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12 pages, 1822 KiB  
Review
H3K4 Methylation and Demethylation in Fungal Pathogens: The Epigenetic Toolbox for Survival and Adaptation in the Host
by Maruti Nandan Rai and Rikky Rai
Pathogens 2024, 13(12), 1080; https://doi.org/10.3390/pathogens13121080 - 9 Dec 2024
Viewed by 461
Abstract
Pathogenic fungi represent a diverse group of eukaryotic microorganisms that significantly impact human health and agriculture. In recent years, the role of epigenetic modifications, particularly histone modifications, in fungal pathobiology has emerged as a prominent area of interest. Among these modifications, methylation of [...] Read more.
Pathogenic fungi represent a diverse group of eukaryotic microorganisms that significantly impact human health and agriculture. In recent years, the role of epigenetic modifications, particularly histone modifications, in fungal pathobiology has emerged as a prominent area of interest. Among these modifications, methylation of histone H3 at lysine-4 (H3K4) has garnered considerable attention for its implications in regulating gene expression associated with diverse cellular processes. A body of literature has uncovered the pivotal roles of H3K4 methylation in multiple biological processes crucial for pathogenic adaptation in a wide range of fungal pathogens of humans and food crops. This review delves into the recent advancements in understanding the impact of H3K4 methylation/demethylation on fungal pathogenesis. We explore the roles of H3K4 methylation in various cellular processes, including fungal morphogenesis and development, genome stability and DNA repair, metabolic adaptation, cell wall maintenance, biofilm formation, antifungal drug resistance, and virulence. We also discuss the conservation of H3K4 methylation regulators and their potential as therapeutic targets to prevent fungal diseases. Collectively, this review underscores the intricate links between H3K4 methylation, fungal pathogenesis, and potential avenues for novel antifungal strategies. Full article
(This article belongs to the Section Fungal Pathogens)
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<p>Graphical abstract of histone methylation-mediated transcriptional activation. Created in BioRender. Rai, N. (2024) <a href="https://BioRender.com/m31m407" target="_blank">https://BioRender.com/m31m407</a>, 2 December 2024.</p>
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<p>A graphical representation of the multifaceted roles of H3K4 methylation in the pathogenic adaptation of human and plant pathogenic fungi. Created in BioRender. Rai, N. (2024) <a href="https://BioRender.com/q87f061" target="_blank">https://BioRender.com/q87f061</a>, 2 December 2024.</p>
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17 pages, 5818 KiB  
Article
DNA Methylation and Histone Acetylation Contribute to the Maintenance of LTP in the Withdrawal Behavior Interneurons in Terrestrial Snails
by Alena Zuzina, Daria Kolotova and Pavel Balaban
Cells 2024, 13(22), 1850; https://doi.org/10.3390/cells13221850 - 8 Nov 2024
Viewed by 710
Abstract
Accumulated data indicate that epigenetic regulations, including histone modifications and DNA methylation, are important means for adjusting the expression of genes in response to various stimuli. In contrast to the success in studying the role of DNA methylation in laboratory rodents, the role [...] Read more.
Accumulated data indicate that epigenetic regulations, including histone modifications and DNA methylation, are important means for adjusting the expression of genes in response to various stimuli. In contrast to the success in studying the role of DNA methylation in laboratory rodents, the role of DNA methylation in the terrestrial snail Helix lucorum has been studied only in behavioral experiments. This prompted us to further investigate the role of DNA methylation and the interaction between DNA methylation and histone acetylation in the mechanisms of neuroplasticity in terrestrial snails using in vitro experiments. Dysregulation of DNA methylation by the DNMT inhibitor RG108 significantly suppressed the long-term potentiation (LTP) of synaptic inputs in identified neurons. We then tested whether the RG108-induced weakening of potentiation can be reversed under co-application of histone deacetylase inhibitors sodium butyrate or trichostatin A. It was found that increased histone acetylation significantly compensated for RG108-induced LTP deficiency. These data bring important insights into the functional role of DNA methylation as an important regulatory mechanism and a necessary condition for the development and maintenance of long-term synaptic changes in withdrawal interneurons of terrestrial snails. Moreover, these results support the idea of the interaction of DNA methylation and histone acetylation in the epigenetic regulation of synaptic plasticity. Full article
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<p>Schematic representations of protocol. 5-HT—serotonin.</p>
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<p>The effects of RG108, sodium butyrate (NaB) and trichostatin A (TSA) on EPSP amplitudes in control, under LTP induction and LTP maintenance in withdrawal interneurons with test stimulations of the second cutaneal nerve. (<b>A</b>) Effects of the bath applications of RG108 on the EPSPs: a time course plot of pooled data for the EPSPs. RG108 reduces LTP duration. * denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108 vs. LTP; # denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108 v vs. control. (<b>B</b>) Effect of the combined bath application of RG108 with either NaB or TSA on the EPSPs: a time course plot of pooled data for the EPSPs. Histone deacetylase inhibitors (NaB or TSA) prevented the weakening of potentiation. * denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108+NaB vs. LTP+RG108; # denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108+TSA vs. LTP+RG108. The data are presented as mean  ±  standard error of the mean. The duration of drugs’ presence is shown as a striped bar at the bottom in (<b>A</b>,<b>B</b>). Arrows indicate the time of tetanization+5-HT applications in (<b>A</b>,<b>B</b>). (<b>C</b>) Example traces of the EPSPs (a, b and c from plots (<b>A</b>,<b>B</b>)) in control, control+RG108, LTP, LTP+RG108, LTP+RG108+NaB and LTP+RG108+TSA groups. Scale bars:5 mV, 500 ms. (<b>D</b>) Comparison of the effects of RG108, NaB and TSA before the tetanization+5-HT. No differences were observed between EPSP amplitudes in groups before 5-HT+tetanization (time point 0 min) (<b>E</b>) Comparison of the effects of RG108, NaB and TSA on LTP induction: EPSP amplitudes 60 min post-5-HT+tetanization (time point of 80 min). EPSP amplitudes of LTP group were significantly higher than those in control; * denotes <span class="html-italic">p</span> &lt; 0.05 LTP vs. control. Moreover, there were no significant differences between the groups with LTP induction. (<b>F</b>) Comparison of the effects of RG108, NaB and TSA on LTP maintenance: EPSP amplitudes 230 min post-5-HT+tetanization (time point 250 min). Application of RG108 caused a significant decrease in EPSP amplitude, while co-administration of RG108+NaB or RG108+TSA was shown to enhance LTP. * denotes <span class="html-italic">p</span> &lt; 0.05 LTP vs. control; # denotes <span class="html-italic">p</span> &lt; 0.05 LTP vs. LTP+RG108; @ denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108 vs. LTP+RG108+NaB; % denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108 vs. LTP+RG108+TSA.</p>
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<p>The effects of RG108, NaB and TSA on EPSP amplitudes in control, under LTP induction and LTP maintenance in withdrawal interneurons with test stimulation of intestinal nerve. (<b>A</b>) Effects of the bath application of RG108 on the EPSPs: a time course plot of averaged data for the EPSPs. RG108 reduces the LTP maintenance. * denotes <span class="html-italic">p</span> &lt; 0.05 in groups LTP+RG108 vs. LTP; # denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108 vs. control. (<b>B</b>) Effect of the combined bath application of RG108 with either NaB or TSA on the EPSPs: a time course plot of averaged data for the EPSPs. Histone deacetylase inhibitors (NaB or TSA) prevented the weakening of potentiation. * denotes <span class="html-italic">p</span> &lt; 0.05 in groups LTP+RG108+NaB vs. LTP+RG108; # denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108+TSA vs. LTP+RG108. % denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108+NaB vs. LTP. The data are presented as mean ± SEM. The duration of drug presence is shown as a striped bar at the bottom in (<b>A</b>,<b>B</b>). Arrows indicate the time of tetanization+5-HT in (<b>A</b>,<b>B</b>). (<b>C</b>) Examples of the EPSPs (a, b and c from plots (<b>A</b>,<b>B</b>)) in control, control+RG108, LTP, LTP+RG108, LTP+RG108+NaB and LTP+RG108+TSA groups. Scale bars:5 mV, 500 ms. (<b>D</b>) Comparison of the effects of RG108, NaB and TSA before the tetanization+5-HT. No differences were observed between EPSP amplitudes in groups before the 5-HT+tetanizations (time point 0 min) (<b>E</b>) Comparison of the effects of RG108, NaB and TSA on LTP induction: EPSP amplitudes 60 min post-5-HT+tetanization (time point 80 min). EPSP amplitudes of LTP group were significantly higher than those in control and LTP+RG108 groups; * denotes <span class="html-italic">p</span> &lt; 0.05 LTP vs. control; # denotes <span class="html-italic">p</span> &lt; 0.05 LTP vs. LTP+RG108; @ denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108+NaB vs. LTP+RG108. (<b>F</b>) Comparison of the effect of RG108, NaB and TSA on LTP maintenance: EPSP amplitudes 230 min post-5-HT+tetanization (time point 250 min). Application of RG108 caused a significant decrease in EPSP amplitude while co-administration of RG108+NaB or RG108+TSA was shown to enhance LTP. * denotes <span class="html-italic">p</span> &lt; 0.05 LTP vs. control; # denotes <span class="html-italic">p</span> &lt; 0.05 LTP vs. LTP+RG108; @ denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108 vs. LTP+RG108+NaB; % denotes <span class="html-italic">p</span> &lt; 0.05 LTP+RG108 vs. LTP+RG108+TSA.</p>
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<p>Epigenetic regulation of LTP in the withdrawal behavior of interneurons in terrestrial snails. (<b>A</b>). The neural network underlying LTP formation. (<b>B</b>). Inhibition of DNMT activity inhibits late LTP without affecting induction and early LTP, while the combined use of HDACi with DNMTi prevents potentiation attenuation. (<b>C</b>). Proposed model of epigenetic regulation of LTP in premotor interneurons with the example of glutamatergic presynaptic input. The induction and stabilization of LTP require NMDA and 5-HT receptor activation. This leads to the burst of intracellular calcium, synthesis of inositol 1,4,5-trisphosphate (IP3, mobilizing calcium from calcium stores) and diacylglycerol (DAG) from phosphatidylinositol 4,5-bisphosphate (PIP2) (phospholipase C (PLC) catalyses the hydrolysis of PIP2). DAG and/or an increase in the intracellular calcium act as activators of protein kinase C (PKC). The latter regulates the expression of DNMT genes. Alterations of DNMT genes’ expression in turn may cause changes in the methylation status of various plasticity-related genes. Moreover, DNA methylation somehow (“?” on the picture) affects the histone acetylation level. Successful activation of these signaling pathways leads to an increase in the number of AMPA receptors and, consequently, the synaptic strength.</p>
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15 pages, 1022 KiB  
Review
PHF8/KDM7B: A Versatile Histone Demethylase and Epigenetic Modifier in Nervous System Disease and Cancers
by Tingyu Fan, Jianlian Xie, Guo Huang, Lili Li, Xi Zeng and Qian Tao
Epigenomes 2024, 8(3), 36; https://doi.org/10.3390/epigenomes8030036 - 15 Sep 2024
Viewed by 1399
Abstract
Many human diseases, such as malignant tumors and neurological diseases, have a complex pathophysiological etiology, often accompanied by aberrant epigenetic changes including various histone modifications. Plant homologous domain finger protein 8 (PHF8), also known as lysine-specific demethylase 7B (KDM7B), is a critical histone [...] Read more.
Many human diseases, such as malignant tumors and neurological diseases, have a complex pathophysiological etiology, often accompanied by aberrant epigenetic changes including various histone modifications. Plant homologous domain finger protein 8 (PHF8), also known as lysine-specific demethylase 7B (KDM7B), is a critical histone lysine demethylase (KDM) playing an important role in epigenetic modification. Characterized by the zinc finger plant homology domain (PHD) and the Jumonji C (JmjC) domain, PHF8 preferentially binds to H3K4me3 and erases repressive methyl marks, including H3K9me1/2, H3K27me1, and H4K20me1. PHF8 is indispensable for developmental processes and the loss of PHF8 enzyme activity is linked to neurodevelopmental disorders. Moreover, increasing evidence shows that PHF8 is highly expressed in multiple tumors as an oncogenic factor. These findings indicate that studying the role of PHF8 will facilitate the development of novel therapeutic agents by the manipulation of PHF8 demethylation activity. Herein, we summarize the current knowledge of PHF8 about its structure and demethylation activity and its involvement in development and human diseases, with an emphasis on nervous system disorders and cancer. This review will update our understanding of PHF8 and promote the clinical transformation of its predictive and therapeutic value. Full article
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<p>(<b>A</b>) Protein structure of PHF8. PHF8 domains are shown in different colors. In blue: plant homology domain (PHD); in green: nuclear localization signals; in orange: Jumonji C (JmjC) domain; in purple: serine-rich region (Ser). (<b>B</b>) Demethylation activity and biological functions of PHF8. Upper lane: histone lysine sites and number of methyl groups demethylated by PHF8; lower lane: fundamental cellular processes regulated by PHF8.</p>
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<p>PHF8 in nervous system. (<b>A</b>) Role of PHF8 in nervous system. (<b>B</b>) Clinically observed PHF8 variants associated with X-linked intellectual disability.</p>
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<p>Regulators and downstream effectors of PHF8 in tumorigenesis.</p>
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13 pages, 946 KiB  
Article
A Genotype/Phenotype Study of KDM5B-Associated Disorders Suggests a Pathogenic Effect of Dominantly Inherited Missense Variants
by Maria Carla Borroto, Coralie Michaud, Chloé Hudon, Pankaj B. Agrawal, Katherine Agre, Carolyn D. Applegate, Alan H. Beggs, Hans T. Bjornsson, Bert Callewaert, Mei-Jan Chen, Cynthia Curry, Orrin Devinsky, Tracy Dudding-Byth, Kelly Fagan, Candice R. Finnila, Ralitza Gavrilova, Casie A. Genetti, Susan M. Hiatt, Friedhelm Hildebrandt, Monica H. Wojcik, Tjitske Kleefstra, Caroline M. Kolvenbach, Bruce R. Korf, Paul Kruszka, Hong Li, Jessica Litwin, Julien Marcadier, Konrad Platzer, Patrick R. Blackburn, Margot R. F. Reijnders, Heiko Reutter, Ina Schanze, Joseph T. Shieh, Cathy A. Stevens, Zaheer Valivullah, Marie-José van den Boogaard, Eric W. Klee and Philippe M. Campeauadd Show full author list remove Hide full author list
Genes 2024, 15(8), 1033; https://doi.org/10.3390/genes15081033 - 6 Aug 2024
Cited by 1 | Viewed by 1940
Abstract
Bi-allelic disruptive variants (nonsense, frameshift, and splicing variants) in KDM5B have been identified as causative for autosomal recessive intellectual developmental disorder type 65. In contrast, dominant variants, usually disruptive as well, have been more difficult to implicate in a specific phenotype, since some [...] Read more.
