually in the United States. ARDS may arise in a number of clinical situations, especially in patients with sepsis. A well-described pathophysiological model of ARDS is one form of

  • the acute lung inflammation mediated by
  1. neutrophils,
  2. cytokines, and
  3. oxidant stress.

Neutrophils are major effect cells at the frontier of

  • innate immune responses, and they play
  • a critical role in host defense against invading microorganisms.

The tissue injury appears to be related to

  • proteases and toxic reactive oxygen radicals
  • released from activated neutrophils.

In addition, neutrophils can produce cytokines and chemokines that

enhance the acute inflammatory response.

Neutrophil accumulation in the lung plays a pivotal role in the pathogenesis of acute lung injury during sepsis. Directed movement of neutrophils is

  • mediated by a group of chemoattractants,
  • especially CXC chemokines.

Local lung production of CXC chemokines is intensified during experimental sepsis induced by cecal ligation and puncture (CLP).

Sepsis, Multi-organ Dysfunction Syndrome, and Septic Shock: A Conundrum of Signaling Pathways Cascading Out of Control

Integrins and extracellular matrix in mechanotransduction

ligand binding of integrins

ligand binding of integrins

Integrins are a family of cell surface receptors which

mediate cell–matrix and cell–cell adhesions.

Among other functions they provide an important

mechanical link between the cells external and intracellular environments while

the adhesions that they form also have critical roles in cellular signal-transduction.

Cell–matrix contacts occur at zones in the cell surface where

adhesion receptors cluster and when activated

the receptors bind to ligands in the extracellular matrix.

The extracellular matrix surrounds the cells of tissues and forms the

structural support of tissue which is particularly important in connective tissues.

Cells attach to the extracellular matrix through

specific cell-surface receptors and molecules

including integrins and transmembrane proteoglycans.

The integrin family of αβ heterodimeric receptors act as

cell adhesion molecules

connecting the ECM to the actin cytoskeleton.

The actin cytoskeleton is involved in the regulation of

1.cell motility,

2.cell polarity,

3.cell growth, and

4.cell survival.

The combination of αβ subunits determines

binding specificity and

signaling properties.

Both α and β integrin subunits contain two separate tails, which

penetrate the plasma membrane and possess small cytoplasmic domains which facilitate

the signaling functions of the receptor.

There is some evidence that the β subunit is the principal site for

binding of cytoskeletal and signaling molecules,

whereas the α subunit has a regulatory role. The integrin tails

link the ECM to the actin cytoskeleton within the cell and with cytoplasmic proteins,

such as talin, tensin, and filamin. The extracellular domains of integrin receptors bind the ECM ligands.

binding of integrins depends on ECM divalent cations ch19

binding of integrins depends on ECM divalent cations ch19

integrin coupled to F-actin via linker

integrin coupled to F-actin via linker

Schematic of the ‘focal adhesion clutch’ on stiff (a) versus soft (b) extracellular matrix (ECM). In all cases, integrins are coupled to F-actin via linker proteins (for example, talin and vinculin). The linker proteins move backwards (as indicated by the small arrows) as F-actin also moves backwards, under pushing forces from actin polymerization and/or pulling forces from myosin II activity. This mechanism transfers force from actin to integrins, which pull on the ECM. A stiff ECM (a) resists this force so that the bound integrins remain immobile. A compliant matrix (b) deforms under this force (as indicated by the compressed ECM labelled as deformed matrix) so that the bound integrins can also move backwards. Their movement reduces the net loading rate on all the force-bearing elements, which results in altered cellular responses

The ECM is a complex mixture of matrix molecules, including –

  • glycoproteins, collagens, laminins, glycosaminoglycans, proteoglycans,
  • and nonmatrix proteins, – including growth factors

The integrin receptor formed from the binding of α and β subunits is

  • shaped like a globular head supported by two rod-like legs (Figure 1).

Most of the contact between the two subunits occurs in the head region, with

  • the intracellular tails of the subunits forming the legs of the receptor.

Integrin recognition of ligands is not constitutive but

  • is regulated by alteration of integrin affinity for ligand binding.

For integrin binding to ligands to occur

  • the integrin must be primed and activated, both of which involve
  • conformational changes to the receptor.

Linking integrin conformation to function

Figure  Integrin binding to extracellular matrix (ECM). Conformational changes to integrin structure and clustering of subunits which allow enhanced function of the receptor.

