Issue 9, 2022

Detecting bacterial infections in wounds: a review of biosensors and wearable sensors in comparison with conventional laboratory methods

Abstract

Bacterial infection is a common impediment towards wound healing. Detecting bacterial infections is important to promote wound healing and curb chronic non-healing wounds. In this review, we firstly discuss bacterial communities, including aerobic and anaerobic bacteria in various types of wounds. Following the discussion of wound sampling methods (swab, biopsy) for different wounds, we then discuss laboratory based conventional methods (bacteria cultures, Gram staining, analytical profile index systems, polymerase chain reaction, and gas chromatography coupled with mass spectrometry), focusing on their recent improvement. After that we discussed the contemporary biosensor methods, including e-Nose, electrochemical sensors, surface enhanced Raman spectroscopy, and nucleic acid lateral flow immunoassay. Biosensors embedded into wound dressing, termed wearable sensors or smart wound dressing, are also discussed for their ability of enabling bacteria detection directly from wound sites without the need for obtaining swab/biopsy samples. We have compared all the detection methods for their performance according to their respective targets (either bacteria cells or volatile/non-volatile metabolites); after that we evaluate the suitability of various methods in providing timely and accurate diagnostic results towards real-time, point-of-care testing of bacterial infections.

Graphical abstract: Detecting bacterial infections in wounds: a review of biosensors and wearable sensors in comparison with conventional laboratory methods

Article information

Article type
Critical Review
Submitted
24 janv. 2022
Accepted
28 mars 2022
First published
30 mars 2022

Analyst, 2022,147, 1756-1776

Detecting bacterial infections in wounds: a review of biosensors and wearable sensors in comparison with conventional laboratory methods

N. A. B. Mohamed Salleh, Y. Tanaka, L. Sutarlie and X. Su, Analyst, 2022, 147, 1756 DOI: 10.1039/D2AN00157H

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