{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T21:44:23Z","timestamp":1775166263610,"version":"3.50.1"},"reference-count":37,"publisher":"Public Library of Science (PLoS)","issue":"6","license":[{"start":{"date-parts":[[2023,6,22]],"date-time":"2023-06-22T00:00:00Z","timestamp":1687392000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000265","name":"Medical Research Council","doi-asserted-by":"publisher","award":["MR\/R015600\/1"],"award-info":[{"award-number":["MR\/R015600\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"name":"FIND"},{"name":"BMBF"},{"name":"BMBF"},{"name":"BMBF"},{"DOI":"10.13039\/501100000833","name":"Rosetrees Trust","doi-asserted-by":"publisher","award":["M683"],"award-info":[{"award-number":["M683"]}],"id":[{"id":"10.13039\/501100000833","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>The increasing availability of high-throughput sequencing (frequently termed next-generation sequencing (NGS)) data has created opportunities to gain deeper insights into the mechanisms of a number of diseases and is already impacting many areas of medicine and public health. The area of infectious diseases stands somewhat apart from other human diseases insofar as the relevant genomic data comes from the microbes rather than their human hosts. A particular concern about the threat of antimicrobial resistance (AMR) has driven the collection and reporting of large-scale datasets containing information from microbial genomes together with antimicrobial susceptibility test (AST) results. Unfortunately, the lack of clear standards or guiding principles for the reporting of such data is hampering the field\u2019s advancement. We therefore present our recommendations for the publication and sharing of genotype and phenotype data on AMR, in the form of 10 simple rules. The adoption of these recommendations will enhance AMR data interoperability and help enable its large-scale analyses using computational biology tools, including mathematical modelling and machine learning. We hope that these rules can shed light on often overlooked but nonetheless very necessary aspects of AMR data sharing and enhance the field\u2019s ability to address the problems of understanding AMR mechanisms, tracking their emergence and spread in populations, and predicting microbial susceptibility to antimicrobials for diagnostic purposes.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1011129","type":"journal-article","created":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T01:38:15Z","timestamp":1687484295000},"page":"e1011129","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":10,"title":["Ten simple rules for the sharing of bacterial genotype\u2014Phenotype data on antimicrobial resistance"],"prefix":"10.1371","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6619-6013","authenticated-orcid":true,"given":"Leonid","family":"Chindelevitch","sequence":"first","affiliation":[]},{"given":"Maarten","family":"van Dongen","sequence":"additional","affiliation":[]},{"given":"Heather","family":"Graz","sequence":"additional","affiliation":[]},{"given":"Antonio","family":"Pedrotta","sequence":"additional","affiliation":[]},{"given":"Anita","family":"Suresh","sequence":"additional","affiliation":[]},{"given":"Swapna","family":"Uplekar","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7075-6896","authenticated-orcid":true,"given":"Elita","family":"Jauneikaite","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4599-9164","authenticated-orcid":true,"given":"Nicole","family":"Wheeler","sequence":"additional","affiliation":[]}],"member":"340","published-online":{"date-parts":[[2023,6,22]]},"reference":[{"issue":"10325","key":"pcbi.1011129.ref001","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1016\/S0140-6736(21)02724-0","article-title":"Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis","volume":"399","author":"CJ Murray","year":"2022","journal-title":"Lancet"},{"key":"pcbi.1011129.ref002","author":"L Chindelevitch","year":"2022","journal-title":"Applying data technologies to combat AMR: current status, challenges, and opportunities on the way forward"},{"issue":"5","key":"pcbi.1011129.ref003","doi-asserted-by":"crossref","first-page":"e0195885","DOI":"10.1371\/journal.pone.0195885","article-title":"How ownership rights over microorganisms affect infectious disease control and innovation: A root-cause analysis of barriers to data sharing as experienced by key stakeholders.","volume":"13","author":"CS Ribeiro","year":"2018","journal-title":"PLoS ONE."},{"key":"pcbi.1011129.ref004","author":"G Cochrane","year":"2022","journal-title":"Pathogen genomics data sharing: public health meets research"},{"issue":"1","key":"pcbi.1011129.ref005","doi-asserted-by":"crossref","DOI":"10.1186\/s42522-020-00026-3","article-title":"Optimizing open data to support one health: best practices to ensure interoperability of genomic data from bacterial pathogens.","volume":"2","author":"RE Timme","year":"2020","journal-title":"One Health. 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