Integrins work alongside other proteins such as


immunoglobulin superfamily

cell adhesion molecules,

selectins, and


to mediate

cell–cell and

cell–matrix interactions and communication.

Activation of adhesion receptors triggers the formation of matrix contacts in which

bound matrix components,

adhesion receptors,

and associated intracellular cytoskeletal and signaling molecules

form large functional, localized multiprotein complexes.

Cell–matrix contacts are important in a variety of different cell and

tissue properties including

1.embryonic development,

2.inflammatory responses,

3.wound healing,

4.and adult tissue homeostasis.

Integrin extracellular binding activity is regulated from inside the cell and binding to the ECM induces signals that are transmitted into the cell. This bidirectional signaling requires


spatially, and

temporally regulated formation and

disassembly of multiprotein complexes that

form around the short cytoplasmic tails of integrins.

Ligand binding to integrin family members leads to clustering of integrin molecules in the plasma membrane and recruitment of actin filaments and intracellular signaling molecules to the cytoplasmic domain of the integrins. This forms focal adhesion complexes which are able to maintain

not only adhesion to the ECM

but are involved in complex signaling pathways

which include establishing

1.cell polarity,

2.directed cell migration, and

3.maintaining cell growth and survival.

Initial activation through integrin adhesion to matrix recruits up to around 50 diverse signaling molecules

to assemble the focal adhesion complex

which is capable of responding to environmental stimuli efficiently.

Mapping of the integrin

adhesome binding and signaling interactions

a network of 156 components linked together which can be modified by 690 interactions.

Genetic programming occurs with the binding of integrins to the ECM

Signal transduction pathway activation arising from integrin-ECM binding results in

  • changes in gene expression of cells and
  • leads to alterations in cell and tissue function.

Various different effects can arise depending on the

1.cell type,

2.matrix composition, and

3.integrins activated

It has been suggested that integrin-type I collagen interaction is necessary for

  • the phosphorylation and activation of osteoblast-specific transcription factors
  • present in committed osteoprogenitor cells.

During mechanical loading/stimulation of chondrocytes there is an

  1. influx of ions across the cell membrane resulting from
  2. activation of mechanosensitive ion channels
  3. which can be inhibited by subunit-specific anti-integrin blocking antibodies or RGD peptides.

Using these strategies it was identified that

  • α5β1 integrin is a major mechanoreceptor in articular chondrocyte
  • responses to mechanical loading/stimulation.

Osteoarthritic chondrocytes show a depolarization response to 0.33 Hz stimulation

  • in contrast to the hyperpolarization response of normal chondrocytes.

The mechanotransduction pathway in chondrocytes derived from normal and osteoarthritic cartilage

  • both involve recognition of the mechanical stimulus
  • by integrin receptors resulting in
  • the activation of integrin signaling pathways
  • leading to the generation of a cytokine loop.

Normal and osteoarthritic chondrocytes show differences

  • at multiple stages of the mechanotransduction cascade.
Signaling pathways activated in chondrocytes

Signaling pathways activated in chondrocytes

Chondrocyte integrins are important mediators of cell–matrix interactions in cartilage

  • by regulating the response of the cells to signals from the ECM that
  1. control cell proliferation,
  2. survival,
  3. differentiation,
  4. matrix remodeling.

Integrins participate in development and maintenance of the tissue but also

  • in pathological processes related to matrix destruction, where
  • they likely play a role in the progression of OA.

Cellular adaptation to mechanical stress: role of integrins, Rho, cytoskeletal tension and mechanosensitive ion channels

Cells exhibited four types of mechanical responses:

(1) an immediate viscoelastic response;

(2) early adaptive behavior characterized by pulse-to-pulse attenuation in response to oscillatory forces;

(3) later adaptive cell stiffening with sustained (>15 second) static stresses; and

(4) a large-scale repositioning response with prolonged (>1 minute) stress.

Importantly, these adaptation responses differed biochemically.

The immediate and early responses were affected by

chemically dissipating cytoskeletal prestress (isometric tension), whereas

the later adaptive response was not.

The repositioning response was prevented by

inhibiting tension through interference with Rho signaling,

similar to the case of the immediate and early responses, but it was also prevented by

blocking mechanosensitive ion channels or

by inhibiting Src tyrosine kinases.

