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20 pages, 2311 KiB  
Article
Effect of Adaptation to High Concentrations of Cadmium on Soil Phytoremediation Potential of the Middle European Ecotype of a Cosmopolitan Cadmium Hyperaccumulator Solanum nigrum L.
by Ewa Miszczak, Sebastian Stefaniak, Danuta Cembrowska-Lech, Lidia Skuza and Irena Twardowska
Appl. Sci. 2024, 14(24), 11808; https://doi.org/10.3390/app142411808 - 17 Dec 2024
Viewed by 236
Abstract
The Cd hyperaccumulator Solanum nigrum L. exhibits a cosmopolitan character and proven high and differentiated efficiency. This suggests the possibility of optimizing its Cd phytoremediation capacity and applicability through searching among remote ecotypes/genotypes. However, the extensive studies on this hyperaccumulator have been limited [...] Read more.
The Cd hyperaccumulator Solanum nigrum L. exhibits a cosmopolitan character and proven high and differentiated efficiency. This suggests the possibility of optimizing its Cd phytoremediation capacity and applicability through searching among remote ecotypes/genotypes. However, the extensive studies on this hyperaccumulator have been limited to Far East (Asian) regions. Pioneer pot experiments on the Middle European ecotype of S. nigrum within a concentration range of 0–50 mg kg−1 Cd in soil revealed its Cd phytoremediation capacity to be comparable to Asian ecotypes but with a fundamentally different Cd tolerance threshold. While biomass of the Asian ecotypes declined sharply at Csoil ≈ 10 mg kg−1 Cd, in the Middle European ecotype, a gradual mild biomass decrease occurred within the whole Csoil ≈ 0–50 mg kg−1 Cd range with no toxic symptoms. Its adapted A50 variety was obtained from the seeds of first-generation plants grown in soil with Csoil ≈ 50 mg kg−1 Cd. In this variety, Cd tolerance, accumulation performance, and all physiological parameters (chlorophyll, carotenoids, RuBisCO, and first- and second-line defense anti-oxidant activity) were significantly enhanced, while cell damage by ROS was considerably lesser. This makes the Middle European ecotype and its adapted variety A50 particularly useful to sustainable decontamination of heavily polluted “hot spots” in degraded post-industrial areas. Full article
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<p>Effects of different Cd treatments on (<b>a</b>) chlorophyll <span class="html-italic">a</span>, (<b>b</b>) chlorophyll <span class="html-italic">b,</span> (<b>c</b>) carotenoids content in the non-adapted N0 and adapted A50 varieties of <span class="html-italic">S. nigrum</span> L. (1) 0 to 50 means control and soil treatments with Cd (mg kg<sup>−1</sup>); (2) Data for the same treatments marked by the same capital letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05. Data for different treatments marked by the same lowercase letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of different Cd treatments on (<b>a</b>) RbcL and (<b>b</b>) RbcS content in the non-adapted N0 and adapted A50 varieties of <span class="html-italic">S. nigrum</span> L. (1) 0 to 50 means control and soil treatments with Cd (mg kg<sup>−1</sup>); (2) Data for the same treatments marked by the same capital letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05. Data for different treatments marked by the same lowercase letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of different Cd treatments on ROS contents: (<b>a</b>) superoxide anion and (<b>b</b>) hydrogen peroxide in in non-adapted N0 and adapted A50 varieties of <span class="html-italic">S. nigrum</span> L. (1) 0 to 50 means control and soil treatments with Cd (mg kg<sup>−1</sup>); (2) Data for the same treatments marked by the same capital letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05. Data for different treatments marked by the same lowercase letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Response of the first-line defense antioxidant (<b>a</b>) CAT, (<b>b</b>) SOD and (<b>c</b>) GPX) activity in the leaves of non-adapted N0 and adapted A50 varieties of <span class="html-italic">S. nigrum</span> to the growing Cd stress. (1) 0 to 50 means control and soil treatments with Cd (mg kg<sup>−1</sup>); (2) Data for the same treatments marked by the same capital letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05. Data for different treatments marked by the same lowercase letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Response of SOD isozyme (<b>a</b>) Cu/ZnSOD, (<b>b</b>) MnSOD (<b>c</b>) FeSOD activities in the leaves of non-adapted N0 and adapted A50 varieties of <span class="html-italic">S. nigrum</span> to the growing Cd stress. (1) 0 to 50 means control and soil treatments with Cd (mg kg<sup>−1</sup>); (2) Data for the same treatments marked by the same capital letters are not significantly different at <span class="html-italic">p</span> &lt; 0.05. Data for different treatments marked by the same lowercase letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Response of the second-line defense antioxidants ascorbate: (<b>a</b>) APX, (<b>b</b>) AsA and glutathione compounds: (<b>c</b>) GR, (<b>d</b>) GSH, (<b>e</b>) GSSG activity and (<b>f</b>) MDA content in the leaves of non-adapted N0 and adapted A50 varieties of <span class="html-italic">S. nigrum</span> L. to the growing Cd stress. (1) 0 to 50 means control and soil treatments with Cd (mg kg<sup>−1</sup>); (2) Data for the same treatments marked by the same capital letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05. Data for different treatments marked by the same lowercase letters over bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05.</p>
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18 pages, 9603 KiB  
Article
High Carbonyl Graphene Oxide Suppresses Colorectal Cancer Cell Proliferation and Migration by Inducing Ferroptosis via the System Xc−/GSH/GPX4 Axis
by Xiecheng Zhou, Qixing Zhang, Haoran Zhu, Guangxiong Ouyang, Xin Wang and Yuankun Cai
Pharmaceutics 2024, 16(12), 1605; https://doi.org/10.3390/pharmaceutics16121605 - 17 Dec 2024
Viewed by 333
Abstract
Background/Objectives: Colorectal cancer (CRC) is characterized by a high rate of both incidence and mortality, and its treatment outcomes are often affected by recurrence and drug resistance. Ferroptosis, an iron-dependent programmed cell death mechanism triggered by lipid peroxidation, has recently gained attention as [...] Read more.
Background/Objectives: Colorectal cancer (CRC) is characterized by a high rate of both incidence and mortality, and its treatment outcomes are often affected by recurrence and drug resistance. Ferroptosis, an iron-dependent programmed cell death mechanism triggered by lipid peroxidation, has recently gained attention as a potential therapeutic target. Graphene oxide (GO), known for its oxygen-containing functional groups, biocompatibility, and potential for functionalization, holds promise in cancer treatment. However, its role in ferroptosis induction in CRC remains underexplored. The objective of this study was to investigate the effects of High Carbonyl Graphene Oxide (HC-GO) on ferroptosis in CRC and elucidate the underlying mechanisms. Methods: In vitro assays were conducted to evaluate the impact of HC-GO on CRC cell proliferation, mitochondrial function, iron accumulation, lipid peroxidation, and reactive oxygen species (ROS) production. The ferroptosis inhibitor Fer-1 was used to confirm the role of ferroptosis in HC-GO’s anti-tumor effects. In vivo, the anti-tumor activity of HC-GO was assessed in a CRC xenograft model, with organ toxicity evaluated. Results: HC-GO significantly inhibited CRC cell proliferation, induced mitochondrial damage, and enhanced iron accumulation, lipid peroxidation, and ROS production. It also downregulated the ferroptosis-inhibiting proteins GPX4 and SLC7A11, which were reversed by Fer-1, confirming the involvement of ferroptosis in HC-GO’s anti-cancer effects. In vivo, HC-GO significantly suppressed tumor growth without noticeable toxicity to vital organs. Conclusions: HC-GO triggered ferroptosis in CRC cells by suppressing the System Xc−/GSH/GPX4 pathway, providing a novel therapeutic strategy for CRC treatment. These findings suggest HC-GO as a promising nanomedicine for clinical application, warranting further investigation to explore its potential in CRC therapy. Full article
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<p>Characterization of HC-GO. (<b>A</b>) Scanning electron microscope images of HC-GO, scale bar: 2 μm, 10 μm; (<b>B</b>) AFM topography image and the corresponding height distribution graph of HC-GO, scale bar: 2 μm; (<b>C</b>) Raman spectra results of HC-GO; (<b>D</b>) XPS results comparing regular GO and HC-GO.</p>
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<p>HC-GO significantly inhibited the in vitro proliferation and migration of HCT116 and HCT15 cells. (<b>A</b>,<b>B</b>) Colony formation assays were used to analyze cell proliferation. (<b>C</b>,<b>D</b>) CCK-8 assays were conducted to assess cell proliferation. (<b>E</b>,<b>F</b>) Scratch wound healing assays were employed to analyze cell migration. (<b>G</b>,<b>H</b>) Transwell assays were performed to measure cell migration capacity. Scale bar: 100 μm. (<b>I</b>,<b>J</b>) Western blot (WB) analysis was used to assess the expression levels of stemness proteins. Data are presented as mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 compared with the control group. All experiments were independently repeated at least three times.</p>
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<p>HC-GO induced ferroptosis in HCT116 and HCT15 cells in vitro. (<b>A</b>) Analysis of Fe<sup>2+</sup> levels. (<b>B</b>,<b>C</b>) Analysis of intracellular ROS levels. (<b>D</b>,<b>E</b>) Analysis of lipid ROS levels. (<b>F</b>) Analysis of GSH levels. (<b>G</b>,<b>H</b>) Western blot analysis of ferroptosis-related protein expression levels. (<b>I</b>) Transmission electron microscopy images of HCT116 cells: blue arrows indicate damaged mitochondria, red arrows indicate mitochondria with vacuolization, and yellow circles highlight structural damage in mitochondria (increased membrane density, reduced cristae, and mitochondrial shrinkage). Scale bars: 1 μm, 2 μm, 500 nm. Data are presented as mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 compared with the control group. All experiments were independently repeated at least three times.</p>
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<p>HC-GO inhibited CRC cells in vivo. (<b>A</b>,<b>B</b>) Tumor appearance; (<b>C</b>,<b>D</b>) Tumor volume and weight. Data are presented as mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01 compared with the control group.</p>
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<p>HC-GO induced ferroptosis in vivo. (<b>A</b>) HE staining used to assess morphological differences in tumor tissues. Scale bar: 200 μm. (<b>B</b>,<b>C</b>) Immunohistochemical staining for GPX4 and SLC7A11. Scale bar: 200 μm. (<b>D</b>) HE staining used to assess the morphology of mouse heart, liver, spleen, lung, and kidney tissues. Scale bar: 200 μm. Data are presented as mean ± SD. **** <span class="html-italic">p</span> &lt; 0.0001compared with the control group.</p>
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<p>Ferroptosis inhibitor Fer-1 blocked HC-GO-induced ferroptosis in HCT116 cells. The concentration of Fer-1 was 10 μM [<a href="#B39-pharmaceutics-16-01605" class="html-bibr">39</a>]. (<b>A</b>) CCK-8 assay used to analyze cell proliferation; (<b>B</b>,<b>C</b>) Colony formation assay used to analyze cell proliferation; (<b>D</b>,<b>E</b>) Fer-1 blocks the increase in intracellular ROS levels induced by HC-GO; (<b>F</b>,<b>G</b>) Fer-1 blocks the increase in intracellular lipid ROS levels induced by HC-GO; (<b>H</b>) Fer-1 blocks the increase in GSH levels induced by HC-GO; (<b>I</b>,<b>J</b>) Western blot (WB) results show that Fer-1 blocks the decrease in GPX4 and SLC7A11 expression induced by HC-GO; (<b>K</b>,<b>L</b>) Immunofluorescence shows that Fer-1 blocks the decrease in GPX4 expression induced by HC-GO; (<b>M</b>,<b>N</b>) Immunofluorescence shows that Fer-1 blocks the decrease in SLC7A11 expression induced by HC-GO. Scale bar: 50 μm. Data are presented as mean ± SD. <sup>ns</sup> <span class="html-italic">p</span> &gt; 0.05, * <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, **** <span class="html-italic">p</span> &lt; 0.0001compared with the control group/ HC-GO. All experiments were independently repeated at least three times.</p>
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19 pages, 3246 KiB  
Article
Physiological Evaluation of Salt Tolerance in Sunflower Seedlings Across Different Genotypes
by Fangyuan Chen, Lvting Xiao, Qixiu Huang, Lijun Xiang, Qiang Li, Xianfei Hou, Zhonghua Lei and Youling Zeng
Agronomy 2024, 14(12), 2995; https://doi.org/10.3390/agronomy14122995 - 16 Dec 2024
Viewed by 284
Abstract
Sunflower (Helianthus annuus L.) is an important oilseed crop cultivated extensively across the globe. High salinity adversely impacts plant growth and physiological processes. In this study, the data on the phenotypes, physiological indices, and expression of relevant genes from different pathways responding [...] Read more.
