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Cells
Volume 13
Issue 23
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Cells, Volume 13, Issue 23 (December-1 2024) – 17 articles

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12 pages, 891 KiB  
Article
Intranasal Treatment with Cannabinoid 2 Receptor Agonist HU-308 Ameliorates Cold Sensitivity in Mice with Traumatic Trigeminal Neuropathic Pain
by Simeng Ma, Yoki Nakamura, Suzuna Uemoto, Kenta Yamamoto, Kazue Hisaoka-Nakashima and Norimitsu Morioka
Cells 2024, 13(23), 1943; https://doi.org/10.3390/cells13231943 (registering DOI) - 22 Nov 2024
Abstract
Post-traumatic trigeminal neuropathy (PTTN) is a sensory abnormality caused by injury to the trigeminal nerve during orofacial surgery. However, existing analgesics are ineffective against PTTN. Abnormal microglial activation in the caudal part of the spinal trigeminal nucleus caudal part (Sp5C), where the central [...] Read more.
Post-traumatic trigeminal neuropathy (PTTN) is a sensory abnormality caused by injury to the trigeminal nerve during orofacial surgery. However, existing analgesics are ineffective against PTTN. Abnormal microglial activation in the caudal part of the spinal trigeminal nucleus caudal part (Sp5C), where the central trigeminal nerve terminals reside, plays an important role in PTTN pathogenesis. Therefore, regulating microglial activity in Sp5C appears to be an important approach to controlling pain in PTTN. Cannabinoid receptor 2 (CB2) is expressed in immune cells including microglia, and its activation has anti-inflammatory effects. The current study demonstrates that the repeated intranasal administration of CB2 agonist HU-308 ameliorates the infraorbital nerve cut (IONC)-induced hyperresponsiveness to acetone (cutaneous cooling). The therapeutic efficacy of oral HU-308 was found to be less pronounced in alleviating cold hypersensitivity in IONC mice compared to intranasal administration, indicating the potential advantages of the intranasal route. Furthermore, repeated intranasal administration of HU-308 suppressed the activation of Sp5C microglia in IONC mice. Additionally, pretreatment with the CB2 antagonist, SR 144528, significantly blocked the anti-nociceptive effect of repeated intranasal administration of HU-308 on cold hypersensitization in IONC mice. These data suggest that the continuous stimulation of CB2 ameliorates PTTN-induced pain via the inhibition of microglial activation. Thus, CB2 agonists are potential candidates for novel therapeutic agents against PTTN. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Neuropathic Pain)
13 pages, 962 KiB  
Article
Exosomal MALAT1 from Rapid Electrical Stimulation-Treated Atrial Fibroblasts Enhances Sox-6 Expression by Downregulating miR-499a-5p
by Cheng-Yen Chuang, Bao-Wei Wang, Ying-Ju Yu, Wei-Jen Fang, Chiu-Mei Lin, Kou-Gi Shyu and Su-Kiat Chua
Cells 2024, 13(23), 1942; https://doi.org/10.3390/cells13231942 (registering DOI) - 22 Nov 2024
Abstract
Background: Atrial fibrillation (AF) is a common cardiac arrhythmia associated with significant morbidity and mortality. Rapid electrical stimulation (RES) of atrial fibroblasts plays a crucial role in AF pathogenesis, but the underlying molecular mechanisms remain unclear. This study investigates the regulatory axis involving [...] Read more.
Background: Atrial fibrillation (AF) is a common cardiac arrhythmia associated with significant morbidity and mortality. Rapid electrical stimulation (RES) of atrial fibroblasts plays a crucial role in AF pathogenesis, but the underlying molecular mechanisms remain unclear. This study investigates the regulatory axis involving MALAT1, miR-499a-5p, and SOX6 in human cardiac fibroblasts from adult atria (HCF-aa) under RES conditions. Methods: HCF-aa were subjected to RES at 0.5V/cm and 10 Hz. The expression levels of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), miR-499a-5p, and SRY-Box Transcription Factor 6 (SOX6) were measured using qPCR and Western blot analyses. Luciferase reporter assays were performed to confirm target relationships. The effects of MALAT1 siRNA, miR-499a-5p mimics/inhibitors, and SOX6 overexpression on gene expression and apoptosis were assessed. Results: RES increased exosomal MALAT1 expression, peaking at 2 h. MiR-499a-5p levels initially increased, then decreased at 2 h, coinciding with peak MALAT1 expression. SOX6 mRNA and protein levels increased, peaking at 4 and 6 h, respectively. Luciferase assays confirmed MALAT1 and SOX6 as miR-499a-5p targets. MALAT1 knockdown increased miR-499a-5p levels and reduced SOX6 expression. MiR-499a-5p overexpression decreased SOX6 levels and inhibited RES-induced apoptosis. Conclusion: In HCF-aa under RES, increased exosomal MALAT1 expression counteracts miR-499-5p’s suppression of SOX6, suggesting that MALAT1-containing exsosomes derived from HCF-aa may offer a novel cell-free therapeutic approach for AF. Full article
(This article belongs to the Collection Cardiovascular Disease: From Molecular and Cellular Mechanisms to Therapeutic Opportunities)
30 pages, 1068 KiB  
Article
Peripheral Blood Leukocyte Subpopulation Changes in Reaction to an Acute Psychosocial Stressor as Compared to an Active Placebo-Stressor in Healthy Young Males: Mediating Effects of Major Stress-Reactive Endocrine Parameters
by Lisa-Marie Walther, Angelina Gideon, Christine Sauter, Marcel Leist and Petra H. Wirtz
Cells 2024, 13(23), 1941; https://doi.org/10.3390/cells13231941 (registering DOI) - 22 Nov 2024
Abstract
Psychosocial stress has been proposed to induce a redistribution of immune cells, but a comparison with an active placebo-psychosocial stress control condition is lacking so far. We investigated immune cell redistribution due to psychosocial stress compared to that resulting from an active placebo-psychosocial [...] Read more.
Psychosocial stress has been proposed to induce a redistribution of immune cells, but a comparison with an active placebo-psychosocial stress control condition is lacking so far. We investigated immune cell redistribution due to psychosocial stress compared to that resulting from an active placebo-psychosocial stress but otherwise identical control condition. Moreover, we tested for mediating effects of endocrine parameters and blood volume changes. The final study sample comprised 64 healthy young men who underwent either a psychosocial stress condition (Trier Social Stress Test; TSST; n = 38) or an active placebo-psychosocial stress control condition (PlacTSST; n = 26). Immune cell counts and hemoglobin, epinephrine, norepinephrine, ACTH, renin, and aldosterone levels, as well as those of saliva cortisol, were determined before and up to 30 min after the TSST/PlacTSST. The TSST induced greater increases in total leukocyte, monocyte, and lymphocyte levels as compared to the PlacTSST (p’s ≤ 0.001), but in not granulocyte counts. Neutrophil granulocyte counts increased in reaction to both the TSST and PlacTSST (p’s ≤ 0.001), while eosinophil and basophil granulocyte counts did not. The psychosocial stress-induced increases in immune cell counts from baseline to peak (i.e., +1 min after TSST cessation) were independently mediated by parallel increases in epinephrine (ab’s ≤ −0.43; 95% CIs [LLs ≤ −0.66; ULs ≤ −0.09]). Subsequent decreases in immune cell counts from +1 min to +10 min after psychosocial stress cessation were mediated by parallel epinephrine, renin, and blood volume decreases (ab’s ≥ 0.17; 95% CIs [LLs ≥ 0.02; ULs ≥ 0.35]). Our findings indicate that psychosocial stress specifically induces immune cell count increases in most leukocyte subpopulations that are not secondary to the physical or cognitive demands of the stress task. Increases in the number of circulating neutrophil granulocytes, however, are not psychosocial stress-specific and even occur in situations with a low probability of threat or harm. Our findings point to a major role of epinephrine in mediating stress-induced immune cell count increases and of epinephrine, renin, and blood volume changes in mediating subsequent immune cell count decreases from +1 min to +10 min after psychosocial stress cessation. Full article
(This article belongs to the Special Issue Innate Immunity in Health and Disease)
42 pages, 2107 KiB  
Review
Impact of Physical Activity on Cellular Metabolism Across Both Neurodegenerative and General Neurological Conditions: A Narrative Review
by Vicente Javier Clemente-Suárez, Alejandro Rubio-Zarapuz, Pedro Belinchón-deMiguel, Ana Isabel Beltrán-Velasco, Alexandra Martín-Rodríguez and José Francisco Tornero-Aguilera
Cells 2024, 13(23), 1940; https://doi.org/10.3390/cells13231940 - 22 Nov 2024
Abstract
Background: Regular physical activity plays a crucial role in modulating cellular metabolism and mitigating the progression of neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. Objective: The objective of this review is to evaluate the molecular mechanisms by which exercise influences cellular [...] Read more.
Background: Regular physical activity plays a crucial role in modulating cellular metabolism and mitigating the progression of neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. Objective: The objective of this review is to evaluate the molecular mechanisms by which exercise influences cellular metabolism, with a focus on its potential as a therapeutic intervention for neurological disorders. Methods: A comprehensive literature review was conducted using peer-reviewed scientific articles, with a focus on the period between 2015 and 2024, to analyze the effects of exercise on mitochondrial function, oxidative stress, and metabolic health. Results: The findings indicate that exercise promotes mitochondrial biogenesis, enhances oxidative phosphorylation, and reduces reactive oxygen species, contributing to improved energy production and cellular resilience. These metabolic adaptations are associated with delayed disease progression and reduced symptoms in patients with neurodegenerative conditions. Additionally, integrating exercise with nutritional strategies may further enhance therapeutic outcomes by addressing metabolic disturbances comprehensively. Conclusion: This review concludes that personalized exercise protocols should be developed to optimize metabolic benefits for patients with neurological diseases, while future research should focus on biomarker development for individualized treatment approaches. These findings highlight the importance of non-pharmacological interventions in managing neurodegenerative diseases. Full article
(This article belongs to the Special Issue Cell-to-Cell Crosstalk as a Target of Therapies)
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
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 Collection Collection of Cell Aging—The Road Map of 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> Full article ">
20 pages, 4672 KiB  
Article
Investigation of Biological Activity of Fucoidan and Laminarin as Bioactive Polysaccharides from Irish Brown Macroalgae
by Shanmugapriya Karuppusamy, Janith Wanigasekara, Stephen Fitzpatrick, Henry Lyons, James Curtin, Gaurav Rajauria, Brijesh K. Tiwari and Colm O’Donnell
Cells 2024, 13(23), 1938; https://doi.org/10.3390/cells13231938 - 22 Nov 2024
Abstract
This study aimed to investigate the biological activity of crude and purified laminarin and fucoidan samples extracted from Irish brown macroalgae species Laminaria digitata and Fucus vesiculosus. The antioxidant capacity of the samples was evaluated using the 2,2-diphenyl-1-picrylhydrazyl and ferric-reducing antioxidant power [...] Read more.
