Recent work has underscored the importance of the microbiome in human health, largely attributing differences in phenotype to differences in the species present across individuals1,2,3,4,5. But mobile genes can confer profoundly different phenotypes on different strains of the same species. Little is known about the function and distribution of mobile genes in the human microbiome, and in particular whether the gene pool is globally homogenous or constrained by human population structure. Here, we investigate this question by comparing the mobile genes found in the microbiomes of 81 metropolitan North Americans with that of 172 agrarian Fiji islanders using a combination of single-cell genomics and metagenomics. We find large differences in mobile gene content between the Fijian and North American microbiomes, with functional variation that mirrors known dietary differences such as the excess of plant-based starch degradation genes. Remarkably, differences are also observed between the mobile gene pools of proximal Fijian villages, even though microbiome composition across villages is similar. Finally, we observe high rates of recombination leading to individual-specific mobile elements, suggesting that the abundance of some genes may reflect environmental selection rather than dispersal limitation. Together, these data support the hypothesis that human activities and behaviors provide selective pressures that shape mobile gene pools, and that acquisition of mobile genes is important to colonizing specific human populations.

Many microbial communities are characterized by high genetic diversity. 16S ribosomal RNA sequencing can determine community members, and metagenomics can determine the functional diversity, but resolving the functional role of individual cells in high throughput remains an unsolved challenge. Here, we describe epicPCR (Emulsion, Paired Isolation and Concatenation PCR), a new technique that links functional genes and phylogenetic markers in uncultured single cells, providing a throughput of hundreds of thousands of cells with costs comparable to one genomic library preparation. We demonstrate the utility of our technique in a natural environment by profiling a sulfate-reducing community in a freshwater lake, revealing both known sulfate reducers and discovering new putative sulfate reducers. Our method is adaptable to any conserved genetic trait and translates genetic associations from diverse microbial samples into a sequencing library that answers targeted ecological questions. Potential applications include identifying functional community members, tracing horizontal gene transfer networks and mapping ecological interactions between microbial cells.

The prophylactic and therapeutic use of tetracyclines in aquaculture has been shown to contribute to the spread of tetracycline resistance in the environment. In this work, the prevalence of four different tetracycline-resistance genes, tetA, tetC, tetH, and tetM, in sediments from four aquaculture farms and their surroundings in the Baltic Sea was monitored by quantitative polymerase chain reaction (qPCR). The presence of three additional tetracycline-resistance genes (tetE, tetG, and tetW) was studied qualitatively by standard PCR, and the amount of bioavailable tetracyclines and total amounts of tetracycline and oxytetracycline in samples were also measured. None of the farms were using tetracycline at the time of the sampling and one of the farms had stopped all antibiotic use six years prior to the first sampling. Two of the farms were sampled over four successive summers and two were sampled once. Our results showed greater copy numbers of tetA, tetC, tetH, and tetM at the farms compared to pristine sites and demonstrated the presence of tetE, tetG, and tetW genes in the sediments under aquaculture farms at most sampling times. However, no resistance genes were found in samples collected 200 m from any of the farms. None of the samples contained therapeutically active concentrations of tetracyclines at any of the sampling times, suggesting that the increase in the prevalence of tetracycline resistance genes is caused by the persistence of these genes in the absence of selection pressure.

Wastewater treatment plants (WWTPs) collect wastewater from various sources for a multi-step treatment process. By mixing a large variety of bacteria and promoting their proximity, WWTPs constitute potential hotspots for the emergence of antibiotic resistant bacteria. Concerns have been expressed regarding the potential of WWTPs to spread antibiotic resistance genes (ARGs) from environmental reservoirs to human pathogens. We utilized epicPCR (Emulsion, Paired Isolation and Concatenation PCR) to detect the bacterial hosts of ARGs in two WWTPs. We identified the host distribution of four resistance-associated genes (tetM, int1, qacEΔ1and blaOXA-58) in influent and effluent. The bacterial hosts of these resistance genes varied between the WWTP influent and effluent, with a generally decreasing host range in the effluent. Through 16S rRNA gene sequencing, it was determined that the resistance gene carrying bacteria include both abundant and rare taxa. Our results suggest that the studied WWTPs mostly succeed in decreasing the host range of the resistance genes during the treatment process. Still, there were instances where effluent contained resistance genes in bacterial groups not carrying these genes in the influent. By permitting exhaustive profiling of resistance-associated gene hosts in WWTP bacterial communities, the application of epicPCR provides a new level of precision to our resistance gene risk estimates.

