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1.
Talanta ; 256: 124275, 2023 May 01.
Article in English | MEDLINE | ID: covidwho-2183604

ABSTRACT

In this study, it is confirmed that without addition of organic solvent and embedding polymer hydrogel into glass nanopore, bare glass nanopore can faithfully measure various lengths of DNA duplexes from 200 to 3000 base pairs with 200 base pairs resolution, showing well-separated peak amplitudes of blockage currents. Furthermore, motivated by this readout capability of duplex DNA, amplicons from Polymerase Chain Reaction (PCR) amplification are straightforwardly discriminated by bare glassy nanopore without fluorescent labeling. Except simultaneous discrimination of up to 7 different segments of the same lambda genome, various pathogenic bacteria and viruses including SARS-CoV-2 and its mutants in clinical samples can be discriminated at high resolution. Moreover, quantitative measurement of PCR amplicons is obtained with detection range spanning from 0.75 aM to 7.5 pM and detection limit of 7.5 aM, which reveals that bare glass nanopore can faithfully disclose PCR results without any extra labeling.


Subject(s)
COVID-19 , Nanopores , Humans , SARS-CoV-2/genetics , Reading , Polymerase Chain Reaction , DNA/genetics , Bacteria , COVID-19 Testing
2.
Biosensors (Basel) ; 12(8)2022 Jul 27.
Article in English | MEDLINE | ID: covidwho-2023153

ABSTRACT

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.


Subject(s)
Ammonium Compounds , Aptamers, Nucleotide , Biosensing Techniques , Aptamers, Nucleotide/chemistry , Ligands , SELEX Aptamer Technique/methods
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