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Bringing RNA into genomics

ENCODE consortium identifies RNA sequences that are involved in regulating gene expression.

Anne Trafton | MIT News Office
July 29, 2020

The human genome contains about 20,000 protein-coding genes, but the coding parts of our genes account for only about 2 percent of the entire genome. For the past two decades, scientists have been trying to find out what the other 98 percent is doing.

A research consortium known as ENCODE (Encyclopedia of DNA Elements) has made significant progress toward that goal, identifying many genome locations that bind to regulatory proteins, helping to control which genes get turned on or off. In a new study that is also part of ENCODE, researchers have now identified many additional sites that code for RNA molecules that are likely to influence gene expression.

These RNA sequences do not get translated into proteins, but act in a variety of ways to control how much protein is made from protein-coding genes. The research team, which includes scientists from MIT and several other institutions, made use of RNA-binding proteins to help them locate and assign possible functions to tens of thousands of sequences of the genome.

“This is the first large-scale functional genomic analysis of RNA-binding proteins with multiple different techniques,” says Christopher Burge, an MIT professor of biology. “With the technologies for studying RNA-binding proteins now approaching the level of those that have been available for studying DNA-binding proteins, we hope to bring RNA function more fully into the genomic world.”

Burge is one of the senior authors of the study, along with Xiang-Dong Fu and Gene Yeo of the University of California at San Diego, Eric Lecuyer of the University of Montreal, and Brenton Graveley of UConn Health.

The lead authors of the study, which appears today in Nature, are Peter Freese, a recent MIT PhD recipient in Computational and Systems Biology; Eric Van Nostrand, Gabriel Pratt, and Rui Xiao of UCSD; Xiaofeng Wang of the University of Montreal; and Xintao Wei of UConn Health.

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Much of the ENCODE project has thus far relied on detecting regulatory sequences of DNA using a technique called ChIP-seq. This technique allows researchers to identify DNA sites that are bound to DNA-binding proteins such as transcription factors, helping to determine the functions of those DNA sequences.

However, Burge points out, this technique won’t detect genomic elements that must be copied into RNA before getting involved in gene regulation. Instead, the RNA team relied on a technique known as eCLIP, which uses ultraviolet light to cross-link RNA molecules with RNA-binding proteins (RBPs) inside cells. Researchers then isolate specific RBPs using antibodies and sequence the RNAs they were bound to.

RBPs have many different functions — some are splicing factors, which help to cut out sections of protein-coding messenger RNA, while others terminate transcription, enhance protein translation, break down RNA after translation, or guide RNA to a specific location in the cell. Determining the RNA sequences that are bound to RBPs can help to reveal information about the function of those RNA molecules.

“RBP binding sites are candidate functional elements in the transcriptome,” Burge says. “However, not all sites of binding have a function, so then you need to complement that with other types of assays to assess function.”

The researchers performed eCLIP on about 150 RBPs and integrated those results with data from another set of experiments in which they knocked down the expression of about 260 RBPs, one at a time, in human cells. They then measured the effects of this knockdown on the RNA molecules that interact with the protein.

Using a technique developed by Burge’s lab, the researchers were also able to narrow down more precisely where the RBPs bind to RNA. This technique, known as RNA Bind-N-Seq, reveals very short sequences, sometimes containing structural motifs such as bulges or hairpins, that RBPs bind to.

Overall, the researchers were able to study about 350 of the 1,500 known human RBPs, using one or more of these techniques per protein. RNA splicing factors often have different activity depending on where they bind in a transcript, for example activating splicing when they bind at one end of an intron and repressing it when they bind the other end. Combining the data from these techniques allowed the researchers to produce an “atlas” of maps describing how each RBP’s activity depends on its binding location.

“Why they activate in one location and repress when they bind to another location is a longstanding puzzle,” Burge says. “But having this set of maps may help researchers to figure out what protein features are associated with each pattern of activity.”

Additionally, Lecuyer’s group at the University of Montreal used green fluorescent protein to tag more than 300 RBPs and pinpoint their locations within cells, such as the nucleus, the cytoplasm, or the mitochondria. This location information can also help scientists to learn more about the functions of each RBP and the RNA it binds to.

“The strength of this manuscript is in the generation of a comprehensive and multilayered dataset that can be used by the biomedical community to develop therapies targeted to specific sites on the genome using genome-editing strategies, or on the transcriptome using antisense oligonucleotides or agents that mediate RNA interference,” says Gil Ast, a professor of human molecular genetics and biochemistry at Tel Aviv University, who was not involved in the research.

Linking RNA and disease

Many research labs around the world are now using these data in an effort to uncover links between some of the RNA sequences identified and human diseases. For many diseases, researchers have identified genetic variants called single nucleotide polymorphisms (SNPs) that are more common in people with a particular disease.

“If those occur in a protein-coding region, you can predict the effects on protein structure and function, which is done all the time. But if they occur in a noncoding region, it’s harder to figure out what they may be doing,” Burge says. “If they hit a noncoding region that we identified as binding to an RBP, and disrupt the RBP’s motif, NetBet live casinothen we could predict that the SNP may alter the splicing or stability of the gene.”

Burge and his colleagues now plan to use their RNA-based techniques to generate data on additional RNA-binding proteins.

