[go: up one dir, main page]

Next Issue
Volume 10, October
Previous Issue
Volume 10, August
 
 

Biomolecules, Volume 10, Issue 9 (September 2020) – 153 articles

Cover Story (view full-size image): Human transcription factors regulate the expression of target genes through their transactivation domains (TADs). As a first step, TADs interact with coactivators that are part of the general transcriptional machinery. MED25, a subunit of the mediator complex, is a coactivator that binds TADs through a cleft on its surface. Since most TADs adopt a rod-like, -helical structure, it is likely that TADs bind only in two main orientations (‘cis’ and ‘trans’) and cannot readily switch between these once bound. TADs, therefore, need to be able to bind bidirectionally. Here, Jeffery and Weinzierl show through computational simulations that human (ETV5) and viral (VP16) TADs can bind in both directions by employing alternative sets of residues to stabilize binding to the coactivator surface. View this paper
  • Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
  • You may sign up for e-mail alerts to receive table of contents of newly released issues.
  • PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Order results
Result details
Section
Select all
Export citation of selected articles as:
43 pages, 4913 KiB  
Article
MiRNA Profiles of Extracellular Vesicles Secreted by Mesenchymal Stromal Cells—Can They Predict Potential Off-Target Effects?
by Timo Z. Nazari-Shafti, Sebastian Neuber, Ana G. Duran, Vasileios Exarchos, Christien M. Beez, Heike Meyborg, Katrin Krüger, Petra Wolint, Johanna Buschmann, Roland Böni, Martina Seifert, Volkmar Falk and Maximilian Y. Emmert
Biomolecules 2020, 10(9), 1353; https://doi.org/10.3390/biom10091353 - 22 Sep 2020
Cited by 14 | Viewed by 3798
Abstract
The cardioprotective properties of extracellular vesicles (EVs) derived from mesenchymal stromal cells (MSCs) are currently being investigated in preclinical studies. Although microRNAs (miRNAs) encapsulated in EVs have been identified as one component responsible for the cardioprotective effect of MSCs, their potential off-target effects [...] Read more.
The cardioprotective properties of extracellular vesicles (EVs) derived from mesenchymal stromal cells (MSCs) are currently being investigated in preclinical studies. Although microRNAs (miRNAs) encapsulated in EVs have been identified as one component responsible for the cardioprotective effect of MSCs, their potential off-target effects have not been sufficiently characterized. In the present study, we aimed to investigate the miRNA profile of EVs isolated from MSCs that were derived from cord blood (CB) and adipose tissue (AT). The identified miRNAs were then compared to known targets from the literature to discover possible adverse effects prior to clinical use. Our data show that while many cardioprotective miRNAs such as miR-22-3p, miR-26a-5p, miR-29c-3p, and miR-125b-5p were present in CB- and AT-MSC-derived EVs, a large number of known oncogenic and tumor suppressor miRNAs such as miR-16-5p, miR-23a-3p, and miR-191-5p were also detected. These findings highlight the importance of quality assessment for therapeutically applied EV preparations. Full article
Show Figures

Figure 1

Figure 1
<p>Cord blood (CB)- and adipose tissue mesenchymal stromal cells (AT-MSCs) maintain their spindle-shaped morphology under extracellular vesicles (EV) biogenesis conditions. MSCs were expanded to a confluence of about 80%, washed with Dulbecco’s phosphate-buffered saline and cultivated for 48 h in exosome-depleted medium. Then, the cells were switched to starvation medium for 24 h to derive the conditioned medium for EV isolation. Representative bright-field images of cell morphology of CB-MSCs (<b>A</b>) and AT-MSCs (<b>B</b>) were taken by phase-contrast microscopy at the time of EV isolation. Bars, 200 µm.</p>
Full article ">Figure 2
<p>Particle number, protein amount and size distribution of EVs isolated from CB- and AT-MSCs. Particle concentration (<b>A</b>) and size distribution (<b>C</b>) of EV preparations were measured by nanoparticle tracking analysis. Protein content (<b>B</b>) was determined by the bicinchoninic acid assay. In (<b>A</b>–<b>C</b>), the results are mean values ± standard deviation (SD) obtained from four different donors per cell type.</p>
Full article ">Figure 3
<p>Identification of EV-like structures via transmission electron microscopy. CB- and AT-MSC-derived EVs shown in (<b>A</b>,<b>B</b>) were isolated using the Qiagen exoEasy Maxi Kit, and CB- and AT-MSC-derived EVs shown in (<b>C</b>,<b>D</b>) were isolated using sequential ultracentrifugation. All EVs exhibit the expected cup-like shape, an artefact of the fixation method. In (<b>A</b>,<b>B</b>), EVs are covered with phosphate-rich matter, and red triangles indicate structures in which covered EVs were detected. In (<b>C</b>,<b>D</b>), exemplary EVs are indicated by blue triangles. In (<b>A</b>–<b>D</b>), enlarged regions of selected EVs are shown on that top right.</p>
Full article ">Figure 4
<p>CB- and AT-MSC-derived EVs display a distinct surface marker profile. Detection of the surface marker proteins CD9, CD63, CD73, CD81, HLA-ABC, and HLA-DR using flow cytometry on EV preparations. The data are presented as means ± SD of normalized mean fluorescence intensities (MFIs), which were calculated as the ratio of the geometric MFI of EV samples (beads + EVs + antibodies) to control samples (beads + antibodies). Statistical analysis was performed by the Mann-Whitney test with * <span class="html-italic">p</span> &lt; 0.05. ND indicates not detected. EVs from four different donors per cell type were included.</p>
Full article ">Figure 5
<p>Heatmap and dendrograms of all microRNAs (miRNAs) detected with certainty according to the guidelines of the Qiagen-Exiqon miRCURY LNA Universal RT microRNA PCR system. Sample IDs are shown on the x-axis. Samples with similar miRNA expression are clustered together. The heatmap was generated by RStudio and 2<sup>dCT</sup> was used for data input. Z-scores of more than zero indicate a higher expression of miRNAs in one sample compared to the others; Z-scores of less than zero indicate the opposite.</p>
Full article ">Figure 6
<p>Venn diagram of miRNAs found in CB- and AT-MSC-derived EVs. In total, 752 miRNAs were analyzed and categorized according to mean CTcorr values. High miRNA expression means CTcorr value ≤ 29.99; low miRNA expression means CTcorr value = 30.00–32.99. Five hundred and forty-seven miRNAs were not detected in EVs from CB-MSCs or in EVs from AT-MSCs (mean CTcorr value ≥ 33.00).</p>
Full article ">Figure 7
<p>Heatmap and dendrograms of miRNAs that were significantly changed in AT-MSC-derived EVs compared to CB-MSC-derived EVs. Sample IDs are shown on the x-axis. Samples with similar miRNA expression are clustered together. The heatmap was generated by RStudio and 2<sup>dCT</sup> was used for data input. Z-scores of more than zero indicate a higher expression of miRNAs in one sample compared to the others; Z-scores of less than zero indicate the opposite.</p>
Full article ">Figure 8
<p>Diagram of literature search rules applied for all miRNAs with a low mean CTcorr value (≤ 29.99) in both CB- and AT-MSC-derived EVs. Search terms were “name of miRNA”, “name of miRNA” AND “heart”, “name of miRNA” AND “cancer”, “name of miRNA” AND “fibrosis”, “name of miRNA” AND “endothelial cells”, “name of miRNA” AND “angiogenesis”, “name of miRNA” AND “immunomodulation”, “name of miRNA” AND “macrophages”, “name of miRNA” AND “t-cells”, and “name of miRNA” AND “immune cells”.</p>
Full article ">Figure 9
<p>Venn diagram of selected miRNAs based on their function. Gray, tumor suppressor miRNAs; yellow, oncogenic miRNAs; red, cardioprotective miRNAs. With the exception of miR-1260a, all miRNAs with a low mean CTcorr value (≤29.99) in both CB- and AT-MSC-derived EVs were included. MiR-1260a could not be included, as no targets were described in the literature so far. Further details on these miRNAs are given in <a href="#biomolecules-10-01353-t0A1" class="html-table">Table A1</a>, <a href="#biomolecules-10-01353-t0A2" class="html-table">Table A2</a> and <a href="#biomolecules-10-01353-t0A3" class="html-table">Table A3</a>.</p>
Full article ">
24 pages, 2946 KiB  
Review
A Great Catch for Investigating Inborn Errors of Metabolism—Insights Obtained from Zebrafish
by Maximilian Breuer and Shunmoogum A. Patten
Biomolecules 2020, 10(9), 1352; https://doi.org/10.3390/biom10091352 - 22 Sep 2020
Cited by 9 | Viewed by 7534
Abstract
Inborn errors of metabolism cause abnormal synthesis, recycling, or breakdown of amino acids, neurotransmitters, and other various metabolites. This aberrant homeostasis commonly causes the accumulation of toxic compounds or depletion of vital metabolites, which has detrimental consequences for the patients. Efficient and rapid [...] Read more.
Inborn errors of metabolism cause abnormal synthesis, recycling, or breakdown of amino acids, neurotransmitters, and other various metabolites. This aberrant homeostasis commonly causes the accumulation of toxic compounds or depletion of vital metabolites, which has detrimental consequences for the patients. Efficient and rapid intervention is often key to survival. Therefore, it requires useful animal models to understand the pathomechanisms and identify promising therapeutic drug targets. Zebrafish are an effective tool to investigate developmental mechanisms and understanding the pathophysiology of disorders. In the past decades, zebrafish have proven their efficiency for studying genetic disorders owing to the high degree of conservation between human and zebrafish genes. Subsequently, several rare inherited metabolic disorders have been successfully investigated in zebrafish revealing underlying mechanisms and identifying novel therapeutic targets, including methylmalonic acidemia, Gaucher’s disease, maple urine disorder, hyperammonemia, TRAPPC11-CDGs, and others. This review summarizes the recent impact zebrafish have made in the field of inborn errors of metabolism. Full article
(This article belongs to the Special Issue Zebrafish: A Model for the Study of Human Diseases)
Show Figures

Figure 1

Figure 1
<p>Overview of inborn errors of metabolism research. (<b>A</b>) Schematic presentation of major IEM Groups and selected disorders. (<b>B</b>) Diagram of animal models since the year 2000 used in IEM research based on Pubmed (<a href="https://www.ncbi.nlm.nih.gov/" target="_blank">https://www.ncbi.nlm.nih.gov/</a>) hits (Search terms: “Inborn errors of metabolism + animal model”) last accessed 22.06.2020 (<b>C</b>) Zebrafish publications in relation to IEM studied since the year 2000 based on Pubmed research hits (Search terms based on IEM disorder group and individual disorders) last accessed 07.08.2020.</p>
Full article ">Figure 2
<p>Advantages of zebrafish for metabolic studies. Overview of zebrafish advantages in regards to metabolic studies and metabolic conservation. The Figure highlights key developmental features that are important in investigating common characteristics of IEM, including heart deficits, craniofacial, spinal, as well as neural and organ abnormalities (Images presented: Neural development: lateral view of 72 hpf tg(isl:GFP) transgenic line; Bone development: close up of vertebral calcein staining of 4-week old zebrafish larvae; Craniofacial development: Dorsal view of Alcian blue staining of 6 dpf zebrafish larvae; Heart development: close up of 72 hpf zebrafish heart, Genetic and Metabolic conservation: whole-mount <span class="html-italic">in situ</span> hybridization of glutamine synthetase in 5 dpf larvae).</p>
Full article ">
13 pages, 734 KiB  
Review
Arsenic Methyltransferase and Methylation of Inorganic Arsenic
by Nirmal K. Roy, Anthony Murphy and Max Costa
Biomolecules 2020, 10(9), 1351; https://doi.org/10.3390/biom10091351 - 22 Sep 2020
Cited by 40 | Viewed by 5356
Abstract
Arsenic occurs naturally in the environment, and exists predominantly as inorganic arsenite (As (III) and arsenate As (V)). Arsenic contamination of drinking water has long been recognized as a major global health concern. Arsenic exposure causes changes in skin color and lesions, and [...] Read more.
Arsenic occurs naturally in the environment, and exists predominantly as inorganic arsenite (As (III) and arsenate As (V)). Arsenic contamination of drinking water has long been recognized as a major global health concern. Arsenic exposure causes changes in skin color and lesions, and more severe health conditions such as black foot disease as well as various cancers originating in the lungs, skin, and bladder. In order to efficiently metabolize and excrete arsenic, it is methylated to monomethylarsonic and dimethylarsinic acid. One single enzyme, arsenic methyltransferase (AS3MT) is responsible for generating both metabolites. AS3MT has been purified from several mammalian and nonmammalian species, and its mRNA sequences were determined from amino acid sequences. With the advent of genome technology, mRNA sequences of AS3MT have been predicted from many species throughout the animal kingdom. Horizontal gene transfer had been postulated for this gene through phylogenetic studies, which suggests the importance of this gene in appropriately handling arsenic exposures in various organisms. An altered ability to methylate arsenic is dependent on specific single nucleotide polymorphisms (SNPs) in AS3MT. Reduced AS3MT activity resulting in poor metabolism of iAs has been shown to reduce expression of the tumor suppressor gene, p16, which is a potential pathway in arsenic carcinogenesis. Arsenic is also known to induce oxidative stress in cells. However, the presence of antioxidant response elements (AREs) in the promoter sequences of AS3MT in several species does not correlate with the ability to methylate arsenic. ARE elements are known to bind NRF2 and induce antioxidant enzymes to combat oxidative stress. NRF2 may be partly responsible for the biotransformation of iAs and the generation of methylated arsenic species via AS3MT. In this article, arsenic metabolism, excretion, and toxicity, a discussion of the AS3MT gene and its evolutionary history, and DNA methylation resulting from arsenic exposure have been reviewed. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p><b>Exon–intron arrangements of seven coding sequences in the <span class="html-italic">AS3MT</span> genome.</b> Exons containing only the coding sequences were indicated according to the way they are arranged in terms of distance from each other. Dark small rectangles represent the exons, whereas the large open rectangle represents introns in the genome of individual species from the start of translation to the stop codon. Space between the two dark rectangles represents the length between two exons. Genbank accession number for the sequences are NW_020822501 (hamster), NC_006610 (dog), CM000231 (rat), NC_013686 (Rabbit), AC009144 (human), NC_013907 (marmoset), and NBAG03000216 (chimpanzee).</p>
Full article ">Figure 2
<p><b>Phylogenetic analyses of 13 full-length AS3MT peptide sequences in vertebrate species.</b> Simple phylogeny application from EMBL-EBI was used to generate a phylogenetic tree as described in the text. See text for Genbank accession numbers.</p>
Full article ">
16 pages, 3034 KiB  
Review
Emerging Roles for the INK4a/ARF (CDKN2A) Locus in Adipose Tissue: Implications for Obesity and Type 2 Diabetes
by Yasmina Kahoul, Frédérik Oger, Jessica Montaigne, Philippe Froguel, Christophe Breton and Jean-Sébastien Annicotte
Biomolecules 2020, 10(9), 1350; https://doi.org/10.3390/biom10091350 - 22 Sep 2020
Cited by 14 | Viewed by 3744
Abstract
Besides its role as a cell cycle and proliferation regulator, the INK4a/ARF (CDKN2A) locus and its associated pathways are thought to play additional functions in the control of energy homeostasis. Genome-wide association studies in humans and rodents have revealed that single [...] Read more.
Besides its role as a cell cycle and proliferation regulator, the INK4a/ARF (CDKN2A) locus and its associated pathways are thought to play additional functions in the control of energy homeostasis. Genome-wide association studies in humans and rodents have revealed that single nucleotide polymorphisms in this locus are risk factors for obesity and related metabolic diseases including cardiovascular complications and type-2 diabetes (T2D). Recent studies showed that both p16INK4a-CDK4-E2F1/pRB and p19ARF-P53 (p14ARF in humans) related pathways regulate adipose tissue (AT) physiology and adipocyte functions such as lipid storage, inflammation, oxidative activity, and cellular plasticity (browning). Targeting these metabolic pathways in AT emerged as a new putative therapy to alleviate the effects of obesity and prevent T2D. This review aims to provide an overview of the literature linking the INK4a/ARF locus with AT functions, focusing on its mechanisms of action in the regulation of energy homeostasis. Full article
(This article belongs to the Special Issue Deciphering alternative functions of the INK4a/ARF locus)
Show Figures

Figure 1

Figure 1
<p>The <span class="html-italic">INK4a/ARF</span> locus. The <span class="html-italic">INK4a/ARF</span> locus is located on chromosome 9p21 in humans and chromosome 4 in rodents. It encodes for two proteins, p16INK4a the principal member of the INK4 family of cyclin-dependent kinase inhibitors (CDKI) and the p53 regulatory protein p14ARF (p19ARF in mice). Both are key regulators of the cell cycle machinery with an anti-proliferative and tumor suppressor role. p16INK4a binds to CDK4/6, inhibiting cyclin D-CDK4/6 complex formation and CDK4/6-mediated phosphorylation of Rb family members (pRB). Expression of p16INK4a maintains pRB in a hypophosphorylated state, which promotes binding to the transcription factors E2F and blocks the passage of the G1 to S phase. p14ARF (p19ARF in mice) mainly exerts its anti-proliferative activity via the inhibition of the mouse double minute 2 homolog (MDM2), an ubiquitin-ligase that hampers the activity of the transcription factor p53, acting as a tumor suppressor, blocking cells in G1 and G2 phase.</p>
Full article ">Figure 2
<p>The <span class="html-italic">INK4a/ARF</span> locus as a key regulatory hub to maintain adipose tissue in a healthy state. The <span class="html-italic">INK4A/ARF</span> locus regulates the balance between adipogenesis and senescence and promotes lipid storage as triglycerides and adipocyte hypertrophy via the insulin-signaling pathway. It has been described as a molecular switch of white-to-beige adipocyte conversion and as a key determinant of brown adipocyte fate, being an alternative way to increase energy expenditure. It is also involved in the switch between macrophage phenotype and thus obesity-related inflammation.</p>
Full article ">Figure 3
<p>The <span class="html-italic">INK4a/ARF</span> locus modulates the insulin-signaling pathway in adipocyte. Insulin attaches to insulin receptor triggering intracellular autophosphorylation of their tyrosine residues, which constitutes an attachment for insulin receptor substrate (IRS) proteins. These molecules undergo phosphorylation and form a complex with PI3K. PI3K phosphorylates PIP2, which results in PIP3 formation and activation of PDK1. AKT gets phosphorylated and activated by PDK1. The latter is responsible for GLUT4 translocation to cellular membrane and glucose inflow. CDK4 was shown to activate the insulin-signaling pathway through phosphorylation of IRS2 at Ser388 upon insulin stimulation, thus maintaining insulin action in adipocytes. Although E2F1 and p53 are thought to interact with the insulin-signaling pathway to modulate AT insulin sensitivity, yet the underlying mechanisms are still unclear.</p>
Full article ">Figure 4
<p>The <span class="html-italic">INK4a/ARF</span> locus: an emerging key actor in metabolic functions. In addition to AT, the <span class="html-italic">INK4A/ARF</span> (<span class="html-italic">CDKN2A</span>) locus is thought to play a variety of role in metabolic functions under normal and physiopathological conditions in other organs (pancreas, liver, muscle, heart, and brain). This locus affects glucose homeostasis, β-cell functions and mass, hepatic gluconeogenesis and lipid storage as well as cardiovascular functions. It also regulates the circadian rhythm, neurogenesis, and axonal regeneration.</p>
Full article ">
23 pages, 5479 KiB  
Article
G-Quadruplexes in the Archaea Domain
by Václav Brázda, Yu Luo, Martin Bartas, Patrik Kaura, Otilia Porubiaková, Jiří Šťastný, Petr Pečinka, Daniela Verga, Violette Da Cunha, Tomio S. Takahashi, Patrick Forterre, Hannu Myllykallio, Miroslav Fojta and Jean-Louis Mergny
Biomolecules 2020, 10(9), 1349; https://doi.org/10.3390/biom10091349 - 21 Sep 2020
Cited by 32 | Viewed by 4994
Abstract
The importance of unusual DNA structures in the regulation of basic cellular processes is an emerging field of research. Amongst local non-B DNA structures, G-quadruplexes (G4s) have gained in popularity during the last decade, and their presence and functional relevance at the DNA [...] Read more.
The importance of unusual DNA structures in the regulation of basic cellular processes is an emerging field of research. Amongst local non-B DNA structures, G-quadruplexes (G4s) have gained in popularity during the last decade, and their presence and functional relevance at the DNA and RNA level has been demonstrated in a number of viral, bacterial, and eukaryotic genomes, including humans. Here, we performed the first systematic search of G4-forming sequences in all archaeal genomes available in the NCBI database. In this article, we investigate the presence and locations of G-quadruplex forming sequences using the G4Hunter algorithm. G-quadruplex-prone sequences were identified in all archaeal species, with highly significant differences in frequency, from 0.037 to 15.31 potential quadruplex sequences per kb. While G4 forming sequences were extremely abundant in Hadesarchaea archeon (strikingly, more than 50% of the Hadesarchaea archaeon isolate WYZ-LMO6 genome is a potential part of a G4-motif), they were very rare in the Parvarchaeota phylum. The presence of G-quadruplex forming sequences does not follow a random distribution with an over-representation in non-coding RNA, suggesting possible roles for ncRNA regulation. These data illustrate the unique and non-random localization of G-quadruplexes in Archaea. Full article
(This article belongs to the Collection Archaea: Diversity, Metabolism and Molecular Biology)
Show Figures

