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Posts Tagged ‘Chromatin’


Effect of mitochondrial stress on epigenetic modifiers

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Early Mitochondrial Stress Alters Epigenetics, Secures Lifelong Health Benefits

GEN 5/3/2016  http://www.genengnews.com/gen-news-highlights/early-mitochondrial-stress-alters-epigenetics-secures-lifelong-health-benefits/81252685/

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

Highlights
  • 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
http://dx.doi.org/10.1016/j.cell.2016.04.011             Publication stage: In Press Corrected Proof
Highlights
  • 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.”

more…

“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
https://whyevolutionistrue.wordpress.com/2016/05/05/the-new-yorker-screws-up-big-time-with-science-researchers-criticize-the-mukherjee-piece-on-epigenetics/

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

Introduction

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.

…..more

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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Schizophrenia genomics

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Histone Methylation at H3K9; Evidence for a Restrictive Epigenome in Schizophrenia

Schizophr Res. 2013 Sep; 149(0): 15–20.      doi:  10.1016/j.schres.2013.06.021

Epigenetic changes are stable and long-lasting chromatin modifications that regulate genomewide and local gene activity. The addition of two methyl groups to the 9th lysine of histone 3 (H3K9me2) by histone methyltransferases (HMT) leads to a restrictive chromatin state, and thus reduced levels of gene transcription. Given the numerous reports of transcriptional down-regulation of candidate genes in schizophrenia, we tested the hypothesis that this illness can be characterized by a restrictive epigenome.

METHODS   We obtained parietal cortical samples from the Stanley Foundation Neuropathology Consortium and lymphocyte samples from the University of Illinois at Chicago (UIC). In both tissues we measured mRNA expression of HMTs GLP, SETDB1 and G9a via real-time RT-PCR and H3K9me2 levels via western blot. Clinical rating scales were obtained from the UIC cohort.

RESULTS   A diagnosis of schizophrenia is a significant predictor for increased GLP, SETDB1 mRNA expression and H3K9me2 levels in both postmortem brain and lymphocyte samples. G9a mRNA is significantly increased in the UIC lymphocyte samples as well. Increased HMT mRNA expression is associated with worsening of specific symptoms, longer durations of illness and a family history of schizophrenia.

CONCLUSIONS   These data support the hypothesis of a restrictive epigenome in schizophrenia, and may associate with symptoms that are notoriously treatment resistant. The histone methyltransferases measured here are potential future therapeutic targets for small molecule pharmacology, and better patient prognosis.

Schizophrenia is conceptualized as a disorder of gene transcription and regulation. Consequently, chromatin is the ideal scaffold to examine this manifested pathophysiology of schizophrenia, as it constitutes the interface between the underlying genetic code and its surrounding biochemical environment. Through post-transcriptional modifications of histone proteins, gene expression can be either transcriptionally active in a ‘euchromatic’ environment, temporarily quieted in ‘facultative heterochromatin,’ or completely silenced in ‘constitutive heterochromatin’ (Zhang and Reinberg 2001). Post-translational modifications to lysine 9 of the H3 protein (H3K9) are uniquely able to reflect these three levels of transcriptional regulation. H3K9 modifications located in the promoter regions of actively transcribed genes are often acetylated (H3K9acetyl). Conversely, quieted transcription in gene-rich areas of the genome are often associated with mono- or dimethyl H3K9 (H3K9me2), while completely silenced areas of the genome are associated with trimethylated H3K9 (H3K9me3). In particular, the formation of H3K9me2 is catalyzed by histone methyltransferases (HMTs), including Eu-HMTase2 (G9a), Eu-HMTase1 (GLP), and SETDB1 (Krishnan et al. 2011) The different degrees of lysine methylation are possible due to the cooperation of these HMTs, which are able to form large heteromeric complexes (Fritsch et al. 2010).

H3K9 methylation has not been extensively studied in the brain, and until recently the regulation and role of the enzymes responsible for its formation were not known. Postnatal, neuronal-specific GLP/G9a knockdown produces a significant decrease in global H3K9me2 levels and inappropriate gene expression, leading to deficits in learning, reduction in exploratory behaviors and motivation in mice (Schaefer et al. 2009; Shinkai and Tachibana 2011;Tachibana et al. 2005;Tzeng et al. 2007). In humans, deletions or loss-of-function mutations of G9a results in Kleefstra Syndrome, characterized by a severe learning disability and developmental delay (Nillesen et al. 2011; Kleefstra et al. 2005). In humans, increased SETDB1 mRNA expression and resultant elevated H3K9me3 levels have been documented in Huntington Disease (HD) (Ryu et al. 2006; Fox et al. 2004).

A hallmark of schizophrenia is aberrant gene regulation, with the vast majority of studies reporting a down-regulation of gene transcription, suggesting that the epigenome of patients with schizophrenia is restrictive (Akbarian et al. 1995;Guidotti et al. 2000;Fatemi et al. 2005; Impagnatiello et al. 1998; Jindal et al. 2010). Postmortem brain studies indicate a reduction of an open histone modification, H3K4me3, and elevated expression of the histone deacetylase HDAC1 mRNA expression (Cheung et al. 2010; Sharma et al. 2008). The use of peripheral blood mononuclear cells as a reflection of overall chromatin state or at particular gene promoters has been successfully implemented in clinical studies of subjects afflicted depression, alcoholism, and schizophrenia. Peripheral blood cell studies have indicated that schizophrenia is associated with an abnormally condensed chromatin structure; (Issidorides et al. 1975; Kosower et al. 1995) specifically increased restrictive H3K9me2 and reduced H3K9 acetylation (Gavin et al. 2009b). Additionally, H3K9 acetylation in schizophrenia patients is less responsive to in vivo treatment with HDAC inhibitors when compared to both patients with bipolar disorder and nonpsychiatric controls (Sharma et al. 2006;Gavin et al. 2008). Finally, a correlation exists between age of onset of psychiatric symptoms of schizophrenia and baseline levels of H3K9me2 (Gavin et al. 2009b). It is the hypothesis of this paper that schizophrenia can be characterized by a restrictive epigenome, which is observable in both brain and peripheral blood, and has specific and observable effects on psychopathology. We have focused on levels of H3K9me2, indicative of facultative heterochromatin, and the enzymes that catalyze this modification, in patients with schizophrenia to examine their role in this illness.

3.1. mRNA Levels of HMT Gene Expression

We performed a multiple linear regression with each HMT gene of interest as the dependent variable. For postmortem brain tissue we examined sex, age, pH, RIN and diagnosis, whereas for lymphocytes we examined sex, age, and diagnosis as explanatory variables. In these two cohorts, we found that a diagnosis of schizophrenia is a significant predictor for GLP mRNA expression in both postmortem brain samples (β=0.44, F(1,24)=5.80, p<0.05), and in lymphocytes (β=−0.41, F(1,40)=7.91, p<0.01), indicating that patients with schizophrenia demonstrated increased levels compared to nonpsychiatric controls (Fig. 1a). Similarly, a diagnosis of schizophrenia is also a significant predictor for increased SETDB1 mRNA levels in both postmortem brain samples (β=0.39, F(1, 24)=4.33,p<0.05), and in lymphocytes (β=0.37, F(1,40)=6.19, p<0.05; Fig. 1b). A diagnosis of schizophrenia is not a significant predictor for elevated G9a mRNA levels in postmortem brain samples (β=0.22, F(1,24)=1.22, p=ns), but is for lymphocytes (β=−0.317, F(1,40)=4.46, p<0.05; Fig. 1c).

Interestingly, in both postmortem tissue (r=0.79, p<0.001) and lymphocytes (r=0.54, p<0.001), GLP and SETDB1 mRNA expression are positively correlated (data not shown).

Fig. 1

mRNA expression in both postmortem parietal cortical samples from the Stanley Foundation Neuropathology Consortium (on the left) and lymphocyte samples from University of Illinois at Chicago (on the right) and a. GLP mRNA levels, b. G9a mRNA levels and

To establish whether there exist differences in HMT mRNA among schizophrenic patients taking psychotropic medication, and those who were not, we performed a second multiple linear regression analysis on each individual cohort. The overall or type-specific use of antipsychotic, antidepressant or mood stabilizing medication are not significant predictors of HMT mRNA levels in either the postmortem or the lymphocyte cohorts.

3.2. H3K9me2 levels in the Postmortem Brain

In a previously published study we documented elevated global H3K9me2 levels in lymphocytes obtained from schizophrenia patients compared to nonpsychiatric controls (Gavin et al. 2009b). In the current study we attempted to discern whether this abnormality in a restrictive histone modification is present in brain tissue from the SFNC cohort as well. We performed a multiple linear regression with H3K9me2 levels as the dependent variable, with sex, age, and diagnosis as explanatory variables. We found that diagnosis of schizophrenia is a significant predictor of H3K9me2 levels extracted from postmortem brain tissue (β=0.40, F(1,24)=4.58, p<0.05; Fig. 2). GLP (r=0.65, p<0.001) and SETDB1 (r=0.44,p<0.05) are positively correlated with H3K9me2 levels, as discovered through a Pearson Correlation (data not shown).

Fig. 2

H3K9me2 levels are significantly increased parietal cortical samples from patients with schizophrenia when compared to nonpsychiatric controls. Below graph, a representative western blot image is shown. All data is shown as a ratio of optical density …     
3.3. Clinical Correlates with Lymphocyte HMT mRNA Levels

Lymphocyte levels of G9a mRNA demonstrated a positive correlation with the PANSS negative subscale total (r=0.61, p<0.05; Fig. 3a), GLP mRNA is positively correlated with the PANSS general subscale total, (r=0.64, p<0.01; Fig. 3b), and SETDB1 mRNA is more highly expressed in patients with longer durations of illness compared to both normal controls and patients in the ‘first episode psychosis’ group (ANOVA, F(2,30)=3.66, p<0.01; Fig. 3c). Patients with a family history of schizophrenia also had significantly increased levels of lymphocyte SETDB1 mRNA (t18=2.52, p<0.05; Fig. 3d).

Fig. 3

Clinical Correlates with Lymphocyte HMT mRNA Levels a. A rise in G9a mRNA is significantly correlated with increasing PANSS negative subscale totals; p<0.05. b. GLP mRNA is significantly increased upon worsening of PANSS general subscale scores;
4. Discussion

The current paper demonstrates an increase in GLP and SETDB1 mRNA in both postmortem parietal cortex and lymphocyte samples from patients with schizophrenia, as well as an increase in G9a mRNA in lymphocytes. G9a and GLP are responsible for the bulk of H3K9me2 modifications across the genome (Shinkai and Tachibana 2011; Tachibana et al. 2005), and SETDB1 is the only euchromatic HMT to specifically di- and tri-methylate H3K9 (Zee et al. 2010;Wang et al. 2003), but all three of these HMTs are able to form large heteromeric complexes, thus allowing for the sequential degrees of lysine methylation (Fritsch et al. 2010). Further, we demonstrate that the ultimate outcome of their catalytic activity, H3K9me2, is significantly increased in patients with schizophrenia as compared to nonpsychiatric controls. Moreover, GLP and SETDB1 mRNA are positively correlated with H3K9me2 levels. These findings add gravity to our previous demonstration of increased H3K9me2 levels in lymphocytes from schizophrenic patients (Gavin et al. 2009b).

Our investigations into the role of H3K9me2 in schizophrenia pathophysiology, as opposed to other H3K9 modifications, were motivated by the hypothesis that initial inactivation of gene promoter activity at various schizophrenia candidate genes can result in gradual entrenchment of the heterochromatin state as a result of disease chronicity and disuse (Sharma et al. 2012). Areas of H3K9me2 can then act as a platform for additional restrictive adaptors, thus resulting in the spreading of heterochromatin across previously unmodified gene rich areas. As such, the gene altering effects of medications are unable to overcome this restrictive burden, leading to repeated medication failures (Sharma et al. 2012). Support for this hypothesis has been previously demonstrated, (Sharma et al. 2008; Benes et al. 2007) including the finding that schizophrenia patients clinically treated for four weeks with the HDAC inhibitor, valproic acid, displayed no increase in peripheral blood cell acetylated histones 3 or 4 as compared to bipolar patients (Sharma et al. 2006). Here, we find an increase in both H3K9me2 levels and the enzymes which catalyze this modification, providing additional evidence supporting an increased heterochromatin state in schizophrenia.

The major role of the parietal cortex is to integrate and evaluate sensory information (Andersen & Buneo, 2003; Cohen & Andersen, 2002). It is one of the last areas of the human brain to fully mature, (Geschwind, 1965) thus early life environmental insults could have a profound effect. Disordered thought, a common symptom in schizophrenia, is most likely explainable through disruption of this system (Torrey, 2007). Patients with schizophrenia report either acute (McGhie & Chapman, 1961) or blunted (Freedman, 1974) sensitivity to sensory stimuli, and demonstrate overall impairment of sensory integration (Manschreck & Ames, 1984; Torrey, 1980). Similar patterns of transcriptional regulation are observed across the cortex, consequently, results from the parietal cortex likely reflect patterns of gene transcription in other brain regions (Hawrylycz et al., 2012).

Due to its heterogeneity, examining schizophrenia as a binary measurement of illness when examining biological relevancy can be limiting (Arango et al. 2000;Buchanan and Carpenter 1994). Through utilizing the PANSS, biological underpinnings that do not demarcate cleanly with diagnostic categories, can be correlated directly with specific symptomatology. Correlations between methyltransferase enzymes and clinical symptomatology indicate that these restrictive enzymes could contribute to specific facets of the illness, particularly negative and general symptoms, which are particularly resistant to improvement. Increased severity of negative symptoms are correlated with poorer disease prognosis, (Wieselgren et al. 1996) and are not alleviated through our current regimen of psychotropics.

Additionally, SETDB1 mRNA levels are also correlated with other markers of a worse disease prognosis, including a more chronic form of the illness, and a history of schizophrenia in the family. Pharmacological targeting of increased levels of SETDB1improves motor performance and extends survival in HD mice, indicating the promise of treatments that modulate gene silencing mechanisms in neuropsychiatric disorders (Ryu et al. 2006).

The main weakness of this current study was that clinical symptoms were correlated with mRNA extracted from peripheral tissue. Enzymes relating specifically to synaptic function were not examined, but rather overall mechanisms of epigenetic regulation that are not tissue specific. While postmortem investigations are able to serve as a useful snapshot at the time of death, the ability to measure and monitor histone marks over time as marker of disease progression, improvement, or as a predictor of pharmacological response are only possible using peripheral blood cells. A strong rationale for the use of blood chromatin ‘levels’ as a type of biosensor that registers the epigenetic milieu has been proposed elsewhere (Sharma 2012). Furthermore, previous studies have indicated the mRNA patterns of expression patterns in lymphocytes are capable of distinguishing between psychiatric diagnostic groups (Middleton et al. 2005).

The present study hypothesized that schizophrenia may be due to abnormal regulation of fundamental epigenetic mechanisms, thus, we chose to measure overall levels of H3K9me2 opposed to specific gene promoters, based on the assumption that while the individual genes silenced in the brain and blood may not be the same, similar global pathogenic processes may be occurring in both tissues.

The results of this paper indicate that chromatin is more restrictive in patients with schizophrenia, and may be significantly contributing to disease pathology. If, through pharmacological interventions, a reduction in this histone hyper-restrictive insult in schizophrenia can be relaxed, inducing a type of “genome softening,” then neuronal gene expression can be enhanced, thus allowing for increased plasticity and improved therapeutic response (Sharma 2005).

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Balancing Histone Methylation Activities in Psychiatric Disorders

Alterations in histone lysine methylation and other epigenetic regulators of gene expression contribute to changes in brain transcriptomes in mood and psychosis spectrum disorders, including depression and schizophrenia. Genetic association studies and animal models implicate multiple lysine methyltransferases (KMTs) and demethylases (KDMs) in the neurobiology of emotion and cognition. Here, we review the role of histone lysine methylation and transcriptional regulation in normal and diseased neurodevelopment and discuss various KMTs and KDMs as potential therapeutic targets in the treatment of neuropsychiatric disease.

