-
The experimental plant materials were obtained from the 'China Chrysanthemum Germplasm Resource Conservation Center' of Nanjing Agricultural University, and the species names and classifications are shown in Supplemental Table S1 and Supplemental Fig. S1. The rooted seedlings were cultured in a 3:1 vermiculite mixture. Seedlings were grown in long-day conditions (16 h light, 25 °C, relative humidity 75%)[26, 27]. Plants with uniform growth were randomly divided into two groups (n = 15): the control group and the treatment group. The strain (A. alternata) used in the study was isolated in our laboratory from leaves with typical symptoms of CBS. The leaf inoculation was carried out as previously described[27]. The fungus used for inoculation was grown in potato dextrose broth (PDB) medium at 28 °C shaking at 200 rpm for 24 h. Then 2 mL of mycelial fluid was inoculated on the back of the third fully expanded leaf of the plant, one leaf per plant and two loci. The inoculated leaves were covered with a ziplock bag, and the control group was inoculated with PDB. After inoculation was completed, the plants were placed in dark conditions at a temperature of 28 °C and 80% humidity for 48 h.
At the same time, we used the method of inoculation with detached leaves. The simplified detached leaf inoculation assay was the same as previous. We chose the third fully expanded leaf of a fresh and healthy plant, rinsed with sterile water and wrapped with moistened skim cotton on the petiole area, then the leaf was placed in a clean Petri dish and inoculated as described previously. After the inoculation was completed, the plants were sealed with plastic wrap and cultured in the dark for 7 d.
Disease statistics
-
The severity of disease was divided into 0~3 levels: leaf health, no disease for level 0, lesion area accounted for less than 25% of the leaf for level 1, lesion area accounted for 25% to 50% of the leaf for level 2, lesion area accounted for more than 50% of the leaf for level 3. Counted the number of incidences at each level and calculated the incidence and disease index (DSI) for each species.
$\rm Incidence\; ({\text {%}})\; =\dfrac{\rm The\; number\; of\; diseased \;plants}{\rm Total\; number\; of\; plants\; treated}\times 100$ $\, {\rm{DSI}} = \dfrac{\sum (\mathrm{D}\mathrm{i}\mathrm{s}\mathrm{e}\mathrm{a}\mathrm{s}\mathrm{e}\;\mathrm{ }\mathrm{g}\mathrm{r}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{ }\times \mathrm{ }\mathrm{N}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r}\mathrm{ }\;\mathrm{o}\mathrm{f}\;\mathrm{i}\mathrm{n}\mathrm{f}\mathrm{e}\mathrm{c}\mathrm{t}\mathrm{e}\mathrm{d}\;\mathrm{ }\mathrm{p}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{s})}{\mathrm{T}\mathrm{h}\mathrm{e}\;\mathrm{ }\mathrm{h}\mathrm{i}\mathrm{g}\mathrm{h}\mathrm{e}\mathrm{s}\mathrm{t}\;\mathrm{ }\mathrm{d}\mathrm{i}\mathrm{s}\mathrm{e}\mathrm{a}\mathrm{s}\mathrm{e}\;\mathrm{ }\mathrm{g}\mathrm{r}\mathrm{a}\mathrm{d}\mathrm{e}\mathrm{ }\times \mathrm{ }\mathrm{T}\mathrm{h}\mathrm{e}\;\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{a}\mathrm{l}\;\mathrm{ }\mathrm{n}\mathrm{u}\mathrm{m}\mathrm{b}\mathrm{e}\mathrm{r}\;\mathrm{ }\mathrm{o}\mathrm{f}\;\mathrm{ }\mathrm{i}\mathrm{n}\mathrm{o}\mathrm{c}\mathrm{u}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{d}\;\mathrm{ }\mathrm{p}\mathrm{l}\mathrm{a}\mathrm{n}\mathrm{t}\mathrm{s}} $ Disease resistance evaluation levels were classified according to DSI, with DSI = 0 for immunity (I), 0 < DSI ≤ 30 for resistance (R), 30 < DSI ≤ 50 for moderate resistance (MR), and DSI > 50 for susceptibility resistance (S).