This study aimed to investigate the biological activity of crude and purified laminarin and fucoidan samples extracted from Irish brown macroalgae species Laminaria digitata and Fucus vesiculosus. The antioxidant capacity of the samples was evaluated using the 2,2-diphenyl-1-picrylhydrazyl and ferric-reducing antioxidant power assays. The anti-inflammatory potential of the samples was analysed using the cyclooxygenases inhibition activity, and the antidiabetic activity was evaluated using a dipeptidyl peptidase-4 inhibitor screening assay. The cytotoxicity of the samples was measured using the Alamar Blue™ assay with different types of cancer cell lines. The crude laminarin and fucoidan samples exhibited higher antioxidant activity (p < 0.05) than the purified samples and commercial standards. Similarly, the crude extracts showed stronger anti-inflammatory and antidiabetic effects compared to the purified samples. Additionally, the crude laminarin and fucoidan samples showed higher cytotoxic activity. Specifically, as confirmed in the flow cytometry analysis, 3D tumour spheres using different cancer cell lines showed significantly higher resistance to bioactive compounds compared to 2D monolayer cells. The laminarin and fucoidan polysaccharide samples investigated are suitable for potential nutraceutical applications based on the biological activity values observed. Future research is necessary to purify the bioactive compounds investigated and improve their selectivity for targeted therapeutic uses in food and biomedical applications. Full article
(This article belongs to the Section Plant, Algae and Fungi Cell Biology)
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Figure 1

Figure 1
<p>Bioactive properties of laminarin and fucoidan samples in different antioxidant assays. (<b>a</b>) 1,1-diphenyl-2-picryl-hydrazyl (DPPH) activity and (<b>b</b>) ferric-reducing antioxidant power (FRAP) assays at different concentrations. The graph shows the sample concentration in µg/mL on the X-axis and the percentage inhibition of antioxidant values on the Y-axis. All values represent the means of triplicate results (n = 3, Mean ± S.D.). Significant statistical differences in the antioxidant potential are represented as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. The seaweed samples used for the study were crude laminarin (C.L.), an MWCO 10 kDa laminarin fraction (M.L.), a Sigma laminarin standard (S.L.), crude fucoidan (C.F.), an MWCO 10 kDa fucoidan fraction (M.F.), and a Sigma fucoidan standard (S.F).</p> Full article ">Figure 2
<p>Effects of anti-inflammatory activity of seaweed samples with COX-1 and COX-2. All values represent the means of triplicate results and are expressed as the mean ± SD. Statistically significant differences in antioxidant potential are represented as * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. Seaweed samples used were crude laminarin (C.L.), MWCO 10 kDa laminarin fraction (M.L.), crude fucoidan (C.F.), MWCO 10 kDa fucoidan fraction (M.F.), and reference drug (diclofenac sodium) as R.D.</p> Full article ">Figure 3
<p>Screening of seaweed extracts for antidiabetic activity using dipeptidyl peptidase-4 (DPP-4) inhibitory activity. The seaweed samples were analysed for the inhibition of DPP-4 at different concentrations. All data represent the means of triplicate results and are represented as the mean ± SD. Statistically significant differences are represented with <span class="html-italic">p</span>-values (* <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; 0.0001; n = 9). Seaweed samples used for the study were crude laminarin (C.L.), MWCO 10 kDa laminarin fraction (M.L.), Sigma laminarin standard (S.L.), crude fucoidan (C.F.), MWCO 10 kDa fucoidan fraction (M.F.), Sigma fucoidan standard (S.F.), and reference drug (R.D.).</p> Full article ">Figure 4
<p>Cytotoxicity effects of different seaweed extracts in U-251MG human glioblastoma multiforme cells (<b>a</b>,<b>b</b>) and A431 human epidermoid carcinoma cells (<b>c</b>,<b>d</b>) at 2 days and 6 days post-treatment incubation. All values are expressed as the mean ± SD. Significant differences were analysed. Seaweed samples used for study were crude laminarin (C.L.), MWCO 10 kDa laminarin fraction (M.L.), Sigma laminarin standard (S.L.), crude fucoidan (C.F.), MWCO 10 kDa fucoidan fraction (M.F.), and Sigma fucoidan standard (S.F.).</p> Full article ">Figure 5
<p>Cytotoxicity effects of different seaweed extracts in HepG2 human hepatoma cells (<b>a</b>,<b>b</b>), Caco-2 human colorectal adenocarcinoma cells (<b>c</b>,<b>d</b>), and HEK293 human embryonic kidney cells (<b>e</b>,<b>f</b>) at 2 days and 6 days of post-treatment incubation. All values are expressed as the mean ± SD. Significant differences were analysed. Seaweed samples used for study were crude laminarin (C.L.), MWCO 10 kDa laminarin fraction (M.L.), Sigma laminarin standard (S.L.), crude fucoidan (C.F.), MWCO 10 kDa fucoidan fraction (M.F.), and Sigma fucoidan standard (S.F.).</p> Full article ">Figure 6
<p>(<b>A</b>) Effects of U-251MG human glioblastoma 3D tumour spheres in in vitro cell culture model. (<b>B</b>) A graph representing different seaweed extracts at 6 days post-treatment incubation. (<b>a</b>) Image of U-251MG 2D cells and (<b>b</b>) 3D tumour spheres in low adhesion using an optical microscope. All values are expressed as the mean ± SD. Significant differences were analysed. Seaweed samples used for study were crude laminarin (C.L.), MWCO 10 kDa laminarin fraction (M.L.), standard laminarin (S.L.), crude fucoidan (C.F.), MWCO 10 kDa fucoidan fraction (M.F.), and standard fucoidan (S.F.).</p> Full article ">Figure 7
<p>(<b>A</b>) Analysis of flow cytometry data for seaweed samples. (<b>a</b>) U-251MG human glioblastoma multiforme cells and (<b>b</b>) A431 human epidermoid carcinoma cells at 6 days post-treatment incubation. (<b>B</b>) Flow cytometry data of seaweed samples at 6 days post-treatment incubation. (<b>a</b>) A graph representing different samples in U-251MG human glioblastoma multiforme cells and (<b>b</b>) a graph representing different samples in A431 human epidermoid carcinoma cells. The graph shows the total number of apoptotic cells (%), represented as a bar chart, and we analysed the significant differences (**** <span class="html-italic">p</span> &lt; 0.0001 vs. P.C. and N.C.). Seaweed samples used for study were crude laminarin (C.L.), MWCO 10 kDa laminarin fraction (M.L.), Sigma laminarin standard (S.L.), crude fucoidan (C.F.), MWCO 10 kDa fucoidan fraction (M.F.), and Sigma fucoidan standard (S.F.); positive and negative controls denoted as P.C. and N.C., respectively.</p> Full article ">Figure 8
<p>(<b>A</b>) Microscopic images captured at 0 h (a-g) and 24 h (h-n) after cell wounding in U-251MG cells and (<b>B</b>) wound closure rate (%) (n = 3; ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001 vs. control at 24 h). Seaweed samples used for study were crude laminarin (C.L., (<b>a</b>,<b>h</b>)), MWCO 10 kDa laminarin fraction (M.L., (<b>b</b>,<b>i</b>)), Sigma laminarin standard (S.L., (<b>c</b>,<b>j</b>)), crude fucoidan (C.F., (<b>d</b>,<b>k</b>)), MWCO 10 kDa fucoidan fraction (M.F., (<b>e</b>,<b>l</b>)), and Sigma fucoidan standard (S.F., (<b>f</b>,<b>m</b>)), compared with control (<b>g</b>,<b>n</b>).</p> Full article ">
24 pages, 1241 KiB  
Review
Exploring the Immunoresponse in Bladder Cancer Immunotherapy
by Inmaculada Ruiz-Lorente, Lourdes Gimeno, Alicia López-Abad, Pedro López Cubillana, Tomás Fernández Aparicio, Lucas Jesús Asensio Egea, Juan Moreno Avilés, Gloria Doñate Iñiguez, Pablo Luis Guzmán Martínez-Valls, Gerardo Server, José Félix Escudero-Bregante, Belén Ferri, José Antonio Campillo, Eduardo Pons-Fuster, María Dolores Martínez Hernández, María Victoria Martínez-Sánchez, Diana Ceballos and Alfredo Minguela
Cells 2024, 13(23), 1937; https://doi.org/10.3390/cells13231937 - 22 Nov 2024
Abstract
Bladder cancer (BC) represents a wide spectrum of diseases, ranging from recurrent non-invasive tumors to advanced stages that require intensive treatments. BC accounts for an estimated 500,000 new cases and 200,000 deaths worldwide every year. Understanding the biology of BC has changed how [...] Read more.
Bladder cancer (BC) represents a wide spectrum of diseases, ranging from recurrent non-invasive tumors to advanced stages that require intensive treatments. BC accounts for an estimated 500,000 new cases and 200,000 deaths worldwide every year. Understanding the biology of BC has changed how this disease is diagnosed and treated. Bladder cancer is highly immunogenic, involving innate and adaptive components of the immune system. Although little is still known of how immune cells respond to BC, immunotherapy with bacillus Calmette–Guérin (BCG) remains the gold standard in high-risk non-muscle invasive BC. For muscle-invasive BC and metastatic stages, immune checkpoint inhibitors targeting CTLA-4, PD-1, and PD-L1 have emerged as potent therapies, enhancing immune surveillance and tumor cell elimination. This review aims to unravel the immune responses involving innate and adaptive immune cells in BC that will contribute to establishing new and promising therapeutic options, while reviewing the immunotherapies currently in use in bladder cancer. Full article
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Immunological mechanisms of intravesical BCG treatment in bladder cancer: (<b>A</b>) Classification of BC according to the TNM staging system. CIS (carcinoma in situ) represents a non-muscle invasive bladder cancer (NMIBC) confined to the bladder lining; Ta, papillary NMIBC limited to the inner lining; T1, NMIBC that invades the subepithelial connective tissue without penetrating the muscle layer; T2, muscle-invasive bladder (MIBC) cancer; T3, MIBC that invades the perivesical tissue surrounding the bladder; and T4, advanced MIBC that invades surrounding structures such as the prostate, uterus, or pelvic wall. (<b>B</b>) NMIBC is treated with BCG. Upon instillation, BCG is taken up by bladder urothelial cells, antigen-presenting cells (APC), macrophages, and dendritic cells (DCs), leading to the release of pro-inflammatory cytokines and the activation of the immune response, including T and natural killer (NK) cells, which recognize and attack tumor cells. DCs express toll-like receptors (TLRs) that recognize pathogen-associated molecular patterns (PAMPs), promoting the secretion of cytokines and the presentation of tumor antigens via the major histocompatibility complex (MHC) to CD4+ and CD8+ T lymphocytes, thus contributing to tumor eradication. BCG induces NK cell functional maturation, increasing the expression of CD56 and the release of proinflamatory cytokines, granzyme, and perforin, which contribute to the destruction of tumor cells. Understanding these mechanisms is vital for optimizing BCG therapy and improving outcomes for patients with bladder cancer.</p> Full article ">Figure 2
<p>Mechanisms of immune checkpoint blockade in cancer therapy. The adequate activation of T lymphocytes requires a primary specific signal delivered by the TCR/MHC interaction together with co-stimulatory signals mainly delivered by the CD28/CD80-CD86 interaction. In contrast, the interactions of CTLA-4/CD80-CD86, PD-1/PD-L1, NKG2A/HLA-E, or TIGIT/CD155 inhibit and regulate T cell activation and function. These inhibitory interactions can be blocked using immunotherapeutic monoclonal antibodies: anti-PD-1 (Nivolumab, Pembrolizumab), anti-PD-L1 (Atezolizumab, Avelumab, and Durvalumab), anti-CTLA-4 (Ipilimumab, Tremelimumab), anti-NKG2A (Monalizumab), or anti-TIGIT (Tiragolumab, Sacituzumab).</p> Full article ">
23 pages, 3349 KiB  
Article
Evidence for a Role of the Long Non-Coding RNA ITGB2-AS1 in Eosinophil Differentiation and Functions
by Timothée Fettrelet, Aref Hosseini, Jacqueline Wyss, Joanna Boros-Majewska, Darko Stojkov, Shida Yousefi and Hans-Uwe Simon
Cells 2024, 13(23), 1936; https://doi.org/10.3390/cells13231936 - 22 Nov 2024
Viewed by 125
Abstract
Eosinophils, a type of granulocyte derived from myeloid precursors in the bone marrow, are distinguished by their cytoplasmic granules. They play crucial roles in immunoregulation, tissue homeostasis, and host defense, while also contributing to the pathogenesis of various inflammatory diseases. Although long non-coding [...] Read more.