Schizophrenia and depression are major psychiatric disorders that lack consensus neuropathology and, in a large majority of cases, a straightforward genetic risk architecture. Furthermore, many patients on the mood and psychosis spectrum show an incomplete response to conventional pharmacological treatments which are mainly aimed at monoamine signaling pathways in the brain (Box 1).

Box 1  Schizophrenia and Depression

Schizophrenia affects 1% of the general population and typically begins during young-adult years, although cognitive disturbances could be evident much earlier. The disease is, in terms of genetics and etiology, highly heterogeneous, and increasingly defined as different and partially independent symptom complexes: (i) psychosis with delusions, hallucinations and disorganized thought; (ii) cognitive dysfunction including deficits in attention, memory and executive function; and (iii) depressed mood and negative symptoms including inability to experience pleasure (anhedonia), social withdrawal and poor thought and speech output [42]. Currently prescribed antipsychotics, which are mainly aimed at dopaminergic and/or serotonergic receptor systems, exert therapeutic effects on psychosis in approximately 75% of patients. However, it is the cognitive impairment which is often the more disabling and persistent feature of schizophrenia [42]. Currently there are no established pharmacological treatments for this symptom complex. However, given that cognitive dysfunction is an important predictor for long-term outcome, this area is considered a high priority in schizophrenia research, as reflected by initiatives combining efforts from government agencies, academia and industry, including MATRICS (the Measurement and Treatment Research to Improve Cognition in Schizophrenia) [42].

Affective disorders as a group show, in terms of genetic risk architecture, some overlap with schizophrenia. For example, rare structural variants, including the balanced translocation at the Disrupted-in-Schizophrenia 1 (DISC-1) locus (1q42) or the 22q11 deletion are, in different individuals, associated with either mood disorder or schizophrenia [81, 82].

Depression, including its more severe manifestation, major depressive disorder which has a lifetime risk of 10–15% for the U.S. general population, is associated with excessive sadness, anhedonia, negative thoughts, and neurovegetative symptoms including changes in sleep pattern and appetite [1]. The disorder, which in more severe cases is accompanied by delusions, hallucinations and other symptoms of psychosis, often takes a chronic and recurrent course. Conventional antidepressant therapies primarily target monoamine metabolism and reuptake mechanisms at the terminals of serotonergic, noradrenergic and dopaminergic neurons. Unfortunately, up to 40% of cases show an insufficient response to these pharmacological treatments [1]. In addition, many antipsychotic and antidepressant drugs have significant side effect burden, including weight gain, diabetes and metabolic defects, extrapyramidal symptoms and sexual dysfunction [83, 84].

However, there is evidence that dysregulated gene transcription, indicative of compromised neural circuitry, contributes to disordered brain function in psychosis and mood spectrum disorder [1, 2]. While no single gene transcript is consistently affected, alterations in RNA levels contribute to defects in GABAergic inhibitory neurotransmission and more generally, synapse organization and function, metabolism and mitochondrial functions, and oligodendrocyte pathology [35]. While a number of transcriptional and post-transcriptional mechanisms may contribute to these changes, chromatin-associated proteins and epigenetic regulators invoked in sustained alterations of gene expression and function (Box 2) could play a critical role in the pathophysiology, or treatment of mental illness [6,7]. Indeed, there is evidence that changes in acetylation of histone lysine residues, which are broadly associated with active gene expression [8] and considered a potential therapeutic target for cancer and other medical conditions [9], also impact gene expression patterns in the brain and thereby influence emotional and cognitive functions. For example, mice or rats exposed to systemic treatment, or localized intracranial injections of class I/II histone deacetylase inhibitors (HDACi) exhibit behavioral changes reminiscent of those elicited by conventional antidepressant drugs [1013]. The short chain fatty acid derivative valproic acid, widely prescribed for its mood-stabilizing and anticonvulsant effects, induces brain histone hyperacetylation at a select set of gene promoters when administered to animals at comparatively high doses [14]. Conversely, overexpression of selected HDACs in neuronal structures implicated in the neurobiology of depression, including the hippocampus, elicit a pro-depressant behavioral phenotype [12]. Similarly, animals treated with class I/II HDACi often show improved performance in learning and memory paradigms and furthermore, drug-induced inhibition or activation of class III HDAC (also known as sirtuins) elicits changes in motivational and reward-related behaviors [15]. Therefore, the orderly balance between histone acetyl-transferase and deacetylase activities is critical for cognitive performance and synaptic and behavioral plasticity [16]. Likewise, However, HDACs interfere with acetylation of many non-histone proteins in the nucleus and cytoplasm [16], and moreover, some of these drugs carry a significant side effect burden [9]. Therefore, in light of the emerging role of epigenetic mechanisms in the neurobiology of these and other psychiatric conditions [6], the therapeutic potential of chromatin modifying drugs, other than the HDACi, warrants further investigations. This review will focus on histone lysine methylation, one of the most highly regulated chromatin markings in brain and other tissues. Multiple methyltransferases (KMTs) and demethylases (KDMs) were recently implicated in emotional and cognitive disorders (Fig. 1), and these types of chromatin modifying enzymes could emerge as novel targets in the treatment of mood and psychosis spectrum disorders.

Box 2  Epigenetic regulators and chromatin structure and function

Epigenetics, in the broader sense, applies both to dividing and postmitotic cells, and refers to a type of cellular memory that involves sustained changes in chromatin structure and function, including gene expression, in the absence of DNA sequence alterations (For in depth discussion, see [85]). Chromatin is essentially a repeating chain of nucleosomes comprised of genomic DNA wrapped around an octamer of core histones H2A/H2B/H3/H4. The histone proteins are intensely decorated with epigenetic information, with more than 70 (amino acid) residue-specific sites subject to various types of post-translational modifications (PTM). These include lysine (K) acetylation, methylation and poly ADP-ribosylation, arginine (R) methylation, and serine (S), threonine (T), tyrosine (Y) and histidine (H) phosphorylation [86]. In addition, a subset of the histone H2A, H2B and H4 lysines are covalently linked to the small protein modifiers ubiquitin and SUMO [87, 88]. Finally, epigenetic markings in genomic DNA include 5-methyl-cytosine and the related form, 5-hydroxy-methyl-cytosine [85]. These DNA and nucleosomal histone markings define the functional architecture of chromatin (see main text).

Proteins associated with methylation and other histone PTM are typically defined either as ‘writers’, ‘erasers’ or ‘readers’, essentially differentiating between the process of establishing or removing a mark as opposed to providing a docking site for chromatin remodeling complexes that regulate transcription, or induce and maintain chromatin condensation [18, 86, 89]. As it pertains to the brain, especially in the context of neuropsychiatric disease, a substantial body of knowledge has been generated for a select set of site-specific (K) methyltransferases and demethylases (Fig. 1A). In contrast, many PTMs are recognized by large numbers of reader proteins [90], but to date only very few of these readers have been explored in the brain. To mention just two examples, there are approximately 75 reader proteins specifically associated with histone H3-trimethyl-lysine 4 (H3K4me3), including several components of the SAGA complex ascribed with a key role for transcriptional initiation at RNA polymerase II target genes [90]. In contrast, H3K9me3, generally considered a repressive mark, provides a central hub for heterochromatin (associated) proteins including several members of the HP1 family and zinc finger domain containing molecules [90]. There is additional complexity because pluripotent stem cells and additional cell types decorate many of their promoters with ‘bivalent domains’ which include both open chromatin-associated (methylated H3K4 and H3/H4 acetylation) and repressive (methylated H3K27) marks [91, 92].

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Regulation of histone (K) methylation. (A) Listings of residue-specific KMTs and KDMs for H3K4/9/27/36/79 and H4K20. The majority of KMT and KDM are highly specific for a single histone residue, while a few enzymes target multiple residues, as indicated. Red marked KMT/KDM are implicated in neurodevelopment or psychiatric disease as discussed in main text. The non-catalytic JARID2 regulates activity and function of related KMTs. (B) Simplified scheme for selected mono- and trimethylated histone lysine markings implicated in transcriptional regulation, silencing and enhancer function.

The methylation of lysine and arginine residues, like other histone PTM, define chromatin states and function [8, 17]. To date, more than 20 methyl-marks on K and R residues have been described [18, 19]. As it pertains to the lysines, the majority of studies focused on the regulation and methylation-related functions of six specific sites: H3K4, H3K9, H3K27, H3K36, H3K79 and H4K20 [18]. For H3K4 and H3K9/K27, there is additional complexity because specific information is also conveyed (i) for H3K4, the unmethylated lysine effectively serving as a DNA methylation signal [20, 21], and (ii) for H3K9/K27 acetylation as an alternative PTM [22, 23] (Fig. 1A). For the aforementioned H3/H4 residues, specific biological functions and their interrelations with functional chromatin states, including transcriptional initiation and elongation, heterochromatic silencing and other mechanisms, have been described for the trimethyl-, and for some of the mono- and dimethyl-modifications (Representative examples are provided in Fig. 1B. See ref [17] for a detailed description of the histone methylation code and its relation to other types of histone PTM).

The following examples further illustrate the complex regulation of histone lysine methylation. Monomethylation of histone H3-lysine 4 (H3K4me1) plays an important role in neuronal activity-induced transcription at enhancer sequences [24], but the related forms, H3K4me3/2 are primarily found at the 5′ end of genes, with H3K4me3 mostly arranged as distinct and sharp peaks within 1–2Kb of transcription start sites. The H3K4me3 mark provides a docking site at the 5′ end of genes for chromatin remodeling complexes that either facilitate or repress transcription [25]. Furthermore, mono-methyl-H4-K20 shows strong positive correlation with gene expression at promoters enriched with CpGs, which contrasts to the trimethylated form of the same residue which generally is associated with repressed chromatin [23]. Taken together, these examples illustrate that even closely related histone lysine methylation markings are potentially associated with very different chromatin states.

To date, H3K4, H4K9, H3K27 and H4K20 methylation signals were measured at specific loci and genome-wide in human brain, essentially confirming that each of these epigenetic markings defines the same type of chromatin as in the peripheral tissues or animal brain [2630]. Interestingly, a subset of psychotherapeutic drugs including the mood-stabilizer valproate, the atypical antipsychotic clozapine and some monoamine oxidase inhibitors and stimulant drugs interfere with brain histone methylation (Table 1).

Molecular mechanisms of histone (lysine) methylation

A complex system of site-specific methyltransferases, which transfer the methyl-group of S-Adenosyl-Methionine (SAM) to lysine residues, has evolved in the vertebrate cell. There are an estimated 70 human genes harboring the Su(var)3–9,Enhancer of Zeste,Trithorax (SET) domain, which spans approximately 130 amino acids essential for KMT enzymatic activity [31]. The only known exception is the H3K79-specific methyltransferase, KMT4/DOT1L [31, 32], which lacks a SET. Each of the histone K residues discussed above is the preferential target of a distinct set of methyltransferase proteins (Fig. 1A)[19]. Of note, these histone-modifying enzymes are thought not to access histone substrates directly unless recruited by DNA-bound activators and repressors, a mechanism which could target each methyltransferase to a highly specific set of genomic loci [19].

An equally complex system exists for the site-specific lysine demethylases (Fig. 1A). There are at least two different mechanisms for active histone demethylation. The first enzyme type, represented by lysine-specific demethylase 1 (LSD1/KDM1A), contains an amine oxidase domain and requires flavin adenine dinucleotide (FAD) as a cofactor to demethylate di- and mono-methylated lysines. LSD1 and its homologue, LSD2, are primarily H3K4 demethylases, albeit depending on species and context, and activity against H3K9 also has been described [18]. Interestingly, monoamine oxidase inhibitors (MAOi) such as tranylcypromine or phenelzine — powerful antidepressants that exert their therapeutic effects mainly by elevating brain monoamine levels through inhibition of MAO-A/B — also block LSD1 type histone demethylases [18]. While LSD1 is thought to regulate histone methylation at promoters, LSD2 is bound to transcriptional elongation complexes and removes H3K4 methyl markings in gene bodies, thereby facilitating gene expression by reducing spurious transcriptional initiation outside of promoters [33]. The second type of demethylase, which in contrast to LSD1/LSD2 is capable of demethylating trimethyl markings, involves Fe2+-dependent dioxygenation by Jumonji-C (JmJC) domain-mediated catalysis [18]. Given that each of the KMTs and KDMs described has a different combinatorial set of functional domains and (protein) binding partners [18, 34], it is likely that the various site-specific methyltransferases and demethylases are largely non-redundant in function.

KMTs and KDMs with a role in cognition and neuropsychiatric disease

An increasing number of KMTs and KDMs are implicated in neurodevelopment and major psychiatric diseases (marked in red in Fig. 1A).

H3K4

The first histone lysine methyltransferase explored in the nervous system was KMT2A/MLL1, a member of the mixed-lineage leukemia (MLL) family of molecules. Mice heterozygous for an insertional (lacZ) loss-of-function Mll1mutation show distinct abnormalities in hippocampal plasticity and signaling [35], in conjunction with defects of learning and memory [36]. Of note, the hippocampus, and other portions of the forebrain including prefrontal cortex and ventral striatum, are frequently implicated in the neural circuitry of mood and psychosis spectrum disorders [1]. Furthermore, conditional deletion of Mll1resulted in defective neurogenesis during the early postnatal period [37]. While the full spectrum of MLL1 target genes in neurons and glia awaits further investigation, dysregulated expression of certain transcription factors such as DLX2, a key regulator for the differentiation of forebrain GABAergic neurons (which are essential for inhibitory neurotransmission and orderly synchronization of neural networks) [38], may contribute to the cognitive phenotype of the Mll1mutant mice. These observations may be relevant for the pathophysiology of schizophrenia, because some patients show in the prefrontal cortex a deficit in H3K4-trimethylation and gene expression at a subset of GABAergic promoters, including GAD1 encoding a GABA synthesis enzyme [28]. While the timing and age-of-onset for this ‘molecular lesion’ remains unknown, it is of interest that in the normal PFC, H3K4 methylation at the site of GABAergic genes progressively increases during the transition from fetal period to childhood to adulthood [28]. The epigenetic vulnerability of the Gad1 promoter during such prolonged developmental periods is further emphasized by recent animal studies demonstrating that Gad1-DNA methylation and histone acetylation are heavily influenced by the level of maternal care in the neonatal period/pre-weanling period [39].

There is additional evidence that epigenetic fine-tuning of the brain’s H3K4 methyl-markings is critical for orderly neurodevelopment. Of note, loss-of-function mutations in KDM5C/JARID1C/SMCX, an X-linked gene encoding a H3K4 demethylase, have been linked to mental retardation [40] and autism spectrum disorders [41]. The KDM5C gene product operates in a chromatin remodeling complex together with HDAC1/2 histone deacetylases and the transcriptional repressor REST, thereby poising neuron-restrictive silencer elements for H3K4 demethylation and decreased expression of target genes including synaptic proteins and sodium channels [40]. However, because this study was conducted with the HeLa cell line, it remains to be determined whether similar mechanisms operate in the nervous system.

In addition to its role in neurodevelopment, MLL-mediated H3K4 methylation could play a potential role for the treatment of psychosis. The atypical antipsychotic clozapine, which has a somewhat higher therapeutic efficacy when compared to conventional antipsychotics that function primarily as dopamine D2 receptor antagonists [42], upregulates H3K4 tri-methylation at the Gad1/GAD1GABA synthesis enzyme gene promoter. These effects were not mimicked in dopamine receptors D2/D3 (Drd2/3) compound null mutant mice, suggesting that blockade of dopamine D2-like receptors is not sufficient for clozapine-induced H3K4 methylation [28]. In the human PFC, GAD1-associated H3K4 methylation was increased in subjects exposed to clozapine, as compared to subjects treated with conventional antipsychotics. Conversely, mice heterozygous for the H3K4-specific KMT, mixed-lineage leukemia 1 (MLL1), exhibited decreased H3K4 methylation at brain Gad1 [28]. Therefore, it is possible that MLL1, which is highly expressed in GABAergic and other neurons of the adult cerebral cortex [28], will in the future emerge as a novel target for the treatment of psychosis. Questions that remain to be resolved include (i) the molecular pathways linking clozapine — a drug that impacts dopaminergic, serotonergic, muscarinic and other signaling pathways — to MLL1-mediated histone methylation, and (ii) whether or not the clozapine-induced changes in H3K4 methylation are restricted to GABAergic gene promoters or, alternatively, the reflection of more widespread epigenetic changes throughout the genome. Of note, clozapine’s effects on H3K4 methylation require intact brain circuitry and cannot be mimicked in cultured neurons differentiated from forebrain progenitor cells [43]. This finding is in good agreement with the recent observation that some of clozapine’s therapeutic effects require an intact serotonergic system, particularly its presynaptic components [44].

