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Int. J. Mol. Sci., Volume 23, Issue 21 (November-1 2022) – 954 articles

Cover Story (view full-size image): Neuroinflammation induces neurometabolic alterations and increases in energy consumption. The orexigenic hormone Ghrelin regulates energy balance, obesity, neuroinflammation and the occurrence of neurodegenerative diseases also acting on microglia. Microglia may be regarded as important therapeutic targets in neuroinflammation as they are able to produce a wide range of chemokines involved in the inflammatory processes of the central nervous system. Together, Ghrelin and microglia are involved in the pathophysiology of neurodegenerative diseases characterized by neuronal damage such as Alzheimer’s disease and Parkinson’s disease. Particularly, Ghrelin induces these cells towards an anti-inflammatory phenotype during obesity-induced neuroinflammation. Understanding this peptide’s functions will allow for the development of new therapeutic and neurological diagnostic strategies. View this paper
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13 pages, 2938 KiB  
Article
The Amino Acid Permease MoGap1 Regulates TOR Activity and Autophagy in Magnaporthe oryzae
by Changli Huang, Lin Li, Lei Wang, Jiandong Bao, Xiaozhi Zhang, Jiongyi Yan, Jiaqi Wu, Na Cao, Jiaoyu Wang, Lili Zhao, Xiaohong Liu, Xiaoping Yu, Xueming Zhu and Fucheng Lin
Int. J. Mol. Sci. 2022, 23(21), 13663; https://doi.org/10.3390/ijms232113663 - 7 Nov 2022
Cited by 2 | Viewed by 2982
Abstract
Rice is an important food crop all over the world. It can be infected by the rice blast fungus Magnaporthe oryzae, which results in a significant reduction in rice yield. The infection mechanism of M. oryzae has been an academic focus for [...] Read more.
Rice is an important food crop all over the world. It can be infected by the rice blast fungus Magnaporthe oryzae, which results in a significant reduction in rice yield. The infection mechanism of M. oryzae has been an academic focus for a long time. It has been found that G protein, AMPK, cAMP-PKA, and MPS1-MAPK pathways play different roles in the infection process. Recently, the function of TOR signaling in regulating cell growth and autophagy by receiving nutritional signals generated by plant pathogenic fungi has been demonstrated, but its regulatory mechanism in response to the nutritional signals remains unclear. In this study, a yeast amino acid permease homologue MoGap1 was identified and a knockout mutant of MoGap1 was successfully obtained. Through a phenotypic analysis, a stress analysis, autophagy flux detection, and a TOR activity analysis, we found that the deletion of MoGap1 led to a sporulation reduction as well as increased sensitivity to cell wall stress and carbon source stress in M. oryzae. The ΔMogap1 mutant showed high sensitivity to the TOR inhibitor rapamycin. A Western blot analysis further confirmed that the TOR activity significantly decreased, which improved the level of autophagy. The results suggested that MoGap1, as an upstream regulator of TOR signaling, regulated autophagy and responded to adversities such as cell wall stress by regulating the TOR activity. Full article
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Figure 1
<p>Identification of MoGap1 in <span class="html-italic">M. oryzae</span>. (<b>A</b>) Gap1 proteins of <span class="html-italic">M. oryzae</span>, <span class="html-italic">S. cerevisiae</span>, <span class="html-italic">S. pombe</span>, <span class="html-italic">C. truncatum</span>, and <span class="html-italic">F. graminearum</span> shown using IBS 1.0 software. Lysp: amino acid permease domain. (<b>B</b>) Schematic diagram of a Gap1 protein that contained 13 transmembrane regions. (<b>C</b>) Phylogenetic trees of the Gap1 proteins constructed using MEGA 7.0. (<b>D</b>) Multiple sequence alignment shown using DNAMAN software.</p>
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<p>Colony morphology and sporulation of <span class="html-italic">M. oryzae</span>. (<b>A</b>) Colony morphology of Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> after 9 days of culture. (<b>B</b>) The conidia of Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> stained using DAPI and CFW on a scale of 10 μm. (<b>C</b>) Relative spore formation of Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> after 9 days of culture, the first of which differed significantly from the others. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>MoGap1 responses to rapamycin stress. (<b>A</b>) The growth of Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> for 8 days of culture on CM and Rap for 8 days, respectively. (<b>B</b>) The inhibition rates of rapamycin in Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> calculated by measuring the growth diameters, which were significantly different between MoGap1 and Guy11 (** <span class="html-italic">p</span> &lt; 0.01). (<b>C</b>) The growth rate was observed in CM liquid medium. The dry weights of Guy11 and Δ<span class="html-italic">Mogap1</span> were calculated after being cultured in CM liquid medium for 2 days. (<b>D</b>) Virulence detection in Δ<span class="html-italic">Mogap1</span> mutant. The conidia (1 × 10<sup>5</sup> spores/mL) were incubated on 2-week-old barley and cultured at 25 °C for 4 days.</p>
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<p>MoGap1 negatively regulates autophagy. (<b>A</b>) MoRps6 phosphorylation levels of Guy11 and Δ<span class="html-italic">Mogap1</span> after 0 h and 4 h of 30 ng/mL rapamycin induction with GAPDH as internal reference. (<b>B</b>) The phosphorylation levels of MoRps6 were calculated and graphed using Prism 7.0 software (<span class="html-italic">t</span>-test; ns: no significant, ** <span class="html-italic">p</span> &lt; 0.01). (<b>C</b>) Autophagy flux was observed in the wild-type Guy11 and Δ<span class="html-italic">Mogap1</span> strain in CM and starvation conditions. Bar = 10 μm. (<b>D</b>) Expression levels of GFP-MoAtg8 and GFP in Guy11 and Δ<span class="html-italic">Mogap1</span>, respectively, after SD-N starvation with GAPDH as internal reference.</p>
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<p>Effect of MoGap1 on CWI. (<b>A</b>) The growth performance of Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> under hypertonic stress (NaCl medium, KCl medium, and SBT medium), cell wall stress (SDS medium and CR medium), or starvation stress (SD-N medium). (<b>B</b>) The inhibition rates of Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> in different stress media, in which those between Δ<span class="html-italic">Mogap1</span> by CR and Guy11 were significantly different (* <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Utilization of different carbon sources in Δ<span class="html-italic">Mogap1</span>. (<b>A</b>) The growth of Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> with different C sources. (<b>B</b>) The relative growth rates of Guy11, Δ<span class="html-italic">Mogap1</span>, and Δ<span class="html-italic">Mogap1-C</span> with different C sources. With oleic acid, mandelic acid, or palmitic acid as the C source, the relative growth rates of Guy11 and Δ<span class="html-italic">Mogap1</span> were significantly different from each other. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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16 pages, 40300 KiB  
Article
Phosphorylcholine Monoclonal Antibody Therapy Decreases Intraplaque Angiogenesis and Intraplaque Hemorrhage in Murine Vein Grafts
by Fabiana Baganha, Thijs J. Sluiter, Rob C. M. de Jong, Louise A. van Alst, Hendrika A. B. Peters, J. Wouter Jukema, Mirela Delibegovic, Knut Pettersson, Paul H. A. Quax and Margreet R. de Vries
Int. J. Mol. Sci. 2022, 23(21), 13662; https://doi.org/10.3390/ijms232113662 - 7 Nov 2022
Cited by 3 | Viewed by 2507
Abstract
Phosphorylcholine (PC) is one of the main oxLDL epitopes playing a central role in atherosclerosis, due to its atherogenic and proinflammatory effects. PC can be cleared by natural IgM antibodies and low levels of these antibodies have been associated with human vein graft [...] Read more.
Phosphorylcholine (PC) is one of the main oxLDL epitopes playing a central role in atherosclerosis, due to its atherogenic and proinflammatory effects. PC can be cleared by natural IgM antibodies and low levels of these antibodies have been associated with human vein graft (VG) failure. Although PC antibodies are recognized for their anti-inflammatory properties, their effect on intraplaque angiogenesis (IPA) and intraplaque hemorrhage (IPH)—interdependent processes contributing to plaque rupture—are unknown. We hypothesized that new IgG phosphorylcholine antibodies (PC-mAb) could decrease vulnerable lesions in murine VGs.Therefore, hypercholesterolemic male ApoE3*Leiden mice received a (donor) caval vein interposition in the carotid artery and weekly IP injections of (5 mg/kg) PCmAb (n = 11) or vehicle (n = 12) until sacrifice at day 28. We found that PCmAb significantly decreased vein graft media (13%), intima lesion (25%), and increased lumen with 32% compared to controls. PCmAb increased collagen content (18%) and decreased macrophages presence (31%). PCmAb resulted in 23% decreased CD163+ macrophages content in vein grafts whereas CD163 expression was decreased in Hb:Hp macrophages. PCmAb significantly lowered neovessel density (34%), EC proliferation and migration with/out oxLDL stimulation. Moreover, PCmAb enhanced intraplaque angiogenic vessels maturation by increasing neovessel pericyte coverage in vivo (31%). Together, this resulted in a 62% decrease in IPH. PCmAb effectively inhibits murine atherosclerotic lesion formation in vein grafts by reducing IPA and IPH via decreased neovessel density and macrophages influx and increased neovessel maturation. PC-mAb therefore holds promise as a new therapeutic approach to prevent vein graft disease. Full article
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Graphical abstract

Graphical abstract
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<p>PC-mAb decreases intimal hyperplasia and increases lumen area in vein graft atherosclerosis. Masson Trichrome staining representative vein grafts cross-sections (<bold>A</bold>) of hypercholesteraemic ApoE3*L mice treated with 0.9% NaCl sterile solution (n = 12) and 5 mg/kg of PC-mAb (n = 11). Quantitative measurements of Vessel Area (= Vessel wall area + lumen) (<bold>B</bold>), Vessel Wall Area (<bold>C</bold>), Intimal Hyperplasia (<bold>D</bold>) and Lumen Area (<bold>E</bold>). Data presented as mean ± SEM. * <italic>p</italic> ≤ 0.05 by <italic>t</italic>-test.</p>
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<p>PC-mAb improves plaque stability by increasing collagen content in vein graft atherosclerosis. Representative vein grafts cross sections (<bold>A</bold>) of Sirus Red Staining, Actin alpha 2 (ACTA2) and Masson Trichrome of CTRL (n = 12) and PC-mAb group (n = 11). Quantitative measurements of % Collagen (<bold>B</bold>), % ACTA2 area (<bold>C</bold>). Data presented as mean ± SEM. * <italic>p</italic> ≤ 0.05 by <italic>t</italic>-test.</p>
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<p>PC-mAb improves plaque inflammation by decreasing macrophage content and VCAM and ICAM expression. Quantification of % MAC-3 (<bold>A</bold>), Representative VG sections (<bold>B</bold>) and adhesion and inflammation associated factors ICAM-1 (<bold>C</bold>), VCAM-1 (<bold>D</bold>) and MCP-1 (<bold>E</bold>) expression in the CTRL (n = 12) and PC-mAb group (n = 11). Representative VG sections (<bold>F</bold>) Data presented as mean ± SEM. * <italic>p</italic> ≤ 0.05, ** <italic>p</italic> ≤ 0.01 by <italic>t</italic>-test.</p>
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<p>PC-mAb reduces plaque neovessel density and increases vessel maturity, reducing intraplaque hemorrhage. (<bold>A</bold>) Representative vein grafts cross sections of CD31 (orange), ACTA2 (green), TER119 (red) and DAPI (blue) staining of CTRL and PC-mAb group. Quantitative measurements of % Neovessels based on the CD31 staining (<bold>B</bold>) and % Immature Neovessels as shown by the lack of ACTA2 coverage (<bold>C</bold>) and Intraplaque Hemorrhage (Ter119+ erythrocytes outside the neovessel) (<bold>D</bold>) scoring in the CTRL (n = 12) and PC-mAb group (n = 11). Data presented as mean ± SEM. ** <italic>p</italic> ≤ 0.01, *** <italic>p</italic> ≤ 0.001 by <italic>t</italic>-test.</p>
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<p>PC-mAb reduces HUVEC metabolic activity and HUVEC migration in vitro and neovessel sprouting ex vivo. Quantification of PC-mAb effects on the MMT assay (<bold>A</bold>), on the migration assay (<bold>B</bold>), and on the aortic ring assay (<bold>C</bold>). Representative images of the scratches on HUVEC mono-layers (<bold>B</bold>) treated with increasing doses of PC-mAb and with and without 5 µg/mL oxLDL, 16 h after scratching. Representative images of the aortic rings (<bold>C</bold>) treated with VEGF and PC-mAb. (<bold>A</bold>) Data normalized to CTRL group (indicated as 1 by a dashed line in the graph) and presented as mean ± SEM (n = 3). * <italic>p</italic> &lt; 0.05, by 1-way ANOVA (*are significances versus control). (<bold>B</bold>) Data presented as mean ± SEM (n = 3). * <italic>p</italic> &lt; 0.05, *** <italic>p</italic> &lt; 0.001; by 2-way ANOVA. (<bold>C</bold>) Data presented as mean ± SEM (n = 3) by 1-way ANOVA.</p>
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<p>PC-mAb targets M(Hb) macrophages in vivo and in vitro by decreasing CD163 expression. Quantification of CD163 expression in VG lesions (<bold>A</bold>) and representative cross sections of CD163 (red) and DAPI (blue) staining of CTRL and PC-mAb group (<bold>B</bold>). Quantification of CD163 expression in THP-1 cells treated with increasing doses of PC-mAb and with and without Hb:Hp (H:H) (<bold>C</bold>).Quantification of VEFG levels in THP-1 cell supernatant (<bold>D</bold>). Data presented as mean ± SEM. * <italic>p</italic> ≤ 0.05, ** <italic>p</italic> ≤ 0.01 by <italic>t</italic>-test and by 1-way ANOVA.</p>
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17 pages, 1070 KiB  
Review
Vitamin D-Related Genes and Thyroid Cancer—A Systematic Review
by Adam Maciejewski and Katarzyna Lacka
Int. J. Mol. Sci. 2022, 23(21), 13661; https://doi.org/10.3390/ijms232113661 - 7 Nov 2022
Cited by 4 | Viewed by 3159
Abstract
Vitamin D, formerly known for its role in calcium-phosphorus homeostasis, was shown to exert a broad influence on immunity and on differentiation and proliferation processes in the last few years. In the field of endocrinology, there is proof of the potential role of [...] Read more.
Vitamin D, formerly known for its role in calcium-phosphorus homeostasis, was shown to exert a broad influence on immunity and on differentiation and proliferation processes in the last few years. In the field of endocrinology, there is proof of the potential role of vitamin D and vitamin D-related genes in the pathogenesis of thyroid cancer—the most prevalent endocrine malignancy. Therefore, the study aimed to systematically review the publications on the association between vitamin D-related gene variants (polymorphisms, mutations, etc.) and thyroid cancer. PubMed, EMBASE, Scopus, and Web of Science electronic databases were searched for relevant studies. A total of ten studies were found that met the inclusion criteria. Six vitamin D-related genes were analyzed (VDR—vitamin D receptor, CYP2R1—cytochrome P450 family 2 subfamily R member 1, CYP24A1—cytochrome P450 family 24 subfamily A member 1, CYP27B1—cytochrome P450 family 27 subfamily B member 1, DHCR7—7-dehydrocholesterol reductase and CUBN—cubilin). Moreover, a meta-analysis was conducted to summarize the data from the studies on VDR polymorphisms (rs2228570/FokI, rs1544410/BsmI, rs7975232/ApaI and rs731236/TaqI). Some associations between thyroid cancer risk (VDR, CYP24A1, DHCR7) or the clinical course of the disease (VDR) and vitamin D-related gene polymorphisms were described in the literature. However, these results seem inconclusive and need validation. A meta-analysis of the five studies of common VDR polymorphisms did not confirm their association with increased susceptibility to differentiated thyroid cancer. Further efforts are necessary to improve our understanding of thyroid cancer pathogenesis and implement targeted therapies for refractory cases. Full article
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Figure 1
<p>Known pathways mediating vitamin D action in thyroid cancer cells. CCL2—C-C motif chemokine ligand 2; ERK—extracellular signal-regulated kinase; FN—fibronectin; FOXO3a—forkhead box protein O3a; MEK—mitogen-activated protein kinase kinase 1; PI3K—phosphoinositide 3-kinase; PTEN—phosphatase and tensin homolog; PTPN2—protein tyrosine phosphatase N 2; SIRT1—sirtuin 1 histon deacethylase; STAT3—signal transducer and activator of transcription 3; VDR—vitamin D receptor. Red lines—inhibition; blue lines—stimulation.</p>
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<p>Vitamin D metabolism (including molecules/enzymes involved, coding genes in brackets): Cubilin (<span class="html-italic">CUBN</span>); DBP—vitamin D binding protein (<span class="html-italic">GC</span>); Megalin (<span class="html-italic">LRP2</span>); VDR—vitamin D receptor (<span class="html-italic">VDR</span>); 1—UVB radiation, 290–315 mm wavelength; 2—nonenzymatic isomerization reaction under the temperature; 3—25-hydroxylase (main enzyme—<span class="html-italic">CYP2R1</span>—cytochrome P450 family 2 subfamily R member 1, minor role of <span class="html-italic">CYP27A1</span>—cytochrome P450 family 27 subfamily A member 1); 4—1α-hydroxylase (<span class="html-italic">CYP27B1</span>—cytochrome P450 family 27 subfamily B member 1); 5—24-hydroxylase (<span class="html-italic">CYP24A1</span>—cytochrome P450 family 24 subfamily A member 1); 6—7-dehydrocholesterol reductase (<span class="html-italic">DHCR7</span>); 7—cholesterol side-chain cleavage enzyme (<span class="html-italic">CYP11A1—</span>cytochrome P450 family 11 subfamily A member 1).</p>
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<p>Flow diagram demonstrating the search and selection process for articles.</p>
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17 pages, 3307 KiB  
Article
De Novo Transcriptome Assembly and Analysis of Longevity Genes Using Subterranean Termite (Reticulitermes chinensis) Castes
by Haroon, Yu-Xin Li, Chen-Xu Ye, Jian Su, Ghulam Nabi, Xiao-Hong Su and Lian-Xi Xing
Int. J. Mol. Sci. 2022, 23(21), 13660; https://doi.org/10.3390/ijms232113660 - 7 Nov 2022
Cited by 1 | Viewed by 2010
Abstract
The longevity phenomenon is entirely controlled by the insulin signaling pathway (IIS-pathway). Both vertebrates and invertebrates have IIS-pathways that are comparable to one another, though no one has previously described de novo transcriptome assembly of IIS-pathway-associated genes in termites. In this research, we [...] Read more.
The longevity phenomenon is entirely controlled by the insulin signaling pathway (IIS-pathway). Both vertebrates and invertebrates have IIS-pathways that are comparable to one another, though no one has previously described de novo transcriptome assembly of IIS-pathway-associated genes in termites. In this research, we analyzed the transcriptomes of both reproductive (primary kings “PK” and queens “PQ”, secondary worker reproductive kings “SWRK” and queens “SWRQ”) and non-reproductive (male “WM” and female “WF” workers) castes of the subterranean termite Reticulitermes chinensis. The goal was to identify the genes responsible for longevity in the reproductive and non-reproductive castes. Through transcriptome analysis, we annotated 103,589,264 sequence reads and 184,436 (7G) unigenes were assembled, GC performance was measured at 43.02%, and 64,046 sequences were reported as CDs sequences. Of which 35 IIS-pathway-associated genes were identified, among 35 genes, we focused on the phosphoinositide-dependent kinase-1 (Pdk1), protein kinase B2 (akt2-a), tuberous sclerosis-2 (Tsc2), mammalian target of rapamycin (mTOR), eukaryotic translation initiation factor 4E (EIF4E) and ribosomal protein S6 (RPS6) genes. Previously these genes (Pdk1, akt2-a, mTOR, EIF4E, and RPS6) were investigated in various organisms, that regulate physiological effects, growth factors, protein translation, cell survival, proliferation, protein synthesis, cell metabolism and survival, autophagy, fecundity rate, egg size, and follicle number, although the critical reason for longevity is still unclear in the termite castes. However, based on transcriptome profiling, the IIS-pathway-associated genes could prolong the reproductive caste lifespan and health span. Therefore, the transcriptomic shreds of evidence related to IIS-pathway genes provide new insights into the maintenance and relationships between biomolecular homeostasis and remarkable longevity. Finally, we propose a strategy for future research to decrypt the hidden costs associated with termite aging in reproductive and non-reproductive castes. Full article
(This article belongs to the Section Molecular Genetics and Genomics)
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<p>KEGG classifications of the <span class="html-italic">R. chinensis</span> unigenes. (<b>A</b>) PK-vs-SWRK; (<b>B</b>) PQ-vs-SWRQ; (<b>C</b>) SWRK-vs-SWRQ; (<b>D</b>) WF-vs-SWRQ; (<b>E</b>) WM-vs-SWRK. PKs (primary king), PQs (primary queen), SWRK (secondary worker reproductive king), SWRQ (secondary worker reproductive queen), WMs (workers male), and WFs (female workers), with 93,078 unigenes were assigned to 343 pathways.</p>
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<p>Histogram presentation of the Gene Ontology (GO) classification in each caste. (<b>A</b>) PK-vs-SWRK; (<b>B</b>) PQ-vs-SWRQ; (<b>C</b>) SWRK-vs-SWRQ; (<b>D</b>) WF-vs-SWRQ; (<b>E</b>) WM-vs-SWRK. PKs (primary king), PQs (primary queen), SWRK (secondary worker reproductive king), SWRQ (secondary worker reproductive queen), WMs (workers male), and WFs (female workers). The figure represents the up (red) and down (green) categorical presentation of biological processes, cellular components, and molecular functions. The <span class="html-italic">x</span>-axis indicates the names of genes in a category, and the <span class="html-italic">y</span>-axis shows the number of genes in the main category.</p>
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<p>Differential expression of genes (DEGs) analysis across distinct castes of <span class="html-italic">R. chinensis</span> (SWRQ-vs-SWRK, PQ-vs-PK, and WM-vs-WF). The red column represents DEGs that are down-regulated, whereas the green column indicates DEGs that are up-regulated. To determine the significance of gene expression changes, FDR ≤ 0.001 and log2Ratio ≥ 1 were employed as thresholds.</p>
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<p>Analysis of DEGs for enhancement across different castes (<b>A</b>–<b>E</b>). PK (primary king), PQ (primary queen), SWRK (secondary worker reproductive king), SWRQ (secondary worker reproductive queen), WM (male worker), and WF (female worker). The volcano plots indicate enriched DEGs expressing genes in the PK, PQ, SWRK, SWRQ, WM, and WF, with a significantly up-regulated (red) and down-regulated (blue). The threshold level for judging the significance of differences in gene expression, FDR ≤ 0.001 and log2Ratio ≥ 1 parameter were used.</p>
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<p>The heat map indicates the differentially expressed gene (DEGs) involved in the insulin signaling pathway in different castes of <span class="html-italic">R. chinensis</span>. The castes are SWRK, SWRQ, PQ, PK, WM, and WF. A change in color from red to blue indicates the gene expression level.</p>
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<p>Log2 fold changes in the insulin signaling pathway in <span class="html-italic">R. chinensis</span> castes SWRK, SWRQ, PK, PQ, WM, and WF. Differential expression of genes in each group is shown as log2 fold changes compared to the reference group. The y-axis represents the log2 fold changes, and the x-axis shows the gene name and individual caste name.</p>
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17 pages, 2190 KiB  
Article
Fine Mapping and Candidate Gene Analysis of Pm36, a Wild Emmer-Derived Powdery Mildew Resistance Locus in Durum Wheat
by Domenica Nigro, Antonio Blanco, Luciana Piarulli, Massimo Antonio Signorile, Pasqualina Colasuonno, Emanuela Blanco and Rosanna Simeone
Int. J. Mol. Sci. 2022, 23(21), 13659; https://doi.org/10.3390/ijms232113659 - 7 Nov 2022
Cited by 4 | Viewed by 2173
Abstract
Powdery mildew (PM) is an economically important foliar disease of cultivated cereals worldwide. The cultivation of disease-resistant varieties is considered the most efficient, sustainable and economical strategy for disease management. The objectives of the current study were to fine map the chromosomal region [...] Read more.
