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Advocating for vaccine equity

Postdoc Dig Bijay Mahat became a cancer researcher to improve healthcare in Nepal, but the COVID-19 pandemic exposed additional resource disparities.

Raleigh McElvery
February 17, 2022

When Dig Bijay Mahat arrived at MIT in 2017 to begin his postdoctoral studies, he had one very clear goal: to become an expert in cancer research and diagnostics so he could improve healthcare in Nepal, where he was born. In 2020, when the COVID-19 pandemic laid bare additional discrepancies in resource equity around the world, his goal did not waiver. But it did expand to fill a more immediate need — help Nepal find the best way to navigate widespread COVID testing requirements and vaccine rollouts.

Mahat was born in the western region of Nepal, where his family has owned a large swath of land for generations. Before Mahat was born, his grandfather passed away unexpectedly. And, as the eldest son, Mahat’s father assumed responsibility for his five of siblings at the age of 21. As a result, Mahat’s father missed his chance to pursue the education he’d envisioned. Perhaps because of this, he made it his mission to give Mahat the education he never received. However, no school was quite good enough, and he shuffled Mahat between nine different institutions before the age of 18.

While his father wished him all the success and prestige that would come with pursing a medical career, Mahat had other plans. Toward the end of high school, he became captivated by song writing, and even secretly used his school tuition money one semester to record an album. “It was a disastrous flop,” he now recalls with a smile.

Although his foray into the music industry provides comic relief today, at the time Mahat was dismayed to be back on the medical track. However, he did convince his father to let him go to the US for college. He ended up at Towson University in Maryland, living with his aunt and uncle and delivering pizzas to support his nuclear family back in Nepal. Some weeks, he clocked in over 100 hours of deliveries.

As a molecular biology, biochemistry, and bioinformatics major, he took every research opportunity he could get, and became enthralled by breast cancer research. Shortly thereafter, his mother was diagnosed with the same disease, which further strengthened his conviction to learn as much as he could in the US, and return to Nepal to help as many patients as he could.

“The state of cancer diagnostics is very poor in Nepal,” he explains. Patient biopsies must be sent to other countries such as India — a costly practice at the mercy of politics and travel restrictions. “The least we can do is become self-sufficient and provide these vital molecular diagnostics tools to our own people,” Mahat says.

He went on to earn his PhD in molecular biology and genetics from Cornell University, and by the fall of 2017 he had secured his dream job: a postdoctoral position in the lab of MIT Professor of Biology Susan Lindquist. Mahat had spent much of his time at Cornell studying a protein known as heat shock factor 1, and Lindquist had conducted seminal work showing that this same protein enables healthy cells to suddenly turn into cancer cells. Just as he had finalized his new apartment lease and was preparing to start his new job, Lindquist wrote from the hospital to tell him she had late-stage ovarian cancer, and suggested he complete his postdoctoral studies elsewhere.

Gutted, he scrambled to find another position, and built up the courage to contact MIT professor, Koch Institute member, and Nobel laureate Phil Sharp. Mahat put together a formal research proposal and presented it to Sharp. A few days later, he became the lab’s newest member.

“From the beginning, the things that struck me about Phil were his humility, his attention to experimental detail, and his inexplicable reservoir of insight,” Mahat says. “If I could carry even just some of that same humility with me for the rest of my life, I would be a good human being.”

In 2018, Mahat and Sharp filed a patent with the potential to revolutionize disease diagnostics. Widely-available single-cell sequencing technologies reveal the subset of RNAs inside a cell that build proteins. But Mahat and his colleagues found a way to take a snapshot of all the RNA inside a single cell that is being transcribed from DNA — including RNAs that will never become proteins. Because many ailments arise from mutations in the “non-coding” DNA that gives rise to this “non-coding” RNA, the researchers hope their new method will help expose the function of non-coding variants in diseases like diabetes, autoimmune disorders, neurological diseases, and cancer.

Mahat was still immersed in this research in early 2020 when the COVID-19 pandemic began to escalate. As case numbers soared around the world, it became clear to him that the wealth of COVID testing resources available on MIT’s campus — and throughout the US in general — dwarfed the means available to his family back in Nepal. Polymerase chain reaction (PCR) testing remains the most popular and accurate means to detect the virus in patient samples. While PCR machines are quite common in molecular biology labs across the US, the entire country of Nepal owned just a few at the start of the pandemic, according to Mahat.

“Digbijay was focused intensely on developing our novel single-cell technology when he became aware of Nepal’s challenges to control the COVID-19 pandemic,” Sharp recalls. “While continuing his research in the lab, he spent several months contacting leaders in pharmaceutical companies in the US and leaders in public health in Nepal to help arrange access to vaccines and rapid tests.”

Mahat was already in contact with the Nepali Ministry of Health and Population regarding the state of the country’s cancer diagnostics, and so the government called on him to advise their COVID testing efforts. Given the high cost and limited availability of PCR machines and reagents, Mahat began discussions with MIT spinoff Sherlock Biosciences, in order to bring an alternative testing technology to Nepal. These COVID tests, which were developed at the Broad Institute of MIT and Harvard, use the CRISPR/Cas9 system — rather than PCR — to detect the SARS-CoV2 virus that causes COVID-19, making them cheaper and more readily available. Sherlock Biosciences ultimately donated $100,000-worth of testing kits, supplemented by an additional $100,000 grant from the Open Philanthropy Project to help purchase the equipment necessary to implement the tests. In December of 2020, Mahat and his wife Rupa Shah flew to Nepal to set up a testing center using these new resources.

Although this required Mahat to briefly pause his MIT research, Sharp was supportive of these extracurricular pursuits. “We are very proud of Jay’s effective work benefiting the people of Nepal,” Sharp says.

Around the same time, Mahat reached out to Institute professor and Moderna co-founder Robert Langer to help initiate vaccine talks with the Nepali government. Through Sharp’s contacts, Mahat was also able to connect the government with Johnson & Johnson. In addition, Mahat, Sharp, and Emeritus Professor Uttam RajBhandary wrote a letter to MIT president Rafael Reif, who joined other university leadership in urging the Biden administration to donate vaccines to low-income countries.

Nepal ultimately received its COVID-19 vaccines through the COVAX program, co-led by the Coalition for Epidemic Preparedness Innovations, GAVI Alliance, and the World Health Organization. Today, the country has begun administering boosters. There were also some funds left over from the Open Philanthropy Project grant, which went toward sending Nepal several thousand PCR kits designed to distinguish between the delta and omicron variants. Professor Tyler Jacks, the Koch Institute director at that time, also connected Mahat with the company Thermo Fisher Scientific to secure additional PCR reagents.

