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Int. J. Mol. Sci., Volume 19, Issue 3 (March 2018) – 278 articles

Cover Story (view full-size image): Tyrosinase is the key enzyme of melanin production in melanosomes, which are transferred from epidermal melanocytes to keratinocytes. Inhibitors of tyrosinase are of great clinical interest for the treatment of hyperpigmentation. However, most inhibitors described in the literature were only tested on mushroom tyrosinase and thus lack clinical efficacy. In the present study, a recombinant soluble human tyrosinase was used to analyze the structure–activity relationships of thiazolyl resorcinols, a novel class of tyrosinase inhibitor. View the paper here.
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23 pages, 1902 KiB  
Review
p53 as a Dichotomous Regulator of Liver Disease: The Dose Makes the Medicine
by Jelena Krstic, Markus Galhuber, Tim J. Schulz, Michael Schupp and Andreas Prokesch
Int. J. Mol. Sci. 2018, 19(3), 921; https://doi.org/10.3390/ijms19030921 - 20 Mar 2018
Cited by 48 | Viewed by 7364
Abstract
Lifestyle-related disorders, such as the metabolic syndrome, have become a primary risk factor for the development of liver pathologies that can progress from hepatic steatosis, hepatic insulin resistance, steatohepatitis, fibrosis and cirrhosis, to the most severe condition of hepatocellular carcinoma (HCC). While the [...] Read more.
Lifestyle-related disorders, such as the metabolic syndrome, have become a primary risk factor for the development of liver pathologies that can progress from hepatic steatosis, hepatic insulin resistance, steatohepatitis, fibrosis and cirrhosis, to the most severe condition of hepatocellular carcinoma (HCC). While the prevalence of liver pathologies is steadily increasing in modern societies, there are currently no approved drugs other than chemotherapeutic intervention in late stage HCC. Hence, there is a pressing need to identify and investigate causative molecular pathways that can yield new therapeutic avenues. The transcription factor p53 is well established as a tumor suppressor and has recently been described as a central metabolic player both in physiological and pathological settings. Given that liver is a dynamic tissue with direct exposition to ingested nutrients, hepatic p53, by integrating cellular stress response, metabolism and cell cycle regulation, has emerged as an important regulator of liver homeostasis and dysfunction. The underlying evidence is reviewed herein, with a focus on clinical data and animal studies that highlight a direct influence of p53 activity on different stages of liver diseases. Based on current literature showing that activation of p53 signaling can either attenuate or fuel liver disease, we herein discuss the hypothesis that, while hyper-activation or loss of function can cause disease, moderate induction of hepatic p53 within physiological margins could be beneficial in the prevention and treatment of liver pathologies. Hence, stimuli that lead to a moderate and temporary p53 activation could present new therapeutic approaches through several entry points in the cascade from hepatic steatosis to HCC. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Human Liver Diseases)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>p53 level-dependent outcomes in liver diseases. Various aspects of liver disease are affected by p53 levels in vivo. Please refer to the text for further details. Red circles depict negative, while green circles depict positive outcomes of p53 level alterations. Abbreviations: HCC, hepatocellular carcinoma; NASH, non-alcoholic steatohepatitis; NAFLD, non-alcoholic fatty liver disease; IR, hepatic insulin resistance; LR, liver regeneration; HSCs, hepatic stellate cells; Mϕ, macrophage; CSC, cancer stem cell; HPCs, hepatic progenitor cells.</p> Full article ">Figure 2
<p>The importance of p53 levels in liver physiology and pathology. Refer to the text for further details. Abbreviations: HCC, hepatocellular carcinoma.</p> Full article ">
17 pages, 6965 KiB  
Article
CpG ODN1826 as a Promising Mucin1-Maltose-Binding Protein Vaccine Adjuvant Induced DC Maturation and Enhanced Antitumor Immunity
by Jing Jie, Yixin Zhang, Hongyue Zhou, Xiaoyu Zhai, Nannan Zhang, Hongyan Yuan, Weihua Ni and Guixiang Tai
Int. J. Mol. Sci. 2018, 19(3), 920; https://doi.org/10.3390/ijms19030920 - 20 Mar 2018
Cited by 29 | Viewed by 7872
Abstract
Mucin 1 (MUC1), being an oncogene, is an attractive target in tumor immunotherapy. Maltose binding protein (MBP) is a potent built-in adjuvant to enhance protein immunogenicity. Thus, a recombinant MUC1 and MBP antitumor vaccine (M-M) was constructed in our laboratory. To [...] Read more.
Mucin 1 (MUC1), being an oncogene, is an attractive target in tumor immunotherapy. Maltose binding protein (MBP) is a potent built-in adjuvant to enhance protein immunogenicity. Thus, a recombinant MUC1 and MBP antitumor vaccine (M-M) was constructed in our laboratory. To enhance the antitumor immune activity of M-M, CpG oligodeoxynucleotides 1826 (CpG 1826), a toll-like receptor-9 agonist, was examined in this study as an adjuvant. The combination of M-M and CpG 1826 significantly inhibited MUC1-expressing B16 cell growth and prolonged the survival of tumor-bearing mice. It induced MUC1-specific antibodies and Th1 immune responses, as well as the Cytotoxic T Lymphocytes (CTL) cytotoxicity in vivo. Further studies showed that it promoted the maturation and activation of the dendritic cell (DC) and skewed towards Th1 phenotype in vitro. Thus, our study revealed that CpG 1826 is an efficient adjuvant, laying a foundation for further M-M clinical research. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Anti-tumor effect of different adjuvants combined with M-M. (<b>A</b>) The anti-tumor effect of different adjuvants combined with M-M. Mice were divided into seven groups, and each group (<span class="html-italic">n</span> = 10) were immunized as followings: M-M, M-M + Tα1, M-M + R848, M-M + BCG, M-M + CpG 1585, M-M + CpG 1826, or PBS on day –21 and –7 and were then subcutaneous injected (s.c.) with 2 × 10<sup>6</sup> B16-<span class="html-italic">MUC1</span> melanoma cells on day 0. Each line represents the tumor growth kinetics in each mouse. (<b>B</b>) The mean tumor growth curves are given by tumor volume. (<b>C</b>) The dose effect of CpG 1826 on the growth of B16-<span class="html-italic">MUC1</span> melanoma. Eight group of mice (<span class="html-italic">n</span> = 6) were immunized two times with CpG 1826 10, 30, and 50 μg alone or in combination with M-M (50 μg). M-M + BCG represent M-M combined BCG. The mice were sacrificed on day 24 after tumor inoculation (5 × 10<sup>5</sup> B16-<span class="html-italic">MUC1</span> melanoma cells). (<b>D</b>) The tumor inhibition rate. Tumor inhibition rate (%) = (1 − experimental group total tumor weight/control group) × 100%. (<b>E</b>) Splenocytes obtained from the immunized mice with different dose of CpG 1826. The production of IFN-γ was detected in splenocytes supernatants stimulated by IL-2 or IL-2 + MUC1-MBP. Six mice per group were analyzed. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. the negative control (NC) group.</p> Full article ">Figure 2
<p>M-M combined with CpG 1826 synergistically enhances the anti-tumor response by inducing MUC1-specific humoral and cellular immune responses. (<b>A</b>–<b>E</b>) Four groups of mice (<span class="html-italic">n</span> = 10) were injected s.c. with PBS, M-M, CpG 1826, or M-M + CpG 1826 on day –21 and –7. On day 0, the sera were collected for the MUC1-specific antibody assay. The splenic mononuclear cells from each group were stimulated in vitro with a specific MUC1 peptide (20 μg/mL) for five days, and then a cell proliferation assay and cytokine assay were carried out. (<b>A</b>) MUC1-specific IgG, IgG1, and IgG2c levels in the sera of the immunized mice were determined by ELISA on day 7 after the last immunization. (<b>B</b>) Serum IgG2c/IgG1 ratio. The data represent the mean of ten mice per group. (<b>C</b>) The lymphocyte proliferation of the different immunized mice was detected by the WST-1 assay. (<b>D</b>) The original image of the chip analysis of the splenocyte cytokine secretion by the Quantibody<sup>®</sup> array. Each mouse was replicated four times, and each group consisted of four mice. (<b>E</b>) The cytokine secretion detected by Quantibody<sup>®</sup> array is expressed as the mean ± standard deviation and is shown in a bar graph. Th1, IFN-γ secreting cells; Th2, IL-4, IL-5, IL-6 IL-13, IL-23 secreting cells; Treg, IL-10, TGF-b1; Th17, IL-17, IL-17F secreting cells. The data represent the mean of four mice per group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. NC group. (<b>F</b>–<b>H</b>) Four group of mice (<span class="html-italic">n</span> = 10) were injected s.c. with PBS, M-M, CpG 1826 or M-M + CpG 1826 on day –21 and –7. On day 0, a tumor challenge was performed with subcutaneous injection of 5 × 10<sup>5</sup> B16-<span class="html-italic">MUC1</span> cells. On day 14, the sera were collected for the MUC1-specific antibody assay. The splenic mononuclear cells from each group were stimulated in vitro with a specific MUC1 peptide (20 μg/mL) for five days, and then a cell proliferation assay, cytokine assay were carried out. (<b>F</b>) MUC1-specific IgG, IgG1 and IgG2c levels in the sera of the immunized mice were determined. (<b>G</b>) The IFN-γ secretion is detected by ELISA (<b>H</b>) lymphocyte proliferation of the different immunized mice was detected by the WST-1 assay. (<b>I</b>) Effects of M-M combined with CpG 1826 on MUC1-specific CTL killing activity. Four groups of mice (<span class="html-italic">n</span> = 10) were injected s.c. with PBS, M-M, CpG 1826, or M-M + CpG 1826 on day –21 and –7. On day 0 splenic mononuclear cells were isolated. The splenic mononuclear cells from each group were stimulated in vitro with a specific MUC1 peptide (20 μg/mL) for five days, and then CTL cytotoxicity assay was carried out. Statistical significance compared with other groups was represented as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. the NC group.</p> Full article ">Figure 2 Cont.
<p>M-M combined with CpG 1826 synergistically enhances the anti-tumor response by inducing MUC1-specific humoral and cellular immune responses. (<b>A</b>–<b>E</b>) Four groups of mice (<span class="html-italic">n</span> = 10) were injected s.c. with PBS, M-M, CpG 1826, or M-M + CpG 1826 on day –21 and –7. On day 0, the sera were collected for the MUC1-specific antibody assay. The splenic mononuclear cells from each group were stimulated in vitro with a specific MUC1 peptide (20 μg/mL) for five days, and then a cell proliferation assay and cytokine assay were carried out. (<b>A</b>) MUC1-specific IgG, IgG1, and IgG2c levels in the sera of the immunized mice were determined by ELISA on day 7 after the last immunization. (<b>B</b>) Serum IgG2c/IgG1 ratio. The data represent the mean of ten mice per group. (<b>C</b>) The lymphocyte proliferation of the different immunized mice was detected by the WST-1 assay. (<b>D</b>) The original image of the chip analysis of the splenocyte cytokine secretion by the Quantibody<sup>®</sup> array. Each mouse was replicated four times, and each group consisted of four mice. (<b>E</b>) The cytokine secretion detected by Quantibody<sup>®</sup> array is expressed as the mean ± standard deviation and is shown in a bar graph. Th1, IFN-γ secreting cells; Th2, IL-4, IL-5, IL-6 IL-13, IL-23 secreting cells; Treg, IL-10, TGF-b1; Th17, IL-17, IL-17F secreting cells. The data represent the mean of four mice per group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. NC group. (<b>F</b>–<b>H</b>) Four group of mice (<span class="html-italic">n</span> = 10) were injected s.c. with PBS, M-M, CpG 1826 or M-M + CpG 1826 on day –21 and –7. On day 0, a tumor challenge was performed with subcutaneous injection of 5 × 10<sup>5</sup> B16-<span class="html-italic">MUC1</span> cells. On day 14, the sera were collected for the MUC1-specific antibody assay. The splenic mononuclear cells from each group were stimulated in vitro with a specific MUC1 peptide (20 μg/mL) for five days, and then a cell proliferation assay, cytokine assay were carried out. (<b>F</b>) MUC1-specific IgG, IgG1 and IgG2c levels in the sera of the immunized mice were determined. (<b>G</b>) The IFN-γ secretion is detected by ELISA (<b>H</b>) lymphocyte proliferation of the different immunized mice was detected by the WST-1 assay. (<b>I</b>) Effects of M-M combined with CpG 1826 on MUC1-specific CTL killing activity. Four groups of mice (<span class="html-italic">n</span> = 10) were injected s.c. with PBS, M-M, CpG 1826, or M-M + CpG 1826 on day –21 and –7. On day 0 splenic mononuclear cells were isolated. The splenic mononuclear cells from each group were stimulated in vitro with a specific MUC1 peptide (20 μg/mL) for five days, and then CTL cytotoxicity assay was carried out. Statistical significance compared with other groups was represented as follows: * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. the NC group.</p> Full article ">Figure 3
<p>Effects of M-M, CpG 1826 on dendritic cell (DC) maturation in vivo and in vitro. (<b>A</b>,<b>B</b>) In vivo study. The draining lymph node was isolated on day 0 after an s.c. injection of PBS, M-M, CpG 1826 or M-M + CpG 1826 in the flank of the C57BL/6 mice on day –21 and –7. The draining lymph node was made into single cell suspensions. (<b>A</b>) The expression of major DCs surface markers was analyzed by flow cytometry. (<b>B</b>) The in vivo percentage of the (double positive) DC cells is expressed as the mean ± standard deviation and is shown in a bar graph. (<b>C</b>,<b>D</b>) In vitro study. (<b>C</b>) The percentage of dual-positive (DP) cells is shown in the flow cytometry histogram. The BMDCs were analyzed for the expression of CD40<sup>+</sup>CD11C<sup>+</sup>, CD80<sup>+</sup>CD11C<sup>+</sup>, CD86<sup>+</sup>CD11C<sup>+</sup>, MHCI<sup>+</sup>CD11C<sup>+</sup>, MHCII<sup>+</sup>CD11C<sup>+</sup> by flow cytometry after stimulation with PBS, M-M, CpG 1826, or M-M + CpG 1826 for 48 h in vitro. (<b>D</b>) The in vitro percentage of (DP) cells is expressed as the mean ± standard deviation and is shown in a bar graph. The data are representative of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. the NC group.</p> Full article ">Figure 3 Cont.
<p>Effects of M-M, CpG 1826 on dendritic cell (DC) maturation in vivo and in vitro. (<b>A</b>,<b>B</b>) In vivo study. The draining lymph node was isolated on day 0 after an s.c. injection of PBS, M-M, CpG 1826 or M-M + CpG 1826 in the flank of the C57BL/6 mice on day –21 and –7. The draining lymph node was made into single cell suspensions. (<b>A</b>) The expression of major DCs surface markers was analyzed by flow cytometry. (<b>B</b>) The in vivo percentage of the (double positive) DC cells is expressed as the mean ± standard deviation and is shown in a bar graph. (<b>C</b>,<b>D</b>) In vitro study. (<b>C</b>) The percentage of dual-positive (DP) cells is shown in the flow cytometry histogram. The BMDCs were analyzed for the expression of CD40<sup>+</sup>CD11C<sup>+</sup>, CD80<sup>+</sup>CD11C<sup>+</sup>, CD86<sup>+</sup>CD11C<sup>+</sup>, MHCI<sup>+</sup>CD11C<sup>+</sup>, MHCII<sup>+</sup>CD11C<sup>+</sup> by flow cytometry after stimulation with PBS, M-M, CpG 1826, or M-M + CpG 1826 for 48 h in vitro. (<b>D</b>) The in vitro percentage of (DP) cells is expressed as the mean ± standard deviation and is shown in a bar graph. The data are representative of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. the NC group.</p> Full article ">Figure 4
<p>CD4<sup>+</sup> T cell activation is enhanced by a co-culture with BMDCs stimulated with the combination of M-M and CpG 1826 in vitro. (<b>A</b>) The isolation of CD4<sup>+</sup> T cells from the spleen samples from immunized mice and BMDCs from untreated mice. The CD4<sup>+</sup> T cell and DC percentage was analyzed by flow cytometry. The purity of the CD4<sup>+</sup> T cells was 96.9%. The purity of the DCs was 96.6%. (<b>B</b>) M-M and CpG 1826 synergistically increased the proliferation of co-cultured CD4<sup>+</sup> T cells and DCs. (<b>C</b>–<b>E</b>) The production of IFN-γ, IL-12p70, and IL-4 in the CD4<sup>+</sup> T cells cocultured with DCs, as detected by ELISA. The CD4 T cells were co-cultured with the DCs at a ratio of 50:1. All the experiments were repeated three times, and all the data are expressed as the mean ± SD (<span class="html-italic">n</span> = 3). # represents production &lt;25 pg/mL. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. NC group.</p> Full article ">Figure 5
<p>Role of M-M + CpG 1826 in prophylactic and therapeutic tumor models. (<b>A</b>–<b>B</b>) M-M + CpG 1826 vaccine induced a protective effect in a prophylactic tumor model. Four groups of mice (<span class="html-italic">n</span> = 10) were injected s.c. with PBS, CpG 1826, M-M + CpG 1826, or M-M + BCG on day –21 and –7 and were then inoculated s.c. with 5 × 10<sup>5</sup> B16-<span class="html-italic">MUC1</span> melanoma cells on day 0. Tumor volume was measured every two days, and the survival of the mice was calculated. The PBS-injected mice were used as a negative control. ** <span class="html-italic">p</span> &lt; 0.01 vs. NC group. (<b>A</b>) The mean tumor growth curves given by the tumor volume. Each line represents the mean tumor growth kinetics of ten mice in each group. (<b>B</b>) Survival time of the mice. (<b>C</b>,<b>D</b>) The M-M + CpG 1826 vaccine confers therapeutic protection against melanoma. Four groups of mice (<span class="html-italic">n</span> = 10) were inoculated with 5 × 10<sup>5</sup> B16-<span class="html-italic">MUC1</span> melanoma cells on day 0 and were then injected s.c. with PBS, CpG 1826, M-M + CpG 1826 or M-M + BCG on days 7 and 21. (<b>C</b>) The mean tumor growth curves given by tumor volume. (<b>D</b>) Survival time of the mice.</p> Full article ">Figure 6
<p>The schematic outline of CpG 1826 as a promising M-M vaccine adjuvant induced DC maturation and enhanced antitumor immunity. CpG 1826 displayed the more prominent effect compared with a series adjuvants. Through in vitro and in vivo study, we found the combination of M-M and CpG 1826 strongly enhanced the maturation of DC and, thus, activated T lymphocytes. Collaboratively, better prophylactic and therapeutic tumor immunotherapy effect were obtained.</p> Full article ">
40 pages, 12893 KiB  
Review
Therapeutic Properties and Biological Benefits of Marine-Derived Anticancer Peptides
by Hee Kyoung Kang, Moon-Chang Choi, Chang Ho Seo and Yoonkyung Park
Int. J. Mol. Sci. 2018, 19(3), 919; https://doi.org/10.3390/ijms19030919 - 20 Mar 2018
Cited by 65 | Viewed by 8413
Abstract
Various organisms exist in the oceanic environment. These marine organisms provide an abundant source of potential medicines. Many marine peptides possess anticancer properties, some of which have been evaluated for treatment of human cancer in clinical trials. Marine anticancer peptides kill cancer cells [...] Read more.