Observation of leaf lower epidermis structure
-
To investigate the variation in physical defenses between resistant and sensitive materials, we examined the trichomes and stomata present on the lower epidermis of leaves. We selected the second fully grown fresh leaf below the upper portion of the plant and cut it at the same spot on both sides of the main vein, resulting in an area of approximately 3 mm2. Next, we treated the leaf with a 2.5% glutaraldehyde fixative to preserve it, and stored it in a refrigerator at 4 °C after leaving it at room temperature for 2 h. The samples were then observed and photographed using scanning electron microscopy (SU8100, 3.0 kV, SEM). We analyzed three leaves for each material, with six fields of view examined for each leaf.
Determination of leaf wax content
-
We investigated the role of leaf wax by measuring the quantity of wax in the leaves. We determined the wax content (mg/g) in the fresh leaves by accurately weighing each plant's fresh leaves. Then, we cut the leaves and soaked them in 10 mL of chloroform for 2 min. The resulting solution was filtered into a beaker with a known weight. After the chloroform evaporated, we reweighed the leaves and subtracted the weight of the beaker to calculate the wax content (mg/g) in the fresh leaves. We repeated this process 20 times for each material and recorded the average value.
Extraction of leaf metabolites
-
The second or third fully expanded fresh leaf below the tip of the plant was taken, and five plants were mixed and sampled three times, for a total of 15 plants. Each 0.2 g of the freshly ground sample was added with 1 mL of ethyl acetate solution, vortexed and mixed, and then shaken in a shaker at 28 °C and 200 rpm/h for 1 h. The upper clear liquid was selected as the material to be used[28].
Determination of antifungal activity
-
At a temperature of approximately 50 °C, 500 μL of the extract was placed in an unconsolidated Potato Dextrose Agar (PDA) medium. The concentration of the preparation was extracted : PDA = 1:200. After mixing, the extract was poured into a sterile Petri dish for solidification. Next, the fungal blocks were picked and placed in the middle of the treated PDA medium, and the test was conducted with PDA medium with ethyl acetate (control 2) and blank treatment (control 1) as the control, with 15 sample sizes set for each treatment. The mycelial extension diameter (cm) was counted after 4 d and photographed and recorded.
$\rm Inhibition rate\; ({\text{%}})\; =\dfrac{\begin{array}{c} \rm(Colony\; diameter\; of\; control\; 2 \;-\\\;\rm Treated\; colony\; diameter\; of\; extract)\end{array}}{Colony\; diameter\; of\; control\; 2}\times 100{\text{%}}$ Determination of antifungal activity of Germacrene D
-
Rapid injection of 500 μL of ethyl acetate (containing 0.002% ethyl nonanoate as an internal standard) was performed into a 250 mg vial of Germacrene D. The vial was quickly wrapped with a sealing film and shaken to mix well, and the mother liquor was prepared for use. Take 20 μL of the mother liquor into a brown bottle containing 200 μL of ethyl acetate, mix well and seal it as the reagent to be used.
After placing the bacterial plots in the centre of the plate, 200 μL of the prepared Germacrene D reagent was sucked up and applied onto the PDA plate with the help of an applicator stick, avoiding the bacterial plots when applying the reagent; the PDA plate coated with ethyl acetate was used as the control; five replicates were set for each treatment. The prepared plates were incubated in the dark at 28 °C in a light incubator, and the mycelial growth diameter was measured after 7 d.
GC-MS analysis
-
The sample preparation and extraction of leaf metabolites were the same. For each sample, 0.2 g of fresh leaf sample was mixed with 1 mL of ethyl acetate solution containing 0.002% nonyl acetate as an internal standard. The analysis was performed using a GC-MS system equipped with an HP-5 capillary column (30 m × 0.25 mm × 0.25 μm, Agilent Technologies, USA) and a 7000 D mass spectrometer (Agilent Technologies, USA). The carrier gas for gas chromatography was high-purity helium (He2, 99.999%), with a flow rate of 1 mL/min. The injection was performed using a 40:1 split injection with an injection temperature of 250 °C. Both liquid extraction and solid-phase microextraction (SPME) were used without splitting. The temperature gradient was set at a rate of 20 °C/min, starting from 40 °C and ramping up to 260 °C, followed by a 5-min hold at 260 °C. The cycle time optimization was performed using rapid cooling. The ionization mode of the mass spectrometer was electron ionization (EI), with an ionization voltage of 70 eV. The ion source temperature was set at 230 °C, and the ion source excitation energy was 70 eV. The solvent delay was 3 min. The GC-MS interface temperature was set at 260 °C, and the mass spectrometry analysis was performed in full-scan mode, with a mass scanning range of 20 to 500 atomic mass units (amu). The total time required for a single sample analysis was 40 min. The instrument was equipped with an automatic sample injector, and the injection volume was 100 μL.
