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16 pages, 2568 KiB  
Article
Polystyrene Microplastics Induce Photosynthetic Impairment in Navicula sp. at Physiological and Transcriptomic Levels
by Xi Li, Zunyan Wang, Yiyong Chen and Qi Li
Int. J. Mol. Sci. 2025, 26(1), 148; https://doi.org/10.3390/ijms26010148 - 27 Dec 2024
Abstract
The rising concentration of microplastics (MPs) in aquatic environments poses increasing ecological risks, yet their impacts on biological communities remain largely unrevealed. This study investigated how aminopolystyrene microplastics (PS-NH2) affect physiology and gene expression using the freshwater alga Navicula sp. as [...] Read more.
The rising concentration of microplastics (MPs) in aquatic environments poses increasing ecological risks, yet their impacts on biological communities remain largely unrevealed. This study investigated how aminopolystyrene microplastics (PS-NH2) affect physiology and gene expression using the freshwater alga Navicula sp. as the test species. After exposing Navicula sp. to high PS-NH2 concentrations for 24 h, growth was inhibited, with the most significant effect seen after 48 h. Increasing PS-NH2 concentrations reduced chlorophyll content, maximum photochemical quantum yield (Fv/Fm), and the photochemical quenching coefficient (Qp), while the non-photochemical quenching coefficient (NPQ) increased, indicating a substantial impact on photosynthesis. PS-NH2 exposure, damaged cell membrane microstructures, activated antioxidant enzymes, and significantly increased malondialdehyde (MDA), glutathione peroxidase (GPX), and superoxide dismutase (SOD) activities. Transcriptomic analysis revealed that PS-NH2 also affected the gene expression of Navicula sp. The differentially expressed genes (DEGs) are mainly related to porphyrin and chlorophyll metabolism, carbon fixation in photosynthesis, endocytosis, and glycolysis/gluconeogenesis. Protein–protein interaction (PPI) analysis revealed significant interactions among DEGs, particularly within photosystem II. These findings shed insights into the toxic mechanisms and environmental implications of microplastic interactions with phytoplankton, deepening our understanding of the potential adverse effects of microplastics in aquatic ecosystems. Full article
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Graphical abstract

Graphical abstract
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<p>Effects of varying PS-NH<sub>2</sub> concentrations on <span class="html-italic">Navicula</span> sp. growth inhibition rate: (<b>A</b>) growth inhibition rate; (<b>B</b>–<b>D</b>) dose–response curves at 24 h, 48 h, and 96 h, respectively. “*” denotes statistical significance (<span class="html-italic">p</span> &lt; 0.05) between the experimental and control groups, and data are expressed as mean ± standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Impact of different PS-NH<sub>2</sub> concentrations on <span class="html-italic">Navicula</span> sp. photosynthetic parameters: (<b>A</b>) chlorophyll content; (<b>B</b>) Fv/Fm; (<b>C</b>) NPQ; (<b>D</b>) Qp. “*” indicates a significant difference (<span class="html-italic">p</span> &lt; 0.05) between the experimental and control groups, and data are expressed as mean ± standard error (<span class="html-italic">n</span> = 3).</p>
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<p>Influence of varying PS-NH<sub>2</sub> concentrations on antioxidative enzymes in <span class="html-italic">Navicula</span> sp. (<b>A</b>) TP; (<b>B</b>) MDA; (<b>C</b>) CAT; (<b>D</b>) SOD; (<b>E</b>) GPX. “*” denotes significant differences (<span class="html-italic">p</span> &lt; 0.05) between the experimental and control groups, and data are expressed as mean ± standard error (<span class="html-italic">n</span> = 3).</p>
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<p>(<b>A</b>,<b>B</b>) Volcano plot illustrating DEGs between control and exposure groups. The <span class="html-italic">x</span>-axis displays log<sub>2</sub>FC (fold-change), and the <span class="html-italic">y</span>-axis displays −log<sub>10</sub> (<span class="html-italic">q</span>-value). Red represents significantly upregulated genes, blue represents significantly downregulated genes, gray represents insignificantly expressed genes, with each circle representing one gene. (<b>C</b>) Number of DEGs; (<b>D</b>) Venn diagram depicting common and unique DEGs in response to the two stressors. C: Control group; L: low concentration; H: high concentration.</p>
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<p>Histogram displaying enriched subcategories from GO analysis of DEGs in <span class="html-italic">Navicula</span> sp. after exposure to (<b>A</b>) Low concentration and (<b>B</b>) High concentration of PS-NH<sub>2</sub>. The <span class="html-italic">x</span>-axis presents GO terms related to the main ontologies (biological process, cellular component, and molecular function), while the <span class="html-italic">y</span>-axis indicates the number of genes. C: Control group; L: low concentration; H: high concentration.</p>
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<p>Analysis of protein–protein interactions among differentially abundant genes in <span class="html-italic">Navicula</span> sp. under PS-NH<sub>2</sub> exposure stress. Each node corresponds to the protein encoded by the respective gene, and line thickness indicates data support strength.</p>
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22 pages, 1693 KiB  
Review
Caveolin-Mediated Endocytosis: Bacterial Pathogen Exploitation and Host–Pathogen Interaction
by Dibyasri Barman and Rishi Drolia
Cells 2025, 14(1), 2; https://doi.org/10.3390/cells14010002 - 24 Dec 2024
Viewed by 27
Abstract
Within mammalian cells, diverse endocytic mechanisms, including phagocytosis, pinocytosis, and receptor-mediated endocytosis, serve as gateways exploited by many bacterial pathogens and toxins. Among these, caveolae-mediated endocytosis is characterized by lipid-rich caveolae and dimeric caveolin proteins. Caveolae are specialized microdomains on cell surfaces that [...] Read more.
Within mammalian cells, diverse endocytic mechanisms, including phagocytosis, pinocytosis, and receptor-mediated endocytosis, serve as gateways exploited by many bacterial pathogens and toxins. Among these, caveolae-mediated endocytosis is characterized by lipid-rich caveolae and dimeric caveolin proteins. Caveolae are specialized microdomains on cell surfaces that impact cell signaling. Caveolin proteins facilitate the creation of caveolae and have three members in vertebrates: caveolin-1, caveolin-2, and caveolin-3. Many bacterial pathogens hijack caveolin machinery to invade host cells. For example, the Gram-positive facultative model intracellular bacterial pathogen Listeria monocytogenes exploits caveolin-mediated endocytosis for efficient cellular entry, translocation across the intestinal barrier, and cell–cell spread. Caveolin facilitates the internalization of group A streptococci by promoting the formation of invaginations in the plasma membrane and avoiding fusion with lysosomes, thereby aiding intracellular survival. Caveolin plays a crucial role in internalizing and modulation of host immune responses by Gram-negative bacterial pathogens, such as Escherichia coli K1, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Salmonella enterica serovar Typhimurium. Here, we summarize how bacterial pathogens manipulate the host’s caveolin system to facilitate bacterial entry and movement within and between host cells, to support intracellular survival, to evade immune responses, and to trigger inflammation. This knowledge enhances the intervention of new therapeutic targets against caveolin in microbial invasion and immune evasion processes. Full article
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<p>Schematic depicting the mechanism of <span class="html-italic">L. monocytogenes</span> LAP and caveolin-mediated translocation across the intestinal epithelial barrier and subsequent InlA-mediated internalization across non-phagocytic cells. LAP on <span class="html-italic">L. monocytogenes</span> binds to its host cell surface receptor heat shock protein 60 (Hsp60), inducing endocytosis of tight junction proteins, claudin-1, occludin, and the adherens junction protein E-cadherin via caveolin-1 and MLCK-mediated endocytosis. This disrupts cell junctions, allowing <span class="html-italic">L. monocytogenes</span> to pass through the paracellular spaces. InlA subsequently binds to its receptor E-cadherin at the adherens junctions to mediate transcytosis across the epithelial barrier. In non-phagocytic cells, the bacterial surface protein InlA and InlB interact with E-cadherin and c-met, leading to the cytoskeletal rearrangement via a zipper mechanism that triggers <span class="html-italic">L. monocytogenes</span> internalization through PI3-K activation and caveolin-mediated endocytosis. Figure created using Biorender and adapted from [<a href="#B43-cells-14-00002" class="html-bibr">43</a>].</p>
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<p>Schematic representation of the cell-to-cell spread mechanism of <span class="html-italic">L. monocytogenes</span> in phagocytic and non-phagocytic cells. In phagocytic cells (<b>left</b>), internalized actin protrusions containing <span class="html-italic">L. monocytogenes</span> secrete LLO, which disrupts phosphatidyl serine on the plasma membrane. Both actin protrusions and phosphatidyl serine-positive <span class="html-italic">L. monocytogenes</span> bind to the TIM4 receptor on the host cell surface, which causes internalization of <span class="html-italic">L. monocytogenes</span> via caveolin-mediated endocytosis. In non-phagocytic cells (<b>right</b>), when actin filament-rich protrusions containing the bacteria extend from one cell, they bind to ubiquitinated E-cadherin in adjacent cells. This binding triggers caveolae to form a flattened invagination that wraps around these bacterial protrusions, effectively engulfing them with the help of some core proteins of caveolae, such as Cav-1, Cav-2, a subset of the caveolin-associated proteins (cavin-2 and EHD2), and clathrin-interacting Epsin that assists in bending the membrane to create these invaginations. Figure created using Biorender.</p>
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<p>Schematics depicting the internalization mechanism of <span class="html-italic">P. gingivalis</span> and <span class="html-italic">Leptospira</span> via caveolin-mediated endocytosis. (<b>A</b>) The interaction of the virulent factor RgpA of <span class="html-italic">P. gingivalis</span> with Cav-1 in the host cell facilitates the internalization of <span class="html-italic">P. gingivalis</span> via caveolae. <span class="html-italic">P. gingivalis</span> inhibits the integrity of Mfsd2a, leading to enhanced transcytosis across the blood–brain barrier and increased Cav-1 expression, which induces albumin uptake to the cell (adapted from [<a href="#B89-cells-14-00002" class="html-bibr">89</a>]). (<b>B</b>) Leptospiral species interacts with integrin-β-1 on host cells; it triggers caveolin to form an invagination; and through the caveolae/integrin-b1-PI3K/FAK-microfilament endocytosis pathway, it enters the host cell. To avoid fusion with lysosomes, it forms leptospiral vesicles inside the host cell, and these vesicles recruit Rab5/Rab11 and Sec/Exo-SNARE proteins in endocytic recycling and vesicular transport systems for intracellular migration and finally release from the cells through a SNARE complex-mediated FAK/microfilament/microtubule endocytosis pathway. Figure created using Biorender.</p>
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22 pages, 1150 KiB  
Review
Endosomal Escape and Nuclear Localization: Critical Barriers for Therapeutic Nucleic Acids
by Randall Allen and Toshifumi Yokota
Molecules 2024, 29(24), 5997; https://doi.org/10.3390/molecules29245997 - 19 Dec 2024
Viewed by 268
Abstract
Therapeutic nucleic acids (TNAs) including antisense oligonucleotides (ASOs) and small interfering RNA (siRNA) have emerged as promising treatment strategies for a wide variety of diseases, offering the potential to modulate gene expression with a high degree of specificity. These small, synthetic nucleic acid-like [...] Read more.
Therapeutic nucleic acids (TNAs) including antisense oligonucleotides (ASOs) and small interfering RNA (siRNA) have emerged as promising treatment strategies for a wide variety of diseases, offering the potential to modulate gene expression with a high degree of specificity. These small, synthetic nucleic acid-like molecules provide unique advantages over traditional pharmacological agents, including the ability to target previously “undruggable” genes. Despite this promise, several biological barriers severely limit their clinical efficacy. Upon administration, TNAs primarily enter cells through endocytosis, becoming trapped inside membrane-bound vesicles known as endosomes. Studies estimate that only 1–2% of TNAs successfully escape endosomal compartments to reach the cytosol, and in some cases the nucleus, where they bind target mRNA and exert their therapeutic effect. Endosomal entrapment and inefficient nuclear localization are therefore critical bottlenecks in the therapeutic application of TNAs. This review explores the current understanding of TNA endosomal escape and nuclear transport along with strategies aimed at overcoming these challenges, including the use of endosomal escape agents, peptide-TNA conjugates, non-viral delivery vehicles, and nuclear localization signals. By improving both endosomal escape and nuclear localization, significant advances in TNA-based therapeutics can be realized, ultimately expanding their clinical utility. Full article
(This article belongs to the Section Chemical Biology)
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<p>Uptake and intracellular trafficking of TNAs. Following endocytosis, TNAs become encapsulated inside early endosomes (EE) which undergo maturation to multivesicular bodies (MVBs) and late endosomes (LEs). Non-productive pathways (red) do not permit TNAs to reach their intracellular targets. Such pathways include recycling to the plasma membrane, retention in depot endosomes, or enzymatic degradation in lysosomes. Productive pathways (green) allow the successful escape of TNAs into the cytosol to interact with mRNA targets, or eventually the nucleus when targeting pre-mRNA. A small portion (1–2%) of freely delivery TNAs escape endosomes during trafficking primarily from MVBs and LEs.</p>
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<p>Traditional endosomal escape strategies. (<b>A</b>) Cationic amphiphilic small molecules (CADs) such as chloroquine enter endosomes buffering changes in pH. The resulting proton-sponge effect induces osmotic swelling and endosomal rupture, allowing TNAs to escape. Other small molecules may directly interact with endosomes causing membrane destabilization. (<b>B</b>) Peptide-mediated endosomal escape can be facilitated by biomimetic or cell-penetrating peptides. Interaction between cationic peptides and the anionic endosomal membrane causes fusion, membrane destabilization, or pore formation. (<b>C</b>) Non-viral delivery vehicle-mediated endosomal escape can be achieved using lipid nanoparticles. Cationic or ionizable lipids facilitate fusion with the endosomal membrane, allowing TNA release.</p>
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<p>Alternative strategies to the endosomal escape problem. (1) Direct cytosolic entry of TNAs which can be facilitated by peptide or nanoparticle-mediated delivery. Avoiding endocytosis and subsequent endosomal entrapment allows free translocation to the nucleus. (2) Inhibition of endosomal recycling can be accomplished through small molecules such as NP3.47. Preventing the exocytosis of internalized TNAs provides increased potential for endosomal escape events. (3) Inhibition of endo-Golgi retrograde transport with small molecules such as Retro-1. The mechanism of action remains unclear but may increase the retention of TNAs in endosomes, increasing the probability for escape. (4) Inhibition of endo-lysosomal fusion with molecules such as SH-BC-893. Preventing the degradation of TNAs entrapped in endosomes increases their cytosolic quantity, improving treatment efficacy.</p>
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<p>Mechanism nuclear localization signal (NLS) internalization. TNA-NLS peptide conjugates interact with importin-α and β in the cytosol which facilitate active transport through the nuclear pore complex (NPC). Following nuclear entry, the binding of RanGTP causes the dissociation of the complex. The free TNA-NLS is now capable of binding to target pre-mRNA in the nucleus.</p>
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12 pages, 4744 KiB  
Article
Peptide-Mediated Transport Across the Intact Tympanic Membrane Is Intracellular, with the Rate Determined by the Middle Ear Mucosal Epithelium
by Arwa Kurabi, Yuge Xu, Eduardo Chavez, Vivian Khieu and Allen F. Ryan
Biomolecules 2024, 14(12), 1632; https://doi.org/10.3390/biom14121632 - 19 Dec 2024
Viewed by 392
Abstract
The tympanic membrane forms an impenetrable barrier between the ear canal and the air-filled middle ear, protecting it from fluid, pathogens, and foreign material entry. We previously screened a phage display library and discovered peptides that mediate transport across the intact membrane. The [...] Read more.