Various organisms exist in the oceanic environment. These marine organisms provide an abundant source of potential medicines. Many marine peptides possess anticancer properties, some of which have been evaluated for treatment of human cancer in clinical trials. Marine anticancer peptides kill cancer cells through different mechanisms, such as apoptosis, disruption of the tubulin-microtubule balance, and inhibition of angiogenesis. Traditional chemotherapeutic agents have side effects and depress immune responses. Thus, the research and development of novel anticancer peptides with low toxicity to normal human cells and mechanisms of action capable of avoiding multi-drug resistance may provide a new method for anticancer treatment. This review provides useful information on the potential of marine anticancer peptides for human therapy. Full article
(This article belongs to the Special Issue Natural Bioactives and Phytochemicals in Cancer Prevention)
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Figure 1

Figure 1
<p>Structures of apratoxins A–D (<b>1</b>–<b>4</b>) [<a href="#B29-ijms-19-00919" class="html-bibr">29</a>,<a href="#B30-ijms-19-00919" class="html-bibr">30</a>].</p> Full article ">Figure 2
<p>Structures of aurilide (<b>5</b>), aurilide B (<b>6</b>), and aurilide C (<b>7</b>) [<a href="#B36-ijms-19-00919" class="html-bibr">36</a>,<a href="#B37-ijms-19-00919" class="html-bibr">37</a>].</p> Full article ">Figure 3
<p>Structure of bisebromoamide (<b>8</b>) [<a href="#B38-ijms-19-00919" class="html-bibr">38</a>].</p> Full article ">Figure 4
<p>Structure of coibamide A (<b>9</b>) [<a href="#B39-ijms-19-00919" class="html-bibr">39</a>].</p> Full article ">Figure 5
<p>Cryptophycin (<b>10</b>) isolated from the cyanobacterium <span class="html-italic">Nostoc</span> sp. [<a href="#B35-ijms-19-00919" class="html-bibr">35</a>].</p> Full article ">Figure 6
<p>Structure of desmethoxymajusculamide C (<b>11</b>) [<a href="#B45-ijms-19-00919" class="html-bibr">45</a>].</p> Full article ">Figure 7
<p>Structures of grassypeptolide A–E (<b>12</b>–<b>16</b>) [<a href="#B46-ijms-19-00919" class="html-bibr">46</a>,<a href="#B47-ijms-19-00919" class="html-bibr">47</a>].</p> Full article ">Figure 8
<p>Hantupeptin A (<b>17</b>) isolated from cyanobacterium <span class="html-italic">Lyngbya majuscula</span> [<a href="#B48-ijms-19-00919" class="html-bibr">48</a>].</p> Full article ">Figure 9
<p>Structure of hectochlorin (<b>18</b>) [<a href="#B51-ijms-19-00919" class="html-bibr">51</a>].</p> Full article ">Figure 10
<p>Hormothamnin A (<b>19</b>) isolated from the cyanobacterium <span class="html-italic">Hormothamnion enteromorphoides</span> [<a href="#B52-ijms-19-00919" class="html-bibr">52</a>].</p> Full article ">Figure 11
<p>Itralamide A (<b>20</b>) and B (<b>21</b>) isolated from cyanobacterium <span class="html-italic">Lyngbya majuscula</span> [<a href="#B53-ijms-19-00919" class="html-bibr">53</a>].</p> Full article ">Figure 12
<p>Structures of Lagunamide A (<b>22</b>), B (<b>23</b>), and C (<b>24</b>) [<a href="#B54-ijms-19-00919" class="html-bibr">54</a>,<a href="#B55-ijms-19-00919" class="html-bibr">55</a>].</p> Full article ">Figure 13
<p>Largazole (<b>25</b>) isolated from cyanobacterium <span class="html-italic">Symploca</span> sp. [<a href="#B56-ijms-19-00919" class="html-bibr">56</a>].</p> Full article ">Figure 14
<p>Structures of laxaphycin A (<b>26</b>) and laxaphycin B (<b>27</b>) [<a href="#B61-ijms-19-00919" class="html-bibr">61</a>,<a href="#B62-ijms-19-00919" class="html-bibr">62</a>].</p> Full article ">Figure 15
<p>Structures of Lyngbyabellin A (<b>28</b>), E, (<b>29</b>) and B (<b>30</b>) [<a href="#B64-ijms-19-00919" class="html-bibr">64</a>,<a href="#B65-ijms-19-00919" class="html-bibr">65</a>].</p> Full article ">Figure 16
<p>Structures of lyngbyastatin 4–7 (<b>31</b>–<b>34</b>) [<a href="#B67-ijms-19-00919" class="html-bibr">67</a>].</p> Full article ">Figure 17
<p>Structure of Symplocamide A (<b>35</b>) [<a href="#B68-ijms-19-00919" class="html-bibr">68</a>].</p> Full article ">Figure 18
<p>Structures of tasiamide (<b>36</b>) and tasiamide B (<b>37</b>) [<a href="#B69-ijms-19-00919" class="html-bibr">69</a>,<a href="#B70-ijms-19-00919" class="html-bibr">70</a>,<a href="#B71-ijms-19-00919" class="html-bibr">71</a>].</p> Full article ">Figure 19
<p>Veraguamide A (<b>38</b>), D (<b>39</b>), and E (<b>40</b>), isolated from <span class="html-italic">Oscillatoria margaritifera</span> [<a href="#B72-ijms-19-00919" class="html-bibr">72</a>,<a href="#B73-ijms-19-00919" class="html-bibr">73</a>].</p> Full article ">Figure 20
<p>Azonazine (<b>41</b>) isolated from <span class="html-italic">Aspergillus insulicola</span> [<a href="#B74-ijms-19-00919" class="html-bibr">74</a>].</p> Full article ">Figure 21
<p>Structure of sansalvamide A (<b>42</b>) [<a href="#B75-ijms-19-00919" class="html-bibr">75</a>].</p> Full article ">Figure 22
<p>Scopularide A (<b>43</b>) and B (<b>44</b>) isolated from fungi <span class="html-italic">Scopulariopsis brevicaulis</span> [<a href="#B77-ijms-19-00919" class="html-bibr">77</a>].</p> Full article ">Figure 23
<p>Structure of arenastatin A (<b>45</b>) [<a href="#B79-ijms-19-00919" class="html-bibr">79</a>].</p> Full article ">Figure 24
<p>Structure of discodermin A–H (<b>46</b>–<b>53</b>) [<a href="#B84-ijms-19-00919" class="html-bibr">84</a>].</p> Full article ">Figure 25
<p>Geodiamolide H (<b>54</b>) isolated from <span class="html-italic">Discodermia</span> sp. [<a href="#B85-ijms-19-00919" class="html-bibr">85</a>,<a href="#B86-ijms-19-00919" class="html-bibr">86</a>,<a href="#B87-ijms-19-00919" class="html-bibr">87</a>].</p> Full article ">Figure 26
<p>Hemiasterlin (<b>55</b>), hemiasterlin A (<b>56</b>), and hemiasterlin C (<b>57</b>) isolated from the marine sponge <span class="html-italic">Hemiasterella minor</span> [<a href="#B88-ijms-19-00919" class="html-bibr">88</a>,<a href="#B89-ijms-19-00919" class="html-bibr">89</a>,<a href="#B90-ijms-19-00919" class="html-bibr">90</a>].</p> Full article ">Figure 27
<p>Structures of homophymine A–E (<b>58</b>–<b>62</b>) and A1–E1 (<b>63</b>–<b>67</b>) [<a href="#B96-ijms-19-00919" class="html-bibr">96</a>].</p> Full article ">Figure 28
<p>Structure of jaspamide (<b>68</b>) [<a href="#B97-ijms-19-00919" class="html-bibr">97</a>].</p> Full article ">Figure 29
<p>Structures of koshikamide B (<b>69</b>) and F–H (<b>70</b>–<b>72</b>) [<a href="#B100-ijms-19-00919" class="html-bibr">100</a>,<a href="#B101-ijms-19-00919" class="html-bibr">101</a>].</p> Full article ">Figure 30
<p>Structures of microcionamide A (<b>73</b>) and B (<b>74</b>) [<a href="#B102-ijms-19-00919" class="html-bibr">102</a>].</p> Full article ">Figure 31
<p>Structure of orbiculamide A (<b>75</b>) [<a href="#B103-ijms-19-00919" class="html-bibr">103</a>].</p> Full article ">Figure 32
<p>Structures of papuamide A–F (<b>76</b>–<b>81</b>) isolated [<a href="#B83-ijms-19-00919" class="html-bibr">83</a>,<a href="#B104-ijms-19-00919" class="html-bibr">104</a>,<a href="#B105-ijms-19-00919" class="html-bibr">105</a>].</p> Full article ">Figure 33
<p>Structures of phakellistatin 1 (<b>82</b>) and 13 (<b>83</b>) [<a href="#B106-ijms-19-00919" class="html-bibr">106</a>].</p> Full article ">Figure 34
<p>Rolloamide A (<b>84</b>) isolated from the Dominican sponge <span class="html-italic">Eurypon laughlini</span> [<a href="#B109-ijms-19-00919" class="html-bibr">109</a>].</p> Full article ">Figure 35
<p>Structure of scleritodermin A (<b>85</b>) [<a href="#B110-ijms-19-00919" class="html-bibr">110</a>,<a href="#B111-ijms-19-00919" class="html-bibr">111</a>].</p> Full article ">Figure 36
<p>Structure of aplidin (<b>86</b>) [<a href="#B112-ijms-19-00919" class="html-bibr">112</a>].</p> Full article ">Figure 37
<p>Structure of didemnin B (<b>87</b>) [<a href="#B123-ijms-19-00919" class="html-bibr">123</a>].</p> Full article ">Figure 38
<p>Cycloxazoline (<b>88</b>) isolated from ascidian <span class="html-italic">Lissoclinum bistratum</span> [<a href="#B124-ijms-19-00919" class="html-bibr">124</a>,<a href="#B125-ijms-19-00919" class="html-bibr">125</a>].</p> Full article ">Figure 39
<p>Diazonamide A (<b>89</b>) isolated from ascidian <span class="html-italic">Diazona angulata</span> [<a href="#B126-ijms-19-00919" class="html-bibr">126</a>,<a href="#B127-ijms-19-00919" class="html-bibr">127</a>].</p> Full article ">Figure 40
<p>Mollamides B (<b>90</b>) and C (<b>91</b>) isolated from the ascidian <span class="html-italic">Didemnum molle</span> [<a href="#B128-ijms-19-00919" class="html-bibr">128</a>,<a href="#B129-ijms-19-00919" class="html-bibr">129</a>].</p> Full article ">Figure 41
<p>Chemical structure of tamandarin A (<b>92</b>) and tamandarin B (<b>93</b>) [<a href="#B131-ijms-19-00919" class="html-bibr">131</a>].</p> Full article ">Figure 42
<p>Trunkamide A (<b>94</b>) isolated from ascidians of the genus Lissoclinum [<a href="#B132-ijms-19-00919" class="html-bibr">132</a>].</p> Full article ">Figure 43
<p>Structures of virenamide A–C (<b>95</b>–<b>97</b>) [<a href="#B133-ijms-19-00919" class="html-bibr">133</a>].</p> Full article ">Figure 44
<p>Structure of vitilevuamide (<b>98</b>) [<a href="#B134-ijms-19-00919" class="html-bibr">134</a>].</p> Full article ">Figure 45
<p>Chemical structure of dolastatin 10 (<b>99</b>) and dolastatin 15 (<b>100</b>) [<a href="#B137-ijms-19-00919" class="html-bibr">137</a>,<a href="#B138-ijms-19-00919" class="html-bibr">138</a>].</p> Full article ">Figure 46
<p>Structure of kahalalide F (<b>101</b>) [<a href="#B142-ijms-19-00919" class="html-bibr">142</a>].</p> Full article ">Figure 47
<p>Structure of keenamide A (<b>102</b>) [<a href="#B156-ijms-19-00919" class="html-bibr">156</a>].</p> Full article ">Figure 48
<p>Structure of kulokekahilide-2 (<b>103</b>) [<a href="#B157-ijms-19-00919" class="html-bibr">157</a>].</p> Full article ">Figure 49
<p>Primary structure of ziconotide (<b>104</b>) [<a href="#B158-ijms-19-00919" class="html-bibr">158</a>]. Ziconotide has six cysteine residues, forming three disulfide bonds.</p> Full article ">
11 pages, 3980 KiB  
Article
Effects of Mutations and Ligands on the Thermostability of the l-Arginine/Agmatine Antiporter AdiC and Deduced Insights into Ligand-Binding of Human l-Type Amino Acid Transporters
by Hüseyin Ilgü, Jean-Marc Jeckelmann, Claire Colas, Zöhre Ucurum, Avner Schlessinger and Dimitrios Fotiadis
Int. J. Mol. Sci. 2018, 19(3), 918; https://doi.org/10.3390/ijms19030918 - 20 Mar 2018
Cited by 18 | Viewed by 4841
Abstract
The l-arginine/agmatine transporter AdiC is a prokaryotic member of the SLC7 family, which enables pathogenic enterobacteria to survive the extremely acidic gastric environment. Wild-type AdiC from Escherichia coli, as well as its previously reported point mutants N22A and S26A, were overexpressed homologously [...] Read more.
The l-arginine/agmatine transporter AdiC is a prokaryotic member of the SLC7 family, which enables pathogenic enterobacteria to survive the extremely acidic gastric environment. Wild-type AdiC from Escherichia coli, as well as its previously reported point mutants N22A and S26A, were overexpressed homologously and purified to homogeneity. A size-exclusion chromatography-based thermostability assay was used to determine the melting temperatures (Tms) of the purified AdiC variants in the absence and presence of the selected ligands l-arginine (Arg), agmatine, l-arginine methyl ester, and l-arginine amide. The resulting Tms indicated stabilization of AdiC variants upon ligand binding, in which Tms and ligand binding affinities correlated positively. Considering results from this and previous studies, we revisited the role of AdiC residue S26 in Arg binding and proposed interactions of the α-carboxylate group of Arg exclusively with amide groups of the AdiC backbone. In the context of substrate binding in the human SLC7 family member l-type amino acid transporter-1 (LAT1; SLC7A5), an analogous role of S66 in LAT1 to S26 in AdiC is discussed based on homology modeling and amino acid sequence analysis. Finally, we propose a binding mechanism for l-amino acid substrates to LATs from the SLC7 family. Full article
(This article belongs to the Special Issue Amino Acids Transport and Metabolism)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>View into the substrate binding sites of the AdiC crystal structures in the outward-open, substrate-free (<sup>apo</sup>AdiC-wt; PDB ID code: 5J4I) (<b>A</b>); and outward-facing, occluded, <span class="html-small-caps">l</span>-arginine-bound states (<sup>Arg</sup>AdiC-N22A; PDB ID code: 3L1L) (<b>B</b>). Amino acid side chains located in the substrate binding pockets and reported to interact with substrates are displayed as sticks. The exception represents N22, which is located near the substrate binding site and was not reported to interact with substrates in the currently available crystal structures. The volumes of the substrate binding pockets (indicated and colored in dark orange) are different in the outward-open and outward-facing occluded states because of the different protein conformations and positions of residue W202. Residues N22 and S26, which are pertinent to the presented study, are colored in magenta and black in the <sup>apo</sup>AdiC-wt and <sup>Arg</sup>AdiC-N22A structures, respectively. The bound Arg molecule in the <sup>Arg</sup>AdiC-N22A structure is colored in yellow. The <sup>apo</sup>AdiC-wt and <sup>Arg</sup>AdiC-N22A structures are shown as ribbons colored in light-yellow and light-magenta. Besides N22 and S26, amino acid side chains involved in substrate binding are colored in salmon and light-blue in the <sup>apo</sup>AdiC-wt and <sup>Arg</sup>AdiC-N22A structures, respectively. The hydrogen bond between S26 and the α-carboxylate group of Arg is indicated by a dotted line, as well as the distance in Å.</p> Full article ">Figure 2
<p>Workflow for <span class="html-italic">T</span><sub>m</sub> determination of ligand-free and -bound membrane protein using SEC. Purified membrane protein samples in the absence and presence of selected ligands are exposed to different temperatures for a defined time period and then subjected to SEC using a thermocycler and an FPLC, respectively. Peak heights in elution profiles enable the quantification of the fraction of membrane protein that remains intact after heat treatment. Plotting of remaining fractions versus temperatures results in melting curves from which <span class="html-italic">T</span><sub>m</sub> values are determined. Comparison of <span class="html-italic">T</span><sub>m</sub>s allows determination of possible ligand-induced stabilization effects on purified membrane proteins, e.g., right shift of the blue melting curve (protein with ligand), indicating increased <span class="html-italic">T</span><sub>m</sub> compared to the red curve (protein without ligand). The flow chart was adapted from Mancusso et al. (2011) [<a href="#B24-ijms-19-00918" class="html-bibr">24</a>]. Membrane protein structures without and with bound ligand are coloured in red and blue (ligand in magenta), respectively.</p> Full article ">Figure 3
<p>SDS-PAGE analysis of purified AdiC variants. A Coomassie brilliant-blue stained 13.5% SDS/polyacrylamide gel of wild-type AdiC (wt), and N22A and S26A AdiC mutants (5 µg of protein loaded per lane) is shown.</p> Full article ">Figure 4
<p>Thermostability curves and resulting melting temperatures of AdiC-wt, AdiC-N22A, and AdiC-S26A in the absence and presence of selected ligands. Ligands: <span class="html-small-caps">l</span>-arginine (Arg), agmatine (Agm), <span class="html-small-caps">l</span>-arginine methyl ester (Arg-OMe), and <span class="html-small-caps">l</span>-arginine amide (Arg-NH2). <span class="html-italic">T</span><sub>m</sub>: melting temperature. The determined <span class="html-italic">T</span><sub>m</sub> values are from at least three independent experiments, each in triplicate, and 95% confidence interval values are indicated below <span class="html-italic">T</span><sub>m</sub>s. Error bars represent SEM.</p> Full article ">Figure 5
<p>Amino acid sequence comparison between AdiC from <span class="html-italic">E. coli</span> and human <span class="html-small-caps">l</span>-amino acid transporters (LATs) from the SLC7 family. Identity and similarity values between different sequences are indicated in percentages and color scored. The Asc-2 (Slc7a12) and arpAT (Slc7a15) LATs were not considered in the sequence analysis, because their genes are not present or highly inactivated in primate genomes [<a href="#B26-ijms-19-00918" class="html-bibr">26</a>].</p> Full article ">Figure 6
<p>Homology model of human LAT1 with docked <span class="html-small-caps">l</span>-Phe substrate (<sup>Phe</sup>LAT1) and <span class="html-small-caps">l</span>-amino acid binding hypothesis for LATs. (<b>A</b>) View into the substrate binding site (colored in dark orange) of the AdiC structure-based human LAT1 homology model [<a href="#B9-ijms-19-00918" class="html-bibr">9</a>]. Oxygen and nitrogen atoms from carbonyl and amide groups of protein backbone amino acid residues (displayed as sticks and colored in grey) that are in hydrogen bond distance to the α-amino and α-carboxyl groups of the substrate <span class="html-small-caps">l</span>-Phe (colored in gold) are indicated as dotted lines. Interatomic distances are indicated, and numbers correspond to Å. The <sup>Phe</sup>LAT1 model is shown as ribbon colored in light-grey. (<b>B</b>) Potential binding mechanism of <span class="html-small-caps">l</span>-amino acid substrates to LATs from the SLC7 family. Based on the LAT1 homology model (<b>A</b>) [<a href="#B9-ijms-19-00918" class="html-bibr">9</a>] and the available AdiC structures with bound substrates [<a href="#B6-ijms-19-00918" class="html-bibr">6</a>,<a href="#B8-ijms-19-00918" class="html-bibr">8</a>], protein backbone interactions via carbonyl and amide groups with the α-amino and α-carboxyl group of the amino acid substrates are proposed. For interactions with the variable R-group of amino acid substrates, one backbone interaction and arbitrary amino acid side chains are displayed.</p> Full article ">
19 pages, 4357 KiB  
Article
The Influence of High and Low Doses of Bisphenol A (BPA) on the Enteric Nervous System of the Porcine Ileum
by Kamila Szymanska, Krystyna Makowska and Slawomir Gonkowski
Int. J. Mol. Sci. 2018, 19(3), 917; https://doi.org/10.3390/ijms19030917 - 20 Mar 2018
Cited by 46 | Viewed by 5847
Abstract
Bisphenol A, used in the production of plastic, is able to leach from containers into food and cause multidirectional adverse effects in living organisms, including neurodegeneration and metabolic disorders. Knowledge of the impact of BPA on enteric neurons is practically non-existent. The destination [...] Read more.
