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Cells, Volume 11, Issue 1 (January-1 2022) – 179 articles

Cover Story (view full-size image): Mammalian fertilization is a Ca2+-dependent multistep process leading to gamete fusion. Herein, we report the expression of Ca2+-dependent adhesion proteins epithelial (E-cad) and neural (N-cad) cadherin in murine gametes and evidence of their involvement in fertilization. E-cad and N-cad were immunodetected in spermatozoa, cumulus cells, and oocytes. Both cadherins were found to participate in oolemma binding, fusion, and in vitro fertilization, as these processes were inhibited with specific antibodies or blocking peptides. Conversely, E-cad alone was found to have a role in cumulus penetration, as neither the N-cad antibody nor the peptide impaired this event. Our studies demonstrate the expression of members of the adherent complex in mice and confirm previous observations in the human model, reinforcing evidence on E-cad and N-cad involvement in mammalian fertilization. View this paper
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22 pages, 2801 KiB  
Review
Metabolic Implications of Immune Checkpoint Proteins in Cancer
by Elizabeth R. Stirling, Steven M. Bronson, Jessica D. Mackert, Katherine L. Cook, Pierre L. Triozzi and David R. Soto-Pantoja
Cells 2022, 11(1), 179; https://doi.org/10.3390/cells11010179 - 5 Jan 2022
Cited by 21 | Viewed by 5973
Abstract
Expression of immune checkpoint proteins restrict immunosurveillance in the tumor microenvironment; thus, FDA-approved checkpoint inhibitor drugs, specifically PD-1/PD-L1 and CTLA-4 inhibitors, promote a cytotoxic antitumor immune response. Aside from inflammatory signaling, immune checkpoint proteins invoke metabolic reprogramming that affects immune cell function, autonomous [...] Read more.
Expression of immune checkpoint proteins restrict immunosurveillance in the tumor microenvironment; thus, FDA-approved checkpoint inhibitor drugs, specifically PD-1/PD-L1 and CTLA-4 inhibitors, promote a cytotoxic antitumor immune response. Aside from inflammatory signaling, immune checkpoint proteins invoke metabolic reprogramming that affects immune cell function, autonomous cancer cell bioenergetics, and patient response. Therefore, this review will focus on the metabolic alterations in immune and cancer cells regulated by currently approved immune checkpoint target proteins and the effect of costimulatory receptor signaling on immunometabolism. Additionally, we explore how diet and the microbiome impact immune checkpoint blockade therapy response. The metabolic reprogramming caused by targeting these proteins is essential in understanding immune-related adverse events and therapeutic resistance. This can provide valuable information for potential biomarkers or combination therapy strategies targeting metabolic pathways with immune checkpoint blockade to enhance patient response. Full article
(This article belongs to the Special Issue Metabolic Interactions in Tumor Microenvironment (TME))
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Figure 1
<p>Immune checkpoint proteins regulate metabolic signaling on T cells. (<b>A</b>) Interactions with cancer or antigen-presenting cells can modulate T cell metabolism (<b>B</b>) PD-L1 binding to PD-1, regulates fatty acid oxidation on T cells and limits glutamine metabolism by reduction of SNAT1/2 (<b>C</b>) Activation of CTLA-4 inhibits glycolysis within activated effector T cells inhibiting PI3K/AKT signaling, reduction of glucose uptake by inhibition of GLUT-1.</p>
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<p>Stimulatory checkpoint proteins regulate metabolic signaling. (<b>A</b>) CD28 activation promotes PI3K/Akt/mTORC1 pathway signaling, increasing glycolysis and mitochondrial metabolism. (<b>B</b>) ICOS/ICOSL activation increases glucose uptake and metabolism through mTOR activation. (<b>C</b>) GITR activation can stimulate the TCA cycle by metabolism lipid, glucose, and other nutrient stores (<b>D</b>) 4-1BB activation increases GLUT-1 expression to enhance glycolysis and fatty acid metabolism through LKB1/AMPK/ACC pathway activation.</p>
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<p>Regulation of metabolic signaling of immune checkpoint inhibitors on cancer cells. (<b>A</b>) PD-L1 engagement results in activation of glycolysis and activation of the PI3K/Akt/mTOR pathway. (<b>B</b>) Antibodies to PD-L1 are known to inhibit its metabolic signaling. (<b>C</b>) PD-1 on cancer cells limits Akt and ERK1/2 signaling regulating cancer cell proliferation.</p>
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<p>Metabolic signaling and regulation of PD-L1 expression. (<b>A</b>) Glucose (GLU) starvation and activation of AMPK results in the degradation of PD-L1 and a decrease in its expression. (<b>B</b>) Glutamine (GLN) depletion activates EGFR and MAPK signaling, resulting in the upregulation of PD-L1 during hypoxia.</p>
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18 pages, 3983 KiB  
Protocol
Isolation and Propagation of Human Corneal Stromal Keratocytes for Tissue Engineering and Cell Therapy
by Nur Zahirah binte M. Yusoff, Andri K. Riau, Gary H. F. Yam, Nuur Shahinda Humaira binte Halim and Jodhbir S. Mehta
Cells 2022, 11(1), 178; https://doi.org/10.3390/cells11010178 - 5 Jan 2022
Cited by 23 | Viewed by 3744
Abstract
The human corneal stroma contains corneal stromal keratocytes (CSKs) that synthesize and deposit collagens and keratan sulfate proteoglycans into the stromal matrix to maintain the corneal structural integrity and transparency. In adult corneas, CSKs are quiescent and arrested in the G0 phase of [...] Read more.
The human corneal stroma contains corneal stromal keratocytes (CSKs) that synthesize and deposit collagens and keratan sulfate proteoglycans into the stromal matrix to maintain the corneal structural integrity and transparency. In adult corneas, CSKs are quiescent and arrested in the G0 phase of the cell cycle. Following injury, some CSKs undergo apoptosis, whereas the surviving cells are activated to become stromal fibroblasts (SFs) and myofibroblasts (MyoFBs), as a natural mechanism of wound healing. The SFs and MyoFBs secrete abnormal extracellular matrix proteins, leading to corneal fibrosis and scar formation (corneal opacification). The issue is compounded by the fact that CSK transformation into SFs or MyoFBs is irreversible in vivo, which leads to chronic opacification. In this scenario, corneal transplantation is the only recourse. The application of cell therapy by replenishing CSKs, propagated in vitro, in the injured corneas has been demonstrated to be efficacious in resolving early-onset corneal opacification. However, expanding CSKs is challenging and has been the limiting factor for the application in corneal tissue engineering and cell therapy. The supplementation of serum in the culture medium promotes cell division but inevitably converts the CSKs into SFs. Similar to the in vivo conditions, the transformation is irreversible, even when the SF culture is switched to a serum-free medium. In the current article, we present a detailed protocol on the isolation and propagation of bona fide human CSKs and the morphological and genotypic differences from SFs. Full article
(This article belongs to the Special Issue 10th Anniversary of Cells—Advances in Cell Techniques)
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<p>Overview of human corneal stromal keratocyte (CSK) cell culture procedure. In the propagation phase, the culture medium is supplemented with 0.5% fetal bovine serum (FBS) to support the proliferation of CSKs, which are otherwise quiescent. In the stabilization phase, the FBS is removed from the culture medium to allow the cells to regain bona fide CSK phenotypes.</p>
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<p>Still photographs of the human corneal tissue dissection. (<b>A</b>–<b>D</b>) The first dissection steps involve the removal of the corneal epithelial and endothelial cells, and trabecular meshwork from the corneas, by scraping with a surgical blade no. 10. (<b>E</b>,<b>F</b>) The corneal stroma is then separated from the scleral tissue by cutting ~2 mm from the sclera. (<b>G</b>–<b>I</b>) Finally, the corneal stroma is cut into smaller pieces by leaving the edges of each piece still attached to the adjacent pieces.</p>
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<p>Proliferative capacity of corneal stromal keratocytes (CSKs), activated CSKs (A-CSKs), and stromal fibroblasts (SFs). The representative images of CSKs (<b>A</b>), A-CSKs (<b>B</b>), and SFs (<b>C</b>) were captured from cells at P5, which were expanded from the same donor. (<b>D</b>) The proliferative capacity (indicated by Ki-67-positive cells/total number of cells × 100%) of the A-CSKs was 5.6 ± 6.1%. On day 14, following medium switching to serum-free conditions, the proliferative capacity of CSKs was 0%. The SFs had a significantly higher proliferation rate of 20.1 ± 7.2% compared to both the CSKs (<span class="html-italic">p</span> = 3.55 × 10<sup>−8</sup>) and the activated CSKs (<span class="html-italic">p</span> = 3.78 × 10<sup>−5</sup>). Group comparisons were statistically determined using one-way ANOVA and Tukey comparison tests. Scale bars = 100 μm.</p>
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<p>Morphology of corneal stromal keratocytes (CSKs), activated CSKs (A-CSKs), and stromal fibroblasts (SFs). The representative images were captured from cells at P5, which were expanded from the same donor. (<b>A</b>–<b>F</b>) Brightfield images at low and high magnification revealed the loss of thin, dendritic morphology and long cellular processes, typically seen in the CSKs, in the SFs. The SFs also featured larger cell bodies compared to the CSKs and A-CSKs. (<b>G</b>–<b>I</b>) Phalloidin staining showed the stellate morphology of the CSKs, which was progressively lost in the A-CSK and SF cell culture. Scale bars = 100 μm.</p>
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<p>Protein expression of corneal stromal keratocytes (CSKs), activated CSKs (A-CSKs), and corneal fibroblasts (SFs). (<b>A</b>,<b>D</b>,<b>G</b>,<b>J</b>) Typical CSK markers, such as ALDH1A1, ALDH3A1, keratocan, and lumican were strongly expressed in the CSKs following 14 days of culture media switching to serum-free conditions. (<b>B</b>,<b>E</b>,<b>H</b>,<b>K</b>) In the propagation medium, the A-CSKs exhibited an attenuated expression of the CSK markers. (<b>C</b>,<b>F</b>,<b>I</b>,<b>L</b>) In contrast, in medium supplemented with 5% FBS, the SFs did not express or express only a little of the CSK markers. (<b>M</b>,<b>N</b>,<b>O</b>) All three cell types were not immunoreactive with α-smooth muscle actin (α-SMA), the cell marker of corneal stromal myofibroblasts (see inset in pane O). Scale bars = 50 μm.</p>
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<p>Gene expression of corneal stromal keratocytes (CSKs), activated CSKs (A-CSKs), and corneal fibroblasts (SFs). The gene expression was detected using real time-polymerase chain reaction. Similar to the protein expression, CSK-associated genes, such as <span class="html-italic">ALDH1A1</span> (<b>A</b>), <span class="html-italic">ALDH3A1</span> (<b>B</b>), <span class="html-italic">KERA</span> (<b>C</b>), and <span class="html-italic">LUM</span> (<b>D</b>) were strongly expressed in the CSKs following 14 days of culture media switching to serum-free conditions and were significantly upregulated when compared to the A-CSKs and SFs. (<b>E</b>) The corneal stromal myofibroblast (MyoFB)-associated gene, <span class="html-italic">ACTA2</span>, was significantly downregulated in the CSKs, A-CSKs, and SFs compared to the MyoFBs. For the analysis of differentially expressed genes, CSKs was used as the reference group for comparison, whereas GAPDH was used as the housekeeping gene. Group comparisons were statistically determined using one-way ANOVA and Tukey comparison tests.</p>
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18 pages, 6420 KiB  
Article
Bioengineered Cystinotic Kidney Tubules Recapitulate a Nephropathic Phenotype
by Elena Sendino Garví, Rosalinde Masereeuw and Manoe J. Janssen
Cells 2022, 11(1), 177; https://doi.org/10.3390/cells11010177 - 5 Jan 2022
Cited by 5 | Viewed by 3009
Abstract
Nephropathic cystinosis is a rare and severe disease caused by disruptions in the CTNS gene. Cystinosis is characterized by lysosomal cystine accumulation, vesicle trafficking impairment, oxidative stress, and apoptosis. Additionally, cystinotic patients exhibit weakening and leakage of the proximal tubular segment of the [...] Read more.
Nephropathic cystinosis is a rare and severe disease caused by disruptions in the CTNS gene. Cystinosis is characterized by lysosomal cystine accumulation, vesicle trafficking impairment, oxidative stress, and apoptosis. Additionally, cystinotic patients exhibit weakening and leakage of the proximal tubular segment of the nephrons, leading to renal Fanconi syndrome and kidney failure early in life. Current in vitro cystinotic models cannot recapitulate all clinical features of the disease which limits their translational value. Therefore, the development of novel, complex in vitro models that better mimic the disease and exhibit characteristics not compatible with 2-dimensional cell culture is of crucial importance for novel therapies development. In this study, we developed a 3-dimensional bioengineered model of nephropathic cystinosis by culturing conditionally immortalized proximal tubule epithelial cells (ciPTECs) on hollow fiber membranes (HFM). Cystinotic kidney tubules showed lysosomal cystine accumulation, increased autophagy and vesicle trafficking deterioration, the impairment of several metabolic pathways, and the disruption of the epithelial monolayer tightness as compared to control kidney tubules. In particular, the loss of monolayer organization and leakage could be mimicked with the use of the cystinotic kidney tubules, which has not been possible before, using the standard 2-dimensional cell culture. Overall, bioengineered cystinotic kidney tubules recapitulate better the nephropathic phenotype at a molecular, structural, and functional proximal tubule level compared to 2-dimensional cell cultures. Full article
(This article belongs to the Special Issue Cellular and Molecular Mechanisms of Nephropathic Cystinosis)
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<p>Confocal images of healthy and cystinotic ciPTECs kidney tubules. After maturation of 7 days, the control ciPTEC (<b>A</b>) form an organized 3-dimensional structure including primary cilia. Both cystinotic kidney tubule models (<b>B</b>,<b>C</b>) show visible holes in the monolayer when compared to the healthy proximal tubule model (<b>A</b>). The close-up images represent a 3-fold zoom increase. In blue: DAPI (nuclei staining), in red: α-tubulin staining, in green: Na<sup>+</sup>/K<sup>+</sup>-ATPase. Scale bar: 100 μm.</p>
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<p>Cellular organization of kidney tubules. Kidney tubules were stained using phalloidin to show the organization of actin filaments in ciPTEC <span class="html-italic">CTNS<sup>WT</sup></span> (<b>A</b>), <span class="html-italic">CTNS</span><sup>−/−</sup> (<b>B</b>), and <span class="html-italic">CTNS<sup>Patient</sup></span> (<b>C</b>). Both cystinotic models (<b>B</b>,<b>C</b>) present a disrupted cell monolayer with visible holes along the membrane when compared to the control cells (<b>A</b>), which is also seen in the image directionality quantification (<b>D</b>–<b>F</b>). In blue: DAPI (nuclei staining), in red: Phalloidin (binds to actin filaments). Directionality analysis was performed in three biological replicates. Scale bar: 100 μm.</p>
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<p>Cellular organization in 2D cell culture. Cells were stained using phalloidin to show the organization of actin filaments in ciPTEC <span class="html-italic">CTNS</span><sup>WT</sup> (<b>A</b>), <span class="html-italic">CTNS</span><sup>−/−</sup> (<b>B</b>), and <span class="html-italic">CTNS</span><sup>Patient</sup> (<b>C</b>). Image directionality analysis revealed loss of organization in all the cell lines when cultured in 2D (<b>D</b>–<b>F</b>). In blue: DAPI (nuclei staining), in red: Phalloidin (binds to actin filaments). Directionality analysis was performed in two biological replicates Scale bar: 100 μm.</p>
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<p>FITC inulin leakage assay in kidney. (<b>A</b>) Graphical presentation of the experimental set-up for the assessment of the monolayer leakage. The kidney tubules were secured into a 3-D printed chamber and connected to a pump with an in-let and out-let needle. Fluorescent FITC-inulin solution was perfused through the inside of the fiber and after 10 min, the solution that leaked through the kidney tubules to the extraluminal compartment was collected and measured. (<b>B</b>) Leakage of the healthy and cystinotic kidney tubules is expressed in fold change compared to the healthy control and normalized to a double-coated but unseeded HFM. One-way ANOVA statistical analysis was performed (N = 3; ** <span class="html-italic">p</span>-value &lt; 0.01; **** <span class="html-italic">p</span>-value &lt; 0.0001).</p>
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<p>Cystine accumulation and <span class="html-italic">CTNS</span> expression in kidney tubules. Real-time PCR quantification showed significant reduction of <span class="html-italic">CTNS</span> gene expression in both cystinotic tubule models when compared to the healthy control (<b>A</b>), which led to an increase in cystine accumulation in the cystinotic kidney tubules (<b>B</b>). One-way ANOVA statistical analysis was performed (N = 3; * <span class="html-italic">p</span>-value &lt; 0.05; ** <span class="html-italic">p</span>-value &lt; 0.01; *** <span class="html-italic">p</span>-value &lt; 0.001; **** <span class="html-italic">p</span>-value &lt; 0.0001).</p>
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<p>Autophagic markers in kidney tubules. Images obtained with a confocal microscope at 63X of the ciPTEC <span class="html-italic">CTNS<sup>WT</sup></span> (<b>A</b>), <span class="html-italic">CTNS<sup>−/−</sup></span> (<b>B</b>), and <span class="html-italic">CTNS<sup>Patient</sup></span> (<b>C</b>) kidney tubules. Image quantification analysis showed a significant increase of the autophagy markers LC3 and p62 in the cystinotic 3D models when compared to the healthy control (<b>D</b>). Real-time PCR quantification also showed a significant impairment of the autophagy-related genes TFEB and p62 in the cystinotic models when compared to the healthy control (<b>E</b>). In blue: nuclei, in green: LC3 protein, in red: p62 protein. Scale bar: 10 μm. One-way ANOVA statistical analysis was performed (N = 3; * <span class="html-italic">p</span>-value &lt; 0.05; ** <span class="html-italic">p</span>-value &lt; 0.01; **** <span class="html-italic">p</span>-value &lt; 0.0001).</p>
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<p>mTOR and LAMP1 staining and colocalization in kidney tubules. Confocal microscopy images taken at 63X of the ciPTEC <span class="html-italic">CTNS</span><span class="html-italic"><sup>WT</sup></span> (<b>A</b>), <span class="html-italic">CTNS</span><sup>−/−</sup> (<b>B</b>), and <span class="html-italic">CTNS</span><span class="html-italic"><sup>Patient</sup></span> (<b>C</b>) kidney tubules. Image analysis quantification showed co-localization of the mTOR/LAMP1 complex in the healthy control and loss of co-localization in both cystinotic models (<b>D</b>), suggesting an impaired autophagosome-lysosome trafficking. In blue: DAPI (nuclei), in green: LAMP1 protein, in red: mTOR protein. Scale bar: 10 μm. One-way ANOVA statistical analysis was performed (N = 3; **** <span class="html-italic">p</span>-value &lt; 0.0001).</p>
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<p>Metabolomic profiling of kidney tubules. Principal component analysis (PCA) of the ciPTEC <span class="html-italic">CTNS</span><sup>WT</sup>, <span class="html-italic">CTNS</span><sup>−/−</sup>, and <span class="html-italic">CTNS</span><span class="html-italic"><sup>Patient</sup></span> kidney tubule models based on the metabolites set measured. In the plot, the individual dots represent one biological repeat, and dots of the same color are the same experimental group (healthy (<span class="html-italic">CTNS<sup>WT</sup></span>, <span class="html-italic">CTNS</span><sup>−/−</sup> and <span class="html-italic">CTNS</span><span class="html-italic"><sup>Patient</sup></span> kidney tubules) (<b>A</b>). Heatmap analysis of the top 60 metabolites differentially expressed in healthy and cystinotic kidney tubule models. Every row represents a different metabolite and its associated Z-score. Significantly increased metabolites (<span class="html-italic">p</span> &lt; 0.01) are displayed in red, and significantly decreased metabolites (<span class="html-italic">p</span> &lt; 0.01) are displayed in blue (<b>B</b>). Global pathway enrichment analysis of the metabolic pathways differentially expressed in the <span class="html-italic">CTNS</span><sup>−/−</sup> compared to the healthy kidney tubules. The larger the circles and the further they appear from the y-axis, the higher the impact of that pathway in the <span class="html-italic">CTNS</span><sup>−/−</sup> kidney tubules (<b>C</b>). Data was normalized to the median intensity. Data analysis was performed using univariate and multivariate analysis (N = 2; <span class="html-italic">p</span>-values &lt; 0.05 were considered significant).</p>
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<p>Cystinotic kidney tubules accumulate α-KG. Real-time PCR quantification show a significant 45% and 89% reduction (<span class="html-italic">CTNS</span><sup>−/−</sup> and <span class="html-italic">CTNS</span><span class="html-italic"><sup>Patient</sup></span> kidney tubules, respectively) of the <span class="html-italic">AKGDH</span> gene (<b>A</b>). Cystinotic kidney tubules significantly accumulate α-KG in the cytoplasm (<b>B</b>). One-way ANOVA statistical analysis was performed (N = 3; *** <span class="html-italic">p</span>-value &lt; 0.001; **** <span class="html-italic">p</span>-value &lt; 0.0001).</p>
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16 pages, 28830 KiB  
Article
Targeting PGM3 as a Novel Therapeutic Strategy in KRAS/LKB1 Co-Mutant Lung Cancer
by Hyunmin Lee, Feng Cai, Neil Kelekar, Nipun K. Velupally and Jiyeon Kim
Cells 2022, 11(1), 176; https://doi.org/10.3390/cells11010176 - 5 Jan 2022
Cited by 11 | Viewed by 4879
Abstract
In non-small-cell lung cancer (NSCLC), concurrent mutations in the oncogene KRAS and tumor suppressor STK11 (also known as LKB1) confer an aggressive malignant phenotype, an unfavourability towards immunotherapy, and overall poor prognoses in patients. In a previous study, we showed that murine KRAS/LKB1 [...] Read more.
In non-small-cell lung cancer (NSCLC), concurrent mutations in the oncogene KRAS and tumor suppressor STK11 (also known as LKB1) confer an aggressive malignant phenotype, an unfavourability towards immunotherapy, and overall poor prognoses in patients. In a previous study, we showed that murine KRAS/LKB1 co-mutant tumors and human co-mutant cancer cells have an enhanced dependence on glutamine-fructose-6-phosphate transaminase 2 (GFPT2), a rate-limiting enzyme in the hexosamine biosynthesis pathway (HBP), which could be targeted to reduce survival of KRAS/LKB1 co-mutants. Here, we found that KRAS/LKB1 co-mutant cells also exhibit an increased dependence on N-acetylglucosamine-phosphate mutase 3 (PGM3), an enzyme downstream of GFPT2. Genetic or pharmacologic suppression of PGM3 reduced KRAS/LKB1 co-mutant tumor growth in both in vitro and in vivo settings. Our results define an additional metabolic vulnerability in KRAS/LKB1 co-mutant tumors to the HBP and provide a rationale for targeting PGM3 in this aggressive subtype of NSCLC. Full article
(This article belongs to the Special Issue New Aspects of Targeting Cancer Metabolism in Therapeutic Approach)
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Figure 1
<p>GFPT2 inhibition selectively reduces glycosylation of KL co-mutant NSCLC cells. (<b>A</b>) Schematic of the HBP, including azaserine, the GFPT inhibitor. Metabolites are in black and enzymes are in red. Metabolites in the glycosylation pathway are shaded in lilac and those in O-GlcNAcylation are shaded in light blue. F6P, fructose-6-phosphate; Gln, glutamine. (<b>B</b>) GFPT2 and LKB1 expression levels were measured in H2122 (<b>left</b>) and H460 (<b>right</b>) KL co-mutant cells depleted of GFPT2 using endoribonuclease-prepared siRNA (esi<span class="html-italic">GFPT2</span>). Actin was used as the loading control. (<b>C</b>) Schematic for cell-surface <span class="html-italic">Sambucus nigra</span> (SNA), <span class="html-italic">Lycopersicon esculentum</span> (LEA), phytohemagglutinin-L (L-PHA) lectins, and corresponding glycan structures, where each lectin interacts. Symbol nomenclature for glycans is shown. (<b>D</b>) Cell surface L-PHA lectin binding was measured by flow cytometry in empty vector (EV)- and LKB1-expressing H460 (<b>left</b>) and H2122 (<b>right</b>) KL co-mutant cells depleted of GFPT2 by esi<span class="html-italic">GFPT2</span>. (<b>E</b>) Cell surface L-PHA lectin binding was measured by flow cytometry in EV- and LKB1-expressing H460 (<b>left</b>) and H2122 (<b>right</b>) KL co-mutant cells treated with azaserine (1 µM, three days). (<b>F</b>) Cell-surface L-PHA lectin binding was measured by flow cytometry in sh<span class="html-italic">GFP</span>- (control) and sh<span class="html-italic">LKB1</span>-expressing H1373 K mutant cells treated with azaserine (1 µM, three days). Mean fluorescence intensity (MFI). (<b>D</b>–<b>F</b>) Statistical significance was assessed using two-tailed Student’s <span class="html-italic">t</span>-test/each isogenic pair. n.s., not significant; * <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. FACS analyses were performed twice, and western blots were repeated three or more times.</p>
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<p>PGM3 inhibition also selectively reduces glycosylation of KL co-mutant NSCLC cells. (<b>A</b>) Schematic of the HBP. Metabolites are in black and enzymes are in red. Metabolites in the glycosylation pathway are shaded in lilac, and those in O-GlcNAcylation are shaded in light blue. (<b>B</b>) PGM3 and LKB1 expression levels were measured in EV- and LKB1-expressing H2122 (<b>left</b>) and H460 (<b>middle</b>) KL co-mutant cells and in sh<span class="html-italic">GFP</span>- and sh<span class="html-italic">LKB1</span>-expressing H1373 (<b>right</b>) K mutant cells, depleted of PGM3 using esiRNA targeting <span class="html-italic">PGM3</span>. Vinculin was used as the loading control. (<b>C</b>) Abundance of hexosamine metabolites in an isogenic pair of H460 KL co-mutant cells depleted of PGM3 by esi<span class="html-italic">PGM3</span>. Area under curve (AUC). (<b>D</b>) Wheat germ agglutinin (WGA) coupled with agarose was used to precipitate glycosylated proteins from EV- and LKB1-expressing H460 (<b>left</b>) KL co-mutant cells depleted of PGM3 by esi<span class="html-italic">PGM3</span>. Precipitated proteins were subsequently separated by SDS-PAGE then imaged. Band intensity was quantified with Photoshop, and relative band intensity was obtained by calculating a ratio between each WGA pulldown and input control. Total protein extract before the addition of WGA was used as input control. (<b>E</b>,<b>F</b>) Cell-surface SNA (<b>E</b>) and L-PHA (<b>F</b>) lectin binding was measured by flow cytometry in EV- and LKB1-expressing H2122 (<b>left</b>) and H460 (<b>middle</b>) and in sh<span class="html-italic">GFP</span>- and sh<span class="html-italic">LKB1</span>-expressing H1373 (<b>right</b>) cells depleted of PGM3 by esi<span class="html-italic">PGM3</span>. Mean fluorescence intensity (MFI). (<b>C</b>,<b>E</b>,<b>F</b>) Statistical significance was assessed using two-tailed Student’s <span class="html-italic">t</span>-test/each isogenic pair. n.s., not significant; * <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. FACS analyses were performed three times. Targeted metabolomics and WGA pulldown assays were performed once.</p>
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<p>KL co-mutant NSCLC cells require PGM3 for survival. (<b>A</b>) Schematic of the HBP. Metabolites are in black and enzymes are in red. Metabolites in the glycosylation pathway are shaded in lilac and those in O-GlcNAcylation are shaded in light blue. (<b>B</b>,<b>C</b>) Sensitivity to <span class="html-italic">PGM3</span> silencing in K mutant and KL co-mutant cells. Two isogenic pairs of KL co-mutant cells (<b>B</b>) and one isogenic pair of K mutant cells (<b>C</b>) were used. (<b>D</b>–<b>G</b>) Effect of <span class="html-italic">PGM3</span> silencing on cell death in NSCLC cells. (<b>D</b>,<b>E</b>) Representative dot plots of Annexin V/PI-stained cells with or without <span class="html-italic">PGM3</span> silencing. (<b>F</b>,<b>G</b>) Quantified data from triplicates/cell line tested in (<b>D</b>,<b>E</b>,<b>H</b>); Left<span class="html-italic">:</span> abundance of PGM3 in parental and <span class="html-italic">PGM3</span> knockout cells. Three KL co-mutant cells were used. Right<span class="html-italic">:</span> Effect of <span class="html-italic">PGM3</span> knockout on anchorage-independent growth of KL co-mutant cells. Representative images of colony formation assay (<span class="html-italic">n</span> = 3). (<b>I</b>) Quantified data from (<b>H</b>). (<b>B</b>,<b>C</b>) Statistical significance was assessed using two-tailed Student’s <span class="html-italic">t</span>-test/each isogenic pair. **** <span class="html-italic">p</span> &lt; 0.0001. (<b>F</b>,<b>G</b>) Statistical significance was assessed using one-way ANOVA with Tukey’s multiple comparisons test. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.0001, compared to EV, with control siRNA transfection (<b>F</b>) or sh<span class="html-italic">GFP</span> with control siRNA transfection (<b>G</b>). <sup><span>$</span></sup> <span class="html-italic">p</span> &lt; 0.0001, compared to LKB1 with control siRNA transfection (<b>F</b>) or sh<span class="html-italic">LKB1</span> with control siRNA transfection (<b>G</b>). * <span class="html-italic">p</span> &lt; 0.0001, compared to LKB1, with <span class="html-italic">PGM3</span> siRNA transfection (<b>F</b>) or sh<span class="html-italic">LKB1</span> with <span class="html-italic">PGM3</span> siRNA transfection (<b>G</b>). (<b>I</b>) Statistical significance was assessed using two-tailed Student’s <span class="html-italic">t</span>-test/each pair of cell line. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01. Western blots, FACS analyses, and soft agar assay were all performed twice.</p>
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<p>PGM3 inhibitor FR054 reduces the HBP flow in both KL and K cells but selectively suppresses glyco-functionalization pathways in KL co-mutant NSCLC cells. (<b>A</b>) Schematic of the HBP, including FR054, the inhibitor of PGM3. [γ-<sup>15</sup>N]glutamine is depicted. (<b>B</b>) <b>Left</b>: time course of <sup>15</sup>N labelling in UDP-HexNAc in EV- and LKB1-expressing H460 cells cultured with [γ-<sup>15</sup>N]glutamine, treated with either DMSO (a vehicle control) or FR054 (50 µM, 3 days). <b>Right</b>: an abundance of UDP-HexNAc from labeling assay was measured by summing mass isotopologues, followed by protein normalization. (<b>C</b>) <b>Left</b>: <sup>15</sup>N labeling in UDP-HexNAc was measured in an isogenic pair of H1373 cells treated with either DMSO or FR054 (100 µM, 3 days). <b>Right</b>: <sup>15</sup>N labeling in ManNAc was measured in an isogenic pair of H1373 cells treated with either DMSO or FR054 (100 µM, 3 days). Cells were cultured with [γ-<sup>15</sup>N] glutamine for 6 h. (<b>D</b>) Effect of FR054 treatment on protein O-GlcNAcylation. One KL isogenic pair and two K isogenic pairs were used. WGA pulldown was performed (left/each cell line), and total protein extract before the addition of WGA was used as the input control (right/each cell line). Band intensity was quantified with Photoshop, and relative band intensity was obtained by calculating a ratio between each WGA pulldown band and input control. (<b>E</b>) Schematic for lectins and glycan structures. (<b>F</b>,<b>G</b>) Cell-surface LEA lectin binding was measured by flow cytometry in three isogenic pair cell lines with or without FR054 treatment for 3 days. (<b>H</b>,<b>I</b>) Cell-surface L-PHA lectin binding was measured by flow cytometry in three isogenic pair cell lines with or without FR054 treatment for 3 days. (<b>J</b>,<b>K</b>) Cell-surface SNA lectin binding was measured by flow cytometry in three isogenic pair cell lines with or without FR054 treatment for 3 days. (<b>B</b>) (left panel) Statistical significance was assessed using two-way ANOVA, followed by Tukey’s multiple comparisons test. * <span class="html-italic">p</span> &lt; 0.05 compared to EV-FR054; <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 compared to LKB1-DMSO; <sup><span>$</span></sup> <span class="html-italic">p</span> &lt; 0.05 compared to LKB1-FR054. (<b>B</b>) (right panel) Statistical significance was assessed using two-tailed Student’s <span class="html-italic">t</span>-test/each isogenic pair. ** <span class="html-italic">p</span> &lt; 0.01. (<b>C</b>,<b>F</b>–<b>K</b>) Statistical significance was assessed using two-tailed Student’s <span class="html-italic">t</span>-test/each isogenic pair. n.s., not significant; * <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. Targeted metabolomics and isotope tracing experiments were performed once. FACS analyses were performed twice.</p>
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<p>FR054 inhibits viability and clonogenicity of KL co-mutant NSCLC cells. (<b>A</b>–<b>C</b>) Sensitivity to <span class="html-italic">PGM3</span> silencing in K mutant and KL co-mutant cells. Two isogenic pairs of KL co-mutant cells (<b>A</b>), two isogenic pairs of K mutant cells (<b>B</b>), and murine NSCLC cells with either <span class="html-italic">KRAS/LKB1</span> co-mutations (KL) or <span class="html-italic">KRAS/TP53</span> co-mutations (KP) (<b>C</b>) were used. (<b>D</b>,<b>E</b>) Effect of FR054 treatment on cell death in K mutant cells and KL co-mutant cells. Three isogenic pairs were treated with either DMSO or FR054 (H460, 50 µM; H2122, 100 µM; H1373, 100 µM) for 3 days. Representative dot plots of FACS results/cell lines are shown. (<b>F</b>,<b>G</b>) Quantified FACS data from (<b>D</b>,<b>E</b>)<b>.</b> (<b>H</b>) Effect of <span class="html-italic">PGM3</span> knockout on anchorage-independent growth of K mutant cells and KL co-mutant cells (<span class="html-italic">n</span> = 3). FR054 concentration: H460, 50 µM; H2122, 100 µM; H1373, 100 µM. (<b>F</b>–<b>H</b>) Statistical significance was assessed using one-way ANOVA, followed by Tukey’s multiple comparisons test. n.s., not significant; ** <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. Cell viability assays (<span class="html-italic">n</span> = 6), FACS analysis, and soft agar assays were performed twice.</p>
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<p>PGM3 inhibition reduces KL co-mutant NSCLC tumor growth in vivo. (<b>A</b>) Schematic diagram of the experimental procedure. sh<span class="html-italic">GFP</span>-expressing H1373 cells (1 × 10<sup>6</sup>cells) were injected into the left flank of the mouse, and sh<span class="html-italic">LKB1</span>-expressing H1373 cells (1 × 10<sup>6</sup> cells) were injected into the right flank of the mouse. (<b>B</b>) Growth of sh<span class="html-italic">GFP</span>- and sh<span class="html-italic">LKB1</span>-expressing H1373 xenografts in the presence and absence of FR054 (500 mg/kg/dose, twice a day, 14 days total). Mean tumor volume and s.d. are shown for each group (<span class="html-italic">n</span> = 4). (<b>C</b>) Mouse weight with either vehicle control or FR054 at the day of euthanasia. (<b>D</b>) Representative Ki67 staining images of vehicle-treated and FR054-treated mice (<span class="html-italic">n</span> = 3/condition). Scale bar, 500 µm. (<b>E</b>) Ki67+ cells and total cells/tumor were quantified using Matlab. (<b>F</b>) Representative TUNEL staining of tumor tissues. 4′,6-diamidino-2-phenylindole (DAPI) was used to stain DNA. Scale bars, 100 μm. (<b>G</b>) TUNEL+ cells and total cells/tumor were quantified using Matlab. (<b>H</b>) Working model. Metabolic alterations mediated by concurrent mutations of KRAS and LKB1 created PGM3 dependence. (<b>I</b>) Kaplan-Meier plot associating <span class="html-italic">PGM3</span> mRNA expression with NSCLC (LUAD, lung adenocarcinoma (<b>left</b>) and LUSC, lung squamous carcinoma (<b>right</b>)) patient survival. Dataset is from Lung Cancer Explore, generated by UTSW (<a href="https://lce.biohpc.swmed.edu/lungcancer/" target="_blank">https://lce.biohpc.swmed.edu/lungcancer/</a>, accessed on 21 November 2021). (<b>J</b>) Kaplan-Meier plot associating <span class="html-italic">PGM3</span> mRNA expression with bladder cancer (BLCA) and breast cancer (BRCA) patient survival. Dataset is from OncoLnc (<a href="http://www.oncolnc.org/" target="_blank">http://www.oncolnc.org/</a>, accessed on 21 November 2021). (<b>B</b>) Statistical significance was assessed using a two-way ANOVA with Tukey’s multiple comparisons test. * <span class="html-italic">p</span> &lt; 0.05 compared to DMSO. (<b>C</b>) Statistical significance was assessed using paired Student’s <span class="html-italic">t</span>-test. n.s., not significant. (<b>E</b>,<b>G</b>) Statistical significance was assessed using one-way ANOVA with Tukey’s multiple comparisons test. * <span class="html-italic">p</span> &lt; 0.05, compared to sh<span class="html-italic">GFP</span> with vehicle treatment, <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05, compared to sh<span class="html-italic">GFP</span> with FR054 treatment, <sup><span>$</span></sup> <span class="html-italic">p</span> &lt; 0.05, compared to sh<span class="html-italic">LKB1</span> with vehicle treatment. Tumor growth experiment was performed once.</p>
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27 pages, 14903 KiB  
Article
Accelerated Growth, Differentiation, and Ploidy with Reduced Proliferation of Right Ventricular Cardiomyocytes in Children with Congenital Heart Defect Tetralogy of Fallot
by Tatyana V. Sukhacheva, Roman A. Serov, Natalia V. Nizyaeva, Artem A. Burov, Stanislav V. Pavlovich, Yulia L. Podurovskaya, Maria V. Samsonova, Andrey L. Chernyaev, Aleksandr I. Shchegolev, Alexei I. Kim, Leo A. Bockeria and Gennady T. Sukhikh
Cells 2022, 11(1), 175; https://doi.org/10.3390/cells11010175 - 5 Jan 2022
Cited by 7 | Viewed by 3105
Abstract
The myocardium of children with tetralogy of Fallot (TF) undergoes hemodynamic overload and hypoxemia immediately after birth. Comparative analysis of changes in the ploidy and morphology of the right ventricular cardiomyocytes in children with TF in the first years of life demonstrated their [...] Read more.