Bi-allelic disruptive variants (nonsense, frameshift, and splicing variants) in KDM5B have been identified as causative for autosomal recessive intellectual developmental disorder type 65. In contrast, dominant variants, usually disruptive as well, have been more difficult to implicate in a specific phenotype, since some of them have been found in unaffected controls or relatives. Here, we describe individuals with likely pathogenic variants in KDM5B, including eight individuals with dominant missense variants. This study is a retrospective case series of 21 individuals with variants in KDM5B. We performed deep phenotyping and collected the clinical information and molecular data of these individuals’ family members. We compared the phenotypes according to variant type and to those previously described in the literature. The most common features were developmental delay, impaired intellectual development, behavioral problems, autistic behaviors, sleep disorders, facial dysmorphism, and overgrowth. DD, ASD behaviors, and sleep disorders were more common in individuals with dominant disruptive KDM5B variants, while individuals with dominant missense variants presented more frequently with renal and skin anomalies. This study extends our understanding of the KDM5B-related neurodevelopmental disorder and suggests the pathogenicity of certain dominant KDM5B missense variants. Full article
(This article belongs to the Special Issue Molecular Genetics of Neurodevelopmental Disorders)
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<p>Dominant and bi-allelic <span class="html-italic">KDM5B</span> variants from this cohort and the literature represented within the KDM5B protein. The active regions are named and highlighted in different colors according to the legend. Variant types are also indicated, and if the same one was shared by multiple individuals, it is shown as a circle with the total number. Illustration is adapted from <a href="https://proteinpaint.stjude.org/" target="_blank">https://proteinpaint.stjude.org/</a>.</p>
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<p>Photographs of individuals with <span class="html-italic">KDM5B</span> variants. (<b>A</b>) Individual No. 5 (p.Ala804Val) at the age of 10 years old. Note the macrotia, straight eyebrows, telecanthus, the full nasal tip, and the broad mouth. (<b>B</b>) Individual No. 19 (Whole gene deletion) at the age of 18 years old. Note the brachycephaly, elongated face, high forehead, temporally sparse hair, broad eyebrows, bilaterally temporal narrowing, downslanted palpebral fissures, short philtrum, facial asymmetry (left side is slightly shorter), increased cervical length and width, and large hands with long, tapered fingers. (<b>C</b>) Individual No. 21 (p.Glu2Ter and p.Trp387Ter) at the age of 4 years old. Note the broad forehead, the midface retraction, the full nasal tip, and the micrognathia.</p>
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21 pages, 6342 KiB  
Article
Mechanism of Histone Arginine Methylation Dynamic Change in Cellular Stress
by Xiao-Guang Ren, Wei Li, Wen-Xuan Li and Wenqiang Yu
Int. J. Mol. Sci. 2024, 25(14), 7562; https://doi.org/10.3390/ijms25147562 - 10 Jul 2024
Viewed by 1264
Abstract
Histone arginine residue methylation is crucial for individual development and gene regulation. However, the dynamics of histone arginine methylation in response to cellular stress remains largely unexplored. In addition, the interplay and regulatory mechanisms between this and other histone modifications are important scientific [...] Read more.
Histone arginine residue methylation is crucial for individual development and gene regulation. However, the dynamics of histone arginine methylation in response to cellular stress remains largely unexplored. In addition, the interplay and regulatory mechanisms between this and other histone modifications are important scientific questions that require further investigation. This study aimed to investigate the changes in histone arginine methylation in response to DNA damage. We report a global decrease in histone H3R26 symmetric dimethylation (H3R26me2s) and hypoacetylation at the H3K27 site in response to DNA damage. Notably, H3R26me2s exhibits a distribution pattern similar to that of H3K27ac across the genome, both of which are antagonistic to H3K27me3. Additionally, histone deacetylase 1 (HDAC1) may be recruited to the H3R26me2s demethylation region to mediate H3K27 deacetylation. These findings suggest crosstalk between H3R26me2s and H3K27ac in regulating gene expression. Full article
(This article belongs to the Special Issue Epigenetic Controls for Gene Panels in Oncology)
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<p>Histone arginine methylation decreased in DNA damaged cells. (<b>A</b>) H3R26me2s methylation level was decreased in bleomycin-treated HepG2 cells analyzed using immunoblot assay, while for H3R26me2a there was no change. (<b>B</b>) H3R26me2s methylation level was decreased in bleomycin-treated LM3 cells analyzed using immunoblot assay, while for H3R26me2a there was no change. (<b>C</b>) H3R26me2s methylation level was decreased in bleomycin-treated Hela cells analyzed using immunoblot assay, while for H3R26me2a there was no change. (<b>D</b>) Relative changes in H3R26me2a and H3R26me2s in bleomycin-treated HepG2 (<b>A</b>), LM3 (<b>B</b>), and Hela (<b>C</b>) cells. (<b>E</b>) γH2A.X modification was increased in bleomycin-treated HepG2 cells measured using immunofluorescence. (<b>F</b>) Immunofluorescence of H3R26me2a in control and bleomycin-treated cells. (<b>G</b>) Immunofluorescence of H3R26me2s in control and bleomycin-treated cells. (<b>H</b>) Nearly half of the H3R26me2s modification peaks were downregulated in bleomycin-treated cells, as a positive control, 93% percent γH2A.X of peaks were upregulated in bleomycin-treated cells. (<b>I</b>) Percentage of H3R26me2s’s different peaks’ distribution features across the genome. Left Pie Chart: Characteristics of H3R26me2s’ different peaks in genome features of Genebody, Intergenic, Promoter, and TES regions. Right Pie Chart: Percentage of H3R26me2s different peaks distribution in Exon and Intron regions. (<b>J</b>) Analysis of H3R26me2s different peaks associated with gene functions using Gene Oncology. Data information: Scale bars in micrographs = 10 μm. Data are shown as the mean ± SEM of three biological replicates and were analyzed with a two-tailed unpaired Student’s <span class="html-italic">t</span>-test. *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Histone modifications respond to the stress of chemical reagents in HepG2 cells. (<b>A</b>) HepG2 cells were treated with 5 μg/mL, 10 μg/mL, and 20 μg/mL bleomycin; for each BLM concentration group, cells were collected at 24 h and 48 h. Histone modifications were detected using immune blot with the indicated antibodies. (<b>B</b>) Relative changes in H3R26me2a, H3R26me2s, H3K27ac, and H3K27me3 in bleomycin-treated HepG2 cells (<b>A</b>). (<b>C</b>) HepG2 cells were treated with 1 mM H<sub>2</sub>O<sub>2</sub> for 1, 2, 4, and 6 h, cell lysate was collected, and histone modifications were detected with the indicated antibodies. (<b>D</b>) Relative changes in H3R26me2a, H3R26me2s, H3K27ac, and H3K27me3 in H<sub>2</sub>O<sub>2</sub>-treated HepG2 cells (<b>C</b>). (<b>E</b>) HepG2 cells were treated with 100 μM, 200 μM, and 400 μM TMZ for 24 h, cell lysate was collected, and histone modifications were detected with the indicated antibodies. (<b>F</b>) Relative changes in H3R26me2a, H3R26me2s, H3K27ac, and H3K27me3 in TMZ-treated HepG2 cells (<b>E</b>). Data are shown as the mean ± SEM of two biological replicates and were analyzed with a two-tailed unpaired Student’s <span class="html-italic">t</span>-test. *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>H3K27ac undergoes hypoacetylation in response to DNA damage. (<b>A</b>) H3k27ac level was decreased in bleomycin-treated HepG2 cells analyzed using immunoblot assay, and the H3K27me3 level showed no change. (<b>B</b>) H3k27ac level was decreased in bleomycin-treated LM3 cells analyzed using immunoblot assay; H3K27me3 level showed no change. (<b>C</b>) H3k27ac level was decreased in bleomycin Hela cells analyzed using immunoblot assay; H3K27me3 level showed no change. (<b>D</b>) Relative changes in H3K27ac and H3K27me3 in bleomycin-treated HepG2 (<b>A</b>), LM3 (<b>B</b>), and Hela (<b>C</b>) cells. (<b>E</b>) Immunofluorescence of H3K27ac in control and bleomycin-treated cells; H3K27ac was decreased in bleomycin-treated cells. (<b>F</b>) Immunofluorescence of H3K27me3 in control and bleomycin-treated cells; H3K27me3 showed no change in bleomycin-treated cells. (<b>G</b>) H3K27ac level was reversed in treatment with bleomycin and HDAC inhibitor LBH598 cells. (<b>H</b>) Relative changes in H3K27ac, H3K27me3, H3R26me2a, and H3R26me2s in BLM- or BLM+HDACi-treated HepG2 cells (<b>G</b>). (<b>I</b>) Immune blot analysis of HDAC1 expression in bleomycin-treated HepG2 cells. (<b>J</b>) HDAC1 was detected in the cellular nucleus and cytoplasmic content using immunoblot; H3 and GAPDH were used as a nucleus or cytoplasm marker. (<b>K</b>) Relative levels of HDAC1 in cytoplasmic or nucleus in bleomycin-treated HepG2 (<b>J</b>) cells. Data information: Scale bars in micrographs = 10 μm. Data were analyzed with a two-tailed unpaired 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, n.s.: no significance.</p>
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<p>H3K27 acetylation or trimethylation does not impair H3R26me2s. (<b>A</b>) Cells were treated with P300 inhibitors for 48 h to inhibit histone lysine acetylation, and the H3R26 methylation state detected using immunoblot assay was not impaired. (<b>B</b>) Relative changes in H3R26me2s, H3K27ac, and H3K27me3 in P300 inhibitor-treated HepG2 cells (<b>A</b>). (<b>C</b>) Cells were treated with 10 nM HDAC inhibitor LHB598 for 24 h to evaluate histone lysine acetylation, the H3R26 symmetric dimethylation state detected via immunoblot assay was not impaired. (<b>D</b>) Relative changes in H3R26me2s, H3K27ac, and H3K27me3 in HDAC inhibitor LHB598-treated HepG2 cells (<b>C</b>). (<b>E</b>) Cells were treated with 10 nM, 50 nM, and 200 nM HDAC inhibitor TSA for 24 h to evaluate histone lysine acetylation; the H3R26 symmetric dimethylation state detected via immunoblot assay was not impaired. (<b>F</b>) Relative changes in H3R26me2s, H3K27ac, and H3K27me3 in HDAC inhibitor TSA-treated HepG2 cells (<b>E</b>). (<b>G</b>) Cells were treated with 5 μM and 10 μM EZH2 inhibitor DZNep for 72 h to inhibit histone lysine methylation, the H3R26 methylation state detected via immunoblot assay was not impaired. (<b>H</b>) Relative changes in H3R26me2s, H3K27ac, and H3K27me3 in EZH2 inhibitor DZNep-treated HepG2 cells (<b>G</b>). Data information: Data were analyzed with a two-tailed unpaired Student’s <span class="html-italic">t</span>-test. *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Histone H3R26me2s modulates H3K27 acetylation state. (<b>A</b>) qPCR analysis of <span class="html-italic">PRMT5</span> knockdown efficiency by siRNA in HepG2 cells. (<b>B</b>) qPCR analysis of <span class="html-italic">PRMT9</span> knockdown efficiency by siRNA in HepG2 cells. (<b>C</b>) <span class="html-italic">PRMT5</span> and <span class="html-italic">PRMT9</span> were knocked down in HepG2 cells by siRNA, and histone modifications were detected with the indicated antibodies. (<b>D</b>) Number of PRMT5 peaks in BLM and control group HepG2 cells; (<b>E</b>) Different PRMT5 peaks in BLM group versus control group HepG2 cells. (<b>F</b>) Cells were treated with 5 μM, 10 μM, and 20 μM PRMT5 inhibitor GSK591 for 48 h to inhibit histone arginine methylation, H3K27ac modification level detected via immunoblot assay was decreased in a dose-dependent manner. (<b>G</b>) Histone H3R26me2s and H3K27ac levels were decreased in the <span class="html-italic">PRMT5</span> knockdown HepG2 cells. (<b>H</b>) Relative changes in H3R26me2s, H3K27ac, and H3K27me3 in <span class="html-italic">PRMT5</span> knockdown HepG2 cells (<b>G</b>). (<b>I</b>) Validation of H3R26me2s and H3K27ac levels change in the PRMT5 overexpressed cells through immunoblot. (<b>J</b>) Relative changes in H3R26me2s, H3K27ac, and H3K27me3 in PRMT5 overexpressed HepG2 cells (<b>I</b>). Data information: Data were analyzed with a two-tailed unpaired Student’s <span class="html-italic">t</span>-test. *: <span class="html-italic">p</span> &lt; 0.05, **: <span class="html-italic">p</span> &lt; 0.01, ***: <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>H3K27ac deacetylation mediated by HDAC1. (<b>A</b>) Normalized H3K27ac, H3K27me3, H3R26me2a, and H3R26me2s levels in bleomycin-treated A549 cells; A549 cells were treated with a single BLM concentration in a time-course manner, immune blot results are provided in <a href="#app1-ijms-25-07562" class="html-app">Figure S1B</a>. (<b>B</b>) Normalized H3K27ac, H3K27me3, H3R26me2a, and H3R26me2s levels in H<sub>2</sub>O<sub>2</sub>-treated HepG2 cells; HepG2 cells were treated with a single H<sub>2</sub>O<sub>2</sub> concentration in a time-course manner, immune blot results are provided in <a href="#ijms-25-07562-f002" class="html-fig">Figure 2</a>C. (<b>C</b>) Respective of the H3R26me2s and H3K27ac modifications landscape of the <span class="html-italic">GAPDH</span> genomic locus. (<b>D</b>) H3R26me2s, H3K27ac, and HDAC1 enrichment in <span class="html-italic">GAPDH</span> genomic locus. (<b>E</b>) Validation of HDAC1 overexpression in HepG2 cells. (<b>F</b>) Respective of the H3R26me2s and H3K27ac modifications landscape of the <span class="html-italic">LPCAT1</span> genomic locus. (<b>G</b>) H3R26me2s, H3K27ac, PRMT5, and HDAC1 enrichment in <span class="html-italic">LPCAT1</span> genomic locus with control or HDAC1 overexpression cells. Data information: Data are shown as the mean ± SEM of three biological replicates and were analyzed with two-tailed unpaired Student’s <span class="html-italic">t</span>-test. *: <span class="html-italic">p</span> &lt; 0.05, ***: <span class="html-italic">p</span> &lt; 0.001, n.s.: no significance. Layered H3K27ac indicates H3K27ac ChIP-seq peaks, each color represents one cell line, and data were downloaded from the UCSC Genome Browser.</p>
