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17 pages, 3522 KiB  
Article
Differential Responses of Pediatric and Adult Primary Epithelial Cells to Human Metapneumovirus and Respiratory Syncytial Virus Infection
by Pius I. Babawale and Antonieta Guerrero-Plata
Viruses 2025, 17(3), 380; https://doi.org/10.3390/v17030380 - 6 Mar 2025
Viewed by 232
Abstract
Human metapneumovirus (HMPV) and respiratory syncytial virus (RSV) are pneumoviruses causing lower respiratory tract infections, primarily in infants and children rather than in healthy adults. Human bronchial epithelial cells serve as a viral replication target and source of the innate immune response to [...] Read more.
Human metapneumovirus (HMPV) and respiratory syncytial virus (RSV) are pneumoviruses causing lower respiratory tract infections, primarily in infants and children rather than in healthy adults. Human bronchial epithelial cells serve as a viral replication target and source of the innate immune response to these viruses. To better understand the immune responses induced by RSV and HMPV in the pediatric airway epithelium, we comparatively studied pediatric and adult epithelial responses. We used normal human bronchial epithelial (NHBE) cells cultured in an air–liquid interface culture system (ALI), which helps to mimic the architecture of the human lower respiratory tract epithelium. Our results demonstrate differential viral replication patterns and reduced interferons; and inflammatory cytokines’ expression in pediatric cells compared to adult cells. However, pediatric epithelial cells expressed an increased mucus response and induced a stronger pro-inflammatory response in monocyte-derived dendritic cells. These findings reveal age-dependent immune epithelial responses that may contribute to more severe infections by HMPV and RSV. Full article
(This article belongs to the Section Human Virology and Viral Diseases)
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Figure 1
<p>Age-related differences in NHBE cell susceptibility to HMPV and RSV infection. NHBE cells from pediatric and adult donors cultured at the air–liquid interface (ALI) and infected with RSV or HMPV. (<b>A</b>) After 7 days of HMPV and RSV infection, cells were stained with H&amp;E staining to assess cell morphology; Scale bar = 50 μm. (<b>B</b>) Kinetics of viral copy numbers. Data represent mean ± SEM from three donors for each age group. Statistical significance was determined using two-way ANOVA with Šídák’s multiple comparisons test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001).</p>
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<p>IFN responses of pediatric and adult NHBE cells to RSV and HMPV infection. NHBE cells were infected with RSV or HMPV. Gene expression of (<b>A</b>) type I IFNs (IFN-α2, IFN-β, IFN-ε, and IFN-ω) and (<b>B</b>) type III IFNs (IFN-λ1 and IFN-λ2/3) was assessed by RT-qPCR at different time points. Statistical significance was determined using two-way ANOVA with Šídák’s multiple comparisons test (* <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). Non-significant (ns).</p>
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<p>Differential expression of ISGs by pediatric and adult NHBE cells. Adult and pediatric NHBE cells were differentiated in ALI culture and infected with RSV and HMPV. RNA samples were collected at different time points and analyzed for expression of key ISGs (IFIT1, IFIT2, IFIT3, OAS1, MX1, and ISG15) by RT-qPCR. Statistical significance was determined using two-way ANOVA with Šídák’s multiple comparisons test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Cytokine responses in NHBE cells infected with HMPV or RSV. Adult and pediatric NHBE cells were differentiated in ALI culture and infected with RSV or HMPV. RNA samples were collected at different time points and analyzed by RT-qPCR for the expression of (<b>A</b>) pro-inflammatory cytokines and (<b>B</b>) epithelial alarmins. Statistical significance was determined using two-way ANOVA with Šídák’s multiple comparisons test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, **** <span class="html-italic">p</span> &lt; 0.0001).</p>
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<p>Cytokine release from human epithelial cells infected with HMPV or RSV. Pediatric and adult NHBE cells were grown in ALI culture and infected with HMPV or RSV. Apical washes were collected at different time points after infection, and concentration of cytokines was determined by LEGENDplex multiplex immunoassay. Statistical significance was determined using two-way ANOVA with Dunnett’s multiple comparisons test (* <span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Mucin expression induced by RSV and HMPV in pediatric and adult NHBE cells. NHBE cells were differentiated in ALI culture and infected with RSV and HMPV. (<b>A</b>) Cells were stained with PAS histological staining on day 7 after infection. Scale bar = 50 μm. (<b>B</b>) Further analysis by RT-qPCR assessed the expression of <span class="html-italic">MUC5AC</span> and <span class="html-italic">MUC5B</span> levels. Statistical significance was determined using two-way ANOVA with Šídák’s multiple comparisons test (** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001. Non-significant (ns).</p>
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<p>Induction of inflammatory cytokines in mo-DCs co-cultured with either pediatric or adult NHBE cells. mo-DCs were co-cultured with NHBE cells from either pediatric or adult donors infected with HMPV or RSV. (<b>A</b>) Schematic representation of the co-culture setup: Fully differentiated NHBE cells were infected with HMPV or RSV and cultured with mo-DCs for 3 days. mo-DCs were analyzed for the expression of (<b>B</b>) IL-6, (<b>C</b>) TNF-α, and (<b>D</b>) IL-1β by RT-qPCR. Data represent mean ± SEM, <span class="html-italic">n</span> = 4–6. Statistical significance was determined using the Kruskal–Wallis test (* <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01); non-significant (ns).</p>
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10 pages, 2333 KiB  
Brief Report
Evaluating Probenecid or Oseltamivir Inhibition of Influenza A Virus Replication Through Plaque Assay or Fluorescent Focus Assay Using Non-Structural Protein 1–H1N1 Venus Reporter Virus
by Jackelyn Murray, Aitor Nogales, Luis Martinez-Sobrido, David E. Martin, Fred D. Sancilio and Ralph A. Tripp
Viruses 2025, 17(3), 335; https://doi.org/10.3390/v17030335 - 27 Feb 2025
Viewed by 152
Abstract
It is essential to understand the molecular mechanisms of influenza antiviral therapeutics to evaluate their efficacy. Virus plaque assays are commonly used to assess the antiviral effects of drugs on virus replication; however, this method is labor-intensive and can present challenges. We avoided [...] Read more.
It is essential to understand the molecular mechanisms of influenza antiviral therapeutics to evaluate their efficacy. Virus plaque assays are commonly used to assess the antiviral effects of drugs on virus replication; however, this method is labor-intensive and can present challenges. We avoided this method by using a replication-competent influenza A virus (IAV) expressing a reporter fluorescent gene fused to the non-structural protein 1 (NS1) gene. The reporter IAV was detectable in normal human bronchoepithelial (NHBE) infected cells and offered an improved method to determine the therapeutic efficacy of the antiviral drugs probenecid and oseltamivir compared to a standard plaque assay. This method provides an excellent means for evaluating therapeutic approaches against IAV. Full article
(This article belongs to the Special Issue Pharmacology of Antiviral Drugs)
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Figure 1
<p>NHBE cells were prophylactically treated with probenecid for 24 h before infection with PR8 NS1-Venus (MOI = 0.1). Infection proceeded for 48 h, after which the cells were analyzed. (<b>A</b>) FFAs were performed on an ArrayScan. Panel A is nuclei (Hoechst dye staining), panel B is IAV infection, and panel C is the composite image of the two. (<b>B</b>) Supernatants were collected and titrated on MDCK cells to perform traditional plaque assays. Statistical analysis was performed via one-way ANOVA. The panels are 20×, as determined using the ArrayScan (Thermofisher). There was no detectable virus (ND) in the 3–100 µM concentrations, indicated by ND.</p>
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<p>NHBE cells were prophylactically treated with oseltamivir for 24 h before infection with PR8 NS1-Venus (MOI = 0.1). Infection proceeded for 48 h, after which the cells were analyzed. (<b>A</b>) FFAs were performed on an ArrayScan. Panel A is nuclei (Hoechst dye staining), panel B is IAV infection, and panel C is the composite image of the two. (<b>B</b>) Supernatants were collected and titrated on MDCK cells to perform traditional plaque assays. Statistical analysis was performed via one-way ANOVA. Statistical analysis was performed via one-way ANOVA. The panels are 20×, as determined using the ArrayScan. There was no detectable (ND) virus in the 100 µM concentration for the FFA and ND virus in the 50–100 µM concentrations.</p>
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<p>NHBE cells were infected for 1 h with PR8 NS1-Venus (MOI = 0.1) and therapeutically treated with probenecid. Infection proceeded for 48 h, and the cells were analyzed. (<b>A</b>) FFAs were performed on an ArrayScan. Panel A is nuclei (Hoechst dye staining), panel B is IAV infection, and panel C is the composite image of the two. (<b>B</b>) Supernatants were collected and titrated on MDCK cells to perform traditional plaque assays. Statistical analysis was performed via one-way ANOVA. No detectable (ND) virus was detected in the 12–100 µM concentrations.</p>
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<p>NHBE cells were infected for 1 h with PR8 NS1-Venus (MOI = 0.1) and therapeutically treated with oseltamivir. Infection proceeded for 48 h, and the cells were analyzed. (<b>A</b>) FFAs were performed on an ArrayScan. Panel A is nuclei (Hoechst dye staining), panel B is IAV infection, and panel C is the composite image of the two. (<b>B</b>) Supernatants were collected and titrated on MDCK cells to perform traditional plaque assays. Statistical analysis was performed via one-way ANOVA.</p>
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12 pages, 2736 KiB  
Article
Impact of Nanoparticles as an Air Pollutant on Angulin-1/Lipolysis-Stimulated Lipoprotein Receptor in Asthma
by DaYeon Hwang, Min-Hyeok An, Pureun-Haneul Lee, Jung-Hyun Kim, Yunha Nam, Shinhee Park, Ae-Rin Baek and An-Soo Jang
Atmosphere 2024, 15(12), 1532; https://doi.org/10.3390/atmos15121532 - 20 Dec 2024
Viewed by 624
Abstract
Background: The tricellular tight junction protein angulin-1/lipolysis-stimulated lipoprotein receptor (LSR) is linked to numerous signal transduction pathways that govern gene expression, epithelial cell function, and morphogenesis. The effect of titanium dioxide (TiO2) on LSR and asthma remains unknown. The objective of [...] Read more.
