Genetic engineering

Subterms

    Latest story

    125 Shares199 Views

    Search algorithm reveals nearly 200 new kinds of CRISPR systems

    by

    Microbial sequence databases contain a wealth of information about enzymes and other molecules that could be adapted for biotechnology. But these databases have grown so large in recent years that they’ve become difficult to search efficiently for enzymes of interest.

    Now, scientists at the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and Harvard, and the National Center for Biotechnology Information (NCBI) at the National Institutes of Health have developed a new search algorithm that has identified 188 kinds of new rare CRISPR systems in bacterial genomes, encompassing thousands of individual systems. The work appears today in Science.

    The algorithm, which comes from the lab of pioneering CRISPR researcher Professor Feng Zhang, uses big-data clustering approaches to rapidly search massive amounts of genomic data. The team used their algorithm, called Fast Locality-Sensitive Hashing-based clustering (FLSHclust) to mine three major public databases that contain data from a wide range of unusual bacteria, including ones found in coal mines, breweries, Antarctic lakes, and dog saliva. The scientists found a surprising number and diversity of CRISPR systems, including ones that could make edits to DNA in human cells, others that can target RNA, and many with a variety of other functions.

    The new systems could potentially be harnessed to edit mammalian cells with fewer off-target effects than current Cas9 systems. They could also one day be used as diagnostics or serve as molecular records of activity inside cells.

    The researchers say their search highlights an unprecedented level of diversity and flexibility of CRISPR and that there are likely many more rare systems yet to be discovered as databases continue to grow.

    “Biodiversity is such a treasure trove, and as we continue to sequence more genomes and metagenomic samples, there is a growing need for better tools, like FLSHclust, to search that sequence space to find the molecular gems,” says Zhang, a co-senior author on the study and the James and Patricia Poitras Professor of Neuroscience at MIT with joint appointments in the departments of Brain and Cognitive Sciences and Biological Engineering. Zhang is also an investigator at the McGovern Institute for Brain Research at MIT, a core institute member at the Broad, and an investigator at the Howard Hughes Medical Institute. Eugene Koonin, a distinguished investigator at the NCBI, is co-senior author on the study as well.

    Searching for CRISPR

    CRISPR, which stands for clustered regularly interspaced short palindromic repeats, is a bacterial defense system that has been engineered into many tools for genome editing and diagnostics.

    To mine databases of protein and nucleic acid sequences for novel CRISPR systems, the researchers developed an algorithm based on an approach borrowed from the big data community. This technique, called locality-sensitive hashing, clusters together objects that are similar but not exactly identical. Using this approach allowed the team to probe billions of protein and DNA sequences — from the NCBI, its Whole Genome Shotgun database, and the Joint Genome Institute — in weeks, whereas previous methods that look for identical objects would have taken months. They designed their algorithm to look for genes associated with CRISPR.

    “This new algorithm allows us to parse through data in a time frame that’s short enough that we can actually recover results and make biological hypotheses,” says Soumya Kannan PhD ’23, who is a co-first author on the study. Kannan was a graduate student in Zhang’s lab when the study began and is currently a postdoc and Junior Fellow at Harvard University. Han Altae-Tran PhD ’23, a graduate student in Zhang’s lab during the study and currently a postdoc at the University of Washington, was the study’s other co-first author.

    “This is a testament to what you can do when you improve on the methods for exploration and use as much data as possible,” says Altae-Tran. “It’s really exciting to be able to improve the scale at which we search.”

    New systems

    In their analysis, Altae-Tran, Kannan, and their colleagues noticed that the thousands of CRISPR systems they found fell into a few existing and many new categories. They studied several of the new systems in greater detail in the lab.

    They found several new variants of known Type I CRISPR systems, which use a guide RNA that is 32 base pairs long rather than the 20-nucleotide guide of Cas9. Because of their longer guide RNAs, these Type I systems could potentially be used to develop more precise gene-editing technology that is less prone to off-target editing. Zhang’s team showed that two of these systems could make short edits in the DNA of human cells. And because these Type I systems are similar in size to CRISPR-Cas9, they could likely be delivered to cells in animals or humans using the same gene-delivery technologies being used today for CRISPR.

