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12 pages, 2618 KiB  
Article
Pathological and Molecular Characterization of Grass Carp Co-Infected with Two Aeromonas Species
by Wenyao Lv, Zhijie Zhou, Lingli Xie, Xinyue Wang, Yifei Zhou, Lang Gui, Xiaoyan Xu, Yubang Shen, Jiale Li and Junqiang Qiu
Animals 2025, 15(2), 263; https://doi.org/10.3390/ani15020263 (registering DOI) - 18 Jan 2025
Viewed by 283
Abstract
The grass carp (Ctenopharyngodon idella) is highly susceptible to infections caused by Aeromonas species, particularly A. hydrophila and A. veronii. However, the immunological mechanisms underlying co-infection by these pathogens remain largely uncharted. This study investigated the pathogenesis and host immune [...] Read more.
The grass carp (Ctenopharyngodon idella) is highly susceptible to infections caused by Aeromonas species, particularly A. hydrophila and A. veronii. However, the immunological mechanisms underlying co-infection by these pathogens remain largely uncharted. This study investigated the pathogenesis and host immune response in grass carp following concurrent infection with A. hydrophila and A. veronii. Mortality was observed as early as 24 h post-infection, with cumulative mortality reaching 68%. Quantitative analysis demonstrated significantly elevated bacterial loads in hepatic tissue at 3 days post-infection (dpi). Histopathological evaluation revealed severe hepatic lesions characterized by cellular necrosis, cytoplasmic vacuolization, and hemorrhagic manifestations. Comparative transcriptomic analysis of hepatic tissues between co-infected and control specimens identified 868 and 411 differentially expressed genes (DEGs) at 1 and 5 dpi, respectively. Gene ontology and KEGG pathway analyses revealed significant enrichment of immune-related genes primarily associated with Toll-like receptor signaling and TNF signaling cascades. Notably, metabolic pathways showed substantial suppression while immune responses were significantly activated after infected. These findings provide novel insights into the host–pathogen interactions during Aeromonas co-infection in grass carp, which may facilitate the development of effective prevention and control strategies. Full article
(This article belongs to the Section Aquatic Animals)
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Figure 1

Figure 1
<p>Survival curve and hepatic bacterial load changes in grass carp co-infected with <span class="html-italic">A. hydrophila</span> and <span class="html-italic">A. veronii</span>. (<b>A</b>) Survival curve of grass carp co-infected with <span class="html-italic">A. hydrophila</span> and <span class="html-italic">A. veronii</span>. (<b>B</b>) Changes in hepatic bacterial load in grass carp co-infected with <span class="html-italic">A. hydrophila</span> and <span class="html-italic">A. veronii.</span>(“***” indicates <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 2
<p>Histological effects of co-infection of <span class="html-italic">A. hydrophila</span> and <span class="html-italic">A. veronii</span> on liver of grass carp. (<b>A</b>–<b>E</b>): infected for 0, 1, 3, 5, and 7 days. The arrows indicate apoptotic cells.</p>
Full article ">Figure 3
<p>Sample relationship analysis. (<b>A</b>) Principal component analysis (PCA) of the genes in terms of variance across samples. (<b>B</b>) Sample correlation heat map.</p>
Full article ">Figure 4
<p>DEGs expression analysis. (<b>A</b>) Summary of differential gene expression between two experimental groups. (<b>B</b>) Expression pattern clustering analysis of differentially expressed genes. (<b>C</b>) Volcano plot of DEGs in the L1 vs. L0 group. (<b>D</b>) Volcano plot of DEGs in the L5 vs. L0 group.</p>
Full article ">Figure 5
<p>GO and KEGG function enrichment analysis of DEGs. (<b>A</b>) GO function enrichment analysis of the L1 vs. L0 group (top 10 enriched terms). (<b>B</b>) GO function enrichment analysis of the L5 vs. L0 group (top 10 enriched terms). (<b>C</b>) KEGG function enrichment analysis of the L1 vs. L0 group (top 10 enriched terms). (<b>D</b>) KEGG function enrichment analysis of the L5 vs. L0 group (top 10 enriched terms).</p>
Full article ">Figure 6
<p>PPI networks of selected key DEGs. The red color indicates the metabolism-related DEGs; the green color indicates the immune-related DEGs.</p>
Full article ">
10 pages, 1537 KiB  
Communication
Establishment of a Rapid and Convenient Fluoroimmunoassay Platform Using Antibodies Against PDL1 and HER2
by Ji Eun Choi, Hanool Yun and Hee-Jin Jeong
Curr. Issues Mol. Biol. 2025, 47(1), 62; https://doi.org/10.3390/cimb47010062 - 17 Jan 2025
Viewed by 534
Abstract
The development of accurate and high-throughput tools for cancer biomarker detection is crucial for the diagnosis, monitoring, and treatment of diseases. In this study, we developed a simple and rapid fluorescence-linked immunosorbent assay (FLISA) using fluorescent dye-conjugated antibody fragments against programmed cell death [...] Read more.
The development of accurate and high-throughput tools for cancer biomarker detection is crucial for the diagnosis, monitoring, and treatment of diseases. In this study, we developed a simple and rapid fluorescence-linked immunosorbent assay (FLISA) using fluorescent dye-conjugated antibody fragments against programmed cell death ligand 1 (PDL1) and human epithelial growth factor receptor 2 (HER2). We optimized key steps in the FLISA process, including antigen immobilization, blocking, and antibody reaction, reading the assay time to 3 h—significantly faster compared to the 23 h duration of usual FLISA. The limit of detection for the rapid FLISA in detecting PDL1 was lower than that of FLISA, and the detection of HER2 was similar between the two methods, indicating that the rapid FLISA provides a fast and accurate approach for detecting PDL1 and HER2. This robust platform can be readily adapted for various fluoroimmunoassays targeting other antigens of interest. Full article
(This article belongs to the Section Biochemistry, Molecular and Cellular Biology)
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Figure 1

Figure 1
<p>Schematic representation of the fluorescence-linked immunosorbent assay (FLISA) and rapid FLISA methods. Optimization of FLISA was performed in this study by adjusting the reaction time of each step. RT indicates room temperature.</p>
Full article ">Figure 2
<p>(<b>A</b>–<b>D</b>) Titration curves with different antigen immobilization conditions. (<b>E</b>–<b>H</b>) Titration curves with different blocking conditions. (<b>I</b>–<b>L</b>) Titration curves with different fluorescent antibody reaction conditions. (<b>A</b>,<b>E</b>,<b>I</b>) Fluorescence response in the presence of phosphate-buffered saline (PBS) for human epithelial growth factor receptor 2 (HER2) detection. (<b>B</b>,<b>F</b>,<b>J</b>) Fluorescence response in the presence of PBS for programmed cell death ligand 1 (PDL1) detection. (<b>C</b>,<b>G</b>,<b>K</b>) Fluorescence response in the presence of denaturant (7 M guanidine hydrochloride with 100 mM dithiothreitol in distilled water) for HER2 detection. (<b>D</b>,<b>H</b>,<b>L</b>) Fluorescence response in the presence of denaturant for PDL1 detection. Fluorescence intensity at 580 nm in the presence of the indicated antigen concentration was plotted in each titration curve. Error bars represent ±1 SD (<span class="html-italic">n</span> = 3). SD = standard deviation. RT indicates room temperature.</p>
Full article ">Figure 3
<p>(<b>A</b>–<b>D</b>) Fluorescence spectra of fluorescence-linked immunosorbent assay (FLISA) (antigen immobilization for 20 h, blocking for 2 h, and fluorescent antibody binding for 1 h) in the presence of phosphate-buffered saline (PBS) or denaturant (7 M guanidine hydrochloride with 100 mM dithiothreitol in distilled water) for programmed cell death ligand 1 (PDL1) or human epithelial growth factor receptor 2 (HER2) detection. (<b>E</b>–<b>H</b>) Fluorescence spectra of rapid FLISA (antigen immobilization for 2 h and fluorescent antibody binding for 1 h) in the presence of PBS or denaturant for PDL1 or HER2 detection. (<b>I</b>–<b>L</b>) Normalized fluorescence intensity of FLISA or rapid FLISA in the presence of PBS or denaturant for PDL1 or HER2 detection. Normalized fluorescence intensity (F.I.) was calculated by dividing the F.I. of each sample with the indicated antigen concentration by the F.I. of the sample without antigen. Error bars represent ±1 SD (<span class="html-italic">n</span> = 3). SD = standard deviation.</p>
Full article ">
54 pages, 6031 KiB  
Article
(E)-1-(3-(3-Hydroxy-4-Methoxyphenyl)-1-(3,4,5-Trimethoxyphenyl)allyl)-1H-1,2,4-Triazole and Related Compounds: Their Synthesis and Biological Evaluation as Novel Antimitotic Agents Targeting Breast Cancer
by Gloria Ana, Azizah M. Malebari, Sara Noorani, Darren Fayne, Niamh M. O’Boyle, Daniela M. Zisterer, Elisangela Flavia Pimentel, Denise Coutinho Endringer and Mary J. Meegan
Pharmaceuticals 2025, 18(1), 118; https://doi.org/10.3390/ph18010118 - 17 Jan 2025
Viewed by 344
Abstract
Background/Objectives: The synthesis of (E)-1-(1,3-diphenylallyl)-1H-1,2,4-triazoles and related compounds as anti-mitotic agents with activity in breast cancer was investigated. These compounds were designed as hybrids of the microtubule-targeting chalcones, indanones, and the aromatase inhibitor letrozole. Methods: A panel of [...] Read more.
Background/Objectives: The synthesis of (E)-1-(1,3-diphenylallyl)-1H-1,2,4-triazoles and related compounds as anti-mitotic agents with activity in breast cancer was investigated. These compounds were designed as hybrids of the microtubule-targeting chalcones, indanones, and the aromatase inhibitor letrozole. Methods: A panel of 29 compounds was synthesized and examined by a preliminary screening in estrogen receptor (ER) and progesterone receptor (PR)-positive MCF-7 breast cancer cells together with cell cycle analysis and tubulin polymerization inhibition. Results: (E)-5-(3-(1H-1,2,4-triazol-1-yl)-3-(3,4,5-trimethoxyphenyl)prop-1-en-1-yl)-2-methoxyphenol 22b was identified as a potent antiproliferative compound with an IC50 value of 0.39 mM in MCF-7 breast cancer cells, 0.77 mM in triple-negative MDA-MB-231 breast cancer cells, and 0.37 mM in leukemia HL-60 cells. In addition, compound 22b demonstrated potent activity in the sub-micromolar range against the NCI 60 cancer cell line panel including prostate, melanoma, colon, leukemia, and non-small cell lung cancers. G2/M phase cell cycle arrest and the induction of apoptosis in MCF-7 cells together with inhibition of tubulin polymerization were demonstrated. Immunofluorescence studies confirmed that compound 22b targeted tubulin in MCF-7 cells, while computational docking studies predicted binding conformations for 22b in the colchicine binding site of tubulin. Compound 22b also selectively inhibited aromatase. Conclusions: Based on the results obtained, these novel compounds are suitable candidates for further investigation as antiproliferative microtubule-targeting agents for breast cancer. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Drugs for the treatment of breast cancer: SERMs (tamoxifen <b>1a</b>, 4-hydroxytamoxifen <b>1b</b>, endoxifen <b>1c</b>, norendoxifen <b>1d</b>), SERD fulvestrant <b>2</b>, PROTAC elacestrant <b>3</b>, ARV-471 <b>4</b>, aromatase inhibitors (exemestane <b>5</b>, letrozole <b>6</b>, and anastrozole <b>7</b>).</p>
Full article ">Figure 2
<p>Targeted therapies for breast cancer: CDK4/6 inhibitors palbociclib <b>8</b>, ribociclib <b>9</b>, and abemacicilib <b>10</b>, mTOR inhibitor everolimus <b>11</b>; PI3K inhibitor alpelisib <b>12</b>, AKT inhibitor capivasertib <b>13</b>; PARP inhibitors olaparib <b>14</b>, and talazoparib <b>15</b>.</p>
Full article ">Figure 3
<p>Antiproliferative chalcones and related compounds that target the colchicine binding site of tubulin: α-methylchalcones <b>16a–e</b>, O-arylchalcone <b>16f</b>, millepachine <b>17</b>, bischalcone <b>18</b>, combretastatins CA-4 <b>19a</b> and CA-1 <b>19b</b>, and phenstatin <b>19c</b>.</p>
Full article ">Figure 4
<p>Target structures <b>A</b> (chalcone-based) and <b>B</b> (indane-based) for synthesis.</p>
Full article ">Figure 5
<p>Preliminary cell viability data for Series 1: (<b>A</b>) compounds <b>22a–22g</b> and chalcone <b>20b</b> and Series 2: (<b>B</b>) compounds <b>23a–e</b> and chalcone <b>20b</b> in MCF-7 breast cancer cells. Cell proliferation of MCF-7 cells was determined with an alamarBlue assay (seeding density 2.5 × 10<sup>4</sup> cells/mL per well for 96-well plates). Compound concentrations of either 1 or 0.1 μM for 72 h were used to treat the cells (in triplicate) with control wells containing vehicle ethanol (1% <span class="html-italic">v</span>/<span class="html-italic">v</span>). The mean value ± SEM for three independent experiments is shown. The positive controls used are CA-4 and phenstatin (1.0 μM and 0.1 μM). Statistical analysis was performed using One-way ANOVA with the Sidak multiple comparison test (***, <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 6
<p>Preliminary cell viability data for (<b>A</b>) triazoles <b>26a–e</b> and related indanone <b>24a</b> and (<b>B</b>) imidazoles <b>27a–f</b>, <b>27h</b>, <b>27i</b> and related compounds <b>30</b> and <b>33b</b> in MCF-7 breast cancer cells. Cell proliferation of MCF-7 cells was determined with an alamarBlue assay (seeding density 2.5 × 10<sup>4</sup> cells/mL per well for 96-well plates). Compound concentrations of either 1 or 0.1 μM for 72 h were used to treat the cells (in triplicate) with control wells containing vehicle ethanol (1% <span class="html-italic">v</span>/<span class="html-italic">v</span>). The mean value ± SEM for three independent experiments is shown. The positive controls used were CA-4 and phenstatin (1.0 μM and 0.1 μM). Statistical test was performed using One-way ANOVA with Sidak multiple comparison test (***, <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 6 Cont.