The tympanic membrane forms an impenetrable barrier between the ear canal and the air-filled middle ear, protecting it from fluid, pathogens, and foreign material entry. We previously screened a phage display library and discovered peptides that mediate transport across the intact membrane. The route by which transport occurs is not certain, but possibilities include paracellular transport through loosened intercellular junctions and transcellular transport through the cells that comprise the various tympanic membrane layers. We used confocal imaging to resolve the phage’s path through the membrane. Phages were observed in puncta within the cytoplasm of tympanic membrane cells, with no evidence of phages within junctions between epithelial cells. This result indicates that transport across the membrane is transcellular and within vesicles, consistent with the transcytosis process. The trans-tympanic peptide phages display a wide range of transport efficiencies for unknown reasons. This could include variation in tympanic membrane binding, entry into the membrane, crossing the membrane, or exiting into the middle ear. To address this, we titered phages recovered from within the membrane for phages with differing transport rates. We found that differences in the transport rate were inversely related to their presence within the tympanic membrane. This suggests that differences in the transport rate primarily reflect the efficiency of an exocytotic exit from the mucosal epithelium rather than entry into, or passage across, the membrane. Full article
(This article belongs to the Section Cellular Biochemistry)
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<p>The confocal image of trans-TM peptide phage TMT3 within cells in the external epithelium of the TM. The representative confocal image shows the anti-phage antibody (green fluoresce) as uniformly distributed puncta (white arrows) in the cytoplasm of external epithelial TM cells. No phage staining is present in cell nuclei (DAPI, blue) or in junctions between epithelial cells. The actin network (red) forms a detailed filamentous pattern, contributing to the overall cellular morphology.</p>
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<p>Trans-TM phage TMT3 within the central, fibrous layer of the TM. The phage is present as puncta (stained green) within the cytoplasm of elongated connective tissue cells, where it clusters in the perinuclear region and extracellularly (asterisk). Green puncta are excluded mainly from actin networks (stained red) within and outside cells.</p>
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<p>Trans-TM phage TMT3 within cells of the internal mucosal epithelium of the TM. DAPI blue fluorescence highlights the nucleus; red staining: phalloidin to visualize the F-actin. Phage puncta (green) are uniformly distributed in cytoplasm but excluded from nuclei and between cells. Variation in puncta density within different cells is greater than in the external TM epithelium.</p>
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<p>The absence of the control phage (WT) not expressing a peptide within cells of the external epithelium of the TM. The phage alone cannot penetrate the TM. Only M13 phage antibody (green fluorescence) clumps are present on the external TM epithelial surface (yellow arrow). DAPI staining (blue) highlights the cell nuclei, while Phalloidin staining (red) reveals the actin filaments within the cytoskeleton.</p>
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<p>The external epithelium of the TM with no phage applied after immunolabeling for phages. The DAPI-stained nuclei (blue fluorescence) are clearly distinguished from the red actin filaments.</p>
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<p>The recovery of phages from the TM during sequential biopanning to discover trans-TM peptides. (<b>A</b>). The screening strategy consists of sequential selection for TM binding, TM internalization, and entry into the ME. (<b>B</b>). Phage titers are shown from the ten rounds of selection. Three rounds are from selection for TM binding, three from selection for TM internalization, and four from selection for ME entry.</p>
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<p>The relationship of trans-TM phage transport efficiency versus recovery from within the TM. (<b>A</b>). ME recovery of phage after a one-hour incubation on the external TM surface for peptide phage species with three different levels of trans-TM transport efficiency. (<b>B</b>). The recovery of phages from within the TM for each of the identical phage clones, which is inversely related to transport efficiency (<b>A</b>). Phage titers (PFUs) are presented as the mean ± standard deviation (SD) derived from six animals per condition.</p>
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13 pages, 7212 KiB  
Article
Clearance of Intracellular Pathogens with Hyaluronic Acid Nanomicelles Responsive to H2S and pH
by Jun Luo, Hui Huang, Junfeng Jiang, Wenyu Zheng, Peng Chen and Hongjin Bai
Molecules 2024, 29(24), 5971; https://doi.org/10.3390/molecules29245971 - 18 Dec 2024
Viewed by 251
Abstract
Hyaluronic acid (HA) is an acidic mucopolysaccharide of animal origin composed of repeating disaccharide units of N-acetylglucosamine and glucuronic acid. Due to its excellent biocompatibility, biodegradability, and selective affinity for CD44 receptors on cell surfaces, HA is widely employed as a drug carrier. [...] Read more.
Hyaluronic acid (HA) is an acidic mucopolysaccharide of animal origin composed of repeating disaccharide units of N-acetylglucosamine and glucuronic acid. Due to its excellent biocompatibility, biodegradability, and selective affinity for CD44 receptors on cell surfaces, HA is widely employed as a drug carrier. In our study, we aimed to target subcellular bacteria by grafting cystamine onto HA scaffolds through an amide reaction, producing a linker responsive to H2S and pH changes. Subsequently, hydrophobic dodecylamine was attached to HA, forming amphiphilic molecules. These amphiphilic entities can self-assemble into nanomicelles in an aqueous solution, thereby encapsulating the antibacterial agent triclosan (TCS). The resulting HA-based system (HASS-TCS) can be internalized via CD44-mediated endocytosis, releasing substantial amounts of streptomycin and TCS in H2S-rich and acidic environments. Additionally, HASS-TCS has demonstrated effectiveness in eradicating biofilms and addressing intracellular infections caused by Salmonella. This study underscores a novel pH-sensitive hyaluronic acid-based drug delivery system with significant potential for the effective treatment of intracellular infections. Full article
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<p>Schematic diagram of HASS synthesis route and loaded TCS.</p>
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<p><sup>1</sup>H NMR spectra of blank HASS nanomicelles. Samples were dissolved in deuterium, and the spectrum was acquired at room temperature using a Bruker AM 500 spectrometer, a–h represent the positions of different H in the nuclear magnetic spectrum of the synthesized material.</p>
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<p>Characterization of both the blank HASS nanomicelles and HASS-TCS nanomicelles includes several key analyses. (<b>A</b>) The correlation between the blank HASS nanomicelles and surface tension at varying concentrations is examined. (<b>B</b>) Scanning electron microscopy (SEM) images illustrate the structure of the synthesized blank HASS nanomicelles alongside the drug-loaded HASS-TCS nanomicelles. (<b>C</b>) The average particle size distribution of both the blank HASS nanomicelles and drug-loaded HASS-TCS nanomicelles is assessed using dynamic light scattering (DLS). (<b>D</b>) The zeta potential measurements for the blank HASS nanomicelles and drug-loaded HASS-TCS nanomicelles are also reported.</p>
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<p>Release curves of Strep (<b>A</b>) and TCS (<b>B</b>) in HASS-TCS nanomicelles under different buffering environments.</p>
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<p>Cell viability of RAW264.7 cells cultured with blank HASS nanomicelles (<b>A</b>) (8.7% Strep) and HASS-TCS nanomicelles (<b>B</b>) (8.7% Strep, 13.2% TCS) of different concentrations for 48 h.</p>
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<p>Functional assessment of the HASS-TCS nanomicelles: (<b>A</b>) Efficacy of the HASS-TCS nanomicelles in biofilm clearance. (<b>B</b>) The capability of HASS-TCS nanomicelles to eradicate intracellular bacteria. (<b>C</b>) Changes in fluorescence intensity within cells post-blockade of the CD44 receptor with hyaluronic acid (HA). (<b>D</b>) Fluorescence microscopy image demonstrating the disruption of <span class="html-italic">Salmonella Typhimurium</span> biofilms by the HASS-TCS nanomicelles. (<b>E</b>) Fluorescence microscopy images displaying the intracellular content of <span class="html-italic">Salmonella Typhimurium</span>. RAW264.7 cells infected with <span class="html-italic">Salmonella Typhimurium</span> were treated with HASS-TCS nanomicelles containing 8.7% streptomycin (Strep) and 13.2% triclosan (TCS), as well as equal concentrations of TCS, Strep, and their combination (Strep + TCS). Treatment was conducted at a micelle concentration of 200 µg/mL for 24 h. The presented data are averages from three independent experiments. “*” indicates (<span class="html-italic">p</span> &lt; 0.05); “***” indicates (<span class="html-italic">p</span> &lt; 0.001).</p>
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13 pages, 1901 KiB  
Article
A Novel Pot-Economy Approach to the Synthesis of Triantennary GalNAc-Oligonucleotide
by Artem Evgenievich Gusev, Vladimir Nikolaevich Ivanov, Nikolai Andreevich Dmitriev, Aleksandr Viktorovich Kholstov, Vladislav Aleksandrovich Vasilichin, Ilya Andreevich Kofiadi and Musa Rakhimovich Khaitov
Molecules 2024, 29(24), 5959; https://doi.org/10.3390/molecules29245959 - 17 Dec 2024
Viewed by 274
Abstract
N-Acetylgalactosamine (GalNAc) is an efficient and multifunctional delivery tool in the development and synthesis of chemically modified oligonucleotide therapeutics (conjugates). Such therapeutics demonstrate improved potency in vivo due to the selective and efficient delivery to hepatocytes in the liver via receptor-mediated endocytosis, which [...] Read more.
N-Acetylgalactosamine (GalNAc) is an efficient and multifunctional delivery tool in the development and synthesis of chemically modified oligonucleotide therapeutics (conjugates). Such therapeutics demonstrate improved potency in vivo due to the selective and efficient delivery to hepatocytes in the liver via receptor-mediated endocytosis, which is what drives the high interest in this molecule. The ways to synthesize such structures are relatively new and have not been optimized in terms of the yields and stages both in lab and large-scale synthesis. Another significant criterion, especially in large-scale synthesis, is to match ecological norms and perform the synthesis in accordance with the Green Chemistry approach, i.e., to control and minimize the amounts of reagents and resources consumed and the waste generated. Here, we provide a robust and resource effective pot-economy method for the synthesis of triantennary GalNAc and GalNAc phosphoramidite/CPG optimized for laboratory scales. Full article
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<p>Standard approach to synthesize GalNAc-L96.</p>
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<p>Standard approach to synthesize GalNAc-L96.</p>
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<p>Standard approach to synthesize GalNAc-L96.</p>
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<p>New approach to synthesize GalNAc-L96. First pot.</p>
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<p>New approach to synthesize GalNAc-L96. Second pot.</p>
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<p>Synthesis of L-96 GalNAc phosphoramidite and L-96 GalNAc CPG.</p>
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<p>Part of synthesis in first pot.</p>
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<p>Part of synthesis in second pot.</p>
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<p>Synthesis of L-96 GalNAc phosphoramidite.</p>
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<p>Synthesis of L-96 GalNAc CPG.</p>
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30 pages, 10385 KiB  
Article
Second-Generation Antipsychotics Induce Metabolic Disruption in Adipose Tissue-Derived Mesenchymal Stem Cells Through an aPKC-Dependent Pathway
by Marco Varalda, Jacopo Venetucci, Herald Nikaj, Chaitanya Reddy Kankara, Giulia Garro, Nazanin Keivan, Valentina Bettio, Paolo Marzullo, Annamaria Antona, Guido Valente, Sergio Gentilli and Daniela Capello
Cells 2024, 13(24), 2084; https://doi.org/10.3390/cells13242084 - 17 Dec 2024
Viewed by 419
Abstract
Metabolic syndrome (MetS) is a cluster of metabolic abnormalities, including visceral obesity, dyslipidemia, and insulin resistance. In this regard, visceral white adipose tissue (vWAT) plays a critical role, influencing energy metabolism, immunomodulation, and oxidative stress. Adipose-derived stem cells (ADSCs) are key players in [...] Read more.
Metabolic syndrome (MetS) is a cluster of metabolic abnormalities, including visceral obesity, dyslipidemia, and insulin resistance. In this regard, visceral white adipose tissue (vWAT) plays a critical role, influencing energy metabolism, immunomodulation, and oxidative stress. Adipose-derived stem cells (ADSCs) are key players in these processes within vWAT. While second-generation antipsychotics (SGAs) have significantly improved treatments for mental health disorders, their chronic use is associated with an increased risk of MetS. In this study, we explored the impact of SGAs on ADSCs to better understand their role in MetS and identify potential therapeutic targets. Our findings reveal that olanzapine disrupts lipid droplet formation during adipogenic differentiation, impairing insulin receptor endocytosis, turnover, and signaling. SGAs also alter the endolysosomal compartment, leading to acidic vesicle accumulation and increased lysosomal biogenesis through TFEB activation. PKCζ is crucial for the SGA-induced nuclear translocation of TFEB and acidic vesicle formation. Notably, inhibiting PKCζ restored insulin receptor tyrosine phosphorylation, normalized receptor turnover, and improved downstream signaling following olanzapine treatment. This activation of PKCζ by olanzapine is driven by increased phosphatidic acid synthesis via phospholipase D (PLD), following G protein-coupled receptor (GPCR) signaling activation. Overall, olanzapine and clozapine disrupt endolysosomal homeostasis and insulin signaling in a PKCζ-dependent manner. These findings highlight SGAs as valuable tools for uncovering cellular dysfunction in vWAT during MetS and may guide the development of new therapeutic strategies to mitigate the metabolic side effects of these drugs. Full article
(This article belongs to the Special Issue Adipose Tissue, Obesity, and Metabolic Diseases)
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Figure 1
<p>Assessment of olanzapine and clozapine cytotoxic activity in ADSCs. Viabilities of ADSCs treated with scalar doses of drugs for 72 h; IC50, i.e., we calculated the drug concentration reduced by 50% in terms of viability compared to the control (<b>a</b>). Bar graphs showing cell viability after 7 days of treatment with scalar doses of drugs; viability data are presented as the percentage of viable cells relative to the negative control treated with DMSO. Data are presented as mean ± SEM from three independent experiments (<b>b</b>). **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01; ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001; ****, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 1 Cont.
<p>Assessment of olanzapine and clozapine cytotoxic activity in ADSCs. Viabilities of ADSCs treated with scalar doses of drugs for 72 h; IC50, i.e., we calculated the drug concentration reduced by 50% in terms of viability compared to the control (<b>a</b>). Bar graphs showing cell viability after 7 days of treatment with scalar doses of drugs; viability data are presented as the percentage of viable cells relative to the negative control treated with DMSO. Data are presented as mean ± SEM from three independent experiments (<b>b</b>). **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01; ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001; ****, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Olanzapine affects ADSC adipogenic differentiation. Representative images of lipid droplets in ADSC#3 treated with 5 μM olanzapine alone or in combination with WAT-differentiating medium using HCS LipidTox for neutral lipids; nuclei were stained using Hoechst 33342 (<b>a</b>). Bar graphs showing quantification of lipid droplet staining/blue nuclei staining ratio as fold change relative to control in ADSC#3 (<b>b</b>) and ADSC#5 (<b>c</b>); data are expressed as the mean ± SD of a representative experiment out of three independent experiments performed in triplicate. Graphs showing quantification of mean dimension and number of lipid droplets in ADSCs treated with olanzapine and in controls (<b>d</b>–<b>g</b>); data are expressed as the mean ± SD of a representative experiment out of three independent experiments. *, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.05. **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01 ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001. ****, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Olanzapine downregulates insulin signaling. Representative Western blot of ADSC#3 cells after 16-h pretreatment with 5 μM olanzapine and stimulation with insulin (50 ng/mL) for 5, 30, and 60 min; lysates were analyzed for P-INSRβ Y1146, INSRβ, P-AKT T308, P-AKT S473, total AKT, P-ERK T202/Y204, and ERK (<b>a</b>). Bar graphs showing quantification of P-INSRβ Y1142 (<b>b</b>), P-AKT T308 (<b>c</b>), P-AKT S473 (<b>d</b>), and P-ERK T202/Y204 (<b>e</b>) normalized on their respective total proteins and expressed as fold change relative to control. Western blot analysis of immunoprecipitated INSRβ P-Ser in cells stimulated with insulin 50 ng/mL for 15 min (<b>f</b>). Bar graph showing quantification of P-Ser signals normalized on total INSR; densitometry expressed as fold change relative to control (<b>g</b>). Graphs are expressed as the mean ± SD of three independent experiments. *, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.05; **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Olanzapine impairs INSR endocytosis. Western blot analysis showing internalization of biotinylated INSRβ in ADSC#5 treated for 16 h with olanzapine and stimulated with insulin for 15 min: Ts represents total biotinylated proteins on the surface, T0 the surface proteins after quenching of the membrane in unstimulated cells, and T15 the surface proteins after endocytosis (<b>a</b>). Bar graph representative of 3 independent experiments showing quantification of internalized receptor; densitometry is expressed as T15 /Ts ratio normalized on total INSRβ, as fold change relative to control (<b>b</b>). Representative images of INSRβ localization on ADSC#5 plasma membrane after 16 h olanzapine treatment and 15 min insulin stimulation; INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 488 (green), while actin was stained using phalloidin 546 (<b>c</b>). Bar graphs showing colocalization of INSRβ and actin on ADSC#3 (<b>d</b>) and ADSC#5 (<b>e</b>) plasma membrane expressed as Pearson coefficient; data are expressed as the mean ± SD of 3 independent experiments. Representative images of INSRβ intracellular localization in ADSC#5 treated with olanzapine and in control cells. INSRβ intracellular localization in RAB7-positive late endosomes after 16 h olanzapine treatment and 15 min insulin stimulation; INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 488 (green); RAB7 using anti-RAB7 primary antibody and secondary Alexa Fluor 546 (red) (<b>f</b>). Bar graph showing colocalization of INSRβ and RAB7 expressed as Pearson coefficient (<b>g</b>). Representative images of INSRβ localization in CD 63-positive exocytic vesicles after 16 h olanzapine treatment and 15 min insulin stimulation; INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 488 (green); CD63 using anti-CD63 primary antibody and secondary Alexa Fluor 546 (red) (<b>h</b>). Bar graph showing colocalization of INSRβ and CD63 expressed as Pearson coefficient (<b>i</b>). Representative images of INSR localization in lysosomes after 16 h olanzapine treatment and 15 min insulin stimulation. INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 488 (green); LAMP1 using anti-LAMP1 primary antibody and secondary Alexa Fluor 546 (red) (<b>j</b>). Bar graph showing colocalization of INSRβ and LAMP1 expressed as Pearson coefficient (<b>k</b>). Results are expressed as the mean ± SD of three independent experiments. White boxes indicates zoom area, white arrows indicates colocalization spots. *, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.05; **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01; ****, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 4 Cont.
