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Volume 22
Issue 4
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Int. J. Mol. Sci., Volume 22, Issue 4 (February-2 2021) – 726 articles

Cover Story (view full-size image): Despite the existing prevention campaigns, cervical cancer remains a leading cause of cancer-related deaths in women worldwide. Progress in finding adequate treatment solutions has been slow in the last years, especially for the patients with recurrent or metastatic disease. Consensus dictates that immunotherapy for cervical cancer holds great promise but currently does not live up to its full effect. We discuss the potential of PD-1 targeting therapy for cervical cancer, how it opens doors for personalized treatment, and which clinical trials are aiming to further exploit this approach in cervical cancer. View this paper
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13 pages, 7652 KiB  
Review
Therapeutic Rationale for Endotoxin Removal with Polymyxin B Immobilized Fiber Column (PMX) for Septic Shock
by Hisataka Shoji and Steven M. Opal
Int. J. Mol. Sci. 2021, 22(4), 2228; https://doi.org/10.3390/ijms22042228 - 23 Feb 2021
Cited by 17 | Viewed by 5238
Abstract
Endotoxin removal therapy with polymyxin B immobilized fiber column (PMX) has been clinically applied for sepsis and septic shock patients since 1994. The effectiveness and usefulness of this therapy have been demonstrated for more than a quarter of a century. However, a documented [...] Read more.
Endotoxin removal therapy with polymyxin B immobilized fiber column (PMX) has been clinically applied for sepsis and septic shock patients since 1994. The effectiveness and usefulness of this therapy have been demonstrated for more than a quarter of a century. However, a documented survival benefit has not yet been demonstrable in a large, multicenter, randomized and controlled trial. Following the findings derived from a large sepsis clinical trial with PMX in North America, a new trial is ongoing to determine if PMX has a long-term survival benefit when administered to septic patients. Another approach to support a survival benefit from intervention with PMX is to utilize a detailed analysis available from a large clinical data base. The endotoxin adsorption capacity of PMX columns in vitro and the effectiveness of PMX columns can be further demonstrable in animal models. The capability of PMX and details of its mechanism of action to intervene in the sepsis cascade and impede organ dysfunction in septic patients is not fully understood. The surface antigen expression in monocytes and neutrophils are improved after PMX therapy. Immunomodulatory effects as a result of endotoxin removal and/or other mechanisms of action have been suggested. These effects and other potential immune effects may explain some of the improved effects upon organ dysfunction of sepsis and septic shock patients. Endotoxemia may be involved in the pathophysiology of other diseases than sepsis. A rapid diagnostic method to detect and target endotoxemia could allow us to practice precision medicine and expand the clinical indications of endotoxin removal therapy. Full article
(This article belongs to the Special Issue Diagnostic Challenge and Therapeutic Approaches in Human Sepsis Based on the Appearance of Endotoxemia and Beta-D-Glucanemia)
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<p>Structure of polymyxin B immobilized fiber column.</p> Full article ">Figure 2
<p>Schematic diagram of hemoperfusion with PMX (PMX-HP). PMX: polymyxin B immobilized fiber column.</p> Full article ">
23 pages, 4314 KiB  
Article
Long Non-Coding RNA Landscape in Prostate Cancer Molecular Subtypes: A Feature Selection Approach
by Simona De Summa, Antonio Palazzo, Mariapia Caputo, Rosa Maria Iacobazzi, Brunella Pilato, Letizia Porcelli, Stefania Tommasi, Angelo Virgilio Paradiso and Amalia Azzariti
Int. J. Mol. Sci. 2021, 22(4), 2227; https://doi.org/10.3390/ijms22042227 - 23 Feb 2021
Cited by 3 | Viewed by 3103
Abstract
Prostate cancer is one of the most common malignancies in men. It is characterized by a high molecular genomic heterogeneity and, thus, molecular subtypes, that, to date, have not been used in clinical practice. In the present paper, we aimed to better stratify [...] Read more.
Prostate cancer is one of the most common malignancies in men. It is characterized by a high molecular genomic heterogeneity and, thus, molecular subtypes, that, to date, have not been used in clinical practice. In the present paper, we aimed to better stratify prostate cancer patients through the selection of robust long non-coding RNAs. To fulfill the purpose of the study, a bioinformatic approach focused on feature selection applied to a TCGA dataset was used. In such a way, LINC00668 and long non-coding(lnc)-SAYSD1-1, able to discriminate ERG/not-ERG subtypes, were demonstrated to be positive prognostic biomarkers in ERG-positive patients. Furthermore, we performed a comparison between mutated prostate cancer, identified as “classified”, and a group of patients with no peculiar genomic alteration, named “not-classified”. Moreover, LINC00920 lncRNA overexpression has been linked to a better outcome of the hormone regimen. Through the feature selection approach, it was found that the overexpression of lnc-ZMAT3-3 is related to low-grade patients, and three lncRNAs: lnc-SNX10-87, lnc-AP1S2-2, and ADPGK-AS1 showed, through a co-expression analysis, significant correlation values with potentially druggable pathways. In conclusion, the data mining of publicly available data and robust bioinformatic analyses are able to explore the unknown biology of malignancies. Full article
(This article belongs to the Special Issue Role of ncRNAs Classes as Biomarkers for Diagnostic and Prognosis in Cancer)
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<p>(<b>a</b>) Variance explained by the surrogate variables (SVs) identified. The red dot indicates that 18 SVs explain 95% of the variance. (<b>b</b>) Correlation plot between the SVs and known variables. It is important to note than none of them were significantly correlated with the class variable (ERG/not-ERG).</p> Full article ">Figure 2
<p>(<b>a</b>) Multidimensional scaling plot that shows the effects of normalization and data adjustment. (<b>b</b>) Feature importance plot showing the best performing long non-coding RNAs (lncRNAs). (<b>c</b>) Cluster gram of the best top 10 lncRNAs discriminating ERG/not-ERG subtypes, and (<b>d</b>) an Ensembl ID/LNCPipedia ID conversion table.</p> Full article ">Figure 3
<p>Violin plot depicting the accuracy, specificity and specificity of the classification algorithms.</p> Full article ">Figure 4
<p>(<b>a</b>) Co-expression network, including significant correlation oflncRNAs/coding genes. Red cells indicate lncRNAs showing significant coexpression with mRNAs (<b>b</b>). Functional enrichment of the co-expression network.</p> Full article ">Figure 4 Cont.
<p>(<b>a</b>) Co-expression network, including significant correlation oflncRNAs/coding genes. Red cells indicate lncRNAs showing significant coexpression with mRNAs (<b>b</b>). Functional enrichment of the co-expression network.</p> Full article ">Figure 5
<p>(<b>a</b>) Protein–protein interaction (PPI) network derived from the co-expression network. (<b>b</b>–<b>d</b>) Subnetworks identified by the Molecular Complex Detection (MCODE) algorithm.</p> Full article ">Figure 5 Cont.
<p>(<b>a</b>) Protein–protein interaction (PPI) network derived from the co-expression network. (<b>b</b>–<b>d</b>) Subnetworks identified by the Molecular Complex Detection (MCODE) algorithm.</p> Full article ">Figure 6
<p>(<b>a</b>) Violin plots showing that ERG-positive patients with Gleason scores ≤ 3+4 overexpress LINC00668 and lnc-SAYSD1-1. (<b>b</b>) PFS Kaplan-Meier curve stratifying the ERG subset according to the LNC00920 expression.</p> Full article ">Figure 7
<p>(<b>a</b>) Dot plot representing lncRNAs ranked by their importance. (<b>b</b>) Cluster gram of the best top 10 lncRNAs discriminated by classified/not-classified prostate cancer (PCa) cases. (<b>c</b>) Ensembl ID/LNCipedia ID conversion table and Venn diagram including top 10 ERG/not-ERG lncRNAs and classified/not-classified lncRNAs.</p> Full article ">Figure 8
<p>(<b>a</b>) Co-expression network, including significant correlations between lncRNAs/coding genes (red cells indicate lncRNAs with significant co-expression with genes) and (<b>b</b>) their functional enrichments. (<b>c</b>) Violin plot that shows that low-grade not-classified patients overexpress lnc-ZMAT3-3.</p> Full article ">
22 pages, 16857 KiB  
Article
Mutation of GGMP Repeat Segments of Plasmodium falciparum Hsp70-1 Compromises Chaperone Function and Hop Co-Chaperone Binding
by Stanley Makumire, Tendamudzimu Harmfree Dongola, Graham Chakafana, Lufuno Tshikonwane, Cecilia Tshikani Chauke, Tarushai Maharaj, Tawanda Zininga and Addmore Shonhai
Int. J. Mol. Sci. 2021, 22(4), 2226; https://doi.org/10.3390/ijms22042226 - 23 Feb 2021
Cited by 15 | Viewed by 3539
Abstract
Parasitic organisms especially those of the Apicomplexan phylum, harbour a cytosol localised canonical Hsp70 chaperone. One of the defining features of this protein is the presence of GGMP repeat residues sandwiched between α-helical lid and C-terminal EEVD motif. The role of the GGMP [...] Read more.
Parasitic organisms especially those of the Apicomplexan phylum, harbour a cytosol localised canonical Hsp70 chaperone. One of the defining features of this protein is the presence of GGMP repeat residues sandwiched between α-helical lid and C-terminal EEVD motif. The role of the GGMP repeats of Hsp70s remains unknown. In the current study, we introduced GGMP mutations in the cytosol localised Hsp70-1 of Plasmodium falciparum (PfHsp70-1) and a chimeric protein (KPf), constituted by the ATPase domain of E. coli DnaK fused to the C-terminal substrate binding domain of PfHsp70-1. A complementation assay conducted using E. coli dnaK756 cells demonstrated that the GGMP motif was essential for chaperone function of the chimeric protein, KPf. Interestingly, insertion of GGMP motif of PfHsp70-1 into DnaK led to a lethal phenotype in E. coli dnaK756 cells exposed to elevated growth temperature. Using biochemical and biophysical assays, we established that the GGMP motif accounts for the elevated basal ATPase activity of PfHsp70-1. Furthermore, we demonstrated that this motif is important for interaction of the chaperone with peptide substrate and a co-chaperone, PfHop. Our findings suggest that the GGMP may account for both the specialised chaperone function and reportedly high catalytic efficiency of PfHsp70-1. Full article
(This article belongs to the Special Issue Molecular Chaperones 3.0)
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<p>Multiple sequence alignment (MSA) of Hsp70s and design of GGMP mutants. (<b>A</b>) MSA of <span class="html-italic">Plasmodium falciparum</span> 3D7 Hsp70 (PfHsp70-1, NCBI accession number: XP_001349336.1); <span class="html-italic">Plasmodium vivax</span> (NCBI: XP_001614972.1); <span class="html-italic">Plasmodium ovale curtisi</span> (GenBank: SBS81157.1); <span class="html-italic">Plasmodium malariae</span> (NCBI: XP_028860418.1); <span class="html-italic">Plasmodium knowlesi</span> strain H (NCBI: XP_002258136.1); <span class="html-italic">Plasmodium berghei</span> ANKA Hsp70 (NCBI: XP_022712526.1); <span class="html-italic">Cryptosporidium parvum Iowa</span> II (NCBI: XP_625373.1); <span class="html-italic">Cyclospora cayetanensis</span> (NCBI: XP_022588287.1); <span class="html-italic">Entamoeba histolytica</span> (GenBank: AAA29102.1); <span class="html-italic">Giardia lamblia</span> ATCC 50,803 (GenBank: EDO80296.1); <span class="html-italic">Leishmania donovani</span> (UniprotKB: P17804); <span class="html-italic">Toxoplasma gondii</span> Hsp70 (UniprotKB: A0A125YXI9); <span class="html-italic">Trypanosoma brucei</span> HSP74 (UniprotKB: P11145); <span class="html-italic">Homo sapiens</span> heat shock cognate 71 kDa (Hsc70, NCBI: NP_006588.1); <span class="html-italic">Homo sapiens</span> Hsp70 protein 1A (HspA1A, NCBI: NP_005336.3); <span class="html-italic">E. coli</span> Hsp70 (DnaK, UniProtKB: A1A766.1); <span class="html-italic">Mycobacterium tuberculosis</span> Hsp70 (UniProtKB: P9WMJ9.1); <span class="html-italic">Staphylococcus aureus</span> HSP70 (GenBank: BAA06359.1); <span class="html-italic">Saccharomyces cerevisiae</span> HSP70 (Ssa1p, GenBank: AAC04952.1); <span class="html-italic">Homo sapiens</span> heat shock protein 70s (HspA14; NCBI: NP_057383.2), HspA6 (NCBI: NP_002146.2), HspA2 (NCBI: NP_068814.2), HspA4 (NCBI: NP_002145.3), HspA13 (NCBI: NP_008879.3), HspA12A (NCBI: NP_001317093.1), HspA12B (NP_001317093.2), HspA9 (NCBI, NP_004125.3). The black rectangle marks the GGMP repeat segment and the top panel highlights the overall residue conservation level. Residue numbering is based on PfHsp70-1. (<b>B</b>) Mutations were introduced at various positions within the GGMP repeat segment of PfHsp70-1 to generate the following derivatives: PfHsp70-1<sub>G632</sub>, PfHsp70-1<sub>G648</sub>, PfHsp70-<sub>1G632-664</sub>, PfHsp70-1<sub>∆G</sub>. The GGMP segment of PfHsp70-1 was inserted into DnaK to generate the derivative, “DnaK-<sub>G</sub>”.</p> Full article ">Figure 2
<p>Superimposed three dimensional models of wild type SBDs of PfHsp70-1 and DnaK versus those of their GGMP variants. Superposition of the SBDβ and SBDα regions of PfHsp70-1 and DnaK against their respective GGMP variants was conducted: (<b>A</b>) PfHsp70-1 versus PfHsp70-1<sub>G632</sub>, the insert represents zoomed segment highlights H-bonding variations; (<b>B</b>) PfHsp70-1 versus PfHsp70-1<sub>G648</sub>, the zoomed SBD section with unique H-bonding is shown; (<b>C</b>) PfHsp70-1 and PfHsp70-1<sub>G632-664</sub>, with the insert showing unique H-bonding variations in SBDβ; (<b>D</b>) PfHsp70-1 versus PfHsp70-1<sub>ΔG</sub> structures and highlighted are structural variations within the SBD; and (<b>E</b>) DnaK superposed with DnaK-<sub>G</sub>, insert highlights unique H-bonding pattern. The structures were visualized using Chimera.</p> Full article ">Figure 3
<p>Secondary structure analysis. (<b>A</b>) The CD spectra of native PfHsp70-1, PfHsp70-1<sub>G632</sub>, PfHs70-1<sub>G648</sub> PfHsp70-1<sub>G632-664</sub>, and PfHsp70-1<sub>ΔG</sub> were presented as molar residue ellipticity (deg.cm<sup>2</sup>.dmol<sup>−1</sup>). (<b>B</b>) Temperature induced unfolding of the recombinant proteins was monitored by ellipticity measured at fixed wavelength of 222 nm as temperature was raised from 20 °C to 90 °C. Shown are: (<b>C</b>) CD spectra for DnaK and its mutant DnaK-<sub>G</sub>; and (<b>D</b>) folded fraction of DnaK and DnaK-<sub>G</sub> monitored at 222 nm. Dotted line represents the melting temperature for 50% of the Hsp70 or its respective variants. Relative folded fraction of each protein was determined at a given temperature relative to fully folded state of the protein observed at 20 °C.</p> Full article ">Figure 4
<p>GGMP mutations compromise basal ATPase and chaperone functions of PfHsp70-1. (<b>A</b>) ATPase activity of the GGMP variants relative to PfHsp70-1 (WT). The basal ATPase activities of PfHsp70-1, DnaK, and their GGMP variants were determined by monitoring the amount of P<span class="html-italic">i</span> released determined by direct colorimetric readings conducted at 595 nm. (<b>B</b>) Heat induced aggregation suppression activities of PfHsp70-1 and its GGMP derivatives were monitored by exposing aggregation prone protein, MDH to heat stress at 51 °C in the presence of equimolar chaperone levels. The heat-induced aggregation of MDH was monitored spectroscopically at 360 nm. The assay was conducted in the absence of nucleotide (NN), or the presence of 5 mM ATP/ADP, respectively. (<b>C</b>) Complementation assay to determine the effect of the GGMP motifs on the function of chimeric protein, KPf, and DnaK. <span class="html-italic">E. coli dnaK756</span> cells transformed with plasmid constructs expressing either KPf, its GGMP mutants; DnaK, and its GGMP insertion mutant, DnaK-<sub>G</sub>, were incubated at the growth permissive temperature of 37 °C. Heat stress resilience of the cells was assessed by growing them 43.5 °C. Negative controls consisted of cells transformed with pQE60, pQE30 plasmid vectors and pQE60/KPf-V436F construct. Expression of the respective proteins was confirmed by Western blotting (“W”). Statistical analysis was carried out using one-way ANOVA at (* <span class="html-italic">p</span> &lt; 0.05; <span class="html-italic">**</span> <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p> Full article ">Figure 5
<p>GGMP mutation compromises peptide binding. The representative SPR sensograms for the interaction of PfHsp70-1 GGMP variants with the peptide ANNNMYRR. Assay was conducted in the absence of nucleotides (<b>A</b>), and the presence of either 5 mM ATP (<b>B</b>) or 5 mM ADP (<b>C</b>), respectively. The relative affinities of PfHsp70-1 and its GGMP variants for ANNNMYRR were determined as shown (<b>D</b>). The error bars indicate data generated from three assays conducted using independent Hsp70 protein preparations. Statistical significance was determined by two-way ANOVA (* <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 6
<p>The GGMP motif of PfHsp70-1 modulates PfHop interaction. Representative SPR sensograms generated for assay monitoring interaction of PfHop and PfHsp70-1 GGMP variants are shown. Assay was conducted in the absence of nucleotides (<b>A</b>), and in the presence of either 5 mM ATP (<b>B</b>); or 5 mM ADP (<b>C</b>), respectively. The binding affinities of PfHop for PfHsp70-1 GGMP derivatives were normalized relative to the affinity of PfHop for wild type PfHsp70-1 as determined in the absence of nucleotides (<b>D</b>). The error bars represent data from three assays. Two-way ANOVA was used to determine the statistical significance at (** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p> Full article ">Figure 7
<p>Insertion of GGMP repeat residues into DnaK did not result in PfHop binding. Slot blot and ELISA were conducted to explore interaction of DnaK-<sub>G</sub> with PfHop. The slot blot images and graphs generated from ELISA absorbance readings to explore interaction of PfHop with DnaK and its variant, DnaK-<sub>G</sub> in the absence of nucleotides (<b>A</b>), and in the presence of either 5 mM ATP (<b>B</b>), or 5 mM ADP (<b>C</b>), respectively. The relative intensities for PfHop-DnaK-<sub>G</sub> interaction were normalized relative to intensity of signal obtained for DnaK-PfHop at their highest amounts of the proteins for the assay conducted in the absence of nucleotides (<b>D</b>). The error bars represent data from three assays. Two-way ANOVA was used to determine the statistical significance at (* <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001).</p> Full article ">Figure 8
<p>Model highlighting the roles of the GGMP repeat residues of PfHsp70-1. PfHsp70-1 exhibits key functional features which are compromised upon removal or mutation of the GGMP repeat residues. The main structural defects leading to compromised function appear to include reorientation of the SBDβ loops and the C-terminal lid region. Reorientation of the SBDβ loops and the lid both adversely impact on substrate affinity and chaperone function.</p> Full article ">
14 pages, 14050 KiB  
Article
Regulation of Glucose Metabolism by MuRF1 and Treatment of Myopathy in Diabetic Mice with Small Molecules Targeting MuRF1
by Siegfried Labeit, Stephanie Hirner, Julijus Bogomolovas, André Cruz, Moldir Myrzabekova, Anselmo Moriscot, Thomas Scott Bowen and Volker Adams
Int. J. Mol. Sci. 2021, 22(4), 2225; https://doi.org/10.3390/ijms22042225 - 23 Feb 2021
Cited by 15 | Viewed by 3751
Abstract
The muscle-specific ubiquitin ligase MuRF1 regulates muscle catabolism during chronic wasting states, although its roles in general metabolism are less-studied. Here, we metabolically profiled MuRF1-deficient knockout mice. We also included knockout mice for MuRF2 as its closely related gene homolog. MuRF1 and MuRF2-KO [...] Read more.
