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Keywords = redox imbalance

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17 pages, 8975 KiB  
Article
A Novel Class of FKBP12 Ligands Rescues Premature Aging Phenotypes Associated with Myotonic Dystrophy Type 1
by Mikel García-Puga, Gorka Gerenu, Ariadna Bargiela, Jorge Espinosa-Espinosa, Laura Mosqueira-Martín, Maialen Sagartzazu-Aizpurua, Jesús M. Aizpurua, Ainara Vallejo-Illarramendi, Rubén Artero, Adolfo López de Munain and Ander Matheu
Cells 2024, 13(23), 1939; https://doi.org/10.3390/cells13231939 - 22 Nov 2024
Viewed by 266
Abstract
Background: Myotonic dystrophy type 1 (DM1) is an autosomal dominant disorder clinically characterized by progressive muscular weakness and multisystem degeneration, which correlates with the size of CTG expansion and MBLN decrease. These changes induce a calcium and redox homeostasis imbalance in several models [...] Read more.
Background: Myotonic dystrophy type 1 (DM1) is an autosomal dominant disorder clinically characterized by progressive muscular weakness and multisystem degeneration, which correlates with the size of CTG expansion and MBLN decrease. These changes induce a calcium and redox homeostasis imbalance in several models that recapitulate the features of premature tissue aging. In this study, we characterized the impact of a new family of FKBP12 ligands (generically named MPs or MP compounds) designed to stabilize FKBP12 binding to the ryanodine receptors and normalize calcium dysregulation under oxidative stress. Methods: Human primary fibroblasts from DM1 patients and control donors, treated with MP compounds or not, were used for functional studies of cell viability, proliferation, and metabolism. The gene expression profile in treated cells was determined using RNA sequencing. The impact of MP compounds in vivo was evaluated in a Drosophila model of the disease using locomotor activity and longevity studies. Results: The treatment with different MP compounds reversed oxidative stress and impaired cell viability and proliferation, mitochondrial activity, and metabolic defects in DM1-derived primary fibroblasts. RNA sequencing analysis confirmed the restoration of molecular pathways related to calcium and redox homeostasis and additional pathways, including the cell cycle and metabolism. This analysis also revealed the rescue of alternative splicing events in DM1 fibroblasts treated with MP compounds. Importantly, treatment with MP compounds significantly extended the lifespan and improved the locomotor activity of a Drosophila model of the DM1 disease, and restored molecular defects characteristic of the disease in vivo. Conclusions: Our results revealed that MP compounds rescue multiple premature aging phenotypes described in DM1 models and decipher the benefits of this new family of compounds in the pre-clinical setting of DM1. Full article
(This article belongs to the Section Cellular Aging)
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Figure 1

Figure 1
<p>MP compounds restore DM1 cell viability and redox homeostasis. (<b>A</b>–<b>C</b>) Cell viability, intracellular calcium measurement, and ROS levels in fibroblasts derived from DM1 patients and controls. Values in DM1 are relative to controls. Dots represent mean values from control and patient individuals. Delineated dots in B represent average values from at least 30 cells, represented as non-delineated dots. (<b>D</b>) Cell viability of DM1 fibroblasts after treatment with 0.1 µM of indicated MP compounds for 72 h (n = 3, different individuals). (<b>E</b>,<b>F</b>) Cell viability of control and DM1 fibroblasts after treatment with 0.1, 1, and 10 µM of MP-001 and MP-002 for 72 h (n = 3). (<b>G</b>) Intracellular calcium measurement in same conditions as ((<b>E</b>); n = 3). (<b>H</b>) ROS levels in fibroblasts derived from DM1 patients and controls after treatment with 0.1 µM of MP-001 and MP-002 for 72 h (n = 3). <span class="html-italic"><sup>≠</sup> p</span> &lt; 0.1, * <span class="html-italic">p</span> &lt; 0.05, and ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 2
<p>MP compounds restore DM1 cell proliferation and metabolism. (<b>A</b>) Quantification of the number of P-H3-positive cells in independent control and DM1 fibroblasts (n &gt; 3) after treatment with 0.1 µM of MP-001 and MP-002 for 72 h. (<b>B</b>) mRNA levels of <span class="html-italic">p16<sup>INK4A</sup></span>, <span class="html-italic">p21<sup>CIP1</sup>,</span> and <span class="html-italic">p14<sup>ARF</sup></span> in control and DM1 fibroblasts (n ≥ 3), (<b>C</b>) and after treatment with 0.1 µM of MPs for 72 h. (<b>D</b>–<b>F</b>) Quantification of basal, maximal respiration, and ATP production in controls and DM1 (n &gt; 3) fibroblasts after 0.1 µM MP compound treatment. (<b>G</b>) Kinetic normalized OCR response in DM1 fibroblasts in the absence or presence of 0.1 µM of MP-001 and MP-002. <span class="html-italic"><sup>≠</sup> p</span> &lt; 0.1, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 3
<p>MP-002 rescues molecular alterations in DM1 fibroblasts. (<b>A</b>,<b>B</b>) mRNA levels of indicated genes in control and DM1 fibroblasts (n = 3). (<b>C</b>,<b>D</b>) Bar plot of the -log10 (p-value) of the significantly upregulated and downregulated GO terms in DM1 fibroblasts treated with MP-002 (n = 3). <span class="html-italic"><sup>≠</sup> p</span> &lt; 0.1, and * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 4
<p>MP-002 rescues splicing events. (<b>A</b>) Quantity of splicing events in each dPSI. (<b>B</b>) Quantity of types of splicing events in each comparison. (<b>C</b>) Venn diagram of common genes in each comparison. (<b>D</b>) Change in direction of the splicing events affected by the treatment. (<b>E</b>) Point plot of the top 10 recovered genes. (<b>F</b>) Bar plot of the -log10 (p-value) of the significantly altered GO terms from genes with aberrant splicing events in DM1 fibroblasts treated with MP-002 (n = 3). (<b>G</b>,<b>H</b>) Quantification of splicing in <span class="html-italic">BIN</span>, <span class="html-italic">MLF1</span>, and <span class="html-italic">MBNL1</span> in control and DM fibroblasts and restoration after MP treatment (n = 3). <span class="html-italic"><sup>≠</sup> p</span> &lt; 0.1, * <span class="html-italic">p</span> &lt; 0.05, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 5
<p>MP-002 restores molecular and functional defects in DM1 <span class="html-italic">Drosophila melanogaster</span>. (<b>A</b>–<b>D</b>) mRNA levels of indicated genes in the thorax of DM1 and control fruit flies (n = 3, each point represents a pool of six flies). (<b>E</b>–<b>H</b>) mRNA levels of indicated genes from the thorax of DM1 fruit flies in the presence of 10 and 100 µM of MP (n = 3, each datapoint comes from a pool of six flies). (<b>I</b>) Locomotor activity of non-treated DM1 (n = 50) flies or in the presence of 10 and 100 µM of MP (n = 50) at the indicated time points. Student <span class="html-italic">t</span>-test values are at 20 days <span class="html-italic">p</span> = 0.02 and <span class="html-italic">p</span> = 0.002, and at 25 days <span class="html-italic">p</span> &lt;0.0001 compared to non-treated flies. <span class="html-italic"><sup>≠</sup> p</span> &lt; 0.1, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 6
<p>MP-002 extends lifespan in DM1 <span class="html-italic">Drosophila melanogaster</span>. (<b>A</b>,<b>B</b>) Survival curves of control (<span class="html-italic">wt</span>), non-treated DM1 (DM1 -), and DM1 flies in the presence of 10 µM (DM1 MP2 10) and 100 µM (DM1 MP2 100) of MP-002 treated since larval stage divided by sexes; male (<b>A</b>), female (<b>B</b>), (n = 100). LogRank values are <span class="html-italic">p</span> &lt; 0.0001 for both sexes compared to non-treated flies. (<b>C</b>,<b>D</b>) Survival curves of control flies, DM1 flies non-treated, and DM1 flies in the presence of 10 and 100 µM of MP-002 treated since adulthood divided by sexes; male (<b>C</b>), female (<b>D</b>), (n = 100). LogRank values are <span class="html-italic">p</span> &lt; 0.0001 for both sexes. (<b>E</b>) Survival curve of control flies, non-treated, or in the presence of 10 µM of MP-002 treated since adulthood (n = 50). LogRank value is <span class="html-italic">p</span> &lt; 0.05.</p>
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13 pages, 1855 KiB  
Article
Treatment with Pterostilbene Ameliorates the Antioxidant Status of Bovine Spermatozoa and Modulates Cell Death Pathways
by Christos Chavas, Vasiliki G. Sapanidou, Konstantinos Feidantsis, Sophia N. Lavrentiadou, Despoina Mavrogianni, Ioanna Zarogoulidou, Dimitrios J. Fletouris and Maria P. Tsantarliotou
Antioxidants 2024, 13(12), 1437; https://doi.org/10.3390/antiox13121437 - 22 Nov 2024
Viewed by 239
Abstract
Reactive Oxygen Species (ROS) play an important role in sperm physiology. They are required in processes such as capacitation and fertilization. However, the exposure of spermatozoa to ROS generated from internal or external sources may create a potentially detrimental redox imbalance. Antioxidant supplementation [...] Read more.
Reactive Oxygen Species (ROS) play an important role in sperm physiology. They are required in processes such as capacitation and fertilization. However, the exposure of spermatozoa to ROS generated from internal or external sources may create a potentially detrimental redox imbalance. Antioxidant supplementation in semen is now a rather common approach to protect spermatozoa from oxidative stress (OS) during their handling and/or cryopreservation. Supplementation with pterostilbene, a potent antioxidant, protects spermatozoa from OS and ameliorates their post-thawing characteristics and viability. In the present study, we used freezing/thawing as a model of natural ROS overproduction and investigated the molecular mechanisms modulated by pterostilbene. Specifically, bovine frozen/thawed spermatozoa were incubated with 10 or 25 μM pterostilbene for 60 min. Results have shown that in a dose-independent manner, pterostilbene decreased lipid peroxidation and increased intracellular GSH levels. Moreover, pterostilbene ameliorated energy production, as ATP and AMP/ATP levels were restored, and increased autophagy levels through AMP-activated protein kinase (AMPK) activation, which finally resulted in the inhibition of apoptotic cell death in bovine spermatozoa when exposed to OS. This study sheds light on spermatozoa redox state, the crosstalk between apoptotic and autophagic pathways, and its role in determining the beneficial or detrimental effect of ROS in spermatozoa. Full article
(This article belongs to the Special Issue Oxidative Stress in Reproduction of Mammals)
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Figure 1

Figure 1
<p>MDA (<b>A</b>), total antioxidant capacity (<b>B</b>), and intracellular GSH (<b>C</b>) levels in bovine spermatozoa under the effect of 10 μM (P10) or 25 μM (P25) pterostilbene treatments. Values constitute means ± S.D. Asterisks (*) denote statistically significant differences compared to control (<span class="html-italic">p</span> &lt; 0.05, n = 6). No statistically significant differences were found between the P10 and P25 groups.</p>
Full article ">Figure 2
<p>Bax (<b>A</b>), Bcl-2 (<b>B</b>), Bax/Bcl-2 (<b>C</b>), and cleaved caspase (<b>D</b>) levels in bovine spermatozoa in the presence of 10 μM (P10) or 25 μM (P25) pterostilbene. Values constitute means ± S.D. Spermatozoa extracts from control, P10, and P25 groups were immunoblotted for Bax, Bcl-2, and cleaved caspases. The levels of β-actin were determined to verify equal loading. Representative blots are shown (<a href="#app1-antioxidants-13-01437" class="html-app">Figures S2 and S3</a>). Asterisks (*) denote statistically significant differences compared to the control (<span class="html-italic">p</span> &lt; 0.05, n = 6). No statistically significant differences were found between P10 and P25 groups.</p>
Full article ">Figure 3
<p>AMP (<b>A</b>) and ATP (<b>B</b>) levels and AMP/ATP (<b>C</b>) ratios in bovine spermatozoa treated with 10 μM (P10) or 25 μM (P25) pterostilbene. Values constitute means ± S.D. Asterisks (*) denote statistically significant differences compared to the control (<span class="html-italic">p</span> &lt; 0.05, n = 6). No statistically significant differences were found between P10 and P25 groups.</p>
Full article ">Figure 4
<p>Phospho AMPK/AMPK ratio (<b>A</b>), ubiquitin conjugates (<b>B</b>), LC3 II/I ratio (<b>C</b>), and SQSTM1/p62 (<b>D</b>) levels in bovine spermatozoa exposed to 10 μM (P10) or 25 μM (P25) pterostilbene treatments. Values constitute means ± S.D. Spermatozoa extracts from control, P10, and P25 groups were immunoblotted for phospho AMPK, AMPK, ubiquitin conjugates, LC3, and SQSTM1/p62. The levels of β-actin were determined to verify equal loading. Representative blots are shown (<a href="#app1-antioxidants-13-01437" class="html-app">Figures S4–S7</a>). Asterisks (*) denote statistically significant differences compared to the control (<span class="html-italic">p</span> &lt; 0.05, n = 6). No statistically significant differences were found between P10 and P25 groups.</p>
Full article ">Figure 5
<p>Summarized model of pterostilbene’s effect on biochemical and physiological stress responses in bovine spermatozoa exposed to oxidative stress.</p>
Full article ">
21 pages, 7859 KiB  
Article
Flavonoid Fisetin Alleviates Ovarian Aging of Laying Chickens by Enhancing Antioxidant Capacity and Glucose Metabolic Homeostasis
by Zhaoyu Yang, Jiaxuan Zhang, Qiongyu Yuan, Xinyu Wang, Weidong Zeng, Yuling Mi and Caiqiao Zhang
Antioxidants 2024, 13(12), 1432; https://doi.org/10.3390/antiox13121432 - 21 Nov 2024
Viewed by 267
Abstract
Oxidative stress is a crucial factor contributing to ovarian follicular atresia and an imbalance in ovarian energy metabolism in poultry, leading to decreased laying performance in aging hens. This study aimed to investigate the effects of a natural flavonoid, fisetin, on laying performance, [...] Read more.
