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20 pages, 3632 KiB  
Review
R-Methylation in Plants: A Key Regulator of Plant Development and Response to the Environment
by Clément Barré-Villeneuve and Jacinthe Azevedo-Favory
Int. J. Mol. Sci. 2024, 25(18), 9937; https://doi.org/10.3390/ijms25189937 (registering DOI) - 14 Sep 2024
Viewed by 201
Abstract
Although arginine methylation (R-methylation) is one of the most important post-translational modifications (PTMs) conserved in eukaryotes, it has not been studied to the same extent as phosphorylation and ubiquitylation. Technical constraints, which are in the process of being resolved, may partly explain this [...] Read more.
Although arginine methylation (R-methylation) is one of the most important post-translational modifications (PTMs) conserved in eukaryotes, it has not been studied to the same extent as phosphorylation and ubiquitylation. Technical constraints, which are in the process of being resolved, may partly explain this lack of success. Our knowledge of R-methylation has recently evolved considerably, particularly in metazoans, where misregulation of the enzymes that deposit this PTM is implicated in several diseases and cancers. Indeed, the roles of R-methylation have been highlighted through the analyses of the main actors of this pathway: the PRMT writer enzymes, the TUDOR reader proteins, and potential “eraser” enzymes. In contrast, R-methylation has been much less studied in plants. Even so, it has been shown that R-methylation in plants, as in animals, regulates housekeeping processes such as transcription, RNA silencing, splicing, ribosome biogenesis, and DNA damage. R-methylation has recently been highlighted in the regulation of membrane-free organelles in animals, but this role has not yet been demonstrated in plants. The identified R-met targets modulate key biological processes such as flowering, shoot and root development, and responses to abiotic and biotic stresses. Finally, arginine demethylases activity has mostly been identified in vitro, so further studies are needed to unravel the mechanism of arginine demethylation. Full article
(This article belongs to the Special Issue Study on Post-translational Modifications of Protein)
17 pages, 4106 KiB  
Article
Immune-Cell-Derived Exosomes as a Potential Novel Tool to Investigate Immune Responsiveness in SCLC Patients: A Proof-of-Concept Study
by Luisa Amato, Caterina De Rosa, Viviana De Rosa, Hamid Heydari Sheikhhossein, Annalisa Ariano, Paola Franco, Valeria Nele, Sara Capaldo, Gaetano Di Guida, Filippo Sepe, Alessandra Di Liello, Giuseppe De Rosa, Concetta Tuccillo, Antonio Gambardella, Fortunato Ciardiello, Floriana Morgillo, Virginia Tirino, Carminia Maria Della Corte, Francesca Iommelli and Giovanni Vicidomini
Cancers 2024, 16(18), 3151; https://doi.org/10.3390/cancers16183151 (registering DOI) - 14 Sep 2024
Viewed by 305
Abstract
Small cell lung cancer (SCLC) is a highly invasive and rapidly proliferating lung tumor subtype. Most patients respond well to a combination of platinum-based chemotherapy and PD-1/PDL-1 inhibitors. Unfortunately, not all patients benefit from this treatment regimen, and few alternative therapies are available. [...] Read more.
Small cell lung cancer (SCLC) is a highly invasive and rapidly proliferating lung tumor subtype. Most patients respond well to a combination of platinum-based chemotherapy and PD-1/PDL-1 inhibitors. Unfortunately, not all patients benefit from this treatment regimen, and few alternative therapies are available. In this scenario, the identification of new biomarkers and differential therapeutic strategies to improve tumor response becomes urgent. Here, we investigated the role of exosomes (EXs) released from the peripheral blood mononuclear cells (PBMCs) of SCLC patients in mediating the functional crosstalk between the immune system and tumors in response to treatments. In this study, we showed that PBMC-EXs from SCLC patients with different responses to chemoimmunotherapy showed different levels of immune (STING and MAVS) and EMT (Snail and c-Myc) markers. We demonstrated that PBMC-EXs derived from best responder (BR) patients were able to induce a significant increase in apoptosis in SCLC cell lines in vitro compared to PBMC-EXs derived from non-responder (NR) SCLC patients. PBMC-EXs were able to affect cell viability and modulate apoptotic markers, DNA damage and the replication stress pathway, as well as the occurrence of EMT. Our work provides proof of concept that PBMC-EXs can be used as a tool to study the crosstalk between cancer cells and immune cells and that PBMC-EXs exhibit an in vitro ability to promote cancer cell death and reduce tumor aggressiveness. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic representation of the exosome isolation protocol, exosome characterization procedure and co-culture with SCLC cell lines. Exosomes were isolated from PBMCs derived from SCLC patients by multiple ultracentrifugation steps. PBMC-EXs were characterized by SEM, nanoparticle tracking analysis was performed using a NanoSight Instrument and exosomal markers were determined by Western blot analysis. The graphical scheme was produced by the authors using the BioRender platform (<a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a>) (basic license terms).</p>
Full article ">Figure 2
<p>Isolation and characterization of exosomes from SCLC patients PBMC-EXs. (<b>A</b>) Representative FEG-SEM images of the isolated exosomes (scale bar = 300 nm). (<b>B</b>) Size distribution of the isolated PBMC-EXs. (<b>C</b>) Western blot analysis and its quantification of exosomal markers CD81, CD63, HSP70, DNA/RNA sensors of antitumor innate immune response (STING and MAVS) and EMT TFs Snail and c-Myc. The isolated exosomes were successfully isolated from the culture supernatants of PBMCs isolated from BR or NR SCLC patients. The data of PBMC-EX samples were expressed as the ratio of each PBMC-EX BR sample to the corresponding PBMC-EX NR sample to evaluate the relative fold-change induction. Red line indicated the band of each protein on the gel. Original western blots are presented in <a href="#app1-cancers-16-03151" class="html-app">File S1</a>.</p>
Full article ">Figure 3
<p>Co-culture effect of PBMC-EXs with SCLC cell lines on cell viability. (<b>A</b>) Cell viability of H661 and H446 cells after co-culture for 24 h with PBMC-EXs from BR and NR SCLC patients. (<b>B</b>) Cell viability of H661 and H446 cells after co-culture for 72 h with PBMC-EXs from BR and NR SCLC patients. Data are expressed as the mean ± SD. Unpaired Student’s <span class="html-italic">t</span>-test with * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 4
<p>Co-culture effect of PBMC-EXs with SCLC cell lines on cell death. (<b>A</b>) Flow cytometry analysis of cell death by Annexin V/PI assay after co-culture for 72 h of PBMC-EXs from BR and NR donors. (<b>B</b>) Bar graph showing summary data of % Annexin V/PI positive cells; H661 (upper panel) and H446 (lower panel). Statistical significance: **** <span class="html-italic">p</span> &lt; 0.0001, *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, # = comparison between H661 and H446 apoptosis; #### <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 5
<p>Apoptotic markers, DNA damage/replication stress markers and EMT markers in co–cultures of SCLC cell lines with PBMC–EXs derived from BR and NR SCLC patients. Representative Western blotting of whole cell lysates from (<b>A</b>) H661 and (<b>B</b>) H446 cell lines showing levels of apoptotic markers (caspase 8, lamin A/C, BID/tBID), DNA damage, replication stress markers (Bcl–2, Bcl–xL, p–Chk2/Chk2, H2A.X) and EMT markers (e–cadherin, Snail, pMAPK/MAPK, TGFBR–I) after co-culture with BR or NR PBMC-EXs. GAPDH was used to ensure equal loading. At least three independent experiments were performed. Original western blots are presented in <a href="#app1-cancers-16-03151" class="html-app">File S1</a>.</p>
Full article ">
33 pages, 1865 KiB  
Review
Oxidative Stress and Age-Related Tumors
by Emma Di Carlo and Carlo Sorrentino
Antioxidants 2024, 13(9), 1109; https://doi.org/10.3390/antiox13091109 - 13 Sep 2024
Viewed by 207
Abstract
Oxidative stress is the result of the imbalance between reactive oxygen and nitrogen species (RONS), which are produced by several endogenous and exogenous processes, and antioxidant defenses consisting of exogenous and endogenous molecules that protect biological systems from free radical toxicity. Oxidative stress [...] Read more.
Oxidative stress is the result of the imbalance between reactive oxygen and nitrogen species (RONS), which are produced by several endogenous and exogenous processes, and antioxidant defenses consisting of exogenous and endogenous molecules that protect biological systems from free radical toxicity. Oxidative stress is a major factor in the aging process, contributing to the accumulation of cellular damage over time. Oxidative damage to cellular biomolecules, leads to DNA alterations, lipid peroxidation, protein oxidation, and mitochondrial dysfunction resulting in cellular senescence, immune system and tissue dysfunctions, and increased susceptibility to age-related pathologies, such as inflammatory disorders, cardiovascular and neurodegenerative diseases, diabetes, and cancer. Oxidative stress-driven DNA damage and mutations, or methylation and histone modification, which alter gene expression, are key determinants of tumor initiation, angiogenesis, metastasis, and therapy resistance. Accumulation of genetic and epigenetic damage, to which oxidative stress contributes, eventually leads to unrestrained cell proliferation, the inhibition of cell differentiation, and the evasion of cell death, providing favorable conditions for tumorigenesis. Colorectal, breast, lung, prostate, and skin cancers are the most frequent aging-associated malignancies, and oxidative stress is implicated in their pathogenesis and biological behavior. Our aim is to shed light on the molecular and cellular mechanisms that link oxidative stress, aging, and cancers, highlighting the impact of both RONS and antioxidants, provided by diet and exercise, on cellular senescence, immunity, and development of an antitumor response. The dual role of ROS as physiological regulators of cell signaling responsible for cell damage and diseases, as well as its use for anti-tumor therapeutic purposes, will also be discussed. Managing oxidative stress is crucial for promoting healthy aging and reducing the risk of age-related tumors. Full article
(This article belongs to the Special Issue Reactive Nitrogen Species (RNS) and Redox Signaling in Tumors)
18 pages, 1608 KiB  
Review
Particulate Matter and Its Molecular Effects on Skin: Implications for Various Skin Diseases
by Kyungho Paik, Jung-Im Na, Chang-Hun Huh and Jung-Won Shin
Int. J. Mol. Sci. 2024, 25(18), 9888; https://doi.org/10.3390/ijms25189888 - 13 Sep 2024
Viewed by 239
Abstract
Particulate matter (PM) is a harmful air pollutant composed of chemicals and metals which affects human health by penetrating both the respiratory system and skin, causing oxidative stress and inflammation. This review investigates the association between PM and skin disease, focusing on the [...] Read more.
