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.

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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.


The past two decades have witnessed rapid advances in engineering individual microbial strains to produce bioproducts. However, engineering microbial consortia has been relatively slow. I propose to develop microbiota as a biomanufacturing host. Specifically, we can develop the soil microbial community itself as a huge bioreactor (https://www.sciencedirect.com/science/article/abs/pii/S0167779922002281). I envision that the soil or the entire planet will be viewed as a huge bioreactor to capture greenhouse gases, store critical nutrients for diverse organisms such as crops, and convert wastes into value-added chemicals and materials. Ultimately, we will provide a generalizable system that enables us to understand and engineer microbial consortium’s interaction and metabolism at diverse temporal and spatial scales to address global problems, including the climate crisis, food inequality, waste issue, and sustainable bioproduction. As the first step toward achieving this ambitious goal, we have developed machine learning-based microbiota engineering tools that are useful to manipulate microbiota at a single strain level (this PNAS article). We will expand and apply these tools to real-world environments (e.g., soil) to specifically kill harmful members of soil (e.g., plant pathogens) and facilitate the isolation of beneficial members of soil (e.g., nitrogen-fixing bacteria, plant-health-promoting microbes, photosynthetic bacteria, plastic-eating microbes, and toxic chemical-degrading bacteria). These beneficial microbes, which I call “probiotics” for soil and its community’s health, can be deployed into “bad” soil to increase its nitrogen and carbon contents, remove toxic compounds and plastic waste, and enhance crop productivity (https://www.sciencedirect.com/science/article/abs/pii/S0167779922002281).

Tae Seok Moon
Washington University in Saint Louis

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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