Powdery mildew (PM) is an economically important foliar disease of cultivated cereals worldwide. The cultivation of disease-resistant varieties is considered the most efficient, sustainable and economical strategy for disease management. The objectives of the current study were to fine map the chromosomal region harboring the wild emmer PM resistance locus Pm36 and to identify candidate genes by exploiting the improved tetraploid wheat genomic resources. A set of backcross inbred lines (BILs) of durum wheat were genotyped with the SNP 25K chip array and comparison of the PM-resistant and susceptible lines defined a 1.5 cM region (physical interval of 1.08 Mb) harboring Pm36. The genetic map constructed with F2:3 progenies derived by crossing the PM resistant line 5BIL-42 and the durum parent Latino, restricted to 0.3 cM the genetic distance between Pm36 and the SNP marker IWB22904 (physical distance 0.515 Mb). The distribution of the marker interval including Pm36 in a tetraploid wheat collection indicated that the positive allele was largely present in the domesticated and wild emmer Triticum turgidum spp. dicoccum and ssp. dicoccoides. Ten high-confidence protein coding genes were identified in the Pm36 region of the emmer, durum and bread wheat reference genomes, while three added genes showed no homologous in the emmer genome. The tightly linked markers can be used for marker-assisted selection in wheat breeding programs, and as starting point for the Pm36 map-based cloning. Full article
(This article belongs to the Special Issue Plant Genomics and Bioinformatics)
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<p>Fine mapping of the wild emmer-derived powdery mildew resistance <span class="html-italic">Pm36</span> locus using homozygous backcross inbred lines (BILs) of durum wheat. (<b>a</b>) Physical location of <span class="html-italic">Pm36</span> on the 5BL chromosome arm (bin 5BL_1) (blue block); (<b>b</b>) Genetic map of the 5BL region harboring <span class="html-italic">Pm36</span> with the genetic position (cM) of relevant SNP markers according to the consensus durum map [<a href="#B44-ijms-23-13659" class="html-bibr">44</a>]; (<b>c</b>,<b>d</b>) Schematic representation of the durum wheat Svevo reference genome (grey block) [<a href="#B45-ijms-23-13659" class="html-bibr">45</a>] and the <span class="html-italic">dicoccoides</span> Zavitan reference genome v2.0 (red block) [<a href="#B46-ijms-23-13659" class="html-bibr">46</a>] with the physical position (Mb) of relevant SNP markers; (<b>e</b>) Genotype and phenotype of four BILs (5BIL-50, 5BIL-29, 5BIL-20, 5BIL-42). S and R on the right of the bars indicate susceptible and resistant phenotype, respectively. Gray and red rectangles represent the genotypes of the PM-susceptible durum wheat Latino and the PM-resistant lines, respectively. <span class="html-italic">Pm36</span> was placed within a 7.3 cM interval flanked by IWB55478 and IWB22904 (between two vertical lines) based on the genotypes of the BILs at the marker loci and their PM phenotypes.</p>
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<p>Phenotypes of powdery mildew resistant durum backcross inbred line 5BIL-42 (on the <b>left</b>) and of the durum recurrent parental line Latino (on the <b>right</b>) 12 days post-inoculation with <span class="html-italic">Bgt</span> race O2.</p>
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<p>Fine mapping of <span class="html-italic">Pm36</span>. (<b>a</b>) Genetic linkage map of the 5BL chromosome region harboring <span class="html-italic">Pm36</span> generated in the 5BIL-42 x Latino F<sub>2:3</sub> progeny population. The grey and red regions represent the durum and the <span class="html-italic">dicoccoides</span> chromosomal segments, respectively. Marker loci are listed above and genetic distances in cM are shown at the bottom of the chromosome bar. The arrow point to the centromere; (<b>b</b>) Secondary recombinant homozygous lines (A15-F6 and PM222-F6) including introgressed <span class="html-italic">dicoccoides</span> chromosomal regions shorter than the 5BIL-42 one; the pink segments indicate the chromosomal interval harboring <span class="html-italic">Pm36</span>. Marker loci are listed above and physical distances in Mb are shown at the bottom of the chromosome bar. The lines connect the common markers between the genetic map and the physical map of the secondary recombinant lines.</p>
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<p>Fine mapping and candidate genes of <span class="html-italic">Pm36</span>. (<b>a</b>) High-density map positioned <span class="html-italic">Pm36</span> within a 1.08 Mb physical interval in the durum wheat Svevo reference genome [<a href="#B45-ijms-23-13659" class="html-bibr">45</a>]. Black arrow indicates direction of the centromere; (<b>b</b>) Micro-collinearity of the genomic region of <span class="html-italic">Pm36</span> between the wild emmer Zavitan [<a href="#B46-ijms-23-13659" class="html-bibr">46</a>], durum wheat Svevo [<a href="#B45-ijms-23-13659" class="html-bibr">45</a>] and bread wheat Chinese Spring genomes [<a href="#B48-ijms-23-13659" class="html-bibr">48</a>]. Arrows represent the annotated genes in each species and their direction indicates which strand they are located on; (<b>c</b>) Genes’ ID and their annotated functions in the emmer, durum and bread wheat genomes.</p>
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<p>Comparison of the genetic linkage map of <span class="html-italic">Pm36</span> with those reported for the powdery mildew resistance genes <span class="html-italic">MlWE29</span> [<a href="#B50-ijms-23-13659" class="html-bibr">50</a>], <span class="html-italic">M3D232</span> [<a href="#B51-ijms-23-13659" class="html-bibr">51</a>], <span class="html-italic">PmAS846</span> [<a href="#B52-ijms-23-13659" class="html-bibr">52</a>], <span class="html-italic">MlWE4</span> [<a href="#B53-ijms-23-13659" class="html-bibr">53</a>], <span class="html-italic">PmG25</span> [<a href="#B54-ijms-23-13659" class="html-bibr">54</a>], <span class="html-italic">Pm53</span> [<a href="#B55-ijms-23-13659" class="html-bibr">55</a>] located on the 5BL chromosome arm. Marker sequences of each map were physically located (in Mb) on the wild emmer Zavitan reference genome v2.0 [<a href="#B46-ijms-23-13659" class="html-bibr">46</a>] and on the Svevo reference genome v1.0 [<a href="#B45-ijms-23-13659" class="html-bibr">45</a>] to make possible the comparison of genetic maps constructed with different molecular markers. Marker loci are listed to the left of the emmer and durum physical maps and Mb distances are shown to the right. The partial comparison maps show the references above the maps, the marker loci on the right and the genetic distance in centiMorgan (cM) on the left. The lines connect the flanking markers of each map with their physical location (in Mb) on the emmer and durum genomes. The red blocks indicate the <span class="html-italic">Pm36</span> genomic interval.</p>
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22 pages, 6732 KiB  
Article
Preliminary Expression Analysis of the OSCA Gene Family in Maize and Their Involvement in Temperature Stress
by Yuanyang Li, Yubin Zhang, Bin Li, Liyuan Hou, Jianing Yu, Chengguo Jia, Zhe Wang, Siqi Chen, Mingzhe Zhang, Jianchun Qin, Ning Cao, Jinhu Cui and Wuliang Shi
Int. J. Mol. Sci. 2022, 23(21), 13658; https://doi.org/10.3390/ijms232113658 - 7 Nov 2022
Cited by 9 | Viewed by 2785
Abstract
Hyperosmolality-gated calcium-permeable channels (OSCA) are characterized as an osmosensor in plants; they are able to recognize and respond to exogenous and endogenous osmotic changes, and play a vital role in plant growth and adaptability to environmental stress. To explore the potential biological functions [...] Read more.
Hyperosmolality-gated calcium-permeable channels (OSCA) are characterized as an osmosensor in plants; they are able to recognize and respond to exogenous and endogenous osmotic changes, and play a vital role in plant growth and adaptability to environmental stress. To explore the potential biological functions of OSCAs in maize, we performed a bioinformatics and expression analysis of the ZmOSCA gene family. Using bioinformatics methods, we identified twelve OSCA genes from the genome database of maize. According to their sequence composition and phylogenetic relationship, the maize OSCA family was classified into four groups (Ⅰ, Ⅱ, Ⅲ, and Ⅳ). Multiple sequence alignment analysis revealed a conserved DUF221 domain in these members. We modeled the calcium binding sites of four OSCA families using the autodocking technique. The expression profiles of ZmOSCA genes were analyzed in different tissues and under diverse abiotic stresses such as drought, salt, high temperature, and chilling using quantitative real-time PCR (qRT-PCR). We found that the expression of twelve ZmOSCA genes is variant in different tissues of maize. Furthermore, abiotic stresses such as drought, salt, high temperature, and chilling differentially induced the expression of twelve ZmOSCA genes. We chose ZmOSCA2.2 and ZmOSCA2.3, which responded most strongly to temperature stress, for prediction of protein interactions. We modeled the calcium binding sites of four OSCA families using autodocking tools, obtaining a number of new results. These results are helpful in understanding the function of the plant OSCA gene family for study of the molecular mechanism of plant osmotic stress and response, as well as exploration of the interaction between osmotic stress, high-temperature stress, and low-temperature stress signal transduction mechanisms. As such, they can provide a theoretical basis for crop breeding. Full article
(This article belongs to the Special Issue Response to Environmental Stress in Plants)
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Figure 1

Figure 1
<p>Phylogenetic analysis of OSCA proteins. <span class="html-italic">Arabidopsis</span>, rice, and maize are denoted by circle, diamond, and triangle respectively, and the tree is divided into four groups.</p>
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<p>Exon–intron gene structures of <span class="html-italic">ZmOSCAs</span>. The horizontal black lines, green boxes, thick blue lines, and numbers in the top right corner of the green boxes indicate the positions of introns, the positions of exons, the positions of UTRs (untranslated regions), and the intron phase, respectively.</p>
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<p>Multiple sequence alignment and transmembrane region of the DUF221 conserved region in ZmOSCAs. The region between two vertical red lines represents the DUF221 conserved region. Identical (100%), conserved (75–99%), and blocks (50–74%) of similar amino acid residues are shaded in dark navy, pink, and cyan, respectively. The transmembrane regions are marked by black lines and called TM1-TM6.</p>
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<p>Predicted secondary structure of maize OSCA proteins. The blue, red, green, and yellow stripes represent the α helices, the β bridges, the β turns, and the random coils, respectively.</p>
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<p>Schematic representation of the organ-specific expression of the <span class="html-italic">ZmOSCA</span> genes. The colors white, 25% grey, 35% grey, 50% grey, 75% grey, and black represent the multiple ranges of <span class="html-italic">ZmOSCA</span> mRNA expression levels, which were &lt;0.01, 0.01–0.1, 0.1–1, 1.0–10, 10–50, and &gt;50, respectively, compared with 0.002 <span class="html-italic">GAPDH</span>.</p>
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<p>Expression profiles of <span class="html-italic">ZmOSCA</span> genes under 10% PEG-6000. The relative expression levels of <span class="html-italic">ZmOSCA</span>s were determined in the roots of three-true-leaf-stage seedlings treated with 10 % PEG-6000 for 0 h, 1 h, and 6 h and compared with the control.</p>
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<p>Expression profiles of <span class="html-italic">ZmOSCA</span> genes under NaCl stress. The relative expression levels of <span class="html-italic">ZmOSCA</span>s were determined in the roots of three-true-leaf-stage seedlings treated with 200 mM NaCl.</p>
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<p>The expression levels of <span class="html-italic">ZmOSCA</span> genes under 40 °C treatment conditions were monitored using qRT-PCR. Samples were collected after 0, 1, 6, 12, and 24 h of heat treatment.</p>
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<p>The expression levels of <span class="html-italic">ZmOSCA</span> genes under 4 °C treatment conditions were monitored with qRT-PCR. Samples were collected after 0, 1, 6, 12, and 24 h of cold treatment.</p>
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<p>The possible binding mode of Ca<sup>2+</sup> and OSCAs was simulated by Auto Dock 4.0 software. (<b>a</b>) Ca<sup>2+</sup> binds to residues GLN-609, ILE-610, and TRY-614 by a covalent bond in OSCA1.1 (<b>b</b>) Ca<sup>2+</sup> binds to residues SER-342 and ASN-343 by a covalent bond in OSCA2.1 (<b>c</b>) Ca<sup>2+</sup> binds to residues ASN-463 and VAL-461 by a covalent bond in OSCA3.1 (<b>d</b>) Ca<sup>2+</sup> bind to residues ILE-662 by a covalent bond in OSCA4.1.</p>
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<p>Predicted protein interaction results for ZmOSCA2.2 and ZmOSCA2.3. (<b>a</b>) Predictive analysis results of ZmOSCA2.2 and (<b>b</b>) Predictive analysis results of ZmOSCA2.3. The length of the line segment indicates the distance between the target protein and the predicted protein in terms of the action relationship. No second shell is set to interact with the protein.</p>
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0 pages, 2535 KiB  
Review
RETRACTED: Impact of Histone Modifications and Their Therapeutic Targeting in Hematological Malignancies
by Mariam Markouli, Dimitrios Strepkos and Christina Piperi
Int. J. Mol. Sci. 2022, 23(21), 13657; https://doi.org/10.3390/ijms232113657 - 7 Nov 2022
Cited by 3 | Viewed by 2552 | Retraction
Abstract
Hematologic malignancies are a large and heterogeneous group of neoplasms characterized by complex pathogenetic mechanisms. The abnormal regulation of epigenetic mechanisms and specifically, histone modifications, has been demonstrated to play a central role in hematological cancer pathogenesis and progression. A variety of epigenetic [...] Read more.
Hematologic malignancies are a large and heterogeneous group of neoplasms characterized by complex pathogenetic mechanisms. The abnormal regulation of epigenetic mechanisms and specifically, histone modifications, has been demonstrated to play a central role in hematological cancer pathogenesis and progression. A variety of epigenetic enzymes that affect the state of histones have been detected as deregulated, being either over- or underexpressed, which induces changes in chromatin compaction and, subsequently, affects gene expression. Recent advances in the field of epigenetics have revealed novel therapeutic targets, with many epigenetic drugs being investigated in clinical trials. The present review focuses on the biological impact of histone modifications in the pathogenesis of hematologic malignancies, describing a wide range of therapeutic agents that have been discovered to target these alterations and are currently under investigation in clinical trials. Full article
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Graphical abstract

Graphical abstract
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<p>Chromatin landscape indicating histone methylation changes related to hematological malignancies. EZH2 methyltransferase regulates the differentiation, proliferation, and apoptosis of the adult hematopoietic stem cells by repressing <span class="html-italic">CDKN2A</span>, <span class="html-italic">BLIMP</span>, and <span class="html-italic">IRF4</span>, as well as pro-apoptotic genes, <span class="html-italic">NOX</span> and <span class="html-italic">p21</span>. EZH2 overexpression or gain-of-function mutations have been detected in high-grade follicular lymphoma, DLBCL, and NKT lymphomas. Loss-of-function <span class="html-italic">EZH2</span> mutations have been observed in MDSs, atypical CML, myelofibrosis, and T-ALL. Mutations in other PRC2 members, such as EED, and SUZ12, have been observed in some MDS and T-ALL cases, whereas ASXL1 mutations promote myeloid transformation through loss of PRC2-mediated gene repression. Frequent <span class="html-italic">MLL1</span> translocations have been detected in AML and ALL. Most common fusion partners accounting for approximately 80% of MLL rearrangements are AFF1/AF4, MLLT3/AF9, MLLT1/ENL, and MLLT10/AF10, which interact with DOT1L that further sustains the expression of key pro-leukemic genes <span class="html-italic">HOXA</span> and <span class="html-italic">MEIS1</span>. <span class="html-italic">PRMT4</span> knockdown inhibits cell-cycle progression and promotes apoptosis by downregulating <span class="html-italic">E2F</span> and <span class="html-italic">MYC</span> target genes in leukemic cell lines. PRMT5 is overexpressed in DLBCL and MCL via regulation of <span class="html-italic">p5</span>, <span class="html-italic">p21</span>, <span class="html-italic">GADD45</span>, and <span class="html-italic">PUMA</span> genes. <span class="html-italic">MECOM</span> and <span class="html-italic">PRDM16</span> are rearranged in AML. PHD finger proteins recognize lysine methylation, upregulating <span class="html-italic">HOXA9</span> and <span class="html-italic">MEIS1</span> gene activity in AML. Lysine demethylase <span class="html-italic">UTX</span> is also frequently mutated in MM and ALL, and LSD1 is overexpressed in ALL, AML, CML, MPNs, and MDSs, repressing <span class="html-italic">p53</span>, <span class="html-italic">STAT3</span>, and <span class="html-italic">DNMT1</span> activity.</p>
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<p>Histone acetylation events related to hematological malignancies. CBP and p300 are often dysregulated in lymphoid neoplasms, leading to abnormal acetylation of histones, as well as nonhistone targets, such as <span class="html-italic">BCL-6</span> and <span class="html-italic">p53</span>. KAT7, KAT2A, KAT6B, and CSRP2BP are overexpressed in B-ALL and may interact with <span class="html-italic">MYC</span>, implicating them in tumor development. BRD4 further associates with p300/CBP-mediated acetylation-enhanced regions, controlling genes associated with cell renewal and pluripotency, such as <span class="html-italic">Nanog</span> and <span class="html-italic">OCT4</span>. MOZ-TIF2 and MLL-CBP are commonly rearranged in myeloid malignancies, resulting in the respective FPs that have been implicated in leukemic transformation. Increased HDAC expression is also common in ALL, regulating <span class="html-italic">RARb</span>, <span class="html-italic">CYP26 Pax5</span>, <span class="html-italic">IKZF3</span>, <span class="html-italic">CXCR4</span>, <span class="html-italic">IL-16</span>, <span class="html-italic">IL-4R</span>, and <span class="html-italic">Bcl-2</span> gene expression. HDACs, and in particular HDAC9, also interact with the PML-RARα and PLZF-RARα FPs, as well as with BCL-6 to promote the development of hematologic malignancies.</p>
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<p>Histone phosphorylation and SUMOylation alterations related to hematological malignancies. JAK2 kinase is commonly activated in MPNs, resulting in histone phosphorylation, which induces the disassembly of HP1α from chromatin and the activation of <span class="html-italic">LMO2</span> oncogene. Phosphorylated genes also attract STAT family members, enabling a functional interaction between JAK kinases and STAT proteins. PIM1 kinase, when simultaneously overexpressed with MYC, promotes lymphomagenesis. It can form complexes with MYC and MAX, activating <span class="html-italic">IEGs</span>, <span class="html-italic">FOSL1</span>, and <span class="html-italic">ID2</span>. Finally, SUMOylation reduces gene expression of the E3 ubiquitin ligase TRAF6 in DLBCL and further represses gene transcription.</p>
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<p>Structure of small-molecule inhibitors targeting epigenetic alterations. Several drugs targeting epigenetic enzymes have been developed and are currently being studied in preclinical and clinical studies. These include small molecules inhibiting CARM-1, PRMT5, DOT1L, EZH2 methyltransferases LSD1, HATs, HDACs, and BET.</p>
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<p>Diagram indicating the status of drugs targeting epigenetic alterations. Currently, only the EZH2 inhibitor tazemetostat and the DNMT inhibitors azacytidine and decitabine have received FDA approval. However, an increasing number of BET, DOT1L, LSD1, HAT, and HDAC inhibitors are already in phase II/III clinical trials with promising results, and several more are under evaluation in phase I trials.</p>
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21 pages, 2117 KiB  
Review
Emerging Effects of IL-33 on COVID-19
by Yuan Gao, Luwei Cai, Lili Li, Yidan Zhang, Jing Li, Chengliang Luo, Ying Wang and Luyang Tao
Int. J. Mol. Sci. 2022, 23(21), 13656; https://doi.org/10.3390/ijms232113656 - 7 Nov 2022
Cited by 14 | Viewed by 3176
Abstract
Since the start of COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), more than 6 million people have lost their lives worldwide directly or indirectly. Despite intensified efforts to clarify the immunopathology of COVID-19, the key factors and processes that [...] Read more.