All adaptive responses were suppressed by cooling cells to 4°C to slow biochemical remodeling. Thus, cells use multiple mechanisms to sense and respond to static and dynamic changes in the level of mechanical stress applied to integrins.

Microtubule-Stimulated ADP Release, ATP Binding, and Force Generation In Transport Kinesins

All three classes of molecular motor proteins are now known to be

  • large protein families with diverse cellular functions.

Both the kinesin family and the myosin family have been defined and their proteins grouped into subfamilies. Finally, the elusive cytoplasmic version of dynein was identified and a multigene family of flagellar and cytoplasmic dyneins defined. Members of a given motor protein family share

  • significant homology in their motor domains with the defining member,
  • kinesin, dynein or myosin; but they also contain
  • unique protein domains that are specialized for interaction with different cargoes.

This large number of motor proteins may reflect

  • the number of cellular functions that require force generation or movement,
  • ranging from mitosis to morphogenesis to transport of vesicles.

Kinesins are a large family of microtubule (MT)-based motors that play important roles in many cellular activities including


motility, and

intracellular transport

Their involvement in a range of pathological processes

  • also highlights their significance as therapeutic targets and
  • the importance of understanding the molecular basis of their function

They are defined by their motor domains that contain both

  • the microtubule (MT) and
  • ATP binding sites.

Three ATP binding motifs—

  1. the P-loop,
  2. switch I,
  3. switch II–

are highly conserved among

  1. kinesins,
  2. myosin motors, and
  • small GTPases.

They share a conserved mode of MT binding such that

  • MT binding,
  • ATP binding, and
  • hydrolysis

are functionally coupled for efficient MT-based work.

The interior of a cell is a hive of activity, filled with

  • proteins and other items moving from one location to another.

A network of filaments called microtubules forms tracks

  • along which so-called motor proteins carry these items.

Kinesins are one group of motor proteins, and a typical kinesin protein has

  • one end (called the ‘motor domain’) that can attach itself to the microtubules.

The other end links to the cargo being carried, and a ‘neck’ connects the two. When two of these proteins work together,

  • flexible regions of the neck allow the two motor domains to move past one another,
  • which enable the kinesin to essentially walk along a microtubule in a stepwise manner.

Although the two kinesins have been thought to move along the microtubule tracks in different ways, Atherton et al. find that the core mechanism used by their motor domains is the same.

When a motor domain binds to the microtubule, its shape changes,

  • first stimulating release of the breakdown products of ATP from the previous cycle.

This release makes room for a new ATP molecule to bind. The structural changes caused by ATP binding

  • produce larger changes in the flexible neck region that
  • enable individual motor domains within a kinesin pair to
  • co-ordinate their movement and move in a consistent direction.

The major and largely invariant point of contact between kinesin motor domains and the MT is helix-α4,

  • which lies at the tubulin intradimer interface.

The conformational changes in functionally important regions of each motor domain are described,

  • starting with the nucleotide-binding site,
  • from which all other conformational changes emanate.

The nucleotide-binding site (Figure 2) has three major elements:

(1) the P-loop (brown) is visible in all our reconstructions;

(2) loop9 (yellow, contains switch I) undergoes major conformational changes through the ATPase cycle; and

(3) loop11 (red, contains switch II) that connects strand-β7 to helix-α4, the conformation and flexibility of which is

  • determined by MT binding and motor nucleotide state.

Movement and extension of helix-α6 controls neck linker docking

the N-terminus of helix-α6 is closely associated with elements of the nucleotide binding site suggesting that

  • its conformation alters in response to different nucleotide states.


  • because the orientation of helix-α6 with respect to helix-α4 controls neck linker docking and
  • because helix-α4 is held against the MT during the ATPase cycle,
    • conformational changes in helix-α6 control movement of the neck linker.

Mechanical amplification and force generation involves conformational changes across the motor domain

A key conformational change in the motor domain following Mg-ATP binding is

  • peeling of the central β-sheet from the C-terminus of helix-α4 increasing their separation;
  • this is required to accommodate rotation of helix-α6 and consequent neck linker docking

ATP binding draws loop11 and loop9 closer together; causing

(1) tilting of most of the motor domain not contacting the MT towards the nucleotide-binding site,

(2) rotation, translation, and extension of helix-α6 which we propose contributes to force generation, and

(3) allows neck linker docking and biases movement of the 2nd head towards the MT plus end.