“This work provides a resource that the human genetics community can use to help identify genetic variants that function at the RNA level,” he says.

The research was funded by the National Human Genome Research Institute ENCODE Project, as well as a grant from the Fonds de Recherche de Québec-Santé.

A recipe for cell fitness

Researchers determine how much of an enzyme is ‘just enough’ to keep a cell healthy and growing.

Raleigh McElvery
July 28, 2020

What ratio of ingredients makes a healthy cell? Researchers know which components are required for proper function, but they’re still working to understand what happens when there’s too much of one protein or not enough of another. As a graduate student in Gene-Wei Li’s lab, Darren Parker PhD ’20 spent years tweaking the recipe for a bacterial cell, adding more or less of one enzyme, aminoacyl-tRNA synthetase (aaRS). He wanted to know: How much aaRS is “just right” for bacterial cells? His findings were published in Cell Systems on July 28.

tRNAs, or transfer RNAs, carry amino acids to the ribosome to help produce proteins. But first, aaRSs must “charge” the tRNAs by attaching an amino acid to them. In doing so, aaRSs not only help the cell make proteins and grow; they also ensure the levels of “uncharged” tRNAs lacking amino acids don’t rise too high, as too many of them can trigger stress responses that slow cell growth. Parker and his collaborators predicted that tinkering with aaRS levels would uncover one of two possible scenarios. Perhaps cells tune their aaRS production to minimize the amount of uncharged tRNAs present. Alternatively, aaRS production could be dictated by the rate of protein synthesis necessary for cell growth — even if that means accumulating uncharged tRNAs.

The researchers determined the latter was true: cells make “just enough” aaRSs to optimize protein production and cell growth. This delicate balance was easily upset when too few aaRSs were produced, cueing the stress responses to kick in and slow growth. Although excess aaRSs reduced the amount of uncharged tRNA, it also hindered cell growth. The researchers determined that the cellular circuits in charge of controlling and sensing tRNA charging are collectively tuned to optimize bacterial growth.

“These results demonstrate that cells have delicately balanced the costs and benefits of producing their proteins,” Parker says. “Understanding the driving forces behind protein production is important for better understanding disease processes, and engineering cells to perform new functions.”

Gene-controlling mechanisms play key role in cancer progression

Study finds “epigenomic” alterations evolve as lung tumors become more aggressive and metastasize.

Anne Trafton | MIT News Office
July 22, 2020

As cancer cells evolve, many of their genes become overactive while others are turned down. These genetic changes can help tumors grow out of control and become more aggressive, adapt to changing conditions, and eventually lead the tumor to metastasize and spread elsewhere in the body.

MIT and Harvard University researchers have now mapped out an additional layer of control that guides this evolution — an array of structural changes to “chromatin,” the mix of proteins, DNA, and RNA that makes up cells’ chromosomes. In a study of mouse lung tumors, the researchers identified 11 chromatin states, also called epigenomic states, that cancer cells can pass through as they become more aggressive.

“This work provides one of the first examples of using single-cell epigenomic data to comprehensively characterize genes that regulate tumor evolution in cancer,” says Lindsay LaFave, an MIT postdoc and the lead author of the study.

In addition, the researchers showed that a key molecule they found in the more aggressive tumor cell states is also linked to more advanced forms of lung cancer in humans, and could be used as a biomarker to predict patient outcomes.

Tyler Jacks, director of MIT’s Koch Institute for Integrative Cancer Research, and Jason Buenrostro, an assistant professor of stem cell and regenerative biology at Harvard University, are the senior authors of the study, which appears today in Cancer Cell.

Epigenomic control

While a cell’s genome contains all of its genetic material, the epigenome plays a critical role in determining which of these genes will be expressed. Every cell’s genome has epigenomic modifications — proteins and chemical compounds that attach to DNA but do not alter its sequence. These modifications, which vary by cell type, influence the accessibility of genes and help to make a lung cell different from a neuron, for example.

Epigenomic changes are also believed to influence cancer progression. In this study, the MIT/Harvard team set out to analyze the epigenomic changes that occur as lung tumors develop in mice. They studied a mouse model of lung adenocarcinoma, which results from two specific genetic mutations and closely recapitulates the development of human lung tumors.

Using a new technology for single-cell epigenome analysis that Buenrostro had previously developed, the researchers analyzed the epigenomic changes that occur as tumor cells evolve from early stages to later, more aggressive stages. They also examined tumor cells that had metastasized beyond the lungs.

This analysis revealed 11 different chromatin states, based on the locations of epigenomic alterations and density of the chromatin. Within a single tumor, there could be cells from all 11 of the states, suggesting that cancer cells can follow different evolutionary pathways.

For each state, the researchers also identified corresponding changes in where gene regulators called transcription factors bind to chromosomes. When transcription factors bind to the promoter region of a gene, they initiate the copying of that gene into messenger RNA, essentially controlling which genes are active. Chromatin modifications can make gene promoters more or less accessible to transcription factors.

“If the chromatin is open, a transcription factor can bind and activate a specific gene program,” LaFave says. “We were trying to understand those transcription factor networks and then what their downstream targets were.”

