Biosensors development for the detection of microbiological contaminants in the Integrated Water Cycle

Escherichia coli is still a harmful pathogen that contaminates water globally, posing serious health risks. Traditional microbiological methods, required by the ISO standards, are widely used and commonly accepted techniques to identify microbial contaminants in water samples; however, the main disadvantage of these methods is that they are time-consuming, providing the results in about 24-48 hours. These long incubation times do not allow timely intervention in cases of water contamination, potentially leading to severe consequences for consumers, including hospitalization and, in worst cases, consumer death. This study aimed to deeply investigate a new alternative approach to water analysis using innovative analytical tools, the biosensors. Biosensors consist of two main components: a biorecognition element and a transduction element. For the biorecognition element, a specific DNA sequence capable of folding, assuming a tridimensional structure, was chosen. The transducer can be categorized into three types: electrochemical, piezoelectrical, and optical. Utilizing an aptamer in silico designed by the company Arta Peptidion (Parma, Italy), this research compared the efficacy of these transducer categories: a carbon and gold screen-printed electrode (SPE) as an electrochemical transducer, a quartz-crystal microbalance (QCM) as a piezoelectric transducer, and a surface plasmon resonance (SPR) as an optical transducer. To proceed with the study, various parameters were examined to establish standardized protocols for each biosensor typology. The first result shifted the attention from carbon SPE to gold ones. Subsequently, the gold substrate was chosen for all the other biosensor typologies. The washing buffer, the redox mediator (only for the electrochemical sensor), the aptamer concentration and its immobilization time on the surface, the saturation step and the time required for the blocking step, and the incubation of the target cells were deeply studied. Following this optimization phase, calibration curves were defined, correlating signal variations (different for all the sensors, including current variation for SPAuE, resonance frequency variation for QCM, and refractive index variation for SPR) with the logarithm of the target cell concentration. Positive performance and results were obtained investigating the sensitivity (expressed as the Limit of Detection) and specificity towards other pathogen cells (including Salmonella enterica DSM 4883, Pseudomonas fluorescens DI4A L22, Enterococcus faecium DSM 20447, Staphylococcus aureus DI4A 226, and Bacillus atropheus DSM 675), with LOD of 25 cells/mL for the SPAuE, 63 cells/mL for the QCM, and 1.8  103 cells/mL for the SPR. Subsequently, real water samples were sourced from different sites in the Friuli-Venezia Giulia region of Italy, including natural water bodies like streams, rivers, a canal, a lake, and wells, as well as potable water distribution systems. These samples were tested with the SPE and QCM protocols, providing almost in all cases results comparable with those of the traditional counting method. In the end, the newly developed protocols were tested in their performance: the reproducibility, which was high for all the sensor typologies; the sensor regeneration capabilities, which may reduce the overall analysis cost; the storage stability at 4°C over time, which further contributed to reduce the costs of the biosensor production. Additionally, an approximate cost analysis for conducting individual tests was performed, resulting in less than 12 euros/analysis. This comprehensive approach underscores the potentiality of biosensors in analyzing water samples while solving the urgent need for rapid detection methods to safeguard public health and consumers’ health and opens the idea of scaling-up these tools.