Since the start of COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), more than 6 million people have lost their lives worldwide directly or indirectly. Despite intensified efforts to clarify the immunopathology of COVID-19, the key factors and processes that trigger an inflammatory storm and lead to severe clinical outcomes in patients remain unclear. As an inflammatory storm factor, IL-33 is an alarmin cytokine, which plays an important role in cell damage or infection. Recent studies have shown that serum IL-33 is upregulated in COVID-19 patients and is strongly associated with poor outcomes. Increased IL-33 levels in severe infections may result from an inflammatory storm caused by strong interactions between activated immune cells. However, the effects of IL-33 in COVID-19 and the underlying mechanisms remain to be fully elucidated. In this review, we systematically discuss the biological properties of IL-33 under pathophysiological conditions and its regulation of immune cells, including neutrophils, innate lymphocytes (ILCs), dendritic cells, macrophages, CD4+ T cells, Th17/Treg cells, and CD8+ T cells, in COVID-19 phagocytosis. The aim of this review is to explore the potential value of the IL-33/immune cell pathway as a new target for early diagnosis, monitoring of severe cases, and clinical treatment of COVID-19. Full article
(This article belongs to the Section Molecular Immunology)
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<p>Molecular biological characteristics of IL-33 (<b>A</b>) The gene spans of human IL-33 (approximately 48 kb) contain eight exons, which are transcribed and translated into proteins containing 270 amino acids. (<b>B</b>) The full length of IL-33 is sheared to obtain different levels of active fragments. Cleaved by cathepsin, elastase, and proteinase released from neutrophils or chymase, Genzyme B, and tryptase released from mast cells, the highly active fragments of IL-33 (IL-33<sub>95-270</sub>, IL-33<sub>99-270</sub>, IL-33<sub>107-270</sub>, IL-33<sub>109-270</sub>, IL-33<sub>111-270</sub>) can bind to the ST2L/IL-1RAcP dimer and activate downstream signaling pathways. In contrast, when the full length of IL-33 is cleaved by casepase3/7 released by apoptotic cells, it forms a fragment (IL-33<sub>179-270</sub>) without biological activity. (<b>C</b>) The 3D structure of the IL-33/ST2 complex (Protein Data Bank ID:4KC3). IL-33 mediates cytokine activity through the structural domain with three Ig-like structural domains in the extracellular domain of ST2 on target cells. At Site 1, the acidic residues Glu144, Glu148, Asp149, and Asp244 of IL-33 interact with the ST2 basic residues Arg38, Lys22, Arg198, and Arg35, respectively, via a critical salt bridge. At Site 2, the acidic residue Glu165 of IL-33 interacts with Arg313 of ST2 via a salt bridge, and Tyr163 and Leu182 of IL-33 form significant hydrophobic structures with Leu246, Leu306, and Leu311 of ST2.</p>
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<p>The effects and putative mechanisms of the involvement of IL-33 in neutrophils and T helper cells in COVID-19. In response to SAS-CoV-2, IL-33 is released as an alarmin from epithelial cells due to disruption of the epithelial barrier and cell damage. This promotes rapid neutrophil infiltration, migration, and activation via macrophage-derived CXCL1 and CXCL2 while inducing massive accumulation of ROS via the IL-33/ST2 signaling pathway, which in turn induces the excessive release of NETs. Additionally, IL-33 dose dependently upregulates MHC-II class and co-stimulatory molecules to induce maturation and activation of immature DCs and then stimulates activation of CD4<sup>+</sup> T cells and induces their differentiation to Th17 cells instead of Treg cells through secretion of IL-1β and IL-6. Finally, a large number of NETs and inflammatory cells enter the bloodstream, triggering serious complications, such as vasoembolic conditions and inflammatory reactions.</p>
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<p>Potential mechanisms by which IL-33 regulates ILC2 and macrophages in COVID-19. SAS-CoV-2 infects cells via ACE2 on the surface of type II alveolar epithelial cells with the assistance of TMPRSS2. IL-33 acts as an alarmin in response to viral infection and is secreted in large quantities by apoptotic alveolar epithelial cells. The released IL-33 acts on the specific receptor of ST2L on the surface of the ILC2 membrane and recruits its accessory receptor IL-1RAcP to form the functional IL-33 receptor complex. Following binding of IL-33 to IL-1RAcP, the receptor complex is activated by exposure of the TIR domain of IL-1RAcP and recruitment of myeloid differentiation primary response gene 88 (MyD88) into the heterodimeric IL-33R1 complex. Recruitment of MyD88 results in the recruitment of IL-1 receptor-associated kinase 1 (IRAK1) and IRAK4 through their death domains. This complex then activates downstream signaling pathways, including mitogen-activated protein kinases MAPK (such as ERK, JNK, p38), GATA3, and NF-κB, and enhances cellular respiration and ATP production, which induces an elevated level of the histone modification H3K4me3. Activation of NF-κB, GATA3, and H3K4me3 in the nuclear membrane further promotes the production of inflammatory cytokines, such as IL-5 and IL-13, and enhances viral recruitment by TMPRSS2. On the other hand, the release of IL-33 directly reduces phagocytosis by macrophages and the antiviral effects of NK cells. In contrast, IL-33 and IL-13 bind to ST2L and IL-4R, respectively, on the surface of macrophage membranes, thereby promoting the activation of macrophage differentiation toward AAMs and damage to alveolar tissue.</p>
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<p>Interaction mechanism between IL-33 and IFN-I released by pDCs during COVID-19 infection. After the lung epithelium is infected with SARS-CoV-2, the replicating virus can cause epithelial cell apoptosis and directly damage the epithelium. Dendritic cells present antigens to helper T cells. Immature DCs differentiate into conventional DCs (cDCs) and plasmacytoid DCs (pDCs). IFN-I specificity derived from pDCs is dependent on the Toll-like receptor-7 (TLR7)/TLR9 pathway. Upon COVID-19 infection, TLR7 or TLR9 activates MyD88 and IL-1 receptor-associated kinase 4 (IRAK-4), which then interact with tumor necrosis factor receptor-associated factor-6 (TRAF6), TRAF3, IRAK1, IKKα, and interferon regulatory factor 7 (IRF7) interaction. Ultimately, IRAK-1 and IKKα phosphorylate IRF7, leading to IRF7 activation and induction of IFN-I gene transcription and massive IFN-I production. Additionally, IL-33, an important inflammatory storm cytokine, is abundantly released from apoptotic epithelial cells and inhibits pDC-dependent IFN-I by rapidly depleting the intracellular adaptor molecules IRAK1 and viperin, resulting in a hyporesponsive state of TLR7. Meanwhile, IL-33 induces the expression of a large number of cytokines by interacting with immune cells, such as macrophages, ILC2 cells, Th2 cells, Th17 cells, and Treg cells, which ultimately leads to abnormal inflammatory damage and decreased antiviral capacity in COVID-19 patients.</p>
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15 pages, 2858 KiB  
Article
Influence of Acidic pH on Wound Healing In Vivo: A Novel Perspective for Wound Treatment
by Pivian Sim, Xanthe L. Strudwick, YunMei Song, Allison J. Cowin and Sanjay Garg
Int. J. Mol. Sci. 2022, 23(21), 13655; https://doi.org/10.3390/ijms232113655 - 7 Nov 2022
Cited by 53 | Viewed by 5840
Abstract
There has been little understanding of acidification functionality in wound healing, highlighting the need to study the efficacy of wound acidification on wound closure and cellular activity in non-infected wounds. This study is focused on establishing the healing potential of wound acidification in [...] Read more.
There has been little understanding of acidification functionality in wound healing, highlighting the need to study the efficacy of wound acidification on wound closure and cellular activity in non-infected wounds. This study is focused on establishing the healing potential of wound acidification in non-infected wounds. Acidic buffers, constituting either phosphoric or citric acid, were employed to modify the physiological pH of non-infected full-thickness excisional murine wounds. Acidification of the wound by acidic buffers was found to be an effective strategy to improve wound healing. A significant improvement in wound healing parameters was observed as early as 2 days post-treatment with acidic buffers compared to controls, with faster rate of epithelialization, wound closure and higher levels of collagen at day 7. pH is shown to play a role in mediating the rate of wound healing, with acidic buffers formulated at pH 4 observed to stimulate faster recovery of wounded tissues than pH 6 buffers. Our study shows the importance of maintaining an acidic wound microenvironment at pH 4, which could be a potential therapeutic strategy for wound management. Full article
(This article belongs to the Special Issue Recent Approaches for Wound Treatment)
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<p>(<b>a</b>) Macroscopic evaluation in relation to the time course of gross wound healing after one week of topical application of phosphoric acid (PA) and citric acid (CA) buffer solutions. (<b>b</b>) Differences in absolute wound area between phosphoric acid pH 4, once-daily treatment (PA4-1), phosphoric acid pH 4 and 6, once-every-second-day treatment (PA4-2 and PA6-2), and saline control group (SAL7-2). (<b>c</b>) Time course of wound regeneration for animal model after dermal treatment with citric acid pH 4, once-daily treatment (CA4-1), citric acid pH 4 and 6, once-every-second-day treatment (CA4-2 and CA6-2) compared with saline control group (SAL7-2). (<b>d</b>) Macroscopic wound healing on day 7 when animals were topically applied with phosphoric acid with pH values of 4 and 6, and with different dosing regimens. (<b>e</b>) Topical administration of citric acid buffer solutions in comparison to saline as control group at day 7 post-treatment. Each bar represents mean ± standard deviation. * <span class="html-italic">p</span> &lt; 0.05 and *** <span class="html-italic">p</span> &lt; 0.001 indicates the results obtained were statistically significant from control group (SAL7-2).</p>
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<p>(<b>a</b>) Macroscopic evaluation in relation to the time course of gross wound healing after one week of topical application of phosphoric acid (PA) and citric acid (CA) buffer solutions. (<b>b</b>) Differences in absolute wound area between phosphoric acid pH 4, once-daily treatment (PA4-1), phosphoric acid pH 4 and 6, once-every-second-day treatment (PA4-2 and PA6-2), and saline control group (SAL7-2). (<b>c</b>) Time course of wound regeneration for animal model after dermal treatment with citric acid pH 4, once-daily treatment (CA4-1), citric acid pH 4 and 6, once-every-second-day treatment (CA4-2 and CA6-2) compared with saline control group (SAL7-2). (<b>d</b>) Macroscopic wound healing on day 7 when animals were topically applied with phosphoric acid with pH values of 4 and 6, and with different dosing regimens. (<b>e</b>) Topical administration of citric acid buffer solutions in comparison to saline as control group at day 7 post-treatment. Each bar represents mean ± standard deviation. * <span class="html-italic">p</span> &lt; 0.05 and *** <span class="html-italic">p</span> &lt; 0.001 indicates the results obtained were statistically significant from control group (SAL7-2).</p>
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<p>Microscopic analysis confirmed by hematoxylin and eosin (H&amp;E) staining of percentage wound recovery after one week of topical administration of phosphoric acid (PA) and citric acid (CA) buffered solutions with different pH values and treatment regimes. (<b>a</b>) Full-thickness punch biopsy sample obtained from animal model in all acidic buffered treatment groups and saline control group at Day 7 post-injury. Original magnification 4×. Black scale bar represents 500 µm. Black arrows indicate the width of new tissue formation, blue dotted line indicate the re-epithelialized area, red dotted line indicate the panniculus gap measurement, and black dotted line indicate the base of epithelium. (<b>b</b>) Percentage re-epithelialization of animal model following topical treatment with phosphoric acid buffer solutions of pH 4 and pH 6. (<b>c</b>) Topical administration of citric acid buffer solutions or saline as control group. (<b>d</b>) Measurement of wound length at Day 7 post-injury following topical treatment with phosphoric acid buffer solutions of pH 4 and pH 6. (<b>e</b>) Wound length obtained from animal model after topically treated with citric acid buffer solutions with pH adjusted to 4 and 6 for 7 days. Each bar represents mean ± standard deviation. * <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 indicates the results obtained were statistically significant from control group (SAL7-2).</p>
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<p>Microscopic analysis confirmed by hematoxylin and eosin (H&amp;E) staining of percentage wound recovery after one week of topical administration of phosphoric acid (PA) and citric acid (CA) buffered solutions with different pH values and treatment regimes. (<b>a</b>) Full-thickness punch biopsy sample obtained from animal model in all acidic buffered treatment groups and saline control group at Day 7 post-injury. Original magnification 4×. Black scale bar represents 500 µm. Black arrows indicate the width of new tissue formation, blue dotted line indicate the re-epithelialized area, red dotted line indicate the panniculus gap measurement, and black dotted line indicate the base of epithelium. (<b>b</b>) Percentage re-epithelialization of animal model following topical treatment with phosphoric acid buffer solutions of pH 4 and pH 6. (<b>c</b>) Topical administration of citric acid buffer solutions or saline as control group. (<b>d</b>) Measurement of wound length at Day 7 post-injury following topical treatment with phosphoric acid buffer solutions of pH 4 and pH 6. (<b>e</b>) Wound length obtained from animal model after topically treated with citric acid buffer solutions with pH adjusted to 4 and 6 for 7 days. Each bar represents mean ± standard deviation. * <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 indicates the results obtained were statistically significant from control group (SAL7-2).</p>
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<p>Comparison of epithelial thickness as an indication of the quality of regenerated wound between (<b>a</b>) phosphoric acid (PA) buffered solution treatment groups on day 7 and (<b>b</b>) citric acid (CA) buffered solution treatment groups on day 7 post-wounding with saline control group (SAL7-2). Each bar represents mean ± standard deviation. * <span class="html-italic">p</span> &lt; 0.05 indicates the results obtained were statistically significant from control group (SAL7-2). PA4-1 n = 14/14, PA4-2 n = 15/16, PA6-2 n = 13/16, CA4-1 n = 16/16, CA4-2 n = 15/16, CA6-2 n = 12/14 and SAL7-2 n = 8/12.</p>
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<p>Panniculus carnosus muscle gap measurement during wound healing process when treated with (<b>a</b>) phosphoric acid (PA) buffered solutions of pH 4 and pH 6, (<b>b</b>) citric acid (CA) buffered solutions of pH 4 and pH 6 in comparison to saline control group (SAL7-2). Each bar represents mean ± standard deviation. * <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 indicates the results obtained were statistically significant from control group (SAL7-2).</p>
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<p>Evaluation of collagen deposition between phosphoric acid (PA) and citric acid (CA) treatment groups on day 7 post-wounding utilizing Masson Trichrome (MT) staining technique. (<b>a</b>) Histology analysis of skin sample obtained from all treatment groups. Original magnification 4×. Black scale bar represents 500 µm. (<b>b</b>) Collagen content evaluation between PA4-1, PA4-2, PA6-2 in comparison to SAL7-2 control group. (<b>c</b>) Differences in collagen index between CA4-1, CA4-2, CA6-2 and SAL7-2 control group. Each bar represents mean ± standard deviation. * <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 indicates the results obtained were statistically significant from control group (SAL7-2).</p>
Full article ">Figure 5 Cont.
<p>Evaluation of collagen deposition between phosphoric acid (PA) and citric acid (CA) treatment groups on day 7 post-wounding utilizing Masson Trichrome (MT) staining technique. (<b>a</b>) Histology analysis of skin sample obtained from all treatment groups. Original magnification 4×. Black scale bar represents 500 µm. (<b>b</b>) Collagen content evaluation between PA4-1, PA4-2, PA6-2 in comparison to SAL7-2 control group. (<b>c</b>) Differences in collagen index between CA4-1, CA4-2, CA6-2 and SAL7-2 control group. Each bar represents mean ± standard deviation. * <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 indicates the results obtained were statistically significant from control group (SAL7-2).</p>
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10 pages, 1480 KiB  
Review
Activity-Dependent Neuroprotective Protein (ADNP): An Overview of Its Role in the Eye
by Grazia Maugeri, Agata Grazia D’Amico, Benedetta Magrì, Giuseppe Musumeci and Velia D’Agata
Int. J. Mol. Sci. 2022, 23(21), 13654; https://doi.org/10.3390/ijms232113654 - 7 Nov 2022
Cited by 4 | Viewed by 2397
Abstract
Vision is one of the dominant senses in humans and eye health is essential to ensure a good quality of life. Therefore, there is an urgent necessity to identify effective therapeutic candidates to reverse the progression of different ocular pathologies. Activity-dependent neuroprotective protein [...] Read more.
Vision is one of the dominant senses in humans and eye health is essential to ensure a good quality of life. Therefore, there is an urgent necessity to identify effective therapeutic candidates to reverse the progression of different ocular pathologies. Activity-dependent neuroprotective protein (ADNP) is a protein involved in the physio-pathological processes of the eye. Noteworthy, is the small peptide derived from ADNP, known as NAP, which shows protective, antioxidant, and anti-apoptotic properties. Herein, we review the current state of knowledge concerning the role of ADNP in ocular pathologies, while providing an overview of eye anatomy. Full article
(This article belongs to the Special Issue The Roles of VIP and PACAP: From Molecular and Genetic Studies)
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<p>The basic anatomy of the human eye.</p>
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<p>Boxplot of transcripts per million (TPM) showing the bulk tissue gene expression for ADNP. GTEx Portal on 29 September 2022.</p>
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<p>Protective effects played by NAP in the eye. The ↑ and ↓ refer to increase and decrease, respectively.</p>
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54 pages, 991 KiB  
Review
Mitochondrial Effects of Common Cardiovascular Medications: The Good, the Bad and the Mixed
by Alina M. Bețiu, Lavinia Noveanu, Iasmina M. Hâncu, Ana Lascu, Lucian Petrescu, Christoph Maack, Eskil Elmér and Danina M. Muntean
Int. J. Mol. Sci. 2022, 23(21), 13653; https://doi.org/10.3390/ijms232113653 - 7 Nov 2022
Cited by 15 | Viewed by 6279
Abstract
Mitochondria are central organelles in the homeostasis of the cardiovascular system via the integration of several physiological processes, such as ATP generation via oxidative phosphorylation, synthesis/exchange of metabolites, calcium sequestration, reactive oxygen species (ROS) production/buffering and control of cellular survival/death. Mitochondrial impairment has [...] Read more.
Mitochondria are central organelles in the homeostasis of the cardiovascular system via the integration of several physiological processes, such as ATP generation via oxidative phosphorylation, synthesis/exchange of metabolites, calcium sequestration, reactive oxygen species (ROS) production/buffering and control of cellular survival/death. Mitochondrial impairment has been widely recognized as a central pathomechanism of almost all cardiovascular diseases, rendering these organelles important therapeutic targets. Mitochondrial dysfunction has been reported to occur in the setting of drug-induced toxicity in several tissues and organs, including the heart. Members of the drug classes currently used in the therapeutics of cardiovascular pathologies have been reported to both support and undermine mitochondrial function. For the latter case, mitochondrial toxicity is the consequence of drug interference (direct or off-target effects) with mitochondrial respiration/energy conversion, DNA replication, ROS production and detoxification, cell death signaling and mitochondrial dynamics. The present narrative review aims to summarize the beneficial and deleterious mitochondrial effects of common cardiovascular medications as described in various experimental models and identify those for which evidence for both types of effects is available in the literature. Full article
(This article belongs to the Special Issue Targeting Mitochondria in Metabolic Diseases 2.0)
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<p>Overview of pathomechanisms of drug-induced mitochondrial toxicity. NAD: Nicotinamide adenine dinucleotide; FAD: flavin adenine dinucleotide; Cyt C: Cytochrome C; ATP: Adenosine triphosphate; mPTP: Mitochondrial permeability transition pore; ROS: Reactive oxygen species. Figure created with BioRender.com.</p>
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23 pages, 4042 KiB  
Article
Dynamical Mechanism Analysis of Three Neuroregulatory Strategies on the Modulation of Seizures
by Honghui Zhang, Zhuan Shen, Yuzhi Zhao, Lin Du and Zichen Deng
Int. J. Mol. Sci. 2022, 23(21), 13652; https://doi.org/10.3390/ijms232113652 - 7 Nov 2022
Cited by 3 | Viewed by 1903
Abstract
This paper attempts to explore and compare the regulatory mechanisms of optogenetic stimulation (OS), deep brain stimulation (DBS) and electromagnetic induction on epilepsy. Based on the Wilson–Cowan model, we first demonstrate that the external input received by excitatory and inhibitory neural populations can [...] Read more.
This paper attempts to explore and compare the regulatory mechanisms of optogenetic stimulation (OS), deep brain stimulation (DBS) and electromagnetic induction on epilepsy. Based on the Wilson–Cowan model, we first demonstrate that the external input received by excitatory and inhibitory neural populations can induce rich dynamic bifurcation behaviors such as Hopf bifurcation, and make the system exhibit epileptic and normal states. Then, both OS and DBS are shown to be effective in controlling the epileptic state to a normal low-level state, and the stimulus parameters have a broad effective range. However, electromagnetic induction cannot directly control epilepsy to this desired state, even if it can significantly reduce the oscillation frequency of neural populations. One main difference worth noting is that the high spatiotemporal specificity of OS allows it to target inhibitory neuronal populations, whereas DBS and electromagnetic induction can only stimulate excitatory as well as inhibitory neuronal populations together. Next, the propagation behavior of epilepsy is explored under a typical three-node feedback loop structure. An increase in coupling strength accelerates and exacerbates epileptic activity in other brain regions. Finally, OS and DBS applied to the epileptic focus play similar positive roles in controlling the behavior of the area of seizure propagation, while electromagnetic induction still only achieves unsatisfactory effects. It is hoped that these dynamical results can provide insights into the treatment of epilepsy as well as other neurological disorders. Full article
(This article belongs to the Special Issue Neural Dynamics and Regulation in Epilepsy)
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<p>Dynamical bifurcation diagrams induced by <math display="inline"><semantics> <msub> <mi>P</mi> <mi>E</mi> </msub> </semantics></math> (<b>a</b>) and <math display="inline"><semantics> <msub> <mi>P</mi> <mi>I</mi> </msub> </semantics></math> (<b>b</b>). Two-dimensional bifurcation diagrams on the plane (<math display="inline"><semantics> <msub> <mi>P</mi> <mi>E</mi> </msub> </semantics></math>, <math display="inline"><semantics> <msub> <mi>P</mi> <mi>I</mi> </msub> </semantics></math>) (<b>c</b>). Time series of normal background state and oscillating state by varying <math display="inline"><semantics> <msub> <mi>P</mi> <mi>E</mi> </msub> </semantics></math> and <math display="inline"><semantics> <msub> <mi>P</mi> <mi>I</mi> </msub> </semantics></math> (<b>d</b>). The phase diagram corresponding to the two states: oscillating state (<b>e</b>) and normal background state (<b>f</b>). The meanings of the symbols are as follows: the low-level stable equilibrium state exists (I), the low-level stable equilibrium state and the medium-level stable equilibrium state coexist (II), the stable limit cycle and the low-level stable equilibrium state coexist (III), the stable limit cycle (oscillating state) exists (IV), the high-level stable equilibrium state exists (V).</p>
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<p>(<b>a</b>–<b>d</b>) Typical time series under the influence of OS. (<b>e</b>) The evolution of the observed quantitative indicators with I<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>r</mi> <mi>r</mi> </mrow> </msub> </semantics></math>. Figures (<b>a</b>,<b>b</b>) represent the OS being invalid and valid, respectively. Figures (<b>c</b>,<b>d</b>) show that the effect of OS on E is desired, but the effect on I is not. The partial, enlarged views in Figures (<b>a</b>–<b>d</b>) are also given for clarity. Peak<math display="inline"><semantics> <msub> <mrow/> <mi>E</mi> </msub> </semantics></math> and trough<math display="inline"><semantics> <msub> <mrow/> <mi>E</mi> </msub> </semantics></math> are the maxima and minima of the stabilized time series of population E, respectively. The definitions of Peak<math display="inline"><semantics> <msub> <mrow/> <mi>I</mi> </msub> </semantics></math> and trough<math display="inline"><semantics> <msub> <mrow/> <mi>I</mi> </msub> </semantics></math> for population I are similar.</p>
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<p>Evolutions of the observed indicators on the two-stimulus parameter plane. Areas enclosed by the white dashed line are the effective parameter area (peak, trough, peak-trough of E and I are all smaller than 0.05). (<b>a</b>,<b>d</b>): f = 40 Hz, (<b>b</b>,<b>e</b>): I<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>r</mi> <mi>r</mi> </mrow> </msub> </semantics></math> = 0.015 mW/mm<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math>, (<b>c</b>,<b>f</b>): ws = 2 ms.</p>
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<p>Control effects of DBS under different parameter settings. The control effect shown in (<b>c</b>) is better than that of (<b>a</b>,<b>b</b>).</p>
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<p>Evolutions of the observed indicators on the two-stimulus parameter plane. The dark blue area represents the stimulus effective area. (<b>a</b>,<b>d</b>): I<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>D</mi> <mi>B</mi> <mi>S</mi> </mrow> </msub> </semantics></math> = 2 mA, (<b>b</b>,<b>e</b>): f<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>D</mi> <mi>B</mi> <mi>S</mi> </mrow> </msub> </semantics></math> = 120 Hz, (<b>c</b>,<b>f</b>): <math display="inline"><semantics> <mi>δ</mi> </semantics></math> = 2.5 ms.</p>
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<p>Time series diagram under the influence of electromagnetic induction. (<b>a</b>) <math display="inline"><semantics> <msub> <mi>I</mi> <mrow> <mi>m</mi> <mi>f</mi> </mrow> </msub> </semantics></math> is ineffective, i.e., the amplitude of the oscillatory state hardly changes. As <math display="inline"><semantics> <msub> <mi>K</mi> <mn>0</mn> </msub> </semantics></math> increases, amplitude of the oscillatory state decreases (<b>b</b>) and eventually becomes the high-level (<b>c</b>) and the medium-level equilibrium point states (<b>d</b>). <math display="inline"><semantics> <msub> <mi>I</mi> <mrow> <mi>m</mi> <mi>f</mi> </mrow> </msub> </semantics></math> and arrows indicate that the electromagnetic induction model and Wilson–Cowan model are coupled at t = 200 ms.</p>
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<p>Dynamical bifurcation diagrams induced by <math display="inline"><semantics> <msub> <mi>P</mi> <mi>E</mi> </msub> </semantics></math> under the influence of electromagnetic induction (<b>a</b>–<b>f</b>). Two-dimensional bifurcation diagrams on the plane (<math display="inline"><semantics> <msub> <mi>P</mi> <mi>E</mi> </msub> </semantics></math>, <math display="inline"><semantics> <msub> <mi>P</mi> <mi>I</mi> </msub> </semantics></math>) under the influence of electromagnetic induction (<b>g</b>–<b>i</b>). All symbols have the same meaning as in <a href="#ijms-23-13652-f001" class="html-fig">Figure 1</a>. An increase in <math display="inline"><semantics> <msub> <mi>K</mi> <mn>0</mn> </msub> </semantics></math> reduces the region of the oscillatory state (IV).</p>
Full article ">Figure 7 Cont.