Background: The tricellular tight junction protein angulin-1/lipolysis-stimulated lipoprotein receptor (LSR) is linked to numerous signal transduction pathways that govern gene expression, epithelial cell function, and morphogenesis. The effect of titanium dioxide (TiO2) on LSR and asthma remains unknown. The objective of the present study was to evaluate the impact of TiO2 on LSR expression in asthma. Methods: A TiO2-induced animal model of asthma was established using BALB/c mice and cell lines using normal human bronchial epithelial (NHBE) lung cells and we examined LSR, RAGE, and TGFβ expression using this model. Additionally, we analyzed plasma-LSR concentrations and their correlation with clinical variables in asthma patients and control subjects. Results: The LSR concentrations in patients with asthma were lower compared to controls, and were correlated with lung function and inflammatory cell ratio. In NHBE cells treated with Derp1, LSR protein expression was reduced and changed by exposure to TiO2, whereas TGFβ expression was increased and changed. In mouse lungs, LSR expression was significantly reduced in OVA mice and changed in OVA/TiO2 mice. Conclusion: Circulating LSR levels were decreased and correlated with clinical variables in patients with asthma, and they were influenced by TiO2 exposure in mice, suggesting the potential involvement of LSR in asthma pathogenesis. Full article
(This article belongs to the Special Issue Research on Air Pollution and Human Exposures)
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<p>(<b>A</b>) LSR level in control subject and asthmatic patients. (<b>B</b>) LSR levels in control subjects and asthmatic patients by level of PM 2.5 and PM 10 μg/m<sup>3</sup>. * <span class="html-italic">p</span> &lt; 0.05, control subjects vs. asthmatic patients.</p>
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<p>Relationship of LSR with (<b>A</b>) FEV<sub>1</sub> (L) (r = 0.337, <span class="html-italic">p</span> = 0.014), FEV<sub>1</sub>% predicted (r = 0.347, <span class="html-italic">p</span> = 0.011) and FEV<sub>1</sub>/FVC (r = 0.415, <span class="html-italic">p</span> = 0.002). (<b>B</b>) WBC (r = −0.364, <span class="html-italic">p</span> = 0.007), neutrophils (r = −0.336, <span class="html-italic">p</span> = 0.014), and blood lymphocyte proportion (r = 0.382, <span class="html-italic">p</span> = 0.005) in control subjects and patients with asthma.</p>
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<p>LSR, RAGE, and TGFβ protein determined by Western blot in NHBE cells treated with 10  μg/mL <span class="html-italic">Dermatophagoides pteronyssinus 1</span> (Derp1) and 100 μg/mL TiO<sub>2</sub> for 4, and 24 h. (<b>A</b>) NHBE cells protein level of RAGE, TGFβ and LSR as determined by Western blot. (<b>B</b>) Densitometric data from the Western blots. Densitometry was determined with 3 immunoblots and normalized to β-actin. Data are expressed as means ± SD. Scale bar means 100 μm. * <span class="html-italic">p</span> &lt; 0.05 vs. normal control (NC).</p>
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<p>(<b>A</b>) Experiment protocol of TiO<sub>2</sub> exposure model. (<b>B</b>) Airway hyperresponsiveness (AHR) and inflammation in OVA mice. (<b>C</b>) Total and differential cell count in bronchoalveolar lavage fluid (BALF). BALF was collected on day 25 and cell differentials determined. Values are means ± SEM (n = 6 mice/group). * <span class="html-italic">p</span> &lt; 0.05 vs. sham. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. OVA.</p>
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<p>Lung protein levels of IL-1β, IL-4 and TNF-α as determined by ELISA. Data are expressed as means ± SD. * <span class="html-italic">p</span> &lt; 0.05 vs. sham. <sup>#</sup> <span class="html-italic">p</span> &lt; 0.05 vs. OVA.</p>
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<p>(<b>A</b>) Lung protein level of RAGE, TGFβ and LSR as determined by Western blot. (<b>B</b>) Densitometric data from the Western blots. Densitometry was determined with 3 immunoblots and normalized to β-actin. (<b>C</b>) Hematoxylin &amp; eosin (H&amp;E)-stained lung tissue and LSR immunohistochemical staining of mouse lung tissue sections. (<b>D</b>) Inflammatory index and quantification of LSR expression. (<b>E</b>) Immunofluorescence of LSR in lung tissue. Data are expressed as means ± SD. Scale bar means 100 μm. * <span class="html-italic">p</span> &lt; 0.05 vs. sham.</p>
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18 pages, 3044 KiB  
Article
Interferon Epsilon-Mediated Antiviral Activity Against Human Metapneumovirus and Respiratory Syncytial Virus
by Iván Martínez-Espinoza, Pius I. Babawale, Hannah Miletello, Nagarjuna R. Cheemarla and Antonieta Guerrero-Plata
Vaccines 2024, 12(10), 1198; https://doi.org/10.3390/vaccines12101198 - 21 Oct 2024
Viewed by 2165
Abstract
Background: Interferon epsilon (IFN-ε) is a type I IFN that plays a critical role in the host immune response against pathogens. Despite having demonstrated antiviral activity in macrophages and mucosal tissues such as the female reproductive tract and the constitutive expression in mucosal [...] Read more.
Background: Interferon epsilon (IFN-ε) is a type I IFN that plays a critical role in the host immune response against pathogens. Despite having demonstrated antiviral activity in macrophages and mucosal tissues such as the female reproductive tract and the constitutive expression in mucosal tissues such as the lung, the relevance of IFN-ε against respiratory viral infections remains elusive. Results: We present, for the first time, the expression of IFN-ε in alveolar epithelial cells and primary human bronchial epithelial cells grown in an air–liquid interface (ALI) in response to human metapneumovirus (HMPV) and respiratory syncytial virus (RSV) infection. The molecular characterization of the IFN-ε induction by the viruses indicates that the expression of RIG-I is necessary for an optimal IFN-ε expression. Furthermore, treatment of the airway epithelial cells with rhIFN-ε induced the expression of IFN-stimulated genes (ISGs) and significantly restricted the viral replication of HMPV and RSV. Conclusions: These findings underscore the relevance of IFN-ε against viral infections in the respiratory tract. Full article
(This article belongs to the Special Issue Adaptive and Innate Response to Viral Disease)
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<p>Expression of IFN-ε by HMPV in A549 cells. Cells were infected with HMPV or RSV at an MOI 1 and cultured for 72 h. Cell lysates were collected at different time points after infection and analyzed by RT-qPCR to determine (<b>A</b>) the expression of IFN-ε (n = 4); (<b>B</b>) the viral copy numbers of the N protein gene for HMPV and RSV (n = 3); and (<b>C</b>) the expression of IFN-α and IFN-β (n = 4). The bar graphs represent the mean ± standard errors of the means. Statistical differences were calculated using ANOVA followed by a Sidak’s multiple comparison test * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> ≤ 0.001. Uninfected (U).</p>
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<p>Role of PRRs in IFN-ε expression by RSV and HMPV. (<b>A</b>) Western blot of KO A549 cell lines lacking MyD88, RIG-I, or MDA-5. GAPDH was used as a housekeeping gene control. (<b>B</b>) KO A549 cells were infected with HMPV or RSV at an MOI of 1.0 for 48 h. Cell lysates were collected and analyzed for IFN-ε. Fold Increase Expression was determined by RT-qPCR. The bar graphs represent the mean ± standard errors of the means (n = 3). Statistical differences were calculated using ANOVA followed by a Tukey’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Induction of ISGs in A549 cells. Cells were treated with increasing concentrations of rhIFN-ε for 24 h. (<b>A</b>) To determine cell viability, cells were collected and stained with 7-AAD and analyzed by flow cytometry. The bar graphs show the percentage of 7-AAD-positive cells. Contour plots show representative data of 7-AAD positive cells. (<b>B</b>) Relative expression of ISGs was assessed with RT-qPCR and normalized to GAPDH. The bar graphs represent the mean ± standard errors of the means (n = 3). Statistical differences were calculated using ANOVA followed by Dunnett’s multiple comparison test. ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> &lt; 0.001; **** <span class="html-italic">p</span> ≤ 0.0001. Non-significant (ns).</p>
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<p>Susceptibility of RSV and HMPV infection to IFN-ε. A549 cells were treated with increasing concentrations of rhIFN-ε for 24 h followed by infection with HMPV or RSV at an MOI of 1.0 for 24 h. Susceptibility was determined by a reduction in the fluorescence signal using the incucyte<sup>®</sup> system. (<b>A</b>) Representative images of fluorescence from cells infected with HMPV-GFP (upper panel) or rrRSV (lower panel). Size bar 800 μm. (<b>B</b>,<b>C</b>) Fluorescence intensity represented in a percentage from the untreated cells infected with (<b>B</b>) HMPV or (<b>C</b>) RSV. The bar graphs represent the mean ± standard errors of the means (n = 5). Statistical differences were calculated using ANOVA followed by a Dunnett’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01; **** <span class="html-italic">p</span> ≤ 0.0001. Non-significant (ns).</p>
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<p>Effect of IFN-ε on RSV and HMPV infection in A549 cells. Cells were treated with increasing concentrations of rhIFN-ε for 24 h followed by infection with (<b>A</b>) HMPV or (<b>B</b>) RSV at an MOI of 1.0 for 24 h. Viral titers were quantified in cell supernatants by a plaque assay. Virus yield is expressed as a percentage relative to the untreated infected cells. The bar graphs represent the mean ± standard errors of the means (n = 4). Statistical differences were calculated using ANOVA followed by a Dunn’s multiple comparison test. * <span class="html-italic">p</span> &lt; 0.05; ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Induction of IFN-ε in primary bronchial epithelial cells. NHBE cells were grown and differentiated in ALI conditions. ALI-cultured cells were infected with HMPV or RSV at an MOI of 0.02. Cell lysates were collected at 0.5, 1, 3, 5, and 7 days after infection and analyzed for the expression of IFN-ε by (<b>A</b>) RT-qPCR. The bar graphs represent the mean ± standard errors of the means (n = 3 donors). Statistical differences were calculated using ANOVA followed by a Sidak’s multiple comparison ** <span class="html-italic">p</span> &lt; 0.01; *** <span class="html-italic">p</span> ≤ 0.001; **** <span class="html-italic">p</span> ≤ 0.0001; and (<b>B</b>) Immunohistochemistry. Cells were fixed at day 7 after infection and analyzed for the expression of IFN-ε. Bar = 50 μm. Uninfected (U).</p>
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<p>Effect of IFN-ε on RSV and HMPV infection in primary bronchial epithelial cells. NHBE cells were grown and differentiated in an air liquid interface (ALI). Cells were treated with 250 ng/mL of rhIFN-ε for 24 h followed by infection with (<b>A</b>) HMPV or (<b>B</b>) RSV at an MOI of 0.02 for 3 days. Viral load was assessed by RT-qPCR to quantify the absolute number of viral copies. Virus yield is expressed as a percentage relative to the untreated infected cells. The bar graphs represent the mean ± standard errors of the means (n = 4 donors). Statistical differences were calculated using a student <span class="html-italic">t</span>-test. * <span class="html-italic">p</span> &lt; 0.05. Non-significant (ns).</p>
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20 pages, 8821 KiB  
Article
The Modulation of Respiratory Epithelial Cell Differentiation by the Thickness of an Electrospun Poly-ε-Carprolactone Mesh Mimicking the Basement Membrane
by Seon Young Choi, Hyun Joo Kim, Soyoung Hwang, Jangho Park, Jungkyu Park, Jin Woo Lee and Kuk Hui Son
Int. J. Mol. Sci. 2024, 25(12), 6650; https://doi.org/10.3390/ijms25126650 - 17 Jun 2024
Viewed by 1239
Abstract
The topology of the basement membrane (BM) affects cell physiology and pathology, and BM thickening is associated with various chronic lung diseases. In addition, the topology of commercially available poly (ethylene terephthalate) (PET) membranes, which are used in preclinical in vitro models, differs [...] Read more.
