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comprises about 100 trillion microorganisms that encode more than 3 million genes. These genes produce thousands of metabolic by-products or metabolites that help humans in crucial functions. For example, certain gut microbes digest dietary fibres and release beneficial short-chain fatty acids that maintain gut health. During digestion, some microbiota and metabolites in the stomach and small and large intestines exit the body via faeces, which researchers can isolate to identify the composition of the gut microbiome. Various researchers estimate through different studies that 1 g of watery excreta contains nearly 100 billion bacteria and 100 million to 1 billion viruses. Singlecelled yeasts, associated with protective immunity, are found in 70 per cent of humans and account for up to 1 million microbes per gram of wet faeces. “There are numerous reports in the scientific literature pointing to associations between the faecal microbiota composition and factors like diet, age, genetics, geography, longevity, drug metabolism and disease conditions,” says Ramya T N C, principal scientist at CSIR-Institute of Microbial Technology in Chandigarh.
Scientists are keen to explore how microbes and their metabolites can biomarker for colo-rectal cancer. A comparison of stool samples from 30 healthy individuals and 30 patients with the disease shows dominance of in the latter, says the study. This bacterium breaks down flavonoids, an antioxidant thought to prevent colo-rectal cancer.
Tatini Rakshit, assistant professor at Shiv Nadar University, Greater Noida, has researched on finding cancer biomarkers in another constituent of excreta— extracellular vesicles. These are nano-sized cell secretions (one nanometre is one-billionth of a metre). Using nanotechnology to isolate extracellular vesicles, Rakshit’s team has identified Hyaluronan, a carbohydrate molecule secreted excessively by diseases and diabetes.”
Artificial intelligence and machine learning can also be deployed to study faecal samples for biomarkers. Ramya says there is a great potential for machine learning in pattern recognition. However, such analyses will require long-term studies and large microbial datasets.
Meanwhile, scientists in the US are working on a bizarre yet clever concept: smart toilets. These are ordinary toilets armed with technology to analyse users’ urine and stool for signs of illness. In 2020, Stanford University researchers published a paper in the journal
describing a smart toilet they have developed. “The smart toilet is the perfect way to