<p>Preliminary cell viability data for (<b>A</b>) triazoles <b>26a–e</b> and related indanone <b>24a</b> and (<b>B</b>) imidazoles <b>27a–f</b>, <b>27h</b>, <b>27i</b> and related compounds <b>30</b> and <b>33b</b> in MCF-7 breast cancer cells. Cell proliferation of MCF-7 cells was determined with an alamarBlue assay (seeding density 2.5 × 10<sup>4</sup> cells/mL per well for 96-well plates). Compound concentrations of either 1 or 0.1 μM for 72 h were used to treat the cells (in triplicate) with control wells containing vehicle ethanol (1% <span class="html-italic">v</span>/<span class="html-italic">v</span>). The mean value ± SEM for three independent experiments is shown. The positive controls used were CA-4 and phenstatin (1.0 μM and 0.1 μM). Statistical test was performed using One-way ANOVA with Sidak multiple comparison test (***, <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 7
<p>Preliminary cell viability data for (<b>A</b>) triazoles <b>22b–d</b>, <b>22f</b>, <b>22g</b> and imidazole <b>23d</b> and (<b>B</b>) triazoles <b>26a–e</b> and imidazoles <b>27a</b>, <b>27b</b>, <b>27e</b>, <b>27f</b>, <b>27h</b> and <b>27i</b> in HL-60 cells. Cell proliferation of HL-60 cells was determined with an alamarBlue assay (seeding density 2.5 × 10<sup>4</sup> cells/mL per well for 96-well plates). Compound concentrations of either 1 or 0.1 μM for 72 h were used to treat the cells (in triplicate) with control wells containing vehicle ethanol (1% <span class="html-italic">v</span>/<span class="html-italic">v</span>). The mean value ± SEM for three independent experiments is shown. The positive control was CA-4 (1.0 μM and 0.1 μM).</p>
Full article ">Figure 7 Cont.
<p>Preliminary cell viability data for (<b>A</b>) triazoles <b>22b–d</b>, <b>22f</b>, <b>22g</b> and imidazole <b>23d</b> and (<b>B</b>) triazoles <b>26a–e</b> and imidazoles <b>27a</b>, <b>27b</b>, <b>27e</b>, <b>27f</b>, <b>27h</b> and <b>27i</b> in HL-60 cells. Cell proliferation of HL-60 cells was determined with an alamarBlue assay (seeding density 2.5 × 10<sup>4</sup> cells/mL per well for 96-well plates). Compound concentrations of either 1 or 0.1 μM for 72 h were used to treat the cells (in triplicate) with control wells containing vehicle ethanol (1% <span class="html-italic">v</span>/<span class="html-italic">v</span>). The mean value ± SEM for three independent experiments is shown. The positive control was CA-4 (1.0 μM and 0.1 μM).</p>
Full article ">Figure 8
<p>Heatmap for compound <b>22b</b> across cell lines in the NCI-60 cell screen. Heatmap for the antiproliferative activity of compound <b>22b</b> (NCI 788807), across the cell lines in the NCI-60 screen, using three different values: (growth-inhibitory effect, GI<sub>50</sub>; drug concentration at which the response is reduced by half, IC<sub>50</sub>; cytostatic effect, TGI; cytotoxic effect, LC<sub>50</sub>; concentration in molar). Color key for GI<sub>50</sub> and IC<sub>50</sub>: green is more sensitive, and red is less sensitive.</p>
Full article ">Figure 9
<p>Effect of compounds <b>22a</b> (<b>A</b>) and <b>22b</b> (<b>B</b>) on the cell viability of non-tumorigenic MCF-10A human mammary epithelial cells at 24, 48, and 72 h. Cells were treated with the compounds <b>22a</b> and <b>22b</b> at concentrations of 10 μM, 1 μM, 0.5 μM, and 0.4 μM for 24, 48, or 72 h. (<b>C</b>) shows a comparison of the cell viability of MCF-10A cells and MCF-7 cells when treated with compound <b>22b</b> for 72 h at concentrations of 10 μM, 1 μM, and 0.5 μM. Cell viability was expressed as a percentage of vehicle control (ethanol 1% (<span class="html-italic">v</span>/<span class="html-italic">v</span>)) and was determined by an alamarBlue assay (average ± SEM of three independent experiments). Two-way ANOVA (Bonferroni post-test) was used to test for statistical significance (*, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 10
<p>Compound (<b>A</b>) <b>22b</b>, (<b>B</b>) phenstatin <b>19c</b> induced apoptosis in a time-dependent manner in MCF-7 cells. Cells were treated with either vehicle control [0.1% ethanol (<span class="html-italic">v</span>/<span class="html-italic">v</span>)] or compound <b>22b</b> or phenstatin <b>19c</b> (1 μM) for 24, 48, and 72 h). The data shown for the control vehicle and phenstatin are as we previously reported [<a href="#B65-pharmaceuticals-18-00118" class="html-bibr">65</a>]. Cells were fixed and stained with PI, followed by analysis using flow cytometry. Cell cycle analysis was performed on histograms of gated counts per DNA area (FL2-A). The number of cells with &lt;2 N (sub-G<sub>1</sub>), 2 N (G<sub>0</sub>G<sub>1</sub>), and 4 N (G<sub>2</sub>/M) DNA content was determined with CellQuest software, BD CellQuest Pro. Values are represented as the mean ± SEM for three separate experiments. Two-way ANOVA (Bonferroni post-test) was used to test for statistical significance (*, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 11
<p>Compound <b>22b</b> induced apoptosis in (<b>A</b>) MCF-7 breast cancer cells and (<b>B</b>) MDA-MB-231 breast cancer cells. MCF-7 breast cancer cells (<b>A</b>) and MDA-MB-23 breast cancer cells (<b>B</b>) were treated with <b>22b</b> (0.1, 0.5, and 1.0 μM) or phenstatin (<b>19c</b>) (0.1 μM and 0.5 μM) or control vehicle (0.1% ethanol (<span class="html-italic">v</span>/<span class="html-italic">v</span>)). The data shown for the control vehicle and phenstatin are as we previously reported [<a href="#B65-pharmaceuticals-18-00118" class="html-bibr">65</a>]. The apoptotic cell content was determined by staining with Annexin V-FITC and PI. In each panel, the lower right quadrant shows Annexin-positive cells in the early apoptotic stage and the upper right shows both Annexin/PI-positive cells in late apoptosis/necrosis. The lower left quadrant shows cells that are negative for both PI and Annexin V-FITC, and the upper left shows PI cells that are necrotic.</p>
Full article ">Figure 11 Cont.
<p>Compound <b>22b</b> induced apoptosis in (<b>A</b>) MCF-7 breast cancer cells and (<b>B</b>) MDA-MB-231 breast cancer cells. MCF-7 breast cancer cells (<b>A</b>) and MDA-MB-23 breast cancer cells (<b>B</b>) were treated with <b>22b</b> (0.1, 0.5, and 1.0 μM) or phenstatin (<b>19c</b>) (0.1 μM and 0.5 μM) or control vehicle (0.1% ethanol (<span class="html-italic">v</span>/<span class="html-italic">v</span>)). The data shown for the control vehicle and phenstatin are as we previously reported [<a href="#B65-pharmaceuticals-18-00118" class="html-bibr">65</a>]. The apoptotic cell content was determined by staining with Annexin V-FITC and PI. In each panel, the lower right quadrant shows Annexin-positive cells in the early apoptotic stage and the upper right shows both Annexin/PI-positive cells in late apoptosis/necrosis. The lower left quadrant shows cells that are negative for both PI and Annexin V-FITC, and the upper left shows PI cells that are necrotic.</p>
Full article ">Figure 12
<p>Compound <b>22b</b> depolymerizes the microtubule network of MCF-7 breast cancer cells. MCF-7 breast cancer cells were treated with (<b>A</b>) vehicle control [1% ethanol (<span class="html-italic">v</span>/<span class="html-italic">v</span>)], (<b>B</b>) paclitaxel (1 μM), (<b>C</b>) phenstatin (<b>19c</b>) (1 μM), or (<b>D</b>) compound <b>22b</b> (10 μM) for 16 h. Cells were preserved in ice-cold methanol and then stained with mouse monoclonal anti-α-tubulin–FITC–antibody (clone DM1A) (green), Alexa Fluor 488 dye, and counterstained with DAPI (blue). The micrograph images were obtained with Leica SP8 confocal microscopy utilizing Leica application suite X software. Representative confocal images of three separate experiments are shown. The scale bar indicates 25 μm.</p>
Full article ">Figure 13
<p>Inhibition of tubulin polymerization in vitro by compound <b>22b</b>. Tubulin polymerization assay for triazole compound <b>22b</b> at 10 μM and 30 μM concentration, together with control compounds paclitaxel (polymeriser) (10 μM) and phenstatin (depolymeriser) <b>19c</b> (10 μM). DMSO (1% <span class="html-italic">v</span>/<span class="html-italic">v</span>) was used in the vehicle control. Purified bovine tubulin and guanosine-5′-triphosphate (GTP) were initially mixed at 4 °C in a 96-well plate; the polymerization reaction was then initiated by warming the solution from 4 to 37 °C. The progress of the tubulin polymerization reaction at 37 °C was monitored at 340 nm in a Spectramax 340PC spectrophotometer at 30 s intervals for 60 min. Fold inhibition of tubulin polymerization can be calculated from the Vmax value for each reaction. The data shown for the control vehicle and phenstatin are as we previously reported [<a href="#B65-pharmaceuticals-18-00118" class="html-bibr">65</a>].</p>
Full article ">Figure 14
<p>Docking of compounds <b>22b</b> in the colchicine binding site of tubulin. Overlay of the X-ray structure of tubulin co-crystallized with DAMA-colchicine (PDB entry 1SA0, [<a href="#B116-pharmaceuticals-18-00118" class="html-bibr">116</a>]) on the best-ranked docked poses of <span class="html-italic">(S)-</span><b>22b</b> and <span class="html-italic">(R)-</span><b>22b</b>. Ligands are rendered as tubes and amino acids as lines. Tubulin amino acids and DAMA-colchicine are colored by atom type; the novel compounds are colored green. The atoms are colored by element type, carbon = grey, hydrogen = white, oxygen = red, nitrogen = blue, sulfur = yellow. Key amino acid residues are labeled, and multiple residues are hidden to enable a clearer view.</p>
Full article ">Scheme 1
<p>Synthesis of (<span class="html-italic">E</span>)-1-(3-aryl)-1-(3,4,5-trimethoxyphenyl)allyl)-1<span class="html-italic">H</span>-1,2,4-triazoles <b>22a–g</b> (Series 1) and (<span class="html-italic">E</span>)-1-(3-(aryl)-1-(3,4,5-trimethoxyphenyl)allyl)-1<span class="html-italic">H</span>-imidazoles <b>23a–e</b> (Series 2): reagents and conditions (<b>a</b>): KOH, methanol, 20 °C (27–87%) (<b>b</b>): NaBH<sub>4</sub>, MeOH/THF, 1 h, 20 °C (85–100%); (<b>c</b>) <span class="html-italic">p</span>-TSA, 1,2,4-triazole, toluene, microwave, 4 h (30–76%); (<b>d</b>) CDI, dry ACN, reflux, 1 h (26–45%).</p>
Full article ">Scheme 2
<p>Synthesis of 1-(3-aryl-4,5,6-trimethoxy-2,3-dihydro-1<span class="html-italic">H</span>-inden-1-yl)-1<span class="html-italic">H</span>-1,2,4-triazoles <b>26a–e</b> (Series 3) and 1-(3-aryl-4,5,6-trimethoxy-2,3-dihydro-1<span class="html-italic">H</span>-inden-1-yl)-1<span class="html-italic">H</span>-imidazoles <b>27a–i</b> (Series 4). Scheme reagents and conditions: (<b>a</b>) TFA, 120 °C, 10 min microwave (44–96%); (<b>b</b>) NaBH<sub>4</sub>, MeOH/THF (1:1), 0–20 °C (43–100%); (<b>c</b>) <span class="html-italic">p</span>-TSA, 1,2,4-triazole, toluene, microwave, 4 h (30–54%); (<b>d</b>) CDI, dry acetonitrile, reflux, 3 h (4–70%).</p>
Full article ">Scheme 3
<p>Synthesis of 1-((1<span class="html-italic">E</span>,4<span class="html-italic">E</span>)-1,5-bis(3,4,5-trimethoxyphenyl)penta-1,4-dien-3-yl)-1<span class="html-italic">H</span>-imidazole <b>30</b>. Reagents and conditions: (<b>a</b>): Acetone, EtOH, NaOH (10%, aqueous), 30 min, 20 °C (68%); (<b>b</b>): NaBH<sub>4</sub>, MeOH/THF, 1 h, 20 °C (92%); (<b>c</b>) CDI, dry ACN, 3 h, reflux (27%).</p>
Full article ">Scheme 4
<p>Synthesis of (<span class="html-italic">E</span>)-3-(anthracen-9-yl)-1-(4-iodophenyl)allyl)-1<span class="html-italic">H</span>-imidazole (<b>33a</b>) and (<span class="html-italic">E</span>)-3-(anthracen-9-yl)-1-(4-pyridyl))allyl)-1<span class="html-italic">H</span>-imidazole (<b>33b</b>): reagents and conditions: (<b>a</b>): KOH, methanol, 20 °C (49–82%) (<b>b</b>): NaBH<sub>4</sub>, MeOH/THF, 1 h, 20 °C (78–98%); (<b>c</b>) CDI, dry ACN, reflux, 1 h (5–58%).</p>
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11 pages, 1230 KiB  
Article
Neuroprotective Actions of Cannabinoids in the Bovine Isolated Retina: Role of Hydrogen Sulfide
by Leah Bush, Anthonia Okolie, Jenaye Robinson, Fatima Muili, Catherine A. Opere, Sunny E. Ohia and Ya Fatou Njie Mbye
Pharmaceuticals 2025, 18(1), 117; https://doi.org/10.3390/ph18010117 - 17 Jan 2025
Viewed by 272
Abstract
Both hydrogen sulfide and endocannabinoids can protect the neural retina from toxic insults under in vitro and in vivo conditions. Purpose: The aim of the present study was two-fold: (a) to examine the neuroprotective action of cannabinoids [methanandamide and 2-arachidonyl glycerol (2-AG)] against [...] Read more.