Sunflower (Helianthus annuus L.) is an important oilseed crop cultivated extensively across the globe. High salinity adversely impacts plant growth and physiological processes. In this study, the data on the phenotypes, physiological indices, and expression of relevant genes from different pathways responding to the stress were collected to clarify the physiological mechanisms underlying sunflower’s salt tolerance with the seedlings of two salt-tolerant (182265 and 182283) and two salt-sensitive (182093 and 186096) genotypes, which were exposed to 350 mM NaCl for 5 days. The findings revealed that, during the seedling stage, salt-tolerant sunflowers accumulated less Na+ and more K+, resulting in a higher K+/Na+ ratio that mitigated ionic toxicity throughout the plants, compared to the salt-sensitive resources. Furthermore, the salt-tolerant germplasms also exerted salt tolerance through the following several pathways: they maintained robust osmotic regulation by accumulating higher levels of proline, soluble sugars, and other osmolytes; they neutralized reactive oxygen species (ROS) by elevating the activity of antioxidant enzymes such as POD, SOD, CAT, APX, and GR; and they sustained optimal growth by boosting photosynthesis. Taken together, this study provided a more comprehensive assessment of the sunflower’s physiological salt tolerance, providing insights that will inform further molecular studies on salt tolerance and accelerating the breeding process for sunflower varieties with improved salt resilience. Full article
(This article belongs to the Section Crop Breeding and Genetics)
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<p>Morphological phenotypes of four sunflower germplasms under salt stress. Ten-day-old seedlings of the genotypes 182265, 182283, 182093, and 186096 were subjected to a 350 mM NaCl stress for a period of five days. A parallel set of seedlings were treated with distilled water as controls. (<b>A</b>) The above-ground phenotype; (<b>B</b>) root contour; (<b>C</b>) total root length. The scale bars were marked at 10 cm. Significant differences between the control and salt-stressed seedlings of the same germplasm were denoted by asterisks, as determined by Duncan’s multiple range test following a post hoc analysis. (** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Comparative analysis of photosynthetic characteristics and leaf anatomical structures between salt-tolerant and salt-sensitive sunflower genotypes under salt stress. (<b>A</b>) Chlorophyll content; (<b>B</b>) Photosynthetic rate; (<b>C</b>) Stomatal conductance; (<b>D</b>) Water use efficiency. (<b>E</b>) Microscopic views of the leaf anatomical structures of genotypes 182265 and 182093. The images were captured at an original magnification of 100×. The anatomical features were labeled as follows: Ue, upper epidermis; le, lower epidermis; pt, palisade tissue; st, spongy tissue; pt and st were collectively classified as parenchyma. vt, vascular tissue. The arrows indicated the location of the vascular tissue. Significant differences (<span class="html-italic">p</span> &lt; 0.05) among all the samples of the four sunflower germplasms under both control and salt treatment were denoted by different letters.</p>
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<p>Comparative cell membrane damage in salt-tolerant and salt-sensitive sunflower germplasms under salt stress. (<b>A</b>–<b>C</b>) Histochemical staining for cellular damage using DAB, NBT, and Evans blue in the leaves, respectively. (<b>D</b>–<b>K</b>) Quantitative analysis of MDA, H<sub>2</sub>O<sub>2</sub>, and O<sub>2</sub><sup>−</sup> contents, and electrolyte leakage rate in the leaves and roots of four sunflower germplasms. The scale bars represented 5 cm. Different letters denoted significant differences among all the samples of the germplasms in control and treatment with 350 mM NaCl for 5 days (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Antioxidant enzyme activities in salt-tolerant and salt-sensitive sunflower germplasms. (<b>A</b>–<b>L</b>) The activities of SOD, POD, CAT, APX, GR, and the T-AOC in both leaves and roots. Data were presented as the mean of three biological replicates. Different letters indicated significant differences among all the samples of the four germplasms in control and treatment with 350 mM NaCl for 5 days (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Comparison of the accumulation of various compatible osmolytes in leaves and roots of salt-tolerant and salt-sensitive sunflower germplasms. The contents of proline (<b>A</b>,<b>B</b>), soluble sugars (<b>C</b>,<b>D</b>), and soluble proteins (<b>E</b>,<b>F</b>) in the leaves and roots were shown. The data represented the average of three biological replicates. Different letters indicated significant differences among all samples of the four germplasms under control condition and treatment with 350 mM NaCl for 5 days (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Assessment of ionic homeostasis in salt-tolerant and salt-sensitive sunflower genotypes under salt stress. The figure depicted comparative levels of Na<sup>+</sup> (<b>A</b>,<b>B</b>), K<sup>+</sup> (<b>C</b>,<b>D</b>), and the ratios of Na<sup>+</sup>/K<sup>+</sup> (<b>E</b>,<b>F</b>) in leaves and roots of the respective sunflower genotypes. Distinct asterisks denoted statistically significant differences between control and salt-stressed conditions for each germplasm, as determined by post hoc Duncan’s multiple comparisons tests (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Expression analysis of various genes related to osmotic regulation, ROS clearance, ion transporter and stress response in salt-tolerant and salt-sensitive sunflower genotypes 182265 and 182093 under salt stress. The expression levels of the osmotic regulation gene <span class="html-italic">HaP5CS</span> (<b>A</b>,<b>B</b>), antioxidant enzyme genes <span class="html-italic">HaPOD2</span> and <span class="html-italic">HaCAT1</span> (<b>C</b>–<b>F</b>), plasma membrane Na<sup>+</sup>/H<sup>+</sup> antiporter genes <span class="html-italic">HaSOS1</span>, <span class="html-italic">HaSOS2</span>, and <span class="html-italic">HaSOS3</span> (<b>G</b>–<b>L</b>), vacuolar membrane Na<sup>+</sup>/H<sup>+</sup> antiporter genes <span class="html-italic">HaNHX1</span> and <span class="html-italic">HaNHX2</span> (<b>M</b>–<b>P</b>), stress-responsive gene <span class="html-italic">HaRD29A</span> (<b>Q</b>,<b>R</b>), and the ABA synthesis key enzyme gene <span class="html-italic">HaNCED3</span> (<b>S</b>,<b>T</b>) in leaves and roots of genotypes 182265 and 182093 were depicted. Asterisks (*) denoted significant differences between control and salt treatment within the same germplasm (* <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, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Principal Component Analysis was performed to assess the physiological state and the response of different genotypes to salt stress, utilizing data from a range of physiological indices. (<b>A</b>) PCA of physiological indices under salt stress. (<b>B</b>) PCA of the different genotypes. SP: Soluble protein; SS: Soluble sugar; Pro: Proline; K: K<sup>+</sup>; Na: Na<sup>+</sup>; NaK: Na<sup>+</sup>/K<sup>+</sup>; APX: APX activity; CAT: CAT activity; GR: GR activity; POD: POD activity; SOD: SOD activity; AOC: T-AOC; O: O<sub>2</sub><sup>−</sup> content; EL: Electrolyte leakage; H<sub>2</sub>O<sub>2</sub>: H<sub>2</sub>O<sub>2</sub> content; T186096, T182093, T182283, and T182265: genotypes in the 350 mM NaCl treatment group. 186096, 182093, 182283, and 182265: genotypes in the control group. R: the root; L: the leaf.</p>
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22 pages, 7159 KiB  
Article
Sucrose Promotes the Proliferation and Differentiation of Callus by Regulating ROS Intensity in Agapanthus praecox
by Jianhua Yue, Yan Dong, Changmei Du, Chaoxin Li, Xinyi Wang and Yan Zhang
Horticulturae 2024, 10(12), 1350; https://doi.org/10.3390/horticulturae10121350 - 16 Dec 2024
Viewed by 303
Abstract
The proliferation and differentiation of callus is the foundation for plant regeneration and propagation. The type of carbon sources in the medium significantly influences the efficacy of callus proliferation and differentiation in plants in vitro. Our study performed transcriptomic and physiological analyses utilizing [...] Read more.
The proliferation and differentiation of callus is the foundation for plant regeneration and propagation. The type of carbon sources in the medium significantly influences the efficacy of callus proliferation and differentiation in plants in vitro. Our study performed transcriptomic and physiological analyses utilizing sucrose, glucose, and maltose to understand the physiological and molecular characteristics of the proliferation and differentiation potential affected by carbon sources in Agapanthus praecox. Differentially expressed genes were notably associated with plant hormone signal transduction, glycolysis/gluconeogenesis, and MAPK signaling in the proliferation and differentiation of callus. The physiological indicators suggest glucose enhanced both callus and cell size by increasing endogenous indole-3-acetic acid (IAA), cytokinin, brassinosteroid, gibberellin (GAs), starch, and glucose levels, while concurrently reducing levels of reactive oxygen species (ROS) such as hydrogen peroxide (H2O2) and hydroxyl radical (·OH). Conversely, sucrose treatment promoted differentiation potential by elevating IAA oxidase activity alongside stress-related hormones such as abscisic acid and ethylene levels. Additionally, sucrose treatment led to increased accumulation of sucrose, fructose, H2O2, and ·OH within the callus tissue. Furthermore, sucrose influenced the regenerative capacity by modulating glycometabolism and osmoregulation. Our study posits that glucose facilitates callus proliferation via diminished ROS intensity while sucrose promotes callus differentiation by maintaining moderate ROS levels. Altogether, our results suggest carbon sources affected the regenerative capabilities of callus by regulating plant hormone signal and ROS intensity in A. praecox. Full article
(This article belongs to the Special Issue Plant Tissue and Organ Cultures for Crop Improvement in Omics Era)
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<p>Morphological and transcriptomic differences of callus cultured by sucrose, glucose, and maltose. (<b>A</b>) Morphology of samples including callus cultured by sucrose, glucose, and maltose; the bar represents 1.0 cm. The white arrow indicates an adventitious bud and a hairy root. (<b>B</b>) Cell micromorphology of callus, bar = 100 μm. (<b>C</b>) Correlation analysis among samples; the horizontal axis represents the sample clusters, and colors from blue to red indicate the correlation index from low to high. (<b>D</b>) Venn diagram of DEGs among three compared pairs, including Suc/Mal, Suc/Glu, and Glu/Mal. The red arrows indicate upregulation, and the green arrows indicate downregulation. (<b>E</b>) KEGG pathway enrichment of the comparison of Suc/Glu. The bubble size represents the number of members detected in the KEGG pathway, and the color of the bubble represents the <span class="html-italic">p</span>-value, the same as below. (<b>F</b>) KEGG pathway enrichment of the comparison of Suc/Mal. (<b>G</b>) KEGG pathway enrichment of the comparison of Glu/Mal.</p>
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<p>Hierarchical clustering analyses of DEGs among samples of sucrose, glucose, maltose, and IEC. (<b>A</b>) Hierarchical clustering analyses of DEGs between samples including Suc, Glu, Mal, and IEC. (<b>B</b>) Hierarchical clustering analyses of DEGs in subcluster 1. (<b>C</b>) Hierarchical clustering analyses of DEGs in subcluster 2. (<b>D</b>) Hierarchical clustering analyses of DEGs in subcluster 3. (<b>E</b>) Hierarchical clustering analyses of DEGs in subcluster 4.</p>
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<p>Differential analyses of plant hormone signal transduction and metabolism. (<b>A</b>) Analyses of the contents and enzymatic activity of plant hormones. The data are means, <span class="html-italic">n</span> = 3. Means marked by the same letter in the column are not significantly different according to Duncan’s multiple range test at <span class="html-italic">p</span> &lt; 0.05. Table marked in red, yellow, and green indicating high, middle, and low values with different carbon source treatments. (<b>B</b>) DEGs with higher expression levels with sucrose. (<b>C</b>) DEGs with lower expression levels with sucrose. (<b>D</b>) Hierarchical clustering analyses of DEGs. (<b>E</b>) Size of callus treated by PIC, <span class="html-italic">n</span> = 3. Means marked by the same letter on the bar are not significantly different according to Duncan’s multiple range test at <span class="html-italic">p</span> &lt; 0.05, and the same hereinafter. (<b>F</b>) Size of callus treated by GA<sub>4</sub>. (<b>G</b>) Size of callus treated by homobrassinolide (HBL). (<b>H</b>) Size of callus treated by ABA. Abbreviations: BIN2: brassinosteroid insensitive2; TGA: TGACG binding TFs; IAA: auxin/indole-3-acetic acid; PP2C: type 2C protein phosphatases; JAZ: jasmonate ZIM domain protein; SAUR: small auxin-up RNA; ARR-A: type-A authentic response regulator; ARR-B: type-B authentic response regulator; NPR1: nonexpressor of pathogenesis-related genes 1; BZR1_2: brassinosteroid-resistant 1/2; AHP: histidine-containing phosphotransfer protein; PIF3: phytochrome-interacting factor 3; SNRK2: sucrose nonfermenting 1-related protein kinase 2; EIN3: ethylene-insensitive protein 3; TIR1: transport inhibitor response 1; TCH4: xyloglucan: xyloglucosyl transferase TOUCH4; BSK: BR-signaling kinase; PIF4: phytochrome-interacting factor 4; GH3: Gretchen Hagen 3; AHK2_3_4: Arabidopsis histidine kinase 2/3/4 (cytokinin receptor); PR1: pathogenesis-related protein 1; DELLA: DELLA transcriptional regulatory proteins; ABF: ABA responsive element binding factor; CTR1: constitutive triple response1; AUX1, LAX: auxin influx carrier (AUX1/LAX family); ARF: auxin response factor; CYCD3: cyclin D3; PYL: pyrabactin resistance 1-like protein; GID1: gibberellin insensitive dwarf1; MPK6: mitogen-activated protein kinase 6; BRI1: brassinosteroid insensitive 1.</p>
