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Cells, Volume 8, Issue 10 (October 2019) – 191 articles

Cover Story (view full-size image): Hepatitis C virus (HCV) infection in human often causes liver fibrosis, although the virus does not replicate in hepatic stellate cells. Exosomes carry different biomolecules as cargo, including soluble and membrane-bound proteins, lipids, and nucleic acids. HCV-infected hepatocytes secrete exosomes for intercellular communication and play a role in the induction of liver fibrosis. Exosomes are easily uptaken by quiescent hepatic stellate cells. The exposure of biomolecules from internalized exosomes promotes activation of quiescent hepatic stellate cells which, in turn, leads to fibrosis. Other mechanisms also play an important role in establishing liver fibrosis. View this paper.
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14 pages, 3059 KiB  
Article
Dental Epithelial Stem Cells as a Source for Mammary Gland Regeneration and Milk Producing Cells In Vivo
by Lucia Jimenez-Rojo, Pierfrancesco Pagella, Hidemitsu Harada and Thimios A. Mitsiadis
Cells 2019, 8(10), 1302; https://doi.org/10.3390/cells8101302 - 22 Oct 2019
Cited by 9 | Viewed by 31879
Abstract
The continuous growth of rodent incisors is ensured by clusters of mesenchymal and epithelial stem cells that are located at the posterior part of these teeth. Genetic lineage tracing studies have shown that dental epithelial stem cells (DESCs) are able to generate all [...] Read more.
The continuous growth of rodent incisors is ensured by clusters of mesenchymal and epithelial stem cells that are located at the posterior part of these teeth. Genetic lineage tracing studies have shown that dental epithelial stem cells (DESCs) are able to generate all epithelial cell populations within incisors during homeostasis. However, it remains unclear whether these cells have the ability to adopt alternative fates in response to extrinsic factors. Here, we have studied the plasticity of DESCs in the context of mammary gland regeneration. Transplantation of DESCs together with mammary epithelial cells into the mammary stroma resulted in the formation of chimeric ductal epithelial structures in which DESCs adopted all the possible mammary fates including milk-producing alveolar cells. In addition, when transplanted without mammary epithelial cells, DESCs developed branching rudiments and cysts. These in vivo findings demonstrate that when outside their niche, DESCs redirect their fates according to their new microenvironment and thus can contribute to the regeneration of non-dental tissues. Full article
(This article belongs to the Special Issue Stem Cell Therapy in Oral and Maxillofacial Region)
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Figure 1
<p>Injection of DESCs and MECs into mammary fat pads results in the formation of a chimeric ductal epithelium. (<b>A</b>) GFP-DESCs and DsRed-mammary epithelial cells (MECs) were mixed and injected into the mammary fat pads of immunocompromised mice. (<b>B</b>) Before injecting them into the mammary microenvironment, DESCs expressed epithelial markers such as keratin 14 (Krt14) and E-cadherin (E-cad); the dental epithelial stem cell marker Sox2 and the incisor epithelium marker Islet1. (<b>C</b>–<b>K</b>) Whole mount fluorescent imaging of epithelial outgrowths from virgin (<b>C</b>–<b>H</b>) and pregnancy day 16.5 (<b>J</b>,<b>K</b>) chimeric mammary glands. Boxes in (<b>G</b>) and (<b>J</b>) represent the areas of high magnifications in (<b>H</b>) and (<b>K</b>), respectively. Scale bars: 25 μm (<b>B</b>); 2 mm (<b>C</b>,<b>J</b>); 400 μm (<b>D</b>–<b>I</b>,<b>K</b>). Abbreviations: cl, cervical loop; de, dental epithelium; DESCs, dental epithelial stem cells; dm, dental mesenchyme; fp, fat pad; me, mammary epithelium; MECs, mammary epithelial cells.</p>
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<p>DESCs give rise to different cell lineages of mammary epithelium. (<b>A</b>,<b>B</b>) Hematoxylin-eosin staining of the chimeric ducts (<b>A</b>) and schematic representation (<b>B</b>). (<b>C</b>–<b>N</b>) Double immunofluorescence against Krt14 and GFP (<b>C</b>,<b>D</b>,<b>F</b>,<b>G</b>,<b>I</b>,<b>J</b>) and against oestrogen receptor alpha (ERα) and GFP (<b>L</b>,<b>M</b>), and schematic representations of the various types of alveolar cells (<b>E</b>,<b>H</b>,<b>K</b>,<b>N</b>) showing the integration of GFP positive cells (DESC-derived) within the different compartments of the chimeric mammary ducts. Boxes in C,F,I,L represent high magnifications shown in D,G,J and M. (<b>O</b>–<b>R</b>) Immunofluorescent staining against GFP and β-casein. (<b>O</b>–<b>Q</b>) Single channels; (<b>R</b>) merged image. Scale bars: 50 μm (<b>A</b>); 40 μm (<b>C</b>,<b>F</b>,<b>I</b>,<b>L</b>); 10 μm (<b>D</b>,<b>G</b>,<b>J</b>,<b>M</b>); 20 μm (<b>O</b>–<b>R</b>). Abbreviation: ld, lipid droplet.</p>
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<p>Injection of DESCs alone in mammary fat pads. (<b>A</b>) GFP<sup>+</sup> DESCs injected alone in mammary fat pads managed to form epithelial branched structures (green colour). (<b>C</b>,<b>D</b>) Hematoxylin-eosin staining showing DESCs-originated ducts. Notice the presence of secretions within the ducts (asterisk in D). (<b>E</b>) Immunofluorescent staining showing that ducts are originated exclusively by GFP<sup>+</sup> DESCs (green colour). (<b>F</b>,<b>G</b>) Immunofluorescent staining showing Krt14-expressing myoepithelial cells (<b>F</b>) and Krt8-expressing luminal cells (<b>G</b>) originated from DESCs. (<b>H</b>–<b>J</b>) Immunofluorescent staining against GFP (green colour) and ERα (<b>H</b>), β-casein (<b>I</b>), or amelogenin (<b>J</b>; red colour). Arrowheads indicate double-positive cells for each combination of staining. (<b>K</b>–<b>M</b>) Fluorescent imaging (<b>K</b>), H and E staining (<b>L</b>), and immunofluorescent staining against GFP (<b>M</b>) showing cyst-like structures originated from DESCs. Scale bars: 400 μm (<b>B</b>,<b>K</b>), 100 μm (<b>C</b>–<b>E</b>,<b>H</b>–<b>J</b>,<b>L</b>,<b>M</b>); 50 μm (<b>F</b>,<b>G</b>). Abbreviations: le, luminal epithelium; m, myoepithelium.</p>
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<p>DESCs integrate in epithelial rudiments and potentially surrounding stroma. (<b>A</b>,<b>B</b>) Hematoxylin-eosin staining showing the formation of dense fibrotic tissue upon transplantation of DESCs. Black rectangular box in A indicates the region shown in B. Notice the presence of secretions within the ducts (asterisk in B). (<b>C</b>,<b>D</b>) Masson’s trichrome staining showing the composition of the fibrotic tissue surrounding the ducts. Black rectangular box in C indicates the region shown in D. (<b>E</b>,<b>F</b>) Double immunofluorescent staining against GFP and αSMA. White arrowheads indicate some of the double GFP<sup>+</sup>/α-SMA<sup>+</sup> cells. (<b>G</b>,<b>H</b>) Double immunofluorescent staining against GFP and Fibronectin. White arrowheads indicate double GFP<sup>+</sup>/Fibronectin<sup>+</sup> cells. Scale bars: 100 μm (<b>B</b>); 200 μm (<b>A</b>,<b>C</b>,<b>E</b>,<b>G</b>); 20 μm (<b>F</b>,<b>H</b>).</p>
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<p>Schematic representation recapitulating the experimental approach and the main results showing the plasticity of dental epithelial stem cells and their potential to adopt mammary epithelial cell fates.</p>
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19 pages, 3211 KiB  
Article
Invertebrate Retinal Progenitors as Regenerative Models in a Microfluidic System
by Caroline D. Pena, Stephanie Zhang, Robert Majeska, Tadmiri Venkatesh and Maribel Vazquez
Cells 2019, 8(10), 1301; https://doi.org/10.3390/cells8101301 - 22 Oct 2019
Cited by 12 | Viewed by 3982
Abstract
Regenerative retinal therapies have introduced progenitor cells to replace dysfunctional or injured neurons and regain visual function. While contemporary cell replacement therapies have delivered retinal progenitor cells (RPCs) within customized biomaterials to promote viability and enable transplantation, outcomes have been severely limited by [...] Read more.
Regenerative retinal therapies have introduced progenitor cells to replace dysfunctional or injured neurons and regain visual function. While contemporary cell replacement therapies have delivered retinal progenitor cells (RPCs) within customized biomaterials to promote viability and enable transplantation, outcomes have been severely limited by the misdirected and/or insufficient migration of transplanted cells. RPCs must achieve appropriate spatial and functional positioning in host retina, collectively, to restore vision, whereas movement of clustered cells differs substantially from the single cell migration studied in classical chemotaxis models. Defining how RPCs interact with each other, neighboring cell types and surrounding extracellular matrixes are critical to our understanding of retinogenesis and the development of effective, cell-based approaches to retinal replacement. The current article describes a new bio-engineering approach to investigate the migratory responses of innate collections of RPCs upon extracellular substrates by combining microfluidics with the well-established invertebrate model of Drosophila melanogaster. Experiments utilized microfluidics to investigate how the composition, size, and adhesion of RPC clusters on defined extracellular substrates affected migration to exogenous chemotactic signaling. Results demonstrated that retinal cluster size and composition influenced RPC clustering upon extracellular substrates of concanavalin (Con-A), Laminin (LM), and poly-L-lysine (PLL), and that RPC cluster size greatly altered collective migratory responses to signaling from Fibroblast Growth Factor (FGF), a primary chemotactic agent in Drosophila. These results highlight the significance of examining collective cell-biomaterial interactions on bio-substrates of emerging biomaterials to aid directional migration of transplanted cells. Our approach further introduces the benefits of pairing genetically controlled models with experimentally controlled microenvironments to advance cell replacement therapies. Full article
(This article belongs to the Special Issue Cell Biological Techniques and Cell-Biomaterial Interactions)
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<p><span class="html-italic">Drosophila melanogaster</span> model. (<b>A</b>) Image of third instar larva. (<b>B</b>) Dissected eye-brain complex with GFP+ glia (Scale bar: 100 µm). (<b>C</b>) Dissection arrangement via microscope within a laminar flow hood. (<b>D</b>) Schematic of key steps in the dissection process, where third instar larvae are segmented using tweezers, and mouth hooks with excess tissue are removed to isolate eye-brain complexes (green cartoon).</p>
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<p>Overview of the µLane system. (<b>A</b>) Schematic of microfluidic system comprised of two volumetric reservoirs connected by a 200-micron-diameter channel. (<b>B</b>) Image of fabricated device loaded with red dye. (<b>C</b>) The distribution of FGF concentration achieved within the µLane, normalized to the input concentration, Co. Transport within the µLane is defined by the convective-diffusion equation shown, where areas of mathematically-distinct changes in concentration gradients are defined along different lengths of the microchannel as marked: G<sub>1</sub>, G<sub>2</sub> and G<sub>3</sub>.</p>
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<p>Distributions of collective RPC clusters and individual cells post-dissection. Average surface areas of individually adhered cells and adhered RPC clusters of small and large size. A representative small cluster of approximately 3 cells is shown alongside a singleton cell to demonstrate consistency with the size and shape of single cells. Error bars the denote standard deviation.</p>
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<p>Average ratio of neuronal progenitors to total cells, R<sub>N</sub>, in third instar larvae. (<b>A</b>) Average ratio of neuronal cells to total cells (R<sub>N</sub>) in large clusters, small clusters and single cells, obtained from immunostaining. Error bars denote the standard deviation. (<b>B</b>,<b>C</b>) Representative confocal images of RFP+ neurons and GFP+ glia at mid-plane.</p>
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<p>Viability and adhesion of disassociated cells upon extracellular substrates. Primary RPCs upon (<b>A</b>) uncoated Petri dish, (<b>B</b>) Concanavalin A (Con-A) with neurite extensions highlighted by arrows, (<b>C</b>) Laminin (LM) with outlined RPC clusters and (<b>D</b>) Poly-L-Lysine (PLL) with both RPC clusters and neurite extensions highlighted. (<b>E</b>) Normalized cell viability at 24 h and 48 h time points. (<b>F</b>) Average RPC cluster surface area (RC SA) on Con-A, LM and PLL. (<b>G</b>) Average values of cell shape index (CSI) measured at 24 h time point for cells adhered on Con-A, LM and PLL. Error bars denote standard deviation. (Scale bar = 20 µm for all images.). Statistical significance (<span class="html-italic">p</span> &lt; 0.05) against control is denoted by *.</p>
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<p>Adhesion of retinal progenitor groups within the µLane system. The three populations of cells observed in suspension and on ECM-treated plates were also seen within the µLane system. Representative images of (<b>A</b>) Small RPC clusters and individual cells, (<b>B</b>) Large RPC clusters and individual cells and (<b>C</b>) Individual cells within the µLane system (Scale bar = 50 µm).</p>
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<p>Bee swarm plots of average path length and chemotactic index. (<b>A</b>) Average path length of single cells in control and gradient fields, G<sub>1</sub>, G<sub>2</sub> and G<sub>3.</sub> Statistical significance ** <span class="html-italic">p</span> &lt; 0.01 between control groups and experimental groups. (<b>B</b>) Average path length of small and large RPC clusters in control (i.e., Schneider’s medium only) and gradient fields, G<sub>1</sub>, G<sub>2</sub> and G<sub>3</sub>, generated within µLane. Statistical significance ** <span class="html-italic">p</span> &lt; 0.01 between control and experimental groups. Statistical significance * <span class="html-italic">p</span> &lt; 0.05 between medium and high gradient fields in large clusters. (<b>C</b>) Chemotactic index, CI, of single cells, small and large RPC clusters in control and gradient fields, G<sub>1</sub>, G<sub>2</sub> and G<sub>3.</sub> No statistical significance amongst groups for single cells. Statistical significance ** <span class="html-italic">p</span> &lt; 0.01 between control groups and experimental groups for RPC clusters.</p>
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10 pages, 1441 KiB  
Article
Association of the Rheumatoid Arthritis Severity Variant rs26232 with the Invasive Activity of Synovial Fibroblasts
by Emma R Dorris, Eimear Linehan, Michelle Trenkmann, Douglas J Veale, Ursula Fearon and Anthony G. Wilson
Cells 2019, 8(10), 1300; https://doi.org/10.3390/cells8101300 - 22 Oct 2019
Cited by 6 | Viewed by 3390
Abstract
rs26232, located in intron one of C5orf30, is associated with the susceptibility to and severity of rheumatoid arthritis (RA). Here, we investigate the relationship between this variant and the biological activities of rheumatoid arthritis synovial fibroblasts (RASFs). RASFs were isolated from the [...] Read more.
rs26232, located in intron one of C5orf30, is associated with the susceptibility to and severity of rheumatoid arthritis (RA). Here, we investigate the relationship between this variant and the biological activities of rheumatoid arthritis synovial fibroblasts (RASFs). RASFs were isolated from the knee joints of 33 RA patients. The rs26232 genotype was determined and cellular migration, invasion, and apoptosis were compared using in vitro techniques. The production of adhesion molecules, chemokines, and proteases was measured by ELISA or flow cytometry. Cohort genotypes were CC n = 16; CT n = 14; TT n = 3. In comparison with the RASFs of the CT genotype, the CC genotype showed a 1.48-fold greater invasiveness in vitro (p = 0.02), 1.6-fold higher expression intracellular adhesion molecule (ICAM)-1 (p = 0.001), and 5-fold IFN-γ inducible protein-10 (IP-10) (p = 0.01). There was no association of the rs26232 genotype with the expression levels of either total C5orf30 mRNA or any of the three transcript variants. The rs26232 C allele, which has previously been associated with both the risk and severity of RA, is associated with greater invasive activity of RASFs in vitro, and with higher expression of ICAM-1 and IP-10. In resting RASFs, rs26232 is not a quantitative trait locus for C5orf30 mRNA, indicating a more complex mechanism underlying the genotype‒phenotype relationship. Full article
(This article belongs to the Special Issue The Molecular and Cellular Basis for Rheumatoid Arthritis)
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<p>The rs26232 genotype is associated with RASF invasiveness. (<b>A</b>) Proliferation rates of RASFs are not associated with rs26232 genotype (<span class="html-italic">p</span> = 0.980). (<b>B</b>) The capacity for cells to migrate was not associated with genotype (<span class="html-italic">p</span> = 0.783). (<b>C</b>) RASF of the CC genotype are more invasive than CT (<span class="html-italic">p</span> = 0.020). Representative images of RASF in vitro (<b>D</b>) migration and (<b>E</b>) invasive assays of rs26232 genotypes. Each circle represents the average of an individual donor. Horizontal black bars represent the cohort mean. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 2
<p>The rs26232 genotype is associated with RASF expression of ICAM1, <span class="html-italic">MMP14</span> and IP-10. (<b>A</b>) Representative histogram showing ICAM-1 expression by RASFs of different rs26232 genotypes. (<b>B</b>) Expression of ICAM-1 protein is greater in RASFs of the CC compared to CT genotype (1.5-fold, <span class="html-italic">p</span> = 0.039). (<b>C</b>) ICAM1 relative gene expression is higher in CC compared to CT RASFs (2-fold, <span class="html-italic">p</span> = 0.044). (<b>D</b>) MMP14 relative gene expression is higher in CC compared to CT RASFs (1.6-fold, <span class="html-italic">p</span> = 0.021) (<b>E</b>) RASFs of CC genotype produce greater IP10 (CXCL10) compared to CT genotype (5-fold, <span class="html-italic">p</span> = 0.011). Each circle represents an individual donor. The black bar represents the mean. Statistical significance: * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 3
<p>rs26232 is not an eQTL for C5orf30. rs26232 genotype was not associated with (<b>A</b>) total C5orf30 mRNA (all variants) (<span class="html-italic">p</span> = 0.506), (<b>B</b>) variant 1 (<span class="html-italic">p</span> = 0.469), (<b>C</b>) variant 2 (<span class="html-italic">p</span> = 0.352), or (<b>D</b>) variant 3 (<span class="html-italic">p</span> = 0.482). Gene expression is analysed using relative quantitation (RQ) to the endogenous control HPRT1. <span class="html-italic">Y</span>-axis is mean Log<sub>2</sub> transformed RQ values per patient RASF line. Each circle represents the average of an individual donor. Horizontal black bars represent the cohort mean.</p>
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17 pages, 2820 KiB  
Article
Opposite Effects of Moderate and Extreme Cx43 Deficiency in Conditional Cx43-Deficient Mice on Angiotensin II-Induced Cardiac Fibrosis
by Laura Valls-Lacalle, Corall Negre-Pujol, Cristina Rodríguez, Saray Varona, Antoni Valera-Cañellas, Marta Consegal, Jose Martínez-González and Antonio Rodríguez-Sinovas
Cells 2019, 8(10), 1299; https://doi.org/10.3390/cells8101299 - 22 Oct 2019
Cited by 14 | Viewed by 4568
Abstract
Connexin 43 (Cx43) is essential for cardiac electrical coupling, but its effects on myocardial fibrosis is controversial. Here, we analyzed the role of Cx43 in myocardial fibrosis caused by angiotensin II (AngII) using Cx43fl/fl and Cx43Cre-ER(T)/fl inducible knock-out (Cx43 content: 50%) [...] Read more.
Connexin 43 (Cx43) is essential for cardiac electrical coupling, but its effects on myocardial fibrosis is controversial. Here, we analyzed the role of Cx43 in myocardial fibrosis caused by angiotensin II (AngII) using Cx43fl/fl and Cx43Cre-ER(T)/fl inducible knock-out (Cx43 content: 50%) mice treated with vehicle or 4-hydroxytamoxifen (4-OHT) to induce a Cre-ER(T)-mediated global deletion of the Cx43 floxed allele. Myocardial collagen content was enhanced by AngII in all groups (n = 8–10/group, p < 0.05). However, animals with partial Cx43 deficiency (vehicle-treated Cx43Cre-ER(T)/fl) had a significantly higher AngII-induced collagen accumulation that reverted when treated with 4-OHT, which abolished Cx43 expression. The exaggerated fibrotic response to AngII in partially deficient Cx43Cre-ER(T)/fl mice was associated with enhanced p38 MAPK activation and was not evident in Cx43 heterozygous (Cx43+/-) mice. In contrast, normalization of interstitial collagen in 4-OHT-treated Cx43Cre-ER(T)/fl animals correlated with enhanced MMP-9 activity, IL-6 and NOX2 mRNA expression, and macrophage content, and with reduced α-SMA and SM22α in isolated fibroblasts. In conclusion, our data demonstrates an exaggerated, p38 MAPK-dependent, fibrotic response to AngII in partially deficient Cx43Cre-ER(T)/fl mice, and a paradoxical normalization of collagen deposition in animals with an almost complete Cx43 ablation, an effect associated with increased MMP-9 activity and inflammatory response and reduced fibroblasts differentiation. Full article
(This article belongs to the Special Issue Cells in Cardiovascular Disease)
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Figure 1
<p>AngII treatment induces a similar cardiac hypertrophic response in hearts from Cx43<sup>fl/fl</sup> and Cx43<sup>Cre-ER(T)/fl</sup> mice, independently of Cx43 expression levels. Changes in cardiac weight/body weight (CW/BW) ratio (<b>a</b>) and cardiomyocyte cross-sectional area (<b>b</b>) in Cx43<sup>fl/fl</sup> (fl/fl) and Cx43<sup>Cre-ER(T)/fl</sup> (Cre/fl) mice, treated with saline or angiotensin II for 14 days. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. the corresponding saline-treated group. (<b>c</b>–<b>g</b>) Changes in left ventricular posterior wall thickness (LVPW), interventricular septum thickness (IVS), left ventricular end-diastolic internal diameter (LVEDD), left ventricular end-systolic internal diameter (LVESD) (all expressed vs. body weight), and ejection fraction (EF) in the same animals. Data from saline-treated animals are shown pooled as a single group. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. all groups except Cx43<sup>fl/fl</sup> +4-OHT + AngII and Cx43<sup>fl/fl</sup> + oil + AngII in C and D, respectively. (<b>h</b>) Changes in myocardial ANP mRNA. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. the corresponding saline-treated group.</p>
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<p>Cardiac fibrosis induced by AngII in Cx43<sup>Cre-ER(T)/fl</sup> and Cx43<sup>+/-</sup> mice. Representative images (upper panels) and mean quantification (lower graphs) of interstitial collagen deposition, expressed as percentage of total myocardial area, in Cx43<sup>fl/fl</sup> ((<b>a</b>) fl/fl) and Cx43<sup>Cre-ER(T)/fl</sup> ((<b>b</b>) Cre/fl) mice, after treatment, for 14 days, with saline or AngII. Bar represents 50 μm. (<b>c</b>) shows changes in fibrosis in wild-type and Cx43<sup>+/-</sup> animals. The approximate amount of Cx43 expression is indicated, in parenthesis, below the name of each group. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. the corresponding saline-treated group. τ (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. all Cx43<sup>fl/fl</sup> or Cx43<sup>Cre-ER(T)/fl</sup> AngII-treated animals.</p>
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<p>Expression of mRNAs coding for proteins involved in collagen turnover in AngII-treated Cx43<sup>Cre-ER(T)/fl</sup> mice. Levels of mRNAs coding for proteins involved in collagen synthesis (COL1A1, P4HA1) (<b>a</b>–<b>c</b>), maturation (LOX) (<b>d</b>) and degradation (TIMP1, TIMP2) (<b>e</b>–<b>f</b>), expressed as percentage vs. Cx43<sup>fl/fl</sup> + oil mice treated with saline, in both wild-type (Cx43<sup>fl/fl</sup>, fl/fl) and Cx43-deficient mice (Cre/fl), implanted with osmotic pumps containing saline or AngII. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. the corresponding saline-treated group. # (<span class="html-italic">p</span> &lt; 0.05) shows significant differences vs. Cx43<sup>fl/fl</sup> mice injected with oil and implanted with saline-filled pumps.</p>
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<p>Enhanced collagen deposition in Cx43<sup>Cre-ER(T)/fl</sup> + oil mice treated with AngII correlates with increased p38 MAPK activation. Expression and degree of activation of p38 MAPK in myocardial samples from Cx43<sup>fl/fl</sup> (fl/fl) and Cx43<sup>Cre-ER(T)/fl</sup> (Cre/fl) mice (<b>a</b>) and from wild-type (WT) and Cx43<sup>+/-</sup> animals. (<b>b</b>) Upper panels show representative Western blots, whereas middle and bottom panels show degree of activation and total protein levels, respectively. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. the corresponding control Cx43<sup>fl/fl</sup> group. (<b>c</b>) Interstitial collagen, expressed as percentage of total myocardial area, in hearts from Cx43<sup>Cre-ER(T)/fl</sup> mice treated with oil and infused, for 14 days, with saline, AngII, or AngII plus the p38 MAPK inhibitor SB203580 (10 mg/Kg/day). (<b>d</b>) Changes in cardiac weight/body weight (CW/BW) ratio in the same animals. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. remaining groups.</p>
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<p>Normalization of collagen deposition in Cx43<sup>Cre-ER(T)/fl</sup> mice treated with 4-OHT and infused with AngII correlates with increased MMP9 activity. Representative gelatin zymography (upper panel) showing MMP2 and MMP9 enzymatic activity in myocardial samples from saline- and AngII-treated Cx43<sup>fl/fl</sup> (fl/fl) and Cx43<sup>Cre-ER(T)/fl</sup> (Cre/fl) mice. Lower panels show mean quantification of 6 different experiments. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. corresponding the Cx43<sup>fl/fl</sup> + oil group.</p>
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<p>Altered phenotype and expression of differentiation markers in isolated cardiac fibroblasts from Cx43<sup>fl/fl</sup> and Cx43<sup>Cre-ER(T)/fl</sup> mice. (<b>a</b>) Upper images show morphology of cardiac fibroblasts isolated from control hearts from the four groups of animals. (<b>b</b>) Representative Western blots for Cx43, αSMA and SM22α, and total protein expression of analyzed proteins, in fibroblasts isolated from hearts from Cx43<sup>fl/fl</sup> (fl/fl) and Cx43<sup>Cre-ER(T)/fl</sup> (Cre/fl) mice. * (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. Cx43<sup>fl/fl</sup> + oil animals. τ (<span class="html-italic">p</span> &lt; 0.05) indicates significant differences vs. Cx43<sup>Cre/fl</sup> + oil animals.</p>
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<p>Expression of inflammatory markers in saline- and AngII-treated Cx43<sup>fl/fl</sup> and Cx43<sup>Cre-ER(T)/fl</sup> mice. Levels of mRNAs coding for IL-6 (<b>a</b>) and NOX2 (<b>b</b>), expressed as percentage vs. Cx43<sup>fl/fl</sup> +oil mice treated with saline, in both Cx43<sup>fl/fl</sup> (fl/fl) and Cx43-deficient mice (Cre/fl), implanted with osmotic pumps containing saline or AngII. # (<span class="html-italic">p</span> &lt; 0.05) shows significant differences vs. Cx43<sup>fl/fl</sup> mice injected with oil and infused with saline. (<b>c–d</b>) Immunohistochemical images of myocardial sections incubated with LAMP-2/Mac-3 (<b>c</b>) or MMP9 (<b>d</b>) antibodies. Bar represents 50 μm.</p>
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17 pages, 5279 KiB  
Article
MicroRNA-29a Suppresses CD36 to Ameliorate High Fat Diet-Induced Steatohepatitis and Liver Fibrosis in Mice
by Hung-Yu Lin, Feng-Sheng Wang, Ya-Ling Yang and Ying-Hsien Huang
Cells 2019, 8(10), 1298; https://doi.org/10.3390/cells8101298 - 22 Oct 2019
Cited by 77 | Viewed by 8075
Abstract
MicroRNA-29 (miR-29) has been shown to play a critical role in reducing inflammation and fibrosis following liver injury. Non-alcoholic fatty liver disease (NAFLD) occurs when fat is deposited (steatosis) in the liver due to causes other than excessive alcohol use and is associated [...] Read more.