Particulate matter (PM) is a harmful air pollutant composed of chemicals and metals which affects human health by penetrating both the respiratory system and skin, causing oxidative stress and inflammation. This review investigates the association between PM and skin disease, focusing on the underlying molecular mechanisms and specific disease pathways involved. Studies have shown that PM exposure is positively associated with skin diseases such as atopic dermatitis, psoriasis, acne, and skin aging. PM-induced oxidative stress damages lipids, proteins, and DNA, impairing cellular functions and triggering inflammatory responses through pathways like aryl hydrocarbon receptor (AhR), NF-κB, and MAPK. This leads to increased production of inflammatory cytokines and exacerbates skin conditions. PM exposure exacerbates AD by triggering inflammation and barrier disruption. It disrupts keratinocyte differentiation and increases pro-inflammatory cytokines in psoriasis. In acne, it increases sebum production and inflammatory biomarkers. It accelerates skin aging by degrading ECM proteins and increasing MMP-1 and COX2. In conclusion, PM compromises skin health by penetrating skin barriers, inducing oxidative stress and inflammation through mechanisms like ROS generation and activation of key pathways, leading to cellular damage, apoptosis, and autophagy. This highlights the need for protective measures and targeted treatments to mitigate PM-induced skin damage. Full article
(This article belongs to the Special Issue Molecular Research in Environmental Toxicology)
Show Figures

Figure 1

Figure 1
<p>Primary molecular mechanisms of PM-induced skin damage. (<b>A</b>) PM can penetrate the skin, infiltrating both the barrier-disrupted interfollicular epidermis and the intact follicular epidermis. (<b>B</b>) PM activates cellular signaling pathways such as AhR and TLR, leading to increased ROS production, while PM itself also generates ROS. ROS from PM causes oxidative stress, damaging lipids, proteins, and DNA, impairing cellular functions, and causing apoptosis. It activates NF-κB, promoting cytokines (TNF, IL-1α, IL-1β), adhesion molecules (ICAM1), and enzymes (COX2). ROS also activate MAPK pathways (ERK, JNK, p38), leading to inflammatory responses in skin.</p>
Full article ">Figure 2
<p>A schematic representation of the molecular effects of particulate matter on skin diseases, illustrating the disease-specific pathways involved. TEWL = transepidermal water loss, FLG = filaggrin, LOR = loricrin, IL = interleukin, TRPV = transient receptor potential vanilloid, AKT = protein kinase B, mTOR = mammalian target of rapamycin, HIF-1a = hypoxia inducible factor 1 subunit alpha, CCL, CXCL = chemokine ligand, IRE1α = Inositol-requiring transmembrane, kinase/endoribonuclease 1α, SCF = stem cell factor, ET-1 = endothelin 1, MMP = matrix metalloproteins, COX = cyclooxygenase, ECM = extracellular matrix.</p>
Full article ">
31 pages, 8294 KiB  
Article
The Role of Mutated Calreticulin in the Pathogenesis of BCR-ABL1-Negative Myeloproliferative Neoplasms
by Roberta Vadeikienė, Baltramiejus Jakštys, Danguolė Laukaitienė, Saulius Šatkauskas, Elona Juozaitytė and Rasa Ugenskienė
Int. J. Mol. Sci. 2024, 25(18), 9873; https://doi.org/10.3390/ijms25189873 - 12 Sep 2024
Viewed by 273
Abstract
Myeloproliferative neoplasms (MPNs) are characterized by increased proliferation of myeloid lineages in the bone marrow. Calreticulin (CALR) 52 bp deletion and CALR 5 bp insertion have been identified in essential thrombocythemia (ET) and primary myelofibrosis (PMF). There is not much data [...] Read more.
Myeloproliferative neoplasms (MPNs) are characterized by increased proliferation of myeloid lineages in the bone marrow. Calreticulin (CALR) 52 bp deletion and CALR 5 bp insertion have been identified in essential thrombocythemia (ET) and primary myelofibrosis (PMF). There is not much data on the crosstalk between mutated CALR and MPN-related signaling pathways, such as JAK/STAT, PI3K/Akt/mTOR, and Hedgehog. Calreticulin, a multifunctional protein, takes part in many cellular processes. Nevertheless, there is little data on how mutated CALR affects the oxidative stress response and oxidative stress-induced DNA damage, apoptosis, and cell cycle progression. We aimed to investigate the role of the CALR 52 bp deletion and 5 bp insertion in the pathogenesis of MPN, including signaling pathway activation and functional analysis in CALR-mutated cells. Our data indicate that the JAK/STAT and PI3K/Akt/mTOR pathways are activated in CALR-mutated cells, and this activation does not necessarily depend on the CALR and MPL interaction. Moreover, it was found that CALR mutations impair calreticulin function, leading to reduced responses to oxidative stress and DNA damage. It was revealed that the accumulation of G2/M-CALR-mutated cells indicates that oxidative stress-induced DNA damage is difficult to repair. Taken together, this study contributes to a deeper understanding of the specific molecular mechanisms underlying CALR-mutated MPNs. Full article
(This article belongs to the Special Issue Hematological Malignancies: Molecular Mechanisms and Therapy)
Show Figures

Figure 1

Figure 1
<p><span class="html-italic">CALR</span> Del52 cell line viability reduction by RAD001 treatment. <span class="html-italic">CALR</span> Del52 cells were treated with varying concentrations of RAD001 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 1 Cont.
<p><span class="html-italic">CALR</span> Del52 cell line viability reduction by RAD001 treatment. <span class="html-italic">CALR</span> Del52 cells were treated with varying concentrations of RAD001 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 2
<p>Reduction of <span class="html-italic">CALR</span> Del52 cell line viability by CYT387 treatment. <span class="html-italic">CALR</span> Del52 cells were treated with varying concentrations of CYT387 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 2 Cont.
<p>Reduction of <span class="html-italic">CALR</span> Del52 cell line viability by CYT387 treatment. <span class="html-italic">CALR</span> Del52 cells were treated with varying concentrations of CYT387 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 3
<p>Reduction of <span class="html-italic">CALR</span> Del52 cell line viability by HPI-1 treatment. <span class="html-italic">CALR</span> Del52 cells were treated with varying concentrations of HPI-1 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 3 Cont.
<p>Reduction of <span class="html-italic">CALR</span> Del52 cell line viability by HPI-1 treatment. <span class="html-italic">CALR</span> Del52 cells were treated with varying concentrations of HPI-1 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 4
<p><span class="html-italic">CALR</span> Ins5 cell line viability reduction by RAD001 treatment. <span class="html-italic">CALR</span> Ins5 cells were treated with varying concentrations of RAD001 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 4 Cont.
<p><span class="html-italic">CALR</span> Ins5 cell line viability reduction by RAD001 treatment. <span class="html-italic">CALR</span> Ins5 cells were treated with varying concentrations of RAD001 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 5
<p>Reduction of <span class="html-italic">CALR</span> Ins5 cell line viability by CYT387 treatment. <span class="html-italic">CALR</span> Ins5 cells were treated with varying concentrations of CYT387 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 5 Cont.
<p>Reduction of <span class="html-italic">CALR</span> Ins5 cell line viability by CYT387 treatment. <span class="html-italic">CALR</span> Ins5 cells were treated with varying concentrations of CYT387 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 6
<p>Reduction of <span class="html-italic">CALR</span> Ins5 cell line viability by HPI-1 treatment. <span class="html-italic">CALR</span> Ins5 cells were treated with varying concentrations of HPI-1 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 6 Cont.
