Research Area: Computational Biology

A Troubling Inheritance
Greta Friar | Whitehead Institute
April 9, 2019

CAMBRIDGE, MA — Cancers have a habit of running in the family. This is due in large part to the inheritance of versions of genes that are linked with cancer, but some researchers are investigating another heritable risk factor: epigenetic modifications. These are not changes in the DNA sequence of a gene itself but rather are processes that change a DNA sequence’s accessibility or ability to be expressed. These changes can regulate gene expression, and in certain circumstances, be passed down from parent to child alongside the genes they regulate. New research published in eLife on April 9 from the lab of Whitehead Member and Institute Director David Page, also a professor of biology at the Massachusetts Institute of Technology and a Howard Hughes Medical Institute investigator, and colleagues has found evidence that when atypical epigenetic modifications, or marks, caused by a gene deletion in the parent’s cells, are inherited it can lead to increased cancer incidence and shorter lifespans in mice.

Studying epigenetic inheritance in mammals can be difficult because mammalian embryos undergo strong epigenetic reprogramming, a kind of “erasing and starting over” for the next generation. Some of the parents’ epigenetic marks resist this reprogramming, but the vast majority are erased, and often what may appear to be epigenetic inheritance can be explained by other factors like environmental exposures during fetal development leading to similar epigenetic profiles.

“We had to design an experiment with a specific, well-defined initiating event, so the epigenetic patterns and health effects would be easy to track,” says first author Bluma Lesch, then a postdoctoral researcher in the Page lab at Whitehead Institute and now an assistant professor of Genetics at Yale School of Medicine and a member of the Genomics, Genetics and Epigenetics Program at Yale Cancer Center.

In order to do this, the researchers first deleted Kdm6a (also called Utx), a gene on the X chromosome that encodes a protein involved in epigenetic regulation, in the male mouse germline—the repository of cells that become sperm. Kdm6a removes epigenetic modifications from histones, the spool-like proteins that house strands of DNA. Deleting Kdm6a led to higher than usual levels of specific types of histone modifications in the genome of the mice’s sperm, which in turn prompted a secondary epigenetic shift, an increase in DNA methylation—the addition of a methyl group to DNA that can alter gene expression.

The researchers used the hypermethylated sperm to create a generation of offspring. A crucial aspect of the experiment was creating offspring that inherited the atypical epigenetic marks but not the gene deletion that caused them in order to uncouple the effects of the two changes. Offspring were bred from a modified male germline and an unmodified female germline, so male offspring inherited a healthy X chromosome from their mothers, and an unaffected Y chromosome from their fathers. Genetically, the mice were normal, but they were formed from sperm that had been exposed to the Kdm6a deletion’s epigenetic effects.

When the researchers studied the epigenome of these offspring, they found that while many of the modifications had been erased due to reprogramming, more than 200 of the sections of DNA that had been hypermethylated in the father’s germline following Kdm6a deletion were likewise hypermethylated in the offspring. That persistence is much higher than would be expected by chance or observed in normal mice. The researchers found matching instances of hypermethylation in the offspring’s bone marrow, liver tumors, and spleen, indicating that the inherited epigenetic changes stuck with the offspring though embryonic development into adulthood. The researchers did not pinpoint the mechanism that allowed these epigenetic marks to resist reprogramming; Lesch hopes to pursue that question in the future.

Then the researchers watched the mice grow, waiting to see how the unusual DNA methylation would affect the mice’s health. For a while, the mice appeared perfectly healthy — until they hit middle age. The mice then began developing tumors, experiencing an increase in cancer incidence and a decrease in lifespan.

To get a better understanding of the effects they were seeing, Page and Lesch sought help from cancer experts Benjamin Ebert, chair of medical oncology at the Dana Farber Cancer Institute (DFCI) and member of the Broad Institute; Zuzana Tothova, DFCI investigator and associate member of the Broad Institute; and Roderick Bronson, veterinary pathologist at Harvard Medical School. The experts helped characterize the mice’s diseases. Instead of becoming more susceptible to one specific type of cancer, the mice had a diverse set of diagnoses, similar to what would be expected of normal mice at a much older age. The researchers believe this is due to hypermethylation that they observed in enhancers, regions of DNA that help increase transcription of many genes but are also commonly implicated in cancer.

Although the researchers cannot say whether the same sort of epigenetic inheritance is occurring in humans, they believe that this is a valuable question for future research. Inherited epigenetic marks would not appear in a typical genetic screen for cancer risk, and as such could be overlooked to the detriment of preventative care. Likewise, the researchers note, cancer drugs that target epigenetic mechanisms are on the rise, and there has been no research into the effects that this might have on children conceived by people taking the drugs. If human embryos are inheriting aberrant epigenetic marks in the manner observed in mice in this investigation, then people taking drugs with epigenetic targets should be warned against conceiving children until after they are clear of the effects of their medication.

“We hope that this research demonstrating the cancer risk of inherited epigenetic marks in mice adds to the burgeoning field of mammalian epigenetic inheritance research,” Page says, “and that we have drawn attention to the possible implications for human health.”

 

Written by Greta Friar

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David Page’s primary affiliation is with Whitehead Institute for Biomedical Research, where his laboratory is located and all his research is conducted. He is also a Howard Hughes Medical Institute Investigator and a Professor of Biology at the Massachusetts Institute of Technology.