The myocardium of children with tetralogy of Fallot (TF) undergoes hemodynamic overload and hypoxemia immediately after birth. Comparative analysis of changes in the ploidy and morphology of the right ventricular cardiomyocytes in children with TF in the first years of life demonstrated their significant increase compared with the control group. In children with TF, there was a predominantly diffuse distribution of Connexin43-containing gap junctions over the cardiomyocytes sarcolemma, which redistributed into the intercalated discs as cardiomyocytes differentiation increased. The number of Ki67-positive cardiomyocytes varied greatly and amounted to 7.0–1025.5/106 cardiomyocytes and also were decreased with increased myocytes differentiation. Ultrastructural signs of immaturity and proliferative activity of cardiomyocytes in children with TF were demonstrated. The proportion of interstitial tissue did not differ significantly from the control group. The myocardium of children with TF under six months of age was most sensitive to hypoxemia, it was manifested by a delay in the intercalated discs and myofibril assembly and the appearance of ultrastructural signs of dystrophic changes in the cardiomyocytes. Thus, the acceleration of ontogenetic growth and differentiation of the cardiomyocytes, but not the reactivation of their proliferation, was an adaptation of the immature myocardium of children with TF to hemodynamic overload and hypoxemia. Full article
(This article belongs to the Section Cell Proliferation and Division)
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Graphical abstract

Graphical abstract
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<p>Distribution of CMCs of different ploidy classes in patients with TF and the control group. Comparison of ploidy (2c:4c:8c:16c:32c) of patients with TF and the control group (<b>A</b>). The ploidy of the CMCs in children with TF was significantly higher than the CMCs in the control groups (median, Mann-Whitney test, <span class="html-italic">p</span> &lt; 0.05) (<b>B</b>). Comparison of CMCs ploidy classes in patients with TF and controls (<b>C</b>). Change in the ratio of different ploidy classes in patients with TF in different age groups: up to six months, 7–12 months, more than 13 months (<b>D</b>). Comparison of the proportion of binucleated CMCs in the group of children with TF and the control group (median, Mann-Whitney test, <span class="html-italic">p</span> &lt; 0.05) (<b>E</b>). Inverse correlation of CMCs ploidy in children with TF with Nakata index (r = −0.44; <span class="html-italic">p</span> = 0.034) (<b>F</b>). In the myocardium of children under six months of age with TF: CMCs ploidy correlated inversely with age (r = −0.73; <span class="html-italic">p</span> = 0.007) (<b>G</b>). The myocardium of patients with a high percentage of diploid CMCs differentiated faster—the number of CMCs filled with myofibrils increased in it (r = 0.68; <span class="html-italic">p</span> = 0.015) (<b>H</b>) and the number of CMCs not filled with myofibrils decreased (r = −0.68; <span class="html-italic">p</span> = 0.014) (<b>I</b>).</p>
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<p>RV myocardium of patients with TF and in the control group. In the myocardium of patients with TF: significant variability of the CMCs diameter was revealed: on average, from 7.5 ± 2.4 μm (patient with TF, 10 months) (<b>A</b>) and 10.0 ± 1.5 μm (patient with TF, 5 months) (<b>B</b>) up to 10.8 ± 1.5 μm (patient with TF, 8 months) (<b>C</b>). In the control group: the diameter was 4.7–7.7 microns (<b>D</b>,<b>E</b>). Hematoxylin and eosin (×400) bar 20 µm. The diameter of the CMCs of children with TF significantly exceeded <a href="#cells-11-00175-t001" class="html-table">Table 1</a>. (<b>F</b>). In children with TF over 6 months of age: The proportion of CMCs filled with myofibrils increased with age (r = 0.49; <span class="html-italic">p</span> = 0.003) (<b>G</b>), a high-pressure gradient on the pulmonary artery provoked accelerated differentiation with a decrease in the number of CMCs with sarcoplasm not filled with myofibrils (r = −0.39; <span class="html-italic">p</span> = 0.04) (<b>H</b>).</p>
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<p>Connexin-43-containing (Cx43) gap junctions (GJs) in RV CMCs of patients with TF and the control group. In the myocardium of children with TF: Cx43-containing GJs were located both in the intercalated discs (<b>A</b>) and on the lateral sides, along the perimeter of the sarcolemma of the CMCs (<b>B</b>); a large number of binucleated CMCs. Immunohistochemical staining (×200), bar 10 µm. At the ultrastructural level, lateral GJs were found at the border of two CMCs in the form of concentric structures, following the bends of the CMCs sarcolemma (arrows) (<b>C</b>). In the control group: point Cx43-containing GJs were diffusely located along the perimeter of the sarcolemma (<b>D</b>). In the differentiated CMCs filled with myofibrils, the Cx43-containing GJs were localized predominantly in the intercalated discs (<b>E</b>). Immunohistochemical staining (×200), bar 10 µm. The relative length of lateral Cx43-containing GJs was significantly higher in the myocardium of patients with TF than in controls (Mann-Whitney test, <span class="html-italic">p</span> &lt; 0.05) (<b>F</b>). The relative length of Cx43-containing GJs on the lateral surfaces of the CMCs decreased with age (r = −0.45; <span class="html-italic">p</span> = 0.0003) (<b>G</b>). The lateral arrangement of Cx43-containing GJs was characteristic of immature CMCs with incomplete differentiation, not filled with myofibrils (<b>H</b>). Lateral Cx43-containing GJs were less frequently observed in TF patients with low blood oxygen saturation, which suggested their accelerated differentiation (r = 0.34; <span class="html-italic">p</span> = 0.016) (<b>I</b>). In children with TF under six months of age, the lateral arrangement of Cx43-containing GJs was inversely correlated with blood oxygen saturation (r = −0.76; <span class="html-italic">p</span> = 0.028) (<b>J</b>) and positively correlated with a history of dyspnea-cyanotic attacks (r = 0.58; <span class="html-italic">p</span> = 0.002) (<b>K</b>).</p>
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<p>Ultrastructure of immature RV CMCs of children with TF. CMCs of an immature phenotype with electron-transparent sarcoplasm, not filled with myofibrils, with many small mitochondria and vacuoles in the sarcoplasm. Myofibrils were located in a thin layer along the periphery of the sarcoplasm, bar 5 µm (<b>A</b>). In the CMCs of a more differentiated phenotype, myofibrils filled most of the sarcoplasm, in the perinuclear zone there were mitochondria, glycogen granules, single lipofuscin granules, bar 5 µm (<b>B</b>). Assembly of myofibrils in the sarcoplasm of the CMC, bar 1 µm. (<b>C</b>). T-system channels at the level of Z-bands of organizing myofibrils, bar 0,5 µm (<b>D</b>). Paired centrioles, cisterns, and vesicles of the Golgi apparatus in the perinuclear zone of the CMC, bar 0.5 µm (<b>E</b>). Myelin figures, vacuole in the perinuclear zone of the CMC, bar 1 µm. (<b>F</b>). In children with TF under six months of age: the assembly of myofibrils was more common in the CMCs of patients with a low gradient on the pulmonary artery (r = −0.52; <span class="html-italic">p</span> = 0.01) (<b>G</b>); signs of dystrophic changes in ultrastructure (myelin figures, phagosomes) were found in the CMCs of children with low hemoglobin levels (r = −0.54; <span class="html-italic">p</span> = 0.025) (<b>H</b>), in the myocardium with a large number of multinucleated CMCs (r = 0.77; <span class="html-italic">p</span> = 0.006) (<b>I</b>)<b>,</b> in differentiated CMCs with a small relative length of lateral Cx43-containing GJs (r = −0.47; <span class="html-italic">p</span> = 0.32) (<b>J</b>).</p>
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<p>Interstitial tissue of the RV myocardium of children with TF and the control group. An insignificant proportion of interstitial tissue in the perivascular zone of the myocardium in children with TF (<b>A</b>,<b>B</b>) and the control group (<b>C</b>,<b>D</b>). Masson trichrome (×200), bar 10 µm. The proportion of interstitial tissue in the myocardium of children with TF and the control group did not differ significantly (<b>E</b>) (median, Mann-Whitney test, <span class="html-italic">p</span> &gt; 0.05). CD34-positive capillaries and small vessels in the myocardial interstitium of a patient with TF. Immunohistochemical staining (×400), bar 20 µm (<b>F</b>). In children with TF over 6 months of age: the proportion of interstitial tissue correlated with age (r = 0.38; <span class="html-italic">p</span> = 0.03) (<b>G</b>) and increased with an increase in the number of differentiated CMCs, the sarcoplasm of which was filled with myofibrils (myofibril-free zones were 10%)(r = 0.64; <span class="html-italic">p</span> = 0.0001) (<b>H</b>). The density of CD34-positive small vessels and capillaries directly correlated with LVEF (r = 0.64; <span class="html-italic">p</span> = 0.003) (<b>I</b>).</p>
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<p>Proliferative-active Ki67<sup>+</sup>/Sarc α-actin<sup>+</sup> CMC in the RV myocardium of patients with TF. In multinucleated CMC, all nuclei were Ki67-positive (arrows) (<b>A</b>). Alexa 488—anti-rabbit antibody to Ki67 (<b>B</b>); Alexa 546—anti-mouse antibody to Sarcomeric α-Actin (<b>C</b>); DAPI nuclei staining (<b>D</b>). Immunoconfocal microscopy, bar 10 мкм. Patient with TF, five months. Ki67-positive CMCs were detected in the myocardium with a large proportion of interstitial tissue (r = 0.33; <span class="html-italic">p</span> = 0.27) (<b>E</b>); in the myocardium with a smaller diameter of the CMCs (r = −0.31; <span class="html-italic">p</span> = 0.02) (<b>F</b>); in the myocardium with a greater relative length of lateral Cx43-containing GJs in the CMCs (r = 0.29; <span class="html-italic">p</span> = 0.02) (<b>G</b>).</p>
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6 pages, 37108 KiB  
Commentary
Lymphoma versus Carcinoma and Other Collaborations
by Karen Pulford
Cells 2022, 11(1), 174; https://doi.org/10.3390/cells11010174 - 5 Jan 2022
Viewed by 1887
Abstract
David Mason started his research career at a time when lymphoma diagnosis was based primarily on cellular morphology, clinical symptoms and special cytochemical stains using formalin fixed tissue sections. There were occasions, however, where the morphology was unhelpful, such as in the case [...] Read more.
David Mason started his research career at a time when lymphoma diagnosis was based primarily on cellular morphology, clinical symptoms and special cytochemical stains using formalin fixed tissue sections. There were occasions, however, where the morphology was unhelpful, such as in the case of anaplastic or poorly differentiated tumours, where a distinction between lymphoma and a non-haematopoietic tumour was often problematical. Accurate diagnosis became even more important with the developments in the clinical staging of lymphoma and the availability of more effective treatments. One way forward to improve diagnosis was to use immunohistochemistry to study the antigens expressed by the tumor cells. Full article
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Figure 1
<p>Immunoperoxidase labelling of formalin sections of a Non-Hodgkin’s lymphoma lymphoma (NHL) (<b>a</b>–<b>c</b>) and a carcinoma (<b>d</b>–<b>f</b>) using the anti-CD45 antibody PD7/26. Haematoxylin and eosin labelling shows the presence of cells with a similar morphology in (<b>a</b>) the NHL and (<b>d</b>) carcinoma. The NHL cells in (<b>b</b>) are however strongly positive for CD45 (brown) but lack cytokeratin (<b>c</b>) confirming their haematopoietic origin. In contrast, the epithelial cells of the carcinoma are (<b>e</b>) CD45 negative but (<b>f</b>) express cytokeratin. Note the labelling of the scattered normal CD45-positive lymphoid cells (arrowed) within the carcinoma in (<b>e</b>).</p>
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22 pages, 4308 KiB  
Article
Dermatan Sulfate Affects Breast Cancer Cell Function via the Induction of Necroptosis
by Grzegorz Wisowski, Adam Pudełko, Krystyna Olczyk, Monika Paul-Samojedny and Ewa M. Koźma
Cells 2022, 11(1), 173; https://doi.org/10.3390/cells11010173 - 5 Jan 2022
Cited by 6 | Viewed by 2480
Abstract
Dermatan sulfate (DS) is widespread in the extracellular matrix (ECM) of animal tissues. This glycosaminoglycan is characterized by a variable structure, which is reflected in the heterogeneity of its sulfation pattern. The sulfate groups are responsible for the binding properties of DS, which [...] Read more.
Dermatan sulfate (DS) is widespread in the extracellular matrix (ECM) of animal tissues. This glycosaminoglycan is characterized by a variable structure, which is reflected in the heterogeneity of its sulfation pattern. The sulfate groups are responsible for the binding properties of DS, which determine an interaction profile of this glycan. However, the detailed role of DS in biological processes such as the neoplasm is still poorly understood. The aim of the study was to assess the effects of the structural variants of DS on breast cancer cells. We found that DS isoforms from normal and fibrotic fascia as well as from intestinal mucosa were able to quickly induce oxidative stress in the cytoplasm and affect the mitochondrial function in luminal breast cancer cells. Moreover, the variants caused the necroptosis of the cells most likely via the first of these mechanisms. This death was responsible for a reduction in the viability and number of breast cancer cells. However, the dynamics and intensity of all of the DS variants-triggered effects were strongly dependent on the cell type and the structure of these molecules. The most pronounced activity was demonstrated by those variants that shared structural features with the DS from the tumor niche. Full article
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Figure 1

Figure 1
<p>Characteristics of sulfation patterns and glucuronosyl epimerization levels in the tested variants of dermatan sulfate (DS). (<b>A</b>) Comparison of the disaccharide profiles that were obtained after the tested variants of DS were treated with chondroitinase ABC. The relative content of an individual disaccharide was calculated as a percentage contribution of the area under its peak into the total area of the chromatogram. Chromatographical analysis of sulfation pattern in DS from the porcine intestinal mucosa (PM) was conducted previously [<a href="#B17-cells-11-00173" class="html-bibr">17</a>]. The results are expressed as the mean of two independent experiments. (<b>B</b>) Comparison of the glucuronosyl epimerization levels that characterized the tested variants of DS. This parameter was calculated as the ratio between the total areas under the peaks of the unsaturated disaccharides that were released by chondroitinase AC I and by chondroitinase ABC. The results are expressed as the mean ± SD of two independent experiments. PS—DS from porcine skin, NF—DS from the normal human fascia, DF—DS from fibrosis affected fascia.</p>
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<p>The DS variants affect the viability (<b>A</b>), DNA biosynthesis (<b>B</b>), and cell counts (<b>C</b>) of luminal breast cancer cells (BT-483 and T-47D) in a manner that is dependent on their structure and cell type. (<b>A</b>) The breast cancer cells were exposed to the structural variants of DS that had been applied at the indicated concentrations for 24 h. Then, the cell viability was evaluated using the test based on measurements of the activity of the mitochondrial dehydrogenases. (<b>B</b>) The cancer cells were grown for 48 h in the presence of the tested variants of DS that had been used at the indicated concentrations. The cell proliferation was evaluated by measuring the incorporation to DNA of the bromodeoxyuridine that had been added to the cultures after the first 24 h of incubation. (<b>C</b>) The cancer cells were grown for 48 h in the exposure to the selected DS variants that had been applied at the indicated concentrations. Then, the cell number in the cultures was estimated using the crystal violet test. The results are expressed as the percentage of effect that was visible in the control cultures and are presented as the mean ±SD of at least three independent experiments in which <span class="html-italic">n</span> = 3 for each DS concentration. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control. CON—control (cultures untreated), PS—DS from porcine skin, NF—DS from normal human fascia, DF—DS from fibrosis affected fascia, PM—DS from porcine intestinal mucosa.</p>
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<p>The DS variants accomplish their effect on the viability and count of the luminal breast cancer cells via the rapid induction of programmed cell death. (<b>A</b>,<b>C</b>) The BT-483 (<b>A</b>) and T-47D (<b>C</b>) cells were grown for the indicated time periods with NF or PM and with DF or PM, respectively, that had been used at a concentration of 25 µg/mL. The cells that were undergoing death were indicated by Annexin V binding (AnV(+) cells) and/or staining with propidium iodide (PI(+) cells). The nuclei of all cells were stained with Hoechst dye. Both living and dying cells were counted in at least ten non-overlapping fields from each of two independent experiments. The results are expressed as the percentage of dying cells and are presented as the mean ± SEM that was calculated for all of the obtained images. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control. (<b>B</b>,<b>D</b>) The representative images illustrating the most pronounced effects on AnV and/or PI binding in the BT-483 (<b>B</b>) or T-47D (<b>D</b>) cells that were exposed for the indicated time periods to NF or DF, respectively. Arrowheads indicate large nuclei in the dying cells. The images were taken at a magnification of ×400.</p>
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<p>Apoptosis is not the predominant form of programmed cell death that is rapidly triggered by the tested DS variants in the luminal breast cancer cell cultures. (<b>A</b>,<b>C</b>) The quantification of caspase-3/7-positive cells in the BT-483 (<b>A</b>) and T-47D (<b>C</b>) cultures that were grown exposed to NF and PM or DF and PM, respectively, for the indicated time periods. The number of the cells exhibiting caspase-3/7 activity was estimated in at least ten non-overlapping fields from each of two independent experiments. The results are expressed as a percentage of the apoptotic cells and are presented as the mean ± SEM for all of the obtained images. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control. (<b>B</b>,<b>D</b>) The representative images that show the number of caspase-3/7-positive cells in the BT-483 (<b>B</b>) or T-47D (<b>D</b>) cultures grown in the exposure to NF or DF, respectively for the time periods in which the maximal AnV binding had been observed. Caspase-positive cells are indicated by green fluorescence. The images were taken at a magnification of ×200.</p>
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<p>Necroptosis is a major form of programmed cell death that is rapidly induced by NF but not by PM in the BT-483 cancer cells. (<b>A</b>) Only NF-mediated death is sensitive to the necroptotic inhibitor necrosulfonamide (NSA). NSA at a concentration of 6 µM had been applied 30 min before adding NF or PM that were used at a concentration of 25 µg/mL and were incubated with the cells for the indicated time periods. Dying cells were indicated using Annexin V binding and/or staining with propidium iodide. The data are expressed as a percentage of the cells exhibiting Annexin V and/or propidium iodide staining and are presented as the mean ± SEM that was calculated for all of the images that were obtained in two independent experiments. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control. (<b>B</b>) The dynamics of MLKL activation/oligomerization in BT-483 cultures that were exposed to NF or PM for the indicated time periods. The MLKL activation was estimated using the anti-phospho-MLKL antibody. The measurement of fluorescence was conducted for the bodies of all of the cells that were present in at least six non-overlapping fields from each of two independent experiments. The results are expressed as the mean red fluorescence value per µm<sup>2</sup> ± SEM. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control. (<b>C</b>) Representative images that show the most prominent effect of NF but not PM on the MLKL activation (magnification, ×400). (<b>D</b>) PM is unable to induce the activation of MLKL in the BT-483 cells. The representative western blot analysis of PM-mediated effect on the level of phospho-MLKL in BT-483 cells that were exposed to this variant for the indicated time periods. (<b>E</b>) Quantitative analysis of the obtained immunoblots illustrates the inability of PM to induce the MLKL activation in the BT-483 cells. The levels of phospho-MLKL were normalized to GAPDH content. The results are expressed as the mean ± SD of three independent experiments.</p>
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<p>Necroptosis is at least a major type of programmed cell death that is quickly triggered by DF or PM in the T-47D cells as results from (<b>A</b>) a significant inhibitory effect of NSA on the number of dying cells in the exposed cultures and from the ability of these variants to induce the activation of MLKL, which was detected by immunofluorescence (<b>B</b>,<b>C</b>) or immunoblotting (<b>D</b>,<b>E</b>) using the anti-phospho-MLKL (S358) antibody. All of the above experiments were performed as described in the legend in <a href="#cells-11-00173-f005" class="html-fig">Figure 5</a>. (<b>A</b>) The data are expressed as a percentage of the cells exhibiting Annexin V and/or propidium iodide staining and are presented as the mean ± SEM that was calculated for all of the images that were obtained in two independent experiments. (<b>B</b>) The results are expressed as the mean red fluorescence value per µm<sup>2</sup> ± SEM. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control. (<b>E</b>) The results are expressed as the mean ± SD of three independent experiments. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control.</p>
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<p>The variants of DS can induce rapid alterations in the mitochondrial transmembrane potential (∆Ψm) of the luminal breast cancer cells in a manner that is dependent on the structure of these molecules and cell type. (<b>A</b>,<b>C</b>) The dynamics of ∆Ψm in the BT-483 (<b>A</b>) and T-47D (<b>C</b>) cells that were cultured in the presence of NF and PM or DF and PM, respectively, for the indicated time periods. ∆Ψm was estimated as a ratio of red-to-green fluorescence, which is dependent on the mitochondrial membrane status-mediated polymerization of JC-1. The measurement of fluorescence was conducted for the bodies of all of the cells that were present in at least ten non-overlapping fields from each of two independent experiments. The results are expressed as the mean ±SEM. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control. (<b>B</b>,<b>D</b>) Representative images that show the most prominent effects of the tested DS variants on ∆Ψm in the cultures of BT-483 (<b>B</b>) and T-47D (<b>D</b>) cells. The images were taken at a magnification of ×400.</p>
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<p>The DS variants can induce oxidative stress in the cytoplasm of the luminal breast cancer cells. (<b>A</b>,<b>C</b>) The dynamics of oxidative status in the BT-483 (<b>A</b>) and T-47D (<b>C</b>) cultures that grew in the exposure to NF and PM or DF and PM, respectively, for the indicated time periods. Red fluorescence was calculated from the bodies of all of the cells that were present in at least ten non-overlapping fields from each of two independent experiments. The results are expressed as the mean red fluorescence value per µm<sup>2</sup> ± SEM. *—difference statistically significant (<span class="html-italic">p</span> ≤ 0.05) versus the control. (<b>B</b>,<b>D</b>) Representative images that show the most prominent effects of the tested DS variants on oxidative stress in the cytoplasm of BT-483 (<b>B</b>) and T-47D (<b>D</b>) cells. The images were taken at a magnification of ×200.</p>
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19 pages, 7538 KiB  
Review
Role and Involvement of TENM4 and miR-708 in Breast Cancer Development and Therapy
by Giulia Peppino, Federica Riccardo, Maddalena Arigoni, Elisabetta Bolli, Giuseppina Barutello, Federica Cavallo and Elena Quaglino
Cells 2022, 11(1), 172; https://doi.org/10.3390/cells11010172 - 5 Jan 2022
Cited by 5 | Viewed by 3652
Abstract
Teneurin 4 (TENM4) is a transmembrane protein that is codified by the ODZ4 gene and is involved in nervous system development, neurite outgrowth, and neuronal differentiation. In line with its involvement in the nervous system, TENM4 has also been implicated in several mental [...] Read more.
