Programmable Genome Sensing with Visual, Fluorescence, and Glucometer Readings: Cell-Free In Vitro Translation...

Rapid and accessible detection of pathogens through diverse detection modalities remains highly desirable. Most current pathogen detection assays rely on a single detection modality. Here, we have used the same RNA switch-CRISPR platform for detection of multiple pathogenic genomes through three different detection modalities. In this study, the RNA switch is repurposed as a reprogrammable platform for genome detection, enabling three orthogonal signal outputs: glucometer-based, fluorescence, and visual. Target pathogen genomes selectively regulate cell-free in vitro translation of β-galactosidase through the RNA switch, producing several hundred-fold increases in glucose following lactose hydrolysis while simultaneously generating fluorescence and colorimetric signals. The platform is readily reprogrammed to recognize conserved genomic regions from five distinct pathogens, with specificity dictated by CRISPR-Cas12a-mediated processing of a DNA regulator that controls RNA switch activation and initiates the downstream cell-free translation cascade. Glucometer-based, fluorescence, and paper-based colorimetric outputs each enabled selective detection of Salmonella typhi, Salmonella enterica, Listeria monocytogenes, Shiga toxin-producing Escherichia coli (STEC), and Campylobacter jejuni. Fluorescence and colorimetric responses were analyzed both qualitatively and quantitatively using image processing and showed strong agreement with glucometer measurements obtained using a handheld glucometer, providing a simple and accessible quantitative readout. The platform was further validated using the complete Listeria monocytogenes genome, achieving a detection sensitivity approaching a single genome copy per microliter. Together, this reprogrammable CRISPR-RNA switch platform enables the same detection setup to be programmed for multiple targets and readouts through three different detection modalities, some of which are well suited for resource-limited environments.