Tufts University School of Engineering researchers and collaborators from Texas A&M University have published the first research to use computational modeling to predict and identify the metabolic products of gastrointestinal (GI) tract microorganisms, reported Science Daily.
Reported in Nature Communications, these metabolic products, or metabolites, could influence how clinicians diagnose and treat GI diseases, as well as many other metabolic and neurological diseases increasingly associated with compromised GI function, according to the news report, noting the human GI tract is colonized by billions of bacteria and other microorganisms, belonging to hundreds of species that are collectively termed “microbiota.”
Disruptions in the microbiota composition, and subsequently the metabolites derived from the microbiota, are increasingly correlated not only to GI diseases such as inflammatory bowel disease (IBD) and colitis, but also to insulin resistance and Type 2 diabetes, reported Science Daily.
“There is increasing evidence that microbiota-derived metabolites play a significant role in modulating physiological functions of the gut,” said Kyongbum Lee, senior author and chair of the Department of Chemical and Biological Engineering, Tuft School of Engineering. “Emerging links between the GI tract microbiota and many other parts of the body, including the brain, suggest the tantalizing possibility to influence even cognition and behavior through relatively benign interventions involving diets or probiotics.”
The newly reported approach models the microbiome as a single, complex network of reactions. By using computational algorithms for network analysis, virtual pathways can be constructed to determine possible metabolic products. Then, these products can be parsed into host-derived or microbiota-derived metabolites. “In addition, we studied AAA-derived metabolites because AAAs can give rise to a variety of bioactive chemicals, such as salicylic acid, an anti-inflammatory compound, and serotonin, which is a neurotransmitter, obviously important in proper brain function,” said Lee.
Next steps for the team include identifying microbiota metabolites whose levels are either significantly elevated or depleted during diseases such as IBD or cancer, to find disease-specific markers and explore possible roles for these metabolites in disease progression, reported Science Daily.
“Ultimately, the goal is to apply our models to arrive at a mechanistic understanding of the roles microbiota products may play in human physiology, and in turn, diagnose and treat disease,” said Lee. “I think the potential for impact is immense.”
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