[go: up one dir, main page]
Next Issue
Volume 24, October-1
Previous Issue
Volume 24, September-1
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
8.1
4.9
Journals
IJMS
Volume 24
Issue 18
ijms-logo

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Int. J. Mol. Sci., Volume 24, Issue 18 (September-2 2023) – 738 articles

Cover Story (view full-size image): The structures of histone complexes are master keys to epigenetics. A new protocol, PepGrow, has been introduced for the construction of histone complexes at atomic resolution. The docked histone fragments are used as seeds and the full peptide tails are grown in the binding pocket of the targeted reader proteins. The new protocol combines the advantages of popular program packages such as AutoDock and Modeller, allowing fast generation of complex structures. PepGrow handles the current challenges of structure determination of complexes of flexible and weakly bound peptide tails of histones. 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
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
26 pages, 3886 KiB  
Review
LOXL2 in Cancer: A Two-Decade Perspective
by Amparo Cano, Pilar Eraso, María J. Mazón and Francisco Portillo
Int. J. Mol. Sci. 2023, 24(18), 14405; https://doi.org/10.3390/ijms241814405 - 21 Sep 2023
Cited by 4 | Viewed by 2817
Abstract
Lysyl Oxidase Like 2 (LOXL2) belongs to the lysyl oxidase (LOX) family, which comprises five lysine tyrosylquinone (LTQ)-dependent copper amine oxidases in humans. In 2003, LOXL2 was first identified as a promoter of tumour progression and, over the course of two decades, numerous [...] Read more.
Lysyl Oxidase Like 2 (LOXL2) belongs to the lysyl oxidase (LOX) family, which comprises five lysine tyrosylquinone (LTQ)-dependent copper amine oxidases in humans. In 2003, LOXL2 was first identified as a promoter of tumour progression and, over the course of two decades, numerous studies have firmly established its involvement in multiple cancers. Extensive research with large cohorts of human tumour samples has demonstrated that dysregulated LOXL2 expression is strongly associated with poor prognosis in patients. Moreover, investigations have revealed the association of LOXL2 with various targets affecting diverse aspects of tumour progression. Additionally, the discovery of a complex network of signalling factors acting at the transcriptional, post-transcriptional, and post-translational levels has provided insights into the mechanisms underlying the aberrant expression of LOXL2 in tumours. Furthermore, the development of genetically modified mouse models with silenced or overexpressed LOXL2 has enabled in-depth exploration of its in vivo role in various cancer models. Given the significant role of LOXL2 in numerous cancers, extensive efforts are underway to identify specific inhibitors that could potentially improve patient prognosis. In this review, we aim to provide a comprehensive overview of two decades of research on the role of LOXL2 in cancer. Full article
(This article belongs to the Special Issue Cell Biology and Functions of the Multifunctional Lysyl Oxidase Family of Proteins 2.0)
►▼ Show Figures

Figure 1

Figure 1
<p>Frequency of gene copy alterations detected in <span class="html-italic">LOXL2</span> locus among all tumour types. Red bars (<b>left</b>) correspond to the frequency of gene amplification and green bars (<b>right</b>) to deep deletions.</p> Full article ">Figure 2
<p>Frequency of point mutations detected in <span class="html-italic">LOXL2</span> gene among all tumour types.</p> Full article ">Figure 3
<p>LOXL2 regulation. Left side, <span class="html-italic">LOXL2</span> gene expression is regulated in different cancer scenarios by three well characterised signalling pathways (extracellular ATP, hypoxia, and ECM remodelling) that impinge on different transcriptional factors, including HIF1α, HIF1β, HIF2α, and lysine demethylases KDM4B and KDM4C. The proto-oncogene c-FOS controls <span class="html-italic">LOXL2</span> expression through the Wnt7/9-ZEB1/2 axis. Deubiquitinase ZRANB1 stabilises the transcription factor SP1. Right bottom cytoplasm side, several miRNAs act through the <span class="html-italic">LOXL2</span> 3’UTR mRNA region to downregulate its gene expression. Long noncoding RNAs (lncRNA) and circular RNAs (circRNA) counteracting the miRNAs (green boxes) are marked in grey. Right upper cytoplasm side, LOXL2 is directed to the ubiquitin–proteasome pathway by the interaction with TRIM44. LOXL2 is phosphorylated by LAST1 with unknown functional consequences. Upper right side, LOXL2 in the extracellular compartment undergoes proteolytic processing by PACE4 and factor Xa proteases, and secreted EGFL7 inhibits LOXL2 catalytic activity. Extracellular LOXL2 also interacts with HSP90, although the functional consequences of this interaction are unknown. Nuclear LOXL2 is negatively regulated by the lncRNA GATA6-AS. The question mark (?) means that the functional consequences of LOXL2 phosphorylation are unknown.</p> Full article ">Figure 4
<p>Targets of secreted LOXL2. LOXL2 provokes ECM remodelling, activating the FAK signalling pathway in fibroblasts and tumour cells. Additionally, it stimulates the AKT and ERK signalling pathways specifically in tumour cells. LOXL2 oxidises PDGFRβ, enhancing ERK signalling in fibroblasts, and increases the secretion of lymphangiogenic factors (VEGFC and SDF-1α). In distant organs, secreted or exosomal LOXL2 stimulates the formation of premetastatic niche.</p> Full article ">Figure 5
<p>Intracellular targets of LOXL2. LOXL2 can influence numerous pro-tumorigenic actions in different tumour contexts by interacting with various effectors located in the plasma membrane (i.e., ERBB2 receptor and ITGA5/ITGB1 integrins) or the cytoplasm (FAK, ezrin, VIM, AKT, MARKSL1, ERK1/2, IQGAP1, and ALDOA), thereby affecting diverse cellular processes. The interaction of LOXL2 and HSPA5/BiP in the ER leads to activation of the transcription factor XBP1, which upregulates several EMT-TFs. Red arrows indicate positive regulation, and red blunt-end arrows signify negative regulation exerted by LOXL2 on the indicated targets. The final functional processes altered by LOXL2 action are marked in grey.</p> Full article ">Figure 6
<p>Nuclear targets of LOXL2. In different tumour scenarios, nuclear LOXL2 exerts its pro-tumorigenic roles by interacting with various transcription factors (SNAI1, E47, KLF4 and GATA6), modifying histone marks (H3K4me3 and H3K36ac), and upregulating the expression of different effectors (HIF1, SMO/GLI, and RAMP3). The downregulation of cell polarity complex genes (LLGL2, CLDN1) and upregulation of antiapoptotic genes (BIRC3 and MDM2) are mediated by unknown transcription factors. Red arrows denote positive regulation and red blunt-end arrows signify negative regulation exerted by LOXL2 on the indicated targets. Final functional processes altered by LOXL2 action are marked in grey. The question mark (?) means that the direct LOXL2 target or the functional consequences of an LOXL2 action are unknown.</p> Full article ">Figure 7
<p>Strategies used to block LOXL2 action on tumour progression. The generation of anti-LOXL2 antibodies, optimisation of copper chelators, search for natural products capable of blocking the expression of LOXL2, or the development of small molecules designed to inhibit the catalytic activity of LOXL2 are different approaches currently being developed with the ultimate goal of interfering with the pro-tumorigenic action of LOXL2.</p> Full article ">
11 pages, 579 KiB  
Review
Hepatocellular Carcinoma Prevention in the Era of Hepatitis C Elimination
by Jeffrey V. Lazarus, Camila A. Picchio and Massimo Colombo
Int. J. Mol. Sci. 2023, 24(18), 14404; https://doi.org/10.3390/ijms241814404 - 21 Sep 2023
Cited by 6 | Viewed by 2151
Abstract
The hepatitis C virus (HCV), a single-stranded RNA virus belonging to the Flaviviridae family, is a major cause of hepatocellular carcinoma (HCC) worldwide. Tumors caused by HCC have an increased mortality rate globally, which is more accentuated in Western countries. The carcinogenic potential [...] Read more.
The hepatitis C virus (HCV), a single-stranded RNA virus belonging to the Flaviviridae family, is a major cause of hepatocellular carcinoma (HCC) worldwide. Tumors caused by HCC have an increased mortality rate globally, which is more accentuated in Western countries. The carcinogenic potential of this virus is mediated through a wide range of mechanisms, spanning from the induction of chronic inflammation to oxidative stress and deregulation of cellular pathways by viral proteins. As the number of new infections continues unabated, HCC-related mortality should be prioritized through early detection, continued prevention of HCV transmission, and treatment of HCV with safe and efficacious direct antiviral agents (DAAs). People who inject drugs (PWID) are a significant reservoir of new HCV infections globally, and in order to eliminate hepatitis C as a global health threat, as set out by the World Health Organization, an integrated approach based on the optimization of care delivery and increased access to harm reduction and treatment for PWID is needed. Thanks to the development of safe and effective antiviral agents, eradication of the infection is now possible in almost all treated patients, leading to a significant reduction but not the elimination of the risk for HCC in cured patients. This is particularly relevant among aged populations who have cofactors of morbidity known to accelerate HCC progression, such as diabetes, obesity, and excessive alcohol consumption. Given the restless accumulation of individuals with cured HCV infection, the implementation of risk-stratified surveillance programs becomes impellent from a cost-effectiveness perspective, whereas the availability of a performant biomarker to predict HCC in cured patients remains an unmet clinical need. Full article
(This article belongs to the Special Issue Hepatitis C Virus: Pathogenetic Mechanisms, Residual Problems after Cure and Hopes for Elimination)
►▼ Show Figures

Figure 1

Figure 1
<p>Potential application of HCC risk stratification using scoring systems [<a href="#B61-ijms-24-14404" class="html-bibr">61</a>]. Abbreviations: hepatocellular carcinoma (HCC); magnetic resonance imaging (MRI); United States (US).</p> Full article ">
22 pages, 2466 KiB  
Review
Exploring the Complex and Multifaceted Interplay between Melanoma Cells and the Tumor Microenvironment
by Magdalena Kuras
Int. J. Mol. Sci. 2023, 24(18), 14403; https://doi.org/10.3390/ijms241814403 - 21 Sep 2023
Cited by 3 | Viewed by 1819
Abstract
Malignant melanoma is a very aggressive skin cancer, characterized by a heterogeneous nature and high metastatic potential. The incidence of melanoma is continuously increasing worldwide, and it is one of the most common cancers in young adults. In the past twenty years, our [...] Read more.
Malignant melanoma is a very aggressive skin cancer, characterized by a heterogeneous nature and high metastatic potential. The incidence of melanoma is continuously increasing worldwide, and it is one of the most common cancers in young adults. In the past twenty years, our understanding of melanoma biology has increased profoundly, and disease management for patients with disseminated disease has improved due to the emergence of immunotherapy and targeted therapy. However, a significant fraction of patients relapse or do not respond adequately to treatment. This can partly be explained by the complex signaling between the tumor and its microenvironment, giving rise to melanoma phenotypes with different patterns of disease progression. This review focuses on the key aspects and complex relationship between pathogenesis, genetic abnormalities, tumor microenvironment, cellular plasticity, and metabolic reprogramming in melanoma. By acquiring a deeper understanding of the multifaceted features of melanomagenesis, we can reach a point of more individualized and patient-centered disease management and reduced costs of ineffective treatments. Full article
(This article belongs to the Special Issue Current Concepts and Advances in Diagnosis and Treatment of Cutaneous Melanoma)
►▼ Show Figures

Figure 1

Figure 1
<p>Melanin production. (1) The production of melanin, a process called melanogenesis, is activated upon UV exposure. (2) UV radiation damages the DNA in the keratinocytes, activating the TP53 pathway, which results in the production of αMSH. αMSH is secreted from the keratinocytes and binds to the MC1R on the melanocyte. (3) cAMP levels are then increased within the melanocytes, activating protein kinase A (PKA). PKA activation induces the recruitment of CRE-binding (CREB) protein and thereby the transcriptional activity of MITF. (4) MITF activates the transcription of pigment genes, including <span class="html-italic">TYR</span>, <span class="html-italic">TYRP1</span>, <span class="html-italic">DCT</span>, and <span class="html-italic">PMEL</span>, which are transported to the membrane-bound melanosome. (5) Matured melanosomes are then transferred from melanocytes to keratinocytes to protect them against UV light. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 19 September 2023).</p> Full article ">Figure 2
<p>The signaling cascades of MAPK, PI3K, and canonical WNT pathways. (<b>A</b>) The NRAS-BRAF MAPK pathway is activated by binding a growth factor (GF) or mitogen to an RTK. Upon activation, the RAS protein phosphorylates (P) MEK1/2, phosphorylating ERK1/2. ERK can then translocate to the nucleus and activate transcription factors which promote proliferation and progression through the cell cycle. NF1 hampers this cell cycle progression by converting RAS to its inactive GDP-bound form. (<b>B</b>) The activation of PI3K signaling by GTP-bound RAS. PI3K activates AKT through phosphorylation using a second messenger (PIP3 not shown). AKT is a kinase that mediates the phosphorylation of protein substrates, subsequently affecting the cell cycle and survival of the tumor cell. PTEN acts as a suppressor of this pathway by dephosphorylating PIP3, thereby blocking the activation of AKT. (<b>C</b>) The canonical WNT signaling pathway and its main effector, β-catenin (β). β-Catenin is activated upon binding a WNT ligand to the G protein-coupled receptor (GPCR), whereby it is prevented from degradation and instead accumulates in the cytoplasm. β-Catenin then relocates to the nucleus, where it acts as a co-activator of transcription of genes such as those related to EMT-like phenotype switching. Created with BioRender.com (accessed on 19 September 2023).</p> Full article ">Figure 3
<p>The immunosuppressive tumor microenvironment. The recruitment of various cells modulates the TME by the secretion of cytokines and chemokines by tumor cells and other infiltrating cells. Most cells within an immunosuppressive tumor microenvironment inhibit the activation and function of cytotoxic CD8+ T cells. (<b>A</b>) Tumor cells can induce the activity of Treg cells, tumor-associated macrophages (M2), and MDSCs by secreting growth factors such as VEGF. They also facilitate the transformation of fibroblasts into cancer-associated fibroblasts and enhance the expression of PD1 on CD8+ T cells. (<b>B</b>) Treg cells inhibit CD8+ T cells and NK cells by upregulating CTLA4 and releasing IL-10 and TGFβ. (<b>C</b>) MDSC expression of PDL1 inhibits T-cell activation by binding to PD1. Furthermore, MDSCs promote Treg cell proliferation in a TGFβ-dependent manner, boost angiogenesis in the tumor microenvironment, and contribute to the phenotypic switch in melanoma cells. In addition, MDSCs hinder CD8+ T cells by releasing arginase I and S100A8/A9 and metabolites such as ROS, NO, and iNOS. (<b>D</b>) TAMs promote regulatory DC maturation, inhibition of CD8+ T cells and NK cells, and facilitate phenotype switching in melanoma cells by IL-10 signaling. (<b>E</b>) Cancer-associated fibroblasts (CAFs) can induce immunosuppression by inhibiting CD8+ T cells. CAFs also secrete TGFβ, CXCL12, matrix metalloproteinase 2 (MMP2), and IL-6, which promote tumor proliferation and invasion. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 19 September 2023).</p> Full article ">Figure 4
<p>Phenotype switching in melanoma. Upon activation of the signaling pathways MAPK, PI3K, WNT, and TGFβ, a changed expression of specific markers leads to ECM degradation and reorganization of the cytoskeleton, which facilitates invasion and metastasis. Using single-cell approaches, it has become evident that phenotype switching is not binary but rather a multistep process in which cells transit through a series of intermediate cell states expressing combinations of epithelial and mesenchymal phenotypes. These intermediate states can simultaneously display proliferation, invasion, and stemness features. Transcriptional regulators are highlighted in italics. The red indicates the switch between E- and N-cadherin and the responsible genes CDH1 and CDH2. Melanocytic markers are highlighted in orange, and other markers are in blue. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 19 September 2023).</p> Full article ">Figure 5
<p>Melanoma phenotype switching and therapeutic tolerance. Up to six differentiation states have been identified in melanoma, each stage being distinguishable by several markers. Stages include a hyperdifferentiated/pigmented state induced by MAPKi, an MITF<sup>high</sup>/AXL<sup>low</sup> melanocytic stage, an intermediate or transitory stage, a therapy-induced starved-like stage, an MITF<sup>low</sup>/AXL<sup>high</sup>-dedifferentiated stage, and a NCSC-like MITF<sup>low</sup>/NGFR<sup>high</sup> state [<a href="#B46-ijms-24-14403" class="html-bibr">46</a>,<a href="#B81-ijms-24-14403" class="html-bibr">81</a>,<a href="#B134-ijms-24-14403" class="html-bibr">134</a>,<a href="#B137-ijms-24-14403" class="html-bibr">137</a>,<a href="#B138-ijms-24-14403" class="html-bibr">138</a>]. Characteristically, the more melanocytic stages comprise a larger proportion of activated immune cells and a “hot” tumor microenvironment—features associated with better therapy response. Conversely, the dedifferentiated and NCSC-like melanomas are absent in immune cells to a greater degree or lack activation of the immune cells. Created with <a href="http://BioRender.com" target="_blank">BioRender.com</a> (accessed on 19 September 2023).</p> Full article ">
16 pages, 5744 KiB  
Article
Knockdown of BAP31 Downregulates Galectin-3 to Inhibit the Wnt/β-Catenin Signaling Pathway to Modulate 5-FU Chemosensitivity and Cancer Stemness in Colorectal Cancer
by Jingjing Liu, Qi Zhang, Jiyu Wang, Changli Wang, Tian Lan, Tianyi Wang and Bing Wang
Int. J. Mol. Sci. 2023, 24(18), 14402; https://doi.org/10.3390/ijms241814402 - 21 Sep 2023
Cited by 3 | Viewed by 1529
Abstract
Increased stemness is causally linked to the development of chemoresistance in cancers. B-cell receptor-associated protein 31 (BAP31) has been identified to play an oncogenic role in many types of cancer. However, the role of BAP31 in 5-fluorouracil (5-FU) chemosensitivity and stemness of colorectal [...] Read more.
Increased stemness is causally linked to the development of chemoresistance in cancers. B-cell receptor-associated protein 31 (BAP31) has been identified to play an oncogenic role in many types of cancer. However, the role of BAP31 in 5-fluorouracil (5-FU) chemosensitivity and stemness of colorectal cancer (CRC) is still unknown. The aim of this study was to investigate the biological function and molecular mechanism of BAP31 in regulating 5-FU chemosensitivity and stemness. The correlation between BAP31 expression and 5-FU chemosensitivity was examined using 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide and colony formation assays. Cancer stemness was analyzed using tumor sphere formation and Western blot assays. Western blot and immunofluorescence analyses of the knockdown cell lines were performed to explore the possible mechanisms. Finally, we investigated the function of BAP31 by constructing xenograft nude mouse models in vivo. In this study, we demonstrated that BAP31 was increased in CRC cells, and knockdown of BAP31 reduced the half maximal inhibitory concentration (IC50) of 5-FU, while this effect was reversed by overexpression of BAP31. In addition, knockdown of BAP31 substantially reduced the stemness of CRC cells in vitro. Consistently, knockdown of BAP31 significantly suppressed the tumorigenicity and stemness of CRC in vivo. The functional study further suggested that knockdown of BAP31 downregulated galectin-3 to inhibit the accumulation of β-catenin, which in turn repressed the transcription of downstream target genes (c-MYC, SOX2) of the Wnt/β-catenin signaling pathway. Knockdown of BAP31 reduced stemness by inhibiting the Wnt/β-catenin signaling pathway to increase 5-FU chemosensitivity. Importantly, intrabodies against BAP31 suppressed tumor growth and enhanced the antitumor effects of 5-FU in vivo. Therefore, using intrabodies against BAP31 may be a strategy for improving the antitumor effect of 5-FU in CRC. Full article
(This article belongs to the Section Molecular Oncology)
►▼ Show Figures

