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Fig. 2 in Untargeted metabolite profiling of petal blight in field-grown Rhododendron agastum using GC-TOF-MS and UHPLC-QTOF-MS/MS

Fig. 2. Total ion current (TIC) chromatogram of healthy flowers (HF) and petal blight flowers (PBF) of R. agastum using GC-TOF-MS.

Fig. 3 in Untargeted metabolite profiling of petal blight in field-grown Rhododendron agastum using GC-TOF-MS and UHPLC-QTOF-MS/MS

Fig. 3. The data analysis of the metabolites based on GC-TOF-MS in the healthy flowers and petal blight flowers of R. agastum. (A) Principal component analysis (PCA). (B) Orthogonal projections to latent structures discriminant analysis (OPLS-DA). The green and red circles display 95% confidence regions of petal blight and healthy flowers. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Untargeted metabolite profiling of petal blight in field-grown Rhododendron agastum using GC-TOF-MS and UHPLC-QTOF-MS/MS

Fig. 1. The petal blight of R. agastum. (A) R. agastum grown in field habitat. (B) The healthy flower of R. agastum. (C) The petal blight flower of R. agastum (white arrow).

Fig. 4 in Untargeted metabolite profiling of petal blight in field-grown Rhododendron agastum using GC-TOF-MS and UHPLC-QTOF-MS/MS

Fig. 4. The data analysis of the metabolites based on UHPLC-QTOF-MS/MS in the healthy flowers and petal blight flowers of R. agastum. (A) Principal component analysis (PCA) analysis in positive ion modes. (B) Principal component analysis (PCA) analysis in negative ion modes. (C) Orthogonal projections to latent structures discriminant (OPLS-DA) analysis in positive ion modes. (D) Orthogonal projections to latent structures discriminant (OPLS-DA) analysis in negative ion modes. The green and red circles display 95% confidence regions of petal blight and healthy flowers. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 6 in Untargeted metabolite profiling of petal blight in field-grown Rhododendron agastum using GC-TOF-MS and UHPLC-QTOF-MS/MS

Fig. 6. The hierarchical clustering of the differentially abundant metabolites in the positive ion modes (A) and in the negative ion modes (B) based on UHPLC-QTOFMS/MS in the healthy flowers and petal blight flowers of R. agastum. The data were log2 transformed, and similarity assessment for clustering was based on the Euclidean distance coefficient and complete clustering algorithm. Columns and rows represent individual metabolites and different samples, respectively.

Fig. 7 in Preliminary investigations on the pathogenesis-related protein expression profile of the medicinal herb Macleaya cordata and anti-bacterial properties of recombinant proteins

Fig. 7. Antibacterial effects of a series of purified McDef1 concentration against S. aureus (A), E. coli (B), S. pullorum (C) and A. hydrophila (D). 1: 30 μg/ml, 2: 40 μg/ ml, 3: 50 μg/ml, 4: 60 μg/ml, 5: 80 μg/ml, 6: 100 μg/ml, 7: Negative control, empty vector expression supernatant; 8: Positive control, for A̢B̢C: 0.2 mg/mL Ampicillin, for D: 0.5 mg/mL Kanamycin.

Fig. 6 in Preliminary investigations on the pathogenesis-related protein expression profile of the medicinal herb Macleaya cordata and anti-bacterial properties of recombinant proteins

Fig. 6. Antibacterial effects of recombinant yeasts with McDef1 or McDef2 fermentation supernatant on S. aureus (A), S. pullorum (B), E. coli (C) and A. hydrophila (D). 1: Fermentation supernatant of the recombinant McDef1; 2: Fermentation supernatant of the recombinant McDef2; 3: Negative control, empty vector expression supernatant; 4: Positive control, A̢B̢C: 0.2 mg/mL Ampicillin; D: 0.5 mg/mL Kanamycin.

