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19 pages, 18851 KiB  
Article
Analysis of Transcriptional and Metabolic Differences in the Petal Color Change Response to High-Temperature Stress in Various Chrysanthemum Genotypes
by Zhimei Li, Hougao Zhou, Yan Chen, Minyi Chen, Yutong Yao, Honghui Luo, Qing Wu, Fenglan Wang and Yiwei Zhou
Agronomy 2024, 14(12), 2863; https://doi.org/10.3390/agronomy14122863 - 30 Nov 2024
Viewed by 305
Abstract
Flower color is one of the most important ornamental traits of chrysanthemums. Previous studies have shown that high temperatures can cause the petals of some chrysanthemum varieties to fade; however, the molecular mechanisms behind this phenomenon remain poorly understood. This study examines the [...] Read more.
Flower color is one of the most important ornamental traits of chrysanthemums. Previous studies have shown that high temperatures can cause the petals of some chrysanthemum varieties to fade; however, the molecular mechanisms behind this phenomenon remain poorly understood. This study examines the mechanisms of color change in purple chrysanthemums under high-temperature stress using combined metabolomic and transcriptomic analyses. Four chrysanthemum varieties—two heat-stable (‘Zi Feng Che’ and ‘Chrystal Regal’) and two heat-sensitive (‘Zi Hong Tuo Gui’ and ‘Zi Lian’)—were analyzed. High-temperature conditions (35 °C) significantly downregulated key anthocyanins in heat-sensitive varieties, particularly cyanidin-3-O-(3″,6″-O-dimalonyl)glucoside and pelargonidin-3-O-(3″,6″-O-dimalonyl)glucoside. Transcriptome analysis revealed differential gene expression involved in anthocyanin biosynthesis and degradation, with significant enrichment in the MAPK signaling, phenylpropanoid biosynthesis, flavonoid biosynthesis, and anthocyanin biosynthesis pathways. The study highlighted the differential expression of CHS, DFR, ANS, GT1, 3AT, and UGT75C1 genes in anthocyanin synthesis between heat-sensitive and heat-tolerant varieties. Compared to heat-stable varieties, the petals of heat-sensitive varieties exhibited greater differential expression of heat-responsive transcription factors, including HSFs, ERFs, MYBs, and WRKYs. Genes that show a significant negative correlation with the downregulated anthocyanins, including Cse_sc012959.1_g030.1 (βG), Cse_sc001798.1_g020.1 (MYB), Cse_sc006944.1_g010.1 (MYB), and Cse_sc000572.1_g090.1 (HSF), might regulate anthocyanin accumulation in chrysanthemums in response to high-temperature stress. These results provide guidance for the cultivation management and variety selection of chrysanthemums under high-temperature conditions. Additionally, they lay the foundation for elucidating the molecular mechanisms of flower color stability under heat stress and for breeding new heat-tolerant varieties. Full article
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<p>Quality control analysis of 24 metabolome samples based on UPLC-MS/MS analysis. (<b>A</b>) PCA analysis. (<b>B</b>) Hierarchical clustering heatmap analysis.</p>
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<p>Identification of differential flavonoid metabolites in the petals of four chrysanthemum varieties under high-temperature stress. (<b>A</b>,<b>D</b>,<b>G</b>,<b>J</b>) OPLS-DA analysis for ZFC, CR, ZHTG, and ZL, respectively. (<b>B</b>,<b>E</b>,<b>H</b>,<b>K</b>) Volcano plot analysis for ZFC, CR, ZHTG, and ZL, respectively. (<b>C</b>,<b>F</b>,<b>I</b>,<b>L</b>) Top 20 flavonoids with the highest fold changes for ZFC, CR, ZHTG, and ZL, respectively.</p>
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<p>Identification of anthocyanins in the petals of four chrysanthemum varieties. (<b>A</b>) Classification of 10 types of anthocyanins. (<b>B</b>) Hierarchical clustering heatmap analysis.</p>
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<p>Mining of differentially expressed genes in the petals of four chrysanthemum varieties under high-temperature stress. (<b>A</b>) Statistics of differentially expressed genes. (<b>B</b>–<b>E</b>) KEGG enrichment analysis of differentially expressed genes in ZFC, CR, ZHTG, and ZL under high-temperature stress compared to the control. The highlighted red boxes indicate the pathways related to anthocyanin biosynthesis.</p>
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<p>Analysis of metabolites and differentially expressed genes related to anthocyanin pathways.</p>
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<p>Identification of differentially expressed genes related to anthocyanin degradation.</p>
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<p>Identification of differentially expressed genes related to heat stress response factors and Ca<sup>2+</sup> signaling.</p>
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<p>Significant correlation network analysis between anthocyanins and genes related to anthocyanin biosynthesis and degradation. (<b>A</b>) Correlation network of heat-insensitive varieties (ZFC and CR). (<b>B</b>) Correlation network of heat-sensitive varieties (ZHTG and ZL).</p>
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<p>Significant correlation network analysis between anthocyanins and heat stress-related transcription factors and genes. (<b>A</b>) Correlation network of heat-insensitive varieties (ZFC and CR). (<b>B</b>) Correlation network of heat-sensitive varieties (ZHTG and ZL).</p>
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16 pages, 7056 KiB  
Article
Silencing of the MP Gene via dsRNA Affects Root Development and Growth in the Invasive Weed Mikania micrantha
by Zhenghui Ou, Yuantong Zhang, Qiang Wu, Kangkang Wang, Guangzhong Zhang, Xi Qiao, Ying Yan, Wanqiang Qian, Fanghao Wan and Bo Liu
Int. J. Mol. Sci. 2024, 25(23), 12678; https://doi.org/10.3390/ijms252312678 - 26 Nov 2024
Viewed by 210
Abstract
Mikania micrantha (“mile-a-minute” weed) is a global invasive alien weed that can cause severe damage to agroforestry ecosystems and significant agricultural losses worldwide. Although chemical, manual, or mechanical control methods are widely used to control M. micrantha, RNA interference (RNAi)-based biocontrol methods [...] Read more.
Mikania micrantha (“mile-a-minute” weed) is a global invasive alien weed that can cause severe damage to agroforestry ecosystems and significant agricultural losses worldwide. Although chemical, manual, or mechanical control methods are widely used to control M. micrantha, RNA interference (RNAi)-based biocontrol methods have rarely been reported for this species. The MONOPTEROS (MP) gene, encoding an auxin response factor, plays an essential role in embryonic root initiation in Arabidopsis thaliana. In this study, we identified the MP gene from M. micrantha via orthologous gene analysis. A total of 37 MP orthologous genes was identified in 4 plants, including 9 MP candidate genes in M. micrantha, 13 in Helianthus annuus, 6 in Chrysanthemum nankingense, and 9 in Lactuca sativa. Phylogenetic analysis revealed that an MP candidate gene in M. micrantha (Mm01G000655, named MmMP) was clustered into one clade with the MP gene in A. thaliana (AtMP). In addition, both MmMP and AtMP contain a B3-DNA binding domain that is shared by transcription factors that regulate plant embryogenesis. To study gene function, dsRNA against MmMP (dsMmMP) was applied to the roots of M. micrantha. Compared with those of the controls, the expression of MmMP was reduced by 43.3%, 22.1%, and 26.2% on the first, third, and fifth days after dsMmMP treatment, respectively. The dsMmMP-treated plants presented several morphological defects, mostly in the roots. Compared with water-treated plants, the dsMmMP-treated plants presented reduced developmental parameters, including root length, number of adventitious roots, root fresh and dry weights, plant height, and aboveground biomass. Additionally, safety assessment suggested that this dsMmMP treatment did not silence MP genes from non-target plants, including rice and tomato; nor did it inhibit root growth in those species. Collectively, these results suggest that MmMP plays an important role in root development in M. micrantha and provides a potential target for the development of species-specific RNAi-based herbicides. Full article
(This article belongs to the Section Molecular Biology)
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<p>Phylogenetic analysis of <span class="html-italic">MP</span> genes from <span class="html-italic">M. micrantha</span> and four other species, namely, <span class="html-italic">A. thaliana</span>, <span class="html-italic">C. nankingense</span>, <span class="html-italic">H. annuus</span>, and <span class="html-italic">L. sativa</span>. I~IV represent the <span class="html-italic">MP</span> proteins of the five species divided into four independent clades. The tree was constructed via the neighbor-joining method based on the protein sequence alignments. The numbers on the branches represent bootstrap values obtained from 1000 replicates. The branch lengths are proportional to the percentage of sequence difference (scale bar, 0.05% difference). The red triangle represents the <span class="html-italic">M. micrantha</span> gene Mm01G000655; the blue circles represent two protein-encoding genes in <span class="html-italic">A. thaliana</span>.</p>
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<p>TPM values of candidate gene expression in different tissues. The values represent the means ± SE derived from five biological replicates.</p>
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<p>The abundance of <span class="html-italic">MmMP</span> transcripts was measured at different time points after the roots were soaked in water (CK) or <span class="html-italic">dsMmMP</span>. Each bar represents the mean ± SE derived from three biological replicates. A t-test was used to determine significant differences in plant-silencing efficiency in this study (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001). CK indicates treatment with water, and <span class="html-italic">dsMmMP</span> indicates double-stranded RNA of the <span class="html-italic">M. micrantha MmMP</span> gene.</p>
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<p>Effects of <span class="html-italic">dsMmMP</span> application on the phenotype of <span class="html-italic">M. micrantha</span>. Phenotypic changes in <span class="html-italic">M. micrantha</span> roots after continuous treatment for 15 days. CK, water control; <span class="html-italic">dsMmMP</span>, double-stranded RNA of the <span class="html-italic">M. micrantha MmMP</span> gene.</p>