Figure 1

Figure 1
<p>B-cell receptor-associated protein 31 (BAP31) is increased in colorectal cancer (CRC) cells and is associated with chemosensitivity to 5-fluorouracil (5-FU). (<b>A</b>) BAP31 levels remained low in normal tissue but were elevated in cancer tissue in a large-scale dataset analysis using GEPIA. (<b>B</b>) Western blot analysis was used to detect BAP31 expression in CRC cancer and normal cells. (<b>C</b>) Western blot analysis of the BAP31 expression in sh-NC, sh-BAP31, and sh-BAP31+Over-BAP31 cells. (<b>D</b>) MTT assay was used to measure viability of HCT116 and SW480 cells treated with different concentrations of 5-FU for 48 h. (<b>E</b>) Colony formation ability of HCT116 and SW480 cells treated with 5-FU. β-actin was used as loading control. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 2
<p>BAP31 is associated with stemness of CRC cells in vitro. (<b>A</b>) Representative images of sphere formation assay of HCT116 and SW480 cells. Scale bar, 100 μm. (<b>B</b>) Western blot was used to detect expression of BAP31, CD44, CD133, Oct4, and Nanog in HCT116 and SW480 cells. (<b>C</b>) Quantitative real-time polymerase chain reaction assay was used to detect mRNA expression of Oct4 and Nanog in HCT116 and SW480 cells. β-actin was used as loading control. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 3
<p>Knockdown of BAP31 suppresses tumorigenesis and stemness of CRC cells in vivo. (<b>A</b>) Tumors were harvested and photographed. (<b>B</b>) Growth curves of each group of tumors. The indicated numbers of HCT116 cells were inoculated into nude mice and tumor volume was measured every 3 days. (<b>C</b>) Each group of tumors was removed and weighed. (<b>D</b>) Western blot was used to detect expression of CD44, CD133, Oct4, and Nanog in mouse xenografts. (<b>E</b>) BAP31, CD44, and Nanog were evaluated by immunohistochemistry (IHC) in mouse xenografts. Scale bar, 100 μm. β-actin was used as loading control. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 4
<p>Knockdown of BAP31 downregulates galectin-3 to inhibit Wnt/β-catenin signaling pathway. (<b>A</b>) Western blot was used to detect expression of galectin-3, p-AKT/AKT, and p-GSK-3β/ GSK-3β in HCT116 and SW480 cells. (<b>B</b>) Western blot was used to detect expression of BAP31, HA, and β-catenin in indicated cancer cells transfected with galectin-3-HA. (<b>C</b>) Cytoplasm and nucleus fractions of β-catenin were analyzed by Western blot in HCT116 and SW480 cells. (<b>D</b>) Relative mRNA expression of BAP31, c-MYC, and SOX2 in HCT116 and SW480 cells. β-actin and histone H3 were used as loading control. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 5
<p>BAP31 regulates stemness through the Wnt/β-catenin signaling pathway. (<b>A</b>) Representative images of sphere formation assay of HCT116 and SW480 cells. Scale bar, 100 µm. (<b>B</b>) Western blot assay shows expression of BAP31, c-MYC, and SOX2 in HCT116 and SW480 cells treated with LiCl. (<b>C</b>) Relative mRNA expression of BAP31, c-MYC, and SOX2 in HCT116 and SW480 cells treated with LiCl. β-actin was used as loading control. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 6
<p>Knockdown of BAP31 increases chemosensitivity to 5-FU by inhibiting the Wnt/β-catenin signaling pathway. (<b>A</b>) MTT assay was used to measure the viability of indicated cells treated with 5-FU for 48 h. (<b>B</b>) Colony formation ability of indicated cells treated with 5-FU. *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 7
<p>Intrabodies against BAP31 enhance antitumor effects of 5-FU in vivo. (<b>A</b>) HCT116 cells were transfected with plasmids containing different VH antibody genes (A5, A17, G10, and G18). Western blot assay was used to detect the effect of VH intrabodies on galectin-3 and β-catenin expression. (<b>B</b>) Tumors were harvested and photographed. (<b>C</b>) Growth curves of each group of tumors. (<b>D</b>) Each group of tumors was removed and weighed. (<b>E</b>) Ki67 was evaluated by IHC in mouse xenografts; TUNEL assay of tumor tissue from different treatment groups was performed. Nuclei were stained with DAPI (blue). Scale bar, 100 μm. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 8
<p>Schematic model of knockdown of BAP31 downregulating galectin-3 to inhibit Wnt/β-catenin signaling pathway to modulate 5-FU chemosensitivity and cancer stemness in colorectal cancer.</p> Full article ">
16 pages, 2555 KiB  
Article
Biosynthesis of Bacterial Nanocellulose from Low-Cost Cellulosic Feedstocks: Effect of Microbial Producer
by Ekaterina A. Skiba, Nadezhda A. Shavyrkina, Maria A. Skiba, Galina F. Mironova and Vera V. Budaeva
Int. J. Mol. Sci. 2023, 24(18), 14401; https://doi.org/10.3390/ijms241814401 - 21 Sep 2023
Cited by 3 | Viewed by 1601
Abstract
Biodegradable bacterial nanocellulose (BNC) is a highly in-demand but expensive polymer, and the reduction of its production cost is an important task. The present study aimed to biosynthesize BNC on biologically high-quality hydrolyzate media prepared from miscanthus and oat hulls, and to explore [...] Read more.
Biodegradable bacterial nanocellulose (BNC) is a highly in-demand but expensive polymer, and the reduction of its production cost is an important task. The present study aimed to biosynthesize BNC on biologically high-quality hydrolyzate media prepared from miscanthus and oat hulls, and to explore the properties of the resultant BNC depending on the microbial producer used. In this study, three microbial producers were utilized for the biosynthesis of BNC: individual strains Komagataeibacter xylinus B-12429 and Komagataeibacter xylinus B-12431, and symbiotic Medusomyces gisevii Sa-12. The use of symbiotic Medusomyces gisevii Sa-12 was found to have technological benefits: nutrient media require no mineral salts or growth factors, and pasteurization is sufficient for the nutrient medium instead of sterilization. The yield of BNCs produced by the symbiotic culture turned out to be 44–65% higher than that for the individual strains. The physicochemical properties of BNC, such as nanofibril width, degree of polymerization, elastic modulus, Iα allomorph content and crystallinity index, are most notably dependent on the microbial producer type rather than the nutrient medium composition. This is the first study in which we investigated the biosynthesis of BNC on hydrolyzate media prepared from miscanthus and oat hulls under the same conditions but using different microbial producers, and showed that it is advisable to use the symbiotic culture. The choice of a microbial producer is grounded on the yield, production process simplification and properties. The BNC production from technical raw materials would cover considerable demands of BNC for technical purposes without competing with food resources. Full article
(This article belongs to the Special Issue Advanced Degradable Biopolymers)
►▼ Show Figures

Figure 1

Figure 1
<p>The variation in the RS concentration with time during BNC biosynthesis in miscanthus hydrolyzate medium, in oat-hull hydrolyzate medium, in control medium using of microbial producer: (<b>A</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12429; (<b>B</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12431; and (<b>C</b>)—<span class="html-italic">Medusomyces gisevii</span> Sa-12. The half-width of the confidence interval for the RS concentration was ±0.2 g/L.</p> Full article ">Figure 2
<p>The variation in pH with time during BNC biosynthesis in miscanthus hydrolyzate medium, in oat-hull hydrolyzate medium, in control medium using microbial producer: (<b>A</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12429; (<b>B</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12431; and (<b>C</b>)—<span class="html-italic">Medusomyces gisevii</span> Sa-12. The half-width of the confidence interval for pH was ±0.1.</p> Full article ">Figure 3
<p>The variation in the acetobacterial count over time during BNC biosynthesis in miscanthus hydrolyzate medium, in oat-hull hydrolyzate medium, in control medium using microbial producer: (<b>A</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12429; (<b>B</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12431; and (<b>C</b>)—<span class="html-italic">Medusomyces gisevii Sa-12.</span> The half-width of the confidence interval for the cell count was ±0.1 ln million CFU/mL.</p> Full article ">Figure 4
<p>The variation in the BNC yield with time during BNC biosynthesis in miscanthus hydrolyzate medium, in oat-hull hydrolyzate medium, in control medium using microbial producer: (<b>A</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12429; (<b>B</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12431; and (<b>C</b>)—<span class="html-italic">Medusomyces gisevii</span> Sa-12. The half-width of the confidence interval for the BNC yield was ±0.1%.</p> Full article ">Figure 5
<p>SEM images of BNC samples in 72 h of culture, ×5000 zoom: (<b>A</b>–<b>C</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12429; (<b>D</b>–<b>F</b>)—<span class="html-italic">Komagataeibacter xylinus</span> B-12431; (<b>G</b>–<b>I</b>)—<span class="html-italic">Medusomyces gisevii</span> Sa-12; (<b>A</b>,<b>D</b>,<b>G</b>)—miscanthus hydrolyzate; (<b>B</b>,<b>E</b>,<b>H</b>)—oat-hull hydrolyzate; and (<b>C</b>,<b>F</b>,<b>I</b>)—control medium.</p> Full article ">
17 pages, 2561 KiB  
Article
Physiological and Morphological Implications of Using Composts with Different Compositions in the Production of Cucumber Seedlings
by Anita Zapałowska, Natalia Matłok, Tomasz Piechowiak, Małgorzata Szostek, Czesław Puchalski and Maciej Balawejder
Int. J. Mol. Sci. 2023, 24(18), 14400; https://doi.org/10.3390/ijms241814400 - 21 Sep 2023
Cited by 2 | Viewed by 1192
Abstract
Compost has a broad application in terms of the improvement of the soil properties. This research work was conducted to present the molecular implications of using compost obtained from different substrates to improve soil parameters for cucumber seedlings cultivation. In the experiment, the [...] Read more.
Compost has a broad application in terms of the improvement of the soil properties. This research work was conducted to present the molecular implications of using compost obtained from different substrates to improve soil parameters for cucumber seedlings cultivation. In the experiment, the following compost mixtures were used: sewage sludge (80%) + sawdust (20%); sewage sludge (40%) + sawdust (10%) + biodegradable garden and park waste (50%); biodegradable garden and park waste (90%) + sawdust (10%); sewage sludge (80%) + sawdust (20%) + Eisenia fetida; sewage sludge (40%) + sawdust (10%) + biodegradable garden and park waste (50%) + Eisenia fetida; biodegradable garden and park waste (90%) + sawdust (10%) + Eisenia fetida. The final substrate compositions consisted of compost mixtures and deacidified peat(O) (pH 6.97; Corg content—55%, N content—2.3%), serving as a structural additive, in different mass ratios (mass %). The produced plants underwent biometric and physiological measurements as well as enzymatic analyses of stress markers. Based on the conducted studies, it has been found that the substrate productivity depends not only on the content of nutrient components but also on their structure, which is moderated by the proportion of peat in the substrate. The most effective and promising substrate for cucumber seedling production was variant 2 (I), which consisted of 25% compost from sewage sludge (40%) + sawdust (10%) + biodegradable garden and park waste (50%) and 75% deacidified peat. Despite the richness of the other substrates, inferior parameters of the produced seedlings were observed. The analysis of the enzymatic activity of stress markers showed that these substrates caused stress in the plants produced. The study’s results showed that this stress was caused by the presence of Eisenia fetida, which damaged the developing root system of plants in the limited volume of substrate (production containers). The adverse influence of Eisenia fetida on the plants produced could possibly be eliminated by thermal treatment of the compost, although this could lead to significant changes in composition. Full article
(This article belongs to the Section Molecular Plant Sciences)
►▼ Show Figures

Figure 1

Figure 1
<p>Surface area of cotyledons (<b>A</b>) and leaves (<b>B</b>) of ground cucumber plants (<span class="html-italic">n</span> = 20) depending on the applied substrate on the 21st day after seed sowing. Differences in the results between substrates; significant differences at the <span class="html-italic">p</span> &lt; 0.05 level; different lowercase letters indicate significant differences between substrate variants. Substrate variants: 0, 1, 2, 3, 4, 5, 6. Compost variants: I (25% compost + 75% peat), II (50% compost + 50% peat), III (75% compost + 25% peat).</p> Full article ">Figure 2
<p>Average values of mass of cotyledons (<b>A</b>) and leaves (<b>B</b>) of ground cucumber plants (<span class="html-italic">n</span> = 20) depending on the substrate on the 21st day after seed sowing. Differences in the results between the substrate; difference at significant level <span class="html-italic">p</span> &lt; 0.05; different lowercase letters indicate significant differences between substrate variants. Substrate variants: 0, 1, 2, 3, 4, 5, 6. Compost variants: I (25% compost + 75% peat), II (50% compost + 50% peat), III (75% compost + 25% peat).</p> Full article ">Figure 3
<p>Examples of cotyledons surface area and leaves of seedling cucumbers produced on control substrate (0) and substrate 2(I) on the 21st day after seed sowing. Scale (1:3).</p> Full article ">Figure 4
<p>Growth habit of seedling cucumber plants produced on control substrate (0) and substrate 2 (I), (II), (III) on the 21st day after seed sowing.</p> Full article ">Figure 5
<p>Deformations of cotyledons and leaves of seedling cucumber plants produced on substrate 6 (III), (II), (I) compared to control (0) on the 10th day after seed sowing.</p> Full article ">Figure 6
<p>The relative content of chlorophyll (SPAD) in cucumber cotyledons (<b>A</b>) and leaves (<b>B</b>) depending on the type of substrate (<span class="html-italic">n</span> = 20). Differences in the results between the substrate; difference at significant level <span class="html-italic">p</span> &lt; 0.05; different lowercase letters indicate significant differences between substrate variants. Substrate variants: 0, 1, 2, 3, 4, 5, 6. Compost variants: I (25% compost + 75% peat), II (50% compost + 50% peat), III (75% compost + 25% peat).</p> Full article ">Figure 7
<p>Maximal photochemical efficiency of PSII (F<sub>v</sub>/F<sub>m</sub>) (<b>A</b>), average values of chlorophyll fluorescence parameters (maximum quantum yield of primary photochemistry (F<sub>v</sub>/F<sub>o</sub>)) (<b>B</b>), in cucumber cotyledons depending on the type of substrate (<span class="html-italic">n</span> = 20). Differences in the results between the substrate; difference at significant level <span class="html-italic">p</span> &lt; 0.05; different lowercase letters indicate significant differences between substrate variants. Substrate variants: 0, 1, 2, 3, 4, 5, 6. Compost variants: I (25% compost + 75% peat), II (50% compost + 50% peat), III (75% compost + 25% peat).</p> Full article ">Figure 8
<p>Maximal photochemical efficiency of PSII (F<sub>v</sub>/F<sub>m</sub>) (<b>A</b>), average values of chlorophyll fluorescence parameters (maximum quantum yield of primary photochemistry (F<sub>v</sub>/F<sub>o</sub>)) (<b>B</b>), in cucumber leaves depending on the type of substrate (<span class="html-italic">n</span> = 20). Differences in the results between the substrate; difference at significant level <span class="html-italic">p</span> &lt; 0.05; different lowercase letters indicate significant differences between substrate variants. Substrate variants: 0, 1, 2, 3, 4, 5, 6. Compost variants: I (25% compost + 75% peat), II (50% compost + 50% peat), III (75% compost + 25% peat).</p> Full article ">Figure 9
<p>Catalases (CATs) (<b>A</b>), guaiacol peroxidase (GPOX) (<b>B</b>) and superoxide dismutase (SOD) (<b>C</b>) in cucumber leaves depending on the substrate (<span class="html-italic">n</span> = 20). Differences in the results between the substrates; difference at significant level <span class="html-italic">p</span> &lt; 0.05; different lowercase letters indicate significant differences between substrate variants. Substrate variants: 0, 1, 2, 3, 4, 5, 6. Compost variants: I (25% compost + 75% peat), II (50% compost + 50% peat), III (75% compost + 25% peat).</p> Full article ">
10 pages, 2048 KiB  
Article
Scopolamine-Induced Memory Impairment in Mice: Effects of PEA-OXA on Memory Retrieval and Hippocampal LTP
by Carmela Belardo, Serena Boccella, Michela Perrone, Antimo Fusco, Andrea Maria Morace, Federica Ricciardi, Roozbe Bonsale, Ines ELBini-Dhouib, Francesca Guida, Livio Luongo, Giacinto Bagetta, Damiana Scuteri and Sabatino Maione
Int. J. Mol. Sci. 2023, 24(18), 14399; https://doi.org/10.3390/ijms241814399 - 21 Sep 2023
Cited by 3 | Viewed by 1751
Abstract
Transient global amnesia, both persistent and transient, is a very common neuropsychiatric syndrome. Among animal models for amnesia and testing new drugs, the scopolamine test is the most widely used for transient global amnesia (TGA). This study examined the scopolamine-induced deficits in working [...] Read more.
Transient global amnesia, both persistent and transient, is a very common neuropsychiatric syndrome. Among animal models for amnesia and testing new drugs, the scopolamine test is the most widely used for transient global amnesia (TGA). This study examined the scopolamine-induced deficits in working memory, discriminative memory, anxiety, and motor activity in the presence of intranasal PEA-OXA, a dual antagonist of presynaptic α2 and H3 receptors. Male C57BL/6 mice were treated with intraperitoneal scopolamine (1 mg/kg) with or without pre-treatment (15 min) or post-treatment (15 min) with intranasal PEA-OXA (10 mg/kg). It was seen that scopolamine induced deficits of discriminative and spatial memory and motor deficit. These changes were associated with a loss of synaptic plasticity in the hippocampal dentate gyrus: impaired LTP after lateral entorhinal cortex/perforant pathway tetanization. Furthermore, hippocampal Ach levels were increased while ChA-T expression was reduced following scopolamine administration. PEA-OXA either prevented or restored the scopolamine-induced cognitive deficits (discriminative and spatial memory). However, the same treatment did not affect the altered motor activity or anxiety-like behavior induced by scopolamine. Consistently, electrophysiological analysis showed LTP recovery in the DG of the hippocampus, while the Ach level and ChoA-T were normalized. This study confirms the neuroprotective and pro-cognitive activity of PEA-OXA (probably through an increase in the extracellular levels of biogenic amines) in improving transient memory disorders for which the available pharmacological tools are obsolete or inadequate and not directed on specific pathophysiological targets. Full article
(This article belongs to the Special Issue Basic, Translational and Clinical Research on Dementia)
►▼ Show Figures

Figure 1

Figure 1
<p>Effects of scopolamine and the preventive or interventistic treatment with PEA-OXA in scopolamine-injected mice on cognitive performance (learning and recognition memory). (<b>A</b>,<b>B</b>) show the NOR index and images of different objects in the object recognition protocol during acquisition and a 1.5 h delay in the CTRL, scopolamine (1 mg/kg), PEA-OXA (10 mg/kg) + scopolamine (1 mg/kg), and scopolamine (1 mg/kg) + PEA-OXA (10 mg/kg) mice. Data are represented as the mean ± SEM of six mice per group. <span class="html-italic">p</span> &lt; 0.05 was considered statistically significant. ** <span class="html-italic">p</span> &lt; 0.01 vs. CTRL, °° <span class="html-italic">p</span> &lt; 0.01, and °°°° <span class="html-italic">p</span> &lt; 0.0001 vs. scopolamine (1 mg/kg). An ANOVA test was assessed and the Tukey test was used for multiple comparisons.</p> Full article ">Figure 2
<p>Effects of scopolamine and the preventive or interventistic treatment with PEA-OXA in scopolamine-injected mice on cognitive performance (spatial working and reference memory). (<b>A</b>,<b>B</b>) show the latency and time spent in the novel arm in the Y-maze forced alternation test in the CTRL, scopolamine (1 mg/kg), PEA-OXA (10 mg/kg) + scopolamine (1 mg/kg), and scopolamine (1 mg/kg) + PEA-OXA (10 mg/kg) mice. Data are represented as the mean ± SEM of six mice per group. <span class="html-italic">p</span> &lt; 0.05 was considered statistically significant. ** <span class="html-italic">p</span> &lt; 0.01 and **** <span class="html-italic">p</span> &lt; 0.0001 vs. CTRL, ° <span class="html-italic">p</span> &lt; 0.05, °°° <span class="html-italic">p</span> &lt; 0.001, and °°°° <span class="html-italic">p</span> &lt; 0.0001 vs. scopolamine (1 mg/kg). An ANOVA was assessed and the Tukey test was used for multiple comparisons.</p> Full article ">Figure 3
<p>Long-term potentiation (LTP) in the LEC-DG-pathway in the CTRL, in mice treated with scopolamine alone 15 min pre-TBS, in mice that underwent intranasal PEA-OXA treatment 15 min before scopolamine, or 15 min post-TBS. (<b>A</b>) Graphical representation of the recording electrode and stimulating electrode in the dentate gyrus and the lateral entorhinal cortex, respectively. (<b>B</b>) Representative traces recorded in the CTRL, scopolamine, PEA-OXA (10 mg/kg) + scopolamine (1 mg/kg), and scopolamine (1 mg/kg) + PEA-OXA (10 mg/kg) groups before and after TBS. (<b>C</b>,<b>D</b>) Plot of the fEPSP amplitude and slope recorded before and after the induction of LTP in the DG of the CTRL, scopolamine, PEA-OXA (10 mg/kg) + scopolamine (1 mg/kg), and scopolamine (1 mg/kg) + PEA-OXA (10 mg/kg) groups. The extent of LTP was calculated as a percentage of the baseline between 40 and 80 min of recording. (<b>E</b>,<b>F</b>) Bar graphs of LTP in the CTRL, scopolamine, PEA-OXA (10 mg/kg) + scopolamine (1 mg/kg), and scopolamine (1 mg/kg) + PEA-OXA (10 mg/kg) groups, <span class="html-italic">n</span> = 6. Two-way ANOVA followed by Tukey’s for multiple comparisons test was performed. <span class="html-italic">p</span> &lt; 0.05 was considered statistically significant. <sup>*</sup> <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and **** <span class="html-italic">p</span> &lt; 0.0001 vs. 0–15, <sup>◦</sup> <span class="html-italic">p</span> &lt; 0.05 and <sup>°°°°</sup> <span class="html-italic">p</span> &lt; 0.0001 vs. 40–80 Scopolamine (1 mg/kg), <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 and <sup>####</sup> <span class="html-italic">p</span> &lt; 0.0001 vs. 40–80 CTRL.</p> Full article ">Figure 4
<p>Effects of scopolamine and PEA-OXA therapeutic and preventive treatment. (<b>A</b>) Plasma level of achetilcoline (<b>B</b>). Plasma level of ChaT. Each histogram represents the mean ± SEM of six mice per group. <span class="html-italic">p</span> &lt; 0.05 was considered statistically significant (one-way ANOVA followed by Dunnett’s multiple comparisons test) *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001 vs. control group. °°°° <span class="html-italic">p</span> &lt; 0.0001 vs. scopolamine (1 mg/kg) group.</p> Full article ">Figure 5
<p>Experimental plan for both (<b>A</b>) therapeutic and (<b>B</b>) preventive treatment in scopolamine-injected mice.</p> Full article ">
15 pages, 3804 KiB  
Article
Transcriptome-Based WGCNA Analysis Reveals the Mechanism of Drought Resistance Differences in Sweetpotato (Ipomoea batatas (L.) Lam.)
by Jikai Zong, Peitao Chen, Qingqing Luo, Jilong Gao, Ruihua Qin, Chunli Wu, Qina Lv, Tengfei Zhao and Yufan Fu
Int. J. Mol. Sci. 2023, 24(18), 14398; https://doi.org/10.3390/ijms241814398 - 21 Sep 2023
Cited by 3 | Viewed by 2017
Abstract
Sweetpotato (Ipomoea batatas (L.) Lam.) is a globally significant storage root crop, but it is highly susceptible to yield reduction under severe drought conditions. Therefore, understanding the mechanism of sweetpotato resistance to drought stress is helpful for the creation of outstanding germplasm [...] Read more.
Sweetpotato (Ipomoea batatas (L.) Lam.) is a globally significant storage root crop, but it is highly susceptible to yield reduction under severe drought conditions. Therefore, understanding the mechanism of sweetpotato resistance to drought stress is helpful for the creation of outstanding germplasm and the selection of varieties with strong drought resistance. In this study, we conducted a comprehensive analysis of the phenotypic and physiological traits of 17 sweetpotato breeding lines and 10 varieties under drought stress through a 48 h treatment in a Hoagland culture medium containing 20% PEG6000. The results showed that the relative water content (RWC) and vine-tip fresh-weight reduction (VTFWR) in XS161819 were 1.17 and 1.14 times higher than those for the recognized drought-resistant variety Chaoshu 1. We conducted RNA-seq analysis and weighted gene co-expression network analysis (WGCNA) on two genotypes, XS161819 and 18-12-3, which exhibited significant differences in drought resistance. The transcriptome analysis revealed that the hormone signaling pathway may play a crucial role in determining the drought resistance in sweetpotato. By applying WGCNA, we identified twenty-two differential expression modules, and the midnight blue module showed a strong positive correlation with drought resistance characteristics. Moreover, twenty candidate Hub genes were identified, including g47370 (AFP2), g14296 (CDKF), and g60091 (SPBC2A9), which are potentially involved in the regulation of drought resistance in sweetpotato. These findings provide important insights into the molecular mechanisms underlying drought resistance in sweetpotato and offer valuable genetic resources for the development of drought-resistant sweetpotato varieties in the future. Full article
(This article belongs to the Special Issue Crop Stress Biology and Molecular Breeding 3.0)
►▼ Show Figures

