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FARPA-based tube array coupled with quick DNA extraction enables ultra-fast bedside detection of antibiotic-resistant pathogens.

Authors :
Huang, Jinling
Yue, Huijie
Wei, Wei
Shan, Jingwen
Zhu, Yue
Feng, Liying
Ma, Yi
Zou, Bingjie
Wu, Haiping
Zhou, Guohua
Source :
Analyst. 7/7/2024, Vol. 149 Issue 13, p3607-3614. 8p.
Publication Year :
2024

Abstract

Rapid and accurate detection of pathogens and antimicrobial-resistant (AMR) genes of the pathogens are crucial for the clinical diagnosis and effective treatment of infectious diseases. However, the time-consuming steps of conventional culture-based methods inhibit the precise and early application of anti-infection therapy. For the prompt treatment of pathogen-infected patients, we have proposed a novel tube array strategy based on our previously reported FARPA (FEN1-aided recombinase polymerase amplification) principle for the ultra-fast detection of antibiotic-resistant pathogens on site. The entire process from "sample to result" can be completed in 25 min by combining quick DNA extraction from a urine sample with FARPA to avoid the usually complicated DNA extraction step. Furthermore, a 36-tube array made from commercial 384-well titre plates was efficiently introduced to perform FARPA in a portable analyser, achieving an increase in the loading sample throughput (from several to several tens), which is quite suitable for the point-of-care testing (POCT) of multiple pathogens and multiple samples. Finally, we tested 92 urine samples to verify the performance of our proposed method. The sensitivities for the detection of E. coli, K. pneumoniae, E. faecium, and E. faecalis were 92.7%, 93.8%, 100% and 88.9%, respectively. The specificities for the detection of the four pathogens were 100%. Consequently, our rapid, low-cost and user-friendly POCT method holds great potential for guiding the rational use of antibiotics and reducing bacterial resistance. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00032654
Volume :
149
Issue :
13
Database :
Academic Search Index
Journal :
Analyst
Publication Type :
Academic Journal
Accession number :
178020071
Full Text :
https://doi.org/10.1039/d4an00185k