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11 pages, 1067 KiB

Open AccessArticle

Deletion of gE in Herpes Simplex Virus 1 Leads to Increased Extracellular Virus Production and Augmented Interferon Alpha Production by Peripheral Blood Mononuclear Cells

by Manon Claeys, Jonas Delva, Cedric Jacqmotte, Cliff Van Waesberghe and Herman W. Favoreel

Pathogens 2024, 13(12), 1138; https://doi.org/10.3390/pathogens13121138 (registering DOI) - 23 Dec 2024

Abstract

Herpes simplex virus (HSV) in humans and pseudorabies virus (PRV) in pigs are both alphaherpesviruses. Plasmacytoid dendritic cells (pDCs) make part of the peripheral blood mononuclear cells (PBMCs) and are specialized in producing large amounts of antiviral type I interferon (IFN-I). IFN-I production [...] Read more.

Herpes simplex virus (HSV) in humans and pseudorabies virus (PRV) in pigs are both alphaherpesviruses. Plasmacytoid dendritic cells (pDCs) make part of the peripheral blood mononuclear cells (PBMCs) and are specialized in producing large amounts of antiviral type I interferon (IFN-I). IFN-I production by PBMCs in response to both HSV-1 and PRV can be virtually exclusively attributed to pDCs. Recently, we discovered that cells infected with gEnull PRV trigger increased production of IFNalpha by porcine PBMCs/pDCs compared with cells infected with wild-type (WT) PRV. This increased IFNalpha response correlates with increased extracellular virus production triggered by gEnull PRV compared with WT PRV. The gE protein and some of its currently described functions are conserved in different alphaherpesviruses, including PRV and HSV-1. In the current study, we report that cells infected with gEnull HSV-1 trigger increased IFNalpha production by human PBMCs and increased extracellular virus production compared with WT HSV-1. Hence, these recently described functions of PRV gE are conserved in HSV-1 gE. Since the increased extracellular virus production and IFNalpha response have also been reported for successful (gEnull) PRV vaccines, the current findings may have important consequences for the rational design of HSV vaccines. Full article

(This article belongs to the Section Viral Pathogens)

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Figure 1

Figure 1
Vero cells infected with gEnull HSV-1 trigger increased IFNalpha by PBMCs compared with cells infected with WT HSV-1. (A) HSV-1 gEnull-infected Vero cells trigger an increased IFN-I response in human PBMCs compared with cells infected with isogenic WT HSV-1. Vero cells were mock-inoculated or inoculated with WT or gEnull HSV-1 strains. At 2 hpi, cells were washed and co-incubated with human PBMCs for 22 h. IFNalpha concentrations in the supernatant were determined by ELISA. (B) Vero cells were either transfected with a plasmid expressing both HSV-1 gE and GFP, not transfected or transfected with a plasmid expressing only GFP. At 24 h post transfection, Vero cells were inoculated with WT or isogenic gEnull HSV-1. The inoculated cells were co-incubated with human PBMCs for 22 h. Supernatant was collected, and IFNalpha concentrations were determined by ELISA. Graphs show means, standard deviations, and individual data points of 5 independent repeats. (A,B): ns, non significant; *, p < 0.05; ***, p < 0.001; ****, p < 0.0001 using two-way ANOVA. Full article ">Figure 2
Infection of Vero cells with gEnull HSV-1 results in increased virus titers in the supernatant at relatively early in infection compared with WT HSV-1. (A,B) Vero cells infected with gEnull HSV-1 display higher extracellular virus titers compared with cells infected with WT HSV-1 at 14 hpi (A). At 24 hpi (B) HSV-1 virus titers of WT and gEnull HSV-1 are comparable. (C) Vero cells were transfected with a gE-expressing plasmid. Twenty-four hours later, cells were inoculated with WT or isogenic gEnull HSV-1. Supernatants were collected at 14 or 24 hpi, and extracellular viral titers were determined. Graphs show means, standard deviations, and individual data points of 4 independent repeats (A–C): ns, not significant; *, p < 0.05, Student’s t-test. (D) Vero cells were inoculated with WT or gEnull HSV-1, and extracellular viral titers in the supernatant were determined at different time points. (E) Vero cells were inoculated with WT or gEnull HSV-1. At different time points, supernatant was collected and co-incubated with human PBMCs for 24 h. IFNalpha concentrations were determined by ELISA. Graphs show means, standard deviations, and individual data points of 5 independent repeats (D,E): ns, not significant; *, p < 0.05, two-way ANOVA with Šidák correction for multiple comparisons. Full article ">Figure 3
Equal amounts of WT or gEnull HSV-1 trigger similar IFNalpha production by PBMCs. (A) Supernatant of WT HSV-1- or gEnull HSV-1-infected Vero cells was collected at 14 hpi and ultracentrifuged to remove viral particles. Next, WT HSV-1 inoculated Vero cells were overlaid with virus-free supernatant of either WT or gEnull HSV-1-infected cells and co-incubated with human PBMCs. After 22 h, IFNalpha concentrations in the supernatant were determined. (B) Human PBMCs were incubated with equal amounts of WT or gEnull HSV-1 infectious virus particles (2.5 × 106 TCID50) for 24 h. Afterward, IFNalpha concentration in the supernatant was determined by ELISA. (C,D) Vero cells were inoculated with WT or gEnull HSV-1 and incubated for 14 h (C) or 22 h (D). Supernatant was collected, and human PBMCs were incubated with the prepared supernatant for 24 h. IFNalpha concentrations were determined. Graphs show means, standard deviations, and individual data points of 5 independent repeats (A–D): ns, not significant; **, p < 0.01, using ratio paired Student’s t-test. Full article ">