Bisphenol A, used in the production of plastic, is able to leach from containers into food and cause multidirectional adverse effects in living organisms, including neurodegeneration and metabolic disorders. Knowledge of the impact of BPA on enteric neurons is practically non-existent. The destination of this study was to investigate the influence of BPA at a specific dose (0.05 mg/kg body weight/day) and at a dose ten times higher (0.5 mg/kg body weight/day), given for 28 days, on the porcine ileum. The influence of BPA on enteric neuron immunoreactive to selected neuronal active substances, including substance P (SP), vasoactive intestinal polypeptide (VIP), galanin (GAL), vesicular acetylcholine transporter (VAChT—used here as a marker of cholinergic neurons), and cocaine- and amphetamine-regulated transcript peptide (CART), was studied by the double immunofluorescence method. Both doses of BPA affected the neurochemical characterization of the enteric neurons. The observed changes depended on the type of enteric plexus but were generally characterized by an increase in the number of cells immunoreactive to the particular substances. More visible fluctuations were observed after treatment with higher doses of BPA. The results confirm that even low doses of BPA may influence the neurochemical characterization of the enteric neurons and are not neutral for living organisms. Full article
(This article belongs to the Special Issue Advances in the Research of Endocrine Disrupting Chemicals)
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Figure 1

Figure 1
<p>The enteric nervous system in the ileum of the pig. Parts of the wall of the intestine: LM—longitudinal muscle layer; CM—circular muscle layer; SL—submucosal layer; ML—mucosal layer. Parts of the enteric nervous system: MP—myenteric plexus; OSP—outer submucous plexus; ISP—inner submucous plexus.</p> Full article ">Figure 2
<p>Histopathological staging of the ileum after administration of low (A) and high (B) doses of BPA: (1) less (<b>1A</b>) and more numerous (<b>1B</b>) eosinophils (indicated by arrows); (2) the lack (<b>2A</b>) and the presence (<b>2B</b>) of inflammatory cells in intestinal crypts (intestinal crypts are indicated by arrows); (3) the changes in the appearance of Peyer’s patches depending on BPA dose: Peyer’s patches in the LD group (<b>3A</b>) and merged structures in the HD group (<b>3B</b>) (Peyer’s patches are indicated by arrows).</p> Full article ">Figure 2 Cont.
<p>Histopathological staging of the ileum after administration of low (A) and high (B) doses of BPA: (1) less (<b>1A</b>) and more numerous (<b>1B</b>) eosinophils (indicated by arrows); (2) the lack (<b>2A</b>) and the presence (<b>2B</b>) of inflammatory cells in intestinal crypts (intestinal crypts are indicated by arrows); (3) the changes in the appearance of Peyer’s patches depending on BPA dose: Peyer’s patches in the LD group (<b>3A</b>) and merged structures in the HD group (<b>3B</b>) (Peyer’s patches are indicated by arrows).</p> Full article ">Figure 3
<p>Myenteric plexus in control animals (<b>a</b>) and after BPA treatment in low (<b>b</b>) and high (<b>c</b>) doses, immunostained for protein gene product 9.5 (PGP 9.5, a pan-neuronal marker) and other neuronal factors including substance P (SP), vasoactive intestinal polypeptide (VIP), galanin (GAL), vesicular acetylcholine transporter (VAChT—used here as a marker of cholinergic neurons), and cocaine- and amphetamine-regulated transcript peptide (CART). Neurons showing co-localization of PGP 9.5 and other neuronal factors are indicated with arrows.</p> Full article ">Figure 4
<p>Outer submucous plexus in control animals (<b>a</b>) and after BPA treatment in low (<b>b</b>) and high (<b>c</b>) doses, immunostained for protein gene product 9.5 (PGP 9.5, a pan-neuronal marker) and other neuronal factors including substance P (SP), vasoactive intestinal polypeptide (VIP), galanin (GAL), vesicular acetylcholine transporter (VAChT—used here as a marker of cholinergic neurons), and cocaine- and amphetamine-regulated transcript peptide (CART). Neurons showing co-localization of PGP 9.5 and other neuronal factors are indicated with arrows.</p> Full article ">Figure 5
<p>Inner submucous plexus in control animals (<b>a</b>) and after BPA treatment in low (<b>b</b>) and high (<b>c</b>) doses, immunostained for protein gene product 9.5 (PGP 9.5—used here as a pan-neuronal marker) and other neuronal factors including substance P (SP), vasoactive intestinal polypeptide (VIP), galanin (GAL), vesicular acetylcholine transporter (VAChT—used here as a marker of cholinergic neurons), and cocaine- and amphetamine-regulated transcript peptide (CART). Neurons showing co-localization of PGP 9.5 and other neuronal factors are indicated with arrows.</p> Full article ">Figure 6
<p>The concentration of the selected pro-inflammatory cytokines in the ileal Payer’s patches in control animals (C) and under low (LD) and high (HD) doses of BPA. Statistically significant (<span class="html-italic">p</span> ≤ 0.05) and highly statistically significant (<span class="html-italic">p</span> ≤ 0.01) differences between C group and LD group, C group and HD group, as well as LD group and HD group, are marked with * and **, respectively.</p> Full article ">
23 pages, 6714 KiB  
Article
Site-Mutation of Hydrophobic Core Residues Synchronically Poise Super Interleukin 2 for Signaling: Identifying Distant Structural Effects through Affordable Computations
by Longcan Mei, Yanping Zhou, Lizhe Zhu, Changlin Liu, Zhuo Wu, Fangkui Wang, Gefei Hao, Di Yu, Hong Yuan and Yanfang Cui
Int. J. Mol. Sci. 2018, 19(3), 916; https://doi.org/10.3390/ijms19030916 - 20 Mar 2018
Cited by 2 | Viewed by 5308
Abstract
A superkine variant of interleukin-2 with six site mutations away from the binding interface developed from the yeast display technique has been previously characterized as undergoing a distal structure alteration which is responsible for its super-potency and provides an elegant case study with [...] Read more.
A superkine variant of interleukin-2 with six site mutations away from the binding interface developed from the yeast display technique has been previously characterized as undergoing a distal structure alteration which is responsible for its super-potency and provides an elegant case study with which to get insight about how to utilize allosteric effect to achieve desirable protein functions. By examining the dynamic network and the allosteric pathways related to those mutated residues using various computational approaches, we found that nanosecond time scale all-atom molecular dynamics simulations can identify the dynamic network as efficient as an ensemble algorithm. The differentiated pathways for the six core residues form a dynamic network that outlines the area of structure alteration. The results offer potentials of using affordable computing power to predict allosteric structure of mutants in knowledge-based mutagenesis. Full article
(This article belongs to the Special Issue Proteins and Protein-Ligand Interactions)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The dynamic network in CypA detected by NMR experiments. The common dynamic network has been reported in the literature. The residues with chemical shift changes in single-mutation R55A (<b>a</b>), H70A (<b>b</b>) and K82A (<b>c</b>) are colored in red. The residues with chemical shift changes in double-mutation R55A and K82A (<b>d</b>), R55A and H70 (<b>e</b>) and H70A and K82A (<b>f</b>) are colored in red and represented as spheres.</p> Full article ">Figure 2
<p>The dynamic network in CypA deduced by cross-correlation analysis and COREX/BEST algorithm. (<b>a</b>–<b>c</b>) The dynamic network deduced by cross-correlation analysis. The dominant correlated pattern of the residues in CypA is shown relative to residues R55 (<b>a</b>), H70 (<b>b</b>) and K82 (<b>c</b>), respectively. The residues color coded red, orange and yellow are correlated, while these residues are anticorrelated with those color-coded blue. (<b>d</b>–<b>f</b>) The dynamic network deduced by COREX/BEST algorithm. The energetic coupling regions in the network for R55A (<b>d</b>), H70A (<b>e</b>) and K82A (<b>f</b>) are colored in red. The effects of single Ala substitution on all other residues are quantified by calculating the change in free energy. For clarity the coupling regions only consist of the residues with the free energy change greater than 0.2 kcal/mol. (<b>g</b>) Comparison of the dynamic network calculated by cross-correlation analysis and NMR experiments. Along the protein sequence, red regions indicate residues within the dynamic network. Boxes with vertical bars indicate the residues experiencing chemical-shift changes by NMR experiments. Numbers along the sequence show residues index.</p> Full article ">Figure 3
<p>Structural rearrangement resulting from the mutations. (<b>a</b>) The crystal structure of interleukin-2 (IL-2). The sidechains of mutated residues are shown as stick type in Red. Q74, L80, R81 are located on the BC loop and L85, I86, I92 are located within the helix C core; (<b>b</b>) The structure superposition of IL-2 (green) and D10 (magenta). The completely overlapped regions in the structures are colored in light color, whereas the obvious deviations are highlighted in bright color. The mini helix, the helix B-C linker region and the loop region subsequent to helix C show significant conformational changes. The N-terminus of helix A and the C-terminus of helix D show slight deviations.</p> Full article ">Figure 4
<p>The possible pathway for the propagation of disturbance by residue mutation at Q74 in IL-2. (<b>a</b>) The dynamic network in IL-2 deduced by cross-correlation analysis. The dominant correlated pattern of the residues in IL-2 is shown relative to residues Q74. The residues color coded red, orange and yellow are correlated, but these residues are anticorrelated with those color-coded blue; (<b>b</b>) The dynamic network in IL-2 deduced by COREX/BEST algorithm. The energetic coupled regions in the network for Q74A are colored in red. For clarity the coupling regions only consist of the residues with the free energy change greater than 1.0 kcal/mol; (<b>c</b>) The possible allosteric pathway between the mutation site of Q74 and the coupling regions. Network representation of IL-2. The red bold edges represent allosteric pathways connecting mutation sites (magenta nodes) and coupling residues (blue nodes). The other components are represented as gray nodes.</p> Full article ">Figure 5
<p>The possible pathway for the propagation of disturbance by residue mutations at L80 in IL-2. (<b>a</b>) The dynamic network in IL-2 deduced by cross-correlation analysis. The dominant correlated pattern of the residues in IL-2 is shown relative to residues L80; (<b>b</b>) The dynamic network in IL-2 deduced by COREX/BEST algorithm. The energetic coupling regions in the network for L80A are colored in red; (<b>c</b>) The possible allosteric pathway between the mutation site of L80 and the coupling regions. The illustration for all graphs is the same as that in <a href="#ijms-19-00916-f004" class="html-fig">Figure 4</a>.</p> Full article ">Figure 6
<p>The possible pathway for the propagation of disturbance by residue mutations at L85 in IL-2. (<b>a</b>) The dynamic network in IL-2 deduced by cross-correlation analysis. The dominant correlated pattern of the residues in IL-2 is shown relative to residues L85; (<b>b</b>) The dynamic network in IL-2 deduced by COREX/BEST algorithm. The energetic coupling regions in the network for L85A are colored in red; (<b>c</b>) The possible allosteric pathway between L85 and the coupling regions. The illustration for all graphs is the same as that in <a href="#ijms-19-00916-f004" class="html-fig">Figure 4</a>.</p> Full article ">Figure 7
<p>The possible pathway for the propagation of disturbance by residue mutations at I92 in IL-2. (<b>a</b>) The dynamic network in IL-2 deduced by cross-correlation analysis. The dominant correlated pattern of the residues in IL-2 is shown relative to residues I92; (<b>b</b>) The dynamic network in IL-2 deduced by COREX/BEST algorithm. The energetic coupling regions in the network for I92A are colored in red; (<b>c</b>) The possible allosteric pathway between I92 and the coupling regions. The illustration for all graphs is the same as that in <a href="#ijms-19-00916-f004" class="html-fig">Figure 4</a>.</p> Full article ">Figure 8
<p>The dynamic network corresponding to the six mutation sites in IL-2 was detected by cross-correlation analysis and COREX/BEST algorithm. (<b>a</b>) The motion correlated regions relative to the mutation sites derived from MD simulation are shown in magenta on the cartoon representation of IL-2 structure; (<b>b</b>) A combined energetic coupling region based on COREX/BEST algorithm are shown in red on the cartoon representation of IL-2 structure; (<b>c</b>) Comparisons of the dynamic networks calculated by cross-correlation analysis and COREX/BEST algorithm, and with the regions undergoing structural changes in the protein crystals. Along the protein sequence, blue regions indicate the residues within the dynamic networks. Boxes with diagonal bars were painted upon the blue regions to indicate overlapped regions of the dynamic networks calculated by these two methods. Boxes with vertical bars indicate the structural change regions from experimental data (Crystal Strucrues). Numbers along the sequence show residues index.</p> Full article ">Figure 9
<p>The measurement of betweenness centrality in IL-2. (<b>a</b>) Betweenness centrality (BC) profile showing regions in IL-2. Peak locations indicate residues with high frequencies of usage in intra-domain communication; (<b>b</b>) Structural mapping of high BC residues. The cartoon presentation of the crystal structure of IL-2 with peak residues shown as blue spheres.</p> Full article ">Figure 10
<p>The measurement of reachability in IL-2. (<b>a</b>) Change in reachability (ΔL<sub>i</sub>) plots for the protein of IL-2. Regions with high ∆L<sub>i</sub> are important structural elements for intra-domain communication; (<b>b</b>) Structural mapping of high ΔL<sub>i</sub> residues on the cartoon presentation of the crystal structure of IL-2. The peak residues in (<b>a</b>) were shown as orange spheres.</p> Full article ">Figure 11
<p>Structural alterations caused by residue mutations in interleukin-1β. (<b>a</b>) The crystal structure of interleukin-1β with a solvent-exposed hydrophobic cavity surrounded by β-strands. The corresponding mutated residues in its double mutant (F42W/W120F) are colored in red. The residue F42 is located at a β-strand in the hydrophobic core, and residue W120 locates in a short loop region outside the hydrophobic core; (<b>b</b>) Structural superposition of wild-type IL-1β (cyan) and its double mutant (orange). The conformational deviations are highlighted in bright color, while the complete overlapped regions are in pale color. Subtle structural changes occur in some β-strands surrounding the hydrophobic cavity and the short loop regions linking these β-strands.</p> Full article ">Figure 12
<p>The dynamic network in IL-1β deduced by cross-correlation analysis. (<b>a</b>,<b>b</b>) The dominant correlated pattern of the residues in IL-1β is shown relative to residues F42 (<b>a</b>) and W120 (<b>b</b>), respectively. The residues color coded red, orange and yellow are correlated, but these residues are anticorrelated with those color coded blue. (<b>c</b>) The motion correlated regions relative to the mutation sites are shown in magenta on the cartoon representation of IL-1β structure, which include all regions mentioned in (<b>a</b>,<b>b</b>).</p> Full article ">Figure 13
<p>The dynamic network in IL-1β deduced by COREX/BEST algorithm. The identified coupling regions in the networks for W120A are colored in red. The susceptible residues in the coupling regions are identified as the residues with the free energy change greater than 0.6 kcal/mol. The widespread coupling regions suggest that the effects of the mutations can propagate to distal regions, not limited to mutation sites.</p> Full article ">
22 pages, 5135 KiB  
Article
Alternative Respiratory Pathway Component Genes (AOX and ND) in Rice and Barley and Their Response to Stress
by Vajira R. Wanniarachchi, Lettee Dametto, Crystal Sweetman, Yuri Shavrukov, David A. Day, Colin L. D. Jenkins and Kathleen L. Soole
Int. J. Mol. Sci. 2018, 19(3), 915; https://doi.org/10.3390/ijms19030915 - 20 Mar 2018
Cited by 39 | Viewed by 5883
Abstract
Plants have a non-energy conserving bypass of the classical mitochondrial cytochrome c pathway, known as the alternative respiratory pathway (AP). This involves type II NAD(P)H dehydrogenases (NDs) on both sides of the mitochondrial inner membrane, ubiquinone, and the alternative oxidase (AOX). The AP [...] Read more.
Plants have a non-energy conserving bypass of the classical mitochondrial cytochrome c pathway, known as the alternative respiratory pathway (AP). This involves type II NAD(P)H dehydrogenases (NDs) on both sides of the mitochondrial inner membrane, ubiquinone, and the alternative oxidase (AOX). The AP components have been widely characterised from Arabidopsis, but little is known for monocot species. We have identified all the genes encoding components of the AP in rice and barley and found the key genes which respond to oxidative stress conditions. In both species, AOX is encoded by four genes; in rice OsAOX1a, 1c, 1d and 1e representing four clades, and in barley, HvAOX1a, 1c, 1d1 and 1d2, but no 1e. All three subfamilies of plant ND genes, NDA, NDB and NDC are present in both rice and barley, but there are fewer NDB genes compared to Arabidopsis. Cyanide treatment of both species, along with salt treatment of rice and drought treatment of barley led to enhanced expression of various AP components; there was a high level of co-expression of AOX1a and AOX1d, along with NDB3 during the stress treatments, reminiscent of the co-expression that has been well characterised in Arabidopsis for AtAOX1a and AtNDB2. Full article
(This article belongs to the Special Issue Plant Mitochondria)
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<p>Rice and barley comparative maps with positions of identified <span class="html-italic">AOX</span> genes. (<b>A</b>) <span class="html-italic">AOX1a</span> and <span class="html-italic">AOX1d</span>; (<b>B</b>) <span class="html-italic">AOX1c</span> and <span class="html-italic">AOX1e</span>. Corresponding genes are indicated by dashed lines. Information about rice and barley genes are their locations was extracted from web-sites, respectively: <a href="http://rice.plantbiology.msu.edu" target="_blank">http://rice.plantbiology.msu.edu</a> and <a href="http://pgsb.helmholtz-muenchen.de/plant/barley" target="_blank">http://pgsb.helmholtz-muenchen.de/plant/barley</a>.</p> Full article ">Figure 2
<p>Identification of an additional intron in the sequence of <span class="html-italic">OsNDB3</span>, japonica rice, which encodes a predicted OsNDB3 polypeptide of 580 aa, correcting the annotated size of 357 aa. A schematic presentation of the <span class="html-italic">OsNDB3</span> gene structures in both japonica and indica rice with the missing or corrected intron. Exons are shown as black boxes or as clear boxes after the premature stop-codon of the missed intron. Start-codons on 5′-end and stop-codons on 3′-end are shown in purple. The predicted sizes of the polypeptides are indicated.</p> Full article ">Figure 3
<p>Relationship tree that shows the sequence homology of alternative dehydrogenases from rice, barley and Arabidopsis. Clades A, B and C correspond to NDA, NDB and NDC, respectively. The tree was constructed using the Neighbour-Joining method in MEGA 7. Numbers at each node are the percentage bootstrap values of 1000 replicates. The scale bar indicates the number of amino acid substitutions at each site.</p> Full article ">Figure 4
<p>Alignment of a section of AOX isoforms in rice and barley. The amino acid sequences were aligned using the Clustal program. The region showing all the cysteine residues of these AOX proteins is shown. OsAOX1d has a serine at Cys<sub>1</sub>; HvAOX1d1, HvAOX1d2 and OsAOX1d have a serine at Cys<sub>II</sub>; all rice and barley AOX isoforms have a leucine at Cys<sub>II</sub> instead of a cysteine or phenylalanine.</p> Full article ">Figure 5
<p>An alignment of the NAD(P)H binding domain in rice and barley ND families with Arabidopsis homologues. The sequences were aligned using the Clustal program. Substrate specificity is given on the right for each enzyme that has been experimentally determined [<a href="#B10-ijms-19-00915" class="html-bibr">10</a>,<a href="#B39-ijms-19-00915" class="html-bibr">39</a>,<a href="#B42-ijms-19-00915" class="html-bibr">42</a>]. Residues are Δ, basic or hydrophilic; □, hydrophobic; ө, acidic; and G, Glycine. The acidic residue alters the specificity for NADH- and NADPH-specific proteins and is indicated as an arrow.</p> Full article ">Figure 6
<p>Chemical treatment increases AOX protein levels in barley shoot and root tissue. Barley seedlings (14 days old) were exposed to 5 mM potassium cyanide (KCN) for up to 24 h, then root and shoot tissue were used for crude protein extractions. (<b>A</b>) Immunoblot of crude protein extracts under reduction conditions. The expected size for HvAOX is 35–37 kDa. Expression levels of <span class="html-italic">AOX</span> isoforms were determined using qRT-PCR in shoots (<b>B</b>) and roots (<b>C</b>). Expression data were normalized with reference genes <span class="html-italic">Actin</span>, <span class="html-italic">Ubiquitin</span> and <span class="html-italic">Pdf</span> (Protein phosphatase) and shown as mean of 4 biological replicates. Gene expression data were derived from the same experiment as presented in <a href="#ijms-19-00915-t003" class="html-table">Table 3</a>, but shown as normalised expression instead of fold-change, to demonstrate the relative level of expression between genes. * denotes significantly different (<span class="html-italic">p</span> &lt; 0.01) from the control (<b>C</b>).</p> Full article ">Figure 7
<p>Response of alternative oxidases (AOXs) in rice under salt stress. Fold change expression of <span class="html-italic">AOX</span> isoforms, <span class="html-italic">AOX1a</span>, <span class="html-italic">AOX1c</span> and <span class="html-italic">AOX1d</span> in seedling shoots (<b>A</b>) and roots (<b>B</b>) were analysed in response to 120 mM NaCl using qRT-PCR over a period of 12 days. Data are shown as the mean ± SE of three biological replicates relative to the control at each time point set as 1.0. Significant differences are indicated by asterisks (*) at <span class="html-italic">p</span> &lt; 0.01 (<span class="html-italic">t</span>-test). Immunoblots of the AOX protein present in purified mitochondria from salt-treated and non-treated (control) shoots (<b>C</b>) and roots (<b>D</b>) harvested 9 days after the start of salt application. The numbers below each lane of the blot, represent the AOX capacity determined for the purified mitochondria for that treatment.</p> Full article ">Figure 8
<p>Expression of alternative dehydrogenases (NDs) in rice under salt stress. Fold change expression of <span class="html-italic">ND</span> isoforms, <span class="html-italic">OsNDA1</span>, <span class="html-italic">OsNDA2</span>, <span class="html-italic">OsNDB1</span>, <span class="html-italic">OsNDB2</span>, <span class="html-italic">OsNDB3</span> and <span class="html-italic">OsNDC1</span>, in seedling shoots (<b>A</b>) and roots (<b>B</b>) were analysed in response to 120 mM NaCl using qRT-PCR over a period of 12 days. Data are shown as the mean ± SE of three biological replicates relative to the control at each time point set as 1.00. Significant differences are indicated by asterisks (*) at <span class="html-italic">p</span> &lt; 0.01 (<span class="html-italic">t</span>-test).</p> Full article ">Figure 9
<p>Expression of <span class="html-italic">OsNDB2</span> in rice under salt stress. Expression was analysed in seedling roots (<b>A</b>) and shoots (<b>B</b>) exposed to 120 mM NaCl over the period of 15 days using qRT-PCR. Data are shown as the mean relative gene expression ± SE of three biological replicates; (<b>C</b>). An immunoblot of the OsNDB2 protein present in mitochondria isolated from salt-treated and control shoots harvested 9 days after the start of salt application. CR-control roots; TR-treated roots; CS-control shoots; TS-treated shoots.</p> Full article ">Figure 10
<p>Detection of AOX protein in barley exposed to moderate drought stress. Soil grown 12 days old barley seedlings (<span class="html-italic">Hordeum vulgare</span>, cv. Golden Promise) were exposed to drought stress by withholding water for 14 days under greenhouse conditions. AOX protein was detected in total protein extracts of shoot tissue in plants grown in well-watered controls (C) and drought, withhold conditions (D) resolved under reducing conditions. The relative water contents for the plant were 83% and 69% in control and drought conditions, respectively.</p> Full article ">
11 pages, 625 KiB  
Review
hCG and Its Disruption by Environmental Contaminants during Human Pregnancy
by Luana Paulesu, Ch.V. Rao, Francesca Ietta, Adalgisa Pietropolli and Carlo Ticconi
Int. J. Mol. Sci. 2018, 19(3), 914; https://doi.org/10.3390/ijms19030914 - 20 Mar 2018
Cited by 35 | Viewed by 9994
Abstract
Human chorionic gonadotropin (hCG) is a hormone of considerable importance in the establishment, promotion and maintenance of human pregnancy. It has been clearly demonstrated that hCG exerts multiple endocrine, paracrine and autocrine actions on a variety of gestational and non-gestational cells and tissues. [...] Read more.