As the structure of tumor cells’ chromatin changed, transcription factors tended to target genes that would help the cells to lose their original identity as lung cells and become less differentiated. Eventually many of the cells also gained the ability to leave their original locations and seed new tumors.

Much of this process was controlled by a transcription factor called RUNX2. In more aggressive cancer cells, RUNX2 promotes the transcription of genes for proteins that are secreted by cells. These proteins help remodel the environment surrounding the tumor to make it easier for cancer cells to escape.

The researchers also found that these aggressive, premetastatic tumor cells were very similar to tumor cells that had already metastasized.

“That suggests that when these cells were in the primary tumor, they actually changed their chromatin state to look like a metastatic cell before they migrated out into the environment,” LaFave says. “We believe they undergo an epigenetic change in the primary tumor that allows them to become migratory and then seed in a distal location like the lymph nodes or the liver.”

A new biomarker

The researchers also compared the chromatin states they identified in mouse tumor cells to chromatin states seen in human lung tumors. They found that RUNX2 was also elevated in more aggressive human tumors, suggesting that it could serve as a biomarker for predicting patient outcomes.

“The RUNX positive state was very highly predictive of poor survival in human lung cancer patients,” LaFave says. “We’ve also shown the inverse, where we have signatures of early states, and they predict better prognosis for patients. This suggests that you can use these single-cell gene regulatory networks as predictive modules in patients.”

RUNX could also be a potential drug target, although it traditionally has been difficult to design drugs that target transcription factors because they usually lack netbet online sports bettingwell-defined structures that could act as drug docking sites. The researchers are also seeking other potential targets among the epigenomic changes that they identified in more aggressive tumor cell states. These targets could include proteins known as chromatin regulators, which are responsible for controlling the chemical modifications of chromatin.

“Chromatin regulators are more easily targeted because they tend to be enzymes,” LaFave says. “We’re using this framework to try to understand what are the important targets that are driving these state transitions, and then which ones are therapeutically targetable.”

The research was funded by a Damon Runyon Cancer Foundation postdoctoral fellowship, the Paul G. Allen Frontiers Group, the National Institutes of Health, and the Koch Institute Support (core) Grant from the National Cancer Institute.

3 Questions: Ibrahim Cissé on using physics to decipher biology

A biophysicist employs super-resolution microscopy to peer inside living cells and witness never-before-seen phenomena.

Raleigh McElvery | Department of Biology
July 23, 2020

How do cells use physics to carry out biological processes? Biophysicist Ibrahim Cissé explores this fundamental question in his interdisciplinary laboratory, leveraging super-resolution microscopy to probe the properties of living matter. As a postdoc in 2013, he discovered that RNA polymerase II, a critical protein in gene expression, forms fleeting (“transient”) clusters with similar molecules in order to transcribe DNA into RNA. He joined the Department of Physics in 2014, and was recently granted tenure and a joint appointment in biology. He sat down to discuss how his physics training led him to rewrite the textbook on biology.

Q: How does your work revise conventional models describing how RNA polymerases carry out their cellular duties?

A: My interest in biology has always been curiosity-driven. As a physicist reading biology textbooks, I thought that transcription — the process by which DNA is made into RNA — was fully understood. It’s so basic, and the textbooks write about it with such confidence. Come to find out, most of what we know about the cell nucleus, where gene expression starts, comes from people studying these processes outside the cell, inside a test tube. I started to wonder: Do we actually know how they work in a living cell?

The textbook models say that when a specific gene is being activated, RNA polymerase and dozens of other molecules are recruited to the DNA to begin transcription. If you don’t look closely enough, the polymerases appear to be uniformly distributed and acting randomly throughout the nucleus. However, my single-molecule and “super-resolution” microscopy methods allowed me to see something different when I looked inside live cells: polymerase clusters, which are very dynamic. In the mid-’90s, people had observed similar clusters in so-called “fixed” cells that were chemically frozen. But these findings were dismissed as possible artifacts of the fixation procedure. However, when we saw these same protein clusters in living cells that were not treated with harsh chemicals, it suggested that the textbook explanation may be incomplete.

Q: How has your background in physics given you a unique perspective on the mechanics of living cells?

A: When I arrived at the University of Illinois at Urbana-Champaign to begin my PhD in physics, I hadn’t enrolled in a biology class since high school. I was really taken with the interdisciplinary work of one physics professor, Taekjip Ha, who became my PhD mentor. He had developed single-molecule fluorescence resonance energy transfer techniques, to study with unprecedented sensitivity when two biomolecules are close to each other and monitor the distance between them in real time.

Taekjip graciously accepted me into his lab despite my limited biology background, and I never looked back. His work mirrored my interest in condensed matter physics, but the material we were looking at wasn’t from the inanimate world, it was living matter.

Between 2006 and 2008, as I was working on my PhD, super-resolution microscopy really took off from the single-molecule microscopes I used in grad school. It was a natural progression, in my mind, to learn cell biology during my postdoc fellowship at École Normale Supérieure in Paris, and to try to visualize weak and transient interactions directly in living cells using single-molecule and super-resolution imaging. You could now pinpoint molecules with nanometer accuracy; you could “turn on” and “off” molecules to observe them individually and ensure there was no overlap between those that were side-by-side.