Figure 1

Figure 1
<p>RWC, VTFWR, and R heat map, correlation analysis, and principal component analysis for 27 genotypes. (<b>a</b>) RWC, VTFWR, and R heat map of 27 sweetpotato genotypes. (<b>b</b>) Correlation analysis between RWC, VTFWR, and R. (<b>c</b>) Principal component analysis of 27 Sweetpotato genotypes. The values in Figure (<b>a</b>) are the RWC, VTFWR, and the R of vine tip from 27 sweetpotato genotypes; this refers to the heatmap of the maximum value of each column. The red box outlines the drought-resistant genotype S01 and the drought-sensitive genotype S26. In (<b>b</b>), * represents <span class="html-italic">p</span> &lt; 0.05, and ** represents <span class="html-italic">p</span> &lt; 0.01. In (<b>c</b>), the red box outlines the drought-resistant genotype S01 and the drought-sensitive genotype S26.</p> Full article ">Figure 2
<p>Physiological indicators and blade phenotypic changes in S01 and S26. (<b>a</b>) Determination of physiological indicators for drought resistance in S01 and S26. (<b>b</b>) Phenotypic changes in S01 and S26 blades under simulated drought conditions. In (<b>a</b>), * and ** indicate that the differences in the physiological index between the control group and experimental group are significant at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01, respectively.</p> Full article ">Figure 3
<p>Heat map, Venn map, and volcano map of DEGs. (<b>a</b>) Cluster analysis of DEGs. (<b>b</b>) Number of DEGs among different groups. (<b>c</b>) Volcanic maps of S01_P and S26_P, and S01_P and S01_CK. Figure (<b>a</b>) S01_P, S01 experimental group; S01_CK, S01 control group; S26_P, S26 experimental group; and S26_CK, S26 control group. Figure (<b>c</b>) NO, all the DEGs; UP, upregulated DEGs; and DOWN, downregulated DEGs.</p> Full article ">Figure 4
<p>Key gene modules and Hub genes for drought tolerance screened by WGCNA. (<b>a</b>) Cluster dendrogram of DEGs based on WGCNA analysis. (<b>b</b>) Number of genes in each module. (<b>c</b>) Correlation analysis between gene modules and traits.</p> Full article ">Figure 5
<p>Selected WGCNA-selected drought-tolerant Hub genes from midnight blue modules. (<b>a</b>) Hub genes discovered in midnight blue. (<b>b</b>) The expression level of Hub genes in RNA-seq. Figure (<b>a</b>) the red circle represents the Hub genes; the size of the circle represents the size of the betweenness centrality.</p> Full article ">Figure 6
<p>Verifying RNA-seq data through qRT-PCR. ** indicates that the differences in the gene-related expression between the control group and the experimental group are significant at <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">
20 pages, 3342 KiB  
Review
Green Hydrogen Production through Ammonia Decomposition Using Non-Thermal Plasma
by Julia Moszczyńska, Xinying Liu and Marek Wiśniewski
Int. J. Mol. Sci. 2023, 24(18), 14397; https://doi.org/10.3390/ijms241814397 - 21 Sep 2023
Cited by 3 | Viewed by 3387
Abstract
Liquid hydrogen carriers will soon play a significant role in transporting energy. The key factors that are considered when assessing the applicability of ammonia cracking in large-scale projects are as follows: high energy density, easy storage and distribution, the simplicity of the overall [...] Read more.
Liquid hydrogen carriers will soon play a significant role in transporting energy. The key factors that are considered when assessing the applicability of ammonia cracking in large-scale projects are as follows: high energy density, easy storage and distribution, the simplicity of the overall process, and a low or zero-carbon footprint. Thermal systems used for recovering H2 from ammonia require a reaction unit and catalyst that operates at a high temperature (550–800 °C) for the complete conversion of ammonia, which has a negative effect on the economics of the process. A non-thermal plasma (NTP) solution is the answer to this problem. Ammonia becomes a reliable hydrogen carrier and, in combination with NTP, offers the high conversion of the dehydrogenation process at a relatively low temperature so that zero-carbon pure hydrogen can be transported over long distances. This paper provides a critical overview of ammonia decomposition systems that focus on non-thermal methods, especially under plasma conditions. The review shows that the process has various positive aspects and is an innovative process that has only been reported to a limited extent. Full article
(This article belongs to the Special Issue Recent Advances in Plasma Application)
►▼ Show Figures

Figure 1

Figure 1
<p>Decomposition on the catalyst surface. Used with permission from [<a href="#B25-ijms-24-14397" class="html-bibr">25</a>] (Creative Commons license).</p> Full article ">Figure 2
<p>Adsorption geometry of pertinent species on CNT, Ru<sub>1</sub>@CNT, and Ru<sub>2</sub>@CNT. The C, Ru, N, and H atoms are colored gray, cyan, blue, and white, respectively. Used with permission from [<a href="#B30-ijms-24-14397" class="html-bibr">30</a>] (Copyright © 2018, American Chemical Society).</p> Full article ">Figure 3
<p>The most stable adsorption configurations of the surface of NHx (x = 0–3) and H on Fe(1 1 0), Co(1 1 1), and Ni(1 1 1). Used with permission from [<a href="#B32-ijms-24-14397" class="html-bibr">32</a>] (Copyright © 2012 Elsevier).</p> Full article ">Figure 4
<p>Most stable adsorption configurations of the NH<sub>3</sub>, NH<sub>2</sub>, NH, N, H, H<sub>2,</sub> and N<sub>2</sub> species on Mo<sub>2</sub>N(100) (<b>a</b>–<b>h</b>) and Mo<sub>2</sub>N (111) (<b>i</b>–<b>p</b>). The insets provide a side view of the corresponding adsorption configurations. “v” and “p” mean the vertical and parallel N<sub>2</sub> adsorption configurations. The lengths of (Å) of the Mo–NH<sub>x</sub> bonds and N–N bonds are given. Gray = Mo; blue = N; orange = N from NH<sub>x</sub>; white = H. Used with permission from [<a href="#B34-ijms-24-14397" class="html-bibr">34</a>] (Copyright © 2019, American Chemical Society).</p> Full article ">Figure 5
<p>States of matter.</p> Full article ">Figure 6
<p>Common DBD reactor configurations.</p> Full article ">Figure 7
<p>Diagram of the LNAD process. Used with permission from [<a href="#B83-ijms-24-14397" class="html-bibr">83</a>] (Copyright © 2014 Elsevier).</p> Full article ">Figure 8
<p>Experimental set-up for H<sub>2</sub> separation and production using a plasma membrane reactor. Used with permission from [<a href="#B86-ijms-24-14397" class="html-bibr">86</a>] Copyright © 2019 Elsevier.</p> Full article ">
17 pages, 4903 KiB  
Article
Interaction of Substrates with γ-Secretase at the Level of Individual Transmembrane Helices—A Methodological Approach
by Theresa M. Pauli, Ayse Julius, Francesco Costa, Sabine Eschrig, Judith Moosmüller, Lea Fischer, Christoph Schanzenbach, Fabian C. Schmidt, Martin Ortner and Dieter Langosch
Int. J. Mol. Sci. 2023, 24(18), 14396; https://doi.org/10.3390/ijms241814396 - 21 Sep 2023
Cited by 1 | Viewed by 1394
Abstract
Intramembrane proteases, such as γ secretase, typically recruit multiple substrates from an excess of single-span membrane proteins. It is currently unclear to which extent substrate recognition depends on specific interactions of their transmembrane domains (TMDs) with TMDs of a protease. Here, we investigated [...] Read more.
Intramembrane proteases, such as γ secretase, typically recruit multiple substrates from an excess of single-span membrane proteins. It is currently unclear to which extent substrate recognition depends on specific interactions of their transmembrane domains (TMDs) with TMDs of a protease. Here, we investigated a large number of potential pairwise interactions between TMDs of γ secretase and a diverse set of its substrates using two different configurations of BLaTM, a genetic reporter system. Our results reveal significant interactions between TMD2 of presenilin, the enzymatic subunit of γ secretase, and the TMD of the amyloid precursor protein, as well as of several other substrates. Presenilin TMD2 is a prime candidate for substrate recruitment, as has been shown from previous studies. In addition, the amyloid precursor protein TMD enters interactions with presenilin TMD 4 as well as with the TMD of nicastrin. Interestingly, the Gly-rich interfaces between the amyloid precursor protein TMD and presenilin TMDs 2 and 4 are highly similar to its homodimerization interface. In terms of methodology, the economics of the newly developed library-based method could prove to be a useful feature in related future work for identifying heterotypic TMD−TMD interactions within other biological contexts. Full article
(This article belongs to the Special Issue Structural Biology of Peptides and Proteins in Alzheimer's Disease and Related Disorders)
►▼ Show Figures

Figure 1

Figure 1
<p>Comparing both approaches used here to investigate substrate/γ secretase TMD−TMD interactions. (<b>a</b>) In Approach 1, we manually tested four substrate TMDs against most γ secretase TMDs. LD<sub>50</sub> values represent relative affinities. (<b>b</b>) In Approach 2, 28 substrate TMDs were run simultaneously against presenilin TMD2, which corresponds to the γ secretase TMD implied by other studies in substrate recognition, using a highly efficient screening technique. Sequence abundance under selective conditions is equivalent to affinity and encoded by the colors of the heatmap (yellow: lowest affinity; dark green: highest affinity). WT = wild type; NC = negative control. Soluble domains extending into the bacterial periplasmic space represent β-lactamase domains; GFP and ToxR domains pointing to the cytoplasm are annotated.</p> Full article ">Figure 2
<p>Overview of γ-secretase and substrate TMDs. (<b>a</b>) Transmembrane topologies of the γ-secretase subunits presenilin (blue), PEN-2 (yellow), nicastrin (red), APH-1 (purple), and a substrate (green). Arrows correspond to the direction of the sequences. (<b>b</b>) Top view onto the γ-secretase TMDs. The two catalytic aspartates in TMD6 and TMD7 of presenilin are represented by arrowheads and the TMDs are numbered from N- to C-terminus.</p> Full article ">Figure 3
<p>TMD−TMD interactions of PS1 with substrates and the non-substrate ITGB1. (<b>a</b>) Strength of parallel heterotypic interactions normalized to the homodimerization signal of GpA used as a reference. Three different variants of PS1 TMD2 were tested in combination with APP. (<b>b</b>) Antiparallel heterotypic interactions normalized to the homodimerization signal of EmrE. The shown data correspond to the combination of TMD frames showing the strongest interactions in any given case (see <a href="#app1-ijms-24-14396" class="html-app">Figure S2</a> A-T, where the GFP expression controls are also given). Means ± SEM, n &gt; 3. The positive and negative controls (grey bars) were included in every single round of experiments.</p> Full article ">Figure 4
<p>TMD−TMD interactions of nicastrin or PEN-2 with substrates and the non-substrate ITGB1. (<b>a</b>) Strength of parallel heterotypic interactions to the nicastrin TMD normalized to the homodimerization signal of GpA. (<b>b</b>) Strength of antiparallel heterotypic interactions to the PEN-2 TMD normalized to the homodimerization signal of EmrE TMD4. The shown data correspond to the TMD pairs showing the strongest interactions, as shown in <a href="#app1-ijms-24-14396" class="html-app">Figure S2</a>, which also contains the GFP expression controls. Means ± SEM, n &gt; 3. The positive and negative controls (grey bars) were included in every single round of experiments. The color coding given in the inset of panel (<b>b</b>) also applies to panel (<b>a</b>).</p> Full article ">Figure 5
<p>Mutational analysis of the APP TMD in its pairwise interactions with different PS1 TMDs or itself. (<b>a</b>) Strength of the interaction of APP TMD (frame 2) mutants vs. PS1 TMD4 (frame 3) normalized to the signal of wt APP TMD. Residues whose mutation reduced the signal to &lt;50% of wt are colored. (<b>b</b>) Strength of interaction of APP TMD (frame 2) mutants vs. PS1 <sup>125–146</sup>TMD2 (frame 0) normalized to the signal of wt. We note that mutant V46A more than tripled the LD<sub>50</sub> in this case, for reasons that are unclear. For technical reasons, a lower LD<sub>50</sub> limits the potential impact of mutations. (<b>c</b>) Strength of homodimerization of APP TMD (frame 2) mutants normalized to the signal of the wt APP TMD. The same residues as in (<b>a</b>) are highlighted in (<b>b</b>,<b>c</b>). (<b>d</b>) Mapping the mutation-sensitive residue positions onto a helical wheel or the NMR structure of the helix (pdb: 6hyf) model suggests that the amino acids colored in yellow or green, respectively, may correspond to two separate helix−helix interfaces formed by the APP TMD. Single, double, or triple asterisks denote statistical significance at the 0.05, 0.01, or 0.001 confidence levels (relative to wt APP). Means ± SEM, n = 4–5. The pairs used as references (dark grey bars) were included in every single round of the respective experiments.</p> Full article ">Figure 6
<p>TMD−TMD interactions of various parts of PS1 TMD2 with substrate TMDs, as identified by the BLaTM library screening approach. Candidate pairs (shown in yellow) were identified by next generation sequencing and the resulting full dataset of 1344 pairs (see <a href="#app1-ijms-24-14396" class="html-app">Figure S7</a>) was filtered for abundances exceeding 40% of the signal of GpA wt. Homotypic interactions of positive and negative controls are given by grey bars; heterotypic TMD pairs also covered by approach 1 (<a href="#ijms-24-14396-f003" class="html-fig">Figure 3</a>) are shown in dark green and orange. The TMD sequences of the pair A4_HUMAN_2|PS1_TMD2_0 (identified by approach 2) are equivalent to those of the APP | PS1_TMD2_0 pair (approach 1) (both colored in green).</p> Full article ">
20 pages, 3275 KiB  
Article
Arsenite Impairs BRCA1-Dependent DNA Double-Strand Break Repair, a Mechanism Potentially Contributing to Genomic Instability
by Tizia Matthäus, Sandra Stößer, Hatice Yasemin Seren, Vivien M. M. Haberland and Andrea Hartwig
Int. J. Mol. Sci. 2023, 24(18), 14395; https://doi.org/10.3390/ijms241814395 - 21 Sep 2023
Viewed by 1291
Abstract
BRCA1 is a key player in maintaining genomic integrity with multiple functions in DNA damage response (DDR) mechanisms. Due to its thiol-rich zinc-complexing domain, the protein may also be a potential target for redox-active and/or thiol-reactive (semi)metal compounds. The latter includes trivalent inorganic [...] Read more.
BRCA1 is a key player in maintaining genomic integrity with multiple functions in DNA damage response (DDR) mechanisms. Due to its thiol-rich zinc-complexing domain, the protein may also be a potential target for redox-active and/or thiol-reactive (semi)metal compounds. The latter includes trivalent inorganic arsenic, which is indirectly genotoxic via induction of oxidative stress and inhibition of DNA repair pathways. In the present study, we investigated the effect of NaAsO2 on the transcriptional and functional DDR. Particular attention was paid to the potential impairment of BRCA1-mediated DDR mechanisms by arsenite by comparing BRCA1-deficient and -proficient cells. At the transcriptional level, arsenite itself activated several DDR mechanisms, including a pronounced oxidative stress and DNA damage response, mostly independent of BRCA1 status. However, at the functional level, a clear BRCA1 dependency was observed in both cell cycle regulation and cell death mechanisms after arsenite exposure. Furthermore, in the absence of arsenite, the lack of functional BRCA1 impaired the largely error-free homologous recombination (HR), leading to a shift towards the error-prone non-homologous end-joining (NHEJ). Arsenic treatment also induced this shift in BRCA1-proficient cells, indicating BRCA1 inactivation. Although BRCA1 bound to DNA DSBs induced via ionizing radiation, its dissociation was impaired, similarly to the downstream proteins RAD51 and RAD54. A shift from HR to NHEJ by arsenite was further supported by corresponding reporter gene assays. Taken together, arsenite appears to negatively affect HR via functional inactivation of BRCA1, possibly by interacting with its RING finger structure, which may compromise genomic stability. Full article
(This article belongs to the Special Issue Cellular and Molecular Mechanisms of Heavy Metal Toxicity: From Death to Immortality)
►▼ Show Figures

