Evaluating different approaches for the quantification of oomycete apple replant pathogens, and their relationship with seedling growth reductions
Investigations into inoculum sources and disease management strategies require effective pathogen quantification techniques, which should ideally also be reflective of the extent of plant damage. The current study investigated whether determination of relative pathogen DNA quantity in root tissue can improve the assessment of plant damage by several oomycete apple replant pathogens when compared to absolute DNA quantifications and percent roots infected. Published real-time quantitative PCR (qPCR) assays were utilized to quantify pathogen DNA, except for Phytopythium vexans for which a new qPCR assay was developed. Relative pathogen DNA quantifications employed a mutated Escherichia coli gene spiked into the DNA extraction buffer. Pathogen quantifications were not improved through relative DNA quantifications since relative DNA quantities were highly and significantly correlated with absolute pathogen DNA quantities. This was evident from: (i) glasshouse experiments where five oomycete apple replant disease pathogens (Pythium sylvaticum, Pythium irregulare, Pythium ultimum, P. vexans and Phytophthora cactorum) were quantified from artificially inoculated apple seedlings roots, and (ii) quantification of P. irregulare from naturally-infected nursery tree roots. Relative- and absolute pathogen DNA quantities in infected glasshouse seedling roots (all five species) and nursery tree roots (P. irregulare), were furthermore significantly correlated with percent roots infected. Pathogen root DNA quantities (relative and absolute) obtained from the fine feeder root systems of seedlings from the glasshouse trials were significantly negatively correlated with increase in seedling length for P. sylvaticum, P. vexans and P. ultimum infected seedlings. This, however, was not true for P. cactorum and P. irregulare. The percent infected roots also had a significant negative correlation with increase in seedling length for P. sylvaticum, P. vexans and P. ultimum and P. irregulare, but not for P. cactorum.
KeywordsPathogen quantification Apples replant pathogens
We would like to thank the South African Apple and Pear Producer’s Association (SAAPPA), the Technology and Human Resources for Industry Programme (THRIP) for financially supporting the research. We would also like to thank Marieta Van der Rijst (Agricultural Research Council, Biometry Unit, Stellenbosch, South Africa) for statistical analyses of the data, and C. A. Lévesque (Central Experimental Farm, Agriculture and Agri-Food Canada, Ottawa, Ontario, Canada) for providing the putative inositol polyphosphate 5-phosphatase gene sequences of various Pythium spp.
Compliance with ethical standards
Our manuscript “Evaluating different approaches for the quantification of oomycete apple replant pathogens, and their relationship with seedling growth reductions” has no potential conflicts of interest (financial or non-financial) and did not involve research with human participants and/or animals.
- Adhikari, B.N., Hamilton, J.P., Zerillo, M.M., Tisserat, N., Lvesque, A. and Buel, C.R. 2013. Comparative genomics reveals insight into virulence strategies of plant pathogenic oomycetes. PLoS One. https://doi.org/10.1371/journal.pone.0075072
- Erwin, D. C., & Ribeiro, O. K. (1996). Phytophthora diseases worldwide. APS Press, St. Paul, Minnesota, USA.Google Scholar
- Eshraghi, L., Aryamanseh, N., Anderson, J. P., Shearer, B., McComb, J. A., Hardy, G. E. S. J., & O’Brien, P. A. (2011). A quantitative PCR assay for accurate in planta quantification of the necrotrophic pathogen Phytophthora cinnamomi. European Journal of Plant Pathology, 131, 419–430.CrossRefGoogle Scholar
- Fall, M. L., Tremblay, D. M., Gobeil-Richard, M., Couillard, J., Rocheleau, H., Van der Heyden, H., Levesque, C. A., Beaulieu, C., & Carisse, O. (2015). Infection efficiency of four Phytophthora infestans clonal lineages and DNA-based quantification of sporangia. PLoS One, 10, e0136312. https://doi.org/10.1371/journal.pone.0136312.CrossRefGoogle Scholar
- Halliday, E., Griffith, J. F., & Gast, R. J. (2010). Use of an exogenous plasmid standard and quantitative PCR to monitor spatial and temporal distribution of Enterococcus spp. in beach sands. Methods, 8, 146–154.Google Scholar
- Kearse, M., Moir, R., Wilson, A., Stones-Havas, S., Cheung, M., Sturrock, S., Buxton, S., Cooper, A., Markowitz, S., Duran, C., & Thierer, T. (2012). Geneious basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data. Bioinformatics, 28, 1647–1649.CrossRefGoogle Scholar
- Klerks, M. M., van Bruggen, A. H., Zijlstra, C., & Donnikov, M. (2006). Comparison of methods of extracting salmonella enterica serovar enteritidis dna from environmental substrates and quantification of organisms by using a general internal procedural control. Applied and Environmental Microbiology, 72, 3879–3886.CrossRefGoogle Scholar
- Lamprecht, S. C. (1986). A new disease of Medicago truncatula caused by Cylindrocladium scoparium. Phytophylactica, 18, 111–114.Google Scholar
- Moein, S. (2016). Quantification of apple replant pathogens from roots, and their occurrence in irrigation water and nursery trees. MSc thesis, Stellenbosch University, South Africa, 124pp.Google Scholar
- Ott, R.L. 1998. An Introduction to Statistical methods and data analysis. Belmont, California: Duxbury Press: 807–837.Google Scholar
- Schena, L., Duncan, J., & Cooke, D. (2008). Development and application of a PCR-based ‘molecular tool box’ for the identification of Phytophthora species damaging forests and natural ecosystems. Plant Pathology, 57, 64–75.Google Scholar
- Schena, L., Li Destri Nicosia, M. G. L., Sanzabi, S. M., Faedda, R., Ippolito, A., & Cacciola, S. O. (2013). Development of quantitative PCR detection methods for phytopathogenic fungi and oomycetes. Journal of Plant Pathology, 95, 7–24.Google Scholar
- Shapiro, S. S. & Francia, R. S. (1972). An approximate analysis of variance test for normality. Journal of the American Statistical Association, 67, 215–216.Google Scholar
- Tewoldemedhin, Y. T., Mazzola, M., Botha, W. J., Spies, C. F. J., & McLeod, A. (2011b). Characterization of fungi (Fusarium and Rhizoctonia) and oomycetes (Phytophthora and Pythium) associated with apple orchards in South Africa. European Journal of Plant Pathology, 130, 215–229.CrossRefGoogle Scholar
- Utkhede, R., Smith, E., & Palmer, R. (1992). Effect of root rot fungi and root-lesion nematodes on the growth of young apple trees grown in apple replant disease soil. Plant Disease and Protection, 99, 414–419.Google Scholar