A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing

Petrillo, Mauro, Fabbri, Marco, Kagkli, Dafni Maria, Querci, Maddalena, Van den Eede, Guy, Alm, Erik, Aytan-Aktug, Derya, Capella-Gutierrez, Salvador, Carrillo, Catherine, Cestaro, Alessandro, Chan, Kok Gan, Coque, Teresa, Endrullat, Christoph, Gut, Ivo, Hammer, Paul, Kay, Gemma L., Madec, Jean Yves, Mather, Alison E., McHardy, Alice Carolyn, Naas, Thierry, Paracchini, Valentina, Peter, Silke, Pightling, Arthur, Raffael, Barbara, Rossen, John, Ruppé, Etienne, Schlaberg, Robert, Vanneste, Kevin, Weber, Lukas M., Westh, Henrik and Angers-Loustau, Alexandre (2022) A roadmap for the generation of benchmarking resources for antimicrobial resistance detection using next generation sequencing. F1000Research, 10. ISSN 2046-1402

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Abstract

Next Generation Sequencing technologies significantly impact the field of Antimicrobial Resistance (AMR) detection and monitoring, with immediate uses in diagnosis and risk assessment. For this application and in general, considerable challenges remain in demonstrating sufficient trust to act upon the meaningful information produced from raw data, partly because of the reliance on bioinformatics pipelines, which can produce different results and therefore lead to different interpretations. With the constant evolution of the field, it is difficult to identify, harmonise and recommend specific methods for large-scale implementations over time. In this article, we propose to address this challenge through establishing a transparent, performance-based, evaluation approach to provide flexibility in the bioinformatics tools of choice, while demonstrating proficiency in meeting common performance standards. The approach is two-fold: first, a community-driven effort to establish and maintain 'live' (dynamic) benchmarking platforms to provide relevant performance metrics, based on different use-cases, that would evolve together with the AMR field; second, agreed and defined datasets to allow the pipelines' implementation, validation, and quality-control over time. Following previous discussions on the main challenges linked to this approach, we provide concrete recommendations and future steps, related to different aspects of the design of benchmarks, such as the selection and the characteristics of the datasets (quality, choice of pathogens and resistances, etc.), the evaluation criteria of the pipelines, and the way these resources should be deployed in the community.

Item Type: Article
Additional Information: Funding Information: We would like to thank Valentina Rizzi (EFSA) and Alberto Orgiazzi (JRC) for their participation to the workshop discussions. The authors are also grateful to the following colleagues for their comments on the manuscript: Sigrid De Keersmaecker and Nancy Roosens (Sciensano) and Tewodros Debebe (Biomes). We are also grateful to Laura Oliva for her invaluable help during the workshop. Publisher Copyright: © 2022 Petrillo M et al.
Uncontrolled Keywords: antimicrobial resistance,benchmarking,bioinformatics,next-generation sequencing,biochemistry, genetics and molecular biology(all),immunology and microbiology(all),pharmacology, toxicology and pharmaceutics(all) ,/dk/atira/pure/subjectarea/asjc/1300
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Depositing User: LivePure Connector
Date Deposited: 04 Nov 2022 14:30
Last Modified: 04 Nov 2022 14:30
URI: https://ueaeprints.uea.ac.uk/id/eprint/89622
DOI: 10.12688/f1000research.39214.2

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