The human gut microbiome, a complex ecosystem of bacteria, plays a vital role in overall health. Imbalances in this ecosystem, known as dysbiosis, have been linked to various inflammatory conditions.

Through harnessing the power of large-scale computer models such as Genome Scale Metabolic Models (GSMMs) and computational methodologies such as Flux Balance Analysis (FBA), researchers can investigate the complexity of the human gut microbiome. By analysing these models, researchers can identify potential targets and design personalised probiotic and prebiotic treatments.

Dr Matteo Barberis, lead author of the study and Reader in Systems Biology from the University of Surrey, says:

"Our research presents a workflow to model human-gut microbiome interactions for probiotic design, a step in the right direction, offering a new way to help the treatment of inflammatory diseases. It can predict metabolic reactions within the bacterial strains in the gut that may be targeted to correct the dysbiosis, thus offering a platform for dietary/probiotic interventions. By understanding the intricate workings of the gut microbiome and developing dedicated modelling workflows, we are paving the way for a future where personalised therapies can improve patients’ health.”

The study has been published in Chemical Engineering Journal.