Eosinophils, a type of granulocyte derived from myeloid precursors in the bone marrow, are distinguished by their cytoplasmic granules. They play crucial roles in immunoregulation, tissue homeostasis, and host defense, while also contributing to the pathogenesis of various inflammatory diseases. Although long non-coding RNAs (lncRNAs) are known to be involved in eosinophilic conditions, their specific expression and functions within eosinophils have not been thoroughly investigated, largely due to the reliance on tissue homogenates. In an effort to address this gap, we analyzed publicly available high-throughput RNA sequencing data to identify lncRNAs associated with eosinophilic conditions. Among the identified lncRNAs, ITGB2 antisense RNA 1 (ITGB2-AS1) was significantly downregulated in blood eosinophils from patients with hypereosinophilia. To further explore its role in eosinophil biology, we generated a stable ITGB2-AS1 knockdown in the HL-60 cell line. Interestingly, ITGB2-AS1 deficiency led to impaired eosinophil differentiation, as evidenced by a reduction in cytoplasmic granules and decreased expression of key eosinophil granule proteins, including eosinophil peroxidase (EPX) and major basic protein-1 (MBP-1). Additionally, ITGB2-AS1-deficient cells exhibited compromised eosinophil effector functions, with reduced degranulation and impaired production of reactive oxygen species (ROS). These findings suggest that ITGB2-AS1 plays a pivotal role in eosinophil differentiation and function, positioning it as a novel regulator in eosinophil biology. Full article
(This article belongs to the Special Issue Eosinophils and Their Role in Allergy and Related Diseases)
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<p>Identification of eight lncRNA candidates predicted <span class="html-italic">in silico</span> from human transcriptomic datasets of eosinophil-related diseases. (<b>A</b>) Identification of lncRNAs. Heatmap illustrating 44 lncRNAs that are differentially expressed in eosinophils compared with other WBCs, identified through a manual query of the Haemopedia dataset [<a href="#B22-cells-13-01936" class="html-bibr">22</a>]. The color key represents row Z-scores, with red indicating overexpression and blue representing downregulation. (<b>B</b>) Correlation network analysis. Correlation network between <span class="html-italic">in silico</span> predicted lncRNAs (yellow) and a gene list of eosinophil-related proteins (color-coded by protein type). Edges represent significant correlations (<span class="html-italic">p</span>-values &lt; 0.05) with a correlation coefficient greater than 0.7. Four distinct clusters were manually defined based on the network of eosinophil-related protein-coding genes associated with the different lncRNAs. Abbreviations: lncRNA, long non-coding RNA; WBC, white blood cell.</p> Full article ">Figure 2
<p>Abundance of <span class="html-italic">in silico</span>-predicted lncRNAs in blood eosinophils from healthy controls and hypereosinophilic patients. (<b>A</b>–<b>H</b>) Quantitative PCR. Abundance of the lncRNAs identified through correlation network analysis of eosinophil-related disease datasets in circulating eosinophils from the blood of healthy controls and HE patients. The name of each lncRNA is indicated above its respective graph. RNA levels were normalized using the geometric mean of the reference genes <span class="html-italic">GAPDH</span> and <span class="html-italic">UBC</span> and presented relative to control samples (<span class="html-italic">n</span> ≥ 3). Values are means ± SEM. ns, not significant; * <span class="html-italic">p</span> &lt; 0.05. Abbreviation: HE, hypereosinophilic; lncRNA, long non-coding RNA; RNA, ribonucleic acid.</p> Full article ">Figure 3
<p>The effect of <span class="html-italic">ITGB2-AS1</span> lncRNA deficiency on eosinophil differentiation, granulogenesis, and EPX expression. (<b>A</b>–<b>F</b>) HL-60c15 cells were differentiated into ELCs in the presence of sodium butyrate and IL-5 for up to 6 days. (<b>A</b>) Cell morphology. (<b>Left</b>) Representative images of differentiating HL-60c15 following Hemacolor Rapid staining at the indicated days of differentiation. Images were acquired with the automatic digital slide scanner Pannoramic MIDI II. Intracellular granules are indicated by black arrows. Scale bars, 10 µm. (<b>Right</b>) The frequency of granulated cells was evaluated manually by light microscopy using a C plan 100×/1.25 Oil objective (<span class="html-italic">n</span> = 4). (<b>B</b>,<b>C</b>) Flow cytometry. The frequency of HL-60c15 cell differentiation was assessed by CD11b (<b>B</b>) and CCR3 (<b>C</b>) surface expression after exclusion of dead cells (<span class="html-italic">n</span> = 4). (<b>D</b>) Quantitative PCR. Relative RNA levels of the granule protein EPX in differentiating HL-60c15 cells after the indicated days of differentiation. <span class="html-italic">EPX</span> RNA levels were normalized using the geometric mean of the reference genes <span class="html-italic">GAPDH</span>, <span class="html-italic">UBC</span>, and <span class="html-italic">HPRT1</span> and presented relative to shControl cells at day 0 of differentiation (<span class="html-italic">n</span> ≥ 3). (<b>E</b>) Immunoblotting. Protein lysates were obtained from differentiating HL-60c15 cells at the indicated days of differentiation. EPX was detected using a monoclonal mouse anti-EPX antibody. GAPDH protein levels served as loading controls. Lysates from human blood eosinophils (Human Eos) were used as a positive control for the presence of EPX. A representative immunoblot of three independent experiments is shown. (<b>F</b>) Confocal microscopy. Differentiating HL-60c15 cells were stained for the eosinophil granule protein EPX and the nuclei using monoclonal mouse anti-EPX antibody and Hoechst 33342, respectively. (<b>Left</b>) Representative images of the presence of EPX in HL-60c15 cells at the indicated days of differentiation. (<b>Right</b>) Quantification of the mean fluorescence intensity (MFI) of intracellular EPX. Cells were delimited using “Surfaces” mode in Imaris, followed by EPX (green channel) MFI quantification (<span class="html-italic">n</span> = 4, with ≥42 cells per condition). Scale bars, 10 µm. Values are means ± SEM. ns, not significant; * <span class="html-italic">p</span> &lt; 0.05. **** <span class="html-italic">p</span> &lt; 0.0001. Significances in black illustrate the significance of shControl cells compared with undifferentiated (day 0) shControl cells. Significances in green denote the significance of shITGB2-AS1 cells compared with shITGB2-AS1 cells at day 0. Significances in red illustrate the significant difference between the shControl and shITGB2-AS1 cells. Abbreviations: ELC, eosinophil-like cell; EPX, eosinophil peroxidase; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; HPRT1, hypoxanthine-guanine phosphoribosyltransferase 1; lncRNA, long non-coding RNA; kDa, kilodalton; MFI, mean fluorescence intensity; RNA, ribonucleic acid; UBC, ubiquitin C.</p> Full article ">Figure 4
<p>Expression of eosinophil-related proteins shown to be co-expressed with the lncRNA <span class="html-italic">ITGB2-AS1</span> in the correlation network analysis. (<b>A</b>–<b>E</b>) Flow cytometry. HL-60c15 cells were differentiated into ELCs in the presence of sodium butyrate and IL-5 for up to 6 days. The surface protein expression of ITGB2 (<b>A</b>), CCR1 (<b>B</b>), CD48 (<b>C</b>), CD52 (<b>D</b>), and CXCR3 (<b>E</b>) was assessed after the exclusion of dead cells (<span class="html-italic">n</span> ≥ 3). (<b>A</b>–<b>E</b>) (<b>Left</b>) Frequency of live cells expressing the proteins at the plasma membrane. (<b>Right</b>) Surface protein expression levels are represented as MFI in live cells. Values are means ± SEM. ns, not significant; * <span class="html-italic">p</span> &lt; 0.05. ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001. Significances in black illustrate the significance of shControl cells compared with undifferentiated (day 0) shControl cells. Significances in green denote the significance of shITGB2-AS1 cells compared with undifferentiated shITGB2-AS1 cells. Significances in red illustrate a significant difference between the shControl and shITGB2-AS1 cells. Abbreviations: CXCR3, C-X-C motif chemokine receptor 3; ELC, eosinophil-like cell; ITGB2, integrin subunit beta 2; MFI, mean fluorescence intensity.</p> Full article ">Figure 5
<p>The impact of <span class="html-italic">ITGB2-AS1</span> lncRNA deficiency on eosinophil degranulation and ROS production. (<b>A</b>–<b>C</b>) HL-60c15 cells differentiated for 6 days in the presence of sodium butyrate and IL-5 were primed with GM-CSF or IL-3 for 20 min and subsequently stimulated with C5a for 30 min at 37 °C. (<b>A</b>,<b>B</b>) Degranulation assays. (<b>A</b>) Flow cytometry. Following the aforementioned stimulation, eosinophil degranulation was assessed by measuring CD63 surface expression (<span class="html-italic">n</span> = 5). (<b>Right</b>) A representative histogram of flow cytometry data is shown for each condition. (<b>B</b>) EPX assay. Subsequent to the previously mentioned stimulation, the release of the eosinophil granule protein EPX into the supernatant was evaluated by determining EPX activity using the peroxidase substrate O-phenylenediamine (OPD) and measuring absorbance at 492 nm (<span class="html-italic">n</span> = 5). (<b>C</b>) ROS production. Following the above-mentioned stimulation, ROS production was assessed by measuring DHR123 fluorescence with a spectrofluorometer (<span class="html-italic">n</span> = 8). Values are means ± SEM. ns, not significant; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> &lt; 0.0001. Significances in black illustrate the significance of shControl cells compared with untreated shControl cells. Significances in green denote the significance of shITGB2-AS1 cells compared with untreated shITGB2-AS1 cells. Significances in red illustrate the significant difference between the shControl and shITGB2-AS1 cells for the same condition. Abbreviations: abs, absorbance; C5a, complement component 5a; EPX, eosinophil peroxidase; GM-CSF, granulocyte-macrophage colony-stimulating factor; DHR123, dihydrorhodamine 123; IL-3, interleukin 3; IL-5, interleukin 5; ITGB2-AS1, ITGB2 antisense RNA 1; MFI, mean fluorescence intensity; OPD, O-phenylenediamine; RFU, relative fluorescence units; ROS, reactive oxygen species.</p> Full article ">
26 pages, 752 KiB  
Review
MicroRNAs and RNA-Binding Protein-Based Regulation of Bone Metastasis from Hepatobiliary Cancers and Potential Therapeutic Strategies
by Sharmila Fagoonee and Ralf Weiskirchen
Cells 2024, 13(23), 1935; https://doi.org/10.3390/cells13231935 - 21 Nov 2024
Viewed by 212
Abstract
Hepatobiliary cancers, such as hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are among the deadliest malignancies worldwide, leading to a significant number of cancer-related deaths. While bone metastases from these cancers are rare, they are highly aggressive and linked to poor prognosis. This review [...] Read more.
Hepatobiliary cancers, such as hepatocellular carcinoma (HCC) and cholangiocarcinoma (CCA), are among the deadliest malignancies worldwide, leading to a significant number of cancer-related deaths. While bone metastases from these cancers are rare, they are highly aggressive and linked to poor prognosis. This review focuses on RNA-based molecular mechanisms that contribute to bone metastasis from hepatobiliary cancers. Specifically, the role of two key factors, microRNAs (miRNAs) and RNA-binding proteins (RBPs), which have not been extensively studied in the context of HCC and CCA, is discussed. These molecules often exhibit abnormal expression in hepatobiliary tumors, influencing cancer cell spread and metastasis by disrupting bone homeostasis, thereby aiding tumor cell migration and survival in the bone microenvironment. This review also discusses potential therapeutic strategies targeting these RNA-based pathways to reduce bone metastasis and improve patient outcomes. Further research is crucial for developing effective miRNA- and RBP-based diagnostic and prognostic biomarkers and treatments to prevent bone metastases in hepatobiliary cancers. Full article
(This article belongs to the Special Issue Molecular Mechanism of Bone Disease)
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<p>Most common functions of RBPs under physiological conditions or in cancer. In healthy cells, RBPs can post-transcriptionally regulate RNA metabolism, including alternative splicing, RNA modification, mRNA stability, and translation. This is represented in a simplified version in the figure. Under pathological conditions, increased expression of RBPs can lead to aberrant RNP formation through recruitment of oncogenic proteins, RBPs, and diverse RNA species, leading to dysregulated mRNA stability, translation, and alternative splicing, as well as alterations in cellular localizations of RNAs.</p> Full article ">
17 pages, 3224 KiB  
Article
Impact of Nannochloropsis oceanica and Chlorococcum amblystomatis Extracts on UVA-Irradiated on 3D Cultured Melanoma Cells: A Proteomic Insight
by Agnieszka Gęgotek, Tiago Conde, Maria Rosário Domingues, Pedro Domingues and Elżbieta Skrzydlewska
Cells 2024, 13(23), 1934; https://doi.org/10.3390/cells13231934 - 21 Nov 2024
Viewed by 245
Abstract
Melanoma is one of the most malignant forms of skin cancer, characterised by the highest mortality rate among affected patients. This study aims to analyse and compare the effects of lipid extracts from the microalgae Nannochloropsis oceanica (N.o.) and Chlorococcum amblystomatis [...] Read more.
