Abstract
The gut microbiome is an ecosystem that involves complex interactions. Currently, our knowledge about the role of the gut microbiome in health and disease relies mainly on differential microbial abundance, and little is known about the role of microbial interactions in the context of human disease. Here, we construct and compare microbial co-abundance networks using 2,379 metagenomes from four human cohorts: an inflammatory bowel disease (IBD) cohort, an obese cohort and two population-based cohorts. We find that the strengths of 38.6% of species co-abundances and 64.3% of pathway co-abundances vary significantly between cohorts, with 113 species and 1,050 pathway co-abundances showing IBD-specific effects and 281 pathway co-abundances showing obesity-specific effects. We can also replicate these IBD microbial co-abundances in longitudinal data from the IBD cohort of the integrative human microbiome (iHMP-IBD) project. Our study identifies several key species and pathways in IBD and obesity and provides evidence that altered microbial abundances in disease can influence their co-abundance relationship, which expands our current knowledge regarding microbial dysbiosis in disease.
Highlights
The gut microbiome is an ecosystem that involves complex interactions
We find that the microbial species and pathway coabundances vary significantly between cohorts and report inflammatory bowel disease (IBD)- and obesity-specific co-abundance networks, which expand our current knowledge regarding microbial dysbiosis in disease
Principle coordinate analysis showed that microbial composition and functional profiles are largely overlapped, we observed a significant shift in species composition in the IBD cohort (Supplementary Fig. 2)
Summary
The gut microbiome is an ecosystem that involves complex interactions. Currently, our knowledge about the role of the gut microbiome in health and disease relies mainly on differential microbial abundance, and little is known about the role of microbial interactions in the context of human disease. Various network inference tools have been developed[25,26,27,28,29] and applied to infer microbial taxonomic networks in healthy individuals and in individuals with extreme longevity, gestational diabetes, Crohn’s disease and colorectal cancer[30,31,32,33,34,35] These studies have identified microbial genera that are potentially key in health and disease, e.g. Porphyromonas and Bacteroides in gestational diabetes[33]. These previous studies were either based on 16S rRNA sequencing data, which yields limited information on microbial species and pathways, or carried out in small cohorts[30,31,32,33,34]. The network key species and pathways identified in IBD and obesity highlight their potential roles in regulating the microbial ecosystem in disease
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