Figure 1

Figure 1
<p>Cytotoxicity of arsenite in UWB1.289 and UWB1.289 + BRCA1 cells. Cell count (<b>A</b>) and ATP content (<b>B</b>) were determined after treatment with NaAsO<sub>2</sub>. Cells were pre-incubated with NaAsO<sub>2</sub> for 18 h, irradiated with 1 Gy, or left unirradiated and post-incubated with NaAsO<sub>2</sub> for 8 h. For the non-irradiated cells, this resulted in a total incubation time of 26 h. Shown are mean values ± standard deviations derived from three independent experiments. Statistically significant difference from the control of the respective cell line as determined using ANOVA followed by Dunnett’s T3 post hoc test: * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01.</p> Full article ">Figure 2
<p>Accumulation of arsenic in UWB1.289 and UWB1.289 + BRCA1 cells following treatment with NaAsO<sub>2</sub> for 18 h. Shown are mean values ± standard deviations derived from three independent experiments. Statistically significant difference from untreated control of the respective cell line as determined by paired, two-tailed student’s <span class="html-italic">t</span>-test: ** <span class="html-italic">p</span> ≤ 0.01.</p> Full article ">Figure 3
<p>Gene expression profiling of UWB1.289 and UWB1.289 + BRCA1 cells after treatment with NaAsO<sub>2</sub>. Cells were pre-incubated with NaAsO<sub>2</sub> for 18 h, irradiated with 1 Gy, or left unirradiated and post-incubated with NaAsO<sub>2</sub> for 8 h. This resulted in a total incubation time with arsenite of 26 h. Gene expression was determined using high-throughput RT-qPCR. Genes were classified into the clusters of metal homeostasis, oxidative stress response, apoptotic factors, and cell cycle regulators as well as DNA damage response. The log<sub>2</sub>-fold changes are derived as mean values from three independent experiments, normalized to the untreated control of the respective cell line, with the control equal to 0.</p> Full article ">Figure 4
<p>Gene expression profiling of UWB1.289 and UWB1.289 + BRCA1 cells after treatment with NaAsO<sub>2</sub>. Cells were pre-incubated with NaAsO<sub>2</sub> for 18 h, irradiated with 1 Gy, or left unirradiated and post-incubated with NaAsO<sub>2</sub> for 8 h. For the non-irradiated cells, this resulted in a total incubation time of 26 h. Gene expression was determined using high-throughput RT-qPCR. Genes were classified into the clusters of metal homeostasis, oxidative stress response, apoptotic factors, and cell cycle regulators as well as DNA damage response. The log<sub>2</sub>-fold changes are derived as mean values from three independent experiments, normalized to the untreated control of the respective cell line, with control equal to 0.</p> Full article ">Figure 5
<p>Analysis of the cell cycle distribution of UWB1.289 and UWB1.289 + BRCA1 cells after treatment with NaAsO<sub>2</sub> for 26 h. Cell cycle distribution was analyzed by DAPI staining using flow cytometry. Shown are mean values ± standard deviations derived from three independent experiments. Statistically significant difference from control as determined using ANOVA followed by Dunnett’s T post hoc test: *** <span class="html-italic">p</span> ≤ 0.001.</p> Full article ">Figure 6
<p>Immunostaining of 53BP1 in UWB1.289 and UWB1.289 + BRCA1 cells after treatment with NaAsO<sub>2</sub>. Cells were pre-incubated with NaAsO<sub>2</sub> for 18 h, irradiated with 1 Gy, and post-incubated with NaAsO<sub>2</sub> for 1 h to 8 h. Cells were stained against 53BP1 and manually counted. For each time point and treatment, foci in 40 cells of the G<sub>2</sub> phase were counted, and the foci counts of the non-irradiated samples were subtracted from those of the irradiated batch. Shown are mean values ± standard deviations derived from three independent experiments. Statistically significant difference from control as determined using ANOVA followed by Dunnett’s T post hoc test: * <span class="html-italic">p</span> ≤ 0.05, ** <span class="html-italic">p</span> ≤ 0.01; *** <span class="html-italic">p</span> ≤ 0.001.</p> Full article ">Figure 7
<p>Immunostaining of BRCA1, RAD51, and RAD54 in UWB1.289 and UWB1.289 + BRCA1 cells after treatment with NaAsO<sub>2</sub>. Cells were pre-incubated with NaAsO<sub>2</sub> for 18 h, irradiated with 1 Gy, and post-incubated with NaAsO<sub>2</sub> for 2 h to 24 h, as indicated in the respective figure. Cells were stained against BRCA1 (<b>A</b>), RAD51 (<b>B</b>), or RAD54 (<b>C</b>), respectively, and manually counted. For each time point and treatment, foci in 40 cells of the G<sub>2</sub> phase were counted, and the foci counts of the non-irradiated samples were subtracted from those of the irradiated batch. Shown are mean values ± standard deviations derived from three independent experiments. Statistically significant difference from control as determined using ANOVA followed by Dunnett’s T post hoc test: ** <span class="html-italic">p</span> ≤ 0.01, *** <span class="html-italic">p</span> ≤ 0.001.</p> Full article ">Figure 8
<p>Immunostaining of DNA-PKcs in UWB1.289 and UWB1.289 + BRCA1 cells after treatment with NaAsO<sub>2</sub>. Cells were pre-incubated with NaAsO<sub>2</sub> for 18 h, irradiated with 1 Gy, and post-incubated with NaAsO<sub>2</sub> for 2 h to 24 h. Cells were stained against DNA-PKcs and manually counted. For each time point and treatment, foci in 40 cells of the G<sub>2</sub> phase were counted, and the foci counts of the non-irradiated samples were subtracted from those of the irradiated batch. Shown are mean values ± standard deviations derived from three independent experiments. Statistically significant difference from control as determined using ANOVA followed by Dunnett’s T post hoc test: * <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01; *** <span class="html-italic">p</span> ≤ 0.001.</p> Full article ">Figure 9
<p>Impact of NaAsO<sub>2</sub> on the repair of DSB measured by U2OS reporter assay. U2OS cells were transfected with ISce-I for 6 h. After removing the transfection cocktail, the cells were incubated with NaAsO<sub>2</sub> for 66 h. Cells were subsequently trypsinized and harvested, and GFP-active cells were quantified via flow cytometry. The results are normalized to the transfected control. Shown are the mean values of three independent experiments performed in double determination ± SD. For each treatment, 50,000 events were counted. Statistical analysis between arsenite treatment and corresponding controls (** <span class="html-italic">p</span> ≤ 0.01) was performed using one-way ANOVA with post hoc Dunnett T.</p> Full article ">Figure 10
<p>Analysis of apoptotic and necrotic cells after treatment with NaAsO<sub>2</sub> for 26 h. To distinguish between necrotic, necrotic, late-apoptotic, apoptotic, and viable cells, cells were stained with Annexin V-FITC and propidium iodide (PI). Cell count was then analyzed using flow cytometry. Shown are mean values ± standard deviations derived from three independent experiments. Statistically significant difference from control as determined using ANOVA followed by Dunnett’s T post hoc test: * <span class="html-italic">p</span> ≤ 0.05; ** <span class="html-italic">p</span> ≤ 0.01; *** <span class="html-italic">p</span> ≤ 0.001.</p> Full article ">
21 pages, 28282 KiB  
Article
Comparative Analysis of Different Proteins and Metabolites in the Liver and Ovary of Local Breeds of Chicken and Commercial Chickens in the Later Laying Period
by Yuan Tang, Lingqian Yin, Li Liu, Qian Chen, Zhongzhen Lin, Donghao Zhang, Yan Wang and Yiping Liu
Int. J. Mol. Sci. 2023, 24(18), 14394; https://doi.org/10.3390/ijms241814394 - 21 Sep 2023
Viewed by 1326
Abstract
The liver and ovary perform a vital role in egg production in hens. In the later laying period, the egg-laying capacity of female hens, particularly that of local breeds, declines significantly. Hence, it is essential to study the features and conditions of the [...] Read more.
The liver and ovary perform a vital role in egg production in hens. In the later laying period, the egg-laying capacity of female hens, particularly that of local breeds, declines significantly. Hence, it is essential to study the features and conditions of the ovary and liver during this period. In this research, we characterized the proteins and metabolites in the liver and ovary of 55-week-old Guangyuan gray chickens (Group G) and Hy-Line gray chickens (Group H) by using liquid chromatography chip/electrospray ionization quadruple time-of-flight/mass spectroscopy (LC-MS/MS). In total, 139 differentially expressed proteins (DEPs) and 186 differential metabolites (DMs) were identified in the liver, and 139 DEPs and 36 DMs were identified in the ovary. The upregulated DEPs and DMs in both the liver and ovary of Group G were primarily enriched in pathways involved in amino acid and carbohydrate metabolism. This suggests that energy metabolism was highly active in the Guangyuan gray chickens. In contrast, the upregulated DEPs and DMs in Group H were mainly enriched in pathways associated with lipid metabolism, which may explain the higher egg production and the higher fatty liver rate in Hy-Line gray hens in the later laying period. Additionally, it was found that the unique protein s-(hydroxymethyl) glutathione dehydrogenase (ADH4) in Group G was implicated in functions such as fatty acid degradation, glycolysis, and pyruvate metabolism, whereas the unique proteins, steroid sulfatase (STS), glucosylceramidase (LOC107050229), and phospholipase A2 Group XV (PLA2G15), in Group H were involved in the metabolism of steroid hormones and glycerol phosphate. In conclusion, variations in how carbohydrates, lipids, and amino acids are processed in the liver and ovary of local breeds of chicken and commercial hens towards the end of their laying period could explain the disparities in their egg production abilities. Full article
(This article belongs to the Special Issue Mass Spectrometric Proteomics 2.0)
►▼ Show Figures

Figure 1

Figure 1
<p>Histological analysis of the liver and ovary in Groups G and H. (<b>A</b>) appearance of the liver from Group G. (<b>B</b>,<b>C</b>) HE result and Oil Red O result of liver staining in Group G. (<b>D</b>) appearance of the liver from Group H. (<b>E</b>,<b>F</b>) HE result and Oil Red O result of liver staining in Group H. (<b>G</b>) appearance of the ovaries from Group G. (<b>H</b>,<b>I</b>) HE result and Oil Red O result of ovary staining in Group G. (<b>J</b>) appearance of the ovaries from Group H. (<b>K</b>,<b>L</b>) HE result and Oil Red O result of ovary staining in Group H. n = 3.</p> Full article ">Figure 2
<p>Differential expression analysis of proteins in the liver and ovary between Groups G and H. (<b>A</b>,<b>B</b>) principal component analysis (PCA) of proteins in the liver and ovary. (<b>C</b>,<b>D</b>) volcano map of differentially expressed proteins (DEPs) in the liver and ovary. Upregulated DEPs were indicated by red dots, downregulated DEPs by blue dots, and proteins with no significant changes by gray dots. (<b>E</b>,<b>F</b>) hierarchical clustering analysis of DEPs in the liver and ovary. Red and blue regions indicate significantly upregulated or downregulated proteins, respectively; gray regions indicate no quantitation information.</p> Full article ">Figure 3
<p>Bar graphs of the GO annotations of the DEPs. (<b>A</b>) GO functional annotations of DEPs in the liver including biological processes (BP), cellular components (CC), and molecular functions (MF). The <span class="html-italic">y</span>-axis indicates the number of proteins. (<b>B</b>) GO functional annotations of DEPs in the ovary.</p> Full article ">Figure 4
<p>The patterns of differential metabolites (DMs) in the liver between Groups G and H were examined in the positive and negative ion modes. (<b>A</b>,<b>B</b>) PLS-DA distribution of 12 samples in the positive and negative ion modes. (<b>C</b>) the chemical classification of all liver metabolites was determined. (<b>D</b>,<b>E</b>) volcano plots displayed the DMs identified in the positive and negative ion modes. Upregulated DMs were indicated by red dots, downregulated DMs by blue dots, and metabolites with no significant changes by gray dots. (<b>F</b>,<b>G</b>) heat maps depicted correlations in the positive and negative ion modes, where red represented positive associations, blue represented negative associations, and white represented non-significant associations.</p> Full article ">Figure 5
<p>The patterns of DMs in the ovary between Groups G and H were examined in the positive and negative ion modes. (<b>A</b>,<b>B</b>) PLS-DA distribution of 12 samples in the positive and negative ion modes. (<b>C</b>) the chemical classification of all ovary metabolites was determined. (<b>D</b>,<b>E</b>) volcano plots displayed the DMs identified in the positive and negative ion modes. Upregulated DMs were indicated by red dots, downregulated DMs by blue dots, and metabolites with no significant changes by gray dots. (<b>F</b>,<b>G</b>) heat maps depicted correlations in the positive and negative ion modes, where red represented positive associations, blue represented negative associations, and white represented non-significant associations.</p> Full article ">Figure 6
<p>Comprehensive analysis of the KEGG pathways of DEPs and DMs in the liver and ovary between Groups G and H. (<b>A</b>,<b>B</b>) Sankey diagram of the KEGG pathways of DEPs and DMs in the liver of Groups G and H. (<b>C</b>,<b>D</b>) Sankey diagram of the KEGG pathways of DEPs and DMs in the ovary of Groups G and H.</p> Full article ">Figure 7
<p>Validation of blood biochemical indicators and protein expression of DEPs found in Groups G and H. (<b>A</b>) follicle stimulating hormone (FSH) levels in serum. (<b>B</b>) luteinizing hormone (LH) levels in serum. (<b>C</b>) lecithin (LEC) levels in serum. (<b>D</b>) vitellogenin (VTG) levels in serum. (<b>E</b>) very-low-density lipoprotein (VLDLy) levels in serum. (<b>F</b>) total cholesterol (TC) levels in serum. (<b>G</b>) triglyceride (TG) levels in serum. (<b>H</b>,<b>I</b>) protein expression of DEPs (ADH4 and FADS1) enriched in carbohydrate and lipid metabolic pathways in the liver. (<b>J</b>,<b>K</b>) protein levels of DEPs (STS and HMGCS1) enriched in carbohydrate and lipid metabolic pathways in the ovary. All results are presented as the mean ± SD. n = 3. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">
11 pages, 1495 KiB  
Article
Circulatory miRNAs as Correlates of Elevated Intra-Pancreatic Fat Deposition in a Mixed Ethnic Female Cohort: The TOFI_Asia Study
by Farha Ramzan, Ivana R. Sequeira-Bisson, Louise W. Lu, Cameron J. Mitchell, Randall F. D’Souza, Mark H. Vickers, Sally D. Poppitt and David Cameron-Smith
Int. J. Mol. Sci. 2023, 24(18), 14393; https://doi.org/10.3390/ijms241814393 - 21 Sep 2023
Viewed by 1624
Abstract
Ectopic lipid accumulation, including intra-pancreatic fat deposition (IPFD), exacerbates type 2 diabetes risk in susceptible individuals. Dysregulated circulating microRNAs (miRNAs) have been identified as correlating with clinical measures of pancreatitis, pancreatic cancer and type 1 diabetes. The aim of the current study was [...] Read more.
Ectopic lipid accumulation, including intra-pancreatic fat deposition (IPFD), exacerbates type 2 diabetes risk in susceptible individuals. Dysregulated circulating microRNAs (miRNAs) have been identified as correlating with clinical measures of pancreatitis, pancreatic cancer and type 1 diabetes. The aim of the current study was therefore to examine the association between circulating abundances of candidate miRNAs, IPFD and liver fat deposition as quantified using magnetic resonance imaging (MRI) and spectroscopy (MRS). Asian Chinese (n = 34; BMI = 26.7 ± 4.2 kg/m2) and European Caucasian (n = 34; BMI = 28.0 ± 4.5 kg/m2) females from the TOFI_Asia cohort underwent MRI and MRS analysis of pancreas (MR-%IPFD) and liver fat (MR-%liver fat), respectively, to quantify ectopic lipid deposition. Plasma miRNA abundances of a subset of circulatory miRNAs associated with IPFD and liver fat deposition were quantified by qRT-PCR. miR-21-3p and miR-320a-5p correlated with MR-%IPFD, plasma insulin and HOMA2-IR, but not MR-%liver fat. MR-%IPFD remained associated with decreasing miR-21-3p abundance following multivariate regression analysis. miR-21-3p and miR-320a were demonstrated to be negatively correlated with MR-%IPFD, independent of ethnicity. For miR-21-3p, this relationship persists with the inclusion of MR-%liver fat in the model, suggesting the potential for a wider application as a specific circulatory correlate of IPFD. Full article
(This article belongs to the Special Issue The Role of microRNA in Human Diseases 2.0)
►▼ Show Figures

Figure 1

Figure 1
<p>Correlation of circulatory miRNAs with IPFD percentage.</p> Full article ">Figure 2
<p>Correlation of circulatory miRNAs with the established T2DM risk markers. (<b>A</b>,<b>B</b>) Correlation plot comparing the relative abundance of miR-320a-5p and miR-21-3p with plasma insulin. (<b>C</b>,<b>D</b>) Relative abundance of miR-320a-5p and miR-21-3p with HOMA2-IR. (<b>E</b>) Relative abundance of miR-320a-5p with C-Peptide. (<b>F</b>) Relative abundance of miR-21-3p and miR-21-3p with HbA1c; r = Pearson’s coefficient with exact <span class="html-italic">p</span>-value listed. Each point represents an individual sample.</p> Full article ">Figure 3
<p>ROC curve analysis using (<b>A</b>) miR-320a-5p, miR-21-3p and miR-320a-5p + miR-21-3p (<b>B</b>) miR-320a-5p + miR-21-3p + established T2DM risk markers (FPG, insulin, HOMA-IR, HBA1c) and miR-320a-5p + miR-21-3p + established T2DM risk markers + age to evaluate the sensitivity and specificity for predicting IFPD.</p> Full article ">
9 pages, 1502 KiB  
Brief Report
Soft Tissue Manipulation Alters RANTES/CCL5 and IL-4 Cytokine Levels in a Rat Model of Chronic Low Back Pain
by Carmela L. Marciano, Taylor A. Hiland, Krista L. Jackson, Sierra Street, Carson Maris, Andrew Ehrsam, Julia M. Hum, Mary Terry Loghmani, Tien-Min G. Chu, Kyung S. Kang and Jonathan W. Lowery
Int. J. Mol. Sci. 2023, 24(18), 14392; https://doi.org/10.3390/ijms241814392 - 21 Sep 2023
Viewed by 1280
Abstract
Low back pain (LBP) is a common musculoskeletal complaint that can impede physical function and mobility. Current management often involves pain medication, but there is a need for non-pharmacological and non-invasive interventions. Soft tissue manipulation (STM), such as massage, has been shown to [...] Read more.
Low back pain (LBP) is a common musculoskeletal complaint that can impede physical function and mobility. Current management often involves pain medication, but there is a need for non-pharmacological and non-invasive interventions. Soft tissue manipulation (STM), such as massage, has been shown to be effective in human subjects, but the molecular mechanisms underlying these findings are not well understood. In this paper, we evaluated potential changes in the soft tissue levels of more than thirty pro- or anti-inflammatory cytokines following instrument-assisted STM (IASTM) in rats with chronic, induced LBP using Complete Freund’s Adjuvant. Our results indicate that IASTM is associated with reduced soft tissue levels of Regulated on Activation, Normal T cell Expressed and Secreted (RANTES)/Chemokine (C-C motif) ligand 5 (CCL5) and increased soft tissue levels of Interleukin (IL)-4, which are pro-inflammatory and anti-inflammatory factors, respectively, by 120 min post-treatment. IASTM was not associated with tissue-level changes in C-X-C Motif Chemokine Ligand (CXCL)-5/Lipopolysaccharide-Induced CXC Chemokine (LIX)–which is the murine homologue of IL-8, CXCL-7, Granulocyte-Macrophage-Colony Simulating Factor (GM-CSF), Intercellular Adhesion Molecule (ICAM)-1, IL1-Receptor Antagonist (IL-1ra), IL-6, Interferon-Inducible Protein (IP)-10/CXCL-10, L-selectin, Tumor Necrosis Factor (TNF)-α, or Vascular Endothelial Growth Factor (VEGF) at either 30 or 120 min post-treatment. Combined, our findings raise the possibility that IASTM may exert tissue-level effects associated with improved clinical outcomes and potentially beneficial changes in pro-/anti-inflammatory cytokines in circulation and at the tissue level. Full article
(This article belongs to the Special Issue Molecular Mechanisms and Therapeutic Strategies of Inflammatory Pain)
►▼ Show Figures

Figure 1

Figure 1
<p>Schematic of study design and timeline. (<b>A</b>): For samples in the present study, injury was performed on Day 0 to <span class="html-italic">n</span> = 15 rats using an injection of Complete Freund’s Adjuvant (CFA). Rats were then randomly assigned to sham (i.e., untreated) (<span class="html-italic">n</span> = 5) or instrument-assisted soft tissue manipulation (IASTM) treatment (<span class="html-italic">n</span> = 10) for intervention 3 times per week over two weeks for five minutes per session. On Day 14, IASTM treatment group was further divided into sacrifice within 30 min (<span class="html-italic">n</span> = 5) or 2 h (<span class="html-italic">n</span> = 5) post final IASTM session. (<b>B</b>): Cage controls (<span class="html-italic">n</span> = 3) were maintained without intervention.</p> Full article ">Figure 2
<p>Membrane-based arrays for levels of select targets in muscle tissue homogenates. Homogenates were generated from muscle biopsies collected from cage controls or rats subjected to injury without treatment (untreated), injury plus IASTM with biopsy collected within 30 min of final IASTM, or injury plus IASTM with biopsy collected 2 h post-IASTM. Samples were pooled within treatment conditions with representative images of array results in (<b>A</b>). The data are expressed as fold change relative to untreated injury control for RANTES (<b>B</b>), TIMP-1 (<b>C</b>), CXCL-7 (<b>D</b>), VEGF (<b>E</b>), L-selectin (<b>F</b>), IL-1ra (<b>G</b>), and ICAM-1 (<b>H</b>). For TIMP-1, the value for the cage control group is presented in text. For IL-1ra, the signal was not detected (ND) for the cage control group.</p> Full article ">Figure 3
<p>ELISAs for levels of select targets in muscle tissue homogenates. Homogenates were generated from muscle biopsies collected from cage controls or rats subjected to injury without treatment (untreated), injury plus IASTM with biopsy collected within 30 min of final IASTM, or injury plus IASTM with biopsy collected 2 h post-IASTM. Multiplex ELISAs were performed to quantify the levels of RANTES (<b>A</b>), TIMP-1 (<b>B</b>), IL-4 (<b>C</b>), GM-CSF (<b>D</b>), IL-6 (<b>E</b>), IP-10/CXCL10 (<b>F</b>), LIX (<b>G</b>), and TNF-α (<b>H</b>). <span class="html-italic">n</span> = 3 for cage controls and <span class="html-italic">n</span> = 5 for other treatment groups. The data are pg/mL (except IL-6 which is mean fluorescence intensity (MIF)) and expressed as mean ± SEM. Statistical testing was performed using a one-way ANOVA with Dunnett’s multiple comparison testing where * indicates <span class="html-italic">p</span> &lt; 0.05 against cage control and † indicates <span class="html-italic">p</span> &lt; 0.05 against untreated injury control.</p> Full article ">
18 pages, 1021 KiB  
Review
Microplastics and Kidneys: An Update on the Evidence for Deposition of Plastic Microparticles in Human Organs, Tissues and Fluids and Renal Toxicity Concern
by Edoardo La Porta, Ottavia Exacoustos, Francesca Lugani, Andrea Angeletti, Decimo Silvio Chiarenza, Carolina Bigatti, Sonia Spinelli, Xhuliana Kajana, Andrea Garbarino, Maurizio Bruschi, Giovanni Candiano, Gianluca Caridi, Nicoletta Mancianti, Marta Calatroni, Daniela Verzola, Pasquale Esposito, Francesca Viazzi, Enrico Verrina and Gian Marco Ghiggeri
Int. J. Mol. Sci. 2023, 24(18), 14391; https://doi.org/10.3390/ijms241814391 - 21 Sep 2023
Cited by 5 | Viewed by 3389
Abstract
Plastic pollution became a main challenge for human beings as demonstrated by the increasing dispersion of plastic waste into the environment. Microplastics (MPs) have become ubiquitous and humans are exposed daily to inhalation or ingestion of plastic microparticles. Recent studies performed using mainly [...] Read more.
Plastic pollution became a main challenge for human beings as demonstrated by the increasing dispersion of plastic waste into the environment. Microplastics (MPs) have become ubiquitous and humans are exposed daily to inhalation or ingestion of plastic microparticles. Recent studies performed using mainly spectroscopy or spectrometry-based techniques have shown astounding evidence for the presence of MPs in human tissues, organs and fluids. The placenta, meconium, breast milk, lung, intestine, liver, heart and cardiovascular system, blood, urine and cerebrovascular liquid are afflicted by MPs’ presence and deposition. On the whole, obtained data underline a great heterogeneity among different tissue and organs of the polymers characterized and the microparticles’ dimension, even if most of them seem to be below 50–100 µm. Evidence for the possible contribution of MPs in human diseases is still limited and this field of study in medicine is in an initial state. However, increasing studies on their toxicity in vitro and in vivo suggest worrying effects on human cells mainly mediated by oxidative stress, inflammation and fibrosis. Nephrological studies are insufficient and evidence for the presence of MPs in human kidneys is still lacking, but the little evidence present in the literature has demonstrated histological and functional alteration of kidneys in animal models and cytotoxicity through apoptosis, autophagy, oxidative stress and inflammation in kidney cells. Overall, the manuscript we report in this review recommends urgent further study to analyze potential correlations between kidney disease and MPs’ exposure in human. Full article
(This article belongs to the Collection Feature Papers in Molecular Pathology, Diagnostics, and Therapeutics)
►▼ Show Figures