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Full citation:

“Intergenerational epigenetic inheritance of cancer susceptibility in mammals”

eLife, April 9, 2019, DOI: https://doi.org/10.7554/eLife.39380

Bluma J. Lesch, Zuzana Tothova, Elizabeth A. Morgan, Zhicong Liao, Roderick T. Bronson, Benjamin L. Ebert, and David C. Page.

Start signal for sex cell creation
Greta Friar | Whitehead Institute
February 27, 2019

Cambridge, MA — Cells can divide and multiply in two ways: mitosis, in which the cell replicates itself, creating two copies identical to the original; or meiosis, in which the cell shuffles its DNA and divides twice, creating four genetically unique cells, each with half of the original cell’s number of chromosomes. In mammals, these latter cells become eggs and sperm.

How do germ line cells, the repository of cells that create eggs and sperm, know when to stop replicating themselves and undergo meiosis? Researchers had been aware that a protein called STRA8, which is only active in germ line cells, was involved in initiating meiosis, but they did not know how. New research from Whitehead Member and Institute Director David Page, also a professor of biology at Massachusetts Institute of Technology and an investigator with Howard Hughes Medical Institute; Mina Kojima, formerly a Massachusetts Institute of Technology graduate student and now a postdoctoral researcher at Yale; and visiting scientist Dirk de Rooij has revealed that in mice, STRA8 initiates meiosis by activating and amplifying a network of thousands of genes. This network includes genes involved in the early stages of meiosis, DNA replication, and other cell division processes. The research was published in eLife on February 27, 2019.

In the past, researchers have had difficulty collecting enough cells on the cusp of meiosis to investigate STRA8’s role. In mammals, germ line cells are inside the body, difficult to access, and they begin meiosis in staggered fashion so few cells are at the same stage during an extraction. Researchers in Page’s lab had previously come up with an approach to solve this problem using developmental synchronization, manipulating the cells’ exposure to the chemical that triggers their development in order to prompt all of the cells to begin meiosis simultaneously. Once the cells were synced up, first author Kojima could get a large enough sample to observe patterns in gene expression leading up to and during meiosis, and to figure out where STRA8 is binding.

She found that STRA8 binds to the regulatory portions of DNA called promoter regions, which initiate or increase transcription of adjacent genes, of most critical meiosis genes. With some exceptions, STRA8 does not switch genes from off to on. Rather, genes in the STRA8-regulated network are already expressed at low levels and STRA8 binding massively ramps up their production. The researchers posit that meiosis is then initiated once the genes reach a threshold of expression. This finding sheds light on instances in previous studies in which researchers found meiosis-related genes active in cells not yet undergoing meiosis.

The researchers were surprised to find that STRA8 also amplifies many genes involved in mitosis. However, they suggest that the meiosis-specific genes activated by STRA8 take precedence in determining which of the two cell-cycle processes the cell will undergo. STRA8 regulates certain critical genes, such as Meioc and Ythdc2, which help to establish a meiosis-specific cell-cycle program.

This research enriches our understanding of the process of sexual reproduction. Identifying the expansive STRA8-regulated network has elucidated the start of meiosis: the moment a cell commits to recombining and dividing, relinquishing its genetic identity for the chance to create something — or someone — new.

This work was supported by the National Science Foundation and the Howard Hughes Medical Institute.

 

Written by Greta Friar

***

David Page’s primary affiliation is with Whitehead Institute for Biomedical Research, where his laboratory is located and all his research is conducted. He is also a Howard Hughes Medical Institute Investigator and a Professor of Biology at the Massachusetts Institute of Technology.

***

Full citation:

“Amplification of a broad transcriptional program by a common factor triggers the meiotic cell cycle in mice”

eLife, February 27, 2019, https://doi.org/10.7554/eLife.43738

Mina L. Kojima (1,2), Dirk G. de Rooij (1), and David C. Page (1,2,3)

1. Whitehead Institute, 455 Main Street, Cambridge, MA 02142, USA

2. Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA

3. Howard Hughes Medical Institute, Whitehead Institute, Cambridge, MA 02142, USA

Predicting sequence from structure

Researchers have devised a faster, more efficient way to design custom peptides and perturb protein-protein interactions.

Raleigh McElvery | Department of Biology
February 15, 2019

One way to probe intricate biological systems is to block their components from interacting and see what happens. This method allows researchers to better understand cellular processes and functions, augmenting everyday laboratory experiments, diagnostic assays, and therapeutic interventions. As a result, reagents that impede interactions between proteins are in high demand. But before scientists can rapidly generate their own custom molecules capable of doing so, they must first parse the complicated relationship between sequence and structure.

Small molecules can enter cells easily, but the interface where two proteins bind to one another is often too large or lacks the tiny cavities required for these molecules to target. Antibodies and nanobodies bind to longer stretches of protein, which makes them better suited to hinder protein-protein interactions, but their large size and complex structure render them difficult to deliver and unstable in the cytoplasm. By contrast, short stretches of amino acids, known as peptides, are large enough to bind long stretches of protein while still being small enough to enter cells.

The Keating lab at the MIT Department of Biology is hard at work developing ways to quickly design peptides that can disrupt protein-protein interactions involving Bcl-2 proteins, which promote cancer growth. Their most recent approach utilizes a computer program called dTERMen, developed by Keating lab alumnus, Gevorg Grigoryan PhD ’07, currently an associate professor of computer science and adjunct associate professor of biological sciences and chemistry at Dartmouth College. Researchers simply feed the program their desired structures, and it spits out amino acid sequences for peptides capable of disrupting specific protein-protein interactions.