Teneurin 4 (TENM4) is a transmembrane protein that is codified by the ODZ4 gene and is involved in nervous system development, neurite outgrowth, and neuronal differentiation. In line with its involvement in the nervous system, TENM4 has also been implicated in several mental disorders such as bipolar disorder, schizophrenia, and autism. TENM4 mutations and rearrangements have recently been identified in a number of tumors. This, combined with impaired expression in tumors, suggests that it may potentially be involved in tumorigenesis. Most of the TENM4 mutations that are observed in tumors occur in breast cancer, in which TENM4 plays a role in cells’ migration and stemness. However, the functional role that TENM4 plays in breast cancer still needs to be better evaluated, and further studies are required to better understand the involvement of TENM4 in breast cancer progression. Herein, we review the currently available data for TENM4′s role in breast cancer and propose its use as both a novel target with which to ameliorate patient prognosis and as a potential biomarker. Moreover, we also report data on the tumorigenic role of miR-708 deregulation and the possible use of this miRNA as a novel therapeutic molecule, as miR-708 is spliced out from TENM4 mRNA. Full article
(This article belongs to the Special Issue Emerging Targets and Therapeutic Strategies in Cancer)
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<p>Schematic representation of the <span class="html-italic">ODZ4</span> gene and of the TENM4 protein structure: (<b>A</b>) The <span class="html-italic">ODZ4</span> gene counts 34 exons (NCBI Gene ID: 26011, updated on 23 November 2021). Two microRNA miR-5579 and miR-708 are situated in the first intron of the <span class="html-italic">ODZ4</span> gene and spliced out. (<b>B</b>) TENM4 protein structure comprehend different domains: an intracellular domain with a nuclear localization sequence and an SH3 binding domain, a transmembrane domain, and an extracellular domain composed by eight EGF repeats, an NHL, and YD domains. “Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a>, accessed on 26 November 2021”.</p>
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<p>Analysis of <span class="html-italic">ODZ4</span> genomic alterations in breast cancer patients: (<b>A</b>) <span class="html-italic">ODZ4</span> alteration frequency observed by analyzing two breast cancer data sets: TCGA (Dataset A) and Metabric (Dataset B). The analyses were performed using the cBioPortal tool (<a href="http://www.cbioportal.org" target="_blank">www.cbioportal.org</a>, accessed on 30 November 2021), an open-access, open-source resource for interactive exploration of multidimensional cancer genomics data sets. (<b>B</b>) Overall survival (upper panel) and relapse free status (lower panel) of breast cancer patients that displayed unaltered <span class="html-italic">ODZ4</span> (blue line) and genomic <span class="html-italic">ODZ4</span> alterations (red line). Statistical analysis was performed using the Log Rank Test.</p>
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<p><span class="html-italic">TENM4</span> mRNA expression relevance in breast cancer patients. Correlation between Relapse Free Survival (RFS) and Overall Survival (OS) in Triple Negative Breast Cancer (TNBC) (<b>A</b>,<b>E</b>), HER2-positive (<b>B</b>,<b>F</b>), Progesterone Receptor (PR)-positive (<b>C</b>,<b>G</b>), Estrogen Receptor (ER)-positive (<b>D</b>,<b>H</b>), and Grade 3 (<b>I</b>,<b>J</b>) with high (red) or low (black) <span class="html-italic">TENM4</span> mRNA expression in the tumor.</p>
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<p>Mir-708 relevance in TNBC patients. Correlation between Overall Survival (OS) in TNBC and high (red) or low (black) miR-708 expression in the tumor.</p>
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<p>TENM4 expression in HER2-positive breast cancer cells and tumors: (<b>A</b>) Immunoblot of TENM4 and loading control protein (Actin) that compares HER2-positive TUBO epithelial cells (ep), first-passage tumorspheres (P1) and second-passage tumorspheres (P2). (<b>B</b>) Immunoblot of TENM4 and loading control protein (Vinculin) that compares HER2-positive mammary tumors from 9- (NeuT9wA and B), 14- (NeuT14wA and B), and 24- (NeuT24wA and B) week-old BALB-neuT mice. A total of 80 µg of TUBO cells and BALB-neuT tumor lysates were separated via electrophoresis in a 7.5% Mini-Protean TGX precast gel (Bio-Rad) and transferred onto an Immobilon-P PVDF membrane. Following blocking with 5% non-fat dry milk, the membrane was incubated with sheep anti-TENM4 (1 µg/mL, Cat#AF6320, R&amp;D Systems, Minneapolis, MN, USA), with mouse anti-β-Actin (1:200, Clone AC-15, Santa Cruz Biotechnology), and with mouse anti-Vinculin (1:8000, produced in-house).</p>
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14 pages, 1515 KiB  
Review
Lithium and Erectile Dysfunction: An Overview
by Mohammad Sheibani, Mehdi Ghasemi and Ahmad Reza Dehpour
Cells 2022, 11(1), 171; https://doi.org/10.3390/cells11010171 - 5 Jan 2022
Cited by 13 | Viewed by 9171
Abstract
Lithium has been a mainstay of therapy for patients with bipolar disorders for several decades. However, it may exert a variety of adverse effects that can affect patients’ compliance. Sexual and erectile dysfunction has been reported in several studies by patients who take [...] Read more.
Lithium has been a mainstay of therapy for patients with bipolar disorders for several decades. However, it may exert a variety of adverse effects that can affect patients’ compliance. Sexual and erectile dysfunction has been reported in several studies by patients who take lithium as monotherapy or combined with other psychotherapeutic agents. The exact mechanisms underlying such side effects of lithium are not completely understood. It seems that both central and peripheral mechanisms are involved in the lithium-related sexual dysfunction. Here, we had an overview of the epidemiology of lithium-related sexual and erectile dysfunction in previous clinical studies as well as possible pathologic pathways that could be involved in this adverse effect of lithium based on the previous preclinical studies. Understanding such mechanisms could potentially open a new avenue for therapies that can overcome lithium-related sexual dysfunction and improve patients’ adherence to the medication intake. Full article
(This article belongs to the Collection Feature Papers in 'Cells of the Nervous System' Section)
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<p>Schematic representation of central and peripheral neural pathways controlling the penile erection. Several brain regions including forebrain, midbrain, hypothalamus, and brainstem are involved in sexual drive, arousal, and ultimately erectile function. Sexual stimuli activate brain regions through which they stimulate the hypothalamus and its nuclei (mainly medial preoptic area [MPOA] and paraventricular nucleus [PVN]). The neural pathway then traverses through the medulla oblongata and the spinal cord to the genital apparatus, i.e., penile tissue in males. Two major nerves innervating the penis include (i) the Pudental nerve, which arises from sacral S2–S4 roots and contains the primary afferent sensory and efferent motor pathway to the penis, and (ii) the Cavernosal nerves, which contain the primary efferent sympathetic and parasympathetic pathways originating from the pelvic plexuses. Three nerve groups also innervate pelvic plexuses: (i) the hypogastric nerve (from T12–L3 nerve roots), (ii) pelvic nerves (from sacral nerve roots), and (iii) the post-ganglionic fibers from the paravertebral sympathetic thoracolumbar (T12–L3 levels) ganglia chain.</p>
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<p>Schematic representation of possible mechanisms underlying the effects of lithium on neurogenic and endothelium-mediated relaxation of cavernosal smooth muscle, and thereby erectile function. In endothelial cells, acetylcholine binds to the G-protein-coupled receptor that can activate phospholipase C (PLC) and thereby increasing the production of inositol 1,4,5-trisphosphate (IP<sub>3</sub>) [<a href="#B92-cells-11-00171" class="html-bibr">92</a>]. IP<sub>3</sub> releases Ca<sup>2+</sup> from the endoplasmic reticulum or increases Ca<sup>2+</sup> influx via calcium channels. Ca<sup>2+</sup> then binds to calmodulin and activates endothelial nitric oxide (NO) synthase (eNOS) that eventually leads to production of NO from L-arginine. Lithium (Li<sup>+</sup>) can negatively affect this process through several mechanisms. It can inhibit the IP<sub>3</sub> production cycle via inhibition of inositol monophastase (IMPase) or inositol phosphatase (IPP) [<a href="#B93-cells-11-00171" class="html-bibr">93</a>]. There is also evidence that lithium prevents IP<sub>3</sub>-sensitive Ca<sup>2+</sup>-release from the endoplasmic reticulum [<a href="#B96-cells-11-00171" class="html-bibr">96</a>,<a href="#B97-cells-11-00171" class="html-bibr">97</a>]. Different prostaglandins produced from arachidonic acid (AA) via cyclooxygenase (COX) activity also contribute to both cavernosal smooth muscle contraction and relaxation. Prostaglandins E<sub>1</sub> (PGE<sub>1</sub>) and PGE<sub>2</sub> activate adenylyl cyclase (AC) and increase the production of cyclic adenosine monophosphate (cAMP), which ultimately leads to muscle relaxation. However, prostaglandin F<sub>2α</sub> (PGF<sub>2α</sub>) causes muscle contraction via activation of PLC. Lithium is reported to decrease COX-2 expression and PGE<sub>2</sub> level in rat brain [<a href="#B101-cells-11-00171" class="html-bibr">101</a>,<a href="#B102-cells-11-00171" class="html-bibr">102</a>]. Neurogenic relaxation of the cavernosal smooth muscle is also mediated by neuronal NO, generated by the neuronal NOS (nNOS) activity in the cavernosal nerves [<a href="#B35-cells-11-00171" class="html-bibr">35</a>]. Lithium can also decrease eNOS and nNOS activities as evidenced by decreased eNOS expression in vascular tissues as well as NO metabolites in brain tissues [<a href="#B51-cells-11-00171" class="html-bibr">51</a>,<a href="#B52-cells-11-00171" class="html-bibr">52</a>,<a href="#B98-cells-11-00171" class="html-bibr">98</a>]. ATP, adenosine triphosphate; CaM, calmodulin; cGMP, cyclic guanosine monophosphate; GC, guanylyl cyclase; GTP, guanosine triphosphate; PK, protein kinase; PKG, protein kinase G; PIP<sub>2</sub>, phosphoinositide 4,5-biphosphate; VDCC, voltage-dependent calcium channel.</p>
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11 pages, 1520 KiB  
Review
Muscle and Bone Impairment in Infantile Nephropathic Cystinosis: New Concepts
by Dieter Haffner, Maren Leifheit-Nestler, Candide Alioli and Justine Bacchetta
Cells 2022, 11(1), 170; https://doi.org/10.3390/cells11010170 - 5 Jan 2022
Cited by 7 | Viewed by 3475
Abstract
Cystinosis Metabolic Bone Disease (CMBD) has emerged during the last decade as a well-recognized, long-term complication in patients suffering from infantile nephropathic cystinosis (INC), resulting in significant morbidity and impaired quality of life in teenagers and adults with INC. Its underlying pathophysiology is [...] Read more.
Cystinosis Metabolic Bone Disease (CMBD) has emerged during the last decade as a well-recognized, long-term complication in patients suffering from infantile nephropathic cystinosis (INC), resulting in significant morbidity and impaired quality of life in teenagers and adults with INC. Its underlying pathophysiology is complex and multifactorial, associating complementary, albeit distinct entities, in addition to ordinary mineral and bone disorders observed in other types of chronic kidney disease. Amongst these long-term consequences are renal Fanconi syndrome, hypophosphatemic rickets, malnutrition, hormonal abnormalities, muscular impairment, and intrinsic cellular bone defects in bone cells, due to CTNS mutations. Recent research data in the field have demonstrated abnormal mineral regulation, intrinsic bone defects, cysteamine toxicity, muscle wasting and, likely interleukin-1-driven inflammation in the setting of CMBD. Here we summarize these new pathophysiological deregulations and discuss the crucial interplay between bone and muscle in INC. In future, vitamin D and/or biotherapies targeting the IL1β pathway may improve muscle wasting and subsequently CMBD, but this remains to be proven. Full article
(This article belongs to the Special Issue Cellular and Molecular Mechanisms of Nephropathic Cystinosis)
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<p>Clinical presentation and causes of CMBD. Figure from Hohenfellner et al., with permission [<a href="#B18-cells-11-00170" class="html-bibr">18</a>].</p>
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<p>Serum levels of phosphate (<b>A</b>), calcium (<b>B</b>), intact parathyroid hormone (iPTH, (<b>C</b>)), and 1,25(OH)<sub>2</sub>D<sub>3</sub> (<b>D</b>) in children with infantile nephropathic cystinosis (INC) and CKD controls as estimated glomerular filtration rate (eGFR) and after kidney transplantation (KTX). Gray box plots indicate INC patients; white box plots indicate CKD controls. Horizontal continuous and broken lines in (<b>A</b>) indicate the mean and upper and lower normal range; horizontal broken lines in (<b>B</b>,<b>C</b>) indicate the upper and lower normal range; horizontal broken lines in (<b>D</b>) indicate the PTH target range recommended by KDOQI; a, b, and c indicate <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 0.01 and <span class="html-italic">p</span> &lt; 0.001 versus healthy children, respectively. SDS, standard deviation score. Figure from Ewert et al., with permission [<a href="#B13-cells-11-00170" class="html-bibr">13</a>].</p>
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<p>Circulating levels of intact (<b>A</b>) and total (<b>B</b>) fibroblast growth factor 23, soluble Klotho (<b>C</b>), bone alkaline phosphatase (<b>D</b>), tartrate-resistant acid phosphatase 5b (<b>E</b>), osteoprotegerin (<b>F</b>) and sclerostin (<b>G</b>) in children with infantile nephropathic cystinosis (INC), and CKD controls at various stages of CKD and after kidney transplantation (KTX): Gray box plots indicate INC patients while white box plots indicate CKD controls. Horizontal continuous and broken lines indicate the mean, upper, and lower normal range; a, b, and c indicate <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">p</span> &lt; 0.01, and <span class="html-italic">p</span> &lt; 0.001 versus healthy children, respectively. eGFR, estimated glomerular filtration rate (eGFR); SDS, standard deviation score; iFGF23, intact fibroblast growth factor 23; BAP, bone alkaline phosphatase; TRAP5b, tartrate-resistant acid phosphatase 5b; OPG, osteoprotegerin; sKlotho, soluble Klotho. Figure from Ewert et al. with permission [<a href="#B13-cells-11-00170" class="html-bibr">13</a>].</p>
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21 pages, 1463 KiB  
Review
LRRK2 at Striatal Synapses: Cell-Type Specificity and Mechanistic Insights
by Patrick D. Skelton, Valerie Tokars and Loukia Parisiadou
Cells 2022, 11(1), 169; https://doi.org/10.3390/cells11010169 - 5 Jan 2022
Cited by 11 | Viewed by 4009
Abstract
Mutations in leucine-rich repeat kinase 2 (LRRK2) cause Parkinson’s disease with a similar clinical presentation and progression to idiopathic Parkinson’s disease, and common variation is linked to disease risk. Recapitulation of the genotype in rodent models causes abnormal dopamine release and increases the [...] Read more.
Mutations in leucine-rich repeat kinase 2 (LRRK2) cause Parkinson’s disease with a similar clinical presentation and progression to idiopathic Parkinson’s disease, and common variation is linked to disease risk. Recapitulation of the genotype in rodent models causes abnormal dopamine release and increases the susceptibility of dopaminergic neurons to insults, making LRRK2 a valuable model for understanding the pathobiology of Parkinson’s disease. It is also a promising druggable target with targeted therapies currently in development. LRRK2 mRNA and protein expression in the brain is highly variable across regions and cellular identities. A growing body of work has demonstrated that pathogenic LRRK2 mutations disrupt striatal synapses before the onset of overt neurodegeneration. Several substrates and interactors of LRRK2 have been identified to potentially mediate these pre-neurodegenerative changes in a cell-type-specific manner. This review discusses the effects of pathogenic LRRK2 mutations in striatal neurons, including cell-type-specific and pathway-specific alterations. It also highlights several LRRK2 effectors that could mediate the alterations to striatal function, including Rabs and protein kinase A. The lessons learned from improving our understanding of the pathogenic effects of LRRK2 mutations in striatal neurons will be applicable to both dissecting the cell-type specificity of LRRK2 function in the transcriptionally diverse subtypes of dopaminergic neurons and also increasing our understanding of basal ganglia development and biology. Finally, it will inform the development of therapeutics for Parkinson’s disease. Full article
(This article belongs to the Collection Feature Papers in 'Cells of the Nervous System' Section)
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<p>Single-cell LRRK2 mRNA levels. Single-cell LRRK2 mRNA expression data from dropviz.org for selected types of striatal neurons and dopaminergic midbrain projection neurons. (<b>A</b>) Top: LRRK2 mRNA expression in global clusters defining striatal neuron types. LRRK2 mRNA is more abundant in SPNs than in striatal interneurons. Bottom: Subclusters selected on the basis of their putative identity with well-characterized subpopulations of striatal neurons (i.e., excluding eSPNs and clusters which had been identified as non-striatal neurons). Cell cluster identities are as described by Saunders et al., except Neurogliaform interneurons, which was assigned based on the expression of NPY but not parvalbumin, somatostatin, or Nos1, as defined by Tepper et al. [<a href="#B62-cells-11-00169" class="html-bibr">62</a>]. Some subclusters of fast-spiking interneurons and SPNs do not correspond to a well-characterized cell type and are referred to by the subcluster name. Consistent with immunohistochemical evidence by Mandemakers et al. [<a href="#B57-cells-11-00169" class="html-bibr">57</a>], LRRK2 mRNA is elevated in lateral and striosomal dSPNs. These data can be accessed in the context of the full dataset at [<a href="http://dropviz.org/?stateid=8afe26552f34f746" target="_blank">http://dropviz.org/?stateid=8afe26552f34f746</a>] (accessed on 20 October 2021). (<b>B</b>) Top: LRRK2 mRNA expression in global clusters defining neuron types in the substantia nigra. Bottom: LRRK2 mRNA levels in the subclusters constituting the “Th” (Tyrosine hydroxylase-expressing) global cluster, i.e., dopaminergic neurons of the SNc and VTA. Cell types are as defined by Saunders et al. LRRK2 mRNA expression is low, but detectable, across dopaminergic subtypes. These data can be accessed in the context of the full dataset at [<a href="http://dropviz.org/?stateid=8c997a178c82063c" target="_blank">http://dropviz.org/?stateid=8c997a178c82063c</a>] (accessed on 20 October 2021). Abbreviations: PV: parvalbumin; TH: tyrosine hydroxylase; Pnoc: prepronociceptin; SST: somatostatin; CIN: cholinergic interneuron; eSPN: eccentric SPN [<a href="#B56-cells-11-00169" class="html-bibr">56</a>]; LTS: low-threshold spiking; FS: fast-spiking; IEG: immediate early gene; Rora: RAR-related orphan receptor A; Gad2: glutamic acid decarboxylase 2.</p>
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<p>Pathway-specific effect of LRRK2 on synaptic AMPARs. The R1441C mutation induces an enhanced phosphorylation of GluR1 by PKA, leading to the increased insertion and retention of AMPA receptors into the synaptic membrane of dSPNs, but not iSPNs [<a href="#B78-cells-11-00169" class="html-bibr">78</a>]. This figure was created using biorender.com.</p>
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<p>Candidate AKAP-like helix in the LRRK2 ROC domain. The sequence of the ROC domain is presented with alpha helices identified from sequence analysis highlighted in green. A candidate amphipathic helix was identified within the ROC domain of LRRK2 and is highlighted by the black lines leading to the inset image of the helical wheel. This helix contains the clinically relevant residue R1441 (circled in red). In the legend the “+” indicates resides belonging to a hydrophobic face when a 3–11 helix is generated. The “*” indicates residues belonging to the hydrophobic face when an alpha helix is modeled. The “#” identifies residues that belong to the hydrophobic face when either a 3–11 or alpha helix is generated.</p>
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<p>Effectors of LRRK2 postsynaptic function. Depiction of mechanisms by which LRRK2 affects synaptic function and downstream LRRK2 effectors that affect synapse function. (1) An interaction between the PKA PKARIIβ subunit and LRRK2 ROC domain acts as an AKAP, anchoring LRRK2 in dendritic shafts. The R1441C mutation impairs this interaction, resulting in increased translocation of PKA into dendritic spines. (2) Mutation- and cell-type-specific alteration of AMPAR trafficking in dendritic spines. The R1441C mutation increases GluR1 phosphorylation and AMPAR insertion into the membrane specifically in direct-pathway SPNs, increasing synapse strength. (3) The LRRK2 substrate Rab8 is essential for trafficking newly translated AMPARs to the synapse. (4) LRRK2 kinase activity modulates the translation (by affecting the efficiency with which ribosomes translate mRNAs with complex 5′ UTRs), and the function of voltage-gated calcium channels (VGCCs), resulting in increased calcium influx. (5) LRRK2 phosphorylates the ribosomal S15 subunit, promoting the increased translation of mRNAs. This figure was created using biorender.com.</p>
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15 pages, 2491 KiB  
Article
In Vitro Anticancer Screening and Preliminary Mechanistic Study of A-Ring Substituted Anthraquinone Derivatives
by Ibrahim Morgan, Ludger A. Wessjohann and Goran N. Kaluđerović
Cells 2022, 11(1), 168; https://doi.org/10.3390/cells11010168 - 5 Jan 2022
Cited by 15 | Viewed by 3407
Abstract
Anthraquinone derivatives exhibit various biological activities, e.g., antifungal, antibacterial and in vitro antiviral activities. They are naturally produced in many fungal and plant families such as Rhamnaceae or Fabaceae. Furthermore, they were found to have anticancer activity, exemplified by mitoxantrone and pixantrone, and [...] Read more.
Anthraquinone derivatives exhibit various biological activities, e.g., antifungal, antibacterial and in vitro antiviral activities. They are naturally produced in many fungal and plant families such as Rhamnaceae or Fabaceae. Furthermore, they were found to have anticancer activity, exemplified by mitoxantrone and pixantrone, and many are well known redox-active compounds. In this study, various nature inspired synthetic anthraquinone derivatives were tested against colon, prostate, liver and cervical cancer cell lines. Most of the compounds exhibit anticancer effects against all cell lines, therefore the compounds were further studied to determine their IC50-values. Of these compounds, 1,4-bis(benzyloxy)-2,3-bis(hydroxymethyl)anthracene-9,10-dione (4) exhibited the highest cytotoxicity against PC3 cells and was chosen for a deeper look into its mechanism of action. Based on flow cytometry, the compound was proven to induce apoptosis through the activation of caspases and to demolish the ROS/RNS and NO equilibrium in the PC3 cell line. It trapped cells in the G2/M phase. Western blotting was performed for several proteins related to the effects observed. Compound 4 enhanced the production of PARP and caspase-3. Moreover, it activated the conversion of LC3A/B-I to LC3A/B-II showing that also autophagy plays a role in its mechanism of action, and it caused the phosphorylation of p70 s6 kinase. Full article
(This article belongs to the Special Issue Crosstalk of Autophagy and Apoptosis)
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Figure 1

Figure 1
<p>(<b>a</b>) Anthraquinone core, (<b>b</b>) mitoxantrone and (<b>c</b>) pixantrone.</p>
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<p>(<b>a</b>) Emodin and (<b>b</b>) aloe-emodin.</p>
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<p>Structural variations of the 1-hydroxyl-anthraquinone core structure and IC<sub>50</sub> values against prostate cancer cells (PC3 in CV assay).</p>
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<p>Representative histograms and dot plots for the impact of compound <b>4</b> using IC<sub>50</sub> and 2 × IC<sub>50</sub> for 48 h against PC3 cell line on (<b>a</b>) the cell distribution in G0/G1, S and G2/M phases using DAPI stain; (<b>b</b>) the inhibition of PC3 cells proliferation, in which cells were stained using CFSE reagent, later treated with the lead compound; (<b>c</b>) the induction of ROS/RNS production, determined with DHR assay; (<b>d</b>) NO production, using DAF-FM dye; (<b>e</b>) the induction of Caspases production, using Apostat staining kit; (<b>f</b>) the induction of apoptosis, using AnnV/PI double staining; (<b>g</b>) induction of autophagy, with acridine orange assay. For CFSE, DHR, DAF-FM, AnnV, and Apostat stains the fluorescence was analyzed using excitation 488 ± 20 nm and emission of 530 ± 30 nm (showed on the <span class="html-italic">x</span>-axis). For DAPI channel, the fluorescence was analyzed using excitation of 375 ± 20 nm and emission of 450 ± 20 nm (presented on <span class="html-italic">x</span>-axis). For AO and PI dyes, the fluorescence was analyzed using excitation and emission of 488 ± 20/695 ± 40 or 561 ± 20/610 ± 20 nm, respectively, (presented on the <span class="html-italic">y</span>-axis).</p>
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<p>Bar graphs representing the impact of compound <b>4</b> using IC<sub>50</sub> and 2 × IC<sub>50</sub> for 48 h against PC3 cell line on (<b>a</b>) the cell distribution in G0/G1, S and G2/M phases; (<b>b</b>) the inhibition of PC3 cells proliferation; (<b>c</b>) the induction of ROS/RNS production; (<b>d</b>) NO production; (<b>e</b>) the induction of caspases production; (<b>f</b>) the induction of apoptosis; (<b>g</b>) induction of autophagy. Data is normalized to the corresponding value in the untreated sample. Bars represent the mean values ± standard deviation calculated from three independent measurements. * <span class="html-italic">p</span> &lt; 0.05 compared to the untreated control cells.</p>
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<p>Bar graphs representing the impact of compound <b>4</b> using IC<sub>50</sub> and 2 × IC<sub>50</sub> for 48 h against PC3 cell line on (<b>a</b>) the cell distribution in G0/G1, S and G2/M phases; (<b>b</b>) the inhibition of PC3 cells proliferation; (<b>c</b>) the induction of ROS/RNS production; (<b>d</b>) NO production; (<b>e</b>) the induction of caspases production; (<b>f</b>) the induction of apoptosis; (<b>g</b>) induction of autophagy. Data is normalized to the corresponding value in the untreated sample. Bars represent the mean values ± standard deviation calculated from three independent measurements. * <span class="html-italic">p</span> &lt; 0.05 compared to the untreated control cells.</p>
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<p>Effect of compound <b>4</b> on the expression of (<b>a</b>) p38 MAPK, p-p38 MAPK, (<b>b</b>) p70 S6 kinase, p-p70 S6 kinase, (<b>c</b>) caspase-3, PARP and (<b>d</b>) LC3 A/B-1, LC3 A/B-2 in PC3 cells. Each protein expression was normalized based on the expression of α/β-tubulin. Mean value and the standard deviation of the normalized value of three independent biological replicates is represented. * <span class="html-italic">p</span> &lt; 0.05 compared to the zero-time point.</p>
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<p>(<b>a</b>) Viability of PC3 cells treated with 3-MA and/or IC<sub>50</sub> dose of compound <b>4</b> (CV assay, 48 h), * <span class="html-italic">p</span> &lt; 0.05 compared to the 3-MA treated cells, no statistical significance between 3-MA + <b>4</b> and <b>4</b> treated cells; (<b>b</b>) the effect of compound <b>4</b> on the topoisomerase I activity in PC3 cells.</p>
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21 pages, 4891 KiB  
Article
Carnosic Acid Attenuates the Free Fatty Acid-Induced Insulin Resistance in Muscle Cells and Adipocytes
by Danja J. Den Hartogh, Filip Vlavcheski, Adria Giacca, Rebecca E. K. MacPherson and Evangelia Tsiani
Cells 2022, 11(1), 167; https://doi.org/10.3390/cells11010167 - 5 Jan 2022
Cited by 18 | Viewed by 3702
Abstract
Elevated blood free fatty acids (FFAs), as seen in obesity, impair insulin action leading to insulin resistance and Type 2 diabetes mellitus. Several serine/threonine kinases including JNK, mTOR, and p70 S6K cause serine phosphorylation of the insulin receptor substrate (IRS) and have been [...] Read more.
Elevated blood free fatty acids (FFAs), as seen in obesity, impair insulin action leading to insulin resistance and Type 2 diabetes mellitus. Several serine/threonine kinases including JNK, mTOR, and p70 S6K cause serine phosphorylation of the insulin receptor substrate (IRS) and have been implicated in insulin resistance. Activation of AMP-activated protein kinase (AMPK) increases glucose uptake, and in recent years, AMPK has been viewed as an important target to counteract insulin resistance. We reported previously that carnosic acid (CA) found in rosemary extract (RE) and RE increased glucose uptake and activated AMPK in muscle cells. In the present study, we examined the effects of CA on palmitate-induced insulin-resistant L6 myotubes and 3T3L1 adipocytes. Exposure of cells to palmitate reduced the insulin-stimulated glucose uptake, GLUT4 transporter levels on the plasma membrane, and Akt activation. Importantly, CA attenuated the deleterious effect of palmitate and restored the insulin-stimulated glucose uptake, the activation of Akt, and GLUT4 levels. Additionally, CA markedly attenuated the palmitate-induced phosphorylation/activation of JNK, mTOR, and p70S6K and activated AMPK. Our data indicate that CA has the potential to counteract the palmitate-induced muscle and fat cell insulin resistance. Full article
(This article belongs to the Special Issue Free Fatty Acids and Pathogenesis of Diabetes Mellitus)
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Figure 1

Figure 1
<p>Carnosic acid restores the insulin-stimulated glucose uptake in palmitate treated skeletal muscle (<b>A</b>) and fat cells (<b>B</b>). Fully differentiated L6 myotubes (<b>A</b>) and 3T3-L1 adipocytes (<b>B</b>) were treated with 0.2 mM palmitate (P) for 16 h in the absence or the presence of 2 µM carnosic acid (CA) followed by stimulation without or with 100 nM insulin (I) for 30 min and [3H]-2-deoxy-D-glucose uptake measurements. The results are the mean ± standard error (SE) of four to six independent experiments, expressed as percent of control (* <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 vs. control, ### <span class="html-italic">p</span> &lt; 0.001, ## <span class="html-italic">p</span> &lt; 0.01, # <span class="html-italic">p</span> &lt; 0.05 as indicated).</p>
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<p>Carnosic acid restores the insulin-stimulated glucose uptake in palmitate treated skeletal muscle (<b>A</b>) and fat cells (<b>B</b>). Fully differentiated L6 myotubes (<b>A</b>) and 3T3-L1 adipocytes (<b>B</b>) were treated with 0.2 mM palmitate (P) for 16 h in the absence or the presence of 2 µM carnosic acid (CA) followed by stimulation without or with 100 nM insulin (I) for 30 min and [3H]-2-deoxy-D-glucose uptake measurements. The results are the mean ± standard error (SE) of four to six independent experiments, expressed as percent of control (* <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 vs. control, ### <span class="html-italic">p</span> &lt; 0.001, ## <span class="html-italic">p</span> &lt; 0.01, # <span class="html-italic">p</span> &lt; 0.05 as indicated).</p>
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<p>Effects of palmitate and carnosic acid on GLUT4 translocation in skeletal muscle cells. GLUT4myc overexpressing L6 myotubes were treated without (control, C) or with 0.2 mM palmitate (P) for 16 h in the absence or the presence of 2 μM carnosic acid (CA) followed by washing, as indicated in the methods, and acute stimulation with 100 nM insulin for 30 min (I). After treatment, plasma membrane GLUT4 glucose transporter levels were measured. Results are the mean ± SE of three independent experiments performed in triplicate (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control, # <span class="html-italic">p</span> &lt; 0.05 as indicated).</p>
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<p>Effects of palmitate and carnosic acid on skeletal muscle cell Akt expression and phosphorylation/activation. Fully differentiated L6 myotubes were treated without (control, C) or with 0.2 mM palmitate (P) for 16 h in the absence or the presence of 2 μM carnosic acid (CA) followed by stimulation without or with 100 nM insulin (I) for 30 min. After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated (Ser<sup>473</sup>), total Akt, or β-actin. Representative immunoblots are shown (<b>A</b>). The densitometry of the bands was measured and expressed in arbitrary units (<b>B</b>). The data are the mean ± SE of three to five separate experiments (*** <span class="html-italic">p</span> &lt; 0.001 vs. control, ## <span class="html-italic">p</span> &lt; 0.01 as indicated).</p>
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<p>Effects of palmitate and carnosic acid on serine phosphorylation and expression of skeletal muscle cell IRS-l. Fully differentiated myotubes were treated without (control, C) or with 0.2 mM palmitate (P) for 16 h in the absence or presence of 2 µM carnosic acid (CA). After treatment, the cells were lysed, and IRS-1 immunoprecipitation was performed, followed by SDS-PAGE and immunoblotting with specific antibodies that recognize phosphorylated Ser<sup>307</sup>, Ser<sup>636/639</sup>, or total IRS-1. Representative immunoblots are shown (<b>A</b>). The densitometry of the bands was measured and expressed in arbitrary units (<b>B</b>). The data is the mean ± SE of three separate experiments. (** <span class="html-italic">p</span> &lt; 0.01 vs. control, # <span class="html-italic">p &lt; 0.05,</span> ## <span class="html-italic">p</span> &lt; 0.01 vs. palmitate alone).</p>
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<p>Effects of palmitate and carnosic acid on JNK expression and phosphorylation in skeletal-muscle cells. Fully differentiated L6 myotubes were treated without (control, C) or with 0.2 mM palmitate (P) for 16 h in the absence or the presence of 2 μM carnosic acid (CA). After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated Thr<sup>183</sup>/Tyr<sup>185</sup> or total JNK. Representative immunoblots are shown (<b>A</b>). The densitometry of the bands was measured and expressed in arbitrary units (<b>B</b>). The data are the mean ± SE of three separate experiments (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001 vs. control, ### <span class="html-italic">p</span> &lt; 0.001 vs. palmitate alone).</p>
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<p>Effects of palmitate and carnosic acid on mTOR, p70S6K and Raptor expression and phosphorylation in skeletal muscle cells. Fully differentiated myotubes were treated without (control, C) or with 0.2 mM palmitate (P) for 16 h in the absence or the presence of 2 μM carnosic acid (CA). After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated Ser<sup>2448</sup> or total mTOR, phosphorylated Thr<sup>389</sup> or total p70S6K (<b>A</b>,<b>B</b>), and phosphorylated Ser<sup>792</sup> or total Raptor (<b>C</b>). Representative immunoblots are shown (<b>A</b>,<b>C</b>). The densitometry of the bands was measured and expressed in arbitrary units (<b>B</b>). The data are the mean ± SE of four separate experiments (** <span class="html-italic">p &lt; 0.01,</span> *** <span class="html-italic">p</span> &lt; 0.001 vs. control, # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01 vs. palmitate alone).</p>
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<p>Effects of palmitate and carnosic acid on AMPK and ACC expression and phosphorylation in skeletal muscle cells. Fully differentiated myotubes were treated without (control, C) or with 0.2 mM palmitate (P) for 16 h in the absence or the presence of 2 μM carnosic acid (CA). After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated Thr<sup>172</sup>, total AMPK, phosphorylated Ser<sup>79</sup>, or total ACC. Representative immunoblots are shown (<b>A</b>). The densitometry of the bands was measured and expressed in arbitrary units (<b>B</b>). The data is the mean ± SE of three separate experiments. (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 vs. control, # <span class="html-italic">p</span> &lt; 0.05 vs. palmitate alone).</p>
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<p>Effects of palmitate and carnosic acid on Akt expression and phosphorylation/activation and serine phosphorylation and expression of IRS-l in adipocytes. Fully differentiated 3T3-L1 adipocytes were treated without (control, C) or with 0.4 mM palmitate (P) for 16 h in the absence or the presence of 20 μM carnosic acid (CA) followed by stimulation without or with 100 nM insulin (I) for 30 min. After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated Ser<sup>473</sup> or total Akt (<b>A</b>) and Ser<sup>307</sup> or total IRS-1 (<b>B</b>). Representative immunoblots are shown. The densitometry of the bands was measured and expressed in arbitrary units. The data are the mean ± SE of four separate experiments (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. control, # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01 as indicated).</p>
Full article ">Figure 8 Cont.
