Species-Level Deconvolution of Metagenome Assemblies with Hi-C–Based Contact Probability Maps

Burton, Joshua N.; Liachko, Ivan; Dunham, Maitreya J.; Shendure, Jay

doi:10.1534/g3.114.011825

Species-Level Deconvolution of Metagenome Assemblies with Hi-C–Based Contact Probability Maps

Journal Article · Thu May 22 00:00:00 EDT 2014 · G3

DOI:https://doi.org/10.1534/g3.114.011825· OSTI ID:1627950

Burton, Joshua N. ^[1]; Liachko, Ivan ^[2]; Dunham, Maitreya J. ^[2]; Shendure, Jay ^[2]

Univ. of Washington, Seattle, WA (United States). Dept. of Genome Sciences; DOE/OSTI
Univ. of Washington, Seattle, WA (United States). Dept. of Genome Sciences

Microbial communities consist of mixed populations of organisms, including unknown species in unknown abundances. These communities are often studied through metagenomic shotgun sequencing, but standard library construction methods remove long-range contiguity information; thus, shotgun sequencing and de novo assembly of a metagenome typically yield a collection of contigs that cannot readily be grouped by species. Methods for generating chromatin-level contact probability maps, e.g., as generated by the Hi-C method, provide a signal of contiguity that is completely intracellular and contains both intrachromosomal and interchromosomal information. Here, we demonstrate how this signal can be exploited to reconstruct the individual genomes of microbial species present within a mixed sample. We apply this approach to two synthetic metagenome samples, successfully clustering the genome content of fungal, bacterial, and archaeal species with more than 99% agreement with published reference genomes. We also show that the Hi-C signal can secondarily be used to create scaffolded genome assemblies of individual eukaryotic species present within the microbial community, with higher levels of contiguity than some of the species’ published reference genomes.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1627950

Journal Information:: G3, Journal Name: G3 Journal Issue: 7 Vol. 4; ISSN 2160-1836

Publisher:: Genetics Society of AmericaCopyright Statement

Country of Publication:: United States

Language:: English

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Clinical metagenomics for the management of hospital- and healthcare-acquired pneumonia Ruppé, Etienne; Baud, Damien; Schicklin, Stéphane Future Microbiology, Vol. 11, Issue 3 https://doi.org/10.2217/fmb.15.144	journal	March 2016
Intriguing Interaction of Bacteriophage-Host Association: An Understanding in the Era of Omics Parmar, Krupa M.; Gaikwad, Saurabh L.; Dhakephalkar, Prashant K. Frontiers in Microbiology, Vol. 8 https://doi.org/10.3389/fmicb.2017.00559	journal	April 2017
Applying Genome-Resolved Metagenomics to Deconvolute the Halophilic Microbiome Uritskiy, Gherman; DiRuggiero, Jocelyne Genes, Vol. 10, Issue 3 https://doi.org/10.3390/genes10030220	journal	March 2019
Mapping the spectrum of 3D communities in human chromosome conformation capture data Lee, Sang Hoon; Kim, Yeonghoon; Lee, Sungmin arXiv https://doi.org/10.48550/arxiv.1810.01307	text	January 2018
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Metagenomic chromosome conformation capture (meta3C) unveils the diversity of chromosome organization in microorganisms Marbouty, Martial; Cournac, Axel; Flot, Jean-François eLife, Vol. 3 https://doi.org/10.7554/eLife.03318	journal	December 2014
Deconvoluting simulated metagenomes: the performance of hard- and soft- clustering algorithms applied to metagenomic chromosome conformation capture (3C) DeMaere, Matthew Z.; Darling, Aaron E. PeerJ, Vol. 4 https://doi.org/10.7717/peerj.2676	journal	January 2016

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