Figure 1

Figure 1
<p>Leading steps for identification and characterization of MPs in human samples.</p> Full article ">Figure 2
<p>Graphical representation of main findings of MPs in human organ, tissues and fluids.</p> Full article ">
17 pages, 1126 KiB  
Review
A Route for Investigating Psoriasis: From the Perspective of the Pathological Mechanisms and Therapeutic Strategies of Cancer
by Xingkang Wu, Yushuang Ma, Lu Wang and Xuemei Qin
Int. J. Mol. Sci. 2023, 24(18), 14390; https://doi.org/10.3390/ijms241814390 - 21 Sep 2023
Cited by 5 | Viewed by 1756
Abstract
Psoriasis is an incurable skin disease that develops in about two-thirds of patients before the age of 40 and requires lifelong treatment; its pathological mechanisms have not been fully elucidated. The core pathological process of psoriasis is epidermal thickening caused by the excessive [...] Read more.
Psoriasis is an incurable skin disease that develops in about two-thirds of patients before the age of 40 and requires lifelong treatment; its pathological mechanisms have not been fully elucidated. The core pathological process of psoriasis is epidermal thickening caused by the excessive proliferation of epidermal keratinocytes, which is similar to the key feature of cancer; the malignant proliferation of cancer cells causes tumor enlargement, suggesting that there is a certain degree of commonality between psoriasis and cancer. This article reviews the pathological mechanisms that are common to psoriasis and cancer, including the interaction between cell proliferation and an abnormal immune microenvironment, metabolic reprogramming, and epigenetic reprogramming. In addition, there are common therapeutic agents and drug targets between psoriasis and cancer. Thus, psoriasis and cancer share a common pathological mechanisms–drug targets–therapeutic agents framework. On this basis, it is proposed that investigating psoriasis from a cancer perspective is beneficial to enriching the research strategies related to psoriasis. Full article
(This article belongs to the Special Issue Progress in the Pathogenesis and Therapeutics of Psoriasis)
►▼ Show Figures

Figure 1

Figure 1
<p>The positive feedback loop of a keratinocyte-immune microenvironment. TNF-α: tumor necrosis factor alpha; INF-γ: interferon-gamma; IL-17: interleukin-17; IL-22: interleukin-22.</p> Full article ">Figure 2
<p>Comparison of the interaction between cell proliferation and immune microenvironment in psoriasis and cancer. DC cells: dendritic cells; IL-12: interleukin-12; IL-23: interleukin-23; Th1 cells: T helper 1 cells; Th17 cells: T helper 17 cells; Th22 cells: T helper 22 cells; TNF-α: tumor necrosis factor alpha; INF-γ: interferon gamma; IL-17: interleukin-17; IL-6: interleukin-6; IL-1β: interleukin-1β; TGFβ: transforming growth factor-β; ILC3 cells: group 3 innate lymphoid cells; γδ T cells: gamma delta T cells; IL-1: interleukin-1; IL-8: interleukin-8; IL-13: interleukin-13; IL-35: interleukin-35; IL-33: interleukin-33; IL-11: interleukin-11.</p> Full article ">
12 pages, 272 KiB  
Communication
Immunosuppressive Therapy of Antibody-Mediated aHUS and TTP
by Kata Kelen, Orsolya Horváth, Éva Kis, Bálint Mikes, Péter Sallay, Zoltán Prohászka, Attila József Szabó and György S. Reusz
Int. J. Mol. Sci. 2023, 24(18), 14389; https://doi.org/10.3390/ijms241814389 - 21 Sep 2023
Viewed by 1336
Abstract
The recent classification of pediatric thrombotic microangiopathies (TMA) takes into consideration mechanisms of disease for guidance to targeted therapies. We present our experience with seven patients with antibody mediated atypical hemolytic uremic syndrome (aHUS) and thrombotic thrombocytopenic purpura (TTP). Five children had aHUS [...] Read more.
The recent classification of pediatric thrombotic microangiopathies (TMA) takes into consideration mechanisms of disease for guidance to targeted therapies. We present our experience with seven patients with antibody mediated atypical hemolytic uremic syndrome (aHUS) and thrombotic thrombocytopenic purpura (TTP). Five children had aHUS with antibodies against complement factor H (CFH-ab) and two with TTP with antibodies against metalloproteinase ADAMTS13. In the aHUS cases diagnosed and treated before the eculizumab era, CFH-ab was detected using the ELISA assay. Mutational analysis of selected complement genes was performed. TTP was diagnosed if, in addition to microangiopathic hemolytic anemia and thrombocytopenia, ischemic organ involvement and severe deficiency in ADAMTS13 activity were present. Treatment protocol consisted of plasma exchanges (PE) and steroid pulses, followed by the combination of cyclophosphamide and rituximab to achieve long-term immunosuppression. Four patients with CFH-ab and the TTP patients with ADAMTS13 antibodies came into sustained remission. After a median follow-up of 11.7 (range 7.7–12.9) years without maintenance therapy, no disease recurrence was observed; nevertheless, six patients, two had hypertension and two had proteinuria as a late consequence. One patient, with late diagnosis of CFH-ab and additional genetic risk factors who was treated only with PE and plasma substitution, reached end-stage renal disease and was later successfully transplanted using eculizumab prophylaxis. In the cases of antibody-mediated TMAs, PE and early immunosuppressive treatment may result in sustained remission with preserved kidney function. Further data are needed to establish optimal treatment of anti-FH antibody-associated HUS. Full article
(This article belongs to the Special Issue Kidney Diseases: Molecular Pathogenesis and Therapeutic Strategies)
14 pages, 1873 KiB  
Article
Evaluating the Utility of ctDNA in Detecting Residual Cancer and Predicting Recurrence in Patients with Serous Ovarian Cancer
by Jie Wei Zhu, Fabian Wong, Agata Szymiczek, Gabrielle E. V. Ene, Shiyu Zhang, Taymaa May, Steven A. Narod, Joanne Kotsopoulos and Mohammad R. Akbari
Int. J. Mol. Sci. 2023, 24(18), 14388; https://doi.org/10.3390/ijms241814388 - 21 Sep 2023
Cited by 7 | Viewed by 1492
Abstract
Ovarian cancer has a high case fatality rate, but patients who have no visible residual disease after surgery have a relatively good prognosis. The presence of any cancer cells left in the peritoneal cavity after treatment may precipitate a cancer recurrence. In many [...] Read more.
Ovarian cancer has a high case fatality rate, but patients who have no visible residual disease after surgery have a relatively good prognosis. The presence of any cancer cells left in the peritoneal cavity after treatment may precipitate a cancer recurrence. In many cases, these cells are occult and are not visible to the surgeon. Analysis of circulating tumour DNA in the blood (ctDNA) may offer a sensitive method to predict the presence of occult (non-visible) residual disease after surgery and may help predict disease recurrence. We assessed 48 women diagnosed with serous ovarian cancer (47 high-grade and 1 low-grade) for visible residual disease and for ctDNA. Plasma, formalin-fixed paraffin-embedded (FFPE) tumour tissue and white blood cells were used to extract circulating free DNA (cfDNA), tumour DNA and germline DNA, respectively. We sequenced DNA samples for 59 breast and ovarian cancer driver genes. The plasma sample was collected after surgery and before initiating chemotherapy. We compared survival in women with no residual disease, with and without a positive plasma ctDNA test. We found tumour-specific variants (TSVs) in cancer cells from 47 patients, and these variants were sought in ctDNA in their post-surgery plasma. Fifteen (31.9%) of the 47 patients had visible residual disease; of these, all 15 had detectable ctDNA. Thirty-one patients (65.9%) had no visible residual disease; of these, 24 (77.4%) patients had detectable ctDNA. Of the patients with no visible residual disease, those patients with detectable ctDNA had higher mortality (20 of 27 died) than those without detectable ctDNA (3 of 7 died) (HR 2.32; 95% CI: 0.67–8.05), although this difference was not statistically significant (p = 0.18). ctDNA in post-surgical serum samples may predict the presence of microscopic residual disease and may be a predictor of recurrence among women with ovarian cancer. Larger studies are necessary to validate these findings. Full article
(This article belongs to the Special Issue Ovarian Cancer: Advances on Pathophysiology and Therapies)
►▼ Show Figures

Figure 1

Figure 1
<p>Flow of enrolled participants from collected samples to final clinical outcome.</p> Full article ">Figure 2
<p>Results of ctDNA analysis of post-surgery plasma samples of patients with no surgical residual disease and their clinical outcome.</p> Full article ">Figure 3
<p>Overview of study design.</p> Full article ">
11 pages, 653 KiB  
Review
Utility of In Vitro Cellular Models of Low-Dose Lipopolysaccharide in Elucidating the Mechanisms of Anti-Inflammatory and Wound-Healing-Promoting Effects of Lipopolysaccharide Administration In Vivo
by Teruko Honda and Hiroyuki Inagawa
Int. J. Mol. Sci. 2023, 24(18), 14387; https://doi.org/10.3390/ijms241814387 - 21 Sep 2023
Cited by 2 | Viewed by 1662
Abstract
Lipopolysaccharide (LPS) is a bacterial component that activates intracellular signaling pathways upon binding to the Toll-like receptor (TLR)-4/MD-2 complex. It is well known that LPS injected into animals and high-dose (100 ng/mL to 1 μg/mL) LPS treatment to innate immune cells induce an [...] Read more.
Lipopolysaccharide (LPS) is a bacterial component that activates intracellular signaling pathways upon binding to the Toll-like receptor (TLR)-4/MD-2 complex. It is well known that LPS injected into animals and high-dose (100 ng/mL to 1 μg/mL) LPS treatment to innate immune cells induce an inflammatory response. In contrast, LPS is naturally present in the gastrointestinal tract, respiratory tract, and skin of humans and animals, and it has been shown that TLR-4-deficient animals cannot maintain their immune balance and gut homeostasis. LPS from commensal bacteria can help maintain homeostasis against mucosal stimulation in healthy individuals. Oral LPS administration has been shown to be effective in preventing allergic and lifestyle-related diseases. However, this effect was not observed after treatment with LPS at high doses. In mice, oral LPS administration resulted in the detection of LPS at a low concentration in the peritoneal fluid. Therefore, LPS administered at low and high doses have different effects. Moreover, the results of in vitro experiments using low-dose LPS may reflect the effects of oral LPS administration. This review summarizes the utility of in vitro models using cells stimulated with LPS at low concentrations (50 pg/mL to 50 ng/mL) in elucidating the mechanisms of oral LPS administration. Low-dose LPS administration has been demonstrated to suppress the upregulation of proinflammatory cytokines and promote wound healing, suggesting that LPS is a potential agent that can be used for the treatment and prevention of lifestyle-related diseases. Full article
(This article belongs to the Special Issue Advances in Lipopolysaccharide (LPS))
►▼ Show Figures

Figure 1

Figure 1
<p>General studies (inflammatory response analysis model) and physiological studies (physiological function analysis model) of lipopolysaccharide (LPS). Intravascular administration of LPS is a model for sepsis and chronic inflammatory diseases, which increase the production of proinflammatory cytokines. In general studies, high-dose LPS has been used in in vitro inflammatory response analysis models. On the other hand, oral and transdermal administration of LPS is a model to evaluate the functionality of foods consumed daily such as brown rice, wheat bran, and buckwheat, which increase the production of anti-inflammatory cytokines as presented in this review. In physiological studies, low-dose LPS has been used in in vitro physiological function analysis models.</p> Full article ">Figure 2
<p>Signaling in monocytes/macrophages differs with LPS dose. High-dose LPS-activated monocytes/macrophages activate the NF-κB pathway and induce inflammatory responses. Whereas low-dose LPS-activated monocytes/macrophages inactive the NF-κB pathway and suppress inflammatory responses. The response of signaling pathways in LPS-activated monocytes/macrophages differs with LPS dose.</p> Full article ">
14 pages, 3339 KiB  
Article
Silibinin Downregulates Types I and III Collagen Expression via Suppression of the mTOR Signaling Pathway
by Sooyeon Choi, Seoyoon Ham, Young In Lee, Jihee Kim, Won Jai Lee and Ju Hee Lee
Int. J. Mol. Sci. 2023, 24(18), 14386; https://doi.org/10.3390/ijms241814386 - 21 Sep 2023
Cited by 2 | Viewed by 1430
Abstract
Keloid scars are fibro-proliferative conditions characterized by abnormal fibroblast proliferation and excessive extracellular matrix deposition. The mammalian target of the rapamycin (mTOR) pathway has emerged as a potential therapeutic target in keloid disease. Silibinin, a natural flavonoid isolated from the seeds and fruits [...] Read more.
Keloid scars are fibro-proliferative conditions characterized by abnormal fibroblast proliferation and excessive extracellular matrix deposition. The mammalian target of the rapamycin (mTOR) pathway has emerged as a potential therapeutic target in keloid disease. Silibinin, a natural flavonoid isolated from the seeds and fruits of the milk thistle, is known to inhibit the mTOR signaling pathway in human cervical and hepatoma cancer cells. However, the mechanisms underlying this inhibitory effect are not fully understood. This in vitro study investigated the effects of silibinin on collagen expression in normal human dermal and keloid-derived fibroblasts. We evaluated the effects of silibinin on the expressions of collagen types I and III and assessed its effects on the suppression of the mTOR signaling pathway. Our findings confirmed elevated mTOR phosphorylation levels in keloid scars compared to normal tissue specimens. Silibinin treatment significantly reduced collagen I and III expressions in normal human dermal and keloid-derived fibroblasts. These effects were accompanied by the suppression of the mTOR signaling pathway. Our findings suggest the potential of silibinin as a promising therapeutic agent for preventing and treating keloid scars. Further studies are warranted to explore the clinical application of silibinin in scar management. Full article
(This article belongs to the Special Issue Molecular Studies of Natural Compounds and Plant Extracts)
►▼ Show Figures

Figure 1

Figure 1
<p>Chemical structure of silibinin. The chemical formula of silibinin is C<sub>25</sub>H<sub>22</sub>O<sub>10,</sub> and the molecular weight is 482.441 g/mol.</p> Full article ">Figure 2
<p>Clinical photographs of the keloid scars included in the present study. (<b>A</b>,<b>B</b>) Keloid scars on the right ear helix that occurred after piercing. (<b>C</b>) A keloid scar on the abdomen that occurred after an orchiopexy surgery. (<b>D</b>) A keloid scar on the anterior chest that occurred after a laceration. (<b>E</b>) A keloid scar on the abdomen that occurred after a total abdominal hysterectomy and bilateral salpingo-oophorectomy.</p> Full article ">Figure 3
<p>Expression of mTOR in keloid tissues. (<b>A</b>) Phosphorylation of mTOR is increased in active keloid scars compared to normal tissue specimens. The scale bar indicates 500 μm. (<b>B</b>) Semi-quantitative analysis showed that the p-mTOR signaling was increased by 21.3-fold in keloid tissue compared to normal tissue (** <span class="html-italic">p</span> &lt; 0.01). (<b>C</b>) mTOR phosphorylation is increased in the cytoplasm of fibroblasts in keloid tissue.</p> Full article ">Figure 4
<p>Effect of silibinin on cell viability of skin fibroblasts. (<b>A</b>) Human dermal fibroblast. (<b>B</b>) Keloid-derived fibroblast. Cells were seeded at a density of 1 × 10<sup>4</sup> cells/well in 96-well plates overnight and then treated with different concentrations of silibinin (0–200 µM) at 37 °C for 24 h. Cell viability was analyzed using the CCK-8 assay kit. The viability of the cells was not markedly suppressed by treatment with silibinin at a concentration of 200 μM. HDF, human dermal fibroblast; KF, keloid-derived fibroblast; CCK-8, Cell Counting Kit-8.</p> Full article ">Figure 5
<p>Effect of silibinin on collagen types I and III expression. Relative mRNA expression levels were compared between control and silibinin treatments. Silibinin treatment resulted in a dose-dependent reduction in COL1A1 (<b>A</b>,<b>B</b>) and COL3A1 (<b>C</b>,<b>D</b>) mRNA transcripts in TGF-β1-treated human dermal and keloid-derived fibroblasts. Bars represent mean ± SD, <span class="html-italic">n</span> = 3 − 6 (* <span class="html-italic">p</span> &lt; 0.05, *** <span class="html-italic">p</span> &lt; 0.001, ns, non-significant).</p> Full article ">Figure 6
<p>Effect of silibinin on the mTOR signaling pathway. (<b>A</b>) Silibinin effectively downregulated the mTOR pathway, including mTOR and its key components—p70S6K, S6, and 4E-BP1—in both HDFs and KFs. (<b>B</b>–<b>E</b>) Results of quantitative analysis. The data are presented as a ratio of the signal intensity of the phosphorylated form to the total form. <span class="html-italic">n</span> = 3 (* <span class="html-italic">p &lt;</span> 0.05, ** <span class="html-italic">p</span> &lt; 0.01, ns, non-significant).</p> Full article ">Figure 6 Cont.
<p>Effect of silibinin on the mTOR signaling pathway. (<b>A</b>) Silibinin effectively downregulated the mTOR pathway, including mTOR and its key components—p70S6K, S6, and 4E-BP1—in both HDFs and KFs. (<b>B</b>–<b>E</b>) Results of quantitative analysis. The data are presented as a ratio of the signal intensity of the phosphorylated form to the total form. <span class="html-italic">n</span> = 3 (* <span class="html-italic">p &lt;</span> 0.05, ** <span class="html-italic">p</span> &lt; 0.01, ns, non-significant).</p> Full article ">Figure 7
<p>Major pathways downstream of mTORC1 signaling in mRNA translation. mTORC1 promotes protein synthesis by phosphorylation of two key effectors, eIF4E binding protein 1 (4E-BP1) and p70S6 Kinase (p70S6K). 4E-BP1 inhibits translation by binding and sequestering eukaryotic translation initiation factor-4E (eIF4E) to prevent assembly of the eIF4F complex. eIF4F complex mediates the recruitment of ribosomes to mRNA, which is the rate-limiting step for translation. mTORC1 phosphorylates 4E-BP1 at multiple sites to trigger its dissociation from eIF4E, allowing 5′-cap-dependent mRNA translation to occur. Unrelated to 4E-BP1, mTORC1 phosphorylates p70S6K, stimulating its subsequent phosphorylation. p70S6K phosphorylates and activates several substrates that promote mRNA translation initiation, including S6.</p> Full article ">Figure 8
<p>Summary and logic flowchart of the study. Silibinin treatment significantly reduced the expressions of collagen I and III in normal human dermal fibroblasts and keloid-derived fibroblasts, with suppression of the mTOR signaling pathway (highlighted in the yellow box). The relationship between mTOR, collagen synthesis, and keloid is described in the introduction and discussion sections of the manuscript.</p> Full article ">
16 pages, 708 KiB  
Review
Endothelial Dysfunction in Systemic Sclerosis
by Eshaan Patnaik, Matthew Lyons, Kimberly Tran and Debendra Pattanaik
Int. J. Mol. Sci. 2023, 24(18), 14385; https://doi.org/10.3390/ijms241814385 - 21 Sep 2023
Cited by 6 | Viewed by 3348
Abstract
Systemic sclerosis, commonly known as scleroderma, is an autoimmune disorder characterized by vascular abnormalities, autoimmunity, and multiorgan fibrosis. The exact etiology is not known but believed to be triggered by environmental agents in a genetically susceptible host. Vascular symptoms such as the Raynaud [...] Read more.
Systemic sclerosis, commonly known as scleroderma, is an autoimmune disorder characterized by vascular abnormalities, autoimmunity, and multiorgan fibrosis. The exact etiology is not known but believed to be triggered by environmental agents in a genetically susceptible host. Vascular symptoms such as the Raynaud phenomenon often precede other fibrotic manifestations such as skin thickening indicating that vascular dysfunction is the primary event. Endothelial damage and activation occur early, possibly triggered by various infectious agents and autoantibodies. Endothelial dysfunction, along with defects in endothelial progenitor cells, leads to defective angiogenesis and vasculogenesis. Endothelial to mesenchymal cell transformation is another seminal event during pathogenesis that progresses to tissue fibrosis. The goal of the review is to discuss the molecular aspect of the endothelial dysfunction that leads to the development of systemic sclerosis. Full article
(This article belongs to the Special Issue Molecular Mechanisms of Endothelial Dysfunction 3.0)
►▼ Show Figures

Figure 1

Figure 1
<p>Endothelial dysfunction in systemic sclerosis; AECA: anti-endothelial cell antibodies, VEGF: vascular endothelial growth factor, EndoMT: endothelial to mesenchymal transition.</p> Full article ">
12 pages, 1481 KiB  
Communication
ICI 182,780 Attenuates Selective Upregulation of Uterine Artery Cystathionine β-Synthase Expression in Rat Pregnancy
by Jin Bai, Yao Li, Guofeng Yan, Jing Zhou, Alejandra Garcia Salmeron, Olamide Tolulope Fategbe, Sathish Kumar, Xuejin Chen and Dong-Bao Chen
Int. J. Mol. Sci. 2023, 24(18), 14384; https://doi.org/10.3390/ijms241814384 - 21 Sep 2023
Cited by 1 | Viewed by 1374
Abstract
Endogenous hydrogen sulfide (H2S) produced by cystathionine β-synthase (CBS) and cystathionine-γ lyase (CSE) has emerged as a novel uterine vasodilator contributing to pregnancy-associated increases in uterine blood flow, which safeguard pregnancy health. Uterine artery (UA) H2S production is stimulated [...] Read more.
Endogenous hydrogen sulfide (H2S) produced by cystathionine β-synthase (CBS) and cystathionine-γ lyase (CSE) has emerged as a novel uterine vasodilator contributing to pregnancy-associated increases in uterine blood flow, which safeguard pregnancy health. Uterine artery (UA) H2S production is stimulated via exogenous estrogen replacement and is associated with elevated endogenous estrogens during pregnancy through the selective upregulation of CBS without altering CSE. However, how endogenous estrogens regulate uterine artery CBS expression in pregnancy is unknown. This study was conducted to test a hypothesis that endogenous estrogens selectively stimulate UA CBS expression via specific estrogen receptors (ER). Treatment with E2β (0.01 to 100 nM) stimulated CBS but not CSE mRNA in organ cultures of fresh UA rings from both NP and P (gestational day 20, GD20) rats, with greater responses to all doses of E2β tested in P vs. NP UA. ER antagonist ICI 182,780 (ICI, 1 µM) completely attenuated E2β-stimulated CBS mRNA in both NP and P rat UA. Subcutaneous injection with ICI 182,780 (0.3 mg/rat) of GD19 P rats for 24 h significantly inhibited UA CBS but not mRNA expression, consistent with reduced endothelial and smooth muscle cell CBS (but not CSE) protein. ICI did not alter mesenteric and renal artery CBS and CSE mRNA. In addition, ICI decreased endothelial nitric oxide synthase mRNA in UA but not in mesenteric or renal arteries. Thus, pregnancy-augmented UA CBS/H2S production is mediated by the actions of endogenous estrogens via specific ER in pregnant rats. Full article
(This article belongs to the Special Issue Molecular Research of Vascular Aspects in Pregnancy)
►▼ Show Figures