<p>Effects of palmitate and carnosic acid on Akt expression and phosphorylation/activation and serine phosphorylation and expression of IRS-l in adipocytes. Fully differentiated 3T3-L1 adipocytes were treated without (control, C) or with 0.4 mM palmitate (P) for 16 h in the absence or the presence of 20 μM carnosic acid (CA) followed by stimulation without or with 100 nM insulin (I) for 30 min. After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated Ser<sup>473</sup> or total Akt (<b>A</b>) and Ser<sup>307</sup> or total IRS-1 (<b>B</b>). Representative immunoblots are shown. The densitometry of the bands was measured and expressed in arbitrary units. The data are the mean ± SE of four separate experiments (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. control, # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01 as indicated).</p>
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<p>Effects of palmitate and carnosic acid on JNK, mTOR, and p70S6K expression and phosphorylation in adipocytes. Fully differentiated adipocytes were treated without (control, C) or with 0.4 mM palmitate (P) for 16 h in the absence or the presence of 20 μM carnosic acid (CA). After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated Thr<sup>183</sup>/Tyr<sup>185</sup> or total JNK (<b>A</b>), phosphorylated Ser<sup>2448</sup> or total mTOR (<b>B</b>), and phosphorylated Thr<sup>389</sup>, or total p70S6K (<b>C</b>). Representative immunoblots are shown. The densitometry of the bands was measured and expressed in arbitrary units. The data are the mean ± SE of four separate experiments (* <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 vs. control, # <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 vs. palmitate alone).</p>
Full article ">Figure 9 Cont.
<p>Effects of palmitate and carnosic acid on JNK, mTOR, and p70S6K expression and phosphorylation in adipocytes. Fully differentiated adipocytes were treated without (control, C) or with 0.4 mM palmitate (P) for 16 h in the absence or the presence of 20 μM carnosic acid (CA). After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated Thr<sup>183</sup>/Tyr<sup>185</sup> or total JNK (<b>A</b>), phosphorylated Ser<sup>2448</sup> or total mTOR (<b>B</b>), and phosphorylated Thr<sup>389</sup>, or total p70S6K (<b>C</b>). Representative immunoblots are shown. The densitometry of the bands was measured and expressed in arbitrary units. The data are the mean ± SE of four separate experiments (* <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 vs. control, # <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 vs. palmitate alone).</p>
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<p>Effects of palmitate and carnosic acid on AMPK expression and phosphorylation in adipocytes. Fully differentiated adipocytes were treated without (control, C) or with 0.4 mM palmitate (P) for 16 h in the absence or the presence of 20 μM carnosic acid (CA). After treatment, the cells were lysed, and SDS-PAGE was performed, followed by immunoblotting with specific antibodies that recognize phosphorylated Thr<sup>172</sup> or total AMPK and Ser<sup>79</sup> or total ACC. Representative immunoblots are shown (<b>A</b>). The densitometry of the bands was measured and expressed in arbitrary units (* <span class="html-italic">p</span> &lt; 0.05 vs. control, # <span class="html-italic">p</span> &lt; 0.05 vs. palmitate alone). (<b>B</b>) The data is the mean ± SE of three separate experiments. (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. control, ## <span class="html-italic">p</span> &lt; 0.01 vs. palmitate alone).</p>
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<p>Carnosic acid counteracted the free fatty acid (FFA; palmitate)-induced muscle and fat cell insulin resistance. Carnosic acid prevented the palmitate-induced phosphorylation/activation of JNK, mTOR, and p70S6K, while the activation of AMPK and phosphorylation of ACC was increased. Under elevated free fatty acid conditions, carnosic acid restored the insulin stimulated Akt phosphorylation/activation, GLUT4 plasma membrane translocation, and glucose uptake. Created with BioRender.com. Green and red arrows represent the findings of the present study. Black and brown arrows represent established common knowledge.</p>
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12 pages, 1695 KiB  
Article
Engineered Liposomes Protect Immortalized Immune Cells from Cytolysins Secreted by Group A and Group G Streptococci
by Hervé Besançon, Yu Larpin, Viktoria S. Babiychuk, René Köffel and Eduard B. Babiychuk
Cells 2022, 11(1), 166; https://doi.org/10.3390/cells11010166 - 5 Jan 2022
Cited by 1 | Viewed by 2467
Abstract
The increasing antibiotic resistance of bacterial pathogens fosters the development of alternative, non-antibiotic treatments. Antivirulence therapy, which is neither bacteriostatic nor bactericidal, acts by depriving bacterial pathogens of their virulence factors. To establish a successful infection, many bacterial pathogens secrete exotoxins/cytolysins that perforate [...] Read more.
The increasing antibiotic resistance of bacterial pathogens fosters the development of alternative, non-antibiotic treatments. Antivirulence therapy, which is neither bacteriostatic nor bactericidal, acts by depriving bacterial pathogens of their virulence factors. To establish a successful infection, many bacterial pathogens secrete exotoxins/cytolysins that perforate the host cell plasma membrane. Recently developed liposomal nanotraps, mimicking the outer layer of the targeted cell membranes, serve as decoys for exotoxins, thus diverting them from attacking host cells. In this study, we develop a liposomal nanotrap formulation that is capable of protecting immortalized immune cells from the whole palette of cytolysins secreted by Streptococcus pyogenes and Streptococcus dysgalactiae subsp. equisimilis—important human pathogens that can cause life-threatening bacteremia. We show that the mixture of cholesterol-containing liposomes with liposomes composed exclusively of phospholipids is protective against the combined action of all streptococcal exotoxins. Our findings pave the way for further development of liposomal antivirulence therapy in order to provide more efficient treatment of bacterial infections, including those caused by antibiotic resistant pathogens. Full article
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Graphical abstract

Graphical abstract
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<p>Different types of immune cells display different sensitivities to filtered bacterial supernatants. The GAS ATCC 19165 supernatant is more toxic to THP-1 and to Jurkat cells than to Raji cells (<b>a</b>). The GAS 50362 supernatant is more toxic to Jurkat cells compared to THP-1 cells; Raji cells are the most resistant (<b>b</b>). The GGS ATCC 12394 supernatant shows comparable toxicity towards Raji and Jurkat cells; THP-1 cells are the most resistant (<b>c</b>). The GGS 5804 supernatant is more toxic to Raji cells compared to Jurkat cells; THP-1 cells are the most resistant (<b>d</b>).</p>
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<p>Neutralization of the cytotoxins secreted by GAS and GGS by cholesterol-containing liposomes. Ch:Sm-liposomes (Ch = 66 mol/%) completely neutralized cytolytic activities of GAS supernatants (LD<sub>&gt;90</sub>) towards all immune cell lines used in the current study (<b>a</b>,<b>b</b>). Ch:Sm-liposomes provided full protection to THP-1 cells against the GGS ATCC 12394 supernatant (LD<sub>&gt;90</sub>), but only partial protection for Jurkat and Raji cells. Protection levels differ significantly between all cell types, <span class="html-italic">p</span>-values &lt; 0.0005 (<b>c</b>). Ch:Sm-liposomes provided no protection against the GGS 5804 supernatant (LD<sub>&gt;90</sub>) for any cell type (<b>d</b>). Ch:Sm-liposomes provided partial protection against the GGS 5804 supernatant for THP-1 cells (~35% of ~LD<sub>90</sub>, <span class="html-italic">p</span>-value &lt; 0.005), Jurkat cells (~40% of ~LD<sub>70</sub>, <span class="html-italic">p</span>-value &lt; 0.008), and Raji cells (~15% of ~LD<sub>85</sub>, <span class="html-italic">p</span>-value &lt; 0.005) (<b>e</b>). Error bars = mean ± SD; N ≥ 3.</p>
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<p>Inhibition of cytolysins secreted by GAS and GGS by liposomes composed of 18:1/18:1 PC. 18:1/18:1 PC-liposomes displayed no protection towards any immune cell line used in the current study treated with either of the GAS supernatants (<b>a</b>,<b>b</b>). No protection for THP-1 or Jurkat cell lines and partial protection for the Raji cell line were observed against the GGS ATCC 12394 supernatant (~20% of ~LD<sub>95</sub>, <span class="html-italic">p</span>-value &lt; 0.03) (<b>c</b>). No protection for Jurkat cells and partial protection for THP-1 cells (~30% of ~LD<sub>90</sub>, <span class="html-italic">p</span>-value &lt; 0.005) and Raji cells (~45% of ~LD<sub>85</sub>, <span class="html-italic">p</span>-value &lt; 0.006) were observed against the GGS 5804 supernatant (<b>d</b>). Errors bars = mean ± SD; N ≥ 3.</p>
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<p>Inhibition of the cytolysins secreted by GGS by a liposomal mixture composed of Ch:Sm and 18:1/18:1 PC-liposomes. The combination of Ch:Sm-liposomes with 18:1/18:1 PC-liposomes completely protects immune cells against GGS ATCC 12394 cytolysins (<b>a</b>). Against GGS 5804 cytolysins, full protection is reached by THP-1 and Jurkat cells, but it is only partial for Raji cells (<b>b</b>).</p>
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13 pages, 2999 KiB  
Article
Role of Nse1 Subunit of SMC5/6 Complex as a Ubiquitin Ligase
by Peter Kolesar, Karel Stejskal, David Potesil, Johanne M. Murray and Jan J. Palecek
Cells 2022, 11(1), 165; https://doi.org/10.3390/cells11010165 - 4 Jan 2022
Cited by 10 | Viewed by 3455 | Correction
Abstract
Structural Maintenance of Chromosomes (SMC) complexes are important for many aspects of the chromosomal organization. Unlike cohesin and condensin, the SMC5/6 complex contains a variant RING domain carried by its Nse1 subunit. RING domains are characteristic for ubiquitin ligases, and human NSE1 has [...] Read more.
Structural Maintenance of Chromosomes (SMC) complexes are important for many aspects of the chromosomal organization. Unlike cohesin and condensin, the SMC5/6 complex contains a variant RING domain carried by its Nse1 subunit. RING domains are characteristic for ubiquitin ligases, and human NSE1 has been shown to possess ubiquitin-ligase activity in vitro. However, other studies were unable to show such activity. Here, we confirm Nse1 ubiquitin-ligase activity using purified Schizosaccharomyces pombe proteins. We demonstrate that the Nse1 ligase activity is stimulated by Nse3 and Nse4. We show that Nse1 specifically utilizes Ubc13/Mms2 E2 enzyme and interacts directly with ubiquitin. We identify the Nse1 mutation (R188E) that specifically disrupts its E3 activity and demonstrate that the Nse1-dependent ubiquitination is particularly important under replication stress. Moreover, we determine Nse4 (lysine K181) as the first known SMC5/6-associated Nse1 substrate. Interestingly, abolition of Nse4 modification at K181 leads to suppression of DNA-damage sensitivity of other SMC5/6 mutants. Altogether, this study brings new evidence for Nse1 ubiquitin ligase activity, significantly advancing our understanding of this enigmatic SMC5/6 function. Full article
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Figure 1
<p><span class="html-italic">S. pombe</span> Nse1 promotes in vitro ubiquitination together with Ubc13/Mms2. (<b>A</b>) Nse1 stimulates ubiquitin-chain formation when combined with Ubc13/Mms2. <span class="html-italic">S. pombe</span> E1 (Uba1), indicated E2s, biotinylated ubiquitin, ATP, and MgCl<sub>2</sub> were incubated in the presence or absence of Nse1/3/4 trimer for 1 h at 37 °C. The mixture was separated on 12% SDS–PAGE followed by Western blotting and visualization of biotinylated ubiquitin using Streptavidin-HRP. Numbers on the left indicate molecular weights of protein standards (in kDa). (<b>B</b>) Nse1/3/4 trimer promotes ubiquitination more efficiently than Nse1/3 dimer or Nse1 alone, and deletion of its vRING domain ablates this activity. In vitro ubiquitination assay was performed using E1, Ubc13/Mms2, biotinylated ubiquitin, indicated E3, and analyzed as in (<b>A</b>).</p>
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<p>Nse1 mutation R188E disrupts its ubiquitin ligase activity. (<b>A</b>) Nse1–Nse4 interaction analyzed by yeast two-hybrid assay is decreased by Nse1 vRING removal, but not by its R188E mutation. Plasmids carrying indicated genes or corresponding empty vectors were co-transformed into the <span class="html-italic">S. cerevisiae</span> PJ69–4a strain, grown to OD<sub>600</sub> ~ 1, fivefold serially diluted and spotted on solid media lacking leucine (L), tryptophan (W), histidine (H), or adenine (A) in absence or presence of 1 mM 3-aminotriazole (1AT), as depicted. Cells were grown for 3 days at 30 °C and scanned. (<b>B</b>) Alignment of the conserved vRING domain sequences of Nse1 from different species: <span class="html-italic">S. pombe</span> (S.p.), <span class="html-italic">S. cerevisiae</span> (S.c.), <span class="html-italic">Dictyostelium discoideum</span> (D.d.), <span class="html-italic">Caenorhabditis elegans</span> (C.e.), <span class="html-italic">Drosophila melanogaster</span> (D.m.), <span class="html-italic">Xenopus laevis</span> (X.l.), <span class="html-italic">Monodelphis domestica</span> (M.d.), <span class="html-italic">Mus musculus</span> (M.m.), <span class="html-italic">Homo sapiens sapiens</span> (H.s.). Amino acid shading represents the following conserved amino acids: violet—Zn<sup>2+</sup>-coordinating cysteins and histidines; dark green—hydrophobic and aromatic; red—basic. Red arrows on top indicate amino acids mutated in (<b>D</b>) and their corresponding numbers in <span class="html-italic">S. pombe</span>. (<b>C</b>) The Nse1 vRING domain (dark violet)—Ubc13 (grey) interaction model based on the crystal structure of the human TRIM21-Ubc13 [<a href="#B26-cells-11-00165" class="html-bibr">26</a>]. The Nse1-R188 residue is red labeled. (<b>D</b>) Nse1 R188E mutation impairs its ability to promote ubiquitination in vitro. E1, Ubc13/Mms2, biotinylated ubiquitin, and indicated Nse1 variants were incubated with ATP and MgCl<sub>2</sub> for 1 h at 37 °C and analyzed as in <a href="#cells-11-00165-f001" class="html-fig">Figure 1</a>A. (<b>E</b>) Nse1(97–178) interacts with ubiquitin in the yeast two-hybrid assay. <span class="html-italic">S. cerevisiae</span> PJ69–4a transformants were analyzed as in (<b>A</b>).</p>
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<p><span class="html-italic">Nse1-R188E</span> ubiquitin ligase mutant shows increased sensitivity to HU, MMS, and synthetic phenotypes with <span class="html-italic">smc5/6</span> mutants. (<b>A</b>) <span class="html-italic">Nse1-R188E</span> strain is sensitive to HU and MMS. The indicated <span class="html-italic">S. pombe</span> strains were grown to OD<sub>600</sub> ~ 1, tenfold serially diluted, spotted onto rich media with the designated amounts of HU, MMS, or UV dose, and incubated at 28 °C for 3 days. (<b>B</b>) <span class="html-italic">Nse1-R188E</span> mutant shows synthetic lethality with <span class="html-italic">smc6-74</span> and severe growth defects with <span class="html-italic">smc6-X</span> and <span class="html-italic">nse6Δ</span>. Double mutants were analyzed by tetrad dissection of <span class="html-italic">S. pombe</span> diploid strains resulting from crosses between the strain carrying the <span class="html-italic">nse1-R188E</span> mutation and the indicated <span class="html-italic">smc5/6</span> mutants. Red rectangles mark double mutants.</p>
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<p><span class="html-italic">Nse4-K181R</span> mutation partially suppresses the sensitivities of <span class="html-italic">smc6-X</span>, <span class="html-italic">smc6-74</span>, and <span class="html-italic">nse3-R254E</span> to DNA-damaging agents and HU. (<b>A</b>) Sensitivity of depicted <span class="html-italic">smc5/6</span> mutants to UV, HU, and MMS is partially suppressed by <span class="html-italic">nse4-K181R</span>. (<b>B</b>) <span class="html-italic">Nse4-K181R</span> does not suppress the sensitivity of the <span class="html-italic">nse1-R188E</span> strain. (<b>C</b>) Suppression of <span class="html-italic">smc6-X</span> sensitivity by <span class="html-italic">nse4-K181R</span> is dependent on <span class="html-italic">Ubc13</span>. The indicated <span class="html-italic">S. pombe</span> strains were grown to OD<sub>600</sub> ~ 1, tenfold serially diluted, spotted onto rich media with specified amounts of DNA-damaging agents, and incubated at 28 °C for 3 days.</p>
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<p>Model for Nse1–Ubc13~Ub complex. The Ubc13 E2 enzyme (grey) is charged with ubiquitin (blue) and binds the Nse1-vRING domain (dark violet). Ubiquitin is localized in the vicinity of the Nse1-WHB domain (light violet), and their interaction may enhance the ubiquitination process.</p>
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29 pages, 3204 KiB  
Review
Overview of Polyamines as Nutrients for Human Healthy Long Life and Effect of Increased Polyamine Intake on DNA Methylation
by Kuniyasu Soda
Cells 2022, 11(1), 164; https://doi.org/10.3390/cells11010164 - 4 Jan 2022
Cited by 39 | Viewed by 10419
Abstract
Polyamines, spermidine and spermine, are synthesized in every living cell and are therefore contained in foods, especially in those that are thought to contribute to health and longevity. They have many physiological activities similar to those of antioxidant and anti-inflammatory substances such as [...] Read more.
Polyamines, spermidine and spermine, are synthesized in every living cell and are therefore contained in foods, especially in those that are thought to contribute to health and longevity. They have many physiological activities similar to those of antioxidant and anti-inflammatory substances such as polyphenols. These include antioxidant and anti-inflammatory properties, cell and gene protection, and autophagy activation. We have first reported that increased polyamine intake (spermidine much more so than spermine) over a long period increased blood spermine levels and inhibited aging-associated pathologies and pro-inflammatory status in humans and mice and extended life span of mice. However, it is unlikely that the life-extending effect of polyamines is exerted by the same bioactivity as polyphenols because most studies using polyphenols and antioxidants have failed to demonstrate their life-extending effects. Recent investigations revealed that aging-associated pathologies and lifespan are closely associated with DNA methylation, a regulatory mechanism of gene expression. There is a close relationship between polyamine metabolism and DNA methylation. We have shown that the changes in polyamine metabolism affect the concentrations of substances and enzyme activities involved in DNA methylation. I consider that the increased capability of regulation of DNA methylation by spermine is a key of healthy long life of humans. Full article
(This article belongs to the Special Issue Epigenetic Mechanisms of Longevity and Aging)
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<p>Polyamine biosynthesis, degradation, and transmembrane transport. The polyamines are synthesized from arginine. Arginase converts arginine to ornithine, and ornithine decarboxylase (ODC), a rate-limiting enzyme with a short half-life, catalyzes the decarboxylation of ornithine to form putrescine, a polyamine precursor containing two amine groups. ODC is inhibited by antizyme, and antizyme is inhibited by an antizyme inhibitor. S-adenosylmethionine decarboxylase (AdoMetDC) is the second rate-limiting enzyme in polyamine synthesis and is involved in the decarboxylation of s-adenosylmethionine (SAM). Spermidine synthetase and spermine synthase are constitutively expressed aminopropyl transferases that catalyze the transfer of the aminopropyl group from decarboxylated s-adenosylmethionine (dcSAM) to putrescine and spermidine to form spermidine and spermine, respectively. Polyamine catabolism is mediated by the back conversion pathway in which spermine or spermidine are first acetylated by spermine/spermidine N1-acetyltransferase (SSAT) and then oxidized by N1-acetylpolyamine oxidase (APAO) to yield spermidine or putrescine, respectively. Spermine can be directly converted to spermidine via the spermine oxidase (SMO) reaction. Polyamines are transported across the membrane by the polyamine transporter. Black text indicates the substance name, while spermidine and spermine are shown in green and blue, respectively. Red letters indicate enzyme names. The solid black arrows indicate the metabolic pathway, and the dashed black arrows indicate the transfer of some material from the upstream material. Thick gray T-bars indicate inhibitory activity on the target. ODC: Ornithine decarboxylase; SSAT: Spermidine/spermine <span class="html-italic">N</span><sup>1</sup>-acetyltransferase; APAO: <span class="html-italic">N</span><sup>1</sup>-acetylpolyamine oxidase; SMO: Spermine oxidase; SAM: S-adenosylmethionine; AdoMetDC: Adenosylmethionine decarboxylase; dcSAM: Decarboxylated S-adenosylmethionine.</p>
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<p>Biological activities of polyamine and polyphenols. Both polyamines (spermidine and spermine) and antioxidants such as polyphenols and antioxidant vitamins have anti-inflammatory properties, antioxidant properties, and protect cells and genes from harmful stimuli and activate autophagy. Despite the vast amount of research on antioxidants, most of the studies have failed to show any benefit in preventing age-related conditions or extending lifespan. Therefore, the biological activities described in the figure are not enough to achieve life span extension and inhibition of the progression of senescence, especially of mammals, even if the mechanism and/or the pathway by which polyamines and polyphenols elicit these biological activities are different. References for A circled: [<a href="#B17-cells-11-00164" class="html-bibr">17</a>,<a href="#B18-cells-11-00164" class="html-bibr">18</a>,<a href="#B19-cells-11-00164" class="html-bibr">19</a>,<a href="#B20-cells-11-00164" class="html-bibr">20</a>,<a href="#B21-cells-11-00164" class="html-bibr">21</a>,<a href="#B22-cells-11-00164" class="html-bibr">22</a>,<a href="#B23-cells-11-00164" class="html-bibr">23</a>,<a href="#B25-cells-11-00164" class="html-bibr">25</a>,<a href="#B26-cells-11-00164" class="html-bibr">26</a>,<a href="#B28-cells-11-00164" class="html-bibr">28</a>,<a href="#B29-cells-11-00164" class="html-bibr">29</a>,<a href="#B30-cells-11-00164" class="html-bibr">30</a>,<a href="#B31-cells-11-00164" class="html-bibr">31</a>], References for B circled: [<a href="#B49-cells-11-00164" class="html-bibr">49</a>,<a href="#B121-cells-11-00164" class="html-bibr">121</a>,<a href="#B124-cells-11-00164" class="html-bibr">124</a>,<a href="#B125-cells-11-00164" class="html-bibr">125</a>,<a href="#B126-cells-11-00164" class="html-bibr">126</a>,<a href="#B127-cells-11-00164" class="html-bibr">127</a>,<a href="#B128-cells-11-00164" class="html-bibr">128</a>,<a href="#B129-cells-11-00164" class="html-bibr">129</a>,<a href="#B130-cells-11-00164" class="html-bibr">130</a>,<a href="#B131-cells-11-00164" class="html-bibr">131</a>,<a href="#B132-cells-11-00164" class="html-bibr">132</a>,<a href="#B133-cells-11-00164" class="html-bibr">133</a>,<a href="#B134-cells-11-00164" class="html-bibr">134</a>,<a href="#B135-cells-11-00164" class="html-bibr">135</a>,<a href="#B136-cells-11-00164" class="html-bibr">136</a>,<a href="#B137-cells-11-00164" class="html-bibr">137</a>,<a href="#B138-cells-11-00164" class="html-bibr">138</a>,<a href="#B139-cells-11-00164" class="html-bibr">139</a>,<a href="#B140-cells-11-00164" class="html-bibr">140</a>,<a href="#B141-cells-11-00164" class="html-bibr">141</a>,<a href="#B142-cells-11-00164" class="html-bibr">142</a>,<a href="#B143-cells-11-00164" class="html-bibr">143</a>,<a href="#B144-cells-11-00164" class="html-bibr">144</a>,<a href="#B145-cells-11-00164" class="html-bibr">145</a>,<a href="#B146-cells-11-00164" class="html-bibr">146</a>,<a href="#B147-cells-11-00164" class="html-bibr">147</a>,<a href="#B148-cells-11-00164" class="html-bibr">148</a>,<a href="#B149-cells-11-00164" class="html-bibr">149</a>,<a href="#B150-cells-11-00164" class="html-bibr">150</a>,<a href="#B151-cells-11-00164" class="html-bibr">151</a>,<a href="#B152-cells-11-00164" class="html-bibr">152</a>,<a href="#B153-cells-11-00164" class="html-bibr">153</a>,<a href="#B154-cells-11-00164" class="html-bibr">154</a>,<a href="#B155-cells-11-00164" class="html-bibr">155</a>,<a href="#B156-cells-11-00164" class="html-bibr">156</a>,<a href="#B157-cells-11-00164" class="html-bibr">157</a>,<a href="#B158-cells-11-00164" class="html-bibr">158</a>,<a href="#B159-cells-11-00164" class="html-bibr">159</a>], References for “?”: [<a href="#B22-cells-11-00164" class="html-bibr">22</a>,<a href="#B25-cells-11-00164" class="html-bibr">25</a>,<a href="#B26-cells-11-00164" class="html-bibr">26</a>,<a href="#B27-cells-11-00164" class="html-bibr">27</a>,<a href="#B28-cells-11-00164" class="html-bibr">28</a>,<a href="#B30-cells-11-00164" class="html-bibr">30</a>,<a href="#B31-cells-11-00164" class="html-bibr">31</a>].</p>
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<p>Polyamine metabolism and gene methylation. The relationship between polyamine metabolism (left side) and gene methylation (right side) is indicated. S-adenosylmethionine (SAM), an amino acid, is a substrate for polyamine synthesis and a donor of methyl groups. During polyamine synthesis, spermidine and spermine synthase require an aminopropyl group from decarboxylated s-adenosylmethionine (dcSAM), which is converted from SAM by the enzymatic action of adenosylmethionine decarboxylase (AdoMetDC). DNA methyltransferases (DNMTs) regulate gene methylation status by receiving a supply of the methyl group from SAM. SAM is essential as a source of methyl groups in gene methylation reactions, and dcSAM is a strong inhibitor of DNMTs. Black text indicates the substance name, while spermidine and spermine are shown in green and blue, respectively. Red letters indicate enzyme names. The solid black arrows indicate the metabolic pathway, and the dashed black arrows indicate the transfer of some material from the upstream material. The thick gray arrow indicates activity on the target, and thick gray T-bar indicates the inhibitory activity on target. ODC: Ornithine decarboxylase; SAM: S-adenosylmethionine; AdoMetDC: Adenosylmethionine decarboxylase; dcSAM: Decarboxylated S-adenosylmethionine; DNMT: DNA methyltransferase.</p>
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<p>The effects of increased polyamine intake on enzyme activities and substance levels related to polyamine metabolism and gene methylation. Increased polyamine intake elevates blood spermine levels and inhibits ODC activity. Increased spermine concentration strongly suppresses AdoMetDC activity, resulting in an increased amount of SAM and reduced amount of dcSAM. Since SAM is a methyl group donor for DNA methylation and dcSAM inhibits the activity of DNMTs, DNMTs are activated. As a result, enhanced aberrant methylation of entire genome and increased demethylation of ITGAL are reversed and regulated. Black text indicates the substance name, while spermidine and spermine are shown in green and blue, respectively. Red letters indicate enzyme names. The solid black arrows indicate the metabolic pathway, and the dashed black arrows indicate the transfer of the methyl group from SAM. The brown arrows indicate the conditions of enzymatic activities (upward and downward arrows). Upward arrows indicate activation of the enzyme, and downward arrows indicate the inhibition of enzyme activity. Green arrows indicate the change in material quantity and enzymatic activity. The thick gray arrows indicate the stimulus given to the target by the upstream enzyme activity, and the thick gray T-bars indicate the inhibitory activities on the target. The right figures show the condition and changes in DNA methylation status. The length of the line of black circles with bars indicates the progression of demethylation and hyper-methylation. The upward line indicates the progression of demethylation, and the downward lines indicate the progression of hyper-methylation. ODC: ornithine decarboxylase; SSAT: Spermidine/spermine <span class="html-italic">N</span><sup>1</sup>-acetyltransferase; APAO: <span class="html-italic">N</span><sup>1</sup>-acetylpolyamine oxidase; SAM: S-adenosylmethionine; AdoMetDC: Adenosylmethionine decarboxylase; dcSAM: Decarboxylated S-adenosylmethionine; DNMT: DNA methyltransferase; ITGAL: gene promoter area that is responsible for the LFA-1 expression.</p>
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<p>The effects of chronic inflammation on enzyme activities and substance levels related to polyamine metabolism and gene methylation. Age-associated chronic inflammation activates SSAT. SSAT activation enhances spermine degradation and results in decreased spermine concentration. Polyamine synthesis is activated as a compensation for polyamine degradation, resulting in an activation of AdoMetDC. AdoMetDC consumes SAM for polyamine synthesis and results in a decreased supply of methyl groups for DNA methylation. The lack of a methyl group supply results in aberrant methylation of the entire genome and increased demethylation of ITGAL. Black text indicates the substance name, while spermidine and spermine are shown in green and blue, respectively. Red letters indicate enzyme names. The solid black arrows indicate the metabolic pathway, and the dashed black arrows indicate the transfer of the aminopropyl group from dcSAM. The brown arrows indicate the conditions of enzymatic activities (upward and downward arrows). Upward arrows indicate the activation of the enzyme, and downward arrows indicate the inhibition of enzyme activity. Green arrows indicate the change in enzymatic activity. The thick gray arrows indicate the stimulus given to the target by the upstream substance or enzyme activity, and the thick gray T-bars indicate the inhibitory activities on the target. The right figures show the condition and changes in DNA methylation status. The length of the line of black circles with bars indicates the progression of demethylation and hyper-methylation. The upward line indicates the progression of demethylation and the downward lines indicate the progression of hyper-methylation. ODC: ornithine decarboxylase; SSAT: Spermidine/spermine <span class="html-italic">N</span><sup>1</sup>-acetyltransferase; APAO: <span class="html-italic">N</span><sup>1</sup>-acetylpolyamine oxidase; SAM: S-adenosylmethionine; AdoMetDC: Adenosylmethionine decarboxylase; dcSAM: Decarboxylated S-adenosylmethionine; DNMT: DNA methyltransferase; ITGAL: gene promoter area that is responsible for the LFA-1 expression.</p>
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<p>Bioactivities and mechanism of polyamines contributing to healthy long life. The mechanism by which increased polyamine intake inhibits onset or progression of aging-associated diseases and senescence. Increased polyamine intake elevates blood spermine levels in humans, in spite the fact that many foods contain spermidine much more than spermine. Polyamine binds to the cell membrane, proteins, and genes by electric charge. Polyamine (spermine and spermidine) protects cells and genes from harmful stimuli indicated in red. Spermine inhibits aberrant DNA methylation and regulates DNA methylation status. These biological activities contribute to a healthy longevity.</p>
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32 pages, 2696 KiB  
Article
Co-Expression Analysis of microRNAs and Proteins in Brain of Alzheimer’s Disease Patients
by Callum N. Watson, Ghazala Begum, Emma Ashman, Daniella Thorn, Kamal M. Yakoub, Moustafa Al Hariri, Ali Nehme, Stefania Mondello, Firas Kobeissy, Antonio Belli and Valentina Di Pietro
Cells 2022, 11(1), 163; https://doi.org/10.3390/cells11010163 - 4 Jan 2022
Cited by 10 | Viewed by 3872
Abstract
Alzheimer’s disease (AD) is the most common form of dementia globally; however, the aetiology of AD remains elusive hindering the development of effective therapeutics. MicroRNAs (miRNAs) are regulators of gene expression and have been of growing interest in recent studies in many pathologies [...] Read more.
