12 research outputs found
Aptamer Conformational Dynamics Modulate Neurotransmitter Sensing in Nanopores
: Aptamers that undergo conformational changes upon small-molecule recognition have been shown to gate the ionic flux through nanopores by rearranging the charge density within the aptamer-occluded orifice. However, mechanistic insight into such systems where biomolecular interactions are confined in nanoscale spaces is limited. To understand 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 dopamine aptamer-functionalized nanopore sensor with femtomolar detection limits and compared the sensing behavior with that of a serotonin sensor fabricated with the same methodology. When these two neurotransmitters with comparable mass and equal charge were detected, 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 aptamer-modified nanopores in detecting specific small-molecule analytes correlates with the structure-switching mechanisms of individual aptamers. 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
Screen-Printed Flexible Circular and Rectangular Silver Spirals for Planar Electrodynamic Loudspeakers: A Comparative Study of Pressure Frequency Response
We present the fabrication and characterization of flexible planar electrodynamic loudspeakers. Conductive spirals are fabricated on a flexible and transparent polyethylene terephthalate substrate via screen printing. Different geometries (circular and rectangular) and sizes of the conductive spirals are investigated to understand their impact on the
performance. The optimized circular spiral allows achieving an average sound pressure level of 63 dB at 1m distance in 2kHz-20kHz band, proving the suitability of these devices as high-frequency loudspeaker drivers
Smart Approach for the Design of Highly Selective Aptamer-Based Biosensors
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
Smart Approach for the Design of Highly Selective Aptamer-Based Biosensors
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
Flexible Screen Printed Aptasensor for Rapid Detection of Furaneol: A Comparison of CNTs and AgNPs Effect on Aptasensor Performance
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
Theoretical Analysis of Divalent Cation Effects on Aptamer Recognition of Neurotransmitter Targets
Aptamer-based sensing of small molecules such as dopamine and serotonin in
the brain, requires characterization of the specific aptamer sequences in
solutions mimicking the in vivo environment with physiological ionic
concentrations. In particular, divalent cations (Mg2+ and Ca2+) present in
brain fluid, have been shown to affect the conformational dynamics of aptamers
upon target recognition. Thus, for biosensors that transduce aptamer structure
switching as the signal response, it is critical to interrogate the influence
of divalent cations on each unique aptamer sequence. Herein, we demonstrate the
potential of molecular dynamics simulations to predict the behaviour of
dopamine and serotonin aptamers on sensor surfaces. The simulations enable
molecular-level visualization of aptamer conformational changes that, in some
cases, are significantly influenced by divalent cations. The correlations of
theoretical simulations with experimental findings validate the potential for
molecular dynamics simulations to predict aptamer-specific behaviors on
biosensorsComment: This is an old versio
Flexible Screen-Printed Amperometric Sensors Functionalized With Spray-Coated Carbon Nanotubes and Electrodeposited Cu Nanoclusters for Nitrate Detection
In this work, we present a novel, sensitive,
easy-to-fabricate, flexible amperometric sensor constituted
by screen-printed silver (Ag) electrodes functionalized with
a copper (Cu) film electrodeposited on top of a spray coated
network of single-walled carbon nanotubes (SWCNTs). The
Cu/SWCNTs/Ag electrode showed excellent catalytic activity
towards the electro-reduction of nitrate ions at neutral pH with
a significant increase in cathodic peak currents in comparison
with the electrode without SWCNTs (Cu/Ag). The developed
Cu/SWCNTs/Ag sensor showed a wide linear detection range
from 0.5 μM to 6.0 mM (0.31 mg/l to 372.02 mg/l) with good
sensitivity (18.39 μA/mM) and a calculated limit of detection (LOD) of 0.166 nM (10.29 μg/l). It also showed a good selectivity
(maximum standard deviation (SD) was 3.25 μA) towards different interfering ions (Fe 2+, Na+, Cu 2+, SO2
4−, CH 3 COO−,
Cl−, NO−
2 and HCO−
3 ), as well as good reproducibility, mechanical durability, time and temperature stability. In real sample
analysis (tap and river water), the sensor exhibited good agreement with the compared outcome of high-performance liquid chromatography (HPLC) measurements, proving to be a promising analytical tool for the detection of nitrate in water