[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

Article Types

Countries / Regions

Search Results (45)

Search Parameters:
Keywords = duox

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
13 pages, 1644 KiB  
Article
Newborn Genetic Screening Improves the Screening Efficiency for Congenital Hypothyroidism: A Prospective Multicenter Study in China
by Liang Ye, Yinhong Zhang, Jizhen Feng, Cidan Huang, Xiaohua Wang, Lianshu Han, Yonglan Huang, Hui Zou, Baosheng Zhu and Jingkun Miao
Int. J. Neonatal Screen. 2024, 10(4), 78; https://doi.org/10.3390/ijns10040078 - 29 Nov 2024
Viewed by 692
Abstract
Newborn congenital hypothyroidism (CH) screening has been widely used worldwide. The objective of this study was to evaluate the effectiveness of applying biochemical and gene panel sequencing as screening tests for CH and to analyze the mutation spectrum of CH in China. Newborns [...] Read more.
Newborn congenital hypothyroidism (CH) screening has been widely used worldwide. The objective of this study was to evaluate the effectiveness of applying biochemical and gene panel sequencing as screening tests for CH and to analyze the mutation spectrum of CH in China. Newborns were prospectively recruited from eight hospitals in China between February and December 2021. Clinical characteristics were collected. Second-generation sequencing was used to detect four CH-related genes, and the genetic patterns of the pathogenic genes were analyzed. We analyzed the relationship between genotype and biochemical phenotype. A total of 29,601 newborns were screened for CH. Gene panel sequencing identified 18 patients, including 10 patients affected by biochemically and genetically screened disorders and 8 patients affected by solely genetically screened disorders. The predictive positive value of genetic screening was 34.62%, which was much greater than that of biochemical screening alone (17.99%). A total of 94 cases of congenital thyroid dysfunction were confirmed by biochemical and genetic screening, including 30 CHs and 64 isolated hyperthyrotropinemia (HTT), with an incidence of 1/987 for CH and 1/463 for HTT, and a total incidence of 1/315 for hypothyroidism. The incidence rate and number of patients in Jinan were the highest, and the incidence rates in Shijiazhuang and Shanghai were the lowest. The gene mutation rate in this study was 19.1%, mainly DUOX2 mutation. The most common variant of DUOX2 was c.1588A>T(p.Lys530*). There was only a difference in sFT4 between groups with gene mutations and those without mutations. Genetic screening is a supplement to biochemical screening. Combining biochemical screening with genetic screening is useful for improving screening efficiency. The incidence of CH in China according to a multicenter study of nearly 30,000 NBS surveys was 1/315. DUOX2 gene mutations are commonly detected in these patients. Full article
(This article belongs to the Special Issue Newborn Screening for Congenital Hypothyroidism)
Show Figures

Figure 1

Figure 1
<p>The screening and diagnosis process of CH. CH, congenital hypothyroidism; HTT, isolated hyperthyrotropinemia; ULN, upper limit of normal value; TSH, thyroid stimulating hormone.</p>
Full article ">Figure 2
<p>Mutation sites in the secondary structure of <span class="html-italic">DUOX2</span>. Sixteen mutation sites distributed in the secondary structure of <span class="html-italic">DUOX2</span> protein. <span class="html-italic">DUOX2</span> contains 5 functional domains, peroxidase-like domain, EF-hand domain, Interaction with TXNDC11 domain, ferric oxidoreductase domain, and FAD-binding FR-type domain.</p>
Full article ">Figure 3
<p>Comparison of serum levels of screening TSH, diagnostic TSH and FT4 among different groups, classified according to clinical phenotype. (<b>A</b>) Comparison of TSH levels in dry blood spots between patients with CH and HTT. (<b>B</b>) Comparison of TSH levels in serum between patients with CH and HTT. (<b>C</b>) Comparison of FT4 levels in serum between patients with CH and HTT. CH, Congenital hypothyroidism; HTT, isolated hyperthyrotropinemia; ***<span class="html-italic">* p</span>  &lt;  0.0001.</p>
Full article ">Figure 4
<p>Comparison of serum levels of screening TSH, diagnostic TSH and FT4 among different groups, classified according to whether there is a gene variation. (<b>A</b>) Comparison of TSH levels in dry blood spots between patients with no mutation, and mutation. (<b>B</b>) Comparison of TSH levels in serum between patients with no mutation, and mutation. (<b>C</b>) Comparison of FT4 levels in serum between patients with no mutation, and mutation. ns, <span class="html-italic">p</span>  &gt;  0.05; ** <span class="html-italic">p</span>  &lt;  0.01.</p>
Full article ">
14 pages, 3635 KiB  
Article
17β-Estradiol Stimulates Oxidative Stress Components and Thyroid Specific Genes in Porcine Thyroid Follicular Cells: Potential Differences Between Sexes
by Jan Stępniak and Małgorzata Karbownik-Lewińska
Cells 2024, 13(21), 1769; https://doi.org/10.3390/cells13211769 - 25 Oct 2024
Viewed by 641
Abstract
17β-estradiol plays a crucial role in regulating cellular processes in both reproductive and non-reproductive tissues, including the thyroid gland. It modulates oxidative stress and contributes to sexual dimorphism in thyroid diseases, with ROS production, particularly H2O2, generated by NOX/DUOX [...] Read more.
17β-estradiol plays a crucial role in regulating cellular processes in both reproductive and non-reproductive tissues, including the thyroid gland. It modulates oxidative stress and contributes to sexual dimorphism in thyroid diseases, with ROS production, particularly H2O2, generated by NOX/DUOX enzymes. This study aimed to investigate the effects of 17β-estradiol (10 nM or 100 nM) on the expression of NOX/DUOX, thyroid-specific genes, and endoplasmic reticulum (ER) stress-related genes in male and female porcine thyroid follicular cells. Expression of the studied genes was evaluated by RT-PCR before and after treatment with 17β-estradiol alone or with the addition of NOX4 inhibitor (GKT-136901). Additionally, the level of ROS was measured by flow cytometry analysis. Our results show that 17β-estradiol significantly upregulates thyroid-specific genes, particularly TPO, and stimulates NOX/DUOX expression, affecting the redox state of thyroid cells. It also stimulates ER stress-related genes such as CHOP. In conclusion, estrogen excess may contribute to thyroid disease development via such possible mechanisms as the upregulation of key thyroid-specific genes, particularly TPO, and of genes involved in the cellular response to ER stress, especially CHOP, as well as by the stimulation of the NOX/DUOX system with consequent ROS overproduction. These mechanisms may play a certain role in the higher prevalence of thyroid diseases in women. Full article
(This article belongs to the Section Cellular Metabolism)
Show Figures

Figure 1

Figure 1
<p>log2 fold change representing the mRNA expression of NOX4, DUOX1, and DUOX2 in cells derived from male or female porcine thyroid. Cells were incubated with 17β-estradiol at concentrations of 0.0 nM, 10 nM, or 100 nM. mRNA expression was calculated relative to the untreated control cells. Bars represent the mean ± SE of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. respective control, i.e., without 17β-estradiol (fold change equal to “0”).</p>
Full article ">Figure 2
<p>log2 fold change representing the mRNA expression of NOX4, DUOX1, and DUOX2 in female porcine thyroid cells relative to male porcine thyroid cells. Cells were incubated with 17β-estradiol at concentrations of 0.0 nM, 10 nM, or 100 nM. Bars indicate the mean ± SE of three independent experiments.</p>
Full article ">Figure 3
<p>The level of ROS in cells derived from male or female porcine thyroid. Cells were incubated after the addition of 17β-estradiol (0.0 nM, 10 nM, or 100 nM) with or without GKT-136901 (20 µM). The level of ROS was evaluated by flow cytometry analysis with the use of CellROX™ Orange Reagent and was expressed relative to the untreated control group. Bars represent the mean ± SE of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. respective control (without 17β-estradiol).</p>
Full article ">Figure 4
<p>The level of ROS in cells derived from male and female porcine thyroid. Cells were incubated after the addition of 17β-estradiol (0.0 nM, 10 nM, or 100 nM) with or without GKT-136901 (20 µM). The level of ROS was evaluated by flow cytometry analysis with the use of CellROX™ Orange Reagent and was expressed relative to the respective male groups.</p>
Full article ">Figure 5
<p>log2 fold change signifying the mRNA expression of thyroid-specific genes in cells derived from male and female porcine thyroid. Cells were incubated with 17β-estradiol at concentrations of 0.0 nM, 10 nM, or 100 nM, with or without GKT-136901 (20 µM). mRNA expression was calculated relative to the untreated control cells. Bars represent the mean ± SE of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. respective control (without 17β-estradiol).</p>
Full article ">Figure 6
<p>log2 fold change representing the mRNA expression of thyroid-specific genes in female porcine thyroid cells relative to male porcine thyroid cells. Cells were incubated with 17β-estradiol at concentrations of 0.0 nM, 10 nM, or 100 nM, with or without GKT-136901 (20 µM). Bars represent the mean ± SE of three independent experiments.</p>
Full article ">Figure 7
<p>log2 fold change representing the mRNA expression of genes related to ER stress/UPR initiation in cells derived from male and female porcine thyroid. Cells were incubated with 17β-estradiol at concentrations of 0.0 nM, 10 nM, or 100 nM, with or without GKT-136901 (20 µM). mRNA expression was calculated relative to the untreated control cells. Bars represent the mean ± SE of three independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. respective control (without 17β-estradiol).</p>
Full article ">Figure 8
<p>log2 fold change representing the mRNA expression of genes related to ER stress/UPR initiation in female porcine thyroid cells relative to male porcine thyroid cells. Cells were incubated with 17β-estradiol at concentrations of 0.0 nM, 10 nM, or 100 nM, with or without GKT-136901 (20 µM). Bars represent the mean ± SE of three independent experiments.</p>
Full article ">
12 pages, 633 KiB  
Review
Ciliary Function, Antigen Stasis and Asthma
by Nadzeya Marozkina
Int. J. Mol. Sci. 2024, 25(18), 10043; https://doi.org/10.3390/ijms251810043 - 18 Sep 2024
Viewed by 847
Abstract
The prevalence of asthma exceeds 3% of the population. Asthma is observed to be more common in children following severe viral lower respiratory illnesses that affect ciliary function, but mechanisms linking ciliary function to asthma pathogenesis have been obscure. Recent data regarding primary [...] Read more.
The prevalence of asthma exceeds 3% of the population. Asthma is observed to be more common in children following severe viral lower respiratory illnesses that affect ciliary function, but mechanisms linking ciliary function to asthma pathogenesis have been obscure. Recent data regarding primary ciliary dyskinesia (PCD) may help us to understand the association. Here, I will review what is known about the relationship between ciliary function and asthma. PCD is caused by pathologic variants in over 50 different genes that affect the structure and function of motile cilia. At the cellular level, a characteristic feature shared by most PCD patients is that antigens and other particles are not cleared from the epithelial surface. Poor antigen clearance results in pro-oxidant pathway activation and airway epithelial damage and may predispose PCD patients to DUOX1- and IL33-mediated asthma. Secondary ciliary dysfunction, such as that caused by viruses or by smoking, can also contribute to asthma development. Moreover, variants in genes that affect the function of cilia can be associated with poor lung function, even in the absence of PCD, and with increased asthma severity. The role of antigen stasis on the surface of dysfunctional airway cilia in the pathophysiology of asthma is a novel area for research, because specific airway clearance techniques and other therapeutic interventions, such as antioxidants, could be of value in preventing the development of asthma. Full article
(This article belongs to the Section Molecular Pathology, Diagnostics, and Therapeutics)
Show Figures

Figure 1

Figure 1
<p>Antigen stasis in PCD increases the risk of asthma.</p>
Full article ">
14 pages, 660 KiB  
Communication
Patients with Thyroid Dyshormonogenesis and DUOX2 Variants: Molecular and Clinical Description and Genotype–Phenotype Correlation
by Noelia Baz-Redón, María Antolín, María Clemente, Ariadna Campos, Eduard Mogas, Mónica Fernández-Cancio, Elisenda Zafon, Elena García-Arumí, Laura Soler, Núria González-Llorens, Cristina Aguilar-Riera, Núria Camats-Tarruella and Diego Yeste
Int. J. Mol. Sci. 2024, 25(15), 8473; https://doi.org/10.3390/ijms25158473 - 3 Aug 2024
Cited by 1 | Viewed by 1442
Abstract
Thyroid dyshormonogenesis (THD) is a heterogeneous group of genetic diseases caused by the total or partial defect in the synthesis or secretion of thyroid hormones. Genetic variants in DUOX2 can cause partial to total iodination organification defects and clinical heterogeneity, from transient to [...] Read more.
Thyroid dyshormonogenesis (THD) is a heterogeneous group of genetic diseases caused by the total or partial defect in the synthesis or secretion of thyroid hormones. Genetic variants in DUOX2 can cause partial to total iodination organification defects and clinical heterogeneity, from transient to permanent congenital hypothyroidism. The aim of this study was to undertake a molecular characterization and genotype–phenotype correlation in patients with THD and candidate variants in DUOX2. A total of 31 (19.38%) patients from the Catalan Neonatal Screening Program presented with variants in DUOX2 that could explain their phenotype. Fifteen (48.39%) patients were compound heterozygous, 10 (32.26%) heterozygous, and 4 (12.90%) homozygous. In addition, 8 (26.67%) of these patients presented variants in other genes. A total of 35 variants were described, 10 (28.57%) of these variants have not been previously reported in literature. The most frequent variant in our cohort was c.2895_2898del/p.(Phe966SerfsTer29), classified as pathogenic according to reported functional studies. The final diagnosis of this cohort was permanent THD in 21 patients and transient THD in 10, according to reevaluation and/or need for treatment with levothyroxine. A clear genotype–phenotype correlation could not be identified; therefore, functional studies are necessary to confirm the pathogenicity of the variants. Full article
(This article belongs to the Special Issue Thyroid Hormone and Molecular Endocrinology)
Show Figures