“It’s such a simple approach to use,” says Keating, an MIT professor of biology and senior author on the study. “In theory, you could put in any structure and solve for a sequence. In our study, the program came up with new sequence combinations that aren’t like anything found in nature — it deduced a completely unique way to solve the problem. It’s exciting to be uncovering new territories of the sequence universe.”

Former postdoc Vincent Frappier and Justin Jenson PhD ’18 are co-first authors on the study, which appears in the latest issue of Structure.

Same problem, different approach

Jenson, for his part, has tackled the challenge of designing peptides that bind to Bcl-2 proteins using three distinct approaches. The dTERMen-based method, he says, is by far the most efficient and general one he’s tried yet.

Standard approaches for discovering peptide inhibitors often involve modeling entire molecules down to the physics and chemistry behind individual atoms and their forces. Other methods require time-consuming screens for the best binding candidates. In both cases, the process is arduous and the success rate is low.

dTERMen, by contrast, necessitates neither physics nor experimental screening, and leverages common units of known protein structures, like alpha helices and beta strands — called tertiary structural motifs or “TERMs” — which are compiled in collections like the Protein Data Bank. dTERMen extracts these structural elements from the data bank and uses them to calculate which amino acid sequences can adopt a structure capable of binding to and interrupting specific protein-protein interactions. It takes a single day to build the model, and mere seconds to evaluate a thousand sequences or design a new peptide.

“dTERMen allows us to find sequences that are likely to have the binding properties we’re looking for, in a robust, efficient, and general manner with a high rate of success,” Jenson says. “Past approaches have taken years. But using dTERMen, we went from structures to validated designs in a matter of weeks.”

Of the 17 peptides they built using the designed sequences, 15 bound with native-like affinity, disrupting Bcl-2 protein-protein interactions that are notoriously difficult to target. In some cases, their designs were surprisingly selective and bound to a single Bcl-2 family member over the others. The designed sequences deviated from known sequences found in nature, which greatly increases the number of possible peptides.

“This method permits a certain level of flexibility,” Frappier says. “dTERMen is more robust to structural change, which allows us to explore new types of structures and diversify our portfolio of potential binding candidates.”

Probing the sequence universe

Given the therapeutic benefits of inhibiting Bcl-2 function and slowing tumor growth, the Keating lab has already begun extending their design calculations to other members of the Bcl-2 family. They intend to eventually develop new proteins that adopt structures that have never been seen before.

“We have now seen enough examples of various local protein structures that computational models of sequence-structure relationships can be inferred directly from structural data, rather than having to be rediscovered each time from atomistic interaction principles,” says Grigoryan, dTERMen’s creator. “It’s immensely exciting that such structure-based inference works and is accurate enough to enable robust protein design. It provides a fundamentally different tool to help tackle the key problems of structural biology — from protein design to structure prediction.”

Frappier hopes one day to be able to screen the entire human proteome computationally, using methods like dTERMen to generate candidate binding peptides. Jenson suggests that using dTERMen in combination with more traditional approaches to sequence redesign could amplify an already powerful tool, empowering researchers to produce these targeted peptides. Ideally, he says, one day developing peptides that bind and inhibit your favorite protein could be as easy as running a computer program, or as routine as designing a DNA primer.

According to Keating, although that time is still in the future, “our study is the first step towards demonstrating this capacity on a problem of modest scope.”

This research was funded the National Institute of General Medical Sciences, National Science Foundation, Koch Institute for Integrative Cancer Research, Natural Sciences and Engineering Research Council of Canada, and Fonds de Recherche du Québec.

Biologist Adam Martin studies the mechanics of tissue folding

The dynamic process is critical to embryonic development and other cellular phenomena.

Anne Trafton | MIT News Office
February 1, 2019

Embryonic development is tightly regulated by genes that control how body parts form. One of the key responsibilities of these genes is to make sure that tissues fold into the correct shapes, forming structures that will become the spine, brain, and other body parts.

During the 1970s and ’80s, the field of embryonic development focused mainly on identifying the genes that control this process. More recently, many biologists have shifted toward investigating the physics behind the tissue movements that occur during development, and how those movements affect the shape of tissues, says Adam Martin, an MIT associate professor of biology.

Martin, who recently earned tenure, has made key discoveries in how tissue folding is controlled by the movement of cells’ internal scaffolding, known as the cytoskeleton. Such discoveries can not only shed light on how tissues form, including how birth defects such as spina bifida occur, but may also help guide scientists who are working on engineering artificial human tissues.

“We’d like to understand the molecular mechanisms that tune how forces are generated by cells in a tissue, such that the tissue then gets into a proper shape,” Martin says. “It’s important that we understand fundamental mechanisms that are in play when tissues are getting sculpted in development, so that we can then harness that knowledge to engineer tissues outside of the body.”

Cellular forces

Martin grew up in Rochester, New York, where both of his parents were teachers. As a biology major at nearby Cornell University, he became interested in genetics and development. He went on to graduate school at the University of California at Berkeley, thinking he would study the genes that control embryonic development.

However, while in his PhD program, Martin became interested in a different phenomenon — the role of the cytoskeleton in a process called endocytosis. Cells use endocytosis to absorb many different kinds of molecules, such as hormones or growth factors.

