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30 pages, 1501 KiB  
Review
The Role of Heat Shock Protein (Hsp) Chaperones in Environmental Stress Adaptation and Virulence of Plant Pathogenic Bacteria
by Donata Figaj
Int. J. Mol. Sci. 2025, 26(2), 528; https://doi.org/10.3390/ijms26020528 - 9 Jan 2025
Viewed by 324
Abstract
Plant pathogenic bacteria are responsible for a substantial number of plant diseases worldwide, resulting in significant economic losses. Bacteria are exposed to numerous stress factors during their epiphytic life and within the host. Their ability to survive in the host and cause symptomatic [...] Read more.
Plant pathogenic bacteria are responsible for a substantial number of plant diseases worldwide, resulting in significant economic losses. Bacteria are exposed to numerous stress factors during their epiphytic life and within the host. Their ability to survive in the host and cause symptomatic infections depends on their capacity to overcome stressors. Bacteria have evolved a range of defensive and adaptive mechanisms to thrive under varying environmental conditions. One such mechanism involves the induction of chaperone proteins that belong to the heat shock protein (Hsp) family. Together with proteases, these proteins are integral components of the protein quality control system (PQCS), which is essential for maintaining cellular proteostasis. However, knowledge of their action is considerably less extensive than that of human and animal pathogens. This study discusses the modulation of Hsp levels by phytopathogenic bacteria in response to stress conditions, including elevated temperature, oxidative stress, changes in pH or osmolarity of the environment, and variable host conditions during infection. All these factors influence bacterial virulence. Finally, the secretion of GroEL and DnaK proteins outside the bacterial cell is considered a potentially important virulence trait. Full article
(This article belongs to the Special Issue Host-Pathogen Interaction, 6th Edition)
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Figure 1
<p>Adaptation of phytopathogenic bacteria to environmental conditions: The right-hand side outlines the stress conditions that bacteria may encounter at different stages of their life cycle, including the epiphytic phase on plant surfaces (<b>A</b>) and host infection within the plant, as represented by the interior of the apoplast (<b>B</b>). The left-hand side highlights the factors used or produced by bacteria to counteract these unfavorable conditions and induce symptomatic plant infection.</p>
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<p>Simplified scheme of Hsp proteins action in <span class="html-italic">E. coli</span>. GroEL-GroES and DnaK-DnaJ are the main systems responsible for protein folding. In addition, HtpG cooperates with DnaK in the remodeling of misfolded proteins. ClpB is a disaggregase that interacts with DnaK. IbpA/B proteins function as holdases and cooperate with other chaperones.</p>
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<p>Secretion and surface exposure of Hsp chaperones in phytopathogenic bacteria: This schematic illustrates the bacterial species likely to secrete or expose Hsp proteins outside the cell during plant infection or under conditions that mimic the infection process. This figure does not account for studies in which cell lysis may have occurred.</p>
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21 pages, 5403 KiB  
Article
Integrated Analysis of Metatranscriptome and Amplicon Sequencing to Reveal Distinctive Rhizospheric Microorganisms of Salt-Tolerant Rice
by Wenna Meng, Zhenling Zhou, Mingpu Tan, Anqi Liu, Shuai Liu, Jiaxue Wang, Zhiguang Sun, Yiluo Tan, Yan Liu, Baoxiang Wang and Yanming Deng
Plants 2025, 14(1), 36; https://doi.org/10.3390/plants14010036 - 26 Dec 2024
Viewed by 432
Abstract
Salt stress poses a significant constraint on rice production, so further exploration is imperative to elucidate the intricate molecular mechanisms governing salt tolerance in rice. By manipulating the rhizosphere microbial communities or targeting specific microbial functions, it is possible to enhance salt tolerance [...] Read more.
Salt stress poses a significant constraint on rice production, so further exploration is imperative to elucidate the intricate molecular mechanisms governing salt tolerance in rice. By manipulating the rhizosphere microbial communities or targeting specific microbial functions, it is possible to enhance salt tolerance in crops, improving crop yields and food security in saline environments. In this study, we conducted rice rhizospheric microbial amplicon sequencing and metatranscriptome analysis, revealing substantial microbiomic differences between the salt-tolerant rice cultivar TLJIAN and the salt-sensitive HUAJING. Fungal taxa including Hormiactis, Emericellopsis, Ceriosporopsis, Dirkmeia, and Moesziomyces predominated in the rhizosphere of salt-tolerant rice, while bacterial genera such as Desulfoprunum and Hydrogenophaga exhibited notable differences. Metatranscriptomic analysis identified 7192 differentially expressed genes (DEGs) in the two rice varieties, with 3934 genes being upregulated and 3258 genes being downregulated. Enrichment analyses in KEGG and GO pathways highlighted the majority of DEGs were associated with the “two-component system”, “sulfur metabolism”, and “microbial metabolism in diverse environments”. The interaction network of DEGs and microbial taxa revealed upregulation of transporters, transcriptional factors, and chaperones, such as ABC transporters and chaperonin GroEL, in the rhizosphere microbiomes of salt-tolerant varieties. Our multi-omics network analysis unveiled that fungi like Ceriosporopsis and Dirkmeria, along with bacteria such as Desulfoprunum, Rippkaea, and Bellilinea, showed a positive correlation with flavonoid synthesis in salt-tolerant rice. This study provides an in-depth exploration of the distinctive microbial communities associated with the rhizosphere of salt-tolerant rice varieties, shedding light on the complex interactions between these microbial consortia and their host plants under stress conditions. Full article
(This article belongs to the Special Issue Physiological and Molecular Responses for Stress Tolerance in Rice)
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<p>Comparative analysis of the microbiome composition based on amplifier sequencing 16S and ITS sequencing in the rhizospheres of four rice varieties with different salt tolerance. (<b>a</b>,<b>b</b>) Venn diagram of specific and shared fungal and bacterial OTUs. (<b>c</b>,<b>d</b>) Principal component analysis of rhizosphere microorganisms. The left figures (<b>a</b>,<b>c</b>) represent fungi, and the right figures (<b>b</b>,<b>d</b>) represent bacteria.</p>
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<p>LEfSe analysis of fungi and bacteria differences in the rhizosphere of two rice varieties. (<b>a</b>) The different fungi taxa between salt-tolerant TLJIAN and salt-sensitive HJING rice rhizosphere. (<b>b</b>) The different bacteria taxa between salt-tolerant TLJIAN and salt-sensitive HJING rice rhizosphere. The circles from inner to outer layers represent the taxonomic levels from the phylum to species. The dots on the circles represent terms on the corresponding taxonomic level. The sizes of the dots indicate relative abundance. Coloring: yellow represents species with no significant difference, red for species enriched in the salt-sensitive HJING rhizosphere, and green for species enriched in salt-tolerant TLJIAN rhizosphere. The lowercase p, c, o, f, g, and s in front of the symbol “_” represent the phylum, class, order, family, genus, and species, respectively.</p>
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<p>Microbial differentially expressed genes (DEGs) in the rhizospheric microbiome of salt-tolerant TLJIAN and salt-sensitive HJING rice. (<b>a</b>) Heat map of DEGs based on hierarchical clustering analysis. (<b>b</b>) Gene ontology (GO) enrichment analysis of DEGs. (<b>c</b>) Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs.</p>
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<p>A metatranscriptome and microbiome network derived from comprehensive gene–microorganism associations. Rectangles represent genes, circles represent bacteria, and triangles represent fungi. The red and blue lines represent positive and negative correlations, respectively; the thickness of the line indicates the strength of the correlation. The thicker the line, the stronger the correlation. The detailed correlation data of genes and microorganisms are presented in <a href="#app1-plants-14-00036" class="html-app">Table S6</a>.</p>
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<p>Multi-omics network of the comprehensive associations among genes, metabolites, and microorganisms. Rectangles represent genes, circles represent rice metabolites, triangles represent bacteria, and diamonds represent fungi. The gray and blue lines represent positive and negative correlations, respectively; the thickness of the line indicates the strength of the correlation. The thicker the line, the stronger the correlation. The 18 metabolites in rice were derived from the previous study [<a href="#B29-plants-14-00036" class="html-bibr">29</a>], and the detailed correlation data of metabolites, genes, and microorganisms are presented in <a href="#app1-plants-14-00036" class="html-app">Table S7</a>.</p>
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16 pages, 3266 KiB  
Article
Tracking Chaperone-Mediated Autophagy Flux with a pH-Resistant Fluorescent Reporter
by Ruotong Qi, Xingyi Chen, Zihan Li, Zheng Wang, Zhuohui Xiao, Xinyue Li, Yuanyuan Han, Hongfei Zheng, Yanjun Wu and Yi Xu
Int. J. Mol. Sci. 2025, 26(1), 17; https://doi.org/10.3390/ijms26010017 - 24 Dec 2024
Viewed by 423
Abstract
Chaperone-mediated autophagy (CMA) is a selective autophagic pathway responsible for degrading cytoplasmic proteins within lysosomes. Monitoring CMA flux is essential for understanding its functions and molecular mechanisms but remains technically complex and challenging. In this study, we developed a pH-resistant probe, KFERQ-Gamillus, by [...] Read more.