Figure 1

Figure 1
<p>Diagram of <span class="html-italic">DUOX2</span> gene and protein. (<b>a</b>) <span class="html-italic">DUOX2</span> gene (NG_009447.1) with boxes indicating the 34 exons (e1–e34). The coding sequence (CDS) from e2 to e34 (NM_014080.5) codifies for the DUOX2 protein. The dashed lines indicate the intronic <span class="html-italic">DUOX2</span> variants described in our cohort that explained the phenotype of patients. (<b>b</b>) DUOX2 protein (NP_054799) with the corresponding functional domains (colored boxes). The dashed lines indicate the localization of the exonic variants detected in our cohort.</p>
Full article ">
12 pages, 2203 KiB  
Communication
Gene Expression and Prognostic Value of NADPH Oxidase Enzymes in Breast Cancer
by Andressa de Vasconcelos e Souza, Caroline Coelho de Faria, Leonardo Matta Pereira, Andrea Claudia Freitas Ferreira, Pedro Henrique Monteiro Torres and Rodrigo Soares Fortunato
Int. J. Mol. Sci. 2024, 25(6), 3464; https://doi.org/10.3390/ijms25063464 - 19 Mar 2024
Cited by 1 | Viewed by 1426
Abstract
NADPH oxidase enzymes (NOX) are involved in all stages of carcinogenesis, but their expression levels and prognostic value in breast cancer (BC) remain unclear. Thus, we aimed to assess the expression and prognostic value of NOX enzymes in BC samples using online databases. [...] Read more.
NADPH oxidase enzymes (NOX) are involved in all stages of carcinogenesis, but their expression levels and prognostic value in breast cancer (BC) remain unclear. Thus, we aimed to assess the expression and prognostic value of NOX enzymes in BC samples using online databases. For this, mRNA expression from 290 normal breast tissue samples and 1904 BC samples obtained from studies on cBioPortal, Kaplan–Meier Plotter, and The Human Protein Atlas were analyzed. We found higher levels of NOX2, NOX4, and Dual oxidase 1 (DUOX1) in normal breast tissue. NOX1, NOX2, and NOX4 exhibited higher expression in BC, except for the basal subtype, where NOX4 expression was lower. DUOX1 mRNA levels were lower in all BC subtypes. NOX2, NOX4, and NOX5 mRNA levels increased with tumor progression stages, while NOX1 and DUOX1 expression decreased in more advanced stages. Moreover, patients with low expression of NOX1, NOX4, and DUOX1 had lower survival rates than those with high expression of these enzymes. In conclusion, our data suggest an overexpression of NOX enzymes in breast cancer, with certain isoforms showing a positive correlation with tumor progression. Full article
(This article belongs to the Special Issue Targeting Oxidative Stress for Disease)
Show Figures

Figure 1

Figure 1
<p>NADPH oxidases mRNA levels in the breast. Differences among NOX family mRNA levels in normal breast tissue. Data were obtained from the online platform Human Protein Atlas (<a href="https://www.proteinatlas.org" target="_blank">https://www.proteinatlas.org</a>, accessed on 2 July 2022). Results are represented as the mean protein-coding transcripts per million (pTPM) ± standard deviation (N = 290; n.d.: not detectable).</p>
Full article ">Figure 2
<p>Comparison of NOX1, NOX2, NOX3, NOX4, NOX5, and DUOX1 mRNA levels in different subtypes of breast tumor tissues. Data were obtained from the cBioPortal online platform (<a href="http://www.cbioportal.org/" target="_blank">http://www.cbioportal.org/</a>, accessed on 3 July 2022) (N = 1904). Claudin-low (N = 199); luminal A (N = 679); luminal B (N = 461); HER2 (N = 220); basal (N = 199). *** <span class="html-italic">p</span> &lt; 0.001.</p>
Full article ">Figure 3
<p>mRNA expression of NOX family at different stages of breast tumor. NOX1, NOX2, NOX4, NOX5, and DUOX1 were evaluated across tumor staging of breast tissues. Data were obtained from the cBioPortal online platform (<a href="http://www.cbioportal.org/" target="_blank">http://www.cbioportal.org/</a>, accessed on 3 July 2022) (N = 1904).</p>
Full article ">Figure 4
<p>Survival analysis according to NOX family gene expression in BC patients. Comparison between the survival of BC patients with high or low expression of NOX1 (<b>A</b>), NOX2 (<b>B</b>), NOX4 (<b>C</b>), NOX5 (<b>D</b>), DUOX1 (<b>E</b>), and DUOX2 (<b>F</b>) in tumor breast tissues using Kaplan–Meier plotter analysis.</p>
Full article ">Figure 5
<p>Expression of NOX family genes in relation to estrogen receptor (ER) status in BC samples. mRNA levels of NOX1 (<b>A</b>), NOX2 (<b>B</b>), NOX4 (<b>C</b>), NOX5 (<b>D</b>), and DUOX1 (<b>E</b>) in relation to the presence (ER+) or absence (ER-) of ER in tumor breast tissues. Data were obtained from the cBioPortal online platform (<a href="http://www.cbioportal.org/" target="_blank">http://www.cbioportal.org/</a>, accessed on 3 July 2022). N = 1904. **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">
21 pages, 2831 KiB  
Article
Antioxidant, Anti-Inflammatory and Pro-Differentiative Effects of Chlorogenic Acid on M03-13 Human Oligodendrocyte-like Cells
by Giuliana La Rosa, Concetta Sozio, Luca Pipicelli, Maddalena Raia, Anna Palmiero, Mariarosaria Santillo and Simona Damiano
Int. J. Mol. Sci. 2023, 24(23), 16731; https://doi.org/10.3390/ijms242316731 - 24 Nov 2023
Cited by 7 | Viewed by 2053
Abstract
Chlorogenic acid (CGA), a polyphenol found mainly in coffee and tea, exerts antioxidant, anti-inflammatory and anti-apoptotic effects at the gastrointestinal level. However, although CGA is known to cross the blood–brain barrier (BBB), its effects on the CNS are still unknown. Oligodendrocytes (OLs), the [...] Read more.
Chlorogenic acid (CGA), a polyphenol found mainly in coffee and tea, exerts antioxidant, anti-inflammatory and anti-apoptotic effects at the gastrointestinal level. However, although CGA is known to cross the blood–brain barrier (BBB), its effects on the CNS are still unknown. Oligodendrocytes (OLs), the myelin-forming cells in the CNS, are the main target in demyelinating neuroinflammatory diseases such as multiple sclerosis (MS). We evaluated the antioxidant, anti-inflammatory and anti-apoptotic roles of CGA in M03-13, an immortalized human OL cell line. We found that CGA reduces intracellular superoxide ions, mitochondrial reactive oxygen species (ROS) and NADPH oxidases (NOXs) /dual oxidase 2 (DUOX2) protein levels. The stimulation of M03-13 cells with TNFα activates the nuclear factor kappa-light-chain-enhancer of activated B cell (NF-kB) pathway, leading to an increase in superoxide ion, NOXs/DUOX2 and phosphorylated extracellular regulated protein kinase (pERK) levels. In addition, tumor necrosis factor alpha (TNF-α) stimulation induces caspase 8 activation and the cleavage of poly-ADP-ribose polymerase (PARP). All these TNFα-induced effects are reversed by CGA. Furthermore, CGA induces a blockade of proliferation, driving cells to differentiation, resulting in increased mRNA levels of myelin basic protein (MBP) and proteolipid protein (PLP), which are major markers of mature OLs. Overall, these data suggest that dietary supplementation with this polyphenol could play an important beneficial role in autoimmune neuroinflammatory diseases such as MS. Full article
(This article belongs to the Section Molecular Endocrinology and Metabolism)
Show Figures

