4.3 Article

Selective detection of live bacteria combining propidium monoazide sample treatment with microarray technology

Journal

JOURNAL OF MICROBIOLOGICAL METHODS
Volume 76, Issue 3, Pages 253-261

Publisher

ELSEVIER
DOI: 10.1016/j.mimet.2008.11.004

Keywords

Propidium monoazide; Viability; Molecular diagnostics; Microarray detection; Quantitative PCR

Funding

  1. U.S. Army Research Office [DAAD 19-03-1-0198]

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The use of DNA-based molecular detection tools for bacterial diagnostics is hampered by the inability to distinguish signals originating from live and dead cells. The detection of live cells is typically most relevant in molecular diagnostics. DNA-intercalating dyes like ethidium monoazide and propidium monoazide (PMA) offer a possibility to selectively remove cells with compromised cell membranes from the analysis. Once these dyes enter a cell, they bind to DNA and can be covalently crosslinked to it by light exposure. PCR amplification of such modified DNA is strongly inhibited. in this study we evaluated the suitability of propidium monoazide treatment to exclude isopropanol-killed cells from detection in defined mixtures using diagnostic microarray technology. The organisms comprised Pseudomonas aeruginosa, Listeria monocytogenes, Salmonella typhimurium, Serratia marcescens, and Escherichia coli O157:H7. PCR products obtained from amplification of chaperonin 60 genes (cpn60; coding for GroEL) were hybridized to a custom-designed microarray containing strain-specific cpn60-based 35-mer oligonucleotide probes. Results were compared with data from quantitative PCR, which confirmed that PMA could successfully inhibit amplification of DNA from killed cells in the mixtures. Although microarray data based on analysis of end-point PCR amplicons is not quantitative, results showed a significant signal reduction when targeting killed cells and consistently agreed with qPCR results. Treatment of samples with PMA in combination with diagnostic microarray detection can therefore be considered beneficial when analyzing mixtures of intact and membrane-compromised cells. Minimization of detection signals deriving from dead cells will render data more relevant in studies including pathogen risk assessment. (C) 2008 Elsevier B.V. All rights reserved.

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