Development and validation of a qPCR-based method for quantifying Shiga toxin-encoding and other lambdoid bacteriophages
Article first published online: 9 FEB 2010
© 2010 Society for Applied Microbiology and Blackwell Publishing Ltd
Volume 12, Issue 5, pages 1194–1204, May 2010
How to Cite
Rooks, D. J., Yan, Y., McDonald, J. E., Woodward, M. J., McCarthy, A. J. and Allison, H. E. (2010), Development and validation of a qPCR-based method for quantifying Shiga toxin-encoding and other lambdoid bacteriophages. Environmental Microbiology, 12: 1194–1204. doi: 10.1111/j.1462-2920.2010.02162.x
- Issue published online: 23 APR 2010
- Article first published online: 9 FEB 2010
- Received 3 August, 2009; accepted 14 December, 2009.
To address whether seasonal variability exists among Shiga toxin-encoding bacteriophage (Stx phage) numbers on a cattle farm, conventional plaque assay was performed on water samples collected over a 17 month period. Distinct seasonal variation in bacteriophage numbers was evident, peaking between June and August. Removal of cattle from the pasture precipitated a reduction in bacteriophage numbers, and during the winter months, no bacteriophage infecting Escherichia coli were detected, a surprising occurrence considering that 1031 tailed-bacteriophages are estimated to populate the globe. To address this discrepancy a culture-independent method based on quantitative PCR was developed. Primers targeting the Q gene and stx genes were designed that accurately and discriminately quantified artificial mixed lambdoid bacteriophage populations. Application of these primer sets to water samples possessing no detectable phages by plaque assay, demonstrated that the number of lambdoid bacteriophage ranged from 4.7 × 104 to 6.5 × 106 ml−1, with one in 103 free lambdoid bacteriophages carrying a Shiga toxin operon (stx). Specific molecular biological tools and discriminatory gene targets have enabled virus populations in the natural environment to be enumerated and similar strategies could replace existing propagation-dependent techniques, which grossly underestimate the abundance of viral entities.