Chaperone-mediated autophagy (CMA) is a selective autophagic pathway responsible for degrading cytoplasmic proteins within lysosomes. Monitoring CMA flux is essential for understanding its functions and molecular mechanisms but remains technically complex and challenging. In this study, we developed a pH-resistant probe, KFERQ-Gamillus, by screening various green fluorescent proteins. This probe is activated under conditions known to induce CMA, such as serum starvation, and relies on LAMP2A and the KFERQ motif for lysosomal localization and degradation, demonstrating its specificity for the CMA pathway. It enables the detection of CMA activity in living cells through both microscopy and image-based flow cytometry. Additionally, we created a dual-reporter system, KFERQ-Gamillus-Halo, by integrating KFERQ-Gamillus with the Halo-tag system. This probe not only distinguishes between protein synthesis and degradation but also facilitates the detection of intracellular CMA flux via immunoblotting and the rapid assessment of CMA activity using flow cytometry. Together, the KFERQ-Gamillus-Halo probe provides quantitative and time-resolved monitoring for CMA activity and flux in living cells. This tool holds promising potential for high-throughput screening and biomedical research related to CMA. Full article
(This article belongs to the Special Issue Latest Molecular Advances in Autophagy)
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<p>Screening of green fluorescent proteins for CMA reporter. (<b>A</b>,<b>B</b>) NIH-3T3 cells stably expressing KFERQ-fused fluorescent proteins, as indicated, were cultured in medium with (+Serum) or without (−Serum) serum for 24 h. Shown are representative cell images (<b>A</b>) and average number of puncta per cell (<b>B</b>) (<span class="html-italic">n</span> = 20 for each of three independent experiments). Scale bar, 10 μm. Data are shown as mean ± SD; *** <span class="html-italic">p</span> &lt; 0.001; unpaired Student’s <span class="html-italic">t</span>-test.</p>
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<p>KFERQ-Gamillus is a CMA-specific fluorescent reporter. (<b>A</b>) Western blot analysis was used to detect the knockout efficiency in NIH-3T3 cells stably expressing the control or two independent sgRNAs targeting <span class="html-italic">Fip200</span>, <span class="html-italic">Vps4,</span> and <span class="html-italic">Lamp2a</span>. (<b>B</b>) and (<b>C</b>) NIH-3T3 KFERQ-Gamillus cells stably expressing the control or sgRNAs targeting <span class="html-italic">Fip200</span>, <span class="html-italic">Vps4,</span> and <span class="html-italic">Lamp2a</span>, as indicated, were cultured in medium with (+Serum) or without (−Serum) serum for 24 h. Shown are representative cell images (<b>B</b>) and average number of puncta per cell (<b>C</b>) (<span class="html-italic">n</span> =12 for each of three independent experiments). Scale bar, 10 μm. (<b>D</b>,<b>E</b>) NIH-3T3 cells stably expressing KFERQ-Gamillus or dKFERQ-Gamillus were cultured in medium with (+Serum) or without (-Serum) serum for 24 h. Shown are representative cell images (<b>D</b>) and average number of puncta per cell (<b>E</b>) (<span class="html-italic">n</span> = 8 for each of three independent experiments). Scale bar, 10 μm. Data are shown as mean ± SD. NS, not significant; * <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; unpaired Student’s <span class="html-italic">t</span>-test.</p>
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<p>KFERQ-Gamillus is suitable for analyzing CMA activity in an image-based cell sorter. (<b>A</b>–<b>C</b>) NIH-3T3 cells stably expressing KFERQ-Gamillus were incubated with Hoechst for nuclear staining and subsequently analyzed using image-based flow cytometry. The selected P2 cell population was sorted based on KFERQ-Gamillus diffusivity, with P6 and P7 representing cells with low and high diffusivity, respectively. The sorted P6 and P7 cells were cultured for several hours until fully attached, followed by immunofluorescence (IF) analysis; representative images of the cells are shown in panel (<b>B</b>), and the average number of puncta per cell is quantified in panel (<b>C</b>) (<span class="html-italic">n</span> = 30 for each of three independent experiments). Scale bar: 10 μm. (<b>D</b>–<b>F</b>) The selected P2 cell population (same as in A) was first sorted based on intensity of KFERQ-Gamillus, and the selected P3 cell population was subsequently sorted based on KFERQ-Gamillus diffusivity, with P4 and P5 representing cells with low and high diffusivity, respectively. The sorted P4 and P5 cells, with low or high intensity, were cultured for several hours until fully attached, followed by immunofluorescence analysis; representative images of the cells are shown in panel (<b>E</b>), and the average number of puncta per cell is quantified in panel (<b>F</b>) (<span class="html-italic">n</span> = 25 for each of three independent experiments). Scale bar: 10 μm. Data are shown as mean ± SD, with *** <span class="html-italic">p</span> &lt; 0.001, as determined by an unpaired Student’s <span class="html-italic">t</span>-test.</p>
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<p>Evaluation of CMA flux with KFERQ-Gamillus-Halo. (A) Schematic representation of the fate of ligand-free and ligand-bound KFERQ-Gamillus-Halo. (<b>B</b>,<b>C</b>) HEK293 cells stably expressing KFERQ-Gamillus-Halo were cultured in serum-deprived medium for the indicated times. The cells were then pulse-labeled for 20 min with 10 nM of Tetramethylrhodamine (TMR)-conjugated ligand, and cell lysates were analyzed by Western blot (<b>B</b>). The Halo<sup>TMR</sup> band intensity was quantified by normalizing it to the combined intensity of the KFERQ-Gamillus-Halo<sup>TMR</sup> and Halo<sup>TMR</sup> bands (<b>C</b>). S.E., short exposure; L.E., long exposure. (<b>D</b>–<b>F</b>) HEK293 cells stably expressing KFERQ-Gamillus-Halo or dKFERQ-Gamillus-Halo were cultured with (+Serum) or without (−Serum) for 24 h. Following this, cells were pulse-labeled for 20 min with 10 nM of TMR-conjugated Halo ligand and then analyzed by immunofluorescence. Panel (<b>D</b>) shows representative images of cells, while panel (<b>E</b>) presents the average number of puncta per cell for Gamillus and Halo<sup>TMR</sup> (<span class="html-italic">n</span> = 8 for each of three independent experiments). Panel (<b>F</b>) quantifies Gamillus<sup>+</sup>Halo<sup>TMR+</sup> and Gamillus<sup>+</sup>Halo<sup>TMR-</sup> puncta, representing substrates associated with lysosomes (<span class="html-italic">n</span> =8 for each of three independent experiments). Scale bar = 10 μm. (<b>G</b>–<b>L</b>) HEK293 cells stably expressing KFERQ-Gamillus-Halo (<b>G</b>–<b>I</b>) or dKFERQ-Gamillus-Halo (<b>J</b>–<b>L</b>) were cultured without serum (-S) for the indicated times; the cells were then pulse-labeled for 20 min with 10 nM of TMR-conjugated ligand and further analyzed by flow cytometry. Shown are mean Gamillus fluorescence intensity (<b>G</b>,<b>J</b>), the relative fluorescence intensity (<b>H</b>,<b>K</b>), and the relative Halo<sup>TMR</sup>/Gamillus fluorescence intensity (<b>I</b>,<b>L</b>). Data are shown as mean ± SD; * <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; unpaired Student’s <span class="html-italic">t</span>-test.</p>
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17 pages, 3318 KiB  
Article
Developing Allosteric Chaperones for GBA1-Associated Disorders—An Integrated Computational and Experimental Approach
by Marta Montpeyo, Natàlia Pérez-Carmona, Elena Cubero, Aida Delgado, Ana Ruano, Jokin Carrillo, Manolo Bellotto, Marta Martinez-Vicente and Ana Maria Garcia-Collazo
Int. J. Mol. Sci. 2025, 26(1), 9; https://doi.org/10.3390/ijms26010009 - 24 Dec 2024
Viewed by 682
Abstract
Mutations in the GBA1 gene, which encodes the lysosomal enzyme glucocerebrosidase (GCase), are associated with Gaucher disease and increased risk of Parkinson’s disease. This study describes the discovery and characterization of novel allosteric pharmacological chaperones for GCase through an innovative computational approach combined [...] Read more.
Mutations in the GBA1 gene, which encodes the lysosomal enzyme glucocerebrosidase (GCase), are associated with Gaucher disease and increased risk of Parkinson’s disease. This study describes the discovery and characterization of novel allosteric pharmacological chaperones for GCase through an innovative computational approach combined with experimental validation. Utilizing virtual screening and structure-activity relationship optimization, researchers identified several compounds that significantly enhance GCase activity and stability across various cellular models, including patient-derived fibroblasts and neuronal cells harboring GBA1 mutations. Among these, compound 3 emerged as a lead candidate, demonstrating the ability to enhance GCase protein levels and enzymatic activity while effectively reducing the accumulation of toxic substrates in neuronal models. Importantly, pharmacokinetic studies revealed that compound 3 has favorable brain penetration, indicating its potential as a disease-modifying therapy for GBA1-related disorders affecting the central nervous system. This research not only offers a framework for developing allosteric GCase modulators but also unveils promising new therapeutic strategies for managing Gaucher disease and Parkinson’s disease. The ability of compound 3 to cross the blood-brain barrier emphasizes its potential significance in addressing neurological symptoms associated with these conditions. Full article
(This article belongs to the Section Molecular Informatics)
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<p>The SEE-Tx<sup>®</sup> approach to discover non-competitive, pharmacological allosteric regulators for the GCase protein: (<b>A</b>) Schematic workflow of the procedure used to discover new allosteric regulators; (<b>B</b>) Docking-based high-throughput virtual screening of small molecules. Abbreviation: GCase; Glucocerebrosidase; VS, virtual screening; DSF, differential scanning fluorometry.</p>
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<p>Binding of small molecule hit compounds to GCase, as determined by DSF: (<b>A</b>) Difference in melting temperature (ΔTm) relative to recombinant human GCase in the presence of hit #1 to #28 at 30 μM and pH 7.2. The mean ΔTm values ± SD are from 2 independent experiments (<span class="html-italic">n</span> = 2). The dotted line shows the threshold value for the DSF screening, which was ΔTm ≥ 0.5 °C; (<b>B</b>) Compound <b>1</b> (hit #22) structure; and (<b>C</b>) Dose-dependent effect on the thermal stability of GCase in the presence of hit #22 (compound <b>1</b>). The mean ΔTm values ± SD are from 2 independent experiments (<span class="html-italic">n =</span> 2). DSF, differential scanning fluorimetry; GCase; glucocerebrosidase; SD, standard deviation; Tm, melting temperature.</p>
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<p>Validation of STAR compounds: (<b>A</b>) Structures of compound <b>2</b>; (<b>B</b>) structure of compound <b>3</b>; and measurement of GCase activity in WT fibroblasts treated for four days with (<b>C</b>) compound <b>2</b> and (<b>D</b>) compound <b>3</b>; and <span class="html-italic">GBA1</span>-associated patient-derived fibroblasts treated for four days with compound <b>2</b> and <b>3</b>, respectively: (<b>E</b>,<b>F</b>) p.L444P/p.L444P; (<b>G</b>,<b>H</b>) p.N370S/84gg; (<b>I</b>,<b>J</b>) p.N188S/p.S107L; and (<b>K</b>,<b>L</b>) p.L444P/p. WT. Mean values from at least three replicates of three independent experiments are represented by bars. Results are normalized to the untreated and presented as mean ± SD values of three experiments after one-way ANOVA with Dunnett’s multiple comparison test, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; n.s.—no significant; WT, wild-type.</p>
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<p>Dose-response for: (<b>A</b>) compound <b>2</b> and (<b>B</b>) compound <b>3</b> binding to immobilized human recombinant GCase monitored at neutral pH (7.4) by SPR; and GCase activity assay in wild-type lysates after treatment with (<b>C</b>) compound <b>2</b>, (<b>D</b>) compound <b>3,</b> and (<b>E</b>) isofagomine (IFG) at acidic pH (5.6). Dose-response curves are plotted with mean values based on two independent assays with three replicates each. Error bars represent the standard deviation of the means.</p>
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<p>Measurement of GCase activity in WT cell lines and fibroblasts derived from GD patients treated for four days. Mean values were derived from (<b>A</b>) one independent experiment with two replicates for compound <b>2</b> and (<b>B</b>) three independent experiments with two replicates each for compound <b>3</b>. HexCer substrate quantification to evaluate the substrate depletion in GD patient-derived fibroblasts (L444P/L444P) by LC/MS-MS for (<b>C</b>) compound <b>2</b> and (<b>D</b>) compound <b>3</b>. Results are presented as mean values from three replicates of two independent experiments after one-way ANOVA with Dunnett’s multiple comparison test, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; ns, no significant; WT, wild-type.</p>
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<p>(<b>A</b>) Basal GCase activity of WT, p.N370S and p.L444P <span class="html-italic">GBA1</span> mutant BE(2)M17 cell lines, results are presented as mean ± SD values after two-way ANOVA followed by Tukey’s multiple comparisons test, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; (<b>B</b>) GCase activity assay of differentiated WT, N370S and L444P neuronal cell lines treated for four days with 25 μM compound <b>3</b>. Activity is expressed as fold activity versus vehicle in each cell line (dashed line); (<b>C</b>) Representative images of GCase immunodetection by western blot and (<b>D</b>) quantification of GCase protein levels (GCase protein levels in vehicle-treated cells are represented as a dashed line) of the three differentiated neuronal cell lines (WT, N370S, and L444P) treated with 25 µM compound <b>3</b> for ten days; (<b>E</b>) GCase activity assay of three differentiated neuronal cell lines (WT, N370S and L444P) treated for 10 days with 25 μM of the selected compound <b>3</b>. Activity is expressed as fold activity versus vehicle in each cell line (dashed line); (<b>F</b>) Quantification of GlcSph levels, the substrate of GCase, following treatment of 10 days with compound <b>3</b> at 25 µM. Lipid levels are expressed in pmol/mg of tissue; and (<b>G</b>) Viability assays for the three differentiated neuronal cell lines treated for 10 with compound <b>3</b> at 25 µM. Viability is expressed as a fold percentage of live cells versus vehicles in each cell line. Results in panel (<b>B</b>,<b>D</b>–<b>G</b>) are presented as mean ± standard deviation values; significance is shown within each cell line compared to their vehicle after two-way ANOVA followed by Sidak’s multiple comparisons test, * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. GCase, glucocerebrosidase; GlcSph, glucosylsphingosine; WT, wild-type.</p>
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<p>Plasma and brain pharmacokinetics distribution at different time points after administration of a single i.v. 10 mg/kg dose of compound <b>3</b> in male C57BL/6 mice.</p>
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14 pages, 2777 KiB  
Article
The Effects of the Combined Co-Expression of GroEL/ES and Trigger Factor Chaperones on Orthopoxvirus Phospholipase F13 Production in E. coli
by Iuliia A. Merkuleva, Vladimir N. Nikitin, Tatyana D. Belaya, Egor. A. Mustaev and Dmitriy N. Shcherbakov
BioTech 2024, 13(4), 57; https://doi.org/10.3390/biotech13040057 - 23 Dec 2024
Viewed by 593
Abstract
Heterologous protein expression often faces significant challenges, particularly when the target protein has posttranslational modifications, is toxic, or is prone to misfolding. These issues can result in low expression levels, aggregation, or even cell death. Such problems are exemplified by the expression of [...] Read more.
