Green Clinical Microbiology: Sustainable PCR-based Detection of Bacterial Pathogens in Environmental and Clinical Samples

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Hanaa Neamah Abdullah, Haider Ammar Alubaidy, Zahraa Essa Radhi, Sura A. Al-Ganahi

Abstract

Antimicrobial resistance continues to challenge healthcare systems worldwide. While regularly diagnostic procedures create huge chemical, plastic, and energy waste. This may disagree with the principles of sustainable laboratory management. This study assesses sustainable strategies for molecular detection through the optimization of PCR protocols of Staphylococcus aureus, Pseudomonas aeruginosa, and Escherichia coli in clinical and environmental samples. Reduced reaction volumes, non-toxic DNA staining reagents, and energy-efficient thermal cycling conditions, were implemented as green laboratory modifications. The reason for using green laboratory modifications is to minimize resource consumption without compromising analytical performance. The improved protocol demonstrated 95% amplification success rate under the optimized conditions. Interestingly, clinical samples exhibited the highest bacterial detection rate among the tested sample types, followed by water, soil, and surface-swab samples. Significantly, the optimized system reduced reagent consumption by approximately 40%. Single-use plastic tube consumption was also reduced by 33%, from 60 to 40 tubes per run. This led to decreased plastic use and hazardous laboratory waste. Moreover, this can lower energy requirements and maintain reliable results. These results demonstrate that sustainable PCR protocols can effectively integrate environmental responsibility with high-quality molecular diagnostics. The combination of emerging procedures could improve diagnostic efficiency and reduce environmental impact. For example, microfluidic platforms, biodegradable biosensors, and automated low-volume molecular systems. The aim of this study was to assess the effectiveness of green molecular diagnostics in reducing laboratory waste, chemical use, and energy consumption while maintaining accurate pathogen detection.

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