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van Belkum, A.

Publications and source records attributed to van Belkum, A..

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Colistin heteroresistance and the involvement of the PmrAB regulatory system in Acinetobacter baumannii

Multidrug-resistant Acinetobacter baumannii infection has recently emerged as a worldwide clinical problem and colistin is increasingly being used as last resort therapy. Despite its favorable bacterial killing, resistance and heteroresistance to colistin have been described. Mutations in the PmrAB regulatory pathway have been already associated with colistin resistance whereas the mechanisms for heteroresistance remain largely unknown. The purpose of the present study is to investigate the role of PmrAB in laboratory-selected mutants representative of global epidemic strains. During brief colistin exposure, colistin resistant and colistin heteroresistant mutants were selected in a one-step strategy. Population Analysis Profiling (PAP) was performed to confirm the suspected phenotype. Upon withdrawal of selective pressure, compensatory mutations were evaluated in another one-step strategy. A trans-complementation assay was designed to delineate the involvement of the PmrAB regulatory system using qPCR and PAP. Mutations in the PmrAB regulatory pathway were associated with colistin resistance and colistin heteroresistance as well. The transcomplementation assay provides a proof for the role played by changes in the PmrAB regulatory pathway. The level of colistin resistance is correlated to the level of expression of pmrC. The resistance phenotype was partially restored since the complemented strain became heteroresistant. This report shows the role of different mutations in the PmrAB regulatory pathway and warns on the development of colistin heteroresistance that could be present but not easily detected with routine testing.

microbiology

A fast and agnostic method for bacterial genome-wide association studies: bridging the gap between kmers and genetic events

MotivationGenome-wide association study (GWAS) methods applied to bacterial genomes have shown promising results for genetic marker discovery or fine-assessment of marker effect. Recently, alignment-free methods based on kmer composition have proven their ability to explore the accessory genome. However, they lead to redundant descriptions and results which are hard to interpret.\n\nMethodsHere, we introduce DBGWAS, an extended kmer-based GWAS method producing interpretable genetic variants associated with pheno-types. Relying on compacted De Bruijn graphs (cDBG), our method gathers cDBG nodes identified by the association model into subgraphs defined from their neighbourhood in the initial cDBG. DBGWAS is fast, alignment-free and only requires a set of contigs and phenotypes. It produces annotated subgraphs representing local polymorphisms as well as mobile genetic elements (MGE) and offers a graphical framework to interpret GWAS results.\n\nResultsWe validated our method using antibiotic resistance phenotypes for three bacterial species. DBGWAS recovered known resistance determinants such as mutations in core genes in Mycobacterium tuberculosis and genes acquired by horizontal transfer in Staphylococcus aureus and Pseudomonas aeruginosa - along with their MGE context. It also enabled us to formulate new hypotheses involving genetic variants not yet described in the antibiotic resistance literature.\n\nConclusionOur novel method proved its efficiency to retrieve any type of phenotype-associated genetic variant without prior knowledge. All experiments were computed in less than two hours and produced a compact set of meaningful subgraphs, thereby outperforming other GWAS approaches and facilitating the interpretation of the results.\n\nAvailabilityOpen-source tool available at https://gitlab.com/leoisl/dbgwas

bioinformatics