MANTRA is a validated multi-omic discovery engine built on that principle: species-level signatures rarely reproduce across cohorts, while the underlying metabolic pathways do. Tested head-to-head against standard bioinformatics tools across seven clinical and applied verticals, MANTRA has already outperformed them — and no non-invasive, India-validated tool currently exists for any of these indications.
A bioinformatics background isn't required to use MANTRA's findings — the three principles below are sufficient context, and the foundation everything else on this site builds on.
Trillions of bacteria, viruses, fungi and archaea act as one interconnected network — not a checklist of "good" or "bad" organisms. Most tools that just count species miss this entirely.
Reshaped continuously by diet, drugs and disease. Unlike a patient's genome, it's something you can act on — which is exactly why it matters for treatment decisions, not just diagnosis.
The specific bacteria in a patient's gut vary person to person, even with the same disease. Function is often more conserved than species composition — which is why MANTRA is built to score at that functional level directly, alongside the species-level picture rather than in place of it.
Eight published results, from independent groups, that MANTRA's design rests on.
The human gut microbial gene catalogue holds about 3.3 million genes. Much of the biochemistry happening in the gut is encoded there, not in the patient's own genome.
Qin et al., Nature 2010Across hundreds of healthy people, the Human Microbiome Project found that microbial composition varied widely while the metabolic pathways performed stayed stable. This is the observation MANTRA is built around.
Human Microbiome Project Consortium, Nature 2012Re-analysing 28 case–control studies across 10 diseases, researchers found roughly half of disease-associated genera respond to more than one condition: a shared response to being unwell, not a specific marker. It is one reason species-only signatures often fail to carry over between cohorts.
Duvallet et al., Nature Communications 2017When 76 human gut bacterial strains were screened against 271 common oral drugs, 176 of those drugs were significantly depleted by at least one strain. Treatment response and toxicity are partly a microbial question.
Zimmermann et al., Nature 2019In a cohort of roughly 800 people, identical foods produced widely different glucose responses, and a model that included gut microbiome features predicted those responses better than standard carbohydrate counting.
Zeevi et al., Cell 2015Patients who had recently taken antibiotics responded less well to PD-1 blockade, and the gut bacterium Akkermansia muciniphila was enriched in responders. Transferring responder microbiota into mice improved their response.
Routy et al., Science 2018In over 1,000 people, host genetics explained only a small share of microbiome variation, while diet, medication and lifestyle explained much more. That is why a microbiome-based readout carries information a genome test cannot.
Rothschild et al., Nature 2018Following people over time with metagenomics, metabolomics and more, the second Human Microbiome Project (HMP2) found that functional and metabolic changes track disease activity, beyond what species counts alone show.
Lloyd-Price et al., Nature 2019Every signature on this site has already cleared the field's toughest public benchmarks, and every one remains unvalidated in an Indian population. This is not a limitation so much as an opening: a clinical partner who leads that validation study becomes the originating site, with joint IP and a meaningful head start on the rest of the country.
Maha is the vast: an ecosystem of trillions of cells. Anim is the minute: the single molecule that tips a patient toward disease. The microbiome is both at once, and MANTRA is built to read across that whole range, from the whole community down to the one pathway that matters.