What is it about?
We describe the development and validation of a novel machine learning-based program, which designs strain-specific CRISPR guide RNAs that can be utilized to modify complex consortia. As a proof of concept, we applied the program to two novel applications: the isolation of specific microbes from consortia and the removal of specific microbes from consortia at the strain level. Using ssCRISPR, we showed a simple plasmid transformation workflow to isolate individual microbes from a consortium. This technique shortens and simplifies microbial isolation techniques, which currently involve complex tailored media and serial culture systems, and allows for the discovery of microbes with novel characteristics. Next, we demonstrated a novel strain-specific antimicrobial by packaging ssCRISPR-designed CRISPR cassettes in liposomes. These liposomes can fuse with and deliver the CRISPR payload to microbes in diverse ecosystems, including intestines, blood, lungs, and soil. This new technique has vast implications in designing strain-specific antimicrobials and combating the growing concern of antibiotic- and bacteriocide-resistant microbes.
Photo by Kelly Sikkema on Unsplash
Why is it important?
Modifying microbial consortia with strain-specificity is critical for maintaining stable and healthy microbiota. However, consortium engineering tools with strain-specificity have yet to be developed. Here, we describe the development and validation of a novel computational program, ssCRISPR, which designs strain-specific CRISPR guide RNAs (gRNAs) that can be utilized to modify complex consortia. ssCRISPR gRNAs can be used in diverse applications, including improving the health of livestock, plants, and humans, identifying and isolating microbes with unique characteristics, investigating the roles of microbial communities, and tailoring microbiota for improved functions.
Read the Original
This page is a summary of: Computational design of CRISPR guide RNAs to enable strain-specific control of microbial consortia, Proceedings of the National Academy of Sciences, December 2022, Proceedings of the National Academy of Sciences, DOI: 10.1073/pnas.2213154120.
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