Plasmids are vessels of genetic exchange in microbial communities. They are known to transfer between different host organisms and acquire diverse genetic elements from chromosomes and/or other plasmids. Therefore, they constitute an important element in microbial evolution by rapidly disseminating various genetic properties among different communities. A paradigmatic example of this is the dissemination of antibiotic resistance (AR) genes that has resulted in the emergence of multiresistant pathogenic bacterial strains. To globally analyze the evolutionary dynamics of plasmids, we built a large graph in which 2,343 plasmids (nodes) are connected according to the proteins shared by each other. The analysis of this gene-sharing network revealed an overall coherence between network clustering and the phylogenetic classes of the corresponding microorganisms, likely resulting from genetic barriers to horizontal gene transfer between distant phylogenetic groups. Habitat was not a crucial factor in clustering as plasmids from organisms inhabiting different environments were often found embedded in the same cluster. Analyses of network metrics revealed a statistically significant correlation between plasmid mobility and their centrality within the network, providing support to the observation that mobile plasmids are particularly important in spreading genes in microbial communities. Finally, our study reveals an extensive (and previously undescribed) sharing of AR genes between Actinobacteria and Gammaproteobacteria, suggesting that the former might represent an important reservoir of AR genes for the latter.

The spatial distribution of microbes on our planet is famously formulated in the Baas Becking hypothesis as “everything is everywhere but the environment selects.” While this hypothesis does not strictly rule out patterns caused by geographical effects on ecology and historical founder effects, it does propose that the remarkable dispersal potential of microbes leads to distributions generally shaped by environmental factors rather than geographical distance. By constructing sequence similarity networks from uncultured environmental samples, we show that microbial gene pool distributions are not influenced nearly as much by geography as ecology, thus extending the Bass Becking hypothesis from whole organisms to microbial genes. We find that gene pools are shaped by their broad ecological niche (such as sea water, fresh water, host, and airborne). We find that freshwater habitats act as a gene exchange bridge between otherwise disconnected habitats. Finally, certain antibiotic resistance genes deviate from the general trend of habitat specificity by exhibiting a high degree of cross-habitat mobility. The strong cross-habitat mobility of antibiotic resistance genes is a cause for concern and provides a paradigmatic example of the rate by which genes colonize new habitats when new selective forces emerge.

Antibiotic resistance among bacteria is a growing problem worldwide, and wastewater treatment plants have been considered as one of the major contributors to the dissemination of antibiotic resistance to the environment. There is a lack of comprehensive quantitative molecular data on extensive numbers of antibiotic resistance genes (ARGs) in different seasons with a sampling strategy that would cover both incoming and outgoing water together with the excess sludge that is removed from the process. In order to fill that gap we present a highly parallel quantitative analysis of ARGs and horizontal gene transfer potential over four seasons at an urban wastewater treatment plant using a high-throughput qPCR array. All analysed transposases and two-thirds of primer sets targeting ARGs were detected in the wastewater. The relative abundance of most of the genes was highest in influent and lower in effluent water and sludge. The resistance profiles of the samples cluster by sample location with a shift from raw influent through the final effluents and dried sludge to the sediments. Wastewater discharge enriched only a few genes, namely Tn25 type transposase gene and clinical class 1 integrons, in the sediment near the discharge pipe, but those enriched genes may indicate a potential for horizontal gene transfer.

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