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GenomicsbioRxiv
Preprint

Hi-C deconvolution of a human gut microbiome yields high-quality draft genomes and reveals plasmid-genome interactions.

Maximilian Oliver PressiD, Andrew H. Wiser, Zev N. KronenbergiD, Kyle W. LangfordiD, Migun ShakyaiD, Chien‐Chi LoiD, Kathryn A. Mueller, Shawn T SullivaniD, Patrick ChainiD, Ivan LiachkoiD

Abstract

The 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.

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02 /Specification & Classification

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Abstract summary

Verified abstract synthesis

Claude Opus 5.5 · xhigh effort · 18 Oct 2026 · from the abstract · CC BY-NC-ND 4.0

Hi-C contacts assign assembled contigs to the cell they came from: 50 near-complete genomes among 252 clusters from one human fecal sample, plus plasmid-host links.

Pulling individual genomes out of a mixed microbial sample is a long-standing challenge. Because the Hi-C proximity signal shows which sequences came from the same cell, genomes and their plasmids can be separated without culture and without a priori information.

Key results

  1. ShownDeconvolving one human fecal metagenome yielded 50 near-complete microbial genomes among 252 genome clusters, with many of them described as previously uncharacterized.

    50 near-complete genomes out of 252 total clusters from a single fecal sample; the abstract gives no completeness or contamination thresholds and no count of the uncharacterized ones. · Abstract

  2. ClaimedProxiMeta performed better than traditional contig binning at reconstructing high-quality genomes, and did particularly well on diverse, poorly characterized members of the gut.

    Asserted in the abstract; no binning tool is named and no accuracy, sensitivity or genome-count figures for the comparison are reported. · Abstract

  3. ClaimedPlasmid sequences were attached to host genomes and plasmids shared between genomes were identified, a task the authors say binning usually fails at.

    Reported as a further application in the abstract, with no plasmid counts, host assignments or validation against known plasmid-host pairs. · Abstract

Methods, data and reproducibility

Hi-C captures proximity between sequences inside the same cell, and ProxiMeta clusters contigs from a human fecal metagenome on that signal alone, without culture and without a priori information; the clusters are then assessed as draft genomes and used to assign plasmids to hosts.

  • Human fecal metagenome deconvolved with Hi-C into genome clusters · human gut microbial community · n = a single fecal sample; 252 genome clusters
Methods & tools
ProxiMeta, Hi-C
Reproducibility gaps
No software availability statement, sequence accession or genome deposit is named in the abstract.
Limitations (2)
  • Everything rests on one fecal sample, and the abstract reports no external validation of the recovered genomes or of the plasmid-host assignments. · noted in this summary
  • The advantage over conventional binning is asserted without naming the competing tools or giving the metric, so the margin cannot be judged. · noted in this summary

Who should read:Read this if you reconstruct genomes from metagenomes and want to weigh what Hi-C adds over traditional contig binning, including plasmid-host assignment.

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