Monitoring antimicrobial resistance trends from global genomics data
Amr.watch
Datos Bibliográficos
| ID | 19593563 |
|---|---|
| Autores | Sophia David (0000-0002-0115-0954, University of Oxford, autor de correspondencia), Julio Diaz Caballero (0000-0003-4664-8577, University of Oxford, autor de correspondencia), Natacha Couto (0000-0002-9152-5464, University of Oxford, autor de correspondencia), Khalil Abudahab (University of Oxford, autor de correspondencia), Nabil-Fareed Alikhan (0000-0002-1243-0767, University of Oxford, autor de correspondencia), Corin Yeats (0000-0003-0080-6242, University of Oxford, autor de correspondencia), Anthony Underwood (0000-0001-6424-626X, University of Oxford, autor de correspondencia), Alison Molloy (0009-0001-5433-0844, Alice Lloyd College, autor de correspondencia), Diana Connor (University of Oxford, autor de correspondencia), Heather M Shane (University of Oxford, autor de correspondencia), Philip Ashton (0000-0001-9257-9424, University of Oxford, autor de correspondencia), Philip M Ashton, Hajo Grundmann (0000-0002-9971-522X, University Medical Center Freiburg, autor de correspondencia), Matthew T G Holden (0000-0002-4958-2166, University of St Andrews, autor de correspondencia), Edward Feil (0000-0003-1446-6744, University of Bath, autor de correspondencia), Edward J Feil, Sonia B Sia (0009-0005-2475-9577, Research Institute for Tropical Medicine, autor de correspondencia), Pilar Donado-Godoy (0000-0001-9839-9264, Colombian Corporation for Agricultural Research - AGROSAVIA, autor de correspondencia), Ravikumar Kadahalli Lingegowda (0000-0001-8629-1459, autor de correspondencia), Iruka N Okeke (0000-0002-1694-7587, University of Ibadan, autor de correspondencia), Silvia Argimón (0000-0002-2884-3857, University of Oxford, autor de correspondencia), David M Aanensen (0000-0001-6688-0854, University of Oxford, autor de correspondencia) |
| Editores | Hui-min Neoh |
| Año | 2025 |
| Volumen | 5 |
| Número | 11 |
| Páginas | e0005256 |
| Fecha de publicación | 2025-11-24 |
| Peer Reviewed | Sí |
| Open Access | Sí |
| Tipo | ARTICLE |
| Revista | PLOS Global Public Health (JOURNAL) |
| Identificadores de la revista | ISSN: 2767-3375 • E-ISSN: 2767-3375 |
| Editorial | Public Library of Science (PLoS) (PUBLISHER) |
| DOI | 10.1371/journal.pgph.0005256 |
| PMID | 41284650 |
| OpenAlex | W4416582015 |
| Idioma | EN |
| Referencias citadas | 23 |
Whole genome sequencing (WGS) is increasingly supporting routine pathogen surveillance at local and national levels, providing comparable data that can inform on the emergence and spread of antimicrobial resistance (AMR) globally. However, the potential for shared WGS data to guide interventions around AMR remains under-exploited, in part due to challenges in collating and transforming the growing volumes of data into timely insights. We present an interactive platform, amr.watch ( https://amr.watch ), that enables interrogation of AMR trends from public WGS data on an ongoing basis to support research and policy. The amr.watch platform incorporates, analyses and visualises high-quality WGS data from WHO-defined priority bacterial pathogens. Analytics are performed using community-standard methods with bespoke species-specific curation of AMR mechanisms. By 31 March 2025, the platform included data from 620,700 pathogen genomes with geotemporal information, with highly variable representation of different species and geographic regions. By integrating WGS data with sampling information, amr.watch enables users to assess geotemporal trends among genotypic variants (e.g., sequence types) and AMR mechanisms, with implications for interventions including antimicrobial prescribing and drug and vaccine development. While metadata inconsistencies demand future attention we focus on the collation of high quality genomic data allied with geotemporal distribution. In conclusion, amr.watch is an information platform for scientists and policy-makers delivering ongoing situational awareness of AMR trends from genomic data. As broad adoption of WGS continues, and crucially, metadata and associated sampling becomes increasingly representative, amr.watch is positioned to monitor both pathogen populations and our global efforts in genomic surveillance, guiding control strategies tailored to each pathogen’s characteristics
Analytics · Antibiotic resistance · Bespoke · Data quality · Genomics · Metadata · Whole genome sequencing · Antibiotic Resistance in Bacteria · Antibiotic Use and Resistance · Genomics and Phylogenetic Studies
| Velocidad de citación | historical |
|---|---|
| Altamente citado | No |