In both motors, microtubule binding promotes

ordered conformations of conserved loops that

stimulate ADP release,

enhance microtubule affinity and

prime the catalytic site for ATP binding.

ATP binding causes only small shifts of these nucleotide-coordinating loops but induces

large conformational changes elsewhere that

allow force generation and

neck linker docking towards the microtubule plus end.

The study presents evidence provide evidence for a conserved ATP-driven

mechanism for kinesins and

reveals the critical mechanistic contribution of the microtubule interface.

Phosphorylation at endothelial cell–cell junctions: Implications for VE-cadherin function

This review summarizes the role of VE-cadherin phosphorylation in the regulation of endothelial cell–cell junctions and highlights how this affects vascular permeability and leukocyte extravasation.

The vascular endothelium is the inner lining of blood vessels and

forms a physical barrier between the vessel lumen and surrounding tissue;

controlling the extravasation of fluids,

plasma proteins and leukocytes.

Changes in the permeability of the endothelium are tightly regulated. Under basal physiological conditions, there is a continuous transfer of substances across the capillary beds. In addition the endothelium can mediate inducible,

transient hyperpermeability

in response to stimulation with inflammatory mediators,

which takes place primarily in post-capillary venules

However, when severe, inflammation may result in dysfunction of the endothelial barrier

  • in various parts of the vascular tree, including large veins, arterioles and capillaries.

Dysregulated permeability is observed in various pathological conditions, such as

  • tumor-induced angiogenesis,
  • cerebrovascular accident and
  • atherosclerosis.

Two fundamentally different pathways regulate endothelial permeability,

  1. the transcellular and
  2. paracellular pathways.

Solutes and cells can pass through the body of endothelial cells via the transcellular pathway, which includes

  • vesicular transport systems,
  • fenestrae, and
  • biochemical transporters.

The paracellular route is controlled by

  • the coordinated opening and closing of endothelial junctions and
  • thereby regulates traffic across the intercellular spaces between endothelial cells.

Endothelial cells are connected by

tight, gap and

adherens junctions,

of which the latter, and particularly the adherens junction component,

vascular endothelial (VE)-cadherin,

are of central importance for the initiation and stabilization of cell–cell contacts.

Although multiple adhesion molecules are localized at endothelial junctions,

  • blocking the adhesive function of VE-cadherin using antibodies
  • is sufficient to disrupt endothelial junctions and
  • to increase endothelial monolayer permeability both in vitro and in vivo.

Like other cadherins, VE-cadherin mediates adhesion via

  • homophilic, calcium-dependent interactions.

This cell–cell adhesion

is strengthened by binding of cytoplasmic proteins, the catenins,

to the C-terminus of VE-cadherin.

VE-cadherin can directly bind

  • β-catenin and plakoglobin, which
  • both associate with the actin binding protein α-catenin.

Initially, α-catenin was thought to directly anchor cadherins to the actin cytoskeleton, but recently it became clear that

  • α-catenin cannot bind to both β-catenin and actin simultaneously.

Numerous lines of evidence indicate that p120-catenin

  • promotes VE-cadherin surface expression and stability at the plasma membrane.

Different models are proposed that describe how

  • p120-catenin regulates cadherin membrane dynamics, including the hypothesis
  • that p120-catenin functions as a ‘cap’ that prevents the interaction of VE-cadherin
  • with the endocytic membrane trafficking machinery.

In addition, p120-catenin might regulate VE-cadherin internalization

  • through interactions with small GTPases.

Cytoplasmic p120-catenin, which is not bound to VE-cadherin, has been shown to

decrease RhoA activity,

elevate active Rac1 and Cdc42, and thereby is thought

to regulate actin cytoskeleton organization and membrane trafficking.

The intact cadherin-catenin complex is required for proper functioning of the adherens junction.

Several mechanisms may be involved in the

  • regulation of the organization and function of the cadherin–catenin complex, including
  1. endocytosis of the complex,
  2. VE-cadherin cleavage and
  3. actin cytoskeleton reorganization.

The remainder of this review primarily focuses on the

role of tyrosine phosphorylation in the control of VE-cadherin-mediated cell–cell adhesion.