Oxidative stress is a crucial factor contributing to ovarian follicular atresia and an imbalance in ovarian energy metabolism in poultry, leading to decreased laying performance in aging hens. This study aimed to investigate the effects of a natural flavonoid, fisetin, on laying performance, ovarian redox status, and energy metabolism in laying chickens. The results showed that dietary fisetin supplementation improved egg production and eggshell quality in aging laying chickens, reduced follicular atresia rate, promoted ovarian cell proliferation, elevated serum estrogen and progesterone levels, restored ovarian antioxidant capacity, and improved energy metabolism. Furthermore, fisetin treatment increased the activity of antioxidant enzymes by inhibiting NF-κB signaling and COX-2 expression while promoting SIRT1 expression in the H2O2-induced small white follicle (SWF). Additionally, fisetin significantly enhanced the anti-apoptotic capacity of SWF and promoted glucose catabolism by activating the AKT and JNK signaling pathways. In summary, fisetin supplementation can alleviate ovarian oxidative stress in aging laying chickens by upregulating SIRT1 expression and inhibiting NF-κB signaling. The activation of AKT and JNK signaling pathways by fisetin contributes to the balance of energy metabolism and promotion of follicular development in the ovaries of aging laying chickens, thereby retarding ovarian aging in poultry production. Full article
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Figure 1
<p>Effect of fisetin on follicle development, egg quality, and hormone balance in NA-OF model. (<b>A</b>) Experimental design of fisetin treatment and analysis in NA-OF model. (<b>B</b>) Scanning electron microscope (SEM) images of eggshells, displaying cross-sections, outer surfaces, and inner surfaces. TT: Total thickness; ET: effective thickness. White arrows indicate calcareous fibers. (<b>C</b>) Eggshell effective thickness (<span class="html-italic">n</span> = 6). (<b>D</b>) Ovaries of aged laying chickens (580-day-old). Avian ovarian follicles are generally categorized by size or color: large preovulatory follicles (F1, F2, F3, etc.), small yellow follicle (SYF), large white follicle (LWF), and small white follicle (SWF). Black arrow: post-ovulation follicle; AF: atretic follicle. (<b>E</b>) Levels of serum estrogen (E<sub>2</sub>) and progesterone (P<sub>4</sub>) (<span class="html-italic">n</span> = 15). (<b>F</b>) Relative mRNA expression of steroid synthesis-related genes (<span class="html-italic">CYP11A1</span>, <span class="html-italic">CYP19A1</span>) in SWF. (<b>G</b>) Images and rate of atretic follicles (<span class="html-italic">n</span> = 6). (<b>H</b>) Western blot and quantitative analysis of CYP11A1 expression in SWF (<span class="html-italic">n</span> = 3). Values are shown as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 2
<p>Effect of fisetin on proliferation and antioxidant enzymes in NA-OF model. (<b>A</b>) Typical images of PCNA expression (TRITC, red) in the ovary and SWF from young (280-day-old) and aged (580-day-old) laying chickens. TL: theca layer; GL: granulosa layer; GF: growing follicle. Yellow arrow: PCNA-positive cell. Nuclei were stained blue with DAPI. Scale bars: 50 μm and 100 μm. (<b>B</b>) PCNA positivity rate of SWF from aged laying chickens (<span class="html-italic">n</span> = 6). The proliferative level was determined by the PCNA positivity rate. (<b>C</b>) Western blotting showing the expression of PCNA, BAX, and Caspase-3 in SWF (<span class="html-italic">n</span> = 3). (<b>D</b>) The mRNA expression levels of cell cycle-related genes (<span class="html-italic">PCNA</span>, <span class="html-italic">CCND1</span>, <span class="html-italic">CDK2</span>, <span class="html-italic">Bcl-2</span>, <span class="html-italic">Bax</span>, <span class="html-italic">Caspase 3</span>, and <span class="html-italic">Caspase 9</span>) in SWF. (<b>E</b>) H&amp;E staining ovaries harvested from young and aged laying chickens. Asterisk: atretic ovarian follicle. (<b>F</b>) Relative mRNA expression of antioxidant-related genes (<span class="html-italic">Mgst</span>, <span class="html-italic">Gsta</span>, <span class="html-italic">Gsr</span>, <span class="html-italic">Cat</span>, and <span class="html-italic">Sod</span>) in SWF (<span class="html-italic">n</span> = 6). (<b>G</b>) Levels of oxidative- and antioxidant-related parameters (T-SOD, CAT, GSH-px, GSH-ST, T-AOC, GSH, MDA, and H<sub>2</sub>O<sub>2</sub>) in SWF (<span class="html-italic">n</span> = 6). Values are shown as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 3
<p>Effect of fisetin on ovarian glucose catabolism in the NA-OF model. (<b>A</b>) Immunofluorescence images of ovaries stained with GLUT1, PFKFB2, and LDHA antibodies (Red: positive cells; Blue: DAPI), and images in the white dotted boxes were enlarged on the right. Scale bar: 50 μm and 20 μm. Green arrow: cyst germ cell (CGC); white arrow: primordial follicle (PF); GF: growing follicle. (<b>B</b>) Relative protein expression of glucose metabolism-related enzymes (GLUT1, PFKFB2, HK2, SDHA) in SWF (<span class="html-italic">n</span> = 3). (<b>C</b>) Relative mRNA expressions of glycolysis-related genes (<span class="html-italic">GLUT1</span>, <span class="html-italic">HK1</span>, <span class="html-italic">LDHA</span>, <span class="html-italic">PFKP</span>, <span class="html-italic">SDHA</span>, <span class="html-italic">IDH1</span>, and <span class="html-italic">PKM</span>) in SWF. (<b>D</b>) Total contents of pyruvate, lactate, and ATP in SWF (<span class="html-italic">n</span> = 6). Values are shown as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of fisetin on the HA-OF model. (<b>A</b>) H&amp;E staining images of SWF, scale bar: 100 μm. The red arrowhead indicates granulosa cell layer. (<b>B</b>) Immunofluorescence images of SWF stained with BrdU (red), scale bar: 50 μm. (<b>C</b>) TUNEL-stained (green) images of SWF, scale bar: 20 μm. (<b>D</b>) BrdU positivity rates and mRNA levels of cell cycle-related genes (<span class="html-italic">CDK2</span>, <span class="html-italic">PCNA</span>) in SWF (<span class="html-italic">n</span> = 4). (<b>E</b>) TUNEL positivity rates and relative expression levels of apoptosis-related genes (<span class="html-italic">Caspase 3</span>, <span class="html-italic">Caspase 9</span>) in SWF (<span class="html-italic">n</span> = 4). (<b>F</b>) Western blot analysis of GLUT1, HK2, LDHA, Caspase-3, and PCNA in SWF (<span class="html-italic">n</span> = 3). Values are presented as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>Effect of fisetin on antioxidant- and glucose metabolism-related enzymes in the HA-OF model. (<b>A</b>) Levels of oxidation- and antioxidant-related parameters (CAT, GSH-ST, GSH-px, T-SOD, T-AOC, GSH, MDA, and H<sub>2</sub>O<sub>2</sub>) in SWF (<span class="html-italic">n</span> = 6). (<b>B</b>) Levels of lactate, pyruvate, and ATP in SWF (<span class="html-italic">n</span> = 6). (<b>C</b>) Relative mRNA expression of antioxidant enzyme genes (<span class="html-italic">Gsr</span>, <span class="html-italic">Mgst</span>, <span class="html-italic">Cat</span>, <span class="html-italic">Sod</span>, and <span class="html-italic">Trx</span>) and glucose metabolism-related enzyme genes (<span class="html-italic">HK1</span>, <span class="html-italic">HK2</span>, <span class="html-italic">PFKL</span>, <span class="html-italic">IDH1</span>, <span class="html-italic">PFKM</span>, <span class="html-italic">PKM</span>, <span class="html-italic">SDHA</span>, <span class="html-italic">SDHB</span>, <span class="html-italic">LDHA</span>, and <span class="html-italic">LDHB</span>) in SWF (<span class="html-italic">n</span> = 4). Values are shown as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 6
<p>Effect of fisetin on the NF-κB signaling pathway in the HA-OF model. (<b>A</b>) Inhibition of NF-κB by fisetin in H<sub>2</sub>O<sub>2</sub>-induced SWF, as revealed by Western blot analysis (<span class="html-italic">n</span> = 3). Phosphorylated NF-κB p65, total NF-κB p65, SIRT-1, and COX-2 were analyzed. (<b>B</b>) Immunohistochemical staining for SIRT-1 and p-p65 in SWF. Black arrows indicate the localization of p-p65, primarily expressed in granulosa cells. Red arrows indicate the localization of SIRT-1, primarily expressed in theca cells. (<b>C</b>) Expression of p-p65 in ovaries (FITC, green). White arrows indicate the presence of phosphorylated p65 in ovarian follicles and its translocation to the nucleus. Scale bar: 20 μm. (<b>D</b>) Levels of oxidative and antioxidant-related parameters. (<b>E</b>) Western blot analysis of p-p65/p65, SIRT-1, and COX-2 in SWF (<span class="html-italic">n</span> = 3). (<b>F</b>) Levels of <span class="html-italic">Cat</span>, <span class="html-italic">Sod2</span>, and <span class="html-italic">Mgst</span> mRNAs in SWF (<span class="html-italic">n</span> = 3). Values are presented as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 7
<p>Effect of fisetin on the AKT signaling and the JNK signaling in the HA-OF model. (<b>A</b>) Immunohistochemical staining of p-JNK and p-AKT in SWF. Scale bars: 20 μm and 50 μm. (<b>B</b>) Activation of AKT signaling by fisetin in the H<sub>2</sub>O<sub>2</sub>-induced SWF. Phosphorylated AKT (Ser473) and total AKT were examined by Western blot. Quantification of AKT and its downstream signaling (p-AKT/AKT, PCNA, CCND1, BAX, BCL-2, and Caspase 3) was plotted on the right. The apoptotic level was determined by the normalized ratio of cleaved to total Caspase 3 and the protein quantification of BAX (<span class="html-italic">n</span> = 3). (<b>C</b>) Activation of JNK and regulation of glucose metabolism-related enzyme expression by fisetin, revealed by Western blot. Quantification of p-JNK/JNK, GLUT1, HK2, PFKFB2, LDHA, and SDHA is plotted on the right (<span class="html-italic">n</span> = 3). Values are shown as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 8
<p>Fisetin promoted ovarian energy metabolism of laying chickens via AKT and JNK signaling pathways. (<b>A</b>) Activation of AKT and JNK signaling was inhibited by AT (100 μM). Total AKT, phosphorylated AKT, total JNK, and phosphorylated JNK were assessed in SWF by Western blot analysis. (<b>B</b>) Western blot and quantitative analyses of total AKT, phosphorylated AKT, total JNK and phosphorylated JNK expression in SWF (<span class="html-italic">n</span> = 3) after SP treatment (50 μM). (<b>C</b>) Western blot and quantitative analyses of GLUT1, HK2, PFKFB2, LDHA, and SDHA after SP treatment (50 μM) in SWF (<span class="html-italic">n</span> = 3). (<b>D</b>) Immunofluorescence images of ovaries stained with GLUT1 (TRITC, red). Scale bar: 20 μm. (<b>E</b>) Levels of lactate and pyruvate in SWF (<span class="html-italic">n</span> = 6). Values are shown as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 9
<p>Effect of fisetin on the growth and development, antioxidant properties, and energy metabolism of aged SWF in vitro. (<b>A</b>) Representative images of BrdU (red) and TUNEL (green) assay of SWF in each group. The red dots represent proliferation-positive cells, and green dots represent apoptosis-positive cells. Scale bar: 50 μm. (<b>B</b>) Quantification of BrdU and TUNEL assay (<span class="html-italic">n</span> = 6). (<b>C</b>) Representative H&amp;E staining images of SWF after 72 h culture in vitro, and images in the black dotted boxes were enlarged on the right. (<b>D</b>) Protein expression levels of BAX and BCL-2 in aged SWF (<span class="html-italic">n</span> = 3). (<b>E</b>) Relative mRNA levels of cell cycle-related genes (<span class="html-italic">PCNA</span>, <span class="html-italic">CCND1</span>, <span class="html-italic">CDK6</span>, <span class="html-italic">Bcl-2</span>, <span class="html-italic">Bax</span>, <span class="html-italic">Caspase 8</span>, and <span class="html-italic">Caspase 9</span>) in aged SWF (<span class="html-italic">n</span> = 3). (<b>F</b>) Levels of CAT, T-SOD, GSH-ST, GSH-Px, T-AOC, GSH, H<sub>2</sub>O<sub>2</sub>, and MDA in aged SWF (<span class="html-italic">n</span> = 6). (<b>G</b>) Relative mRNA levels of antioxidant-related genes (<span class="html-italic">Sod</span>, <span class="html-italic">Cat</span>, <span class="html-italic">Mgst</span>, <span class="html-italic">Gsr</span>, <span class="html-italic">Gsta</span>, <span class="html-italic">Trx</span>, and <span class="html-italic">Gclm</span>) in aged SWF (<span class="html-italic">n</span> = 4). (<b>H</b>) Transcription levels of glucose metabolism-related genes (<span class="html-italic">PKM</span>, <span class="html-italic">PFKM</span>, <span class="html-italic">LDHB</span>, <span class="html-italic">HK1</span>, <span class="html-italic">PFKL</span>, <span class="html-italic">LDHA</span>, and <span class="html-italic">SDHB</span>) in aged SWF (<span class="html-italic">n</span> = 4). (<b>I</b>) Contents of lactate, pyruvate and ATP in aged SWF (<span class="html-italic">n</span> = 6). (<b>J</b>) Relative protein levels of GLUT1, HK2, PFKFB2, and SDHA in aged SWF (<span class="html-italic">n</span> = 3). Values are shown as mean ± SEM. Different letters represent statistically significant differences among the groups (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Schematic diagram illustrating the mechanism by which fisetin alleviates ovarian aging in laying chickens.</p>
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15 pages, 325 KiB  
Review
Oxidative Imbalance in Psoriasis with an Emphasis on Psoriatic Arthritis: Therapeutic Antioxidant Targets
by Rafał Bilski, Daria Kupczyk and Alina Woźniak
Molecules 2024, 29(22), 5460; https://doi.org/10.3390/molecules29225460 - 19 Nov 2024
Viewed by 264
Abstract
Psoriasis and psoriatic arthritis (PsA) are chronic autoimmune diseases characterized by persistent inflammation and oxidative imbalance. Oxidative stress, caused by excessive production of reactive oxygen species (ROS) and dysfunction in antioxidant mechanisms, plays a critical role in the pathogenesis of both conditions, leading [...] Read more.