<p>Reduction of <span class="html-italic">CALR</span> Ins5 cell line viability by HPI-1 treatment. <span class="html-italic">CALR</span> Ins5 cells were treated with varying concentrations of HPI-1 for 24, 48, and 72 h before alamarBlue (<b>A</b>) and trypan exclusion assays (<b>B</b>) were performed. * <span class="html-italic">p</span> &lt; 0.05 vs. DMSO-treated control. # <span class="html-italic">p</span> &lt; 0.01 vs. DMSO-treated control.</p>
Full article ">Figure 7
<p>Gene expression in <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, and SET-2 cells. (<b>A</b>) <span class="html-italic">EIF4EBP1</span>, (<b>B</b>) <span class="html-italic">RPS6KB1</span>, (<b>C</b>) <span class="html-italic">STAT5A</span>, and (<b>D</b>) <span class="html-italic">STAT1</span> relative expression levels (2<sup>−ΔΔCt</sup>) were normalized to <span class="html-italic">ACTB</span> gene expression as an endogenous control. Bar graphs represent the mean of three independent experiments. Error bars show the standard deviation from the mean. The differences between the UT-7 cell line, which served as a <span class="html-italic">JAK2</span> and <span class="html-italic">CALR</span> wild-type control, and SET-2 and <span class="html-italic">CALR</span>-mutated cells were evaluated using an independent sample <span class="html-italic">t</span>-test. Gene expression, which is significantly different from the control at <span class="html-italic">p</span> &lt; 0.05, is represented as *.</p>
Full article ">Figure 8
<p>Changes in 4E-BP1 protein levels in <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, and SET-2 cell lines. Representative pictures of protein bands on the left of the figure are obtained from Western blot membranes and show protein expression levels. Densitometric quantification of total 4E-BP1 levels was normalized to that of β-actin for fold-change calculations. Bar graphs represent the mean of at least three independent experiments. Error bars show the standard deviation from the mean. The differences in protein expression between the UT-7 cell line, which served as a <span class="html-italic">JAK2</span> and <span class="html-italic">CALR</span> wild-type control, and SET-2 and <span class="html-italic">CALR</span>-mutated cells, were evaluated using an independent sample <span class="html-italic">t</span>-test.</p>
Full article ">Figure 9
<p>Induction of the phosphorylation of 4E-BP1 in <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, and SET-2 cell lines. Representative pictures of protein bands on the left of the figure are obtained from Western blot membranes and show induced activation of 4E-BP1. Densitometric quantification of phosphorylated 4E-BP1 levels was normalized to total 4E-BP1 for fold-change calculations. The bar graphs represent the mean of at least three independent experiments. Error bars show the standard deviation from the mean. The differences in protein levels between the UT-7 cell line, which served as a <span class="html-italic">JAK2</span> and <span class="html-italic">CALR</span> wild-type control, and SET-2 and <span class="html-italic">CALR</span>-mutated cells, were evaluated using an independent sample <span class="html-italic">t</span>-test. Protein levels significantly different from the control (<span class="html-italic">p</span> &lt; 0.05) are represented as *.</p>
Full article ">Figure 10
<p>Changes in STAT5A protein levels in <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, and SET-2 cell lines. Representative pictures of protein bands on the left of the figure are obtained from Western blot membranes and show protein expression. Densitometric quantification of total STAT5A levels was normalized to that of β-actin for fold-change calculations. The bar graphs represent the mean of at least three independent experiments. Error bars show the standard deviation from the mean. The differences in protein levels between the UT-7 cell line, which served as a <span class="html-italic">JAK2</span> and <span class="html-italic">CALR</span> wild-type control, and SET-2 and <span class="html-italic">CALR</span>-mutated cells, were evaluated using an independent sample <span class="html-italic">t</span>-test. Protein level significantly different from the control at <span class="html-italic">p</span> &lt; 0.05 is represented as *.</p>
Full article ">Figure 11
<p>Induction of the phosphorylation of STAT5A in <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, and SET-2 cell lines. Representative pictures of protein bands on the left of the figure are obtained from Western blot membranes and show induced activation of STAT5A. Densitometric quantification of phosphorylated STAT5A levels was normalized to total STAT5A for fold-change calculations. The bar graphs represent the mean of at least three independent experiments. Error bars show the standard deviation from the mean. The differences in protein levels between the UT-7 cell line, which served as a <span class="html-italic">JAK2</span> and <span class="html-italic">CALR</span> wild-type control, and SET-2 as well, as <span class="html-italic">CALR</span>-mutated cells, were evaluated using an independent sample <span class="html-italic">t</span>-test. Protein level significantly different from the control at <span class="html-italic">p</span> &lt; 0.05 is represented as *.</p>
Full article ">Figure 12
<p>Changes in STAT1 protein levels in <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, and SET-2 cell lines. Representative pictures of protein bands on the left of the figure are obtained from Western blot membranes and show protein expression. Densitometric quantification of total STAT1 levels was normalized to β-actin levels for fold-change calculations. The bar graphs represent the mean of at least three independent experiments. Error bars show the standard deviation from the mean. Differences in protein levels between the UT-7 control cell line and SET-2, as well as <span class="html-italic">CALR</span>-mutated cells, were evaluated using an independent sample <span class="html-italic">t</span>-test. Protein level significantly different from the control at <span class="html-italic">p</span> &lt; 0.05 is represented as *.</p>
Full article ">Figure 13
<p>Changes in STAT1 protein phosphorylation in <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, and SET-2 cell lines. Representative pictures of protein bands on the left of the figure are obtained from Western blot membranes and show induced activation of STAT1. Densitometric quantification of phosphorylated STAT1 levels was normalized to total STAT1 for fold-change calculations. The bar graphs represent the mean of at least three independent experiments. The protein level differences between the UT-7 cell line, which served as a <span class="html-italic">JAK2</span> and <span class="html-italic">CALR</span> wild-type control, and SET-2 as well, as <span class="html-italic">CALR</span>-mutated cells, were evaluated using an independent sample <span class="html-italic">t</span>-test. Error bars show the standard deviation from the mean.</p>
Full article ">Figure 14
<p>Results of ROS level analysis in <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, SET-2, and UT-7 cells after 24 h of exposure to H<sub>2</sub>O<sub>2</sub> and 24 h of repair. (<b>A</b>) Representative ROS profile histograms are shown. (<b>B</b>) The graph represents the percentage of positive ROS in different cell lines. Values represent the mean and a standard deviation of at least three experiments performed in triplicate. An asterisk represents <span class="html-italic">p</span> &lt; 0.05 vs. control.</p>
Full article ">Figure 15
<p><span class="html-italic">CALR</span> mutations impair oxidative stress-induced DNA damage repair. DNA damage in SET-2, <span class="html-italic">CALR</span> Del52, <span class="html-italic">CALR</span> Ins5, and UT-7 was detected after 24 h of exposure to H<sub>2</sub>O<sub>2</sub> and 24 h of repair using the Muse Multi-Color DNA Damage Kit. (<b>A</b>) Representative scatterplots of pATM and pH2AX profiles in <span class="html-italic">JAK2</span>-mutated, <span class="html-italic">CALR</span>-mutated, and wild-type cells. (<b>B</b>) The graph shows the percentage of cells expressing phosphorylated ATM and H2AX. Values show the mean with a standard deviation of at least three experiments performed in triplicate. An asterisk represents <span class="html-italic">p</span> &lt; 0.05 vs. control.</p>
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<p>An increase in apoptosis level in <span class="html-italic">CALR</span> Ins5 cells after H<sub>2</sub>O<sub>2</sub>-induced oxidative stress. The evaluation of apoptosis levels in the tested cells was performed after 24 h of exposure to H<sub>2</sub>O<sub>2</sub> using the Muse Annexin V and Dead Cell Kit. (<b>A</b>) Representative scatter plots of the apoptosis profile are shown. (<b>B</b>) The graph shows the percentage of apoptotic cells. Values show the mean with a standard deviation of at least three experiments performed in triplicate. An asterisk represents <span class="html-italic">p</span> &lt; 0.05 vs. control.</p>
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<p><span class="html-italic">CALR</span>-mutated cells cycle arrest at the G2/M phase after H<sub>2</sub>O<sub>2</sub>-induced oxidative stress. The analysis of the cell cycle was performed after 24 h of exposure to H<sub>2</sub>O<sub>2</sub> using a Muse Cell Cycle Kit. (<b>A</b>) Representative histograms of cell cycle distribution in the tested cell lines. (<b>B</b>) The graph represents the percentage of cell cycle distribution. Values show the mean with a standard deviation of at least three experiments performed in triplicate. An asterisk represents <span class="html-italic">p</span> &lt; 0.05 vs. control.</p>
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30 pages, 1339 KiB  
Systematic Review
Pathogenesis and New Pharmacological Approaches to Noise-Induced Hearing Loss: A Systematic Review
by Francisco Javier Santaolalla Sanchez, Juan David Gutierrez Posso, Francisco Santaolalla Montoya, Javier Aitor Zabala, Ane Arrizabalaga-Iriondo, Miren Revuelta and Ana Sánchez del Rey
Antioxidants 2024, 13(9), 1105; https://doi.org/10.3390/antiox13091105 - 12 Sep 2024
Viewed by 242
Abstract
Noise-induced hearing loss (NIHL) is responsible for significant adverse effects on cognition, quality of life and work, social relationships, motor skills, and other psychological aspects. The severity of NIHL depends on individual patient characteristics, sound intensity, and mainly the duration of sound exposure. [...] Read more.
Noise-induced hearing loss (NIHL) is responsible for significant adverse effects on cognition, quality of life and work, social relationships, motor skills, and other psychological aspects. The severity of NIHL depends on individual patient characteristics, sound intensity, and mainly the duration of sound exposure. NIHL leads to the production of a reactive oxygen (ROS) inflammatory response and the activation of apoptotic pathways, DNA fragmentation, and cell death. In this situation, antioxidants can interact with free radicals as well as anti-apoptotics or anti-inflammatory substances and stop the reaction before vital molecules are damaged. Therefore, the aim of this study was to analyze the effects of different pharmacological treatments, focusing on exogenous antioxidants, anti-inflammatories, and anti-apoptotics to reduce the cellular damage caused by acoustic trauma in the inner ear. Experimental animal studies using these molecules have shown that they protect hair cells and reduce hearing loss due to acoustic trauma. However, there is a need for more conclusive evidence demonstrating the protective effects of antioxidant/anti-inflammatory or anti-apoptotic drugs’ administration, the timeline in which they exert their pharmacological action, and the dose in which they should be used in order to consider them as therapeutic drugs. Further studies are needed to fully understand the potential of these drugs as they may be a promising option to prevent and treat noise-induced hearing loss. Full article
(This article belongs to the Special Issue Oxidative Stress in Hearing Loss)
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<p>Systematic review strategy flowchart.</p>
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<p>Systematic review strategy flowchart.</p>
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14 pages, 2352 KiB  
Article
Bisphenol S Promotes the Transfer of Antibiotic Resistance Genes via Transformation
by Jiayi Zhang, Shuyao Zhu, Jingyi Sun and Yuan Liu
Int. J. Mol. Sci. 2024, 25(18), 9819; https://doi.org/10.3390/ijms25189819 - 11 Sep 2024
Viewed by 325
Abstract
The antibiotic resistance crisis has seriously jeopardized public health and human safety. As one of the ways of horizontal transfer, transformation enables bacteria to acquire exogenous genes naturally. Bisphenol compounds are now widely used in plastics, food, and beverage packaging, and have become [...] Read more.