H3K9

The 9q34 subtelomeric deletion syndrome, which includes mental retardation and other developmental defects, is caused by deleterious mutations and haploinsufficiency of euchromatin histone methyltransferase 1 (EHMT1, also known as GLP and KMT1D) [45]. This gene encodes a H3K9-specific methyltransferase that operates in a multimeric complex that includes its closest homologue, G9a/KMT1C, and additional H3K9-specific HMTs [46]. Studies in mutant mice suggest that the GLP/G9a complex is important for suppression of non-neuronal and progenitor genes in mature neurons, and loss of this complex has deleterious effects on cognition and other higher brain functions [47]. Furthermore, G9a-mediated H3K9 methylation events within the reward circuitry, including the ventral striatum, are critical intermediates for the long-term effects of cocaine on reward behavior and neuronal morphology [48]. This would suggest that GLP/G9a, and proper regulation of H3K9 levels, is important for orderly brain function both in developing and mature brain.

Furthermore, changes in motivational and affective behaviors could be elicited by overexpression of the H3K9-HMT, SET domain bifurcated 1 (KMT1C/SETDB1/ESET), in adult forebrain neurons [49]. Interestingly, SETDB1 occupancy in neuronal chromatin is highly restricted, and may be confined to less than 0.75% of annotated genes [49]. However, among these are several NMDA and other ionotropic glutamate receptor subunit genes, including Grin2a/b (Nr2a/b)[49]. Mild to moderate inhibition of NMDA receptor-mediated (including Grin2b) neurotransmission elicits a robust improvement of depressive symptoms in some mood disorder patients [50], and, indeed, SETDB1-mediated H3K9 methylation and repressive chromatin remodeling at the Grin2b locus was associated with antidepressant-like behavioral phenotypes in the Setdb1 transgenic mice [49]. Of note, NMDA receptor antagonists, including GRIN2B-specific drugs, elicit significant therapeutic benefits even in subjects who failed multiple trials of selective serotonin reuptake inhibitors (SSRI) and other conventional antidepressants [50]. However, drugs directly acting at the NMDA receptor site have an unfavorable side effect profile, and therapeutic strategies aimed at SETDB1 expression and activity may therefore provide an alternative strategy.

Interestingly, mice with a genetic ablation of Kap1, encoding the SETDB1 binding partner KRAB-associated protein 1, also known as TRIM28/TIF1b/KRIP1)[51], show increased anxiety and deficits in cognition and memory [52], which are phenotypes that are broadly opposite from those observed in mice with increasedSetdb1 expression in brain [49]. These findings further speak to the therapeutic potential of the Kap1-Setdb1 repressor complex in the context of neuropsychiatric disease.

Finally, the H3K9-specific demethylase, KDM3A/Jmjd1A, showed increased H3K9-methylation at its own promoter in the ventral striatum of mice exposed to social defeat (a type of stressor associated with a depression-like syndrome in these animals), while mice that were treated with a conventional antidepressant or that were resilient to this type of stress did not show changes in KDM3A promoter methylation [53]. While it is unclear whether KDM3A or some other demethylase acitivity is altered in the depressed animals, the same study [53] reported widespread repressive histone methylation changes, including increased dimethyl-H3K9 and methylated H3K27 at hundreds of gene promoters in stress susceptible animals, which further emphasizes the importance of these PTMs for the epigenetics of mood disorder.

H3K27

The H3K27-selective methyltransferase, KMT6A, also known as Enhancer of zeste homolog2 (EZH2), is associated with the polycomb repressive chromatin remodeling complex 2 (PRC2) [54], and essential for cortical progenitor cell and neuron production. Consequently, loss of EZH2 function is associated with severe thinning of the cerebral cortex and a disproportionate loss of neurons residing in upper cortical layers I–IV [55]. Likewise, the H3K27-specific demethylase, JMJD3, is important for neurogenesis and neuronal lineage commitment [56]. Furthermore, H3K27 methylation is dynamically regulated in mature brain and involved in the neurobiology of major psychiatric disease. For example, changes in expression of brain-derived neurotrophic factor (Bdnf) in hippocampus of mice exposed to environmental enrichment or chronic stress are associated with opposite changes in the H3K27me3 mark at a subset of Bdnf gene promoters [12,57]. In addition, acute stress leads to an overall decrease in hippocampal H3K27me3 and H3K9me3 [58]. Furthermore, in the orbitofrontal cortex of suicide completers, alterations in H3K27 methylation were described at the TRKB gene, encoding the high affinity receptor for the nerve growth factor molecule, BDNF [27]. Changes in the balance between histone H3K4 and H3K27 methylation, or DNA cytosine and H3K27 methylation may also contribute to GABAergic gene expression deficits in schizophrenia [28, 43]. To date it remains unclear which of the various H3K27-specific KMTs and KDMs (Fig. 1) are involved in these disease-related alterations in postmortem brain tissue. Of note, the Jumonji and Arid containing protein 2 (JARID2), which by itself lacks catalytic activity but is crucial for subsequent H3K27 or H3K9 methylation by recruiting the polycomb PRC2 complex to its target genes [59, 60], is located within the schizophrenia susceptibility locus on chromosome 6p22 and confers genetic risk in multiple populations of different ethnic origin [61, 62]. While the biological functions of JARID2 have been studied primarily in the context of transcriptional regulation in stem cells [63, 64], this gene shows widespread expression in the mature nervous system [65], implying JARID2-mediated control over polycomb repressive chromatin remodeling in the adult brain.

H3K36 and H4K20

Epigenetic dysregulation of nuclear receptor-binding SET domain containing protein 1/KMT3B could play a role in some neuro- and glioblastomas [66], but like for other H3K36 and H4K20 regulating enzymes (Fig. 1), to date little is known about their role in neurodevelopment, cognition and psychiatric disease. Strikingly, however, KMT3A/HYPB/SETD2, a member of the SET2 family of KMTs mediating H3K36 methylation [67], is also known as huntingtin-interacting protein 1 (HIP-1) or huntingtin(yeast)-interacting protein B (HYPB) [68]. Huntington’s is a triplet repeat disorder and chronic neurodegenerative condition with motor symptoms and cognitive defects, and significant changes in mood and affect [69]. Whether or not there is altered H3K36 methylation in the neuronal populations that are at risk for degeneration is unclear. Furthermore, the huntingtin/KMT3A interaction has been documented for yeast [68] but not brain. Of note, wildtype huntingtin is a facilitator of polycomb complex PCR2-mediated H3K27 methylation [70], and furthermore, H3K4 and H3K9 methylation changes have been reported in preclinical model systems and postmortem brains with Huntington’s disease [71, 72]. Therefore, it is possible that transcriptional dysregulation in this condition is associated with aberrant methylation patterns of multiple lysine residues.

KMTs and KDMs as Novel Drug Targets

Given the emerging role of histone methylation in the neurobiology of psychiatric disease, the next obvious question is whether this type of PTM could provide a target for a new generation of psychotropic therapeutics. In principle, KMTs and KDMs should provide fertile ground for the development of novel drugs, because these enzymes are considered more specific than, for example, HDACs, because each HDAC enzyme is likely to affect a much larger number of histone residues as compared to KMTs/KDMs [73]. However, like for other histone modifying enzymes, the specificity of KMTs and KDMs is not limited to histones but includes the (de)methylation of lysines of non-histone proteins, including the p53 tumor suppressor protein and the VEGF growth factor [74]. Druggable domains within the KMTs and KDMs could involve not only their catalytic sites, such as the SET domain for the KMTs or the amino oxidase and JmjC domains for the LSD1 and JMJD subtypes of KDMs, respectively, but also some of the many other functional domains that are specific to subsets of these proteins [75]. One potential candidate would be the bromodomain of the MLLs and other H3K4-specific methyltransferases [75]. Bromodomains, which are present in many different types of nuclear proteins, bind to acetylated histones and small molecules interfering with some of these interactions recently emerged as powerful modulators of systemic inflammation [76].

The catalytic activity of the SET domain containing KMTs requires the universal methyl donor, S-adenosyl-methionine (also known as AdoMET). Crystallographic and functional studies revealed that the SAM binding pocket of KMTs is different from the SAM pockets of other proteins, which may increase the chance to develop compounds which specifically target histone methyltransferases but not other enzymes and proteins [31]. Currently, however, no KMT or KDM related drug is in clinical trials. However, several of these compounds show therapeutic promise in preclinical studies. For example, the S-adenosylhomocysteine hydrolase inhibitor, 3-deazaneplanocin A (DZNep) induces apoptosis in breast cancer cells [77]. This drug alters H3K27 and H4K20 trimethylation via interference with polycomb PRC2 repressive chromatin remodeling [73]. Antioncogenic effects were also observed with BIX-01294, a drug that downregulates H3K9 methylation levels by binding to the SET domain of the G9a/GLP(EHMT1) methyltransferases [73]. The same drug was shown to alter addictive behaviors and H3K9 methylation when infused locally into the brain of cocaine-exposed mice [48]. As discussed above, while tranylcypromine and other monoamine oxidase inhibitors used for the treatment of depression are weak inhibitors of the LSD1 type of KDM, recently several compounds emerged with much stronger activity against LSD1/LSD2 [18]. It will be extremely interesting to explore these drugs in preclinical models for mood and psychosis spectrum disorders. Finally, microRNA-based therapeutic strategies, aimed at decreasing levels and expression of chromatin remodeling complexes, including some of the histone modifying enzymes discussed here, are gaining increasing prominence in the field of cancer therapy [73] and may in the future emerge as a novel therapeutic option in the context of neuropsychiatric disease.

Emerging Concept in DNA Methylation: Role of Transcription Factors in Shaping DNA Methylation Patterns
CLAIRE MARCHAL AND BENOIT MIOTTO*   Journal of Cellular Physiology Volume 230, Issue 4,  http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1097-4652

DNA methylation in mammals is a key epigenetic modification essential to normal genome regulation and development. DNA methylation patterns are established during early embryonic development, and subsequently maintained during cell divisions. Yet, discrete site-specific de novo DNA methylation or DNA demethylation events play a fundamental role in a number of physiological and pathological contexts, leading to critical changes in the transcriptional status of genes such as differentiation, tumor suppressor or imprinted genes. How the DNA methylation machinery targets specific regions of the genome during early embryogenesis and in adult tissues remains poorly understood. Here, we report advances being made in the field with a particular emphasis on the implication of transcription factors in establishing and in editing DNA methylation profiles. J. Cell. Physiol. 230: 743–751, 2015.

DNA methylation is a well-studied epigenetic modification in mammalian genomes, discovered in 1948. It is involved in a number of essential cellular processes such as transcription regulation, cellular differentiation, cellular identity maintenance, X inactivation, gene imprinting, and the cellular response to environmental changes (Klose and Bird, 2006; Guibert and Weber, 2013; Smith and Meissner, 2013; Subramaniam et al., 2014). DNA methylation has proved to be a dynamic process, requiring continuous regulation and potentially having an important regulatory role for tissuespecific differentiation or cellular signaling. Indeed, the analysis of the distribution of DNA methylation at the genome scale, and nowadays at the single-base resolution, in different physiological and pathological states, unraveled that local changes in DNA methylation contribute to cell-type specific variation in gene expression. Furthermore, aberrant DNA methylation patterns are documented in a number of human diseases from Immunodeficiency, Centromere instability, and Facial anomalies (ICF) syndrome to cancer, and contribute to the onset or development of these diseases (Smith and Meissner, 2013; Weng et al., 2013; Subramaniam et al., 2014). Needless to say, these discoveries also fuel the promising idea that therapeutic strategies targeting DNA methylation can be used in the prevention and the treatment of cancer and other human diseases, including neuro-developmental disorders (Weng et al., 2013; Subramaniam et al., 2014). As an example, antipsychotic drugs clozapine and sulpiride, combined with histone deacetylase inhibitor valproate, have a beneficial action in schizophrenia and bipolar patients, maybe because they revert the aberrant DNA methylation status at GABAergic gene promoters (Dong et al., 2008). In 2004, 5-azacytidine (VidazaTM, Celgene Corporation, Summit, NJ). A drug blocking DNA methylation, received approval by the Food and Drug Administration for the treatment of myelodysplastic syndromes (Kaminskas et al., 2005).

Figure 1. Overview of the DNA methylation and demethylation pathway. (A) DNMT1 is responsible for the maintenance of DNA methylation during DNA replication. It recognizes hemi-methylated CpG, thanks to its interaction with co-factor UHRF1, and it adds methylation on the un-methylated strand. Black bubbles: methylated CpG. Empty bubbles: un-methylated CpG. (B) DNMT3A/B are responsible for de novo DNA methylation. They establish new patterns of methylation directly from unmethylated CpG-containing sequences. In the embryo, their activity is modulated by a catalytically inactive family member DNMT3L. (C) Passive demethylation occurs through loss of DNMT1/3 activity in actively dividing cells. Loss can be attributed to post-translational modifications, gene mutations, gene silencing or any other mechanism that will eventually lead to DNMT activity inhibition. (D) Active DNA demethylation is catalyzed by the TET family of enzymes. TET1, 2 and 3 can oxydate 5mC into 5hmC (represented in grey bubbles), and eventually oxidate 5hmC into 5-formylcytosine and 5-carboxy-cytosine. None of these bases is recognized by DNMTs causing loss of DNA methylation during DNA replication. In addition, these oxidated bases are recognized by the base-excision repair (BER) pathway and catalytically removed.

Figure 2. Summary of the nuclear factors and epigenetic marks involved in the maintenance of DNA methylation status in different regions of the genome. The table recapitulates our current knowledge on transcription factors, chromatin remodellers and histone marks contributing to the establishment of DNA methylation and its erasure. The information is presented according to genomic features, sharing common regulators, such as promoters/enhancers, tumor suppressor genes, germline gene promoters, imprinted regions, DNA repeats, and retroviral elements and peri-centromeric regions.

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t KAP1/DNMTs control the maintenance of DNA methylation, independently of DNA replication, on a number of genomic targets. Yet, DNMTs have been shown to be recruited onto the chromatin by other chromatin remodelers, such as SETDB1 or G9a, or secondary to gene silencing (Gibbons et al., 2000; Dennis et al., 2001; Guibert and Weber, 2013; Pacaud et al., 2014). Thus, only the identification of the full-spectrum of transcription factors involved in the regulation of DNA methylation will tell whether this function is predominantly confer to KRAB-ZNF factors. This systematic analysis might help understand why only a limited number of factors per family are involved in the shaping of DNA methylation. In the case of ZNF factors several explanations have been postulated. The resolution of the structure of the ZNF fingers of Zfp57 bound onto methylated DNA indicated that a specific amino-acid sequence in the DNA binding ZNF fingers might be required for the recognition and binding of methylated CpG sequences (Liu et al., 2012; BuckKoehntop and Defossez, 2013). Using this knowledge, researchers have postulated that ZNF factors containing this motif might likely contribute to shape DNA methylation profile (Liu et al., 2013). An alternative hypothesis rely on the observation that KRAB-ZNF factors are present uniquely in vertebrate genomes and have expanded quite dramatically in mammalian genomes. As DNA repeats sequences also quickly evolved in mammalian genomes, it is suggested that humanspecific KRAB-ZNF factors might primarily contribute in DNA repeats silencing (Lukic et al., 2014).

