Analysis of Volatile Profiles for Tracking Asymptomatic Infections of Phytophthora ramorum and Other Pathogens in Rhododendron - PubMed (original) (raw)

Analysis of Volatile Profiles for Tracking Asymptomatic Infections of Phytophthora ramorum and Other Pathogens in Rhododendron

Cai H Thompson et al. Phytopathology. 2021 Oct.

Abstract

Phytophthora ramorum is an invasive, broad host range pathogen that causes ramorum blight and sudden oak death in forest landscapes of western North America. In commercial nurseries, asymptomatic infections of nursery stock by P. ramorum and other Phytophthora species create unacceptable risk and complicate inspection and certification programs designed to prevent introduction and spread of these pathogens. In this study, we continue development of a volatile organic compound (VOC)-based test for detecting asymptomatic infections of P. ramorum in Rhododendron sp. We confirmed detection of P. ramorum from volatiles collected from asymptomatic root-inoculated Rhododendron plants in a nursery setting, finding that the VOC profile of infected plants is detectably different from that of healthy plants, when measured from both ambient VOC emissions and VOCs extracted from leaf material. Predicting infection status was successful from ambient volatiles, which had a mean area under the curve (AUC) value of 0.71 ± 0.17, derived from corresponding receiver operating characteristic curves from an extreme gradient boosting discriminant analysis. This finding compares with that of extracted leaf volatiles, which resulted in a lower AUC value of 0.51 ± 0.21. In a growth chamber, we contrasted volatile profiles of asymptomatic Rhododendron plants having roots infected with one of three pathogens: P. ramorum, P. cactorum, and Rhizoctonia solani. Each pathogen induced unique and measurable changes, but generally the infections reduced volatile emissions until 17 weeks after inoculation, when emissions trended upward relative to those of mock-inoculated controls. Forty-five compounds had significant differences compared with mock-inoculated controls in at least one host-pathogen combination.

Keywords: mass spectrometry; metabolomics; nursery detection; oomycetes; pathogen detection; ramorum blight; volatile organic compounds (VOCs).

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Figures

Figure 1.

Figure 1.

Receiver operating characteristic (ROC) curves from XGB-DA validation sets to predict P. ramorum infections of rhododendrons in a nursery trial. Compared are results from ambient headspace measurements (HSSE) to volatiles extracted from leaf tissue (SBSE). Overall, more accurate predictions were made from ambient headspace. TPP: True positive proportion; TNP: true negative proportion.

Figure 2.

Figure 2.

Comparison of chemical signal differences in field ambient headspace samples (HSSE), field leaf extract samples (SBSE) and enclosed headspace samples from growth chamber plants using the 1st Latent Variable (LV1) from PLS-DA models.

Figure 3:

Figure 3:

Heatmap of the log2 of the ratio of each compound’s peak area to the average peak area of the mock samples for each time point. Normalization to the average mock peak area for each time point is used as an external control. Blue tones indicate downregulation of compounds in infected plants, and red tones indicate upregulation. Compounds are identified in Table 2.

Figure 4:

Figure 4:

PLS-DA latent variable (LV) plots for growth chamber, enclosed plants at the sampled weeks after infection.

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