MicroRNA-29 (miR-29) has been shown to play a critical role in reducing inflammation and fibrosis following liver injury. Non-alcoholic fatty liver disease (NAFLD) occurs when fat is deposited (steatosis) in the liver due to causes other than excessive alcohol use and is associated with liver fibrosis. In this study, we asked whether miR-29a could reduce experimental high fat diet (HFD)-induced obesity and liver fibrosis in mice. We performed systematical expression analyses of miR-29a transgenic mice (miR-29aTg mice) and wild-type littermates subjected to HFD-induced NAFLD. The results demonstrated that increased miR-29a not only alleviated HFD-induced body weight gain but also subcutaneous, visceral, and intestinal fat accumulation and hepatocellular steatosis in mice. Furthermore, hepatic tissue in the miR-29aTg mice displayed a weak fibrotic matrix concomitant with low fibrotic collagen1α1 expression within the affected tissues compared to the wild-type (WT) mice fed the HFD diet. Increased miR-29a signaling also resulted in the downregulation of expression of the epithelial mesenchymal transition-executing transcription factor snail, mesenchymal markers vimentin, and such pro-inflammation markers as il6 and mcp1 within the liver tissue. Meanwhile, miR-29aTg-HFD mice exhibited significantly lower levels of peroxisome proliferator-activated receptor γ (PPARγ), mitochondrial transcription factor A TFAM, and mitochondria DNA content in the liver than the WT-HFD mice. An in vitro luciferase reporter assay further confirmed that miR-29a mimic transfection reduced fatty acid translocase CD36 expression in HepG2 cells. Conclusion: Our data provide new insights that miR-29a can improve HDF-induced obesity, hepatocellular steatosis, and fibrosis, as well as highlight the role of miR-29a in regulation of NAFLD. Full article
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Graphical abstract

Graphical abstract
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<p>Overexpression of miR-29a reduces weight gain, but has no effect on physical activity in the context of chronic high fat diet (HFD). Weight gain and physical activity of wild type and miR-29aTg mice fed a chow or high-fat diet for 12 months were measured, including (<b>A</b>) body weight, (<b>B</b>) frequency rearing stand, and (<b>C</b>) moving distance documented using a 30 × 30 cm open field box in ten minutes. Data calculated from five to ten mice per group are expressed as mean ± SE. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 between the indicated groups. WT, wild type mice. HFD, high-fat diet. miR-29a, mice harboring overexpression of miR-29a.</p>
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<p>Overexpression of miR-29a significantly reduces fat accumulation in adipose tissue and liver weight in the context of chronic HFD. Various tissue parts were dissected and weighed immediately after sacrifice, with weight of (<b>A</b>) subcutaneous, (<b>B</b>) visceral, (<b>C</b>) intestinal fat tissue, and (<b>D</b>) liver. Data calculated from seven to ten mice per group are expressed as mean ± SE. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 between the indicated groups. WT, wild type mice. HFD, high-fat diet. miR-29a, mice harboring overexpression of miR-29a.</p>
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<p>Overexpression of miR-29a reduces hepatocellular steatosis in the context of chronic HFD. Paraformaldehyde-fixed paraffin-embedded liver tissue was used to determine the abundance of lipid droplets with hematoxylin-eosin (HE) stain. (<b>A</b>) Representative HE stain image of each group. (<b>B</b>) Lipid droplet area quantified using ImageJ. Data collected from three fields of view of each specimen and six to nine specimens for each group are expressed as mean ± SE. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 between the indicated groups. WT, wild type mice. HFD, high-fat diet. miR-29a, mice harboring overexpression of miR-29a.</p>
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<p>Overexpression of miR-29a reduces liver fibrosis in the context of chronic HFD. Paraformaldehyde-fixed paraffin-embedded liver tissue was used to determine collagen fiber accumulation using Mason’s trichrome stain. Liver tissue stored at −80 ℃ was used for RNA and protein extraction for subsequent qPCR and Western blot experiments, respectively. (<b>A</b>) Representative Masson’s trichrome stain image of each group. Blue color indicates positive signal of collagen fiber. (<b>B</b>) Positive signal percentage quantified using ImageJ. (<b>C</b>) mRNA expression level of <span class="html-italic">col1</span><span class="html-italic">α1</span>, with <span class="html-italic">β-actin</span> level as normalization control. (<b>D</b>) Representative immunoblotting bands of COL1α1 protein abundance and densitometric results, with glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as the loading control. For the imaging study, data were collected from five fields of view of each specimen and five to eight specimens for each group. For qPCR and Western blot, five to seven specimens were used for each group. Data are expressed as mean ± SE. * <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 between the indicated groups. WT, wild type mice. HFD, high-fat diet. miR-29a, mice harboring overexpression of miR-29a.</p>
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<p>Overexpression of miR-29a represses hepatic epithelial-mesenchymal transition and inflammation in the context of chronic HFD. mRNA expression level of (<b>A</b>) vimentin, (<b>B</b>) snail, (<b>C</b>) mcp1, and (<b>D</b>) il6. <span class="html-italic">β-actin</span> level is used as the normalization control. Five to seven specimens were used for each group. Data are expressed as mean ± SE. * <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 between the indicated groups. WT, wild type mice. HFD, high-fat diet. miR-29a, mice harboring overexpression of miR-29a.</p>
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<p>Overexpression of miR-29a modulates HFD-caused perturbation of mitochondrial biogenesis in the liver. Representative immunoblotting bands and densitometric results of (<b>A</b>) peroxisome proliferator-activated receptor γ (PPARγ) and (<b>B</b>) mitochondrial transcription factor A (TFAM), using GAPDH as the loading control. (<b>C</b>) mtDNA copy number per cell probed using qPCR, with <span class="html-italic">TERT</span> as the normalization control. Five to ten specimens were used for each group. Data are expressed as mean ± SE. * <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 between the indicated groups. WT, wild type mice. HFD, high-fat diet. miR-29a, mice harboring overexpression of miR-29a.</p>
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<p>MiR-29a inhibits the expression of fatty acid translocase CD36 by targeting 3’ untranslated region (UTR). (<b>A</b>) qPCR analysis of Cd36 in live tissue. (<b>B</b>) Representative immunoblotting bands and densitometric results of CD36 in liver tissue. (<b>C</b>) qPCR analysis of <span class="html-italic">cd36</span> expression of HepG2 cells in vitro after 48h transfection of scramble sequence or miR-29a-mimic. Data obtained from six independent experiments. (<b>D</b>) Upper panel, sequence information, and mutual pairing status of CD36-3’UTR, mmu-miR29a, and CD36-3’UTR Mut. Note that red characters represent mismatching sites. HepG2 was first transfected with CD36-3’UTR or CD36-3’UTR mutant luciferase reporter construct then treated with control medium (ctrl), miRNA-scramble, or miR-29a mimic, and finally lysed to detect the luciferase signal. Data are expressed as mean ± SE. * <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 between the indicated groups. WT, wild type mice. HFD, high-fat diet. miR-29a, mice harboring overexpression of miR-29a. mmu-miR29a, mouse-origin miR-29a. ctrl, control. Mut, mutant. UTR, untranslated region.</p>
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<p>The proposed model of miR-29a exerting a protective effect by targeting CD36 and modulating downstream signaling pathway in HFD-elicited liver fibrosis. HFD causes considerable fatty acid influx into the liver, leading to the up-regulation of PPARγ, TFAM, and mtDNA content. MtDNA and mitochondrial-derived reactive oxygen species can initiate an inflammatory response, leading to the release of such pro-inflammatory cytokines as MCP-1 and IL-6. Chronic inflammation is a stimulator for EMT, which is characterized by the up-regulation of typical makers like snail and vimentin. Activation of EMT facilitates the transformation of hepatic stellate cells to myofibroblasts, contributing to the progression of liver fibrosis. Of particular note, miR-29a can exert an anti-NAFLD effect by targeting CD36 3’UTR and repressing its expression, which may decrease intracellular fatty acid influx, subsequently reducing the up-regulation of PPARγ, TFAM, and mtDNA content, modulating downstream inflammatory response and EMT, and ultimately mitigating liver fibrosis.</p>
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26 pages, 7021 KiB  
Article
Inhibition of Non-Small Cell Lung Cancer Cells by Oxy210, an Oxysterol-Derivative that Antagonizes TGFβ and Hedgehog Signaling
by Frank Stappenbeck, Feng Wang, Liu-Ya Tang, Ying E. Zhang and Farhad Parhami
Cells 2019, 8(10), 1297; https://doi.org/10.3390/cells8101297 - 22 Oct 2019
Cited by 14 | Viewed by 5193
Abstract
Non-Small Cell Lung Cancer (NSCLC) is a common malignancy and leading cause of death by cancer. Metastasis and drug resistance are serious clinical problems encountered in NSCLC therapy. Aberrant activation of the Transforming Growth Factor beta (TGFβ) and Hedgehog (Hh) signal transduction cascades [...] Read more.
Non-Small Cell Lung Cancer (NSCLC) is a common malignancy and leading cause of death by cancer. Metastasis and drug resistance are serious clinical problems encountered in NSCLC therapy. Aberrant activation of the Transforming Growth Factor beta (TGFβ) and Hedgehog (Hh) signal transduction cascades often associate with poor prognosis and aggressive disease progression in NSCLC, as these signals can drive cell proliferation, angiogenesis, metastasis, immune evasion and emergence of drug resistance. Therefore, simultaneous inhibition of TGFβ and Hh signaling, by a single agent, or in combination with other drugs, could yield therapeutic benefits in NSCLC and other cancers. In the current study, we report on the biological and pharmacological evaluation of Oxy210, an oxysterol-based dual inhibitor of TGFβ and Hh signaling. In NSCLC cells, Oxy210 inhibits proliferation, epithelial-mesenchymal transition (EMT) and invasive activity. Combining Oxy210 with Carboplatin (CP) increases the anti-proliferative response to CP and inhibits TGFβ-induced resistance to CP in A549 NSCLC cells. In addition, Oxy210 displays encouraging drug-like properties, including chemical scalability, metabolic stability and oral bioavailability in mice. Unlike other known inhibitors, Oxy210 antagonizes TGFβ and Hh signaling independently of TGFβ receptor kinase inhibition and downstream of Smoothened, respectively. Full article
(This article belongs to the Special Issue Hedgehog Signaling in Development and Cancer)
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Figure 1
<p>The molecular structures of Cholesterol, Oxy8, Oxy133, Oxy16, Oxy186 and Oxy210.</p>
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<p>Ortep representation of Oxy210 in the solid state.</p>
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<p>Ortep representation of Oxy16 in the solid state.</p>
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<p>Inhibition of ligand-induced Hedgehog and TGFβ signaling in mouse fibroblast cells. NIH3T3 cells were pretreated for 2 h with Oxy210 or various inhibitors as indicated in DMEM containing 5% FBS. Next, cells were treated with CAPAN-1 conditioned medium (CM) in the absence or presence of oxysterols or inhibitors. After 72 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of Hh target genes <span class="html-italic">Gli1</span> and <span class="html-italic">Ptch1</span> and normalized to Oaz1 expression (<b>a</b>,<b>b</b>). (<b>c</b>,<b>e</b>) NIH3T3 cells were treated in DMEM containing 0.1% BCS overnight and then pretreated for 2 h with the inhibitors as indicated in DMEM containing 0.1%BCS. The cells were then treated with TGFβ (20ng/mL) in the absence or presence of the compounds. After 48 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of TGFβ target genes as indicated and normalized to Oaz1 expression. (<b>d</b>) NIH3T3 cells cultured in 24 well-plates were transfected with a Smad response element reporter (SBE-Luciferase) plasmid and a pTK-Renilla-Luciferase plasmid. 6 hrs after transfection, cells were treated with the test agents as indicated for 48 hrs. Luciferase activity was measured and normalized to the Renilla luciferase activity. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. CM (<b>a</b>,<b>b</b>) or TGFβ (<b>c</b>,<b>d</b> and <b>e</b>) treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Inhibition of ligand-induced Hedgehog and TGFβ signaling in mouse fibroblast cells. NIH3T3 cells were pretreated for 2 h with Oxy210 or various inhibitors as indicated in DMEM containing 5% FBS. Next, cells were treated with CAPAN-1 conditioned medium (CM) in the absence or presence of oxysterols or inhibitors. After 72 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of Hh target genes <span class="html-italic">Gli1</span> and <span class="html-italic">Ptch1</span> and normalized to Oaz1 expression (<b>a</b>,<b>b</b>). (<b>c</b>,<b>e</b>) NIH3T3 cells were treated in DMEM containing 0.1% BCS overnight and then pretreated for 2 h with the inhibitors as indicated in DMEM containing 0.1%BCS. The cells were then treated with TGFβ (20ng/mL) in the absence or presence of the compounds. After 48 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of TGFβ target genes as indicated and normalized to Oaz1 expression. (<b>d</b>) NIH3T3 cells cultured in 24 well-plates were transfected with a Smad response element reporter (SBE-Luciferase) plasmid and a pTK-Renilla-Luciferase plasmid. 6 hrs after transfection, cells were treated with the test agents as indicated for 48 hrs. Luciferase activity was measured and normalized to the Renilla luciferase activity. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. CM (<b>a</b>,<b>b</b>) or TGFβ (<b>c</b>,<b>d</b> and <b>e</b>) treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Inhibition of ligand-induced Hedgehog and TGFβ signaling in mouse fibroblast cells. NIH3T3 cells were pretreated for 2 h with Oxy210 or various inhibitors as indicated in DMEM containing 5% FBS. Next, cells were treated with CAPAN-1 conditioned medium (CM) in the absence or presence of oxysterols or inhibitors. After 72 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of Hh target genes <span class="html-italic">Gli1</span> and <span class="html-italic">Ptch1</span> and normalized to Oaz1 expression (<b>a</b>,<b>b</b>). (<b>c</b>,<b>e</b>) NIH3T3 cells were treated in DMEM containing 0.1% BCS overnight and then pretreated for 2 h with the inhibitors as indicated in DMEM containing 0.1%BCS. The cells were then treated with TGFβ (20ng/mL) in the absence or presence of the compounds. After 48 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of TGFβ target genes as indicated and normalized to Oaz1 expression. (<b>d</b>) NIH3T3 cells cultured in 24 well-plates were transfected with a Smad response element reporter (SBE-Luciferase) plasmid and a pTK-Renilla-Luciferase plasmid. 6 hrs after transfection, cells were treated with the test agents as indicated for 48 hrs. Luciferase activity was measured and normalized to the Renilla luciferase activity. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. CM (<b>a</b>,<b>b</b>) or TGFβ (<b>c</b>,<b>d</b> and <b>e</b>) treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Oxy210 acts downstream of Smo. (<b>a</b>) Sufu-/- MEF cells were treated with DMEM containing 5% FBS in the presence or absence of Oxy210. After 72 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of Hh target genes Gli1 and Hip, normalized to Oaz1 expression. (<b>b</b>) Sufu-/- cells cultured in 24 well-plate were transfected with a Gli response-element reporter (pGL3b-8xGliBS-Luciferase) plasmid and a pSV40-Renilla-Luciferase plasmid. 6 hrs after transfection, cells were treated with the compounds as indicated for 72 hrs. Luciferase activity was measured and normalized to the Renilla luciferase activity. (<b>c</b>) NIH3T3 cells cultured in 24 well-plate were transfected with a Gli response-element reporter (pGL3b-8xGliBS-Luciferase) plasmid, a pSV40-Renilla-Luciferase plasmid and a vector expressing Gli1, pSRa-Gli1. 6 h after transfection, cells were treated with the test agents as indicated for 72 hrs. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (* <span class="html-italic">p</span> &lt; 0.05 vs. DMSO or control; ** <span class="html-italic">p</span> &lt; 0.01 vs. DMSO or control).</p>
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<p>Inhibition of Glis and SHH expression in Non-Small Cell Lung Cancer (NSCLC) cells. A549 (<b>a</b>) and H2030 (<b>b</b>) cells were treated with Oxy210 in RPMI 1640 containing 5% FBS for 72 h, then RNA was extracted and analyzed by Q-RT-PCR for the expression of the indicated genes and normalized to <span class="html-italic">GAPDH</span> expression. (<b>c</b>) A549 cells were pretreated for 2 h with Oxy210 in RPMI 1640 containing 5% FBS. Next, cells were treated with TGFβ (10 ng/mL) in the absence or presence of Oxy210. After 48 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of <span class="html-italic">Gli1</span> and <span class="html-italic">Shh</span> and normalized to <span class="html-italic">GAPDH</span> expression. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Inhibition of Glis and SHH expression in Non-Small Cell Lung Cancer (NSCLC) cells. A549 (<b>a</b>) and H2030 (<b>b</b>) cells were treated with Oxy210 in RPMI 1640 containing 5% FBS for 72 h, then RNA was extracted and analyzed by Q-RT-PCR for the expression of the indicated genes and normalized to <span class="html-italic">GAPDH</span> expression. (<b>c</b>) A549 cells were pretreated for 2 h with Oxy210 in RPMI 1640 containing 5% FBS. Next, cells were treated with TGFβ (10 ng/mL) in the absence or presence of Oxy210. After 48 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of <span class="html-italic">Gli1</span> and <span class="html-italic">Shh</span> and normalized to <span class="html-italic">GAPDH</span> expression. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Inhibition of NSCLC cell proliferation by Oxy210. A549 (<b>a</b>), (<b>c</b>) and H2030 (<b>b</b>) cells were treated with the test agents as indicated in RPMI 1640 containing 5% FBS for 5 days and then were trypsinized and counted as described in Methods and Materials section. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (* <span class="html-italic">p</span> &lt; 0.05 vs. control; ** <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Inhibition of TGFβ-induced EMT in NSCLC cells. (<b>a</b>) A549 cells were treated with TGFβ in the absence or presence of Oxy210 in RPMI 1640 containing 2% FBS for 5 days. The cells were washed with PBS and then fixed with 2% formaldehyde in PBS at room temperature for 15 min. Formaldehyde was then removed, cells washed with PBS and stained with 4% Trypan Blue for 5 min. Phase contrast images were obtained using a 20X objective lens. A549 (<b>b</b>,<b>c</b>) and H2030 (<b>d</b>) cells were treated in RPMI 1640 containing 0.1% FBS overnight and then pretreated for 2 h with Oxy210 in RPMI 1640 containing 0.1% FBS. Next, cells were treated with TGFβ in the absence or presence of Oxy210. After 48 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of the genes as indicated and normalized to <span class="html-italic">GAPDH</span> expression. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Inhibition of TGFβ-induced EMT in NSCLC cells. (<b>a</b>) A549 cells were treated with TGFβ in the absence or presence of Oxy210 in RPMI 1640 containing 2% FBS for 5 days. The cells were washed with PBS and then fixed with 2% formaldehyde in PBS at room temperature for 15 min. Formaldehyde was then removed, cells washed with PBS and stained with 4% Trypan Blue for 5 min. Phase contrast images were obtained using a 20X objective lens. A549 (<b>b</b>,<b>c</b>) and H2030 (<b>d</b>) cells were treated in RPMI 1640 containing 0.1% FBS overnight and then pretreated for 2 h with Oxy210 in RPMI 1640 containing 0.1% FBS. Next, cells were treated with TGFβ in the absence or presence of Oxy210. After 48 h, RNA was extracted and analyzed by Q-RT-PCR for the expression of the genes as indicated and normalized to <span class="html-italic">GAPDH</span> expression. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Inhibition of TGFβ-induced invasive activity of A549 cells. In vitro invasion assays were performed using chambers with matrigel-coated membrane as described in the Materials and Methods section. (<b>a</b>) Images of invaded cells on the membranes. (<b>b</b>) Quantitative analysis of invasion of A549 cells induced by TGFβ in the absence or presence of Oxy210. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. control).</p>
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<p>Effect of Oxy210 on TGFβ-induced resistance to carboplatin. A549 cells were treated with the agents as indicated (in front of --) in RPMI 1640 containing 2% FBS for 3 days, and then treated with the agents as indicated (after --) for 4 days. The cells were then trypsinized and counted. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (## <span class="html-italic">p</span> &lt; 0.01 vs. Control--Control; ++ <span class="html-italic">p</span> &lt; 0.01 vs. Control--CP; ** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ--CP).</p>
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<p>Inhibition of TGFβ-induced Smad2/3 phosphorylation and transcriptional activity. (<b>a</b>) Western blot analysis of A549 cells. Cells were pretreated with DMSO, Oxy186 or Oxy210 for 3 h, then treated with TGFβ (4 ng/mL) for the indicated times. (<b>b</b>) Kinase assay was performed as described in Materials and Methods with the agents as indicated. (<b>c</b>) TGFβRI-deficient R1BL17 cells were transfected with TGFβRI plasmid (WT or TD mutant), Smad responsive luciferase reporter (CAGA12-Luc), and pTK-Renilla-Luciferase plasmid. Twenty-four hours after transfection, cells were treated with the test agents as indicated for 20 hrs. Luciferase activity was measured and normalized to the Renilla luciferase activity. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. DMSO; ++ <span class="html-italic">p</span> &lt; 0.01 vs. Control).</p>
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<p>Inhibition of TGFβ-induced Smad2/3 phosphorylation and transcriptional activity. (<b>a</b>) Western blot analysis of A549 cells. Cells were pretreated with DMSO, Oxy186 or Oxy210 for 3 h, then treated with TGFβ (4 ng/mL) for the indicated times. (<b>b</b>) Kinase assay was performed as described in Materials and Methods with the agents as indicated. (<b>c</b>) TGFβRI-deficient R1BL17 cells were transfected with TGFβRI plasmid (WT or TD mutant), Smad responsive luciferase reporter (CAGA12-Luc), and pTK-Renilla-Luciferase plasmid. Twenty-four hours after transfection, cells were treated with the test agents as indicated for 20 hrs. Luciferase activity was measured and normalized to the Renilla luciferase activity. Data from a representative experiment are reported as the mean of triplicate determinations ± SD (** <span class="html-italic">p</span> &lt; 0.01 vs. TGFβ treated cells; ## <span class="html-italic">p</span> &lt; 0.01 vs. DMSO; ++ <span class="html-italic">p</span> &lt; 0.01 vs. Control).</p>
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<p>Conformational properties of Oxy186 and Oxy210 (<b>a</b>) The molecular structures of Oxy186 and Oxy210 and an overlay of their crystal structures. A structure alignment algorithm (Mercury, The Cambridge Crystallographic Data Centre) determined the minimal root mean square deviation (RMSD) of atomic positions in the overlay to equal 0.221 Å. (<b>b</b>) Varying the substitution pattern and stereochemical configuration of the C17–C20 bond, can result in a preference for either an extended or bent conformation of the ‘Large’ substituent, usually the sterol side, with respect to the tetracyclic sterol core.</p>
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<p>Drug-like properties of Oxy210. (<b>a</b>) A single dose of Oxy210 at 50 mg/kg, formulated in 3% DMSO + 7% Ethanol + 5% PEG400 + 85% corn oil, was administered to balb/c mice by oral gavage. Plasma samples were taken at 10 min, 30 min, 1h, 2h, 4h, 6h, and 8h, followed by LC/MS analysis of the plasma. (<b>b</b>) Evolution of Oxy210 and Oxy186 from parent compound Oxy16 and their drug-like properties.</p>
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<p>Synthesis of Oxy210.</p>
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19 pages, 3017 KiB  
Article
Hepatitis C Virus Improves Human Tregs Suppressive Function and Promotes Their Recruitment to the Liver
by Laurissa Ouaguia, Olivier Moralès, Lynda Aoudjehane, Czeslaw Wychowski, Abhishek Kumar, Jean Dubuisson, Yvon Calmus, Filomena Conti and Nadira Delhem
Cells 2019, 8(10), 1296; https://doi.org/10.3390/cells8101296 - 22 Oct 2019
Cited by 10 | Viewed by 3457
Abstract
Background: The role of regulatory T cells (Tregs) is now well established in the progression of hepatocellular carcinoma (HCC) linked to Hepatitis C virus (HCV) infection. However, nothing is known about the potential interplay between Tregs and HCV. In this pilot study, we [...] Read more.