<p>Dynamical bifurcation diagrams induced by <math display="inline"><semantics> <msub> <mi>P</mi> <mi>E</mi> </msub> </semantics></math> under the influence of electromagnetic induction (<b>a</b>–<b>f</b>). Two-dimensional bifurcation diagrams on the plane (<math display="inline"><semantics> <msub> <mi>P</mi> <mi>E</mi> </msub> </semantics></math>, <math display="inline"><semantics> <msub> <mi>P</mi> <mi>I</mi> </msub> </semantics></math>) under the influence of electromagnetic induction (<b>g</b>–<b>i</b>). All symbols have the same meaning as in <a href="#ijms-23-13652-f001" class="html-fig">Figure 1</a>. An increase in <math display="inline"><semantics> <msub> <mi>K</mi> <mn>0</mn> </msub> </semantics></math> reduces the region of the oscillatory state (IV).</p>
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<p>Time series of the three columns under different coupling connection strengths <span class="html-italic">K</span>. An increase in <span class="html-italic">K</span> will cause columns 2 and 3 to oscillate gradually (<b>b</b>–<b>d</b>), and column2 will oscillate before column3 (<b>b</b>).</p>
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<p>(<b>a</b>) Relationship of the extreme value difference with <span class="html-italic">K</span>. (<b>b</b>) Relationship of the system’s state with <span class="html-italic">K</span>. When <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>≥</mo> <mn>0.2</mn> </mrow> </semantics></math>, column2 starts to oscillate, that is, from non-oscillating state 0 to oscillating state 1. Column3 starts to oscillate from <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.3</mn> </mrow> </semantics></math>.</p>
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<p>Under the different coupling strengths <span class="html-italic">K</span>, time series of the three columns when OS targets <math display="inline"><semantics> <msub> <mi>I</mi> <mn>1</mn> </msub> </semantics></math> with different stimulus parameters. When <span class="html-italic">K</span> is small (<math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.31</mn> </mrow> </semantics></math>, <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.52</mn> </mrow> </semantics></math>), the proper OS can always control all the three columns (<b>b</b>,<b>e</b>). However, if the value of <span class="html-italic">K</span> is larger (<math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.8</mn> </mrow> </semantics></math>), column3 cannot always be controlled regardless of the settings of the stimulus parameters (<b>f</b>).</p>
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<p>Dynamical responses of the three columns when OS targets <math display="inline"><semantics> <msub> <mi>I</mi> <mn>1</mn> </msub> </semantics></math>. The control effect of column2 and column3 is closely related to K. Three compartments can be controlled well when <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.31</mn> </mrow> </semantics></math> (<b>a</b>). The controllable areas of column2 and column3 are reduced (<math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.52</mn> </mrow> </semantics></math>, (<b>b</b>)), even to zero (<math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.8</mn> </mrow> </semantics></math>, (<b>c</b>)).</p>
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<p>Control rate of the three columns, CR(%), when DBS targets column1. The higher the CR(%) value, the better the control effect. Regardless of the value of <span class="html-italic">K</span>, column1 is well controlled. When <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.52</mn> </mrow> </semantics></math>, the CR of column2 is slightly reduced, and the CR of column3 is reduced by half. When <math display="inline"><semantics> <mrow> <mi>K</mi> <mo>=</mo> <mn>0.8</mn> </mrow> </semantics></math>, column2 also has a significant reduction in CR, and column3 has a zero CR.</p>
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<p>Dynamical responses of the three columns ((<b>a</b>,<b>d</b>): column1, (<b>b</b>,<b>e</b>): column2, (<b>c</b>,<b>f</b>): column3) under the influence of different coupling strengths <span class="html-italic">K</span> and electromagnetic induction feedback gains <math display="inline"><semantics> <msub> <mi>K</mi> <mn>0</mn> </msub> </semantics></math>. The electromagnetic induction applied in column1 appears to be unable to control column2 (<b>b</b>,<b>e</b>) and column3 (<b>c</b>,<b>f</b>), which are in an epileptic state due to the propagation effects.</p>
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<p>Schematic diagram of the Wilson–Cowan model. E and I are the excitatory and inhibitory neural populations, respectively. <math display="inline"><semantics> <mrow> <msub> <mi>C</mi> <mi>i</mi> </msub> <mspace width="3.33333pt"/> <mrow> <mo>(</mo> <mi>i</mi> <mo>=</mo> <mn>1</mn> <mo>,</mo> <mn>2</mn> <mo>,</mo> <mn>3</mn> <mo>,</mo> <mn>4</mn> <mo>)</mo> </mrow> </mrow> </semantics></math> represent the coupling strengths between and within the subpopulations. Excitatory projections are denoted by arrows, while lines with filled circle represent inhibitory projections.</p>
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29 pages, 4124 KiB  
Article
Modulation of the Functional State of Mouse Neutrophils by Selenium Nanoparticles In Vivo
by Valentina N. Mal’tseva, Sergey V. Gudkov and Egor A. Turovsky
Int. J. Mol. Sci. 2022, 23(21), 13651; https://doi.org/10.3390/ijms232113651 - 7 Nov 2022
Cited by 8 | Viewed by 2119
Abstract
This study aimed to discover the immunomodulatory effect of selenium nanoparticles (SeNPs) on the functional state of neutrophils in vivo. Intraperitoneal injections of SeNPs (size 100 nm) 2.5 mg/kg/daily to BALB/c mice for a duration of 7–28 days led to the development of [...] Read more.
This study aimed to discover the immunomodulatory effect of selenium nanoparticles (SeNPs) on the functional state of neutrophils in vivo. Intraperitoneal injections of SeNPs (size 100 nm) 2.5 mg/kg/daily to BALB/c mice for a duration of 7–28 days led to the development of an inflammatory reaction, which was registered by a significant increase in the number of neutrophils released from the peritoneal cavity, as well as their activated state, without additional effects. At the same time, subcutaneous injections of the same SeNPs preparations at concentrations of 0.1, 0.5, and 2.5 mg/kg, on the contrary, modulated the functional state of neutrophils depending on the concentration and duration of SeNPs administration. With the use of fluorescence spectroscopy, chemiluminescence, biochemical methods, and PCR analysis, it was found that subcutaneous administration of SeNPs (0.1, 0.5, and 2.5 mg/kg) to mice for a short period of time (7–14 days) leads to modification of important neutrophil functions (adhesion, the number of migrating cells into the peritoneal cell cavity, ROS production, and NET formation). The obtained results indicated the immunostimulatory and antioxidant effects of SeNPs in vivo during short-term administration, while the most pronounced immunomodulatory effects of SeNPs were observed with the introduction of a low concentration of SeNPs (0.1 mg/kg). Increase in the administration time of SeNPs (0.1 mg/kg or 2.5 mg/kg) up to 28 days led to a decrease in the adhesive abilities of neutrophils and suppression of the expression of mRNA of adhesive molecules, as well as proteins involved in the generation of ROS, with the exception of NOX2; there was a tendency to suppress gene expression pro-inflammatory factors, which indicates the possible manifestation of immunosuppressive and anti-inflammatory effects of SeNPs during their long-term administration. Changes in the expression of selenoproteins also had features depending on the concentration and duration of the administered SeNPs. Selenoprotein P, selenoprotein M, selenoprotein S, selenoprotein K, and selenoprotein T were the most sensitive to the introduction of SeNPs into the mouse organism, which indicates their participation in maintaining the functional status of neutrophils, and possibly mediated the immunomodulatory effect of SeNPs. Full article
(This article belongs to the Special Issue Interaction of Nanomaterials with the Immune System 2.0)
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<p>Effect of injection of various concentrations of SeNPs into mice on the neutrophil number and adhesion. (<b>А</b>)—Dose- and time-dependent increase in the number of neutrophils isolated from mice peritoneal cavities after zymosan injection. The curves show the counts of neutrophil migration induced by zymosan (5 mg/mL) at 5 h after the daily intraperitoneal injection of SeNPs or saline (control) on days 7, 14, 21, and 28. Abbreviations: 2.5 mg/kg (s.c.)—subcutaneous injections of SeNPs and 2.5 mg/kg (i.p.) intraperitoneal injections of SeNPs. The data are the mean values ± SEM of seven mice. * <span class="html-italic">p</span> &lt; 0.01 compared with respective control group. Peritoneal evoked neutrophils of male mice of outbreed strain BALB/c were used in the experiments. Neutrophils comprised nearly 98% of the total number of cells, as determined by acridine orange staining. (<b>B</b>)—Dose- and time-dependent modification of neutrophil adhesion on days 7, 14, 21, and 28 after daily injection of SeNPs or saline (control). Concentration-dependent effects of SeNPs (0.1 mg Se/kg, 0.5 mg Se/kg, 2.5 mg Se/kg) on mouse neutrophil adhesion: сurves shown are blue—on day 7, red—on day 14, green—on day 21, and dark blue—on day 28 of administration of SeNPs, respectively. Adhesion was determined by spectrophotometric analysis at 492 nm and then OD492 in the neutrophils from experimental groups with administration of SeNPs normalized to the same parameter measured in control group. Data presented are the mean ± SEM (<span class="html-italic">n</span> = 7). Statistical analyses of experimental groups vs. control were performed with paired <span class="html-italic">t</span>-test. Significance between group means: * <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. Values not marked with an asterisk are invalid. (<b>C</b>)—Effect of SeNP injection in vivo on expression of neutrophil adhesion molecules CD11b and CD62L. Relative mRNA expression of genes encoding of CD11b and CD62L in neutrophils on days 14 and 28 after daily injection of 0.1 mg Se/kg (black bars) and 2.5 mg Se/kg (red bars) SeNPs. Dashed line—level of gene expression in controls (mice with administration of saline). GAPDH was used as housekeeping gene. Data are shown as mean ± SEM of five independent experiments. Statistical analysis of experimental groups versus control was performed with paired <span class="html-italic">t</span>-test and is marked with black asterisks. Significance between experimental groups is marked with red asterisks: *** <span class="html-italic">p</span> &lt; 0.001 and ** <span class="html-italic">p</span> &lt; 0.01; n/s—no significance.</p>
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<p>Effect of SeNP injections in vivo on spontaneous ROS production by neutrophils. (<b>А</b>)—The changes in spontaneous ROS production in neutrophils of the control and experimental groups with injection of 0.1 mg Se/kg, 0.5 mg Se/kg, and 2.5 mg Se/kg SeNPs. Data are presented at 7 (blue curve), 14 (red), 21 (green), and 28 days (dark blue) after daily injection. Control is the control group with injection of saline. (<b>В</b>)—Dynamics of changes in spontaneous ROS production in neutrophils of the control (red) and experimental group with intraperitoneal injection of 2.5 mg Se/kg (black) were estimated at 0, 7, 14, 21, and 28 days after daily injection of SeNPs or saline (control). The neutrophil ROS generation was determined by luminol-dependent chemiluminescence with automated multiplate reader (Spark™ 10M multimode microplate reader). Data are shown as the mean of chemiluminescence intensity, arb.units ± SEM of five animals for each group. Statistical analysis of experimental groups versus control was performed with paired <span class="html-italic">t</span>-test. Significance between group means: *** <span class="html-italic">p</span> &lt; 0.001 and ** <span class="html-italic">p</span> &lt; 0.01. Values not marked with an asterisk are n/s—no significance.</p>
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<p>Effect of injection of various concentrations of SeNPs for 28 days on activated ROS production by neutrophils. (<b>A</b>,<b>B</b>)—Dynamics of changes in ROS production in response to 1 μM FMLF (<b>A</b>) and 1 mg/mL OZ (<b>B</b>) in neutrophils of control mice and mice of experimental groups with injection of SeNPs: 0.1 mg Se/kg (red), 0.5 mg Se/kg (green), 2.5 mg Se/kg (blue), s.c. (subcutaneous), and 2.5 mg Se/kg (black), i.p. (intraperitoneally). The control group (saline)—dark-blue curve. The neutrophil ROS generation was determined by luminol-dependent chemiluminescence with automated multiplate reader (Spark™ 10M multimode microplate reader). Total ROS production was calculated as the area under the curve of chemiluminescence intensity in time. Data are expressed as the mean chemiluminescence intensity arb.units ± SEM of six animals for each group. Statistical analysis of experimental groups versus control was performed with paired <span class="html-italic">t</span>-test. Significance between group means: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span>&lt; 0.01, and * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Changes in intracellular expression of neutrophil genes involved in redox homeostasis after administration of 0.1 (<b>A</b>) and 2.5 (<b>B</b>) mg/kg SeNPs for 14 and 28 days. Neutrophils prepared from mice 14 (black bars) and 28 (red bars) days after daily injection of 0.1 mg Se/kg (<b>A</b>) and 2.5 mg Se/kg (<b>B</b>) SeNPs. GAPDH was used as housekeeping gene. Dashed line—level of gene expression in controls (mice with administration of saline). Data are expressed as mean ± SEM of five independent experiments. Statistical analysis of experimental groups versus control was performed with paired <span class="html-italic">t</span>-test and marked with black asterisks. Significance between experimental groups marked with red asterisks: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, and * <span class="html-italic">p</span> &lt; 0.05; n/s—no significance.</p>
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<p>The introduction of 0.1 (<b>A</b>) and 2.5 (<b>B</b>) mg/kg SeNPs for 14 and 28 days impacted the expression of genes associated with inflammation. Neutrophils prepared from mice 14 (black bars) and 28 (red bars) days after 0.1 mg Se/kg (<b>A</b>) and 2.5 mg Se/kg (<b>B</b>) SeNPs were injected daily. GAPDH was used as housekeeping gene. Data were analyzed by 2<sup>(-ΔΔCT)</sup> method. Dashed line—level of gene expression in controls (mice with administration of saline). Data are expressed as mean ± SEM of five independent experiments. Statistical analysis of experimental groups versus control was performed with paired <span class="html-italic">t</span>-test and marked with black asterisks. Significance between experimental groups marked with red asterisks: *** <span class="html-italic">p</span> &lt; 0.001 and * <span class="html-italic">p</span> &lt; 0.05; n/s—no significance.</p>
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<p>SeNPs modified unstimulated and stimulated NETs formation in a dose-dependent manner. NETs were released by unstimulated (neutrophils alone) (<b>A</b>) and stimulated (neutrophils + 1 mg/mL zymosan) (<b>B</b>) neutrophils: the control group (saline)—blue, groups with SeNP injection—0.1 mg Se/kg (red), 0.5 mg Se/kg (green), 2.5 mg Se/kg (dark blue). The NETs quantification estimated 0, 7, 14, 21, and 28 days after SeNPs or saline (control) were injected daily. NETs were identified as quantification extracellular DNA of supernatants from neutrophils using fluorometric DNA quantification assay (Pico488 DNA quantification kit) at 503 nm excitation wavelength and at 525 nm detection wavelength. Neutrophils were isolated from eight animals for each experimental group. Data are shown as mean ± SEM. Statistical analysis of experimental groups versus control was performed with paired <span class="html-italic">t</span>-test. Significance between group means: *** <span class="html-italic">p</span> &lt; 0.001 and * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effect of SeNPs applied in vivo on expression of genes involved in NETs formation. Respective mRNA expression genes encoding H2A.1, H2B, H3, neutrophil elastase (NE), and myeloperoxidase (MPO) in neutrophils 14 (black bars) and 28 (red bars) days after 0.1 mg Se/kg (<b>A</b>) and 2.5 mg Se/kg (<b>B</b>) SeNPs were injected daily. Dashed line—level of gene expression in controls (mice with administration of saline). GAPDH was used as housekeeping gene. Data are shown as mean ± SEM of five independent experiments. Statistical analysis of experimental groups versus control was performed with paired <span class="html-italic">t</span>-test and marked with black asterisks. Significance between experimental groups marked with red asterisks: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, and * <span class="html-italic">p</span> &lt; 0.05; n/s—no significance.</p>
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<p>Effect of SeNPs applied in vivo on expression of selenoproteins encoding genes in the neutrophils. Relative mRNA expression of genes encoding selenoproteins 14 (black bars) and 28 (red bars) days after SeNP daily injection in concentrations 0.1 mg Se/kg (<b>A</b>) and 2.5 mg Se/kg (<b>B</b>). Dashed line—level of gene expression in controls (mice with administration of saline). GAPDH was used as housekeeping gene. Data are expressed as mean ± SEM of five independent experiments. Statistical analysis of experimental groups versus control was performed with paired <span class="html-italic">t</span>-test and marked with black asterisks. Significance between experimental groups marked with red asterisks: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01, and * <span class="html-italic">p</span> &lt; 0.05; n/s—no significance.</p>
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26 pages, 11747 KiB  
Article
In Silico Identification of Multi-Target Ligands as Promising Hit Compounds for Neurodegenerative Diseases Drug Development
by Petko Alov, Hristo Stoimenov, Iglika Lessigiarska, Tania Pencheva, Nikolay T. Tzvetkov, Ilza Pajeva and Ivanka Tsakovska
Int. J. Mol. Sci. 2022, 23(21), 13650; https://doi.org/10.3390/ijms232113650 - 7 Nov 2022
Cited by 2 | Viewed by 2462
Abstract
The conventional treatment of neurodegenerative diseases (NDDs) is based on the “one molecule—one target” paradigm. To combat the multifactorial nature of NDDs, the focus is now shifted toward the development of small-molecule-based compounds that can modulate more than one protein target, known as [...] Read more.
The conventional treatment of neurodegenerative diseases (NDDs) is based on the “one molecule—one target” paradigm. To combat the multifactorial nature of NDDs, the focus is now shifted toward the development of small-molecule-based compounds that can modulate more than one protein target, known as “multi-target-directed ligands” (MTDLs), while having low affinity for proteins that are irrelevant for the therapy. The in silico approaches have demonstrated a potential to be a suitable tool for the identification of MTDLs as promising drug candidates with reduction in cost and time for research and development. In this study more than 650,000 compounds were screened by a series of in silico approaches to identify drug-like compounds with predicted activity simultaneously towards three important proteins in the NDDs symptomatic treatment: acetylcholinesterase (AChE), histone deacetylase 2 (HDAC2), and monoamine oxidase B (MAO-B). The compounds with affinities below 5.0 µM for all studied targets were additionally filtered to remove known non-specifically binding or unstable compounds. The selected four hits underwent subsequent refinement through in silico blood-brain barrier penetration estimation, safety evaluation, and molecular dynamics simulations resulting in two hit compounds that constitute a rational basis for further development of multi-target active compounds against NDDs. Full article
(This article belongs to the Collection Computational Studies of Biomolecules)
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Figure 1

Figure 1
<p>PDB crystallographic structures and reference ligands of the selected target protein complexes.</p>
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<p>A flowchart representing the computational workflow with the main steps/approaches applied to identify the hit compounds toward AChE, HDAC2 and MAO-B enzymes.</p>
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<p>Active sites together with the bound reference ligands (in orange) of the selected proteins: the amino acids involved in specific interactions are presented in sticks &amp; balls: AChE (Trp86, Trp286, Phe295); HDAC2 (Gly154, Asp181, Tyr308 and Zn<sup>2+</sup> cofactor, represented as a sphere); MAO-B (Leu171, Gln206).</p>
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<p>Distribution (in %) of the top 377 compounds based on the predicted <span class="html-italic">K<sub>i</sub></span> values for each of the three proteins.</p>
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<p>Consensus pharmacophore models of the top 16 hit ligands of AChE, HDAC2, and MAO-B. The following pharmacophoric features are outlined in the models: AChE—F1 (hydrophobic/aromatic feature), F2 (functional groups capable of performing hydrogen bonds (HB)), F3 (functional groups capable of performing HBs as HB acceptors); HDAC2—F1, F2 (hydrophobic/aromatic features), F3, F4 (functional groups capable of performing HBs as HB acceptors), F5 (functional groups capable of performing HBs as HB donors); MAO-B—F1, F2, F3 (hydrophobic/aromatic features).Individually for each protein, the pharmacophore features were present in 11 ligands for MAO-B, 8 for HDAC2 and 7 for AChE. Finally, four ligands contained every single pharmacophore feature for each protein (compounds: Specs AH-487/42478269 (1), Comgenex CGX-3274395 (8), Chem T&amp;I AMCLME-10390 (10), and Asinex BAS 07211091 (16) in <a href="#ijms-23-13650-t003" class="html-table">Table 3</a>). These compounds were outlined as potential multi-target acting hits and subjected to further analyses as described below.</p>
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<p>Calculated RMSDs (Å) of the displacements of the protein-ligand complexes over the MD simulation time: (<b>A</b>) AChE with reference ligand/hit ligands; (<b>B</b>) HDAC2 with reference ligand/hit ligands; (<b>C</b>) MAO-B with reference ligand/hit ligands.</p>
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<p>Calculated RMSDs (Å) of the displacements of the protein-ligand complexes over the MD simulation time: (<b>A</b>) AChE with reference ligand/hit ligands; (<b>B</b>) HDAC2 with reference ligand/hit ligands; (<b>C</b>) MAO-B with reference ligand/hit ligands.</p>
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<p>Protein-ligand interactions for the enzyme complexes with reference ligand/hit ligands obtained in the MD simulations: (<b>A</b>) AChE; (<b>B</b>) HDAC2; (<b>C</b>) MAO-B.</p>
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<p>Protein-ligand interactions for the enzyme complexes with reference ligand/hit ligands obtained in the MD simulations: (<b>A</b>) AChE; (<b>B</b>) HDAC2; (<b>C</b>) MAO-B.</p>
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<p>Protein-ligand interactions for the enzyme complexes with reference ligand/hit ligands obtained in the MD simulations: (<b>A</b>) AChE; (<b>B</b>) HDAC2; (<b>C</b>) MAO-B.</p>
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20 pages, 5781 KiB  
Article
The Cysteine Protease Giardipain-1 from Giardia duodenalis Contributes to a Disruption of Intestinal Homeostasis
by Rodrigo Quezada-Lázaro, Yessica Vázquez-Cobix, Rocío Fonseca-Liñán, Porfirio Nava, Daniel Dimitri Hernández-Cueto, Carlos Cedillo-Peláez, Yolanda López-Vidal, Sara Huerta-Yepez and M. Guadalupe Ortega-Pierres
Int. J. Mol. Sci. 2022, 23(21), 13649; https://doi.org/10.3390/ijms232113649 - 7 Nov 2022
Cited by 3 | Viewed by 2100
Abstract
In giardiasis, diarrhoea, dehydration, malabsorption, weight loss and/or chronic inflammation are indicative of epithelial barrier dysfunction. However, the pathogenesis of giardiasis is still enigmatic in many aspects. Here, we show evidence that a cysteine protease of Giardia duodenalis called giardipain-1, contributes to the [...] Read more.
