Research Roundup: August 28, 2020

Welcome to the August 28, 2020 installment of Research Roundup, a recurring snapshot of recent studies published by scientists at the Broad Institute and their collaborators.

SHERLOCK diagnostic validated in Sierra Leone and Nigeria

In Nature Communications, an international team led by postdoctoral associate Kayla Barnes, Anna Lachenauer, institute member Pardis Sabeti of the Infectious Disease and Microbiome Program (IDMP), and collaborators in the US, Nigeria, and Sierra Leone validate the CRISPR-based SHERLOCK diagnostic on patient samples for Ebola and Lassa fever in settings with limited infrastructure. The diagnostic requires only a simple heat block and basic supplies, could be used on saliva or urine, and incorporates the HUDSON lab protocol to inactive the virus and eliminate the need for RNA extraction. The team also developed a mobile app called HandLens, spearheaded by Andres Colubri, that can read paper strip SHERLOCK results. Learn more in a Broad news story and video.

SHERLOCK SARS-CoV-2 test validated in Thai study

Rapid, accurate, low-cost, point-of-care diagnostics are crucial tools for doctors, scientists, and epidemiologists working to manage COVID-19 outbreaks, especially in regions with limited resources. A Thai research team collaborating with core institute member Feng Zhang's group benchmarked a SHERLOCK-based SARS-CoV-2 diagnostic against a gold-standard quantitative PCR assay using more than 500 samples collected at a large medical center in Bangkok, Thailand. The researchers found the CRISPR-Cas13-based assay to be 100 percent specific and between 96 and 100 percent sensitive across a range of viral loads, down to 42 RNA copies per reaction. The Thai team is now using SHERLOCK in their hospital for screening patients. Learn more in Nature Biomedical Engineering.

SARS-CoV-2 genomes show how superspreading events shaped the first wave of COVID-19 in Boston

In a medRxiv preprint, Jacob Lemieux, Katherine Siddle, Bronwyn MacInnis in the Sabeti lab, and many colleagues used genomic epidemiology to track the introduction and spread of SARS-CoV-2 across the first wave of the epidemic in the Boston area. The team estimates that the virus entered the region at least 80 separate times, mostly from Europe and elsewhere in the US. One of those introductions was linked to a superspreading event that led to massive community transmission across the city and to other states and countries. Read more on the Broadminded and Terra blogs, including posts from Sabeti lab research associates and Stanley Center project managers who contributed to the research. See coverage in the New York Times, Washington Post, WBUR, and Boston Globe.

Many animal species are vulnerable to SARS-CoV-2 infection

An international team of scientists, including many at the Broad, used genomic and protein structure analysis to compare the ACE2 cellular receptor (which SARS-CoV-2 uses to gain entry into cells) in 410 vertebrate species, including 252 mammals. They found that many mammals could be susceptible to the virus; some wildlife and endangered species among them are at high risk for infection. These findings may help researchers identify intermediate SARS-CoV-2 hosts and help control future outbreaks in humans and animals. Read more in the Proceedings of the National Academy of Sciences, a news story, and a tweetorial from vertebrate genomics director Elinor Karlsson.

Aging cells reorganize their genome structure to fend off cancer

Sarah Johnstone, Alejandro Reyes, institute member Martin Aryee, institute member and Epigenomics Program director Bradley Bernstein, and colleagues have revealed previously unknown changes that occur in aging cells: the genome's entire three-dimensional structure is reorganized over time as the cells divide. Surprisingly, the team found that these changes help prevent the development of cancer. Cancer cells undergo this reorganization as well, but adapt other mechanisms to overcome the tumor-suppressive effects. The findings have potential implications for preventing and treating a wide variety of tumor types. Read more in Cell and a Broad story.

Deep learning tells good blood from bad

Over time, banked blood cells undergo changes that impair their health and ability to carry oxygen, rendering them unusable for transfusions. Experts rate blood quality by examining blood samples under a microscope, a time-consuming and often subjective task. Minh Doan, institute scientist and Imaging Platform senior director Anne Carpenter, and collaborators developed a method that uses imaging and deep learning to rapidly and automatically identify differences between new and old red blood cells. The work lays the groundwork for a faster and more accurate way for blood banks to assess blood quality. Read more in PNAS and a Broad story.