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<p>Statistical analysis of morphological indicators of <span class="html-italic">M. micrantha</span>. Statistical analysis of the length of the longest adventitious root (<b>A</b>), plant height (<b>B</b>), number of all adventitious roots (<b>C</b>), dry weights of all adventitious roots and aboveground parts (<b>D</b>), and fresh weights of all adventitious roots and fresh weights of the aboveground parts (<b>E</b>) after 15 d of continuous treatment. Each bar represents the mean and standard error for <span class="html-italic">n</span> = 8 biological replicates. A <span class="html-italic">t</span>-test was used to determine significant differences in plant-silencing efficiency in this study (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001). CK, water control; <span class="html-italic">dsMmMP</span>, double-stranded RNA of the <span class="html-italic">M. micrantha MmMP</span> gene.</p>
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<p>Effects of <span class="html-italic">dsMmMP</span> on <span class="html-italic">MP</span> gene expression in non-target plants. The expression of the <span class="html-italic">MP</span> gene from rice (<span class="html-italic">OsARF11</span>) or tomato (<span class="html-italic">SlARF5</span>) was measured 3 d after <span class="html-italic">dsMmMP</span> and water treatment. (<b>A</b>) Rice (<b>B</b>) Tomato Each bar chart represents the mean and standard error of <span class="html-italic">n</span> = 3 biological replicates, and the data were analyzed via one-way ANOVA to identify significant differences in plant-inhibition efficiency and multiple Tukey comparisons (<span class="html-italic">p</span> &lt; 0.05). “ns” indicates no significant difference between the CK and <span class="html-italic">dsMmMP</span> treatments. CK, water control; <span class="html-italic">dsMmMP</span>, double-stranded RNA of the <span class="html-italic">M. micrantha MmMP</span> gene.</p>
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<p>Effects of <span class="html-italic">dsMmMP</span> on the growth of <span class="html-italic">O. sativa</span>. (<b>A</b>) Image of a whole plant. (<b>B</b>) Plant height. (<b>C</b>) Number of adventitious roots. (<b>D</b>) Length of the longest adventitious root. (<b>E</b>) Fresh weight of all adventitious roots. Each bar represents the mean and standard error for <span class="html-italic">n</span> = 8 biological replicates, and the data were analyzed via one-way ANOVA to identify significant differences in plant-inhibition efficiency and multiple Tukey comparisons (<span class="html-italic">p</span> &lt; 0.05). “ns” represents no significant difference between the CK and <span class="html-italic">dsMmMP</span> treatments. CK, water control; <span class="html-italic">dsMmMP</span>, double-stranded RNA of the <span class="html-italic">M. micrantha MmMP</span> gene.</p>
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<p>Effects of <span class="html-italic">dsMmMP</span> on the growth of <span class="html-italic">S. lycopersicum</span>. (<b>A</b>) Image of a whole plant. (<b>B</b>) Plant height. (<b>C</b>) Number of adventitious roots. (<b>D</b>) Length of the longest adventitious root. (<b>E</b>) Fresh weight of all adventitious roots. Each bar represents the mean and standard error for <span class="html-italic">n</span> = 6 biological replicates, and the data were analyzed via one-way ANOVA to identify significant differences in plant-inhibition efficiency and multiple Tukey comparisons (<span class="html-italic">p</span> &lt; 0.05). “ns” indicates no significant difference between the CK and <span class="html-italic">dsMmMP</span> treatments. CK, water control; <span class="html-italic">dsMmMP</span>, double-stranded RNA of the <span class="html-italic">M. micrantha MmMP</span> gene.</p>
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26 pages, 1420 KiB  
Article
Functional, Antioxidant, Antibacterial, and Antifungal Activity of Edible Flowers
by Elena Coyago-Cruz, Alejandro Alarcón, Aida Guachamin, Gabriela Méndez, Edison Osorio, Jorge Heredia-Moya, Johana Zuñiga-Miranda, Elena Beltrán-Sinchiguano and Edwin Vera
Antioxidants 2024, 13(11), 1297; https://doi.org/10.3390/antiox13111297 - 25 Oct 2024
Viewed by 771
Abstract
Edible flowers have been used since ancient times, but their potential for improving human health has not been explored. This study aimed to evaluate the profile of bioactive compounds (organic acids, phenolics, and carotenoids) and the antioxidant and antimicrobial activity of nine flower [...] Read more.
Edible flowers have been used since ancient times, but their potential for improving human health has not been explored. This study aimed to evaluate the profile of bioactive compounds (organic acids, phenolics, and carotenoids) and the antioxidant and antimicrobial activity of nine flower varieties with high concentrations of carotenoids or total phenolic compounds. Ninety-three edible flowers were analysed for physicochemical characteristics, total phenolic and carotenoid concentrations, and antioxidant activity (ABTS). Bioactive profiles were determined by rapid resolution liquid chromatography (RRLC), and antimicrobial activity was determined against Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa and Streptococcus mutans, and Candida albicans and Candida tropicalis. Chrysanthemum x hybrid orange, Helianthus annuus yellow, Tagetes patula orange, Canna indica red, and Hibiscus rosa-sinensis (orange1 and yellow) showed significant concentrations of total carotenoids. In contrast, Pelargonium hortorum orange2, Hibiscus rosa-sinensis red1, and Rosa x hybrid variety medium yellow showed high levels of total phenolics. The predominant compounds in these species were citric acid (991.4 mg/g DW in Hibiscus rosa-sinensis red1), 4-hydroxybenzoic acid (936.2 mg/100 g DW in P. hortorum orange2), kaempferol (971. 9 mg/100 g DW in T. patula orange), quercetin glucoside (958.8 in C. x hybrid), quercetin (919.3 mg/100 g DW in T. patula), α-carotene, and β-carotene in T. patula orange (989.5 and 601.2 mg/100 g DW, respectively). Regarding antimicrobial activity, T. patula orange and P. hortorum orange2 inhibited bacterial growth, while C. x hybrid orange and P. hortorum orange2 inhibited Candida albicans, and the latter inhibited Candida tropicalis. These results indicate the potential of edible flowers as a natural source of bioactive compounds and as a tool in the fight against antimicrobial resistance. Full article
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<p>CIELAB colour coordinates of the flowers under study. <b>Note:</b> The numbers correspond to the number of blossoms examined (<a href="#antioxidants-13-01297-t001" class="html-table">Table 1</a>).</p>
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<p>Exploratory multivariate analysis using correlation (<b>A</b>) and principal component (<b>B</b>) analysis of the 93 flowers under study. Notes: W, weight; DL, longitudinal diameter; DE, equatorial diameter; SS, soluble solids; AT, titratable acidity; H, humidity; AH, ash; a*, colour coordinate; b*, colour; L, colour intensity; CT, total carotenoids; PT, total phenolics; %In, % inhibition; AB, antioxidant activity.</p>
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<p>Antimicrobial activity of flower extracts against (<b>A</b>) <span class="html-italic">Escherichia coli</span>; (<b>B</b>) <span class="html-italic">Staphylococcus aureus</span>; (<b>C</b>) <span class="html-italic">Pseudomonas aeruginosa</span>; (<b>D</b>) <span class="html-italic">Streptococcus mutans</span>; (<b>E</b>) <span class="html-italic">Candida albicans</span>; and (<b>F</b>) <span class="html-italic">Candida tropicalis</span>. Note: 3, <span class="html-italic">C. x hybrid</span> (orange); 6, <span class="html-italic">H. annuus</span> (yellow); 12, <span class="html-italic">C. indica</span> (red); 19, <span class="html-italic">P. hortorum</span> (orange2); 45, <span class="html-italic">H. rosa-sinensis</span> (orange1); 49, <span class="html-italic">H. rosa-sinensis</span> (red1); 51, <span class="html-italic">H. rosa-sinensis</span> (yellow); 70, <span class="html-italic">Rosa x hybrid</span> medium red.</p>
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<p>Exploratory multivariate analysis using correlation (<b>A</b>) and principal component (<b>B</b>) analysis of the nine selected flowers. Notes: %Inh, % inhibition; AB, antioxidant activity; Ta, tartaric acid; Ma, malic acid; Cit, citric acid; α-C, α-carotene; β-C, β-carotene; L, β-cryptoxanthin; L, lutein; Vio, violaxanthin; Ze, zeaxanthin; Zei, zeinoxanthin; Caf, caffeic acid; Ch, chlorogenic acid; Fer, ferulic acid; Ga, gallic acid; 4-Hi, 4-hydroxy benzoic acid; K, kaempferol; L, luteolin; <span class="html-italic">p</span>-C, <span class="html-italic">p</span>-C; <span class="html-italic">m</span>-Cumaric, <span class="html-italic">m</span>-cumaric acid; Na, naringin; QG, quercetin glycoside; Q, quercetin; Ru, rutin; Sy, syringic acid; V, vanillic acid; Ec, <span class="html-italic">Escherichia coli</span>; Sa, <span class="html-italic">Staphylococcus aureus</span>; Pa, <span class="html-italic">Pseudomonas aeruginosa</span>; Sm, <span class="html-italic">Streptococcus mutans</span>; Ca, <span class="html-italic">Candiad albicans</span>; Ct, <span class="html-italic">Candiad tropicalis</span>.</p>
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18 pages, 4062 KiB  
Article
Altitude Distribution Patterns and Driving Factors of Rhizosphere Soil Microbial Diversity in the Mountainous and Hilly Region of Southwest, China
by Yanlin Li, Yonggang Wang, Yunpeng Liu, Yangyang Chen and Shuangrong Yang
Agronomy 2024, 14(10), 2441; https://doi.org/10.3390/agronomy14102441 - 21 Oct 2024
Viewed by 562
Abstract
The distribution characteristics of the microbial community in rhizosphere soils of different altitudinal gradients were explored to uncover ecological factors affecting microbial community composition. In this study, the community variations of bacteria and fungi in the rhizosphere soil of Chrysanthemum indicum L. were [...] Read more.
