Literature DB >> 35853169

Electrochemical Sensors Based on MoSx -Functionalized Laser-Induced Graphene for Real-Time Monitoring of Phenazines Produced by Pseudomonas aeruginosa.

Keren Zhou1,2, Vinay Kammarchedu1,2, Derrick Butler1,2, Pouya Soltan Khamsi1,2, Aida Ebrahimi1,2,3.   

Abstract

Pseudomonas aeruginosa (P. aeruginosa) is an opportunistic pathogen causing infections in blood and implanted devices. Traditional identification methods take more than 24 h to produce results. Molecular biology methods expedite detection, but require an advanced skill set. To address these challenges, this work demonstrates functionalization of laser-induced graphene (LIG) for developing flexible electrochemical sensors for P. aeruginosa based on phenazines. Electrodeposition as a facile approach is used to functionalize LIG with molybdenum polysulfide (MoSx ). The sensor's limit of detection (LOD), sensitivity, and specificity are determined in broth, agar, and wound simulating medium (WSM). Control experiments with Escherichia coli, which does not produce phenazines, demonstrate specificity of sensors for P. aeruginosa. The LOD for pyocyanin (PYO) and phenazine-1-carboxylic acid (PCA) is 0.19 × 10-6  and 1.2 × 10-6  m, respectively. Furthermore, the highly stable sensors enable real-time monitoring of P. aeruginosa biofilms over several days. Comparing square wave voltammetry data over time shows time-dependent generation of phenazines. In particular, two configurations-"Normal" and "Flipped"-are studied, showing that the phenazines time dynamics vary depending on how cells interact with sensors. The reported results demonstrate the potential of the developed sensors for integration with wound dressings for early diagnosis of P. aeruginosa infection.
© 2022 Wiley-VCH GmbH.

Entities:  

Keywords:  biofilm infection; electrochemical sensors; laser-induced graphene; phenazines; pseudomonas aeruginosa; wound infection

Mesh:

Substances:

Year:  2022        PMID: 35853169      PMCID: PMC9547893          DOI: 10.1002/adhm.202200773

Source DB:  PubMed          Journal:  Adv Healthc Mater        ISSN: 2192-2640            Impact factor:   11.092


  51 in total

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Journal:  ACS Nano       Date:  2021-12-09       Impact factor: 15.881

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Authors:  Daniel L Bellin; Hassan Sakhtah; Yihan Zhang; Alexa Price-Whelan; Lars E P Dietrich; Kenneth L Shepard
Journal:  Nat Commun       Date:  2016-01-27       Impact factor: 14.919

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