Plasmids are self-replicating genetic elements capable of mobilization between different hosts. Plasmids often serve as mediators of lateral gene transfer, a process considered to be a strong and sculpting evolutionary force in microbial environments. Our aim was to characterize the overall plasmid population in the environment of the bovine rumen, which houses a complex and dense microbiota that holds enormous significance for humans. We developed a procedure for the isolation of total rumen plasmid DNA, termed rumen plasmidome, and subjected it to deep sequencing using the Illumina paired-end protocol and analysis using public and custom-made bioinformatics tools. A large number of plasmidome contigs aligned with plasmids of rumen bacteria isolated from different locations and at various time points, suggesting that not only the bacterial taxa, but also their plasmids, are defined by the ecological niche. The bacterial phylum distribution of the plasmidome was different from that of the rumen bacterial taxa. Nevertheless, both shared a dominance of the phyla Firmicutes, Bacteroidetes, and Proteobacteria. Evidently, the rumen plasmidome is of a highly mosaic nature that can cross phyla. Interestingly, when we compared the functional profile of the rumen plasmidome to two plasmid databases and two recently published rumen metagenomes, it became apparent that the rumen plasmidome codes for functions, which are enriched in the rumen ecological niche and could confer advantages to their hosts, suggesting that the functional profiles of mobile genetic elements are associated with their environment, as has been previously implied for viruses.

MotivationPlasmids and other mobile elements are central contributors to microbial evolution and genome innovation. Recently, they have been found to have important roles in antibiotic resistance and in affecting production of metabolites used in industrial and agricultural applications. However, their characterization through deep sequencing remains challenging, in spite of rapid drops in cost and throughput increases for sequencing. Here, we attempt to ameliorate this situation by introducing a new circular element assembly algorithm, leveraging assembly graphs provided by a conventional de novo assembler and alignments of paired-end reads to assemble cyclic sequences likely to be plasmids, phages and other circular elements.ResultsWe introduce Recycler, the first tool that can extract complete circular contigs from sequence data of isolate microbial genomes, plasmidome and metagenome sequence data. We show that Recycler greatly increases the number of true plasmids recovered relative to other approaches while remaining highly accurate. We demonstrate this trend via simulations of plasmidomes, comparisons of predictions with reference data for isolate samples, and assessments of annotation accuracy on metagenome data. In addition, we provide validation by DNA amplification of 77 plasmids predicted by Recycler from the different sequenced samples in which Recycler showed mean accuracy of 89% across all data types—isolate, microbiome and plasmidome.Availability and ImplementationRecycler is available at http://github.com/Shamir-Lab/RecyclerSupplementary information Supplementary data are available at Bioinformatics online.

Motivation: Plasmids and other mobile elements are central contributors to microbial evolution and genome innovation. Recently, they have been found to have important roles in antibiotic resistance and in affecting production of metabolites used in industrial and agricultural applications. However, their characterization through deep sequencing remains challenging, in spite of rapid drops in cost and throughput increases for sequencing. Here, we attempt to ameliorate this situation by introducing a new circular element assembly algorithm, leveraging assembly graphs provided by a conventional de novo assembler and alignments of paired-end reads to assemble cyclic sequences likely to be plasmids, phages and other circular elements. Results: We introduce Recycler, the first tool that can extract complete circular contigs from sequence data of isolate microbial genomes, plasmidome and metagenome sequence data. We show that Recycler greatly increases the number of true plasmids recovered relative to other approaches while remaining highly accurate. We demonstrate this trend via simulations of plasmidomes, comparisons of predictions with reference data for isolate samples, and assessments of annotation accuracy on metagenome data. In addition, we provide validation by DNA amplification of 77 plasmids predicted by Recycler from the different sequenced samples in which Recycler showed mean accuracy of 89% across all data types-isolate, microbiome and plasmidome.

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SummaryHorizontal gene transfer via plasmids plays a pivotal role in microbial evolution. The forces that shape plasmidomes functionality and distribution in natural environments are insufficiently understood. Here, we present a comparative study of plasmidomes across adjacent microbial environments present in different individual rumen microbiomes. Our findings show that the rumen plasmidome displays enormous unknown functional potential currently unannotated in available databases. Nevertheless, this unknown functionality is conserved and shared with published rat gut plasmidome data. Moreover, the rumen plasmidome is highly diverse compared with the microbiome that hosts these plasmids, across both similar and different rumen habitats. Our analysis demonstrates that its structure is shaped more by stochasticity than selection. Nevertheless, the plasmidome is an active partner in its intricate relationship with the host microbiome with both interacting with and responding to their environment.

Antimicrobial resistance (AMR) is a significant threat to public health. Plasmids are principal vectors of AMR genes, significantly contributing to their spread and mobility across hosts. Nevertheless, little is known about the dynamics of plasmid genetic exchange across animal hosts. Here, we use theory and methodology from network and disease ecology to investigate the potential of gene transmission between plasmids using a data set of 21 plasmidomes from a single dairy cow population. We constructed a multilayer network based on pairwise plasmid genetic similarity. Genetic similarity is a signature of past genetic exchange that can aid in identifying potential routes and mechanisms of gene transmission within and between cows. Links between cows dominated the transmission network, and plasmids containing mobility genes were more connected. Modularity analysis revealed a network cluster where all plasmids contained a mobM gene, and one where all plasmids contained a beta-lactamase gene. Cows that contain both clusters also share transmission pathways with many other cows, making them candidates for super-spreading. In support, we found signatures of gene super-spreading in which a few plasmids and cows are responsible for most gene exchange. An agent-based transmission model showed that a new gene invading the cow population will likely reach all cows. Finally, we showed that edge weights contain a non-random signature for the mechanisms of gene transmission, allowing us to differentiate between dispersal and genetic exchange. These results provide insights into how genes, including those providing AMR, spread across animal hosts.

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Antimicrobial resistance (AMR) is a major threat to public health. Plasmids are principal vectors of antimicrobial resistance genes, greatly contributing to their spread and mobility across hosts. Nevertheless little is known about the dynamics of plasmid genetic exchange across animal hosts. The cow rumen ecosystem is an excellent model system because it hosts diverse plasmid communities which interact and exchange genes. Here, we use theory and methodology from network and disease ecology to investigate the potential of gene transmission between plasmids using a data-set of 21 plasmidomes from a single dairy cow population. We constructed a multilayer network based on pairwise genetic similarity between plasmids serving as a signature for past genetic exchange to identify potential routes and mechanisms of gene transmission within and between cows. The transmission network was dominated by links between cows. Modularity analysis unraveled a major cross-cow transmission pathway with additional small pathways. Plasmid functions influenced network structure: plasmids containing mobility genes were more connected; those with the same AMR genes formed their own modules. We find signatures of gene superspreading in which a few plasmids and cows are responsible for most gene exchange. An agent-based transmission model showed that a new gene invading the cow population is likely to reach all cows. Finally, we showed that link weights contain a non-random signature for the mechanisms of gene transmission allowing us to differentiate between dispersal and genetic exchange. These results provide insights into the mechanisms by which genes, including those providing AMR, spread across animal hosts.