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Abstract
A major challenge in genomics is the knowledge gap between sequence and its encoded function. Gain-of-function methods based on gene overexpression are attractive avenues for phenotype-based functional screens, but are not easily applied in high-throughput across many experimental conditions. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a method that uses random DNA barcodes to greatly increase experimental throughput. As a demonstration of this approach, we construct a Dub-seq library with Escherichia coli genomic DNA, performed 155 genome-wide fitness assays in 52 experimental conditions, and identified overexpression phenotypes for 813 genes. We show that Dub-seq data is reproducible, accurately recapitulates known biology, and identifies hundreds of novel gain-of-function phenotypes for E. coli genes, a subset of which we verified with assays of individual strains. Dub-seq provides complementary information to loss-of-function approaches and will facilitate rapid and systematic functional characterization of microbial genomes.
Highlights
A major challenge in genomics is the knowledge gap between sequence and its encoded function
We show that Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq) yields gene fitness data that is consistent with known biology and provides novel gene function insights
Dub-seq couples shotgun cloning of random DNA fragments with competitive fitness assays to assess the phenotypic importance of the genes contained on those fragments in a single tube assay
Summary
A major challenge in genomics is the knowledge gap between sequence and its encoded function. A number of large-scale approaches based on loss-of-function genetics have been developed for microorganisms including geneknockout libraries[5,6,7,8,9], recombineering based methods[10,11], transposon mutagenesis coupled to next-generation sequencing (TnSeq)[12,13], and CRISPR interference (CRISPRi)[14]. These strategies all rely on measuring the phenotypic consequences of removing a gene from a microorganism and inferring protein function based on these phenotypes. These loss-of-function approaches suffer some limitations: only CRISPRi is effective for interrogating essential genes under multiple conditions, it is challenging to identify phenotypes for genes with redundant functions using single mutants, and these approaches require some degree of genetic tractability in the target microorganism
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