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<p>Differential analyses of starch and sucrose metabolism. (<b>A</b>) Analyses of the contents of starch and soluble sugars. The data are means, <span class="html-italic">n</span> = 3. Means marked by the same letter in the column are not significantly different according to Duncan’s multiple range test at <span class="html-italic">p</span> &lt; 0.05. Table marked in red, yellow, and green indicates high, middle, and low values with different carbon source treatments. (<b>B</b>) DEGs with higher expression levels in Suc/Glu and Suc/Mal. (<b>C</b>) DEGs with lower expression levels in Suc/Glu and higher expression levels in Glu/Mal. (<b>D</b>) DEGs with lower expression levels in Suc/Glu and higher expression levels in Glu/Mal. (<b>E</b>) Hierarchical clustering analyses of DEGs involved in starch and sucrose metabolism. (<b>F</b>) DEGs with lower expression levels in Suc/Glu and Suc/Mal. (<b>G</b>) Size of callus treated by different concentrations of sucrose, <span class="html-italic">n</span> = 3. Means marked by the same letter on the bar are not significantly different according to Duncan’s multiple range test at <span class="html-italic">p</span> &lt; 0.05, and the same hereinafter. (<b>H</b>) Size of callus treated by the combination of sucrose and glucose. (<b>I</b>) Size of callus treated by the combination of sucrose and fructose. (<b>J</b>) Size of callus treated by the combination of sucrose and maltose. Abbreviations: GBE1, glgB: 1,4-alpha-glucan branching enzyme; SUS: sucrose synthase; glgC: glucose-1-phosphate adenylyltransferase; INV, sacA: beta-fructofuranosidase; PYG, glgP: glycogen phosphorylase; scrK: fructokinase; malZ: alpha-glucosidase; TREH, treA, treF: alpha-trehalase; TPS: trehalose 6-phosphate synthase/phosphatase; ISA, treX: isoamylase; otsB: trehalose 6-phosphate phosphatase; GPl, pgi: glucose-6-phosphate isomerase; ENPP1_3, CD203: ectonucleotide pyrophosphatase/phosphodiesterase family member 1/3; malQ: 4-alpha-glucanotransferase; UGP2, galU, galF: UTP--glucose-1-phosphate uridylyltransferase; SPP: sucrose-6-phosphatase; HK: hexokinase; NV, sacA: beta-fructofuranosidase; TREH, treA, treF: alpha,alpha-trehalase.</p>
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<p>Differential analyses of MAPK signaling pathway. (<b>A</b>) Analyses of the contents and enzymatic activity involved in ROS metabolism. The data are means, <span class="html-italic">n</span> = 3. Means marked by the same letter in the column are not significantly different according to Duncan’s multiple range test at <span class="html-italic">p</span> &lt; 0.05. Table marked in red, yellow, and green indicates high, middle, and low values with different carbon source treatments. (<b>B</b>) DEGs with higher expression levels in Suc/Glu and Suc/Mal. (<b>C</b>) DEGs with higher expression levels in Suc/Glu and lower expression levels in Glu/Mal. (<b>D</b>) DEGs with lower expression levels in Suc/Glu and higher expression levels in Glu/Mal. (<b>E</b>) DEGs with lower expression levels in Suc/Glu and Suc/Mal. (<b>F</b>) Size of callus treated by H<sub>2</sub>O<sub>2</sub>, <span class="html-italic">n</span> = 3. Means marked by the same letter on the bar are not significantly different according to Duncan’s multiple range test at <span class="html-italic">p</span> &lt; 0.05, and the same hereinafter. (<b>G</b>) Size of callus treated by 2, 4-D. (<b>H</b>) Size of callus treated by PEG 6000. (<b>I</b>) Size of callus treated by Ac-DEVD-CHO (CHO) and carbonyl cyanide m-chlorophenylhydrazone (CCCP). Abbreviations: MAPK7: mitogen-activated protein kinase 7; RBOH: respiratory burst oxidase; IRAK1: interleukin-1 receptor-associated kinase 1; CALM: calmodulin; WRKY33: WRKY DNA-binding protein 33; CTSL: cathepsin L; IDH1, IDH2, icd: isocitrate dehydrogenase; CYC: cytochrome c; PR1: pathogenesis-related protein 1; ACsL, fadD: long-chain acyl-CoA synthetase; CTSH: cathepsin H; PEX12, PAF3: peroxin-12; HAO: (S)-2-hydroxy-acid oxidase; VIP1: transcription factor VIP1; ACAA1: acetyl-CoA acyltransferase 1; PXMP2, PMP22: peroxisomal membrane protein 2; PEX10: peroxin-10; FLS2: LRR receptor-like serine/threonine-protein kinase FLS2; EIN3: ethylene-insensitive protein 3; FBXL2_20: F-box and leucine-rich repeat protein 2/20; PP2C: type 2C protein phosphatases; PYL: abscisic acid receptor PYR/PYL family; NRK2: sucrose nonfermenting 1-related protein kinase 2; ANP1: mannan polymerase II complex ANP1 subunit; copA, ATP7: P-type Cu+ transporter; katE, CAT, catB, srpA: catalase; MKK9: mitogen-activated protein kinase kinase 9; PARP: poly (ADP-ribose) polymerases; ATF4, CREB2: cyclic AMP-dependent transcription factor ATF-4; EIF2S1: translation initiation factor 2 subunit 1.</p>
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<p>Analyses of the effects of carbon source combination on the proliferation and differentiation of callus. (<b>A</b>) Morphological differences of callus treated by the combination of sucrose and the hydrolysate of sucrose (glucose and fructose). The bars in the morphology and micromorphology represent 1.0 cm and 100 μm, respectively, and the same hereinafter. (<b>B</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of sucrose and hydrolysate of sucrose. Data on the bars marked without the same lowercase letter indicate significant differences at <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 3, and the same hereinafter. (<b>C</b>) Morphological differences of callus treated by the combination of sucrose and glucose. (<b>D</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of sucrose and glucose. (<b>E</b>) Morphological differences of callus treated by the combination of sucrose and fructose. (<b>F</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of sucrose and fructose. (<b>G</b>) Morphological differences of callus treated by the combination of hydrolysate of sucrose and glucose. (<b>H</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of hydrolysate of sucrose and glucose. (<b>I</b>) Morphological differences of callus treated by the combination of hydrolysate of sucrose and fructose. (<b>J</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of hydrolysate of sucrose and fructose. (<b>K</b>) Morphological differences of callus treated by the combination of hydrolysate of sucrose and maltose. (<b>L</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of hydrolysate of sucrose and maltose.</p>
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<p>Analyses of the effects of osmotic regulatory substance (ORS) on the proliferation and differentiation of callus. (<b>A</b>) Morphological differences of callus treated by the combination of sucrose and PEG. The bars in the morphology and micromorphology represent 1.0 cm and 100 μm, respectively, and the same hereinafter. (<b>B</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of sucrose and PEG. Data on the bars marked without the same lowercase letter indicate significant differences at <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 3, and the same hereinafter. (<b>C</b>) Morphological differences of callus treated by the combination of glucose and PEG. (<b>D</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of glucose and PEG. (<b>E</b>) Morphological differences of callus treated by the combination of fructose and PEG. (<b>F</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of fructose and PEG. (<b>G</b>) Morphological differences of callus treated by the combination of glucose, fructose, and PEG. (<b>H</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of glucose, fructose, and PEG. (<b>I</b>) Morphological differences of callus treated by the combination of sucrose, glucose, and PEG. (<b>J</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of sucrose, glucose, and PEG. (<b>K</b>) Morphological differences of callus treated by the combination of sucrose, fructose, and PEG. (<b>L</b>) Size of callus (left Y-axis) and single cell (right Y-axis) treated by the combination of sucrose, fructose, and PEG.</p>
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<p>Hypothesized model diagram of the acquisition of regenerative potential induced by carbon sources in <span class="html-italic">A. praecox</span>. (<b>A</b>) Carbon sources affected the proliferation and differentiation of callus, and the intensity of ROS determined the cell fate of callus. (<b>B</b>) Schematic diagram about the influence of carbon sources on hormone metabolism, sugar content, ROS, and protective enzymes. Since maltose treatment usually results in moderate levels of physiological indicators, maltose is used as a control. The short horizontal line indicate control, the red arrows indicate a significant increase, and the green arrows a indicate significant decrease.</p>
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20 pages, 2978 KiB  
Article
Response of Arabidopsis thaliana to Flooding with Physical Flow
by Momoko Kaji, Kazuma Katano, Taufika Islam Anee, Hiroshi Nitta, Ryotaro Yamaji, Rio Shimizu, Shunsuke Shigaki, Hiroyuki Suzuki and Nobuhiro Suzuki
Plants 2024, 13(24), 3508; https://doi.org/10.3390/plants13243508 - 16 Dec 2024
Viewed by 302
Abstract
Flooding causes severe yield losses worldwide, making it urgent to enhance crop tolerance to this stress. Since natural flooding often involves physical flow, we hypothesized that the effects of submergence on plants could change when combined with physical flow. In this study, we [...] Read more.
Flooding causes severe yield losses worldwide, making it urgent to enhance crop tolerance to this stress. Since natural flooding often involves physical flow, we hypothesized that the effects of submergence on plants could change when combined with physical flow. In this study, we analyzed the growth and transcriptome of Arabidopsis thaliana exposed to submergence or flooding with physical flow. Plants exposed to flooding with physical flow had smaller rosette diameters, especially at faster flow rates. Transcriptome analysis revealed that “defense response” transcripts were highly up-regulated in response to flooding with physical flow. In addition, up-regulation of transcripts encoding ROS-producing enzymes, SA synthesis, JA synthesis, and ethylene signaling was more pronounced under flooding with physical flow when compared to submergence. Although H2O2 accumulation changed in response to submergence or flooding with physical flow, it did not lead to lipid peroxidation, suggesting a role for ROS as signaling molecules under these conditions. Multiple regression analysis indicated possible links between rosette diameter under flooding with physical flow and the expression of Rbohs and SA synthesis transcripts. These findings suggest that pathogen defense responses, regulated by SA and ROS signaling, play crucial roles in plant responses to flooding with physical flow. Full article
(This article belongs to the Special Issue Deciphering Plant Molecular Data Using Computational Methods)
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<p>Schematic design of the channel to treat plants with flooding. (<b>A</b>) Top view, (<b>B</b>) side view.</p>
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<p>Growth characteristics of plants subjected to submergence or flooding with physical flow. (<b>A</b>) Number of leaves, (<b>B</b>) plant diameter and (<b>C</b>) inflorescent length. Error bars indicate standard deviation (<span class="html-italic">n</span> = 9–10). * and **: Student’s <span class="html-italic">t</span>-test significantly different at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01, respectively (compared to control).</p>
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<p>Characteristics of transcripts up-regulated in response to flooding with physical flow. (<b>A</b>) Venn diagram showing the overlap between transcripts up-regulated in response to submergence or flooding with physical flow. (<b>B</b>,<b>C</b>) Gene Ontology (GO) terms of “biological processes” represented in transcripts specifically up-regulated in response to submergence (<b>B</b>) or flooding with physical flow (<b>C</b>).</p>
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<p>Involvement of pathogen defense pathways in response of plants to flooding with physical flow. (<b>A</b>) Fold change of transcripts belong to Gene Ontologies (GOs) that are highly represented in the transcripts specifically up-regulated in response to flooding with physical flow. (<b>B</b>) Proportion of hormone response transcripts among the transcripts specifically up-regulated in response to submergence or flooding with physical flow. ABA: abscisic acid, ACC: 1-aminocyclopropane-1-carboxylate, BL: brassinosteroids, CK: Cytokinin, GA: gibberellic acid, IAA: indole-3-acetic acid, MJ: methyl jasmonate, SA: salicylic acid.</p>
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<p>FPKM of transcripts involved in Salicylic acid (SA) synthesis (<b>A</b>), Jasmonic acid (JA) synthesis (<b>B</b>) or ROS production (<b>C</b>). Values relative to control are indicated. Error bars indicate standard deviation (<span class="html-italic">n</span> = 3). * and **: Student’s <span class="html-italic">t</span>-test significantly different at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01, respectively (compared to control).</p>
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<p>FPKM of transcripts encoding ERFs. Values relative to control are indicated. Error bars indicate standard deviation (<span class="html-italic">n</span> = 3). Transcripts were categorized into three groups; Sub: significantly up-regulated specifically in response to submergence, Flood: significantly up-regulated specifically in response to flooding with physical flow, Sub and Flood: significantly up-regulated in response to both stresses.</p>
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<p>Multiple regression analysis of transcripts involved in ROS production ((<b>A</b>) <span class="html-italic">Rboh</span>s), SA (salicylic acid) synthesis (<b>B</b>) and AU (auxin) signaling (<b>C</b>). Circles indicate the transcript that showed the highest contribution to the determination of rosette diameter under flooding with physical flow. In this figure, the <span class="html-italic">X</span>- and <span class="html-italic">Y</span>-axis values indicate the ranking of transcripts that contribute to the effects on rosette diameter, with lower numbers indicating a higher contribution.</p>
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<p>Accumulation of H<sub>2</sub>O<sub>2</sub> (<b>A</b>) and MDA (<b>B</b>) in plants exposed to submergence (Sub) or flooding with different flow rates. Error bars indicate standard deviation (<span class="html-italic">n</span> = 3). * and **: Student’s <span class="html-italic">t</span>-test significantly different at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01, respectively (<span class="html-italic">n</span> = 3, compared to control).</p>
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16 pages, 4859 KiB  
Article
The Role of Potato Glycoside Alkaloids Mediated Oxidative Stress in Inducing Apoptosis of Wolfberry Root Rot Pathogen Fungi
by Yuyan Sun, Bin Wang, Wei Chen, Yanbo Wang, Dongdong Zhou, Mengyang Zhang, Chongqing Zhang, Ruiyun Li and Jing He
Antioxidants 2024, 13(12), 1537; https://doi.org/10.3390/antiox13121537 - 15 Dec 2024
Viewed by 497
Abstract
Wolfberry (Lycium barbarum) is a vital economic tree species in northwest China, but root rot caused by Fusarium solani occurs frequently, which seriously endangers the quality and yield of wolfberry. In this study, potato glycoside alkaloids (PGAs), a plant-derived active substance, [...] Read more.
