An efficient method for zoospore production, infection and real-time quantification of Phytophthora cajani causing Phytophthora blight disease in pigeonpea under elevated atmospheric CO₂

Abstract

Background: Phytophthora blight caused by Phytophthora cajani is an emerging disease of pigeonpea (Cajanus cajan L.) affecting the crop irrespective of cropping system, cultivar grown and soil types. Current detection and identification methods for Phytophthora species rely primarily on cultural and morphological characteristics, the assessment of which is time-consuming and not always suitable. Sensitive and reliable methods for isolation, identification, zoospore production and estimating infection severity are therefore desirable in case of Phytophthora blight of pigeonpea.

Results: In this study, protocols for isolation and identification of Phytophthora blight of pigeonpea were standardized. Also the method for zoospore production and in planta infection of P. cajani was developed. Quantification of fungal colonization by P. cajani using real-time PCR was further standardized. Phytophthora species infecting pigeonpea was identified based on mycological characters such as growth pattern, mycelium structure and sporangial morphology of the isolates and confirmed through molecular characterization (sequence deposited in GenBank). For Phytophthora disease development, zoospore suspension of 1 × 10(5) zoospores per ml was found optimum. Phytophthora specific real-time PCR assay was developed using specific primers based on internal transcribed spacer (ITS) 1 and 2. Use of real-time PCR allowed the quantitative estimation of fungal biomass in plant tissues. Detection sensitivities were within the range of 0.001 pg fungal DNA. A study to see the effect of elevated CO₂ on Phytophthora blight incidence was also conducted which indicated no significant difference in disease incidence, but incubation period delayed under elevated CO₂ as compared to ambient level.

Conclusion: The zoospore infection method for Phytophthora blight of pigeonpea will facilitate the small and large scale inoculation experiments and thus devise a platform for rapid and reliable screening against Phytophthora blight disease of pigeonpea. qPCR allowed a reliable detection and quantification of P. cajani in samples with low pathogen densities. This can be useful in early warning systems prior to potential devastating outbreak of the disease.

Figure 1

Morphology of Phytophthora cajani isolate ICPC 1: (a) growth in Petriplate; (b) coenocytic mycelium; (c) hyphal swellings; (d) non-papillate sporangia; (e) zoospores; (f) oospore.

Figure 2

The maximum likelihood phylogenetic tree showing the relationship among the P. cajani isolates of this study and other Phytopthora spp. based on ITS sequences of 5.8S rDNA. Scale bar represent the genetic distance, proportional to the number of nucleotide differences between branch nodes. The significance of the nodes was estimated with 1000 bootstrap repetitions. The isolates of the current study is marked by Italics font.

Figure 3

Comparison on progression of PB incidence under ambient condition and elevated CO ₂ .

Figure 4

Calibration of qPCR for quantification of P. cajani : (a) Standard curve analysis: Standard curve showing the correlation between the log10 DNA amounts (ng) vs. the Ct values for 10 fold dilution of P. cajani pure genomic DNA. (b) Melting curve analysis: The melting curve (SYBR Green florescence versus temperature) of specific amplifications from the ITS sequences of 5.8S rDNA at different concentrations. The single pick of targeted amplicon at melting temperature (Tm) 79.8°C indicates the specificity of the qPCR primers to P. cajani. No contaminating product was detected in PCR reaction.

Figure 5

Chronological colonization profile of P. cajani in root tissues of inoculated pigeonpea (cv. ICP 7119) seedlings grown in three different CO ₂ conditions, ambient, 550 ppm and 700 ppm respectively. Absolute quantification of fungal DNA was determined in real time PCR assay using ITS sequences of 5.8S rDNA. Error bar represents the standard error of three biological replicationsat the 95% confidence interval.