The topology of the basement membrane (BM) affects cell physiology and pathology, and BM thickening is associated with various chronic lung diseases. In addition, the topology of commercially available poly (ethylene terephthalate) (PET) membranes, which are used in preclinical in vitro models, differs from that of the human BM, which has a fibrous and elastic structure. In this study, we verified the effect of BM thickness on the differentiation of normal human bronchial epithelial (NHBE) cells. To evaluate whether the thickness of poly-ε-carprolactone (PCL) mesh affects the differentiation of NHBE cells, cells were grown on thin- (6-layer) and thick-layer (80-layer) meshes consisting of electrospun PCL nanofibers using an air–liquid interface (ALI) cell culture system. It was found that the NHBE cells formed a normal pseudostratified epithelium composed of ciliated, goblet, and basal cells on the thin-layer PCL mesh; however, goblet cell hyperplasia was observed on the thick-layer PCL mesh. Differentiated NHBE cells cultured on the thick-layer PCL mesh also demonstrated increased epithelial–mesenchymal transition (EMT) compared to those cultured on the thin-layer PCL mesh. In addition, expression of Sox9, nuclear factor (NF)-κB, and oxidative stress-related markers, which are also associated with goblet cell hyperplasia, was increased in the differentiated NHBE cells cultured on the thick-layer PCL mesh. Thus, the use of thick electrospun PCL mesh led to NHBE cells differentiating into hyperplastic goblet cells via EMT and the oxidative stress-related signaling pathway. Therefore, the topology of the BM, for example, thickness, may affect the differentiation direction of human bronchial epithelial cells. Full article
(This article belongs to the Section Materials Science)
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Figure 1
<p>Characterization of electrospun PCL meshes. Characterization of the 6- and 80-layer electrospun PCL meshes. (<b>a</b>) Surface morphology of 6-layer PCL mesh. (<b>b</b>) Cross-sectional image of 6-layer PCL mesh. (<b>c</b>) Surface morphology of 80-layer PCL mesh. (<b>d</b>) Cross-sectional image of 80-layer PCL mesh. (<b>e</b>) Stress–strain diagrams of the two different PCL meshes. (<b>f</b>) Comparison of elastic modulus of the two different PCL meshes. (<b>g</b>) Comparison of the ultimate tensile strengths of the two different PCL meshes. “n.s” indicates not significant (<span class="html-italic">p</span> &gt; 0.05).</p>
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<p>Airway epithelium on PCL mesh. (<b>a</b>) Scheme for the growth and differentiation of NHBE cells on the PCL mesh insert. (<b>b</b>) Viability of NHBE cells during the ALI on the 6- and 80-layer PCL meshes and PET Transwell inserts. Significance is denoted as * <span class="html-italic">p</span> &lt; 0.05. (<b>c</b>) TEER values of NHBE cells differentiated on 6- and 80-layer PCL meshes. TEER (Ω × cm<sup>2</sup>) was quantified during the ALI. (<b>d</b>) H&amp;E staining images of sectioned airway epithelium for 28 days (ALI) on 6- and 80-layer PCL meshes. Objective: 40×; scale bars: 20 μm.</p>
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<p>Establishment of normal and diseased airway epithelium on the 6- and 80-layer PCL meshes. (<b>a</b>) mRNA expression of specific cell markers in differentiated NHBE cells cultured on 6- and 80-layer PCL meshes. All data shown were obtained from at least three independent biological experiments. (<b>b</b>) Immunofluorescent images of sectioned NHBE cells differentiated on 6- and 80-layer PCL meshes for staining ciliated cells (Ac-tubulin, green), goblet cells (MUC5AC, red), club cells (CC10, green), basal cells (CK5, green), and nuclear stain (DAPI, blue). Scale bar: 20 μm. (<b>c</b>) Protein expression of specific cell markers in differentiated NHBE cells differentiated on PCL meshes. Each protein was normalized with GAPDH. All data shown were obtained from at least three independent biological experiments. Significance is denoted as * <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells at days 7, 14, and 21 compared to day 0 and as # <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells between the 6- and 80-layer PCL meshes at each time point.</p>
Full article ">Figure 3 Cont.
<p>Establishment of normal and diseased airway epithelium on the 6- and 80-layer PCL meshes. (<b>a</b>) mRNA expression of specific cell markers in differentiated NHBE cells cultured on 6- and 80-layer PCL meshes. All data shown were obtained from at least three independent biological experiments. (<b>b</b>) Immunofluorescent images of sectioned NHBE cells differentiated on 6- and 80-layer PCL meshes for staining ciliated cells (Ac-tubulin, green), goblet cells (MUC5AC, red), club cells (CC10, green), basal cells (CK5, green), and nuclear stain (DAPI, blue). Scale bar: 20 μm. (<b>c</b>) Protein expression of specific cell markers in differentiated NHBE cells differentiated on PCL meshes. Each protein was normalized with GAPDH. All data shown were obtained from at least three independent biological experiments. Significance is denoted as * <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells at days 7, 14, and 21 compared to day 0 and as # <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells between the 6- and 80-layer PCL meshes at each time point.</p>
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<p>Goblet cell hyperplasia observed in NHBE cells differentiated on the 6- and 80-layer PCL meshes. (<b>a</b>) Stained mucin in NHBE cells differentiated on the 6- and 80-layer PCL meshes. Objective: 40×; scale bar: 20 μm. (<b>b</b>) Goblet cell and ciliated cell distributions on the 6- and 80-layer PCL meshes. Scale bars: 20 μm. (<b>c</b>) EMT-related markers in differentiated NHBE cells cultured on 6- and 80-layer PCL meshes. (<b>d</b>) Fibrosis-related markers in differentiated NHBE cells cultured on 6- and 80-layer PCL meshes. (<b>e</b>) Inflammation-related markers in differentiated NHBE cells cultured on 6- and 80-layer PCL meshes. Significance is denoted as * <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells at days 7, 14, and 21 compared to day 0 and as # <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells between the 6- and 80-layer PCL meshes at each time point. All the data were obtained from at least three independent biological experiments.</p>
Full article ">Figure 4 Cont.
<p>Goblet cell hyperplasia observed in NHBE cells differentiated on the 6- and 80-layer PCL meshes. (<b>a</b>) Stained mucin in NHBE cells differentiated on the 6- and 80-layer PCL meshes. Objective: 40×; scale bar: 20 μm. (<b>b</b>) Goblet cell and ciliated cell distributions on the 6- and 80-layer PCL meshes. Scale bars: 20 μm. (<b>c</b>) EMT-related markers in differentiated NHBE cells cultured on 6- and 80-layer PCL meshes. (<b>d</b>) Fibrosis-related markers in differentiated NHBE cells cultured on 6- and 80-layer PCL meshes. (<b>e</b>) Inflammation-related markers in differentiated NHBE cells cultured on 6- and 80-layer PCL meshes. Significance is denoted as * <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells at days 7, 14, and 21 compared to day 0 and as # <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells between the 6- and 80-layer PCL meshes at each time point. All the data were obtained from at least three independent biological experiments.</p>
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<p>Expression of oxidative stress-related markers in the NHBE cells differentiated on PCL meshes. (<b>a</b>) Oxidative stress-related markers in the NHBE cells differentiated on 6- and 80-layer PCL meshes. (<b>b</b>) Protein expression of SOX9, NF-κB, RAC1, NOX2, and NOX4. Protein was quantified using western blotting. Each protein was normalized with GAPDH. (<b>c</b>) Immunofluorescence assay for oxidative stress-related markers in the NHBE cells differentiated on 6- and 80-layer PCL meshes at day 21 post-initiation of the ALI. RAC1 (green), NOX2 (green), NOX4 (red), and nuclear stain (DAPI, blue). (<b>d</b>) Whole-mount staining for AP-1 in cells differentiated on 6- and 80-layer PCL meshes. Scale bars: 20 µm. Significance is denoted as * <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells at days 7, 14, and 21 compared to day 0 and as # <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells between the 6- and 80-layer PCL meshes at each time point. All the data were obtained from at least three independent biological experiments.</p>
Full article ">Figure 5 Cont.
<p>Expression of oxidative stress-related markers in the NHBE cells differentiated on PCL meshes. (<b>a</b>) Oxidative stress-related markers in the NHBE cells differentiated on 6- and 80-layer PCL meshes. (<b>b</b>) Protein expression of SOX9, NF-κB, RAC1, NOX2, and NOX4. Protein was quantified using western blotting. Each protein was normalized with GAPDH. (<b>c</b>) Immunofluorescence assay for oxidative stress-related markers in the NHBE cells differentiated on 6- and 80-layer PCL meshes at day 21 post-initiation of the ALI. RAC1 (green), NOX2 (green), NOX4 (red), and nuclear stain (DAPI, blue). (<b>d</b>) Whole-mount staining for AP-1 in cells differentiated on 6- and 80-layer PCL meshes. Scale bars: 20 µm. Significance is denoted as * <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells at days 7, 14, and 21 compared to day 0 and as # <span class="html-italic">p</span> &lt; 0.05 in the differentiated NHBE cells between the 6- and 80-layer PCL meshes at each time point. All the data were obtained from at least three independent biological experiments.</p>
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<p>The signaling pathway for goblet-cell hyperplasia of NHBE cells on PCL meshes.</p>
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19 pages, 3805 KiB  
Article
The Diagnostic Value of ACSL1, ACSL4, and ACSL5 and the Clinical Potential of an ACSL Inhibitor in Non-Small-Cell Lung Cancer
by Yunxia Ma, Miljana Nenkov, Alexander Berndt, Mohamed Abubrig, Martin Schmidt, Tim Sandhaus, Otmar Huber, Joachim H. Clement, Susanne M. Lang, Yuan Chen and Nikolaus Gaßler
Cancers 2024, 16(6), 1170; https://doi.org/10.3390/cancers16061170 - 16 Mar 2024
Cited by 8 | Viewed by 2767
Abstract
Abnormal expression of ACSL members 1, 3, 4, 5, and 6 is frequently seen in human cancer; however, their clinical relevance is unclear. In this study, we analyzed the expression of ACSLs and investigated the effects of the ACSL inhibitor Triacsin C (TC) [...] Read more.
Abnormal expression of ACSL members 1, 3, 4, 5, and 6 is frequently seen in human cancer; however, their clinical relevance is unclear. In this study, we analyzed the expression of ACSLs and investigated the effects of the ACSL inhibitor Triacsin C (TC) in lung cancer. We found that, compared to normal human bronchial epithelial (NHBE) cells, ACSL1, ACSL4, and ACSL6 were highly expressed, while ACSL3 and ACSL5 were lost in the majority of lung cancer cell lines. ACSL activity was associated with the expression levels of the ACSLs. In primary lung tumors, a higher expression of ACSL1, ACSL4, and ACSL5 was significantly correlated with adenocarcinoma (ADC). Moreover, ACSL5 was significantly reversely related to the proliferation marker Ki67 in low-grade tumors, while ACSL3 was positively associated with Ki67 in high-grade tumors. Combination therapy with TC and Gemcitabine enhanced the growth-inhibitory effect in EGFR wild-type cells, while TC combined with EGFR-TKIs sensitized the EGFR-mutant cells to EGFR-TKI treatment. Taken together, the data suggest that ACSL1 may be a biomarker for lung ADC, and ACSL1, ACSL4, and ACSL5 may be involved in lung cancer differentiation, and TC, in combination with chemotherapy or EGFR-TKIs, may help patients overcome drug resistance. Full article
(This article belongs to the Special Issue Pathology, Diagnosis and Treatment in Non-small Cell Lung Cancer)
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<p>The expression of ACSL isoforms and ACSL enzymatic activity in normal bronchial epithelium (NHBE) cells and a panel of lung cancer cell lines. The expression of ACSL isoforms at both the mRNA and protein levels was analyzed by (<b>A</b>) RT-qPCR and (<b>B</b>) WB. Gene expression in comparison to the internal control GAPDH in NHBE cells was set to 1.0 for RT-qPCR analysis. GAPDH was used as a loading control for WB. (<b>C</b>) ACSL enzymatic activity was measured by liquid scintillation counting using [<sup>3</sup>H]-palmitic acid as the substrate. V: variant.</p>
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<p>Tissue distribution and expression of ACSL1 and ACSL3 in normal human lung tissue. ACSL1 and ACSL3 were co-stained with cytokeratin (CK), surfactant protein C (SFPC), and DAPI in the same panel. (A) Alveolar type II cell. (B) Bronchial epithelial cells. (C) Macrophages.</p>
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<p>Representative staining of ACSL isoforms in primary lung tumors.</p>
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<p>The effect of Triacsin C (TC) on ACSL enzymatic activity and cell viability in lung cancer cell lines. (<b>A</b>) The effect of TC (2, 4, and 8 µM) on ACSL activity in H1650 and H1975 (upper panel) cells; the effect of 8 µM of TC on ACSL activity in five lung cancer cell lines (lower panel). (<b>B</b>) The effect of TC (8 µM) on ACSL5-overexpressing cells (upper panel) and ACSL5-knockdown cells (lower panel); (<b>C</b>). The effect of TC at serial concentrations on cell viability in six lung cancer cell lines. ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001 when analyzed using Student’s <span class="html-italic">t</span>-test.</p>
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<p>The antitumor efficacy of Triacsin C combined with Gemcitabine or EGFR-TKIs in lung cancer cell lines, as revealed by a cell viability assay. (<b>A</b>) The effect of Gemcitabine alone or combined with TC in both EGFR-WT cell lines. (<b>B</b>) The effect of EGFR-TKI alone or combined with TC in EGFR-mutant cell lines.</p>
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<p>The effect of ACSL1, ACSL4, or ACSL5 knockdown combined with Gemcitabine or Gefitinib on cell viability in lung cancer cell lines. (<b>A</b>) The effect of ACSL1 and ACSL4 knockdown combined with Gemcitabine on cell viability in H2170. (<b>B</b>) The effect of ACSL5 knockdown combined with Gemcitabine (<b>left</b>) or Gefitinib (<b>right</b>) on cell viability in H1650.</p>
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15 pages, 1398 KiB  
Article
Probenecid Inhibits Influenza A(H5N1) and A(H7N9) Viruses In Vitro and in Mice
by Jackelyn Murray, David E. Martin, Sarah Hosking, Nichole Orr-Burks, Robert J. Hogan and Ralph A. Tripp
Viruses 2024, 16(1), 152; https://doi.org/10.3390/v16010152 - 19 Jan 2024
Cited by 4 | Viewed by 2216
Abstract
Avian influenza (AI) viruses cause infection in birds and humans. Several H5N1 and H7N9 variants are highly pathogenic avian influenza (HPAI) viruses. H5N1 is a highly infectious bird virus infecting primarily poultry, but unlike other AIs, H5N1 also infects mammals and transmits to [...] Read more.