The antibiotic resistance crisis has seriously jeopardized public health and human safety. As one of the ways of horizontal transfer, transformation enables bacteria to acquire exogenous genes naturally. Bisphenol compounds are now widely used in plastics, food, and beverage packaging, and have become a new environmental pollutant. However, their potential relationship with the spread of antibiotic resistance genes (ARGs) in the environment remains largely unexplored. In this study, we aimed to assess whether the ubiquitous bisphenol S (BPS) could promote the transformation of plasmid-borne ARGs. Using plasmid pUC19 carrying the ampicillin resistance gene as an extracellular ARG and model microorganism E. coli DH5α as the recipient, we established a transformation system. Transformation assays revealed that environmentally relevant concentrations of BPS (0.1–10 μg/mL) markedly enhanced the transformation frequency of plasmid-borne ARGs into E. coli DH5α up to 2.02-fold. Fluorescent probes and transcript-level analyses suggest that BPS stimulated increased reactive oxygen species (ROS) production, activated the SOS response, induced membrane damage, and increased membrane fluidity, which weakened the barrier for plasmid transfer, allowing foreign DNA to be more easily absorbed. Moreover, BPS stimulates ATP supply by activating the tricarboxylic acid (TCA) cycle, which promotes flagellar motility and expands the search for foreign DNA. Overall, these findings provide important insight into the role of bisphenol compounds in facilitating the horizontal spread of ARGs and emphasize the need to monitor the residues of these environmental contaminants. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>BPS promotes the transformation of ARGs into <span class="html-italic">E. coli</span> DH5α. (<b>A</b>) Growth curves of the recipient bacterium (<span class="html-italic">E. coli</span> DH5α) in the presence of different concentrations of the BPS (0.1–10 μg/mL). (<b>B</b>) Effects of different concentrations of the BPS on the frequency of transformation of pUC19 plasmid into <span class="html-italic">E. coli</span> DH5α. Statistically significant differences were determined using one-way ANOVA at * <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, respectively. NS, not significant. (<b>C</b>) Gel electropherograms of pUC19 plasmid, recipient bacteria, and transformants at different concentrations of BPS. (<b>D</b>) MIC values of recipient bacteria and transformants.</p>
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<p>BPS stimulates the production of ROS and enhances membrane permeability in the recipient bacteria. (<b>A</b>) Effects of different concentrations of BPS on ROS production by recipient bacteria. (<b>B</b>) Heat map of increased expression levels of genes related to the oxidative stress system and SOS response system of bacteria after BPS treatment. (<b>C</b>) Changes in outer membrane permeability of recipient bacteria following BPS pressure. (<b>D</b>) Changes in inner membrane permeability in response to BPS treatment. (<b>E</b>) Effect of BPS on membrane fluidity. Statistically significant differences were determined using one-way ANOVA at * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001, respectively. NS, not significant. (<b>F</b>) Heatmap of the increased expression levels of genes related to bacterial membrane permeability after BPS treatment. (<b>G</b>) SEM images of <span class="html-italic">E. coli</span> DH5α bacterial cells exposed to 0.5 μg/mL BPS for 4 h. Cell membrane damage is indicated by red arrows.</p>
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<p>BPS enhances bacterial metabolism by accelerating the TCA cycle. (<b>A</b>) Bacterial respiration levels of <span class="html-italic">E. coli</span> DH5α were unchanged or even decreased under the pressure of BPS. (<b>B</b>) Heatmap of the expression levels of genes related to bacterial electron transport chain in response to BPS treatment. (<b>C</b>) Heatmap of TCA cycle-related gene expression levels in response to BPS. Bacterial (<b>D</b>) NAD<sup>+</sup>/NADH ratio, (<b>E</b>) NAD<sup>+</sup> content, and (<b>F</b>) NADH content under BPS treatment. Statistically significant differences were determined using one-way ANOVA at ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001, respectively. NS, not significant.</p>
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<p>BPS stimulates ATP synthesis and flagellar motility. (<b>A</b>) ΔpH changes of recipient bacteria in response to BPS treatment, measured using BCECF. (<b>B</b>) Membrane potential of recipient bacteria in response to BPS stress, monitored using DiSC<sub>3</sub>(5). (<b>C</b>) Bacterial ATP synthesis after exposure to BPS. (<b>D</b>) Heat map of the expression level of bacterial ATP synthase-related genes under BPS stress. (<b>E</b>) Heatmap of the expression level of bacterial flagellum-related genes after BPS treatment. (<b>F</b>) Swimming motility test of <span class="html-italic">E. coli</span> DH5α under BPS stress, scale bar, 0.5 cm. Statistically significant differences were determined using one-way ANOVA at **** <span class="html-italic">p</span> &lt; 0.0001. NS, not significant.</p>
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<p>Schematic diagram of the mechanism of increased transformation by BPS treatment. The frequency of transformation of antibiotic-resistant plasmids was significantly increased under the stress of low concentrations of BPS. Potential mechanisms include a dramatic increase in ROS production and activation of the SOS response, which increases membrane permeability and fluidity. In addition, the accelerated TCA cycle generates a large amount of ATP, and flagellar motility was also enhanced. These actions are favorable for plasmid uptake, facilitation, and integration.</p>
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45 pages, 18356 KiB  
Review
Dual-Action Therapeutics: DNA Alkylation and Antimicrobial Peptides for Cancer Therapy
by Celia María Curieses Andrés, José Manuel Pérez de la Lastra, Elena Bustamante Munguira, Celia Andrés Juan and Eduardo Pérez-Lebeña
Cancers 2024, 16(18), 3123; https://doi.org/10.3390/cancers16183123 - 10 Sep 2024
Viewed by 516
Abstract
Cancer remains one of the most difficult diseases to treat, requiring continuous research into innovative therapeutic strategies. Conventional treatments such as chemotherapy and radiotherapy are effective to a certain extent but often have significant side effects and carry the risk of resistance. In [...] Read more.
Cancer remains one of the most difficult diseases to treat, requiring continuous research into innovative therapeutic strategies. Conventional treatments such as chemotherapy and radiotherapy are effective to a certain extent but often have significant side effects and carry the risk of resistance. In recent years, the concept of dual-acting therapeutics has attracted considerable attention, particularly the combination of DNA alkylating agents and antimicrobial peptides. DNA alkylation, a well-known mechanism in cancer therapy, involves the attachment of alkyl groups to DNA, leading to DNA damage and subsequent cell death. Antimicrobial peptides, on the other hand, have been shown to be effective anticancer agents due to their ability to selectively disrupt cancer cell membranes and modulate immune responses. This review aims to explore the synergistic potential of these two therapeutic modalities. It examines their mechanisms of action, current research findings, and the promise they offer to improve the efficacy and specificity of cancer treatments. By combining the cytotoxic power of DNA alkylation with the unique properties of antimicrobial peptides, dual-action therapeutics may offer a new and more effective approach to fighting cancer. Full article
(This article belongs to the Special Issue Novel Therapeutic Approaches for Cancer Treatment)
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<p>Classification of oncological drugs and mechanism of action of each drug type.</p>
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<p>Modes of ligand binding to DNA. DNA can bind to small molecules or drugs through covalent or non-covalent interactions. Covalent binding in DNA can be irreversible and can lead to inhibition of all DNA processes that subsequently lead to cell death. Covalent interactions lead to permanent changes in the structure of nucleic acids. Non-covalent interaction of molecules with DNA can be due to electrostatic interaction, intercalation, and groove binding.</p>
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<p>Types of cancers treated with alkylating agents.</p>
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<p>Different types of links produced on DNA by bis-alkylating agents.</p>
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<p>Classification of antineoplastics–alkylating agents according to the reactive groups. They may act as monofunctional agents or may form bifunctional derivatives by forming cross-links (inter- or intra-chain) in DNA or between DNA and proteins.</p>
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<p>Arrows indicate DNA base alkylation sites.</p>
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<p>In situ generation of an aziridinium cation.</p>
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<p>Mechlorethamine structure.</p>
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<p>Phosphamide nitrogen mustard.</p>
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<p>Biotransformation mechanism of cyclophosphamide.</p>
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<p>Mechanism of acrolein toxicity.</p>
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<p>Spontaneous decomposition of Maphosphamide into 4-HO-CP and mesna.</p>
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<p>Activation of trophosphamide by cytochrome P450 into oxazaphosphorine mustards. N-dealkylation by cytochrome P450s results in the formation of inactive metabolites and chloracetaldehyde.</p>
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<p>Chemical structure of (S)-(-)-Bromophosphamide Gluphosphamide (β-D-glucoseisophosphoramide-mustard).</p>
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<p>Aromatic nitrogen mustards.</p>
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<p>Chemical synthesis of Estramustine phosphate sodium.</p>
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<p>Chemical synthesis of Prednimustine.</p>
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<p>Chemical structure of Lactandrate and Lactestoxate.</p>
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<p>Chemical structure of Melflufen.</p>
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<p>Metabolism of Melflufen hydrochloride.</p>
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<p>Action of alkylating agents on guanine.</p>
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<p>(<b>A</b>) DNA monoalkylation and dialkylation mechanism. (<b>B</b>) DNA–protein complexes.</p>
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<p>Hydrogen bonding interactions in guanine–cytosine and guanine–thymine pairs.</p>
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<p>Cleavage of the heteroside bond.</p>
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<p>DNA fragmentation that takes place following guanine monoalkylation.</p>
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<p>The first compounds derived from aziridines introduced into therapeutics.</p>
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<p>Monoalkylation of guanine by thiotepa.</p>
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<p>(<b>A</b>) alkylation and cross-linking by sequential reaction of a single aziridine group. (<b>B</b>) Cross-linking produced by sequential alkylating reactions of two aziridine groups of thiotepa.</p>
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<p>Chemical structure of mitomycins.</p>
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<p>Bioreductive alkylation of DNA by mitomycin C.</p>
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<p>Chemical structure of Aziridinylquinones.</p>
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<p>Chemical structure of AzGalp.</p>
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<p>Reduction mechanism and structure of cross-links in DNA by aziridinylbenzoquinone derivatives.</p>
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<p>Inactivation of aziridinium benzoquinones (<b>A</b>) with loss of the aziridine ring and (<b>B</b>) initiated by a 1,5-sigmatropic shift.</p>
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<p>Inactivation of hydroquinone forms of aziridinylbenzoquinones by one-electron reduction.</p>
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<p>(<b>A</b>) DNA alkylation by mitobronitol and (<b>B</b>) DNA alkylation by treosulphan.</p>
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<p>Chemical structure of the main nitrosoureas.</p>
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<p>(<b>A</b>) Decomposition of nitrosoureas under anhydrous conditions. (<b>B</b>) In aqueous solution with the products of the alkylation of DNA and proteins.</p>
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<p>DNA cross-linking by nitrosoureas.</p>
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<p>Mesylate ion resonant forms and average structure.</p>
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<p>Methanesulphonate used as antitumor agents.</p>
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<p>(<b>A</b>) Alkylation of cysteine residues by busulphan and (<b>B</b>) mechanism of DNA alkylation by busulphan.</p>
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<p>Current therapeutic use triazenes.</p>
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<p>Generation of methanediazonium from dacarbazine.</p>
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<p>Mechanism of DNA methylation by Dacarbazine.</p>
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<p>Dacarbazine photodegradation products.</p>
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<p>Temozolomide hydrolysis.</p>
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<p>Advantages of antimicrobial peptides in combination with alkylating agents for cancer therapy.</p>
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<p>Technological advances in the administration of AMPs and alkylating drugs for cancer therapy.</p>
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32 pages, 2904 KiB  
Article
Per- and Polyfluoroalkyl Substances in the Duluth, Minnesota Area: Exposure to and Biomarker Responses in Tree Swallows Relative to Known Fire-Fighting Foam Sources
by Christine M. Custer, Paul M. Dummer, Matthew A. Etterson, Jonathan T. Haselman, Sandra Schultz, Natalie Karouna-Renier and Cole Matson
Toxics 2024, 12(9), 660; https://doi.org/10.3390/toxics12090660 - 10 Sep 2024
Viewed by 309
Abstract
Tree swallow nest boxes were deployed at sites proximal to two putative aqueous film forming foam (AFFF) sources in the Duluth, MN area, as well as along the St. Louis River and a reference lake for comparative purposes in 2019, 2020 and 2021. [...] Read more.