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<p>H3R26me2s shares a similar pattern with H3K27ac. (<b>A</b>) Respective of the H3R26me2a, H3R26me2s, H3K27ac, and H3K27me3 modifications landscape across a 1 Mb segment of the human genome; H3R26me2s shares a similar distribution pattern with H3K27ac and antagonizes H3K27me3. (<b>B</b>) Respective of the H3R26me2a, H3R26me2s, H3K27ac, and H3K27me3 modifications landscape across a 100 Kb segment of the human genome; H3R26me2s shares a similar distribution pattern with H3K27ac and antagonizes H3K27me3. (<b>C</b>) Overlapped H3R26me2s and H3K27ac up or down peaks; the cyan dots represent that H3R26me2s and H3K27ac have the same change pattern, while the grey dots represent that they have an opposite change pattern. (<b>D</b>) Gene Oncology of H3R26me2s and H3K27ac overlapped positive correction peaks shown in <a href="#ijms-25-07562-f004" class="html-fig">Figure 4</a>F associated genes. (<b>E</b>) Volcano Plot of 256 downregulated and 84 upregulated genes in bleomycin-treated cells compared with control cells. (<b>F</b>) Number of genes up and down in bleomycin-treated HepG2 cells; gene fold changes above two were in the account. (<b>G</b>) Respective of the control and bleomycin-treated cells histone H3R26me2a, H3R26me2s, H3K27me3, and H3K27ac modifications in the downregulated gene <span class="html-italic">LPCAT1</span> locus. (<b>H</b>) H3R26me2s and H3K27ac modifications were decreased in bleomycin-treated cells at the <span class="html-italic">LPCAT1</span> locus quantitated using CUT&amp;Tag-qPCR. Data information: Data are shown as the mean ± SEM of three biological replicates and were analyzed with two-tailed unpaired Student’s <span class="html-italic">t</span>-test. *: <span class="html-italic">p</span> &lt; 0.05, ****: <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Feature and function of H3R26me2s and H3K27ac overlapped peaks. (<b>A</b>) H3R26me2s and H3K27ac peaks were increased in the upregulated gene <span class="html-italic">ISG15</span> locus. (<b>B</b>) H3R26me2s and H3K27ac peaks were increased in the upregulated gene <span class="html-italic">GADD45A</span> locus.</p>
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<p>Proposed scheme for DNA damage-induced histone modifications change. During DNA damage, histone modifications change to regulate gene expression or DNA repair. In this study, we found DNA damage-induced histone arginine demethylation and lysine deacetylation. Moreover, the lower H3R26me2s region then recruited HDAC1 to catalyze H3K27 deacetylation. H3R26me2s and H3K27ac have similar occupancy across the genome, indicating the crosstalk between H3R26me2s and H3K27ac in regulating gene expression.</p>
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15 pages, 2827 KiB  
Article
SAHA/5-AZA Enhances Acetylation and Degradation of mutp53, Upregulates p21 and Downregulates c-Myc and BRCA-1 in Pancreatic Cancer Cells
by Michele Di Crosta, Francesca Chiara Ragone, Rossella Benedetti, Gabriella D’Orazi, Maria Saveria Gilardini Montani and Mara Cirone
Int. J. Mol. Sci. 2024, 25(13), 7020; https://doi.org/10.3390/ijms25137020 - 27 Jun 2024
Viewed by 1870
Abstract
Epigenetic changes are common in cancer and include aberrant DNA methylation and histone modifications, including both acetylation or methylation. DNA methylation in the promoter regions and histone deacetylation are usually accompanied by gene silencing, and may lead to the suppression of tumor suppressors [...] Read more.
Epigenetic changes are common in cancer and include aberrant DNA methylation and histone modifications, including both acetylation or methylation. DNA methylation in the promoter regions and histone deacetylation are usually accompanied by gene silencing, and may lead to the suppression of tumor suppressors in cancer cells. An interaction between epigenetic pathways has been reported that could be exploited to more efficiently target aggressive cancer cells, particularly those against which current treatments usually fail, such as pancreatic cancer. In this study, we explored the possibility to combine the DNA demethylating agent 5-AZA with HDAC inhibitor SAHA to treat pancreatic cancer cell lines, focusing on the acetylation of mutp53 and the consequences on its stability, as well as on the interaction of this protein with c-myc and BRCA-1, key molecules in cancer survival. The results obtained suggest that SAHA/5-AZA combination was more effective than single treatments to promote the degradation of mutp53, to upregulate p21 and downregulate c-Myc and BRCA-1, thus increasing DNA damage and cytotoxicity in pancreatic cancer cells. Full article
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Figure 1
<p>5-AZA increases acetylation and cytotoxicity more than SAHA in pancreatic cancer cells. (<b>A</b>) Acetylated proteins as evaluated by western blot analysis in PaCa44 and PT45 pancreatic cancer cell lines treated with SAHA (5 μM), 5-AZA (AZA) (40 nM), SAHA/AZA combination for 48 h or untreated (CT) by using an antibody against acetylated lysine (see material and methods). Ponceau staining is shown as loading control. (<b>B</b>) Acetylated Histone H3 expression level as evaluated by western blot analysis in PaCa44 cells treated as above reported. Histograms represent the mean plus SD of the densitometric analysis of the ratio of Acetylate Histone H3/Histone H3; <span class="html-italic">p</span>-value: ** &lt; 0.01 and **** &lt; 0.0001, as calculated by ANOVA test. (<b>C</b>) Cell survival was assessed by Trypan blue assay in PaCa44 and PT45 pancreatic cancer cell lines treated with SAHA, 5-AZA (AZA), SAHA/AZA combination at the same concentrations reported above, or untreated (CT). The histograms represent the percentage of cell viability relative to the control; data are shown as the mean plus SD of more than three experiments <span class="html-italic">p</span>-value: ** &lt; 0.01; *** &lt; 0.001; and **** &lt; 0.0001, as calculated by ANOVA test. (<b>D</b>) Cleaved Caspase 3 (cl Casp3) expression level as evaluated by western blot analysis in PaCa44 and PT45 cells treated as above with SAHA, 5-AZA (AZA), SAHA/AZA combination or untreated (CT). β-Actin was used as loading control. Histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between cleaved Capase3 and β-Actin; <span class="html-italic">p</span>-value: * &lt; 0.05; ** &lt; 0.01; and **** &lt; 0.0001, as calculated by ANOVA test.</p>
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<p>SAHA/5-AZA enhances MT2A expression more strongly than SAHA. (<b>A</b>) mRNA expression of MT1E and MT2A was evaluated by qRT-PCR by using the SYBR Green assay (Applied Biosystems, Carlsbad, CA, USA) with a StepOne instrument and 7500 Fast Real-Time PCR System (Applied Biosystems). The data are expressed relative to the reference gene (βActin). Histograms represent the mRNA expression levels of MT1E and MT2A. Data are represented as the mean relative to the control plus SD. **** <span class="html-italic">p</span> &lt; 0.0001; (<b>B</b>) To evaluate the role of zinc on acetylation, ZnCl<sub>2</sub> (50 mM) was added to PaCa44 cells treated with SAHA, 5-AZA (AZA), SAHA/AZA combination or untreated (CT) and acetylated Histone H3 was investigated by western blot analysis. Histograms represent the mean plus SD of the densitometric analysis of the ratio of Acetylate Histone H3/Histone H3; <span class="html-italic">p</span>-value: ** &lt; 0.01; *** &lt; 0.001 and **** &lt; 0.0001, as calculated by ANOVA test. (<b>C</b>) cell survival was assessed by Trypan blue assay in PaCa44 cell line treated with SAHA, 5-AZA (AZA), SAHA/AZA combination or untreated (CT) in the presence or in the absence of ZnCl<sub>2</sub>. The histograms represent the percentage of cell viability relative to the control; data are shown as the mean plus SD of more than three experiments <span class="html-italic">p</span>-value: ** &lt; 0.01 and **** &lt; 0.0001, as calculated by ANOVA test. (<b>D</b>) Cleaved Caspase 3 (cl Casp3) was evaluated by Western Blot analysis in PaCa44 treated as described in panel B. Histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between cleaved Capase3 and β-Actin; <span class="html-italic">p</span>-value: ** &lt; 0.01; and **** &lt; 0.0001, as calculated by ANOVA test.</p>
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<p>SAHA/5-AZA increases acetylation and proteasomal degradation of mutp53. (<b>A</b>,<b>B</b>) Acetylation of p53 as evaluated (<b>A</b>) by immunoprecipitation of p53 and blotting with an antibody against acetylated lysine; <span class="html-italic">p</span>-value: *** &lt; 0.001 and (<b>B</b>) by western blot by using an anti-acetyl 373/382 p53 antibody in SAHA or SAHA/AZA-treated or untreated PaCa44 cells. GAPDH was used as the house-keeping control. Histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between acetyl p53/p53 and acetyl p53 and GAPDH; <span class="html-italic">p</span>-value: **** &lt; 0.0001, as calculated by ANOVA test. (<b>C</b>) p53 was evaluated by Western Blot analysis in SAHA or SAHA/AZA and AZA-treated or untreated (CT) PaCa44 and PT45 cells. GAPDH and β-Actin were used as loading controls. Histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53 and loading controls; <span class="html-italic">p</span>-value: ** &lt; 0.01; *** &lt; 0.001; and **** &lt; 0.0001, as calculated by ANOVA test. (<b>D</b>) proteasomal degradation of mutp53 by SAHA and SAHA/5-AZA as evaluated by Bortezomib (BZ) supplementation (10 nM), as reported in MM. β-Actin was used as the loading control. Histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53 and β-Actin; <span class="html-italic">p</span>-value: *** &lt; 0.001; and **** &lt; 0.0001, as calculated by ANOVA test. (<b>E</b>) p53 expression as evaluated by western blot in PaCa44 cells, transfected with <span class="html-italic">p53 K381/382R</span> vector or with empty vector (EV) and treated with SAHA/AZA combination or left untreated. β-Actin was used as loading control. Histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53 and β-Actin; <span class="html-italic">p</span>-value: ** &lt; 0.01; *** &lt; 0.001; and **** &lt; 0.0001, as calculated by ANOVA test.</p>
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<p>SAHA/5-AZA interferes with the positive crosstalk between c-myc and p53. (<b>A</b>) p21, c-Myc and p53 were evaluated by western blot analysis in PaCa44 and PT45 cells treated with SAHA, 5-AZA (AZA), SAHA/AZA combination or untreated (CT), as above reported. β-Actin and GAPDH were used as the loading controls. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio of p21/β-Actin, c-Myc/β-Actin and p53/β-Actin for PaCa44 cells and as the ratio of p21/GAPDH and c-Myc/GAPDH for PT45; <span class="html-italic">p</span>-value: * &lt; 0.05; ** &lt; 0.01; *** &lt; 0.001; and **** &lt; 0.0001, as calculated by ANOVA test. (<b>B</b>,<b>C</b>) PaCa44 cells, transfected with p53 K381/382R vector or with empty vector (EV) were treated with SAHA/AZA combination or untreated and p21 (<b>B</b>) and c-Myc (<b>C</b>) were evaluated by western blot. GAPDH was used as the loading control. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p21/GAPDH and c-Myc/GAPDH; <span class="html-italic">p</span>-value: *** &lt; 0.001; and **** &lt; 0.0001, as calculated by ANOVA test. (<b>D</b>) c-Myc expression level following Bortezomib (BZ) supplementation, added during the last 12 h of treatments. β-Actin was used as loading control. Histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53/β-Actin and c-Myc/β-Actin; <span class="html-italic">p</span>-value: **** &lt; 0.0001, as calculated by ANOVA test. (<b>E</b>) PT45 cells were p53-silenced (Sip53) or treated or with empty vector (EV) and p53, and c-Myc expression was evaluated by western blot analysis. GAPDH was used as the loading control. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53/GAPDH and c-Myc/GAPDH; <span class="html-italic">p</span>-value: ** &lt; 0.01 and *** &lt; 0.001; as calculated by Student’s <span class="html-italic">t</span>-test. (<b>F</b>) p53 was evaluated in PT45 cells treated with c-Myc inhibitor (i c-Myc) (50 μM) for 48 h by western blot analysis. GAPDH was used as the loading control. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53/GAPDH and c-Myc/GAPDH; <span class="html-italic">p</span>-value: **** &lt; 0.0001; as calculated by Student’s <span class="html-italic">t</span>-test.</p>