Avian influenza (AI) viruses cause infection in birds and humans. Several H5N1 and H7N9 variants are highly pathogenic avian influenza (HPAI) viruses. H5N1 is a highly infectious bird virus infecting primarily poultry, but unlike other AIs, H5N1 also infects mammals and transmits to humans with a case fatality rate above 40%. Similarly, H7N9 can infect humans, with a case fatality rate of over 40%. Since 1996, there have been several HPAI outbreaks affecting humans, emphasizing the need for safe and effective antivirals. We show that probenecid potently inhibits H5N1 and H7N9 replication in prophylactically or therapeutically treated A549 cells and normal human broncho-epithelial (NHBE) cells, and H5N1 replication in VeroE6 cells and mice. Full article
(This article belongs to the Section Human Virology and Viral Diseases)
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<p>A549 cells were treated 24 h before (<b>A</b>) or 1 h after (<b>B</b>) inoculation with Anhui/1-H7N9 (MOI = 0.1) with probenecid or oseltamivir at different concentrations (100,000, 10,000, 1000, 100, 1, 0.1, 0.01, 0.001, or 0 µM).</p>
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<p>NHBE cells were treated 24 h before (<b>A</b>) or 1 h after (<b>B</b>) inoculation with Anhui/1-H7N9 (MOI = 0.1) with probenecid or oseltamivir at different concentrations (100,000, 10,000, 1000, 100, 1, 0.1, 0.01, 0.001, or 0 µM).</p>
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<p>VeroE6 cells were treated 24 h before (<b>A</b>) or 1 h after (<b>B</b>) inoculation with VN/1203-H5N1 (MOI = 0.1) with probenecid or oseltamivir at different concentrations (100,000, 10,000, 1000, 100, 1, 0.1, 0.01, 0.001, or 0 µM).</p>
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<p>Weight Change. BALB/c mice were anesthetized with avertin and inoculated intranasally with 3LD<sub>50</sub> of VN/1203-H5N1 (30 µL/mouse). Probenecid (10 or 100 mg/kg) or oseltamivir (10 mg/kg) were administered by oral gavage twice daily for 3 days. Uninfected control mice were gavaged twice daily for 3 days with 100 µL sterile PBS.</p>
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<p>Survival. BALB/c mice were anesthetized with avertin and inoculated intranasally with 3LD<sub>50</sub> of VN/1203-H5N1 (30 µL/mouse). Probenecid (10 or 100 mg/kg) or oseltamivir (10 mg/kg) were administered by oral gavage twice daily for 3 days. Uninfected control mice were gavaged twice daily for 3 days with 100 µL sterile PBS.</p>
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<p>Infectious virus in the lungs. BALB/c mice were anesthetized with avertin and inoculated intranasally with 3LD<sub>50</sub> of VN/1203-H5N1 (30 µL/mouse). Probenecid (10 or 100 mg/kg) or oseltamivir (10 mg/kg) were administered by oral gavage twice daily for 3 days. Uninfected control mice were gavaged twice daily for 3 days with 100 µL sterile PBS.</p>
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<p>BALB/c mice were anesthetized with avertin and inoculated intranasally with 3LD<sub>50</sub> of VN/1203-H5N1 (30 µL/mouse). Probenecid (10 or 100 mg/kg) or oseltamivir (10 mg/kg) were administered by oral gavage twice daily for 3 days. Uninfected control mice were gavaged twice daily for 3 days with 100 µL sterile PBS. The cytokines were assayed by ELISA in serum samples of mice obtained on days 3 and 5 pi.</p>
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21 pages, 4495 KiB  
Article
Genomic Analysis of Influenza A and B Viruses Carrying Baloxavir Resistance-Associated Substitutions Serially Passaged in Human Epithelial Cells
by Brady T. Hickerson, Bruce K. Huang, Svetlana N. Petrovskaya and Natalia A. Ilyushina
Viruses 2023, 15(12), 2446; https://doi.org/10.3390/v15122446 - 16 Dec 2023
Cited by 1 | Viewed by 1894
Abstract
Baloxavir marboxil (baloxavir) is an FDA-approved inhibitor of the influenza virus polymerase acidic (PA) protein. Here, we used next-generation sequencing to compare the genomic mutational profiles of IAV H1N1 and H3N2, and IBV wild type (WT) and mutants (MUT) viruses carrying baloxavir resistance-associated [...] Read more.
Baloxavir marboxil (baloxavir) is an FDA-approved inhibitor of the influenza virus polymerase acidic (PA) protein. Here, we used next-generation sequencing to compare the genomic mutational profiles of IAV H1N1 and H3N2, and IBV wild type (WT) and mutants (MUT) viruses carrying baloxavir resistance-associated substitutions (H1N1—PA I38L, I38T, and E199D; H3N2—PA I38T; and IBV—PA I38T) during passaging in normal human bronchial epithelial (NHBE) cells. We determined the ratio of nonsynonymous to synonymous nucleotide mutations (dN/dS) and identified the location and type of amino acid (AA) substitutions that occurred at a frequency of ≥30%. We observed that IAV H1N1 WT and MUT viruses remained relatively stable during passaging. While the mutational profiles for IAV H1N1 I38L, I38T, and E199D, and IBV I38T MUTs were relatively similar after each passage compared to the respective WTs, the mutational profile of the IAV H3N2 I38T MUT was significantly different for most genes compared to H3N2 WT. Our work provides insight into how baloxavir resistance-associated substitutions may impact influenza virus evolution in natural settings. Further characterization of the potentially adaptive mutations identified in this study is needed. Full article
(This article belongs to the Special Issue Influenza Virus Pathogenesis and Transmission)
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<p>Percent frequency of mutations at each nucleotide loci for each passage within the IAV H1N1 WT genes. ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). To generate mutations, H1N1 WT virus was serially passaged three times in NHBE cells. NGS was then performed on RNA extracted from supernatant aliquots from each passage and the data were analyzed using the FDA in-house NGS data analysis platform, HIVE. The dashed line indicates the 5% cutoff mutation frequency. PB2, Polymerase basic 2; PB1, Polymerase basic 1; PA, Polymerase acidic; HA, Hemagglutinin; NP, Nucleoprotein; NA, Neuraminidase; M, Matrix; NS, Nonstructural.</p>
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<p>Percent frequency of mutations at each nucleotide loci for each passage within the IAV H1N1 I38L genes ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). To generate mutations, H1N1 I38L MUT virus was serially passaged three times in NHBE cells. NGS was then performed on RNA extracted from supernatant aliquots from each passage and the data were analyzed using the FDA in-house NGS data analysis platform, HIVE. The dashed line indicates the 5% cutoff mutation frequency. PB2, Polymerase basic 2; PB1, Polymerase basic 1; PA, Polymerase acidic; HA, Hemagglutinin; NP, Nucleoprotein; NA, Neuraminidase; M, Matrix; NS, Nonstructural.</p>
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<p>Percent frequency of mutations at each nucleotide loci for each passage within the IAV H1N1 I38T genes ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). To generate mutations, H1N1 I38T MUT virus was serially passaged three times in NHBE cells. NGS was then performed on RNA extracted from supernatant aliquots from each passage and the data was analyzed using the FDA in-house NGS data analysis platform, HIVE. The dashed line indicates the 5% cutoff mutation frequency. PB2, Polymerase basic 2; PB1, Polymerase basic 1; PA, Polymerase acidic; HA, Hemagglutinin; NP, Nucleoprotein; NA, Neuraminidase; M, Matrix; NS, Nonstructural.</p>
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<p>Percent frequency of mutations at each nucleotide loci for each passage within the IAV H1N1 E199D genes ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). To generate mutations, H1N1 E199D MUT virus was serially passaged three times in NHBE cells. NGS was then performed on RNA extracted from supernatant aliquots from each passage and the data was analyzed using the FDA in-house NGS data analysis platform, HIVE. The dashed line indicates the 5% cutoff mutation frequency. PB2, Polymerase basic 2; PB1, Polymerase basic 1; PA, Polymerase acidic; HA, Hemagglutinin; NP, Nucleoprotein; NA, Neuraminidase; M, Matrix; NS, Nonstructural.</p>
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<p>Percent frequency of mutations at each nucleotide loci for each passage within the IAV H3N2 WT genes ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). To generate mutations, H3N2 WT virus was serially passaged three times in NHBE cells. NGS was then performed on RNA extracted from supernatant aliquots from each passage and the data was analyzed using the FDA in-house NGS data analysis platform, HIVE. The dashed line indicates the 5% cutoff mutation frequency. PB2, Polymerase basic 2; PB1, Polymerase basic 1; PA, Polymerase acidic; HA, Hemagglutinin; NP, Nucleoprotein; NA, Neuraminidase; M, Matrix; NS, Nonstructural.</p>
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<p>Percent frequency of mutations at each nucleotide loci for each passage within the IAV H3N2 I38T genes ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). To generate mutations, H3N2 I38T MUT virus was serially passaged three times in NHBE cells. NGS was then performed on RNA extracted from supernatant aliquots from each passage and the data was analyzed using the FDA in-house NGS data analysis platform, HIVE. The dashed line indicates the 5% cutoff mutation frequency. PB2, Polymerase basic 2; PB1, Polymerase basic 1; PA, Polymerase acidic; HA, Hemagglutinin; NP, Nucleoprotein; NA, Neuraminidase; M, Matrix; NS, Nonstructural.</p>
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<p>Percent frequency of mutations at each nucleotide loci for each passage within the IBV WT genes ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). To generate mutations, IBV WT virus was serially passaged three times in NHBE cells. NGS was then performed on RNA extracted from supernatant aliquots from each passage and the data was analyzed using the FDA in-house NGS data analysis platform, HIVE. The dashed line indicates the 5% cutoff mutation frequency. IBV, Influenza B virus; PB2, Polymerase basic 2; PB1, Polymerase basic 1; PA, Polymerase acidic; HA, Hemagglutinin; NP, Nucleoprotein; NA, Neuraminidase; M, Matrix; NS, Nonstructural.</p>
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<p>Percent frequency of mutations at each nucleotide loci for each passage within the IBV I38T genes ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). To generate mutations, IBV I38T MUT virus was serially passaged three times in NHBE cells. NGS was then performed on RNA extracted from supernatant aliquots from each passage and the data was analyzed using the FDA in-house NGS data analysis platform, HIVE. The dashed line indicates the 5% cutoff mutation frequency. IBV, Influenza B virus; PB2, Polymerase basic 2; PB1, Polymerase basic 1; PA, Polymerase acidic; HA, Hemagglutinin; NP, Nucleoprotein; NA, Neuraminidase; M, Matrix; NS, Nonstructural.</p>
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<p>Location of substitutions in the influenza virus proteins that arose to frequencies of ≥30% after serial passage ((<b>a</b>) PB2, (<b>b</b>) PB1, (<b>c</b>) PA, (<b>d</b>) HA, (<b>e</b>) NP, (<b>f</b>) NA, (<b>g</b>) M, (<b>h</b>) NS). The locations of the substitutions are shown in blue and the substitution label is bolded. For the influenza virus replication centers, PB1 is colored light blue, PB2 is colored light green, and PA is colored gray. PA, Polymerase acidic; PB2, Polymerase basic 2; PB1, Polymerase basic 1; NS, Nonstructural; HA, Hemagglutinin; NA, Neuraminidase; RdRp, RNA-dependent RNA polymerase.</p>
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21 pages, 10935 KiB  
Article
Analyzing the Impact of Diesel Exhaust Particles on Lung Fibrosis Using Dual PCR Array and Proteomics: YWHAZ Signaling
by Byeong-Gon Kim, Pureun-Haneul Lee, Jisu Hong and An-Soo Jang
Toxics 2023, 11(10), 859; https://doi.org/10.3390/toxics11100859 - 13 Oct 2023
Cited by 1 | Viewed by 2027
Abstract
Air pollutants are associated with exacerbations of asthma, chronic bronchitis, and airway inflammation. Diesel exhaust particles (DEPs) can induce and worsen lung diseases. However, there are insufficient data to guide polymerase chain reaction (PCR) array proteomics studies regarding the impacts of DEPs on [...] Read more.