Figure 1

Figure 1
<p>A schematic phylogenic tree for Archaea. This unrooted evolutionary tree of Archaea is based on the schematic tree of Forterre (2015) [<a href="#B17-biomolecules-10-01349" class="html-bibr">17</a>] updated according to recent phylogenetic analyses [<a href="#B9-biomolecules-10-01349" class="html-bibr">9</a>,<a href="#B18-biomolecules-10-01349" class="html-bibr">18</a>]. BAT stands for Bathyarchaeota, Aigarchaeota, and Thaumarchaeota. DPANN is an acronym based on the first five groups discovered: <span class="html-italic">Diapherotrites</span>, <span class="html-italic">Parvarchaeota</span>, <span class="html-italic">Aenigmarchaeota</span>, <span class="html-italic">Nanoarchaeota</span>, and <span class="html-italic">Nanohaloarchaeota</span>. The term BAT superphylum has been proposed by Gaia et al. in 2018 [<a href="#B19-biomolecules-10-01349" class="html-bibr">19</a>], and the terms Eury and Cren superphyla are suggested here. The terms Cren superphylum is suggested here because the phyla <span class="html-italic">Crenarchaeota</span>, <span class="html-italic">Verstratearchaeota Marsarchaeota</span>, <span class="html-italic">Nezaarchaeota</span>, and Geothermarchaeota form a consensus monophyletic clade in all archaeal phylogeny. We included <span class="html-italic">Korarchaeota</span> in this superphylum because they often branch as sister groups of the above phyla in archaeal phylogenies, although the fast evolutionary rate made their positioning sometimes difficult. We suggested in parallel the term Eury superphylum because Euryarchaeota includes very diverse groups of cultivated and uncultivated Archaea which are difficult to the group in a single phylum, especially considering that phyla, such as <span class="html-italic">Verstratearchaeota Marsarchaeota</span>, or <span class="html-italic">Nezaarchaeota</span> only contain few uncultivated species only defined by a few metagenome associated genomes (MAGs). Names in bold letters correspond to subgroups that include cultivated species; names in thin letters correspond to subgroups that include only MAGs.</p>
Full article ">Figure 2
<p>A G-quartet involves four coplanar guanines establishing a cyclic array of H-bonds (left). Stacking of two or more (three in this example) quartets leads to the formation of a G-quadruplex structure (right), stabilized by cations, such as potassium (not shown).</p>
Full article ">Figure 3
<p>Examples of sequences with different G-quadruplexes (G4) Hunter scores (G4HS) and distribution of PQS according to threshold category. (<b>A</b>) Examples of archaea 25-nt long sequences (corresponding to the window size chosen for the analysis) for which G4Hunter scores are provided within parentheses. Isolated guanines are shown in red, all other guanines in bold red characters. Longer archaea motifs with high G4H scores are provided in <a href="#biomolecules-10-01349-t003" class="html-table">Table 3</a>. (<b>B</b>) Distribution of G4-prone motifs according to the G4Hunter score. 1.2 means any sequence with a score between 1.2 and 1.399; 1.4 between 1.4 and 1.599, etc. These numbers are normalized by the total number of PQS found in bacteria, archaea, and compared with <span class="html-italic">Homo sapiens</span>. The first category represents 97.9% and 97.2% of all PQS sequences in bacteria and archaea, respectively. Note the log scale on the Y-axis.</p>
Full article ">Figure 4
<p>Frequencies of PQS in subgroups of analyzed archaeal genomes. Data within boxes span the interquartile range, and whiskers show the lowest and highest values within 1.5 interquartile range. Black points denote outliers. Horizontal black lines inside boxplots are median values.</p>
Full article ">Figure 5
<p>Cluster dendrogram of PQS characteristics of archaeal subgroups. Cluster dendrogram of PQS characteristics (<a href="#app1-biomolecules-10-01349" class="html-app">Supplementary Table S4</a>) was made in R v. 3.6.3 (code provided in <a href="#app1-biomolecules-10-01349" class="html-app">Supplementary Table S4</a>) using pvclust package with these parameters: Cluster method ‘ward.D2′, distance ‘euclidean’, number of bootstrap resamplings was 10,000. AU values are in blue and indicate the statistical significance of particular branching (values above 95 are equivalent to <span class="html-italic">p</span>-values lesser than 0.05). Statistically significant clusters are highlighted by red dashed rectangles.</p>
Full article ">Figure 6
<p>Relationship between the observed frequency of PQS per 1000 bp and GC content. Different G4Hunter score intervals are considered. In each G4Hunter score interval miniplot, frequencies were normalized according to the highest observed frequency of PQS. Organisms with max. frequency per 1000 bp greater than 50% are described and highlighted in color.</p>
Full article ">Figure 7
<p>Relationship between GC percentage and % of PQS in genomes of particular archaeal subgroups. The Fitted equation with the R<sup>2</sup> coefficient is depicted on the top side of the plot.</p>
Full article ">Figure 8
<p>Differences in PQS frequency by DNA locus. The chart shows PQS frequencies normalized per 1000 bp annotated locations from the NCBI database and shows a comparison between Archaea and Bacteria. Archaea G4-prone motifs are strongly over-represented in ncRNA and rRNA compared to the average G4 density in Archaea (mean f = 1.207), but also compared to bacteria. PQS count is provided in <a href="#app1-biomolecules-10-01349" class="html-app">Supplementary Table S3</a> Excel file.</p>
Full article ">Figure 9
<p>Experimental evidence for quadruplex formation with archaea sequences. Isothermal differential absorbance (IDS; panel <b>A</b>) and circular dichroism (CD; panels <b>B</b> and <b>C</b>) spectra of <span class="html-italic">Hadesarchaea archeon</span> DNA sequences were recorded at 20 °C (panels <b>A</b> and <b>B</b>) or at a high temperature (80 °C) for CD (panel <b>C</b>).</p>
Full article ">
23 pages, 1442 KiB  
Review
Current Understanding of the Relationship of HDL Composition, Structure and Function to Their Cardioprotective Properties in Chronic Kidney Disease
by Gunther Marsche, Gunnar H. Heine, Julia T. Stadler and Michael Holzer
Biomolecules 2020, 10(9), 1348; https://doi.org/10.3390/biom10091348 - 21 Sep 2020
Cited by 28 | Viewed by 4306
Abstract
In the general population, the ability of high-density lipoproteins (HDLs) to promote cholesterol efflux is a predictor of cardiovascular events, independently of HDL cholesterol levels. Although patients with chronic kidney disease (CKD) have a high burden of cardiovascular morbidity and mortality, neither serum [...] Read more.
In the general population, the ability of high-density lipoproteins (HDLs) to promote cholesterol efflux is a predictor of cardiovascular events, independently of HDL cholesterol levels. Although patients with chronic kidney disease (CKD) have a high burden of cardiovascular morbidity and mortality, neither serum levels of HDL cholesterol, nor cholesterol efflux capacity associate with cardiovascular events. Important for the following discussion on the role of HDL in CKD is the notion that traditional atherosclerotic cardiovascular risk factors only partially account for this increased incidence of cardiovascular disease in CKD. As a potential explanation, across the spectrum of cardiovascular disease, the relative contribution of atherosclerotic cardiovascular disease becomes less important with advanced CKD. Impaired renal function directly affects the metabolism, composition and functionality of HDL particles. HDLs themselves are a heterogeneous population of particles with distinct sizes and protein composition, all of them affecting the functionality of HDL. Therefore, a more specific approach investigating the functional and compositional features of HDL subclasses might be a valuable strategy to decipher the potential link between HDL, cardiovascular disease and CKD. This review summarizes the current understanding of the relationship of HDL composition, metabolism and function to their cardio-protective properties in CKD, with a focus on CKD-induced changes in the HDL proteome and reverse cholesterol transport capacity. We also will highlight the gaps in the current knowledge regarding important aspects of HDL biology. Full article
Show Figures

Figure 1

Figure 1
<p>Principle of the cholesterol efflux assay. J774 macrophages are cultivated in multiwell plates to form a monolayer. The cells are then treated for 24 h with an ACAT (acyl coenzyme A: cholesterol acyltransferase) inhibitor and radiolabeled cholesterol ([<sup>3</sup>H]-cholesterol). The ACAT inhibitor prevents cholesterol esterification and the added cholesterol remains cell-associated as free cholesterol. On the following day, the cells are treated with cyclic adenosine monophosphate (cAMP) for 16 h to stimulate the expression of the cholesterol exporter ABCA1. The cholesterol efflux in unstimulated macrophages is mediated to 15% by ABCA1, 25% by SR-BI and 55% by passive diffusion (includes ABCG1-mediated efflux). By cAMP treatment, the ABCA1-dependent cholesterol efflux triples to about 40%, while passive diffusion accounts for 50% and SR-BI-mediated efflux for 10% [<a href="#B125-biomolecules-10-01348" class="html-bibr">125</a>]. Human serum shows a depletion of lipoproteins containing apoB100 (mainly VLDL, LDL) using polyethylene glycol. After extensive rinsing of the cells, apoB-depleted serum (containing all HDL subclasses) is added to the [<sup>3</sup>H]-cholesterol-labeled macrophages at a concentration of 2.8%. After 4 h, the [<sup>3</sup>H]-cholesterol that has passed from the cells into the supernatant is quantified by liquid scintillation counting.</p>
Full article ">Figure 2
<p>Most frequently identified changes in the proteome of HDL in CKD patients. Approximately 70% of the HDL protein mass is comprised of apoA-I (A-I), while apoA-II(A-II) comprises about 15–20% [<a href="#B50-biomolecules-10-01348" class="html-bibr">50</a>]. The remaining 10–15% of protein mass is composed of less abundant proteins, including apoC-III, apoC-II, apoE, apoD, apoM, apoA-IV, as well as enzymes such as paraoxonase 1 (PON1) and lipid transfer proteins, including lecithin:cholesterol acyl transferase and cholesteryl ester transfer protein [<a href="#B50-biomolecules-10-01348" class="html-bibr">50</a>]. To simplify the illustration only the major constituents of HDL are shown. In CKD, a specific remodeling of the HDL particle occurs depending on the stage of CKD and the vintage of dialysis treatment. The most noticeable change in the composition of HDL in CKD is the accumulation of serum amyloid a (SAA), especially SAA1, together with the enrichment in apoC-II and apoC-III. The accumulation of these proteins is accompanied by a loss of apoA-I, apoA-II, apoM and a decrease in the mass and enzymatic activity of paraoxonase 1 (PON1).</p>
Full article ">
15 pages, 2927 KiB  
Communication
Identification of a Proanthocyanidin from Litchi Chinensis Sonn. Root with Anti-Tyrosinase and Antioxidant Activity
by Matthew Saive, Manon Genva, Thibaut Istasse, Michel Frederich, Chloé Maes and Marie-Laure Fauconnier
Biomolecules 2020, 10(9), 1347; https://doi.org/10.3390/biom10091347 - 21 Sep 2020
Cited by 6 | Viewed by 3004
Abstract
This work follows an ethnobotanical study that took place in the island of Mayotte (France), which pointed out the potential properties of Litchi chinensis Sonn. roots when used to enhance skin health and appearance. Through in vitro testing of a crude methanolic extract, [...] Read more.
This work follows an ethnobotanical study that took place in the island of Mayotte (France), which pointed out the potential properties of Litchi chinensis Sonn. roots when used to enhance skin health and appearance. Through in vitro testing of a crude methanolic extract, high anti-tyrosinase (skin whitening effect) and antioxidant activities (skin soothing effect) could be measured. HPLC successive bio-guided fractionation steps allowed the purification of one of the compounds responsible for the biological activities. The isolated compound was characterized by UV, IR, MS and 2D-NMR, revealing, for the first time in Litchi chinensis Sonn. roots, an A-type proanthocyanidin and thus revealing a consensus among the traditional use shown by the ethnobotanical study, in vitro biological activities and chemical characterization. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Picture of <span class="html-italic">Litchi chinensis</span> roots. (Credit Matthew Saive).</p>
Full article ">Figure 2
<p>Chromatogram from the first fractionation process (preparative HPLC). Seventeen fractions were isolated. The peak of interest is F10 (RT = 37′49″) (shown in red).</p>
Full article ">Figure 3
<p>Chromatogram from the second fractionation process (preparative HPLC). Five fractions were isolated. The peak of interest is F10.3 (RT = 14′45″) (shown in red).</p>
Full article ">Figure 4
<p>Chromatogram from the third fractionation process (analytical HPLC with fraction collector). Five fractions were isolated. The peak of interest is F10.3.3 (RT = 43′49″) (shown in red).</p>
Full article ">Figure 5
<p>FTIR spectrum.</p>
Full article ">Figure 6
<p>MS spectra of the purified molecule recorded in the positive mode.</p>
Full article ">Figure 7
<p>Two-dimensional heteronuclear single quantum correlation (HSQC) NMR spectrum of the isolated compound (right) and its hypothetical chemical structure (left). The structure proposal is based on both NMR and mass spectrometry data.</p>
Full article ">Figure 8
<p>Purified compound from the roots of L. chinensis.</p>
Full article ">
26 pages, 5875 KiB  
Article
Recognition of Potential COVID-19 Drug Treatments through the Study of Existing Protein–Drug and Protein–Protein Structures: An Analysis of Kinetically Active Residues
by Ognjen Perišić
Biomolecules 2020, 10(9), 1346; https://doi.org/10.3390/biom10091346 - 21 Sep 2020
Cited by 10 | Viewed by 4948
Abstract
We report the results of our in silico study of approved drugs as potential treatments for COVID-19. The study is based on the analysis of normal modes of proteins. The drugs studied include chloroquine, ivermectin, remdesivir, sofosbuvir, boceprevir, and α-difluoromethylornithine (DMFO). We applied [...] Read more.
We report the results of our in silico study of approved drugs as potential treatments for COVID-19. The study is based on the analysis of normal modes of proteins. The drugs studied include chloroquine, ivermectin, remdesivir, sofosbuvir, boceprevir, and α-difluoromethylornithine (DMFO). We applied the tools we developed and standard tools used in the structural biology community. Our results indicate that small molecules selectively bind to stable, kinetically active residues and residues adjoining them on the surface of proteins and inside protein pockets, and that some prefer hydrophobic sites over other active sites. Our approach is not restricted to viruses and can facilitate rational drug design, as well as improve our understanding of molecular interactions, in general. Full article
(This article belongs to the Section Bioinformatics and Systems Biology)
Show Figures

Figure 1

Figure 1
<p>Chloroquine and its target proteins. Images on the left depict chloroquine bound to the cofactor binding site of <span class="html-italic">Plasmodium falciparum</span> lactate dehydrogenase (pdb id 1cet). Images on the right depict chloroquine bound to saposin B (pdb id 4v2o). (<b>a</b>) Lactate dehydrogenase is depicted as a blue ribbon, self-adjustable Gaussian network model (SAGNM) predictions are yellow and chloroquine green atoms. (<b>b</b>) Lactate dehydrogenase is depicted as a transparent hydrophobic surface (chain is visible as ribbon inside surface). SAGNM predictions are depicted as yellow atoms and chloroquine as green atoms. (<b>c</b>) Lactate dehydrogenase is depicted as an opaque hydrophobic surface and chloroquine as green balls and sticks. (<b>d</b>) The inset shows chloroquine within the hydrophobic pocket. (<b>e</b>) Saposin B chains are depicted as blue (chain A), pink (chain B), and red (chain C) ribbons. SAGNM predictions are depicted as blue, pink, and red atoms. Chloroquine molecules are shown as green atoms. (<b>f</b>) Saposin B is depicted as a transparent hydrophobic surface. SAGNM predictions are depicted as yellow atoms and chloroquine green atoms. (<b>g</b>) Saposin B is depicted as an opaque hydrophobic surface and chloroquine as green balls and sticks. (<b>h</b>) The two insets show chloroquine molecules within the hydrophobic pockets on the surface of the saposin B trimer. The figure is produced with the UCSF Chimera program [<a href="#B58-biomolecules-10-01346" class="html-bibr">58</a>].</p>
Full article ">Figure 2
<p>Ivermectin and its target protein, human glycine receptor alpha-3 (pdb id 5vdh). (<b>a</b>) Five pentamer chains (A to E) are represented as ribbons. Ivermectin is represented via green atoms. Glycine molecules are brown and represented as atoms, and 7C6 molecules are represented as purple atoms. (<b>b</b>) Chain A from human glycine receptor Alpha-3 is represented as a blue ribbon. SAGNM predictions are depicted as yellow atoms. Ivermectin is represented via green atoms. The glycine molecule is brown and represented as spherical atoms. The 7C6 molecule is represented as purple atoms. (<b>c</b>) Chain A from human glycine receptor alpha-3 is depicted as a transparent hydrophobic surface. SAGNM predictions are yellow, glycine molecule is represented as brown, 7C6 molecule as purple, and ivermectin as green atoms. (<b>d</b>) Chain A from human glycine receptor alpha-3 is depicted as an opaque hydrophobic surface. The glycine molecule is represented as brown balls and sticks, the 7C6 molecule is represented as purple, and ivermectin as green balls and sticks. (<b>e</b>) The three insets show glycine, 7C6, and ivermectin molecules inside the hydrophobic pockets on the surface of the chain A of human glycine receptor alpha-3. The figure is produced with the VMD and UCSF Chimera programs [<a href="#B58-biomolecules-10-01346" class="html-bibr">58</a>,<a href="#B59-biomolecules-10-01346" class="html-bibr">59</a>].</p>
Full article ">Figure 3
<p>Remdesivir bound to the primer RNA inside the central channel of SARS-CoV-2 RNA-dependent RNA polymerase (RdRp), NSP12 (pdb id 7bv2 described in [<a href="#B12-biomolecules-10-01346" class="html-bibr">12</a>]). (<b>a</b>) Three RNA polymerase chains, NSP 12, NSP7, and NSP8, are represented as blue, cyan, and dark cyan ribbons. Remdesivir is represented as green atoms and pyrophosphate as dark green atoms. The dashed lines represent protein segments missing from the deposited structure. (<b>b</b>) The same structure rotated approximately 180° around the vertical axis. (<b>c</b>) Remdesivir and pyrophosphate inside the binding pocket, surrounded by the yellow SAGNM predictions (left), and inside the pocket with contact residues colored by hydrophobicity.</p>
Full article ">Figure 4
<p>Comparative analysis of hepatitis C virus (HCV) (pdb id 4wtg, chain A, left) bound to sofosbuvir, and COVID-19 RNA directed RNA polymerase (RdRp, pdb id 6m71, chain A, right). (<b>a</b>) HCV RNA-directed RNA polymerase is depicted as a blue ribbon, RNA is purple, and sofosbuvir is a green molecule (full atom representation). (<b>b</b>) HCV RdRp is represented as a transparent hydrophobic surface, SAGNM predictions are yellow and sofosbuvir is represented via green atoms. (<b>c</b>) HCV RdRp is represented as an opaque hydrophobic surface, and sofosbuvir is represented via green sticks. (<b>d</b>) The inset shows sofosbuvir inside the polymerase catalytic core. (<b>e</b>) HCV RdRp (blue ribbon) structurally aligned with COVID-19 RdRp (light blue ribbon). Sofosbuvir is a green molecule inside the HCV RdRp catalytic core. (<b>f</b>) COVID-19 RdRp as a light blue ribbon. SAGNM predictions are dark yellow atoms. Sofosbuvir is a green molecule inside the catalytic core. The position stems from the structurally aligned HCV RdRp. (<b>g</b>) COVID-19 RdRp as hydrophobically colored atoms (residues hydrophobicities). Sofosbuvir is a green molecule inside the catalytic core. The position stems from the structurally aligned HCV RdRp. With COVID-19 RNA polymerase, sofosbuvir’s position corresponds to the position it has when bound to HCV RNA polymerase.</p>
Full article ">Figure 5
<p>COVID-19 RNA directed RNA polymerase with cofactors NSP7 and NSP8 (pdb id 6m71). The NSP 12 chain is cyan, and its SAGNM predictions are yellow. The NSP 7 chain is pink and its SAGNM predictions are purple. The NSP 8 chain is orange and SAGNM predictions are dark red. The dashed lines represent segments missing from the coordinates file.</p>
Full article ">Figure 6
<p>Boceprevir and its target protein COVID-19 (SARS-CoV-2) main protease (pdb id 6wnp). (<b>a</b>) COVID-19 Main protease is depicted as a blue ribbon, SAGNM predictions are yellow, and boceprevir as green atoms. (<b>b</b>) COVID-19 main protease is depicted as a transparent hydrophobic surface, SAGNM predictions are yellow, and chloroquine is a green molecule. (<b>c</b>) COVID-19 main protease is depicted as an opaque hydrophobic surface, and chloroquine is depicted via green balls and sticks. (<b>d</b>) The inset shows boceprevir inside the binding pocket.</p>
Full article ">Figure 7
<p>D-ornithine and its target protein <span class="html-italic">Trypanosoma brucei</span> ornithine decarboxylase (pdb id 1njj). (<b>a</b>) Ornithine decarboxylase chains A (red) and B (blue) are depicted as ribbons, with D-ornithine and G-418 as green and dark green molecules, respectively. (<b>b</b>) Ornithine decarboxylase chains A and B are depicted as hydrophobicity surface, with D-ornithine and G-418 as green and dark green molecules, respectively. (<b>c</b>) Ornithine decarboxylase chain A depicted as a transparent hydrophobicity surface, with SAGNM predictions are yellow atoms, and with D-ornithine and G-418 as green and dark green molecules. (<b>d</b>) D-ornithine and G-418 molecules depicted as colored bonds and sticks, correspondingly to the atom type and inside pockets on the surface of ornithine decarboxylase.</p>
Full article ">Figure 8
<p>SARS spike glycoprotein chain B RBD bound to the angiotensin-converting enzyme 2 (ACE2) receptor (pdb id 6cs2) in comparison to COVID-19 spike glycoprotein chain A RBD bound to the ACE2 receptor (pdb id 6m0j). (<b>a</b>) The ACE2 receptor is represented via blue atoms and its SAGM predictions are yellow atoms. SARS spike glycoprotein is represented via red atoms, and its SAGNM predictions and green atoms. (<b>b</b>) The ACE2 receptor is represented as a blue ribbon, and its SAGM predictions are yellow atoms. SARS spike glycoprotein is the red ribbon, and its SAGNM predictions and green atoms. (<b>c</b>) Contact areas for both chains are represented as hydrophobicity surfaces. The contact chains in each case are shown as ribbons, and predictions are represented via Cα atoms only. (<b>d</b>) The ACE2 receptor is represented via blue atoms, and its SAGM predictions are yellow atoms. COVID-19 spike glycoprotein is represented via red atoms, and its SAGNM predictions and green atoms. (<b>e</b>) The ACE2 receptor is represented as a blue ribbon, and its SAGM predictions are yellow atoms. COVID-19 spike glycoprotein is the red ribbon, and its SAGNM predictions are green atoms. (<b>f</b>) Contact areas for both chains are represented as hydrophobic surfaces. The contact chains in each case are shown as ribbons, and predictions are represented via Cα atoms only.</p>
Full article ">Figure 9
<p>SARS-CoV spike glycoprotein (Chain B, pdb id 6nb6) with glycans (NAG, BMA, MAN) bound to it. (<b>a</b>) Ribbon-like representation of SARS spike glycoprotein. The SAGNM predictions are yellow atoms. BMA molecules are represented via purple atoms. MAN molecules are represented via orange atoms. NAG molecules are represented via green atoms. Cyan bars represent missing glycoprotein segments. Circles represent areas where the SAGNM predictions recognize real binding spots. (<b>b</b>) SARS spike glycoprotein is depicted via hydrophobicity colored atoms. Glycans (NAG, BMA, MAN) are represented via colored bonds (same colors as above). (<b>c</b>) SARS spike glycoprotein is depicted via transparent hydrophobicity colored atoms. Glycans (NAG, BMA, MAN) are represented via colored bonds (same colors as above). The SAGNM predictions are yellow atoms. Glycans (NAG, BMA, MAN) are represented via colored atoms.</p>
Full article ">Figure 10
<p>Receptor binding domain (RBD) of SARS-CoV spike glycoprotein (chain A, pdb id 6nb6) with the human neutralizing S230 antibody FAB fragment. (<b>a</b>) SARS-CoV RBD (blue, chain A) with heavy (green, H, and I) and light (red, L, and M) chains. Predictions are cyan (SARS), yellow (S230 light), and light green (S230 heavy). (<b>b</b>) Hydrophobic surface of SARS RBD bound to S230 (chains H and L). (<b>c</b>) Transparent hydrophobic surface of SARS RBD and S230 (chains H and L) with predictions.</p>
Full article ">
14 pages, 2438 KiB  
Article
Lipophilic Cations Rescue the Growth of Yeast under the Conditions of Glycolysis Overflow
by Svyatoslav S. Sokolov, Ekaterina A. Smirnova, Olga V. Markova, Natalya A. Kireeva, Roman S. Kirsanov, Liudmila S. Khailova, Dmitry A. Knorre and Fedor F. Severin
Biomolecules 2020, 10(9), 1345; https://doi.org/10.3390/biom10091345 - 20 Sep 2020
Cited by 4 | Viewed by 3268
Abstract
Chemicals inducing a mild decrease in the ATP/ADP ratio are considered as caloric restriction mimetics as well as treatments against obesity. Screening for such chemicals in animal model systems requires a lot of time and labor. Here, we present a system for the [...] Read more.
Chemicals inducing a mild decrease in the ATP/ADP ratio are considered as caloric restriction mimetics as well as treatments against obesity. Screening for such chemicals in animal model systems requires a lot of time and labor. Here, we present a system for the rapid screening of non-toxic substances causing such a de-energization of cells. We looked for chemicals allowing the growth of yeast lacking trehalose phosphate synthase on a non-fermentable carbon source in the presence of glucose. Under such conditions, the cells cannot grow because the cellular phosphate is mostly being used to phosphorylate the sugars in upper glycolysis, while the biosynthesis of bisphosphoglycerate is blocked. We reasoned that by decreasing the ATP/ADP ratio, one might prevent the phosphorylation of the sugars and also boost bisphosphoglycerate synthesis by providing the substrate, i.e., inorganic phosphate. We confirmed that a complete inhibition of oxidative phosphorylation alleviates the block. As our system includes a non-fermentable carbon source, only the chemicals that did not cause a complete block of mitochondrial ATP synthesis allowed the initial depletion of glucose followed by respiratory growth. Using this system, we found two novel compounds, dodecylmethyl diphenylamine (FS1) and diethyl (tetradecyl) phenyl ammonium bromide (Kor105), which possess a mild membrane-depolarizing activity. Full article
(This article belongs to the Section Cellular Biochemistry)
Show Figures