Psoriasis and psoriatic arthritis (PsA) are chronic autoimmune diseases characterized by persistent inflammation and oxidative imbalance. Oxidative stress, caused by excessive production of reactive oxygen species (ROS) and dysfunction in antioxidant mechanisms, plays a critical role in the pathogenesis of both conditions, leading to increased inflammatory processes and tissue damage. This study aims to review current antioxidant-based therapeutic options and analyze oxidative stress biomarkers in the context of psoriasis and PsA. Based on available literature, key biomarkers, such as malondialdehyde (MDA), advanced glycation end-products (AGEs), and advanced oxidation protein products (AOPP), were identified as being elevated in patients with psoriasis and PsA. Conversely, antioxidant enzymes, such as superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx), showed reduced activity, correlating with symptom severity. The study also examines the efficacy of various antioxidant therapies, including curcumin, resveratrol, coenzyme Q10, and vitamins C and E, which may aid in reducing oxidative stress and alleviating inflammation. The findings indicated that antioxidants can play a significant role in alleviating symptoms and slowing the progression of psoriasis and PsA through modulation of redox mechanisms and reduction of ROS levels. Antioxidant-based therapies offer a promising direction in treating autoimmune diseases, highlighting the need for further research on their efficacy and potential clinical application. Full article
11 pages, 1721 KiB  
Article
Disruptions of rpiAB Genes Encoding Ribose-5-Phosphate Isomerases in E. coli Increases Sensitivity of Bacteria to Antibiotics
by Tatyana A. Seregina, Rustem S. Shakulov, Svetlana A. Sklyarova and Alexander S. Mironov
Cells 2024, 13(22), 1915; https://doi.org/10.3390/cells13221915 - 19 Nov 2024
Viewed by 308
Abstract
In Escherichia coli cells, the main enzymes involved in pentose interconversion are ribose-5-phosphate isomerases RpiA and RpiB and ribulose-5-phosphate epimerase Rpe. The inactivation of rpiAB limits ribose-5-phosphate (R5P) synthesis via the oxidative branch of the pentose phosphate pathway (PPP) and unexpectedly results in [...] Read more.
In Escherichia coli cells, the main enzymes involved in pentose interconversion are ribose-5-phosphate isomerases RpiA and RpiB and ribulose-5-phosphate epimerase Rpe. The inactivation of rpiAB limits ribose-5-phosphate (R5P) synthesis via the oxidative branch of the pentose phosphate pathway (PPP) and unexpectedly results in antibiotic supersensitivity. This type of metabolism is accompanied by significant changes in the level of reducing equivalents of NADPH and glutathione, as well as a sharp drop in the ATP pool. However, this redox and energy imbalance does not lead to the activation of the soxRS oxidative stress defense system but the increased sensitivity to oxidants paraquat and H2O2. The deletion of rpiAB leads to a significant increase in the activity of transketalase (Tkt), a key enzyme of the nonoxidative branch of the PPP and increased sensitivity to ribose added in the growth medium. The phenotype of supersensitivity of rpiAB to antibiotics and ribose can be suppressed by activating the utilization of sedoheptulose-7-phosphate, which originates from R5P, to LPS synthesis or limitation of nucleoside catabolism by the inactivation of the DeoB enzyme, responsible for conversion of ribose-1-phospate to R5P. Our results indicate that the induction of unidirectional synthesis of R5P is the cause of supersensitivity to antibiotics in rpiAB mutant. Full article
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Figure 1

Figure 1
<p>(<b>a</b>) Scheme of canonical pentose phosphate pathway (PPP). Isomerases RpiA and RpiB convert ribulose-5-phosphate (Ru5P) to R5P. Rpe epimerase catalyzes the reaction that converts Ru5P to xylose 5-phosphate (Xu5P). As a result of the synthesis of R5P in the oxidative branch of PPP, the reduction in NADP<sup>+</sup> equivalents occurs. Excess PPs can be returned to glycolysis through the non-oxidative branch of PPP. (<b>b</b>) Inactivation of <span class="html-italic">rpiA</span> and <span class="html-italic">rpiB</span> genes does not lead to cell death since the synthesis of R5P from the glycolysis products fructose-6-phosphate (F6P) and glyceraldehyde-3-phosphate (GAP) is possible by reversing the non-oxidative branch of PPP. Abbreviations used: G6P—glucose-6-phosphate; 6PG—6-phosphogluconate; Ru5P—ribulose-5-phosphate; R5P—ribose-5-phosphate; Xu5P—xylose-5-phosphate; S7P—sedoheptulose-7-phosphate; DHAP—dihydroxyacetone phosphate; E4P—erythrose-4-phosphate; F6P—fructose-6-phosphate; GAP—glyceraldehyde-3-phosphate.</p>
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<p>Sensitivity of <span class="html-italic">E. coli</span> strains with inactivated <span class="html-italic">rpiAB</span> and <span class="html-italic">rpe</span> genes to various antibiotics. (<b>a</b>) Representative efficiencies of colony formation of WT (MG1655) and mutant <span class="html-italic">E. coli</span> cells in the presence of antibiotics: quinolones (nalidixic acid (Nal) and moxifloxacin (Mox)), aminoglycosides (gentamicin (Gm), macrolides (erythromycin (Em)), inhibitors RNA polymerase (rifampicin (Rif)). Cells were spotted on LB agar plates in serial 10-fold dilutions and incubated at 37 °C for 24 h; (<b>b</b>) cell survival was determined by counting cfu and is shown as the mean ± SD from three independent experiments. * <span class="html-italic">p</span> &lt; 0.05, compared to the wild-type cells. Overnight cultures of indicated <span class="html-italic">E. coli</span> strains were diluted with fresh LB 1:100 and grown to OD<sub>600nm</sub> ≈ 0.5. Antibiotics were added for 30 min at concentration 25 µg/mL Nal, 3 µg/mL Mox, 3 µg/mL Gm, 150 µg/mL Em and 25 µg/mL Rif.</p>
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<p>Levels of reduced equivalents of (<b>a</b>) NADPH, (<b>b</b>) glutathione, and (<b>c</b>) ATP in the ∆<span class="html-italic">rpiAB</span> and ∆<span class="html-italic">rpe</span> mutants. Mean values ± SD from at least three independent experiments are shown. * <span class="html-italic">p</span> &lt; 0.05, compared to the wild-type cells.</p>
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<p><span class="html-italic">∆rpiAB</span> and <span class="html-italic">∆rpe</span> mutants exhibit resistance to oxidative stress. (<b>a</b>) Luminescence intensity of the lux-biosensor containing the <span class="html-italic">soxS</span> promoter in the ∆<span class="html-italic">rpiAB</span> and ∆<span class="html-italic">rpe</span> strains. The <span class="html-italic">∆zwf</span> strain was used as a positive control; (<b>b</b>) cell survival of ∆<span class="html-italic">rpiAB</span> and ∆<span class="html-italic">rpe</span> strains in the presence of hydrogen peroxide (2.5 mM) and paraquat (PQ) (250 µM). Cell suspensions were incubated in the presence of oxidizing agents for 30 min at 37 °C and plated on plates with solid medium to count colonies. Mean values ± SD from at least three independent experiments are shown.</p>
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<p>(<b>a</b>) Growth curves of the parent strain MG1655 (wt) and mutants <span class="html-italic">rpiAB</span> and <span class="html-italic">rpe</span>. (<b>b</b>) Representative curves demonstrating the effect of exogenous pentoses on the growth of <span class="html-italic">rpiAB</span> and <span class="html-italic">rpe</span> mutants. Cells were grown in complete LB medium supplemented with 0.1% ribose or xylose. (<b>c</b>) Level of transketolase activity in cell extracts of the parental strain and mutants. Mean values ± SD from at least three independent experiments are shown.</p>
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<p>(<b>а</b>) Inactivation of the nucleoside catabolism gene (∆<span class="html-italic">deoB</span>) and increased biosynthesis of ADP-heptose (P<sub>tet</sub>-<span class="html-italic">gmhA</span>) suppress the sensitivity of the <span class="html-italic">rpiAB</span> mutant to antibiotics of various mechanisms of action. Representative efficiencies of colony formation of WT (MG1655) and mutant <span class="html-italic">E. coli</span> cells in the presence of antibiotics. (<b>b</b>) Cell survival was determined by counting cfu and is shown as the mean ± SD from three independent experiments. (<b>c</b>) Representative curves demonstrating the suppressive effect of <span class="html-italic">ΔdeoB</span> and P<sub>tet</sub>-<span class="html-italic">gmhA</span> mutations on sensitivity <span class="html-italic">ΔrpiAB</span> to exogenous D-ribose.</p>
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15 pages, 5537 KiB  
Article
Methyl Paraben Affects Porcine Oocyte Maturation Through Mitochondrial Dysfunction
by Huimei Huang, Chuman Huang, Yinghua Li, Xingwei Liang, Namhyung Kim and Yongnan Xu
Biomolecules 2024, 14(11), 1466; https://doi.org/10.3390/biom14111466 - 18 Nov 2024
Viewed by 464
Abstract
Parabens are widely used in various industries, which are including chemical, pharmaceutical, food, cosmetic, and plastic processing industries. Among these, methyl paraben (MP) serves as an antimicrobial preservative in processed foods, pharmaceuticals, and cosmetics, and it is particularly detected in baby care products. [...] Read more.
