Bait-capture metagenomics for detection of antimicrobial resistance genes and plasmid markers in livestock and a mock community

Citation

Shay et al (2020) Bait-capture metagenomics for detection of antimicrobial resistance genes and plasmid markers in livestock and a mock community. International Conference on Intelligent Systems for Molecular Biology Ottawa - Virtual 2020/07/13

Résumé en langage clair

Bait-capture is a technique where DNA fragments of interest are enriched before sequencing to amplify specific targets. Bait-capture metagenomics allows for gene detection at lower abundance, and with lower sequencing depth, while still allowing detection of novel gene sequences. We designed baits for 4275 antimicrobial resistance (AMR) genes and 266 plasmid markers. We developed a bioinformatic pipeline to detect targets in metagenomic data sets. We tested limit of detection using mock communities and swine, beef, and poultry samples. The bait-capture approach can detect greater AMR gene diversity compared to shotgun sequencing, although bait-capture may be less sensitive for detecting genes not in the target data set.

Résumé

Bait-capture is a technique where DNA fragments of interest are enriched before sequencing by hybridizing with biotinylated probes. Bait-capture metagenomics allows for gene detection at lower abundance, and with lower sequencing depth, while still allowing detection of novel gene sequences. We designed baits for 4275 antimicrobial resistance (AMR) genes from the NCBI AMRFinderPlus database and 266 plasmid markers from the PlasmidFinder database. We developed a Galaxy pipeline to detect targets in metagenomic data sets. We tested limit of detection of shotgun data for multiple pipelines using in silico mock communities. We performed shotgun and bait-capture metagenomics on 36 swine, beef, and poultry samples, and a 35-component in vitro mock community. 98% of expected AMR genes in the mock community were detected from just 1.25 million HiSeq reads with a 90% gene coverage cutoff, while only 60% were detected by shotgun sequencing of the same community with 10 million HiSeq reads. The bait-capture approach can detect greater AMR gene diversity compared to shotgun sequencing, although bait-capture may be less sensitive for detecting genes not in the target data set. A higher gene coverage cutoff can be used with bait-capture sequencing, which allows for distinguishing between alleles within an AMR gene family.