A new study entitled “Prediction and quantification of bioactive microbiota metabolites in the mouse gut” describes a new algorithm capable of predicting and identifying metabolic products produced by microorganisms in the gastrointestinal tract. The study was published in the Nature Communications journal.

Professor Kyongbum Lee, the study’s lead author and chair of the Department of Chemical and Biological Engineering at the Tuft School of Engineering noted, “There is increasing evidence that microbiota-derived metabolites play a significant role in modulating physiological functions of the gut. Emerging links between the GI tract microbiota and many other parts of the body, including the brain, suggest the tantalizing possibility to influence cognition and behavior through relatively benign interventions involving diets or probiotics.”

However, strategies to identify microbial metabolites, rather than host metabolites, are lacking and thus the knowledge of the role of these microbial factors in normal physiology and disease is still very limited. As a result, the authors developed a new strategy where they analyzed the microbiome as a complex network of metabolic reactions. By using pathway analyses, they are now capable of inferring new microbial metabolites. In their model, they identified 2,409 reactions and approximately 53% of these proved to not occur in the human host, thus reporting to microbiome metabolism.

“Current methods of identifying and quantifying these metabolites are unable to distinguish whether the metabolites are produced by the host or the microbiota,” said Lee.

This study has implications for hospitals and clinics, since identifying new microbial metabolites will allow novel diagnosis and treatment methods for gastrointestinal diseases in the future. Since the gastrointestinal tract is colonized by billions of microbes, the knowledge retrieved from this new data will also have implications on other microbiome-related diseases, such as metabolic and neurological disorders that are increasingly being recognized as connected to the composition of the body’s own microbiome.