Engineered biosensors distribute sensing across a microbial community and use time-resolved modeling and machine learning to infer multiple chemical concentrations from cross-reactive and indirect responses.

A computational framework coupling kinetic modeling with machine learning maps community dynamics to input concentrations, enabling quantitative inference in microbial communities with low or high sensor crosstalk, indirect responses, and pooled hospital sink water spiked with target analytes.