Wolfberry (Lycium barbarum) is a vital economic tree species in northwest China, but root rot caused by Fusarium solani occurs frequently, which seriously endangers the quality and yield of wolfberry. In this study, potato glycoside alkaloids (PGAs), a plant-derived active substance, were used as materials to explore its inhibitory effect on F. solani. By analyzing the changes of reactive oxygen species (ROS) level, antioxidant capacity, and apoptosis, the role of PGAs-mediated oxidative stress in inducing apoptosis of F. solani was revealed. The findings suggest that PGAs treatment inhibited mycelium growth, reduced biomass and sporulation, and delayed spore germination in F. solani. The concentration for 50% of maximal effect (EC50) was 1.85 mg/mL. PGAs treatment induced an increase in caspase-3 activity, disrupting the cell membrane of fungi. In addition, PGAs treatment activated NADH oxidase (NOX) and superoxide dismutase (SOD), promoted hydrogen peroxide (H2O2) and superoxide anion (O2) accumulation, and decreased ascorbate peroxidase (APX), glutathione reductase (GR), and dehydroascorbate reductase (DHAR) activities as well as oxidized glutathione (GSSG), reduced glutathione (GSH), and electron donor NADPH content. In summary, PGAs has a strong inhibitory effect on F. solani, and its inhibitory effect may be related to the promotion of ROS accumulation by PGAs, causing the disorder of intracellular redox balance of fungi, the decrease of total antioxidant capacity, and finally the induction of apoptosis. This study provides a new insight into the antifungal mechanism of PGAs against F. solani. Full article
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<p>Effects of different concentrations of potato glycoside alkaloids (PGAs) on the growth of <span class="html-italic">F. solani</span> colony after 9 d. Note: Control indicates sterile water treatment; PGAs indicates potato glycoside alkaloids treatment (the same as below).</p>
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<p>Effects of EC<sub>50</sub> potato glycoside alkaloids (PGAs) treatment on colony diameter (<b>A</b>,<b>B</b>), biomass (<b>C</b>), sporulation (<b>D</b>), and spore germination rate (<b>E</b>) of <span class="html-italic">F. solani</span>. The vertical line indicates the standard error. Different lowercase letters indicated significant differences between the control and PGAs treatment (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of EC<sub>50</sub> potato glycoside alkaloids (PGAs) treatment on the caspase-3 activity of <span class="html-italic">F. solani</span> at 3, 5, 7, and 9 d. The vertical line indicates the standard error. Different lowercase letters indicated significant differences between the control and PGAs treatment (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of EC<sub>50</sub> potato glycoside alkaloids (PGAs) treatment on cell membrane integrity of <span class="html-italic">F. solani</span>.</p>
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<p>Effects of EC<sub>50</sub> potato glycoside alkaloids (PGAs) treatment on <span class="html-italic">F. solani</span> NADH oxidase (NOX) (<b>A</b>), superoxide dismutase (SOD) (<b>B</b>), superoxide anion (O<sub>2</sub><sup>−</sup>) (<b>C</b>), and hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) (<b>D</b>). The vertical line indicates the standard error. Different lowercase letters indicated significant differences between the control and PGAs treatment (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Reactive oxygen species (ROS) staining (<b>A</b>) and fluorescence intensity (<b>B</b>) of <span class="html-italic">F. solani</span>. The vertical line indicates the standard error. Different lowercase letters indicated significant differences between the control and PGAs treatment (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of EC<sub>50</sub> potato glycoside alkaloids (PGAs) treatment on <span class="html-italic">F. solani</span> catalase (CAT) (<b>A</b>), thioredoxin peroxidase (TPX) (<b>B</b>), ascorbate peroxidase (APX) (<b>C</b>), glutathione reductase (GR) (<b>D</b>), dehydroascorbate reductase (DHAR) (<b>E</b>), and monodehydroascorbate reductase (MDHAR) (<b>F</b>). The vertical lines represent standard errors. Different lowercase letters indicated significant differences between the control and PGAs treatment (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of EC<sub>50</sub> potato glycoside alkaloids (PGAs) treatment on <span class="html-italic">F. solani</span> ascorbic acid (AsA) (<b>A</b>), dehydroascorbic acid (DHA) (<b>B</b>), reduced glutathione (GSH) (<b>C</b>), oxidized glutathione (GSSG) (<b>D</b>), GSH/GSSG (<b>E</b>), and NADPH (<b>F</b>). The vertical lines represent standard errors. Different lowercase letters indicated significant differences between the control and PGAs treatment (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of EC<sub>50</sub> potato glycoside alkaloids (PGAs) treatment on <span class="html-italic">F. solani</span> total antioxidant capacity (T-AOC) (<b>A</b>) and inhibition of hydroxyl radical (·OH) (<b>B</b>). The vertical lines represent standard errors. Different lowercase letters indicated significant differences between the control and PGAs treatment (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Pattern of antifungal action of potato glycoside alkaloids (PGAs) on <span class="html-italic">F. solani</span> (By Figdraw).</p>
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25 pages, 1462 KiB  
Review
Targeting Reactive Oxygen Species for Diagnosis of Various Diseases
by Moung Young Lee, Donguk Lee, Dayun Choi, Kye S. Kim and Peter M. Kang
J. Funct. Biomater. 2024, 15(12), 378; https://doi.org/10.3390/jfb15120378 - 15 Dec 2024
Viewed by 510
Abstract
Reactive oxygen species (ROS) are generated predominantly during cellular respiration and play a significant role in signaling within the cell and between cells. However, excessive accumulation of ROS can lead to cellular dysfunction, disease progression, and apoptosis that can lead to organ dysfunction. [...] Read more.
Reactive oxygen species (ROS) are generated predominantly during cellular respiration and play a significant role in signaling within the cell and between cells. However, excessive accumulation of ROS can lead to cellular dysfunction, disease progression, and apoptosis that can lead to organ dysfunction. To overcome the short half-life of ROS and the relatively small amount produced, various imaging methods have been developed, using both endogenous and exogenous means to monitor ROS in disease settings. In this review, we discuss the molecular mechanisms underlying ROS production and explore the methods and materials that could be used to detect ROS overproduction, including iron-based materials, ROS-responsive chemical bond containing polymers, and ROS-responsive molecule containing biomaterials. We also discuss various imaging and imaging techniques that could be used to target and detect ROS overproduction. We discuss the ROS imaging potentials of established clinical imaging methods, such as magnetic resonance imaging (MRI), sonographic imaging, and fluorescence imaging. ROS imaging potentials of other imaging methods, such as photoacoustic imaging (PAI) and Raman imaging (RI) that are currently in preclinical stage are also discussed. Finally, this paper focuses on various diseases that are associated with ROS overproduction, and the current and the future clinical applications of ROS-targeted imaging. While the most widely used clinical condition is cardiovascular diseases, its potential extends into non-cardiovascular clinical conditions, such as neurovascular, neurodegenerative, and other ROS-associated conditions, such as cancers, skin aging, acute kidney injury, and inflammatory arthritis. Full article
(This article belongs to the Collection Feature Papers in Biomaterials for Drug Delivery)
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<p>Molecular mechanisms of H<sub>2</sub>O<sub>2</sub> production. (<b>a</b>) H<sub>2</sub>O<sub>2</sub> is generated during cellular respiration in the mitochondria. This process generates superoxide anion through ubiquinone and cytochrome. Superoxide anion is rapidly converted to H<sub>2</sub>O<sub>2</sub> in the mitochondria by superoxide dismutases (SODs) and in the cytosol by xanthine oxidase. (<b>b</b>) H<sub>2</sub>O<sub>2</sub> can also form through the action of NADPH oxidase and monoamine oxidase. (<b>c</b>) In peroxisomes, H<sub>2</sub>O<sub>2</sub> is generated during fatty acid β-oxidation. (<b>d</b>) Proteins generate H<sub>2</sub>O<sub>2</sub> by endoplasmic reticulum oxireductin 1 (ERO1) and protein disulfide isomerase (PDI) in the endoplasmic reticulum. An increase in proteins under physiological conditions promotes oxidative folding, resulting in electron transfer between PDI and ERO1, generating H<sub>2</sub>O<sub>2</sub>. (<b>e</b>) NADPH oxidase (NOX) interacts with O<sub>2</sub> in the extracellular space, producing superoxide anion, which is then converted to H<sub>2</sub>O<sub>2</sub>.</p>
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<p>Clinical imaging modalities to detect ROS. (<b>a</b>) Fluorescence imaging using drug/contrast agent delivery system. When ROS-targeting materials are injected into the body, they be released at the site of ROS overproduction, which allows detection using fluorescence imaging. (<b>b</b>) Ultrasound imaging using microbubble-based drug delivery. When directed to ROS-overproducing targets, the microbubble structure is disrupted. This enhances the ultrasound signal, which can be detected using an ultrasound transducer. (<b>c</b>) MRI imaging using Gadolinium-based materials. Gadolinium is released near the target, amplifying the T1-weighted signal.</p>
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<p>Preclinical imaging modalities to detect ROS. (<b>a</b>) Photoacoustic imaging. When contrast agent-loaded materials reach ROS overproduced regions, they release drugs and contrast agents. The contrast agents amplify the ultrasound signal upon pulsed laser irradiation. (<b>b</b>) Raman imaging. When the laser is applied to the sample, the sample molecules vibrate, causing a shift in the light wavelength. Rayleigh signals are filtered out. The remaining signals are organized by wavelength to reconstruct images.</p>
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43 pages, 28157 KiB  
Article
Exploring the Physiological and Molecular Mechanisms by Which Potassium Regulates Low-Temperature Tolerance of Coconut (Cocos nucifera L.) Seedlings
by Lilan Lu, Yuping Wang, Md. Abu Sayed, Amjad Iqbal and Yaodong Yang
Agronomy 2024, 14(12), 2983; https://doi.org/10.3390/agronomy14122983 - 14 Dec 2024
Viewed by 347
Abstract
Coconut holds significant importance as a fruit and oilseed crop in tropical and subtropical regions. However, low-temperature (LT) stress has caused substantial reductions in yield and economics and impedes coconut production, therefore constraining its widespread cultivation and utilization. The appropriate application of potassium [...] Read more.
Coconut holds significant importance as a fruit and oilseed crop in tropical and subtropical regions. However, low-temperature (LT) stress has caused substantial reductions in yield and economics and impedes coconut production, therefore constraining its widespread cultivation and utilization. The appropriate application of potassium (K) has the potential to enhance the cold tolerance of crops and mitigate cold damage, but the regulatory mechanisms by which K improves coconut adaptability to cold stress remain poorly understood. Transcriptome and metabolomic analyses were performed on coconut seedlings treated with LT (5 °C) and room temperature (25 °C) under various K conditions: K0 (0.1 mM KCL), KL (2 mM KCL), KM (4 mM KCL), and KH (8 mM KCL). Correlation analysis with physiological indicators was also conducted. The findings indicated that K absorption, nutrient or osmotic regulation, accumulation of substances, photosynthesis, hormone metabolism, and reactive oxygen species (ROS) clearance pathways played crucial roles in the adaptation of coconut seedlings to LT stress. LT stress disrupted the homeostasis of hormones, antioxidant enzyme activity, chlorophyll, K, and the regulation of nutrients and osmolytes. This stress also leads to the downregulation of genes and metabolites related to K transporters, hormone metabolism, transcription factors, and the metabolism of nutrients and osmolytes. Applying K helped maintain the homeostasis of hormones, antioxidant enzyme activity, chlorophyll, K, and the regulation of nutrients and osmolytes, promoted the removal of ROS, and reduced malondialdehyde, consequently diminishing the damage caused by LT stress to coconut seedlings. Furthermore, the comprehensive analysis of metabolomics and transcriptomics highlighted the importance of carbohydrate metabolism, biosynthesis of other secondary metabolites, amino acid metabolism, lipid metabolism, and ABC transporters in K’s role in improving coconut seedlings’ tolerance to LT stress. This study identified the pivotal biological pathways, regulatory genes, and metabolites implicated in K regulation of coconut seedlings to acclimate to LT stress. Full article
(This article belongs to the Special Issue Application of Multi-Omics and Systems Biology in Crop Breeding)
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Figure 1
<p>Investigating the effect of different K levels on the growth of coconut seedlings under LT and RT conditions. Note: (<b>a</b>) Phenotypes of coconut seedlings treated with different K levels under LT and RT conditions; (<b>b</b>) Structural diagram of paraffin sections of coconut seedling leaves treated with different K levels under LT and RT conditions. CP, Cytoplasm; CW, cell wall; CD, cell duct; CN, cell nucleus. LT, RT, K<sub>0</sub>, K<sub>L</sub>, K<sub>M</sub>, and K<sub>H</sub> are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>Physiological characteristics of coconut seedling leaves across various K levels under LT and RT conditions. (<b>a</b>) Endogenous hormones; (<b>b</b>) Enzyme activities. Note: POD, peroxidase; SOD, superoxide dismutase; CAT, catalase; APX, ascorbic acid peroxidase; IAA, auxin; ABA, abscisic acid; ZR, zein; GA, gibberellin. The values are the average of three biological replicates and three detection experiment replicates (n = 6). The vertical bar represents the average standard error. The statistical significance was calculated by the Student’s t-test, and “*” indicated a significant difference at the <span class="html-italic">p</span> &lt; 0.05 level. LT, RT, K<sub>0</sub>, K<sub>L</sub>, K<sub>M</sub>, and K<sub>H</sub> are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>Examining the top 20 KEGG enrichments of DEGs in coconut seedling leaves in different K levels under LT and RT conditions. Note: DEGs, differentially expressed genes; (<b>a</b>) K<sub>0</sub> vs. K<sub>L</sub> in LT; (<b>b</b>) K<sub>0</sub> vs. K<sub>M</sub> in LT; (<b>c</b>) K<sub>0</sub> vs. K<sub>H</sub> in LT; (<b>d</b>) K<sub>0</sub> vs. K<sub>L</sub> in RT; (<b>e</b>) K<sub>0</sub> vs. K<sub>M</sub> in RT; (<b>f</b>) K<sub>0</sub> vs. K<sub>H</sub> in RT. LT, RT, K<sub>0</sub>, K<sub>L</sub>, K<sub>M</sub>, and K<sub>H</sub> are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>Heat map of KEGG enriched DEGs in coconut seedling leaves in different K levels under LT and RT conditions. Note: DEGs, differentially expressed genes; A, K<sub>0</sub> vs. K<sub>L</sub>; B, K<sub>0</sub> vs. K<sub>M</sub>; C, K<sub>0</sub> vs. K<sub>H</sub>; (<b>a</b>) Plant hormone signal translation; (<b>b</b>) Flavonoid biosynthesis; (<b>c</b>) Alpha-Linolenic acid metabolism; (<b>d</b>) Starch and sucrose metabolism; (<b>e</b>) Amino sugar and nucleoside sugar metabolism; (<b>f</b>) Glycerophospholipid metabolism; (<b>g</b>) Galactose