The distribution characteristics of the microbial community in rhizosphere soils of different altitudinal gradients were explored to uncover ecological factors affecting microbial community composition. In this study, the community variations of bacteria and fungi in the rhizosphere soil of Chrysanthemum indicum L. were analyzed. Samples were distributed along an altitudinal gradient of 300–1500 m above sea level in the Fuling watershed of the Three Gorges Reservoir area, China. The analysis was conducted using Illumina MiSeq high-throughput sequencing and bioinformatics analyses. Through correlation analysis with ecological factors, the altitude distribution pattern and driving factors of soil microbial diversity in the mountainous and hilly region of Chongqing were explored. According to the results, the richness and diversity of rhizosphere soil bacteria increased with altitude, while fungi were the richest and most diverse at an altitude of 900 m. The composition of the microbial community differed among different altitudes. Actinobacteria, Proteobacteria, Acidobacteriota, Chloroflexi, Bacteroidota, Ascomycota, unclassified_k_Fungi, Basidiomycota, and Mortierellomycota dominated the microbial community in rhizosphere soil. Correlation analysis showed that the distribution of rhizosphere soil microbial communities correlated with soil ecological factors at different altitudes. Moisture, pH, total nitrogen, total potassium, available potassium, urease, and catalase were significantly positively correlated with rhizosphere soil bacterial α-diversity, while their correlations with fungi were not significant. Variation partition analysis showed that the combined effects of soil physical and chemical factors, enzyme activity, and microbial quantity regulated bacterial community structure and composition. Their combined contributions (19.21%) were lower than the individual effects of soil physical and chemical factors (48.49%), enzyme activity (53.24%), and microbial quantity (60.38%). The effects of ecological factors on fungal communities differed: While the soil physical and chemical factors (44.43%) alone had a clear effect on fungal community structures, their combined contributions had no apparent effect. The results of this study not only contribute to a deeper understanding of the impact mechanism of altitude gradient on the diversity of rhizosphere soil microbial communities, but also provide a scientific basis for the protection and management of mountainous and hilly ecosystems. It lays a foundation for the future exploration of the relationship between microbial communities and plant–soil interactions. Full article
(This article belongs to the Special Issue Nutrient Cycling and Microorganisms in Agroecosystems)
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<p>Locations of sampling sites.</p>
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<p>Principal component analysis of (<b>A</b>) bacterial and (<b>B</b>) fungal communities in the rhizosphere soil at 300, 600, 900, 1200, and 1500 m above sea level (C300, C600, C900, C1200, and C1500, respectively).</p>
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<p>Genus-level composition of (<b>A</b>) bacterial and (<b>B</b>) fungal communities in the rhizosphere soil at 300, 600, 900, 1200, and 1500 m above sea level (C300, C600, C900, C1200, and C1500, respectively).</p>
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<p>Correlation between soil microbial alpha diversity (Chao and Shannon indexes) and soil ecological factors at 300, 600, 900, 1200, and 1500 m above sea level (C300, C600, C900, C1200, and C1500, respectively) for (<b>A</b>) bacteria and (<b>B</b>) fungi. TN, total nitrogen; TP, total phosphorous; TK, total potassium; AN, available nitrogen; AP, available phosphorous; AK, available potassium. * <span class="html-italic">p</span> &lt; 0.05, significant correlation.</p>
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<p>Redundancy analysis (RDA) showing correlations between (<b>A</b>) bacterial and (<b>C</b>) fungal community structures and environmental variables; variation partition analysis (VPA) of the difference in (<b>B</b>) bacterial and (<b>D</b>) fungal communities explained by the comprehensive contribution of different ecological factors. C300, 300 m (above sea level); C600, 600 m; C900, 900 m; C1200, 1200 m; C1500, 1500 m; TN, total nitrogen; TP, total phosphorous; TK, total potassium; AN, available nitrogen; AP, available phosphorous; AK, available potassium.</p>
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<p>Heatmap of Pearson correlation coefficients between the abundances of dominant (<b>A</b>) bacterial and (<b>B</b>) fungal genera and various ecological factors. TN, total nitrogen; TP, total phosphorous; TK, total potassium; AN, available nitrogen; AP, available phosphorous; AK, available potassium. * 0.01 &lt; <span class="html-italic">p</span> &lt; 0.05; ** 0.001 &lt; <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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17 pages, 5322 KiB  
Article
Both the Positioned Supplemental or Night-Interruptional Blue Light and the Age of Leaves (or Tissues) Are Important for Flowering and Vegetative Growth in Chrysanthemum
by Jingli Yang, Jinnan Song, Yoo Gyeong Park and Byoung Ryong Jeong
Plants 2024, 13(20), 2874; https://doi.org/10.3390/plants13202874 - 14 Oct 2024
Viewed by 677
Abstract
In this study, the effects of supplemental or night interruptional blue light (S-BL or NI-BL) positioning on morphological growth, photoperiodic flowering, and expression of floral genes in Chrysanthemum morifolium were investigated. Blue light-emitting diodes (LEDs) at an intensity of 30 μmol·m−2·s [...] Read more.
In this study, the effects of supplemental or night interruptional blue light (S-BL or NI-BL) positioning on morphological growth, photoperiodic flowering, and expression of floral genes in Chrysanthemum morifolium were investigated. Blue light-emitting diodes (LEDs) at an intensity of 30 μmol·m−2·s−1 photosynthetic photon flux density (PPFD) were used for 4 h either (1) to supplement the white LEDs at the end of the 10 h short-day (SD10 + S-BL4) and 13 h long-day conditions (LD13 + S-BL4), or (2) to provide night interruption in the SD10 (SD10 + NI-BL4) and LD13 (LD13 + NI-BL4). The S-BL4 or NI-BL4 was positioned to illuminate either the shoot tip, the youngest leaf (vigorously growing the third leaf from the shoot tip), or the old leaf (the third leaf from the stem base). In the text, they will be denoted as follows: SD10 + S-BL4-S, -Y, or -O; SD10 + NI-BL4-S, -Y, or -O; LD13 + S-BL4-S, -Y, or -O; LD13 + NI-BL4-S, -Y, or -O. Normally, the LD13 conditions enhanced more vegetative growth than the SD10 periods. The growth of leaves, stems, and branches strongly responded to the S-BL4 or NI-BL4 when it was targeted onto the shoot tip, followed by the youngest leaf. The SD10 + S-BL4 or +NI-BL4 on the old leaf obviously suppressed plant extension growth, resulting in the smallest plant height. Under LD13 conditions, the flowering-related traits were significantly affected when the S-BL4 or NI-BL4 was shed onto the youngest leaf. However, these differences do not exist in the SD10 environments. At the harvest stage, other than the non-flowered LD13 treatment, the LD13 + S-BL4 irradiating the youngest leaf induced the most flowers, followed by the shoot tip and old leaf. Moreover, LD13 + NI-BL4 resulted in the latest flowering, especially when applied to the shoot tip and old leaf. However, the SD10 + S-BL4 or + NI-BL4 irradiated the shoot tip, youngest leaf, or old leaf all significantly earlier and increased flowering compared to the SD10 treatment. Overall: (1) Generally, vegetative growth was more sensitive to photoperiod rather than lighting position, while, during the same photoperiod, the promotion of growth was stronger when the light position of S-BL4 or NI-BL4 was applied to the shoot tip or the youngest leaf. (2) The photoperiodic flowering of these short-day plants (SDPs) comprehensively responded to the photoperiod combined with blue light positioning. Peculiarly, when they were exposed to the LD13 flowering-inhibited environments, the S-BL4 or NI-BL4 shed onto the leaves, especially the youngest leaves, significantly affecting flowering. Full article
(This article belongs to the Section Horticultural Science and Ornamental Plants)
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Figure 1
<p>Morphology and flowering of ‘Gaya Glory’ grown under different lighting positions of supplemental or night-interruptional blue light for 60 days. Top (<b>A</b>) and side (<b>B</b>) views. The “❌” means non-flowered treatment.</p>
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<p>Measurements of morphological and growth parameters (<b>A</b>–<b>F</b>) of ‘Gaya Glory’ grown under different lighting positions of supplemental or night-interruptional blue light for 60 days. The “❌” means non-flowered treatment. Shoot tip, S; the youngest leaf, Y; and the old leaf, O. Different lowercase letters indicate significant differences within treatments by Duncan’s multiple range test at <span class="html-italic">p</span> ≤ 0.05. Vertical bars indicate the means ± standard error (n = 9).</p>
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<p>Leaf anatomy of ‘Gaya Glory’ grown under different lighting positions of supplemental or night-interruptional blue light for 60 days. I, leaf thickness; II, palisade tissue; III, spongy tissue. Bars indicate 0.2 mm.</p>
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<p>Measurements of leaf anatomy of ‘Gaya Glory’ grown under different lighting positions of supplemental or night-interruptional blue light for 60 days. Shoot tip, S; the youngest leaf, Y; and the old leaf, O. Different lowercase letters indicate significant differences within treatments by Duncan’s multiple range test at <span class="html-italic">p</span> ≤ 0.05. Vertical bars indicate the means ± standard error (n = 9).</p>
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<p>Stem anatomy of ‘Gaya Glory’ grown under different lighting positions of supplemental or night-interruptional blue light for 60 days. I, stem diameter; II, main pith diameter. Bars indicate 0.2 mm.</p>
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<p>Measurements of stem anatomy of ‘Gaya Glory’ grown under different lighting positions of supplemental or night-interruptional blue light for 60 days. Shoot tip, S; the youngest leaf, Y; and the old leaf, O. Different lowercase letters indicate significant differences within treatments by Duncan’s multiple range test at <span class="html-italic">p</span> ≤ 0.05. Vertical bars indicate the means ± standard error (n = 9).</p>
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<p>Expression patterns of flowering-related genes in chrysanthemum ‘Gaya Glory’ under different lighting positions of supplemental or night-interruptional blue light for 60 days. (<b>A</b>–<b>D</b>) The tissue-specific expression patterns of flowering-related genes in leaves and shoot apexes, and (<b>E</b>) the expression levels of flowering or photoreceptor-related genes in leaves. The top four mature leaves from the shoot apex and shoot apexes were harvested at 12:00 a.m. (4 h after lights-on) for RNA extraction and RT-PCR. Data were averagely normalized against the expression of <span class="html-italic">CmACTIN</span> and <span class="html-italic">CmEF1α</span>. The maximum value in each experiment was set to “1”. Shoot tip, S; the youngest leaf, Y; and the old leaf, O. Vertical bars indicate the means ± standard error of 9 biological replicates (n = 9).</p>
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<p>Spectral distribution of experimental light treatments: the daily white LEDs (range about 400~720 nm, and peaked at 452 nm) (<b>A</b>), and supplemental or night-interruptional blue LEDs (peaked at 450 nm) (<b>B</b>).</p>
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<p>Experimental light schemes employed in this study (<b>A</b>). The treatment position of supplemental or night-interruptional blue light (<b>B</b>).</p>
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14 pages, 3202 KiB  
Article
Toward Cross-Species Crop Se Content Prediction Using Random Forest Modeling
by Yafeng Zhang, Guowen Miao, Yao Niu, Qiang Ma, Shuai Wang, Lianzhu He, Mingxia Zhu, Kaili Xu and Qiaohui Zhu
Sustainability 2024, 16(19), 8679; https://doi.org/10.3390/su16198679 - 8 Oct 2024
Viewed by 684
Abstract
Selenium is an indispensable trace element in the human body that plays an important role in maintaining life activities. The consumption of Se-rich crops provides a practical and effective way for the body to supplement Se. However, the Se content in crops is [...] Read more.