Figure 1

Figure 1
<p>Two routes of inorganic phosphate entry into cell catabolism under glycolysis-overflow conditions induced by <span class="html-italic">TPS1</span> deletion. (1) Glyceraldehyde dehydrogenase reaction consumes Pi and induces upstream fructose-1,6-bisphosphate processing. This route is expected to alleviate glycolytic block. (2) ATP synthesis via oxidative phosphorylation (OxPhos) consumes Pi; this route can aggravate glycolytic block because ATP contributes to the carbohydrate phosphorylation in the upper glycolysis and drives the synthesis of fructose-1,6-bisphosphate. Uncouplers inhibit the second pathway and, therefore, may increase the assimilation of Pi via the first route.</p>
Full article ">Figure 2
<p>C<sub>12</sub>TPP and myxothiazol alleviate the glucose-induced inhibition of the growth of <span class="html-italic">tps1-delta</span> cells in a different fashion. The representative growth curves. (<b>A</b>) Titration of glucose. (<b>B</b>) Titration of C<sub>12</sub>TPP. (<b>C</b>) Titration of glucose in the presence of myxothiazol, 1 µM. (<b>D</b>) Titration of glucose in the presence of C<sub>12</sub>TPP, 1 µM.</p>
Full article ">Figure 3
<p>Glucose consumption rates of tps1-delta cells treated with various chemicals (normalized to the control). Error bars correspond to standard deviations; <span class="html-italic">n</span> = 3–8.</p>
Full article ">Figure 4
<p>A list of chemicals tested for their ability to stimulate the growth of <span class="html-italic">tps1-delta</span> cells in the presence of glucose. The concentrations that did not produce any stimulation are shown in gray. The concentrations that correspond to the flat-followed-by-steep-shaped growth curves are shown in green; steep-followed-by-flat-shaped, in red.</p>
Full article ">Figure 5
<p>(<b>A</b>) Structural formulas of C<sub>12</sub>TPP and its analogs with varying degrees of charge shielding by phenyl groups. (<b>B</b>) A scheme illustrating the dissipation of the membrane potential by the lipophilic cations. “+” and “−” correspond to positive and negative electic charge, respectively.</p>
Full article ">Figure 6
<p>FS1 and Kor105 possess uncoupling activity. Respiration rates of intact yeast cells (<b>A</b>) and isolated yeast mitochondria (<b>D</b>) in the presence of different concentrations of the compounds, expressed as V divided by V0 (V, the rate in the presence of a compound, divided by V0, the rate without addition). (<b>B</b>,<b>C</b>) Stimulation of the respiration of rat liver mitochondria by FS1 and FCCP, absolute values of V divided by V0 and normalized ones (the maximal stimulation by a compound corresponds to 100%; the value without addition, i.e., without stimulation, corresponds to 0%), respectively. Error bars correspond to standard deviations; <span class="html-italic">n</span> = 3.</p>
Full article ">Figure 7
<p>An increase in the plasma membrane (PM) ergosterol protects cells against the lipophilic cations. The graphs show the values of the cell densities grown for 24 h in the presence of the indicated concentrations of the cations. The wild-type and <span class="html-italic">lam1-4-delta</span> (the strain with elevated PM ergosterol) cells are compared on each graph. The cells were grown on YPD (YP-Dextrose) medium. Error bars correspond to standard deviations; <span class="html-italic">n</span> = 3.</p>
Full article ">
12 pages, 2496 KiB  
Article
5-Hydroxytryptamine (5-HT) Positively Regulates Pigmentation via Inducing Melanoblast Specification and Melanin Synthesis in Zebrafish Embryos
by Li Liu, Min Zhong, Jing Dong, Minghan Chen, Jing Shang and Yunyun Yue
Biomolecules 2020, 10(9), 1344; https://doi.org/10.3390/biom10091344 - 19 Sep 2020
Cited by 12 | Viewed by 4042
Abstract
It has been reported that 5-hydroxytryptamine (5-HT) is related to melanogenesis in mice and melanoma cells. However, the underlying mechanisms of 5-HT in regulating pigmentation remains unknown. In this study, we aim to clarify the regulatory mechanism of 5-HT in the pigmentation of [...] Read more.
It has been reported that 5-hydroxytryptamine (5-HT) is related to melanogenesis in mice and melanoma cells. However, the underlying mechanisms of 5-HT in regulating pigmentation remains unknown. In this study, we aim to clarify the regulatory mechanism of 5-HT in the pigmentation of zebrafish embryos and B16F10 cells. Our results show that 5-HT induces the pigmentation of zebrafish embryos in a dosage-dependent manner at concentrations of 0.01–1 mM. Whole mount in situ hybridizations and qRT-PCR in zebrafish embryos indicate that the expression of neural crest cells marker gene sox10 is not changed in embryos treated with 5-HT compared to control group. The expression of mitfa, the marker gene of melanoblasts, is increased in the presence of 5-HT. Furthermore, 5-HT increased the expression of regeneration associated genes, namely kita, mitfa, and dct, after ablation of the melanogenic cells in zebrafish embryos. The experiments in B16F10 cells show that 5-HT promotes melanin synthesis by up-regulating the expression of key proteins MITF, TYR, TRP-1, and TRP-2. Especially, the small molecule inhibitor of PKA signaling, but not AKT and MAPK signaling, attenuates the up-regulation of MITF and TYR resulted from 5-HT induction in B16F10 cells. These results will help us to further understand the regulatory network of vertebrate pigmentation. Full article
(This article belongs to the Section Molecular Biology)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>5-HT induces pigmentation in a dose dependent manner in zebrafish embryos. (<b>A</b>–<b>E</b>) Photos of zebrafish morphology at 60 hpf. The zebrafish embryos were pre-treated with 0.2 mM PTU from 9 to 35 hpf. a-MSH (<b>B</b>–<b>B’</b>) and different concentration 5-HT (<b>C</b>–<b>E’</b>) were added and incubated for a further 25 h (until 60 hpf). Every groups were showed at both lateral view (<b>A</b>–<b>E</b>) and dorsal view (<b>A’</b>–<b>E’</b>). (<b>F</b>) Relative melanin content was calculated through normalizing with control group. (<b>G</b>) Relative tyrosinase activity was calculated through normalizing with control group. * <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, compared vs. control. Error bars, S.D.</p>
Full article ">Figure 2
<p>5-HT regulates both melanocytes development and melanin synthesis. (<b>A</b>–<b>B’</b>) Photos of zebrafish morphology at 48 hpf. Control group (<b>A</b>–<b>A’</b>) was not treated. The zebrafish embryos were treated with 1 mM 5-HT at 9 hpf and incubated until 48 hpf (B-B’). (<b>C</b>–<b>D’</b>) Photos of zebrafish morphology at 24 hpf. The embryos were treated with 1 mM 5-HT at 9 hpf and incubated until 24hpf (<b>D</b>–<b>D’</b>) compared with control group without treatment (<b>C</b>–<b>C’</b>). (<b>E</b>–<b>F’</b>) Photos of zebrafish morphology at 48 hpf. All zebrafish embryos were pre-treated with 0.2 mM PTU from 9 to 24 hpf. Then the zebrafish embryos were treated with 1 mM 5-HT at 24-48 hpf (<b>F</b>–<b>F’</b>) compared with control group without treatment (<b>E</b>–<b>E’</b>).</p>
Full article ">Figure 3
<p>5-HT is sufficient to induce melanoblast specification from neural crest cells. (<b>A</b>-<b>B</b>) Whole mount in situ hybridization showed the expression of neural crest cells marker gene <span class="html-italic">sox10</span> at 18 hpf in zebrafish embryos of control group (<b>A</b>) and 5-HT treatment (1 mM, 9-18 hpf) group (<b>B</b>). (<b>C</b>,<b>D</b>) Whole mount in situ hybridization showed the expression of melanoblast marker gene <span class="html-italic">mitfa</span> at 24 hpf in zebrafish embryos of control group (<b>C</b>) and 5-HT treatment (1 mM, 18-24 hpf) group (<b>D</b>). (<b>E</b>–<b>H</b>) Whole mount in situ hybridization showed the expression of differentiated melanocytes marker gene <span class="html-italic">dct</span> at 48 hpf in zebrafish embryos. The embryos were treated with 5-HT from 24 to 48 hpf (<b>E</b>–<b>F</b>) and from 9 to 48 hpf (<b>G</b>–<b>H</b>). All photos were taken at dorsal view. (<b>I</b>) qRT-PCR results showed the relative expression level of <span class="html-italic">sox10</span> at 18 hpf, <span class="html-italic">mitfa</span> at 24 pf and <span class="html-italic">dct</span> at 48 hpf. The black column indicates the control group. The red column indicates the 5-HT treatment (1 mM) at different time window group. ns <span class="html-italic">p</span> &gt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, compared vs. control. Error bars, S.D.</p>
Full article ">Figure 4
<p>5-HT induces melanocytes regeneration in zebrafish embryos after ablation of melanogenic lineage by chemical. Whole mount in situ hybridization showed the expression of melanocytes regeneration related gene <span class="html-italic">kita</span> (<b>A</b>–<b>E’</b>), melanoblast marker gene <span class="html-italic">mitfa</span> (<b>F</b>–<b>J’</b>) and differentiated melanocytes marker gene <span class="html-italic">dct</span> (<b>K</b>–<b>O’</b>) at 60 hpf in zebrafish embryos. Blank groups were wild type zebrafish embryos without any treatment. Control groups were treated with 50 µM MoTP from 9 to 35 hpf to ablate most melanocytes and melanoblast cells. Then marker genes were tested at 60 hpf. The 5-HT groups were treated with 50 µM MoTP from 9 to 35 hpf, then treated with different concentration 5-HT (0.01, 0.1, 1 mM) from 35 to 60 hpf. The marker genes were tested at 60 hpf.</p>
Full article ">Figure 5
<p>5-HT up-regulates MITF and TYR expression through activating PKA signaling pathway in B16F10 cells. (<b>A</b>) Western blot assays were performed to examine melanin synthesis related proteins, MITF, TYR, TRP-1 and TRP-2 in B16F10 cells with 5-HT treatment for 48 h. (<b>B</b>) Western blot assays show the protein levels of key signaling pathways, total CREB, phospho-CREB, total AKT, phospho-AKT, p38, phospho-p38, JNK2, phospho-JNK, ERK1/2, phospho-ERK. (<b>C</b>) Western blot assays show the expression of MITF and TYR in B16F10 cells treated with 5-HT and/or H89 (small molecule inhibitor of PKA signaling pathway). β-Actin was used for normalization. “+” means treat, “-” means no treat.</p>
Full article ">
12 pages, 1500 KiB  
Article
Molecular Topology for the Discovery of New Broad-Spectrum Antibacterial Drugs
by Jose I. Bueso-Bordils, Pedro A. Alemán-López, Beatriz Suay-García, Rafael Martín-Algarra, Maria J. Duart, Antonio Falcó and Gerardo M. Antón-Fos
Biomolecules 2020, 10(9), 1343; https://doi.org/10.3390/biom10091343 - 19 Sep 2020
Cited by 4 | Viewed by 2208
Abstract
In this study, molecular topology was used to develop several discriminant equations capable of classifying compounds according to their antibacterial activity. Topological indices were used as structural descriptors and their relation to antibacterial activity was determined by applying linear discriminant analysis (LDA) on [...] Read more.
In this study, molecular topology was used to develop several discriminant equations capable of classifying compounds according to their antibacterial activity. Topological indices were used as structural descriptors and their relation to antibacterial activity was determined by applying linear discriminant analysis (LDA) on a group of quinolones and quinolone-like compounds. Four equations were constructed, named DF1, DF2, DF3, and DF4, all with good statistical parameters such as Fisher–Snedecor’s F (over 25 in all cases), Wilk’s lambda (below 0.36 in all cases) and percentage of correct classification (over 80% in all cases), which allows a reliable extrapolation prediction of antibacterial activity in any organic compound. From the four discriminant functions, it can be extracted that the presence of sp3 carbons, ramifications, and secondary amine groups in a molecule enhance antibacterial activity, whereas the presence of 5-member rings, sp2 carbons, and sp2 oxygens hinder it. The results obtained clearly reveal the high efficiency of combining molecular topology with LDA for the prediction of antibacterial activity. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>DF1 pharmacological distribution diagram. Black bars: Training Inactives. White bars: Training Actives. Dashed line: Test Inactives. Straight line: Test Actives.</p>
Full article ">Figure 2
<p>DF2 pharmacological distribution diagram. Black bars: Training Inactives. White bars: Training Actives. Dashed line: Test Inactives. Straight line: Test Actives.</p>
Full article ">Figure 3
<p>DF3 pharmacological distribution diagram. Black bars: Training Inactives. White bars: Training Actives. Dashed line: Test Inactives. Straight line: Test Actives.</p>
Full article ">Figure 4
<p>DF4 pharmacological distribution diagram. Black bars: Training Inactives. White bars: Training Actives. Dashed line: Test Inactives. Straight line: Test Actives.</p>
Full article ">
11 pages, 2813 KiB  
Article
Cryo-EM Structure of Heterologous Protein Complex Loaded Thermotoga Maritima Encapsulin Capsid
by Xiansong Xiong, Chen Sun, Frank S. Vago, Thomas Klose, Jiankang Zhu and Wen Jiang
Biomolecules 2020, 10(9), 1342; https://doi.org/10.3390/biom10091342 - 19 Sep 2020
Cited by 8 | Viewed by 4175
Abstract
Encapsulin is a class of nanocompartments that is unique in bacteria and archaea to confine enzymatic activities and sequester toxic reaction products. Here we present a 2.87 Å resolution cryo-EM structure of Thermotoga maritima encapsulin with heterologous protein complex loaded. It is the [...] Read more.
Encapsulin is a class of nanocompartments that is unique in bacteria and archaea to confine enzymatic activities and sequester toxic reaction products. Here we present a 2.87 Å resolution cryo-EM structure of Thermotoga maritima encapsulin with heterologous protein complex loaded. It is the first successful case of expressing encapsulin and heterologous cargo protein in the insect cell system. Although we failed to reconstruct the cargo protein complex structure due to the signal interference of the capsid shell, we were able to observe some unique features of the cargo-loaded encapsulin shell, for example, an extra density at the fivefold pore that has not been reported before. These results would lead to a more complete understanding of the encapsulin cargo assembly process of T. maritima. Full article
Show Figures