The muscle-specific ubiquitin ligase MuRF1 regulates muscle catabolism during chronic wasting states, although its roles in general metabolism are less-studied. Here, we metabolically profiled MuRF1-deficient knockout mice. We also included knockout mice for MuRF2 as its closely related gene homolog. MuRF1 and MuRF2-KO (knockout) mice have elevated serum glucose, elevated triglycerides, and reduced glucose tolerance. In addition, MuRF2-KO mice have a reduced tolerance to a fat-rich diet. Western blot and enzymatic studies on MuRF1-KO skeletal muscle showed perturbed FoxO-Akt signaling, elevated Akt-Ser-473 activation, and downregulated oxidative mitochondrial metabolism, indicating potential mechanisms for MuRF1,2-dependent glucose and fat metabolism regulation. Consistent with this, the adenoviral re-expression of MuRF1 in KO mice normalized Akt-Ser-473, serum glucose, and triglycerides. Finally, we tested the MuRF1/2 inhibitors MyoMed-205 and MyoMed-946 in a mouse model for type 2 diabetes mellitus (T2DM). After 28 days of treatment, T2DM mice developed progressive muscle weakness detected by wire hang tests, but this was attenuated by the MyoMed-205 treatment. While MyoMed-205 and MyoMed-946 had no significant effects on serum glucose, they did normalize the lymphocyte–granulocyte counts in diabetic sera as indicators of the immune response. Thus, small molecules directed to MuRF1 may be useful in attenuating skeletal muscle strength loss in T2DM conditions. Full article
(This article belongs to the Special Issue Skeletal Muscle Organelle Maintenance in Health and Disease: From Molecular Mechanisms to Practical Recommendations)
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<p>MuRF1- and MuRF2-KO (knockout) mice have elevated serum glucose and triglycerides. (<b>A</b>–<b>C</b>) Clinical chemistry of sera from MuRF1-KO (M1KO), MuRF2-KO (M2KO) and MuRF1-Tg (TG or trangene) mice. (<b>A</b>) MuRF1-KO and MuRF2-KO mice have upregulated serum glucose (*** <span class="html-italic">p</span> &lt; 0.001; <span class="html-italic">n</span> = 20). (<b>B</b>) Triglycerides were elevated in MuRF1-KO mice (* <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 20), and a trend was noted in MuRF2-KO mice (<span class="html-italic">p</span> = 0.1, <span class="html-italic">n</span> = 20). (<b>C</b>) Transgenic (“TG”) mice that overexpress MuRF1 in their skeletal muscles have lower serum glucose (FVBN mouse strain; see [<a href="#B24-ijms-22-02225" class="html-bibr">24</a>]. for details; * <span class="html-italic">p</span> &lt; 0.05; <span class="html-italic">n</span> = 12). (<b>D</b>) Electron micrographs of the quadriceps (QUAD) from starved wild-type (WT) and MuRF2-KO mice. MuRF2-KO QUAD retains glycogen granules (white arrows) in its high molecular weight electron-dense macro-glycogen form after 16-h starvation (arrows) in contrast to WT.</p> Full article ">Figure 2
<p>Reduced tolerance to glucose or fat in MuRF1 and MuRF2-KO mice. (<b>A</b>) Intraperitoneal glucose tolerance tests (IPGTT) on MuRF1- and MuRF2-KO mice. MuRF2-KO mice showed elevated glucose levels at the 60- and 120-min time points (* <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6). (<b>B</b>) Insulin was determined from blood samples from A, and the areas under the glucose and insulin curves were calculated. Respective ratios as an indicator for insulin sensitivity are shown. MuRF1-KO mice had, at 30 min, a reduced glucose–insulin ratio; MuRF2-KO mice have lowered glucose–insulin ratios at 30, 60, and 120 min, respectively (* <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6). (<b>C</b>) WT, MuRF1-KO-, and MuRF2-KO mice were fed with a fat-enriched diet. MuRF2-KO mice became progressively obese after 13 weeks when compared to WT (* <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6).</p> Full article ">Figure 3
<p>MuRF1 and MuRF2 inactivation perturbs Akt- and FOXO3a-phosphorylation. (<b>A</b>,<b>B</b>) Western blot screens with specific antibodies using 16-h-starved MuRF1- and MuRF2-deficient QUAD or cell extracts. (<b>A</b>) In QUAD, phospho-Ser-473 is upregulated, and total Akt is normal. (<b>B</b>) Augmented Akt-Ser-473 phosphorylation in cultured primary cardiac myocytes obtained from MuRF1 or MuRF2 fetal mice indicates the cell-autonomous MuRF1,2 dependent regulation of Akt. (<b>C</b>,<b>D</b>) Quantitation of Akt, Foxo, and their Ser-473 and Ser-253 phosphoforms, respectively, by Western blots from TA mouse muscle extracts. MuRF1 inactivation leads to elevated phospho-Akt and phospho-Foxo3a, respectively; MuRF2 inactivation instead lowered phospho-Foxo3a (MuRF1-KO, <span class="html-italic">n</span> = 6 and MuRF2-KO, <span class="html-italic">n</span> = 8; see <a href="#app1-ijms-22-02225" class="html-app">Figure S1</a>).</p> Full article ">Figure 4
<p>Effects of MuRF1 on SDH, complex-1, and PDC, and of MuRF1 and MuRF2 on PDK2. (<b>A</b>,<b>B</b>) SDH and complex-1 activities were measured in myocardial extracts by enzymatic assays [<a href="#B20-ijms-22-02225" class="html-bibr">20</a>,<a href="#B25-ijms-22-02225" class="html-bibr">25</a>]. MuRF1-KO myocardium had significantly lower SDH and complex-1 activities (** <span class="html-italic">p</span> &lt; 0.01; <span class="html-italic">n</span> = 5). (<b>C</b>) PDC activities (PDCa) in myocardial extracts were measured by determining the conversion rate of pyruvate to acetyl-CoA (coenzyme A). PDCa is given in artificial units (AUs), where WT was defined as the reference as 1.0. AAV9-MCL2-MuRF1 (MLC2 indicates myosin light chain-2 promoter driven) injections elevated the PDCa (* <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 5). (<b>D</b>) In vitro ubiquitination of PDK2 by MuRF1 and MuRF2. Addition of the full-length recombinant MuRF1 or MuRF2 E3 ligases to reaction mixes containing the PDC regulator PDK2 and the cofactors ubiquitin and E1 and E2 ligases results in the mono-ubiquitination of PDK2 as detected with specific antibodies (arrow).</p> Full article ">Figure 5
<p>Rescue of metabolic alterations in MuRF1-KO mice after adenoviral re-expression of MuRF1 in the myocardium. (<b>A</b>) MuRF1 protein, physiologically expressed in the mouse myocardium from the left ventricle (WT lanes), is absent in MuRF1-KO mice (see, also, <a href="#app1-ijms-22-02225" class="html-app">Figure S2</a>). One and nine months after AAV9-MLC2-MuRF1 injection, respectively, MuRF1 is detected in the previously MuRF1-free myocardium. (<b>B</b>) Elevated serum glucose in MuRF1-KO mice is normalized after AAV9-MLC2-MuRF1 injections (* <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6). (<b>C</b>) Triglycerides were significantly elevated in MuRF1-KO mice when compared to the WT (* <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">n</span> = 6). This significance is lost after AAV9-MLC2-MuRF1 injection.</p> Full article ">Figure 6
<p>Normalization of lymphocyte and granulocyte counts during the compound treatments. Control mice had white blood cell counts with about 65% lymphocytes and 30% granulocytes (Con group). DIO mice, in contrast, had similar lymphocyte and granulozyte percentages at day 28 for <span class="html-italic">p</span> &lt; 0.05, comparison of Con to DIO). The treatments with MyoMed-205 and MyoMed-946 normalized the white blood cell ratios. The treatments with MyoMed-203, MyoMed-205, and MyoMed-946 were all three closely structurally related and normalized the white blood cell ratios. In contrast, their metabolite MyoMed-154, which is generated by their hydrolysis in the serum, had no effect on the white blood cell counts (* <span class="html-italic">p</span> &lt; 0.05 for the DIO+ compound compared to the DIO group, <span class="html-italic">n</span> = 8 and <sup>&amp;</sup> <span class="html-italic">p</span> &lt; 0.05 for DIO compared to the control group, <span class="html-italic">n</span> = 8).</p> Full article ">Figure 7
<p>Protective effects of MyoMed-205 on the holding impulse in DIO mice. The muscle function was assessed by wire hang tests (WHTs) at days 3, 7, 14, 21, and 28. Mice in the DIO group have impaired holding impulses at day 28. Feeding with MyoMed-205 improved the holding impulse, whereas MyoMed-946 had no effect on the holding impulses in WHTs (* <span class="html-italic">p</span> &lt; 0.05 DIO + 205 compared to the DIO group, <span class="html-italic">n</span> = 8).</p> Full article ">
26 pages, 1399 KiB  
Review
Development of Antimicrobial Phototreatment Tolerance: Why the Methodology Matters
by Aleksandra Rapacka-Zdonczyk, Agata Wozniak, Joanna Nakonieczna and Mariusz Grinholc
Int. J. Mol. Sci. 2021, 22(4), 2224; https://doi.org/10.3390/ijms22042224 - 23 Feb 2021
Cited by 21 | Viewed by 4316
Abstract
Due to rapidly growing antimicrobial resistance, there is an urgent need to develop alternative, non-antibiotic strategies. Recently, numerous light-based approaches, demonstrating killing efficacy regardless of microbial drug resistance, have gained wide attention and are considered some of the most promising antimicrobial modalities. These [...] Read more.
Due to rapidly growing antimicrobial resistance, there is an urgent need to develop alternative, non-antibiotic strategies. Recently, numerous light-based approaches, demonstrating killing efficacy regardless of microbial drug resistance, have gained wide attention and are considered some of the most promising antimicrobial modalities. These light-based therapies include five treatments for which high bactericidal activity was demonstrated using numerous in vitro and in vivo studies: antimicrobial blue light (aBL), antimicrobial photodynamic inactivation (aPDI), pulsed light (PL), cold atmospheric plasma (CAP), and ultraviolet (UV) light. Based on their multitarget activity leading to deleterious effects to numerous cell structures—i.e., cell envelopes, proteins, lipids, and genetic material—light-based treatments are considered to have a low risk for the development of tolerance and/or resistance. Nevertheless, the most recent studies indicate that repetitive sublethal phototreatment may provoke tolerance development, but there is no standard methodology for the proper evaluation of this phenomenon. The statement concerning the lack of development of resistance to these modalities seem to be justified; however, the most significant motivation for this review paper was to critically discuss existing dogma concerning the lack of tolerance development, indicating that its assessment is more complex and requires better terminology and methodology. Full article
(This article belongs to the Special Issue Antimicrobial Resistance-New Insights)
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Figure 1

Figure 1
<p>Minimum inhibitory concentration (MIC) characteristics of bacterial responses to light-based treatments. MIC values for bacterial strains resistant to light-based treatment are significantly higher than those for susceptible strains. Resistance is an acquired and inherited decline in the effectiveness of a given treatment (the need for higher concentrations of a photosensitizing agent); Tolerance is an acquired stable feature (the need for longer treatment duration to achieve the same killing efficacy regardless of the concentration of the photosensitizing agent); Persistence is a nonheritable and dormant phenotypic state (transient tolerance) represented by a small subpopulation (about 0.1–1%). Colored probes represent bacterial growth, and orange indicates growth inhibition due to phototreatment conditions leading to cell death. MIC values for strains expressing tolerance or persistence are similar to those of susceptible strains. Concentrations are chosen for illustration purposes only (modified from Brauner et al.).</p> Full article ">Figure 2
<p>Characteristics of bacterial responses to light-based treatments. Minimum duration for killing 99% of bacterial cells (MDK<sub>99</sub>) is substantially longer for tolerant than susceptible and persistent strains. MDK<sub>99</sub> for persistent and susceptible strains is similar, but MDK<sub>99.99</sub> for persistent strains is substantially higher than for susceptible strains. Time scale is chosen for illustration purposes only (modified from Brauner et al.).</p> Full article ">Figure 3
<p>Framework for photoinduced adaptation research.</p> Full article ">Figure 4
<p>Schematic overview of a mature biofilm structure. Biofilm is characterized by heterogenous environment and the presence of a variety of subpopulations. A biofilm structure is composed of metabolically active (both resistant and tolerant) and non-active cells (viable but not culturable cells, VBNC, and persisters) as well as polymer matrix consisting of polysaccharide, extracellular DNA and proteins. Biofilm growth is associated with an escalated level of mutations and horizontal gene transfer (HGT) which is promoted in due to the packed and dense structure. Bacteria in biofilms communicate by QS, which activates genes participating in virulence factors production (modified from Hall and Mah).</p> Full article ">
4 pages, 165 KiB  
Editorial
The Self-Assembly and Design of Polyfunctional Nanosystems
by Ruslan Kashapov and Lucia Zakharova
Int. J. Mol. Sci. 2021, 22(4), 2223; https://doi.org/10.3390/ijms22042223 - 23 Feb 2021
Cited by 1 | Viewed by 1945
Abstract
The current task of the molecular sciences is to create unique nanostructured materials with a given structure and with specific physicochemical properties on the basis of the existing wide range of molecules of natural and synthetic origin. A promising and inexpensive way to [...] Read more.
The current task of the molecular sciences is to create unique nanostructured materials with a given structure and with specific physicochemical properties on the basis of the existing wide range of molecules of natural and synthetic origin. A promising and inexpensive way to obtain nanostructured materials is the spontaneous self-assembly of molecular building blocks during random collisions in real dispersive systems in solution and at interfaces. This editorial aims to summarize the major points from the 11 scientific papers that contributed to the special issue “The Self-Assembly and Design of Polyfunctional Nanosystems”, assessing the modern self-assembly potential and strategies for maintaining sustainable development of the nanoindustry. Full article
(This article belongs to the Special Issue The Self-Assembly and Design of Polyfunctional Nanosystems)
15 pages, 2333 KiB  
Communication
KRASG12C Can Either Promote or Impair Cap-Dependent Translation in Two Different Lung Adenocarcinoma Cell Lines
by George Kyriakopoulos, Vicky Katopodi, Ilias Skeparnias, Eleni G. Kaliatsi, Katerina Grafanaki and Constantinos Stathopoulos
Int. J. Mol. Sci. 2021, 22(4), 2222; https://doi.org/10.3390/ijms22042222 - 23 Feb 2021
Cited by 3 | Viewed by 2980
Abstract
KRASG12C is among the most common oncogenic mutations in lung adenocarcinoma and a promising target for treatment by small-molecule inhibitors. KRAS oncogenic signaling is responsible for modulation of tumor microenvironment, with translation factors being among the most prominent deregulated targets. In the [...] Read more.
KRASG12C is among the most common oncogenic mutations in lung adenocarcinoma and a promising target for treatment by small-molecule inhibitors. KRAS oncogenic signaling is responsible for modulation of tumor microenvironment, with translation factors being among the most prominent deregulated targets. In the present study, we used TALENs to edit EGFRWT CL1-5 and A549 cells for integration of a Tet-inducible KRASG12C expression system. Subsequent analysis of both cell lines showed that cap-dependent translation was impaired in CL1-5 cells via involvement of mTORC2 and NF-κB. In contrast, in A549 cells, which additionally harbor the KRASG12S mutation, cap-dependent translation was favored via recruitment of mTORC1, c-MYC and the positive regulation of eIF4F complex. Downregulation of eIF1, eIF5 and eIF5B in the same cell line suggested a stringency loss of start codon selection during scanning of mRNAs. Puromycin staining and polysome profile analysis validated the enhanced translation rates in A549 cells and the impaired cap-dependent translation in CL1-5 cells. Interestingly, elevated translation rates were restored in CL1-5 cells after prolonged induction of KRASG12C through an mTORC1/p70S6K-independent way. Collectively, our results suggest that KRASG12C signaling differentially affects the regulation of the translational machinery. These differences could provide additional insights and facilitate current efforts to effectively target KRAS. Full article
(This article belongs to the Section Molecular Oncology)
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Figure 1

Figure 1
<p>Phenotypic characterization of A549 and CL1-5 KRAS<sup>G12C</sup> Tet-inducible stable cell lines. (<b>A</b>) Cell viability assay using ready resazurin solution and absorbance measurement at 570 nm and 600 nm before the addition of doxycycline (Off) and after short-term (72 h) and long-term (&gt;1 month) induction of KRAS<sup>G12C</sup> in A549 and CL1-5 cells. All levels are shown as a percentage (%) of relative viability as compared to the control (Off condition for both cases). (<b>B</b>) Cell proliferation assay using 0.2% crystal violet in 20% methanol and absorbance measurement at 590 nm before addition of doxycycline (Off) and after short-term (72 h) and long-term (&gt;1 month) induction of KRAS<sup>G12C</sup> in A549 and CL1-5 cells. All levels are shown as a percentage (%) of relative proliferation as compared to the control (Off condition for both cases). (<b>C</b>) Colony-formation assay before addition of doxycycline (Off) and after short-term (72 h) and long-term (&gt;1 month) induction of KRAS<sup>G12C</sup> in A549 and CL1-5 cells. All levels are shown as a percentage (%) of relative colony number as compared to the control (Off condition for both cases). (<b>D</b>) Wound healing assay before addition of doxycycline (Off) and after short-term (72 h) and long-term (&gt;1 month) induction of KRAS<sup>G12C</sup> in A549 at 12 h and 24 h and in CL1-5 cells at 24 h and 48 h following the wound procedure. Each time-point for each condition was compared to the initial wound at 0 h and the statistical analysis involved the comparison of On and long-term conditions with the Off condition. All levels are shown as a percentage (%) of wound closure as compared to the control (0 h). Data are compared by using unpaired Student’s <span class="html-italic">t</span>-test and are presented as means ± SD of biological triplicates. <span class="html-italic">P</span>-values are indicated with * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 2
<p>KRAS<sup>G12C</sup> differentially affects MAPK and PI3K/AKT/mTOR pathways effectors. (<b>A</b>) Immunoblot analysis of MAPK and PI3K/AKT/mTOR signaling effectors in A549 and CL1-5 cells before (Off) and after (On) KRAS<sup>G12C</sup> short-term induction with doxycycline. The protein levels were normalized against <span class="html-italic">β</span>-actin levels in each separate set of experiments. Band intensities are shown as a percentage (%) of relative protein levels as compared to the control (dotted line). Phosphorylation levels are shown as a ratio of phosphorylated to total relative protein levels, where indicated. (<b>B</b>) Immunoblot analysis of the IκB-α inhibitor of NF-κB in A549 and CL1-5 cells before (Off) and after (On) KRAS<sup>G12C</sup> short-term induction with doxycycline. The protein levels were normalized against <span class="html-italic">β</span>-actin levels in each separate set of experiments. Band intensities are shown as a percentage (%) of relative protein levels as compared to the control (dotted line). (<b>C</b>) Expression levels of miRNAs and <span class="html-italic">PTEN</span> gene as measured by RT-qPCR in A549 and CL1-5 cells before (Off) and after (On) KRAS<sup>G12C</sup> short-term induction with doxycycline. All levels are shown as relative expression compared to the control (dotted line) using the 2<sup>-ΔΔCt</sup> method. (<b>D</b>) Cumulative expression profile of all members of the let-7 family of miRNAs in A549 and CL1-5 cells before (Off) and after (On) KRAS<sup>G12C</sup> short-term induction with doxycycline (left panel). Expression levels of each member are also shown (right panel). All levels are shown as log2 fold change compared to the control (corresponding to 0 log2fold) using the -ΔΔCt method. Data are compared by using unpaired Student’s <span class="html-italic">t</span>-test and are presented as means ± SD of biological triplicates. P-values are indicated with * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 3
<p>KRAS<sup>G12C</sup> affects translation fidelity during mRNA scanning and cap-dependent translation initiation. (<b>A</b>) Immunoblot analysis of key translation initiation factors involved in the stringency of start codon selection during mRNA scanning in A549 and CL1-5 cells before (Off) and after (On) KRAS<sup>G12C</sup> short-term induction with doxycycline. The protein levels were normalized against <span class="html-italic">β</span>-actin levels in each separate set of experiments. Band intensities are shown as a percentage (%) of relative protein levels as compared to the control (dotted line). (<b>B</b>) Immunoblot analysis of key translation initiation factors that regulate global translation rates in A549 and CL1-5 cells before (Off) and after (On) KRAS<sup>G12C</sup> short-term induction with doxycycline. The protein levels were normalized against <span class="html-italic">β</span>-actin levels in each separate set of experiments. Band intensities are shown as a percentage (%) of relative protein levels as compared to the control (dotted line). Phosphorylation levels are shown as a ratio of phosphorylated to total relative protein levels. (<b>C</b>) Immunoblot analysis of c-MYC in A549 and CL1-5 cells before (Off) and after (On) KRAS<sup>G12C</sup> short-term induction with doxycycline. mRNA levels were identified by RT-qPCR and the relative protein levels were calculated after normalization against <span class="html-italic">β</span>-actin levels. Relative levels are shown as compared to the control (dotted line). Data are compared by using unpaired Student’s <span class="html-italic">t</span>-test and are presented as means ± SD of biological triplicates. <span class="html-italic">P</span>-values are indicated with * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 4
<p>KRAS<sup>G12C</sup> can either enhance or impair cap-dependent translation initiation. (<b>A</b>) Non-radioactive measurement of translation rates using puromycin staining of nascent peptides before addition of doxycycline (Off) and after short-term (72 h) and long-term (&gt;1 month) induction of KRAS<sup>G12C</sup> in A549 and CL1-5 cells. (<b>B</b>) Polysome profile analysis before addition of doxycycline (Off) and after short-term (72 h) and long-term (&gt;1 month) induction of KRAS<sup>G12C</sup> in CL1-5 cells analyzed on 15–50% sucrose density gradients upon treatment with cycloheximide. The peaks corresponding to ribosomal subunits (40S, 60S and 80S) and the polysomes tail are indicated. Relative polysome levels (%) were calculated by measuring the AUC on ImageJ (Fiji) and compared to the means AUC of the control triplicates. (<b>C</b>) Immunoblot analysis of key proteins involved in translation regulation in CL1-5 cells before addition of doxycycline (Off) and after short-term (72 h) and long-term (&gt;1 month) induction of KRAS<sup>G12C</sup> in CL1-5 cells. The protein levels were normalized against <span class="html-italic">β</span>-actin levels in each separate set of experiments. Band intensities are shown as a percentage (%) of relative protein levels as compared to the means values of the control triplicates. Phosphorylation levels are shown as a ratio of phosphorylated to total relative protein levels, where indicated. Data are compared by using unpaired Student’s <span class="html-italic">t</span>-test and are presented as means ± SD of biological triplicates. <span class="html-italic">P</span>-values are indicated with * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 5
<p>Schematic representation of the differential KRAS<sup>G12C</sup>-mediated oncogenic signaling and modulation of translation. (<b>A</b>) In A549 cells, expression of KRAS<sup>G12C</sup> mediates its oncogenic signaling through the MAPK and PI3K/AKT/mTORC1/p70S6K signaling pathways. Downstream targeting of 4E-BPs and eIF4E, along with the hypophosphorylation of the eIF2α subunit, leads to enhanced cap-dependent translation. Downregulation of eIF1, eIF5 and eIF5B is possibly associated with loss of translation fidelity during scanning of the mRNA, while recruitment of c-MYC, along with activated mTORC1, further promotes translation at the transcription level. All these events lead to promotion of translation and enhanced cell proliferation. (<b>B</b>) In CL1-5 cells, expression of KRAS<sup>G12C</sup> leads to activation of both MAPK and PI3K/AKT signaling pathways. PI3K axis activation is further enhanced by targeting of tumor-suppressor <span class="html-italic">PTEN</span> by miRNAs, while the tumor-suppressor let-7 family of miRNAs is upregulated due to a possible stress response mechanism. Interestingly, mTORC2 formation is promoted and is possibly correlated with the activation of NF-κB. Downstream transcriptional and translational events, with participation of unidentified effectors, which could involve the ERK1/2-targeted RSK (Ribosomal S6 Kinase), along with the hypophosphorylation of both p70S6K and eIF4E, lead to impairment of cap-dependent translation.</p> Full article ">
11 pages, 1678 KiB  
Communication
Alternative to Poly(2-isopropyl-2-oxazoline) with a Reduced Ability to Crystallize and Physiological LCST
by Wojciech Wałach, Agnieszka Klama-Baryła, Anna Sitkowska, Agnieszka Kowalczuk and Natalia Oleszko-Torbus
Int. J. Mol. Sci. 2021, 22(4), 2221; https://doi.org/10.3390/ijms22042221 - 23 Feb 2021
Cited by 11 | Viewed by 2315
Abstract
In this work, we sought to examine whether the presence of alkyl substituents randomly distributed within the main chain of a 2-isopropyl-2-oxazoline-based copolymer will decrease its ability to crystallize when compared to its homopolymer. At the same time, we aimed to ensure an [...] Read more.
In this work, we sought to examine whether the presence of alkyl substituents randomly distributed within the main chain of a 2-isopropyl-2-oxazoline-based copolymer will decrease its ability to crystallize when compared to its homopolymer. At the same time, we aimed to ensure an appropriate hydrophilic/lipophilic balance in the copolymer and maintain the phase transition in the vicinity of the human body temperature. For this reason, copolymers of 2-ethyl-4-methyl-2-oxazoline and 2-isopropyl-2-oxazoline were synthesized. The thermoresponsive behavior of the copolymers in water, the influence of salt on the cloud point, the presence of hysteresis of the phase transition and the crystallization ability in a water solution under long-term heating conditions were studied by turbidimetry. The ability of the copolymers to crystallize in the solid state, and their thermal properties, were analyzed by differential scanning calorimetry and X-ray diffractometry. A cytotoxicity assay was used to estimate the viability of human fibroblasts in the presence of the obtained polymers. The results allowed us to demonstrate a nontoxic alternative to poly(2-isopropyl-2-oxazoline) (PiPrOx) with a physiological phase transition temperature (LCST) and a greatly reduced tendency to crystallize. The synthesis of 2-oxazoline polymers with such well-defined properties is important for future biomedical applications. Full article
(This article belongs to the Section Macromolecules)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>The 2-Oxazoline polymerization scheme.</p> Full article ">Figure 2
<p>Structure of the copolymers of 2-ethyl-4-methyl-2-oxazoline (EtMetOx) and 2-isopropyl-2-oxazoline (iPrOx).</p> Full article ">Figure 3
<p>(<b>a</b>) Plot of T<sub>CP</sub> as a function of the P(EtMetOx<sub>10</sub>-iPrOx<sub>90</sub>) concentration, (<b>b</b>) transmittance-temperature dependence of the aqueous solution of the copolymer (c = 5 g L<sup>−1</sup>), (<b>c</b>) plot of T<sub>CP</sub> as a function of the NaCl concentration (the copolymer concentration in water is 5 g L<sup>−1</sup>) and (<b>d</b>) transmittance-temperature dependence of the aqueous solution of the copolymer (c = 5 g L<sup>−1</sup>) kept for 12 h at 50 °C before cooling.</p> Full article ">Figure 4
<p>(<b>a</b>) DSC traces and (<b>b</b>) X-ray diffraction curve of P(EtMetOx<sub>10</sub>-iPrOx<sub>90</sub>).</p> Full article ">Figure 5
<p>Structure of the copolymer of 2-ethyl-2-oxazoline (EtOx) and iPrOx.</p> Full article ">Figure 6
<p>(<b>a</b>) DSC traces and (<b>b</b>) X-ray diffraction curve of P(EtOx<sub>14</sub>-iPrOx<sub>86</sub>).</p> Full article ">Figure 7
<p>Cytotoxicity assay of P(EtMetOx<sub>50</sub>-iPrOx<sub>50</sub>) at increasing concentrations (given in mg/mL). The assay was performed with fibroblasts. The results are shown as a percentage of the control, where untreated cells constituted 100%.</p> Full article ">
16 pages, 2171 KiB  
Article
Structural Determinants of Substrate Specificity of SplF Protease from Staphylococcus aureus
by Natalia Stach, Abdulkarim Karim, Przemyslaw Golik, Radoslaw Kitel, Katarzyna Pustelny, Natalia Gruba, Katarzyna Groborz, Urszula Jankowska, Sylwia Kedracka-Krok, Benedykt Wladyka, Marcin Drag, Adam Lesner and Grzegorz Dubin
Int. J. Mol. Sci. 2021, 22(4), 2220; https://doi.org/10.3390/ijms22042220 - 23 Feb 2021
Cited by 7 | Viewed by 2798
Abstract
Accumulating evidence suggests that six proteases encoded in the spl operon of a dangerous human pathogen, Staphylococcus aureus, may play a role in virulence. Interestingly, SplA, B, D, and E have complementary substrate specificities while SplF remains to be characterized in this [...] Read more.
