Arsenic contamination in environmental water sources poses a significant threat to human health, necessitating the development of sensitive and accessible detection methods. This study presents a multidimensional optimization of a bacterial biosensor for the susceptible and deoxyviolacein (DV)-based visual detection of arsenic. The research involved screening six different arsenic resistance (ars) operons and optimizing the genetic circuit to minimize background noise. Introducing an arsenic-specific transport channel enhanced the sensor's sensitivity to 1 nM with a quantitative range from 0.036 to 1.171 μM. The pigment-based biosensor offers a simple colorimetric approach for arsenic detection without complex instrumentation. The preferred biosensor demonstrated characteristics of anti-chelating agent interference, consistently quantified As(III) concentrations ranging from 0.036 to 1.171 μM covering the World Health Organization (WHO) drinking water limit. Innovatively, it effectively detects arsenic in seawater within a linear regression range of 0.071 to 1.125 μM. The biosensor's selectivity for arsenic was confirmed, with minimal cross-response to group 15 metals. Our naked-eye biosensor offers a novel approach for the rapid, on-site detection of arsenic in various water sources. Its simplicity, cost-effectiveness, and versatility make it a valuable tool for environmental monitoring and public health initiatives.
Keywords: Bacterial biosensor; Colorimetric detection; Environmental water analysis; Genetic optimization; Pigment-based signal.
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