Both hydrogen sulfide and endocannabinoids can protect the neural retina from toxic insults under in vitro and in vivo conditions. Purpose: The aim of the present study was two-fold: (a) to examine the neuroprotective action of cannabinoids [methanandamide and 2-arachidonyl glycerol (2-AG)] against hydrogen peroxide (H2O2)-induced oxidative damage in the isolated bovine retina and (b) to evaluate the role of endogenously biosynthesized hydrogen sulfide (H2S) in the inhibitory actions of cannabinoids on the oxidative stress in the bovine retina. Methods: Isolated neural retinas from cows were exposed to oxidative damage using H2O2 (100 µM) for 10 min. When used, tissues were pretreated with methanandamide (1 nM–100 nM) and 2-AG (1–10 µM) for 30 min before a 10 min treatment with H2O2 (100 µM). In some experiments, retinas were pretreated with inhibitors of the biosynthesis of H2S [cystathionine β-synthase/cystathionine γ-lyase (CBS/CSE), aminooxyacetic acid, AOAA 30 µM, or 3-mercaptopyruvate sulfurtransferase (3MST), α-keto-butyric acid, KBA 1 mM] and the CB1-receptor antagonist, AM251 (100 nM) for 30 min before treatment with methanandamide (1 nM–100 µM). Enzyme immunoassay measurement of 8-epi PGF2α (8-isoprostane) levels was performed to assess lipid peroxidation in retinal tissues. Results: In the presence of H2O2 (100 µM), methanandamide (1 nM–100 µM) and 2-AG (1–10 µM) significantly (p < 0.001) blocked the H2O2-induced elevation in 8-isoprostane levels in the isolated bovine retina. In the presence of the CB1 antagonist AM251 (100 nM), the effect of methanandamide (1 nM) on the H2O2-induced 8-isoprostane production was significantly (p < 0.001) attenuated. While AOAA (30 µM) had no significant (p > 0.05) effect on the inhibition of H2O2-induced oxidative stress elicited by methanandamide, KBA (1 mM) reversed the neuroprotective action of methanandamide. Conclusions: The cannabinoids, methanandamide and 2-AG can prevent H2O2-induced oxidative stress in the isolated bovine retina. The neuroprotective actions of cannabinoids are partially dependent upon the activation of the CB1 receptors and endogenous production of H2S via the 3-MST/CAT pathway. Full article
(This article belongs to the Section Pharmacology)
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Figure 1
<p>Concentration-dependent effect of methanandamide on H<sub>2</sub>O<sub>2</sub>-induced 8-isoprostane production in isolated bovine retina. Each value represents the mean ± SEM for <span class="html-italic">n</span> = 12; *** <span class="html-italic">p</span> &lt; 0.001 significantly different from the control; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 significantly different from H<sub>2</sub>O<sub>2</sub>-treated tissues.</p>
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<p>Concentration-dependent effect of 2-arachidonyl glycerol on H<sub>2</sub>O<sub>2</sub>-induced 8-isoprostane production in isolated bovine retina. Each value represents the mean ± SEM for <span class="html-italic">n</span> = 12. *** <span class="html-italic">p</span> &lt; 0.001 significantly different from the control; <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 significantly different from H<sub>2</sub>O<sub>2</sub>-treated tissues.</p>
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<p>Role of the CB1 receptor and TRPV channels in methanandamide-mediated effects on H<sub>2</sub>O<sub>2</sub>-induced 8-isoprostane production in isolated bovine retina. Vertical bars represent mean ± S.E.M. <span class="html-italic">n</span> = 12; *** <span class="html-italic">p</span> &lt; 0.001 significantly different from the control; <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 significantly different from H<sub>2</sub>O<sub>2</sub>-treated tissues; <sup>@@@</sup> <span class="html-italic">p</span> &lt; 0.001 significantly different from methanandamide-treated tissues.</p>
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<p>Role of CBS/CSE and the 3MST pathway in methanandmide-mediated neuroprotection in isolated bovine retina. Vertical bars represent mean ± S.E.M. <span class="html-italic">n</span> = 12. *** <span class="html-italic">p</span> &lt; 0.001 significantly different from the control; <sup>###</sup> <span class="html-italic">p</span> &lt; 0.001 significantly different from H<sub>2</sub>O<sub>2</sub>-treated tissues; <sup>@@@</sup> <span class="html-italic">p</span> &lt; 0.001 significantly different from methanandamide-treated tissues.</p>
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30 pages, 6406 KiB  
Article
Discovery of PPAR Alpha Lipid Pathway Modulators That Do Not Bind Directly to the Receptor as Potential Anti-Cancer Compounds
by Arwa Al Subait, Raghad H. Alghamdi, Rizwan Ali, Amani Alsharidah, Sarah Huwaizi, Reem A. Alkhodier, Aljawharah Saud Almogren, Barrak A. Alzomia, Ahmad Alaskar and Mohamed Boudjelal
Int. J. Mol. Sci. 2025, 26(2), 736; https://doi.org/10.3390/ijms26020736 - 16 Jan 2025
Viewed by 428
Abstract
Peroxisome proliferator-activated receptors (PPARs) are considered good drug targets for breast cancer because of their involvement in fatty acid metabolism that induces cell proliferation. In this study, we used the KAIMRC1 breast cancer cell line. We showed that the PPARE-Luciferase reporter gets highly [...] Read more.
Peroxisome proliferator-activated receptors (PPARs) are considered good drug targets for breast cancer because of their involvement in fatty acid metabolism that induces cell proliferation. In this study, we used the KAIMRC1 breast cancer cell line. We showed that the PPARE-Luciferase reporter gets highly activated without adding any exogenous ligand when PPAR alpha is co-transfected, and the antagonist GW6471 can inhibit the activity. Using this reporter system, we screened 240 compounds representing kinase inhibitors, epigenetic modulators, and stem cell differentiators and identified compounds that inhibit the PPARα-activated PPARE-Luciferase reporter in the KAIMRC1 cell. We selected 11 compounds (five epigenetic modulators, two stem cell differentiators, and four kinase inhibitors) that inhibited the reporter by at least 40% compared to the controls (DMSO-treated cells). We tested them in a dose-dependent manner and measured the KAIMRC1 cell viability after 48 h. All 11 compounds induced the cell killing at different IC50 values. We selected two compounds, PHA665752 and NSC3852, to dissect how they kill KAIMRC1 cells compared to the antagonist GW6741. First, molecular docking and a TR-FRET PPARα binding assay showed that compared to GW6471, these two compounds could not bind to PPARα. This means they inhibit the PPARα pathway independently rather than binding to the receptor. We further confirmed that PHA665752 and NSC3852 induce cell killing depending on the level of PPARα expression, and as such, their potency for killing the SW620 colon cancer cell line that expresses the lowest level of PPARα was less potent than for the KAIMRC1 and MDA-MB-231 cell lines. Further, using an apoptosis array and fatty acid gene expression panel, we found that both compounds regulate the PPARα pathway by controlling the genes involved in the fatty acid oxidation process. Our findings suggest that these two compounds have opposite effects involving fatty acid oxidation in the KAIMRC1 breast cancer cell line. Although we do not fully understand their mechanism of action, our data provide new insights into the potential role of these compounds in targeting breast cancer cells. Full article
(This article belongs to the Special Issue Recombinant Proteins, Protein Folding and Drug Discovery)
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<p>Activity of PPARE-Luciferase in KAIMRC1 cells: KAIMRC1 cells were transfected with PPARE-Luciferase (PPARE) alone, with PPAR alpha (PRα) (<b>A</b>) or PPAR gamma (<b>B</b>). As indicated, the cells were treated with PPAR alpha agonist (GW7647), antagonist (GW6471) or PPAR gamma agonist (Rosiglitazone), or antagonist (T0070907) in the absence (no FBS) or presence of 10% FBS. The ratio of PPARE-Luciferase/Renilla-Luciferase is blotted.</p>
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<p>Schematic representation of screening cascade: KAIMRC1 cells transfected with PPARE-Luciferase and PPARα were treated with kinase inhibitors, epigenetic modulators, or stem cell differentiators. The identified compounds that inhibited the PPARE-Luciferase were characterized further as indicated.</p>
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<p>Inhibition of PPARE-Luciferase by selected compounds: the 11 compounds that inhibited by 40% the PPARE-Luciferase in the presence of PPAR alpha and did not affect the renilla or kill the KAIMRC1 cells were retested in the Luciferase reporter assay for confirmation after 24 h of treatment.</p>
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<p>Structures of GW6471, NSC3852, and PHA665752.</p>
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<p>Overlay of the docked pose of GW6471 (magenta sticks) and the X-ray crystal structure pose (yellow sticks). The SMRT co-repressor is shown as a teal carton, residues as platinum sticks, and hydrogen bonds as yellow dashed lines.</p>
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<p>The docked poses of (<b>A</b>) NSC3852 (pink sticks) and (<b>B</b>) PHA665752 (green sticks). The X-ray crystal structure pose of GW6471 is shown as yellow sticks, the SMRT co-repressor as a teal carton, residues as platinum sticks, hydrogen bonds as yellow dashed lines, and halogen bonds as gold dashed lines.</p>
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<p>TR-FRET-based competitive binding assay for PPAR alphawas conducted for one hour for the compounds GW7647, GW6471, NSC3852, and PHA665752 at three concentrations (0.1, 1, and 10 µM). GW7647 was used as a positive (agonist) ligand control for PPAR α. GW6471 was used as an antagonist for PPAR alpha, while DMSO was used as a negative control.</p>
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<p>PPARα expression in different cancer cell lines. Real-time quantitative PCR showing the relative quantification (RQ) of PPARα in KAIMRC1, MDA-MB231, and SW620 cells. The cells were grown for 48 h for RNA isolation, and cDNA was synthesized using gene-specific primers. Relative quantification values are means (bars) ± and standard deviations (error bars) from three biological replicates.</p>
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<p>Dose-response curve for the half-maximal inhibitory concentration IC<sub>50</sub> (μM) of (<b>A</b>) NSC3852 and (<b>B</b>) PHA665752 against KAIMRC1, MDAMB231, and SW620 cell lines. The X-axis is the log of concentrations in µM, and the Y-axis is normalized cell viability in percentages.</p>
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<p>Effect of PPAR alpha pathway inhibitors on KAIMRC1 cell stress pathway: (<b>A</b>) post-treatment multiplex protein profiling of KAIMRC1 cells. The human cell stress array was utilized to detect the expression of key proteins involved in the PPARα inhibition pathway. (<b>B</b>) Graphical representation of selected analytes. The X-axis shows compounds, and the y-axis denotes the mean pixel density.</p>
Full article ">Figure 10 Cont.
