Published
in eLife, a paper presents a new mathematical model that can predict the
effectiveness of microbiome therapies that manipulate the immune system through
live bacteria.
To
the authors' knowledge, this is the first model that allows for the
simultaneous prediction of the dynamics of both the microbiota and the immune
response, and can be "considered a stepping stone to the development and
rational design of microbiome therapies".
Introduction
of therapeutically potent bacteria into patients with infections or metabolic
diseases is an emerging approach with great promise. But there are two
challenges standing in the way of its success. First, the bacteria must be able
to set up home alongside the already resident microbes. Second, in the context
of autoimmune diseases, they must stimulate a range of immune responses that
dampen down unwanted inflammation. This study focused on stimulating one such
group of immune cells called regulatory T-cells, or Tregs.
Single
bacterial strains are less effective than groups of different strains. But
testing the huge number of potential bacterial combinations experimentally
simply isn’t feasible.
The
team built a 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. They then
combined this model with another that predicts the growth and expansion of
bacterial colonies in mice over time.
To
measure the model’s accuracy, they tested 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 more stably the gut – proving
the value of including both measures in the model.
Posted by Dr. Tim Sandle
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