Figure 1

Figure 1
<p>Schematic representation of heterologous cargo-loaded encapsulin expression in insect cells. Diagrams of in vivo encapsulin assembly resulted from the coexpression of Encap and cargo proteins in the baculovirus expression system with IDM1 as cargo alone (<b>a</b>) and the IDM holo complex as cargo (<b>b</b>).</p>
Full article ">Figure 2
<p>Production of heterologous cargo-loaded encapsulin. The SDS-PAGE result of His-GFP-IDM1 and His-GFP-IDM complex (<b>a</b>), Encap/IDM1 and Encap/IDM complex (<b>b</b>). His-GFP-IDM1: His-GFP fused at the N-terminal of IDM1. The IDM complex without encapsulin (<b>a</b>) was purified with the His-tag on the N terminal of IDM1 protein. In the Encap/IDM complex, there was no His-tag on IDM1 but was at the C-terminal of encapsulin capsid (Encap). The molecular weight of His-GFP tag, MBP tag, IDM1, IDM2, IDM3, HDP1, HDP2, and MBD7 are 32kDa, 40kDa, 131kDa, 39kDa, 52kDa, 46kDa, 33kDa, and 35kDa, respectively. Cryo-EM image of Encap/IDM1 (<b>c</b>) from Talos F200X G2 and Encap/IDM complex (<b>d</b>) from Titan Krios. Representative 2D class averages generated from the Encap/IDM1 (<b>e</b>) and the Encap/IDM complex dataset (<b>f</b>). The “matchto” processor in EMAN2 [<a href="#B27-biomolecules-10-01342" class="html-bibr">27</a>] accessed through <span class="html-italic">e2proc2d.py</span> was used to filter the 2D class averages to the same level by matching their structure factor curves.</p>
Full article ">Figure 2 Cont.
<p>Production of heterologous cargo-loaded encapsulin. The SDS-PAGE result of His-GFP-IDM1 and His-GFP-IDM complex (<b>a</b>), Encap/IDM1 and Encap/IDM complex (<b>b</b>). His-GFP-IDM1: His-GFP fused at the N-terminal of IDM1. The IDM complex without encapsulin (<b>a</b>) was purified with the His-tag on the N terminal of IDM1 protein. In the Encap/IDM complex, there was no His-tag on IDM1 but was at the C-terminal of encapsulin capsid (Encap). The molecular weight of His-GFP tag, MBP tag, IDM1, IDM2, IDM3, HDP1, HDP2, and MBD7 are 32kDa, 40kDa, 131kDa, 39kDa, 52kDa, 46kDa, 33kDa, and 35kDa, respectively. Cryo-EM image of Encap/IDM1 (<b>c</b>) from Talos F200X G2 and Encap/IDM complex (<b>d</b>) from Titan Krios. Representative 2D class averages generated from the Encap/IDM1 (<b>e</b>) and the Encap/IDM complex dataset (<b>f</b>). The “matchto” processor in EMAN2 [<a href="#B27-biomolecules-10-01342" class="html-bibr">27</a>] accessed through <span class="html-italic">e2proc2d.py</span> was used to filter the 2D class averages to the same level by matching their structure factor curves.</p>
Full article ">Figure 3
<p>Overall structure of IDM complex-loaded <span class="html-italic">T. maritima</span> encapsulin. (<b>a</b>) The sharpened density map of Encap/IDM complex from the icosahedral reconstruction. (<b>b</b>) The closeup view of the side-chain densities of short segments of a.a.67-74, a.a.17-33, and a.a.105-125. (<b>c</b>) The FSC curve of the reconstructed cryo-EM half maps. (<b>d</b>) Structure alignment of the Encap (coral) and Encap/IDM monomer (light blue).</p>
Full article ">Figure 4
<p>Pores of the heterologous IDM-loaded encapsulin. The inner surface view along the fivefold axis of Encap/IDM complex. From left to right: the X-ray density map of PDB-3DKT (<b>a</b>), the crystal model of <span class="html-italic">T. maritima</span> fitted into the icosahedral reconstructed density map of our dataset (<b>b</b>), and the C1 symmetry reconstructed map (<b>c</b>).</p>
Full article ">Figure 5
<p>Conformation comparison of the crystal encapsulin structure (PDB:3DKT) fitted in the X-ray 2fo-fc map (grey) (<b>a</b>) and Encap/IDM complex (<b>b</b>) refined model fitted in the EM density map (purple) at the fivefold pore.</p>
Full article ">
22 pages, 3882 KiB  
Article
Triapine Derivatives Act as Copper Delivery Vehicles to Induce Deadly Metal Overload in Cancer Cells
by Kateryna Ohui, Iryna Stepanenko, Iuliana Besleaga, Maria V. Babak, Radu Stafi, Denisa Darvasiova, Gerald Giester, Vivien Pósa, Eva A. Enyedy, Daniel Vegh, Peter Rapta, Wee Han Ang, Ana Popović-Bijelić and Vladimir B. Arion
Biomolecules 2020, 10(9), 1336; https://doi.org/10.3390/biom10091336 - 19 Sep 2020
Cited by 12 | Viewed by 4795
Abstract
Thiosemicarbazones continue to attract the interest of researchers as potential anticancer drugs. For example, 3-aminopyridine-2-carboxaldehyde thiosemicarbazone, or triapine, is the most well-known representative of this class of compounds that has entered multiple phase I and II clinical trials. Two new triapine derivatives HL [...] Read more.
Thiosemicarbazones continue to attract the interest of researchers as potential anticancer drugs. For example, 3-aminopyridine-2-carboxaldehyde thiosemicarbazone, or triapine, is the most well-known representative of this class of compounds that has entered multiple phase I and II clinical trials. Two new triapine derivatives HL1 and HL2 were prepared by condensation reactions of 2-pyridinamidrazone and S-methylisothiosemicarbazidium chloride with 3-N-(tert-butyloxycarbonyl) amino-pyridine-2-carboxaldehyde, followed by a Boc-deprotection procedure. Subsequent reaction of HL1 and HL2 with CuCl2·2H2O in 1:1 molar ratio in methanol produced the complexes [CuII(HL1)Cl2]·H2O (1·H2O) and [CuII(HL2)Cl2] (2). The reaction of HL2 with Fe(NO3)3∙9H2O in 2:1 molar ratio in the presence of triethylamine afforded the complex [FeIII(L2)2]NO3∙0.75H2O (3∙0.75H2O), in which the isothiosemicarbazone acts as a tridentate monoanionic ligand. The crystal structures of HL1, HL2 and metal complexes 1 and 2 were determined by single crystal X-ray diffraction. The UV-Vis and EPR spectroelectrochemical measurements revealed that complexes 1 and 2 underwent irreversible reduction of Cu(II) with subsequent ligand release, while 3 showed an almost reversible electrochemical reduction in dimethyl sulfoxide (DMSO). Aqueous solution behaviour of HL1 and 1, as well as of HL2 and its complex 2, was monitored as well. Complexes 13 were tested against ovarian carcinoma cells, as well as noncancerous embryonic kidney cells, in comparison to respective free ligands, triapine and cisplatin. While the free ligands HL1 and HL2 were devoid of antiproliferative activity, their respective metal complexes showed remarkable antiproliferative activity in a micromolar concentration range. The activity was not related to the inhibition of ribonucleotide reductase (RNR) R2 protein, but rather to cancer cell homeostasis disturbance—leading to the disruption of cancer cell signalling. Full article
(This article belongs to the Section Molecular Biology)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>ORTEP views of (<b>a</b>) <b>HL<sup>1</sup></b>, (<b>b</b>) <b>HL<sup>2</sup></b>, (<b>c</b>) <b>[Cu(HL<sup>1</sup>)Cl<sub>2</sub>]</b> (<b>1</b>) and (<b>d</b>) <b>[Cu(HL<sup>2</sup>)Cl<sub>2</sub>]</b> (<b>2</b>). Selected bond distances (Å) and bond/torsion angles (deg) in <b>HL<sup>1</sup></b>: C4–N2 1.350(3), C4–C5 1.422(3), C5–C6 1.455(2), C6–N3 1.290(2), N3–N4 1.4062(19), N4–C7 1.302(2), C7–N5 1.345(2), C7–C8 1.487(2), C8–N6 1.345(2); N3–N4–C7–N5 –1.8(2); H-bond parameters: N2–H···N3 [N2···N3 2.765(2) Å, N2–H···N3 131.0°]; in <b>HL<sup>2</sup></b>: C4–N2 1.3514(15), C6–N3 1.2828(14), N3–N4 1.3970(12), N4–C7 1.3044(14), C7–N5 1.3471(14), C7–S 1.7643(11), S1–C8 1.8043(12); C1–N1–C5–C6 –179.31(10), N3–N4–C7–N5 –174.898(10); in <b>1</b>: Cu–N1 1.997(2), Cu–N4 1.973(2), Cu–N6 2.006(2), Cu–Cl1 2.3255(7), Cu–Cl2 2.5190(6), C6–N3 1.278(4), N3–N4 1.372(3), N4–C7 1.330(3), C7–N5 1.321(3); N1–Cu–N4 91.52(8), N4–Cu–N6 80.12(8), N4–Cu–Cl1 136.54(7), N4–Cu–Cl2 111.58(6); in <b>2</b>: Cu–N1 2.063(5), Cu–N3 1.960(5), Cu–N5 1.990(4), Cu–Cl1 2.2370(17), Cu–Cl2 2.5517(17), C6–N3 1.281(7), N3–N4 1.369(6), N4–C7 1.370(7), C7–N5 1.300(7); C7–S1 1.747(5), S1–C8 1.804(6), N1–Cu–N3 78.50(19), N3–Cu–N5 78.13(19), N3–Cu–Cl1 162.08(17), N3–Cu–Cl2 100.07(16), C1–N1–C5–C6 175.7(5), N3–N4–C7–N5 0.8(8).</p>
Full article ">Figure 2
<p>Time-dependent UV–Vis spectra of (<b>a</b>) <b>HL<sup>1</sup></b> and (<b>b</b>) <b>HL<sup>2</sup></b> at physiological pH {c<sub>L</sub> = 100 µM; pH = 7.40 (20 mM HEPES); T = 298 K; I = 0.10 M (KCl); <span class="html-italic">ℓ</span> = 1.0 cm; 1% (<span class="html-italic">v</span>/<span class="html-italic">v</span>) DMSO}.</p>
Full article ">Figure 3
<p>UV–Vis spectra of <b>2</b> in the presence of EDTA at various concentrations, and the numbers show the complex-to-EDTA ratios {c<b><sub>2</sub></b> = 50 µM; c<sub>EDTA</sub> = 0–422 µM; pH = 5.90 (50 mM MES); T = 298 K; I = 0.10 M (KCl); ℓ = 1.0 cm; 1% DMSO}.</p>
Full article ">Figure 4
<p>Intracellular Cu accumulation in A2780 cells. A2780 cells were treated with Cu(II) complexes <b>1</b> and <b>2</b> at 37 °C for 24 h at indicated concentrations (µM), and Cu content was measured by ICP-MS. Statistical analysis was performed by two-tailed T-test using GraphPad Prism software (GraphPad Software Inc., CA) with <span class="html-italic">p</span> &lt; 0.05 considered as significant (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001).</p>
Full article ">Figure 5
<p>Cyclic voltammograms of 0.5 mM (<b>a</b>) of <b>1</b>, (<b>b</b>) <b>2</b> and (<b>c</b>) <b>3</b> in DMSO/<span class="html-italic">n-</span>Bu<sub>4</sub>NPF<sub>6</sub> at a scan rate of 100 mV s<sup>–1</sup> (black traces represent the first scan, while red traces the second scan).</p>
Full article ">Figure 6
<p>In situ UV–Vis spectroelectrochemistry for <b>2</b> in DMSO/<span class="html-italic">n</span>-Bu<sub>4</sub>NPF<sub>6</sub> (scan rate of 10 mV s<sup>−1</sup>, Pt-microstructured honeycomb working electrode): (<b>a</b>) Evolution of UV−Vis spectra in 2D projection in the forward scan; (<b>b</b>) UV–Vis spectra detected simultaneously upon the cyclic voltammetric scan (Inset—respective cyclic voltammogram).</p>
Full article ">Figure 7
<p>Spectroelectrochemistry of <b>3</b> in <span class="html-italic">n</span>-Bu<sub>4</sub>NPF<sub>6</sub>/DMSO in the region of the first cathodic peak. (<b>a</b>) UV–Vis spectra detected simultaneously during the in situ reduction (Pt-microstructured honeycomb working electrode, scan rate v = 10 mV s<sup>−1</sup>); (<b>b</b>) potential dependence of UV−Vis spectra (Inset—respective cyclic voltammogram with the colour-highlighted potential region, where spectra were recorded).</p>
Full article ">Figure 8
<p>Tyrosyl radical reduction in human R2 RNR protein by 3-AP and <b>HL<sup>2</sup></b> in the presence of an external reductant. The samples contained 20 μM hR2 in 50 mM Hepes buffer, pH 7.60/100 mM KCl/5% glycerol, and 20 μM 3-AP or <b>HL<sup>2</sup></b> in 1% (<span class="html-italic">v</span>/<span class="html-italic">v</span>) DMSO/H<sub>2</sub>O, and 2 mM dithiothreiotol (DTT). Error bars are the standard deviation from two independent experiments.</p>
Full article ">Figure 9
<p>Western blot analysis of various proteins involved in apoptosis (PARP and cleaved PARP), cell cycle (cyclins B1 and D1), antioxidant defence (Nrf2) and ER stress (UPR) presented as a fold change in comparison with untreated cells and normalised to actin as a loading control (one representative strip is shown). A2780 cells were treated with indicated concentrations of <b>2</b> for 24 h. Total lysates were isolated and examined by Western Blotting. The quantification of the bands was performed in Image J software.</p>
Full article ">Scheme 1
<p>Line drawings of 3-AP (triapine), carboxamidrazone <b>HL<sup>1</sup></b> and isothiosemicarbazone <b>HL<sup>2</sup></b> free ligands and complexes <b>1−3</b> reported in this work. Underlined labels/numbers indicate compounds studied by X-ray crystallography.</p>
Full article ">
25 pages, 4764 KiB  
Review
Metabolic Diversity and Therapeutic Potential of Holarrhena pubescens: An Important Ethnomedicinal Plant
by Kulsoom Zahara, Sujogya Kumar Panda, Shasank Sekhar Swain and Walter Luyten
Biomolecules 2020, 10(9), 1341; https://doi.org/10.3390/biom10091341 - 18 Sep 2020
Cited by 13 | Viewed by 5773
Abstract
Holarrhena pubescens is an important medicinal plant of the Apocynaceae family that is widely distributed over the Indian subcontinent. The plant is extensively used in Ayurveda and other traditional medicinal systems without obvious adverse effects. Beside notable progress in the biological and phytochemical [...] Read more.
Holarrhena pubescens is an important medicinal plant of the Apocynaceae family that is widely distributed over the Indian subcontinent. The plant is extensively used in Ayurveda and other traditional medicinal systems without obvious adverse effects. Beside notable progress in the biological and phytochemical evaluation of this plant over the past few years, comprehensive reviews of H. pubescens are limited in scope. It has economic importance due to the extensive use of seeds as an antidiabetic. Furthermore, the plant is extensively reported in traditional uses among the natives of Asia and Africa, while scientifical validation for various ailments has not been studied either in vitro or in vivo. This review aims to summarize information on the pharmacology, traditional uses, active constituents, safety and toxicity of H. pubescens. Chemical analysis of H. pubescens extracts revealed the presence of several bioactive compounds, such as conessine, isoconnessine, conessimine, conimine, conessidine, conkurchicine, holarrhimine, conarrhimine, mokluangin A-D and antidysentericine. Overall, this review covers the ethnopharmacology, phytochemical composition, and pharmacological potential of H. pubescens, with a critical discussion of its toxicity, biological activities (in vitro and in vivo), the mechanism of action, as well as suggestions for further basic and clinical research. Full article
(This article belongs to the Collection Pharmacology of Medicinal Plants)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Worldwide distribution of <span class="html-italic">H. pubescens</span> [<a href="#B3-biomolecules-10-01341" class="html-bibr">3</a>].</p>
Full article ">Figure 2
<p>Medicinal use of <span class="html-italic">H. pubescens</span> in India, Pakistan, Bangladesh and Nepal.</p>
Full article ">Figure 3
<p>Schematic representation of the Structural-Activity-Relationship (SAR) of the steroid-alkaloid class of phytoconstituents; conarrhimine, conessimine, conessine, conimine and isoconnessine, isolated from <span class="html-italic">H. pubescens.</span> IC<sub>50</sub> expressed in µM, range of 4 to &gt;300 for acetylcholinesterase (AChE)/neuroprotective activity.</p>
Full article ">Figure 4
<p>Schematic representation of the Structural-Activity-Relationship (SAR) of the steroid-alkaloid class of phytoconstituents; Mokluangin A-C and antidysentericine, isolated from <span class="html-italic">H. pubescens</span>. IC<sub>50</sub> expressed in µM, range of 1.44 to 23.22 for acetylcholinesterase activity.</p>
Full article ">Figure 5
<p>Three-dimensional molecular interaction of connesine with six different biological targets using the software, BIOVIA-DSV after a blind molecular docking study using software, AutoDock 4.2. Herein each protein data bank (PDB) ID represents the putative target proteins’ crystallographic structural information. PDB ID: 1HNJ, beta-ketoacyl-acyl carrier protein synthase III (FabH) of <span class="html-italic">E. coli</span>; PDB ID: 1C2B, acetylcholinesterase (AChE) of <span class="html-italic">E. electricus;</span> PDB ID: 5NN4, human lysosomal acid α glucosidase (GAA); PDB ID: 6TZ6, calcineurin catalytic (CnA) of <span class="html-italic">Candida albicans</span>; PDB ID: 5F19, human cyclooxygenase-2 (COX-2) and PDB ID: 1LDG, L-Lactate dehydrogenase (LDH) of <span class="html-italic">Plasmodium falciparum</span>.</p>
Full article ">
25 pages, 4193 KiB  
Article
Evaluation of the Adverse Effects of Chronic Exposure to Donepezil (An Acetylcholinesterase Inhibitor) in Adult Zebrafish by Behavioral and Biochemical Assessments
by Gilbert Audira, Nguyen Thi Ngoc Anh, Bui Thi Ngoc Hieu, Nemi Malhotra, Petrus Siregar, Omar Villalobos, Oliver B. Villaflores, Tzong-Rong Ger, Jong-Chin Huang, Kelvin H.-C. Chen and Chung-Der Hsiao
Biomolecules 2020, 10(9), 1340; https://doi.org/10.3390/biom10091340 - 18 Sep 2020
Cited by 15 | Viewed by 5365
Abstract
Donepezil (DPZ) is an acetylcholinesterase inhibitor used for the clinical treatment of mild cognitive impairment. However, DPZ has been reported to have adverse effects, including causing abnormal cardiac rhythm, insomnia, vomiting, and muscle cramps. However, the existence of these effects in subjects without [...] Read more.
Donepezil (DPZ) is an acetylcholinesterase inhibitor used for the clinical treatment of mild cognitive impairment. However, DPZ has been reported to have adverse effects, including causing abnormal cardiac rhythm, insomnia, vomiting, and muscle cramps. However, the existence of these effects in subjects without Dementia is unknown. In this study, we use zebrafish to conduct a deeper analysis of the potential adverse effects of DPZ on the short-term memory and behaviors of normal zebrafish by performing multiple behavioral and biochemical assays. Adult zebrafish were exposed to 1 ppm and 2.5 ppm of DPZ. From the results, DPZ caused a slight improvement in the short-term memory of zebrafish and induced significant elevation in aggressiveness, while the novel tank and shoaling tests revealed anxiolytic-like behavior to be caused by DPZ. Furthermore, zebrafish circadian locomotor activity displayed a higher reduction of locomotion and abnormal movement orientation in both low- and high-dose groups, compared to the control group. Biomarker assays revealed that these alterations were associated with an elevation of oxytocin and a reduction of cortisol levels in the brain. Moreover, the significant increases in reactive oxygen species (ROS) and malondialdehyde (MDA) levels in muscle tissue suggest DPZ exposure induced muscle tissue oxidative stress and muscle weakness, which may underlie the locomotor activity impairment. In conclusion, we show, for the first time, that chronic waterborne exposure to DPZ can severely induce adverse effects on normal zebrafish in a dose-dependent manner. These unexpected adverse effects on behavioral alteration should be carefully addressed in future studies considering DPZ conducted on zebrafish or other animals. Full article
(This article belongs to the Special Issue Cholinesterase Research)
Show Figures

Figure 1

Figure 1
<p>T-maze conditioning passive avoidance to test short-term memory of fish after 21 days exposure to 2.5 ppm of donepezil: (<b>A</b>) the latency of control and donepezil-exposed fish swimming into the punish chamber for each training session; (<b>B</b>) the total number of electric shocks given for successful training between control and donepezil-exposed fish; (<b>C</b>) the freezing time of control and donepezil-exposed fish at different time points before and after training; (<b>D</b>) the memory retention of control and donepezil-exposed fish at different time points before and after training; (<b>E</b>) the time spent in punish arm of control and donepezil-exposed fish at different time points before and after training; (<b>F</b>) the time spent in the non-punish area of control and donepezil-exposed fish at different time points before and after training. The data are expressed as the mean ± standard error of the mean (SEM) values. Different letters (a, b, c) on the error bars represent the significant differences (<span class="html-italic">p</span> &lt; 0.05); A and C–F were analyzed by two-way ANOVA with Tukey-HSD (Honestly Significant Difference) post hoc test; B was analyzed by unpaired t-test; <span class="html-italic">n</span> = 18, ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 2
<p>Behavior endpoints of control and donepezil-exposed zebrafish in novel tank test after 14 days of incubation: (<b>A</b>) average speed; (<b>B</b>) freezing time movement ratio; (<b>C</b>) time in top duration; (<b>D</b>) number of entries to the top; (<b>E</b>) latency to enter the top; and (<b>F</b>) total distance traveled in the top were analyzed. The swimming trajectories of (<b>G</b>,<b>J</b>) control; (<b>H</b>,<b>K</b>) 1 ppm Donepezil-exposed fish; and (<b>I</b>,<b>L</b>) 2.5 ppm Donepezil-exposed fish for novel tank test after 1 min and 15 min were recorded and compared. The black line represents control and the red line represented 1 ppm Donepezil-exposed fish, while the blue line represents 2.5 ppm Donepezil-exposed fish. The data are expressed as the median with interquartile range and were analyzed using a two-way repeated measure ANOVA with Geisser–Greenhouse correction. To observe the main column (donepezil) effect, Dunnett’s multiple comparison test was carried out; <span class="html-italic">n</span> = 30, * <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; 0.005, **** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 3
<p>Mirror biting and predator avoidance behavior endpoint comparisons between the control, 1 ppm, and 2.5 ppm donepezil-exposed zebrafish groups after 14 days of exposure: (<b>A</b>) mirror biting time percentage and (<b>B</b>) longest duration in the mirror side were analyzed in the mirror biting. The swimming trajectories of (<b>C</b>) control, (<b>D</b>) 1 ppm Donepezil-exposed fish, and (<b>E</b>) 2.5 ppm Donepezil-exposed fish for the mirror biting test were recorded and compared (<span class="html-italic">n</span> = 30 for control and 1 ppm groups, <span class="html-italic">n</span> = 29 for 2.5 ppm group). (<b>F</b>) Approaching predator time and (<b>G</b>) average distance to the separator were measured in the predator avoidance test. The swimming trajectories of (<b>H</b>) control, (<b>I</b>) 1 ppm Donepezil-exposed fish, and (<b>J</b>) 2.5 ppm Donepezil-exposed fish for predator avoidance test were recorded and compared (<span class="html-italic">n</span> = 23 for the control group, <span class="html-italic">n</span> = 26 for 1 ppm group, <span class="html-italic">n</span> = 28 for 2.5 ppm group). The data are expressed as the median with interquartile range and were analyzed using the Kruskal–Wallis test followed by Dunn’s multiple comparisons test (####/**** <span class="html-italic">p</span> &lt; 0.001, ns = not significant).</p>
Full article ">Figure 4
<p>Social interaction behavior endpoint comparisons between the control group, 1 ppm, and 2.5 ppm donepezil-exposed zebrafish groups after 14 days of exposure: (<b>A</b>) interaction time percentage; (<b>B</b>) longest duration at separator side; (<b>C</b>) average distance to the separator; and (<b>D</b>) average speed were analyzed. The swimming trajectories of (<b>E</b>) control, (<b>F</b>) 1 ppm Donepezil-exposed fish, and (<b>G</b>) 2.5 ppm Donepezil-exposed fish for social interaction tests were recorded and compared. The data are expressed as the median with interquartile range and were analyzed using the Kruskal–Wallis test followed by Dunn’s multiple comparisons test (<span class="html-italic">n</span> = 29 for control and 2.5 ppm groups, <span class="html-italic">n</span> = 30 for 1 ppm group, * <span class="html-italic">p</span> &lt; 0.05, ##/** <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001, #### <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 5
<p>Shoaling behavior endpoint comparisons between the control group, 1 ppm, and 2.5 ppm donepezil-exposed zebrafish groups after 14 days of exposure: (<b>A</b>) average inter-fish distance; (<b>B</b>) average nearest neighbor distance; and (<b>C</b>) average farthest neighbor distance were analyzed. The swimming trajectories of (<b>D</b>) control, (<b>E</b>) 1 ppm Donepezil-exposed fish, and (<b>F</b>) 2.5 ppm Donepezil-exposed fish for shoaling tests were recorded and compared. Groups of three fish were tested for shoaling behavior. The data are expressed as the median with interquartile range and were analyzed using the Kruskal–Wallis test followed by Dunn’s multiple comparisons test (<span class="html-italic">n</span> = 30, * <span class="html-italic">p</span> &lt; 0.05, ##/** <span class="html-italic">p</span> &lt; 0.01, ### <span class="html-italic">p</span> &lt; 0.001, #### <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 6
<p>Evaluation of the circadian locomotor activity for control and chronic donepezil-exposed fish: (<b>A</b>) Circadian patterns of average speed; (<b>B</b>) average speed; (<b>C</b>) average angular velocity; (<b>D</b>) meandering; (<b>E</b>) freezing movement time ratio; (<b>F</b>) swimming movement time ratio; and (<b>G</b>) rapid movement ratio during the light cycle. (<b>H</b>) Average speed; (<b>I</b>) average angular velocity; (<b>J</b>) meandering; (<b>K</b>) freezing movement time ratio; (<b>L</b>) swimming movement time ratio; and (<b>M</b>) rapid movement ratio during the dark cycle. The data are expressed as the median with interquartile range and were analyzed using Kruskal–Wallis test followed by Dunn’s multiple comparisons test (<span class="html-italic">n</span> control fish = 18; <span class="html-italic">n</span> donepezil-treated fish = 18; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 7
<p>Comparison of the color preference behavior between control and donepezil-exposed fish after 17 days of donepezil exposure. The combinations of four colors were: (<b>A</b>) the green/blue test, (<b>B</b>) green/yellow test, (<b>C</b>) green/red test, (<b>D</b>) red/blue test, (<b>E</b>) red/yellow test, and (<b>F</b>) blue/yellow test. The data are expressed as the mean ± SEM values and were analyzed by two-way ANOVA (<span class="html-italic">n</span> = 24; * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, and **** <span class="html-italic">p</span> &lt; 0.0001).</p>
Full article ">Figure 8
<p>Summary of biochemical and behavioral changes in adult zebrafish after acute or chronic exposure to Donepezil. The behavioral alterations are summarized in the right panel and the biochemical alterations in brain and muscle tissues are summarized in the left panel.</p>
Full article ">
19 pages, 588 KiB  
Review
Pompe Disease: New Developments in an Old Lysosomal Storage Disorder
by Naresh K. Meena and Nina Raben
Biomolecules 2020, 10(9), 1339; https://doi.org/10.3390/biom10091339 - 18 Sep 2020
Cited by 59 | Viewed by 14380
Abstract
Pompe disease, also known as glycogen storage disease type II, is caused by the lack or deficiency of a single enzyme, lysosomal acid alpha-glucosidase, leading to severe cardiac and skeletal muscle myopathy due to progressive accumulation of glycogen. The discovery that acid alpha-glucosidase [...] Read more.
Pompe disease, also known as glycogen storage disease type II, is caused by the lack or deficiency of a single enzyme, lysosomal acid alpha-glucosidase, leading to severe cardiac and skeletal muscle myopathy due to progressive accumulation of glycogen. The discovery that acid alpha-glucosidase resides in the lysosome gave rise to the concept of lysosomal storage diseases, and Pompe disease became the first among many monogenic diseases caused by loss of lysosomal enzyme activities. The only disease-specific treatment available for Pompe disease patients is enzyme replacement therapy (ERT) which aims to halt the natural course of the illness. Both the success and limitations of ERT provided novel insights in the pathophysiology of the disease and motivated the scientific community to develop the next generation of therapies that have already progressed to the clinic. Full article
Show Figures