14 pages, 2047 KiB

Open AccessArticle

Enhancement of Human Immunodeficiency Virus-Specific CD8⁺ T Cell Responses with TIGIT Blockade Involves Trogocytosis

by Nazanin Ghasemi, Kayla A. Holder, Danielle P. Ings and Michael D. Grant

Pathogens 2024, 13(12), 1137; https://doi.org/10.3390/pathogens13121137 (registering DOI) - 23 Dec 2024

Abstract

Natural killer (NK) and CD8⁺ T cell function is compromised in human immunodeficiency virus type 1 (HIV-1) infection by increased expression of inhibitory receptors such as TIGIT (T cell immunoreceptor with Ig and ITIM domains). Blocking inhibitory receptors or their ligands with [...] Read more.

Natural killer (NK) and CD8⁺ T cell function is compromised in human immunodeficiency virus type 1 (HIV-1) infection by increased expression of inhibitory receptors such as TIGIT (T cell immunoreceptor with Ig and ITIM domains). Blocking inhibitory receptors or their ligands with monoclonal antibodies (mAb) has potential to improve antiviral immunity in general and facilitate HIV eradication strategies. We assessed the impact of TIGIT engagement and blockade on cytotoxicity, degranulation, and interferon-gamma (IFN-γ) production by CD8⁺ T cells from persons living with HIV (PLWH). The effect of TIGIT engagement on non-specific anti-CD3-redirected cytotoxicity was assessed in redirected cytotoxicity assays, and the effect of TIGIT blockade on HIV-specific CD8⁺ T cell responses was assessed by flow cytometry. In 14/19 cases where peripheral blood mononuclear cells (PBMC) mediated >10% redirected cytotoxicity, TIGIT engagement reduced the level of cytotoxicity to <90% of control values. We selected PLWH with >1000 HIV Gag or Nef-specific IFN-γ spot forming cells per million PBMC to quantify the effects of TIGIT blockade on HIV-specific CD8⁺ T cell responses by flow cytometry. Cell surface TIGIT expression decreased on CD8⁺ T cells from 23/40 PLWH following TIGIT blockade and this loss was associated with increased anti-TIGIT mAb fluorescence on monocytes. In total, 6 of these 23 PLWH had enhanced HIV-specific CD8⁺ T cell degranulation and IFN-γ production with TIGIT blockade, compared to 0/17 with no decrease in cell surface TIGIT expression. Reduced CD8⁺ T cell TIGIT expression with TIGIT blockade involved trogocytosis by circulating monocytes, suggesting that an effector monocyte population and intact fragment crystallizable (Fc) functions are required for mAb-based TIGIT blockade to effectively enhance HIV-specific CD8⁺ T cell responses. Full article