Selenium is an indispensable trace element in the human body that plays an important role in maintaining life activities. The consumption of Se-rich crops provides a practical and effective way for the body to supplement Se. However, the Se content in crops is affected by the soil Se content and the interactions between other elements in the soil. In this study, the Tibetan Plateau of China was chosen as the study area. The random forest algorithm was applied to select four key indicators—selenium (Se), bioavailable phosphorus (P), cadmium (Cd), and bioavailable copper (Cu)—from 29 soil variables to predict the Se content in rapeseed, wheat, potato, pasture, and chrysanthemum crops. The results showed that, despite the rich soil Se resources in the Tibetan Plateau, only 20% of the crop samples met the national Se enrichment standard (>0.07 mg kg−1). Compared with the traditional multiple linear regression method, the random forest model is more accurate, efficient, and reliable in predicting the Se content of crops. In cross-species crop prediction, which refers to the simultaneous cultivation and analysis of multiple distinct crop species within the same agricultural setting, the random forest model demonstrated superior performance, marking a significant breakthrough in cross-species crop research. This approach effectively eliminates the tedious process of conducting repetitive individual evaluations for different crop types in the same region, highlighting its innovative significance. Meanwhile, the Tibetan Plateau, known as the “Roof of the World”, is also of great research value. These results provide valuable references for the planning and management of Se-enriched farmlands, which will help improve the yield and quality of Se-enriched crops and promote the growth of farmers’ interests. Full article
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<p>Location of the study area, geological profile, and map of sampling points.</p>
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<p>Spatial distribution of Se.</p>
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<p>Relationship between soil Se content and crops.</p>
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<p>Spatial distribution of soil Se content and crop Se content.</p>
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<p>Importance estimation of five selected elements after selection.</p>
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<p>Correlation matrix between Se content in crops and soil indicators in the study area.</p>
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<p>Comparison of BCF<sub>Se</sub> measured values with random forest and MLR model predicted values: (<b>a</b>) random forest model; (<b>b</b>) MLR model.</p>
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<p>Predictions of naturally Se-enriched crops in agricultural fields across the entire study area using random forest and MLR models ((<b>top</b>): random forest model, (<b>bottom</b>): MLR Model).</p>
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22 pages, 9571 KiB  
Article
Differences in the Determination of Volatile Organic Compounds between Chrysanthemum morifolium Ramat. and Chrysanthemum indicum L. (Wild Chrysanthemum) by HS-GC-IMS
by Gaigai Liu, Hao Duan, Yue Zheng, Jinhong Guo, Diandian Wang and Wenjie Yan
Molecules 2024, 29(19), 4609; https://doi.org/10.3390/molecules29194609 - 27 Sep 2024
Viewed by 652
Abstract
Chrysanthemums and wild chrysanthemums are herbs with high application value. As edible plants of the Asteraceae family, they have good antioxidant, anti-inflammatory and hepatoprotective properties. Chrysanthemums and wild chrysanthemums contain a wide variety of volatile organic compounds, and these volatile components are the [...] Read more.
Chrysanthemums and wild chrysanthemums are herbs with high application value. As edible plants of the Asteraceae family, they have good antioxidant, anti-inflammatory and hepatoprotective properties. Chrysanthemums and wild chrysanthemums contain a wide variety of volatile organic compounds, and these volatile components are the main factors contributing to the flavor differences. Therefore, in this study, we investigated the volatile components of holland chrysanthemum from Bozhou, Anhui Province, Chu-chrysanthemum from Chuzhou, Anhui Province, Gong-chrysanthemums from Huangshan, Anhui Province, Huai-chrysanthemums from Jiaozuo, Henan Province, Hang-chrysanthemum from Hangzhou, Zhejiang Province, and wild chrysanthemum from Dabie Mountain by headspace–gas chromatography–ion mobility spectrometry (HS-GC-IMS) coupled with principal component analysis (PCA). The results showed that Chrysanthemum and wild chrysanthemum contain alcohols, esters, hydrocarbons, ketones, aldehydes, acids, camphor, pyrazines and furans. Among them, alcohols, esters and hydrocarbons accounted for more than 15%. It was hypothesized that 2-methyl-1-propanol, 2-methylbutanol, 1-hexanol in alcohols and hexyl acetate, 3-methylbutyl acetate and ethyl 2-methylpropanoate in esters might be the main reasons for the alcoholic and sweet flavors of chrysanthemum and chrysanthemum officinale. Based on the principal component analysis, cluster analysis with the Euclidean distance and similarity analysis of fingerprints, it was found that there were significant differences in the volatile components in chrysanthemums from different origins, among which the differences between Chu-chrysanthemum and Hang-chrysanthemum were the most significant. In addition, as a genus of wild chrysanthemum with the same species, it contains a richer variety of volatile organic compounds, and the content of hydrocarbons and alcohols is significantly higher than that of chrysanthemum. Full article
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<p>3D geomorphological map.</p>
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<p>Topographic maps of all samples. (A: Huai-chrysanthemum; B: Bo-chrysanthemum; C: Chu-chrysanthemum; D: Gong-chrysanthemum; E: Hang-chrysanthemum; F: Wild chrysanthemum cm<sup>2</sup>).</p>
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<p>GC-IMS difference spectrum of volatile components.</p>
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<p>Fingerprints of volatile components. (A: Huai-chrysanthemum; B: Bo-chrysanthemum; C: Chu-chrysanthemum; D: Gong-chrysanthemum; E: Hang-chrysanthemum; F: Wild chrysanthemum cm<sup>2</sup>).</p>
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<p>(<b>a</b>) Fingerprint similarity based on the Euclidean distance of different samples; (<b>b</b>) results of the PCA analysis of six samples.</p>
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<p>Qualitative characterization information for samples.</p>
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<p>HCA of volatile components in six samples.</p>
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<p>Representative component difference chart.</p>
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<p>Chrysanthemum and wild chrysanthemum appearance.</p>
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13 pages, 2537 KiB  
Article
Effect of Extraction Methods on Chemical Characteristics and Bioactivity of Chrysanthemum morifolium cv. Fubaiju Extracts
by Shang Gao, Tiantian Li, Zhao-Rong Li, Bingwu Liao, Zirui Huang, Chunxia Zhou and Rui-Bo Jia
Foods 2024, 13(19), 3057; https://doi.org/10.3390/foods13193057 - 26 Sep 2024
Viewed by 873
Abstract
Chrysanthemum morifolium cv. Fubaiju (CMF) is regarded as one of the three most renowned varieties of white Chrysanthemum in China, and different extraction methods have significant effects on its composition and activities. Therefore, six extractions were used in this study to assess the [...] Read more.