“I was interested in what generates the force to promote this internalization,” Martin says.

He discovered that the force is generated by the assembly of arrays of actin filaments. These filaments tug on a section of the cell membrane, pulling it inward so that the membrane encloses the molecule being absorbed. He also found that myosin, a protein that can act as a motor and controls muscle contractions, helps to control the assembly of actin filaments.

After finishing his PhD, Martin hoped to find a way to combine his study of cytoskeleton mechanics with his interest in developmental biology. As a postdoc at Princeton University, he started to study the phenomenon of tissue folding in fruit fly embryonic development, which is now one of the main research areas of his lab at MIT. Tissue folding is a ubiquitous shape change in tissues to convert a planar sheet of cells into a three-dimensional structure, such as a tube.

In developing fruit fly embryos, tissue folding invaginates cells that will form internal structures in the fly. This folding process is similar to tissue folding events in vertebrates, such as neural tube formation. The neural tube, which is the precursor to the vertebrate spinal cord and brain, begins as a sheet of cells that must fold over and “zip” itself up along a seam to form a tube. Problems with this process can lead to spina bifida, a birth defect that results from an incomplete closing of the backbone.

When Martin began working in this area, scientists had already discovered many of the transcription factors (proteins that turn on networks of specific genes) that control the folding of the neural tube. However, little was known about the mechanics of this folding.

“We didn’t know what types of forces those transcription factors generate, or what the mechanisms were that generated the force,” he says.

He discovered that the accumulation of myosin helps cells lined up in a row to become bottle-shaped, causing the top layer of the tissue to pucker inward and create a fold in the tissue. More recently, he found that myosin is turned on and off in these cells in a dynamic way, by a protein called RhoA.

“What we found is there’s essentially an oscillator running in the cells, and you get a cycle of this signaling protein, RhoA, that’s being switched on and off in a cyclical manner,” Martin says. “When you don’t have the dynamics, the tissue still tries to contract, but it falls apart.”

He also found that the dynamics of this myosin activity can be disrupted by depleting genes that have been linked to spina bifida.

Breaking free

Another important cellular process that relies on tissue folding is the epithelial-mesenchymal transition (EMT). This occurs during embryonic development when cells gain the ability to break free and move to a new location. It is also believed to occur when cancer cells metastasize from tumors to seed new tumors in other parts of the body.

During embryonic development, cells lined up in a row need to orient themselves so that when they divide, both daughter cells remain in the row. Martin has shown that when the mechanism that enables the cells to align correctly is disrupted, one of the daughter cells will be squeezed out of the tissue.

“This has been proposed as one way you can get an epithelial-to-mesenchymal transition, where you have cells dissociate from native tissue,” Martin says.  He now plans to further study what happens to the cells that get squeezed out during the EMT.

In addition to these projects, he is also collaborating with Jörn Dunkel, an MIT associate professor of mathematics, to map the network connections between the myosin proteins that control tissue folding during development. “That project really highlights the benefits of getting people from diverse backgrounds to analyze a problem,” Martin says.

Revising the textbook on introns

Whitehead Institute researchers uncover a group of introns in yeast that possess surprising stability and function.

Nicole Davis | Whitehead Institute
January 16, 2019

A research team from Whitehead Institute has uncovered a surprising and previously unrecognized role for introns, the parts of genes that lack the instructions for making proteins and are typically cut away and rapidly destroyed. Through studies of baker’s yeast, the researchers identified a highly unusual group of introns that linger and accumulate, in their fully intact form, long after they have been freed from their neighboring sequences, which are called exons. Importantly, these persistent introns play a role in regulating yeast growth, particularly under stressful conditions.

The researchers, whose work appears online in the journal Nature, suggest that some introns also might accumulate and carry out functions in other organisms.

“This is the first time anyone has found a biological role for full-length, excised introns,” says senior author David Bartel, a member of the Whitehead Institute. “Our findings challenge the view of these introns as simply byproducts of gene expression, destined for rapid degradation.”

Imagine the DNA that makes up your genes as the raw footage of a movie. The exons are the scenes used in the final cut, whereas the introns are the outtakes — shots that are removed, or spliced out, and therefore not represented in the finished product.

Despite their second-class status, introns are known to play a variety of important roles. Yet these activities are primarily confined to the period prior to splicing — that is, before introns are separated from their nearby exons. After splicing, some introns can be whittled down and retained for other uses — part of a group of so-called “non-coding RNAs.” But by and large, introns have been thought to be relegated to the genome’s cutting room floor.

Bartel and his Whitehead Institute colleagues, including world-renowned yeast expert Gerald Fink, now add an astonishing new dimension to this view: Full-length introns — that is, those that have been cut out but remain otherwise intact — can persist and carry out useful biological functions. As reported in their Nature paper, the team discovered that these extraordinary introns are regulated by and function within the essential TORC1 growth signaling network, forming a previously unknown branch of this network that controls cell growth during periods of stress.

“Our initial reaction was: ‘This is really weird,’” recalls first author Jeffrey Morgan, a former graduate student in Bartel’s lab who is now a postdoc in Jared Rutter’s lab at the University of Utah. “We came across genes where the introns were much more abundant than the exons, which is the exact opposite of what you’d expect.”