Heterologous protein expression often faces significant challenges, particularly when the target protein has posttranslational modifications, is toxic, or is prone to misfolding. These issues can result in low expression levels, aggregation, or even cell death. Such problems are exemplified by the expression of phospholipase p37, a critical target for chemotherapeutic drugs against pathogenic human orthopoxviruses, including monkeypox and smallpox viruses. The complex structure and broad enzymatic activity of phospholipase p37 render it toxic to host cells, necessitating specialized strategies for heterologous expression. In our study, we addressed these challenges using the vaccinia virus F13 protein as a model. We demonstrated that p37 can be effectively synthesized in E. coli as a GST fusion protein by co-expressing it with the GroEL/ES chaperone system and Trigger Factor chaperone. Full article
(This article belongs to the Section Medical Biotechnology)
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<p>A model of the tertiary structure of the GST-F13 protein (Alphafold2 prediction): The GST protein is represented in light gray, with the 3CL cleavage site highlighted in blue. The secondary structure elements of F13 are color-coded as follows: α-helices are shown in red, β-sheets in blue, and loops in gray. The phospholipase domain is emphasized in purple, as well as the amino acid residues of the phospholipase motif. The non-structural region of the complex, corresponding to the 6× His-tag, is depicted in green.</p>
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<p>Analysis of extracts of <span class="html-italic">E. coli</span> BL21 (DE3) cells co-expressing the GST-F13 protein along with the chaperones Trigger Factor (TF) and GroEL/ES. (<b>A</b>) SDS-PAGE of insoluble (I) and soluble (S) protein fractions; (<b>B</b>) Western blot analysis of expressed proteins using anti-6× His antibodies; (<b>C</b>) SDS-PAGE analysis of insoluble (I) and soluble (S) proteins induced at different temperatures. The GST-F13 protein fraction (~69 kDa) is indicated by arrows.</p>
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<p>Map of the pGTi plasmid, containing GroEL/ES and Trigger Factor (TF) chaperone genes.</p>
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<p>(<b>A</b>) SDS-PAGE analysis of insoluble (I) and soluble (S) fractions of <span class="html-italic">E. coli</span> BL21 (DE3) cells harboring pET21-GST-F13 and pGTi plasmids, induced with 1 mM IPTG for 4 h; (<b>B</b>) Immunoblotting of protein fractions with anti-His antibodies.</p>
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<p><span class="html-italic">E. coli</span> BL21 (DE3)/pET21-GST-F13/pGTi culture growth and GST-F13 protein expression kinetics: (<b>A</b>) Growth curve (mean ± SD, <span class="html-italic">n</span> = 3) and relative GST-F13 expression. Protein quantity was determined by densitometric analysis of SDS-PAGE (n = 3), and normalized with maximum value. (<b>B</b>) SDS-PAGE analysis of the time course production of GST-F13 in <span class="html-italic">E. coli</span>.</p>
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<p>SDS-PAGE analysis of eluted fractions (1, 2) of GST-F13 protein after affinity chromatography.</p>
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<p>(<b>A</b>) Schematic illustration of pNPPC hydrolysis by GST-F13; (<b>B</b>) phospholipase activity of GST-F13 protein in the presence of NIOCH-14 inhibitor (0.01 mg/mL). Data are presented as mean ± SD, n = 3.</p>
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14 pages, 2033 KiB  
Article
Inflammatory Stimulation Upregulates the Receptor Transporter Protein 4 (RTP4) in SIM-A9 Microglial Cells
by Wakako Fujita and Yusuke Kuroiwa
Int. J. Mol. Sci. 2024, 25(24), 13676; https://doi.org/10.3390/ijms252413676 - 21 Dec 2024
Viewed by 486
Abstract
The receptor transporter protein 4 (RTP4) is a receptor chaperone protein that targets class A G-protein coupled receptor (GPCR)s. Recently, it has been found to play a role in peripheral inflammatory regulation, as one of the interferon-stimulated genes (ISGs). However, the detailed role [...] Read more.
The receptor transporter protein 4 (RTP4) is a receptor chaperone protein that targets class A G-protein coupled receptor (GPCR)s. Recently, it has been found to play a role in peripheral inflammatory regulation, as one of the interferon-stimulated genes (ISGs). However, the detailed role of RTP4 in response to inflammatory stress in the central nervous system has not yet been fully understood. While we have previously examined the role of RTP4 in the brain, particularly in neuronal cells, this study focuses on its role in microglial cells, immunoreactive cells in the brain that are involved in inflammation. For this, we examined the changes in the RTP4 levels in the microglial cells after exposure to inflammatory stress. We found that lipopolysaccharide (LPS) treatment (0.1~1 µg/mL, 24 h) significantly upregulated the RTP4 mRNA levels in the microglial cell line, SIM-A9. Furthermore, the interferon (IFN)-β mRNA levels and extracellular levels of IFN-β were also increased by LPS treatment. This upregulation was reversed by treatment with neutralizing antibodies targeting either the interferon receptor (IFNR) or toll-like receptor 4 (TLR4), and with a TLR4 selective inhibitor, or a Janus kinase (JAK) inhibitor. On the other hand, the mitogen-activated protein kinase kinase (MEK) inhibitor, U0126, significantly enhanced the increase in RTP4 mRNA following LPS treatment, whereas the PKC inhibitor, calphostin C, had no effect. These findings suggest that in microglial cells, LPS-induced inflammatory stress activates TLR4, leading to the production of type I IFN, the activation of IFN receptor and JAK, and finally, the induction of RTP4 gene expression. Based on these results, we speculate that RTP4 functions as an inflammation-responsive molecule in the brain. However, further research is needed to fully understand its role. Full article
(This article belongs to the Special Issue Pharmacological Treatment of Neuroinflammation)
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<p>Changes in <span class="html-italic">RTP4</span> mRNA levels after LPS stimulation in SIM-A9 microglial cell line. Cells were treated with LPS (100 ng/mL) for 24 h (<b>A</b>), 6 h (<b>C</b>) or for indicated periods (<b>B</b>) and then collected to perform RT-qPCR analysis by using selective primers targeting <span class="html-italic">GAPDH</span> (internal control) or <span class="html-italic">RTP</span>s. Control cells were treated with a vehicle instead of LPS for the indicated periods. Data are the mean ± S.E.M. n = 10 (<b>A</b>), n = 7 (<b>B</b>), n = 4 (<b>C</b>), * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.0001, vs. control (without LPS), one-way ANOVA and Tukey’s multiple comparison test (<b>A</b>), multiple unpaired <span class="html-italic">t</span>-test (<b>B</b>,<b>C</b>).</p>
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<p>The effect of LPS stimulation on the expression levels of RTP4 determined by immunofluorescent analysis. SIM-A9 microglial cells were treated without or with LPS (100 ng/mL) for the indicated periods and immunofluorescent analysis performed as described in Materials and Methods. Control cells (−) were treated with vehicle instead of LPS for 24 h. Scale bar is 10 micrometer. Data are the mean ± S.E.M. n = 144 (Control), n = 53 (LPS 6 h), n = 138 (LPS 12 h), n = 130 (LPS 24 h), n = 100 (LPS 48 h) ’n’ represents the total number of cells from 3 independent experiments. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.0001, vs. control, one-way ANOVA and Tukey’s multiple comparison test.</p>
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<p>Changes in <span class="html-italic">TNFα</span> (<b>A</b>), <span class="html-italic">IL-1β</span> (<b>B</b>), and <span class="html-italic">iNOS</span> (<b>C</b>) mRNA levels after LPS treatment. SIM-A9 microglial cells were treated with LPS (100 ng/mL) for the indicated periods and then collected to perform RT-qPCR analysis using selective primers targeting <span class="html-italic">GAPDH</span> (internal control), <span class="html-italic">TNFα, IL-1β</span> or <span class="html-italic">iNOS</span>. Control cells (−) were treated with a vehicle instead of LPS for indicated periods. Data are the mean ± S.E.M. n = 12 (3 and 12 h); n = 16 (6 and 24 h); n = 10 (48 h), * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.001, *** <span class="html-italic">p</span> &lt; 0.0001, vs. control, multiple unpaired t-test.</p>
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<p>Changes in <span class="html-italic">IFN-α</span> (<b>A</b>) and <span class="html-italic">IFN-β</span> (<b>B</b>) mRNA levels after LPS treatment. SIM-A9 microglial cells were treated with LPS (100 ng/mL) for the indicated periods and collected for RT-qPCR analysis as described in Methods using selective primers targeting <span class="html-italic">GAPDH</span> (internal control), <span class="html-italic">IFN-α</span>, or <span class="html-italic">IFN-β</span>. Control cells were treated with a vehicle instead of LPS for indicated periods. Data are the mean ± S.E.M. n = 12 (3, 12 h), n = 16 (6, 24 h), n = 10 (48 h), ** <span class="html-italic">p</span> &lt; 0.001, *** <span class="html-italic">p</span> &lt; 0.0001, vs. control, one-way ANOVA, and Tukey’s multiple comparison test. Effect of TAK242, a TLR4 inhibitor, on the increase in extracellular IFN-β levels after LPS treatment (<b>C</b>–<b>E</b>). SIM-A9 microglial cells were treated with LPS (100 ng/mL) for the indicated periods and the culture medium was collected for ELISA analysis as described in Methods. Data are the mean ± S.E.M. n = 5–6, *** <span class="html-italic">p</span> &lt; 0.0001, vs. control, ### <span class="html-italic">p</span> &lt; 0.0001, vs. LPS alone. Multiple unpaired <span class="html-italic">t</span>-test (<b>A</b>,<b>B</b>), one-way ANOVA and Turkey’s multiple comparison test (<b>C</b>–<b>E</b>).</p>
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<p>The effect of neutralizing antibody targeting TLR4 (<b>A</b>), selective inhibitor of TLR4 (TAK242) (<b>B</b>), neutralizing antibody targeting IFNR (IFNAR-1) (<b>C</b>) and inhibitor of JAK (Pyridone 6) (<b>D</b>) on LPS-induced upregulation of <span class="html-italic">RTP4</span> mRNA levels. SIM-A9 microglial cells were pretreated with TLR4 antibody (10 µg/mL), TAK242 (100 nM), IFNR antibody (20 ug/mL) or Pyridone 6 at indicated concentrations for 30 min before the LPS (100 ng/mL) or vehicle treatment for 6 h or 24 h which cells were collected and subjected to RT-qPCR analyses using primers that target <span class="html-italic">GAPDH</span> and <span class="html-italic">RTP4</span>. Control cells were pretreated with medium instead of antibody or inhibitor and treated with vehicle instead of LPS for 24 h. Data are the mean ± S.E.M. n = 3–7 (<b>A</b>), n = 5–6 (<b>B</b>), n = 7 (<b>C</b>), n = 4 (<b>D</b>). *** <span class="html-italic">p</span> &lt; 0.0001, vs. control, ### <span class="html-italic">p</span> &lt; 0.0001, vs. LPS alone. One-way ANOVA and Turkey’s multiple comparison test.</p>
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<p>The effect of inhibitors of MAPK kinase (<b>A</b>) and PKC (<b>B</b>), TLR4 downstream signaling molecules, on LPS-induced upregulation of <span class="html-italic">RTP4</span> mRNA levels. SIM-A9 microglial cells were pretreated with inhibitors at indicated concentrations for 30 min before the LPS (100 ng/mL) or vehicle treatment for 24 h after which cells were collected and subjected to RT-qPCR analyses using primers that target <span class="html-italic">GAPDH</span> and <span class="html-italic">RTP4</span>. Control cells were pretreated with medium instead of inhibitor and treated with vehicle instead of LPS for 24 h. Data are mean ± S.E.M. n = 8, * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.0001, vs. control, # <span class="html-italic">p</span> &lt; 0.05, vs. LPS alone, n.s., not significant, one-way ANOVA and Turkey’s multiple comparison test.</p>
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<p>Illustration of the TLR4 signaling pathways and the mechanism of <span class="html-italic">RTP4</span> induction under LPS stimulation. Following LPS stimulation, TLR4 activation leads to IFN-β production in microglial cells. IFN-β is subsequently released into the extracellular compartment and transactivates IFNR, resulting in <span class="html-italic">RTP4</span> production. ‘?’ and the dashed line indicates a pathway that has not been elucidated in this study and is thus a hypothesis here.</p>
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12 pages, 1330 KiB  
Article
Magnesium Supplementation Modifies Arthritis Synovial and Splenic Transcriptomic Signatures Including Ferroptosis and Cell Senescence Biological Pathways
by Teresina Laragione, Carolyn Harris and Pércio S. Gulko
Nutrients 2024, 16(23), 4247; https://doi.org/10.3390/nu16234247 - 9 Dec 2024
Viewed by 1479
Abstract
Background: Rheumatoid arthritis (RA) is a common systemic autoimmune inflammatory disease that can cause joint damage. We have recently reported that oral magnesium supplementation significantly reduces disease severity and joint damage in models of RA. Methods: In the present study, we analyzed the [...] Read more.
