Galaxy ASIST: A web-based platform for mapping and assessment of global standards of antimicrobial susceptibility: A case study in Acinetobacter baumannii genomes - Sharma, Tina; Kumar, Rakesh; Kalra, Jasmeer Singh; Singh, Shreya; Bhalla, Gurpreet Singh; Bhardwaj, Anshu (Frontiers in Microbiology, 2023)
Introduction Antimicrobial susceptibility testing (AST) is used to determine the susceptibility of an organism to antibiotics. The determination of susceptibility is based on MIC breakpoints and is provided by EUCAST and CLSI. Likewise, phenotypic classification criteria developed by CDC/ECDC are used for the classification of pathogens into susceptible, multidrug-resistant, extremely drug-resistant, or totally drug-resistant categories. Whole-genome sequencing (WGS)-based diagnosis is now supplementing existing gold-standard microbiology methods for rapid and more precise AST, and therefore, EUCAST recommended quality criteria to assess whole-genome sequence for reporting the same. In this study, these three global standards, MIC breakpoints, phenotypic classification, and genome quality, are applied to the largest publicly available data for Acinetobacter baumannii (AB), the most critical priority pathogen identified by WHO. Materials and Methods The drug sensitivity profile and genomes for isolates of AB were obtained from PATRIC and evaluated with respect to AST standards (CLSI and EUCAST). Whole genome quality assessment and antimicrobial resistance mapping is performed with QUAST and ABRicate, respectively. Four in-house methods are developed for mapping standards and are integrated into a Galaxy workflow based system, Galaxy-ASIST. Analysis of the extent of agreement between CLSI 2022 and EUCAST 2022 for antibiotics was carried out using Cohen’s kappa statistics. Results and Discussion An automated pipeline, Galaxy-ASIST, is designed and developed for the characterization of clinical isolates based on these standards. Evaluation of over 6,500 AB strains using Galaxy-ASIST indicated that only 10% of the publicly available datasets have metadata to implement these standards. Furthermore, given that CLSI and EUCAST have different MIC breakpoints, discrepancies are observed in the classification of resistant and susceptible isolates following these standards. It is, therefore, imperative that platforms are developed that allow the evaluation of ever increasing phenotypic and genome sequence datasets for AST. Galaxy-ASIST offers a centralized repository and a structured metadata architecture to provide a single globally acceptable framework for AST profiling of clinical isolates based on global standards. The platform also offers subsequent fine mapping of antimicrobial-resistant determinants. Galaxy-ASIST is freely available at https://ab-openlab.csir.res.in/asist.