ARGminer: A web platform for crowdsourcing-based curation of antibiotic resistance genes

Abstract

15Curation of antibiotic resistance gene (ARG) databases is a labor-intensive process that 16 requires expert knowledge to manually collect, correct, and/or annotate individual 17 genes. Correspondingly, updates to existing databases tend to be infrequent, commonly 18 requiring years for completion and often containing inconsistences. Further, because of 19 limitations of manual curation, most existing ARG databases contain only a small 20 proportion of known ARGs (~5k genes). A new approach is needed to achieve a truly 21 comprehensive ARG database, while also maintaining a high level of accuracy. Here we 22propose a new web-based curation system, ARG-miner, which supports annotation of 23ARGs at multiple levels, including: gene name, antibiotic category, resistance 24NC 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/274282 doi: bioRxiv preprint first posted online Mar. 1, 2018; 2 mechanism, and evidence for mobility and occurrence in clinically-important bacterial 25 strains. To overcome limitations of manual curation, we employ crowdsourcing as a 26 novel strategy for expanding curation capacity towards achieving a truly comprehensive, 27 up-to-date database.We develop and validate the approach by comparing 28 performance of multiple cohorts of curators with varying levels of expertise, 29 demonstrating that ARG-miner is more cost effective and less time-consuming relative 30 to traditional expert curation. We further demonstrate the reliability of a trust validation 31 filter for rejecting confounding input generated by spammers. Crowdsourcing was found 32 to be as accurate as expert annotation, with an accuracy >90% for the annotation of a 33 diverse test set of ARGs. ARG-miner provides a public API and database available at 34

Probiotics impact the antibiotic resistance gene reservoir along the human GI tract in a person-specific and antibiotic-dependent manner

“…Sequences were aligned to the ARGminer database v.1.1.1 (ref. 53 ) using BLASTP (identity > 85 and length > 60). Only those ARGs previously detected in the assembled contigs were quantified.…”

Using Genomics to Track Global Antimicrobial Resistance

“…At present, at least 47 online available resources for in silico AMR prediction are published in the scientific literature (13, 26, 28–63) (Table 2). They range from basic AMR reference databases that can be embedded in the user's own bioinformatics pipeline, to systems having a well-curated database with integrated search tools.…”

MALDI-TOF Mass Spectrometry and Specific Biomarkers: Potential New Key for Swift Identification of Antimicrobial Resistance in Foodborne Pathogens

“…The real advantage of these tools is that they are intended for scientists who do not necessarily have advanced bioinformatic skills. Many pipelines that are able to predict AMR patterns, such as Resfinder [65], AMRFinder [66], ARGS-OAP [67], SEAR [68] or ARGminer [69] are today online. Historically, Resfinder, developed by the Center for Genomic Epidemiology, was one of the first types of platforms of this kind, and it is a widely used AMR determinant detection program [65].…”