(This article belongs to the Section Viral Pathogens)

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Figure 1

Figure 1
Effect of TIGIT engagement on T cell-mediated cytotoxicity. (a) Diagram illustrating strategy employed to enact TIGIT engagement on freshly isolated T cells triggered by anti-CD3 to lyse P815 cells (created with BioRender.com). (b) Comparison of anti-CD3-triggered lysis of P815 targets by PBMC from PLWH in the presence of anti-TIGIT or isotype control. Cases where specific lysis was reduced by >1/10 of baseline values by TIGIT engagement compared to the isotype control are shown with red lines and the probability of a significant reduction in specific lysis for the overall group following TIGIT engagement was calculated. (** p < 0.01, Student’s paired t test). Full article ">Figure 2
Impact of TIGIT blockade on CD8+ T cell TIGIT expression. To assess the effects of TIGIT blockade on HIV-specific CD8+ T cell function, PBMC were labeled with fluorescence conjugated anti-TIGIT mAb for 30 min before 5 h incubation with HIV Gag or Nef peptides. Additional labeled anti-TIGIT mAb was added after the 5 h incubation period with cell surface staining for CD3, CD4, and CD8. Our gating strategy for analysis of CD8+ T cell TIGIT expression is shown (a–c) with representative results in (d,e). Summary results for 23 subjects losing >1/10th of TIGIT expression from their CD8+ T cells following TIGIT blockade are shown graphically in (f). Full article ">Figure 3
Flow cytometry analysis of HIV-specific CD8+ T cell activation and effect of TIGIT blockade. The gating strategy for analyzing effects of TIGIT blockade on IFN-γ production and CD107a expression by CD8+ T cells stimulated with HIV Gag and Nef peptides is shown with a representative example of an HIV-specific CD8+ T cell response enhanced by TIGIT blockade (a–f). Summary graphs of effect of TIGIT blockade on (g) IFN-γ production and (h) CD107a expression by CD8+ T cells from responders to TIGIT blockade with an increase >10% above that seen with isotype control treatment. Full article ">Figure 4
Detection of monocyte-mediated trogocytosis of TIGIT from CD8+ T cells. After five-hour incubation of PBMC with either fluorescent anti-TIGIT mAb or isotype control, anti-TIGIT, and isotype control-treated cells were surface stained with fluorescent anti-TIGIT mAb and monocytes gated for analysis as shown in (a,b). A representative example of the gain in anti-TIGIT mAb fluorescence on monocytes following TIGIT blockade is shown in (c,d). Letters A, B, and C within the flow cytometry plot frames refer to the gated population analyzed and the percentages above markers in (c,d) indicate the percent of cells in that gate positive for anti-TIGIT fluorescence. Monocyte identity was confirmed by 0% CD3 expression and >90% CD14 expression on cells gated in (b). (e) Summary graph of the results obtained with PBMC from eight PLWH responders to TIGIT blockade in terms of loss of CD8+ T cell TIGIT expression. (f) TIGIT blockade was carried out in PBMC separated from untreated PBMC with a semi-permeable membrane with changes in anti-TIGIT mAb fluorescence in the monocyte population shown after 5 h incubation with or without cell contact allowed. Full article ">

9 pages, 273 KiB

Open AccessCommunication

Compartmentalization of the Inflammatory Response in the Pericardial Cavity in Patients Undergoing Cardiac Surgery

by Mohammad M. El-Diasty, Javier Rodríguez, Luis Pérez, Souhayla Souaf, Sonia Eiras and Angel L. Fernández

Int. J. Mol. Sci. 2024, 25(24), 13720; https://doi.org/10.3390/ijms252413720 - 23 Dec 2024

Abstract

The systemic inflammatory response after cardiopulmonary bypass has been widely studied. However, there is a paucity of studies that focus on the local inflammatory changes that occur in the pericardial cavity. The purpose of this study is to assess the inflammatory mediators in [...] Read more.