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<p>SAHA/5-AZA downregulates BRCA-1 and induces a strong DNA damage in pancreatic cancer cells. (<b>A</b>) BRCA1 and γH2AX were evaluated by western blot in PaCa44 and PT45 cells treated with SAHA, 5-AZA (AZA), SAHA/AZA combination or untreated (CT), as above reported. GAPDH was used as loading control. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio of BRCA1/GAPDH and γH2AX GAPDH; <span class="html-italic">p</span>-value: *** &lt; 0.001; and **** &lt; 0.0001, as calculated by ANOVA test. (<b>B</b>) PaCa44 cells, transfected with <span class="html-italic">p53 K381/382R vector</span> or with empty vector (EV) were treated with SAHA/AZA combination or untreated and BRCA1 was evaluated by western blot. β-Actin was used as the loading control. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between BRCA1/β-Actin; <span class="html-italic">p</span>-value: * &lt; 0.05; ** &lt; 0.01; *** &lt; 0.001; and **** &lt; 0.0001, as calculated by ANOVA test (<b>C</b>) PaCa44 cells were p53-silenced (Sip53) or treated with empty vector (EV) and p53 and BRCA1 expression was evaluated by western blot analysis. GAPDH was used as the loading control. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53/GAPDH and BRCA1/GAPDH; <span class="html-italic">p</span>-value: *** &lt; 0.001; as calculated by Student’s <span class="html-italic">t</span>-test. (<b>D</b>) BRCA1 and γH2AX were evaluated in PT45 cells treated with c-Myc inhibitor (i c-Myc) (50 μM) for 48 h by western blot analysis. GAPDH was used as the loading control. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53/GAPDH and c-Myc/GAPDH; <span class="html-italic">p</span>-value: *** &lt; 0.001 and **** &lt; 0.0001; as calculated by Student’s <span class="html-italic">t</span>-test. (<b>E</b>) Proteasomal degradation of BRCA1 evaluated by Bortezomib (BZ) supplementation, added for the last 12 h of treatments. β-Actin was used as the loading control. The histograms represent the mean plus SD of the densitometric analysis derived from three experiments and expressed as the ratio between p53/β-Actin and BRCA-1/β-Actin; <span class="html-italic">p</span>-value: * &lt; 0.05; ** &lt; 0.01; **** &lt; 0.0001, as calculated by ANOVA test.</p>
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21 pages, 9097 KiB  
Review
To Erase or Not to Erase: Non-Canonical Catalytic Functions and Non-Catalytic Functions of Members of Histone Lysine Demethylase Families
by Elena Di Nisio, Valeria Manzini, Valerio Licursi and Rodolfo Negri
Int. J. Mol. Sci. 2024, 25(13), 6900; https://doi.org/10.3390/ijms25136900 - 24 Jun 2024
Cited by 1 | Viewed by 1274
Abstract
Histone lysine demethylases (KDMs) play an essential role in biological processes such as transcription regulation, RNA maturation, transposable element control, and genome damage sensing and repair. In most cases, their action requires catalytic activities, but non-catalytic functions have also been shown in some [...] Read more.
Histone lysine demethylases (KDMs) play an essential role in biological processes such as transcription regulation, RNA maturation, transposable element control, and genome damage sensing and repair. In most cases, their action requires catalytic activities, but non-catalytic functions have also been shown in some KDMs. Indeed, some strictly KDM-related proteins and some KDM isoforms do not act as histone demethylase but show other enzymatic activities or relevant non-enzymatic functions in different cell types. Moreover, many studies have reported on functions potentially supported by catalytically dead mutant KDMs. This is probably due to the versatility of the catalytical core, which can adapt to assume different molecular functions, and to the complex multi-domain structure of these proteins which encompasses functional modules for targeting histone modifications, promoting protein–protein interactions, or recognizing nucleic acid structural motifs. This rich modularity and the availability of multiple isoforms in the various classes produced variants with enzymatic functions aside from histone demethylation or variants with non-catalytical functions during the evolution. In this review we will catalog the proteins with null or questionable demethylase activity and predicted or validated inactive isoforms, summarizing what is known about their alternative functions. We will then go through some experimental evidence for the non-catalytical functions of active KDMs. Full article
(This article belongs to the Collection Feature Papers in Molecular Oncology)
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Figure 1
<p>Schematic representation of the predicted and validated transcripts for KDM4 and KDM5 genes (from NCBI Gene RefSeq database). Each of these transcripts could generate different predicted or validated protein isoforms with or without known protein domains, resulting in non-truncated or truncated isoforms. Among the truncated protein isoforms, we highlighted the absence of JmjN, JmjC, or both of these domains, using orange, purple, and blue, respectively. Green arrows show the translational start sites for transcripts giving rise to shorter protein isoforms. For KDM4A, KDM4D, KDM5A, KDM5C, and KDM5D, no truncated protein isoforms were predicted. More details are in <a href="#app1-ijms-25-06900" class="html-app">Table S1</a>. <a href="#ijms-25-06900-f001" class="html-fig">Figure 1</a> was created using R v4.3.1 and ggplot2 package v3.5.1. Final editing with Inkscape 1.3.2.</p>
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<p>Model of the competitive action of the KDM5B-NTT isoform on the KDM5B-PLU1 targets. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>.</p>
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<p>Schematic representation of different protein domains that confer demethylase activity or determine demethylase-independent functions, including other enzymatic activities, which in turn regulate many biological processes. Created with <a href="http://Biorender.com" target="_blank">Biorender.com</a>.</p>
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15 pages, 2453 KiB  
Article
TNFα Induces DNA and Histone Hypomethylation and Pulmonary Artery Smooth Muscle Cell Proliferation Partly via Excessive Superoxide Formation
by Patrick Crosswhite and Zhongjie Sun
Antioxidants 2024, 13(6), 677; https://doi.org/10.3390/antiox13060677 - 31 May 2024
Viewed by 880
Abstract
Objective: The level of tumor necrosis factor-α (TNF-α) is upregulated during the development of pulmonary vascular remodeling and pulmonary hypertension. A hallmark of pulmonary arterial (PA) remodeling is the excessive proliferation of PA smooth muscle cells (PASMCs). The purpose of this study is [...] Read more.
Objective: The level of tumor necrosis factor-α (TNF-α) is upregulated during the development of pulmonary vascular remodeling and pulmonary hypertension. A hallmark of pulmonary arterial (PA) remodeling is the excessive proliferation of PA smooth muscle cells (PASMCs). The purpose of this study is to investigate whether TNF-α induces PASMC proliferation and explore the potential mechanisms. Methods: PASMCs were isolated from 8-week-old male Sprague-Dawley rats and treated with 0, 20, or 200 ng/mL TNF-α for 24 or 48 h. After treatment, cell number, superoxide production, histone acetylation, DNA methylation, and histone methylation were assessed. Results: TNF-α treatment increased NADPH oxidase activity, superoxide production, and cell numbers compared to untreated controls. TNF-α-induced PASMC proliferation was rescued by a superoxide dismutase mimetic tempol. TNF-α treatment did not affect histone acetylation at either dose but did significantly decrease DNA methylation. DNA methyltransferase 1 activity was unchanged by TNF-α treatment. Further investigation using QRT-RT-PCR revealed that GADD45-α, a potential mediator of DNA demethylation, was increased after TNF-α treatment. RNAi inhibition of GADD45-α alone increased DNA methylation. TNF-α impaired the epigenetic mechanism leading to DNA hypomethylation, which can be abolished by a superoxide scavenger tempol. TNF-α treatment also decreased H3-K4 methylation. TNF-α-induced PASMC proliferation may involve the H3-K4 demethylase enzyme, lysine-specific demethylase 1 (LSD1). Conclusions: TNF-α-induced PASMC proliferation may be partly associated with excessive superoxide formation and histone and DNA methylation. Full article
(This article belongs to the Special Issue Understanding Oxidative Stress in Cardiovascular Disorders)
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Figure 1
<p><b>TNF-α treatment increases superoxide production in PASMCs.</b> PASMCs were treated with recombinant TNF-α (rTNF-α) for 24 or 48 h. The cells were then incubated with dihydroethidium (DHE), rinsed, and the nuclear stain DAPI was applied. Cell lysates were also collected and NADPH oxidase activity was measured using a lucigenin assay. (<b>A</b>) Photos showing representative superoxide production (<b>red</b>), nuclear staining (<b>blue</b>), and the merged images at 24 h of treatment (200×). (<b>B</b>) Photos showing representative superoxide production (<b>red</b>), nuclear staining (<b>blue</b>), and the merged images at 48 h of treatment (100×). (<b>C</b>) Quantification of superoxide production in PASMCs at 24 h of treatment. (<b>D</b>) Quantification of superoxide production in PASMCs at 48 h of treatment. (<b>E</b>) NADPH oxidase activity at 24 h of treatment of treatment. <span class="html-italic">n</span> = 3 independent replicates. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 vs. untreated.</p>
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<p><b>TNF-α treatment increases PASMC proliferation</b>. (<b>A</b>) PASMCs were treated with rTNF-α for 24 and 48 h and cell proliferation was assessed using two different methods. (<b>B</b>) The average number of cells was counted in each photographic field (5 photos per well, 3 wells/treatment). (<b>C</b>) The number of cells counted using an automated Bio-Rad cell counter. <span class="html-italic">n</span> = 3 independent replicates. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. 24 h untreated; <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05 and <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01 vs. 48 h untreated. Photos are shown at 200×.</p>
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<p><b>Tempol prevents TNF-α induced superoxide increase and PASMC proliferation.</b> PASMCs were pre-treated with or without tempol (1 mM) for 24 h followed by treatment with rTNF-α for 24 h. (<b>A</b>) Photos from the DHE staining, as described previously, showing the superoxide production (red), nuclear staining (blue), and merged images. (<b>B</b>) Superoxide level. (<b>C</b>) Cell proliferation assessed using an automated cell counter. Tempol was dissolved in DMEM (vehicle) immediately before adding to cell culture dishes. <span class="html-italic">n</span> = 3 independent replicates. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001 vs. Vehicle 0 ng. Photos are shown at 100×.</p>
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<p><b>TNF-α treatment decreases DNA methylation in PASMCs</b>. DNA was purified from PASMCs treated with or without recombinant TNF-α (rTNF-α) for 24 or 48 h and the global DNA methylation was measured using an ELISA-based microplate assay that bound methylated DNA. (<b>A</b>) DNA methylation after 24 h of treatment. (<b>B</b>) DNA methylation after 48 h of treatment. (<b>C</b>) DNMT1 activity. (<b>D</b>) Cells were then pre-treated with tempol (1 mM) for 24 h prior to rTNF-α treatment for 24 h. DNA methylation was measured using the same method as described above. <span class="html-italic">n</span> = 3 independent replicates. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 vs. untreated. ^ <span class="html-italic">p</span> &lt; 0.05 vs. 200 ng TNF. <sup>∆</sup> <span class="html-italic">p</span> &lt; 0.05 &lt; 0.01 vs. (<b>A</b>); <sup>+</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>++</sup> <span class="html-italic">p</span> &lt; 0.01 vs. (<b>D</b>); <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. (<b>B</b>,<b>C</b>).</p>
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<p><b>GADD45-α siRNA does not prevent the TNF-α-induced decrease in DNA methylation.</b> (<b>A</b>) Real-time reverse transcription PCR was used to determine GADD45-α mRNA in PASMCs treated with rTNF-α for 24 or 48 h. PASMCs were treated with GADD45-α siRNA, negative siRNA, or lipofectamine only for 24 h prior to rTNF-α treatment for 24 h. <sup>∆</sup> <span class="html-italic">p</span> &lt; 0.05, <sup>∆∆</sup> <span class="html-italic">p</span> &lt; 0.01 vs. untreated; (<b>B</b>) Cell proliferation. (<b>C</b>) DNA methylation. <span class="html-italic">n</span> = 3 independent replicates. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 vs. GADD45 RNAi + 0 ng.</p>
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<p>H3-K4 methylation is decreased in rTNF-α treated PASMCs, which is not prevented by pargyline, an LSD1 demethylase inhibitor. (<b>A</b>) H3-K4 methylation was measured in PASMCs treated with rTNF-α for 24 or 48 h. (<b>B</b>) Cell proliferation was determined in PASMCs co-treated with pargyline, a LSD1 inhibitor, and rTNF-α. (<b>C</b>) LSD1 activity was determined in PASMCs co-treated with pargyline and rTNF-α. <span class="html-italic">n</span> = 3 independent replicates. * <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 vs. Control. ^ <span class="html-italic">p</span> &lt; 0.05 vs. 48 h Untreated.</p>
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<p>Schematic diagram illustrating the epigenetic pathway in TNF-α-induced PASMC proliferation.</p>
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11 pages, 1473 KiB  
Review
LSD2 Is an Epigenetic Player in Multiple Types of Cancer and Beyond
by Hyun-Min Kim and Zifei Liu
Biomolecules 2024, 14(5), 553; https://doi.org/10.3390/biom14050553 - 3 May 2024
Viewed by 1898
Abstract
Histone demethylases, enzymes responsible for removing methyl groups from histone proteins, have emerged as critical players in regulating gene expression and chromatin dynamics, thereby influencing various cellular processes. LSD2 and LSD1 have attracted considerable interest among these demethylases because of their associations with [...] Read more.