Air pollutants are associated with exacerbations of asthma, chronic bronchitis, and airway inflammation. Diesel exhaust particles (DEPs) can induce and worsen lung diseases. However, there are insufficient data to guide polymerase chain reaction (PCR) array proteomics studies regarding the impacts of DEPs on respiratory diseases. This study was performed to identify genes and proteins expressed in normal human bronchial epithelial (NHBE) cells. MicroRNAs (miRNAs) and proteins expressed in NHBE cells exposed to DEPs at 1 μg/cm2 for 8 h and 24 h were identified using PCR array analysis and 2D PAGE/LC-MS/MS, respectively. YWHAZ gene expression was estimated using PCR, immunoblotting, and immunohistochemical analyses. Genes discovered through an overlap analysis were validated in DEP-exposed mice. Proteomics approaches showed that exposing NHBE cells to DEPs led to changes in 32 protein spots. A transcriptomics PCR array analysis showed that 6 of 84 miRNAs were downregulated in the DEP exposure groups compared to controls. The mRNA and protein expression levels of YWHAZ, β-catenin, vimentin, and TGF-β were increased in DEP-treated NHBE cells and DEP-exposed mice. Lung fibrosis was increased in mice exposed to DEPs. Our combined PCR array–omics analysis demonstrated that DEPs can induce airway inflammation and lead to lung fibrosis through changes in the expression levels of YWHAZ, β-catenin, vimentin, and TGF-β. These findings suggest that dual approaches can help to identify biomarkers and therapeutic targets involved in pollutant-related respiratory diseases. Full article
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<p>DEP-exposed NHBE cell viability assessed using CCK-8 assay. The CCK-8 assay showed that DEP exposure decreased cell viability in NHBE cells. * <span class="html-italic">p</span> &lt; 0.05 vs. the control group.</p>
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<p>Two-dimensional electrophoresis in DEP-exposed NHBE cells. The 2D PAGE image from lysates of untreated cells was used as a master gel and reference map.</p>
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<p>Cluster analysis of 32 proteins with significant differential expression caused by DEP treatment of NHBE cells at 1 μg/cm<sup>2</sup> for 8 and 24 h. The profile of 32 proteins with differential expression was visualized according to stimulation time using hierarchical clustering algorithms. Protein names (National Center for Biotechnology Information (NCBI)) are displayed for each cluster.</p>
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<p>Scatter plots showing the differential expression of miRNAs in DEP-exposed NHBE cells. Scatter plots showing the miRNA expression levels of NHBE cells exposed to DEPs for (<b>A</b>) 8 and (<b>B</b>) 24 h.</p>
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<p>Overlap of miRNA in DEP-exposed NHBE cells. hsa-miR-146a-5p, hsa-miR18a-5p, hsa-miR,22-3p, hsa-miR-30c-5p, and hsa-let-7a-5p levels were decreased in NHBE cells exposed to DEPs. * <span class="html-italic">p</span> &lt; 0.05 vs. control group.</p>
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<p>miRNA–mRNA networks of predicted regulation in DEP-exposed NHBE cells. Network visualization for miRNA–mRNA study was performed using Cytoscape software (version: 3.5.1, <a href="https://cytoscape.org/" target="_blank">https://cytoscape.org/</a> (accessed on 25 September 2020)).</p>
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<p>Gene ontology (GO) analysis of potential predicted genes and Kyoto Encyclopedia of Genes and Genomes database (KEGG) pathway enrichment analysis performed using DIANA-miRPath. (<b>A</b>) The 10 most significant genes for each GO enrichment term, including molecular functions, biological processes, and cellular components. (<b>B</b>) KEGG pathway analysis associated with predicted genes of the top 20 highly enriched pathways.</p>
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<p><span class="html-italic">YWHAZ</span>, <span class="html-italic">β-catenin</span>, <span class="html-italic">vimentin</span>, and <span class="html-italic">TGF-β</span> gene mRNA and proteins levels in epithelial cells. Band intensity in densitometry analysis graphs for (<b>A</b>) mRNA and (<b>B</b>) protein expression of <span class="html-italic">YWHAZ</span>, <span class="html-italic">β-catenin</span>, <span class="html-italic">vimentin</span>, and <span class="html-italic">TGF-β</span> was normalized to <span class="html-italic">β-actin</span>. * <span class="html-italic">p</span> &lt; 0.05 vs. the NC group.</p>
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<p>DEP exposure in mice increased airway inflammation, AHR, and differential cell count in BALF. (<b>A</b>) Experimental protocol for DEP exposure in mice (<span class="html-italic">n</span> = 30 in each group). (<b>B</b>) DEP nebulizer treatment increased AHR in mice. Penh was measured following increasing doses of methacholine. (<b>C</b>) Numbers of total cells, macrophages, eosinophils, neutrophils, and lymphocytes in BALF. * <span class="html-italic">p</span> &lt; 0.05 compared with sham group. ** <span class="html-italic">p</span> &lt; 0.05 compared with 4w DEP group.</p>
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<p><span class="html-italic">YWHAZ</span>, <span class="html-italic">β-catenin</span>, <span class="html-italic">vimentin</span>, and <span class="html-italic">TGF-β</span> gene mRNA and proteins levels in mouse lung tissue. Band intensity in densitometry analysis graphs for (<b>A</b>) mRNA and (<b>B</b>) protein expression of <span class="html-italic">YWHAZ</span>, <span class="html-italic">β-catenin</span>, <span class="html-italic">vimentin</span>, and <span class="html-italic">TGF-β</span> was normalized to <span class="html-italic">β-actin</span> in mouse lung tissue. (<b>C</b>) Immunohistochemistry (IHC) stain and Masson trichrome stain of mouse lung tissue using antibodies for <span class="html-italic">YWHAZ</span>. Quantitation of the <span class="html-italic">YWHAZ</span> expression area intensity. Fibrosis as shown by Masson trichrome stain. * <span class="html-italic">p</span> &lt; 0.05 vs. the sham group.</p>
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<p>DEP-exposed mice were sacrificed after 4 weeks and 8 weeks, and the lung weight and body weight of each mouse were measured. Mouse model of DEP inhalation. (<b>A</b>) Body weight loss and (<b>B</b>) increased lung weight. * <span class="html-italic">p</span> &lt; 0.05 compared with sham group.</p>
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<p>Summary of <span class="html-italic">YWHAZ</span>, <span class="html-italic">β-catenin</span>, <span class="html-italic">vimentin</span>, and <span class="html-italic">TGF-β</span> signaling and airway inflammation induced by DEP exposure in the lung.</p>
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14 pages, 1700 KiB  
Article
Genes Involved in miRNA Biogenesis Are Not Downregulated in SARS-CoV-2 Infection
by Nathalie Garnier, Famara Sane, Layal Massara, Fabrice Soncin, Philippe Gosset, Didier Hober, Sabine Szunerits and Ilka Engelmann
Viruses 2023, 15(5), 1177; https://doi.org/10.3390/v15051177 - 16 May 2023
Cited by 4 | Viewed by 2133
Abstract
miRNAs, small non-coding RNAs that regulate gene expression, are involved in various pathological processes, including viral infections. Virus infections may interfere with the miRNA pathway through the inhibition of genes involved in miRNA biogenesis. A reduction in the number and the levels of [...] Read more.
miRNAs, small non-coding RNAs that regulate gene expression, are involved in various pathological processes, including viral infections. Virus infections may interfere with the miRNA pathway through the inhibition of genes involved in miRNA biogenesis. A reduction in the number and the levels of miRNAs expressed in nasopharyngeal swabs of patients with severe COVID-19 was lately observed by us, pointing towards the potential of miRNAs as possible diagnostic or prognostic biomarkers for predicting outcomes among patients with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. The objective of the present study was to investigate whether SARS-CoV-2 infection influences the expression levels of messenger RNAs (mRNAs) of key genes involved in miRNA biogenesis. mRNA levels of AGO2, DICER1, DGCR8, DROSHA, and Exportin-5 (XPO5) were measured by quantitative reverse-transcription polymerase chain reaction (RT-qPCR) in nasopharyngeal swab specimens from patients with COVID-19 and controls, as well as in cells infected with SARS-CoV-2 in vitro. Our data showed that the mRNA expression levels of AGO2, DICER1, DGCR8, DROSHA, and XPO5 were not significantly different in patients with severe COVID-19 when compared to patients with non-severe COVID-19 and controls. Similarly, the mRNA expression of these genes was not affected by SARS-CoV-2 infection in NHBE and Calu-3 cells. However, in Vero E6 cells, AGO2, DICER1, DGCR8, and XPO5 mRNA levels were slightly upregulated 24 h after infection with SARS-CoV-2. In conclusion, we did not find evidence for downregulation of mRNA levels of miRNA biogenesis genes during SARS-CoV-2 infection, neither ex vivo nor in vitro. Full article
(This article belongs to the Special Issue RNA Biology of Viral Infection)
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<p>mRNA expression levels of genes involved in miRNA biogenesis. Normalized mRNA expression (delta Ct values) of <span class="html-italic">AGO2</span> (<b>A</b>), <span class="html-italic">DICER1</span> (<b>B</b>), <span class="html-italic">DGCR8</span> (<b>C</b>), <span class="html-italic">DROSHA</span> (<b>D</b>), and <span class="html-italic">XPO5</span> (<b>E</b>) genes in nasopharyngeal swabs of patients with severe COVID-19 (n = 19), patients with non-severe COVID-19 (n = 21) and controls (n = 20). Each data point represents one nasopharyngeal swab specimen. The bar indicates the median value.</p>
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<p>mRNA expression of genes involved in miRNA biogenesis in NHBE cells. Normalized mRNA levels (delta Ct values) of <span class="html-italic">AGO2</span>, <span class="html-italic">DICER1</span>, <span class="html-italic">DGCR8</span>, <span class="html-italic">DROSHA</span>, and <span class="html-italic">XPO5</span> genes were measured in NHBE cells infected with SARS-CoV-2 (black circles) or in non-infected cells (empty circles), 24 h (<b>A</b>) and 48 h (<b>B</b>) post infection. Four independent infections are shown, each data point represents one replicate. The bar indicates the median.</p>
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<p>mRNA expression of genes involved in miRNA biogenesis in Calu-3 cells. Normalized mRNA levels (delta Ct values) of <span class="html-italic">AGO2</span>, <span class="html-italic">DICER1</span>, <span class="html-italic">DGCR8</span>, <span class="html-italic">DROSHA</span>, and <span class="html-italic">XPO5</span> genes were measured in Calu-3 cells infected with SARS-CoV-2 (black circles) or in non-infected cells (empty circles) 24 h (<b>A</b>) and 48 h (<b>B</b>) post infection. Four independent infections are shown. Each data point represents one replicate. The bar indicates the median.</p>
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<p>mRNA expression of genes involved in miRNA biogenesis in Vero E6 cells. Normalized mRNA levels (delta Ct values) of <span class="html-italic">AGO2</span>, <span class="html-italic">DICER1</span>, <span class="html-italic">DGCR8</span>, <span class="html-italic">DROSHA,</span> and <span class="html-italic">XPO5</span> genes were measured in Vero E6 cells infected with SARS-CoV-2 (black circles) or in non-infected cells (empty circles), 24 h (<b>A</b>) and 48 h (<b>B</b>) post infection. Four independent infections are shown. Each data point represents one replicate. The bar indicates the median. * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Fold changes of mRNA expression of genes involved in miRNA biogenesis in infected Vero E6 cells. Fold changes of mRNA expression of <span class="html-italic">AGO2</span>, <span class="html-italic">DICER1</span>, <span class="html-italic">DGCR8</span>, <span class="html-italic">DROSHA</span>, and <span class="html-italic">XPO5</span> genes in SARS-CoV-2 infected compared to uninfected Vero E6 cells at 24 h (<b>A</b>) and 48 h (<b>B</b>) post infection. Means and standard deviations of four independent infections are shown.</p>
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14 pages, 3999 KiB  
Article
Lung Epithelial Cells from Obese Patients Have Impaired Control of SARS-CoV-2 Infection
by Mellissa Gaudet, Eva Kaufmann, Nour Jalaleddine, Andrea Mogas, Mahmood Hachim, Abiola Senok, Maziar Divangahi, Qutayba Hamid and Saba Al Heialy
Int. J. Mol. Sci. 2023, 24(7), 6729; https://doi.org/10.3390/ijms24076729 - 4 Apr 2023
Cited by 1 | Viewed by 2466
Abstract
Obesity is known to increase the complications of the COVID-19 coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the exact mechanisms of SARS-CoV-2 infection in obese patients have not been clearly elucidated. This study aims to better understand the [...] Read more.