Data processing and analysis
-
The area of each lesion was measured using Image J, and data analysis was performed with SPSS 26 software. These data were integrated and visualized using the R programming language and GraphPad Prism 8.0. The qualitative analysis of volatile organic compounds (VOCs) was identified by comparing the retention times of substances in the NIST (National Institute of Standards and Technology) mass spectrometry database and the mass spectra of the standards, the quantification was based on the peak area of the mass spectra.
-
For disease assays, simplified detached leaf inoculation assay and whole plant inoculation assay were performed. We divided the 14 germplasms into resistant (R), moderately resistant (MR), and sensitive (S) according to the disease index. The results of identification using in vitro leaf inoculation were listed in Table 1. The statistical results after 7 d of inoculation showed that C. japonese was a resistant material (DSI = 24). Eleven germplasms, including C. ornatum and A. vulgaris, were identified as MR. Meanwhile, A. vulgaris Variegate, and A. pacificum had disease indices of 55 and 57, respectively, and were both identified as S. With the prolongation of the inoculation time, the area of the lesion continued to expand, and the lesion spreading speed of susceptible germplasms were much faster than that of resistant germplasms (Fig. 1a).
Table 1. Evaluation of disease resistance after inoculation of isolated leaves of CRG.
Name Incidence rate (%) Percentage of spot area (%) Disease index (DSI) Resistance type C. japonese 73 5.9 24 R C. ornatum 100 6.7 33 MR A. vulgaris 100 6.2 33 MR A. leucophylla 100 7.5 33 MR A. parviflora 100 16.2 33 MR A. rubripes 100 15.1 33 MR A. annua 100 16.0 33 MR A. sieversiana 100 18.4 33 MR A. indices 100 24.1 33 MR A. viridisquama 100 19.3 33 MR A. yunnanensis 100 26.6 33 MR A. japonica 100 22.3 36 MR A. vulgaris Variegate 100 30.7 55 S A. pacificum 100 52.8 57 S Figure 1.
Differences in disease phenotype of different plants after inoculation. From left to right: the disease degree of leaves deepens. n = 15. (a) Disease symptoms on 4 and 7 d after inoculation of isolated leaves. (b) Disease symptoms of whole plants at post 2 d inoculation. Scale bar = 1 cm.
The results of identification using whole plant inoculation are shown in Table 2. We performed two independent replicates, at the same time, and the correlation coefficient was 0.974** (** means p < 0.01) which suggested good reproducibility. Typical disease symptoms appeared 2 d after plant inoculation (Fig. 1b). Based on the results of the DSI division, two germplasms with 'disease resistance' grade were obtained as C. japonese and A. parviflora. Meanwhile, 11 'moderately resistant' germplasms including A. japonica and A. vulgaris, etc. A. pacificum were still susceptible. A. pacificum had the largest average spot area percentage among the test materials, with a mean value of 42.7%, followed by A. vulgaris Variegate, with an average spot area percentage of 20.5%. The top three with a smaller proportion of lesion area were A. japonica, A. parviflora, and C. japonese, which were 4.2%, 5.7%, and 6.6%, respectively. Although A. japonica has the smallest mean lesion area percentage, it is not the most resistant.
Table 2. Evaluation of disease resistance after inoculation of whole plants of CRG.
Name EXP 1 EXP 2 Average percentage
of spot area (%)Average DSI Resistance type Incidence rate (%) DSI Incidence rate (%) DSI C. japonese 83 28 92 30 6.6 29 R A. parviflora 100 32 83 28 5.7 30 R A. japonica 92 31 100 33 4.2 32 MR A. vulgaris 100 33 100 33 6.9 33 MR A. leucophylla 100 33 100 33 15.4 33 MR A. rubripes 100 33 100 33 10.4 33 MR A. yunnanensis 100 33 100 33 12.1 33 MR A. indices 100 33 100 33 19.2 33 MR A. viridisquama 100 33 100 33 20.1 33 MR A. sieversiana 100 33 100 33 18.0 33 MR A. annua 100 36 100 36 18.8 36 MR C. ornatum 100 40 100 38 16.1 39 MR A. vulgaris Variegate 100 42 100 44 20.5 43 MR A. pacificum 100 62 100 57 42.7 60 S Comparing the results above of the isolated leaf identification and plant inoculation identification, it can be seen that the agreement of the two results was very good, with a Pearson correlation coefficient for the ratios of 0.872** (** means that p < 0.01, data not shown). Combining the two methods, C. japonese and A. parviflora were identified as R, 11 germplasms such as A. japonica, C. ornatum, A. vulgaris, A. vulgaris Variegate as MR, A. pacificum as S.