Histone demethylases, enzymes responsible for removing methyl groups from histone proteins, have emerged as critical players in regulating gene expression and chromatin dynamics, thereby influencing various cellular processes. LSD2 and LSD1 have attracted considerable interest among these demethylases because of their associations with cancer. However, while LSD1 has received significant attention, LSD2 has not been recognized to the same extent. In this study, we conduct a comprehensive comparison between LSD2 and LSD1, with a focus on exploring LSD2’s implications. While both share structural similarities, LSD2 possesses unique features as well. Functionally, LSD2 shows diverse roles, particularly in cancer, with tissue-dependent roles. Additionally, LSD2 extends beyond histone demethylation, impacting DNA methylation, cancer cell reprogramming, E3 ubiquitin ligase activity and DNA damage repair pathways. This study underscores the distinct roles of LSD2, providing insights into their contributions to cancer and other cellular processes. Full article
(This article belongs to the Special Issue Histone Modifications in Health and Diseases)
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<p>Versatile roles of LSD2 from cancer implications to epigenetic regulation. LSD2 has been implicated in various cancers, either promoting or suppressing human cancers. Additionally, LSD2 is involved in establishing DNA methylation imprints during oogenesis, as well as epigenetic reprogramming during tumorigenesis. Moreover, <span class="html-italic">C. elegans</span> LSD2 homolog AMX-1 has been associated with non-transgenerational fertility defects and DNA damage repair. Furthermore, LSD2 is known for its E3 ubiquitin ligase activities, which contribute to the intricate regulation of specific target genes.</p>
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<p>Schematic representations of LSD1 and LSD2. At the top, human and <span class="html-italic">C. elegans</span> LSD1 are shown, while at the bottom, the LSD2 homologs are displayed. Most domains are well conserved across the species, except for the zinc finger domain, which is missing in the <span class="html-italic">C. elegans</span> LSD2 homolog suggesting a conserved function across species [<a href="#B12-biomolecules-14-00553" class="html-bibr">12</a>,<a href="#B15-biomolecules-14-00553" class="html-bibr">15</a>].</p>
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<p>Schematic binding of LSD2 with nucleosome and NPAC. Left: the catalytic cavity in the amine oxidase (AO) domain serves as the first substrate-binding site, binding to the N-terminus of histone H3K4 for demethylation. The linker region forms the second binding site away from the catalytic cavity. This additional interaction is crucial for histone H3 recognition and essential for the demethylation activity of LSD2. Right: NPAC tetramer binds to LSD2-Nucleosome complex. Not all nucleosomes are shown for simplicity purposes. The image was based on the previous reports [<a href="#B11-biomolecules-14-00553" class="html-bibr">11</a>,<a href="#B16-biomolecules-14-00553" class="html-bibr">16</a>].</p>
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18 pages, 8366 KiB  
Article
Isorhamnetin Alleviates Mitochondrial Injury in Severe Acute Pancreatitis via Modulation of KDM5B/HtrA2 Signaling Pathway
by Xiaojuan Li, Tao Wang, Qilong Zhou, Fan Li, Ting Liu, Kun Zhang, Ao Wen, Lijuan Feng, Xiaoling Shu, Simin Tian, Yijiang Liu, Yu Gao, Qing Xia, Guang Xin and Wen Huang
Int. J. Mol. Sci. 2024, 25(7), 3784; https://doi.org/10.3390/ijms25073784 - 28 Mar 2024
Cited by 2 | Viewed by 1424
Abstract
Severe acute pancreatitis (SAP), a widespread inflammatory condition impacting the abdomen with a high mortality rate, poses challenges due to its unclear pathogenesis and the absence of effective treatment options. Isorhamnetin (ISO), a naturally occurring flavonoid, demonstrates robust antioxidant and anti-inflammatory properties intricately [...] Read more.
Severe acute pancreatitis (SAP), a widespread inflammatory condition impacting the abdomen with a high mortality rate, poses challenges due to its unclear pathogenesis and the absence of effective treatment options. Isorhamnetin (ISO), a naturally occurring flavonoid, demonstrates robust antioxidant and anti-inflammatory properties intricately linked to the modulation of mitochondrial function. However, the specific protective impact of ISO on SAP remains to be fully elucidated. In this study, we demonstrated that ISO treatment significantly alleviated pancreatic damage and reduced serum lipase and amylase levels in the mouse model of SAP induced by sodium taurocholate (STC) or L-arginine. Utilizing an in vitro SAP cell model, we found that ISO co-administration markedly prevented STC-induced pancreatic acinar cell necrosis, primarily by inhibiting mitochondrial ROS generation, preserving ATP production, maintaining mitochondrial membrane potential, and preventing the oxidative damage and release of mitochondrial DNA. Mechanistically, our investigation identified that high-temperature requirement A2 (HtrA2) may play a central regulatory role in mediating the protective effect of ISO on mitochondrial dysfunction in STC-injured acinar cells. Furthermore, through an integrated approach involving bioinformatics analysis, molecular docking analysis, and experimental validation, we uncovered that ISO may directly impede the histone demethylation activity of KDM5B, leading to the restoration of pancreatic HtrA2 expression and thereby preserving mitochondrial function in pancreatic acinar cells following STC treatment. In conclusion, this study not only sheds new light on the intricate molecular complexities associated with mitochondrial dysfunction during the progression of SAP but also underscores the promising value of ISO as a natural therapeutic option for SAP. Full article
(This article belongs to the Special Issue Natural Products as Multitarget Agents in Human Diseases)
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<p>Protective effects of ISO against STC-induced SAP. (<b>A</b>) Intraperitoneal administration of saline or ISO (10, 30 mg/kg) one hour after SAP induction. (<b>B</b>) In the STC-induced SAP mouse model, the survival rate of SAP mice was calculated at different times (0, 24, 48, 72 h). (<b>C</b>) Representative images of freshly harvested pancreatic tissues. (<b>D</b>) Ratio of pancreatic weight to body weight at the time of sampling. <span class="html-italic">n</span> = 5. (<b>E</b>,<b>F</b>) Levels of serum amylase and lipase 24 h after SAP induction. <span class="html-italic">n</span> = 5. (<b>G</b>) Representative H&amp;E images of pancreatic tissue sections, scale bars = 50 μm. (<b>H</b>) Histological scoring of inflammatory infiltration, edema and necrosis in pancreatic tissues to evaluate the extent of pancreatic injury. <span class="html-italic">n</span> = 5. (<b>I</b>) Representative images of primary pancreatic acinar cells stained with PI (red) and Hoechst 33342 (blue), scale bars = 50 μm. (<b>J</b>) Quantification of the percentage of PI-positive primary pancreatic acinar cells using Image J, <span class="html-italic">n</span> = 5. All data are presented as mean ± SD. Statistical significance was assessed using one-way ANOVA followed by Tukey’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>ISO-inhibited STC-induced oxidative stress and mitochondrial dysfunction. (<b>A</b>) Pharmacological target diagram of ISO. (<b>B</b>) Volcano plot of DEGs identified from the NCBI GEO database. (<b>C</b>) Venn diagram illustrating the targets of ISO in SAP. (<b>D</b>) GO enrichment analysis. (<b>E</b>) Bubble plot depicting the top 25 pathways based on KEGG enrichment analysis. (<b>F</b>) DCFH-DA fluorescence staining for measuring intracellular ROS levels in primary pancreatic acinar cells, scale bars = 20 μm, <span class="html-italic">n</span> = 5. (<b>G</b>) MitoSOX fluorescence staining for assessing mitochondrial ROS levels in primary pancreatic acinar cells, <span class="html-italic">n</span> = 5. (<b>H</b>) TMRE fluorescence staining to assess ΔΨm in primary pancreatic acinar cells, scale bars = 20 μm, <span class="html-italic">n</span> = 5. (<b>I</b>) ATP assay kit used to measure ATP levels in primary pancreatic acinar cells. <span class="html-italic">n</span> = 5. (<b>J</b>) qPCR analysis to determine the ratio of mtDNA to nDNA in the cytoplasm. <span class="html-italic">n</span> = 5. (<b>K</b>) ELISA measurement of Ox-mtDNA concentration in primary pancreatic acinar cells. <span class="html-italic">n</span> = 5. All data are presented as mean ± SD. Statistical significance was assessed using one-way ANOVA followed by Tukey’s multiple comparison 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>
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<p>HtrA2 is essential for ISO’s protective effect on STC-induced mitochondrial dysfunction. (<b>A</b>,<b>B</b>) Western blot analysis of HtrA2 protein expression in pancreas and primary pancreatic acinar cells, <span class="html-italic">n</span> = 3. (<b>C1</b>,<b>C2</b>) Representative images of primary pancreatic acinar cells stained with PI (red) and Hoechst 33342 (blue), and quantification of the percentage of PI-positive primary pancreatic acinar cells using Image J, scale bars = 50 μm., <span class="html-italic">n</span> = 5. (<b>D</b>) TMRE fluorescence staining to assess ΔΨm in primary pancreatic acinar cells, scale bars = 20 μm, <span class="html-italic">n</span> = 5. (<b>E</b>) ATP assay kit used to measure ATP levels in primary pancreatic acinar cells, <span class="html-italic">n</span> = 5. (<b>F</b>) DCFH-DA fluorescence staining for measuring intracellular ROS levels in primary pancreatic acinar cells, scale bars = 20 μm, <span class="html-italic">n</span> = 5. (<b>G</b>) MitoSOX fluorescence staining for assessing mitochondrial ROS levels in primary pancreatic acinar cells, scale bars = 20 μm, <span class="html-italic">n</span> = 5. (<b>H</b>) ELISA measurement of Ox-mtDNA concentration in primary pancreatic acinar cells, <span class="html-italic">n</span> = 5. (<b>I</b>) qPCR analysis to determine the ratio of mtDNA to nDNA in the cytoplasm, <span class="html-italic">n</span> = 5. All data are presented as mean ± SD. Statistical significance was assessed using one-way ANOVA followed by Tukey’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>KDM5B suppressed expression of HtrA2. (<b>A</b>) Intersection between predicted transcription factors regulating HtrA2 and AP related genes. (<b>B</b>) Western blot analysis of KDM5B protein expression in pancreas, <span class="html-italic">n</span> = 3. (<b>C</b>) Western blot analysis of KDM5B protein expression in primary pancreatic acinar cells, <span class="html-italic">n</span> = 3. (<b>D</b>) The mRNA level of HtrA2 was detected by quantitative RT-PCR, <span class="html-italic">n</span> = 5. (<b>E</b>) Immunofluorescence staining for detecting HtrA2 protein expression in primary pancreatic acinar cells, scale bars = 100 μm, <span class="html-italic">n</span> = 5. (<b>F</b>) ATP assay kit used to measure ATP levels in primary pancreatic acinar cells, <span class="html-italic">n</span> = 5. (<b>G</b>) MitoSOX fluorescence staining for assessing mitochondrial ROS levels in primary pancreatic acinar cells, scale bars = 20 μm, <span class="html-italic">n</span> = 5. (<b>H</b>) Representative images of primary pancreatic acinar cells stained with PI (red) and Hoechst 33342 (blue), scale bars = 50 μm. (<b>I</b>) Quantification of the percentage of PI-positive primary pancreatic acinar cells using Image J, <span class="html-italic">n</span> = 5. All data are presented as mean ± SD. Statistical significance was assessed using one-way ANOVA followed by Tukey’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>ISO functions as a potential inhibitor for KDM5B. (<b>A</b>) Western blot analysis of ISO’s impact on H3K4me3 protein expression, <span class="html-italic">n</span> = 3. (<b>B</b>) Representative visualized molecular binding model of ISO and KDM5B. (<b>C</b>,<b>D</b>) Representative images of primary pancreatic acinar cells stained with PI (red) and Hoechst 33342 (blue), and quantification of the percentage of PI-positive primary pancreatic acinar cells using Image J, scale bars = 50 μm, <span class="html-italic">n</span> = 5. (<b>E</b>) The mRNA level of HtrA2 was detected by quantitative RT-PCR, <span class="html-italic">n</span> = 5. All data are presented as mean ± SD. Statistical significance was assessed using one-way ANOVA followed by Tukey’s multiple comparison test. *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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12 pages, 4513 KiB  
Article
5-AZA Upregulates SOCS3 and PTPN6/SHP1, Inhibiting STAT3 and Potentiating the Effects of AG490 against Primary Effusion Lymphoma Cells
by Michele Di Crosta, Andrea Arena, Rossella Benedetti, Maria Saveria Gilardini Montani and Mara Cirone
Curr. Issues Mol. Biol. 2024, 46(3), 2468-2479; https://doi.org/10.3390/cimb46030156 - 14 Mar 2024
Viewed by 1391
Abstract
Epigenetic modifications, including aberrant DNA methylation occurring at the promoters of oncogenes and oncosuppressor genes and histone modifications, can contribute to carcinogenesis. Aberrant methylation mediated by histone methylatransferases, alongside histones, can affect methylation of proteins involved in the regulation of pro-survival pathways such [...] Read more.