Melanoma is one of the most malignant forms of skin cancer, characterised by the highest mortality rate among affected patients. This study aims to analyse and compare the effects of lipid extracts from the microalgae Nannochloropsis oceanica (N.o.) and Chlorococcum amblystomatis (C.a.) on the intra and extracellular proteome of UVA-irradiated melanoma cells using a three-dimensional model. Proteomic analysis revealed that UVA radiation significantly increases the levels of pro-inflammatory proteins in melanoma cells. Treatment with algae extracts reduced these protein levels in both non-irradiated and irradiated cells. Furthermore, untreated cells released proteins responsible for cell growth and proliferation into the medium, a process hindered by UVA radiation through the promotion of pro-inflammatory molecules secretion. The treatment with algae extracts effectively mitigated UVA-induced alterations. Notably, UVA radiation significantly induced the formation of 4-HNE and 15-PGJ2 protein adducts in both cells and the medium, while treatment with algae extracts stimulated the formation of 4-HNE-protein adducts and reduced the level of 15-PGJ2-protein adducts. However, both algae extracts successfully prevented these UVA-induced modifications. In conclusion, lipid extracts from N.o. and C.a. appear to be promising agents in supporting anti-melanoma therapy. However, their potent protective capacity may limit their applicability, particularly following cells exposure to UVA. Full article
(This article belongs to the Special Issue Melanoma: From Molecular Mechanisms to Therapeutic Opportunities—Series 2)
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<p>The diagram showing the course of the experiment.</p> Full article ">Figure 2
<p>The viability of control (Ctr) and UVA (18 J/cm<sup>2</sup>) irradiated melanoma cells treated with algae lipid extracts (3 ng/mL; <span class="html-italic">N.o.</span>, <span class="html-italic">Nannochloropsis oceanica</span>; <span class="html-italic">C.a.</span>, <span class="html-italic">Chlorococcum amblystomatis</span>) cultured in vitro in a three-dimensional (3D) model was measured using the MTT assay. The results are presented as mean values ± standard deviation (SD) with statistically significant differences (<span class="html-italic">p</span> &lt; 0.05) indicated as follows: x—vs. Ctr cells; a—vs. UVA irradiated cells; b—vs. <span class="html-italic">N.o.</span> non-irradiated/irradiated cells, respectively.</p> Full article ">Figure 3
<p>Principal component analysis (PCA) was performed to assess protein expression in control (Ctr) and UVA (18 J/cm<sup>2</sup>) irradiated melanoma cells treated with algae lipid extracts (3 ng/mL; <span class="html-italic">N.o.</span>, and <span class="html-italic">Nannochloropsis oceanica</span>; and <span class="html-italic">C.a.</span>, <span class="html-italic">Chlorococcum amblystomatis</span>) cultured in vitro in a three-dimensional (3D) model. The results obtained for cell lysates are shown in (<b>A</b>), and for FBS-free medium, labelled with “m”, in (<b>B</b>).</p> Full article ">Figure 4
<p>Heatmap and clustering of the top 16 proteins, with the lowest <span class="html-italic">p</span>-values, in control (Ctr) and UVA (18 J/cm<sup>2</sup>) irradiated melanoma cells treated with algae lipid extracts (3 ng/mL; <span class="html-italic">N.o.</span>, <span class="html-italic">Nannochloropsis oceanica</span>; and <span class="html-italic">C.a.</span>, <span class="html-italic">Chlorococcum amblystomatis</span>) cultured in vitro in a three-dimensional model (3D). Results are shown for cell lysates (<b>A</b>) and FBS-free medium (<b>B</b>). Protein abbreviations are as follows: ANGPTL, angiopoietin; APO, apolipoprotein; BDNF, brain-derived neurotrophic factor; CXCL1, growth-regulated alpha protein; DHX29, ATP-dependent RNA helicase; EGFR, epidermal growth factor receptor; FGF, fibroblast growth factor; Fox, forkhead box protein; FUBP1, Far upstream element-binding protein 1; HIF, hypoxia-inducible factor; IL, interleukin; KIF5B-ALK, tyrosine-protein kinase receptor; PABPC4, polyadenylate-binding protein 4; PDIA4, protein disulfide-isomerase A4; PGF, placenta growth factor; TGF, protransforming growth factor; TNF, tumour necrosis factor; VEGF, vascular endothelial growth factor; and ZFP, zinc finger protein.</p> Full article ">Figure 5
<p>Boxplots of the top 16 proteins, with the lowest <span class="html-italic">p</span>-values, in control (Ctr) and UVA (18 J/cm<sup>2</sup>)-irradiated melanoma cells treated with algae lipid extracts (3 ng/mL; <span class="html-italic">N.o.</span>, <span class="html-italic">Nannochloropsis oceanica</span>; and <span class="html-italic">C.a.</span>, <span class="html-italic">Chlorococcum amblystomatis</span>) cultured in vitro in a three-dimensional model (3D). Protein abbreviations are as follows: ANGPTL, angiopoietin; DHX29, ATP-dependent RNA helicase; Fox, forkhead box protein; HIF, hypoxia-inducible factor; KIF5B-ALK, tyrosine-protein kinase receptor; and PABPC4, polyadenylate-binding protein 4. Statistically significant differences are marked 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; ****, and <span class="html-italic">p</span> &lt; 0.0001.</p> Full article ">Figure 6
<p>Boxplots of the top 16 proteins, with the lowest <span class="html-italic">p</span>-values, in the medium in control (Ctr) and UVA (18 J/cm<sup>2</sup>)-irradiated melanoma cells treated with algae lipid extracts (3 ng/mL; <span class="html-italic">N.o.</span>, <span class="html-italic">Nannochloropsis oceanica</span>; and <span class="html-italic">C.a.</span>, <span class="html-italic">Chlorococcum amblystomatis</span>) cultured in vitro in a three-dimensional model (3D). Protein abbreviations are as follows: APO, apolipoprotein; BDNF, brain-derived neurotrophic factor; CXCL1, growth-regulated alpha protein; EGFR, epidermal growth factor receptor; FGF, fibroblast growth factor; FUBP1, Far upstream element-binding protein 1; IL, interleukin; PDIA4, protein disulfide-isomerase A4; PGF, placenta growth factor; TGF, protransforming growth factor; TNF, tumour necrosis factor; VEGF, vascular endothelial growth factor; and ZFP, zinc finger protein. Statistically significant differences are marked 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; ****, <span class="html-italic">p</span> &lt; 0.0001.</p> Full article ">Figure 7
<p>Total levels of protein modifications by lipid peroxidation products (4-hydroxynonenal (4-HNE) and 15-deoxy-12,14-prostaglandin J2 (15d-PGJ2)) in control (Ctr) and UVA (18 J/cm<sup>2</sup>) irradiated melanoma cells treated with algae lipid extracts (3 ng/mL; <span class="html-italic">N.o.</span>, <span class="html-italic">Nannochloropsis oceanica</span>; <span class="html-italic">C.a.</span>, <span class="html-italic">Chlorococcum amblystomatis</span>) cultured in vitro in a three-dimensional model (3D). Results were obtained for cell lysates (<b>A</b>) and FBS-free medium (<b>B</b>). Mean values ± SD are presented with statistically significant differences (<span class="html-italic">p</span> &lt; 0.05): x—vs. Ctr cells; a—vs. UVA irradiated cells; b—vs. <span class="html-italic">N.o.</span> non-irradiated/irradiated cells, respectively; and c—vs. non-irradiated, <span class="html-italic">N.o.</span>/<span class="html-italic">C.a.</span>-treated cells, respectively.</p> Full article ">
20 pages, 10684 KiB  
Article
Environmental Enrichment Attenuates Repetitive Behavior and Alters the Functional Connectivity of Pain and Sensory Pathways in C58 Mice
by Anna L. Farmer, Marcelo Febo, Bradley J. Wilkes and Mark H. Lewis
Cells 2024, 13(23), 1933; https://doi.org/10.3390/cells13231933 - 21 Nov 2024
Viewed by 228
Abstract
Restricted repetitive behaviors (RRB) encompass a variety of inflexible behaviors, which are diagnostic for autism spectrum disorder (ASD). Despite being requisite diagnostic criteria, the neurocircuitry of these behaviors remains poorly understood, limiting treatment development. Studies in translational animal models show environmental enrichment (EE) [...] Read more.
Restricted repetitive behaviors (RRB) encompass a variety of inflexible behaviors, which are diagnostic for autism spectrum disorder (ASD). Despite being requisite diagnostic criteria, the neurocircuitry of these behaviors remains poorly understood, limiting treatment development. Studies in translational animal models show environmental enrichment (EE) reduces the expression of RRB, although the underlying mechanisms are largely unknown. This study used functional magnetic resonance imaging to identify functional connectivity alterations associated with RRB and its attenuation by EE in C58 mice, an animal model of RRB. Extensive differences were observed between C58 mice and C57BL/6 control mice. Higher RRB was associated with altered connectivity between the somatosensory network and reticular thalamic nucleus and between striatal and sensory processing regions. Animals housed in EE displayed increased connectivity between the somatosensory network and the anterior pretectal nucleus and hippocampus, as well as reduced connectivity between the visual network and area prostriata. These results suggest aberrant sensory perception is associated with RRB in C58 mice. EE may reduce RRB by altering functional connectivity in pain and visual networks. This study raises questions about the role of sensory processing and pain in RRB development and identifies new potential intervention targets. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Autism Spectrum Disorder)
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<p>Resting state networks identified by independent component analysis of fMRI scans of C58 and C57 mice at 6 weeks post-weaning including scans from both sexes and housing treatments (n = 78). Networks shown in red to yellow with yellow indicating higher Z scores.</p> Full article ">Figure 2
<p>Resting state networks identified by independent component analysis of fMRI scans of C58 and C57 mice at 3 weeks post-weaning including scans from both sexes and housing treatments (n = 18). Networks shown in red to yellow with yellow indicating higher Z scores.</p> Full article ">Figure 3
<p>Brain regions with significant differences (FWE-corrected <span class="html-italic">p</span> &lt; 0.05) in functional connectivity between C58 and C57 mouse strains in the older 6-week post-weaning cohort. Red and orange areas indicate greater connectivity in C58 mice. Blue indicates decreased connectivity in C58 mice. APN = anterior pretectal nucleus. GRN = gigantocellular reticular nucleus.</p> Full article ">Figure 4
<p>Brain regions with a significant (FWE-corrected <span class="html-italic">p</span> &lt; 0.05) positive correlation between functional connectivity and repetitive motor behavior scores in the older 6-week post-weaning cohort.</p> Full article ">Figure 5
<p>Brain regions with a significant (FWE-corrected <span class="html-italic">p</span> &lt; 0.05) negative correlation between functional connectivity and repetitive motor scores in 3-week post-weaning C58 mice. Arrows indicate a small significant region in the right striatum in blue.</p> Full article ">Figure 6
<p>Significant differences (FWE-corrected <span class="html-italic">p</span> &lt; 0.05) in functional connectivity between mice housed in environmental enrichment (EE) versus standard housing (SH). Brain regions identified have significantly increased functional connectivity with the left somatosensory network in EE-housed mice in the older 6-week post-weaning cohort.</p> Full article ">Figure 7
<p>Nearly significant differences (FWE-corrected <span class="html-italic">p</span> &lt; 0.10) in functional connectivity between mice housed in environmental enrichment (EE) versus standard housing (SH). Brain regions identified have decreased functional connectivity with the caudal striatal network in EE-housed mice in the older 6-week post-weaning cohort.</p> Full article ">Figure 8
<p>Significant differences (FWE-corrected <span class="html-italic">p</span> &lt; 0.05) in functional connectivity between C58 mice at 3 weeks post-weaning housed in environmental enrichment (EE) versus standard housing (SH). Brain regions identified have significantly decreased functional connectivity with the left visual network in EE-housed C58 mice.</p> Full article ">
15 pages, 2925 KiB  
Article
Influence of Soft and Stiff Matrices on Cytotoxicity in Gingival Fibroblasts: Implications for Soft Tissue Biocompatibility
by Ye-Jin Yang, Dong-Hyeon Yeo, Seong-Jin Shin, Jun-Hee Lee and Jung-Hwan Lee
Cells 2024, 13(23), 1932; https://doi.org/10.3390/cells13231932 - 21 Nov 2024
Viewed by 170
Abstract
The biocompatibility of dental materials is critical for ensuring safety in clinical applications. However, standard in vitro cytotoxicity assays often rely on stiff tissue culture plastic (TCP), which does not accurately replicate the biomechanical properties of soft oral tissues. In this study, we [...] Read more.
