Nitrate (NO 3 – ) contamination is becoming a major concern due to the negative effects of an excessive NO 3 – presence in water which can have detrimental effects on human health. Sensitive, real-time, low-cost, and portable measurement systems able to detect extremely low concentrations of NO 3 – in water are thus becoming extremely important. In this work, we present a novel method to realize a low-cost and easy to fabricate amperometric sensor capable of detecting small concentrations of NO 3 – in real water samples. The novel fabrication technique combines printing of a silver (Ag) working electrode with subsequent modification of the electrode with electrodeposited copper (Cu) nanoclusters. The process was tuned in order to reach optimized sensor response, with a high catalytic activity toward electroreduction of NO 3 – (sensitivity: 19.578 μA/mM), as well as a low limit of detection (LOD: 0.207 nM or 0.012 μg/L) and a good dynamic linear concentration range (0.05 to 5 mM or 31 to 310 mg/L). The sensors were tested against possible interference analytes (NO 2 – , Cl – , SO 4 2– , HCO 3 – , CH 3 COO – , Fe 2+ , Fe 3+ , Mn 2+ , Na + , and Cu 2+ ) yielding only negligible effects [maximum standard deviation (SD) was 3.9 μA]. The proposed sensors were also used to detect NO 3 – in real samples, including tap and river water, through the standard addition method, and the results were compared with the outcomes of high-performance liquid chromatography (HPLC). Temperature stability (maximum SD 3.09 μA), stability over time (maximum SD 3.69 μA), reproducibility (maximum SD 3.20 μA), and repeatability (maximum two-time useable) of this sensor were also investigated.

Heterocyclic amine histamine is a well-known foodborne toxicant (mostly linked to “scombroid poisoning”) synthesized from the microbial decarboxylation of amino acid histidine. In this work, we report the fabrication of a flexible screen-printed immunosensor based on a silver electrode coated with single-walled carbon nanotubes (SWCNTs) for the detection of histamine directly in fish samples. Biosensors were realized by first spray depositing SWCNTs on the working electrodes and by subsequently treating them with oxygen plasma to reduce the unwanted effects related to their hydrophobicity. Next, anti-histamine antibodies were directly immobilized on the treated SWCNTs. Histamine was detected using the typical reaction of histamine and histamine-labeled with horseradish peroxidase (HRP) competing to bind with anti-histamine antibodies. The developed immunosensor shows a wide linear detection range from 0.005 to 50 ng/mL for histamine samples, with a coefficient of determination as high as 98.05%. Average recoveries in fish samples were observed from 96.00% to 104.7%. The biosensor also shows good selectivity (less than 3% relative response for cadaverine, putrescine, and tyramine), reproducibility, mechanical and time stability, being a promising analytical tool for the analysis of histamine, as well as of other food hazards.

Furaneol is a widely used flavoring agent, which can be naturally found in different products, such as strawberries or thermally processed foods. This is why it is extremely important to detect furaneol in the food industry using ultra-sensitive, stable, and selective sensors. In this context, electrochemical biosensors are particularly attractive as they provide a cheap and reliable alternative measurement device. Carbon nanotubes (CNTs) and silver nanoparticles (AgNPs) have been extensively investigated as suitable materials to effectively increase the sensitivity of the biosensors. However, a comparison of the performance of biosensors employing CNTs and AgNPs is still missing. Herein, the effect of CNTs and AgNPs on the biosensor performance has been thoughtfully analyzed. Therefore, disposable flexible and screen printed electrochemical aptasensor modified with CNTs (CNT-ME), or AgNPs (AgNP-ME) have been developed. Under optimized conditions, CNT-MEs showed better performance compared to AgNP-ME, yielding a linear range of detection over a dynamic concentration range of 1 fM–35 μM and 2 pM–200 nM, respectively, as well as high selectivity towards furaneol. Finally, our aptasensor was tested in a real sample (strawberry) and validated with high-performance liquid chromatography (HPLC), showing that it could find an application in the food industry.

Aptamers are chemically synthesized single-stranded DNA or RNA oligonucleotides widely used nowadays 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 ligands by exponential enrichment (SELEX) process is employed to isolate aptamers. Nevertheless, this method requires complex and time-consuming 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 five aptamer candidates obtained from the design process and 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 five 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. We studied these conformational changes using a molecular dynamics simulation and suggested a possible explanation of the experimental observations. Finally, electrochemical measurements exposing the same sensors to different molecules were 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 and potentially be applied to any target molecule.

Aptamers that undergo conformational changes upon small molecule recognition have been shown to gate the ionic flux through nanopores by rearranging charge density within the aptamer-occluded orifice. However, mechanistic insight into such systems where biomolecular interactions are confined in nanoscale spaces, is limited. To shed light on the fundamental mechanisms that facilitate the detection of small-molecule analytes inside structure-switching aptamer-modified nanopores, we correlated experimental observations to theoretical models. We developed a novel dopamine aptamerfunctionalized nanopore sensor with femtomolar detection limits and compared the sensing behavior with a serotonin sensor fabricated with the same methodology. When sensing these two neurotransmitters with comparable mass and equal charge, the sensors showed an opposite electronic behavior. This distinctive phenomenon was extensively studied using complementary experimental techniques such as quartz crystal microbalance with dissipation monitoring, in combination with theoretical assessment by the finite element method and molecular dynamic simulations. Taken together, our studies demonstrate that the sensing behavior of highly sensitive aptamer-modified nanopores correlates with the structure-switching mechanisms unique to the selected aptamers targeting specific small-molecule analytes. We believe that such investigations not only improve our understanding of the complex interactions occurring in confined nanoscale environments, but will also drive further innovations in biomimetic nanopore technologies.