Parabens are widely used in various industries, which are including chemical, pharmaceutical, food, cosmetic, and plastic processing industries. Among these, methyl paraben (MP) serves as an antimicrobial preservative in processed foods, pharmaceuticals, and cosmetics, and it is particularly detected in baby care products. Studies indicate that MP functions as an endocrine-disrupting compound with estrogenic properties, negatively affecting mitochondrial bioenergetics and antioxidant activity in testicular germ cells. However, limited information exists regarding studies on the effects of MP in oocytes. The aim of this study was to investigate the specific mechanism and the toxic effects of MP during oocyte maturation cultured in vitro using a porcine oocyte model. The results indicated that MP (50 μM) inhibited oocyte expansion, significantly reducing the expression of expansion-related genes MAPK1 and ERK1, and decreased the first polar body extrusion significantly as well. ATP levels decreased, reactive oxygen species (ROS) levels remained unchanged, and glutathione (GSH) levels decreased significantly, resulting in an elevated ROS/GSH ratio. The expression of antioxidant genes SOD1 and GPX was significantly decreased. Additionally, a significant decrease in levels of mitochondrial production and biosynthesis protein PGC1α+β, whereas levels of antioxidant-related protein Nrf2 and related gene expression were significantly increased. Autophagy protein LC3B and gene expression significantly decreased, and apoptosis assay indicated a significant increase in levels of caspase3 protein and apoptosis-related genes. These results demonstrated the negative effect of MP on oocyte maturation. In conclusion, our findings indicate that MP disrupts redox balance and induces mitochondrial dysfunction during meiosis in porcine oocytes, resulting in the inhibition of meiotic progression. The present study reveals the mechanism underlying the effects of methyl para-hydroxybenzoate on oocyte maturation. Full article
(This article belongs to the Section Natural and Bio-derived Molecules)
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Figure 1

Figure 1
<p>MP exposure affects porcine oocyte maturation. (<b>A</b>) Representative morphology of oocyte maturation after control and 50 μM MP exposure. Arrows indicate PBI. Scale bar = 100 μm. The white arrow marked in the enlarged image is a prominent polar body and is also used as a standard example of polar body discharge. The red box serves as the selection area for Posting large images. (<b>B</b>) Polar body extrusion rate in the control group and groups exposed to different concentrations (5, 50, and 500 μM) of MP. “ns” shows no difference, *** <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>) Representative images of three COCs with different degrees of expansion. A dashed red box of different expansion levels, with D indicating the oocyte radius and L indicating the cumulus expansion radius. Scale bar = 100 μm. (<b>D</b>) The date of COCs with different degrees of expansion. Difference is statistically significant. “***” indicates significance and “ns” shows no difference. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001. (<b>E</b>) Relative expansion of cumulus observed after control and 50 μM MP treatment. Grade A: fully expanded; Grade B: partially expanded; Grade C: poorly expanded. * <span class="html-italic">p</span> &lt; 0.05. *** <span class="html-italic">p</span> &lt; 0.001. (<b>F</b>) Expression of cumulus expansion-related genes detected in the control and 50 μM MP groups. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001. The error bars are representing the mean ± SEM. The <span class="html-italic">p</span>-values were calculated using Student’s <span class="html-italic">t</span>-test. The experiment was repeated 3 times for each group of data.</p>
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<p>MP exposure affects redox homeostasis in porcine oocytes. (<b>A</b>) Representative images of reactive oxygen species (ROS) levels in the control and 50 μM MP-exposed oocytes. Scale bar = 100 μm. (<b>B</b>) Representative images of glutathione (GSH) levels after 50 μM MP exposure. (<b>C</b>) Relative fluorescence intensity of GSH analyzed in the control and 50 μM MP-exposed oocytes of date. *** <span class="html-italic">p</span> &lt; 0.001. (<b>D</b>) Relative fluorescence intensity of ROS/GSH analyzed in the control and 50 μM MP-exposed oocytes. *** <span class="html-italic">p</span> &lt; 0.001. (<b>E</b>) Representative images of nuclear factor erythroid 2-related factor 2 (Nrf2) levels analyzed in the control and 50 μM MP-exposed oocytes. (<b>F</b>) Relative fluorescence intensity of Nrf2 in the control and 50 μM MP-exposed oocytes. *** <span class="html-italic">p</span> &lt; 0.001. (<b>G</b>) Relative expression of antioxidant-related genes in the control and 50 μM MP-exposed oocytes. * <span class="html-italic">p</span> &lt; 0.05. The average fluorescence intensity of each oocyte was statistically analyzed. The error bars are representing the mean ± SEM. The <span class="html-italic">p</span>-values were calculated using Student’s <span class="html-italic">t</span>-test. The experiment was repeated 3 times for each group of data.</p>
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<p>MP exposure affects mitochondrial function in porcine oocytes. (<b>A</b>) Representative images of mitochondria from the control and 50 μM MP-exposed oocytes. Scale bar = 100 μm. (<b>B</b>) Relative fluorescence intensity of mitochondria after 50 μM MP exposure. *** <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>) Mitochondrial abnormal distribution rate. *** <span class="html-italic">p</span> &lt; 0.001. (<b>D</b>) Representative images of ATP content in the control and 50 μM MP-exposed oocytes of date. Scale bar = 100 μm. (<b>E</b>) Relative fluorescence intensity of ATP after 50 μM MP exposure. *** <span class="html-italic">p</span> &lt; 0.001. (<b>F</b>) Representative images of Peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PGC1α+β) content in the control and 50 μM MP-exposed oocytes. Scale bar = 100 μm. (<b>G</b>) Relative fluorescence intensity of PGC1α+β after 50 μM MP exposure. *** <span class="html-italic">p</span> &lt; 0.001. (<b>H</b>) Relative expression of mitochondrial function-related genes in the control and 50 μM MP-exposed oocytes. *** <span class="html-italic">p</span> &lt; 0.001. The average fluorescence intensity of each oocyte was statistically analyzed. The error bars are representing the mean ± SEM. The <span class="html-italic">p</span>-values were calculated using Student’s <span class="html-italic">t</span>-test. The experiment was repeated 3 times for each group of data.</p>
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<p>MP exposure affects autophagy and apoptosis levels in porcine oocytes. (<b>A</b>) Representative images of microtubule-associated protein 1 light chain 3 beta (LC3B) from the control and 50 μM MP-exposed oocytes. Scale bar = 100 μm. (<b>B</b>) Relative fluorescence intensity of microtubule-associated protein 1 light chain 3 beta (LC3B) after 50 μM MP exposure of date. *** <span class="html-italic">p</span> &lt; 0.001 (<b>C</b>) Representative images of caspase3 levels in the control and 50 μM MP-exposed oocytes. Scale bar = 100 μm. (<b>D</b>) The relative florescence intensity of cysteine-requiring aspartate protease 3 (Caspase3) in the control and 50 μM MP-exposed oocytes of date. *** <span class="html-italic">p</span> &lt; 0.001. (<b>E</b>) RT-PCR detection of autophagy-related gene expression in the control and 50 μM MP-exposed oocytes. * <span class="html-italic">p</span> &lt; 0.05. (<b>F</b>) RT-PCR detection of apoptosis-related gene expression in the control and 50 μM MP-exposed oocytes. * <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. The average fluorescence intensity of each oocyte was statistically analyzed. The error bars are representing the mean ± SEM. The <span class="html-italic">p</span>-values were calculated using Student’s <span class="html-italic">t</span>-test. The experiment was repeated 3 times for each group of data.</p>
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<p>Schematic representation of the effects of MP exposure on porcine oocytes. The arrows indicate that the changes in cell related indicators in the 50μm treatment group. It is indicated increased when the arrow is up and it is indicated decreased when the arrow is down relative to the control group.</p>
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19 pages, 4547 KiB  
Article
p75NTR Modulation Reduces Oxidative Stress and the Expression of Pro-Inflammatory Mediators in a Cell Model of Rett Syndrome
by Michela Varone, Giuseppe Scavo, Mayra Colardo, Noemi Martella, Daniele Pensabene, Emanuele Bisesto, Andrea Del Busso and Marco Segatto
Biomedicines 2024, 12(11), 2624; https://doi.org/10.3390/biomedicines12112624 - 16 Nov 2024
Viewed by 374
Abstract
Background: Rett syndrome (RTT) is an early-onset neurological disorder primarily affecting females, leading to severe cognitive and physical disabilities. Recent studies indicate that an imbalance of redox homeostasis and exacerbated inflammatory responses are key players in the clinical manifestations of the disease. Emerging [...] Read more.
Background: Rett syndrome (RTT) is an early-onset neurological disorder primarily affecting females, leading to severe cognitive and physical disabilities. Recent studies indicate that an imbalance of redox homeostasis and exacerbated inflammatory responses are key players in the clinical manifestations of the disease. Emerging evidence highlights that the p75 neurotrophin receptor (p75NTR) is implicated in the regulation of oxidative stress (OS) and inflammation. Thus, this study is aimed at investigating the effects of p75NTR modulation by LM11A-31 on fibroblasts derived from RTT donors. Methods: RTT cells were treated with 0.1 µM of LM11A-31 for 24 h, and results were obtained using qPCR, immunofluorescence, ELISA, and Western blot techniques. Results: Our findings demonstrate that LM11A-31 reduces OS markers in RTT fibroblasts. Specifically, p75NTR modulation by LM11A-31 restores protein glutathionylation and reduces the expression of the pro-oxidant enzyme NOX4. Additionally, LM11A-31 significantly decreases the expression of the pro-inflammatory mediators interleukin-6 and interleukin-8. Additionally, LM11A-31 normalizes the expression levels of transcription factors involved in the regulation of the antioxidant response and inflammation. Conclusions: Collectively, these data suggest that p75NTR modulation may represent an effective therapeutic target to improve redox balance and reduce inflammation in RTT. Full article
(This article belongs to the Special Issue Antioxidants and Oxidative Stress in Human Health and Diseases)
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Graphical abstract

Graphical abstract
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<p>Expression of NGF and p75NTR fibroblasts derived from control individuals and Rett patients. (<b>A</b>) Total RNA was extracted from healthy control (HC-1) and Rett syndrome (RTT-1) fibroblasts, and the expression levels of <span class="html-italic">ngf</span> were measured by qRT-PCR. <span class="html-italic">n</span> = 3 biological replicates. Data represent means ± SD. (<b>B</b>) Immunofluorescence and respective quantitative analysis of NGF in HC and RTT. Cells were fixed in 4% PFA and stained with antibodies against NGF (red). DAPI (blue) was employed for nuclear counterstaining. <span class="html-italic">n</span> = 6 biological replicates. (<b>C</b>) qRT-PCR analysis of <span class="html-italic">ngfr</span> (<span class="html-italic">p75NTR</span>) in HC-1 and RTT-1 fibroblasts. <span class="html-italic">n</span> = 3 biological replicates. (<b>D</b>) Immunofluorescence and respective quantitative analysis of p75NTR immunoreactivity in HC-1 and RTT-1 cells. Cells were fixed in 4% PFA and stained with anti-p75NTR (red). DAPI (blue) was used to counterstain nuclei. <span class="html-italic">n</span> = 5 biological replicates. Data are expressed as mean ± SD. Statistical analysis was performed by using the Student’s unpaired <span class="html-italic">t</span>-test. Statistical significance is indicated as follows: * <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 vs. DMSO. Images were acquired using the Leica TCS SP8 confocal microscope and Leica Application Suite X (LAS X) software at 40× magnification. Scale bar: 50 µm.</p>
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<p>Effects of LM11A-31 on oxidative stress markers in RTT fibroblasts. Immunofluorescence and quantitative analysis of the OS biomarkers (<b>A</b>) 8-OHdG and (<b>B</b>) 4-HNE in healthy control fibroblast (HC-1), Rett syndrome fibroblasts (RTT-1), and RTT fibroblasts treated with LM11A-31 (RTT-1+LM) at the dose of 0.1 µM for 24 h. Cells were fixed in 4% PFA and stained with antibodies against 8-OHdG (red) or 4-HNE (red). Nuclei were counterstained with DAPI (blue). <span class="html-italic">n</span> = 14 biological replicates. Data are expressed as mean ± SD. Statistical analysis was performed using one-way ANOVA, followed by Tukey’s post hoc test. Statistical significance is indicated as follows: ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. “a” indicates statistical significance vs. HC-1; “b” indicates statistical significance vs. RTT-1. Images were acquired using the Leica TCS SP8 confocal microscope and Leica Application Suite X (LAS X) software at 40× magnification. Scale bar: 50 µm.</p>
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<p>Effects of p75NTR modulation on the antioxidant response in RTT fibroblasts. Representative Western blot and densitometric analysis of (<b>A</b>) SOD1, (<b>B</b>) SOD2, (<b>C</b>) Catalase, (<b>D</b>) TrxR1, and (<b>E</b>) Gpx1 in healthy control fibroblasts (HC-1), Rett syndrome fibroblasts (RTT-1) and RTT fibroblasts treated with 0.1 μM of LM11A-31(RTT-1+LM) for 24 h. <span class="html-italic">n</span> = 3–5 biological replicates. GAPDH was used as a loading control. (<b>F</b>) Immunofluorescence and quantification of GSH immunoreactivity in HC-1, RTT-1, and RTT-1+LM experimental groups. Cells were fixed in 4% PFA and stained with antibodies against GSH (red). Nuclear staining was performed with DAPI (blue). <span class="html-italic">n</span> = 12 biological replicates. Data are expressed as mean ± SD. Statistical analysis was performed using one-way ANOVA, followed by Tukey’s post hoc test. Statistical significance is indicated as follows: ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. “a” indicates statistical significance vs. HC-1; “b” indicates statistical significance vs. RTT-1. Images were acquired using the Leica TCS SP8 confocal microscope and Leica Application Suite X (LAS X) software at 40× magnification. Scale bar: 50 µm.</p>
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<p>Impact of LM11A-31 on the expression of NADPH oxidase 4 subunits. Immunofluorescence and quantitative analysis of (<b>A</b>) NOX4 and (<b>B</b>) p22<sup>phox</sup> fluorescence intensity in control fibroblast (HC-1), Rett syndrome fibroblasts (RTT-1), and RTT fibroblasts treated with LM11A-31 (0.1 μM for 24 h) (RTT-1+LM). Cells were fixed in 4% PFA and stained with antibodies against NOX4 (red) and p22<sup>phox</sup>. DAPI was employed for nuclear counterstaining. <span class="html-italic">n</span> = 5–6 biological replicates. Images were acquired using the Leica TCS SP8 confocal microscope and Leica Application Suite X (LAS X) software at 40× magnification. Scale bar: 50 µm. Data are expressed as mean ± SD. Statistical analysis was performed using a one-way ANOVA, followed by Tukey’s post hoc test. Statistical significance is indicated as follows: *** <span class="html-italic">p</span> &lt; 0.001. “a” indicates statistical significance vs. HC-1; “b” indicates statistical significance vs. RTT-1.</p>
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<p>p75NTR modulation reduces IL-6 and IL-8 expression in RTT fibroblasts. Representative immunofluorescence and respective quantitative analysis of (<b>A</b>) IL-6 immunoreactivity in control fibroblasts (HC-1), Rett syndrome fibroblasts (RTT-1), and RTT fibroblasts treated with LM11A-31(RTT-1+LM) at the dose of 0.1 μM for 24 h. Cells were fixed in 4% PFA and stained with antibodies against IL-6 (red). DAPI was used to counterstain nuclei. <span class="html-italic">n</span> = 6 biological replicates. Images were acquired using the Leica TCS SP8 confocal microscope and Leica Application Suite X (LAS X) software at 40× magnification. Scale bar: 50 µm. (<b>B</b>) ELISA on IL-6 in culture medium from HC-1, RTT-1, and RTT-1+LM groups treated as abovementioned. <span class="html-italic">n</span> = 4 biological replicates. (<b>C</b>) IL-8 immunoreactivity (red) and respective quantitative analysis performed on HC-1, RTT-1, and RTT-1+LM fibroblasts treated as in (<b>A</b>). DAPI was used for nuclear staining. <span class="html-italic">n</span> = 6 biological replicates. Scale bar: 50 µm. (<b>D</b>) ELISA on secreted IL-8 in conditioned medium from HC-1, RTT-1, and RTT-1+LM cells treated as abovementioned. <span class="html-italic">n</span> = 4 biological replicates. Data are expressed as mean ± SD. Statistical analysis was performed using one-way ANOVA, followed by Tukey’s post hoc test. Statistical significance is indicated as follows: * <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. “a” indicates statistical significance vs. HC-1; “b” indicates statistical significance vs. RTT-1.</p>
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<p>LM11A-31 modulates PPAR expression in RTT fibroblasts. Immunofluorescence and signal intensity analysis of (<b>A</b>) PPARα, (<b>B</b>) PPARβ/δ, and (<b>C</b>) PPARγ in control fibroblast (HC-1), Rett syndrome fibroblasts (RTT-1) and RTT fibroblasts treated with 0.1 μM of LM11A-31 (RTT-1+LM) for 24 h. Cells were fixed in 4% PFA and stained with antibodies against PPARα (green), PPARβ/δ (green) and PPARγ (red). Nuclei were counterstained with DAPI (blue). <span class="html-italic">n</span> = 6–8 biological replicates. Data are expressed as mean ± SD. Statistical analysis was performed using a one-way ANOVA, followed by Tukey’s post hoc test. Statistical significance is indicated as follows: * <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. “a” indicates statistical significance vs. HC-1; “b” indicates statistical significance vs. RTT-1. Images were acquired using the Leica TCS SP8 confocal microscope and Leica Application Suite X (LAS X) software at 40× magnification. Scale bar: 50 µm.</p>
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<p>LM11A-31 influences the expression of transcription factors involved in redox homeostasis. Immunofluorescence and quantification of signal intensity of (<b>A</b>) PGC1α, (<b>B</b>) Sirt1, and (<b>C</b>) Nrf2 in control fibroblast (HC-1), Rett syndrome fibroblasts (RTT-1), and RTT fibroblasts treated with LM11A-31 (RTT-1+LM) at the dose of 0.1 μM for 24 h. Cells were fixed in 4% PFA and stained with antibodies against PGC1α (green), Sirt1 (green) and Nrf2 (red). DAPI was employed for nuclear counterstaining. <span class="html-italic">n</span> = 8–14 biological replicates. Data are expressed as mean ± SD. Statistical analysis was performed using a one-way ANOVA, followed by Tukey’s post hoc test. Statistical significance is indicated as follows: * <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. “a” indicates statistical significance vs. HC-1; “b” indicates statistical significance vs. RTT-1. Images were acquired using the Leica TCS SP8 confocal microscope and Leica Application Suite X (LAS X) software at 40× magnification. Scale bar: 50 µm.</p>
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32 pages, 2311 KiB  
Article
Muscle Proteome Analysis of Facioscapulohumeral Dystrophy Patients Reveals a Metabolic Rewiring Promoting Oxidative/Reductive Stress Contributing to the Loss of Muscle Function
by Manuela Moriggi, Lucia Ruggiero, Enrica Torretta, Dario Zoppi, Beatrice Arosio, Evelyn Ferri, Alessandra Castegna, Chiara Fiorillo, Cecilia Gelfi and Daniele Capitanio
Antioxidants 2024, 13(11), 1406; https://doi.org/10.3390/antiox13111406 - 16 Nov 2024
Viewed by 383
Abstract
Facioscapulohumeral muscular dystrophy (FSHD) is caused by the epigenetic de-repression of the double homeobox 4 (DUX4) gene, leading to asymmetric muscle weakness and atrophy that begins in the facial and scapular muscles and progresses to the lower limbs. This incurable condition can severely [...] Read more.