The researchers identified a total of 34 of these unusually stable introns, representing 11 percent of all introns in the yeast, also known as Saccharomyces cerevisiae. Surprisingly, there are very few criteria that determine which introns will become stable introns. For example, the genetic sequences of the introns or the regions that surround them are of no significance. The only defining — and necessary — feature, the team found, is a structural one, and involves the precise shape the introns adopt as they are being excised from their neighboring exons. Excised introns typically form a lasso-shaped structure, known as a lariat. The length of the lasso’s handle appears to dictate whether an intron will be stabilized or not.

Remarkably, both yeast and introns have been studied for several decades. Yet until now, these unique introns went undetected. One reason, Bartel and his colleagues believe, is the conditions under which yeast are typically grown. Often, researchers study yeast that are growing very rapidly — so-called log-phase growth. That is because abnormalities are often easiest to detect when cells are multiplying quickly.

“Biologists have focused heavily on log-phase for very good reasons, but in the wild, yeast are very rarely in that condition, whether it’s because of limited nutrients or other stresses,” says Bartel, who is also professor of biology at MIT and a Howard Hughes Medical Institute investigator.

He and his colleagues decided to grow yeast under more stressful circumstances, and that is what ultimately led them to their discovery. Although their experiments were confined to yeast, the researchers believe it is possible other organisms may harbor this long-overlooked class of introns — and that similar approaches using less-often-studied conditions could help illuminate them.

“Right now, we can say it is happening in yeast, but we’d be surprised if this is the only organism in which it is happening,” Bartel says.

The research was supported by the National Institutes of Health and the Howard Hughes Medical Institute.

Biologists discover an unusual hallmark of aging in neurons

Snippets of RNA that accumulate in brain cells could interfere with normal function.

Anne Trafton | MIT News Office
November 27, 2018

As we age, neurons in our brains can become damaged by free radicals. MIT biologists have now discovered that this type of damage, known as oxidative stress, produces an unusual pileup of short snippets of RNA in some neurons.

This RNA buildup, which the researchers believe may be a marker of neurodegenerative diseases, can reduce protein production. The researchers observed this phenomenon in both mouse and human brains, especially in a part of the brain called the striatum — a site involved in diseases such as Parkinson’s and Huntington’s.

“The brain is very metabolically active, and over time, that causes oxidative damage, but it affects some neurons more than others,” says Christopher Burge, an MIT professor of biology. “This phenomenon appears to be a previously unrecognized consequence of oxidative stress, which impacts hundreds of genes and may influence translation and RNA regulation globally.”

Burge and Myriam Heiman, the Latham Family Career Development Associate Professor of Brain and Cognitive Sciences, are the senior authors of the paper, which appears in the Nov. 27 issue of Cell Reports. Peter Sudmant, a former MIT postdoc, is the lead author of the paper, and postdoc Hyeseung Lee and former postdoc Daniel Dominguez are also authors.

A mysterious finding

For this study, the researchers used a technique developed by Heiman that allows them to isolate and sequence messenger RNA from specific types of cells. Messenger RNA carries protein-building instructions to cell organelles called ribosomes, which read the mRNA and translate the instructions into proteins by stringing together amino acids in the correct sequence.

Heiman’s technique involves tagging ribosomes from a specific type of cells with green fluorescent protein, so that when a tissue sample is analyzed, researchers can use the fluorescent tag to isolate and sequence RNA from only those cells. This allows them to determine which proteins are being produced by different types of cells.

“This is particularly useful in the nervous system where you’ve got different types of neurons and glia closely intertwined together, if you want to isolate the mRNAs from one particular cell type,” Burge says.

In separate groups of mice, the researchers tagged ribosomes from either D1 or D2 spiny projection neurons, which make up 95 percent of the neurons found in the striatum. They labeled these cells in younger mice (6 weeks old) and 2-year-old mice, which are roughly equivalent to humans in their 70s or 80s.

The researchers had planned to look for gene expression differences between those two cell types, and to explore how they were affected by age. “These two types of neurons are implicated in several neurodegenerative diseases that are aging-related, so it is important to understand how normal aging changes their cellular and molecular properties,” says Heiman, who is a member of MIT’s Picower Institute for Learning and Memory and the Broad Institute of MIT and Harvard.

To the researchers’ surprise, a mysterious result emerged — in D1 neurons from aged mice (but not neurons from young mice or D2 neurons from aged mice), they found hundreds of genes that expressed only a short fragment of the original mRNA sequence. These snippets, known as 3’ untranslated regions (UTRs), were stuck to ribosomes, preventing the ribosomes from assembling normal proteins. “While these RNAs have been observed before, the magnitude and age-associated cell-type specificity was really unprecedented,” says Sudmant.

The 3’ UTR snippets appeared to originate from about 400 genes with a wide variety of functions. Meanwhile, many other genes were totally unaffected.

“There are some genes that are completely normal, even in aged D1 neurons. There’s a gene-specific aspect to this phenomenon that is quite interesting and mysterious,” Burge says.

The findings led the researchers to explore a possible role for oxidative stress in this 3’ UTR accumulation. Neurons burn a great deal of energy, which can produce free radicals as byproducts. Unlike many other cell types, neurons do not get replaced, so they are believed to be susceptible to accumulated damage from these radicals over time.