In giardiasis, diarrhoea, dehydration, malabsorption, weight loss and/or chronic inflammation are indicative of epithelial barrier dysfunction. However, the pathogenesis of giardiasis is still enigmatic in many aspects. Here, we show evidence that a cysteine protease of Giardia duodenalis called giardipain-1, contributes to the pathogenesis of giardiasis induced by trophozoites of the WB strain. In an experimental system, we demonstrate that purified giardipain-1 induces apoptosis and extrusion of epithelial cells at the tips of the villi in infected jirds (Meriones unguiculatus). Moreover, jird infection with trophozoites expressing giardipain-1 resulted in intestinal epithelial damage, cellular infiltration, crypt hyperplasia, goblet cell hypertrophy and oedema. Pathological alterations were more pronounced when jirds were infected intragastrically with Giardia trophozoites that stably overexpress giardipain-1. Furthermore, Giardia colonization in jirds results in a chronic inflammation that could relate to the dysbiosis triggered by the protist. Taken together, these results reveal that giardipain-1 plays a key role in the pathogenesis of giardiasis. Full article
(This article belongs to the Special Issue Gut Microbiota and Immunity 2.0)
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Figure 1
<p>Giardiapain-1 induces apoptosis in intestinal epithelial cells of the jird duodenum. Staining by terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL; green) of duodenal cryosections from control and giardipain-1 treated animals. Representative histological sections of the duodenum of control jirds or infected animals are included. The panels are identified as follows, sections from: (<b>A</b>) and (<b>B</b>) (amplification) control animals, (<b>C</b>) and (<b>D</b>) (amplification) giardipain-1 treated animals at 4 h p.i. (<b>E</b>) and (<b>F</b>) (amplification) control animals, (<b>G</b>) and (<b>H</b>) (magnification) animals treated with giardipain-1 at 6 h p.i. PAN-cadherin an intestinal epithelial cell marker = red. Nuclei = Blue. Dashed line delimits the villi. V = villi. LP = lamina propria. Arrows identify apoptotic epithelial cells that are extruded from the villi. Scale bar = 50 μm.</p>
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<p>Recognition of giardipain-1 by monoclonal antibody 1G3 in total extracts of <span class="html-italic">G. duodenalis</span> WB giardipain pAC trophozoites, WB<sup>+</sup> and WB<sup>−</sup> and detection of its proteolytic activity. (<b>A</b>) Total extracts of <span class="html-italic">G. duodenalis</span> trophozoites were separated by SDS-PAGE transferred to PVDF membranes and probed with mAb 1G3. (a) A 25 kDa band was recognized with high (WB giardiapin pAC), wild type (WB<sup>+</sup>) or low expression (WB<sup>−</sup>) of giardipain-1 by 1G3 antibodies. (b) In these assays Tubulin was used as loading control. (<b>B</b>) Proteolytic activity detected in the same parasite samples. A specific proteolytic band with molecular weight of 25 kDa was detected with high (WB giardipain-pAC) wild type (WB<sup>+</sup>) and low (WB<sup>−</sup>) proteolytic activity.</p>
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<p>WB<sup>+</sup>, WB<sup>−</sup> and WB giardipain-pAC trophozoites recovered from the duodenum of infected jirds at 14 days post-inoculation. Bars indicate the average number of trophozoites recovered from groups of three animals each ±SEM.</p>
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<p>The infection of jirds with <span class="html-italic">Giardia duodenalis</span> trophozoites triggers microscopic alterations in the duodenum of these animals. Representative histological sections of the duodenum of control jirds or animals that were infected with WB<sup>−</sup>, or WB<sup>+</sup> or WB giardipain-pAC. Time p.i. are 14 days, 21 days, 3 months and 6 months. Panels A to D are sections of control animals displaying normal mucosa with no alterations. In Panels E to H are sections of the duodenum from jirds infected with WB<sup>−</sup> trophozoites, in panels I to L are section of duodenum from jirds infected with WB<sup>+</sup> trophozoites and in panels M to P are sections of jirds infected with WB giardipain-pAC trophozoites. Hypertrophy, shortening and fusion of villi (black arrow) as well as hyperplasia of the intestinal crypts (head arrow), oedema and inflammatory infiltrate (*) were observed in WB<sup>+</sup> infected jirds. The alterations were more severe at 6 months p.i. WB giardipain-pAC trophozoite induced similar histopathological alterations to the ones described for WB<sup>+</sup> trophozoites However, the changes were more severe and cryptitis (black ball) was observed at 6 months p.i. A lower number of globet cells were observed in WB<sup>−</sup> infected jirds. H&amp;E stain, 300 μm and 100 μm scale bar.</p>
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<p>The infection of jirds with <span class="html-italic">Giardia duodenalis</span> trophozoites increases proliferation in the intestinal crypts of the duodenum in these animals. Proliferation in the duodenum of jirds that were infected with WB giardipain-pAC or WB<sup>+</sup> trophozoites as assessed by the detection of Ki-67 (green) or of pH3 (green). Representative histological sections of the duodenum of control jirds or infected animals are included, and panels are as follows, sections stained with Ki-67 from: (<b>A</b>) control jirds, (<b>B</b>) animals infected with WB<sup>+</sup> trophozoites (<b>C</b>) jirds infected with WB giardipain-pAC trophozoites, at 14 days p.i. (<b>D</b>) control animals (<b>E</b>) animals infected with WB<sup>+</sup> trophozoites. (<b>F</b>) jirds infected with WB giardipain–pAC trophozoites, at 21 days p.i. (<b>G</b>) control animals (<b>H</b>) animals infected with WB<sup>+</sup> trophozoites, (<b>I</b>) animals infected with WB giardipain-pAC trophozoites, at 3 months p.i. Sections stained with pH3 from: (<b>J</b>) control animals (<b>K</b>) animals infected with WB<sup>+</sup> trophozoites, (<b>L</b>) animals infected with WB giardipain-pAC trophozoites, at 14 days p.i. (<b>M</b>) control animals (<b>N</b>) animals infected with WB<sup>+</sup> trophozoites (<b>O</b>) jirds infected with WB giardipain-pAC trophozoites, at 21 days p.i. (<b>P</b>) control animals (<b>Q</b>) animals infected with WB<sup>+</sup> trophozoites (<b>R</b>) animals infected with WB giardipain-pAC trophozoites, at 3 months p.i. Nuclei = blue. Dashed line marks the crypt border. Scale bar = 100 μm.</p>
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<p>The infection of jirds with <span class="html-italic">Giardia duodenalis</span> trophozoites affects the biogenesis of goblet cells in the intestinal crypts of the duodenum in these animals. Goblet cells were identified by Alcian blue and Periodic acid–Schiff (PAS) staining of the duodenum of control jirds of animals that were infected with WB giardipain-pAC or WB<sup>+</sup> or WB<sup>−</sup> trophozoites. Representative histological sections of the duodenum of control jirds or infected animals are included. Times p.i. are 14 days, 21 days, 3 months and 6 months. PAS-AB + IEC representing the normal population of goblet cells in intestinal villi is observed in the control animals (<b>A–D</b>). PAS-AB <sup>+</sup> IEC increased in sections of the duodenum of the group infected with trophozoites. Panels are as follows: WB<sup>-</sup> trophozoites (<b>E</b>) 14 days p.i. (<b>F</b>) 21 days p.i. (<b>G</b>) 3 months p.i. (<b>H</b>) 6 months p.i. WB<sup>+</sup> (<b>I</b>) 14 days p.i. (<b>J</b>) 21 days p.i. (<b>K</b>) 3 months p.i. (<b>L</b>) 6 months p.i. and WB giardipain-pAC trophozoites (<b>M</b>) 14 days p.i. (<b>N</b>) 21 days p.i. (<b>O</b>) 3 months p.i. (<b>P</b>) 6 months p.i. At 14 and 21 days, goblet cells were detected in the crypt base. At 3 and 6 months, goblet cells were observed along the whole crypt-villus axis. A lower number of globet cells were observed in WB<sup>−</sup> infected jirds. AB<sup>+</sup> cells = blue color. PAS<sup>+</sup> = purple color. Arrows indicate positively stained goblet cells.</p>
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<p>MUC2 is increased in the duodenum of jirds infected with <span class="html-italic">Giardia duodenalis</span> trophozoites. Mucin 2 (MUC2) was detected by immunofluorescence staining of the duodenum of jirds that were infected with WB giardipain-pAC or WB<sup>+</sup> trophozoites. Representative histological sections of the duodenum of control jirds or infected animals are included. Panels are as follows, sections from: (<b>A</b>) control animals (<b>B</b>) animals infected with WB<sup>+</sup> trophozoites (<b>C</b>) animals infected with WB giardipain-pAC trophozoites at 14 days p.i. (<b>D</b>) control animals (<b>E</b>) animals infected with WB<sup>+</sup> trophozoites (<b>F</b>) animals infected with WB giardipain-pAC trophozoites, at 21 days p.i. (<b>G</b>) control animals (<b>H</b>) animals infected with WB<sup>+</sup> trophozoites (<b>I</b>), animals infected with WB giardipain-pAC trophozoites, at 3 months p.i. MUC2 = Green. Nuclei = blue. Dashed line marks the crypt border. White arrow indicates secreted MUC2. Red arrow = indicates intracellular accumulation of MUC2. Scale bar = 100 μm.</p>
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<p>The infection of jirds with <span class="html-italic">Giardia duodenalis</span> trophozoites triggers the recruitment of CD3+ at the duodenum of jirds. CD3<sup>+</sup> cells were determined by immunohistochemistry in histological sections of the duodenum of jirds that were infected with WB giardipain-pAC or WB<sup>+</sup> trophozoites. Representative histological sections of the duodenum of control jirds or infected animals are included. Panels are identified as follows, sections from: (<b>A</b>) control animals, (<b>B</b>) animals infected with WB<sup>+</sup> trophozoites, (<b>C</b>) animals infected with WB giardipain-pAC trophozoites at 14 days p.i. (<b>D</b>) control animals (<b>E</b>) animals infected with WB<sup>+</sup> trophozoites (<b>F</b>) animals infected with WB giardipain-pAc trophozoites at 21 days p.i. (<b>G</b>) control animals (<b>H</b>) animals infected with WB<sup>+</sup> trophozoites. (<b>I</b>) jirds infected with WB giardipain-pAc trophozoites at 3 months p.i. CD3<sup>+</sup> cells are stained in brown. Scale bar = 300 μm and 100 μM.</p>
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<p>Microscopic alterations in sections of the duodenum of the animals treated with fecotransplants, then infected with WB giardipain-pAC trophozoites and euthanized at 21 days p.i. Representative histological and histochemistry sections of the duodenum of jirds that received the microbiota of previously infected jirds and then were infected with WB giardipain-pAC. Sections are from: (<b>A</b>) control animals displaying normal mucosa with no alterations. (<b>B</b>) jirds given microbiota from animals infected with WB giardipain-pAC trophozoites; in these animals slight thickening of villi was observed, (<b>C</b>) animals that received microbiota and that were infected with WB giardipain-pAC. In these atrophy, fusion of villi (red arrow) as well as hyperplasia of the intestinal crypts (head arrow) and inflammatory infiltrate (*) were observed by H&amp;E stain, 300 μm and 100 scale bar. PAS-AB+ stained of sections from: (<b>D</b>) control animals in which the normal population of goblet cells in intestinal villi was observed. (<b>E</b>) jirds that were given microbiota from animals previously infected with WB giardipain-pAC trophozoites; in these sections a slight increase in goblet cells was observed and (<b>F</b>) animals given microbiota and then infected with WB giardipain-pAC. In these a marked increase in goblet cells was observed = arrow. Scale bar = 300 μm and 100 μM.</p>
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<p>Determination of changes in the microbiota (Mb) composition of jirds that received different treatments and were euthanized at 21 days p.i. Composition of the microbiota in jird feces that received different treatments was determined by 16S ribosomal RNA gene amplicon sequencing. The data were compared between the control group (PBS) and the group of animals that was given microbiota from giardipain-pAC infected animals and then were infected with WB giardipain-pAC trophozoites. (<b>A</b>) Average relative microbial abundance at the family levels in the different groups. (<b>B</b>) Variation in beta-diversity of jird gut bacterial communities based on Bray–Curtis dissimilarities. (<b>C</b>) Heat map for relative abundance at species level with significant changes.</p>
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18 pages, 14811 KiB  
Article
E3 Ubiquitin Ligase FBXO3 Drives Neuroinflammation to Aggravate Cerebral Ischemia/Reperfusion Injury
by Yu Gao, Xinyu Xiao, Jing Luo, Jianwei Wang, Qiling Peng, Jing Zhao, Ning Jiang and Yong Zhao
Int. J. Mol. Sci. 2022, 23(21), 13648; https://doi.org/10.3390/ijms232113648 - 7 Nov 2022
Cited by 6 | Viewed by 2588
Abstract
Ischemic stroke, one of the most universal causes of human mortality and morbidity, is pathologically characterized by inflammatory cascade, especially during the progression of ischemia/reperfusion (I/R) injury. F-Box Protein 3 (FBXO3), a substrate-recognition subunit of SKP1-cullin 1-F-box protein (SCF) E3 ligase complexes, has [...] Read more.
Ischemic stroke, one of the most universal causes of human mortality and morbidity, is pathologically characterized by inflammatory cascade, especially during the progression of ischemia/reperfusion (I/R) injury. F-Box Protein 3 (FBXO3), a substrate-recognition subunit of SKP1-cullin 1-F-box protein (SCF) E3 ligase complexes, has recently been proven to be severed as an underlying pro-inflammatory factor in pathological processes of diverse diseases. Given these considerations, the current study aims at investigating whether FBXO3 exerts impacts on inflammation in cerebral I/R injury. In this study, first, it was verified that FBXO3 protein expression increased after a middle cerebral artery occlusion/reperfusion (MCAO/R) model in Sprague–Dawley (SD) rats and was specifically expressed in neurons other than microglia or astrocytes. Meanwhile, in mouse hippocampal neuronal cell line HT22 cells, the elevation of FBXO3 protein was observed after oxygen and glucose deprivation/reoxygenation (OGD/R) treatment. It was also found that interference of FBXO3 with siRNA significantly alleviated neuronal damage via inhibiting the inflammatory response in I/R injury both in vivo and in vitro. The FBXO3 inhibitor BC-1215 was used to confirm the pro-inflammatory effect of FBXO3 in the OGD/R model as well. Furthermore, by administration of FBXO3 siRNA and BC-1215, FBXO3 was verified to reduce the protein level of Homeodomain-Interacting Protein Kinase 2 (HIPK2), likely through the ubiquitin–proteasome system (UPS), to aggravate cerebral I/R injury. Collectively, our results underline the detrimental effect FBXO3 has on cerebral I/R injury by accelerating inflammatory response, possibly through ubiquitylating and degrading HIPK2. Despite the specific interaction between FBXO3 and HIPK2 requiring further study, we believe that our data suggest the therapeutic relevance of FBXO3 to ischemic stroke and provide a new perspective on the mechanism of I/R injury. Full article
(This article belongs to the Special Issue Advances in Molecular Mechanisms of Stroke)
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Figure 1
<p>FBXO3 was elevated after Middle cerebral artery occlusion/reperfusion (MCAO/R) in Sprague-Dawley (SD) rats, and specifically expressed in neurons. (<b>A</b>,<b>B</b>) Western blotting (WB) analysis of FBXO3 in the peri-infarcted cortex of SD rats at MCAO 1 h/R 6, 12, 24, 48, 72 h, and sham treatment. (<b>C</b>–<b>E</b>) Representative images (400×, scale bar = 100 μm) of FBXO3 (green)/NeuN (neuronal biomarker, red)/DAPI (blue), FBXO3/Iba-1 (microglial biomarker, red)/DAPI, and FBXO3/GFAP (astrocytic biomarker, red)/ DAPI immunostaining in the ischemic penumbra at sham and MCAO 1 h/R 24 h treatment, respectively. The arrows in <a href="#ijms-23-13648-f001" class="html-fig">Figure 1</a>C indicate representative FBXO3+ neurons. Statistics for each group are expressed as mean ± SD (<span class="html-italic">n</span> = 6). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 (values in Sham group versus different reperfusion time group).</p>
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<p>Interference of FBXO3 rescued the neurological outcomes after MCAO/R in vivo. (<b>A</b>–<b>C</b>) WB and qPCR analysis of FBXO3 in the peri-infarcted cortex of MCAO/R rats with or without siRNA treatment and in sham rats. (<b>D</b>) Representative TTC (2,3,5-triphenyltetrazolium chloride) staining images of coronal sections of MCAO/R rats with or without siRNA treatment and sham rats. (<b>E</b>) Quantification of infarct volumes of coronal sections of MCAO/R rats with or without siRNA treatment and sham rats by ImageJ (total lesion volume/total brain volume × 100%). (<b>F</b>) Neurological deficit scores of MCAO/R rats with or without siRNA treatment and sham rats. (<b>G</b>) HE and Nissl staining (400×, scale bar = 50 μm) in the peri-infarcted cortex of MCAO/R rats with or without siRNA treatment and in sham rats. The arrows indicate representative Nissl bodies. Statistics for each group are expressed as mean ± SD (<span class="html-italic">n</span> = 6). ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001 (values in Sham group versus MCAO group), and # <span class="html-italic">p</span> &lt; 0.05, #### <span class="html-italic">p</span> &lt; 0.0001 (values in NC group versus si-FBXO3 group).</p>
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<p>Interference of FBXO3 rescued the neurological outcomes after MCAO/R in vivo. (<b>A</b>–<b>C</b>) WB and qPCR analysis of FBXO3 in the peri-infarcted cortex of MCAO/R rats with or without siRNA treatment and in sham rats. (<b>D</b>) Representative TTC (2,3,5-triphenyltetrazolium chloride) staining images of coronal sections of MCAO/R rats with or without siRNA treatment and sham rats. (<b>E</b>) Quantification of infarct volumes of coronal sections of MCAO/R rats with or without siRNA treatment and sham rats by ImageJ (total lesion volume/total brain volume × 100%). (<b>F</b>) Neurological deficit scores of MCAO/R rats with or without siRNA treatment and sham rats. (<b>G</b>) HE and Nissl staining (400×, scale bar = 50 μm) in the peri-infarcted cortex of MCAO/R rats with or without siRNA treatment and in sham rats. The arrows indicate representative Nissl bodies. Statistics for each group are expressed as mean ± SD (<span class="html-italic">n</span> = 6). ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001 (values in Sham group versus MCAO group), and # <span class="html-italic">p</span> &lt; 0.05, #### <span class="html-italic">p</span> &lt; 0.0001 (values in NC group versus si-FBXO3 group).</p>
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<p>Interference of FBXO3 attenuated the glucose deprivation/reoxygenation (OGD/R) induced neuronal death in vitro. (<b>A</b>,<b>C</b>) WB analysis of FBXO3 in HT22 cells at OGD 4 h/R 3, 6, 12, 24, and 48 h. (<b>B</b>–<b>E</b>) WB and qPCR analysis of FBXO3 in HT22 cells at OGD 4 h/R 24 h with or without siRNA treatment. (<b>F</b>) CCK8 assays of HT22 cells at OGD 4 h/R 24 h with or without siRNA treatment. (<b>G</b>–<b>H</b>) Quantification and representative images of Flowcytometry by detecting the fluorescent intensity of Annexin V-FITC and Propidium Iodide (PI) of HT22 cells at OGD 4 h/R 24 h with or without siRNA treatment. (<b>I</b>) Representative immunofluorescence images (400×, scale bar = 50 μm) of Calcein and PI in HT22 cells at OGD 4 h/R 24 h with or without siRNA treatment. Statistics for each group are expressed as mean ± SD (<span class="html-italic">n</span> ≥ 6). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 (values in Control group versus different reoxygenation time group), ### <span class="html-italic">p</span> &lt; 0.001 (values in NC group versus si-FBXO3 group).</p>
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<p>Treatment of si-FBXO3 inhibited inflammatory response induced by ischemia/reperfusion (I/R) injury in vivo. (<b>A</b>,<b>B</b>) WB analysis of inflammatory cytokines including IL-1β, IL-18, and TNFα in the peri-infarcted cortex of MCAO/R rats with or without siRNA treatment and in sham rats. (<b>C</b>,<b>D</b>) ELISA analysis of inflammatory cytokines including IL-1β and TNFα in the peri-infarcted cortex of MCAO/R rats with or without siRNA treatment and in sham rats. (<b>E</b>) Immunostaining of MPO (inflammation indicator, green) and DAPI (blue) in the peri-infarcted cortex of MCAO/R rats with or without siRNA treatment and in sham rats. (×630, scale bar = 100 μm). Statistics for each group are expressed as mean ± SD (<span class="html-italic">n</span> ≥ 6). ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001 (values in Control group versus MCAO group), # <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 (values in NC group versus si-FBXO3 group).</p>
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<p>Inhibition of FBXO3 alleviated inflammatory response induced by I/R injury in vitro. (<b>A</b>,<b>B</b>) WB analysis of inflammatory cytokines including IL-1β, IL-18, and TNFα in HT22 cells at OGD 4 h/R 24 h with or without siRNA treatment. (<b>C</b>,<b>D</b>) ELISA analysis of inflammatory cytokines including IL-1β and IL-18 in HT22 cells at OGD 4 h/R 24 h with or without siRNA treatment. (<b>E</b>,<b>F</b>) WB analysis of inflammatory cytokines including IL-1β, IL-18, and TNFα in HT22 cells at OGD 4 h/R 24 h with DMSO or BC-1215 treatment. (<b>G</b>,<b>H</b>) ELISA analysis of inflammatory cytokines including IL-1β and IL-18 in HT22 cells at OGD 4 h/R 24 h with DMSO or BC-1215 treatment. Statistics for each group are expressed as mean ± SD (<span class="html-italic">n</span> ≥ 6). * <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 (values in Control group versus MCAO group), # <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 (values in NC group versus si-FBXO3 group), &amp; <span class="html-italic">p</span> &lt; 0.05, &amp;&amp; <span class="html-italic">p</span> &lt; 0.01, &amp;&amp;&amp; <span class="html-italic">p</span> &lt; 0.001 (values in DMSO group versus BC-1215 group).</p>
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<p>FBXO3 facilitated inflammation probably through binding and degrading HIPK2 in HT22 cells after OGD/R stimulation. (<b>A</b>,<b>C</b>) WB analysis of HIPK2 in HT22 cells at OGD4 h/R 24 h with or without siRNA treatment. (<b>B</b>,<b>D</b>) WB analysis of HIPK2 in HT22 cells at OGD4 h/R 24 h with DMSO or BC-1215 treatment. (<b>E</b>) Co-Immunoprecipitation (Co-IP) analysis of FBXO3 and HIPK2 in HT22 cells. (<b>F</b>) Representative immunofluorescence images (200×, scale bar = 100 μm) of FBXO3 (red) and HIPK2 (green) in HT22 cells at OGD4 h/R 24 h with or without siRNA treatment. Statistics for each group are expressed as mean ± SD (<span class="html-italic">n</span> ≥ 6). * <span class="html-italic">p</span> &lt; 0.05 (values in Control group versus MCAO group), # <span class="html-italic">p</span> &lt; 0.05 (values in NC group versus si-FBXO3 group), &amp;&amp; <span class="html-italic">p</span> &lt; 0.01 (values in DMSO group versus BC-1215 group).</p>
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<p>FBXO3 facilitated inflammation probably through binding and degrading HIPK2 in HT22 cells after OGD/R stimulation. (<b>A</b>,<b>C</b>) WB analysis of HIPK2 in HT22 cells at OGD4 h/R 24 h with or without siRNA treatment. (<b>B</b>,<b>D</b>) WB analysis of HIPK2 in HT22 cells at OGD4 h/R 24 h with DMSO or BC-1215 treatment. (<b>E</b>) Co-Immunoprecipitation (Co-IP) analysis of FBXO3 and HIPK2 in HT22 cells. (<b>F</b>) Representative immunofluorescence images (200×, scale bar = 100 μm) of FBXO3 (red) and HIPK2 (green) in HT22 cells at OGD4 h/R 24 h with or without siRNA treatment. Statistics for each group are expressed as mean ± SD (<span class="html-italic">n</span> ≥ 6). * <span class="html-italic">p</span> &lt; 0.05 (values in Control group versus MCAO group), # <span class="html-italic">p</span> &lt; 0.05 (values in NC group versus si-FBXO3 group), &amp;&amp; <span class="html-italic">p</span> &lt; 0.01 (values in DMSO group versus BC-1215 group).</p>
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<p>Schematic illustration of FBXO3 driving neuroinflammation to aggravate neuronal damage in cerebral I/R injury by degrading HIPK2.</p>
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17 pages, 3488 KiB  
Article
Biological Solubilisation of Leather Industry Waste in Anaerobic Conditions: Effect of Chromium (III) Presence, Pre-Treatments and Temperature Strategies
by Juana Fernández-Rodríguez, Beñat Lorea and Gustavo González-Gaitano
Int. J. Mol. Sci. 2022, 23(21), 13647; https://doi.org/10.3390/ijms232113647 - 7 Nov 2022
Cited by 7 | Viewed by 2188
Abstract
Collagen-based polymers and their blends have attracted considerable interest for new materials development due to their unique combination of biocompatibility, physical and mechanical properties and durability. Leather, a modified natural biopolymer made from animal rawhide and the first synthetic collagen-based polymer known since [...] Read more.