Figure 1

Figure 1
<p>Chemical structure of 5-caffeoylquinic acid (5CQA).</p>
Full article ">Figure 2
<p>Cell viability according to trypan blue assay in M03-13 cells. The cells were starved for 18 h in 0.2% FBS medium in the absence (CTR) and in the presence of CGA (10, 25, 100, 250, 500 and 1000 µM); the data are reported as percentage variation compared to control. The graph shows the mean ± SEM of the values from three independent experiments. * <span class="html-italic">p</span> &lt; 0.05 vs. CTR.</p>
Full article ">Figure 3
<p>CGA reduces intracellular superoxide ion and mitochondrial ROS levels. Cells were starved for 18 h with 0.2% FBS medium in the absence (CTR) and in the presence of CGA (10, 25, 100 μM). (<b>A</b>,<b>B</b>) Fluorescence microscopy images of M03-13 cells incubated with 10 μM fluorescent probe DHE (<b>A</b>) and 1 μM MitoSOX (<b>B</b>) for staining intracellular superoxide ions and mitochondrial ROS, respectively. The histograms (<b>A</b>,<b>B</b>) show the mean ± SEM total corrected cellular fluorescence (TCCF) values, obtained via quantitative analysis of 50 cells for each sample from three independent experiments performed in triplicate. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR. ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR. Scale bar is 50 µm.</p>
Full article ">Figure 3 Cont.
<p>CGA reduces intracellular superoxide ion and mitochondrial ROS levels. Cells were starved for 18 h with 0.2% FBS medium in the absence (CTR) and in the presence of CGA (10, 25, 100 μM). (<b>A</b>,<b>B</b>) Fluorescence microscopy images of M03-13 cells incubated with 10 μM fluorescent probe DHE (<b>A</b>) and 1 μM MitoSOX (<b>B</b>) for staining intracellular superoxide ions and mitochondrial ROS, respectively. The histograms (<b>A</b>,<b>B</b>) show the mean ± SEM total corrected cellular fluorescence (TCCF) values, obtained via quantitative analysis of 50 cells for each sample from three independent experiments performed in triplicate. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR. ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR. Scale bar is 50 µm.</p>
Full article ">Figure 4
<p>CGA reduces NADPH oxidase levels. Western blotting analysis for NOX3 (<b>A</b>), NOX5 (<b>B</b>) and DUOX2; (<b>C</b>) protein levels in M03-13 cells incubated with 0.2% FBS medium for 18 h in the absence (CTR) and in the presence of CGA (10, 25, 100 μM). The histograms show the values (means ± SEM) relative to the control (CTR), obtained via densitometric analysis of protein bands normalized to α-Tubulin of three independent experiments. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR; ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR.</p>
Full article ">Figure 5
<p>NADPHox-dependent ROS are involved in TNFα-induced pro-inflammatory/proapoptotic pathways. M03-13 were incubated with 0.2% FBS medium for 18 h with 10 µM TNFα in the absence and in the presence of 10 µM AEBSF, and then, incubated with 10 μM of the superoxide probe DHE (<b>A</b>). Intracellular superoxide ion levels were measured via fluorometric analysis. The graph shows the mean ± SEM values from three independent experiments (<b>A</b>), scale bar is 50 µm. Western blot analysis for IkB⍺ (<b>B</b>), pERK (<b>C</b>) and the cleaved form of PARP; (<b>D</b>) protein levels in M03-13 cells treated with 10 µM TNFα in the presence and absence of 10 µM AEBSF. The histograms show the values (means ± SEM) relative to the control (CTR), obtained via densitometric analysis of protein bands normalized to α-Tubulin of three independent experiments. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR; ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR; § <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 10′; # <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 1 h; ## <span class="html-italic">p</span> ≤ 0.001 vs. TNFα 1 h; ° <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 4 h; °° <span class="html-italic">p</span> ≤ 0.001 vs. TNFα 4 h.</p>
Full article ">Figure 5 Cont.
<p>NADPHox-dependent ROS are involved in TNFα-induced pro-inflammatory/proapoptotic pathways. M03-13 were incubated with 0.2% FBS medium for 18 h with 10 µM TNFα in the absence and in the presence of 10 µM AEBSF, and then, incubated with 10 μM of the superoxide probe DHE (<b>A</b>). Intracellular superoxide ion levels were measured via fluorometric analysis. The graph shows the mean ± SEM values from three independent experiments (<b>A</b>), scale bar is 50 µm. Western blot analysis for IkB⍺ (<b>B</b>), pERK (<b>C</b>) and the cleaved form of PARP; (<b>D</b>) protein levels in M03-13 cells treated with 10 µM TNFα in the presence and absence of 10 µM AEBSF. The histograms show the values (means ± SEM) relative to the control (CTR), obtained via densitometric analysis of protein bands normalized to α-Tubulin of three independent experiments. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR; ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR; § <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 10′; # <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 1 h; ## <span class="html-italic">p</span> ≤ 0.001 vs. TNFα 1 h; ° <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 4 h; °° <span class="html-italic">p</span> ≤ 0.001 vs. TNFα 4 h.</p>
Full article ">Figure 6
<p>TNF⍺ induces increase in intracellular superoxide levels, measured via DHE fluorescence (<b>A</b>). M03-13 cells were preincubated with CGA 100 µM for 18 h and subsequently stimulated with TNFα 10 µM at increasing times (10 min, 1 h and 4 h) in the absence and in the presence of 10 µM AEBSF; then, the cells were incubated with 10 μM DHE and, superoxide levels were measured via fluorometric analysis (scale bar is 50 µm). The graph shows the mean ± SEM values from three independent experiments. Western blot analysis for NOX3 (<b>B</b>), NOX5 (<b>C</b>) and DUOX2 (<b>D</b>). M03-13 cells were incubated with 10 µM TNFα at increasing times (10 min, 1 h and 4 h) in the absence and presence of 100 µM CGA. The histograms show the values (means ± SEM) relative to the control (CTR), obtained via densitometric analysis of protein bands normalized to α-Tubulin of three independent experiments. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR; ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR; § <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 10′; # <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 1 h; ## <span class="html-italic">p</span> ≤ 0.001 vs. TNFα 1 h; ° <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 4 h; °° <span class="html-italic">p</span> ≤ 0.001 vs. TNFα 4 h.</p>
Full article ">Figure 6 Cont.
<p>TNF⍺ induces increase in intracellular superoxide levels, measured via DHE fluorescence (<b>A</b>). M03-13 cells were preincubated with CGA 100 µM for 18 h and subsequently stimulated with TNFα 10 µM at increasing times (10 min, 1 h and 4 h) in the absence and in the presence of 10 µM AEBSF; then, the cells were incubated with 10 μM DHE and, superoxide levels were measured via fluorometric analysis (scale bar is 50 µm). The graph shows the mean ± SEM values from three independent experiments. Western blot analysis for NOX3 (<b>B</b>), NOX5 (<b>C</b>) and DUOX2 (<b>D</b>). M03-13 cells were incubated with 10 µM TNFα at increasing times (10 min, 1 h and 4 h) in the absence and presence of 100 µM CGA. The histograms show the values (means ± SEM) relative to the control (CTR), obtained via densitometric analysis of protein bands normalized to α-Tubulin of three independent experiments. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR; ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR; § <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 10′; # <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 1 h; ## <span class="html-italic">p</span> ≤ 0.001 vs. TNFα 1 h; ° <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 4 h; °° <span class="html-italic">p</span> ≤ 0.001 vs. TNFα 4 h.</p>
Full article ">Figure 7
<p>CGA blocks the pro-inflammatory and pro-apoptotic pathways activated by TNF⍺. Western blot analysis for IκBα (<b>A</b>), pERK (<b>B</b>), caspase 8 (<b>C</b>) and cleaved PARP (<b>D</b>). M03-13 cells were treated with TNFα 10 µM for 10 min, 1 h, 4 h and 15 h in the absence and/or presence of 100 µM CGA. The histograms show the values (means ± SEM) relative to the control (CTR), obtained via densitometric analysis of protein bands normalized to α-Tubulin of three independent experiments. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR; ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR; § <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 10′; # <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 1 h; ° <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 4 h; ^ <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 15 h.</p>
Full article ">Figure 7 Cont.
<p>CGA blocks the pro-inflammatory and pro-apoptotic pathways activated by TNF⍺. Western blot analysis for IκBα (<b>A</b>), pERK (<b>B</b>), caspase 8 (<b>C</b>) and cleaved PARP (<b>D</b>). M03-13 cells were treated with TNFα 10 µM for 10 min, 1 h, 4 h and 15 h in the absence and/or presence of 100 µM CGA. The histograms show the values (means ± SEM) relative to the control (CTR), obtained via densitometric analysis of protein bands normalized to α-Tubulin of three independent experiments. * <span class="html-italic">p</span> ≤ 0.05 vs. CTR; ** <span class="html-italic">p</span> ≤ 0.001 vs. CTR; § <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 10′; # <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 1 h; ° <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 4 h; ^ <span class="html-italic">p</span> ≤ 0.05 vs. TNFα 15 h.</p>
Full article ">Figure 8
<p>CGA inhibits proliferation and leads to a cell cycle block in M03-13 cells. (<b>A</b>) M03-13 cells were incubated for 30 min with CFSE dye and grown in complete medium. A total of 1 × 10<sup>6</sup> cells per point were analyzed via flow cytofluorimetry after 24 h incubation with the fluorescent dye. Cells were treated with or without CGA 25 µM and 100 µM in the presence of CFSE. The histograms show the means ± SEM of three independent experiments. The graphs of the representative experiments are also shown (<b>B</b>). For the cell cycle analysis, the M03-13 cells were treated with CGA for 24 h, and then, treated with propidium iodide (PI) for 30 min; 230.000 cells were analyzed via cytofluorimetry. The histograms show the means ± SEM of three independent experiments, and graphs of the representative experiments are also shown. * <span class="html-italic">p</span> ≤ 0.05 vs. GROW (G0/G1); ** <span class="html-italic">p</span> ≤ 0.001 vs. GROW 24 h; # <span class="html-italic">p</span> ≤ 0.05 vs. GROW (S); ° <span class="html-italic">p</span> ≤ 0.05 vs. GROW (G2/M).</p>
Full article ">Figure 9
<p>M03-13 cells differentiate in the presence of 100 µM CGA. Crystal Violet staining images of M03-13, to highlight cellular morphological changes, were obtained using a Leica DMI1 microscope. The cells were grown in complete medium for 1 day (CTR) and in serum-free medium in the presence of 100 nM PMA or 100 µM CGA for 4 days (scale bar 100 µm).</p>
Full article ">Figure 10
<p>CGA induces an increase in MBP and PLP mRNA levels in M03-13 cells. The M03-13 cells were grown in complete medium for 4 days in the absence (GROW) and in the presence of 25 and 100 µM CGA. PMA 4d indicates differentiated cells grown in serum-free medium in the presence of 100 nM PMA for 4 days. mRNA from treated cells was extracted, and MBP (<b>A</b>) and PLP (<b>B</b>) mRNA levels were analyzed via real-time PCR. The histograms show the mean ± SEM values of three independent experiments. * <span class="html-italic">p</span> ≤ 0.05 vs. GROW; ** <span class="html-italic">p</span> ≤ 0.001 vs. GROW.</p>
Full article ">Figure 11
<p>Schematic diagram showing antioxidant, anti-inflammatory and pro-differentiative effects of CGA in OLs. In the presence of CGA, basal levels of ROS and the proinflammatory and pro-apoptotic effects induced by TNFα are reduced. CGA increases mRNA levels of MBP and PLP, major markers of mature OLs. The image was partially created by using BioRender.com.</p>
Full article ">
19 pages, 3010 KiB  
Article
Epithelial Dual Oxidase 2 Shapes the Mucosal Microbiome and Contributes to Inflammatory Susceptibility
by Juan Camilo Castrillón-Betancur, Víctor Alonso López-Agudelo, Nina Sommer, Sven Cleeves, Joana Pimenta Bernardes, Saskia Weber-Stiehl, Philip Rosenstiel and Felix Sommer
Antioxidants 2023, 12(10), 1889; https://doi.org/10.3390/antiox12101889 - 21 Oct 2023
Cited by 2 | Viewed by 1996
Abstract
Reactive oxygen species (ROS) are highly reactive molecules formed from diatomic oxygen. They act as cellular signals, exert antibiotic activity towards invading microorganisms, but can also damage host cells. Dual oxidase 2 (DUOX2) is the main ROS-producing enzyme in the intestine, regulated by [...] Read more.
Reactive oxygen species (ROS) are highly reactive molecules formed from diatomic oxygen. They act as cellular signals, exert antibiotic activity towards invading microorganisms, but can also damage host cells. Dual oxidase 2 (DUOX2) is the main ROS-producing enzyme in the intestine, regulated by cues of the commensal microbiota and functions in pathogen defense. DUOX2 plays multiple roles in different organs and cell types, complicating the functional analysis using systemic deletion models. Here, we interrogate the precise role of epithelial DUOX2 for intestinal homeostasis and host-microbiome interactions. Conditional Duox2∆IEC mice lacking DUOX2, specifically in intestinal epithelial cells, were generated, and their intestinal mucosal immune phenotype and microbiome were analyzed. Inflammatory susceptibility was evaluated by challenging Duox2∆IEC mice in the dextran sodium sulfate (DSS) colitis model. DUOX2-microbiome interactions in humans were investigated by paired analyses of mucosal DUOX2 expression and fecal microbiome data in patients with intestinal inflammation. Under unchallenged conditions, we did not observe any obvious phenotype of Duox2∆IEC mice, although intestinal epithelial ROS production was drastically decreased, and the mucosal microbiome composition was altered. When challenged with DSS, Duox2∆IEC mice were protected from colitis, possibly by inhibiting ROS-mediated damage and fostering epithelial regenerative responses. Finally, in patients with intestinal inflammation, DUOX2 expression was increased in inflamed tissue, and high DUOX2 levels were linked to a dysbiotic microbiome. Our findings demonstrate that bidirectional DUOX2-microbiome interactions contribute to mucosal homeostasis, and their dysregulation may drive disease development, thus highlighting this axis as a therapeutic target to treat intestinal inflammation. Full article
(This article belongs to the Section ROS, RNS and RSS)
Show Figures