The systemic inflammatory response after cardiopulmonary bypass has been widely studied. However, there is a paucity of studies that focus on the local inflammatory changes that occur in the pericardial cavity. The purpose of this study is to assess the inflammatory mediators in the pericardial fluid of patients undergoing cardiac surgery. We conducted a prospective cohort study on patients undergoing aortic valve replacement. Pericardial fluid and peripheral venous blood samples were collected after the opening of the pericardium. Additional samples were obtained from peripheral blood and the pericardial fluid shed through mediastinal drains 24 and 48 h after surgery. Levels of interleukin 1α (IL-1α), interleukin 1β (IL-1β), interleukin 2 (IL-2), interleukin 4 (IL-4), interleukin 6 (IL-6), interleukin 8 (IL-8), interleukin 10 (IL-10), tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), vascular endothelial growth factor (VEGF), monocyte chemotactic protein-1 (MCP-1), epidermal growth factor (EGF), soluble E-selectin, L-selectin, P-selectin, intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1) were determined in all pericardial fluid and serum samples. A total of 45 patients with a mean age of 74 years were included, of which 66% were males. Serum levels of IL-6, IL-8, and MCP-1 were significantly increased at 24 and 48 h after surgery. No significant changes were observed in the serum levels of the remaining mediators. A significant increase of postoperative pericardial fluid levels of IL-1α, IL-1β, IL-6, IL-8, IL-10, IFN-γ, VEGF, MCP-1, VCAM-1, and P-selectin was observed at 24 and 48 h after surgery. There is a robust systemic and pericardial inflammatory response after cardiac surgery on cardiopulmonary bypass. However, postoperative pericardial inflammatory activity shows a distinct pattern and is more marked than at the systemic level. These findings suggest that there is a compartmentalization of the inflammatory response within the pericardial cavity after cardiac surgery. Full article

(This article belongs to the Section Molecular Immunology)

16 pages, 2650 KiB

Open AccessArticle

Insulin Sensitivity Controls Activity of Pathogenic CD4+ T Cells in Rheumatoid Arthritis

by Malin C. Erlandsson, Eric Malmhäll-Bah, Venkataragavan Chandrasekaran, Karin M. E. Andersson, Lisa M. Nilsson, Sofia Töyrä Silfverswärd, Rille Pullerits and Maria I. Bokarewa

Cells 2024, 13(24), 2124; https://doi.org/10.3390/cells13242124 (registering DOI) - 22 Dec 2024

Viewed by 231

Abstract

Hyperinsulinemia connects obesity, and a poor lipid profile, with type 2 diabetes (T2D). Here, we investigated consequences of insulin exposure for T cell function in the canonical autoimmunity of rheumatoid arthritis (RA). We observed that insulin levels correlated with the glycolytic index of [...] Read more.

Hyperinsulinemia connects obesity, and a poor lipid profile, with type 2 diabetes (T2D). Here, we investigated consequences of insulin exposure for T cell function in the canonical autoimmunity of rheumatoid arthritis (RA). We observed that insulin levels correlated with the glycolytic index of CD4+ cells but suppressed transcription of insulin receptor substrates, which was inversely related to insulin sensitivity. This connection between insulin levels and the glycolytic index was not seen in CD4+ cells of healthy controls. Exposure of CD4+ cells to insulin induced a senescent state recognized by cell cycle arrest and DNA content enrichment measured by flow cytometry. It also resulted in accumulation of DNA damage marker γH2AX. Insulin suppressed IFNγ production and induced the senescence-associated secretome in CD4+ cell cultures and in patients with hyperinsulinemia. Inhibition of JAK-STAT signaling (JAKi) improved insulin signaling, which activated the glycolytic index and facilitated senescence in CD4+ cell cultures. Treatment with JAKi was associated with an abundance of naïve and recent thymic emigrant T cells in the circulation of RA patients. Thus, we concluded that insulin exerts immunosuppressive ability by inducing senescence and inhibiting IFNγ production in CD4+ cells. JAKi promotes insulin effects and supports elimination of the pathogenic CD4+ cell in RA patients. Full article