Tree swallow nest boxes were deployed at sites proximal to two putative aqueous film forming foam (AFFF) sources in the Duluth, MN area, as well as along the St. Louis River and a reference lake for comparative purposes in 2019, 2020 and 2021. The two AFFF sites were the current Duluth Air National Guard Base (ANG) and the Lake Superior College Emergency Response Training Center. Between 13 and 40 per- and polyfluoroalkyl substances (PFAS), depending on year, were detected and quantified in tree swallow egg, nestling carcasses, and stomach contents. Assessments were made of oxidative stress and ethoxyresorufin-O-dealkylase activity in liver tissue, thyroid hormone levels in plasma and thyroid glands, DNA damage in red blood cells, and two measures of immune response (haptoglobin-like activity and immunoglobulin) in plasma of the nestlings. Additionally, other contaminants, such as polychlorinated biphenyls, legacy organochlorine pesticides, and trace elements, were assessed at sites with no previous data. Total egg PFAS concentrations at the ANG site and north of that site were 30–40 times higher than at the reference lake, while nestling PFAS concentrations were 10–15 times higher. In contrast, the St. Louis River sites had slightly, but non-statistically significant, elevated egg and nestling PFAS concentrations relative to the reference lake (2–5 times higher). One PFAS, perfluorohexane sulfonate (PFHxS), was higher, as a proportion of total PFAS, at sites with a known AFFF source compared to the reference lake, as well as compared to sites along the St. Louis River with mainly urban and industrial sources of PFAS. The ratio of total carboxylates to total sulfonates also distinguished between PFAS sources. There were few to no differences in biomarker responses among sites, and no association with PFAS exposure. Full article
(This article belongs to the Special Issue Ecotoxicology and Ecological Risks of PFAS)
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<p>Map of per- and polyfluorinated substances (PFAS) study sites in the Duluth, MN area 2019–2021. Two underlined site names are known as locations at which aqueous film forming foams (AFFFs) were used. Note: ANG = Duluth Air National Guard Base and UMD = farm at University of Minnesota, Duluth.</p>
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<p>Correlation between original 13 (PFAS<sub>13</sub>) and current 40 (PFAS<sub>40</sub>) per- and polyfluoroalkyl substances (PFAS) in tree swallow eggs from the Duluth, MN area in 2021. Lower panel is an enlargement of the lower end of the distribution.</p>
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<p>Total mass (ng) of perfluorooctane sulfonate (PFOS) in pairs of eggs and sibling 12- to 15-day old nestlings at Rice Lake North and the reference site (Boulder Lake, upper panel) in the Duluth, MN area in 2020–2021. Lower panel is expanded to provide more detail at the reference lake. Average accumulation rates (ng/day) are provided for the two sites.</p>
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<p>Correlation between the sum of 40 per- and polyfluoroalkyl substances (PFAS<sub>40</sub>) in diet and nestling carcasses (<b>upper</b>) and diet and eggs (<b>lower</b>) from the Duluth, MN area in 2020–2021.</p>
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<p>Nonmetric multidimensional scaling (NMDS) plot of per- and polyfluoroalkyl substances (PFAS) in tree swallow nestlings (2010 and 2021) by region in the Duluth, MN area for n = 25 PFAS detected in ≥2 samples. Note: NMDS plots are unitless, AFFF = aqueous film forming foam, SLR = St. Louis River.</p>
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<p>Nonmetric multidimensional scaling (NMDS) plot of per- and polyfluoroalkyl substances (PFAS) in tree swallow egg, nestling, and diet samples (2010 and 2021) in the Duluth, MN area for n = 27 PFAS detected in ≥2 samples in at least one of the three matrices. Note that NMDS plots are unitless.</p>
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<p>Average percentage of 40 per- and polyfluoroalkyl substances (PFAS<sub>40</sub>) that individual PFAS comprised in tree swallow nestling carcasses in the three regions near Duluth, MN 2020–2021. St. Louis River includes Boy Scout Landing which has an aqueous film forming foam (AFFF) source and has been pulled out for visualization. Percentages inside circles are for perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS). Concentrations or range of total PFAS<sub>40</sub> concentrations are provided for sites within each region in parentheses. Note: AFFF = aqueous film forming foam, PFOA = perfluorooctanoate, PFNA = perfluorononanoate, PFDA = perfluorodecanoate, PFUnA = perfluoroundecanoate, PFDoA = perfluorododecanoate, PFTrDA = perfluorotridecanoate.</p>
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<p>Average percentage of 40 per- and polyfluoroalkyl substances (PFAS<sub>40</sub>) that individual PFAS comprised in tree swallow eggs in the three regions near Duluth, MN 2020–2021. St. Louis River includes Boy Scout Landing, which has been pulled out (lower right) for visualization. Percentages inside circles are for perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS). Concentrations or range of total PFAS<sub>40</sub> concentrations are provided for sites within each region in parentheses. Note: AFFF = aqueous film forming foam, PFOA = perfluorooctanoate, PFNA = perfluorononanoate, PFDA = perfluorodecanoate, PFUnA = perfluoroundecanoate, PFDoA = perfluorododecanoate, PFTrDA = perfluorotridecanoate.</p>
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<p>Ratio of total carboxylates to total sulfonates in tree swallow eggs (<b>upper</b>) and in nestlings (<b>lower</b>) at sites in the three regions near Duluth, MN, 2020–2021.</p>
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16 pages, 1596 KiB  
Review
Sperm DNA Fragmentation in Male Infertility: Tests, Mechanisms, Meaning and Sperm Population to Be Tested
by Donata Conti, Costanza Calamai and Monica Muratori
J. Clin. Med. 2024, 13(17), 5309; https://doi.org/10.3390/jcm13175309 - 7 Sep 2024
Viewed by 479
Abstract
Sperm DNA fragmentation (sDF) is a DNA damage able to predict natural conception. Thus, many laboratories added tests for the detection of sDF as an adjunct to routine semen analysis with specific indications. However, some points related to sDF are still open. The [...] Read more.
Sperm DNA fragmentation (sDF) is a DNA damage able to predict natural conception. Thus, many laboratories added tests for the detection of sDF as an adjunct to routine semen analysis with specific indications. However, some points related to sDF are still open. The available tests are very different each from other, and a direct comparison, in terms of the prediction of reproductive outcomes, is mandatory. The proposed mechanisms responsible for sDF generation have not yielded treatments for men with high levels of sDF that have gained the general consent in clinical practice, thus requiring further research. Another relevant point is the biological meaning to attribute to sDF and, thus, what we can expect from tests detecting sDF for the diagnosis of male infertility. SDF can represent the “tip of iceberg” of a more extended and undetected sperm abnormality somehow impacting upon reproduction. Investigating the nature of such a sperm abnormality might provide novel insights into the link between sDF and reproduction. Finally, several studies reported an impact of native sDF on assisted reproduction technique outcomes. However, to fertilise the oocyte, selected spermatozoa are used where sDF, if present, associates with highly motile spermatozoa, which is the opposite situation to native semen, where most sDF associates with non-viable spermatozoa. Studies comparing the impact of sDF, as assessed in both native and selected spermatozoa, are needed. Full article
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<p>The main tests available for sDF detection. (<b>A</b>). SCSA. Left panel: AO-Green/AO-Red fluorescence dot plot. After excluding debris and diploid cells with a proper gate, the software calculates the DFI by the ratio red/(red + green) AO fluorescence from the raw data. DFI is represented as frequency histogram (right panel), where the percentages of DNA fragmented spermatozoa are determined (%DFI). DFI, DNA fragmentation index; DC, diploid cells; D, debris; HSD, high DNA stainability. (<b>B</b>). TUNEL. Left panel: Frequency histogram of TUNEL labelling. A negative control (absence of the enzyme TdT, solid histogram) is prepared for each patient in order to set a threshold beyond which spermatozoa are considered DNA fragmented in the test sample (open histogram). Right panel: Image of TUNEL labelling, as observed by fluorescence microscopy, showing spermatozoa with DNA fragmentation (green). Sample is counterstained by propidium iodide (red). (<b>C</b>). COMET assay. Typical patterns of spermatozoa with and without DNA fragmentation. In the former, the calculation of tail fluorescence intensity by software for image analysis is also shown. (<b>D</b>). SCD test. Typical patterns of spermatozoa with (without halo) and without DNA fragmentation (with halo). F, fragmented. The images of SCSA and COMET assay were kind gifts by, respectively, Dr. Giorgio Leter (ENEA Casaccia Research Center, Rome, Italy) and Prof. Lisa Giovannelli (Department NEUROFARBA, University of Florence, Florence, Italy).</p>
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<p>SDF detected by TUNEL in viable and non-viable spermatozoa of a native semen sample (<b>A</b>) and after selection (<b>B</b>). Note that sDF in the native semen sample is mainly associated with non-viable spermatozoa. Note also that selection deletes a large part of non-viable DNA fragmented spermatozoa and can induce de novo sDF in the viable fraction.</p>
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<p>Mechanisms and sites of origin of sDF.</p>
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<p>Two hypothetical changes in sDF amounts during sperm selection, starting from similar sDF amounts. In (<b>A</b>), selection deletes non-viable DNA fragmented spermatozoa and, thus, reduces the percentage of sDF. In (<b>B</b>), selection deletes non-viable DNA fragmented spermatozoa but induces a de novo damage in viable spermatozoa, thus increasing the percentage of sDF. Induction of sDF is due to a non-detectable sperm abnormality, present only in (<b>A</b>). Black heads, non-viable DNA fragmented spermatozoa; white heads, healthy spermatozoa; pale-grey heads, spermatozoa with a hidden abnormality; dark grey, viable DNA fragmented spermatozoa.</p>
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17 pages, 974 KiB  
Review
Protein SUMOylation and Its Functional Role in Nuclear Receptor Control
by Nele Wild, Charlotte Sophia Kaiser, Gerhard Wunderlich, Eva Liebau and Carsten Wrenger
Receptors 2024, 3(3), 408-424; https://doi.org/10.3390/receptors3030020 - 3 Sep 2024
Viewed by 486
Abstract
Post-translational protein modifications (PTMs) significantly enhance the functional diversity of proteins and are therefore important for the expansion and the dynamics of the cell’s proteome. In addition to structurally simpler PTMs, substrates also undergo modification through the reversible attachment of small proteins. The [...] Read more.
