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Reconstruction of the personal information from human genome reads in gut metagenome sequencing data.

ABSTRACT: Human DNA present in faecal samples can result in a small number of human reads in gut shotgun metagenomic sequencing data. However, it is presently unclear how much personal information can be reconstructed from such reads, and this has not been quantitatively evaluated. Such a quantitative evaluation is necessary to clarify the ethical concerns related to data sharing and to enable efficient use of human genetic information in stool samples, such as for research and forensics. Here we used genomic approaches to reconstruct personal information from the faecal metagenomes of 343 Japanese individuals with associated human genotype data. Genetic sex could be accurately predicted based on the sequencing depth of sex chromosomes for 97.3% of the samples. Individuals could be re-identified from the matched genotype data based on human reads recovered from the faecal metagenomic data with 93.3% sensitivity using a likelihood score-based method. This method also enabled us to predict the ancestries of 98.3% of the samples. Finally, we performed ultra-deep shotgun metagenomic sequencing of five faecal samples as well as whole-genome sequencing of blood samples. Using genotype-calling approaches, we demonstrated that the genotypes of both common and rare variants could be reconstructed from faecal samples. This included clinically relevant variants. Our approach can be used to quantify personal information contained within gut metagenome data.

SUBMITTER: Tomofuji Y

PROVIDER: S-EPMC10234815 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature

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Reconstruction of the personal information from human genome reads in gut metagenome sequencing data.

Tomofuji Yoshihiko Y Sonehara Kyuto K Kishikawa Toshihiro T Maeda Yuichi Y Ogawa Kotaro K Kawabata Shuhei S Nii Takuro T Okuno Tatsusada T Oguro-Igashira Eri E Kinoshita Makoto M Takagaki Masatoshi M Yamamoto Kenichi K Kurakawa Takashi T Yagita-Sakamaki Mayu M Hosokawa Akiko A Motooka Daisuke D Matsumoto Yuki Y Matsuoka Hidetoshi H Yoshimura Maiko M Ohshima Shiro S Nakamura Shota S Inohara Hidenori H Kishima Haruhiko H Mochizuki Hideki H Takeda Kiyoshi K Kumanogoh Atsushi A Okada Yukinori Y

Nature microbiology 20230515 6

Human DNA present in faecal samples can result in a small number of human reads in gut shotgun metagenomic sequencing data. However, it is presently unclear how much personal information can be reconstructed from such reads, and this has not been quantitatively evaluated. Such a quantitative evaluation is necessary to clarify the ethical concerns related to data sharing and to enable efficient use of human genetic information in stool samples, such as for research and forensics. Here we used gen ...[more]

PMID: 37188815

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Project description:BackgroundA major bottleneck in the use of metagenome sequencing for human gut microbiome studies has been the lack of a comprehensive genome collection to be used as a reference database. Several recent efforts have been made to re-construct genomes from human gut metagenome data, resulting in a huge increase in the number of relevant genomes. In this work, we aimed to create a collection of the most prevalent healthy human gut prokaryotic genomes, to be used as a reference database, including both MAGs from the human gut and ordinary RefSeq genomes.ResultsWe screened > 5,700 healthy human gut metagenomes for the containment of > 490,000 publicly available prokaryotic genomes sourced from RefSeq and the recently announced UHGG collection. This resulted in a pool of > 381,000 genomes that were subsequently scored and ranked based on their prevalence in the healthy human metagenomes. The genomes were then clustered at a 97.5% sequence identity resolution, and cluster representatives (30,691 in total) were retained to comprise the HumGut collection. Using the Kraken2 software for classification, we find superior performance in the assignment of metagenomic reads, classifying on average 94.5% of the reads in a metagenome, as opposed to 86% with UHGG and 44% when using standard Kraken2 database. A coarser HumGut collection, consisting of genomes dereplicated at 95% sequence identity-similar to UHGG, classified 88.25% of the reads. HumGut, half the size of standard Kraken2 database and directly comparable to the UHGG size, outperforms them both.ConclusionsThe HumGut collection contains > 30,000 genomes clustered at a 97.5% sequence identity resolution and ranked by human gut prevalence. We demonstrate how metagenomes from IBD-patients map equally well to this collection, indicating this reference is relevant also for studies well outside the metagenome reference set used to obtain HumGut. All data and metadata, as well as helpful code, are available at http://arken.nmbu.no/~larssn/humgut/ . Video Abstract.

Dataset Information

Reconstruction of the personal information from human genome reads in gut metagenome sequencing data.

Publications

Reconstruction of the personal information from human genome reads in gut metagenome sequencing data.

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