Thanks to these new techniques, we saw clusters of RNA polymerases in living cells for the first time during my postdoc, and I pushed the technique further to reveal the cluster dynamics. But the fact that you had to turn individual molecules on and off made it really hard to see these clusters assembling or disassembling. I didn’t want to trade temporal resolution for spatial resolution. So I came up with an approach called Time-Correlated Photoactivated Localization Microscopy (tcPALM). It allowed us to measure the lifetimes of these ephemeral polymerase clusters, and we found that they last just a few seconds.

Once I arrived at MIT, we wanted to test whether the clusters could be fleeting but still biologically relevant. We pushed a dual-color super-resolution technique where we correlated the clusters with gene activity. With RNA live-imaging experts at Howard Hughes Medical Institute’s Janelia Research Campus, Brian English and Tim Lionnet, and my postdoc, Wonki Cho, we found that roughly 80 to 100 polymerases form a cluster on a gene where transcription is about to start. Although the cluster is only there for a few seconds, that’s enough time to load a handful of polymerases and generate “bursts” of RNA transcription. In fact, there was a linear correlation between the clusters’ transient dynamics and the number of messenger RNAs made in each burst.

Q: What is it like to be a physicist working with biologists?

A: Even though I joined MIT as a physics hire, I was lucky enough to get lab space in Building 68 alongside amazing biologists. They were the perfect people to talk to about my crazy ideas. And it turned out that renowned researchers like Rick Young and Phil Sharp actually had similar theories. They had genomic evidence for clusters of gene regulators, which they call “super enhancers,” that we all thought could relate to what my lab was seeing. That’s led to hours of exciting discussions between our labs, and has evolved into one of my most rewarding collaborations — and revealed that clusters associate as tiny transcriptional condensates with properties of liquid droplets.

Now, students and postdocs in my lab are wondering about the clusters’ functions and mechanisms of action, and whether protein clustering extends beyond transcription. For instance, clustering could explain some aspects of neurodegeneration. One perplexing idea that came out of this work is that perhaps it gets harder for our cells to clear protein condensates as we age, leading to Parkinson’s, Alzheimer’s, and other diseases. It’s becoming clearer that physics may be just as important as biology for understanding how cells work. The physics of how condensates and droplets form in the inanimate world is increasingly helpful in determining how living cells can evolve to regulate the same process for specific biological functions like transcription. Nature uses physics in much more elaborate ways than we initially anticipated.

Proteins and labs come together to prevent Rett syndrome
Greta Friar | Whitehead Institute
July 22, 2020

New discoveries about the disruption of condensates in the neurodevelopmental disorder Rett syndrome provide insights into how cells compartmentalize chromosomes as well as new potential paths for therapies.

Scientists have, for many years, conceptualized the cell as a relatively free-flowing space, where–apart from the organization provided by specific cellular structures–molecules float freely, somehow ultimately ending up in the right place at the right time. In recent years, however, scientists netbet online sports bettinghave discovered that cells have much more spatial organization than previously thought thanks to a mechanism called phase separation, which occurs in cells when certain molecules form large droplet-like structures that separate what’s inside of the droplet from the rest of the cell. The droplets, called condensates, help sequester and concentrate molecules in specific locations, and appear to increase the efficiency of certain cellular functions.

Whitehead Institute Member Richard Young, also a professor of biology at Massachusetts Institute of Technology (MIT), has been exploring the previously unknown role that condensates play in gathering the molecules needed for gene transcription–the process by which DNA is read into RNA. In order to better understand when and how cells use phase separation, Charles Li, a graduate student in Young’s lab, set out to identify more proteins that can form condensates. That search led him to MeCP2, a protein associated with the severe neurodevelopmental disorder Rett syndrome, studied by Young’s colleague at Whitehead Institute, Founding Member Rudolf Jaenisch, who is also a professor of biology at MIT. No cure for Rett syndrome currently exists, and Jaenisch’s lab has been investigating the biology of the disorder in the hopes of discovering a medical therapy that can rescue neurons affected by Rett syndrome.

With the discovery of MeCP2’s condensate forming ability, Young and Jaenisch saw the opportunity for a promising collaboration between their labs. Led by co-first authors Li and Eliot Coffey, another graduate student in Young’s lab, the two labs investigated MeCP2 and whether the disruption of its condensate-forming ability contributes to Rett syndrome. During these investigations, the researchers also uncovered how cells may use condensates to help organize the active and inactive parts of chromosomes. Their findings, published in the journal Nature on June 22, report on these insights and suggest new paths for developing therapies for Rett syndrome.

PHASE SEPARATION AND RETT SYNDROME

Proteins that form condensates often contain intrinsically disordered regions (IDRs), long spaghetti-like strands that transiently stick together to form a dynamic mesh. Research has historically focused on the structured regions of proteins, which bind very specifically to other molecules, while IDRs have largely been overlooked. In this case, MeCP2’s large IDRs were exactly what drew Li to it.

“What was striking to me was that this protein has been studied for decades, and so much function has been ascribed to the protein as a whole, yet it only has one structured domain with a recognized function, the DNA binding domain. Beyond that, the entire protein is disordered, and how its parts function was largely unknown,” Li says.

