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opennotspecifiedMar 2022View details →

Fig. 1 in Profiling alkaloids in Aconitum pendulum N. Busch collected from different elevations of Qinghai province using widely targeted metabolomics

Fig. 1. Comparison of the total peak areas of various classes of metabolites among HZX, MYG, ZKW, GLM, YSZ, and GNG samples from different regions. Bars represent the sum of the peak areas for all metabolites belonging to each class.

opennotspecifiedMar 2022View details →

Fig. 4 in Profiling alkaloids in Aconitum pendulum N. Busch collected from different elevations of Qinghai province using widely targeted metabolomics

Fig. 4. Volcano plots for (a) MYG vs. HZX, (b) ZKW vs. HZX, (c) GLM vs. HZX, (d) YSZ vs. HZX, and (e) GNG vs. HZX. The green dots indicate differential metabolites that were significantly downregulated, red dots indicate differential metabolites that were significantly upregulated, and black dots indicate metabolites that were detected in the samples but were not significant. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3 in Transcriptome and metabolome profiling unveiled mechanisms of tea (Camellia sinensis) quality improvement by moderate drought on pre-harvest shoots

Fig. 3. Transcriptome analysis of DEGs. (A) Venn diagram of DEGs. (B–D) Biological processes of corresponding DEGs related to differentially accumulated metabolites in groups of CK vs. MI, CK vs. MO, and CK vs. SE.

Fig. 1 in Transcriptome and metabolome profiling unveiled mechanisms of tea (Camellia sinensis) quality improvement by moderate drought on pre-harvest shoots

Fig. 1. Metabolomic analysis of differentially accumulated metabolites. (A) Venn diagram of differentially accumulated metabolites. (B) The top five most abundant categories. A, amino acids and derivatives; F, flavonoids; N, nucleotide and derivatives; L, lipids; O, organic acids. Blue dot, categories with less metabolites. (C) Accumulation tendencies of the five categories under diferent SWCs.. CK, control (21–24% SWC); MI, milder drought (15–18% SWC); MO, moderate drought (12–15% SWC); SE, severe drought (9–12% SWC). (D) KEGG enrichment of group CK vs. MI from metabolic data. (E) KEGG enrichment of group CK vs. MO from metabolic data. (F) KEGG enrichment of group CK vs. SE from metabolic data. Plot: mean with standard deviation (SD). (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 Transcriptome and metabolome profiling unveiled mechanisms of tea (Camellia sinensis) quality improvement by moderate drought on pre-harvest shoots

Fig. 6. Regulation of lipid metabolisms under different SWCs. (A) Phospholipid metabolism, glycerolipid metabolism, and fatty acid biosynthesis, and the expression tendencies of corresponding differentially accumulated lipids. (B) Connection network of 16 DEGs and 30 differentially accumulated lipids according to PCC> 0.9. Blue dots indicate DEGs, and pink dots denote closely correlated lipids. Colors from green to red in heatmaps represent the relative expression patterns of DEGs; colors from blue to pink represent the accumulated pattern of related metabolites. The compounds index in A and B are referred to in Supplementary Table S6-1. CK, control; MI, mild drought; MO, moderate drought; SE, severe drought. ADH3, alcohol dehydrogenase 3; AFP1-like, ninja-family protein AFP1-like; ALA2_like, phospholipid-transporting ATPase 2; AOS, allene oxide synthase; CIPK5-like, CBL-interacting protein kinase 5-like; DAD1, phospholipase A(1) DAD1; DGK7-like, diacylglycerol kinase 7-like; GDSL-1, GDSL esterase/lipase At5g33370-like; GDSL-2, GDSL esterase/lipase At4g26790-like; GDSL-3, GDSL esterase/lipase 1-like; GDSL-4, GDSL esterase/lipase At1g33811; KCS-12/19-like, 3-ketoacyl-CoA synthase 12/19-like; LTP1-like, non-specific lipid-transfer protein 1-like; MGLL, caffeoylshikimate esterase-like, the isozyme gene of monoglyceride lipase; MTACP, acyl carrier protein; PL A1-Ibeta2, phospholipase A1-Ibeta2; PLD1-like, phospholipase D alpha 1-like. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5 in Transcriptome and metabolome profiling unveiled mechanisms of tea (Camellia sinensis) quality improvement by moderate drought on pre-harvest shoots

