Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.04.17.649298

amr.watch - monitoring antimicrobial resistance trends from global genomics data

Abstract

BackgroundWhole 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. MethodsThe 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. FindingsBy 31 March 2025, amr.watch 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. Interpretationamr.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, amr.watch is positioned to monitor both pathogen populations and our global efforts in genomic surveillance, guiding control strategies tailored to each pathogens characteristics. FundingUK National Institute for Health Research & Gates Foundation. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWhole genome sequencing (WGS) approaches enable us to track the spread of bacterial pathogens and antimicrobial resistance (AMR) with high resolution at local, national and global levels. To date, genomic studies assessing AMR dynamics have largely used retrospective data collected for specific research agendas. However, the growing volumes of publicly-shared WGS data, generated increasingly from routine surveillance, provide improved power to detect novel trends and guide interventions. Efforts to collate public bacterial genome data exist, such as AllTheBacteria, although these are aimed at the research community and do not facilitate data usage and interpretation by non-genomics experts, particularly those in public health. To our knowledge, no platforms exist for readily interrogating AMR dynamics from continuously updated public genome data across the array of different WHO priority bacterial pathogens. Of note, however, TyphiNet provides an interactive online dashboard for examining AMR trends exclusively from Salmonella Typhi using a periodically-updated data set from the Pathogenwatch platform. These findings are based on searching PubMed without language restrictions from Jan 1 2000 to December 31 2024, using terms related to "genomic surveillance" and "antimicrobial resistance". Added value of this studyWe have developed amr.watch which, to our knowledge, is the first platform that enables ongoing analysis and visualisation of AMR trends from public genome data across the spectrum of WHO priority bacterial pathogens via an accessible interface. Crucially, the platform incorporates processed genome data via a live always-on stream, enabling insights that are delayed only by the time to data deposition. We reviewed public genomes with available geotemporal information up until 31 March 2025, providing a contemporary global landscape of pathogen genome sequencing. While the number of genomes available annually grew over five-fold globally between 2010 and 2018, we also revealed the extent of differences in geographic representation, with 89.6% of genomes originating from high-income countries and 89 countries contributing no genome data from the priority pathogens. Implications of all the available evidenceRapid generation and sharing of global genome data enables us to more precisely track the spread and define the characteristics of contemporary circulating resistant pathogens. The amr.watch platform provides a solution for retrieving, curating and translating shared genomic data into relevant insights that are accessible and actionable by diverse stakeholders. It thereby forms a basis for monitoring progress in surveillance efforts, alerting on ongoing population changes and guiding enhanced precision for surveillance and interventional development. Additionally, our review of available bacterial genome data highlights the need for additional efforts to increase and sustain the implementation of genomic surveillance of AMR globally, and improve the timely sharing of WGS data and its associated metadata.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

David, S., Diaz Caballero, J., Couto, N., Abudahab, K., Fareed-Alikhan, N., Yeats, C., Underwood, A., Molloy, A., Connor, D., Shane, H. M., Ashton, P. M., Grundmann, H., Holden, M. T., Feil, E. J., Sia, S. B., Donado-Godoy, P., Lingegowda, R. K., Okeke, I. N., Argimon, S., Aanensen, D. M., NIHR Global Health Research Unit on Genomics and enabling data for the Surveillance of AMR,. 2025-04-17. amr.watch - monitoring antimicrobial resistance trends from global genomics data. https://doi.org/10.1101/2025.04.17.649298

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Structural variation in repeat elements is widespread in normal human tissues and in tumorigenesis

Somatic mosaicism contributes to genomic variation, yet postzygotic structural variants remain under-characterized. We performed long- and short-read WGS from multiple individuals (n=47 normal tissues; n=168 samples) and identified mosaic structural variants in all individuals and germ layers, impacting a median 285.2 kb/genome. Nearly half of breakpoints were independently validated, with tissue distributions reflecting both early and late developmental origins. Most mosaic variants were repeat-mediated and 8.3% overlapped functional elements, an enrichment compared to germline variants. To extend these analyses in samples where long-read sequencing is infeasible, we measured repeat alterations from short-read sequencing, recapitulating mosaic tissue-specific differences. We characterized tumor- and tissue- specific variation in repeats across 15 cancer types and found tumor-related repeat variation to be similar in scale to that of normal mosaic variation. Tracking repeat changes in cell-free DNA provided a noninvasive approach for tumor monitoring. Our analyses revealed widespread repeat-driven structural variation in health and disease.

genomics↗

RNA isoform-resolved multiplexed sequencing with bioorthogonal barcoding

RNA isoform dysregulation drives disease pathogenesis and is the target of FDA-approved splice-switching therapeutics. However, multiplexed sequencing methods discard splice junction information because only 3' termini are barcoded and counted. Here, we repurpose acylation and click chemistries to conjugate bioorthogonal barcodes (bobcodes) directly onto multiple internal positions along cellular RNAs. Bobcoded RNAs from multiple samples are pooled for multiplexed cDNA synthesis, during which reverse transcriptase switches from each RNA template onto its tethered bobcode with greater than 99% accuracy in species mixing experiments. Bobcode attachment intervals set cDNA insert sizes without a library fragmentation step, and priming with poly(dT) or random hexamers selects between 3'-end counting and full-length isoform capture. A bioorthogonal barcode-sequencing (BOB-seq v0.1) drug screen identifies transcriptome-wide on- and off-target RNA splicing effects and outperforms existing multiplexing RNA sequencing methods in workflow simplicity, sample-to-sample variability, and barcoding accuracy. Bobcodes add isoform resolution to scalable multiplexed RNA sequencing.

genomics↗

Structural polymorphism and population-variable coding capacity of HERV-K(HML-2) in human pangenomes

Approximately 8% of the human genome is derived from ancient retroviral infections. The most recently integrated of these endogenous retroviruses is the HERV-K(HML-2) clade, whose expression has been associated with cancer, amyotrophic lateral sclerosis, and embryogenesis. Studies of HERV expression, particularly HML-2, have relied predominantly on short-read sequencing. However, the high similarity among HML-2 proviruses prevents many short reads from being assigned uniquely to individual loci. We therefore compared haplotype-resolved long-read genome assemblies from 292 donors to resolve variation in proviral structure and coding capacity. Several loci previously thought to be fixed were structurally polymorphic. Tandem arrays occurred at 13 loci and contained up to six proviral copies in a single array. At 8q11.23, we identified a previously undescribed full-length provirus in one haplotype. All 583 other haplotypes carried a solo-LTR. We found that standard reference genomes failed to represent the coding capacity retained in many individuals, whose proviruses contained intact open reading frames despite disruptive mutations in the reference sequences. Short-read genotypes left 32.5% of the tested donor-variant pairs unresolved at sites associated with viral reading frames. These findings show why HML-2 expression must be interpreted in the context of the structural and coding alleles each individual carries.

genomics↗