Epigenetic modifications, including aberrant DNA methylation occurring at the promoters of oncogenes and oncosuppressor genes and histone modifications, can contribute to carcinogenesis. Aberrant methylation mediated by histone methylatransferases, alongside histones, can affect methylation of proteins involved in the regulation of pro-survival pathways such as JAK/STAT and contribute to their activation. In this study, we used DNA or histone demethylating agents, 5-Azacytidine (5-AZA) or DS-3201 (valemetostat), respectively, to treat primary effusion lymphoma (PEL) cells, alone or in combination with AG490, a Signal transducer and activator of transcription 3 (STAT3) inhibitor. Cell viability was investigated by trypan blue assay and FACS analysis. The molecular changes induced by 5-AZA and/or AG490 treatments were investigated by Western blot analysis, while cytokine release by PEL cells treated by these drugs was evaluated by Luminex. Statistical analyses were performed with Graphpad Prism® software (version 9) and analyzed by Student’s t test or a nonparametric one-way ANOVA test. The results obtained in this study suggest that 5-AZA upregulated molecules that inhibit STAT3 tyrosine phosphorylation, namely Suppressor of Cytokine Signaling 3 (SOCS3) and tyrosine–protein phosphatase non-receptor type (PTPN) 6/Src homology region 2 domain-containing phosphatase-1 (SHP-1), reducing STAT3 activation and downregulating several STAT3 pro-survival targets in PEL cells. As this lymphoma is highly dependent on the constitutive activation of STAT3, 5-AZA impaired PEL cell survival, and when used in combination with AG490 JAK2/STAT3 inhibitor, it potentiated its cytotoxic effect. Differently from 5-AZA, the inhibition of the EZH1/2 histone methyltransferase by DS-3201, reported to contribute to STAT3 activation in other cancers, slightly affected STAT3 phosphorylation or survival in PEL cells, either alone or in combination with AG490. This study suggests that 5-AZA, by upregulating the expression level of SOCS3 and PTPN6/SHP1, reduced STAT3 activation and improved the outcome of treatment targeting this transcription factor in PEL cells. Full article
(This article belongs to the Section Biochemistry, Molecular and Cellular Biology)
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<p>5-AZA induces a cytotoxic effect in PEL cells in correlation with the inhibition of STAT3 and its targets. BC3 and BCBL-1 cell lines were treated with 5-Azacitidine (5-AZA) for 48 h. (<b>A</b>) Cell survival was evaluated by trypan blue exclusion assay. The histograms represent the mean of the percentage of cell viability relative to the control plus S.D. (<b>B</b>) FACS profiles and percentage of sub-G1 events as evaluated by FACS analysis in BC3 and BCBL-1 cells. One representative experiment out of three is shown. (<b>C</b>) Protein expression level of pSTAT3, STAT3, c-MYC, SOCS3, PTPN6, JACK2, and DNMT1, as evaluated by Western blot analysis. GAPDH was used as a loading control, and one representative experiment is shown. The histograms represent the densitometric analysis of specific protein and the appropriate control from three experiments. Data are represented as the mean plus S.D. <span class="html-italic">p</span>-value: * &lt; 0.05; ** &lt; 0.01; *** &lt; 0.001; **** &lt; 0.0001 and ns means no significance.</p>
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<p>5-AZA further inhibits STAT3 activity in PEL cells treated by AG490. BC3 and BCBL-1 cell lines were treated singly or in combination with 5-Azacitidine (5-AZA) and AG490. (<b>A</b>) Cell survival was estimated by trypan blue exclusion assay after treatment with AG490 (100 μM), 5-AZA (20 nM), or a combination of both. The histograms represent the mean of the percentage of cell viability relative to the control plus S.D. (<b>B</b>) Sub-G1 events as evaluated via FACS analysis in BC3 and BCBL-1 cells. The histograms represent the mean of the percentage of sub G1 of three independent experiments. (<b>C</b>) Protein expression level of pSTAT3, STAT3, c-MYC, HSP27, Cyclin D1, as evaluated by Western blot analysis. GAPDH was used as a loading control, and one representative experiment is shown. The histograms represent the densitometric analysis of specific protein and the appropriate control from three experiments. Data are represented as the mean plus S.D. <span class="html-italic">p</span>-value: * &lt; 0.05; ** &lt; 0.01; *** &lt; 0.001; and **** &lt; 0.0001, ns means no significance.</p>
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<p>Effect of AG490, 5-AZA, and their combination on cytokine and cathepsin S release. The BC3 cell line was treated by AG490, 5-AZA or with 5-AZA and AG490 combination. The amount in pg/mL of IL-6, IL-10, VEGF and cathepsin S, as evaluated by Luminex, is shown. Means ± standard deviation (SD) of three independent experiments are shown. <span class="html-italic">p</span>-values: * &lt; 0.05; ** &lt; 0.01; *** &lt; 0.001; and **** &lt; 0.0001.</p>
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<p>Valemetostat (DS-3201) induces mild cytotoxicity in PEL cells alone or in combination with AG490. BC3 and BCBL-1 cell lines were treated singly or in combination with valemetostat (DS-3201) and AG490. (<b>A</b>) Cell survival was estimated by trypan blue exclusion assay after treatment with valemetostat (DS-3201) (1–2 μM) for 48 h. The histograms represent the mean of the percentage of cell viability relative to the control plus S.D. (<b>B</b>) Protein expression level of pSTAT3, STAT3, and c-MYC, as evaluated by Western blot analysis. GAPDH was used as a loading control, and one representative experiment is shown. The histograms represent the densitometric analysis of specific proteins and the appropriate control from three experiments. Data are represented as means plus S.D. (<b>C</b>) Cell survival was estimated by trypan blue exclusion assay after treatment with valemetostat (DS-3201) (1 μM) and AG 490 (100 μM). The histograms represent the mean of the percentage of cell viability relative to the control plus S.D. <span class="html-italic">p</span>-value: *** &lt; 0.001; and **** &lt; 0.0001, ns means no significance.</p>
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10 pages, 1738 KiB  
Brief Report
Expression of Immunotherapy Target PRAME in Cancer Correlates with Histone H3 Acetylation and Is Unrelated to Expression of Methylating (DMNT3A/3B) and Demethylating (TET1) Enzymes
by Maciej Kaczorowski, Jerzy Lasota, Krzysztof Dudek, Bartosz Małkiewicz, Markku Miettinen and Agnieszka Hałoń
J. Clin. Med. 2024, 13(6), 1554; https://doi.org/10.3390/jcm13061554 - 8 Mar 2024
Cited by 1 | Viewed by 1324
Abstract
Background/Objectives: Preferentially expressed antigen in melanoma (PRAME), a member of the cancer testis antigen family, is a promising target for cancer immunotherapy. Understanding the epigenetic mechanisms involved in the regulation of PRAME expression might be crucial for optimizing anti-PRAME treatments. Methods: Three malignancies [...] Read more.
Background/Objectives: Preferentially expressed antigen in melanoma (PRAME), a member of the cancer testis antigen family, is a promising target for cancer immunotherapy. Understanding the epigenetic mechanisms involved in the regulation of PRAME expression might be crucial for optimizing anti-PRAME treatments. Methods: Three malignancies of different lineages (sinonasal melanoma, testicular seminoma, and synovial sarcoma), in which immunohistochemical (IHC) reactivity for PRAME is a common yet variable feature, were studied. The expression of PRAME, ten-eleven translocation demethylase 1 (TET1), and DNA methyltransferase (DNMT) 3A and 3B were evaluated using immunohistochemistry. Moreover, the expression of two epigenetic marks, 5-hydroxymethylcytosine (5hmC) and histone 3 acetylation (H3ac), was tested. Results: All PRAME-positive tumors expressed medium-to-high levels of H3ac but differed considerably with respect to other markers. In seminomas, PRAME expression correlated with TET1, but in melanomas and synovial sarcomas, it correlated with both DNMTs and DNMT3A, respectively. Conclusions: PRAME expression was not determined by a balance between the global expression of DNA methylating/demethylating enzymes. However, histone acetylation may be one of the epigenetic mechanisms involved in PRAME regulation. Thus, the therapeutic combination of histone deacetylase inhibitors and PRAME immunotherapy merits further investigation. Full article
(This article belongs to the Section Oncology)
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<p>Immunohistochemical expression of PRAME (<b>A</b>), TET1 (<b>B</b>), DNMT3A (<b>C</b>), DNMT3B (<b>D</b>), 5hmC (<b>E</b>), and H3ac (<b>F</b>) in testicular seminoma (magnification ×200).</p>
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<p>Immunohistochemical expression of PRAME (<b>A</b>), TET1 (<b>B</b>), DNMT3A (<b>C</b>), DNMT3B (<b>D</b>), 5hmC (<b>E</b>), and H3ac (<b>F</b>) in mucosal melanoma (magnification ×200).</p>
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<p>Immunohistochemical expression of PRAME (<b>A</b>), TET1 (<b>B</b>), DNMT3A (<b>C</b>), DNMT3B (<b>D</b>), 5hmC (<b>E</b>), and H3ac (<b>F</b>) in synovial sarcoma (magnification ×200).</p>
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<p>Quantitative analysis of expression of PRAME (<b>A</b>), TET1 (<b>B</b>), DNMT3A (<b>C</b>), DNMT3B (<b>D</b>), 5hmC (<b>E</b>), and H3ac (<b>F</b>) in testicular seminomas (Sem), mucosal melanomas (MM), and synovial sarcomas (SS).</p>
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12 pages, 1591 KiB  
Article
Alterations in Histone Methylation States Increased Profusion of Lethal(2)-Essential-for-Life-Like (l(2)elf), Trithorax and Polycomb Genes in Apis mellifera under Heat Stress
by Ahmad A. Alghamdi and Yehya Z. Alattal
Insects 2024, 15(1), 33; https://doi.org/10.3390/insects15010033 - 5 Jan 2024
Cited by 2 | Viewed by 1760
Abstract
Histone post-translational modifications (PTMs) represent a key mechanism in the thermal adaptation of the honeybee Apis mellifera. In this study, a chromatin immunoprecipitation assay and qPCR were employed to explore the changes in the methylation states of H3K4m2, H3K4m3, H3K27m2 and H3K27m3 [...] Read more.
Histone post-translational modifications (PTMs) represent a key mechanism in the thermal adaptation of the honeybee Apis mellifera. In this study, a chromatin immunoprecipitation assay and qPCR were employed to explore the changes in the methylation states of H3K4m2, H3K4m3, H3K27m2 and H3K27m3 associated with l2efl (ID: 72474, 724405, 724488), histone methyltransferases (HMTs) ((trx) and PR-set7) and Polycomb (Pc) and (Su(z)12) genes in A. m. jemenitica (tolerant subspecies) and A. m. carnica (susceptible subspecies) in response to heat treatment (42 °C for 1 h). The results revealed significant enrichment fold changes in the methylation/demethylation of most H3K4 and H3K27 marks at all targeted genes. These changes increased the profusion of l2efl (ID: 72474, 724405, 724488), histone methyltransferases (HMTs) (trx) and Polycomb (Pc) and Su(z)12 and decreased the profusion of HMT (PR-set7) in both honeybee subspecies. The changes in the methylation enrichment folds of histone methyltransferases (HMTs) ((trx), PR-set) and Polycomb (Pc), Su(z)12 genes demonstrate the well-harmonized coordination of epigenetic gene regulation in response to heat treatment. Compared to the control, the changes in the methylation enrichment folds of H3K4m3 at Polycomb Su(z)12 were about 30× and 100× higher in treated A. m. jemenitica and A.m. carnica, respectively. Similarly, changes in the methylation/demethylation enrichment folds of HMT (trx) and Polycomb (Pc) and Su(z)12 were 2–3× higher in A. m. carnica than in A. m. jemenitica after treatment (42 °C). It is evident that post-translational chromatin modification in both honeybee subspecies can diminish heat stress impact by (I) increasing the transcriptional provision of l2efl associated with survival and (II) increasing the silencing of genes associated with general cellular activities. Full article
(This article belongs to the Special Issue The Emerging Role of Chromatin Remodelling in Insects)
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<p>Enrichment-folds’ comparison (means ± SD) of ChIP-qPCR for different histone marks (K4m2, K4m3, K27m2, K27m3) at: <span class="html-italic">lethal(2)-essential-for-life-like (l(2)efl)</span> (<span class="html-italic">A. mellifera</span>) (genes IDs: 724274; 724405; 724488) in the native tolerant honeybee subspecies of the Arabian Peninsula <span class="html-italic">A. m. jemenitica</span> and the susceptible <span class="html-italic">A. m. carnica</span> after exposure to 42 °C for one hour. Antibodies of histone marks associated with gene activation (H3K4me2 and H3K4me3) and histone marks associated with gene repression (H3K27me2 and H3K27me3) were used to precipitate sonicated chromatin of each sample. Enrichment fold (EF) was calculated using DNA from non-immune IgG as negative control. EF = 2<sup>ct(IgG-AB)</sup>. Pairwise comparison of means was performed using GraphPad Prism 8.0.1. (<a href="http://www.graphpad.com" target="_blank">www.graphpad.com</a>, accessed on 10 September 2023). (*: 0.01 ˂ <span class="html-italic">p</span> ≤ 0.05, **: 0.001 ˂ <span class="html-italic">p</span> ≤ 0.01).</p>
Full article ">Figure 2
<p>Enrichment folds’ comparison of ChIP-qPCR (means ± SD) of histone marks (K4m2, K4m3, K27m2, K27m3) at <span class="html-italic">A. mellifera</span> histone-lysine N-methyltransferase (<span class="html-italic">trx</span>) gene ID: 408716; <span class="html-italic">Apis mellifera</span> histone-lysine N-methyltransferase pr-set7 (<span class="html-italic">PR-set7</span>), mRNA, gene ID: 412027; <span class="html-italic">A. mellifera</span> Polycomb protein <span class="html-italic">Su(z)12</span>, mRNA gene ID: 409170; <span class="html-italic">Apis mellifera</span> Polycomb (<span class="html-italic">Pc</span>), mRNA, gene ID:725474 in the native honeybee subspecies of the Arabian Peninsula <span class="html-italic">A. m. jemenitica</span> and <span class="html-italic">A. m. carnica</span> after exposure to 42 °C for one hour. Activation histone marks antibodies (H3K4me2 and H3K4me3) and silencing marks (H3K27me2 and H3K27me3) were used to precipitate sonicated chromatin. Enrichment fold (EF) was calculated using DNA from non-immune IgG as negative control. EF = 2<sup>ct(IgG-AB)</sup>. Pairwise comparison of means was performed using GraphPad Prism 8.0.1 (<a href="http://www.graphpad.com" target="_blank">www.graphpad.com</a>, accessed on 10 September 2023), (ns: non-significant; *: 0.01 ˂ <span class="html-italic">p</span> ≤ 0.05, **: 0.001 ˂ <span class="html-italic">p</span> ≤ 0.01, ***: <span class="html-italic">p</span> ≤ 0.001).</p>
Full article ">Figure 2 Cont.