Alzheimer’s disease (AD) is the most common form of dementia globally; however, the aetiology of AD remains elusive hindering the development of effective therapeutics. MicroRNAs (miRNAs) are regulators of gene expression and have been of growing interest in recent studies in many pathologies including AD not only for their use as biomarkers but also for their implications in the therapeutic field. In this study, miRNA and protein profiles were obtained from brain tissues of different stage (Braak III-IV and Braak V-VI) of AD patients and compared to matched controls. The aim of the study was to identify in the late stage of AD, the key dysregulated pathways that may contribute to pathogenesis and then to evaluate whether any of these pathways could be detected in the early phase of AD, opening new opportunity for early treatment that could stop or delay the pathology. Six common pathways were found regulated by miRNAs and proteins in the late stage of AD, with one of them (Rap1 signalling) activated since the early phase. MiRNAs and proteins were also compared to explore an inverse trend of expression which could lead to the identification of new therapeutic targets. These results suggest that specific miRNA changes could represent molecular fingerprint of neurodegenerative processes and potential therapeutic targets for early intervention. Full article
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<p>Heatmap showing the expression of 54 differentially regulated microRNAs in Alzheimer’s disease. Fifty-four microRNAs were found using Mann–Whitney statistical analysis across the 2 different comparisons, Control vs. Braak stage III-IV and Control vs. Braak stage V-VI. A <span class="html-italic">p</span>-value of less than 0.05 was considered significant. Hierarchal clustering is present on the left with colours relevant to their group. This was made using heatmap.2 in the R programming language with complete linkage, and Euclidean distance used to compute.</p>
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<p>Heatmap showing the expression of 174 differentially regulated proteins in Alzheimer’s disease across the 2 compariosns Control vs. Braak stage IiI–IV and Control vs. Braak stage V-VI. A <span class="html-italic">p</span>-value of less than 0.05 was considered significant. Hierarchal clustering is present on the left with colours relevant to their group. This was made using heatmap.2 in the R programming language with complete linkage, and Euclidean distance used to compute.</p>
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<p>Braak stage III-IV pathways analyses.</p>
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<p>Braak stage V-VI pathways analyses.</p>
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<p>DE-miRNA pathway studio analyses in Braak III-IV and Braak V-VI. The pathological processes triggered by Braak III-IV DE-miRNA (panel <b>A</b>) and Braak V-VI DE-miRNA (panel <b>C</b>). The related pathways of Braak III-IV DE-miRNA (panel <b>B</b>) and Braak V-VI DE-miRNA (panel <b>D</b>).</p>
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<p>DE-protein pathway studio analyses in Braak III-IV and Braak V-VI. AD pathways generated by DE-proteins in Braak III-IV (panel <b>A</b>) and Braak V-VI DE-miRNA (panel <b>B</b>).</p>
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13 pages, 1668 KiB  
Article
N-Glycosylation Facilitates 4-1BB Membrane Localization by Avoiding Its Multimerization
by Ruoxuan Sun, Alyssa Min Jung Kim, Allison A. Murray and Seung-Oe Lim
Cells 2022, 11(1), 162; https://doi.org/10.3390/cells11010162 - 4 Jan 2022
Cited by 8 | Viewed by 3259
Abstract
Leveraging the T cell immunity against tumors represents a revolutionary type of cancer therapy. 4-1BB is a well-characterized costimulatory immune receptor existing on activated T cells and mediating their proliferation and cytotoxicity under infectious diseases and cancers. Despite the accumulating interest in implementing [...] Read more.
Leveraging the T cell immunity against tumors represents a revolutionary type of cancer therapy. 4-1BB is a well-characterized costimulatory immune receptor existing on activated T cells and mediating their proliferation and cytotoxicity under infectious diseases and cancers. Despite the accumulating interest in implementing 4-1BB as a therapeutic target for immune-related disorders, less is known about the pattern of its intracellular behaviors and regulations. It has been previously demonstrated that 4-1BB is heavily modified by N-glycosylation; however, the biological importance of this modification lacks detailed elucidation. Through biochemical, biophysical, and cell-biological approaches, we systematically evaluated the impact of N-glycosylation on the ligand interaction, stability, and localization of 4-1BB. We hereby highlighted that N-glycan functions by preventing the oligomerization of 4-1BB, thus permitting its membrane transportation and fast turn-over. Without N-glycosylation, 4-1BB could be aberrantly accumulated intracellularly and fail to be sufficiently inserted in the membrane. The N-glycosylation-guided intracellular processing of 4-1BB serves as the potential mechanism explicitly modulating the “on” and “off” of 4-1BB through the control of protein abundance. Our study will further solidify the understanding of the biological properties of 4-1BB and facilitate the clinical practice against this promising therapeutic target. Full article
(This article belongs to the Special Issue Mechanism of Anti-tumor Immunity of Cells and Immunotherapy)
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<p>4-1BB is a heavily <span class="html-italic">N</span>-glycosylated protein with two modified sites. (<b>A</b>) Alignment of mammalian 4-1BB sequence around the <span class="html-italic">N</span>-glycosylation sites. The N-X-S/T motif is outlined by the red square. (<b>B</b>) Immunoblotting analysis of 4-1BB undergoing deglycosylation treatment by PNGase F. (<b>C</b>) MALDI-MS profiling of permethylated N-glycans released from PNGase F-treated recombinant 4-1BB protein. The masses of indicated glycan species represents the [M + Na<sup>+</sup>] values. SP, signal peptide; ECD, extracellular domain; TM, transmembrane domain; ICD, intracellular domain; CDR, cysteine-rich domain; EV, empty vector; 4-1BB (G), <span class="html-italic">N</span>-glycosylated 4-1BB; 4-1BB (NG), non-<span class="html-italic">N</span>-glycosylated 4-1BB.</p>
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<p>The impact of <span class="html-italic">N</span>-glycosylation on 4-1BB/4-1BBL interaction. (<b>A</b>) The relative level of bound 4-1BBL to PNGase F-treated and untreated 4-1BB protein (<span class="html-italic">n</span> = 3). (<b>B</b>) Octet analysis calculating the binding affinity of glycosylated (black) and deglycosylated 4-1BB (red) to 4-1BBL along with the K<sub>D</sub> values. N.S., not significant (Two-tailed student’s <span class="html-italic">t</span>-test).</p>
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<p>The regulation of cell surface level of 4-1BB by <span class="html-italic">N</span>-glycosylation. (<b>A</b>) Jurkat cells were transduced with lentivirus encoding 4-1BB WT and glycosylation-deficient mutant including N138Q, N149Q and 2NQ, respectively. The membrane levels of 4-1BB in each group were compared by flow cytometry. The percentages of positive events were included in the plots. (<b>B</b>) The quantitative results of membrane 4-1BB level in each group in (<b>A</b>) (<span class="html-italic">n</span> = 3). (<b>C</b>) The immunoblotting analysis of total 4-1BB from cells in (<b>A</b>). N.S., not significant; ***, <span class="html-italic">p</span> &lt; 0.001 (Two-tailed student’s <span class="html-italic">t</span>-test); MFI, mean fluorescence intensity.</p>
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<p><span class="html-italic">N</span>-glycosylation plays an essential role in determining 4-1BB stability. (<b>A</b>) HEK293T cells were transfected with Flag-tagged 4-1BB WT and 2NQ followed by CHX-chase assay to compare their stability. (<b>B</b>) The quantification of the remaining 4-1BB at each time point (<span class="html-italic">n</span> = 3). The percentage values of band intensity were normalized to time 0 h. 50% degradation is indicated by the dashed line. (<b>C</b>) Immunoblotting analysis of the MG-132 effect on 4-1BB WT and 2NQ. HEK293T/4-1BB WT and HEK293T/4-1BB 2NQ cells were treated by 10 μM MG-132 for 0, 4, and 8 h followed by immunoblotting assay. (<b>D</b>) Comparison of polyubiquitination level between WT and 2NQ 4-1BB. Flag-tagged 4-1BB and HA-tagged Ub were co-transfected to HEK293T cells followed by in vivo ubiquitination assay 48 h after transfection. IP, immunoprecipitates. **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001 (Two-tailed student’s <span class="html-italic">t</span>-test).</p>
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<p>Oligomerization is associated with augmented stability of unglycosylated 4-1BB. (<b>A</b>) Non-reducing SDS-PAGE uncovered the formation of dimerized, trimerized, and oligomerized 4-1BB 2NQ. The bands that exist in the presence of DTT were considered monomers. The white circle, triangle, square, and star represent the monomerized, dimerized, trimerized, and oligomerized form of 4-1BB 2NQ. (<b>B</b>) 4-1BB 2NQ failed to form multimers when lacking the key cysteine residue C121. (<b>C</b>) HEK293T cells were transfected with Flag-tagged 4-1BB WT, C121A, 2NQ, and 2NQ/C121A followed by CHX-chase assay to compare their stability. (<b>D</b>) The quantification of the remaining 4-1BB at each time point (<span class="html-italic">n</span> = 3). The percentage values of band intensity were normalized to time 0 h. 50% degradation is indicated by the dashed line. Two-tailed student’s t-test was performed to compare the values on 8 h point. N.S., not significant; **, <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>C121-mediated multimerization governs the stability and localization of unglycosylated 4-1BB. (<b>A</b>) Jurkat cells were transduced with lentivirus encoding 4-1BB WT, C121A, 2NQ, and 2NQ/C121A, respectively. The membrane levels of 4-1BB in each group were compared by flow cytometry. The percentages of positive events were included in the plots. (<b>B</b>) The quantitative results of membrane 4-1BB level in each group in (<b>A</b>) (<span class="html-italic">n</span> = 3). (<b>C</b>) The immunoblotting analysis of total 4-1BB from each group of cells in (<b>A</b>). N.S., not significant; ***, <span class="html-italic">p</span> &lt; 0.001 (Two-tailed student’s <span class="html-italic">t</span>-test); MFI, mean fluorescence intensity.</p>
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22 pages, 7188 KiB  
Article
Cell Type-Selective Loss of Peroxisomal β-Oxidation Impairs Bipolar Cell but Not Photoreceptor Survival in the Retina
by Daniëlle Swinkels, Yannick Das, Sai Kocherlakota, Stefan Vinckier, Eric Wever, Antoine H.C. van Kampen, Frédéric M. Vaz and Myriam Baes
Cells 2022, 11(1), 161; https://doi.org/10.3390/cells11010161 - 4 Jan 2022
Cited by 13 | Viewed by 4153
Abstract
Retinal degeneration is a common feature in peroxisomal disorders leading to blindness. Peroxisomes are present in the different cell types of the retina; however, their precise contribution to retinal integrity is still unclear. We previously showed that mice lacking the central peroxisomal β-oxidation [...] Read more.
Retinal degeneration is a common feature in peroxisomal disorders leading to blindness. Peroxisomes are present in the different cell types of the retina; however, their precise contribution to retinal integrity is still unclear. We previously showed that mice lacking the central peroxisomal β-oxidation enzyme, multifunctional protein 2 (MFP2), develop an early onset retinal decay including photoreceptor cell death. To decipher the function of peroxisomal β-oxidation in photoreceptors, we generated cell type selective Mfp2 knockout mice, using the Crx promotor targeting photoreceptors and bipolar cells. Surprisingly, Crx-Mfp2−/− mice maintained photoreceptor length and number until the age of 1 year. A negative electroretinogram was indicative of preserved photoreceptor phototransduction, but impaired downstream bipolar cell signaling from the age of 6 months. The photoreceptor ribbon synapse was affected, containing free-floating ribbons and vesicles with altered size and density. The bipolar cell interneurons sprouted into the ONL and died. Whereas docosahexaenoic acid levels were normal in the neural retina, levels of lipids containing very long chain polyunsaturated fatty acids were highly increased. Crx-Pex5−/− mice, in which all peroxisomal functions are inactivated in photoreceptors and bipolar cells, developed the same phenotype as Crx-Mfp2−/− mice. In conclusion, the early photoreceptor death in global Mfp2−/− mice is not driven cell autonomously. However, peroxisomal β-oxidation is essential for the integrity of photoreceptor ribbon synapses and of bipolar cells. Full article
(This article belongs to the Special Issue Peroxisome Biogenesis and Protein Targeting Mechanisms)
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<p>Confirmation of conditional <span class="html-italic">Mfp2</span> knockout in <span class="html-italic">Crx-Mfp2</span><sup>−/−</sup> mice. (<b>A</b>) Immunohistochemical staining for Cre recombinase (red) showed no specific staining in control mice, but clear expression in photoreceptors. Additionally, some expression was seen in the INL in <span class="html-italic">Crx-Mfp2</span><sup>−/−</sup> mice (arrows). (<b>B</b>) Western blotting confirmed loss of MFP2 in the neural retina of <span class="html-italic">Crx-Mfp2</span><sup>−/−</sup> mice. The full length MFP2 band and the hydratase band were combined to calculate MFP2 levels. The band around 50 kDa is believed to be aspecific. Vinculin was used as loading control. (<b>C</b>) In situ hybridization showed substantial loss of <span class="html-italic">Mfp2</span> transcripts (red) in the PR, PIS and INL of <span class="html-italic">Crx-Mfp2</span><sup>−/−</sup> mice. <span class="html-italic">N</span> = 4/group. Statistical difference based on unpaired <span class="html-italic">t</span>-test: * <span class="html-italic">p</span> &lt; 0.05. Error bars indicate SD. RPE—retinal pigment epithelium; PR—photoreceptor layer; POS—photoreceptor outer segments; PIS—photoreceptor inner segments; ONL—outer nuclear layer; OPL—outer plexiform layer; INL—inner nuclear layer; IPL—inner plexiform layer; GCL—ganglion cell layer; MFP2—multifunctional protein 2.</p>
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<p>The morphology of the retina is normal in <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. (<b>A</b>) HE staining did not reveal morphological changes in <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice at any investigated age. (<b>B</b>,<b>D</b>) No shortening of the photoreceptor layers is observed with phase contrast microscopy. (<b>C</b>) PLIN2 (green) staining showed a gradual increase in lipid droplet accumulation, primarily in the POS, to a lesser extent in the PIS, and sporadically in the OPL, IPL and GCL (white arrows) of <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. <span class="html-italic">N</span> = 4–5/group. Statistical analysis based on unpaired <span class="html-italic">t</span>-test of CT vs. mutant mice at each age. ns—not significant. Error bars indicate SD. RPE—retinal pigment epithelium; PR—photoreceptor layer; POS—photoreceptor outer segments; PIS—photoreceptor inner segments; ONL—outer nuclear layer; OPL—outer plexiform layer; INL—inner nuclear layer; IPL—inner plexiform layer; GCL—ganglion cell layer; PLIN2—perilipin 2.</p>
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<p>PUFA levels in the neural retina of 6-month-old <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. (<b>A</b>) DHA levels were not altered in the neural retina of <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. However, VLC-PUFAs accumulated in lysophosphatidylcholine (<b>B</b>), cholesterol esters (<b>C</b>), phosphatidylcholine (<b>D</b>) and triglycerides (<b>E</b>). Data are presented as fold change compared to CT levels. CT levels are presented as a dashed line. N = 4/group. Statistical analysis is explained in materials and methods (<a href="#sec2dot10-cells-11-00161" class="html-sec">Section 2.10</a>). Error bars indicate SD. DHA—docosahexaenoic acid; VLC-PUFA—very long chain polyunsaturated fatty acid; LPC—lysophosphatidylcholine; CE—cholesterol ester; PC—phosphatidylcholine; TG—triglyceride. * <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>Reduced visual acuity and function in <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. (<b>A</b>) No change in scotopic a-wave between control and <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice at any investigated age. The scotopic and photopic b-wave was significantly reduced in 6 M and 1 Y old <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. (<b>B</b>) Flicker ERG responses were impaired (6 M). (<b>C</b>) Optokinetic tracking response showed a significant reduction in visual acuity at 3 M, 6 M and 1 Y. N = 4–8/group. Statistical difference based on unpaired t-test and two-way ANOVA: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001; ns—not significant. Error bars indicate SD.</p>
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<p><span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice show loss of bipolar cells and impaired synaptic connections. (<b>A</b>) PKCα (red) staining showed clear loss of bipolar cells at the age of 1 Y. (<b>B</b>) Higher magnification images revealed sprouting of bipolar cells (red) and VGLUT1 (green) mislocalization into the ONL. White arrows indicate the sprouting. (<b>C</b>) Quantification of PKCα positive bipolar cells per 100 µm revealed a significant loss in both 6-month-old and 1-year-old <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. N = 4/group. Statistical difference based on unpaired <span class="html-italic">t</span>-test: ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001. Error bars indicate SD. RPE—retinal pigment epithelium; PR—photoreceptor; ONL—outer nuclear layer; OPL—outer plexiform layer; INL—inner nuclear layer; IPL—inner plexiform layer; GCL—ganglion cell layer.</p>
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<p>Loss of photoreceptor ribbon synapse integrity in 6-month-old <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. Transmission electron microscopy images showed normal photoreceptor ribbon synapse formation in CT mice, with a ribbon (green), two horizontal cells (yellow) and a bipolar cell (pink). <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice presented with free-floating photoreceptor ribbons and abnormal structures (*) in the photoreceptor synapses, which did not occur in CT mice. Top and bottom panel are the same images. Bottom panel includes interpretation. N = 4/group.</p>
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<p>Retinal inflammation in the <span class="html-italic">Crx-Mfp2<sup>−/−</sup></span> mice. (<b>A</b>) Activated Müller cells were observed starting from the age of 3 M. Progressive sprouting into the retinal layers is observed at later time points. (<b>B</b>) Microglia infiltration is seen in the OPL already from 3 M of age. From 6 M microglia are swollen and reactive both in the OPL and IPL (white arrows). N = 4/group. RPE—retinal pigment epithelium; PR—photoreceptor layer; ONL—outer nuclear layer; OPL—outer plexiform layer; INL—inner nuclear layer; IPL—inner plexiform layer; GCL—ganglion cell layer; GFAP—glial fibrillary acidic protein; IBA1—ionized calcium binding adaptor molecule 1.</p>
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<p>Retinal phenotype of <span class="html-italic">Crx-Pex5<sup>−/−</sup></span> mice. (<b>A</b>) HE staining showed no morphological differences between CT and <span class="html-italic">Crx-Pex5<sup>−/−</sup></span> mice at any investigated age. (<b>B</b>) Lipid droplet staining revealed a gradual increase in lipid droplets in the POS, PIS, OPL (white arrows), IPL (white arrows) and GCL in <span class="html-italic">Crx-Pex5<sup>−/−</sup></span> mice. (<b>C</b>) Activated Müller cells were observed starting from the age of 3 M, with progressive sprouting into the neural retina at later time points. (<b>D</b>) Microglia are swollen and reactive both in the OPL and IPL (white arrows) from 3 M of age. N = 4/group. RPE—retinal pigment epithelium; PR—photoreceptor; POS—photoreceptor outer segments; PIS—photoreceptor inner segments; ONL—outer nuclear layer; OPL—outer plexiform layer; INL—inner nuclear layer; IPL—inner plexiform layer; GCL—ganglion cell layer; GFAP—glial fibrillary acid protein; IBA1—ionized calcium binding adaptor molecule 1; PLIN2—perilipin 2.</p>
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<p>Reduced visual acuity and function in <span class="html-italic">Crx-Pex5<sup>−/−</sup></span> mice. (<b>A</b>) Optokinetic tracking response showed a significant reduction in visual acuity starting at 3 M. (<b>B</b>) Flicker ERG responses are lower in 6-month-old <span class="html-italic">Crx-Pex5<sup>−/−</sup></span> mice. (<b>C</b>–<b>E</b>) Scotopic and photopic b-wave responses are significantly affected in <span class="html-italic">Crx-Pex5<sup>−/−</sup></span> mice starting from 6 M of age. N = 4/group. Statistical difference based on two-way ANOVA and unpaired <span class="html-italic">t</span>-test: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001; ns—not significant. Error bars indicate SD.</p>
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41 pages, 1737 KiB  
Review
Multifactorial Mechanism of Sarcopenia and Sarcopenic Obesity. Role of Physical Exercise, Microbiota and Myokines
by Jan Bilski, Piotr Pierzchalski, Marian Szczepanik, Joanna Bonior and Jerzy A. Zoladz
Cells 2022, 11(1), 160; https://doi.org/10.3390/cells11010160 - 4 Jan 2022
Cited by 89 | Viewed by 18834
Abstract
Obesity and ageing place a tremendous strain on the global healthcare system. Age-related sarcopenia is characterized by decreased muscular strength, decreased muscle quantity, quality, and decreased functional performance. Sarcopenic obesity (SO) is a condition that combines sarcopenia and obesity and has a substantial [...] Read more.
Obesity and ageing place a tremendous strain on the global healthcare system. Age-related sarcopenia is characterized by decreased muscular strength, decreased muscle quantity, quality, and decreased functional performance. Sarcopenic obesity (SO) is a condition that combines sarcopenia and obesity and has a substantial influence on the older adults’ health. Because of the complicated pathophysiology, there are disagreements and challenges in identifying and diagnosing SO. Recently, it has become clear that dysbiosis may play a role in the onset and progression of sarcopenia and SO. Skeletal muscle secretes myokines during contraction, which play an important role in controlling muscle growth, function, and metabolic balance. Myokine dysfunction can cause and aggravate obesity, sarcopenia, and SO. The only ways to prevent and slow the progression of sarcopenia, particularly sarcopenic obesity, are physical activity and correct nutritional support. While exercise cannot completely prevent sarcopenia and age-related loss in muscular function, it can certainly delay development and slow down the rate of sarcopenia. The purpose of this review was to discuss potential pathways to muscle deterioration in obese individuals. We also want to present the current understanding of the role of various factors, including microbiota and myokines, in the process of sarcopenia and SO. Full article
(This article belongs to the Collection Molecular Mechanisms of Exercise and Healthspan)
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<p>Potential pathogenic mechanisms of age-related sarcopenia and sarcopenic obesity.</p>
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<p>Diagram illustrating myostatin, and IGF-1 pathway interactions. Myostatin’s effects require both Smad2 and Smad3, which block muscle differentiation. Smad2 and 3 activations are both required for myostatin’s inhibitory effects on Akt. IGF-1 released in response to exercise can counteract myostatin’s effects.</p>
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<p>A general outline of the functioning of the Hippo pathway. Diagram presents central axis of pathway consisting of ‘core kinases’ MST1/2, LATS1/2, their up-stream modulators: Merlin/NF2, Kibra/WWC1/2 and effector part of the pathway—YAP (Yes-associated protein encoded by YAP1). What is worth mentioning is active ‘core kinases’ phosphorylate YAP resulting in its cytoplasmic sequestration and down-regulation of the pathway activity. A detailed description of the pathway functioning is in the text of the article. MST1/2 (mammalian sterile 20-like kinases), LATS (large tumor suppressor kinases), Vgll1-4 (vestigial-like, Vito, Tondu), Tead1-4 (TEA/ATTS domain/TEF/scalloped), Merlin/NF2 (neurofibromatosis type 2), WW45/Sav1 (adaptor proteins Salvador homologue1), MOBKL1A (Mps-one binder kinase activator 1), TAOK1, thousand-and-one amino acids kinase 1, Amot (angiomotin). FOXO3a (Forkhead box O3).</p>
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<p>Involvement of Hippo signaling in muscle cells development. Active— non phosphorylated YAP nuclear translocation results in direct activation of co-activation of TEAD dependent genes regulating muscle cells such as α-actin, Mef2c and Myogin. For details, please refer to the text.</p>
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<p>Diagram presenting dynamics of changes in expression of YAP, MyoD and myogenin during activation of satellite cells division, conversion to myoblast and differentiation to myofiber. Based on the information summarized in the article, Hippo pathway might be considered an additional important mediator of balance between development and differentiation of muscle cells.</p>
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<p>Myokines linked to age-related changes, their release during exercise, and putative mechanisms of action. More information on the listed myokines is described in specific paragraphs.</p>
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33 pages, 50489 KiB  
Review
Aptamer-Enabled Nanomaterials for Therapeutics, Drug Targeting and Imaging
by Mengping Liu, Lin Wang, Young Lo, Simon Chi-Chin Shiu, Andrew B. Kinghorn and Julian A. Tanner
Cells 2022, 11(1), 159; https://doi.org/10.3390/cells11010159 - 4 Jan 2022
Cited by 46 | Viewed by 7035
Abstract
A wide variety of nanomaterials have emerged in recent years with advantageous properties for a plethora of therapeutic and diagnostic applications. Such applications include drug delivery, imaging, anti-cancer therapy and radiotherapy. There is a critical need for further components which can facilitate therapeutic [...] Read more.
A wide variety of nanomaterials have emerged in recent years with advantageous properties for a plethora of therapeutic and diagnostic applications. Such applications include drug delivery, imaging, anti-cancer therapy and radiotherapy. There is a critical need for further components which can facilitate therapeutic targeting, augment their physicochemical properties, or broaden their theranostic applications. Aptamers are single-stranded nucleic acids which have been selected or evolved to bind specifically to molecules, surfaces, or cells. Aptamers can also act as direct biologic therapeutics, or in imaging and diagnostics. There is a rich field of discovery at the interdisciplinary interface between nanomaterials and aptamer science that has significant potential across biomedicine. Herein, we review recent progress in aptamer-enabled materials and discuss pending challenges for their future biomedical application. Full article
(This article belongs to the Special Issue Frontiers in Aptamers)
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<p>Illustration of the aptamer selection process. Typically, four steps are involved in the SELEX cycle. Step 1, the single-stranded DNA or RNA library is incubated with target molecules. Step 2, the bound sequences are separated from unbound strands and recovered for further process. Step 3, the target-binding sequences are amplified by PCR. RNA molecules need additional transcription procedures for amplification purposes. Step 4, single-stranded DNA/RNA sequences are re-generated from PCR products as a new library for the next round of selection. Through several iterative cycles, aptamers can be identified by sequencing and characterization assays.</p>
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<p>Applications of aptamer-functionalized drug delivery nanocarriers. Aptamer-incorporated drug nanocarriers can be designed for (<b>a</b>) targeted drug delivery, (<b>b</b>) controllable drug release, and (<b>c</b>) imaging-guided therapy. In (<b>b</b>), drugs captured by conformation-switchable aptamers or other stimulus-responsive agents can be programmatically released in response to the environmental stimuli. In (<b>c</b>), imaging signals can be designed to release with payloads or upon binding to target cells, enabling guiding and tracking of therapeutics in vivo.</p>
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<p>Schematic representation of DNA nanostructure assembly. (<b>a</b>) DNA nanotrain with aptamers assembled via complementary sequence. Modified with permission from reference [<a href="#B64-cells-11-00159" class="html-bibr">64</a>]. Copyright 2013 PNAS. (<b>b</b>) Assembly of DNA tetrahedron through simple extension of strands. Modified with permission from reference [<a href="#B65-cells-11-00159" class="html-bibr">65</a>]. Copyright 2019 RSC publishing. (<b>c</b>) Aptamer guided and gated the delivery of therapeutic drugs. Adapted from reference [<a href="#B66-cells-11-00159" class="html-bibr">66</a>]. Copyright 2017 ACS publications.</p>
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<p>Schematic illustration of aptamer-functionalized micelles. They have been used to, (<b>a</b>) specifically deliver DOX to WR22Rν1 tumor-bearing mice for anti-prostate cancer therapy and (<b>b</b>) mediate pH/NIR-responsive breast cancer-specific imaging and therapy. (<b>a</b>) is modified with permission from reference [<a href="#B98-cells-11-00159" class="html-bibr">98</a>]. Copyright 2013 Elsevier. (<b>b</b>) is adapted from reference [<a href="#B102-cells-11-00159" class="html-bibr">102</a>]. Copyright 2014 Wiley Online Library.</p>
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<p>Schematic representation of the gel-sol transition of aptamer-decorated hydrogels. For target capture, aptamers in hydrogels would be de-hybridized from complementary strands to capture targets. For target release, aptamer-captured targets are released via a competitive hybridization from complementary oligonucleotides of aptamers or aptamer holders.</p>
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<p>Schematic illustration of aptamer-functionalized polymeric nanoparticles and branched polymers. (<b>a</b>) Polymeric nanoparticles. (<b>b</b>) Branched polymeric nanostructures.</p>
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<p>Schematic representation of aptamer-decorated gold nanostructures. They have been used to track A549-specifc tumors via gold-enhanced SERS imaging and kill tumor cells through NIR-triggered chemo-hyperthermia. It’s modified with permission from ref. [<a href="#B149-cells-11-00159" class="html-bibr">149</a>]. Copyright 2019 RSC publishing.</p>
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<p>Schematic illustration of aptamer-functionalized magnetic nanomaterials. They have been used to (<b>a</b>) monitor the specific MRI-guided anti-prostate cancer therapy via DOX and (<b>b</b>) perform synergistic anti-cancer therapy mediated by DOX and hyperthermia in the guidance of MR imaging. (<b>a</b>) is adapted from reference [<a href="#B155-cells-11-00159" class="html-bibr">155</a>]. Copyright 2011 Wiley Online Library. (<b>b</b>) is modified with permission of reference [<a href="#B157-cells-11-00159" class="html-bibr">157</a>]. Copyright 2019 Elsevier.</p>
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<p>Schematic diagram of aptamer-empowered QDs nanomaterials. (<b>a</b>) ATP-triggered DOX release and FRET-guided targeted anti-cancer therapy. It’s modified with permission of reference [<a href="#B164-cells-11-00159" class="html-bibr">164</a>]. Copyright 2015 ACS publishing. (<b>b</b>) UV-mediated FRET imaging and ROS-driven targeted photodynamic therapy of cervical cancer. It’s modified with permission of reference [<a href="#B165-cells-11-00159" class="html-bibr">165</a>]. Copyright 2016 RSC publishing.</p>
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<p>Illustration of aptamer-decorated silica nanomaterials. They have been used to, (<b>a</b>) control the release of Ru(bipy)<sup>32+</sup> by de-hybridizing from complementary oligos in a ATP-responsive manner, and (<b>b</b>) guide BMPP-Pt to specifically image and suppress Huh7 cancer cells. (<b>a</b>) is modified with permission of reference [<a href="#B178-cells-11-00159" class="html-bibr">178</a>]. Copyright 2012 ACS publishing. (<b>b</b>) is adapted from reference [<a href="#B186-cells-11-00159" class="html-bibr">186</a>]. Copyright 2018 RSC publishing.</p>
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<p>Schematic illustration of aptamer-functionalized carbon and liposome nanomaterials. (<b>a</b>,<b>b</b>) are aptamer-decorated versatile carbon and liposome nanomaterials, respectively.</p>
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26 pages, 24241 KiB  
Article
Altered White Matter and microRNA Expression in a Murine Model Related to Williams Syndrome Suggests That miR-34b/c Affects Brain Development via Ptpru and Dcx Modulation
by Meitar Grad, Ariel Nir, Gilad Levy, Sari Schokoroy Trangle, Guy Shapira, Noam Shomron, Yaniv Assaf and Boaz Barak
Cells 2022, 11(1), 158; https://doi.org/10.3390/cells11010158 - 4 Jan 2022
Cited by 10 | Viewed by 4291
Abstract
Williams syndrome (WS) is a multisystem neurodevelopmental disorder caused by a de novo hemizygous deletion of ~26 genes from chromosome 7q11.23, among them the general transcription factor II-I (GTF2I). By studying a novel murine model for the hypersociability phenotype associated with [...] Read more.