<p>Effect of PPAR alpha pathway inhibitors on KAIMRC1 cell stress pathway: (<b>A</b>) post-treatment multiplex protein profiling of KAIMRC1 cells. The human cell stress array was utilized to detect the expression of key proteins involved in the PPARα inhibition pathway. (<b>B</b>) Graphical representation of selected analytes. The X-axis shows compounds, and the y-axis denotes the mean pixel density.</p>
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<p>Profiling apoptosis proteins in treated KAIMRC1 cells. (<b>A</b>) Arrays were incubated with 400 µg of KAIMRC1 cell lysates treated with DMSO, NSC3852, PHA66575, and GW6471. The human apoptosis array detects multiple apoptosis-related proteins in treated KAIMRC1 cell lysates. Each protein was spotted in duplicate. The pairs of dots in each corner are the positive controls. (<b>B</b>) Graphical representation of selected lysates. The X-axis shows PPARA alpha modulators and the Y-axis denotes averaged pixel density.</p>
Full article ">Figure 11 Cont.
<p>Profiling apoptosis proteins in treated KAIMRC1 cells. (<b>A</b>) Arrays were incubated with 400 µg of KAIMRC1 cell lysates treated with DMSO, NSC3852, PHA66575, and GW6471. The human apoptosis array detects multiple apoptosis-related proteins in treated KAIMRC1 cell lysates. Each protein was spotted in duplicate. The pairs of dots in each corner are the positive controls. (<b>B</b>) Graphical representation of selected lysates. The X-axis shows PPARA alpha modulators and the Y-axis denotes averaged pixel density.</p>
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<p>Effect of PPAR alpha pathway inhibitor of expression of fatty acid metabolism genes. Gene expression of human fatty acid metabolism genes in KAIMRC1 cells treated with PPARα modulators (NSC3852 and PHA665752) in comparison to the PPARα antagonist (GW6471).</p>
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<p>Effect of PPAR alpha pathway inhibitor of expression of fatty acid metabolism genes. Gene expression of human fatty acid metabolism genes in KAIMRC1 cells treated with PPARα modulators (NSC3852 and PHA665752) in comparison to the PPARα antagonist (GW6471).</p>
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<p>The protein–protein interaction network using the STRING app. Proteins are represented with color nodes, and interactions are represented with edges. Strong interactions are shown with thicker edges. The proteins are segregated into target, connector, and modulated proteins.</p>
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16 pages, 3994 KiB  
Article
Syringaldehyde Alleviates Cardiac Hypertrophy Induced by Hyperglycemia in H9c2 Cells Through GLP-1 Receptor Signals
by Yingxiao Li, Chao-Tien Hsu, Ting-Ting Yang and Kai-Chun Cheng
Pharmaceuticals 2025, 18(1), 110; https://doi.org/10.3390/ph18010110 - 16 Jan 2025
Viewed by 253
Abstract
Background: Cardiac hypertrophy is a significant complication of diabetes, often triggered by hyperglycemia. Glucagon-like peptide-1 (GLP-1) receptor agonists alleviate cardiac hypertrophy, but their efficacy diminishes under GLP-1 resistance. Syringaldehyde (SA), a natural phenolic compound, may activate GLP-1 receptors and mitigate hypertrophy. This study [...] Read more.
Background: Cardiac hypertrophy is a significant complication of diabetes, often triggered by hyperglycemia. Glucagon-like peptide-1 (GLP-1) receptor agonists alleviate cardiac hypertrophy, but their efficacy diminishes under GLP-1 resistance. Syringaldehyde (SA), a natural phenolic compound, may activate GLP-1 receptors and mitigate hypertrophy. This study explores SA’s therapeutic potential in hyperglycemia-induced cardiac hypertrophy in H9c2 cardiomyocytes. Methods: H9c2 cells were exposed to high glucose to induce hypertrophy. Cells were treated with varying SA concentrations, and hypertrophic biomarkers were analyzed using ELISA, qPCR, and Western blot. Results: SA reduced cell size and hypertrophic biomarkers in a dose-dependent manner while increasing GLP-1 receptor expression and cAMP levels. These effects were attenuated in GLP-1-resistant cells, highlighting the role of GLP-1 receptor activation. AMPK activation was essential, as its inhibition abolished SA’s effects. SA also decreased O-linked N-acetylglucosamine transferase (OGT) expression via AMPK activation, contributing to reduced hypertrophy. Conclusions: SA alleviates hyperglycemia-induced cardiac hypertrophy in H9c2 cells by activating the GLP-1 receptor and AMPK signaling pathway. Full article
(This article belongs to the Special Issue Natural Products in Diabetes Mellitus: 2nd Edition)
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<p>Syringaldehyde (SA) increases the expression of the GLP-1 receptor in H9c2 cells with hypertrophy. (<b>a</b>) Changes in GLP-1 receptor protein levels induced via SA administration at concentrations of 0.1 μM (low), 0.5 μM (medium), and 1 μM (high). (<b>b</b>) Changes in calcium influx induced via SA administration at different concentrations. (<b>c</b>) Levels of cellular cyclic AMP (cAMP) in cells subjected to different concentrations of SA. (<b>d</b>) The cellular cAMP level induced by SA at 1 μM was inhibited, following 30 min pretreatment with Ex 9 at concentrations of 0.1 μM or 0.5 μM. The sample size was 6 except for the Western blotting analysis (n = 4). Statistical significance was indicated as follows: * <span class="html-italic">p</span> &lt; 0.05 vs. control (Con); <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. vehicle (Veh).</p>
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<p>Syringaldehyde (SA) ameliorated the hyperglycemia-induced hypertrophy of H9c2 cells. (<b>a</b>) Changes in the size of the hypertrophic cells treated with syringaldehyde at different concentrations of 0.1 μM (low), 0.5 μM (medium), and 1 μM (high). * <span class="html-italic">p</span> &lt; 0.05 vs. control (Con). <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05) vs. vehicle (Veh). Gene expression levels of (<b>b</b>) the gene expression levels of ANP (Con: 1 ± 0.2; Veh: 2.1 ± 0.2; SA Med: 1.3 ± 0.1; SA High: 1.2 ± 0.1), BNP (Con: 1 ± 0.2; Veh: 1.9 ± 0.1; SA Med: 1.4 ± 0.2; SA High: 1.1 ± 0.1) and (<b>c</b>) β-MHC (Con: 1 ± 0.1; Veh: 1.9 ± 0.1; SA Med: 1.3 ± 0.2; SA High: 1 ± 0.1) in hypertrophic cells administered various concentrations of SA or without treatment. * <span class="html-italic">p</span> &lt; 0.05 vs. control (Con). <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05) vs. vehicle (Veh). (<b>d</b>) The size of the H9c2 cells was observed using light microscopy (scale bar: 100 μm). Control cells in a normal culture (Con) were not modified with SA at 1 μM (Con + SA), as indicated in the upper panel. * <span class="html-italic">p</span> &lt; 0.05 vs. normal cells (Con). <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05) vs. high glucose-induced hypertrophic cell (HG). Values for each indicator are expressed as fold changes in gene expressions of ANP, BNP, and β-MHC, relative to the control group. Fold change is calculated as follows: fold change = data of the experimental group/data of the control group.</p>
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<p>The signaling pathway for syringaldehyde (SA) alleviated cardiac hypertrophy in H9c2 cells. (<b>a</b>) Changes in cell size in hypertrophic cardiomyocytes with GLP-1 resistance. Cells were treated with or without SA at 1 μM (high dose), exendin-4 (EX-4) at 0.5 μM, and metformin at 5 μM, respectively. (<b>b</b>) SA and EX-4 failed to stimulate cAMP levels in H9c2 cells with GLP-1 resistance, whereas dopamine at 5 μM elevated cAMP levels in these cells. (<b>c</b>) A decrease in hypertrophic cell size due to SA at 0.5 μM (a medium dose) was reversed via pretreatment with H-89 at doses of 0.5 μM (low) or 1 μM (high). (<b>d</b>) Changes in cellular ROS levels in high glucose-induced hypertrophic cells with or without SA treatment. The inhibition of PKA by H-89 (1 μM) reversed the ROS-lowering effect of SA. Values for each indicator are expressed as fold changes in cell size, gene expressions of ANP, BNP, and β-MHC, relative to the control group. Results are presented as the mean ± SE from independent experiments, n = 6. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05 vs. normal control (Con). <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. vehicle (Veh). <sup>†</sup> <span class="html-italic">p</span> &lt; 0.05 vs. hypertrophic cells treated with SA at 0.5 μM (Blank).</p>
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<p>The role of AMPK in syringaldehyde (SA)-alleviated cardiac hypertrophy in H9c2 cells. H9c2 cells were treated with a high glucose medium for 48 h. siRNA was used to ablate the expression of AMPK and H9c2 cells that received with same volume of scramble. (<b>a</b>) Changes in cell size due to SA at 1 μM (high) were, like the effect of EX-4, reversed by AMPK ablation. Additionally, the effects of metformin were also removed in AMPK-silenced cells. (<b>b</b>) The changes in gene expression levels of ANP (Con: 1 ± 0.2; Veh: 2.6 ± 0.4; SA High + scramble: 1.2 ± 0.2; SA High + siRNA: 2.2 ± 0.3; EX4+ scramble: 1.4 ± 0.1; EX4 + siRNA: 2.2 ± 0.3), and BNP (Con: 1 ± 0.3; Veh: 2.4 ± 0.3; SA High + scramble: 1.3 ± 0.4; SA High + siRNA: 2.3 ± 0.4; EX4+ scramble: 1.6 ± 0.2; EX4 + siRNA: 2.2 ± 0.4). (<b>c</b>) The changes in gene expression levels of β-MHC (Con: 1 ± 0.2; Veh: 1.9 ± 0.2; SA High + scramble: 1.2 ± 0.1; SA High + siRNA: 1.7 ± 0.2; EX4+ scramble: 1.3 ± 0.1; EX4 + siRNA: 1.7 ± 0.3). (<b>d</b>) The expression of O-linked b-N-acetylglucosamine transferase (OGT) was promoted by high glucose levels and reduced by SA at a 1 μM (high) dose. The effect of SA was reversed by compound C (CpC) at doses of 5 μM (low) and 10 μM (high). The value of each indicator shown in a column is the mean ± standard error of the mean (SEM) per group; n = 6. Values for each indicator are expressed as fold changes in cell size, cAMP levels, and ROS levels relative to the control group. Fold change is calculated as follows: fold change = data of the experimental group/data of the control group. * <span class="html-italic">p</span> &lt; 0.05 vs. normal control (Con). <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. vehicle (Veh). <sup>†</sup> <span class="html-italic">p</span> &lt; 0.05 vs. hypertrophic cell administered with SA 1 μM (Blank).</p>
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<p>The schematic diagram that presents how syringaldehyde alleviates cardiac hypertrophy.</p>
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26 pages, 1855 KiB  
Article
Effect of a Low-Molecular-Weight Allosteric Agonist of the Thyroid-Stimulating Hormone Receptor on Basal and Thyroliberin-Stimulated Activity of Thyroid System in Diabetic Rats
by Kira V. Derkach, Alena S. Pechalnova, Viktor N. Sorokoumov, Inna I. Zorina, Irina Y. Morina, Elizaveta E. Chernenko, Egor A. Didenko, Irina V. Romanova and Alexander O. Shpakov
Int. J. Mol. Sci. 2025, 26(2), 703; https://doi.org/10.3390/ijms26020703 - 15 Jan 2025
Viewed by 324
Abstract
The approaches to correct thyroid deficiency include replacement therapy with thyroid hormones (THs), but such therapy causes a number of side effects. A possible alternative is thyroid-stimulating hormone (TSH) receptor activators, including allosteric agonists. The aim of this work was to study the [...] Read more.