Chrysanthemum morifolium cv. Fubaiju (CMF) is regarded as one of the three most renowned varieties of white Chrysanthemum in China, and different extraction methods have significant effects on its composition and activities. Therefore, six extractions were used in this study to assess the effects on extracts. The basic chemical composition showed that hot water extract (Hw) had the highest total phenolic content, alkali water immersion-assisted hot water extract (Al) had the highest content of protein, and enzyme-assisted hot water extract (Enz) had the highest content of carbohydrate. The UPLC-Q-Exactive-MS results evinced the presence of 19 small-molecule compounds, including chlorogenic acid, caffeic acid, tuberonic acid glucoside, luteolin-7-O-rutinoside, and other substances. In addition, the antioxidant test found that the Hw exhibited the best 1,1-diphenyl-2-picrylhydrazyl (DPPH) (82.05 ± 1.59 mM TE/mg) and 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) (ABTS) (61.91 ± 0.27 mM TE/mg) scavenging ability. The anti-glycation test demonstrated that Enz possessed the most pronounced inhibitory effect on glycation products, including fructosamine and advanced glycation end products (AGEs). Additionally, the Enz also exhibited the most significant inhibitory effect on the protein oxidation product N’-formylkynurenine. The correlation analysis revealed that there was a close relationship between antioxidant properties and glycation resistance of extracts, and tuberonic acid glucoside, 1,3-di-O-caffeoylquinic acid, 1,4-Dicaffeoylquinic acid, quercetin-7-O-β-D-glucopyranoside, and isochlorogenic acid B were key small molecule components that affected activities. In summary, the extracts of CMF can be regarded as an excellent antioxidant and anti-glycosylation agent. Full article
(This article belongs to the Section Food Engineering and Technology)
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<p>Technical roadmap of this work.</p>
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<p>The activities of the various extracts of CMF, including ABTS (<b>A</b>) and DPPH (<b>B</b>) free radical scavenging capacity. Data are expressed as mean ± SD (<span class="html-italic">n</span> = 3). Significant differences (<span class="html-italic">p</span> &lt; 0.05) are indicated with different letters.</p>
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<p>Inhibition rate of fructosamine (<b>A</b>), <span class="html-italic">α</span>-dicarbonyl compound (<b>B</b>), and AGEs (<b>C</b>) of 6 extracts. Data are expressed as mean ± SD (<span class="html-italic">n</span> = 3). Significant differences (<span class="html-italic">p</span> &lt; 0.05) are indicated with different letters.</p>
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<p>The inhibition rate of 6 extracts on BSA protein oxidation products: (<b>A</b>) dityrosine; (<b>B</b>) N’-formylkynurenine. Data are expressed as mean ± SD (<span class="html-italic">n</span> = 3). Significant differences (<span class="html-italic">p</span> &lt; 0.05) are indicated with different letters.</p>
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<p>Network of Spearman’s correlation between glycosylation products and antioxidant indexes (<b>A</b>); heatmap of Spearman’s correlation of antioxidant and glycosylation indexes in CMF extracts (<b>B</b>).</p>
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18 pages, 7282 KiB  
Article
Delineating Molecular Regulatory of Flavonoids Indicated by Transcriptomic and Metabolomics Analysis during Flower Development in Chrysanthemum morifolium ‘Boju’
by Zhuannan Chu, Rui Xiong, Xingxing Peng, Guangsheng Cui, Ling Dong and Weiwen Li
Int. J. Mol. Sci. 2024, 25(19), 10261; https://doi.org/10.3390/ijms251910261 - 24 Sep 2024
Viewed by 1576
Abstract
Flavonoids are pharmacologically active compounds in flowers of Chrysanthemum morifoliumBoju’ (C. morifolium); however, the molecular regulatory network governing flower development remains largely elusive. Flower samples were collected at four stages, namely budding (BD), bud breaking (BB), early blooming (EB), [...] Read more.
Flavonoids are pharmacologically active compounds in flowers of Chrysanthemum morifoliumBoju’ (C. morifolium); however, the molecular regulatory network governing flower development remains largely elusive. Flower samples were collected at four stages, namely budding (BD), bud breaking (BB), early blooming (EB), and full blooming (FB), for omics analysis. We revealed distinct transcriptional regulation patterns at these four stages of the flower from the perspective of differentially expressed unigenes (DEGs). There are 152 DEGs shared among the three comparative groups (BD vs. BB, BB vs EB, EB vs FB), wherein the expression of 44 DEGs (including AtADT6, MDL3, and ROMT) continues to be upregulated, and 85 DEGs (including CYP81E, TPS-Cin-1, and TPS-Cin-2) showed persistent downregulation with flower development. Flavonoid-targeted metabolomics identified 118 differentially abundant metabolites (DAMs) in the FB group compared to the BD stage; the top three upregulated and downregulated metabolites are Cyanidin-3-O-(6″-O-malonyl)glucoside-5-O-glucoside, Luteolin-7-O-(6″-caffeoyl)rhamnoside, Kaempferol-3-O-(6″-p-coumaroyl)glucoside and Chrysoeriol-6,8-di-C-glucoside-7-O-glucoside, Kaempferol, Kaempferol-3,7-O-dirhamnoside, respectively. These DAMs were predominantly enriched in “flavonoid biosynthesis”, “isoflavonoid biosynthesis”, and “flavone and flavonol biosynthesis” pathways. AtADT6, MDL3, ROMT, CYP81E, TPS-Cin-1, and TPS-Cin-2 were correlated with kaempferol. Our findings provide a new idea for interfering with flavonoid production, especially kaempferol, in flowers. Full article
(This article belongs to the Section Bioactives and Nutraceuticals)
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<p>Transcriptomic profiles of four developmental stages of C. <span class="html-italic">morifolium</span> flower. (<b>A</b>) Representative images of C. <span class="html-italic">morifolium</span> flowers at four different stages of development. (<b>B</b>) Statistical pie charts of transcript sequences mapped to different species in the NR database. (<b>C</b>) Principal component analysis plot of all samples in the transcriptome. B1, B2, B3, and B4 means BD, BB, EB, and FB, respectively.</p>
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<p>Flowers of C. <span class="html-italic">morifolium</span> exhibit differential transcriptomic profiles at four different stages. Volcano map of differentially expressed unigenes in the comparison groups of BD vs. BB (<b>A</b>), BB vs. EB (<b>B</b>), BB vs. FB (<b>C</b>). Red indicates up-regulated genes, green indicates down-regulated genes, and blue indicates non-significant genes. (<b>D</b>) The hierarchical clustering heatmap of all differentially expressed unigenes. Bubble plot of KEGG enrichment of differentially expressed unigenes in the comparison groups of BD vs. BB (<b>E</b>), BB vs. EB (<b>F</b>), BB vs. FB (<b>G</b>).</p>
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<p>Identification of common differentially expressed unigenes in all the comparison groups. (<b>A</b>) A Venn diagram of intersected differentially expressed unigenes from the three comparative groups. (<b>B</b>) Kmeans_clustering analysis of differentially expressed unigenes in four groups. (<b>C</b>) Bubble plot of KEGG enrichment of 44 common upregulated differentially expressed unigenes. (<b>D</b>) Bubble plot of KEGG enrichment of 85 common downregulated differentially expressed unigenes.</p>
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<p>The metabolic landscape of flavonoid compounds in the flowers undergoes significant changes, particularly in the early and mature stages. (<b>A</b>) Scores of OPLS-DA plot and OPLS-DA model in the comparison groups of BD vs. FB. M1, M2, M3, and M4 means BD, BB, EB, and FB, respectively. (<b>B</b>) The hierarchical clustering heatmap of differentially abundance metabolites between BD vs. FB. (<b>C</b>) Histogram of the top 20 differentially abundance metabolites between BD vs. FB. (<b>D</b>) Histogram of KEGG enrichment pathway of differentially abundance metabolites between BD vs. FB.</p>
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<p>Four candidate metabolites from metabolome data were verified by LC-MS detection. ns means <span class="html-italic">p</span> &gt; 0.05, * means <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Integrative analyses of transcriptome and metabolome reveal the molecular mechanism underlying variation in flavonoids during flower development of <span class="html-italic">C</span>. <span class="html-italic">morifolium</span>. (<b>A</b>) A nine-quadrant volcano plot of Pearson correlation coefficients between genes and metabolites. (<b>B</b>) Genes and metabolites exhibiting a consistent regulatory trend were visualized in a hierarchical clustering heatmap. (<b>C</b>) The canonical correlation analysis (CCA) plot in flavonoid biosynthesis pathway. (<b>D</b>) The CCA plot in flavone and flavonol biosynthesis pathway.</p>
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<p>KEGG map of flavone and flavonol biosynthesis. Red and green circles indicate differentially abundance metabolites that are up-regulated and down-regulated in BD vs. FB, respectively. The blue boxes indicate genes that are up-regulated or down-regulated.</p>
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18 pages, 12839 KiB  
Article
Systematic Identification and Characterization of O-Methyltransferase Gene Family Members Involved in Flavonoid Biosynthesis in Chrysanthemum indicum L.
by Man Zhang, Tao Wang, Qiaosheng Guo, Yong Su and Feng Yang
Int. J. Mol. Sci. 2024, 25(18), 10037; https://doi.org/10.3390/ijms251810037 - 18 Sep 2024
Viewed by 823
Abstract
Chrysanthemum indicum L. capitulum is an enriched source of flavonoids with broad-ranging biological activities, mainly due to their anti-inflammatory, anti-cancer, immune regulation, anti-microbial activity, hepatoprotective, and neuroprotective effects. The O-methylation of various secondary metabolites has previously been demonstrated to be mainly catalyzed [...] Read more.