Human chorionic gonadotropin (hCG) is a hormone of considerable importance in the establishment, promotion and maintenance of human pregnancy. It has been clearly demonstrated that hCG exerts multiple endocrine, paracrine and autocrine actions on a variety of gestational and non-gestational cells and tissues. These actions are directed to promote trophoblast invasiveness and differentiation, placental growth, angiogenesis in uterine vasculature, hormone production, modulation of the immune system at the maternal-fetal interface, inhibition of myometrial contractility as well as fetal growth and differentiation. In recent years, considerable interest has been raised towards the biological effects of environmental contaminants, particularly endocrine disrupting chemicals (EDCs). Emerging evidence suggests that prenatal exposure to selected EDCs can have a deleterious impact on the fetus and long-lasting consequences also in adult life. The results of the in vitro effects of commonly found EDCs, particularly Bisphenol A (BPA) and para-Nonylphenol (p-NP), indicate that these substances can alter hCG production and through this action could exert their fetal damage, suggesting that hCG could represent and become a potentially useful clinical biomarker of an inappropriate prenatal exposure to these substances. Full article
(This article belongs to the Special Issue hCG—An Endocrine, Regulator of Gestation and Cancer)
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<p>Potential mechanisms by which EDCs could alter placental development and hCG production and affect pregnancy outcome: changes in maternal serum hCG concentration could act as biomarkers of EDCs action.</p> Full article ">
14 pages, 1337 KiB  
Review
PPARβ/δ: A Key Therapeutic Target in Metabolic Disorders
by Xavier Palomer, Emma Barroso, Javier Pizarro-Delgado, Lucía Peña, Gaia Botteri, Mohammad Zarei, David Aguilar, Marta Montori-Grau and Manuel Vázquez-Carrera
Int. J. Mol. Sci. 2018, 19(3), 913; https://doi.org/10.3390/ijms19030913 - 20 Mar 2018
Cited by 76 | Viewed by 7345
Abstract
Research in recent years on peroxisome proliferator-activated receptor (PPAR)β/δ indicates that it plays a key role in the maintenance of energy homeostasis, both at the cellular level and within the organism as a whole. PPARβ/δ activation might help prevent the development of metabolic [...] Read more.
Research in recent years on peroxisome proliferator-activated receptor (PPAR)β/δ indicates that it plays a key role in the maintenance of energy homeostasis, both at the cellular level and within the organism as a whole. PPARβ/δ activation might help prevent the development of metabolic disorders, including obesity, dyslipidaemia, type 2 diabetes mellitus and non-alcoholic fatty liver disease. This review highlights research findings on the PPARβ/δ regulation of energy metabolism and the development of diseases related to altered cellular and body metabolism. It also describes the potential of the pharmacological activation of PPARβ/δ as a treatment for human metabolic disorders. Full article
(This article belongs to the Special Issue PPARs in Cellular and Whole Body Energy Metabolism)
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<p>PPARβ/δ activation prevents obesity through several mechanisms. PPARβ/δ activation reduces pre-adipocyte proliferation and differentiation, attenuates angiotensin II-mediated dysfunctional hypertrophic adipogenesis and inhibits inflammation in adipose tissue. PPARβ/δ ligands reduce the availability of fatty acids to be stored in adipose tissue since these drugs induce fat burn in skeletal muscle by either increasing fatty acid oxidation or switching muscle fibre type towards oxidative metabolism. Blue arrow: increases. Red arrow: decreases.</p> Full article ">Figure 2
<p>Effects of PPARβ/δ activation in dyslipidaemia. PPARβ/δ activation ameliorates atherogenic dyslipidaemia by reducing the amounts of very low-density lipoprotein (VLDL)-triglyceride (TG) and small dense low-density lipoprotein (LDL) particles and increasing the levels of high-density lipoprotein (HDL)-cholesterol. PPARβ/δ ligands reduce VLDL-TG by increasing hepatic fatty acid (FA) oxidation, which decreases the availability of this lipid for TG synthesis and changing the expression of several apoproteins. PPARβ/δ ligands increase HDL-cholesterol levels by elevating the amounts of the main apopoproteins of these lipoproteins (ApoA1 and ApoA2) in the liver and raising the levels of ATP-binding cassette A1 (ABCA1) in macrophages. Reduced LDL-cholesterol levels results from a decrease in cholesterol absorption and an increase in faecal excretion that are mediated by PPARβ/δ activation. Blue arrow: increases. Red arrow: decreases.</p> Full article ">Figure 3
<p>Effects of PPARβ/δ in type 2 diabetes mellitus. This figure depicts the effects of PPARβ/δ ligands in adipose tissue, skeletal muscle, the liver and pancreatic β cells that contribute to the attenuation of type 2 diabetes mellitus. In adipose tissue, PPARβ/δ activation switches macrophage polarization towards the anti-inflammatory M2 phenotype and prevents IL-6-induced insulin resistance by inhibiting STAT3. In skeletal muscle, PPARβ/δ ligands induce FA oxidation, reducing their availability for the synthesis of deleterious complex lipids involved in inflammation and prevent endoplasmic reticulum (ER) stress by activating AMPK. PPARβ/δ activation in hepatocytes blocks the effects of IL-6 by inhibiting the STAT3 pathway through several mechanisms and increasing FGF21 levels. PPARβ/δ activators promote the beneficial effects of GLP-1 in the pancreas and enhance GSIS.ER, endoplasmic reticulum; FA, fatty acid; GLP-1, glucagon-like peptide 1; GSIS, glucose-stimulated insulin secretion; IL-6, interleukin 6; STAT3, signal transducer and activator of transcription 3. Blue arrow: increases. Red arrow: decreases.</p> Full article ">
17 pages, 22730 KiB  
Article
Suppression Effect of Astaxanthin on Osteoclast Formation In Vitro and Bone Loss In Vivo
by Yun-Ho Hwang, Kwang-Jin Kim, Su-Jin Kim, Seul-Ki Mun, Seong-Gyeol Hong, Young-Jin Son and Sung-Tae Yee
Int. J. Mol. Sci. 2018, 19(3), 912; https://doi.org/10.3390/ijms19030912 - 19 Mar 2018
Cited by 43 | Viewed by 7193
Abstract
Osteoporosis is characterized by a reduction of the bone mineral density (BMD) and microarchitectural deterioration of the bone, which lead to bone fragility and susceptibility to fracture. Astaxanthin (AST) has a variety of biological activities, such as a protective effect against asthma or [...] Read more.
Osteoporosis is characterized by a reduction of the bone mineral density (BMD) and microarchitectural deterioration of the bone, which lead to bone fragility and susceptibility to fracture. Astaxanthin (AST) has a variety of biological activities, such as a protective effect against asthma or neuroinflammation, antioxidant effect, and decrease of the osteoclast number in the right mandibles in the periodontitis model. Although treatment with AST is known to have an effect on inflammation, no studies on the effect of AST exposure on bone loss have been performed. Thus, in the present study, we examined the antiosteoporotic effect of AST on bone mass in ovariectomized (OVX) mice and its possible mechanism of action. The administration of AST (5, 10 mg/kg) for 6 weeks suppressed the enhancement of serum calcium, inorganic phosphorus, alkaline phosphatase, total cholesterol, and tartrate-resistant acid phosphatase (TRAP) activity. The bone mineral density (BMD) and bone microarchitecture of the trabecular bone in the tibia and femur were recovered by AST exposure. Moreover, in the in vitro experiment, we demonstrated that AST inhibits osteoclast formation through the expression of the nuclear factor of activated T cells (NFAT) c1, dendritic cell-specific transmembrane protein (DC-STAMP), TRAP, and cathepsin K without any cytotoxic effects on bone marrow-derived macrophages (BMMs). Therefore, we suggest that AST may have therapeutic potential for the treatment of postmenopausal osteoporosis. Full article
(This article belongs to the Section Biochemistry)
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<p>Astaxanthin suppresses osteoclastogenesis. (<b>A</b>) Chemical structure of Astaxanthin; (<b>B</b>) BMMs prepared from bone marrow cells were cultured for 4 days with RANKL (10 ng/mL) and M-CSF (30 ng/mL) in the presence of the indicated concentrations of Astaxanthin or 0.1% DMSO (control vehicle). The cells were fixed in 3.7% formalin, permeabilized in 0.1% Triton X-100, and stained for TRAP, a marker enzyme of osteoclasts; (<b>C</b>) TRAP-positive multinuclear cells (nuclei ≥ 3) were counted as osteoclasts. * <span class="html-italic">p</span> &lt;0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt;0.001; (<b>D</b>) The effect of Astaxanthin on the viability of BMMs was evaluated by CCK-8 assay. In (<b>C</b>, <b>D</b>), <span class="html-italic">n</span> = 3.</p> Full article ">Figure 2
<p>Astaxanthin inhibits the expression of the genes involved in osteoclastogenesis. BMMs were treated with 0.1% DMSO or Astaxanthin (30 μM) and then stimulated with RANKL (10 ng/mL) and M-CSF (30 ng/ml) for the indicated number of days. The expressed mRNA levels of (<b>A</b>) <span class="html-italic">NFATc1</span>, (<b>B</b>) <span class="html-italic">TRAP</span>, (<b>C</b>) <span class="html-italic">DC-STAMP</span>, and (<b>D</b>) <span class="html-italic">cathepsin K</span> were analyzed by real-time PCR compared with the DMSO control. * <span class="html-italic">p</span> &lt;0.05, ** <span class="html-italic">p</span> &lt;0.01, *** <span class="html-italic">p</span> &lt;0.001 (<span class="html-italic">n</span> = 3).</p> Full article ">Figure 3
<p>BMMs were pretreated with 0.1%DMSO or Astaxanthin (30 μM) for 1 h and then stimulated with RANKL (10 ng/mL) and M-CSF (30 ng/mL) for the indicated time. Cell lysates were resolved by SDS-PAGE, and western blotting was performed with anti-NFATc1 and actin antibodies as indicated.</p> Full article ">Figure 4
<p>Experimental protocol for the induction and therapy of osteoporosis along with the treatment scheme.</p> Full article ">Figure 5
<p>Effect of AST on body weight and uterus weight. The (<b>A</b>) body weight and (<b>B</b>) uterus weight measured at 24 h after the last treatment. Each value represents the mean ± SD for <span class="html-italic">n</span> = 5. # <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 SHAM group vs. OVX group. * <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 OVX group vs. E2, AST 5, and AST 10 group.</p> Full article ">Figure 6
<p>Effect of AST on serum biochemical markers. In the control, SHAM-operated mice and OVX mice with or without the administration of AST (5 and 10 mg/kg/day, p.o.) for 6 weeks, the serum (<b>A</b>) calcium, (<b>B</b>) phosphorus, (<b>C</b>) alkaline phosphatase, and (<b>D</b>) total cholesterol were determined by using a diagnostic slide. Each value represents the mean ± SD for <span class="html-italic">n</span> = 5. ## <span class="html-italic">p</span> &lt; 0.01 and ### <span class="html-italic">p</span> &lt; 0.001 SHAM group vs. OVX group. * <span class="html-italic">p</span> &lt; 0.05 and *** <span class="html-italic">p</span> &lt; 0.001 OVX group vs. E2, AST 5, and AST 10 group.</p> Full article ">Figure 7
<p>Effect of AST on serum tartrate-resistant acid phosphatase (TRAP) in the control, SHAM-operated mice and OVX mice with or without the administration of AST (5 and 10 mg/kg/day, p.o.) for 6 weeks. Serum TRAP was measured by ELISA kit. Each value represents the mean ± SD for <span class="html-italic">n</span> = 5. Group numbers (1 = SHAM, 2 = OVX, 3 = AST 5 mg/kg, 4 = 10 mg/kg).</p> Full article ">Figure 8
<p>Effect of AST on trabecular morphometric parameters in proximal tibia of C3H/HeN mice. The mice were treated with the vehicle, AST (5 and 10 mg/kg/day, p.o.) for 6 weeks. (<b>A</b>) The three-dimensional micro-computed tomography images were analyzed by CTvol. (<b>B</b>) Tissue volume (TV), (<b>C</b>) bone volume (BV), (<b>D</b>) bone volume/tissue volume, (<b>E</b>) bone surface, (<b>F</b>) bone surface/tissue volume, (<b>G</b>) trabecular pattern factor, (<b>H</b>) structure model index, (<b>I</b>) trabecular thickness, (<b>J</b>) trabecular number, and (K) trabecular separation as analyzed with micro-CT Skyscan CTAn software. Each value represents the mean ± SD for <span class="html-italic">n</span> = 5. ## <span class="html-italic">p</span> &lt; 0.01 and ### <span class="html-italic">p</span> &lt; 0.001 SHAM group vs. OVX group. * <span class="html-italic">p</span> &lt; 0.05 and *** <span class="html-italic">p</span> &lt; 0.001 OVX group vs. E2, AST 5, and AST 10 group.</p> Full article ">Figure 9
<p>Effect of AST on trabecular morphometric parameters in distal femur of C3H/HeN mice. The mice were treated with the vehicle, AST (5 and 10 mg/kg/day, p.o.) for 6 weeks. (<b>A</b>) The three-dimensional micro-computed tomography images were analyzed by CTvol. (<b>B</b>) Tissue volume (TV), (<b>C</b>) bone volume (BV), (<b>D</b>) bone volume/tissue volume, (<b>E</b>) bone surface, (<b>F</b>) bone surface/tissue volume, (<b>G</b>) trabecular pattern factor, (<b>H</b>) structure model index, (<b>I</b>) trabecular thickness, (<b>J</b>) trabecular number, and (<b>K</b>) trabecular separation as analyzed with micro-CT Skyscan CTAn software. Each value represents the mean ± SD for <span class="html-italic">n</span> = 5. ## <span class="html-italic">p</span> &lt; 0.01 and ### <span class="html-italic">p</span> &lt; 0.001 SHAM group vs. OVX group. * <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 OVX group vs. E2, AST 5, and AST 10 group.</p> Full article ">Figure 10
<p>Effect of AST on bone mineral density (BMD) of trabecular in distal femur and proximal tibia of C3H/HeN mice in the control, SHAM-operated mice and OVX mice with or without the administration of AST (5 and 10 mg/kg/day, p.o.) for 6 weeks. (<b>A</b>) The femur BMD and (<b>B</b>) tibia BMD were analyzed by CTAn software. ### <span class="html-italic">p</span> &lt; 0.001 SHAM group vs. OVX group. * <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 OVX group vs. E2, AST 5, and AST 10 group.</p> Full article ">Figure 11
<p>Effect of AST on bone tissue of trabecular in distal femur of C3H/HeN mice. The mice were treated with the vehicle, AST (5 and 10 mg/kg/day, p.o.), for 6 weeks. (<b>A</b>) Histological analysis of distal femur with hematoxylin and eosin (H&amp;E) and tartrate-resistant acid phosphatase (TRAP) staining; (<b>B</b>) Trabecular and (<b>C</b>) TRAP positive cells in femur were analyzed by Image J program. Each value represents the mean ± SD for <span class="html-italic">n</span> = 3. ### <span class="html-italic">p</span> &lt; 0.001 SHAM group vs. OVX group. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 OVX group vs. E2, AST 5, and AST 10 group.</p> Full article ">Figure 11 Cont.
<p>Effect of AST on bone tissue of trabecular in distal femur of C3H/HeN mice. The mice were treated with the vehicle, AST (5 and 10 mg/kg/day, p.o.), for 6 weeks. (<b>A</b>) Histological analysis of distal femur with hematoxylin and eosin (H&amp;E) and tartrate-resistant acid phosphatase (TRAP) staining; (<b>B</b>) Trabecular and (<b>C</b>) TRAP positive cells in femur were analyzed by Image J program. Each value represents the mean ± SD for <span class="html-italic">n</span> = 3. ### <span class="html-italic">p</span> &lt; 0.001 SHAM group vs. OVX group. ** <span class="html-italic">p</span> &lt; 0.01 and *** <span class="html-italic">p</span> &lt; 0.001 OVX group vs. E2, AST 5, and AST 10 group.</p> Full article ">
11 pages, 289 KiB  
Review
Genetic and Epigenetic Regulation in Nonalcoholic Fatty Liver Disease (NAFLD)
by José A Del Campo, Rocío Gallego-Durán, Paloma Gallego and Lourdes Grande
Int. J. Mol. Sci. 2018, 19(3), 911; https://doi.org/10.3390/ijms19030911 - 19 Mar 2018
Cited by 113 | Viewed by 9022
Abstract
Genetics and epigenetics play a key role in the development of several diseases, including nonalcoholic fatty liver disease (NAFLD). Family studies demonstrate that first degree relatives of patients with NAFLD are at a much higher risk of the disease than the general population. [...] Read more.