Background: The role of regulatory T cells (Tregs) is now well established in the progression of hepatocellular carcinoma (HCC) linked to Hepatitis C virus (HCV) infection. However, nothing is known about the potential interplay between Tregs and HCV. In this pilot study, we have investigated the ability of Tregs to hang HCV on and the subsequent effect on their suppressive function and phenotype. Moreover, we have evaluated how HCV could promote the recruitment of Tregs by infected primary human hepatocytes. Methods: Tregs of healthy donors were incubated with JFH-1/HCVcc. Viral inoculation was assessed using adapted assays (RT-qPCR, Flow Citometry (FACS) and Western Blot (WB). Expression of Tregs phenotypic (CD4, CD25, CD127 and Foxp3) and functional (IL-10, GZMB, TGF-β1 and IL-2) markers was monitored by RT-qPCR, FACS and ELISA. Suppressive activity was validated by suppressive assays. Tregs recruitment by infected primary hepatic cells was evaluated using Boyden Chamber. Results: Tregs express the classical HCV receptors (CD81, CLDN1 and LDLR) and some co-receptors (CD5). HCV inoculation significantly increases the suppressive phenotype and activity of Tregs, and raises their anergy by inducing an unexpected IL-2 production. Moreover, HCV infection induces the expression of chemokines (CCL17, CXCL16, and CCL20) by primary hepatic human hepatocytes and chemokine receptors (CCR4, CXCR6 and CCR6) by Tregs. Finally, infected hepatocytes have a significantly higher potential to recruit Tregs in a seemingly CCL20-dependent manner. Conclusions: Direct interaction between HCV and Tregs represents a newly defined mechanism that could potentiate HCV immune evasion and favor intratumoral recruitment contributing to HCC progression. Full article
(This article belongs to the Special Issue Regulatory T (Treg) Cells in Health and Diseases)
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Figure 1

Figure 1
<p>Tregs possess the classical hepatitis C virus (HCV) entry receptors: CD81, CLDN1 and LDLR. Gene expression analyses (qPCR) of receptors CD81 (<b>A</b>), CLDN1 (<b>B</b>), SCARB1 (<b>C</b>) and LDLR (<b>D</b>), associated with HCV entry in host cells (left panels). Results are expressed as relative expression and presented as means of four independent experiments ± standard error of the mean (SEM) bars. Protein expression Flow Cytometry (FACS) of receptors related to HCV entry (middle panels). Results are expressed in histograms displaying the percentage of cells positive for protein labeling compared to isotype control. Protein expression (Western Blot) of receptors linked to HCV entry (right panels). Analyses were performed on Huh7 (control), PBMC and Tregs. The images are representative of at least four independent experiments.</p>
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<p>HCV inoculation increases the expression of its receptors on Tregs. HCV inoculation increases the mRNA expression of <span class="html-italic">CLDN1</span> and <span class="html-italic">SCARB1</span> at 3 h post-inoculation (3 h p.i) (<b>A</b>) and <span class="html-italic">CD81, EGFR</span> and <span class="html-italic">CD5</span> at 24 h p.i (<b>B</b>). Gene expression is normalized using GADPH, beta-actin, 18s and Hypoxanthine-guanine phosphoribosyltransferase (HRPT) mRNA as a housekeeping-gene before being reported to non-inoculated Tregs (black bars<span class="html-italic">).</span> Results represent means of five independent experiments and are presented as fold change (2<sup>–ΔΔCt</sup>) ± SEM bars. <span class="html-italic">p</span> ≤ <span class="html-italic">0.05</span> (*), <span class="html-italic">p</span> ≤ 0.001 (**), <span class="html-italic">p</span> ≤ 0.0001 (***) and <span class="html-italic">p</span> ≤ 0.00001 (****).</p>
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<p>HCV inoculation increases the suppressive phenotype of Tregs. HCV inoculation affects CD4, CD25, CD127, FOXP3, CTLA4 and LAG3 expression in activated Tregs at 3 h post HCV inoculation (3 h p.i) (<b>A</b>) and 24 h p.i (<b>B</b>). Results are presented as means of four independent experiments of inoculated Tregs (light grey bars) versus non-inoculated Tregs (dark bars). Gene expressions are normalized by using GADPH, beta-actin, 18s and HRPT mRNA as housekeeping-genes and result are expressed in fold change (2<sup>–ΔΔCt</sup>) ± SEM bars. (<b>C</b>) Representative dot plot of double stained CD4+CD25<sup>high</sup> and CD25<sup>high</sup> CD127<sup>-/low</sup> Tregs 0 h post HCV inoculation (0 h p.i), 3 h p.i and 24 h p.i.</p>
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<p>HCV inoculation increases the in vitro proliferative capacity of Tregs. Tregs proliferation was measured by using [<sup>3</sup>H]-thymidine incorporation assay and cell counting assays at 24 h (<b>A</b>), 48 h (<b>B</b>) and 72 h (<b>C</b>) after HCV inoculation. Results are expressed in index of proliferation of inoculated Tregs (hatched column) compared to non-inoculated (light column). Results are presented as mean values of triplicate ± SEM bars of four independent experiments. qPCR analyses showed that HCV inoculation increases <span class="html-italic">IL-2, IL-4, BLIMP1, BCL6</span> and <span class="html-italic">IL-15</span> gene expressions in Tregs at 3 h p.i, (<b>D</b>) and 24 h p.i (<b>E</b>). Results are presented as means of four independent experiments in inoculated Tregs (light grey bars) versus non-inoculated Tregs (dark bars). Gene expressions are normalized by using GADPH, beta-actin, 18s and HRPT mRNA as housekeeping-genes and the results are expressed in fold change (2<sup>–ΔΔCt</sup>) ± SEM bars. Secretion of the proliferative cytokine IL-2 by Tregs after HCV inoculation (<b>F</b>). Results are expressed as mean of three independent experiments and presented in pg/mL ± SEM bars comparing secretion by inoculated Tregs (light grey bars) versus non-inoculated Tregs (dark bars). <span class="html-italic">p</span> ≤ 0.05 (*), <span class="html-italic">p</span> ≤ 0.001 (**).</p>
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<p>HCV inoculation increases the suppressive activity of Tregs. Tregs were pre-incubated for 24 h with HCV virions produced in cell culture (HCVcc) before co-cultured with autologous PBMC at 2:1 ratio in activated conditions (<b>A</b>). Results are expressed as mean values of triplicates of three independent experiments and presented in index of suppression ± SEM bars. Mechanistic analyses highlight an increase expression of IL-2RA, IL-10, IL-24, IL-12p35, EBI3, GZMB and TGF-β1 mRNA in inoculated Tregs at 3 h p.i (<b>B</b>) and 24 h p.i (<b>C</b>). Results are presented as means of four independent experiments in inoculated Tregs (light grey bars) versus non inoculated Tregs (dark bars). Gene expressions are normalized by using GADPH, beta-actin, 18s and HRPT mRNA as housekeeping-genes and the results are expressed in fold change (2<sup>–ΔΔCt</sup>) ± SEM bars. Secretion of immunosuppressive cytokine TGF-β1 (<b>D</b>) and IL-10 (<b>E</b>) was evaluated at different time point after HCV inoculation on three independent experiments. Results are expressed in pg/mL ± SEM bars comparing secretion by inoculated Tregs (light grey bars) versus non-inoculated Tregs (dark bars). <span class="html-italic">p</span> ≤ 0.05 (*).</p>
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<p>Tregs are recruited by infected primary human hepatocytes supernatants. Tregs recruitment by primary human hepatocytes (PHH) was evaluated by a Boyden chamber assay. In vitro infected PHHs recruit more natural Tregs than non-infected PHHs (<b>A</b>). Results are expressed as mean values of quintuplicate of six independent experiments and presented in index of migration of Tregs ± SEM bars. qPCR analyses show an increase of the expression of several chemokines associated with Treg recruitment such as CCL20, CCL17 or CXCL16 by PHH (<b>B</b>). Results are presented as means of five independent experiments on infected PHH (light grey bars) versus non-infected PHH (dark bars). HCV inoculation also increases the expression of corresponding chemokines receptors by isolated Tregs at 3 h p.i and 24 h p.i (<b>C</b>). All gene expressions are normalized by using GADPH, beta-actin, 18s and HRPT mRNA as housekeeping-genes and the results are expressed in fold change (2<sup>–ΔΔCt</sup>) ± SEM bars of five independent experiments. Secretion of three chemokines CCL20, CCL17 and CXCL16 has been examined by ELISA (<b>D</b>–<b>F</b>, left panels). Results are expressed as the mean of four independent experiments and presented in pg/mL ± SEM bars comparing secretion by infected PHH (light grey bars) versus non-infected PHH (dark bars). The chemotactic potential of PHHs on CD4+CD25<sup>high</sup>CD127<sup>−/low</sup> Tregs was investigated in a Boyden chamber assay, using DMEM medium as a negative control; h-rec-CCL20, h-rec-CCL17 and h-rec-CXCL16 as positive controls and PHH supernatant with specific blocking anti-chemokines (<b>D</b>–<b>F</b>, right panels). Results are presented as means of quintuplicate of four independent experiments and presented in the index of migration related to DMEM medium ± SEM bars. When stated, statistical analysis were achieved by comparing the pointed condition to either infected PHH in the presence of non-inoculated (NI; <span>$</span>) or inoculated (I) Tregs (*), 50 ng of human recombinant (h) CLL20 with NI (+) or I (#) Tregs, h CCL17 in the presence of NI (•) or I (◦) Treg. <span class="html-italic">p</span> ≤ 0.05 (*), <span class="html-italic">p</span> ≤ 0.001 (**), <span class="html-italic">p</span> ≤ 0.0001 (***) and <span class="html-italic">p</span> ≤ 0.00001 (****).</p>
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<p>Tregs are recruited by infected primary human hepatocytes supernatants. Tregs recruitment by primary human hepatocytes (PHH) was evaluated by a Boyden chamber assay. In vitro infected PHHs recruit more natural Tregs than non-infected PHHs (<b>A</b>). Results are expressed as mean values of quintuplicate of six independent experiments and presented in index of migration of Tregs ± SEM bars. qPCR analyses show an increase of the expression of several chemokines associated with Treg recruitment such as CCL20, CCL17 or CXCL16 by PHH (<b>B</b>). Results are presented as means of five independent experiments on infected PHH (light grey bars) versus non-infected PHH (dark bars). HCV inoculation also increases the expression of corresponding chemokines receptors by isolated Tregs at 3 h p.i and 24 h p.i (<b>C</b>). All gene expressions are normalized by using GADPH, beta-actin, 18s and HRPT mRNA as housekeeping-genes and the results are expressed in fold change (2<sup>–ΔΔCt</sup>) ± SEM bars of five independent experiments. Secretion of three chemokines CCL20, CCL17 and CXCL16 has been examined by ELISA (<b>D</b>–<b>F</b>, left panels). Results are expressed as the mean of four independent experiments and presented in pg/mL ± SEM bars comparing secretion by infected PHH (light grey bars) versus non-infected PHH (dark bars). The chemotactic potential of PHHs on CD4+CD25<sup>high</sup>CD127<sup>−/low</sup> Tregs was investigated in a Boyden chamber assay, using DMEM medium as a negative control; h-rec-CCL20, h-rec-CCL17 and h-rec-CXCL16 as positive controls and PHH supernatant with specific blocking anti-chemokines (<b>D</b>–<b>F</b>, right panels). Results are presented as means of quintuplicate of four independent experiments and presented in the index of migration related to DMEM medium ± SEM bars. When stated, statistical analysis were achieved by comparing the pointed condition to either infected PHH in the presence of non-inoculated (NI; <span>$</span>) or inoculated (I) Tregs (*), 50 ng of human recombinant (h) CLL20 with NI (+) or I (#) Tregs, h CCL17 in the presence of NI (•) or I (◦) Treg. <span class="html-italic">p</span> ≤ 0.05 (*), <span class="html-italic">p</span> ≤ 0.001 (**), <span class="html-italic">p</span> ≤ 0.0001 (***) and <span class="html-italic">p</span> ≤ 0.00001 (****).</p>
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<p>Tregs cannot be recruited by primary human intra-hepatic fibroblasts even upon HCV inoculation. Tregs recruitment by in vitro inoculated primary human intra-hepatic fibroblast (IHF) was evaluated by a Boyden chamber assay (<b>A</b>). Results are expressed as mean values of quintuplicate of two independent experiments and presented in an index of migration of Tregs ± SEM bars. Secretion of chemokines CCL20, CCL17 and CXCL16 has been examined by ELISA (<b>B</b>). Results are expressed as the mean of two independent experiments and presented in pg/mL ± SEM bars comparing secretion by inoculated IHF (light grey bars) versus non-inoculated IHF (dark bars). <span class="html-italic">p</span> ≤ 0.05 (*).</p>
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17 pages, 1806 KiB  
Article
Tumor Cells Develop Defined Cellular Phenotypes After 3D-Bioprinting in Different Bioinks
by Sonja K. Schmidt, Rafael Schmid, Andreas Arkudas, Annika Kengelbach-Weigand and Anja K. Bosserhoff
Cells 2019, 8(10), 1295; https://doi.org/10.3390/cells8101295 - 22 Oct 2019
Cited by 41 | Viewed by 5611
Abstract
Malignant melanoma is often used as a model tumor for the establishment of novel therapies. It is known that two-dimensional (2D) culture methods are not sufficient to elucidate the various processes during cancer development and progression. Therefore, it is of major interest to [...] Read more.
Malignant melanoma is often used as a model tumor for the establishment of novel therapies. It is known that two-dimensional (2D) culture methods are not sufficient to elucidate the various processes during cancer development and progression. Therefore, it is of major interest to establish defined biofabricated three-dimensional (3D) models, which help to decipher complex cellular interactions. To get an impression of their printability and subsequent behavior, we printed fluorescently labeled melanoma cell lines with Matrigel and two different types of commercially available bioinks, without or with modification (RGD (Arginine-Glycine-Aspartate)-sequence/laminin-mixture) for increased cell-matrix communication. In general, we demonstrated the printability of melanoma cells in all tested biomaterials and survival of the printed cells throughout 14 days of cultivation. Melanoma cell lines revealed specific differential behavior in the respective inks. Whereas in Matrigel, the cells were able to spread, proliferate and form dense networks throughout the construct, the cells showed no proliferation at all in alginate-based bioink. In gelatin methacrylate-based bioink, the cells proliferated in clusters. Surprisingly, the modifications of the bioinks with RGD or the laminin blend did not affect the analyzed cellular behavior. Our results underline the importance of precisely adapting extracellular matrices to individual requirements of specific 3D bioprinting applications. Full article
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<p>Printability of bioink and cell distribution. Constructs with an area of 1 cm<sup>2</sup>, three layers high, containing 10<sup>5</sup> cells/mL were printed with <span class="html-italic">Cellink Bioink, Cellink RGD, GelXA, GelXA Laminink+</span> or Matrigel, respectively, using the Cellink+ bioprinter. (<b>A</b>) Representative macroscopic images of cell-loaded 3D printed constructs at time points d0, d7, and d14. (<b>B</b>) Representative fluorescence microscope images of melanoma cell lines Mel Im GFP (green) and MV3dc (red/green) in the respective inks 1 day after 3D printing. Scale bars represent 200 µm.</p>
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<p>Survival of melanoma cells in the bioinks. (<b>A</b>) Two representative fluorescence microscope images of each of the cell lines Mel Im GFP and MV3dc one day after 3D printing. Both melanoma cell lines survived the bioprinting and crosslinking process in all bioinks. Scale bars represent 100 µm. (<b>B</b>) Quantification of living cells per mm<sup>2</sup> in the bioinks on the day Mel Im GFP showed low amounts of living cells in both <span class="html-italic">Cellink</span>-based inks, a higher rate in <span class="html-italic">GelXA</span>-based inks, and revealed the significantly highest amount of viable cells in Matrigel. MV3dc revealed appropriate amounts of living cells in all materials, with the lowest amount in the <span class="html-italic">Cellinks</span> and <span class="html-italic">GelXA Laminink+</span>, and the significantly highest amount in Matrigel. * <span class="html-italic">p</span> ≤ 0.05 (One-way ANOVA).</p>
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<p>Morphology of melanoma cells in the different bioinks. (<b>A</b>) Fluorescence microscope images revealing the morphology of each three representative Mel Im GFP or MV3dc single cells on day 4, cultured in the different 3D matrices. The scale bars represent 20 µm. (<b>B</b>) Quantification of protrusion lengths (in 2D) of single cells at time points d1, d2, and d4 in all bioinks. Mel Im GFP spread and revealed increasing protrusion lengths over the observation period. Most distinct protrusions were observed in Matrigel. MV3dc cells revealed a tendency to form shorter protrusions in all bioinks, without clear time dependency of their lengths. Protrusion lengths on day 4 are not significantly different in the different materials for both cell lines (One-way ANOVA). (<b>C</b>) Fluorescence images of MCAT-eGFP transfected MV3 cells in printed constructs on day 4 and 7, the respective fluorescence/brightfield overlay images are shown for day 7. In all materials, some cells activate YAP/TAZ-TEAD, indicating cell–material interactions. The scale bars represent 100 µm.</p>
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<p>Tumor cell proliferation in bioinks over 14 days of culture. (<b>A</b>) Representative fluorescence images showing the proliferation of Mel Im GFP and MV3dc on d4, d7, and d14 after being printed with <span class="html-italic">Cellink Bioink</span>, <span class="html-italic">Cellink RGD</span>, <span class="html-italic">GelXA</span>, <span class="html-italic">GelXA Laminink+</span> and Matrigel. Mel Im GFP and MV3dc showed hardly any growth or proliferation <span class="html-italic">in Cellink Bioink</span> and <span class="html-italic">Cellink RGD</span> but formed irregular clusters in <span class="html-italic">GelXA</span> and <span class="html-italic">GelXA Laminink+</span>. In Matrigel, cells proliferated quickly, Mel Im GFP grew in clusters, which fused together with time, whereas MV3dc cells formed dense chain-like networks throughout the material. Scale bars represent 200 µm. (<b>B</b>) Quantification of proliferation by determination of the mean gray value intensities of at least three fluorescence images per time point plotted logarithmically to emphasize the strongest proliferation of both cell types in Matrigel. The statistical comparison presents the significant difference of mean gray value intensities in Matrigel on day 14 with the other materials on that day. The same significance was observed in comparing day 4 or day 7; however, due to clarity reasons, these significances are not shown in the graph. * <span class="html-italic">p</span> ≤ 0.05 (One-way ANOVA).</p>
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7 pages, 238 KiB  
Editorial
Tubulin: Structure, Functions and Roles in Disease
by Pavla Binarová and Jack Tuszynski
Cells 2019, 8(10), 1294; https://doi.org/10.3390/cells8101294 - 22 Oct 2019
Cited by 83 | Viewed by 9826
Abstract
Highly conserved α- and β-tubulin heterodimers assemble into dynamic microtubules and perform multiple important cellular functions such as structural support, pathway for transport and force generation in cell division. Tubulin exists in different forms of isotypes expressed by specific genes with spatially- and [...] Read more.
Highly conserved α- and β-tubulin heterodimers assemble into dynamic microtubules and perform multiple important cellular functions such as structural support, pathway for transport and force generation in cell division. Tubulin exists in different forms of isotypes expressed by specific genes with spatially- and temporally-regulated expression levels. Some tubulin isotypes are differentially expressed in normal and neoplastic cells, providing a basis for cancer chemotherapy drug development. Moreover, specific tubulin isotypes are overexpressed and localized in the nuclei of cancer cells and/or show bioenergetic functions through the regulation of the permeability of mitochondrial ion channels. It has also become clear that tubulin isotypes are involved in multiple cellular functions without being incorporated into microtubule structures. Understanding the mutations of tubulin isotypes specifically expressed in tumors and their post-translational modifications might help to identify precise molecular targets for the design of novel anti-microtubular drugs. Knowledge of tubulin mutations present in tubulinopathies brings into focus cellular functions of tubulin in brain pathologies such as Alzheimer’s disease. Uncovering signaling pathways which affect tubulin functions during antigen-mediated activation of mast cells presents a major challenge in developing new strategies for the treatment of inflammatory and allergic diseases. γ-tubulin, a conserved member of the eukaryotic tubulin superfamily specialized for microtubule nucleation is a target of cell cycle and stress signaling. Besides its microtubule nucleation role, γ-tubulin functions in nuclear and cell cycle related processes. This special issue “Tubulin: Structure, Functions and Roles in Disease” contains eight articles, five of which are original research papers and three are review papers that cover diverse areas of tubulin biology and functions under normal and pathological conditions. Full article
(This article belongs to the Special Issue Tubulin: Structure, Functions and Roles in Disease)
17 pages, 695 KiB  
Review
What Do Microglia Really Do in Healthy Adult Brain?
by Marcus Augusto-Oliveira, Gabriela P. Arrifano, Amanda Lopes-Araújo, Leticia Santos-Sacramento, Priscila Y. Takeda, Daniel C. Anthony, João O. Malva and Maria Elena Crespo-Lopez
Cells 2019, 8(10), 1293; https://doi.org/10.3390/cells8101293 - 22 Oct 2019
Cited by 101 | Viewed by 16328
Abstract
Microglia originate from yolk sac-primitive macrophages and auto-proliferate into adulthood without replacement by bone marrow-derived circulating cells. In inflammation, stroke, aging, or infection, microglia have been shown to contribute to brain pathology in both deleterious and beneficial ways, which have been studied extensively. [...] Read more.
Microglia originate from yolk sac-primitive macrophages and auto-proliferate into adulthood without replacement by bone marrow-derived circulating cells. In inflammation, stroke, aging, or infection, microglia have been shown to contribute to brain pathology in both deleterious and beneficial ways, which have been studied extensively. However, less is known about their role in the healthy adult brain. Astrocytes and oligodendrocytes are widely accepted to strongly contribute to the maintenance of brain homeostasis and to modulate neuronal function. On the other hand, contribution of microglia to cognition and behavior is only beginning to be understood. The ability to probe their function has become possible using microglial depletion assays and conditional mutants. Studies have shown that the absence of microglia results in cognitive and learning deficits in rodents during development, but this effect is less pronounced in adults. However, evidence suggests that microglia play a role in cognition and learning in adulthood and, at a cellular level, may modulate adult neurogenesis. This review presents the case for repositioning microglia as key contributors to the maintenance of homeostasis and cognitive processes in the healthy adult brain, in addition to their classical role as sentinels coordinating the neuroinflammatory response to tissue damage and disease. Full article
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<p><b>Microglial responses to different molecules released by neurons</b>. CX3CL1, CD200, glutamate, ATP, and TGF-β induce an anti-inflammatory microglial profile, with microglia performing housekeeping tasks and contributing to homeostasis, plasticity, and cognition processes through release of TNF-α, IL-1β, IFN, and BDNF. In a different scenario, ATP, glutamate, danger-associated molecular patterns (DAMPs), pathogen-associated molecular patterns (PAMPs), and amyloid-beta proteins drive microglial behavior to a more responsive pro-inflammatory state, releasing IL-1β, TNF-α, IFN-γ, IL-4, ROS, NO, IL-8, and MMP. When the pro-inflammatory profile is maintained for a long time, it foments pathological conditions, such as toxicity, neuroinflammation, and neurodegeneration.</p>
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13 pages, 3711 KiB  
Protocol
Turning the World Upside-Down in Cellulose for Improved Culturing and Imaging of Respiratory Challenges within a Human 3D Model
by Viktoria Zaderer, Martin Hermann, Cornelia Lass-Flörl, Wilfried Posch and Doris Wilflingseder
Cells 2019, 8(10), 1292; https://doi.org/10.3390/cells8101292 - 21 Oct 2019
Cited by 19 | Viewed by 11515
Abstract
Polarized growth of human-derived respiratory epithelial cells on hydrogel-coated filters offers big advantages concerning detailed experiments with respect to drug screening or host pathogen interactions. Different microscopic approaches, such as confocal analyses and high content screening, help to examine such 3D respiratory samples, [...] Read more.
Polarized growth of human-derived respiratory epithelial cells on hydrogel-coated filters offers big advantages concerning detailed experiments with respect to drug screening or host pathogen interactions. Different microscopic approaches, such as confocal analyses and high content screening, help to examine such 3D respiratory samples, resulting in high-resolution pictures and enabling quantitative analyses of high cell numbers. A major problem employing these techniques relates to single-use instead of multiple-use of Transwell filters and difficulties in the digestion of collagen if subsequent analyses are needed. Up to date, cells are seeded in collagen-based matrices to the inner field of Transwell inserts, which makes it impossible to image due to the design of the inserts and hard to perform other analyses since digestion of the collagen matrix also affects Transwell grown cells. To overcome these problems, we optimized culturing conditions for monitoring cell differentiation or repeated dose experiments over a long time period. For this, cells are seeded upside-down to the bottom side of filters within an animal-free cellulose hydrogel. These cells were then grown inverted under static conditions and were differentiated in air-liquid interphase (ALI). Full differentiation of goblet (Normal Human Bronchial Epithelial (NHBE))/Club (small airway epithelia (SAE)) cells and ciliated cells was detected after 12 days in ALI. Inverted cell cultures could then be used for ‘follow-up’ live cell imaging experiments, as well as, flow-cytometric analyses due to easy digestion of the cellulose compared to classical collagen matrices. Additionally, this culture technique also enables easy addition of immune cells, such as dendritic cells (DCs), macrophages, neutrophils, T or B cells alone or in combination, to the inner field of the Transwell to monitor immune cell behavior after repeated respiratory challenge. Our detailed protocol offers the possibility of culturing human primary polarized cells into a fully differentiated, thick epithelium without any animal components over >700 days. Furthermore, this animal-free, inverted system allows investigation of the same inserts, because the complete Transwell can be readily transferred to glass-bottom dishes for live cell imaging analyses and then returned to its original plate for further cultivation. Full article
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<p>Normal seeding (left) of primary, respiratory epithelial cells (Normal Human Bronchial Epithelial (NHBE), small airway epithelia (SAE)) in cellulose-based GrowDex<sup>®</sup> does not allow multiple uses of 3D grown tissue, since Transwell inserts have to be cut out or paraffin-embedded for imaging analyses. Imaging is not possible from below due to the thickness of the filter-grown tissue and flipping of normally grown wells is not possible due to the side walls of the Transwell. Upside-down seeding of respiratory cells grown in GrowDex<sup>®</sup> allows an easy transfer of the Transwell to a glass-bottom dish by lifting the Transwell insert to the other dish under sterile conditions. After-life cell imaging analyses are done, the Transwell insert is transferred back into the original well. Therefore, among many other applications, cell differentiation and mucociliary clearance can be monitored using the same cells grown in an animal-free cellulose hydrogel.</p>
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<p>NHBE cells, day 15 (d15) in air-liquid interphase (ALI) and seeded upside-down. Left panel: cells grown on the animal-free, birch-based hydrogel. Right panel: cells grown on rat tail collagen-coated membranes. Images show faster proliferation, due to more cell layers and an increased cell number when the hydrogel was applied. Nuclei were stained using Höchst (blue), cilia using wheat germ agglutinin (green), mitochondria using mitotracker (red). An overlay is illustrated in the bottom right panels. Two representative images from at least 3 independent experiments are depicted for cells cultured upside-down in GrowDex<sup>®</sup> or rat-tail collagen.</p>
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<p>Quantitative analyses of nuclei within GrowDex<sup>®</sup> and rat-tail collagen. Differentiated cells revealed a significantly higher cell number within the birch-based hydrogel on day 15 post-ALI. Five independent regions of two Transwell inserts were quantified using the Operetta CLS™ HCS, and cells were automatically quantified using the Harmony software.</p>
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<p>Analysis of mucociliary clearance of NHBE cells cultured in birch-based cellulose hydrogel and upside-down. High content screening of the mucociliary clearance was performed after the addition of fluorescently labeled beads (green) and an overview of the bead distribution is depicted. The experiment was repeated three times in independent experiments.</p>
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<p>Analysis of epithelial integrity of upside-down cultured NHBE cells on d700 in ALI. Cilia of NHBE cells cultured in GrowDex® for 700 days in ALI and upside-down were stained using WGA-488 (green), cytoskeleton using Phalloidin-Alexa555 (yellow) and nuclei using Höchst (blue).</p>
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<p>Seeding procedure of primary respiratory cells in cellulose for upside-down cell culture in Transwell chambers. Primary cells (NHBE/SAE) are mixed in GrowDex<sup>®</sup> as described below and then transferred to an inverted Transwell chamber fixed with tape in a 6-well plate. Cells are allowed to adhere overnight, and the next day, the Transwell chamber is flipped into a 24-Transwell plate. Cells are cultured submerged for 3 days and then transferred into ALI during the differentiation process.</p>
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25 pages, 1143 KiB  
Review
Current Paradigms of Tolerogenic Dendritic Cells and Clinical Implications for Systemic Lupus Erythematosus
by Patcharee Ritprajak, Chamraj Kaewraemruaen and Nattiya Hirankarn
Cells 2019, 8(10), 1291; https://doi.org/10.3390/cells8101291 - 21 Oct 2019
Cited by 25 | Viewed by 5787
Abstract
Tolerogenic dendritic cells (tolDCs) are central players in the initiation and maintenance of immune tolerance and subsequent prevention of autoimmunity. Recent advances in treatment of autoimmune diseases including systemic lupus erythematosus (SLE) have focused on inducing specific tolerance to avoid long-term use of [...] Read more.
