(Harvard University) Researchers from Harvard University and the Broad Institute prove they can engineer botulinum toxin proteins (called proteases) to find new targets with high selectivity, a critical advance toward potential new treatments for everything from neuroregeneration to cytokine storm.
(Picower Institute at MIT) A new computational approach for analyzing complex datasets shows that as disease progresses, neurons and astrocytes lose the ability to maintain homeostasis. The "Geomic" approach can be applied to other diseases, authors say.
(Massachusetts Institute of Technology) MIT researchers have published the most comprehensive map yet of noncoding DNA circuitry, helping elucidate candidate mechanisms for 30,000 disease-associated regions.
“Science will always be at the forefront of my administration."
(Massachusetts Institute of Technology) A CRISPR-based diagnostic for the SARS-Cov-2 virus can produce results in less than an hour with similar accuracy as the standard PCR test now used. Development of the Covid-19 test was led by researchers at MIT and the Broad Institute of MIT and Harvard.
The story behind ArsenalBio begins with Sean Parker’s Institute for Cancer Immunotherapy.Founded in 2016, the Institute has been instrumental in providing a space for the top researchers into cancer across different fields to collaborate and communicate on the latest breakthroughs in settings that range from formal meetings to informal retreats.It was at one of these informal retreats that luminaries like: Dr. Bradley Bernstein, a professor of pathology and researcher at the Broad Institute; W. Nicholas Haining, vice president of discovery oncology at Merck Research Laboratories; Dr. Alexander Mason, an associate professor of immunology at the University of California San Francisco; and E. John Wherry, a professor of systems immunology at the University of Pennsylvania, began to talk about the current state of the art in cancer diagnostics and therapies and the technologies powering cell-based therapies to potentially cure cancer.“I look at this as a tour de force of a combination of bringing academics together who typically would start separate companies and get them working together with a dream team management team,” says Beth Seidenberg, the founder of Westlake Village BioPartners and an investor in ArsenalBio.Indeed, the management team is just as impressive as the researchers behind the project.Kleiner Perkins founding partner, Brooke Byers recruited Dr. Ken Drazan to serve as a consultant to the company as it was getitng off the ground Drazan, now the company’s chief executive, was the former President of the cancer research and diagnostics startup Grail has served as an executive and founder at a number of healthcare startups and large medical companies.
August 27, 2019--Santa Cruz, CA -- Seagate Technology (NASDAQ: STX), a world leader in data storage solutions, and the Genomics Institute and Baskin School of Engineering at UC Santa Cruz announced today that they have entered into a multi-year, joint research and development agreement to accelerate genomics data analysis using computational storage technology.The initial focus of this collaboration will be on accelerating the analysis of the Human Cell Atlas (HCA), a scientist-led initiative that has emerged as a collaborative federation of diverse experts to map every type of cell in the healthy human body as a resource for studies of health and disease.The UC Santa Cruz Genomics Institute has been working with specialists in biology, computation, and medicine -- including those at the European Bioinformatics Institute and the Broad Institute of Harvard and MIT -- to formulate, fund, and jointly build the Data Coordination Platform for the Human Cell Atlas.Existing sequencing techniques combine millions of cells to generate a single 'bulk' measurement.This technique is rapidly translating from research into the clinic, where reducing the analysis and exploration time could ultimately lead to the acceleration of precision medicine at scale."Single-cell sequencing is poised to revolutionize cancer treatment, as it helps convey a detailed picture of the tumor microenvironment, which facilitates selection of combination, targeted, and precision therapies," Stuart explained.
"We need better strategies to unravel how complex biology works, especially in diseases like cancer where multiple biological events can occur to transform normal cell into diseased ones," says senior author Timothy Lu, an electrical engineer and computer scientist at MIT and the Broad Institute.This technology can give us deeper insights into what signals go up and down over time to drive disease development."With DOMINO, we can write DNA to change the information encoded into different positions, and then read out this information on the fly, like a read-write head in a computer hard drive" says first author Fahim Farzadfard, a postdoctoral fellow and former PhD student in Lu's laboratory who developed the DOMINO concept."We can also combine and layer multiple DNA reading and writing events together to build various forms of logic, such as 'AND' and 'OR' operations, which can then be used to create more complex memory and computing operations in living cells."The guide RNA in DOMINO operator can be designed in a way that it can bind to its target sequence only after a certain mutation is first introduced into that sequence by a previous event.The team also demonstrated that these DNA signatures can be coupled with a fluorescent reporter, so that DNA writing/editing results in higher fluorescence signal.