Differences in leaf epidermis structure of resistant and susceptible germplasms
-
The results of resistance identification prompted us to explore the defense mechanism of plant disease resistance. Therefore, we selected three typical species for further analysis of leaf lower epidermis structure, namely stress resistant (C. japonese, abbreviated as R1 below, and A. parviflora, abbreviated as R2 below), and sensitive (A. pacificum, abbreviated as S below).
The morphology of the lower epidermal hairs under the leaves of the three species were found to be quite different through leaf SEM (Fig. 2). R1 trichomes were long and fine 'T'-shaped (Fig. 2a), while S was short and broad 'T'-shaped (Fig. 2c). The trichomes of R2 were mostly 'V'-shaped (Fig. 2b). To determine if the observed CRG resistance phenotype was associated with trichome density, we quantified trichomes on the leaves of R and S. The comparison of trichome density showed that the density of trichome under the leaves of S was 6.2/mm2, while the density of trichome under R1 was as high as 29.21/mm2, 4.71 times higher than that of S, and the density of trichome on the leaves of the plants was negatively correlated with the DSI with a correlation coefficient of −0.998* (Fig. 3f). In short, the higher the density of plant trichomes, the greater the resistance to CBS.
Figure 2.
Scanning electron microscopy (SEM) images of the lower epidermis of leaves from disease-resistant and susceptible materials. From left to right, the parts that were observed under the scanning electron microscope (red box part) showed the distribution and shape of trichome and stomata respectively. The red arrows indicate epidermal hairs, and the yellow arrows point to the stomata.
Figure 3.
Correlation analysis of leaf wax content and lower epidermal structure with disease index. (a) Trichome densities of leaf abaxial surfaces, n = 30. (b) Stomata length and width of leaf abaxial surfaces, n = 30. (c) Stomata aperture, n = 30. (d) Stomata densities of leaf abaxial surfaces, n = 30. (e) Wax content of leaves, n = 20. (f) Visualization of the correlation analysis, Pearson correlation coefficient. All bar charts show mean ± SD. Red and green represent positive and negative correlations, respectively, and color intensity reflects the magnitude of the correlation. DI refers to disease index; TD refers to trichome density; SL refers to stomata length; SW refers to stomata width; SA refers to stomata aperture; SD refers to stomata density; WC refers to wax content.
Upon further analysis of the stomata, there were marked differences in the stomatal aperture, size and density of the three plants (Fig. 3). To quantify the degree of stomatal closure, we expressed it in terms of stomatal aperture, which was calculated as the ratio of stomatal width to length. The stomata of S were mostly open, while the stomata of R1 were largely closed (Fig. 2, Fig. 3d). Additionally, the stomatal length and width of S were significantly greater than R1 and R2 (Fig. 3c). In addition, we found differences in stomatal density across species (Fig. 3b), but no clear correlation with plant resistance.
The next question we wished to address was to understand whether plant wax content was related to resistance. Wax content was significantly different in species with different resistance levels (Fig. 3e). R1 had the highest wax content at 28.6 mg/g, whereas S leaves had the lowest at 9.4 mg/g, resulting in a 3.04-fold difference between the two.
Differences of volatile metabolites in leaves of disease-resistant germplasm and sensitive germplasm
-
To further explore the chemical defense mechanism of resistant and sensitive materials, the antifungal activity of plant leaf extracts was determined by plate inhibition test. The results of the experiments were calculated after 4 d of treatment. We found that A. alternata grew significantly more on PDA without leaf extract (Fig. 4). Overall, the fungal inhibition effect of the resistant material was better than that of the susceptible material, although the inhibition rate did not have a regular correlation with the DSI. Unexpectedly, the inhibitory effect of R2 leaf extracts was significantly higher than that of R1.
Figure 4.
Antifungal activity of leaf extracts against A. alternate. (a) The morphology of the colony on the PDA medium after the leaves extracts were co-cultured with the A. alternate for 4 d. (b) Antifungal rate statistics.