<p>Olanzapine impairs INSR endocytosis. Western blot analysis showing internalization of biotinylated INSRβ in ADSC#5 treated for 16 h with olanzapine and stimulated with insulin for 15 min: Ts represents total biotinylated proteins on the surface, T0 the surface proteins after quenching of the membrane in unstimulated cells, and T15 the surface proteins after endocytosis (<b>a</b>). Bar graph representative of 3 independent experiments showing quantification of internalized receptor; densitometry is expressed as T15 /Ts ratio normalized on total INSRβ, as fold change relative to control (<b>b</b>). Representative images of INSRβ localization on ADSC#5 plasma membrane after 16 h olanzapine treatment and 15 min insulin stimulation; INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 488 (green), while actin was stained using phalloidin 546 (<b>c</b>). Bar graphs showing colocalization of INSRβ and actin on ADSC#3 (<b>d</b>) and ADSC#5 (<b>e</b>) plasma membrane expressed as Pearson coefficient; data are expressed as the mean ± SD of 3 independent experiments. Representative images of INSRβ intracellular localization in ADSC#5 treated with olanzapine and in control cells. INSRβ intracellular localization in RAB7-positive late endosomes after 16 h olanzapine treatment and 15 min insulin stimulation; INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 488 (green); RAB7 using anti-RAB7 primary antibody and secondary Alexa Fluor 546 (red) (<b>f</b>). Bar graph showing colocalization of INSRβ and RAB7 expressed as Pearson coefficient (<b>g</b>). Representative images of INSRβ localization in CD 63-positive exocytic vesicles after 16 h olanzapine treatment and 15 min insulin stimulation; INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 488 (green); CD63 using anti-CD63 primary antibody and secondary Alexa Fluor 546 (red) (<b>h</b>). Bar graph showing colocalization of INSRβ and CD63 expressed as Pearson coefficient (<b>i</b>). Representative images of INSR localization in lysosomes after 16 h olanzapine treatment and 15 min insulin stimulation. INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 488 (green); LAMP1 using anti-LAMP1 primary antibody and secondary Alexa Fluor 546 (red) (<b>j</b>). Bar graph showing colocalization of INSRβ and LAMP1 expressed as Pearson coefficient (<b>k</b>). Results are expressed as the mean ± SD of three independent experiments. White boxes indicates zoom area, white arrows indicates colocalization spots. *, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.05; **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01; ****, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Olanzapine and clozapine induce expansion of intracellular acidic compartments and lysosomal biogenesis. Effects of olanzapine and clozapine on intracellular acidic compartments were evaluated by Lysotracker red staining and fluorescence microscopy after 24 h, 72 h, and 7 days of treatment. Nuclei were stained using Hoechst 33342. Representative images of ADSC#3 treated with vehicle (DMSO, negative control), 5 µM olanzapine, or clozapine at different time points (<b>a</b>). Graphs showing quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to control; data are expressed as the mean ± SD of a representative experiment out of three independent experiments performed in triplicate (<b>b</b>,<b>c</b>). Representative image of WB analysis of ADSC#3 after 16 h treatment with SGAs; lysates were analyzed for LC3B, P62, and GAPDH (<b>d</b>). Bar graph showing quantification of the LC3B II/I ratio in ADSC#3 upon chloroquine treatment; densitometric analyses are expressed as the mean ± SD of three independent experiments performed in triplicate (<b>e</b>). Colocalization between LC3B (green) and LAMP1 (red) evaluated in ADSC#3 using confocal microscopy after 16 h treatment with vehicle, olanzapine, or clozapine (<b>f</b>). Histogram showing colocalization LAMP1/LC3B in ADSC#3 expressed as Pearson coefficient (<b>g</b>). Evaluation of intracellular acidic compartments, using Lysotracker red staining, in ADSC#3 cells after 16-h treatment with SGAs alone or in combination with 3-methyladenine (<b>h</b>). Bar graph showing acidic vesicle accumulation in ADSC#3 (<b>i</b>)) and ADSC#5 (<b>j</b>) treated for 16 h with olanzapine and 5 μM clozapine alone or in association with 3-methyladenine (3-MA); data are expressed as quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to negative control. *, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.05; **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01; ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001; ****, <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 5 Cont.
<p>Olanzapine and clozapine induce expansion of intracellular acidic compartments and lysosomal biogenesis. Effects of olanzapine and clozapine on intracellular acidic compartments were evaluated by Lysotracker red staining and fluorescence microscopy after 24 h, 72 h, and 7 days of treatment. Nuclei were stained using Hoechst 33342. Representative images of ADSC#3 treated with vehicle (DMSO, negative control), 5 µM olanzapine, or clozapine at different time points (<b>a</b>). Graphs showing quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to control; data are expressed as the mean ± SD of a representative experiment out of three independent experiments performed in triplicate (<b>b</b>,<b>c</b>). Representative image of WB analysis of ADSC#3 after 16 h treatment with SGAs; lysates were analyzed for LC3B, P62, and GAPDH (<b>d</b>). Bar graph showing quantification of the LC3B II/I ratio in ADSC#3 upon chloroquine treatment; densitometric analyses are expressed as the mean ± SD of three independent experiments performed in triplicate (<b>e</b>). Colocalization between LC3B (green) and LAMP1 (red) evaluated in ADSC#3 using confocal microscopy after 16 h treatment with vehicle, olanzapine, or clozapine (<b>f</b>). Histogram showing colocalization LAMP1/LC3B in ADSC#3 expressed as Pearson coefficient (<b>g</b>). Evaluation of intracellular acidic compartments, using Lysotracker red staining, in ADSC#3 cells after 16-h treatment with SGAs alone or in combination with 3-methyladenine (<b>h</b>). Bar graph showing acidic vesicle accumulation in ADSC#3 (<b>i</b>)) and ADSC#5 (<b>j</b>) treated for 16 h with olanzapine and 5 μM clozapine alone or in association with 3-methyladenine (3-MA); data are expressed as quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to negative control. *, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.05; **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01; ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001; ****, <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>TFEB nuclear localization was investigated using confocal microscopy in ADSC#3 treated for 16 h with a vehicle or olanzapine. TFEB was stained using an anti-TFEB primary antibody and a secondary Alexa Fluor 488 (green), nuclei were stained using DAPI, and actin was stained using phalloidin 546 (<b>a</b>). Bar graph showing quantification of TFEB nuclear localization expressed as TFEB mean fluorescence in nuclear area normalized as fold change relative to control of three independent experiments (<b>b</b>). Representative images of WB analysis of ADSC#3 after 16-h treatment with olanzapine; lysates were analyzed for cathepsin B and GAPDH (<b>c</b>). Bar graph showing quantification of cathepsin B expression normalized on GAPDH. Densitometric analysis is expressed as the mean ± SD of three independent experiments (<b>d</b>). Evaluation of intracellular acidic compartments, using Lysotracker red staining, in ADSC#3 cells after 16-h treatment with SGAs alone or in combination with CHX (<b>e</b>). Bar graph showing acidic vesicle accumulation in cells treated for 16 h with olanzapine (5 µM) and clozapine (5 µM) alone or in the presence of CHX; data are expressed as quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to negative control (<b>f</b>,<b>g</b>). **, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.01; ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001, Student’s <span class="html-italic">t</span>-test ****, <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>PKCζ-dependent expansion of acidic vesicles mediated by SGAs. Western blot analysis of ADSCs treated with 5 μM SGAs for 16 h. Lysates were analyzed for P-(Ser)-PKC substrate, P-PKCζ T560, total PKCζ, and tubulin (<b>a</b>). Confocal microscopy experiments showing P-PKCζ T560 localization in ADSC#3 treated with 5 μM olanzapine for 16 h (<b>b</b>). Bar graph showing quantification of P-PKCζ T560 normalized to cell area; data are expressed as the mean ± SD of three independent experiments (<b>c</b>,<b>d</b>). Evaluation of intracellular acidic compartments, based on Lysotracker red staining, in ADSC#3 cells after 16-h treatment with SGAs alone or in combination with Go6850 or PKCζ inhibitory pseudosubstrate (PS-PKCζ); nuclei were stained using Hoechst 33342 (<b>e</b>). Bar graph showing acidic vesicle quantification in cells treated for 16 h with olanzapine (5 μM) or clozapine (5 μM) alone, or in combination with Go6850 or PS-PKCζ; data are expressed as quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to negative control and expressed as the mean ± SD of a representative experiment out of three independent experiments performed in triplicate (<b>f</b>). Representative images showing acidic vesicle accumulation in ADSC#3 transfected with SiRNA NT and SiRNA PKCζ and treated with olanzapine or clozapine for 16 h; nuclei were stained using Hoechst 33342 (<b>g</b>). Bar graph showing acidic vesicle quantification in ADSC#3 cells silenced for PKCζ and treated for 16 h with olanzapine or clozapine; data are expressed as quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to negative control and expressed as the mean ± SD of a representative experiment out of three independent experiments performed in triplicate (<b>h</b>). Representative images of confocal microscopy analysis of TFEB localization using anti-TFEB primary antibody and Alexa Fluor 488 secondary antibody in ADSC#3 treated with olanzapine alone or in combination with PS-PKCζ (<b>i</b>). Bar graph showing quantification of TFEB nuclear localization expressed as TFEB mean fluorescence in nuclear area normalized as fold change relative to control of three independent experiments (<b>j</b>). ****, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.0001; ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 7 Cont.
<p>PKCζ-dependent expansion of acidic vesicles mediated by SGAs. Western blot analysis of ADSCs treated with 5 μM SGAs for 16 h. Lysates were analyzed for P-(Ser)-PKC substrate, P-PKCζ T560, total PKCζ, and tubulin (<b>a</b>). Confocal microscopy experiments showing P-PKCζ T560 localization in ADSC#3 treated with 5 μM olanzapine for 16 h (<b>b</b>). Bar graph showing quantification of P-PKCζ T560 normalized to cell area; data are expressed as the mean ± SD of three independent experiments (<b>c</b>,<b>d</b>). Evaluation of intracellular acidic compartments, based on Lysotracker red staining, in ADSC#3 cells after 16-h treatment with SGAs alone or in combination with Go6850 or PKCζ inhibitory pseudosubstrate (PS-PKCζ); nuclei were stained using Hoechst 33342 (<b>e</b>). Bar graph showing acidic vesicle quantification in cells treated for 16 h with olanzapine (5 μM) or clozapine (5 μM) alone, or in combination with Go6850 or PS-PKCζ; data are expressed as quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to negative control and expressed as the mean ± SD of a representative experiment out of three independent experiments performed in triplicate (<b>f</b>). Representative images showing acidic vesicle accumulation in ADSC#3 transfected with SiRNA NT and SiRNA PKCζ and treated with olanzapine or clozapine for 16 h; nuclei were stained using Hoechst 33342 (<b>g</b>). Bar graph showing acidic vesicle quantification in ADSC#3 cells silenced for PKCζ and treated for 16 h with olanzapine or clozapine; data are expressed as quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to negative control and expressed as the mean ± SD of a representative experiment out of three independent experiments performed in triplicate (<b>h</b>). Representative images of confocal microscopy analysis of TFEB localization using anti-TFEB primary antibody and Alexa Fluor 488 secondary antibody in ADSC#3 treated with olanzapine alone or in combination with PS-PKCζ (<b>i</b>). Bar graph showing quantification of TFEB nuclear localization expressed as TFEB mean fluorescence in nuclear area normalized as fold change relative to control of three independent experiments (<b>j</b>). ****, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.0001; ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Olanzapine-induced metabolic alterations in ADSCs are PKCζ-dependent. Representative Western blot of ADSC#3 cells after 16 h of pretreatment with 5 µM olanzapine, either alone or in the presence of PS-PKCζ, followed by insulin stimulation (50 ng/mL) for 30 min. Lysates were analyzed for P-INSRβ Y1146 and total INSRβ (<b>a</b>). The bar graph shows the quantification of P-INSRβ Y1146 normalized to total INSRβ, expressed as fold change relative to control; data are presented as mean ± SD from three independent experiments (<b>b</b>). Representative images of ADSC#3 stimulated with insulin (50 ng/mL) following 16-h treatment with 5 μM olanzapine alone or in combination with PKCζ inhibitory pseudosubstrate showing INSRβ localization on the plasma membrane and in late endosomes; INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 546 (red); RAB7 was stained using anti-RAB7 primary antibody and secondary Alexa Fluor 488 (green); and actin was stained using phalloidin 633 (<b>c</b>). Bar graph showing colocalization of INSRβ and actin (<b>d</b>) or RAB7 (<b>e</b>) in ADSC#3 expressed as Pearson coefficient; data are expressed as the mean ± SD of three independent experiments. Bar graph showing colocalization of INSRβ and actin or RAB7 in ADSC#5 expressed as Pearson coefficient; data are expressed as the mean ± SD of three independent experiments (<b>f</b>,<b>g</b>). Representative images of ADSC#3 transfected with siRNA-targeting PKCζ and stimulated with insulin (50 ng/mL) after 16 h of treatment with 5 μM olanzapine. The images show INSRβ localization on the plasma membrane and within late endosomes; INSRβ was stained using anti-INSRβ primary antibody and secondary Alexa Fluor 546 (red); RAB7 was stained using anti-RAB7 primary antibody and secondary Alexa Fluor 488 (green); and actin was stained using phalloidin 633 (<b>h</b>). Bar graph showing colocalization of INSRβ and actin on plasma membrane expressed as Pearson coefficient in ADSC#3 and #5; data are expressed as the mean ± SD of three independent experiments (<b>i</b>,<b>k</b>). Bar graph showing quantification of colocalization of INSRβ with late endosome marker RAB7 expressed as Pearson coefficient in ADSC#3 and #5; results are expressed as the mean ± SD of three independent experiments (<b>j</b>,<b>l</b>). White arrows indicates colocalization spots. *, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.05; ***, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.001; ****, Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>Olanzapine activates PKCζ by modulating GPCR signaling. PA accumulation was analyzed in 3T3L1 cells transfected with Pii-PA (PA indicator with superior sensitivity) DOCK2 (DOCK2-Pii) [<a href="#B34-cells-13-02084" class="html-bibr">34</a>] after 16 h treatment with olanzapine alone or in combination with PLD inhibitor FIPI, EPAC inhibitor CE3F4, and Gq/11 inhibitor YM254890. Representative images of transfected cells treated with DMSO, negative control, 5 μM olanzapine alone or in combination with 750 nM FIPI. Arrows point to dots representing PA accumulation (<b>a</b>). Bar graph quantification of green dots normalized on cell area and expressed as fold change relative to control; results are expressed as the mean ± SD of three independent experiments (<b>b</b>). Bar graphs showing acidic vesicle accumulation in ADSC#3 (<b>c</b>) and ADSC#5 (<b>d</b>) treated for 16 h with olanzapine or clozapine (5 μM) alone or in combination with 750 nM Fipi, 10 μM EPAC inhibitor, 10 μM SQ22, 10 μM Suramin, or 10 μM YM254890; data are expressed as quantification of red Lysotracker staining/blue nuclei staining ratio as fold change relative to negative control and are expressed as the mean ± SD of a representative experiment out of three independent experiments performed in triplicate. Confocal microscopy assessment of P-PKCζ T560 expression in cells treated with 5 μM olanzapine/vehicle alone or in combination with 750 nM Fipi or 10 μM YM254890 for 16 h; phosphorylated PKC was evaluated using P-PKCζ T560 primary antibody and Alexa Fluor 546 secondary antibody, while actin was stained using Phalloidin 633 (<b>e</b>). Bar graph showing quantification of P-PKCζ T560 normalized to cell area; data are expressed as mean ± SD from three independent experiments (<b>f</b>). ** <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 (Student’s <span class="html-italic">t</span>-test).</p>
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<p>Proposed mechanism of olanzapine-induced metabolic disruption. Olanzapine’s effects are mediated by Gαq and Gαs, initiating signaling cascades that activate phospholipase D and PKCζ. PKCζ disrupts insulin signaling and impairs INSR turnover. Through PP2A activation, this leads to TFEB dephosphorylation and nuclear translocation, promoting lysosomal biogenesis. The combined effects of lysosomal accumulation and PKCζ-induced disruption of INSR phosphorylation further impair insulin signaling and INSR turnover. Image created in <a href="https://BioRender.com" target="_blank">https://BioRender.com</a> (accessed on 30 October 2024).</p>
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12 pages, 1482 KiB  
Article
Bovine Lactoferrin Enhances Toll-like Receptor 7 Response in Plasmacytoid Dendritic Cells and Modulates Cellular Immunity
by Takumi Yago, Asuka Tada, Shutaro Kubo, Hirotsugu Oda, Sadahiro Iwabuchi, Miyuki Tanaka and Shinichi Hashimoto
Int. J. Mol. Sci. 2024, 25(24), 13369; https://doi.org/10.3390/ijms252413369 - 13 Dec 2024
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Abstract
Plasmacytoid dendritic cells (pDCs) express Toll-like receptor 7 (TLR7) in the endosomes, recognize viral single-stranded RNA (ssRNA), and produce significant amounts of interferon (IFN)-α. Bovine lactoferrin (LF) enhances the response of IFN regulatory factors followed by the activation of IFN-sensitive response elements located [...] Read more.
