Evidence map›Paper›PMID 38600293›Full record

ArticleScience China. Life sciences2024

Gut microbial interactions based on network construction and bacterial pairwise cultivation.

Min-Zhi Jiang, Chang Liu, Chang Xu, He Jiang, Yulin Wang, Shuang-Jiang Liu

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Article in Science China. Life sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–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

9 citing papers in PubMed.

  1. Article
  2. The island biology of the host microbiome.Trends in microbiology · 2026
    Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
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

6 authors.

Min-Zhi JiangState Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China.
Chang LiuState Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China.
Chang XuState Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China.
He JiangState Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China.
Yulin WangState Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China. wangyulin@sdu.edu.cn.
Shuang-Jiang LiuState Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266000, China. liusj@sdu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Association networks are widely applied for the prediction of bacterial interactions in studies of human gut microbiomes. However, the experimental validation of the predicted interactions is challenging due to the complexity of gut microbiomes and the limited number of cultivated bacteria. In this study, we addressed this challenge by integrating in vitro time series network (TSN) associations and co-cultivation of TSN taxon pairs. Fecal samples were collected and used for cultivation and enrichment of gut microbiome on YCFA agar plates for 13 days. Enriched cells were harvested for DNA extraction and metagenomic sequencing. A total of 198 metagenome-assembled genomes (MAGs) were recovered. Temporal dynamics of bacteria growing on the YCFA agar were used to infer microbial association networks. To experimentally validate the interactions of taxon pairs in networks, we selected 24 and 19 bacterial strains from this study and from the previously established human gut microbial biobank, respectively, for pairwise co-cultures. The co-culture experiments revealed that most of the interactions between taxa in networks were identified as neutralism (51.67%), followed by commensalism (21.67%), amensalism (18.33%), competition (5%) and exploitation (3.33%). Genome-centric analysis further revealed that the commensal gut bacteria (helpers and beneficiaries) might interact with each other via the exchanges of amino acids with high biosynthetic costs, short-chain fatty acids, and/or vitamins. We also validated 12 beneficiaries by adding 16 additives into the basic YCFA medium and found that the growth of 66.7% of these strains was significantly promoted. This approach provides new insights into the gut microbiome complexity and microbial interactions in association networks. Our work highlights that the positive relationships in gut microbial communities tend to be overestimated, and that amino acids, short-chain fatty acids, and vitamins are contributed to the positive relationships.

Indexed as

BacteriaCoculture TechniquesFecesGastrointestinal MicrobiomeHumansMetagenomeMetagenomicsMicrobial Interactionsassociation networkco-culturegut microbial pairwise interactionhuman gut microbiomemicrobial community

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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.