Chrysanthemum indicum L. capitulum is an enriched source of flavonoids with broad-ranging biological activities, mainly due to their anti-inflammatory, anti-cancer, immune regulation, anti-microbial activity, hepatoprotective, and neuroprotective effects. The O-methylation of various secondary metabolites has previously been demonstrated to be mainly catalyzed by S-adenosyl-L-methionine-dependent O-methyltransferase (OMT) proteins encoded by the OMT gene family. However, limited comprehensive study was published on the OMT gene family, especially the CCoAOMT subfamily, involved in the O-methylation of flavonoids in Chrysanthemum. Here, we analyzed the spatiotemporal expression patterns of C. indicum OMT genes in leaf and flower at different developmental stages. Transcriptome sequencing and qRT-PCR analysis showed that COMTs were mainly highly expressed in capitulum, especially in full bloom, while CCoAOMTs were mainly highly expressed in leaves. Correlation analysis of OMT gene expression and flavonoids accumulation revealed that four OMTs (CHR00029120, CHR00029783, CHR00077404, and CHR00078333) were putatively involved in most methylated flavonoids biosynthesis in the capitulum. Furthermore, we identified a true CCoAOMT enzyme, CiCCoAOMT1, and found that it catalyzed O-methylation of quercetin and luteolin at the 3′-OH position. In summary, this work provides an important theoretical basis for further research on the biological functions of OMTs in C. indicum. Full article
(This article belongs to the Section Bioactives and Nutraceuticals)
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<p>Phylogenetic relationships of OMTs in different species. Subclades are marked by different backgrounds. The blue arc represents COMT subfamily; green and yellow arcs represent CCoAOMT subfamily. UniProt entries for these OMTs are given in <a href="#app1-ijms-25-10037" class="html-app">Table S2</a>.</p>
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<p>Phylogenetic relationship, gene structure, and motif analysis of <span class="html-italic">C</span>. <span class="html-italic">indicum OMT</span>s. (<b>a</b>) Phylogenetic tree. (<b>b</b>) Gene structure analysis. Exons (CDS, coding sequence) and introns are represented by the yellow box and the grey line, respectively. The green box represents UTR (untranslated region). (<b>c</b>) Conserved domain prediction. The protein length can be estimated using the scale at the bottom. (<b>d</b>) Conserved motif prediction. Motifs 1–14 are indicated by the different color boxes.</p>
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<p>Expression pattern of <span class="html-italic">OMT</span>s in different capitulum development stages and leaves of <span class="html-italic">C</span>. <span class="html-italic">indicum</span>. (<b>a</b>) <span class="html-italic">C</span>. <span class="html-italic">indicum</span> tissues. Flower1–3, respectively, correspond to flower bud stage, early flowering stage, full opening stage. Heatmap display of <span class="html-italic">C</span>. <span class="html-italic">indicum OM</span>Ts with relatively high transcript levels (FPKM &gt; 10) (<b>b</b>) and with relatively low transcript levels (FPKM &lt; 10) (<b>c</b>). The original data of the RNA-seq are shown in <a href="#app1-ijms-25-10037" class="html-app">Table S3</a>, and the hierarchical clustering analysis (<a href="#app1-ijms-25-10037" class="html-app">Figure S1</a>) shows its reproducibility and reliability. The color scale from blue to red color represents Z-score-normalized gene expression levels from low to high. Dendrograms on the left side of the heat map show the hierarchical clustering between genes. At the tip of the cluster tree, <span class="html-italic">CiCOMT</span>s and <span class="html-italic">CiCCoAOMT</span>s are marked with red and blue circle dots, respectively.</p>
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<p>Quantitative expression and relative expression levels of <span class="html-italic">OMT</span>s in capitulum at different development stages and leaves of <span class="html-italic">C</span>. <span class="html-italic">indicum</span>. The gene name appears at the top of each histogram and tissues appear at the bottom. The relative expression level of each gene in flower1 is set to 1. Error bar means standard deviation (SD) among three independent replicates. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, ns means no significance.</p>
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<p>Screening of <span class="html-italic">C</span>. <span class="html-italic">indicum OMT</span> genes involved in flavonoid accumulation in the capitulum. (<b>a</b>) Correlation analysis heatmap between methylated flavonoid concentrations content and the expression of <span class="html-italic">C</span>. <span class="html-italic">indicum OMT</span> genes (FPKM &gt; 10 in at least one sample) based on Pearson correlation coefficient (r). (<b>b</b>) Correlation analysis heatmap between potential methylation substrates content and the expression of <span class="html-italic">OMT</span> genes based on Pearson correlation coefficient (r). (<b>c</b>) Flavonoid structure. Methylation sites are marked in blue.</p>
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<p>UPLC chromatograms of the reactions of CiCCoAOMT1 with different flavones substrates including quercetin (<b>a</b>) and luteolin (<b>b</b>). Substrates incubated with the empty vector (pET32a) are indicated in cyan. Substrates utilized by recombinant CiCCoAOMT1 are indicated in red. Authentic compounds of methylated products are indicated in yellow. OCH3 in blue color represents the methylation site. The interrupted line points to the retention time of the compound.</p>
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<p>Subcellular localization of CiCCoAOMT1 in <span class="html-italic">N</span>. <span class="html-italic">benthamiana</span>. GFP, GFP channel; mCherry, RFP channel; Bright, blight field channel; Merged, merged image of the GFP, mCherry, and Bright channels. Scale bars are 20 μm.</p>
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<p>Overexpression analysis of <span class="html-italic">CiCCoAOMT1</span> in <span class="html-italic">C</span>. <span class="html-italic">indicum</span>. (<b>A</b>) The expression pattern of <span class="html-italic">CiCCoAOMT1</span>. (<b>B</b>) LC-MS extracted ion chromatograms (EIC) of <span class="html-italic">C</span>. <span class="html-italic">indicum</span> with CiCCoAOMT1 or empty vector. (<b>C</b>) Changes in the chrysoeriol content after overexpression of <span class="html-italic">CiCCoAOMT1</span> gene. Data are mean ± standard deviation of three biological replicates. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 (1-tailed paired <span class="html-italic">t</span>-test).</p>
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15 pages, 8144 KiB  
Article
Regulatory Effects of Different Biochar on Soil Properties and Microbial Community Structure in Chrysanthemum Continuous Cropping Soil
by Yang Feng, Xin Hu, Yanhuan Guan, Zhixuan Chu, Xianfeng Du, Yuyan Xie, Shiqi Yang, Siru Ye, Lei Zhang, Jinyi Ma and Haoming Chen
Agronomy 2024, 14(9), 2034; https://doi.org/10.3390/agronomy14092034 - 6 Sep 2024
Viewed by 686
Abstract
Chrysanthemum, an agricultural economic crop with ornamental, medicinal, and edible values, faces the problem of continuous cropping obstacles in its cultivation. As a potential soil conditioner used to address continuous cropping obstacles (CCOs), the applicability of biochar in chrysanthemum cultivation has become a [...] Read more.
Chrysanthemum, an agricultural economic crop with ornamental, medicinal, and edible values, faces the problem of continuous cropping obstacles in its cultivation. As a potential soil conditioner used to address continuous cropping obstacles (CCOs), the applicability of biochar in chrysanthemum cultivation has become a research hotspot. This study explored the effects of three different types of biochar (rice straw biochar = RB, pig manure biochar = PB, and sludge biochar = SB) on soil for chrysanthemum that had been continuously cultivated for eight years through pot experiments. The results indicate that the addition of biochar significantly reduced soil water loss. Compared with CK, the water retention rates of the SB and PB treatments increased by 25.4% and 18.4%, respectively. In the PB treatment, the contents of available phosphorus (AP) and available potassium (AK) increased by 85% and 164%, respectively. The available nitrogen (AN) content showed the highest increase under the SB treatment. All three types of biochar could improve the pH value of chrysanthemum soil with CCOs (increased by 0.4–5.4%). The results of microbial community diversity showed that, compared with CK, PB and RB slightly reduced the diversity of bacterial communities in chrysanthemum soil with CCOs (by 1.50% and 0.41%, respectively). However, the SB treatment increased the diversity of bacterial communities in chrysanthemum soil with CCOs (by 0.41%). At the same time, SB and PB significantly inhibited the diversity of fungal communities (reduced by 15.15% and 6.67%, respectively), while RB promoted the diversity of fungal communities (increased by 5.45%). Furthermore, the analysis results of bacterial phyla and genera indicated that PB and SB had enhancing effects on the beneficial bacterial phylum Actinobacteriota (8.66% and 4.64%) and the beneficial bacterial genus Nocardioides (23.29% and 9.69%). Additionally, the PB treatment enhanced the beneficial bacterial phylum Firmicutes (7.03%). The analysis results of fungal genera and phyla indicated that PB contributed to an increase in the beneficial fungal phylum Ascomycota (1.51%). RB significantly enhanced the beneficial fungal genus Chaetomium (56.34%). Additionally, all three types of biochar effectively reduced the abundance of the harmful fungal phylum Basidiomycota (30.37–73.03%). In the PB and SB treatments, the harmful fungal phylum Mucoromycota was significantly decreased (by 36.22% and 62.60%, respectively). Finally, all three types of biochar reduced the abundance of harmful fungal genera Acremonium (1.15–35.19%) and Phoma (97.1–98.7%). In this study, we investigated the effect of three kinds of biochar (RB, PB, and SB) on the soil of chrysanthemum continuous cropping through potting experiments and found that they could significantly reduce water loss, enhance water retention, increase the soil nutrient content, improve the pH value, regulate microbial communities, increase beneficial microorganisms, and reduce harmful microorganisms. These results provide a scientific basis for addressing barriers to continuous cropping (CC) while supporting the sustainability of agriculture and the development of agroecology. Full article
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<p>Three-dimensional PCoA map of soil bacterial community (<b>A</b>) and soil fungi community (<b>B</b>); 95% confidence interval.</p>
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<p>Venn plots of soil bacteria (<b>A</b>) and fungi (<b>B</b>) community composition. Note: red, blue, green, and yellow represent CK, PB, RB, and SB treatments, respectively.</p>
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<p>Heatmaps of bacterial phylum level (<b>A</b>) and bacterial genus level (<b>B</b>) of soil under different treatments.</p>
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<p>Heatmaps of fungal phylum level (<b>A</b>) and fungal genus level (<b>B</b>) of soil under different treatments.</p>
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<p>Abundance plots of bacterial phyla level (<b>A</b>) and bacterial genera level (<b>B</b>) under different treatments.</p>
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<p>Abundance plots of fungal phyla level (<b>A</b>) and fungal genera level (<b>B</b>) under different treatments.</p>
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16 pages, 3284 KiB  
Article
Influence of Tea Polyphenols, Chitosan, and Melatonin as the Eco-Friendly Post-Harvest Treatments on the Vase Life of the Cut Chrysanthemum ‘Pingpong’ Group
by Ziyi Yu, Shuangda Li and Yan Hong
Agriculture 2024, 14(9), 1507; https://doi.org/10.3390/agriculture14091507 - 2 Sep 2024
Viewed by 1031
Abstract
Vase life is a decisive measure of the marketability of post-harvest physiology in cut flowers. In the process of petal senescence, the cut chrysanthemum (Chrysanthemum × morifolium) ‘Pingpong’ group develops severe capitulum collapse which manifests as wilting and browning, leading to [...] Read more.