Williams syndrome (WS) is a multisystem neurodevelopmental disorder caused by a de novo hemizygous deletion of ~26 genes from chromosome 7q11.23, among them the general transcription factor II-I (GTF2I). By studying a novel murine model for the hypersociability phenotype associated with WS, we previously revealed surprising aberrations in myelination and cell differentiation properties in the cortices of mutant mice compared to controls. These mutant mice had selective deletion of Gtf2i in the excitatory neurons of the forebrain. Here, we applied diffusion magnetic resonance imaging and fiber tracking, which showed a reduction in the number of streamlines in limbic outputs such as the fimbria/fornix fibers and the stria terminalis, as well as the corpus callosum of these mutant mice compared to controls. Furthermore, we utilized next-generation sequencing (NGS) analysis of cortical small RNAs’ expression (RNA-Seq) levels to identify altered expression of microRNAs (miRNAs), including two from the miR-34 cluster, known to be involved in prominent processes in the developing nervous system. Luciferase reporter assay confirmed the direct binding of miR-34c-5p to the 3’UTR of PTPRU—a gene involved in neural development that was elevated in the cortices of mutant mice relative to controls. Moreover, we found an age-dependent variation in the expression levels of doublecortin (Dcx)—a verified miR-34 target. Thus, we demonstrate the substantial effect a single gene deletion can exert on miRNA regulation and brain structure, and advance our understanding and, hopefully, treatment of WS. Full article
(This article belongs to the Special Issue Pathophysiological Mechanism of Neurodevelopmental Disorders)
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<p>White matter microstructure, tract connectivity, and myelin deficits in the brains of 1-month-old NexKO mice: (<b>A</b>) Significantly decreased number of streamlines in the limbic outputs through the fimbria/fornix fibers and the stria terminalis as well as the corpus callosum of NexKO mice compared to controls. (<b>B</b>) Brain images overlaid with tractography results for diffusion tensor imaging showing fiber tracking results for control (<b>upper row</b>) and NexKO (<b>lower row</b>) P30 mice. (<b>C</b>) Significantly smaller area of the genu of the corpus callosum of NexKO mice compared to controls. (<b>D</b>) Midsagittal brain images from control and NexKO mice, demonstrating the altered anatomical features of the corpus callosum. Western blots of (<b>E</b>) MBP isoforms and (<b>F</b>) Plp1 expression levels in the cortices of P30 controls and NexKO mice. Data are shown as the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01; (<b>A,C</b>) two-tailed <span class="html-italic">t</span>-test. (<b>A,C</b>) <span class="html-italic">n</span> = 16 control; <span class="html-italic">n</span> = 15 NexKO.</p>
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<p>Whole-cortex small RNA sequencing analysis of P30 NexKO mice. Small RNA sequencing analysis of total RNA extracted from the cortices of P30 NexKO mice compared to controls revealed altered miRNA expression. (<b>A</b>) Volcano plot representation of differentially expressed miRNAs. Data are shown as the log2 fold change in counts in NexKO mice compared to controls. (<b>B</b>–<b>H</b>) Seven downregulated and (<b>I</b>) one upregulated miRNA in the cortices of NexKO mice compared to controls. Data are shown as medians ± quartiles. <span class="html-italic">n</span> = 3 control; <span class="html-italic">n</span> = 2 NexKO. (<b>J</b>) Gene Ontology analysis of verified targets of the murine miR-34 cluster, presenting biological pathways significantly associated with verified targets of the miR-34 cluster; among them are pathways associated with axonogenesis, forebrain development, gliogenesis, and developmental growth.</p>
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<p>miR-34c-5p directly regulates <span class="html-italic">PTPRU</span> mRNA: (<b>A</b>) Significantly increased expression levels of <span class="html-italic">Ptpru</span> mRNA in the cortices of P30 NexKO mice compared to controls. (<b>B</b>) RT-qPCR validation of miR-34c-5p overexpression 72 h post-transfection of hsa-pre-miR-34c in the SH-SY5Y cell line, compared to controls. (<b>C</b>) Reduced levels of <span class="html-italic">PTPRU</span> mRNA 72 h post-transfection of hsa-pre-miR-34c in SH-SY5Y cells, compared to controls. (<b>D</b>) Sequences of the mature hsa-miR-34c-5p and the Renilla/firefly luciferase psiCHECK2 constructs (WT and MUT) under the regulation of <span class="html-italic">PTPRU</span> 3’UTR around the hsa-miR-34 binding site; miR-mRNA binding sites are shown in bold; mutated nucleotides are in red. (<b>E</b>) Significantly higher luciferase activity levels of the mutated <span class="html-italic">PTPRU</span> 3’UTR luciferase construct 72 h post-transfection of hsa-pre-miR-34c in HEK-293T cells, compared to the activity levels of the WT luciferase construct. Data are shown as the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, # <span class="html-italic">p</span> = 0.08; (<b>A</b>–<b>C</b>) two-tailed <span class="html-italic">t</span>-test (<b>B</b>,<b>C</b>) with Welch’s correction; (<b>E</b>) one-tailed <span class="html-italic">t</span>-test. (<b>A</b>) <span class="html-italic">n</span> = 10 per group; (<b>B</b>,<b>C</b>,<b>E</b>) <span class="html-italic">n</span> = 6 per group. OE: overexpression.</p>
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<p>miR-34c-5p does not directly regulate <span class="html-italic">RHEBL1</span> mRNA: (<b>A</b>) Significantly increased expression levels of <span class="html-italic">Rheb1</span> mRNA in the cortices of P30 NexKO mice compared to controls. (<b>B</b>) Reduced levels of <span class="html-italic">RHEBL1</span> mRNA 72 h post-transfection of hsa-pre-miR-34c in SH-SY5Y cells, compared to controls. (<b>C</b>) Sequences of the mature hsa-miR-34c-5p and the Renilla/firefly luciferase psiCHECK2 constructs (WT and MUT) under the regulation of <span class="html-italic">RHEBL1</span> 3’UTR, around the hsa-miR-34 binding site; miR-mRNA binding sites are shown in bold; mutated nucleotides are in red. (<b>D</b>) Reduced luciferase activity levels of the mutated <span class="html-italic">RHEBL1</span> 3’UTR luciferase construct, 72 h post-transfection of hsa-pre-miR-34c in HEK-293T cells, compared to the activity levels of the WT luciferase construct. Data are shown as the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, # <span class="html-italic">p</span> = 0.08; (<b>A</b>,<b>B</b>) two-tailed <span class="html-italic">t</span>-test (<b>B</b>) with Welch’s correction; (<b>D</b>) one-tailed <span class="html-italic">t</span>-test. (<b>A</b>) <span class="html-italic">n</span> = 10 control; <span class="html-italic">n</span> = 9 NexKO; (<b>B</b>) <span class="html-italic">n</span> = 6 per group; (<b>D</b>) <span class="html-italic">n</span> = 4 per group. OE: overexpression.</p>
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<p>Alterations in Dcx expression levels in the cortices of NexKO embryos, neonates, and young adults compared to age-matched controls: (<b>A</b>) Dcx expression in the cortices of E15.5 embryos demonstrate a higher percentage of neuronal layers in the cortices of NexKO embryos compared to controls, as measured by the higher ratio of the thickness of Dcx-positive neuronal layers over the total cortical thickness. (<b>B</b>) Representative confocal images showing staining of cell nuclei (DAPI, in blue) and Dcx (green) in the cortices of E15.5 control and NexKO embryos. (<b>C</b>) Comparable <span class="html-italic">Dcx</span> mRNA levels in P1 NexKO mice compared to controls. (<b>D</b>) A trend towards an increase in miR-34c-5p levels in the cortices of P1 NexKO mice compared to controls. (<b>E</b>) Significantly decreased expression levels of <span class="html-italic">Dcx</span> mRNA in the cortices of P30 NexKO mice compared to controls. Data are shown as the mean ± SEM. * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.005, # <span class="html-italic">p</span> = 0.08 (<b>A</b>) two-tailed Mann–Whitney test, (<b>C</b>–<b>E</b>) two-tailed <span class="html-italic">t</span>-test with Welch’s correction. (<b>A</b>) <span class="html-italic">n</span> = 4 per group; (<b>C</b>) <span class="html-italic">n</span> = 12 control; <span class="html-italic">n</span> = 11 NexKO; (<b>D</b>) <span class="html-italic">n</span> = 11 per group; (<b>E</b>) <span class="html-italic">n</span> = 9 per group. ns: non-significant.</p>
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26 pages, 6589 KiB  
Article
Recognition and Chaperoning by Pex19, Followed by Trafficking and Membrane Insertion of the Peroxisome Proliferation Protein, Pex11
by Katarzyna M. Zientara-Rytter, Shanmuga S. Mahalingam, Jean-Claude Farré, Krypton Carolino and Suresh Subramani
Cells 2022, 11(1), 157; https://doi.org/10.3390/cells11010157 - 4 Jan 2022
Cited by 5 | Viewed by 3299
Abstract
Pex11, an abundant peroxisomal membrane protein (PMP), is required for division of peroxisomes and is robustly imported to peroxisomal membranes. We present a comprehensive analysis of how the Pichia pastoris Pex11 is recognized and chaperoned by Pex19, targeted to peroxisome membranes and inserted [...] Read more.
Pex11, an abundant peroxisomal membrane protein (PMP), is required for division of peroxisomes and is robustly imported to peroxisomal membranes. We present a comprehensive analysis of how the Pichia pastoris Pex11 is recognized and chaperoned by Pex19, targeted to peroxisome membranes and inserted therein. We demonstrate that Pex11 contains one Pex19-binding site (Pex19-BS) that is required for Pex11 insertion into peroxisomal membranes by Pex19, but is non-essential for peroxisomal trafficking. We provide extensive mutational analyses regarding the recognition of Pex19-BS in Pex11 by Pex19. Pex11 also has a second, Pex19-independent membrane peroxisome-targeting signal (mPTS) that is preserved among Pex11-family proteins and anchors the human HsPex11γ to the outer leaflet of the peroxisomal membrane. Thus, unlike most PMPs, Pex11 can use two mechanisms of transport to peroxisomes, where only one of them depends on its direct interaction with Pex19, but the other does not. However, Pex19 is necessary for membrane insertion of Pex11. We show that Pex11 can self-interact, using both homo- and/or heterotypic interactions involving its N-terminal helical domains. We demonstrate that Pex19 acts as a chaperone by interacting with the Pex19-BS in Pex11, thereby protecting Pex11 from spontaneous oligomerization that would otherwise cause its aggregation and subsequent degradation. Full article
(This article belongs to the Special Issue Peroxisome Biogenesis and Protein Targeting Mechanisms)
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<p>Graphical representation of the Pex11 protein in yeast and humans. Graphical representation of the domain/motif architecture organization for each Pex11 protein in yeast <span class="html-italic">S. cerevisiae</span>, <span class="html-italic">P. pastoris</span> and in humans. Proteins are drawn to scale with the amino acids (aa) number indicated at the bottom. Most, but not all (e.g., HsPex11γ), Pex11-family proteins have four putative amphipathic helices, whose coordinates in PpPex11 are as follows—H1 (aa14-19), H2 (aa25-45), H3 (aa55-86), and H4 (aa203-218), shown as yellow, orange, green, and grey rectangles, respectively) and two hydrophobic domains (HD1 and HD2, blue rectangles).</p>
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<p>PpPex11 contains one Pex19-binding site (Pex19-BS) near its N-terminal end. Pex11 interacts with Pex19 via its Pex19-BS. (<b>A</b>) Y2H screen to determine the location of the Pex19-BS within PpPex11. Two truncated forms of PpPex11 were subjected to site-directed mutagenesis within H2 region of Pex11 and fused with the BD domain of GAL4 to test their abilities to interact with AD-Pex19. Schematic representation of Pex11 mutants used in this study is shown and the H2 helix (aa25-45), within which the Pex19-BS was mapped for other yeast Pex11s, is highlighted in orange. 3-AT, 3-amino-1,2,4-triazole; AD, activation domain; BD, DNA binding domain; -LW, yeast synthetic drop-out medium without leucine and tryptophan serving as a positive control to show equal plating of cells; -LWH, yeast synthetic drop-out medium without leucine, tryptophan, and histidine. (<b>B</b>) Precise mapping of the Pex19-BS. Based on the location of the Pex19-BS in the H2 helix of Pex11, 14-mer (aa27-40) and 16-mer (aa30-45) peptides, with a 3aa shift between them, were synthesized, spotted onto a nitrocellulose membrane, and subjected to the in vitro Pex19 binding assay. Peptides and proper positive (C<sup>+</sup>) and negative (C<sup>−</sup>) controls were spotted at two concentrations (20 nmol and 5 nmol, respectively) and tested for interaction with GST-PpPex19. Bound protein was detected immunologically with polyclonal anti-Pex19 or anti-GST antibodies. As a control, free GST and monoclonal anti-GST antibodies were used. Sequence alignment of N-terminal regions of Pex11 proteins from various species, showing conservation of specific residues within the H2 helix, is included. Residues in H2 helix are colored by Clustal X [<a href="#B38-cells-11-00157" class="html-bibr">38</a>] based on their physico-chemical properties: hydrophilic, charged: D, E (magenta), K, R, H (red); hydrophilic, neutral: S, T, Q, N (green); hydrophobic: A, V, L, I, M, W, F (blue); P (yellow); G (orange; and other aromatic Y and H (cyan). Abbreviations and accessions numbers used in sequence alignments: Pp—<span class="html-italic">Pichia pastoris</span>, CAY69135; Hp—<span class="html-italic">Hansenula polymorpha</span>, DQ645582; Sc—<span class="html-italic">Saccharomyces cerevisiae</span>, CAA99168; Ca—<span class="html-italic">Candida albicans</span>, EAK92906; Yl—<span class="html-italic">Yarrowia lipolytica</span>, CAG81724. (<b>C</b>) The Pex11 (45-249) deletion mutant does not bind Pex19 in vitro. Binding studies revealed that removal of N-terminal end of Pex11 (aa1-44) is sufficient to inhibit Pex11–Pex19 binding in vitro. Only the mutant, Pex11 (45-249), was deficient in Pex19 binding, whereas the full-length and other deletion mutants, Pex11 (1-180), were still pulled down with GST-Pex19. Free GST protein was used as a control. There was equivalent loading in the input and bound lanes. Proteins were detected by anti-GFP, anti-GST, and anti-Pex19 antibodies.</p>
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<p>The Pex19-BS of Pex11 binds to Pex19 via its hydrophobic surface and flanking positively-charged residues. Identification of H2 mutants of Pex11 deficient in Pex19 binding by dot-blot analysis. (<b>A</b>) The H2 peptides generated, including one harboring the HsPex11β H2 sequence but lacking Pex19-binding properties, as well as the PpPex11 H2 WT or mutant sequences (sequence details are indicated and mutated residues are marked in red) are shown on left. Dot-blot analysis (shown on right) was done as described in <a href="#cells-11-00157-f002" class="html-fig">Figure 2</a>B. Peptides were spotted on a nitrocellulose membrane at two concentrations (20 nmol and 5 nmol) and tested for interaction with GST-PpPex19. The top panel shows spotted peptides stained with Ponceau S prior to GST-PpPex19 addition. Bound protein was detected immunologically with polyclonal anti-Pex19 antibodies in the middle (short exposure) and bottom (long exposure) panels. (<b>B</b>) Helical-wheel diagrams of HsPex11β and PpPex11 H2 variants using HeliQuest. Positively-charged residues are shown in blue, negatively-charged residues in red, and hydrophobic residues in yellow. In addition, Ser and Thr are shown in purple, Gly and Ala in gray, Asn and Gln in pink, and His in sky blue. The arrows represent the helical hydrophobic moment. (<b>C</b>) CD spectra of the PpPex11 H2 wild-type and mutant peptides. The spectrum shows that H2 and its mutant variant H2 L8A, Y10A are unstructured in phosphate buffer, but the addition of 30% of TFE induces changes in the spectrum, typical for α-helical structures.</p>
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<p>Pex11 is chaperoned by Pex19, which determines its stability via direct interaction with the Pex19-BS of Pex11. (<b>A</b>). Western blot analyses of GFP-Pex11 and other protein levels in WT and <span class="html-italic">pex19</span>Δ strains after methanol induction. WT and <span class="html-italic">pex19</span>Δ cells expressing Pex11-2HA from its endogenous <span class="html-italic">PEX11</span> promoter, or the constitutive <span class="html-italic">GAPDH</span> promoter, were grown in methanol medium, and 2 OD cells were collected at the indicated time points. GFP-Pex11 levels were visualized by anti-GFP antibodies. Pex3 and Pex19 were detected using custom antibodies, and F1β was used as loading control. (<b>B</b>). Western blot analysis of Pex11-2HA and other protein levels at various time points in peroxisome-deficient strains after methanol induction. WT, <span class="html-italic">pex19</span>Δ, and <span class="html-italic">pex3</span>Δ cells in an <span class="html-italic">atg30</span>Δ (pexophagy-deficient) background expressing Pex11-2HA from its endogenous promoter were grown in methanol medium, and 2 OD cells were collected at indicated time points. Endogenous PMPs were detected with indicated antibodies, and F1β was used as loading control. SE—short exposure and LE—long exposure. (<b>C</b>). Removal of Pex19-BS destabilizes Pex11. Western blot analysis of levels of truncated forms of GFP-Pex11 at various time points in atg30Δ cells after methanol induction. GFP-Pex11, GFP-Pex11 (45-249), GFP-Pex11 (1-223) (referred to collectively as GFP-Pex11 (X)), and free GFP were expressed from the PEX11 promoter in the atg30Δ strain in methanol medium, and 2 OD cells were collected at indicated time points. Proteins were identified using respective antibodies. SE, short exposure and LE, long exposure.</p>
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<p>N-terminal amphipathic helices H2 and H3 enable Pex11 dimerization. (<b>A</b>). Involvement of N-terminal helices of Pex11 in its self-interaction with Y2H. Full-length Pex11 and its truncated forms, as well as their mutated variants, were fused to either BD or AD domains of GAL4. As negative controls, empty pGBKT7 and pGADT7 were used. Different combinations of these vectors were transformed into the yeast strain Y2H Gold for mapping the regions involved in Pex11 dimerization. Schematic representation of Pex11 truncated and mutant forms used in this study. The H2 helix (aa25-45) containing the Pex19-BS is highlighted in orange, and the H3 (aa55-86) helix, known for lipid binding and dimerization properties, is in green. Sequence alignment of the N-terminal part of Pex11 proteins from various species, showing conservation of specific residues within the H3 helix, whose residues are colored as in <a href="#cells-11-00157-f001" class="html-fig">Figure 1</a>. Abbreviations and accessions numbers used in sequence alignments: Pp—<span class="html-italic">Pichia pastoris</span>, CAY69135; Hp—<span class="html-italic">Hansenula polymorpha</span>, DQ645582; Sc—<span class="html-italic">Saccharomyces cerevisiae</span>, CAA99168; Ca—<span class="html-italic">Candida albicans</span>, EAK92906; Yl—<span class="html-italic">Yarrowia lipolytica</span>, CAG81724. 3-AT, 3-amino-1,2,4-triazole; AD, activation domain; BD, DNA binding domain. (<b>B</b>). Pex11 preferentially dimerizes via its H2 helix. Pull-down assays using biotinylated peptides corresponding to the H2, H3, or H4 helices (sequences indicated in the figure) bound to streptavidin-coated resin as a bait and His<sub>6</sub>-GFP-Pex11 as a prey. Resins were washed, and proteins were eluted and analyzed by SDS-PAGE. His<sub>6</sub>-GFP-Pex11 was detected by immunoblotting with anti-GFP antibody, and the presence of peptides on the resin was verified by HRP-conjugated streptavidin. Shown is 25% of the input. SE, short exposure; ME, moderate exposure. Quantification of the pull-down assay is shown on the right, with the averages and standard deviations based on three independent sets of experiments. Western blot signals were quantified using the program ImageJ. (<b>C</b>). Same as panel B, except full-length His<sub>6</sub>-GFP-Pex11 or truncated form His<sub>6</sub>-GFP-Pex11 (45-249) was used as a prey. Quantification of the Western blots from three independent experiments is shown on the right with standard deviations. (<b>D</b>). Graphical representation of homotypic (H2-H2 or H3-H3) and heterotypic (H2-H3) interactions that drive Pex11 dimerization. The thickness of the arrows reflects the strength of the interactions detected by in vitro pull-down assays.</p>
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<p>Pex19 binding and Pex11 dimerization to the H2 helix are mutually exclusive. (<b>A</b>). Dimerization of Pex11 via its H2 helix involves the same surface as that required for Pex19 binding. Identification of H2 mutants deficient in binding to Pex11 by in vitro pull-down. Biotinylated H2 peptides harboring either the HsPex11β H2 sequence (negative control) or Pex11 H2 WT (positive control) or mutant sequences (see <a href="#cells-11-00157-f002" class="html-fig">Figure 2</a> for sequence details) were bound to streptavidin-coated resin prior to the addition of a 4-fold molar excess of His<sub>6</sub>-GFP-Pex11. Levels of captured His<sub>6</sub>-GFP-Pex11 were examined on SDS-PAGE and detected by immunoblotting with anti-GFP antibody. The presence of peptides on the resin was verified by HRP-conjugated streptavidin. Input was diluted 1:4 or 1:6 prior to loading. SE, short exposure; ME, moderate exposure. (<b>B</b>). Pex19 competes with Pex11 for the access to H2. Pull-down competition assays of the interaction between the H2 or H3 peptide and His<sub>6</sub>-GFP-Pex11 or His<sub>6</sub>-GFP-Pex11 (45-249) in competition with increasing amounts of the GST-Pex19 or GST alone used as a control are shown. GST-Pex19 or GST alone were added to the resin with bound H2 or H3 simultaneously with His<sub>6</sub>-GFP-Pex11 or His<sub>6</sub>-GFP-Pex11 (45-249). Resins were washed, and proteins were eluted and analyzed by SDS-PAGE. His<sub>6</sub>-GFP-Pex11s, GST-Pex19, and free GST were detected with respective antibodies, and presence of peptides on the resin was verified by HRP-conjugated streptavidin. A graphical illustration of possible interactions for each combination is included.</p>
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<p>Pex11 import to peroxisomal membranes, but not its trafficking to peroxisomes, requires Pex19 binding. (<b>A</b>). Both full-length (GFP-Pex11) and truncated (GFP-Pex11 (45-249)) fusion proteins, respectively, colocalize with the peroxisomal membrane marker, mPTS-RFP. The <span class="html-italic">pex11</span>Δ cells containing mPTS-RFP and expressing GFP-tagged Pex11 variants from the endogenous <span class="html-italic">PEX11</span> promoter were grown in methanol medium for 5 h (upper panel) or 16 h (o/n-lower panel) for fusion protein induction, prior to observation by fluorescence microscopy. Schematic representation of Pex11 forms used for live-cell imaging is shown below microscopy pictures. Positions of known and predicted modules are highlighted: Pex19-BS (orange), amphipathic helix (green), and hydrophobic regions (HD1 and HD2) predicted to be buried in lipid bilayers (blue). (<b>B</b>). Full-length Pex11, but not the Pex11 (45-249) truncated form, is an integral membrane protein. Western blot of membrane protein extraction assay in which the organelle membrane fraction from <span class="html-italic">pex11</span>Δ strains expressing Pex11-2HA, GFP-Pex11, and GFP-Pex11 (45-249) were resuspended in four different buffers for peripheral membrane protein extraction (Tris buffer pH 8, 2 mM Urea in Tris buffer pH 8, 0.1 M Na<sub>2</sub>CO<sub>3</sub> pH 11.5, and Tris buffer pH 8 with Triton X-100) for 30 min at room temperature and fractionated by ultracentrifugation to obtain supernatant (S) and pellet (P) fractions. Proteins were visualized with anti-GFP, anti-HA, and Pex3 antibodies. Pex3 protein was used as a reference integral membrane protein. Note that for GFP-Pex11, the arrowhead indicates proper protein size, and asterisk is probably a truncated form. (<b>C</b>). Graphical representation of results. Model (A) presents Pex11 trafficking and incorporation into peroxisomal membranes with the assistance of Pex19 (and Pex3). Model (B) presents Pex11 (45-249) trafficking to, but not its insertion, into the peroxisome membrane, due to the lack of Pex19-BS. It is unclear if Pex11 (45-249) requires interaction with another protein (marked as “?”) for its targeting to peroxisomes. Bar = 5 μm.</p>
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<p>Pex11 has a Pex19-independent mPTS that is distinct from the Pex19-BS. Fluorescence microscopy images of <span class="html-italic">pex11</span>Δ cells expressing full-length and truncated GFP-Pex11 fusion proteins and mPTS-RFP for peroxisome visualization after 5 h in methanol medium. Bar = 5μm. A schematic representation of Pex11 truncated forms used in this study is shown below the micrographs. Positions of known and predicted modules are highlighted as shown in <a href="#cells-11-00157-f005" class="html-fig">Figure 5</a>: Pex19-BS (orange); amphipathic helix (green); and hydrophobic regions, HD1, and HD2, predicted to be buried in lipid bilayers (blue).</p>
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<p>Amphipathic helix H4 of Pex11 has a Pex19-independent mPTS. (<b>A</b>). Fluorescence microscopy images of <span class="html-italic">pex11</span>Δ cells expressing full-length and truncated GFP-Pex11 fusion proteins and mPTS-RFP for peroxisome visualization after 16 h in methanol medium. A schematic representation of Pex11 truncated forms used in this study is shown below the micrographs. Positions of known and predicted modules are highlighted similarly as in <a href="#cells-11-00157-f005" class="html-fig">Figure 5</a>. Bar = 5 μm. (<b>B</b>). The H4 (aa203-218) region in Pex11 is not recognized by Pex19. Short 14 and 15-mer peptides with three amino acid shifts spanning the identified mPTS with its flanking N- and C-terminal residues were synthesized and subjected to the Pex19 in vitro binding assay. Dot-blot analysis was done as described in <a href="#cells-11-00157-f002" class="html-fig">Figure 2</a>B. Peptides and proper controls (including peptides described in <a href="#cells-11-00157-f002" class="html-fig">Figure 2</a>B) were spotted on a nitrocellulose membrane at two concentrations (20 nmol and 5 nmol) and tested for interaction with GST-Pex19. Bound protein was detected immunologically with polyclonal anti-Pex19 antibodies. Sequence alignment of regions from various Pex11s corresponding to identified mPTS in Pex11 is shown at the bottom. Residues were colored by Clustal X [<a href="#B38-cells-11-00157" class="html-bibr">38</a>], based on their physico-chemical properties as in <a href="#cells-11-00157-f002" class="html-fig">Figure 2</a>B. The position of the amphipathic helix H4 in Pex11 is marked by a red arrow, and its helical wheel plot generated using HeliQuest is shown on the right. The black arrow in the plot points to the hydrophobic face, and its length corresponds to the hydrophobic moment. (<b>C</b>). The secondary structures of the H3 (used as reference) and H4 peptides were analysed by CD spectroscopy. The spectrum shows that, like the H3 peptide, H4 is unstructured in phosphate buffer, but α-helical in 30% TFE. Abbreviations and accession numbers used in sequence alignments: Pp—<span class="html-italic">Pichia pastoris</span>, CAY69135; Hp—<span class="html-italic">Hansenula polymorpha</span>, DQ645582; Sc—<span class="html-italic">Saccharomyces cerevisae</span>, CAA99168; Ca—<span class="html-italic">Candida albicans</span>, EAK92906; Yl—<span class="html-italic">Yarrowia lipolytica</span>, CAG81724.</p>
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18 pages, 2603 KiB  
Article
Pathologic Proteolytic Processing of N-Cadherin as a Marker of Human Fibrotic Disease
by Paul Durham Ferrell, Kristianne Michelle Oristian, Everett Cockrell and Salvatore Vincent Pizzo
Cells 2022, 11(1), 156; https://doi.org/10.3390/cells11010156 - 4 Jan 2022
Cited by 7 | Viewed by 3732
Abstract
Prior research has implicated the involvement of cell adhesion molecule N-cadherin in tissue fibrosis and remodeling. We hypothesize that anomalies in N-cadherin protein processing are involved in pathological fibrosis. Diseased tissues associated with fibrosis of the heart, lung, and liver were probed for [...] Read more.
