bioRxiv Science⌕ 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

Genome-wide diversity across 130 years reveals drastic post-bottleneck genetic erosion in a recovering population of golden eagles (Aquila chrysaetos)

Many wild populations have experienced severe human-induced declines, but the genetic consequences of such bottlenecks are often poorly understood. In Finland, as well as in many other countries, golden eagles were heavily persecuted during the 19th-20th centuries, disappearing from southern regions and reaching their lowest population size in the 1950-1960s. Although conservation efforts facilitated demographic recovery, the long-term genomic consequences of the bottleneck remained unknown. Here, we used whole-genome sequencing data spanning 136 years to evaluate patterns of genetic diversity in 26 Finnish golden eagles before, during, and after the mid-20th century bottleneck. We found substantial loss of genetic variation, including an 82% reduction in genome-wide heterozygosity, a 42% decline in nucleotide diversity, a 67% reduction in Watterson's theta, and a substantial loss of variable sites. Analyses of the site frequency spectrum and Tajima's D confirmed historical population contraction, and runs of homozygosity analysis indicated elevated post-bottleneck inbreeding. These results indicate strong genetic erosion in Finnish golden eagles despite the census size recovery. Therefore, incorporating genomic indicators in conservation monitoring and performing regional assessments are necessary to guide management and preserve biodiversity in line with the Global Biodiversity Framework's goal of maintaining genetic variation.

genomics↗

Long-read analysis of complete human 5S rDNA arrays reveals a zoned organization with two-state unit methylation linked to chromatin architecture

Despite the fundamental importance of the 5S ribosomal DNA (rDNA) to all cellular life, the landscape of its units by position along its array has remained poorly understood. Here, recent telomere-to-telomere long-read sequencing is used to resolve 5S rDNA arrays from flank to flank and to follow the state of each unit along single molecules. The array is zoned at both the sequence and the epigenetic level. Notably, methylation is bimodal at the level of the unit, and the combination of low-methylation and high-methylation units gives rise to the overall methylation pattern of the array. Moreover, the average number of low-methylation units remains relatively constant regardless of array length. Chromatin fiber sequencing (Fiber-seq) data further show that low-methylation units are more accessible, have lower nucleosome occupancy and are more frequently footprinted at the TFIIIB-binding site, consistent with analyses of ATAC-seq and ChIP-seq data from cell lines. Across species, this pattern is shared among apes, whereas other species show diverse patterns. These results provide a unit-resolved view of the human 5S rDNA array and reveal a zone-specific organization of unit methylation that is associated with chromatin architecture.

genomics↗

Using Oyster Genomics to Understand Human Health

As sessile filter feeders that experience continuous environmental exposure, oysters, particularly Crassostrea virginica, offer a unique opportunity to understand how environmental exposure alters the genome and influence health. Furthermore, oysters must be sorted by size for market value for premium size and taste. However, it requires intensive labor, specialized equipment (tumblers), and is susceptible to environmental risks like pollution. Therefore, it is desirable to produce uniform oysters without machines. However, limitations in the previous reference genome [2] have constrained our understanding of how genes are organized and maintained in oyster populations. To this end, we harvested 240 adult oysters in same location, 120 extremely large size and 120 extremely small, controlled with all confounding factors such as age and water temperature. We perform a genome wise associate study (GWAS) using next generation whole genome sequencing, aiming to discover genomic regions associated with oyster size. Using PacBio HiFi, Illumina, and Hi-C technologies, we generated a 99.7% complete chromosome-level genome assembly for C. virginica (NCBI RefSeq GCF_053477285.1) [75]. We identified a ~13 Mb region on chromosome 1 uniquely expanded in C. virginica and enriched for innate immune and stress-response genes. To evaluate whether these structural features are reflected at the population level, we then conducted a k-mer analysis. This revealed differential sequence patterns by size, including enrichment of bacterial DNA in smaller individuals and host variation at the RNF213 locus within this region. By highlighting genome structure as a mediator of immune resilience, this work supports the use of oysters as sentinels to advance out understanding of how the dynamic reassembly of the genome due to environmental exposures influence health in human populations.

genomics↗