Accumulating evidence suggests that six proteases encoded in the spl operon of a dangerous human pathogen, Staphylococcus aureus, may play a role in virulence. Interestingly, SplA, B, D, and E have complementary substrate specificities while SplF remains to be characterized in this regard. Here, we describe the prerequisites of a heterologous expression system for active SplF protease and characterize the enzyme in terms of substrate specificity and its structural determinants. Substrate specificity of SplF is comprehensively profiled using combinatorial libraries of peptide substrates demonstrating strict preference for long aliphatic sidechains at the P1 subsite and significant selectivity for aromatic residues at P3. The crystal structure of SplF was provided at 1.7 Å resolution to define the structural basis of substrate specificity of SplF. The obtained results were compared and contrasted with the characteristics of other Spl proteases determined to date to conclude that the spl operon encodes a unique extracellular proteolytic system. Full article
(This article belongs to the Section Biochemistry)
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Figure 1

Figure 1
<p>Substrate specificity of SplF protease at the P1 subsite. Substrate preference of SplF at the P1 subsite was determined using two fluorogenic substrate libraries: Ac-Ala-Arg-Leu-P1-ACC and Ac-Leu-Arg-Ser-P1-ACC. Vertical bars indicate the activity of the enzyme against each tested sublibrary normalized to the most active sublibrary. Residues fixed at the P1 subsite are indicated with the single-letter amino acid code.</p> Full article ">Figure 2
<p>Substrate specificity of SplF determined using combinatorial libraries of synthetic tetrapeptide substrates (LSTS). A library of a general structure Abz-X4-X3-X2-X1-Anb containing 19 sublibraries each having a defined proteinogenic amino acid at the X4 position (X-axis) and an equimolar mixture of these residues at other positions was contacted with SplF and the release of fluorescence was monitored (Y-axis, normalized to the most active sublibrary). X4 position was fixed with the most active residue and X3 scanning was performed in a similar manner. The procedure was repeated until all positions of the library were deconvoluted, yielding a consensus substrate Abz-Tyr-Met-Leu-Ser-Anb.</p> Full article ">Figure 3
<p>Model of consensus substrate recognition by SplF protease. (<b>A</b>) The overall orientation of the substrate (green) backbone was modeled based on the crystal structure of substrate mimetic inhibitors in complex with trypsin. The positions of the sidechains were adjusted by energy minimization. SplF (gray) residues involved in active site formation are highlighted in the stick model and labeled. (<b>B</b>) Schematic representation of substrate (black line)–enzyme (gray line) interaction. Hydrogen bonds are shown as dashed lines. Ring stacking is indicated. The enzyme residues involved in hydrophobic interaction are indicated by dashed ovals.</p> Full article ">Figure 4
<p>S1 specificity pockets of Spl proteases in the context of their substrate specificities. (<b>A</b>) The residues defining the S1 pocket of SplF (PDB 6SF7, yellow) are overlaid on relevant pockets of other proteases of the <span class="html-italic">spl</span> operon: SplA (PDB 2W7S, red) [<a href="#B13-ijms-22-02220" class="html-bibr">13</a>], SplB (PDB 2VID, orange) [<a href="#B14-ijms-22-02220" class="html-bibr">14</a>], SplC (PDB 2AS9, cyan) [<a href="#B17-ijms-22-02220" class="html-bibr">17</a>] and SplD (PDB 4INK, blue) [<a href="#B15-ijms-22-02220" class="html-bibr">15</a>] and SplE (PDB 5MM8, green) [<a href="#B16-ijms-22-02220" class="html-bibr">16</a>]. Catalytic triad residues are highlighted grey. Residues exposed at the S1 pocket and thus of direct significance in specificity determination are shown in stick model and colored according to the compared proteases. See <a href="#app1-ijms-22-02220" class="html-app">Figure S4</a> for broader overview of the binding cleft in compared enzymes. (<b>B</b>) Consensus sequences recognized and cleaved by Spl proteases characterized to date.</p> Full article ">
15 pages, 3347 KiB  
Article
Runx3 Induces a Cell Shape Change and Suppresses Migration and Metastasis of Melanoma Cells by Altering a Transcriptional Profile
by Ning Wang, Haiying Zhang, Xiulin Cui, Chao Ma, Linghui Wang and Wenguang Liu
Int. J. Mol. Sci. 2021, 22(4), 2219; https://doi.org/10.3390/ijms22042219 - 23 Feb 2021
Cited by 4 | Viewed by 2804
Abstract
Runt-related transcription factor-3 (Runx3) is a tumor suppressor, and its contribution to melanoma progression remains unclear. We previously demonstrated that Runx3 re-expression in B16-F10 melanoma cells changed their shape and attenuated their migration. In this study, we found that Runx3 re-expression in B16-F10 [...] Read more.
Runt-related transcription factor-3 (Runx3) is a tumor suppressor, and its contribution to melanoma progression remains unclear. We previously demonstrated that Runx3 re-expression in B16-F10 melanoma cells changed their shape and attenuated their migration. In this study, we found that Runx3 re-expression in B16-F10 cells also suppressed their pulmonary metastasis. We performed microarray analysis and uncovered an altered transcriptional profile underlying the cell shape change and the suppression of migration and metastasis. This altered transcriptional profile was rich in Gene Ontology/Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) annotations relevant to adhesion and the actin cytoskeleton and included differentially expressed genes for some major extracellular matrix (ECM) proteins as well as genes that were inversely associated with the increase in the metastatic potential of B16-F10 cells compared to B16-F0 melanoma cells. Further, we found that this altered transcriptional profile could have prognostic value, as evidenced by myelin and lymphocyte protein (MAL) and vilin-like (VILL). Finally, Mal gene expression was correlated with metastatic potential among the cells and was targeted by histone deacetylase (HDAC) inhibitors in B16-F10 cells, and the knockdown of Mal gene expression in B16-F0 cells changed their shape and enhanced the migratory and invasive traits of their metastasis. Our study suggests that self-entrapping of metastatic Runx3-negative melanoma cells via adhesion and the actin cytoskeleton could be a powerful therapeutic strategy. Full article
(This article belongs to the Section Molecular Oncology)
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<p>Runt-related transcription factor-3 (Runx3) re-expression in B16-F10 melanoma cells resulted in a cell shape change and suppressed the pulmonary metastasis of the cells. (<b>A</b>) Runx3 changed the cell shape and altered the actin cytoskeleton. The green fluorescent signals indicate actin filaments. (<b>B</b>) Runx3 delayed cell migration, and altered the dynamics of stress fiber formation in the migrating cells. <span class="html-italic">Start</span> denotes when the wound is just made, and <span class="html-italic">end</span> denotes when wound healing is terminated. The green fluorescent signals indicate actin filaments. The arrows indicate the directions of migration fronts. The arrowheads indicate the ends of stress fibers. The thin arrows indicate microspike-like structures. (<b>C</b>) Runx3 completely suppressed pulmonary metastasis. <span class="html-italic">n</span> = 4. The black dots on the surface of the lungs indicate metastasis foci. The windows-arrows representatively indicate metastasis foci. (<b>D</b>) Runx3 slightly reduced the tumor formation rate. The averaged tumor volumes are compared to each other (mean ± SEM, <span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05 is generated by the <span class="html-italic">t</span>-test. A representative image is shown. Bar: 1 cm. (<b>E</b>) Runx3 changed the cell shape in vivo. A representative section is shown. Ctrl: mock control B16-F10 cells; Runx3: B16-F10/Runx3 cells. All bars: 22 μm.</p> Full article ">Figure 2
<p>Microarray analysis uncovered an altered and specific transcriptional profile underlying the cell shape change and the suppression of the metastatic potential by Runx3. (<b>A</b>) Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations assigned different repertoires of differentially expressed genes (DEGs) that were regulated by Runx3 in B16-F10 cells and, in the case of B16-F0 cells vs. B16-F10 cells, to the terms relevant to the actin cytoskeleton and adhesion. Each GO/KEGG annotation term is inscribed as a caption. The number of DEGs within a repertoire is described at x axis. The columns for the downregulated and the upregulated DEGs are shown in different colors as explained at the top of the figure., <span class="html-italic">Down/Up by Runx3</span> indicates the appearance of DEGs in the case of B16-F10/Runx3 cells vs. mock control B16-F10 cells. <span class="html-italic">Down/Up in B16-F0</span> indicates the appearance of DEGs in the case of B16-F0 cells vs. B16-F10 cells. <span class="html-italic">Down/Up in common</span> indicates the appearance of same DEGs in both cases. (<b>B</b>) Runx3 upregulated the expression of extracellular matrix (ECM) genes. The summary table indicates the gene names and their corresponding fold changes. (<b>C</b>) Runx3 regulated the expression of a list of DEGs that were inversely associated with an increase in the metastatic potential of B16-F10 cells compared to B16-F0 cells. The heatmap shows the gene names and their fold changes in the cases of B16-F10/Runx3 cells vs. mock control B16-F10 cells and B16-F0 cells vs. B16-F10 cells, respectively.</p> Full article ">Figure 3
<p>The gene expression of myelin and lymphocyte protein (<span class="html-italic">MAL</span>) and/or vilin-like (<span class="html-italic">VILL</span>) had prognostic value for various cancers. (<b>A</b>) Kaplan–Meier survival analysis implicated <span class="html-italic">MAL</span> or <span class="html-italic">VILL</span> in various cancers. (<b>B</b>) Kaplan–Meier survival analysis implicated both <span class="html-italic">MAL</span> and <span class="html-italic">VILL</span> in various cancers. The information about cancer type, patient number, and <span class="html-italic">p</span>-value is inscribed at each panel. The gene level was defined as fragments per kilobase of exon per million reads (FPKM). The median cutoff was used to group patients into low (L) and high (H) expression of <span class="html-italic">MAL</span> and/or <span class="html-italic">VILL</span>. The <span class="html-italic">p</span>-values are generated by the log-rank test.</p> Full article ">Figure 4
<p><span class="html-italic">Mal</span> gene expression was correlated with metastatic potential among the cell lines and was subject to epigenetic regulation. (<b>A</b>) <span class="html-italic">Mal</span> gene expression was validated in the cells used in this study with qRT-PCR. The relative <span class="html-italic">Mal</span> gene expression levels were compared among the indicated cell lines (means ± SEM, <span class="html-italic">n</span> = 3). (<b>B</b>) Treatment with histone deacetylase (HDAC) inhibitors induced the gene expression of <span class="html-italic">Mal</span> in B16-F10 cells. The relative <span class="html-italic">Mal</span> gene expression levels of inhibitor-treated cells were compared to those of untreated (DMSO) cells (means ± SEM, <span class="html-italic">n</span> = 3). (<b>C</b>) The gene expression of <span class="html-italic">MAL</span> was correlated with that of other genes in human melanoma. The top left panel indicates the overall <span class="html-italic">MAL</span> correlation. The other panels indicate the correlation between <span class="html-italic">MAL</span> and the other genes. The information about patient number and <span class="html-italic">p</span>-value is inscribed at each panel. The gene level at <span class="html-italic">x</span>/<span class="html-italic">y</span> axis is defined from FPKM. The <span class="html-italic">p</span>-values are generated by the Spearman correlation test. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 are generated by the <span class="html-italic">t</span>-test.</p> Full article ">Figure 5
<p>Mal was necessary for suppressing the migratory and invasive traits of metastatic melanoma cells. (<b>A</b>) The knockdown of <span class="html-italic">Mal</span> gene expression was validated with qRT-PCR and Western blotting. The relative <span class="html-italic">Mal</span> gene expression levels are compared to each other (means ± SEM, <span class="html-italic">n</span> = 3). Mal’s molecular weight: 18 kDa; actin’s molecular weight: 43 kDa. (<b>B</b>) The knockdown of <span class="html-italic">Mal</span> gene expression changed the cell shape and altered the actin cytoskeleton of steady or migrating cells. The green fluorescent signals indicate actin filaments. The arrows indicate the directions of migration fronts. The thin arrows indicate microspike-like structures. Bars: 22 μm. (<b>C</b>) The knockdown of <span class="html-italic">Mal</span> gene expression slightly reduced the proliferation rate. The relative proliferation rates were determined by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) and were compared to each other (means ± SEM, <span class="html-italic">n</span> = 3). (<b>D</b>) The knockdown of <span class="html-italic">Mal</span> gene expression slightly delayed the progress of the cell cycle. The percentages of cells at various phases (G0/G1, S, and G2/M) were determined by flow cytometry (means ± SEM, <span class="html-italic">n</span> = 3, ns: not significant). (<b>E</b>) The knockdown of <span class="html-italic">Mal</span> gene expression had no effect on the tumor formation rate. The averaged tumor volumes were compared to each other (means ± SEM, <span class="html-italic">n</span> = 4, ns: not significant). (<b>F</b>) The knockdown of <span class="html-italic">Mal</span> gene expression increased the migration rate in wound healing. The relative scratch open areas were compared to each other (means ± SEM, <span class="html-italic">n</span> = 3). (<b>G</b>) The knockdown of <span class="html-italic">Mal</span> gene expression increased the migration rate through the Transwell chambers. A representative image is shown on the left of the panel, and the averaged cell numbers were compared to each other, as shown on the right (means ± SEM, <span class="html-italic">n</span> = 6). (<b>H</b>) The knockdown of <span class="html-italic">Mal</span> gene expression increased the invasion rate through Matrigel-coated Transwell chambers. A representative image is shown on the left of the panel, and the averaged cell numbers were compared to each other, as shown on the right (means ± SEM, <span class="html-italic">n</span> = 6). (<b>I</b>) The knockdown of <span class="html-italic">Mal</span> gene expression increased the frequency of metastasis-focus-positive lungs. A representative image is shown. The arrowheads indicate metastasis foci. The frequencies are inscribed at the top of the image. Ctrl: mock control; shMal: short hairpin RNA interference of <span class="html-italic">Mal</span>. * <span class="html-italic">p</span> &lt; 0.05 and ** <span class="html-italic">p</span> &lt; 0.01 are generated by the <span class="html-italic">t</span>-test.</p> Full article ">
13 pages, 1433 KiB  
Review
Chemistry and Toxicology of Major Bioactive Substances in Inocybe Mushrooms
by Jiri Patocka, Ran Wu, Eugenie Nepovimova, Martin Valis, Wenda Wu and Kamil Kuca
Int. J. Mol. Sci. 2021, 22(4), 2218; https://doi.org/10.3390/ijms22042218 - 23 Feb 2021
Cited by 31 | Viewed by 6779
Abstract
Mushroom poisoning has always been a threat to human health. There are a large number of reports about ingestion of poisonous mushrooms every year around the world. It attracts the attention of researchers, especially in the aspects of toxin composition, toxic mechanism and [...] Read more.
Mushroom poisoning has always been a threat to human health. There are a large number of reports about ingestion of poisonous mushrooms every year around the world. It attracts the attention of researchers, especially in the aspects of toxin composition, toxic mechanism and toxin application in poisonous mushroom. Inocybe is a large genus of mushrooms and contains toxic substances including muscarine, psilocybin, psilocin, aeruginascin, lectins and baeocystin. In order to prevent and remedy mushroom poisoning, it is significant to clarify the toxic effects and mechanisms of these bioactive substances. In this review article, we summarize the chemistry, most known toxic effects and mechanisms of major toxic substances in Inocybe mushrooms, especially muscarine, psilocybin and psilocin. Their available toxicity data (different species, different administration routes) published formerly are also summarized. In addition, the treatment and medical application of these toxic substances in Inocybe mushrooms are also discussed. We hope that this review will help understanding of the chemistry and toxicology of Inocybe mushrooms as well as the potential clinical application of its bioactive substances to benefit human beings. Full article
(This article belongs to the Special Issue Natural and Synthetic Toxins: Molecular Aspects and Development Treatment Strategy)
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<p><span class="html-italic">Inocybe</span> mushrooms.</p> Full article ">Figure 2
<p><span class="html-italic">Inocybe erubescens</span>, the most common <span class="html-italic">Inocybe</span> species associated with toxicity in Europe.</p> Full article ">Figure 3
<p>Structures of compounds isolated from the mushrooms of the genus <span class="html-italic">Inocybe</span>: I. muscarine; II. psilocin; III. psilocybin; IV. aeruginascin and V. baeocystin.</p> Full article ">Figure 4
<p>Four stereoisomers of muscarinee: I. muscarine; II.epi-muscarinee; III. allo-muscarinee and IV. epiallo-muscarinee.</p> Full article ">
15 pages, 1867 KiB  
Review
The Multifaceted Role of CMA in Glioma: Enemy or Ally?
by Alessia Lo Dico, Cristina Martelli, Cecilia Diceglie and Luisa Ottobrini
Int. J. Mol. Sci. 2021, 22(4), 2217; https://doi.org/10.3390/ijms22042217 - 23 Feb 2021
Cited by 7 | Viewed by 3653
Abstract
Chaperone-mediated autophagy (CMA) is a catabolic pathway fundamental for cell homeostasis, by which specific damaged or non-essential proteins are degraded. CMA activity has three main levels of regulation. The first regulatory level is based on the targetability of specific proteins possessing a KFERQ-like [...] Read more.
Chaperone-mediated autophagy (CMA) is a catabolic pathway fundamental for cell homeostasis, by which specific damaged or non-essential proteins are degraded. CMA activity has three main levels of regulation. The first regulatory level is based on the targetability of specific proteins possessing a KFERQ-like domain, which can be recognized by specific chaperones and delivered to the lysosomes. Target protein unfolding and translocation into the lysosomal lumen constitutes the second level of CMA regulation and is based on the modulation of Lamp2A multimerization. Finally, the activity of some accessory proteins represents the third regulatory level of CMA activity. CMA’s role in oncology has not been fully clarified covering both pro-survival and pro-death roles in different contexts. Taking all this into account, it is possible to comprehend the actual complexity of both CMA regulation and the cellular consequences of its activity allowing it to be elected as a modulatory and not only catabolic machinery. In this review, the role covered by CMA in oncology is discussed with a focus on its relevance in glioma. Molecular correlates of CMA importance in glioma responsiveness to treatment are described to identify new early efficacy biomarkers and new therapeutic targets to overcome resistance. Full article
(This article belongs to the Special Issue Microautophagy)
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<p>Schematic representation of the multi-level CMA (chaperone-mediated autophagy) regulation machinery. <b>Panel 1:</b> The first regulatory level is based on the availability and accessibility of the KFERQ motif. Non-canonical motifs can be modified to be recognized by chaperone proteins. HSC70 chaperone delivers specific proteins to the lysosome. <b>Panel 2:</b> The second regulatory level depends on LAMP-2A quaternary structure. Its trafficking in the lysosomal membrane is finely regulated. Moreover, unphosphorylated GFAP (GFAP) stabilizes the LAMP-2A multimer, favoring the translocation of unfolded proteins within the lysosomes. When GFAP is present in its phosphorylated form (GFAP-P), it interacts with EF-1α, determining the disassembling of LAMP-2A multimers. In addition, LAMP-2A de novo expression can be regulated by the transcription factor NRF-2. <b>Panel 3:</b> The third regulatory level is due to the availability of accessory proteins among which the main regulator is PHLPP1. It is a phosphatase influencing the activity of other proteins. Rac-1 bound to PHLPP1 favors its activity on AKT. Inactive AKT is not able to phosphorylate GFAP allowing LAMP-2A multimer stabilization.</p> Full article ">Figure 2
<p>General scheme of the mechanism of action of temozolomide. TMZ (temozolomide) can induce different events. On one hand, it methylates DNA forming N7-methylguanine (N7-meG) and N3-methyladenine (N3-meA), and less frequently, O6-methylguanine. DNA methylation induces the DNA mismatch repair (MMR) system that cannot remove the O6MG, creating futile cycles of mismatch and repair and generating DNA single- and double-strand breaks. Finally, stalled replication forks appear, and the cell cycle is blocked. All these events induce cell death through the activation of apoptosis, senescence, and mitotic catastrophe. On the other hand, TMZ can induce endoplasmic reticulum stress with consequent mitochondrial membrane depolarization and release of reactive oxygen species (ROS) in the cytoplasm. ROS release is associated with the induction of CMA activity, which in turn concurs to cell death.</p> Full article ">
13 pages, 2613 KiB  
Article
Targeting lncRNA H19/miR-29b/COL1A1 Axis Impedes Myofibroblast Activities of Precancerous Oral Submucous Fibrosis
by Cheng-Chia Yu, Yi-Wen Liao, Pei-Ling Hsieh and Yu-Chao Chang
Int. J. Mol. Sci. 2021, 22(4), 2216; https://doi.org/10.3390/ijms22042216 - 23 Feb 2021
Cited by 34 | Viewed by 3285
Abstract
Oral submucous fibrosis (OSF) is known as a potentially malignant disorder, which may result from chemical irritation due to areca nuts (such as arecoline). Emerging evidence suggests that fibrogenesis and carcinogenesis are regulated by the interaction of long noncoding RNAs (lncRNAs) and microRNAs. [...] Read more.
