Evidence map›Paper›PMID 32983030›Full record

ArticleFrontiers in microbiology2020

Species-Level Analysis of Human Gut Microbiota With Metataxonomics.

Jing Yang, Ji Pu, Shan Lu, Xiangning Bai, Yangfeng Wu, Dong Jin, Yanpeng Cheng, Gui Zhang, Wentao Zhu, Xuelian Luo and 2 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed, 2 pooled it
–field-weighted citation impact
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

62 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Fecal microbiota composition is related to brown adipose tissueJournal of endocrinological investigation · 2023
    Trial
  4. High-throughput analyses ofGut microbes · 2026
    Article
  5. Gut microbes · 2026
    Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Synergistic effect of a naturally derivedBioscience of microbiota, food and health · 2026
    Article
  11. Article
  12. Review
  13. Article
  14. Nutrients · 2025
    Article
  15. Nutrients · 2025
    Article
  16. Review
  17. Article
  18. Targeted sequencing ofmSystems · 2025
    Article
  19. Article
  20. Article

2 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

12 authors.

Jing YangState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Ji PuState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Shan LuState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Xiangning BaiState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Yangfeng WuPeking University Clinical Research Institute, Beijing, China.
Dong JinState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Yanpeng ChengState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Gui ZhangState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Wentao ZhuState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Xuelian LuoState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.
Ramon Rosselló-MóraMarine Microbiology Group, Department of Ecology and Marine Resources, Instituto Mediterráneo de Estudios Avanzados (IMEDEA), Esporles, Spain.
Jianguo XuState Key Laboratory of Infectious Disease Prevention and Control, Chinese Center for Disease Control and Prevention, National Institute for Communicable Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The current understanding of human gut microbial community is mainly limited to taxonomic features at the genus level. Here, we examined the human gut microbial community at the species level by metataxonomics. To achieve this purpose, a high-throughput approach involving operational phylogenetic unit analysis of the near full-length 16S ribosomal RNA (rRNA) gene sequence was used. A total of 1,235 species-level phylotypes (SLPs) were classified in the feces of 120 Chinese healthy individuals, including 461 previously classified species, 358 potentially new species, and 416 potentially new taxa, which were categorized into low, medium, and high prevalent bacteria groups based on their prevalence. Each individual harbored 186 ± 51 SLPs on average. There was no universal bacterial species shared by all the individuals. However, 90 ± 19 of 116 SLPs were shared in the high prevalent bacteria group. Thirty-two out of thirty-eight species in the high prevalent bacteria group detected in this study were also found in at least one previous study on human gut microbiota based on either culture-dependent or culture-independent approaches. Through compositional analysis, a hierarchical clustering of the prevalence and relative abundance of the 1,235 SLPs revealed two types of gut microbial communities, which were dominated by

Indexed as

gut microbiotametataxonomicspotential pathogenic speciesresident bacteriaspecies-level phylotypes

Identifiers

PMID32983030
PMCPMC7479098

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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.