Martina Aurora’s research while affiliated with Free University of Bozen-Bolzano and other places

Aptamers are chemically synthesized single-stranded DNA or RNA oligonucleotides nowadays widely used in sensors and nanoscale devices as highly sensitive biorecognition elements. With proper design, aptamers are able to bind to a specific target molecule with high selectivity. To date, the systematic evolution of ligand by exponential enrichment (SELEX) process is employed to isolate aptamers. Nevertheless, this method requires complex and timeconsuming procedures. In-silico methods comprising machine learning models have been recently proposed to reduce the time and cost of aptamer design. In this work, we present a new in-silico approach allowing the generation of highly sensitive and selective RNA aptamers towards a specific target, here represented by ammonium dissolved in water. By using machine learning and bioinformatics tools a rational design of aptamers is demonstrated. This “smart” SELEX method is experimentally proved by choosing the best 5 aptamer candidates obtained from the design process and by applying them as functional elements in an electrochemical sensor to detect, as the target molecule, ammonium at different concentrations. We observed that the use of 5 different aptamers leads to a significant difference in the sensor’s response. This can be explained by considering the aptamers’ conformational change due to their interaction with the target molecule. By using molecular dynamics simulation, we studied these conformational changes and suggested a possible explanation of the experimental observations. Finally, electrochemical measurements exposing the same sensors to different molecules are used to confirm the high selectivity of the designed aptamers. The proposed in-silico SELEX approach can potentially reduce the cost and the time needed to identify the aptamers while being able to be potentially applied to any target molecule.

In this work, we propose a novel disposable flexible and screen-printed electrochemical aptamer-based sensor (aptasensor) for the rapid detection of chlorpyrifos (CPF). To optimize the process, various characterization procedures were employed, including Fourier transform infrared spectroscopy (FT-IR), electrochemical impedance spectroscopy (EIS), and cyclic voltammetry (CV). Initially, the aptasensor was optimized in terms of electrolyte pH, aptamer concentration, and incubation time for chlorpyrifos. Under optimal conditions, the aptasensor showed a wide linear range from 1 to 105 ng/mL with a calculated limit of detection as low as 0.097 ng/mL and sensitivity of 600.9 µA/ng. Additionally, the selectivity of the aptasensor was assessed by identifying any interference from other pesticides, which were found to be negligible (with a maximum standard deviation of 0.31 mA). Further, the stability of the sample was assessed over time, where the reported device showed high stability over a period of two weeks at 4 °C. As the last step, the ability of the aptasensor to detect chlorpyrifos in actual samples was evaluated by testing it on banana and grape extracts. As a result, the device demonstrated sufficient recovery rates, which indicate that it can find application in the food industry.