Plasmacytoid dendritic cells (pDCs) express Toll-like receptor 7 (TLR7) in the endosomes, recognize viral single-stranded RNA (ssRNA), and produce significant amounts of interferon (IFN)-α. Bovine lactoferrin (LF) enhances the response of IFN regulatory factors followed by the activation of IFN-sensitive response elements located in the promoter regions of the IFN-α gene and IFN-stimulated genes in the TLR7 reporter THP-1 cells in the presence of R-848, a TLR7 agonist. In ex vivo experiments using human peripheral blood mononuclear cells, LF enhances IFN-α levels in the supernatant in the presence of R-848. Additionally, it increases the expression of IFN-α, human leukocyte antigen (HLA)-DR, and CD86 in pDCs; HLA-DR and CD86 in myeloid dendritic cells; CD69 in CD56 dim natural killer and T killer cells; and IFN-γ in T helper type 1 and B cells in the presence of R-848. The inhibition of phagocytosis or neutralization of nucleolin, a receptor of LF, suppresses LF incorporation into pDCs. These results suggest that pDCs incorporate LF through phagocytosis or nucleolin-mediated endocytosis, and LF enhances TLR7 response in the endosome and subsequent IFN signaling pathway and activates innate and adaptive immune cells. We anticipate that LF modulates antiviral immunity against environmental ssRNA viruses and contributes to homeostasis. Full article
(This article belongs to the Special Issue New Insights into Lactoferrin)
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Graphical abstract

Graphical abstract
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<p>Interferon (IFN) regulatory factor (IRF) response followed by activation of IFN-sensitive response element (ISRE) in Toll-like receptor 7 reporter THP-1 cells. After 6 h of incubation in the presence or absence of 100 µg/mL lactoferrin (LF) and 10 µg/mL R-848, IRF response followed by ISRE activation was assessed using a luciferase reporter assay. Values are presented as the mean and standard deviation (SD); Open circles represent individual values. n = 3. Different letters above the bars (a, b, c) indicate significant differences among treatments (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>IFN-α concentration in peripheral blood mononuclear cell (PBMC) culture supernatants. After 24 h incubation of PBMCs with 10 µg/mL R-848 (control) or 10 µg/mL R-848 and 100 µg/mL LF, IFN-α concentration in culture supernatants was measured using an ELISA kit. White bars represent the control group, and gray bars represent the LF-treated group. Values are presented as the mean and SD; Open circles represent individual values. n = 11. * Significantly different from the control group (<span class="html-italic">p</span> &lt; 0.05). LF, lactoferrin.</p>
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<p>Intracellular IFN-α, cell surface human leukocyte antigen (HLA)-DR, and cell surface CD86 expression levels in plasmacytoid dendritic cells (pDCs). After 20–24 h incubation of peripheral blood mononuclear cells with 10 µg/mL R-848 (control) or 10 µg/mL R-848 and 100 µg/mL LF, the expression levels of pDC activity markers, (<b>a</b>) intracellular IFN-α (n = 7), (<b>b</b>) cell surface HLA-DR (n = 4), and (<b>c</b>) cell surface CD86 (n = 4) were measured using flow cytometry. CD123+CD304+ cells are defined as pDCs. White bars represent the control group, and gray bars represent the LF-treated group. Values are presented as the mean and SD. Open circles represent individual values. * Significantly different from the control group (<span class="html-italic">p</span> &lt; 0.05). MFI, geometric mean fluorescence intensity. LF, lactoferrin.</p>
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<p>Expression of activation markers in the immune cells. After 6–24 h incubation of peripheral blood mononuclear cells with 10 µg/mL R-848 (control) or 10 µg/mL R-848 and 100 µg/mL LF, the expression levels of immune cell activity markers were measured using flow cytometry. (<b>a</b>) Cell surface HLA-DR and (<b>b</b>) CD86 in myeloid dendritic cells (mDCs, CD11c+CD123− cells) (n = 4). (<b>c</b>) Intracellular IFN-γ in CD56 bright natural killer (NK) cells (CD3−CD56 bright cells) (n = 3). (<b>d</b>) Cell surface CD69 in CD56 dim NK cells (CD3−CD16+CD56 dim cells) (n = 11). (<b>e</b>) Intracellular IFN-γ in T helper type 1 (Th1) cells (CD3+CD4+CD183+ cells) (n = 7). Cell surface CD69 in (<b>f</b>) T helper cells (CD3+CD4+ cells) (n = 3) and (<b>g</b>) T killer cells (CD3+CD8+ cells) (n = 3). (<b>h</b>) Intracellular IFN-γ in B cells (CD19+ cells) (n = 7). (<b>i</b>) Cell surface CD69 in B cells (CD19+ cells) (n = 3). White bars represent the control group, and gray bars represent the LF-treated group. Values are presented as the mean and SD. Open circles represent individual values. * Significantly different from the control group (<span class="html-italic">p</span> &lt; 0.05). MFI, geometric mean fluorescence intensity; LF, lactoferrin.</p>
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<p>Incorporation of LF into pDCs. (<b>a</b>) Fluorescein isothiocyanate (FITC) fluorescence signals of pDCs, as measured through flow cytometry after 24 h incubation of peripheral blood mononuclear cells with 10 µg/mL R-848 and 100 µg/mL FITC-labeled LF, in the presence or absence of 1 µM cytochalasin D or 5 µg/mL nucleolin-neutralizing antibody. Values are presented as the mean and SD; Open circles represent individual values. n = 3. Different letters above the bars (a, b, c) indicate significant differences among treatments (<span class="html-italic">p</span> &lt; 0.05). (<b>b</b>) Images captured of pDCs, as measured through fluorescence microscopy, after 24 h incubation of isolated pDCs with 10 µg/mL R-848 and 100 µg/mL FITC-labeled LF. Green: FITC-labeled LF; red: pDC membrane surface (CD123); and blue: nuclear staining with Hoechst 33324. Magnification: ×100; scale bar: 10 μm. LF, lactoferrin; pDCs, plasmacytoid dendritic cells.</p>
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19 pages, 4061 KiB  
Article
Discovery of a Small Molecule with an Inhibitory Role for RAB11
by Camille Lempicki, Julian Milosavljevic, Christian Laggner, Simone Tealdi, Charlotte Meyer, Gerd Walz, Konrad Lang, Carlo Cosimo Campa and Tobias Hermle
Int. J. Mol. Sci. 2024, 25(23), 13224; https://doi.org/10.3390/ijms252313224 - 9 Dec 2024
Viewed by 606
Abstract
RAB11, a pivotal RabGTPase, regulates essential cellular processes such as endocytic recycling, exocytosis, and autophagy. The protein was implicated in various human diseases, including cancer, neurodegenerative disorders, viral infections, and podocytopathies. However, a small-molecular inhibitor is lacking. The complexity and workload associated with [...] Read more.
RAB11, a pivotal RabGTPase, regulates essential cellular processes such as endocytic recycling, exocytosis, and autophagy. The protein was implicated in various human diseases, including cancer, neurodegenerative disorders, viral infections, and podocytopathies. However, a small-molecular inhibitor is lacking. The complexity and workload associated with potential assays make conducting large-scale screening for RAB11 challenging. We employed a tiered approach for drug discovery, utilizing deep learning-based computational screening to preselect compounds targeting a specific pocket of RAB11 protein with experimental validation by an in vitro platform reflecting RAB11 activity through the exocytosis of GFP. Further validation included the exposure of Drosophila by drug feeding. In silico pre-screening identified 94 candidates, of which 9 were confirmed using our in vitro platform for Rab11 activity. Focusing on compounds with high potency, we assessed autophagy, which independently requires RAB11, and validated three of these compounds. We further analyzed the dose–response relationship, observing a biphasic, potentially hormetic effect. Two candidate compounds specifically caused a shift in Rab11 vesicles to the cell periphery, without significant impact on Rab5 or Rab7. Drosophila larvae exposed to another candidate compound with predicted oral bioavailability exhibited minimal toxicity, subcellular dispersal of endogenous Rab11, and a decrease in RAB11-dependent nephrocyte function, further supporting an inhibitory role. Taken together, the combination of computational screening and experimental validation allowed the identification of small molecules that modify the function of Rab11. This discovery may further open avenues for treating RAB11-associated disorders. Full article
(This article belongs to the Special Issue Techniques and Strategies in Drug Design and Discovery, 2nd Edition)
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Figure 1

Figure 1
<p>A screening platform for RAB11 and computational drug screening. (<b>a</b>) Schematic shows cycling of RAB proteins between the active state (GTP-bound) that is terminated by support of GAPs by hydrolysis of GTP to GDP, which in turn is displaced by GEFs to allow reactivation by GTP binding. (<b>b</b>) Schematic illustrates the screening platform. HEK293T cells express a secretory GFP that carries an <span class="html-italic">IFNA2</span>-derived signal peptide. Secretion is promoted by RAB11, so that reduction in GFP secretion into the supernatant indicates reduced activity of RAB11. (<b>c</b>,<b>c’</b>) Fluorescence microscopy image of HEK293T cells stably transduced with the secretory GFP shows that all cells are GFP-positive by comparing the nuclear stain (blue) with the green channel. (<b>d</b>) Immunoblotting with anti-GFP using cellular supernatants from different wells with HEK293T cells stably transduced with secretory GFP reveals strong, random variation in GFP positivity between different wells. (<b>e</b>) Transient transfection of HEK293T cells from (<b>c</b>,<b>d</b>) with RAB11-GEF SH3BP5 or empty vector shows strong increase in GFP from the cellular supernatant with activation of RAB11 after immunoblotting. (<b>f</b>) This panel illustrates the target domain on RAB11 used for computational screening. On the left, the structure of RAB11A is shown as a dimer (green) in complex with the effector FIP3 (PBD ID: 2HV8). The enlargement illustrates the binding pocket near GTP (yellow) and two switch regions. The targeted residues are blue. The right side of the panel shows the structure of RAB11B (green, PBD ID: 2F9M) with the binding pocket highlighted in red and overlay of RAB11A/FIP3 complex in yellow (PDB ID 2HV8, active form binding GTP) and the RAB11B/PKG II in magenta (PDB ID 4OJK, inactive form binding GDP) to illustrate the flexibility of the switch region and its interaction with effector proteins. The enlargement illustrates the binding pocket with the targeted residues. (<b>g</b>) The schematic illustrates the deep learning-based computational high-throughput screening using the AtomNet<sup>®</sup> technology (Atomwise Inc., San Francisco, CA, USA). Millions of commercially available compounds are screened virtually against the target structure before the selection of 94 compounds that are purchased for further testing.</p>
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<p>Screening identifies nine hits as inhibiting compounds. (<b>a</b>) Schematic illustrates the work flow of in vitro screening of compounds. (<b>b</b>) Representative Western blot shows GFP bands in the supernatant as an example. GFP is undetectable in control conditions (empty vector) but strongly enhanced after activation of RAB11 by transfection of GFP-<span class="html-italic">SH3BP5</span> with DMSO (vehicle), while compounds reduce secretion of GFP to a variable extent. (<b>c</b>) Quantification of immunoblot for all tested compounds analogous to (<b>b</b>) showing repeat measurements of compounds after censoring four compounds with excessively overshooting GFP secretion. Statistical significance was defined as <span class="html-italic">p</span> &lt; 0.01; individual <span class="html-italic">p</span>-values, see <a href="#app1-ijms-25-13224" class="html-app">Supplementary Table S2</a>. Bars marked in green represent the blinded negative controls. Grey background indicates control, blue background significant increase, red background significant decrease in GFP secretion. Censored: F6, A10, G6, and B10. Significantly activating, from left to right: B2, H9, C5, E6, and F1. Not significant, from left to right: F9, E1, E10, D12, C7, E7, B12, H2, B5, E9, A4, D2, C4, B4, D4, G11, A11, E12, A3, H6, H12 (blinded control 1), D7, B9, F10, A8, A12, G8, G10, A7, E11, F5, F3, G5, E4, B1, D10, D8, F8, G12 (blinded control 2), A2, B8, D11, H10, F11, F4, C9, H8, G4, D9, H7, D3, E2, H5, C11, B3, G3, A6, A9, E8, A5, D1, C12, F7, C8, H4, G7, H11, F12, B7, E3, F2, C3, G2, H1, G1, B11, and C10. Significantly inhibiting, from left to right: D6, G9, E5, B6, C6, H3, C2, D5, and A1. (<b>d</b>) Quantification of immunoblots analogous to (<b>b</b>) of nine compounds with an initially overshooting response show normal or even reduced activity after replicate measurement that did not differ significantly from the control (DMSO, mean ± SD, <span class="html-italic">n</span> = 3–5 per condition, <span class="html-italic">p</span> &gt; 0.05 for all compounds). This suggests unspecific toxicity as the cause of the previously observed excessive response. (<b>e</b>) Quantification of immunoblots analogous to (<b>b</b>) shows selection of nine hits with significant reduction in GFP secretion after censoring overshooting responses (mean ± SD). Statistical significance was defined as <span class="html-italic">p</span> &lt; 0.01; individual <span class="html-italic">p</span>-values, see <a href="#app1-ijms-25-13224" class="html-app">Supplementary Table S2</a>.</p>
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<p>Validation for potency, by detection of basal autophagy and subcellular localization. (<b>a</b>) Representative Western blot stained for secreted GFP in the supernatant at a dose of 5 µM shows variable effects using the lower dose, which is compatible with variable potency. (<b>b</b>) Quantification of immunoblotting using anti-GFP antibody on supernatant from HEK293T cells stably expressing secretory GFP after compound exposure at 5 µM is shown for seven compounds. Two of the nine compounds significant at 20 µM were censored here due to an excessive response. At the lower dose, only compounds B6, C6, D5, and D6 showed a significant reduction, while A1 showed a trend that was not significant (mean ± SD, <span class="html-italic">n</span> = 4–7 per condition, <span class="html-italic">p</span> &lt; 0.05 for D5, <span class="html-italic">p</span> &lt; 0.01 for D6 and C6, <span class="html-italic">p</span> &lt; 0.001 for B6. For the remaining compounds, <span class="html-italic">p</span> &gt; 0.05). (<b>c</b>) Schematic illustrates phagophore formation with activation of LC3-I to LC3II, which marks the autophagosomes. The phagophore elongates to form the mature autophagosome, which in turn fuses with the lysosome. RAB11 promotes both phagophore formation and the lysosomal fusion event. (<b>d</b>,<b>e</b>) Immunoblotting of lysates from HEK293T cells after compound exposure using anti-LC3B reveals a lower band around 15 kDa that reflects the active LC3B that travels faster due to lipidation. Cells have been treated with 80 µM chloroquine for 2 h to show basal autophagic flux. Treatment with compounds B6 and D5 (<b>d</b>) and D6 (<b>e</b>) reduces the lower band that corresponds to LC3-II. (<b>f</b>) Quantification of density of LC3-II/loading control analogous to experiment in (<b>c</b>) is shown for the indicated genotypes. Compounds D5, B6, and D6 show a significant reduction in basal autophagy, suggesting an effect on the activity of RAB11 (mean ± SD, <span class="html-italic">n</span> = 3–10 per condition, <span class="html-italic">p</span> &gt; 0.05 for A1 and C6, <span class="html-italic">p</span> &lt; 0.001 for D6, and <span class="html-italic">p</span> &lt; 0.0001 for B6 and D5). (<b>g</b>) Quantitative analysis of FRET efficiency (FRET ratio) is shown as readout of RAB11A-GTP loading after application of Rab11-inhibitor-D6 at 20 µM for 16 h compared to vehicle does not prevent GTP loading (mean ± SE, <span class="html-italic">n</span> = 53 cells for vehicle and 33 cells for Rab11-inhibitor-D6 condition, <span class="html-italic">p</span> &gt; 0.05). (<b>h</b>) Quantification of the number of Rab5 (left panel), Rab7 (middle panel), and Rab11 (right panel) vesicles per single Cos-7 cell in the peripheral region when treated with either DMSO (vehicle) or D6 or D5 or B6 compounds. Error bars represent mean ± S.E.M. n.s., not significant, <span class="html-italic">p</span> &lt; 0.05 (one-sample Student’s <span class="html-italic">t</span>-test), <span class="html-italic">n</span> = 3 independent experiments.</p>