<p>Enrichment folds’ comparison of ChIP-qPCR (means ± SD) of histone marks (K4m2, K4m3, K27m2, K27m3) at <span class="html-italic">A. mellifera</span> histone-lysine N-methyltransferase (<span class="html-italic">trx</span>) gene ID: 408716; <span class="html-italic">Apis mellifera</span> histone-lysine N-methyltransferase pr-set7 (<span class="html-italic">PR-set7</span>), mRNA, gene ID: 412027; <span class="html-italic">A. mellifera</span> Polycomb protein <span class="html-italic">Su(z)12</span>, mRNA gene ID: 409170; <span class="html-italic">Apis mellifera</span> Polycomb (<span class="html-italic">Pc</span>), mRNA, gene ID:725474 in the native honeybee subspecies of the Arabian Peninsula <span class="html-italic">A. m. jemenitica</span> and <span class="html-italic">A. m. carnica</span> after exposure to 42 °C for one hour. Activation histone marks antibodies (H3K4me2 and H3K4me3) and silencing marks (H3K27me2 and H3K27me3) were used to precipitate sonicated chromatin. Enrichment fold (EF) was calculated using DNA from non-immune IgG as negative control. EF = 2<sup>ct(IgG-AB)</sup>. Pairwise comparison of means was performed using GraphPad Prism 8.0.1 (<a href="http://www.graphpad.com" target="_blank">www.graphpad.com</a>, accessed on 10 September 2023), (ns: non-significant; *: 0.01 ˂ <span class="html-italic">p</span> ≤ 0.05, **: 0.001 ˂ <span class="html-italic">p</span> ≤ 0.01, ***: <span class="html-italic">p</span> ≤ 0.001).</p>
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16 pages, 2502 KiB  
Article
Novel Insights on the Role of Epigenetics in Androgen Receptor’s Expression in Prostate Cancer
by Vânia Camilo, Mariana Brütt Pacheco, Filipa Moreira-Silva, Gonçalo Outeiro-Pinho, Vítor M. Gaspar, João F. Mano, C. Joana Marques, Rui Henrique and Carmen Jerónimo
Biomolecules 2023, 13(10), 1526; https://doi.org/10.3390/biom13101526 - 14 Oct 2023
Viewed by 2196
Abstract
The androgens/androgen receptor (AR) axis is the main therapeutic target in prostate cancer (PCa). However, while initially responsive, a subset of tumors loses AR expression through mechanisms putatively associated with epigenetic modifications. In this study, we assessed the link between the presence of [...] Read more.
The androgens/androgen receptor (AR) axis is the main therapeutic target in prostate cancer (PCa). However, while initially responsive, a subset of tumors loses AR expression through mechanisms putatively associated with epigenetic modifications. In this study, we assessed the link between the presence of CpG methylation in the 5′UTR and promoter regions of AR and loss of AR expression. Hence, we characterized and compared the methylation signature at CpG resolution of these regulatory regions in vitro, both at basal levels and following treatment with 5-aza-2-deoxycytidine (DAC) alone, or in combination with Trichostatin A (TSA). Our results showed heterogeneity in the methylation signature of AR negative cell lines and pinpointed the proximal promoter region as the most consistently methylated site in DU-145. Furthermore, this region was extremely resistant to the demethylating effects of DAC and was only significantly demethylated upon concomitant treatment with TSA. Nevertheless, no AR re-expression was detected at the mRNA or protein level. Importantly, after treatment, there was a significant increase in repressive histone marks at AR region 1 in DU-145 cells. Altogether, our data indicate that AR region 1 genomic availability is crucial for AR expression and that the inhibition of histone methyltransferases might hold promise for AR re-expression. Full article
(This article belongs to the Section Molecular Biology)
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Graphical abstract

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<p>Methylation profile of <span class="html-italic">AR</span> regulatory regions in prostate cancer cell lines. (<b>A</b>) Schematic representation of the human <span class="html-italic">AR</span> gene 5′UTR and proximal promoter regions. The regions examined by bisulfite sequencing cover ~250 bp upstream the TSS (region 1) and the core promoter region (−74 to +87 bp) (regions 1 and 2), the first 250 bp of the 5′UTR (region 2) and the region surrounding the translation start site (region 3). The first and last CpG sites of each region are found under each respective region box. The bent arrow marks the transcription start site (TSS; +1) and the ATG arrow represents the translation start at +1126 bp (exon 1). The CpG sites were numbered according to previous reports [<a href="#B14-biomolecules-13-01526" class="html-bibr">14</a>]. (<b>B</b>) Mean percentage of methylation per CpG across regions 1 to 3, in DU-145 (upper), PC-3 (middle) and RWPE-1 (lower) cell lines. Closed circles represent 100% methylation, whereas open circles represent 0% methylation. (<b>C</b>) Overall percentage of methylation per region obtained for each cell line. The percentage of methylation is obtained by dividing the total number of methylated CpG sites within a region by the total number of CpG sites that are present in that region. Data are represented as mean ± standard error of the mean (SEM).</p>
Full article ">Figure 2
<p>Methylation profile of AR regulatory regions 1 and 2 following DAC treatment. (<b>A</b>) Mean percentage of methylation per CpG across regions 1 and 2, in DU-145 (upper), PC-3 (middle) and RWPE-1 (lower) cell lines following treatment with DAC at 5 µM or its respective vehicle. (<b>B</b>) Overall percentage of methylation per region obtained for each cell line. Data are represented as mean ± standard error of the mean (SEM). (<b>C</b>) Methylation levels of <span class="html-italic">miR-130a</span>, <span class="html-italic">CCND2</span> and <span class="html-italic">RASSF1A</span> genes in prostate cell lines treated with DAC at 5 µM or its respective control. (<b>D</b>) Western blot of AR following 72 h exposure to DAC at 5 µM or its respective control. An asterisk (*) marks the specific AR full length band at 110 kDa. (Significance level 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.)</p>
Full article ">Figure 3
<p>Methylation profile of AR regulatory regions 1 and 2 in DU-145 cells following combined treatment with DAC and TSA. (<b>A</b>) Mean percentage of methylation per CpG across regions 1 and 2 in DU-145 following combined treatment with DAC at 5 µM and TSA at 0.33 µM or their respective vehicles. (<b>B</b>) Overall percentage of methylation per region. Data are represented as mean ± standard error of the mean (SEM). (<b>C</b>) Western blot of AR following 72 h exposure to DAC at 5 µM and TSA at 0.33 µM, both alone and in combination, and the respective vehicles. An asterisk (*) marks the specific AR full length band at 110 kDa. (Significance level represented as: * <span class="html-italic">p</span> &lt; 0.05.)</p>
Full article ">Figure 4
<p>Chromatin architecture of DU-145 cells at <span class="html-italic">AR</span> region 1 following DAC/TSA treatment. (<b>A</b>) Mean percentage of histone repressive marks H3K9me3, H3K9me2, H3K27me3 and H4K20me3, as well as activating marks. (<b>B</b>) H3K36me2, H3K9Ac and H3K27Ac following concomitant treatment with DAC at 5 µM and TSA at 0.33 µM. (<b>C</b>) Schematic representation of the chromatin architecture of DU-145 cells after DAC/TSA treatment. ↑ represents increased levels of the respective hisytone mark. Created with Biorender.com (Accessed on 8 February 2023). (Significance level 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.)</p>
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20 pages, 5647 KiB  
Article
Prolonged Inhibition of the MEK1/2-ERK Signaling Axis Primes Interleukin-1 Beta Expression through Histone 3 Lysine 9 Demethylation in Murine Macrophages
by Rachel Low, Soon-Duck Ha, Nichita Sleapnicov, Parthiv Maneesh and Sung Ouk Kim
Int. J. Mol. Sci. 2023, 24(19), 14428; https://doi.org/10.3390/ijms241914428 - 22 Sep 2023
Cited by 2 | Viewed by 1787
Abstract
Macrophages undergo different cellular states upon activation that can be hyporesponsive (tolerated) or hyperresponsive (primed or trained) to subsequent stimuli. Epigenetic modifications are known to play key roles in determining these cellular states. However, little is known about the role of signaling pathways [...] Read more.