Regulation of the adhesive function of VE-cadherin by tyrosine phosphorylation

It is a widely accepted concept that tyrosine phosphorylation of

  • components of the VE–cadherin-catenin complex
  • Correlates with the weakening of cell–cell adhesion.

A general idea has emerged that

tyrosine phosphorylation of the VE-cadherin complex

leads to the uncoupling of VE-cadherin from the actin cytoskeleton

through dissociation of catenins from the cadherin.

However, tyrosine phosphorylation of VE-cadherin

  • is required for efficient transmigration of leukocytes.

This suggests that VE-cadherin-mediated cell–cell contacts

1.are not just pushed open by the migrating leukocytes, but play

2.a more active role in the transmigration process.

A schematic overview of leukocyte adhesion-induced signals leading to VE-cadherin phosphorylation

Regulation of the integrity of endothelial cell–cell contacts by phosphorylation of VE-cadherin.

Regulation of the integrity of endothelial cell–cell contacts by phosphorylation of VE-cadherin

Regulation of the integrity of endothelial cell–cell contacts by phosphorylation of VE-cadherin

N-glycosylation status of E-cadherin controls cytoskeletal dynamics through the organization of distinct β-catenin- and γ-catenin-containing AJs

N-glycosylation of E-cadherin has been shown to inhibit cell–cell adhesion.

Specifically, our recent studies have provided evidence that

  • the reduction of E-cadherin N-glycosylation
  • promoted the recruitment of stabilizing components,
  • vinculin and serine/ threonine protein phosphatase 2A (PP2A), to adherens junctions (AJs)
  • and enhanced the association of AJs with the actin cytoskeleton.

Here, we examined the details of how

N-glycosylation of E-cadherin affected the molecular organization of AJs and their cytoskeletal interactions.

Using the hypoglycosylated E-cadherin variant, V13, we show that

V13/β-catenin complexes preferentially interacted with PP2A and with the microtubule motor protein dynein.

This correlated with dephosphorylation of the microtubule-associated protein tau, suggesting that

increased association of PP2A with V13-containing AJs promoted their tethering to microtubules.

These studies provide the first mechanistic insights into how N-glycosylation of E-cadherin drives changes in AJ composition through

  • the assembly of distinct β-catenin- and γ-catenin-containing scaffolds that impact the interaction with different cytoskeletal components

Cytoskeletal Basis of Ion Channel Function in Cardiac Muscle

MacKinnon. Fig 1  Ion channels exhibit three basic properties

MacKinnon. Fig 1 Ion channels exhibit three basic properties

In order to contract and accommodate the repetitive morphological changes induced by the cardiac cycle, cardiomyocytes

depend on their highly evolved and specialized cytoskeletal apparatus.

Defects in components of the cytoskeleton, in the long term,

affect the ability of the cell to compensate at both functional and structural levels.

In addition to the structural remodeling,

the myocardium becomes increasingly susceptible to altered electrical activity leading to arrhythmogenesis.

The development of arrhythmias secondary to structural remodeling defects has been noted, although the detailed molecular mechanisms are still elusive.

subjects with severe left ventricular chamber dilation such as in DCM can have left bundle branch block (LBBB), while right bundle branch block (RBBB) is more characteristic of right ventricular failure.  LBBB and RBBB have both been repeatedly associated with AV block in heart failure.

The impact of volume overload on structural and electro-cardiographic alterations has been noted in cardiomyopathy patients treated with left ventricular assist device (LVAD) therapy, which puts the heart at mechanical rest.

In LVAD-treated subjects,

QRS- and both QT- and QTc duration decreased,

suggesting that QRS- and QT-duration are significantly influenced by mechanical load and

that the shortening of the action potential duration contributes to the improved contractile performance after LVAD support.

An early postoperative period study after cardiac unloading therapy in 17 HF patients showed that in the first two weeks after LVAD implantation,

HF was associated with a relatively high incidence of ventricular arrhythmias associated with QTc interval prolongation.

In addition, a recent retrospective study of 100 adult patients with advanced HF, treated with an axial-flow HeartMate LVAD suggested that

  • the rate of new-onset monomorphic ventricular tachycardia (MVT) was increased in LVAD treated patients compared to patients given only medical treatment,

The myocardium is exposed to severe and continuous biomechanical stress during each contraction-relaxation cycle. When fiber tension remains uncompensated or simply unbalanced,

it may represent a trigger for arrhythmogenesis caused by cytoskeletal stretching,

which ultimately leads to altered ion channel localization, and subsequent action potential and conduction alterations.

