Scientists at the McGovern Institute for Brain Research at MIT, the Broad Institute of MIT and Harvard, and the National Center for Biotechnology Information have developed a new search algorithm called FLSHclust that allows for more efficient searching of microbial sequence databases. The algorithm identified 188 new rare CRISPR systems in bacterial genomes, revealing a high level of diversity and flexibility in CRISPR. These new systems have potential applications in gene editing, diagnostics, and molecular recording. The researchers also emphasize the importance of expanding sampling diversity in order to discover more rare systems.
New Search Algorithm Identifies 188 Rare CRISPR Systems
A team of scientists at MIT, Harvard, and the National Institutes of Health have developed a new search algorithm called FLSHclust that can efficiently search enormous microbial sequence databases for enzymes of interest. The algorithm uses big-data clustering approaches to rapidly mine genomic data and has identified 188 new rare CRISPR systems in bacterial genomes. These systems have a wide range of functions, including the potential to edit mammalian cells with fewer off-target effects, serve as diagnostics, or act as molecular records of cellular activity.
This breakthrough highlights the unprecedented diversity and flexibility of CRISPR and suggests that there are likely many more rare systems yet to be discovered as databases continue to grow. The algorithm, developed by Professor Feng Zhang, allows for faster data analysis and biological hypothesis generation, enabling researchers to make significant progress in exploring the vast sequence space of microbial databases.
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