Roshan Pokhrel, the Secretary of Nepal’s Ministry of Health and Population, met Mahat prior to the pandemic, and relied on his expertise to begin establishing Nepal’s National Cancer Institute (NCI) in 2020. “It was his cooperation and coordination that helped us set up NCI,” Pokhrel says. “Mr. Mahat’s continuous support during the first two waves of our COVID-19 vaccine distribution was also netbet sports betting apphighly appreciated. During the recent omicron outbreak, his support in our public laboratory helped us to monitor the variant.”

Bhagawan Koirala, chairman of the Nepal Medical Council, participated in the vaccine talks that Mahat organized between Nepal’s Ministry of Health and Johnson & Johnson. Koirala says he was impressed by Mahat’s exceptional credentials and his modesty, as well as his desire to promote cancer research and diagnostics. As the chairman of the Kathmandu Institute of Child Health, Koirala hopes to engage Mahat’s expertise in the future to help advance pediatric cancer research in Nepal.

“We have spoken extensively about the policies regarding cancer diagnostics in Nepal,” Koirala says. “Dr. Mahat and I are eager to work with the government to introduce policies that will help develop local diagnostic capacity and discourage sending patient samples out of the country. This will save costs, ensure patient privacy, and improve quality of care and research.”

These days, Mahat is nothing short of a local celebrity in Nepal. Despite his current drive for ensuring vaccine equity, his ultimate goal is still to work with individuals like Koirala and Pokhrel to bring cancer treatment resources to the country. He not only envisions setting up his own research center there, but also inspiring young people to pursue careers in research. “Before me, no one in my entire village had pursued a scientific career, so if I could motivate even a few young kids to follow that path, it would be a win for me.”

But, he adds, he’s not ready to leave MIT just yet; he still has more to learn. “I feel privileged and honored to be part of this compassionate community,” he says. “I’m also proud — proud that we’ve been able to come together in this time of need.”

Sometimes science takes a village
Greta Friar | Whitehead Institute
February 17, 2022

Alexandra Navarro, a graduate student in Whitehead Institute Member Iain Cheeseman’s lab, was studying the gene for CENPR, a protein related to cell division—the Cheeseman lab’s research focus—when she came across something interesting: another molecule hidden in CENPR’s genetic code. The hidden molecule is a peptide only 37 amino acids long, too small to show up in most surveys of the cell. It gets created only when the genetic code for CENPR is translated from an offset start and stopping place—essentially, when a cell reads the instructions for making CENPR in a different way. The Cheeseman lab has become very interested in these sorts of hidden molecules, which they have found lurking in a number of other molecules’ genetic codes. Navarro began studying the peptide as a side project during slow periods in her main research on cell division proteins. However, as her research on the peptide progressed, Navarro eventually found herself unsure of how to proceed. CENPR belongs in the centromere, a part of the cell necessary for cell division, but the alternative peptide ends up in the Golgi, a structure that helps to modify molecules and prep them for delivery to different destinations. In other words, the peptide had nothing to do with the part of the cell that Navarro and Cheeseman typically study.

Usually when Navarro comes across something outside of her area of expertise, she will consult with her lab mates, others in Whitehead Institute, or nearby collaborators. However, none of her usual collaborators’ research focuses on the Golgi, so this time Cheeseman suggested that Navarro share what they had found and ask for input from as wide a circle of researchers as possible—on the internet. Often, researchers guard their work in progress carefully, reluctant to share it lest they be scooped, which means someone else publishes a paper on the same topic first. In the competitive world of academic research, where publishing papers is a key part of getting jobs, tenure, and future funding, the specter of scooping can loom large. But science is also an inherently collaborative practice, with scientists contributing droplets of discovery to a shared pool of knowledge, so that new findings can be built upon what came before. Cheeseman is a board member of ASAPbio (Accelerating Science and Publication in biology), a nonprofit that promotes open communication, the use of preprints, and transparent peer review in the life sciences. Researchers like Cheeseman believe that if science adopts more transparent and collaborative practices, such as more frequently and widely sharing research in progress, this will benefit both the people involved and the quality of the science, and will speed up the search for discoveries with the potential to positively impact humankind. But how helpful are such “open science” practices in reality? Navarro and Cheeseman had the perfect opportunity to find out.

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Navarro and Cheeseman wrote up what they knew so far–they had found a hidden peptide that localizes exclusively to the Golgi, and it stays there throughout the cell cycle–as a “preprint in progress,” an incomplete draft of a paper that acknowledges there is more to come. In December 2020, they posted the preprint in progress to bioRxiv, a website that serves as a repository for biology preprints, or papers that have not yet

been published. The site was inspired by arXiv, a similar repository launched in 1991 to provide free and easy access to research in math, physics, computer science, and similar fields. arXiv has become a central hub for research in these fields, with an average of 10-15,000 submissions and 30 million downloads per month. The biology fields were slower to create such a hub: BioRxiv launched in 2013. In December, 2021, it received around 3,000 submissions and 2.3 million downloads.

Navarro and Cheeseman’s decision to post a preprint in progress to bioRvix is not common practice, but a lot of researchers have started posting preprints that resemble the final paper closer to publication. Some journals even require it. This type of early sharing has many benefits: contrary to the fear that sharing research before publication will lead to scooping, it allows researchers to stake a claim sooner by making their work public record pre-publication. Preprints enable researchers to show off their most current work during the narrow windows of the academic job cycle. This can be particularly crucial for early career researchers whose biggest project to date—such as graduate thesis work—is still in publication limbo. Preprints also allow new ideas and knowledge to get out into the world sooner, the better to inspire other researchers. Findings that seemed minor at first have provided the key insight for someone else’s major discovery throughout biology’s history. The sooner research is shared, the sooner it can be built upon to develop important advances, like new medicines or a better model of how a disease spreads.

Navarro and Cheeseman weren’t expecting their discovery to have that kind of major impact, but they knew the peptide could be useful to researchers studying the Golgi. The peptide is small and doesn’t disrupt any functions in the cell. Researchers can attach fluorescent proteins to it that make the Golgi glow in imaging. These traits make the peptide a useful potential tool. Since Navarro and Cheeseman posted the preprint, multiple researchers have reached out about using the peptide.

However, the main goal of posting a preprint in progress, as opposed to a polished preprint, is to ask for input to further the research. The morning after the researchers put their preprint on bioRxiv, Cheeseman shared it on Twitter and asked for feedback. Other researchers soon shared the tweet further, and responses started flooding in. Some researchers simply commented that they found the project interesting, which was reassuring for Cheeseman and Navarro.