Background: Rheumatoid arthritis (RA) is a common systemic autoimmune inflammatory disease that can cause joint damage. We have recently reported that oral magnesium supplementation significantly reduces disease severity and joint damage in models of RA. Methods: In the present study, we analyzed the transcriptome of spleens and synovial tissues obtained from mice with KRN serum-induced arthritis (KSIA) consuming either a high Mg supplemented diet (Mg2800; n = 7) or a normal diet (Mg500; n = 7). Tissues were collected at the end of a 15-day KSIA experiment. RNA was extracted and used for sequencing and analyses. Results: There was an enrichment of differentially expressed genes (DEGs) belonging to Reactome and Gene Ontology (GO) pathways implicated in RA pathogenesis such as RHO GTPases, the RUNX1 pathway, oxidative stress-induced senescence, and the senescence-associated secretory phenotype. Actc1 and Nr4a3 were among the genes with the highest expression, while Krt79 and Ffar2 were among the genes with the lowest expression in synovial tissues of the Mg2800 group compared with the Mg500 group. Spleens had an enrichment for the metabolism of folate and pterines and the HSP90 chaperone cycle for the steroid hormone receptor. Conclusions: We describe the tissue transcriptomic consequences of arthritis-protecting Mg supplementation in KSIA mice. These results show that oral Mg supplementation may interfere with the response to oxidative stress and senescence and other processes known to participate in RA pathogenesis. We provide new evidence supporting the disease-suppressing effect of increased Mg intake in arthritis and its potential to become a new addition to the therapeutic options for RA and other autoimmune and inflammatory diseases. Full article
(This article belongs to the Special Issue Magnesium Homeostasis and Magnesium Transporters in Human Health)
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<p>Arthritis severity scores of mice with KRN serum-induced arthritis (KSIA). (<b>A</b>) Mice were placed on either a normal Mg500 (n = 7) or a high Mg2800 (n = 7) diet 14 days prior to the induction of KSIA and kept on the same diet for an additional 15 days and scored for disease severity (** <span class="html-italic">p</span> = 0.004993 and <span class="html-italic">p</span> = 0.001462, respectively; non-paired <span class="html-italic">t</span>-test). Representative histology sections of KSIA mice on (<b>B</b>) the normal Mg500 diet, showing pronounced synovial hyperplasia and joint damage, and (<b>C</b>) the high Mg2800 diet, showing a protected and normal-looking joint without synovial hyperplasia or damage (H&amp;E staining, 200× magnification).</p>
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<p>Biological pathways enriched in the DEGs between KSIA arthritic mice on Mg2800 and Mg500 diets. (<b>A</b>) Selected Reactome biological pathways and cellular processes enriched in synovial tissues (top section) and spleens (bottom section). (<b>B</b>) Selected Gene Ontology (GO) pathways enriched in the DEGs between mice on Mg2800 and Mg500 diets in the synovial tissues (top section), and spleens (bottom section). (See <a href="#app1-nutrients-16-04247" class="html-app">Supplemental Tables S1 and S2</a> for additional details).</p>
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<p>Volcano plots of the DEGs between KSIA arthritic mice on the Mg2800 diet and those on the Mg500 diet and selected genes’ qPCR confirmation. (<b>A</b>) Volcano plot of DEGs in synovial tissues. (<b>B</b>) Volcano plot of DEGs in spleens. (<b>C</b>) Quantitative PCR (qPCR) confirmation of selected genes expressed in increased and decreased levels in the Mg2700 diet synovial tissues showing a trend in the same direction as seen in the RNA sequencing analyses (<span class="html-italic">p</span> &gt; 0.05).</p>
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13 pages, 1631 KiB  
Article
Dietary Docosahexaenoic Acid-Rich Supplementation Decreases Neurotoxic Lipid Mediators in Participants with Type 2 Diabetes and Neuropathic Pain
by Alfonso M. Durán, Francis Zamora and Marino De León
Nutrients 2024, 16(23), 4025; https://doi.org/10.3390/nu16234025 - 24 Nov 2024
Viewed by 1044
Abstract
Background/Objectives: There is increasing evidence linking circulating neurotoxic lipids to the progression of chronic neuroinflammatory diseases in the peripheral and central nervous systems. Strategies to modify lipid profiles, such as docosahexaenoic acid (DHA)-rich supplementation, may aid in managing conditions like painful diabetic neuropathy [...] Read more.
Background/Objectives: There is increasing evidence linking circulating neurotoxic lipids to the progression of chronic neuroinflammatory diseases in the peripheral and central nervous systems. Strategies to modify lipid profiles, such as docosahexaenoic acid (DHA)-rich supplementation, may aid in managing conditions like painful diabetic neuropathy (pDN). In a previous study, we demonstrated that three months of DHA supplementation significantly altered the metabolomic profile of patients with painful diabetic neuropathy (pDN), resulting in symptom improvement. This study investigates whether DHA-rich supplementation reduces neurotoxic lipid mediators associated with pDN in individuals with type 2 diabetes mellitus (T2DM). Methods: Forty individuals with type 2 diabetes participated in the “En Balance-PLUS” study, attending weekly lifestyle and nutrition education sessions while receiving daily supplementation of 1000 mg DHA and 200 mg EPA. Pain levels were assessed using the Short-Form McGill Pain Questionnaire (SF-MPQ) at baseline and after three months. Blood serum samples collected at these time points underwent untargeted lipidomic analyses, with ELISA used to evaluate biomarkers of necrosis (MLKL), autophagy (ATG5), and lipid chaperone protein (FABP5). Results: Untargeted lipidomic analysis revealed that several neurotoxic-associated lipids significantly decreased after DHA-rich supplementation. Also, circulating levels of MLKL were reduced, while protein levels of ATG5 and FABP5 significantly increased. Conclusions: The reduction of circulating neurotoxic lipids and increase in neuroprotective lipids following DHA-rich supplementation are consistent with the reported roles of omega-3 polyunsaturated fatty acids (PUFAs) in reducing adverse symptoms associated with neuroinflammatory diseases and painful neuropathy. Full article
(This article belongs to the Section Nutrition and Diabetes)
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<p>Matched pairs <span class="html-italic">t</span>-test with adjusted <span class="html-italic">p</span>-value (FDR) cutoff of 0.05. Eighty-one (81) lipid features were significantly different (<span class="html-italic">p</span> &lt; 0.05) at three months.</p>
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<p>RF classification of serum samples collected at baseline (0) and three (3) months after DHA-rich supplementation (1). Classification was ~96% accurate for samples when a value of 50% would be expected by random chance. The plot for lipid features is important because it shows the top factors contributing to group separation.</p>
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<p>Mixed lineage kinase domain-like (MLKL) decreases after three (3) months of DHA-rich supplementation in participants with type 2 diabetes and neuropathic pain. Match pairs Wilcoxon test: (<b>A</b>) ELISA measured all participants’ serum levels of MLKL at baseline and three months. (<b>B</b>) Participants with moderately high pain at baseline and serum levels of MLKL, measured by ELISA, at baseline and three months. * <span class="html-italic">p</span> &lt; 0.05, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>ATG5 increases after three months of DHA-rich supplementation in participants with type 2 diabetes and with painful DN. Match pairs Wilcoxon test: (<b>A</b>) All participants’ serum levels of ATG5, measured by ELISA, at baseline and three months. (<b>B</b>) Participants with moderately high pain at baseline and serum levels of ATG5, measured by ELISA, at baseline and three months. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>FABP5 increases after three months of DHA-rich supplementation in participants with type 2 diabetes and neuropathic pain. Match pairs Wilcoxon test: (<b>A</b>) ELISA measured all participants’ serum levels of FABP5 at baseline and three months. (<b>B</b>) Participants with moderately high pain at baseline and serum levels of FABP5, measured by ELISA, at baseline and three months. ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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32 pages, 5633 KiB  
Review
The Mechanistic Link Between Tau-Driven Proteotoxic Stress and Cellular Senescence in Alzheimer’s Disease
by Karthikeyan Tangavelou and Kiran Bhaskar
Int. J. Mol. Sci. 2024, 25(22), 12335; https://doi.org/10.3390/ijms252212335 - 17 Nov 2024
Viewed by 1482
Abstract
In Alzheimer’s disease (AD), tau dissociates from microtubules (MTs) due to hyperphosphorylation and misfolding. It is degraded by various mechanisms, including the 20S proteasome, chaperone-mediated autophagy (CMA), 26S proteasome, macroautophagy, and aggrephagy. Neurofibrillary tangles (NFTs) form upon the impairment of aggrephagy, and eventually, [...] Read more.
