Predictive models of the gut microbiota

The primary function of intestinal microbiota seems to be to provide genes for metabolic reactions that are not available in the host’s genome. This enables us to process nutrients that would otherwise be unavailable to us. Another, perhaps secondary, function is to keep pathogens out. A healthy and biodiverse microbiota is resilient against invasion by invasive pathogenic bacteria such as Clostridium difficile and vancomycin-resistant Enterococcus (VRE). When we take antibiotics to cure an infection we may disrupt an ecological balance, compromising the microbiota’s resilience and opening the door for pathogens.
Microbiota resilience can involve ecological processes such as competition for nutrients, bacteriocin mediated bacterial warefare and the production of small molecules that stimulate the host to secrete antibacterial substances into the gut to harm competitor microbes. It should be possible to model these mechanisms with mathematics and build predictive computer models to help design antibiotic prescription regimens and minimize risk of disease.
In a review with Vanni Bucci we ask how far we are from such predictive models? Our conclusion is that we are probably far from a fully mechanistic, spatially structured model such as those used in environmental biotechnology. However, coarser grained models such as network inference and metabolic modeling are making great progress and may soon lead to the clinical applications.
This review is part of a special issue on the human microbiome in the Journal of Molecular Biology.

Microbiota dynamics of a bone marrow transplant patient

Microbiota dynamics of a bone marrow transplant patient

Read our review:
Towards predictive models of the human gut microbiome
Bucci V and Xavier JB. Journal of Molecular Biology [PDF]

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