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J Microbiol Methods. 2007 Apr;69(1):154-60. Epub 2006 Dec 30.

Optimization of methods for detecting Mycobacterium avium subsp. paratuberculosis in environmental samples using quantitative, real-time PCR.

Author information

1
AWMRU, USDA-ARS, 230 Bennett Lane, Bowling Green, KY 42104, USA. klcook@ars.usda.gov

Abstract

Detection of Johne's disease, an enteric infection of cattle caused by Mycobacterium avium subsp. paratuberculosis (M. paratuberculosis), has been impeded by the lack of rapid, reliable detection methods. The goal of this study was to optimize methodologies for detecting M. paratuberculosis in manure from an infected dairy cow or in contaminated soil samples using a quantitative, real-time PCR (QRT-PCR) based analysis. Three different nucleic acid extraction techniques, the efficiency of direct versus indirect sample extraction, and sample pooling were assessed. The limit of detection was investigated by adding dilutions of M. paratuberculosis to soil. Results show that the highest yield (19.4+/-2.3 microg(-1) DNA extract) and the highest copy number of the targeted M. paratuberculosis IS900 sequence (1.3+/-0.2x10(8) copies g(-1) manure) were obtained with DNA extracted from manure using Qbiogene's Fast DNA Spin kit for soil. Pooling ten samples of M. paratuberculosis-contaminated soil improved the limit of detection ten fold (between 20 and 115 M. paratuberculosis cells g(-1) soil). Detection was between 65% and 95% higher when samples were extracted directly using bead-beating than when using pre-treatment with cell extraction buffers. The final soil-sampling and extraction regime was applied for detection of M. paratuberculosis in pasture soil after the removal of a M. paratuberculosis culture positive dairy cow. M. paratuberculosis remained in the pasture soil for more than 200 days. Results from these studies suggest that DNA extraction method, sampling protocol and PCR conditions each critically influence the outcome and validity of the QRT-PCR analysis of M. paratuberculosis concentrations in environmental samples.

PMID:
17257697
DOI:
10.1016/j.mimet.2006.12.017
[Indexed for MEDLINE]

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