0000000001080787

AUTHOR

Alexandre Meunier

showing 7 related works from this author

The rise and the fall of a Pseudomonas aeruginosa endemic lineage in a hospital

2021

The biological features that allow a pathogen to survive in the hospital environment are mostly unknown. The extinction of bacterial epidemics in hospitals is mostly attributed to changes in medical practice, including infection control, but the role of bacterial adaptation has never been documented. We analysed a collection of Pseudomonas aeruginosa isolates belonging to the Besançon Epidemic Strain (BES), responsible for a 12year nosocomial outbreak, using a genotype-to-phenotype approach. Bayesian analysis estimated the emergence of the clone in the hospital 5 years before its opening, during the creation of its water distribution network made of copper. BES survived better than the refe…

DNA Bacterialparallel evolutionLineage (genetic)Genomic IslandsPathogens and EpidemiologyBiologymedicine.disease_causeAmoeba (operating system)Disease OutbreaksMicrobiology03 medical and health sciencesAntibiotic resistanceDrug Resistance Multiple BacterialGenomic islandbacterial pathogensmedicineHumansPseudomonas InfectionsPathogenGenome size[SDV.MP] Life Sciences [q-bio]/Microbiology and ParasitologyResearch Articles030304 developmental biology0303 health sciencesoutbreak030306 microbiologyPseudomonas aeruginosahigh-risk cloneOutbreakBayes TheoremSequence Analysis DNAGeneral MedicineHospitals3. Good healthPhenotype[SDV.MP]Life Sciences [q-bio]/Microbiology and ParasitologyPseudomonas aeruginosa
researchProduct

Comparison of pulsed-field gel electrophoresis and whole-genome-sequencing-based typing confirms the accuracy of pulsed-field gel electrophoresis for…

2020

Summary Aim To determine whether pulsed-field gel electrophoresis (PFGE) accurately recognizes isolates belonging to clusters defined by techniques based on whole-genome sequencing (WGS) using Pseudomonas aeruginosa as a model. Methods We selected 65 isolates of ST395 P. aeruginosa isolated in seven European hospitals between 1998 and 2012. Isolates were typed by PFGE and sequenced by WGS. A core genome multi-locus sequence typing (cgMLST) analysis based on 3831 genes was performed with a homemade pipeline. Findings PFGE identified eight pulsotypes and cgMLST differentiated nine clusters and nine singletons. Five cgMLST clusters and pulsotypes (31/65 isolates) coincided perfectly. Isolates …

Bacterial typingMicrobiology (medical)030501 epidemiologymedicine.disease_causeGenomeDisease Outbreaks03 medical and health sciencesPulsed-field gel electrophoresisHumansMedicinePseudomonas InfectionsTypingPulsed-field gel electrophoresisReference standardsGel electrophoresisWhole genome sequencingGeneticsWhole-genome sequencing0303 health sciencesWhole Genome Sequencing030306 microbiologybusiness.industryPseudomonas aeruginosaOutbreaksReproducibility of ResultsOutbreakGeneral MedicineBacterial Typing TechniquesElectrophoresis Gel Pulsed-FieldEurope[SDV.MP]Life Sciences [q-bio]/Microbiology and ParasitologyInfectious DiseasesPseudomonas aeruginosacgMLST0305 other medical sciencebusinessGenome BacterialMultilocus Sequence TypingJournal of Hospital Infection
researchProduct

Contamination of a hospital plumbing system by persister cells of a copper-tolerant high-risk clone of Pseudomonas aeruginosa

2019

Abstract Background Pseudomonas aeruginosa (PA) is an important opportunistic pathogen that thrives best in the distal elements of plumbing and waste-water systems. Although nosocomial outbreaks of PA have been associated with water sources, the role of the plumbing system of healthcare premises as a reservoir for this pathogen is still unclear. Materials and methods We collected water samples from 12 technical areas, distant from any medical activity, in a teaching hospital in France once a week for 11 weeks. We used a method that resuscitates persister cells because of the nutrient-poor conditions and the presence of inhibitors (e.g. chlorine and copper ions). Briefly, water was sampled i…

Environmental EngineeringMultidrug tolerance0208 environmental biotechnology02 engineering and technology010501 environmental sciencesmedicine.disease_cause01 natural sciencesMicrobiologyAgar platechemistry.chemical_compoundGenomic islandmedicinePseudomonas syringaeHumansWaste Management and DisposalPathogen0105 earth and related environmental sciencesWater Science and TechnologyCivil and Structural EngineeringOne healthbiologyPersistersPseudomonas aeruginosaEcological Modelingbiology.organism_classificationPollutionPremises plumbingPseudomonas putidaHospitals020801 environmental engineering3. Good healthR2a agar[SDV.MP]Life Sciences [q-bio]/Microbiology and ParasitologychemistryPseudomonas aeruginosaFranceSanitary EngineeringCopper
researchProduct

Enhanced emergence of antibiotic-resistant pathogenic bacteria after in vitro induction with cancer chemotherapy drugs.

