CRISPR-Associated Transposase for Targeted Mutagenesis in Diverse Proteobacteria

CRISPR相关转座酶用于多种变形菌的靶向诱变

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Abstract

Genome editing tools, through the disruption of an organism's native genetic material or the introduction of non-native DNA, facilitate functional investigations to link genotypes to phenotypes. Transposons have been instrumental genetic tools in microbiology, enabling genome-wide, randomized disruption of genes and insertions of new genetic elements. Due to this randomness, identifying and isolating particular transposon mutants (i.e., those with modifications at a genetic locus of interest) can be laborious, often requiring one to sift through hundreds or thousands of mutants. Programmable, site-specific targeting of transposons became possible with recently described CRISPR-associated transposase (CASTs) systems, allowing the streamlined recovery of desired mutants in a single step. Like other CRISPR-derived systems, CASTs can be programmed by guide-RNA that is transcribed from short DNA sequence(s). Here, we describe a CAST system and demonstrate its function in bacteria from three classes of Proteobacteria. A dual plasmid strategy is demonstrated: (i) CAST genes are expressed from a broad-host-range replicative plasmid and (ii) guide-RNA and transposon are encoded on a high-copy, suicidal pUC plasmid. Using our CAST system, single-gene disruptions were performed with on-target efficiencies approaching 100% in Beta- and Gammaproteobacteria (Burkholderia thailandensis and Pseudomonas putida, respectively). We also report a peak efficiency of 45% in the Alphaproteobacterium Agrobacterium fabrum. In B. thailandensis, we performed simultaneous co-integration of transposons at two different target sites, demonstrating CAST's utility in multilocus strategies. The CAST system is also capable of high-efficiency large transposon insertion totaling over 11 kbp in all three bacteria tested. Lastly, the dual plasmid system allowed for iterative transposon mutagenesis in all three bacteria without loss of efficiency. Given these iterative capabilities and large payload capacity, this system will be helpful for genome engineering experiments across several fields of research.

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