Oral submucous fibrosis (OSF) is known as a potentially malignant disorder, which may result from chemical irritation due to areca nuts (such as arecoline). Emerging evidence suggests that fibrogenesis and carcinogenesis are regulated by the interaction of long noncoding RNAs (lncRNAs) and microRNAs. Among these regulators, profibrotic lncRNA H19 has been found to be overexpressed in several fibrosis diseases. Here, we examined the expression of H19 in OSF specimens and its functional role in fibrotic buccal mucosal fibroblasts (fBMFs). Our results indicate that the aberrantly overexpressed H19 contributed to higher myofibroblast activities, such as collagen gel contractility and migration ability. We also demonstrated that H19 interacted with miR-29b, which suppressed the direct binding of miR-29b to the 3′-untranslated region of type I collagen (COL1A1). We showed that ectopic expression of miR-29b ameliorated various myofibroblast phenotypes and the expression of α-smooth muscle actin (α-SMA), COL1A1, and fibronectin (FN1) in fBMFs. In OSF tissues, we found that the expression of miR-29b was downregulated and there was a negative correlation between miR-29b and these fibrosis markers. Lastly, we demonstrate that arecoline stimulated the upregulation of H19 through the transforming growth factor (TGF)-β pathway. Altogether, this study suggests that increased TGF-β secretion following areca nut chewing may induce the upregulation of H19, which serves as a natural sponge for miR-29b and impedes its antifibrotic effects. Full article
(This article belongs to the Special Issue Oral Fibrosis and Oral Cancer: From Molecular Targets to Therapeutics)
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<p>The expression of <span class="html-italic">H19</span> is aberrantly upregulated in oral submucous fibrosis (OSF) tissues. (<b>A</b>) Heatmap representation of differentially expressed genes between normal (<span class="html-italic">n</span> = 2) and OSF tissues (<span class="html-italic">n</span> = 2). ** <span class="html-italic">p</span> &lt; 0.01 (<b>B</b>) qRT-PCR analysis showing lncRNA expression of <span class="html-italic">H19</span> in normal (<span class="html-italic">n</span> = 20; blue dots) and OSF tissues (<span class="html-italic">n</span> = 20; red dots). (<b>C</b>) Positive correlation between myofibroblast marker smooth muscle actin (SMA) and <span class="html-italic">H19</span> in OSF tissues (blue dots). (<b>D</b>) RT-PCR analysis of the expression level of <span class="html-italic">H19</span> in fBMFs (fibrotic buccal mucosal fibroblasts) and BMFs (buccal mucosal fibroblasts) extracted from OSF and normal counterparts, respectively; ** <span class="html-italic">p</span> &lt; 0.01 compared with normal BMFs. (<b>E</b>) Knockdown efficiency of lentivirus-mediated short hairpin RNA (shRNA) targeting <span class="html-italic">H19</span> in two patient-derived fibrotic buccal mucosal fibroblasts (fBMFs). * <span class="html-italic">p</span> &lt; 0.05 compared to sh-Luc (luciferase).</p> Full article ">Figure 2
<p>Downregulation of <span class="html-italic">H19</span> suppresses the phenotypes of myofibroblasts. (<b>A</b>) <span class="html-italic">H19</span>-silenced fBMFs were embedded into collagen gels. After 48 h, the contraction of gels was photographed, and the gel areas were calculated using Image J software v.1.8 (National Institutes of Health, Bethesda, Maryland, USA). (<b>B</b>) A Transwell migration assay was conducted to examine the effect of <span class="html-italic">H19</span> knockdown on migration ability after 24 h of incubation. Magnification, 100×. * <span class="html-italic">p</span> &lt; 0.05 compared to sh-Luc.</p> Full article ">Figure 3
<p>Repression of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> by <span class="html-italic">H19</span> results in upregulation of type I collagen. (<b>A</b>) Schematic of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> and the putative binding sequence, as well as the mutant sequence at the 3’-untranslated region (3′UTR) of <span class="html-italic">H19</span>. (<b>B</b>) Luciferase activity decreased when fBMFs were cotransfected with <span class="html-italic">Wt</span>-<span class="html-italic">H19</span> and <span class="html-italic">miR</span>-<span class="html-italic">29b</span> mimics. (<b>C</b>) Relative expression of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> in <span class="html-italic">H19</span>-silenced fBMFs. Collagen gel contraction (<b>D</b>) and migration ability (<b>E</b>) of BMFs with <span class="html-italic">miR</span>-<span class="html-italic">29b</span> inhibitor or miR-Scr (scramble). Magnification, 100× (<b>F</b>) Schematic of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> and the putative binding sequence in the 3′UTR sequence of Wt-COL1A1 and mutant sequence. (<b>G</b>) Luciferase activity was decreased when fBMFs were cotransfected with Wt-COL1A1 and <span class="html-italic">miR</span>-<span class="html-italic">29b</span> mimics. (<b>H</b>) Protein expression of type I collagen in BMFs with or without sh-Luc, <span class="html-italic">sh</span>-<span class="html-italic">H19</span>, miR-Scr, and <span class="html-italic">miR</span>-<span class="html-italic">29b</span> inhibitor. * <span class="html-italic">p</span> &lt; 0.05 compared to miR-Scr.</p> Full article ">Figure 4
<p>Overexpression of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> mitigates the features of myofibroblasts. (<b>A</b>) Collagen gel contraction and (<b>B</b>) migration ability of fBMFs with miR-Scr or <span class="html-italic">miR</span>-<span class="html-italic">29b</span> mimics. Magnification, 100× (<b>C</b>) Relative expression of SMA, type I collagen, and fibronectin (FN1) in fBMFs with miR-Scr or <span class="html-italic">miR</span>-<span class="html-italic">29b</span> mimics. (<b>D</b>) Wound healing capacity of BMFs, fBMFs with miR-Scr, or fBMFs with <span class="html-italic">miR</span>-<span class="html-italic">29b</span> mimics. Magnification, 100×, * <span class="html-italic">p</span> &lt; 0.05 compared to miR-Scr.</p> Full article ">Figure 5
<p>The expression of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> is diminished in OSF and inversely associated with fibrosis markers. (<b>A</b>) Gene expression of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> in OSF (red dots) and normal tissues (<span class="html-italic">n</span> = 20; blue dots). <span class="html-italic">** p</span> &lt; 0.01 (<b>B</b>) Relative expression of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> in BMFs and fBMFs derived from OSF specimens (<span class="html-italic">n</span> = 5). <span class="html-italic">** p</span> &lt; 0.01 The expression of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> was negatively correlated with (<b>C</b>) α-SMA and (<b>D</b>) FN1 expression in OSF tissues (blue dots) <span class="html-italic">** p</span> &lt; 0.01.</p> Full article ">Figure 6
<p>Arecoline increased the expression of <span class="html-italic">H19</span> through transforming growth factor (TGF)-β1. (<b>A</b>) The expression of <span class="html-italic">H19</span> was increased following arecoline stimulation in a dose-dependent manner. (<b>B</b>) Relative expression of <span class="html-italic">H19</span> in BMFs treated with arecoline, TGF-β1, or SB431542 (a specific inhibitor of the TGF-β type I receptor). * <span class="html-italic">p</span> &lt; 0.05 compared to no treatment. # <span class="html-italic">p</span> &lt; 0.05 compared to arecoline treatment. (<b>C</b>) Western blotting analysis describing the expression levels of COLA1 with indicated transfections.</p> Full article ">Figure 7
<p>Possible mechanism for the areca nut-associated OSF. This study connects current knowledge and demonstrates that the upregulation of TGF-β by arecoline stimulation induces the expression of lncRNA <span class="html-italic">H19</span>, which sequesters <span class="html-italic">miR</span>-<span class="html-italic">29b</span> and impedes its binding of type 1 collagen 1. Moreover, suppression of the inhibitory effect of <span class="html-italic">miR</span>-<span class="html-italic">29b</span> on various fibrosis markers (such as type 1 collagen 1, α-smooth muscle actin, and fibronectin) results in transdifferentiation of buccal mucosal fibroblasts into myofibroblasts.</p> Full article ">
12 pages, 1356 KiB  
Article
GBA Mutations Influence the Release and Pathological Effects of Small Extracellular Vesicles from Fibroblasts of Patients with Parkinson’s Disease
by Silvia Cerri, Cristina Ghezzi, Gerardo Ongari, Stefania Croce, Micol Avenali, Roberta Zangaglia, Donato A. Di Monte, Enza Maria Valente and Fabio Blandini
Int. J. Mol. Sci. 2021, 22(4), 2215; https://doi.org/10.3390/ijms22042215 - 23 Feb 2021
Cited by 20 | Viewed by 3788
Abstract
Heterozygous mutations in the GBA gene, encoding the lysosomal enzyme glucocerebrosidase (GCase), are the strongest known genetic risk factor for Parkinson’s disease (PD). The molecular mechanisms underlying the increased PD risk and the variable phenotypes observed in carriers of different GBA mutations are [...] Read more.
Heterozygous mutations in the GBA gene, encoding the lysosomal enzyme glucocerebrosidase (GCase), are the strongest known genetic risk factor for Parkinson’s disease (PD). The molecular mechanisms underlying the increased PD risk and the variable phenotypes observed in carriers of different GBA mutations are not yet fully elucidated. Extracellular vesicles (EVs) have gained increasing importance in neurodegenerative diseases since they can vehiculate pathological molecules potentially promoting disease propagation. Accumulating evidence showed that perturbations of the endosomal–lysosomal pathway can affect EV release and composition. Here, we investigate the impact of GCase deficiency on EV release and their effect in recipient cells. EVs were purified by ultracentrifugation from the supernatant of fibroblast cell lines derived from PD patients with or without GBA mutations and quantified by nanoparticle tracking analysis. SH-SY5Y cells over-expressing alpha-synuclein (α-syn) were used to assess the ability of patient-derived small EVs to affect α-syn expression. We observed that defective GCase activity promotes the release of EVs, independently of mutation severity. Moreover, small EVs released from PD fibroblasts carrying severe mutations increased the intra-cellular levels of phosphorylated α-syn. In summary, our work shows that the dysregulation of small EV trafficking and alpha-synuclein mishandling may play a role in GBA-associated PD. Full article
(This article belongs to the Special Issue Role and Dynamics of Extracellular Vesicles in Central Nervous System Diseases)
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<p>Assessment of EV release and lysosomal alterations in fibroblast cell cultures. (<b>A</b>,<b>B</b>) EVs were isolated by sequential centrifugation from surnatant of fibroblasts from non-mutated (NM-PD) and GBA-mutated (GBA-PD) PD patients, carrying mild (N370S) or severe (L444P) mutations, and healthy subjects (HC). Nanoparticle tracking analysis was used to determine the concentration of (<b>A</b>) medium and (<b>B</b>) small EV released. Data were expressed as number of vesicles secreted per cell. (<b>C</b>–<b>E</b>) Evaluation of (<b>C</b>) glucocerebrosidase and (<b>D</b>) cathepsin D (CathD) activity by fluorimetric assay, and (<b>E</b>) Western blot analysis of pro-CathD and mature CathD (mCathD) levels. The ratio between pro/mCathD was also reported in the bar graph. All data were expressed as mean ± SEM of three independent experiments (<span class="html-italic">n</span> = 2 for cathepsin D turnover).</p> Full article ">Figure 2
<p>Inducible α-syn expression in differentiated SH-SY5Y cells: experimental design. Schematic representation of the timeline of SH-SY5Y differentiation and sEV treatment. Bright-field and fluorescent images (20× and 40× magnification, respectively) show the progressive development of a neuron-like phenotypes in these cell lines and the increase in α-syn expression after tetracycline treatment, as also confirmed by Western blot images.</p> Full article ">Figure 3
<p>Effect of patient-derived sEVs on α-syn expression in SH-SY5Y cells. (<b>A</b>) Total α-syn levels in SH-SY5Y cells after treatment with sEVs derived from non-mutated (NM-PD) and GBA-mutated (GBA-PD) PD patients, carrying mild (N370S) or severe (L444P) mutations. (<b>B</b>) Expression levels and representative images of fluorescent signal of phospho-syn (Ser129) in SH-SY5Y cells after treatment with patient-derived sEVs. The expression of α-syn (total and phosphorylated form) is normalized with the housekeeping protein (β-actin) and reported as a percentage compared with α-syn expression in SH-SY5Y cells treated with healthy control (HC)-derived sEVs. All data were expressed as mean ± SEM of three independent experiments. Representative images of proteins blots are reported.</p> Full article ">
27 pages, 1792 KiB  
Article
How Are the Flower Structure and Nectar Composition of the Generalistic Orchid Neottia ovata Adapted to a Wide Range of Pollinators?
by Emilia Brzosko, Andrzej Bajguz, Magdalena Chmur, Justyna Burzyńska, Edyta Jermakowicz, Paweł Mirski and Piotr Zieliński
Int. J. Mol. Sci. 2021, 22(4), 2214; https://doi.org/10.3390/ijms22042214 - 23 Feb 2021
Cited by 11 | Viewed by 3481
Abstract
Plant-pollinator interactions significantly influence reproductive success (RS) and drive the evolution of pollination syndromes. In the context of RS, mainly the role of flower morphology is touched. The importance of nectar properties is less studied, despite its significance in pollination effectiveness. Therefore, the [...] Read more.
Plant-pollinator interactions significantly influence reproductive success (RS) and drive the evolution of pollination syndromes. In the context of RS, mainly the role of flower morphology is touched. The importance of nectar properties is less studied, despite its significance in pollination effectiveness. Therefore, the aim of this study was to test selection on flower morphology and nectar chemistry in the generalistic orchid Neottia ovata. In 2019–2020, we measured three floral displays and six flower traits, pollinaria removal (PR), female reproductive success (FRS), and determined the soil properties. The sugars and amino acids (AAs) were analyzed using the HPLC method. Data were analyzed using multiple statistical methods (boxplots, ternary plot, one-way ANOVA, Kruskal-Wallis test, and PCA). Variation of flower structure and nectar chemistry and their weak correlation with RS confirms the generalistic character of N. ovata. In particular populations, different traits were under selection. PR was high and similar in all populations in both years, while FRS was lower and varied among populations. Nectar was dominated by glucose, fructose, and included 28 AAs (Ala and Glu have the highest content). Sugars and AAs influenced mainly FRS. Among soil parameters, carbon and carbon:nitrogen ratio seems to be the most important in shaping flower structure and nectar chemistry. Full article
(This article belongs to the Special Issue Orchid Biochemistry 2.0)
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<p>Boxplots of sugar amounts for <span class="html-italic">Neottia ovata</span> populations. Colored dots are individual samples. The crossed square shows the mean. The lower and upper hinges correspond to the lower (Q1) and upper (Q3) quartiles. Thus box length shows the interquartile range (IQR). The thicker line inside boxes corresponds to the median. The lower whisker extends from the hinge to the smallest value at most Q1 − 1.5 × IQR of the hinge. The upper whisker extends from the hinge to the largest value no further than Q3 + 1.5 × IQR. Data beyond the end of the whiskers, indicated with an asterisk symbol, are outliers.</p> Full article ">Figure 2
<p>Ternary plot of amino acid classes for <span class="html-italic">Neottia ovata</span> populations: II (Asp, Glu, His, Arg, Lys), III (Hyp, Pro), and IV (Val, Met, Trp, Phe, Ile, Leu). Blue lines show 50%, 90%, and 95% confidence intervals via the Mahalanobis Distance and use of the Log-Ratio Transformation. The first class of AAs (Asn, Gln, Ala, Cys, Gly, Ser, Thr, Tyr) does not affect the chemoreceptors of fly (data not shown).</p> Full article ">Figure 3
<p>Biplot of amino acid profiles for <span class="html-italic">Neottia ovata</span> populations, showing the first two dimensions/factors (Dim1-2) of PCA that together explain 73.5% of the variance. Biplot vectors indicate the strength and direction of factor loading for the first two factors. Vectors of supplementary variables are in blue. Individuals (populations) are color-coded and labeled with a number corresponding to Id used in <a href="#app1-ijms-22-02214" class="html-app">Table S3</a>.</p> Full article ">
25 pages, 2315 KiB  
Review
Cell-to-Cell Communication by Host-Released Extracellular Vesicles in the Gut: Implications in Health and Disease
by Natalia Diaz-Garrido, Cecilia Cordero, Yenifer Olivo-Martinez, Josefa Badia and Laura Baldomà
Int. J. Mol. Sci. 2021, 22(4), 2213; https://doi.org/10.3390/ijms22042213 - 23 Feb 2021
Cited by 33 | Viewed by 5948
Abstract
Communication between cells is crucial to preserve body homeostasis and health. Tightly controlled intercellular dialog is particularly relevant in the gut, where cells of the intestinal mucosa are constantly exposed to millions of microbes that have great impact on intestinal homeostasis by controlling [...] Read more.
Communication between cells is crucial to preserve body homeostasis and health. Tightly controlled intercellular dialog is particularly relevant in the gut, where cells of the intestinal mucosa are constantly exposed to millions of microbes that have great impact on intestinal homeostasis by controlling barrier and immune functions. Recent knowledge involves extracellular vesicles (EVs) as mediators of such communication by transferring messenger bioactive molecules including proteins, lipids, and miRNAs between cells and tissues. The specific functions of EVs principally depend on the internal cargo, which upon delivery to target cells trigger signal events that modulate cellular functions. The vesicular cargo is greatly influenced by genetic, pathological, and environmental factors. This finding provides the basis for investigating potential clinical applications of EVs as therapeutic targets or diagnostic biomarkers. Here, we review current knowledge on the biogenesis and cargo composition of EVs in general terms. We then focus the attention to EVs released by cells of the intestinal mucosa and their impact on intestinal homeostasis in health and disease. We specifically highlight their role on epithelial barrier integrity, wound healing of epithelial cells, immunity, and microbiota shaping. Microbiota-derived EVs are not reviewed here. Full article
(This article belongs to the Special Issue Intercellular and Intracellular Communication in Human Health and Disease)
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<p>Schematic overview of extracellular vesicle (EV) biogenesis and cargo. At least three different subclasses of EVs are generated by eukaryotic cells: exosomes (30–200 nm), microvesicles (200–1000 nm), and apoptotic bodies (1–5 µm). The left panel schematically shows the biogenesis pathway for each EV type. Microvesicles and apoptotic bodies sprout directly from the plasma membrane, whereas exosomes are generated within multivesicular body (MVB) subpopulations that upon maturation fuse with the plasma membrane. The biogenesis pathway influences the cargo of EVs. In particular, the composition of exosomes is presented in the right panel. Exosomes are rich in the adhesion molecules tetraspanins (CD9, CD81, CD63), antigen-presenting molecules (MHCI/II), membrane transport proteins (annexins, flotillin), enzymes (elongation factors, metabolic enzymes), and other cytosolic proteins (ribosomal proteins). In addition, lipids (sphingomyelin and phosphatidylserine) and nucleic acids (DNA, RNA, non-coding RNAs (ncRNAs), and micro-RNAs (miRNAs)) also are bioactive components.</p> Full article ">Figure 2
<p>Modulation of immune responses by EVs originated from intestinal epithelial and immune cells. Schematic view of the intestinal mucosa showing the epithelium and the underlying immune system. These host cells receive information from microbiota mainly through secreted factors and lumen antigens that can diffuse through the mucus layer and initiate appropriate immune responses. In this scenario, EVs are key for the host to communicate with neighboring cells. Intestinal epithelial cells (IECs) release EVs from the basolateral side (colored in brown) that participate in the crosstalk with lymphocytes and dendritic cells, being able to activate naïve T cells towards immunogenic (Th) or tolerogenic (Treg) responses depending on the exosome-expressed epitopes and cargo. DCs are the main antigen-presenting cells in the gut lamina propria. These immune cells can integrate information either directly from the intestinal lumen or transmitted through EVs secreted by other cell types under healthy and pathological conditions (intestinal infections, inflammation, or cancer). Once activated, DCs secrete EVs (colored in purple) containing MHC and costimulatory molecules that mediate antigen presentation and immunomodulatory effects towards CD4+ or CD8+ T cells, eliciting suitable T cell responses.</p> Full article ">Figure 3
<p>Graphical summary of functions of EVs within the gut environment. EVs derived from IECs and immune cells of the lamina propria contribute to cell-to-cell communication in the gut and have great impact on the homeostasis/inflammation balance. The scheme summarized the bioactive cargo in EVs that can influence epithelial barrier integrity, tissue repair, immune responses, control of pathogens, and microbiota shaping.</p> Full article ">
26 pages, 2988 KiB  
Review
KRAB-ZFP Transcriptional Regulators Acting as Oncogenes and Tumor Suppressors: An Overview
by Joanna Sobocińska, Sara Molenda, Marta Machnik and Urszula Oleksiewicz
Int. J. Mol. Sci. 2021, 22(4), 2212; https://doi.org/10.3390/ijms22042212 - 23 Feb 2021
Cited by 48 | Viewed by 5596
Abstract
Krüppel-associated box zinc finger proteins (KRAB-ZFPs) constitute the largest family of transcriptional factors exerting co-repressor functions in mammalian cells. In general, KRAB-ZFPs have a dual structure. They may bind to specific DNA sequences via zinc finger motifs and recruit a repressive complex through [...] Read more.
Krüppel-associated box zinc finger proteins (KRAB-ZFPs) constitute the largest family of transcriptional factors exerting co-repressor functions in mammalian cells. In general, KRAB-ZFPs have a dual structure. They may bind to specific DNA sequences via zinc finger motifs and recruit a repressive complex through the KRAB domain. Such a complex mediates histone deacetylation, trimethylation of histone 3 at lysine 9 (H3K9me3), and subsequent heterochromatization. Nevertheless, apart from their repressive role, KRAB-ZFPs may also co-activate gene transcription, likely through interaction with other factors implicated in transcriptional control. KRAB-ZFPs play essential roles in various biological processes, including development, imprinting, retroelement silencing, and carcinogenesis. Cancer cells possess multiple genomic, epigenomic, and transcriptomic aberrations. A growing number of data indicates that the expression of many KRAB-ZFPs is altered in several tumor types, in which they may act as oncogenes or tumor suppressors. Hereby, we review the available literature describing the oncogenic and suppressive roles of various KRAB-ZFPs in cancer. We focused on their association with the clinicopathological features and treatment response, as well as their influence on the cancer cell phenotype. Moreover, we summarized the identified upstream and downstream molecular mechanisms that may govern the functioning of KRAB-ZFPs in a cancer setting. Full article
(This article belongs to the Special Issue Transcription Factors in Cancer)
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<p>The structure of various Krüppel-associated box zinc finger proteins (KRAB-ZFP) factors and their composing domains. The diagram shows the structure of selected factors (based on the Uniprot database) containing a KRAB domain at the N-terminus and the variable number of zinc fingers at the C-terminus. A KRAB domain may consist of two boxes: KRAB-A and KRAB-B. In some of the KRAB-ZFPs, an additional “SRE-ZBP, CTfin51, AW-1 and Number 18 cDNA” (SCAN) or “domain of the unknown function” (DUF3669) may also be present.</p> Full article ">Figure 2
<p>Repressive complex with the participation of a KRAB-ZFP factor. The repression complex contains the scaffold protein KAP1, H3K9 methyltransferase SET Domain Bifurcated 1 (SETDB1), heterochromatin protein 1 (HP1), and repressive Nucleosome Remodeling Deacetylase (NuRD) complex with Mi2α histone deacetylase. In certain cell types, the complex may also interact with DNA methyltransferase. These protein partners cooperatively inhibit transcriptional activity and promoter heterochromatization of the locus recognized by the zinc finger domain within an interacting KRAB-ZFP factor. A—histone acetylation, M—H3K9me3, white circles—unmethylated cytosines, black circles—methylated cytosines.</p> Full article ">Figure 3
<p>The involvement of ZFP57 and ZFP445 in gene imprinting. Both ZFP57 and ZNF445 are involved in maintaining methylation patterns by recruiting KAP1, DNA methyltransferase DNMT1, and histone methyltransferase SETDB1 to induce H3K9 trimethylation. The methylated imprinting control regions (ICR) on the top (black circles), unmethylated ICR on the bottom (white circles).</p> Full article ">Figure 4
<p>KRAB-ZFPs oncogene and tumor suppressor genes (TSG) role in the cancers of various tissue origins. The scheme presents the localization of different cancers in the human body, in which KRAB-ZFP factors may act as oncogenes (red font, the gene is upregulated) or tumor suppressor genes (green font, the gene is downregulated). Abbreviations: BLCA—bladder cancer, BRCA—breast cancer, CAA—cholangiocarcinoma, CESC—cervical cancer, CLL—chronic lymphocytic leukemia, CRC—colorectal cancer, EC—endometrial cancer, ESCC—esophageal squamous-cell carcinoma, GBM—glioblastoma, HCC—hepatocellular carcinoma, LUC—lung cancer, MM—multiple myeloma, OD—oligodendroglioma; OvCa—ovarian cancer, PAAD—pancreatic cancer, PRAD—prostate adenocarcinoma, RCC—kidney cancer, SC—skin cancer, SKCM—melanoma, STAD—gastric cancer, THCA—thyroid cancer.</p> Full article ">Figure 5
<p>The influence of selected KRAB-ZFPs on cell cycle. The KRAB-ZFP factors may induce cell cycle arrest (red arrows) or promote phase transition (green arrows) in a given phase. Abbreviations: KD—knockdown, OE—overexpression, AEL—acute erythroid leukemia, BRCA—breast cancer, CESC—cervical cancer, CLL—chronic lymphocytic leukemia, CRC—colorectal cancer, ESCC—esophageal squamous-cell carcinoma, HCC—hepatocellular carcinoma, NSCLC—non-small cell lung cancer, OvCa—ovarian cancer, STAD—gastric cancer.</p> Full article ">Figure 6
<p>An influence of selected KRAB-ZFP TSGs (<b>A</b>) and oncogenes (<b>B</b>) on various cancer-related signaling pathways and phenotypic features in neoplastic cells. The schematic representation demonstrates selected KRAB-ZFPs with oncogenic and TSG properties and their impact on the cellular signaling, apoptosis, response to treatment, proliferation, migration, and invasion of cancer cells, as well as patient survival. Some signaling pathways are yet to be understood. Green arrow—induction, red—inhibition, P—phosphorylation.</p> Full article ">
13 pages, 3323 KiB  
Article
Identification of Active Site Residues of the Siderophore Synthesis Enzyme PvdF and Evidence for Interaction of PvdF with a Substrate-Providing Enzyme
by Priya Philem, Torsten Kleffmann, Sinan Gai, Bill C. Hawkins, Sigurd M. Wilbanks and Iain L. Lamont
Int. J. Mol. Sci. 2021, 22(4), 2211; https://doi.org/10.3390/ijms22042211 - 23 Feb 2021
Cited by 4 | Viewed by 2610
Abstract
The problematic opportunistic pathogen Pseudomonas aeruginosa secretes a siderophore, pyoverdine. Pyoverdine scavenges iron needed by the bacteria for growth and for pathogenicity in a range of different infection models. PvdF, a hydroxyornithine transformylase enzyme, is essential for pyoverdine synthesis, catalysing synthesis of formylhydroxyornithine [...] Read more.