Facioscapulohumeral muscular dystrophy (FSHD) is caused by the epigenetic de-repression of the double homeobox 4 (DUX4) gene, leading to asymmetric muscle weakness and atrophy that begins in the facial and scapular muscles and progresses to the lower limbs. This incurable condition can severely impair muscle function, ultimately resulting in a loss of ambulation. A thorough analysis of molecular factors associated with the varying degrees of muscle impairment in FSHD is still lacking. This study investigates the molecular mechanisms and biomarkers in the biceps brachii of FSHD patients, classified according to the FSHD clinical score, the A-B-C-D classification scheme, and global proteomic variation. Our findings reveal distinct metabolic signatures and compensatory responses in patients. In severe cases, we observe pronounced metabolic dysfunction, marked by dysregulated glycolysis, activation of the reductive pentose phosphate pathway (PPP), a shift toward a reductive TCA cycle, suppression of oxidative phosphorylation, and an overproduction of antioxidants that is not matched by an increase in the redox cofactors needed for their function. This imbalance culminates in reductive stress, exacerbating muscle wasting and inflammation. In contrast, mild cases show metabolic adaptations that mitigate stress by activating polyols and the oxidative PPP, preserving partial energy flow through the oxidative TCA cycle, which supports mitochondrial function and energy balance. Furthermore, activation of the hexosamine biosynthetic pathway promotes autophagy, protecting muscle cells from apoptosis. In conclusion, our proteomic data indicate that specific metabolic alterations characterize both mild and severe FSHD patients. Molecules identified in mild cases may represent potential diagnostic and therapeutic targets for FSHD. Full article
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<p>Principal component analysis (PCA) score plots showing the spatial distribution of (<b>A</b>) control (blue circles, n = 6), mild (red circles, n = 9), and severe FSHD patients (green circles, n = 5) and (<b>B</b>) control and mild FSHD patients only, according to the 2D-DIGE proteomic profile of the <span class="html-italic">biceps brachii</span> muscle. The amount of variance explained by each component is indicated on the PC1 and PC2 axes. Each sample was analyzed in duplicate.</p>
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<p>(<b>A</b>) Representative bar graph (means ± SD) and immunoblot images of PAX7 and myogenin from healthy controls (CTR, black bars) and mild and severe FSHD patients (gray bars) (n = 2; mean ± SD; Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> &lt; 0.05). Data were normalized against the total amount of loaded proteins stained with Sypro Ruby. O.D. = optical density. * = statistically significant. Full-length images are available in <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Figure S5</a>. (<b>B</b>) IPA analysis showing the over-represented canonical pathways in mild and severe FSHD patients compared to controls ordered by <span class="html-italic">p</span>-value and z-score. The significance threshold, indicated by an orange vertical line, is set at <span class="html-italic">p</span> = 0.05. The color orange indicates predicted pathway activation, while the color blue indicates predicted pathway inhibition. The z-score statistic is used to determine this, with a threshold of z-scores ≥ 2 and ≤ −2. In gray are the canonical pathways with no predicted z-score, but a significant <span class="html-italic">p</span>-value. (<b>C</b>) Extracellular matrix muscle proteins. Histogram of common (<b>left</b>) and characteristic (<b>right</b>) dysregulated extracellular matrix proteins in FSHD mild vs. CTR (black bar) and FSHD severe vs. CTR (gray bar) from the proteomic datasets. (FSHD mild vs. CTR and FSHD severe vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). Proteins are indicated by gene name; the full name is given in the <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Files</a> downloadable at <a href="https://doi.org/10.13130/RD_UNIMI/KTS29V" target="_blank">https://doi.org/10.13130/RD_UNIMI/KTS29V</a>. (<b>D</b>) Structural and contractile proteins. Histogram of common (left) and characteristic (right) dysregulated structural and contractile proteins in FSHD mild vs. CTR (black bar) and FSHD severe vs. CTR (gray bar) from the proteomic datasets. (FSHD mild vs. CTR and FSHD severe vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). Proteins are indicated by gene name; the full name is given in the <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Files</a> downloadable from <a href="https://doi.org/10.13130/RD_UNIMI/KTS29V" target="_blank">https://doi.org/10.13130/RD_UNIMI/KTS29V</a>.</p>
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<p>(<b>A</b>) Schematic representation of metabolic enzymes dysregulated in FSHD mild vs. CTR. (FSHD mild vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) Schematic representation of metabolic enzymes dysregulated in FSHD severe vs. CTR. (FSHD severe vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). * = results obtained by immunoblotting. Green and red colors indicate statistically significant decreases or increases in protein abundance from proteomics datasets, expressed as a % fold change. Proteins are indicated by gene name; the full name is given in the <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Files</a> downloadable from <a href="https://doi.org/10.13130/RD_UNIMI/KTS29V" target="_blank">https://doi.org/10.13130/RD_UNIMI/KTS29V</a>.</p>
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<p>(<b>A</b>) Schematic representation of metabolic enzymes dysregulated in FSHD mild vs. CTR. (FSHD mild vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) Schematic representation of metabolic enzymes dysregulated in FSHD severe vs. CTR. (FSHD severe vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). * = results obtained by immunoblotting. Green and red colors indicate statistically significant decreases or increases in protein abundance from proteomics datasets, expressed as a % of fold change. Proteins are indicated by gene name; the full name is given in the <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Files</a> downloadable from <a href="https://doi.org/10.13130/RD_UNIMI/KTS29V" target="_blank">https://doi.org/10.13130/RD_UNIMI/KTS29V</a>.</p>
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<p>(<b>A</b>) Schematic representation of lipid enzyme dysregulation in FSHD mild vs. CTR. (FSHD mild vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) Schematic representation of lipid enzymes’ dysregulation in FSHD severe vs. CTR. (FSHD severe vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). Green and red colors indicate statistically significant decreases or increases in protein abundance from proteomics datasets, expressed as a % fold change. (<b>C</b>) Histograms of dysregulated proteins involved in lipid transport and storage in FSHD mild vs. CTR (black bar) and FSHD severe vs. CTR (gray bar) from the proteomic datasets (FSHD mild vs. CTR and FSHD severe vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). Proteins are indicated by gene name; the full name is given in the <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Files</a> downloadable from <a href="https://doi.org/10.13130/RD_UNIMI/KTS29V" target="_blank">https://doi.org/10.13130/RD_UNIMI/KTS29V</a>.</p>
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<p>(<b>A</b>) Bar chart showing nicotinamide adenine dinucleotide phosphate cofactor levels in controls (CTR, black bar) and in mild (light gray bar) and severe (dark gray bar) FSHD patients. * = significant changes (ANOVA + Tukey, n = 2, <span class="html-italic">p</span> &lt; 0.05); (<b>B</b>) Pie chart indicating the % of oxidized (NADP<sup>+</sup>, gray) and reduced (NADPH, black) nicotinamide adenine dinucleotide phosphate cofactor in CTR, FSHD mild, and FSHD severe cases. a = significant variation compared to CTR, b = significant variation compared to FSHD mild (ANOVA + Tukey, n = 2, <span class="html-italic">p</span> &lt; 0.01). (<b>C</b>) Bar chart showing nicotinamide adenine dinucleotide cofactor levels in CTR (black bar) and in mild (light gray bar) and severe (dark gray bar) FSHD patients. * = significant changes (ANOVA + Tukey, n = 2, <span class="html-italic">p</span> &lt; 0.05); (<b>D</b>) Pie chart indicating the percentage of oxidized (NAD<sup>+</sup>, gray) and reduced (NADH, black) nicotinamide adenine dinucleotide cofactor in each experimental group. a = significant variation compared to CTR (ANOVA + Tukey, n = 2, <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Stress response proteins and the hexosamine biosynthetic pathway. (<b>A</b>) Histogram of common (left) and characteristic (right) dysregulated proteins’ levels of stress response in FSHD mild vs. CTR (black bar) and FSHD severe vs. CTR (gray bar) from the proteomic datasets. (FSHD mild vs. CTR and FSHD severe vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). Proteins are indicated by gene name, the full name is given in the <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Files</a> downloadable from <a href="https://doi.org/10.13130/RD_UNIMI/KTS29V" target="_blank">https://doi.org/10.13130/RD_UNIMI/KTS29V</a>. (<b>B</b>–<b>E</b>) Representative bar graph (means ± SD) and immunoblot images of glutamine synthetase, hexosamine pathway (GFAT1, OGT, OGA, STT3B), O-GlcNac and hyaluronan synthase 1 (HAS1) (n = 2; mean ± SD; Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> &lt; 0.05) in healthy controls (CTR, black bars) and FSHD mild and severe patients (light and dark gray bars). Data were normalized against the total amount of loaded proteins stained with Sypro Ruby. O.D. = optical density. * = statistically significant. Full-length images are available in <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Figure S5</a>.</p>
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<p>Inflammation and immune response proteins. (<b>A</b>) Histograms of common dysregulated proteins levels of inflammation and immune response in FSHD mild vs. CTR (black bar) and FSHD severe vs. CTR (gray bar) from the proteomic datasets. (FSHD mild vs. CTR and FSHD severe vs. CTR, ANOVA test and FDR, <span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) Histogram of dysregulated proteins levels of inflammation and the immune response in FSHD mild vs. CTR and in FSHD severe vs. CTR (gray bar) from the proteomic datasets. Proteins are indicated by gene name; the full name is given in the <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Tables</a> downloadable from <a href="https://doi.org/10.13130/RD_UNIMI/KTS29V" target="_blank">https://doi.org/10.13130/RD_UNIMI/KTS29V</a>.</p>
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<p>(<b>A</b>) Representative bar graph (means ± SD) and immunoblot images of p53, CASPASE-3, LC3BII/LC3BI, HSC70, and lysosome-associated membrane protein 2 (LAMP2) in healthy controls (CTR, black bars) and mild and severe FSHD patients (gray bars) (n = 2; mean ± SD; Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> &lt; 0.05). Data were normalized against the total amount of loaded proteins stained with Sypro Ruby. O.D. = optical density. Full-length images are available in <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Figure S5</a>. (<b>B</b>–<b>E</b>) Validation of proteomic data by quantitative PCR analysis performed in the OpenArray<sup>®</sup> QuantStudio 12K Flex Real-Time PCR System, using the commercial probes shown in <a href="#app1-antioxidants-13-01406" class="html-app">Supplementary Table S2</a>. The GAPDH, ACTB, and 18S genes were included in the OpenArray<sup>®</sup> chip and used as housekeeping endogenous control genes. Each analysis was conducted in duplicate. * = statistically significant.</p>
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12 pages, 2159 KiB  
Review
Molecular Roles of NADPH Oxidase-Mediated Oxidative Stress in Alzheimer’s Disease: Isoform-Specific Contributions
by Junhyung Kim and Jong-Seok Moon
Int. J. Mol. Sci. 2024, 25(22), 12299; https://doi.org/10.3390/ijms252212299 - 15 Nov 2024
Viewed by 465
Abstract
Oxidative stress is linked to the pathogenesis of Alzheimer’s disease (AD), a neurodegenerative disorder marked by memory impairment and cognitive decline. AD is characterized by the accumulation of amyloid-beta (Aβ) plaques and the formation of neurofibrillary tangles (NFTs) of hyperphosphorylated tau. AD is [...] Read more.