Genetics and epigenetics play a key role in the development of several diseases, including nonalcoholic fatty liver disease (NAFLD). Family studies demonstrate that first degree relatives of patients with NAFLD are at a much higher risk of the disease than the general population. The development of the Genome Wide Association Study (GWAS) technology has allowed the identification of numerous genetic polymorphisms involved in the evolution of diseases (e.g., PNPLA3, MBOAT7). On the other hand, epigenetic changes interact with inherited risk factors to determine an individual’s susceptibility to NAFLD. Modifications of the histones amino-terminal ends are key factors in the maintenance of chromatin structure and gene expression (cAMP-responsive element binding protein H (CREBH) or SIRT1). Activation of SIRT1 showed potential against the physiological mechanisms related to NAFLD. Abnormal DNA methylation represents a starting point for cancer development in NAFLD patients. Besides, the evaluation of circulating miRNA profiles represents a promising approach to assess and non-invasively monitor liver disease severity. To date, there is no approved pharmacologic therapy for NAFLD and the current treatment remains weight loss with lifestyle modification and exercise. In this review, the status of research into relevant genetic and epigenetic modifiers of NAFLD progression will be discussed. Full article
(This article belongs to the Special Issue Transcriptional Regulation in Lipid Metabolism)
21 pages, 2066 KiB  
Article
In-Silico Integration Approach to Identify a Key miRNA Regulating a Gene Network in Aggressive Prostate Cancer
by Claudia Cava, Gloria Bertoli, Antonio Colaprico, Gianluca Bontempi, Giancarlo Mauri and Isabella Castiglioni
Int. J. Mol. Sci. 2018, 19(3), 910; https://doi.org/10.3390/ijms19030910 - 19 Mar 2018
Cited by 11 | Viewed by 6165
Abstract
Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have [...] Read more.
Like other cancer diseases, prostate cancer (PC) is caused by the accumulation of genetic alterations in the cells that drives malignant growth. These alterations are revealed by gene profiling and copy number alteration (CNA) analysis. Moreover, recent evidence suggests that also microRNAs have an important role in PC development. Despite efforts to profile PC, the alterations (gene, CNA, and miRNA) and biological processes that correlate with disease development and progression remain partially elusive. Many gene signatures proposed as diagnostic or prognostic tools in cancer poorly overlap. The identification of co-expressed genes, that are functionally related, can identify a core network of genes associated with PC with a better reproducibility. By combining different approaches, including the integration of mRNA expression profiles, CNAs, and miRNA expression levels, we identified a gene signature of four genes overlapping with other published gene signatures and able to distinguish, in silico, high Gleason-scored PC from normal human tissue, which was further enriched to 19 genes by gene co-expression analysis. From the analysis of miRNAs possibly regulating this network, we found that hsa-miR-153 was highly connected to the genes in the network. Our results identify a four-gene signature with diagnostic and prognostic value in PC and suggest an interesting gene network that could play a key regulatory role in PC development and progression. Furthermore, hsa-miR-153, controlling this network, could be a potential biomarker for theranostics in high Gleason-scored PC. Full article
(This article belongs to the Special Issue The Role of MicroRNAs in Human Diseases)
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<p>Venn diagram for the integrative approaches.</p> Full article ">Figure 2
<p>Co-expression gene network of core genes from four gene signatures overlapping with published gene signatures (* four gene signatures).</p> Full article ">Figure 3
<p>Gene co-expression network and putative miRNA-regulated targets.</p> Full article ">Figure 4
<p>Area Under Curve (AUC) values of six different approaches: green bar (I method with 3069 genes), red bar (II method with 38 genes), blue bar (III method with 21 genes), gray bar (IV method with 4 genes), yellow bar (V method with 19 genes), and pink bar (VI method with <span class="html-italic">hsa-miR-153</span>).</p> Full article ">Figure 5
<p>Classification for single gene from the IV approach (four gene signatures): blue bar (<span class="html-italic">CLU</span> gene), red bar (<span class="html-italic">KLF5</span>), gray bar (<span class="html-italic">EPHA3</span>), and yellow bar (<span class="html-italic">TRIB1</span>).</p> Full article ">Figure 6
<p>AUC values among three different approaches with dataset TCGA, considering also a subset of random genes. The light green box represents AUC with 3069 random genes, and the dark green box AUC with 3069 genes according to our approach. The orange box represents AUC with 38 random genes, and the red box AUC with 38 genes according to our approach. The light blue box represents AUC with 21 random genes, and the dark blue box AUC with 21 genes according to our approach.</p> Full article ">Figure 7
<p>AUC values of six different approaches with a validation dataset GEO (GSE79021 for gene expression, and GSE21036 for miRNA): green bar (I method with 3069 genes), red bar (II method with 38 genes), blue bar (III method with 21 genes), gray bar (IV method with 4 genes), yellow bar (V method with 19 genes), and pink bar (VI method with <span class="html-italic">hsa-miR-153</span>).</p> Full article ">Figure 8
<p>Workflow of the proposed analysis.</p> Full article ">
12 pages, 712 KiB  
Review
Amino Acid Metabolism and Transport Mechanisms as Potential Antifungal Targets
by Matthew W. McCarthy and Thomas J. Walsh
Int. J. Mol. Sci. 2018, 19(3), 909; https://doi.org/10.3390/ijms19030909 - 19 Mar 2018
Cited by 30 | Viewed by 6038
Abstract
Discovering new drugs for treatment of invasive fungal infections is an enduring challenge. There are only three major classes of antifungal agents, and no new class has been introduced into clinical practice in more than a decade. However, recent advances in our understanding [...] Read more.
Discovering new drugs for treatment of invasive fungal infections is an enduring challenge. There are only three major classes of antifungal agents, and no new class has been introduced into clinical practice in more than a decade. However, recent advances in our understanding of the fungal life cycle, functional genomics, proteomics, and gene mapping have enabled the identification of new drug targets to treat these potentially deadly infections. In this paper, we examine amino acid transport mechanisms and metabolism as potential drug targets to treat invasive fungal infections, including pathogenic yeasts, such as species of Candida and Cryptococcus, as well as molds, such as Aspergillus fumigatus. We also explore the mechanisms by which amino acids may be exploited to identify novel drug targets and review potential hurdles to bringing this approach into clinical practice. Full article
(This article belongs to the Special Issue Amino Acids Transport and Metabolism)
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<p>Comparative structures of proline, cispentacin, and icofungipen.</p> Full article ">Figure 2
<p>Comparative structures of <span class="html-italic">S</span>-adenosylmethionine and sinefungin.</p> Full article ">
13 pages, 8447 KiB  
Article
HER2-Targeted Multifunctional Silica Nanoparticles Specifically Enhance the Radiosensitivity of HER2-Overexpressing Breast Cancer Cells
by Haruka Yamaguchi, Kazuhide Hayama, Ichiro Sasagawa, Yasuo Okada, Tomoyuki Kawase, Norio Tsubokawa and Makoto Tsuchimochi
Int. J. Mol. Sci. 2018, 19(3), 908; https://doi.org/10.3390/ijms19030908 - 19 Mar 2018
Cited by 24 | Viewed by 6000
Abstract
We investigated the effects of targeted functionalized silica nanoparticles on the radiosensitivity of cancer cells. Better control of the local concentration of silica nanoparticles may facilitate their use as an adjuvant in conjunction with ionizing radiation to target cancer cells while preventing damage [...] Read more.
We investigated the effects of targeted functionalized silica nanoparticles on the radiosensitivity of cancer cells. Better control of the local concentration of silica nanoparticles may facilitate their use as an adjuvant in conjunction with ionizing radiation to target cancer cells while preventing damage to normal cells. Hyperbranched polyamidoamine (PAMAM) was grafted onto the surface of amorphous silica nanoparticles to functionalize them. The PAMAM-coated silica nanoparticles (PCSNs) were then conjugated with fluorescent dyes. Anti-HER2 antibodies were covalently attached to the labeled PCSNs. The HER2-overexpressing SK-BR3 breast cancer cell line was incubated in medium containing the PCSN probes. After incubation; the cells were exposed to X-ray radiation. Cells were counted in all samples using cell proliferation assays; and apoptotic cells were detected. The cell survival results showed that the combination of the targeted PCSN probes and radiation reduced the survival rate of SK-BR3 cells to a greater extent than when either PCSN probes, PCSNs or radiation were applied individually. The results also showed an increase in apoptosis in the SK-BR3 cells that internalized the PCSN probes and were then irradiated. Based on these data, PCSN probes act as specific radiosensitizing agents for HER2-overexpressing cells. Full article
(This article belongs to the Special Issue Bioactive Nanoparticles)
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<p>The size of the PAMAM-coated silica nanoparticles, PCSNs prepared was evaluated using a transmission electron microscope (TEM). The PCSN size was approximately 40 nm (between 35 nm and 46 nm).</p> Full article ">Figure 2
<p>(<b>a</b>) Alexa 488 fluorescent dye was run on thin-layer chromatography (TLC) plates, each 2.5 cm × 7.5 cm; (<b>b</b>) Conversely, the Alexa 488 of PCSN probes remained at the initial spot.</p> Full article ">Figure 3
<p>(<b>a</b>) Confocal laser scanning microscopy (LSM) image showing strong Alexa 488 fluorescence intensity on the surface of SK-BR3 cells. PCSN probes were bound to the surface of SK-BR3 cells within 4 h. (<b>b</b>) LSM image showing strong fluorescence signals inside the SKBR3 cells. PCSN probes were internalized into the cytoplasm during a 24-h incubation in medium containing targeted PCSN probes (1200 ppm). (<b>c</b>) PCSN probes remained inside the SK-BR3 cells after 48 h. (<b>d</b>) For three-dimensional analysis of the SK-BR3 cells, images were collected at 0.41-µm intervals with a 488-nm laser to create a Z stack. The images show internalized PCSN probes inside an SK-BR3 cell.</p> Full article ">Figure 4
<p>Transmission electron microscopy (TEM) images showing nanoparticles (PCSNs, yellow arrows), confirming that the probes are inside the cells. Some of the silica nanoparticles are found within lysosomes.</p> Full article ">Figure 5
<p>Images of a nucleus (DAPI, 4′,6-diamidino-2-phenylindole), lysosomes (Lyso Tracker Red) and probes (Alexa488). The probe and lysosomal signals overlap. Scale bars represent 10 µm.</p> Full article ">Figure 6
<p>Cell viability assays show that the medium containing 2400 ppm PCSNs resulted in the lowest absorbance. The difference between 2400 ppm PCSNs and the other samples was statistically significant. Thus, a PCSN concentration of 2400 ppm damages SK-BR3 cells. The y-axis represents the absorbance unit (450 nm). n.s., not significant.</p> Full article ">Figure 7
<p>The combination of PCSN probes (PCSN concentration: 1200 ppm) and 8-Gy irradiation resulted in the lowest absorbance 24 h after irradiation. The numbers (0, 6, 600, 1200) indicate the concentration of PCSN (ppm). The <span class="html-italic">y</span>-axis represents the absorbance unit (450 nm).</p> Full article ">Figure 8
<p>Day 1: passage the SK-BR3 cells, Day 2: add PCSN probes or silica to the cell medium, Day 3: irradiate the cells (8 Gy). In subsequent cell viability assays, the combination of 1200 ppm PCSN probes and irradiation for 24 h at 8 Gy resulted in reduced SK-BR3 cell absorbance. The <span class="html-italic">y</span>-axis represents the absorbance unit (450 nm). Radiation dose: 0 Gy or 8 Gy; Cell: SK-BR3 cell; Probe: containing PCSN probe; Si: containing PCSNs.</p> Full article ">Figure 9
<p>In the Terminal deoxynucleotidyl transferase (dUTP)-mediated nick end-labeling (TUNEL) assays, the three samples irradiated with 8 Gy showed stronger fluorescence intensity than the non-irradiated samples. The combination of PCSN probes and 8-Gy irradiation produced the strongest fluorescence intensity. Scale bars represent 100 µm. Cell: SK-BR3 cells alone; Si: cells in medium containing 1200 ppm PCSNs; Probe: cells in medium containing 1200 ppm PCSN probes.</p> Full article ">Figure 10
<p>The TUNEL assay shows the highest fluorescence intensity for cells that underwent combination therapy compared to that of other samples. Combination therapy thus induced the greatest extent of apoptotic cell death. Control: SK-BR3 cells; Si: cells in medium containing 1200 ppm PCSNs; Probe: cells in medium containing 1200 ppm PCSN probes.</p> Full article ">Figure 11
<p>The highest fluorescence intensity resulted from the combination of PCSN probes and 8-Gy irradiation. There was a significant difference between “probe” and the other samples, showing that combination therapy caused the greatest extent of apoptotic cell death. * <span class="html-italic">p</span> &lt; 0.1. Control: SK-BR3 cells, silica: cells in medium containing 1200 ppm PCSNs, probe: cells in medium containing 1200 ppm PCSN probes.</p> Full article ">Figure 12
<p>Possible mechanism for targeted radiosensitization by PCSN probes. Internalized silica nanoparticles may disturb the permeability of the lysosomal membrane in the targeted cell (HER2 positive), and the resulting lysosomal destabilization leads to cell destruction and autophagy. The major effect of ionizing radiation on the cell is direct damage to the DNA, and possible additional effect can also damage lysosomal membrane permeabilization, thereby activating cell death. The combination of PCSN probes and radiation may thus cause cell growth inhibition and cell death through lysosomal membrane destabilization. Anti-HER2 antibody on PCSN probes can also inhibit the MAPK and PI3K pathways, leading to the suppression of cell growth and proliferation. Yellow arrow signals: ionized radiation; mAb: Anti-HER2 antibody; Orange star-like dots around silica nanoparticle: fluorophore; Blue dots in the cell: degraded silica nanoparticle.</p> Full article ">Figure 13
<p>PCSN: Hyperbranched polyamidoamine (PAMAM) is grafted onto the surface of an amorphous silica nanoparticle to functionalize the particle. PCSN probe: PCSN is conjugated with a fluorescent dye, Alexa Fluor 488, and anti-HER2 antibodies are covalently attached to the labeled PCSN.</p> Full article ">
17 pages, 896 KiB  
Review
Amino Acid Transporters and Glutamine Metabolism in Breast Cancer
by Yoon Jin Cha, Eun-Sol Kim and Ja Seung Koo
Int. J. Mol. Sci. 2018, 19(3), 907; https://doi.org/10.3390/ijms19030907 - 19 Mar 2018
Cited by 109 | Viewed by 16265
Abstract
Amino acid transporters are membrane transport proteins, most of which are members of the solute carrier families. Amino acids are essential for the survival of all types of cells, including tumor cells, which have an increased demand for nutrients to facilitate proliferation and [...] Read more.
Amino acid transporters are membrane transport proteins, most of which are members of the solute carrier families. Amino acids are essential for the survival of all types of cells, including tumor cells, which have an increased demand for nutrients to facilitate proliferation and cancer progression. Breast cancer is the most common malignancy in women worldwide and is still associated with high mortality rates, despite improved treatment strategies. Recent studies have demonstrated that the amino acid metabolic pathway is altered in breast cancer and that amino acid transporters affect tumor growth and progression. In breast cancer, glutamine is one of the key nutrients, and glutamine metabolism is closely related to the amino acid transporters. In this review, we focus on amino acid transporters and their roles in breast cancer. We also highlight the different subsets of upregulated amino acid transporters in breast cancer and discuss their potential applications as treatment targets, cancer imaging tracers, and drug delivery components. Glutamine metabolism as well as its regulation and therapeutic implication in breast cancer are also discussed. Full article
(This article belongs to the Special Issue Amino Acids Transport and Metabolism)
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<p>Important amino acid transporters in breast cancer. SLC1A5, SLC6A14, SLC7A5, and SLC7A11 are upregulated in breast cancer. SLC1A5, SLC7A5, and SLC7A11 exhibit functional coupling and enhance the proliferation of cancer cells. SLC7A11-mediated intracellular cysteine is used for glutathione synthesis, which results in reduced oxidative stress. c-Myc acts as a positive regulator for SLC1A5, SLC6A14, SLC7A5, and SLC7A11. STAT5: signal transducer and activator of transcription 5; ER: estrogen receptor; GLS: glutaminase; SERM: selective estrogen receptor modulator; mTOR: mammalian target of rapamycin; HER-2: human epidermal growth factor receptor 2; TNBC: triple-negative breast cancer.</p> Full article ">
13 pages, 991 KiB  
Review
CRISPR/Cas9 Technology as an Emerging Tool for Targeting Amyotrophic Lateral Sclerosis (ALS)
by Ewa Kruminis-Kaszkiel, Judyta Juranek, Wojciech Maksymowicz and Joanna Wojtkiewicz
Int. J. Mol. Sci. 2018, 19(3), 906; https://doi.org/10.3390/ijms19030906 - 19 Mar 2018
Cited by 20 | Viewed by 10050
Abstract
The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein-9 nuclease (Cas9) is a genome editing tool that has recently caught enormous attention due to its novelty, feasibility, and affordability. This system naturally functions as a defense mechanism in bacteria and has been repurposed [...] Read more.
The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein-9 nuclease (Cas9) is a genome editing tool that has recently caught enormous attention due to its novelty, feasibility, and affordability. This system naturally functions as a defense mechanism in bacteria and has been repurposed as an RNA-guided DNA editing tool. Unlike zinc-finger nucleases (ZFNs) and transcription activator-like effector nucleases (TALENs), CRISPR/Cas9 takes advantage of an RNA-guided DNA endonuclease enzyme, Cas9, which is able to generate double-strand breaks (DSBs) at specific genomic locations. It triggers cellular endogenous DNA repair pathways, contributing to the generation of desired modifications in the genome. The ability of the system to precisely disrupt DNA sequences has opened up new avenues in our understanding of amyotrophic lateral sclerosis (ALS) pathogenesis and the development of new therapeutic approaches. In this review, we discuss the current knowledge of the principles and limitations of the CRISPR/Cas9 system, as well as strategies to improve these limitations. Furthermore, we summarize novel approaches of engaging the CRISPR/Cas9 system in establishing an adequate model of neurodegenerative disease and in the treatment of SOD1-linked forms of ALS. We also highlight possible applications of this system in the therapy of ALS, both the inherited type as well as ALS of sporadic origin. Full article
(This article belongs to the Special Issue Rare Diseases: Molecular Mechanisms and Therapeutic Strategies)
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<p>The three steps of CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated protein-9 nuclease) immunity.</p> Full article ">Figure 2
<p>CRISPR/Cas9 mediated cleavage of genomic DNA and two major repair pathways.</p> Full article ">
22 pages, 1690 KiB  
Review
Galectins as Molecular Targets for Therapeutic Intervention
by Ruud P. M. Dings, Michelle C. Miller, Robert J. Griffin and Kevin H. Mayo
Int. J. Mol. Sci. 2018, 19(3), 905; https://doi.org/10.3390/ijms19030905 - 19 Mar 2018
Cited by 89 | Viewed by 9924
Abstract
Galectins are a family of small, highly conserved, molecular effectors that mediate various biological processes, including chemotaxis and angiogenesis, and that function by interacting with various cell surface glycoconjugates, usually targeting β-galactoside epitopes. Because of their significant involvement in various biological functions and [...] Read more.
Galectins are a family of small, highly conserved, molecular effectors that mediate various biological processes, including chemotaxis and angiogenesis, and that function by interacting with various cell surface glycoconjugates, usually targeting β-galactoside epitopes. Because of their significant involvement in various biological functions and pathologies, galectins have become a focus of therapeutic discovery for clinical intervention against cancer, among other pathological disorders. In this review, we focus on understanding galectin structure-function relationships, their mechanisms of action on the molecular level, and targeting them for therapeutic intervention against cancer. Full article
(This article belongs to the Special Issue Galectins in Cancer and Translational Medicine)
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<p>Galectin oligomer states. (<b>A</b>,<b>B</b>) Gal-3 carbohydrate recognition domain (CRD) (Protein Data Bank (PDB) access code 1A3K) as a monomer illustrating the β-sandwich fold common to all galectins. The 11 β-strands found within the CRD β-sandwich are labeled β1 to β11 in <b>A</b>, and the S- and F-faces of the CRD are identified in <b>B</b>. (<b>C</b>,<b>D</b>) Two prototype galectin dimers are shown. The CRD of the Gal-1 “terminal” dimer (PDB access code 1GZW) is shown in <b>C</b>, and the “symmetric sandwich” dimer of human Gal-7 (PDB access code 1BKZ) is shown in <b>D</b>. The carbohydrate binding sites in all structures are indicated by the lactose molecules shown in blue with a ball-and-stick structure.</p> Full article ">Figure 2
<p>Galectins are involved in multiple processes of cancer initiation and development. A diversity of galectins is associated with key aspects of carcinogenesis, including apoptosis, adhesion and migration, cell transformation (EMT), invasion and metastasis, immune escape, and angiogenesis. Their tentative roles can be pro- and/or anti-tumorigenic, as indicated by green arrows up and red arrows down, respectively.</p> Full article ">Figure 3
<p>Involvement of galectins in organ-specific carcinogenesis within different physiological systems. Various elevated galectin expression is associated with tumor progression (green arrow up). In some instances, low galectin expression is correlated with the generation of neoplastic tissue (red arrow down). Additionally, galectins can have potential protective roles (black shield) during carcinogenesis.</p> Full article ">
19 pages, 869 KiB  
Review
Profiling Prostate Cancer Therapeutic Resistance
by Cameron A. Wade and Natasha Kyprianou
Int. J. Mol. Sci. 2018, 19(3), 904; https://doi.org/10.3390/ijms19030904 - 19 Mar 2018
Cited by 98 | Viewed by 11298
Abstract
The major challenge in the treatment of patients with advanced lethal prostate cancer is therapeutic resistance to androgen-deprivation therapy (ADT) and chemotherapy. Overriding this resistance requires understanding of the driving mechanisms of the tumor microenvironment, not just the androgen receptor (AR)-signaling cascade, that [...] Read more.