The problematic opportunistic pathogen Pseudomonas aeruginosa secretes a siderophore, pyoverdine. Pyoverdine scavenges iron needed by the bacteria for growth and for pathogenicity in a range of different infection models. PvdF, a hydroxyornithine transformylase enzyme, is essential for pyoverdine synthesis, catalysing synthesis of formylhydroxyornithine (fOHOrn) that forms part of the pyoverdine molecule and provides iron-chelating hydroxamate ligands. Using a mass spectrometry assay, we confirm that purified PvdF catalyses synthesis of fOHOrn from hydroxyornithine and formyltetrahydrofolate substrates. Site directed mutagenesis was carried out to investigate amino acid residues predicted to be required for enzymatic activity. Enzyme variants were assayed for activity in vitro and also in vivo, through measuring their ability to restore pyoverdine production to a pvdF mutant strain. Variants at two putative catalytic residues N168 and H170 greatly reduced enzymatic activity in vivo though did not abolish activity in vitro. Change of a third residue D229 abolished activity both in vivo and in vitro. A change predicted to block entry of N10-formyltetrahydrofolate (fTHF) to the active site also abolished activity both in vitro and in vivo. A co-purification assay showed that PvdF binds to an enzyme PvdA that catalyses synthesis of hydroxyornithine, with this interaction likely to increase the efficiency of fOHOrn synthesis. Our findings advance understanding of how P. aeruginosa synthesises pyoverdine, a key factor in host–pathogen interactions. Full article
(This article belongs to the Special Issue Transition Metals in the Host-Pathogen Interaction)
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<p>Pyoverdine structure and synthesis of formylhydroxyornithine. (<b>A</b>) Pyoverdine from <span class="html-italic">P. aeruginosa</span> PAO1. (<b>B</b>) Synthesis of formylhydroxyornithine (fOHOrn) from <span class="html-small-caps">l</span>-ornithine (<span class="html-small-caps">l</span>-Orn). PvdA catalyses hydroxylation of <span class="html-small-caps">l</span>-Orn to <span class="html-small-caps">l</span>-OHOrn which is then formylated by PvdF with N<sup>10</sup>-formyltetrahydrofolate (fTHF) as the co-substrate to give <span class="html-small-caps">l</span>-fOHOrn and tetrahydrofolate (THF).</p> Full article ">Figure 2
<p>PvdF catalyses synthesis of fOHOrn from OHOrn and N<sup>10</sup>-formyltetrahydrofolate (fTHF). Reaction mixtures containing OHOrn (hydroxyornithine), N<sup>10</sup>-fH<sup>4</sup>F and His<sub>6</sub>PvdF were incubated at 30 °C for 3 h and analysed by direct injection mass spectrometry. Spectra present relative peak intensities of ionised molecules in a range of mass to charge ratios (<span class="html-italic">m</span>/<span class="html-italic">z</span>) from 125 to 185. (<b>A</b>) His<sub>6</sub>PvdF reaction showing peaks corresponding to OHOrn ([M+H]<sup>+</sup> 149.0921 ± ppm; blue) and fOHOrn (formylhydroxyornithine) ([M+H]<sup>+</sup> 177.0870 ± 3 ppm; red). (<b>B</b>) Negative control with omission of His<sub>6</sub>PvdF. (<b>C</b>) Negative control with omission of OHOrn. Note the background peak at m/z 177.0566 is not related to the fOHOrn peak at <span class="html-italic">m</span>/<span class="html-italic">z</span> 177.0870 (delta <span class="html-italic">m</span>/<span class="html-italic">z</span> &gt; 170 ppm). (<b>D</b>) Negative control with omission of fTHF. (<b>E</b>) Timecourse of fOHOrn synthesis. Assays were set up in technical triplicates at 0, 30, 60, 180 and 240 min. Abundances of L-fOHOrn were obtained and the average of three technical replicates is shown as a function of incubation time. The error bars are standard errors of the mean. Spectra are representative of at least three independent enzyme preparations.</p> Full article ">Figure 3
<p>Superposition of PvdF on glycinamideribonucleotide transferase (GART). The view looks into the major cleft between domains of PvdF (cyan, chain H of PDB 6CUL). This aligns with the active site of GART (chain A of PDB 1C2T, shown in olive). Stick representations of sidechains identify the residues that were modified in PvdF and the corresponding active site residues in GART with oxygen in red and nitrogen in blue. G147 of PvdF and G 87 of GART are emphasised in dark blue. Residues are labelled with the PvdF numbering.</p> Full article ">Figure 4
<p>PvdF consists of two independently melting domains. (<b>A</b>) Thermal stability tests of PvdF and variants were carried out using differential scanning fluorometry. Black dots indicate inflection points that are likely to represent domain melting events. All the variants had evidence for two inflection points except H170R which showed only one. (<b>B</b>) Stability tests of His<sub>6</sub>PvdF in presence of fTHF (formyltetrahydrofolate) (grey and yellow curves) showed a single, cooperative melting event of large amplitude, in contrast to the two inflection points and low amplitudes observed in absence of this substrate (blue and orange curves). In contrast, the presence of OHOrn (hydroxyornithine) (grey and orange curves) did not affect melting of PvdFHis<sub>6</sub>. Spectra are averages of at least three independent enzyme preparations.</p> Full article ">Figure 5
<p>In vitro activity of PvdF enzyme variants. Reaction mixtures of PvdF variants were incubated at 30 °C for 3 h and then analysed using direct injection mass spectrometry. Spectra present relative peak intensities of ionised molecules in a range of mass to charge ratios (<span class="html-italic">m</span>/<span class="html-italic">z</span>) from 125 to 185. The detection of OHOrn (hydroxyornithine) at <span class="html-italic">m</span>/<span class="html-italic">z</span> 149.0921 ± 3 ppm and fOHOrn (formylhydroxyornithine) at <span class="html-italic">m</span>/<span class="html-italic">z</span> 177.0870 ± 3 ppm is indicated by peaks highlighted in blue and red, respectively. (<b>A</b>) G147A. (<b>B</b>) G147F. (<b>C</b>) N168H. (<b>D</b>) H170R. (<b>E</b>) D229H. (<b>F</b>) N254A. Spectra are representative of at least three independent enzyme preparations.</p> Full article ">Figure 6
<p>Pyoverdine production in <span class="html-italic">P. aeruginosa pvdF</span> containing PvdF variants. Pyoverdine production in broth culture was measured for the <span class="html-italic">P. aeruginosa pvdF</span> mutant containing plasmid-borne <span class="html-italic">pvdF</span> variants. The mean of three biological replicates along with standard error bars are shown. Agar plates, with pyoverdine giving green pigmentation, are shown above each bar.</p> Full article ">Figure 7
<p>Co-purification of PvdF and PvdA (<b>A</b>) PvdF and His<sub>6</sub>PvdA were expressed from pET-DUET-1 in <span class="html-italic">E. coli</span> BL21 DE3. Following purification by nickel affinity chromatography, proteins from bacteria containing the plasmids shown were visualised by SDS-PAGE. The identities of the bands in red boxes were confirmed as His<sub>6</sub>PvdA and PvdF by mass spectrometry (<a href="#app1-ijms-22-02211" class="html-app">Table S1</a>). (<b>B</b>) PvdFHis<sub>6</sub> and PvdA were expressed separately in <span class="html-italic">E. coli</span> BL21 DE3 and cell lysates prepared. Nickel affinity chromatography was carried out on individual lysates (PvdFHis<sub>6</sub>; PvdA) and following mixture of lysates (PvdFHis6 and PvdA). The eluates were analysed using SDS-PAGE. The positions of PvdFHis<sub>6</sub> and PvdA proteins are indicated.</p> Full article ">
37 pages, 2005 KiB  
Review
Therapeutic Targeting of MicroRNAs in the Tumor Microenvironment
by Rebecca Raue, Ann-Christin Frank, Shahzad Nawaz Syed and Bernhard Brüne
Int. J. Mol. Sci. 2021, 22(4), 2210; https://doi.org/10.3390/ijms22042210 - 23 Feb 2021
Cited by 32 | Viewed by 6172
Abstract
The tumor-microenvironment (TME) is an amalgamation of various factors derived from malignant cells and infiltrating host cells, including cells of the immune system. One of the important factors of the TME is microRNAs (miRs) that regulate target gene expression at a post transcriptional [...] Read more.
The tumor-microenvironment (TME) is an amalgamation of various factors derived from malignant cells and infiltrating host cells, including cells of the immune system. One of the important factors of the TME is microRNAs (miRs) that regulate target gene expression at a post transcriptional level. MiRs have been found to be dysregulated in tumor as well as in stromal cells and they emerged as important regulators of tumorigenesis. In fact, miRs regulate almost all hallmarks of cancer, thus making them attractive tools and targets for novel anti-tumoral treatment strategies. Tumor to stroma cell cross-propagation of miRs to regulate protumoral functions has been a salient feature of the TME. MiRs can either act as tumor suppressors or oncogenes (oncomiRs) and both miR mimics as well as miR inhibitors (antimiRs) have been used in preclinical trials to alter cancer and stromal cell phenotypes. Owing to their cascading ability to regulate upstream target genes and their chemical nature, which allows specific pharmacological targeting, miRs are attractive targets for anti-tumor therapy. In this review, we cover a recent update on our understanding of dysregulated miRs in the TME and provide an overview of how these miRs are involved in current cancer-therapeutic approaches from bench to bedside. Full article
(This article belongs to the Special Issue Pharmacologic Targeting of the Tumor Microenvironment)
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<p>Examples of dysregulated microRNAs (miRs) in cells of the tumor microenvironment (TME) and their impact on tumor cells. MiRs can either act as tumor-suppressors by regulating molecules or pathways with anti-tumoral characteristics (red box; red T bar) or oncomiRs that directly or indirectly impact on tumor-promoting genes and protein networks (green box; green arrow). The differential expression of miRs in macrophages and tumor-associated macrophages (TAMs), or the uptake of exogenous miRs, modulate their polarization. Similarly, miRs expressed in cancer-associated fibroblasts (CAFs) regulate their migration, cytokine production, and trans-differentiation as well as tumor growth. CAF-derived miRs (e.g., miR-522) can also enhance drug resistance of tumor cells. In dendritic cells (DCs), miRs regulate Th17 differentiation, co-stimulatory molecule expression, and T cell activation. miRs expressed in cancer-associated endothelial cells (CAEs) regulate the microvascular invasion and angiogenesis activity to drive tumorigenesis. In myeloid-derived suppressor cell (MDSCs), miRs modulate the expansion/immune-suppressive functions. In natural killer (NK) cells, miRs modulate the production of effector molecules (e.g., IFN-γ) and the activating receptor encoded by killer cell lectin like receptor K1 (NKG2D). Furthermore, miRs regulate the expression of transcription factors and cytokine production of regulatory T cells (Tregs). ARG1, arginase 1; α-SMA, α-smooth muscle actin; CAE, cancer-associated endothelial cell; CAF, cancer-associated fibroblast; DC, dendritic cell; Fgf2, fibroblast growth factor 2; IFN, interferon; iNOS, inducible NO synthase; NF, normal fibroblast; NKG2D, encoded by killer cell lectin like receptor K1; ROS, reactive oxygen species; TAM, tumor-associated macrophage; Treg, regulatory T cell.</p> Full article ">Figure 2
<p>Therapeutic modulation of miR expression and miR carriers. Tumor suppressive miRs can be replenished by miR mimics (<b>a</b>), thereby suppressing translation of mRNAs encoding for oncogenes. On the other hand, oncogenic miRs can be inhibited by ASOs (<b>b</b>), miR-sponges (<b>c</b>), artificial ribonucleases (<b>d</b>), small molecules (<b>e</b>), or the CRISPR/Cas9 system (<b>f</b>). Small molecules have been shown to either suppress oncomiRs or globally enhance miR expression. To increase oligonucleotide stability, chemical modifications can be inserted. Several delivery systems have been established to further increase the stability of the miR therapeutic agent and improve tumor cell targeting, e.g., cationic dendrimers (<b>g</b>), lipoplexes (<b>h</b>), nanoparticles with tumor-specific ligands (<b>i</b>), inorganic nanoparticles (<b>j</b>), micelles (<b>k</b>), polymer nanoparticles (<b>l</b>), and exosomes/microvesicles (<b>m</b>). See text for more details. AGO, argonaute protein; ASOs, antisense-oligonucleotides; AuNPs, gold nanoparticles; DOPC, 1,2 dioleoyl-sn glycerol-3 phosphatidylcholine-lipid nanoparticles; EDVs, EnGeneIC Delivery Vehicle; LNA, locked nucleic acid; NLE, neutral lipid emulsions; PAMAM, poly(amidoamine); PEI, poly(ethyleneimine); pHLIP, pH low insertion peptide; PLGA, Poly(lactide-co-glycolide); Pol II, RNA-polymerase II; PPI, poly(propylenimine); RISC, RNA-induced silencing complex.</p> Full article ">
23 pages, 3736 KiB  
Article
Divalent Cation Modulation of Ion Permeation in TMEM16 Proteins
by Dung M. Nguyen, Hwoi Chan Kwon and Tsung-Yu Chen
Int. J. Mol. Sci. 2021, 22(4), 2209; https://doi.org/10.3390/ijms22042209 - 23 Feb 2021
Cited by 7 | Viewed by 2990
Abstract
Intracellular divalent cations control the molecular function of transmembrane protein 16 (TMEM16) family members. Both anion channels (such as TMEM16A) and phospholipid scramblases (such as TMEM16F) in this family are activated by intracellular Ca2+ in the low µM range. In addition, intracellular [...] Read more.
Intracellular divalent cations control the molecular function of transmembrane protein 16 (TMEM16) family members. Both anion channels (such as TMEM16A) and phospholipid scramblases (such as TMEM16F) in this family are activated by intracellular Ca2+ in the low µM range. In addition, intracellular Ca2+ or Co2+ at mM concentrations have been shown to further potentiate the saturated Ca2+-activated current of TMEM16A. In this study, we found that all alkaline earth divalent cations in mM concentrations can generate similar potentiation effects in TMEM16A when applied intracellularly, and that manipulations thought to deplete membrane phospholipids weaken the effect. In comparison, mM concentrations of divalent cations minimally potentiate the current of TMEM16F but significantly change its cation/anion selectivity. We suggest that divalent cations may increase local concentrations of permeant ions via a change in pore electrostatic potential, possibly acting through phospholipid head groups in or near the pore. Monovalent cations appear to exert a similar effect, although with a much lower affinity. Our findings resolve controversies regarding the ion selectivity of TMEM16 proteins. The physiological role of this mechanism, however, remains elusive because of the nearly constant high cation concentrations in cytosols. Full article
(This article belongs to the Special Issue Ca2+-Activated Chloride Channels and Phospholipid Scramblases)
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Figure 1

Figure 1
<p>Potentiation of the TMEM16A current by intracellular Co<sup>2+</sup> and Ca<sup>2</sup><b><sup>+</sup>.</b> TMEM16A currents were obtained at voltages clamped at −20 mV (blue traces) and +20 mV (orange traces). Currents were activated by 0.3 mM intracellular calcium concentration ([Ca<sup>2+</sup>]<sub>i</sub>). (<b>A</b>) Recording traces showing the dual effects, inhibition and potentiation on the wild-type TMEM16A (WT<sub>16A</sub>) current by 20 mM intracellular cobalt concentration ([Co<sup>2+</sup>]<sub>i</sub>). (<b>B</b>) Recording traces showing potentiation of WT<sub>16A</sub> by 20 mM [Ca<sup>2+</sup>]<sub>i</sub>. In the bottom panel of both A and B, an expanded view of the yellow shaded area in the upper panel is depicted to focus on the current potentiation. I<sub>0</sub> represents the control current before the application of divalent cations, whereas I<sub>peak</sub> and I<sub>Co</sub> represent the peak current after the application of Co<sup>2+</sup> and the quasi-steady-state current at the end of the Co<sup>2+</sup> application, respectively.</p> Full article ">Figure 2
<p>Potentiation of WT<sub>16A</sub> current by various divalent cations. (<b>A</b>) Dose-dependent Mg<sup>2+</sup> and Ca<sup>2+</sup> potentiation of the WT<sub>16A</sub> current. Left three panels show raw recording traces of Mg<sup>2+</sup> or Ca<sup>2+</sup> potentiation of WT<sub>16A</sub> current. The currents were normalized to the current immediately before the application of mM intracellular concentration of magnesium ([Mg<sup>2+</sup>]) or [Ca<sup>2+</sup>]. Right panel shows averaged potentiation of WT<sub>16A</sub> current as a function of [Mg<sup>2+</sup>] (<span class="html-italic">n</span> = 5–8) or [Ca<sup>2+</sup>] (<span class="html-italic">n</span> = 6–7). (<b>B</b>) Averaged potentiation of 0.3 mM [Ca<sup>2+</sup>]<sub>i</sub>-induced WT<sub>16A</sub> current by 20 mM Ca<sup>2+</sup>, Co<sup>2+</sup>, Mg<sup>2+</sup>, Sr<sup>2+</sup> or Ba<sup>2+</sup> (<span class="html-italic">n</span> = 6–11). Insets show raw recording traces of Sr<sup>2+</sup> or Ba<sup>2+</sup> potentiation of WT<sub>16A</sub> current.</p> Full article ">Figure 3
<p>Manipulating Co<sup>2+</sup> and Ca<sup>2+</sup> potentiation of WT<sub>16A</sub>, Y589V<sub>16A</sub>, and Y589A<sub>16A</sub> by intracellular reagents that affect membrane phospholipids. (<b>A</b>,<b>B</b>) Representative recordings showing Co<sup>2+</sup> and Ca<sup>2+</sup> potentiation, respectively, before and after treating the patch with poly<span class="html-small-caps">-l-</span>lysine (PLL, 0.3 mg/mL) for 5 sec. All currents were induced by 0.3 mM [Ca<sup>2+</sup>]<sub>i</sub> and potentiated with an additional 20 mM Co<sup>2+</sup> or Ca<sup>2+</sup> (black bars underneath phenotype labels). (<b>C</b>,<b>D</b>) Degree of Co<sup>2+</sup> and Ca<sup>2+</sup> potentiation, respectively, before and after poly<span class="html-small-caps">-l-</span>lysine treatment. Orange (+20 mV) and blue (−20 mV) circles are the potentiation before poly<span class="html-small-caps">-l-</span>lysine treatment while light orange (+20 mV) and light blue (−20 mV) diamonds are the potentiation after poly<span class="html-small-caps">-l-</span>lysine. (<b>E</b>,<b>F</b>) Effects of PIP2 for reversing the effect of poly<span class="html-small-caps">-l-</span>lysine on the Ca<sup>2+</sup>-induced potentiation of the WT<sub>16A</sub> current. Degree of Ca<sup>2+</sup> potentiation was measured before poly<span class="html-small-caps">-l-</span>lysine treatment, after poly<span class="html-small-caps">-l-</span>lysine treatment, and after PIP2 treatment. In (<b>C</b>,<b>D</b>,<b>F</b>), data points from the same patch are connected by solid lines, and colored horizontal line segments represent the mean of the data set. ns <span class="html-italic">p</span> &gt; 0.05; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005 by one-way ANOVA followed by Bonferroni’s multiple comparisons.</p> Full article ">Figure 4
<p>Involvement of Phospholipids in divalent cation-induced potentiation. (<b>A</b>) Representative recording traces are depicted to illustrate the decrease in Mg<sup>2+</sup> potentiation of Y589A<sub>16A</sub> after channel rundown. For every minute, current was elicited with 100 µM Ca<sup>2+</sup> (a concentration chosen for reducing the speed of rundown), and 20 mM Mg<sup>2+</sup> were applied subsequently for 1 s (black bar above traces). (<b>B</b>) Reduction of Mg<sup>2+</sup> potentiation (I<sub>peak</sub>/I<sub>0</sub>) over time at +20 mV (left panel, orange) and −20 mV (right panel, blue) (<span class="html-italic">n</span> = 6–9). The rundown of the control current (I<sub>0</sub> normalized to the I<sub>0</sub> of the trace at t = 0 min) is shown by circles, whereas the reduction of the Mg<sup>2+</sup> potentiation is shown by squares. (<b>C</b>) Mg<sup>2+</sup> potentiation of a PIP2 binding-site mutant P566A<sub>16A</sub> at ±20 mV. The P566A<sub>16A</sub> current was easier to run down and the degree of potentiation was also smaller compared to that in WT<sub>16A</sub>. (<b>D</b>) Comparing Mg<sup>2+</sup> potentiation at ±20 mV between WT<sub>16A</sub> (replotted from <a href="#ijms-22-02209-f001" class="html-fig">Figure 1</a>) and four mutants (numbers below each column are the number of patches). ns <span class="html-italic">p</span> &gt; 0.05; * <span class="html-italic">p</span> &lt; 0.05; and ** <span class="html-italic">p</span> &lt; 0.005 by one-way ANOVA followed by Bonferroni’s multiple comparisons.</p> Full article ">Figure 5
<p>Enhanced divalent cation potentiation of WT<sub>16A</sub> in low ionic strength solutions. (Top) Recording traces comparing the Co<sup>2+</sup> or Mg<sup>2+</sup> potentiation of WT<sub>16A</sub> between conditions of symmetrical 140 mM and 40 mM NaCl. The 40 mM NaCl solution also contains 100 mM D-mannitol. All currents were induced by 0.3 mM [Ca<sup>2+</sup>]<sub>i</sub>. (Bottom) Bar graph summarizing Co<sup>2+</sup> and Mg<sup>2+</sup> potentiation under symmetrical 140 mM or 40 mM NaCl (<span class="html-italic">n</span> = 6–8). ns <span class="html-italic">p</span> &gt; 0.05; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005 by one-way ANOVA followed by Bonferroni’s multiple comparisons.</p> Full article ">Figure 6
<p>Potentiation and inhibition of the Q559W<sub>16F</sub> current by Mg<sup>2+</sup> and Co<sup>2+</sup>. (<b>A</b>) Representative recording traces for the Mg<sup>2+</sup> and Co<sup>2+</sup> effects on the Q559W<sub>16F</sub> current (induced by 0.3 mM [Ca<sup>2+</sup>]<sub>i</sub>). (<b>B</b>) Averaged potentiation (I<sub>peak</sub>/I<sub>0</sub>) of Mg<sup>2+</sup> and Co<sup>2+</sup> on the Q559W<sub>16F</sub> current. (<b>C</b>) Averaged inhibition (I<sub>Divalent</sub>/I<sub>peak</sub>, i.e., I<sub>Mg</sub>/I<sub>peak</sub> or I<sub>Co</sub>/I<sub>peak</sub>) of Mg<sup>2+</sup> and Co<sup>2+</sup> on the Q559W<sub>16F</sub> current.</p> Full article ">Figure 7
<p>Intracellular Ca<sup>2+</sup> effect on the Na<sup>+</sup> versus Cl<sup>-</sup> permeability ratios (P<sub>Na</sub>/P<sub>Cl</sub>) of TMEM16 currents. Representative I–V curves for (<b>A</b>) WT<sub>16A</sub> and (<b>B</b>) Q559W<sub>16F</sub> under asymmetrical [NaCl]. [NaCl]<sub>o</sub> = 140 mM in all recordings, whereas [NaCl]<sub>i</sub> was 140 mM (green), 40 mM (blue) and 15 mM (red), respectively. The reduced [NaCl]<sub>i</sub> in the 40 and 15 mM [NaCl]<sub>i</sub> solutions was replaced with D-mannitol. Currents were elicited with either 0.02 mM or 1 mM [Ca<sup>2+</sup>]<sub>i</sub>, indicated by the colored numbers next to each curve. (<b>C</b>) Summary of reverse potential (E<sub>rev</sub>) measured under asymmetrical [NaCl] for WT<sub>16A</sub> (squares) and Q559W<sub>16F</sub> (circles). The P<sub>Na</sub>/P<sub>Cl</sub> ratios (calculated based on the Goldman–Hodgkin–Katz equation, see equation 1 in Materials and Methods) of WT<sub>16A</sub> and Q559W<sub>16F</sub> are shown in the box on the right and in <a href="#ijms-22-02209-t001" class="html-table">Table 1</a> (<span class="html-italic">n</span> = 5–15). * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005 by one-way ANOVA followed by Bonferroni’s multiple comparisons.</p> Full article ">Figure 8