The researchers found that MeCP2 used its IDRs to glom together and form condensates. Then they tested many of the mutations in the MECP2 gene that are associated with Rett syndrome and found that they all disrupt MeCP2’s ability to form condensates. Their findings suggest that therapies targeting condensates associated with the protein, rather than the protein itself, may be promising in the hunt for a Rett syndrome treatment.

“MeCP2 and Rett syndrome have been studied intensely for many years in many labs and yet not a single therapy has been developed. When the project began, I was immediately fascinated by the idea that we might find a new disease mechanism that could help us finally understand how Rett syndrome arises and how it could be treated,” Coffey says.

“Rick [Young] has shown that condensates play key roles in maintaining normal cellular function, and our latest collaboration illuminates how their disruption may drive diseases such as Rett syndrome,” Jaenisch says. “I hope the insights we have gained will prove useful both in our continued search for a treatment for Rett syndrome and more broadly in research on condensates and disease.”

COMPARTMENTALIZING CHROMOSOMES

The researchers’ investigation into MeCP2’s condensate forming behavior also shed light on how chromosomes are organized into regions of active and inactive genes. When MeCP2 is functioning normally, it helps to maintain heterochromatin, the roughly half of our chromosomes where genes are “turned off,” unable to be read into RNA or further processed to make proteins. MeCP2 binds to sequences of DNA marked with a certain type of regulatory tag that is typically found in heterochromatin. This helps crowd MeCP2 to the threshold concentration needed to form heterochromatin condensates. These condensates, in turn, help to sequester the molecules needed to maintain it apart from euchromatin, the half of our chromosomes filled with active genes. Different proteins form condensates near euchromatin, concentrating the molecular machinery needed to transcribe active genes there.

Since condensates form when proteins with large spaghetti-like IDRs stick together, one might expect that any protein containing IDRs could interact with any other IDR-containing protein to form droplets, and that is what the researchers have often seen. However, what they observed with MeCP2, which is associated with heterochromatin, is that key condensate-forming proteins associated with euchromatin refused to mix.

It’s important for the health of the cell that the genes in heterochromatin not be inadvertently turned on. The researchers reason that discrete euchromatin and heterochromatin condensates may play a key role in ensuring that transcriptional machinery localizes to euchromatin only, while repressive machinery–like MeCP2–localizes to heterochromatin. The researchers are excited to turn their attention to how proteins are able to join condensates selectively, and when and where else in the cell they do so.

“There’s a chemical grammar waiting to be deciphered that explains this difference in the ability of some proteins to move into one condensate versus another,” Young says. “Discovering that grammar can help us understand how cells maintain the crucial balance between the active and silent halves of our genome, and it could help us understand how to treat disorders such as Rett syndrome.”

***

Written by Greta Friar

Richard Young’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 professor of biology at the Massachusetts Institute of Technology.

Rudolf Jaenisch’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 professor of biology at Massachusetts Institute of Technology.

Li, C.H., Coffey, E., et al. (2020). MeCP2 links heterochromatin condensates and neurodevelopmental disease. Nature. DOI: 10.1038/s41586-020-2574-4

Ankur Jain and Pulin Li appointed to prestigious chairs
Whitehead Institute
July 13, 2020

Massachusetts Institute of Technology (MIT) provost Martin A. Schmidt has announced that two Whitehead Institute Members — Ankur Jain and Pulin Li — have been appointed to MIT career development professorships.

Jain has been named to the Thomas D. and Virginia W. Cabot Career Development Professorship. Li has been named the Eugene Bell Career Development Professor of Tissue Engineering. Both also continue to be assistant professors in the MIT department of Biology.

The Cabot and Bell chairs both recognize and support excellence in teaching and research by gifted faculty members who show exceptional promise in their professional careers. In addition to affirming Jain’s and Li’s status as emerging leaders in biomedical research, the appointment provides funding to advance their scientific initiatives — better enabling them to pursue new research directions and capitalize on new opportunities.

“The Biology Department and MIT are delighted to provide this support to Pulin and Ankur,” says Alan D. Grossman, professor and head of the MIT department of Biology, “and we are thrilled that they are engaged and active members of our community.”

“We are very proud to have accomplished, early-career researchers like Ankur and Pulin on our faculty,” says Whitehead Institute netbet sports bettingdirector Ruth Lehmann, “and pleased that MIT is recognizing their talents and promise for leadership with these prestigious professorships.”

Both appointments are for a three-year term beginning July 1, 2020.

How to Reopen? Tools Visualizing Covid-19 Data Provide Concrete Guidance
Kara Baskin | Slice of MIT
July 14, 2020

Where could another Covid-19 spike happen? During the next major hurricane, will residents have access to food and appropriate shelter?

Ellie Graeden PhD ’11 answers questions like these as founder and CEO of Talus Analytics, a Colorado-based research and consulting firm. She’s a scientific interpreter, deciphering natural-disaster and public-health data for decision makers who must act sensibly—and quickly.

Talus is currently focused on modeling the spread of Covid-19 to guide response efforts, working closely with academic and research partners and the US Centers for Disease Control and Prevention in a range of efforts, several of which are publicly available.“Often, those kinds of data aren’t communicated in a way that’s immediately useful,” she explains. “We translate the data and the modeling results to inform practical decisions that need to get made on a day-in, day-out basis.”