Vase life is a decisive measure of the marketability of post-harvest physiology in cut flowers. In the process of petal senescence, the cut chrysanthemum (Chrysanthemum × morifolium) ‘Pingpong’ group develops severe capitulum collapse which manifests as wilting and browning, leading to shorter vase life. Melatonin (MT), tea polyphenols (TPs), and chitosan (CT) are natural alternatives to chemical compounds with proven preservation effects. In this study, the possibility of mitigating capitulum collapse using the preservation solutions of these three eco-friendly ingredients was investigated on four varieties from the ‘Pingpong’ group, aiming to delay the senescence process. The effects on vase life of 0.02/0.04 mmol·L−1 MT, 200/400 mg·L−1 TPs, and 0.10/0.20 g·L−1 CT were, respectively, assessed with the basis of 20 g·L−1 sucrose and 250 mg·L−1 citric acid. The yellow and white varieties tend to have a longer vase life compared with the green and pink varieties. Compared to the control with only base ingredients, the greatest delay in capitulum collapse was observed with 0.04 mmol·L−1 MT in the yellow variety, maximizing the vase life to 13.4 days. MT maintained the best ornamental quality of the capitulum by decelerating fresh weight and flower diameter loss in terms of all varieties. TPs significantly increased flower diameter to improve vase life up to four more days. However, CT caused significant negative effects on vase life, with severe loss of both flower diameter and fresh weight. Therefore, the application of 0.04 mmol·L−1 MT and 200 mg·L−1 TPs was suggested to enhance the marketability of cut ‘Pingpong’, which highlighted the eco-friendly potential of post-harvest treatments. Full article
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<p>Four stages of flower senescence in the cut chrysanthemum ‘Pingpong’ group during the vase life. S1: fresh stage; S2: growing stage; S3: wilting and browning stage; S4: collapsing stage (half of petals brown or wilted).</p>
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<p>Exhibitive flowers of the cut chrysanthemum ‘Pingpong’ group. From left to right: <span class="html-italic">Chrysanthemum × morifolium</span> ‘Yellow Pingpong’, <span class="html-italic">C. × morifolium</span> ‘White Pingpong’, <span class="html-italic">C. × morifolium</span> ‘Pink Pingpong’, and <span class="html-italic">C. × morifolium</span> ‘Green Pingpong’.</p>
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<p>Senescence processes during the vase life period of the variety <span class="html-italic">Chrysanthemum × morifolium</span> ‘White Pingpong’. A certain stage is reached if more than half (i.e., three replicates) of the five replicates in a treatment reach that stage.</p>
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<p>Flower diameter changing process in the vase life period. (<b>A</b>) Yellow variety; (<b>B</b>) white variety; (<b>C</b>) green variety; (<b>D</b>) pink variety. Values are the means ± standard error (SE) (<span class="html-italic">n</span> = 5). LSD at <span class="html-italic">p</span> &lt; 0.05 was used for means comparison. TPs, tea polyphenols; CT, chitosan; MT, melatonin.</p>
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<p>Comparison of the range of flower diameter of the CK sample (max. and min.).</p>
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<p>Fresh weight and water balance changing process in the vase life period of the white variety. Values are the means ± standard error (SE) (<span class="html-italic">n</span> = 5). LSD at <span class="html-italic">p</span> &lt; 0.05 was used for means comparison. TPs, tea polyphenols; CT, chitosan; MT, melatonin.</p>
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<p>PCA of four treats among varieties under seven treatments.</p>
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15 pages, 9123 KiB  
Article
Comparative Analysis of the Chemical Constituents of Chrysanthemum morifolium with Different Drying Processes Integrating LC/GC–MS−Based, Non-Targeted Metabolomics
by Na Chen, Jizhou Fan, Gang Li, Xuanxuan Guo, Xiao Meng, Yuqing Wang, Yingying Duan, Wanyue Ding, Kai Liu, Yaowu Liu and Shihai Xing
Metabolites 2024, 14(9), 481; https://doi.org/10.3390/metabo14090481 - 2 Sep 2024
Viewed by 1032
Abstract
Chrysanthemum morifolium is a perennial herbaceous plant in the Asteraceae family that is used as a medicine and food owing to its superior pharmacological properties. Irrespective of its application, C. morifolium must be dried before use. Shade drying (YG) and heat drying (HG) [...] Read more.
Chrysanthemum morifolium is a perennial herbaceous plant in the Asteraceae family that is used as a medicine and food owing to its superior pharmacological properties. Irrespective of its application, C. morifolium must be dried before use. Shade drying (YG) and heat drying (HG) are the two drying methods used in most origins. Given the abundance of flavonoids, phenolic acids, and terpenoids, the primary medicinal active constituents of C. morifolium, it is important to determine whether the composition and content of these compounds are altered during the drying processes. To test this, the changes in the chemical composition of C. morifolium flowers after YG and HG using full-spectrum, non-targeted LC/GC–MS−based metabolomics and, subsequently, the three indicator components of C. morifolium—chlorogenic acid, 3,5−dicaffeoylquinic acid, and luteolin−7−O−glucoside—were accurately quantified by HPLC. The results of the non-targeted metabolomics analysis revealed that YG- and HG-processed C. morifolium differed significantly with respect to chemical contents, especially flavonoids, phenolic acids, and terpenoids. The levels of the indicator components and their precursors also differed significantly between the YG and HG treatments. The contents of most of the flavonoids and key phenolic acids, terpenoids, and carbohydrates were higher with YG than with HG pre-treatment. These results revealed the changes in the chemical composition of C. morifolium during the YG and HG processes, thus providing a reference for the further optimization of the production and processing of chrysanthemums. Full article
(This article belongs to the Special Issue LC-MS/MS Analysis for Plant Secondary Metabolites)
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<p>The global metabolite profile of Chrysanthemum morifolium flowers based on gas chromatography–mass spectrometry (GC–MS) and liquid chromatography–mass spectrometry (LC–MS). (<b>A</b>) LC–MS chromatograms in positive mode electrospray ionization (ESI). (<b>B</b>) LC–MS chromatograms in negative mode ESI. (<b>C</b>) GC–MS chromatograms. Blue, shade-drying group (YG); red, heat−drying group (HG). (<b>D</b>) The superclass of 7908 metabolites identified. Different color blocks represent different compound classes.</p>
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<p>Multivariate model and its cross-validation. (<b>A</b>,<b>B</b>) Principal Component Analysis (PCA) of the LC/GC–MS data. (Combine both positive and negative ion data to generate) (<b>C</b>,<b>D</b>) Orthogonal Partial Least Squares−Discriminant Analysis (OPLS−DA) of the LC/GC–MS data. (<b>E</b>,<b>F</b>) Response permutation testing of the model predicted by OPLS−DA. R2X (cum): cumulative interpretation rate in the X direction; R2Y (cum): cumulative interpretation rate in the Y direction; Q2 (cum): cumulative forecast rate of the model; R2 and Q2: parameters of the response sequencing test used to measure whether the model was overfitted.</p>
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<p>Differentially abundant metabolites between the YG and HG samples. (<b>A</b>) A volcano plot comprising both LC–MS and GC–MS data of the 7908 metabolites identified by metabolomics analysis. VIP &gt; 1 and <span class="html-italic">p</span> &lt; 0.05 served as the criteria for differential metabolite classification. (<b>B</b>) Classification of the 759 differential metabolites. (<b>C</b>) A heat map of top 50 differential metabolites. (VIP: Variable importance in the projection. P: Probability Value. HG: heat drying. YG: Shade drying).</p>
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<p>High-performance liquid chromatography (HPLC) analysis of 3 medicinal ingredients in <span class="html-italic">chrysanthemum</span> (boju). (<b>A</b>) HPLC chromatogram for 3 medicinal ingredients in <span class="html-italic">chrysanthemum</span> (boju). (<b>B</b>) Bar charts of the three indicator components of <span class="html-italic">chrysanthemum</span> (boju) (* <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. (<b>A</b>) The top 20 pathways in terms of −lg (<span class="html-italic">p</span>-value) for the HG samples compared to the YG samples. (<b>B</b>) A KEGG analysis bubble plot of the top 20 enriched pathways. (<b>C</b>) The 10 most significantly (smallest <span class="html-italic">p</span>-value) upregulated and downregulated KEGG metabolic pathways between the HG and YG groups. (<b>D</b>) The chlorogenic acid, 3,5−O−dicaffeoyl−quinic acid, and luteolin−7−O−glucoside synthetic pathways.</p>
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<p>A heatmap of the 81 flavonoids in HG− and YG−processed <span class="html-italic">C. morifolium</span>.</p>
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<p>Box plots of β-farnesene, mannose, rhamnose, and 1-kestose. (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p>
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21 pages, 16331 KiB  
Article
Construction of Optimal Regeneration System for Chrysanthemum ‘11-C-2’ Stem Segment with Buds
by Qingbing Chen, Kang Gao, Bo Pan, Yaoyao Wang, Lijie Chen, Junjun Yu, Lili Wang, Yongming Fan, Haiying Li and Conglin Huang
Plants 2024, 13(17), 2403; https://doi.org/10.3390/plants13172403 - 28 Aug 2024
Viewed by 704
Abstract
Chrysanthemum morifolium ‘11-C-2’ is a variety of chrysanthemums with high ornamental and tea value, experiencing significant market demand. However, as cultivation areas expand, issues such as viral infection, germplasm degradation, low proliferation coefficient, and slow proliferation rate arise, necessitating the establishment of an [...] Read more.