Post-translational protein modifications (PTMs) significantly enhance the functional diversity of proteins and are therefore important for the expansion and the dynamics of the cell’s proteome. In addition to structurally simpler PTMs, substrates also undergo modification through the reversible attachment of small proteins. The best understood PTM of this nature to date is the covalent conjugation of ubiquitin and ubiquitin-like proteins (UBLs) to their substrates. The protein family of small ubiquitin-like modifier (SUMO) is one of these UBLs that has received increasing scientific attention. The pathway of SUMOylation is highly conserved in all eukaryotic cells and is crucial for their survival. It plays an essential role in many biological processes, such as the maintenance of genomic integrity, transcriptional regulation, gene expression, and the regulation of intracellular signal transduction, and thereby influences DNA damage repair, immune responses, cell cycle progression, and apoptosis. Several studies have already shown that in this context protein SUMOylation is involved in the control mechanisms of various cellular receptors. This article unites data from different studies focusing on the investigation of the strictly conserved three-step enzyme cascade of protein SUMOylation and the functional analysis of the involved proteins E1, E2, and E3 and SUMOylation target proteins. Furthermore, this review highlights the role of nuclear receptor SUMOylation and its importance for the cellular functionality and disease development arising from defects in correct protein SUMOylation. Full article
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<p>Schematic illustration of the protein SUMOylation cascade. In a preliminary step, the inactive SUMO precursor protein is cleaved by a SUMO-specific SENP cysteine protease, revealing a C-terminal diglycine motif. Subsequently, SUMO is then activated in an ATP-dependent reaction by the SUMO-E1 activating enzyme, forming a thioester bond between the C-terminal diglycine motif of SUMO and the catalytically active cysteine residue of SUMO-E1. In a trans-thioester reaction, SUMO is transferred from SUMO-E1 to the catalytically active cysteine residue of the SUMO-E2 conjugating enzyme in the next step. Finally, with the help of the SUMO-E3 protein a covalent peptide bond is established between SUMO and the target protein. Since the SENP can also catalyze the deconjugation of SUMO, the overall process of post-translational protein SUMOylation is reversible [<a href="#B10-receptors-03-00020" class="html-bibr">10</a>,<a href="#B11-receptors-03-00020" class="html-bibr">11</a>]. This figure was generated with the help of BioRender.com (License #2364–1511, Toronto, ON, Canada).</p>
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<p>Schematic overview of the diverse molecular consequences of nuclear receptor SUMOylation. The SUMOylation status of nuclear receptors affects the crosstalk of the receptor with other PTMs and influences the receptor’s stability. In addition, modification by SUMO can positively or negatively influence the transcriptional regulation of specific genes. This regulates complex signal transduction pathways as well as various cellular responses and plays an essential role in different physiological contexts. Therefore, receptor SUMOylation is also involved in the pathogenesis of different diseases [<a href="#B10-receptors-03-00020" class="html-bibr">10</a>,<a href="#B59-receptors-03-00020" class="html-bibr">59</a>]. This figure was generated with the help of BioRender.com (License #2364–1511, Toronto, ON, Canada).</p>
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15 pages, 2212 KiB  
Article
Genome Sequencing of Lentinula edodes Revealed a Genomic Variant Block Associated with a Thermo-Tolerant Trait in Fruit Body Formation
by Seung-il Yoo, Suyun Moon, Chang Pyo Hong, Sin-Gi Park, Donghwan Shim and Hojin Ryu
J. Fungi 2024, 10(9), 628; https://doi.org/10.3390/jof10090628 - 2 Sep 2024
Viewed by 524
Abstract
The formation of multicellular fruiting bodies in basidiomycete mushrooms is a crucial developmental process for sexual reproduction and subsequent spore development. Temperature is one of the most critical factors influencing the phase transition for mushroom reproduction. During the domestication of mushrooms, traits related [...] Read more.
The formation of multicellular fruiting bodies in basidiomycete mushrooms is a crucial developmental process for sexual reproduction and subsequent spore development. Temperature is one of the most critical factors influencing the phase transition for mushroom reproduction. During the domestication of mushrooms, traits related to fruiting bodies have significantly impacted agricultural adaptation and human preferences. Recent research has demonstrated that chromosomal variations, such as structural variants (SVs) and variant blocks (VBs), play crucial roles in agronomic traits and evolutionary processes. However, the lack of high-quality genomic information and important trait data have hindered comprehensive identification and characterization in Lentinula edodes breeding processes. In this study, the genomes of two monokaryotic L. edodes strains, characterized by thermo-tolerance and thermo-sensitivity during fruiting body formation, were reassembled at the chromosomal level. Comparative genomic studies of four thermo-tolerant and thermo-sensitive monokaryotic L. edodes strains identified a 0.56 Mbp variant block on chromosome 9. Genes associated with DNA repair or cellular response to DNA damage stimulus were enriched in this variant block. Finally, we developed eight CAPS markers from the variant block to discriminate the thermo-tolerant traits in L. edodes cultivars. Our findings show that the identified variant block is highly correlated with the thermo-tolerant trait for fruiting body formation and that alleles present in this block may have been artificially selected during L. edodes domestication. Full article
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<p>Strain selection for analysis of high-temperature tolerance of <span class="html-italic">Lentinula edodes</span>. (<b>A</b>) Fruiting temperature range of high-temperature-tolerant (Red lines, Sanmaru1 and Sanmaru2) and high-temperature-sensitive (Blue lines, Sanjo501, Sanjo502, and Kinko135) cultivars. Red arrow indicates temperature range for thermo-tolerant cultivars, including Sanmaru1 and Sanmaru2. (<b>B</b>) Fruiting phenotypes of Sanmaru1 and Sanjo502 grown under low (10 °C) and high (25 °C) temperature conditions. Sanmaru1 showed fruiting body formation under both high and low temperature conditions, whereas Sanjo502 showed fruiting body formation under only low temperature conditions.</p>
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<p>Overview of whole-genome sequences of monokaryotic Sanmaru1-33 and Sanjo502-23. (<b>A</b>) Whole-genome sequence assembly of Sanmaru1-33 (Sanmaru) and Sanjo502-23 (Sanjo) strains. A total of 12 and 11 contigs of Sanmaru and Sanjo, respectively, were anchored to the chromosome-level genome map (Lemap 2.0) reported by Zhang et al. [<a href="#B23-jof-10-00628" class="html-bibr">23</a>]. Each track in the Circos plot, from the outside in, represents the following: each chromosome anchored to Lemap 2.0 (1st track); GC content (%) (2nd track); gene density (3rd track); transposable element (TE) density (4th track); and synteny blocks conserved between Sanmaru and Sanjo (5th track). (<b>B</b>) Quality assessment of Sanmaru and Sanjo assemblies. The left panel shows BUSCO scores for B17 [<a href="#B12-jof-10-00628" class="html-bibr">12</a>], Lemap, Sanmaru, and Sanjo assemblies. The results are categorized as complete and single-copy (Complete.SC), complete and duplicated (Complete.Du), fragmented, or missing BUSCOs. The right panel shows the number of assembled contigs in these four species. (<b>C</b>) Overlap of gene orthologous clusters between Sanmaru and Sanjo. Significant GO-enriched terms for species-specific orthologous genes with <span class="html-italic">p</span>-values are presented in the bottom rectangular box. (<b>D</b>) Carbohydrate-active enzyme (CAZyme) annotation for genes specific to Sanmaru and Sanjo.</p>
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<p>Genomic differences between Sanmaru and Sanjo. (<b>A</b>) Identification of a large variant block (VB) that predominantly consists of SNVs on chromosome 9 between Sanmaru and Sanjo relatives. (<b>B</b>) Distribution of SNVs identified in the VB region. The frequency of SNVs was calculated by dividing 1 kb of genomic features (i.e., exons, introns, or intergenic regions) in the 560 kb VB region by the number of SNVs. SNVs were categorized as missense, synonymous, intron, and intergenic. (<b>C</b>) Functional annotation of genes within the VB region. (<b>D</b>) Gene structural variation of the phospholipase C 1-encoding gene (PLC1) in the VB region. In the dot plot (978 bp) comparing Sanmaru and Sanjo, structural differences in PLC1 were identified.</p>
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<p>CAPS markers associated with high-temperature tolerance of fruiting body formation. (<b>A</b>) The restriction enzymes used in the development of CAPS markers and schematic diagrams illustrating the position of the restriction enzyme recognition sites in the marker sequence of each allele. The fragment sizes of PCR and CAPS products are shown. Additional restriction enzyme recognition sites unrelated to the target SNP (RL-LE-316_NlaIII) are indicated by black boxes. The red and blue boxes represent the restriction enzyme-recognizing and non-recognizing sites present in the high-temperature tolerance allele, respectively. (<b>B</b>) The cleaved fragment patterns of each CAPS marker among five <span class="html-italic">L. edodes</span> cultivars. Sanmaru1 and Sanmaru2 show the high-temperature-tolerant allele-specific fragment pattern. Arrowheads indicate the position of putative high-temperature-tolerant allele-specific fragments. Asterisks represent undigested bands.</p>
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22 pages, 14282 KiB  
Article
Synergistic Roles of Non-Homologous End Joining and Homologous Recombination in Repair of Ionizing Radiation-Induced DNA Double Strand Breaks in Mouse Embryonic Stem Cells
by Gerarda van de Kamp, Tim Heemskerk, Roland Kanaar and Jeroen Essers
Cells 2024, 13(17), 1462; https://doi.org/10.3390/cells13171462 - 30 Aug 2024
Viewed by 466
Abstract
DNA double strand breaks (DSBs) are critical for the efficacy of radiotherapy as they lead to cell death if not repaired. DSBs caused by ionizing radiation (IR) initiate histone modifications and accumulate DNA repair proteins, including 53BP1, which forms distinct foci at damage [...] Read more.