Obesity is known to increase the complications of the COVID-19 coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the exact mechanisms of SARS-CoV-2 infection in obese patients have not been clearly elucidated. This study aims to better understand the effect of obesity on the course of SARS-CoV-2 infection and identify candidate molecular pathways involved in the progression of the disease, using an in vitro live infection model and RNA sequencing. Results from this study revealed the enhancement of viral load and replication in bronchial epithelial cells (NHBE) from obese subjects at 24 h of infection (MOI = 0.5) as compared to non-obese subjects. Transcriptomic profiling via RNA-Seq highlighted the enrichment of lipid metabolism-related pathways along with LPIN2, an inflammasome regulator, as a unique differentially expressed gene (DEG) in infected bronchial epithelial cells from obese subjects. Such findings correlated with altered cytokine and angiotensin-converting enzyme-2 (ACE2) expression during infection of bronchial cells. These findings provide a novel insight on the molecular interplay between obesity and SARS-CoV-2 infection. In conclusion, this study demonstrates the increased SARS-CoV-2 infection of bronchial epithelial cells from obese subjects and highlights the impaired immunity which may explain the increased severity among obese COVID-19 patients. Full article
(This article belongs to the Special Issue Chronic Inflammatory Lung Diseases: Molecular Pathology)
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<p>Increased SARS-CoV-2 replication in human bronchial epithelial cells (NHBE) from obese subjects. SARS-CoV-2 infection of bronchial epithelial cells (NHBE) with MOI 0.5. (<b>A</b>) Viral load was assessed by measuring nucleocapsid mRNA, <span class="html-italic">n</span> = 4/group; (<b>B</b>) replication was evaluated by measuring the SARS-CoV-2 envelope (UpE) gene, which was significantly higher in NHBE cells from obese subjects (<span class="html-italic">n</span> = 4) compared to non-obese (<span class="html-italic">n</span> = 4) subjects. One-way ANOVA test and Tukey post hoc, * <span class="html-italic">p</span> &lt; 0.05; *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Differentially expressed genes between bronchial epithelial cells from non-infected non-obese and obese subjects. (<b>A</b>) Venn diagram showing the intersection of DEGs found between non-infected bronchial epithelial cells from non-obese and obese subjects at 4 and 24 h. (<b>B</b>) Enrichment analysis of intersecting genes found in Venn diagram.</p>
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<p>Core transcriptome of bronchial epithelial cells during SAR-CoV-2 infection. (<b>A</b>) Venn diagram of intersecting DEGs from non-infected, infected, bronchial epithelial cells from non-obese and obese at 4 and 24 h post-infection. (<b>B</b>) Enrichment analysis of the 41 genes found in the intersection of all groups of Venn diagram. This being the core transcriptomic of infected vs. non-infected (non-obese and obese). (<b>C</b>) Enrichment analysis of the 728 genes found in the obese uninfected 24 h vs. obese infected 24 h group of the Venn diagram.</p>
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<p>Five DEGs were identified as unique to bronchial epithelial cells from obese subjects and are core players in SARS-CoV-2-infected cells. Venn diagram of intersecting DEGs unique to SARS-CoV-2 infection and associated to obesity. Five genes were identified: <span class="html-italic">CASC5 (KNL1)</span>, <span class="html-italic">LPIN2</span>, <span class="html-italic">MIR143HG (CARMN)</span>, <span class="html-italic">ULBP1</span> and <span class="html-italic">THRB</span>.</p>
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<p>Differential expression of <span class="html-italic">LPIN2</span> over infection time between cells from non-obese and obese subjects. The percentage of change of <span class="html-italic">LPIN2</span> expression in infected compared to non-infected NHBE cells.</p>
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<p>Inflammatory responses in SARS-CoV-2 infection of bronchial epithelial cells. mRNA expression of (<b>A</b>) <span class="html-italic">IL-17A</span>, (1) obese uninfected vs. obese infected at 4 h, non-obese infected vs. obese infected at 4 h, obese infected at 4 h vs. 8 h, obese infected at 4 h vs. 12 h, obese infected at 4 h vs. 18 h, obese infected at 4 h vs. 24 h, obese infected at 4 h vs. 48 h, (2) obese infected at 4 h vs. 72 h. (<b>B</b>) <span class="html-italic">IL-1β</span>, (1) non-obese infected at 4 h vs. 72 h, non-obese infected at 18 h vs. 72 h, (2) non-obese infected at 12 h vs. 72 h, non-obese infected at 8 h vs. 72 h, non-obese infected at 24 h vs. 72 h, (3) non-obese infected at 48 h vs. 72 h. (<b>C</b>) <span class="html-italic">IL-6</span> (1), non-obese infected vs. obese infected at 4 h (2) obese infected at 4 h vs. 48 h, (3) obese infected at 4 h vs. 72 h, (4) obese infected at 8 h vs. 72 h, non-obese infected at 72 h vs. obese infected 72 h, (5) obese infected at 12 h vs. 72 h. (<b>D</b>) <span class="html-italic">IL-8</span> (1) obese infected at 4 h vs. 12 h, (2) non-obese infected vs. obese infected at 4 h, obese infected at 4 h vs. 18 h, obese infected at 4 h vs. 24, obese infected at 4 h vs. 48, (3) non-obese infected vs. obese infected at 72 h, (4) non-obese uninfected vs. non-obese infected at 72 h, non-obese infected at 4 h vs. 72 h, non-obese infected at 8 h, 12 h, 18 h, 24 h, 48 h vs. 72 h. (<b>E</b>) <span class="html-italic">IFN-β</span>, (1) non-obese infected vs. obese infected at 4 h, (2) non-obese infected vs. obese infected. (<b>F</b>) <span class="html-italic">ACE2</span>, (1) obese non-infected vs. obese infected at 4 h, non-obese infected vs. obese infected at 4 h, obese infected at 4 h vs. 48 h, obese infected at 4 h vs. 12 h, obese infected at 4 h vs. 18 h, (2) non-obese infected at 4 h vs. 72 h, (3) obese infected at 4 h vs. obese infected at 12 h, (4) non-obese infected at 18 h vs. non-obese infected 72 h, (5) non-obese infected at 24 h vs. 72 h, non-obese infected at 48 h vs. 72 h, non-obese uninfected at 72 h vs. non-obese infected at 72 h, (6) non-obese infected at 8 h vs. non-obese infected at 72 h. <span class="html-italic">n</span> = 4/group. One-way ANOVA test and Tukey post hoc, * <span class="html-italic">p</span> ≤ 0,05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001.</p>
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13 pages, 1944 KiB  
Article
New Data on Anti-Inflammatory and Wound Healing Potential of Transgenic Senna obtusifolia Hairy Roots: In Vitro Studies
by Tomasz Kowalczyk, Przemysław Sitarek, Tomasz Śliwiński, Sophia Hatziantoniou, Nikolitsa Soulintzi, Rafal Pawliczak and Joanna Wieczfinska
Int. J. Mol. Sci. 2023, 24(6), 5906; https://doi.org/10.3390/ijms24065906 - 21 Mar 2023
Cited by 2 | Viewed by 2267
Abstract
Asthma is an inflammatory disease whose etiology remains unclear. Its characteristics encompass a wide range of clinical symptoms, inflammatory processes, and reactions to standard therapies. Plants produce a range of constitutive products and secondary metabolites that may have therapeutic abilities. The aim of [...] Read more.
Asthma is an inflammatory disease whose etiology remains unclear. Its characteristics encompass a wide range of clinical symptoms, inflammatory processes, and reactions to standard therapies. Plants produce a range of constitutive products and secondary metabolites that may have therapeutic abilities. The aim of this study was to determine the effects of Senna obtusifolia transgenic hairy root extracts on virus-induced airway remodeling conditions. Three cell lines were incubated with extracts from transformed (SOA4) and transgenic (SOPSS2, with overexpression of the gene encoding squalene synthase 1) hairy roots of Senna obtusifolia in cell lines undergoing human rhinovirus-16 (HRV-16) infection. The effects of the extracts on the inflammatory process were determined based on the expression of inflammatory cytokines (IL-8, TNF-α, IL-1α and IFN-γ) and total thiol content. The transgenic Senna obtusifolia root extract reduced virus-induced expression of TNF, IL-8 and IL-1 in WI-38 and NHBE cells. The SOPSS2 extract reduced IL-1 expression only in lung epithelial cells. Both tested extracts significantly increased the concentration of thiol groups in epithelial lung cells. In addition, the SOPPS2 hairy root extract yielded a positive result in the scratch test. SOA4 and SOPPS2 Senna obtusifolia hairy root extracts demonstrated anti-inflammatory effects or wound healing activity. The SOPSS2 extract had stronger biological properties, which may result from a higher content of bioactive secondary metabolites. Full article
(This article belongs to the Special Issue Biosynthesis and Application of Natural Compound)
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<p>Viability of WI-38, NHBE and HGF-1 cells after exposure to extracts from transformed (SOA4) and transgenic (SOPSS2) <span class="html-italic">Senna obtusifolia</span> hairy roots. Cell viability was assessed after 24 h. The values represent means.</p>
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<p>The effect of the extracts from transformed (SOA4) and transgenic (SOPSS2) <span class="html-italic">Senna obtusifolia</span> hairy roots and viral infection (HRV-16) on the expression of <span class="html-italic">IL-8</span> on mRNA and protein levels in human lung fibroblasts, epithelial cells, and gingival fibroblasts. (<b>A</b>) presents mRNA expression of IL-8; (<b>B</b>) presents protein concentration in airway fibroblasts (WI-38), epithelial cells (NHBE) and gingival fibroblasts (HGF1).Data presented as mean ± SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>TNF-α expression in WI-38, NHBE and HGF-1 cells after treatment with SOPSS2 and SOA4 extracts from <span class="html-italic">Senna obtusifolia</span> under the conditions of HRV-16 infection. (<b>A</b>) mRNA and (<b>B</b>) protein level of TNF-α expression. Extracts from transformed (SOA4) and transgenic (SOPSS2) <span class="html-italic">Senna obtusifolia</span> hairy roots. Data presented as mean ± SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The effect of the extracts from transformed (SOA4) and transgenic (SOPSS2) <span class="html-italic">Senna obtusifolia</span> hairy roots and viral infection (HRV-16) on the expression of <span class="html-italic">IL-1α</span> on mRNA (<b>A</b>) and protein (<b>B</b>) levels in human cells. Data presented as mean ± SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>The lack of effects of SOA4 and SOPSS2 extracts from <span class="html-italic">Senna obtusifolia</span> roots on IFN-γ expression on mRNA (<b>A</b>) and protein (<b>B</b>) levels. Extracts from transformed (SOA4) and transgenic (SOPSS2) <span class="html-italic">Senna obtusifolia</span> hairy roots. Data presented as mean ± SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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<p>Wound recovery (% scratch reduction) at 24 h (<span style="color:#262626">■</span>) and 48 h (<span style="color:#AEAAAA">■</span>) for SOPSS2 root extract at concentrations ranging from 0.001 mg/mL to 0.1 mg/mL, compared to positive (pos.ctrl) and negative (neg.ctrl) controls.</p>
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<p>SOPSS2 induced the concentration of thiols in HRV infection conditions. Extracts from transformed (SOA4) and transgenic (SOPSS2) <span class="html-italic">Senna obtusifolia</span> hairy roots are given. Data presented as mean ± SEM, * <span class="html-italic">p</span> &lt; 0.05.</p>
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16 pages, 5696 KiB  
Article
Epigallocatechin Gallate (EGCG), an Active Phenolic Compound of Green Tea, Inhibits Tumor Growth of Head and Neck Cancer Cells by Targeting DNA Hypermethylation
by Anshu Agarwal, Vikash Kansal, Humaira Farooqi, Ram Prasad and Vijay Kumar Singh
Biomedicines 2023, 11(3), 789; https://doi.org/10.3390/biomedicines11030789 - 5 Mar 2023
Cited by 16 | Viewed by 2809
Abstract
Head and neck cancers are among the deadliest cancers, ranked sixth globally in rates of high mortality and poor patient prognoses. The prevalence of head and neck squamous cell carcinoma (HNSCC) is associated with smoking and excessive alcohol consumption. Despite several advances in [...] Read more.
