Microbiota-Based Diagnosis and Prediction of Ecosystem Health (e.g., in our body)
Xu Jian, Single-Cell Center, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences
Microbiotas inhabit every corner of our planet and drive key bioprocesses that range from development of caries and obesity in the human body to fixation and storage of carbon dioxide in the ocean. Therefore the interactions between microbiotas and their environments are shaping the destiny of human society, particularly in light of the challenges of global warming and environmental pollution. Can the microbiota and their intimate relationship with environment be utilized as a general strategy to diagnose or even predict the “health” of ecosystems? To test this hypothesis, we employed human oral microbiota (such as those from saliva and plaque) as a model, as they are easy to sample and thus friendly to patients. Gingivitis is one of the most prevalent infections in adults worldwide. By tracking oral microbiota in the development of and recovery from gingivitis in 50 human adults, we showed that a microbiota-based model, consisting of 27 bacterial taxa from plaque (which we termed “Microbial Index of Gingivitis”), correlates with Mazza Index (a clinical parameter measuring the degree of gingivitis) and can distinguish healthy from diseased hosts with 95% accuracy. Moreover two host types with distinct gingivitis sensitivity are distinguished based on plague microbiota with 74% reliability. In another example, we showed that oral microbiota can predict the on-set of Early Childhood Caries, which is one of the most prevalent public health problems in children in China and in many developed countries. These findings highlight microbiota as native “sensors” of ecosystem health, and promise to usher in novel strategies for understanding, preventing and treating oral and even system diseases.