Fig. 5. Underlying regulation of flavonoid biosynthesis under different SWCs. (A) Expressions of differentially accumulated flavonoids. (B) Underlying regulation mechanism of flavonoid biosynthesis pathway. (C) Connection network of 11 DEGs and 32 differentially accumulated flavonoids according to PCC> 0.9. Blue dots indicate DEGs, and pink dots denote flavonoids. In B and C, the colors from green to red in the heatmap show the relative expression pattern of DEGs, and the colors from blue to pink represent the relative accumulated pattern of closely related metabolites. The compounds index in A and C are referred to in Supplementary Tables S5-1. CK, control; MI, mild drought; MO, moderate drought; SE, severe drought. ANR, anthocyanidin reductase; ANS, anthocyanidin synthase; AS-like, hydroquinone glucosyltransferase-like; C, catechin; DFR, dihydroflavonol 4-reductase; EC, epicatechin; ECG, epicatechin gallate; EGCG, epigallocatechin gallate; FLS, flavonol synthase/flavanone 3-hydroxylase; GC, gallocatechin; LAR, leucoanthocyanidin reductase; PKSB, type III polyketide synthase B; UFGT, anthocyanidin 3-Oglucosyltransferase; UGT83A1, UDP-glycosyltransferase 83A1; UGT94P1, beta-D-glucosyl crocetin beta-1,6-glucosyltransferase-like. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4 in Transcriptome and metabolome profiling unveiled mechanisms of tea (Camellia sinensis) quality improvement by moderate drought on pre-harvest shoots

Fig. 4. Levels of quality-associated compounds for different SWCs. (A) Total differentially accumulated flavonoids, isoflavonoids, and C- and O- glycosylflavonoids. (B) Levels of catechins, theanine, and theobromine. (C) Levels of glycerophospholipids, glycerolipids, and fatty acids. Plot: mean with SD.

opennotspecifiedAug 2020View details →

Fig. 2 in A H NMR-based metabolomic approach to study the production of antimalarial compounds from Psiadia arguta leaves (pers.) voigt

Fig. 2. (A) Aphids on leaves of P. arguta acclimatized plants, (B) Mealybugs on leaves of P. arguta acclimatized plants, (C) Aphids and (D) mealybugs.

opennotspecifiedAug 2020View details →

Fig. 4. 1H in A H NMR-based metabolomic approach to study the production of antimalarial compounds from Psiadia arguta leaves (pers.) voigt

Fig. 4. 1H NMR spectra (CDCl, 600 MHz) of the ethyl acetate extracts from in vitro, healthy, attacked, and elicited acclimatized plants of P. arguta. Assignments: 3 signals a (δH 0.80, H3-19 and H3-20), b (δH 0.88, H3-18), and c (δH 1.16, H3-17) are characteristic of the labdane bicyclic ring; d (δH 0.92, H3-16), e (δH 1.71, H3-16), f (δH 2.12, H3-2′), g (δH 3.69, H2-15), and h (δH 4.13, H2-15) are assigned to labda-13(E)-en-8α-ol-15-yl acetate (1); labda-8α-ol-15-yl acetate (2); labda-13(E)-ene-8αol-15-diol (3); (8R,13S)-labda-8,15-diol (4).

opennotspecifiedAug 2020View details →

Fig. 3 in A H NMR-based metabolomic approach to study the production of antimalarial compounds from Psiadia arguta leaves (pers.) voigt

Fig. 3. (A) OPLS-DA score plot, (B) permutation plot, (C) ROC plot and (D) S-plot generated from the 1H NMR spectra (600 MHz) of healthy and attacked P. arguta plantlets crude extracts. (E) Contribution plot generated from the comparison of spectral variables of attacked samples vs healthy samples. The labels 6, 7, 8 and 9 on the PCA score plot correspond to the age of the plant; AA: attacked acclimatized plants; AH: healthy acclimatized plants and VH: healthy axenic plants.

Fig. 4 in Metabolomic fingerprinting and genetic discrimination of four Hypericum taxa from Greece

Fig. 4. UPGMA dendrogram of the Hypericum taxa studied revealed four distinct strongly supported clades. A close phylogenetic relationship was observed between H. triquetrifolium and H. perforatum ssp. veronense. These two taxa were phylogenetically related to H. perfoliatum, while H. empetrifolium ssp. empetrifolium was the most distant. Bootstrap values were calculated from 1000 resamplings of the alignment data.