<p>Effects of manipulating membrane phospholipids on the P<sub>Na</sub>/P<sub>Cl</sub> ratio of Q559W<sub>16F</sub>. All experiments were performed with 20 µM [Ca<sup>2+</sup>]<sub>i</sub>. [NaCl]<sub>o</sub> = 140 mM in all experiments. (<b>A</b>) Representative I–V curves of Q559W<sub>16F</sub> in various intracellular solutions; −80 mV to +80 mV are shown in the top panel, whereas the expanded traces near reversal potentials are depicted at the bottom. Experiments were first performed in 140 mM [NaCl]<sub>i</sub> (green traces), followed by experiments in 40 mM [NaCl]<sub>i</sub> before (blue traces) and after (pink traces) 0.3 mg/mL intracellular poly<span class="html-small-caps">-l-</span>lysine treatment for 5 sec. Finally, the I–V curve was obtained after the patch was intracellularly treated with 20 µM PIP2 for 1 min (purple traces). (<b>B</b>) Altering the P<sub>Na</sub>/P<sub>Cl</sub> ratio of Q559W<sub>16F</sub> after treating membrane patches with intracellular poly<span class="html-small-caps">-l-</span>lysine or PIP2. Results are from experiments like those shown in (A) and data points from the same patch are connected by line segments. Horizontal lines depict the averaged reversal potentials from individual data set. The mean P<sub>Na</sub>/P<sub>Cl</sub> ratios (± SEM) at the bottom of the plot were calculated according to equation 1. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005 by one-way ANOVA followed by Bonferroni’s multiple comparisons.</p> Full article ">Figure 9
<p>Effects of [Mg<sup>2+</sup>]<sub>i</sub> on the P<sub>Na</sub>/P<sub>Cl</sub> ratio of Q559W<sub>16F</sub>. (<b>A</b>) Representative I–V curves of Q559W<sub>16F</sub> under asymmetrical [NaCl] in the presence and absence of 1 mM Mg<sup>2+</sup>. Currents were activated by 20 µM [Ca<sup>2+</sup>]<sub>i</sub>. Bottom panel shows the same I–V curves expanded around E<sub>rev</sub>. (<b>B</b>) Paired data showing the values of E<sub>rev</sub> in the presence (pink circles) of 1 mM Mg<sup>2+</sup>, and the values of E<sub>rev</sub> before Mg<sup>2+</sup> wash-in and after Mg<sup>2+</sup> wash-out (blue circles). Horizontal black lines indicate the mean value for each data set. Calculated P<sub>Na</sub>/P<sub>Cl</sub> ratios are shown at the bottom of the plot. ns <span class="html-italic">p</span> &gt; 0.05; ** <span class="html-italic">p</span> &lt; 0.005 by one-way ANOVA followed by Bonferroni’s multiple comparisons.</p> Full article ">Figure 10
<p>Dependence of the P<sub>Na</sub>/P<sub>Cl</sub> ratio of Q559W<sub>16F</sub> on [NaCl]<sub>i</sub>. (<b>A</b>) Representative I–V curves for Q559W<sub>16F</sub> in various [NaCl]<sub>i</sub> (from 15 to 280 mM). In all recordings, [NaCl]<sub>o</sub> = 140 mM and the currents were activated by 20 µM [Ca<sup>2+</sup>]<sub>i</sub>. The same I–V curves expanded around the E<sub>rev</sub> are shown in the bottom panel. (<b>B</b>) Averaged E<sub>rev</sub> as a function of [NaCl]<sub>i</sub> from the recordings like those shown in A. (<b>C</b>) P<sub>Na</sub>/P<sub>Cl</sub> ratio as a function of [NaCl]<sub>i</sub>. Note the reduction of the P<sub>Na</sub>/P<sub>Cl</sub> ratio as [NaCl]<sub>i</sub> increases (<span class="html-italic">n</span> = 6–22).</p> Full article ">Figure 11
<p>Illustration of divalent cation effects on TMEM16 molecules. (<b>A</b>) High resolution structure of the “ac” alternatively spliced variant of TMEM16A (left, PDB:5OYB). The six transmembrane helices (helices 3–8) of a single subunit forming the ion-conduction pathway are rotated 90° clockwise along the axis perpendicular to the cell membrane (right). Helix 4 is colored in orange, whereas all other helices are colored in green. Residue K584 of the alternatively spliced “a” variant of TMEM16A (used in our experiments) and residue Q559 of TMEM16F corresponds to residue K588 of the TMEM16A “ac” variant (colored in red). Y589 of the TMEM16A “a” variant mentioned in the text corresponds to Y593 in the TMEM16A “ac” variant (colored in blue). Light purple oval roughly depicts the intracellular pore vestibule. (<b>B</b>) Intracellular view perpendicular to the cell membrane of a single subunit. (Left) all transmembrane helices (with helix numbers) are shown. (Right) Cartoon model of the six pore-forming helices depicted as cylinders (same orientation as that in the left panel). Intracellular leaflet of cell membranes contains negatively charged phospholipids (yellow circles labeled with “−”) as well as neutral ones (yellow circles without “−”). PIP2 molecules are depicted as salmon-color circles with “3−”. The Ca<sup>2+</sup> ions at the activation sites are colored in pink. Monovalent (not shown), divalent (depicted as small green circles) or even multivalent cations (not shown) can bind to phospholipid head groups, consequently decreasing the negative potential from phospholipids. Four mutations associated with PIP2 regulations of TMEM16A studied in this paper are shown. Notice that residues P556 (dark green star) and D481 (purple diamond) appear to be closer to the intracellular pore vestibule than residues R437 (cyan down triangle) and K678 (brown hexagon).</p> Full article ">
18 pages, 6433 KiB  
Communication
Exploring Molecular Contacts of MUC1 at CIN85 Binding Interface to Address Future Drug Design Efforts
by Maria Rita Gulotta, Serena Vittorio, Rosaria Gitto, Ugo Perricone and Laura De Luca
Int. J. Mol. Sci. 2021, 22(4), 2208; https://doi.org/10.3390/ijms22042208 - 23 Feb 2021
Cited by 1 | Viewed by 2317
Abstract
The modulation of protein-protein interactions (PPIs) by small molecules represents a valuable strategy for pharmacological intervention in several human diseases. In this context, computer-aided drug discovery techniques offer useful resources to predict the network of interactions governing the recognition process between protein partners, [...] Read more.
The modulation of protein-protein interactions (PPIs) by small molecules represents a valuable strategy for pharmacological intervention in several human diseases. In this context, computer-aided drug discovery techniques offer useful resources to predict the network of interactions governing the recognition process between protein partners, thus furnishing relevant information for the design of novel PPI modulators. In this work, we focused our attention on the MUC1-CIN85 complex as a crucial PPI controlling cancer progression and metastasis. MUC1 is a transmembrane glycoprotein whose extracellular domain contains a variable number of tandem repeats (VNTRs) regions that are highly glycosylated in normal cells and under-glycosylated in cancer. The hypo-glycosylation fosters the exposure of the backbone to new interactions with other proteins, such as CIN85, that alter the intracellular signalling in tumour cells. Herein, different computational approaches were combined to investigate the molecular recognition pattern of MUC1-CIN85 PPI thus unveiling new structural information useful for the design of MUC1-CIN85 PPI inhibitors as potential anti-metastatic agents. Full article
(This article belongs to the Section Molecular Informatics)
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Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>SH3A domain structure of CIN85. The residues of the hydrophobic and acidic pockets are highlighted as cyan sticks. The image was created by PyMOL software v2.4.0 (<a href="http://www.pymol.org" target="_blank">www.pymol.org</a>, accessed on 19 May 2020).</p> Full article ">Figure 2
<p>(<b>A</b>) Pseudo-symmetrical orientation of Cbl-b-derived peptide in complex with two CIN85 SH3 domains. The N-terminal region of the peptide is involved in the Type I orientation, while the C-terminus is engaged in the Type II orientation [<a href="#B21-ijms-22-02208" class="html-bibr">21</a>]. (<b>B</b>) 2D interaction diagram of Cbl-b peptide and the established interactions with CIN85 SH3 domains amino acids retrieved from PDB 2BZ8.</p> Full article ">Figure 2 Cont.
<p>(<b>A</b>) Pseudo-symmetrical orientation of Cbl-b-derived peptide in complex with two CIN85 SH3 domains. The N-terminal region of the peptide is involved in the Type I orientation, while the C-terminus is engaged in the Type II orientation [<a href="#B21-ijms-22-02208" class="html-bibr">21</a>]. (<b>B</b>) 2D interaction diagram of Cbl-b peptide and the established interactions with CIN85 SH3 domains amino acids retrieved from PDB 2BZ8.</p> Full article ">Figure 3
<p>Schematic representations of the interactions occurring in the first MD simulation of CIN85-Cbl-b complex from PDB 2BZ8. (<b>A</b>) Histogram plot highlighting the CIN85 residues involving in the interactions with Cbl-b. (<b>B</b>) Timeline representations of the interactions during the MD simulation.</p> Full article ">Figure 4
<p>Schematic representations of the interactions occurring in the second MD simulation of CIN85-Cbl-b complex from PDB 2BZ8. (<b>A</b>) Histogram plot highlighting the CIN85 residues involving in the interactions with Cbl-b. (<b>B</b>) Timeline representations of the interactions during the MD simulation.</p> Full article ">Figure 5
<p>(<b>A</b>) Binding mode of MUC1 VNTR peptide CIN85 SH3 domains with the sequence GVTSAPDT*RPAP (filament with green stick bonds) retrieved from PDB 5OWP to CIN85 dimer from PDB 2BZ8 (orange structures), where chain A is represented on the right and chain B on the left. (<b>B</b>) MUC1 VNTR peptide interactions with SH3 domains residues of CIN85 from first prioritized protein-peptide docked complex.</p> Full article ">Figure 6
<p>Schematic representations of the interactions occurring in the first MD simulation of CIN85 dimer from PDB 2BZ8 in complex with MUC1 peptide from PDB 5OWP. (<b>A</b>) Histogram plot highlighting the CIN85 residues involving in the interactions with MUC1. (<b>B</b>) Timeline representations of the interactions during the MD simulation.</p> Full article ">Figure 7
<p>Schematic representations of the interactions occurring in the second MD simulation of CIN85 dimer from PDB 2BZ8 in complex with MUC1 peptide from PDB 5OWP. (<b>A</b>) Histogram plot highlighting the CIN85 residues involving in the interactions with MUC1. (<b>B</b>) Timeline representations of the interactions during the MD simulation.</p> Full article ">Figure 8
<p>(<b>A</b>) Putative binding mode of MUC1 peptide on CIN85 SH3A domain. MUC1 peptide is displayed as green sticks. The amino acids residues of the binding site are represented as grey sticks. The different types of interactions are highlighted as colour coded dotted lines: H-bonds are represented in yellow, salt bridge in violet and π-cation in green. (<b>B</b>) 2D depiction of the peptide-protein interactions.</p> Full article ">Figure 9
<p>Schematic representations of the interactions occurring in the first MD simulation of the complex MUC1-CIN85 monomer. (<b>A</b>) Histogram plot highlighting the CIN85 residues involving in the interactions with MUC1. (<b>B</b>) Timeline representations of the interactions during the MD simulation.</p> Full article ">Figure 10
<p>Schematic representations of the interactions occurring in the second MD simulation of the complex MUC1-CIN85 monomer. (<b>A</b>) Histogram plot highlighting the CIN85 residues involving in the interactions with MUC1. (<b>B</b>) Timeline representations of the interactions during the MD simulation.</p> Full article ">
24 pages, 4836 KiB  
Article
Differential Effects of STCH and Stress-Inducible Hsp70 on the Stability and Maturation of NKCC2
by Dalal Bakhos-Douaihy, Elie Seaayfan, Sylvie Demaretz, Martin Komhoff and Kamel Laghmani
Int. J. Mol. Sci. 2021, 22(4), 2207; https://doi.org/10.3390/ijms22042207 - 23 Feb 2021
Cited by 11 | Viewed by 3276
Abstract
Mutations in the Na-K-2Cl co-transporter NKCC2 lead to type I Bartter syndrome, a life-threatening kidney disease. We previously showed that export from the ER constitutes the limiting step in NKCC2 maturation and cell surface expression. Yet, the molecular mechanisms involved in this process [...] Read more.
Mutations in the Na-K-2Cl co-transporter NKCC2 lead to type I Bartter syndrome, a life-threatening kidney disease. We previously showed that export from the ER constitutes the limiting step in NKCC2 maturation and cell surface expression. Yet, the molecular mechanisms involved in this process remain obscure. Here, we report the identification of chaperone stress 70 protein (STCH) and the stress-inducible heat shock protein 70 (Hsp70), as two novel binding partners of the ER-resident form of NKCC2. STCH knock-down increased total NKCC2 expression whereas Hsp70 knock-down or its inhibition by YM-01 had the opposite effect. Accordingly, overexpressing of STCH and Hsp70 exerted opposite actions on total protein abundance of NKCC2 and its folding mutants. Cycloheximide chase assay showed that in cells over-expressing STCH, NKCC2 stability and maturation are heavily impaired. In contrast to STCH, Hsp70 co-expression increased NKCC2 maturation. Interestingly, treatment by protein degradation inhibitors revealed that in addition to the proteasome, the ER associated degradation (ERAD) of NKCC2 mediated by STCH, involves also the ER-to-lysosome-associated degradation pathway. In summary, our data are consistent with STCH and Hsp70 having differential and antagonistic effects with regard to NKCC2 biogenesis. These findings may have an impact on our understanding and potential treatment of diseases related to aberrant NKCC2 trafficking and expression. Full article
(This article belongs to the Section Biochemistry)
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Figure 1

Figure 1
<p>Identification of STCH as a novel NKCC2-interacting protein. (<b>A</b>) Mouse NKCC2 yeast two-hybrid baits constructs. A proposed topology for sodium-coupled chloride co-transporter NKCC2. N442 and N452 are the potential <span class="html-italic">N</span>-glycosylation sites. As previously described, mouse NKCC2 C terminus was divided into three peptide fragments (C1-term, C2-term, and C3-term) used as baits for the yeast two-hybrid. Similar to Aldolase B [<a href="#B39-ijms-22-02207" class="html-bibr">39</a>] and SCAMP2 [<a href="#B40-ijms-22-02207" class="html-bibr">40</a>], STCH interacts with C1-term while OS9 binds to C3-term [<a href="#B28-ijms-22-02207" class="html-bibr">28</a>]. (<b>B</b>) NKCC2 binds, in vivo, to STCH in HEK cells. HEK cells transiently transfected with Myc-NKCC2 singly or in combination with GFP-STCH were immunoprecipitated (IP) with anti-GFP anti-body (<b>lanes 2 and 3</b>). 5% of total cell lysate (Lys) was resolved as positive control. Co-immunoprecipitated NKCC2 and STCH proteins were detected by immunoblotting (IB) using anti-Myc (<b>lane 3</b>) and anti-GFP respectively (<b>lane 3</b>). IgGH, the heavy chain of IgG. The positions of immature (core glycosylated) and mature (complex-glycosylated) proteins of NKCC2 are indicated. The interaction of NKCC2 with STCH involves mainly the immature form of the co-transporter. (<b>C</b>) Imunofluorescence confocal microscopy showing distribution of Myc-NKCC2 and GFP-STCH in HEK cells. Fixed and permeabilized cells were stained with mouse anti-Myc for NKCC2 (Texas Red). The yellow color (merged image) indicates co-localization of the proteins. Bars, 5 μm.</p> Full article ">Figure 2
<p>STCH co-localizes with NKCC2 mainly at the Endoplasmic Reticulum. (<b>A</b>) Intracellular localization of NKCC2 and STCH in HEK cells. All panels are fluorescence micrographs of HEK cells overexpressing NKCC2 tagged with myc and STCH tagged with GFP. After transfection, cells were fixed and immunostained with mouse anti-Myc and rabbit anti-calnexin (ER marker) antibodies, and analyzed using a confocal laser scanning microscope. The merge color indicates overlap between the Myc tag of NKCC2 protein (Alexa Fluor 647, Blue), the GFP tag of STCH (green) and the ER marker (Alexa Fluor 555, red) and represents co-localization of the proteins. Bars, 5 μm. (<b>B</b>) <span class="html-italic">N</span>-glycosidases digestion of STCH in HEK cells. Exogenous STCH-GFP (<b>upper panel</b>) and endogenous STCH (<b>lower panel</b>) in lysates from cells overexpressing STCH-GFP were digested with Endo H and/or PNGase F and analyzed by Western blotting. (<b>C</b>) Comparison between the cellular localization of STCH and several organelle markers. Cells transfected with NKCC2 tagged with myc and STCH tagged with GFP were fixed after transfection, immunostained with anti-calnexin (ER marker) or -Giantin (Golgi marker) or -GM130 (Cis Golgi marker) or -LAMP2 (Lysosomal marker) antibodies and visualized with GFP tag of STCH (green) and Alexa Fluor 555 conjugated secondary antibodies for each organelle marker. Analysis was performed by confocal laser scanning microscopy. Bars, 5 μm.</p> Full article ">Figure 3
<p>STCH alters NKCC2 stability and maturation. (<b>A</b>) Total NKCC2 protein abundance is reduced by STCH in a dose-dependent fashion. HEK cells were co-transfected with Myc-NKCC2 (0.2 μg/well) and increasing amounts of STCH (0.2–0.6 μg/well) as indicated. NKCC2 proteins were detected by Western blotting with Myc antibody (left panel). <b>Right panel</b>, densitometric analysis of total, immature, and mature NKCC2 proteins. Data are expressed as a percentage of control. *, <span class="html-italic">p</span> &lt; 0.05 (<span class="html-italic">n</span> = 3). (<b>B</b>) STCH co-expression decreases the expression of NKCC2 proteins. <b>Upper panel</b>, representative immunoblot analysis showing the effect of STCH overexpression on NKCC2 protein abundance in HEK cells. Cells were transfected with Myc-NKCC2 alone (0.2 μg/well) or in the presence of GFP-STCH (0.6 μg/well). 16–18 h post-transfection, total cell lysates were subjected to immunoblot analysis for Myc-NKCC2 and anti-GFP. <b>Lower panel</b>, quantitation of steady state mature, immature, and total NKCC2 expression levels with or without STCH co-expression. Data are expressed as a percentage of control <span class="html-italic">±</span> SE, *, <span class="html-italic">p</span> &lt; 0.04 (<span class="html-italic">n</span> = 4); #, <span class="html-italic">p</span> &lt; 0.003 (<span class="html-italic">n</span> = 4); **, <span class="html-italic">p</span> &lt; 0.002 (<span class="html-italic">n</span> = 4), versus control. (<b>C</b>) STCH decreases NKCC2 stability and maturation. <b>Upper panel</b>, representative immunoblot showing cycloheximide chase analysis of NKCC2 in the presence or absence of GFP-STCH. 14–16 h post-transfection, HEK cells transiently expressing WT NKCC2 alone or in combination with STCH, were chased for the indicated time after addition of cycloheximide. Total cell lysates were separated by SDS-PAGE and probed by anti-Myc antibodies. <b>Lower panels,</b> quantitative analysis of NKCC2 stability and maturation. The density of the mature and immature form of NKCC2 proteins was normalized to the density at time 0. #, *; <span class="html-italic">p</span> &lt; 0.05 (<span class="html-italic">n</span> = 3) versus control. <span class="html-italic">NS</span>, a non-specific band illustrating the equal loading of protein extracts.</p> Full article ">Figure 4
<p>The effect of STCH on NKCC2 expression is independent of the expression system. (<b>A</b>) STCH interacts with immature NKCC2 in OKP cells. Cells were transiently transfected with Myc-NKCC2 either singly or in combination with GFP-STCH construct. Cell lysates were immunoprecipitated (IP) with anti-GFP antibody. NKCC2 protein was recovered from STCH immunoprecipitates mainly in its immature form (<b>lane 3</b>). (<b>B</b>) Imunofluorescence confocal microscopy showing distribution of Myc-NKCC2 and GFP-STCH in OKP cells. Cells were stained with mouse anti-Myc for NKCC2 (Texas Red). The yellow color (merged image) indicates co-localization of the proteins. Bars, 5 μm. (<b>C</b>) Similar to HEK cells, STCH and NKCC2 co-localizes mainly at the ER in OKP cells. All panels are fluorescence micrographs of OKP cells overexpressing myc-NKCC2 and GFP-STCH. <b>Upper panel</b>, fixed and permeabilized cells were stained with mouse anti-Myc and rabbit anti-calnexin (ER marker) antibodies. The merge color indicates overlap between the Myc tag of NKCC2 protein (Alexa Fluor 647, Blue), the GFP tag of STCH (green), and the ER marker (Alexa Fluor 555, red) and represents co-localization of the proteins. In <b>lower panel</b>, fixed and permeabilized cells were stained with mouse anti-Myc and rabbit anti-GM130 (cis-Golgi marker) antibodies. The merge color indicates overlap between the Myc tag of NKCC2 protein (Alexa Fluor 647, Blue), the GFP tag of STCH (green), and the cis-Golgi marker (Alexa Fluor 555, red) and represents co-localization of the proteins. In addition to the ER, the interaction between NKCC2 and STCH may also occur at the cis-Golgi. Analysis was performed by confocal laser scanning microscopy. Bars, 5 μm. (<b>D</b>) Analysis of NKCC2 stability and maturation monitored by cycloheximide-chase upon STCH expression. OKP cells were co-transfected with NKCC2 together with a control vector or GFP-STCH construct. Then, 14 h later, cell lysates were prepared at the indicated time points after cycloheximide treatment (100 μM). Total protein extracts are subjected to SDS-PAGE and probed using anti-Myc antibody. The density of the mature and immature forms of NKCC2 proteins was normalized to the density at time 0. #, *; <span class="html-italic">p</span> &lt; 0.05 (<span class="html-italic">n</span> = 3) versus control.</p> Full article ">Figure 5
<p>The ERAD of NKCC2 mediated by STCH involves both the proteasome and the lysosome. (<b>A</b>) Mannose trimming is required for STCH effect on NKCC2. OKP cells transiently transfected for with Myc-NKCC2 alone or with GFP-STCH, were treated with 25 μM of kifunensine (KIF) or without for 12–14 h prior to cell lysis. The cell lysates were subjected to SDS-PAGE and immunoblotted with anti-Myc and anti-GFP antibodies. <b>Bottom</b>, densitometric analysis of NKCC2 bands from untreated and treated cells with kifumensine (KIF). Data are expressed as percentage of control ± SE. *, <span class="html-italic">p</span> &lt; 0.02 versus control (<span class="html-italic">n</span> = 3). (<b>B</b>) STCH decreases NKCC2 expression in a proteasome-dependent and lysosome dependent manner. 16 h post-transfection, HEK cells were treated with or without 2 μm MG132 or 100 μm chloroquine for 6 h prior to cell lysis. The cell lysates were subjected to immunoblotting with anti-Myc and anti-GFP antibodies. <b>Bottom</b>, densitometric analysis of NKCC2 bands from untreated and treated cells with MG132 or chloroquine (CHLO). Data are expressed as percentage of control ±S.E. #, <span class="html-italic">p</span> &lt; 0.05 versus control (<span class="html-italic">n</span> = 3). <span class="html-italic">NS</span>, a non-specific band illustrating the equal loading of protein extracts.</p> Full article ">Figure 6