Oxidative stress is linked to the pathogenesis of Alzheimer’s disease (AD), a neurodegenerative disorder marked by memory impairment and cognitive decline. AD is characterized by the accumulation of amyloid-beta (Aβ) plaques and the formation of neurofibrillary tangles (NFTs) of hyperphosphorylated tau. AD is associated with an imbalance in redox states and excessive reactive oxygen species (ROS). Recent studies report that NADPH oxidase (NOX) enzymes are significant contributors to ROS generation in neurodegenerative diseases, including AD. NOX-derived ROS aggravates oxidative stress and neuroinflammation during AD. In this review, we provide the potential role of all NOX isoforms in AD pathogenesis and their respective structural involvement in AD progression, highlighting NOX enzymes as a strategic therapeutic target. A comprehensive understanding of NOX isoforms and their inhibitors could provide valuable insights into AD pathology and aid in the development of targeted treatments for AD. Full article
(This article belongs to the Special Issue Molecular Insight into Alzheimer’s Disease)
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<p>Summary for the structures of NOX isoforms. NOX1 NADPH oxidase 1, NOX2 NADPH oxidase 2, NOX4 NADPH oxidase 4, NOX5 NADPH oxidase 5, DUOX dual oxidases.</p>
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<p>The summary for the role of NOX isoforms in Alzheimer’s disease. NOX1 NADPH oxidase 1, NOX2 NADPH oxidase 2, NOX4 NADPH oxidase 4, NOX5 NADPH oxidase 5, DUOX dual oxidases. Arrows mean upregulation.</p>
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20 pages, 843 KiB  
Review
Evidence of Oxidative Stress as a Mechanism of Pharmaceutical-Induced Toxicity in Amphibians
by Jesús Daniel Cardoso-Vera, Hariz Islas-Flores, Itzayana Pérez-Alvarez and Nidya Díaz-Camal
Antioxidants 2024, 13(11), 1399; https://doi.org/10.3390/antiox13111399 - 15 Nov 2024
Viewed by 615
Abstract
Amphibians, which are essential components of ecosystems, are susceptible to pharmaceutical contamination, a phenomenon of increasing concern owing to the widespread consumption and detection of pharmaceutical compounds in environmental matrices. This review investigates oxidative stress (OS) as the primary mechanism of drug toxicity [...] Read more.
Amphibians, which are essential components of ecosystems, are susceptible to pharmaceutical contamination, a phenomenon of increasing concern owing to the widespread consumption and detection of pharmaceutical compounds in environmental matrices. This review investigates oxidative stress (OS) as the primary mechanism of drug toxicity in these organisms. The evidence gathered reveals that various pharmaceuticals, from antibiotics to anesthetics, induce OS by altering biomarkers of oxidative damage and antioxidant defense. These findings underscore the deleterious effects of pharmaceuticals on amphibian health and development and emphasize the necessity of incorporating OS biomarkers into ecotoxicological risk assessments. Although further studies on diverse amphibian species, drug mixtures, and field studies are required, OS biomarkers offer valuable tools for identifying sublethal risks. Furthermore, the development of more refined OS biomarkers will facilitate the early detection of adverse effects, which are crucial for protecting amphibians and their ecosystems. Ultimately, this review calls for continued research and mitigation strategies to safeguard biodiversity from pharmaceutical contamination. Full article
(This article belongs to the Special Issue The Role of Oxidative Stress in Environmental Toxicity)
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<p>Mechanism and main consequences of oxidative stress at the cellular level.</p>
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18 pages, 5164 KiB  
Article
Redox Imbalance and Antioxidant Defenses Dysfunction: Key Contributors to Early Aging in Childhood Cancer Survivors
by Vanessa Cossu, Nadia Bertola, Chiara Fresia, Federica Sabatini and Silvia Ravera
Antioxidants 2024, 13(11), 1397; https://doi.org/10.3390/antiox13111397 - 15 Nov 2024
Viewed by 322
Abstract
Survival rates for childhood cancer survivors (CCS) have improved, although they display a risk for early frailty due to the long-term effects of chemo/radiotherapy, including early aging. This study investigates antioxidant defenses and oxidative damage in mononuclear cells (MNCs) from CCS, comparing them [...] Read more.
Survival rates for childhood cancer survivors (CCS) have improved, although they display a risk for early frailty due to the long-term effects of chemo/radiotherapy, including early aging. This study investigates antioxidant defenses and oxidative damage in mononuclear cells (MNCs) from CCS, comparing them with those from age-matched and elderly healthy individuals. Results show impaired antioxidant responses and increased oxidative stress in CCS MNCs, which exhibited uncoupled oxidative phosphorylation, leading to higher production of reactive oxygen species, similar to metabolic issues seen in elderly individuals. Key antioxidant enzymes, namely glucose-6-phosphate dehydrogenase, hexose-6-phosphate dehydrogenase, glutathione reductase, glutathione peroxidase, catalase, and superoxide dismutase, showed reduced activity, likely due to lower expression of nuclear factor erythroid 2–related factor 2 (Nrf2). This imbalance caused significant damage to lipids, proteins, and DNA, potentially contributing to cellular dysfunction and a higher risk of cancer recurrence. These oxidative and metabolic dysfunctions persist over time, regardless of cancer type or treatment. However, treatment with N-acetylcysteine improved Nrf2 expression, boosted antioxidant defenses, reduced oxidative damage, and restored oxidative phosphorylation efficiency, suggesting that targeting the redox imbalance could enhance long-term CCS health. Full article
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<p>OxPhos efficiency, ROS production, and oxidative damage accumulation in MNCs isolated from CCS, age-matched healthy subjects, and elderly healthy controls. All data were obtained on MNCs isolated from age-matched healthy controls (&lt;10 y.o., <span class="html-italic">n</span> = 18; 11–20 y.o., <span class="html-italic">n</span> = 32; 21–40 y.o, <span class="html-italic">n</span> = 20), CCS of solid tumor (sCCS; &lt;10 y.o., <span class="html-italic">n</span> = 27; 11–20 y.o., <span class="html-italic">n</span> = 29; 21–40 y.o., <span class="html-italic">n</span> = 18), CCS of hematological tumors (hCCS; &lt;10 y.o., <span class="html-italic">n</span> = 25; 11–20 y.o., <span class="html-italic">n</span> = 28; 21–40 y.o., <span class="html-italic">n</span> = 22), healthy donors aged between 41–60 y.o., <span class="html-italic">n</span> = 19; healthy donors aged between 61–80 y.o., <span class="html-italic">n</span> = 25; healthy donors aged over 80 y.o., <span class="html-italic">n</span> = 22. (<b>A</b>) P/O value, an OxPhos efficiency marker, evaluated in the presence of pyruvate plus malate as respiring substrates; (<b>B</b>) Reactive oxygen species (ROS) production; (<b>C</b>) Malondialdehyde (MDA) intracellular concentration, as a lipid peroxidation marker; (<b>D</b>) 4-hydroxynonenal (4-HNE) intracellular concentration, as a lipid peroxidation marker; (<b>E</b>) 8-Hydroxy-2′-deoxyguanosine (8-OHdG) intracellular concentration, as a DNA oxidative damage marker; (<b>F</b>) Nitrotyrosine intracellular level, as a protein oxidative damage marker. **** indicates a <span class="html-italic">p</span> &lt; 0.0001. ##, ###, and #### indicate a <span class="html-italic">p</span> &lt; 0.01, 0.001, or 0.0001, respectively, between sCCS or hCCS and healthy donors aged 41–60 y.o. No significant differences were observed between CCS samples and healthy subjects aged between 61–80 y.o. and over 80 y.o.</p>
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<p>Intracellular level of oxidized and reduced forms of NADP and glutathione in MNCs isolated from CCS, age-matched healthy subjects, and elderly healthy controls. All data were obtained on MNCs isolated from age-matched healthy controls (&lt;10 y.o., <span class="html-italic">n</span> = 18; 11–20 y.o., <span class="html-italic">n</span> = 32; 21–40 y.o., <span class="html-italic">n</span> = 20), CCS of solid tumor (sCCS; &lt;10 y.o., <span class="html-italic">n</span> = 27; 11–20 y.o., <span class="html-italic">n</span> = 29; 21–40 y.o., <span class="html-italic">n</span> = 18), CCS of hematological tumors (hCCS; &lt;10 y.o., <span class="html-italic">n</span> = 25; 11–20 y.o., <span class="html-italic">n</span> = 28; 21–40 y.o., <span class="html-italic">n</span> = 22), healthy donors aged between 41–60 y.o., <span class="html-italic">n</span> = 19; healthy donors aged between 61–80 y.o., <span class="html-italic">n</span> = 25; healthy donors aged over 80 y.o., <span class="html-italic">n</span> = 22. (<b>A</b>) Total intracellular concentration of reduced and oxidized forms of NADP; (<b>B</b>) Ratio between NADPH and NADP; (<b>C</b>) Total intracellular concentration of reduced and oxidized forms of glutathione (GSH + GSSG); (<b>D</b>) Ratio between GSH and GSSG. **** indicates a <span class="html-italic">p</span> &lt; 0.0001. #, ##, ###, and #### indicate a <span class="html-italic">p</span> &lt; 0.05, 0.01, 0.001, or 0.0001, respectively, between sCCS or hCCS and healthy donors aged 61–80 y.o. No significant differences were observed between CCS samples and healthy subjects over 80 y.o.</p>
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<p>Activity and protein expression of G6PD, H6PD, GR, and GPX in MNCs isolated from CCS, age-matched healthy subjects, and elderly healthy controls. Data reported in Panels (<b>A</b>–<b>D</b>) were obtained on MNCs isolated from age-matched healthy controls (&lt;10 y.o., <span class="html-italic">n</span> = 18; 11–20 y.o., <span class="html-italic">n</span> = 32; 21–40 y.o., <span class="html-italic">n</span> = 20), CCS of solid tumor (sCCS; &lt;10 y.o., <span class="html-italic">n</span> = 27; 11–20 y.o., <span class="html-italic">n</span> = 29; 21–40 y.o., <span class="html-italic">n</span> = 18), CCS of hematological tumors (hCCS; &lt;10 y.o., <span class="html-italic">n</span> = 25; 11–20 y.o., <span class="html-italic">n</span> = 28; 21–40 y.o., <span class="html-italic">n</span> = 22), healthy donors aged between 41–60 y.o., <span class="html-italic">n</span> = 19; healthy donors aged between 61–80 y.o., <span class="html-italic">n</span> = 25; healthy donors aged over 80 y.o., <span class="html-italic">n</span> = 22. Data reported in Panels (<b>E</b>–<b>I</b>) are representative of three independent experiments, each on <span class="html-italic">n</span> = 3 age-matched healthy donors (&lt;40 y.o.); <span class="html-italic">n</span> = 3 (CCS &lt; 40 y.o.), and <span class="html-italic">n</span> = 3 elderly healthy subjects (&gt;60 y.o.) (<b>A</b>) G6PD activity; (<b>B</b>) H6PD activity; (<b>C</b>) GR activity; (<b>D</b>) GPx activity; (<b>E</b>) Representative Western blot signals of G6PD, H6PD, GR, and GPX. Actin was evaluated as a housekeeping signal. (<b>F</b>) Densitometric analysis of G6PD signal normalized against actin signal; (<b>G</b>) Densitometric analysis of H6PD signal normalized against actin signal; (<b>H</b>) Densitometric analysis of GR signal normalized against actin signal; (<b>I</b>) Densitometric analysis of GPx signal normalized against actin signal. ROD = Relative Optical Density. *, **** indicate a <span class="html-italic">p</span> &lt; 0.05, 0.0001. In panels (<b>A</b>–<b>D</b>), #, ##, and ### indicate a <span class="html-italic">p</span> &lt; 0.05, 0.01, or 0.001, respectively, between sCCS or hCCS and healthy donors over 80 y.o.</p>
Full article ">Figure 3 Cont.