……

DNA methylation plays an important role in the control of gene expression and cell fate in mammals. Its regulation and function has been upon intense scrutiny since its discovery in mid-1900s. Yet, how DNA methylation patterns are established during embryogenesis, and edited in adult tissue, remains a matter of intense debate. Profiling of DNA methylation in many cell type, species and environmental set up indicates that the DNA methylation profile is thighly correlated with the cell type and its environment. As a consequence, de novo methylation and DNA demethylation events are not randomly distributed but are actually targeted to particular regulatory DNA elements in the genome, including promoters, enhancers or repeated DNAs. For this latter reason researchers have focused on the role of transcription factor in these DNA methylation events. Yet, it is also recognized that non-coding RNAs, short and long, contribute to the establishment and editing of DNA methylation profiles in mammals. Non-coding RNAs may directly interact and control methylation and demethylation activities and, as a consequence, the pattern of DNA methylation in the genome (Di Ruscio et al., 2013; Arab et al., 2014; Castro-Diaz et al., 2014; Molaro et al., 2014; Turelli et al., 2014). For instance, antisense long non-coding RNA TARID (TCF21 antisense RNA inducing demethylation), activates TCF21 expression by inducing promoter demethylation. TARID sequence is complementary to the sequence of the TCF21 promoter. Its transcription causes the anchoring of GADD45A (growth arrest and DNA-damageinducible, alpha), a regulator of DNA demethylation, at the TCF21 promoter and its subsequent chromatin remodelling (Arab et al., 2014). Understanding the interplay between noncoding RNAs and transcription factors in the establishment and the maintenance of DNA methylation is therefore an important challenge for the future.

The Expanding Role of MBD Genes in Autism: Identification of a MECP2 Duplication and Novel Alterations in MBD5, MBD6, and SETDB1

The methyl-CpG-binding domain (MBD) gene family was first linked to autism over a decade ago when Rett syndrome, which falls under the umbrella of autism spectrum disorders (ASDs), was revealed to be predominantly caused by MECP2mutations. Since that time, MECP2 alterations have been recognized in idiopathic ASD patients by us and others. Individuals with deletions across the MBD5 gene also present with ASDs, impaired speech, intellectual difficulties, repetitive behaviors, and epilepsy. These findings suggest that further investigations of the MBD gene family may reveal additional associations related to autism. We now describe the first study evaluating individuals with ASD for rare variants in four autosomal MBD family members, MBD5, MBD6, SETDB1, and SETDB2, and expand our initial screening in the MECP2 gene. Each gene was sequenced over all coding exons and evaluated for copy number variations in 287 patients with ASD and an equal number of ethnically matched control individuals. We identified 186 alterations through sequencing, approximately half of which were novel (96 variants, 51.6%). We identified seventeen ASD specific, nonsynonymous variants, four of which were concordant in multiplex families: MBD5 Tyr1269Cys, MBD6 Arg883Trp, MECP2 Thr240Ser, and SETDB1 Pro1067del. Furthermore, a complex duplication spanning the MECP2 gene was identified in two brothers who presented with developmental delay and intellectual disability. From our studies, we provide the first examples of autistic patients carrying potentially detrimental alterations in MBD6 and SETDB1, thereby demonstrating that the MBD gene family potentially plays a significant role in rare and private genetic causes of autism.

There is growing evidence of the involvement of the methyl-CpG-binding domain (MBD) genes in neurological disorders. To date, pathogenic mutations have been found in patients with clinical features along the autism continuum for two genes in this family, methyl-CpG-binding domain protein 5 (MBD5) and methyl-CpG-binding protein 2 (MECP2). Both genes carry an MBD domain, the unifying feature for the family that includes nine additional genes; BAZ1A, BAZ1B, MBD1,MBD2, MBD3, MBD4, MBD6, SETDB1 and SETDB2 (Roloff et al., 2003). The MBD genes are involved in a variety of functions, including chromatin remodeling (BAZ1A, BAZ1B, MBD1, MBD2, MBD3, and MECP2), DNA damage repair (BAZ1A and MBD4), histone methylation (SETBD1 and SETDB2), and X chromosome inactivation (MBD2, Roloff et al., 2003, Bogdanovic & Veenstra, 2009). There is also functional interplay among members of this family as they have been found to bind at the same promoter regions (MBD1, MBD2, MBD3, andMECP2), partner with each other in complexes (MBD1 and SETBD1), or act in the same complexes in a mutually exclusive manner (MBD2 and MBD3, Sarraf & I. Stancheva 2004; Ballestar et al., 2005; Le Guezennec et al., 2006; Matarazzo et al., 2007). Little is known thus far about the functions of MBD5 and MBD6; they each encode proteins that localize to chromatin but fail to bind methylated DNA (Laget et al., 2010).

One specific disorder in the autism spectrum, Rett syndrome, is caused almost exclusively by alterations in MECP2 (Amir et al., 1999). Due to the location ofMECP2 on the X chromosome, mutations in females can lead to Rett syndrome while males with the same genetic changes typically present with neonatal encephalopathy (Moretti & Zoghbi 2006). Further investigations have demonstrated that MECP2 misregulation can lead to a wide range of clinical features including autism, Angelman-like symptoms, mental retardation with or without infantile seizures, mild learning disabilities, and schizophrenia (Watson et al., 2001; Klauck et al., 2002; Carney et al., 2003; Shibayama et al., 2004;Coutinho et al., 2007; Harvey et al., 2007; Lugtenberg et al., 2009). Our group previously evaluated the MECP2 gene in a dataset of female ASD patients and identified two mutations reported in classic Rett syndrome patients; an Arg294X mutation and a 41 base pair deletion (Leu386fs) predicted to generate a truncated protein (Carney et al., 2003). Furthermore, while point mutations in MECP2 were first recognized to result in abnormal clinical phenotypes, increased expression of the wild type protein due to gene duplication also results in neurodevelopmental disorders (Meins et al., 2005; Van Esch et al., 2005; del Gaudio et al., 2006;Ramocki et al., 2009).

A second gene in the MBD family, MBD5, was tied to neurodevelopmental disorders following the identification of microdeletions on chromosome 2q22–2q23 (Vissers et al., 2003; Koolen et al., 2004; de Vries et al., 2005; Wagenstaller et al., 2007; Jaillard et al., 2008; van Bon et al., 2009; Williams et al., 2009; Chung et al., 2011; Talkowski et al., 2011; Noh & J. M. Graham Jr 2012). The minimal region for these nonrecurrent deletions covers only a single gene, MBD5 (van Bon et al., 2009; Williams et al., 2009; Talkowski et al., 2011). This suggests that the common features of ASDs, delayed or impaired speech, intellectual disability, epilepsy, and stereotypic hand movements found across microdeletion patients manifest due to a decreased expression of this critical gene (van Bon et al., 2009;Williams et al., 2009; Talkowski et al., 2011). Notably, two cases of individuals with duplications across the critical MBD5 region also present with autistic features and developmental delay (Chung et al., 2012). This demonstrates that precise regulation of both MBD5 and MECP2 must be maintained as either increased or decreased expression of each gene can result in a range of neurodevelopmental disorders.

Supplementing clinical evidence, mouse models have reiterated the potential significance of the MBD family in autism etiology. Mbd1 and Mecp2 null models have abnormal neurobehavioral phenotypes including increased anxiety, and impaired social interactions and synaptic plasticity (Guy et al., 2001; Shahbazian et al., 2002b; Zhao et al., 2003; Allan et al., 2008). Furthermore, a transgenicSetdb1 model established a link between this gene and behavior (Jiang et al., 2010a). Additionally, Setdb1 plays a role in the repression of Grin2b, a gene linked to autism, bipolar disorder, intellectual disability, and schizophrenia (Avramopoulos et al., 2007; Allen et al., 2008; Endele et al., 2010; Jiang et al., 2010a; Myers et al., 2011; O’Roak et al., 2011).

Studies have demonstrated that each of the MBD genes are expressed in the brain, while their specific functions having only been determined for a subset of genes (Shahbazian et al., 2002a, Bogdanovic & Veenstra, 2009, Jiang et al., 2010b, Laget et al., 2010, Safran et al., 2010). MeCP2 is a transcriptional regulator believed to act in neuronal maturation as levels increase over time (Shahbazian et al., 2002a,Chahrour et al., 2008). Stable levels of MeCP2 are required through adulthood, as elimination of this protein in adult mice mimics features seen in knockout Mecp2mice (McGraw et al., 2011). The H3K9 methyltransferase SETDB1 acts both in early development as well as later stages of life (Jiang et al., 2010a, Cho et al., 2012). Removal of Setdb1 in mice results in peri-implantation lethality (Dodge et al., 2004). Studies in the forebrain of transgenic Setdb1 mice demonstrate that it targets the NMDA receptors Grin2a and Grin2b as well as the glutamate receptorGrid2 (Yang et al., 2002, Jiang et al., 2010a).

While there is clinical evidence of MECP2 and MBD5 playing a role in autism, only two studies to date have evaluated patients with ASD for mutations in additional MBD family members (Li et al., 2005; Cukier et al., 2010). Previous work in our laboratory analyzed the coding regions of MBD1, MBD2, MBD3, andMBD4 in over 200 individuals with ASD of African and European ancestry and identified multiple variants that altered the amino acid sequence, were unique to patients with autism, and concordant with disease in multiplex families (Cukier et al., 2010). In contrast, a study by Li and colleagues was restricted to a dataset of 65 Japanese autistic patients and reported only a single variation that might be related to autism (Li et al., 2005). We now expand our initial study of MECP2 to a larger dataset that includes male patients and perform the first study evaluating patients with ASD for alterations in four additional MBD family members: MBD5MBD6, SETDB1 and SETDB2.

Sequencing across the five MBD genes in 287 patients with ASD and 288 ethnically matched control individuals identified a total of 186 unique variations (Table 1, Supplemental Tables 37). These variants included 177 single nucleotide polymorphisms (SNPs), five deletions and four insertions. Ninety (48.4%) of the variations have been previously reported in either the dbSNP 134 database (http://www.ncbi.nlm.nih.gov/projects/SNP/) or RettBASE (http://mecp2.chw.edu.au/), while the remaining 96 variants (51.6%) are novel. Fifty-six variations are predicted to alter the amino acid sequence. Fifty-three of the changes were found solely in patients with ASD and absent from controls. To determine variants most likely to contribute to ASD susceptibility, we prioritized changes that were either unique to affected individuals or that had an increased frequency in cases when compared to controls. The 17 most interesting variants were nonsynonymous and unique to our ASD population (Table 1). We utilized four distinct programs to characterize the variants; GERP (Cooper et al., 2005) and PhastCons (Siepel et al., 2005) to measure the level of amino acid conservation across species and PolyPhen (Adzhubei et al., 2010) and SIFT (Kumar et al., 2009) to predict which alterations might have the damaging consequences to protein function.

ASD Unique, Nonsynonymous Variations

The mutational burden between cases and controls of African or European ancestry for each gene was not statistically significant by the chi-squared test (Supplemental Table 8). This was determined for the overall load of all variants as well as nonsynonymous alterations (Supplemental Table 9).

MBD5

Thirty-two changes were identified in MBD5, 18 of which have been previously reported (Supplemental Table 3). A distinct set of 11 alterations were nonsynonymous, four of which were only identified in patients with ASD (Val443Met, Ile1247Thr, Tyr1269Cys, and Arg1299Gln, Figure 1A–D, Table 1). Three of these four alterations (75%) are predicted to be damaging by SIFT, as compared to only two of seven nonsynonymous variants (28.6%) identified solely in control individuals (Supplemental Table 3). One alteration of high interest, MBD5 Tyr1269Cys, was inherited paternally in all three ASD children in multiplex family 7763 (Figure 1C). Two of the affected individuals (0001 and 0100) were intellectually impaired with measured IQ in the moderate to severe range (Full Scale IQ: 40 and 50, respectively), while the remaining brother with autism (0101) had borderline intellectual functioning (Full Scale IQ=78). Furthermore, all three siblings had a delay in language and displayed self-injurious behaviors. Two individuals presented with macrocephaly (0100 and 0101), and individual 0100 has a history of epilepsy (recurrent non-febrile seizures).

Pedigrees of ASD families carrying alterations in MBD5 and MBD6

MBD6

A total of 44 alterations were detected in MBD6, two being single base pair insertions and the remainder of which were SNPs (Supplemental Table 4). Sixteen of the single nucleotide changes have been previously reported and 28 are novel. A subset of 17 alterations was identified only in individuals with ASD, seven of which are predicted to cause missense changes (Table 1, Figure 1E–K). While each of these changes was only identified in a single proband, three of the alterations have high PolyPhen and SIFT scores and are novel (Arg883Trp, Pro943Arg and Arg967Cys), suggesting a strong functional consequence. Furthermore, one of these alterations, Arg883Trp, was identified in multiplex family 7979 and passed maternally to both affected children (Figure 1I). Individual 0001 has a diagnosis of autism and is nonverbal with moderate intellectual disability. His sister (0100) has a diagnosis of Pervasive Developmental Disorder-Not Otherwise Specified and mild intellectual disability, displaying some phrase speech. Both siblings have a history self-injurious behavior. Their mother (1001), who also carries the alteration, was diagnosed with anxiety/panic disorders, depression, obsessive compulsive disorder, and has a history of epilepsy (adolescent onset seizures).

Along with novel variations of interest in MBD6, we found that two known SNPs occur at a higher frequency within our affected population compared to our control population. The first variation, rs61741508 (c.-2C>A), was recognized in sixteen patients with ASD and five controls and is located just upstream of the ATG start site in the Kozak consensus sequence. This variation also has high conservation scores (Supplemental Table 4). The second SNP, rs117084250 (c.2407-64C>T), falls within intron nine and was found in twelve individuals with ASD but only four controls. However, the conservation scores were relatively low, thereby making this a variant of lesser interest (Supplemental Table 4).

MECP2

Twenty-eight alterations were identified in MECP2 (Supplemental Table 5). Sixteen of these are currently in the dbSNP database and another one has been previously reported in RettBASE, leaving 11 novel variations. While none of the frequently recurring, classic Rett syndrome variations were identified in this study, there are two previously reported MeCP2 alterations of undetermined pathogenicity (Thr240Ser and Ala370Thr) that may cause clinical phenotypes. This first variation, MeCP2 Thr240Ser (rs61749738), was identified in two families of African ancestry (1072 and 17130) and absent in control individuals (Figure 2A,B). Further investigation into additional family members showed that the variation was inherited maternally in both cases and concordant with disease in multiplex family 1072. The second alteration, Ala370Thr (rs147017239), was also inherited maternally in a single proband of African ancestry (family18024, Figure 2C).

Pedigrees of ASD families carrying alterations in MeCP2

SETDB1

A total of 44 changes were found in SETDB1, comprised of 19 known and 25 novel alterations (Supplemental Table 6). Eight changes are predicted to be nonsynonymous, but only one of these, Pro1067del, was found solely in patients with ASD. This change is also the only ASD specific, nonsynonymous deletion identified in the entire study. The variant removes three nucleotides and predicts an in-frame deletion of a single amino acid. This deletion falls within the SET domain of the protein and was inherited maternally in both affected sons in family 17187 (Figure 3A).

Figure 3

Pedigrees of ASD families carrying alterations in SETDB1 and SETDB2

Another novel variation of interest in SETDB1 that we identified in a high proportion of cases versus controls, Pro529Leu, was identified in five ASD families of European ancestry and only a single control (Figure 3B–F). This variant was inherited paternally in one family and maternally in the remaining four families. In family 37265, the variation was passed from the father, who has dyslexia, to both the female proband with autism (0001) who was diagnosed with developmental and language delays as well as her brother (0100) who presented with ADHD, anxiety/panic disorder, language delay and macrocephaly (Figure 3E). In two of the families with maternal inheritance (17663 and 37673), the mothers presented with anxiety/panic disorder. In family 17663, the mother also presented with a history of seizures, sleep disorder and self-reported depression, while the mother in family 37673 reported history of adolescent onset Anorexia Nervosa. The increased incidence of this alteration in cases versus controls, along with neuropsychiatric and neurodevelopmental disorders in parents carrying the alteration, suggests that this variation may confer a variety of clinical consequences.