Prior research has implicated the involvement of cell adhesion molecule N-cadherin in tissue fibrosis and remodeling. We hypothesize that anomalies in N-cadherin protein processing are involved in pathological fibrosis. Diseased tissues associated with fibrosis of the heart, lung, and liver were probed for the precursor form of N-cadherin, pro-N-cadherin (PNC), by immunohistochemistry and compared to healthy tissues. Myofibroblast cell lines were analyzed for cell surface pro-N-cadherin by flow cytometry and immunofluorescent microscopy. Soluble PNC products were immunoprecipitated from patient plasmas and an enzyme-linked immunoassay was developed for quantification. All fibrotic tissues examined show aberrant PNC localization. Cell surface PNC is expressed in myofibroblast cell lines isolated from cardiomyopathy and idiopathic pulmonary fibrosis but not on myofibroblasts isolated from healthy tissues. PNC is elevated in the plasma of patients with cardiomyopathy (p ≤ 0.0001), idiopathic pulmonary fibrosis (p ≤ 0.05), and nonalcoholic fatty liver disease with cirrhosis (p ≤ 0.05). Finally, we have humanized a murine antibody and demonstrate that it significantly inhibits migration of PNC expressing myofibroblasts. Collectively, the aberrant localization of PNC is observed in all fibrotic tissues examined in our study and our data suggest a role for cell surface PNC in the pathogenesis of fibrosis. Full article
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<p>PNC is aberrantly expressed in fibrotic heart, lung, and liver tissues. (<b>A</b>) Representative images of stained tissues from explanted failed human hearts (<span class="html-italic">n</span> = 20, ischemic and non-ischemic etiology), lungs (<span class="html-italic">n</span> = 10, IPF etiology) and livers (<span class="html-italic">n</span> = 40, NAFLD-cirrhosis etiology) show positive expression and aberrant localization of PNC (Brown stain). Corresponding representative images of stained normal human heart (<span class="html-italic">n</span> = 24), lung (<span class="html-italic">n</span> = 18), and liver (<span class="html-italic">n</span> = 32) show lack of aberrantly expressed PNC at the tissue level. Perinuclear staining, consistent with normal N-cadherin processing can be seen in the healthy cardiac tissue. Scale bar = 100 µm. (<b>B</b>) Graphical representation of human samples analyzed in this study. Each column represents a single human sample, annotated by color to indicate the organ system of relevance to this study (top row), whether the patient had fibrosis (second row), the reported sex of the patient (third row), the age of the patient (fourth row) and the method by which the sample was analyzed in this study (fourth row). In cases where demographic data is unknown, unavailable, or unreported, a white bar with black hatch is shown. <span class="html-italic">n</span> = 257 total samples analyzed.</p>
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<p>PNC is localized to the cell surface of myofibroblasts. Myofibroblasts from heart and lung tissues were stained and analyzed by flow cytometry using m-α-PNC mAb 10A10, excluding debris and dead cells via gating and 7AAD exclusion using Flowjo software. Myofibroblasts from fibrosis origins stain positive for cell surface PNC: (<b>A</b>) CF-DCM, cardiac myofibroblasts from dilated cardiomyopathy; Chi-Squared = 177.5; SE Dymax % Positive = 48.0. LL97A, IPF; Chi-Squared = 93.4; SE Dymax % Positive = 54.8, and LL29, IPF; Chi-Squared = 113.5; SE Dymax % Positive = 51.0. PNC was not detected on the surface of primary normal human cardiac myofibroblasts from healthy donor, NHCF; Chi-Squared = 3.47; SE Dymax % Positive = 8.54, primary normal human lung myofibroblasts from healthy donor, NHLF; Chi-Squared = 0; SE Dymax % Positive = 0, or immortalized CCD-16Lu lung myofibroblasts from healthy donor; Chi-Squared = 0; SE Dymax % Positive = 0. Mouse IgG1 isotype control (blue shaded) was compared to m-α-PNC mAb (unshaded). Results are representative of 3 independent experiments, <span class="html-italic">n</span> = 3. For all flow cytometry experiments, Chi-squared ≥ 4 is statistically significant. (<b>B</b>) Cell surface proteins were isolated from myofibroblasts and immunoblotted for N-cadherin, PNC, and Na,k-ATPase α-1 (ATP1A1) cell surface compartment loading control. PNC and N-Cadherin lysates were normalized to the ATP1A1 cell surface loading control for each sample and are reported as a relative value below each band.</p>
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<p>PNC is localized to cellular protrusions. Fixed, unpermeabilized myofibroblasts from fibrotic and healthy tissues were immunostained for m-α-PNC mAb 10A10 (red) and DAPI (blue). PNC is localized to cellular protrusions on pathological myofibroblasts DCM-CF, LL29, and LL97A (arrows). PNC is not expressed on the surface of NHCF, NHLF, or CCD-16Lu isolated from healthy donor.</p>
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<p>Feasibility and development of a PNC ELISA. (<b>A</b>) Soluble PNC product was immunoprecipitated from LL29 conditioned media and patient plasma from pooled healthy donors, IPF patients, NAFLD-Cirrhosis patients and cardiomyopathy patients using m-α-PNC mAb 10A10 compared to mouse IgG1 isotype control (mIgG1) and immunoblotted. (<b>B</b>) Recombinant prodomain analyte was serially diluted in duplicate starting at 100 ng/mL in standard diluent and measured by ELISA to determine the range of the standard. (<b>C</b>) Linearity of endogenous analyte was measured. Plasma from patients with heart failure was serially diluted 1:3, 1:7, 1:15, 1:31 in standard diluent and sPNC was measured by ELISA in duplicate. All linear regression r<sup>2</sup> values were calculated to be within acceptable range (r<sup>2</sup> ≥ 0.99). (<b>D</b>,<b>E</b>) Healthy donor plasma was diluted in standard diluent to indicated dilutions (1:1, 1:3, 1:7, 1:15) then spiked with recombinant prodomain analyte at 10 ng/mL (<b>D</b>) and 5 ng/mL (<b>E</b>) and analyzed by ELISA. Recovery of analyte was quantified and compared to back calculation of the standard. All dilutions were within the consensus range of 20 percent ± the standard back calculations at concentrations 10 ng/mL and 5 ng/mL. (<b>F</b>) Plasma was assayed for sPNC from healthy controls (<span class="html-italic">n</span> = 26), patients with IPF (<span class="html-italic">n</span> = 9), NAFLD with cirrhosis (<span class="html-italic">n</span> = 12), and cardiomyopathy (<span class="html-italic">n</span> = 9). Ordinary one-way ANOVA analysis with Dunnett’s multiple comparisons test was performed to determine significance (* <span class="html-italic">p</span> ≤ 0.05, **** <span class="html-italic">p</span> ≤ 0.0001).</p>
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<p>FN1 is a potential PNC binding partner. (<b>A</b>) Medium binding ELISA plates were coated with human fibronectin, collagen type I, or collagen type III, then blocked and incubated with his-tagged recombinant N-cadherin prodomain. After washing unbound prodomain, prodomain binding to the immobilized substrate was measured using a biotinylated his-tag specific monoclonal antibody and streptavidin-HRP for detection. Assay was performed in quadruplicate and is representative of at least 3 independent experiments. (<b>B</b>) Representative image of a cardiac myofibroblast isolated from failed cardiac explant tissue showing colocalization of PNC and FN1 immunostained for PNC (red), FN1 (green) and DAPI (blue). Yellow indicates PNC/FN1 colocalization (Merge). (<b>C</b>) Medium binding ELISA plates were coated with fibronectin, blocked, then incubated with either recombinant prodomain of N-cadherin or prodomain in combination with mouse IgG1 isotype control, human IgG4 isotype control, m-α-PNC mAb 10A10 or h-α-PNC mAb HC5LC4. Bound recombinant prodomain was detected using anti-his-tag monoclonal antibody in technical duplicates and representative of at least 3 independent experiments (<span class="html-italic">n</span> = 3). Ordinary one-way ANOVA analysis with Tukey’s multiple comparisons test was performed to determine significance (* <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01).</p>
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<p>Cell surface PNC has a role in myofibroblast migration. Transwell permeable supports with a 6.5 mm polycarbonate membrane and 8 µm pores were coated with human fibronectin and used to separate the upper and lower chambers of a 24-well cell culture plate to measure migration of cells across the membrane (<span class="html-italic">n</span> = 4). Pathological myofibroblast migration is significantly reduced by h-α-PNC mAb (HC5LC4) and recombinant prodomain of N-cadherin (rPro) after 5 h; (<b>A</b>) DCM-CF, dilated cardiomyopathy myofibroblasts (<b>C</b>) LL29, IPF myofibroblasts. No significant effect on myofibroblasts isolated from healthy tissues was observed; (<b>D</b>) immortalized CCD-16Lu lung myofibroblasts from healthy donor (<b>B</b>) NHCF, normal human cardiac myofibroblasts. Two tailed T-test assuming Gaussian distribution analysis was performed to determine significance. (* <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01).</p>
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<p>AUROC analysis of plasma PNC for specificity and sensitivity. Normal donor samples (<span class="html-italic">n</span>= 26) were compared to samples from cardiomyopathy (Red, <span class="html-italic">n</span> = 9), NAFLD-Cirrhosis (Green, <span class="html-italic">n</span> = 12) and IPF (Yellow, <span class="html-italic">n</span> = 9) patients. To determine tissue-agnostic AUROC, all fibrotic samples were combined (Black, <span class="html-italic">n</span>= 30) and compared to normal donor samples. AUROC = area under the receiver operating characteristics curve.</p>
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25 pages, 5004 KiB  
Article
Extracellular Vesicles Derived from Bone Marrow in an Early Stage of Ionizing Radiation Damage Are Able to Induce Bystander Responses in the Bone Marrow
by Dávid Kis, Ilona Barbara Csordás, Eszter Persa, Bálint Jezsó, Rita Hargitai, Tünde Szatmári, Nikolett Sándor, Enikő Kis, Katalin Balázs, Géza Sáfrány and Katalin Lumniczky
Cells 2022, 11(1), 155; https://doi.org/10.3390/cells11010155 - 4 Jan 2022
Cited by 7 | Viewed by 3067
Abstract
Ionizing radiation (IR)-induced bystander effects contribute to biological responses to radiation, and extracellular vesicles (EVs) play important roles in mediating these effects. In this study we investigated the role of bone marrow (BM)-derived EVs in the bystander transfer of radiation damage. Mice were [...] Read more.
Ionizing radiation (IR)-induced bystander effects contribute to biological responses to radiation, and extracellular vesicles (EVs) play important roles in mediating these effects. In this study we investigated the role of bone marrow (BM)-derived EVs in the bystander transfer of radiation damage. Mice were irradiated with 0.1Gy, 0.25Gy and 2Gy, EVs were extracted from the BM supernatant 24 h or 3 months after irradiation and injected into bystander mice. Acute effects on directly irradiated or EV-treated mice were investigated after 4 and 24 h, while late effects were investigated 3 months after treatment. The acute effects of EVs on the hematopoietic stem and progenitor cell pools were similar to direct irradiation effects and persisted for up to 3 months, with the hematopoietic stem cells showing the strongest bystander responses. EVs isolated 3 months after irradiation elicited no bystander responses. The level of seven microRNAs (miR-33a-3p, miR-140-3p, miR-152-3p, miR-199a-5p, miR-200c-5p, miR-375-3p and miR-669o-5p) was altered in the EVs isolated 24 hour but not 3 months after irradiation. They regulated pathways highly relevant for the cellular response to IR, indicating their role in EV-mediated bystander responses. In conclusion, we showed that only EVs from an early stage of radiation damage could transmit IR-induced bystander effects. Full article
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Graphical abstract

Graphical abstract
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<p>Gating Strategy for the Identification of Different Bone Marrow Cell Populations by Flow Cytometry. (<b>A</b>) Lymphoid progenitor cells were identified as CD45 and CD90.2 double positive cells in bone marrow cells. (<b>B</b>) Granulocytes/monocytes were characterized as Gr1 and CD11b double positive cells in bone marrow cells. (<b>C</b>) Hematopoietic stem and progenitor cells were identified as Sca1 and cKit double positive cells in the Lineage negative bone marrow cells. (<b>D</b>) Hematopoietic stem cell subpopulation characterization was done by using the CD34 and CD135 markers in the hematopoietic stem and progenitor cell pool. Long-term hematopoietic stem cells were identified as CD34 and CD135 double negative cells, short-term hematopoietic stem cells were CD34+CD135- cells, multipotent progenitors were characterized as CD34 and CD135 double positive cells. (<b>E</b>) Mesenchymal stem and stromal cells were identified as Sca1 and CD44 double positive cells in the lineage-negative bone marrow cells.</p>
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<p>Characterization of Bone Marrow-Derived Extracellular Vesicles. (<b>A</b>) Representative transmission electron microscopy images of extracellular vesicles isolated from the bone marrow of mice irradiated with the indicated doses of ionizing radiation. (<b>B</b>) Size and concentration of extracellular vesicle suspensions were examined by tunable resistance pulse sensing. Mean values of extracellular vesicle size (<b>B/1</b>) and mean extracellular vesicle particle numbers released by 10<sup>6</sup> bone marrow cells (<b>B/2</b>) are shown with bars representing standard deviations (SD). <span class="html-italic">n</span> = 3, significance tested by Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> * &lt; 0.05. (<b>C</b>) Representative Western blot analysis of whole cell lysates and extracellular vesicles isolated from the bone marrow of mice irradiated with the indicated doses of ionizing radiation. Lane 1: protein ladder, lane 2: whole cell lysate, lane 3: extracellular vesicle sample from unirradiated mice, lane 4-5: extracellular vesicle samples from mice irradiated with 0.1Gy and 2Gy.</p>
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<p>Schematic Presentation of the Workflow of the Study. C57Bl/6 mice were total-body irradiated with different doses (0Gy, 0.1Gy, 0.25Gy and 2Gy) of ionizing radiation. Mice were humanely killed 4 h, 24 h or 3 months later and the bone marrow and spleen were collected. Bone marrow-derived extracellular vesicles were isolated from the bone marrow supernatant of age-matched control and irradiated mice. Bystander effects were monitored in non-irradiated, healthy mice after injecting them with bone marrow-derived extracellular vesicles. Bystander mice were humanely killed 4 h, 24 h or 3 months after extracellular vesicle injection and the same organs were harvested as from the directly irradiated animals. Apoptosis in the bone marrow stem and progenitor cells was measured by TUNEL assay. Bone marrow hematopoietic stem, progenitor and stromal cell subpopulations were characterized phenotypically by flow cytometry. MiRNA expression of BM-EVs was investigated by qRT-PCR.</p>
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<p>Bone Marrow-Derived Extracellular Vesicles from Irradiated Mice Induce Long-Term Hematopoietic Stem Cell Depletion in the Bone Marrow of Bystander Mice. Irradiation, extracellular vesicle treatment and bone marrow cell phenotyping were carried out as described in the Materials and Methods section. Lin-Sca1+cKit+ cells were considered hematopoietic stem cells. (<b>A</b>) Relative changes in hematopoietic stem cell numbers were evaluated 24 h after treatment. Grey bars represent total-body irradiated mice; red bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation; yellow bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 3 months after irradiation. (<b>B</b>) Relative changes in hematopoietic stem cell numbers were evaluated 3 months after treatment. Grey bars represent total-body irradiated mice; blue bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation. Bars represent mean values of relative hematopoietic stem cell numbers, dots show individual values, error bars represent SD. <span class="html-italic">n</span> = 6–11, significance tested by Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> ** &lt; 0.01, <span class="html-italic">p</span> *** &lt; 0.001.</p>
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<p>Both Direct Irradiation and Extracellular Vesicles-Mediated Bystander Effects Induce Persistent Redistribution between Multipotent Progenitors and Long-Term Hematopoietic Stem Cells in the Bone Marrow. Irradiation, extracellular vesicle treatment and bone marrow cell phenotyping was carried out as described in the Materials and Methods section. Cellular subpopulations were identified as Lin-Sca1+cKit+CD34-CD135- long-term hematopoietic stem cells (LT-HSC), Lin-Sca1+cKit+CD34+CD135- short-term hematopoietic stem cells (ST-HSC) and Lin-Sca1+cKit+CD34+CD135+ multipotent progenitor cells (MPP) [<a href="#B36-cells-11-00155" class="html-bibr">36</a>,<a href="#B37-cells-11-00155" class="html-bibr">37</a>] and were measured by flow cytometry. (<b>A</b>) multipotent progenitors; (<b>C</b>) short-term hematopoietic stem cells; (<b>E</b>) long-term hematopoietic stem cells. Relative changes in hematopoietic stem cell subpopulations were evaluated 24 h after treatment. Grey bars represent total-body irradiated mice; red bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation; yellow bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 3 months after irradiation. (<b>B</b>) multipotent progenitors; (<b>D</b>) short-term hematopoietic stem cells; (<b>F</b>) long-term hematopoietic stem cells. Relative changes in hematopoietic stem cell numbers were evaluated 3 months after treatment. Grey bars represent total-body irradiated mice; blue bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation. (<b>G</b>) Distribution of individual subpopulations within the hematopoietic stem and progenitor cells was evaluated 24 h after treatment. Left columns represent total-body irradiated mice; middle columns represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation; right columns represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 3 months after irradiation. (<b>H</b>) Distribution of individual subpopulations within the hematopoietic stem and progenitor cells was evaluated 3 months after treatment. Left columns represent total-body irradiated mice; right columns represent mice treated with bone marrow-derived extracellular vesicles, which were isolated from mice 24 h after irradiation. Bars represent mean fraction of subpopulations, dots show individual values, error bars represent SD. <span class="html-italic">n</span> = 6–8, significance tested for individual subtypes of hematopoietic stem cells by Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> * &lt; 0.05, <span class="html-italic">p</span> ** &lt; 0.01, <span class="html-italic">p</span> *** &lt; 0.001.</p>
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<p>High Dose Irradiation Induces Persistent Depression of Lymphoid Progenitor Numbers, Extracellular Vesicle-Mediated Mild Bystander Effects Develop Late after Treatment. Irradiation, extracellular vesicle treatment and bone marrow cell phenotyping was carried out as described in the Materials and methods section. CD45+CD90.2+ cells were considered lymphoid progenitors. (<b>A</b>) Relative changes in lymphoid progenitor numbers were evaluated 24 h after treatment. Grey bars represent total-body irradiated mice; red bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation; yellow bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 3 months after irradiation. (<b>B</b>) Relative changes in lymphoid progenitor numbers were evaluated 3 months after treatment. Grey bars represent total-body irradiated mice; blue bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation Bars represent mean values of relative lymphoid progenitor numbers, dots show individual values, error bars represent SD. <span class="html-italic">n</span> = 5–11, significance tested by Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> * &lt; 0.05, <span class="html-italic">p</span> ** &lt; 0.01, <span class="html-italic">p</span> *** &lt; 0.001.</p>
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<p>Long-Term Direct Radiation and Extracellular Vesicles-Mediated Bystander Effects on the Granulocytes/Monocytes Pool Are More Severe than Acute Effects. Irradiation, extracellular vesicles treatment and bone marrow cell phenotyping was carried out as described in the Materials and methods section. Gr1+CD11b+ cells were considered granulocytes/monocytes. (<b>A</b>) Relative changes in the numbers of granulocytes/monocytes were evaluated 24 h after treatment. Grey bars represent total-body irradiated mice; red bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation; yellow bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 3 months after irradiation. (<b>B</b>) Relative changes in the numbers of granulocytes/monocytes were evaluated 3 months after treatment. Grey bars represent total-body irradiated mice; blue bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation. Bars represent mean values of relative granulocytes/monocytes progenitor numbers, dots show individual values, error bars represent SD. <span class="html-italic">n</span> = 5–11, significance tested by Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> * &lt; 0.05, <span class="html-italic">p</span> ** &lt; 0.01, <span class="html-italic">p</span> *** &lt; 0.001.</p>
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<p>Short-Term Direct Irradiation and Extracellular Vesicle-Mediated Bystander Effects Affecting the Mesenchymal Stromal Cell Pool Are More Severe than Long-Term Effects. Irradiation, extracellular vesicle treatment and bone marrow cell phenotyping was done as described in the Materials and Methods section. Lin-Sca1+CD44+ cells were considered mesenchymal stromal cells. (<b>A</b>) Relative changes in mesenchymal stromal cell numbers were evaluated 24 h after treatment. Grey bars represent total-body irradiated mice; red bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation; yellow bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 3 months after irradiation. (<b>B</b>) Relative changes in mesenchymal stromal cell numbers were evaluated 3 months after treatment. Grey bars represent total-body irradiated mice; blue bars represent mice treated with bone marrow-derived extracellular vesicles isolated from mice 24 h after irradiation. Bars represent mean values of relative mesenchymal stromal cell numbers, dots show individual values, error bars represent SD. <span class="html-italic">n</span> = 5–11, significance tested by Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> * &lt; 0.05, <span class="html-italic">p</span> ** &lt; 0.01, <span class="html-italic">p</span> *** &lt; 0.001.</p>
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<p>Transfer of Bone Marrow-Derived Extracellular Vesicles from Irradiated Mice Is Able to Induce Apoptosis in a Bystander Manner in Hematopoietic Stem Cells and Lymphoid Progenitors but Not Mesenchymal Stromal Cells. Bone-marrow single-cell suspension was prepared from directly irradiated and extracellular vesicle-treated mice 4 h after treatment and apoptosis was measured by the Tunnel assay as described in the Materials and Methods section. The relative change in apoptosis frequency compared to control mice (either non-irradiated or treated with extracellular vesicles originating from the bone marrow of non-irradiated mice) is shown for hematopoietic stem and progenitor cells (<b>A</b>), lymphoid progenitors (<b>B</b>) and mesenchymal stromal cells (<b>C</b>). Mean, minimum and maximum values are shown, error bars represent SD. <span class="html-italic">n</span> = 4, significance tested by Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> * &lt; 0.05; <span class="html-italic">p</span> ** &lt; 0.01.</p>
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<p>Bone Marrow-Derived Extracellular Vesicles from Low-Dose Irradiated Mice Induce Migration of Hematopoietic Stem and Progenitor Cells into the Spleen in Bystander Mice. Lin-Sca1+cKit+ hematopoietic stem and progenitor cells (<b>A</b>) and Lin-Sca1+CD44+ mesenchymal stromal cells (<b>B</b>) in the spleen were measured by flow cytometry 24 h after irradiation or injection of extracellular vesicles. Isolation of spleens and splenocyte phenotyping was performed as described in the Materials and Methods section. Black bars represent positive control mice treated with AMD3100. Mean, minimum and maximum values are shown, error bars represent SD. <span class="html-italic">N</span> = 6, significance tested by Student’s <span class="html-italic">t</span>-test, <span class="html-italic">p</span> * &lt; 0.05, <span class="html-italic">p</span> ** &lt; 0.01, <span class="html-italic">p</span> *** &lt; 0.001.</p>
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<p>Pathways Related to Cellular Response to Ionizing Radiation Prevail in miRNAs Differentially Expressed in the Bone Marrow-Derived Extracellular Vesicles Isolated from Mice 24 Hours after Irradiation. (<b>A</b>) Extracellular vesicles were isolated from the bone marrow of mice, miRNAs purified from extracellular vesicles and the relative concentration of miRNAs was measured by qRT-PCR as described in the Materials and Methods section. <span class="html-italic">n</span> = 3; * indicate significant changes (<span class="html-italic">p</span> ˂ 0.05) compared to control (0Gy extracellular vesicles samples). Arrows show increased (red arrows) or decreased (green arrows) expression in miRNAs from extracellular vesicles isolated 24 h or 3 months after irradiation. (<b>B</b>) KEGG analysis of differentially expressed 7 miRNAs in murine bone marrow-derived extracellular vesicles isolated 24 h but not 3 months after irradiation. A pathway was considered significant if the <span class="html-italic">p</span>-value was ˂0.05 (−log10 (0.05) indicated by the dashed line.</p>
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<p>The Influence of Differentially Expressed miRNAs on the Wnt Pathway. The Wnt signal transduction pathway is an evolutionary conserved pathway regulating basic developmental processes such as progenitor cell proliferation and cell-fate specification [<a href="#B63-cells-11-00155" class="html-bibr">63</a>], and it can be downregulated upon exposure to ionizing radiation [<a href="#B64-cells-11-00155" class="html-bibr">64</a>,<a href="#B65-cells-11-00155" class="html-bibr">65</a>]. The transcription of Wnt-related genes can be regulated by the cytoplasmic concentration of the β-catenin intracellular signal transducer. Without Wnt ligand binding to its receptor Frizzeld [<a href="#B66-cells-11-00155" class="html-bibr">66</a>] and co-receptor low-density lipoprotein receptor related 5/6 (LRP5/6) [<a href="#B67-cells-11-00155" class="html-bibr">67</a>,<a href="#B68-cells-11-00155" class="html-bibr">68</a>,<a href="#B69-cells-11-00155" class="html-bibr">69</a>], β-catenin is degraded by a destruction complex, which contains axin, adenomatosus polyposis coli (APC), protein phosphatase 2A (PP2A), and two kinases, glycogen synthase kinase 3 (GSK3) and casein kinase 1α (CK1α). In the β-catenin destruction complex, GSK3 and CK1α phosphorylate β-catenin, leading to its proteosomal degradation [<a href="#B70-cells-11-00155" class="html-bibr">70</a>]. Upon Wnt ligand binding, the destruction complex is disrupted, and β-catenin is enriched in the cytoplasm, which leads to its nuclear transport. In the nucleus β-catenin binds to lymphoid enhancer-binding factor/T-cell factor (LEF/TCF) proteins, transforming it into a transcriptional activator, leading to the transcription of Wnt target genes [<a href="#B71-cells-11-00155" class="html-bibr">71</a>,<a href="#B72-cells-11-00155" class="html-bibr">72</a>,<a href="#B73-cells-11-00155" class="html-bibr">73</a>,<a href="#B74-cells-11-00155" class="html-bibr">74</a>]. In the absence of β-catenin, LEF/TCF block the transcription of Wnt target genes [<a href="#B75-cells-11-00155" class="html-bibr">75</a>,<a href="#B76-cells-11-00155" class="html-bibr">76</a>]. The Wnt pathway was targeted by multiple differentially expressed miRNAs in the extracellular vesicles. Targets were associated with miRNAs by Diana mirPath v.3. We present our hypothesis of how differentially expressed miRNAs in 2Gy extracellular vesicles isolated from the bone marrow of mice 24 h after irradiation lead to the repression of the Wnt pathway. MiRNAs mostly repress the expression of their targets, so Wnt components targeted by upregulated miRNAs (illustrated in red in the Figure) are supposed to be downregulated, and components targeted by downregulated miRNAs (illustrated in green in the Figure) are supposed to be upregulated, compared to 0Gy samples. Arrows indicate the possible changes in the expression of the proteins targeted by the differentially expressed miRNAs: a red down arrow indicates decreased expression upon miRNA interaction, and a green up arrow indicates increased target expression. Mmu-miR-33-3p, a down-regulated miRNA targets a secreted frizzled-related protein 2 (Sfrp2), which is a Wnt antagonist [<a href="#B77-cells-11-00155" class="html-bibr">77</a>,<a href="#B78-cells-11-00155" class="html-bibr">78</a>], and nemo-like kinase (NLK), which is an inactivator of β-catenin TCF/LEF transcription complex formation [<a href="#B79-cells-11-00155" class="html-bibr">79</a>]. The other downregulated miRNA mmu-miR-669o-5p interacts with the BMP and Activin Membrane Bound Inhibitor (Bambi) which can both up- and downregulate the β-catenin signaling [<a href="#B80-cells-11-00155" class="html-bibr">80</a>,<a href="#B81-cells-11-00155" class="html-bibr">81</a>,<a href="#B82-cells-11-00155" class="html-bibr">82</a>]. The upregulated mmu-miR-152-3p targets Wnt10b, which promotes the β-catenin-dependent Wnt signaling pathway [<a href="#B83-cells-11-00155" class="html-bibr">83</a>]. Wnt receptors are also targeted by upregulated miRNAs: LRP5 by mm-miR-375-3p and FZD5 by mmu-miR-199a-5p. Two Wnt inhibitors are targeted by two upregulated miRNAs: GSK-3β by mmu-miR-199a-5p, and Ctbp2 by mmu-miR-375-3p. Ctbp2 is originally an inhibitor, but some studies indicate that it may also act as an activator of TCF [<a href="#B84-cells-11-00155" class="html-bibr">84</a>,<a href="#B85-cells-11-00155" class="html-bibr">85</a>]. Thus, it can be seen that downregulated miRNAs target inhibitors, while upregulated miRNAs mostly target Wnt pathway initiators, which indicate an overall downregulation of the Wnt signaling pathway.</p>
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20 pages, 3421 KiB  
Article
Comprehensive Molecular Landscape of Cetuximab Resistance in Head and Neck Cancer Cell Lines
by Izabela N. F. Gomes, Renato J. da Silva-Oliveira, Luciane Sussuchi da Silva, Olga Martinho, Adriane F. Evangelista, André van Helvoort Lengert, Letícia Ferro Leal, Viviane Aline Oliveira Silva, Stéphanie Piancenti dos Santos, Flávia Caroline Nascimento, André Lopes Carvalho and Rui Manuel Reis
Cells 2022, 11(1), 154; https://doi.org/10.3390/cells11010154 - 4 Jan 2022
Cited by 14 | Viewed by 5278
Abstract
Cetuximab is the sole anti-EGFR monoclonal antibody that is FDA approved to treat head and neck squamous cell carcinoma (HNSCC). However, no predictive biomarkers of cetuximab response are known for HNSCC. Herein, we address the molecular mechanisms underlying cetuximab resistance in an in [...] Read more.
Cetuximab is the sole anti-EGFR monoclonal antibody that is FDA approved to treat head and neck squamous cell carcinoma (HNSCC). However, no predictive biomarkers of cetuximab response are known for HNSCC. Herein, we address the molecular mechanisms underlying cetuximab resistance in an in vitro model. We established a cetuximab resistant model (FaDu), using increased cetuximab concentrations for more than eight months. The resistance and parental cells were evaluated for cell viability and functional assays. Protein expression was analyzed by Western blot and human cell surface panel by lyoplate. The mutational profile and copy number alterations (CNA) were analyzed using whole-exome sequencing (WES) and the NanoString platform. FaDu resistant clones exhibited at least two-fold higher IC50 compared to the parental cell line. WES showed relevant mutations in several cancer-related genes, and the comparative mRNA expression analysis showed 36 differentially expressed genes associated with EGFR tyrosine kinase inhibitors resistance, RAS, MAPK, and mTOR signaling. Importantly, we observed that overexpression of KRAS, RhoA, and CD44 was associated with cetuximab resistance. Protein analysis revealed EGFR phosphorylation inhibition and mTOR increase in resistant cells. Moreover, the resistant cell line demonstrated an aggressive phenotype with a significant increase in adhesion, the number of colonies, and migration rates. Overall, we identified several molecular alterations in the cetuximab resistant cell line that may constitute novel biomarkers of cetuximab response such as mTOR and RhoA overexpression. These findings indicate new strategies to overcome anti-EGFR resistance in HNSCC. Full article
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<p>Cetuximab resistant model establishment and characterization. (<b>A</b>) EGFR signaling of parental and cetuximab-resistant clones after cetuximab resistant model establishment. (<b>B</b>) Cell viability assay of parental and resistant clone upon cetuximab exposition in 72 h. (<b>C</b>) Cell morphology of parental and resistant cells P: FaDu parental; R: FaDu resistant; C: Clone. The images were acquired in 10× magnification.</p>
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<p>Karyotypes and Copy number alterations (CNA) overview of FaDu parental and FaDu resistant cells. (<b>A</b>) Representative metaphase of FaDu parental and FaDu resistant cells. (<b>B</b>) Overview of the CNAs found in FaDu resistant cells in comparison with FaDu parental cells. In red gain and in blue deletions. M: marker chromosome.</p>
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<p>Molecular characterization after cetuximab-acquired resistance. (<b>A</b>) Heatmap of genes altered in FaDu parental and FaDu resistant cells. In red are represented the overexpressed genes, and in blue the downregulated genes. FaDu parental is shown in purple and FaDu resistant in green. (<b>B</b>) Genetic interaction network associated with cetuximab resistance on the STRING database. In this figure, each circle represents a protein (node), and each connection represents a direct or indirect connection (edge). Line color indicates the type of interaction evidence: purple—experimental evidence, light blue—curate database, black—co-expression, pink—experimentally determined, yellow—text mining, dark blue—gene co-occurrence (MAPK associated genes are shown in red, RAS associated genes are shown in blue, and mTOR signaling-related genes are shown in yellow. <span class="html-italic">p</span>. adjusted &lt;0.01; FC ≥ 2.</p>
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<p>Cell surface markers and cytokines profile expression in FaDu parental and FaDu resistant cells. (<b>A</b>) Representation of cell-surface markers expression in FaDu parental and FaDu resistant cells. <span class="html-italic">p</span>. adjusted &lt; 0.01. (<b>B</b>) Representative images of Cytokines protein array in FaDu parental and FaDu resistant cells. (<b>C</b>) Bars demonstrated the cytokines differential expression in FaDu cells.</p>
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<p>EGFR-FITC+ internalization and mTOR-FITC+ expression in FaDu parental and FaDu resistant cells. (<b>A</b>) Subcellular protein fractionation assay for EGFR detection in parental and resistant cells. (<b>B</b>) p-EGFR nuclear translocation in resistant cells by Immunofluorescence assay. (<b>C</b>) p-mTOR immunofluorescence assay in parental and resistant cells. (<b>D</b>) mTOR-related genes differentially expressed in FaDu parental and FaDu resistant by microarray of expression. DAPI (Hoescht) staining in blue. p-EGFR-FITC+ p-mTOR-FITC+. Arrows indicate EGFR-FITC+ and p-mTOR-FITC+ localization. The images were acquired in 40× magnification. The number under the bands represented relative ratios (phospho/total).</p>
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<p>Malignant phenotype acquired after cetuximab resistance establishment. (<b>A</b>) Representative images of wound healing assay of FaDu parental and FaDu resistant cell lines in 24, 48, and 72 h. The yellow lines represent the distance between both edges of the wound; Scale bars, 200 µm; (<b>B</b>) Migration rates of FaDu parental and FaDu resistant cells in a wound-healing assay; (<b>C</b>) Representative images of adhesion and clonogenic assay for parental and resistant cells; (<b>D</b>) The absolute number of adherent cells; (<b>E</b>) The absolute number of colonies in clonogenic cell assay for anchorage-dependent in parental and resistant cells. (*** <span class="html-italic">p</span> &lt; 0.0001). The images were acquired in 10× magnification.</p>
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<p>Epithelial–mesenchymal transition (EMT) markers expression in FaDu parental and FaDu resistant cells. (<b>A</b>) Representative images of EMT proteins detected in Western blot assay in parental and resistant cells. (<b>B</b>) E-cadherin densitometry. (<b>C</b>) N-cadherin densitometry. (<b>D</b>) α-smooth densitometry. (<b>E</b>) Slug densitometry. (<b>F</b>) Snail densitometry (<b>G</b>) TGF-β densitometry (<b>H</b>) CD44 densitometry Data are presented in fold-change in comparison with FaDu parental. Fadu p: FaDu parental; FaDu R: FaDu resistant. (*** <span class="html-italic">p</span> &lt; 0.001).</p>
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18 pages, 3844 KiB  
Review
The Impact of Exercise on Telomere Length, DNA Methylation and Metabolic Footprints
by Sandra Haupt, Tobias Niedrist, Harald Sourij, Stephan Schwarzinger and Othmar Moser
Cells 2022, 11(1), 153; https://doi.org/10.3390/cells11010153 - 4 Jan 2022
Cited by 9 | Viewed by 8282
Abstract
Aging as a major risk factor influences the probability of developing cancer, cardiovascular disease and diabetes, amongst others. The underlying mechanisms of disease are still not fully understood, but research suggests that delaying the aging process could ameliorate these pathologies. A key biological [...] Read more.