Encouraged by the divergence in vitro antifungal effect, the key antifungal substances were explored. Therefore, GC-MS was used to analyze the composition of VOCs. The retention times for each compound separated by GC-MS were showed in Supplemental Table S2, heat map of the VOCs via GC-MS are shown in Fig. 5. Among the three species, 36 kinds of terpenes were detected, the main components were monoterpenes and sesquiterpenes (Fig. 5b). In terms of the content of VOCs in leaves, the highest concentration was found in sesquiterpenes. Furthermore, unlike the other two species, R2 exhibited a very low content of monoterpenes, while other organic volatiles were relatively high; with falcarinol being the main component (Fig. 5c).
Figure 5.
VOCs components identification of leaf extracts. (a) Heat map with major VOCs (above 1% of total VOCs present in chromatograms) emitted by three species of CRG. Colors reflect the VOC’s relative content, n = 3. (b) Venn diagram of the proportion of different classes of terpenes. (c) Statistics of different types of VOCs content in the leaves and the proportion of total VOCs content in the leaves.
The study found that disease-resistant material had significantly higher terpenoid content than disease-susceptible material (Fig. 6a). Beta-Ylangene, beta-Copaene, Germacrene D, gamma-muurolene and neophytadiene were present in all three materials with relatively high content. Additionally, analysis demonstrated a positive correlation between the content of these substances and plant disease resistance (Fig. 6g). Interestingly, our experimental materials contained abundant amounts of falcarinol and Germacrene D, which had been identified as antifungal substances[29, 30].
Figure 6.
The contents of volatiles in leaves of different germplasm were significantly different and correlated with plant disease index. (a) Comparison of total volatiles content in leaves. (b)−(f) Comparison of the contents of main volatiles in leaves of different species. (g) Visualization of the correlation analysis, Pearson correlation coefficient. Red and blue represent positive and negative correlations, respectively, and color intensity reflects the magnitude of the correlation. DI refers to disease index, TV refers to total VOCs, BC refers to beta-Copaene, BY refers to beta-Ylangene, GD refers to Germacrene D, GM refers to gamma-muurolene, NE refers to neophytadiene.
Considering that the content of Germacrene D was significantly positively correlated with plant resistance, and the relative content of Germacrene D was abundant, we further analyzed the antifungal activity of Germacrene D, and found that it can significantly inhibit the mycelia growth of A. alternate (Fig. 7). Therefore, we hypothesise that the strength of plant disease resistance is influenced by the terpene content in the leaves, and that an abundance of terpenes contributes to the ability of the plant to fight off invading pathogens.
-
All data generated or analyzed during this study are included in this published article and its supplementary information files.
-
About this article
Cite this article
Zhan Q, Li W, Liu Y, Zhao S, Chen S, et al. 2024. Genetic resources resistant to black spot (Alternaria alternate) identified from Chrysanthemum-related genera and potential underlying mechanisms. Ornamental Plant Research 4: e001 doi: 10.48130/opr-0023-0023
Genetic resources resistant to black spot (Alternaria alternate) identified from Chrysanthemum-related genera and potential underlying mechanisms
- Received: 06 November 2023
- Accepted: 15 December 2023
- Published online: 09 January 2024
Abstract: Chrysanthemum black spot disease caused by Alternaria alternate infestation is a widespread and extremely destructive foliar disease of chrysanthemums. We compared the resistance of 14 chrysanthemum relatives to chrysanthemum black spot disease, and identified the main indicators for the evaluation and screening of chrysanthemum disease resistance, which is of great significance in laying the foundation for a larger-scale screening of chrysanthemum relatives for disease resistance and the breeding of new disease-resistant cultivars. After artificial inoculation and identification, two disease-resistant germplasm resources, 11 moderately resistant materials, and one sensitive material were obtained. In both resistant and susceptible species, we found that the trichome density and leaf wax content of the resistant material were significantly higher than that of the sensitive material, while the stomata size was smaller than that of the sensitive material. In addition, we found that the leaf extract of the disease-resistant germplasm effectively inhibited the growth rate of A. alternate mycelium on the plate, and GC-MS components found that the leaves of resistant germplasm contained more volatile antifungal organic compounds, of which the abundant falcarinol and Germacrene D might play an important role in resistance to chrysanthemum black spot disease. In summary, epidermal trichome density, wax content and terpene substance content are three important reference indicators for disease resistance evaluation of related genera of chrysanthemum. The identified resistant germplasm can also be used as parents for future cross-breeding or as rootstocks.