<p>Activity and protein expression of G6PD, H6PD, GR, and GPX in MNCs isolated from CCS, age-matched healthy subjects, and elderly healthy controls. Data reported in Panels (<b>A</b>–<b>D</b>) were obtained on MNCs isolated from age-matched healthy controls (&lt;10 y.o., <span class="html-italic">n</span> = 18; 11–20 y.o., <span class="html-italic">n</span> = 32; 21–40 y.o., <span class="html-italic">n</span> = 20), CCS of solid tumor (sCCS; &lt;10 y.o., <span class="html-italic">n</span> = 27; 11–20 y.o., <span class="html-italic">n</span> = 29; 21–40 y.o., <span class="html-italic">n</span> = 18), CCS of hematological tumors (hCCS; &lt;10 y.o., <span class="html-italic">n</span> = 25; 11–20 y.o., <span class="html-italic">n</span> = 28; 21–40 y.o., <span class="html-italic">n</span> = 22), healthy donors aged between 41–60 y.o., <span class="html-italic">n</span> = 19; healthy donors aged between 61–80 y.o., <span class="html-italic">n</span> = 25; healthy donors aged over 80 y.o., <span class="html-italic">n</span> = 22. Data reported in Panels (<b>E</b>–<b>I</b>) are representative of three independent experiments, each on <span class="html-italic">n</span> = 3 age-matched healthy donors (&lt;40 y.o.); <span class="html-italic">n</span> = 3 (CCS &lt; 40 y.o.), and <span class="html-italic">n</span> = 3 elderly healthy subjects (&gt;60 y.o.) (<b>A</b>) G6PD activity; (<b>B</b>) H6PD activity; (<b>C</b>) GR activity; (<b>D</b>) GPx activity; (<b>E</b>) Representative Western blot signals of G6PD, H6PD, GR, and GPX. Actin was evaluated as a housekeeping signal. (<b>F</b>) Densitometric analysis of G6PD signal normalized against actin signal; (<b>G</b>) Densitometric analysis of H6PD signal normalized against actin signal; (<b>H</b>) Densitometric analysis of GR signal normalized against actin signal; (<b>I</b>) Densitometric analysis of GPx signal normalized against actin signal. ROD = Relative Optical Density. *, **** indicate a <span class="html-italic">p</span> &lt; 0.05, 0.0001. In panels (<b>A</b>–<b>D</b>), #, ##, and ### indicate a <span class="html-italic">p</span> &lt; 0.05, 0.01, or 0.001, respectively, between sCCS or hCCS and healthy donors over 80 y.o.</p>
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<p>Activity and protein expression of SOD and CAT in MNCs isolated from CCS, age-matched healthy subjects, and elderly healthy controls. Data reported in Panels (<b>A</b>,<b>B</b>) were obtained on MNCs isolated from age-matched healthy controls (&lt;10 y.o., <span class="html-italic">n</span> = 18; 11–20 y.o., <span class="html-italic">n</span> = 32; 21–40 y.o., <span class="html-italic">n</span> = 20), CCS of solid tumor (sCCS; &lt;10 y.o., <span class="html-italic">n</span> = 27; 11–20 y.o., <span class="html-italic">n</span> = 29; 21–40 y.o., <span class="html-italic">n</span> = 18), CCS of hematological tumors (hCCS; &lt;10 y.o., <span class="html-italic">n</span> = 25; 11–20 y.o., <span class="html-italic">n</span> = 28; 21–40 y.o., <span class="html-italic">n</span> = 22), healthy donors aged between 41–60 y.o., <span class="html-italic">n</span> = 19; healthy donors aged between 61–80 y.o., <span class="html-italic">n</span> = 25; healthy donors aged over 80 y.o., <span class="html-italic">n</span> = 22. Data reported in Panels (<b>C</b>–<b>F</b>) are representative of three independent experiments, each on <span class="html-italic">n</span> = 3 age-matched healthy donors (&lt;40 y.o); <span class="html-italic">n</span> = 3 (CCS &lt; 40 y.o.), and <span class="html-italic">n</span> = 3 elderly healthy subjects (&gt;60 y.o.). (<b>A</b>) SOD activity; (<b>B</b>) CAT activity; (<b>C</b>) Representative Western blot signals of SOD1 (cytosolic form), SOD2 (mitochondrial form), and CAT. Actin was evaluated as a housekeeping signal. (<b>D</b>) Densitometric analysis of SOD1 signal normalized against actin signal; (<b>E</b>) Densitometric analysis of SOD2 signal normalized against actin signal; (<b>F</b>) Densitometric analysis of CAT signal normalized against actin signal. ROD = Relative Optical Density. *, **** indicate a <span class="html-italic">p</span> &lt; 0.05, 0.0001. In panels (<b>A</b>,<b>B</b>), ##, and ### indicate a <span class="html-italic">p</span> &lt; 0.01, or 0.001, respectively, between sCCS or hCCS and healthy donors over 80 y.o.</p>
Full article ">Figure 4 Cont.
<p>Activity and protein expression of SOD and CAT in MNCs isolated from CCS, age-matched healthy subjects, and elderly healthy controls. Data reported in Panels (<b>A</b>,<b>B</b>) were obtained on MNCs isolated from age-matched healthy controls (&lt;10 y.o., <span class="html-italic">n</span> = 18; 11–20 y.o., <span class="html-italic">n</span> = 32; 21–40 y.o., <span class="html-italic">n</span> = 20), CCS of solid tumor (sCCS; &lt;10 y.o., <span class="html-italic">n</span> = 27; 11–20 y.o., <span class="html-italic">n</span> = 29; 21–40 y.o., <span class="html-italic">n</span> = 18), CCS of hematological tumors (hCCS; &lt;10 y.o., <span class="html-italic">n</span> = 25; 11–20 y.o., <span class="html-italic">n</span> = 28; 21–40 y.o., <span class="html-italic">n</span> = 22), healthy donors aged between 41–60 y.o., <span class="html-italic">n</span> = 19; healthy donors aged between 61–80 y.o., <span class="html-italic">n</span> = 25; healthy donors aged over 80 y.o., <span class="html-italic">n</span> = 22. Data reported in Panels (<b>C</b>–<b>F</b>) are representative of three independent experiments, each on <span class="html-italic">n</span> = 3 age-matched healthy donors (&lt;40 y.o); <span class="html-italic">n</span> = 3 (CCS &lt; 40 y.o.), and <span class="html-italic">n</span> = 3 elderly healthy subjects (&gt;60 y.o.). (<b>A</b>) SOD activity; (<b>B</b>) CAT activity; (<b>C</b>) Representative Western blot signals of SOD1 (cytosolic form), SOD2 (mitochondrial form), and CAT. Actin was evaluated as a housekeeping signal. (<b>D</b>) Densitometric analysis of SOD1 signal normalized against actin signal; (<b>E</b>) Densitometric analysis of SOD2 signal normalized against actin signal; (<b>F</b>) Densitometric analysis of CAT signal normalized against actin signal. ROD = Relative Optical Density. *, **** indicate a <span class="html-italic">p</span> &lt; 0.05, 0.0001. In panels (<b>A</b>,<b>B</b>), ##, and ### indicate a <span class="html-italic">p</span> &lt; 0.01, or 0.001, respectively, between sCCS or hCCS and healthy donors over 80 y.o.</p>
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<p>Nrf2 and KEAP1 protein expression in MNCs isolated from CCS, age-matched healthy subjects, and elderly healthy controls. Data reported in this figure are representative of three independent experiments, each on <span class="html-italic">n</span> = 3 age-matched healthy donors (&lt;40 y.o); <span class="html-italic">n</span> = 3 (CCS &lt; 40 y.o.), and <span class="html-italic">n</span> = 3 elderly healthy subjects (&gt;60 y.o.). (<b>A</b>) Representative Western blot signals of Nrf2 and KEAP1. Actin was evaluated as a housekeeping signal. (<b>B</b>) Densitometric analysis of Nrf2 signal normalized against actin signal; (<b>C</b>) Densitometric analysis of KEAP1 signal normalized against actin signal. ROD = Relative Optical Density. **, ***, **** indicate a <span class="html-italic">p</span> &lt; 0.01, 0.001, 0.0001. ns: not significant.</p>
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<p>Nrf2 and antioxidant enzymes protein expression in MNCs isolated from CCS before and after NAC treatment. Data reported in this figure are representative of three independent experiments, each on <span class="html-italic">n</span> = 3 CCS and <span class="html-italic">n</span> = 3 same CCS treated with NAC. (<b>A</b>) Representative Western blot signals of Nrf2, G6PD, H6PD, GR, GPx, SOD1, SOD2, and CAT. Actin was evaluated as a housekeeping signal. (<b>B</b>) Densitometric analysis of Nrf2 signal normalized against actin signal; (<b>C</b>) Densitometric analysis of G6PD signal normalized against actin signal; (<b>D</b>) Densitometric analysis of H6PD signal normalized against actin signal; (<b>E</b>) Densitometric analysis of GR signal normalized against actin signal; (<b>F</b>) Densitometric analysis of GPx signal normalized against actin signal; (<b>G</b>) Densitometric analysis of SOD1 (cytosolic form) signal normalized against actin signal; (<b>H</b>) Densitometric analysis of SOD2 (mitochondrial form) signal normalized against actin signal; (<b>I</b>) Densitometric analysis of CAT signal normalized against actin signal. ROD = Relative Optical Density. **** indicates a <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Antioxidant enzyme activities, OxPhos coupling, and oxidative damage accumulation in MNCs isolated from CCS before and after NAC treatment. Data reported in this figure were obtained on MNCs isolated from <span class="html-italic">n</span> = 20 CCS of solid tumor (sCCS; aged under 40 y.o.) and <span class="html-italic">n</span> = 22 CCS of hematological tumors (hCCS; aged under 40 y.o.) treated or not with NAC. (<b>A</b>) G6PD activity; (<b>B</b>) H6PD activity; (<b>C</b>) GR activity; (<b>D</b>) GPx activity; (<b>E</b>) SOD activity; (<b>F</b>) CAT activity; (<b>G</b>) ROS production; (<b>H</b>) P/O value as an OxPhos efficiency marker; (<b>I</b>) Malondialdehyde (MDA) intracellular concentration, as a lipid peroxidation marker; (<b>J</b>) 4-hydroxynonenal (4-HNE) intracellular concentration, as a lipid peroxidation marker; (<b>K</b>) 8-Hydroxy-2′-deoxyguanosine (8-OHdG) intracellular concentration, as a DNA oxidative damage marker; (<b>L</b>) Nitrotyrosine intracellular level, as a protein oxidative damage marker. **** indicates a <span class="html-italic">p</span> &lt; 0.0001.</p>
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20 pages, 5511 KiB  
Article
Antioxidant Effect of a Plant-Derived Extracellular Vesicles’ Mix on Human Skin Fibroblasts: Induction of a Reparative Process
by Rossella Di Raimo, Davide Mizzoni, Antonella Aloi, Giulia Pietrangelo, Vincenza Dolo, Giuseppina Poppa, Stefano Fais and Mariantonia Logozzi
Antioxidants 2024, 13(11), 1373; https://doi.org/10.3390/antiox13111373 - 9 Nov 2024
Viewed by 917
Abstract
Plant-Derived Extracellular Vesicles extracellular vesicles (PDEVs) from organic agriculture (without the use of pesticides and microbicides) contain high levels of antioxidants. Organic PDEVs have shown an increased antioxidant power compared to PDEVs from single plants, suggesting a synergistic effect of the bioactives constitutively [...] Read more.
Plant-Derived Extracellular Vesicles extracellular vesicles (PDEVs) from organic agriculture (without the use of pesticides and microbicides) contain high levels of antioxidants. Organic PDEVs have shown an increased antioxidant power compared to PDEVs from single plants, suggesting a synergistic effect of the bioactives constitutively expressed in the PDEVs from single fruits. With this study, we wanted to investigate the beneficial effects of a mix of PDEVs on human skin cells. We found detectable levels of citric acid, ascorbic acid, glutathione, catalase, and SOD in a mix of PDEVs deriving from five different fruits (grape, red orange, papaya, pomegranate, and tangerine). We then treated H2O2-conditioned fibroblasts with the mix of PDEVs. The results showed that the PDEVs’ mixture reverted the H2O2-induced redox imbalance, restoring mitochondrial homeostasis, with a strong reduction of mitochondrial anion superoxide and an increase in sirtuin levels. The antioxidant action was consistent with wound repair on a lesion produced in a fibroblast’s monolayer. This result was consistent with an increased level of vimentin and matrix metalloproteinase-9, whose expression is directly related to the efficiency of the reparative processes. These data support a beneficial role of PDEVs in both preventing and treating skin injuries through their potent antioxidant and reparative activities. Full article
(This article belongs to the Special Issue The OxInflammation Process and Tissue Repair)
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Figure 1

Figure 1
<p>PDEVs biophysical characterization. (<b>a</b>) Size and distribution of PDEVs through NTA; (<b>b</b>) Distribution of PDEVs’ zeta potential.</p>
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<p>PDEVs morphological characterization through TEM. (<b>a</b>) Round structure and membrane integrity of PDEVs with sizes between 50 and 80 nm; (<b>b</b>) Round structure and membrane integrity of PDEVs with sizes between 150 and 200 nm; (<b>c</b>) PDEVs plasma membrane visible at 34.000 magnification and (<b>d</b>) 64.000 (insert). The arrow indicates the plasma membrane of vesicles.</p>
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<p>Cellular uptake of Dil-PDEVs in skin fibroblasts after (<b>a</b>) 24 h of treatment; (<b>b</b>) 48 h of treatment; and (<b>c</b>) 72 h of treatment. PDEVs were labeled with Dil (red), and nuclei were counterstained with DAPI (blue).</p>
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<p>PDEVs effect of mitochondrial metabolism. (<b>a</b>) Analysis of mitochondrial membrane potential; (<b>b</b>) analysis of mitochondrial anion superoxide levels. Data are expressed as mean ± SE. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001. Statistical analysis was performed using one-way ANOVA Bonferroni. M.I.F. (a.u.) = Mean I Intensity of Fluorescence (arbitrary unit).</p>
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<p>Quantification of extracellular sirtuin 1 concentration. Data are expressed as mean ± SE. **** <span class="html-italic">p</span> &lt; 0.0001. Statistical analysis was performed using one-way ANOVA Bonferroni.</p>
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<p>Wound healing assay of skin fibroblasts. Representative images are shown from three independent experiments. Data are expressed as mean ± SE. ns: not significant; **** <span class="html-italic">p</span> &lt; 0.0001. Statistical analysis was performed using unpaired <span class="html-italic">t</span>-test (Student’s <span class="html-italic">t</span>-test). Scale bar = 500 µm.</p>
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<p>Collagen I expression in skin fibroblasts at the wound site. Cells were stained with anti-collagen I primary antibody, subsequently a secondary antibody AlexaFluor<sup>®</sup> 488 conjugated was added (green) and nuclei were counterstained with DAPI (blue). Scale bar = 100 µm.</p>
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<p>MMP-9 expression in skin fibroblasts at the wound site. Cells were stained with anti-MMP-9-FITC (green) and nuclei were counterstained with DAPI (blue). Scale bar = 50 µm.</p>
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<p>Quantification of extracellular vimentin. Data are expressed as mean ± SE. **** <span class="html-italic">p</span> &lt; 0.0001. Statistical analysis was performed using unpaired <span class="html-italic">t</span>-test (Student’s <span class="html-italic">t</span>-test).</p>
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19 pages, 6339 KiB  
Article
Autocrine Motility Factor and Its Peptide Derivative Inhibit Triple-Negative Breast Cancer by Regulating Wound Repair, Survival, and Drug Efflux
by Se Gie Kim, Seok Joong Kim, Thanh Van Duong, Yuhan Cho, Bogeun Park, Ulhas Sopanrao Kadam, Hee Sung Park and Jong Chan Hong
Int. J. Mol. Sci. 2024, 25(21), 11714; https://doi.org/10.3390/ijms252111714 - 31 Oct 2024
Viewed by 512
Abstract
Triple-negative breast cancer (TNBC) presents a significant challenge in oncology due to its aggressive nature and limited targeted therapeutic options. This study explores the potential of autocrine motility factor (AMF) and an AMF-derived peptide as novel treatments for TNBC. AMF, primarily secreted by [...] Read more.
