ResFinder - an open online resource for identification of antimicrobial resistance genes in next-generation sequencing data and prediction of phenotypes from genotypes.

Antimicrobial resistance (AMR) is one of the most important health threats globally. The ability to accurately identify resistant bacterial isolates and the individual antimicrobial resistance genes (ARGs) is essential for understanding the evolution and emergence of AMR and to provide appropriate treatment. The rapid developments in next-generation sequencing technologies have made this technology available to researchers and microbiologists at routine laboratories around the world. However, tools available for those with limited experience with bioinformatics are lacking, especially to enable researchers and microbiologists in low- and middle-income countries (LMICs) to perform their own studies. The CGE-tools (Center for Genomic Epidemiology) including ResFinder (https://cge.cbs.dtu.dk/services/ResFinder/) was developed to provide freely available easy to use online bioinformatic tools allowing inexperienced researchers and microbiologists to perform simple bioinformatic analyses. The main purpose was and is to provide these solutions for people involved in frontline diagnosis especially in LMICs. Since its original publication in 2012, ResFinder has undergone a number of improvements including improvement of the code and databases, inclusion of point mutations for selected bacterial species and predictions of phenotypes also for selected species. As of 28 September 2021, 820 803 analyses have been performed using ResFinder from 61 776 IP-addresses in 171 countries. ResFinder clearly fulfills a need for several people around the globe and we hope to be able to continue to provide this service free of charge in the future. We also hope and expect to provide further improvements including phenotypic predictions for additional bacterial species.

CRHP Finder, a webtool for the detection of clarithromycin resistance in Helicobacter pylori from whole-genome sequencing data.

BACKGROUND: Resistance to clarithromycin in Helicobacter pylori (H pylori) is mediated by mutations in the domain V of the 23S rRNA gene (A2142G, A2143G, A2142C). Other polymorphisms in the 23S rRNA gene have been reported to cause low-level clarithromycin resistance but their importance is still under debate. In this study, we aimed to develop and evaluate the CRHP Finder webtool for detection of the most common mutations mediating clarithromycin resistance from whole-genome sequencing (WGS) data. Moreover, we included an analysis of 23 H pylori strains from Danish patients between January 2017 and September 2019 in Copenhagen, Denmark. MATERIALS AND METHODS: The CRHP Finder detects the fraction of each of the four nucleotides in nucleotide positions 2142, 2143, 2182, 2244 and 2712 of the 23S rRNA gene in H pylori (E coli numbering) by aligning raw sequencing reads (fastq format) with k-mer alignment (KMA). The nucleotide distribution in each position is compared to previously described point mutations mediating clarithromycin resistance in H pylori, and a genotypic prediction of the clarithromycin resistance phenotype is presented as output. For validation of the CRHP webtool, 137 fastq paired-end sequencing datasets originating from a well-characterized strain collection of H pylori were analyzed. RESULTS: The CRHP Finder correctly identified all resistance mutations reported in the sequencing data of 137 H pylori strains. In the 23 Danish H pylori strains, CRHP Finder detected A2143G (13%) in all resistant strains, and T2182C (13%) and C2244T (4,3%) nucleotide exchanges in only susceptible strains. CONCLUSION: In this study, we present the validation of the first webtool for H pylori resistance prediction based on the detection of 23S rRNA mutations (A2142C, A2142G, A2143G, T2182C, C2244T, T2712C) from WGS data of H pylori.

Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage.

Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.