Figure 1

Figure 1
<p><b>DUOX2 controls epithelial proliferation and ROS production</b>. (<b>A</b>) The DUOX2 protein is located in the apical epithelium in the small and large intestines and the upper crypt in the small intestine. DUOX2 was completely absent in epithelial cells of <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice. (<b>B</b>–<b>D</b>) Relative <span class="html-italic">Duox2</span> expression in small intestine (<span class="html-italic">n</span> = 7 per group) (<b>B</b>), colon (<span class="html-italic">n</span> = 9 for WT and <span class="html-italic">n</span> = 6 for DX2) (<b>C</b>) and liver (<span class="html-italic">n</span> = <span class="html-italic">n</span> = 5 for WT and <span class="html-italic">n</span> = 4 for DX2) (<b>D</b>) tissue of WT and <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice. <span class="html-italic">Duox2</span> expression was abolished, specifically in intestinal tissues. (<b>E</b>) Relative expression of NOX family members in small intestinal IECs isolated from WT and <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice (<span class="html-italic">n</span> = 8 per group). n.d. = not detected. (<b>F</b>) Schematic depiction of the procedure of intestinal organoid isolation and monolayer growth. (<b>G</b>) DUOX2 protein is not detectable in lysates of intestinal organoids derived from <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice by Western blot. (<b>H</b>) Reduced H<sub>2</sub>O<sub>2</sub> production in intestinal organoids derived from <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice. H<sub>2</sub>O<sub>2</sub> concentrations were normalized to DNA content to account for variation in cell density (<span class="html-italic">n</span> = 12 per group). (<b>I</b>) Accelerated growth of DUOX2-deficient intestinal organoids as measured by monolayer size (<span class="html-italic">n</span> = 5 per group). (<b>J</b>) Increased epithelial proliferation in <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice as measured by Ki-67 positive cells per colon crypt (<span class="html-italic">n</span> = 8 per group). Scale bars correspond to 50 µm. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 and **** <span class="html-italic">p</span> &lt; 0.0001.</p>
Full article ">Figure 2
<p><b>Ablation of epithelial DUOX2 shapes the mucosal microbiome</b>. Paired mucosal and luminal samples from the small intestine and colon of WT and <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice underwent 16S rRNA microbiome analysis. (<b>A</b>) Principal coordinate analysis revealed the different composition of the mucosal but not in the luminal microbiome in WT and <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice (WT: ILE−muc <span class="html-italic">n</span> = 6, ILE−lum <span class="html-italic">n</span> = 6, DC−muc <span class="html-italic">n</span> = 6, DC−lum <span class="html-italic">n</span> = 9. DX2: ILE−muc <span class="html-italic">n</span> = 6, ILE−lum <span class="html-italic">n</span> = 6, DC−muc <span class="html-italic">n</span> = 7, DC−lum <span class="html-italic">n</span> = 8). (<b>B</b>) Alpha diversity (within sample diversity) using the Inverse Simpson metric. (<b>C</b>) Taxonomic overview on species level color−shaded by phylum. (<b>D</b>,<b>E</b>) Linear discriminant analysis (LDA) effect size (Lefse) of the ileum mucosa microbiome. (<b>D</b>) The cladogram depicts the phylogenetic distribution of differential taxa. (<b>E</b>) Differential taxa ranked by LDA. ILE = ileum, DC = distal colon. muc = mucosal, lum = lumen. ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Figure 3
<p><b>Loss of DUOX2 in the intestinal epithelium protects from colitis</b>. (<b>A</b>) Body weight loss of WT and <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice during DSS-induced colitis (WT <span class="html-italic">n</span> = 6, DX2 <span class="html-italic">n</span> = 7). (<b>B</b>) Disease activity index (DAI) consists of stool consistency, fecal blood occurrence, and body weight loss (WT <span class="html-italic">n</span> = 6, DX2 <span class="html-italic">n</span> = 7). (<b>C</b>) Serum KC/CXCL1 (pro-inflammatory cytokine) levels as determined by ELISA (WT <span class="html-italic">n</span> = 6, DX2 <span class="html-italic">n</span> = 7). (<b>D</b>) Histological score of H&amp;E-stained colon sections, including representative images. The scale bar represents 50 µm (WT <span class="html-italic">n</span> = 6, DX2 <span class="html-italic">n</span> = 7). (<b>E</b>) Increased epithelial proliferation in <span class="html-italic">Duox2</span><sup>∆IEC</sup> compared to WT mice after challenge with DSS as measured by Ki-67<sup>+</sup> cells per colon crypt (WT <span class="html-italic">n</span> = 6, DX2 <span class="html-italic">n</span> = 7). (<b>F</b>) Epithelial <span class="html-italic">Duox2</span> expression follows disease activity during colitis induction and recovery. RNAseq data [<a href="#B34-antioxidants-12-01889" class="html-bibr">34</a>] of WT mice treated with 2.5% DSS for 7 days and additional recovery for 7 days. <span class="html-italic">Duox2</span> expression was normalized to the epithelial marker gene <span class="html-italic">Cdh1</span>. The trendline is indicated in blue (<span class="html-italic">n</span> = 3). * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 4
<p><b>Under inflammatory stress, <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice develop an altered fecal microbiome</b>. (<b>A</b>) Constrained analysis of principal coordinates revealed differential developmental transitions in fecal microbiomes of WT and <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice during DSS−induced colitis (WT <span class="html-italic">n</span> = 8, DX2 <span class="html-italic">n</span> = 7). (<b>B</b>) Reduced alpha diversity (Inverse Simpson metric) in <span class="html-italic">Duox2</span><sup>∆IEC</sup> mice at the late stage of DSS−colitis. (<b>C</b>,<b>D</b>) Lefse analysis of the merged day 7–12 microbiomes. (<b>C</b>) The cladogram depicts the phylogenetic distribution of differential taxa. (<b>D</b>) Differential taxa ranked by LDA. * <span class="html-italic">p</span> &lt; 0.05.</p>
Full article ">Figure 5
<p><b><span class="html-italic">Duox2</span> expression is dysregulated in the mucosa of patients with intestinal inflammation</b>. HC = healthy controls, CD = Crohn’s disease, UC = Ulcerative colitis, PSC = primary sclerosing cholangitis, NIC = non-IBD colitis. Note that y-axes in the panels show raw and normalized read counts; thus, data should only be compared between conditions within a single study. (<b>A</b>) <span class="html-italic">DUOX2</span> expression in HC (<span class="html-italic">n</span> = 42) and pediatric CD (<span class="html-italic">n</span> = 174) or UC (<span class="html-italic">n</span> = 38) patients and combined as IBD (<span class="html-italic">n</span> = 212) [<a href="#B41-antioxidants-12-01889" class="html-bibr">41</a>]. (<b>B</b>) <span class="html-italic">DUOX2</span> expression in HC (<span class="html-italic">n</span> = 35) and pediatric IBD patients (<span class="html-italic">n</span> = 210) [<a href="#B40-antioxidants-12-01889" class="html-bibr">40</a>]. (<b>C</b>) <span class="html-italic">DUOX2</span> expression in HC (<span class="html-italic">n</span> = 60) and CD (<span class="html-italic">n</span> = 42) or UC (<span class="html-italic">n</span> = 32) patients and combined as IBD (<span class="html-italic">n</span> = 74) [<a href="#B39-antioxidants-12-01889" class="html-bibr">39</a>]. (<b>D</b>) <span class="html-italic">DUOX2</span> expression in HC (<span class="html-italic">n</span> = 11) or CD patients (<span class="html-italic">n</span> = 21) [<a href="#B38-antioxidants-12-01889" class="html-bibr">38</a>]. (<b>E</b>) <span class="html-italic">DUOX2</span> expression in ileum and colon biopsies of HC (<span class="html-italic">n</span> = 143/86 for ileum/colon) and CD (<span class="html-italic">n</span> = 751/63) or UC (<span class="html-italic">n</span> = 133/70) patients [<a href="#B37-antioxidants-12-01889" class="html-bibr">37</a>]. (<b>F</b>) <span class="html-italic">DUOX2</span> expression in HC (<span class="html-italic">n</span> = 40) and UC (<span class="html-italic">n</span> = 40) or PSC (<span class="html-italic">n</span> = 40) patients [<a href="#B36-antioxidants-12-01889" class="html-bibr">36</a>]. (<b>G</b>) <span class="html-italic">DUOX2</span> expression in inflamed and non-inflamed mucosa of patients with CD, UC, or NIC [<a href="#B35-antioxidants-12-01889" class="html-bibr">35</a>]. <span class="html-italic">n</span> = 4–8 per group. * <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.</p>
Full article ">Figure 6
<p><b>Dysregulated DUOX2-microbiome interactions in IBD patients</b>. Paired mucosal <span class="html-italic">DUOX2</span> expression and fecal microbiome data [<a href="#B42-antioxidants-12-01889" class="html-bibr">42</a>] were used for an interaction analysis. (<b>A</b>) <span class="html-italic">DUOX2</span> expression was increased in CD (<span class="html-italic">n</span> = 79) and UC (<span class="html-italic">n</span> = 49) compared to HC (<span class="html-italic">n</span> = 29). Samples from CD and UC patients were divided into high and low <span class="html-italic">DUOX2</span> expression groups based on the median (dotted line). (<b>B</b>) Principal coordinate analysis revealed an altered fecal microbiome in high <span class="html-italic">DUOX2</span> expression IBD patients. (<b>C</b>) Differential taxa in high versus low <span class="html-italic">DUOX2</span> expression samples. Significance (FDR—false discovery rate) is color-coded, and the symbol size indicates the number of taxa reads.</p>
Full article ">
14 pages, 2081 KiB  
Article
DUOX2-Induced Oxidative Stress Inhibits Intestinal Angiogenesis through MMP3 in a Low-Birth-Weight Piglet Model
by Dongbin Zou, Yun Yang, Fengjie Ji, Renlong Lv, Tieshan Xu and Chengjun Hu
Antioxidants 2023, 12(10), 1800; https://doi.org/10.3390/antiox12101800 - 25 Sep 2023
Cited by 3 | Viewed by 1680
Abstract
Intestinal vessels play a critical role in nutrient absorption, whereas the effect and mechanism of low birth weight (LBW) on its formation remain unclear. Here, twenty newborn piglets were assigned to the control (CON) group (1162 ± 98 g) and LBW group (724 [...] Read more.
Intestinal vessels play a critical role in nutrient absorption, whereas the effect and mechanism of low birth weight (LBW) on its formation remain unclear. Here, twenty newborn piglets were assigned to the control (CON) group (1162 ± 98 g) and LBW group (724 ± 31 g) according to their birth weight. Results showed that the villus height and the activity of maltase in the jejunum were lower in the LBW group than in the CON group. LBW group exhibited a higher oxidative stress level and impaired mitochondrial function in the jejunum and was lower than the CON group in the intestinal vascular density. To investigate the role of oxidative stress in intestinal angiogenesis, H2O2 was employed to induce oxidative stress in porcine intestinal epithelial cells (IPEC-J2). The results showed that the conditioned media from IPEC-J2 with H2O2 treatment decreased the angiogenesis of porcine vascular endothelial cells (PVEC). Transcriptome analysis revealed that a higher expression level of dual oxidase 2 (DUOX2) was found in the intestine of LBW piglets. Knockdown of DUOX2 in IPEC-J2 increased the proliferation and decreased the oxidative stress level. In addition, conditioned media from IPEC-J2 with DUOX2-knockdown was demonstrated to promote the angiogenesis of PVEC. Mechanistically, the knockdown of DUOX2 decreased the reactive oxygen species (ROS) level, thus increasing the angiogenesis in a matrix metalloproteinase 3 (MMP3) dependent manner. Conclusively, our results indicated that DUOX2-induced oxidative stress inhibited intestinal angiogenesis through MMP3 in a LBW piglet model. Full article
(This article belongs to the Special Issue Cellular ROS and Antioxidants: Physiological and Pathological Role)
Show Figures

