Determination and quantification of microbial communities and antimicrobial resistance on food through host DNA-depleted metagenomics

Abstract

Food products carry bacteria unless specifically sterilised. These bacteria can be pathogenic, commensal or associated with food spoilage, and may also be resistant to antimicrobials. Current methods for detecting bacteria on food rely on culturing for specific bacteria, a time-consuming process, or 16S rRNA metabarcoding that can identify different taxa but not their genetic content. Directly sequencing metagenomes of food is inefficient as its own DNA vastly outnumbers the bacterial DNA present. We optimised host DNA depletion enabling efficient sequencing of food microbiota, thereby increasing the proportion of non-host DNA sequenced 13-fold (mean; range: 1.3–40-fold) compared to untreated samples. The method performed best on chicken, pork and leafy green samples which had high mean prokaryotic read proportions post-depletion (0.64, 0.74 and 0.74, respectively), with lower mean prokaryotic read proportions in salmon (0.50) and prawn samples (0.19). We show that bacterial compositions and concentrations of antimicrobial resistance (AMR) genes differed by food type, and that salmon metagenomes were influenced by the production/harvesting method. The approach described in this study is an efficient and effective method of identifying and quantifying the predominant bacteria and AMR genes on food.