Enterococcus faecalis (EF) is both a common commensal of the human gastrointestinal tract (GI) and a leading cause of hospital acquired infections1. Systemic infections with multi-drug resistant enterococci occur subsequent to GI colonization2. Preventing colonization by multi-drug resistant EF could therefore be a valuable approach to limiting infection. However, little is known about mechanisms EF uses to colonize and compete for stable gastrointestinal niches. Pheromone-responsive, conjugative plasmids encoding bacteriocins are common among enterococcal strains3, and could modulate niche competition among enterococci or between enterococci and the intestinal microbiota. We developed a model of mouse gut colonization with EF without disrupting the microbiota, to evaluate the role of the conjugative plasmid pPD1 expressing bacteriocin 214 on enterococcal colonization. Here we show that EF harboring pPD1 replaces indigenous enterococci and outcompetes EF lacking pPD1. Furthermore, in the intestine, pPD1 is transferred to other EF strains by conjugation, enhancing their survival. Moreover, colonization with an EF strain carrying a conjugation-defective pPD1 mutant resulted in clearance of vancomycin-resistant enterococci, without plasmid transfer. Therefore bacteriocin expression by commensal bacteria can influence niche-competition in the GI tract, and bacteriocins, delivered by commensals that occupy a precise intestinal bacterial niche, may be an effective therapeutic approach to specifically eliminate intestinal colonization by multi-drug resistant bacteria, without profound disruption of the indigenous microbiota.

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Background Recently, pioneering expression quantitative trait loci (eQTL) studies on single cell RNA sequencing (scRNA-seq) data have revealed new and cell-specific regulatory single nucleotide variants (SNVs). Here, we present an alternative QTL-related approach applicable to transcribed SNV loci from scRNA-seq data: scReQTL. ScReQTL uses Variant Allele Fraction (VAFRNA) at expressed biallelic loci, and corelates it to gene expression from the corresponding cell. Results Our approach employs the advantage that, when estimated from multiple cells, VAFRNA can be used to assess effects of SNVs in a single sample or individual. In this setting scReQTL operates in the context of identical genotypes, where it is likely to capture RNA-mediated genetic interactions with cell-specific and transient effects. Applying scReQTL on scRNA-seq data generated on the 10 × Genomics Chromium platform using 26,640 mesenchymal cells derived from adipose tissue obtained from three healthy female donors, we identified 1272 unique scReQTLs. ScReQTLs common between individuals or cell types were consistent in terms of the directionality of the relationship and the effect size. Comparative assessment with eQTLs from bulk sequencing data showed that scReQTL analysis identifies a distinct set of SNV-gene correlations, that are substantially enriched in known gene-gene interactions and significant genome-wide association studies (GWAS) loci. Conclusion ScReQTL is relevant to the rapidly growing source of scRNA-seq data and can be applied to outline SNVs potentially contributing to cell type-specific and/or dynamic genetic interactions from an individual scRNA-seq dataset. Availability:https://github.com/HorvathLab/NGS/tree/master/scReQTL

Motivation By testing for associations between DNA genotypes and gene expression levels, expression quantitative trait locus (eQTL) analyses have been instrumental in understanding how thousands of single nucleotide variants (SNVs) may affect gene expression. As compared to DNA genotypes, RNA genetic variation represents a phenotypic trait that reflects the actual allele content of the studied system. RNA genetic variation at expressed SNV loci can be estimated using the proportion of alleles bearing the variant nucleotide (variant allele fraction, VAFRNA). VAFRNA is a continuous measure which allows for precise allele quantitation in loci where the RNA alleles do not scale with the genotype count. We describe a method to correlate VAFRNA with gene expression and assess its ability to identify genetically regulated expression solely from RNA-sequencing (RNA-seq) datasets. Results We introduce ReQTL, an eQTL modification which substitutes the DNA allele count for the variant allele fraction at expressed SNV loci in the transcriptome (VAFRNA). We exemplify the method on sets of RNA-seq data from human tissues obtained though the Genotype-Tissue Expression (GTEx) project and demonstrate that ReQTL analyses are computationally feasible and can identify a subset of expressed eQTL loci. Availability and implementation A toolkit to perform ReQTL analyses is available at https://github.com/HorvathLab/ReQTL. Supplementary information Supplementary data are available at Bioinformatics online.