There is tremendous microbiomic variation between individuals – a person’s gut microbiomic signature is perhaps as uniquely distinguishable as a fingerprint. There may be variability within the individual too, but there is a strong trend to persistent populations over time. The microbiome adjusts quickly to dietary and environmental change, within a day, and can shift back just as quickly. If certain populations are wiped out, other substitute species within the same taxa or phylum may emerge to (supposedly) fulfill a similar function. Pathology conditions like Crohn’s disease, colitis, and irritable bowel syndrome (IBS, IBD) are likely to mean the dysbiosis (e.g.; microbial imbalance) of the whole biosystem (not just are certain disease-related bacterial populations elevated, but mitigating populations may be much lower. Given the complexity of the microbiome with thousands of species across tax and phyla, machine learning techniques may be useful in combining a series of weak signals into a prognostication as the SLiME Project in the Eric Alm lab at MIT has done, claiming to predict IBD as accurately as other non-invasive methods.
In the longer term, the microbiome could be the perfect platform for many different less-invasive augmentations for the human - bringing on board micro-connectivity, memory, processing, and electronic storage (Google Gut Glass?), with applications such as real-time life-tracking and quantified-self monitoring and intervention.