Design and Deployment of Microbial and Enzyme-Based Biosensors for Real-Time Detection of Heavy Metals and Organic Pollutants in Aquatic Ecosystems

This study investigates the design, development, and deployment of microbial and enzyme-based biosensors for the detection of pollutants in aquatic ecosystems. By leveraging microbial strains such as Pseudomonas putida and Shewanella oneidensis, alongside enzymes like acetylcholinesterase (AChE) and laccase, the research aims to provide real-time, on-site monitoring solutions for heavy metals (Cd, Pb, Hg) and organic pollutants (malathion, naphthalene). The biosensors demonstrated high sensitivity and quick response times, with detection limits as low as 0.02 µg/L for malathion and 0.05 µg/L for heavy metals. The sensors' performance was optimized by varying environmental factors, including pH, temperature, and salinity, with statistical analysis revealing that these factors significantly impact sensor sensitivity. This study highlights the potential of these biosensors in addressing the challenges of aquatic pollution monitoring, emphasizing the importance of integrating advanced materials and sensor designs for robust, long-term environmental applications. The findings suggest that these biosensors, when coupled with real-time data acquisition and IoT technologies, could contribute significantly to sustainable water management practices and pollution detection in complex water matrices.