The Two Frontiers Project

Initiative 04

Exposome

Building statistical tools to identify the parts of the exposome — microbial and otherwise — that shape human health, and microbial approaches to modulate it, from degrading PFAS to improving gut function.

What we are looking for

PFAS-degrading microbesGut microbiome modulatorsExposome-health association modelsBuilt environment microbiomeUrban microbial signaturesAntibiotic resistance genes

The exposome is the set of all environmental factors — from microbes to forever chemicals — that humans are exposed to over a lifetime. Most of it is still poorly understood: we don’t have a clear map of which exposures actually move the needle on health outcomes, or how to intervene on the ones that do.

Our Exposome initiative works on both halves of that problem. On the statistical side, we build computational tools to identify which aspects of the exposome — microbial and otherwise — are most predictive of individual well-being, drawing on population-scale datasets and our own sampling programs. On the remediation side, we hunt for microbial approaches to modulate the exposome directly: organisms and consortia capable of degrading persistent pollutants like PFAS, or reshaping gut function to improve health outcomes.

Our Resilient Soils citizen science program is part of our exposome initiative. It involves sampling chemically-impact landed — PFAS-affected sites, old mining and industrial land, agricultural runoff zones. Participants collect soil samples from these environments, helping us characterize how microbial life adapts under chemical pressure and identify organisms with potential to degrade the pollutants themselves.

Together, these programs are building both the map and the toolkit: a clearer picture of which exposures matter, and a growing set of microbial interventions for the ones we can actually change.

Participate in our community science programs

Extremophiles in Your Home & Resilient Soils — swab your space, sample contaminated sites, contribute real data