<p>NKCC2 interacts with the stress-inducible Hsp70. (<b>A</b>) Hsp70 interacts also with immature NKCC2. Cell lysates from OKP cells transiently transfected with Myc-NKCC2 singly or in combination with of Myc-Hsp70 were immunoprecipitated (IP) with anti-Hsp70 or anti-V5 antibody. NKCC2 protein was recovered from Hsp70 immunoprecipitates only in its immature form (<b>lane 3</b>). (<b>B</b>) Similar to STCH, Hsp70, and NKCC2 co-localizes at the ER. <b>Upper panel</b>, immunofluorescence confocal microscopy showing distribution of NKCC2 and Hsp70 in HEK cells. Transiently transfected HEK cells with EGFP-NKCC2 and Myc-HSP70, were fixed, permeabilized, and then stained with mouse anti-Myc for NKCC2 (Texas Red). The yellow color (merged image) illustrates co-localization of the proteins. <b>Middle panel</b>, HEK cells transfected with Myc-Hsp70 were stained with mouse anti-Myc (Texas Red; red) and rabbit anti-calnexin (FITC; green). Yellow indicates overlap between Hsp70 (red) and the ER marker (green). <b>Lower panel</b>, STCH colocalizes with Hsp70. HEK cells transiently transfected with GFP-STCH and Myc-Hsp70, were fixed and permeabilized before being stained with mouse anti-Myc for Hsp70 (Texas red, Red). Yellow illustrates overlap between Hsp70 (red) and the STCH (green). Bars, 5 μm.</p> Full article ">Figure 7
<p>STCH and Hsp70 differentially regulate NKCC2 and its disease-causing mutants. (<b>A</b>) Representative immunoblot of two independent experiments showing opposite effects of STCH and Hsp70 on NKCC2 protein abundance. HEK cells were co-transfected with Myc-NKCC2 (0.1 μg/well) and increasing amounts of GFP-STCH (0.1–0.5 μg/well) or Myc-Hsp70 (0.1–0.5 μg/well) as indicated. NKCC2, Hsp70, and STCH proteins were detected by immunoblotting with anti-Myc and anti-GFP anti-bodies. <b>Lower panel</b>, densitometric analysis of total NKCC2 proteins. Data are expressed as a percentage of control (<span class="html-italic">n</span> = 2). (<b>B</b>) Hsp70 co-expression increases NKCC2 maturation efficiency. <b>Upper panel</b>, two representative immunoblots illustrating the effect of Hsp70 overexpression on NKCC2 protein abundance and maturation in HEK cells. Cells were transfected with Myc-NKCC2 alone (0.1 μg/well) or in the presence of Myc-Hsp70 (0.1–0.5 μg/well). Then, 24–48 h post-transfection, total cell lysates were subjected to immunoblot analysis for NKCC2 and Hsp70 proteins using anti-Myc. <span class="html-italic">NS</span>, a non-specific band illustrating the equal loading of protein extracts. <b>Lower panel</b>, densitometric analysis of the maturation efficiency (ratio of the mature vs. immature form of NKCC2) of WT NKCC2 in the presence or absence of Hsp70. Data are expressed as percentage of control ± S.E. Each point represents mean ± SE from three independent experiments (<span class="html-italic">n</span> = 3). *, <span class="html-italic">p</span> &lt; 0.05 versus control. (<b>C</b>) Differential regulation of NKCC2 mutants by STCH and Hsp70. HEK cells were transiently transfected with NKCC2 or BS1 mutants (A508T or Y998X) in the presence or absence of STCH or Hsp70, as indicated. NKCC2, Hsp70, and STCH proteins were detected by immunoblotting with Myc antibody and anti-GFP. <b>Lower right panel</b>, densitometric analysis of total NKCC2 proteins. Data are expressed as a percentage of control. * and #, <span class="html-italic">p</span> &lt; 0.05 versus control. NKCC2 alone, <span class="html-italic">n</span> = 6. NKCC2 with STCH, <span class="html-italic">n</span> = 5. NKCC2 with Hsp70, <span class="html-italic">n</span> = 5. A508T alone, <span class="html-italic">n</span> = 4. A508T with STCH, <span class="html-italic">n</span> = 3. A508T with Hsp70, <span class="html-italic">n</span> = 3. Y998X alone, <span class="html-italic">n</span> = 6. Y998X with STCH, <span class="html-italic">n</span> = 3. Y998X with Hsp70, <span class="html-italic">n</span> = 4. <b>Lower left panel</b>, densitometric analysis of the maturation efficiency (ratio of the mature vs. immature form of NKCC2) of WT NKCC2 (<span class="html-italic">n</span> = 3), A508T (<span class="html-italic">n</span> = 3), and Y998X (<span class="html-italic">n</span> = 4), the presence or absence of Hsp70. Data are expressed as percentage of control ± S.E. *, <span class="html-italic">p</span> &lt; 0.05 versus control.</p> Full article ">Figure 8
<p>Differential regulation of NKCC2 expression by endogenous Hsp70 and STCH. (<b>A</b>,<b>B</b>) Knockdown of endogenous STCH or Hsp70 in HEK cells regulate total NKCC2 protein abundance in a dose-dependent fashion. <b>Upper panels</b>, representative immunoblot analysis of two independent experiments illustrating the effect of STCH knockdown (<b>upper left panel</b>) or Hsp70 knockdown (<b>lower right panel</b>) on NKCC2. HEK cells were transfected with NKCC2 in the absence (-) or presence of an increasing amount (+, ++, +++) of specific STCH siRNA or Hsp70 siRNA. 48 h post-transfection, total cell extract from each sample was run on a parallel SDS gel and Western blotted for total NKCC2 expression. NKCC2 proteins were detected by immunoblotting with Myc antibody. <b>Lower panels</b>, densitometric analysis of total NKCC2 proteins. Data are expressed as percentage of control (<span class="html-italic">n</span> = 2). (<b>C</b>) Opposite effects of STCH and Hsp70 knockdowns on total NKCC2 protein. Representative immunoblot analysis showing the effect of Hsp70 knockdown and STCH knockdown on total NKCC2. HEK cells were transfected with NKCC2 in the absence (−) or presence of specific Hsp70 siRNA (+) or STCH siRNA (+). Then, 48 h post-transfection, total cell extract from each sample was subjected to immunoblotting analysis. <b>Lower panel</b>, densitometric analysis of total NKCC2 proteins. Data are expressed as percentage of control. Each point represents mean ± SE from four independent experiments (<span class="html-italic">n</span> = 4). #, <span class="html-italic">p</span> &lt; 0.05 versus control. *, <span class="html-italic">p</span> &lt; 0.003 versus control. (<b>D</b>) Effect of Hsp70 inhibitor YM-01 on NKCC2. HEK cells transfected with NKCC2 were treated with 1 μM of YM-01 (+) or without (−) overnight before cell lysis and immunoblotting using anti-Myc for NKCC2. <span class="html-italic">NS</span>, a non-specific band illustrating the equal loading of protein extracts. <b>Lower panel</b>, densitometric analysis of total NKCC2 proteins. Data are expressed as percentage of control. Each point represents mean ± SE from three independent experiments (<span class="html-italic">n</span> = 3). *, <span class="html-italic">p</span> &lt; 0.05 versus control.</p> Full article ">
13 pages, 2054 KiB  
Review
Macrophage Function and the Role of GSK3
by Sarvatit Patel and Geoff H. Werstuck
Int. J. Mol. Sci. 2021, 22(4), 2206; https://doi.org/10.3390/ijms22042206 - 23 Feb 2021
Cited by 18 | Viewed by 4392
Abstract
Macrophages are present in nearly all vertebrate tissues, where they respond to a complex variety of regulatory signals to coordinate immune functions involved in tissue development, metabolism, homeostasis, and repair. Glycogen synthase kinase 3 (GSK3) is a ubiquitously expressed protein kinase that plays [...] Read more.
Macrophages are present in nearly all vertebrate tissues, where they respond to a complex variety of regulatory signals to coordinate immune functions involved in tissue development, metabolism, homeostasis, and repair. Glycogen synthase kinase 3 (GSK3) is a ubiquitously expressed protein kinase that plays important roles in multiple pathways involved in cell metabolism. Dysregulation of GSK3 has been implicated in several prevalent metabolic disorders, and recent findings have highlighted the importance of GSK3 activity in the regulation of macrophages, especially with respect to the initiation of specific pathologies. This makes GSK3 a potential therapeutic target for the development of novel drugs to modulate immunometabolic responses. Here, we summarize recent findings that have contributed to our understanding of how GSK3 regulates macrophage function, and we discuss the role of GSK3 in the development of metabolic disorders and diseases. Full article
(This article belongs to the Special Issue Pathomechanisms of Atherosclerosis. Part III)
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<p>Macrophage: polarization, function, and associated diseases. Three main families of receptors regulate macrophage polarization and function. These are (1) the toll-like receptors (TLRs) that signal through nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) and AP-1, (2) the interferon receptor (IFNR) and interleukin (IL)-4 receptors that signal through signal transducer and activator of transcriptions (STATs), and (3) the nuclear receptors. Macrophage stimulated with lipopolysaccharide (LPS) and/or interferon-gamma (IFNγ) polarize to pro-inflammatory (M1) macrophages. Stimulation with IL4 induce polarization to anti-inflammatory (M2) macrophages. Regulation is important for proper physiological responses; however, dysregulation can contribute to the pathogenesis of diseases.</p> Full article ">Figure 2
<p>GSK3α/β: regulation, cellular functions and diseases. Three cellular signaling pathways are directly involved in GSK3α/β regulation: (1) insulin binds to the insulin receptor and activates the PI3-Akt pathway leading to GSK3α/β inhibition; (2) endoplasmic reticulum stress (ER stress) signaling and/or unfolded protein response (UPR) activation promotes the activation of GSK3α/β through the endoplasmic reticulum kinase (PERK) pathway; and (3) Wnt ligands bind to the Frizzled receptor and induces the formation of a complex of the scaffold protein axin, APC, CK1 and the kinase Dishevelled, which phosphorylates and inactivates GSK3α/β. The complex interplay between these pathways regulates the network of signaling pathways that modulate cell viability and metabolism.</p> Full article ">Figure 3
<p>A summary of the GSK3α/β signaling pathways in macrophage functions and related diseases. In macrophages GSK3α/β can be activated or inactivated by different upstream signaling pathways. GSK3α/β has a large number of downstream substrates that regulate a variety of different downstream signaling pathways to control macrophage phenotype and function. Dysregulation of one or more of these pathways has been implicated in the development of several different disorders/diseases.</p> Full article ">
17 pages, 1939 KiB  
Article
Rainbow Trout (Oncorhynchus mykiss) Na+/H+ Exchangers tNhe3a and tNhe3b Display Unique Inhibitory Profiles Dissimilar from Mammalian NHE Isoforms
by Salvatore Blair, Xiuju Li, Debajyoti Dutta, Danuta Chamot, Larry Fliegel and Greg Goss
Int. J. Mol. Sci. 2021, 22(4), 2205; https://doi.org/10.3390/ijms22042205 - 23 Feb 2021
Cited by 10 | Viewed by 2459
Abstract
Freshwater fishes maintain an internal osmolality of ~300 mOsm, while living in dilute environments ranging from 0 to 50 mOsm. This osmotic challenge is met at least partially, by Na+/H+ exchangers (NHE) of fish gill and kidney. In this study, [...] Read more.
Freshwater fishes maintain an internal osmolality of ~300 mOsm, while living in dilute environments ranging from 0 to 50 mOsm. This osmotic challenge is met at least partially, by Na+/H+ exchangers (NHE) of fish gill and kidney. In this study, we cloned, expressed, and pharmacologically characterized fish-specific Nhes of the commercially important species Oncorhynchus mykiss. Trout (t) Nhe3a and Nhe3b isoforms from gill and kidney were expressed and characterized in an NHE-deficient cell line. Western blotting and immunocytochemistry confirmed stable expression of the tagged trout tNhe proteins. To measure NHE activity, a transient acid load was induced in trout tNhe expressing cells and intracellular pH was measured. Both isoforms demonstrated significant activity and recovered from an acute acid load. The effect of the NHE transport inhibitors amiloride, EIPA (5-(N-ethyl-N-isopropyl)-amiloride), phenamil, and DAPI was examined. tNhe3a was inhibited in a dose-dependent manner by amiloride and EIPA and tNhe3a was more sensitive to amiloride than EIPA, unlike mammalian NHE1. tNhe3b was inhibited by high concentrations of amiloride, while even in the presence of high concentrations of EIPA (500 µM), some activity of tNhe3b remained. Phenamil and DAPI were ineffective at inhibiting tNhe activity of either isoform. The current study aids in understanding the pharmacology of fish ion transporters. Both isoforms display inhibitory profiles uniquely different from mammalian NHEs and show resistance to inhibition. Our study allows for more direct interpretation of past, present, and future fish-specific sodium transport studies, with less reliance on mammalian NHE data for interpretation. Full article
(This article belongs to the Section Biochemistry)
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<p>RT-PCR analysis of gene expression in trout tissues. Total RNA was extracted from adult rainbow trout gill and kidney tissue and analyzed with RT-PCR using gene specific primers for <span class="html-italic">nhe3a nhe3b</span>, and <span class="html-italic">ef1α (elongation factor 1 alpha)</span>.</p> Full article ">Figure 2
<p>Western blot analysis of expression tNhe3 proteins. Western blot of whole cell lysates of stable cell lines expressing tNhe3a or tNhe3b proteins. Moreover, 100 μg of total protein was loaded in each lane. The sample was immunoblotted with anti-GFP tag antibody. AP-1 is a cell lysate from mock transfected AP-1 cells.</p> Full article ">Figure 3
<p>Confocal imaging of expression tNhe3 proteins. Confocal fluorescent imaging (63 × objective lens) of cell preparations of stable AP-1 cell lines either non-transfected or expressing tNhe3a or tNhe3b proteins. (<b>A</b>) Non-transfected AP-1 cell stained with DAPI. (<b>B</b>) GFP tagged-tNhe3a expressing cells. (<b>C</b>) GFP tagged-tNhe3b expressing cells. Intracellular and cell membrane protein expression is present in each of the stably expressing tNhe cell lines. Scale bar represents 20 μm.</p> Full article ">Figure 4
<p>Summary of activity of tNhe3 proteins in stably transfected AP-1 cells. Activity was measured after ammonium chloride pre-pulse as described in the “Materials and Methods”. Results are ∆ intracellular pH/s. Data are presented mean ± SE, while dissimilar letters indicate statistical significance between groups as demonstrated by one-way ANOVA, with Tukey’s multiple comparisons test (n ≥ 6, <span class="html-italic">p</span> &lt; 0.05, ANOVA).</p> Full article ">Figure 5
<p>Effect of varying concentrations of amiloride on activity of tNhe3a. tNhe3a containing cells were subjected to a two pulse Na<sup>+</sup>/H<sup>+</sup> exchanger activity assay and the activity (ROR, rate of recovery) of the exchanger in the second pulse was compared to that of the first pulse. The second pulse was in the presence of the indicated inhibitor. A control was in the presence of equal amounts of vehicle (DMSO). Amiloride concentrations were from 1 to 1000 µM. IC50 was estimated at 9.3 uM as described earlier [<a href="#B28-ijms-22-02205" class="html-bibr">28</a>]. Raw data presented in <a href="#app1-ijms-22-02205" class="html-app">Figure S2</a>. Asterisk * indicates significantly different from the control at <span class="html-italic">p</span> &lt; 0.05, one-way ANOVA, with Tukey’s multiple comparison’s test. Data are presented as mean +/− SE. Each data point is mean of 8–11 measurements.</p> Full article ">Figure 6
<p>Effect of varying concentrations of EIPA on activity of tNhe3a. tNhe3a containing cells were subjected to a two pulse Na<sup>+</sup>/H<sup>+</sup> exchanger activity assay and measured as described in <a href="#ijms-22-02205-f005" class="html-fig">Figure 5</a>. EIPA concentrations were from 1 to 500 µM. IC50 estimated at 44 µM. Raw data presented in <a href="#app1-ijms-22-02205" class="html-app">Figure S3</a>. Asterisk * indicates significantly different from the control at <span class="html-italic">p</span> &lt; 0.05, one-way ANOVA, with Tukey’s multiple comparison’s test. Data are presented as mean +/− SE and each experimental point is 8–10 measurements, control n = 18.</p> Full article ">Figure 7
<p>Effect of phenamil, or DAPI on tNhe3b activity. The cells were subjected to a two pulse Na<sup>+</sup>/H<sup>+</sup> exchanger activity assay and measured as described in <a href="#ijms-22-02205-f005" class="html-fig">Figure 5</a>. The control treatment was in the presence of equal amounts of vehicle (DMSO). Na<sup>+</sup>/H<sup>+</sup> exchanger activity presented as % of control AP1 cells. Asterisk <sup>*</sup> indicates significance from the control as demonstrated by one-way ANOVA at <span class="html-italic">p</span> &lt; 0.05. Results are mean +/− SE of at least eight independent experiments.</p> Full article ">Figure 8
<p>Effect of Amiloride on tNhe3b activity. The cells were subjected to a two pulse Na<sup>+</sup>/H<sup>+</sup> exchanger activity assay and measured as described in <a href="#ijms-22-02205-f005" class="html-fig">Figure 5</a>. A control was in the presence of equal amounts of vehicle (DMSO). Asterisk * indicates significantly different from the control at <span class="html-italic">p</span> &lt; 0.05, one-way ANOVA, with Tukey’s multiple comparison’s test. IC50 relatively incalculable, but approximately 335 µM. Each experimental point is mean +/− SE of 7–11 measurements, control n = 17.</p> Full article ">Figure 9
<p>Effect of varying concentrations of EIPA on activity of tNhe3b. tNhe3b containing cells were subjected to a two pulse Na<sup>+</sup>/H<sup>+</sup> exchanger activity assay and the activity was measured as described in <a href="#ijms-22-02205-f005" class="html-fig">Figure 5</a>. EIPA concentrations were from 1 to 500 uM. IC50 cannot be calculated. Results are mean +/− SE of 8–16 independent experiments with no significant differences (<span class="html-italic">p</span> &lt; 0.05, ANOVA).</p> Full article ">
17 pages, 8210 KiB  
Review
The Interplay between Drivers of Erythropoiesis and Iron Homeostasis in Rare Hereditary Anemias: Tipping the Balance
by Simon Grootendorst, Jonathan de Wilde, Birgit van Dooijeweert, Annelies van Vuren, Wouter van Solinge, Roger Schutgens, Richard van Wijk and Marije Bartels
Int. J. Mol. Sci. 2021, 22(4), 2204; https://doi.org/10.3390/ijms22042204 - 23 Feb 2021
Cited by 6 | Viewed by 3993
Abstract
Rare hereditary anemias (RHA) represent a group of disorders characterized by either impaired production of erythrocytes or decreased survival (i.e., hemolysis). In RHA, the regulation of iron metabolism and erythropoiesis is often disturbed, leading to iron overload or worsening of chronic anemia due [...] Read more.
Rare hereditary anemias (RHA) represent a group of disorders characterized by either impaired production of erythrocytes or decreased survival (i.e., hemolysis). In RHA, the regulation of iron metabolism and erythropoiesis is often disturbed, leading to iron overload or worsening of chronic anemia due to unavailability of iron for erythropoiesis. Whereas iron overload generally is a well-recognized complication in patients requiring regular blood transfusions, it is also a significant problem in a large proportion of patients with RHA that are not transfusion dependent. This indicates that RHA share disease-specific defects in erythroid development that are linked to intrinsic defects in iron metabolism. In this review, we discuss the key regulators involved in the interplay between iron and erythropoiesis and their importance in the spectrum of RHA. Full article
(This article belongs to the Special Issue Regulation of Erythropoiesis 2.0)
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<p>Simplified overview of iron homeostasis. Thickness of arrows reflects amount of iron per compartment. In humans, daily absorption of iron, as well as iron loss, is minimal. Most iron is either stored, used for cellular processes or is present in the erythroid compartment. (<b>A</b>) Iron recycling within the erythroid compartment. Iron is incorporated in hemoglobin and recycling of iron occurs due to splenic clearance of senescent red blood cells. (<b>B</b>) Iron absorption, transport and storage. Enteral absorption is facilitated by divalent metal transporter 1 (DMT1). Iron is processed and secreted to the circulation via ferroportin (FPN), the carrier protein through which stored iron is also secreted from within macrophages and hepatocytes. In the circulation iron binds to transferrin (Tf) and cellular uptake occurs upon binding of Tf to transferrin receptor 1 (TfR1). Iron is primarily stored as ferritin within cells. (<b>C</b>) Hepcidin-ferroportin axis. Hepcidin expression is predominantly induced by the bone morphogenetic protein (BMP)/Smad signaling pathway, upon increased serum iron levels. Alternatively, the Janus kinase 2/Signal Transducer and Activator of Transcription 3 (JAK2/STAT3) pathway is activated upon inflammation through interleukin-6 (IL-6). Hepcidin blocks FPN-dependent iron export, and induces FPN degradation, resulting in a limitation of iron absorption and iron efflux from body iron storages [<a href="#B16-ijms-22-02204" class="html-bibr">16</a>].</p> Full article ">Figure 2
<p>Simplified overview of connecting factors in erythropoiesis and iron metabolism. (<b>A</b>) Healthy situation. Normal production of red blood cells (RBCs) to prevent tissue hypoxia, erythropoietin (EPO) levels are low. erythroferrone (ERFE) levels are normal, little impact on iron metabolism. (<b>B</b>) Acute anemia or EPO injection. Low levels of oxygen lead to increased EPO levels. EPO stimulates erythroblast proliferation and maturation and subsequently upregulation of soluble transferrin receptor 1 (sTfr1) and ERFE levels. Hepcidin levels are suppressed via ERFE, allowing increased iron uptake, followed by incorporation in hemoglobin in erythroblasts. This results in an increase in RBCs and compensation for the anemia. (<b>C</b>) Iron loading anemia. This is characterized by ineffective erythropoiesis, resulting in suboptimal compensation for anemia, leading to a constitutively hyperactive bone marrow and a persistent increase in EPO and sTfR levels, with or without high reticulocyte numbers. Iron levels are sufficient to cover for erythroid demand. Hepcidin levels are persistently low, partially due to high ERFE levels, leading to iron overload.</p> Full article ">
13 pages, 1093 KiB  
Review
Current Understanding of Role of Vesicular Transport in Salt Secretion by Salt Glands in Recretohalophytes
by Chaoxia Lu, Fang Yuan, Jianrong Guo, Guoliang Han, Chengfeng Wang, Min Chen and Baoshan Wang
Int. J. Mol. Sci. 2021, 22(4), 2203; https://doi.org/10.3390/ijms22042203 - 23 Feb 2021
Cited by 18 | Viewed by 4059
Abstract
Soil salinization is a serious and growing problem around the world. Some plants, recognized as the recretohalophytes, can normally grow on saline–alkali soil without adverse effects by secreting excessive salt out of the body. The elucidation of the salt secretion process is of [...] Read more.