SETDB2

Thirty-eight single base pair alterations were identified in the SETDB2gene, 21 of which have been previously reported and the remaining 17 are novel (Supplemental Table 7). Eight SNPs are predicted to alter amino acids and three of these were unique to affected individuals: Ile425Thr, Thr475Met and Pro536Arg (Table 1, Figure 3C,G,H). However, these alterations are not predicted to have a highly detrimental effect on the protein and occur within singleton families, making it difficult to determine whether they may play a pathogenic role in ASD.

Along with isolating additional variations in MBD5 and MECP2 that may contribute to neuropsychiatric disease, this study is the first to report prospective pathogenic variations in MBD6 and SETDB1. These include two novel, nonsynonymous alterations in MBD6 (Arg883Trp and Pro943Arg) and one more in SETDB1 (Pro1067del). Furthermore, the MBD6 Arg883Trp and SetDB1 Pro1067del variations each segregated with ASD in the multiplex families. Potential for SETDB1 to play a role in neurobehavioral phenotypes is supported by results from transgenic Setdb1 mice demonstrating a role in mood behaviors (Jiang et al., 2010a).

To date, MBD5 mutations have been identified in individuals presenting a range of clinical phenotypes including ASD, developmental delay, intellectual disability, epilepsy, repetitive movements, and language impairments (Vissers et al., 2003;Koolen et al., 2004; de Vries et al., 2005; Wagenstaller et al., 2007; Jaillard et al., 2008; van Bon et al., 2009; Williams et al., 2009; Chung et al., 2011; Talkowski et al., 2011; Noh & Graham Jr 2012). These results suggest a significant role for theMBD5 isoform 1, which presents with increased expression in the brain (Laget et al., 2010). It has been estimated that between microdeletions and point mutations of MBD5, this gene may play a contributing genetic role in up to 1% of individuals with ASD (Talkowski et al., 2011). Of the nonsynonymous alterations identified in this study, ASD specific changes were more likely to be predicted to be damaging as compared to those variations found in control individuals (Supplemental Table 3). MBD5 Tyr1269Cys is a strong potentially pathogenic change due to its co-segregation with ASD in a multiplex family of three affected children, high conservation of this amino acid across species and altered function in the luciferase transcriptional activation assay. While this alteration does not fall in a known protein domain, it is specific to isoform 1, the isoform predominately expressed in brain (Laget et al., 2010). It seems likely that most alterations inMBD5 related to disease will be rare and unique, as the one alteration previously reported to have an increased frequency in patients with ASD, Gly79Glu, was only identified in a single control in the current study (Talkowski et al., 2011).

The role of MECP2 in developmental disorders is undisputed (Samaco & Neul 2011). Our study supports the possible pathogenicity of two specific MeCP2 alterations: Thr240Ser and Ala370Thr. The first variant, Thr240Ser was identified in two male probands from families of African ancestry, including the multiplex family 1072 where the variant segregated with ASD (Figure 2A,B). The maternal inheritance in family 17130 and presence of an unaffected carrier sister suggests that the variation may only present with a clinical phenotype in a hemizygous state. This variant falls within the transcriptional repression domain and has been previously reported in four studies; three cases of males with intellectual disability and one female with Rett syndrome (Yntema et al., 2002; Bourdon et al., 2003;Bienvenu & J. Chelly 2006; Campos et al., 2007; Bunyan & D. O. Robinson 2008). The second alteration, Ala370Thr, was identified in a singleton family of African ancestry and previously reported in three Chinese individuals: one female with Rett syndrome, her unaffected mother and a male presenting with epileptic encephalopathy (Figure 2C, Li et al., 2007; Wong & Li 2007). Both of these alterations must be further evaluated to isolate their potential functional consequences.

Finally, while we did identify variants of interest in four of the genes studied,SETDB2 alterations did not appear to be related to the occurrence of ASDs.

This is the first study to evaluate the coding regions of MBD5, MBD6, SETDB1, and SETDB2 for rare alterations in individuals with ASD. We identified novel point mutations predicted to be damaging and concordant with disease in multiplex families, as well as a complex duplication encompassing MECP2. Additional studies, ideally both in patients and animal models, are required to determine the precise consequences of these alterations. The results described here compound the evidence of MECP2 and MBD5’s involvement in ASDs and neurodevelopmental disorders and provide the first examples of autistic patients carrying potentially detrimental alterations in MBD6 and SETDB1. This study demonstrates the expanding role MBD genes play in autism etiology.

PI3K/Akt: getting it right matters

T F Franke1          Oncogene (2008) 27, 6473–6488;      http://dx.doi.org:/10.1038/onc.2008.313

The Akt serine/threonine kinase (also called protein kinase B) has emerged as a critical signaling molecule within eukaryotic cells. Significant progress has been made in clarifying its regulation by upstream kinases and identifying downstream mechanisms that mediate its effects in cells and contribute to signaling specificity. Here, we provide an overview of present advances in the field regarding the function of Akt in physiological and pathological cell function within a more generalized framework of Akt signal transduction. An emphasis is placed on the involvement of Akt in human diseases ranging from cancer to metabolic dysfunction and mental disease.

The molecular mechanisms of Akt regulation are summarized in Figure 1.

Figure 1.

Figure 1 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the authorCanonical schematic depicting the present state of our understanding of Akt activation and regulation of downstream biological responses. Autophosphorylation of RTKs induces the recruitment of p85 regulatory subunits leading to PI3K activation. Once activated, p110 catalytic subunits phosphorylate plasma membrane-bound phosphoinositides (PI-4-P and PI-4,5-P2) on the D3-position of their inositol rings. The second messengers resulting from this PI3K-dependent reaction are PI-3,4-P2and PI-3,4,5-P3 (also called PIP3). PIP3, in turn, is the substrate for the phosphoinositide 3-phosphatase PTEN, an endogenous inhibitor of PI3K signaling in cells. The phosphoinositide products of PI3K form high-affinity binding sites for the PH domains of intracellular molecules. PDK1 and Akt are two of the many targets of PI3K products in cells. Following binding of the Akt PH domain to PI3K products, Akt is phosphorylated by PDK1 on a critical threonine residue in its kinase domain. mTORC2 is the main kinase activity that through phosphorylation of a C-terminal HM serine residue locks Akt enzyme into an active conformation. Other kinases such as DNA-PK and ILK1 are also capable of phosphorylating Akt at the HM site but may do so in a cell- or context-dependent manner. Akt activation is blunted by phosphatases including PP2A and PHLPP that inhibit Akt activity by dephosphorylation. Studies examining Akt-interacting proteins such as CTMP or second messengers such as Ins(1,3,4,5)P4 suggest that this common pathway of Akt regulation may be further specified within certain functional contexts or during development. Once activated, Akt activation is channeled into a plethora of downstream biological responses reaching from angiogenesis, cell survival, proliferation, translation to metabolism.

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Consequences of Akt activation include diverse biological responses, ranging from primarily metabolic functions such as glucose transport, glycolysis, glycogen synthesis and the suppression of gluconeogenesis to protein synthesis, increased cell size, cell-cycle progression and apoptosis suppression.

Insights into the molecular consequences of increased Akt activation were derived from seminal studies that ultimately identified the ‘orphan’ proto-oncogene as an obligate intermediate downstream of PI3K in the insulin-dependent metabolic control of glycogen synthesis. When searching for kinases that could regulate GSK3, the groups of Brian Hemmings and Phil Cohen realized that Akt inhibited GSK3 activity in an insulin-stimulated and PI3K-dependent manner by direct phosphorylation of an N-terminal regulatory serine residue (Cross et al., 1995). By systematically permutating the amino-acid sequence surrounding the Akt phosphorylation site in GSK3, Alessi et al. (1996b) derived an optimal peptide sequence for Akt phosphorylation (R-X-R-X-X-S/T; where R is an arginine residue, S is serine, T is threonine and X is any amino acid). This Akt consensus motif is a common feature of known substrates of Akt, and its presence predicts reasonably well whether a given protein may be phosphorylated by Akt enzyme in vitro (for review, see Manning and Cantley, 2007). Experiments using randomized permutations on the basis of the motif to optimize substrate peptides have defined the requirement for optimal phosphorylation by Akt further (Obata et al., 2000). The preferred phosphoacceptor for Akt-dependent phosphorylation is a serine residue, but a synthetic substrate peptide with a threonine residue as the phosphoacceptor instead (R-P-R-A-A-T-F; P=proline, A=alanine, F=phenylalanine) is also easily phosphorylated. For achieving optimal phosphorylation efficiency, the phosphoacceptor is best followed by a hydrophobic residue with a large side-chain in the p+1 position, and preceded by a serine or threonine at the p−2 position.

One of the first targets of Akt to be identified that has direct implications for regulating cell survival is the pro-apoptotic BCL2-antagonist of death (BAD) protein. BAD regulation by Akt has exemplified the molecular pathways linking survival factor signaling to apoptosis suppression (for review, see Franke and Cantley, 1997). When BAD is not phosphorylated, it will inhibit Bcl-xL and other anti-apoptotic Bcl-2 family members by direct binding of its Bcl-2 homology domain to their hydrophobic grooves (Gajewski and Thompson, 1996). Once phosphorylated, these phospho-serine residues of BAD form high-affinity binding sites for cytoplasmic 14-3-3 molecules. As a result, phosphorylated BAD is retained in the cytosol where its pro-apoptotic activity is effectively neutralized (Zha et al., 1996). The importance of BAD as an integration point of survival signaling is underscored by the fact that it is a substrate for multiple independent kinase pathways in cells, not all of which phosphorylate BAD at the same site(s) as Akt (Datta et al., 2000). The mechanisms of 14-3-3-dependent regulation of BAD function hereby resemble the Akt-dependent inhibition of FoxO transcription factors that regulate the transcription of pro-apoptotic genes (Brunet et al., 1999).

The function of Akt extends beyond maintaining mitochondrial integrity to keep cytochrome c and other apoptogenic factors in the mitochondria (Kennedy et al., 1999). Akt activity also mitigates the response of cells to the release of cytochrome c into the cytoplasm. Although caspase-9 is an Akt substrate in human cells, where it may explain cytochrome c resistance (Cardone et al., 1998), it may not be the only, or even the most important, target because Akt-dependent cytochrome c resistance can be observed in animal species where caspase-9 lacks a potential Akt phosphorylation site (Fujita et al., 1999; Zhou et al., 2000). Not surprisingly, other components of the post-mitochondrial machinery such as the X-linked inhibitor of apoptotic proteins (XIAP) have been suggested as potential Akt substrates (Dan et al., 2004).

Another important class of Akt targets are proteins involved in the stress-activated/mitogen activated protein kinase (SAPK/MAPK) cascades. Growing experimental evidence points to a close functional relationship between the Akt survival pathway and SAPK/MAPK cascades that are activated by various cellular stresses and are linked to apoptosis. Increased Akt activity has been shown to suppress the JNK and p38 pathways (Berra et al., 1998; Cerezoet al., 1998; Okubo et al., 1998). It has been shown that apoptosis signal-regulating kinase 1 (ASK1) is regulated by Akt and contains an Akt-specific phosphorylation site (Kim et al., 2001). These findings have been confirmed independently by other groups (Yuan et al., 2003; Mabuchi et al., 2004). Thus, ASK1 is likely to be one of the points of convergence between PI3K/Akt signaling and stress-activated kinase cascades, although probably not the only one. Akt also phosphorylates the small G protein Rac1 (Kwon et al., 2000), the MAP2K stress-activated protein kinase kinase-1 (SEK1; also known as JNKK1 or MKK4) (Park et al., 2002) and the MAP3K mixed lineage kinase 3 (MLK3) (Barthwal et al., 2003; Figueroa et al., 2003). Using yeast-2-hybrid screens to identify interacting partners for Akt kinases, Figueroa et al. (2003) found binding of Akt2 to the JNK adaptor POSH. These authors showed that the binding of Akt2 to POSH results in an inhibition of JNK activity, and that this inhibition is mediated by phosphorylation of the upstream kinase MLK3 and leads to the disassembly of the JNK signaling complex. In turn, POSH is also an Akt substrate (Lyons et al., 2007). Taken together, these findings point to an intriguing model for the regulation of the JNK pathway by Akt, in which the Akt-dependent phosphorylation of specific components can block signal transduction through the stress-regulated kinase cascade. In spite of this, it has been reported that Akt also blocks the pro-apoptotic activity of other MAP3Ks such as MLK1 and MLK2 that act in parallel to MLK3 but do not contain a typical Akt consensus phosphorylation motif (Xu et al., 2001). Thus, phosphorylation-based mechanisms may be limited in explaining the role of Akt in blocking JNK signaling.

Although many of its substrates are involved in clearly defined biological functions within a circumscribed context such as cell proliferation, a more thorough analysis of Akt signaling has suggested that the boundaries between metabolic processes and apoptosis suppression may be artificial. For example, the Akt target GSK3 has been implicated both in the regulation of glucose metabolism and cell survival (Pap and Cooper, 1998). These findings suggest that the distinctions between cell growth, survival, metabolism and apoptosis regulation do not properly reflect functional interactions between concurrent biological processes in cells. This shift in perception has been fueled by studies from the Korsmeyer laboratory that have demonstrated a canonical function for the pro-apoptotic Bcl-2 family member BAD in the regulation of glucokinase activity (Danial et al., 2003). It is conceivable that findings of PKA-dependent regulation of BAD in glucose metabolism can be extrapolated to BAD inhibition by Akt. Still, a formal confirmation for a role of Akt in this process has yet to be presented (for review, see Downward, 2003).

The critical importance of Akt signaling for neuronal function is implied from several lines of in vitro evidence using neuronal cell lines and dispersed primary neuronal cultures that have demonstrated a requirement for Akt in the protection against trophic factor deprivation, oxidative stress and ischemic injury (Dudek et al., 1997; Salinas et al., 2001; Noshita et al., 2002). Dysregulation of Akt activity is observed in neurodegenerative diseases including Alzheimer’s disease (Rickle et al., 2004; Ryderet al., 2004), Parkinson’s disease (Hashimoto et al., 2004) and Huntington’s disease (Humbert et al., 2002), and it is also associated with the pathobiological mechanisms underlying spinocerebellar ataxia (Chen et al., 2003). A mechanistic involvement of impaired Akt signaling in neurodegeneration is further supported by the Akt-dependent phosphorylation of the disease-related proteins huntingtin (Humbert et al., 2002) and ataxin (Chen et al., 2003).

Other studies suggest that the involvement of Akt in brain function extends beyond the protection of neuronal cells against apoptotic insults. Indeed, pathological changes in Akt signal transduction have been described that are associated with mental diseases. Significantly decreased Akt1 expression has been reported in patients suffering from familial schizophrenia (Emamian et al., 2004). Decreased Akt1 levels are correlated with increased GSK3 activity, presumably because of the lack of the Akt-dependent inhibitory input on GSK3. In support of AKT1 being a susceptibility gene for schizophrenia, Akt1(−/−) mice exhibit increased sensitivity to the sensorimotor disruptive effect of amphetamine, which is partly reversed by the treatment of mutant mice with the antipsychotic drug haloperidol (Emamian et al., 2004). Additional support for a contribution of impaired Akt signaling in the pathogenesis of schizophrenia derives from the finding of mutant PI3K signaling in schizophrenia (for review, see Arnold et al., 2005). A direct involvement of Akt in dopaminergic action is indicated by the observation that Akt1(−/−) mutant mice exhibit a behavioral phenotype resembling enhanced dopaminergic transmitter function (Emamian et al., 2004). By interacting with the GSK3 pathway, Akt modulates the suppression of dopamine (DA)-associated behaviors after treatment with the mood stabilizer lithium (Beaulieu et al., 2004). Furthermore, a β-arrestin 2-mediated kinase/phosphatase scaffold of Akt and protein phosphatase A (PP2A) is required for the regulation of Akt downstream of DA receptors (Beaulieu et al., 2005). Still, the role of Akt in dopaminergic responses by far exceeds actions downstream of DA receptors: the insulin-dependent regulation of DA transporter also depends on Akt activity (Garcia et al., 2005).