Chrysanthemum morifolium ‘11-C-2’ is a variety of chrysanthemums with high ornamental and tea value, experiencing significant market demand. However, as cultivation areas expand, issues such as viral infection, germplasm degradation, low proliferation coefficient, and slow proliferation rate arise, necessitating the establishment of an efficient in vitro regeneration system. This study, based on the principles of orthogonal experimental design, explored the regeneration system of Chrysanthemum cultivar ‘11-C-2’ using sterile seedlings. The research focused on three key stages: adventitious bud differentiation, rooting culture, and acclimatization–transplantation, employing shoot-bearing stem segments and leaves as explants. The findings indicate that the optimal explant for the Chrysanthemum ‘11-C-2’ sterile seedlings is the shoot-bearing stem segment. The best medium for adventitious bud differentiation was determined to be MS supplemented with 1.5 mg/L 6-BA and 0.5 mg/L NAA. Bud differentiation began on day 17 with a 100% differentiation rate, completing around day 48. The maximum differentiation coefficient reached 87, with an average of 26.67. The adventitious buds were then cultured for rooting in the optimal medium of 1/2 MS supplemented with 0.1 mg/L NAA. Rooting was initiated on day 4 and was completed by day 14, achieving a rooting rate of 97.62%. After a 5-day acclimatization under natural light, the rooted seedlings were transplanted into a growth substrate with a peat-to-vermiculite ratio of 1:2. The plants exhibited optimal growth, with a transplantation survival rate of 100%. The findings provide data support for the efficient large-scale propagation of ‘11-C-2’ and lay the foundation for germplasm preservation and genetic transformation research of tea chrysanthemums. Full article
(This article belongs to the Special Issue In Vitro Techniques on Plant Propagation and Genetic Improvement)
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<p>Effect of 6-BA (<b>A</b>) and NAA (<b>B</b>) concentrations on the differentiation coefficient of stem segments with buds.</p>
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<p>Illustrates the adventitious bud differentiation of ‘11-C-2’ stem segments. (<b>A</b>) Callus induction and adventitious bud differentiation process using stem segments as explants (Bar = 2 cm); (<b>B</b>) Completed state of adventitious bud differentiation (Bar = 2 cm); (<b>C</b>) Maximum differentiation coefficient of ‘11-C-2’ stem segments (Bar = 2 cm); (a) Formation of callus at the cut end of the budded stem segment; (b) The callus starts to differentiate into adventitious buds; (c) Axillary buds on the stem segment directly differentiate into adventitious buds.</p>
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<p>Effects of basal medium and NAA concentration on root length and root number. (<b>A</b>) The effect of basic medium on the number of seedlings; (<b>B</b>) Effect of NAA concentration on the number of seedling roots; (<b>C</b>) Effect of base medium on root length of seedling; (<b>D</b>) Effect of NAA concentration on root length of seedling.</p>
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<p>Illustrates the rooting status of ‘11-C-2’ adventitious shoots under various treatments. Rooting and plant status of ‘11-C-2’ adventitious buds at 0–14 days under different treatments, Bars = 2 cm.</p>
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<p>Morphological appearance of tissue-cultured plantlets after 14 days of rooting under different treatments. Bar = 2 cm.</p>
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<p>Effects of seedling refining time and transplanting medium on plant height. (<b>A</b>) Effect of seedling refining time on plant height (5 d); (<b>B</b>) Effect of transplanting medium on plant height (5 d); (<b>C</b>) Effect of seedling refining time on plant height (10 d); (<b>D</b>) Effect of transplanting medium on plant height (10 d); (<b>E</b>) Effect of seedling refining time on plant height (15 d); (<b>F</b>) Effect of transplanting medium on plant height (15 d).</p>
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<p>Illustrates the growth status of ‘11-C-2’ under different substrate ratios. ‘11-C-2’ growth of root-rooted seedlings after transplanting 0–15 d; Bar = 4 cm.</p>
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<p>‘11-C-2’ Regeneration process of sprouted stem segments. (<b>A</b>) Explant, Bar = 2 cm; (<b>B</b>) Callus induction and adventitious bud differentiation, Bar = 2 cm; (<b>C</b>) Adventitious bud differentiation is complete, Bar = 2 cm; (<b>D</b>) Rooting culture, Bar = 2 cm; (<b>E</b>) Root plant, Bar = 2 cm; (<b>F</b>) Hardening and transplanting, Bar = 4 cm.</p>
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<p>Morphology of the whole plant and floral organs of Chrysanthemum ‘11-C-2’. (<b>A</b>) Whole plant (Bar = 3 cm); (<b>B</b>) Capitulum (Bar = 2 cm); (<b>C</b>) Stem segment with leaf and stem segment (Bar = 2 cm); (<b>D</b>) Leaf blade (Bar = 2 cm).</p>
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14 pages, 7781 KiB  
Article
Fast Screening of Tyrosinase Inhibitors in Coreopsis tinctoria Nutt. by Ligand Fishing Based on Paper-Immobilized Tyrosinase
by Ayzohra Ablat, Ming-Jie Li, Xiao-Rui Zhai, Yuan Wang, Xiao-Lin Bai, Peng Shu and Xun Liao
Molecules 2024, 29(17), 4018; https://doi.org/10.3390/molecules29174018 - 25 Aug 2024
Viewed by 943
Abstract
Coreopsis tinctoria Nutt. is an important medicinal plant in traditional Uyghur medicine. The skin-lightening potential of the flower has been recognized recently; however, the active compounds responsible for that are not clear. In this work, tyrosinase, a target protein for regulating melanin synthesis, [...] Read more.
Coreopsis tinctoria Nutt. is an important medicinal plant in traditional Uyghur medicine. The skin-lightening potential of the flower has been recognized recently; however, the active compounds responsible for that are not clear. In this work, tyrosinase, a target protein for regulating melanin synthesis, was immobilized on the Whatman paper for the first time to screen skin-lightening compounds present in the flower. Quercetagetin-7-O-glucoside (1), marein (2), and okanin (3) were found to be the enzyme inhibitors. The IC50 values of quercetagetin-7-O-glucoside (1) and okanin (3) were 79.06 ± 1.08 μM and 30.25 ± 1.11 μM, respectively, which is smaller than 100.21 ± 0.11 μM of the positive control kojic acid. Enzyme kinetic analysis and molecular docking were carried out to investigate their inhibition mechanism. Although marein (2) showed a weak inhibition effect in vitro, it inhibited the intracellular tyrosinase activity and diminished melanin production in melanoma B16 cells as did the other two inhibitors. The paper-based ligand fishing method developed in this work makes it effective to quickly screen tyrosinase inhibitors from natural products. This is the first report on the tyrosinase inhibitory effect of those three compounds, showing the promising potential of Coreopsis tinctoria for the development of herbal skin-lightening products. Full article
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<p>Scanning electron microscopy (SEM) images of (<b>A</b>) cellulose chromatography paper and (<b>B</b>) CP@DA@TYR.</p>
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<p>The influence of different buffer solvent systems on fishing results. (<b>a</b>) Extraction of <span class="html-italic">C. tinctoria</span> (S0); (<b>b</b>) CP@DA@TYR-S5 (compounds fished by CP@DA@TYR) in pH7.8 Tris-HCl; (<b>c</b>) CP@DA@TYR-S5 in pH6.0 PBS; (<b>d</b>) CP@DA@TYR-S5 in ultrapure water; and (<b>e</b>) CP@DA-BS5 (blank control: compounds fished by CP@DA).</p>
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<p>HPLC chromatograms (280 nm) of (<b>a</b>) S0, (<b>b</b>) CP@DA@TYR-S5, (<b>c</b>) MNPs@TYR-S5, (<b>d</b>) CP@DA-BS5, and (<b>e</b>) MNPs-BS5.</p>
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<p>HPLC chromatograms of ligand fishing of <span class="html-italic">C. tinctoria</span>. (<b>a</b>) S0, (<b>b</b>) S5, and (<b>c</b>) standard mixture of quercetagetin-7-<span class="html-italic">O</span>-glucoside, marein, and okanin. Chemical structures of (<b>1</b>) quercetagetin-7-<span class="html-italic">O</span>-glucoside, (<b>2</b>) marein, and (<b>3</b>) okanin.</p>
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<p>HPLC chromatograms of ligand fishing of <span class="html-italic">C. tinctoria</span>. (<b>a</b>) S0, (<b>b</b>) S5, and (<b>c</b>) standard mixture of quercetagetin-7-<span class="html-italic">O</span>-glucoside, marein, and okanin. Chemical structures of (<b>1</b>) quercetagetin-7-<span class="html-italic">O</span>-glucoside, (<b>2</b>) marein, and (<b>3</b>) okanin.</p>
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<p>Lineweaver–Burk plots for the inhibition of TYR by (<b>A</b>) <b>1</b> and (<b>B</b>) <b>3</b> at different concentrations.</p>
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<p>Molecular docking simulations of TYR with compounds <b>1</b> and <b>3</b>. Three-dimensional docking modes of (<b>A</b>) <b>1</b> and (<b>D</b>) <b>3</b> with TYR. The surface of docking modes of (<b>B</b>) <b>1</b> and (<b>E</b>) <b>3</b> with TYR. The details of binding modes of (<b>C</b>) <b>1</b> and (<b>F</b>) <b>3</b> with TYR. The backbone of protein was rendered in a tube and colored green. Yellow and gray dash lines represent the hydrogen bond and π-stacking, respectively.</p>
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<p>Toxicity of compound <b>1</b>–<b>3</b> against B16 cells. Kojic acid was used as a positive control. Data (cell viability) are expressed as means ± SD (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and **** <span class="html-italic">p</span> &lt; 0.0001 compared with the model group).</p>
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<p>Intracellular TYR inhibition activity of compounds <b>1–3</b> at different concentrations. Data (relative activity) are expressed as means ± SD (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001 compared with the model group).</p>
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<p>Intracellular melanin reduction activity of compounds <b>1–3</b> at different concentrations. Data (melanin content) are expressed as means ± SD (**** <span class="html-italic">p</span> &lt; 0.0001 compared with the model group).</p>
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