The biocompatibility of dental materials is critical for ensuring safety in clinical applications. However, standard in vitro cytotoxicity assays often rely on stiff tissue culture plastic (TCP), which does not accurately replicate the biomechanical properties of soft oral tissues. In this study, we compared human gingival fibroblasts (HGFs) cultured on soft, gel-based substrates mimicking gingival tissue stiffness (0.2 kPa) with those cultured on conventional TCP (3 GPa) to assess the influence of substrate stiffness on the cytotoxicity of methyl methacrylate (MMA), as well as other cytotoxic agents, including DMSO and H2O2. The results demonstrated that cells cultured on softer substrates exhibited enhanced resistance to cytotoxic stress, with increased viability and decreased apoptosis and DNA damage following exposure to MMA, DMSO, and H2O2. Notably, HGFs on soft substrates showed significantly greater resilience to MMA-induced cytotoxicity compared to those cultured on TCP. These findings emphasize the critical role of substrate stiffness in modulating cellular responses to toxic agents and highlight the necessity of using physiologically relevant models for cytotoxicity testing of dental materials. This study provides valuable insights for improving biocompatibility assessment protocols in clinical settings. Full article
(This article belongs to the Special Issue Recent Advances in Regenerative Dentistry—Second Edition)
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Figure 1
<p>Schematic representation of substrate stiffness influencing MMA-induced cytotoxicity in HGFs. (<b>A</b>) This figure presents the effect of methyl methacrylate (MMA) on human gingival fibroblasts (HGFs) cultured on substrates of different stiffness (0.2 kPa and tissue culture plastic (TCP)). (<b>B</b>) MMA, a constituent of dental resins, generates toxic byproducts that impose cellular stress on gingival tissue. The schematic depicts a stiffness-dependent cytotoxic response, where increased substrate rigidity correlates with elevated cell death and DNA damage. Cells on the softer 0.2 kPa substrate exhibit reduced cytotoxicity compared to those on the stiffer TCP at MMA concentrations of 5 mM, 7.5 mM, and 10 mM.</p> Full article ">Figure 2
<p>Impact of dental material extracts on gingival tissue and cellular responses to substrates with different stiffnesses. (<b>A</b>) Schematic representation of the potential cytotoxic effects of dental material extracts on gingival tissue. While current ISO standards utilize TCP (stiff) for testing, dental materials in actual gingival environments interact with soft tissues. This image illustrates the hypothesis that the cytotoxicity of these extracts may differ in soft gingival conditions compared to standard stiff substrates. (<b>B</b>) Representative bright-field (top) and DAPI-stained fluorescent images (bottom) of human gingival fibroblasts (HGFs) cultured on 0.2 kPa and TCP (3 GPa) substrates and seeded at 11 × 10<sup>4</sup> cells/well and 5 × 10<sup>4</sup> cells/well, respectively. Scale bar = 100 μm. (<b>C</b>) Quantitative comparison of HGF counts on 0.2 kPa and TCP after 24 h incubation, showing minimal differences (n = 4). (<b>D</b>) Immunofluorescent staining of DAPI (blue) and F-actin (red) in HGFs on each substrate. Scale bar = 100 μm. (<b>E</b>) Quantitative analysis of F-actin area, intensity, circularity, and aspect ratio. Cells on 0.2 kPa showed smaller areas, decreased intensity, and a more rounded morphology compared to TCP (n = 30). Data are mean ± SD from three independent experiments. Statistical significance was determined by Student’s <span class="html-italic">t-</span>test (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001).</p> Full article ">Figure 3
<p>Effects of DMSO-induced cytotoxicity on HGFs cultured on 0.2 kPa and TCP. (<b>A</b>) Experimental workflow schematic for assessing DMSO cytotoxicity. DMSO, an organic solvent used to dissolve polar and non-polar compounds, serves as a standard cytotoxicity agent. HGFs were seeded for 24 h, starved for 12 h, then treated with varying DMSO concentrations. (<b>B</b>) Cell viability measured with Cell Counting Kit-8 (CCK-8) showed significantly higher viability at 10% DMSO on 0.2 kPa than on TCP. (<b>C</b>) Flow cytometry analysis displaying live, apoptotic, and necrotic cells after 5% and 10% DMSO treatment on both substrates. (<b>D</b>) Quantification of cell death distribution; live cell proportion was higher on 0.2 kPa, while apoptotic cells were more prevalent on TCP. Representative data sets after three independent experiments are shown. Statistical significance was determined by two-way analysis of variance (ANOVA) with Tukey’s post hoc test for multiple comparison (**** <span class="html-italic">p</span> &lt; 0.0001).</p> Full article ">Figure 4
<p>Effects of H<sub>2</sub>O<sub>2</sub>-induced oxidative stress on HGFs cultured on 0.2 kPa and TCP. (<b>A</b>) Schematic of the experimental design highlighting the role of reactive oxygen species (ROS) in periodontal disease, implants, and infections. Human gingival fibroblasts (HGFs) were seeded for 24 h on 0.2 kPa and TCP, starved for 12 h, and treated with hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>). (<b>B</b>) Cell viability after treatment with 300 µM and 400 µM H<sub>2</sub>O<sub>2</sub> on both substrates, measured with Cell Counting Kit-8 (CCK-8), showing minimal differences. (<b>C</b>) Flow cytometry displaying the distribution of live, apoptotic, and necrotic cells after H<sub>2</sub>O<sub>2</sub> treatment. (<b>D</b>) Quantification of cell death distribution; live cells and early apoptosis were higher on 0.2 kPa, while late apoptosis and necrosis were more pronounced on TCP. Representative data sets from three independent experiments are shown in the manuscript.</p> Full article ">Figure 5
<p>Effects of MMA on HGFs cultured on 0.2 kPa and TCP. (<b>A</b>) Immunofluorescence images of DAPI (blue) and F-actin (red)-stained HGFs treated with 5 mM, 7.5 mM, and 10 mM MMA for 12 h, showing cell morphology differences between 0.2 kPa and TCP substrates. Scale bar = 100 µm. (<b>B</b>) Cell viability after MMA treatment, indicating a significant reduction in TCP compared to 0.2 kPa at higher MMA concentrations (n = 5). (<b>C</b>) Quantification of cell area and circularity, showing a smaller cell area and more spreading on 0.2 kPa (n = 90). (<b>D</b>) Immunofluorescence staining for γH2AX (green) and DAPI (blue) showing DNA damage; TCP cells exhibited higher γH2AX levels. Scale bar = 100 µm. (<b>E</b>) Flow cytometry analysis of apoptosis and necrosis following MMA treatment, with higher apoptotic/necrotic populations on TCP. (<b>F</b>) Quantification of apoptotic and necrotic cells, with apoptosis and necrosis increasing at higher MMA concentrations, particularly on TCP. Representative data sets after three independent experiments are shown. Statistical significance was determined by two-way ANOVA followed by Tukey’s multiple comparison test (ns = non-significant, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001).</p> Full article ">Figure 6
<p>Schematic overview of surface stiffness and cytotoxicity effects of MMA on gingival tissue. Dental resin materials containing methyl methacrylate (MMA) can release toxic substances, leading to gingival irritation and inflammation. This figure illustrates the relationship between surface stiffness and cytotoxicity in human gingival fibroblasts (HGF) exposed to increasing concentrations of MMA (5 mM, 7.5 mM, 10 mM) on 0.2 kPa and TCP substrates. As surface stiffness increases, cytotoxicity is elevated, suggesting a stiffness-dependent cytotoxic response to MMA exposure.</p> Full article ">
31 pages, 12498 KiB  
Review
Using Small Molecules to Reprogram RPE Cells in Regenerative Medicine for Degenerative Eye Disease
by Lyubov A. Rzhanova, Elena V. Alpeeva and Maria A. Aleksandrova
Cells 2024, 13(23), 1931; https://doi.org/10.3390/cells13231931 - 21 Nov 2024
Viewed by 179
Abstract
The main purpose of regenerative medicine for degenerative eye diseases is to create cells to replace lost or damaged ones. Due to their anatomical, genetic, and epigenetic features, characteristics of origin, evolutionary inheritance, capacity for dedifferentiation, proliferation, and plasticity, mammalian and human RPE [...] Read more.
The main purpose of regenerative medicine for degenerative eye diseases is to create cells to replace lost or damaged ones. Due to their anatomical, genetic, and epigenetic features, characteristics of origin, evolutionary inheritance, capacity for dedifferentiation, proliferation, and plasticity, mammalian and human RPE cells are of great interest as endogenous sources of new photoreceptors and other neurons for the degrading retina. Promising methods for the reprogramming of RPE cells into retinal cells include genetic methods and chemical methods under the influence of certain low-molecular-weight compounds, so-called small molecules. Depending on the goal, which can be the preservation or the replacement of lost RPE cells and cellular structures, various small molecules are used to influence certain biological processes at different levels of cellular regulation. This review discusses the potential of the chemical reprogramming of RPE cells in comparison with other somatic cells and induced pluripotent stem cells (iPSCs) into neural cells of the brain and retina. Possible mechanisms of the chemically induced reprogramming of somatic cells under the influence of small molecules are explored and compared. This review also considers other possibilities in using them in the treatment of retinal degenerative diseases based on the protection, preservation, and support of survived RPE and retinal cells. Full article
(This article belongs to the Special Issue Mechanism of Cell Signaling during Eye Development and Diseases)
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Figure 1

Figure 1
<p>Eye injury induces different RPE responses in lower vertebrates and mammals, including humans. The initial stages of cellular reprogramming are the same in all studied organisms: cells enter the cell cycle, begin to proliferate, lose pigment, and dedifferentiate. However, subsequently, the cells develop completely differently: in some species, RPE cells are transformed into neuronal retinal cells, thereby restoring the retina, while in humans, dedifferentiated RPE cells differentiate into myofibroblasts, which leads to serious pathologies.</p> Full article ">Figure 2
<p>Some small molecules and signaling pathways promoting the development of the nervous system (based on the poster <a href="https://www.stemcell.com/media/files/wallchart/WA10014-Small_Molecules_Big_Impact.pdf" target="_blank">https://www.stemcell.com/media/files/wallchart/WA10014-Small_Molecules_Big_Impact.pdf</a> (accessed on 16 November 2024)). Notes: The transforming growth factor β (TGFβ) is involved in a whole range of biological functions, from cell growth to cell differentiation and apoptosis. SMAD1, 2, 3, 5, and 8 are receptor-regulated SMADs. They bind to membrane-bound serine/threonine receptors and are activated by the kinase activity of the receptors. SMAD4 acts as a cofactor that binds to activated R-SMADS (SMADs) forming a complex that translocates into the nucleus [<a href="#B63-cells-13-01931" class="html-bibr">63</a>]. Pathway inhibitors: SB431542, LY364947, RepSox, Dorsomorphin, LDN193189. The Notch signaling pathway regulates cell proliferation, cell fate, differentiation, and cell death in all metazoans. The Notch pathway is activated when Delta or Jagged ligands on neighboring cells activate cleavage of the receptor releasing the Notch intracellular domain (NICD). The Notch pathway plays a role in specifying neural subtypes [<a href="#B64-cells-13-01931" class="html-bibr">64</a>]. Pathway inhibitors: DAPT, LY411575. Fibroblast growth factor (FGF) signaling regulates several developmental processes, including cellular proliferation, differentiation, migration, morphogenesis, and patterning. FGF signaling via MEK/ERK is critical for self-renewal and proliferation of human PSCs [<a href="#B65-cells-13-01931" class="html-bibr">65</a>]. The WNT signaling pathway is an ancient and evolutionarily conserved pathway that regulates crucial aspects of cell fate determination, cell migration, cell polarity, neural patterning, and organogenesis during embryonic development [<a href="#B66-cells-13-01931" class="html-bibr">66</a>]. Pathway activators: CHIR99021, SB216763; pathway inhibitors: IWR-1-endo. The Hedgehog (Shh) pathway is important in post-embryonic tissue regeneration and repair processes. Specifically, Shh signaling is implicated in the induction of multifarious neuronal populations in central nervous system [<a href="#B67-cells-13-01931" class="html-bibr">67</a>]. Pathway activators: Purmorphamine, SAg. The RHO/ROCK pathway regulates cytoskeletal dynamics and plays an important role in cell adhesion, proliferation, motility, contraction, and apoptosis. Loss of cadherin or integrin binding activates the Rho pathway in human PSCs, leading to anoikis [<a href="#B68-cells-13-01931" class="html-bibr">68</a>]. Pathway inhibitors: Y-27632, thiazovivin. The 3′,5′-cyclic adenosine monophosphate (cAMP) is a second messenger important in reprogramming and differentiation for many cell subtypes [<a href="#B69-cells-13-01931" class="html-bibr">69</a>]. Pathway activator: forskolin. The protein kinase C (PKC) family of kinases is commonly activated by diacylglycerol (DAG) and calcium and is involved in several signaling pathways that can regulate differentiation [<a href="#B70-cells-13-01931" class="html-bibr">70</a>]. Pathway activators: prostaglandin E2, (−)-Indolactam V; pathway inhibitors: HA-100, GO6983. Retinoic acid (RA) is a potent morphogen required for embryonic development. RA acts in a paracrine fashion to shape the developing eye and is essential for normal optic vesicle and anterior segment formation [<a href="#B71-cells-13-01931" class="html-bibr">71</a>]. Activators: 9-cis retinoic acid, all-trans retinoic acid, CD437, TTNPB. RAR, RXR -RA receptors. Epigenetic marks such as acetylation (Ac) of histones and methylation (Me) of histones or DNA serve to induce or inhibit gene expression in a heritable manner. Global changes in epigenetic marks are critical for reprogramming [<a href="#B35-cells-13-01931" class="html-bibr">35</a>]. DNA Methyltransferase inhibitors: RG108; histone methyltransferase inhibitors: BIX01294; histone demethylase inhibitors: tranylcypromine; histone acetyltransferase inhibitors: garcinol; histone deacetylase inhibitors: sodium butyrate, trichostatin A, valproic acid.</p> Full article ">Figure 3