Since the field of Akt signaling in psychiatric disorders is still emerging, it may be too early to speculate about the molecular involvement of Akt in regulating higher brain function. Possible functional outlets of Akt include some of the substrates mentioned above, including mTORC1 and GSK3. In addition, substrates of Akt related to synaptic plasticity and transmission have been described. One such novel substrate of Akt related to neuronal excitability is the β2-subunit of the type A γ-aminobutyric acid receptor (GABAA-R) (Lin et al., 2001). In support of a direct involvement of Akt in synaptic function, studies directed at working memory performance performed in Akt1(−/−) mice (Lai et al., 2006) and in healthy individuals carrying the AKT1 coding variation observed in familial schizophrenia (Tan et al., 2008) find a strong correlation with cognitive performance. Additional roles for Akt in higher brain function are suggested by studies from the Nestler laboratory that have explored the IRS2-Akt pathway during the development of tolerance to opiate reward (Russo et al., 2007). By using viral-mediated gene transfer to express mutant Akt in midbrain neurons, these authors demonstrate that downregulation of the IRS2-Akt pathway mediates morphine-induced decreases in cell size of DA neurons in brain regions that are critically involved in the reward circuitry and affected in individuals addicted to drugs of abuse.

Finally, TSC patients show an increased incidence of autism spectrum disorders (ASD) ranging from 25 to 50% (for review, seeWiznitzer, 2004). Individuals with macrocephaly due to Lhermitte–Duclos disease are prone to ASD and show a pronounced incidence of mutations in the PTEN tumor suppressor gene (Butler et al., 2005). Additional experimental support for a possible involvement of PTEN/Akt in ASD is provided by data from the Parada laboratory examining the morphology and behavior of mutant mice with neuron-specific knockout of PTEN (Kwon et al., 2006). Future studies will be required to clarify the function of Akt in cognition and characterize the underlying molecular mechanisms. In spite of this, these initial studies suggest a complex function of Akt in conditions affecting brain function and mental health.

The emerging involvement of Akt in higher brain function is summarized in Figure 2.

Figure 2.

Figure 2 - Unfortunately we are unable to provide accessible alternative text for this. If you require assistance to access this image, please contact help@nature.com or the author

Akt kinase regulates diverse aspects of neuronal cell function. Akt activation in neuronal cells follows similar mechanisms to those outlined in Figure 1, including activation of PI3K by RTKs including IGF-1/insulin and nerve growth factor (BDNF/NT-3) receptors. Other mechanisms governing Akt activity in neuronal cells include G-coupled receptors for the monoamine neurotransmitters serotonin (5-HT) (for review, see Raymond et al., 2001) and dopamine (DA) (for review, see Beaulieu et al., 2007). Depending on receptor type (D2-DA and 5-HT1A receptors vs D1-DA receptors), binding of 5-HT or DA decreases or increases the activity of adenylyl cyclase (AC), respectively. Changes in cAMP second messenger levels, in turn, alter PKA and PP2A activity. PP2A is inhibited by increased PKA activity, thus maintaining Akt in an activated state after 5-HT1Areceptor simulation (Hsiung et al., 2008). After binding of DA to D2-DA receptor, following initial inhibition of AC, a secondary internalization complex is formed between β-arrestin 2, PP2A and Akt leading to the inhibition of Akt. In neuronal cells, activated Akt regulates diverse targets that have been implicated in the regulation of protein translation and cell size (mTORC1), axonal outgrowth (GSK3), apoptosis suppression (BAD) and synaptic plasticity (GABAA-R). Details regarding functional consequences of Akt regulation for higher brain function are discussed in the text.

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When considering the present understanding of all the signals leading to and from Akt, we face a growing complexity that is in part compounded by the intersection of multiple signaling cascades. Many substrates of Akt are shared with other kinases that have similar specificities. Moreover, signals originating from activated Akt do not simply lead to changes in the biological activity of specific downstream substrates, but affect entire signaling networks. In spite of this, there is hope that there is order to the far-reaching physiological involvement of Akt. One possibility is that differential regulation of the binding partners of Akt may determine cell- and context-specific signaling by Akt. Studies are now needed to elucidate the physiological functions of the binding partners of Akt in mammalian physiology.

A second challenge that the field is facing arises from the involvement of Akt in multiple areas of physiology. These now exceed cancer and diabetes and, as briefly outlined above, include higher brain functions related to cognition.

SETDB1 in Early Embryos and Embryonic Stem Cells

Yong-Kook Kang

The histone methyltransferase SETDB1 contributes to the silencing of local chromatin and the target specificity appears to be determined through various proteins that SETDB1 interacts with. This fundamental function endows SETDB1 with specialized roles in embryonic cells. Keeping the genomic and transcriptomic integrity via proviral silencing and maintaining the pluripotency by repressing the differentiation-associated genes have been demonstrated as the roles of SETDB1 in embryonic stem cells. In early developing embryos, SETDB1 exhibits characteristic nuclear mobilizations that might account for its pleiotropic roles in these rapidly changing cells as well. Early lethality of SETDB1-null embryos, along with other immunolocalization findings, suggests that SETDB1 is necessary for reprogramming and preparing the genomes of zygotes and pluripotent cells for the post-implantation developmental program.

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3706629/

Exome sequencing of probands with autism have revealed broadly similar results:de novo mutations in a large set of genes occur in a significant fraction of patients, with relatively high OR’s for damaging mutations in genes expressed in the brain9,1921. Most interestingly, CHD8, which like CHD7 reads H3K4me marks, is frequently mutated in autism22, raising the question of whether the H3K4me pathway may play a role in many congenital diseases. Among 249 protein-alteringde novo mutations in CHD (Supplementary Table 4) and 570 such mutations in autism9,19,20,23, there were two genes, CUL3 and NCKAP1, with damaging mutations in both CHD and autism and none in controls (P = 0.001, Monte Carlo simulation), and several others with mutations in both (e.g., SUV40H1 and CHD7). Similarly, rare copy number variants at 22q11.2, 1q21, and 16p11 are found in patients with autism, CHD or both diseases2426. These observations suggest variable expressivity of mutations in key developmental genes. Identification of the complete set of these developmental genes and the full spectrum of the resulting phenotypes will likely be important for patient care and genetic counseling.

 

Context-specific microRNA function in developmental complexity

Adam P. Carroll1,2Paul A. Tooney1,2 and Murray J. Cairns1,2,*      http://jmcb.oxfordjournals.org/content/early/2013/03/01/jmcb.mjt004.full     J Mol Cell Biol (2013)    doi: 10.1093/jmcb/mjt004

Since their discovery, microRNAs (miRNA) have been implicated in a vast array of biological processes in animals, from fundamental developmental functions including cellular proliferation and differentiation, to more complex and specialized roles such as longterm potentiation and synapse-specific modifications in neurons. This review recounts the history behind this paradigm shift, which has seen small non-coding RNA molecules coming to the forefront of molecular biology, and introduces their role in establishing developmental complexity in animals. The fundamental mechanisms of miRNA biogenesis and function are then considered, leading into a discussion of recent discoveries transforming our understanding of how these molecules regulate gene network behaviour throughout developmental and pathophysiological processes. The emerging complexity of this mechanism is also examined with respect to the influence of cellular context on miRNA function. This discussion highlights the absolute imperative for experimental designs to appreciate the significance of context-specific factors when determining what genes are regulated by a particular miRNA. Moreover, by establishing the timing, location, and mechanism of these regulatory events, we may ultimately understand the true biological function of a specific miRNA in a given cellular environment.

It was once considered the central dogma of molecular biology that gene expression was regulated in a unidirectional manner whereby cellular instructions were encoded in DNA to be transcribed to produce RNA, which simply acted as a messenger molecule to produce the protein end-products that executed these cellular instructions. In fact, signs of a biological phenomenon whereby non-protein-coding RNA molecules could interfere with this very process were not even realized until the 1970s and early 1980s, when exogenous oligonucleotides complementary to ribosomal RNA were found to interfere with ribosome function (Taniguchi and Weissmann, 1978; Eckhardt and Luhrmann, 1979;Jayaraman et al., 1981). A number of experiments in both prokaryotes and eukaryotes further supported the notion of antisense RNA as an antagonist to RNA function (Chang and Stoltzfus, 1985; Ellison et al., 1985; Harland and Weintraub, 1985; Izant and Weintraub, 1985; Melton, 1985), and one such experiment elegantly demonstrated that the introduction of synthetic oligonucleotides complementary to 3′- and 5′-terminal repeats of Rous sarcoma virus 35S RNA not only attenuated viral replication and cell transformation, but also inhibited viral RNA translation in vitro (Stephenson and Zamecnik, 1978; Zamecnik and Stephenson, 1978).

In addition to this, the successful inhibition of thymidine kinase gene expression by antisense RNA in eukaryotic cells precipitated the concept of antisense RNA not only as an experimental tool, but also as a therapeutic design (Izant and Weintraub, 1984). Determining the functionality of a previously identified gene sequence without identifying, isolating, or characterizing the protein product; interfering with RNAs that are never translated; and silencing the expression of disease-associated transcripts in a sequence-specific manner: these were some very appealing prospects. By the late 1980s and early 1990s, a variety of techniques had evolved in the field of molecular and applied genetics whereby various antisense DNA and RNA construct designs were employed to efficiently downregulate target gene expression (Fire et al., 1991).

Meanwhile, the scientific community was also beginning to appreciate a role for endogenous antisense RNA. Short antisense transcripts were found to form an RNA–RNA duplex with the 5′ end of the replication primer of the ColE1 plasmid (Tomizawa et al., 1981; Tomizawa and Itoh, 1982). Endogenous antisense RNA control in prokaryotes was also linked with various biological processes such as plasmid replication, transposition, temporal bacteriophage development, and catabolite repression in bacteria (Light and Molin, 1983; Simons and Kleckner, 1983; Kumar and Novick, 1985). Evidence was also beginning to mount to implicate antisense control mechanisms in eukaryotic organisms (Adeniyi-Jones and Zasloff, 1985; Farnham et al., 1985; Heywood, 1986; Spencer et al., 1986; Williams and Fried, 1986; Stevens et al., 1987), including the demonstration that antisense transcripts in the bovine papillomavirus type 1 (BPV-1) genome prevented episomal replication (Bergman et al., 1986).

It was only a matter of time before phenomena of gene silencing began to unfold in animals. Previous work in the 1980s with Caenorhabditis elegans had established that mutations in the genes for lin-4, lin-14, lin-28, lin-29, and lin-41 altered the heterochronic lineage of developing larvae, resulting in a failure to control temporal aspects of post-embryonic development (Chalfie et al., 1981; Ambros and Horvitz, 1984; 1987; Ambros, 1989); thus, these genes were referred to as being ‘heterochronic’. However, in 1993 it was discovered that lin-4 was located within an intron and was thus unlikely to encode a protein. More significantly, two lin-4 transcripts ∼22 and 61 nucleotides in length were identified that exhibited complementarity to a repeat sequence element in the 3′ untranslated region (UTR) of lin-14 mRNA (Lee et al., 1993). With another report soon replicating this finding in C. elegans andCaenorhabditis briggsae (Wightman et al., 1993), the notion was set forth that the 22-nucloetide lin-4 transcript represented an active mature form of the 61-nucelotide transcript and functioned to control worm larval development by binding to the 3′-UTR of lin-14, thereby negatively regulating its function via an antisense RNA–RNA interaction. Furthermore, lin-4 exhibited complementarity to seven regions within the 3′-UTR of lin-14, demonstrating that gene expression was more potently inhibited as more of these non-coding transcripts bound to the mRNA (He and Hannon, 2004). Retrospectively, we can identify the lin-4 gene in C. elegans as the pioneer of a new class of small, non-coding RNAs called microRNA (miRNA) (Lee et al., 1993), which utilize the RNA interference (RNAi) pathway to regulate the expression of protein-encoding genes at post-transcriptional level (He and Hannon, 2004).

The following few years were somewhat quiet at the forefront of miRNA research, with lin-4 mechanism assumed to be a unique event. Meanwhile, RNAi was coming to prominence in 1998 with Fire and Mello (along with their colleagues) reporting double-stranded RNA (dsRNA) to be far more potent at mediating gene suppression in C. elegans than single-stranded antisense RNA (Fire et al., 1998). Interestingly, only small quantities of dsRNA were required to induce post-transcriptional gene silencing (PTGS), and it was hypothesized that an endogenous catalytic or amplification component was mediating mRNA degradation prior to translation (Montgomery et al., 1998). RNAi was soon thereafter reported as an ATP-dependent process in an in vitroDrosophila embryo lysate system where dsRNA was processed into 21–23-nucleotide species that appeared to guide sequence-specific mRNA cleavage (Zamore et al., 2000). When dsRNA was shown by the Tuschl laboratory to be processed into 21–22-nucleotide short interfering RNA (siRNA) by a ribonuclease III enzyme to mediate sequence-specific RNAi in human embryonic kidney HEK-293 cells, the prospect was set forth for exogenous 21–22-nucleotide siRNA to be developed as gene-specific therapeutic molecules (Elbashir et al., 2001a).

With incredible excitement surrounding the implications of RNAi, Ruvkun and colleagues discovered a second miRNA inC. elegans in 2000. Like lin-4, the newly discovered let-7 exhibited complementarity to the 3′-UTR of heterochronic genes, in this case lin-14, lin-28, lin-41, lin-42, and daf-12 (Reinhart et al., 2000). Moreover, they discovered that let-7 was highly conserved in its temporal regulation across phylogeny (Pasquinelli et al., 2000), refuting the widely believed concept that lin-4 and let-7 were a worm-specific oddity and propelling miRNA to significance as native endogenous clients of the RNAi machinery. This catalysed intense genome-wide searches for the discovery of more endogenous small regulatory RNAs in numerous species, to the point that miRBase Release 19 currently contains sequence data for 25141 mature miRNA products in 193 organism species (Kozomara and Griffiths-Jones, 2011).

The significance of non-coding RNA was further illuminated in 2001 when the completion of the human genome project revealed that <2% of the human genome encoded proteins (Lander et al., 2001). It has been realized that the ratio of non-coding to protein-coding DNA in the genome correlates with developmental complexity (Mattick, 2004), and a recent publication has reported on the exponential correlation of miRNA gene number and 3′-UTR length—but not 5′-UTR or coding sequence length—with morphological complexity in animals (Chen et al., 2012). This was measured according to the number of cell types within each organism, and also confirmed earlier observations that 3′-UTR length in housekeeping genes has remained short across organisms, thereby minimizing miRNA-binding site potential and reducing the complexity with which these constitutively expressed genes are regulated (Stark et al., 2005). Today we certainly have a stronger appreciation for RNA molecules to function not only as messengers of protein production, but also as complex regulatory molecules facilitating the intricate control of gene expression required for developmental complexity (Kosik, 2009).

Mechanisms of miRNA function

When considering non-coding RNA function, miRNAs constitute one of the largest classes of endogenous, non-coding regulatory RNA molecules in animals. In their mature form they are ∼19–22 nucleotides in length, and they interact via Watson–Crick binding with regions of complementarity primarily within the 3′-UTR of mRNA transcripts. In doing so, miRNAs act as sequence-specificity guides for the RNAi machinery to mediate repression of target gene expression at post-transcriptional level by negatively regulating mRNA stability and/or protein translation.

miRNA biogenesis

miRNAs are typically transcribed by RNA polymerase II (pol II) as long primary miRNA (pri-miRNA) transcripts, which undergo sequential cleavage into a precursor miRNA (pre-miRNA) transcript before being cleaved again into the mature miRNA duplex (Figure 1). These pri-miRNA transcripts range in length from several hundred nucleotides to several kilobases, can contain either a single miRNA or clusters of several miRNAs, and originate from intronic regions of protein-coding and non-coding genes, as well as from intergenic and exonic regions (Rodriguez et al., 2004; Saini et al., 2007). The microprocessor complex is responsible for mediating pri-miRNA cleavage, with the dsRNA-binding protein DGCR8 (DiGeorge syndrome critical region gene 8) binding the pri-miRNA and positioning the catalytic site of Drosha—a ribonuclease III (RNase III) dsRNA-specific endonuclease—11 nucleotides from the base of the duplex stem to mediate nuclear processing to the pre-miRNA transcript (Denli et al., 2004; Han et al., 2006). This produces a pre-miRNA hairpin typically 55–70 nucleotides in length with a two-nucleotide 3′ overhang, characteristic of RNase III-mediated cleavage (Lee et al., 2003). This two-nucleotide overhang facilitates the subsequent exportation of the pre-miRNA from the nucleus to the cytoplasm by a RanGTP/Exportin5-dependent mechanism and is suspected to also facilitate subsequent cleavage by the RNase III endonuclease Dicer (Yi et al., 2003; Bohnsack et al., 2004; Lund et al., 2004). This cleavage requires the interaction of Dicer with the dsRNA-binding protein TRBP [HIV-1 transactivating response (TAR) RNA-binding protein] (Forstemann et al., 2005), and as a result of Dicer processing the terminal base pairs and the loop of the pre-miRNA are excised. This produces a 19–22-nucleotide mature miRNA duplex, which possess two-nucleotide overhangs at each 3′ end (Lee et al., 2002).

