Abstract
To fully exploit the microbial genome resources, a high-throughput experimental platform is needed to associate genes with phenotypes at the genome level. We present here a novel method that enables investigation of the cellular consequences of repressing individual transcripts based on the CRISPR interference (CRISPRi) pooled screening in bacteria. We identify rules for guide RNA library design to handle the unique structure of prokaryotic genomes by tiling screening and construct an E. coli genome-scale guide RNA library (~60,000 members) accordingly. We show that CRISPRi outperforms transposon sequencing, the benchmark method in the microbial functional genomics field, when similar library sizes are used or gene length is short. This tool is also effective for mapping phenotypes to non-coding RNAs (ncRNAs), as elucidated by a comprehensive tRNA-fitness map constructed here. Our results establish CRISPRi pooled screening as a powerful tool for mapping complex prokaryotic genetic networks in a precise and high-throughput manner.
Highlights
To fully exploit the microbial genome resources, a high-throughput experimental platform is needed to associate genes with phenotypes at the genome level
With current CRISPR interference (CRISPRi) single guide RNA (sgRNA) library design guidelines in eukaryotic cells, a target site is selected around the transcription start site (TSS)[23]
Considering that the CRISPR-Cas system is broadly applicable in many prokaryotic organisms[13,14,15,16,17,18], we expect that our method will open up the possibility to screen for genephenotype associations or genetic interactions across many different environments and species based on either genome-wide or focused sgRNA libraries, especially for relatively rarely explored non-coding RNAs (ncRNAs)
Summary
To fully exploit the microbial genome resources, a high-throughput experimental platform is needed to associate genes with phenotypes at the genome level. We first perform a tiling screening where we test the activity of 2,281 sgRNAs targeting 44 genes with known phenotypes Based on this experiment, we indirectly (at the functional level) learn the activity positioning of sgRNAs in coding regions where CRISPRi maximally changes the expression of endogenous genes, as well as rules for a minimal sgRNA number per gene to maintain reliable hit gene calling. We indirectly (at the functional level) learn the activity positioning of sgRNAs in coding regions where CRISPRi maximally changes the expression of endogenous genes, as well as rules for a minimal sgRNA number per gene to maintain reliable hit gene calling This results in an algorithm to further design a genome-scale sgRNA library targeting each protein-coding or RNA-coding gene in the E. coli genome. These experiments demonstrate that CRISPRi screening platform represents a transformative tool for defining gene function in a cost-effective and high-throughput manner for potentially any prokaryotic organism
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