“It was nice to see that we weren’t the only ones who thought this thing we found was really cool,” Navarro says. “It gave me a lot of motivation to keep moving on with this project.”

Then, some researchers had specific questions and ideas. The topic that seemed of greatest interest was how the peptide ends up at the Golgi, followed by where exactly in the Golgi it ends up. Researchers suggested online tools that might help predict answers to these questions. They proposed different mechanisms that might be involved.

Navarro used these suggestions to design a new series of experiments, in order to better characterize how the peptide associates with the Golgi. She found out that the peptide attaches to the Golgi’s outer-facing membrane. She started developing an understanding of which of peptide’s 37 amino acids were necessary for Golgi localization, and so was able to narrow in on a 14-amino acid sequence within the peptide that was sufficient for this localization.

Her next question was what specific mechanisms were driving the peptide’s Golgi localization. Navarro had a good lead for one mechanism: the evidence and outside input suggested that after the peptide was created, it likely underwent a modification that gave it a sticky tag to anchor it to the Golgi. What would be the best experiments to confirm this mechanism and determine the other mechanisms involved? Navarro and Cheeseman decided it was time to check back in with the crowd online.

Narrowing in on answers

Navarro and Cheeseman updated their preprint with their new findings, and invited further feedback. This time, they had a specific ask: how to test whether the peptide has the modification they suspected. They received suggestions: a probe, an inhibitor. They also received some unexpected feedback that took them in a new direction. Harmit Malik, professor and associate director of the basic sciences division at Fred Hutch, studies the evolutionary changes that occur in genes. Malik found the peptide interesting enough to dig into its evolutionary history across primates. He emailed Cheeseman and Navarro his findings. Versions of the peptide existed in many primates, and some of the variations between species affected where the peptide ended up. This was a rich new vein of inquiry for Navarro to follow in order to pinpoint exactly which parts of the sequence were necessary for Golgi localization, and the researchers might never netbet sports betting apphave come across it if they had not sought input online.

Guided by the latest set of suggestions, Navarro resumed work on the project. She found evidence that the peptide does undergo the suspected modification. She winnowed down to a 10-amino acid sequence within the peptide that appears to be the minimal sequence necessary for this type of Golgi localization. Navarro and Cheeseman rewrote the paper, adding the discovery of a minimal Golgi targeting sequence—basically a postal code that marks a molecule’s destination as the Golgi. They posted a third version of the preprint in September, 2021. This time, Cheeseman did not ask Twitter for feedback: the paper may undergo more changes, but it now contains a complete research story.

The changing face of science

Based on their experience, would Cheeseman and Navarro recommend sharing preprints in progress? The answer is a resounding yes—if the project is a good fit. Both agree that for projects like this, where the subject is outside the expertise of a researcher’s usual circle of collaborators, asking the wider scientific community for help can be extremely valuable.

“I often share my research with other people at Whitehead Institute, and other cell division researchers at conferences, but this process allowed me to share it with people who work in different scientific areas, with whom I would not normally engage,” Navarro says.

Cheeseman hopes that sharing hubs like bioRxiv will develop ways for even larger and more diverse groups of scientists to connect.

If researchers are hesitant to use an open science approach, Cheeseman and Navarro recommend testing the waters by starting with a lower stakes project. In this case, Navarro’s Golgi paper was a side project, something of personal interest but not integral to her career. Having had a positive experience using an open approach on this project, Cheeseman and Navarro agree they would be comfortable using such an approach again in the future.

“I wouldn’t suggest sharing a preprint in progress for every paper, but I think constructive opportunities are more plentiful than researchers may realize,” Cheeseman says.

In general, Cheeseman thinks, the biology field needs to re-envision how its science gets shared.

“The idea that one size fits all, that everything needs to be a multi-figure paper in a high impact journal, is just not compatible with the way that people do research,” Cheeseman says. “We need to get flexible and explore and value scholarship in every form.”

As for the peptide paper? Regardless of where it ends up, Cheeseman and Navarro consider their open science experiment a success. By sharing their research and asking for input, they gained insights, research tools, and points of view that took the project from a curious finding to a rich understanding of the mechanisms behind Golgi localization. Their early realization that the peptide functions outside of their region of expertise could have been a dead end. But by being open about what they were working on and what sort of guidance they needed, the researchers were able to overcome that hurdle and decode their mystery peptide, with a little help from the wider scientific community.

Seven new faculty join the MIT School of Science

Departments of Biology and Brain and Cognitive Sciences welcome new professors.

School of Science
February 16, 2022

This winter, seven new faculty members join the MIT School of Science in the departments of Biology and Brain and Cognitive Sciences.

Siniša Hrvatin studies how animals initiate, regulate, and survive states of stasis, such as torpor and hibernation. To survive extreme environments, many animals have evolved the ability to decrease metabolic rate and body temperature and enter dormant states. His long-term goal is to harness the potential of these biological adaptations to advance medicine. Previously, he identified the neurons that regulate mouse torpor and established a platform for the development of cell-type-specific viral drivers.

Hrvatin earned his bachelor’s degree in biochemical sciences in 2007 and his PhD in stem cell and regenerative medicine in 2013, both from Harvard University. He was then a postdoc in bioengineering at MIT and a postdoc in neurobiology at Harvard Medical School. Hrvatin returns to MIT as an assistant professor of biology and a member of the Whitehead Institute for Biomedical Research.

Sara Prescott investigates how sensory inputs from within the body control mammalian physiology and behavior. Specifically, she uses mammalian airways as a model system to explore how the cells that line the surface of the body communicate with parts of the nervous system. For example, what mechanisms elicit a reflexive cough? Prescott’s research considers the critical questions of how airway insults are detected, encoded, and adapted to mammalian airways with the ultimate goal of providing new ways to treat autonomic dysfunction.

Prescott earned her bachelor’s degree in molecular biology from Princeton University in 2008 followed by her PhD in developmental biology from Stanford University in 2016. Prior to joining MIT, she was a postdoc at Harvard Medical School and Howard Hughes Medical Institute. The Department of Biology welcomes Prescott as an assistant professor.

Alison Ringel is a T-cell immunologist with a background in biochemistry, biophysics, and structural biology. She investigates how environmental factors such as aging, metabolism, and diet impact tumor progress and the immune responses that cause tumor control. By mapping the environment around a tumor on a cellular level, she seeks to gain a molecular understanding of cancer risk factors.

