title: Network analysis suggests a potentially 'evil' alliance of opportunistic pathogens inhibited by a cooperative network in human milk bacterial communities.
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.
authors: Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources &Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
authors: Zhanshan
authors: Z
authors: Sam Ma
authors: Computational Biology and Medical Ecology Lab, State Key Laboratory of Genetic Resources &Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.
authors: Qiong
authors: Q
authors: Guan
authors: 1] 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.
authors: Chengxi
authors: C
authors: Ye
authors: School of Public Health Columbia University 722 West 168th Street New York, NY 10032, USA.
authors: Chengchen
authors: C
authors: Zhang
authors: Institute of Bioinformatics and Evolutionary Studies &Department of Biological Sciences University of Idaho Moscow, ID 83843, USA.
authors: James A
authors: JA
authors: Foster
authors: Institute of Bioinformatics and Evolutionary Studies &Department of Biological Sciences University of Idaho Moscow, ID 83843, USA.
authors: Larry J
authors: LJ
authors: Forney
mesh_terms: D001419:Bacteria / Q000145:classification / Q000235:genetics; D005516:Food Microbiology; D006801:Humans; D064307:Microbiota; D008895:Milk, Human / Q000382:microbiology*; D008962:Models, Theoretical; D010802:Phylogeny; D012336:RNA, Ribosomal, 16S / Q000235:genetics
chemical_list: D012336:RNA, Ribosomal, 16S
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