E. coli is usually harmless, but Shiga toxin-producing strains such as O157:H7 can cause severe disease, highlighting the need for rapid, low-cost, field-deployable detection methods. Here, we present a rapid paper-based dual-substrate colorimetric assay combined with machine learning for simultaneous detection and differentiation of E. coli and E. coli O157:H7. The assay utilizes two β-galactosidase-responsive substrates, X-gal and CPRG. These substrates take advantage of the strain-specific enzyme affinities and result in clearly distinguishable colour changes, producing green for E. coli and magenta for E. coli O157:H7 within 20 min. This represents the first single-enzyme, dual-substrate system enabling both visual and quantitative discrimination of the E. coli strains. The assay showed comparable performance on commercial and paper-based 96-well plates, with identical detection limits and assay time. The paper format used tenfold less reagent, generated less waste, and enabled reagent pre-coating, simplifying the workflow to a single sample-addition step. The assay achieved a LOD of 103 CFU/mL in pure cultures within 30 min and was able to differentiate strains at 106 CFU/mL within 20 min. In enriched food samples, the LODenriched is 10 CFU/mL. Absorbance and ratiometric analysis identified 650/574 and 574/650 ratios as the most discriminative, supported by PCA and variable-importance analysis. AGREE assessment (0.86) confirmed the superior sustainability of the paper device. Overall, the assay offers a rapid, cost-effective, sensitive, and eco-friendly platform for pathogenic E. coli detection with strong potential for decentralized food and water monitoring.
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