Ringel received a bachelor’s degree in molecular biology, biochemistry, and physics from Wesleyan University, then a PhD in molecular biophysics from John Hopkins University School of Medicine. Previously, Ringel was a postdoc in the Department of Cell Biology at Harvard Medical School. She joins MIT as an assistant professor in the Department of Biology and a core member of the Ragon Institute of MGH, MIT and Harvard.

Francisco J. Sánchez-Rivera PhD ’16 investigates genetic variation with a focus on cancer. He integrates genome engineering technologies, genetically-engineered mouse models (GEMMs), and single cell lineage tracing and omics approaches in order to understand the mechanics of cancer development and evolution. With state-of-the-art technologies — including a CRISPR-based genome editing system he developed as a graduate student at MIT — he hopes to make discoveries in cancer genetics that will shed light on disease progression and pave the way for better therapeutic treatments.

Sánchez-Rivera received his bachelor’s degree in microbiology from the University of Puerto Rico at Mayagüez followed by a PhD in biology from MIT. He then pursued postdoctoral studies at Memorial Sloan Kettering Cancer Center supported by a HHMI Hanna Gray Fellowship. Sánchez-Rivera returns to MIT as an assistant professor in the Department of Biology and a member of the Koch Institute for Integrative Cancer Research at MIT.

Nidhi Seethapathi builds predictive models to help understand human movement with a combination of theory, computational modeling, and experiments. Her research focuses on understanding the objectives that govern movement decisions, the strategies used to execute movement, and how new movements are learned. By studying movement in real-world contexts using creative approaches, Seethapathi aims to make discoveries and develop tools that could improve neuromotor rehabilitation.

Seethapathi earned her bachelor’s degree in mechanical engineering from the Veermata Jijabai Technological Institute followed by her PhD in mechanical engineering from Ohio State University. In 2018, she continued to the University of Pennsylvania where she was a postdoc. She joins MIT as an assistant professor in the Department of Brain and Cognitive Sciences with a shared appointment in the Department of Electrical Engineering and Computer Science at the MIT Schwarzman College of Computing.

Hernandez Moura Silva researches how the immune system supports tissue physiology. Silva focuses on macrophages, a type of immune cell involved in tissue homeostasis. He plans to establish new strategies to explore the effects and mechanisms of such immune-related pathways, his research ultimately leading to the development of therapeutic approaches to treat human diseases.

Silva earned a bachelor’s degree in biological sciences and a master’s degree in molecular biology from the University of Brasilia. He continued to complete a PhD in immunology at the University of São Paulo School of Medicine: Heart Institute. Most recently, he acted as the Bernard Levine Postdoctoral Fellow in immunology and immuno-metabolism at the New York University School of Medicine: Skirball Institute of Biomolecular Medicine. Silva joins MIT as an assistant professor in the Department of Biology and a core member of the Ragon Institute.

Yadira Soto-Feliciano PhD ’16 studies chromatin — the complex of DNA and proteins that make up chromosomes. She combines cancer biology and epigenetics to understand how certain proteins affect gene expression and, in turn, how they impact the development of cancer and other diseases. In decoding the chemical language of chromatin, Soto-Feliciano pursues a basic understanding of gene regulation that could improve the clinical management of diseases associated with their dysfunction.

Soto-Feliciano received her bachelor’s degree in chemistry from the University of Puerto Rico at Mayagüez followed by a PhD in biology from MIT, where she was also a research fellow with the Koch Institute. Most recently, she was the Damon Runyon-Sohn Pediatric Cancer Postdoctoral Fellow at The Rockefeller University. Soto-Feliciano returns to MIT as an assistant professor in the Department of Biology and a member of the Koch Institute.

Whitehead Institute Member Pulin Li named an Allen Distinguished Investigator
Merrill Meadow | Whitehead Institute
February 9, 2022

Whitehead Institute Member Pulin Li has been selected by The Paul G. Allen Frontiers Group to be an Allen Distinguished Investigator. The Allen Distinguished Investigator program backs creative, early-stage research projects in biology and medical research that would not otherwise be supported by traditional research funding programs. Each Allen Distinguished Investigator award provides three years of research funding.

Li, who is also an assistant professor of biology and the Eugene Bell Career Development Professor of Tissue Engineering at Massachusetts Institute netbet online sports bettingof Technology, studies how circuits of genes within individual cells enable multicellular functions and phenomena such as the patterns of varied cell types that comprise a tissue. Her lab combines approaches from synthetic biology, developmental biology, biophysics, and systems biology to quantitatively understand how cells communicate to produce those phenomena. The work could lead to ways to program stem cells to form tissues for regenerative medicine.

“I am very grateful for this generous support ,” Li says. “The Frontiers Group’s commitment to early-stage investigations is welcome by scientists who are trying to open new paths to discovery.”

Li’s project seeks to advance the field of synthetic developmental biology through improving the process researchers use to create small groups of cells that develop certain functions of organs. Known as organoids, these tissues enable researchers to learn more about how organs develop and function in both healthy and diseased states; and they could be used for rapid and accurate preclinical drug testing.

“All organs in our body are ecosystems of different cell types that constantly talk to each other and regulate each other’s fates, and the challenge researchers face is creating organoids that reflect this multifaceted interaction,” Li explains. “Organoids that include a more complex and complete suite of tissues may prove to function more like real organs. In the project supported by the Allen Distinguished Investigator award, my lab seeks to improve the development of organoids by introducing a type of supportive tissue known as the stroma.”

Most organs are made of epithelial cells juxtaposed with the stroma’s connective tissue. Within the stroma, mesenchymal cells help to orchestrate tissue formation and the spatial organization of other cell types. The versatile function of mesenchymal cells critically depends on their extraordinary capability to produce an array of molecules that can stimulate other cell types.

As a result, each population of mesenchymal cells has distinct capability to support the development of other cell types, control organ shapes, respond to tissue injury, and regulate inflammation.

“Despite the important function of mesenchymal cells,” Li says, “they are mostly missing in the organoids that researchers have thus far developed. Our goal is to engineer diverse populations of human mesenchymal cells and  reconstitute their spatial relationship and communication with other cell types in the stroma.

“Ultimately, we believe, these synthetically engineered stroma will help unleash the full potential of organoids as useful tools for studying organ formation and physiology.”

The Paul G. Allen Frontiers Group was founded in 2016 by the late philanthropist Paul G. Allen to explore the landscape of bioscience and to identify and foster ideas that will change the world. Its Allen Distinguished Investigators program advances frontier explorations with exceptional creativity and potential impact.

Probing how proteins pair up inside cells

MIT biologists drilled down into how proteins recognize and bind to one another, informing drug treatments for cancer.