    One of the Type I systems also showed “collateral activity” — broad degradation of nucleic acids after the CRISPR protein binds its target. Scientists have used similar systems to make infectious disease diagnostics such as SHERLOCK, a tool capable of rapidly sensing a single molecule of DNA or RNA. Zhang’s team thinks the new systems could be adapted for diagnostic technologies as well.

    The researchers also uncovered new mechanisms of action for some Type IV CRISPR systems, and a Type VII system that precisely targets RNA, which could potentially be used in RNA editing. Other systems could potentially be used as recording tools — a molecular document of when a gene was expressed — or as sensors of specific activity in a living cell.

    Mining data

    The scientists say their algorithm could aid in the search for other biochemical systems. “This search algorithm could be used by anyone who wants to work with these large databases for studying how proteins evolve or discovering new genes,” Altae-Tran says.

    The researchers add that their findings illustrate not only how diverse CRISPR systems are, but also that most are rare and only found in unusual bacteria. “Some of these microbial systems were exclusively found in water from coal mines,” Kannan says. “If someone hadn’t been interested in that, we may never have seen those systems. Broadening our sampling diversity is really important to continue expanding the diversity of what we can discover.”

    This work was supported by the Howard Hughes Medical Institute; the K. Lisa Yang and Hock E. Tan Molecular Therapeutics Center at MIT; Broad Institute Programmable Therapeutics Gift Donors; The Pershing Square Foundation, William Ackman and Neri Oxman; James and Patricia Poitras; BT Charitable Foundation; Asness Family Foundation; Kenneth C. Griffin; the Phillips family; David Cheng; and Robert Metcalfe. More

    More stories

    • 100 Shares189 Views

      in Data Management & Statistics

      New leadership at MIT’s Center for Biomedical Innovation

      by

      As it continues in its mission to improve global health through the development and implementation of biomedical innovation, the MIT Center for Biomedical Innovation (CBI) today announced changes to its leadership team: Stacy Springs has been named executive director, and Professor Richard Braatz has joined as the center’s new associate faculty director.

      The change in leadership comes at a time of rapid development in new therapeutic modalities, growing concern over global access to biologic medicines and healthy food, and widespread interest in applying computational tools and multi-disciplinary approaches to address long-standing biomedical challenges.

      “This marks an exciting new chapter for the CBI,” says faculty director Anthony J. Sinskey, professor of biology, who cofounded CBI in 2005. “As I look back at almost 20 years of CBI history, I see an exponential growth in our activities, educational offerings, and impact.”

      The center’s collaborative research model accelerates innovation in biotechnology and biomedical research, drawing on the expertise of faculty and researchers in MIT’s schools of Engineering and Science, the MIT Schwarzman College of Computing, and the MIT Sloan School of Management.

      Springs steps into the role of executive director having previously served as senior director of programs for CBI and as executive director of CBI’s Biomanufacturing Program and its Consortium on Adventitious Agent Contamination in Biomanufacturing (CAACB). She succeeds Gigi Hirsch, who founded the NEW Drug Development ParadIGmS (NEWDIGS) Initiative at CBI in 2009. Hirsch and NEWDIGS have now moved to Tufts Medical Center, establishing a headquarters at the new Center for Biomedical System Design within the Institute for Clinical Research and Health Policy Studies there.

      Braatz, a chemical engineer whose work is informed by mathematical modeling and computational techniques, conducts research in process data analytics, design, and control of advanced manufacturing systems.

      “It’s been great to interact with faculty from across the Institute who have complementary expertise,” says Braatz, the Edwin R. Gilliland Professor in the Department of Chemical Engineering. “Participating in CBI’s workshops has led to fruitful partnerships with companies in tackling industry-wide challenges.”

      CBI is housed under the Institute for Data Systems and Society and, specifically, the Sociotechnical Systems Research Center in the MIT Schwarzman College of Computing. CBI is home to two biomanufacturing consortia: the CAACB and the Biomanufacturing Consortium (BioMAN). Through these precompetitive collaborations, CBI researchers work with biomanufacturers and regulators to advance shared interests in biomanufacturing.

