Dataset Information

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.

SUBMITTER: Li L

PROVIDER: S-EPMC5093780 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Construction and Analysis of Functional Networks in the Gut Microbiome of Type 2 Diabetes Patients.

Li Lianshuo L Wang Zicheng Z He Peng P Ma Shining S Du Jie J Jiang Rui R

Genomics, proteomics & bioinformatics 20161014 5

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) orthologou ...[more]

PMID: 27746285

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Project description:BackgroundThe coexistence of hypertension and type 2 diabetes mellitus (T2DM) may largely increase the risk for cardiovascular disease. However, there is no clear consensus on the association between hypertension and the risk of diabetes. Gut microbiota plays important roles in the development of hypertension and T2DM, but whether there is difference between hypertension patients with or without T2DM has not been explored yet.MethodsWe recruited 101 hypertension patients in this study (72 patients without T2DM named HT group and 29 patients with T2DM named HT-T2DM group). Their blood samples were collected for testing clinical characteristics and fecal samples were tested for bacterial DNA using 16 S ribosomal RNA gene sequencing targeting the V3 and V4 region. The data of 40 samples were downloaded from project PRJNA815750 as health control (HC group) in this study. The community composition and structure of the microbiome, taxonomic difference, co-occurrence network and functional enrichment were analyzed by alpha/beta diversity, LEfSe, Fruchterman Reingold's algorithm and PICRUSt2 functional analysis, respectively.ResultsAlpha and beta diversity analysis showed significant differences in microbial community richness and composition among the three groups. The HC group had a significantly higher Simpson index and a distinct microbiota community compared to the HT and HT-T2DM groups, as demonstrated by significant differences in unweighted and weighted UniFrac distances. The LEfSe analysis identified specific taxa that had significantly different abundance among the groups, such as Bacteroides uniformis, Blautia wexlerae, Alistipes putredinis, and Prevotella stercorea in the HC group, Prevotella copri and Phascolarctobacterium faecium in the HT group, and Klebsiella pneumoniae in the HT-T2DM group. Co-occurrence network analysis indicates that Prevotella copri, Mediterraneibacter gnavus, Alistipes onderdonkii and some unidentified species act as key nodes in the network. Differentially functional pathway identified by PICRUSt2 were concentrated in nutrition and energy metabolism, as well as the biosynthesis of other secondary metabolites.ConclusionsOur study found significant differences in microbial community richness, composition, and function among the healthy controls, hypertension patients with and without T2DM. Some specific taxa may explain this difference and serve as potential therapeutic targets for hypertension, T2DM, and their coexistence.

Project description:INTRODUCTION:Diabetes remains a growing public health concern in Egypt, as prevalence of Type II diabetes (TIID) has nearly tripled there in the last two decades. Egypt was ranked ninth worldwide in number of diabetes cases, with prevalence of 15.56% among adults. Recent studies have proposed that disturbance of gut microbiota could influence TIID development and indicated associations between a reduced diversity in microbiomes and Type I diabetes (TID). In the present study, we investigated the composition and abundance of the bacterial microbiome in disease state (TID and TIID) of Egyptian patients. Our goal in this study was to characterize features of the gut microbiota and possible differences associated with TID and TIID in this population. METHODS:DNA was extracted from fecal samples taken from 22 TID and 18 TIID outpatients of Al-Hussein hospital, Cairo, Egypt. 16S rRNA amplicon sequencing was used to characterize the bacterial taxa and these reads were processed using the software mothur with analysis utilizing packages vegan, phyloseq and metagenomSeq in R. RESULTS AND CONCLUSIONS:Our results highlighted a significant increase in abundance of Gram negative, potentially opportunistic pathogenic taxa (Pseudomonas, Prevotella) in all diabetic groups, compared to the control. Lipopolysccharide (LPS), a component of the gram-negative bacterial wall, can activate local immune response and may result in low-grade systemic inflammation contributing to insulin resistance. The gram-positive Gemella, which is associated with increased risk to diabetes, also had a significant increase in abundance in all diabetic groups, compared to the control. In contrast, the commensal bacterial taxa Turicibacter, Terrisporobacter and Clostridium were found to be more abundant in the control group than in TID. Further studies are needed to understand the role of these taxa in health and disease. Lower Richness and low Shannon diversity, though not statistically significant, were observed for TID subjects with no glucose control and with onset of liver disease or hypertension compared to other subjects. In addition, large variation in alpha diversity within the control group could also be observed. Future studies will include larger samples sizes to further elucidate these findings, as well as possible metagenomic studies to examine the intriguing function of significant microbes.

Project description:BackgroundThe study was conducted to investigate the effects of metformin treatment on the human gut microbiome's taxonomic and functional profile in the Latvian population, and to evaluate the correlation of these changes with therapeutic efficacy and tolerance.MethodsIn this longitudinal observational study, stool samples for shotgun metagenomic sequencing-based analysis were collected in two cohorts. The first cohort included 35 healthy nondiabetic individuals (metformin dose 2x850mg/day) at three time-points during metformin administration. The second cohort was composed of 50 newly-diagnosed type 2 diabetes patients (metformin dose-determined by an endocrinologist) at two concordant times. Patients were defined as Responders if their HbA1c levels during three months of metformin therapy had decreased by ≥12.6 mmol/mol (1%), while in Non-responders HbA1c were decreased by <12.6 mmol/mol (1%).ResultsMetformin reduced the alpha diversity of microbiota in healthy controls (p = 0.02) but not in T2D patients. At the species level, reduction in the abundance of Clostridium bartlettii and Barnesiella intestinihominis, as well as an increase in the abundance of Parabacteroides distasonis and Oscillibacter unclassified overlapped between both study groups. A large number of group-specific changes in taxonomic and functional profiles was observed. We identified an increased abundance of Prevotella copri (FDR = 0.01) in the Non-Responders subgroup, and enrichment of Enterococcus faecium, Lactococcus lactis, Odoribacter, and Dialister at baseline in the Responders group. Various taxonomic units were associated with the observed incidence of side effects in both cohorts.ConclusionsMetformin effects are different in T2D patients and healthy individuals. Therapy induced changes in the composition of gut microbiome revealed possible mediators of observed short-term therapeutic effects. The baseline composition of the gut microbiome may influence metformin therapy efficacy and tolerance in T2D patients and could be used as a powerful prediction tool.

Dataset Information

Construction and Analysis of Functional Networks in the Gut Microbiome of Type 2 Diabetes Patients.

Publications

Construction and Analysis of Functional Networks in the Gut Microbiome of Type 2 Diabetes Patients.

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