Evidence map›Paper›PMID 34446072›Full record

ArticleGenome medicine2021

Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes.

Chan Yeong Kim, Muyoung Lee, Sunmo Yang, Kyungnam Kim, Dongeun Yong, Hye Ryun Kim, Insuk Lee

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 1 pooled it
8.8field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

73 citing papers in PubMed, 1 synthesis or guideline pooled it, 124 citations in OpenAlex.

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13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Chan Yeong Kim *Department of Biotechnology, College of Life Science & Biotechnology, Yonsei University, Seoul, 03722, Korea.
Muyoung Lee *Department of Biotechnology, College of Life Science & Biotechnology, Yonsei University, Seoul, 03722, Korea.
Sunmo YangDepartment of Biotechnology, College of Life Science & Biotechnology, Yonsei University, Seoul, 03722, Korea.
Kyungnam KimDepartment of Laboratory Medicine, Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, 03722, Korea.
Dongeun YongDepartment of Laboratory Medicine, Research Institute of Bacterial Resistance, Yonsei University College of Medicine, Seoul, 03722, Korea.
Hye Ryun KimDivision of Medical Oncology, Department of Internal Medicine, Yonsei Cancer Center, Yonsei University College of Medicine, Seoul, 03722, Korea.
Insuk LeeDepartment of Biotechnology, College of Life Science & Biotechnology, Yonsei University, Seoul, 03722, Korea. insuklee@yonsei.ac.kr.ORCID 0000-0003-3146-6180
Yonsei University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMetagenome sampling bias for geographical location and lifestyle is partially responsible for the incomplete catalog of reference genomes of gut microbial species. Thus, genome assembly from currently under-represented populations may effectively expand the reference gut microbiome and improve taxonomic and functional profiling.

methodsWe assembled genomes using public whole-metagenomic shotgun sequencing (WMS) data for 110 and 645 fecal samples from India and Japan, respectively. In addition, we assembled genomes from newly generated WMS data for 90 fecal samples collected from Korea. Expecting genome assembly for low-abundance species may require a much deeper sequencing than that usually employed, so we performed ultra-deep WMS (> 30 Gbp or > 100 million read pairs) for the fecal samples from Korea. We consequently assembled 29,082 prokaryotic genomes from 845 fecal metagenomes for the three under-represented Asian countries and combined them with the Unified Human Gastrointestinal Genome (UHGG) to generate an expanded catalog, the Human Reference Gut Microbiome (HRGM).

resultsHRGM contains 232,098 non-redundant genomes for 5414 representative prokaryotic species including 780 that are novel, > 103 million unique proteins, and > 274 million single-nucleotide variants. This is an over 10% increase from the UHGG. The new 780 species were enriched for the Bacteroidaceae family, including species associated with high-fiber and seaweed-rich diets. Single-nucleotide variant density was positively associated with the speciation rate of gut commensals. We found that ultra-deep sequencing facilitated the assembly of genomes for low-abundance taxa, and deep sequencing (e.g., > 20 million read pairs) may be needed for the profiling of low-abundance taxa. Importantly, the HRGM significantly improved the taxonomic and functional classification of sequencing reads from fecal samples. Finally, analysis of human self-antigen homologs on the HRGM species genomes suggested that bacterial taxa with high cross-reactivity potential may contribute more to the pathogenesis of gut microbiome-associated diseases than those with low cross-reactivity potential by promoting inflammatory condition.

conclusionsBy including gut metagenomes from previously under-represented Asian countries, Korea, India, and Japan, we developed a substantially expanded microbiome catalog, HRGM. Information of the microbial genomes and coding genes is publicly available ( www.mbiomenet.org/HRGM/ ). HRGM will facilitate the identification and functional analysis of disease-associated gut microbiota.

Indexed as

Gastrointestinal MicrobiomeMetagenomeMetagenomicsComputational BiologyFecesGenetic VariationHost Microbial InteractionsHumansIndiaJapanKoreaPhylogenyCross-reactive antigenHuman gut microbiomeMetagenome-assembled genomeMetagenomic shotgun sequencing

Identifiers

PMID34446072
PMCPMC8394144
OpenAlexW3193361577

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.