Macrophages undergo different cellular states upon activation that can be hyporesponsive (tolerated) or hyperresponsive (primed or trained) to subsequent stimuli. Epigenetic modifications are known to play key roles in determining these cellular states. However, little is known about the role of signaling pathways that lead to these epigenetic modifications. Here, we examined the effects of various inhibitors targeting key signaling pathways induced by lipopolysaccharide (LPS) on tolerance and priming in murine macrophages. We found that a prolonged inhibition (>18 h) of the mitogen-activated protein kinase (MEK)1/2—extracellular signal-regulated kinase (ERK)1/2 signaling axis reversed tolerance and primed cells in expressing interleukin (IL)-1β and other inflammatory cytokines such as IL-6, tumor necrosis factor (TNF)α, and CXCL10. The ectopic expression of catalytically active and inactive MEK1 mutants suppressed and enhanced IL-1β expression, respectively. A transcriptomic analysis showed that cells primed by the MEK1/2 inhibitor U0126 expressed higher levels of gene sets associated with immune responses and cytokine/chemokine production, but expressed lower levels of genes with cell cycle progression, chromosome organization, and heterochromatin formation than non-primed cells. Of interest, the mRNA expressions of the histone 3 lysine 9 (H3K9) methyltransferase Suv39h1 and the H3K9 methylation reader Cbx5 were substantially suppressed, whereas the H3K9 demethylase Kdm7a was enhanced, suggesting a role of the MEK1/2-ERK signaling axis in H3K9 demethylation. The H3K9 trimethylation levels in the genomic regions of IL-1β, TNFα, and CXCL10 were decreased by U0126. Also, the H3K9 methyltransferase inhibitor BIX01294 mimicked the U0126 training effects and the overexpression of chromobox homolog (CBX)5 prevented the U0126 training effects in both RAW264.7 cells and bone-marrow-derived macrophages. Collectively, these data suggest that the prolonged inhibition of the MEK1/2-ERK signaling axis reverses tolerance and primed macrophages likely through decreasing the H3K9 methylation levels. Full article
(This article belongs to the Special Issue Advanced Research on Immune Cells and Cytokines)
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Figure 1

Figure 1
<p>Prolonged MEK1/2 inhibition reverses LPS tolerance in IL-1β mRNA expression without affecting ERK and NF-κB activation. (<b>A</b>) RAW264.7 cells were tolerized with LPS (10 ng/mL) for 24 h and replated in fresh media for 6–72 h. Cells were then activated with LPS (100 ng/mL) for 6 h. <b>Upper</b> panel: A diagram describing the experimental procedure. <b>Lower</b> panel: Expression of IL-1β mRNA was measured via RT-qPCR. (<b>B</b>) Cells were tolerized for 24 h in the presence of signaling pathway inhibitors targeting MEK1/2 (U0126; 5 µM), p38 MAPK (p38i, SB203580; 5 µM), JNK (JNKi, SP600125; 5 µM), NF-κB (NF-κBi; 2 µM), or AKT (AKTi, MK-2206; 5 µM). Cells were then replated with fresh media for 4 h and then activated with LPS for 6 h. Expression of IL-1β mRNA was measured via RT-qPCR. (<b>C</b>) The MEK1/2 inhibitor U0126 was added at the first 6 h, the last 6 h, or throughout the 24 h tolerization period. <b>Upper</b> panel: A diagram describing the experimental procedure. <b>Lower</b> panel: Expression of IL-1β mRNA was measured via RT-qPCR. (<b>D</b>) Key signaling inhibitors were added 30 min before activation and activated with LPS (100 ng/mL) for 6 h. Expression of IL-1β mRNA was measured via RT-qPCR. (<b>E</b>) Cells were non-tolerized, tolerized, and tolerized in the presence of U0126 (5 µM) for 24 h. Cells were then replated with fresh culture media for 4–6 h and then activated by LPS (100 ng/mL) for 0, 30, or 60 min. <b>Upper</b> panel: Activation of ERK1/2 and degradation of inhibitor (I)κB were examined via immunoblotting against phospho(p)-ERK1/2, inhibitor (I)κB, and β-actin (loading control). <b>Lower</b> panel: Relative amounts of p-ERK and IκB over β-actin (loading control) were expressed. (<b>A</b>–<b>D</b>) A one-way ANOVA test followed by Dunnett’s multiple comparisons test was performed for statistical analysis (<span class="html-italic">n</span> = 3; ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001). (<b>E</b>) Student’s <span class="html-italic">t</span>-test was performed between no LPS vs. 30 min LPS treatment groups in non-tolerized, tolerized, and tolerized + U0126 groups (<span class="html-italic">n</span> = 3, * <span class="html-italic">p</span> ≤ 0.05).</p>
Full article ">Figure 2
<p>Inhibition of the MEK1/2-ERK signaling pathway enhances IL-1β expression in non-tolerized RAW264.7 cells. (<b>A</b>–<b>C</b>) Cells were treated with key signaling inhibitors for 18 h (<b>A</b>), for varying durations (3–24 h) with U0126 (<b>B</b>), or varying concentrations of U0126 for 24 h (<b>C</b>). Cells were then activated with LPS (100 ng/mL) for 6 h, and the expression of IL-1β mRNA was measured via qPCR. (<b>D</b>) Production of IL-1β was measured via immunoblotting. Cells were primed with U0126 or tolerized with LPS (10 ng/mL) ± U0126 for 18 h. Cells were replated with fresh media for 4 h and then activated by LPS (100 ng/mL) for 6 h. Whole-cell lysates were then used for immunoblotting against murine pro-IL-1β (<b>upper</b> panel). For loading controls, both β-actin and p38 immunoreactivities were examined. Relative amounts of IL-1β over β-actin (loading control) were expressed using LPS-activated samples as reference point 1 (<b>lower</b> panel). (<b>E</b>) Cells were infected with the Ad5-CMV vector alone (VC), the vector containing catalytically active MEK1 (MEK1-CA), or the vector containing catalytically inactive MEK1 (MEK1-CI) for 24 h. Cells were then washed and further cultured with fresh media for another 48 h. <b>Upper</b> panel: Cells were activated with LPS (100 ng/mL) for 30 min for immunoblotting against p-ERK and β-actin. <b>Lower</b> panel: Cells were activated with LPS (100 ng/mL) for 6 h, and the expression of IL-1β mRNA was measured via qPCR. A one-way ANOVA test followed by Dunnett’s multiple comparisons test was performed for statistical analysis (<span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, **** <span class="html-italic">p</span> ≤ 0.0001).</p>
Full article ">Figure 3
<p>Transcriptomic analysis of RAW264.7 cells primed with U0126. (<b>A</b>) Total mRNAs of non-treated and U0126-treated cells (5 µM, 18 h) were sequenced via Illumina sequencing, and differential gene expression was analyzed using the FeatureCount and Limma-voom tools in the Galaxy platform as described in <a href="#sec4-ijms-24-14428" class="html-sec">Section 4</a>. Results shown in the volcano plot indicate the top 3 genes in the fold of increase, decrease, and adjusted <span class="html-italic">p</span> value (Adj. P) categories. Red dots indicate genes with Adj. <span class="html-italic">p</span> &lt; 0.05; dotted vertical lines indicate fold of change (FC) &gt; 1.5. (<b>B</b>). Gene ontology analysis was performed using the GSEA program and visualized using Cytoscape. Dots represent gene sets (nodes), and dots with a common function are clustered with a circle. Red and blue dots represent positively and negatively enriched gene sets, respectively. (<b>C</b>). Three positively and negatively over-represented gene ontology pathways are presented via enrichment plots, with size corresponding to gene count and color contrast corresponding to Adj. <span class="html-italic">p</span>. (<b>D</b>). The heat map shows the genes in the heterochromatin gene subsets. Expression values are represented as colors, where the range of colors (red, pink, light blue, and dark blue) shows the range of expression values (high, moderate, low, and lowest).</p>
Full article ">Figure 3 Cont.
<p>Transcriptomic analysis of RAW264.7 cells primed with U0126. (<b>A</b>) Total mRNAs of non-treated and U0126-treated cells (5 µM, 18 h) were sequenced via Illumina sequencing, and differential gene expression was analyzed using the FeatureCount and Limma-voom tools in the Galaxy platform as described in <a href="#sec4-ijms-24-14428" class="html-sec">Section 4</a>. Results shown in the volcano plot indicate the top 3 genes in the fold of increase, decrease, and adjusted <span class="html-italic">p</span> value (Adj. P) categories. Red dots indicate genes with Adj. <span class="html-italic">p</span> &lt; 0.05; dotted vertical lines indicate fold of change (FC) &gt; 1.5. (<b>B</b>). Gene ontology analysis was performed using the GSEA program and visualized using Cytoscape. Dots represent gene sets (nodes), and dots with a common function are clustered with a circle. Red and blue dots represent positively and negatively enriched gene sets, respectively. (<b>C</b>). Three positively and negatively over-represented gene ontology pathways are presented via enrichment plots, with size corresponding to gene count and color contrast corresponding to Adj. <span class="html-italic">p</span>. (<b>D</b>). The heat map shows the genes in the heterochromatin gene subsets. Expression values are represented as colors, where the range of colors (red, pink, light blue, and dark blue) shows the range of expression values (high, moderate, low, and lowest).</p>
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<p>Priming RAW264.7 cells with U0126 is partly mediated by repressing genes involved in H3K9 methylation. (<b>A</b>) Based on the transcriptomic analysis, the expression of epigenetic-related genes with changes greater than 2-fold in U0126-primed cells are grouped and plotted with bubble heat maps. (<b>B</b>) Expressions of <span class="html-italic">Cbx5</span>, <span class="html-italic">Suv39h1</span>, and <span class="html-italic">Kdm7a</span> were confirmed via qPCR in U0126-primed and non-primed cells. Statistical significance was determined using multiple unpaired two-tailed t-tests (<span class="html-italic">n</span> = 3). (<b>C</b>,<b>D</b>) Cells were treated with various inhibitors for 18 h and then activated by LPS (100 ng/mL) for 6 h. Expression of IL-1β was quantified via qPCR. (<b>C</b>). Cells were treated with U0126 together with or without KDM2/7 and/or KDM5 inhibitors. (<b>D</b>) Cells were treated with inhibitors against the H3K9 methyltransferases G9a (BIX01294, 1.5 µM) and/or SUV(VAR)3–9 (chaetocin, 100 nM) or the DNMT inhibitors 5-azacytidine (2 µM) and SGI-1027 (10 µM). (<b>E</b>) Cells were stably transfected with the eGFP vector control (Vector) or the GFP-mCBX5 plasmid (CBX5). <b>Left</b> panel: Stable transfections were confirmed via eGFP or eGFP-CBX5 Western blots, using p38 antibody as a loading control. <b>Right</b> panel: Cells were activated with LPS (100 ng/mL) for 6 h, and IL-1β expression was measured with qPCR. Statistical significance was determined using one-way ANOVA tests followed by Dunnett’s multiple comparisons test (<span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001).</p>
Full article ">Figure 4 Cont.
<p>Priming RAW264.7 cells with U0126 is partly mediated by repressing genes involved in H3K9 methylation. (<b>A</b>) Based on the transcriptomic analysis, the expression of epigenetic-related genes with changes greater than 2-fold in U0126-primed cells are grouped and plotted with bubble heat maps. (<b>B</b>) Expressions of <span class="html-italic">Cbx5</span>, <span class="html-italic">Suv39h1</span>, and <span class="html-italic">Kdm7a</span> were confirmed via qPCR in U0126-primed and non-primed cells. Statistical significance was determined using multiple unpaired two-tailed t-tests (<span class="html-italic">n</span> = 3). (<b>C</b>,<b>D</b>) Cells were treated with various inhibitors for 18 h and then activated by LPS (100 ng/mL) for 6 h. Expression of IL-1β was quantified via qPCR. (<b>C</b>). Cells were treated with U0126 together with or without KDM2/7 and/or KDM5 inhibitors. (<b>D</b>) Cells were treated with inhibitors against the H3K9 methyltransferases G9a (BIX01294, 1.5 µM) and/or SUV(VAR)3–9 (chaetocin, 100 nM) or the DNMT inhibitors 5-azacytidine (2 µM) and SGI-1027 (10 µM). (<b>E</b>) Cells were stably transfected with the eGFP vector control (Vector) or the GFP-mCBX5 plasmid (CBX5). <b>Left</b> panel: Stable transfections were confirmed via eGFP or eGFP-CBX5 Western blots, using p38 antibody as a loading control. <b>Right</b> panel: Cells were activated with LPS (100 ng/mL) for 6 h, and IL-1β expression was measured with qPCR. Statistical significance was determined using one-way ANOVA tests followed by Dunnett’s multiple comparisons test (<span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001).</p>
Full article ">Figure 5
<p>Inhibition of the MEK1/2-ERK signaling pathway decreases H3K9me3 levels proximal to IL-1β, CXCL10, and TNFα gene areas. (<b>A,C</b>) Left panel: H3K9me3 peaks in murine peritoneal macrophages from the GEO database (GSE107227), together with the built-in BMDM H3K4me1/3 and H3K27ac from the ENCODE database, were visualized in the UCSC mouse genome browser (mm9). For each gene, two peaks were selected: one was located upstream of the promoter (Site 1), and one was in an intragenic region (Site 2). (<b>A</b>) Right panel: RAW264.7 cells were treated with or without U0126 for 18 h, and associations of H3K9me3 with the IL-1β genomic area were examined via ChIP-qPCR as described in <a href="#sec4-ijms-24-14428" class="html-sec">Section 4</a>. (<b>B</b>) RAW264.7 cells were treated with or without U0126 for 18 h before activation with LPS (100 ng/mL) for 6 h. Expressions of IL-6, TNFα, and CXCL10 were analyzed via qPCR. (<b>C</b>) Right panel: Similar to (<b>A</b>), associations of H3K9me3 with the IL-6, TNFα, and CXCL10 genomic areas were examined via ChIP-qPCR. Statistical significance was determined using multiple unpaired two-tailed <span class="html-italic">t</span>-tests (<span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> ≤ 0.05).</p>
Full article ">Figure 5 Cont.
<p>Inhibition of the MEK1/2-ERK signaling pathway decreases H3K9me3 levels proximal to IL-1β, CXCL10, and TNFα gene areas. (<b>A,C</b>) Left panel: H3K9me3 peaks in murine peritoneal macrophages from the GEO database (GSE107227), together with the built-in BMDM H3K4me1/3 and H3K27ac from the ENCODE database, were visualized in the UCSC mouse genome browser (mm9). For each gene, two peaks were selected: one was located upstream of the promoter (Site 1), and one was in an intragenic region (Site 2). (<b>A</b>) Right panel: RAW264.7 cells were treated with or without U0126 for 18 h, and associations of H3K9me3 with the IL-1β genomic area were examined via ChIP-qPCR as described in <a href="#sec4-ijms-24-14428" class="html-sec">Section 4</a>. (<b>B</b>) RAW264.7 cells were treated with or without U0126 for 18 h before activation with LPS (100 ng/mL) for 6 h. Expressions of IL-6, TNFα, and CXCL10 were analyzed via qPCR. (<b>C</b>) Right panel: Similar to (<b>A</b>), associations of H3K9me3 with the IL-6, TNFα, and CXCL10 genomic areas were examined via ChIP-qPCR. Statistical significance was determined using multiple unpaired two-tailed <span class="html-italic">t</span>-tests (<span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> ≤ 0.05).</p>
Full article ">Figure 6
<p>Inhibition of the MEK1/2-ERK signaling pathway reverses LPS tolerance and enhances inflammatory cytokine expression in BMDMs in a G9a-dependent manner. (<b>A</b>) BMDMs were tolerized with LPS for 24 h together with or without U0126 or BIX01294 (<b>left</b> panel) or treated 24 h before activation (<b>middle</b> panel). Cells were then activated with LPS (100 ng/mL) for 6 h for quantification of IL-1β mRNA or for 18 h for IL-1β protein levels (<b>right</b> panel). (<b>B</b>) Similarly, expressions of IL-6, TNFα, and CXCL10 mRNAs in BMDMs activated by LPS tolerized with or without U0126 or BIX, and non-tolerized cells pretreated with U0126 or BIX were analyzed via qPCR. One-way ANOVA tests with Dunnett’s multiple comparisons test were conducted to calculate significance (<span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001).</p>
Full article ">Figure 6 Cont.
<p>Inhibition of the MEK1/2-ERK signaling pathway reverses LPS tolerance and enhances inflammatory cytokine expression in BMDMs in a G9a-dependent manner. (<b>A</b>) BMDMs were tolerized with LPS for 24 h together with or without U0126 or BIX01294 (<b>left</b> panel) or treated 24 h before activation (<b>middle</b> panel). Cells were then activated with LPS (100 ng/mL) for 6 h for quantification of IL-1β mRNA or for 18 h for IL-1β protein levels (<b>right</b> panel). (<b>B</b>) Similarly, expressions of IL-6, TNFα, and CXCL10 mRNAs in BMDMs activated by LPS tolerized with or without U0126 or BIX, and non-tolerized cells pretreated with U0126 or BIX were analyzed via qPCR. One-way ANOVA tests with Dunnett’s multiple comparisons test were conducted to calculate significance (<span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001, **** <span class="html-italic">p</span> ≤ 0.0001).</p>
Full article ">
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