The MIT team found that the activation of oxidative stress response pathways was higher in D1 neurons compared to D2 neurons, suggesting that they are indeed undergoing more oxidative damage. The researchers propose a model for the production of isolated 3′ UTRs involving an enzyme called ABCE1, which normally separates ribosomes from mRNA after translation is finished. This enzyme contains iron-sulfur clusters that can be damaged by free radicals, making it less effective at removing ribosomes, which then get stuck on the mRNA. This leads to cleavage of the RNA by a mechanism that operates upstream of stalled ribosomes.

“Sending neural signals takes a lot of energy,” Burge says. “Over time, that causes oxidative damage, and in our model one of the proteins that eventually gets damaged is ABCE1, and that triggers the production of 3’ UTRs.”

RNA buildup

The researchers also found the same accumulation in most parts of the human brain, including the frontal cortex, which is very metabolically active. They did not see it in most other types of human tissue, with the exception of liver tissue, which is exposed to high levels of potentially toxic molecules.

In human brain tissue, the researchers found that the amount of 3’ UTRs gradually increased with age, which fits their proposed model of gradual damage by oxidative stress. The researchers’ findings and model suggest that the production of these 3′ UTRs involves the destruction of normal mRNAs, reducing the amount of protein produced from the affected genes.  This buildup of 3′ UTRs with ribosomes stuck to them can also block ribosomes from producing other proteins.

It remains to be seen exactly what effect this would have on those neurons, Burge says, but it is possible that this kind of cellular damage could combine with genetic and environmental factors to produce a general decline in cognitive ability or even neurodegenerative conditions such as Parkinson’s disease. In future studies, the researchers hope to further explore the causes and consequences of the accumulation of 3’ UTRs.

The research was funded by the National Institutes of Health and the JPB Foundation.

Decoding patterns and meaning in biological data

Senior Anna Sappington found her perfect balance of “innovative computer science and innovative biology” as a member of the team mapping every cell in the human body.

Raleigh McElvery
December 5, 2018

When Anna Sappington was six years old, her parents gave her a black and white composition notebook. Together, they began jotting down observations to identify the patterns in their wooded backyard near the Chesapeake Bay. How would the harsh winters or the early springs affect the blooming trees? How many bluebirds nested each season and how many eggs would they lay? When would the cicada population cycle peak? Her father, the environmental scientist, taught her to sift through data to uncover the trends. Her mother, the journalist, gave her the words to describe her findings.

But it wasn’t until Sappington competed in the Intel International Science and Engineering Fair her junior year of high school that she probed one tiny niche of the natural world more keenly than she ever had before: the physiology of the water flea. Specifically, she investigated the developmental changes that these minute creatures experienced after being exposed to the antimicrobial compound triclosan, present in many soaps and toothpastes. She was surprised to learn that it required only a low concentration of triclosan (0.5 ppm) to cause developmental defects.

She’d been familiar with the concept of DNA since middle school, but her fellow science fair finalists were delving beyond their observations and into the letters of the genetic code. This gave her a new impetus: to understand how triclosan worked at the level of the genome and epigenome to engender the physical deformities she observed under the microscope. She just needed the proper tools, so she made some calls.

Environmental geneticist and water flea aficionado John Colbourne took an interest, and invited her to his lab at University of Birmingham in the U.K. the following summer so she could learn basic lab techniques. Although her friends and classmates didn’t quite get why she needed to travel to an entirely different country to study an organism they’d never heard of, as she puts it, she had burning scientific questions that needed answers.

“That was the experience that really turned me on to genomics,” says Sappington, now a senior and 6-7 (Computer Science and Molecular Biology) major. “I was finally getting the tools to dig through large amounts of data, using code to find patterns and meaning. I wanted to keep asking ‘why?’ and ‘how?’ all the way down to the molecular level.”

The summer before her freshman year of college, Sappington asked these questions in humans for the time as an intern at the National Human Genome Research Institute (NHGRI). There, she helped create a computational pipeline to identify the genomic changes associated with heightened risk of cardiovascular disease.

She enrolled at MIT the following fall, because she wanted to be around people from every scientific subfield imaginable. When she arrived, the joint major in computer science and biology was still relatively new.

“While a few of the required classes did meld the two, many of them offered training in each separately,” she says. “That approach really appealed to me because I was hoping to develop both skill sets independently. I wanted to learn code and write algorithms that could be applied to any field, and I also loved understanding the biological mechanisms behind different diseases and viruses.”

Before she’d even officially declared her major, Sappington was already running experiments in Sangeeta Bhatia’s lab. There, at the Koch Institute, she studied the effects of HPV infection on gene expression in liver cells. Sappington’s main role was data analysis, striving to determine which genes were amplified in response to disease.Despite their obvious differences, Sappington found the two areas to be more similar than she had initially anticipated. In her Introduction to Algorithms class, she leveraged an arsenal of algorithms with certain outputs, conditions, and run times to decode her problem sets. In Organic Chemistry, she deployed a list of foundational reactions to solve synthesis questions on her exams. “In each case, you have to combine your understanding of these fundamental rules and come up with a creative solution to decipher an unknown,” she says.

One year later, Sappington moved to Aviv Regev’s lab at the Broad Institute. There, she learned computational techniques for decoding protein interaction networks. After a year, she began working on an international project called the Human Cell Atlas as a member of the Regev and the Sanes lab collaboration.

“The overarching mission is to create a reference map of all human cells,” Sappington explains. “We want to add a layer of functional understanding on top of what we know about the genome, to understand how different cell types differ and how they interact to impact disease. This kind of endeavor has never been undertaken on such a large scale before, so it’s incredibly exciting.”