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<p>Dose–response relationship indicates a hormetic response. (<b>a</b>) Shown is the structure and Simplified Molecular Input Line Entry System (SMILES) string of RAB11-inhibitor D5. (<b>b</b>) The dose–response curve illustrates a bell-shaped relationship between increasing doses of an RAB11-inhibitor-D5 treatment and the corresponding changes in GFP secretion. GFP was evaluated by densitometry after immunoblotting with anti-GFP using our secretory GFP HEK293T cells. The y-axis shows the normalized response of treated cells against the vehicle (DMSO) in percent that is plotted against the dose range in logarithmic scale on the x-axis. The data were fitted using non-linear regression for a biphasic, bell-shaped effect (blue line), with an R-squared value of 0.43. The logEC<sub>50</sub> values were 3.34 µM and 0.27 µM for Rab11-inhibitor-D5 (<span class="html-italic">n</span> = 2–5 per concentration). (<b>c</b>) Shown is the structure and Simplified Molecular Input Line Entry System (SMILES) string of RAB11-inhibitor B6. (<b>d</b>) The dose–response curve illustrates the biphasic relationship between increasing doses of an RAB11-inhibitor-B6 treatment and the corresponding changes in GFP analogous to (<b>b</b>). The data were fitted using non-linear regression for a biphasic, bell-shaped effect (blue line), with an R-squared value of 0.45. The logEC<sub>50</sub> values were determined as 3.34 µM and 0.10 µM for Rab11-inhibitor-B6 (<span class="html-italic">n</span> = 2–5 per concentration). (<b>e</b>) Shown is the structure and Simplified Molecular Input Line Entry System (SMILES) string of RAB11-inhibitor D6. (<b>f</b>) The dose–response curve shows a largely biphasic relationship between increasing doses of an RAB11-inhibitor-D6 treatment and the respective changes in GFP analogous to (<b>b</b>). The data were fitted using non-linear regression for a biphasic effect (blue line), with an R-squared value of 0.30. The resultant logEC<sub>50</sub> values were 2.73 and 1.83 µM for Rab11-inhibitor-D6 (<span class="html-italic">n</span> = 2–5 per concentration). (<b>g</b>) Quantification of immunoblotting using anti-GFP antibody on supernatant from HEK293T cells stably expressing secretory GFP after compound exposure at 1.25 µM is shown. There is a trend towards increased secretion that is statistically not significant for RAB11-inhibitor-B6 and RAB11-inhibitor-D5 and a statistically significant increase for RAB11-inhibitor-D6 (mean ± SD, <span class="html-italic">n</span> = 6–8 per genotype, <span class="html-italic">p</span> &gt; 0.05 for RAB11-inhibitor-B6 and RAB11-inhibitor-D5, <span class="html-italic">p</span> &lt; 0.001 for RAB11-inhibitor-D6).</p>
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<p>RAB11-inhibitors show no significant toxicity in vitro. (<b>a</b>–<b>e</b>) Immortalized podocytes were exposed to the respective compounds each at a concentration of 20 µM for 24 h preceding Annexin V/propidium iodide exposure and flow cytometry. Representative original dot plots (left) are shown for the indicated conditions. Green fluorescence indicates FITC-Annexin (apoptotic cells bottom right section in green) while red fluorescence represents propidium iodide (dead cells, upper left section in red). Cells negative for either cell death marker (bottom left section in red) or double positive cells (upper right section in blue) are shown as well. Corresponding histograms for green fluorescence under these conditions are displayed on the right. Elevated Annexin positivity compared to control (<b>b</b>) is observed for Doxorubicin (Adriamycin, panel a), but not for the novel inhibitors of RAB11 (<b>c</b>–<b>e</b>). (<b>f</b>) Quantification of data analogous to a-e (mean ± SD, <span class="html-italic">n</span> = 4, <span class="html-italic">p</span> &lt; 0.0001 for Adriamycin compared to control, <span class="html-italic">p</span> &gt; 0.05 for all RAB11-inhibitors).</p>
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<p>Drug exposure in <span class="html-italic">Drosophila</span> larvae confirms low toxicity and Rab11 inhibition by morphological and functional criteria. (<b>a</b>) Representative image showing <span class="html-italic">Drosophila</span> third instar larvae from a <span class="html-italic">Drosophila</span> strain similar to wild-type (yw<sup>1118</sup>) that are being exposed to RAB11-inhibitors or vehicle (DMSO) using 96-well plates and liquid food. (<b>b</b>) Quantification of surviving larvae after 24 h of drug exposure analogous to (<b>a</b>) as indicated by movement and feeding upon inspection, (<span class="html-italic">n</span> = 100 larvae per genotype). (<b>c</b>,<b>d</b>) Confocal images of garland cell nephrocytes stained for the slit diaphragm protein Pyd are shown after RAB11-inhibitor-D6 feeding (<b>d</b>) or DMSO control (<b>c</b>). (<b>e</b>–<b>h</b>) Representative confocal images of nephrocytes stained for RAB11 show increasing dispersal of Rab11 upon drug feeding and reflect four categories used for quantification (1: strong vesicular signal, low background, 2: strong vesicular signal, high background, 3: weak vesicular signal high background, 4: high background only). (<b>i</b>) Blinded quantification of data analogous to e-f using Chi-squared test (comparing two groups, categories 1 + 2 vs. 3 + 4) indicates a strong shift towards dispersal of RAB11 upon exposure to RAB11-inhibitor-D6 (<span class="html-italic">n</span> = 20 animals per genotype, <span class="html-italic">p</span> &lt; 0.05). (<b>j</b>) FITC-albumin endocytosis as an assay of nephrocyte function is shown after exposure for 30 s and wash out of 5 min. Exposing larvae to Rab11-inhibitor-D6 in liquid food for 24 h strongly reduces uptake of FITC-albumin compared with the control (DMSO). (<b>k</b>) Quantification of results as average of the three brightest individual cells per animal from (<b>j</b>) in ratio to a control experiment performed in parallel (mean ± SD, <span class="html-italic">n</span> = 10–12 animals per genotype, <span class="html-italic">p</span> &lt; 0.01 for exposure with Rab11-inhibitor-D6).</p>
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28 pages, 4920 KiB  
Article
Interactions of VMAT2 with CDCrel-1 and Parkin in Methamphetamine Neurotoxicity
by Heli Chauhan, Nicholas J. Carruthers, Paul M. Stemmer, Bernard L. Schneider and Anna Moszczynska
Int. J. Mol. Sci. 2024, 25(23), 13070; https://doi.org/10.3390/ijms252313070 - 5 Dec 2024
Viewed by 344
Abstract
In recent years, methamphetamine (METH) misuse in the US has been rapidly increasing, and there is no FDA-approved pharmacotherapy for METH use disorder (MUD). In addition to being dependent on the drug, people with MUD develop a variety of neurological problems related to [...] Read more.
In recent years, methamphetamine (METH) misuse in the US has been rapidly increasing, and there is no FDA-approved pharmacotherapy for METH use disorder (MUD). In addition to being dependent on the drug, people with MUD develop a variety of neurological problems related to the toxicity of this drug. A variety of molecular mechanisms underlying METH neurotoxicity has been identified, including the dysfunction of the neuroprotective protein parkin. However, it is not known whether parkin loss of function within striatal dopaminergic (DAergic) terminals translates into decreased DA storage capacity. This study examined the relationship between parkin, its substrate cell division cycle related-1 (CDCrel-1) associated with synaptic vesicles, and vesicular monoamine transporter-2 (VMAT2) responsible for packaging DA in an in vivo model of METH neurotoxicity. To assess the individual differences in response to METH’s neurotoxic effects, a large group of male Sprague Dawley rats were treated with binge METH or saline and sacrificed 1 h or 24 h later. This study is the first to show that CDCrel-1 interacts with VMAT2 in the rat striatum and that binge METH can alter this interaction as well as the levels and subcellular localization of CDCrel-1. The proteomic analysis of VMAT-2-associated proteins revealed the upregulation of several proteins involved in the exocytosis/endocytosis cycle and responses to stress. The results suggest that DAergic neurons are engaged in counteracting METH-induced toxic effects, including attempts to increase endocytosis and autophagy at 1 h after the METH binge, with the responses varying widely between individual rats. Studying CDCrel-1, VMAT2, and other proteins in large groups of outbred rats can help define individual genetic and molecular differences in responses to METH neurotoxicity, which, in turn, may aid treating humans suffering from MUD and its neurological consequences. Full article
(This article belongs to the Special Issue Mechanisms of Neurotoxicity)
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Figure 1

Figure 1
<p>Experimental design and assessment of METH neurotoxicity. (<b>a</b>) A total of 8.0 mg/kg free base METH or saline (1 mL/kg) was administered to rats every 2 h in four successive intraperitoneal (i.p.) injections. Core body temperatures (°C) were measured before the first METH or saline injection and 1 h after each METH or saline injection. The rats were sacrificed 1 h or 24 h after the last injection of METH or saline. Stratal synaptosomes were isolated, separated into total, membrane/endosomal, and vesicular/cytosolic fractions, and analyzed. Proteomic analysis was performed on VMAT2-associated proteins coimmunoprecipitated from membrane/endosomal fractions. (<b>b</b>,<b>c</b>) Core body temperatures of rats euthanized at 1 h (<b>b</b>) or 24 h (<b>c</b>) after METH or saline. (<b>d</b>,<b>e</b>) The METH-treated rats were divided into two groups depending on the severity of hyperthermia: those with high hyperthermia and those with low hyperthermia (average of 4 temperature readings &gt;40 °C and &lt;40 °C, respectively) and euthanized at 1 h (<b>d</b>) or 24 h (<b>e</b>) after METH or saline. Significant differences between saline and METH rats: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001. Significant differences between HH and LH rats: <span class="html-italic"><sup>ƒƒ</sup> p</span> &lt; 0.01, <span class="html-italic"><sup>ƒƒƒ</sup> p</span> &lt; 0.001, and <span class="html-italic"><sup>ƒƒƒƒ</sup> p</span> &lt; 0.0001. Values expressed as mean ± SEM. Abbreviations: METH, methamphetamine; SAL, saline.</p>
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<p>The effects of the 4 × 8 mg/kg METH binge on α-tubulin and β-actin immunoreactivity in striatal synaptosomal fractions. Immunoreactivity of β-actin (<b>a</b>,<b>b</b>) or α-tubulin (<b>c</b>,<b>d</b>) in the total (TOT or T), membrane/endosomal (M/E or M), and vesicular/cytosolic (V/C or C) synaptosomal fractions of the striatum in rats that were euthanized at 1 h (<b>a</b>,<b>c</b>) or 24 h (<b>b</b>,<b>d</b>) after the last dose of saline or METH. * <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 7–11. Values are expressed as mean ± SEM. Vertical grey lines show where the blot was cut for rearrangement. Abbreviations: METH, methamphetamine; SAL, saline; PonS, Ponceau S.</p>
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<p>The effects of the 4 × 8 mg/kg METH binge on parkin immunoreactivity in striatal synaptosomal fractions. Immunoreactivity of parkin in the total (TOT or T), membrane/endosomal (M/E or M), and vesicular/cytosolic (V/C or C) synaptosomal fractions of the striatum in rats euthanized at (<b>a</b>) 1 h or (<b>b</b>) 24 h. (<b>c</b>) Immunoreactivity of parkin in striatal synaptosomal fractions in high-hyperthermia (HH) and low-hyperthermia (LH) rats. (<b>d</b>) Correlations of parkin immunoreactivity in synaptosomal fractions with core body temperature (area under the curve AUC) of the rats sacrificed 1 h after the last METH dose. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, <span class="html-italic">n</span> = 10–17. Values are expressed as mean ± SEM. Abbreviations: METH, methamphetamine; SAL, saline; PonS, Ponceau S.</p>
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<p>The effects of the 4 × 8 mg/kg METH binge on VMAT2 immunoreactivity in striatal synaptosomal fractions. Immunoreactivity of VMAT2 in the total (TOT or T), membrane/endosomal (M/E or M), and vesicular/cytosolic (V/C or C) synaptosomal fractions of the striatum in rats euthanized at (<b>a</b>) 1 h or (<b>b</b>) 24 h. ** <span class="html-italic">p</span> &lt; 0.01, <span class="html-italic">n</span> = 9–11. (<b>c</b>) Immunoreactivity of VMAT2 in striatal synaptosomal fractions in high-hyperthermia (HH) and low-hyperthermia (LH) rats. (<b>d</b>) Correlations of VMAT2 immunoreactivity in synaptosomal fractions with core body temperature (area under the curve, AUC) of rats sacrificed 1 h after the last METH dose. A strong trend toward statistical significance was detected in the membrane/endosomal fraction (<span class="html-italic">p</span> = 0.055). Values are expressed as mean ± SEM. Vertical grey lines show where the blot was cut for rearrangement. Abbreviations: METH, methamphetamine; SAL, saline; PonS, Ponceau S.</p>
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<p>The effects of the 4 × 8 mg/kg METH binge on VMAT2 immunoreactivity in striatal synaptosomal fractions. Immunoreactivity of VMAT2 in the total (TOT or T), membrane/endosomal (M/E or M), and vesicular/cytosolic (V/C or C) synaptosomal fractions of the striatum in rats euthanized at (<b>a</b>) 1 h or (<b>b</b>) 24 h. ** <span class="html-italic">p</span> &lt; 0.01, <span class="html-italic">n</span> = 9–11. (<b>c</b>) Immunoreactivity of VMAT2 in striatal synaptosomal fractions in high-hyperthermia (HH) and low-hyperthermia (LH) rats. (<b>d</b>) Correlations of VMAT2 immunoreactivity in synaptosomal fractions with core body temperature (area under the curve, AUC) of rats sacrificed 1 h after the last METH dose. A strong trend toward statistical significance was detected in the membrane/endosomal fraction (<span class="html-italic">p</span> = 0.055). Values are expressed as mean ± SEM. Vertical grey lines show where the blot was cut for rearrangement. Abbreviations: METH, methamphetamine; SAL, saline; PonS, Ponceau S.</p>
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<p>Parkin does not affect VMAT2 immunoreactivity in striatal synaptosomal fractions. (<b>a</b>) Core body temperatures (°C) of the wild-type rats and rats overexpressing parkin in the nigrostriatal dopamine pathway. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. (<b>b</b>) Immunoreactivity of parkin in the total synaptosomal fraction of the striatum in rats euthanized at 1 h after METH or saline. ** <span class="html-italic">p</span> &lt; 0.01 <span class="html-italic">n</span> = 5. Parkin overexpression was about 5-fold in both treatment groups. METH did not significantly alter parkin immunoreactivity in the wild-type (<span class="html-italic">p</span> = 0.09) or parkin-overexpressing (<span class="html-italic">p</span> &gt; 0.1) striatal synaptosomes at 1 h after the treatment. (<b>c</b>) Immunoreactivity of VMAT2 in the total (TOT), membrane/endosomal (M/E), and vesicular/cytosolic (V/C) synaptosomal fractions in the striatum from wild-type and parkin-overexpressing saline-treated rats. (<b>d</b>) Immunoreactivity of VMAT2 in striatal synaptosomal fractions in the wild-type and parkin-overexpressing rats treated with METH or saline at 1 h after the treatment. (<b>e</b>) Correlations of VMAT2 immunoreactivity in synaptosomal fractions with total synaptosomal parkin immunoreactivity. Values are expressed as mean ± SEM. Vertical grey lines show where the blot was cut for rearrangement. Abbreviations: AAV2/6, adeno-associated viral vector 2/6; METH, methamphetamine; SAL, saline; PO, parkin-overexpressing; WT, wild-type; PonS, Ponceau S; AAV2/6-parkin, parkin-encoding AAV2/6; AAV6, non-coding AAV2/6.</p>
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<p>The effects of the 4 × 8 mg/kg METH binge on CDCrel-1 immunoreactivity in striatal synaptosomal fractions. Immunoreactivity of CDCrel-1 in the total (TOT or T), membrane/endosomal (M/E or M), and vesicular/cytosolic (V/C or C) synaptosomal fractions of the striatum in rats euthanized at (<b>a</b>) 1 h or (<b>b</b>) 24 h. * <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 9–10. (<b>c</b>,<b>d</b>) Immunoreactivity of CDCrel-1 in striatal synaptosomal fractions separated into two subgroups based on individual variability to METH. * <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, <span class="html-italic">n</span> = 6–13. (<b>e</b>) Immunoreactivity of CDCrel-1 in striatal synaptosomal fractions in high-hyperthermia (HH) and low-hyperthermia (LH) rats. * <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6–10. (<b>f</b>) Correlations of CDCrel-1 immunoreactivity in synaptosomal fractions with core body temperature (area under the curve, AUC) of the wild-type rats sacrificed 1 h after the last METH dose. Values are expressed as mean ± SEM. Vertical grey lines show where the blot was cut for rearrangement. Abbreviations: METH, methamphetamine; SAL, saline; PonS, Ponceau S.</p>
Full article ">Figure 6 Cont.