The approaches to correct thyroid deficiency include replacement therapy with thyroid hormones (THs), but such therapy causes a number of side effects. A possible alternative is thyroid-stimulating hormone (TSH) receptor activators, including allosteric agonists. The aim of this work was to study the effect of ethyl-2-(4-(4-(5-amino-6-(tert-butylcarbamoyl)-2-(methylthio)thieno[2,3-d]pyrimidin-4-yl)phenyl)-1H-1,2,3-triazol-1-yl) acetate (TPY3m), a TSH receptor allosteric agonist developed by us, on basal and thyroliberin (TRH)-stimulated TH levels and the hypothalamic-pituitary-thyroid (HPT) axis in male rats with high-fat diet/low-dose streptozotocin-induced type 2 diabetes mellitus (T2DM). Single and three-day administration of TPY3m (i.p., 20 mg/kg) was studied, and the effect of TPY3m on the HPT axis was compared with that of levothyroxine. TPY3m increased TH levels when administered to both healthy and diabetic rats, normalizing thyroxine and triiodothyronine levels in T2DM and, unlike levothyroxine, without negatively affecting TSH levels or the expression of hypothalamic and pituitary genes responsible for TSH production. TPY3m pretreatment preserved the stimulatory effects of TRH on TH levels and thyroid gene expression. This indicates the absence of competition between TPY3m and endogenous TSH for TSH receptor activation and is supported by our in vitro results on TPY3m- and TSH-stimulated adenylate cyclase activity in rat thyroid membranes. Morphological analysis of thyroid glands in diabetic rats after three-day TPY3m administration shows an increase in its functional activity without destructive changes. To summarize, TPY3m, with the activity of a partial allosteric agonist of the TSH receptor, was created as a prototype of drugs to correct thyroid insufficiency in T2DM. Full article
(This article belongs to the Special Issue Thyroid Hormone and Molecular Endocrinology)
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<p>Effect of different concentrations of TPY3m on the basal (<b>A</b>) and TSH-stimulated (<b>B</b>) adenylate cyclase activity in the rat thyroid membranes. (<b>A</b>) The basal AC activity was 19.7 ± 0.8 pmol cAMP/min per mg of membrane protein. Stimulating effects of TPY3m were assessed in the concentration range from 10<sup>−9</sup> to 10<sup>−4</sup> M. (<b>B</b>) The AC activity stimulated by TSH (10<sup>−9</sup> M) was 144.2 ± 4.1 pmol cAMP/min per mg of membrane protein (+632% over the basal AC activity). Combined action of TSH and TPY3m were assessed in the presence of 10<sup>−9</sup>–10<sup>−4</sup> M TPY3m. <sup>a</sup> The differences from the basal AC activity are significant at <span class="html-italic">p</span> &lt; 0.05. <sup>b</sup> The differences from AC activity stimulated by TSH alone (in the absence of TPY3m) are significant at <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effect of treatment with TPY3m (single dose 20 mg/kg, i.p.) on the basal and thyroliberin-stimulated levels of thyroid hormones and TSH in the blood of healthy rats. (<b>A</b>)—fT4, (<b>B</b>)—tT4, (<b>C</b>)—fT3, (<b>D</b>)—tT3, (<b>E</b>)—TSH. Differences with the control (<sup>a</sup>), C + TRH (<sup>b</sup>), and C + TP (<sup>c</sup>) groups are significant at <span class="html-italic">p</span> &lt; 0.05. Data are presented as M ± SEM, and in all groups, <span class="html-italic">n</span> = 6.</p>
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<p>Effect of single-dose TPY3m administration (20 mg/kg, i.p.) on basal and thyroliberin-stimulated thyroid hormone levels in rats with high-fat diet/low-dose streptozotocin-induced T2DM. (<b>A</b>)—fT4, (<b>B</b>)—tT4, (<b>C</b>)—fT3, (<b>D</b>)—tT3. The differences with the C1 (<sup>a</sup>) and D1 (<sup>b</sup>) groups are significant at <span class="html-italic">p</span> &lt; 0.05. The data on the blood tT4 levels are not normally distributed and are presented as median and interquartile ranges (25%; 75%). The data on the blood levels of fT4, fT3, and tT3 are normally distributed and are presented as M ± SEM. In all groups, <span class="html-italic">n</span> = 6.</p>
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<p>Effect of three-day treatment with TPY3m and levothyroxine on the blood levels of thyroid hormones and TSH in male rats with T2DM. (<b>A</b>)—fT4, (<b>B</b>)—tT4, (<b>C</b>)—fT3, (<b>D</b>)—tT3, (<b>E</b>)—TSH. Differences with the C2 (<sup>a</sup>), D2 (<sup>b</sup>), and D2 + TP (<sup>c</sup>) groups are significant at <span class="html-italic">p</span> &lt; 0.05. The data on the blood tT4 and TSH levels are not normally distributed and are presented as median and interquartile ranges (25%; 75%). The data on the blood levels of fT4, fT3 and tT3 are normally distributed and are presented as M ± SEM. In all groups, <span class="html-italic">n</span> = 6.</p>
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<p>Thyroid gland sections from control (C2) and diabetic rats (D2) and diabetic animals treated with TPY3m for three days (D2 + TP). Hematoxylin and eosin staining. Scale bar: 100 μm. A detailed description of the morphological features is given in the text.</p>
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20 pages, 4323 KiB  
Article
Treatment of Acid Mine Water from the Breiner-Băiuț Area, Romania, Using Iron Scrap
by Gheorghe Iepure and Aurica Pop
Water 2025, 17(2), 225; https://doi.org/10.3390/w17020225 - 15 Jan 2025
Viewed by 311
Abstract
Acid mine drainage (AMD) forms in mining areas during or after mining operations cease. This is a primary cause of environmental pollution and poses risks to human health and the environment. The hydrographic system from the Maramureș mining industry (especially the Baia Mare [...] Read more.
Acid mine drainage (AMD) forms in mining areas during or after mining operations cease. This is a primary cause of environmental pollution and poses risks to human health and the environment. The hydrographic system from the Maramureș mining industry (especially the Baia Mare area) was heavily contaminated with heavy metals for many years due to mining activity, and after the closing of mining activity, it continues to be polluted due to water leaks from the abandoned galleries, the pipes, and the tailing ponds. The mineralization in the Băiuț area, predominantly represented by pyrite and marcasite associated with other sulfides, such as chalcopyrite, covelline, galena, and sphalerite, together with mine waters contribute to the formation of acid mine drainage. The Breiner-Băiuț mining gallery (copper mine) permanently discharges acidic water into the rivers. The efficiency of iron scrap (low-cost absorbent) for the treatment of mine water from this gallery was investigated. The treatment of mine water with iron shavings aimed to reduce the concentration of toxic metals and pH. Mine water from the Breiner-Baiut mine, Romania, is characterized by high acidity, pH = 2.75, and by the association of many heavy metals, whose concentration exceeds the limit values for the pollutant loading of wastewater discharged into natural receptors: Cu—71.1 mg/L; Zn—42.5 mg/L; and Fe—122.5 mg/L. Iron scrap with different weights (200 g, 400 g, and 600 g) was put in contact with 1.5 L of acid mine water. After 30 days, all three treatment variants showed a reduction in the concentrations of toxic metals. A reduction in Cu concentration was achieved below the permissible limit. In all three samples, the Cu concentrations were 0.005 for Sample 1, 0.001 for Sample 2, and <LOQ for Sample 3. The Zn concentration decreased significantly compared to the original mine water concentration from 42.5 mg/L to 1.221 mg/L, 1.091 mg/L, and 0.932 mg/L. These values are still above the permissible limit (0.5 mg/L). The Fe concentration increased compared to the original untreated water sample due to the dissolution of iron scrap. This research focuses on methods to reduce the toxic metal concentration in mine water, immobilizing (separating) certain toxic metals in sludge, and immobilizing various compounds on the surface of iron shavings in the form of insoluble crystals. Full article
(This article belongs to the Special Issue Basin Non-Point Source Pollution)
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<p>Mine water sampling area in the Baiuț region: (<b>a</b>) location in the Baia Mare area (Baiut, Romania—47°37′31.0″ N 24°00′32.5″ E (source: Google Maps); (<b>b</b>) overview of the mine entrance; (<b>c</b>) detailed view of the mine gallery and sampling point.</p>
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<p>Iron scrap (iron borings).</p>
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<p>Graphical representation of the concentration of heavy metals in mine water samples treated with iron shavings for each element: (<b>a</b>) Cu; (<b>b</b>) Zn; (<b>c</b>) Fe; (<b>d</b>) Cd.</p>
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<p>Graphical representation of the distribution of heavy metals in the sludge: (<b>a</b>) Cu; (<b>b</b>) Zn; (<b>c</b>) Fe; (<b>d</b>) Cd.</p>
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<p>Diffractogram of the sludge (P3-600): M—montmorillonite; I—illite; T—tenorite; Gs—goslarite; B—brochantite; L—lepidocrocite; G—goethite.</p>
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<p>Microscopic image of iron scrap fragments with deposits of yellow-orange salts: (<b>a</b>) aggregation of iron scrap; (<b>b</b>) crystals grown on the surface of an iron scrap; (<b>c</b>) crystals detached from the shavings, magnification 80×.</p>
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<p>Secondary electron images (SEIs) showing crystals clustered on the surface of iron scrap: (<b>a</b>) overview image, sample C1, magnification 95×; (<b>b</b>) detail of point (1), sample C1, magnification 1700×; (<b>c</b>) detail point (1), sample C1, magnification 2700×.</p>
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<p>SEM image of a concretion on the surface of a steel chip (crystal C2). (<b>a</b>) Image of crystal C2; (<b>b</b>) spectral analysis at point 3.</p>
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<p>Microstructure (COMPO) of crystal C3. (<b>a</b>) Image of crystal C3, 190×; (<b>b</b>) detail 1800×; (<b>c</b>) point 5 spectral analysis.</p>
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12 pages, 5969 KiB  
Article
Predaceous and Phytophagous Pentatomidae Insects Exhibit Contrasting Susceptibilities to Imidacloprid
by Hongmei Cheng, Zhen Wang, Xiaoyu Yan, Changjin Lin, Yu Chen, Le Ma, Luyao Fu, Xiaolin Dong and Chenxi Liu
Int. J. Mol. Sci. 2025, 26(2), 690; https://doi.org/10.3390/ijms26020690 - 15 Jan 2025
Viewed by 263
Abstract
Imidacloprid, a widely used neonicotinoid insecticide, targets insect pests but also affects natural enemies. However, the effects of neonicotinoid insecticides on closely related insects remain unclear. We evaluated the harmful effects of imidacloprid on the phytophagous Halyomorpha halys and predaceous Arma chinensis. [...] Read more.
Imidacloprid, a widely used neonicotinoid insecticide, targets insect pests but also affects natural enemies. However, the effects of neonicotinoid insecticides on closely related insects remain unclear. We evaluated the harmful effects of imidacloprid on the phytophagous Halyomorpha halys and predaceous Arma chinensis. Bioassays revealed that imidacloprid was more toxic to H. halys than to A. chinensis and more harmful to the males than to the females of the two insects. A. chinensis adults recovered from imidacloprid-induced knockdown, as evidenced by restored respiratory rates, metabolic rates, and locomotion. Surviving A. chinensis showed reduced fecundity, suggesting a trade-off between detoxification and reproduction. Bioinformatics analysis of nicotinic acetylcholine receptors (nAChRs) and molecular docking simulations indicated a lower diversity of the nAChR gene family in A. chinensis than in H. halys, with weaker binding to imidacloprid, consistent with the relatively low toxicity of the insecticide in this species. This might account for the susceptibility differences to imidacloprid between the species. These findings underscore the efficacy of imidacloprid against H. halys and provide insights into the toxicities of neonicotinoids to target and non-target insects. Full article
(This article belongs to the Section Molecular Toxicology)
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<p>(<b>A</b>) The toxic effects of imidacloprid on <span class="html-italic">Arma chinensis</span> and <span class="html-italic">Halyomorpha halys</span> 24, 48, 72, 96, and 120 h post exposure. The points indicate the KD<sub>50</sub> value (n = 3, error bars, SEM) used to assess changes, determined using a probit regression model. Analysis of the weight, respiration, and metabolism of <span class="html-italic">A</span>. <span class="html-italic">chinensis</span> exposed to different concentrations of imidacloprid [Control, Con1 (700 mg/L), Con2 (1900 mg/L)] for 24 h (gray) and 96 h (red). (<b>B</b>,<b>C</b>) Weight differences between male (M) and female (F) adults. (<b>D</b>,<b>E</b>) Respiratory rates. (<b>F</b>,<b>G</b>) Metabolic rates. Box plots show the median (line), mean (dotted line), 25th and 75th percentiles, and outliers (circles). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and ns, not significant, for comparisons of males and females, as determined using two-way repeated measures ANOVA, followed by pairwise multiple comparisons, Bonferroni test. Black asterisks indicate intra-group comparison; red asterisks indicate inter-group comparisons. The metabolic data of the Control (96 h), Con1 (700 mg/L) (96 h), and Con2 (1900 mg/L) (24 h) males were transformed by SQRT (square root transformed).</p>
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<p>The behavioral tracking analysis of <span class="html-italic">Arma chinensis</span> following imidacloprid treatment. The representative trajectory of imidacloprid-treated females and males after 120 h of exposure (Control, Con1, Con2), recorded using a Luowice Y10 camera fitted with infrared lights.</p>
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<p>(<b>A</b>,<b>B</b>) The average distance traveled females and males after 120 h of exposure to various concentrations (control (black), Con1 (blue), Con2 (red)) of imidacloprid. The data are expressed as the means ± SEM, analyzed using one-way ANOVA and the Waller–Duncan test. Significant differences in average total distance traveled for 0–24 h (<b>C</b>,<b>F</b>), 24–96 h (<b>D</b>,<b>G</b>), and 96–120 h. (<b>E</b>,<b>H</b>). n = 15 for all groups. Means with different letters differ significantly, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>(<b>A</b>,<b>B</b>) Egg mass and number of Groups Ⅰ and Ⅱ. (<b>C</b>,<b>D</b>) Egg mass and number of Groups Ⅰ and Ⅲ. (<b>E</b>) Egg hatching rate of Groups Ⅰ, Ⅱ, and Ⅲ. Means with different letters are significantly different; Waller–Duncan test, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>(<b>A</b>) The root mean square deviations of the nAchR subunit from <span class="html-italic">Arma chinensis</span> and <span class="html-italic">Halyomorpha halys</span>. (<b>B</b>) The minimum binding energy of imidacloprid with the nAchR subunit of <span class="html-italic">A. chinensis</span> (open circles) and <span class="html-italic">H. halys</span> (solid circles). The distance from the point to the center represents the binding energy values; the longer the distance, the weaker the binding capacity.</p>
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28 pages, 6640 KiB  
Article
Overexpression of the GmPM35 Gene Significantly Enhances Drought Tolerance in Transgenic Arabidopsis and Soybean
by Xinyu Wang, Yao Sun, Rui Wang, Xinyang Li, Yongyi Li, Tianyu Wang, Zhaohao Guo, Yan Li, Wenxi Qiu, Shuyan Guan, Qi Zhang, Piwu Wang, Mingze Li, Siyan Liu and Xuhong Fan
Agronomy 2025, 15(1), 192; https://doi.org/10.3390/agronomy15010192 - 15 Jan 2025
Viewed by 321
Abstract
Drought stress is one of the major adversity stresses affecting soybean (Glycine max [L.] Merr.) yield. Late embryogenesis abundant protein (LEA protein) is a large family of proteins widely distributed in various types of organisms, and this class of proteins plays an [...] Read more.