Cancer cell screening gets in the MIX

A new method for studying cancer cell lines combines the efficiency of pooled cell screening with the high resolution of single-cell RNA sequencing. The method was developed by a team including associate director of data science in the Broad’s Cancer Program James McFarland, Cancer Dependency Map Project (DepMap) research scientist Brenton Paolella, DepMap associate director Francisca Vazquez, associate member Andrew Aguirre at Harvard Medical School and Dana-Farber Cancer Institute, and Cancer Program scientific advisor Aviad Tsherniak. MIX-Seq relies on cells’ own genetic fingerprints to distinguish individual cells' transcriptional profiles. By measuring cellular responses after exposure to a drug or genetic tweak, the method can reveal how drugs work and pave the way for new cancer therapies. Read more in Nature Communications, a Broad news story, and a Cancer Data Science Blog post.

Genetic background matters in disease risk

Some people with high-risk genetic variants for a disease never develop it, and postdoctoral scholar Akl Fahed, computational scientist Minxian Wang, Julian Homburger (Color), Amit Khera of Massachusetts General Hospital and associate director of Broad’s Cardiovascular Disease Initiative, and colleagues, in partnership with IBM Research and Color, have discovered a possible reason why. They found that a person’s genetic background — quantified using polygenic scores — influences the risk of heart disease, breast cancer, and colorectal cancer in individuals with high-risk single-gene variants for these diseases, in some cases bringing risk closer to the population average. The findings suggest that looking for both high-risk variants and polygenic background will enable more accurate risk estimation. Read more in Nature Communications and a Broad story.

Examining the COVID experience

Recognizing the need to quickly collect information about COVID-19-related symptoms, health behaviors, and demographics, early in the pandemic William Allen, Feng Zhang, Xihong Lin, and colleagues launched How We Feel, a mobile- and web-based survey application. In Nature Human Behavior, they present an analysis of more than 500,000 users' responses between April and May 2020. Their findings provide a unique window into many aspects of users' experiences related to COVID-19, including risk factors, symptom history, and motivations for testing.

Tapping into the bacterial/viral arms race

The defenses bacteria use to keep viruses at bay have yielded some of the most fundamental tools in biotechnology. But the antiviral mechanisms we know about may be far outnumbered by the ones we don't. In Science, a team led at the Broad by Linyi Gao and Feng Zhang report the discovery of 29 new defense mechanisms, harbored by a wide variety of bacteria and archaea. Their findings, drawn from a computational study of all bacterial and archaeal genomes deposited in GenBank (more than 250,000 in all) and subsequent lab experiments, hint at a number of enzymatic functions that scientists might harness as molecular tools in the future.

Regulator register

RNA-binding proteins (RBPs) regulate gene expression, but determining the effects of individual RBPs is difficult. A team led by MIT scientists Konstantin Krismer, Yi Wen Kong, Ian Cannell, and senior associate member Michael Yaffe in the Cell Circuits Program developed Transite, a computational approach that analyzes changes in RNA stability and degradation to systematically infer RBPs’ effects. They applied Transite to RNA expression data from human patients with non-small-cell lung cancer and highlighted known RBP regulators of DNA damage response and a new modulator of chemotherapeutic resistance, hnRNPC. Described in Cell Reports, Transite adds value to publicly available gene expression datasets.

What makes for a successful FMT?

Transplantation of gut microbes from healthy donors (aka fecal microbiota transplantation, or FMT) is emerging as a promising approach for treating patients with Crohn's disease (CD). In Gastroenterology, a team led by Lingjia Kong, Harry Sokol (Sorbonne Université), and core institute member and IDMP co-director Ramnik Xavier published the first metagenomic sequencing-based study of FMT engraftment dynamics in CD patients. They found that the engraftment of particular microbial species and strains correlated with clinical remission, that donors' microbes often end up co-existing alongside patients' (as opposed to replacing them completely), and that it may be possible to match donors and recipients based on metagenomic microbial signatures.

Targeting viral vectors to specific neuronal subtypes

In theory, researchers can use regulatory elements to target viral vectors to specific cell types for gene therapy, but in the brain’s cerebral cortex these tools are currently limited to broad classes of neurons. To overcome this limitation, research associates Douglas Vormstein-Schneider and Jessica Lin, Jordane Dimidschstein, senior group leader in the Stanley Center for Psychiatric Research, and colleagues identified several novel enhancers that target distinct neuronal subtypes, including parvalbumin (PV) and vasoactive intestinal peptide (VIP) cortical interneurons. The PV-specific enhancer allowed for selective targeting and manipulation of these neurons across species in mice, non-human primates, and humans. The approach is generalizable and could be useful for therapeutics development. Learn more in Nature Neuroscience.

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