Evaluating different approaches for the quantification of oomycete apple replant pathogens, and their relationship with seedling growth reductions

  • S. Moein
  • M. Mazzola
  • C. F. J. Spies
  • A. McLeodEmail author


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.


Pathogen 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.


  1. 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.
  2. Catal, M., Erler, F., Fulbright, D. W., & Adams, G. C. (2013). Real-time quantitative PCR assays for evaluation of soybean varieties for resistance to the stem and root rot pathogen Phytophthora sojae. European Journal of Plant Pathology, 137, 859–869.CrossRefGoogle Scholar
  3. Daniell, T., Davidson, J., Alexander, C., Caul, S., & Roberts, D. (2012). Improved real-time PCR estimation of gene copy number in soil extracts using an artificial reference. Journal of Microbiological Methods, 91, 38–44.CrossRefGoogle Scholar
  4. Emmett, B., Nelson, E. B., Kessler, A., & Bauerle, T. L. (2014). Fine-root system development and susceptibility to pathogen colonization. Planta, 239, 325–340.CrossRefGoogle Scholar
  5. Engelbrecht, J., Duing, T. A., & Van den Berg, N. (2013). Development of a nested quantitative real-time PCR for detecting Phytophthora cinnamomi in Persea americana rootstocks. Plant Disease, 97, 1012–1017.CrossRefGoogle Scholar
  6. Erwin, D. C., & Ribeiro, O. K. (1996). Phytophthora diseases worldwide. APS Press, St. Paul, Minnesota, USA.Google Scholar
  7. 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
  8. 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. Scholar
  9. 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
  10. 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
  11. Kernaghan, G., Reeleder, R., & Hoke, S. (2008). Quantification of Pythium populations in ginseng soils by culture dependent and real-time PCR methods. Applied Soil Ecology, 40, 447–455.CrossRefGoogle Scholar
  12. 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
  13. Lamprecht, S. C. (1986). A new disease of Medicago truncatula caused by Cylindrocladium scoparium. Phytophylactica, 18, 111–114.Google Scholar
  14. Le Floch, G., Tambong, J., Vallance, J., Tirilly, Y., Levesque, A., & Rey, P. (2007). Rhizosphere persistence of three Pythium Oligandrum strains in tomato soilless culture assessed by DNA macroarray and real-time PCR. FEMS Microbiology Ecology, 61, 317–326.CrossRefGoogle Scholar
  15. Li, M., Inada, M., Watanabe, H., Suga, H., & Kageyama, K. (2013). Simultaneous detection and quantification of Phytophthora nicotianae and P. cactorum, and distribution analyses in strawberry greenhouses by duplex real-time PCR. Microbes and Environments, 28, 195–203.CrossRefGoogle Scholar
  16. Matheron, M., Young, J., & Matejka, J. (1988). Phytophthora root and crown rot in apple trees in Arizona. Plant Disease, 72, 481–484.CrossRefGoogle Scholar
  17. Mazzola, M. (1998). Elucidation of the microbial complex having a causal role in the development of apple replant disease in Washington. Phytopathology, 88, 930–938.CrossRefGoogle Scholar
  18. Mazzola, M., & Manici, L. M. (2012). Apple replant disease: Role of microbial ecology in cause and control. Annual Review of Phytopathology, 50, 45–65.CrossRefGoogle Scholar
  19. Mazzola, M., Brown, J., Zhao, X., Izzo, A. D., & Fazio, G. (2009). Interaction of Brassicaceous seed meal and apple rootstock on recovery of Pythium spp. and Pratylenchus penetrans from roots grown in replant soils. Plant Disease, 93, 51–57.CrossRefGoogle Scholar
  20. Mazzola, M., Hewavitharana, S. S., & Strauss, S. L. (2015). Brassica seed meal soil amendments transform the rhizosphere microbiome and improve apple production through resistance to pathogen reinfestation. Phytopathology, 105, 460–469.CrossRefGoogle Scholar
  21. Mendes, R., Garbeva, P., & Raaijmakers, J. M. (2013). The rhizosphere microbiome: Significance of plant beneficial, plant pathogenic, and human pathogenic microorganisms. FEMS Microbiological Reviews, 37, 634–663.CrossRefGoogle Scholar
  22. 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
  23. Ott, R.L. 1998. An Introduction to Statistical methods and data analysis. Belmont, California: Duxbury Press: 807–837.Google Scholar
  24. Okubara, P. A., Schroeder, K. L., & Paulitz, T. C. (2005). Real-time polymerase chain reaction: Applications to studies on soilborne pathogens. Canadian Journal of Plant Pathology, 27, 300–313.CrossRefGoogle Scholar
  25. 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
  26. 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
  27. Schroeder, K., Okubara, P., Tambong, J., Lévesque, C., & Paulitz, T. (2006). Identification and quantification of pathogenic Pythium spp. from soils in eastern Washington using real-time polymerase chain reaction. Phytopathology, 96, 637–647.CrossRefGoogle Scholar
  28. 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
  29. Spies, C. F. J., Mazzola, M., & McLeod, A. (2011). Characterisation and detection of Pythium and Phytophthora species associated with grapevines in South Africa. European Journal of Plant Pathology, 131, 103–119.CrossRefGoogle Scholar
  30. Tewoldemedhin, Y. T., Mazzola, M., Labuschagne, I., & McLeod, A. (2011a). A multi-phasic approach reveals that apple replant disease is caused by multiple biological agents, with some agents acting synergistically. Soil Biology and Biochemistry, 43, 1917–1927.CrossRefGoogle Scholar
  31. 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
  32. Tewoldemedhin, Y. T., Mazzola, M., Mostert, L., & McLeod, A. (2011c). Cylindrocarpon species associated with apple tree roots in South Africa and their quantification using real-time PCR. European Journal of Plant Pathology, 129, 637–651.CrossRefGoogle Scholar
  33. Untergrasser, A., Cutcutache, I., Koressaar, T., Ye, J., Faircloth, B. C., Remm, M., & Rozen, S. G. (2012). Primer 3—new capabilities and interfaces. Nucleic Acids Research, 40, 115–116.CrossRefGoogle Scholar
  34. 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
  35. Vandemark, G. J., & Barker, B. M. (2003). Quantifying Phytophthora medicaginis in susceptible and resistant alfafa with a real-time fluorescent PCR assay. Journal of Phytopathology, 151, 577–583.CrossRefGoogle Scholar
  36. Vandemark, G. J., & Grünwald, N. J. (2005). Use of real-time PCR to examine the relationship between disease severity in pea and Aphanomyces euteiches DNA content in roots. European Journal of Plant Pathology, 111, 309–316.CrossRefGoogle Scholar

Copyright information

© Koninklijke Nederlandse Planteziektenkundige Vereniging 2019

Authors and Affiliations

  • S. Moein
    • 1
  • M. Mazzola
    • 1
    • 2
  • C. F. J. Spies
    • 3
  • A. McLeod
    • 1
    Email author
  1. 1.Department of Plant PathologyUniversity of StellenboschStellenboschSouth Africa
  2. 2.United States Department of AgricultureAgricultural Research ServiceWenatcheeUSA
  3. 3.Agricultural Research Council – Plant Health and ProtectionStellenboschSouth Africa

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