Soil salinization is a serious and growing problem around the world. Some plants, recognized as the recretohalophytes, can normally grow on saline–alkali soil without adverse effects by secreting excessive salt out of the body. The elucidation of the salt secretion process is of great significance for understanding the salt tolerance mechanism adopted by the recretohalophytes. Between the 1950s and the 1970s, three hypotheses, including the osmotic potential hypothesis, the transfer system similar to liquid flow in animals, and vesicle-mediated exocytosis, were proposed to explain the salt secretion process of plant salt glands. More recently, increasing evidence has indicated that vesicular transport plays vital roles in salt secretion of recretohalophytes. Here, we summarize recent findings, especially regarding the molecular evidence on the functional roles of vesicular trafficking in the salt secretion process of plant salt glands. A model of salt secretion in salt gland is also proposed. Full article
(This article belongs to the Special Issue Channels and Transporters in Cells and Tissues 2.0)
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<p>Simplified illustration of salt secretion from plant salt glands. Na<sup>+</sup> is transported into the salt gland from the collecting cell, which covers the salt gland, and consists of a huge vacuole and a shrinking cytoplasm, through the plasmodesmata (pathway 1), membrane-bound transporters (pathway 2) such as SOS1 in the transfusion zone, or via vesicular transport (pathway 3). In the salt gland (blue), the ions can be directly transported into the intercellular space of the outer or inner cup cells and the secretory cells via the different pathways (①, ②, ③). The ions are parceled into vesicles for transport from the cytosol to the plasma membrane, then secreted out of the salt gland cells via pathways ② and ③. The ions are eventually forced out of the secretory pores ④ at the top of the salt gland as result of the high hydrostatic pressure. Ion transporters in charge of influx (green) and efflux (blue) are asymmetrically distributed in the plasma membrane of salt gland cells. PLAS, plasmodesmata; HKT1, high-affinity K<sup>+</sup> transporter 1; CNGC, cyclic nucleotide-gated cation channel; NSCC, non-selective cationic channel; PIP, plasma membrane intrinsic protein; NHX, Na<sup>+</sup>/H<sup>+</sup> antiporter; SOS1, Na<sup>+</sup>/H<sup>+</sup> antiporter; CLC, chloride channel.</p> Full article ">Figure 2
<p>Vesicular transport in the salt gland secretion process. Excessive ions in the cytoplasm are pumped into the SYP61- or ECH-labeled vesicles by NHX5/6 and the CLCd/f anti-transporter. The osmotic potential and pH balance of the vesicles are adjusted by the aquaporin PIP 2;7 and the proton pump VHA-a1. SYP61, Syntaxin of plants 61; ECH, ECHIDNA protein; NHX5/6, Na<sup>+</sup>/H<sup>+</sup> antiporter 5/6; PIP2;7, plasma membrane intrinsic protein 2;7; CLCd/f, chloride channel d/f.</p> Full article ">
18 pages, 7197 KiB  
Article
Overexpression of miR-1306-5p, miR-3195, and miR-3914 Inhibits Ameloblast Differentiation through Suppression of Genes Associated with Human Amelogenesis Imperfecta
by Hiroki Yoshioka, Yin-Ying Wang, Akiko Suzuki, Meysam Shayegh, Mona V. Gajera, Zhongming Zhao and Junichi Iwata
Int. J. Mol. Sci. 2021, 22(4), 2202; https://doi.org/10.3390/ijms22042202 - 23 Feb 2021
Cited by 10 | Viewed by 2975
Abstract
Amelogenesis imperfecta is a congenital form of enamel hypoplasia. Although a number of genetic mutations have been reported in humans, the regulatory network of these genes remains mostly unclear. To identify signatures of biological pathways in amelogenesis imperfecta, we conducted bioinformatic analyses on [...] Read more.
Amelogenesis imperfecta is a congenital form of enamel hypoplasia. Although a number of genetic mutations have been reported in humans, the regulatory network of these genes remains mostly unclear. To identify signatures of biological pathways in amelogenesis imperfecta, we conducted bioinformatic analyses on genes associated with the condition in humans. Through an extensive search of the main biomedical databases, we found 56 genes in which mutations and/or association/linkage were reported in individuals with amelogenesis imperfecta. These candidate genes were further grouped by function, pathway, protein–protein interaction, and tissue-specific expression patterns using various bioinformatic tools. The bioinformatic analyses highlighted a group of genes essential for extracellular matrix formation. Furthermore, advanced bioinformatic analyses for microRNAs (miRNAs), which are short non-coding RNAs that suppress target genes at the post-transcriptional level, predicted 37 candidates that may be involved in amelogenesis imperfecta. To validate the miRNA–gene regulation association, we analyzed the target gene expression of the top seven candidate miRNAs: miR-3195, miR-382-5p, miR-1306-5p, miR-4683, miR-6716-3p, miR-3914, and miR-3935. Among them, miR-1306-5p, miR-3195, and miR-3914 were confirmed to regulate ameloblast differentiation through the regulation of genes associated with amelogenesis imperfecta in AM-1 cells, a human ameloblastoma cell line. Taken together, our study suggests a potential role for miRNAs in amelogenesis imperfecta. Full article
(This article belongs to the Special Issue Gene Networks That Control Cell Proliferation and Differentiation)
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<p>The flowchart for literature mining based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline, including the sequential steps for the identification, screening, eligibility check, and qualification of the literature.</p> Full article ">Figure 2
<p>Bioinformatic analysis of the identified amelogenesis imperfecta-related genes, including functional enrichment analysis, construction of amelogenesis imperfecta-related protein interaction network, tissue-specific expression of amelogenesis imperfecta-related genes, and construction of miRNA–gene regulations.</p> Full article ">Figure 3
<p>Functional enrichment analysis of amelogenesis imperfecta-related genes. (<b>a</b>) Top 20 most significantly enriched diseases. (<b>b</b>) Enriched pathway–gene network: nodes annotated in black represent pathways, while the others in red denote genes. Genes associated with multiple terms, especially multiple categories of functions, are marked with different colors.</p> Full article ">Figure 4
<p>Protein–protein interaction (PPI) network of amelogenesis imperfecta-related genes. Red nodes represent amelogenesis imperfecta-related genes and blue nodes denote the genes that interact with amelogenesis imperfecta genes in the PPI network. The size of the nodes was ranked according to node degree. The PPI network we used here was a combination of all five databases.</p> Full article ">Figure 5
<p>Characteristics of miRNAs associated with amelogenesis imperfecta (AI). (<b>a</b>) The distribution of miRNAs interacting with amelogenesis imperfecta-associated genes. (<b>b</b>) The enriched miRNA regulation network. Red circles denote genes related with amelogenesis imperfecta. Green squares denote human miRNAs enriched with amelogenesis imperfecta-related genes. An edge is laid when interaction between miRNA and gene has been reported in the database.</p> Full article ">Figure 6
<p>Effects of overexpression of candidate miRNAs on ameloblast differentiation. (<b>a</b>) Scheme of the experimental timeline. (<b>b</b>) Gene expression of AMELX, AMTN, KLK4, and MMP20 after treatment with a mimic of control or candidate miRNAs in AM-1 cells. * <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>c</b>) Immunocytochemistry analysis for KLK4 (green) in AM-1 cells under the indicated conditions. The nuclei were counterstained with 4’,6’-diamidino-2-phenylindole [DAPI (blue)]. Scale bar, 150 μm.</p> Full article ">Figure 7
<p>Effects of overexpression of candidate miRNAs on target gene expression. (<b>a</b>) Quantitative real-time polymerase chain reaction (RT-PCR) analyses for the target gene expression after treatment with control and miR-1306-5p mimic. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; NS, not significant. Control miR proliferation: cells were treated with control miR mimic during the cell proliferation phase. Control miR differentiation: cells were treated with control miR mimic under differentiation conditions for 3 days. (<b>b</b>) Quantitative RT-PCR analyses for target gene expression after treatment with control and miR-3195 mimic. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; NS, not significant. (<b>c</b>) Quantitative RT-PCR analyses for target gene expression after treatment with control and miR-3914 mimic. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; NS, not significant.</p> Full article ">
26 pages, 8897 KiB  
Review
Advances in Targeting HPV Infection as Potential Alternative Prophylactic Means
by Sinead Carse, Martina Bergant and Georgia Schäfer
Int. J. Mol. Sci. 2021, 22(4), 2201; https://doi.org/10.3390/ijms22042201 - 23 Feb 2021
Cited by 12 | Viewed by 6491
Abstract
Infection by oncogenic human papillomavirus (HPV) is the primary cause of cervical cancer and other anogenital cancers. The majority of cervical cancer cases occur in low- and middle- income countries (LMIC). Concurrent infection with Human Immunodeficiency Virus (HIV) further increases the risk of [...] Read more.
Infection by oncogenic human papillomavirus (HPV) is the primary cause of cervical cancer and other anogenital cancers. The majority of cervical cancer cases occur in low- and middle- income countries (LMIC). Concurrent infection with Human Immunodeficiency Virus (HIV) further increases the risk of HPV infection and exacerbates disease onset and progression. Highly effective prophylactic vaccines do exist to combat HPV infection with the most common oncogenic types, but the accessibility to these in LMIC is severely limited due to cost, difficulties in accessing the target population, cultural issues, and maintenance of a cold chain. Alternative preventive measures against HPV infection that are more accessible and affordable are therefore also needed to control cervical cancer risk. There are several efforts in identifying such alternative prophylactics which target key molecules involved in early HPV infection events. This review summarizes the current knowledge of the initial steps in HPV infection, from host cell-surface engagement to cellular trafficking of the viral genome before arrival in the nucleus. The key molecules that can be potentially targeted are highlighted, and a discussion on their applicability as alternative preventive means against HPV infection, with a focus on LMIC, is presented. Full article
(This article belongs to the Special Issue Human Papillomavirus from Lab to Life: Insights from Molecular Researches)
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<p>Schematic illustration of the early stages of human papillomavirus (HPV) infection, indicating the sites of inhibition of various anti-HPV molecules. Briefly: binding to heparan sulfate proteoglycans (HSPGs) results in conformational changes of the viral capsid, which facilitates interactions between the capsid and cyclophilin B (CyPB) and cleavage by kallikrein-8 (KLK8). This results in the exposure of the L2 N-terminus, containing a conserved site which is cleaved by furin. This is followed by dissociation of the capsid from HSPGs and exposure of a binding site in L1, potentially needed for recognition by an unknown entry receptor complex. The viral capsid undergoes ligand induced endocytosis (which is clathrin-, caveolin-, cholesterol- and dynamin-independent) and depends on the reorganization of the actin cytoskeleton. Membrane protrusion of the L2 capsid protein is chaperoned by γ-secretase, which allows L2 to interact with host cell factors in the cytosol during transport. HPVs localize with early antigen 1 (EEA10) compartments in a Rab5 GTPase-dependent manner. The early endosome matures into the late endosome when it fuses with lysosomes. Lysosomal degradation is driven by the formation of multivesicular bodies (MVBs). Most of the contents are degraded by lysosomal degradation, including the majority of the L1 capsid protein. Endosomal escape and subsequent post-endocytic trafficking of high-risk HPVs is regulated by CD63-syntenin-1-ALIX, which traffics HPV to these multivesicular endosomes. Here, the capsids disassemble in a pH-dependent manner, and egress from the late endosome. The L2/vDNA cargo enters the TGN, where the protruding L2 protein interacts with SNX17, SNX27 and retromer complex.</p> Full article ">
21 pages, 31051 KiB  
Article
Structural Communication between the E. coli Chaperones DnaK and Hsp90
by Matthew P. Grindle, Ben Carter, John Paul Alao, Katherine Connors, Riina Tehver and Andrea N. Kravats
Int. J. Mol. Sci. 2021, 22(4), 2200; https://doi.org/10.3390/ijms22042200 - 23 Feb 2021
Cited by 7 | Viewed by 3518
Abstract
The 70 kDa and 90 kDa heat shock proteins Hsp70 and Hsp90 are two abundant and highly conserved ATP-dependent molecular chaperones that participate in the maintenance of cellular homeostasis. In Escherichia coli, Hsp90 (Hsp90Ec) and Hsp70 (DnaK) directly interact [...] Read more.
The 70 kDa and 90 kDa heat shock proteins Hsp70 and Hsp90 are two abundant and highly conserved ATP-dependent molecular chaperones that participate in the maintenance of cellular homeostasis. In Escherichia coli, Hsp90 (Hsp90Ec) and Hsp70 (DnaK) directly interact and collaborate in protein remodeling. Previous work has produced a model of the direct interaction of both chaperones. The locations of the residues involved have been confirmed and the model has been validated. In this study, we investigate the allosteric communication between Hsp90Ec and DnaK and how the chaperones couple their conformational cycles. Using elastic network models (ENM), normal mode analysis (NMA), and a structural perturbation method (SPM) of asymmetric and symmetric DnaK-Hsp90Ec, we extract biologically relevant vibrations and identify residues involved in allosteric signaling. When one DnaK is bound, the dominant normal modes favor biological motions that orient a substrate protein bound to DnaK within the substrate/client binding site of Hsp90Ec and release the substrate from the DnaK substrate binding domain. The presence of one DnaK molecule stabilizes the entire Hsp90Ec protomer to which it is bound. Conversely, the symmetric model of DnaK binding results in steric clashes of DnaK molecules and suggests that the Hsp90Ec and DnaK chaperone cycles operate independently. Together, this data supports an asymmetric binding of DnaK to Hsp90Ec. Full article
(This article belongs to the Section Biochemistry)
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<p>DnaK-Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> docked model. The residues of DnaK and Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> that are involved in the direct interaction have previously been described [<a href="#B65-ijms-22-02200" class="html-bibr">65</a>,<a href="#B66-ijms-22-02200" class="html-bibr">66</a>,<a href="#B72-ijms-22-02200" class="html-bibr">72</a>]. (<b>a</b>) Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math>-DnaK docked model. (<b>b</b>) Residues of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> (magenta) that interact with DnaK are localized in the MD (green) outside of the cleft of the Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> dimer. (<b>c</b>) Residues of DnaK (orange) that interact with Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> are located in the NBD (grey).</p> Full article ">Figure 2
<p>Normal modes of apo Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> (<b>a</b>) Structural overlap of the normal modes of apo Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> with ADP bound Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> to identify the modes that contribute to the biological movement. The closed circles represent the overlap for individual modes. Lines are drawn for clarity. Nonzero modes with the highest structural overlap are considered. (<b>b</b>) The sum of the individual amino acid fluctuations in both modes 7 and 8 are represented on the structure of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math>. Blue represents static residues while red highlights highly mobile residues.</p> Full article ">Figure 3
<p>Motions associated with significant normal modes of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> alone. (<b>a</b>) Mode 7 consists of swing motions of each protomer that contributes to closing and dimerization. (<b>b</b>) Covariance matrix of amino acid pairs for Mode 7 (<b>c</b>) Mode 8 consists of torsional motions about the CTD. (<b>d</b>) Covariance matrix of amino acid pairs for modes 8. Arrows in (<b>a</b>,<b>c</b>) indicate the amplitude and direction of motions of amino acids in each mode. The color scheme highlights the Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> N-domain in yellow, M-domain in green, C-domain in blue. Correlated movements in covariance matricies (<b>b</b>,<b>d</b>) are highlighted in red while anticorrelated movements are represented in blue.</p> Full article ">Figure 4
<p>Normal modes of asymmetric DnaK bound Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> (<b>a</b>) Structural overlap of DnaK bound Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> model with ADP bound Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> to identify the dominant modes that contribute to the biological movement. The closed circles represent the overlap for individual modes. Lines are drawn for clarity. Nonzero modes with the highest structural overlap are considered. (<b>b</b>) The sum of the individual amino acid fluctuations in both modes 8 and 10 are represented on the structure of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math>. Blue represents static residues while red highlights highly mobile residues.</p> Full article ">Figure 5
<p>Motions associated with significant normal modes of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> when one DnaK is bound. (<b>a</b>) Mode 8 involves a scissoring motion about the CTD domains of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> with DnaK undergoing torsional motions perpendicular to the protomer of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> which it is bound. The DnaK SBD is placed into the client binding site of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> (<b>b</b>) Covariance matrix of amino acid pairs for Mode 8 (<b>c</b>) Mode 10 is a torsional motion of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> about the CTD dimerization domain with DnaK undergoing torsions about the same axis as Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math>. (<b>d</b>) Covariance matrix of amino acid pairs for modes 10. The DnaK SBD-<math display="inline"><semantics> <mi>α</mi> </semantics></math> and SBD-<math display="inline"><semantics> <mi>β</mi> </semantics></math> open to potentially release a client. Arrows in (<b>a</b>,<b>c</b>) indicate the amplitude and direction of motions of amino acids in each mode. The NBD of DnaK is colored in grey with the SBD-<math display="inline"><semantics> <mi>α</mi> </semantics></math> in mauve and the SBD-<math display="inline"><semantics> <mi>β</mi> </semantics></math> in red. Correlated movements in covariance matricies (<b>b</b>,<b>d</b>) are highlighted in red while anticorrelated movements are represented in blue.</p> Full article ">Figure 6
<p>Normal modes of symmetric DnaK bound Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> (<b>a</b>) Structural overlap of the two DnaK bound Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> model with ADP bound Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> to identify the dominant modes that contribute to the biological movement. The closed circles represent the overlap for individual modes. Lines are drawn for clarity. Nonzero modes with the highest structural overlap are considered.(<b>b</b>) The sum of the individual amino acid fluctuations in both modes 13, 28, and 8 are represented on the structure of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math>. Blue represents static residues while red highlights highly mobile residues.</p> Full article ">Figure 7
<p>Motions associated with significant normal modes of one Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> dimer when two DnaK monomers are bound. (<b>a</b>) Mode 13 is characterized by a torsional motion about the C-terminus of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math>. The DnaK SBDs are oriented toward the client binding region of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> resulting in steric clashes. (<b>b</b>) The covariance matrix of amino acid pairs for Mode 13. (<b>c</b>) Mode 28 involves a torsional motion of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> about the CTD dimerization domain. The NBD of both DnaK molecules moves away from the axis of Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> while the DnaK SBDs are immobile. (<b>d</b>) The covariance matrix of amino acid pairs for Mode 28. (<b>e</b>) Mode 8 also involves a torsional motion about the Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> CTD similar to Mode 13, but with the SBDs of each DnaK moving away from the Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> vertex. (<b>f</b>) Covariance matrix of amino acid pairs for Mode 8. Arrows in (<b>a</b>,<b>c</b>,<b>e</b>) indicate the amplitude and direction of motions of amino acids in each mode. Correlated movements in covariance matrices (<b>b</b>,<b>d</b>,<b>f</b>) are highlighted in red while anticorrelated movements are represented in blue.</p> Full article ">Figure 8
<p>Hot-spot residues for the Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> and asymmetric Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math>-DnaK models. The top 2% (38) residues were mapped on the structures as cyan beads to indicate the amino acids involved in the allosteric wiring diagrams for each mode. (<b>a</b>,<b>b</b>) unbound Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math> modes 7 and 8 (<b>c</b>,<b>d</b>) asymmetric Hsp90<math display="inline"><semantics> <msub> <mrow/> <mrow> <mi>E</mi> <mi>c</mi> </mrow> </msub> </semantics></math>-DnaK modes 8 and 10, respectively. All two-dimensional graphs in this paper including displacement graphs and correlation matrices were made using Python [<a href="#B122-ijms-22-02200" class="html-bibr">122</a>] and MatPlotLib [<a href="#B123-ijms-22-02200" class="html-bibr">123</a>]. Three-dimensional protein models were made with both PyMol [<a href="#B124-ijms-22-02200" class="html-bibr">124</a>] and VMD [<a href="#B125-ijms-22-02200" class="html-bibr">125</a>]. Raster images were edited using GIMP [<a href="#B126-ijms-22-02200" class="html-bibr">126</a>] and vector images were edited using Inkscape [<a href="#B127-ijms-22-02200" class="html-bibr">127</a>].</p> Full article ">
15 pages, 1806 KiB  
Review
Exercise–Linked Irisin: Consequences on Mental and Cardiovascular Health in Type 2 Diabetes
by Ricardo Augusto Leoni De Sousa, Alex Cleber Improta-Caria and Bruno Solano de Freitas Souza
Int. J. Mol. Sci. 2021, 22(4), 2199; https://doi.org/10.3390/ijms22042199 - 23 Feb 2021
Cited by 49 | Viewed by 8581
Abstract
Type 2 diabetes mellitus (T2DM) is a metabolic disorder associated with insulin resistance and hyperglycemia. Chronic exposure to a T2DM microenvironment with hyperglycemia, hyperinsulinemia, oxidative stress and increased levels of proinflammatory mediators, has negative consequences to the cardiovascular system and mental health. Therefore, [...] Read more.
Type 2 diabetes mellitus (T2DM) is a metabolic disorder associated with insulin resistance and hyperglycemia. Chronic exposure to a T2DM microenvironment with hyperglycemia, hyperinsulinemia, oxidative stress and increased levels of proinflammatory mediators, has negative consequences to the cardiovascular system and mental health. Therefore, atherosclerotic cardiovascular diseases (CVD) and mental health issues have been strongly associated with T2DM. Lifestyle modifications, including physical exercise training, are necessary to prevent T2DM development and its associated complications. It is widely known that the regular practice of exercise provides several physiological benefits to subjects with T2DM, such as managing glycemic and blood pressure levels. Different types of exercise, from aerobic to resistance training, are effective to improve mental health and cognitive function in T2DM. Irisin is a myokine produced in response to exercise, which has been pointed as a relevant mechanism of action to explain the benefits of exercise on cardiovascular and mental health in T2DM patients. Here, we review emerging clinical and experimental evidence about exercise-linked irisin consequences to cardiovascular and mental health in T2DM. Full article
(This article belongs to the Section Molecular Neurobiology)
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Figure 1

Figure 1
<p><b>PI3K pathway</b>. Insulin is produced in the Langerhans cells of the pancreas. Insulin binds to its receptor, which phosphorylates (p symbols) several substrates, but just two of them acts directly in glucose metabolism (IRS-1 and IRS-2). Thereafter, PI3K molecule, which is a dimer compound by P85 and P110 proteins, is also phosphorylated and activates AKT.</p> Full article ">Figure 2
<p><b>Irisin is produced by exercise.</b> In response to exercise peroxisome proliferator, PGC-1α, leads to the production of FNDC5, a protein which contains an N-terminal signal sequence (green); fibronectin III (blue); a transmembrane region (TR) (yellow); a cytosolic region with a C-terminal tail (red). The proteolytic cleavage of mature FNDC5 results in the release of irisin, which corresponds to the fibronectin III domain with the signal sequence being removed.</p> Full article ">Figure 3
<p><b>Exercise-linked irisin: consequences on cardiovascular system in T2DM.</b> In T2DM there are many physiological changes that interfere with the cardiovascular system functioning like: hyperglycemia and hyperinsulinemia; reduced circulating irisin; enhancement of ROS; glucotoxicity and lipotoxicity; higher levels of pro-inflammatory proteins such as TNF-α, IL-6, IL-1b, TGF-β; prevalence of white adipose tissue; vascular endothelium inflammation; myocardial inflammation; cardiomyocyte hypertrophy; cardiomyocyte death; fibroblasts activation; fibrosis; and reduced insulin receptor sensitization. Although, the regular practice of exercise can inhibit these outcomes through many different ways like enhancing the UCP-1 expression in white adipose tissue cells inducing conversion of these cells into brown type fat cells. The production of irisin also leads to phosphorylation of p38 MAPK and activation of ERK, producing an increase in the expression of betatrophin, which generates proliferation and regeneration of beta-pancreatic cells.</p> Full article ">Figure 4
<p><b>Exercise-linked irisin: potential molecular mechanisms on cognitive function and memory in T2DM.</b> Proteins that are upregulated due to exercise in green (PGC-1α, FNDC5, irisin, BDNF, CREB, and IRS-1); proteins downregulated or that maintain their levels unaltered are in red (GFAP, IL-1β, IL-6, P38, STAT3, NFκB, and GSKβ) in T2DM. Thus, anti-inflammatory mechanisms occur due to exercise in T2DM. These potential exercise effects are suggested to protect against cognitive decline and memory loss in T2DM.</p> Full article ">
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