Abstract
The role of our gut microbiota in health and disease is largely attributed to the collective metabolic activities of the inhabitant microbes. A system-level framework of the microbial community structure, mediated through metabolite transport, would provide important insights into the complex microbe-microbe and host-microbe chemical interactions. This framework, if adaptable to both mouse and human systems, would be useful for mechanistic interpretations of the vast amounts of experimental data from gut microbiomes in murine animal models, whether humanized or not. Here, we constructed a literature-curated, interspecies network of the mammalian gut microbiota for mouse and human hosts, called NJC19. This network is an extensive data resource, encompassing 838 microbial species (766 bacteria, 53 archaea, and 19 eukaryotes) and 6 host cell types, interacting through 8,224 small-molecule transport and macromolecule degradation events. Moreover, we compiled 912 negative associations between organisms and metabolic compounds that are not transportable or degradable by those organisms. Our network may facilitate experimental and computational endeavors for the mechanistic investigations of host-associated microbial communities.
Highlights
The mammalian intestinal tract is colonized by various microorganisms, called the gut microbiota or microbiome[1,2,3]
Recent advances in metagenomics have revealed that alterations in the human gut microbiota are implicated in a number of disorders, such as obesity, inflammatory bowel disease, colorectal cancer, and diabetes[4,5,6,7]
The metabolites secreted by the microbes are absorbed by host tissues, and translate into beneficial or detrimental mediators of host physiology[6,9]
Summary
The mammalian intestinal tract is colonized by various microorganisms, called the gut microbiota or microbiome[1,2,3]. NJC19 represents the largest ever, literature-based network data resource for the mammalian gut microbiota, as a compilation of information from 769 research and review articles and textbooks (Fig. 1) This network is an advancement from our previous network, NJS16, which is limited to the human gut microbiota[10]. Does NJC19 incorporate metabolite transport and macromolecule degradation events of the microbiota, but it provides literature-annotated, negative information of which metabolic compounds are not able to be transported or degraded by the organisms Such negative information would be useful to curate computational microbial models, such as constraint-based metabolic models, which can include false-positive transport reactions from automatic genome annotations. We expect our network NJC19 to be a useful template for the mechanistic interpretation of various microbiome data from murine and human experiments
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