Figure 1

Figure 1
<p>Pathogenic cascade of muscle damage in Pompe disease.</p>
Full article ">
30 pages, 3017 KiB  
Article
Production of Aromatic Compounds by Catalytic Depolymerization of Technical and Downstream Biorefinery Lignins
by Alfonso Cornejo, Fernando Bimbela, Rui Moreira, Karina Hablich, Íñigo García-Yoldi, Maitane Maisterra, António Portugal, Luis M. Gandía and Víctor Martínez-Merino
Biomolecules 2020, 10(9), 1338; https://doi.org/10.3390/biom10091338 - 18 Sep 2020
Cited by 12 | Viewed by 3856
Abstract
Lignocellulosic materials are promising alternatives to non-renewable fossil sources when producing aromatic compounds. Lignins from Populus salicaceae. Pinus radiata and Pinus pinaster from industrial wastes and biorefinery effluents were isolated and characterized. Lignin was depolymerized using homogenous (NaOH) and heterogeneous (Ni-, Cu- [...] Read more.
Lignocellulosic materials are promising alternatives to non-renewable fossil sources when producing aromatic compounds. Lignins from Populus salicaceae. Pinus radiata and Pinus pinaster from industrial wastes and biorefinery effluents were isolated and characterized. Lignin was depolymerized using homogenous (NaOH) and heterogeneous (Ni-, Cu- or Ni-Cu-hydrotalcites) base catalysis and catalytic hydrogenolysis using Ru/C. When homogeneous base catalyzed depolymerization (BCD) and Ru/C hydrogenolysis were combined on poplar lignin, the aromatics amount was ca. 11 wt.%. Monomer distributions changed depending on the feedstock and the reaction conditions. Aqueous NaOH produced cleavage of the alkyl side chain that was preserved when using modified hydrotalcite catalysts or Ru/C-catalyzed hydrogenolysis in ethanol. Depolymerization using hydrotalcite catalysts in ethanol produced monomers bearing carbonyl groups on the alkyl side chain. The analysis of the reaction mixtures was done by size exclusion chromatography (SEC) and diffusion ordered nuclear magnetic resonance spectroscopy (DOSY NMR). 31P NMR and heteronuclear single quantum coherence spectroscopy (HSQC) were also used in this study. The content in poly-(hydroxy)-aromatic ethers in the reaction mixtures decreased upon thermal treatments in ethanol. It was concluded that thermo-solvolysis is key in lignin depolymerization, and that the synergistic effect of Ni and Cu provided monomers with oxidized alkyl side chains. Full article
(This article belongs to the Special Issue Biomolecules from Plant Residues)
Show Figures

Figure 1

Figure 1
<p>(<b>a</b>) Aromatic region for the DOSY spectra of BioB (black) and BioB<sub>473</sub> (blue); (<b>b</b>) SEC for BioB (red) and BioB<sub>473</sub> (blue); (<b>c</b>) DOSY spectra and (<b>d</b>) SEC for OrgB (black), OrgB<sub>463</sub> (red) and OrgB<sub>HTC2.5</sub> (blue). Figures in black, red and blue correspond to polystyrene, PS, calibration.</p>
Full article ">Figure 2
<p>(<b>a</b>) DOSY in the aromatic region and (<b>b</b>) SEC for SeolA (black), A<sub>493</sub> (blue) and A<sub>493-Ru</sub> (red). (<b>c</b>) DOSY in the aromatic region and (<b>d</b>) SEC for SeolA (black), A<sub>523</sub> (blue) and A<sub>523-Ru</sub> (red). Figures in red and blue correspond to PS calibration.</p>
Full article ">Figure 3
<p>(<b>a</b>) DOSY spectra and (<b>b</b>) SEC for SeolA (black), A<sub>523-Ru</sub> (red) and A<sub>Ru</sub> (blue). Figures on the left correspond to PS calibration.</p>
Full article ">Figure 4
<p>DOSY spectrum for SeolA523-Ru. Figures on the left correspond to PS calibration and figures on the right to PEG calibration. Red dotted squares correspond to the integration regions in the aromatic and in the aliphatic regions.</p>
Full article ">Scheme 1
<p>Strategies for the isolation of lignins from the feedstocks selected in this work.</p>
Full article ">Scheme 2
<p>Lignin depolymerization strategies.</p>
Full article ">
14 pages, 18129 KiB  
Article
The Cytokine IL-1β and Piperine Complex Surveyed by Experimental and Computational Molecular Biophysics
by Gabriel Zazeri, Ana Paula Ribeiro Povinelli, Marcelo de Freitas Lima and Marinônio Lopes Cornélio
Biomolecules 2020, 10(9), 1337; https://doi.org/10.3390/biom10091337 - 18 Sep 2020
Cited by 8 | Viewed by 2626
Abstract
The bioactive piperine, a compound found in some pepper species, has been widely studied because of its therapeutic properties that include the inhibition of an important inflammation pathway triggered by interleukin-1 beta (IL-1β). However, investigation into the molecular interactions between IL-1β and piperine [...] Read more.
The bioactive piperine, a compound found in some pepper species, has been widely studied because of its therapeutic properties that include the inhibition of an important inflammation pathway triggered by interleukin-1 beta (IL-1β). However, investigation into the molecular interactions between IL-1β and piperine is not reported in the literature. Here, we present for the first time the characterisation of the complex formed by IL-1β and piperine through experimental and computational molecular biophysical analyses. Fluorescence spectroscopy unveiled the presence of one binding site for piperine with an affinity constant of 14.3 × 104 M−1 at 298 K. The thermodynamic analysis indicated that the interaction with IL-1β was spontaneous (∆G = −25 kJ/mol) and, when split into enthalpic and entropic contributions, the latter was more significant. Circular dichroism spectroscopy showed that piperine did not affect IL-1β secondary structure (~2%) and therefore its stability. The set of experimental data parameterized the computational biophysical approach. Through molecular docking, the binding site micro-environment was revealed to be composed mostly by non-polar amino acids. Furthermore, molecular dynamics, along with umbrella sampling, are in agreement with the thermodynamic parameters obtained by fluorescence assays and showed that large protein movements are not present in IL-1β, corroborating the circular dichroism data. Full article
Show Figures

Figure 1

Figure 1
<p>Spectra of fluorescence emission of IL-1β obtained from titration experiments with increments in the concentration of piperine (pH 7.4, T = 298 K, λ<sub>ex</sub> = 295 nm). [IL-1β] = 4.0 μM; Piperine titrations with increment of 4 μM (a → u). The inset is a representation of the molecular structure of piperine.</p>
Full article ">Figure 2
<p>Left ordinate Stern–Volmer plots at three temperatures, 288, 298, and 308 K, and right ordinate time-resolved fluorescence lifetime plot at 298 K; [IL-1β] = 4 μM, [piperine] = 0–48 μM. Piperine increments of 4 μM. R<sup>2</sup> &gt; 0.98.</p>
Full article ">Figure 3
<p>Double-log plots for the fluorescence quenching of IL-1β (4 μM) by the presence of piperine at 288, 298, and 308 K. R<sup>2</sup> &gt; 0.98.</p>
Full article ">Figure 4
<p>van’t Hoff plot for the complex IL-1β/piperine at 288, 298, and 308 K. R<sup>2</sup> &gt; 0.99.</p>
Full article ">Figure 5
<p>Plot of ∆F versus log [piperine] obtained from piperine titration experiments with IL-1β concentrations of 4 and 8 μM at 298 K. The horizontal solid line indicates the same percentage of quenching at different IL-1β concentrations. The inset shows an example of the lines obtained for each set of quenching percentage.</p>
Full article ">Figure 6
<p>Scatchard plot of IL-1β and piperine at 298 K temperature with linear regression (black line). R<sup>2</sup> &gt; 0.99.</p>
Full article ">Figure 7
<p>IL-1β circular dichroism experiments in the presence and absence of piperine with 1:12 stoichiometry at (<b>a</b>) 288 K, (<b>b</b>) 298 K and (<b>c</b>) 308 K.</p>
Full article ">Figure 8
<p>IL-1β binding site of piperine predicted by molecular docking in (<b>a</b>) a general view, (<b>b</b>) with the amino acids (licorice outfit) that compose the binding environment; hydrogen bonds are highlighted with dots and (<b>c</b>) the interactions represented by LigPlot.</p>
Full article ">Figure 9
<p>Configuration histograms of the pulling in <span class="html-italic">z</span>-axis from ξ = 1.7 nm to ξ = 6 nm with the windows distance as being 0.1 nm.</p>
Full article ">Figure 10
<p>Potential of mean force (PMF) for the dissociation of piperine from IL-1β. Piperine was pulled away from the protein using the reaction coordinate ξ as being the distance between Glu111 carbon atom (CA index 1129) and piperine carbon atom (CAE 1585) with the force applied in Z direction (see <a href="#app1-biomolecules-10-01337" class="html-app">Figure S4</a>).</p>
Full article ">Figure 11
<p>IL-1β secondary structures changes of (<b>a</b>) the whole protein and (<b>b</b>) only the binding site during the dissociation of piperine (from ξ = 1.7 nm to ξ = 5.7 nm), where T represents the Turns (green), E the β-sheet (yellow), B the isolated bridge(brown), H the alpha-helix (pink), G the 3–10 helix (blue), I the Pi-helix (red) and C the coil (white).</p>
Full article ">
11 pages, 7212 KiB  
Article
Natural Compounds Modulate Drug Transporter Mediated Oral Cancer Treatment
by Hsiang Yang, Yu-Ching Wei, Wan-Chun Li, Hsin-Yung Chen, Hung-Ying Lin, Chun-Pin Chiang and Hsin-Ming Chen
Biomolecules 2020, 10(9), 1335; https://doi.org/10.3390/biom10091335 - 17 Sep 2020
Cited by 12 | Viewed by 3014
Abstract
Oral cancer (OC) is a serious health problem. Surgery is the best method to treat the disease but might reduce the quality of life of patients. Photodynamic therapy (PDT) may enhance quality of life but with some limitations. Therefore, the development of a [...] Read more.
Oral cancer (OC) is a serious health problem. Surgery is the best method to treat the disease but might reduce the quality of life of patients. Photodynamic therapy (PDT) may enhance quality of life but with some limitations. Therefore, the development of a new strategy to facilitate PDT effectiveness has become crucial. ATP-binding cassette G2 (ABCG2) is a membrane protein-associated drug resistance and stemness in cancers. Here, we examined whether ABCG2 plays an important role in regulating the treatment efficacy of PDT and whether ABCG2 inhibition by natural compounds can promote the effect of PDT in OC cells. Several head and neck cancer cells were utilized in this study. OECM1 and SAS cells were selected to investigate the relationship between ABCG2 expression and protoporphyrin IX (PpIX) accumulation. Western blot analysis, flow cytometry analysis, and survival probability were performed to determine PDT efficacy and cellular stemness upon treatment of different dietary compounds, including epigallocatechin gallate (EGCG) and curcumin. In this study, we found that ABCG2 expression varied in OC cells. Hypoglycemic culture for SAS cells enhanced ABCG2 expression as higher ABCG2 expression was associated with lower PpIX accumulation and cellular stemness in OC cells. In contrast, suppression of ABCG2 expression by curcumin and tea polyphenol EGCG led to greater PpIX accumulation and enhanced PDT treatment efficiency in OC cells. In conclusion, ABCG2 plays an important role in regulating the effect of PDT. Change in glucose concentration and treatment with natural compounds modulated ABCG2 expression, resulting in altered PDT efficacy for OC cells. These modulations raise a potential new treatment strategy for early-stage OCs. Full article
(This article belongs to the Special Issue Application and Mechanism of Natural Compounds in Dentistry)
Show Figures

Figure 1

Figure 1
<p>ATP-binding cassette G2 (ABCG2) expression was different in varied head and neck cancer (HNC) cell lines, which affected the amount of protoporphyrin IX (PpIX) and the survival percentage while the cells were treated with 5-aminolevulinic acid photodynamic therapy (ALA-PDT), and was modulated by different compounds. (<b>A</b>) Western blot analysis showed that ABCG2 was highly expressed in OECM1 but not in SAS, HSC3, and Fadu cells. (<b>B</b>) In parental status, PpIX amount of the four HNC cell lines showed no significant difference. For those cells treated with ALA, OECM1 produced the lowest amount of PpIX in comparison with SAS, HSC3, and Fadu cells. Switch of SAS cells from a medium containing 25 mM glucose to 5.5 mM glucose (<b>C</b>) induced ABCG2 expression and (<b>D</b>) downregulated PpIX accumulation in a time-dependent manner. (<b>E</b>) Western blot analysis for phospho-Akt, total Akt, Nrf2, and ABCG2 protein expression in OECM1 and SASL90d cells with/without treatment of PI3K inhibitor LY294002 (<span class="html-italic">n</span> ≥ 3; *<span class="html-italic">p</span> &lt; 0.05; ***<span class="html-italic">p</span> &lt; 0.001). IC<sub>50</sub> of ALA-PDT treatment was measured in ABCG2-enriched cells: (<b>F</b>) OECM1, parental SAS, and SASL90d cells; (<b>G</b>) OECM1; and (<b>H</b>) SASL90d. ABCG2 level was significantly inhibited by gefitinib, epigallocatechin gallate (EGCG), and curcumin but not by naringenin. <span class="html-italic">n</span> ≥ 3, *<span class="html-italic">p</span> &lt; 0.05, ***<span class="html-italic">p</span> &lt; 0.001, ****<span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 2
<p>Gefitinib treatment suppresses ABCG2 expression, increases PpIx accumulation, and decreases ALA-PDT-mediated HNC cell viability. (<b>A</b>) Western blot analysis for p-EGFR (Y1068), p-Akt (S473), Nrf2, and ABCG2 expression in OECM1 and SASL90d cells treated with different concentrations of gefitinib. Gefitinib repressed EGFR and Akt signaling activities as well as ABCG2 and Nrf2 expression. In OECM1 and SASL90d, gefitinib treatment (<b>B</b>) upregulated PpIX accumulation and (<b>C</b>) decreased cell viability in a dose-dependent manner. <span class="html-italic">n</span> ≥ 3; *<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>EGCG treatment suppresses ABCG2 expression, increases PpIx accumulation, and decreases ALA-PDT mediated-HNC cell viability. (<b>A</b>) Western blot analysis for p-EGFR (Y1068), p-Akt (S473), Nrf2, and ABCG2 expression in OECM1 and SASL90d cells treated with different concentrations of tea polyphenol EGCG. EGCG inhibited EGFR and Akt signaling activities as well as ABCG2 and Nrf2 expression. In OECM1 and SASL90d, EGCG treatment (<b>B</b>) upregulated PpIX accumulation and (<b>C</b>) decreased cell viability in a dose-dependent manner. <span class="html-italic">n</span> ≥ 3; ***<span class="html-italic">p</span> &lt; 0.001, ****<span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 4
<p>Curcumin treatment suppresses ABCG2 expression, increases PpIx accumulation, and decreases ALA-PDT-mediated HNC cell viability. (<b>A</b>) Western blot analysis for p-EGFR (Y1068), p-Akt (S473), Nrf2, and ABCG2 expression in OECM1 and SASL90d cells treated with different concentrations of curcumin. Curcumin inhibited EGFR and Akt signaling activities as well as ABCG2 and Nrf2 expression. In OECM1 and SASL90d, curcumin treatment (<b>B</b>) upregulated PpIX accumulation and (<b>C</b>) decreased cell viability in a dose-dependent manner. <span class="html-italic">n</span> ≥ 3; *<span class="html-italic">p</span> &lt; 0.05; **<span class="html-italic">p</span> &lt; 0.01, ****<span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 5
<p>ABCG2 expression is associated with increased stemness, tumor grade, and HNC prognosis. (<b>A</b>) ABCG2 was enriched in SAS sphere culture compared with SAS parental cells. (<b>B</b>) Aldehyde dehydrogenase (ALDH)<sup>+</sup> cell population gradually increased once SAS cells were cultured in a medium containing lower glucose. ABCG2 expression increased with increasing low-glucose culture time. ALDH<sup>+</sup> percentage also increased with ABCG2 expression, with individual values of 16.24%, 18.29%, and 27.01%. BODIPY-aminoacetaldehyde (BAAA) is an ALDH substrate, and diethylaminobenzaldehyde (DEAB) is an inhibitor of ALDH activity. (<b>C</b>) Statistical analysis for ABCG2 mRNA levels in normal and primary HNC tissues stratified by clinical grades from UALCAN database. *<span class="html-italic">p</span> &lt; 0.05. (<b>D</b>) Kaplan–Meier analysis for cancer-specific survival rates in HNSCC patients classified by ABCG2 expression using the Human Protein Atlas database. The expression cut-off value is 0.32 FPKM (fragments per kilobase of transcript per million mapped reads).</p>
Full article ">
25 pages, 26408 KiB  
Article
Automatic Quantification of Cardiomyocyte Dimensions and Connexin 43 Lateralization in Fluorescence Images
by Antoni Oliver-Gelabert, Laura García-Mendívil, José María Vallejo-Gil, Pedro Carlos Fresneda-Roldán, Katarína Andelová, Javier Fañanás-Mastral, Manuel Vázquez-Sancho, Marta Matamala-Adell, Fernando Sorribas-Berjón, Carlos Ballester-Cuenca, Narcisa Tribulova, Laura Ordovás, Emiliano Raúl Diez and Esther Pueyo
Biomolecules 2020, 10(9), 1334; https://doi.org/10.3390/biom10091334 - 17 Sep 2020
Cited by 8 | Viewed by 4278
Abstract
Cardiomyocytes’ geometry and connexin 43 (CX43) amount and distribution are structural features that play a pivotal role in electrical conduction. Their quantitative assessment is of high interest in the study of arrhythmias, but it is usually hampered by the lack of automatic tools. [...] Read more.
Cardiomyocytes’ geometry and connexin 43 (CX43) amount and distribution are structural features that play a pivotal role in electrical conduction. Their quantitative assessment is of high interest in the study of arrhythmias, but it is usually hampered by the lack of automatic tools. In this work, we propose a software algorithm (Myocyte Automatic Retrieval and Tissue Analyzer, MARTA) to automatically detect myocytes from fluorescent microscopy images of cardiac tissue, measure their morphological features and evaluate the expression of CX43 and its degree of lateralization. The proposed software is based on the generation of cell masks, contouring of individual cells, enclosing of cells in minimum area rectangles and splitting of these rectangles into end-to-end and middle compartments to estimate CX43 lateral-to-total ratio. Application to human ventricular tissue images shows that mean differences between automatic and manual methods in terms of cardiomyocyte length and width are below 4 μm. The percentage of lateral CX43 also agrees between automatic and manual evaluation, with the interquartile range approximately covering from 3% to 30% in both cases. MARTA is not limited by fiber orientation and has an optimized speed by using contour filtering, which makes it run hundreds of times faster than a trained expert. Developed for CX43 studies in the left ventricle, MARTA is a flexible tool applicable to morphometric and lateralization studies of other markers in any heart chamber or even skeletal muscle. This open-access software is available online. Full article
(This article belongs to the Special Issue Connexins, Innexins, and Pannexins: From Biology to Clinical Targets)
Show Figures