Figure 1

Figure 1
<p>The morphology and the activities of digestive enzymes in jejunum. (<b>a</b>) Images of immunohistochemistry staining of jejunum. Bar = 75 μm. Summarized data of the intestinal villus height (<b>b</b>) and crypt depth (<b>c</b>). (<b>d</b>–<b>f</b>) The activities of sucrase, maltase, and lactase in jejunum. (<b>g</b>) The mRNA expression levels of genes related to amino acid and glucose transporters in jejunum between CON and LBW groups. (<b>h</b>,<b>i</b>) The protein levels of Occludin and Claudin 1 in the jejunum. Values are described as mean ± SEM, <span class="html-italic">n</span> = 10. The difference between the two groups was analyzed using the Student’s <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01. CON: normal birth weight group; LBW: low birth weight group.</p>
Full article ">Figure 2
<p>Oxidative stress level in the jejunum. The levels of ROS (<b>a</b>), protein carbonyl (<b>b</b>), GSH (<b>c</b>), MDA (<b>d</b>), 8-OHdG (<b>e</b>), SOD (<b>f</b>), and GSH-Px (<b>g</b>) in the jejunum. (<b>h</b>) The mRNA expression levels of endoplasmic stress markers. (<b>i</b>,<b>j</b>) Immunohistochemistry for ATF6 in jejunum. bar = 100 μm. (<b>k</b>) The mRNA expression level of Keap 1 in the jejunum. (<b>l</b>,<b>m</b>) The protein level of Keap1 in jejunum. Values are described as mean ± SEM, <span class="html-italic">n</span> = 10. CON: normal birth weight group; LBW: low birth weight group. The difference between the two groups was analyzed using the Student’s <span class="html-italic">t</span>-test. * indicates <span class="html-italic">p</span> &lt; 0.05. CON: normal birth weight group; LBW: low birth weight group.</p>
Full article ">Figure 3
<p>Mitochondrial biogenesis in jejunum. The levels of ATP (<b>a</b>), CS (<b>b</b>), and mtDNA (<b>c</b>) in the jejunum. The activities of Complex I (<b>d</b>) and Complex III (<b>e</b>) in the jejunum. Values are described as mean ± SEM, <span class="html-italic">n</span> = 10. The difference between the two groups was analyzed using the Student’s <span class="html-italic">t</span>-test. * indicates <span class="html-italic">p</span> &lt; 0.05. CON: normal birth weight group; LBW: low birth weight group.</p>
Full article ">Figure 4
<p>LBW increased the DUOX2 expression level and decreased vessel density in the jejunum. (<b>a</b>,<b>b</b>) Volcano map and cluster heat map illustrating the DEGs in jejunum between CON and LBW groups. <span class="html-italic">n</span> = 5. (<b>c</b>) GO enrichment analysis of the DEGs. <span class="html-italic">n</span> = 5. (<b>d</b>) The relative expression level of genes associated with angiogenesis and oxidative stress in jejunum. <span class="html-italic">n</span> = 5. (<b>e</b>) The mRNA expression level of DUOX2 in jejunum. (<b>f</b>) The mRNA expression levels of angiogenic factors in the jejunum. (<b>g</b>) CD31 immunofluorescence staining in jejunum. DAPI staining for the nucleus. bar = 100 μm. (<b>h</b>) Summarized data of CD31 fluorescence intensity in jejunum. (<b>i</b>) Western blotting analysis of the protein levels of VEGF-A and CD31 in jejunum. Values are described as mean ± SEM. <span class="html-italic">n</span> = 10. The difference between the two groups was analyzed using the Student’s <span class="html-italic">t</span>-test. * indicates <span class="html-italic">p</span> &lt; 0.05, ** indicates <span class="html-italic">p</span> &lt; 0.01, *** indicates <span class="html-italic">p</span> &lt; 0.001. CON: normal birth weight group; LBW: low birth weight group.</p>
Full article ">Figure 5
<p>H<sub>2</sub>O<sub>2</sub>-induced oxidative stress in IPEC-J2 impairs angiogenesis of PVEC in vitro. (<b>a</b>) Proliferation assays of IPEC-J2 treated with 200 μM H<sub>2</sub>O<sub>2</sub> for 24 h, 48 h, and 72 h. <span class="html-italic">n</span> = 6. (<b>b</b>,<b>c</b>) The ROS level in IPEC-J2 treated with 200 μM H<sub>2</sub>O<sub>2</sub> for 48 h. bar = 75 μm, <span class="html-italic">n</span> = 6. (<b>d</b>,<b>e</b>) VEGF-A immunofluorescence staining in IPEC-J2 treated with 200 μM H<sub>2</sub>O<sub>2</sub> for 48 h. DAPI staining for the nucleus. Bar = 200 μm, <span class="html-italic">n</span> = 6. Conditioned media from H<sub>2</sub>O<sub>2</sub>-treated IPEC-J2 were collected to perform PVEC tube formation (<b>f</b>,<b>g</b>) and wound healing assays (<b>h</b>,<b>i</b>). bar = 75 μm, <span class="html-italic">n</span> = 6. Values are described as mean ± SEM. The difference between the two groups was analyzed using the Student’s <span class="html-italic">t</span>-test. * indicates <span class="html-italic">p</span> &lt; 0.05. All experiments were performed in triplicate.</p>
Full article ">Figure 6
<p>Knockdown of DUOX2 in IPEC-J2 increased PVEC angiogenesis in vitro. (<b>a</b>) The mRNA level of DUOX2 in IPEC-J2 with siRNA against DUOX2. (<b>b</b>) The ROS level in IPEC-J2 with siRNA against DUOX2. <span class="html-italic">n</span> = 6. Images of tube formation (<b>c</b>,<b>d</b>) and cell migration (<b>e</b>,<b>f</b>) of PVEC cultured with conditioned media from the IPEC-J2 with siRNA against DUOX2. bar = 75 μm. (<b>g</b>) The mRNA expression levels of angiogenic factors in IPEC-J2. (<b>h</b>) Images of DUOX2 and MMP3 immunofluorescence staining in IPEC-J2 with siRNA against DUOX2. bar = 200 μm. (<b>i</b>) IPEC-J2 with siRNA against DUOX2 was treated with actinomycin D (5 μg/mL) for 0, 6, and 12 h, then RNA was isolated at indicated time points. qPCR was performed to assess the mRNA expression level of MMP3. (<b>j</b>) Proliferation assay of IPEC-J2 cells. IPEC-J2 with siRNA against DUOX2 were treated with or without 10 μM MMP3 inhibitor UK356618 for 24, 48, and 72 h, respectively. Images of wound healing assay (<b>k</b>,<b>l</b>) and tube formation (<b>k</b>,<b>m</b>) of PVEC cultured with conditioned media from the NC and DUOX2 knockdown cells treated with or without 10 μM UK356618. bar = 75 μm. Values are described as mean ± SEM, <span class="html-italic">n</span> = 6. The difference between the two groups was analyzed using the Student’s <span class="html-italic">t</span>-test. * indicates <span class="html-italic">p</span> &lt; 0.05. NS, no significance. All experiments were performed in triplicate.</p>
Full article ">
17 pages, 827 KiB  
Article
Interactions between Polygenetic Variants and Lifestyle Factors in Hypothyroidism: A Hospital-Based Cohort Study
by Da Sol Kim and Sunmin Park
Nutrients 2023, 15(17), 3850; https://doi.org/10.3390/nu15173850 - 3 Sep 2023
Cited by 2 | Viewed by 2759
Abstract
Hypothyroidism is a prevalent endocrine disorder and is associated with a variety of metabolic disturbances. This study aimed to investigate the polygenic variants associated with hypothyroidism risk and the interaction of polygenic risk scores (PRS) with dietary patterns in influencing disease risk in [...] Read more.
Hypothyroidism is a prevalent endocrine disorder and is associated with a variety of metabolic disturbances. This study aimed to investigate the polygenic variants associated with hypothyroidism risk and the interaction of polygenic risk scores (PRS) with dietary patterns in influencing disease risk in 56,664 participants aged >40 in a hospital-based cohort. The participants were classified as having hypothyroidism (n = 870) diagnosed by a physician and no hypothyroidism (n = 55,794). Genetic variants associated with hypothyroidism were identified using a genome-wide association study (GWAS). Genetic variants interacting with each other were selected using a generalized multifactor dimensionality reduction analysis, and the PRS generated was evaluated for interaction with lifestyle parameters. Coffee, alcohol, meat intake, and a Korean balanced diet were inversely associated with hypothyroidism risk, as were selenium, copper, and manganese intakes. White blood cell (WBC) counts and serum alkaline phosphatase and triglyceride concentrations were positively associated with hypothyroidism risk, as were osteoporosis and thyroid cancer. The GMDR analysis generated a three-single nucleotide polymorphism (SNP) model comprising dual oxidase-1 (DUOX1)_rs1648314; thyroid-stimulating hormone receptor (TSHR)_rs75664963; and major histocompatibility complex, class-II, DQ Alpha-1 (HLA-DQA1)_rs17426593. The PRS derived from the three- and seven-SNP models were associated with a 2.11- and 2.32-fold increase in hypothyroidism risk, respectively. Furthermore, the PRS from the three-SNP model showed interactions with WBC counts, wherein the positive association with hypothyroidism risk was more pronounced in participants with low WBC counts than those with high WBC counts (≥4 × 109 /L). Dietary patterns, such as the plant-based diet (PBD) and the Western-style diet (WSD), along with smoking status, exhibited interactions with the PRS, influencing hypothyroidism risk. In participants with a high PRS, those in the high-PBD, low-WSD, and smoker groups had a higher proportion of hypothyroidism than those in the low-PBD, high-WSD, and non-smoker groups. In conclusion, genetic variants related to immunity and thyroid hormone secretion were linked to hypothyroidism risk, and their PRS interacted with PBD and WSD intake and smoking status. These results contribute to a better understanding of hypothyroidism and its prevention strategies for precision medicine intervention. Full article
(This article belongs to the Special Issue Nutrition and Gene Interaction)
Show Figures

Figure 1

Figure 1
<p>Flow chart to generate the polygenic risk score system influencing hypothyroidism risk.</p>
Full article ">Figure 2
<p>Adjusted odds ratio (ORs) and 95% confidence intervals (CIs) of the polygenic risk scores (PRS) of three- and seven-single nucleotide polymorphism (SNP) models generated for assessing SNP–SNP interactions associated with hypothyroidism risk. The best generalized multifactor dimensionality reduction analysis (GMDR) models with three-SNPs and seven-SNPs were calculated by summing the number of risk alleles of six and seven SNPs. The calculated PRS were divided into three categories (0–3, 4–5, and ≥6; 0–5, 6–8, and ≥9), the low-PRS, medium-PRS, and high-PRS groups, for the three-SNP and seven-SNP models, respectively. The adjusted OR was analyzed by logistic regression with covariates, including age, gender, residence areas, income, education, energy intake, smoking status, physical activity, alcohol intake, and the survey year. The reference group was the low-PRS in logistic regression. Red and blue boxes indicate the adjusted ORs for the three and seven SNPs, respectively, and the lines through red and blue boxes indicate 95% CIs.</p>
Full article ">Figure 3
<p>The proportion of individuals with hypothyroidism with the polygenic risk scores (PRS) of the three-single nucleotide polymorphism (SNP) model according to white blood cell (WBC) counts, diets, and smoking status. (<b>A</b>). WBC (cutoff: 4.0 × 10<sup>9</sup> /L); (<b>B</b>). Serum C-reactive protein (CRP) concentration (Cutoff: 0.5 mg/dL); (<b>C</b>). Carbohydrate intake (Cutoff: 70th energy percentile); (<b>D</b>). Korean balanced diet (KBD, Cutoff: 33rd percentile); (<b>E</b>). Plant-based diet (PBD, Cutoff: 33rd percentile); (<b>F</b>). Western-style diet (WSD, Cutoff: 33rd percentile); (<b>G</b>). Smoking status; Low-PRS (0–3), Medium-PRS (4–5), and High-PRS (≥6) in the six-SNP model.</p>
Full article ">
15 pages, 2991 KiB  
Article
Pharmacologic Ascorbate and DNMT Inhibitors Increase DUOX Expression and Peroxide-Mediated Toxicity in Pancreatic Cancer
by Garett J. Steers, Brianne R. O’Leary, Juan Du, Brett A. Wagner, Rory S. Carroll, Frederick E. Domann, Prabhat C. Goswami, Garry R. Buettner and Joseph J. Cullen
Antioxidants 2023, 12(9), 1683; https://doi.org/10.3390/antiox12091683 - 29 Aug 2023
Viewed by 1744
Abstract
Recent studies have demonstrated an important role for vitamin C in the epigenetic regulation of cancer-related genes via DNA demethylation by the ten-eleven translocation (TET) methylcytosine dioxygenase enzymes. DNA methyltransferase (DNMT) reverses this, increasing DNA methylation and decreasing gene expression. Dual oxidase (DUOX) [...] Read more.
Recent studies have demonstrated an important role for vitamin C in the epigenetic regulation of cancer-related genes via DNA demethylation by the ten-eleven translocation (TET) methylcytosine dioxygenase enzymes. DNA methyltransferase (DNMT) reverses this, increasing DNA methylation and decreasing gene expression. Dual oxidase (DUOX) enzymes produce hydrogen peroxide (H2O2) in normal pancreatic tissue but are silenced in pancreatic cancer (PDAC). Treatment of PDAC with pharmacologic ascorbate (P-AscH, intravenous, high dose vitamin C) increases DUOX expression. We hypothesized that inhibiting DNMT may act synergistically with P-AscH to further increase DUOX expression and cytotoxicity of PDAC. PDAC cells demonstrated dose-dependent increases in DUOX mRNA and protein expression when treated with DNMT inhibitors. PDAC cells treated with P-AscH + DNMT inhibitors demonstrated increased DUOX expression, increased intracellular oxidation, and increased cytotoxicity in vitro and in vivo compared to either treatment alone. These findings suggest a potential therapeutic, epigenetic mechanism to treat PDAC. Full article
(This article belongs to the Special Issue Current Insights and Trends in Vitamin C Research)
Show Figures