metabolism. LT, RT, K<sub>0</sub>, K<sub>L</sub>, K<sub>M</sub>, and K<sub>H</sub> are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>Heat map of DEGs of major transcription factors in coconut seedling leaves under different K levels under LT and RT conditions. Note: DEGs, differentially expressed genes, A, K<sub>0</sub> vs. K<sub>L</sub>; B, K<sub>0</sub> vs. K<sub>M</sub>; C, K<sub>0</sub> vs. K<sub>H</sub>; LT, RT, are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>Expression of DAMs in key pathways occurs in K<sub>0</sub> vs. K<sub>L</sub>, K<sub>0</sub> vs. K<sub>M</sub>, and K<sub>0</sub> vs. K<sub>H</sub> in LT and RT. Note: DAMs, differentially accumulated metabolites; DAMs are displayed in red, highlighted font. The redder the color of the heat map, the more significant the upregulation of DAMs; the bluer the color, the more significant the downregulation of DAMs. LT, RT, K<sub>0</sub>, K<sub>L</sub>, K<sub>M</sub>, and K<sub>H</sub> are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>Expression of DAMs in key pathways occurs in K<sub>0</sub> vs. K<sub>L</sub>, K<sub>0</sub> vs. K<sub>M</sub>, and K<sub>0</sub> vs. K<sub>H</sub> in LT and RT. Note: DAMs, differentially accumulated metabolites; DAMs are displayed in red, highlighted font. The redder the color of the heat map, the more significant the upregulation of DAMs; The bluer the color, the more significant the downregulation of DAMs. LT, RT, K<sub>0</sub>, K<sub>L</sub>, K<sub>M</sub>, and K<sub>H</sub> are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>Expression of DEGs and DAMs in key pathways found in K<sub>0</sub> vs. K<sub>L</sub>, K<sub>0</sub> vs. K<sub>M</sub>, and K<sub>0</sub> vs. K<sub>H</sub> in LT and RT. Note: DEGs, differentially expressed genes; DAMs, differentially accumulated metabolites; (<b>a</b>) Starch and sucrose metabolism, amino sugar and nucleate sugar metabolism, pyrimidine metabolism, galactose metabolism, and ascorbate and alarate metabolism; (<b>b</b>) Cysteine and methionine metabolism, glycerophoric metabolism, and ABC transporters; (<b>c</b>) Biosynthesis of amino acids; (<b>d</b>). Alpha-linolenic acid metabolism. DEGs are displayed in blue boxes, while DAMs are displayed in red, highlighted font. The redder the color of the heat map, the more significant the upregulation of DEGs and DAMs; The greener and bluer the color, the more significant the downregulation of DEGs and DAMs. LT, RT, K<sub>0</sub>, K<sub>L</sub>, K<sub>M</sub>, and K<sub>H</sub> are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>Expression of DEGs and DAMs in key pathways observed in K<sub>0</sub> vs. K<sub>L</sub>, K<sub>0</sub> vs. K<sub>M</sub>, and K<sub>0</sub> vs. K<sub>H</sub> in LT and RT. Note: DEGs, differentially expressed genes; DAMs, differentially accumulated metabolites; (<b>a</b>) Phenolpropanoid biosynthesis; (<b>b</b>) Flavonoid biosynthesis; (<b>c</b>) Tyrosine metabolism; (<b>d</b>) Lysine degradation. DEGs are shown in blue boxes, while DAMs are highlighted in red font. The redder the color of the heatmap, the more significant the upregulation of DEGs and DAMs; the greener and bluer the color, the more significant the downregulation of DEGs and DAMs. LT, RT, K<sub>0</sub>, K<sub>L</sub>, K<sub>M</sub>, and K<sub>H</sub> are detailed in <a href="#agronomy-14-02983-t001" class="html-table">Table 1</a>.</p>
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<p>A network regulation diagram of DAMs and DEGs in key metabolic pathways based on the Pearson correlation coefficient model. Note: DEGs, differentially expressed genes; DAMs, differentially accumulated metabolites; (<b>a</b>) Starch and sucrose metabolism (Ko00500); (<b>b</b>) Amino sugar and nucleate sugar metabolism (Ko00520); (<b>c</b>) Glycerophospholipid metabolism (Ko00564); (<b>d</b>) Galactose metabolism (Ko00052); (<b>e</b>) ABC transporters (Ko02010); (<b>f</b>) Cysteine and methionine metabolism (Ko00270); 1, UDP-glucose (meta_46); 2, N-Glycolylneuraminic acid (meta_997); 3, 1-Linoleoylcerophosphocholine (meta_172); 4, Phosphocholine (meta_53); 5, Choline (meta_19); 6, Stachyose (meta_343); 7, N-Acetyl-D-galactosamine (meta_241); 8, Raffinose (meta_402); 9, Betaine (meta_116); 10, Glutathione (meta_208); 11, DL-Methionine sulfoxide (meta_1083); 12, S-Adenosylhomocysteine (meta_842). Filtered and plotted based on absolute values with correlation coefficients &gt; 0.8. The straight line between DEGs and DAMs represents correlation, with thicker and darker lines indicating greater positive correlation and thinner and lighter lines indicating greater negative correlation.</p>
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<p>A network regulation diagram of DEGs and DAMs in key metabolic pathways based on the Pearson correlation coefficient model. Note: DEGs, differentially expressed genes; DAMs, differentially accumulated metabolites; (<b>a</b>) alpha-Linolenic acid metabolism (Ko 00592); (<b>b</b>) Tyrosine metabolism (Ko00350); (<b>c</b>) Flavonoid biosynthesis (Ko00941); (<b>d</b>) Phenolpropanoid biosynthesis (Ko00940); 1, Traumatic acid (meta_743); 2, alpha-Linolenic acid(meta_551); 3, 12-oxo-10E-dodecenoic acid (meta_392); 4, 9(S)-HpOTrE (meta_29); 5, 13(S)-HOTrE (meta_31); 6, Gentisaldehyde (meta_715); 7, 2,5-Dihydroxybenzaldehyde (meta_432); 8, Gentisic acid (meta_66); 9, DL-Vanillylmandelic acid (meta_672); 10, 2-(4-Hydroxyphenyl) ethanal (meta_1042); 11, 4-Hydroxypheylpyruvate(meta_580); 12, Succinic acid (meta_9); 13, Phenol(meta_743); 14, Cyanidin (meta_423); 15, Neohesperidin (meta_530); 16, Chlorogenate (meta_569); 17,Chlorogenic acid (meta_52); 18, Trans-Cinnamate (meta_923); 19, Caffeic acid (meta_10); 20, 3,5-Dimethoxy-4-hydroxycinnamic acid(meta_632); 21, Coumarin (meta_216); 22, 4-Hydroxy-3-methoxycinnamaldehyde (meta_211). Filtered and plotted based on absolute values with correlation coefficients &gt; 0.8. The straight line between DEGs and DAMs represents correlation, with red lines indicating a positive correlation, thicker and darker red lines indicating a greater positive correlation, green lines indicating a negative correlation, and thicker and darker green lines indicating a greater negative correlation.</p>
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<p>A schematic diagram of the mechanism by which K enhances the cold tolerance of coconut seedlings. Note: Rectangles represent genes, while ovals represent metabolites. Red font indicates upregulation of gene and metabolite expression, while green font indicates downregulation of gene and metabolite expression. Orange font indicates both upregulation and downregulation of gene and metabolite expression.</p>
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15 pages, 3664 KiB  
Article
Poly-Glutamic Acid Regulates Physiological Characteristics, Plant Growth, and the Accumulation of the Main Medical Ingredients in the Root of Salvia miltiorrhiza Under Water Shortage
by Changjuan Shan and Yibo Zhang
Agronomy 2024, 14(12), 2977; https://doi.org/10.3390/agronomy14122977 - 13 Dec 2024
Viewed by 319
Abstract
To supply information concerning the application of poly-glutamic acid (PGA) in the drought-resistant cultivation of red sage (Salvia miltiorrhiza), we investigated the role of PGA in regulating the physiological characteristics, plant growth, and the accumulation of the main medical components in [...] Read more.
To supply information concerning the application of poly-glutamic acid (PGA) in the drought-resistant cultivation of red sage (Salvia miltiorrhiza), we investigated the role of PGA in regulating the physiological characteristics, plant growth, and the accumulation of the main medical components in the root under water shortage. The findings showed that different levels of water shortage (WS) all suppressed the photosynthetic function by reducing the net photosynthetic rate (Pn), Soil and plant analyzer development (SPAD) value, maximum photochemical efficiency of PSII (Fv/Fm), photochemical quenching (qP), and actual photochemical efficiency of PSII (Y(II)), as well as increasing non-photochemical quenching (qN). Compared with WS, PGA plus WS enhanced the photosynthetic function by reducing qN and increasing the other indicators above. For water metabolism, WS increased stomatal limit value (Ls) and water use efficiency (WUE), but decreased transpiration rate (Tr) and stomatal conductance (Gs). Compared with WS, PGA plus WS decreased Ls and increased Tr, Gs, and WUE. Meanwhile, WS enhanced the antioxidant capacity by increasing superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) activities. However, WS increased malondialdehyde (MDA) content. Compared with WS, PGA plus WS enhanced the above antioxidant enzymes. In this way, PGA reduced MDA content and improved the antioxidant capacity under WS. In addition, WS decreased the shoot and root biomass, but increased the root/shoot ratio. Compared with WS, PGA plus WS further increased the root/shoot ratio and shoot and root biomass. For medical ingredients, WS decreased the yield of rosmarinic acid (RosA) and salvianolic acid B (SalB), but increased the yield of dihydrotanshinone (DHT), cryptotanshinone (CTS), tanshinone I (Tan I), and tanshinone ⅡA (Tan ⅡA). Compared with WS, PGA plus WS increased the yield of these medical ingredients. Our findings clearly suggested that PGA application was an effective method to enhance sage drought tolerance and the yield of the main medical ingredients in sage root. This provides useful information for its application in sage production under WS. Full article
(This article belongs to the Section Water Use and Irrigation)
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<p>Effects of PGA on SPAD value (<b>A</b>) and Pn (<b>B</b>) under WS. Different letters represent significant differences between treatments at <span class="html-italic">p</span> &lt; 0.05 as determined by DMRT. The plants were treated as below. Control, 60% field water capacity; 50%FC, 50% field water capacity; 50%FC + PGA-1, 50% field water capacity + 0.22 g/L PGA; 50%FC + PGA-2, 50% field water capacity + 0.44 g/L PGA; 50%FC + PGA-3, 50% field water capacity + 0.88 g/L PGA; 40%FC, 40% field water capacity; 40%FC + PGA-1, 40% field water capacity + 0.22 g/L PGA; 40%FC + PGA-2, 40% field water capacity + 0.44 g/L PGA; 40%FC + PGA-3, 40% field water capacity + 0.88 g/L PGA.</p>
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<p>Effects of PGA on gas exchange parameters Tr (<b>A</b>), Gs (<b>B</b>), Ls (<b>C</b>), and WUE (<b>D</b>) under WS. Different letters represent significant differences between treatments at <span class="html-italic">p</span> &lt; 0.05 as determined by DMRT. The plants were treated as below. Control, 60% field water capacity; 50%FC, 50% field water capacity; 50%FC + PGA-1, 50% field water capacity + 0.22 g/L PGA; 50%FC + PGA-2, 50% field water capacity + 0.44 g/L PGA; 50%FC + PGA-3, 50% field water capacity + 0.88 g/L PGA; 40%FC, 40% field water capacity; 40%FC + PGA-1, 40% field water capacity + 0.22 g/L PGA; 40%FC + PGA-2, 40% field water capacity + 0.44 g/L PGA; 40%FC + PGA-3, 40% field water capacity + 0.88 g/L PGA.</p>
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<p>Effects of PGA on Y(Ⅱ) (<b>A</b>), F<sub>v</sub>/F<sub>m</sub> (<b>B</b>), q<sub>N</sub> (<b>C</b>), and q<sub>P</sub> (<b>D</b>) under WS. Different letters represent significant differences between treatments at <span class="html-italic">p</span> &lt; 0.05 as determined by DMRT. The plants were treated as below. Control, 60% field water capacity; 50%FC, 50% field water capacity; 50%FC + PGA-1, 50% field water capacity + 0.22 g/L PGA; 50%FC + PGA-2, 50% field water capacity + 0.44 g/L PGA; 50%FC + PGA-3, 50% field water capacity + 0.88 g/L PGA; 40%FC, 40% field water capacity; 40%FC + PGA-1, 40% field water capacity + 0.22 g/L PGA; 40%FC + PGA-2, 40% field water capacity + 0.44 g/L PGA; 40%FC + PGA-3, 40% field water capacity + 0.88 g/L PGA.</p>
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<p>Effects of PGA on SOD (<b>A</b>), POD (<b>B</b>), and CAT (<b>C</b>) activities, and MDA content (<b>D</b>) under WS. Different letters represent significant differences between treatments at <span class="html-italic">p</span> &lt; 0.05 as determined by DMRT. The plants were treated as below. Control, 60% field water capacity; 50%FC, 50% field water capacity; 50%FC + PGA-1, 50% field water capacity + 0.22 g/L PGA; 50%FC + PGA-2, 50% field water capacity + 0.44 g/L PGA; 50%FC + PGA-3, 50% field water capacity + 0.88 g/L PGA; 40%FC, 40% field water capacity; 40%FC + PGA-1, 40% field water capacity + 0.22 g/L PGA; 40%FC + PGA-2, 40% field water capacity + 0.44 g/L PGA; 40%FC + PGA-3, 40% field water capacity + 0.88 g/L PGA.</p>
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<p>Effects of PGA on shoot biomass (<b>A</b>) and root biomass (<b>B</b>), root/shoot ratio (<b>C</b>), and root volume (<b>D</b>) under WS. Different letters represent significant differences between treatments at <span class="html-italic">p</span> &lt; 0.05 as determined by DMRT. The plants were treated as below. Control, 60% field water capacity; 50%FC, 50% field water capacity; 50%FC + PGA-1, 50% field water capacity + 0.22 g/L PGA; 50%FC + PGA-2, 50% field water capacity + 0.44 g/L PGA; 50%FC + PGA-3, 50% field water capacity + 0.88 g/L PGA; 40%FC, 40% field water capacity; 40%FC + PGA-1, 40% field water capacity + 0.22 g/L PGA; 40%FC + PGA-2, 40% field water capacity + 0.44 g/L PGA; 40%FC + PGA-3, 40% field water capacity + 0.88 g/L PGA.</p>
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<p>Effects of PGA on the yield of main water-soluble medical ingredients (<b>A</b>) and main fat-soluble medical ingredients (<b>B</b>) in root under WS. Different letters represent significant differences between treatments at <span class="html-italic">p</span> &lt; 0.05 as determined by DMRT. The plants were treated as below. Control, 60% field water capacity; 50%FC, 50% field water capacity; 50%FC + PGA-1, 50% field water capacity + 0.22 g/L PGA; 50%FC + PGA-2, 50% field water capacity + 0.44 g/L PGA; 50%FC + PGA-3, 50% field water capacity + 0.88 g/L PGA; 40%FC, 40% field water capacity; 40%FC + PGA-1, 40% field water capacity + 0.22 g/L PGA; 40%FC + PGA-2, 40% field water capacity + 0.44 g/L PGA; 40%FC + PGA-3, 40% field water capacity + 0.88 g/L PGA.</p>
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<p>Pearson correlation analysis between parameters related to plant growth and medical ingredient yield and parameters related to physiological characteristics, measured in June and August. The abbreviations in this figure are as follows: SPAD = soil and plant analyzer development; Pn = net photosynthetic rate; Tr = transpiration rate; Gs = stomatal conductance; Ls = stomatal limit value; WUE = water use efficiency; Y(Ⅱ) = actual photochemical efficiency of PSII; F<sub>v</sub>/F<sub>m</sub> = maximum photochemical efficiency of PSII; q<sub>N</sub> = non-photochemical quenching; q<sub>P</sub> = photochemical quenching; SOD = superoxide dismutase; POD = peroxidase; CAT = catalase; MDA = malondialdehyde; RosA = rosmarinic acid; SalB = salvianolic acid B; DHT = dihydrotanshinone; CTS = cryptotanshinone; Tan I = tanshinone I and Tan ⅡA = tanshinone ⅡA.</p>
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18 pages, 3388 KiB  
Article
The Molecular Mechanism Regulating Flavonoid Production in Rhododendron chrysanthum Pall. Against UV-B Damage Is Mediated by RcTRP5
by Fushuai Gong, Jinhao Meng, Hongwei Xu and Xiaofu Zhou
Int. J. Mol. Sci. 2024, 25(24), 13383; https://doi.org/10.3390/ijms252413383 - 13 Dec 2024
Viewed by 287
Abstract
Elevated levels of reactive oxygen species (ROS) are caused by ultraviolet B radiation (UV-B) stress. In response, plants strengthen their cell membranes, impeding photosynthesis. Additionally, UV-B stress initiates oxidative stress within the antioxidant defense system and alters secondary metabolism, particularly by increasing the [...] Read more.