Figure 1

Figure 1
<p>Input fluorescence microscopy images. <span class="html-italic">A</span>, <span class="html-italic">B</span>, <span class="html-italic">C</span>, from left to right: human samples from three individuals <span class="html-italic">a</span>, <span class="html-italic">b</span> and <span class="html-italic">c</span>. <span class="html-italic">D</span> and <span class="html-italic">E</span>, from left to right: rat samples <math display="inline"><semantics> <mrow> <mi>d</mi> <mn>2</mn> </mrow> </semantics></math> and <span class="html-italic">e</span>. Green signal corresponds to sarco/endoplasmic reticulum <math display="inline"><semantics> <mrow> <mi>C</mi> <msup> <mi>a</mi> <mrow> <mn>2</mn> <mo>+</mo> </mrow> </msup> </mrow> </semantics></math> ATPase (SERCA2) in humans and F-actin in rat samples (channel <math display="inline"><semantics> <msub> <mi>c</mi> <mn>1</mn> </msub> </semantics></math>). White signal marks connexin 43 (CX43) (channel <math display="inline"><semantics> <msub> <mi>c</mi> <mn>2</mn> </msub> </semantics></math>). Red signal is wheat germ agglutinin (WGA) in human samples (channel <math display="inline"><semantics> <msub> <mi>c</mi> <mn>3</mn> </msub> </semantics></math>). Scale bar is in all cases 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 2
<p>Image of a left ventricular rat tissue partly analyzed in this study (<b>left</b>) and three insets at higher magnification (<b>right</b>). Green signal represents F-actin (channel <math display="inline"><semantics> <msub> <mi>c</mi> <mn>1</mn> </msub> </semantics></math>). White signal is CX43 (channel <math display="inline"><semantics> <msub> <mi>c</mi> <mn>2</mn> </msub> </semantics></math>). Within the myocardium, black background estimates the interstitium (channel <math display="inline"><semantics> <msub> <mi>c</mi> <mn>3</mn> </msub> </semantics></math>). Scale bar: left, 1000 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m; right insets, 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 3
<p>Left panel: representation of vertex projection from original coordinates (<math display="inline"><semantics> <mrow> <msub> <mi>x</mi> <mrow> <mi>v</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> <mo>,</mo> <msub> <mi>y</mi> <mrow> <mi>v</mi> <mo>,</mo> <mi>i</mi> </mrow> </msub> </mrow> </semantics></math>) to extended coordinates (<math display="inline"><semantics> <mrow> <msubsup> <mi>x</mi> <mrow> <mi>v</mi> <mo>,</mo> <mi>i</mi> </mrow> <mo>*</mo> </msubsup> <mo>,</mo> <msubsup> <mi>y</mi> <mrow> <mi>v</mi> <mo>,</mo> <mi>i</mi> </mrow> <mo>*</mo> </msubsup> </mrow> </semantics></math>). Right panel: illustration of how the intersection between cardiomyocytes (CMs) in the manual and automatic masks was computed. The red box <math display="inline"><semantics> <msub> <mi>B</mi> <msub> <mi>a</mi> <mi>j</mi> </msub> </msub> </semantics></math> shows the enclosing rectangle for a CM in the automatic mask <math display="inline"><semantics> <msub> <mi>M</mi> <mi>a</mi> </msub> </semantics></math>, whereas the blue box <math display="inline"><semantics> <msub> <mi>B</mi> <msub> <mi>m</mi> <mi>i</mi> </msub> </msub> </semantics></math> shows the enclosing rectangle for a CM in the manual mask <math display="inline"><semantics> <msub> <mi>M</mi> <mi>m</mi> </msub> </semantics></math>. The purple area is the intersection between the areas of the two rectangles: <math display="inline"><semantics> <mrow> <msub> <mi>A</mi> <msub> <mi>a</mi> <mi>j</mi> </msub> </msub> <mspace width="2.0pt"/> <mspace width="2.0pt"/> <mo>∩</mo> <msub> <mi>A</mi> <msub> <mi>m</mi> <mi>i</mi> </msub> </msub> </mrow> </semantics></math>.</p>
Full article ">Figure 4
<p>Top: <math display="inline"><semantics> <msub> <mi>M</mi> <mrow> <mi>c</mi> <mn>1</mn> </mrow> </msub> </semantics></math> (SERCA2) and <math display="inline"><semantics> <msub> <mi>M</mi> <mrow> <mi>c</mi> <mn>3</mn> </mrow> </msub> </semantics></math> (WGA) binarized channels. Bottom left: <math display="inline"><semantics> <msub> <mi>M</mi> <mrow> <mi>c</mi> <mn>2</mn> </mrow> </msub> </semantics></math> (CX43) binarized channel. Bottom right: merged channel. Scale bar = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 5
<p>Merged channels for image <span class="html-italic">a</span> before (<b>left</b>) and after (<b>right</b>) noise removal. Scale bar = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 6
<p>Manual versus automatic cell delineation in image <span class="html-italic">a</span>. Top left: mask <math display="inline"><semantics> <msub> <mi>M</mi> <mi>m</mi> </msub> </semantics></math> obtained by manual delineation of CMs’ boundaries in image <span class="html-italic">a</span>. Top right: mask <math display="inline"><semantics> <msub> <mi>M</mi> <mi>a</mi> </msub> </semantics></math> generated by Myocyte Automatic Retrieval and Tissue Analyzer (MARTA) software for image <span class="html-italic">a</span>. Bottom left: CMs’ contours for manual (white) and automatic (green) masks and corresponding enclosing rectangles (blue for manual, red for automatic). Bottom right: Enclosing rectangles from manual and automatic masks showing overlapping above 50%. Scale bar = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 7
<p>Percentile curves of maximum intersection <math display="inline"><semantics> <msub> <mi>I</mi> <mi>i</mi> </msub> </semantics></math> for CMs <span class="html-italic">i</span> in <math display="inline"><semantics> <msub> <mi>M</mi> <mi>m</mi> </msub> </semantics></math>, for all the analyzed images. Area Under the Curve (AUC) values are presented in the legend.</p>
Full article ">Figure 8
<p>CMs in the manual (<b>left</b>) and automatic (<b>right</b>) masks contoured in pink, with enclosing rectangles in yellow. At the bottom right corner of each panel is an example of morphological measures computed for a CM detected in both masks. Scale bar = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 9
<p>Box plots of length <span class="html-italic">L</span> (top left), width <span class="html-italic">W</span> (top right), length-to-width ratio <span class="html-italic">R</span> (bottom left) and area <span class="html-italic">A</span> (bottom right) for manual (in blue) and automatic (in red) masks, calculated for images <span class="html-italic">a</span>, <span class="html-italic">b</span> and <span class="html-italic">c</span>.</p>
Full article ">Figure 10
<p>Left: Tissue mask <math display="inline"><semantics> <msub> <mi>M</mi> <mi>t</mi> </msub> </semantics></math> represented in white, enclosed by maximum contour in red, for image <span class="html-italic">a</span>. Right: Equalized and binarized channel <math display="inline"><semantics> <msub> <mi>M</mi> <mrow> <mi>c</mi> <mn>4</mn> </mrow> </msub> </semantics></math> (<math display="inline"><semantics> <mrow> <mi>t</mi> <mi>h</mi> <msub> <mi>r</mi> <mrow> <mi>c</mi> <mn>4</mn> </mrow> </msub> <mo>=</mo> <mn>254</mn> </mrow> </semantics></math>) for the same image. Scale bar = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 11
<p>Representative images of box partitioning for two CMs A and B of the manual <math display="inline"><semantics> <msub> <mi>M</mi> <mi>m</mi> </msub> </semantics></math> (<b>left</b>) and automatic <math display="inline"><semantics> <msub> <mi>M</mi> <mi>a</mi> </msub> </semantics></math> (<b>right</b>) masks. Top: overlay of channels <math display="inline"><semantics> <msub> <mi>c</mi> <mn>1</mn> </msub> </semantics></math> (SERCA2, green), <math display="inline"><semantics> <msub> <mi>c</mi> <mn>2</mn> </msub> </semantics></math> (CX43, white) and <math display="inline"><semantics> <msub> <mi>c</mi> <mn>3</mn> </msub> </semantics></math> (WGA, red) and results of CMs contour in pink, and the minimum area rectangles enclosing them in yellow. Rectangles are divided into four regions corresponding to polar (i.e., end-to-end) and lateral (i.e., middle) cell compartments. Bottom: channel <math display="inline"><semantics> <msub> <mi>c</mi> <mn>2</mn> </msub> </semantics></math> without binarization. Polar CX43 bands appear as discontinuous line patterns because of the low signal intensity. Scale bar = 20 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 12
<p>Histograms and density plots for <math display="inline"><semantics> <msub> <mi>C</mi> <mrow> <mi>l</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics></math> computed for images <span class="html-italic">a</span> (<b>top left</b>), <span class="html-italic">b</span> (<b>top right</b>) and <span class="html-italic">c</span> (<b>bottom left</b>), as well as for pooled data from the three images (<b>bottom right</b>), both from automatic (red) and manual (blue) CM masks.</p>
Full article ">Figure 13
<p>Detected CMs in the automatic mask <math display="inline"><semantics> <msub> <mi>M</mi> <mi>a</mi> </msub> </semantics></math> computed under the supervised mode for images <math display="inline"><semantics> <mrow> <mi>d</mi> <mn>1</mn> </mrow> </semantics></math> (<b>left</b>) and <math display="inline"><semantics> <mrow> <mi>d</mi> <mn>2</mn> </mrow> </semantics></math> (<b>right</b>). Scale bar = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 14
<p>Examples of four detected CMs from automatic masks obtained for images <math display="inline"><semantics> <mrow> <mi>d</mi> <mn>1</mn> </mrow> </semantics></math> (<b>top</b>) and <math display="inline"><semantics> <mrow> <mi>d</mi> <mn>2</mn> </mrow> </semantics></math> (<b>bottom</b>). Morphological measurements and <math display="inline"><semantics> <msub> <mi>C</mi> <mrow> <mi>l</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics></math> values are provided in <a href="#biomolecules-10-01334-t003" class="html-table">Table 3</a> for <math display="inline"><semantics> <mrow> <mi>d</mi> <msub> <mn>1</mn> <mrow> <mi>C</mi> <mi>M</mi> <mo>,</mo> <mn>1</mn> </mrow> </msub> </mrow> </semantics></math> (<b>top left</b>), <math display="inline"><semantics> <mrow> <mi>d</mi> <msub> <mn>1</mn> <mrow> <mi>C</mi> <mi>M</mi> <mo>,</mo> <mn>2</mn> </mrow> </msub> </mrow> </semantics></math> (<b>top right</b>), <math display="inline"><semantics> <mrow> <mi>d</mi> <msub> <mn>2</mn> <mrow> <mi>C</mi> <mi>M</mi> <mo>,</mo> <mn>3</mn> </mrow> </msub> </mrow> </semantics></math> (<b>bottom left</b>) and <math display="inline"><semantics> <mrow> <mi>d</mi> <msub> <mn>2</mn> <mrow> <mi>C</mi> <mi>M</mi> <mo>,</mo> <mn>4</mn> </mrow> </msub> </mrow> </semantics></math> (<b>bottom right</b>). Scale bar = 20 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 15
<p>Binarized channels representing the CM mask <math display="inline"><semantics> <msub> <mi>M</mi> <mrow> <mi>c</mi> <mn>1</mn> </mrow> </msub> </semantics></math> (<b>top left</b>, in green), the interstitium generated by inverting the CM mask (<b>top right</b>, in red) and the CX43 mask <math display="inline"><semantics> <msub> <mi>M</mi> <mrow> <mi>c</mi> <mn>2</mn> </mrow> </msub> </semantics></math> (<b>bottom left</b>, in white), as well as original image <span class="html-italic">e</span> with overlaid CMs detected in supervised mode (<b>bottom right</b>). Scale bar = 100 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">Figure 16
<p>Four detected CMs from the automatic mask <math display="inline"><semantics> <msub> <mi>M</mi> <mi>a</mi> </msub> </semantics></math> on top of image <span class="html-italic">e</span>. Morphological measurements and <math display="inline"><semantics> <msub> <mi>C</mi> <mrow> <mi>l</mi> <mi>a</mi> <mi>t</mi> </mrow> </msub> </semantics></math> values are provided in <a href="#biomolecules-10-01334-t003" class="html-table">Table 3</a> for <math display="inline"><semantics> <msub> <mi>e</mi> <mrow> <mi>C</mi> <mi>M</mi> <mo>,</mo> <mn>1</mn> </mrow> </msub> </semantics></math> (<b>top left</b>), <math display="inline"><semantics> <msub> <mi>e</mi> <mrow> <mi>C</mi> <mi>M</mi> <mo>,</mo> <mn>2</mn> </mrow> </msub> </semantics></math> (<b>top right</b>), <math display="inline"><semantics> <msub> <mi>e</mi> <mrow> <mi>C</mi> <mi>M</mi> <mo>,</mo> <mn>3</mn> </mrow> </msub> </semantics></math> (<b>bottom left</b>) and <math display="inline"><semantics> <msub> <mi>e</mi> <mrow> <mi>C</mi> <mi>M</mi> <mo>,</mo> <mn>4</mn> </mrow> </msub> </semantics></math> (<b>bottom right</b>). Scale bar = 20 <math display="inline"><semantics> <mi mathvariant="sans-serif">μ</mi> </semantics></math>m.</p>
Full article ">
25 pages, 4138 KiB  
Review
Mulinane- and Azorellane-Type Diterpenoids: A Systematic Review of Their Biosynthesis, Chemistry, and Pharmacology
by Angel de Jesús Dzul-Beh, Andrés Humberto Uc-Cachón, Jorge Bórquez, Luis A. Loyola, Luis Manuel Peña-Rodríguez and Gloria María Molina-Salinas
Biomolecules 2020, 10(9), 1333; https://doi.org/10.3390/biom10091333 - 17 Sep 2020
Cited by 7 | Viewed by 3079
Abstract
Mulinane- and azorellane-type diterpenoids have unique tricyclic fused five-, six-, and seven-membered systems and a wide range of biological properties, including antimicrobial, antiprotozoal, spermicidal, gastroprotective, and anti-inflammatory, among others. These secondary metabolites are exclusive constituents of medicinal plants belonging to the Azorella, [...] Read more.
Mulinane- and azorellane-type diterpenoids have unique tricyclic fused five-, six-, and seven-membered systems and a wide range of biological properties, including antimicrobial, antiprotozoal, spermicidal, gastroprotective, and anti-inflammatory, among others. These secondary metabolites are exclusive constituents of medicinal plants belonging to the Azorella, Laretia, and Mulinum genera. In the last 30 years, more than 95 mulinanes and azorellanes have been reported, 49 of them being natural products, 4 synthetics, and the rest semisynthetic and biotransformed derivatives. This systematic review highlights the biosynthetic origin, the chemistry, and the pharmacological activities of this remarkably interesting group of diterpenoids. Full article
(This article belongs to the Section Chemical Biology)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Carbon skeletons of mulinane (<b>a</b>) and azorellane (<b>b</b>) diterpenoids.</p>
Full article ">Figure 2
<p>Biosynthetic pathway to mulinane and azorellane diterpenoid skeletons. GGPP: geranylgeranyl pyrophosphate; <span class="html-italic">S</span>-GLPP: <span class="html-italic">S</span>-geranyllinaloyl pyrophosphate; OPP: Pyrophosphate [<a href="#B11-biomolecules-10-01333" class="html-bibr">11</a>].</p>
Full article ">Figure 3
<p>Natural mulinane and azorellane diterpenoids.</p>
Full article ">Figure 3 Cont.
<p>Natural mulinane and azorellane diterpenoids.</p>
Full article ">Figure 4
<p>Synthetic mulinanes diterpenoids.</p>
Full article ">Figure 5
<p>Semisynthetic mulinane diterpenoids.</p>
Full article ">Figure 6
<p>Biotransformed mulinane diterpenoids.</p>
Full article ">
25 pages, 3302 KiB  
Review
Rescue of Hepatic Phospholipid Remodeling Defect in iPLA2β-Null Mice Attenuates Obese but Not Non-Obese Fatty Liver
by Walee Chamulitrat, Chutima Jansakun, Huili Li and Gerhard Liebisch
Biomolecules 2020, 10(9), 1332; https://doi.org/10.3390/biom10091332 - 17 Sep 2020
Cited by 9 | Viewed by 3891
Abstract
Polymorphisms of group VIA calcium-independent phospholipase A2 (iPLA2β or PLA2G6) are positively associated with adiposity, blood lipids, and Type-2 diabetes. The ubiquitously expressed iPLA2β catalyzes the hydrolysis of phospholipids (PLs) to generate a fatty acid and a lysoPL. We [...] Read more.
Polymorphisms of group VIA calcium-independent phospholipase A2 (iPLA2β or PLA2G6) are positively associated with adiposity, blood lipids, and Type-2 diabetes. The ubiquitously expressed iPLA2β catalyzes the hydrolysis of phospholipids (PLs) to generate a fatty acid and a lysoPL. We studied the role of iPLA2β on PL metabolism in non-alcoholic fatty liver disease (NAFLD). By using global deletion iPLA2β-null mice, we investigated three NAFLD mouse models; genetic Ob/Ob and long-term high-fat-diet (HFD) feeding (representing obese NAFLD) as well as feeding with methionine- and choline-deficient (MCD) diet (representing non-obese NAFLD). A decrease of hepatic PLs containing monounsaturated- and polyunsaturated fatty acids and a decrease of the ratio between PLs and cholesterol esters were observed in all three NAFLD models. iPLA2β deficiency rescued these decreases in obese, but not in non-obese, NAFLD models. iPLA2β deficiency elicited protection against fatty liver and obesity in the order of Ob/Ob › HFD » MCD. Liver inflammation was not protected in HFD NAFLD, and that liver fibrosis was even exaggerated in non-obese MCD model. Thus, the rescue of hepatic PL remodeling defect observed in iPLA2β-null mice was critical for the protection against NAFLD and obesity. However, iPLA2β deletion in specific cell types such as macrophages may render liver inflammation and fibrosis, independent of steatosis protection. Full article
(This article belongs to the Special Issue Phospholipases: From Structure to Biological Function)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Lipid contents and composition show a defect of hepatic PL remodeling in Ob/Ob mice. Male wild-type (WT) and Ob/Ob mice at six months old were used. (<b>A</b>) The contents of hepatic triglycerides (TG), total fatty acids (FAs). (<b>B</b>) FA composition of saturated, monounsaturated fatty acids (MUFA), di unsaturated, and &gt; 2 unsaturated FA. (<b>C</b>) The composition of phospholipids (PLs) and cholesterol esters (CEs). (<b>D</b>) The contents of PLs and CEs containing monounsaturated fatty acids (MUFA). (<b>E</b>) The contents of PLs and CEs containing polyunsaturated fatty acids (PUFA). (<b>F</b>) The contents of sphingolipids. Data are mean ± SEM, N = 5–7; *, <span class="html-italic">p</span> &lt; 0.05 <span class="html-italic">versus</span> WT.</p>
Full article ">Figure 2
<p>iPLA<sub>2</sub>β inactivation in Ob/Ob mice rescues the defect of hepatic PL remodeling. Male WT, Ob/Ob, and double knockout Ob/Ob-iPLA<sub>2</sub>β KO at six months old were used. (<b>A</b>) Representative photographs of hematoxylin- and eosin-stained livers of Ob/Ob mice and Ob/Ob-iPLA<sub>2</sub>β KO. (<b>B</b>) The composition of PLs and CEs. (<b>C</b>) The contents of PLs and CEs containing MUFA. (<b>D</b>) The contents of PLs and CEs containing PUFA. Data are mean ± SEM, N = 5–7; #, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">versus</span> WT; *, <span class="html-italic">p</span> &lt; 0.05, Ob/Ob <span class="html-italic">versus</span> Ob/Ob-iPLA<sub>2</sub>β KO.</p>
Full article ">Figure 3
<p>Lipid contents and composition show a defect of hepatic PL remodeling of WT mice fed with high-fat diet (HFD) for six months. Male WT mice at six months old were used. (<b>A</b>) The contents of hepatic triglycerides (TG), total fatty acids (FA). (<b>B</b>) FA composition of saturated, MUFA, di unsaturated, and &gt; 2 unsaturated FA. (<b>C</b>) The composition of PLs and CEs. (<b>D</b>) The contents of PLs and CEs containing MUFA. (<b>E</b>) The contents (nmol/mg liver) of PLs and CEs containing PUFA. (<b>F</b>) The contents of sphingolipids SMs and Cers. Data are mean ± SEM, N = 5–12; *, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">versus</span> WT.</p>
Full article ">Figure 4
<p>Inactivation in HFD-fed mice rescues the defect of hepatic PL remodeling. Male WT and iPLA<sub>2</sub>β KO mice at six months old were fed with HFD for six months. (<b>A</b>) Representative photographs of hematoxylin- and eosin-stained livers of HFD-fed WT and iPLA<sub>2</sub>β KO mice. (<b>B</b>) The composition of PLs and CEs. (<b>C</b>) The contents of PLs and CEs containing MUFA. (<b>D</b>) The contents of PLs and CEs containing PUFA. Data are mean ± SEM, N = 5–12; #, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">versus</span> WT; *, <span class="html-italic">p</span> &lt; 0.05, WT/HFD <span class="html-italic">versus</span> iPLA<sub>2</sub>β KO/HFD.</p>
Full article ">Figure 5
<p>Inactivation does not rescue the defect of hepatic phospholipid remodeling in methionine- and choline-deficient (MCD) diet-fed mice. Female WT and iPLA<sub>2</sub>β KO mice at 12 months old were fed with MCD diet for four weeks. (<b>A</b>) Representative photographs of hematoxylin- and eosin-stained livers of MCD-fed WT and iPLA<sub>2</sub>β KO mice. (<b>B</b>) The composition of hepatic PLs, CEs, and free cholesterol (FC). (<b>C</b>) The contents of PLs and CEs containing MUFA. (<b>D</b>) The contents of PLs and CEs containing PUFA. (<b>E</b>) The contents of sphingolipids SMs and Cers. Data are mean ± SEM, N = 5–6; #, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">versus</span> WT; *, <span class="html-italic">p</span> &lt; 0.05, WT/MCD <span class="html-italic">versus</span> iPLA<sub>2</sub>β KO/MCD.</p>
Full article ">Figure 6
<p>iPLA<sub>2</sub>β inactivation on PL profiles of liver ER fractions of HFD- and MCD-fed mice. Feeding with HFD or MCD diet was described in <a href="#biomolecules-10-01332-f004" class="html-fig">Figure 4</a> and <a href="#biomolecules-10-01332-f005" class="html-fig">Figure 5</a>, respectively. ER fractions were isolated from mouse livers and ER proteins subjected to PL profiling by LC-MS/MS. (<b>A</b>) The contents of PC, PE, PI, and PS in the ER of WT, iPLA<sub>2</sub>β-KO, WT/HFD, and iPLA<sub>2</sub>β-KO/HFD livers. (<b>B</b>) Saturated, MUFA, PUFA, and total contents of PC and PE in liver ER fractions of WT, iPLA<sub>2</sub>β-KO, WT/MCD, and iPLA<sub>2</sub>β-KO/MCD livers. Data are mean ± SEM, N = 5–12 for (A) and 5–6 for (B); *, <span class="html-italic">p</span> &lt; 0.05, between indicated pairs.</p>
Full article ">Figure 7
<p>Alters the ratios among phospholipid subclasses in 3 NAFLD models: Ob/Ob mice, HFD-, and MCD-fed mice. Ob/Ob mice, HFD-, and MCD-fed mice are described in <a href="#biomolecules-10-01332-f001" class="html-fig">Figure 1</a>, <a href="#biomolecules-10-01332-f003" class="html-fig">Figure 3</a> and <a href="#biomolecules-10-01332-f005" class="html-fig">Figure 5</a>, respectively. The ratio among PLs in livers of (<b>A</b>) Ob/Ob, (<b>B</b>) HFD-fed mice, and (<b>C</b>) MCD-fed mice. Data are mean ± SEM, N = 5–7 for (<b>A</b>); N = 4–5 for (<b>B</b>), and N = 5–6 for (<b>C</b>). #, <span class="html-italic">p</span> &lt; 0.05, <span class="html-italic">versus</span> WT; *, <span class="html-italic">p</span> &lt; 0.05, Ob/Ob <span class="html-italic">versus</span> Ob/Ob-iPLA<sub>2</sub>β KO or WT/HFD <span class="html-italic">versus</span> iPLA<sub>2</sub>β KO/HFD.</p>
Full article ">Figure 8
<p>Expression of iPLA<sub>2</sub>β protein and de novo lipogenesis mRNA in livers of WT, Ob/Ob mice, HFD-, and MCD-fed mice. Ob/Ob mice, HFD-, and MCD-fed mice are described in <a href="#biomolecules-10-01332-f001" class="html-fig">Figure 1</a>, <a href="#biomolecules-10-01332-f003" class="html-fig">Figure 3</a> and <a href="#biomolecules-10-01332-f005" class="html-fig">Figure 5</a>, respectively. Expression of (<b>A</b>) iPLA<sub>2</sub>β protein, (<b>B</b>) HFD-fed mice, and (<b>C</b>) MCD-fed mice. Data are mean ± SEM, N = 5–7 for PCR data; #, <span class="html-italic">p</span> &lt; 0.05; §, <span class="html-italic">p</span> &lt; 0.05, KO <span class="html-italic">versus</span> KO/MCD; *, <span class="html-italic">p</span> &lt; 0.05 between indicated groups.</p>
Full article ">Figure 9
<p>Role of iPLA<sub>2</sub>β deficiency in obese and non-obese NAFLD/NASH mouse models. (<b>A</b>) Livers of genetic Ob/Ob and chronic HFD-fed mice exhibited a defect in PL remodeling with suppressed contents of PUFA PLs. PC/PE ratio was increased in Ob/Ob mice while that of HFD-fed mice was decreased. iPLA<sub>2</sub>β inactivation replenished PLs associated with fatty liver protection. (<b>B</b>) Livers of MCD-fed mice exhibited a defect in PL remodeling with suppressed PUFA PLs as well as PC/PE ratio. iPLA<sub>2</sub>β inactivation in MCD-fed mice did not rescue this defect with no protection. We propose that iPLA<sub>2</sub>β deficiency in specific cell types may lead to no protection in liver inflammation and liver fibrosis in HFD and MCD NAFLD model, respectively (marked in red).</p>
Full article ">
20 pages, 1085 KiB  
Review
Targeting Receptors on Cancer Cells with Protein Toxins
by Antonella Antignani, Eric Chun Hei Ho, Maria Teresa Bilotta, Rong Qiu, Robert Sarnvosky and David J. FitzGerald
Biomolecules 2020, 10(9), 1331; https://doi.org/10.3390/biom10091331 - 17 Sep 2020
Cited by 27 | Viewed by 4958
Abstract
Cancer cells frequently upregulate surface receptors that promote growth and survival. These receptors constitute valid targets for intervention. One strategy involves the delivery of toxic payloads with the goal of killing those cancer cells with high receptor levels. Delivery can be accomplished by [...] Read more.
Cancer cells frequently upregulate surface receptors that promote growth and survival. These receptors constitute valid targets for intervention. One strategy involves the delivery of toxic payloads with the goal of killing those cancer cells with high receptor levels. Delivery can be accomplished by attaching a toxic payload to either a receptor-binding antibody or a receptor-binding ligand. Generally, the cell-binding domain of the toxin is replaced with a ligand or antibody that dictates a new binding specificity. The advantage of this “immunotoxin” approach lies in the potency of these chimeric molecules for killing cancer cells. However, receptor expression on normal tissue represents a significant obstacle to therapeutic intervention. Full article
(This article belongs to the Special Issue Immunotoxins: From Design to Clinical Application)
Show Figures