The major challenge in the treatment of patients with advanced lethal prostate cancer is therapeutic resistance to androgen-deprivation therapy (ADT) and chemotherapy. Overriding this resistance requires understanding of the driving mechanisms of the tumor microenvironment, not just the androgen receptor (AR)-signaling cascade, that facilitate therapeutic resistance in order to identify new drug targets. The tumor microenvironment enables key signaling pathways promoting cancer cell survival and invasion via resistance to anoikis. In particular, the process of epithelial-mesenchymal-transition (EMT), directed by transforming growth factor-β (TGF-β), confers stem cell properties and acquisition of a migratory and invasive phenotype via resistance to anoikis. Our lead agent DZ-50 may have a potentially high efficacy in advanced metastatic castration resistant prostate cancer (mCRPC) by eliciting an anoikis-driven therapeutic response. The plasticity of differentiated prostate tumor gland epithelium allows cells to de-differentiate into mesenchymal cells via EMT and re-differentiate via reversal to mesenchymal epithelial transition (MET) during tumor progression. A characteristic feature of EMT landscape is loss of E-cadherin, causing adherens junction breakdown, which circumvents anoikis, promoting metastasis and chemoresistance. The targetable interactions between androgens/AR and TGF-β signaling are being pursued towards optimized therapeutic regimens for the treatment of mCRPC. In this review, we discuss the recent evidence on targeting the EMT-MET dynamic interconversions to overcome therapeutic resistance in patients with recurrent therapeutically resistant prostate cancer. Exploitation of the phenotypic landscape and metabolic changes that characterize the prostate tumor microenvironment in advanced prostate cancer and consequential impact in conferring treatment resistance are also considered in the context of biomarker discovery. Full article
(This article belongs to the Special Issue Molecular Research on Urology)
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<p>Signaling pathways contributing to therapeutic resistance in prostate cancer and their targetable interactions via EMT to MET interconversions. (A) First and second line antiandrogens (abiraterone and enzalutamide) target the AR signaling cascade by reducing testosterone production or inhibiting the binding site of AR and subsequent translocation to the nucleus, respectively. (B) Mutations in AR signaling promote transcriptional activation despite ADT. (C) TGF-β bi-functionally affects cell growth and differentiation through intracellular SMAD and non-SMAD signaling including MAP-kinases, loss of E-cadherin, and consequential changes in cell polarity. (D) Distinct cell types such as myofibroblasts, CAFs, neuroendocrine (NE) cells, and MDSCs (Myeloid-derived suppressor cells) within the microenvironment may navigate therapeutic resistance to antiandrogens and taxane chemotherapy by engaging ECM components, growth factors such as TGF-β, VEGF, IGF, mitotic promoters, and immune suppression. (E) Loss and gain of E-cadherin serves as a causative factor of cell polarity and biomarker of EMT, respectively, under the transcriptional repression of <span class="html-italic">SNAI</span>, <span class="html-italic">ZEB1</span>, and Twist-related protein (<span class="html-italic">TWIST</span>) (nuclear transcription factors). Color code: Orange/yellow: normal cellular signaling, red: promotors of therapeutic resistance, blue: existing or experimental therapies for prostate cancer.</p> Full article ">
13 pages, 4488 KiB  
Article
Hydroquinone Exhibits In Vitro and In Vivo Anti-Cancer Activity in Cancer Cells and Mice
by Se Eun Byeon, Young-Su Yi, Jongsung Lee, Woo Seok Yang, Ji Hye Kim, Jooyoung Kim, Suntaek Hong, Jong-Hoon Kim and Jae Youl Cho
Int. J. Mol. Sci. 2018, 19(3), 903; https://doi.org/10.3390/ijms19030903 - 19 Mar 2018
Cited by 19 | Viewed by 6085
Abstract
Hydroquinone (HQ, 1,4-benzenediol) is a hydroxylated benzene metabolite with various biological activities, including anti-oxidative, neuroprotective, immunomodulatory, and anti-inflammatory functions. However, the anti-cancer activity of HQ is not well understood. In this study, the in vitro and in vivo anti-cancer activity of HQ was [...] Read more.
Hydroquinone (HQ, 1,4-benzenediol) is a hydroxylated benzene metabolite with various biological activities, including anti-oxidative, neuroprotective, immunomodulatory, and anti-inflammatory functions. However, the anti-cancer activity of HQ is not well understood. In this study, the in vitro and in vivo anti-cancer activity of HQ was investigated in various cancer cells and tumor-bearing mouse models. HQ significantly induced the death of A431, SYF, B16F10, and MDA-MB-231 cells and also showed a synergistic effect on A431 cell death with other anti-cancer agents, such as adenosine-2′,3′-dialdehyde and buthionine sulfoximine. In addition, HQ suppressed angiogenesis in fertilized chicken embryos. Moreover, HQ prevented lung metastasis of melanoma cells in mice in a dose-dependent manner without toxicity and adverse effects. HQ (10 mg/kg) also suppressed the generation of colon and reduced the thickness of colon tissues in azoxymethane/dextran sodium sulfate-injected mice. This study strongly suggests that HQ possesses in vitro and in vivo anti-cancer activity and provides evidence that HQ could be developed as an effective and safe anti-cancer drug. Full article
(This article belongs to the Section Molecular Toxicology)
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<p>Effect of HQ on the proliferation of A431 and SYF cells. (<b>A</b>) Chemical structures of HQ and BQ. (<b>B</b>–<b>G</b>) A431 cells (1 × 10<sup>6</sup> cells/mL) were treated with the indicated doses of either HQ or BQ for (<b>B</b>) 24 h, (<b>C</b>) 48 h, and (<b>D</b>) 72 h. SYF cells (1 × 10<sup>6</sup> cells/mL) were treated with the indicated doses of either HQ or BQ for (<b>E</b>) 24 h, (<b>F</b>) 48 h, and (<b>G</b>) 72 h. Cell viability was determined via MTT assay. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to normal.</p> Full article ">Figure 1 Cont.
<p>Effect of HQ on the proliferation of A431 and SYF cells. (<b>A</b>) Chemical structures of HQ and BQ. (<b>B</b>–<b>G</b>) A431 cells (1 × 10<sup>6</sup> cells/mL) were treated with the indicated doses of either HQ or BQ for (<b>B</b>) 24 h, (<b>C</b>) 48 h, and (<b>D</b>) 72 h. SYF cells (1 × 10<sup>6</sup> cells/mL) were treated with the indicated doses of either HQ or BQ for (<b>E</b>) 24 h, (<b>F</b>) 48 h, and (<b>G</b>) 72 h. Cell viability was determined via MTT assay. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to normal.</p> Full article ">Figure 2
<p>Effect of HQ on the morphological change of B16F10 and MDA-MB-231 cells (<b>A</b>,<b>B</b>) B16F10 cells and MDA-MB-231 cells were treated with either vehicle or HQ (50 μM) for 48 h, and cell morphologies were photographed.</p> Full article ">Figure 3
<p><span class="html-italic">S</span>ynergistic effect of HQ on the proliferation of A431 cells under AdOx- or BSO-treated conditions. (<b>A</b>) A431 cells were treated with HQ (50 μM) and AdOx (200 μM) for 24 h, and cell viability was determined via MTT assay. +1 h, HQ treatment 1 h after AdOx treatment; 0 h, HQ and AdOx treatment at the same time; and −1 h, HQ treatment 1 h before AdOx treatment. (<b>B</b>) A431 cells were treated with the indicated doses of HQ and BSO for 24 h, and cell viability was determined via MTT assay. n.s., not significant; ** <span class="html-italic">p</span> &lt; 0.01 compared to the normal or control.</p> Full article ">Figure 4
<p>Effect of HQ on the blood vessel generation. (<b>A</b>,<b>B</b>) Fertilized chicken eggs were treated with either vehicle, RA, or the indicated doses of HQ (circle areas) at 37 °C for 3 days, and the vasculatures in the fertilized chicken eggs were photographed (<b>A</b>). Numbers of vessels at drug-treated area were counted by a counter (<b>B</b>). ** <span class="html-italic">p</span> &lt; 0.01 compared to the vehicle control.</p> Full article ">Figure 5
<p>Effect of HQ on the lung metastasis of B16F10 melanoma. (<b>A</b>) Schematic diagram of in vivo lung metastasis model. (<b>B</b>) The body weight of B16F10 melanoma lung metastasis mice treated with either vehicle or the indicated doses of HQ was measured every day for 18 days. (<b>C</b>) B16F10 melanoma lung metastasis mice treated with either vehicle or the indicated doses of HQ were euthanized at day 19. After euthanasia, the lungs of the mice were excised and the total number of melanoma spots in the lungs of each group was counted and plotted. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to the vehicle control.</p> Full article ">Figure 5 Cont.
<p>Effect of HQ on the lung metastasis of B16F10 melanoma. (<b>A</b>) Schematic diagram of in vivo lung metastasis model. (<b>B</b>) The body weight of B16F10 melanoma lung metastasis mice treated with either vehicle or the indicated doses of HQ was measured every day for 18 days. (<b>C</b>) B16F10 melanoma lung metastasis mice treated with either vehicle or the indicated doses of HQ were euthanized at day 19. After euthanasia, the lungs of the mice were excised and the total number of melanoma spots in the lungs of each group was counted and plotted. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 compared to the vehicle control.</p> Full article ">Figure 6
<p>Effect of HQ on the generation of AOM/DSS-induced colon cancer in mice. (<b>A</b>) Schematic diagram of in vivo colitis-associated colon cancer model. (<b>B</b>) AOM/DSS-induced colon cancer mice were treated with either vehicle or HQ (10 mg/kg) twice a week for 4 weeks. After euthanasia, the colons excised from AOM/DSS-induced colon cancer mice were photographed and compared with that from normal mice treated with vehicle. (<b>C</b>) The total number of tumors generated in the colons of the mice were counted and plotted. (<b>D</b>) The three parts of the colons excised from these mice were stained with hematoxylin and eosin. dn, distal colon; m, middle colon; up, proximal colon. * <span class="html-italic">p</span> &lt; 0.05 compared to the control.</p> Full article ">Figure 6 Cont.
<p>Effect of HQ on the generation of AOM/DSS-induced colon cancer in mice. (<b>A</b>) Schematic diagram of in vivo colitis-associated colon cancer model. (<b>B</b>) AOM/DSS-induced colon cancer mice were treated with either vehicle or HQ (10 mg/kg) twice a week for 4 weeks. After euthanasia, the colons excised from AOM/DSS-induced colon cancer mice were photographed and compared with that from normal mice treated with vehicle. (<b>C</b>) The total number of tumors generated in the colons of the mice were counted and plotted. (<b>D</b>) The three parts of the colons excised from these mice were stained with hematoxylin and eosin. dn, distal colon; m, middle colon; up, proximal colon. * <span class="html-italic">p</span> &lt; 0.05 compared to the control.</p> Full article ">Figure 7
<p>Putative inhibitory pathway of HQ-mediated anti-cancer activity. ↑ (ateneo blue): stimulation; ↓ (blue): inhibition; T (red): suppression of target biological responses.</p> Full article ">
16 pages, 4040 KiB  
Article
Agnoprotein Is an Essential Egress Factor during BK Polyomavirus Infection
by Margarita-Maria Panou, Emma L. Prescott, Daniel L. Hurdiss, Gemma Swinscoe, Michael Hollinshead, Laura G. Caller, Ethan L. Morgan, Louisa Carlisle, Marietta Müller, Michelle Antoni, David Kealy, Neil A. Ranson, Colin M. Crump and Andrew Macdonald
Int. J. Mol. Sci. 2018, 19(3), 902; https://doi.org/10.3390/ijms19030902 - 19 Mar 2018
Cited by 23 | Viewed by 6728
Abstract
BK polyomavirus (BKPyV; hereafter referred to as BK) causes a lifelong chronic infection and is associated with debilitating disease in kidney transplant recipients. Despite its importance, aspects of the virus life cycle remain poorly understood. In addition to the structural proteins, the late [...] Read more.
BK polyomavirus (BKPyV; hereafter referred to as BK) causes a lifelong chronic infection and is associated with debilitating disease in kidney transplant recipients. Despite its importance, aspects of the virus life cycle remain poorly understood. In addition to the structural proteins, the late region of the BK genome encodes for an auxiliary protein called agnoprotein. Studies on other polyomavirus agnoproteins have suggested that the protein may contribute to virion infectivity. Here, we demonstrate an essential role for agnoprotein in BK virus release. Viruses lacking agnoprotein fail to release from host cells and do not propagate to wild-type levels. Despite this, agnoprotein is not essential for virion infectivity or morphogenesis. Instead, agnoprotein expression correlates with nuclear egress of BK virions. We demonstrate that the agnoprotein binding partner α-soluble N-ethylmaleimide sensitive fusion (NSF) attachment protein (α-SNAP) is necessary for BK virion release, and siRNA knockdown of α-SNAP prevents nuclear release of wild-type BK virions. These data highlight a novel role for agnoprotein and begin to reveal the mechanism by which polyomaviruses leave an infected cell. Full article
(This article belongs to the Special Issue Human Polyomaviruses and Papillomaviruses)
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Figure 1

Figure 1
<p>Loss of agnoprotein increases BK gene expression. (<b>A</b>) Schematic illustration of the BK Dunlop genome including the agnoprotein sequence mutated to generate the ΔAgno virus. Agnoprotein start codon in bold and base changes underlined in red; (<b>B</b>) Lysates from RPTE cells transfected with BK WT and ΔAgno genomes were probed with antibodies against early (LT) and late (VP1-3 and agnoprotein) proteins. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was included as a protein loading control. Loss of agnoprotein correlated with increased expression of other virus protein products; (<b>C</b>) Levels of early (LT) and late (VP1) mRNA transcripts were measured from RPTE cells containing BK WT or ΔAgno genomes. Levels of virus transcript were increased in the absence of agnoprotein; (<b>D</b>) Virus genome replication was measured by qPCR in RPTE cells containing BK WT and ΔAgno virus. Genome replication was increased in the absence of agnoprotein. All experiments are representative of at least three independent experimental repeats. Significance of changes were analyzed by Student’s <span class="html-italic">t</span>-test and indicated by * <span class="html-italic">p</span> &lt;0.05, ** <span class="html-italic">p</span> &lt;0.01.</p> Full article ">Figure 2
<p>Agnoprotein facilitates virion release and enhances virus propagation. (<b>A</b>) RPTE cells transfected with BK WT and ΔAgno genomes were incubated over a 6-day time course, and levels of VP1 protein expression determined by indirect immunofluorescence using Incucyte Zoom software (Essen BioScience, Ann Arbor, MI, USA). Levels of VP1 expression are shown relative to the Day 3 BK WT sample. Significance of the changes were analyzed by Student’s <span class="html-italic">t</span>-test and indicated by ** <span class="html-italic">p</span> &lt;0.01; (<b>B</b>) BK virus lacking agnoprotein fails to release virus into the cell culture media. Whole cell lysates and media samples from RPTE cells transfected with BK WT or ΔAgno genomes were analyzed at 48 and 72 h post-transfection for the VP1 capsid protein. GAPDH served as a protein loading control for the whole cell lysates; (<b>C</b>) RPTE cells were infected with BK WT and ΔAgno and cell-associated and media fractions harvested separately. Fluorescence focus assay was then performed to determine the IU/mL<sup>−1</sup> of virus in the cells and supernatant; (<b>D</b>) Effect of the anion channel blocker DIDS is independent of agnoprotein. RPTE cells were infected with BK WT or ΔAgno and treated with dimethyl sulphoxide (DMSO) only (control) or 50–100 μM DIDS at 48 h post infection. Media and cell-associated fractions were harvested separately at 72 h post infection. Infectious virus titers were quantified by fluorescence focus assay on naïve RPTE cells and the proportion of total infectivity released into the media for each condition was calculated. Levels of released infectivity are represented as relative to the untreated BK WT samples. The graph corresponds to an average of three experimental repeats. Significance was analyzed by Student’s <span class="html-italic">t</span>-test and is indicated by an asterix * <span class="html-italic">p</span> &lt;0.05, ** <span class="html-italic">p</span> &lt;0.01.</p> Full article ">Figure 3
<p>Loss of agnoprotein does not impair BK virion assembly. Negative stain electron micrograph of BK WT and ΔAgno virions following centrifugation through an isopycnic caesium chloride gradient. Scale bars 50 nm.</p> Full article ">Figure 4
<p>Agnoprotein facilitates nuclear release of BK virions. (<b>A</b>) Electron microscopy analysis of BK WT and ΔAgno infected RPTE cells (<span class="html-italic">n</span> = 40 cells). Boxed areas in the upper panel are shown at higher magnification in the middle panels. Viral particles of about 40 nm in diameter were found in the nuclei of BK WT and ΔAgno transfected cells. Nuclei (N) and cytoplasm (C) are labeled. Scale bars are shown in the panels; (<b>B</b>) Cell fractionation of RPTE cells transfected with BK WT or ΔAgno genomes. Fractions were probed with for VP1 expression. Antibodies detecting GAPDH and Histone H3 served as markers for the cytoplasm and nuclear fractions; (<b>C</b>) Quantification of the Western blot data was performed using ImageJ software (1.8.0_101, NIH, USA) on the VP1 positive bands and is represented relative to BK WT VP1. The graph corresponds to an average from three independent experimental repeats. Significance was analyzed by Student’s <span class="html-italic">t</span>-test and is indicated by an asterix * <span class="html-italic">p</span> &lt;0.05.</p> Full article ">Figure 5
<p>Lamin B localization is not altered by agnoprotein. Immunofluorescence staining of RPTE cells 72 h post transfection with BK WT or ΔAgno genomes. Cells were incubated with antibodies against VP1 and Lamin B and a secondary antibodies. Alexa Fluor 488 chicken anti-mouse and Alexa Fluor 594 chicken anti-rabbit. 4′,6-diamidino-2-phenylindole (DAPI) was used to indicate cell nuclei. Representative images are shown from at least three independent experimental repeats and white frames indicate area shown in the zoomed image. Scale bar 10 μm.</p> Full article ">Figure 6
<p>The agnoprotein binding partner α-SNAP is required for BK virion release. (<b>A</b>) Recombinant GST-agnoprotein interacts with α-SNAP. Bacterial expressed GST-agnoproteins from BK and JC virus bound to glutathione-agarose beads were incubated with RPTE cell lysates. GST alone served as a negative control. Bound samples were probed with an anti-α-SNAP antibody; (<b>B</b>) Quantification of transmission electron microscopy data. RPTE cells infected with BK WT were treated with siRNA targeting α-SNAP or a scrambled control and electron microscopy used to quantify the numbers cells demonstrating BK virions in nuclear (nuc) and cytoplasmic (cyto) compartments from 50 cells. Associated Western blots for α-SNAP to confirm effective knockdown. Tubulin serves as a loading control.</p> Full article ">
3 pages, 169 KiB  
Editorial
Advances in Multiple Sclerosis 2017
by Kerstin Göbel, Christoph Kleinschnitz and Sven G. Meuth
Int. J. Mol. Sci. 2018, 19(3), 901; https://doi.org/10.3390/ijms19030901 - 19 Mar 2018
Cited by 2 | Viewed by 4126
Abstract
Multiple sclerosis (MS) is one of the most emerging fields in neurology[...] Full article
(This article belongs to the Special Issue Advances in Multiple Sclerosis 2017)
12 pages, 279 KiB  
Article
Evaluation of Promoter Methylation of RASSF1A and ATM in Peripheral Blood of Breast Cancer Patients and Healthy Control Individuals
by Xue Cao, Qiuqiong Tang, Tim Holland-Letz, Melanie Gündert, Katarina Cuk, Sarah Schott, Jörg Heil, Michael Golatta, Christof Sohn, Andreas Schneeweiss and Barbara Burwinkel
Int. J. Mol. Sci. 2018, 19(3), 900; https://doi.org/10.3390/ijms19030900 - 19 Mar 2018
Cited by 17 | Viewed by 4551
Abstract
Breast cancer (BC) is the most common cancer among women and has high mortality rates. Early detection is supposed to be critical for the patient’s prognosis. In recent years, several studies have investigated global DNA methylation profiles and gene-specific DNA methylation in blood-based [...] Read more.