      In addition, CBI researchers are engaged in several sponsored research programs focused on integrated continuous biomanufacturing capabilities for monoclonal antibodies and vaccines, analytical technologies to measure quality and safety attributes of a variety of biologics, including gene and cell therapies, and rapid-cycle development of virus-like particle vaccines for SARS-CoV-2.

      In another significant initiative, CBI researchers are applying data analytics strategies to biomanufacturing problems. “In our smart data analytics project, we are creating new decision support tools and algorithms for biomanufacturing process control and plant-level decision-making. Further, we are leveraging machine learning and natural language processing to improve post-market surveillance studies,” says Springs.

      CBI is also working on advanced manufacturing for cell and gene therapies, among other new modalities, and is a part of the Singapore-MIT Alliance for Research and Technology – Critical Analytics for Manufacturing Personalized-Medicine (SMART CAMP). SMART CAMP is an international research effort focused on developing the analytical tools and biological understanding of critical quality attributes that will enable the manufacture and delivery of improved cell therapies to patients.

      “This is a crucial time for biomanufacturing and for innovation across the health-care value chain. The collaborative efforts of MIT researchers and consortia members will drive fundamental discovery and inform much-needed progress in industry,” says MIT Vice President for Research Maria Zuber.

      “CBI has a track record of engaging with health-care ecosystem challenges. I am confident that under the new leadership, it will continue to inspire MIT, the United States, and the entire world to improve the health of all people,” adds Daniel Huttenlocher, dean of the MIT Schwarzman College of Computing. More

    • 125 Shares189 Views

      in Data Management & Statistics

      New CRISPR-based map ties every human gene to its function

      by

      The Human Genome Project was an ambitious initiative to sequence every piece of human DNA. The project drew together collaborators from research institutions around the world, including MIT’s Whitehead Institute for Biomedical Research, and was finally completed in 2003. Now, over two decades later, MIT Professor Jonathan Weissman and colleagues have gone beyond the sequence to present the first comprehensive functional map of genes that are expressed in human cells. The data from this project, published online June 9 in Cell, ties each gene to its job in the cell, and is the culmination of years of collaboration on the single-cell sequencing method Perturb-seq.

      The data are available for other scientists to use. “It’s a big resource in the way the human genome is a big resource, in that you can go in and do discovery-based research,” says Weissman, who is also a member of the Whitehead Institute and an investigator with the Howard Hughes Medical Institute. “Rather than defining ahead of time what biology you’re going to be looking at, you have this map of the genotype-phenotype relationships and you can go in and screen the database without having to do any experiments.”

      The screen allowed the researchers to delve into diverse biological questions. They used it to explore the cellular effects of genes with unknown functions, to investigate the response of mitochondria to stress, and to screen for genes that cause chromosomes to be lost or gained, a phenotype that has proved difficult to study in the past. “I think this dataset is going to enable all sorts of analyses that we haven’t even thought up yet by people who come from other parts of biology, and suddenly they just have this available to draw on,” says former Weissman Lab postdoc Tom Norman, a co-senior author of the paper.

      Pioneering Perturb-seq

      The project takes advantage of the Perturb-seq approach that makes it possible to follow the impact of turning on or off genes with unprecedented depth. This method was first published in 2016 by a group of researchers including Weissman and fellow MIT professor Aviv Regev, but could only be used on small sets of genes and at great expense.

      The massive Perturb-seq map was made possible by foundational work from Joseph Replogle, an MD-PhD student in Weissman’s lab and co-first author of the present paper. Replogle, in collaboration with Norman, who now leads a lab at Memorial Sloan Kettering Cancer Center; Britt Adamson, an assistant professor in the Department of Molecular Biology at Princeton University; and a group at 10x Genomics, set out to create a new version of Perturb-seq that could be scaled up. The researchers published a proof-of-concept paper in Nature Biotechnology in 2020. 

      The Perturb-seq method uses CRISPR-Cas9 genome editing to introduce genetic changes into cells, and then uses single-cell RNA sequencing to capture information about the RNAs that are expressed resulting from a given genetic change. Because RNAs control all aspects of how cells behave, this method can help decode the many cellular effects of genetic changes.

