Target-enriched metagenomics-informed qPCR detects rare, potentially dangerous β-lactamase genes in wastewater

Abstract

The rapid emergence of novel antibiotic resistance genes (ARGs) decreases the effectiveness of empirical antibiotic treatment for pathogen infections. Environmental ARG surveillance is an early-warning approach that can better inform antibiotic usage. Quantitative polymerase chain reaction (qPCR) is widely used for ARG surveillance because qPCR is easy, fast, and highly sensitive. However, it can only identify DNA targeted by pre-selected primers. In contrast, metagenomic sequencing can identify ARGs agnostically. However, sequencing is more expensive, less sensitive, and requires lengthy analysis of complex data sets. Target-enrichment metagenomic sequencing (TEMS), a method we developed previously, can mitigate the disadvantage of low sensitivity of traditional metagenomic sequencing. In this study, we propose a hybrid ARG surveillance pipeline for wastewater that capitalizes on both TEMS and qPCR. It uses a large-scale target determination of ARGs by using TEMS, followed by fine-scale routine surveillance of ARGs using qPCR. To connect the two steps, we developed a primer design tool, MSEDAP, which automatically analyzes metagenomic sequencing data and designs qPCR primers for ARG surveillance. This new workflow was ground-truthed using wastewater samples. TEMS identified seventeen {beta}-lactamase gene targets of potential clinical importance. qPCR validated their presence and abundance using primers generated by MSEDAP. SynopsisA metagenomics-qPCR hybrid scheme can be used for environmental surveillance of antibiotic resistance genes (ARGs) to discover emerging ARGs originating from communities. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=110 SRC="FIGDIR/small/665820v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@625e06org.highwire.dtl.DTLVardef@ae34aorg.highwire.dtl.DTLVardef@d03e7borg.highwire.dtl.DTLVardef@1b625a9_HPS_FORMAT_FIGEXP M_FIG C_FIG