Breast cancer (BC) is the most common cancer among women and has high mortality rates. Early detection is supposed to be critical for the patient’s prognosis. In recent years, several studies have investigated global DNA methylation profiles and gene-specific DNA methylation in blood-based DNA to develop putative screening markers for cancer. However, most of the studies have not yet been validated. In our study, we analyzed the promoter methylation of RASSF1A and ATM in peripheral blood DNA of 229 sporadic patients and 151 healthy controls by the MassARRAY EpiTYPER assay. There were no significant differences in DNA methylation levels of RASSF1A and ATM between the sporadic BC cases and the healthy controls. Furthermore, we performed the Infinium HumanMethylation450 BeadChip (450K) array analysis using 48 sporadic BC cases and 48 healthy controls (cases and controls are the same from those of the MassARRAY EpiTYPER assay) and made a comparison with the published data. No significant differences were presented in DNA methylation levels of RASSF1A and ATM between the sporadic BC cases and the healthy controls. So far, the evidence for powerful blood-based methylation markers is still limited and the identified markers need to be further validated. Full article
(This article belongs to the Special Issue DNA Methylation)
13 pages, 1488 KiB  
Article
Individual versus Combinatorial Effects of Silicon, Phosphate, and Iron Deficiency on the Growth of Lowland and Upland Rice Varieties
by Nanthana Chaiwong, Chanakan Prom-u-thai, Nadia Bouain, Benoit Lacombe and Hatem Rouached
Int. J. Mol. Sci. 2018, 19(3), 899; https://doi.org/10.3390/ijms19030899 - 18 Mar 2018
Cited by 22 | Viewed by 5408
Abstract
Mineral nutrient homeostasis is essential for plant growth and development. Recent research has demonstrated that the occurrence of interactions among the mechanisms regulating the homeostasis of different nutrients in plants is a general rule rather than an exception. Therefore, it is important to [...] Read more.
Mineral nutrient homeostasis is essential for plant growth and development. Recent research has demonstrated that the occurrence of interactions among the mechanisms regulating the homeostasis of different nutrients in plants is a general rule rather than an exception. Therefore, it is important to understand how plants regulate the homeostasis of these elements and how multiple mineral nutrient signals are wired to influence plant growth. Silicon (Si) is not directly involved in plant metabolism but it is an essential element for a high and sustainable production of crops, especially rice, because of its high content in the total shoot dry weight. Although some mechanisms underlying the role of Si in plants responses to both abiotic and biotic stresses have been proposed, the involvement of Si in regulating plant growth in conditions where the availability of essential macro- and micronutrients changes remains poorly investigated. In this study, the existence of an interaction between Si, phosphate (Pi), and iron (Fe) availability was examined in lowland (Suphanburi 1, SPR1) and upland (Kum Hom Chiang Mai University, KH CMU) rice varieties. The effect of Si and/or Fe deficiency on plant growth, Pi accumulation, Pi transporter expression (OsPHO1;2), and Pi root-to-shoot translocation in these two rice varieties grown under individual or combinatorial nutrient stress conditions were determined. The phenotypic, physiological, and molecular data of this study revealed an interesting tripartite Pi-Fe-Si homeostasis interaction that influences plant growth in contrasting manners in the two rice varieties. These results not only reveal the involvement of Si in modulating rice growth through an interaction with essential micro- and macronutrients, but, more importantly, they opens new research avenues to uncover the molecular basis of Pi-Fe-Si signaling crosstalk in plants. Full article
(This article belongs to the Special Issue Regulation of Mineral Nutrients Homeostasis and Their Crosstalk in Plants)
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Full article ">Figure 1
<p>Phenotypes of lowland rice (SPR1) (<b>A</b>) and upland rice (KH CMU) (<b>B</b>) varieties grown under individual and combinatory nutrient deficiency conditions. The seedlings were grown for 18 days under non-aerated conditions in culture solution with and without silicon application. The dash lines are separated between growing condition of without Si (−Si) and with silicon (+Si) in each rice variety.</p> Full article ">Figure 2
<p>Fresh weight of lowland rice (SPR1) and upland rice (KH CMU) varieties grown under individual and combinatory nutrient deficiency stresses. The seedlings were grown in complete Yoshida media (CT), under single (−Pi and −Fe) or double (−Pi−Fe) nutrient deficiency stresses, with (+Si) and without (−Si) Si application. Shoot (<b>A</b>) and root (<b>C</b>) fresh weight of SPR1 and shoot (<b>B</b>) and root (<b>D</b>) fresh weight of KH CMU. The bars represent the standard errors of the corresponding means of the three replicates. Different lowercase letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05. LSD, least significant difference.</p> Full article ">Figure 3
<p>Silicon concentration in the shoot of lowland rice (SPR1) (<b>A</b>) and upland rice (KH CMU) (<b>B</b>) varieties grown under individual and combinatory nutrient deficiency stresses. The seedlings were grown for 18 days in complete Yoshida media (CT), under single (−P and −Fe) or double (−P−Fe) nutrient deficiency stresses, with (+Si) and without (−Si) Si application. The bars represent the standard errors of the corresponding means of the three replicates. Different lowercase letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 4
<p>Phosphate concentration in lowland rice (SPR1) and upland rice (KH CMU) varieties grown under individual and combinatory nutrient deficiency stresses. The seedlings were grown for 18 days in complete Yoshida media (CT), under single (−P and −Fe) or double (−P−Fe) nutrient deficiency stresses, with (+Si) and without (−Si) Si application. Shoot (<b>A</b>) and root (<b>C</b>) Pi concentration of SPR1, and shoot (<b>B</b>) and root (<b>D</b>) Pi concentration of KH CMU. The bars represent the standard errors of the corresponding means of the three replicates. Different lowercase letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 5
<p>Iron concentration in the shoot (<b>A</b>) and roots (<b>B</b>) of lowland rice (SPR1) and upland rice (KH CMU) varieties grown in individual and combinatory nutrient deficiency stresses. The seedlings were grown for 18 days in complete Yoshida media (CT), under single (−P and −Fe) or double (−P−Fe) nutrient deficiency stress, with (+Si) and without (−Si) Si application (−Fe−Pi−Si). Shoots and roots were collected separately. Fe concentration was determined as described in [<a href="#B22-ijms-19-00899" class="html-bibr">22</a>] and presented as mg/kg DW. DW, dry weight. The black and grey histograms represent SPR1 and KH CMU, respectively. The bars represent the standard errors of the corresponding means of the three replicates. Different lowercase letters indicate significant differences at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 6
<p>Expression of <span class="html-italic">OsPHO1;2</span> and effect of Fe and/or Si deficiency on the phosphate root-to-shoot transport in rice. (<b>A</b>) Rice seedlings were grown in Yoshida medium with different ionic concentrations: (<b>B</b>,<b>C</b>) rice varieties SPR1 and KH CMU were grown in media containing inorganic phosphate (Pi) in the presence or in the absence of iron (Fe) and silicon (Si). Abbreviations: complete medium (Ct) medium lacking either an individual element, i.e., iron (Fe) or silicon (−Si), or both (−Fe−Si). Quantitative real-time PCR (qRT-PCR) was performed to analyze <span class="html-italic">OsPHO1;2</span> mRNA levels; <span class="html-italic">OsActin1</span> expression level was used as the internal reference. Pi root-to-shoot transfer is defined as the ratio of radioactive Pi in the shoot over total radioactive Pi in the plant. Individual measurements were obtained from the analysis of shoots and roots collected from a pool of “<span class="html-italic">n</span>” plants (<span class="html-italic">n</span> &gt; 3). The bars represent the standard errors of the corresponding means of the three replicates. Different lowercase letters indicate a significant difference between the treatment conditions at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">
11 pages, 768 KiB  
Review
Understanding Splenomegaly in Myelofibrosis: Association with Molecular Pathogenesis
by Moo-Kon Song, Byeong-Bae Park and Ji-Eun Uhm
Int. J. Mol. Sci. 2018, 19(3), 898; https://doi.org/10.3390/ijms19030898 - 18 Mar 2018
Cited by 33 | Viewed by 9700
Abstract
Myelofibrosis (MF) is a clinical manifestation of chronic BCR-ABL1-negative chronic myeloproliferative neoplasms. Splenomegaly is one of the major clinical manifestations of MF and is directly linked to splenic extramedullary hematopoiesis (EMH). EMH is associated with abnormal trafficking patterns of clonal hematopoietic cells due [...] Read more.
Myelofibrosis (MF) is a clinical manifestation of chronic BCR-ABL1-negative chronic myeloproliferative neoplasms. Splenomegaly is one of the major clinical manifestations of MF and is directly linked to splenic extramedullary hematopoiesis (EMH). EMH is associated with abnormal trafficking patterns of clonal hematopoietic cells due to the dysregulated bone marrow (BM) microenvironment leading to progressive splenomegaly. Several recent data have emphasized the role of several cytokines for splenic EMH. Alteration of CXCL12/CXCR4 pathway could also lead to splenic EMH by migrated clonal hematopoietic cells from BM to the spleen. Moreover, low Gata1 expression was found to be significantly associated with the EMH. Several gene mutations were found to be associated with significant splenomegaly in MF. In recent data, JAK2 V617F homozygous mutation was associated with a larger spleen size. In other data, CALR mutations in MF were signigicantly associated with longer larger splenomegaly-free survivals than others. In addition, MF patients with ≥1 mutations in AZXL1, EZH1 or IDH1/2 had significantly low spleen reduction response in ruxolitinib treatment. Developments of JAK inhibitors, such as ruxolitinib, pacritinib, momelotinib, and febratinib enabled the effective management in MF patients. Especially, significant spleen reduction responses of the drugs were demonstrated in several randomized clinical studies, although those could not eradicate allele burdens of MF. Full article
(This article belongs to the Special Issue Spleen: Crossroad between Immune System, Metabolic Asset and Endocrine Function)
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<p>Splenic extramedullary hematopoiesis in myelofibrosis. Cooperation between <span class="html-italic">JAK2</span> signaling and C-X-C motif chemokine ligand 12 (CXCL12)/C-X-C chemokine receptor type 4 (CXCR4) axis activates downstream signal transducer and activator of transcription (STAT), phosphatidylinositol-3-kinase (PI3K/AKT), and RAS/MAPK pathways, leading to clonal expansion of hematopoietic stem cells (HSCs) and hematopoietic progenitor cells (HPCs) in the bone marrow. Moreover, it encourages the transfer and engraftment of the HSCs and HPCs to the spleen.</p> Full article ">
10 pages, 1496 KiB  
Article
An Anion Conductance, the Essential Component of the Hydroxyl-Radical-Induced Ion Current in Plant Roots
by Igor Pottosin, Isaac Zepeda-Jazo, Jayakumar Bose and Sergey Shabala
Int. J. Mol. Sci. 2018, 19(3), 897; https://doi.org/10.3390/ijms19030897 - 18 Mar 2018
Cited by 11 | Viewed by 4386
Abstract
Oxidative stress signaling is essential for plant adaptation to hostile environments. Previous studies revealed the essentiality of hydroxyl radicals (HO•)-induced activation of massive K+ efflux and a smaller Ca2+ influx as an important component of plant adaptation to a broad range [...] Read more.
Oxidative stress signaling is essential for plant adaptation to hostile environments. Previous studies revealed the essentiality of hydroxyl radicals (HO•)-induced activation of massive K+ efflux and a smaller Ca2+ influx as an important component of plant adaptation to a broad range of abiotic stresses. Such activation would modify membrane potential making it more negative. Contrary to these expectations, here, we provide experimental evidence that HO• induces a strong depolarization, from −130 to −70 mV, which could only be explained by a substantial HO•-induced efflux of intracellular anions. Application of Gd3+ and NPPB, non-specific blockers of cation and anion conductance, respectively, reduced HO•-induced ion fluxes instantaneously, implying a direct block of the dual conductance. The selectivity of an early instantaneous HO•-induced whole cell current fluctuated from more anionic to more cationic and vice versa, developing a higher cation selectivity at later times. The parallel electroneutral efflux of K+ and anions should underlie a substantial leak of the cellular electrolyte, which may affect the cell’s turgor and metabolic status. The physiological implications of these findings are discussed in the context of cell fate determination, and ROS and cytosolic K+ signaling. Full article
(This article belongs to the Special Issue Plasma-Membrane Transport)
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Full article ">Figure 1
<p>Evidence for the anionic component of HO•-induced ion flux in vivo. (<b>A</b>) HO• but not H<sub>2</sub>O<sub>2</sub> provokes a substantial sustained depolarization in the mature zone of intact pea roots. HO• are generated either by mixing of copper with ascorbate in aerated BSM solution or by reducing of H<sub>2</sub>O<sub>2</sub> by iron. (<b>B</b>) Cationic (Ca<sup>2+</sup>, K<sup>+</sup> and H<sup>+</sup>) fluxes evoked by same treatments as in (<b>A</b>). The negative flux corresponds to <span class="html-italic">efflux</span> of cation. It can be seen that at all times there is net cation efflux, so that membrane depolarization requires even larger efflux of intracellular anions. (<b>C</b>) Passive cationic (Ca<sup>2+</sup> and K<sup>+</sup>) fluxes are blocked not only by the direct application of cationic blockers (Gd<sup>3+</sup> and nifedipine) but also by the anionic blocker NPPB. Blockers were applied at the moment, when passive Ca<sup>2+</sup> influx clearly dominated over the Ca<sup>2+</sup> pumping. Note the instantly developed block by Gd<sup>3+</sup> and NPPB.</p> Full article ">Figure 2
<p>HO•-induced current is mediated by low conductance pores. Example of a steady-state HO•-induced whole-cell current at −100 mV, measured in the epidermal protoplast isolated from the mature zone of pea root. Measurements were taken at different time points after the initiation of treatment, reflecting the development of whole-cell current and respective noise pattern. The records are low-pass filtered at 2 KHz. Currents were averaged at fixed voltages of −100 and +60 mV, and the current variance (σ<sup>2</sup>) was calculated by subtracting this value from the actual current value and then raising the respective numbers to a second power. Mean σ<sup>2</sup> values were plotted against the respective mean current values for three individual protoplasts, which displayed comparative magnitudes of limiting HO•-induced whole-cell currents (in the range of −300–−350 pA at −100 mV). Data are means ± SE. Solid lines are best fits to equation σ<sup>2</sup> = <span class="html-italic">i</span>I − I<sup>2</sup>/N, with unitary current values, <span class="html-italic">i</span>, of −110 fA and +80 fA for −100 and +60 mV. See text for more details.</p> Full article ">Figure 3
<p>Ionic selectivity of the HO•-induced whole-cell current is variable. (<b>A</b>) An example of the development of HO•-induced current in isolated barley root epidermis protoplast from the elongation zone. The current responses to a sequence of voltage steps were recorded at different time points (examples are at the left-hand side; dotted lines indicate zero current). The current-voltage relationships for HO•-induced currents are plotted at the right (for the last record both instantaneous, <span class="html-italic">inst</span>, and time-dependent components, <span class="html-italic">t-dep</span>). Beneath are the time course for the changes in whole cell conductance and zero current potential; dotted lines are equilibrium potential values for K<sup>+</sup> and Cl<sup>−</sup>. (<b>B</b>) A variability of the cation/anion selectivity of the HO•-induced whole-cell current between individual protoplasts. After 40 min of HO• treatment, the reversal potential of the whole cell current was evaluated, and then low salt bath was supplemented with 80 mM NaCl and reversal potential was evaluated again. E<sub>K</sub> and E<sub>Cl</sub> are Nernst potentials for K<sup>+</sup> and Cl<sup>−</sup>, E<sub>X</sub><sup>+</sup> corresponds to a theoretical reversal potential for a hypothetical current, strictly selective for monovalent cations over anions, but which does not differentiate between K<sup>+</sup> and Na<sup>+</sup>. The lines connect reversal potential values before and after addition of high-NaCl bath, red and blue ones are for preferential anionic and cationic selectivity, respectively.</p> Full article ">
16 pages, 4021 KiB  
Article
Study of Imidazolium Salt Derivatives as PIK3CA Inhibitors Using a Comprehensive in Silico Method
by Ming-yang Wang, Jing-wei Liang, Xin-yang Li, Kamara Mohamed Olounfeh, Shi-long Li, Shan Wang, Lin Wang and Fan-hao Meng
Int. J. Mol. Sci. 2018, 19(3), 896; https://doi.org/10.3390/ijms19030896 - 18 Mar 2018
Cited by 8 | Viewed by 4399
Abstract
A series of imidazolium salt derivatives have demonstrated potent antitumor activity in prior research. A comprehensive in silicon method was carried out to identify the putative protein target and detailed structure-activity relationship of the compounds. The Topomer CoMFA and CoMSIA techniques were implemented [...] Read more.
A series of imidazolium salt derivatives have demonstrated potent antitumor activity in prior research. A comprehensive in silicon method was carried out to identify the putative protein target and detailed structure-activity relationship of the compounds. The Topomer CoMFA and CoMSIA techniques were implemented during the investigation to obtain the relationship between the properties of the substituent group and the contour map of around 77 compounds; the Topomer CoMFA and CoMSIA models were reliable with the statistical data. The protein–protein interaction network was constructed by combining the Pharmmapper platform and STRING database. After generating the sub-network, the phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit α (PIK3CA with protein data bank ID: 3ZIM) was selected as the putative target of imidazolium salt derivatives. A docking study was carried out to correlate interactions of amino acids in protein active pockets surrounded by the ligand with contour maps generated by the structure-activity relationship method. Then the molecular dynamics simulations demonstrated that the imidazolium salt derivatives have potent binding capacity and stability to receptor 3ZIM, and the two ligand-receptor complex was stable in the last 2 ns. Finally, the ligand-based structure-activity relationship and receptor-based docking were combined together to identify the structural requirement of the imidazolium salt derivatives, which will be used to design and synthesize the novel PIK3CA inhibitors. Full article
(This article belongs to the Section Molecular Biophysics)
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<p>The result of the database alignment using CoMSIA technique (<b>a</b>) and topomer fragment method using the topomer CoMFA technique (<b>b</b>), the fragment 1 was painted in blue and the fragment 2 was painted in red.</p> Full article ">Figure 2
<p>The experimental pIC<sub>50</sub> values and predicted pIC<sub>50</sub> values of the topomer CoMFA model (<b>a</b>) and the CoMSIA model (<b>b</b>).</p> Full article ">Figure 3
<p>Contour maps of the results of topomer CoMFA and CoMSIA. (<b>a</b>,<b>b</b>) Topomer CoMFA steric contour maps of fragment 1 and 2, the green and yellow regions indicate the sterically favorable and unfavorable regions, respectively; (<b>c</b>,<b>d</b>) Topomer CoMFA electrostatic contour map of fragment 1 and 2, the blue and red regions are favorable to positively and negatively charged substituents, respectively; (<b>e</b>) CoMSIA hydrophobic contour map, the yellow and white regions are favorable and unfavorable to hydrophobic substituent groups, respectively; (<b>f</b>) CoMFA hydrogen bond acceptor field, magenta and red indicate regions favorable and unfavorable to hydrogen bond acceptor (HBA) atoms, respectively.</p> Full article ">Figure 4
<p>Network of cancer-related targets (<b>a</b>) and sub-network with essential targets (<b>b</b>), as generated by Cytoscape software and the CytoNCA plugin.</p> Full article ">Figure 5
<p>Molecular Dock interaction of CNX-1351 (<b>a</b>) and compounds 04 (<b>b</b>), 72 (<b>c</b>) and 74 (<b>d</b>) with the amino acids in the active pocket of protein 3zim.</p> Full article ">Figure 6
<p>RMSD tendency of the ligand-receptor complex at different MD simulation times, red and blue curves indicate the compounds 04-3zim and 72-3zim complexes, respectively.</p> Full article ">Figure 7
<p>Structural requirements of a series of imidazolium salt derivatives demonstrate cytotoxic activity against tumor cells.</p> Full article ">
13 pages, 2515 KiB  
Article
Dietary Quercetin Attenuates Adipose Tissue Expansion and Inflammation and Alters Adipocyte Morphology in a Tissue-Specific Manner
by Laura A. Forney, Natalie R. Lenard, Laura K. Stewart and Tara M. Henagan
Int. J. Mol. Sci. 2018, 19(3), 895; https://doi.org/10.3390/ijms19030895 - 17 Mar 2018
Cited by 51 | Viewed by 8956
Abstract
Chronic inflammation in adipose tissue may contribute to depot-specific adipose tissue expansion, leading to obesity and insulin resistance. Dietary supplementation with quercetin or botanical extracts containing quercetin attenuates high fat diet (HFD)-induced obesity and insulin resistance and decreases inflammation. Here, we determined the [...] Read more.