Figure 1

Figure 1
<p>Effects of estradiol-17β on CBS and CSE expression in isolated uterine arteries. Endothelium-intact uterine artery (UA) rings from nonpregnant (NP) and pregnant (P, day 20) rats were treated with estradiol-17β (E2β, 0.01–100 nM) for 24 h. Total RNA was extracted to measure mRNAs of cystathionine β-synthase (CBS) and cystathionine γ-lyase (CSE) using quantitative real-time PCR (qPCR) using gene-specific primers listed in <a href="#ijms-24-14384-t001" class="html-table">Table 1</a>; L19 was measured as an internal control for quantitation. Data (means ± SEM) were summarized from 3 different rats. Bars with different superscripts differ significantly, <span class="html-italic">p</span> &lt; 0.05 vs. untreated controls. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, NP vs. P rats; ns: not significant.</p> Full article ">Figure 2
<p>Effects of ICI 182, 760 on uterine and systemic (mesenteric and renal) artery CBS, CSE, and eNOS mRNA expression in pregnant rats in vivo. Time pregnant rats on gestation day 19 were treated with either sesame oil alone (Ctl) or with a specific estrogen receptor (ER) antagonist ICI 182, 780 (ICI, 0.3 mg/rat). Rats (n = 8) were sacrificed at 24 h after injection. Uterine (UA), mesenteric (MA), and renal (RA) arteries were collected to analyze mRNAs of cystathionine β-synthase (CBS), cystathionine γ-lyase (CSE), and endothelial nitric oxide synthase (eNOS) via qPCR with gene-specific primers listed in <a href="#ijms-24-14384-t001" class="html-table">Table 1</a>; L19 mRNA was measured as an internal control for quantitation. Data (means ± SEM) were summarized from artery samples of 5 different rats/group. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. vehicle (Ctl) treated controls.</p> Full article ">Figure 3
<p>Effects of ICI 182, 760 on uterine artery CBS and CSE protein expression in pregnant rats in vivo. Uterine arteries (UAs) were collected from pregnant (gestation day 20) rats at 24 h treatment with vehicle (Ctl) or ICI 182, 780 (ICI, 0.3 mg/rat). Paraffin-embedded UA sections (5 µM) were subjected to immunofluorescence labeling of cystathionine β-synthase (CBS) and cystathionine γ-lyase (CSE) proteins using specific CBS or CSE antibodies, with CD31 antibody for co-labeling endothelial cells (ECs) distinct from smooth muscle cells (SMCs). After incubation with corresponding fluorescently labeled secondary antibodies, sections were mounted with DAPI to label nuclei and examined under confocal microscopy. IgG was used as negative control (insert). Images were taken to determine CBS and CSE proteins (relative green fluorescence intensity; RFI) using Image J and summarized as fold changes relative to untreated smooth muscles. Data (means ± SEM) were summarized from UA sections from three different rats. * and #, <span class="html-italic">p</span> &lt; 0.05 vs. vehicle (Ctl) treated. Scale bar = 100 μm.</p> Full article ">
15 pages, 3325 KiB  
Review
The Effect of Plant-Derived Low-Ratio Linoleic Acid/α-Linolenic Acid on Markers of Glucose Controls: A Systematic Review and Meta-Analysis
by Qiong Wang and Xingguo Wang
Int. J. Mol. Sci. 2023, 24(18), 14383; https://doi.org/10.3390/ijms241814383 - 21 Sep 2023
Cited by 1 | Viewed by 1580
Abstract
The objective of this meta-analysis was to examine the impact of a low-ratio linoleic acid/α-linolenic acid (LA/ALA) diet on the glycemic profile of adults. A comprehensive search was performed across four databases (Web of Science, Scopus, Embase, and PubMed) to evaluate the influence [...] Read more.
The objective of this meta-analysis was to examine the impact of a low-ratio linoleic acid/α-linolenic acid (LA/ALA) diet on the glycemic profile of adults. A comprehensive search was performed across four databases (Web of Science, Scopus, Embase, and PubMed) to evaluate the influence of the low-ratio LA/ALA. Relevant references were screened up until February 2023. Intervention effects were analyzed by calculating change values as weighted mean differences (WMD) and 95% confidence intervals (CI) using fixed-effects models. Additionally, subgroup analysis and meta-regression were employed to investigate potential sources of heterogeneity. Twenty-one randomized controlled trials (RCTs) were included, and the low-ratio LA/ALA diet had no significant effect on fasting blood sugar (FBS, WMD: 0.00 mmol/L, 95% CI: −0.06, 0.06, p = 0.989, I2 = 0.0%), insulin levels (WMD: 0.20 μIU/mL, 95% CI: −0.23, 0.63, p = 0.360, I2 = 3.2%), homeostatic model assessment insulin resistance (HOMA-IR, WMD: 0.09, 95% CI: −0.06, 0.23, p = 0.243, I2 = 0.0%), and hemoglobin A1c (HbA1c, WMD: −0.01%, 95% CI: −0.07, 0.06, p = 0.836, I2 = 0.0%). Based on subgroup analyses, it was observed that the impact of a low-ratio LA/ALA diet on elevated plasma insulin (WMD: 1.31 μIU/mL, 95% CI: 0.08, 2.54, p = 0.037, I2 = 32.0%) and HOMA-IR (WMD: 0.47, 95% CI: 0.10, 0.84, p = 0.012, I2 = 0.0%) levels exhibited greater prominence in North America compared to Asian and European countries. Publication bias was not detected for FBS, insulin, HOMA-IR, and HbA1c levels according to the Begg and Egger tests. Furthermore, the conducted sensitivity analyses indicated stability, as the effects of the low-ratio LA/ALA diet on various glycemic and related metrics remained unchanged even after removing individual studies. Overall, based on the available studies, it can be concluded that the low-ratio LA/ALA diet has limited impact on blood glucose-related biomarker levels. Full article
(This article belongs to the Special Issue Fatty Acids and Metabolic Syndrome)
►▼ Show Figures

Figure 1

Figure 1
<p>Screening flowchart of this study.</p> Full article ">Figure 2
<p>The effect of low-ratio LA/ALA on FBS. Refs. [<a href="#B22-ijms-24-14383" class="html-bibr">22</a>,<a href="#B23-ijms-24-14383" class="html-bibr">23</a>,<a href="#B24-ijms-24-14383" class="html-bibr">24</a>,<a href="#B28-ijms-24-14383" class="html-bibr">28</a>,<a href="#B29-ijms-24-14383" class="html-bibr">29</a>,<a href="#B30-ijms-24-14383" class="html-bibr">30</a>,<a href="#B31-ijms-24-14383" class="html-bibr">31</a>,<a href="#B32-ijms-24-14383" class="html-bibr">32</a>,<a href="#B33-ijms-24-14383" class="html-bibr">33</a>,<a href="#B34-ijms-24-14383" class="html-bibr">34</a>,<a href="#B35-ijms-24-14383" class="html-bibr">35</a>,<a href="#B36-ijms-24-14383" class="html-bibr">36</a>,<a href="#B37-ijms-24-14383" class="html-bibr">37</a>,<a href="#B38-ijms-24-14383" class="html-bibr">38</a>,<a href="#B39-ijms-24-14383" class="html-bibr">39</a>,<a href="#B40-ijms-24-14383" class="html-bibr">40</a>,<a href="#B41-ijms-24-14383" class="html-bibr">41</a>,<a href="#B42-ijms-24-14383" class="html-bibr">42</a>,<a href="#B43-ijms-24-14383" class="html-bibr">43</a>,<a href="#B44-ijms-24-14383" class="html-bibr">44</a>,<a href="#B45-ijms-24-14383" class="html-bibr">45</a>].</p> Full article ">Figure 3
<p>The effect of low-ratio LA/ALA on insulin. Refs. [<a href="#B22-ijms-24-14383" class="html-bibr">22</a>,<a href="#B23-ijms-24-14383" class="html-bibr">23</a>,<a href="#B24-ijms-24-14383" class="html-bibr">24</a>,<a href="#B29-ijms-24-14383" class="html-bibr">29</a>,<a href="#B30-ijms-24-14383" class="html-bibr">30</a>,<a href="#B31-ijms-24-14383" class="html-bibr">31</a>,<a href="#B32-ijms-24-14383" class="html-bibr">32</a>,<a href="#B34-ijms-24-14383" class="html-bibr">34</a>,<a href="#B36-ijms-24-14383" class="html-bibr">36</a>,<a href="#B37-ijms-24-14383" class="html-bibr">37</a>,<a href="#B38-ijms-24-14383" class="html-bibr">38</a>,<a href="#B39-ijms-24-14383" class="html-bibr">39</a>,<a href="#B40-ijms-24-14383" class="html-bibr">40</a>,<a href="#B41-ijms-24-14383" class="html-bibr">41</a>,<a href="#B42-ijms-24-14383" class="html-bibr">42</a>,<a href="#B43-ijms-24-14383" class="html-bibr">43</a>,<a href="#B44-ijms-24-14383" class="html-bibr">44</a>].</p> Full article ">Figure 4
<p>The effect of low-ratio LA/ALA on HOMA-IR. Refs. [<a href="#B22-ijms-24-14383" class="html-bibr">22</a>,<a href="#B23-ijms-24-14383" class="html-bibr">23</a>,<a href="#B24-ijms-24-14383" class="html-bibr">24</a>,<a href="#B30-ijms-24-14383" class="html-bibr">30</a>,<a href="#B33-ijms-24-14383" class="html-bibr">33</a>,<a href="#B37-ijms-24-14383" class="html-bibr">37</a>,<a href="#B39-ijms-24-14383" class="html-bibr">39</a>,<a href="#B41-ijms-24-14383" class="html-bibr">41</a>,<a href="#B42-ijms-24-14383" class="html-bibr">42</a>,<a href="#B44-ijms-24-14383" class="html-bibr">44</a>].</p> Full article ">Figure 5
<p>The effect of low-ratio LA/ALA on HbA1c. Refs. [<a href="#B22-ijms-24-14383" class="html-bibr">22</a>,<a href="#B24-ijms-24-14383" class="html-bibr">24</a>,<a href="#B34-ijms-24-14383" class="html-bibr">34</a>,<a href="#B36-ijms-24-14383" class="html-bibr">36</a>,<a href="#B37-ijms-24-14383" class="html-bibr">37</a>,<a href="#B38-ijms-24-14383" class="html-bibr">38</a>,<a href="#B44-ijms-24-14383" class="html-bibr">44</a>].</p> Full article ">
13 pages, 1070 KiB  
Article
Emerging Role of Decoy Receptor-2 as a Cancer Risk Predictor in Oral Potentially Malignant Disorders
by Lucas de Villalaín, Saúl Álvarez-Teijeiro, Tania Rodríguez-Santamarta, Álvaro Fernández del Valle, Eva Allonca, Juan P. Rodrigo, Juan Carlos de Vicente and Juana M. García-Pedrero
Int. J. Mol. Sci. 2023, 24(18), 14382; https://doi.org/10.3390/ijms241814382 - 21 Sep 2023
Viewed by 870
Abstract
The aim of this study was to evaluate the expression of the senescence markers, Decoy Receptor 2 (DcR2) and Differentiated Embryo-Chondrocyte expressed gen 1 (DEC1), in oral potentially malignant disorders (OPMDs) to ascertain their possible association with oral cancer risk. The immunohistochemical analysis [...] Read more.
The aim of this study was to evaluate the expression of the senescence markers, Decoy Receptor 2 (DcR2) and Differentiated Embryo-Chondrocyte expressed gen 1 (DEC1), in oral potentially malignant disorders (OPMDs) to ascertain their possible association with oral cancer risk. The immunohistochemical analysis of DcR2 and DEC1 expression (along with p16 and Ki67 expression) was carried out in 60 patients with clinically diagnosed oral leukoplakia. Fifteen cases (25%) subsequently developed an invasive carcinoma. Correlations between protein marker expression, histological grade and oral cancer risk were assessed. DcR2, DEC1 and Ki67 protein expressions were found to correlate significantly with increased oral cancer risk, and also with an increased grade of dysplasia. Multivariate analysis demonstrated that DcR2 and Ki67 expression are independent predictors of oral cancer development. Our results evidence for the first time the potential of DcR2 as an early biomarker to assess oral cancer risk in patients with oral leukoplakia (HR = 59.7, p = 0.015), showing a superior predictive value to histology (HR = 4.225, p = 0.08). These findings reveal that the increased expression of DcR2 and DEC1 occurred frequently in OPMDs. In addition, DcR2 expression emerges as a powerful biomarker for oral cancer risk assessment in patients with oral leukoplakia. Full article
(This article belongs to the Special Issue Molecular Pathogenesis of Oral Potentially Malignant Disorders Transformation)
►▼ Show Figures

Figure 1

Figure 1
<p>Representative examples of Ki67 and p16 immunoexpression in oral leukoplakia. Ki67 expression restricted to the basal layer in an oral leukoplakia that did not undergo malignant transformation (<b>A</b>), whereas Ki67 expression extended above the basal third of the epithelium and affected a high percentage of cells in a case of oral dysplastic leukoplakia that finally evolved to invasive carcinoma (<b>B</b>). Two cases of dysplastic oral epithelia showing p16 staining in basal and suprabasal layers of epithelium; however, subsequent evolution was different. While the case shown in (<b>C</b>) underwent malignant transformation, the case in (<b>D</b>) did not progress to oral cancer. Original magnification 200× (<b>A</b>); 100× (<b>B</b>–<b>D</b>).</p> Full article ">Figure 2
<p>Representative examples of immunohistochemical expression patterns of DcR2 and DEC1 in oral leukoplakia and patient-matched OSCC. Examples of dysplastic lesions that evolved to invasive carcinoma showing either a distribution of DcR2 expression in the epithelium (<b>A</b>), or in the corium (<b>B</b>). Patient-matched OSCC also showed DcR2 expression in the stroma (<b>C</b>). Original magnification 100×. A patient with oral leukoplakia that subsequently developed oral carcinoma, showing both patterns of nuclear and cytoplasmic DEC1 expression in epithelial cells (<b>D</b>). Original magnification 200×.</p> Full article ">
17 pages, 2751 KiB  
Article
A Side-by-Side Comparison of Wildtype and Variant Melanocortin 1 Receptor Signaling with Emphasis on Protection against Oxidative Damage to DNA
by Sonia Cerdido, José Sánchez-Beltrán, Ana Lambertos, Marta Abrisqueta, Lidia Padilla, Cecilia Herraiz, Conchi Olivares, Celia Jiménez-Cervantes and José C. García-Borrón
Int. J. Mol. Sci. 2023, 24(18), 14381; https://doi.org/10.3390/ijms241814381 - 21 Sep 2023
Cited by 3 | Viewed by 1200
Abstract
Common variants of the MC1R gene coding the α-melanocyte stimulating hormone receptor are associated with light skin, poor tanning, blond or red hair, and increased melanoma risk, due to pigment-dependent and -independent effects. This complex phenotype is usually attributed to impaired activation of [...] Read more.
Common variants of the MC1R gene coding the α-melanocyte stimulating hormone receptor are associated with light skin, poor tanning, blond or red hair, and increased melanoma risk, due to pigment-dependent and -independent effects. This complex phenotype is usually attributed to impaired activation of cAMP signaling. However, several MC1R variants show significant residual coupling to cAMP and efficiently activate mitogenic extracellular signal-regulated kinase 1 and 2 (ERK1/2) signaling. Yet, residual signaling and the key actions of wildtype and variant MC1R have never been assessed under strictly comparable conditions in melanocytic cells of identical genetic background. We devised a strategy based on CRISPR-Cas9 knockout of endogenous MC1R in a human melanoma cell line wildtype for BRAF, NRAS and NF1, followed by reconstitution with epitope-labeled MC1R constructs, and functional analysis of clones expressing comparable levels of wildtype, R151C or D294H MC1R. The proliferation rate, shape, adhesion, motility and sensitivity to oxidative DNA damage were compared. The R151C and D294H RHC variants displayed impaired cAMP signaling, intracellular stability similar to the wildtype, triggered ERK1/2 activation as effectively as the wildtype, and afforded partial protection against oxidative DNA damage, although less efficiently than the wildtype. Therefore, common melanoma-associated MC1R variants display biased signaling and significant genoprotective activity. Full article
(This article belongs to the Special Issue Advances in Pathogenesis and Treatment of Skin Cancer)
►▼ Show Figures

Figure 1

Figure 1
<p>Stable expression of WT and variant MC1R in melanoma cells of identical genetic background. (<b>A</b>) Strategy for the generation of HBL human melanoma cell-derived clones expressing a single and defined variant of the MC1R. See text and <a href="#app1-ijms-24-14381" class="html-app">Supplementary Figure S1</a> for details. (<b>B</b>) Expression and intracellular stability of the WT, R151C and D294H forms of MC1R. Cells were treated with 0.1 mM cycloheximide for the indicated times, detergent-solubilized, electrophoresed, and analyzed for MC1R with anti-flag. (<b>C</b>) Steady-state level of expression of WT and variant MC1R. Detergent-solubilized cell extracts were analyzed for MC1R expression via Western blot. The intensity of the MC1R band was corrected for protein loading using β-actin (ACTB) as the loading control. Results are normalized to the expression of WT MC1R and are the mean ± sem for 7 independent experiments. (<b>D</b>) Semi-logarithmic plots for the estimation of the rate of decay of WT or variant MC1R in live HBL cells. The intracellular half-lives of the different receptor forms, estimated from the slopes of the adjusted linear plots, are indicated (mean ± sem, n ≥ 3). (<b>E</b>) Confocal micrographs of HBL cells expressing defined MC1R variants. MC1R was immunostained with anti-FLAG, with or without a 15 min treatment with 0.4% Triton X-100 in PBS for permeabilization of the cell membrane. The graphs on the right show the MC1R staining intensity normalized to the cells expressing the WT receptor. **, <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. Scale bar 50 µm.</p> Full article ">Figure 2
<p>Functional coupling of WT and variant MC1R. Cells expressing the indicated MC1R variants were stimulated with 100 nM NDP-MSH for the times shown and analyzed for (<b>A</b>) intracellular cAMP and (<b>B</b>) ERK activation. The upper Western blots are representative of three independent experiments, and the lower bar graphs represent the quantification of the active ERK intensity, normalized to the non-stimulated control (0 min timepoint, mean ± sem, n = 3). (<b>C</b>) Steady-state levels of MITF in unstimulated cells expressing the indicated MC1R forms. The image is representative of five independent Western blots, whose quantification is shown below as a bar graph (values normalized to the MC1R-KO expression, results given as mean ± sem, n = 5). (<b>D</b>) Changes in MITF expression upon stimulation of cells expressing the indicated MC1R form with 100 nM NDP-MSH for 48 h. Representative blots are shown at the top, and the fold change in band intensity, normalized to each non-stimulated control, is shown below (mean ± sem, n = 3).</p> Full article ">Figure 3
<p>MC1R activation modulates proliferation and cell cycle progression. (<b>A</b>) Growth curves of MC1R clones cultured in 2D and complete medium (DMEM + 10% FCS) determined by manual cell counting. Equal numbers of cells were seeded, cells were allowed to attach for 24 h (time 0) and counted every 24 h. Growth was represented as fold increase in cell number relative to the initial number in the 0-time point. The statistical significance of the cell numbers in MC1R-expressing cells compared with MC1R-KO cells at 72 h is shown. (<b>B</b>) FACS analysis of MC1R clones cultured in total medium (DMEM + 10% FCS) for three days. Results are given as mean ± sd (n = 5). Stars indicate the statistical significance of each phase compared with the same phase in MC1R-KO cells. (<b>C</b>) FACS analysis of MC1R clones cultured under FCS-starved conditions (DMEM and no FCS) for two days in the presence or absence of 100 nM NDP-MSH. For each receptor form, the stars within the bars of the NDP-MSH condition indicate the statistical significance of each phase compared with the same phase in the corresponding untreated control (results given as mean ± sd, n ≥ 3; ns, not significant). *, <span class="html-italic">p</span> &lt; 0.05; **, <span class="html-italic">p</span> &lt; 0.01; ***, <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 4
<p>Effect of the <span class="html-italic">MC1R</span> genotype on cell shape and motility. (<b>A</b>) Effect of WT MC1R on shape and dendricity. MC1R-KO cells or cells expressing WT MC1R were grown in complete medium with 10% FCS. Micrographs were taken using an Eclipse TS2 microscope with 20x objective lenses, scale bar 50 µm. A quantitative analysis of the number and length of dendrites per cell in randomly selected images is shown below the micrographs (at least 100 cells per condition were analyzed, and the results are given as median ± SEM for length or mean ± SEM for number, n = 3). (<b>B</b>) Effect of NDP-MSH on shape of cells expressing WT or variant MC1R. When required, cells were treated for 48 h with 100 nM NDP-MSH before acquisition and analysis of the micrographs (100 cells quantified per condition; the scale bar and results are formatted as in (<b>A</b>)). (<b>C</b>) Basal and MC1R-agonist induced migration of cells expressing the different MC1R forms. Cells were seeded on Oris™ 96-well plates with silicon stoppers in serum-reduced medium, and if required were treated with 100 nM NDP-MSH for 24 h. The stoppers were removed, and images were taken at 24 h or 48 h after removal of the stoppers. Representative images are shown, along with the quantification of wound healing at 24 h or 48 h (results are given as mean ± SEM, n = 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>Genoprotective action against oxidative stress of the different MC1R forms. (<b>A</b>) γH2AX immunostaining of control cells and cells challenged with Luperox (150 µM, 30 min) with or without a previous treatment with NDP-MSH (100 nM, 48 h). The confocal images correspond to one of two independent experiments with comparable results. Scale bar 50 µm. For each experiment, at least 100 cells were randomly selected and analyzed for staining intensity. The plots below show the median of the staining intensity of cells, normalized to the control condition (no treatment with NDP-MSH or Luperox). (<b>B</b>) Neutral comet assay. In this case, cells pretreated or not with NDP-MSH were challenged with 100 µM Luperox for 20 min. Two independent experiments were performed with consistent results. *, <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. Scale bar 25 µm.</p> Full article ">
17 pages, 4442 KiB  
Article
Myogenetic Oligodeoxynucleotide Induces Myocardial Differentiation of Murine Pluripotent Stem Cells
by Mina Ishioka, Yuma Nihashi, Yoichi Sunagawa, Koji Umezawa, Takeshi Shimosato, Hiroshi Kagami, Tatsuya Morimoto and Tomohide Takaya
Int. J. Mol. Sci. 2023, 24(18), 14380; https://doi.org/10.3390/ijms241814380 - 21 Sep 2023
Cited by 2 | Viewed by 1978
Abstract
An 18-base myogenetic oligodeoxynucleotide (myoDN), iSN04, acts as an anti-nucleolin aptamer and induces myogenic differentiation of skeletal muscle myoblasts. This study investigated the effect of iSN04 on murine embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). In the undifferentiated state, iSN04 [...] Read more.
An 18-base myogenetic oligodeoxynucleotide (myoDN), iSN04, acts as an anti-nucleolin aptamer and induces myogenic differentiation of skeletal muscle myoblasts. This study investigated the effect of iSN04 on murine embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs). In the undifferentiated state, iSN04 inhibited the proliferation of ESCs and iPSCs but did not affect the expression of pluripotent markers. In the differentiating condition, iSN04 treatment of ESCs/iPSCs from day 5 onward dramatically induced differentiation into Nkx2-5+ beating cardiomyocytes with upregulation of Gata4, Isl1, and Nkx2-5, whereas iSN04 treatment from earlier stages completely inhibited cardiomyogenesis. RNA sequencing revealed that iSN04 treatment from day 5 onward contributes to the generation of cardiac progenitors by modulating the Wnt signaling pathway. Immunostaining showed that iSN04 suppressed the cytoplasmic translocation of nucleolin and restricted it to the nucleoli. These results demonstrate that nucleolin inhibition by iSN04 facilitates the terminal differentiation of cardiac mesoderm into cardiomyocytes but interferes with the differentiation of early mesoderm into the cardiac lineage. This is the first report on the generation of cardiomyocytes from pluripotent stem cells using a DNA aptamer. Since iSN04 did not induce hypertrophic responses in primary-cultured cardiomyocytes, iSN04 would be useful and safe for the regenerative therapy of heart failure using stem cell-derived cardiomyocytes. Full article
(This article belongs to the Special Issue Advanced Research on Nucleic Acids: Therapeutic Potential and Applications)
►▼ Show Figures

