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Addressing the Antimicrobial Resistance of Ruminant Mycoplasmas Using a Clinical Surveillance Network

Antimicrobial resistance (AMR) surveillance of mycoplasmas of veterinary importance has been held back for years due to lack of harmonized methods for antimicrobial susceptibility testing (AST) and interpretative criteria, resulting in a crucial shortage of data. To address AMR in ruminant mycoplasm...

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Autores principales: Jaÿ, Maryne, Poumarat, François, Colin, Adélie, Tricot, Agnès, Tardy, Florence
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236625/
https://www.ncbi.nlm.nih.gov/pubmed/34195247
http://dx.doi.org/10.3389/fvets.2021.667175
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author Jaÿ, Maryne
Poumarat, François
Colin, Adélie
Tricot, Agnès
Tardy, Florence
author_facet Jaÿ, Maryne
Poumarat, François
Colin, Adélie
Tricot, Agnès
Tardy, Florence
author_sort Jaÿ, Maryne
collection PubMed
description Antimicrobial resistance (AMR) surveillance of mycoplasmas of veterinary importance has been held back for years due to lack of harmonized methods for antimicrobial susceptibility testing (AST) and interpretative criteria, resulting in a crucial shortage of data. To address AMR in ruminant mycoplasmas, we mobilized a long-established clinical surveillance network called “Vigimyc.” Here we describe our surveillance strategy and detail the results obtained during a 2-year monitoring period. We also assess how far our system complies with current guidelines on AMR surveillance and how it could serve to build epidemiological cut-off values (ECOFFs), as a first attainable criterion to help harmonize monitoring efforts and move forward to clinical breakpoints. Clinical surveillance through Vigimyc enables continuous collection, identification and preservation of Mycoplasma spp. isolates along with metadata. The most frequent pathogens, i.e., M. bovis and species belonging to M. mycoides group, show stable clinicoepidemiological trends and were included for annual AST. In the absence of interpretative criteria for ruminant mycoplasmas, we compared yearly minimum inhibitory concentration (MIC) results against reference datasets. We also ran a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis on the overall service provided by our AMR surveillance strategy. Results of the 2018–2019 surveillance campaign were consistent with the reference datasets, with M. bovis isolates showing high MIC values for all antimicrobial classes except fluoroquinolones, and species of the Mycoides group showing predominantly low MIC values. A few new AMR patterns were detected, such as M. bovis with lower spectinomycin MICs. Our reference dataset partially complied with European Committee on Antimicrobial Susceptibility Testing (EUCAST) requirements, and we were able to propose tentative epidemiological cut-off values (TECOFFs) for M. bovis with tilmicosin and spectinomycin and for M. mycoides group with tilmicosin and lincomycin. These TECOFFs were consistent with other published data and the clinical breakpoints of Pasteurellaceae, which are often used as surrogates for mycoplasmas. SWOT analysis highlighted the benefit of pairing clinical and antimicrobial resistance surveillance despite the AST method-related gaps that remain. The international community should now direct efforts toward AST method harmonization and clinical interpretation.
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spelling pubmed-82366252021-06-29 Addressing the Antimicrobial Resistance of Ruminant Mycoplasmas Using a Clinical Surveillance Network Jaÿ, Maryne Poumarat, François Colin, Adélie Tricot, Agnès Tardy, Florence Front Vet Sci Veterinary Science Antimicrobial resistance (AMR) surveillance of mycoplasmas of veterinary importance has been held back for years due to lack of harmonized methods for antimicrobial susceptibility testing (AST) and interpretative criteria, resulting in a crucial shortage of data. To address AMR in ruminant mycoplasmas, we mobilized a long-established clinical surveillance network called “Vigimyc.” Here we describe our surveillance strategy and detail the results obtained during a 2-year monitoring period. We also assess how far our system complies with current guidelines on AMR surveillance and how it could serve to build epidemiological cut-off values (ECOFFs), as a first attainable criterion to help harmonize monitoring efforts and move forward to clinical breakpoints. Clinical surveillance through Vigimyc enables continuous collection, identification and preservation of Mycoplasma spp. isolates along with metadata. The most frequent pathogens, i.e., M. bovis and species belonging to M. mycoides group, show stable clinicoepidemiological trends and were included for annual AST. In the absence of interpretative criteria for ruminant mycoplasmas, we compared yearly minimum inhibitory concentration (MIC) results against reference datasets. We also ran a SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis on the overall service provided by our AMR surveillance strategy. Results of the 2018–2019 surveillance campaign were consistent with the reference datasets, with M. bovis isolates showing high MIC values for all antimicrobial classes except fluoroquinolones, and species of the Mycoides group showing predominantly low MIC values. A few new AMR patterns were detected, such as M. bovis with lower spectinomycin MICs. Our reference dataset partially complied with European Committee on Antimicrobial Susceptibility Testing (EUCAST) requirements, and we were able to propose tentative epidemiological cut-off values (TECOFFs) for M. bovis with tilmicosin and spectinomycin and for M. mycoides group with tilmicosin and lincomycin. These TECOFFs were consistent with other published data and the clinical breakpoints of Pasteurellaceae, which are often used as surrogates for mycoplasmas. SWOT analysis highlighted the benefit of pairing clinical and antimicrobial resistance surveillance despite the AST method-related gaps that remain. The international community should now direct efforts toward AST method harmonization and clinical interpretation. Frontiers Media S.A. 2021-06-14 /pmc/articles/PMC8236625/ /pubmed/34195247 http://dx.doi.org/10.3389/fvets.2021.667175 Text en Copyright © 2021 Jaÿ, Poumarat, Colin, Tricot and Tardy. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Veterinary Science
Jaÿ, Maryne
Poumarat, François
Colin, Adélie
Tricot, Agnès
Tardy, Florence
Addressing the Antimicrobial Resistance of Ruminant Mycoplasmas Using a Clinical Surveillance Network
title Addressing the Antimicrobial Resistance of Ruminant Mycoplasmas Using a Clinical Surveillance Network
title_full Addressing the Antimicrobial Resistance of Ruminant Mycoplasmas Using a Clinical Surveillance Network
title_fullStr Addressing the Antimicrobial Resistance of Ruminant Mycoplasmas Using a Clinical Surveillance Network
title_full_unstemmed Addressing the Antimicrobial Resistance of Ruminant Mycoplasmas Using a Clinical Surveillance Network
title_short Addressing the Antimicrobial Resistance of Ruminant Mycoplasmas Using a Clinical Surveillance Network
title_sort addressing the antimicrobial resistance of ruminant mycoplasmas using a clinical surveillance network
topic Veterinary Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8236625/
https://www.ncbi.nlm.nih.gov/pubmed/34195247
http://dx.doi.org/10.3389/fvets.2021.667175
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