In Alzheimer’s disease (AD), tau dissociates from microtubules (MTs) due to hyperphosphorylation and misfolding. It is degraded by various mechanisms, including the 20S proteasome, chaperone-mediated autophagy (CMA), 26S proteasome, macroautophagy, and aggrephagy. Neurofibrillary tangles (NFTs) form upon the impairment of aggrephagy, and eventually, the ubiquitin chaperone valosin-containing protein (VCP) and heat shock 70 kDa protein (HSP70) are recruited to the sites of NFTs for the extraction of tau for the ubiquitin–proteasome system (UPS)-mediated degradation. However, the impairment of tau degradation in neurons allows tau to be secreted into the extracellular space. Secreted tau can be monomers, oligomers, and paired helical filaments (PHFs), which are seeding competent pathological tau that can be endocytosed/phagocytosed by healthy neurons, microglia, astrocytes, oligodendrocyte progenitor cells (OPCs), and oligodendrocytes, often causing proteotoxic stress and eventually triggers senescence. Senescent cells secrete various senescence-associated secretory phenotype (SASP) factors, which trigger cellular atrophy, causing decreased brain volume in human AD. However, the molecular mechanisms of proteotoxic stress and cellular senescence are not entirely understood and are an emerging area of research. Therefore, this comprehensive review summarizes pertinent studies that provided evidence for the sequential tau degradation, failure, and the mechanistic link between tau-driven proteotoxic stress and cellular senescence in AD. Full article
(This article belongs to the Special Issue Proteasome Activity Regulation)
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<p><b><span class="html-italic">20S proteasomal degradation of tau.</span></b> The structure of the 20S proteasome consists of 7 different α subunit proteins (α1–α7—blue) and β subunit proteins (β1–β7—light red) in which β1, β2, and β5 subunits are constitutively catalytic active. The heptameric α subunits form an outer ring-like structure at the top and bottom of the inner two layers of heptameric β subunit proteins, stacked antiparallelly as an inner ring-like structure. The 20S proteasome can degrade natively unfolded tau. But, it does not degrade folded, phosphorylated (conformational changed), and ubiquitinated tau because of the absence of protein unfoldase and deubiquitinase activities, which are required to unfold and deubiquitinate tau before entering into the catalytic β subunit core proteins. Abbreviation: Ub, ubiquitin.</p>
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<p><b><span class="html-italic">Overview of dynamics of tau degradation in AD.</span></b> The degradation pathway for tau is selected based on the diversity of tau species based on their structure and post-translational modifications. In AD, non-ubiquitinated tau substrates, including unfolded and misfolded tau, can be degraded by the 20S proteasome and CMA, respectively. Misfolded ubiquitinated tau substrates, including phosphorylated and acetylated tau, can be degraded by the 26S proteasome and macroautophagy (autophagy), respectively. Hyperubiquitinated aqueous tau aggregates are degraded by liquid-phase aggrephagy, whereas solid tau aggregates of NFTs with or without ubiquitin chains are degraded by solid-phase aggrephagy. The ubiquitin chaperone, VCP/p97 ATPase, binds to HSP70 and synergistically extracts tau from NFTs for the UPS or autophagy degradation. The pathological tau extracted from NFTs can be monomers, oligomers, and PHFs secreted into the extracellular space upon the impairment of the UPS or autophagy in neurons. Abbreviations: p-Tau, phosphorylated tau; CMA, chaperone-mediated autophagy; AD, Alzheimer’s disease; NFTs, neurofibrillary tangles; VCP, valosin-containing protein; HSP70, heat shock protein 70, UPS, ubiquitin–proteasome system; and PHFs, paired helical filaments.</p>
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<p><b><span class="html-italic">Molecular chaperones regulate tau degradation and stability via ubiquitination.</span></b> (<b>A</b>) The 26S proteasomal degradation of tau. In AD, MT-bound tau can be phosphorylated by various kinases such as PKA, CaMKII, GSK-3β, and Cdk-5, causing tau to detach from MT (1). Then, aggregation-prone phosphorylated tau is recognized by HSP70/Hsc70 and its cochaperone BAG-1 to assist K48-linked polyubiquitination by the E3-ubiquitin ligase CHIP and E2-ubiquitin-conjugating UbcH5B protein complex (2). BAG-1 functions as a nucleotide exchange factor to release the misfolded and ubiquitinated tau from chaperones (3). The 26S proteasome consists of the inner catalytic core 20S proteasome and the outer regulatory 19S proteasome subunits, which recognize the ubiquitinated tau through binding to its ubiquitin chains and immediately unfold and deubiquitinate before entering into the 20S proteasome for tau degradation. The ubiquitinated tau substrate can be (4a) folded, (4b) phosphorylated and folded, and (4c) phosphorylated and unfolded. The non-ubiquitinated tau, including phosphorylated and non-phosphorylated folded tau, unfolded phosphorylated tau, and K63-linked polyubiquitinated tau, are not substrates for the 26S proteasomal degradation (5). (<b>B</b>) HSP90-FKBP51 regulates tau oligomerization. During in vitro conditions, HSP90 binds to paper-clip conformers of tau and promotes their oligomerization, which involves MTBRs (1). During in vivo conditions, HSP90 binds to its co-chaperone FKBP51 and enhances tau oligomerization (2), but this interaction does not allow transition into Thioflavin-T positive fibrillar tau (3). The HSP90-FKBP51 complex synergistically inhibits 20S proteasome-mediated degradation of tau (3), leading to the accumulation of phosphorylated tau (pT231) and toxic tau oligomers (T22 positive oligomers) (4). Tau oligomers can be stabilized by K63-linked polyubiquitin chains, which cannot be degraded by the 26S proteasome (5) unless it obtains K48-linked ubiquitin as a hybrid K63/K48-linked ubiquitination. Abbreviations: Ub, ubiquitin; CHIP, C-terminus of Hsc70-interacting protein; HSP70, heat shock protein 70; BAG-1, BCL2 Associated Athanogene-1; UbcH5B, ubiquitin-conjugating enzyme E2D 2; ATP, adenosine triphosphate; ADP, adenosine diphosphate; Pi, inorganic phosphate; HSP90, heat shock protein 90 kDa; FKBP51, FK506 binding protein 51 kDa; pT231, phosphorylated Tau at threonine 231; T22, tau oligomer specific antibody; and MTBRs, microtubule-binding repeats.</p>
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<p><b><span class="html-italic">Chaperone-mediated autophagy (CMA) degradation of tau</span>.</b> The molecular chaperone Hsc70 binds to CMA motifs in tau and eventually interacts with the lysosome-associated membrane protein 2A (LAMP2A), which oligomerizes to form a channel-like structure to deliver tau along with Hsc70 into the lumen of the lysosome for degradation. Hsc70 stays with tau until the proteases digest tau. If not, tau gets aggregated in an acidic environment, leading to the generation of amyloidogenic tau fragments. The CMA can degrade tau if the CMA motifs can be easily accessible in either folded or unfolded tau. Acetylated tau is not a substrate of CMA, and it can eventually obtain ubiquitin chains for either autophagy or 26S proteasomal degradation. Abbreviations: HSP70, heat shock protein 70; Hsc70, heat shock cognate 71 kDa protein; CHIP, C-terminus of Hsc70-interacting protein; UPS, ubiquitin–proteasome system; CMA, chaperone-mediated autophagy; LAMP2A, lysosome-associated membrane protein 2A; and Ub, ubiquitin.</p>
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<p><b><span class="html-italic">Autophagy degradation of tau</span>.</b> (<b>A</b>) Macroautophagy (autophagy) can degrade ubiquitinated non-aggregates or aggregates of tau upon the impairment of the ubiquitin–proteasome system (UPS). An autophagy receptor p62 (SQSTM1) recognizes polyubiquitinated tau as an autophagy cargo and interacts with LC3 (ATG8), which is lipidated with phosphatidylethanolamine (PE) to anchor cargo at the inner leaflet of the lipid bilayer for phagophore membrane expansion. Autophagosomes formed against tau can fuse to lysosomes for tau degradation, which is known as macroautophagy (autophagy). (<b>B</b>) Aggrephagy degradation of tau aggregates. Hyperubiquitinated tau aggregates within the aqueous phase are recognized by the p62 receptor initially and subsequently recruit other SQSTM1-like receptors (SLRs), including the next to BRCA1 gene 1 protein (NBR1) and Tax1 binding protein 1 (TAX1PB1) via their ubiquitin-binding domain (UBA). Tau aggregates are condensed via liquid–liquid phase separation (LLPS) (1) and recruit autophagy regulatory proteins, including LC3, for phagophore membrane expansion for liquid aggrephagy-mediated clearance of tau aggregates (2). However, some unknown factor(s) impair autophagosome formation or autophagosome maturation with the lysosome, leading to the formation of membrane-less solid aggregates of NFTs, which can be differentially marked with various linkage-specific ubiquitin chains (3). The molecular chaperone aggrephagy receptor chaperonin containing TCP1 subunit 2 (CCT2) can recognize solid protein aggregates via its apical domain for solid aggrephagy-mediated clearance of tau aggregates with or without ubiquitin chains (4a). The ubiquitin chaperone valosin-containing protein (VCP)/p97 ATPase extract ubiquitinated tau aggregates (K48/K6, K48/K11, or K48/K63 hybrid ubiquitin chains) for either autophagy or UPS-mediated degradation (4b). However, pathological tau, including monomers, oligomers (K63-linked or K48/K63-linked hybrid ubiquitin chains), and PHFs, are secreted into the extracellular space upon the impairment of autophagy or UPS. NFTs are marked with M1-linked linear ubiquitin chains for NF-κB associated inflammatory signaling activation in AD brains. Abbreviations: Ub, ubiquitin; LC3-PE, phosphatidylethanolamine conjugated to C-terminus of microtubule-associated protein 1 light chain 3; UPS, ubiquitin–proteasome system; HSP70, heat shock protein 70; and NFTs, neurofibrillary tangles.</p>
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<p><b><span class="html-italic">Proteotoxic stress drives cellular senescence in AD</span>.</b> Pathological tau and Aβ drive proteotoxic stress in neurons by impairing the UPS and autophagy, causing an accumulation of intracellular NFTs and extracellular Aβ plaques in AD brains. Degenerating neurons secrete pathological tau into the extracellular space, where healthy neurons, microglia, astrocytes, OPC, and OL can endocytose/phagocytose tau for clearance. However, secreted tau species, including monomers, oligomers, and PHFs, are seeding competent, which propagates tau pathology in neurons and mature OL. Degenerating neuronal dendrites can secrete CSF1 and IL-34 that induce replicative senescence in microglia associated with the extracellular Aβ plaques (1). Pathological tau induces proteotoxic stress-driven senescence in microglia upon proteostasis impairment (2). Endocytosed tau oligomers can induce senescence in astrocytes and lead to the secretion of HMGB1 into the extracellular space. Senescent astrocytes may impair glutamate homeostasis, leading to glutamate excitotoxicity in AD (3). Protein aggregates (PAs) and senescent astrocytes secreted HMGB1 can also impair the differentiation of OPC into mature OL, causing demyelination of neurons (4). Abbreviations: CSF1, colony-stimulating factor 1; IL-34, interleukin-34; PAs, protein aggregates; Aβ, amyloid beta; NFT, neurofibrillary tangle; OPC, oligodendrocyte progenitor cell; OL, oligodendrocyte; and HMGB1, high mobility group box 1.</p>
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<p><b><span class="html-italic">Senescent astrocytes impair glutamate homeostasis in AD</span>.</b> Senescence in astrocytes is induced by AD-associated tau oligomers/Aβ<sub>1–42</sub> peptide. Senescent astrocytes show characteristics of increased GFAP, p16, HMGB1, APOE, and connexin-43 (CX43), and decreased EAAT 1/2, Kir4.1, and AQP4 levels upon exposure to ionizing radiation (1). The glutamate–glutamine cycle is essential for proper neuronal excitation by which presynaptic neurons release glutamate at the synaptic zone. The SNARE complex regulates the fusion of glutamate vesicles with the presynaptic membrane to release glutamate (2). AMPAR/NMDAR binds to glutamate, eventually allowing an influx of Na+ and Ca<sup>2+</sup> ions to induce an action potential at the postsynaptic neurons (3). Excessively released glutamate is taken up by astrocytes via EAAT 1/2 channels, where glutamine synthase (GS) converts glutamate into glutamine and is exported into neurons for the next cycle of neuron excitation by which regulated neurotransmission is maintained (4). In senescent astrocytes, the EAAT 1/2 level is decreased, causing the accumulation of glutamate in the synaptic cleft and extrasynaptic regions, which leads to excitotoxicity (5), impairing AD memory retrieval. Abbreviations: HMGB1, high mobility group box 1; GFAP, glial fibrillary acidic protein; p16, cyclin-dependent kinase inhibitor 2A; K<sup>+</sup>, potassium ion; Kir4.1, inwardly rectifying potassium channel 4.1; AQP4, aquaporin-4; GS, glutamine synthase; EAAT 1/2, excitatory amino acid transporters 1/2; APOE, apolipoprotein E; CX43, connexin-43; Gln, glutamine; Glu, glutamic acid; VGLUT, vesicular glutamate transporter; SNARE, soluble N-ethylmaleimide-sensitive factor attachment protein receptor; mGluR, metabotropic glutamate receptor; Na<sup>+</sup>, sodium ion; Ca<sup>+</sup>, calcium ion; AMPAR, alpha-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor; and NMDAR, N-methyl-D-aspartate receptor.</p>
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<p><b><span class="html-italic">Nuclear remodeling and TOR-autophagy spatial coupling compartment (TASCC) regulate senescence cell survival</span>.</b> Senescent-inducing factors regulate the translocation of nuclear transmembrane protein lamin B receptor (LBR) into the cytoplasm for proteasomal degradation or are, perhaps, degraded by nucleophagy (1). Chronic inhibition of the UPS or autophagy induces senescence by remodeling the nucleus for relaxed gene expression. The oncogene RAS-induced autophagy, but not by mTOR inhibition or starvation-induced autophagy, regulates the degradation of lamin B1 (LMNB1), causing oncogene-induced senescence (2). In senescent cells, nuclear autophagy (nucleophagy) degrades LMNB1 nuclear blebs (2) and SIRT1 (3) by interacting with ubiquitin-like LC3B to remodel the nuclear membrane and chromatin for relaxed gene expression (4). Senescent cells import the proteasome subunit proteins into the nucleus to assemble the 26S proteasome and eventually form senescence-associated nuclear proteasome foci (SANP) by actively recruiting VCP/p97 ATPase and RAD23 to degrade unknown nuclear proteins (5). Senescent cells enhance the nuclear translocation of active dephosphorylated TFEB (6) and NF-κB (7) for increased lysosome biogenesis and senescence-associated immune response gene expression (8), respectively. In RAS-induced senescence, the trans-Golgi network (TGN) provides a novel compartment, TOR-autophagy spatial coupling compartment (TASCC), for accelerated mTOR and autophagy activities (9), which is essential for senescent cell survival. An alternative autophagy, LC3-independent Golgi-membrane-associated degradation (GOMED) pathway is activated upon the impairment of the Golgi to plasma membrane trafficking that eventually triggers extensive remodeling of the nuclear membrane leading to the terminal cell atrophy (10). Abbreviations: LBR, lamin B receptor; LMNB1, lamin B1; SIRT1, sirtuin 1; LC3B, microtubule-associated protein 1 light chain 3 beta; TFEB, transcription factor EB; TGN, trans-Golgi network; SASP, senescence-associated secretory phenotype; NF-κB, nuclear factor kappa B; IL, interleukin; TNFα, tumor necrosis factor alpha; ER, endoplasmic reticulum; RAD23B, UV excision repair protein RAD23 homolog B; VCP, valosin-containing protein; mTOR, mammalian target of rapamycin; RAS, rat sarcoma virus; TASCC, TOR-autophagy spatial coupling compartment; GOMED, Golgi-membrane-associated degradation; and SANP, senescence-associated nuclear proteasome foci.</p>
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18 pages, 3243 KiB  
Article
Integrated Transcriptome Profiling and Pan-Cancer Analyses Reveal Oncogenic Networks and Tumor-Immune Modulatory Roles for FABP7 in Brain Cancers
by Yool Lee, Carlos C. Flores, Micah Lefton, Sukanya Bhoumik, Yuji Owada and Jason R. Gerstner
Int. J. Mol. Sci. 2024, 25(22), 12231; https://doi.org/10.3390/ijms252212231 - 14 Nov 2024
Viewed by 1362
Abstract
Fatty acid binding protein 7 (FABP7) is a multifunctional chaperone involved in lipid metabolism and signaling. It is primarily expressed in astrocytes and neural stem cells (NSCs), as well as their derived malignant glioma cells within the central nervous system. Despite growing evidence [...] Read more.