"He has already taken CRISPR technology to the next level with an exciting RNA editing approach that targets dementia, and we look forward to many more health-changing innovations from him in the years to come.As a bioengineer, Hsu aims to understand and manipulate the genetic circuits that control brain and immune cell function for the next generation of gene and cell therapies.In 2018, he published a paper in the journal Cell describing his lab's development of a tool that targets RNA rather than DNA, and used it to correct a tau protein imbalance in cells from a dementia patient, restoring them to healthy levels.Working with Feng Zhang at the Broad Institute of MIT and Harvard and the McGovern Institute for Brain Research at MIT, Hsu previously contributed to the early development of CRISPR-Cas9 technologies for efficient and precise genome engineering in eukaryotic cells.These profiles offer a glimpse into what the face of technology looks like today as well as in the future."Learn more about this year's honorees on the MIT Technology Review website here and in the July/August print magazine, which hits newsstands worldwide on July 2.
New Rochelle, NY, June 24, 2019--SHERLOCK technology is a new CRISPR-based platform that is rapid and portable and enables detection and quantitation of plant genes to support a variety of agricultural applications.Additional advantages, including the ability to process crude plant extracts with minimal nucleic acid sample preparation required are described in a research article published in The CRISPR Journal, a new peer-reviewed journal from Mary Ann Liebert, Inc., publishers.Click here to read the full-text article free on The CRISPR Journal website through July 24, 2019.Feng Zhang, from the Broad Institute of MIT and Harvard (Cambridge, MA) and Massachusetts Institute of Technology (Cambridge), and coauthors Omar Abudayyeh, Jonathan Gootenberg, and Max Kellner, from the Broad Institute, MIT, and Harvard Medical School (Boston, MA) present the recently developed nucleic acid detection system called SHERLOCK in the article entitled "Nucleic Acid Detection of Plant Genes Using CRISPR-Cas13."The paper describes how the refined CRISPR-based tool SHERLOCK was applied for the first time in plants.SHERLOCK has the potential to be an important tool in agriculture for the rapid detection of pathogens or pests and in plant breeding.
The Journal is dedicated to validating and publishing outstanding research and commentary on all aspects of CRISPR and gene editing, including CRISPR biology, technology, and genome editing, and commentary and debate of key policy, regulatory, and ethical issues affecting the field.The Journal, led by Editor-in-Chief Rodolphe Barrangou, PhD (North Carolina State University) and Executive Editor Dr. Kevin Davies, is published bimonthly in print and online.For full-text copies of articles or to arrange interviews with Dr. Barrangou, Dr. Davies, authors, or members of the editorial board, contact Kathryn Ryan at the Publisher.Writing in The CRISPR Journal, researchers from Feng Zhang's laboratory at the Broad Institute and co-founders of Sherlock Biosciences, have repurposed their recently described SHERLOCK CRISPR-Cas13 detection system for agricultural applications.The SHERLOCKv2 platform combines same-sample multiplexing, lateral flow visual readouts, quantitation, and amplification of signal detection.This modified tool was used to quantify glyphosate resistance genes in a soybean mixture and detected multiple herbicide resistance and native plant genes within a single reaction.
"DNA microscopy is an entirely new way of visualizing cells that captures both spatial and genetic information simultaneously from a single specimen," says first author Joshua Weinstein, a postdoctoral associate at the Broad Institute."It will allow us to see how genetically unique cells -- those comprising the immune system, cancer, or the gut, for instance -- interact with one another and give rise to complex multicellular life."Aviv Regev, core institute member and director of the Klarman Cell Observatory at the Broad Institute and professor of biology at MIT, and Feng Zhang, core institute member of the Broad Institute, investigator at the McGovern Institute for Brain Research at MIT, and the James and Patricia Poitras Professor of Neuroscience at MIT, are co-authors.The evolution of biological imagingIn recent decades, researchers have developed tools to collect molecular information from tissue samples, data that cannot be captured by either light or electron microscopes.However, attempts to couple this molecular information with spatial data -- to see how it is naturally arranged in a sample -- are often machinery-intensive, with limited scalability.