Figure 1

Figure 1
<p>DUOX hypermethylation in PDAC. (<b>A</b>) DUOX1 methylation vs. overall survival in PDAC. The NIH Cancer Genome Atlas (TCGA) Pancreatic Cancer Database (PAAD) (<span class="html-italic">n</span> = 223) was accessed via the University of California Santa Cruz (UCSC) Xena Functional Genomics Explorer (<span class="html-italic">n</span> = 148; overall survival at 5 years 30% vs. 5%; * <span class="html-italic">p</span> = 0.03; Gehan–Breslow–Wilcoxon test). (<b>B</b>) DUOX1 mRNA expression is increased in a dose-dependent manner in the MIA PaCa-2, PANC-1, and PDX-339 PDAC cell lines after exposure to AZC (1–2 µM) for 5 days (means ± SEM; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) DUOX2 mRNA expression is increased in a dose-dependent manner in MIA PaCa-2, PANC-1, and PDX-339 PDAC cell lines after exposure to AZC (1–2 µM) for 5 days (means ± SEM; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05). (<b>D</b>) DUOX1 and DUOX2 immunoreactive protein was increased in PDX-339 cells after AZC (1–2 µM). Representative blots are shown.</p>
Full article ">Figure 2
<p>DNMT inhibitors with P-AscH<sup>−</sup> increase DUOX expression in PDAC cell lines in a dose-dependent manner. Treatment with a DNMT inhibitor also produces sustained increases in DUOX expression. (<b>A</b>) DUOX1 mRNA expression is increased after exposure to AZC (2 µM) for 5 days ± P-AscH<sup>−</sup> (20 pmol/cell) for 1 h in PDX-339 cells. The combination group demonstrated a significant increase in expression compared to either treatment group alone (means ± SEM; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) DUOX1 mRNA expression increased in a dose-dependent manner after exposure to AZD (0.5–1 µM) for 3 days in MIA PaCa-2 cells. The addition of P-AscH<sup>−</sup> (10 pmol/cell) for 1 h produces a significant increase in expression compared to either treatment group alone (means ± SEM; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) DUOX2 mRNA expression increased in a similar manner with the same treatments. (<b>D</b>) DUOX1 immunoreactive protein increased in MIA-PaCa-2 cells with AZD (0.5–1 µM) for 3 days and P-AscH<sup>−</sup> (10 pmol/cell) for 1 h. (<b>E</b>) DUOX2 immunoreactive protein increased with the same treatments. Representative blots are shown. (<b>F</b>) DUOX1 mRNA expression is increased for up to 72 h after exposure to AZD (1 µM). (<b>G</b>) DUOX2 mRNA expression is increased immediately following exposure to AZD (1 µM) (means ± SEM; <span class="html-italic">n</span> = 4; * <span class="html-italic">p</span> &lt; 0.05 vs. control).</p>
Full article ">Figure 3
<p>DNMT inhibitors and P-AscH<sup>−</sup> generate dose-dependent, H<sub>2</sub>O<sub>2</sub>-dependent cytotoxicity. (<b>A</b>) Mean fluorescence intensity (MFI) is increased following exposure to AZC (2 µM) for 5 days and P-AscH<sup>−</sup> (20 pmol/cell) for 1 h in PDX-339 cells. Pretreatment with bovine catalase (100 µg/mL) reverses this effect demonstrating that the oxidation of DCFH-DA is mediated by H<sub>2</sub>O<sub>2</sub> (means ± SEM; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) MIA PaCa-2, PANC-1 and PDX-339 cells were treated with AZC (0.5–2 µM) for 5 days ± P-AscH<sup>−</sup> (20 pmol/cell) for 1 h demonstrating decreases in clonogenic survival with the combination treatments (means ± SEM; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) MIA PaCa-2 and PANC-1 cells were treated with AZD ± P-AscH<sup>−</sup> demonstrating decreases in clonogenic survival with the combination treatments (means ± SEM; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05). (<b>D</b>) Clonogenic survival in MIA PaCa-2 treated with AZD (0.1 µM), P-AscH<sup>−</sup> (10 pmol/cell), and catalase (100 µg/mL). Catalase reverses the decrease in clonogenic survival supporting a H<sub>2</sub>O<sub>2</sub> mechanism (means ± SEM; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.01).</p>
Full article ">Figure 4
<p>The hypoxia-induced increase in DNMT1 expression is decreased with P-AscH<sup>−</sup>. (<b>A</b>) DNMT1 immunoreactive protein was increased after exposure to 4% O<sub>2</sub> for 6 h and decreased to baseline following exposure to P-AscH<sup>−</sup> (10 pmol/cell). Representative blots are shown. (<b>B</b>) Quantification of densitometric evaluation of Western blots (mean ± SEM, values normalized to control; <span class="html-italic">n</span> = 3; * <span class="html-italic">p</span> &lt; 0.05). (<b>C</b>) DNMT1 immunofluorescence staining was performed on xenograft tumor samples. Samples were visualized using a Zeiss Confocal Microscope 40× oil objective. Results show decreased DNMT1 immunofluorescence in the P-AscH<sup>−</sup> treatment group compared to control. Green staining, DNMT1; blue staining, nuclear topoisomerase-3. Representative images are shown. (<b>D</b>) Quantification demonstrating MFI normalized to nuclear content (means ± SEM; <span class="html-italic">n</span> = 8; * <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">Figure 5
<p>DNMT inhibitors combined with P-AscH<sup>−</sup> decrease tumor volume and increase DUOX1 expression in vivo. Athymic nude mice with heterotopic MIA PaCa-2 xenografts were treated with intraperitoneal normal saline (4 g/kg, 1 M, daily), AZD (1 g/kg, three times weekly), P-AscH<sup>−</sup> (4 g/kg, daily), or a combination of P-AscH<sup>−</sup> and AZD. Mice were treated for 21 days and tumor volume was measured twice weekly. (<b>A</b>) Tumor growth was significantly inhibited in the combination AZD + P-AscH<sup>−</sup> group compared to the control group and compared to either treatment group alone. Tumor volumes (mm<sup>3</sup>) were normalized to their starting volumes on treatment day 1 to avoid heterogeneity in the starting tumor volumes. Data represent average tumor volume over 18 d (means ± SEM; * <span class="html-italic">p</span> &lt; 0.05). (<b>B</b>) DUOX1 immunofluorescence staining was performed on xenograft tumor samples. Samples were visualized using a Zeiss Confocal Microscope 40× oil objective. Results show increased DUOX1 immunofluorescence in the AZD treatment groups compared to control. Green staining, DUOX1; blue staining, nuclear topoisomerase-3. Representative images are shown. (<b>C</b>) Quantification demonstrating MFI normalized to nuclear content (means ± SEM; <span class="html-italic">n</span> = 7; * <span class="html-italic">p</span> &lt; 0.05).</p>
Full article ">
18 pages, 4986 KiB  
Article
Novel NADPH Oxidase-2 Inhibitors as Potential Anti-Inflammatory and Neuroprotective Agents
by Matea Juric, Varun Rawat, Radhika Amaradhi, Jacek Zielonka and Thota Ganesh
Antioxidants 2023, 12(9), 1660; https://doi.org/10.3390/antiox12091660 - 23 Aug 2023
Cited by 3 | Viewed by 2451
Abstract
A family of seven NADPH oxidase enzymes (Nox1-5, Duox1-2) has been implicated in a variety of diseases, including inflammatory lung diseases, neurodegenerative diseases, cardiovascular diseases, and cancer. Here, we report the results of our studies aimed at developing novel brain-permeable Nox2 inhibitors with [...] Read more.
A family of seven NADPH oxidase enzymes (Nox1-5, Duox1-2) has been implicated in a variety of diseases, including inflammatory lung diseases, neurodegenerative diseases, cardiovascular diseases, and cancer. Here, we report the results of our studies aimed at developing novel brain-permeable Nox2 inhibitors with potential application as neuroprotective agents. Using cell-based assays, we identified a novel Nox2 inhibitor, TG15-132, that prevents PMA-stimulated oxygen consumption and reactive oxygen species (superoxide radical anion and hydrogen peroxide) formation upon acute treatment in differentiated HL60 cells. Long-term treatment with TG15-132 attenuates the induction of genes encoding Nox2 subunits, several inflammatory cytokines, and iNOS in differentiated THP-1 cells. Moreover, TG15-132 shows a relatively long plasma half-life (5.6 h) and excellent brain permeability, with a brain-to-plasma ratio (>5-fold) in rodent models. Additionally, TG15-132 does not cause any toxic effects on vital organs or blood biomarkers of toxicity in mice upon chronic dosing for seven days. We propose that TG15-132 may be used as a Nox2 inhibitor and a potential neuroprotective agent, with possible further structural modifications to increase its potency. Full article
Show Figures

Graphical abstract

Graphical abstract
Full article ">Figure 1
<p>NOX enzymes are early inducers of ROS (O<sub>2</sub><sup>•−</sup>, H<sub>2</sub>O<sub>2</sub>), which are further converted into other, highly reactive oxidants including <sup>•</sup>OH, HOCl, <sup>•</sup>NO<sub>2</sub>, ONOO<sup>−</sup>, and ONOO<sup>−</sup>-derived radicals (<sup>•</sup>OH, <sup>•</sup>NO<sub>2</sub>, and CO<sub>3</sub><sup>•−</sup>), overwhelming cellular antioxidant systems and resulting in oxidative stress. Oxidative stress triggers an inflammatory cascade that can further induce ROS formation. Oxidative stress and neuroinflammation lead to the damage of neurons and other brain cells, and modify the function of glial cells, resulting in an increased risk of developing neuronal excitability and epileptogenesis.</p>
Full article ">Figure 2
<p>Chemical structures of the candidate Nox2 inhibitors tested. The structures of other compounds used for SAR study are shown in <a href="#antioxidants-12-01660-sch001" class="html-scheme">Scheme 1</a> and <a href="#antioxidants-12-01660-sch002" class="html-scheme">Scheme 2</a>.</p>
Full article ">Figure 3
<p>Inhibition of H<sub>2</sub>O<sub>2</sub> production by activated <span class="html-italic">d</span>HL60 cells by selected inhibitors, as measured using a CBA probe. (<b>A</b>) Chemical principle of H<sub>2</sub>O<sub>2</sub> measurement. (<b>B</b>,<b>C</b>) Kinetic traces of probe oxidation in the absence and presence of the inhibitors tested. (<b>D</b>,<b>E</b>) Concentration dependence of the inhibitory effects of TG15-132 (<b>D</b>) and TG15-139 (<b>E</b>) candidate inhibitors on H<sub>2</sub>O<sub>2</sub> production (blue symbols) and cell viability (red symbols). Dashed lines represent fitted curves used to determine the IC<sub>50</sub> values.</p>
Full article ">Figure 4
<p>Inhibition of H<sub>2</sub>O<sub>2</sub> production by activated <span class="html-italic">d</span>HL60 cells by selected inhibitors, as measured using an Amplex Red-based assay. (<b>A</b>) Chemical principle of H<sub>2</sub>O<sub>2</sub> measurement. (<b>B</b>,<b>C</b>) Kinetic traces of probe oxidation in the absence and presence of the inhibitors tested. (<b>D</b>,<b>E</b>) Concentration dependence of the inhibitory effects of TG15-132 (<b>D</b>) and TG15-139 (<b>E</b>) candidate inhibitors on H<sub>2</sub>O<sub>2</sub> production. Dashed lines represent fitted curves used to determine the IC<sub>50</sub> values.</p>
Full article ">Figure 5
<p>Inhibition of O<sub>2</sub><sup>•−</sup> production by activated <span class="html-italic">d</span>HL60 cells by TG15-132, as measured using hydroethidine-based assays. (<b>A</b>) Chemical principle of O<sub>2</sub><sup>•−</sup> measurement. (<b>B</b>) Kinetic traces of probe oxidation in the absence and presence of different concentrations of TG15-132. (<b>C</b>) Concentration dependence of the inhibitory effects of TG15-132 on O<sub>2</sub><sup>•−</sup> production. Red line represents the fitted curve used to determine the IC<sub>50</sub> value. (<b>D</b>) HPLC chromatograms of 2–OH–E<sup>+</sup> formed at different concentrations of TG15-132 or 10 µM DPI. (<b>E</b>) Quantitative analyses of the HPLC data on the levels of 2–OH–E<sup>+</sup> formed (blue bars) and HE probe (red bars) consumption at different concentrations of TG15-132.</p>
Full article ">Figure 6
<p>Inhibition of oxygen consumption by activated <span class="html-italic">d</span>HL60 cells by TG15-132, as measured using Seahorse XFe96-based respirometry. (<b>A</b>) Kinetic traces of OCR before and after sequential injection of TG15-132 and PMA. (<b>B</b>) Concentration dependence of the inhibitory effects of TG15-132 on basal (blue circles) and PMA-stimulated (red squares) OCR.</p>
Full article ">Figure 7
<p>(<b>A</b>) Nox2 inhibitor TG15-132 suppresses the induction of Nox2 and inflammatory mediators in human THP-1 cells. (<b>B</b>) Nox2 inhibitor TG15-132 (3 µM) performed significantly better compared with GSK 2795039 (3 µM) in alleviating the effect of PMA treatment in THP-1 cells. THP-1 cells were treated with PMA with or without TG15-132 or a known Nox2 inhibitor, GSK 2795039, for 48 h, followed by the analysis of the mRNA expression levels. A one-way ANOVA with Tukey’s multiple comparison test was used for analysis. * <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, ns—not significant (<span class="html-italic">p</span> &gt; 0.05).</p>
Full article ">Figure 8
<p>Plasma and brain levels of TG15-132 in male Sprague Dawley rats (<b>A</b>) and male C57BL6 mice (<b>B</b>) after single i.p. administration of TG15-132 solution (20 mg/kg b.w.). (<b>C</b>) Brain-to-plasma ratio values.</p>
Full article ">Figure 9
<p>Potential in vivo toxicity of TG15-132. (<b>A</b>) Body weight over the course of the mice (<span class="html-italic">n</span> = 6) treatment with vehicle or TG15-132 (i.p., 20 mg/kg; vehicle: DMSO 10%, PEG400 30%, water 60%). Two-way ANOVA with Tukey’s multiple comparison test was used for analysis. (<b>B</b>) Nox2 inhibitor TG15-132•HCl (20 mg/kg) did not lead to a negative effect on liver or kidney function or to tissue damage. Animals treated with saline, vehicle, or TG15-132•HCl (20 mg/kg) were sacrificed, blood was collected with cardiac puncture, and serum was isolated. Serum was analyzed for kidney function using blood urea nitrogen (BUN) and creatinine (CREAT), liver function using alanine amino transferase (ALT), and tissue damage using lactate dehydrogenase (LDH). One-way ANOVA with Tukey’s multiple comparison test was used for analysis. ** <span class="html-italic">p</span> &lt; 0.01.</p>
Full article ">Scheme 1
<p>Synthesis of Nox2 inhibitors. Reagents and conditions are shown in arrows, and the yields are shown in parentheses.</p>
Full article ">Scheme 2
<p>Synthesis of TG15-293, TG17-56, and TG17-57 compounds. Reagents and conditions are shown in arrows, and the yields are shown in parentheses.</p>
Full article ">
9 pages, 7580 KiB  
Case Report
Multiple Independent Gene Disorders Causing Bardet–Biedl Syndrome, Congenital Hypothyroidism, and Hearing Loss in a Single Indian Patient
by Isabella Peixoto de Barcelos, Dong Li, Deborah Watson, Elizabeth M. McCormick, Lisa Elden, Thomas S. Aleman, Erin C. O’Neil, Marni J. Falk and Hakon Hakonarson
Brain Sci. 2023, 13(8), 1210; https://doi.org/10.3390/brainsci13081210 - 16 Aug 2023
Viewed by 1533
Abstract
We report a 20-year-old, female, adopted Indian patient with over 662 Mb regions of homozy-gosity who presented with intellectual disability, ataxia, schizophrenia, retinal dystrophy, moder-ate-to-severe progressive sensorineural hearing loss (SNHL), congenital hypothyroidism, cleft mi-tral valve with mild mitral valve regurgitation, and dysmorphic features. [...] Read more.
We report a 20-year-old, female, adopted Indian patient with over 662 Mb regions of homozy-gosity who presented with intellectual disability, ataxia, schizophrenia, retinal dystrophy, moder-ate-to-severe progressive sensorineural hearing loss (SNHL), congenital hypothyroidism, cleft mi-tral valve with mild mitral valve regurgitation, and dysmorphic features. Exome analysis first on a clinical basis and subsequently on research reanalysis uncovered pathogenic variants in three nu-clear genes following two modes of inheritance that were causal to her complex phenotype. These included (1) compound heterozygous variants in BBS6 potentially causative for Bardet–Biedl syn-drome 6; (2) a homozygous, known pathogenic variant in the stereocilin (STRC) gene associated with nonsyndromic deafness; and (3) a homozygous variant in dual oxidase 2 (DUOX2) gene asso-ciated with congenital hypothyroidism. A variant of uncertain significance was identified in a fourth gene, troponin T2 (TNNT2), associated with cardiomyopathy but not the cleft mitral valve, with mild mitral regurgitation seen in this case. This patient was the product of an apparent first-degree relationship, explaining the multiple independent inherited findings. This case high-lights the need to carefully evaluate multiple independent genetic etiologies for complex pheno-types, particularly in the case of consanguinity, rather than presuming unexplained features are expansions of known gene disorders. Full article
(This article belongs to the Special Issue Neurogenetic Disorders across Human Life: From Infancy to Adulthood)
Show Figures

