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Denamur, E.

Publications and source records attributed to Denamur, E..

2 recordsLinked to original sources

PlaScope: a targeted approach to assess the plasmidome of Escherichia coli strains

Plasmid prediction may be of great interest when studying bacteria such as Enterobacteriaceae. Indeed many resistance and virulence genes are located on such replicons and can have major impact in terms of pathogenicity and spreading capacities. Beyond strains outbreak, plasmids outbreaks have been reported especially for some extended-spectrum beta-lactamase or carbapenemase producing Enterobacteriaceae. Several tools are now available to explore the \"plasmidome\" from whole-genome sequence data, with many interesting and various approaches. However recent benchmarks have highlighted that none of them succeed to combine high sensitivity and specificity. With this in mind we developed PlaScope, a targeted approach to recover plasmidic sequences in Escherichia coli. Based on Centrifuge, a metagenomic classifier, and a custom database containing complete sequences of chromosomes and plasmids from various curated databases, it performs a classification of contigs from an assembly according to their predicted location. Compared to other plasmid classifiers, Plasflow and cBar, it achieves better recall (0.87), specificity (0.99), precision (0.96) and accuracy (0.98) on a dataset of 70 genomes containing plasmids. Finally we tested our method on a dataset of E. coli strains exhibiting an elevated rate of extended-spectrum beta-lactamase coding gene chromosomal integration, and we were able to identify 20/21 of these events. Moreover virulence genes and operons predicted locations were also in agreement with the literature. Similar approaches could also be developed for other well-characterized bacteria such as Klebsiella pneumoniae.\n\nData summaryO_LIAll the genomes were downloaded from the National Center for Biotechnology Information Sequence Read Archive and Genome database (Supplementary table 1 and 2).\nC_LIO_LIThe source code of PlaScope is available on Github (https://github.com/GuilhemRoyer/PlaScope).\nC_LI\n\nImportancePlasmid exploration could be of great interest since these replicons are pivotal in the adaptation of bacteria to their environment. They are involved in the exchange of many genes within and between species, with a significant impact on antibiotic resistance and virulence in particular. However, plasmid characterization has been a laborious task for many years, requiring complex conjugation or electroporation manipulations for example. With the advent of whole genome sequencing techniques, access to these sequences is now potentially easier provided that appropriate tools are available. Many softwares have been developed to explore the plasmidome of a large variety of bacteria, but they rarely managed to combine sensitivity and specificity. Here, we focus on a single species, E. coli, and we use the many data available to overcome this problem. With our tool called PlaScope, we achieve high performance compared with two other classifiers, Plasflow and cBar, and we demonstrate the utility of such an approach to determine the location of virulence or resistance genes. We think that PlaScope could be very useful in the analysis of specific and well-known bacteria.

bioinformatics

Phenotype prediction in an Escherichia coli strain panel

Understanding how genetic variation contributes to phenotypic differences is a fundamental question in biology. Here, we set to predict fitness defects of an individual using mechanistic models of the impact of genetic variants combined with prior knowledge of gene function. We assembled a diverse panel of 696 Escherichia coli strains for which we obtained genomes and measured growth phenotypes in 214 conditions. We integrated variant effect predictors to derive gene-level probabilities of loss of function for every gene across strains. We combined these probabilities with information on conditional gene essentiality in the reference K-12 strain to predict the strains growth defects, providing significant predictions for up to 38% of tested conditions. The putative causal variants were validated in complementation assays highlighting commonly perturbed pathways in evolution for the emergence of growth phenotypes. Altogether, our work illustrates the power of integrating high-throughput gene function assays to predict the phenotypes of individuals.\n\nHighlightsO_LIAssembled a reference panel of E. coli strains\nC_LIO_LIGenotyped and high-throughput phenotyped the E. coli reference strain panel\nC_LIO_LIReliably predicted the impact of genetic variants in up to 38% of tested conditions\nC_LIO_LIHighlighted common genetic pathways for the emergence of deleterious phenotypes\nC_LI

systems biology