Understanding Horizontal Gene Transfer network in human gut microbiota

• Main Authors: Chen Li, Jiaxing Chen, Shuai Cheng Li
• Format: Article
• Language: English
• Published: BMC 2020-07-01
• Series: Gut Pathogens
• Subjects: HGT network; Scale free; Von Newman entropy; Network evolving; Community analysis
• Online Access: http://link.springer.com/article/10.1186/s13099-020-00370-9

Abstract Background Horizontal Gene Transfer (HGT) is the process of transferring genetic materials between species. Through sharing genetic materials, microorganisms in the human microbiota form a network. The network can provide insights into understanding the microbiota. Here, we constructed the HGT networks from the gut microbiota sequencing data and performed network analysis to characterize the HGT networks of gut microbiota. Results We constructed the HGT network and perform the network analysis to two typical gut microbiota datasets, a 283-sample dataset of Mother-to-Child and a 148-sample dataset of longitudinal inflammatory bowel disease (IBD) metagenome. The results indicated that (1) the HGT networks are scale-free. (2) The networks expand their complexities, sizes, and edge numbers, accompanying the early stage of lives; and microbiota established in children shared high similarity as their mother (p-value = 0.0138), supporting the transmission of microbiota from mother to child. (3) Groups harbor group-specific network edges, and network communities, which can potentially serve as biomarkers. For instances, IBD patient group harbors highly abundant communities of Proteobacteria (p-value = 0.0194) and Actinobacteria (p-value = 0.0316); children host highly abundant communities of Proteobacteria (p-value = 2.8785 $$e^{-5}$$ e - 5 ) and Actinobacteria (p-value = 0.0015), and the mothers host highly abundant communities of Firmicutes (p-value = 8.0091 $$e^{-7}$$ e - 7 ). IBD patient networks contain more HGT edges in pathogenic genus, including Mycobacterium, Sutterella, and Pseudomonas. Children’s networks contain more edges from Bifidobacterium and Escherichia. Conclusion Hence, we proposed the HGT network constructions from the gut microbiota sequencing data. The HGT networks capture the host state and the response of microbiota to the environmental and host changes, and they are essential to understand the human microbiota.