Collagen-based polymers and their blends have attracted considerable interest for new materials development due to their unique combination of biocompatibility, physical and mechanical properties and durability. Leather, a modified natural biopolymer made from animal rawhide and the first synthetic collagen-based polymer known since the dawn of civilization, combines all these features. Rawhide is transformed into leather by tanning, a process in which the collagen is cross-linked with different agents to make it stronger and more durable and to prevent its decay. Research on the development of environmentally friendly procedures and sustainable materials with higher efficiency and lower costs is a rapidly growing field, and leather industry is not an exemption. Chrome-tanned and vegetable-tanned (chromium-free) shavings from the leather industry present a high content of organic matter, yet they are considered recalcitrant waste to be degraded by microbiological processes like anaerobic digestion (AD), a solid technology to treat organic waste in a circular economy framework. In this technology however, the solubilisation of organic solid substrates is a significant challenge to improving the efficiency of the process. In this context, we have investigated the process of microbial decomposition of leather wastes from the tannery industry to search for the conditions that produce optimal solubilisation of organic matter. Chrome-tanned and chromium-free leather shavings were pre-treated and anaerobically digested under different temperature ranges (thermophilic–55 °C-, intermediate–42 °C- and mesophilic–35 °C) to evaluate the effect on the solubilisation of the organic matter of the wastes. The results showed that the presence of chromium significantly inhibited the solubilization (up to 60%) in the mesophilic and intermediate ranges; this is the fastest and most efficient solubilization reached under thermophilic conditions using the chromium-free leather shaving as substrates. The most suitable temperature for the solubilization was the thermophilic regime (55 °C) for both chromium-free and chrome-tanned shavings. No significant differences were observed in the thermophilic anaerobic digestion of chromium-free shavings when a pre-treatment was applied, since the solubilisation was already high without pre-treatment. However, the pre-treatments significantly improved the solubilisation in the mesophilic and intermediate configurations; the former pre-treatment was better suited in terms of performance and cost-effectiveness compared to the thermophilic range. Thus, the solubilisation of chromium-free tannery solid wastes can be significantly improved by applying appropriate pre-treatments at lower temperature ranges; this is of utter importance when optimizing anaerobic processes of recalcitrant organic wastes, with the added benefit of substantial energy savings in the scaling up of the process in an optimised circular economy scenario. Full article
(This article belongs to the Special Issue Biosynthesis and Biodegradation—Eco-Concept for Polymer Materials)
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<p>Thermogravimetric profiles (TGA and DTG) of chrome-tanned (C) and chromium-free (NC) leather wastes.</p>
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<p>(<b>a</b>) ATR-FTIR spectra of Cr(III)-free leather waste as a function of the temperature; and (<b>b</b>) zoomed-in view of the amide III zone of the FTIR spectra of Cr(III)-free leather waste as a function of the temperature.</p>
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<p>Shift of the amide III band as a function of the temperature (heating and cooling runs), showing the structural hysteresis.</p>
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<p>Evolution of organic matter solubilisation at thermophilic (55 °C), intermediate (42 °C) and mesophilic (35 °C) temperature regimes: (<b>a</b>) COD<sub>s</sub> from chrome-tanned (C); (<b>b</b>) DOC from chrome-tanned (C); (<b>c</b>) COD<sub>s</sub> from chromium-free (NC); and (<b>d</b>) DOC from chromium-free (NC) leather shavings.</p>
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<p>Evolution of organic matter solubilisation at thermophilic (55 °C), intermediate (42 °C) and mesophilic (35 °C) temperature regimes: (<b>a</b>) COD<sub>s</sub> from pre-treated chrome-tanned (C-P); (<b>b</b>) DOC from pre-treated chrome-tanned (C-P); (<b>c</b>) COD<sub>s</sub> from pre-treated chromium-free (NC-P); and (<b>d</b>) DOC from pre-treated chromium-free (NC-P) leather shavings.</p>
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<p>Solubilisation of the leather shavings expressed as CODs (mg/L) at different temperatures (55, 42, 35 °C). Not pre-treated (-); pre-treated (P); with Cr(III) (C) and without Cr(III) (NC). On top of bars, increments over the not pre-treated substrates.</p>
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<p>Micrographs of the leather shavings used: (<b>a</b>) Chrome-tanned (C), tanned from the wet blue industrial process; and (<b>b</b>) chromium-free (NC), from the wet white industrial process.</p>
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<p>Scheme of the experimental setup for the AD.</p>
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19 pages, 1006 KiB  
Review
Helicobacter pylori in the Oral Cavity: Current Evidence and Potential Survival Strategies
by Lin Zhang, Xi Chen, Biao Ren, Xuedong Zhou and Lei Cheng
Int. J. Mol. Sci. 2022, 23(21), 13646; https://doi.org/10.3390/ijms232113646 - 7 Nov 2022
Cited by 20 | Viewed by 8260
Abstract
Helicobacter pylori (H. pylori) is transmitted primarily through the oral–oral route and fecal–oral route. The oral cavity had therefore been hypothesized as an extragastric reservoir of H. pylori, owing to the presence of H. pylori DNA and particular antigens in [...] Read more.
Helicobacter pylori (H. pylori) is transmitted primarily through the oral–oral route and fecal–oral route. The oral cavity had therefore been hypothesized as an extragastric reservoir of H. pylori, owing to the presence of H. pylori DNA and particular antigens in distinct niches of the oral cavity. This bacterium in the oral cavity may contribute to the progression of periodontitis and is associated with a variety of oral diseases, gastric eradication failure, and reinfection. However, the conditions in the oral cavity do not appear to be ideal for H. pylori survival, and little is known about its biological function in the oral cavity. It is critical to clarify the survival strategies of H. pylori to better comprehend the role and function of this bacterium in the oral cavity. In this review, we attempt to analyze the evidence indicating the existence of living oral H. pylori, as well as potential survival strategies, including the formation of a favorable microenvironment, the interaction between H. pylori and oral microorganisms, and the transition to a non-growing state. Further research on oral H. pylori is necessary to develop improved therapies for the prevention and treatment of H. pylori infection. Full article
(This article belongs to the Special Issue New Advances on Helicobacter pylori Research)
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<p>The oral cavity is a potential source for <span class="html-italic">H. pylori</span> gastric reinfection. However, the oral cavity seems not to be an ideal habitat for <span class="html-italic">H. pylori</span>, owing to the unstable temperature, high O<sub>2</sub> tension, and varied bacterial composition [<a href="#B13-ijms-23-13646" class="html-bibr">13</a>,<a href="#B14-ijms-23-13646" class="html-bibr">14</a>]. Therefore, survival strategies of living <span class="html-italic">H. pylori</span> in the oral cavity remain to be investigated. The green arrows symbolize the common transmission pathway of <span class="html-italic">H. pylori</span>. PCR, polymerase chain reaction; RUT, rapid urease test.</p>
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<p>Potential survival strategies of <span class="html-italic">H. pylori</span> in the oral cavity. <span class="html-italic">H. pylori</span> can hide within dental plaque biofilm in caries cavities and periodontal pockets. Moreover, this organism has the ability to adhere to and invade host oral cells in these niches. Synergistic interaction with oral microorganisms and transition to a VBNC or dormant state may also help <span class="html-italic">H. pylori</span> adapt to adverse conditions in the oral cavity.</p>
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23 pages, 5974 KiB  
Article
EMT Molecular Signatures of Pancreatic Neuroendocrine Neoplasms
by Abhirami Venugopal, Agnes Michalczyk, Mustafa Khasraw and M. Leigh Ackland
Int. J. Mol. Sci. 2022, 23(21), 13645; https://doi.org/10.3390/ijms232113645 - 7 Nov 2022
Cited by 4 | Viewed by 1899
Abstract
Neuroendocrine neoplasms (NENs) are relatively rare neoplasms occurring predominantly in the gastrointestinal tract and pancreas. Their heterogeneity poses challenges for diagnosis and treatment. There is a paucity of markers for characterisation of NEN tumours. For routine diagnosis, immunohistochemistry of the NEN-specific markers CgA [...] Read more.
Neuroendocrine neoplasms (NENs) are relatively rare neoplasms occurring predominantly in the gastrointestinal tract and pancreas. Their heterogeneity poses challenges for diagnosis and treatment. There is a paucity of markers for characterisation of NEN tumours. For routine diagnosis, immunohistochemistry of the NEN-specific markers CgA and synaptophysin and the proliferation marker Ki-67 are used. These parameters, however, are qualitative and lack the capacity to fully define the tumour phenotype. Molecules of epithelial–mesenchymal transition (EMT) are potential candidates for improved tumour characterisation. Using qRT-PCR, we measured mRNA levels of 27 tumour markers, including 25 EMT-associated markers, in tumour tissue and matched non-tumour tissues for 13 patients with pancreatic NENs. Tissue from patients with three different grades of tumour had distinctly different mRNA profiles. Of the 25 EMT-associated markers analysed, 17 were higher in G3 tissue relative to matched non-tumour tissue, including CD14, CD24, CD31, CD44, CD45, CD56, CK6, CK7, CK13, CK20, NSE, CDX2, CgA, DAXX, PCNA, laminin and Ki-67. The differences in levels of seven EMT-associated markers, Ki-67, DAXX, CD24, CD44, vimentin, laminin and PDX1 plus CgA and NSE (neuroendocrine markers) enabled a distinct molecular signature for each tumour grade to be generated. EMT molecules differentially expressed in three tumour grades have potential for use in tumour stratification and prognostication and as therapeutic targets for treatment of neuroendocrine cancers, following validation with additional samples. Full article
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<p>mRNA marker profiles for each of grade 1 (<b>A</b>), grade 2 (<b>B</b>) and grade 3 (<b>C</b>) pancreatic neuroendocrine tumours. These profiles were developed using the average expression of all the samples from each grade. All marker expressions were normalised to the matched non-tumour tissues and using β-actin as the endogenous control. * represents a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05) in the marker expression in the tumour relative to that in non-tumour.</p>
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<p>mRNA marker profiles in the tumour tissue across grades. The markers have been grouped according to the tumour characteristic: NE origin (<b>A</b>), proliferation (<b>B</b>), stem cell (<b>C</b>), angiogenesis (<b>D</b>), multifunctional including EMT (<b>E</b>), cell adhesion (<b>F</b>), differentiation (<b>G</b>), tumour suppressor (<b>H</b>). The marker expressions in G2 and G3 have been normalised to the average of the G1 samples. “a” represents a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05) in marker expression in the tumour relative to that in the G1 tumour. “b” represents a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05) in marker expression in the G3 tumour relative to that in the G2 tumour.</p>
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<p>mRNA marker profiles in the tumour tissue across grades. The markers have been grouped according to the tumour characteristic: NE origin (<b>A</b>), proliferation (<b>B</b>), stem cell (<b>C</b>), angiogenesis (<b>D</b>), multifunctional including EMT (<b>E</b>), cell adhesion (<b>F</b>), differentiation (<b>G</b>), tumour suppressor (<b>H</b>). The marker expressions in G2 and G3 have been normalised to the average of the G1 samples. “a” represents a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05) in marker expression in the tumour relative to that in the G1 tumour. “b” represents a statistically significant difference (<span class="html-italic">p</span> &lt; 0.05) in marker expression in the G3 tumour relative to that in the G2 tumour.</p>
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<p>IHC images for selected markers (<b>A</b>) CgA, (<b>B</b>) synaptophysin, (<b>C</b>) CD56, (<b>D</b>) Ki-67, (<b>E</b>) DAXX, (<b>F</b>) CD44, (<b>G</b>) CD31, (<b>H</b>) vimentin, (<b>I</b>) laminin, (<b>J</b>) PDX1, (<b>K</b>) CK7, (<b>L</b>) p53 at 200× magnification. For each marker, the four images represent (i) non-tumour pancreatic tissue, (ii) G1, (iii) G2 and (iv) G3 tumour tissue. Scale: 20 μm.</p>
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<p>IHC images for selected markers (<b>A</b>) CgA, (<b>B</b>) synaptophysin, (<b>C</b>) CD56, (<b>D</b>) Ki-67, (<b>E</b>) DAXX, (<b>F</b>) CD44, (<b>G</b>) CD31, (<b>H</b>) vimentin, (<b>I</b>) laminin, (<b>J</b>) PDX1, (<b>K</b>) CK7, (<b>L</b>) p53 at 200× magnification. For each marker, the four images represent (i) non-tumour pancreatic tissue, (ii) G1, (iii) G2 and (iv) G3 tumour tissue. Scale: 20 μm.</p>
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<p>IHC images for selected markers (<b>A</b>) CgA, (<b>B</b>) synaptophysin, (<b>C</b>) CD56, (<b>D</b>) Ki-67, (<b>E</b>) DAXX, (<b>F</b>) CD44, (<b>G</b>) CD31, (<b>H</b>) vimentin, (<b>I</b>) laminin, (<b>J</b>) PDX1, (<b>K</b>) CK7, (<b>L</b>) p53 at 200× magnification. For each marker, the four images represent (i) non-tumour pancreatic tissue, (ii) G1, (iii) G2 and (iv) G3 tumour tissue. Scale: 20 μm.</p>
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<p>IHC images for selected markers (<b>A</b>) CgA, (<b>B</b>) synaptophysin, (<b>C</b>) CD56, (<b>D</b>) Ki-67, (<b>E</b>) DAXX, (<b>F</b>) CD44, (<b>G</b>) CD31, (<b>H</b>) vimentin, (<b>I</b>) laminin, (<b>J</b>) PDX1, (<b>K</b>) CK7, (<b>L</b>) p53 at 200× magnification. For each marker, the four images represent (i) non-tumour pancreatic tissue, (ii) G1, (iii) G2 and (iv) G3 tumour tissue. Scale: 20 μm.</p>
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<p>IHC images for selected markers (<b>A</b>) CgA, (<b>B</b>) synaptophysin, (<b>C</b>) CD56, (<b>D</b>) Ki-67, (<b>E</b>) DAXX, (<b>F</b>) CD44, (<b>G</b>) CD31, (<b>H</b>) vimentin, (<b>I</b>) laminin, (<b>J</b>) PDX1, (<b>K</b>) CK7, (<b>L</b>) p53 at 200× magnification. For each marker, the four images represent (i) non-tumour pancreatic tissue, (ii) G1, (iii) G2 and (iv) G3 tumour tissue. Scale: 20 μm.</p>
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<p>IHC images for selected markers (<b>A</b>) CgA, (<b>B</b>) synaptophysin, (<b>C</b>) CD56, (<b>D</b>) Ki-67, (<b>E</b>) DAXX, (<b>F</b>) CD44, (<b>G</b>) CD31, (<b>H</b>) vimentin, (<b>I</b>) laminin, (<b>J</b>) PDX1, (<b>K</b>) CK7, (<b>L</b>) p53 at 200× magnification. For each marker, the four images represent (i) non-tumour pancreatic tissue, (ii) G1, (iii) G2 and (iv) G3 tumour tissue. Scale: 20 μm.</p>
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<p>Molecular fingerprint depicting the pattern of the mean mRNA levels in tumour tissue relative to those in non-tumour for each marker across three grades for different categories of markers including neuroendocrine, proliferation, stem cell, multifunctional including EMT (EMT+), adhesion and differentiation.</p>
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22 pages, 2388 KiB  
Article
Altered Expression of Genes Associated with Major Neurotransmitter Systems in the Reward-Related Brain Regions of Mice with Positive Fighting Experience
by Dmitry A. Smagin, Anna G. Galyamina, Irina L. Kovalenko and Natalia N. Kudryavtseva
Int. J. Mol. Sci. 2022, 23(21), 13644; https://doi.org/10.3390/ijms232113644 - 7 Nov 2022
Cited by 7 | Viewed by 2347
Abstract
The main neurotransmitters in the brain—dopamine, γ-aminobutyric acid (GABA), glutamate, and opioids—are recognized to be the most important for the regulation of aggression and addiction. The aim of this work was to study differentially expressed genes (DEGs) in the main reward-related brain regions, [...] Read more.
The main neurotransmitters in the brain—dopamine, γ-aminobutyric acid (GABA), glutamate, and opioids—are recognized to be the most important for the regulation of aggression and addiction. The aim of this work was to study differentially expressed genes (DEGs) in the main reward-related brain regions, including the ventral tegmental area (VTA), dorsal striatum (STR), ventral striatum (nucleus accumbens, NAcc), prefrontal cortex (PFC), and midbrain raphe nuclei (MRNs), in male mice with 20-day positive fighting experience in daily agonistic interactions. Expression of opioidergic, catecholaminergic, glutamatergic, and GABAergic genes was analyzed to confirm or refute the influence of repeated positive fighting experience on the development of “addiction-like” signs shown in our previous studies. High-throughput RNA sequencing was performed to identify differentially expressed genes in the brain regions of chronically aggressive mice. In the aggressive mice, upregulation of opioidergic genes was shown (Oprk1 in VTA, Pdyn in NAcc, Penk in PFC, and Oprd1 in MRNs and PFC), as was downregulation of genes Opcml and Oprk1 in STR and Pomc in VTA and NAcc. Upregulation of catecholaminergic genes in VTA (Ddc and Slc6a2) and in NAcc (Th and Drd2) and downregulation of some differentially expressed genes in MRNs (Th, Ddc, Dbh, Drd2, Slc18a2, and Sncg) and in VTA (Adra2c, Sncg, and Sncb) were also documented. The expression of GABAergic and glutamatergic genes that participate in drug addiction changed in all brain regions. According to literature data, the proteins encoded by genes Drd2, Oprk1, Oprd1, Pdyn, Penk, and Pomc are directly involved in drug addiction in humans. Thus, our results confirm our earlier claim about the formation of addiction-like signs following repeated positive fighting experience in mice, as shown previously in our biobehavioral studies. Full article
(This article belongs to the Section Molecular Neurobiology)
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<p>DEGs in the VTA of highly aggressive mice. (<b>A</b>) FPKM of the DEGs in the VTA (<a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S1</a>). White bars—controls; colored bars—winners: brown—opioidergic genes; pink—CAergic genes; lilac—GABAergic genes; violet—glutamatergic genes. * <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. (<b>B</b>) AHC based on 13 reference DEGs’ expression profiles (additional information: <a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S2</a>). Similarity: Pearson’s correlation coefficient. Agglomeration method: unweighted pair-group average. The main clusters are highlighted with a blue rounded rectangle.</p>
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<p>DEGs in the NAcc of highly aggressive mice. (<b>A</b>) FPKM of the DEGs in the NAcc (<a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S1</a>). White bars: controls; colored bars—winners: brown—opioidergic genes; pink - CAergic genes; lilac—GABAergic genes; violet—glutamatergic genes. * <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. (<b>B</b>) AHC based on expression profiles of eight reference DEGs (additional information: <a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S2</a>). Similarity: Pearson’s correlation coefficient. Agglomeration method: Unweighted pair-group average. The main clusters are highlighted with a blue rounded rectangle.</p>
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<p>DEGs in the STR of highly aggressive mice. (<b>A</b>) FPKM of opioidergic, GABAergic, and glutamatergic DEGs in the STR. White bars—controls; colored bars—winners: brown—opioidergic genes; lilac—GABAergic genes; violet—glutamatergic genes. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01 (<a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S1</a>). (<b>B</b>) AHC based on expression profiles of eight reference DEGs (<a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S2</a>). Similarity: Pearson’s correlation coefficient. Agglomeration method: Unweighted pair-group average. The main clusters are highlighted with a blue rounded rectangle.</p>
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<p>DEGs in the PFC of highly aggressive mice. (<b>A</b>) FPKM of opioidergic and glutamatergic DEGs in the PFC of mice. White bars—controls; colored bars—winners: brown—opioidergic genes; violet—glutamatergic genes (<a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S1</a>). * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) AHC based on five reference DEGs’ expression profiles (<a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S2</a>). Similarity: Pearson’s correlation coefficient. Agglomeration method: Unweighted pair-group average. The main clusters are highlighted with a blue rounded rectangle.</p>
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<p>DEGs in the MRNs of highly aggressive mice. (<b>A</b>) FPKM of opioidergic, CAergic, GABAergic and glutamatergic DEGs in the MRNs (<a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S1</a>). White bars—controls; colored bars—winners: brown—opioidergic genes; pink—CAergic genes; lilac—GABAergic genes; violet—glutamatergic genes. * <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. (<b>B</b>) AHC based on expression profiles of 18 reference DEGs (<a href="#app1-ijms-23-13644" class="html-app">Supplementary Table S2</a>). Similarity: Pearson’s correlation coefficient. Agglomeration method: Unweighted pair-group average. The main clusters are highlighted with a blue rounded rectangle.</p>
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<p>PCA plots based on covariation of genes on the basis of expression profiles of 15 CAergic and opioidergic DEGs across 30 samples, which comprise RNA-Seq FPKM data for five brain regions. (<b>A</b>) Active observations. W1, W2, and W3: winners; C1, C2, and C3: controls; VTA: ventral tegmental area, NAcc: nucleus accumbens, MRN: midbrain raphe nuclei, STR: dorsal striatum, and PFC: prefrontal cortex. Ovals denote brain regions. (<b>B</b>) Active variables. The graph illustrates distinct clustering of DEGs.</p>
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<p>FPKM values of five CAergic- and opioid-specific DEGs across 30 samples on the basis of the included RNA-Seq FPKM data for five brain regions. C1, C2, and C3: controls; W1, W2, and W3: winners; VTA: ventral tegmental area, NAcc: nucleus accumbens, MRN: midbrain raphe nuclei, STR: dorsal striatum, and PFC: prefrontal cortex.</p>
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<p>The experimental cage.</p>
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19 pages, 1937 KiB  
Review
Interplay between Autophagy and Herpes Simplex Virus Type 1: ICP34.5, One of the Main Actors
by Inés Ripa, Sabina Andreu, José Antonio López-Guerrero and Raquel Bello-Morales
Int. J. Mol. Sci. 2022, 23(21), 13643; https://doi.org/10.3390/ijms232113643 - 7 Nov 2022
Cited by 5 | Viewed by 3330
Abstract
Herpes simplex virus type 1 (HSV-1) is a neurotropic virus that occasionally may spread to the central nervous system (CNS), being the most common cause of sporadic encephalitis. One of the main neurovirulence factors of HSV-1 is the protein ICP34.5, which although it [...] Read more.