Raleigh McElvery | Department of Biology
February 3, 2022

Despite its minute size, a single cell contains billions of molecules that bustle around and bind to one another, carrying out vital functions. The human genome encodes about 20,000 proteins, most of which interact with partner proteins to mediate upwards of 400,000 distinct interactions. These partners don’t just latch onto one another haphazardly; they only bind to very specific companions that they must recognize inside the crowded cell. If they create the wrong pairings — or even the right pairings at the wrong place or wrong time — cancer or other diseases can ensue. Scientists are hard at work investigating these protein-protein relationships, in order to understand how they work, and potentially create drugs that disrupt or mimic them to treat disease.

The average human protein is composed of approximately 400 building blocks called amino acids, which are strung together and folded into a complex 3D structure. Within this long string of building blocks, some proteins contain stretches of four to six amino acids called short linear motifs (SLiMs), which mediate protein-protein interactions. Despite their simplicity and small size, SLiMs and their binding partners facilitate key cellular processes. However, it’s been historically difficult to devise experiments to probe how SLiMs recognize their specific binding partners.

To address this problem, a group led by Theresa Hwang PhD ’21 designed a screening method to understand how SLiMs selectively bind to certain proteins, and even distinguish between those with similar structures. Using the detailed information they gleaned from studying these interactions, the researchers created their own synthetic molecule capable of binding extremely tightly to a protein called ENAH, which is implicated in cancer metastasis. The team shared their findings in a pair of eLife studies, one published on Dec. 2, 2021, and the other published Jan. 25.

“The ability to test hundreds of thousands of potential SLiMs for binding provides a powerful tool to explore why proteins prefer specific SLiM partners over others,” says Amy Keating, professor of biology and biological engineering and the senior author on both studies. “As we gain an understanding of the tricks that a protein uses to select its partners, we can apply these in protein design to make our own binders to modulate protein function for research or therapeutic purposes.”

Most existing screens for SLiMs simply select for short, tight binders, while neglecting SLiMs that don’t grip their partner proteins quite as strongly. To survey SLiMs with a wide range of binding affinities, Keating, Hwang, and their colleagues developed their own screen called MassTitr.

The researchers also suspected that the amino acids on either side of the SLiM’s core four-to-six amino acid sequence might play an underappreciated role in binding. To test their theory, they used MassTitr to screen the human proteome in longer chunks comprised of 36 amino acids, in order to see which “extended” SLiMs would associate with the protein ENAH.

ENAH, sometimes referred to as Mena, helps cells to move. This ability to migrate is critical for healthy cells, but cancer cells can co-opt it to spread. Scientists have found that reducing the amount of ENAH decreases the cancer cell’s ability to invade other tissues — suggesting that formulating drugs to disrupt this protein and its interactions could treat cancer.

Thanks to MassTitr, the team identified 33 SLiM-containing proteins that bound to ENAH — 19 of which are potentially novel binding partners. They also discovered three distinct patterns of amino acids flanking core SLiM sequences that helped the SLiMs bind even tighter to ENAH. Of these extended SLiMs, one found in a protein called PCARE bound to ENAH with the highest known affinity of any SLiM to date.

Next, the researchers combined a computer program called dTERMen with X-ray crystallography in order understand how and why PCARE binds to ENAH over ENAH’s two nearly identical sister proteins (VASP and EVL). Hwang and her colleagues saw that the amino acids flanking PCARE’s core SliM caused ENAH to change shape slightly when the two made contact, allowing the binding sites to latch onto one another. VASP and EVL, by contrast, could not undergo this structural change, so the PCARE SliM did not bind to either of them as tightly.

Inspired by this unique interaction, Hwang designed her own protein that bound to ENAH with unprecedented affinity and specificity. “It was exciting that we were able to come up with such a specific binder,” she says. “This work lays the foundation for designing synthetic molecules with the potential to disrupt protein-protein interactions that cause disease — or to help scientists learn more about ENAH and other SLiM-binding proteins.”

Ylva Ivarsson, a professor of biochemistry at Uppsala University who was not involved with the study, says that understanding how proteins find their binding partners is a question of fundamental importance to cell function and regulation. The two eLife studies, she explains, show that extended SLiMs play an underappreciated role in determining the affinity and specificity of these binding interactions.

“The studies shed light on the idea that context matters, and provide a screening strategy for a variety of context-dependent binding interactions,” she says. “Hwang and co-authors have created valuable tools for dissecting the cellular function of proteins and their binding partners. Their approach could even inspire ENAH-specific inhibitors for therapeutic purposes.”

Hwang’s biggest takeaway from the project is that things are not always as they seem: even short, simple protein segments can play complex roles in the cell. As she puts it: “We should really appreciate SLiMs more.”

New high-throughput method greatly expands view of how mutations impact cells

Broad scientists have developed a new approach for studying the functional effects of the millions of mutations associated with cancer and other diseases

Tom Ulrich | Broad Institute
January 27, 2022

There are millions of mutations and other genetic variations in cancer. Understanding which of these mutations is an impactful tumor “driver” compared to an innocuous “passenger”, and what each of the drivers does to the cancer cell, however, has been a challenging undertaking. Many studies rely on bespoke, time-consuming, gene-specific approaches that provide one-dimensional views into a given mutation’s broader functional impacts. Alternatively, computational predictions can provide functional insights, but those findings must then be confirmed through experiments.

Now, in a report published in Nature Biotechnology, a research team at the Broad Institute of MIT and Harvard has unveiled a massive-scale, high resolution method for functionally assessing large numbers of protein-coding mutations simultaneously, one that returns rich phenotypic information and which could potentially be used to study any mutation in any gene in cancer and perhaps other diseases. Their results, gained through proof-of-concept NetBet live casinoexperiments with cancer cell lines, also show that individual mutations can have a spectrum of effects not only on their impacted genes but also on molecular pathways and cell state as a whole, and add nuance to the long-accepted practice of dividing cancer mutations into so-called “drivers” and “passengers.”

“When you look at the genetic data from patients’ tumors, you see that the majority of cancer-associated mutations are actually quite rare, which means we have few insights into what these mutations do,” said Jesse Boehm of the Broad’s Cancer Program, who was co-senior author of the study with Aviv Regev, a Broad core institute member now at Genentech, a member of the Roche Group. “For cancer precision medicine to become a reality, we need a firm understanding of the function of each mutation, but a major challenge has been defining an experimental approach that could be implemented in the lab at the scale required. This new method may be the tool we need.”