      Since their initial proof-of-concept paper, Weissman, Regev, and others have used this sequencing method on smaller scales. For example, the researchers used Perturb-seq in 2021 to explore how human and viral genes interact over the course of an infection with HCMV, a common herpesvirus.

      In the new study, Replogle and collaborators including Reuben Saunders, a graduate student in Weissman’s lab and co-first author of the paper, scaled up the method to the entire genome. Using human blood cancer cell lines as well noncancerous cells derived from the retina, he performed Perturb-seq across more than 2.5 million cells, and used the data to build a comprehensive map tying genotypes to phenotypes.

      Delving into the data

      Upon completing the screen, the researchers decided to put their new dataset to use and examine a few biological questions. “The advantage of Perturb-seq is it lets you get a big dataset in an unbiased way,” says Tom Norman. “No one knows entirely what the limits are of what you can get out of that kind of dataset. Now, the question is, what do you actually do with it?”

      The first, most obvious application was to look into genes with unknown functions. Because the screen also read out phenotypes of many known genes, the researchers could use the data to compare unknown genes to known ones and look for similar transcriptional outcomes, which could suggest the gene products worked together as part of a larger complex.

      The mutation of one gene called C7orf26 in particular stood out. Researchers noticed that genes whose removal led to a similar phenotype were part of a protein complex called Integrator that played a role in creating small nuclear RNAs. The Integrator complex is made up of many smaller subunits — previous studies had suggested 14 individual proteins — and the researchers were able to confirm that C7orf26 made up a 15th component of the complex.

      They also discovered that the 15 subunits worked together in smaller modules to perform specific functions within the Integrator complex. “Absent this thousand-foot-high view of the situation, it was not so clear that these different modules were so functionally distinct,” says Saunders.

      Another perk of Perturb-seq is that because the assay focuses on single cells, the researchers could use the data to look at more complex phenotypes that become muddied when they are studied together with data from other cells. “We often take all the cells where ‘gene X’ is knocked down and average them together to look at how they changed,” Weissman says. “But sometimes when you knock down a gene, different cells that are losing that same gene behave differently, and that behavior may be missed by the average.”

      The researchers found that a subset of genes whose removal led to different outcomes from cell to cell were responsible for chromosome segregation. Their removal was causing cells to lose a chromosome or pick up an extra one, a condition known as aneuploidy. “You couldn’t predict what the transcriptional response to losing this gene was because it depended on the secondary effect of what chromosome you gained or lost,” Weissman says. “We realized we could then turn this around and create this composite phenotype looking for signatures of chromosomes being gained and lost. In this way, we’ve done the first genome-wide screen for factors that are required for the correct segregation of DNA.”

      “I think the aneuploidy study is the most interesting application of this data so far,” Norman says. “It captures a phenotype that you can only get using a single-cell readout. You can’t go after it any other way.”

      The researchers also used their dataset to study how mitochondria responded to stress. Mitochondria, which evolved from free-living bacteria, carry 13 genes in their genomes. Within the nuclear DNA, around 1,000 genes are somehow related to mitochondrial function. “People have been interested for a long time in how nuclear and mitochondrial DNA are coordinated and regulated in different cellular conditions, especially when a cell is stressed,” Replogle says.

      The researchers found that when they perturbed different mitochondria-related genes, the nuclear genome responded similarly to many different genetic changes. However, the mitochondrial genome responses were much more variable. 

      “There’s still an open question of why mitochondria still have their own DNA,” said Replogle. “A big-picture takeaway from our work is that one benefit of having a separate mitochondrial genome might be having localized or very specific genetic regulation in response to different stressors.”

      “If you have one mitochondria that’s broken, and another one that is broken in a different way, those mitochondria could be responding differentially,” Weissman says.

      In the future, the researchers hope to use Perturb-seq on different types of cells besides the cancer cell line they started in. They also hope to continue to explore their map of gene functions, and hope others will do the same. “This really is the culmination of many years of work by the authors and other collaborators, and I’m really pleased to see it continue to succeed and expand,” says Norman. More