title: Construction and Analysis of Functional Networks in the Gut Microbiome of Type 2 Diabetes Patients.
abstract: Although networks of microbial species have been widely used in the analysis of 16S rRNA sequencing data of a microbiome, the construction and analysis of a complete microbial gene network are in general problematic because of the large number of microbial genes in metagenomics studies. To overcome this limitation, we propose to map microbial genes to functional units, including KEGG orthologous groups and the evolutionary genealogy of genes: Non-supervised Orthologous Groups (eggNOG) orthologous groups, to enable the construction and analysis of a microbial functional network. We devised two statistical methods to infer pairwise relationships between microbial functional units based on a deep sequencing dataset of gut microbiome from type 2 diabetes (T2D) patients as well as healthy controls. Networks containing such functional units and their significant interactions were constructed subsequently. We conducted a variety of analyses of global properties, local properties, and functional modules in the resulting functional networks. Our data indicate that besides the observations consistent with the current knowledge, this study provides novel biological insights into the gut microbiome associated with T2D.
authors.affiliation: MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.
authors.forename: Lianshuo
authors.initials: L
authors.lastname: Li
authors.affiliation: MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.
authors.forename: Zicheng
authors.initials: Z
authors.lastname: Wang
authors.affiliation: MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.
authors.forename: Peng
authors.initials: P
authors.lastname: He
authors.affiliation: MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.
authors.forename: Shining
authors.initials: S
authors.lastname: Ma
authors.affiliation: Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Beijing 100029, China.
authors.forename: Jie
authors.initials: J
authors.lastname: Du
authors.affiliation: MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China. Electronic address: ruijiang@tsinghua.edu.cn.
authors.forename: Rui
authors.initials: R
authors.lastname: Jiang
mesh_terms: D003924:Diabetes Mellitus, Type 2 / Q000235:genetics* / Q000382:microbiology / Q000473:pathology; D000069196:Gastrointestinal Microbiome / Q000235:genetics* / Q000276:immunology; D015964:Gene Expression Regulation, Bacterial; D053263:Gene Regulatory Networks; D054884:Host-Pathogen Interactions; D006801:Humans; D056186:Metagenomics / Q000379:methods*; D064307:Microbiota / Q000235:genetics*; D012336:RNA, Ribosomal, 16S / Q000235:genetics
chemical_list: D012336:RNA, Ribosomal, 16S
keywords: Functional network; Metagenomics; Microbiome; Network motif; Type 2 diabetes