COVID Local is a data-driven decision framework that helps policymakers determine when and how to reopen during each phase. A dashboard uses clear metrics to determine the parameters for each threshold. It’s a joint initiative from the Global Biological Policy Program at the Nuclear Threat Initiative (NTI), the Center for Global Development, and the Georgetown University Center for Global Health Science and Security, where Graeden is an adjunct professor.

“COVID Local is focused on getting concrete guidance in place for those local decision makers so that they have a checklist that they can work through, driven by some of the best experts in global public health, who have managed outbreaks for Ebola in 2014 and elsewhere,” she says.

A second tool, Re:Public COVID Log, is a map-based platform that tracks communities visually, providing views of hazard risk, infrastructure, and population. It was developed with support from the US Department of Homeland Security and FEMA, and it’s simple enough for a nonexpert to use.

“A lot of the current tools are very expert focused. This is targeted for use by those without hazard-specific expertise—for example, by the communications office for a mayor,” she says.

In collaboration with Georgetown University, Talus has also built a large-scale database to track the effectiveness of various mitigation policies, helping to guide policymakers who might need to close for a second wave.

“We let them know what worked the first time,” she says.

All of this might seem like a leap for a microbiologist. Graeden earned her doctorate in cell biology at MIT, where she studied brain development in zebrafish under Professor Hazel L. Sive.

“I learned how to tell scientific stories visually, which is essentially what microscopy is. You’re telling stories with pictures,” she says.

She founded her 10-person firm in 2015 to do the same with global health issues: There was plenty of data, she felt, that nobody was looking at under a microscope and bringing to light. (Fellow MIT alum Trae Wallace MBA ’10 guides Talus’s development as its head of data.)

The company first made a name for itself during Hurricane Matthew in 2016, when Talus deployed to FEMA’s National Response Coordination Center to deduce how many people would be impacted by the storm’s wrath.

Her team harnessed data from the Department of Energy, looking at real-time power outages, and merged them with inland and coastal flood modeling to determine counties that would be hit. Next, they leveraged census data to capture the total number of people affected. While all the data from each source had been previously available, the questions being asked required real-time integration of the information for the response effort.

Since then, Talus has become a go-to for government and academic partners when “integrating different types of information and doing that storytelling,” Graeden says. “Flood modelers didn’t feel comfortable pulling in energy data or outage data or coastal modeling data. It was really a data analysis and storytelling problem,” she says.

Now, she tells these number stories from her perch in Colorado, where she moved in 2015 to be farther from what she calls “power-driven” Washington. It’s also closer to northern Idaho, where she grew up. Still, she looks back fondly on her time in Cambridge, where she jogged in the Arboretum and played competitive Ultimate Frisbee off campus, practicing up to 16 hours on the weekends. She also leaves a legacy of service to the school community as the founder of MIT BioREFS (Resource for Easing Friction and Stress), a peer mentorship program within the biology department, after a friend died by suicide.

“MIT was the first place I’d ever been where the response to an idea was routinely, ‘Well, is that the right thing to do?’ Whereas prior, the response had always been, ‘Well, can it be done right?’ At MIT, it’s not ‘Can it be done?’ but ‘What is the right way to solve it?’” she says.

As for the right thing to be doing about Covid, her assessment is stark.

“In the US, we are functionally no different from where we were three months ago. We have better treatments and a better sense for what works on the treatment side, but we have no preventative measures. We have no vaccine. We have no way to prevent people from getting sick, except social distancing measures,” she warns.

She hopes for equitable distribution of an eventual vaccine, using transparent data with demographic information layered in to target vulnerable communities.

“We need to be clear-eyed about what is happening. We need to collect data with demographic details attached. Florida, for example, decided at one point not to allow its coroners to report Covid deaths, and those limitations on data release really hamstring our ability to respond in an informed way. We have to collect the data, we need to be able to analyze it, and we need to be able to integrate data so that we can make decisions on the basis of it,” she says.

Seemingly similar, two neurons show distinct styles as they interact with the same muscle partner
Picower Institute
July 7, 2020

A new study by MIT neuroscientists into how seemingly similar neuronal subtypes drive locomotion in the fruit fly revealed an unexpected diversity as the brain’s commands were relayed to muscle fibers. A sequence of experiments revealed a dramatic difference between the two nerve cells – one neuron scrambled to adjust to different changes by the other, but received no requital in response when circumstances were reversed.

The findings published in the Journal of Neuroscience suggest that these subclasses of neurons, which are also found abundantly in people and many other animals, exhibit a previously unappreciated diversity in their propensity to respond to changes, a key property known as “synaptic plasticity.” Synaptic plasticity is considered an essential mechanism of how learning and memory occur in the brain, and aberrations in of the process are likely central to disorders such as autism.

“By seeing that these two different types of motor neurons actually show very distinct types of plasticity, that’s exciting because it means it’s not just one thing happening,” said senior author Troy Littleton, a member of The Picower Institute for Learning and Memory and Menicon Professor of Neuroscience in MIT’s Departments of Biology and of Brain and Cognitive Sciences. “There’s multiple types of things that can be altered to change connectivity within the neuromuscular system.”