The new method, called single-cell expression-based variant impact phenotyping (sc-eVIP), builds on Perturb-seq — an approach developed in 2016 by Regev and colleagues for manipulating genes and exploring the consequences of those manipulations using high-throughput single-cell RNA sequencing —  and eVIP, a method also developed in 2016 by Boehm and colleagues for profiling cancer variants at low scale using RNA measurements. While Perturb-seq assays originally relied on CRISPR to introduce mutations into cells, the sc-eVIP team adopted an overexpression-based approach, engineering DNA-barcoded gene constructs for each mutation of interest and introducing them into pools of cells in such a way that the cells expressed the mutated genes at higher-than-normal levels.

By then recording each perturbed cell’s expression profile using single cell RNA sequencing, the team could both identify which mutation a given cell carried (based on the constructs’ unique barcodes) and examine the mutation’s broader impact on the cell’s overall expression state. This approach provides a highly detailed view of a mutation’s impact on a variety of molecular pathways and circuits, and does not need to be adapted for each new gene studied.

“In a sense, we’re using the cell as a biosensor,” said Oana Ursu, a postdoctoral fellow in the Regev lab, formerly within the Broad’s Klarman Cell Observatory and now at Genentech, and co-first author of the study with JT Neal, a senior group leader in the Broad’s Cancer Program. “By looking at the expression changes that take place when we overexpress a mutated gene, we can learn whether it has a meaningful impact. But also, we can compare and categorize variants based on the changes they trigger, and look for patterns in the biology they affect.”

“Most of the technologies developed for interpreting coding variants up to now have been very scalable, but have had relatively simple readouts like cell viability or maybe looked at a single trait. Their information content has been low, and it takes a lot of work to optimize them,” said Neal. “With sc-eVIP, we’ve engineered a comprehensive approach that’s high throughput and information-rich, which could be a real boon for large-scale variant-to-function studies.”

To test sc-eVIP’s potential, the team chose to study TP53 — the most commonly mutated gene in cancer — and KRAS — which encodes a key oncogene responsible for abnormal growth of many cancers. Neal, Ursu, and their collaborators generated constructs containing 200 known TP53 and KRAS mutations (including cancer-associated mutations and control mutations known to leave gene function unaffected) and introduced them into 300,000 lung cancer cells, and captured each cell’s individual expression profile. Based on those profiles, the team categorized each mutation as either “wildtype-like” (that is, effectively functionally indistinguishable from the unmutated gene) or “putatively impactful,” from there further defining mutations based on whether they reduced or enhanced the gene’s function.

The profiles also revealed each mutation’s broader impact on cell state, based on how the activity of a variety of pathways changed across single cells. For instance, the sc-eVIP data revealed KRAS mutations that fall along a continuum in how they impact cell state at the population level, from having no impact to influencing subtle shifts in cellular abundances to causing outright activation or repression of key pathways in a majority of cells. These findings suggest that different mutations within the same gene can influence cell state along a spectrum of impact.

“The cancer community has long embraced a binary conceptual framework of ‘driver’ mutations, ones that promote cancer development and progression, versus ‘passenger’ mutations, which are completely inert and just happened to arise along the way,” Boehm noted. “These initial findings suggest that biologically those categories are likely overly simplistic, that there’s actually a continuum of functional impact from inert to completely tumorigenic.”

While the team focused on cancer-associated genes and mutations for this study, they noted that sc-eVIP is gene-agnostic, highly scalable, and that using single cell RNA sequencing as a readout offers an efficient and generalizable approach to producing rich phenotypic data. They also calculated that it should be possible to thoroughly characterize most mutations with only 20 to a few hundred cells. Based on those numbers, it may be possible with sc-eVIP to generate a first-draft functional map of more than 2 million variants in approximately 200 known cancer genes with 71 million cells.

“If we can map where every cancer-associated variant fits on the continuum of impact in a variety of cancers and cell types,” Boehm said, “we’ll have a much better grasp of how the interplay of variants affects cell state, which in turn affects cancer development, growth, and response. Such knowledge would represent a true advance toward cancer precision medicine.”

Support for this study came from the National Cancer Institute, the National Human Genome Research Institute, the Mark Foundation for Cancer Research, the Howard Hughes Medical Institute, the Broadnext10 and Variant to Function programs and the Klarman Cell Observatory at the Broad Institute, and other sources.

Paper(s) cited:

Ursu O, Neal JT, et al. Massively parallel phenotyping of coding variants in cancer with Perturb-seq. Nature Biotechnology. Online January 20, 2022. DOI:10.1038/s41587-021-01160-7.

Blending machine learning and biology to predict cell fates and other changes
Greta Friar | Whitehead Institute
February 1, 2022

Imagine a ball thrown in the air: it curves up, then down, tracing an arc to a point on the ground some distance away. The path of the ball can be described with a simple mathematical equation, and if you know the equation, you can figure out where the ball is going to land. Biological systems tend to be harder to forecast, but Whitehead Institute Member Jonathan Weissman, postdoc in his lab Xiaojie Qiu, and collaborators at the University of Pittsburgh School of Medicine are working on making the path taken by cells as predictable as the arc of a ball. Rather than looking at how cells move through space, they are considering how cells change with time.

Weissman, Qiu, and collaborators Jianhua Xing, professor of computational and systems biology at the University of Pittsburgh School of Medicine, and Xing lab graduate student Yan Zhang have built a machine learning framework that can define the mathematical equations describing a cell’s trajectory from one state to another, such as its development from a stem cell into one of several different types of mature cell. The framework, called dynamo, can also be used to figure out the underlying mechanisms—the specific cocktail of gene activity—driving changes in the cell. Researchers could potentially use these insights to manipulate cells into taking one path instead of another, a common goal in biomedical research and regenerative medicine.  

The researchers describe dynamo in a paper published in the journal Cell on February 1. They explain the framework’s many analytical capabilities and use it to help understand mechanisms of human blood cell production, such as why one type of blood cell forms first (appears more rapidly than others).

“Our goal is to move towards a more quantitative version of single cell biology,” Qiu says. “We want to be able to map how a cell changes in relation to the interplay of regulatory genes as accurately as an astronomer can chart a planet’s movement in relation to gravity, and then we want to understand and be able to control those changes.”

How to map a cell’s future journey

 Dynamo uses data from many individual cells to come up with its equations. The main information that it requires is how the expression of different genes in a cell changes from moment to moment. The researchers estimate this by looking at changes in the amount of RNA over time, because RNA is a measurable product of gene expression. In the same way that knowing the starting position and velocity of a ball is necessary to understand the arc it will follow, researchers use the starting levels of RNAs and how those RNA levels are changing to predict the path of the cell. However, calculating changes in the amount of RNA from single cell sequencing data is challenging, because sequencing only measures RNA once. Researchers must then use clues like RNA-being-made at the time of sequencing and equations for RNA turnover to estimate how RNA levels were changing. Qiu and colleagues had to improve on previous methods in several ways in order to get clean enough measurements for dynamo to work. In particular, they used a recently developed experimental method that tags new RNA to distinguish it from old RNA, and combined this with sophisticated mathematical modeling, to overcome limitations of older estimation approaches.