Figure 1

Figure 1
<p>(<b>A</b>) Color fundus photography of the central retina. The asterisk marks depigmented foveal center, the white arrow points to parafoveal islands of better-preserved retinal pigment epithelium (RPE), and the yellow arrow points to bone spicule pigment. (<b>B</b>) Horizontal, 3 mm, SD-OCT cross-section through the fovea and nasal retina at two ages. Nuclear layers are labeled: outer nuclear layer = ONL, inner nuclear layer = INL, ganglion cell layer = GCL, retinal nerve fiber layer = RNFL, and basal retinal pigment epithelium = RPE. The ONL can be seen bracketed between the outer plexiform layer (OPL) and the RPE/Bruch’s membrane (RPE/BrM). Arrow in the parafovea at age 20 points to a segment where signals superficial to the RPE may correspond with detectable but short inner and/or outer segments. (<b>C</b>) Horizontal, 16 mm, SD-OCT vertical cross-section through the fovea at age 20. Inset shows the location of the scan. Arrow points to intraretinal hyperreflectivity corresponding to intraretinal pigment migration and bone spicule formation in a thinner mid-peripheral retina. Scale bars to the bottom right. Only the right eye is shown for clarity; left eye is nearly identical.</p>
Full article ">Figure 2
<p>Audiograms (<b>Left</b>: at 16 years old. <b>Right</b>: at 18 years old). Bilateral moderate-to-profound progressive hearing loss. The sign “O” stands for right ear unmasked air conduction. The symbol “X” stands for left ear unmasked air conduction. The symbol “[” stands for right ear masked bone conduction. The sign “]” stands for right ear masked bone conduction.</p>
Full article ">Figure 3
<p>Head circumference or occipitofrontal circumference (OFC) measurements.</p>
Full article ">
13 pages, 2577 KiB  
Article
Homeostatic Regulation of the Duox-ROS Defense System: Revelations Based on the Diversity of Gut Bacteria in Silkworms (Bombyx mori)
by Qilong Shu, Xiqian Guo, Chao Tian, Yuanfei Wang, Xiaoxia Zhang, Jialu Cheng, Fanchi Li and Bing Li
Int. J. Mol. Sci. 2023, 24(16), 12731; https://doi.org/10.3390/ijms241612731 - 12 Aug 2023
Cited by 3 | Viewed by 2012
Abstract
The Duox-ROS defense system plays an important role in insect intestinal immunity. To investigate the role of intestinal microbiota in Duox-ROS regulation herein, 16S rRNA sequencing technology was utilized to compare the characteristics of bacterial populations in the midgut of silkworm after different [...] Read more.
The Duox-ROS defense system plays an important role in insect intestinal immunity. To investigate the role of intestinal microbiota in Duox-ROS regulation herein, 16S rRNA sequencing technology was utilized to compare the characteristics of bacterial populations in the midgut of silkworm after different time-periods of treatment with three feeding methods: 1–4 instars artificial diet (AD), 1–4 instars mulberry leaf (ML) and 1–3 instars artificial diet + 4 instar mulberry leaf (TM). The results revealed simple intestinal microbiota in the AD group whilst microbiota were abundant and variable in the ML and TM silkworms. By analyzing the relationship among intestinal pH, reactive oxygen species (ROS) content and microorganism composition, it was identified that an acidic intestinal environment inhibited the growth of intestinal microbiota of silkworms, observed concurrently with low ROS content and a high activity of antioxidant enzymes (SOD, TPX, CAT). Gene expression associated with the Duox-ROS defense system was detected using RT-qPCR and identified to be low in the AD group and significantly higher in the TM group of silkworms. This study provides a new reference for the future improvement of the artificial diet feeding of silkworm and a systematic indicator for the further study of the relationship between changes in the intestinal environment and intestinal microbiota balance caused by dietary alterations. Full article
(This article belongs to the Special Issue Gut Microbiota–Host Interactions: From Symbiosis to Dysbiosis 2.0)
Show Figures

Figure 1

Figure 1
<p>Flow chart of the experiment. Three different treatment groups were fed to silkworms: 1–4 instars artificial diet (AD), 1–4 instars mulberry leaf (ML) and 1–3 instars artificial diet + 4 instar mulberry leaf (TM). 16S rRNA sequencing was used to compare the changing characteristics of the microorganisms of the intestinal microbiota of silkworms in relation to interactions with the intestinal immune system, DUOX-ROS.</p>
Full article ">Figure 2
<p>α-Diversity of the gut microbiota of <span class="html-italic">B. mori</span>. (<b>A</b>) Shannon index. (<b>B</b>) Simpson index. (<b>C</b>) Chao1 index. (<b>D</b>) Ace index (<span class="html-italic">n</span> = 5 in each group). <span class="html-italic">p</span> &lt; 0.05 (*); <span class="html-italic">p</span> &lt; 0.01 (**); <span class="html-italic">p</span> &lt; 0.001 (***); NS, not significant by Student’s <span class="html-italic">t</span>-test.</p>
Full article ">Figure 3
<p>Dynamics of the gut microbial community of the <span class="html-italic">B. mori</span>. (<b>A</b>) Venn diagram displaying the number of OTUs distributed. (<b>B</b>) Relative abundance of bacterial phyla level in different samples. (<b>C</b>) Visualization of gut bacterial community clusters in <span class="html-italic">B. mori</span> on PCoA plots (97% similarity level) based on Bray–Curtis distances (ANOSIM, <span class="html-italic">p</span> = 0.001). (<b>D</b>) Visualization of gut bacterial community clusters in <span class="html-italic">B. mori</span> on NMDS plots (97% similarity level) based on Bray–Curtis distances (ANOSIM, <span class="html-italic">p</span> = 0.001) (<span class="html-italic">n</span> = 5 in each group).</p>
Full article ">Figure 4
<p>Differences in the composition of the intestinal microbiota of the <span class="html-italic">B. mori</span>. (<b>A</b>) Heat map illustrating the relative abundance of dominant bacterial genera. Each column represents a silkworm larva. (<b>B</b>) Differences in microbiota between the TM and ML groups at 24 h. (<b>C</b>) Differences in microbiota between the TM and ML groups at 48 h.</p>
Full article ">Figure 5
<p>ROS-level detection and antioxidant enzyme activity. (<b>A</b>) ROS-level detection. (<b>B</b>) <span class="html-italic">Mesh</span>, (<b>C</b>) <span class="html-italic">Arrestin</span> and (<b>D</b>) <span class="html-italic">Duox</span>; Duox-ROS-related genes; (<b>E</b>) SOD, (<b>F</b>) TPX and (<b>G</b>) CAT; antioxidant enzyme activity. The results are indicated as mean ± SE (<span class="html-italic">n</span> = 5). <span class="html-italic">p</span> &lt; 0.05 (*); <span class="html-italic">p</span> &lt; 0.01 (**); <span class="html-italic">p</span> &lt; 0.001 (***); NS, Not significant by Student’s <span class="html-italic">t</span>-test.</p>
Full article ">Figure 6
<p>Body weight and ROS levels of silkworms fed with <span class="html-italic">E. cloacae</span>. (<b>A</b>) Weight of larvae of the silkworm. (<b>B</b>) ROS-level detection. <span class="html-italic">p</span> &lt; 0.01 (**); <span class="html-italic">p</span> &lt; 0.001 (***); NS, not significant by Student’s <span class="html-italic">t</span>-test.</p>
Full article ">
19 pages, 3505 KiB  
Article
Expression Profiling along the Murine Intestine: Different Mucosal Protection Systems and Alterations in Tff1-Deficient Animals
by Franz Salm, Eva B. Znalesniak, Aikaterini Laskou, Sönke Harder, Hartmut Schlüter and Werner Hoffmann
Int. J. Mol. Sci. 2023, 24(16), 12684; https://doi.org/10.3390/ijms241612684 - 11 Aug 2023
Cited by 3 | Viewed by 1711
Abstract
Tff1 is a typical gastric peptide secreted together with the mucin, Muc5ac. Tff1-deficient (Tff1KO) mice are well known for their prominent gastric phenotype and represent a recognized model for antral tumorigenesis. Notably, intestinal abnormalities have also been reported in [...] Read more.
Tff1 is a typical gastric peptide secreted together with the mucin, Muc5ac. Tff1-deficient (Tff1KO) mice are well known for their prominent gastric phenotype and represent a recognized model for antral tumorigenesis. Notably, intestinal abnormalities have also been reported in the past in these animals. Here, we have compared the expression of selected genes in Tff1KO mice and their corresponding wild-type littermates (RT-PCR analyses), focusing on different mucosal protection systems along the murine intestine. As hallmarks, genes were identified with maximum expression in the proximal colon and/or the duodenum: Agr2, Muc6/A4gnt/Tff2, Tff1, Fut2, Gkn2, Gkn3, Duox2/Lpo, Nox1. This is indicative of different protection systems such as Tff2/Muc6, Tff1-Fcgbp, gastrokines, fucosylation, and reactive oxygen species (ROS) in the proximal colon and/or duodenum. Few significant transcriptional changes were observed in the intestine of Tff1KO mice when compared with wild-type littermates, Clca1 (Gob5), Gkn1, Gkn2, Nox1, Tff2. We also analyzed the expression of Tff1, Tff2, and Tff3 in the pancreas, liver, and lung of Tff1KO and wild-type animals, indicating a cross-regulation of Tff gene expression. Furthermore, on the protein level, heteromeric Tff1-Fcgbp and various monomeric Tff1 forms were identified in the duodenum and a high-molecular-mass Tff2/Muc6 complex was identified in the proximal colon (FPLC, proteomics). Full article
(This article belongs to the Section Biochemistry)
Show Figures