Tonic and phasic neurons

Both of the neurons work in the same way, by emitting the neurotransmitter glutamate onto their connections, or synapses, with the muscles. But these two neurons do so with different styles. The “tonic” neuron, which connects only to a single muscle, emits its glutamate at a constant but low rate while the muscle is active. Meanwhile, the “phasic” neuron connects to a whole group of muscles and jumps in with a strong quick pulse of activity to spring the muscles into action.

Heading into the study Littleton and lead author Nicole Aponte-Santiago were curious to explore whether these different neurons compete or cooperate NetBet sportto drive the muscle fibers, and if they exhibited different plasticity when their functions were altered. To get started on what ultimately became her dissertation research, Aponte-Santiago developed the means to tailor genetic alterations specifically in each of the two neurons.

“The reason we were able to answer these questions in the first place was because we produced tools to start differentially manipulating one neuron versus the other one, or label one versus the other one,” said Aponte-Santiago, who earned her PhD in Littleton’s lab earlier this spring and is now a postdoc at the University of California at San Francisco.

With genetic access to each neuron, Aponte-Santiago distinctly labeled them to watch each one grow in fly larvae as they developed. She saw that the tonic neuron reached the muscle first and that the phasic one connected to the muscle later. She also observed that unlike in mammals, the neurons did not compete to control the muscle but remained side by side, each contributing in its characteristic way to the total electrical activity needed to drive movement.

To study the neurons’ plasticity, Aponte-Santiago employed two manipulations of each neuron. She either wiped them out completely by making them express a lethal protein called “reaper” or she substantially tamped down their glutamate activity via expression of tetanus toxin.

When she wiped out the phasic neuron with reaper, the tonic neuron quickly stepped up its signaling, attempting to compensate as much as it could. But in flies where she wiped out the tonic neuron, the phasic neuron didn’t budge at all, continuing as if nothing had changed.

Similarly when Aponte-Santiago reduced the activity of the phasic neuron with the toxin, the tonic neuron increased the number of boutons and active zone structures in its synapses to respond to the loss of its partner. But when she reduced the activity of the tonic neuron the phasic neuron again didn’t appear to respond.

In all the experiments, the muscle received less overall drive from the neurons than when everything was normal. And while the phasic neuron  apparently didn’t bother to make up for any loss on the part of the tonic neuron, the tonic neuron employed different means to compensate – either increasing its signaling or by enhancing the number of its connections on the muscle – depending on how the phasic neuron was diminished.

“It was quite intriguing that Nicole found that when the phasic input wasn’t there, there was a unique form of plasticity that the tonic neuron showed,” Littleton said, “but if the phasic neuron was there and wasn’t working, the tonic neuron behaved in a very different way.”

Another intriguing aspect of the study is the role of the muscle itself, which may be an active intermediary of the plasticity, Littleton said. The neurons may not sense when each other have been wiped out or inactivated. Instead the muscle appears to call for those changes.

“Even though a muscle has two distinct inputs, it can sort of uniquely control those two,” Littleton said. “When the muscle is getting glutamate, does it know whether it is coming from the tonic or the phasic neuron and does it care? It appears that it does care, that it really needs the tonic more than the phasic. When the phasic is gone it shifts some of the plasticity, but when the tonic is gone the phasic can’t do much about it.”

In new work, the lab is now looking at differences in gene expression between the two neurons to identify which proteins are responsible for the unique properties and plasticity of the tonic and phasic neurons. By defining the genetic underpinnings of their unique properties, the lab hopes to begin to get a handle on the molecular underpinnings of neuronal diversity in the brain.

In addition to Aponte-Santiago and Littleton, the paper’s other authors are Kiel Ormerod and Yulia Akbergenova.

The National Institutes of Health and the JPB Foundation supported the study.

Nine MIT School of Science professors receive tenure for 2020

Professors earn tenure in the departments of Brain and Cognitive Sciences, Chemistry, Mathematics, and Physics.

School of Science
July 6, 2020

Beginning July 1, nine faculty members in the MIT School of Science have been granted tenure by MIT. They are appointed in the departments of Brain and Cognitive Sciences, Chemistry, Mathematics, and Physics.

Physicist Ibrahim Cisse investigates living cells to reveal and study collective behaviors and biomolecular phase transitions at the resolution of single molecules. The results of his work help determine how disruptions in genes can cause diseases like cancer. Cisse joined the Department of Physics in 2014 and now holds a joint appointment with the Department of Biology. His education includes a bachelor’s degree in physics from North Carolina Central University, concluded in 2004, and a doctoral degree in physics from the University of Illinois at Urbana-Champaign, achieved in 2009. He followed his PhD with a postdoc at the École Normale Supérieure of Paris and a research specialist appointment at the Howard Hughes Medical Institute’s Janelia Research Campus.

Jörn Dunkel is a physical applied mathematician. His research focuses on the mathematical description of complex nonlinear phenomena in a variety of fields, especially biophysics. The models he develops help predict dynamical behaviors and structure formation processes in developmental biology, fluid dynamics, and even knot strengths for sailing, rock climbing and construction. He joined the Department of Mathematics in 2013 after completing postdoctoral appointments at Oxford University and Cambridge University. He received diplomas in physics and mathematics from Humboldt University of Berlin in 2004 and 2005, respectively. The University of Augsburg awarded Dunkel a PhD in statistical physics in 2008.

