Plasmids in the human gut reveal neutral dispersal and recombination that is overpowered by inflammatory diseases.

Plasmids are pivotal in driving bacterial evolution through horizontal gene transfer. Here, we investigated 3467 human gut microbiome samples across continents and disease states, analyzing 11,086 plasmids. Our analyses reveal that plasmid dispersal is predominantly stochastic, indicating neutral processes as the primary driver of their wide distribution. We find that only 20-25% of plasmid DNA is being selected in various disease states, constraining its distribution across hosts. Selective pressures shape specific plasmid segments with distinct ecological functions, influenced by plasmid mobilization lifestyle, antibiotic usage, and inflammatory gut diseases. Notably, these elements are more commonly shared within groups of individuals with similar health conditions, such as Inflammatory Bowel Disease (IBD), regardless of geographic location across continents. These segments contain essential genes such as iron transport mechanisms- a distinctive gut signature of IBD that impacts the severity of inflammation. Our findings shed light on mechanisms driving plasmid dispersal and selection in the human gut, highlighting their role as carriers of vital gene pools impacting bacterial hosts and ecosystem dynamics.

Plasmid-encoded toxin defence mediates mutualistic microbial interactions.

Gut environments harbour dense microbial ecosystems in which plasmids are widely distributed. Plasmids facilitate the exchange of genetic material among microorganisms while enabling the transfer of a diverse array of accessory functions. However, their precise impact on microbial community composition and function remains largely unexplored. Here we identify a prevalent bacterial toxin and a plasmid-encoded resistance mechanism that mediates the interaction between Lactobacilli and Enterococci. This plasmid is widespread across ecosystems, including the rumen and human gut microbiota. Biochemical characterization of the plasmid revealed a defence mechanism against reuterin, a toxin produced by various gut microbes, such as Limosilactobacillus reuteri. Using a targeted metabolomic approach, we find reuterin to be prevalent across rumen ecosystems with impacts on microbial community structure. Enterococcus strains carrying the protective plasmid were isolated and their interactions with L. reuteri, the toxin producer, were studied in vitro. Interestingly, we found that by conferring resistance against reuterin, the plasmid mediates metabolic exchange between the defending and the attacking microbial species, resulting in a beneficial relationship or mutualism. Hence, we reveal here an ecological role for a plasmid-coded defence system in mediating a beneficial interaction.

Cryptic diversity of cellulose-degrading gut bacteria in industrialized humans.

Humans, like all mammals, depend on the gut microbiome for digestion of cellulose, the main component of plant fiber. However, evidence for cellulose fermentation in the human gut is scarce. We have identified ruminococcal species in the gut microbiota of human populations that assemble functional multienzymatic cellulosome structures capable of degrading plant cell wall polysaccharides. One of these species, which is strongly associated with humans, likely originated in the ruminant gut and was subsequently transferred to the human gut, potentially during domestication where it underwent diversification and diet-related adaptation through the acquisition of genes from other gut microbes. Collectively, these species are abundant and widespread among ancient humans, hunter-gatherers, and rural populations but are rare in populations from industrialized societies thus indicating potential disappearance in response to the westernized lifestyle.

Multilayer networks of plasmid genetic similarity reveal potential pathways of gene transmission.

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.

Asgard ESCRT-III and VPS4 reveal conserved chromatin binding properties of the ESCRT machinery.

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.

Generating lineage-resolved, complete metagenome-assembled genomes from complex microbial communities.

Microbial communities might include distinct lineages of closely related organisms that complicate metagenomic assembly and prevent the generation of complete metagenome-assembled genomes (MAGs). Here we show that deep sequencing using long (HiFi) reads combined with Hi-C binning can address this challenge even for complex microbial communities. Using existing methods, we sequenced the sheep fecal metagenome and identified 428 MAGs with more than 90% completeness, including 44 MAGs in single circular contigs. To resolve closely related strains (lineages), we developed MAGPhase, which separates lineages of related organisms by discriminating variant haplotypes across hundreds of kilobases of genomic sequence. MAGPhase identified 220 lineage-resolved MAGs in our dataset. The ability to resolve closely related microbes in complex microbial communities improves the identification of biosynthetic gene clusters and the precision of assigning mobile genetic elements to host genomes. We identified 1,400 complete and 350 partial biosynthetic gene clusters, most of which are novel, as well as 424 (298) potential host-viral (host-plasmid) associations using Hi-C data.

SCAPP: an algorithm for improved plasmid assembly in metagenomes.

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 . Video abstract.