(This article belongs to the Section Cellular Metabolism)

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Figure 1

Figure 1
Glycolytic index of CD4+ T cells is in proportion to plasma insulin levels in rheumatoid arthritis. (A) Insulin signaling pathway. (B) Scatter plot of glycolytic index (GI) in CD4+ cells of untreated RA (n = 16) and age matched HC (n = 41). Solid line indicates median. Dotted line indicates average level. (C) Scatter plot of correlation between GI and plasma insulin levels of RA patients (red) and HC (black). Solid lines indicate lineal regression curve. (D). Scatter plot of gene expression in CD4+ cells. Solid line indicates median. (E) Heatmap of Spearman correlation rho values between GI, plasma insulin, and IGF1 levels with the insulin signaling genes and serological parameters. Color scale bar indicates rho value range. (F) Heatmap of the log2 fold change (FC) difference in gene expression of CD4+ cells with high (GI-hi, n = 34) and low (GI-lo, n = 35) GI, and between RA and HC with high GI, by RNA-Seq. p-values were obtained by DESeq2 test. Color scale bar indicates log2FC range. (G) Bubble diagram of transcription factor target enrichment (by FDR) among DEGs upregulated in CD4+ cells with high and low GI. (H) Bar diagram of biological processes (by GO:terms) enriched among DEGs upregulated in CD4+ cells with high and low GI. * p < 0.05, ** p < 0.01, *** p < 0.001. RA, rheumatoid arthritis; HC, healthy controls; CRP, C-reactive protein; WBC, white blood cell count; IGF1, insulin-like growth factor 1; INSR, insulin receptor; IGF1R, IGF1 receptor; IRS, insulin receptor substrate; IFNγ, interferon gamma; FDR, false discovery rate; GI, glycolytic index; VEGF, vascular endothelial growth factor. Full article ">Figure 2
Insulin induces senescence and suppresses IFNγ production in CD4+ cells. CD4+ cells of 18 healthy subjects were stimulated with anti-CD3 and insulin 10 nM for 48 h. DNA content (7AAD) was analyzed by flow cytometry in large-size cell (LSC) and small-size cell (SSC) subsets. p-values were obtained by paired Wilcoxon test. (A) Scatter plot of DNA content by mean fluorescence intensity (MFI) of 7AAD+ cells. Scatter plot of DNA content change with insulin treatment. Con, control; Ins, insulin treated. Solid line indicates median. (B) Histogram of 7AAD+ cell distribution by phases of the cell cycle. Colored areas correspond to G1 (blue), S (yellow) and G2 (green) phases. (C) Scatter plot of 7AAD+ cell frequency in cell cycle phases. (D) Scatter plot of change in proliferation dye CellTrace violet (CTV) in insulin-stimulated CD4+ cells. Solid line indicates median. (E) Confocal microscopy image of nuclear γH2AX enrichment in insulin-treated THP1 cells. Blue line confines nuclear area. (F) Scatter plot of γH2AX density in nuclei of insulin-treated THP1 cells. Solid line indicates median. (G) Scatter plot of gene expression in insulin-treated CD4+ cells, in relative quantity (RQ) to control cell cultures. Expression was measured by qPCR. (H) Dotblot images of cytokine levels in pooled supernatants of insulin-treated and control cells measured by cytokine array. FC, fold change. (I) Scatter plot of cytokine protein levels in supernatants, by specific ELISA. (J) Heatmap of gene expression difference by log2 FC, by RNA-Seq. Samples are grouped by high (n = 34) and low (n = 35) glycolytic index (GI), high (n = 12) and low (n = 44) insulin, and JAKi-treated (n = 24) and non-JAKi-treated patients (Other, n = 32). p-values were obtained by DESeq2 test. Color scale bar indicates log2FC range. * p < 0.05, ** p < 0.01, *** p < 0.001. Full article ">Figure 3
