Self-priming mediated Chain Extension Cysteine Catalytic Oxidation‑Based Colorimetric Method for Sensitive Pseudomonas aeruginosa Detection

Abstract

Nursing hospital infections with Pseudomonas aeruginosa (P. aeruginosa) pose a significant risk to human health, especially these immunosuppressed patients receiving surgical therapy. Consequently, it is imperative to create a novel and portable P. aeruginosa analysis method for the early diagnosis of P. aeruginosa infections. For sensitive and reliable P. aeruginosa analysis, we depict here a novel colorimetric approach based on rolling circle amplification (RCA) based construction of detection scaffold and self-priming mediated signal recycling. In this method, the RCA product is attached to the plate surface to recognize P. aeruginosa targets and initiate the chain extension mediated cysteine catalytic oxidation based colorimetric reaction. This method involves activating the RCA to generate several RCA products with repetitive functional portions by cyclizing the padlock sequence using primer sequences. To facilitate the color reaction based on gold nanoparticles, the produced G-rich sequences during the self-priming mediated signal recycling process can fold to G-quadruplex DNAzyme, which can catalyze the conversion of cysteine to cystine and produce color changes that can be observed directly with the naked eye. Based on this elegant design, the method has a broad detection range and a low limit of detection of 3.6 cfu/mL. In addition, this colorimetric approach showed good selectivity to target bacteria. This technology has great potential for use in biomedical diagnostics and bio-sensing of pathogenic bacteria.

Supplementary files

Article information

Article type
Paper
Submitted
05 Feb 2025
Accepted
25 May 2025
First published
29 May 2025

Anal. Methods, 2025, Accepted Manuscript

Self-priming mediated Chain Extension Cysteine Catalytic Oxidation‑Based Colorimetric Method for Sensitive Pseudomonas aeruginosa Detection

J. Xie, L. Xia, J. Han, Z. Wang and J. Huang, Anal. Methods, 2025, Accepted Manuscript , DOI: 10.1039/D5AY00197H

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