Figure 1

Figure 1
<p>iSN04 inhibits proliferation of undifferentiated miPSCs and mESCs. (<b>A</b>) Representative fluorescence images of 20D17 cells treated with 10 μM iSN04 in GM for 24 and 48 h. Scale bar, 200 μm. <span class="html-italic">Nanog</span>-GFP<sup>+</sup> colony size was quantified. * <span class="html-italic">p</span> &lt; 0.05 vs. control (Student’s <span class="html-italic">t</span>-test). <span class="html-italic">n</span> = 4 fields. (<b>B</b>) qPCR results of 20D17 cells treated with 10 μM iSN04 in GM for 48 h. <span class="html-italic">n</span> = 3. (<b>C</b>) Representative images of ALP staining of hCGp7 cells treated with 10 μM iSN04 in GM for 48 h. Scale bar, 200 μm. ALP<sup>+</sup> colony size was quantified. ** <span class="html-italic">p</span> &lt; 0.01 vs. control (Student’s <span class="html-italic">t</span>-test). <span class="html-italic">n</span> = 4 fields.</p> Full article ">Figure 2
<p>iSN04 induces myocardial differentiation of mESCs. (<b>A</b>) Representative fluorescence images of hCGp7 cells induced to differentiate in DM and treated with 10 μM iSN04 from day 5 to day 8 on 30 mm dishes. Scale bar, 200 μm. (<b>B</b>) hCGp7 cells induced to differentiate in DM and treated with 10 μM iSN04 from day 3, 4, 5, 6, or 7 on 96-well plates. Cumulative percentages of wells in which <span class="html-italic">Nkx2-5</span>-GFP<sup>+</sup> beating clusters were observed are shown. <span class="html-italic">n</span> = 10. (<b>C</b>) qPCR results of hCGp7 cells induced to differentiate in DM and treated with 10 μM iSN04 from day 3, 4, or 5 on 30 mm dishes. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. control on each day (Tukey-Kramer test). <span class="html-italic">n</span> = 3.</p> Full article ">Figure 3
<p>Experimental protocol of mESC differentiation and iSN04 treatment. hCGp7 cells were seeded on feeder-free gelatin-coated 30 mm dishes (3.0 × 10<sup>4</sup> cells/dish) or 96-well plates (2.0 × 10<sup>3</sup> cells/well) in DM (defined as day 0). DM (containing 10 μM iSN04 if necessary) was changed every two or three days. MC, medium change.</p> Full article ">Figure 4
<p>iSN04-dependent expression of mesodermal and cardiac genes in mESCs. RNA-seq results of hCGp7 cells induced to differentiate in DM and treated with 10 μM iSN04 from day 4 or 5 on 30 mm dishes (same samples as in <a href="#ijms-24-14380-f002" class="html-fig">Figure 2</a>C). FPKM values are displayed as expression levels.</p> Full article ">Figure 5
<p>Heatmap of the iSN04-dependent DEGs in mESCs. The DEGs and their subsets at day 6 (<b>A</b>) and day 7 (<b>B</b>) in hCGp7 cells induced to differentiate in DM and treated with iSN04 from day 4 or 5 on 30 mm dishes (same samples as in <a href="#ijms-24-14380-f002" class="html-fig">Figure 2</a>C) are shown with expression levels as Z-scores.</p> Full article ">Figure 6
<p>Hypothetical model of the effect of iSN04 on the Wnt signaling pathway during myocardial differentiation of PSCs. The genes investigated in this study are shown. β, β-catenin; ant, antagonist; nc, non-canonical.</p> Full article ">Figure 7
<p>iSN04 restricts nucleolin localization in mESCs during differentiation. Representative fluorescence images of nucleolin staining of hCGp7 cells induced to differentiate in DM and treated with 10 μM iSN04 from day 4 or 5 on 30 mm dishes. Scale bar, 25 μm.</p> Full article ">Figure 8
<p>iSN04 does not affect myocardial cell hypertrophy. Representative fluorescence images of α-actinin staining of rat cardiomyocytes induced hypertrophy using 30 μM PE and treated with 10 μM iSN04 for 48 h. Scale bar, 50 μm. α-actinin<sup>+</sup> cell surface area was quantified. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01 vs. saline with the same concentration of iSN04 (Scheffe’s <span class="html-italic">F</span> test). NS, no significant difference. <span class="html-italic">n</span> = 3 (200 cardiomyocytes in each experiment).</p> Full article ">
16 pages, 2123 KiB  
Article
A Decrease in Maternal Iron Levels Is the Predominant Factor Suppressing Hepcidin during Pregnancy in Mice
by Sheridan L. Helman, Sarah J. Wilkins, Jennifer C. J. Chan, Gunter Hartel, Daniel F. Wallace, Gregory J. Anderson and David M. Frazer
Int. J. Mol. Sci. 2023, 24(18), 14379; https://doi.org/10.3390/ijms241814379 - 21 Sep 2023
Viewed by 1052
Abstract
In order to supply adequate iron during pregnancy, the levels of the iron regulatory hormone hepcidin in the maternal circulation are suppressed, thereby increasing dietary iron absorption and storage iron release. Whether this decrease in maternal hepcidin is caused by changes in factors [...] Read more.
In order to supply adequate iron during pregnancy, the levels of the iron regulatory hormone hepcidin in the maternal circulation are suppressed, thereby increasing dietary iron absorption and storage iron release. Whether this decrease in maternal hepcidin is caused by changes in factors known to regulate hepcidin expression, or by other unidentified pregnancy factors, is not known. To investigate this, we examined iron parameters during pregnancy in mice. We observed that hepatic iron stores and transferrin saturation, both established regulators of hepcidin production, were decreased in mid and late pregnancy in normal and iron loaded dams, indicating an increase in iron utilization. This can be explained by a significant increase in maternal erythropoiesis, a known suppressor of hepcidin production, by mid-pregnancy, as indicated by an elevation in circulating erythropoietin and an increase in spleen size and splenic iron uptake. Iron utilization increased further in late pregnancy due to elevated fetal iron demand. By increasing maternal iron levels in late gestation, we were able to stimulate the expression of the gene encoding hepcidin, suggesting that the iron status of the mother is the predominant factor influencing hepcidin levels during pregnancy. Our data indicate that pregnancy-induced hepcidin suppression likely occurs because of reductions in maternal iron reserves due to increased iron requirements, which predominantly reflect stimulated erythropoiesis in mid-gestation and increased fetal iron requirements in late gestation, and that there is no need to invoke other factors, including novel pregnancy factor(s), to explain these changes. Full article
(This article belongs to the Section Molecular Endocrinology and Metabolism)
►▼ Show Figures

Figure 1

Figure 1
<p>Hepatic <span class="html-italic">Hamp</span> expression is suppressed in pregnancy and correlates with reduced transferrin saturation and iron stores. Non-iron-loaded and iron-loaded pregnant mice were examined at E12.5 or E18.5 and compared to age-matched nonpregnant mice to investigate the effect of pregnancy progression on hepatic <span class="html-italic">Hamp</span> expression (<b>A</b>), nonheme liver iron (<b>B</b>), hepatic <span class="html-italic">Bmp6</span> (<b>C</b>) and <span class="html-italic">Smad7</span> expression (<b>D</b>), serum iron (<b>E</b>) and transferrin saturation (<b>F</b>). Gene expression was calculated relative to the housekeeping gene <span class="html-italic">Hprt</span> and is expressed as a proportion of levels in the nonpregnant group. Data are expressed as mean ± SEM with the number of mice in each group indicated in parentheses along the <span class="html-italic">x</span>-axis. Statistically significant differences between groups were determined using one-way ANOVA followed by either Tukey or Games–Howell post-hoc testing, with <span class="html-italic">p</span> values indicated for each significantly different comparison. NP: nonpregnant mice; E12.5: pregnant mice studied at embryonic day 12.5; E18.5: pregnant mice studied at embryonic day 18.5; NPL: iron-loaded nonpregnant mice; E12.5L: iron-loaded pregnant mice studied at embryonic day 12.5; E18.5L: iron-loaded pregnant mice studied at embryonic day 18.5.</p> Full article ">Figure 2
<p>Erythropoietic activity is increased in pregnant mice by embryonic day 12.5. Non-iron-loaded and iron-loaded pregnant mice were examined at E12.5 or E18.5 and compared to age-matched nonpregnant mice to investigate the effect of pregnancy progression on hemoglobin (<b>A</b>), mean corpuscular volume (<b>B</b>), spleen weight (<b>C</b>), serum erythropoietin (<b>D</b>) and sTFR1 levels (<b>E</b>). Data are expressed as mean ± SEM with the number of mice in each group indicated in parentheses along the <span class="html-italic">x</span>-axis. Statistically significant differences between groups were determined using one-way ANOVA followed by either Tukey or Games–Howell post-hoc testing, with <span class="html-italic">p</span> values indicated for each significantly different comparison. NP: nonpregnant mice; E12.5: pregnant mice studied at embryonic day 12.5; E18.5: pregnant mice studied at embryonic day 18.5; NPL: iron-loaded nonpregnant mice; E12.5L: iron-loaded pregnant mice studied at embryonic day 12.5; E18.5L: iron-loaded pregnant mice studied at embryonic day 18.5.</p> Full article ">Figure 3
<p>Increased erythropoiesis at E12.5 correlates with <span class="html-italic">GypA</span> and <span class="html-italic">Erfe</span> mRNA expression in the spleen and bone marrow. Non-iron-loaded and iron-loaded pregnant mice were examined at E12.5 or E18.5 and compared to age-matched nonpregnant mice to investigate the effect of pregnancy progression on the expression of the erythrocyte marker <span class="html-italic">GypA</span> in the spleen (<b>A</b>) and bone marrow (<b>B</b>), the hepcidin suppressor <span class="html-italic">Erfe</span> in the spleen (<b>C</b>) and bone marrow (<b>D</b>). Gene expression was calculated relative to the housekeeping gene <span class="html-italic">Hprt</span> and is expressed as a proportion of levels in the nonpregnant group. Data are expressed as mean ± SEM with the number of mice in each group indicated in parentheses along the <span class="html-italic">x</span>-axis. Statistically significant differences between groups were determined using one-way ANOVA followed by either Tukey or Games–Howell post-hoc testing, with <span class="html-italic">p</span> values indicated for each significantly different comparison. NP: nonpregnant mice; E12.5: pregnant mice studied at embryonic day 12.5; E18.5: pregnant mice studied at embryonic day 18.5; NPL: iron-loaded nonpregnant mice; E12.5L: iron-loaded pregnant mice studied at embryonic day 12.5; E18.5L: iron-loaded pregnant mice studied at embryonic day 18.5.</p> Full article ">Figure 4
<p><span class="html-italic">Tfrc</span> expression is increased in the spleen and bone marrow at embryonic day 12.5 of pregnancy. Non-iron-loaded and iron-loaded pregnant mice were examined at E12.5 or E18.5 and compared to age-matched nonpregnant mice to investigate the effect of pregnancy progression on the expression of the iron uptake molecule <span class="html-italic">Tfrc</span> the spleen (<b>A</b>) and bone marrow (<b>B</b>). Gene expression was calculated relative to the housekeeping gene <span class="html-italic">Hprt</span> and is expressed as a proportion of levels in the nonpregnant group. Data are expressed as mean ± SEM with the number of mice in each group indicated in parentheses along the <span class="html-italic">x</span>-axis. Statistically significant differences between groups were determined using one-way ANOVA followed by either Tukey or Games–Howell post-hoc testing, with <span class="html-italic">p</span> values indicated for each significantly different comparison. NP: nonpregnant mice; E12.5: pregnant mice studied at embryonic day 12.5; E18.5: pregnant mice studied at embryonic day 18.5; NPL: iron-loaded nonpregnant mice; E12.5L,: iron-loaded pregnant mice studied at embryonic day 12.5; E18.5L: iron-loaded pregnant mice studied at embryonic day 18.5.</p> Full article ">Figure 5
<p>Iron uptake from the circulation is increased by embryonic day 12.5 of pregnancy. Non-iron-loaded pregnant mice were injected with <sup>55</sup>Fe at E12.5 or E18.5 and euthanized 2 h later to examine iron uptake in the entire spleen (<b>A</b>) and fetoplacental unit (<b>B</b>). Absolute values from the spleen and fetoplacental unit were then combined to produce a graph of the total uptake from these two organ systems (<b>C</b>) represented as a proportion of the amount of <sup>55</sup>Fe taken up by the spleen of nonpregnant mice. Data are expressed as mean ± SEM with the number of mice in each group indicated in parentheses along the <span class="html-italic">x</span>-axis. Statistically significant differences between groups were determined using one-way ANOVA followed by either Tukey or Games–Howell post-hoc testing, with <span class="html-italic">p</span> values indicated for each significantly different comparison. NP: nonpregnant mice; E12.5: pregnant mice studied at embryonic day 12.5; E18.5: pregnant mice studied at embryonic day 18.5.</p> Full article ">Figure 6
<p>Hepatic <span class="html-italic">Hamp</span> expression is induced in pregnant mice treated with iron. Hepatic iron stores in pregnant mice were increased by switching to a 0.1% carbonyl iron diet from E12.5 and circulating iron was elevated by intravenous iron at 2 and 4 h prior to euthanasia at E18.5 (<b>A</b>), as described in Methods. Control nonpregnant and pregnant mice were switched to the control diet and injected with saline only. Hepatic nonheme iron content (<b>B</b>), transferrin saturation (<b>C</b>), serum iron levels (<b>D</b>), the expression of hepatic <span class="html-italic">Hamp</span> (<b>E</b>) and <span class="html-italic">Bmp6</span> (<b>F</b>) and <span class="html-italic">Erfe</span> expression in the bone marrow (<b>G</b>) and spleen (<b>H</b>) were then determined for each animal. Gene expression was calculated relative to the housekeeping gene <span class="html-italic">Hprt</span> and is expressed as a proportion of levels in the nonpregnant group. Data are expressed as mean ± SEM with the number of mice in each group indicated in parentheses along the <span class="html-italic">x</span>-axis. Statistically significant differences between groups were determined using one-way ANOVA followed by either Tukey or Games–Howell post-hoc testing, with <span class="html-italic">p</span> values indicated for each significantly different comparison. NP: nonpregnant control mice; P: pregnant control mice; P + Fe: pregnant mice treated with iron.</p> Full article ">Figure 7
<p>Increasing maternal iron status in iron-loaded pregnant mice induces hepatic <span class="html-italic">Hamp</span> expression. Pregnant mice were iron-loaded by injection with iron dextran at E0.5. Hepatic iron stores in iron-loaded pregnant mice were increased by switching to a 0.5% carbonyl iron diet from E12.5 and circulating iron was elevated by intravenous iron at 2 and 4 h prior to euthanasia at E18.5 (<b>A</b>), as described in Methods. Control nonpregnant and pregnant mice were switched to the control diet and injected with saline only. Hepatic nonheme iron content (<b>B</b>), transferrin saturation (<b>C</b>), serum iron levels (<b>D</b>), the expression of hepatic <span class="html-italic">Hamp</span> (<b>E</b>) and <span class="html-italic">Bmp6</span> (<b>F</b>) and <span class="html-italic">Erfe</span> expression in the bone marrow (<b>G</b>) and spleen (<b>H</b>) were then determined for each animal. Gene expression was calculated relative to the housekeeping gene <span class="html-italic">Hprt</span> and is expressed as a proportion of levels in the nonpregnant group. Data are expressed as mean ± SEM with the number of mice in each group indicated in parentheses along the <span class="html-italic">x</span>-axis. Statistically significant differences between groups were determined using one-way ANOVA followed by either Tukey or Games–Howell post-hoc testing, with <span class="html-italic">p</span> values indicated for each significantly different comparison. NPL: nonpregnant iron-loaded control mice; PL: pregnant iron-loaded control mice; PL + Fe: pregnant iron-loaded mice treated with iron.</p> Full article ">
17 pages, 786 KiB  
Review
Assessment of Inflammatory Hematological Ratios (NLR, PLR, MLR, LMR and Monocyte/HDL–Cholesterol Ratio) in Acute Myocardial Infarction and Particularities in Young Patients
by Bogdan-Sorin Tudurachi, Larisa Anghel, Andreea Tudurachi, Radu Andy Sascău and Cristian Stătescu
Int. J. Mol. Sci. 2023, 24(18), 14378; https://doi.org/10.3390/ijms241814378 - 21 Sep 2023
Cited by 23 | Viewed by 3143
Abstract
Cardiovascular disease, particularly coronary artery disease (CAD), remains a predominant cause of mortality globally. Factors such as atherosclerosis and inflammation play significant roles in the pathogenesis of CAD. The nexus between inflammation and CAD is underscored by the role of immune cells, such [...] Read more.
Cardiovascular disease, particularly coronary artery disease (CAD), remains a predominant cause of mortality globally. Factors such as atherosclerosis and inflammation play significant roles in the pathogenesis of CAD. The nexus between inflammation and CAD is underscored by the role of immune cells, such as neutrophils, lymphocytes, monocytes, and macrophages. These cells orchestrate the inflammatory process, a core component in the initiation and progression of atherosclerosis. The activation of these pathways and the subsequent lipid, fibrous element, and calcification accumulation can result in vessel narrowing. Hematological parameters derived from routine blood tests offer insights into the underlying inflammatory state. Recent studies have highlighted the potential of inflammatory hematological ratios, such as the neutrophil/lymphocyte ratio, platelet/lymphocyte ratio, monocyte/lymphocyte ratio and lymphocyte/monocyte ratio. These parameters are not only accessible and cost-effective but also mirror the degree of systemic inflammation. Several studies have indicated a correlation between these markers and the severity, prognosis, and presence of CAD. Despite the burgeoning interest in the relationship between inflammatory markers and CAD, there remains a paucity of data exploring these parameters in young patients with acute myocardial infarction. Such data could offer valuable insights into the unique pathophysiology of early-onset CAD and improve risk assessment and predictive strategies. Full article
(This article belongs to the Special Issue Molecular Biomarkers in Cardiovascular Disease)
►▼ Show Figures

