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Background Metagenomic sequencing has led to the identification and assembly of many new bacterial genome sequences. These bacteria often contain plasmids: usually small, circular double-stranded DNA molecules that may transfer across bacterial species and confer antibiotic resistance. These plasmids are generally less studied and understood than their bacterial hosts. Part of the reason for this is insufficient computational tools enabling the analysis of plasmids in metagenomic samples. Results We developed SCAPP (Sequence Contents-Aware Plasmid Peeler)—an algorithm and tool to assemble plasmid sequences from metagenomic sequencing. SCAPP builds on some key ideas from the Recycler algorithm while improving plasmid assemblies by integrating biological knowledge about plasmids. We compared the performance of SCAPP to Recycler and metaplasmidSPAdes on simulated metagenomes, real human gut microbiome samples, and a human gut plasmidome dataset that we generated. We also created plasmidome and metagenome data from the same cow rumen sample and used the parallel sequencing data to create a novel assessment procedure. Overall, SCAPP outperformed Recycler and metaplasmidSPAdes across this wide range of datasets. Conclusions SCAPP is an easy to use Python package that enables the assembly of full plasmid sequences from metagenomic samples. It outperformed existing metagenomic plasmid assemblers in most cases and assembled novel and clinically relevant plasmids in samples we generated such as a human gut plasmidome. SCAPP is open-source software available from: https://github.com/Shamir-Lab/SCAPP.

Microbial communities in many environments include distinct lineages of closely related organisms which have proved challenging to separate in metagenomic assembly, preventing generation of complete metagenome-assembled genomes (MAGs). The advent of long and accurate HiFi reads presents a possible means to address this challenge by generating complete MAGs for nearly all sufficiently abundant bacterial genomes in a microbial community. We present a metagenomic HiFi assembly of a complex microbial community from sheep fecal material that resulted in 428 high-quality MAGs from a single sample, the highest resolution achieved with metagenomic deconvolution to date. We applied a computational approach to separate distinct haplotype lineages and identified haplotypes of hundreds of variants across hundreds of kilobases of genomic sequence. Analysis of these haplotypes revealed 220 lineage-resolved complete MAGs, including 44 in single circular contigs, and demonstrated improvement in overall assembly compared to error-prone long reads. We report the characterization of multiple, closely-related microbes within a sample with potential to improve precision in assigning mobile genetic elements to host genomes within complex microbial communities.

Motivation: Metagenomic sequencing has led to the identification and assembly of many new bacterial genome sequences. These bacteria often contain plasmids, which are less studied or understood. In order to assist in the study of these plasmids we developed SCAPP (Sequence Contents Aware Plasmid Peeler) -an algorithm and tool to assemble plasmid sequences from metagenomic sequencing. Results: SCAPP builds on some key ideas from the Recycler plasmid assembly algorithm while improving plasmid assemblies by integrating biological knowledge about plasmids. We compared performance of SCAPP to Recycler and metaplasmidSPAdes on simulated metagenomes, real human gut microbiome samples, and a human gut plasmidome that we generated. We also created a parallel plasmidome-metagenome cow rumen sample and used it to create a novel assessment procedure. In most cases SCAPP performed better than or similar to Recycler and meta-plasmidSPAdes across this wide range of datasets. Availability: https://github.com/Shamir-Lab/SCAPP

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.

The ESCRT machinery drive membrane remodeling in numerous processes in eukaryotes. Genes encoding for ESCRT proteins have been identified in Asgard archaea, a newly discovered superphylum, currently recognized as the ancestor of all eukaryotes. This begs the question of the functional evolutionary origin of this machinery and its conservation across lineages. Here, we find that Asgard-ESCRT’s exhibit conserved DNA-binding properties, which is derived from recruitment of specific members. We show that Asgard-ESCRT-III/VPS4 homologs interact with one another inside mammalian cells, associate with chromatin, and recruit their counterparts to organize in discrete foci in the mammalian nucleus. This is congruent with human-ESCRT-III homologs. We find that human- and Asgard-ESCRT-IIIs associate with chromatin via the same N terminal domain, and that human-ESCRT-III can recruit Asgard-VPS4 to the nucleus to form foci. Therefore, ESCRTs possess chromatin binding properties that were preserved through the billion years of evolution that separate Asgard and human cells.

The archaeal Asgard superphylum currently stands as the most promising prokaryotic candidate, from which eukaryotic cells emerged. This unique superphylum encodes for eukaryotic signature proteins (ESP) that could shed light on the origin of eukaryotes, but the properties and function of these proteins is largely unresolved. Here, we set to understand the function of an Asgard archaeal protein family, namely the ESCRT machinery, that is conserved across all domains of life and executes basic cellular eukaryotic functions, including membrane constriction during cell division. We find that ESCRT proteins encoded in Loki archaea, express in mammalian and yeast cells, and that the Loki ESCRT-III protein, CHMP4-7, resides in the eukaryotic nucleus in both organisms. Moreover, Loki ESCRT-III proteins associated with chromatin, recruited their AAA-ATPase VPS4 counterpart to organize in discrete foci in the mammalian nucleus, and directly bind DNA. The human ESCRT-III protein, CHMP1B, exhibited similar nuclear properties and recruited both human and Asgard VPS4s to nuclear foci, indicating interspecies interactions. Mutation analysis revealed a role for the N terminal region of ESCRT-III in mediating these phenotypes in both human and Asgard ESCRTs. These findings suggest that ESCRT proteins hold chromatin binding properties that were highly preserved through the billion years of evolution separating Asgard archaea and humans. The conserved chromatin binding properties of the ESCRT membrane remodeling machinery, reported here, may have important implications for the origin of eukaryogenesis.

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.