CAMBRIDGE, MA -- Most antibiotics work by interfering with critical functions such as DNA replication or construction of the bacterial cell wall.However, these mechanisms represent only part of the full picture of how antibiotics act.In a new study of antibiotic action, MIT researchers developed a new machine-learning approach to discover an additional mechanism that helps some antibiotics kill bacteria.Exploiting this mechanism could help researchers to discover new drugs that could be used along with antibiotics to enhance their killing ability, the researchers say.Jason Yang, an IMES research scientist, is the lead author of the paper, which appears in the May 9 issue of Cell.Other authors include Sarah Wright, a recent MIT MEng recipient; Meagan Hamblin, a former Broad Institute research technician; Miguel Alcantar, an MIT graduate student; Allison Lopatkin, an IMES postdoc; Douglas McCloskey and Lars Schrubbers of the Novo Nordisk Foundation Center for Biosustainability; Sangeeta Satish and Amir Nili, both recent graduates of Boston University; Bernhard Palsson, a professor of bioengineering at the University of California at San Diego; and Graham Walker, an MIT professor of biology.
The results allowed the team to identify distinctive cellular pathways that are affected in neurons and other types of brain cells."This study provides, in my view, the very first map for going after all of the molecular processes that are altered in Alzheimer's disease in every single cell type that we can now reliably characterize," says Manolis Kellis, a professor of computer science and a member of MIT's Computer Science and Artificial Intelligence Laboratory and of the Broad Institute of MIT and Harvard.Kellis and Li-Huei Tsai, director of MIT's Picower Institute for Learning and Memory, are the senior authors of the study, which appears in the May 1 online edition of Nature.The researchers analyzed postmortem brain samples from 24 people who exhibited high levels of Alzheimer's disease pathology and 24 people of similar age who did not have these signs of disease.All of the subjects were part of the Religious Orders Study, a longitudinal study of aging and Alzheimer's disease.The MIT team performed single-cell RNA sequencing on about 80,000 cells from these subjects.
Elaborate molecular networks inside living cells enable them to sense and process many signals from the environment to perform desired cellular functions.Synthetic biologists have been able to reconstruct and mimic simpler forms of this cellular signal processing.But now, a new toolset powered by self-assembling molecules and predictive modeling will allow researchers to construct the complex computation and signal processing found in eukaryotic organisms, including human cells.The work by Assistant Professor Ahmad 'Mo' Khalil (BME), Assistant Professor Caleb Bashor of Rice University, BME graduate student Nikit Patel, and other colleagues at MIT, Harvard, the Broad Institute and Brandeis University, has been published in Science.The type of combinatorial signal processing that they've been able to engineer synthetically is what cells naturally and elegantly do to enable intricate tasks, like those in embryonic development and differentiation."By taking a common principle that we know exists in nature, the ability for regulatory molecules to collaborate and form higher-order assemblies, you can program cells to execute very difficult computational and combinatorial problems," says Khalil.
HOUSTON -- (April 18, 2019) -- Synthetic biologists have added high-precision analog-to-digital signal processing to the genetic circuitry of living cells.The research, described online today in the journal Science, dramatically expands the chemical, physical and environmental cues engineers can use to prompt programmed responses from engineered organisms.Using a biochemical process called cooperative assembly, Caleb Bashor of Rice University, Ahmad "Mo" Khalil of Boston University (BU) and colleagues from MIT, Harvard, the Broad Institute and Brandeis University engineered genetic circuits that were able to both decode frequency-dependent signals and conduct dynamic signal filtering.Synthetically engineering cooperative assembly allowed the researchers to perform the type of combinatorial signal processing that cells naturally and elegantly do to accomplish intricate tasks, like those in embryonic development and differentiation."This work is a tour de force of synthetic biology that addresses a major question in how cells process information at the DNA level," said Tom Ellis, Reader in Synthetic Genome Engineering in the department of bioengineering at Imperial College London, who was not involved in the study.By recreating the way human cells process information at the DNA level, but in a simple yeast cell model with synthetic parts, they have been able to recreate complex signaling from first principles.
