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Coque, T.

Publications and source records attributed to Coque, T..

3 recordsLinked to original sources

Tracking the emergence and dissemination of a blaNDM-23 Gene in a Multi-Drug Resistance Plasmid of Klebsiella pneumoniae

ObjectivesSince the discovery of blaNDM-1, NDM beta-lactamases have become one of the most widespread carbapenemases worldwide. To date, 28 different NDM variants have been reported but some, such as blaNDM-23, have not been characterized in detail yet. Here, we describe the emergence of a novel blaNDM-23 allele from a blaNDM-1 ancestor and the multidrug resistant plasmid that has disseminated it through a K. pneumoniae ST407 clone in several Spanish hospitals. MethodsBetween 2016 and 2019, 1,972 isolates were collected in an epidemiological survey for ESBL-producing Klebsiella pneumoniae in the Comunitat Valenciana (Spain). Three carbapenem resistant strains failed to be detected by CPE screening tests. These isolates carried a blaNDM-23 gene. To characterize this gene, its emergence, and dissemination, we performed antimicrobial susceptibility tests, hybrid sequencing with Illumina and Nanopore technologies, and phylogenetic analyses. ResultsThe MICs of the blaNDM-23 variant were identical to those of the blaNDM-1. The blaNDM-23 variant was found in 14 isolates in a 97 Kb non-mobilizable, multidrug-resistant plasmid carrying 19 resistance genes for 9 different antimicrobial families. In this plasmid, the blaNDM-23 gene is located in the variable region of a complex class-1 integron with a singular genetic environment. The short genetic distance between blaNDM-23-producing isolates reflects a 5-year-long clonal dispersion involving several hospitals and interregional spread. ConclusionsWe have characterized the genomic and epidemiological contexts in the emergence and community spread of a new blaNDM-23 allele in an MDR-plasmid of Klebsiella pneumoniae. TweetGenomic, epidemiologic and phylogenetic analyses of the emergence of a new NDM allele provide information on the rapid changes underlying the spread of antimicrobial resistance genes and strains in Klebsiella pneumoniae. ImportanceAt a time when antimicrobial resistance has become one of the biggest concerns worldwide, the emergence of novel alleles and extremely drug-resistant plasmids are a threat to public health worldwide. More so when they produce carbapenem resistance in one of the most problematic pathogens in clinical settings, such as Klebsiella pneumoniae. Here, we have used genomic epidemiology to describe the emergence of a novel NDM-23 allele and identify it in a MDR plasmid that has been disseminated through a K. pneumoniae ST407 clone in several hospitals in a Spanish region. By means of bioinformatic and phylogenetic analyses, we have been able to trace the evolutionary and epidemiological route of the new allele, the hosting plasmid, and the strain that carried both of them from Pakistan to Spain. A better understanding of the NDM-producing K. pneumoniae populations and its plasmids has made evident the spread of this clone through the region, enhancing the importance of genomic surveillance in the control of antimicrobial resistance.

microbiology↗

Multi-Hierarchical Dynamics of Antimicrobial Resistance Simulated in a Nested Membrane Computing Model

Membrane Computing is a bio-inspired computing paradigm, whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested \"membrane-surrounded entities\" able to divide, propagate and die, be transferred into other membranes, exchange informative material according to flexible rules, mutate and being selected by external agents. This allows the exploration of hierarchical interactive dynamics resulting from the probabilistic interaction of genes (phenotypes), clones, species, hosts, environments, and antibiotic challenges. Our model facilitates analysis of several aspects of the rules that govern the multi-level evolutionary biology of antibiotic resistance. We examine a number of selected landscapes where we predict the effects of different rates of patient flow from hospital to the community and viceversa, cross-transmission rates between patients with bacterial propagules of different sizes, the proportion of patients treated with antibiotics, antibiotics and dosing in opening spaces in the microbiota where resistant phenotypes multiply. We can also evaluate the selective strength of some drugs and the influence of the time-0 resistance composition of the species and bacterial clones in the evolution of resistance phenotypes. In summary, we provide case studies analyzing the hierarchical dynamics of antibiotic resistance using a novel computing model with reciprocity within and between levels of biological organization, a type of approach that may be expanded in the multi-level analysis of complex microbial landscapes.

microbiology↗

Prediction of the intestinal resistome by a novel 3D-based method

The intestinal microbiota is considered to be a major reservoir of antibiotic resistance determinants (ARDs) that could potentially be transferred to bacterial pathogens. Yet, this question remains hypothetical because of the difficulty to identify ARDs from intestinal bacteria. Here, we developed and validated a new annotation method (called pairwise comparative modelling, PCM) based on homology modelling in order to characterize the Human resistome. We were able to predict 6,095 ARDs in a 3.9 million protein catalogue from the Human intestinal microbiota. We found that predicted ARDs (pdARDs) were distantly related to known ARDs (mean amino-acid identity 29.8%). Among 3,651 pdARDs that were identified in metagenomic species, 3,489 (95.6%) were assumed to be located on the bacterial chromosome. Furthermore, genes associated with mobility were found in the neighbourhood of only 7.9% (482/6,095) of pdARDs. According to the composition of their resistome, we were able to cluster subjects from the MetaHIT cohort (n=663) into 6 \"resistotypes\". Eventually, we found that the relative abundance of pdARDs was positively associated with gene richness, but not when subjects were exposed to antibiotics. Altogether, our results support that most ARDs in the intestinal microbiota should be considered as intrinsic genes of commensal microbiota with a low risk of transfer to bacterial pathogens.

microbiology↗