 

Figure 1

http://jmcb.oxfordjournals.org/content/early/2013/03/01/jmcb.mjt004/F1.medium.gif

Figure 1

A model for canonical miRNA biogenesis and function in animals. After their transcription by RNA polymerase II, pri-miRNAs are cleaved in the nucleus by Drosha, which forms a microprocessor complex with DGCR8. This generates the pre-miRNA, which is actively exported into the cytoplasm via a RanGTP/Exportin 5-dependent mechanism. In the cytoplasm, Dicer binds the base of the pre-miRNA stem defined in the nucleus by Drosha. Dicer cleavage liberates a mature miRNA duplex that exhibits imperfect complementarity. This miRNA duplex is assembled into the miRISC loading complex, in which the passenger strand is discarded. The miRNA guides the mature miRISC to regions of complementarity within mRNA transcripts, thereby mediating post-transcriptional gene silencing through translational repression and/or mRNA degradation.

miRISC loading

After their maturation into small RNA duplexes, miRNAs are loaded into ribonucleoprotein (RNP) complexes, often referred to as miRNA-induced silencing complexes (miRISCs), RISCs, or miRNPs. The signature components of each miRISC are the miRNA and an Argonaute (AGO) protein. In humans, there are four AGO proteins (AGO1-4), each consisting of the highly conserved P-element-induced wimpy testes (PIWI), middle (MID), and PIWI-AGO-Zwille (PAZ) domains, along with a less-conserved terminal domain. The loading of the miRNA into this protein complex has been proposed to occur in tandem with Dicer-mediated miRNA maturation (Gregory et al., 2005;Maniataki and Mourelatos, 2005) and requires ATP hydrolysis with additional chaperone proteins to create an open conformation to facilitate loading of the miRNA duplex (Liu et al., 2004; Yoda et al., 2010).

A key feature of miRNA is that while both strands of a small RNA duplex are capable of activating the miRISC, typically only one strand will induce silencing (Khvorova et al., 2003). This asymmetry is primarily governed by the relative thermodynamic properties of the RNA duplex, such that the miRISC-associated helicase preferentially unwinds the miRNA duplex from the end with least resistance in terms of inter-strand hydrogen bonding. The strand with its 5′ end at this less thermodynamically stable end is selected as the guide strand, and proteins such as TRBP or protein kinase, interferon-inducible dsRNA-dependent activator (PACT) are proposed to interact with Dicer to sense this thermodynamic asymmetry (Schwarz et al., 2003; Noland et al., 2011). In doing so, the guide strand is retained in the miRISC, while the other strand (the passenger, or the miRNA* strand) is discarded (Hutvagner, 2005; Matranga et al., 2005). miRNA strand selection also appears to be independent of Dicer processing polarity (Preall et al., 2006), where both ends of a duplex have similar thermodynamic properties, both the miRNA and miRNA* act as the guide strand with similar frequencies (Schwarz et al., 2003). However, strand selection does not always occur according to the axiom of thermodynamic strand asymmetry, with tissue-specific factors appearing to play a role in enabling both the miRNA and miRNA* strands to co-accumulate and function as the guide strand (Ro et al., 2007). For this reason, miRNA nomenclature has advanced beyond the miRNA* system, with the adoption of miRNA-5p and -3p names to indicate whether the mature miRNA sequence is derived from the 5′ or 3′ end of the pre-miRNA transcript.

Once the mature miRNA strand has been isolated in the mature miRISC, the AGO protein functions as an interface for the miRNA to interact with its mRNA targets. Recent characterization of human AGO2 has revealed that the 3′ hydroxyl of the miRNA inserts into a hydrophobic pocket of AGO such that the terminal nucleotide stacks against the aromatic ring of a conserved phenylalanine residue in the AGO PAZ domain (Jinek and Doudna, 2009). Meanwhile, the MID domain forms a binding pocket that anchors the miRNA 5′ phosphate such that this terminal nucleotide is distorted and does not interact with the target mRNA (Ma et al., 2005; Parker et al., 2005).

…….

Since being discovered as regulators of developmental timing in C. elegans, it has become widely established that miRNA-mediated regulation of gene expression is a fundamental biological phenomenon required to facilitate key developmental processes such as cellular proliferation, programmed cell death, and cell lineage determination and differentiation (Bartel, 2009; Ambros, 2011). Their significance is such that 60% of the human genome is predicted to be regulated by miRNA function (Friedman et al., 2009), each miRNA estimated to regulate around 200 target genes (Krek et al., 2005).

Figure 2

http://jmcb.oxfordjournals.org/content/early/2013/03/01/jmcb.mjt004/F2.medium.gif

Figure 2

Characteristic miRNA associated with the proliferation and differentiation of specialized cell types. A number of distinct miRNAs are expressed at specific stages through development to play a vital role in mediating cell proliferation, specification, and differentiation. A number of miRNAs involved in the establishment of specialized cell types are illustrated for neurogenesis (Smirnova et al., 2005;Makeyev et al., 2007; Shen and Temple, 2009; Shi et al., 2010; Zhao et al., 2010), myogenesis (Chen et al., 2006; Kim et al., 2006), haematopoiesis (Chen et al., 2004; Georgantas et al., 2007;Vasilatou et al., 2010), oligodendrocyte differentiation (Lau et al., 2008; Dugas et al., 2010), as well as induced pluripotent stem (iPS) cell reprogramming (Miyoshi et al., 2011).

 

miRNAs play a central role in establishing the spatiotemporal gene expression patterns required to establish specialized cell types and promote developmental complexity. The inherent complexity of miRNA function, however, requires a scientific approach in which context-specific miRNA function must be acknowledged if advancements are to be made in understanding how these small regulatory RNA molecules function in various developmental and pathophysiological processes. While this requires an appreciation for mechanistic aspects such as non-redundant miRISC function and the dynamic regulatory outcomes this facilitates, arguably the greatest challenge facing miRNA biology is the identification of the many genes that each miRNA targets and an understanding of the context-specific factors that determine when and how these genes are regulated.

 

 

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Introduction to Subcellular Structure

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

 

 

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

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

I here list the organelles:

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

cell_organelle_quiz

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

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

Golgi Apparatus

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

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

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

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

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

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

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

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

Nucleus_ER_golgi

Nucleus_ER_golgi

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

Exocytotic vesicles

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

Secretory vesicles

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

Lysosomal vesicles

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

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

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

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

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

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

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

endoplasmic_reticulum

endoplasmic_reticulum

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

Cytoskeleton

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

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

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

nuclear pores in nuclear envelope

nuclear pores in nuclear envelope

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

nuclear envelope and FG filaments

nuclear envelope and FG filaments

nuclear envelope and FG filaments

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

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

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

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

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Targeting Untargetable Proto-Oncogenes

Curators: Larry H. Bernstein, MD, FCAP and Aviva Lev-Ari, PhD, RN

The following is a summary of a just published cancer research paper that describes the discovery of targetting proteins previously thought to be untargetable.

Getting Around “Undruggable” Proto-Oncogenes

Patricia Fitzpatrick Dimond, Ph.D.
The Notch1 protein and BET bromodomains are among the targets researchers are investigating. [© iQoncept – Fotolia.com]
    While multiple human cancers are associated with oncogene amplification,
  • epigenetic targets causing amplification such as transcription factors were once considered “undruggable,” or
  • unlikely to be modulated with a small molecule drug.
Generally, these proteins lack surface involutions suitable for high-affinity binding by small molecules. But by thinking outside the “loop” or the usual structures required for drug targets, investigators have been making headway in targeting the formerly untargetable.
    Multiple human cancers are associated with c-Myc gene amplification including lung carcinoma breast carcinoma, colon carcinoma, and neuroblastoma. The protogene also plays a key role in cell cycle regulation, metabolism, apoptosis, differentiation, cell adhesion, as well as in tumorigenesis, and participates in regulating hematopoietic homeostasis. Its gene product functions as a transcription regulator, part of
an extensive network of interacting factors regulating the expression, it has been estimated, of more than 15 percent of all human genes.
    While Myc oncogene family members, for example, act as key drivers in human cancers,
  • they have been considered undruggable as
  • they encode transcription factors and carry out essential functions in proliferative tissues,
  • suggesting that their inhibition could cause severe side effects.
And from a chemist’s point of view, these proteins’ surfaces are not amenable to binding drugs. In an online dialog posted on the NCI’s website in October of 2010, an investigator noted, “We don’t know how to interfere with these factors or their activities in clinical settings because, in general,
  • we lack the means to inhibit proteins that are not enzymes.”
    But by preventing key protein-protein interactions that enable the actions of these transcriptional drivers, scientists are drugging the formerly undruggable.

To Drug the Undruggable Target

    One such approach published  in Nature in 2009 by a team of Harvard scientists who was reported that they had successfully targeted a “master” protein, Notch1, which had been considered “untouchable” by conventional drugs. The protein is a
  • key transcription factor regulating genes involved in cell growth and survival but
  • like other transcription factors has proven an elusive drug target due to its structure.
The scientists said they had designed
  • a synthetic, cell-permeable alpha-helical peptide, SAHM1,
  • which could target a critical protein-protein interface in the notch transactivation complex.
The drug molecule enters cells and interferes with a protein-protein interaction essential for the transmission of cell growth signals via the Notch pathway.
    The researchers tested the drug using cells from patients with T-cell acute lymphoblastic leukemia (T-ALL) and a mouse model of the disease. The Notch1 gene is mutated in half of patients with T-ALL and
  • produces an inappropriately active Notch1 protein.
Activated Notch signaling has been seen in several other cancers including lung, ovarian, and pancreatic cancer, and melanoma.
    “We’ve drugged a so-called undruggable target,” said Gregory L. Verdine, Ph.D., Erving professor of chemistry at Harvard University. “This study validates the notion that you can target a transcription factor
  • by choosing a new class of molecules, namely stapled peptides.”

He added that, because the molecular logic of these proteins is similar to Notch1’s,

  • this strategy might work for other transcription factors as well.

Targeting BET

    Another emerging approach to drugging the undruggable is to target the bromo and extra C-terminal domain (BET) family of bromodomains that are
  • involved in binding epigenetic “marks” on histone proteins.
Four members of this 47-protein family interact with chromatin including histone acetylases and nucleosome remodeling complexes. Bromodomain proteins act as chromatin “readers” to recruit chromatin-regulating enzymes, including
  • “writers” and “erasers” of histone modification, to target promoters and to regulate gene expression.
As mentioned in a previous GEN article, epigenetic control systems generally involve three types of proteins:
  1. “writers”,   Writers attach chemical marks, such as methyl groups (to DNA) or acetyl groups (to the histone proteins that DNA wraps around)
  2. “readers”,  Readers bind to these marks, thereby influencing gene expression
  3. “erasers.”  Erasers remove the marks
    While investigators have considered that the precise function of the so-called BET bromodomain remains incompletely defined,
  • proteins containing this domain have become another epigenetic target for drug development companies.
  • these domains may allow researchers a way to get at oncogenic targets that were once thought undruggable including the proto-oncogene Myc.
    Small molecule inhibition of BET protein bromodomains also selectively suppresses other genes such as Bcl-2 that have important roles in cancer, as well as some NF-κB-dependent genes that have roles in both cancer and inflammation. Small molecule inhibition of BET bromodomains
  • leads to selective killing of tumor cells across a range of hematologic malignancies and in subsets of solid tumors.
In particular, the bromodomain protein, BRD4, has been identified recently as a therapeutic target in acute myeloid leukemia, multiple myeloma, Burkitt’s lymphoma, human nuclear protein in testis (NUT) midline carcinoma, colon cancer, and inflammatory disease;
  • its loss is a prognostic signature for metastatic breast cancer.
    BRD4 also contributes to regulation of both cell cycle and transcription of oncogenes, HIV, and human papilloma virus (HPV). Despite its role in a broad range of biological processes, the precise molecular mechanism of BRD4 function, until very recently, remained unknown.
    In 2010, investigators reported in Nature that they had identified a cell-permeable small molecule that bound competitively to bromodomains, or acetyl-lysine recognition motifs. Competitive binding by the small molecule JQ1, the investigators reported,
  • displaces the BRD4 fusion oncoprotein from chromatin,
  • prompting squamous differentiation and
  • specific antiproliferative effects in BRD4-dependent cell lines and patient-derived xenograft models.
    The authors say that these data established proof-of-concept for targeting protein–protein interactions of epigenetic readers, and could provide a versatile
  • chemical scaffold for the development of chemical probes more broadly throughout the bromodomain family.
    More recently, writing in the Journal of Medicinal Chemistry, investigators at GlaxoSmithKline reported that they had successfully optimized
a class of benzodiazepines as BET bromodomain inhibitors, apparently without any prior knowledge of identified molecular targets.
Significant medicinal chemistry provided the bromodomain inhibitor, I-BET762 or GSK525762, which is currently in a Phase I clinical trial for the treatment of NUT midline carcinoma, a rare but lethal form of cancer, and other cancers.

 Casting a Wide Net

    Constellation Pharmaceuticals of Cambridge, MA, announced that it has initiated a Phase I clinical trial of CPI-0610, a novel small molecule BET protein bromodomain inhibitor, in patients with previously treated and progressive lymphomas. This first-in-human trial is currently open at Sarah Cannon Research Institute in Nashville, Tennessee, and at the John Theurer Cancer Center in Hackensack, New Jersey. Additional study sites in the U.S. will join the trial over the next several months. Studies of CPI-0610 are also planned in patients with multiple myeloma and in patients with acute leukemia or myelodysplastic syndrome.
    Constellation’s CMO, Michael Cooper, M.D. told GEN that “small molecule inhibitors of BET protein bromodomains have demonstrated broad activity against hematologic malignancies in preclinical models. And this activity can be achieved in vivo with levels of compound exposure that are well tolerated. While we are encouraged by these observations, what really makes the area interesting is
  • the novel mechanism by which BET protein bromodomain inhibitors elicit their biologic effects.
  • They disrupt the interaction of BET proteins with acetylated lysine residues on histones and thereby
  • suppress the transcription of key cancer-related genes such as MYC, BCL-2, and a subset of NF-κB-dependent genes.
These genes have in the past been difficult to target with small molecules. In light of the breadth of the activity in preclinical models of hematologic malignancies and the important genes that are targeted, we intend to cast a wide net across hematologic malignancies in the clinic.”
    Robert Sims, Ph.D., and senior director of biology at Constellation explained that BET protein bromodomain inhibition is only of several areas of interest for the company. “The BET proteins constitute one class of epigenetic targets, namely
  • molecules that recognize patterns in chromatin architecture and
  • either enhance or suppress gene transcription.
Constellation’s approach to epigenetics also includes programs in the enzymes that modify the architecture of chromatin, for example by the
  • methylation or demethylation of histone proteins (writers and erasers, respectively).
Even though our first drug candidate is directed against a set of reader proteins, we are also looking at inhibitors of the writer protein, EZH2, which is mutated in some types of non-Hodgkin lymphoma and overexpressed in many malignancies.”
    In January 2012, Constellation and Genentech announced collaboration based on the science of epigenetics and chromatin biology to discover and develop innovative treatments for cancer and other diseases. Each company will each commit a significant portion of their research and development efforts to the advancement of programs under the collaboration, and each party will have the right to retain exclusive rights to programs emerging from the collaboration.
    And more biotech giants can be expected to enter the field of epigenetics as smaller companies advance into the clinic with this novel approach to controlling gene expression gone wrong in cancer cells.
Patricia Fitzpatrick Dimond, Ph.D. (pdimond@genengnews.com), is technical editor at Genetic Engineering & Biotechnology News
Employing Metabolomics in Cell Culture and Bioprocessing: Gaining greater predictability, control and quality
Challenges in developing and producing biotherapeutics are numerous and dynamic, including various market drivers and industry responses. Finding effective measures to support a foundation of control, predictability, and quality have been a concern and have paved the way to seeking out and applying newer technologies such as metabolomics successfully to bioprocessing. This webinar will first navigate through the landscape and challenges in developing and producing biotherapeutics. The journey continues with a walk through of the rationale for why metabolomics is a key tool for addressing critical bioprocessing needs followed by specific case studies and examples of how a functional metabolomic approach has been applied.
There are many relevant applications for functional metabolomics in bioprocessing starting with process development that include being able to: boost titer or productivity, improve product quality, enhance viability, or optimize defined media. The technology has be employed in biomarker discovery applications for the following purposes: to identify predictors of lactate consumption, to assess product quality, to predict indicative biomarkers of bioreactor performance or identify ideal clones. Lastly, functional metabolomics has been applied to enrich DOE experiments and troubleshooting for: historical deviation, process transfer, scale-up issues, disposable concerns, and lot or performance changes.

