Advances in optical biosensors as alternative diagnostics for clinical determination of ESKAPE bacteria
The global rise of antimicrobial resistance (AMR), manifesting as multidrug-resistant, extremely drug-resistant, and pandrug-resistant pathogens, is causing morbidities which are alarmingly translating to mortalities. The issue is pertinent to low and middle-income countries, which rely heavily on t...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-12-01
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| Series: | Sensors and Actuators Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666053925000839 |
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| Summary: | The global rise of antimicrobial resistance (AMR), manifesting as multidrug-resistant, extremely drug-resistant, and pandrug-resistant pathogens, is causing morbidities which are alarmingly translating to mortalities. The issue is pertinent to low and middle-income countries, which rely heavily on their primary and secondary healthcare setups with severely constrained infrastructure and diagnostics. Traditional and molecular diagnostic methods are effective, but have long turnaround times, are expensive, and require specialized facilities. Due to these constraints, these facilities are usually not present at the primary healthcare centers. This review explores the urgent need for alternative diagnostic strategies beyond conventional pathogen identification and antibiotic susceptibility testing, emphasizing the detection of bacterial metabolites and virulence factors as innovative biomarkers for AMR. This article provides critical insight into tailoring optical biosensor technologies as alternate diagnostics for ESKAPE pathogens in resource-limited settings. It highlights the integration of these biosensing platforms with emerging metabolomics and biomarker profiling technologies, offering a promising route toward point-of-care diagnostics. In addition, incorporating artificial intelligence and machine learning algorithms in signal processing and feature extraction enhances biosensor performance and accelerates diagnostic accuracy. The review critiques the current state of the art in AMR diagnostics and provides strategic inroads for developing robust and deployable diagnostics to help better bacterial infection control. |
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| ISSN: | 2666-0539 |