Tolerogenic dendritic cells (tolDCs) are central players in the initiation and maintenance of immune tolerance and subsequent prevention of autoimmunity. Recent advances in treatment of autoimmune diseases including systemic lupus erythematosus (SLE) have focused on inducing specific tolerance to avoid long-term use of immunosuppressive drugs. Therefore, DC-targeted therapies to either suppress DC immunogenicity or to promote DC tolerogenicity are of high interest. This review describes details of the typical characteristics of in vivo and ex vivo tolDC, which will help to select a protocol that can generate tolDC with high functional quality for clinical treatment of autoimmune disease in individual patients. In addition, we discuss the recent studies uncovering metabolic pathways and their interrelation intertwined with DC tolerogenicity. This review also highlights the clinical implications of tolDC-based therapy for SLE treatment, examines the current clinical therapeutics in patients with SLE, which can generate tolDC in vivo, and further discusses on possibility and limitation on each strategy. This synthesis provides new perspectives on development of novel therapeutic approaches for SLE and other autoimmune diseases. Full article
(This article belongs to the Special Issue The Molecular and Cellular Basis for Lupus)
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<p>Desirable phenotypes of tolDCs.</p>
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<p>Metabolic circuits vital for DC tolerogenicity.</p>
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13 pages, 2838 KiB  
Article
Helicobacter pylori Induces IL-33 Production and Recruits ST-2 to Lipid Rafts to Exacerbate Inflammation
by Chia-Jung Kuo, Chun-Ya Chen, Horng-Ren Lo, Chun-Lung Feng, Hui-Yu Wu, Mei-Zi Huang, Tung-Nan Liao, Yu-An Chen and Chih-Ho Lai
Cells 2019, 8(10), 1290; https://doi.org/10.3390/cells8101290 - 21 Oct 2019
Cited by 16 | Viewed by 5201
Abstract
Helicobacter pylori colonizes human gastric epithelial cells and contributes to the development of several gastrointestinal disorders. Interleukin (IL)-33 is involved in various immune responses, with reported proinflammatory and anti-inflammatory effects, which may be associated with colitis and colitis-associated cancer. IL-33 induces the inflammatory [...] Read more.
Helicobacter pylori colonizes human gastric epithelial cells and contributes to the development of several gastrointestinal disorders. Interleukin (IL)-33 is involved in various immune responses, with reported proinflammatory and anti-inflammatory effects, which may be associated with colitis and colitis-associated cancer. IL-33 induces the inflammatory cascade through its receptor, suppression of tumorigenicity-2 (ST-2). Binding of IL-33 to membrane-bound ST-2 (mST-2) recruits the IL-1 receptor accessory protein (IL-1RAcP) and activates intracellular signaling pathways. However, whether IL-33/ST-2 is triggered by H. pylori infection and whether this interaction occurs in lipid rafts remain unclear. Our study showed that both IL-33 and ST-2 expression levels were significantly elevated in H. pylori-infected cells. Confocal microscopy showed that ST-2 mobilized into the membrane lipid rafts during infection. Depletion of membrane cholesterol dampened H. pylori-induced IL-33 and IL-8 production. Furthermore, in vivo studies revealed IL-33/ST-2 upregulation, and severe leukocyte infiltration was observed in gastric tissues infected with H. pylori. Together, these results demonstrate that ST-2 recruitment into the lipid rafts serves as a platform for IL-33-dependent H. pylori infection, which aggravates inflammation in the stomach. Full article
(This article belongs to the Special Issue Immunomodulatory Factors in Host Defense)
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<p><span class="html-italic">H. pylori</span> induces Interleukin (IL)-33 and suppression of tumorigenicity-2 (ST-2) expression in gastric epithelial cells. AGS cells were infected with <span class="html-italic">H. pylori</span> (<b>A</b>) at a multiplication of infection (MOI) of 100 for the indicated times or (<b>B</b>) at different MOIs for 9 h. Total cell lysates were prepared to analyze the expression levels of IL-33 and ST-2 by Western blot. Molecular weights of full-length IL-33 and processed IL-33 were 36 KDa and 18 KDa, respectively. β-actin was used as an internal control. The expression levels of processed IL-33 and ST-2 were quantified by the signal intensity and indicated at the bottom of each lane.</p>
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<p>IL-33 translocates from the nucleus to cytoplasm in response to <span class="html-italic">H. pylori</span> infection. AGS cells were left untreated or infected with <span class="html-italic">H. pylori</span> at an MOI of 100 for 9 h. Cells were fixed and stained for IL-33 (red), then probed with Hoechst 33342 (blue) to identify the cell nucleus. (<b>A</b>) The stained cells were analyzed by confocal microscopy. Scale bar, 5 μm. (<b>B</b>) IL-33 (red) signal was quantified and normalized with Hoechst 33342. (<b>C</b>) The cytoplasmic IL-33 was quantified and normalized with nuclear fluorescence. Imaging data of arithmetic mean intensity were analyzed by using the ZEN-blue edition software (Carl Zeiss). (<b>D</b>) Cytoplasmic and nuclear fractions were analyzed to determine IL-33 levels by ELISA. *, <span class="html-italic">p</span> &lt; 0.05.</p>
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<p><span class="html-italic">H. pylori</span> induces IL-1 receptor accessory protein (IL-1RAcP) expression but not in lipid rafts. AGS cells were left untreated or infected with <span class="html-italic">H. pylori</span> at an MOI of 100 for 9 h. (<b>A</b>) Expression levels of IL-1RAcP and β-actin were assessed using Western blot. (<b>B</b>) Cells were stained for IL-1RAcP (green), Hoechst 33342 (blue), and cholera toxin subunit B (CTX-B) to label lipid rafts (red). The stained cells were analyzed by confocal microscopy. Scale bar, 5 μm.</p>
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<p><span class="html-italic">H. pylori</span> elicits ST-2 mobilization into lipid rafts. AGS cells were left untreated or infected with <span class="html-italic">H. pylori</span> at an MOI of 100 for 9 h. Cells were subsequently stained for ST-2 (green), CTX-B (red), and Hoechst 33342 (blue). The stained cells were analyzed by confocal microscopy. The co-localization of ST-2 with CTX-B appears yellow in the merged image. Scale bar, 5 μm.</p>
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<p>Recruitment of ST-2 into the lipid rafts is induced by IL-33. AGS cells were pretreated with or without 5 mM MβCD followed by incubation with recombinant IL-33 (100 ng/mL) at 11 °C for 1 h. Cells were then stained for ST-2 (green), CTX-B (red), and Hoechst 33342 (blue). Fluorescence distributions of ST-2 (green) and CTX-B (red) signals across the white lines were analyzed and exhibited as a line intensity histogram in the right panel. Scale bar, 10 µm.</p>
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<p>Sufficient cholesterol in the membrane rafts is crucial for <span class="html-italic">H. pylori</span>-induced IL-33 and IL-8 production. AGS cells were left untreated or pretreated with nystatin (50 μg/mL), simvastatin (10 μM), or MβCD (5.0 mM), or treated MβCD followed by replenishment of water-soluble cholesterol (400 μg/mL). After <span class="html-italic">H. pylori</span> infection at an MOI of 100 for 9 h, the expression levels of (<b>A</b>) IL-8 and (<b>B</b>) IL-33 were determined by ELISA. *, <span class="html-italic">P</span> &lt; 0.05.</p>
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<p><span class="html-italic">H. pylori</span> infection induces IL-33 and ST-2 expression in mouse gastric epithelial cells. (<b>A</b>) Mice were infected with <span class="html-italic">H. pylori</span> (1 × 10<sup>8</sup>) by intragastric gavage once every 2 days for a total of six administrations. (<b>B</b>) Tissue sections of the stomach were fixed and stained with H&amp;E, or prepared for IHC staining with specific antibodies against IL-33 and ST-2. The magnified images are shown in the right panel of each cropped image. Inflammatory cell infiltration in the gastric epithelium was observed (black arrowheads), along with evidence of both IL-33 and ST-2 expression in the gastric tissues (red arrowheads). Scale bars in left panels, 20 μm, and in magnified right panels, 60 μm.</p>
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19 pages, 2969 KiB  
Article
The Charcot–Marie Tooth Disease Mutation R94Q in MFN2 Decreases ATP Production but Increases Mitochondrial Respiration under Conditions of Mild Oxidative Stress
by Christina Wolf, Rahel Zimmermann, Osamah Thaher, Diones Bueno, Verena Wüllner, Michael K.E. Schäfer, Philipp Albrecht and Axel Methner
Cells 2019, 8(10), 1289; https://doi.org/10.3390/cells8101289 - 21 Oct 2019
Cited by 16 | Viewed by 4780
Abstract
Charcot–Marie tooth disease is a hereditary polyneuropathy caused by mutations in Mitofusin-2 (MFN2), a GTPase in the outer mitochondrial membrane involved in the regulation of mitochondrial fusion and bioenergetics. Autosomal-dominant inheritance of a R94Q mutation in MFN2 causes the axonal subtype 2A2A which [...] Read more.
Charcot–Marie tooth disease is a hereditary polyneuropathy caused by mutations in Mitofusin-2 (MFN2), a GTPase in the outer mitochondrial membrane involved in the regulation of mitochondrial fusion and bioenergetics. Autosomal-dominant inheritance of a R94Q mutation in MFN2 causes the axonal subtype 2A2A which is characterized by early onset and progressive atrophy of distal muscles caused by motoneuronal degeneration. Here, we studied mitochondrial shape, respiration, cytosolic, and mitochondrial ATP content as well as mitochondrial quality control in MFN2-deficient fibroblasts stably expressing wildtype or R94Q MFN2. Under normal culture conditions, R94Q cells had slightly more fragmented mitochondria but a similar mitochondrial oxygen consumption, membrane potential, and ATP production as wildtype cells. However, when inducing mild oxidative stress 24 h before analysis using 100 µM hydrogen peroxide, R94Q cells exhibited significantly increased respiration but decreased mitochondrial ATP production. This was accompanied by increased glucose uptake and an up-regulation of hexokinase 1 and pyruvate kinase M2, suggesting increased pyruvate shuttling into mitochondria. Interestingly, these changes coincided with decreased levels of PINK1/Parkin-mediated mitophagy in R94Q cells. We conclude that mitochondria harboring the disease-causing R94Q mutation in MFN2 are more susceptible to oxidative stress, which causes uncoupling of respiration and ATP production possibly by a less efficient mitochondrial quality control. Full article
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Figure 1

Figure 1
<p>Fragmented mitochondria but similar basal respiration in cells expressing wildtype and disease-causing R94Q MFN2. (<b>A</b>) Immunoblot showing endogenous MFN2 in wildtype (WT) cells and similar MFN2 protein overexpression levels in MFN2 knockout (KO) cells rescued with wildtype MFN2 (KO + WT) or R94Q MFN2 (KO + R94Q). Actin served as loading control. (<b>B</b>) Increased mitochondrial fragmentation in KO + R94Q cells. Mitotracker-stained cells were categorized upon their mitochondrial morphology as tubular, mixed, or fragmented by blinded investigators. A representative picture of KO + WT and KO + R94Q is shown. (<b>C</b>) Oxygen flow per cells quantitated by high-resolution respirometry demonstrates similar routine, leak and electron transfer system capacity (ETS) of KO + WT and KO + R94Q cells. Data are expressed as mean ± SEM of n = 4 immunoblots in (<b>A</b>), n = 6 independent experiments analyzed by two blinded investigators in (<b>B</b>), and n = 5 independent experiments in (<b>C</b>). Statistical significance was determined using one-way ANOVA and Tukey’s multiple comparison test (* <span class="html-italic">p</span> &lt; 0.05; n.s., non-significant).</p>
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<p>Oxidative stress causes increased mitochondrial fragmentation in cells expressing R94Q MFN2. (<b>A</b>) Reduced but similar proliferation rate of WT and R94Q cells exposed to H<sub>2</sub>O<sub>2</sub>. Similar amounts of cells were seeded and treated with 100 µM H<sub>2</sub>O<sub>2</sub> 24 h later. Luminescence was measured every 24 h for 72 h. Data are expressed as mean proliferation rate ± SEM of n = 4 independent experiments done in triplicates and normalized to the first day. (<b>B</b>) Relative distribution of mitochondrial morphologies in mitotracker-stained cells. Cells were categorized according to their mitochondrial morphology as tubular, mixed, or fragmented. Data are expressed as mean ± SEM of n = 4 independent experiments analyzed by investigators blind to cell line identity in (<b>B</b>). Statistical significance was determined using one-way ANOVA and Tukey’s multiple comparison test (* <span class="html-italic">p</span> &lt; 0.05; n.s., non-significant).</p>
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<p>Oxidative stress causes increased mitochondrial uncoupling in cells expressing R94Q MFN2. (<b>A</b>) Representative high-resolution respirometry of intact cell recordings showing oxygen concentration (blue line) and oxygen flow per cells (red line) over time. Time points of oligomycin (Omy), FCCP (F), rotenone (Rot) and antimycin A (Ama) additions are indicated. Oxygen flow per cells were corrected for ROX at the indicated mitochondrial respiration state. Basal cellular routine respiration, leak and ETS capacity increased in R94Q but not WT treated with 100 µM H<sub>2</sub>O<sub>2</sub> 24 h prior to measurement. (<b>B</b>) High-resolution respirometry of cells permeabilized with digitonin with GSH or GSSG added. Mitochondrial respiration stimulated by ADP represents complex I (CI) activity, addition of succinate and ADP corresponds to respiration with convergent input of electrons via complexes I and II into the respiratory system (CII). Mitochondrial membrane integrity was tested by the application of cytochrome c. ATP synthase inhibition by oligomycin revealed the leak state (Leak). The electron transfer system (ETS) capacity at maximum oxygen flow per cells was determined by titration of FCCP and ROX after antimycin A-induced inhibition of complex III. Data are expressed as mean oxygen flow per cell corrected for ROX ± SEM at the indicated mitochondrial respiration state. GSH and GSSG had no effect on mitochondrial respiration. Data in A and B show the mean ± SEM of n = 6 independent experiments. Statistical significance was determined using multiple <span class="html-italic">t</span>-tests with a false discovery rate (Q) of 1% according to the two-stage method by Benjamini, Krieger and Yekutieli (* <span class="html-italic">p</span> &lt; 0.05; n.s., non-significant). (<b>C</b>) Relative ATP levels quantitated by targeting BTeam, a ratiometric BRET-based ATP biosensor to the cytosol or to the mitochondrial matrix. Data are expressed as YFP/NLuc emissions ratio. Statistical variation in (<b>C</b>) is shown as Tukey boxplots and significance calculated using student’s <span class="html-italic">t</span>-test comparing cell lines with and without H<sub>2</sub>O<sub>2</sub> exposure, * <span class="html-italic">p</span> &lt; 0.05, n = 4 independent experiments done in triplicates.</p>
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<p>Reduced and not increased oxidative stress in cells expressing R94Q MFN2. (<b>A</b>) Cells were stained with CellRox and the intensity in single cells quantitated by confocal microscopy. (<b>B</b>) GSSG was measured by monitoring NADPH consumption by GSH reductase in 2-vinylpyridine-treated samples. (<b>C</b>) The mRNA of transcripts involved in the antioxidant response were quantified by real-time RT-PCR using Taqman primer-probe assays for glutamate-cysteine ligase, catalytic subunit (GCLc), glutathione S transferase omega 1 (GSTO1), NADPH-quinone-oxidoreductase-1 (NQO1), glutathione peroxidase 1 (GPX1), heme-oxygenase-1 (HO1) and xCT and normalized to the expression of the housekeeping gene hypoxanthine-guanine phosphoribosyltransferase (hprt). RNAse-free water was used as non-template control. Analysis of the results was performed using the ΔΔCT-method. All conditions were normalized to their untreated control group. In all experiments, H<sub>2</sub>O<sub>2</sub> was added 24 h before analysis. Statistical variation is shown as Tukey boxplots and significance calculated using one-way ANOVA and Tukey’s multiple comparisons test, * <span class="html-italic">p</span> &lt; 0.05, in (<b>A</b>) n = 3 independent experiments with a total of 150–170 individual cells, in (<b>B</b>) n = 5 independent experiments, in (<b>C</b>) n = 3 independent experiments done in triplicates.</p>
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<p>Glucose uptake and fueling of mitochondria with pyruvate in R94Q cells. (<b>A</b>) Scheme depicting metabolism upstream of the tricarboxylic acid cycle (TCA). G6PD, glutamate 6-phosphate dehydrogenase; PPP, pentose phosphate pathway; PEP, phosphoenolpyruvate; PKM, pyruvate dehydrogenase isozyme M; LDHA, lactate dehydrogenase A. (<b>B</b>) Cells were stained with 2-NBDG and the intensity in single cells quantitated by confocal microscopy. (<b>C</b>–<b>e</b>) Cells were treated with 100 µM H<sub>2</sub>O<sub>2</sub> 24 h prior to immunoblotting against (<b>C</b>) hexokinase 1 (HK1), (<b>D</b>) G6PD, (<b>E</b>) PKM isozymes 1 and 2. Actin served as loading control. Size is indicated. (<b>F</b>) Lactate levels were measured photometrically and normalized to the protein content of the wells. Statistical variation is shown as Tukey boxplots and significance calculated using one-way ANOVA and Tukey’s multiple comparisons test, * <span class="html-italic">p</span> &lt; 0.05, in (<b>A</b>) n = 4 independent experiments with a total of 207–243 individual cells, in (<b>C</b>–<b>E</b>) n = 2 independent blots with a total of 6 individual lysates, (<b>F</b>) n = 6 measurements.</p>
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<p>CCCP-induced degradation of MFN2 in R94Q cells. (<b>A</b>) Cells were treated with the uncoupler CCCP for the indicated time and immunoblotted against MFN2 in (<b>A</b>) and against TOM20 or VDAC1 in (<b>B</b>). Actin served as loading control. Size is indicated. Statistical variation is shown in (<b>A</b>) as Tukey boxplots and significance calculated using one-way ANOVA and Tukey’s multiple comparisons test, * <span class="html-italic">p</span> &lt; 0.05 with n = 5 independent experiments and in (<b>B</b>) as individual data points, mean ± SEM.</p>
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<p>Steady-state mitophagy and mitochondrial Parkin localization in R94Q cells. (<b>A</b>) Cells were transfected with mitochondrially targeted mKeima and fluorescence at 620 nm quantified after excitation at 550 nm (red) and 438 nm (green) by confocal microscopy. Scale bar is 5 µm. (<b>B</b>) Cells were transfected with Parkin-GFP and mitochondrially targeted TurboFarRed and the fluorescence intensity measured at 488/518 (ex/em) for GFP-Parkin and at 633/640 (ex/em) for Mito-TurboFarRed. Scale bar is 5 µm. Parkin-Mito-TurboFarRed colocalization was quantitated using the JACoP plugin of ImageJ and is expressed as Pearson’s coefficient. Statistical variation is shown as Tukey boxplots and significance calculated using one-way ANOVA and Tukey’s multiple comparisons test, * <span class="html-italic">p</span> &lt;0.05, in (<b>A</b>) n = 5 independent experiments, in (<b>B</b>,<b>C</b>) n = 3 independent experiments with a total of (<b>B</b>) 91–115 and (<b>C</b>) 59–61 individual cells.</p>
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23 pages, 9489 KiB  
Article
Subcutaneous and Visceral Adipose-Derived Mesenchymal Stem Cells: Commonality and Diversity
by Andreas Ritter, Alexandra Friemel, Susanne Roth, Nina-Naomi Kreis, Samira Catharina Hoock, Babek Khan Safdar, Kyra Fischer, Charlotte Möllmann, Christine Solbach, Frank Louwen and Juping Yuan
Cells 2019, 8(10), 1288; https://doi.org/10.3390/cells8101288 - 21 Oct 2019
Cited by 41 | Viewed by 4259
Abstract
Adipose-derived mesenchymal stem cells (ASCs) are considered to be a useful tool for regenerative medicine, owing to their capabilities in differentiation, self-renewal, and immunomodulation. These cells have become a focus in the clinical setting due to their abundance and easy isolation. However, ASCs [...] Read more.