<p>Schematic representation of chemically induced reprogramming of fibroblasts into neural stem cells and into neurons in the brain and retina [<a href="#B12-cells-13-01931" class="html-bibr">12</a>,<a href="#B36-cells-13-01931" class="html-bibr">36</a>,<a href="#B37-cells-13-01931" class="html-bibr">37</a>,<a href="#B39-cells-13-01931" class="html-bibr">39</a>,<a href="#B41-cells-13-01931" class="html-bibr">41</a>,<a href="#B42-cells-13-01931" class="html-bibr">42</a>,<a href="#B43-cells-13-01931" class="html-bibr">43</a>,<a href="#B85-cells-13-01931" class="html-bibr">85</a>,<a href="#B86-cells-13-01931" class="html-bibr">86</a>]. This approach utilized small molecules that acted on the cellular epigenome (Epi) and on various signaling pathways that control cellular identity (TGFβ, GSK3β, PKC, BMP, SHH, JNR, ROCK, and others). FG—growth factor; m—mouse; h—human; CiNs—chemically induced neurons; CiNSCs—chemically induced neural stem cells; CiPCs—chemically induced photoreceptor-like cells; m rd1—mouse model of retinal degeneration; m NaIO<sub>3</sub>—mouse model of sodium iodate (NaIO<sub>3</sub>)-induced retinal degeneration; SRT—subretinal transplantation, LVT—lateral ventricle transplantation. Pathway activators: green color; pathway inhibitors: red color.</p> Full article ">Figure 4
<p>Schematic representation of chemically induced reprogramming of astrocytes into neural stem cells and into neurons in the brain and retina [<a href="#B34-cells-13-01931" class="html-bibr">34</a>,<a href="#B38-cells-13-01931" class="html-bibr">38</a>,<a href="#B50-cells-13-01931" class="html-bibr">50</a>,<a href="#B87-cells-13-01931" class="html-bibr">87</a>,<a href="#B88-cells-13-01931" class="html-bibr">88</a>,<a href="#B89-cells-13-01931" class="html-bibr">89</a>,<a href="#B90-cells-13-01931" class="html-bibr">90</a>,<a href="#B91-cells-13-01931" class="html-bibr">91</a>,<a href="#B92-cells-13-01931" class="html-bibr">92</a>]. Chemically induced reprogramming utilized small molecules that acted on the cellular epigenome (Epi) and on various signaling pathways that control cellular identity (TGFβ, GSK3β, PKC, SHH, Notch, RAR, ROCK, and others). FG—growth factor; m—mouse; nm—neonatal mouse; h—human; r—rat; CiNs—chemically induced neurons; CiNSCs—chemically induced neural stem cells; CRI—microinjection into the cortices; STI—microinjection into the striatum; LVT—lateral ventricle transplantation. Pathway activators: green color; pathway inhibitors: red color.</p> Full article ">Figure 5
<p>Schematic representation of chemically induced reprogramming of ESCs and iPSCs into neural stem cells and into neurons of the brain and retina [<a href="#B2-cells-13-01931" class="html-bibr">2</a>,<a href="#B47-cells-13-01931" class="html-bibr">47</a>,<a href="#B52-cells-13-01931" class="html-bibr">52</a>,<a href="#B54-cells-13-01931" class="html-bibr">54</a>,<a href="#B97-cells-13-01931" class="html-bibr">97</a>,<a href="#B98-cells-13-01931" class="html-bibr">98</a>,<a href="#B99-cells-13-01931" class="html-bibr">99</a>]. Chemically induced reprogramming utilized small molecules that acted on the cellular epigenome (Epi) and on various signaling pathways that control cellular identity (TGFβ, GSK3β, WNT, BMP, NOTCH, ROCK, and others). GF—growth factor; iPSC—induced pluripotent stem cell; ESCs—embryonic stem cells; RSCs—retinal stem cell; CiRGCs—chemically induced retinal ganglion cells; CiR—chemically induced retina; CiROD—chemically induced rods; CiRPE—chemically induced retinal pigment epithelium; CiPCs—chemically induced photoreceptor-like cells; m NOD-SCID—the nonobese diabetic/severe combined immunodeficient mouse; m Crx<sup>tvrm65</sup>/IL2rγ<sup>−/−</sup>—model of immunosuppressive mouse/retinal degeneration; m NOD.SCID-rd1—the nonobese diabetic/severe combined immunodeficient mouse model of retinal degeneration; RCS rat—rat model of retinal degeneration from Royal College of Surgeons; IVT—intravitreal injection; SRT—subretinal injection; mMNU—mouse model of N-Nitroso-N-methylurea (MNU)-induced retinal degeneration, m—mouse, h—human. Pathway activators: green color; pathway inhibitors: red color. 2.3.4. Reprogramming of the RPE into CiNSCs and CiNs.</p> Full article ">Figure 6
<p>Schematic representation of chemically induced reprogramming of RPE into neural stem cells and into neurons in the brain and retina [<a href="#B12-cells-13-01931" class="html-bibr">12</a>,<a href="#B27-cells-13-01931" class="html-bibr">27</a>,<a href="#B46-cells-13-01931" class="html-bibr">46</a>,<a href="#B93-cells-13-01931" class="html-bibr">93</a>]. Chemically induced reprogramming utilized small molecules that acted on the cellular epigenome (Epi) and on various signaling pathways that control cellular identity (TGFβ, GSK3β, WNT, BMP, NOTCH, PKC, and others). Fh—fetal human; Mn—cynomolgus monkeys (<span class="html-italic">Macaca fascicularis</span>); MPTP hydrochloride—induced Parkinson’s disease model; PPI—implantation into posterior putamen; sphere—free floating conditions; for other abbreviations, refer to <a href="#cells-13-01931-f003" class="html-fig">Figure 3</a> and <a href="#cells-13-01931-f005" class="html-fig">Figure 5</a>. Pathway activators: green color; pathway inhibitors: red color.</p> Full article ">
17 pages, 6700 KiB  
Article
The Role of Plzf in Spermatogonial Stem Cell Maintenance and Differentiation: Mapping the Transcriptional Dynamics and Key Interactions
by Nima Ghasemi, Hossein Azizi, Seyedeh-Kiana Razavi-Amoli and Thomas Skutella
Cells 2024, 13(23), 1930; https://doi.org/10.3390/cells13231930 - 21 Nov 2024
Viewed by 222
Abstract
Spermatogonial stem cells (SSCs) sustain and modulate spermatogenesis through intricate signaling pathways and transcription factors. Promyelocytic leukemia zinc-finger (Plzf, also known as Zbtb16) has been identified as a critical transcription factor influencing various signaling and differentiation pathways. Plzf plays a [...] Read more.
Spermatogonial stem cells (SSCs) sustain and modulate spermatogenesis through intricate signaling pathways and transcription factors. Promyelocytic leukemia zinc-finger (Plzf, also known as Zbtb16) has been identified as a critical transcription factor influencing various signaling and differentiation pathways. Plzf plays a pivotal role in regulating the differentiation properties of SSCs and is essential for the proper maintenance of spermatogenesis. However, the transcription patterns of Plzf along the seminiferous tubules and its interaction network with adjacent partners still need to be fully elucidated. This study employed immunostaining techniques coupled with Fluidigm quantitative real-time polymerase chain reaction (Fluidigm qPCR) to quantify Plzf expression in undifferentiated and differentiated spermatogonia. Furthermore, we utilized bioinformatics analyses to identify Plzf partners and their associations with other regulatory factors. Immunohistostaining (IMH) revealed a high expression of Plzf in cells near the basal membrane of seminiferous tubules and a lower expression in the middle regions in vivo. Immunocytochemistry (ICC) demonstrated that undifferentiated spermatogonia exhibited significant Plzf positivity, whereas differentiated spermatogonia showed reduced Plzf expression in vitro. Fluidigm qPCR confirmed a significant differential expression of Plzf between undifferentiated and differentiated spermatogonia. In silico differential expression analysis between undifferentiated spermatogonia and spermatids indicated that Plzf is closely associated with Mycn, Lin28a, Kras, Ccnd1, and Jak1, highlighting the importance of these partnerships during spermatogenesis. Our findings suggest that the network of Plzf-related partners and their associated proteins involves differentiation, localization, apoptosis, and signal transduction. This comprehensive approach advances our understanding of Plzf transcription patterns and sheds light on its interactions with other cellular factors, revealing previously obscure pathways and interactions. These insights could lead to more effective diagnostic strategies for reproductive system-related diseases and inform the development of improved therapeutic and clinical applications. Full article
(This article belongs to the Special Issue Advance in Spermatogenesis)
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Figure 1
<p>(<b>A1</b>–<b>A4</b>) The immunohistochemistry image of seminiferous tubules stained for PLZF reveals a distinct population of cells located near the basal membrane—identified as undifferentiated spermatogonia—that are positive for PLZF. In contrast, other cell types within the tubules do not express Plzf. (Scale bar = 50 µm).</p> Full article ">Figure 2
<p>Immunohistochemistry (IHC) analysis of testis cross-sections reveals that VASA-positive cells do not express <span class="html-italic">Plzf</span> (<b>A1</b>–<b>A4</b>). Among the VASA-positive population, a subset shows positivity for nMYC. In contrast, another group of VASA-positive cells located near the basal membrane of the seminiferous tubules remains negative for nMYC (<b>B1</b>–<b>B4</b>). In contrast, the more differentiated cell tubules near the tubules’ luminal region with more advanced differentiation status are negative for VASA, NMYC, and PLZF. Partial tubule images were used to highlight specific structures and the intense staining in the interstitial regions is likely due to autofluorescence (Scale bar = 50 µm).</p> Full article ">Figure 3
<p>Immunocytochemistry (ICC) reveals the expression of <span class="html-italic">Plzf</span>, <span class="html-italic">Vasa</span>, and <span class="html-italic">nMyc</span> (green or red) with DAPI nuclear counterstain (blue) in undifferentiated (left panel) and differentiated (right panel) spermatogonia. Plzf and Vasa show robust expression in undifferentiated spermatogonia, significantly diminishing upon differentiation. nMYC, on the other hand, demonstrates prominent nuclear localization in differentiated spermatogonia, while its nuclear expression remains relatively low in undifferentiating spermatogonia. The merged images display the colocalization of these gene markers with nuclear staining. (Scale bar = 50 µm (All images except nMYC in differentiated spermatogonia (Scale bar = 100 µm)).</p> Full article ">Figure 4
<p>The results of the Fluidigm qPCR analysis display the fold change in mRNA expression (<span class="html-italic">Y</span>-axis) on a logarithmic scale (Base 10). The “Sig*” symbol indicates a statistically significant difference in gene expression (<span class="html-italic">p</span> &lt; 0.05) for the analyzed genes. The analysis revealed significantly different mRNA expression levels of <span class="html-italic">Vasa</span> and <span class="html-italic">Plzf</span> in undifferentiated spermatogonia compared to differentiating, underscoring their roles in spermatogenesis.</p> Full article ">Figure 5
<p>This composite figure presents key SSCs and spermatids. (<b>A</b>) The volcano plot shows differentially expressed genes between SSCs and spermatids. Genes with significant upregulation in SSCs are highlighted in green, while those upregulated in spermatids are red. <span class="html-italic">Plzf</span>, a key transcription factor in SSC maintenance, is specifically labeled. (<b>B</b>) The heatmap illustrates the hierarchical clustering of gene expression across SSC and spermatid samples, with distinct clusters of upregulated and downregulated genes in both cell types. The color scale represents expression levels, from low (green) to high (red). (<b>C1</b>,<b>C2</b>) Electron microscopy images show the ultrastructure of undifferentiated spermatogonia (<b>C1</b>) and differentiating spermatogonia (<b>C2</b>), highlighting their morphological differences (Scale bar = 2 µm).</p> Full article ">Figure 6
<p>The diagram depicts a protein interaction network for ZBTB16 (PLZF), highlighting its role in spermatogenesis. The red node at the top represents ZBTB16 (PLZF). Direct interactors, indicated by green diamond-shaped nodes, include key proteins such as PTPRC, LIN28A, NCOR2, and others involved in stem cell regulation and differentiation. The yellow rectangular nodes represent the second interactors of ZBTB16, forming an extended network of downstream interactions. The connections suggest a complex.</p> Full article ">Figure 7
<p>The network diagram illustrates the PPI network centered around ZBTB16 (PLZF), shown at the top, and its hierarchical interactors. The three layers (labeled 1, 2, and 3) represent primary, secondary, and tertiary interactors of ZBTB16, respectively. Each node represents a protein, with the multicolored sectors indicating enrichment analysis results based on the legend below the figure. The edges between nodes indicate predicted interactions between proteins, with a dense network of interconnections suggesting complex regulatory relationships. The color legend at the bottom provides functional context for each protein based on specific biological processes such as signal transduction, chromatin organization, transcription regulation, and others, highlighting the diverse roles of proteins interacting with ZBTB16 in stem cells.</p> Full article ">
24 pages, 13352 KiB  
Article
A Dual Role of the Senescence Marker P16Ink4a in Liver Endothelial Cell Function
by Kay-Dietrich Wagner, Hasan Safwan-Zaiter and Nicole Wagner
Cells 2024, 13(23), 1929; https://doi.org/10.3390/cells13231929 - 21 Nov 2024
Viewed by 336
Abstract
P16Ink4a is a well-established marker of senescence. Although P16Ink4a is expressed in endothelial cells, little is known about its function in these cells. Using isolated liver endothelial cells with silencing or overexpression of P16Ink4a, we show here that dependent on P16Ink4a levels, different [...] Read more.