Fig. 4 in Preliminary investigations on the pathogenesis-related protein expression profile of the medicinal herb Macleaya cordata and anti-bacterial properties of recombinant proteins

Fig. 4. Multiple sequence alignments of the mature peptides of McLTP1 homologs from different plants with ClustalW2. The target proteins McLTP1 of this study are highlighted with yellow fluorescent background. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 2 in Preliminary investigations on the pathogenesis-related protein expression profile of the medicinal herb Macleaya cordata and anti-bacterial properties of recombinant proteins

Fig. 2. Multiple sequence alignments of the McDef1 (A) and McDef2-5 (B) homologs from different plants with ClustalW2. The conserved domains α-core and γ-core are marked under the homologous sequences respectively. The target proteins McDef1 in (A) and McDef2-5 in (B) of this study are highlighted with yellow fluorescent background. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Preliminary investigations on the pathogenesis-related protein expression profile of the medicinal herb Macleaya cordata and anti-bacterial properties of recombinant proteins

Fig. 1. The alignment analysis of McDef1-5. The underlined amino acids represent the signal sequence predicted with SignalP. The cysteines are marked in yellow background and the putative disulfide bonds are also shown. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 8 in Preliminary investigations on the pathogenesis-related protein expression profile of the medicinal herb Macleaya cordata and anti-bacterial properties of recombinant proteins

Fig. 8. Antibacterial effects of a series of purified McDef2 concentration against S. aureus (A), E. coli (B), S. pullorum (C) and A. hydrophila (D). 1: 30 μg/ml, 2: 40 μg/ ml, 3: 50 μg/ml, 4: 60 μg/ml, 5: 80 μg/ml, 6: 100 μg/ml, 7: Negative control, empty vector expression supernatant; 8: Positive control, for A̢B̢C: 0.2 mg/mL Ampicillin, for D: 0.5 mg/mL Kanamycin.

Fig. 11. Experiment 3 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 11. Experiment 3, mean GC/MS peak area (±SE) of branches, buds, and needles in blue and Norway spruce. Means with different letters are significantly different within each species (ANOVA, Tukey's HSD).

Fig. 3 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 3. Sample GC traces of blue spruce (B1), Norway spruce (N1), and cedar of Lebanon (C1). Compounds were identified by retention indices, mass spectra (NIST library), and reference comparisons. Identified compounds are: (1) tricyclene, (2) α-pinene, (3) camphene, (4) sabinene, (5) β-pinene, (6) β-myrcene, (7) 3-carene, (8) limonene, (9) β-phellandrene (coeluting with limonene), (10) 1,8-cineole, (11) γ-terpinene, (12) terpinolene, (13) camphor, (14) α-terpineol, and (15) β-caryophyllene.

Fig. 2. Chemical structures for terpenes detected from branch tip samples. Numbering follows Table 1 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 2. Chemical structures for terpenes detected from branch tip samples. Numbering follows Table 1 (elution order).

Fig. 12. Experiment 4 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 12. Experiment 4, PCA of B1, B7, B8, N1, N7, N11, and C1 run on a chiral column (standardized TIC responses). Largest circles show 95% confidence limits for each tree species, small circles show 95% confidence limits for each tree.

Fig. 1 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 1. Mean abundance of Norway volatiles vs time (left) and the logarithm of average abundance of Norway vs AHS oven temperature (right).

Fig. 9. Experiment 2 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 9. Experiment 2, comparison of N1, N7, and N11 GC traces (standardized TIC responses). Different colored sample at right (N1 – blue, N7 – green, and N11 – red) correspond to colored peaks at left (as indicated by arrows). N1 samples had higher percentages of β-pinene, N7 samples had higher percentages of α-pinene and limonene (and β-phellandrene), and N11 had higher percentages of camphene, β-myrcene and 1,8-cineole. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 10. Experiment 3 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 10. Experiment 3, PCA of B1–B11 and N1–N11 run over two days (standardized TIC responses). Circles show 95% confidence limits.

Fig. 5. Experiment 1 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 5. Experiment 1, PCA of B1, N1, and C1 over time (standardized TIC responses). Samples were collected and analyzed roughly every week over an 8-month time period (September 2018 through April 2019). Circles show 95% confidence limits.

Fig. 8. Experiment 2 in Headspace GC-MS analysis of differences in intra- and interspecific Terpene profiles of Picea pungens Engelm. and P. abies (L.) Karst

Fig. 8. Experiment 2, PCA of B1–B11, N1–N11, and C1 run over two days (standardized TIC responses). Circles show 95% confidence limits.