JAK/STAT-inhibitors (JAKi) increase insulin sensitivity and aggravate senescence in CD4+ cells. (A) Cell cycle phases and control check points. (B) Heatmap of transcription difference in CD4+ cell transcriptome of RA patients with high (n = 12) and low (n = 44) plasma insulin, JAKi-treated (n = 24) or non-JAKi-treated (Other, n = 32) and HC with high (n = 34) and low (n = 35) glycolytic index (GI), by RNA-Seq. Difference between groups was calculated by DESeq2-test. Color scale bar presents log2FC range. * p < 0.05, ** p < 0.01, *** p < 0.001. (C) Scatter plot of GI in CD4+ cells split by plasma insulin levels within JAKi-treated (Hi, n = 7, Lo, n = 17) and non-JAKi-treated (Other, Hi, n = 5, Lo, n = 27) RA patients. Solid line indicates median. (D) Heatmap of gene transcription difference in insulin signaling and GI of CD4+ cells as in B. (E) Scatter plot of DNA content by mean fluorescent intensity (MFI) in JAKi-treated and control cell cultures (n = 10). Scatter plot of frequency of 7AAD+ cells in different phases of the cell cycle. Scatter plot of proliferation tracer cell trace violet (CTV) intensity in JAKi-stimulated and control CD4+ cells. Solid line indicates median. (F) Histogram of 7AAD+ cell distribution in small-size CD4+ cells (SSC). Colored areas indicate cells stimulated with JAKi (yellow), JAKi + insulin (blue), and control culture (red line). (G) Box plot of DNA content change by 7AAD and population size change in paired CD4+ cell cultures stimulated with JAKi and insulin (n = 6). p-values by paired Wilcoxon test. Dotted line indicates basal level. (H) Scatter plot of gene transcription in CD4+ cells stimulated with anti-CD3 and tofacitinib (JAKi, 10 µM; Con, 0 µM) for 48 h. mRNA levels were analyzed by qPCR and are presented in relative quantity (RQ) to mock treated cells. Full article ">Figure 4
Insulin mitigates transcriptional effect of JAK-inhibitors (JAKi) in CD4+ T cells. CD4+ cells of RA patients were isolated by positive selection, activated on anti-CD3 for 2 h, and analyzed by RNA-Seq. Serum was used for protein measurements by immunosorbent assay. Differences between the groups were analyzed by DESeq2 test and Mann–Whitney U test. (A) Scatter plot of normalized gene transcription in JAKi-treated (Hi, n = 7, Lo, n = 17) and non-JAKi-treated patients (Other, Hi, n = 5, Lo, n = 27), split by high (Hi) and low (Lo) insulin levels. Solid line indicates median. (B) Scatter plot of IL6, IL8, survivin, and VEGF levels in serum. Solid line indicates median. (C) Heatmap of transcription difference by log2 fold change (FC) in CD4+ cells of RA patients with high (n = 12) and low (n = 44) plasma insulin levels, JAKi-treated (n = 24) or non-JAKi-treated (n = 32), by DESeq2. Color scale bar presents log2FC range. * p < 0.05, ** p < 0.01, *** p < 0.001. RT emigrants, recent thymic emigrants. Full article ">