Even within a single cell type — say, retinal cells — there are about six main cell categories, each of which splinter into as many as 40 subtypes with distinct molecular profiles and roles.

Beyond the biological challenges that go along with trying to distinguish all these cell types, there are numerous computational hurdles as well. Sappington enjoys these the most — grappling with how best to analyze the gene expression of a single cell separated from its tissue of origin.

“Since you’re only working with single cells rather than entire groups of cells from a tissue, the data that you get are much more sparse,” she says. “You have to sequence a lot of individual cells and build up lots of statistical power before you can be confident that a given cell is expressing specific genes. Coming up with models to determine what constitutes a cell type — and map cell types between time points or between species — are broad problems in computer science that we’re now applying to this very specific type of data.”

Although she’s been at the Broad since her sophomore year, Sappington has supplemented her MIT research experiences with summer studies elsewhere: another stint at the NHGRI and an Amgen Scholars fellowship in Japan. She’s especially excited because her first co-authored paper will soon be published. As she puts it, she’s finally found her ideal balance of “innovative computer science and innovative biology.”

But Sappington’s time at MIT has been defined by more than just lab work. She is the co-president of the Biology Undergraduate Student Association, which serves as a liaison between the Department of Biology and the wider community. She’s also a member of MedLinks, a volunteer at the Massachusetts General Hospital Department of Radiology, former managing director of TechX, and a performer for several campus dance troupes. In 2018, Sappington earned the prestigious Barry Goldwater Scholarship Award, alongside fellow 6-7 major Meena Chakraborty.

She was recently awarded the Marshall Scholarship, which will fund her master’s degrees in machine learning at University College London and oncology at the University of Cambridge beginning in the fall of 2019. After two years, she plans to start her MD-PhD. That way, she can become a practicing physician without having to give up her computer science research.

Her advice to prospective students: “When you get to MIT, just explore. Try different academic disciplines, different extracurriculars, and talk to as many people as you can. The campus is full of passionate individuals in every field imaginable, whether that’s computer science or political science.”

Posted 12.5.18
Computer model offers more control over protein design

New approach generates a wider variety of protein sequences optimized to bind to drug targets.

Anne Trafton | MIT News Office
October 15, 2018

Designing synthetic proteins that can act as drugs for cancer or other diseases can be a tedious process: It generally involves creating a library of millions of proteins, then screening the library to find proteins that bind the correct target.

MIT biologists have now come up with a more refined approach in which they use computer modeling to predict how different protein sequences will interact with the target. This strategy generates a larger number of candidates and also offers greater control over a variety of protein traits, says Amy Keating, a professor of biology, a member of the Koch Institute, and the leader of the research team.

“Our method gives you a much bigger playing field where you can select solutions that are very different from one another and are going to have different strengths and liabilities,” she says. “Our hope is that we can provide a broader range of possible solutions to increase the throughput of those initial hits into useful, functional molecules.”

In a paper appearing in the Proceedings of the National Academy of Sciences the week of Oct. 15, Keating and her colleagues used this approach to generate several peptides that can target different members of a protein family called Bcl-2, which help to drive cancer growth.

Recent PhD recipients Justin Jenson and Vincent Xue are the lead authors of the paper. Other authors are postdoc Tirtha Mandal, former lab technician Lindsey Stretz, and former postdoc Lothar Reich.

Modeling interactions

Protein drugs, also called biopharmaceuticals, are a rapidly growing class of drugs that hold promise for treating a wide range of diseases. The usual method for identifying such drugs is to screen millions of proteins, either randomly chosen or selected by creating variants of protein sequences already shown to be promising candidates. This involves engineering viruses or yeast to produce each of the proteins, then exposing them to the target to see which ones bind the best.

“That is the standard approach: Either completely randomly, or with some prior knowledge, design a library of proteins, and then go fishing in the library to pull out the most promising members,” Keating says.

While that method works well, it usually produces proteins that are optimized for only a single trait: how well it binds to the target. It does not allow for any control over other features that could be useful, such as traits that contribute to a protein’s ability to get into cells or its tendency to provoke an immune response.

“There’s no obvious way to do that kind of thing — specify a positively charged peptide, for example — using the brute force library screening,” Keating says.

Another desirable feature is the ability to identify proteins that bind tightly to their target but not to similar targets, which helps to ensure that drugs do not have unintended side effects. The standard approach does allow researchers to do this, but the experiments become more cumbersome, Keating says.

The new strategy involves first creating a computer model that can relate peptide sequences to their binding affinity for the target protein. To create this model, the researchers first chose about 10,000 peptides, each 23 amino acids in length and helical in structure, and tested their binding to three different members of the Bcl-2 family. They intentionally chose some sequences they already knew would bind well, plus others they knew would not, so the model could incorporate data about a range of binding abilities.

From this set of data, the model can produce a “landscape” of how each peptide sequence interacts with each target. The researchers can then use the model to predict how other sequences will interact with the targets, and generate peptides that meet the desired criteria.

Using this model, the researchers produced 36 peptides that were predicted to tightly bind one family member but not the other two. All of the candidates performed extremely well when the researchers tested them experimentally, so they tried a more difficult problem: identifying proteins that bind to two of the members but not the third. Many of these proteins were also successful.

