Comprehensive detection of genes causing a phenotype using phenotype sequencing and pathway analysis

Genomic sequencing-based mutational enrichment analysis identifies motility genes in a genetically intractable gut microbe

A major roadblock to understanding how microbes in the gastrointestinal tract colonize and influence the physiology of their hosts is our inability to genetically manipulate new bacterial species and experimentally assess the function of their genes. We describe the application of population-based genomic sequencing after chemical mutagenesis to map bacterial genes responsible for motility in Exiguobacterium acetylicum, a representative intestinal Firmicutes bacterium that is intractable to molecular genetic manipulation. We derived strong associations between mutations in 57 E. acetylicum genes and impaired motility. Surprisingly, less than half of these genes were annotated as motility-related based on sequence homologies. We confirmed the genetic link between individual mutations and loss of motility for several of these genes by performing a large-scale analysis of spontaneous suppressor mutations. In the process, we reannotated genes belonging to a broad family of diguanylate cyclases and phosphodiesterases to highlight their specific role in motility and assigned functions to uncharacterized genes. Furthermore, we generated isogenic strains that allowed us to establish that Exiguobacterium motility is important for the colonization of its vertebrate host. These results indicate that genetic dissection of a complex trait, functional annotation of new genes, and the generation of mutant strains to define the role of genes in complex environments can be accomplished in bacteria without the development of species-specific molecular genetic tools.

An ultra-dense library resource for rapid deconvolution of mutations that cause phenotypes in Escherichia coli

With the wide availability of whole-genome sequencing (WGS), genetic mapping has become the rate-limiting step, inhibiting unbiased forward genetics in even the most tractable model organisms. We introduce a rapid deconvolution resource and method for untagged causative mutations after mutagenesis, screens, and WGS in Escherichia coli. We created Deconvoluter—ordered libraries with selectable insertions every 50 kb in the E. coli genome. The Deconvoluter method uses these for replacement of untagged mutations in the genome using a phage-P1-based gene-replacement strategy. We validate the Deconvoluter resource by deconvolution of 17 of 17 phenotype-altering mutations from a screen of N-ethyl-N-nitrosourea-induced mutants. The Deconvoluter resource permits rapid unbiased screens and gene/function identification and will enable exploration of functions of essential genes and undiscovered genes/sites/alleles not represented in existing deletion collections. This resource for unbiased forward-genetic screens with mapping-by-sequencing (‘forward genomics’) demonstrates a strategy that could similarly enable rapid screens in many other microbes.

Linking gene expression to phenotypes via pathway information

Establishing robust links among gene expression, pathways and phenotypes is critical for understanding diseases and developing treatments. In recent years there have been many efforts to develop the computational means to traverse from genes to gene expression, model pathways and classify phenotypes. Numerous ontologies and other controlled vocabularies have been developed, as well as computational methods to combine and mine these data sets and establish connections. Here we discuss these efforts and identify areas of future work that could lead to a better integration of genes, pathways and phenotypes to provide insights into the mechanisms under which gene mutations affect expression and pathways and how these effects are manifested onto the phenotype.