Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts

Abstract

The gut microbiota is a reservoir for antimicrobial resistance genes (ARGs). With current sequencing methods, it is difficult to assign ARGs to their microbial hosts, particularly if these ARGs are located on plasmids. Metagenomic chromosome conformation capture approaches (meta3C and Hi-C) have recently been developed to link bacterial genes to phylogenetic markers, thus potentially allowing the assignment of ARGs to their hosts on a microbiome-wide scale. Here, we generated a meta3C dataset of a human stool sample and used previously published meta3C and Hi-C datasets to investigate bacterial hosts of ARGs in the human gut microbiome. Sequence reads mapping to repetitive elements were found to cause problematic noise in, and may importantly skew interpretation of, meta3C and Hi-C data. We provide a strategy to improve the signal-to-noise ratio by discarding reads that map to insertion sequence elements and to the end of contigs. We also show the importance of using spike-in controls to quantify whether the cross-linking step in meta3C and Hi-C protocols has been successful. After filtering to remove artefactual links, 87 ARGs were assigned to their bacterial hosts across all datasets, including 27 ARGs in the meta3C dataset we generated. We show that commensal gut bacteria are an important reservoir for ARGs, with genes coding for aminoglycoside and tetracycline resistance being widespread in anaerobic commensals of the human gut.

Host- plasmid network structure in wastewater is linked to antimicrobial resistance genes

“…Any contigs that did not identify as either of these elements were automatically removed from the dataset. Contigs that were identified as potential transposons were removed from the dataset, as their ubiquity can generate spurious associations 51 . Transposons and IS elements were identified by performing a homology search with BLASTp on predicted genes from all contigs using an e -value < 0.01 against all known transposase proteins from the databases from IS finder 52 available from https://github.com/thanhleviet/ISfinder-sequences/blob/master/README.md and from Tn3 Transposon Finder 53 available from https://tncentral.proteininformationresource.org/TnFinder.html .…”