Fatty acid binding protein 7 (FABP7) is a multifunctional chaperone involved in lipid metabolism and signaling. It is primarily expressed in astrocytes and neural stem cells (NSCs), as well as their derived malignant glioma cells within the central nervous system. Despite growing evidence for FABP7’s tumor-intrinsic onco-metabolic functions, its mechanistic role in regulating the brain tumor immune microenvironment (TIME) and its impact on prognosis at the molecular level remain incompletely understood. Utilizing combined transcriptome profiling and pan-cancer analysis approaches, we report that FABP7 mediates the expression of multiple onco-immune drivers, collectively impacting tumor immunity and clinical outcomes across brain cancer subtypes. An analysis of a single-cell expression atlas revealed that FABP7 is predominantly expressed in the glial lineage and malignant cell populations in gliomas, with nuclear localization in their parental NSCs. Pathway and gene enrichment analysis of RNA sequencing data from wild-type (WT) and Fabp7-knockout (KO) mouse brains, alongside control (CTL) and FABP7-overexpressing (FABP7 OV) human astrocytes, revealed a more pronounced effect of FABP7 levels on multiple cancer-associated pathways. Notably, genes linked to brain cancer progression and tumor immunity (ENO1, MUC1, COL5A1, and IL11) were significantly downregulated (>2-fold) in KO brain tissue but were upregulated in FABP7 OV astrocytes. Furthermore, an analysis of data from The Cancer Genome Atlas (TCGA) showed robust correlations between the expression of these factors, as well as FABP7, and established glioma oncogenes (EGFR, BRAF, NF1, PDGFRA, IDH1), with stronger associations seen in low-grade glioma (LGG) than in glioblastoma (GBM). TIME profiling also revealed that the expression of FABP7 and the genes that it modulates was significantly associated with prognosis and survival, particularly in LGG patients, by influencing the infiltration of immunosuppressive cell populations within tumors. Overall, our findings suggest that FABP7 acts as an intracellular regulator of pro-tumor immunomodulatory genes, exerting a synergistic effect on the TIME and clinical outcomes in brain cancer subtypes. Full article
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<p>FABP7 modulates the expression of genes associated with brain cancer progression and tumor immunity. (<b>A</b>) Volcano plot showing differential gene expression in cortical tissues from wild-type (WT) and Fabp7-knockout (KO) mice (adjusted <span class="html-italic">p</span>-value ≤ 0.05, fold change cutoff: 2.0). (<b>B</b>) Log2 fold-change values for significantly upregulated (red) and downregulated (blue) genes in Fabp7-KO compared to WT tissues. (<b>C</b>) Pie chart illustrating the characteristics and functions of downregulated coding genes (≥2-fold change, <span class="html-italic">n</span> = 26) categorized into the following: Oncogenic Drivers (<span class="html-italic">n</span> = 16, red), Tumor Suppressors (<span class="html-italic">n</span> = 4, bright blue), and Unresolved Functions (<span class="html-italic">n</span> = 6, blue-green) (see <a href="#app1-ijms-25-12231" class="html-app">Dataset S1</a> for details). (<b>D</b>) Oncogenic driver genes identified in (<b>C</b>) further categorized into those functional in non-brain tumors (<span class="html-italic">n</span> = 7, orange) and brain tumors (<span class="html-italic">n</span> = 9, red), with immunomodulatory functions noted. (<b>E</b>) Heatmap of tumor immunomodulatory gene expression (TIMGs) in WT (<span class="html-italic">n</span> = 5) vs. Fabp7-KO (<span class="html-italic">n</span> = 4) samples, with brain and non-brain TIMGs marked by dashed red and orange lines, respectively. (<b>F</b>) Heatmap of TIMG expression in control (CTL, <span class="html-italic">n</span> = 4) and FABP7-overexpressing (FABP7 OV, <span class="html-italic">n</span> = 3) human astrocytes, with markings as in (<b>E</b>).</p>
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<p><span class="html-italic">FABP7</span> expression is more strongly correlated with the expression of its modulated factors in LGG than GBM. (<b>A</b>) Correlations between <span class="html-italic">FABP7</span> expression and the expression levels of its regulated brain tumor immunomodulatory genes (identified in <a href="#ijms-25-12231-f001" class="html-fig">Figure 1</a>C–F) were assessed in low-grade glioma (LGG, <span class="html-italic">n</span> = 516) and glioblastoma (GBM, <span class="html-italic">n</span> = 153) using the Gene_Corr module in the Tumor Immune Estimation Resource (TIMER) database (see <a href="#sec4-ijms-25-12231" class="html-sec">Section 4</a> for details). Genes with significantly positive or negative correlations (<span class="html-italic">p</span> &lt; 0.05), based on purity-adjusted partial Spearman’s rho values, are indicated with red and blue boxes, respectively. (<b>B</b>) Table of the purity-adjusted partial Spearman’s rho values indicating the degree of correlation between <span class="html-italic">FABP7</span> expression and the expression of the brain tumor immunomodulatory genes that it regulates, as shown in (<b>A</b>). Abbreviations: ENO1, Enolase 1; MUC1, Mucin 1; COL5A1, Collagen Type V Alpha 1 Chain; COL11A1, Collagen Type XI Alpha 1 Chain; IL11, Interleukin 11.</p>
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<p>The expression of <span class="html-italic">FABP7</span> and its modulated genes is more highly correlated with patient prognosis and outcomes in LGG than GBM. (<b>A</b>) Survival curves for brain cancer patients with low-grade glioma (LGG) and glioblastoma (GBM) were generated based on the expression levels of <span class="html-italic">FABP7</span> and its modulated genes, as indicated. Data were obtained from the TIMER database and are represented using the Cox proportional hazard model. Kaplan–Meier (KM) curve parameters were applied to evaluate the significance of gene expression outcomes in both LGG and GBM. The hazard ratio and <span class="html-italic">p</span>-value for the Cox model, as well as the log-rank <span class="html-italic">p</span>-value for the KM curve, are shown on each KM curve plot. Genes with positive correlations (<span class="html-italic">p</span> &lt; 0.05), based on purity-adjusted partial Spearman’s rho values, are indicated by boxes of varying shades of red to indicate significance, as shown in (<b>B</b>). (<b>B</b>) Table of the purity-adjusted partial Spearman’s rho values indicating the degree of correlation between <span class="html-italic">FABP7</span> and its regulated factors, as described in (<b>A</b>). The analysis was adjusted for clinical factors, such as age, stage, and purity (see <a href="#sec4-ijms-25-12231" class="html-sec">Section 4</a> for details). Abbreviations: FABP7, Fatty Acid Binding Protein 7; ENO1, Enolase 1; MUC1, Mucin 1; COL5A1, Collagen Type V Alpha 1 Chain; IL11, Interleukin 11.</p>
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<p>The expression of <span class="html-italic">FABP7</span> and its modulated factors impact the tumor-immune microenvironment of LGG and GBM by enhancing immunosuppressive infiltrates. (<b>A</b>) Table showing the associations between the expression of the indicated genes (<span class="html-italic">FABP7</span>, <span class="html-italic">ENO1</span>, <span class="html-italic">MUC1</span>, <span class="html-italic">COL5A1</span>, <span class="html-italic">IL11</span>) and immune cell (CD4+ T cells, CD8+ T cells, macrophages, Tregs, CAFs, and MDSCs) infiltration in low-grade glioma (LGG) and glioblastoma (GBM). (<b>B</b>) Representative Kaplan–Meier (KM) curves illustrating significantly positive (boxed in red) and negative (boxed in blue) correlations between the expression of <span class="html-italic">FABP7</span> and the infiltration of the indicated immune cells (CAFs and MDSCs) in LGG and GBM are shown. The purity-adjusted Spearman’s rank correlation test was applied to determine both the <span class="html-italic">p</span>-values and partial correlation (cor) values. Significantly positive and negative correlations were determined, based on purity-adjusted Spearman’s rho values (<span class="html-italic">p</span> &lt; 0.05). Abbreviations: T cell CD8+, cytotoxic t lymphocytes; T cell CD4+, helper T lymphocytes, Treg, regulatory T cells; CAF, cancer-associated fibroblasts; MDSC, myeloid-derived suppressor cells; FABP7, Fatty Acid Binding Protein 7; ENO1, Enolase 1; MUC1, Mucin 1; COL5A1, Collagen Type V Alpha 1 Chain; IL11, Interleukin 11; n.s, non-significant.</p>
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27 pages, 2212 KiB  
Article
C11orf58 (Hero20) Gene Polymorphism: Contribution to Ischemic Stroke Risk and Interactions with Other Heat-Resistant Obscure Chaperones
by Irina Shilenok, Ksenia Kobzeva, Vladislav Soldatov, Alexey Deykin and Olga Bushueva
Biomedicines 2024, 12(11), 2603; https://doi.org/10.3390/biomedicines12112603 - 14 Nov 2024
Cited by 1 | Viewed by 781
Abstract
Background: Recently identified Hero proteins, which possess chaperone-like functions, are promising candidates for research into atherosclerosis-related diseases, including ischemic stroke (IS). Methods: 2204 Russian subjects (917 IS patients and 1287 controls) were genotyped for fifteen common SNPs in Hero20 gene C11orf58 [...] Read more.
Background: Recently identified Hero proteins, which possess chaperone-like functions, are promising candidates for research into atherosclerosis-related diseases, including ischemic stroke (IS). Methods: 2204 Russian subjects (917 IS patients and 1287 controls) were genotyped for fifteen common SNPs in Hero20 gene C11orf58 using probe-based PCR and the MassArray-4 system. Results: Six C11orf58 SNPs were significantly associated with an increased risk of IS in the overall group (OG) and significantly modified by smoking (SMK) and low fruit/vegetable intake (LFVI): rs10766342 (effect allele (EA) A; P(OG = 0.02; SMK = 0.009; LFVI = 0.04)), rs11024032 (EA T; P(OG = 0.01; SMK = 0.01; LFVI = 0.036)), rs11826990 (EA G; P(OG = 0.007; SMK = 0.004; LFVI = 0.03)), rs3203295 (EA C; P(OG = 0.016; SMK = 0.01; LFVI = 0.04)), rs10832676 (EA G; P(OG = 0.006; SMK = 0.002; LFVI = 0.01)), rs4757429 (EA T; P(OG = 0.02; SMK = 0.04; LFVI = 0.04)). The top ten intergenic interactions of Hero genes (two-, three-, and four-locus models) involved exclusively polymorphic loci of C11orf58 and C19orf53 and were characterized by synergic and additive (independent) effects between SNPs. Conclusions: Thus, C11orf58 gene polymorphism represents a major risk factor for IS. Bioinformatic analysis showed the involvement of C11orf58 SNPs in molecular mechanisms of IS mediated by their role in the regulation of redox homeostasis, inflammation, vascular remodeling, apoptosis, vasculogenesis, neurogenesis, lipid metabolism, proteostasis, hypoxia, cell signaling, and stress response. In terms of intergenic interactions, C11orf58 interacts most closely with C19orf53. Full article
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<p>Materials and methods of the study.</p>
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<p>Graph reflecting the structure and strength of the most significant G × G interactions of Hero genes associated with IS. The color of the lines reflects the nature of the interaction: red and orange lines mean pronounced and moderate synergism, brown—additive effect of genes (independent effects); % reflects the strength and direction of the phenotypic effect of gene interaction (% entropy).</p>
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<p>Graph of the most significant G × E interactions associated with the development of IS. The color of the line reflects the nature of the interaction: red and orange—pronounced and moderate synergism, brown—independent effect of individual loci; % reflects the strength and direction of the phenotypic effect of gene interaction (% entropy).</p>
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<p>TF-associated overrepresented biological processes of <span class="html-italic">C11orf58</span> SNPs.</p>
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22 pages, 2240 KiB  
Article
The Transcriptomic Response of Cells of the Thermophilic Bacterium Geobacillus icigianus to Terahertz Irradiation
by Sergey Peltek, Svetlana Bannikova, Tamara M. Khlebodarova, Yulia Uvarova, Aleksey M. Mukhin, Gennady Vasiliev, Mikhail Scheglov, Aleksandra Shipova, Asya Vasilieva, Dmitry Oshchepkov, Alla Bryanskaya and Vasily Popik
Int. J. Mol. Sci. 2024, 25(22), 12059; https://doi.org/10.3390/ijms252212059 - 9 Nov 2024
Viewed by 844
Abstract
As areas of application of terahertz (THz) radiation expand in science and practice, evidence is accumulating that this type of radiation can affect not only biological molecules directly, but also cellular processes as a whole. In this study, the transcriptome in cells of [...] Read more.