P16Ink4a is a well-established marker of senescence. Although P16Ink4a is expressed in endothelial cells, little is known about its function in these cells. Using isolated liver endothelial cells with silencing or overexpression of P16Ink4a, we show here that dependent on P16Ink4a levels, different pathways and functions are affected. High levels of P16Ink4a reduce proliferation and induce senescence, while low levels have the opposite effects. Only high P16Ink4a expression reduces in vitro angiogenesis. Expression profiling reveals an inflammatory phenotype upon silencing of P16Ink4a, while P16Ink4a overexpression is associated with a profile associated with DNA damage, repair and senescence. Low levels of P16Ink4a induce reactive oxygen species (ROS) generation and increase endothelial cell leakage. Collectively, P16Ink4a represents an “antagonistic pleiotropy” gene, which is, on the one hand, required to prevent ROS generation and endothelial damage and, on the other hand, inhibits angiogenesis through induction of senescence at high levels. Full article
(This article belongs to the Section Cells of the Cardiovascular System)
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<p>Liver vascular Cd31+ and Cd146+ cells express comparable levels of P16Ink4a. (<b>a</b>) Quantitative RT-PCRs for <span class="html-italic">p16Ink4a</span> of sorted liver endothelial Cd31+ and Cd146+ cells at 3 months of age of the mice. Expression of <span class="html-italic">p16Ink4a</span> was normalized to the respective means of <span class="html-italic">Gapdh</span>, <span class="html-italic">actin</span>, and <span class="html-italic">Rplp0</span> expression. Data are mean ± SEM (<span class="html-italic">n</span> = 4 each). Symbols indicate individual values. (<b>b</b>) Western blot for P16Ink4a in isolated Cd31+ and Cd146+ liver endothelial cell populations from 3-month-old mice. β-actin served as standard (left panel) and relative quantification of the Western blot bands (right panel graph). Data are mean ± SEM (<span class="html-italic">n</span> = 3 each). Symbols indicate individual values.</p> Full article ">Figure 2
<p>Lentiviral transduction with small hairpin RNA (shRNA) or P16Ink4a overexpression constructs (P16) efficiently modifies P16Ink4a expression levels in Cd31+ and Cd146+ liver endothelial cells. Quantitative RT-PCRs for P16Ink4a of Cd31- (<b>a</b>,<b>b</b>) and Cd146- (<b>d</b>,<b>e</b>) sorted liver endothelial cells. RNA was extracted one week after lentiviral transduction. Expression of P16Ink4a was normalized to the respective mean of Gapdh, actin, and Rplp0 expression. The average of the non-coding small hairpin construct (nc shRNA) transduced cells was calculated and set to 1. Individual samples of non-coding construct transduced or P16 small hairpin (P16 shRNA) transduced cells were then normalized against this average value (<b>a</b>,<b>d</b>). For the overexpression experiments, the average of the empty vector transduced cells was calculated and set to 1. All samples of empty vector transduced or P16 overexpression construct transduced cells were then normalized against this average value (<b>b</b>,<b>e</b>). Data are mean ± SEM (<span class="html-italic">n</span> = 10 each). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. Symbols indicate individual values. Western blot for P16Ink4a in Cd31+ (<b>c</b>) and Cd146+ (<b>f</b>) liver endothelial cells transduced with a P16 small hairpin construct (P16 shRNA) and the respective non-coding control (nc shRNA) or with a P16Ink4a overexpression construct (P16) and the corresponding empty vector control. Tubulin served as standard. Note that the P16 overexpression construct is a fusion between the P16Ink4a cDNA and green fluorescent protein (GFP) resulting in a band at the expected size of 43 kDa.</p> Full article ">Figure 3
<p>SA-β-galactosidase staining of Cd31+ and Cd146+ liver endothelial cell populations with modified P16Ink4a expression as marker for senescence. Cd31+ cells were transduced with lentiviral particles containing non-coding small hairpin constructs (nc shRNA, (<b>a</b>)), P16Ink4a silencing plasmids (P16 shRNA, (<b>b</b>)), empty vector controls (<b>c</b>) for the P16Ink4a overexpression construct (P16, (<b>d</b>)). Quantification of the number of SA-β-galactosidase positive Cd31+ cells with silencing of P16Ink4a compared to the non-coding control (<b>e</b>) and overexpression of P16Ink4a compared to the corresponding empty vector control (<b>f</b>). Representative SA-β-galactosidase staining of Cd146+ cells transduced with non-coding control constructs (<b>g</b>), P16Ink4a small hairpin silencing plasmids (<b>h</b>), empty vector controls (<b>i</b>) corresponding to the P16Ink4a overexpression construct (<b>j</b>). Quantification of the number of SA-β-galactosidase positive Cd146+ cells with silencing of P16Ink4a compared to the non-coding control (<b>k</b>) and overexpression of P16Ink4a compared to the corresponding empty vector control (<b>l</b>). Scale bars represent 50 µm. Data are mean ± SEM (<span class="html-italic">n</span> = 6, each). Symbols indicate individual values. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> ˂ 0.01; *** <span class="html-italic">p</span> ˂ 0.001.</p> Full article ">Figure 4
<p>Modification of P16Ink4a levels alters proliferation of liver endothelial cells. Cd31+ were transduced with lentiviral particles containing non-coding small hairpin constructs (nc shRNA) or P16Ink4a silencing plasmids (P16 shRNA) (<b>a</b>), or empty vector controls (empty vector) and a P16Ink4a overexpression construct (P16) (<b>b</b>). A total of 5 × 10<sup>3</sup> cells were seeded in 96-well plates and the cells counted daily for two weeks to establish the cell growth curves. (<span class="html-italic">n</span> = 12, each). BrdU incorporation was measured after one week of the cell transduction as independent measure for cell proliferation in Cd31+ cells with silencing of P16Ink4a compared to the respective control (<b>c</b>) and in cells with P16Ink4a overexpression compared to the corresponding empty vector controls (<b>d</b>) (<span class="html-italic">n</span> = 18, each). Growth curves of Cd146+ cells with silencing (<b>e</b>) or overexpression (<b>f</b>) of P16Ink4a (<span class="html-italic">n</span> = 12, each). Cells were subjected to the same experimental conditions as for the Cd31+ cells. BrdU incorporation in Cd146+ cells with silencing of P16Ink4a compared to the respective control (<b>g</b>) and in cells with P16Ink4a overexpression compared to the corresponding empty vector controls (<b>h</b>) (<span class="html-italic">n</span> = 18, each). Data are mean ± SEM. Symbols indicate individual values. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> ˂ 0.01; *** <span class="html-italic">p</span> ˂ 0.001.</p> Full article ">Figure 5
<p>Migration of liver endothelial cells is affected by P16Ink4a. Representative photomicrographs of DAPI-stained Cd31 cells migrated through Transwell membranes. Cells transduced with non-coding small hairpin plasmids (nc shRNA) served as control (<b>a</b>) for P16Ink4a silencing plasmid (P16 shRNA) transduced cells (<b>b</b>). Empty vector controls (<b>c</b>) were compared to cells with overexpression of P16Ink4a (P16) (<b>d</b>). Quantification of the number of migrated cells with silencing of P16Ink4a (<b>e</b>) and with overexpression of P16Ink4a (<b>f</b>) compared to the respective controls. The same experimental approach was repeated with Cd146+ cells including nc shRNA (<b>g</b>), P16 shRNA (<b>h</b>), empty vector controls (<b>i</b>), and overexpression of P16Ink4a (<b>j</b>). Quantification of the number of migrated cells was repeated for Cd146+ cells with silencing (<b>k</b>) or overexpression of P16Ink4a (<b>l</b>) compared to the respective controls. Scale bars represent 50 µm. (<span class="html-italic">n</span> = 6, each). Data are mean ± SEM. Symbols indicate individual values. * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> ˂ 0.001. Note that although Cd146+ cells migrate less compared to CD31+ cells, P16Ink4a overexpression significantly inhibits endothelial cell passage through the Transwell membranes in both cell populations.</p> Full article ">Figure 6
<p>High P16Ink4a reduces in vitro angiogenesis of Cd31+ and Cd146+ liver endothelial cells. Matrigel tube formation assays as in vitro measure for angiogenesis. Branching points (<b>a</b>), number of branches (<b>b</b>), and total branch length (<b>c</b>) were quantified in Cd31+ cells with silencing of P16Ink4a (p16 shRNA) in comparison to the respective controls (nc shRNA). Representative photomicrographs of control endothelial tubes (<b>d</b>) and endothelial cells with silencing of P16Ink4a (<b>e</b>). Quantification of branching points (<b>f</b>), number of branches (<b>g</b>), and total branch length (<b>h</b>) of endothelial tubes formed from Cd31+ cells with overexpression of P16Ink4a (P16) and the respective controls (empty vector). Photomicrographs of empty vector transduced control Cd31+ cells (<b>i</b>) and cells with overexpression of P16Ink4a (<b>j</b>). Quantification of branching points (<b>k</b>), number of branches (<b>l</b>), and total branch length (<b>m</b>) of endothelial tubes formed from Cd146+ cells with silencing of P16Ink4a (p16 shRNA) in comparison to the respective controls (nc shRNA). Photomicrographs of Cd146+ control endothelial tubes (<b>n</b>) and endothelial cells with silencing of P16Ink4a (<b>o</b>). Quantification of branching points (<b>p</b>), number of branches (<b>q</b>), and total branch length (<b>r</b>) of endothelial tubes formed from Cd146+ cells’ overexpression of P16Ink4a (P16) and the respective controls (empty vector). Photomicrographs of empty vector transduced control Cd146+ cells (<b>s</b>) and cells with overexpression of P16Ink4a (<b>t</b>). Scale bars represent 50 µm. (<span class="html-italic">n</span> = 6, each). Data are mean ± SEM. Symbols indicate individual values. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> ˂ 0.001.</p> Full article ">Figure 7
<p>RNA sequencing analysis of Cd31+ (<b>a</b>–<b>d</b>) and Cd146+ (<b>e</b>–<b>h</b>) cells with modification of P16Ink4a expression levels (<span class="html-italic">n</span> = 3 each) corroborates the dual function of P16Ink4a in endothelial cells. Cells were transduced with lentiviral particles containing either P16 small hairpin (P16 shRNA) or overexpression constructs (P16) and the respective controls (nc shRNA, empty vector). (<b>a</b>) Volcano plot analysis of differentially expressed genes in Cd31+ cells with silencing of P16Ink4a (Cd31sh) compared to the respective controls (Cd31nc). (<b>b</b>) Volcano plot of differentially expressed genes in Cd31+ cells with overexpression of P16Ink4a (Cd31OE) and the respective control (Cd31E). (<b>c</b>) Cluster analysis of differentially expressed genes with the most significantly changed gene ontology terms (BP: biological process) in Cd31+ cells with silencing of P16Ink4a compared to the respective control and (<b>d</b>) cluster analysis of differentially expressed genes in Cd31+ cells with overexpression of P16Ink4a compared to the respective control. (<b>e</b>) Volcano plot of differentially expressed genes in Cd146+ cells with silencing of P16Ink4a (Cd146sh) compared to the respective controls (Cd146nc). (<b>f</b>) Volcano plot of differentially expressed genes in Cd146+ cells with overexpression of P16Ink4a (Cd146OE) and the respective control (Cd146E). (<b>g</b>) Cluster analysis of differentially expressed genes with the most significantly changed gene ontology terms (BP: biological process) in Cd146+ cells with silencing of P16Ink4a compared to the respective control and (<b>h</b>) cluster analysis of differentially expressed genes in Cd146+ cells with overexpression of P16Ink4a compared to the respective control.</p> Full article ">Figure 7 Cont.