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An illustration of the central dogma of molecu...

An illustration of the central dogma of molecular biology annotated with the processes ncRNAs are involved in. (Photo credit: Wikipedia)

X-ray structure of the tRNA Phe from yeast. Da...

X-ray structure of the tRNA Phe from yeast. Data was obtained by PDB 1ehz and rendered with PyMOL. violet: acceptor stem wine red: D-loop blue: anticodon loop orange: variable loop green: TPsiC-loop yellow: CCA-3′ of the acceptor stem grey: anticodon (Photo credit: Wikipedia)

 Our genome must be packed tightly to fit into the nucleus. Genome is the blue print of a living organism whether made up off a single or multiple cell.   Recently, the genome seen as a functional network of physical contacts within (cis) and between (trans) chromosomes.  It became necessary to map these physical DNA contacts at high-resolution with technologies such as the “chromosome conformation capture” (3C) and other 3C-related methods including 3C-Carbon Copy (5C) and Hi-C.  Yet, we all know that in vivo conformation, gene to gene interactions from a long distance, histones and 3D have an impact on gene regulation and expression.  The game is not just a sequence but functional genomics with a correct translation of sequence for development so that proper molecular diagnostics can be applied not only for prevention but also for monitoring the efficacy of the intervention. Thus, we can provide a targeted therapy for personalized medicine.

On the other hand, we still know very little about genome organization at the molecular level, although spatial genome organization can critically affect gene expression.  It is important to recognize who is there to be present and who is there to create the functional impact for regulation in a specific tissue and time.  In addition, mediation of these chromatin contacts based on a specific tissue is quite essential.  For example, during long-range control mechanism specific enhancers and distal promoters needed to be invited to a close physical proximity to each other by transcription factors that has been found at other loci.  Furthermore, chromatin-binding proteins such as the CCCTC-binding factor (CTCF) and cohesin seem to have critical roles in genome organization and gene expression.  Let’s not forget about epigenetics, since there are so many methods to regulate chromatin interactions like cytosine methylation, maternal gene, gradient level, post-translational modifications and non-coding RNAs.

The non-coding RNAs (ncRNAs) are silent but they have the 99% power because ncRNAs are a broad class of transcripts consisting of structural (rRNAs, tRNAs, snRNAs, snoRNAs, etc.), regulatory (miRNAs, piRNAs, etc.), and of sense/antisense transcripts.  Among these an interesting class is the latter group.   This class includes transcriptional “features” (eRNAs, tiRNAs), and a very large number of long non-coding RNAs (lncRNAs), length from 200 nt to 100 kb.  The magnificent future of lncRNAs comes from their production, as they can be transcribed nearby known protein-coding genes or from their introns. As a result, because of their intergenical production they are also called as “lincRNAs (long intergenical non-coding RNAs).  They are abundant and specific as microRNAs.  Hence, their inclusion into the biomarker list and assuming their roles during targeted therapy don’t require us to be a wizard but a functional genomicist knowing evolution, development and molecular genetics and plus signaling.

lincRNA can both activate and repress the gene either cis or trans acting to effect gene regulation will be discussed next.

As a result, one gene expression regulation needs from twenty to several hundred genes. As they say raising a child needs a village.

References:

“Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs”.

Rinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, Brugmann SA, Goodnough LH, Helms JA, Farnham PJ, Segal E, Chang HY.  Cell. 2007 Jun 29; 129(7):1311-23.

“Long noncoding RNA as modular scaffold of histone modification complexes”

Tsai MC, Manor O, Wan Y, Mosammaparast N, Wang JK, Lan F, Shi Y, Segal E, Chang HYScience. 2010 Aug 6; 329(5992):689-93.

“Capturing Chromosome Conformation”.

Dekker J, Rippe K, Dekker M, Kleckner N.Science.2002;295:1306–1311.

“Chromosome Conformation Capture Carbon Copy (5C): a massively parallel solution for mapping interactions between genomic elements”.

Dostie J, Richmond TA, Arnaout RA, Selzer RR, Lee WL, Honan TA, Rubio ED, Krumm A, Lamb J, Nusbaum C, Green RD, Dekker J.Genome Res. 2006;16:1299–1309.

“Chromosome conformation capture carbon copy technology”.

Dostie J, Zhan Y, Dekker J. Curr. Protoc. Mol. Biol. 2007 Chapter 21, Unit 21 14.

“Comprehensive mapping of long-range interactions reveals folding principles of the human genome”.

Lieberman-Aiden E, van Berkum NL, Williams L, Imakaev M, Ragoczy T, Telling A, Amit I, Lajoie BR, Sabo PJ, Dorschner MO, Sandstrom R, Bernstein B, Bender MA, Groudine M, Gnirke A, Stamatoyannopoulos J, Mirny LA, Lander ES, Dekker J.  Science. 2009;326:289–293.

“Chromatin conformation signatures: ideal human disease biomarkers?”

Crutchley JL, Wang XQ, Ferraiuolo MA, Dostie J.Biomark. Med. 2010;4:611–629.

“Relationship between CAD risk genotype in the chromosome 9p21 locus and gene expression. Identification of eight new ANRIL splice variants”.

Folkersen L, Kyriakou T, Goel A, Peden J, Mälarstig A, Paulsson-Berne G, Hamsten A, Hugh Watkins, Franco-Cereceda A, Gabrielsen A, Eriksson P, PROCARDIS consortia

PLoS One. 2009 Nov 2; 4(11):e7677.

” A myelopoiesis-associated regulatory intergenic noncoding RNA transcript within the human HOXA cluster”.

Zhang X, Lian Z, Padden C, Gerstein MB, Rozowsky J, Snyder M, Gingeras TR, Kapranov P, Weissman SM, Newburger PE.  Blood. 2009 Mar 12; 113(11):2526-34.

Monk M.   Genes Dev. 1988 Aug; 2(8):921-5.

Hox genes specify vertebral types in the presomitic mesoderm

Marta Carapuço,1 Ana Nóvoa,1 Nicoletta Bobola,2 and Moisés Mallo1,3 .  Genes Dev. 2005 September 15; 19(18): 2116–2121.

Krumlauf R.  Cell. 1994 Jul 29; 78(2):191-201.

“Noncoding RNA synthesis and loss of Polycomb group repression accompanies the colinear activation of the human HOXA cluster”.

Sessa L, Breiling A, Lavorgna G, Silvestri L, Casari G, Orlando V.  RNA. 2007 Feb; 13(2):223-39.

“Functional demarcation of active and silent chromatin domains in human HOX loci by noncoding RNAs”.

Rinn JL, Kertesz M, Wang JK, Squazzo SL, Xu X, Brugmann SA, Goodnough LH, Helms JA, Farnham PJ, Segal E, Chang HY.  Cell. 2007 Jun 29; 129(7):1311-23.

“Long noncoding RNAs with enhancer-like function in human cells”.

Ørom UA, Derrien T, Beringer M, Gumireddy K, Gardini A, Bussotti G, Lai F, Zytnicki M, Notredame C, Huang Q, Guigo R, Shiekhattar R

“Histone modifications at human enhancers reflect global cell-type-specific gene expression”.

Heintzman ND, Hon GC, Hawkins RD, Kheradpour P, Stark A, Harp LF, Ye Z, Lee LK, Stuart RK, Ching CW, Ching KA, Antosiewicz-Bourget JE, Liu H, Zhang X, Green RD, Lobanenkov VV, Stewart R, Thomson JA, Crawford GE, Kellis M, Ren B.   Nature. 2009 May 7; 459(7243):108-12.

“Tiny RNAs associated with transcription start sites in animals”.

Taft RJ, Glazov EA, Cloonan N, Simons C, Stephen S, Faulkner GJ, Lassmann T, Forrest AR, Grimmond SM, Schroder K, Irvine K, Arakawa T, Nakamura M, Kubosaki A, Hayashida K, Kawazu C, Murata M, Nishiyori H, Fukuda S, Kawai J, Daub CO, Hume DA, Suzuki H, Orlando V, Carninci P, Hayashizaki Y, Mattick JS.  Nat Genet. 2009 May; 41(5):572-8.

“Chromatin modifications and their function”.

Kouzarides T.   Cell. 2007 Feb 23; 128(4):693-705.

Tripathi V, Ellis JD, Shen Z, Song DY, Pan Q, Watt AT, Freier SM, Bennett CF, Sharma A, Bubulya PA, Blencowe BJ, Prasanth SG, Prasanth KV.   Mol Cell. 2010 Sep 24; 39(6):925-38.

Selected Further Reading

“Small and long non-coding RNAs in cardiac homeostasis and regeneration”

Ounzain, S.; Crippa, S.; Pedrazzini, T.  BBA – Molecular Cell Research vol. 1833 issue 4 April, 2013. p. 923-933

“Regulatory mechanisms of long noncoding RNAs in vertebrate central nervous system development and function.” 

Knauss, J.L.; Sun, T.  “Neuroscience vol. 235 April 3, 2013. p. 200-214

“Comparative genomics reveals ‘novel’ Fur regulated sRNAs and coding genes in diverse proteobacteria.”

Sridhar, J.; Sabarinathan, R.; Gunasekaran, P.; Sekar, K.   Gene vol. 516 issue 2 March 10, 2013. p. 335-344 DOI: 10.1016/j.gene.2012.12.057. ISSN: 0378-1119.

miRNAs Regulate Expression and Function of Extracellular Matrix Molecules”

Rutnam, Z.J.; Wight, T.N.; Yang,  B.B.Matrixixix Biology vol. 32 issue 2 March 11, 2013. p. 74-85 DOI: 10.1016/j.matbio.2012.11.003. ISSN: 0945-053X.

Transcript profiling of microRNAs during the early development of the maize brace root via Solexa sequencing

Liu, P.; Yan, K.; Lei, Y.x.; Xu, R.; Zhang, Y.m.; Yang, G.d.; Huang, J.g.; Wu, C.A.; Zheng, C.C.Genomics vol. 101 issue 2 February, 2013. p. 149-156 DOI: 10.1016/j.ygeno.2012.11.004. ISSN: 0888-7543.

Regulatory mechanisms of long noncoding RNAs in vertebrate central nervous system development and function

Knauss, J.L.; Sun, T.  Neuroscience vol. 235 April 3, 2013. p. 200-214 DOI: 10.1016/j.neuroscience.2013.01.022. ISSN: 0306-4522.

“The dynamic biliary epithelia: Molecules, pathways, and disease”

O’Hara, Steven P.; Tabibian, James H.; Splinter, Patrick L.; LaRusso, Nicholas F. Journal of Hepatology vol. 58 issue 3 March, 2013. p. 575-582 DOI: 10.1016/j.jhep.2012.10.011. ISSN: 0168-8278

ABBREVIATIONS

3C = Chromosome conformation capture

rRNAs = Ribosomal RNAs

tRNAs = Transfer RNAs

snRNAs = Small nuclear RNAs

snoRNAs = Small nucleolar RNAs

miRNAs = MicroRNAs

piRNAs = Piwi-interacting RNAs

eRNAs = Enhancer RNAs

tiRNAs = Transcription initiation RNAs

spliRNAs = Splice-site RNAs

lincRNAs = Long intergenic non-coding RNAs

lncRNPs = Long non-coding ribonucleoprotein complexes

Igf2r = Insulin-like growth factor II receptor

HMTs = Histone methyl transferases

TSSs = Transcriptional start sites

TFs = Transcription factors

RNAi = RNA interference

PTMs = Post-translational modifications

  • Patent. (postdocstreet.wordpress.com)

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Transcript Dynamics of Proinflammatory Genes

Author: Larry H Bernstein, MD, FCAP

Transcript Dynamics of Proinflammatory Genes Revealed by Sequence Analysis of Subcellular RNA Fractions

DM Bhatt, A Pandya-Jones, Ann-Jay Tong, I Barozzi, MM Lissner, et al.
Cell 2012;150: 279–290

In addition to documenting the subcellular locations of coding and noncoding transcripts, the results provide a high-resolution view of the relationship between
  • defined promoter and chromatin properties and
    • the temporal regulation of diverse classes of coexpressed genes.
The data also reveal a striking accumulation of full-length yet incompletely spliced transcripts in the chromatin fraction, suggesting that
  • splicing often occurs after transcription has been completed,
  • with transcripts retained on the chromatin until fully spliced.
Summary
Macrophages respond to inflammatory stimuli by modulating the expression of hundreds of genes in
  • a defined temporal cascade,
  • with diverse transcriptional and posttranscriptional mechanisms contributing to the regulatory network.
We examined proinflammatory gene regulation in activated macrophages by
  • performing RNA-seq with fractionated chromatin-associated, nucleoplasmic, and cytoplasmic transcripts.
This methodological approach allowed us
  • to separate the synthesis of nascent transcripts from transcript processing and
  • the accumulation of mature mRNAs.
In addition to documenting the subcellular locations of coding and noncoding transcripts,
the results provide a high-resolution view of the relationship between
  • defined promoter and chromatin properties and
  • the temporal regulation of diverse classes of coexpressed genes.
The data also reveal a striking accumulation of full-length yet incompletely spliced transcripts in the chromatin fraction, suggesting that
  • splicing often occurs after transcription has been completed, with transcripts retained on the chromatin until fully spliced.

Two independent experiments were performed with lipid A-stimulated bone marrow-derived macrophages. The two experiments made use of different macrophages prepared from different mice, several months apart.(A) Pearson pair-wise correlation values (R) derived from an analysis of greater than 500 lipid A-induced genes (>5-fold induced) are shown. Each time point from the first experiment, A, was compared to every other time point from the same experiment and from the second experiment, B.(B) Hierarchical clustering of the R-values from panel A was performed. This analysis reveals that, when only induced genes are considered, each time point from each experiment correlates more closely with the corresponding time point from the other experiment than with any of the other time points from either experiment.(C)

This analysis reveals that, when the transcript levels of expressed genes are compared,
  • each time point from a given experiment correlates with the same time point from the independent experiment.
The results reveal close correlations between all time-points from both experiments, presumably because genes that are consistently unexpressed (i.e., not counted in B) are contributing to the high degree of correlation. Nevertheless, the time points of each independent experiment still have the highest degree of correlation with each other.
Hierarchical clustering of the R values from panel D was performed. As with other clusterings, each sample clusters with its cognate time point in the independent experiment
Highlights
► Coding and noncoding transcripts exhibit characteristic subcellular distributions
► The most potently induced genes favor promoters with low CpG content
► Full-length, incompletely spliced transcripts accumulate on the chromatin
► Delayed transcript release may reflect a requirement for the completion of splicing
Eukaryotic transcription overview

Eukaryotic transcription overview (Photo credit: Allen Gathman)

English: Nucleosome structure.

English: Nucleosome structure. (Photo credit: Wikipedia)

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