Monitoring antimicrobial resistance trends from global genomics data
Amr.watch
Bibliographic Data
| ID | 19593563 |
|---|---|
| Authors | Sophia David (0000-0002-0115-0954, University of Oxford, corresponding author), Julio Diaz Caballero (0000-0003-4664-8577, University of Oxford, corresponding author), Natacha Couto (0000-0002-9152-5464, University of Oxford, corresponding author), Khalil Abudahab (University of Oxford, corresponding author), Nabil-Fareed Alikhan (0000-0002-1243-0767, University of Oxford, corresponding author), Corin Yeats (0000-0003-0080-6242, University of Oxford, corresponding author), Anthony Underwood (0000-0001-6424-626X, University of Oxford, corresponding author), Alison Molloy (0009-0001-5433-0844, Alice Lloyd College, corresponding author), Diana Connor (University of Oxford, corresponding author), Heather M Shane (University of Oxford, corresponding author), Philip Ashton (0000-0001-9257-9424, University of Oxford, corresponding author), Philip M Ashton, Hajo Grundmann (0000-0002-9971-522X, University Medical Center Freiburg, corresponding author), Matthew T G Holden (0000-0002-4958-2166, University of St Andrews, corresponding author), Edward Feil (0000-0003-1446-6744, University of Bath, corresponding author), Edward J Feil, Sonia B Sia (0009-0005-2475-9577, Research Institute for Tropical Medicine, corresponding author), Pilar Donado-Godoy (0000-0001-9839-9264, Colombian Corporation for Agricultural Research - AGROSAVIA, corresponding author), Ravikumar Kadahalli Lingegowda (0000-0001-8629-1459, corresponding author), Iruka N Okeke (0000-0002-1694-7587, University of Ibadan, corresponding author), Silvia Argimón (0000-0002-2884-3857, University of Oxford, corresponding author), David M Aanensen (0000-0001-6688-0854, University of Oxford, corresponding author) |
| Editors | Hui-min Neoh |
| Year | 2025 |
| Volume | 5 |
| Issue | 11 |
| Pages | e0005256 |
| Publication date | 2025-11-24 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | PLOS Global Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2767-3375 • E-ISSN: 2767-3375 |
| Publisher | Public Library of Science (PLoS) (PUBLISHER) |
| DOI | 10.1371/journal.pgph.0005256 |
| PMID | 41284650 |
| OpenAlex | W4416582015 |
| Language | EN |
| References cited | 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
| Citation velocity | historical |
|---|---|
| Highly cited | No |