Adipose-derived mesenchymal stem cells (ASCs) are considered to be a useful tool for regenerative medicine, owing to their capabilities in differentiation, self-renewal, and immunomodulation. These cells have become a focus in the clinical setting due to their abundance and easy isolation. However, ASCs from different depots are not well characterized. Here, we analyzed the functional similarities and differences of subcutaneous and visceral ASCs. Subcutaneous ASCs have an extraordinarily directed mode of motility and a highly dynamic focal adhesion turnover, even though they share similar surface markers, whereas visceral ASCs move in an undirected random pattern with more stable focal adhesions. Visceral ASCs have a higher potential to differentiate into adipogenic and osteogenic cells when compared to subcutaneous ASCs. In line with these observations, visceral ASCs demonstrate a more active sonic hedgehog pathway that is linked to a high expression of cilia/differentiation related genes. Moreover, visceral ASCs secrete higher levels of inflammatory cytokines interleukin-6, interleukin-8, and tumor necrosis factor α relative to subcutaneous ASCs. These findings highlight, that both ASC subpopulations share multiple cellular features, but significantly differ in their functions. The functional diversity of ASCs depends on their origin, cellular context and surrounding microenvironment within adipose tissues. The data provide important insight into the biology of ASCs, which might be useful in choosing the adequate ASC subpopulation for regenerative therapies. Full article
(This article belongs to the Special Issue Adipose-Derived Stromal/Stem Cells)
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Figure 1
<p>Subcutaneous and visceral adipose-derived mesenchymal stem cells (ASCs) display comparable cell surface marker profiles, cell cycle distribution and cell proliferation. (<b>A</b>) Immunofluorescence staining of mesenchymal stem cell surface markers CD90 (green) and CD73 (red), and DNA (DAPI, blue) in subcutaneous ASCs (ASCsub) and visceral ASCs (ASCvis). Scale: 20 μm. (<b>B</b>) Flow cytometric analyses of positive cell surface markers CD90, CD73, CD146, and CD105, and negative markers CD14, CD31, CD106, and CD34 for mesenchymal stem cells (MSCs). Values represent the percentages of ASCs expressing the indicated protein. The results from eight independent experiments (donors) are presented as mean ± standard error of the mean (SEM). (<b>C</b>,<b>D</b>) Cell cycle distribution was analyzed using a FACSCalibur<sup>TM</sup>. Profile examples were shown (<b>C</b>). Cell cycle phases of ASCs were presented in percentage and the results were derived from four independent experiments (<b>D</b>). (<b>E</b>,<b>F</b>) ASCs were stained for pHH3 (S10) (green), α-tubulin (yellow), pericentrin (red) and DNA (blue), and representatives are shown (<b>E</b>). Scale: 10 μm. pHH3 positive cells were quantified in ASCsub and ASCvis (<b>F</b>). The results are from three independent experiments with ASCs from three different donors and presented as median ± min/max whiskers in box plots. n.s. &gt; 0.05. (<b>G</b>) Cellular extracts from ASCs were prepared for Western blot analyses with indicated antibodies. β-actin served as loading control. (<b>H</b>) ASCs were seeded in 96-well plates for 0, 24, 48, 72, and 96 h. Cell viability was measured via CellTiter-Blue<sup>®</sup> assay. The results are presented as mean ± SEM and statistically analyzed, showing no significant difference (n.s.).</p>
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<p>Both ASC subtypes display a comparable motility rate, but subcutaneous ASCs have a significantly higher directed migration capacity. (<b>A</b>,<b>B</b>) Wound healing/migration assays were performed with subcutaneous and visceral ASCs, and images were taken at indicated time points (0, 8, 16, 24 h) to document the migration front. (<b>A</b>) Representatives are shown. White dashed line depicts the migration front. Scale: 300 μm. (<b>B</b>) Quantification of the open area between both migration fronts at various time points. The cell-free area at 0 h was assigned as 100%. The results from three independent experiments are presented as mean ± SEM. *** <span class="html-italic">p</span> &lt; 0.001. (<b>C</b>,<b>D</b>) Time-lapse microscopy was performed with subcutaneous or visceral ASCs for up to 12 h. Random motility of these cells was analyzed. (<b>D</b>) Representative trajectories of individual cells (<span class="html-italic">n</span> = 30) are shown. (<b>C</b>) Evaluated accumulated distance (left), velocity (middle), and directionality (right) from three independent experiments are shown as box plots with variations. Unpaired Mann–Whitney <span class="html-italic">U</span>-test, * <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span>&lt; 0.001. (<b>E</b>,<b>F</b>) Invasion assay. ASCs were seeded into transwells and starved for 12 h. The cells were released into fresh medium for 24 h and fixed for quantification. (<b>E</b>) Quantification of invaded cells per field in percent. The results from three independent experiments are presented as mean ± SEM. Student’s t test was performed showing no significant difference (n.s. &gt; 0.05). (<b>F</b>) Representatives of invaded ASCs are shown. Scale: 25 μm. (<b>G</b>,<b>H</b>) Homing assays. ASCs and breast cancer cells were seeded in separated chambers of a culture insert and cultured for 0, 8 and 15 h. (<b>G</b>) Evaluation of cell homing distance, the length between the nucleus and the outermost cell protrusion, in subcutaneous and visceral ASCs toward MCF-7 cells (left), MDA-MB-231 cells (middle), and ASC themselves (right). Each experiment was performed in triplicate, and the results are based on three independent experiments and presented as scatter plot showing mean ± SEM. (red dashed line indicates median value of ASCsub). ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. (<b>H</b>) Representatives of ASCs on both migration fronts stained against phalloidin (red) and DAPI (blue) are depicted. White bars indicate cellular protrusion length. Scale: 50 μm.</p>
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<p>Subcutaneous ASCs show a typical mesenchymal-like phenotype compared to their visceral counterparts. (<b>A</b>) Immunofluorescence staining of ASCsub and ASCvis. ASCs were stained for phalloidin (green), paxillin (red) and DNA (blue) to underline their cell morphology. Examples are shown. Scale: 25 μm. (<b>B</b>) Cellular extracts from ASCs were prepared for Western blot analyses with antibodies against β-actin, E-cadherin, fibronectin and vimentin. Glyceraldehyde-3-phosphate dehydrogenase (GAPDH) served as loading control. (<b>C</b>,<b>D</b>) Gene levels of mesenchymal associated transcription factors and cytoskeleton proteins <span class="html-italic">ZEB1</span>, <span class="html-italic">SNAIL, TWIST, VIM,</span> and <span class="html-italic">EpCAM</span> are shown for subcutaneous and visceral ASCs. The results are from three experiments, presented as RQ with minimum and maximum range. RQ, relative quantification of gene expression. Student’s t test, ∗ <span class="html-italic">p</span> &lt; 0.05. (<b>E</b>–<b>K</b>) The focal adhesion composition was analyzed by staining ASCs for focal adhesion kinase (FAK) (green), p-FAK (red), and DNA (DAPI, blue), or for p-paxillin (red), paxillin (green) and DNA (DAPI, blue) for fluorescence microscopy. Quantification of the mean fluorescence intensity of FAK (<b>E</b>), p-FAK (<b>F</b>)<b>,</b> paxillin (<b>G</b>) p-paxillin (<b>H</b>), and focal adhesion area (<b>I</b>) in ASCsub versus ASCvis (at least 200 FAs per staining). The results are based on three independent experiments and presented as scatter plot showing mean ± SEM. Unpaired Mann–Whitney <span class="html-italic">U</span>-test, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. a.u., arbitrary units. Representatives are depicted (<b>J</b>,<b>K</b>). Scale: 25 μm.</p>
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<p>Subcutaneous ASCs dynamically disassemble and reassemble their FAs. (<b>A</b>) Schedule of the nocodazole washout assay. (<b>B</b>) ASCs were incubated for 5 h with 10 µM nocodazole followed by washout, where the microtubules (MTs) were allowed to regrow for 0, 30 and 75 min. Cells were stained for paxillin (green), p-FAK (red), and DNA (DAPI, blue). Representatives of FA disassembly/reassembly are shown. Scale: 15 µm. (<b>C</b>–<b>E</b>) Kinetics of FA disassembly during MT regrowth and FA reassembly after MT regrowth. Quantification of the mean fluorescence intensity of paxillin (<b>C</b>), p-FAK (<b>D</b>), and FA size (<b>E</b>) (270 FA per condition) is depicted. The results are based on three independent experiments and presented as scatter plots showing mean ± SEM. Unpaired Mann–Whitney U-test, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. a.u., arbitrary units.</p>
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<p>Visceral ASCs are superior in osteogenic and adipogenic differentiation compared to subcutaneous ASCs. (<b>A</b>) Gene levels of stemness/self-renewal associated genes <span class="html-italic">c-MYC</span>, <span class="html-italic">SOX2</span>, <span class="html-italic">KLF4,</span> and <span class="html-italic">NANOG</span> are shown for subcutaneous and visceral ASCs. The results are from three experiments, presented as RQ with minimum and maximum range. Student’s t test, ∗ <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>–<b>D</b>) ASCsub and ASCvis cells were induced into osteogenic differentiation for up to 14 days. The percentage of differentiated ASCs was evaluated by Alizarin Red S staining. (<b>B</b>) The quantification data are presented as median ± min/max whiskers (red dashed line indicates median value of ASCsub, <span class="html-italic">n</span> = 300 cells for each condition, pooled from three experiments). Student’s t test, ∗<span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Example images for Alizarin Red S staining are shown. Scale: 20 μm. (<b>D</b>) Expression levels of differentiation related genes <span class="html-italic">PTCH1</span> (1<sup>st</sup> graph), <span class="html-italic">RUNX2</span> (2<sup>nd</sup> graph), <span class="html-italic">KLF4</span> (3<sup>rd</sup> graph), and <span class="html-italic">c-MYC</span> (4<sup>th</sup> graph) in differentiated subcutaneous and visceral ASCs. The results are from three experiments and presented as RQ with minimum and maximum range. Student’s t test, ∗ <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. (<b>E</b>–<b>G</b>) Analyses of cells with lipid vacuoles after 14 days of adipogenic differentiation. (<b>E</b>) The quantification shows the percentage of cells differentiated into adipogenic-like cells. Results are presented as median ± min/max whiskers in visceral ASCs (<span class="html-italic">n</span> = 200 cells for each condition, pooled from three experiments) and the red dashed line illustrates the median value of ASCsub. Student’s t test, ∗ <span class="html-italic">p</span> &lt; 0.05. (<b>F</b>) Representative images of cells displaying lipid vacuoles stained for adiponectin (red) and DNA (DAPI, blue). (<b>G</b>) Gene levels of <span class="html-italic">ADIPOQ, LEPTIN,</span> and <span class="html-italic">PPARγ</span> after adipogenic differentiation are shown for subcutaneous and visceral ASCs. The results are from three experiments, presented as RQ with minimum and maximum range. Student’s t test, ∗ <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Visceral ASCs display high deciliation gene levels and enhanced activation of the sonic hedgehog (Hh) signaling pathway. (<b>A</b>) Primary cilia of ASCsub and ASCvis were stained for acetylated α-tubulin and Arl13b. Representatives are shown. Scale: 10 μm. Regions outlined in boxes are shown in a higher magnification. Inset scale: 10 µm. (<b>B</b>) The cilium length was evaluated. The results are based on six experiments using ASCs from six donors (<span class="html-italic">n</span> = 180 cilia for each group). (<b>C</b>) Ciliated ASCs were evaluated and the results are presented as mean ± SEM (<span class="html-italic">n</span> = 600 cells, pooled from six experiments). Unpaired Mann–Whitney <span class="html-italic">U</span>-test, * <span class="html-italic">p</span> &lt; 0.05. (<b>D</b>) The gene levels of deciliation regulators <span class="html-italic">PLK1</span>, <span class="html-italic">PLK4,</span> and <span class="html-italic">KIF2A</span>. The data are based on three experiments and presented as RQ with minimum and maximum range. Student’s t test, ∗ <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. (<b>E</b>–<b>G</b>) Fluorescence intensities and expression levels of important genes related to the Hh pathway are shown for ASCs treated with SAG for 24 h. (<b>E</b>) Each point of the curve represents the mean fluorescence intensity (mean ± SEM) based on three experiments (<span class="html-italic">n</span> = 30 cilia). Unpaired Mann–Whitney <span class="html-italic">U</span>-test, * <span class="html-italic">p</span> &lt; 0.05. (<b>F</b>) Representatives are shown for measurements of primary cilium staining of acetylated α-tubulin, Arl13b and Smoothened (Smo). Scale: 3 μm. (G) The gene levels of <span class="html-italic"><span class="html-small-caps">GLI1</span></span>, <span class="html-italic">PTCH1</span>, <span class="html-italic">NANOG</span>, <span class="html-italic">SMO,</span> and <span class="html-italic">TP53</span> are shown for ASCs treated or non-treated with 200 nM SAG for 24 h. The results are from three experiments, merged as biological group, and presented as mean ± SEM. Student’s t 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>Visceral ASCs secrete more pro-inflammatory cytokines. (<b>A</b>) The supernatants of subcutaneous and visceral ASCs in the third passage were collected after 72 h culture and used for evaluation of IL-6 (left), IL-8 (middle) and TNF-α (right) by enzyme-linked immunosorbent assay (ELISA). The results are from four experiments and presented as median ± min/max whiskers in box plots. Student’s t test, <sup>∗</sup> <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. (<b>B</b>) The gene levels of <span class="html-italic">IL-6</span>, <span class="html-italic">IL-8</span>, <span class="html-italic">IL-10,</span> and <span class="html-italic">TNFα</span>. The data are based on three experiments and presented as RQ with minimum and maximum range. Student’s t test, <sup>∗</sup> <span class="html-italic">p</span> &lt; 0.05. (<b>C</b>) Schematic illustration of the proposed similarities and dissimilarities between both ASC subtypes. The key dissimilarities between subcutaneous and visceral ASCs are their migration mode, differentiation capacity, and cytokine secretion, which affect a variety of different pathways, like the Hh signaling on the primary cilium.</p>
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17 pages, 8243 KiB  
Article
Estimating Dynamic Cellular Morphological Properties via the Combination of the RTCA System and a Hough-Transform-Based Algorithm
by Lejun Zhang, Yang Ye, Rana Dhar, Jinsong Deng and Huifang Tang
Cells 2019, 8(10), 1287; https://doi.org/10.3390/cells8101287 - 21 Oct 2019
Cited by 10 | Viewed by 3397
Abstract
The xCELLigence real-time cell analysis (RTCA) system has the potential to detect cellular proliferation, migration, cytotoxicity, adherence, and remodeling. Although the RTCA system is widely recognized as a noninvasive and efficient tool for real-time monitoring of cellular fate, it cannot describe detailed cell [...] Read more.
The xCELLigence real-time cell analysis (RTCA) system has the potential to detect cellular proliferation, migration, cytotoxicity, adherence, and remodeling. Although the RTCA system is widely recognized as a noninvasive and efficient tool for real-time monitoring of cellular fate, it cannot describe detailed cell morphological parameters, such as length and intensity. Transforming growth factor beta(TGF-β) induced the epithelial–mesenchymal transition (EMT), which produces significant changes in cellular morphology, so we used TGF-β to treat A549 epithelial cells in this study. We compared it with lipopolysaccharide (LPS) and cigarette smoke extract (CSE) as stimulators. We developed an efficient algorithm to quantify the morphological cell changes. This algorithm is comprised of three major parts: image preprocessing, Hough transform (HT), and post-processing. We used the RTCA system to record the A549 cell index. Western blot was used to confirm the EMT. The RTCA system showed that different stimulators produce different cell index curves. The algorithm determined the lengths of the detected lines of cells, and the results were similar to the RTCA system in the TGF-β group. The Western blot results show that TGF-β changed the EMT markers, but the other stimulator remained unchanged. Optics-based computer vision techniques can supply the requisite information for the RTCA system based on good correspondence between the results. Full article
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Figure 1
<p>The framework of the digital image process. (<b>a</b>) Image preprocessing includes gray transformation, median filter, contrast manipulation, and canny edge detection; (<b>b</b>) Hough transform (HT) demonstrates the transformation between image space and parameter space; and (<b>c</b>) post-processing includes removing excessive lines and integrating intersecting lines.</p>
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<p>Two kinds of detection before and after post-processing. The red circles represent excessive lines for marking cells, and the blue circles represent lines with points of intersection.</p>
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<p>Changes in morphology and biomarkers in the transforming growth factor beta (TGF-β)-induced epithelial–mesenchymal transition (EMT) process of A549 cells. (<b>a</b>) Schematic treatment points of experimental design. After serum starvation for 24 h, cells were treated with TGF-β (10 ng/mL), lipopolysaccharide (LPS) (100 and 500 ng/mL), and cigarette smoke extract (CSE) (1% and 2%) for 48 h. (<b>b</b>) Representative images (original magnification 200×). Red arrows indicate a part of the typical cell shape (cobblestone type) in the control group, and blue arrows indicate a part of the fibroblast type of A549 cells after stimulation by TGF-β. (<b>c</b>) Representative bands and quantitative analysis of EMT markers (fibronectin, E-cadherin, and alpha smooth muscle actin (α-SMA). The expressions were detected by Western blot. GAPDH was used as the loading control. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01 vs. the control group, <span class="html-italic">n</span> = 3.</p>
Full article ">Figure 3 Cont.
<p>Changes in morphology and biomarkers in the transforming growth factor beta (TGF-β)-induced epithelial–mesenchymal transition (EMT) process of A549 cells. (<b>a</b>) Schematic treatment points of experimental design. After serum starvation for 24 h, cells were treated with TGF-β (10 ng/mL), lipopolysaccharide (LPS) (100 and 500 ng/mL), and cigarette smoke extract (CSE) (1% and 2%) for 48 h. (<b>b</b>) Representative images (original magnification 200×). Red arrows indicate a part of the typical cell shape (cobblestone type) in the control group, and blue arrows indicate a part of the fibroblast type of A549 cells after stimulation by TGF-β. (<b>c</b>) Representative bands and quantitative analysis of EMT markers (fibronectin, E-cadherin, and alpha smooth muscle actin (α-SMA). The expressions were detected by Western blot. GAPDH was used as the loading control. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01 vs. the control group, <span class="html-italic">n</span> = 3.</p>
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<p>Real-time detection cell index of A549 with different treatments in the xCELLigence real-time cell analysis (RTCA) single-plate (SP) (RTCA SP) system. (<b>a</b>) A549 cells were treated with TGF-β and LPS (100 and 500 ng/mL). The serum starvation step for 24 h starts from the blue vertical line to the black vertical line in the timeline. The time interval between the black and red vertical lines represents administration for 48 h, and the black vertical line is the time to normalize the cell index. Representative curves of the normalized cell index. (<b>b</b>) The representative interval slope of the TGF-β and LPS groups. (<b>c</b>) A549 cells were treated with TGF-β and CSE (1% and 2%). The conditions were the same as above. (<b>d</b>) The representative interval slope of the TGF-β and CSE groups. For the LPS experiment, <span class="html-italic">n</span> = 9; for the CSE experiment, <span class="html-italic">n</span> = 6. *** <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 vs. control group. ### <span class="html-italic">p</span> &lt; 0.01 24–48 h groups vs. 0–24 h groups. &amp;&amp;&amp; <span class="html-italic">p</span> &lt; 0.001 vs. TGF-β group in different time intervals.</p>
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<p>Morphological analysis of A549 cells using image processing techniques. The original pictures were obtained by optical microscope (200× magnification). (<b>a</b>) Representative images of A549 cells in the control and TGF-β groups from days 0 to 3. (<b>b</b>) Representative images of A549 cells in LPS (100 and 500 ng/mL) and CSE (1% and 2%) groups on days 2 and 3 (green: cell length; red: start point; yellow: end point).</p>
Full article ">Figure 5 Cont.
<p>Morphological analysis of A549 cells using image processing techniques. The original pictures were obtained by optical microscope (200× magnification). (<b>a</b>) Representative images of A549 cells in the control and TGF-β groups from days 0 to 3. (<b>b</b>) Representative images of A549 cells in LPS (100 and 500 ng/mL) and CSE (1% and 2%) groups on days 2 and 3 (green: cell length; red: start point; yellow: end point).</p>
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<p>The quantification of the length and quantity of detected lines. (<b>a</b>) A scatter dot plot of the length of the detected lines between the control and TGF-β groups. Pie charts represent the percentages of different length levels on day 2: 20–25, 25–30, 30–40, and &gt;40 pixels. (<b>b</b>) A scatter dot plot comparing the six different groups (control; TGF-β; LPS 100 ng/mL and 500 ng/mL; 1% and 2% CSE groups) on day 2. (<b>c</b>) A scatter dot comparing the six different treatments on day 3. (<b>d</b>) A line graph focused on the number of lines detected from day 0 to 3 in the six groups. <span class="html-italic">n</span> = 3. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01 vs. control group in different time points. ### <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 Day 1 vs. Day 2. <span>$</span><span>$</span> <span class="html-italic">p</span> &lt; 0.01, <span>$</span> <span class="html-italic">p</span> &lt; 0.05 Day 2 vs. Day 3. &amp;&amp;&amp; <span class="html-italic">p</span> &lt; 0.001 vs. TGF-β group in different time points.</p>
Full article ">Figure 6 Cont.
<p>The quantification of the length and quantity of detected lines. (<b>a</b>) A scatter dot plot of the length of the detected lines between the control and TGF-β groups. Pie charts represent the percentages of different length levels on day 2: 20–25, 25–30, 30–40, and &gt;40 pixels. (<b>b</b>) A scatter dot plot comparing the six different groups (control; TGF-β; LPS 100 ng/mL and 500 ng/mL; 1% and 2% CSE groups) on day 2. (<b>c</b>) A scatter dot comparing the six different treatments on day 3. (<b>d</b>) A line graph focused on the number of lines detected from day 0 to 3 in the six groups. <span class="html-italic">n</span> = 3. *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span> &lt; 0.01 vs. control group in different time points. ### <span class="html-italic">p</span> &lt; 0.001, ## <span class="html-italic">p</span> &lt; 0.01, # <span class="html-italic">p</span> &lt; 0.05 Day 1 vs. Day 2. <span>$</span><span>$</span> <span class="html-italic">p</span> &lt; 0.01, <span>$</span> <span class="html-italic">p</span> &lt; 0.05 Day 2 vs. Day 3. &amp;&amp;&amp; <span class="html-italic">p</span> &lt; 0.001 vs. TGF-β group in different time points.</p>
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17 pages, 2101 KiB  
Article
A Machine Learning-Based Prediction Platform for P-Glycoprotein Modulators and Its Validation by Molecular Docking
by Onat Kadioglu and Thomas Efferth
Cells 2019, 8(10), 1286; https://doi.org/10.3390/cells8101286 - 21 Oct 2019
Cited by 23 | Viewed by 4966
Abstract
P-glycoprotein (P-gp) is an important determinant of multidrug resistance (MDR) because its overexpression is associated with increased efflux of various established chemotherapy drugs in many clinically resistant and refractory tumors. This leads to insufficient therapeutic targeting of tumor populations, representing a major drawback [...] Read more.
P-glycoprotein (P-gp) is an important determinant of multidrug resistance (MDR) because its overexpression is associated with increased efflux of various established chemotherapy drugs in many clinically resistant and refractory tumors. This leads to insufficient therapeutic targeting of tumor populations, representing a major drawback of cancer chemotherapy. Therefore, P-gp is a target for pharmacological inhibitors to overcome MDR. In the present study, we utilized machine learning strategies to establish a model for P-gp modulators to predict whether a given compound would behave as substrate or inhibitor of P-gp. Random forest feature selection algorithm-based leave-one-out random sampling was used. Testing the model with an external validation set revealed high performance scores. A P-gp modulator list of compounds from the ChEMBL database was used to test the performance, and predictions from both substrate and inhibitor classes were selected for the last step of validation with molecular docking. Predicted substrates revealed similar docking poses than that of doxorubicin, and predicted inhibitors revealed similar docking poses than that of the known P-gp inhibitor elacridar, implying the validity of the predictions. We conclude that the machine-learning approach introduced in this investigation may serve as a tool for the rapid detection of P-gp substrates and inhibitors in large chemical libraries. Full article
(This article belongs to the Special Issue ABC Transporters: From Basic Functions to Diseases)
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Figure 1
<p>Receiver operating characteristic (ROC) curves of k Nearest Neighboring (kNN), Neural Network, Random Forest (RF), and Support Vector Machine (SVM) classification algorithms based on random leave-one-out sampling for the P-gp modulator/non-modulator prediction model for the learning step.</p>
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<p>ROC curves of kNN, Neural Network, RF, and SVM classification algorithms based on random leave-one-out sampling for the P-gp inhibitor/substrate prediction model for the learning step.</p>
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<p>Molecular docking results for selected non-modulators (pink).</p>
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<p>Molecular docking results for selected inhibitors (red) and substrates (green) yielded from the P-gp inhibitor/substrate prediction model. Elacridar (blue) and doxorubicin (yellow) were selected as control drugs.</p>
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<p>Boxplot analysis of the descriptors used for the model and comparison of the predicted inhibitors and substrates.</p>
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14 pages, 1399 KiB  
Review
Nuclear Mechanics in the Fission Yeast
by Paola Gallardo, Ramón R. Barrales, Rafael R. Daga and Silvia Salas-Pino
Cells 2019, 8(10), 1285; https://doi.org/10.3390/cells8101285 - 20 Oct 2019
Cited by 6 | Viewed by 5656
Abstract
In eukaryotic cells, the organization of the genome within the nucleus requires the nuclear envelope (NE) and its associated proteins. The nucleus is subjected to mechanical forces produced by the cytoskeleton. The physical properties of the NE and the linkage of chromatin in [...] Read more.
In eukaryotic cells, the organization of the genome within the nucleus requires the nuclear envelope (NE) and its associated proteins. The nucleus is subjected to mechanical forces produced by the cytoskeleton. The physical properties of the NE and the linkage of chromatin in compacted conformation at sites of cytoskeleton contacts seem to be key for withstanding nuclear mechanical stress. Mechanical perturbations of the nucleus normally occur during nuclear positioning and migration. In addition, cell contraction or expansion occurring for instance during cell migration or upon changes in osmotic conditions also result innuclear mechanical stress. Recent studies in Schizosaccharomyces pombe (fission yeast) have revealed unexpected functions of cytoplasmic microtubules in nuclear architecture and chromosome behavior, and have pointed to NE-chromatin tethers as protective elements during nuclear mechanics. Here, we review and discuss how fission yeast cells can be used to understand principles underlying the dynamic interplay between genome organization and function and the effect of forces applied to the nucleus by the microtubule cytoskeleton. Full article
(This article belongs to the Special Issue Nuclear Organisation)
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Figure 1
<p>Schematic representation of the fission yeast nucleus. Schematic representation of a fission yeast cell (above). Magnification of the area marked by dashed lines (below). Global chromosome organization with centromeres attached underneath the spindle pole body (SPB) and telomeres and nucleolus distantly positioned. Chromatin is linked to the nuclear envelope (NE) by the interaction of different genomic elements with inner nuclear membrane (INM) proteins and linker of nucleoskeleton and cytoskeleton (LINC) complexes. Note that the interaction of Lem2 protein with chromatin might be indirect. The NE is continuous with the perinuclear endoplasmic reticulum. The SBP and other microtubule organizing centers (MTOCs) organize antiparallel bundles of microtubules (MTs).</p>
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<p>NE microdomains and their association with different genomic regions. Schematic representation of the linkage between centromeres, telomeres, double strand breaks (DSBs) and other genomic loci and INM proteins. DSB repair factories are linked to the NE by the LINC complex and can be moved by cytoplasmic MTs and positioned in close proximity of the SPB. The different elements are depicted as in <a href="#cells-08-01285-f001" class="html-fig">Figure 1</a>.</p>
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<p>Fission yeast nucleus-SPB and NE under the forces produced by MTs. (<b>A</b>) Schematic representation of a fission yeast cell over time. The nucleus suffers periodic oscillations. Chromosomes are depicted as dark lines. SPB/centromeres are depicted in orange. MTs are depicted in green. The red color at MT ends represent stronger forces. (<b>B</b>) Image of the SPB (marked with GFP) showing regular oscillations around the cell center. Numbers correspond to those marked in A. Nuclear and SPB oscillations depend on alternative MT pushing (by polymerization) at each cell tip. (<b>C</b>) Schematic representation of the transmission of forces produced by cytoplasmic MTs to the chromatin, coupled to MT dynamics. (<b>D</b>) Schematic representation of a fission yeast nucleus under MT-dependent forces applied to the SPB, NE, and centromeric regions. Tethering of chromatin to the NE through INM proteins contributes to support nuclear mechanics. Notice that forces produced by other non-SPB MT bundles at other sites of the NE are not shown.</p>
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18 pages, 4480 KiB  
Article
Transcriptional Regulator TonEBP Mediates Oxidative Damages in Ischemic Kidney Injury
by Eun Jin Yoo, Sun Woo Lim, Hyun Je Kang, Hyun Park, Sora Yoon, Dougu Nam, Satoru Sanada, Mi Jin Kwon, Whaseon Lee-Kwon, Soo Youn Choi and Hyug Moo Kwon
Cells 2019, 8(10), 1284; https://doi.org/10.3390/cells8101284 - 20 Oct 2019
Cited by 2 | Viewed by 3753
Abstract
TonEBP (tonicity-responsive enhancer binding protein) is a transcriptional regulator whose expression is elevated in response to various forms of stress including hyperglycemia, inflammation, and hypoxia. Here we investigated the role of TonEBP in acute kidney injury (AKI) using a line of TonEBP haplo-deficient [...] Read more.
TonEBP (tonicity-responsive enhancer binding protein) is a transcriptional regulator whose expression is elevated in response to various forms of stress including hyperglycemia, inflammation, and hypoxia. Here we investigated the role of TonEBP in acute kidney injury (AKI) using a line of TonEBP haplo-deficient mice subjected to bilateral renal ischemia followed by reperfusion (I/R). In the TonEBP haplo-deficient animals, induction of TonEBP, oxidative stress, inflammation, cell death, and functional injury in the kidney in response to I/R were all reduced. Analyses of renal transcriptome revealed that genes in several cellular pathways including peroxisome and mitochondrial inner membrane were suppressed in response to I/R, and the suppression was relieved in the TonEBP deficiency. Production of reactive oxygen species (ROS) and the cellular injury was reproduced in a renal epithelial cell line in response to hypoxia, ATP depletion, or hydrogen peroxide. The knockdown of TonEBP reduced ROS production and cellular injury in correlation with increased expression of the suppressed genes. The cellular injury was also blocked by inhibitors of necrosis. These results demonstrate that ischemic insult suppresses many genes involved in cellular metabolism leading to local oxidative stress by way of TonEBP induction. Thus, TonEBP is a promising target to prevent AKI. Full article
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Graphical abstract

Graphical abstract
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<p>TonEBP (tonicity-responsive enhancer binding protein) expression in <span class="html-italic">TonEBP<sup>+/Δ</sup></span> (+/Δ, filled bars) mice and their <span class="html-italic">TonEBP<sup>+/+</sup></span> littermates (+/+, open bars) after ischemia/reperfusion (I/R) or sham treatment of kidneys. TonEBP and Hsc70 immunoblot were performed from renal cortices (<b>A</b>) and renal outer medullae (OM) (<b>B</b>), (<b>C</b>,<b>D</b>) Ratio of TonEBP and Hsc70 band intensity was determined and shown in arbitrary unit (AU). Mean + SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Renal tissues were obtained from <span class="html-italic">TonEBP<sup>+/Δ</sup></span> (+/Δ, filled bars) mice and their <span class="html-italic">TonEBP<sup>+/+</sup></span> littermates (+/+, open bars) after I/R treatment of kidneys. Tissue sections were stained with periodic acid-Schiff stain (PAS) and acute tubular necrosis (ATN) score was obtained. Tissue sections were also immunostained for 4-hydroxynonenal (4-HNE). 4-HNE positive area (%) was measured. Mean + SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Renal apoptosis and expression of apoptotic proteins in <span class="html-italic">TonEBP<sup>+/Δ</sup></span> (+/Δ, filled bars) mice and their <span class="html-italic">TonEBP<sup>+/+</sup></span> littermates (+/+, open bars) after I/R or sham treatment of kidneys. (<b>A</b>) Kidney sections were stained for TUNEL. TUNEL-positive cells were counted and expressed as number per high power field (HPF), (<b>B</b>) Renal cortices were immunoblotted for Bax, Bcl-2, and Hsc70, (<b>C</b>,<b>D</b>) Ratio of band intensity, Bax/Hsc70, and Bcl-2/Hsc70, was calculated and shown in arbitrary unit (AU). Mean + SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Serum creatinine (S<sub>cr</sub>, <b>A</b>), blood urea nitrogen (BUN, <b>B</b>), urine osmolality (U<sub>osm</sub>, <b>C</b>), fractional excretion of sodium (FE<sub>Na</sub>, <b>D</b>), and mRNA abundance for Kim-1 in renal cortices (<b>E</b>) from <span class="html-italic">TonEBP<sup>+/Δ</sup></span> (filled bars) mice and their <span class="html-italic">TonEBP<sup>+/+</sup></span> littermates (open bars) after I/R or sham treatment of kidneys. Mean + SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of TonEBP knockdown and inhibitors on cell viability and release of lactate dehydrogenase (LDH). (<b>A</b>) HK-2 cells were transfected with TonEBP targeted siRNA (filled bars) or scrambled (non-targeting) siRNA (open bars). Cells were then incubated with hypoxia (1% O<sub>2</sub>) for 24 h, ATP depletion (AD—10 μM of antimycin A and 10 mM 2-deoxy-<span class="html-small-caps">d</span>-glucose, or ACD—10 μM of antimycin A, 10 mM 2-deoxy-<span class="html-small-caps">d</span>-glucose and 1 μM of ionomycin) for 3 h, or H<sub>2</sub>O<sub>2</sub> treatment for 1 h. (<b>B</b>) Cells were pretreated for 60 min with vehicle (VH), cyclosporin A (CsA, 1 μM), ferrostatin-1 (Fer-1, 0.5 μM), or necrostatin-1 (Nec-1, 5 μM) followed by ATP depletion for 3 h or treatment with 1 mM H<sub>2</sub>O<sub>2</sub> for 1 h. CTL, not treated. Mean + SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of TonEBP knockdown on apoptosis. (<b>A</b>) HK-2 cells were transfected with TonEBP targeted siRNA or scrambled siRNA followed by hypoxia, ATP depletion, or H<sub>2</sub>O<sub>2</sub> treatment. The cells were then labeled with propidium iodide (PI) and annexin V and analyzed using fluorescence-activated cell sorting. (<b>B</b>) Percentage of cells of early apoptosis (positive for annexin V and negative for PI) and late apoptosis / dead (positive for both PI and annexin V) is shown in Mean + SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of TonEBP knockdown on the expression of Bax and Bcl-2. HK-2 cells were transfected with TonEBP targeted siRNA (Ton, filled bars) or scrambled siRNA (Scr, open bars) followed by hypoxia (<b>A</b>), ATP depletion (<b>B</b>), or H<sub>2</sub>O<sub>2</sub> treatment (<b>C</b>). CTL, not treated. Cell lysates were immunoblotted for TonEBP, Bax, Bcl-2 and Hsc7, (<b>D</b>) TonEBP/Hsc70, Bax/Hsc70 and Bcl-2/Hsc70 ratio are shown. Mean ± SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>A heatmap of genes whose expression was significantly higher in the <span class="html-italic">TonEBP<sup>+/Δ</sup></span> mice over their <span class="html-italic">TonEBP<sup>+/+</sup></span> littermates after I/R treatment of kidneys, as described in <a href="#cells-08-01284-t002" class="html-table">Table 2</a>. Numbers 1 to 4 at the bottom denote individual animals (n = 4).</p>
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<p>RT-qPCR analyses of kidneys (left) and HK-2 cells (right) for selected genes in the clusters shown in <a href="#cells-08-01284-t002" class="html-table">Table 2</a>: (<b>A</b>) peroxisome, (<b>B</b>) mitochondrial inner membrane, (<b>C</b>) PPAR signaling pathways, (<b>D</b>) glycolysis/gluconeogenesis. Kidneys were isolated from <span class="html-italic">TonEBP<sup>+/Δ</sup></span> (filled bars) mice and their <span class="html-italic">TonEBP<sup>+/+</sup></span> littermates (open bars) after I/R or sham treatment. HK-2 cells were transfected with scrambled (open bars) or TonEBP-targeted siRNA (filled bars) followed by treatment with hypoxia (1% O<sub>2</sub>), ATP depletion (10 μM of A.A. and 10 mM of 2-DG) or 0.5 mM H<sub>2</sub>O<sub>2</sub> for 3 h. Mean + SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Effects of TonEBP deficiency on oxidative stress in kidneys and HK-2 cells. Renal I/R or sham treatment was performed on <span class="html-italic">TonEBP<sup>+/Δ</sup></span> mice (+/Δ, filled bars) and their <span class="html-italic">TonEBP<sup>+/+</sup></span> littermates (+/+, open bars). (<b>A</b>) Kidney sections were stained for 8-OHdG. 8-OHdG and creatinine were measured from urine samples and their ratios in ng/mg are shown (<b>B</b>). (<b>C</b>) HK-2 cells were transfected with TonEBP targeted (open bars) or scrambled siRNA (filled bars) followed by no treatment (CTL), or treatment with hypoxia, ATP depletion, or H<sub>2</sub>O<sub>2</sub>. Fluorescent images of DCF (green) and Hoechst 33342 (blue) in HK-2 cells loaded with DCF-DA are shown at the top. DCF fluoresence intensity as Mean ± SEM is shown at the bottom. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Model for the role of TonEBP in acute kidney injury. Mitochondrial damage in response to ischemia (as well as sepsis and cisplatin) leads to the production of reactive oxygen species (ROS) in addition release of cytochrome c and mitochondrial DNA in renal tubules. Induced by ROS, TonEBP promotes further ROS production via suppression of genes involved in cellular pathways including peroxisome, mitochondrial inner membrane, PPAR signaling, and glycolysis/gluconeogenesis. ROS causes apoptosis and necorinflammation (cell death and inflammation) in tubular cells leading to functional kidney injury. See text for details.</p>
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15 pages, 1676 KiB  
Article
Increased Expression of Meteorin-Like Hormone in Type 2 Diabetes and Obesity and Its Association with Irisin
by Irina AlKhairi, Preethi Cherian, Mohamed Abu-Farha, Ashraf Al Madhoun, Rasheeba Nizam, Motasem Melhem, Mohamed Jamal, Suleiman Al-Sabah, Hamad Ali, Jaakko Tuomilehto, Fahd Al-Mulla and Jehad Abubaker
Cells 2019, 8(10), 1283; https://doi.org/10.3390/cells8101283 - 19 Oct 2019
Cited by 58 | Viewed by 5721
Abstract
Type 2 diabetes (T2D) is a growing pandemic associated with metabolic dysregulation and chronic inflammation. Meteorin-like hormone (METRNL) is an adipomyokine that is linked to T2D. Our objective was to evaluate the changes in METRNL levels in T2D and obesity and assess the [...] Read more.