<p>The effects of the 4 × 8 mg/kg METH binge on CDCrel-1 immunoreactivity in striatal synaptosomal fractions. Immunoreactivity of CDCrel-1 in the total (TOT or T), membrane/endosomal (M/E or M), and vesicular/cytosolic (V/C or C) synaptosomal fractions of the striatum in rats euthanized at (<b>a</b>) 1 h or (<b>b</b>) 24 h. * <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 9–10. (<b>c</b>,<b>d</b>) Immunoreactivity of CDCrel-1 in striatal synaptosomal fractions separated into two subgroups based on individual variability to METH. * <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, <span class="html-italic">n</span> = 6–13. (<b>e</b>) Immunoreactivity of CDCrel-1 in striatal synaptosomal fractions in high-hyperthermia (HH) and low-hyperthermia (LH) rats. * <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6–10. (<b>f</b>) Correlations of CDCrel-1 immunoreactivity in synaptosomal fractions with core body temperature (area under the curve, AUC) of the wild-type rats sacrificed 1 h after the last METH dose. Values are expressed as mean ± SEM. Vertical grey lines show where the blot was cut for rearrangement. Abbreviations: METH, methamphetamine; SAL, saline; PonS, Ponceau S.</p>
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<p>CDCrel-1 interactions with parkin in striatal synaptosomal fractions. (<b>a</b>) Anti-parkin antibody immunoprecipitated CDCrel-1 from untreated striatal synaptosomes (asterisk). (<b>b</b>) There was a weak trend toward statistical significance for the overexpression of parkin in the nigrostriatal dopamine pathway decreasing CDCrel-1 levels in the total and vesicular/cytosolic synaptosomal fractions (<span class="html-italic">p</span> = 0.09, <span class="html-italic">n</span> = 5). (<b>c</b>) Trends toward statistical significance for parkin and METH decreasing CDCrel-1 immunoreactivity in the wild-type rats at 1 h after the last dose of the drug were detected (<span class="html-italic">p</span> = 0.054 and <span class="html-italic">p</span> = 0.079, respectively, <span class="html-italic">n</span> = 5). METH treatment did not decrease CDcrel-1 levels in parkin-overexpressing rats. (<b>d</b>) Correlations of CDCrel-1 immunoreactivity in synaptosomal fractions with parkin immunoreactivity of the wild-type rats sacrificed 1 h after the last METH dose. A statistically significant positive correlation was found in the total synaptosomal fraction. Values are expressed as mean ± SEM. Abbreviations: METH, methamphetamine; SAL, saline; PonS, Ponceau S; AAV2/6-parkin, parkin-encoding AAV2/6; AAV6, non-coding AAV2/6; IP, immunoprecipitation; WB, Western blotting.</p>
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<p>CDCrel-1 interactions with VMAT2 in striatal synaptosomes. (<b>a</b>) Anti-VMAT2 antibody immunoprecipitated CDCrel-1 from untreated striatal synaptosomes. (<b>b</b>) METH treatment increased the amount of immunoprecipitated CDCrel-1 at 1 h after the last dose of the drug. (<b>c</b>) There was a significant positive correlation between CDCrel-1 and VMAT2 immunoreactivity in the membrane/endosomal fraction of striatal synaptosomes (<span class="html-italic">p</span> &lt; 0.05). (<b>d</b>) Striatal VMAT2 vesicles associated with the membrane/endosomal fraction had significantly lower dopamine content in METH-treated rats than the saline-treated rats at 1 h after the treatment (−29%). Over the next 24 h, dopamine content decreased to 66%. (<b>e</b>) Representative chromatogram for (<b>d</b>). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, <span class="html-italic">n</span> = 5–7. Values are expressed as mean ± SEM. Abbreviations: DA, dopamine; METH, methamphetamine; SAL, saline; IP, immunoprecipitation; WB, Western blotting.</p>
Full article ">Figure 8 Cont.
<p>CDCrel-1 interactions with VMAT2 in striatal synaptosomes. (<b>a</b>) Anti-VMAT2 antibody immunoprecipitated CDCrel-1 from untreated striatal synaptosomes. (<b>b</b>) METH treatment increased the amount of immunoprecipitated CDCrel-1 at 1 h after the last dose of the drug. (<b>c</b>) There was a significant positive correlation between CDCrel-1 and VMAT2 immunoreactivity in the membrane/endosomal fraction of striatal synaptosomes (<span class="html-italic">p</span> &lt; 0.05). (<b>d</b>) Striatal VMAT2 vesicles associated with the membrane/endosomal fraction had significantly lower dopamine content in METH-treated rats than the saline-treated rats at 1 h after the treatment (−29%). Over the next 24 h, dopamine content decreased to 66%. (<b>e</b>) Representative chromatogram for (<b>d</b>). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, <span class="html-italic">n</span> = 5–7. Values are expressed as mean ± SEM. Abbreviations: DA, dopamine; METH, methamphetamine; SAL, saline; IP, immunoprecipitation; WB, Western blotting.</p>
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23 pages, 4536 KiB  
Article
Proteomic Profile Regulated by the Immunomodulatory Jusvinza Drug in Neutrophils Isolated from Rheumatoid Arthritis Patients
by Mabel Hernández-Cedeño, Arielis Rodríguez-Ulloa, Yassel Ramos, Luis J. González, Anabel Serrano-Díaz, Katharina Zettl, Jacek R. Wiśniewski, Gillian Martinez-Donato, Gerardo Guillen-Nieto, Vladimir Besada and María del Carmen Domínguez-Horta
Biomedicines 2024, 12(12), 2740; https://doi.org/10.3390/biomedicines12122740 - 29 Nov 2024
Viewed by 827
Abstract
Jusvinza is an immunomodulatory drug composed of an altered peptide ligand (APL) designed from a novel CD4+ T cell epitope of human heat shock protein 60 (HSP60), an autoantigen involved in the pathogenesis of rheumatoid arthritis (RA). The peptide induces regulatory T cells [...] Read more.
Jusvinza is an immunomodulatory drug composed of an altered peptide ligand (APL) designed from a novel CD4+ T cell epitope of human heat shock protein 60 (HSP60), an autoantigen involved in the pathogenesis of rheumatoid arthritis (RA). The peptide induces regulatory T cells and decreases levels of TNF-α and IL-17; pre-clinical and phase I clinical studies support its use for the treatment of RA. This peptide was repositioned for the treatment of COVID-19 patients with signs of hyperinflammation. Neutrophils play a pathogenic role in both RA and severe forms of COVID-19. To add novel evidence about the mechanism of action of Jusvinza, the proteomic profile regulated by this peptide of neutrophils isolated from four RA patients was investigated using LC-MS/MS and bioinformatics analysis. A total of 149 proteins were found to be differentially modulated in neutrophils treated with Jusvinza. The proteomic profile regulated by Jusvinza is characterized by the presence of proteins related to RNA splicing, phagocytosis, endocytosis, and immune functions. In response to Jusvinza treatment, several proteins that regulate the NF-κB signaling pathway were differentially modulated, supporting the peptide’s anti-inflammatory effect. Proteins related to metabolic pathways that supply ATP for cellular functions or lipid metabolites with immunoregulatory properties were also identified. Additionally, several structural components of neutrophil extracellular traps (NETs) were decreased in Jusvinza-treated cells, supporting its impairment of this biological process. Of note, these findings were validated by in vitro experiments which confirmed that Jusvinza decreased NET formation. Such results provide evidence of the molecular mechanism of action and support the therapeutic potentialities of Jusvinza to treat other diseases characterized by hyperinflammation besides RA and COVID-19. Full article
(This article belongs to the Special Issue Neutrophils in Immunity and Diseases)
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Graphical abstract

Graphical abstract
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<p>Proteomic profile of neutrophils treated with Jusvinza. (<b>A</b>) Workflow for the exploration and analysis of the proteomic profile modulated in response to Jusvinza treatment. (<b>B</b>) Number of significantly modulated proteins in Jusvinza-treated neutrophils at 6 h and 18 h. Down- and up-regulated proteins are highlighted in blue and red, respectively. The table shows the overlapping proteins between the two datasets. (*) MED-FASP: multienzyme digestion filter-assisted sample preparation [<a href="#B33-biomedicines-12-02740" class="html-bibr">33</a>].</p>
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<p>Enrichment analysis of differentially modulated proteins in neutrophils treated with Jusvinza at 6 h and 18 h. Biological processes and pathways significantly represented in the proteomic profiles (<span class="html-italic">p</span>-value &lt; 0.01, enrichment factor &gt; 1.5) were identified using the Metascape gene annotation and analysis resource (<a href="https://metascape.org/" target="_blank">https://metascape.org/</a>, accessed on 5 November 2020). In the heatmap and bar graph, enriched terms are colored according to <span class="html-italic">p</span>-values.</p>
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<p>Functional association networks between differentially modulated proteins and some (<b>A</b>) biological processes and (<b>B</b>) subcellular locations which were found to be over-represented in the proteomic profile. In networks, proteins are shown as yellow circles, with the outside circle representing the expression level (blue, decreased; red, increased; white, not differentially modulated) and colored in a clockwise fashion according to the fold change at each time point (6 h and 18 h). Proteins that were modulated at both time points are highlighted in green.</p>
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<p>Protein–protein interaction networks associated with the proteomic profile modulated at 6 h (<b>A</b>) and 18 h (<b>B</b>) in Jusvinza-treated neutrophils. In both networks, proteins are represented according to the expression level (blue, decreased; red, increased; yellow, not identified); dark and light colors represent proteins identified in neutrophils isolated from four and three AR patients, respectively. Biological processes and proteins complexes gathered using the STRING functional enrichment tool and datamining are indicated by squares and green colors, respectively. Proteins related to the immune system are highlighted by a bold circle. Direct interactions between differentially modulated proteins are represented by black edges.</p>
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<p>(<b>A</b>) Representative fluorescence images of LPS-induced NETosis. Neutrophils isolated from healthy donors were subjected to different experimental conditions: (<b>a</b>) unstimulated neutrophils, (<b>b</b>) LPS-stimulated neutrophils, (<b>c</b>) neutrophils stimulated with 5 μg of Jusvinza, (<b>d</b>) neutrophils simultaneously stimulated with LPS and 5 μg of Jusvinza, (<b>e</b>) neutrophils treated with 5 μg of Jusvinza 30 min after pre-stimulation with LPS. The DNA was stained with 10 μg/mL propidium iodide solution. Images were captured at 20× magnification. White arrows indicate neutrophils in NETosis. (<b>B</b>) Quantification of NETs induced by LPS in neutrophils treated with Jusvinza. NETs were quantified using neutrophils isolated from three healthy donors. Five fluorescent images were acquired for each experimental condition. Neutrophils in NETosis were defined when the nucleus area was ≥1-fold the cellular area. Results are expressed as a fraction of the number of neutrophils in NETosis/the total number of neutrophils. Significant differences were calculated by one-way ANOVA followed by Tukey’s multiple comparisons test (* <span class="html-italic">p</span>-value &lt; 0.05, *** <span class="html-italic">p</span>-value &lt; 0.0002, **** <span class="html-italic">p</span>-value &lt; 0.0001).</p>
Full article ">Figure 5 Cont.