Figure 1

Figure 1
<p>Immunotoxin and ligand toxin constructs. In examples 1 and 2, antibodies (blue) are joined with toxins (red) to form immunotoxins. Shown in example 1, a toxin is attached chemically to a full-length antibody. Example 2 is a genetic fusion between the single-chain Fv portion of an antibody and a toxin. In examples 3 and 4, the two most common ligand toxin constructs are shown. Example 3 shows a ligand toxin whereby the ligand (blue) is placed at the <span class="html-italic">N</span>-terminus of the construct, in place of pseudomonas exotoxin’s (PE’s) native binding domain. Example 4 shows the ligand at the <span class="html-italic">C</span>-terminus, replacing the native binding domain of diphtheria toxin (DT).</p>
Full article ">Figure 2
<p>Anti-receptor targeting by immunotoxins and ligand toxins. A ligand toxin is shown interacting with a target receptor at the ligand-binding site. Similarly, an immunotoxin is shown binding the same receptor but at a distinct site. Following binding, internalization results in delivery to endosomes. In endosomes, toxins are processed (often by furin-like proteases) to separate the antibody or ligand from the toxin. After the processing step, some toxins such as DT translocate directly from endosomes (yellow arrow) to the cell cytosol while others traffic further into the cell to the endoplasmic reticulum where translocation is noted for pseudomonas exotoxin (PE) and some plant toxins (purple arrow). Once in the cytosol, toxins shut down protein synthesis.</p>
Full article ">
17 pages, 18386 KiB  
Article
Allosteric Inhibition of Adenylyl Cyclase Type 5 by G-Protein: A Molecular Dynamics Study
by Elisa Frezza, Tina-Méryl Amans and Juliette Martin
Biomolecules 2020, 10(9), 1330; https://doi.org/10.3390/biom10091330 - 17 Sep 2020
Cited by 6 | Viewed by 2930
Abstract
Adenylyl cyclases (ACs) have a crucial role in many signal transduction pathways, in particular in the intricate control of cyclic AMP (cAMP) generation from adenosine triphosphate (ATP). Using homology models developed from existing structural data and docking experiments, we have carried out all-atom, [...] Read more.
Adenylyl cyclases (ACs) have a crucial role in many signal transduction pathways, in particular in the intricate control of cyclic AMP (cAMP) generation from adenosine triphosphate (ATP). Using homology models developed from existing structural data and docking experiments, we have carried out all-atom, microsecond-scale molecular dynamics simulations on the AC5 isoform of adenylyl cyclase bound to the inhibitory G-protein subunit Gαi in the presence and in the absence of ATP. The results show that Gαi has significant effects on the structure and flexibility of adenylyl cyclase, as observed earlier for the binding of ATP and Gsα. New data on Gαi bound to the C1 domain of AC5 help explain how Gαi inhibits enzyme activity and obtain insight on its regulation. Simulations also suggest a crucial role of ATP in the regulation of the stimulation and inhibition of AC5. Full article
(This article belongs to the Section Molecular Structure and Dynamics)
Show Figures

Figure 1

Figure 1
<p>Structure of the cytoplasmic segment of the AC5 isoform of adenylyl cyclase and of its complexes with ATP and the regulating G-proteins Gsα and Gαi viewed from the side closest to the cell membrane. Proteins are shown as backbone ribbons. The C1 and C2 subunits of AC5 are colored blue and red respectively, Gsα is colored green, and Gαi is colored purple. ATP is shown in a CPK representation with standard chemical coloring. In each case, the structures are averages taken from the molecular dynamics simulations. For the AC5 in complex with Gαi with and without ATP, we chose one of the docking poses we used in this work.</p>
Full article ">Figure 2
<p>The two different configurations of the Gαi + AC5 + ATP complex simulated in this study. (<b>A</b>): Gαi_sym + AC5 + ATP: Gαi has an orientation symmetrical to the Gsα protein in the AC5 + Gsα complex. (<b>B</b>): Gαi_tilted + AC5 + ATP: Gαi protein is tilted with respect to AC5.</p>
Full article ">Figure 3
<p>Illustration of the key regions of AC5 catalytic domain structure with bound ATP. The C1 domain is colored blue and the C2 domain is in red, with relevant parts in darker color: the helices of C2 are involved in the binding of the stimulatory protein Gsα, the helices of C1 are involved in the binding of the inhibitory protein Gαi, the β2 loop of C2 (<b>left side</b>), and the β4 loop of C2 (<b>right side</b>), which bears the catalytic Lysine residue. The green oval indicates the binding site of Gsα, and the purple oval indicates the binding site of Gαi.</p>
Full article ">Figure 4
<p>Snapshots of the Gαi + AC5 + ATP complexes observed during the simulations, viewed from the membrane side. Gαi structures extracted every 250 ns are colored on a rainbow scale from blue to red. The C1 domain of AC5 is colored in gray and the C2 domain in beige.</p>
Full article ">Figure 5
<p>Substates of domain C2 observed during the simulation of Gαi_sym + AC5 + ATP complex. Left side: Root mean square deviation (RMSD) time series for the C2 domain, colored according to cluster membership. Right: structures closest to the center of each cluster, and relative size of each cluster as percentages. Prominent structural changes are indicated by red arrows.</p>
Full article ">Figure 6
<p>Changes in conformation induced by Gαi protein. (<b>A</b>) scenario where ATP is already bound to AC5 when Gαi interacts, (<b>B</b>) scenario where ATP is not yet bound to AC5 when Gαi interacts. More intense colors (blue for domain C1 and red for domain C2) correspond to larger movements compared to the preceding structure (i.e., AC5 + ATP for A and AC5 and AC5 + Gαi for B) on a scale of 0 to 4 Å. The insets display the β4 loop.</p>
Full article ">Figure 7
<p>Changes in flexibility induced by G proteins. (<b>A</b>) Scenario where ATP is already bound to AC5 when Gαi interacts, (<b>B</b>) scenario where ATP is not yet bound to AC5 when Gαi interacts. More intense colors (orange for increased flexibility and cyan for decreased flexibility) correspond to differences with respect to the preceding structure on a scale of −1.2 to +1.2 Å. The insets display the β4 loop.</p>
Full article ">Figure 8
<p>Interactions between ATP and key residues in different complexes. (<b>A</b>) active AC5 + ATP + Gsα, (<b>B</b>) inactive AC5 + ATP complex, (<b>C)</b> inactive Gαi_tilted + AC5 + ATP complex. Key residues of C2 are shown as sticks and colored in purple (LYS 1065) and green (ARG 1029). The C1 and C2 subunits of AC5 are colored blue and red, respectively. For clarity, the region 394–428 of C1 is omitted from the representation.</p>
Full article ">
13 pages, 2608 KiB  
Article
The Receptor Tyrosine Kinase TrkA Is Increased and Targetable in HER2-Positive Breast Cancer
by Nathan Griffin, Mark Marsland, Severine Roselli, Christopher Oldmeadow, John Attia, Marjorie M. Walker, Hubert Hondermarck and Sam Faulkner
Biomolecules 2020, 10(9), 1329; https://doi.org/10.3390/biom10091329 - 17 Sep 2020
Cited by 11 | Viewed by 3323
Abstract
The tyrosine kinase receptor A (NTRK1/TrkA) is increasingly regarded as a therapeutic target in oncology. In breast cancer, TrkA contributes to metastasis but the clinicopathological significance remains unclear. In this study, TrkA expression was assessed via immunohistochemistry of 158 invasive ductal carcinomas (IDC), [...] Read more.
The tyrosine kinase receptor A (NTRK1/TrkA) is increasingly regarded as a therapeutic target in oncology. In breast cancer, TrkA contributes to metastasis but the clinicopathological significance remains unclear. In this study, TrkA expression was assessed via immunohistochemistry of 158 invasive ductal carcinomas (IDC), 158 invasive lobular carcinomas (ILC) and 50 ductal carcinomas in situ (DCIS). TrkA was expressed in cancer epithelial and myoepithelial cells, with higher levels of TrkA positively associated with IDC (39% of cases) (p < 0.0001). Interestingly, TrkA was significantly increased in tumours expressing the human epidermal growth factor receptor-2 (HER2), with expression in 49% of HER2-positive compared to 25% of HER2-negative tumours (p = 0.0027). A panel of breast cancer cells were used to confirm TrkA protein expression, demonstrating higher levels of TrkA (total and phosphorylated) in HER2-positive cell lines. Functional investigations using four different HER2-positive breast cancer cell lines indicated that the Trk tyrosine kinase inhibitor GNF-5837 reduced cell viability, through decreased phospho-TrkA (Tyr490) and downstream AKT (Ser473) activation, but did not display synergy with Herceptin. Overall, these data highlight a relationship between the tyrosine kinase receptors TrkA and HER2 and suggest the potential of TrkA as a novel or adjunct target for HER2-positive breast tumours. Full article
(This article belongs to the Special Issue Protein Phosphorylation in Cancer: Unraveling the Signaling Pathways)
Show Figures

Figure 1

Figure 1
<p><span class="html-italic">NTRK1</span> (TrkA) gene expression in breast cancer patients from The Cancer Genome Atlas (TCGA) PAM50 dataset. The cBioPortal platform was used to data mine the TCGA PAM50 dataset. <span class="html-italic">NTRK1</span> (TrkA) gene expression, number and percentage of altered cases (amplification, mRNA upregulation, mRNA downregulation, missense mutations) are reported for (<b>A</b>) all breast tumours as well as for the following molecular subtypes of breast cancer: (<b>B</b>) basal, (<b>C</b>) luminal A, (<b>D</b>) luminal B and (<b>E</b>) HER2 enriched. (<b>F</b>) Overall patient survival for all cases of invasive breast carcinomas (<span class="html-italic">n</span> = 825), with <span class="html-italic">NTRK1</span> (TrkA)-altered cases in red and <span class="html-italic">NTRK1</span> (TrkA)-unaltered cases in blue. The number of total and deceased cases are reported in addition to medium survival (months).</p>
Full article ">Figure 2
<p>Immunohistochemical detection of TrkA in human breast cancers. The protein expression of TrkA was assessed by immunohistochemistry in a series of invasive breast cancers and ductal carcinomas in situ (DCIS). TrkA immunolabelling was observed in 39% of invasive ductal carcinomas (IDC), 20% of invasive lobular carcinomas (ILC) and 24% of DCIS, with staining mostly concentrated in the cancer epithelial cells and myoepithelium. Representative images of TrkA immunolabelling are shown. (<b>A</b>,<b>D</b>) IDC entire core. (<b>B</b>,<b>E</b>) Enlargement of areas in A and D, respectively. (<b>C</b>,<b>F</b>) IDC high magnification. For IDC, TrkA labelling was observed in cancer epithelial cells and myoepithelial cells. (<b>G</b>) ILC entire core. (<b>H</b>,<b>I</b>) Higher magnification of areas found in G. For ILC, some myoepithelial and cancer epithelial cells were positive for TrkA. (<b>J</b>) DCIS entire core. (<b>K</b>) Higher magnification of area in J. TrkA immunolabelling was rarely observed in DCIS. (<b>L</b>) Normal breast tissue. TrkA immunolabelling was not observed in normal breast tissues. Quantification of TrkA immunolabelling is reported in <a href="#biomolecules-10-01329-t001" class="html-table">Table 1</a>. <span class="html-italic">n</span> = 158 IDC, 158 ILC and 50 DCIS. Scale bars: 50 µm. Original magnification: x50 and x400 for entire cores and higher magnification regions, respectively.</p>
Full article ">Figure 3
<p>TrkA, phospho-TrkA and HER2 protein expression in a panel of breast cancer cell lines. Western blotting for TrkA was performed with cellular proteins extracted from HME (non-tumourigenic human mammary epithelial) cells and the following breast cancer cell lines: MCF-7 (luminal A), MDA-MB-231 (triple-negative) and 231-BR (brain metastatic derivative), MDA-MB-468 (triple-negative); as well as the following the HER2-positive cell lines: SK-BR-3, BT-474, MDA-MB-453 and JIMT-1. TrkA was detected as a 140 kDa band in all cell lines. In addition, a second band at 180 kDa was observed in SK-BR-3 and BT-474 cell lines. Another band at 150 kDa was detected only in HME cells. The intensity of TrkA immunoreactive bands was higher in the HER2-positive cell lines SK-BR-3, BT-474 and MDA-MB-453. Phospho-TrkA (p-TrkA) immunoreactive bands were observed at 180 kDa in SK-BR-3, BT-474 and MDA-MB-453 cell lines. HER2 protein expression was confirmed across all HER2-positive breast cancer cell lines and β-actin protein expression was used as the equal loading control.</p>
Full article ">Figure 4
<p>Impact of the Trk inhibitor GNF-5837 on HER2-positive breast cancer cell lines. HER2-positive breast cancer cells were treated with 0–40 µM grade concentrations of the Trk inhibitor GNF-5837, with and without 50 µg/mL Herceptin, in media containing 10% FBS for 48 h and a dose–response curve and associated IC<sub>50</sub> values were generated for (<b>A</b>) SK-BR-3, (<b>B</b>) BT-474, (<b>C</b>) MDA-MB-453 and (<b>D</b>) JIMT-1. Data are presented as the mean ± SD of samples from three independent experiments. (<b>E</b>) Effect of 0–20 µM GNF-5837 on TrkA phosphorylation and downstream cellular signaling. Western blot analysis was performed 48 h post-treatment with GNF-5837. The level of phospho-TrkA (p-TrkA) and phospho-AKT (p-AKT, Ser473) both decreased in a dose-dependent manner in all HER2-positive breast cancer cell lines. The 0.1% DMSO was used as the negative control treatment for the viability assay and β-actin protein expression was used as an equal loading control in Western blotting.</p>
Full article ">
10 pages, 1140 KiB  
Article
Oxygen: The Rate-Limiting Factor for Episodic Memory Performance, Even in Healthy Young Individuals
by Gil Suzin, Tom Halpert Frolinger, Dror Yogev, Amir Hadanny, Merav Catalogna, Yuri Rassovsky and Shai Efrati
Biomolecules 2020, 10(9), 1328; https://doi.org/10.3390/biom10091328 - 17 Sep 2020
Cited by 3 | Viewed by 4484
Abstract
Cognition is a crucial element of human functionality. Like any other physical capability, cognition is both enabled and limited by tissue biology. The aim of this study was to investigate whether oxygen is a rate-limiting factor for any of the main cognitive domains [...] Read more.
Cognition is a crucial element of human functionality. Like any other physical capability, cognition is both enabled and limited by tissue biology. The aim of this study was to investigate whether oxygen is a rate-limiting factor for any of the main cognitive domains in healthy young individuals. Fifty-six subjects were randomly assigned to either increased oxygen supply using hyperbaric oxygen (two atmospheres of 100% oxygen) or to a “sham” treatment (a simulation of increased pressure in a chamber with normal air). While in the chamber, participants went through a battery of tests evaluating the major cognitive domains including information processing speed, episodic memory, working memory, cognitive flexibility, and attention. The results demonstrated that from all evaluated cognitive domains, a statistically significant improvement was found in the episodic memory of the hyper-oxygenized group. The hyper-oxygenized group demonstrated a better learning curve and a higher resilience to interference. To conclude, oxygen delivery is a rate-limiting factor for memory function even in healthy young individuals under normal conditions. Understanding the biological limitations of our cognitive functions is important for future development of interventional tools that can be used in daily clinical practice. Full article
(This article belongs to the Special Issue Oxygen Therapy)
Show Figures