Type 2 diabetes (T2D) is a growing pandemic associated with metabolic dysregulation and chronic inflammation. Meteorin-like hormone (METRNL) is an adipomyokine that is linked to T2D. Our objective was to evaluate the changes in METRNL levels in T2D and obesity and assess the association of METRNL levels with irisin. Overall, 228 Arab individuals were enrolled. Plasma levels of METRNL and irisin were assessed using immunoassay. Plasma levels of METRNL and irisin were significantly higher in T2D patients than in non-diabetic patients (p < 0.05). When the population was stratified based on obesity, METRNL and irisin levels were significantly higher in obese than in non-obese individuals (p < 0.05). We found a significant positive correlation between METRNL and irisin (r = 0.233 and p = 0.001). Additionally, METRNL and irisin showed significant correlation with various metabolic biomarkers associated with T2D and Obesity. Our data shows elevated METRNL plasma levels in individuals with T2D, further exacerbated with obesity. Additionally, a strong positive association was observed between METRNL and irisin. Further studies are necessary to examine the role of these proteins in T2D and obesity, against their ethnic background and to understand the mechanistic significance of their possible interplay. Full article
(This article belongs to the Special Issue Adipocytes and Metabolic Health)
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<p>Meteorin-like hormone (METRNL) level in plasma in all populations (n = 228). (<b>A</b>) Comparing non-diabetic to T2D individuals; (<b>B</b>) comparing non-obese to obese individuals. The METRNL level in plasma was determined using enzyme linked immunosorbent assay (ELISA). The population was classified on the basis of their diabetic status (<b>A</b>). Diabetes was defined by fasting plasma glucose ≥ 126 mg/L (7 mmol/L). Furthermore, the population was classified on the basis of obesity (<b>B</b>). Obesity was defined based on BMI, where participants with BMI &gt; 30 kg/m<sup>2</sup> were considered obese and those with BMI between 20 and 30 kg/m<sup>2</sup> were considered non-obese. Statistical assessment was 2-sided and considered statistically significant at * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>METRNL level in plasma following sub-classification into four groups: non-diabetic non-obese and obese (n = 124), and T2D non-obese and obese (n = 104). (<b>A</b>) Comparing non-diabetic non-obese to obese individuals; (<b>B</b>) plasma level of METRNL in T2D comparing non-obese to obese individuals. METRNL level in plasma was determined using enzyme linked immunosorbent assay. The population was classified on the basis of their diabetic status and further sub-classified on the basis of obesity. Diabetes was defined by fasting plasma glucose ≥ 126 mg/L (7 mmol/L). Obesity was defined based on BMI, where participants with BMI &gt; 30 kg/m<sup>2</sup> were considered obese and those with BMI between 20 and 30 kg/m<sup>2</sup> were considered non-obese. Statistical assessment was 2-sided and considered statistically significant at * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Irisin level in plasma in all populations (n = 228). (<b>A</b>) Comparing non-diabetic to T2D individuals; (<b>B</b>) comparing non-obese to obese individuals (n = 228). Irisin level in plasma was determined using enzyme linked immunosorbent assay. The population was classified on the basis of their diabetic status (<b>A</b>). Diabetes was defined by fasting plasma glucose ≥ 126 mg/L (7 mmol/L). Furthermore, the population was classified on the basis of obesity (<b>B</b>). Obesity was defined based on BMI, where participants with BMI &gt; 30 kg/m<sup>2</sup> were considered obese and those with BMI between 20 and 30 kg/m<sup>2</sup> were considered non-obese. Statistical assessment was 2-sided and considered statistically significant at ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Irisin level in plasma following sub-classification into four groups: non-diabetic non-obese and obese (n = 124) and T2D non-obese and obese (n = 104). (<b>A</b>) Comparing the plasma level of irisin in non-diabetic non-obese and obese individuals; (<b>B</b>) comparing the plasma level of irisin in T2D non-obese and obese individuals. Irisin level in plasma was determined using enzyme linked immunosorbent assay. The population was classified on the basis of their diabetic status and further sub-classified on the basis of obesity. Diabetes was defined by fasting plasma glucose ≥ 126 mg/L (7 mmol/L). Obesity was defined based on BMI, where participants with BMI &gt; 30 kg/m<sup>2</sup> were considered obese and those with BMI between 20 and 30 kg/m<sup>2</sup> were considered non-obese. Statistical assessment was 2-sided and considered statistically significant at ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Correlation analysis between METRNL and irisin levels in plasma. (<b>A</b>) All populations. (<b>B</b>) Individuals with T2D. (<b>C</b>) Non-diabetic individuals. METRNL and irisin levels in plasma were determined using enzyme linked immunosorbent assay. Diabetes was defined by fasting plasma glucose ≥ 126 mg/L (7 mmol/L). Spearman correlation coefficient was used to determine the association of METRNL with irisin. Statistical assessment was 2-sided and considered statistically significant at ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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15 pages, 3727 KiB  
Article
Differentiation of Baboon (Papio anubis) Induced-Pluripotent Stem Cells into Enucleated Red Blood Cells
by Emmanuel N. Olivier, Kai Wang, Joshua Grossman, Nadim Mahmud and Eric E. Bouhassira
Cells 2019, 8(10), 1282; https://doi.org/10.3390/cells8101282 - 19 Oct 2019
Cited by 3 | Viewed by 5002
Abstract
As cell culture methods and stem cell biology have progressed, the in vitro production of cultured RBCs (cRBCs) has emerged as a viable option to produce cells for transfusion or to carry therapeutic cargoes. RBCs produced in culture can be quality-tested either by [...] Read more.
As cell culture methods and stem cell biology have progressed, the in vitro production of cultured RBCs (cRBCs) has emerged as a viable option to produce cells for transfusion or to carry therapeutic cargoes. RBCs produced in culture can be quality-tested either by xeno-transfusion of human cells into immuno-deficient animals, or by transfusion of autologous cells in immuno-competent models. Although murine xeno-transfusion methods have improved, they must be complemented by studies in immuno-competent models. Non-human primates (NHPs) are important pre-clinical, large animal models due to their high biological and developmental similarities with humans, including their comparable hematopoietic and immune systems. Among NHPs, baboons are particularly attractive to validate cRBCs because of the wealth of data available on the characteristics of RBCs in this species that have been generated by past blood transfusion studies. We report here that we have developed a method to produce enucleated cRBCs by differentiation of baboon induced pluripotent stem cells (iPSCs). This method will enable the use of baboons to evaluate therapeutic cRBCs and generate essential pre-clinical data in an immuno-competent, large animal model. Production of the enucleated baboon cRBCs was achieved by adapting the PSC-RED protocol that we previously developed for human cells. Baboon-PSC-RED is an efficient chemically-defined method to differentiate iPSCs into cRBCs that are about 40% to 50% enucleated. PSC-RED is relatively low cost because it requires no albumin and only small amounts of recombinant transferrin. Full article
(This article belongs to the Special Issue iPS Cells for Disease Modeling)
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<p>Production of baboon iPSCs: (<b>a</b>) FACS analysis of human and baboon iPSCs grown in chemically-defined-conditions. Blue histogram: human iPSCs; red histograms: baboon iPSCs; grey histograms: isotype controls. Baboon iPSCs express pluripotency markers albeit at lower levels than human iPSCs. (<b>b</b>) Teratoma analysis. 1 × 10<sup>6</sup> baboon iPSCs were injected intramuscularly into the hind leg of a 6–8 week old NSG mouse. Six weeks later, tumors were fixed in 10% formalin, paraffin embedded, sectioned, and stained with hematoxylin/eosin. Tumors from two different iPSC clones are shown. Structures originating from all three germ layers were found in most tumors analyzed; (<b>c</b>) embryoid bodies were formed using the hanging drop method in 20% FBS for 10 days. Cells were fixed with paraformaldehyde, stained with indicated antibodies, and counterstained with DAPI. Cells expressing α-feto-protein (endoderm), α-smooth muscle actin (mesoderm) and β-III-tubulin were detectable in 10-day EBs. Baboon iPSCs maintained in chemically-defined conditions are pluripotent; (<b>d</b>) karyotyping: two clones of iPSCs were analyzed using standard karyotyping methods.</p>
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<p>PSC-RED protocols: (<b>a</b>) Scheme illustrating the long PSC-RED protocol to produce enucleated cultured RBCs (cRBCs) from iPSC. In the short version of the protocol, the expansion step in S4 from day 10 to day 16 is omitted. Media and cytokine supplements are described in the Methods section; (<b>b</b>) graphs illustrating the number of cRBCs/iPSCs observed during the erythroid differentiation of two different baboon iPSC clones (clone 1 and clone 3) using the short or long PSC-RED protocols. Data are expressed as average ± SEM of 3 independent experiments.</p>
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<p>Morphological analysis of baboon iPSCs differentiating into cRBCs using the short PSC-RED protocol. 630x magnification micrograph illustrating the typical morphology of the erythroid cells observed at days 17, 24, 27, 31, and 35 of culture after rapid Romanowsky staining. The majority of cells were pro or basophilic erythroblasts at day 17, and orthochromatic erythroblasts at day 35.</p>
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<p>Morphological analysis of baboon iPSCs differentiating into cRBCs using the long PSC-RED protocol: 630x magnification micrograph illustrating the typical morphology of the erythroid cells observed at days 22, 31, 34, 38, and 42 of culture after rapid Romanowsky staining. The majority of cells were pro-erythroblasts at day 22, and orthochromatic erythroblasts and reticulocytes at day 42.</p>
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<p>Differentiation analysis: (<b>a</b>) Cells were spun on microscope slides, stained using the rapid Romanowsky methods and classified as proE (pro-erythroblasts); basoE (basophilic erythroblasts); polyE (polychromatophilic erythroblasts); orthoE (orthochromatophilic erythroblasts) or retic. (reticulocytes (enucleated cRBCs)). Graphs illustrate the average (±SD) number of erythroid precursors during differentiation using either the short (left) or long (right) PSC-RED protocols (<span class="html-italic">n</span> = 2); (<b>b</b>) FACS plots representative of the enucleation rates as determined by DNA content measurement using Draq5. The rate of enucleation is much higher using the long protocol (Student’s <span class="html-italic">t</span>-test <span class="html-italic">p</span>-value between the rate of enucleation short and long protocol in s: &lt;0.00001) (<b>c</b>) FACS plots illustrating the proportion of erythroid cells during the culture using anti-baboon RBCs antibody E34-731.</p>
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<p>Globin expression. (<b>a</b>) HPLC chromatograms illustrating globin expression. Cultured RBCs obtained at day 32 (short-protocol) or 36 (long-protocol) were lysed and analyzed by HPLCs. RBCs from an adult baboon were used as controls (lower chromatogram). ζ and ε-globins are expressed at lower levels in cells obtained with the short protocol; (<b>b</b>) histograms summarizing the results of the HPLC analysis. Percentage of a-like = 100 × (α or ζ)/(α + ζ). Percentage of β-like = 100 × (ε( Gα + Aγ) or β)/(ε + Gγ + Aγ + β). Data are the average ± SEM of four independent experiments. The long PSC-RED protocol yields more developmentally mature cells.</p>
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19 pages, 1934 KiB  
Review
Enhancer Dysfunction in 3D Genome and Disease
by Ji-Han Xia and Gong-Hong Wei
Cells 2019, 8(10), 1281; https://doi.org/10.3390/cells8101281 - 19 Oct 2019
Cited by 13 | Viewed by 9342
Abstract
Spatiotemporal patterns of gene expression depend on enhancer elements and other factors during individual development and disease progression. The rapid progress of high-throughput techniques has led to well-defined enhancer chromatin properties. Various genome-wide methods have revealed a large number of enhancers and the [...] Read more.
Spatiotemporal patterns of gene expression depend on enhancer elements and other factors during individual development and disease progression. The rapid progress of high-throughput techniques has led to well-defined enhancer chromatin properties. Various genome-wide methods have revealed a large number of enhancers and the discovery of three-dimensional (3D) genome architecture showing the distant interacting mechanisms of enhancers that loop to target gene promoters. Whole genome sequencing projects directed at cancer have led to the discovery of substantial enhancer dysfunction in misregulating gene expression and in tumor initiation and progression. Results from genome-wide association studies (GWAS) combined with functional genomics analyses have elucidated the functional impacts of many cancer risk-associated variants that are enriched within the enhancer regions of chromatin. Risk variants dysregulate the expression of enhancer variant-associated genes via 3D genomic interactions. Moreover, these enhancer variants often alter the chromatin binding affinity for cancer-relevant transcription factors, which in turn leads to aberrant expression of the genes associated with cancer susceptibility. In this review, we investigate the extent to which these genetic regulatory circuits affect cancer predisposition and how the recent development of genome-editing methods have enabled the determination of the impacts of genomic variation and alteration on cancer phenotype, which will eventually lead to better management plans and treatment responses to human cancer in the clinic. Full article
(This article belongs to the Special Issue Nuclear Organisation)
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<p>Active enhancers promote high-level gene expression. Epigenetic marks for active enhancers usually include H3K4me1 (monomethylation of H3 lysine 4) and H3K27ac whereas the trimethylation of histone H3 lysine 4 (H3K4me3) is often enriched at gene promoters. The active enhancers regulate gene transcription through chromatin looping with the promoters of target genes. Thus, looping formation eventually contributes to the recruitment of transcription factors, coactivators, and RNA polymerase, promoting high levels of target gene expressions.</p>
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<p>Genome-wide identification of cis-regulatory drivers, the enhancers. The cells were cross-linked with formaldehyde, and glycine was added to stop the reaction. Cell pellets were collected and suspended to isolate the nuclei. Chromatin was prepared by sonication into certain size, and the fragments were incubated with antibodies against target proteins. Then, extraction buffer was added to extract and purify the DNA from the complexes. The target DNA fragments were enriched and sequenced by using ChIP-seq in combination with bioinformatics analysis. According to the called ChIP-seq peaks, the enhancer elements in the chromatin can be identified.</p>
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<p>Looping between clusters of activators, mediators and transcription factors in enhancer and promoter regions. The enhancer region of chromatin is bound by the transcriptional complexes including various activators, mediators and transcription factors, which form enhancer clusters. The enhancer interacts with the promoter region, which combines with transcription factors and RNA polymerase to increase the rate of gene transcription.</p>
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<p>Enhancers in gene regulation and disease. (<b>A</b>) The aggressive G allele of rs11672691 enhances the binding of transcription factor HOXA2, thus increasing the expression level of the plausible candidate genes PCAT19 and CEACAM21, which results in prostate cancer cell growth and progression. (<b>B</b>) In wild-type cells, the driver of transcription factor binding with other factors in the enhancer region contributes to promoter interaction with the promoter of target genes to upregulate gene expression. However, in disease conditions, genetic variation and chromosomal aberrations affect the binding affinity of clusters of activators, mediators, and transcription factors, thereby dysregulating the expression of target genes.</p>
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<p>Integrated analysis of germline and somatic mutations. The mutation in germline and somatic cells can be tested by high-throughput sequencing techniques at the genetic or transcript level. Integrated analyses of disease-related gene expression or pathways combined with histological data might contribute to the identification of biomarkers for disease diagnoses and treatment.</p>
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21 pages, 2338 KiB  
Review
The Adaptive Immune System in Multiple Sclerosis: An Estrogen-Mediated Point of View
by Alessandro Maglione, Simona Rolla, Stefania Federica De Mercanti, Santina Cutrupi and Marinella Clerico
Cells 2019, 8(10), 1280; https://doi.org/10.3390/cells8101280 - 19 Oct 2019
Cited by 27 | Viewed by 5160
Abstract
Multiple sclerosis (MS) is a chronic central nervous system inflammatory disease that leads to demyelination and neurodegeneration. The third trimester of pregnancy, which is characterized by high levels of estrogens, has been shown to be associated with reduced relapse rates compared with the [...] Read more.
Multiple sclerosis (MS) is a chronic central nervous system inflammatory disease that leads to demyelination and neurodegeneration. The third trimester of pregnancy, which is characterized by high levels of estrogens, has been shown to be associated with reduced relapse rates compared with the rates before pregnancy. These effects could be related to the anti-inflammatory properties of estrogens, which orchestrate the reshuffling of the immune system toward immunotolerance to allow for fetal growth. The action of these hormones is mediated by the transcriptional regulation activity of estrogen receptors (ERs). Estrogen levels and ER expression define a specific balance of immune cell types. In this review, we explore the role of estradiol (E2) and ERs in the adaptive immune system, with a focus on estrogen-mediated cellular, molecular, and epigenetic mechanisms related to immune tolerance and neuroprotection in MS. The epigenome dynamics of immune systems are described as key molecular mechanisms that act on the regulation of immune cell identity. This is a completely unexplored field, suggesting a future path for more extensive research on estrogen-induced coregulatory complexes and molecular circuitry as targets for therapeutics in MS. Full article
(This article belongs to the Special Issue The Molecular and Cellular Basis for Multiple Sclerosis)
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<p>Estradiol levels in the bloodstream vary throughout a woman’s lifespan. The mean value during childhood is 200 pg/mL. During fertility age, the menstrual cycle range is 100–400 pg/mL. The pregnancy condition (highlighted in pink) is characterized by a huge increase in levels of circulating estradiol from the first trimester to delivery, with a range of 2000–15,000 pg/mL. During menopause, the level of estrogens drops drastically to &lt;100 pg/mL. Data retrieved from Watson et al., 2010 [<a href="#B36-cells-08-01280" class="html-bibr">36</a>].</p>
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<p>The three main different isoforms of ERα are presented: the full-length 66 kDa ERα (ERα66), the AF-1 domain-truncated 46 kDa variant of ERα (ERα46), and a 36 kDa ERα variant (ERα36) that lacks both AF-1 and AF-2 domains [<a href="#B43-cells-08-01280" class="html-bibr">43</a>,<a href="#B44-cells-08-01280" class="html-bibr">44</a>,<a href="#B45-cells-08-01280" class="html-bibr">45</a>]. The relative protein levels in different immune system cells are indicated by ++, +, or ND (not detected) [<a href="#B61-cells-08-01280" class="html-bibr">61</a>,<a href="#B65-cells-08-01280" class="html-bibr">65</a>].</p>
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<p>ERα and ERβ expression in the immune system. The bar plots represent gene expression data of the human genes <span class="html-italic">ESR1</span> and <span class="html-italic">ESR2</span>, which encode for ERα and ERβ, respectively. Data were retrieved from the Database of Immune Cell expression, expression quantitative trait loci (eQTL), and epigenomics (DICE) [<a href="#B67-cells-08-01280" class="html-bibr">67</a>]. RNA-Seq data are normalized between samples and expressed in transcripts per million (TPM). Data were generated from 13 immune cell types from 91 healthy subjects. The cell types include: three innate immune cell types (CD14high CD16− classical monocytes, CD14− CD16+ non-classical monocytes, and CD56dim CD16+ natural killer (NK) cells); four adaptive immune cell types that have not encountered their cognate antigen in the periphery (naive B cells, naive CD4+ T cells, naive CD8+ T cells, and naive Treg cells); six differentiated T cell subsets (Th1, Th1/17, Th17, Th2, follicular helper T cells (TFH), and memory Treg cells); and two ex vivo activated cell types (naive CD4+ and CD8+ T cells).</p>
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<p>E2 regulates cytokine production in CD4+ T cells. As estrogen levels increase, IFN-γ and TNF-α production decreases, while IL-10 secretion increases.</p>
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<p>A model of ERα-dependent modulation of nuclear organization of chromatin in T helper cells. Estrogens participate in the mechanisms of transcriptional regulation through the binding of ERα at regulatory regions, thereby influencing the phenotype of T helper cells. Estrogens at normal levels promote the binding and activation of Th17 lineage-specific TFs (e.g., <span class="html-italic">RORC</span>), whereas estrogens at pregnancy levels bind preferentially to Treg lineage-specific TFs, thus inhibiting RORC and promoting <span class="html-italic">FOXP3</span> transcriptional activation [<a href="#B90-cells-08-01280" class="html-bibr">90</a>]. ERα may participate with TFs that are specific for Th17 and Treg lineages in chromatin remodeling in these cells, although the mechanisms are still unclear.</p>
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26 pages, 1395 KiB  
Review
Magnetic-Assisted Treatment of Liver Fibrosis
by Kateryna Levada, Alexander Omelyanchik, Valeria Rodionova, Ralf Weiskirchen and Matthias Bartneck
Cells 2019, 8(10), 1279; https://doi.org/10.3390/cells8101279 - 19 Oct 2019
Cited by 28 | Viewed by 6835
Abstract
Chronic liver injury can be induced by viruses, toxins, cellular activation, and metabolic dysregulation and can lead to liver fibrosis. Hepatic fibrosis still remains a major burden on the global health systems. Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are considered [...] Read more.
Chronic liver injury can be induced by viruses, toxins, cellular activation, and metabolic dysregulation and can lead to liver fibrosis. Hepatic fibrosis still remains a major burden on the global health systems. Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH) are considered the main cause of liver fibrosis. Hepatic stellate cells are key targets in antifibrotic treatment, but selective engagement of these cells is an unresolved issue. Current strategies for antifibrotic drugs, which are at the critical stage 3 clinical trials, target metabolic regulation, immune cell activation, and cell death. Here, we report on the critical factors for liver fibrosis, and on prospective novel drugs, which might soon enter the market. Apart from the current clinical trials, novel perspectives for anti-fibrotic treatment may arise from magnetic particles and controlled magnetic forces in various different fields. Magnetic-assisted techniques can, for instance, enable cell engineering and cell therapy to fight cancer, might enable to control the shape or orientation of single cells or tissues mechanically. Furthermore, magnetic forces may improve localized drug delivery mediated by magnetism-induced conformational changes, and they may also enhance non-invasive imaging applications. Full article
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<p>Cells, their roles, and potential targets in liver fibrosis. Liver disease is in most cases initiated by a noxa that leads to hepatocyte cell death. Cytokines secreted by immune and other cell types promote hepatocyte cell injury, i.e., the tumor necrosis factor (TNF) triggers apoptosis of hepatocytes. Hepatic collagen deposition by activated hepatic stellate cells is a hallmark of fibrosis and in part is facilitated by extracellular enzymes.</p>
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<p>Applications of magnetic nanoparticles in medicine and biotechnology. We would like to highlight four main fields of application for magnetic materials and have chosen some representative schemes for each field of application.</p>
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<p>Ligand-based targeting of hepatic stellate cells. Hepatic stellate cells can be targeted based on their expression of receptors on their surface, in the cytoplasm, or inside the cell nucleus. The endocytic route allows the transport of HSC-directed sncRNA, small molecules, or liposomal carriers.</p>
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21 pages, 3076 KiB  
Article
Intrinsically Disordered SRC-3/AIB1 Protein Undergoes Homeostatic Nuclear Extrusion by Nuclear Budding While Ectopic Expression Induces Nucleophagy
by Miguel A. Cabrita, L. Isabel Renart, Rosanna Lau and M. A. Christine Pratt
Cells 2019, 8(10), 1278; https://doi.org/10.3390/cells8101278 - 19 Oct 2019
Cited by 2 | Viewed by 4278
Abstract
SRC-3/AIB1 (Amplified in Breast Cancer-1) is a nuclear receptor coactivator for the estrogen receptor in breast cancer cells. It is also an intrinsically disordered protein when not engaged with transcriptional binding partners and degraded upon transcriptional coactivation. Given the amplified expression of SRC-3 [...] Read more.
