Evidence map›Paper›PMID 25651890›Full record

ArticleScientific reports2015

Network analysis suggests a potentially 'evil' alliance of opportunistic pathogens inhibited by a cooperative network in human milk bacterial communities.

Zhanshan Sam Ma, Qiong Guan, Chengxi Ye, Chengchen Zhang, James A Foster, Larry J Forney

Abstract read
In one paragraph

Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing 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

36 citing papers in PubMed.

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  15. Computational and structural biotechnology journal · 2021
    Article
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  20. The Microbiota of the Human Mammary Ecosystem.Frontiers in cellular and infection microbiology · 2020
    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.

Zhanshan Sam MaComputational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources &Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
Qiong GuanComputational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources &Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
Chengxi Ye1] Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources &Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China [2] Department of Computer Science University of Maryland College Park, MD 20740, USA.
Chengchen ZhangSchool of Public Health Columbia University 722 West 168th Street New York, NY 10032, USA.
James A FosterInstitute of Bioinformatics and Evolutionary Studies &Department of Biological Sciences University of Idaho Moscow, ID 83843, USA.
Larry J ForneyInstitute of Bioinformatics and Evolutionary Studies &Department of Biological Sciences University of Idaho Moscow, ID 83843, USA.

Funding

Genomics Resources Core (GRC)P30GM103324 · NIGMS · UNIVERSITY OF IDAHO · PI SETTLES, MATTHEW · 2013 to 2017
$5.0M
NIGMS NIH HHS P30 GM103324
6 · The paper itself

Abstract

The critical importance of human milk to infants and even human civilization has been well established. Yet our understanding of the milk microbiome has been limited to cataloguing OTUs and computation of community diversity. To the best of our knowledge, there has been no report on the bacterial interactions within the milk microbiome. To bridge this gap, we reconstructed a milk bacterial community network based on Hunt et al. Our analysis revealed that the milk microbiome network consists of two disconnected sub-networks. One sub-network is a fully connected complete graph consisting of seven genera as nodes and all of its pair-wise interactions among the bacteria are facilitative or cooperative. In contrast, the interactions in the other sub-network of eight nodes are mixed but dominantly cooperative. Somewhat surprisingly, the only 'non-cooperative' nodes in the second sub-network are mutually cooperative Staphylococcus and Corynebacterium that include some opportunistic pathogens. This potentially 'evil' alliance between Staphylococcus and Corynebacterium could be inhibited by the remaining nodes that cooperate with one another in the second sub-network. We postulate that the 'confrontation' between the 'evil' alliance and 'benign' alliance and the shifting balance between them may be responsible for dysbiosis of the milk microbiome that permits mastitis.

Indexed as

BacteriaFood MicrobiologyMicrobiotaModels, TheoreticalHumansMilk, HumanPhylogenyRNA, Ribosomal, 16SRNA, Ribosomal, 16S

Identifiers

PMID25651890
PMCPMC4317708

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.