Aging as a major risk factor influences the probability of developing cancer, cardiovascular disease and diabetes, amongst others. The underlying mechanisms of disease are still not fully understood, but research suggests that delaying the aging process could ameliorate these pathologies. A key biological process in aging is cellular senescence which is associated with several stressors such as telomere shortening or enhanced DNA methylation. Telomere length as well as DNA methylation levels can be used as biological age predictors which are able to detect excessive acceleration or deceleration of aging. Analytical methods examining aging are often not suitable, expensive, time-consuming or require a high level of technical expertise. Therefore, research focusses on combining analytical methods which have the potential to simultaneously analyse epigenetic, genomic as well as metabolic changes. Full article
(This article belongs to the Special Issue Metabolic Inflammation and Cellular Immunity)
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<p>Biological age correlates with the chronological age of a person and depends, among other things, on genetic predisposition, phenotypic changes and epigenetic changes. Nutritional, environmental, psychosocial and other lifestyle (exercise, weight) factors have the potential to both delay and accelerate the aging process and thus modulate risk of diseases. Specific biomarkers could serve as biological age predictors for risk assessment of age-specific diseases and thus influence the aging process positively as well as negatively. This could allow the detection of differences in the risk of age-related diseases for individuals of the same chronological age and identify pathways that have the potential to target these negative epigenetic changes.</p>
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<p>Telomeres act as protective caps at the end of chromosomes. They consist of a sequence of 6 nucleotides (G-strand: 5′-TTAGGG-3′; C-strand: 3′-AATCCC-5′) repeated several thousand times. Telomeres loses length with each cell division. To prevent excessive shortening, they are protected by shelterin. Shelterin is a protein complex consisting of six subunits: telomere repeat binding factor 1 (TRF1), telomere repeat binding factor 2 (TRF2), protection of telomere 1 (POT1), repressor/activator protein 1 (RAP1), TRF1- and TRF2-interacting nuclear protein 2 (TIN2) and tripeptidyl peptidase 1 (TPP1). The 3’ end of the G-rich strand extends over the end of the C-rich strand (5’ end) of the telomere. Given sufficient length of the telomere, this forms the t-loop, which overlaps with the double-stranded 5’ end, building the D-loop protecting the telomeres (<b>c</b>). During replication, the G- and C-strands are open. Telomerase can bind to the G-strand to add telomeric repeats preventing the cell from damage (<b>b</b>). Loss of function and degradation of the shelterin complex leading to DNA damage occur more frequently during aging and cause the cell to stop dividing (<b>a</b>).</p>
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<p>Normal cells can be induced to become senescent, which can induce paracrine senescence. Together with a decline in immune function, this could induce accumulation of senescent cells. In the elderly this accumulation contributes to increased risk in developing age-related diseases.</p>
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17 pages, 5275 KiB  
Article
The Negative Regulative Roles of BdPGRPs in the Imd Signaling Pathway of Bactrocera dorsalis
by Ping Zhang, Zhichao Yao, Shuai Bai and Hongyu Zhang
Cells 2022, 11(1), 152; https://doi.org/10.3390/cells11010152 - 4 Jan 2022
Cited by 5 | Viewed by 2296
Abstract
Peptidoglycan recognition proteins (PGRPs) are key regulators in insects’ immune response, functioning as sensors to detect invading pathogens and as scavengers of peptidoglycan (PGN) to reduce immune overreaction. However, the exact function of PGRPs in Bactrocera dorsalis is still unclear. In this study, [...] Read more.
Peptidoglycan recognition proteins (PGRPs) are key regulators in insects’ immune response, functioning as sensors to detect invading pathogens and as scavengers of peptidoglycan (PGN) to reduce immune overreaction. However, the exact function of PGRPs in Bactrocera dorsalis is still unclear. In this study, we identified and functionally characterized the genes BdPGRP-LB, BdPGRP-SB1 and BdPGRP-SC2 in B. dorsalis. The results showed that BdPGRP-LB, BdPGRP-SB1 and BdPGRP-SC2 all have an amidase-2 domain, which has been shown to have N-Acetylmuramoyl-l-Alanine amidase activity. The transcriptional levels of BdPGRP-LB and BdPGRP-SC2 were both high in adult stages and midgut tissues; BdPGRP-SB1 was found most abundantly expressed in the 2nd instar larvae stage and adult fat body. The expression of BdPGRP-LB and BdPGRP-SB1 and AMPs were significantly up-regulated after injury infected with Escherichia coli at different time points; however, the expression of BdPGRP-SC2 was reduced at 9 h, 24 h and 48 h following inoculation with E. coli. By injection of dsRNA, BdPGRP-LB, BdPGRP-SB1 and BdPGRP-SC2 were knocked down by RNA-interference. Silencing of BdPGRP-LB, BdPGRP-SB1 and BdPGRP-SC2 separately in flies resulted in over-activation of the Imd signaling pathway after bacterial challenge. The survival rate of the ds-PGRPs group was significantly reduced compared with the ds-egfp group after bacterial infection. Taken together, our results demonstrated that three catalytic PGRPs family genes, BdPGRP-LB, BdPGRP-SB1 and BdPGRP-SC2, are important negative regulators of the Imd pathway in B. dorsalis. Full article
(This article belongs to the Collection Feature Papers in ‘Cellular Immunology’)
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Graphical abstract

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<p>Amino acid sequence alignment of <span class="html-italic">BdPGRPs</span> with that of homologous genes in other insect species. (<b>A</b>) Multiple alignments of <span class="html-italic">PGRP-LB</span>. <span class="html-italic">Bd</span><span class="html-italic">PGRP-LB</span> was aligned with <span class="html-italic">Bactrocera latifrons PGRP-LB</span> (XP_018789449.1), <span class="html-italic">Bactrocera oleae PGRP-LB</span> (XP_014091181.2), <span class="html-italic">Zeugodacus cucurbitae PGRP-LB</span> (XP_011197144.1), <span class="html-italic">Ceratitis capitate PGRP-LB</span> (XP_004518089.1), <span class="html-italic">Rhagoletis zephyria PGRP-LB</span> (XP_017470705.1), <span class="html-italic">Rhagoletis pomonella PGRP-LB</span> (XP_036322481.1), <span class="html-italic">Aedes aegypti PGRP-LB</span> (XP_021709443.1), <span class="html-italic">Drosophila melanogaster PGRP-LB</span> (NP_731575.1), <span class="html-italic">Bombyx mori PGRP-LB</span> (XP_012548100.1), <span class="html-italic">Musca domestica PGRP-LB</span> (XP_005180889.1), and <span class="html-italic">Glossina fuscipes PGRP-LB</span> (ACI22620.1). (<b>B</b>) Multiple alignments of <span class="html-italic">PGRP-SB</span>. <span class="html-italic">BdPGRP-SB</span><sub>1</sub> was aligned with <span class="html-italic">B. latifrons PGRP-SB</span> (XP_018789286.1), <span class="html-italic">B. oleae PGRP-SB</span> (XP_014099773.1), <span class="html-italic">Z. cucurbitae PGRP-SB</span> (XP_011181375.1), <span class="html-italic">C. capitate PGRP-SB</span> (XP_004537949.1), <span class="html-italic">R. zephyria PGRP-SB</span> (XP_017486043.1), <span class="html-italic">R. pomonella PGRP-SB</span> (XP_036336342.1), <span class="html-italic">D. melanogaster PGRP-SB</span> (CAD89135.1), <span class="html-italic">M. domestica PGRP-SB</span> (NP_001295929.1), and <span class="html-italic">B. mori PGRP-SB</span> (XP_004929843.1). (<b>C</b>) Multiple alignments of <span class="html-italic">PGRP-SC</span><sub>2</sub>. <span class="html-italic">BdPGRP-SC</span><sub>2</sub> was aligned with <span class="html-italic">B. latifrons PGRP-SC</span><sub>2</sub> (XP_018798904.1), <span class="html-italic">B. oleae PGRP-SC</span><sub>2</sub> (XP_014085196.2), <span class="html-italic">C. capitate PGRP-SC</span><sub>2</sub> (XP_004520319.1), <span class="html-italic">Z. cucurbitae PGRP-SC</span><sub>2</sub> (XP_011180165.1), <span class="html-italic">R. pomonella PGRP-SC</span><sub>2</sub> (XP_036334551.1), <span class="html-italic">M. domestica PGRP-SC</span><sub>2</sub> (XP_005184140.3), <span class="html-italic">D. melanogaster PGRP-SC</span><sub>2</sub> (CAD89184.1), <span class="html-italic">A. aegypti PGRP-SC</span><sub>2</sub> (XP_011492940.1), and <span class="html-italic">B. mori PGRP-SC</span><sub>2</sub> (XP_004929814.1). The identical amino acids are shown against a black background; 75% conserved amino acids are shown against a pink background; 50% conserved amino acids are shown against a blue background. The signal peptides are indicated by dashed lines. The amidase domains are indicated by solid lines. Black arrows indicate the amino acid residues required for the recognition of DAP-type peptidoglycan. Grey arrows indicate the amino acid residues required for Zn<sup>2+</sup> binding. White arrows indicate the amino acid residues required for amidase activity.</p>
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<p>Expression profiles of <span class="html-italic">BdPGRPs</span> in <span class="html-italic">B</span><span class="html-italic">.dorsalis</span>. (<b>A</b>) Relative expression of <span class="html-italic">BdPGRP-LB</span> at different development stages. (<b>B</b>) Relative expression of <span class="html-italic">BdPGRP-SB</span><sub>1</sub> at different development stages. (<b>C</b>) Relative expression of <span class="html-italic">BdPGRP-S</span><span class="html-italic">C</span><sub>2</sub> at different development stages. (<b>D</b>) Relative expression of <span class="html-italic">BdPGRP-LB</span> from different tissue samples. (<b>E</b>) Relative expression of <span class="html-italic">BdPGRP-SB</span><sub>1</sub> from different tissue samples. (<b>F</b>) Relative expression of <span class="html-italic">BdPGRP-S</span><span class="html-italic">C</span><sub>2</sub> from different tissue samples. <span class="html-italic">B.</span> <span class="html-italic">dorsalis</span> was collected at various developmental stages: 1 L, 1st instar larvae; 2 L, 2nd instar larvae; 3 L, 3rd instar larvae; EP, early pupal stage; LP, late pupal stage; EA, newly emergence adults; LA, late adult stage. Different adult tissues were collected: HD, head; MG, midgut; HG, hindgut; MT, Malpighian tube; FB, fatbody; OV, ovary; TE, testis. Multiple comparisons were carried out with one-way analysis of variance (ANOVA) and Turkey’s test in SPSS 16.0. Different lower-case letters indicate a significant difference at the level of <span class="html-italic">p</span> &lt; 0.05 and a confidence interval of 95%. The relative gene expression data were analyzed using a 2<sup>−ΔΔCT</sup> method and the data were normalized to reference gene <span class="html-italic">Rpl32</span>.</p>
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<p>Responses of <span class="html-italic">Dpt</span> and <span class="html-italic">BdPGRPs</span> to opportunistic pathogen <span class="html-italic">E. coli</span> challenges. Relative expression of <span class="html-italic">Dp</span><span class="html-italic">t</span> (<b>A</b>), <span class="html-italic">BdPGRP-LB</span> (<b>B</b>), <span class="html-italic">BdPGRP-SB</span><sub>1</sub> (<b>C</b>), and <span class="html-italic">BdPGRP-SC</span><sub>2</sub> (<b>D</b>) after infection with <span class="html-italic">E. coli</span> at different time points, respectively. The data are expressed as mean ± SEM and the mean refers to the average of four biological replicates for each sample. Statistical analysis was based on Student’s <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001. The relative gene expression data were analyzed using a 2<sup>−ΔΔCT</sup> method and the data were normalized to reference gene <span class="html-italic">Rpl32</span>.</p>
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<p>Off-target detection after dsRNA injection. (<b>A</b>) Influence of silencing <span class="html-italic">BdPGRP-LB</span> on expression of <span class="html-italic">Bd</span><span class="html-italic">PGRP-SB</span><sub>1</sub> and <span class="html-italic">Bd</span><span class="html-italic">PGRP-SC</span><sub>2</sub>. (<b>B</b>) Influence of silencing <span class="html-italic">BdPGRP-</span> <span class="html-italic">SB</span><sub>1</sub> on expression of <span class="html-italic">Bd</span><span class="html-italic">PGRP-</span><span class="html-italic">LB</span> and <span class="html-italic">Bd</span><span class="html-italic">PGRP</span>-SC<sub>2</sub>. (<b>C</b>) Influence of silencing <span class="html-italic">BdPGRP-</span> <span class="html-italic">S</span><span class="html-italic">C</span><sub>2</sub> on expression of <span class="html-italic">Bd</span><span class="html-italic">PGRP-</span><span class="html-italic">LB</span> and <span class="html-italic">Bd</span><span class="html-italic">PGRP-S</span><span class="html-italic">B</span><sub>1</sub>. All error bars represent the SEM of the mean of three independent biological replicates. Statistical analysis was based on Student’s <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; NS, no significant difference; <span class="html-italic">p</span> &gt; 0.05. The relative gene expression data were analyzed using a 2<sup>−ΔΔCT</sup> method and the data were normalized to reference gene <span class="html-italic">Rpl32</span>.</p>
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<p>RNA interference efficiency of <span class="html-italic">BdPGRPs</span>. Relative expression of <span class="html-italic">PGRP-LB</span> (<b>A</b>), <span class="html-italic">PGRP-SB</span><sub>1</sub> (<b>B</b>), and <span class="html-italic">PGRP-SC</span><sub>2</sub> (<b>C</b>) after dsRNA injection at different time points with whole body samples. All error bars represent the SEM of the mean of three independent biological replicates. Statistical analysis was based on Student’s <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01. The relative gene expression data were analyzed using a 2<sup>−ΔΔCT</sup> method and the data were normalized to reference gene <span class="html-italic">Rpl32</span>.</p>
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<p>Antimicrobial peptide gene expression in <span class="html-italic">BdPGRPs</span> RNAi flies after bacterial challenges. (<b>A</b>,<b>B</b>) Injury infection with <span class="html-italic">E. coli</span> induced a higher <span class="html-italic">Diptericin</span> (<span class="html-italic">Dp</span><span class="html-italic">t</span>) expression in <span class="html-italic">BdPGRPs</span> RNAi flies than in the <span class="html-italic">ds-egfp</span> dsRNA injection flies. The data are expressed as the mean ± SEM, and the mean refers to the average of at least three replicates for each sample. Statistical analysis was based on Student’s <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01. The relative gene expression data were analyzed using a 2<sup>−ΔΔCT</sup> method and the data were normalized to reference gene <span class="html-italic">Rpl32</span>.</p>
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<p>Survival rate of <span class="html-italic">B. dorsalis</span> after <span class="html-italic">BdPGRPs</span> RNAi followed by <span class="html-italic">E. coli</span> infection. (<b>A</b>) Three <span class="html-italic">BdPGRPs</span> were knocked down separately. (<b>B</b>) Three <span class="html-italic">BdPGRPs</span> were knocked down at the same time. Statistical analysis was based on Log-rank (Mantel–Cox) test (* <span class="html-italic">p</span> &lt; 0.05).</p>
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14 pages, 2707 KiB  
Article
Characterization of Oxygen Levels in an Uninfected and Infected Human Blood-Cerebrospinal-Fluid-Barrier Model
by Alexander Martens, Nicole de Buhr, Hiroshi Ishikawa, Horst Schroten and Maren von Köckritz-Blickwede
Cells 2022, 11(1), 151; https://doi.org/10.3390/cells11010151 - 4 Jan 2022
Cited by 2 | Viewed by 2437
Abstract
The host–pathogen interaction during meningitis can be investigated with blood-cerebrospinal-fluid-barrier (BCSFB) cell culture models. They are commonly handled under atmospheric oxygen conditions (19–21% O2), although the physiological oxygen conditions are significantly lower in cerebrospinal fluid (CSF) (7–8% O2). We [...] Read more.
The host–pathogen interaction during meningitis can be investigated with blood-cerebrospinal-fluid-barrier (BCSFB) cell culture models. They are commonly handled under atmospheric oxygen conditions (19–21% O2), although the physiological oxygen conditions are significantly lower in cerebrospinal fluid (CSF) (7–8% O2). We aimed to characterize oxygen levels in a Streptococcus (S.) suis-infected BCSFB model with transmigrating neutrophils. A BCSFB model with human choroid plexus epithelial cells growing on transwell-filters was used. The upper “blood”-compartment was infected and blood-derived neutrophils were added. S. suis and neutrophils transmigrated through the BCSFB into the “CSF”-compartment. Here, oxygen and pH values were determined with the non-invasive SensorDish® reader. Slight orbital shaking improved the luminescence-based measurement technique for detecting free oxygen. In the non-infected BCSFB model, an oxygen value of 7% O2 was determined. However, with S. suis and transmigrating neutrophils, the oxygen value significantly decreased to 2% O2. The pH level decreased slightly in all groups. In conclusion, we characterized oxygen levels in the BCSFB model and demonstrated the oxygen consumption by cells and bacteria. Oxygen values in the non-infected BCSFB model are comparable to in vivo values determined in pigs in the CSF. Infection and transmigrating neutrophils decrease the oxygen value to lower values. Full article
(This article belongs to the Collection Advances in Cell Culture and Tissue Engineering)
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Figure 1
<p>Experimental setup of the BCSFB model under shaking conditions. (<b>A</b>) The experimental setup of the BCSFB model is displayed. Human choroid plexus epithelial cells (HIBCPP) form the BCSFB barrier and divided the model into an upper “blood” compartment and a lower “CSF” compartment. Sensor spots for oxygen and pH measurement are inside the CSF compartment. (<b>B</b>) The number of transmigrated neutrophils was quantified inside the CSF compartment at the end of the six-hour experiment. The shaking setup did not influence the transmigration. One example of an immunofluorescence microscopy picture of the choroid plexus cells grown on a filter shows a transmigrating neutrophil (arrow). Scale bar 10 µm; blue = DNA, gray = phalloidin, green = LL-37, red = myeloperoxidase; single channels and overview pictures are presented in <a href="#cells-11-00151-f0A3" class="html-fig">Figure A3</a>. (<b>C</b>) The host–pathogen interaction of neutrophils and <span class="html-italic">S. suis</span> were not influenced regarding the neutrophil killing capacity of <span class="html-italic">S. suis</span>. All data are presented as mean ± SD of three independent experiments. Statistical differences were analyzed with one-tailed paired Student’s <span class="html-italic">t</span>-test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01).</p>
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<p>Choroid plexus epithelial cells (HIBCPP), neutrophils, and <span class="html-italic">S. suis</span> consume oxygen over time. The oxygen level was determined in the CSF compartment in a shaking setup. (<b>A</b>) The oxygen level did not change in media, whereas with HIBCPP cells, the oxygen decreased over time. (<b>B</b>) Non-activated neutrophils did not consume a high level of oxygen, whereas <span class="html-italic">S. suis</span> significantly consumed oxygen. (<b>C</b>) The host–pathogen interaction of HIBCPP cells, transmigrating neutrophils, and <span class="html-italic">S. suis</span> significantly consumed oxygen. All data are presented as mean ± SD of three independent experiments. Statistical differences were analyzed in A with a one-tailed paired Student’s <span class="html-italic">t</span>-test in each group at 0 h. Statistical differences were analyzed in B and C with a one-way ANOVA at each time-point (<span class="html-italic">p</span> &lt; 0.0001), followed by Tukey multiple comparisons (* <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>The pH in the CSF compartment is slightly decreased by <span class="html-italic">S. suis</span> and interacting neutrophils after a six-hour incubation period. The pH level was determined in the CSF compartment in a shaking setup. (<b>A</b>) The pH decrease in media and with HIBCPP cells is comparable. (<b>B</b>) No significant influence on pH was detected in the absence of HIBCPP cells. (<b>C</b>) The host–pathogen interaction of HIBCPP cells, transmigrating neutrophils, and <span class="html-italic">S. suis</span> significantly decreased the pH slightly after six hours. All data are presented as mean ± SD of three independent experiments. Statistical differences were analyzed in A with a one-tailed paired Student’s <span class="html-italic">t</span>-test in each group at 0 h. Statistical differences were analyzed in B and C with a one-way ANOVA at each time-point (<b>C</b>: <span class="html-italic">p</span><sub>2h</sub> = 0.002; <span class="html-italic">p</span><sub>6h</sub> = 0.02), followed by Tukey multiple comparisons in (<b>C</b>) (* <span class="html-italic">p</span> &lt;0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>A shaking setup of the BCSFB model is obligatory to reduce bacterial-related false reduced oxygen levels inside the CSF compartment. (<b>A</b>) The dextran flux rate was determined as an indicator of barrier integrity. No cells on the filter (TEER = 0 Ω x cm<sup>2</sup>) led to a dextran flux rate of 100%. With increasing TEER values, the dextran flux rate decreased. Dextran flow rates lower than 5% indicate increasing barrier integrity of the HIBCPP layer. At the start of all experiments, only filters with TEER values of the experiment in the gray marked range were included. (<b>B</b>) The oxygen partial pressures were compared in a non-shaking and shaking setup during <span class="html-italic">S. suis</span> infection. After a 2-h incubation period with <span class="html-italic">S. suis</span>, significantly lower oxygen partial pressure was measured in the non-shaking setup (** <span class="html-italic">p</span> ≤ 0.01). (<b>C</b>) The determined bacterial number remained constant between the two setups. (<b>D</b>) Two areas were defined inside the well to quantify <span class="html-italic">S. suis</span> around the sensor spot (S) and in the outer circle. The area of “S” and a defined extra area = “E” were named “A1”. The rest of the well was named “A2”. (<b>E</b>) Significant different numbers of <span class="html-italic">S. suis</span> were reisolated from the two defined areas with the two shaking setups. The total amount of bacteria was comparable (* <span class="html-italic">p</span> &lt; 0.05). (<b>F</b>) The TEER was not influenced by the shaking setup during an infection experiment with transmigrating neutrophils.</p>
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<p><span class="html-italic">S. suis</span> significantly decreased the barrier integrity after seven hours. The TEER values of <span class="html-italic">S. suis</span>-infected HIBCPP filters were measured before infection (0 h) and after 4, 7, 20, and 24 h (h). The filters were infected and incubated for 24 h with and without antibiotic treatment. (<b>A</b>) A significant decrease in TEER was detectable after 7 h <span class="html-italic">S. suis</span> infection in the absence of antibiotics. After 20 h, the low TEER reflected a loss of barrier integrity. (<b>B</b>) Antibiotic treatment after 4 h did not lead to a TEER value after 24 h in a range higher than 380 Ω x cm<sup>2</sup>. The mean value ± SD of independent experiments is presented. Each dot represents one filter. Statistical differences were analyzed with one-way ANOVA (<span class="html-italic">p</span> &lt; 0.0001), followed by Dunnett’s multiple comparison test in A and Tukey’s multiple comparison test in 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).</p>
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<p>LL-37 and myeloperoxidase signals identify a transmigrating neutrophil through the BCSFB. Immunofluorescence microscopy was conducted to detect transmigrating neutrophils. Filters were stained and imaged from the “CSF” side. White squares highlight the area of magnification. Settings were adjusted to the respective isotype control; blue = DNA, green = LL-37, red = myeloperoxidase (MPO) and gray = phalloidin). Scale bar overview = 50 µm; scale bar zoom = 10 µm.</p>
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Article
The Molecular Subtype of Adult Acute Lymphoblastic Leukemia Samples Determines the Engraftment Site and Proliferation Kinetics in Patient-Derived Xenograft Models
by Anna Richter, Catrin Roolf, Anett Sekora, Gudrun Knuebel, Saskia Krohn, Sandra Lange, Vivien Krebs, Bjoern Schneider, Johannes Lakner, Christoph Wittke, Christoph Kiefel, Irmela Jeremias, Hugo Murua Escobar, Brigitte Vollmar and Christian Junghanss
Cells 2022, 11(1), 150; https://doi.org/10.3390/cells11010150 - 3 Jan 2022
Cited by 4 | Viewed by 2709
Abstract
In acute lymphoblastic leukemia (ALL), conventional cell lines do not recapitulate the clonal diversity and microenvironment. Orthotopic patient-derived xenograft models (PDX) overcome these limitations and mimic the clinical situation, but molecular stability and engraftment patterns have not yet been thoroughly assessed. We herein [...] Read more.
In acute lymphoblastic leukemia (ALL), conventional cell lines do not recapitulate the clonal diversity and microenvironment. Orthotopic patient-derived xenograft models (PDX) overcome these limitations and mimic the clinical situation, but molecular stability and engraftment patterns have not yet been thoroughly assessed. We herein describe and characterize the PDX generation in NSG mice. In vivo tumor cell proliferation, engraftment and location were monitored by flow cytometry and bioluminescence imaging. Leukemic cells were retransplanted for up to four passages, and comparative analyses of engraftment pattern, cellular morphology and genomic hotspot mutations were conducted. Ninety-four percent of all samples were successfully engrafted, and the xenograft velocity was dependent on the molecular subtype, outcome of the patient and transplantation passage. While BCR::ABL1 blasts were located in the spleen, KMT2A-positive cases had higher frequencies in the bone marrow. Molecular changes appeared in most model systems, with low allele frequency variants lost during primary engraftment. After the initial xenografting, however, the PDX models demonstrated high molecular stability. This protocol for reliable ALL engraftment demonstrates variability in the location and molecular signatures during serial transplantation. Thorough characterization of experimentally used PDX systems is indispensable for the correct analysis and valid data interpretation of preclinical PDX studies. Full article
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Figure 1

Figure 1
<p>Engraftment-influencing parameters. Every dot represents a separate animal. (<b>A</b>) Comparison of the initial weight and weight at experiment termination of all 101 mice used for tumor cell expansion. Weight gain is indicated by green dots, while weight loss up to 10% and 20% is displayed in yellow and red, respectively. (<b>B</b>–<b>H</b>) Influence of clinical–pathological parameters on tumor cell engraftment and proliferation in the first PDX passage. (<b>B</b>) Only patients with confirmed date of death or a recent checkup no older than twelve months were included in the analysis to investigate the influence of patient survival. Samples of unknown status or when the last contact was longer than one year ago were excluded. <span class="html-italic">n</span> = 19 mice, mean ± standard deviation, Mann–Whitney test. (<b>C</b>) Influence of patient sex on engraftment velocity. <span class="html-italic">n</span> = 30 mice, mean ± standard deviation, Mann–Whitney test. (<b>D</b>) Correlation of patient age at sample collection with engraftment kinetics. <span class="html-italic">n</span> = 30 mice (Spearman’s correlation coefficient r). (<b>E</b>) Influence of sample origin (bone marrow or peripheral blood) on engraftment velocity. <span class="html-italic">n</span> = 29 mice, mean ± standard deviation, Mann–Whitney test. (<b>F</b>) Influence of the molecular subtype of the primary tumor on engraftment speed. Patients with <span class="html-italic">BCR::ABL1</span> or <span class="html-italic">KMT2A</span> translocations and additional aberrations were only considered for the <span class="html-italic">BCR::ABL1</span> and <span class="html-italic">KMT2A</span> cohorts, respectively. <span class="html-italic">n</span> = 30 mice, mean ± standard deviation, no statistical evaluation due to limited sample numbers in subgroups. (<b>G</b>) Correlation of the number of cells injected and the engraftment velocity. <span class="html-italic">n</span> = 30 mice (Spearman’s correlation coefficient r). (<b>H</b>) Influence of mouse sex on engraftment speed. <span class="html-italic">n</span> = 30 mice, mean ± standard deviation, Mann–Whitney test.</p>
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<p>Influence of the molecular subtype on the engraftment sites. All 101 animals used for cell expansion irrespective of the engraftment passage were considered for these analyses. (<b>A</b>,<b>B</b>) Bone marrow and spleen infiltration were determined by a flow cytometric analysis of human C45<sup>+</sup>/CD19<sup>+</sup>, C45<sup>+</sup>/CD5<sup>+</sup> and CD45<sup>+</sup>/CD7<sup>+</sup> blasts isolated from animals at the end of the expansion experiment. Kruskal–Wallis and post-hoc Dunn’s multiple comparisons test. (<b>C</b>) Influence of the molecular subtype on the spleen weight. Kruskal–Wallis test. (<b>D</b>,<b>E</b>) Correlation analysis between the spleen weight and spleen infiltration (<b>D</b>) and spleen and bone marrow blast frequency (<b>E</b>). Each dot represents a single animal, and mice engrafted with the same patient material are displayed in the same color. Similar color shades indicate the same molecular subtype. Spearman’s correlation value r.</p>
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<p>Evaluation of tumor engraftment and growth kinetics. (<b>A</b>) Longitudinal quantification of the bioluminescence (full lines) and circulating blast frequency (dotted lines) of two representative animals. (<b>B</b>) Corresponding bioluminescence images of mice depicted in <a href="#cells-11-00150-f003" class="html-fig">Figure 3</a>A. (<b>C</b>) Influence of serial transplantation on the engraftment velocity. Samples with <span class="html-italic">BCR::ABL1</span>, <span class="html-italic">KMT2A</span> and T-ALL are painted in green, red and grey, respectively. Flow cytometric determination of the tumor cell frequency in peripheral blood was performed throughout the observation period. Each line represents an individual animal, and mice engrafted within the same passage are displayed in the same color. Earlier passages are depicted in darker colors. A line printed in bold indicates that the following passage was derived from the indicated animal. (<b>D</b>) Flow cytometric analysis of bone marrow (BM) and spleen infiltration upon termination of the experiment. Each dot represents an individual mouse. Mean ± standard deviation.</p>
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<p>Presence of single nucleotide variants in the <span class="html-italic">KMT2A</span>-positive primary samples and consecutive PDX passages. Only somatic or likely somatic variants detected using the Ion AmpliSeq™ Cancer Hotspot Panel v2 (Thermo Fisher Scientific) are summarized irrespectively of their pathogenicity. Two individual mice were analyzed in passage 2 of patients #0122 and #0134 and depicted by separate lines. Only cells from one of those mice were used for the subsequent xenografting to generate passage 3. P, passage.</p>
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