Figure 1

Figure 1
<p>Semi-quantitative RT-PCR analyses. <span class="html-italic">A4gnt</span>, <span class="html-italic">Agr2</span>, <span class="html-italic">Cdx1</span>, <span class="html-italic">Cdx2</span>, <span class="html-italic">Clca1</span>, <span class="html-italic">Duox2</span>, <span class="html-italic">Fcgbp</span>, <span class="html-italic">Fut2</span>, <span class="html-italic">Gast</span>, <span class="html-italic">Gkn1</span>, <span class="html-italic">Gkn2</span>, <span class="html-italic">Gkn3</span>, <span class="html-italic">Mki67</span>, <span class="html-italic">Lgr5</span>, <span class="html-italic">Lpo</span>, <span class="html-italic">Muc2</span>, <span class="html-italic">Muc6</span>, <span class="html-italic">Nox1</span>, <span class="html-italic">Pdia3</span>, <span class="html-italic">Pdia6</span>, <span class="html-italic">Pdx1</span>, <span class="html-italic">Qsox1</span>, <span class="html-italic">Sod1</span>, <span class="html-italic">Sod2</span>, <span class="html-italic">Sod3</span>, <span class="html-italic">Spdef</span>, <span class="html-italic">Tff1</span>, <span class="html-italic">Tff2</span>, <span class="html-italic">Tff3</span>, and <span class="html-italic">Zg16</span> expression in different parts of the murine intestine, i.e., proximal, medial, and distal parts of the duodenum (pD, mD, dD), middle section of the jejunum (J), distal ileum (I), and proximal/ascending colon (aC). Extracts of 10 female wild-type (WT, black bars) and 10 female <span class="html-italic">Tff1</span><sup>KO</sup> mice (white bars) were investigated. The number of amplification cycles is given after each gene. The relative gene expression levels were normalized against β-actin (<span class="html-italic">Actb</span>, 23x or 24x). Significances are indicated by asterisks (*, <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 2
<p>Semi-quantitative RT-PCR analyses (murine pancreas, liver, and lung). <span class="html-italic">Tff1</span>, <span class="html-italic">Tff2</span>, and <span class="html-italic">Tff3</span> expression was monitored in extracts of 10 female wild-type (WT, black bars) and 10 female <span class="html-italic">Tff1</span><sup>KO</sup> mice (white bars). The number of amplification cycles is given after each gene. The relative gene expression levels were normalized against β-actin (<span class="html-italic">Actb</span>; pancreas 27x, liver 24x, lung 21x). Significances are indicated by asterisks (***, <span class="html-italic">p</span> ≤ 0.001).</p>
Full article ">Figure 3
<p>Analysis of a murine duodenal extract (complete duodena from four animals). The elution profile after SEC on a Superdex 75 HL column as well as the distribution of Tff2 have been reported previously [<a href="#B22-ijms-24-12684" class="html-bibr">22</a>]. (<b>A</b>) Distribution of the relative Tff1 (black) and Tff3 contents (green) as determined via Western blot analysis under reducing conditions and semi-quantitative analysis of monomeric band intensities. For Tff1, a regular band (black drawn line) and a somewhat shortened band (black dashed line) were analyzed separately. For comparison, the fractions were analyzed for their mucin content using the PAS reaction (pink); (<b>B</b>) 15% SDS-PAGE under reducing (R) and non-reducing (NR) conditions (post-in-gel reduction), respectively, and Western blot analysis of the high-molecular-mass fraction B8 and the low-molecular-mass fractions D3 and D5 concerning Tff1. As a control, fraction D1 from a murine stomach extract (St; [<a href="#B22-ijms-24-12684" class="html-bibr">22</a>]) was analyzed. (<b>C</b>) Analysis of the high-molecular-mass fractions B8–B10 concerning Tff3; (<b>D</b>) 1% AgGE and Western blot analysis of the high-molecular-mass fractions B8 and B9 concerning Tff3, Fcgbp, and Tff1, respectively (D, duodenal extract; Cae+C, extract from caecum plus total colon). Relative standard: DNA ladder (base pairs).</p>
Full article ">Figure 4
<p>Proteome analysis of the high- and low-molecular-mass forms of Tff1 in a duodenal extract (fractions B8, and D1, D3, and D5 from <a href="#ijms-24-12684-f003" class="html-fig">Figure 3</a>). (<b>A</b>,<b>B</b>) SDS-PAGE under reducing conditions of the high-molecular mass fractions B7–B10 (<b>A</b>) and the low-molecular-mass fractions C12–D7 (<b>B</b>) and Western blot analysis concerning Tff1. Fractions B8, D1, D3, and D5 were then separated via preparative reducing of SDS-PAGE, and after Coomassie staining, bands termed B8, D1, D3a, D3b, and D5 were excised (marked in red). (<b>C</b>) Results of the proteome analyses after tryptic in-gel digestion of bands B8, D1, D3a, D3b, and D5. Identified regions in Tff1 are shown in red. In B8, Tff3 was also identified. The results of the Tff1 reference (from a stomach extract) are also shown. The longest N-terminal sequences identified are shown. (<b>D</b>) Identification of heterogeneous Tff1 N-terminal sequences in bands D3b and the stomach reference (q indicates a pyro-Glu residue). The predominant sequences are underlined.</p>
Full article ">Figure 5
<p>Analysis of a murine caecum plus total colon extract (single individual). (<b>A</b>) Elution profile after SEC on a Superdex 75 HL column as determined via absorbance at 280 nm (PAS-positive mucin fractions: pink). Underneath: distribution of the relative Tff2 (red) and Tff3 contents (green) as determined via Western blot analysis under reducing conditions and semi-quantitative analysis of the monomeric band intensities; (<b>B</b>) 15% SDS-PAGE under reducing (R) and non-reducing (NR) conditions (post-in-gel reduction), respectively, and Western blot analysis of the high-molecular-mass fractions B8–B10 concerning Tff2; (<b>C</b>) 1% AgGE and Western blot analysis of the fractions B6–C2 concerning Muc6 (lectin GSA-II). Relative standard: DNA ladder (base pairs). (<b>D</b>) SDS-PAGE under reducing conditions of fraction B8. Shown is a Western blot analysis concerning Tff2 and in parallel, Coomassie staining. Bands 1 and 2 were excised for proteome analysis. (<b>E</b>) Results of the proteome analysis after tryptic in-gel digestion of bands 1 and 2. Identified regions in Tff2 are shown in red.</p>
Full article ">Figure 6
<p>Schematic structure of the murine intestine and its different mucosal protection systems. Shown are stomach (Sto); proximal (pD), medial (mD), and distal parts of the duodenum (dD); jejunum (J); ileum (I); caecum (Cae); ascending/proximal (aC), transverse/medial (tC), and descending/distal colon (dC); rectum (R). The regions investigated in this study via RT-PCR are hatched. The predominant localization of the different intestinal protection systems is indicated.</p>
Full article ">
13 pages, 2145 KiB  
Article
Dual Role of DUOX1-Derived Reactive Oxygen Species in Melanoma
by Irene Pardo-Sánchez, Sofía Ibañez-Molero, Diana García-Moreno and Victoriano Mulero
Antioxidants 2023, 12(3), 708; https://doi.org/10.3390/antiox12030708 - 13 Mar 2023
Cited by 1 | Viewed by 2200
Abstract
Melanoma is the most serious type of skin cancer. Inflammation and oxidative stress play an essential role in the development of several types of cancer, including melanoma. Although oxidative stress promotes tumor growth, once cells escape from the primary tumor, they are subjected [...] Read more.
Melanoma is the most serious type of skin cancer. Inflammation and oxidative stress play an essential role in the development of several types of cancer, including melanoma. Although oxidative stress promotes tumor growth, once cells escape from the primary tumor, they are subjected to a more hostile environment, with higher levels of oxidative stress typically killing most cancer cells. As Dual Oxidase 1 (DUOX1) is a major producer of reactive oxygen species (ROS) in epithelia, we used allotransplantation and autochthonous melanoma models in zebrafish together with in silico analysis of the occurrence and relevance of DUOX1 expression of the skin cutaneous melanoma (SKCM) cohort of The Cancer Genome Atlas (TCGA) to address the role of this enzyme in the aggressiveness of melanoma cells in vivo. It was found that high transcript levels of the gene encoding DUOX1 were associated with the poor prognosis of patients in the early-stage melanoma of TCGA cohort. However, DUOX1 transcript levels were not found to be associated to the prognosis of late-stage SKCM patients. In addition, the transcript level of DUOX1 in metastatic SKCM was lower than in primary SKCM. Using zebrafish primary melanoma and allotransplantation models, we interrogated the role of DUOX1 in vivo. Our results confirmed a dual role of DUOX1, which restrains melanoma proliferation but promotes metastasis. As this effect is only observed in immunocompromised individuals, the immune system appears to be able to counteract this elevated metastatic potential of DUOX1-deficient melanomas. Full article
Show Figures

Figure 1

Figure 1
<p><b><span class="html-italic">DUOX1</span> expression correlates with survival in SKCM patients and decreases in metastatic SKCM.</b> (<b>A</b>) Kaplan–Meier survival analysis of TCGA cohort of early- (I + II + III Clark levels at diagnosis) and late- (IV and V Clark levels at diagnosis) stage SKCM patients according to their <span class="html-italic">DUOX1</span> transcript levels: first quartile (Low), second and third (Medium) and fourth (High). Early-stage melanoma: Low, <span class="html-italic">n</span> = 22; Medium, <span class="html-italic">n</span> = 59; High, <span class="html-italic">n</span> = 16. Late-stage melanoma: Low, <span class="html-italic">n</span> = 57; Medium, <span class="html-italic">n</span> = 100; High, <span class="html-italic">n</span> = 60. Statistical significance was calculated with Mantel–Cox test. (<b>B</b>) Kaplan–Meier survival analysis of TCGA cohort of SKCM patients according to Clark-level classification at diagnosis: early-stage (I + II + III, <span class="html-italic">n</span> = 99) and late-stage (IV + V, <span class="html-italic">n</span> = 217). Statistical significance was calculated with Mantel–Cox test. (<b>C</b>) DUOX1 transcript levels in primary (<span class="html-italic">n</span> = 102) and metastatic (<span class="html-italic">n</span> = 360) SKCMs from TCGA cohort. Each dot represents a patient, and the mean is also shown. **** <span class="html-italic">p</span> &lt; 0.0001 according to unpaired Student <span class="html-italic">t</span> test. a.u., arbitrary units.</p>
Full article ">Figure 2
<p><b>Melanocyte DUOX1 inhibition does not affect melanocyte transformation and early melanoma progression.</b> (<b>A</b>) Schematic representation of the procedure to co-express oncogenic NRAS-Q61R and DN-DUOX1 in melanocytes. Zebrafish one-cell Casper zebrafish embryos were injected with MinicoopR <span class="html-italic">mitfa:NRAS-Q61R</span> and either MinicoopR <span class="html-italic">mitfa:DN-DUOX1</span> or MinicoopR <span class="html-italic">mitfa:EGFP</span> (control). Larvae were examined at 5 dpf for the presence of melanocytes and images were acquired monthly for 3 months to track melanoma development. (<b>B</b>) Representative images of the five different categories established to classify tumor progression. (<b>C</b>) Percentages of fish in the different categories at 30, 60, 75 and 90 dpf. (<b>D</b>) Tumor free curve. Representation of the percentage of fish without nodular tumors.</p>
Full article ">Figure 3
<p><b>DUOX1 inhibition autonomously reduces aggressiveness and growth of transplanted SKCMs.</b> (<b>A</b>) Schematic diagram showing adult allotransplantation procedure. One-year-old Casper zebrafish were irradiated 2 days before transplantation to prevent tumor rejection. Three hundred thousand cells from the nodular tumors of either MinicoopR <span class="html-italic">mitfa:NRAS-QW61R</span>/<span class="html-italic">mitfa:DN-DUOX1</span> or MinicoopR <span class="html-italic">mitfa:NRAS-Q61R</span>/<span class="html-italic">mitfa:EGFP</span> (control) fish were subcutaneously injected in pre-irradiated recipients, and images were taken weekly during the following 4 weeks after transplantation and analyzed as indicated in the Methods and Materials section. Arrow, timeline; dpi, days post-injection; wpt, weeks post-transplant. (<b>B</b>) Representative images of transplanted melanoma growth rate of MinicoopR <span class="html-italic">mitfa:NRAS-QW61R</span>/<span class="html-italic">mitfa:DN-DUOX1</span> and MinicoopR <span class="html-italic">mitfa:NRAS-Q61R</span>/<span class="html-italic">mitfa:EGFP</span> in pre-irradiated adult Casper zebrafish. (<b>C</b>) Average tumor size for each week post-transplant. Each dot represents a recipient-transplanted fish, and the mean is also shown. ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001 according to unpaired Student <span class="html-italic">t</span> test. (<b>D</b>) Growth rate of transplanted MinicoopR <span class="html-italic">mitfa:NRAS-QW61R</span>/<span class="html-italic">mitfa:DN-DUOX1</span> and MinicoopR <span class="html-italic">mitfa:NRAS-Q61R</span>/<span class="html-italic">mitfa:EGFP</span> SKCMs. DN-DUOX1: <span class="html-italic">n</span> = 5 tumors and 111 recipient fish; EGFP: <span class="html-italic">n</span> = 3 tumors and 72 recipient fish.</p>
Full article ">Figure 4
<p><b>DUOX1 deficiency in SKCM promotes metastasis.</b> (<b>A</b>) Schematic diagram of adult allotransplantation assays. (<b>B</b>) Representative images of the progression of metastasis (arrows). (<b>C</b>) Metastasis-free curve of adult zebrafish transplanted with MinicoopR <span class="html-italic">mitfa:NRAS-Q61R</span>/<span class="html-italic">mitfa:DN-DUOX1</span> and MinicoopR <span class="html-italic">mitfa:NRAS-Q61R</span>/<span class="html-italic">mitfa:EGFP</span> (control). ** <span class="html-italic">p</span> &lt; 0.01 according to a Log rank Mantel–Cox test. DN-DUOX1: <span class="html-italic">n</span> = 5 tumors and 111 recipient fish; EGFP: <span class="html-italic">n</span> = 3 tumors and 72 recipient fish.</p>
Full article ">
Back to TopTop