Head and neck cancers are among the deadliest cancers, ranked sixth globally in rates of high mortality and poor patient prognoses. The prevalence of head and neck squamous cell carcinoma (HNSCC) is associated with smoking and excessive alcohol consumption. Despite several advances in diagnostic and interventional methods, the morbidity of subjects with HNSCC has remained unchanged over the last 30 years. Epigenetic alterations, such as DNA hypermethylation, are commonly associated with several cancers, including HNSCC. Thus, epigenetic changes are considered promising therapeutic targets for chemoprevention. Here, we investigated the effect of EGCG on DNA hypermethylation and the growth of HNSCC. First, we assessed the expression levels of global DNA methylation in HNSCC cells (FaDu and SCC-1) and observed enhanced methylation levels compared with normal human bronchial epithelial cells (NHBE). Treatment of EGCG to HNSCC cells significantly inhibited global DNA hypermethylation by up to 70–80% after 6 days. Inhibition of DNA hypermethylation in HNSCC cells was confirmed by the conversion of 5-methylcytosine (5-mc) into 5-hydroxy methylcytosine (5hmC). DNA methyltransferases regulate DNA methylation. Next, we checked the effect of EGCG on the expression levels of DNA methyltransferases (DNMTs) and DNMT activity. Treatment of EGCG to HNSCC cells significantly reduced DNMT activity to 60% in SCC-1 and 80% in FaDu cells. The protein levels of DNMT3a and DNMT3b were downregulated in both cell lines after EGCG treatment. EGCG treatment to HNSCC cells reactivated tumor suppressors and caused decreased cell proliferation. Our in vivo study demonstrated that administration of EGCG (0.5%, w/w) as a supplement within an AIN76A diet resulted in inhibition of tumor growth in FaDu xenografts in nude mice (80%; p < 0.01) compared with non-EGCG-treated controls. The growth inhibitory effect of dietary EGCG on the HNSCC xenograft tumors was associated with the inhibition of DNMTs and reactivation of silenced tumor suppressors. Together, our study provides evidence that EGCG acts as a DNA demethylating agent and can reactivate epigenetically silenced tumor suppressors to inhibit the growth of HNSCC cells. Full article
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<p>Effect of EGCG on global DNA methylation levels in head and neck squamous cell carcinoma cell lines. Comparative levels of global DNA methylation in NHBE, SCC-1, and FaDu cells. Data are presented in terms of percentage of NHBE, used as normal control cells. Significant difference of global DNA methylation level versus NHBE (<b>A</b>,<b>B</b>). Effect of EGCG on the global DNA methylation levels in SCC-1 (<b>C</b>,<b>D</b>) and FaDu (<b>E</b>,<b>F</b>) cells. Both HNSCC cell lines (SCC-1 and FaDu) were treated with various concentrations of EGCG (0, 5, 10, and 20 μg/mL) for 3 and 6 days, and the levels of global DNA methylation were determined using a global DNA methylation kit. Data are presented in terms of percentage of control (non-EGCG-treated) group, which was assigned a value of 100%, and as means ± S.E.M. n = 3.</p>
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<p>Treatment of SCC-1 and FaDu cells with EGCG decreases the levels of 5-mC in a dose- and time-dependent manner. Dot-blot analysis of 5-mc in DNA, extracted from various groups treated with or without EGCG in both cell lines (<b>A</b>). The intensity of individual dots was measured by densitometry in SCC-1 (<b>B</b>) and FaDu (<b>C</b>), and levels of 5-mc are presented in terms of relative density of dot blots as means ± S.E.M in different treatment groups, n = 3. Significant difference versus non-EGCG-treated controls. The effect of EGCG on DNA methylation in SCC-1 and FaDu cells was reconfirmed by immunostaining of 5-mc using an anti-5-mc antibody. Cells were counter stained with methylene green (<b>D</b>). Scale bar = 20 µM.</p>
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<p>EGCG treatment inhibits DNA methyltransferases in HNSCC cells. Total DNMT activity in nuclear extracts of SCC-1 (<b>A</b>,<b>B</b>), and FaDu (<b>C</b>,<b>D</b>) was determined using the DNA methyltransferase activity assay kit. Data are presented in terms of percentage versus non- EGCG-treated controls, which were assigned a value of 100%, and as means ± S.E.M from three independent experiments. Significant differences were observed versus non-EGCG-treated controls. The levels of DNMT1, DNMT3a, and DNMT3b in nuclear lysates of SCC-1 and FaDu cells were determined using Western blot analysis after treating the cells with EGCG for 6 days (<b>E</b>).</p>
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<p>EGCG treatment synergistically modulates 5Aza-dc effects on DNA methylation and DNMT activity. FaDu cells were treated with 5Aza-dc in a dose-dependent manner for 6 days. The levels of global DNA methylation (<b>A</b>) and DNMT activity (<b>B</b>) in nuclear extracts were determined using global DNA methylation and DNA methyltransferase activity assay kit. The combined effect of EGCG and 5Aza-dc was observed on the expression level of global DNA methylation (<b>C</b>) and DNMT activity (<b>D</b>). Data are presented in terms of percentage versus non-EGCG-treated controls, which was assigned a value of 100%, and as means ± S.E.M from three independent experiments. A significant difference was observed versus non-EGCG-treated controls. The levels of DNMT1, DNMT3a, and DNMT3b in nuclear lysates of FaDu cells were determined using Western blot analysis after the combined treatment (<b>E</b>).</p>
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<p>Effects of EGCG on DNA demethylation in HNSCC cells. SCC-1 and FaDu cells were treated with various concentrations of EGCG (10 and 20 μg/mL) for 6 days, and DNA demethylation was analyzed by immunostaining of 5-hydroxymethylcytosine (5hmC). Representative images of 5hmC staining (green) in FaDu and SCC-1 cells (<b>A</b>). The expression of 5hmC was quantified by ImageJ software and presented as mean gray value intensity ± S.E.M (<b>B,C</b>). <b>A</b> significant difference was observed versus non-EGCG-treated controls. EGCG treatment increased the expression of p16<sup>INK4a</sup>, p21<sup>Waf1/Cip1</sup>, and p27<sup>Kip1</sup> compared with the untreated group (<b>D</b>).</p>
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<p>Dietary administration of EGCG inhibits the tumor growth of FaDu tumor xenograft in BALB/c nude mice. Mice were inoculated subcutaneously with 2 × 10<sup>6</sup> cells (FaDu) on the right flank. Dietary administration of EGCG started one week before tumor cell inoculation. Representation of tumor bearing mice (<b>A</b>), tumor volume (<b>B</b>), body weight (<b>C</b>), and tumor weight (<b>D</b>). Data are presented as mean ± S.E.M. Statistical significance vs. non-EGCG-fed control group. n = 4.</p>
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<p>Effect of dietary administration of EGCG on epigenetic changes and tumor suppressor proteins in FaDu tumor xenografts in BALB/c nude mice. At the termination of the experiment, tumors from all groups were harvested and subjected to epigenetic changes. The effect of EGCG on global DNE methylation was assessed by immunostaining of 5-mc (<b>A</b>). The changes in DNMT1, DNMT3a, and DNMT3b protein expression were observed by immunostaining (<b>B</b>) and Western blot (<b>C</b>). EGCG administration increased the expression of p16<sup>INK4a</sup>, p21<sup>Waf1/Cip1</sup>, and p27<sup>Kip1</sup> (<b>D</b>). Each column of the Western blot represents a pool of two tumor samples, obtained from two different mice. n = 4.</p>
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23 pages, 6496 KiB  
Article
Cytotoxic and Bactericidal Effects of Inhalable Ciprofloxacin-Loaded Poly(2-ethyl-2-oxazoline) Nanoparticles with Traces of Zinc Oxide
by Mohammad Zaidur Rahman Sabuj, Flavia Huygens, Kirsten M. Spann, Abdullah A. Tarique, Tim R. Dargaville, Geoffrey Will, Md Abdul Wahab and Nazrul Islam
Int. J. Mol. Sci. 2023, 24(5), 4532; https://doi.org/10.3390/ijms24054532 - 25 Feb 2023
Cited by 8 | Viewed by 2680
Abstract
The bactericidal effects of inhalable ciprofloxacin (CIP) loaded-poly(2-ethyl-2-oxazoline) (PEtOx) nanoparticles (NPs) with traces of zinc oxide (ZnO) were investigated against clinical strains of the respiratory pathogens Staphylococcus aureus and Pseudomonas aeruginosa. CIP-loaded PEtOx NPs retained their bactericidal activity within the formulations compared to [...] Read more.
