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Uracil-DNA-glycosylase-assisted loop-mediated isothermal amplification for detection of bacteria from urine samples with reduced contamination

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Abstract

Loop-mediated isothermal amplification (LAMP) is a useful molecular biology technology for analytical applications, but it is prone to contamination because of escaped aerosols, leading to false positive results. This report establishes an integrated, rapid, and accurate method to detect bacteria in urine samples by incorporating uracil-DNA-glycosylase (UDG) into real-time loop-mediated isothermal amplification (RT-LAMP). To do this, nucleic acids from five clinically important uropathogens, including Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Proteus mirabilis, and Enterococcus faecalis, were directly captured and concentrated using Flinders Technology Associates (FTA) Elute cards. Following elution, the extracted DNAs were specifically amplified with sets of LAMP primers. The added UDG in the modified LAMP reaction excises uracils from previously amplified products or contaminants and generates apyrimidinic (AP) sites, reducing false positive rates. This UDG-assisted RT LAMP strategy was able to degrade carryover contaminants to as little as 1 femtogram (10−15 g). The assay showed a limit of detection of 104 CFU mL−1 with a sensitivity of 94.1% and a specificity of 95.0%. Both the sensitivity and specificity were improved compared to LAMP carried out without UDG. Our results indicate that the UDG-assisted RT LAMP is of great potential for rapid and precise analysis of nucleic acids in real applications.

Graphical abstract: Uracil-DNA-glycosylase-assisted loop-mediated isothermal amplification for detection of bacteria from urine samples with reduced contamination

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Supplementary files

Article information


Submitted
18 May 2020
Accepted
31 Jul 2020
First published
11 Aug 2020

Analyst, 2020, Advance Article
Article type
Paper

Uracil-DNA-glycosylase-assisted loop-mediated isothermal amplification for detection of bacteria from urine samples with reduced contamination

Y. Zeng, M. Liu, Y. Xia and X. Jiang, Analyst, 2020, Advance Article , DOI: 10.1039/D0AN01001D

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