2019

International audience; BACKGROUND:Infections with antibiotic-resistant pathogens in cancer patients are a leading cause of mortality. Cancer patients are treated with compounds that can damage bacterial DNA, potentially triggering the SOS response, which in turn enhances the bacterial mutation rate. Antibiotic resistance readily occurs after mutation of bacterial core genes. Thus, we tested whether cancer chemotherapy drugs enhance the emergence of resistant mutants in commensal bacteria.METHODS:Induction of the SOS response was tested after the incubation of Escherichia coli biosensors with 39 chemotherapeutic drugs at therapeutic concentrations. The mutation frequency was assessed after …

0301 basic medicineMicrobiology (medical)Staphylococcus aureusmedicine.drug_class030106 microbiologyAntibioticsAntineoplastic AgentsDrug resistanceMicrobial Sensitivity TestsBiologymedicine.disease_causeMicrobiology03 medical and health sciencesSOS Response (Genetics)0302 clinical medicineAntibiotic resistanceDrug Resistance BacterialEnterobacter cloacaemedicineHumansPharmacology (medical)030212 general & internal medicineMutation frequencySOS responseSOS Response GeneticsPharmacologyPathogenic bacteriaChemotherapy regimen3. Good healthAnti-Bacterial Agents[SDV.MP]Life Sciences [q-bio]/Microbiology and ParasitologyInfectious DiseasesPseudomonas aeruginosaThe Journal of antimicrobial chemotherapy
researchProduct

panISa: ab initio detection of insertion sequences in bacterial genomes from short read sequence data.

2018

Abstract Motivation The advent of next-generation sequencing has boosted the analysis of bacterial genome evolution. Insertion sequence (IS) elements play a key role in prokaryotic genome organization and evolution, but their repetitions in genomes complicate their detection from short-read data. Results PanISa is a software pipeline that identifies IS insertions ab initio in bacterial genomes from short-read data. It is a highly sensitive and precise tool based on the detection of read-mapping patterns at the insertion site. PanISa performs better than existing IS detection systems as it is based on a database-free approach. We applied it to a high-risk clone lineage of the pathogenic spec…

0301 basic medicineStatistics and ProbabilityLineage (genetic)Computer scienceAb initioComputational biologyBacterial genome size[INFO.INFO-SE]Computer Science [cs]/Software Engineering [cs.SE]BiochemistryGenome[INFO.INFO-IU]Computer Science [cs]/Ubiquitous Computing03 medical and health sciences[INFO.INFO-CR]Computer Science [cs]/Cryptography and Security [cs.CR][SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry Molecular Biology/Genomics [q-bio.GN]Insertion sequenceMolecular BiologyGenomic organizationHigh-Throughput Nucleotide SequencingSequence Analysis DNA[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM][SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/BacteriologyPipeline (software)[INFO.INFO-MO]Computer Science [cs]/Modeling and SimulationComputer Science ApplicationsComputational Mathematics030104 developmental biologyComputational Theory and Mathematics[INFO.INFO-MA]Computer Science [cs]/Multiagent Systems [cs.MA]DNA Transposable Elements[INFO.INFO-ET]Computer Science [cs]/Emerging Technologies [cs.ET][INFO.INFO-DC]Computer Science [cs]/Distributed Parallel and Cluster Computing [cs.DC]Genome BacterialSoftwareBioinformatics (Oxford, England)
researchProduct

The rise and the fall of a Pseudomonas aeruginosa epidemic lineage in a hospital

2020

AbstractThe biological features that allow a pathogen to survive in the hospital environment are mostly unknown. The extinction of bacterial epidemics in hospitals is mostly attributed to changes in medical practice, including infection control, but the role of bacterial adaptation has never been documented. We analyzed a collection of Pseudomonas aeruginosa isolates belonging to the Besançon Epidemic Strain (BES), responsible for a 12-year nosocomial outbreak, using a genotype-to-phenotype approach. Bayesian analysis estimated the emergence of the clone in the hospital five years before its opening, during the creation of its water distribution network made of copper. BES survived better t…

Genome evolutionAntibiotic resistancePseudomonas aeruginosaGenomic islandmedicineOutbreakBacterial genome sizeBiologymedicine.disease_causeGenome sizePathogenMicrobiology
researchProduct

Populations of extended-spectrum β-lactamase-producing Escherichia coli and Klebsiella pneumoniae are different in human-polluted environment and foo…

2021

Abstract Objectives To assess the extent to which food items are a source of extended-spectrum β-lactamase (ESBL) -producing Escherichia coli (ESBL-Ec) and ESBL-producing Klebsiella pneumoniae (ESBL-Kp) for humans in five European cities. Methods We sampled 122 human polluted (hp)-environments (sewers and polluted rivers, as a proxy of human contamination) and 714 food items in Besancon (France), Geneva (Switzerland), Sevilla (Spain), Tubingen (Germany) and Utrecht (The Netherlands). A total of 254 ESBL-Ec and 39 ESBL-Kp isolates were cultured. All genomes were fully sequenced to compare their sequence types (ST) and core genomes, along with the distribution of blaESBL genes and their genet…

Microbiology (medical)Veterinary medicineKlebsiella pneumoniaeEscherichia coli K. pneumoniae ESBL food environmentBiologyEnvironmentPolluted environmentmedicine.disease_causebeta-LactamasesK. pneumoniae03 medical and health sciencesFood chainPlasmidData sequencesExtended-spectrum β-lactamasemedicinepolycyclic compoundsEscherichia coliHumansEscherichia coliEscherichia coli Infections030304 developmental biologyddc:6160303 health sciences030306 microbiologyK pneumoniaeGeneral MedicineSequence typesbiochemical phenomena metabolism and nutritionbiology.organism_classificationbacterial infections and mycoses3. Good healthAnti-Bacterial AgentsKlebsiella InfectionsKlebsiella pneumoniaeInfectious Diseases[SDV.MP]Life Sciences [q-bio]/Microbiology and ParasitologyESBLFoodbacteria[SDV.MHEP]Life Sciences [q-bio]/Human health and pathologyPlasmids
researchProduct