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Electrochemical Aptasensor for the Detection of the Key Virulence Factor YadA of . | LitMetric

AI Article Synopsis

Article Abstract

New point-of-care (POC) diagnosis of bacterial infections are imperative to overcome the deficiencies of conventional methods, such as culture and molecular methods. In this study, we identified new aptamers that bind to the virulence factor Yersinia adhesin A (YadA) of Yersinia enterocolitica using cell-systematic evolution of ligands by exponential enrichment (cell-SELEX). Escherichia coli expressing YadA on the cell surface was used as a target cell. After eight cycles of selection, the final aptamer pool was sequenced by high throughput sequencing using the Illumina Novaseq platform. The sequencing data, analyzed using the Geneious software, was aligned, filtered and demultiplexed to obtain the key nucleotides possibly involved in the target binding. The most promising aptamer candidate, Apt1, bound specifically to YadA with a dissociation constant (Kd) of 11 nM. Apt1 was used to develop a simple electrochemical biosensor with a two-step, label-free design towards the detection of YadA. The sensor surface modifications and its ability to bind successfully and stably to YadA were confirmed by cyclic voltammetry, impedance spectroscopy and square wave voltammetry. The biosensor enabled the detection of YadA in a linear range between 7.0 × 104 and 7.0 × 107 CFU mL−1 and showed a square correlation coefficient >0.99. The standard deviation and the limit of detection was ~2.5% and 7.0 × 104 CFU mL−1, respectively. Overall, the results suggest that this novel biosensor incorporating Apt1 can potentially be used as a sensitive POC detection system to aid the diagnosis of Y. enterocolitica infections. Furthermore, this simple yet innovative approach could be replicated to select aptamers for other (bacterial) targets and to develop the corresponding biosensors for their detection.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9405658PMC
http://dx.doi.org/10.3390/bios12080614DOI Listing

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