As areas of application of terahertz (THz) radiation expand in science and practice, evidence is accumulating that this type of radiation can affect not only biological molecules directly, but also cellular processes as a whole. In this study, the transcriptome in cells of the thermophilic bacterium Geobacillus icigianus was analyzed immediately after THz irradiation (0.23 W/cm2, 130 μm, 15 min) and at 10 min after its completion. THz irradiation does not affect the activity of heat shock protein genes and diminishes the activity of genes whose products are involved in peptidoglycan recycling, participate in redox reactions, and protect DNA and proteins from damage, including genes of chaperone protein ClpB and of DNA repair protein RadA, as well as genes of catalase and kinase McsB. Gene systems responsible for the homeostasis of transition metals (copper, iron, and zinc) proved to be the most sensitive to THz irradiation; downregulation of these systems increased significantly 10 min after the end of the irradiation. It was also hypothesized that some negative effects of THz radiation on metabolism in G. icigianus cells are related to disturbances in activities of gene systems controlled by metal-sensitive transcription factors. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>Proposed mechanism of action of THz irradiation on Fur-dependent operons in <span class="html-italic">G. icigianus</span>.</p>
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<p>The experimental scheme.</p>
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<p>RNA quality of total RNA from the K3-ink sample.</p>
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<p>An example of the quality of an obtained RNA-Seq library.</p>
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20 pages, 7684 KiB  
Article
Genome-Wide Analysis of Heat Shock Protein Family and Identification of Their Functions in Rice Quality and Yield
by Hong Wang, Sidra Charagh, Nannan Dong, Feifei Lu, Yixin Wang, Ruijie Cao, Liuyang Ma, Shiwen Wang, Guiai Jiao, Lihong Xie, Gaoneng Shao, Zhonghua Sheng, Shikai Hu, Fengli Zhao, Shaoqing Tang, Long Chen, Peisong Hu and Xiangjin Wei
Int. J. Mol. Sci. 2024, 25(22), 11931; https://doi.org/10.3390/ijms252211931 - 6 Nov 2024
Cited by 1 | Viewed by 1149
Abstract
Heat shock proteins (Hsps), acting as molecular chaperones, play a pivotal role in plant responses to environmental stress. In this study, we found a total of 192 genes encoding Hsps, which are distributed across all 12 chromosomes, with higher concentrations on chromosomes 1, [...] Read more.
Heat shock proteins (Hsps), acting as molecular chaperones, play a pivotal role in plant responses to environmental stress. In this study, we found a total of 192 genes encoding Hsps, which are distributed across all 12 chromosomes, with higher concentrations on chromosomes 1, 2, 3, and 5. These Hsps can be divided into six subfamilies (sHsp, Hsp40, Hsp60, Hsp70, Hsp90, and Hsp100) based on molecular weight and homology. Expression pattern data indicated that these Hsp genes can be categorized into three groups: generally high expression in almost all tissues, high tissue-specific expression, and low expression in all tissues. Further analysis of 15 representative genes found that the expression of 14 Hsp genes was upregulated by high temperatures. Subcellular localization analysis revealed seven proteins localized to the endoplasmic reticulum, while others localized to the mitochondria, chloroplasts, and nucleus. We successfully obtained the knockout mutants of above 15 Hsps by the CRISPR/Cas9 gene editing system. Under natural high-temperature conditions, the mutants of eight Hsps showed reduced yield mainly due to the seed setting rate or grain weight. Moreover, the rice quality of most of these mutants also changed, including increased grain chalkiness, decreased amylose content, and elevated total protein content, and the expressions of starch metabolism-related genes in the endosperm of these mutants were disturbed compared to the wild type under natural high-temperature conditions. In conclusion, our study provided new insights into the HSP gene family and found that it plays an important role in the formation of rice quality and yield. Full article
(This article belongs to the Special Issue Gene Mining and Germplasm Innovation for the Important Traits in Rice)
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<p>Conservative domains of 6 Hsp subfamilies in rice: (<b>A</b>) 23 small Hsp (sHsp) members: protein name suffix is subcellular localization, and each protein has the α-crystallin domain, which is the characteristic domain of sHsp; (<b>B</b>) 104 Hsp40 members, including three types, A (DjA1-DjA12), B (DjB1-DjB9), and C (DjC1-DjC83); each member has the DnaJ domain; (<b>C</b>) 22 Hsp60 members: each protein has a GroEL domain, and these proteins were named according to their positions on the chromosome; (<b>D</b>) 32 Hsp70 members, including 18 proteins whose name contain Hsp70, 6 Bips (Binding immunoglobulin proteins), and 8 Hsp110 members, each with an Hsp70 domain; (<b>E</b>) 8 Hsp90 members, each containing the Hsp90 domain; (<b>F</b>) 3 Hsp100 members, each harboring the ClpB domain specific to Hsp100. The scale at the bottom represents the number of amino acids. The conserved domain data of sHsp, Hsp70, and Hsp90 were downloaded from the Pfam database and visualized using the TBtools-II software. For Hsp40, Hsp60, and Hsp100, the conserved domain data were obtained from NCBI and visualized using a website.</p>
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<p>Phylogenetic tree and chromosomal localization analysis of 6 Hsp subfamilies. (<b>A</b>) Phylogenetic tree illustrating relationships among 192 Hsps. (<b>B</b>) Chromosomal distribution of 192 <span class="html-italic">Hsp</span> genes. The scale on the left is chromosome physical distance.</p>
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<p>Gene structure of 192 <span class="html-italic">Hsp</span> genes in rice. (<b>A</b>–<b>F</b>) Gene structure depicting <span class="html-italic">sHsp</span>, <span class="html-italic">Hsp40</span>, <span class="html-italic">Hsp60</span>, <span class="html-italic">Hsp70</span>, <span class="html-italic">Hsp90</span>, and <span class="html-italic">Hsp100</span>. CDS indicates coding sequence for protein; UTR denotes untranslated region. The scale is the number of gene bases.</p>
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<p>Expression pattern of 15 <span class="html-italic">Hsp</span> genes and subcellular localization analysis of 15 Hsp proteins. (<b>A</b>) The relative expression levels of 15 <span class="html-italic">Hsps</span> in roots, stems, leaves, panicles, and seeds at 5, 10, 15, 20, and 25 days after flowering. The heat map shows the expression level determined by TBtools-II (<a href="https://github.com/CJ-Chen/TBtools-II" target="_blank">https://github.com/CJ-Chen/TBtools-II</a>, (accessed on 31 March 2024)); the range of blue to red indicates the expression levels from low to high. Clustering is according to the expression level in each tissue. (<b>B</b>–<b>E</b>) Subcellular localization of Hsp proteins. Free green fluorescent protein (GFP) and full-length Hsp fusion proteins (Hsp-GFP) were transiently expressed in rice protoplasts. Hsp60-11-GFP co-localized with the chloroplast autofluorescence, Hsp16.9A and DjB7 localized in the cytoplasm (<b>B</b>). mtHsp70-1 and mtHsp70-3 co-localized with mitochondria, and the yellow signal represents the mitochondria dyed by Mito-Tracker Red (<b>C</b>). DjB6, DjC43, DjC79, Hsp110-2, Hsp110-8, Hsp90-1, and Hsp90-4 co-localized with HDEL-mCherry signals of the endoplasmic reticulum (<b>D</b>). cHsp70-6, cHsp70-7 and Hsp110-7 co-localized with the cytoplasm and DAPI signals of the nucleus (<b>E</b>). Scale bars, 5 μm.</p>
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<p>The induced expression levels of 15 <span class="html-italic">Hsp</span> genes in the seedlings of ZH11 under different stresses. ZH11-CK represents the normal seedlings as control with no treatment. HT-10min and HT-60min represent the seedlings that were moved to a high temperature of 42 °C from normal temperature for 10 and 60 min. HT-6h-Rec represents the seedlings that recovered at a normal temperature for 6 h after 60 min of heat shock. LT-6h represents the seedlings that were treated at 5 °C for 6 h. NaCl-6h represents the seedlings that were treated with high salt stress for 6 h (100 mmol/L NaCl). PEG6000-6h represents the seedlings that were treated at 20% PEG stress for 6 h. The expression levels of <span class="html-italic">Hsps</span> were detected in the above treated seedlings and ZH11-CK. Data are means ± SD (n = 3). Different letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05 by ANOVA and Duncan’s test.</p>
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<p>Grain size- and yield-related traits of ZH11 and the <span class="html-italic">hsp</span> mutants. (<b>A</b>–<b>C</b>) Comparison of the grain length (<b>A</b>), grain width (<b>B</b>), and grain thickness (<b>C</b>) of ZH11 and <span class="html-italic">hsp</span> mutants; scale bars = 1 cm. (<b>D</b>–<b>I</b>) Grain length (<b>D</b>), grain width (<b>E</b>), grain thickness (<b>F</b>), 1000-grain weight (<b>G</b>), seed setting rate (<b>H</b>), and yield per plant (<b>I</b>) of ZH11 and the mutants. The investigated plants were grown in natural high-temperature conditions in fields in Hangzhou in 2023. Data are means ± SD; n = 20 in (<b>D</b>–<b>F</b>), n = 3 in (<b>G</b>), and n = 10 in (<b>H</b>,<b>I</b>), and no less than 200 grains per replication in (<b>G</b>). Asterisks show statistical significance between the WT and the mutants, as determined by Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Grain quality of ZH11 and <span class="html-italic">hsp</span> mutants under natural high temperature in the Hangzhou field in 2023. (<b>A</b>) Appearance of mature grains of ZH11 and 15 <span class="html-italic">hsp</span> mutants. Scale bars = 1 cm. (<b>B</b>,<b>C</b>) Chalkiness rate and chalkiness degree of ZH11 and 15 <span class="html-italic">hsp</span> mutants grains. (<b>D</b>–<b>F</b>) Total starch, amylose, and total protein contents of ZH11 and the mutant grains. Data are means ± SD (n = 3); no less than 200 grains per replication in (<b>B</b>,<b>C</b>). Asterisks show the statistical significance between the WT and the mutants, as determined by Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>The expression levels of starch synthesis-related genes in developing endosperm of the wild type (WT) and 7 mutants (<span class="html-italic">hsp16.9a</span>, <span class="html-italic">chsp70-6</span>, <span class="html-italic">chsp70-7</span>, <span class="html-italic">hsp110-7</span>, <span class="html-italic">hsp110-8</span>, <span class="html-italic">djc79</span>, and <span class="html-italic">hsp90-4</span>). (<b>A</b>–<b>G</b>) The relative expression level of starch synthesis-related genes in endosperm at 10d after flowering under natural high temperature in the Hangzhou field in 2023. The data presented here are the relative expression levels of the genes that are expressed differently between mutants and the wild type. The rice UBIQUITIN gene was used as the internal control. Data are means ± SD of three individual replicates. Asterisks show the statistical significance between the WT and the mutants, as determined by Student’s <span class="html-italic">t</span>-test (** <span class="html-italic">p</span> &lt; 0.01).</p>
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34 pages, 3816 KiB  
Review
The Yin and Yang of Microglia-Derived Extracellular Vesicles in CNS Injury and Diseases
by Mousumi Ghosh and Damien D. Pearse
Cells 2024, 13(22), 1834; https://doi.org/10.3390/cells13221834 - 6 Nov 2024
Viewed by 2010
Abstract
Microglia, the resident immune cells of the central nervous system (CNS), play a crucial role in maintaining neural homeostasis but can also contribute to disease and injury when this state is disrupted or conversely play a pivotal role in neurorepair. One way that [...] Read more.