The bactericidal effects of inhalable ciprofloxacin (CIP) loaded-poly(2-ethyl-2-oxazoline) (PEtOx) nanoparticles (NPs) with traces of zinc oxide (ZnO) were investigated against clinical strains of the respiratory pathogens Staphylococcus aureus and Pseudomonas aeruginosa. CIP-loaded PEtOx NPs retained their bactericidal activity within the formulations compared to free CIP drugs against these two pathogens, and bactericidal effects were enhanced with the inclusion of ZnO. PEtOx polymer and ZnO NPs did not show bactericidal activity alone or in combination against these pathogens. The formulations were tested to determine the cytotoxic and proinflammatory effects on airway epithelial cells derived from healthy donors (NHBE), donors with chronic obstructive pulmonary disease (COPD, DHBE), and a cell line derived from adults with cystic fibrosis (CFBE41o-) and macrophages from healthy adult controls (HCs), and those with either COPD or CF. NHBE cells demonstrated maximum cell viability (66%) against CIP-loaded PEtOx NPs with the half maximal inhibitory concentration (IC50) value of 50.7 mg/mL. CIP-loaded PEtOx NPs were more toxic to epithelial cells from donors with respiratory diseases than NHBEs, with respective IC50 values of 0.103 mg/mL for DHBEs and 0.514 mg/mL for CFBE41o- cells. However, high concentrations of CIP-loaded PEtOx NPs were toxic to macrophages, with respective IC50 values of 0.002 mg/mL for HC macrophages and 0.021 mg/mL for CF-like macrophages. PEtOx NPs, ZnO NPs, and ZnO-PEtOx NPs with no drug were not cytotoxic to any cells investigated. The in vitro digestibility of PEtOx and its NPs was investigated in simulated lung fluid (SLF) (pH 7.4). The analysed samples were characterized using Fourier transform infrared spectroscopy (ATR-FTIR), scanning electron microscopy (SEM), and UV–Vis spectroscopy. Digestion of PEtOx NPs commenced one week following incubation and was completely digested after four weeks; however, the original PEtOx was not digested after six weeks of incubation. The outcome of this study revealed that PEtOx polymer could be considered an efficient drug delivery carrier in respiratory linings, and CIP-loaded PEtOx NPs with traces of ZnO could be a promising addition to inhalable treatments against resistant bacteria with reduced toxicity. Full article
(This article belongs to the Special Issue Nanoparticles in Inhaled Drug Delivery)
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Figure 1
<p>Bactericidal effects of PEtOx, blank NPs, free CIP, and CIP-loaded PEtOx NPs against <span class="html-italic">S. aureus</span>. <span class="html-italic">p</span> &gt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.05 (**).</p>
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<p>Bactericidal effects of PEtOx, blank NPs, free CIP, and CIP-loaded PEtOx NPs against <span class="html-italic">P. aeruginosa</span>.</p>
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<p>Bactericidal effects of free CIP, ZnO NPs, ZnO-PEtOx NPs, and combination of CIP-ZnO-loaded PEtOx NPs against <span class="html-italic">S. aureus</span>. <span class="html-italic">p</span> &gt; 0.05 (*).</p>
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<p>Bactericidal effects of free CIP, ZnO NPs, ZnO-PEtOx NPs, and combination of CIP-ZnO-loaded PEtOx NPs against <span class="html-italic">P. aeruginosa</span>. <span class="html-italic">p</span> &gt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.05 (**).</p>
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<p>Effect of CIP alone, blank PEtOx NPs, and CIP-loaded PEtOx NPs on cell viability (%) of (<b>A</b>) NHBE cells, (<b>B</b>) DHBEs, (<b>C</b>) CFBE41o- cell line, (<b>D</b>) HCs macrophages, and (<b>E</b>) CF-like macrophages. <span class="html-italic">p</span> &gt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.05 (**), <span class="html-italic">p</span> &lt; 0.001 (***).</p>
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<p>Effect of ZnO NPs, ZnO-PEtOx NPs, and CIP-ZnO-PEtOx NPs on the cell viability (%) of NHBE cells. <span class="html-italic">p</span> &lt; 0.001 (***).</p>
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<p>Proinflammatory effects of CIP alone, blank PEtOx NPs, and CIP-loaded PEtOx NPs on (<b>A</b>) NHBE cells, (<b>B</b>) DHBEs, (<b>C</b>) CFBE41o-cell line, (<b>D</b>) HCs macrophages, and (<b>E</b>) CF-like macrophages. The IL-8 secretion levels were normalized with the number of cells by dividing the % cell viability estimated by the LDH assay. Results expressed as the mean ± SD (<span class="html-italic">n</span> = 3) and <span class="html-italic">p</span> &gt; 0.05 (*), <span class="html-italic">p</span> &lt; 0.05 (**), <span class="html-italic">p</span> &lt; 0.001 (***).</p>
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<p>FTIR spectra of PEtOx powder and PEtOx NPs before incubating them in SLF.</p>
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<p>FTIR spectra of PEtOx powder before and after the incubation period of six weeks in SLF.</p>
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<p>FTIR spectra of PEtOx NPs before and after the incubation period of six weeks in SLF.</p>
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<p>SEM photomicrographs of PEtOx powder before and after incubating in SLF at different time intervals (<b>A</b>) PEtOx original powder (<b>B</b>) PEtOx 1 week (<b>C</b>) PEtOx 2 weeks (<b>D</b>) PEtOx 3 weeks (<b>E</b>) PEtOx 4 weeks (<b>F</b>) PEtOx 5 weeks (<b>G</b>) PEtOx 6 weeks.</p>
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<p>SEM photomicrographs of PEtOx NPs before and after incubating in SLF at different time intervals (<b>A</b>) PEtOx original NPs (<b>B</b>) PEtOx NPs 1 week (<b>C</b>) PEtOx NPs 2 weeks (<b>D</b>) PEtOx NPs 3 weeks (<b>E</b>) PEtOx NPs 4 weeks (<b>F</b>) PEtOx NPs 5 weeks (<b>G</b>) PEtOx NPs 6 weeks.</p>
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<p>UV–Vis spectra of PEtOx solution (16 µg/mL) in PBS, PEtOx NPs in PBS (16 µg/mL), and lysozyme solution (0.2 mg/mL) in PBS (pH 7.4) PBS was used as the reference.</p>
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<p>UV–Vis spectra of PEtOx powder at different time intervals incubated in SLF. SLF was used as the reference.</p>
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<p>UV–Vis spectra of PEtOx NPs at different time intervals incubated in SLF. SLF was used as the reference.</p>
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13 pages, 2589 KiB  
Article
SARS-CoV-2-Induced TSLP Is Associated with Duration of Hospital Stay in COVID-19 Patients
by Luke Gerla, Subhabrata Moitra, Desmond Pink, Natasha Govindasamy, Marc Duchesne, Eileen Reklow, Angela Hillaby, Amy May, John D. Lewis, Lyle Melenka, Tom C. Hobman, Irvin Mayers and Paige Lacy
Viruses 2023, 15(2), 556; https://doi.org/10.3390/v15020556 - 17 Feb 2023
Cited by 5 | Viewed by 3339
Abstract
Thymic stromal lymphopoietin (TSLP) is an epithelium-derived pro-inflammatory cytokine involved in lung inflammatory responses. Previous studies show conflicting observations in blood TSLP in COVID-19, while none report SARS-CoV-2 inducing TSLP expression in bronchial epithelial cells. Our objective in this study was to determine [...] Read more.
Thymic stromal lymphopoietin (TSLP) is an epithelium-derived pro-inflammatory cytokine involved in lung inflammatory responses. Previous studies show conflicting observations in blood TSLP in COVID-19, while none report SARS-CoV-2 inducing TSLP expression in bronchial epithelial cells. Our objective in this study was to determine whether TSLP levels increase in COVID-19 patients and if SARS-CoV-2 induces TSLP expression in bronchial epithelial cells. Plasma cytokine levels were measured in patients hospitalized with confirmed COVID-19 and age- and sex-matched healthy controls. Demographic and clinical information from COVID-19 patients was collected. We determined associations between plasma TSLP and clinical parameters using Poisson regression. Cultured human nasal (HNEpC) and bronchial epithelial cells (NHBEs), Caco-2 cells, and patient-derived bronchial epithelial cells (HBECs) obtained from elective bronchoscopy were infected in vitro with SARS-CoV-2, and secretion as well as intracellular expression of TSLP was detected by immunofluorescence. Increased TSLP levels were detected in the plasma of hospitalized COVID-19 patients (603.4 ± 75.4 vs 997.6 ± 241.4 fg/mL, mean ± SEM), the levels of which correlated with duration of stay in hospital (β: 0.11; 95% confidence interval (CI): 0.01–0.21). In cultured NHBE and HBECs but not HNEpCs or Caco-2 cells, TSLP levels were significantly elevated after 24 h post-infection with SARS-CoV-2 (p < 0.001) in a dose-dependent manner. Plasma TSLP in COVID-19 patients significantly correlated with duration of hospitalization, while SARS-CoV-2 induced TSLP secretion from bronchial epithelial cells in vitro. Based on our findings, TSLP may be considered an important therapeutic target for COVID-19 treatment. Full article
(This article belongs to the Special Issue Cytokines in SARS-CoV-2 Infection)
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<p>Cytokine profile of study participants. Data presented as mean (solid line, standard error of mean (SEM)), unless otherwise specified. Quartile values presented by dashed lines. <span class="html-italic">p</span> values were obtained from one-way analysis of covariance (ANCOVA) adjusted for age and sex. Note that there are missing values (2 measurements) for GM-CSF in the COVID-19 group. For abbreviations, see text.</p>
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<p>Correlation between plasma TSLP and other cytokines. Bivariate scatterplots of continuous variables are presented below the diagonal; heatmap generated from the Spearman’s correlation coefficients (<span class="html-italic">ρ</span>) with corrections for multiple comparisons (Šidák’s correction) are above the diagonal. Units shown are in pg/mL.</p>
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<p>Association between plasma TSLP levels and days of hospitalization in COVID-19 patients. Data presented as regression coefficient (β) (red line) and 95% confidence interval (CI) (shaded area). Multivariable analysis was adjusted for age, sex, heart rate, respiratory rate, body temperature and SpO<sub>2</sub> on admission, number of comorbidities, and the interval between the date of the COVID-19-positive test result and the date of hospitalization.</p>
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<p>Infection of cultured normal human bronchial epithelial cells (NHBE) with SARS-CoV-2 leads to increased intracellular TSLP. (<b>A</b>) NHBE cells were incubated with mock or SARS-CoV-2 (MOI 1) for 24 h. Cells were fixed, permeabilized, and labeled for nucleus (blue), SARS-CoV-2 SP (white), TSLP (green), and actin cytoskeleton (red). Arrowheads indicate punctated regions of SP immunoreactivity. (<b>B</b>) Intracellular fluorescent intensity of TSLP in cells, quantified using Volocity software. Each point represents a single cell (<span class="html-italic">n</span> = 190 for Mock, <span class="html-italic">n</span> = 202 for SARS-CoV-2-infected). (<b>C</b>) Fluorescence intensity of TSLP in mock- and SARS-CoV-2-infected cells expressing no detectable levels of SP (SP<sup>−</sup>) compared to cells with detectable SP (SP<sup>+</sup>) in the SARS-CoV-2 population (<span class="html-italic">n</span> = 22 for Mock SP<sup>−</sup>, <span class="html-italic">n</span> = 27 for SARS-CoV-2 SP<sup>−</sup>, <span class="html-italic">n</span> = 25 for SARS-CoV-2 SP<sup>+</sup>). Results shown are representative of 8 separate experiments. Data are presented as individual cells (dots), median (solid line), interquartile range (dotted line) and kernel density (violin). Mann–Whitney and Kruskal–Wallis were used to compare fluorescence in (<b>B</b>,<b>C</b>), respectively. Scale bar represents 10 μm.</p>
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<p>Infection of patient-derived bronchial brushings with SARS-CoV-2. (<b>A</b>) Bronchial brushings were collected from an individual donor, grown in culture, and subjected to mock infection (upper panel) or infected with SARS-CoV-2 virus (MOI 1) for 24 h (lower panel). Cells were fixed, permeabilized, and labeled for TSLP (green), SARS-CoV-2 SP (white), nucleus (blue), and actin cytoskeleton (red). Arrowheads indicate SP immunofluorescence in punctate regions. (<b>B</b>) Volocity software analysis of intracellular TSLP fluorescence intensity in mock and SARS-CoV-2-infected cells (<span class="html-italic">n</span> = 358 for Mock, <span class="html-italic">n</span> = 324 for SARS-CoV-2-infected cells). (<b>C</b>) Fluorescence intensity of TSLP in mock- and SARS-CoV-2-infected SP<sup>−</sup> cells compared with SARS-CoV-2 infected SP<sup>+</sup> cells (<span class="html-italic">n</span> = 90 for mock, <span class="html-italic">n</span> = 86 for SARS-CoV-2 SP<sup>−</sup>, <span class="html-italic">n</span> = 72 for SARS-CoV-2 SP<sup>+</sup>). Results from all donors (<span class="html-italic">n</span> = 3) are shown in (<b>B</b>) and from a representative donor in (<b>C</b>). Data are presented as individual cells (dots), median (solid line), interquartile range (dotted line), and kernel density (violin). Mann–Whitney and Kruskal–Wallis were used to compare fluorescence in (<b>B</b>,<b>C</b>), respectively. Scale bar represents 10 μm.</p>
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