<p>RNA sequencing analysis of Cd31+ (<b>a</b>–<b>d</b>) and Cd146+ (<b>e</b>–<b>h</b>) cells with modification of P16Ink4a expression levels (<span class="html-italic">n</span> = 3 each) corroborates the dual function of P16Ink4a in endothelial cells. Cells were transduced with lentiviral particles containing either P16 small hairpin (P16 shRNA) or overexpression constructs (P16) and the respective controls (nc shRNA, empty vector). (<b>a</b>) Volcano plot analysis of differentially expressed genes in Cd31+ cells with silencing of P16Ink4a (Cd31sh) compared to the respective controls (Cd31nc). (<b>b</b>) Volcano plot of differentially expressed genes in Cd31+ cells with overexpression of P16Ink4a (Cd31OE) and the respective control (Cd31E). (<b>c</b>) Cluster analysis of differentially expressed genes with the most significantly changed gene ontology terms (BP: biological process) in Cd31+ cells with silencing of P16Ink4a compared to the respective control and (<b>d</b>) cluster analysis of differentially expressed genes in Cd31+ cells with overexpression of P16Ink4a compared to the respective control. (<b>e</b>) Volcano plot of differentially expressed genes in Cd146+ cells with silencing of P16Ink4a (Cd146sh) compared to the respective controls (Cd146nc). (<b>f</b>) Volcano plot of differentially expressed genes in Cd146+ cells with overexpression of P16Ink4a (Cd146OE) and the respective control (Cd146E). (<b>g</b>) Cluster analysis of differentially expressed genes with the most significantly changed gene ontology terms (BP: biological process) in Cd146+ cells with silencing of P16Ink4a compared to the respective control and (<b>h</b>) cluster analysis of differentially expressed genes in Cd146+ cells with overexpression of P16Ink4a compared to the respective control.</p> Full article ">Figure 8
<p>Quantitative RT-PCR corroborates inflammatory signatures upon silencing and DNA damage/senescence features upon overexpression of P16Ink4a. Quantitative RT-PCR of angiogenesis, DNA damage/senescence and inflammation markers of Cd31+ (<b>a</b>–<b>f</b>) and Cd146+ (<b>g</b>–<b>l</b>) liver endothelial cells with silencing or overexpression of P16Ink4a (<span class="html-italic">n</span> = 8 each). Data are mean ± SEM. <sup>∗</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>∗∗</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>∗∗∗</sup> <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 8 Cont.
<p>Quantitative RT-PCR corroborates inflammatory signatures upon silencing and DNA damage/senescence features upon overexpression of P16Ink4a. Quantitative RT-PCR of angiogenesis, DNA damage/senescence and inflammation markers of Cd31+ (<b>a</b>–<b>f</b>) and Cd146+ (<b>g</b>–<b>l</b>) liver endothelial cells with silencing or overexpression of P16Ink4a (<span class="html-italic">n</span> = 8 each). Data are mean ± SEM. <sup>∗</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>∗∗</sup> <span class="html-italic">p</span> &lt; 0.01, <sup>∗∗∗</sup> <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 9
<p>Reduction in P16Ink4a levels generates a higher amount of reactive oxygen species (ROS) in liver endothelial cells. Cd31+ (<b>a</b>–<b>f</b>) and Cd146+ (<b>g</b>–<b>l</b>) cells were incubated with CellROX<sup>TM</sup> Deep Red reagent one week after transduction with P16Ink4a silencing or overexpression constructs and the respective controls and the signal was analyzed by flow cytometry. (<b>a</b>) Median values of ROS fluorescence in Cd31+ samples following silencing of P16Ink4a (P16 shRNA) and the respective control (nc shRNA). Representative examples for control (<b>b</b>) and P16Ink4a silencing (<b>c</b>). (<b>d</b>) Median values of ROS fluorescence in Cd31+ samples following overexpression of P16Ink4a (P16) and the respective control (empty vector). Representative examples for control (<b>e</b>) and P16Ink4a overexpression (<b>f</b>). (<b>g</b>) Median values of ROS fluorescence in Cd146+ samples following silencing of P16Ink4a and the respective control. Representative examples for control (<b>h</b>) and P16Ink4a silencing (<b>i</b>) in Cd146+ cells. (<b>j</b>) Median values of ROS fluorescence in Cd146+ samples following overexpression of P16Ink4a (P16) and the respective control (empty vector). Representative examples for control (<b>k</b>) and P16Ink4a overexpression (<b>l</b>). The data are presented as the mean ± SEM (<span class="html-italic">n</span> = 4, each). Symbols indicate individual values. * <span class="html-italic">p</span> &lt; 0.05. Note that silencing of P16Ink4a increases ROS production as sign of endothelial damage in both cell populations.</p> Full article ">Figure 10
<p>Reduction in P16Ink4a levels causes leakage in liver endothelial cells. Permeability of confluent CD31+ or Cd146+ liver endothelial cells was measured as streptavidin–horseradish peroxidase leakage in Transwell chambers following transduction with P16Ink4a silencing (P16 shRNA) (<b>a</b>,<b>c</b>) or overexpression constructs (<b>b</b>,<b>d</b>) and the respective controls (nc shRNA, empty vector). The data are presented as the mean ± SEM (<span class="html-italic">n</span> = 6, each). Symbols indicate individual values. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. Note that silencing of P16Ink4a significantly increased the permeability while overexpression had no significant effect.</p> Full article ">
15 pages, 1123 KiB  
Article
Activation of BDNF–TrkB Signaling in Specific Structures of the Sheep Brain by Kynurenic Acid
by Katarzyna Roszkowicz-Ostrowska, Patrycja Młotkowska, Elżbieta Marciniak, Michał Szlis, Marcin Barszcz and Tomasz Misztal
Cells 2024, 13(23), 1928; https://doi.org/10.3390/cells13231928 - 21 Nov 2024
Viewed by 346
Abstract
Fluctuations in kynurenic acid (KYNA) and brain-derived neurotrophic factor (BDNF) levels in the brain reflect its neurological status. The aim of the study was to investigate the effect of transiently elevated KYNA concentrations in the cerebroventricular circulation on the expression of BDNF and [...] Read more.
Fluctuations in kynurenic acid (KYNA) and brain-derived neurotrophic factor (BDNF) levels in the brain reflect its neurological status. The aim of the study was to investigate the effect of transiently elevated KYNA concentrations in the cerebroventricular circulation on the expression of BDNF and its high-affinity tropomyosin-related kinase receptor B (TrkB) in specific structures of the sheep brain. Intracerebroventricularly cannulated anestrous sheep were subjected to a series of four 30 min infusions of KYNA: 4 × 5 μg/60 μL/30 min (KYNA20, n = 6) and 4 × 25 μg/60 μL/30 min (KYNA100, n = 6) or a control infusion (n = 6), at 30 min intervals. Sections of the hippocampal CA3 field, amygdala (AMG), prefrontal cortex (PCx), and the hypothalamic medial-basal (MBH) and preoptic (POA) areas were dissected from the brain immediately after the experiment. The highest concentration of BDNF protein was found in the CA3 field (p < 0.001), which was 8-fold higher than in the AMG and 12-fold higher than that in the PCx (MBH and POA were not analyzed). The most pronounced BDNF mRNA expression was observed in the MBH, followed by the PCx, POA, AMG and CA3, while the highest abundance of TrkB mRNA was recorded in the AMG, followed by the MBH, PCx, CA3, and POA. KYNA increased (p < 0.05–p < 0.01) BDNF protein levels and the expression of its gene in the brain structures were examined, with the effect varying by dose and brain region. KYNA, particularly at the KYNA100 dose, also increased (p < 0.01) TrkB gene expression, except for the AMG, where the lower KYNA20 dose was more effective (p < 0.01). These findings suggest a positive relationship between KYNA levels in the cerebroventricular circulation and BDNF–TrkB expression in specific brain regions in a sheep model. This indicates that a transient increase in the CSF KYNA concentration can potentially restore BDNF production, for which deficiency underlies numerous neurological disorders. Full article
(This article belongs to the Section Cells of the Nervous System)
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Figure 1
<p>Brain-derived neurotrophic factor (BDNF) protein concentration (pg/mg protein, mean ± SEM) in homogenates of the examined sheep brain structures: CA3 field of the hippocampus (CA3), amygdala (AMG), and the prefrontal cortex (PCx). Significance of differences: ***, <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 2
<p>Comparison of brain-derived neurotrophic factor (BDNF) protein concentration (pg/mg protein, mean ± SEM) in homogenates of the hippocampal CA3 field (<b>A</b>), amygdala (<b>B</b>), and the prefrontal cortex (<b>C</b>) in sheep infused with control solution and the lower (total 20 μg, (KYNA20) and higher (total 100 μg, KYNA100) doses of kynurenic acid (KYNA) into the third brain ventricle. Significance of differences: *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 3
<p>Comparison of relative brain-derived neurotrophic factor (BDNF) mRNA expression (mean ± SEM) in the hippocampal CA3 field (<b>A</b>), amygdala (<b>B</b>), prefrontal cortex (<b>C</b>), in the hypothalamic medial-basal area (<b>D</b>), and the preoptic area (<b>E</b>) in sheep infused with control solution and the lower (total 20 μg, (KYNA20) and higher (total 100 μg, KYNA100) doses of kynurenic acid (KYNA) into the third brain ventricle. Significance of differences: *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 4
<p>Comparison of relative tropomyosin-related kinase receptor B (TrkB) mRNA expression (mean ± SEM) in the hippocampal CA3 field (<b>A</b>), amygdala (<b>B</b>), prefrontal cortex (<b>C</b>), in the hypothalamic medial-basal area (<b>D</b>), and the preoptic area (<b>E</b>) in sheep infused with control solution and the lower (total 20 μg, (KYNA20) and higher (total 100 μg, KYNA100) doses of kynurenic acid (KYNA) into the third brain ventricle. Significance of differences: *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">
2 pages, 182 KiB  
Correction
Correction: Podolska et al. Graphene Oxide Nanosheets for Localized Hyperthermia—Physicochemical Characterization, Biocompatibility, and Induction of Tumor Cell Death. Cells 2020, 9, 776
by Malgorzata J. Podolska, Alexandre Barras, Christoph Alexiou, Benjamin Frey, Udo Gaipl, Rabah Boukherroub, Sabine Szunerits, Christina Janko and Luis E. Muñoz
Cells 2024, 13(23), 1927; https://doi.org/10.3390/cells13231927 - 21 Nov 2024
Viewed by 119
Abstract
Add New References [...] Full article
(This article belongs to the Special Issue The Interaction of Biomedical Nanoparticles with the Immune System)
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