Microglia, the resident immune cells of the central nervous system (CNS), play a crucial role in maintaining neural homeostasis but can also contribute to disease and injury when this state is disrupted or conversely play a pivotal role in neurorepair. One way that microglia exert their effects is through the secretion of small vesicles, microglia-derived exosomes (MGEVs). Exosomes facilitate intercellular communication through transported cargoes of proteins, lipids, RNA, and other bioactive molecules that can alter the behavior of the cells that internalize them. Under normal physiological conditions, MGEVs are essential to homeostasis, whereas the dysregulation of their production and/or alterations in their cargoes have been implicated in the pathogenesis of numerous neurodegenerative diseases, including Alzheimer’s disease (AD), Parkinson’s disease (PD), multiple sclerosis (MS), spinal cord injury (SCI), and traumatic brain injury (TBI). In contrast, MGEVs may also offer therapeutic potential by reversing inflammation or being amenable to engineering for the delivery of beneficial biologics or drugs. The effects of MGEVs are determined by the phenotypic state of the parent microglia. Exosomes from anti-inflammatory or pro-regenerative microglia support neurorepair and cell survival by delivering neurotrophic factors, anti-inflammatory mediators, and molecular chaperones. Further, MGEVs can also deliver components like mitochondrial DNA (mtDNA) and proteins to damaged neurons to enhance cellular metabolism and resilience. MGEVs derived from pro-inflammatory microglia can have detrimental effects on neural health. Their cargo often contains pro-inflammatory cytokines, molecules involved in oxidative stress, and neurotoxic proteins, which can exacerbate neuroinflammation, contribute to neuronal damage, and impair synaptic function, hindering neurorepair processes. The role of MGEVs in neurodegeneration and injury—whether beneficial or harmful—largely depends on how they modulate inflammation through the pro- and anti-inflammatory factors in their cargo, including cytokines and microRNAs. In addition, through the propagation of pathological proteins, such as amyloid-beta and alpha-synuclein, MGEVs can also contribute to disease progression in disorders such as AD and PD, or by the transfer of apoptotic or necrotic factors, they can induce neuron toxicity or trigger glial scarring during neurological injury. In this review, we have provided a comprehensive and up-to-date understanding of the molecular mechanisms underlying the multifaceted role of MGEVs in neurological injury and disease. In particular, the role that specific exosome cargoes play in various pathological conditions, either in disease progression or recovery, will be discussed. The therapeutic potential of MGEVs has been highlighted including potential engineering methodologies that have been employed to alter their cargoes or cell-selective targeting. Understanding the factors that influence the balance between beneficial and detrimental exosome signaling in the CNS is crucial for developing new therapeutic strategies for neurodegenerative diseases and neurotrauma. Full article
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<p>The function of microglial exosomes is influenced by the phenotypic state of the parent cell. Exosomal vesicles released from anti-inflammatory microglia are depicted in green, representing their neuroprotective and pro-regenerative roles (indicated by green arrows). In contrast, EVs derived from pro-inflammatory microglia are shown in red, indicating their association with heightened neuroinflammation, cell death and neurodegenerative conditions (indicated by red arrows).</p>
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<p>Biogenesis of exosomal vesicles.</p>
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<p>miRNA-driven beneficial roles of microglial exosomes in the CNS.</p>
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<p>Detrimental effects of EVs released from pro-inflammatory microglia.</p>
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<p>Critical steps for translating microglial exosomes from bench to bedside.</p>
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27 pages, 6291 KiB  
Review
Endoplasmic Reticulum Stress in Bronchopulmonary Dysplasia: Contributor or Consequence?
by Tzong-Jin Wu, Michelle Teng, Xigang Jing, Kirkwood A. Pritchard, Billy W. Day, Stephen Naylor and Ru-Jeng Teng
Cells 2024, 13(21), 1774; https://doi.org/10.3390/cells13211774 - 26 Oct 2024
Viewed by 1381
Abstract
Bronchopulmonary dysplasia (BPD) is the most common complication of prematurity. Oxidative stress (OS) and inflammation are the major contributors to BPD. Despite aggressive treatments, BPD prevalence remains unchanged, which underscores the urgent need to explore more potential therapies. The endoplasmic reticulum (ER) plays [...] Read more.
Bronchopulmonary dysplasia (BPD) is the most common complication of prematurity. Oxidative stress (OS) and inflammation are the major contributors to BPD. Despite aggressive treatments, BPD prevalence remains unchanged, which underscores the urgent need to explore more potential therapies. The endoplasmic reticulum (ER) plays crucial roles in surfactant and protein synthesis, assisting mitochondrial function, and maintaining metabolic homeostasis. Under OS, disturbed metabolism and protein folding transform the ER structure to refold proteins and help degrade non-essential proteins to resume cell homeostasis. When OS becomes excessive, the endogenous chaperone will leave the three ER stress sensors to allow subsequent changes, including cell death and senescence, impairing the growth potential of organs. The contributing role of ER stress in BPD is confirmed by reproducing the BPD phenotype in rat pups by ER stress inducers. Although chemical chaperones attenuate BPD, ER stress is still associated with cellular senescence. N-acetyl-lysyltyrosylcysteine amide (KYC) is a myeloperoxidase inhibitor that attenuates ER stress and senescence as a systems pharmacology agent. In this review, we describe the role of ER stress in BPD and discuss the therapeutic potentials of chemical chaperones and KYC, highlighting their promising role in future therapeutic interventions. Full article
(This article belongs to the Special Issue Endoplasmic Reticulum Stress Signaling Pathway: From Bench to Bedside)
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Figure 1
<p>Endoplasmic reticulum (ER) stress or unfolded protein response (UPR). Stress distorting correct protein folding in the ER can elicit the ER stress response. Basal ER stress will upregulate the synthesis of the endogenous chaperone (BiP/GRP78) that assists protein refolding. Basal ER stress also inhibits the synthesis of non-essential proteins or degrades them so that raw material can be generated to synthesize essential proteins. The basal ER stress response is a survival mechanism for cells (left panel). If, however, the stress is overwhelming, BiP/GRP78 will all leave the ER stress sensors (IRE1α, PERK, and ATF6) to cope with the unfolded proteins. The protein refolding will generate reactive oxygen species that aggravate oxidative stress (OS) and lead to cell death. AMP: adenosine monophosphate; BiP: binding immunoglobulin protein; GRP78: glucose-regulated protein 78; IRE1α: inositol-requiring enzyme 1α; PERK: protein kinase R-like ER kinase; ATF6: activating transcription factor 6; cATF6: cleaved ATF6; mROS: reactive oxygen species from mitochondria; Cyt-C: cytochrome C; Casp 3/7: caspase 3 and 7; CHOP: C/EBP homologous protein; XBP1: X-box binding protein 1 (XBP1); sXBP1: split XBP1.</p>
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<p>ER stress-associated responses that negatively affect angiogenesis. The ER intimately assists mitochondrial function in normal conditions and adequately processes protein post-translation modifications. Adequate oxidative phosphorylation and growth factor receptor function can produce appropriate angiogenesis critical for alveolar formation in neonatal lungs (left panel). Under excessive ER stress, growth factor receptors and substrate transporters cannot be adequately modified. The increased protein refolding generates many reactive oxygen species (ROS). Mitochondria distance themselves from the ER, so the electron transport chain becomes uncoupled, generating ROS. The accumulated OS then results in cell death that releases DAMPs to recruit neutrophils. The sterile inflammation, impaired oxidative phosphorylation, and dysfunctional growth factor receptors culminate in dysangiogenesis and impaired alveolar formation in neonatal lungs. OS: oxidative stress; DAMPs: damage-associated molecular patterns.</p>
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<p>ER stress is detected in BPD lungs. (<b>A</b>) Immunofluorescence stain of phospho-IRE1α (green) and alveolar type 1 cell (AT1, red) shows increased colocalization in human BPD lungs. (<b>B</b>) Immunofluorescence stain of phospho-PERK (green) and AT1 (red) shows increased colocalization in hyperoxia (HOX)-exposed rat pup lungs. (<b>C</b>) Western blots show ER stress markers are upregulated as early as postnatal day 4 (P4). (<b>D</b>) Heatmap of the mRNA expression shows ER stress-related mRNAs increase in HOX-exposed rat pup lungs at P10. (The figure is modified from [<a href="#B16-cells-13-01774" class="html-bibr">16</a>] under the Creative Commons CC BY 4.0 license). *: <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Taurodeoxycholate (TUDC) attenuates the alveolar simplification by HOX and tunicamycin. (<b>A</b>) The decreased radial alveolar counts in HOX rat lungs are increased in the group treated with 100 mg/kg/day TUDC. (<b>B</b>) The decreased radial alveolar counts in 0.1 mg/kg tunicamycin-treated rat lungs are increased in the group treated with TUDC. (The figure is reproduced from [<a href="#B16-cells-13-01774" class="html-bibr">16</a>] under the Creative Commons CC BY 4.0 license.) Bar = 500 µm; *: <span class="html-italic">p</span> &lt; 0.05, n = 5–6.</p>
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<p><span class="html-italic">N</span>-acetyl-lysyltyrosylcysteine amide (KYC) reduces ER stress caused by HOX and tunicamycin injection. (<b>A</b>) All the markers for ER stress in HOX-induced BPD in rat lungs are decreased by a daily KYC injection. (<b>B</b>) All the markers for ER stress in 0.1 mg/kg tunicamycin (TUN)-induced BPD in rat lungs are decreased by a daily injection of 10 mg/kg KYC. (The figure is reproduced from [<a href="#B16-cells-13-01774" class="html-bibr">16</a>] under the Creative Commons CC BY 4.0 license.) *: <span class="html-italic">p</span> &lt; 0.05, n = 6–12.</p>
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<p>Cellular senescence is detected in multiple lung cell types of BPD rat lungs. The p16 (INK4/CDKN2A) antibody detects cellular senescence, the mouse anti-rat RT140 antibody detects AT1 cells, and the mouse anti-rat-endothelial-cell-antigen-1 (RECA-1) antibody detects rat endothelial cells. (<b>A</b>) Immunofluorescence stain shows colocalization of rat BPD lungs’ AT1 stain (red) and p16 stain (green). (<b>B</b>) Colocalization is seen between the AT2 stain (surfactant protein B, red) and p16 (green). (<b>C</b>) Colocalization is seen between endothelial cells and p16. (The figure is reproduced from [<a href="#B21-cells-13-01774" class="html-bibr">21</a>] under permission obtained from the American Thoracic Society.) The arrows indicate specific cells identified.</p>
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<p>The intertwined interaction between inflammation and OS forms the destructive cycle of BPD. Oxidative stress (OS) from oxygen treatment is the initiating event (OS(a)) in BPD, which recruits myeloperoxidase (MPO)-containing myeloid cells (macrophages and neutrophils) to infiltrate the alveolar sacs. MPO released from the myeloid cells then generates hypochlorous acid (HOCl), a potent reactive oxygen species (ROS), as the second source of OS (OS(b)). The unopposed OS perturbates the proteostasis to elicit endoplasmic reticulum (ER) stress with a subsequent third source of OS (OS(c)). The ER stress contributes to cellular senescence or unfolded protein response (UPR) with another wave of OS (OS(d)). The high-mobility group box 1 (HMGB1) from the senescence-associated secretory pattern (SASP) and UPR induce sterile inflammation to perpetuate the inflammatory process and OS. ER stress will inhibit the glycosylation of vascular-endothelial-cell-growth-factor receptor 2 (VEGFR<sub>2</sub>) and, with the sterile inflammation, will inhibit angiogenesis in neonatal lungs with poor alveolar formation. (The figure is modified from [<a href="#B9-cells-13-01774" class="html-bibr">9</a>] under the Creative Commons CC BY 4.0 license.) ↑: increase; ↓: decrease.</p>
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