Elevated levels of reactive oxygen species (ROS) are caused by ultraviolet B radiation (UV-B) stress. In response, plants strengthen their cell membranes, impeding photosynthesis. Additionally, UV-B stress initiates oxidative stress within the antioxidant defense system and alters secondary metabolism, particularly by increasing the quantity of UV-absorbing compounds such as flavonoids. The v-myb avian myeloblastosis viral oncogene homolog (MYB) transcription factor (TF) may participate in a plant’s response to UV-B damage through its regulation of flavonoid biosynthesis. In this study, we discovered that the photosynthetic activity of Rhododendron chrysanthum Pall. (R. chrysanthum) decreased when assessing parameters of chlorophyll (PSII) fluorescence parameters under UV-B stress. Concurrently, antioxidant system enzyme expression increased under UV-B exposure. A multi-omics data analysis revealed that acetylation at the K68 site of the RcTRP5 (telomeric repeat binding protein of Rhododendron chrysanthum Pall.) transcription factor was upregulated. This acetylation modification of RcTRP5 activates the antioxidant enzyme system, leading to elevated expression levels of peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT). Upregulation is also observed at the K95 site of the chalcone isomerase (CHI) enzyme and the K178 site of the anthocyanidin synthase (ANS) enzyme. We hypothesize that RcTRP5 influences acetylation modifications of CHI and ANS in flavonoid biosynthesis, thereby indirectly regulating flavonoid production. This study demonstrates that R. chrysanthum can be protected from UV-B stress by accumulating flavonoids. This could serve as a useful strategy for enhancing the plant’s flavonoid content and provide a valuable reference for research on the metabolic regulation mechanisms of other secondary substances. Full article
(This article belongs to the Special Issue Abiotic Stress in Plant)
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<p>Trends in <span class="html-italic">R. chrysanthum’s</span> photosynthetic characteristics under UV-B stress: (<b>a</b>–<b>d</b>) real-time fluorescence actual, quantum yield of modulatable quenching in PSII, quantum yield of non-modulatable quenching in PSII, and photosynthetic efficiency of PSII, respectively. The data represent the mean ± SD for <span class="html-italic">n</span> = 3. A significant difference among treatments at <span class="html-italic">p</span> &lt; 0.05 is indicated by different letters (a, b).</p>
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<p>Flavonoid trends in six <span class="html-italic">R. chrysanthum</span> species in response to UV-B exposure: (<b>a</b>–<b>f</b>) gallocatechin, 6-methoxyflavone, kaempferol-3-O-arabinoside, naringenin chalcone, butin, and quercetin-3-O-arabinoside, respectively. The data represent the mean ± SD for <span class="html-italic">n</span> = 3. A significant difference among treatments at <span class="html-italic">p</span> &lt; 0.05 is indicated by different letters (a, b).</p>
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<p>Enrichment analysis of MYB transcription factors significantly altered by UV-B stress in the <span class="html-italic">R. chrysanthum</span>: (<b>a</b>) there were notable variations in the expression levels of eight MYB transcription factors in rhododendron that respond to UV-B stress; red indicates higher expression levels and green lower expression levels; (<b>b</b>) eight MYB transcription factors in the <span class="html-italic">R. chrysanthum</span> were analyzed for enrichment.</p>
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<p>Response of antioxidant enzyme system of <span class="html-italic">R. chrysanthum</span> to UV-B stress and correlation analysis with <span class="html-italic">RcTRP5</span>: (<b>a</b>–<b>c</b>) POD: peroxidase; CAT1: catalase isozyme 1; SODCC: superoxide dismutase; SODCP: superoxide dismutase; (<b>d</b>) the more pinkish the color, the stronger the positive correlation; the more bluish the color, the stronger the negative correlation. The data represent the mean ± SD for <span class="html-italic">n</span> = 3. A significant difference among treatments at <span class="html-italic">p</span> &lt; 0.05 is indicated by different letters (a, b). Asterisks denote treatments with significant changes (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p><span class="html-italic">R. chrysanthum</span> regulates the production of flavonoids: (<b>a</b>) data on metabolite content and enzyme gene expression were shown on a heat map after being normalized using the formula (Xi − min(x))/(max(x) − min(x)). Heatmaps with dark-red and dark-blue hues show changes in metabolite expression, with redder hues denoting higher expression and bluer hues denoting lower expression. Red and green heatmaps show changes in the expression of enzyme genes; redder hues denote higher expression, while greener hues denote lower expression; (<b>b</b>,<b>c</b>) the more pinkish the color, the stronger the positive correlation; the more bluish the color, the stronger the negative correlation. For <span class="html-italic">n</span> = 3, the data are the mean ± SD. Asterisks denote treatments with significant changes (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Examination of two important enzymes’ acetylation changes in the <span class="html-italic">R. chrysanthum</span> flavonoid biosynthesis pathway: (<b>a</b>) from left to right: the three-dimensional architectures of the CHI’s hydrophobic clusters, salt bridges, and acetylation modification sites; (<b>b</b>) from left to right: the three-dimensional architectures of the ANS’s hydrophobic clusters, salt bridges, and acetylation modification sites.</p>
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<p>Correlation analysis of <span class="html-italic">R. chrysanthum’s</span> antioxidant enzyme systems and photosynthetic parameters under UV-B stress. The stronger the association, the more pinkish the color, and the stronger the correlation, the more bluish the color. For <span class="html-italic">n</span> = 3, the data are the mean ± SD. Asterisks denote treatments with significant changes (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Diagram illustrating the defense mechanisms that <span class="html-italic">R. chrysanthum</span> uses against UV-B rays. <span class="html-italic">R. chrysanthum’s</span> enzyme systems and flavonoid biosynthesis pathways under normal light and UV-B stress are depicted in the left and right leaves, respectively. The damaging injuries and reactions to UV-B stress in <span class="html-italic">R. chrysanthum</span> are shown by the red lines. Acetylation modification sites and their upregulation are indicated by pink arrows. Inhibitory effects are indicated by blue lines.</p>
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26 pages, 5107 KiB  
Article
A Zeolitic Imidazolate Framework-Based Antimicrobial Peptide Delivery System with Enhanced Anticancer Activity and Low Systemic Toxicity
by Jingwen Jiang, Kaderya Kaysar, Yanzhu Pan, Lijie Xia and Jinyao Li
Pharmaceutics 2024, 16(12), 1591; https://doi.org/10.3390/pharmaceutics16121591 - 13 Dec 2024
Viewed by 525
Abstract
Background: The clinical efficacies of anticancer drugs are limited by non-selective toxic effects on healthy tissues and low bioavailability in tumor tissue. Therefore, the development of vehicles that can selectively deliver and release drugs at the tumor site is critical for further improvements [...] Read more.