Triple-negative breast cancer (TNBC) presents a significant challenge in oncology due to its aggressive nature and limited targeted therapeutic options. This study explores the potential of autocrine motility factor (AMF) and an AMF-derived peptide as novel treatments for TNBC. AMF, primarily secreted by neoplastic cells, plays a crucial role in cancer cell motility, metastasis, and proliferation. The research demonstrates that AMF and its derived peptide inhibit TNBC cell proliferation by modulating cellular migration, redox homeostasis, apoptotic pathways, and drug efflux mechanisms. Dose-dependent antiproliferative effects were observed across three TNBC cell lines, with higher concentrations impairing cellular migration. Mechanistic studies revealed decreased glucose-6-phosphate dehydrogenase expression and elevated reactive oxygen species production, suggesting redox imbalance as a primary mediator of apoptosis. Combination studies with conventional therapeutics showed near-complete eradication of resistant TNBC cells. The observed reduction in p53 levels and increased intranuclear doxorubicin accumulation highlight the AMF/AMF peptide’s potential as multidrug resistance modulators. This study underscores the promise of using AMF/AMF peptide as a novel therapeutic approach for TNBC, addressing current treatment limitations and warranting further investigation. Full article
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Figure 1
<p>AMFs and their derived peptides differentially inhibit TNBC cell proliferation. (<b>A</b>) Cell growth following treatment with eight distinct AMFs at a concentration of 2 µg/mL. (<b>B</b>) Cell growth following treatment with AS:AMF at various concentrations. (<b>C</b>) AMF peptides containing AMF206-219 amino acid sequence are illustrated, where long and short grey boxes indicate AMF209-213 and 325-339 segment, respectively. (<b>D</b>) Cell growth following treatment with AMF peptides at various concentrations. (<b>E</b>) MDA-MB-231 cells at 100% confluency treated with or without 5 µg/mL of AS:AMF or HG-P for 48 h, followed by cell staining. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Internalized HG-P peptides induce apoptosis and alter mitochondrial viability in TNBC cells. (<b>A</b>) MDA-MB-231 cells were treated with FITC-labeled HG-P (10 µg/mL) with or without AS:AMF (10 µg/mL) for 24 h. Scale bar: 100 µm. (<b>B</b>) TNBC cells were treated with propidium iodide (PI) and various concentrations of HG-P for 24 h. Intracellular PI was quantified. (<b>C</b>) MDA-MB-231 cells were assessed for the induction of apoptosis following HG-P treatment as various concentrations. (<b>D</b>) MDA-MB-231 cells were treated with Hoechst 33258 in the presence or absence of 5 µg/mL HG-P for 24 h and imaged. Scale bar: 100 µm. (<b>E</b>) Hoechst 33258 intensity in TNBC cells was measured after 24 h treatment with 0.5 or 5 µg/mL HG-P. (<b>F</b>) MDA-MB-231 cells were treated with Rhodamine 123 (Rho) in the presence or absence of 5 µg/mL HG-P for 24 h and imaged. Scale bar: 100 µm. (<b>G</b>) Rhodamine 123 intensity in TNBC cells was measured after 24 h treatment with or without 5 µg/mL HG-P. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>AMF and AMF peptide influence wound repair capacity in a type- and dose-dependent manner. (<b>A</b>) TNBC cells were treated with various concentrations of AMF or HG-P for 24 h following scratch wounding. Results were photographed at 100× magnification using microscopy or at 40× magnification after crystal violet staining. (<b>B</b>) Quantification of scratch wound repair shown in (<b>A</b>), expressed as relative unrepaired wound area. (<b>C</b>) AMFR/gp78 protein expression in TNBC cells treated with 5 µg/mL of AMF or HG-P. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>AMF and AMF peptide enhance ROS generation and regulate apoptosis-related protein expression. (<b>A</b>) Flow cytometry analysis of ROS-positive and ROS-negative TNBC cells after HG-P treatment. (<b>B</b>) Histogram representation of flow cytometry data from (<b>A</b>). (<b>C</b>) Time course of ROS generation in MDA-MB-231 cells treated with various concentrations of AS:AMF or HG-P, measured using DCFDA fluorescence. (<b>D</b>) Time-dependent ROS generation in additional TNBC cell lines, presented as histograms. (<b>E</b>) <span class="html-italic">G6PD</span> mRNA expression changes in TNBC cells analyzed using qPCR. (<b>F</b>) Protein expression alterations in TNBC cells following HG-P treatment, assessed using Western blot. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Synergistic inhibition of TNBC cell proliferation by HG-P and Tam. (<b>A</b>) MDA-MB-21 cell morphology changes after 24 h treatment with HG-P, Tam, or both. Results were photographed at 200× magnification using microscopy. (<b>B</b>) Crystal violet-stained TNBC cell colonies demonstrating the combined effect of HG-P and Tam at various concentrations. (<b>C</b>) Histogram representation of clonogenic assays from (<b>B</b>). * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Synergistic inhibition of TNBC cell proliferation by HG-P and Dox. (<b>A</b>) MDA-MB-21 cell morphology changes after 24 h treatment with HG-P, Dox, or both. Results were photographed at 200× magnification using microscopy. (<b>B</b>) Crystal violet-stained TNBC cell colonies demonstrating the combined effect of HG-P and Dox at various concentrations. (<b>C</b>) Histogram representation of clonogenic assays from (<b>B</b>). ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>HG-P enhances Dox accumulation in cell nuclei. (<b>A</b>) Dox fluorescence in TNBC cells after co-administration with 5 µg/mL HG-P or 1 µM cyclosporin A (CsA). Scale bar: 100 µm. (<b>B</b>) Intracellular Dox accumulation measured following co-administration with various concentrations of HG-P. (<b>C</b>) Comparison of Dox accumulation following treatment with different concentrations of CsA or HG-P. (<b>D</b>) Dox distribution in MDA-MB-231 cells and culture medium after treatment with various HG-P concentrations. Scale bar: 100 µm. (<b>E</b>) Enlarged images of Dox accumulation shown in (<b>D</b>). Scale bar: 100 µm. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The impact of HG-P on the expression of MDR-associated genes. (<b>A</b>) qPCR analysis was performed to examine the expression levels of three key genes linked to MDR following HG-P (5 µg/mL) treatment. (<b>B</b>) Western blot analysis (n = 3) demonstrated P-gp regulation in response to HG-P and AMF treatments (5 µg/mL). Arrow: 150 kDa P-gp.</p>
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18 pages, 1703 KiB  
Review
miRNAs Involvement in Modulating Signalling Pathways Involved in Ros-Mediated Oxidative Stress in Melanoma
by José Daniel Escobar Moreno, José Luis Fajardo Castiblanco, Laura Camila Riaño Rodriguez, Paula Marcela Barrios Ospina, Carlos Andrés Zabala Bello, Esther Natalia Muñoz Roa and Hernán Mauricio Rivera Escobar
Antioxidants 2024, 13(11), 1326; https://doi.org/10.3390/antiox13111326 - 30 Oct 2024
Viewed by 992
Abstract
Reactive oxygen species (ROS) are intermediates in oxidation–reduction reactions with the capacity to modify biomolecules and temporarily or permanently alter cell behaviour through signalling pathways under physiological and pathophysiological conditions where there is an imbalance between oxidative factors and the antioxidant response of [...] Read more.
Reactive oxygen species (ROS) are intermediates in oxidation–reduction reactions with the capacity to modify biomolecules and temporarily or permanently alter cell behaviour through signalling pathways under physiological and pathophysiological conditions where there is an imbalance between oxidative factors and the antioxidant response of the organism, a phenomenon known as oxidative stress. Evidence suggests that the differential modulation of ROS-mediated oxidative stress occurs in the pathogenesis and progression of melanoma, and that this imbalance in redox homeostasis appears to be functionally linked to microRNA (miRNA o miRs)-mediated non-mutational epigenetic reprogramming involving genes and transcription factors. The relationship between ROS-mediated stress control, tumour microenvironment, and miRNA expression in melanoma is not fully understood. The aim of this review is to analyse the involvement of miRNAs in the modulation of the signalling pathways involved in ROS-mediated oxidative stress in melanoma. It is hoped that these considerations will contribute to the understanding of the mechanisms associated with a potential epigenetic network regulation, where the modulation of oxidative stress is consolidated as a common factor in melanoma, and therefore, a potential footprint poorly documented. Full article
(This article belongs to the Special Issue Non-Coding RNAs and Reactive Oxygen Species)
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<p>Workflow for database selection and graph construction.</p>
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<p>Heatmap of differentially expressed genes (DEGs) between the cell line depleted of miR-211 and the xenografts derived from these cell lines. The colour and intensity of the squares represent changes (absolute values) in expression. Red (over expression) and green (under expression).</p>
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<p>Protein regulatory network associated with oxidative stress in melanoma.</p>
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<p>Regulatory network of miRNAs, genes, and transcription factors associated with oxidative stress in melanoma.</p>
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17 pages, 2269 KiB  
Review
New Insights into the Fanconi Anemia Pathogenesis: A Crosstalk Between Inflammation and Oxidative Stress
by Anna Repczynska, Barbara Ciastek and Olga Haus
Int. J. Mol. Sci. 2024, 25(21), 11619; https://doi.org/10.3390/ijms252111619 - 29 Oct 2024
Viewed by 641
Abstract
Fanconi anemia (FA) represents a rare hereditary disease; it develops due to germline pathogenic variants in any of the 22 currently discovered FANC genes, which interact with the Fanconi anemia/breast cancer-associated (FANC/BRCA) pathway to maintain genome integrity. FA is characterized by a triad [...] Read more.
Fanconi anemia (FA) represents a rare hereditary disease; it develops due to germline pathogenic variants in any of the 22 currently discovered FANC genes, which interact with the Fanconi anemia/breast cancer-associated (FANC/BRCA) pathway to maintain genome integrity. FA is characterized by a triad of clinical traits, including congenital anomalies, bone marrow failure (BMF) and multiple cancer susceptibility. Due to the complex genetic background and a broad spectrum of FA clinical symptoms, the diagnostic process is complex and requires the use of classical cytogenetic, molecular cytogenetics and strictly molecular methods. Recent findings indicate the interplay of inflammation, oxidative stress, disrupted mitochondrial metabolism, and impaired intracellular signaling in the FA pathogenesis. Additionally, a shift in the balance towards overproduction of proinflammatory cytokines and prooxidant components in FA is associated with advanced myelosuppression and ultimately BMF. Although the mechanism of BMF is very complex and needs further clarification, it appears that mutual interaction between proinflammatory cytokines and redox imbalance causes pancytopenia. In this review, we summarize the available literature regarding the clinical phenotype, genetic background, and diagnostic procedures of FA. We also highlight the current understanding of disrupted autophagy process, proinflammatory state, impaired signaling pathways and oxidative genotoxic stress in FA pathogenesis. Full article
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<p>Schematic concept of Fanconi anemia pathogenesis.</p>
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<p>A simplified diagnostic algorithm for Fanconi anemia, including indications for FA diagnosis and general genetic tests.</p>
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<p>Chromosomal aberrations after addition of cross-linking agent (MMC) to the lymphocyte culture of patient with FA (<b>A</b>) and healthy control (<b>B</b>). Arrows indicate chromatid breaks.</p>
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<p>Schematic representation of how biallelic pathogenic variants in <span class="html-italic">FANC</span> (<span class="html-italic">Fanc<sup>−/−</sup>)</span> genes trigger a vicious circle between proinflammatory cytokines, oxidative genotoxic stress and MAPK, Notch as well as NF-κB signaling pathways.</p>
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