Cancer cells adapt to potentially fatal mutations and other molecular malfunctions by adjusting one or more other genes' activity, in the process becoming dependent on those genes for their survival and growth.Reporting in Nature, researchers led by members of the Cancer Dependency Map (DepMap) project at the Broad Institute of MIT and Harvard and the Dana-Farber Cancer Institute describe one such vulnerability shared by a large subset of colon, gastric, endometrial, and ovarian cancer cell lines.This predisposition to rampant mutation is seen only in cancer cells, and results from the breakdown of one of the cells' means for repairing damaged DNA (a mechanism called mismatch repair).About 15 percent of colon cancers, 22 percent of gastric cancers, 20 to 30 percent of endometrial cancers, and 12 percent of ovarian cancers diagnosed every year lack mismatch repair and bear the hallmarks of MSI."We hope our work will encourage the development of WRN inhibitors for MSI tumors," said co-senior author and DepMap associate director Francisca Vazquez of the Broad, who, along with co-first authors Edmond Chan of the Broad Cancer Program and Dana-Farber and Tsukasa Shibue of the Broad, and Broad associate member and Dana-Farber gastrointestinal oncologist Adam Bass, led the study.Seeking ways to address the remaining half, the research team wondered whether the loss of mismatch repair activity that leads to MSI might promote unique genetic dependencies within tumor cells.
Innovation Endeavors, the fund backed by Google’s Eric Schmidt, has for years now been taking a novel approach to working on difficult and still-evolving problems like cybersecurity and food shortages: it sets up incubators that bring together different stakeholders to identify, develop and fund ways of tackling these issues.Today, Innovation unveiled the latest of these: a new project called Deep Life, which aims to identify tricky problems in the world of life sciences, and figure out how to use computer science — specifically innovations in areas like machine learning — to help fix them.Target areas will include therapeutics, diagnostics and industrial life sciences in biology, chemistry and other fields; and Deep Life will provide startups with “investment capital across all stages of growth; access to experts, including scientists and decision-makers; proprietary data sets; early feedback on product; identification of market needs; initial customers and potential partners.In exchange for their startup support, Deep Life member organizations gain access to emerging technologies and hard-to-find talent,” according to a blog post introducing the new project penned by Innovation Endeavors’ co-founder Dror Berman.Deep Life will unveil the first fruits of its efforts during a pitch day on May 30, and it’s accepting applications for places as of right now.Alternately called an “ecosystem” and “collective”, Deep Life — in the words of Berman — is “taking inspiration” from Farm2050 and Team8, the two other incubators that the firm helped create in past years.
A new technique developed by scientists at the Broad Institute of MIT and Harvard gives an unprecedented view of the cellular organization of tissues.Known as Slide-seq, the method uses genetic sequencing to draw detailed, three-dimensional maps of tissues, revealing not only what cell types are present, but where they are located and what they are doing.Because it does not require specialized imaging equipment, the technique can be employed by scientists across diverse fields of biology, genetics, and medicine who want to look at the cellular structure of tissues, or to observe where particular genes are active in a tissue, an organ, or even whole organisms.Such a platform offers unparalleled views of the cellular structure of tissues, the roles played by genes in different tissues, and the effects of injury or other perturbations on tissue, giving researchers rich maps of tissue function that have never before been possible.In the 19th century, neurobiologist Santiago Ramón y Cajal thrilled the scientific world with his detailed drawings of human tissue, demonstrating that the brain is made up of individual cells.In recent years, RNA sequencing has enabled scientists to identify which cell types are present in a tissue and which genes are turned on across the genome, but not where those cells are precisely located.
With the announcement today that Mammoth Biosciences has received the exclusive license from the University of California, Berkeley to the new CRISPR protein Cas14, the company now has the last piece of its diagnostics toolkit in place.Cas14 is a newly discovered protein from the lab of Jennifer Doudna, a pioneer in gene-editing research and a member of the first research team to identify and unlock the power of CRISPR technology.Doudna and Mammoth Biosciences co-founder Lucas Harrington were part of the team of researchers to identify the new Cas14 protein, which can identify single-stranded DNA.The journal Science published their findings in October 2018.“With the addition of this protein that is DNA binding and target single strands, it really means we can target any nucleic acid,” says Mammoth chief executive Trevor Martin .“It’s an extension of the toolbox.”