SRC-3/AIB1 (Amplified in Breast Cancer-1) is a nuclear receptor coactivator for the estrogen receptor in breast cancer cells. It is also an intrinsically disordered protein when not engaged with transcriptional binding partners and degraded upon transcriptional coactivation. Given the amplified expression of SRC-3 in breast cancers, the objective of this study was to determine how increasing SRC-3 protein levels are regulated in MCF-7 breast cancer cells. We found that endogenous SRC-3 was expelled from the nucleus in vesicle-like spheres under normal growth conditions suggesting that this form of nuclear exclusion of SRC-3 is a homeostatic mechanism for regulating nuclear SRC-3 protein. Only SRC-3 not associated with CREB-binding protein (CBP) was extruded from the nucleus. We found that overexpression in MCF-7 cells results in aneuploid senescence and cell death with frequent formation of nuclear aggregates which were consistently juxtaposed to perinuclear microtubules. Transfected SRC-3 was SUMOylated and caused redistribution of nuclear promyelocytic leukemia (PML) bodies and perturbation of the nuclear membrane lamin B1, hallmarks of nucleophagy. Increased SRC-3 protein-induced autophagy and resulted in SUMO-1 localization to the nuclear membrane and formation of protrusions variously containing SRC-3 and chromatin. Aspects of SRC-3 overexpression and toxicity were recapitulated following treatment with clinically relevant agents that stabilize SRC-3 in breast cancer cells. We conclude that amplified SRC-3 levels have major impacts on nuclear protein quality control pathways and may mark cancer cells for sensitivity to protein stabilizing therapeutics. Full article
(This article belongs to the Section Cell Nuclei: Function, Transport and Receptors)
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<p>SRC-3 undergoes nuclear extrusion dependent on association with CBP. (<b>A</b>) MCF-7 cells cultured as described in Methods were subjected to IF for SRC-3. DNA was visualized with DAPI. Arrows indicate nuclear SRC-3 protrusions (63× magnification). (<b>B</b>) MCF-7 cells transfected with SRC-3 (tSRC-3) in the absence (endogenous only- eCBP)(panel i) or presence of cotransfected (tCBP) CBP (panel ii). In panel (i) Z-stack images show SRC-3 aggregates overlapping with diffuse CBP (red arrows). CBP not associated with SRC-3 is indicated by the green arrow. In panel (ii) some aggregates merge as CBP and SRC-3 foci (white arrows), while others near the nuclear periphery contain only SRC-3 (red arrows) (100× magnification).</p>
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<p>Establishment of SRC-3-overexpressing MCF-7 cells. (<b>A</b>) Immunoblot analysis showing SRC-3 protein expression in MCF-7 cells transfected with pCMX-RAC3 (SRC-3) or pcDNA3 and selected for puromycin resistance. SRC-3 stable cells were categorized according to the relative size of the average cell within a colony prior to expansion. Examples of clones that survived at least one passage are shown: control pcDNA3 cells (1,2,3), small-sized SRC-3 transfected clones (S1,2,5) and medium-sized SRC-3 clones (M1,2,4). Large cell clones did not survive passage. (<b>B</b>) Immunoblot of original clones showing SRC-3 expression relative to empty vector-transfected control. (<b>C</b>) Flow analysis of DNA content derived from the indicated clones. (<b>D</b>) DNA content graphs derived from the analysis of several clones. Bars are SD of means from: pcDNA control (<span class="html-italic">n</span> = 4), SRC-3 small (<span class="html-italic">n</span> = 15), SRC-3 medium (<span class="html-italic">n</span> = 4). (<b>E</b>) Phase-contrast images of control pcDNA3- and pCMX-RAC3- (SRC-3) transfected MCF-7 cells. Panels are (i) Control clones, (ii) small SRC-3-overexpressing clones, (iii and iv) medium SRC-3-overexpressing clones which were enlarged and flat with abundant cytoplasm. (<b>F</b>) Cell lysates harvested after infection at the indicated times after infection with Ad-LacZ or Ad-SRC-3 were probed with antibodies to SRC-3, P-Chk2, Chk2 (denoted by arrowhead), p21 and actin. (<b>G</b>) MCF-7 cells infected with the Ad-RFP and Ad-SRC-3 viruses were cultured for 72 h and assayed for senescence-associated (SA) β-galactosidase activity. (<b>H</b>) Immunoblot for SRC-3, cyclin E and PARP-1 in MCF-7 cell lysates 72 h post-transfection with empty vector (EV), wtSRC-3 or the stable mutant SRC-3(S102A). Note that although highly expressed relative to wtSRC-3 and to the gel loading control, S102A does not induce transcription of cyclin E. Actin was used as a protein loading control.</p>
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<p>Overexpressed SRC-3 rapidly forms nuclear aggregates. (<b>A</b>) GFP imaging of MCF-7 cells 72 h post-transfection with wtSRC-3, three different SRC-3-GFP phospho-mutants, and SRC-3 deleted for the polyQ region (residues 1230–1300). 63× magnification (<b>B</b>) Still images from video-microscopy of aggregation of YFP-SRC-3 in transfected cells. MCF-7 cells were transfected with YFP-SRC-3 and microscopy was performed 24 h later on an Axiovert 200M inverted fluorescent microscope (Carl Zeiss, Toronto, ON, Canada) for a total of 24 using Axiovision 4.8 acquisition software (Carl Zeiss). Images were acquired using a 10× objective (EC Plan-Neofluar) with a side-mounted AxiocamHRm camera (Carl Zeiss). YFP was excited using the Colibri LED illumination system (LEDmodule 505nm, Carl Zeiss) and detected using the 46HEYFP filter (Carl Zeiss). Exposure times were 1 ms (brightfield/phase contrast) and 100ms (YFP) at 10 min intervals for 24 h and compiled into video files using Axiovision 4.8 software (Carl Zeiss). 20 min intervals are shown. Cells circled in blue showed continuous accumulation of SRC-3 while cells circled in orange appeared to resolve aggregates.</p>
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<p>SRC-3 overexpression induces autophagy but does not affect the proteasome. (<b>A</b>) MCF-7 cells stably transfected with a nuclear-targeted GFP (NLS-GFPu) were mock-infected, or infected with Ad-SRC-3 or Ad-Lac-Z. Cells harvested 72 h after infection with or without 10 μM MG132 for the final 3 h of culture. Immunoblots were probed with anti-GFP and anti-SRC-3. Anti-actin reactivity was used as a control for protein loading on anti-GFP-probed blots. E-cadherin or vinculin were used as loading controls for blots probed with anti-SRC-3. (<b>B</b>) Cells infected as in <b>A</b> were seeded on coverslips and IF was performed after 72 h. GFP (green), anti-SRC-3/CY5 (red) and DAPI fluorescence are shown (63× magnification). (<b>C</b>) Graph depicting average of uGFP pixels/nuclear area within nuclei of MCF-7 cells described as above in <b>A</b>. Bars are S.E.M. (<b>D</b>) Immunoblots to detect the activation of the unfolded-protein response in LCC9 (L) (a tamoxifen-resistant MCF-7 derivative [<a href="#B30-cells-08-01278" class="html-bibr">30</a>]) and MCF-7 (M) cells uninfected or infected with adenoviral (Ad)-LacZ or Ad-SRC-3. Actin reactivity serves as a protein loading control. (<b>E</b>) MCF-7 cells stably expressing LC3-EGFP were infected with Ad-SRC-3 or Ad-RFP. Anti-SRC-3 and GFP-LC-3 were detected by epifluorescence microscopy (63× magnification). (<b>F</b>) MCF-7 cells were infected with Ad-Lac Z or Ad-SRC-3 and treated with a vehicle or 20 μM HCQ for 48 h. Lysates were immunoblotted for SRC-3, LC3 or actin, (LE denotes long exposure).</p>
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<p>SRC-3 aggregates are associated with microtubules, redistribute PML and SUMO and compromise nuclear membrane integrity. (<b>A</b>) 3D deconvoluted model constructed as described in Materials and Methods using Z-stacks acquired with confocal microscopy from SRC-3-transfected cells and immunostained for SRC-3 (red) and β-tubulin (green) and imaged. Blue is DAPI (100× magnification). (<b>B</b>) Immunofluorescence of β-tubulin (green) and SRC-3 (red) showing regions of increased perinuclear tubulin density in SRC-3 overexpressing cells. Nuclear protrusion of SRC-3 and DNA (blue) are indicated with arrows (63× magnification). (<b>C</b>) SRC-3 expression interferes with mitotic microtubule dynamics. MCF-7 cells were infected with Ad-LacZ or Ad-SRC-3 on coverslips and 48 h later were treated with taxol for 18hrs and IF performed to detect mitotic microtubules and SRC-3 (63× magnification). (<b>D</b>) Cells treated in <b>C</b> were enumerated for the presence of mitotic figures. Bars are S.D., ** <span class="html-italic">p</span> &lt; 0.01. (<b>E</b>) Z-stack images of cells transfected with SRC-3-YFP and immunostained for lamin B1 (red) and tubulin (green) immunofluorescence showing nuclear membrane distortion, and degradation associated with cytoplasmic SRC-3 aggregates (100× magnification). (<b>F</b>) IF of lamin B1 in SRC-3-GFP-transfected cells showing cells with discontinuous nuclear membranes, lamin B1 fragments, and distortions of nuclear shape.</p>
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<p>Effects of increased SRC-3 expression on PML: (<b>A</b>) IF of PML and SRC-3 in SRC-3 transfected cells shows ring-like aggregates of SRC-3 adjacent to PML bodies. (<b>B</b>) Dispersion of PML bodies (circled nuclei in panels i and ii’) in MCF-7 cells containing varying levels of homogenously distributed SRC-3. Nuclear membrane accumulation into caps of PML was observed in a subset of SRC-3 transfected cells (arrow in panels ii and ii’) (63× magnification). (<b>C</b>) Diffuse accumulations of PML form near the nuclear membrane. Cytoplasmic SRC-3(red open arrow) and PML (green open arrow). (<b>D</b>) Immunoblot of PML 96hrs following SRC-3 transfection. “V” denotes empty vector control. Vinculin was used as a protein loading control.</p>
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<p>Overexpressed SRC-3 is SUMOylated and disrupts the SUMO pathway. (<b>A</b>) Immunoprecipitation of protein from control (pcDNA3) or SRC-3 transfected MCF-7 cells using anti-SRC-3 or non-immune IgG was immunoblotted with anti-SUMO and anti-SRC-3. (<b>B</b>) SRC-3 immunoblot of input cell lysates in A as indicated. (<b>C</b>) MCF-7 cells were transfected with SRC-3-GFP then IF performed for UBC9. A representative cell expressing transfected SRC-3 (SRC-3-GFP<sup>+</sup>) is shown (63× magnification). (<b>D</b>) Graph depicting mean of UBC9 pixels/nuclear area within cells transfected with SRC-3-GFP (<span class="html-italic">n</span> = 12 GFP<sup>pos</sup> cells and <span class="html-italic">n</span> = 20 GFP<sup>neg</sup> cells as shown) or transfected with pcDNA3 (<span class="html-italic">n</span> = 25 cells) ± S.E. * <span class="html-italic">p</span> &lt; 0.05 (paired t-test). (<b>E</b>) Examples of SUMO IF in SRC-3 overexpressing MCF-7 cells. Panel (i): SUMO-1 puncta in the nucleus and associated with an SRC-3/chromatin nuclear protrusion. Panel (ii): Nuclear membrane-associated SUMO-1 with loss of nuclear puncta in an SRC-3 overexpressing cell. Panel (iii): MCF-7 cell with SUMO-1 aggregates and SUMO-1 distribution at the nuclear membrane. Note the absence of detectable nucleoli. Images on the right of each panel represent inverted and posturized (IP) DAPI channel images (Photoshop CS6) to visualize extranuclear DNA. (<b>F</b>) RanGAP1 IF (red) in MCF-7 cells transfected with SRC-3 (green) shows redistribution of ranGAP1 at the nuclear periphery. DNA is stained with DAPI (blue) (E and F, 63× magnification).</p>
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<p>Pharmacological protein stabilization results in strong increases in cytoplasmic SRC-3 and correlates with growth inhibition. (<b>A</b>) Immunoblot of SRC-3 after a 48hr treatment with vehicle, HCQ, B or HCQ+B. Vinculin immunoreactivity was used is a protein loading control. (<b>B</b>) MCF-7 cells were treated as indicated for 96 h and viability assessed by Alamar blue assay. Cells were assayed in quadruplicate. Bars are mean ± S.D. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.01 (One-way ANOVA). (<b>C</b>) IF of SRC-3 in MCF-7 cells treated with vehicle or B or HCQ+B for 48hrs. Panels (i, ii, iii) merged DAPI (blue)/anti-SRC-3 (red) pseudocolored IF, panels (i’,ii’,iii’) anti-SRC-3 epifluorescence only (identical exposure images inverted in Photoshop CS6). Panel iii’’ represents DAPI only (grayscale) enlargement of the boxed area in (iii). Arrows point to extranuclear chromatin. All images 63× magnification. (<b>D</b>) Immunoblot for SRC-3 in MCF-7 lysates from cells treated for the indicated times in 5 μM tamoxifen. Vinculin was used as a protein loading control. (<b>E</b>), IF for SRC-3 in cells treated with vehicle or 5 μM Tam for 3 h. Cells with SRC-3 nuclear protrusions are boxed. Cells with reduced nucleoli are indicated with closed arrows. (<b>F</b>), Nucleolar regions were enumerated from DAPI-stained images in cultures treated as in (<b>E</b>). Bars are S.E.M. ** <span class="html-italic">p</span> &lt; 0.01. (<b>G</b>), IF to detect PML protein in MCF-7 cells treated as in (<b>E</b>). (<b>H</b>) Enumeration of discrete PML bodies in cells treated as in (<b>E</b>). Bars are S.E.M. *** <span class="html-italic">p</span> &lt; 0.001(paired t-test).</p>
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14 pages, 1738 KiB  
Article
Increased Expression of RUNX1 in Liver Correlates with NASH Activity Score in Patients with Non-Alcoholic Steatohepatitis (NASH)
by Savneet Kaur, Preety Rawal, Hamda Siddiqui, Sumati Rohilla, Shvetank Sharma, Dinesh M Tripathi, Sukriti Baweja, Mohsin Hassan, Sebastian Vlaic, Reinhard Guthke, Maria Thomas, Rania Dayoub, Chaggan Bihari, Shiv K. Sarin and Thomas S. Weiss
Cells 2019, 8(10), 1277; https://doi.org/10.3390/cells8101277 - 18 Oct 2019
Cited by 28 | Viewed by 5864
Abstract
Given the important role of angiogenesis in liver pathology, the current study investigated the role of Runt-related transcription factor 1 (RUNX1), a regulator of developmental angiogenesis, in the pathogenesis of non-alcoholic steatohepatitis (NASH). Quantitative RT-PCRs and a transcription factor analysis of angiogenesis-associated differentially [...] Read more.
Given the important role of angiogenesis in liver pathology, the current study investigated the role of Runt-related transcription factor 1 (RUNX1), a regulator of developmental angiogenesis, in the pathogenesis of non-alcoholic steatohepatitis (NASH). Quantitative RT-PCRs and a transcription factor analysis of angiogenesis-associated differentially expressed genes in liver tissues of healthy controls, patients with steatosis and NASH, indicated a potential role of RUNX1 in NASH. The gene expression of RUNX1 was correlated with histopathological attributes of patients. The protein expression of RUNX1 in liver was studied by immunohistochemistry. To explore the underlying mechanisms, in vitro studies using RUNX1 siRNA and overexpression plasmids were performed in endothelial cells (ECs). RUNX1 expression was significantly correlated with inflammation, fibrosis and NASH activity score in NASH patients. Its expression was conspicuous in liver non-parenchymal cells. In vitro, factors from steatotic hepatocytes and/or VEGF or TGF-β significantly induced the expression of RUNX1 in ECs. RUNX1 regulated the expression of angiogenic and adhesion molecules in ECs, including CCL2, PECAM1 and VCAM1, which was shown by silencing or over-expression of RUNX1. Furthermore, RUNX1 increased the angiogenic activity of ECs. This study reports that steatosis-induced RUNX1 augmented the expression of adhesion and angiogenic molecules and properties in ECs and may be involved in enhancing inflammation and disease severity in NASH. Full article
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<p>Correlation between <span class="html-italic">RUNX1</span> mRNA expression and histopathological parameters. Expression of <span class="html-italic">RUNX1</span> mRNA was analyzed by qRT-PCR in liver tissue samples from patients with NASH (<span class="html-italic">n</span> = 43), hepatic steatosis (<span class="html-italic">n</span> = 46) and normal liver tissue (<span class="html-italic">n</span> = 33) and correlated to histopathologic proven (<b>A</b>) NASH activity score (<b>B</b>) steatosis grade (<b>C</b>) inflammation grade and (<b>D</b>) fibrosis grade. <span class="html-italic">HPRT</span> mRNA expression was determined for normalization, statistical differences between several grades were analyzed by Kruskal-Wallis Test (<span class="html-italic">p</span> &lt; 0.05 was considered significant) and ‘r’ denotes the Pearson’s correlation coefficient.</p>
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<p>Immunohistochemical (IHC) analysis of RUNX1 expression in NASH patients. (<b>A</b>) RUNX1 immunostained images (20× objective) with an increasing number of brown nuclear immuno-positive cells (score 1–4). RUNX1 positivity was mostly observed in the non-parenchymal cells. Hematoxylin stained nuclei were distinguishable from RUNX1-positive brown nuclei. (<b>B</b>) Correlation between RUNX1 IHC and NASH activity score (<span class="html-italic">n</span> = 16), (<b>C</b>) RUNX1 IHC score and fibrosis grade (<span class="html-italic">n</span> = 16), and (<b>D</b>) RUNX1 IHC score and inflammatory grade (<span class="html-italic">n</span> = 16) in NASH patients. (<b>E</b>) Correlation between <span class="html-italic">RUNX1</span> mRNA and its IHC score in liver tissues of patients (n = 16). The Pearson correlation (r) and statistical significance (<span class="html-italic">p</span>) were calculated.</p>
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<p><span class="html-italic">RUNX1</span> and angiogenic gene expression in endothelial cells maintained in conditioned medium (CM) from palmitic acid (PA) treated hepatoma (Huh7) cells. (<b>A</b>) Huh7 cells treated with 0.2 mM PA for 48 h were analyzed for mRNA expression of <span class="html-italic">RUNX1</span> and genes identified as angiogenesis associated DEGs in human NASH samples. The dotted line represents the control showing gene expression in Huh7 cells treated with BSA (<span class="html-italic">n</span> = 4). (<b>B</b>) HUVECs incubated with CM from PA-Huh7 cells were analyzed for mRNA expression of <span class="html-italic">RUNX1</span>, its target and angiogenic genes. The dotted line represents control, showing gene expression in HUVECs treated with CM from BSA-Huh7 cells (<span class="html-italic">n</span> = 4). 18S RNA expression was used for normalization. (<b>C</b>) Huh7 cells were treated with BSA or PA or CM alone and analyzed for the release of VEGF, PDGF-BB and TGF-β (pg/mL) (<span class="html-italic">n</span> = 3). (<b>D</b>) Relative <span class="html-italic">RUNX1</span> mRNA expression in HUVECs treated with VEGF and TGF-β (10 ng/mL each) for 24 h. Un-induced cells without any manipulation were used as respective controls (Dotted line) (<span class="html-italic">n</span> = 3). 18S RNA expression was used for normalization. Data represent mean ± SD. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>RUNX1 alters expression of angiogenic and adhesion molecules in endothelial cells (<b>A</b>) HUVECs, treated with <span class="html-italic">RUNX1</span> siRNA or NC siRNA and incubated with CM from PA-Huh7 cells, were analyzed for mRNA expression (fold change) of angiogenic, adhesion molecule and RUNX1 target genes (<span class="html-italic">n</span> = 3). (<b>B</b>) HUVECs transfected with RUNX1 expression plasmid (pRUNX1), control plasmid (pControl, i.e., empty vector) and/or incubated with VEGF (10 ng/mL) were analyzed for mRNA expression of adhesion molecule and chemotactic genes. HUVECs without any treatment were used as respective controls (Dotted line) (<span class="html-italic">n</span> = 3). 18S RNA expression was used for normalization. (<b>C</b>) Quantitative analysis of flow cytometry from (<b>C</b>) is shown (<span class="html-italic">n</span> = 3). (<b>D</b>) CCL2 levels (pg/mL) in culture media of HUVECs transfected with RUNX1 expression plasmid (pRUNX1), control plasmid (pControl, empty vector) and/or incubated with VEGF (10 ng/mL) (<span class="html-italic">n</span> = 4). Data represent mean ± SD. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>RUNX1 enhances the angiogenic activitiy of endothelial cells. (<b>A</b>) Representative tube formation images of HUVECs on matrigel (4× objective) transfected with RUNX1 expression plasmid (pRUNX1), control plasmid (pControl, empty vector) and/or incubated with VEGF (10 ng/mL). (<b>B</b>) Average number of branch points per field and (<b>C</b>) tube length per field formed by HUVECs on matrigel under conditions described in (<b>A</b>) (<span class="html-italic">n</span> = 3). Data represent mean ± SD. * <span class="html-italic">p</span> &lt; 0.05.</p>
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20 pages, 3118 KiB  
Article
Inhibition of JAK-STAT Signaling with Baricitinib Reduces Inflammation and Improves Cellular Homeostasis in Progeria Cells
by Chang Liu, Rouven Arnold, Gonçalo Henriques and Karima Djabali
Cells 2019, 8(10), 1276; https://doi.org/10.3390/cells8101276 - 18 Oct 2019
Cited by 55 | Viewed by 6013
Abstract
Hutchinson-Gilford progeria syndrome (HGPS), a rare premature aging disorder that leads to death at an average age of 14.7 years due to myocardial infarction or stroke, is caused by mutations in the LMNA gene. Nearly 90% of HGPS cases carry the G608G mutation [...] Read more.