Figure 1

Figure 1
<p>A trial from the cognitive processing speed test (gray frames were added for illustration purposes).</p>
Full article ">Figure 2
<p>An example of three trials from the augmented Stroop task. The three colored boxes in the center of each trial were used to indicate either the location of the correct answer (left/right) or the color of the right answer (red/green/blue). The correct sequence in the three trials above would be “red—blue—red.”</p>
Full article ">Figure 3
<p>An example of two simple series and one complex series. Grey frames and the answers in red on the right side were added for illustration purposes.</p>
Full article ">Figure 4
<p>Subject inclusion flow diagram.</p>
Full article ">
35 pages, 1893 KiB  
Review
Extracellular Vesicles as Nanotherapeutics for Parkinson’s Disease
by Loredana Leggio, Greta Paternò, Silvia Vivarelli, Francesca L’Episcopo, Cataldo Tirolo, Gabriele Raciti, Fabrizio Pappalardo, Carmela Giachino, Salvatore Caniglia, Maria Francesca Serapide, Bianca Marchetti and Nunzio Iraci
Biomolecules 2020, 10(9), 1327; https://doi.org/10.3390/biom10091327 - 16 Sep 2020
Cited by 22 | Viewed by 6099
Abstract
Extracellular vesicles (EVs) are naturally occurring membranous structures secreted by normal and diseased cells, and carrying a wide range of bioactive molecules. In the central nervous system (CNS), EVs are important in both homeostasis and pathology. Through receptor–ligand interactions, direct fusion, or endocytosis, [...] Read more.
Extracellular vesicles (EVs) are naturally occurring membranous structures secreted by normal and diseased cells, and carrying a wide range of bioactive molecules. In the central nervous system (CNS), EVs are important in both homeostasis and pathology. Through receptor–ligand interactions, direct fusion, or endocytosis, EVs interact with their target cells. Accumulating evidence indicates that EVs play crucial roles in the pathogenesis of many neurodegenerative disorders (NDs), including Parkinson′s disease (PD). PD is the second most common ND, characterized by the progressive loss of dopaminergic (DAergic) neurons within the Substantia Nigra pars compacta (SNpc). In PD, EVs are secreted by both neurons and glial cells, with either beneficial or detrimental effects, via a complex program of cell-to-cell communication. The functions of EVs in PD range from their etiopathogenetic relevance to their use as diagnostic tools and innovative carriers of therapeutics. Because they can cross the blood–brain barrier, EVs can be engineered to deliver bioactive molecules (e.g., small interfering RNAs, catalase) within the CNS. This review summarizes the latest findings regarding the role played by EVs in PD etiology, diagnosis, prognosis, and therapy, with a particular focus on their use as novel PD nanotherapeutics. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Schematic representation of biogenesis and release mechanisms for different types of extracellular vesicles.</p>
Full article ">Figure 2
<p>Naturally occurring and engineered EVs as cell-free treatment for PD. EVs may be manipulated to deliver: (i) anti-oxidant agents (e.g., curcumin, catalase or ApoD) which protect neurons from oxidative stress; (ii) growth factors (e.g., GDNF) to stimulate proliferation of DAergic neurons; (iii) DA to ameliorate behavioral parameters; (iv) siRNAs silencing the expression of SNCA gene to decrease α-Syn levels. Different routes of administration (systemic injection, intranasal injection and intraperitoneal injection) may be used to treat PD mouse models.</p>
Full article ">Figure 3
<p>Naturally occurring and engineered EVs in the treatment of PD: mechanism of action. Following their administration, EVs cross the BBB to reach the brain, where they target neurons and glial cells. Among the effects in EV recipient cells: (i) production of anti-oxidant molecules, (ii) reduction of neuroinflammation, (iii) decrease in α-Syn levels, (iv) increase in DA bioavailability.</p>
Full article ">
17 pages, 12871 KiB  
Article
Isolation of Cysteine-Rich Peptides from Citrullus colocynthis
by Behzad Shahin-Kaleybar, Ali Niazi, Alireza Afsharifar, Ghorbanali Nematzadeh, Reza Yousefi, Bernhard Retzl, Roland Hellinger, Edin Muratspahić and Christian W. Gruber
Biomolecules 2020, 10(9), 1326; https://doi.org/10.3390/biom10091326 - 16 Sep 2020
Cited by 7 | Viewed by 4292
Abstract
The plant Citrullus colocynthis, a member of the squash (Cucurbitaceae) family, has a long history in traditional medicine. Based on the ancient knowledge about the healing properties of herbal preparations, plant-derived small molecules, e.g., salicylic acid, or quinine, have been integral to [...] Read more.
The plant Citrullus colocynthis, a member of the squash (Cucurbitaceae) family, has a long history in traditional medicine. Based on the ancient knowledge about the healing properties of herbal preparations, plant-derived small molecules, e.g., salicylic acid, or quinine, have been integral to modern drug discovery. Additionally, many plant families, such as Cucurbitaceae, are known as a rich source for cysteine-rich peptides, which are gaining importance as valuable pharmaceuticals. In this study, we characterized the C. colocynthis peptidome using chemical modification of cysteine residues, and mass shift analysis via matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry. We identified the presence of at least 23 cysteine-rich peptides in this plant, and eight novel peptides, named citcol-1 to -8, with a molecular weight between ~3650 and 4160 Da, were purified using reversed-phase high performance liquid chromatography (HPLC), and their amino acid sequences were determined by de novo assignment of b- and y-ion series of proteolytic peptide fragments. In silico analysis of citcol peptides revealed a high sequence similarity to trypsin inhibitor peptides from Cucumis sativus, Momordica cochinchinensis, Momordica macrophylla and Momordica sphaeroidea. Using genome/transcriptome mining it was possible to identify precursor sequences of this peptide family in related Cucurbitaceae species that cluster into trypsin inhibitor and antimicrobial peptides. Based on our analysis, the presence or absence of a crucial Arg/Lys residue at the putative P1 position may be used to classify these common cysteine-rich peptides by functional properties. Despite sequence homology and the common classification into the inhibitor cysteine knot family, these peptides appear to have diverse and additional bioactivities yet to be revealed. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Chemical analysis of the citcol peptidome using matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) analysis. (<b>A</b>) The mass spectrum of a representative <span class="html-italic">Citrullus colocynthis</span> C<sub>18</sub> peptide-enriched extract is illustrated in the range of <span class="html-italic">m/z</span> 3500–4600 (black trace). Each black dotted arrow indicated by numbers (#) represents a cysteine-rich peptide (refer to Table in C). (<b>B</b>) Chemical modification of cysteine residues was performed by reduction and alkylation. A representative spectrum after S-carbamidomethylation is illustrated in green. The mass shift of Δ348 Da indicates the presence of six cysteine residues. For instance, the peptide signal at <span class="html-italic">m/z</span> 3734.2 shifts by 348.1 Da to <span class="html-italic">m/z</span> 4082.3. (<b>C</b>) List of monoisotopic mass signals [M + H]<sup>+</sup> of citcol peptides before and after S-carbamidomethylation.</p>
Full article ">Figure 2
<p>Fractionation and purification of cysteine-rich citcol peptides by reversed-phase HPLC. (<b>A</b>) Purification chromatogram by preparative RP-HPLC; the dashed line indicates the elution region of citcol peptides. (<b>B</b>) Semi-preparative RP-HPLC of the elution region of citcol peptides (retention time 47-60 min) indicating peaks for citcol-1 to -8. (<b>C</b>) Analytical RP-HPLC chromatogram of citcol-2 (purity ~95%). (<b>D</b>) Molecular weight analysis of citcol-2 corresponding to a monoisotopic mass [M + H]<sup>+</sup> of 3734.1 Da. For HPLC analysis linear gradients of solvent C (90% acetonitrile, 9.92% H<sub>2</sub>O and 0.08% TFA) were used at flow rates of 8, 3 and 0.3 mL/min for preparative, semi-preparative and analytical RP-HPLC, respectively.</p>
Full article ">Figure 3
<p>De novo sequencing of citcol-2 by MALDI-TOF/TOF. (<b>A</b>) Schematic structure and full sequence of citcol-2; scissors on the inside of the circle indicates potential trypsin cleavage sites and scissors on the outside indicate potential chymotrypsin cleavage sites. MS spectrum of citcol-2 after partial digestion with chymotrypsin (<b>B</b>) and trypsin (<b>C</b>). MS/MS fragmentation spectra of precursor peptides with a molecular weight of 3279.2 Da (<b>D</b>) and 822.4 Da (<b>E</b>) after tryptic digestion, and 1858.6 Da (<b>F</b>) and 1723.8 Da (<b>G</b>) after chymotrypsin digestion, which covers the entire sequence of citcol-2. The amino acid sequence was determined by assembly of digested fragments and assignment of N-terminal b- and C-terminal y-ions series. Complete tryptic digestion was used to distinguish between isobaric amino acids Gln/Lys and complete chymotrypsin for Leu/Ile. Comparison of the sequences of the fragments produced by these two enzymes showed the correct order of the fragments. The <span class="html-italic">m/z</span> value list of each of the precursor masses used for de novo sequencing are shown in <a href="#app1-biomolecules-10-01326" class="html-app">Figure S1</a>, where A, B, C and D correspond to precursors with a molecular weight of 3279.2 Da, 822.4 Da, 1723.8 Da and 1858.6 Da, respectively.</p>
Full article ">Figure 4
<p>Homology and phylogenetic distribution of citcol peptides. (<b>A</b>) Maximum-likelihood phylogenetic tree calculated with sequences found by blastp searches against six-frame translated genomes/transcriptomes (E-value ≤ 0.1). The antimicrobial branch is colored in orange and the trypsin inhibitory branch is colored in black. The sequences are encoded by numbers (Data 2), and the Cucurbitaceae subfamilies summarized with one color (Cucurbita—green, Cucumis—light blue, Luffa—dark blue, Lagenaria—dark purple, Momordica—violet, Others—white). (<b>B</b>) Alignment of frequency logos calculated with citcol-1 to -8, sequences from the squash antimicrobial peptides branch and the squash trypsin inhibitor branch (see Materials and Methods for details). Cysteines are colored in yellow, amino acids with positively charged side chains (at pH 7) are colored in blue (H, K, R) and with negative charged sidechains (at pH 7) are colored in red (D, E). Gaps ‘-’ were introduced to maximize the alignment.</p>
Full article ">
26 pages, 5039 KiB  
Article
Regulation of Poly(ADP-Ribose) Polymerase 1 Activity by Y-Box-Binding Protein 1
by Konstantin N. Naumenko, Mariya V. Sukhanova, Loic Hamon, Tatyana A. Kurgina, Elizaveta E. Alemasova, Mikhail M. Kutuzov, David Pastré and Olga I. Lavrik
Biomolecules 2020, 10(9), 1325; https://doi.org/10.3390/biom10091325 - 16 Sep 2020
Cited by 20 | Viewed by 3329
Abstract
Y-box-binding protein 1 (YB-1) is a multifunctional positively charged protein that interacts with DNA or RNA and poly(ADP-ribose) (PAR). YB-1 is poly(ADP-ribosyl)ated and stimulates poly(ADP-ribose) polymerase 1 (PARP1) activity. Here, we studied the mechanism of YB-1-dependent PAR synthesis by PARP1 in vitro using [...] Read more.
Y-box-binding protein 1 (YB-1) is a multifunctional positively charged protein that interacts with DNA or RNA and poly(ADP-ribose) (PAR). YB-1 is poly(ADP-ribosyl)ated and stimulates poly(ADP-ribose) polymerase 1 (PARP1) activity. Here, we studied the mechanism of YB-1-dependent PAR synthesis by PARP1 in vitro using biochemical and atomic force microscopy assays. PAR synthesis activity of PARP1 is known to be facilitated by co-factors such as Mg2+. However, in contrast to an Mg2+-dependent reaction, the activation of PARP1 by YB-1 is accompanied by overall up-regulation of protein PARylation and shortening of the PAR polymer. Therefore, YB-1 and cation co-factors stimulated PAR synthesis in divergent ways. PARP1 autoPARylation in the presence of YB-1 as well as trans-PARylation of YB-1 are greatly affected by the type of damaged DNA, suggesting that PARP1 activation depends on the formation of a PARP1–YB-1–DNA ternary complex. An unstructured C-terminal part of YB-1 involved in an interaction with PAR behaves similarly to full-length YB-1, indicating that both DNA and PAR binding are involved in the stimulation of PARP1 activity by YB-1. Thus, YB-1 is likely linked to the regulation of PARylation events in cells via an interaction with PAR and damaged DNA. Full article
(This article belongs to the Special Issue DNA Damage Response)
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>Y-box-binding protein 1 (YB-1) stimulates mono(ADP-ribosyl)ation (MARylation) activity of the poly(ADP-ribose) polymerase 1 (PARP1)(E988K) mutant. Evaluation of protein MARylation in the presence of [<sup>32</sup>P]NAD and DNA duplexes containing a nick by SDS-polyacrylamide gel electrophoresis (PAGE) with subsequent phosphor imaging. The reaction mixtures contained 100–500 nM PARP1(E988K), 100 nM DNA substrate 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD<sup>+</sup> (0.4 μCi), and 1600 nM YB-1, as indicated.</p>
Full article ">Figure 2
<p>YB-1 stimulates PARP1 activity in the presence of different types of <span class="html-italic">DNA</span> damage. (<b>a</b>) Protein PARylation in the presence of DNA duplexes and [<sup>32</sup>P]NAD according to SDS-PAGE with phosphor imaging. The reaction mixtures contained 100 nM PARP1, 100 nM DNA substrate 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi), and 1600 nM YB-1, as indicated. (<b>b</b>) Quantification of PARP1 activity. PARP1 at 100 nM was incubated with 100 nM DNA substrate, and 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi) in the presence of 1600 nM YB-1, as indicated; <sup>32</sup>P-PAR–modified proteins were trichloroacetic acid (TCA)-precipitated and counted. The relative level of PAR synthesis was normalized to the level of PAR synthesis catalyzed by PARP1 alone for 15 min with ss32 DNA substrate. The experiments were conducted at least three times; the histogram shows the means ± SD of three independent experiments.</p>
Full article ">Figure 3
<p>The C-terminal fragment of YB-1 is sufficient to stimulate PARP1 activity. (<b>a</b>) Schematic view of the YB-1 constructs employed in this study. (<b>b</b>) Quantification of PARP1 activity. PARP1 (100 nM) was incubated with 100 nM DNA substrate, and 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi) in the presence of 1600 nM YB-1 or its mutant (where indicated). <sup>32</sup>P-PAR–modified proteins were TCA-precipitated and counted. The relative level of PAR synthesis was normalized to the level of PAR synthesis catalyzed by PARP1 alone for 15 min with dumbbell DNA substrate. The experiments were performed at least three times; the histogram presents the means ± SD of three independent experiments. (<b>c</b>) Protein PARylation in the presence of DNA duplexes and [<sup>32</sup>P]NAD according to SDS-PAGE and phosphor imaging. The reaction mixtures contained 100 nM PARP1, 1600 nM YB-1 or its mutant (where indicated), 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi), and 100 nM DNA substrate. AP-CSD, alanine/proline-rich N-terminal domain and the cold shock domain.</p>
Full article ">Figure 4
<p>YB-1 stimulates PARP1 upon activation by a mononucleosome. (<b>a</b>) Quantification of PARP1 activity. PARP1 at 100 nM was incubated with 100 nM substrate and 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi) in the presence of 1600 nM YB-1 (where indicated). <sup>32</sup>P-PAR–modified proteins were TCA-precipitated and counted. The relative level of PAR synthesis was normalized to the level of PAR synthesis catalyzed by PARP1 alone for 60 min with 147 bp DNA. The experiments were conducted at least three times; the histogram shows the means ± SD of three independent experiments. (<b>b</b>) Assessment of the protein PARylation in the presence of 147 bp DNA or mononucleosome substrates and 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi) [<sup>32</sup>P]NAD<sup>+</sup> by SDS-PAGE and phosphor imaging. The reaction mixtures contained 100 nM PARP1, 1600 nM YB-1 (where indicated), and 100 nM substrate.</p>
Full article ">Figure 5
<p>YB-1 modulates the dissociation of the autoPARylated PARP1 from 147 bp DNA substrates and mononucleosomes. (<b>a</b>) Comparative analysis of dissociation curves of the protein–DNA complex after protein PARylation in the presence of a 147 bp DNA substrate. The reaction mixtures contained 100 nM PARP1, 4 μM NAD<sup>+</sup>, 1600 nM YB-1 (where indicated), and 100 nM undamaged or damaged 147 bp DNA (gap). (<b>b</b>) Comparative analysis of dissociation curves of the protein–DNA complex after protein PARylation in the presence of a mononucleosome substrate. The reaction mixtures contained 100 nM PARP1, 4 μM NAD<sup>+</sup>, 1600 nM YB-1 (where indicated), and 100 nM undamaged or damaged mononucleosome (gap).</p>
Full article ">Figure 6
<p>A comparison of the effects of cations, histones, and YB-1 on PARP1 activity. (<b>a</b>) Protein PARylation in the presence of different co-factors and [<sup>32</sup>P]NAD according to SDS-PAGE with subsequent phosphor imaging. The reaction mixtures contained 100 nM PARP1, 0.5 OD<sub>260</sub>/mL activated DNA, 10 mM EDTA, 5 mM Mg<sup>2+</sup>, 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi), 1600 nM YB-1, 2 mM spermine<sup>3+</sup>, and 0.054 mg/mL mixture of core histones (H2A, H2B, H3, and H4) or recombinant histone H1, as indicated. (<b>b</b>) Quantification of PARP1 activity. PARP1 at 100 nM was incubated with 0.5 OD<sub>260</sub>/mL activated DNA, 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi) in the presence of 5 mM Mg<sup>2+</sup>, 1600 nM YB-1, 2 mM spermine<sup>3+</sup>, and 0.054 mg/mL mixture [of either core histones (H2A, H2B, H3, and H4) or recombinant histone H1] or 10 mM EDTA, as indicated. <sup>32</sup>P-PAR–modified proteins were TCA-precipitated and counted. The relative level of PAR synthesis was normalized to the level of PAR synthesis catalyzed by PARP1 alone for 15 min in the presence of EDTA. The experiments were conducted at least three times; the histogram presents the means ± SD of three independent experiments.</p>
Full article ">Figure 7
<p>YB-1 stimulates PARP1 activity in the presence of damaged plasmid DNA. (<b>a</b>) Protein PARylation in the presence of damaged plasmid DNA and [<sup>32</sup>P]NAD according to SDS-PAGE and phosphor imaging. The reaction mixtures contained 30 nM PARP1, 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi) 560 nM YB-1, 3 nM plasmid DNA, and 10 mM EDTA or 5 mM MgCl<sub>2</sub>, as indicated. (<b>b</b>) Quantification of PARP1 activity. PARP1 (30 nM) was incubated with 3 nM plasmid DNA, 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi) in the presence of 560 nM YB-1, and either 10 mM EDTA or 5 mM MgCl<sub>2</sub>, as indicated. <sup>32</sup>P-PAR–modified proteins were TCA-precipitated and counted. The relative level of PAR synthesis was normalized to the level of PAR synthesis catalyzed by PARP1 alone for 60 min without co-factors. The experiments were performed at least three times; the histogram shows the means ± SD of three independent experiments.</p>
Full article ">Figure 8
<p>Atomic force microscopy (AFM) images of PARylated PARP1 in the presence of different co-factors. The images illustrate auto-PARylation of PARP1 in the presence of Mg<sup>2+</sup> (<b>a</b>), in the presence of Mg<sup>2+</sup> and YB-1 (<b>b</b>), without co-factors (<b>c</b>), or in the presence of YB-1 (<b>d</b>). Upper panel: AFM images of PARylated PARP1. White arrows indicate plasmid DNA molecules, and red arrows point to PARylated proteins. Scale bar: 300 nm; Z scale: 5 nm. Lower panel: zoomed-in images of PARylated PARP1. The two radii of the ellipse enclosing PARylated PARP1 were used to estimate the area of a modified protein molecule. Scale bar: 116 nm; Z scale: 5 nm.</p>
Full article ">Figure 9
<p>AFM-based analysis of PARylated PARP1 revealing molecular size distributions in the presence of Mg<sup>2+</sup> (<b>a</b>), in the presence of Mg<sup>2+</sup> and YB-1 (<b>a</b>), without Mg<sup>2+</sup> (<b>b</b>), or in the presence of YB-1 without Mg<sup>2+</sup> (<b>b</b>). The percentage histograms present the percentage of PARylated molecules in each size range in the presence of Mg<sup>2+</sup>, in the presence of Mg<sup>2+</sup> plus YB-1, without co-factors, or in the presence of YB-1. Numbers of PARylated molecules analysed: 91 in the Mg<sup>2+</sup> group, 81 in group ‘Mg<sup>2+</sup> and YB-1′, 133 in the group without co-factors, and 145 in the YB-1 group. An ellipse with the smallest area whose centre coincided with the centre of a PARylated molecule and completely enclosed it was chosen to estimate the area of the molecules. The sizes of PARylated PARP1 smaller than 600 nm<sup>2</sup> were disregarded. (<b>c</b>) The average size of PARylated PARP1 measured in images shown in (<b>a</b>,<b>b</b>). Results are mean ± SD of two to five images of three independent samples for each assay group. <span class="html-italic">p</span>-values were obtained by comparing the results by Student’s t-test, *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 10
<p>AFM-based analysis of PARylated PARP1 showing the molecular size distributions in the presence of the AP-CSD fragment. (<b>a</b>) AFM images show auto-PARylation of PARP1 in the presence of Mg<sup>2+</sup>, in the presence of Mg<sup>2+</sup> and AP-CSD, without co-factors, and in the presence of AP-CSD. White arrows indicate plasmid DNA molecules and red arrows indicate PARylated proteins. Scale bar: 500 nm; Z scale: 5 nm. (<b>b</b>,<b>c</b>) The percentage histograms showing the percentage of PARylated molecules in each size range in the presence of Mg<sup>2+</sup> (<b>c</b>), in the presence of Mg<sup>2+</sup> and AP-CSD fragment (<b>c</b>), without co-factors (<b>b</b>), and in the presence of AP-CSD fragment (<b>b</b>). Number of PARylated molecules analyzed: 89 for Mg<sup>2+</sup>, 84 for Mg<sup>2+</sup> and AP-CSD fragment, 82 for without co-factors, and 93 for AP-CSD fragments. The area of minimum ellipse enclosing the PARylated protein was used to estimate the area of PARylated proteins. The size of PARylated PARP1 smaller than 600 nm<sup>2</sup> was not taken into account. (<b>d</b>) The average size of PARylated PARP1 measured in images shown in (<b>a</b>). Results are mean ± SD of two to five images of three independent samples for each assay group. <span class="html-italic">p</span>-values were obtained by comparing the results by Student’s <span class="html-italic">t</span>-test, ns, not significant.</p>
Full article ">Figure 11
<p>YB-1 affects the PARylation reactions catalysed by proteins of nuclear extracts from HeLa cells. (<b>a</b>,<b>b</b>) Protein PARylation in the presence of HeLa nuclear extracts and [<sup>32</sup>P]NAD according to SDS-PAGE and phosphor imaging. The reaction mixtures consisted of 1.0 mg/mL nuclear extract proteins, 0.25 OD<sub>260</sub>/mL activated DNA, 5 mM MgCl<sub>2</sub>, 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi), 1600 nM YB-1 (<b>b</b>), and either 1 µM PARG inhibitor ((<b>a</b>,<b>b</b>), lanes 1–4) or no such inhibitor ((<b>a</b>,<b>b</b>) lanes 5–8), as indicated in the figure. The arrow points to the border between the concentrating and separating gel. (<b>c</b>) The efficiency of PAR synthesis in the nuclear extracts of HeLa cells in the presence of exogenous YB-1. Nuclear extract proteins (1.0 mg/mL) were incubated with 0.25 OD<sub>260</sub>/mL activated DNA, 5 mM MgCl<sub>2</sub>, 4 μM NAD<sup>+</sup> and [<sup>32</sup>P]NAD (0.4 μCi), 1600 nM YB-1, and 1 µM PARG inhibitor (PARGi), as indicated in the figure. <sup>32</sup>P-PAR–modified proteins were TCA-precipitated and counted. The relative level of PAR synthesis was normalized to the level of PAR synthesis catalyzed by cell extracts for 10 min in the absence of PARGi. The experiments were conducted at least three times; the histogram shows the means ± SD of three independent experiments.</p>
Full article ">Figure 12
<p>A simplified model of YB-1-dependent mechanisms of PARP1 activity regulation. (<b>a</b>) Formation of the heteromeric complex of PARP1–YB-1 with damaged DNA. In the ternary complex, YB-1 is a preferable PAR acceptor, but auto-modification of PARP1 occurs too. (<b>b</b>) Formation of the complex of YB-1 with PAR covalently attached to PARP1. As soon as the PAR chains on PARP1 reach a certain length, predominant formation of YB-1–PAR rather than YB-1–DNA–PARP1 complexes takes place. (<b>c</b>) Upon binding to PAR, YB-1 promotes the formation of shortened PAR during PARP1 auto-PARylation. YB-1 non-covalently binds to PAR chains of auto-PARylated PARP1 and relocates into spatial proximity of the catalytic centre of PARP1. Modified YB-1 molecules dissociate from the complexes, and new unmodified YB-1 molecules bind to the PAR molecule on PARP1.</p>
Full article ">
18 pages, 510 KiB  
Review
Inflammation in Obesity-Related Complications in Children: The Protective Effect of Diet and Its Potential Role as a Therapeutic Agent
by Valeria Calcaterra, Corrado Regalbuto, Debora Porri, Gloria Pelizzo, Emanuela Mazzon, Federica Vinci, Gianvincenzo Zuccotti, Valentina Fabiano and Hellas Cena
Biomolecules 2020, 10(9), 1324; https://doi.org/10.3390/biom10091324 - 16 Sep 2020
Cited by 46 | Viewed by 5392
Abstract
Obesity is a growing health problem in both children and adults, impairing physical and mental state and impacting health care system costs in both developed and developing countries. It is well-known that individuals with excessive weight gain frequently develop obesity-related complications, which are [...] Read more.
Obesity is a growing health problem in both children and adults, impairing physical and mental state and impacting health care system costs in both developed and developing countries. It is well-known that individuals with excessive weight gain frequently develop obesity-related complications, which are mainly known as Non-Communicable Diseases (NCDs), including cardiovascular disease, type 2 diabetes mellitus, metabolic syndrome, non-alcoholic fatty liver disease, hypertension, hyperlipidemia and many other risk factors proven to be associated with chronic inflammation, causing disability and reduced life expectancy. This review aims to present and discuss complications related to inflammation in pediatric obesity, the critical role of nutrition and diet in obesity-comorbidity prevention and treatment, and the impact of lifestyle. Appropriate early dietary intervention for the management of pediatric overweight and obesity is recommended for overall healthy growth and prevention of comorbidities in adulthood. Full article
Show Figures

Figure 1

Figure 1
<p>Pro-inflammatory and anti-inflammatory effects of diet in children.</p>
Full article ">
Previous Issue
Next Issue
Back to TopTop