Chronic inflammation in adipose tissue may contribute to depot-specific adipose tissue expansion, leading to obesity and insulin resistance. Dietary supplementation with quercetin or botanical extracts containing quercetin attenuates high fat diet (HFD)-induced obesity and insulin resistance and decreases inflammation. Here, we determined the effects of quercetin and red onion extract (ROE) containing quercetin on subcutaneous (inguinal, IWAT) vs. visceral (epididymal, EWAT) white adipose tissue morphology and inflammation in mice fed low fat, high fat, high fat plus 50 μg/day quercetin or high fat plus ROE containing 50 μg/day quercetin equivalents for 9 weeks. Quercetin and ROE similarly ameliorated HFD-induced increases in adipocyte size and decreases in adipocyte number in IWAT and EWAT. Furthermore, quercetin and ROE induced alterations in adipocyte morphology in IWAT. Quercetin and ROE similarly decreased HFD-induced IWAT inflammation. However, quercetin and red onion differentially affected HFD-induced EWAT inflammation, with quercetin decreasing and REO increasing inflammatory marker gene expression. Quercetin and REO also differentially regulated circulating adipokine levels. These results show that quercetin or botanical extracts containing quercetin induce white adipose tissue remodeling which may occur through inflammatory-related mechanisms. Full article
(This article belongs to the Special Issue Nutraceuticals in Human Health and Disease)
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Graphical abstract
Full article ">Figure 1
<p>Mice (<span class="html-italic">N</span> = 10/group) were fed low fat (LF; white), high fat (HF; black), high fat + quercetin (HF + Q; blue) or high fat + ROE (HF + RO; red) diets for 9 weeks and (<b>a</b>) inguinal white adipose tissue (IWAT) and (<b>b</b>) epididymal white adipose tissue (EWAT) depots were extracted and weighed. Graphs are mean ± SEM. Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 2
<p>Adipocyte size (<b>a</b>) as the percent area, or the number of adipocytes in a given area of tissue, and density (<b>b</b>) were determined in inguinal white adipose tissue (IWAT) from mice were fed low fat (LF; white), high fat (HF; black), high fat + quercetin (HF + Q; blue) or high fat + ROE (HF + RO; red) diets and representative images are shown (<b>c</b>). Graphs are mean ± SEM. Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05. Asterisks represent unilocular adipocytes and arrows point to multilocular adipocytes.</p> Full article ">Figure 2 Cont.
<p>Adipocyte size (<b>a</b>) as the percent area, or the number of adipocytes in a given area of tissue, and density (<b>b</b>) were determined in inguinal white adipose tissue (IWAT) from mice were fed low fat (LF; white), high fat (HF; black), high fat + quercetin (HF + Q; blue) or high fat + ROE (HF + RO; red) diets and representative images are shown (<b>c</b>). Graphs are mean ± SEM. Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05. Asterisks represent unilocular adipocytes and arrows point to multilocular adipocytes.</p> Full article ">Figure 3
<p>Adipocyte size (<b>a</b>) as the percent area, or the number of adipocytes in a given area of tissue, and density (<b>b</b>) were determined in epididymal white adipose tissue (EWAT) from mice were fed low fat (LF; white), high fat (HF; black), high fat + quercetin (HF + Q; blue) or high fat + ROE (HF + RO; red) diets and representative images are shown (<b>c</b>). Graphs are mean ± SEM. Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 3 Cont.
<p>Adipocyte size (<b>a</b>) as the percent area, or the number of adipocytes in a given area of tissue, and density (<b>b</b>) were determined in epididymal white adipose tissue (EWAT) from mice were fed low fat (LF; white), high fat (HF; black), high fat + quercetin (HF + Q; blue) or high fat + ROE (HF + RO; red) diets and representative images are shown (<b>c</b>). Graphs are mean ± SEM. Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 4
<p>Gene expression for inflammatory markers (<b>a</b>) <span class="html-italic">Cd11b</span> (<b>b</b>) <span class="html-italic">Cd68</span> (<b>c</b>) <span class="html-italic">F4</span>/<span class="html-italic">80</span> and (<b>d</b>) <span class="html-italic">Mcp</span>-<span class="html-italic">1</span> were determined in inguinal white adipose tissue (IWAT) from mice were fed low fat (LF; white), high fat (HF; black), high fat + quercetin (HF + Q; blue) or high fat + ROE (HF+RO; red) diets and graphs of respective means ± SEM are shown as arbitrary units (AU). Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 5
<p>Gene expression for inflammatory markers (<b>a</b>) <span class="html-italic">Cd11b</span> (<b>b</b>) <span class="html-italic">Cd68</span> (<b>c</b>) <span class="html-italic">F4</span>/<span class="html-italic">80</span> and (<b>d</b>) <span class="html-italic">Mcp</span>-<span class="html-italic">1</span> were determined in epididymal white adipose tissue (EWAT) from mice were fed low fat (LF; white), high fat (HF; black), high fat + quercetin (HF + Q; blue) or high fat + ROE (HF + RO; red) diets and graphs of respective means ± SEM are shown as arbitrary units (AU). Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 6
<p>Serum levels of (<b>a</b>) leptin (<b>b</b>) adiponectin and (<b>c</b>) IL-6 were determined in serum from mice were fed low fat (LF; white), high fat (HF; black), high fat + quercetin (HF + Q; blue) or high fat + ROE (HF + RO; red) diets and graphs of respective means ± SEM are shown. Different letters denote significant differences between groups at <span class="html-italic">p</span> &lt; 0.05. A is the protein leptin. B is adiponectin and C is IL-6.</p> Full article ">
14 pages, 1777 KiB  
Article
Distinct Properties of Human M-CSF and GM-CSF Monocyte-Derived Macrophages to Simulate Pathological Lung Conditions In Vitro: Application to Systemic and Inflammatory Disorders with Pulmonary Involvement
by Alain Lescoat, Alice Ballerie, Yu Augagneur, Claudie Morzadec, Laurent Vernhet, Olivier Fardel, Patrick Jégo, Stéphane Jouneau and Valérie Lecureur
Int. J. Mol. Sci. 2018, 19(3), 894; https://doi.org/10.3390/ijms19030894 - 17 Mar 2018
Cited by 38 | Viewed by 6866
Abstract
Macrophages play a central role in the pathogenesis of inflammatory and fibrotic lung diseases. However, alveolar macrophages (AM) are poorly available in humans to perform in vitro studies due to a limited access to broncho-alveolar lavage (BAL). In this study, to identify the [...] Read more.
Macrophages play a central role in the pathogenesis of inflammatory and fibrotic lung diseases. However, alveolar macrophages (AM) are poorly available in humans to perform in vitro studies due to a limited access to broncho-alveolar lavage (BAL). In this study, to identify the best alternative in vitro model for human AM, we compared the phenotype of AM obtained from BAL of patients suffering from three lung diseases (lung cancers, sarcoidosis and Systemic Sclerosis (SSc)-associated interstitial lung disease) to human blood monocyte-derived macrophages (MDMs) differentiated with M-CSF or GM-CSF. The expression of eight membrane markers was evaluated by flow cytometry. Globally, AM phenotype was closer to GM-CSF MDMs. However, the expression levels of CD163, CD169, CD204, CD64 and CD36 were significantly higher in SSc-ILD than in lung cancers. Considering the expression of CD204 and CD36, the phenotype of SSc-AM was closer to MDMs, from healthy donors or SSc patients, differentiated by M-CSF rather than GM-CSF. The comparative secretion of IL-6 by SSc-MDMs and SSc-AM is concordant with these phenotypic considerations. Altogether, these results support the M-CSF MDM model as a relevant in vitro alternative to simulate AM in fibrotic disorders such as SSc. Full article
(This article belongs to the Special Issue Macrophages in Inflammation)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Comparison of cell surface molecule expression of alveolar MΦ (AM) and GM-CSF or M-CSF-derived MDMs (monocyte-derived macrophages). Primary human monocytes from healthy donors were differentiated into MDMs in vitro in the presence of GM-CSF (GM-MDMs) or M-CSF (M-MDMs) for 6 days. Bronchoalveolar lavage fluids of patients were washed and cells were plated until the following day. Cells were then harvested, stained and the expression of cell surface molecules was analyzed by flow cytometry. Data are expressed as mean fluorescence intensity (MFI) relative to isotype control (ratio) +SEM (<b>A</b>) and as percentage of positive cells + SEM (<b>B</b>) for at least six healthy donors and 14 or 15 AM. ANOVA followed by Newman–Keuls’ multiple comparison Test, * <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.</p> Full article ">Figure 2
<p>Comparison of cell surface molecules expression of alveolar MΦ (AM) from patients suffering of lung neoplasia (Neo), sarcoidosis (Sarco) or SSc-ILD. Bronchoalveolar lavages fluids of patients were washed and cells were plated until the following day. Cells were then harvested, stained and the expression of cell surface molecules was analyzed by flow cytometry. Data are expressed as mean fluorescence intensity (MFI) relative to isotype control (ratio) +SEM (<b>A</b>) and as percentage of positive cells +SEM (<b>B</b>) for five or six lung neoplasia, five sarcoidosis and four ILD-SSc. ANOVA followed by Newman–Keuls’ multiple comparison Test, * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 2 Cont.
<p>Comparison of cell surface molecules expression of alveolar MΦ (AM) from patients suffering of lung neoplasia (Neo), sarcoidosis (Sarco) or SSc-ILD. Bronchoalveolar lavages fluids of patients were washed and cells were plated until the following day. Cells were then harvested, stained and the expression of cell surface molecules was analyzed by flow cytometry. Data are expressed as mean fluorescence intensity (MFI) relative to isotype control (ratio) +SEM (<b>A</b>) and as percentage of positive cells +SEM (<b>B</b>) for five or six lung neoplasia, five sarcoidosis and four ILD-SSc. ANOVA followed by Newman–Keuls’ multiple comparison Test, * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 3
<p>Comparison of the percentage of cells co-expressing CD206, CD163 and CD169 between GM-CSF and M-CSF-derived MDMs and AM from patients suffering of lung neoplasia, sarcoidosis or SSc-ILD. Primary human monocytes from healthy donors were differentiated into MDMs in vitro in the presence of GM-CSF (GM-MDM) or M-CSF (M-MDM) for 6 days. Bronchoalveolar lavage fluids of patients were washed and cells were plated until the following day. Cells were then harvested, stained and the expression of cell surfaces molecules was analyzed by flow cytometry. Graphs representing the percentage of GM-CSF or M-CSF-derived MDMs co-expressing CD206/CD163, CD206/CD169 or CD163/CD169 are representative of 5 independent experiments (<b>A</b>). Data expressed as the percentage of CD206+/CD163+ cells +SEM (<b>B</b>) or of CD206+/CD169+ cells +SEM (<b>C</b>) are the means of 5 independent experiments except for SSc-ILD with 4 samples. ANOVA followed by Newman–Keuls’ multiple comparison Test: * <span class="html-italic">p</span> &lt; 0.05; <span>$</span> <span class="html-italic">p</span> &lt; 0.05 and <span>$</span><span>$</span><span>$</span> <span class="html-italic">p</span> &lt; 0.001 when compared to M-MDM.</p> Full article ">Figure 4
<p>Comparison of cell surface molecule expression of GM-CSF and M-CSF-derived MDMs from healthy donors and from SSc patients with alveolar MΦ (AM) from patients with SSc-ILD. Primary human monocytes from healthy donors or SSc patients were differentiated into MDMs in vitro in the presence of GM-CSF (GM-MDM or GM-SSc) or M-CSF (M-MDM or M-SSc) for 6 days. Culture media were replaced between the 6th–7th day. Bronchoalveolar lavage fluids were washed and cells were plated until the following day. Cells were harvested, stained and the expression of cell surface molecules was analyzed by flow cytometry. Data are expressed as mean fluorescence intensity (MFI) relative to isotype control (ratio) +SEM for at least five healthy donors, or 7 SSc patients and 4 AM from patients with SSc-ILD. ANOVA followed by Newman–Keuls’ multiple comparison Test, * <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.</p> Full article ">Figure 5
<p>Comparison of IL-6 and CCL18 secretion levels in GM-CSF and M-CSF-derived MDMs from healthy donors and from SSc patients, with alveolar MΦ (AM) from patients with SSc-ILD. Primary human monocytes from healthy donors or SSc patients were differentiated into MDMs in vitro in the presence of GM-CSF (GM-MDM or GM-SSc) or M-CSF (M-MDM or M-SSc) for 6 days. Culture media were replaced at day 6 and, 24 h later, conditioned media were removed, stocked and ELISA were performed. Data are expressed as the mean of concentration in pg/mL + SEM from at least 5 healthy donors, or 7 SSc patients and four AM from patients with SSc-ILD. ANOVA followed by Newman–Keuls’ multiple comparison Test, ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">
19 pages, 355 KiB  
Review
Treatment with Growth Hormone for Adults with Growth Hormone Deficiency Syndrome: Benefits and Risks
by Juan J. Díez, Susana Sangiao-Alvarellos and Fernando Cordido
Int. J. Mol. Sci. 2018, 19(3), 893; https://doi.org/10.3390/ijms19030893 - 17 Mar 2018
Cited by 57 | Viewed by 10114
Abstract
Pharmacological treatment of growth hormone deficiency (GHD) in adults began in clinical practice more than 20 years ago. Since then, a great volume of experience has been accumulated on its effects on the symptoms and biochemical alterations that characterize this hormonal deficiency. The [...] Read more.
Pharmacological treatment of growth hormone deficiency (GHD) in adults began in clinical practice more than 20 years ago. Since then, a great volume of experience has been accumulated on its effects on the symptoms and biochemical alterations that characterize this hormonal deficiency. The effects on body composition, muscle mass and strength, exercise capacity, glucose and lipid profile, bone metabolism, and quality of life have been fully demonstrated. The advance of knowledge has also taken place in the biological and molecular aspects of the action of this hormone in patients who have completed longitudinal growth. In recent years, several epidemiological studies have reported interesting information about the long-term effects of GH replacement therapy in regard to the possible induction of neoplasms and the potential development of diabetes. In addition, GH hormone receptor polymorphism could potentially influence GH therapy. Long-acting GH are under development to create a more convenient GH dosing profile, while retaining the excellent safety, efficacy, and tolerability of daily GH. In this article we compile the most recent data of GH replacement therapy in adults, as well as the molecular aspects that may condition a different sensitivity to this treatment. Full article
(This article belongs to the Special Issue Growth Hormone: Therapeutic Possibilities)
18 pages, 930 KiB  
Review
Health Risks of Hypovitaminosis D: A Review of New Molecular Insights
by Daniela Caccamo, Sergio Ricca, Monica Currò and Riccardo Ientile
Int. J. Mol. Sci. 2018, 19(3), 892; https://doi.org/10.3390/ijms19030892 - 17 Mar 2018
Cited by 57 | Viewed by 10841
Abstract
Hypovitaminosis D has become a pandemic, being observed in all ethnicities and age groups worldwide. Environmental factors, such as increased air pollution and reduced ultraviolet B (UVB) irradiation, as well as lifestyle factors, i.e., decreased outdoor activities and/or poor intake of vitamin D-rich [...] Read more.
Hypovitaminosis D has become a pandemic, being observed in all ethnicities and age groups worldwide. Environmental factors, such as increased air pollution and reduced ultraviolet B (UVB) irradiation, as well as lifestyle factors, i.e., decreased outdoor activities and/or poor intake of vitamin D-rich food, are likely involved in the etiology of a dramatic reduction of vitamin D circulating levels. The insufficiency/deficiency of vitamin D has long been known for its association with osteoporosis and rickets. However, in the last few decades it has become a serious public health concern since it has been shown to be independently associated with various chronic pathological conditions such as cancer, coronary heart disease, neurological diseases, type II diabetes, autoimmune diseases, depression, with various inflammatory disorders, and with increased risk for all-cause mortality in the general population. Prevention strategies for these disorders have recently involved supplementation with either vitamin D2 or vitamin D3 or their analogs at required daily doses and tolerable upper-limit levels. This review will focus on the emerging evidence about non-classical biological functions of vitamin D in various disorders. Full article
(This article belongs to the Special Issue Vitamin D and Its Analogues: New Insights on Biological Effects and Therapeutic Uses)
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Graphical abstract

Graphical abstract
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<p>VDR heterodimer transcription complex and VDR distribution throughout the human body (brown small and big dots) and. Tissue targets of VDR are the following: skin, brain regions, spinal cord, pituitary gland, salivary glands, nasal-oral mucosa, teeth, parathyroid, thymus, lung, heart, spleen, pancreas, adrenal gland, kidney, esophagus, stomach, pylorus, small intestine, large intestine, testis, prostate, bone, immune cells, others. On the left and right of the figure are shown some of VDR old (cardiovascular system) and emerging tissue targets (brain, intestinal microbioma, mast cells). Some of main known VDR gene targets in these latter are shown (<b>in green</b>, up-regulated; <b>in red</b>, down-regulated): <span class="html-italic">ATG16L1</span>, Autophagy-related protein 16-1; <span class="html-italic">BDNF</span>, brain-derived neurotrophic factor; <span class="html-italic">CACNA1C</span>, L-type voltage-sensitive calcium channel subunit A1C; <span class="html-italic">CAMP</span>, cathelicidin antimicrobial peptide; <span class="html-italic">CNTF</span>, ciliary neurotrophic factor; <span class="html-italic">COMT</span>, catechol-O-methyl-transferase; <span class="html-italic">COX</span>, cycloxygenase; <span class="html-italic">DRD2</span>, dopamine receptor D2; <span class="html-italic">ECE1</span>, Endothelin 1-converting enzyme; <span class="html-italic">FCER1A</span>, Fc fragment of IgE receptor IA; <span class="html-italic">GDNF</span>, glia-derived neurotrophic factor; <span class="html-italic">IFNG</span>, Interferon-γ; <span class="html-italic">IL3RA</span>, IL-3 receptor-alpha chain; <span class="html-italic">KIT</span>, gene-encoding CD117; <span class="html-italic">NGF</span>, nerve growth factor; <span class="html-italic">NOS3</span>, endothelial nitric oxide synthase; <span class="html-italic">NT3</span>, neurotrophin 3; Nurr1, nuclear receptor related 1 protein; <span class="html-italic">SERPINE1</span>, serine-protease inhibitor 1 (PAI-1); <span class="html-italic">REN</span>, Renin; <span class="html-italic">RXR</span>, retinoid X receptor; <span class="html-italic">TBP</span>, TATA-binding protein; <span class="html-italic">TFIIB</span>, transcripton factor IIB; <span class="html-italic">THBS1</span>, Thrombospondin-1; <span class="html-italic">TRPV6</span>, transient receptor potential cation channel subfamily V member 6; <span class="html-italic">VDRE</span>, vitamin D response elements on DNA sequence; <span class="html-italic">VD</span>, vitamin D.</p> Full article ">
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