Computational design of CRISPR guide RNAs to enable strain-specific control of microbial consortia

Author:

Rottinghaus Austin G.1ORCID,Vo Steven2,Moon Tae Seok12ORCID

Affiliation:

1. Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130

2. Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, MO 63110

Abstract

Microbes naturally coexist in complex, multistrain communities. However, extracting individual microbes from and specifically manipulating the composition of these consortia remain challenging. The sequence-specific nature of CRISPR guide RNAs can be leveraged to accurately differentiate microorganisms and facilitate the creation of tools that can achieve these tasks. We developed a computational program, ssCRISPR, which designs strain-specific CRISPR guide RNA sequences with user-specified target strains, protected strains, and guide RNA properties. We experimentally verify the accuracy of the strain specificity predictions in both Escherichia coli and Pseudomonas spp. and show that up to three nucleotide mismatches are often required to ensure perfect specificity. To demonstrate the functionality of ssCRISPR, we apply computationally designed CRISPR-Cas9 guide RNAs to two applications: the purification of specific microbes through one- and two-plasmid transformation workflows and the targeted removal of specific microbes using DNA-loaded liposomes. For strain purification, we utilize gRNAs designed to target and kill all microbes in a consortium except the specific microbe to be isolated. For strain elimination, we utilize gRNAs designed to target only the unwanted microbe while protecting all other strains in the community. ssCRISPR will be of use in diverse microbiota engineering applications.

Funder

HHS | National Institutes of Health

DOD | USN | Office of Naval Research

U.S. Department of Agriculture

National Science Foundation

U.S. Environmental Protection Agency

Publisher

Proceedings of the National Academy of Sciences

Subject

Multidisciplinary

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