Cytoskeletal proteins not only provide the backbone of the cellular structure, but they also

maintain the shape and flexibility of the different sub-cellular compartments, including the

1.plasma membrane,

2.the double lipid layer, which defines the boundaries of the cell and where

ion channels are mainly localized.

The interaction between the sarcomere, which is the basic for the passive force during diastole and for the restoring force during systole.

Sarcomeric Proteins and Ion Channels

besides fiber stretch associated with mechanical and hemodynamic impairment, cytoskeletal alterations due to primary genetic defects or indirectly to alterations in response to cellular injury can potentially

1.affect ion channel anchoring, and trafficking, as well as

2.functional regulation by second messenger pathways,

3.causing an imbalance in cardiac ionic homeostasis that will trigger arrhythmogenesis.

Intense investigation of

the sarcomeric actin network,

the Z-line structure, and

chaperone molecules docking in the plasma membrane,

has shed new light on the molecular basis of

  • cytoskeletal interactions in regulating ion channels

Actin disruption using cytochalasin D, an agent that interferes with actin polymerization, increased Na+ channel activity in 90% of excised patches tested within 2 min, which indicated that

the integrity of the filamentous actin (F-actin) network was essential for the maintenance of normal Na+ channel function

These data were the first to support a role for the cytoskeleton in cardiac arrhythmias.

Molecular interactions between the cytoskeleton and ion channels

The figure illustrates the interactions between the ion channels on the sarcolemma, and the sarcomere in cardiac myocytes. Note that the Z-line is connected to the cardiac T-tubules. The diagram illustrates the complex protein-protein interactions that occur between structural components of the cytoskeleton and ion channels. The cytoskeleton is involved in regulating the metabolism of ion channels, modifying their expression, localization, and electrical properties.

sarcomere structure

sarcomere structure

It is important to be aware of the enormous variety of clinical presentations that derive from distinct variants in the same pool of genetic factors. Knowledge of these variants could facilitate tailoring the therapy of choice for each patient. In particular,

the recent findings of structural and functional links between

the cytoskeleton and ion channels

could expand the therapeutic interventions in

arrhythmia management in structurally abnormal myocardium, where aberrant binding

between cytoskeletal proteins can directly or indirectly alter ion channel function.

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Preface to Metabolomics as a Discipline in Medicine

Author: Larry H. Bernstein, MD, FCAP


The family of ‘omics fields has rapidly outpaced its siblings over the decade since
the completion of the Human Genome Project.  It has derived much benefit from
the development of Proteomics, which has recently completed a first draft of the
human proteome.  Since genomics, transcriptomics, and proteomics, have matured
considerably, it has become apparent that the search for a driver or drivers of cellular signaling and metabolic pathways could not depend on a full clarity of the genome. There have been unresolved issues, that are not solely comprehended from assumptions about mutations.

The most common diseases affecting mankind are derangements in metabolic
pathways, develop at specific ages periods, and often in adulthood or in the
geriatric period, and are at the intersection of signaling pathways.  Moreover,
the organs involved and systemic features are heavily influenced by physical
activity, and by the air we breathe and the water we drink.

The emergence of the new science is also driven by a large body of work
on protein structure, mechanisms of enzyme action, the modulation of gene
expression, the pH dependent effects on protein binding and conformation.
Beyond what has just been said, a significant portion of DNA has been
designated as “dark matter”. It turns out to have enormous importance in
gene regulation, even though it is not transcriptional, effected in a
modulatory way by “noncoding RNAs.  Metabolomics is the comprehensive
analysis of small molecule metabolites. These might be substrates of
sequenced enzyme reactions, or they might be “inhibiting” RNAs just
mentioned.  In either case, they occur in the substructures of the cell
called organelles, the cytoplasm, and in the cytoskeleton.

The reactions are orchestrated, and they can be modified with respect to
the flow of metabolites based on pH, temperature, membrane structural
modifications, and modulators.  Since most metabolites are generated by
enzymatic proteins that result from gene expression, and metabolites give
organisms their biochemical characteristics, the metabolome links
genotype with phenotype.