The researchers’ next netbet sports betting appchallenge was to move from observing cells at discrete points in time to a continuous picture of how cells change. The difference is like switching from a map showing only landmarks to a map that shows the uninterrupted landscape, making it possible to trace the paths between landmarks. Led by Qiu and Zhang, the group used machine learning to reveal continuous functions that define these spaces. 

“There have been tremendous advances in methods for broadly profiling transcriptomes and other ‘omic’ information with single-cell resolution. The analytical tools for exploring these data, however, to date have been descriptive instead of predictive. With a continuous function, you can start to do things that weren’t possible with just accurately sampled cells at different states. For example, you can ask: if I changed one transcription factor, how is it going to change the expression of the other genes?” says Weissman, who is also a professor of biology at the Massachusetts Institute of Technology (MIT), a member of the Koch Institute for Integrative Biology Research at MIT, and an investigator of the Howard Hughes Medical Institute.

Dynamo can visualize these functions by turning them into math-based maps. The terrain of each map is determined by factors like the relative expression of key genes. A cell’s starting place on the map is determined by its current gene expression dynamics. Once you know where the cell starts, you can trace the path from that spot to find out where the cell will end up.

The researchers confirmed dynamo’s cell fate predictions by testing it against cloned cells–cells that share the same genetics and ancestry. One of two nearly-identical clones would be sequenced while the other clone went on to differentiate. Dynamo’s predictions for what would have happened to each sequenced cell matched what happened to its clone.

Moving from math to biological insight and non-trivial predictions

With a continuous function for a cell’s path over time determined, dynamo can then gain insights into the underlying biological mechanisms. Calculating derivatives of the function provides a wealth of information, for example by allowing researchers to determine the functional relationships between genes—whether and how they regulate each other. Calculating acceleration can show that a gene’s expression is growing or shrinking quickly even when its current level is low, and can be used to reveal which genes play key roles in determining a cell’s fate very early in the cell’s trajectory. The researchers tested their tools on blood cells, which have a large and branching differentiation tree. Together with blood cell expert Vijay Sankaran of Boston Children’s Hospital, the Dana-Farber Cancer Institute, Harvard Medical School, and Broad Institute of MIT and Harvard, and Eric Lander of Broad Institute, they found that dynamo accurately mapped blood cell differentiation and confirmed a recent finding that one type of blood cell, megakaryocytes, forms earlier than others. Dynamo also discovered the mechanism behind this early differentiation: the gene that drives megakaryocyte differentiation, FLI1, can self-activate, and because of this is present at relatively high levels early on in progenitor cells. This predisposes the progenitors to differentiate into megakaryocytes first.

The researchers hope that dynamo could not only help them understand how cells transition from one state to another, but also guide researchers in controlling this. To this end, dynamo includes tools to simulate how cells will change based on different manipulations, and a method to find the most efficient path from one cell state to another. These tools provide a powerful framework for researchers to predict how to optimally reprogram any cell type to another, a fundamental challenge in stem cell biology and regenerative medicine, as well as to generate hypotheses of how other genetic changes will alter cells’ fate. There are a variety of possible applications.

“If we devise a set of equations that can describe how genes within a cell regulate each other, we can computationally describe how to transform terminally differentiated cells into stem cells, or predict how a cancer cell may respond to various combinations of drugs that would be impractical to test experimentally,” Xing says.

Dynamo’s computational modeling can be used to predict the most likely path that a cell will follow when reprogramming one cell type to another, as well as the path that a cell will take after specific genetic manipulations. 

Dynamo moves beyond merely descriptive and statistical analyses of single cell sequencing data to derive a predictive theory of cell fate transitions. The dynamo toolset can provide deep insights into how cells change over time, hopefully making cells’ trajectories as predictable for researchers as the arc of a ball, and therefore also as easy to change as switching up a pitch.

School of Science announces 2022 Infinite Expansion Awards

Eight postdocs and research scientists within the School of Science honored for contributions to the Institute.

School of Science
January 28, 2022

The MIT School of Science has announced eight postdocs and research scientists as recipients of the 2022 Infinite Expansion Award.

The award, formerly known as the Infinite Kilometer Award, was created in 2012 to highlight extraordinary members of the MIT science community. The awardees are nominated not only for their research, but for going above and beyond in mentoring junior colleagues, participating in educational programs, and contributing to their departments, labs, and research centers, the school, and the Institute.

The 2022 School of Science Infinite Expansion winners are:

  • Héctor de Jesús-Cortés, a postdoc in the Picower Institute for Learning and Memory, nominated by professor and Department of Brain and Cognitive Sciences (BCS) head Michale Fee, professor and McGovern Institute for Brain Research Director Robert Desimone, professor and Picower Institute Director Li-Huei Tsai, professor and associate BCS head Laura Schulz, associate professor and associate BCS head Joshua McDermott, and professor and BCS Postdoc Officer Mark Bear for his “awe-inspiring commitment of time and energy to research, outreach, education, mentorship, and community;”
  • Harold Erbin, a postdoc in the Laboratory for Nuclear Science’s Institute for Artificial Intelligence and Fundamental Interactions (IAIFI), nominated by professor and IAIFI Director Jesse Thaler, associate professor and IAIFI Deputy Director Mike Williams, and associate professor and IAIFI Early Career and Equity Committee Chair Tracy Slatyer for “provid[ing] exemplary service on the IAIFI Early Career and Equity Committee” and being “actively involved in many other IAIFI community building efforts;”
  • Megan Hill, a postdoc in the Department of Chemistry, nominated by Professor Jeremiah Johnson for being an “outstanding scientist” who has “also made exceptional contributions to our community through her mentorship activities and participation in Women in Chemistry;”
  • Kevin Kuns, a postdoc in the Kavli Institute for Astrophysics and Space Research, nominated by Associate Professor Matthew Evans for “consistently go[ing] beyond expectations;”
  • Xingcheng Lin, a postdoc in the Department of Chemistry, nominated by Associate Professor Bin Zhang for being “very talented, extremely hardworking, and genuinely enthusiastic about science;”
  • Alexandra Pike, a postdoc in the Department of Biology, nominated by Professor Stephen Bell for “not only excel[ing] in the laboratory” but also being “an exemplary citizen in the biology department, contributing to teaching, community, and to improving diversity, equity, and inclusion in the department;”
  • Nora Shipp, a postdoc with the Kavli Institute for Astrophysics and Space Research, nominated by Assistant Professor Lina Necib for being “independent, efficient, with great leadership qualities” with “impeccable” research; and
  • Jakob Voigts, a research scientist in the McGovern Institute for Brain Research, nominated by Associate Professor Mark Harnett and his laboratory for “contribut[ing] to the growth and development of the lab and its members in numerous and irreplaceable ways.”