Herpes simplex virus type 1 (HSV-1) is a neurotropic virus that occasionally may spread to the central nervous system (CNS), being the most common cause of sporadic encephalitis. One of the main neurovirulence factors of HSV-1 is the protein ICP34.5, which although it initially seems to be relevant only in neuronal infections, it can also promote viral replication in non-neuronal cells. New ICP34.5 functions have been discovered during recent years, and some of them have been questioned. This review describes the mechanisms of ICP34.5 to control cellular antiviral responses and debates its most controversial functions. One of the most discussed roles of ICP34.5 is autophagy inhibition. Although autophagy is considered a defense mechanism against viral infections, current evidence suggests that this antiviral function is only one side of the coin. Different types of autophagic pathways interact with HSV-1 impairing or enhancing the infection, and both the virus and the host cell modulate these pathways to tip the scales in its favor. In this review, we summarize the recent progress on the interplay between autophagy and HSV-1, focusing on the intricate role of ICP34.5 in the modulation of this pathway to fight the battle against cellular defenses. Full article
(This article belongs to the Special Issue Alphaherpesviruses)
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<p>Degradation of HSV-1 by selective autophagy. The ULK complex initiates the formation of the phagophore by phosphorylating components of the PI3KC3 complex I and mediating the trafficking of ATG9-containing vesicles. The LC3-PE conjugation system participates in the elongation and closure of the double membrane, resulting in the formation of the autophagosome. The selective autophagy receptors (SARs) p62/SQSTM1 [<a href="#B21-ijms-23-13643" class="html-bibr">21</a>] and optineurin (OPTN) [<a href="#B22-ijms-23-13643" class="html-bibr">22</a>] and the autophagy receptor-like factors Fanconi anemia group C protein (FANCC) [<a href="#B23-ijms-23-13643" class="html-bibr">23</a>] and SMAD ubiquitin regulatory factor 1 (SMURF-1) [<a href="#B21-ijms-23-13643" class="html-bibr">21</a>] can interact with HSV-1 and mediate the recruitment of HSV-1 virions and/or viral cytoplasmic components into the autophagosomes. Once cargo has been engulfed, the external membrane of the autophagosome fuses with a lysosome for degradation of viral components.</p>
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<p>ICP34.5 of HSV-1 strain 17. HSV-1 ICP34.5 is a protein with 248 amino acids that can be divided into three regions: the amino and the carboxyl terminal domains, and a linked tandem of five ATP repeats (161–175 aa) (orange box). The N-terminal region of ICP34.5 contains a nucleolar localization and nuclear export signals, and the C-terminal domain includes a nuclear localization signal (red boxes). Three binding domains (green boxes) have been characterized: the Beclin-1-binding domain (BBD) in the N-terminus, and the PP1α- and elF2α-binding domains in the C-terminus.</p>
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<p>Functions of ICP34.5 in HSV-1 infected cells. Functions of ICP34.5 can be classified according to the cellular location of the protein, which shuttles between the cytoplasm and the nucleus. The amino and the carboxyl domains of ICP34.5 play different roles in infected cells. The C-terminus prevents the translational arrest by the binding of PP1α and the subsequent dephosphorylation of elF2α. The N-terminus is involved in the suppression of Beclin-1-autophagy, the degradation of the nuclear lamina to facilitate nucleocapsid egress from the nucleus, and the blockade of IFN response by the inhibition of the dsDNA-sensing pathway. The full-length protein plays a role in virus replication in non-dividing cells, in the prevention of DCs maturation, and in the suppression of the IFN response by blocking the RNA-sensing pathway.</p>
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<p>Autophagy modulation by ICP34.5 in HSV-1 infection. Early in HSV-1 infection, detection of the virus by host cell promotes the stimulation of macroautophagy. This pathway may act as a cellular defense mechanism involved in virophagy and the processing of viral antigen for MHC presentation. Autophagic flux can be induced in manner that is dependent on viral gene expression by the PKR/elF2α pathway. Autophagy may be enhanced through the recognition of PAMPs by the surface receptor TLR2. Activated TLR2 recruits the adaptor MyD88, which causes the dissociation of Beclin-1 from the BCL-2 inhibitory complex, resulting in the induction of autophagy. Finally, HSV-1 dsDNA may be recognized by the cytosolic dsDNA-sensing cGAS, which produces cGAMP to activate STING and TBK1. Activation of TBK1 promotes autophagy stimulation.</p>
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<p>HSV-1 mechanisms for autophagy inhibition. HSV-1 proteins Us3 and ICP34.5 can inhibit macroautophagy by binding to Beclin-1, which is required for autophagosome formation. Us3 can also suppress the pathway by the activation of the negative regulator of autophagy mTORC1 or by the inactivation of the ULK1 complex, which is involved in phagophore initiation. The HSV-1 protein Us11 can prevent the induction of autophagy mediated by the PKR/elF2α pathway. Besides, Us11 inhibits virus-induced autophagy by the disassembly of the TRIM23-Hsp90-TBK1 complex. Finally, the HSV-1 protein ICP0 promotes the degradation in the proteasome of the selective autophagy receptors p62/SQSTM1 and OPTN, which are implied in the recruitment of HSV-1 in autophagosomal membranes. The TRIM23-TBK1 complex is involved in the phosphorylation and activation of these selective receptors. However, the inhibitory role of Us11 on the TRIM23-TBK1 complex has not been directly associated with a possible SARs inactivation.</p>
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7 pages, 889 KiB  
Case Report
Changes in Brain Volumes Are Relevant during Natalizumab-Associated Progressive Multifocal Leukoencephalopathy: Lessons from a Case Report
by Roberto De Masi, Stefania Orlando, Silvia Armenise, Pantaleo Spagnolo, Ruggero Capra and Maria Carmela Costa
Int. J. Mol. Sci. 2022, 23(21), 13642; https://doi.org/10.3390/ijms232113642 - 7 Nov 2022
Cited by 1 | Viewed by 1419
Abstract
This is a case report concerning a Natalizumab-associated Progressive Multifocal Leukoencephalopathy (PML) with cerebellar localization and wakefulness disturbances. Awakening and clinical improvement dramatically occurred as soon as the immune reconstitution inflammatory syndrome (IRIS) took place, being it mild in nature and colocalizing with [...] Read more.
This is a case report concerning a Natalizumab-associated Progressive Multifocal Leukoencephalopathy (PML) with cerebellar localization and wakefulness disturbances. Awakening and clinical improvement dramatically occurred as soon as the immune reconstitution inflammatory syndrome (IRIS) took place, being it mild in nature and colocalizing with the PML lesion. In these ideal experimental conditions, we applied brain magnetic resonance imaging post-analysis in order to know changes in brain volumes underlying the pathological process over the infection period. White matter volume increased with a decrease in grey matter during IRIS. Conversely, we found a constant increase in cerebrospinal fluid volume throughout the duration of PML, suggesting a widespread abiotrophic effect, far from the lesion. Furthermore, brain parenchymal fraction significantly decreased as expected while the total brain volume remained stable at all times. Neurodegeneration is the main contributor to the steady disability in Natalizumab-associated PML. This process is thought to be widespread and inflammatory in nature as well as sustained by IRIS and humoral factors derived from the PML lesion. Full article
(This article belongs to the Special Issue State-of-the-Art Molecular Neurobiology in Italy)
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<p>Timeline of changes in brain and PML lesion volumes. Volume (in ml) of total brain (TBV), cerebrospinal fluid (CSF), grey (GM) and white matter (WM), and PML lesion are shown in (<b>A</b>); fraction of grey matter (GMF), white matter (WMF), and brain parenchymal (BPF) are shown in (<b>B</b>). In both graphs, volumes and fractions curves regarding the entire observation period are represented. Specifically, T0: baseline, T1–T5: PML, T6*–T8*: IRIS, T9: recovery from IRIS. The numerical value of each point is expressed with the same color code as the corresponding curve. PML: progressive multifocal leukoencephalopathy; IRIS: immune reconstitution inflammatory syndrome.</p>
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<p>Timeline of evolution of PML, IRIS, and EDSS. Axial brain MRI on FLAIR and T1-weighted post-contrast sequence showing the evolution of PML (top) and IRIS (bottom), respectively. Specifically, T0 shows the baseline MRI, T1 the first MRI suggestive of PML, T2–T5 the progression of PML, T6*–T8* IRIS, and T9 the recovery from IRIS. Note the cerebellar colocalization of PML and IRIS as well as the progressive enlargement of PML lesion from T1 to T5, expressing, the latter, an involvement similar to that of T9, when the infection is over. EDSS is also represented, as well as the time-period characterized by the wakefulness disturbances. Note the progressive accumulation of PML lesion volume and the concomitant worsening of EDSS, from T1 to T5. Wakefulness disturbances manifest in T3 and regress in T6, as soon as IRIS occurs. PML: progressive multifocal leukoencephalopathy; IRIS: immune reconstitution inflammatory syndrome; EDSS: expanded disability status scale.</p>
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14 pages, 2495 KiB  
Article
Non-Muscle MLCK Contributes to Endothelial Cell Hyper-Proliferation through the ERK Pathway as a Mechanism for Vascular Remodeling in Pulmonary Hypertension
by Mariam Anis, Janae Gonzales, Rachel Halstrom, Noman Baig, Cat Humpal, Regaina Demeritte, Yulia Epshtein, Jeffrey R. Jacobson and Dustin R. Fraidenburg
Int. J. Mol. Sci. 2022, 23(21), 13641; https://doi.org/10.3390/ijms232113641 - 7 Nov 2022
Cited by 4 | Viewed by 2129
Abstract
Pulmonary arterial hypertension (PAH) is characterized by endothelial dysfunction, uncontrolled proliferation and migration of pulmonary arterial endothelial cells leading to increased pulmonary vascular resistance resulting in great morbidity and poor survival. Bone morphogenetic protein receptor II (BMPR2) plays an important role in the [...] Read more.
Pulmonary arterial hypertension (PAH) is characterized by endothelial dysfunction, uncontrolled proliferation and migration of pulmonary arterial endothelial cells leading to increased pulmonary vascular resistance resulting in great morbidity and poor survival. Bone morphogenetic protein receptor II (BMPR2) plays an important role in the pathogenesis of PAH as the most common genetic mutation. Non-muscle myosin light chain kinase (nmMLCK) is an essential component of the cellular cytoskeleton and recent studies have shown that increased nmMLCK activity regulates biological processes in various pulmonary diseases such as asthma and acute lung injury. In this study, we aimed to discover the role of nmMLCK in the proliferation and migration of pulmonary arterial endothelial cells (HPAECs) in the pathogenesis of PAH. We used two cellular models relevant to the pathobiology of PAH including BMPR2 silenced and vascular endothelial growth factor (VEGF) stimulated HPAECs. Both models demonstrated an increase in nmMLCK activity along with a robust increase in cellular proliferation, inflammation, and cellular migration. The upregulated nmMLCK activity was also associated with increased ERK expression pointing towards a potential integral cytoplasmic interaction. Mechanistically, we confirmed that when nmMLCK is inhibited by MLCK selective inhibitor (ML-7), proliferation and migration are attenuated. In conclusion, our results demonstrate that nmMLCK upregulation in association with increased ERK expression may contribute to the pathogenesis of PAHby stimulating cellular proliferation and migration. Full article
(This article belongs to the Special Issue Arteriogenesis, Angiogenesis and Vascular Remodeling)
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<p>BMPR2 silencing in human pulmonary artery endothelial cells (HPAECs) is associated with ERK/MAPK activation. Representative Western blot images denoting BMPR2 and p-ERK (<b>A</b>) as well as p-MLC (<b>B</b>) protein expression between HPAECs transfected with BMPR2 siRNA or control siRNA for 48 h. Bar graphs summarizing relative BMPR2 (<b>C</b>), phosphorylated ERK (<b>D</b>), and phosphorylated MLC (<b>E</b>) protein expression at 48 h in BMPR2 silenced HPAECs compared to control (<span class="html-italic">n</span> = 3). * indicates <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> ≤ 0.01; BMPR2, Bone morphogenetic protein receptor type II; p-ERK, phosphorylated extracellular signal-regulated kinase; p-MLC, phosphorylated myosin light-chain; siRNA, small interfering (silencing) RNA.</p>
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<p>BMPR2 silencing increases HPAEC proliferation and cytokine release which is attenuated by inhibition of myosin light chain kinase (MLCK). Representative Western blot (<b>A</b>) and accompanying bar graph (<b>B</b>) depicting PCNA protein expression at 48 h between HPAECs transfected with BMPR2 or control siRNA (<span class="html-italic">n</span> = 3). (<b>C</b>) Bar graph representing changes in proliferation and viability as measured by WST-1 assay in HPAECs transfected with BMPR2 siRNA, control siRNA, and BMPR2 siRNA with ML-7 (10 μM) pre-treatment for 48 h (<span class="html-italic">n</span> = 9). Bar graph measuring IL-6 (<b>D</b>) and IL-8 (<b>E</b>) concentrations in the media of HPAECs transfected with BMPR2 siRNA, control siRNA, and BMPR2 siRNA with ML-7 (10 μM) pre-treatment for 48 h (<span class="html-italic">n</span> = 3). * indicates <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> ≤ 0.01; ***, <span class="html-italic">p</span> ≤ 0.001; PCNA, proliferating cell nuclear antigen; BMPR2, Bone morphogenetic protein receptor type II; siRNA, small interfering (silencing) RNA; ML-7, myosin light chain kinase specific inhibitor; IL-6, Interleukin-6; IL-8, Interleukin-8.</p>
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<p>BMPR2 silencing increases HPAEC migration which is attenuated by MLCK inhibition. (<b>A</b>) Plot demonstrating the transendothelial resistance by ECIS-based wounding over time in HPAECs transfected with BMPR2 siRNA, control siRNA, BMPR2 siRNA with ML-7 (10 μM), and control siRNA with ML-7 (10 μM) (<span class="html-italic">n</span> = 2). (<b>B</b>) Bar graph denoting the area under the curve measurements at 12 h for the ECIS-based wounding experiments (<span class="html-italic">n</span> = 2). (<b>C</b>) Representative images of wound healing assay depicting scratches created in confluent cultures of HPAECs transfected with BMPR2 siRNA, control siRNA, and BMPR2 siRNA with ML-7 (10 μM) at 0 h and 24 h time points; scale bar = 100 μm. (<b>D</b>) Bar graph summarizing percent gap closure at 24 h for the wound healing assay experiments (<span class="html-italic">n</span> = 3). * indicates <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> ≤ 0.01; BMPR2, Bone morphogenetic protein receptor type II; siRNA, small interfering (silencing) RNA; ML-7, myosin light chain kinase specific inhibitor.</p>
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<p>VEGF stimulation in HPAECs leads to upregulation of ERK/MAPK, which is abrogated by MLCK inhibition. (<b>A</b>) Representative Western blot images denoting p-ERK and p-MLC protein expression in HPAECs treated with VEGF (100 ng/mL), control (PBS vehicle), and VEGF with ML-7 (10 μM) pre-treatment for 72 h. Bar graphs summarizing relative phosphorylated ERK (<b>B</b>) and phosphorylated MLC (<b>C</b>) protein expression at 72 h in HPAECs treated with VEGF, control, and VEGF with ML-7 (<span class="html-italic">n</span> = at least 4 for p-ERK, <span class="html-italic">n</span> = at least 7 for p-MLC). ** indicates <span class="html-italic">p</span> ≤ 0.01; ***, <span class="html-italic">p</span> ≤ 0.001; VEGF, vascular endothelial growth factor; p-ERK, phosphorylated extracellular signal-regulated kinase; p-MLC, phosphorylated myosin light-chain; ML-7, myosin light chain kinase specific inhibitor.</p>
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<p>VEGF treatment increases HPAEC proliferation and cytokine release which is attenuated by inhibition of myosin light chain kinase (MLCK). Representative Western blot (<b>A</b>) and accompanying bar graph (<b>B</b>) depicting PCNA protein expression at 72 h between HPAECs treated with VEGF (100 ng/mL), control (PBS vehicle), and VEGF with ML-7 (10 μM) pre-treatment (<span class="html-italic">n</span> = at least 2). β-actin loading control is identical to <a href="#ijms-23-13641-f004" class="html-fig">Figure 4</a>A as the representative blot was derived from the same experiment. (<b>C</b>) Bar graph denoting changes in proliferation and viability as measured by WST-1 assay in HPAECs treated with VEGF, control, and VEGF with ML-7 for 72 h (<span class="html-italic">n</span> = 4). ** indicated <span class="html-italic">p</span> ≤ 0.01; *** indicates <span class="html-italic">p</span> ≤ 0.001; PCNA, proliferating cell nuclear antigen; VEGF, vascular endothelial growth factor; ML-7, myosin light chain kinase specific inhibitor; IL-6, Interleukin-6; IL-8, Interleukin-8.</p>
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<p>VEGF treatment increases HPAEC migration which is attenuated by MLCK inhibition. (<b>A</b>) Plot demonstrating the transendothelial resistance by ECIS-based wounding over time in HPAECs treated with VEGF (100 ng/mL), control (PBS vehicle), VEGF with ML-7 (10 μM) pre-treatment, and control with ML-7 (<span class="html-italic">n</span> = at least 3). (<b>B</b>) Bar graph denoting the area under the curve measurements at 12 h for the ECIS-based wounding experiments (<span class="html-italic">n</span> = at least 3). (<b>C</b>) Representative images of wound healing assays depicting scratches created in confluent cultures of HPAECs treated with VEGF (100 ng/mL), control (PBS vehicle), VEGF with ML-7 (10 μM) pre-treatment at 0 h and 24 h time points; scale bar = 100 μm. (<b>D</b>) Bar graph summarizing percent gap closure at 24 h for the wound healing assay experiments (<span class="html-italic">n</span> = 2). * indicates <span class="html-italic">p</span> ≤ 0.05; **, <span class="html-italic">p</span> ≤ 0.01; ***, <span class="html-italic">p</span> ≤ 0.001 VEGF, vascular endothelial growth factor; ML-7, myosin light chain kinase specific inhibitor.</p>
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<p>Schematic representation of our findings demonstrating that nmMLCK activation due to BMPR2 downregulation or VEGF stimulation is associated with increased ERK phosphorylation, potentially directly or indirectly, contributing to the pathogenesis of PAH by stimulating cellular proliferation and migration.</p>
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17 pages, 2575 KiB  
Article
Exploring the RNA Editing Events and Their Potential Regulatory Roles in Tea Plant (Camellia sinensis L.)
by Mengyuan Zhang, Zhuo Li, Zijian Wang, Yao Xiao, Lu Bao, Min Wang, Chuanjing An and Yuefang Gao
Int. J. Mol. Sci. 2022, 23(21), 13640; https://doi.org/10.3390/ijms232113640 - 7 Nov 2022
Cited by 3 | Viewed by 1712
Abstract
RNA editing is a post-transcriptional modification process that alters the RNA sequence relative to the genomic blueprint. In plant organelles (namely, mitochondria and chloroplasts), the most common type is C-to-U, and the absence of C-to-U RNA editing results in abnormal plant development, such [...] Read more.
RNA editing is a post-transcriptional modification process that alters the RNA sequence relative to the genomic blueprint. In plant organelles (namely, mitochondria and chloroplasts), the most common type is C-to-U, and the absence of C-to-U RNA editing results in abnormal plant development, such as etiolation and albino leaves, aborted embryonic development and retarded seedling growth. Here, through PREP, RES-Scanner, PCR and RT-PCR analyses, 38 and 139 RNA editing sites were identified from the chloroplast and mitochondrial genomes of Camellia sinensis, respectively. Analysis of the base preference around the RNA editing sites showed that in the −1 position of the edited C had more frequent occurrences of T whereas rare occurrences of G. Three conserved motifs were identified at 25 bases upstream of the RNA editing site. Structural analyses indicated that the RNA secondary structure of 32 genes, protein secondary structure of 37 genes and the three-dimensional structure of 5 proteins were altered due to RNA editing. The editing level analysis of matK and ndhD in six tea cultivars indicated that matK-701 might be involved in the color change of tea leaves. Furthermore, 218 PLS-CsPPR proteins were predicted to interact with the identified RNA editing sites. In conclusion, this study provides comprehensive insight into RNA editing events, which will facilitate further study of the RNA editing phenomenon of the tea plant. Full article
(This article belongs to the Collection Genetics and Molecular Breeding in Plants)
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<p>RNA editing sites predicted by PREP suite in tea chloroplast and mitochondria. (<b>A</b>) Amino acid residue substitutions resulting from RNA editing; the letters are the abbreviations for amino acid residues, and the block size represents the number of RNA editing sites. (<b>B</b>) Position of RNA editing sites in codons. The outer pie charts represent chloroplasts, and the inner pie charts represent mitochondria.</p>
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<p>Distribution of RNA editing sites on the tea chloroplast (<b>A</b>) and mitochondria (<b>B</b>) genome. PREP suite and RES-Scanner represent the results predicted by PREP-suite and RES-Scanner, respectively. RT-PCR represents these RNA editing sites that were validated by RT-PCR.</p>
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<p>Features of sequences around RNA editing sites. (<b>A</b>) The base preference around edited C. A, C, G and T are abbreviation for nucleotide. The numbers represent the flanking base positions of the edited Cs. (<b>B</b>) Conserved motifs around RNA editing sites. The horizontal axis is the base position in the corresponding motif. The vertical axis is the fraction of bits per base.</p>
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<p>The 3-D structure of proteins were changed by RNA editing events. (<b>A</b>) Before cox2 is edited. (<b>B</b>) After cox2 is edited. Red circle indicates monomer introduced after RNA editing. (<b>C</b>) Before cob is edited. (<b>D</b>) After cob is edited. Red circles show monomers introduced after RNA editing. (<b>E</b>) Before ccmB is edited. (<b>F</b>) After ccmB is edited. (<b>G</b>) Before nad5 is edited. (<b>H</b>) After nad5 is edited.</p>
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<p>Editing levels of 4 RNA editing events in 6 varieties (LJ43 and SC1 with normal green leaves, HJYA and ZH3 with etiolation leaves and HB1 and BY1 with albino leaves) of tea plants. HJYA represents <span class="html-italic">C. sinensis cv. ‘Huangjinya’</span>; ZH3 represents <span class="html-italic">C. sinensis cv. ‘Zhonghuang 3’</span>; SC1 represents <span class="html-italic">C. sinensis cv. ‘Shaancha 1’</span>; LJ43 represents <span class="html-italic">C. sinensis cv. ‘Longjing 43’</span>; HB1 represents <span class="html-italic">C. sinensis cv. ‘Huabai 1’</span>; BY1 represents <span class="html-italic">C. sinensis cv. ‘Baiye 1’</span>. The <span class="html-italic">matk-445</span> represents 445 position of <span class="html-italic">matK</span>. The <span class="html-italic">matk-701</span> represents 701 position of <span class="html-italic">matK</span>. The <span class="html-italic">ndhD-674</span> represents 674 position of <span class="html-italic">ndhD</span>. The <span class="html-italic">ndhD-1310</span> represents 1310 position of <span class="html-italic">ndhD</span>. Red boxes indicate the RNA editing sites in the gDNA and cDNA.</p>
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17 pages, 2916 KiB  
Article
Effects of Two Bacillus Velezensis Microbial Inoculants on the Growth and Rhizosphere Soil Environment of Prunus davidiana
by Huimin Shi, Lanxiang Lu, Jianren Ye and Lina Shi
Int. J. Mol. Sci. 2022, 23(21), 13639; https://doi.org/10.3390/ijms232113639 - 7 Nov 2022
Cited by 12 | Viewed by 2385
Abstract
Microbial inoculants, as harmless, efficient, and environmentally friendly plant growth promoters and soil conditioners, are attracting increasing attention. In this study, the effects of Bacillus velezensis YH-18 and B. velezensis YH-20 on Prunus davidiana growth and rhizosphere soil bacterial community in continuously cropped [...] Read more.