Hutchinson-Gilford progeria syndrome (HGPS), a rare premature aging disorder that leads to death at an average age of 14.7 years due to myocardial infarction or stroke, is caused by mutations in the LMNA gene. Nearly 90% of HGPS cases carry the G608G mutation within exon 11 that generates a truncated prelamin A protein “progerin”. Progerin accumulates in HGPS cells and induces premature senescence at the cellular and organismal levels. Children suffering from HGPS develop numerous clinical features that overlap with normal aging, including atherosclerosis, arthritis, hair loss and lipodystrophy. To determine whether an aberrant signaling pathway might underlie the development of these four diseases (atherosclerosis, arthritis, hair loss and lipodystrophy), we performed a text mining analysis of scientific literature and databases. We found a total of 17 genes associated with all four pathologies, 14 of which were linked to the JAK1/2-STAT1/3 signaling pathway. We report that the inhibition of the JAK-STAT pathway with baricitinib, a Food and Drug Administration-approved JAK1/2 inhibitor, restored cellular homeostasis, delayed senescence and decreased proinflammatory markers in HGPS cells. Our ex vivo data using human cell models indicate that the overactivation of JAK-STAT signaling mediates premature senescence and that the inhibition of this pathway could show promise for the treatment of HGPS and age-related pathologies. Full article
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<p>Text mining analysis to identify genes associated with vascular disease, arthritis, alopecia and lipodystrophy, and characterization of the cell-based aging model. (<b>a</b>) Venn diagram of the 2778 genes linked to the four diseases as determined by text mining. (<b>b</b>) Interaction network of the 17 gene products visualized by STRING. Nodes are proteins, and lines represent functional associations between proteins. A green line indicates neighborhood evidence; a blue line indicates cooccurrence evidence; a purple line indicates experimental evidence; a light blue line indicates database evidence; a black line indicates coexpression evidence. (<b>c</b>) Venn diagram of the signal transducer and activator of transcription (STAT) gene family showing the number of genes that are regulated by different STATs as indicated by the corresponding circles. Each gene was searched in the TRRUST version 2 (<a href="https://www.grnpedia.org/trrust/" target="_blank">https://www.grnpedia.org/trrust/</a>), TfactS (<a href="http://www.tfacts.org/" target="_blank">http://www.tfacts.org/</a>) and Regulatory Circuits databases (<a href="http://regulatorycircuits.org/" target="_blank">http://regulatorycircuits.org/</a>). Altogether, a total of 269 genes were found and curated to prevent repetitions due to aliases. (<b>d</b>) Growth curves of four independent control cell strains (purple, blue, orange, gray) and three Hutchinson-Gilford progeria syndrome (HGPS) cell strains (light blue, red, and turquoise). All cultures started at passage 13, and at this passage, the percentage of SA-ß-gal-positive cells was less than 5% in all cell strains. Proliferation rates were determined over 26 passages over 104 days. (<b>e</b>) The percentage of SA-ß-gal-positive cells was scored every other passage in cultures from panel d. (<b>f</b>) Representative images of SA-ß-gal-positive cells in cultures exhibiting &lt;5% SNS, 15% SNS and 30% SNS. GMO1651c corresponds to normal fibroblasts and P003 corresponds to HGADFN003, an HGPS cell strain. (<b>g</b>) Relative percentage of cells in the G<sub>0</sub>/G<sub>1</sub>, S and G<sub>2</sub>/M phases of the cell cycle are shown for normal (1651c) and HGPS (P003) cultures with a senescence index of &lt;5% and 30%. PI was used for DNA staining. (<b>h</b>) Representative western blot of control (1651c, 1652c) and HGPS (P003, P127) fibroblasts from cultures at the indicated percentages of senescence. Antibodies directed against the indicated proteins were used. All experiments were performed at least three times (<span class="html-italic">n</span> &gt; 3).</p>
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<p>Quantitative real-time PCR analysis of the 17 genes identified by text mining in normal and HGPS cells during replicative senescence. (<b>a</b>) Table showing the cell strains and the passages corresponding percentage of senescence (SNS). (<b>b</b>–<b>r</b>) mRNA levels of the indicated genes were determined in controls (GMO1651c, and GMO1652c) and HGPS (HGADFN003 and HGADFN127) cell strains at the indicated percentage of senescence (SNS). Relative expression was normalized to the expression of GAPDH. Graphs show the mean ± SD (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, <span class="html-italic">n</span> &gt; 3). The mean fold changes between 5% and 30% SNS for control and HGPS are indicated.</p>
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<p>Status of the JAK-STAT signaling pathway in control and HGPS cells during replicative senescence. (<b>a</b>) Table showing the cell strains and the passages corresponding percentages of senescence (SNS). (<b>b</b>,<b>e</b>,<b>h</b>) Representative western blot images for JAK1/2, STAT1/3, p-STAT1 (tyr701), p-STAT3 (tyr705) and β-actin in the control (GMO1651c, and GMO1652c) and HGPS (HGADFN003, and HGADFN127) cell strains at the indicated percentages of senescence. (<b>c</b>) Quantification of JAK1, (<b>d</b>) JAK2, (<b>f</b>) STAT1, (<b>g</b>) p-STAT1, (<b>i</b>) STAT3, and (<b>j</b>) p-STAT3. Graphs show the mean ± SD. (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, <span class="html-italic">n</span> &gt; 3). Fold changes between the samples with 5% and 30% senescence are indicated.</p>
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<p>Status of the JAK-STAT signaling pathway in normal and HGPS cells treated with 1 μM Bar. (<b>a</b>,<b>b</b>) Representative images of western blots for JAK1/2, STAT1/3, P-STAT1/3 and β-actin in normal (GMO1651c, and GMO1652c) and HGPS (HGADFN003, and HGADFN127) cells treated as indicated. Cultures exhibiting &lt;5% senescence were treated with Bar or DMSO for a period of one month. (<b>c</b>) Quantification of JAK1, (<b>d</b>) JAK2, (<b>e</b>) P-STAT3, (<b>f</b>) STAT3, (<b>g</b>) P-STAT1, and (<b>h</b>) STAT1. Graphs show the mean ± SD. Protein levels were compared by two-tailed t test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, <span class="html-italic">n</span> &gt; 3).</p>
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<p>Bar treatment ameliorates normal and HGPS cellular functions during long-term treatment. (<b>a</b>) Graph shows the population doublings of control (GMO1651c, and GMO1652c) and HGPS (HGADFN003, and HGADFN127) cells. Bar (1 μM) or DMSO treatment was administrated for one week or one month as indicated. The percentage of senescence (SNS) in cultures prior to treatment is indicated. (<b>b</b>) Graph shows the percentage of SA-ß-gal-positive cells measured after treatment. (<b>c</b>) Autophagy activity was determined by measuring MDC levels using fluorescence photometry of the same cultures as in (<b>a</b>). (<b>d</b>) Proteasome activity was determined by measuring chymotrypsin-like proteasome activity using Suc-LLVY-AMC as a substrate. (<b>e</b>) Intracellular ROS levels were determined by measuring oxidized dichlorofluorescein (DCF) levels using a DCFDA cellular ROS detection assay. (<b>f</b>) Cellular ATP levels were measured using a CellTiter-Glo luminescence ATP assay. (<b>c</b>–<b>f</b>) The percent change in Bar-treated cells relative to mock-treated counterparts is indicated. (<b>g</b>) Representative images of a western blot for progerin in HGPS (HGADFN127) cells from cultures at 5% and 15% senescence that were administrated the mock or Bar treatment for one week or one month as indicated. (<b>h</b>) Quantification of the progerin signal. The percent change between Bar-treated cells and mock-treated counterparts are indicated. Graphs show the mean ± SD. Comparisons were performed by two-tailed t 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; 0.01, (<span class="html-italic">n</span> &gt; 3)).</p>
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<p>Etoposide treatment activates the JAK-STAT signaling pathway in HGPS and normal cells. (<b>a</b>) Schematic representation of the etoposide treatment protocol. All treatments started with cultures exhibiting &lt;5% senescence (SNS). Cells were either pretreated with or without 1 µM Bar for two days and then expose to medium with or without etoposide in the presence or absence of Bar for a period of six days. Next, cells were grown for four days with or without Bar as indicated. (<b>b</b>) Representative images of SA-ß-gal-positive cells in mock-, etoposide- and etoposide + Bar-treated cultures (GMO1651c and HGADFN003) are shown. The percentages of senescence (SNS) after treatment are indicated. (<b>c</b>) Representative images of western blots for progerin, p21 and ß-actin in normal (GMO1651c, and GMO1652c) and HGPS (HGADFN003, and HGADFN127) cells treated as indicated. (<b>d</b>) and (<b>g</b>) Representative images of western blots for JAK1/2, STAT1/3, P-STAT1/3 and ß-actin in normal (GMO1651c, and GMO1652c) and HGPS (HGADFN003, and HGADFN127) cells treated as indicated. (<b>e</b>) Quantification of STAT1, (<b>f</b>) p-STAT1, (<b>h</b>) STAT3, and (<b>i</b>) p-STAT3. The percent change between etoposide- and etoposide+Bar-treated cells is indicated. (<b>j</b>–<b>n</b>) Quantitative real-time PCR analysis of CCL2, CXCL8, IFNG, IL6, and TNFα in cells treated as indicated. Relative expression was normalized to the expression of GAPDH. Graphs show the mean ± SD. Comparisons were done by two-tailed t 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). All experiments were repeated at least three times (<span class="html-italic">n</span> &gt; 3).</p>
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12 pages, 2351 KiB  
Article
Capsaicin Targets tNOX (ENOX2) to Inhibit G1 Cyclin/CDK Complex, as Assessed by the Cellular Thermal Shift Assay (CETSA)
by Atikul Islam, Ally J. Su, Zih-Ming Zeng, Pin Ju Chueh and Ming-Hung Lin
Cells 2019, 8(10), 1275; https://doi.org/10.3390/cells8101275 - 18 Oct 2019
Cited by 26 | Viewed by 6785
Abstract
Capsaicin (8-methyl-N-vanillyl-6-noneamide), which is an active component in red chili peppers, is used as a chemopreventive agent that shows favorable cytotoxicity against cancer cells. Accumulating evidence indicates that capsaicin preferentially inhibits a tumor-associated NADH oxidase (tNOX, ENOX2) that is ubiquitously expressed [...] Read more.
Capsaicin (8-methyl-N-vanillyl-6-noneamide), which is an active component in red chili peppers, is used as a chemopreventive agent that shows favorable cytotoxicity against cancer cells. Accumulating evidence indicates that capsaicin preferentially inhibits a tumor-associated NADH oxidase (tNOX, ENOX2) that is ubiquitously expressed in cancer but not in non-transformed cells. This attenuates cancer cell growth by inducing apoptosis. The capsaicin-mediated inhibition of tNOX was recently shown to prolong the cell cycle. However, the molecular events underlying this regulation have not yet been investigated. In the present study, we used a cellular thermal shift assay (CETSA) to detect “target engagement” of capsaicin and its consequent impact on cell cycle progression. Our results indicated that capsaicin engaged with tNOX and triggered the proteasomal degradation of tNOX, which leads to the inhibition of NAD+-dependent SIRT1 deacetylase. Ultimately, the acetylation levels of c-Myc and p53 were enhanced, which suppressed the activation of G1 cyclin/Cyclin-dependent kinase complexes and triggered cell cycle arrest in cancer cells. The results obtained when tNOX was overexpressed in non-cancer cells validated its importance in cell cycle progression. These findings provide the first molecular insights into the regulatory role of tNOX and the anti-proliferative property of capsaicin in regulating the cell cycle of bladder cancer cells. Full article
(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Stress Responses)
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Figure 1

Figure 1
<p>CETSA-based determination of binding between capsaicin and tNOX. (<b>A</b>) CETSA was performed as described in the Materials and Methods section. Cell lysates were separated by SDS-PAGE and analyzed by Western blotting. β-Actin was detected as an internal control. Representative images are shown. (<b>B</b>) CETSA curves of tNOX in T24 cells were determined in the absence and presence of capsaicin. Each band intensity of tNOX was normalized with respect to that obtained at 43 °C. The graphs are an average of three independent experiments. (<b>C</b>) The quantification of relative intensity of tNOX protein versus increased temperature from three independent experiments (* <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>Capsaicin suppresses tNOX expression through proteasome-mediated degradation. Aliquots of cell lysates were separated by SDS-PAGE and analyzed by Western blotting. β-Actin was detected as an internal control. Representative images are shown. Values (mean ± S. E.) are from at least three independent experiments (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001 for capsaicin-treated cells vs. controls). (<b>A</b>) tNOX expression was significantly decreased by capsaicin at 100 and 200 μM. (<b>B</b>) Capsaicin (200 μM) clearly reduces tNOX stability as assessed with a cycloheximide-chase assay. (<b>C</b>) The proteasome inhibitor, MG132, reverses the capsaicin-induced suppression of tNOX expression.</p>
Full article ">Figure 3
<p>Capsaicin induces cell cycle arrest at the G0/G1 phases. T24 cells were treated with capsaicin or ethanol for 24 h. Aliquots of cell lysates were separated by SDS-PAGE and analyzed by Western blotting. β-Actin was detected as an internal control. Representative images are shown.</p>
Full article ">Figure 4
<p>Effect of capsaicin on the proliferation and cell cycle of T24 cells. (<b>A</b>) Dynamic monitoring of cell proliferation was performed using impedance technology, as described in the Materials and Methods section. Normalized cell index values measured over 96 h are shown. (<b>B</b>) Cells were exposed to different concentrations of capsaicin for 24 or 48 h and cell viability was measured using MTT assays. Values (means ± SDs) are from three independent experiments. There was a significant decrease in cell viability in cells treated with capsaicin when compared with controls (** <span class="html-italic">p</span> &lt;0.01, *** <span class="html-italic">p</span> &lt;0.001). (<b>C</b>,<b>D</b>) T24 cells were exposed to different concentrations of capsaicin for 24 h and flow cytometry was used to assess their cell-cycle phase. The graphs are representative of three independent experiments.</p>
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<p>tNOX overexpression in NIH3T3 cells enhances cell growth. NIH3T3 cells were transfected with GST, GST–tNOX wild-type, GST–tNOX<sup>S504D</sup>, or GST–tNOX<sup>S504A</sup>. (<b>A</b>,<b>B</b>) Overexpression of GST–tNOX wild-type, GST–tNOX<sup>S504D</sup>, or GST–tNOX S504A fusion proteins was analyzed using anti-GST, anti-tNOX, anti-phospho-ERK, and anti-ERK antibodies. β-Actin was detected as a loading control. Representative images are shown. (<b>C</b>) The cell-doubling time was determined by CMFDA staining of NIH3T3 cells. The presented values (mean ± S.E.) represent at least three independent experiments (** <span class="html-italic">p</span> &lt; 0.001). (<b>C</b>) Dynamic monitoring of cell proliferation was performed using impedance technology, as described in the Materials and Methods section. Normalized cell index values measured over 138 h are shown.</p>
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18 pages, 2070 KiB  
Article
The Oncogenic Signaling Pathways in BRAF-Mutant Melanoma Cells Are Modulated by Naphthalene Diimide-Like G-Quadruplex Ligands
by Marta Recagni, Martina Tassinari, Filippo Doria, Graziella Cimino-Reale, Nadia Zaffaroni, Mauro Freccero, Marco Folini and Sara N. Richter
Cells 2019, 8(10), 1274; https://doi.org/10.3390/cells8101274 - 18 Oct 2019
Cited by 12 | Viewed by 3642
Abstract
Melanoma is the most aggressive and deadly type of skin cancer. Despite the advent of targeted therapies directed against specific oncogene mutations, melanoma remains a tumor that is very difficult to treat, and ultimately remains incurable. In the past two decades, stabilization of [...] Read more.
Melanoma is the most aggressive and deadly type of skin cancer. Despite the advent of targeted therapies directed against specific oncogene mutations, melanoma remains a tumor that is very difficult to treat, and ultimately remains incurable. In the past two decades, stabilization of the non-canonical nucleic acid G-quadruplex structures within oncogene promoters has stood out as a promising approach to interfere with oncogenic signaling pathways in cancer cells, paving the way toward the development of G-quadruplex ligands as antitumor drugs. Here, we present the synthesis and screening of a library of differently functionalized core-extended naphthalene diimides for their activity against the BRAFV600E-mutant melanoma cell line. The most promising compound was able to stabilize G-quadruplexes that formed in the promoter regions of two target genes relevant to melanoma, KIT and BCL-2. This activity led to the suppression of protein expression and thus to interference with oncogenic signaling pathways involved in BRAF-mutant melanoma cell survival, apoptosis, and resistance to drugs. This G-quadruplex ligand thus represents a suitable candidate for the development of melanoma treatment options based on a new mechanism of action and could reveal particular significance in the context of resistance to targeted therapies of BRAF-mutant melanoma cells. Full article
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Graphical abstract

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<p>(<b>A</b>) Time-dependent assessment of cell growth in untreated A375 and SKMEL-2 cells. Data are reported as the recorded absorbance (Abs) as a function of time and represent mean values ± s.d. from at least three independent experiments. The curves represent the exponential growth equation obtained by nonlinear fit of data points using GraphPad Prism 5.01 (GraphPad Software Inc., San Diego, California, United States). (<b>B</b>) Dose-response curves of melanoma cells exposed to increasing concentrations (0.1–10,000 nM) of <b>1</b>. Data are reported as the percentage of viable cells with respect to untreated cells as a function of the Log<sub>10</sub> of compound concentrations (for details see <a href="#app1-cells-08-01274" class="html-app">Supporting Information Table S2</a>) and represent mean values ± s.d. from at least three independent experiments. (<b>C</b>) Representative photomicrographs showing the uptake of the G4 ligand (red) and the occurrence of G4 structures (green) in A375 and SKMEL-2 cells exposed to c-exNDI 1 (IC<sub>50</sub>) for 48 h and analyzed by fluorescence microscopy. The panels on the bottom show untreated cells. Nuclei were counterstained with DAPI. Magnification: ×100; bars: 10 μm. (<b>D</b>) Analysis of gene expression levels in A375 cells upon 48 h of exposure to <b>1</b> (IC<sub>50</sub>). Data are reported as Relative Quantity (mean RQ values ± s.d.) in treated vs. untreated cells, according to the 2<sup>−ΔΔCt</sup> method. Dotted line: calibrator sample. * <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 (Student’s <span class="html-italic">t</span>-test).</p>
Full article ">Figure 2
<p>Representative circular dichroism (CD) spectra of G4s formed by c-myc, bcl-2, c-kit1, c-kit2, and b-raf oligonucleotides (4 μM) recorded in the absence (<b>A</b>) or presence (<b>B</b>) of a 4-fold excess of <b>1</b> (16 μM). (<b>C</b>) Image of a typical Taq polymerase stop assay. The b-raf, bcl-2, c-myc, and c-kit1+2 templates were amplified by Taq polymerase in the absence (lanes 1) and presence of 10 mM K<sup>+</sup>, alone (lanes 2) or combined, with increasing amounts (37.5, 75.0, and 150.0 nM) of <b>1</b> (lanes 3–5). A template (non-G4 cnt) made of a scramble sequence unable to fold into G4 was also used as an internal control. Lane M: Ladder of markers obtained by the Maxam and Gilbert sequencing carried out on the amplified strand complementary to the template strand. Lane P: Unreacted labelled primer. Vertical bars indicate G4-specific Taq polymerase stop sites. (<b>D</b>) Quantification of the intensity of G4 stop bands obtained in the Taq polymerase stop assay. G4 stop band intensities are expressed as percentages with respect to the total elongated products.</p>
Full article ">Figure 3
<p>(<b>A</b>) Analysis of <span class="html-italic">KIT</span> and <span class="html-italic">MYC</span> mRNA expression levels in A375 and SKMEL-2 cells upon 48 h of exposure to <b>1</b> (IC<sub>50</sub>). Data are reported as Relative Quantity (mean RQ values ± s.d.) in treated vs. untreated cells, according to the 2<sup>−ΔΔCt</sup> method. Dotted line: calibrator sample. (<b>B</b>) Representative Western immunoblotting showing the effects of 48 and 72 h of exposure of A375 cells to <b>1</b> (IC<sub>50</sub>) on the amounts of the indicated proteins. Cropped images of selected proteins are shown. Beta-actin (ACTB) was used to ensure equal protein loading. The graph on the right shows the extent of KIT (black bars) and BCL2 (white bars) protein inhibition in A375 cells exposed to <b>1</b> (IC<sub>50</sub>) for 48 and 72 h. Data are reported as the inhibition of protein expression in treated vs. untreated cells, and represent the mean values ± s.d. from at least three independent experiments. (<b>C</b>) Representative Western immunoblotting showing the amounts of the indicated proteins in untreated (−) A375 cells and upon 72 h of exposure (+) to <b>1</b> (IC<sub>50</sub>). Vinculin (VCL) was used to ensure equal protein loading. Cropped images of selected proteins are shown. The graph on the bottom reports the quantification of protein levels in untreated (white bars) and <b>1</b>-treated (black bars) A375 cells. Data are reported as relative protein amounts following the normalization of densitometric signals toward Vinculin, and represent the mean values ± s.d. (<b>D</b>) Time-dependent assessment of the cell cycle in untreated and <b>1</b>-treated A375 cells. Data are reported as the percentages of cells in G0/G1 (red), S (green), and G2/M (black) phases of the cell cycle, and represent the mean values ± s.d. from at least three independent experiments. (<b>E</b>) Representative Western immunoblotting showing the amounts of full length and cleaved PARP1 in untreated (−) A375 cells and upon 48 and 72 h of exposure (+) to <b>1</b> (IC<sub>50</sub>). Beta-actin (ACTB) was used to ensure equal protein loading. Cropped images of selected proteins are shown. The graph on the right reports the amounts of cleaved PARP1 in untreated (white bars) and <b>1</b>-treated (black bars) cells. Data are reported as relative protein amounts vs. full length PARP1, and represent the mean values ± s.d. * <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 (Student’s <span class="html-italic">t</span>-test).</p>
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21 pages, 5570 KiB  
Article
Is NO the Answer? The Nitric Oxide Pathway Can Support Bone Morphogenetic Protein 2 Mediated Signaling
by Christopher Differ, Franka Klatte-Schulz, Nicole Bormann, Susann Minkwitz, Petra Knaus and Britt Wildemann
Cells 2019, 8(10), 1273; https://doi.org/10.3390/cells8101273 - 18 Oct 2019
Cited by 8 | Viewed by 5396
Abstract
The growth factor bone morphogenetic protein 2 (BMP2) plays an important role in bone development and repair. Despite the positive effects of BMP2 in fracture healing, its use is associated with negative side effects and poor cost effectiveness, partly due to the large [...] Read more.
The growth factor bone morphogenetic protein 2 (BMP2) plays an important role in bone development and repair. Despite the positive effects of BMP2 in fracture healing, its use is associated with negative side effects and poor cost effectiveness, partly due to the large amounts of BMP2 applied. Therefore, reduction of BMP2 amounts while maintaining efficacy is of clinical importance. As nitric oxide (NO) signaling plays a role in bone fracture healing and an association with the BMP2 pathway has been indicated, this study aimed to investigate the relationship of BMP2 and NO pathways and whether NO can enhance BMP2-induced signaling and osteogenic abilities in vitro. To achieve this, the stable BMP reporter cell line C2C12BRELuc was used to quantify BMP signaling, and alkaline phosphatase (ALP) activity and gene expression were used to quantify osteogenic potency. C2C12BRELuc cells were treated with recombinant BMP2 in combination with NO donors and substrate (Deta NONOate, SNAP & L-Arginine), NOS inhibitor (LNAME), soluble guanylyl cyclase (sGC) inhibitor (LY83583) and activator (YC-1), BMP type-I receptor inhibitor (LDN-193189), or protein kinase A (PKA) inhibitor (H89). It was found that the NOS enzyme, direct NO application, and sGC enhanced BMP2 signaling and improved BMP2 induced osteogenic activity. The application of a PKA inhibitor demonstrated that BMP2 signaling is enhanced by the NO pathway via PKA, underlining the capability of BMP2 in activating the NO pathway. Collectively, this study proves the ability of the NO pathway to enhance BMP2 signaling. Full article
(This article belongs to the Special Issue TGF-beta/BMP Signaling Pathway)
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<p>Bone morphogenetic protein (BMP) reporter activity and BMP target gene expression after stimulation with the nitric oxide synthase (NOS) substrate Arginine. C2C12BRELuc cells stimulated for 24 h in Arginine-free Dulbecco's Modified Eagle Medium (DMEM) with (<b>A</b>) 0.1 to 7.5 mM Arginine alone or in combination with (<b>B</b>) 1 nM BMP2 or (<b>C</b>) 5 nM BMP2. (<b>D</b>) C2C12BRELuc cells were stimulated for six hours in Arginine-free DMEM with 1 nM BMP2, with or without 1 mM Arginine. The gene expression of <span class="html-italic">Id1</span>, <span class="html-italic">Id2</span>, and <span class="html-italic">Id3</span> was investigated. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Stars and circles are outlying values. Number of replications: (<b>A</b>) n = 12; (<b>B</b>) n = 6; (<b>C</b>) n = 9; (<b>D</b>) n = 3.</p>
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<p>BMP reporter and alkaline phosphatase activity (ALP) activity following the inhibition of NOS enzyme by NOS inhibitor (LNAME): C2C12BRELuc cells were stimulated for 24 h with (<b>A</b>) 250-10,000 µM LNAME or (<b>B</b>) 5 nM BMP2 and 1 mM Arginine in combination with 250-10,000 µM LNAME. ALP activity was normalized to cell number of cells stimulated for 72 h with 10 nM BMP2 with (<b>C</b>) NOS inhibitor LNAME (0.01 to 100 µM) and (<b>D</b>) following recovery of 10 µM or 100 µM LNAME inhibition with the direct NO donor. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**) or <span class="html-italic">p</span> &lt; 0.001 (***). Stars and circles are outlying values. Abbreviation: Deta: Deta NONOate. Number of replications: (<b>A</b>–<b>D</b>) n = 6.</p>
Full article ">Figure 3
<p>BMP reporter activity after stimulation with the NO donors Deta NONOate and SNAP for six hours: C2C12BRELuc cell were stimulated in Arginine-free DMEM with (<b>A</b>) 10–1000 µM Deta NONOate or (<b>B</b>) in combination with 1 nM BMP2, with (<b>C</b>) 1-100 µM SNAP or (<b>D</b>) SNAP in combination with 1 nM BMP2. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Abbreviations: Deta = Deta NONOate. Stars and circles are outlying values. Number of replications (<b>A</b>,<b>B</b>) n = 6; (<b>C</b>) n = 18; (<b>D</b>) n = 9.</p>
Full article ">Figure 4
<p>BMP reporter activity after stimulation with the NO donors Deta NONOate and SNAP for 24-h: C2C12BRELuc cells stimulated in Arginine-free DMEM with (<b>A</b>) 1–100 µM Deta NONOate, (<b>B</b>) and in combination 1 nM BMP2. (<b>C</b>) Cells stimulated in normal DMEM containing Arginine with 1 to 100 µM Deta NONOate and 1 nM BMP2. (<b>D</b>) Stimulation in Arginine-free DMEM with 5–50 µM SNAP in combination with 5 nM BMP2. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Abbreviation: Deta = Deta NONOate. Circles are outlying values. Replication (<b>A</b>–<b>D</b>) n = 6.</p>
Full article ">Figure 5
<p>ALP activity after NO supplemented BMP2 stimulation: ALP activity normalized to cell number of C2C12BRELuc cells stimulated with direct NO donor Deta NONOate (10–100 µM) (<b>A</b>) without BMP2, (<b>B</b>) with 4 nM BMP2, (<b>C</b>) with 10 nM BMP2, or (<b>D</b>) with 20 nM BMP2. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Abbreviation: Deta = Deta NONOate. Circles are outlying values. Replications (<b>A</b>,<b>B</b>) n = 6.</p>
Full article ">Figure 6
<p>Osteogenic gene expression after stimulation with the NOS substrate Arginine. C2C12BRELuc cells were stimulated for six days in Arginine-free DMEM with 10 nM BMP2 alone or in combination with 1 mM Arginine. The gene expression of <span class="html-italic">OPG, Runx2</span>, and <span class="html-italic">Col1a1</span> was investigated by qRT-PCR. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Circles are outlying values. Number of replications: n = 6.</p>
Full article ">Figure 7
<p>BMP reporter and ALP activity after inhibition of soluble guanylyl cyclase (sGC): C2C12BRELuc cell line was stimulated for 24 h in DMEM without Arginine (<b>A</b>) with 10 or 100 µM LY83583 in the presence of 1 nM BMP2 with and without 100 µM Deta NONOate. (<b>B</b>) ALP activity normalized to cell number after stimulation for 72 h in DMEM/Hams with 10 nM BMP2 and sGC inhibitor LY83583 (0.01 to 0.5 µM). Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Abbreviation: Deta = Deta NONOate. Stars and circles are outlying values. Replications (<b>A</b>) n = 9, (<b>B</b>) n = 6.</p>
Full article ">Figure 8
<p>BMP reporter activity following NO independent activation of sGC: C2C12BRELuc reporter cell line stimulated for 24 h in DMEM without Arginine with (<b>A</b>) 0.5-30 µM YC-1 and (<b>B</b>) in combination with 1 nM BMP2. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.001 (***). Circles are outlying values. Replications (<b>A</b>, <b>B</b>) n = 9.</p>
Full article ">Figure 9
<p>BMP reporter activity and SMAD1 phosphorylation after inhibition of the SMAD pathway. (<b>A</b>) C2C12BRELuc cells were stimulated for 6 h in Arginine-free DMEM with 1 nM BMP2 with or without 1 mM Arginine and 0.5 µM LDN. (<b>B</b>) C2C12BRELuc cells were stimulated for 30 min in Arginine-free DMEM with 1 nM BMP2 with or without 1 mM Arginine and 0.5 µM LDN. SMAD1 phosphorylation was measured with the SMAD1 InstantOne ELISA™ kit and normalized to total SMAD1. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Abbreviations: LDN: LDN-193189 (<b>A</b>) n = 6; (<b>B</b>) n = 3.</p>
Full article ">Figure 10
<p>BMP reporter activity after inhibition of protein kinase A (PKA) by H89: BMP reporter activity of C2C12BRELuc cells stimulated for 6 h with 1 nM BMP2, 1 µM H89, 10 and 100 µM Deta NONOate. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Abbreviation: Deta = Deta NONOate. Circles are outlying values. Replications n = 6.</p>
Full article ">Figure 11
<p>Treating C2C12BRELuc cells with BMP2 stimulated NO signaling. (<b>A</b>) NO production quantified by DAF-2-mediated fluorescence and fold comparison to untreated group. C2C12BRELuc cells were stimulated for 2 h with 750 µM Deta NONOate or 10, 20, or 50 nM BMP2. (<b>B</b>) cGMP production in cells after 1 h stimulation with 10, 50, or 100 µM Deta NONOate or 5 nM BMP2 given as fold comparison to untreated groups. Statistics: Kruskal–Wallis Test followed by Mann-Whitney <span class="html-italic">U</span> test. Mann-Whitney <span class="html-italic">U</span> test significances between samples were assigned if <span class="html-italic">p</span> &lt; 0.05 (*) or <span class="html-italic">p</span> &lt; 0.01 (**). Abbreviation: Deta: = Deta NONOate. Stars and circles indicate outlying values. Replications (A, B) n = 6.</p>
Full article ">Figure 12
<p>Graphical summary of perceived crosstalk of BMP2-mediated signaling and the NO pathway. Figure image composed from graphics taken from Servier Medical Art.</p>
Full article ">
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