A Molecular-Level Landscape of Diet-Gut Microbiome Interactions: Toward Dietary Interventions Targeting Bacterial Genes.
As diet is considered the major regulator of the gut ecosystem, the overall objective of this work was to demonstrate that a detailed knowledge of the phytochemical composition of food could add to our understanding of observed changes in functionality and activity of the gut microbiota. We used metatranscriptomic data from a human dietary intervention study to develop a network that consists of >400 compounds present in the administered plant-based diet linked to 609 microbial targets in the gut. Approximately 20% of the targeted bacterial proteins showed significant changes in their gene expression levels, while functional and topology analyses revealed that proteins in metabolic networks with high centrality are the most "vulnerable" targets. This global view and the mechanistic understanding of the associations between microbial gene expression and dietary molecules could be regarded as a promising methodological approach for targeting specific bacterial proteins that impact human health.


OBJECTIVE
It is a general belief that microbiome-derived drugs and therapies will come to the market in coming years, either in the form of molecules that mimic a beneficial interaction between bacteria and host or molecules that disturb a harmful interaction or proteins that can modify the microbiome or bacterial species to change the balance of "good" and "bad" bacteria in the gut microbiome. However, among the numerous factors, what has proven the most influential for modulating the microbial composition of the gut is diet. In line with this, we demonstrate here that a systematic analysis of the interactions between the small molecules present in our diet and the gut bacterial proteome holds great potential for designing dietary interventions to improve human health.
Systems Biology and Bioinformatics Group, School of Biological Sciences, The University of Hong Kong, Hong Kong, Hong Kong, China.
Yueqiong
Y
Ni
Systems Biology and Bioinformatics Group, School of Biological Sciences, The University of Hong Kong, Hong Kong, Hong Kong, China.
Jun
J
Li
Systems Biology and Bioinformatics Group, School of Biological Sciences, The University of Hong Kong, Hong Kong, Hong Kong, China gipa@hku.hk.
Gianni
G
Panagiotou
D001419:Bacteria / Q000235:genetics*; D001426:Bacterial Proteins / Q000235:genetics / Q000378:metabolism*; D000069196:Gastrointestinal Microbiome / Q000235:genetics* / Q000502:physiology; D041981:Gastrointestinal Tract / Q000382:microbiology*; D020869:Gene Expression Profiling; D005798:Genes, Bacterial; D006801:Humans; D064209:Phytochemicals / Q000737:chemistry / Q000378:metabolism*; D020543:Proteome
D001426:Bacterial Proteins; D064209:Phytochemicals; D020543:Proteome