Computer-Aided Therapy for Gut Health
Manipulation of the gut microbiota holds great promise for the treatment of diseases. However, a major challenge is the identification of therapeutically potent microbial consortia that colonize the host effectively while maximizing immunologic outcome.
Scientists have now, therefore, proposed a novel system to select optimal immune-inducing consortia from microbiome composition and immune effectors measurements in order to dictate better gut health.
The team built a mathematical model using published and newly generated data showing which bacterial strains were most efficient at colonizing the gut and at stimulating Treg cells in germ-free mice, both individually and together.
When combined with another model that was capable of predicting the growth and expansion of bacterial colonies in mice over time, the combination allowed researchers to determine both the growth of each bacterial strain in the mice and the extent of each strain’s contribution to the increase in Treg immune cells. Based on this, they developed a way of scoring how well groups of bacteria colonize together and stimulate an immune response.
To test the effectiveness, the team employed this model in five different four-strain combinations of bacteria in germ-free mice. They found that the bacterial combinations with the
highest scores predicted by the model not only stimulated immune cells more potently, but also colonized the gut more stably—proving the value of including both measures in the model.“Treatment of immune or inflammatory diseases is not necessarily achieved by targeting a single biological function but will require simultaneous manipulation of multiple processes within the host immune system,” said lead author Richard Stein, Ph.D., research associate at the Dana-Farber Cancer Institute. “To our knowledge, this is the first model that allows for the simultaneous prediction of the dynamics of both the microbiota and the immune response. It can be considered a stepping stone to the development and rational design of microbiome therapies.”