“This approach represents a shift from posing a very specific problem and then designing an experiment to solve it, to investing some work up front to generate this landscape of how sequence is related to function, capturing the landscape in a model, and then being able to explore it at will for multiple properties,” Keating says.

Sagar Khare, an associate professor of chemistry and chemical biology at Rutgers University, says the new approach is impressive in its ability to discriminate between closely related protein targets.

“Selectivity of drugs is critical for minimizing off-target effects, and often selectivity is very difficult to encode because there are so many similar-looking molecular competitors that will also bind the drug apart from the intended target. This work shows how to encode this selectivity in the design itself,” says Khare, who was not involved in the research. “Applications in the development of therapeutic peptides will almost certainly ensue.”

Selective drugs

Members of the Bcl-2 protein family play an important role in regulating programmed cell death. Dysregulation of these proteins can inhibit cell death, helping tumors to grow unchecked, so many drug companies have been working on developing drugs that target this protein family. For such drugs to be effective, it may be important for them to target just one of the proteins, because disrupting all of them could cause harmful side effects in healthy cells.

“In many cases, cancer cells seem to be using just one or two members of the family to promote cell survival,” Keating says. “In general, it is acknowledged that having a panel of selective agents would be much better than a crude tool that just knocked them all out.”

The researchers have filed for patents on the peptides they identified in this study, and they hope that they will be further tested as possible drugs. Keating’s lab is now working on applying this new modeling approach to other protein targets. This kind of modeling could be useful for not only developing potential drugs, but also generating proteins for use in agricultural or energy applications, she says.

The research was funded by the National Institute of General Medical Sciences, National Science Foundation Graduate Fellowships, and the National Institutes of Health.

Jarrett Smith receives Hanna Gray Fellowship from HHMI
Greta Friar | Whitehead Institute
September 12, 2018

Cambridge, Mass — Jarrett Smith, postdoctoral researcher in David Bartel’s lab at the Whitehead Institute, has been announced as a recipient of the Howard Hughes Medical Institute (HHMI)’s 2018 Hanna Gray fellowship. The fellowship supports outstanding early career scientists from groups underrepresented in the life sciences. Each of this year’s fifteen awardees will be given up to $1.4 million dollars in funding over the course of their postdoctoral program and beginning of a tenure-track faculty position.

“This program will help us retain the most diverse talent in science,” said HHMI President Erin O’Shea. “We feel it’s critically important in academia to have exceptional people from all walks of life, all cultures, and all backgrounds – people who can inspire the next generation of scientists.”

For Smith, who began his postdoctoral training in the Bartel lab in January, finding out he got the fellowship was a defining moment.

“I’m grateful for the support that the fellowship will provide during the formative years of my career,” Smith says. “This kind of opportunity gives you the confidence to set ambitious research goals and find out what you can accomplish.”

In the Bartel lab, Smith studies how cells respond to stress. When a cell is exposed to environmental stressors such as heat, UV radiation, or viral infection, proteins and RNAs in the cell may clump together into dense aggregates called stress granules. Several diseases are associated with altered stress granule formation, but the exact function of stress granules and their potential role in disease are unknown. Smith is investigating changes in the cell linked to their formation. His findings could shed light on a potential role for stress granules in cancer, viral infection, and neurodegenerative disease.

Growing up, Smith was always interested in science but no one in his family had ever received a PhD, making biology research feel like an unlikely career path for him. Nevertheless, he followed his passion, which led him to a PhD program at the Johns Hopkins University School of Medicine. Despite his strong academic performance, Smith began graduate school with doubts about his ability to become a scientist. His mentors were incredible teachers but their self-assuredness could be intimidating.

“They were absolutely my role models, but I didn’t think of them as having gone through what I was going through. In the first few years, I felt like I had a lot of catching up to do,” Smith said.

Smith says he was frequently inspired and guided by his graduate school mentor, Geraldine Seydoux. Under her tutorship he became more confident in his abilities.

“I try to pick mentors who are the kind of scientist I aspire to be,” Smith said.

With that tenet in mind, he set his sights on David Bartel’s lab for his postdoctoral research. He had heard that Bartel was a great mentor and knew the Bartel lab had expertise in all of the research techniques he wanted to learn. Since arriving at Whitehead Institute, Smith says he has experienced support not only from Bartel, but from the entire lab as well.

“Jarrett’s graduate experience with P granules in nematodes brings much appreciated expertise to our lab, and we are all excited about what he will discover here on stress-granule function,” Bartel says. “Receiving this fellowship is a well-deserved honor, and I am very happy for him.”

Smith noted that he is deeply grateful for the community he’s found at Whitehead Institute. However, he also noted that throughout his scientific career he has typically been the only black person in the room. One of the joys of applying for the fellowship was meeting the rest of the candidates, a diverse and impressive group of scientists, he says. He looks forward to seeing the other fellows again at meetings hosted by the HHMI.

“I’ve never really had a scientific role model that shared those experiences or that I could identify with in that way,” Smith says, but he hopes that future aspiring scientists won’t have to go through the same experience. His brother-in-law recently began an undergraduate major in biology. Smith enjoys being there to answer his questions about school work or life as a researcher.

“I’d never ask him if he thinks of me as a role model,” Smith says, laughing. “But I’m glad that I have the chance to help people who—like I did—might question whether they could be successful in the sciences.” With the support of the fellowship and his lab, and an exciting research question he is eager to tackle, Smith has never been more certain that he belongs right where he is.