DNA double strand breaks (DSBs) are critical for the efficacy of radiotherapy as they lead to cell death if not repaired. DSBs caused by ionizing radiation (IR) initiate histone modifications and accumulate DNA repair proteins, including 53BP1, which forms distinct foci at damage sites and serves as a marker for DSBs. DSB repair primarily occurs through Non-Homologous End Joining (NHEJ) and Homologous Recombination (HR). NHEJ directly ligates DNA ends, employing proteins such as DNA-PKcs, while HR, involving proteins such as Rad54, uses a sister chromatid template for accurate repair and functions in the S and G2 phases of the cell cycle. Both pathways are crucial, as illustrated by the IR sensitivity in cells lacking DNA-PKcs or Rad54. We generated mouse embryonic stem (mES) cells which are knockout (KO) for DNA-PKcs and Rad54 to explore the combined role of HR and NHEJ in DSB repair. We found that cells lacking both DNA-PKcs and Rad54 are hypersensitive to X-ray radiation, coinciding with impaired 53BP1 focus resolution and a more persistent G2 phase cell cycle block. Additionally, mES cells deficient in DNA-PKcs or both DNA-PKcs and Rad54 exhibit an increased nuclear size approximately 18–24 h post-irradiation. To further explore the role of Rad54 in the absence of DNA-PKcs, we generated DNA-PKcs KO mES cells expressing GFP-tagged wild-type (WT) or ATPase-defective Rad54 to track the Rad54 foci over time post-irradiation. Cells lacking DNA-PKcs and expressing ATPase-defective Rad54 exhibited a similar phenotypic response to IR as those lacking both DNA-PKcs and Rad54. Despite a strong G2 phase arrest, live-cell imaging showed these cells eventually progress through mitosis, forming micronuclei. Additionally, mES cells lacking DNA-PKcs showed increased Rad54 foci over time post-irradiation, indicating an enhanced reliance on HR for DSB repair without DNA-PKcs. Our findings underscore the essential roles of HR and NHEJ in maintaining genomic stability post-IR in mES cells. The interplay between these pathways is crucial for effective DSB repair and cell cycle progression, highlighting potential targets for enhancing radiotherapy outcomes. Full article
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<p>mES cells lacking DNA-PK<sub>cs</sub> and Rad54 are hypersensitive to X-ray radiation. (<b>a</b>) Two independent clones of the DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>−/−</sup> mES cell line were generated in a two-step process. First, DNA-PK<sub>cs</sub><sup>−/−</sup> mES cells were targeted with a targeting construct against Rad54 containing a hygromycin resistance gene to generate DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>WT/−</sup> mES cells. Secondly, two independent DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>WT/−</sup> mES cell clones were targeted with a targeting construct against Rad54 containing a puromycin resistance gene to generate DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>−/−</sup> mES cells. (<b>b</b>) Western blot was used to confirm the lack of Rad54 and DNA-PK<sub>cs</sub> in the mES cells with the indicated genotypes. The upper Western blot in the figure shows probing for Rad54 and β-actin as the loading control. The lower Western blot in the figure shows probing for DNA-PK<sub>cs</sub> and vinculin as the loading control. (<b>c</b>) Clonogenic survival of mES cell lines with indicated genotypes after X-ray irradiation. Error bars represent SEM.</p>
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<p>mES cells lacking DNA-PK<sub>cs</sub> and Rad54 show impaired resolution of 53BP1 foci and increased nuclear size after 2 Gy of X-ray radiation. (<b>a</b>) Representative images of mES cells irradiated with 2 Gy of X-ray radiation and incubated for indicated times. After the recovery time, cells were fixed and stained for 53BP1. (<b>b</b>) Quantification of 53BP1 foci per mES nucleus (left) and area of mES nuclei (right). Error bars represent SEM.</p>
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<p>X-ray irradiation results in more persistent G2 phase cell cycle block in mES cells lacking DNA-PK<sub>cs</sub> and Rad54. (<b>a</b>) mES cells were irradiated with 1 Gy of X-ray radiation and incubated for indicated times. After recovery time, cells were fixed and stained for DAPI (DNA content), EdU (S phase cells), and phospho-H3 (mitotic (M) phase cells). Cell cycle distribution was analyzed using flow cytometry. (<b>b</b>) Quantification of percentage of G1, S, G2, and M phase cells in mES cells irradiated with 1 Gy of X-ray radiation, as shown in (<b>a</b>). (<b>c</b>) mES cells were irradiated with 1 and 2 Gy of X-ray radiation and incubated for indicated times. After recovery time, cells were fixed, and DNA was stained using Propidium Iodide. Cell cycle distribution was analyzed using flow cytometry. (<b>d</b>) Quantification of percentage of G1, S, and G2 phase cells in mES cells irradiated with 1 and 2 Gy of X-ray radiation, as shown in (<b>c</b>).</p>
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<p>X-ray irradiation results in more persistent G2 phase cell cycle block in mES cells lacking DNA-PK<sub>cs</sub> and Rad54. (<b>a</b>) mES cells were irradiated with 1 Gy of X-ray radiation and incubated for indicated times. After recovery time, cells were fixed and stained for DAPI (DNA content), EdU (S phase cells), and phospho-H3 (mitotic (M) phase cells). Cell cycle distribution was analyzed using flow cytometry. (<b>b</b>) Quantification of percentage of G1, S, G2, and M phase cells in mES cells irradiated with 1 Gy of X-ray radiation, as shown in (<b>a</b>). (<b>c</b>) mES cells were irradiated with 1 and 2 Gy of X-ray radiation and incubated for indicated times. After recovery time, cells were fixed, and DNA was stained using Propidium Iodide. Cell cycle distribution was analyzed using flow cytometry. (<b>d</b>) Quantification of percentage of G1, S, and G2 phase cells in mES cells irradiated with 1 and 2 Gy of X-ray radiation, as shown in (<b>c</b>).</p>
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<p>mES cells lacking DNA-PK<sub>cs</sub> and expressing ATPase-defective Rad54 are hypersensitive to X-ray radiation. (<b>a</b>) The DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>WT-GFP/−</sup> and DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>KR-GFP/−</sup> mES cell lines were generated by targeting the mES DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>WT/−</sup> 1 cell line with a targeting construct against Rad54 containing Rad54<sup>WT-GFP</sup> or Rad54<sup>KR-GFP</sup>. (<b>b</b>) Western blot was used to confirm the knockin of GFP-Rad54 in mES cells with the indicated genotypes. The upper Western blot in the figure shows probing for Rad54 and β-actin as the loading control. The lower Western blot in the figure shows probing for DNA-PKcs and vinculin as the loading control. (<b>c</b>) Sanger sequencing results to confirm K189R mutation in Rad54. (<b>d</b>) Clonogenic survival of mES cell lines with indicated genotypes after X-ray irradiation. Error bars represent SEM.</p>
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<p>mES cells lacking DNA-PK<sub>cs</sub> show impaired Rad54 focus resolution and increased nuclear size after 2 Gy of X-ray radiation. (<b>a</b>) Representative images of mES cells irradiated with 2 Gy of X-ray radiation and incubated for indicated times. After the recovery time, cells were fixed and imaged for Rad54. (<b>b</b>) Quantification of Rad54 foci per mES nucleus. Rad54 foci disappear in cells with enlarged nuclei (<a href="#cells-13-01462-f006" class="html-fig">Figure 6</a>); therefore, nuclei larger than 400 µm<sup>2</sup> were excluded from the analysis. Error bars represent SEM. (<b>c</b>) Quantification of area of mES nuclei. Error bars represent SEM.</p>
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<p>Rad54 foci disappear in mitotic cells and in cells with enlarged nuclei. (<b>a</b>) Representative images of live-cell imaging of WT Rad54<sup>WT-GFP/−</sup> (top) and DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>WT-GFP/−</sup> (bottom) mES cells. Top row shows the cells going through cell division with the disappearance of Rad54 foci towards cell division. Bottom row shows the cell with disappearing Rad54 foci, swelling up but with no cell division happening. (<b>b</b>) Quantification of the Rad54-GFP foci in the cells shown in (<b>a</b>). (<b>c</b>) Quantification of the percentage of dividing cells in the live-cell image. (<b>d</b>) Quantification of the percentage of cells that show a larger nuclear size.</p>
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<p>Increased micronuclei formation in mES cells lacking DNA-PK<sub>cs</sub> and expressing ATPase-defective Rad54. (<b>a</b>) Representative DAPI images of WT Rad54<sup>WT-GFP/−</sup>, WT Rad54<sup>KR-GFP/−</sup>, DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>WT-GFP/−</sup>, and DNA-PK<sub>cs</sub><sup>−/−</sup> Rad54<sup>KR-GFP/−</sup> mES cells 24 h after 2 Gy of X-ray radiation. (<b>b</b>) Quantification of the percentage of cells that have micronuclei in fixed samples. Error bars represent SEM. Asterisks represent the following <span class="html-italic">p</span>-values: * ≤ 0.05; ** ≤ 0.01 (left). Quantification of the percentage of cells that are normal, have micronuclei, or have chromatin bridges in live-cell imaging data (right). (<b>c</b>) Number of micronuclei per cell in fixed samples (left, normalized for total number of nuclei) and live-cell imaging data (right, normalized for total number of cell divisions).</p>
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12 pages, 2619 KiB  
Article
The Combined Effect of Two Alternaria Mycotoxins (Alternariol and Alternariol Monomethyl Ether) on Porcine Epithelial Intestinal Cells
by Daniela Eliza Marin, Iulian Alexandru Grosu, Gina Cecilia Pistol, Cristina Valeria Bulgaru, Ana Maria Pertea and Ionelia Taranu
Agriculture 2024, 14(9), 1478; https://doi.org/10.3390/agriculture14091478 - 30 Aug 2024
Viewed by 285
Abstract
Alternariol (AOH) and alternariol monomethyl ether (AME) are secondary metabolites produced by fungi belonging to the genus Alternaria, which generally contaminate fruits but also cereal crops and vegetables. The objective of this study was to investigate if the co-exposure of the swine [...] Read more.
