The cow rumen is adapted for the breakdown of plant material into energy and nutrients, a task largely performed by enzymes encoded by the rumen microbiome. Here we present 913 draft bacterial and archaeal genomes assembled from over 800 Gb of rumen metagenomic sequence data derived from 43 Scottish cattle, using both metagenomic binning and Hi-C-based proximity-guided assembly. Most of these genomes represent previously unsequenced strains and species. The draft genomes contain over 69,000 proteins predicted to be involved in carbohydrate metabolism, over 90% of which do not have a good match in public databases. Inclusion of the 913 genomes presented here improves metagenomic read classification by sevenfold against our own data, and by fivefold against other publicly available rumen datasets. Thus, our dataset substantially improves the coverage of rumen microbial genomes in the public databases and represents a valuable resource for biomass-degrading enzyme discovery and studies of the rumen microbiome.

Summary Proper centromere function is critical to maintain genomic stability and to prevent aneuploidy, a hallmark of tumors and birth defects. A conserved feature of all eukaryotic centromeres is an essential histone H3 variant called CENP-A that requires a centromere targeting domain (CATD) for its localization. Although proteolysis prevents CENP-A from mislocalizing to euchromatin, regulatory factors have not been identified. Here, we identify an E3 ubiquitin ligase called Psh1 that leads to the degradation of Cse4, the budding yeast CENP-A homolog. Cse4 overexpression is toxic to psh1Δ cells and results in euchromatic localization. Strikingly, the Cse4 centromere targeting domain is a key regulator of its stability and helps Psh1 discriminate Cse4 from histone H3. Taken together, we propose that the CATD has a previously unknown role in maintaining the exclusive localization of Cse4 by preventing its mislocalization to euchromatin via Psh1-mediated degradation.

The rapid spread of antibiotic resistance among bacterial pathogens is a serious human health threat. While a range of environments have been identified as reservoirs of antibiotic resistance genes (ARGs), we lack understanding of the origins of these ARGs and their spread from environment to clinic. This is partly due to our inability to identify the natural bacterial hosts of ARGs and the mobile genetic elements that mediate this spread, such as plasmids and integrons. Here we demonstrate that the in vivo proximity-ligation method Hi-C can reconstruct a known plasmid-host association from a wastewater community, and identify the in situ host range of ARGs, plasmids, and integrons by physically linking them to their host chromosomes. Hi-C detected both previously known and novel associations between ARGs, mobile genetic elements and host genomes, thus validating this method. We showed that IncQ plasmids and class 1 integrons had the broadest host range in this wastewater, and identified bacteria belonging to Moraxellaceae, Bacteroides, and Prevotella, and especially Aeromonadaceae as the most likely reservoirs of ARGs in this community. A better identification of the natural carriers of ARGs will aid the development of strategies to limit resistance spread to pathogens.

T he assembly of high-quality genomes from mixed microbial samples is a long-standing challenge in genomics and metagenomics. Here, we describe the application of ProxiMeta, a Hi-C-based metagenomic deconvolution method, to deconvolve a human fecal metagenome. This method uses the intra-cellular proximity signal captured by Hi-C as a direct indicator of which sequences originated in the same cell, enabling culture-free de novo deconvolution of mixed genomes without any reliance on a priori information. We show that ProxiMeta deconvolution provides results of markedly high accuracy and sensitivity, yielding 50 near-complete microbial genomes (many of which are novel) from a single fecal sample, out of 252 total genome clusters. ProxiMeta outperforms traditional contig binning at high-quality genome reconstruction. ProxiMeta shows particularly good performance in constructing high-quality genomes for diverse but poorly-characterized members of the human gut. We further use ProxiMeta to reconstruct genome plasmid content and sharing of plasmids among genomes-tasks that traditional binning methods usually fail to accomplish. Our findings suggest that Hi-C-based deconvolution can be useful to a variety of applications in genomics and metagenomics.