MetaTOR: A Computational Pipeline to Recover High-Quality Metagenomic Bins From Mammalian Gut Proximity-Ligation (meta3C) Libraries.

Characterizing the complete genomic structure of complex microbial communities would represent a key step toward the understanding of their diversity, dynamics, and evolution. Current metagenomics approaches aiming at this goal are typically done by analyzing millions of short DNA sequences directly extracted from the environment. New experimental and computational approaches are constantly sought for to improve the analysis and interpretation of such data. We developed MetaTOR, an open-source computational solution that bins DNA contigs into individual genomes according to their 3D contact frequencies. Those contacts are quantified by chromosome conformation capture experiments (3C, Hi-C), also known as proximity-ligation approaches, applied to metagenomics samples (meta3C). MetaTOR was applied on 20 meta3C libraries of mice gut microbiota. We quantified the program ability to recover high-quality metagenome-assembled genomes (MAGs) from metagenomic assemblies generated directly from the meta3C libraries. Whereas nine high-quality MAGs are identified in the 148-Mb assembly generated using a single meta3C library, MetaTOR identifies 82 high-quality MAGs in the 763-Mb assembly generated from the merged 20 meta3C libraries, corresponding to nearly a third of the total assembly. Compared to the hybrid binning softwares MetaBAT or CONCOCT, MetaTOR recovered three times more high-quality MAGs. These results underline the potential of 3C-/Hi-C-based approaches in metagenomic projects.

Generation of a Metagenomics Proximity Ligation 3C Library of a Mammalian Gut Microbiota.

Microbial species thrive in very diverse environments and play fundamental roles in their equilibrium and dynamics. Metagenomics consists in extracting, sequencing, and studying the DNA present in ecosystems to better understand their regulation. Ideally, the maximal amount of information would be gathered from the full sequences of the genomes, episomes, and phages present in the microbial communities. Current high-throughput DNA sequencing produces reads ranging in size from a few dozen base pairs for the most commonly used technologies to several kb for emerging single-molecule real-time sequencing techniques. Although valuable information can be extracted from processing these DNA sequences into contigs, reconstructing full genomes remains a difficult task. Clustering contigs according to their similarities or read coverage covariations gives some insights on these genomes, but remains limited as viral sequences, or recent horizontal gene transfers, often differ from their host genomes. We recently developed meta3C, a proximity ligation approach that bins contigs in a sequence-independent way by quantifying and exploiting their tridimensional collisions frequencies in vivo. This technique has demonstrated a great potential to reconstruct genomes as well as to assign plasmids and phages to their hosts. It nevertheless requires a specific processing of the microbial samples before sequencing, which has to be carefully planned.