Background: The clinical efficacies of anticancer drugs are limited by non-selective toxic effects on healthy tissues and low bioavailability in tumor tissue. Therefore, the development of vehicles that can selectively deliver and release drugs at the tumor site is critical for further improvements in patient survival. Methods: We prepared a CEC nano-drug delivery system, CEC@ZIF-8, with a zeolite imidazole framework-8 (ZIF-8) as a carrier, which can achieve the response of folate receptor (FR). We characterized this system in terms of morphology, particle size, zeta potential, infrared (IR), x-ray diffraction (XRD), and transcriptome analysis, and examined the in vitro cytotoxicity and cellular uptake properties of CEC@ZIF-8 using cervical cancer cells. Lastly, we established a TC-1 tumor-bearing mouse model and evaluated its in vivo anti-cervical cancer activity. Results: The CEC@ZIF-8 nano-delivery system had favorable biocompatibility, heat stability, and pH responsiveness, with a CEC loading efficiency of 12%, a hydrated particle size of 174 ± 5.8 nm, a zeta potential of 20.57 mV, and slow and massive drug release in an acidic environment (pH 5.5), whereas release was 6% in a neutral environment (pH 7.4). At the same time, confocal imaging and cell viability assays demonstrated greater intracellular accumulation and more potent cytotoxicity against cancer cells compared to free CEC. The mechanism was analyzed by a series of transcriptome analyses, which revealed that CEC@ZIF-8 NPs differentially regulate the expression levels of 1057 genes in cancer cells, and indicated that the enriched pathways were mainly cell cycle and apoptosis-related pathways via the enrichment analysis of the differential genes. Flow cytometry showed that CEC@ZIF-8 NPs inhibited the growth of HeLa cells by arresting the cell cycle at the G0/G1 phase. Flow cytometry also revealed that CEC@ZIF-8 NPs induced greater apoptosis rates than CEC, while unloaded ZIF-8 had little inherent pro-apoptotic activity. Furthermore, the levels of reactive oxygen species (ROS) were also upregulated by CEC@ZIF-8 NPs while ROS inhibitors and caspase inhibitors reversed CEC@ZIF-8 NPs-induced apoptosis. Finally, CEC@ZIF-8 NPs also reduced the growth rate of xenograft tumors in mice without the systemic toxicity observed with cisplatin treatment. Conclusions: The CEC@ZIF-8 nano-drug delivery system significantly enhanced the anti-cervical cancer effect of CEC both in vivo and in vitro, providing a more promising drug delivery system for clinical applications and tumor management. At the same time, this work demonstrates the clinical potential of CEC-loaded ZIF-8 nanoparticles for the selective destruction of tumor tissues. Full article
(This article belongs to the Section Drug Delivery and Controlled Release)
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<p>Characterization of the CEC@ZIF-8 nanoparticles and ZIF-8 nanoparticles. (<b>a</b>) TEM images of CEC@ZIF-8 and ZIF-8 nanoparticles. Scale bar, 200 nm. (<b>b</b>) SEM images of CEC@ZIF-8 and ZIF-8 nanoparticles. (<b>c</b>) DLS profile of ZIF-8, CEC@ZIF-8. (<b>d</b>) Zeta potentials of ZIF-8 NPs and CEC@ZIF-8 NPs (The red line represents ZIF-8, and the black line represents CEC@ZIF-8).</p>
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<p>Basic properties of ZIF-8 and CEC@ZIF-8. (<b>a</b>) XRD patterns of CEC@ZIF-8, ZIF-8, and simulated ZIF-8. (<b>b</b>) FTIR spectrum of ZIF-8 and CEC@ZIF-8. (<b>c</b>) TGA curves of ZIF-8 and CEC@ZIF-8.</p>
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<p>In vitro therapy effect of CEC@ZIF-8 against cervical cancer cells. (<b>a</b>) CLSM images of the distribution of drugs in HeLa cells incubated with CEC@ZIF-8 (scale bar = 25 µm). (<b>b</b>) Cell viability of HeLa cells after treatment with (1) free CEC, (2) CEC@ZIF-8, and (3) ZIF-8 for 24 h. (<b>c</b>) Differences in the number of HeLa cell clones formed by different concentrations of CEC@ZIF-8; (<b>d</b>) Statistics of the number of HeLa cell clones formed by different concentrations of CEC@ZIF-8; Compared to the control group, *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>(<b>a</b>) Principal component analysis of HeLa cells based on (control) untreated control (Triangle representation) and (CEC@ZIF-8) CEC@ZIF-8 treatment groups (Circular representation). (<b>b</b>) Volcano plots to determine the DEGs of the control vs. CEC@ZIF-8 groups. (<b>c</b>) GO pathway annotation analysis of differential genes.</p>
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<p>Anticancer action mechanism of CEC@ZIF-8 on HeLa cells. (<b>a</b>,<b>b</b>) Flow cytometric analysis of HeLa cell cell cycle arrest induced by CEC@ZIF-8 and free CEC. (<b>c</b>,<b>d</b>) Flow cytometric analysis of HeLa cell apoptosis induced by CEC@ZIF-8 and free CEC. Compared to the control group, *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Anticancer action mechanism of CEC@ZIF-8 on HeLa cells. (<b>a</b>) ROS production in HeLa cells after CEC@ZIF-8 NPs treatment for 3, 6, and 24 h, the cells were stained with the fluorescent probe DCFH-DA and analyzed using flow cytometry. (<b>b</b>) The statistical figure. (<b>c</b>) HeLa cells were treated with 30 and 35 μg/mL CEC@ZIF-8NPs and free CEC (35 μg/mL) as the control. After 24 h, cells were treated with JC-1 dye and analyzed by inverted fluorescence microscope. (<b>d</b>) Flow cytometry was used to analyze the changes in JC-1 fluorescence. (<b>e</b>) HeLa cells were pretreated with 10 mM NAC for 1 h, and then treated with CEC@ZIF-8 NPs and CEC for 24 h. The cells were stained with the fluorescent probe DCFH-DA and analyzed using flow cytometry, and the statistical figure. Compared to the control group, *** <span class="html-italic">p</span> &lt; 0.001. At the same concentration, the group treated with inhibitor was compared with the group without inhibitor treatment, # <span class="html-italic">p</span> &lt; 0.05, ### <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Effect of different concentrations of CEC@ZIF-8 nanoparticles on the migration of tumor cells. (<b>a</b>) HeLa cells were treated with different concentrations of CEC@ZIF-8 nanoparticles for 0 h and 24 h. (<b>b</b>) Statistical chart of the migration ability of HeLa cells. (<b>c</b>) Tumor cell invasion and statistics of HeLa cells treated with different concentrations of CEC@ZIF-8 nanoparticles for 24 h. (<b>d</b>) Statistical plot of the invasion ability of HeLa cells. Compared to the control group, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>1 × 10<sup>5</sup> TC-1 cells were injected into the right back of mice, and when the tumor was palpable, the mice were randomly divided into 5 groups. (<b>a</b>) The tumor volume and (<b>b</b>) body weight of the mice were measured every two days during drug treatment. Compared to the control group, * <span class="html-italic">p</span> &lt; 0.05. (<b>c</b>,<b>d</b>) On day 25, the mice were sacrificed and weighed for tumor photography and weight. (<b>e</b>) Tissue sections of TC-1 tumor-bearing mice after CEC@ZIF-8NPs treatment: (1) a section of tumor tissue, (2) liver tissue section, (3) kidney tissue section. Compared to the control group, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. ZIF-8 group compared with CEC@ZIF-8 group, # <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Synthesis of CEC@ZIF-8.</p>
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20 pages, 60225 KiB  
Article
Oligomeric Proanthocyanidins Ameliorate Cadmium-Induced Senescence of Osteocytes Through Combating Oxidative Stress and Inflammation
by Gengsheng Yu, Zehao Wang, Anqing Gong, Xiaohui Fu, Naineng Chen, Dehui Zhou, Yawen Li, Zongping Liu and Xishuai Tong
Antioxidants 2024, 13(12), 1515; https://doi.org/10.3390/antiox13121515 - 12 Dec 2024
Viewed by 386
Abstract
Osteocyte senescence is associated with skeletal dysfunction, but how to prevent bone loss and find the effective therapeutic targets is a potential scientific concern. Cadmium (Cd) is a widespread environmental contaminant that causes substantial bone damage in both animals and humans. Oligomeric proanthocyanidins [...] Read more.
Osteocyte senescence is associated with skeletal dysfunction, but how to prevent bone loss and find the effective therapeutic targets is a potential scientific concern. Cadmium (Cd) is a widespread environmental contaminant that causes substantial bone damage in both animals and humans. Oligomeric proanthocyanidins (OPC) are naturally polyphenolic substances found in various plants and demonstrate significant anti-senescence potential. Here, we investigated the protective effects of OPC against Cd-induced senescence of osteocytes and identify potential regulatory mechanisms. OPC alleviated Cd-induced senescence of osteocytes by attenuating cell cycle arrest, reducing ROS accumulation, and suppressing pro-inflammatory responses in vitro. Furthermore, OPC effectively prevented the Cd-induced breakdown of dendritic synapses in osteocytes in vitro. Correspondingly, OPC ameliorated Cd-induced damage of osteocytes through anti-senescence activity in vivo. Taken together, our results establish OPC as a promising therapeutic agent that ameliorates Cd-induced osteocyte senescence by mitigating oxidative stress and inflammatory responses. Full article
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<p>OPC alleviates Cd-induced cytotoxicity in MLO-Y4 cells. The chemical structure of OPC (<b>A</b>), MLO-Y4 cells were exposed to various concentrations of Cd or OPC for 24 h. Cell viability was detected using CCK8 assay (<b>B</b>,<b>D</b>) and RTCA (<b>C</b>) (The black arrow indicates the point in time when Cd exposure began). MLO-Y4 cells were pretreated with OPC for 2 h, followed by exposure to 6 μmol/L Cd for 24 h. Cell viability was evaluated using CCK-8 assay (<b>E</b>) and RTCA (<b>F</b>) (The black arrow indicates the point at which the Cd treatment began), and morphological changes were examined by phase-contrast microscopy (<b>G</b>). Scale bar = 100 μm. Results are shown as mean ± SD (n = 3). Compared with the control group, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, or ns represent <span class="html-italic">p</span> &gt; 0.05. Compared with the Cd group, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, or ns represent <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>OPC alleviates Cd exposure-induced cellular senescence. MLO-Y4 cells were pretreated with 1 μmol/L OPC for 2 h, followed by exposure to 6 μmol/L Cd for 24 h. Cellular senescence was detected by SA-β-gal staining (<b>A</b>). Scale bar = 100 μm. The protein expression of SirT1, p53, p21, and p16 was detected by Western blot (<b>B</b>). p21 and p16 fluorescence intensities in MLO-Y4 cells were observed using immunofluorescence and quantitatively analyzed using ImageJ software (<b>C</b>,<b>D</b>). Scale bar = 50 μm. Results are shown as the mean ± SD (n = 3). Compared with the control group, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Compared with the Cd group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>OPC alleviated Cd-induced cell cycle arrest and apoptosis<b>.</b> MLO-Y4 cells were pretreated with 1 μmol/L OPC for 2 h, followed by exposure to 6 μmol/L Cd for 24 h. Cell cycle distribution was detected by flow cytometry (<b>A</b>). The protein expression of cyclinB1, cyclinE1, CDK2, CDK4, caspase-3, Bax, BCL-2 and the levels of cleaved caspase-3 were detected by Western blot (<b>B</b>,<b>C</b>). Cell apoptosis was detected by flow cytometry (<b>D</b>). Results are shown as the mean ± SD (n = 3). Compared with the control group, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, or ns represent <span class="html-italic">p</span> &gt; 0.05. Compared with the Cd group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01, or ns represent <span class="html-italic">p</span> &gt; 0.05.</p>
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<p>OPC alleviates Cd-induced mitochondrial dysfunction and DNA damage. MLO-Y4 cells were pretreated with 1 μmol/L OPC for 2 h, followed by exposure to 6 μmol/L Cd for 24 h. Mitochondrial membrane potential was detected by the JC-1 probe using flow cytometry (<b>A</b>). The protein expression of PGC-1β, HSP70, HSP60, and COX4 was detected by Western blot (<b>B</b>). ATP content were detected by ATP assay kit (<b>C</b>). DNA replication ability was detected by EdU staining (<b>D</b>). Scale bar = 50 μm. The expression of FOXO1 and γ-H2AX was detected by Western blot (<b>E</b>). Immunofluorescence analysis showed nuclear distribution and intensity of γ-H2AX foci (<b>F</b>). Scale bar = 100 μm. Results are shown as the mean ± SD (n = 3). Compared with the control group, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Compared with the Cd group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>OPC alleviates Cd-induced ROS accumulation and oxidative damage by inhibiting the Nrf2 pathway. MLO-Y4 cells were pretreated with 1 μmol/L OPC for 2 h, followed by exposure to 6 μmol/L Cd for 24 h. ROS levels were observed using fluorescence microscopy (<b>A</b>) or detected using flow cytometry (<b>B</b>). The expression of Nrf2 and HO-1 was detected by Western blot (<b>C</b>). The mRNA levels of <span class="html-italic">Nrf2</span>, <span class="html-italic">HO-1</span>, <span class="html-italic">GCLC</span>, and <span class="html-italic">GCLM</span> were detected using qRT-PCR (<b>D</b>). Nrf2 nuclear translocation in MLO-Y4 cells was observed using immunofluorescence, red circles represent cells with Nrf2 nuclear translocation; specifically, set a fluorescence intensity threshold value, above which cells will be considered to have positive nuclear translocation of Nrf2, then calculate the percentage of cells with positive nuclear translocation for each treatment group based on the established threshold (<b>E</b>,<b>G</b>). (Red circles represent cells with positive Nrf2 nuclear translocation). Scale bar = 100 μm. The activities of T-AOC, CAT, GSH, and SOD were determined using colorimetry (<b>F</b>). MLO-Y4 cells were co-treated with 6 μmol/L Cd and 5 μmol/L ML385 for 24 h. Cellular senescence was detected by SA-β-gal staining (<b>H</b>,<b>I</b>). Scale bar = 100 μm. The protein expression of p53, p21, and p16 was detected by Western blot (<b>J</b>–<b>M</b>). Results are shown as the mean ± SD (n = 3). Compared with the control group, ** <span class="html-italic">p</span> &lt; 0.01. Compared with the Cd group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>OPC reduces Cd-induced SASP production by inhibiting the NF-κB pathway. MLO-Y4 cells were pretreated with 1 μmol/L OPC for 2 h, followed by exposure to 6 μmol/L Cd for 24 h. The levels of IL-1, IL-1β, and IL-6 intracellularly were detected by ELISA kits (<b>A</b>). The expression of NLRP3, Cleaved Caspase-1, Cleaved IL-1β, COX2, NF-κB, and p-NF-κB was detected by Western blot (<b>B</b>,<b>C</b>). NF-κB nuclear translocation in MLO-Y4 cells was observed using immunofluorescence, red circles represent cells with NF-κB nuclear translocation (<b>D</b>). (Red circles represent cells with positive NF-κB nuclear translocation). Scale bar = 100 μm. Results are shown as the mean ± SD (n = 3). Compared with the control group, ** <span class="html-italic">p</span> &lt; 0.01. Compared with the Cd group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>OPC protects Cd-induced damage to dendritic synapses between MLO-Y4 cells. MLO-Y4 cells were pretreated with 1 μmol/L OPC for 2 h, followed by exposure to 6 μmol/L Cd for 24 h. Intercellular synaptic structures were observed by SEM (<b>A</b>).(The red arrows represent damaged or broken synapses). Scale bar = 10 μm. The expression of E11, CX43, COL1A1, OPN, OCN, and SOST was detected by Western blot (<b>B</b>,<b>C</b>). Results are shown as the mean ± SD (n = 3). Compared with the control group, ** <span class="html-italic">p</span> &lt; 0.01. Compared with the Cd group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>##</sup> <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>OPC attenuates Cd-induced osteocyte senescence and dysfunction in vivo. Schematic diagram of the animal experiment design and treatment protocol (<b>A</b>). Histopathological evaluation of femur was conducted by HE staining (<b>B</b>), scale bar = 50 μm. SOST (<b>C</b>) and p16 (<b>E</b>) expression in femur osteocytes was observed using IHC staining, scale bar = 50 μm. The expression of osteocyte- function proteins COL1A1, OPN, OCN, SOST, E11 (<b>D</b>) and senescence-associated proteins p53, p21, p16 (<b>F</b>) in the femur was detected by Western blot. Results are shown as the mean ± SD (n = 3). Compared with the control group, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Compared with the Cd group, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Schematic representation of the dual molecular mechanisms by which OPC ameliorates cadmium-induced senescence of osteocytes: (i) suppression of oxidative stress and ROS accumulation through modulating the Nrf2 signaling pathway, and (ii) inhibition of pro-inflammatory cytokine production via regulating the NF-κB signaling. (Red downward arrows represent decreased levels of antioxidant enzyme activity, and red up arrows represent increased levels of inflammatory factors).</p>
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16 pages, 6036 KiB  
Article
Ganoderma lucidum Spore Powder Alleviates Metabolic-Associated Fatty Liver Disease by Improving Lipid Accumulation and Oxidative Stress via Autophagy
by Yuxuan Zhang, Jiali Zhou, Lan Yang, Hang Xiao, Dongbo Liu and Xincong Kang
Antioxidants 2024, 13(12), 1501; https://doi.org/10.3390/antiox13121501 - 9 Dec 2024
Viewed by 751
Abstract
Lipid accumulation and oxidative stress, which could be improved by autophagy, are the “hits” of metabolic-associated fatty liver disease (MAFLD). Ganoderma lucidum spore powder (GLSP) has the effect of improving liver function. However, there are few reports about its effects on and mechanisms [...] Read more.