Winners are honored with a monetary award and will be celebrated with family, friends, and nominators at a later date, along with recipients of the Infinite Mile Award.

Life Sciences at MIT is unmatched

Paul Schimmel and family’s recent donation can match up to $25 million in additional funds to support life sciences at MIT

Julia Keller | MIT School of Science
January 18, 2022

This past August, the Department of Biology and the School of Science announced the creation of the Schimmel Family Program for Life Sciences at MIT as a result of the $50 million dollar donation from Professor Emeritus Paul Schimmel PhD ’66 and his family. Half of this support is designated to be matched with donations from other supporters of the department and the life sciences research enterprise. Now, with a recent donation from Institute Professor Phillip Sharp — a friend of the Schimmels and another lifelong supporter of biology — the matching funds, and opportunities for life sciences research at MIT, continue to be unlocked.

“The life sciences educational enterprise spreads across a dozen departments at MIT,” says Schimmel of the impact of this giving. “What makes the Biology Department and the life sciences at MIT so extraordinary is the singular ability to transfer knowledge and inventions to society for its benefit.”

Schimmel and Sharp, well-matched

In August 2021, the Schimmel family committed $50 million to support the life sciences at MIT. The family’s initial gift of $25 million established the Schimmel Family Program for Life Sciences and was matched with $25 million secured from other sources in support of the Department of Biology. The remaining $25 million from the Schimmel family now serves as matching funds for future gifts supporting the life sciences. To date, $7 million in new gifts from other donors have been committed toward this effort, eliciting an additional $7 million in matching funds from the Schimmel family.

Professor Sharp is among those supporters who have joined his former colleague and friend, Paul Schimmel.

“Paul and I taught together, shared an interest in RNA biology, and have remained close friends netbet online sports bettingsince his move to Scripps Institute,” says Sharp of his career-long friendship with Schimmel, who is the Ernst and Jean Hahn Professor at the Skaggs Institute for Chemical Biology at the Scripps Research Institute.

Though Schimmel formally left MIT for the Scripps Institute in 1997, he remained actively involved in supporting MIT’s research enterprise, with a particular focus on MIT graduate students, through his role on the Biology Visiting Committee.

Sharp and Schimmel agree that the success of graduate students remains key to the long-term sustainability of the life sciences at MIT. “We share a passion for supporting and engaging with the next generation of outstanding biologists, scientists, and leaders — well represented among MIT graduate students,” Sharp adds.

Sharp’s donation — matched by the Schimmel family gift — provides funds to establish fellowships for biology graduate students. “I hope others will join me in supporting the biology department and life sciences here at the Institute through the Schimmel family matching opportunity, as their investment will impact students and research for generations to come.”

Match point

“I am extremely grateful to Paul, his family, and Professor Phillip Sharp and Ann Sharp for their generosity and helping to inspire others to follow their lead,” says Biology Department Head and Praecis Professor of Biology Alan Grossman.

Grossman has worked with Sharp and the Schimmels for many years and is keenly aware of the important role these gifts play in a time of dwindling government investment in the sciences.

“As federal support for graduate training continues to wane over time, support from individuals like Paul, Phil, and others becomes crucial to the future of the life sciences,” Grossman says. “As COVID-19 has laid bare, there has never been a more critical need or better time to invest in basic science than right now.”

With $18 million remaining in available matching funds, Grossman says that he and partners throughout MIT continue to seek out others who wish to contribute to and participate in the Schimmel Family Program for Life Sciences. “Providing students with the resources they need to be successful in their education, research, and careers remains at the core of our mission,” says Grossman.

“Paul and the Schimmel family have provided other donors with an extraordinary opportunity to amplify the impact of their giving by leveraging their vision for the betterment of life sciences at the Institute,” says Biology Director of Development Daniel Griffin. “This initiative is resonating with people in and outside of the MIT community and we are all excited to see where it leads.”

Ensuring a bright future for Seattle
Ari Daniel | MIT Technology Review
January 10, 2022
In 1982, when Lynn Best ’69 joined the public utility Seattle City Light, her team faced an immediate challenge: evaluating the environmental, cultural, and financial impacts of its three dams generating electricity on the Skagit River in northwest Washington State. As acting director, she was able to persuade City Light to allow the environmental team to lead negotiations.

“Of course,” Best says, “the biggest issue was protecting the salmon on the river.” Four species of salmonids were known to spawn at different times and depths. The team relied upon science to determine optimal flow and ramping rates, placing the health of these species first, above power demand. Because the work was done in collaboration with state and federal agencies as well as local tribal communities, these partner groups signed on to the approach, which was the first time this had ever happened on a large hydro project. The fish responded immediately. The chum and pink salmon returned to historic abundances.

City Light’s efforts didn’t go unnoticed. In 1992, a senior member of the Federal Energy Regulatory Commission said that the utility’s Skagit River effort was the most comprehensive piece of work for the public good that he had ever seen. According to Best, if you dig hard enough, multiple science-based solutions to a problem emerge. And in her experience, at least one of these answers can benefit all the stakeholders. It’s a lesson she learned during her time as a biology major at MIT.

Of course, mistakes happen. Roughly a decade ago, the dam gates failed to open properly, draining water away from a number of salmon nests. This time, as environmental affairs director of Seattle City Light, Best and her now much larger team reported the violation to their partners. The tribal communities “didn’t advocate for any penalties, which is pretty unheard-of in those circumstances,” she says. It was a testament to how effective her cooperative approach had been.

In 2005, under Best’s leadership, Seattle City Light became the first utility in the nation to go carbon neutral. And more recently, during her time as the organization’s chief environmental officer, she championed an environmental justice program to protect and support diverse and economically disadvantaged communities.

Best retired from Seattle City Light in early 2020. She is now a commissioner on the Skagit Environmental Endowment Commission, dedicated to protecting the Upper Skagit environment on both sides of the border. She also spends time birdwatching and hiking. Her legacy of relationship building and environmental stewardship endures.