Large-scale assessment of antimicrobial resistance marker databases for genetic phenotype prediction: a systematic review

Abstract

Background Antimicrobial resistance (AMR) is a rising health threat with 10 million annual casualties estimated by 2050. Appropriate treatment of infectious diseases with the right antibiotics reduces the spread of antibiotic resistance. Today, clinical practice relies on molecular and PCR techniques for pathogen identification and culture-based antibiotic susceptibility testing (AST). Recently, WGS has started to transform clinical microbiology, enabling prediction of resistance phenotypes from genotypes and allowing for more informed treatment decisions. WGS-based AST (WGS-AST) depends on the detection of AMR markers in sequenced isolates and therefore requires AMR reference databases. The completeness and quality of these databases are material to increase WGS-AST performance. Methods We present a systematic evaluation of the performance of publicly available AMR marker databases for resistance prediction on clinical isolates. We used the public databases CARD and ResFinder with a final dataset of 2587 isolates across five clinically relevant pathogens from PATRIC and NDARO, public repositories of antibiotic-resistant bacterial isolates. Results CARD and ResFinder WGS-AST performance had an overall balanced accuracy of 0.52 (±0.12) and 0.66 (±0.18), respectively. Major error rates were higher in CARD (42.68%) than ResFinder (25.06%). However, CARD showed almost no very major errors (1.17%) compared with ResFinder (4.42%). Conclusions We show that AMR databases need further expansion, improved marker annotations per antibiotic rather than per antibiotic class and validated multivariate marker panels to achieve clinical utility, e.g. in order to meet performance requirements such as provided by the FDA for clinical microbiology diagnostic testing.

Limited and Strain-Specific Transcriptional and Growth Responses to Acquisition of a Multidrug Resistance Plasmid in Genetically Diverse Escherichia coli Lineages

“…In addition, F022 and F047 carry bla TEM-1 but vary in their cefotaxime resistance responses, suggesting that bla TEM-1 does not explain the variable resistance response. This is perhaps unsurprising as the prediction of a strain’s resistance phenotype from gene content alone is notoriously inaccurate ( 23 ).…”

Taxonomic Identification of Different Species of the Genus Aeromonas by Whole-Genome Sequencing and Use of Their Species-Specific β-Lactamases as Phylogenetic Markers

“…As it is mandatory to use more than one public resistance database, we found that, using the ResFinder and CARD, some entries were exclusive to either one or the other: bla AmpS and bla AmpH only appeared in ResFinder and bla AQU-1 , bla AQU-2 , bla MOX-9 and bla CepS were exclusive to CARD. These specific entries yielded matches with higher identities for our query sequences, indicating that completeness is essential for proper diagnosis and that more than one curated database for antimicrobial resistance genes should be used when screening isolates [ 37 ]. Nevertheless, regarding Aeromonas resistance genes, both ResFinder and CARD are good tools for screening, but we found that the percentage of identity for many species-specific resistance genes, such as bla AmpC of A. hydrophila and bla OXA -like of A. caviae , was too low.…”

Performance characteristics of next-generation sequencing for antimicrobial resistance gene detection in genomes and metagenomes

“…A large majority of the AMR genes detected in the E. coli ST38 isolate and across the E. coli isolate set were efflux-associated AMR genes. Efflux-associated genes are of uncertain relevance for prediction of microbial phenotypes 36,37 . In some scenarios (e.g.…”