Lipid accumulation and oxidative stress, which could be improved by autophagy, are the “hits” of metabolic-associated fatty liver disease (MAFLD). Ganoderma lucidum spore powder (GLSP) has the effect of improving liver function. However, there are few reports about its effects on and mechanisms impacting MAFLD alleviation. This study investigated the effect of GLSP on hepatic lipid accumulation and oxidative stress and explored the role that autophagy played in this effect. The results showed that GLSP effectively reduced lipid accumulation and activated autophagy in the livers of mice with high-fat-diet-induced disease and palmitic acid-induced hepatocytes. GLSP reduced the lipid accumulation by reducing lipogenesis and promoting lipid oxidation in HepG2 cells. It decreased the production of ROS, increased the activity of SOD and CAT, and improved the mitochondrial membrane potential via the Keap1/Nrf2 pathway. The alleviating effects of GLSP on the lipid accumulation and oxidative stress was reversed by 3-methyladenine (3-MA), an autophagy inhibitor. GLSP activated autophagy via the AMPK pathway in HepG2 cells. In conclusion, GLSP could attenuate MAFLD by the improvement of lipid accumulation and oxidative stress via autophagy. This paper is the first to report the improvement of MAFLD through autophagy promotion. It will shed novel light on the discovery of therapeutic strategies targeting autophagy for MAFLD. Full article
(This article belongs to the Section Health Outcomes of Antioxidants and Oxidative Stress)
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<p>GLSP alleviated high-fat-induced MAFLD in mice. (<b>A</b>) Food intake (<span class="html-italic">n</span> = 12 in each group), (<b>B</b>) body weight (<span class="html-italic">n</span> = 12 in each group), and (<b>C</b>) body weight gain (<span class="html-italic">n</span> = 12 in each group); (<b>D</b>) representative images of livers; (<b>E</b>) liver weight (<span class="html-italic">n</span> = 12 in each group); (<b>F</b>) liver index (weight of liver/weight of body; <span class="html-italic">n</span> = 12 in each group); (<b>G</b>) representative images of H&amp;E and Oil Red O staining of liver; (<b>H</b>) TG and TC levels in liver and serum (<span class="html-italic">n</span> = 6 in each group). NCD: control group; HFD: high-fat diet group; SIM: simvastatin (15 mg/kg b.w/day) group; GLSP: GLSP (3%) group. Data are expressed as mean ± SEM, and different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). Statistical differences were assessed by Tukey’s test of one-way ANOVA.</p>
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<p>GLSP reduced palmitic acid (PA)-induced lipid accumulation in HepG2 cells. (<b>A</b>) Effects of 0, 200, 400, 800, 1600, and 3200 μg/mL of GLSP on cell viability after 12 h treatment. (<b>B</b>) Intracellular lipid accumulation was analyzed by Oil red O staining; scale bars, 50 μm. (<b>C</b>,<b>D</b>) Intracellular TG and TC levels in HepG2 cells. (<b>E</b>) Western blot analysis of ACC, FASN, SREBP1, ACOX1, CPT1A, PPARα, and GAPDH protein levels. HepG2 cells treated with or without PA (0.6 mM) and with or without GLSP (50, 200, 800 μg/mL). Data are expressed as mean ± SEM, and different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). Statistical differences were assessed by Tukey’s test of one-way ANOVA.</p>
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<p>Effect of GLSP on PA-induced oxidative stress in HepG2 cells. (<b>A</b>) ROS production detected by DCFH-DA detector; scale bars, 50 μm. (<b>B</b>) SOD activity was measured with Total Superoxide Dismutase Assay Kit with WST-8. (<b>C</b>) CAT activity was measured with Micro CAT Assay Kit. (<b>D</b>) Effect of GLSP on mitochondrial damage. GLSP was added into HepG2 cells for 12 h. Representative images of JC-1-derived red and green fluorescence; scale bars, 50 μm. (<b>E</b>) Western blot analysis of Keap1, Nrf2, and HO-1 protein levels with GAPDH as control. HepG2 cells treated with or without PA (0.6 mM) and with or without GLSP (50, 200, 800 μg/mL). Data are expressed as mean ± S.E., and different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). Statistical differences were assessed by Tukey’s test of one-way ANOVA.</p>
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<p>GLSP induced autophagy in vivo and in vitro and activated autophagy via AMPK signal pathway in HepG2 cells. (<b>A</b>) Representative images of LC3 immunohistochemistry of liver sections. (<b>B</b>) LC3 immunofluorescence staining in HepG2 cells; scale bars, 10 μm. Liver sections or HepG2 cells were stained with anti-LC3 antibody and observed with laser confocal microscope. (<b>C</b>) Effects of GLSP on protein expressions of autophagic indicators LC3, P-AMPK/AMPK, and P-mTOR/mTOR in HepG2 cells, with GAPDH as control. HepG2 cells were treated with or without PA (0.6 mM) and with or without GLSP (50, 200, 800 μg/mL).</p>
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<p>GLSP improved lipid accumulation in HepG2 cells by inducing autophagy. HepG2 cells were treated with 800 µg/mL of GLSP and 3 mM of 3-MA for 12 h and then treated with PA (0.6 mM) for 12 h. (<b>A</b>) LC3 immunofluorescence staining showed endogenous LC3 level of HepG2 cells; scale bars, 10 μm. (<b>B</b>) Western blot analysis of LC3, P-AMPK/AMPK, and P-mTOR/mTOR protein levels, with GAPDH as control. (<b>C</b>) Intracellular lipid accumulation was analyzed by Oil Red O staining; scale bars, 50 μm. (<b>D</b>,<b>E</b>) Intracellular TG and TC levels in HepG2 cells. (<b>F</b>) Western blot analysis of P-ACC/ACC, FASN, SREBP1, ACOX1, CPT1A, and PPARα protein levels, with GAPDH as control. Data are expressed as mean ± SEM, and different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). Statistical differences were assessed by Tukey’s test of one-way ANOVA.</p>
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<p>Autophagy contributed to effect of GLSP protecting HepG2 cells from oxidative stress under PA stress. HepG2 cells were treated with 800 µg/mL of GLSP and/or 3 mM of 3-MA for 12 h and then treated with 0.6 mM PA for 12 h. (<b>A</b>) Intracellular ROS in HepG2 cells after fluorescence staining is exhibited; scale bars, 50 µm. (<b>B</b>,<b>C</b>) SOD and CAT were measured with Total Superoxide Dismutase Assay Kit with WST-8 and Micro Catalase (CAT) Assay Kit in HepG2 cells. (<b>D</b>) Representative images of JC-1-derived red and green fluorescence of HepG2 cells treated with or without 3-MA; scale bars, 50 µm. (<b>E</b>) Effect of GLSP on protein expression of Keap1, Nrf2, and HO-1 protein levels with or without autophagy inhibitor 3-MA. GAPDH was used as control. Data are expressed as mean ± S.E., and different letters indicate significant differences (<span class="html-italic">p</span> &lt; 0.05). Statistical differences were assessed by Tukey’s test of one-way ANOVA.</p>
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10 pages, 2726 KiB  
Brief Report
Effect of Biopesticide Novochizol on Development of Stem Rust Puccinia graminis f. sp. tritici in Wheat, T. aestivum L.
by Andrey B. Shcherban, Ekaterina S. Skolotneva, Anna V. Fedyaeva, Natalya I. Boyko and Vladislav V. Fomenko
Plants 2024, 13(23), 3455; https://doi.org/10.3390/plants13233455 - 9 Dec 2024
Viewed by 689
Abstract
The use of biological plant protection products is promising for agriculture. In particular, chitosan-based biopesticides have become widespread for stimulating growth and protecting plants from a wide range of pathogens. Novochizol is a product obtained by intramolecular cross-linking of linear chitosan molecules and [...] Read more.
The use of biological plant protection products is promising for agriculture. In particular, chitosan-based biopesticides have become widespread for stimulating growth and protecting plants from a wide range of pathogens. Novochizol is a product obtained by intramolecular cross-linking of linear chitosan molecules and has a globular shape, which provides it with a number of advantages over chitosan. Novochizol has previously been shown to have a stimulating effect on the growth and development of common wheat (Triticum aestivum L.). However, the effect of this preparation on the protective mechanisms against rust diseases has not been studied before. Our studies have revealed the dose effect of the preparation on the development of stem rust of wheat. When treating plants with novochizol at a concentration of 0.125% four days before infection, the best results were obtained, namely: a stable reaction was observed and the number of pustules decreased. To identify critical points of the drug’s effect on the protective mechanism against stem rust, we used an adrenaline test, which allows for a quick assessment of the pro/antioxidant status of plant extracts. We also assessed the activity of the major antioxidant enzymes, peroxidase and catalase, using commercial kits and the Folin–Ciocalteu reaction to assess the concentration of phenolic compounds. As a result, two stages were identified in infected plants pretreated with novochizol: early (up to 10 h after inoculation), characterized by antioxidant activity, and late (10–244 h), with prooxidant activity. These stages correspond to two peaks of accumulation of reactive oxygen species (ROS) in response to pathogen infection. The first peak is associated with the accumulation of superoxide anion O2−, which is converted into oxygen and hydrogen peroxide under the action of the enzyme SOD (superoxide dismutase). The second peak is associated with the accumulation of H2O2. Hydrogen peroxide performs a protective function leading to the death of pathogen mycelial cells. In comparison with infected plants without novochizol treatment, we found a decrease in the activity of catalase (an enzyme that breaks down H2O2) at both stages, as well as peroxidase in the interval from 10 to 144 h after inoculation. Also, an increase in the concentration of phenolic compounds was found in the treated infected plants. We suggest that these changes under the influence of pretreatment with novochizol contribute to enhancements in plant defense functions against stem rust. Taking into account the physicochemical advantages of novochizol over chitosan, which provide a very low effective dose of the drug, the obtained results indicate its promise and safety as a biological plant protection product. This work is a preliminary stage for an extended analysis of the effect of novochizol on plant immunity using biochemical and molecular genetic approaches. Full article
(This article belongs to the Special Issue Strategies and Mechanisms for Enhancing Stress Tolerance in Wheat)
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<p>Visual assessment of the novochizol effect on the stem rust development. c—control plants treated with water; 0.125; 0.75; 1.5; 2.5—the different concentrations of novochizol (in %) used to treat plants before infection with stem rust pathogen. The sensitivity indices of IT are indicated above the figure.</p>
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<p>Changes in pro/antioxidant activity (<b>A</b>), total phenol content (<b>B</b>), catalase activity (<b>C</b>) and peroxidase activity (<b>D</b>) in leaves of common wheat after treatment with 0.125% novochizol and inoculation with urediniospores of the West Siberian population <span class="html-italic">Pgt</span>. Designations: C—control; N—novochizol treatment; In—inoculation; N+In—novochizol treatment and inoculation. <span class="html-italic">p</span> values * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, when compared with control plants at the same time point.</p>
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19 pages, 1541 KiB  
Review
Protective, Anti-Inflammatory, and Anti-Aging Effects of Soy Isoflavones on Skin Cells: An Overview of In Vitro and In Vivo Studies
by Magdalena Wójciak, Piotr Drozdowski, Agnieszka Skalska-Kamińska, Martyna Zagórska-Dziok, Aleksandra Ziemlewska, Zofia Nizioł-Łukaszewska and Małgorzata Latalska
Molecules 2024, 29(23), 5790; https://doi.org/10.3390/molecules29235790 - 7 Dec 2024
Viewed by 643
Abstract
Isoflavones are found in numerous plant species within the Leguminosae family; however, soy isoflavones are particularly significant in practice and have been extensively studied in recent years. The health-promoting potential of orally administered soy isoflavones is widely documented in the scientific literature, and [...] Read more.
Isoflavones are found in numerous plant species within the Leguminosae family; however, soy isoflavones are particularly significant in practice and have been extensively studied in recent years. The health-promoting potential of orally administered soy isoflavones is widely documented in the scientific literature, and many review articles have been developed to highlight their significance. However, it should be noted that soy-isoflavone-rich extracts and isolated soy isoflavones, such as genistein and daidzein, are also often applied topically as ingredients in many formulations, including face creams, tonics, and emulsions. New delivery systems are continuously being developed to enhance the skin permeability of isoflavones, thus improving their efficacy. In this context, their direct activity on skin cells is an important aspect of scientific research. The anti-inflammatory, protective, and antioxidant properties of isoflavones and soy extracts make them promising cosmetic ingredients with anti-aging potential because inflammation and the accumulation of reactive oxygen species (ROS) can lead to structural and functional changes in skin cells, accelerating the aging process. This review provides an overview of research on the impact of the application of soy isoflavone extract and soy-derived isoflavones on skin cells, with a focus on the documented molecular mechanisms underlying their effects. This study aims to offer essential insights to aid in the development of functional cosmetics and future clinical applications. Full article
(This article belongs to the Special Issue Flavonoids and Derivatives: One Health Approach)
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<p>General structure of flavonoids and isoflavones and the chemical structure of aglycone forms of soy isoflavones: (<b>a</b>) daidzein, (<b>b</b>) genistein, and (<b>c</b>) glycitein.</p>
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<p>Comparison of chemical structure of daidzein (green) and 17β-estradiol (red).</p>
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<p>Diagram illustrating the molecular mechanisms studied for the protective effects of isoflavones on skin cells exposed to external stimuli. Reactive oxygen species (ROS) activate signaling pathways, including nuclear factor kappa B (NF-κB), phosphoinositide 3-kinase-protein kinase B (PI3K-Akt), signal transducer and activator of transcription 3 (STAT3), and mitogen-activated protein kinases (MAPK). These pathways can further induce inflammatory responses and promote the degradation of extracellular matrix (ECM) components, thereby contributing to skin damage and aging. In addition, ROS activate antioxidant enzyme systems, including catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx), which help mitigate oxidative stress and protect skin cells from damage.</p>
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