Drought stress is one of the major adversity stresses affecting soybean (Glycine max [L.] Merr.) yield. Late embryogenesis abundant protein (LEA protein) is a large family of proteins widely distributed in various types of organisms, and this class of proteins plays an important role in protecting proteins, membrane lipids, and lipids inside the cell. The soybean GmPM35 gene is a member of the LEA_6 subfamily. The expression of the GmPM35 gene was significantly increased after drought stress in soybeans. A subcellular localization assay confirmed that the gene acts on the cell membrane. Against wild-type Arabidopsis thaliana, we found that Arabidopsis lines overexpressing the GmPM35 gene were significantly more drought-tolerant at germination and seedling stages under drought stress. To further investigate the drought tolerance function of this gene in soybeans, nine overexpression lines of the T3 generation soybean GmPM35 gene and two editing lines of the T3 generation soybean GmPM35 gene were obtained by Agrobacterium-mediated method using a wild-type soybean strain (JN28) as a receptor. Germination rate, root length, chlorophyll (CHL) content, Proline (Pro) content, malondialdehyde (MDA) content, superoxide anion (O2) content, hydrogen peroxide (H2O2) content, (NBT, DAB) staining, and activities of antioxidant enzymes (CAT, SOD, POD), and photosynthetic physiological indexes of the three different types of strains were measured and analyzed before and after drought stress. Combined with the results of rehydration experiments and physiological and biochemical indices, we found that overexpression of the GmPM35 gene protected the activities of antioxidant enzymes under drought stress. The activities of superoxide dismutase (SOD), catalase (CAT), and peroxidase (POD) were increased by an average of 34.28%, 26.12%, and 30.01%, respectively, in soybean plants overexpressing the GmPM35 gene compared with wild-type soybeans. Under drought stress conditions, soybean plants overexpressing the GmPM35 gene showed an average increase of 76.81% in photosynthesis rate (Pn), 39.8% in transpiration rate (Tr), 126% in stomatal conductance (Gs), 47.71% in intercellular CO2 concentration (Ci), and 26.44% in instantaneous water use efficiency (WUEi). The improvement of these indexes helped to reduce the accumulation of reactive oxygen species (ROS) in the plants. In addition, we found that under drought stress, the MDA content was reduced by an average of 18.8%, and the Pro content was increased by an average of 60.14% in soybean plants overexpressing the GmPM35 gene, and the changes in these indexes indicated that the plants had stronger antioxidant and osmoregulatory capacities in response to drought stress. In summary, this experiment demonstrated that the GmPM35 gene plays an important role in soybean tolerance to drought stress, and by overexpressing the GmPM35 gene, soybean plants can better tolerate drought stress and maintain normal physiological functions. Full article
(This article belongs to the Section Crop Breeding and Genetics)
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<p>Subcellular localization of GmPM35 protein in the lower epidermal cells of <span class="html-italic">Nicotiana benthamiana</span>. Enhanced green fluorescent protein (eGFP), bright field images, and merged images are shown from left to right. Fluorescence was observed with a confocal microscope. Scale bar = 25 µm.</p>
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<p>Tissue-specific expression of <span class="html-italic">GmPM35</span> gene in soybean and analysis of <span class="html-italic">GmPM35</span> gene expression under abiotic stress: (<b>A</b>) Electropherogram of total RNA extracted from soybean. (<b>B</b>) Analysis of <span class="html-italic">GmPM35</span> gene expression in different tissues at different developmental stages; <span class="html-italic">n</span> = 3. Error line indicates standard deviation. (<b>C</b>) Analysis of <span class="html-italic">GmPM35</span> gene expression under abiotic stress; <span class="html-italic">n</span> = 3. Error lines indicate standard deviation.</p>
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<p>Correlation statistical analysis of gene expression, germination rate, and green shoot rate in transgenic Arabidopsis overexpressing lines. (<b>A</b>) PCR detection of transgenic Arabidopsis in T<sub>2</sub> generation. m: DL2000 marker; P: positive control; N: negative control; CK: wild-type control; 1–11: PCR products; <span class="html-italic">n</span> = 3. (<b>B</b>) qRT-PCR to detect the expression of different strains of T<sub>3</sub>-generation transgenic <span class="html-italic">Arabidopsis thaliana</span>; <span class="html-italic">n</span> = 3. (<b>C</b>) Germination rate statistics of wild type (WT) and transgenic <span class="html-italic">Arabidopsis thaliana</span> (OE) inoculated in 1/2 MS solid medium. Error lines indicate standard deviation. (<b>D</b>) Statistics of green seedling rate in wild-type (WT) and transgenic Arabidopsis (OE) inoculated in 1/2 MS solid medium. Error lines indicate standard deviation. (<b>E</b>) Germination rate statistics of wild-type (WT) and transgenic <span class="html-italic">Arabidopsis thaliana</span> (OE) inoculated in 1/2 MS + 200 mmol/L mannitol solid medium. Error lines indicate standard deviation. (<b>F</b>) Statistics of green seedling rate in wild-type (WT) and transgenic Arabidopsis (OE) inoculated in 1/2 MS + 200 mmol/L mannitol solid medium. Error lines indicate standard deviations.</p>
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<p>Root length and fresh weight statistics of wild-type (WT) and transgenic <span class="html-italic">Arabidopsis thaliana</span> (OE) under mannitol-modeled drought stress. (<b>A</b>) Root length statistics of each strain under 1/2 MS and mannitol treatment conditions; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05 and (**) <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>) Statistics of fresh weight of each strain under 1/2 MS and mannitol treatment conditions; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05 and (**) <span class="html-italic">p</span> &lt; 0.01. (<b>C</b>) Root length phenotypes of each strain under 1/2 MS conditions. (<b>D</b>) Root length phenotypes of each strain under mannitol treatment conditions.</p>
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<p>Rehydration test of T<sub>2</sub>-generation transgenic <span class="html-italic">Arabidopsis thaliana</span> and its biochemical index analysis under drought stress. (<b>A</b>) T<sub>2</sub>-generation transgenic <span class="html-italic">Arabidopsis thaliana</span> drought and rehydration assays, the front panel is after drought treatment, and the back panel is after rehydration. (<b>B</b>) Survival rate of each Arabidopsis strain after rehydration; the error line indicates the standard deviation. (<b>C</b>) Analysis of MDA content determination of Arabidopsis lines before and after drought stress; <span class="html-italic">n</span> = 3. (**) <span class="html-italic">p</span> &lt; 0.01. The error line indicates the standard deviation. (<b>D</b>) Analysis of POD activity of Arabidopsis strains before and after drought stress; <span class="html-italic">n</span> = 3. (**) <span class="html-italic">p</span> &lt; 0.01. Error lines indicate standard deviation. (<b>E</b>) Determination and analysis of Pro content in each Arabidopsis strain before and after drought stress; <span class="html-italic">n</span> = 3. (**) <span class="html-italic">p</span> &lt; 0.01. The error line indicates the standard deviation. (<b>F</b>) Determination and analysis of SOD content in each Arabidopsis strain before and after drought stress; <span class="html-italic">n</span> = 3. (**) <span class="html-italic">p</span> &lt; 0.01. Error lines indicate standard deviation.</p>
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<p><span class="html-italic">Bar</span> gene detection in soybean hairy roots and qRT-PCR under drought stress. (<b>A</b>) <span class="html-italic">Bar</span> gene assay of transformed overexpression vector pCAMBIA3301-GmPM35 soybean hairy root. M: DL2000 marker; P: positive control; N: negative control; CK: K599 hairy root control; 1–9: PCR products. (<b>B</b>) Expression analysis of overexpression of soybean hairy root under drought stress; <span class="html-italic">n</span> = 3. (*) <span class="html-italic">p</span> &lt; 0.05 and (**) <span class="html-italic">p</span> &lt; 0.01. The error line represents the standard deviation.</p>
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<p>Phenograms of the root system phenotypes of overexpressed soybean hairy roots under drought stress. (<b>A</b>) Comparison of the root system of soybean hairy roots without stress. (<b>B</b>) Root system changes of overexpressed soybean hairy roots under drought stress: (<b>a</b>,<b>c</b>,<b>e</b>,<b>g</b>) unstressed hairy roots, (<b>b</b>,<b>d</b>,<b>f</b>,<b>h</b>) hairy roots after 7 days of drought stress, (<b>a</b>,<b>b</b>) K599 hairy roots, and (<b>c</b>–<b>h</b>) overexpressed hairy roots.</p>
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<p>Analysis of physiological and biochemical indicators of drought tolerance in overexpressed soybean hairy roots under drought stress. (<b>A</b>) Measurement and analysis of SOD activity in K599 hairy roots and overexpressed hairy roots before and after drought stress; <span class="html-italic">n</span> = 3. (**) <span class="html-italic">p</span> &lt; 0.01. Error lines indicate standard deviation. (<b>B</b>) Analysis of POD activity in K599 and overexpressed roots before and after drought stress; <span class="html-italic">n</span> = 3. (**) <span class="html-italic">p</span> &lt; 0.01. Error lines indicate standard deviation. (<b>C</b>) Analysis of Pro content in K599 and overexpressed roots before and after drought stress; <span class="html-italic">n</span> = 3. (**) <span class="html-italic">p</span> &lt; 0.01. Error lines indicate standard deviation. (<b>D</b>) analysis of MDA content in K599 and overexpressed roots before and after drought stress; <span class="html-italic">n</span> = 3. Error line indicates standard deviation. (<b>E</b>) Analysis of root activity in K599 and overexpressed roots before and after drought stress; <span class="html-italic">n</span> = 3. Error lines indicate standard deviations.</p>
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<p>Analysis of <span class="html-italic">GmPM35</span> gene target design and editing in soybean hairy roots: (<b>A</b>) <span class="html-italic">GmPM35</span> gene target design. (<b>B</b>) Analysis of editing in soybean hairy roots transfected with pCBSG015-GmPM35 vector.</p>
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<p>Identification and gene expression analysis of soybean overexpression and gene editing plants with <span class="html-italic">GmPM35</span> gene in T<sub>3</sub> generation. (<b>A</b>) Diagram of soybean genetic transformation process by Agrobacterium-mediated method. a: germination diagram, b: pre-cultivation diagram, c, d: first sieve and second sieve diagrams, e: elongation diagram, f: rooting diagram, and g: seedling refining and transplanting diagram. (<b>B</b>) PCR assay of T<sub>3</sub>-generation overexpression plants. m: DL5000 Marker, n: negative control, 1–9: PCR products. (<b>C</b>) <span class="html-italic">GmPM35</span> gene expression assay in different soybean lines; <span class="html-italic">n</span> = 3. Error lines indicate standard deviation; (*) denotes <span class="html-italic">p</span> &lt; 0.01 and (**) denotes <span class="html-italic">p</span> &lt; 0.05. (<b>D</b>) Analysis of editing in soybean KO<sub>1</sub> and KO<sub>2</sub> lines transformed with the pCBSG015-GmPM35 vector.</p>
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<p>Determination of germination rate and shoot length of T<sub>3</sub>-generation positive soybean plants under drought stress. (<b>A</b>) Relative germination rates of different soybean lines under drought stress; n ≥ 3. Error lines indicate standard deviations; (*) denotes <span class="html-italic">p</span> &lt; 0.01 and (**) denotes <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) Determination of shoot length of different soybean lines; <span class="html-italic">n</span> = 3. Error lines denote standard deviation; (*) denotes <span class="html-italic">p</span> &lt; 0.01 and (**) denotes <span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Comparison of shoot length of different soybean lines under drought stress.</p>
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<p>Root phenotypes of T<sub>3</sub>-generation positive soybean plants in rehydration test and drought stress. (<b>A</b>) Comparison of drought and rehydration phenotypes of different soybean lines: (<b>a</b>) before drought, (<b>b</b>) 10 days of drought, and (<b>c</b>) 3 days of rehydration. (<b>B</b>) Comparison of root length phenotypes of different soybean lines in natural drought: (<b>a</b>) before drought and (<b>b</b>) 10 days of drought. (<b>C</b>) Determination of root length and other indexes of different soybean lines; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Determination of biochemical indexes in T<sub>3</sub>-generation transgenic soybean plants. (<b>A</b>) Chlorophyll content of different soybean lines before and after drought stress; n ≥ 3. Error lines indicate standard deviations. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>) Determination of proline in different soybean lines before and after drought stress; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01. (<b>C</b>) Comparison of malondialdehyde content in different soybean strains before and after drought stress; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01. (<b>D</b>) Measurement of SOD activity in different soybean lines before and after drought stress; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01. (<b>E</b>) Determination of POD activity in different soybean lines before and after drought stress; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01. (<b>F</b>) Measurement of CAT activity in different soybean lines before and after drought stress; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>T<sub>3</sub>-generation transgenic soybean plants’ biochemical indexes were determined. (<b>A</b>) DAB staining and NBT staining of different soybean lines before and after drought stress: (<b>a</b>) DAB staining and (<b>b</b>) NBT staining. (<b>B</b>) Determination of O<sub>2</sub><sup>−</sup> and H<sub>2</sub>O<sub>2</sub> content in different soybean lines before and after drought stress; a: O<sub>2</sub><sup>−</sup> content and b: H<sub>2</sub>O<sub>2</sub> content CAT activity in different soybean lines before and after drought stress; n ≥ 3. Error lines indicate standard deviation. (*) <span class="html-italic">p</span> &lt; 0.05, (**) <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Comparison of agronomic traits of different soybean strains.</p>
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<p>Soybean <span class="html-italic">GmPM35</span> gene − mediated drought tolerance mechanism is demonstrated.</p>
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16 pages, 4483 KiB  
Article
Establishment of a Yeast Two-Hybrid-Based High-Throughput Screening Model for Selection of SARS-CoV-2 Spike-ACE2 Interaction Inhibitors
by Dongsheng Li, Baoqing You, Keyu Guo, Wenwen Zhou, Yan Li, Chenyin Wang, Xiaofang Chen, Zhen Wang, Jing Zhang and Shuyi Si
Int. J. Mol. Sci. 2025, 26(2), 678; https://doi.org/10.3390/ijms26020678 - 15 Jan 2025
Viewed by 387
Abstract
The recent coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has exerted considerable impact on global health. To prepare for rapidly mutating viruses and for the forthcoming pandemic, effective therapies targeting the critical stages of the viral [...] Read more.