<p>(<b>A</b>) Representative fluorescence images of LPS-induced NETosis. Neutrophils isolated from healthy donors were subjected to different experimental conditions: (<b>a</b>) unstimulated neutrophils, (<b>b</b>) LPS-stimulated neutrophils, (<b>c</b>) neutrophils stimulated with 5 μg of Jusvinza, (<b>d</b>) neutrophils simultaneously stimulated with LPS and 5 μg of Jusvinza, (<b>e</b>) neutrophils treated with 5 μg of Jusvinza 30 min after pre-stimulation with LPS. The DNA was stained with 10 μg/mL propidium iodide solution. Images were captured at 20× magnification. White arrows indicate neutrophils in NETosis. (<b>B</b>) Quantification of NETs induced by LPS in neutrophils treated with Jusvinza. NETs were quantified using neutrophils isolated from three healthy donors. Five fluorescent images were acquired for each experimental condition. Neutrophils in NETosis were defined when the nucleus area was ≥1-fold the cellular area. Results are expressed as a fraction of the number of neutrophils in NETosis/the total number of neutrophils. Significant differences were calculated by one-way ANOVA followed by Tukey’s multiple comparisons test (* <span class="html-italic">p</span>-value &lt; 0.05, *** <span class="html-italic">p</span>-value &lt; 0.0002, **** <span class="html-italic">p</span>-value &lt; 0.0001).</p>
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<p>Molecular basis of Jusvinza’s mechanism of action on neutrophils. Jusvinza treatment inhibits pro-inflammatory cytokine release and NETosis. Supporting Jusvinza’s anti-inflammatory effect, the proteomic profile includes several transcription factors (YBX1 and FLI1) and regulator proteins of the heat shock response (HSBP1) and the NF κB signaling pathway. The abundance levels of positive regulators of NF-κB signaling (LIGHT, MTDH, HMGB1, CDC37, and LRRFIP2) were decreased, while negative regulators (APPL2, IKBIP, and ASCC1) were increased in Jusvinza-treated neutrophils. Structural components of NETs (histones and HMGB1) were also decreased in response to Jusvinza treatment. Furthermore, the peptide could inhibit PAD4 activation dependent on Ca<sup>2+</sup>/ROS and consequently suppress NET release. Additionally, proteins related to lipid metabolic pathways (DBI, HELZ2, MBOAT7, and PLIN3) were identified, some of which regulate the synthesis of lipid metabolites (LTB4 and PGE2) with immunoregulatory properties. Juzvinza treatment also modulates proteins related to neutrophil effector functions, such as phagocytosis/endocytosis (CLTA), migration, and priming of neutrophils (HCLS1, WIP, and WASP), probably decreasing the over-activation of such cells in chronic inflammatory conditions. Proteins are represented as boxes and colored according to their expression levels (blue, decreased; red, increased; grey, not identified). In signaling pathways, the lines indicate regulatory events (arrows: activation, lines: inhibition).</p>
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22 pages, 11231 KiB  
Article
Sprouty2 Regulates Endocytosis and Degradation of Fibroblast Growth Factor Receptor 1 in Glioblastoma Cells
by Barbara Hausott, Lena Pircher, Michaela Kind, Jong-Whi Park, Peter Claus, Petra Obexer and Lars Klimaschewski
Cells 2024, 13(23), 1967; https://doi.org/10.3390/cells13231967 - 28 Nov 2024
Viewed by 619
Abstract
The Sprouty (SPRY) proteins are evolutionary conserved modulators of receptor tyrosine kinase (RTK) signaling. SPRY2 inhibits fibroblast growth factor (FGF) signaling, whereas it enhances epidermal growth factor (EGF) signaling through inhibition of EGF receptor (EGFR) endocytosis, ubiquitination, and degradation. In this study, we [...] Read more.
The Sprouty (SPRY) proteins are evolutionary conserved modulators of receptor tyrosine kinase (RTK) signaling. SPRY2 inhibits fibroblast growth factor (FGF) signaling, whereas it enhances epidermal growth factor (EGF) signaling through inhibition of EGF receptor (EGFR) endocytosis, ubiquitination, and degradation. In this study, we analyzed the effects of SPRY2 on endocytosis and degradation of FGF receptor 1 (FGFR1) using two human glioblastoma (GBM) cell lines with different endogenous SPRY2 levels. SPRY2 overexpression (SPRY2-OE) inhibited clathrin- and caveolae-mediated endocytosis of FGFR1, reduced the number of caveolin-1 vesicles and the uptake of transferrin. Furthermore, FGFR1 protein was decreased by SPRY2-OE, whereas EGFR protein was increased. SPRY2-OE enhanced FGFR1 degradation by increased c-casitas b-lineage lymphoma (c-CBL)-mediated ubiquitination, but it diminished binding of phospholipase Cγ1 (PLCγ1) to FGFR1. Consequently, SPRY2-OE inhibited FGF2-induced activation of PLCγ1, whereas it enhanced EGF-induced PLCγ1 activation. Despite the reduction of FGFR1 protein and the inhibition of FGF signaling, SPRY2-OE increased cell viability, and knockdown of SPRY2 enhanced the sensitivity to cisplatin. These results demonstrate that the inhibitory effect of SPRY2-OE on FGF signaling is at least in part due to the reduction in FGFR1 levels and the decreased binding of PLCγ1 to the receptor. Full article
(This article belongs to the Section Cell Signaling)
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Figure 1

Figure 1
<p>Western blot analyses of endogenous SPRY2 protein in U251 and SF126 cells and the effects of SPRY2 overexpression (SPRY2-OE) and SPRY2 short hairpin RNA (shSPRY2). (<b>A</b>) Endogenous SPRY2 protein is much lower in U251 cells than in SF126 cells. N = 4, mean ± SD. *** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) SPRY2-OE increased SPRY2 protein levels in U251 cells, whereas shSPRY2 reduced SPRY2 protein in SF126 cells. N = 4, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>SPRY2 reduces the number of FGFR1 and FGF2 vesicles and their colocalization in U251 and SF126 cells. (<b>A</b>) U251 control cells with low endogenous SPRY2 level and U251 cells with SPRY2-OE were transfected with FGFR1 fused to enhanced green fluorescent protein (FGFR1-EGFP) and treated with cyanine 3-labeled FGF2 (FGF2-Cy3) for 30 min. Whole-cell analysis of confocal images revealed a reduction in FGFR1 (green) and FGF2 (red) vesicles per cell and their reduced colocalization (yellow) in response to SPRY2-OE. N = 18 experiments, mean ± SEM. *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. (<b>B</b>) SF126 control cells with high endogenous SPRY2 content and SF126 cells with shSPRY2 were transfected with FGFR1-EGFP and treated with FGF2-Cy3 for 30 min. Whole-cell analysis of confocal images revealed an increase in FGFR1 (green) and FGF2 (red) vesicles per cell as well as their enhanced colocalization (yellow) in response to shSPRY2. N = 15 experiments, mean ± SEM. *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001. White, bold arrowheads indicate cell surface localization of FGFR1 and FGF2. Yellow arrowheads mark internalized FGFR1 vesicles colocalizing with FGF2. Scale bar = 4 µm.</p>
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<p>SPRY2 inhibits colocalization of clathrin with FGFR1 and FGF2 in U251 and SF126 cells. (<b>A</b>) U251 control cells with low endogenous SPRY2 level and U251 cells with SPRY2-OE were transfected with FGFR1-EGFP, treated with FGF2-Cy3 for 30 min, and immunostained against clathrin. Whole-cell analysis of confocal images revealed no change in the number of clathrin vesicles per cell (blue) after SPRY2-OE. The colocalization of clathrin (blue) with FGFR1 (green; colocalization with clathrin = turquoise) and FGF2 (red; colocalization with clathrin = magenta) was reduced in response to SPRY2-OE. N = 6 experiments, mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) SF126 control cells with high endogenous SPRY2 content and SF126 cells with shSPRY2 were transfected with FGFR1-EGFP, treated with FGF2-Cy3 for 30 min, and immunostained against clathrin. The number of clathrin vesicles per cell (blue) was not altered with shSPRY2. The colocalization of clathrin (blue) with FGFR1 (green; colocalization with clathrin = turquoise) and FGF2 (red; colocalization with clathrin = magenta) was enhanced with shSPRY2. N = 5 experiments, mean ± SEM. ** <span class="html-italic">p</span> &lt; 0.01. White, bold arrowheads indicate cell surface localization of FGFR1 and FGF2. Yellow arrowheads mark internalized FGFR1 and FGF2 vesicles colocalizing with clathrin. Scale bar = 4 µm.</p>
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<p>SPRY2 inhibits colocalization of caveolin-1 with FGFR1 and FGF2 in U251 and SF126 cells and reduces caveolin-1 vesicles. (<b>A</b>) U251 control cells with low endogenous SPRY2 level and U251 cells with SPRY2-OE were transfected with FGFR1-EGFP, treated with FGF2-Cy3 for 30 min, and immunostained against caveolin-1. Whole-cell analysis of confocal images revealed a reduction in the number of caveolin-1 vesicles per cell (blue) after SPRY2-OE. The colocalization of caveolin-1 (blue) with FGFR1 (green; colocalization with caveolin-1 = turquoise) and FGF2 (red; colocalization with caveolin-1 = magenta) was reduced in response to SPRY2-OE. N = 6 experiments, mean ± SEM. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) SF126 control cells with high endogenous SPRY2 content and SF126 cells with shSPRY2 were transfected with FGFR1-EGFP, treated with FGF2-Cy3 for 30 min, and immunostained against caveolin-1. The number of caveolin-1 vesicles per cell (blue) was slightly but not significantly enhanced with shSPRY2. The colocalization of caveolin-1 (blue) with FGFR1 (green; colocalization with caveolin-1 = turquoise) and FGF2 (red; colocalization with caveolin-1 = magenta) was enhanced with shSPRY2. N = 5 experiments, mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05. White, bold arrowheads indicate cell surface localization of FGFR1 and FGF2. Yellow arrowheads mark internalized FGFR1 and FGF2 vesicles colocalizing with caveolin-1. Scale bar = 4 µm.</p>
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<p>SPRY2 reduces caveolin-1 protein in U251 and SF126 cells. (<b>A</b>) SPRY2-OE reduced caveolin-1 protein levels in U251 cells and shSPRY2 slightly enhanced caveolin-1 protein in SF126 cells. N = 4 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) U251 cells with low endogenous SPRY2 revealed higher caveolin-1 protein levels than SF126 cells with high endogenous SPRY2. N = 4 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>SPRY2 decreases transferrin-647 uptake and colocalization of transferrin with FGFR1 and FGF2 in U251 and SF126 cells. (<b>A</b>) U251 control cells with low endogenous SPRY2 level and U251 cells with SPRY2-OE were transfected with FGFR1-EGFP and treated with FGF2-Cy3 for 30 min and with transferrin-647 for 15 min. Whole-cell analysis of confocal images revealed a reduction in the uptake of transferrin vesicles per cell (blue) after SPRY2-OE. The colocalization of transferrin (blue) with FGFR1 (green; colocalization with transferrin = turquoise) and FGF2 (red; colocalization with transferrin = magenta) was also reduced in response to SPRY2-OE. N = 6 experiments, mean ± SEM. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) SF126 control cells with high endogenous SPRY2 content and SF126 cells with shSPRY2 were transfected with FGFR1-EGFP and treated with FGF2-Cy3 for 30 min and with transferrin-647 for 15 min. The uptake of transferrin vesicles per cell (blue) was increased with shSPRY2, and the colocalization of transferrin (blue) with FGFR1 (green; colocalization with transferrin = turquoise) and FGF2 (red; colocalization with transferrin = magenta) was enhanced with shSPRY2. N = 5 experiments, mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. White, bold arrowheads indicate cell surface localization of FGFR1 and FGF2. Yellow arrowheads mark FGFR1 and FGF2 vesicles colocalizing with transferrin. Scale bar = 4 µm.</p>
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<p>SPRY2 reduces FGFR1 and increases EGFR protein but has no effect on FGFR1 and EGFR mRNA levels. (<b>A</b>) Western blot analyses of U251 and SF126 cells overexpressing FGFR1-EGFP and treated with FGF2 for 30 min revealed reduced FGFR1 protein after SPRY2-OE in U251 cells and enhanced FGFR1 protein in SF126 cells with shSPRY2. N = 4 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05. (<b>B</b>) qRT-PCR did not reveal changes in FGFR1 mRNA content in response to SPRY2-OE in U251 cells or shSPRY2 in SF126 cells overexpressing FGFR1-EGFP and treated with FGF2 for 30 min. N = 3 experiments, mean ± SEM. (<b>C</b>) Western blot analyses of endogenous FGFR1 in U251 and SF126 cells that were not transfected with FGFR1-EGFP but treated with FGF2 for 30 min also revealed reduced FGFR1 protein after SPRY2-OE in U251 cells and enhanced FGFR1 protein in SF126 cells with shSPRY2. N = 4 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05. (<b>D</b>) Western blot analyses of U251 cells overexpressing EGFR-EGFP and treated with EGF for 30 min revealed increased EGFR protein after SPRY2-OE, whereas SF126 cells with shSPRY2 exhibited reduced EGFR protein. N = 3 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05. (<b>E</b>) qRT-PCR did not reveal changes in EGFR mRNA content in response to SPRY2-OE in U251 cells or shSPRY2 in SF126 cells overexpressing EGFR-EGFP and treated with EGF for 30 min. N = 3 experiments, mean ± SEM.</p>
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<p>SPRY2-OE increases FGFR1 degradation by enhanced c-CBL-mediated ubiquitination and reduces binding of PLCγ1 to FGFR1 in U251 cells. (<b>A</b>) Whole-cell lysates of U251 control cells and U251 cells with SPRY2-OE transfected with FGFR1-EGFP and treated with FGF2 for 10 min. U251 cells with SPRY2-OE revealed reduced FGFR1 protein but no change in ubiquitin, c-CBL, or PLCγ1. (<b>B</b>) Anti-FGFR1 immunoprecipitates (IP) revealed reduced FGFR1 protein but enhanced ubiquitination and c-CBL after SPRY2-OE. PLCγ1 was reduced in anti-FGFR1 immunoprecipitates with SPRY2-OE, and the overexpressed but not the endogenous SPRY2 was detected in anti-FGFR1 immunoprecipitates. (<b>C</b>) Quantification of anti-FGFR1 immunoprecipitates (IP) confirmed the increase of ubiquitin and c-CBL but the reduction of PLCγ1 in response to SPRY2-OE. N = 3 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>SiRNA-induced knockdown of c-CBL increases FGFR1 protein in U251 cells with SPRY2-OE but the mutant SPRY2<sup>Y55F</sup>, which does not bind c-CBL, reduces FGFR1 protein. (<b>A</b>) Western blot analyses of U251 cells transfected with scrambled control siRNA (siControl) or siRNA against c-CBL (siCBL) overexpressing FGFR1-EGFP and treated with FGF2 for 30 min revealed reduced c-CBL with siCBL compared to siControl in U251 control cells and in U251 cells with SPRY2-OE. N = 4 experiments, mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>) U251 cells transfected with control siRNA (siControl) and siRNA against c-CBL (siCBL) overexpressing FGFR1-EGFP and treated with FGF2 for 30 min revealed increased FGFR1 protein in U251 control cells and in U251 cells with SPRY2-OE in response to siCBL. N = 5 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>) FGFR1 protein was reduced by SPRY2-OE and by overexpression of mutant SPRY2<sup>Y55F</sup> in U251 cells overexpressing FGFR1-EGFP and treated with FGF2 for 30 min. N = 3 experiments, mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>SPRY2-OE inhibits FGF2-induced activation of PLCγ1 and ERK in U251 cells, but shSPRY2 only increases FGF2-induced PLCγ1 activation in SF126 cells. (<b>A</b>) U251 control cells with low endogenous SPRY2 level and U251 cells with SPRY2-OE transfected with FGFR1-EGFP and treated with FGF2 for 30 and 120 min. Activation of PLCγ1 and ERK was inhibited by SPRY2-OE. N = 4 experiments, mean ± SD. ** <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. (<b>B</b>) Naive SF126 control cells with high endogenous SPRY2 content and SF126 cells with shSPRY2 transfected with FGFR1-EGFP and treated with FGF2 for 30 and 120 min. Activation of PLCγ1 but not of ERK was elevated by shSPRY2. N = 4 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001.</p>
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<p>SPRY2-OE increases EGF-induced PLCγ1 signaling in U251 cells, and shSPRY2 inhibits EGF-induced PLCγ1 and ERK signaling in SF126 cells. (<b>A</b>) U251 control cells and U251 cells with SPRY2-OE transfected with EGFR-EGFP and treated with EGF for 30 and 120 min. Activation of PLCγ1 but not of ERK was increased by SPRY2-OE. N = 3 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001. (<b>B</b>) Naive SF126 control cells and SF126 cells with shSPRY2 transfected with EGFR-EGFP and treated with EGF for 30 and 120 min. Activation of PLCγ1 and ERK was reduced by shSPRY2. N = 3 experiments, mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>SPRY2-OE increases cell viability and reduces stemness markers in U251 cells, whereas shSPRY2 enhances cisplatin sensitivity and increases stemness markers in SF126 cells. (<b>A</b>) U251 control cells and U251 cells with SPRY2-OE were transfected with FGFR1-EGFP and treated with FGF2 and 15 and 30 µM cisplatin for 24 h. Cell viability of U251 cells was increased by SPRY2-OE in all groups. N = 4 experiments, mean ± SEM. **** <span class="html-italic">p</span> &lt; 0.0001. (<b>B</b>) Naive SF126 control cells and SF126 cells with shSPRY2 were transfected with FGFR1-EGFP and treated with FGF2 and 10 and 15 µM cisplatin for 24 h. Cell viability of SF126 cells was not altered by shSPRY2, but cell viability was more strongly reduced by cisplatin treatment in cells with shSPRY2 than in control cells. N = 5 experiments, mean ± SEM. ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001. (<b>C</b>) SPRY2-OE reduces SOX2 and CD44 in U251 cells overexpressing FGFR1-EGFP. N = 4 experiments, mean ± SD. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. (<b>D</b>) ShSPRY2 increases SOX2 and CD44 in SF126 cells overexpressing FGFR1-EGFP. N = 4 experiments, mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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14 pages, 1896 KiB  
Article
Nobiletin Regulates Lysosome Function in Bovine Endometrial Epithelial Cells
by Karen Koshimizu, Ren Ozawa, Sohei Kuribayashi, Maho Taru, Hisataka Iwata, Ryotaro Miura, Seizo Hamano and Koumei Shirasuna
Dairy 2024, 5(4), 754-767; https://doi.org/10.3390/dairy5040055 - 22 Nov 2024
Viewed by 657
Abstract
The existence of repeat breeder cows (RBCs) causes low reproductive performance. The causes of RBCs include low-quality oocytes and embryos, hormonal dysregulation, and unsuitable uterine environments. To improve unsuitable uterine conditions for RBCs, we focused on nobiletin (NOB), a natural citrus flavone with [...] Read more.