A cognitive neuroscientist, Mehrdad Jazayeri studies the neurobiological underpinnings of mental functions such as planning, inference, and learning by analyzing brain signals in the lab and using theoretical and computational models, including artificial neural networks. He joined the Department of Brain and Cognitive Sciences in 2013. He achieved a BS in electrical engineering from the Sharif University of Technology in 1994, an MS in physiology at the University of Toronto in 2001, and a PhD in neuroscience from New York University in 2007. Prior to joining MIT, he was a postdoc at the University of Washington. Jazayeri is also an investigator at the McGovern Institute for Brain Research.

Yen-Jie Lee is an experimental particle physicist in the field of proton-proton and heavy-ion physics. Utilizing the Large Hadron Colliders, Lee explores matter in extreme conditions, providing new insight into strong interactions and what might have existed and occurred at the beginning of the universe and in distant star cores. His work on jets and heavy flavor particle production in nuclei collisions improves understanding of the quark-gluon plasma, predicted by quantum chromodynamics (QCD) calculations, and the structure of heavy nuclei. He also pioneered studies of high-density QCD with electron-position annihilation data. Lee joined the Department of Physics in 2013 after a fellowship at CERN and postdoc research at the Laboratory for Nuclear Science at MIT. His bachelor’s and master’s degrees were awarded by the National Taiwan University in 2002 and 2004, respectively, and his doctoral degree by MIT in 2011. Lee is a member of the Laboratory for Nuclear Science.

Josh McDermott investigates the sense of hearing. His research addresses both human and machine audition using tools from experimental psychology, engineering, and neuroscience. McDermott hopes to better understand the neural computation underlying human hearing, to improve devices to assist hearing impaired, and to enhance machine interpretation of sounds. Prior to joining MIT’s Department of Brain and Cognitive Sciences, he was awarded a BA in 1998 in brain and cognitive sciences by Harvard University, a master’s degree in computational neuroscience in 2000 by University College London, and a PhD in brain and cognitive sciences in 2006 by MIT. Between his doctoral time at MIT and returning as a faculty member, he was a postdoc at the University of Minnesota and New York netbet online sports bettingUniversity, and a visiting scientist at Oxford University. McDermott is also an associate investigator at the McGovern Institute for Brain Research and an investigator in the Center for Brains, Minds and Machines.

Solving environmental challenges by studying and manipulating chemical reactions is the focus of Yogesh Surendranath’s research. Using chemistry, he works at the molecular level to understand how to efficiently interconvert chemical and electrical energy. His fundamental studies aim to improve energy storage technologies, such as batteries, fuel cells, and electrolyzers, that can be used to meet future energy demand with reduced carbon emissions. Surendranath joined the Department of Chemistry in 2013 after a postdoc at the University of California at Berkeley. His PhD was completed in 2011 at MIT, and BS in 2006 at the University of Virginia. Suendranath is also a collaborator in the MIT Energy Initiative.

A theoretical astrophysicist, Mark Vogelsberger is interested in large-scale structures of the universe, such as galaxy formation. He combines observational data, theoretical models, and simulations that require high-performance supercomputers to improve and develop detailed models that simulate galaxy diversity, clustering, and their properties, including a plethora of physical effects like magnetic fields, cosmic dust, and thermal conduction. Vogelsberger also uses simulations to generate scenarios involving alternative forms of dark matter. He joined the Department of Physics in 2014 after a postdoc at the Harvard-Smithsonian Center for Astrophysics. Vogelsberger is a 2006 graduate of the University of Mainz undergraduate program in physics, and a 2010 doctoral graduate of the University of Munich and the Max Plank Institute for Astrophysics. He is also a principal investigator in the MIT Kavli Institute for Astrophysics and Space Research.

Adam Willard is a theoretical chemist with research interests that fall across molecular biology, renewable energy, and material science. He uses theory, modeling, and molecular simulation to study the disorder that is inherent to systems over nanometer-length scales. His recent work has highlighted the fundamental and unexpected role that such disorder plays in phenomena such as microscopic energy transport in semiconducting plastics, ion transport in batteries, and protein hydration. Joining the Department of Chemistry in 2013, Willard was formerly a postdoc at Lawrence Berkeley National Laboratory and then the University of Texas at Austin. He holds a PhD in chemistry from the University of California at Berkeley, achieved in 2009, and a BS in chemistry and mathematics from the University of Puget Sound, granted in 2003.

Lindley Winslow seeks to understand the fundamental particles shaped the evolution of our universe. As an experimental particle and nuclear physicist, she develops novel detection technology to search for axion dark matter and a proposed nuclear decay that makes more matter than antimatter. She started her faculty position in the Department of Physics in 2015 following a postdoc at MIT and a subsequent faculty position at the University of California at Los Angeles. Winslow achieved her BA in physics and astronomy in 2001 and PhD in physics in 2008, both at the University of California at Berkeley. She is also a member of the Laboratory for Nuclear Science.