Metabolomics is still developing, and the continued development has
relied on two major events. The first is chromatographic separation and
mass  spectroscopy (MS), MS/MS, as well as advances in fluorescence
ultrasensitive optical photonic methods, and the second, as crucial,
is the developments in computational biology. The continuation of
this trend brings expectations of an impact on pharmaceutical and
on neutraceutical developments, which will have an impact on medical
practice. What has lagged behind, and may continue to contribute to the
lag is the failure to develop a suitable electronic medical record to
assist the physician in decisions confronted with so much as yet,
hidden data, the ready availability of which could guide more effective
diagnosis and management of the patient. Put all of this together, and
we can meet series challenges as the research community
interprets and integrates the complex data they are acquiring.


Read Full Post »

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.


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


Part 4

Cancer Research

Part 5

Metabolic Syndrome

Part 6


Part 7

Epigenetics and Drug Metabolism

Part 8


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.


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



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:

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.


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.

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

Universitt Mainz. “Vesicles influence function of nerve cells.” ScienceDaily. ScienceDaily, 6 October 2014.

Neuroscientists use snail research to help explain “chemo brain”

It is estimated that as many as half of patients taking cancer drugs experience a decrease in mental sharpness. While there have been many theories, what causes “chemo brain” has eluded scientists.

In an effort to solve this mystery, neuroscientists at The University of Texas Health Science Center at Houston (UTHealth) conducted an experiment in an animal memory model and their results point to a possible explanation. Findings appeared in The Journal of Neuroscience.

In the study involving a sea snail that shares many of the same memory mechanisms as humans and a drug used to treat a variety of cancers, the scientists identified

  • memory mechanisms blocked by the drug.

Then, they were able to counteract or

  • unblock the mechanisms by administering another agent.

“Our research has implications in the care of people given to cognitive deficits following drug treatment for cancer,” said John H. “Jack” Byrne, Ph.D., senior author, holder of the June and Virgil Waggoner Chair and Chairman of the Department of Neurobiology and Anatomy at the UTHealth Medical School. “There is no satisfactory treatment at this time.”

Byrne’s laboratory is known for its use of a large snail called Aplysia californica to further the understanding of the biochemical signaling among nerve cells (neurons).  The snails have large neurons that relay information much like those in humans.

When Byrne’s team compared cell cultures taken from normal snails to

  • those administered a dose of a cancer drug called doxorubicin,

the investigators pinpointed a neuronal pathway

  • that was no longer passing along information properly.

With the aid of an experimental drug,

  • the scientists were able to reopen the pathway.

Unfortunately, this drug would not be appropriate for humans, Byrne said. “We want to identify other drugs that can rescue these memory mechanisms,” he added.

According the American Cancer Society, some of the distressing mental changes cancer patients experience may last a short time or go on for years.

Byrne’s UT Health research team includes co-lead authors Rong-Yu Liu, Ph.D., and Yili Zhang, Ph.D., as well as Brittany Coughlin and Leonard J. Cleary, Ph.D. All are affiliated with the W.M. Keck Center for the Neurobiology of Learning and Memory.

Byrne and Cleary also are on the faculty of The University of Texas Graduate School of Biomedical Sciences at Houston. Coughlin is a student at the school, which is jointly operated by UT Health and The University of Texas MD Anderson Cancer Center.

The study titled “Doxorubicin Attenuates Serotonin-Induced Long-Term Synaptic Facilitation by Phosphorylation of p38 Mitogen-Activated Protein Kinase” received support from National Institutes of Health grant (NS019895) and the Zilkha Family Discovery Fellowship.

Doxorubicin Attenuates Serotonin-Induced Long-Term Synaptic Facilitation by Phosphorylation of p38 Mitogen-Activated Protein Kinase

Source: Univ. of Texas Health Science Center at Houston

Doxorubicin Attenuates Serotonin-Induced Long-Term Synaptic Facilitation by Phosphorylation of p38 Mitogen-Activated Protein Kinase

Rong-Yu Liu*,  Yili Zhang*,  Brittany L. Coughlin,  Leonard J. Cleary, and  John H. Byrne   +Show Affiliations
The Journal of Neuroscience, 1 Oct 2014, 34(40): 13289-13300;

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


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

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).

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…

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

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

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

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)

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.

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. (, 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.

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;

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



  • 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).



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.



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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