Fig. 1 in Comparative metabolomics analysis of the response to cold stress of resistant and susceptible Tibetan hulless barley (Hordeum distichon)

Fig. 1. HCA and PCA of metabolite profiles under different temperatures of different varieties. (A) Heatmap of the metabolites detected in the total samples. Red indicates high abundance, green indicates low abundance. Metabolites were divided into three main clusters (1, 2, 3). (B) Score plot of PCA of metabolite datasets of the different samples. Each point represents one metabolite profiling experiment. There were three biological repeats for each temperature. 1/2/3/4/5/6 represent the different temperatures: 24 °C/12 °C/ 5 °C/0 °C/–5 °C/–8 °C, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5 in Comparative metabolomics analysis of the response to cold stress of resistant and susceptible Tibetan hulless barley (Hordeum distichon)

Fig. 5. Abundance of the metabolites enriched in glutathione metabolism during cold treatment. Fold changes in metabolite levels under the indicated temperatures in XL and ZQ are shown; red represents upregulation, blue represents downregulation. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4 in Comparative metabolomics analysis of the response to cold stress of resistant and susceptible Tibetan hulless barley (Hordeum distichon)

Fig. 4. Analysis of DAMs in XL and ZQ. (A) Venn diagram of DAMs between cold stress and control conditions (ZQ1) in ZQ. (B) Venn diagram of DAMs between cold stress and control conditions (XL1) in XL. (C, D) Top 10 upregulated and downregulated DAMs in XL (C) and ZQ (D) plants exposed to −8 °C or 24 °C.

Fig. 3 in Comparative metabolomics analysis of the response to cold stress of resistant and susceptible Tibetan hulless barley (Hordeum distichon)

Fig. 3. DAMs in XL and ZQ plants exposed to freezing stress compared to the control condition. Metabolites significantly altered in XL, but not in ZQ plants exposed to freezing stress compared to the control condition (24 °C).

Fig. 3 in Metabolomic fingerprinting and genetic discrimination of four Hypericum taxa from Greece

Fig. 3. PCA biplots (after Varimax rotation) of major metabolites of essential oils (A and B) and methanolic extracts (C and D) obtained from Hypericum samples. HPV: Hypericum perforatum ssp. veronense, HP: Hypericum perforatum, HT: Hypericum triquetrifolium, HEE: Hypericum empetrifolium ssp. empetrifolium.

Fig. 2. DAMs between XL in Comparative metabolomics analysis of the response to cold stress of resistant and susceptible Tibetan hulless barley (Hordeum distichon)

Fig. 2. DAMs between XL and ZQ. (A) Numbers of DAMs under cold stress (12 °C, 5 °C, 0 °C, −5 °C, −8 °C) or the control condition (24 °C) in XL and ZQ. 1/2/3/4/5/ 6 represent 24 °C/12 °C/5 °C/0 °C/–5 °C/–8 °C, respectively.(B) Upregulated and downregulated metabolites in XL and ZQ at different temperatures. 1/2/3/4/5/6 represent 24 °C/12 °C/5 °C/0 °C/–5 °C/–8 °C, respectively. (C, D) Metabolites that were significantly altered in XL exposed to cold stress (12 °C, 5 °C, 0 °C) compared to the control condition (24 °C), but not in ZQ.

Fig. 1 in Metabolomic fingerprinting and genetic discrimination of four Hypericum taxa from Greece

Fig. 1. Content (%) of the groups of volatile metabolites in the essential oils of the four Hypericum taxa (mean ± s.d.). HC–S: sesquiterpene hydrocarbons; OS: oxygenated sesquiterpenes; HC–O: monoterpene hydrocarbons; OM: oxygenated monoterpenes.

Fig. 2 in Metabolomic fingerprinting and genetic discrimination of four Hypericum taxa from Greece

Fig. 2. Concentration (mean ± s.d.) of different groups of polar metabolites (phenolic acids, flavanols, flavonols, biflavones, naphthodianthrones and phloroglucinols) in the methanolic extracts of the Hypericum taxa expressed as mg per g dry extract weight.