The existence of repeat breeder cows (RBCs) causes low reproductive performance. The causes of RBCs include low-quality oocytes and embryos, hormonal dysregulation, and unsuitable uterine environments. To improve unsuitable uterine conditions for RBCs, we focused on nobiletin (NOB), a natural citrus flavone with various beneficial roles. The role of NOB in bovine endometrial epithelial cells (BEECs) was examined. An analysis of BEECs showed that gene expression and altered pathways differed between the control and NOB treatment, with NOB regulating the pathways of steroid biosynthesis, lysosomal function, and inflammatory responses. NOB treatment significantly increased the number and activation of endosomes and lysosomes in BEECs. Moreover, we performed phagocytosis assays using fluorescence-conjugated lipopolysaccharide (LPS) with lysosomes in NOB-treated BEECs, which resulted in an increase in the co-localization of phagocytosed LPS with lysosomes. NOB treatment stimulated the mRNA expression of various lysosomal hydrolases, including cathepsin B and cathepsin K, and suppressed the gene expression of cytokines in inflammation-associated pathways (rheumatoid arthritis, the IL-17 signaling pathway, etc.). NOB significantly suppressed the LPS-induced mRNA expression of the inflammatory cytokine IL-8 and its secretion in BEECs. In conclusion, NOB activates the endosome–lysosomal system via phagocytosis to eliminate the bacterial component LPS and suppress inflammatory responses to defense mechanisms in BEECs. Full article
(This article belongs to the Section Reproduction)
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Figure 1
<p>Differentially expressed genes and pathways in BEECs. (<b>A</b>) KEGG enrichment analysis of differentially regulated genes between the control and NOB-treated groups; 20 pathways showed significant variations (<span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) GO cellular component enrichment analysis of differentially regulated genes between the control and NOB-treated groups; 10 pathways showed significant variations (<span class="html-italic">p</span> &lt; 0.005).</p>
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<p>Effects of NOB on cholesterol, cell membrane, and endocytosis in BEECs. BEECs were treated with or without NOB for 24 h. (<b>A</b>) Intracellular cholesterol levels were determined. (<b>B</b>) After treatment, cell membranes were stained and observed using fluorescence microscopy. Arrowheads indicate dot-like staining area. (<b>C</b>) After treatment, the endocytosed cells were stained and observed using a fluorescence microscope. The number of cells endocytosed was calculated (<span class="html-italic">n</span> = 3–4). (<b>D</b>) After treatment, the fluorescence intensity of the endosomes was determined by flow cytometry (<span class="html-italic">n</span> = 3–4). The results are shown as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of NOB on lysosomes in BEECs. BEECs were treated with or without NOB for 24 h. (<b>A</b>) Lysosomes were stained and observed under a fluorescence microscope. The number of lysosomes/cells was calculated (<span class="html-italic">n</span> = 3–4). (<b>B</b>) After treatment, the fluorescence intensity of lysosomes was determined by flow cytometry (<span class="html-italic">n</span> = 3–4). The results are shown as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05 or ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effects of NOB on lysosome function in BEECs. BEECs were pretreated with or without NOB for 24 h and then further treated with fluorescence-conjugated LPS for 24 h. (<b>A</b>) After treatment, lysosome and fluorescence-conjugated LPS was observed using fluorescence microscopy. (<b>B</b>) The number or size of co-localization was calculated (<span class="html-italic">n</span> = 3–4). The results are shown as mean ± SEM. ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Effects of NOB on inflammatory cytokines in BEECs. BEECs were pretreated with or without NOB for 24 h and then further treated with LPS for 24 h. (<b>A</b>,<b>B</b>) After treatment, <span class="html-italic">IL-8</span> mRNA expression and IL-8 secretion were determined by qPCR and ELISA (<span class="html-italic">n</span> = 3–4). The results are shown as mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05 or ** <span class="html-italic">p</span> &lt; 0.01.</p>
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15 pages, 3230 KiB  
Article
Enhanced Ocular Bioavailability and Prolonged Duration via Hydrophilic Surface Nanocomposite Vesicles for Topical Drug Administration
by Sa Huang, Yuan Xu, Yingyao Luo, Zhijiong Wang, Fan Li, Zhenmiao Qin and Junfeng Ban
Pharmaceutics 2024, 16(12), 1496; https://doi.org/10.3390/pharmaceutics16121496 - 21 Nov 2024
Viewed by 443
Abstract
Background: Internal ocular diseases, such as macular edema, uveitis, and diabetic macular edema require precise delivery of therapeutic agents to specific regions within the eye. However, the eye’s complex anatomical structure and physiological barriers present significant challenges to drug penetration and distribution. Traditional [...] Read more.
Background: Internal ocular diseases, such as macular edema, uveitis, and diabetic macular edema require precise delivery of therapeutic agents to specific regions within the eye. However, the eye’s complex anatomical structure and physiological barriers present significant challenges to drug penetration and distribution. Traditional eye drops suffer from low bioavailability primarily due to rapid clearance mechanisms. Methods: The novel ocular drug delivery system developed in this study utilizes poly(lactic-co-glycolic acid) (PLGA) nanoparticles modified with cell-penetrating peptides (CPPs). In vitro drug release studies were conducted to evaluate the sustained-release properties of the nanoparticles. Ex vivo experiments using MDCK cells assessed corneal permeability and uptake efficiency. Additionally, in vivo studies were performed in rabbit eyes to determine the nanoparticles’ resistance to elimination by tears and their retention time in the aqueous humor. Results: In vitro drug release studies demonstrated superior sustained-release properties of the nanoparticles. Ex vivo experiments revealed enhanced corneal permeability and increased uptake efficiency by MDCK cells. In vivo studies in rabbit eyes confirmed the nanoparticles’ resistance to elimination by lacrimal fluid and their ability to extend retention time in the aqueous humor. CPP modification significantly improved ocular retention, corneal penetration, and cellular endocytosis efficiency. Conclusions: The CPP-modified PLGA nanoparticles provide an effective and innovative solution for ocular drug delivery, offering improved bioavailability, prolonged retention, and enhanced drug penetration, thereby overcoming the challenges of traditional intraocular drug administration methods. Full article
(This article belongs to the Special Issue Polymer-Based Delivery System)
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Graphical abstract
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<p>Particle size, potential, and microscopic images of NPs. (<b>A</b>) The particle size and potential of NPs. (<b>B</b>) Microscopic image of the NPs.</p>
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<p>In vitro release and ex vivo corneal permeation studies. (<b>A</b>) The cumulative release rate of NPs. (<b>B</b>) In vitro corneal permeation of NPs.</p>
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<p>Tear elimination and aqueous humor dynamics studies. (<b>A</b>) TA elimination curve in tears. (<b>B</b>) The pharmacokinetic curves of TA within aqueous humor.</p>
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<p>Properties and mechanisms of NPs transport across cellular barriers The data are given as mean ± SD. (<b>A</b>) The cytotoxicity study of coumarin-6 nanoparticles. (<b>B</b>) The difference in NP uptake by MDCK cells. (<b>C</b>) Epithelial barrier penetration studies of NPs. (<b>D</b>) The mechanism analysis of endocytosis of MDCK cells monolayer for nanoparticles with different properties by adding various inhibitors. (<b>E</b>) The mechanism analysis of NP transport across the epithelial cell barrier by adding different inhibitors.</p>
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19 pages, 2564 KiB  
Article
Genome Structure, Evolution, and Host Shift of Nosema
by Xiao Xiong, Christopher J. Geden, Yongjun Tan, Ying Zhang, Dapeng Zhang, John H. Werren and Xu Wang
Biology 2024, 13(11), 952; https://doi.org/10.3390/biology13110952 - 19 Nov 2024
Viewed by 588
Abstract
Nosema is a diverse fungal genus of unicellular, obligate symbionts infecting various arthropods. We performed comparative genomic analyses of seven Nosema species that infect bees, wasps, moths, butterflies, and amphipods. As intracellular parasites, these species exhibit significant genome reduction, retaining only about half [...] Read more.
Nosema is a diverse fungal genus of unicellular, obligate symbionts infecting various arthropods. We performed comparative genomic analyses of seven Nosema species that infect bees, wasps, moths, butterflies, and amphipods. As intracellular parasites, these species exhibit significant genome reduction, retaining only about half of the genes found in free-living yeast genomes. Notably, genes related to oxidative phosphorylation are entirely absent (p < 0.001), and those associated with endocytosis are significantly diminished compared to other pathways (p < 0.05). All seven Nosema genomes display significantly lower G-C content compared to their microsporidian outgroup. Species-specific 5~12 bp motifs were identified immediately upstream of start codons for coding genes in all species (p ≤ 1.6 × 10−72). Our RNA-seq data from Nosema muscidifuracis showed that this motif is enriched in highly expressed genes but depleted in lowly expressed ones (p < 0.05), suggesting it functions as a cis-regulatory element in gene expression. We also discovered diverse telomeric repeats within the genus. Phylogenomic analyses revealed two major Nosema clades and incongruency between the Nosema species tree and their hosts’ phylogeny, indicating potential host switch events (100% bootstrap values). This study advances the understanding of genomic architecture, gene regulation, and evolution of Nosema, offering valuable insights for developing strategies to control these microbial pathogens. Full article
(This article belongs to the Special Issue Advances in Evolutionary Ecology of Host–Parasite Interactions)
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Figure 1
<p>A novel type of telomere in the <span class="html-italic">Nosema Muscidifuracis</span> genome. (<b>A</b>) Presence of telomeric sequences at the termini of 28 <span class="html-italic">N. Muscidifuracis</span> genome contigs. (<b>B</b>) Plot of GC content along contig14 showing the high GC content at telomeric regions. (<b>C</b>) Sequence alignment at the telomere-subtelomere boundaries, showing the novel composite 4 bp and 5 bp telomeric repeat motifs. (<b>D</b>) Total length and relative abundance of telomeric repeat motifs (TAGG, TTAGG, and TAGGG) in telomeric regions. (<b>E</b>) Phylogenetic tree of 27 subtelomeric sequences from different genomic contigs in <span class="html-italic">N. muscidifuracis</span>. (Yellow shading, subtelomeric region. Red color, positions that are not identical across all contigs. Purple shading: TTAGG repeats in telomeric region. Green shading: TAGG repeats in telomeric region).</p>
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<p><b>Functional pathway specific genome reduction in <span class="html-italic">Nosema muscidifuracis</span>.</b> (<b>A</b>) Gene number in 23 pathways in <span class="html-italic">Nosema muscidifuracis</span> and <span class="html-italic">Saccharomyces cerevisiae</span> (Chi-squared test, *, <span class="html-italic">p</span> &lt; 0.05; ***, <span class="html-italic">p</span> &lt; 0.001). (<b>B</b>) KEGG pathway analysis of <span class="html-italic">Nosema muscidifuracis</span> mitochondrial proteins suggested that the entire electron transport chain and eukaryotic F-type ATPase were completely missing in the mitochondrial oxidative phosphorylation metabolic pathway. The enzymes/proteins that are present in the <span class="html-italic">N. muscidifuracis</span> genome are shaded in red.</p>
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<p>A motif associated with translation start sites and gene expression levels in <span class="html-italic">Nosema muscidifuracis</span>. (<b>A</b>) A sequence motif enriched upstream of <span class="html-italic">N. muscidifuracis</span> genes, containing a homopolymer of seven thymine (T) nucleotides, followed by an adenine (<b>A</b>) and three consecutive cytosine (C) nucleotides. (<b>B</b>) Distribution of the motif upstream of the gene regions. The <span class="html-italic">x</span>-axis measures the distance from the first nucleotide of the motif to the start codon in bases, and the <span class="html-italic">y</span>-axis indicates the number of detected motifs. (<b>C</b>) Average RNA-seq coverage across protein-coding gene regions in <span class="html-italic">N. muscidifuracis</span>. (<b>D</b>) The percentage of genes with the motif in gene groups with different expression levels.</p>
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<p>Phylogenomic analysis revealed a host switch event and conserved sequence motifs in <span class="html-italic">Nosema</span>. A maximum-likelihood tree of <span class="html-italic">N. muscidifuracis</span> isolated in parasitoid wasps <span class="html-italic">Muscidifurax zaraptor</span> (NosMusMzar) and <span class="html-italic">M. raptor</span> (NosMusMrap) with other <span class="html-italic">Nosema</span> was constructed based on 449 shared proteins. The <span class="html-italic">Nosema</span> species/strains included are <span class="html-italic">N. apis</span> strain BRL01 (NosApis), <span class="html-italic">N. ceranae</span> strain PA08 1199 (NcerPA08), <span class="html-italic">N. ceranae</span> strain BRL (NcerBRL), <span class="html-italic">N. ceranae</span> strain BRL01 (NcerBRL01), the tussar moth <span class="html-italic">Antheraea pernyi Nosema strain YNPr</span> (NosYNPr), <span class="html-italic">N. antheraeae</span> strain YY (NosYY), <span class="html-italic">N. bombycis</span> strain CQ1 (NosBomCQ1), and <span class="html-italic">N. granulosis</span> strain Ou3-Ou53 (NosGranOu53). The <span class="html-italic">Encephalitozoon cuniculi</span> GB-M1 strain (Ecuniculi) was included as the outgroup. The bootstrap value is indicated by dots, with red representing a support level of 100/100. The length of each branch is indicated beneath the branches. The sequence logos displayed the conserved motifs located upstream of the start codons, as predicted by MEME using 449 shared orthologous genes and other gene models in the seven <span class="html-italic">Nosema</span> species and <span class="html-italic">E. cuniculi</span>. Genome-wide average G-C content for each species is displayed beneath their respective logos. The inferred ancestral G-C content, along with the standard deviation, is labeled near the nodes and shaded in orange.</p>
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<p>Codon bias and evolution toward AT-rich genomes in <span class="html-italic">Nosema</span>. (<b>A</b>) Boxplot of GC3 (G-C content at the 3rd codon position) over G-C content at all condo positions, rank ordered by the genome average G-C content in <span class="html-italic">Encephalitozoon cuniculi</span> (Ecuni), <span class="html-italic">Nosema granulosis</span> (NgOu53), <span class="html-italic">Nosema bombycis</span> (NosBom), <span class="html-italic">Nosema antheraeae</span> (NosYY), <span class="html-italic">Nosema ceranae</span> (Ncer), <span class="html-italic">Nosema</span> sp. <span class="html-italic">YNPr</span> (NosYNPr), <span class="html-italic">Nosema muscidifuracis</span> (Nmus), and <span class="html-italic">Nosema apis</span> (Napis). (<b>B</b>) The correlation between coding region G-C content (<span class="html-italic">x</span>-axis) and GC3/GC (<span class="html-italic">y</span>-axis). (<b>C</b>) Proportion of codon usage for glutamic acid and tyrosine in eight microsporidian genomes. The proportion of arginine codon usage across eight microsporidian genomes. (<b>D</b>) Proportion of codon usage for alanine and threonine in eight microsporidian genomes (Chi-squared test, ***, <span class="html-italic">p</span> &lt; 0.001). (<b>E</b>) Proportion of codon usage for arginine in eight microsporidian genomes. (<b>F</b>) Proportion of STOP codon usage in eight microsporidian genomes.</p>
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