The recent coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has exerted considerable impact on global health. To prepare for rapidly mutating viruses and for the forthcoming pandemic, effective therapies targeting the critical stages of the viral life cycle need to be developed. Viruses are dependent on the interaction between the receptor-binding domain (RBD) of the viral Spike (S) protein (S-RBD) and the angiotensin-converting enzyme 2 (ACE2) receptor to efficiently establish infection and the following replicate. Targeting this interaction provides a promising strategy to inhibit the entry process of the virus, which in turn has both preventive and therapeutic effects. In this study, we developed a robust and straightforward assay based on the Yeast-Two Hybrid system (Y2H) for identifying inhibitors targeting the S-RBD-ACE2 interaction of SARS-CoV-2. Through high-throughput screening, two compounds were identified as potential entry inhibitors. Among them, IMB-1C was superior in terms of pseudovirus entry inhibition and toxicity. It could bind to both ACE2 and S-RBD and induce conformational change in the S-RBD+ACE2 complex. This is the first study to verify the feasibility of utilizing the Y2H system to discover potent SARS-CoV-2 inhibitors targeting the receptor recognition stage. This approach may also be applied in the discovery of other virus receptor recognition inhibitors. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>Illustrative representation of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) binding to host cells through Spike (S)-angiotensin-converting enzyme 2 (ACE2) interaction. SARS-CoV-2 utilizes human ACE2 as an entry receptor to gain access into target cells. Small-molecule inhibitors that block S-mediated entry offer a promising blueprint for the development of therapeutic interventions.</p>
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<p>Establishment of the yeast-two hybrid (Y2H)-based high-throughput screening (HTS) model targeting S-RBD-ACE2 interaction. (<b>A</b>) Schematic diagram of the Y2H-based S-RBD-ACE2 binding assay. The interaction between ACE2 and S-RBD restores the function of the transcription factor Gal4, leading to the expression of the reporter genes <span class="html-italic">ADE2</span>, <span class="html-italic">HIS3</span>, and <span class="html-italic">LacZ</span>, which ultimately enables the recombinant Y2H system to grow in SD/-Leu/-Trp/-His/-Ade dropout medium. (<b>B</b>) The proliferation of AH109 and AH109 cells carrying various combinations of the Gal4 DNA-binding domain (BD) and the Gal4 activation domain (AD) fusion proteins (pAD-T+pBD-53, pAD-S-RBD+pBD-ACE2, pAD+pBD-ACE2, pAD-S-RBD+pBD, and pAD-T+pBD-λ) on an SD/-Leu/-Trp/-His/-Ade dropout plate. (<b>C</b>) Qualitative assessment of β-gal activity within the Y2H assay. Filter paper containing lysed colonies from selective plates were overlaid with X-gal buffer. Color change can be observed after overnight incubation. (<b>D</b>) Quantitative measurement of β-gal activity within the Y2H assay. Pelleted cells were resuspended in Z-buffer. After the addition of chloroform, SD, ONPG solution, and chilled Na<sub>2</sub>CO<sub>3</sub> successively, absorbance was measured at a wavelength of 420 nm. Data were expressed as mean ± standard deviation of three independent experiments, each performed in triplicate. ** <span class="html-italic">p</span> &lt; 0.01. (<b>E</b>) The expression of S-RBD and ACE2 in newly built Y2H assay detected by the expression of the corresponding vector-tagged proteins. (<b>F</b>) Evaluation of Y2H assay by Pixatimod. Inhibitory effect of Pixatimod on the interaction of S-RBD with ACE2 was tested within the Y2H assay.</p>
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<p>HTS of inhibitors targeting S-RBD-ACE2 interaction. (<b>A</b>) Growth inhibition within Y2H assay by S-RBD-ACE2 interaction inhibitors. AH109 cells with indicated plasmids (pAD-S-RBD+pBD-ACE2 and pAD-T+pBD-53) were treated with hit compounds IMB-1C and IMB-4A (from 0.78 to 100 µg/mL) in 96-well plates in SD/-Leu/-Trp/-His/-Ade dropout medium for 48 h and the growth of cells is shown. (<b>B</b>) The inhibition of β-galactosidide (β-gal) activity of IMB-1C and IMB-4A against AH109 (pAD-S-RBD+pBD-ACE2) cells and their structures. The data show the ratios of β-gal activity of cells treated with compounds over that of untreated cells. The results are mean ± standard deviation (SD) from triplicated assays. (<b>C</b>) The inhibitory effect on SARS-CoV-2 pseudovirus entry into host cells by IMB-1C. Pseudoviruses and compounds, at concentrations of 10 and 20 μg/mL, were incubated at 37 °C for a period of 1 h prior to addition into HEK-293T-hACE2 cells for an additional 18 h incubation. Pseudotyped virus entry into HEK-293T-hACE2 was determined by measuring relative luciferase units (RLU) in cell lysates. IMB-1C showed concentration-dependent inhibition, whereas the negative control showed no significant effect. The results are from triplicated assays. (<b>D</b>) Overview of the screening process for inhibitors of S-RBD and ACE2 interaction. During the initial screening process, 3,500 compounds were evaluated for their ability to inhibit the interaction between S-RBD and ACE2, resulting in the selection of 56 compounds that completely halted the growth of AH109 (pAD-S-RBD+pBD-ACE2) at a concentration of 50 μg/mL. After excluding the ones with antifungal activity, there were 5 compounds left. Among them, only 2 compounds exhibited more potent inhibitory effects on AH109 (pAD-S-RBD+pBD-ACE2) compared to AH109 (pAD-T+pBD-53) with MICs more than 2 times. Ultimately, IMB-1C was chosen as the most promising candidate due to its demonstrated antiviral activity exceeding 50% at a concentration of 40 μg/mL against pseudoviruses.</p>
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<p>The inhibition profile of IMB-1C against the interaction between S-RBD-ACE2 of SARS-CoV-2. (<b>A</b>) IMB-1C inhibited SARS-CoV-2-S-mediated cell–cell fusion. Vero cells (target cells) were co-cultured with HEK-293T/EGFP/SARS-CoV-2-S (effector cells) in the absence or presence of IMB-1C (5, 10, and 20 μmol/L). After co-incubation at 37 °C for 12 h, syncytium formation was observed under a high-content analysis system and the inhibition rate was calculated. The red arrow represents the fused cells. (<b>B</b>) Detection of ACE2-S-RBD binding affinity by surface plasmon resonance (SPR). S-RBD was coated on a SAM chip and serially concentrated solutions of ACE2 (from 6.25 nmol/L to 200 nmol/L) were injected into the chamber. The change in response units is shown. (<b>C</b>) IMB-1C blocked the binding of ACE2 with S-RBD in vitro. S-RBD was fixed and sealed onto the SAM chip, and IMB-1C (0.40 μmol/L) flowed over the SAM chip. After ACE2 was injected, the change in response units is shown. PBSP was injected as the negative control. (<b>D</b>) SPR analysis indicated SARS-CoV-2 S-RBD was the binding partner of IMB-1C. Serially concentrated solutions of IMB-1C (0.10~1.56 µmol/L) were injected into the chamber with a SAM chip coated with S-RBD. The change in response units was shown. (<b>E</b>) SPR analysis indicated that ACE2 was also the binding partner of IMB-1C. Serially concentrated solutions of IMB-1C (0.10~1.56 µmol/L) were injected into the chamber with a SAM chip coated with ACE2. The change in response units is shown. (<b>F</b>) Conformational change in S-RBD+ACE2 complex assessed by Circular dichroism (CD) spectroscopy. The secondary structure of S-RBD+ACE2 complex with or without IMB-1C (10 µmol/L) in PBS was examined by CD spectroscopy. Double minima at 208 nm and 222 nm are revealed. (<b>G</b>) SwissADME analysis for IMB-1C. Radar plot depicts the ADME data of IMB-1C. The pink region signifies the desired range for each property (clockwise from top, lipophilicity: XLOGP3 between −0.7 and +5.0, size: MW between 150 and 500 g/mol, polarity: TPSA between 20 and 130 Å2, solubility: log S ≤ 6, saturation: fraction of carbons in the sp3 hybridization ≥ 0.25, and flexibility: ≤9 rotatable bonds).</p>
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16 pages, 2990 KiB  
Article
A Novel Approach for In Vitro Testing and Hazard Evaluation of Nanoformulated RyR2-Targeting siRNA Drugs Using Human PBMCs
by Valeria Bettinsoli, Gloria Melzi, Angelica Crea, Lorenzo Degli Esposti, Michele Iafisco, Daniele Catalucci, Paolo Ciana and Emanuela Corsini
Life 2025, 15(1), 95; https://doi.org/10.3390/life15010095 - 14 Jan 2025
Viewed by 475
Abstract
Nucleic acid (NA)-based drugs are promising therapeutics agents. Beyond efficacy, addressing safety concerns—particularly those specific to this class of drugs—is crucial. Here, we propose an in vitro approach to screen for potential adverse off-target effects of NA-based drugs. Human peripheral blood mononuclear cells [...] Read more.