Alternariol (AOH) and alternariol monomethyl ether (AME) are secondary metabolites produced by fungi belonging to the genus Alternaria, which generally contaminate fruits but also cereal crops and vegetables. The objective of this study was to investigate if the co-exposure of the swine epithelial intestinal cell line (IPEC-1) to a mixture of mycotoxins would cause an increase in toxicity as compared with exposure to a single toxin. The effects of individual toxins as well as those of their combination (1:1 ratio), in a range of 1–250 μM, were assessed in vitro for the cell viability of proliferating IPEC-1 cells and then on parameters related to the oxidative stress. Our results indicate that both AOH and AME significantly decreased the IPEC-1 cell viability, but the cytotoxicity induced by the AOH + AME combination was significantly higher than that induced by the exposure to the individual toxins. The main interaction type ranged from slight synergy for the AOH-AME combination affecting 25% of cell viability (CI = 0.88), which evolved into a synergistic effect for a higher level of cytotoxicity IL50 (CI = 0.41) and a strong synergistic effect at IL90 (CI = 0.10). In addition, we investigated the effects of two low concentrations (2.5 μM and 5 μM) of AOH and AME mycotoxins administered individually or in combination on oxidative stress in IPEC-1 cells. Both AOH and AME can induce an increase in reactive oxygen species—ROS (+) cells%—and oxidative damage in porcine IPEC-1 cells. At least an additive effect was observed when the cells were exposed to the combination of AOH-AME, consisting of an increase in the percentage of ROS (+) cells and the oxidation of lipids, proteins, and DNA as compared with the individual toxin effect. A breakdown of the antioxidant defense was observed in IPEC-1 cells after the exposure to individual toxins, related to the decrease in the activity of antioxidant enzymes superoxide dismutase (SOD) and catalase (CAT), but no additive or synergic effect resulted after the exposure to the mixture of the toxins. In conclusion, our data indicate that both AOH and AME interfere with cell proliferation and oxidative stress. Moreover, the exposure of IPEC-1 cells to the combination of AOH and AME mycotoxins had a dose-dependent synergistic effect on IPEC-1 cell viability. Also, the oxidative damage induced in IPEC-1 cells by the combination of AOH and AME was stronger than the effects of individual toxins. However, the signaling pathways responsible for the toxicity of AOH, AME, and their combinations need further investigations in order to provide important data for risk assessments in swine in the case of the contamination of feed with Alternaria toxins. Full article
(This article belongs to the Section Farm Animal Production)
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<p>The effect of exposure to 0 to 250 μM of AOH, AME, and a combination of the two on the viability of IPEC-1 cells; the results represent the mean ± standard error of the mean (SEM) of three independent experiments, n = 6. Differences among groups were tested using one-way ANOVA followed by Fisher’s PSLD test. <sup>a–h</sup> indicate significant differences between treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Dose–effect curve (<b>A</b>) and median-effect plot (<b>B</b>) for the combined AOH and AME in relation to IPEC-1 cell viability.</p>
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<p>Interrelation between combination index and fraction affected (<b>A</b>) and isobologram for the combined AOH-AME (<b>B</b>).</p>
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<p>Effect of AOH, AME, and a combination thereof on the % of ROS (+) cells. Quantification of ROS (+) cells% was performed by flow-cytometry analysis in IPEC-1 cells that underwent 24 h of exposure to AOH, AME, and a combination of the two (ratio 1:1) in concentrations from 0 to 5 μM. M1 = %ROS (−) cells; M2 = %ROS (+) cells. Figures (<b>a</b>–<b>g</b>) represent flow-cytometry histograms for different treatments; figure (<b>h</b>) represents the effect of AOH, AME, and a combination of the two on the % of ROS (+) cells; the results represent the mean ± standard error of the mean (SEM) of three independent experiments, n = 6. Differences among groups were tested using one-way ANOVA followed by Fisher’s PSLD test. <sup>a,b,c,d</sup> indicate significant differences between different treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effects of AOH, AME, and a combination of the two in concentrations from 0 to 5 μM on different parameters associated with oxidative stress—lipid oxidation (TBARSs), protein oxidation (protein carbonyl), and DNA oxidation (8 oxo dG); the results represent the mean ± standard error of the mean (SEM) of three independent experiments, n = 6. (<b>A</b>) Effect of AOH, AME, and a combination of the two on protein carbonyl concentrations; (<b>B</b>) effect of AOH, AME, and a combination of the two on TBARSs; (<b>C</b>) effect of AOH, AME, and a combination of the two on 8-Oxo-2′-deoxyguanosine. Differences among groups were tested using one-way ANOVA followed by Fisher’s PSLD test. <sup>a–e</sup> indicate significant differences between treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of AOH, AME, and their combination in concentrations from 0 to 5 μM on the activity of the enzymes involved in the oxidative stress. The activities of superoxide dismutase (SOD), figure (<b>A</b>), glutathione peroxidase (GPx), Figure (<b>B</b>), and catalase (CAT), Figure (<b>C</b>), were analyzed from IPEC-1 cell lysates; the results represent the mean ± standard error of the mean (SEM) of three independent experiments, n = 6. Differences among groups were tested using one-way ANOVA followed by Fisher’s PSLD test. <sup>a,b,c</sup> indicate significant differences between different treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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23 pages, 1736 KiB  
Review
The Potential for Targeting G2/M Cell Cycle Checkpoint Kinases in Enhancing the Efficacy of Radiotherapy
by Emma Melia and Jason L. Parsons
Cancers 2024, 16(17), 3016; https://doi.org/10.3390/cancers16173016 - 29 Aug 2024
Viewed by 359
Abstract
Radiotherapy is one of the main cancer treatments being used for ~50% of all cancer patients. Conventional radiotherapy typically utilises X-rays (photons); however, there is increasing use of particle beam therapy (PBT), such as protons and carbon ions. This is because PBT elicits [...] Read more.
Radiotherapy is one of the main cancer treatments being used for ~50% of all cancer patients. Conventional radiotherapy typically utilises X-rays (photons); however, there is increasing use of particle beam therapy (PBT), such as protons and carbon ions. This is because PBT elicits significant benefits through more precise dose delivery to the cancer than X-rays, but also due to the increases in linear energy transfer (LET) that lead to more enhanced biological effectiveness. Despite the radiotherapy type, the introduction of DNA damage ultimately drives the therapeutic response through stimulating cancer cell death. To combat this, cells harbour cell cycle checkpoints that enables time for efficient DNA damage repair. Interestingly, cancer cells frequently have mutations in key genes such as TP53 and ATM that drive the G1/S checkpoint, whereas the G2/M checkpoint driven through ATR, Chk1 and Wee1 remains intact. Therefore, targeting the G2/M checkpoint through specific inhibitors is considered an important strategy for enhancing the efficacy of radiotherapy. In this review, we focus on inhibitors of Chk1 and Wee1 kinases and present the current biological evidence supporting their utility as radiosensitisers with different radiotherapy modalities, as well as clinical trials that have and are investigating their potential for cancer patient benefit. Full article
(This article belongs to the Special Issue Personalized Radiotherapy in Cancer Care)
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<p>Overview of the cellular DDR to DSBs. Ionising radiation induces DSBs, leading to γH2AX formation stimulated by ATM, ATR and DNA-Pkcs, which recruits multiple DNA damage response proteins, including MDC1. γH2AX is targeted for ubiquitination by the RNF8-RNF168-UBC13 complex, enabling accumulation of further DDR proteins, including 53BP1, BRCA1 and the MRN complex. DSB breaks can be repaired by either NHEJ (c-NHEJ or a-NHEJ) or HR. In c-NHEJ, Ku70/80 heterodimers bind to and anchor the damaged DNA ends, which recruit DNA-Pkcs and other end-processing proteins, such as Artemis and PNKP, before ligation occurs via the XRCC4-Ligase IV-XLF complex. Alternatively in a-NHEJ, the MRN complex can bind to the DNA ends and initiate end resection with CtIP. Following this, PARP-1 binds to the DNA ends, allowing for synthesis within the break by Pol θ and ligation by either Ligase I or XRCC1-Ligase IIIα. Binding of the MRN-complex also recruits and activates ATM, which allows for a signalling cascade through Chk2, p53 and p21 for arrest at the G<sub>1</sub>/S checkpoint. During HR, EXO1, Dna2, BLM and WRN can be associated with end resection in addition to the MRN complex and CtIP, which results in ssDNA that is then coated by RPA. This simulates the activation of ATR via ATRIP which results in intra-S and G<sub>2</sub>/M checkpoint arrest, orchestrated via Chk1 and Wee1 activity. Following this, BRCA1 and its dimerization partner BARD1 interact with PALB2 and recruit BRCA2 and RAD51. RAD51 then replaces RPA to form nucleofilaments on ssDNA. The activity of RAD51 is also influenced by Chk1 (dashed arrow). RAD51-ssDNA then undergoes homology search and invasion of the sister chromatid, facilitated by BRCA2 and RAD54, and DNA synthesis is completed by either Pol δ or Pol ε. DNA ligation then forms Holliday junctions which are processed by resolvases, including MUS81-EME1/2, GEN1 and BLM-TopoIIIα-RMI1. This figure was created with Biorender.com.</p>
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<p>The major signalling roles of Chk1 and Wee1. Chk1 is phosphorylated by activated ATR at serine 317 and 345, via interaction with Claspin adaptor protein, which stimulates autophosphorylation of Chk1 at serine 296. Activated Chk1 phosphorylates histone H3 at threonine 11, which reduces acetylation and ultimately reduces transcription of various CDK and cyclin genes. The phosphatase Cdc25a is directly phosphorylated by Chk1 which targets this for ubiquitination and reduces dephosphorylation of CDK2, resulting in arrest at intra-S and G<sub>1</sub>/S checkpoints. CDK2 also influences the loading of Cdc45 during DNA replication, which is further controlled by Cdc7 that is directly phosphorylated by Chk1. Additionally, Chk1 influences genome stability during replication via phosphorylation of Tlk1 and targeting PCNA for ubiquitination. RAD51 is directly phosphorylated by Chk1 at threonine 309, which influences both DNA replication and HR. Direct phosphorylation of the phosphatase Cdc25c prevents dephosphorylation of CDK1, which results in G<sub>2</sub>/M arrest. Finally, Chk1 influences SAC activation through phosphorylation of Aurora B, which impacts the localisation of Bub1. Wee1 is also a direct target for activation by Chk1. Activated Wee1 causes phosphorylation of histone H2B at tyrosine 37, which reduces acetylation and prevents the transcription of the <span class="html-italic">Hist1</span> gene cluster. Wee1 also directly phosphorylates CDK2 and CDK1 at tyrosine 15, resulting in intra-S-G<sub>1</sub>/S and G<sub>2</sub>/M checkpoint arrest, respectively. Phosphorylated CDK1, furthermore, is able to influence MUS81-EME1 required for genome stability. Wee1 also targets various APC/C components for phosphorylation and therefore influences the activation of SAC. Finally, CDK1 stimulated phosphorylation of Wee1 at serine 123 allows for further phosphorylation via PLK1 and CK1/2 at serines 53 and 121, thus targeting Wee1 for degradation via the SCFβ-TrCP complex.</p>
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<p>Overview of our current understanding of Chk1 and Wee1 inhibitors as radiosensitisers. Ionising radiation induces DNA damage, specifically to DSBs, which stimulates the cellular DDR including cell cycle arrest. In combination with Chk1 or Wee1 inhibitors, radiation-induced arrest at both intra-S and G<sub>2</sub>/M checkpoint is abrogated, and HR repair is limited. This forces the cells through the cell cycle under replication stress and harbouring unrepaired DNA damage, resulting in mitotic catastrophe (micronuclei/fragmentation) and apoptosis, ultimately increasing cellular radiosensitivity. Preclinical evidence demonstrating the radiosensitisation potential of Chk1 and Wee1 inhibitors is listed in red, with those progressing to clinical trials (indicated with *). Despite this, there are still some uncertainties regarding the underlying mechanisms of action (highlighted in grey).</p>
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