Microbial inoculants, as harmless, efficient, and environmentally friendly plant growth promoters and soil conditioners, are attracting increasing attention. In this study, the effects of Bacillus velezensis YH-18 and B. velezensis YH-20 on Prunus davidiana growth and rhizosphere soil bacterial community in continuously cropped soil were investigated by inoculation tests. The results showed that in a pot seedling experiment, inoculation with YH-18 and YH-20 resulted in a certain degree of increase in diameter growth, plant height, and leaf area at different time periods of 180 days compared with the control. Moreover, after 30 and 90 days of inoculation, the available nutrients in the soil were effectively improved, which protected the continuously cropped soil from acidification. In addition, high-throughput sequencing showed that inoculation with microbial inoculants effectively slowed the decrease in soil microbial richness and diversity over a one-month period. At the phylum level, Proteobacteria and Bacteroidetes were significantly enriched on the 30th day. At the genus level, Sphingomonas and Pseudomonas were significantly enriched at 15 and 30 days, respectively. These bacterial phyla and genera can effectively improve the soil nutrient utilization rate, antagonize plant pathogenic bacteria, and benefit the growth of plants. Furthermore, inoculation with YH-18 and inoculation with YH-20 resulted in similar changes in the rhizosphere microbiome. This study provides a basis for the short-term effect of microbial inoculants on the P. davidiana rhizosphere microbiome and has application value for promoting the cultivation and production of high-quality fruit trees. Full article
(This article belongs to the Section Molecular Plant Sciences)
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<p>Effects of inoculation with YH-18 and YH-20 on (<b>A</b>) ground diameter growth, (<b>B</b>) height growth, (<b>C</b>) chlorophyll content and (<b>D</b>) leaf area of <span class="html-italic">P. davidiana</span>. Different letters indicate significant differences between different treatments in a group within the same period at a confidence level of <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of YH-18 and YH-20 microbial inoculants on (<b>A</b>) OM, (<b>B</b>) AN, (<b>C</b>) AP, (<b>D</b>) AK, and (<b>E</b>) pH in soil.</p>
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<p>The 20 most abundant bacterial groups at the phylum level.</p>
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<p>The 30 most abundant bacterial groups at the genus level.</p>
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<p>Venn diagram of different combinations: (<b>A</b>) Venn diagram of different treatments 15 days after inoculation. (<b>B</b>) Venn diagram of different treatments 30 days after inoculation.</p>
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<p>Principal coordinate analysis of 16S rRNA genes of total bacteria based on the weighted similarity index at 97% identity (operational taxonomic unit level). PC1 and PC2 explained 25.9% and 12.3%, respectively, of the variance.</p>
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<p>Redundancy analysis of the soil bacterial community composition at the genus level and soil environmental parameters. Soil environmental parameters are represented by red lines and bacterial genera are represented by blue lines (1: <span class="html-italic">Sphingomonas</span>, 2: <span class="html-italic">Pseudomonas</span>, 3: <span class="html-italic">Flavobacterium</span>, 4: <span class="html-italic">RB41</span>, 5: <span class="html-italic">Dongia</span>, 6: <span class="html-italic">Gemmatimonas</span>, 7: <span class="html-italic">Haliangium</span>, 8: <span class="html-italic">MND1</span>, 9: <span class="html-italic">Acidibacter</span>, 10: <span class="html-italic">Arenimonas</span>, 11: <span class="html-italic">Bryobacter</span>, 12: <span class="html-italic">Flavisolibacter</span>, 13: <span class="html-italic">Ellin6067</span>; 14: <span class="html-italic">Steroidobacter</span>, 15: <span class="html-italic">Ferruginibacter</span>).</p>
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36 pages, 1047 KiB  
Review
Vulnerable Atherosclerotic Plaque: Is There a Molecular Signature?
by Roxana Mihaela Chiorescu, Mihaela Mocan, Andreea Ioana Inceu, Andreea Paula Buda, Dan Blendea and Sonia Irina Vlaicu
Int. J. Mol. Sci. 2022, 23(21), 13638; https://doi.org/10.3390/ijms232113638 - 7 Nov 2022
Cited by 17 | Viewed by 4619
Abstract
Atherosclerosis and its clinical manifestations, coronary and cerebral artery diseases, are the most common cause of death worldwide. The main pathophysiological mechanism for these complications is the rupture of vulnerable atherosclerotic plaques and subsequent thrombosis. Pathological studies of the vulnerable lesions showed that [...] Read more.
Atherosclerosis and its clinical manifestations, coronary and cerebral artery diseases, are the most common cause of death worldwide. The main pathophysiological mechanism for these complications is the rupture of vulnerable atherosclerotic plaques and subsequent thrombosis. Pathological studies of the vulnerable lesions showed that more frequently, plaques rich in lipids and with a high level of inflammation, responsible for mild or moderate stenosis, are more prone to rupture, leading to acute events. Identifying the vulnerable plaques helps to stratify patients at risk of developing acute vascular events. Traditional imaging methods based on plaque appearance and size are not reliable in prediction the risk of rupture. Intravascular imaging is a novel technique able to identify vulnerable lesions, but it is invasive and an operator-dependent technique. This review aims to summarize the current data from literature regarding the main biomarkers involved in the attempt to diagnose vulnerable atherosclerotic lesions. These biomarkers could be the base for risk stratification and development of the new therapeutic drugs in the treatment of patients with vulnerable atherosclerotic plaques. Full article
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<p>Circulating biomarkers of the vulnerable plaque and the main mechanisms involved in atherosclerotic plaque development. CRP-C, reactive protein; IFN-γ, Interferon-γ; IL-1, Interleukin-1; IL-18, Interleukin-18; IL-6, Interleukin-6; LPS, lipopolysaccharide; LYS-C, lysozyme c; MMP-9, matrix metalloproteinase-9; NOS, nitric oxide species; PAPP-A, pregnancy associated plasma protein A; PLA-2, Phospholipase A2; TMAO, Trimethylamine-N-oxide; TNF-α, Tumor necrosis factor alpha.</p>
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<p>Potential role of miRNA as biomarkers of vulnerable plaque in coronary artery disease.</p>
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<p>Inflammatory proteins involved in atherosclerotic plaque instability detected in tissue samples. CTS-D, Cathepsin-D; LYS-C, Lysozyme-C; ox-LDL, oxidized-LDL; PLA-2, Phospholipase-A2.</p>
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24 pages, 2032 KiB  
Review
Extracellular Vesicle (EVs) Associated Non-Coding RNAs in Lung Cancer and Therapeutics
by Anjugam Paramanantham, Rahmat Asfiya, Siddharth Das, Grace McCully and Akhil Srivastava
Int. J. Mol. Sci. 2022, 23(21), 13637; https://doi.org/10.3390/ijms232113637 - 7 Nov 2022
Cited by 16 | Viewed by 3134
Abstract
Lung cancer is one of the most lethal forms of cancer, with a very high mortality rate. The precise pathophysiology of lung cancer is not well understood, and pertinent information regarding the initiation and progression of lung cancer is currently a crucial area [...] Read more.
Lung cancer is one of the most lethal forms of cancer, with a very high mortality rate. The precise pathophysiology of lung cancer is not well understood, and pertinent information regarding the initiation and progression of lung cancer is currently a crucial area of scientific investigation. Enhanced knowledge about the disease will lead to the development of potent therapeutic interventions. Extracellular vesicles (EVs) are membrane-bound heterogeneous populations of cellular entities that are abundantly produced by all cells in the human body, including the tumor cells. A defined class of EVs called small Extracellular Vesicles (sEVs or exosomes) carries key biomolecules such as RNA, DNA, Proteins and Lipids. Exosomes, therefore, mediate physiological activities and intracellular communication between various cells, including constituent cells of the tumor microenvironment, namely stromal cells, immunological cells, and tumor cells. In recent years, a surge in studying tumor-associated non-coding RNAs (ncRNAs) has been observed. Subsequently, studies have also reported that exosomes abundantly carry different species of ncRNAs and these exosomal ncRNAs are functionally involved in cancer initiation and progression. Here, we discuss the function of exosomal ncRNAs, such as miRNAs and long non-coding RNAs, in the pathophysiology of lung tumors. Further, the future application of exosomal-ncRNAs in clinics as biomarkers and therapeutic targets in lung cancer is also discussed due to the multifaceted influence of exosomes on cellular physiology. Full article
(This article belongs to the Special Issue Non-coding RNAs in Cancer, Aging and Regeneration)
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<p>Release of extracellular vesicles and the functional impact on target cells. Since the cargo of EVs is solely reliant on the pathophysiological circumstances of the cell at the precise moment the vesicle is produced, EVs are a heterogeneous population in terms of both form and content. It is important to consider how the same vesicle, or the same message, might be interpreted differently depending on the cytotype that receives it when analyzing the intricacy of EV-mediated cell–cell communication. The recipient cell’s gene expression profile will play a significant role in this. Figure is created with BioRender.</p>
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<p>Exosomal ncRNAs and lung cancer. Malignant cells produce exosomes that transport ncRNAs that can promote tumor growth to distant organs and the cancer microenvironment. ncRNAs can have a variety of impacts on recipient cells, including: (1) Increase cancer proliferation (2) Increase cancer drug resistance; (3) Modify immune cell signaling, affecting, and changing the immune response; (4) Alter the metabolism of cancer cells. Figure is created with BioRender.</p>
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<p>Extracellular Vesicle (EVs) for non-coding RNA (ncRNA) delivery: Overview of different ncRNA loading procedures (endogenous/exogenous loading) and methods of EVs surface modification (chemical and biological modification). Figure is created with BioRender.</p>
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16 pages, 2482 KiB  
Article
Hypo-Osmoregulatory Roles of Vasotocinergic and Isotocinergic Systems in the Intestines of Two European Sea Bass Lineages
by Quanquan Cao, Eva Blondeau-Bidet and Catherine Lorin-Nebel
Int. J. Mol. Sci. 2022, 23(21), 13636; https://doi.org/10.3390/ijms232113636 - 7 Nov 2022
Cited by 2 | Viewed by 1489
Abstract
European sea bass (Dicentrarchus labrax) are a major aquaculture species that live in habitats with fluctuating salinities that are sometimes higher than in seawater (SW). Atlantic and West-Mediterranean genetic lineages were compared regarding intestinal neuropeptide receptor expression in SW (36%) and [...] Read more.
European sea bass (Dicentrarchus labrax) are a major aquaculture species that live in habitats with fluctuating salinities that are sometimes higher than in seawater (SW). Atlantic and West-Mediterranean genetic lineages were compared regarding intestinal neuropeptide receptor expression in SW (36%) and following a two-week transfer to hypersalinity (HW, 55%). Phylogenetic analysis revealed seven neuropeptide receptors belonging to the arginine vasotocine (AVTR) family and two isotocin receptors (ITR). Among AVTR paralogs, the highest mRNA levels were recorded for v1a2, with a two- to fourfold upregulation in the European sea bass intestinal sections after transfer of fish to HW. Principal component analysis in posterior intestines showed that v1a2 expression grouped together with the expression and activity of main ion transporters and channels involved in solute-coupled water uptake, indicating a possible role of this receptor in triggering water absorption. v1a1 expression, however, was decreased or did not change after transfer to hypersaline water. Among ITR paralogs, itr1 was the most expressed paralog in the intestine and opposite expression patterns were observed following salinity transfer, comparing intestinal sections. Overall, different expression profiles were observed between genetic lineages for several analyzed genes which could contribute to different osmotic stress-related responses in D. labrax lineages. Full article
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<p>Phylogenetic tree of AVTRV-1A1, -1A2, -2A1, -2A2, -2B1, -2B2, -2C, ITR1 and ITR2. Sequences from European sea bass are indicated in blue. Branch lengths represent the degree of divergence. Bayesian posterior probabilities (bpp) are indicated in nodes as red asterisks (if bpp ≥0.99) and in black asterisks (if 0.95 ≤ bpp ≥ 0.98). Nodes with bpp &lt;0.95 are not annotated.</p>
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<p>Relative <span class="html-italic">avtrv</span> and <span class="html-italic">itr</span> mRNA expression in the anterior (AI) and posterior (PI) intestines of Mediterranean European sea bass maintained in seawater. Within the intestinal region, columns displaying different letters are significantly different. Upper letters were indicated for anterior intestines and lower letters were indicated for posterior intestines. Asterisks indicated expression differences between AI and PI for a given gene (two-way ANOVA followed by Tukey’s test, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 11).</p>
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<p>Relative <span class="html-italic">avtrv1a1</span> (<b>A</b>), <span class="html-italic">avtrv1a2</span> (<b>B</b>), <span class="html-italic">avtrv2a1</span> (<b>C</b>), <span class="html-italic">avtrv2b1</span> (<b>D</b>) and <span class="html-italic">itr1</span> (<b>E</b>) mRNA expression were measured in the anterior intestines of Mediterranean (M) and Atlantic (A) European sea bass maintained in seawater (SW) and hypersaline water (HW). Different letters denote significant differences between groups (two-way ANOVA followed by Tukey’s test, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 11). Data are represented as the median, first and third quartiles (box), minimum and maximum values. ns: non significant.</p>
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<p>Relative <span class="html-italic">avtrv1a1</span> (<b>A</b>), <span class="html-italic">avtrv1a2</span> (<b>B</b>), <span class="html-italic">avtrv2b1</span> (<b>C</b>) and <span class="html-italic">itr1</span> (<b>D</b>) mRNA expression were measured in the posterior intestines of Mediterranean (M) and Atlantic (A) European sea bass maintained in seawater (SW) and hypersaline water (HW). Different letters denote significant differences between groups (two-way ANOVA followed by Tukey’s test, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 11). Data are represented as the median, first and third quartile (box), minimum and maximum values. ns: non significant.</p>
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<p>Loading plot of principal component analysis (PCA) representing the individuals (<b>A</b>) and measured variables (<b>B</b>) based on NKA activity, <span class="html-italic">nkaα1a</span>, <span class="html-italic">aqp8ab</span>, <span class="html-italic">aqp8aa</span>, <span class="html-italic">aqp8b</span>, <span class="html-italic">aqp10b</span>, <span class="html-italic">aqp1a</span>, <span class="html-italic">aqp1b</span>, <span class="html-italic">nkcc2</span>, <span class="html-italic">avtrv1a2</span>, <span class="html-italic">avtrv1a1</span>, <span class="html-italic">itr1</span> and <span class="html-italic">avtrv2b1</span> gene expressions in posterior intestines. Four conditions were compared (Mediterranean (M) and Atlantic (<b>A</b>) European sea bass maintained in seawater (SW) and hypersaline water (HW) in the (Dim1 × Dim2) coordination plane. Orange and green colors in (<b>B</b>) respectively represent strong and weak cos<sup>2</sup> values. Ellipses in (<b>A</b>) group <span class="html-italic">D. labrax</span> from the four conditions (MSW in blue crosses, MHW in red squares, ASW in yellow triangles and AHW in green circles).</p>
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11 pages, 1948 KiB  
Article
Effects of Biochar and Nitrogen Application on Rice Biomass Saccharification, Bioethanol Yield and Cell Wall Polymers Features
by Izhar Ali, Muhammad Adnan, Anas Iqbal, Saif Ullah, Muhammad Rafiullah Khan, Pengli Yuan, Hua Zhang, Jamal Nasar, Minghua Gu and Ligeng Jiang
Int. J. Mol. Sci. 2022, 23(21), 13635; https://doi.org/10.3390/ijms232113635 - 7 Nov 2022
Cited by 2 | Viewed by 1595
Abstract
Rice is a major food crop that produces abundant biomass wastes for biofuels. To improve rice biomass and yield, nitrogen (N) fertilizer is excessively used, which is not eco-friendly. Alternatively, biochar (B) application is favored to improve rice biomass and yield under low [...] Read more.
Rice is a major food crop that produces abundant biomass wastes for biofuels. To improve rice biomass and yield, nitrogen (N) fertilizer is excessively used, which is not eco-friendly. Alternatively, biochar (B) application is favored to improve rice biomass and yield under low chemical fertilizers. To minimize the reliance on N fertilizer, we applied four B levels (0, 10, 20, and 30 t B ha−1) combined with two N rates (low-135 and high-180 kg ha−1) to improve biomass yield. Results showed that compared to control, the combined B at 20–30 t ha−1 with low N application significantly improved plant dry matter and arabinose (Ara%), while decreasing cellulose crystallinity (Crl), degree of polymerization (DP), and the ratio of xylose/arabinose (Xyl/Ara), resulting in high hexoses (% cellulose) and bioethanol yield (% dry matter). We concluded that B coupled with N can alter cell wall polymer features in paddy rice resulting in high biomass saccharification and bioethanol production. Full article
(This article belongs to the Collection Feature Papers in 'Macromolecules')
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<p>Total biomass production in rice plants under different biochar and nitrogen fertilizer treatments during 2019 and 2020. Different letters on bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05.; Bars indicate means ± SD (n = 3).</p>
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<p>Changes in hexose yields (% cellulose) released with tween (<b>A</b>) and without tween (<b>B</b>) of rice straw treated with biochar and nitrogen fertilizers. Different letters on bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05. (n = 3).</p>
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<p>Impact of biochar and nitrogen fertilizer on bioethanol yields from biomass process in rice. ** above the column represent significant difference among the biochar and biochar treatments by <span class="html-italic">t</span>-test at <span class="html-italic">p</span> &lt; 0.05 or <span class="html-italic">p</span> &lt; 0.01 (n = 3). % value indicates the increase in the same treatment with Tween-80 from without Tween-80.</p>
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<p>Biochar and nitrogen fertilizer effect on cell wall polymers feature (<b>A</b>) crystalline index (CrI) of cellulose, (<b>B</b>) degree of polymerization of cellulose, (<b>C</b>) arabinose proportion of hemicellulose, (<b>D</b>) ratio of xylose and arabinose. Different letters on bars are not significantly different at <span class="html-italic">p</span> &lt; 0.05. (n = 3).</p>
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<p>Mechanism involving the primary wall polymer characteristics has an influence on biomass enzymatic saccharification in rice under biochar and nitrogen fertilizer. (<b>A</b>) The correlation coefficient between biochar + N fertilizers, cellulose, hemicelluloses, lignin, and DM. (<b>B</b>) Correlation analysis between hexoses, Crl, Dp, Ara, Xyl/Ara, and DM. (<b>C</b>) A model for improving biomass yield and enzymatic digestibility with biochar and N fertilizer by changing wall polymer characteristics. * and ** indicate a significant coefficient correlation value at <span class="html-italic">p</span> &lt; 0.005 and 0.001. (+) and (−) represented increased and reduced effects, respectively.</p>
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13 pages, 2040 KiB  
Article
Magnetic Multi-Enzymatic System for Cladribine Manufacturing
by Guillermo Cruz, Laura Pilar Saiz, Muhammad Bilal, Lobna Eltoukhy, Christoph Loderer and Jesús Fernández-Lucas
Int. J. Mol. Sci. 2022, 23(21), 13634; https://doi.org/10.3390/ijms232113634 - 7 Nov 2022
Cited by 5 | Viewed by 1975
Abstract
Enzyme-mediated processes have proven to be a valuable and sustainable alternative to traditional chemical methods. In this regard, the use of multi-enzymatic systems enables the realization of complex synthetic schemes, while also introducing a number of additional advantages, including the conversion of reversible [...] Read more.
Enzyme-mediated processes have proven to be a valuable and sustainable alternative to traditional chemical methods. In this regard, the use of multi-enzymatic systems enables the realization of complex synthetic schemes, while also introducing a number of additional advantages, including the conversion of reversible reactions into irreversible processes, the partial or complete elimination of product inhibition problems, and the minimization of undesirable by-products. In addition, the immobilization of biocatalysts on magnetic supports allows for easy reusability and streamlines the downstream process. Herein we have developed a cascade system for cladribine synthesis based on the sequential action of two magnetic biocatalysts. For that purpose, purine 2′-deoxyribosyltransferase from Leishmania mexicana (LmPDT) and Escherichia coli hypoxanthine phosphoribosyltransferase (EcHPRT) were immobilized onto Ni2+-prechelated magnetic microspheres (MagReSyn®NTA). Among the resulting derivatives, MLmPDT3 (activity: 11,935 IU/gsupport, 63% retained activity, operational conditions: 40 °C and pH 5–7) and MEcHPRT3 (12,840 IU/gsupport, 45% retained activity, operational conditions: pH 5–8 and 40–60 °C) emerge as optimal catalysts for further synthetic application. Moreover, the MLmPDT3/MEcHPRT3 system was biochemically characterized and successfully applied to the one-pot synthesis of cladribine under various conditions. This methodology not only displayed a 1.67-fold improvement in cladribine synthesis (compared to MLmPDT3), but it also implied a practically complete transformation of the undesired by-product into a high-added-value product (90% conversion of Hyp into IMP). Finally, MLmPDT3/MEcHPRT3 was reused for 16 cycles, which displayed a 75% retained activity. Full article
(This article belongs to the Special Issue Biocatalysis: An Eco-Friendly Scenario for the Manufacturing of APIs)
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Graphical abstract

Graphical abstract
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<p>Enzymatic synthesis of Cladribine catalyzed by: (<b>A</b>) <span class="html-italic">Lm</span>PDT. (<b>B</b>) <span class="html-italic">Lm</span>PDT/<span class="html-italic">Ec</span>HPRT. dIno: 2′-deoxyinosine; 2-ClAde: 2-chloroadenine; Hyp: hypoxanthine; PRPP: 5-phospho-α-D-ribosyl-1-pyrophosphate; <span class="html-italic">Lm</span>PDT: <span class="html-italic">Leishmania mexicana</span> purine 2′-deoxyribosyltransferase; <span class="html-italic">Ec</span>HPRT; <span class="html-italic">Escherichia coli</span> hypoxanthine phosphoribosyltransferase.</p>
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<p>Biochemical characterization of M<span class="html-italic">Lm</span>PDT3 and M<span class="html-italic">Ec</span>HPRT3. (<b>A</b>) Effect of temperature on M<span class="html-italic">Lm</span>PDT3 activity (<b>●</b>). (<b>B</b>) Effect of pH on M<span class="html-italic">Lm</span>PDT3 activity, (<b>●</b>) 50 mM sodium citrate (pH 4–6), (△) 50 mM sodium phosphate (pH 6–8), (○) 50 mM MES (pH 6–7), (■) 50 mM Tris-HCl (pH 7–9), (□) 50 mM sodium borate (pH 8–10). (<b>C</b>) Effect of temperature M<span class="html-italic">Ec</span>HPRT3 activity (<b>●</b>). (<b>D</b>) Effect of pH on M<span class="html-italic">Ec</span>HPRT3 activity, (<b>●</b>) 12 mM sodium citrate (pH 4–6), (△) 12 mM sodium phosphate (pH 6–8), (○) 12 mM MES (pH 6–7), (■) 12 mM Tris-HCl (pH 7–9), (□) 12 mM sodium borate (pH 8–10).</p>
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<p>Biochemical characterization of the M<span class="html-italic">Lm</span>PDT3/M<span class="html-italic">Ec</span>HPRT3 system. (<b>A</b>) Effect of temperature on cladribine synthesis (●). (<b>B</b>) Effect of pH on cladribine synthesis, (<b>●</b>) 50 mM sodium citrate (pH 4–6), (△) 50 mM sodium phosphate (pH 6–8), (○) 50 mM MES (pH 6–7), (■) 50 mM Tris-HCl (pH 7–9), (□) 50 mM sodium borate (pH 8–10).</p>
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<p>Thermal inactivation profile of M<span class="html-italic">Lm</span>PDT3/M<span class="html-italic">Ec</span>HPRT3 on cladribine synthesis at 40 °C (<b>●</b>) and 50 °C (○).</p>
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<p>Effect of M<span class="html-italic">Lm</span>PDT3/M<span class="html-italic">Ec</span>HPRT3 ratio (μg of immobilized <span class="html-italic">Lm</span>PDT/μg of immobilized <span class="html-italic">Ec</span>HPRT) in the product formation. (<b>A</b>) cladribine (reaction 1). (<b>B</b>) Hyp converted into IMP (reaction 2).</p>
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<p>Reusability of the M<span class="html-italic">Lm</span>PDT3/M<span class="html-italic">Ec</span>HPRT3 system. 2′-deoxyribosyltransferase activity, reaction 1 (black bar); phosphoribosyltransferase activity, reaction 2 (white bar).</p>
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