Nucleic acid (NA)-based drugs are promising therapeutics agents. Beyond efficacy, addressing safety concerns—particularly those specific to this class of drugs—is crucial. Here, we propose an in vitro approach to screen for potential adverse off-target effects of NA-based drugs. Human peripheral blood mononuclear cells (PBMCs), purified from buffy coats of healthy donors, were used to investigate the ability of NA-drugs to trigger toxicity pathways and inappropriate immune stimulation. PBMCs were selected for their ability to represent potential human responses, given their likelihood of interacting with administered drugs. As proof of concept, a small interfering RNA (siRNA) targeting Ryanodine Receptor mRNA (RyR2) identified by the Italian National Center for Gene Therapy and Drugs based on RNA Technology as a potential therapeutic target for dominant catecholaminergic polymorphic ventricular tachycardia, was selected. This compound and its scramble were formulated within a calcium phosphate nanoparticle-based delivery system. Positive controls for four toxicity pathways were identified through literature review, each associated with a specific type of cellular stress: oxidative stress (tert-butyl hydroperoxide), mitochondrial stress (rotenone), endoplasmic reticulum stress (thapsigargin), and autophagy (rapamycin). These controls were used to define specific mRNA signatures triggered in PBMCs, which were subsequently used as indicators of off-target effects. To assess immune activation, the release of pro-inflammatory cytokines (interleukin-6, interleukin-8, tumor necrosis factor-α, and interferon-γ) was measured 24 h after exposure. The proposed approach provides a rapid and effective screening method for identifying potential unintended effects in a relevant human model, which also allows to address gender effects and variability in responses. Full article
(This article belongs to the Section Pharmaceutical Science)
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<p>Experimental design of the study; created in BioRender. <a href="https://BioRender.com/s74d404" target="_blank">https://BioRender.com/s74d404</a> (accessed on 14 December 2024). PBMC: peripheral blood mononuclear cells; NA-drugs: nucleic-acid drugs; LDH: lactate dehydrogenase; IL: interleukin; TNF: tumor necrosis factor; IFN: interferon.</p>
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<p>Effect of CaP-siRNA and CaP-scramble on cell viability. PBMCs were treated with CaP NPs loaded with RyR2 siRNA (CaP-siRNA), scramble siRNA (CaP-sramble), and non-loaded CaP NPs at three different concentrations (100, 200, 400 nM) for 24 h. The results are reported as percentage of LDH release normalized on CaP NPs (dashed line). Each column represents the mean ± SD (n = 7).</p>
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<p>Effect of CaP-siRNA and CaP-scramble on cytokines release. PBMCs were exposed to CaP NPs loaded with RyR2 siRNA (CaP-siRNA), scramble siRNA (CaP-scramble), and non-loaded CaP NPs at three different concentrations (100, 200, 400 nM) for 24 h. TNF-α (<b>A</b>), IL-8 (<b>B</b>), IL-6 (<b>C</b>), and IFN-γ (<b>D</b>) release were assessed by specific ELISA. Results are normalized on the cytokine release in CaP NPs-treated cells (dashed line). Each column represents the mean ± SD (<span class="html-italic">n</span> = 7). Statistical analysis was performed by one Way ANOVA, Dunnett’s Multiple Comparison test, with # <span class="html-italic">p</span> &lt; 0.05 vs. CaP NPs and ** <span class="html-italic">p</span> &lt; 0.01 vs. CaP-scramble.</p>
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<p>Modulation of the genes involved in the toxicity pathways. The expression of the selected genes was analyzed by RT-PCR 24 h after exposure to CaP NPs loaded with RyR2 siRNA (CaP-siRNA), the scramble siRNA (CaP-scramble), or non-loaded CaP NPs at three different concentrations (100, 200, 400 nM). Results are reported as 2<sup>−ΔΔct</sup> and normalized on the non-loaded CaP NPs gene expression. In the graphs, the results of the gene modulation are reported: autophagy (<b>A</b>) mTOR and (<b>B</b>) ULK1; ER stress (<b>C</b>) ATF4, (<b>D</b>) BBC3, and (<b>E</b>) DDIT3; mitochondrial stress (<b>F</b>) ATF5; oxidative stress (<b>G</b>) SOD1. The black dashed line represents the CaP NPs, and the red dashed line represents the positive controls selected for each pathway (Rapa, TG, Rot, or tBHP). The data of the positive controls are normalized on the DMSO vehicle. Each column represents the mean ± SD, (<span class="html-italic">n</span> = 7). Statistical analysis: One Way ANOVA, Dunnett’s Multiple Comparison test. # <span class="html-italic">p</span> &lt; 0.05 vs. CaP NPs; * <span class="html-italic">p</span> &lt; 0.05 vs. CaP-scramble.</p>
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22 pages, 3444 KiB  
Article
Synthesis, Antimalarial Activity and Molecular Dynamics Studies of Pipecolisporin: A Novel Cyclic Hexapeptide with Potent Therapeutic Potential
by Nety Kurniaty, Taufik Muhammad Fakih, Rani Maharani, Unang Supratman, Ace Tatang Hidayat, Nurhidanatasha Abu Bakar and Xiaoshuang Wei
Molecules 2025, 30(2), 304; https://doi.org/10.3390/molecules30020304 - 14 Jan 2025
Viewed by 281
Abstract
Malaria, caused by Plasmodium species and transmitted by Anopheles mosquitoes, continues to pose a significant global health threat. Pipecolisporin, a cyclic hexapeptide isolated from Nigrospora oryzae, has emerged as a promising antimalarial candidate due to its potent biological activity and stability. This [...] Read more.
Malaria, caused by Plasmodium species and transmitted by Anopheles mosquitoes, continues to pose a significant global health threat. Pipecolisporin, a cyclic hexapeptide isolated from Nigrospora oryzae, has emerged as a promising antimalarial candidate due to its potent biological activity and stability. This study explores the synthesis, antimalarial activity, and computational studies of pipecolisporin, aiming to better understand its therapeutic potential. The peptide was successfully synthesized using Fmoc-based solid-phase peptide synthesis (SPPS) followed by cyclization in solution. The purified compound was characterized using HPLC and mass spectrometry, confirming a molecular ion peak at m/z [M + H]+ 692.4131, which matched the calculated mass. Structural verification through 1H- and 13C-NMR demonstrated strong alignment with the natural product. Pipecolisporin exhibited significant antimalarial activity with an IC50 of 26.0 ± 8.49 nM, highlighting its efficacy. In addition to the experimental synthesis, computational studies were conducted to analyze the interaction of pipecolisporin with key malaria-related enzymes, such as dihydrofolate reductase, plasmepsin V, and lactate dehydrogenase. These combined experimental and computational insights into pipecolisporin emphasize the importance of hydrophobic interactions, particularly in membrane penetration and receptor binding, for its antimalarial efficacy. Pipecolisporin represents a promising lead for future antimalarial drug development, with its efficacy, stability, and binding characteristics laying a solid foundation for ongoing research. Full article
(This article belongs to the Section Bioorganic Chemistry)
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<p>The structure of pipecolisporin.</p>
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<p>Three-dimensional and residue interactions analysis of pipecolisporin with dihydrofolate reductase (2BL9), plasmepsin V (4ZL4), and lactate dehydrogenase.</p>
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<p>Root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) of the pipecolisporin complex.</p>
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<p>Solvent-Accessible Surface Area (SASA) and Radius of Gyration (rGy) of the pipecolisporin complex.</p>
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<p>Radial Distribution Function (RDF) and hydrogen bonds analysis of the pipecolisporin complex.</p>
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<p>Synthesis of pipecolisporin: (a) (2) Fmoc-Pro-OH, DCM, DIPEA, overnight, (b) (3)Fmoc-Pro-resin, piperidine 20%, DMF, 10 min, (c) (4)NH-Pro-Resin, HBTU (3 ek.), HOBt (3 ek.), Fmoc-Leu-OH (3 ek.), DIPEA (6 ek.) 4 mL DMF, 4 h, RT, (d) Piperidine 20%, DMF, 10 min, (e) TFA in water, 60 min, twice, (f) HATU/HOAt DMF, DIPEA, DCM, 72 h, rt.</p>
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Article
Early Use of Liraglutide for the Treatment of Acute COVID-19 Infection: An Open-Label Single-Center Phase II Safety Study with Biomarker Profiling
by Eloara V. M. Ferreira, Rudolf K. F. Oliveira, Reinaldo Salomao, Milena K. C. Brunialti, Martyella B. A. Cardoso, Chien-nien Chen, Lan Zhao and Colm McCabe
Infect. Dis. Rep. 2025, 17(1), 5; https://doi.org/10.3390/idr17010005 - 10 Jan 2025
Viewed by 413
Abstract
Background: Glucagon-like peptide-1 (GLP-1) agonists are an existing treatment option for patients with insulin-resistant states, which elicit further pleiotropic effects related to immune cell recruitment and vascular inflammation. GLP-1 agonists downregulate the cluster of differentiation 147 (CD147) receptor, one of several receptors for [...] Read more.
Background: Glucagon-like peptide-1 (GLP-1) agonists are an existing treatment option for patients with insulin-resistant states, which elicit further pleiotropic effects related to immune cell recruitment and vascular inflammation. GLP-1 agonists downregulate the cluster of differentiation 147 (CD147) receptor, one of several receptors for the SARS-CoV-2 spike protein that mediate viral infection of host cells. Methods: We conducted an open-label prospective safety and tolerability study including biomarker responses of the GLP-1 agonist Liraglutide, administered for 5 days as an add-on therapy to the standard of care within 48 h of presentation in a cohort of 13 patients hospitalized with COVID-19 pneumonia. Biomarker responses were compared in patients admitted to critical care and those not requiring critical care admission (non-critical group). Results: Liraglutide (0.6 mg, subcutaneously) was well tolerated by all patients and all patients were alive 30 days after diagnosis. Plasma soluble CD147 levels were reduced in the non-critical patient group at day 5 in contrast to critical care-treated patients, who demonstrated an increase in soluble CD147 levels between day 0 and day 5. Patients with milder COVID-19 pneumonia severity also demonstrated improvement in echocardiographic parameters of right and left ventricular function, reduction in plasma Troponin levels, increased CD147 expression on T lymphocytes, and reduction in plasma IL-8. Conclusions: This first-in-disease use of the GLP-1 agonist Liraglutide demonstrates its safety and tolerability in an unselected cohort of patients hospitalized with COVID-19 pneumonia across a range of clinical severities. Full article
(This article belongs to the Special Issue Pulmonary Vascular Manifestations of Infectious Diseases)
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<p>Significant changes in clinical parameters from peripheral blood in all study patients in response to 5 days administration of Liraglutide (data recapitulated from <a href="#idr-17-00005-t002" class="html-table">Table 2</a>).</p>
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<p>Fluorescence-activated cell sorting (FACS) data showing changes in mean geometric fluorescence intensities of CD147 positive lymphocyte subpopulations (CD4, CD8, CD19, and CD56 positive) between day 0 and day 5 after treatment with Liraglutide (green/red colour represent greater fluorsecence intensity). No significant changes were observed in fluorescence intensities of CD147 positive lymphocytes across the whole study group following the administration of Liraglutide.</p>
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16 pages, 2015 KiB  
Article
Hybridization Design and High-Throughput Screening of Peptides with Immunomodulatory and Antioxidant Activities
by Junyong Wang, Rijun Zhang, Xuelian Zhao, Jing Zhang, Yucui Tong, Zaheer Abbas, Zhenzhen Li, Haosen Zhang, Dayong Si and Xubiao Wei
Int. J. Mol. Sci. 2025, 26(2), 505; https://doi.org/10.3390/ijms26020505 - 9 Jan 2025
Viewed by 325
Abstract
With the increasing recognition of the role of immunomodulation and oxidative stress in various diseases, designing peptides with both immunomodulatory and antioxidant activities has emerged as a promising therapeutic strategy. In this study, a hybridization design was applied as a powerful method to [...] Read more.
With the increasing recognition of the role of immunomodulation and oxidative stress in various diseases, designing peptides with both immunomodulatory and antioxidant activities has emerged as a promising therapeutic strategy. In this study, a hybridization design was applied as a powerful method to obtain multifunctional peptides. A total of 40 peptides with potential immunomodulatory and antioxidant activities were designed and screened. First, molecular docking was employed to screen peptides with a high binding affinity to MD2, a key receptor protein in the NFκB immune pathway. For the in vitro high-throughput screening, we constructed a reporter gene-based stable cell line, IPEC-J2-Lucia ARE cells, which was subsequently used to screen peptides with antioxidant activity. Furthermore, the biocompatibility, immunomodulatory, and antioxidant activities of these peptides were assessed. Among the candidates, the hybrid peptide VA exhibited the strongest immune-enhancing activity through the activation of the NF-κB pathway and significant antioxidant activity via the Nrf2-ARE pathway. Additionally, VA demonstrated protective effects against H2O2-induced oxidative damage in HepG2 cells. This study not only demonstrates the potential of peptide hybridization, but also develops a screening platform for multifunctional peptides. It provides a new tool for the treatment of autoimmune diseases and oxidative stress-related diseases. Full article
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<p>Workflow for the design and screening of immunomodulatory and antioxidant hybrid peptides.</p>
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<p>Three-dimensional structural modeling of 40 hybrid peptides using PEPFOLD 3.5.</p>
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<p>Biocompatibility evaluation of candidate hybrid peptides and their parent peptides. (<b>a</b>) Hemolytic activity of hybrid peptides and their parent peptides on sheep red blood cells. (<b>b</b>) Cytotoxicity of hybrid peptides and their parent peptides on RAW 264.7 cells. The data are presented as the mean ± SD (n = 3).</p>
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<p>Immunomodulatory activity of candidate hybrid peptides. (<b>a</b>) Level of activation of RAW-Lucia NF-κB cells by hybrid peptides and their parent peptides. (<b>b</b>–<b>d</b>) Effect of hybrid peptides and their parent peptides on the secretion levels of immune-modulatory factors TNF-α (<b>b</b>), IL-1β (<b>c</b>), and IL-6 (<b>d</b>) in RAW 264.7 cells. The data are presented as the mean ± SD (n = 3). * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, and **** <span class="html-italic">p</span> ≤ 0.0001 compared to the CON group.</p>
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<p>Screening and verification of the antioxidant activity of candidate hybrid peptides. (<b>a</b>) Stimulation activity of candidate hybrid peptides and their parent peptides on IPEC-J2-Lucia ARE cells. *** <span class="html-italic">p</span> ≤ 0.001 and **** <span class="html-italic">p</span> ≤ 0.0001 compared to the CON group. (<b>b</b>) Protective effect of candidate hybrid peptides and their parent peptides on H<sub>2</sub>O<sub>2</sub>-induced oxidative damage in the HepG2 model. ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, and **** <span class="html-italic">p</span> ≤ 0.0001 compared to the H<sub>2</sub>O<sub>2</sub>-treated group.</p>
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