Effects of Poty-Potexvirus Synergism on Growth, Photosynthesis and Metabolite Status of Nicotiana benthamiana

Abstract

Mixed virus infections threaten crop production because interactions between the host and the pathogen mix may lead to viral synergism. While individual infections by potato virus A (PVA), a potyvirus, and potato virus X (PVX), a potexvirus, can be mild, co-infection leads to synergistic enhancement of PVX and severe symptoms. We combined image-based phenotyping with metabolite analysis of single and mixed PVA and PVX infections and compared their effects on growth, photosynthesis, and metabolites in Nicotiana benthamiana. Viral synergism was evident in symptom severity and impaired growth in the plants. Indicative of stress, the co-infection increased leaf temperature and decreased photosynthetic parameters. In contrast, singly infected plants sustained photosynthetic activity. The host's metabolic response differed significantly between single and mixed infections. Over 200 metabolites were differentially regulated in the mixed infection: especially defense-related metabolites and aromatic and branched-chain amino acids increased compared to the control. Changes in the levels of methionine cycle intermediates and a low S-adenosylmethionine/S-adenosylhomocysteine ratio suggested a decline in the methylation potential in co-infected plants. The decreased ratio between reduced glutathione, an important scavenger of reactive oxygen species, and its oxidized form, indicated that severe oxidative stress developed during co-infection. Based on the results, infection-associated oxidative stress is successfully controlled in the single infections but not in the synergistic infection, where activated defense pathways are not sufficient to counter the impact of the infections on plant growth.

Keywords: metabolite profiling; mixed infection; phenotyping; plant-virus interactions; potexvirus; potyvirus; viral synergism.

Figure 1

Quantification of reporter gene expression in single and mixed PVA and PVX infections revealed synergistic benefits for PVX in both local and systemic leaves. (A) PVX-derived GFP and (B) PVA-derived RFP fluorescence intensities were measured from local and systemic samples at 6 and 10 dpi, respectively. Averages of one independent experiment (n = 8–9 plants per treatment) are shown. Error bars indicate standard deviation and statistical significance was calculated with Student’s t-test (* p < 0.05, ** p < 0.01, *** p < 0.001).

Figure 2

Image-based phenotyping results showing the effect of single and mixed PVA and PVX infections on (A) plant height, (B) surface area. Effects on plant morphology, i.e., (C) compactness and (D) eccentricity were calculated from image data at 10 dpi. (E) Representative RGB images of control, PVA, PVX and PVA + PVX -infected plants at 10 dpi. (F) Effect of single and mixed PVA and PVX infections on minimum leaf temperature. Plants were imaged with a thermal infrared camera. Results are presented as averages from one phenotyping experiment, error bars denote standard deviation and statistical significance was calculated by Student’s t-test (* p < 0.5, ** p < 0.01, *** p < 0.001).

Figure 3

PVA + PVX co-infection lowers photosynthetic performance. (A) F_v/F_m, maximum PSII quantum yield in selected plants. A white arrow indicates a systemic leaf with low F_v/F_m in the PVA + PVX co-infected plant. False color images were created by normalizing to RGB values and percentage decrease was calculated from Fluorcam whole plant image data.(B) Average percentage decrease in F_v/F_m compared to healthy control plants (* p < 0.05, *** p < 0.001). (C) Dispersion of F_v/F_m pixel values representing maximum PSII quantum yield in the control and single and mixed PVA and PVX infections at 10 dpi. The X-axis was limited to represent 1% of total counts to magnify the F_v/F_m value dispersion below threshold. (D) PSII operating efficiency (ΦPSII), (E) non-photochemical quenching and (F) ratio of fluorescence decline during light adaptation (L1–L4) and light-adapted steady state (Lss) at 10 dpi in control, PVA, PVX and co-infected plants. Average percentage differences compared to the control are shown from one phenotyping experiment.

Figure 4

Metabolite analysis of single and mixed infections. (A) A dendrogram showing the differences between metabolite profiles in healthy controls and single and mixed PVA and PVX infections was generated based on hierarchical clustering analysis of the samples. 6 dpi local samples are boxed in gray and 10 dpi systemic samples are boxed in white. (B) Significantly up and down regulated metabolites in the infections at 6 and 10 dpi. Venn diagrams represent the numbers unique and shared metabolites in single and mixed infections compared to the control samples. Statistical significance (p < 0.05) was analyzed with the Student’s t-test and visualized with Venn diagrams.

Figure 5

Levels of methionine cycle intermediates and selected metabolites in single and mixed infections. Data represents averages of one experiment, statistical significance compared to the healthy controls of the same day was calculated with Student’s t-test (* p < 0.5, ** p < 0.01, *** p < 0.001). The following abbreviations are used: cysteine (Cys), cystathionine (Cystat), homocysteine (HCys), methionine (Met), S-adenosylmethionine (SAM), S-adenosylhomocysteine (SAH). The diagram was created with BioRender.

Figure 6

(A) SAM/SAH ratio and (B) glutathione balance in local (6 dpi) and systemic (10 dpi) leaves of healthy controls, PVA and PVX single infections and the PVA + PVX co-infection. Results are shown from one independent experiment, error bars in A) represent standard deviation and statistical significance was calculated using Student’s t-test (* p < 0.5, ** p < 0.01).