Author

L. Opatowski

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Microbiology· 5 Ecology· 2 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 8 Organism:human· 4 Research Focus:host-pathogen & immune response· 3 Assay:metagenomics· 3 Assay:whole-genome sequencing· 2 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Organism:E. coli· 1

Frequent Co-Authors

L. Temime· 4 shared P. Glaser· 3 shared B.-T. Huynh· 2 shared D. R. M. Smith· 2 shared J. Bastard· 2 shared P. Henriot· 2 shared A. Duval· 1 shared A. Kovacevic· 1 shared

Activity by Year

2018-2022 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 14 mutual co-author links

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4 shared papersMicrobiology

L. Temime

Mutual co-authors in cluster

Author profile →

8 papers

Recent·Most cited

Collateral impacts of pandemic COVID-19 drive the nosocomial spread of antibiotic resistance

D. R. M. Smith, G. Shirreff, L. Temime, L. Opatowski

This paper models how pandemic COVID-19 control measures impact the spread of antibiotic-resistant bacteria in hospitals, showing both reduced transmission and increased resistance under certain conditions.

bioRxiv · Aug 15, 2022Evolutionary Biology

Revealing the drivers of antibiotic resistance trends in Streptococcus pneumoniae amidst the 2020 COVID-19 pandemic: Insights from mathematical modeling

A. Kovacevic, D. R. M. Smith, E. Rahbe, S. Novelli, P. Henriot, E. Varon, R. Cohen, C. Levy, L. Temime, L. Opatowski

This study uses mathematical modeling to show that reduced antibiotic use, decreased IPD risk, and azithromycin use during the pandemic increased antibiotic resistance in Streptococcus pneumoniae while keeping carriage stable.

bioRxiv · Aug 8, 2022Ecology

Is it the same strain? Defining genomic epidemiology thresholds tailored to individual outbreaks

A. Duval, L. opatowski, S. Brisse

This paper introduces a framework to determine genomic relatedness thresholds for outbreak strains based on outbreak-specific parameters, improving accuracy in identifying clusters.

bioRxiv · Feb 15, 2022 · PreprintMicrobiology

Modelling the impact of urban and hospital wastewaters eco-exposomes on the antibiotic-resistance dynamics.

P. Henriot, E. Buelow, F. Petit, M.-C. Ploy, C. DAGOT, L. Opatowski

This paper develops a simple model to analyze how antibiotics and pollutants affect antibiotic resistance dynamics in wastewater and identifies key compounds influencing resistance gene persistence.

bioRxiv · Dec 17, 2021 · PreprintMicrobiology

Drivers of ESBL-producing Escherichia coli dynamics in calf fattening farms: a modelling study

J. Bastard, M. Haenni, E. Gay, P. Glaser, J.-Y. Madec, L. Temime, L. Opatowski

This study models ESBL-EC dynamics in veal calf farms, finding that within-farm transmission and AMU influence carriage duration and prevalence.

bioRxiv · Sep 14, 2020Microbiology

Dynamics of Livestock-Associated Methicillin Resistant Staphylococcus aureus in pig farms networks: insight from mathematical modeling and French data

J. Bastard, M. Andraud, C. Chauvin, P. Glaser, L. Opatowski, L. Temime

The paper models LA-MRSA spread in French pig farms, showing that targeting central farms reduces prevalence and identifies high indegree farms as best for surveillance of new strains.

Epidemics · Jun 1, 2020Peer-reviewedMicrobiology

Clonal transmission and new mechanism of resistance to trimethoprim-sulfamethoxazole in Stenotrophomonas maltophilia strains isolated in a neonatology unit at Antananarivo, Madagascar, deciphered by whole genome sequence analysis

M. A. N. Rabenandrasana, V. Andrianoelina, M. Bonneault, P. Herindrainy, B. Garin, S. Breurec, E. Delarocque-Astagneau, Z. Z. Andrianirina, V. Enouf, B.-T. Huynh, L. Opatowski, J. M. Collard

The paper identifies clonal transmission of SXT-resistant S. maltophilia strains in a neonatology unit and links a folA mutation to trimethoprim resistance via whole genome sequencing.

bioRxiv · Jul 10, 2019 · PreprintMicrobiology

Inference of significant microbial interactions from longitudinal metagenomics sequencing data

X. Gao, B.-T. Huynh, D. Guillemot, P. Glaser, L. Opatowski

The paper infers microbial interactions from longitudinal metagenomics data, finding differences in interaction patterns between healthy children and T1D progressors.

bioRxiv · Apr 20, 2018Ecology