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The horizonal transfer of plasmid-encoded genes allows bacteria to adapt to constantly shifting environmental pressures, bestowing functional advantages to their bacterial hosts such as antibiotic resistance, metal resistance, virulence factors, and polysaccharide utilization. However, common molecular methods such as short- and long-read sequencing of microbiomes cannot associate extrachromosomal plasmids with the genome of the host bacterium. Alternative methods to link plasmids to host bacteria are either laborious, expensive, or prone to contamination. Here we present the One-step Isolation and Lysis PCR (OIL-PCR) method, which molecularly links plasmid-encoded genes with the bacterial 16S rRNA gene via fusion PCR performed within an emulsion. After validating this method, we apply it to identify the bacterial hosts of three clinically relevant beta-lactamases within the gut microbiomes of neutropenic patients, as they are particularly vulnerable multidrug-resistant infections. We successfully detect the known association of a multi-drug resistant plasmid with Klebsiella pneumoniae , as well as the novel associations of two low-abundance genera, Romboutsia and Agathobacter . Further investigation with OIL-PCR confirmed that our detection of Romboutsia is due to its physical association with Klebsiella as opposed to directly harboring the beta-lactamase genes. Here we put forth a robust, accessible, and high-throughput platform for sensitively surveying the bacterial hosts of mobile genes, as well as detecting physical bacterial associations such as those occurring within biofilms and complex microbial communities. 

Bacteria acquire novel DNA through horizontal gene transfer (HGT), a process that enables an organism to rapidly adapt to changing environmental conditions, provides a competitive edge and potentially alters its relationship with its host. Although the HGT process is routinely exploited in laboratories, there is a surprising disconnect between what we know from laboratory experiments and what we know from natural environments, such as the human gut microbiome. Owing to a suite of newly available computational algorithms and experimental approaches, we have a broader understanding of the genes that are being transferred and are starting to understand the ecology of HGT in natural microbial communities. This Review focuses on these new technologies, the questions they can address and their limitations. As these methods are applied more broadly, we are beginning to recognize the full extent of HGT possible within a microbiome and the punctuated dynamics of HGT, specifically in response to external stimuli. Furthermore, we are better characterizing the complex selective pressures on mobile genetic elements and the mechanisms by which they interact with the bacterial host genome.