Figure 1

Figure 1
<p>The role of monocytes, neutrophils and lymphocytes in atherosclerotic plaque formation. A, B: Activated endothelial cells produce chemoattractants and adhesion molecules that draw in monocytes. The binding of inflammatory chemoattractants by monocytes from the blood promotes their chemotaxis to the atherosclerotic endothelium; C, D: Inflammatory monocytes then move intima by adhering to the atherosclerotic endothelium; E: Once reaching the location of the lesion, monocytes differentiate into macrophages, which further contribute to inflammation. Ingesting cholesterol causes these cell types to develop into foam cells, thus contributing to the formation of atherosclerotic plaque. Although these macrophages initially help by removing these lipoproteins from the subendothelium, with time the macrophages become engorged with lipids, which leads to dysregulated lipid metabolism. These foam cells eventually experience apoptosis and necrosis, and if they are not removed effectively by M2 macrophages through efferocytosis, they will release their toxic and pro-inflammatory contents into the subendothelial space. This will further encourage cell death and inflammation, the development of the necrotic core and further increase the vulnerability of the plaque. The plaque is susceptible to rupture when the fibrous cover thins and the necrotic core expands, which might cause a thrombosis or other acute cardiovascular event. F: Endothelial cell lesions result from the breakdown of the basement membrane by neutrophilic MMP, MPO and ROS. G: Neutrophils produce chemoattractant for monocytes. H: NETs complexes trigger macrophages to release the proinflammatory cytokine. NETosis, a cell death mechanism distinct from apoptosis or necrosis, is the method by which these chromatin complexes are released from neutrophil nuclei. NETosis enables neutrophils to destroy infections more effectively by creating a mechanical barrier to “trap” germs. I: Neutrophils block the tissue factor plasminogen inhibitor, which causes thrombus to develop. J: Neutrophils that have been activated produce NETs complexes, which promote thrombus development. K: T lymphocyte responses are induced by APCs such as macrophages, DCs and B cells. There are many subsets of naive CD4+ T helper (Th) cells, and stimulatory chemicals in fact encourage T cells to express transcription factors that result in differentiation into Th phenotypes. Both pro-atherogenic and atheroprotective properties may be seen in CD4+ T cells. Th1, Th2, Th9, Th17, Th22, Treg and follicular helper T (TFH) cells may be detected in atherosclerotic lesions. By releasing IFN-γ, interleukins, TGF-β and protease, these lymphocytes promote inflammation, endothelial cell death, plaque cell apoptosis, monocytic migration, and thus the development of atherosclerotic plaques, foam cells and atherosclerotic plaque rupture. Type I NKT cells may stimulate immune cells in plaque by secreting cytokines and accelerating the development of atherosclerosis. The cytotoxic effects of CD8+ T cells, in contrast with lesion-stabilizing cells and the generation of inflammatory cytokines by CD8+ T cells, may worsen the growth and instability of lesions by escalating inflammatory reactions in plaques of atherosclerosis. L. White blood cells of the lymphocyte subtype known as B cells, or B lymphocytes, are classified into two separate groups (B1 and B2). By secreting antibodies, B cells are essential to the humoral immunity part of the adaptive immune system. B cells also present antigens, which are classified as expert APCs, and release cytokines. B lymphocytes, which aid in the development of lymphoid follicles, may contribute to atherosclerosis. At all phases of the disease’s development, IgG and IgM antibodies may be found in atherosclerotic plaques. Ox-LDL—oxidized low-density lipoprotein; TFPI—tissue factor plasminogen inhibitor; MMP—matrix metalloproteinases; MPO—myeloperoxidase; ROS—reactive oxygen species; NETs—neutrophil extracellular traps; APCs—antigen-presenting cell; DCs—dendritic cells; IFN-γ—interferon gamma; TGF-β—transforming growth factor beta; NKT—natural killer T; IgG—immunoglobulin G; IgM—immunoglobulin M. There are some potential factors that may influence the inflammatory hematological ratios.</p> Full article ">
18 pages, 2720 KiB  
Article
Slowed Intestinal Transit Induced by Less Mucus in Intestinal Goblet Cell Piezo1-Deficient Mice through Impaired Epithelial Homeostasis
by Feifei Fang, Ying Liu, Yilin Xiong, Xueyan Li, Gangping Li, Yudong Jiang, Xiaohua Hou and Jun Song
Int. J. Mol. Sci. 2023, 24(18), 14377; https://doi.org/10.3390/ijms241814377 - 21 Sep 2023
Cited by 1 | Viewed by 1380
Abstract
Mucus secreted by goblet cells (GCs) may play an important role in intestinal transit function. Our previous study found that Piezo1 protein is essential for GC function; however, the effect of GC Piezo1 on intestinal transit function is unclear. Our study aimed to [...] Read more.
Mucus secreted by goblet cells (GCs) may play an important role in intestinal transit function. Our previous study found that Piezo1 protein is essential for GC function; however, the effect of GC Piezo1 on intestinal transit function is unclear. Our study aimed to investigate the effect of Piezo1 in GCs on intestinal transit and the potential mechanism. We compared intestinal mucus, fecal form, intestinal transit time, intestinal epithelial cell composition, and stem cell function in WT and GC-specific Piezo1-deficient (Piezo1ΔGC) mice. Our results revealed a correlation between mucus and intestinal transit: the less mucus there was, the slower the intestinal transit. Piezo1 deficiency in GCs led to decreased mucus synthesis and also disrupted the ecological niche of colon stem cells (CSCs). Through organoid culture, we found that the capacity of proliferation and differentiation in Piezo1ΔGC mouse CSCs was significantly decreased, which also led to a reduced source of GCs. Further studies found that the reduced Wnt and Notch signals in colon crypts might be the potential mechanism. These results indicated the importance of GC Piezo1 in intestinal transit function, which acts by maintaining the homeostasis of intestinal epithelial cells and mucus. Full article
(This article belongs to the Special Issue Gastrointestinal Diseases: Molecular Mechanism, Diagnostics, and Novel Therapeutic Approaches)
►▼ Show Figures

Figure 1

Figure 1
<p>Identification of Piezo1<sup>ΔGC</sup> mice. (<b>A</b>) Immunofluorescence co-localization of Piezo1 and Agr2 (label goblet cells) in WT and Piezo1<sup>ΔGC</sup> mouse colons. The yellow box shows a magnified localized image. Scale bar: 100 μm. (<b>B</b>) mRNA level of <span class="html-italic">Piezo1</span> in WT and Piezo1<sup>ΔGC</sup> mouse colon crypts (normalized to <span class="html-italic">GAPDH</span>). At least three independent experiments were conducted. Data are expressed as the mean ± SEM. (<span class="html-italic">n</span> = 5 mice). ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 2
<p>Decreased GC numbers and thinner mucus layer in Piezo1<sup>ΔGC</sup> mouse colons. (<b>A</b>) Immunofluorescence staining of Agr2 in WT and Piezo1<sup>ΔGC</sup> mouse colons. Scale bar: 100 μm. The crypt was divided equally into three parts: upper, middle, and base. The white arrow indicates a goblet cell. (<b>B</b>) Statistical analysis of goblet cells/epithelial cells in (<b>A</b>). (<b>C</b>) Statistical analysis of goblet cells in different parts/epithelial cells in (<b>A</b>). (<b>D</b>) RNA level of <span class="html-italic">Mucin2</span> in colon tissues from WT and Piezo1<sup>ΔGC</sup> mice (normalized to <span class="html-italic">GAPDH</span>). (<b>E</b>) AB-PAS staining of mucus in WT and Piezo1<sup>ΔGC</sup> mouse colons. The red arrows indicate the mucus layer. Scale bar: 50 μm. (<b>F</b>) Statistical analysis of mucus layer thickness in (<b>D</b>). At least three independent experiments were conducted. Data are expressed as the mean ± SEM. (<span class="html-italic">n</span> = 5 mice). ns, not significant; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 3
<p>Decreased fecal excretion and thinning mucus layer on fecal pellet surface in Piezo1<sup>ΔGC</sup> mice. (<b>A</b>,<b>B</b>) Fecal pellets excreted (<b>A</b>) and their number (<b>B</b>) in 3 h from WT and Piezo1<sup>ΔGC</sup> mice. (<b>C</b>,<b>E</b>) Dry weight (<b>C</b>), wet weight (<b>D</b>), and water content (<b>E</b>) of feces excreted by WT and Piezo1<sup>ΔGC</sup> mice in 3 h. (<b>F</b>) AB-PAS staining of mucus in and on the fecal pellet surface of WT and Piezo1<sup>ΔGC</sup> mice. The fecal pellet from the distal colon was wrapped in the abdominal muscle. Scale bar: 100 μm. (<b>G</b>) Statistics analysis of mucus layer thickness in (<b>F</b>). At least three independent experiments were conducted. Data are expressed as the mean ± SEM. (<span class="html-italic">n</span> = 5 mice). ns, not significant; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 4
<p>Prolonged gastrointestinal transit time in the Piezo1<sup>ΔGC</sup> mice correlates with intestinal mucus thickness. (<b>A</b>–<b>C</b>) Intestinal transit-related parameters of WT and Piezo1<sup>ΔGC</sup> mice: the gastrointestinal transit time (<b>A</b>), the distal colonic transit time (<b>B</b>), and the small intestinal transit rate (<b>C</b>). (<b>D</b>) Line regression of mucus thickness and gastrointestinal transit time. (<b>E</b>) Line regression of mucus thickness on fecal pellet surface and gastrointestinal transit time. (<b>F</b>,<b>G</b>) The AWR score and pain threshold measured by colorectal distension (CRD) test in the WT and Piezo1<sup>ΔGC</sup> mice. At least three independent experiments were conducted. Data are expressed as the mean ± SEM. (<span class="html-italic">n</span> = 5 mice). ns, not significant; ** <span class="html-italic">p</span> &lt; 0.01.</p> Full article ">Figure 5
<p>Abnormal colonic development in the Piezo1<sup>ΔGC</sup> mice. (<b>A</b>) Gross image of colons from the WT and Piezo1<sup>ΔGC</sup> mice. (<b>B</b>) Lengths of colons in the WT and Piezo1<sup>ΔGC</sup> mice. (<b>C</b>) H&amp;E staining of colon tissues in WT and Piezo1<sup>ΔGC</sup> mice. Scale bar: 100 μm. (<b>D</b>) Depth of colon crypt in the WT and Piezo1<sup>ΔGC</sup> mice. (<b>E</b>) The thickness of the colonic wall in the WT and Piezo1<sup>ΔGC</sup> mice. At least three independent experiments were conducted. Data are expressed as the mean ± SEM. (<span class="html-italic">n</span> = 7 mice). * <span class="html-italic">p</span> &lt; 0.05.</p> Full article ">Figure 6
<p>Abnormal intestinal epithelial cell composition and impaired colon stem cell niche in Piezo1<sup>ΔGC</sup> mice. (<b>A</b>) RNA levels of <span class="html-italic">Ki67</span> and stem cell markers (<span class="html-italic">Lgr5</span>, <span class="html-italic">Sox9</span>, and <span class="html-italic">EphB2</span>) in WT and Piezo1<sup>ΔGC</sup> mouse colon crypts (normalized to <span class="html-italic">GAPDH</span>). (<b>B</b>) Immunohistochemistry of Ki67 in WT and Piezo1<sup>ΔGC</sup> mouse colons. Scale bar: 100 μm. (<b>C</b>) Statistical analysis of Ki67 positive cell ratio in (<b>B</b>). (<b>D</b>) RNA levels of stem cell niche marker (<span class="html-italic">cKit</span>), differentiated colonocyte marker (<span class="html-italic">Alpi</span>), goblet cell marker (<span class="html-italic">Agr2</span>), and enteroendocrine cell marker (<span class="html-italic">Chga</span>) in WT and Piezo1<sup>ΔGC</sup> mouse colon crypts (normalized to <span class="html-italic">GAPDH</span>). (<b>E</b>) Immunohistochemistry of cKit in WT and Piezo1<sup>ΔGC</sup> mouse colons. The white dashed lines mark the crypt borders, and the red arrow indicates a cKit-positive cell. Scale bar: 50 μm. (<b>F</b>) Statistical analysis of cKit-positive cell ratio in (<b>E</b>). (<b>G</b>,<b>H</b>) Immunofluorescence staining of Alpi (<b>G</b>) and Chga (<b>H</b>) in WT and Piezo1<sup>ΔGC</sup> mouse colons. The white dashed lines mark crypt borders, and the white arrow indicates a differentiated colonocyte in (<b>G</b>) and an enteroendocrine cell in (<b>H</b>). Scale bar: 25 μm. (<b>I</b>,<b>J</b>) Statistical analysis of differentiated colonocyte ratio in (<b>G</b>) and enteroendocrine cell ratio in (<b>H</b>). At least three independent experiments were conducted. Data are presented as the mean ± SEM. (<span class="html-italic">n</span> = 5 mice). ns, not significant; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 7
<p>Decreased self-renewal capacity of colon stem cells from Piezo1<sup>ΔGC</sup> mice. (<b>A</b>) Representative images of colonoids from WT and Piezo1<sup>ΔGC</sup> mice at day 5. Images of one colonoid on day 1, 3, and 5 are below, reflecting the growth process of a colonoid. Scale bar: 100 μm. (<b>B</b>–<b>D</b>) Indicators related to colonoids growth: number of buds per colonoid (<b>B</b>), surface area per colonoid (<b>C</b>), and percentage of colonoids with buds per well (<b>D</b>). (<b>E</b>) Immunofluorescence staining of EDU and Ki67 in colonoids from WT and Piezo1<sup>ΔGC</sup> mice. Scale bar: 100 μm. (<b>F</b>) Statistical analysis of EDU and Ki67 positive cell ratio in (<b>E</b>). (<b>G</b>) Immunofluorescence staining of differentiated colonocyte (Alpi), goblet cell (Agr2), and enteroendocrine cell (Chga) in colonoids from WT and Piezo1<sup>ΔGC</sup> mice. Scale bar: 100 μm. (<b>H</b>) Statistical analysis of Alpi, Agr2, and Chga positive cell ratio in (<b>G</b>). (<b>I</b>) RNA levels of <span class="html-italic">Ki67</span> from WT and Piezo1<sup>ΔGC</sup> mouse colonoids (normalized to <span class="html-italic">GAPDH</span>). (<b>J</b>) AB-PAS staining of colonoids from WT and Piezo1<sup>ΔGC</sup> mice. The red arrows indicate mucus secreted by goblet cells in colonoids. Scale bar: 100 μm. At least three independent experiments were conducted. Data are presented as the mean ± SEM. (<span class="html-italic">n</span> = 5 mice). ns, not significant; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 8
<p>Reshaped Wnt and Notch signaling expression in Piezo1<sup>ΔGC</sup> mouse colon crypts lead to reduced GCs. (<b>A</b>) Volcano plot depicting the differentially expressed genes between Piezo1-knockdown and Control LS174T cells (determined via RNA-Seq). The genes were selected via |Log2 (Fold Change)| &gt; 1 and <span class="html-italic">p</span>-value &lt; 0.05. The gray dots indicate genes with no significant difference between the two groups. (<b>B</b>) KEGG analysis of differentially expressed genes. The interested KEGG terms are marked in red. The threshold for significance was <span class="html-italic">p</span>-value &lt; 0.05. (<b>C</b>,<b>D</b>) RNA levels of Wnt and Notch signaling pathway target genes in WT and Piezo1<sup>ΔGC</sup> mouse colon crypts (normalized to <span class="html-italic">GAPDH</span>). (<b>E</b>,<b>F</b>) RNA levels of Foxo and Hippo signaling pathway key genes in WT and Piezo1<sup>ΔGC</sup> mouse colon crypts (normalized to <span class="html-italic">GAPDH</span>). Data are presented as the mean ± SEM. (<b>A</b>, <span class="html-italic">n</span> = 3; <b>C</b>–<b>F</b>, <span class="html-italic">n</span> = 5 mice). ns, not significant; * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">
16 pages, 3255 KiB  
Article
Resistant and Susceptible Pinus thunbergii ParL. Show Highly Divergent Patterns of Differentially Expressed Genes during the Process of Infection by Bursaphelenchus xylophilus
by Tingyu Sun, Mati Ur Rahman, Xiaoqin Wu and Jianren Ye
Int. J. Mol. Sci. 2023, 24(18), 14376; https://doi.org/10.3390/ijms241814376 - 21 Sep 2023
Cited by 2 | Viewed by 1144
Abstract
Pine wilt disease (PWD) is a devastating disease that threatens pine forests worldwide, and breeding resistant pines is an important management strategy used to reduce its impact. A batch of resistant seeds of P. thunbergii was introduced from Japan. Based on the resistant [...] Read more.
Pine wilt disease (PWD) is a devastating disease that threatens pine forests worldwide, and breeding resistant pines is an important management strategy used to reduce its impact. A batch of resistant seeds of P. thunbergii was introduced from Japan. Based on the resistant materials, we obtained somatic plants through somatic embryogenesis. In this study, we performed transcriptome analysis to further understand the defense response of resistant somatic plants of P. thunbergii to PWD. The results showed that, after pine wood nematode (PWN) infection, resistant P. thunbergii stimulated more differential expression genes (DEGs) and involved more regulatory pathways than did susceptible P. thunbergii. For the first time, the alpha-linolenic acid metabolism and linoleic acid metabolism were intensively observed in pines resisting PWN infection. The related genes disease resistance protein RPS2 (SUMM2) and pathogenesis-related genes (PR1), as well as reactive oxygen species (ROS)-related genes were significantly up-expressed in order to contribute to protection against PWN inoculation in P. thunbergii. In addition, the diterpenoid biosynthesis pathway was significantly enriched only in resistant P. thunbergii. These findings provided valuable genetic information for future breeding of resistant conifers, and could contribute to the development of new diagnostic tools for early screening of resistant pine seedlings based on specific PWN-tolerance-related markers. Full article
(This article belongs to the Special Issue Advances in Plant Breeding and Resistance)
►▼ Show Figures

Figure 1

Figure 1
<p>Comparison of DEGs between susceptible and resistant <span class="html-italic">P. thunbergii</span> at different disease stages. (<b>A</b>,<b>B</b>) indicated the number of DEGs obtained in susceptible and resistant <span class="html-italic">P. thunbergii</span> at infection stages, respectively. (<b>C</b>,<b>D</b>) indicated the number and overlapping relationships of DEGs in venn diagram between susceptible and resistant <span class="html-italic">P. thunbergii</span> at different infection stages, respectively.</p> Full article ">Figure 2
<p>Enriched biological processes in DEGs by GO annotation for susceptible and resistant <span class="html-italic">P. thunbergii</span> at different infection stages. (<b>A</b>) indicated GO annotation of susceptible and resistant <span class="html-italic">P. thunbergii</span> at first infection stage (1d vs 3d). (<b>B</b>) indicated GO annotation of susceptible and resistant <span class="html-italic">P. thunbergii</span> at second infection stage (3d vs 7d).</p> Full article ">Figure 3
<p>qRT-PCR validation of selected transcripts for validation. Relative expression levels of qRT-PCR are calculated using elongation factor 1-alpha as the internal control. The data are expressed as the mean (±SE). Error bars represent the SE.</p> Full article ">Figure 4
<p>DEGs involved in alpha-linolenic acid metabolism and linoleic acid metabolism in <span class="html-italic">P. thunbergii</span>. (<b>A</b>) indicated linoleic acid metabolism pathway. (<b>B</b>) indicated alpha-linolenic acid metabolism pathway. Enzymes involved in each step are shown in purple, and the green boxes represent DEGs encoding enzyme activity. R represents resistant <span class="html-italic">P. thunbergii</span>. S represents susceptible <span class="html-italic">P. thunbergii</span>. R1 represents the first stage of the resistant <span class="html-italic">P. thunbergii</span> inoculated with PWN (1 d vs. 3 d). S2 represents the second stage of susceptible <span class="html-italic">P. thunbergii</span> inoculated with PWN (3 d vs. 7 d). <span class="html-italic">LOX1-5</span> (E5.5.1.13) represents <span class="html-italic">lindoleate 9S-lipoxygenase</span>. <span class="html-italic">LOX2S</span> (E1.14.11.13) represents <span class="html-italic">lipoxygenase</span>. <span class="html-italic">AOS</span> represents <span class="html-italic">hydroperoxide dehydratase</span>. <span class="html-italic">OPR</span> represents <span class="html-italic">12-oxophytodienoic acid reductase</span>. <span class="html-italic">ADH1</span> represents <span class="html-italic">alcohol dehydrogenase class-P</span>, E2.2.1.141 represents <span class="html-italic">jasmonate O-methyltransferase</span>.</p> Full article ">Figure 5
<p>The expression of partial DEGs in “MAPK signaling pathway—plant” and “biosynthesis of various secondary metabolites—part 2” pathways. (<b>A</b>,<b>B</b>) The expression of DEGs in the “MAPK signaling pathway—plant” in susceptible and PWN-resistant <span class="html-italic">P. thunbergii</span>, respectively. (<b>C</b>,<b>D</b>) Expression of DEGs in “biosynthesis of various secondary metabolites—part 2” in susceptible and PWN-resistant <span class="html-italic">P. thunbergii</span>, respectively. S1 represents the 1st stage (1 d vs. 3 d) of PWN infection in susceptible <span class="html-italic">P. thunbergii</span>. S2 represents the 2nd stage (3 d vs. 7 d) of PWN infection in susceptible <span class="html-italic">P. thunbergii</span>. R1 represents the 1st stage (1d vs. 3d) of PWN infection in resistant <span class="html-italic">P. thunbergii</span>. R2 represents the 2nd stage (3 d vs. 7 d) of PWN infection in resistant <span class="html-italic">P. thunbergii</span>. * and ** indicate significant differences at <span class="html-italic">p</span> &lt; 0.05 and <span class="html-italic">p</span> &lt; 0.01, respectively. *** indicate significant differences at <span class="html-italic">p</span> &lt; 0.001.</p> Full article ">Figure 6
<p>DEGs involved in diterpenoid biosynthesis in the stem of <span class="html-italic">P. thunbergii</span>. (<b>A</b>) indicates the number of DEG terpenoid types. (<b>B</b>) indicated diterpenoid biosynthesis pathway. Enzymes involved in each step are shown in purple, and the green boxes represent DEGs encoding enzyme activity. R represents resistant <span class="html-italic">P. thunbergii</span>. S represents susceptible <span class="html-italic">P. thunbergii</span>. R1 represents the first stage of the resistant <span class="html-italic">P. thunbergii</span> inoculated with PWN (1 d vs. 3 d). S1 represents the first stage of the susceptible <span class="html-italic">P. thunbergii</span> inoculation with PWN (1 d vs. 3 d). S2 represents the second stage of susceptible <span class="html-italic">P. thunbergii</span> inoculated with PWN (3 d vs. 7 d). E5.5.1.13 represents <span class="html-italic">ent-copalyl diphosphate synthase</span>. E3.1.7.10 represents <span class="html-italic">(13E)-labda-7,13-dien-15-ol synthase</span>. E1.14.11.13 represents <span class="html-italic">gibberellin 2beta-dioxygenase</span>.</p> Full article ">
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-738
Previous Issue
Next Issue
Back to TopTop