14 pages, 1485 KiB

Open AccessArticle

Antiviral Activity of Ecklonia cava Extracts and Dieckol Against Zika Virus

by Eun-A Kim, Nalae Kang, Jun-Ho Heo, Areumi Park, Seong-Yeong Heo, Hyun-Soo Kim and Soo-Jin Heo

Int. J. Mol. Sci. 2024, 25(24), 13694; https://doi.org/10.3390/ijms252413694 - 21 Dec 2024

Viewed by 269

Abstract

Ecklonia cava and its major compound dieckol, both natural marine products, possess antioxidant, anti-inflammatory, and metabolic-regulating effects. Zika virus (ZIKV), an arbovirus from the Flaviviridae family, is transmitted by mosquitoes and causes serious illnesses in humans. This study aimed to evaluate the anti-ZIKV [...] Read more.

Ecklonia cava and its major compound dieckol, both natural marine products, possess antioxidant, anti-inflammatory, and metabolic-regulating effects. Zika virus (ZIKV), an arbovirus from the Flaviviridae family, is transmitted by mosquitoes and causes serious illnesses in humans. This study aimed to evaluate the anti-ZIKV potential of Ecklonia cava and dieckol. The antiviral activity of Ecklonia cava extract (ECE), prepared with 80% ethanol, was assessed in ZIKV-infected Vero E6 cells through MTT assay, plaque assay, and quantitative polymerase chain reaction (qPCR), demonstrating no cytotoxicity and a significant reduction in viral titers and ZIKV mRNA levels. In addition, ECE decreased the expression of tumor necrosis factor-α and interferon-induced protein with tetratricopeptide repeats in the ZIKV-infected cells. Dieckol, the primary active compound in ECE, exhibited potent anti-ZIKV activity, with a half maximal inhibitory concentration (IC₅₀), value of 4.8 µM. In silico molecular docking analysis revealed that dieckol forms stable complexes with key ZIKV proteins, including the envelope, NS2B/NS3, and RNA-dependent RNA polymerase (RdRp) protein, exhibiting high binding energies of −438.09 kcal/mol, −1040.51 kcal/mol, and −1043.40 kcal/mol, respectively. Overall, our findings suggest that ECE and dieckol are promising candidates for the development of anti-ZIKV agents. Full article

(This article belongs to the Special Issue Emerging Biotechnological Approaches for Natural Antiviral Molecules Discovery)

14 pages, 2033 KiB

Open AccessArticle

Inflammatory Stimulation Upregulates the Receptor Transporter Protein 4 (RTP4) in SIM-A9 Microglial Cells

by Wakako Fujita and Yusuke Kuroiwa

Int. J. Mol. Sci. 2024, 25(24), 13676; https://doi.org/10.3390/ijms252413676 - 21 Dec 2024

Viewed by 194

Abstract

The receptor transporter protein 4 (RTP4) is a receptor chaperone protein that targets class A G-protein coupled receptor (GPCR)s. Recently, it has been found to play a role in peripheral inflammatory regulation, as one of the interferon-stimulated genes (ISGs). However, the detailed role [...] Read more.

The receptor transporter protein 4 (RTP4) is a receptor chaperone protein that targets class A G-protein coupled receptor (GPCR)s. Recently, it has been found to play a role in peripheral inflammatory regulation, as one of the interferon-stimulated genes (ISGs). However, the detailed role of RTP4 in response to inflammatory stress in the central nervous system has not yet been fully understood. While we have previously examined the role of RTP4 in the brain, particularly in neuronal cells, this study focuses on its role in microglial cells, immunoreactive cells in the brain that are involved in inflammation. For this, we examined the changes in the RTP4 levels in the microglial cells after exposure to inflammatory stress. We found that lipopolysaccharide (LPS) treatment (0.1~1 µg/mL, 24 h) significantly upregulated the RTP4 mRNA levels in the microglial cell line, SIM-A9. Furthermore, the interferon (IFN)-β mRNA levels and extracellular levels of IFN-β were also increased by LPS treatment. This upregulation was reversed by treatment with neutralizing antibodies targeting either the interferon receptor (IFNR) or toll-like receptor 4 (TLR4), and with a TLR4 selective inhibitor, or a Janus kinase (JAK) inhibitor. On the other hand, the mitogen-activated protein kinase kinase (MEK) inhibitor, U0126, significantly enhanced the increase in RTP4 mRNA following LPS treatment, whereas the PKC inhibitor, calphostin C, had no effect. These findings suggest that in microglial cells, LPS-induced inflammatory stress activates TLR4, leading to the production of type I IFN, the activation of IFN receptor and JAK, and finally, the induction of RTP4 gene expression. Based on these results, we speculate that RTP4 functions as an inflammation-responsive molecule in the brain. However, further research is needed to fully understand its role. Full article

(This article belongs to the Special Issue Pharmacological Treatment of Neuroinflammation)

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Figure 1

Figure 1
Changes in RTP4 mRNA levels after LPS stimulation in SIM-A9 microglial cell line. Cells were treated with LPS (100 ng/mL) for 24 h (A), 6 h (C) or for indicated periods (B) and then collected to perform RT-qPCR analysis by using selective primers targeting GAPDH (internal control) or RTPs. Control cells were treated with a vehicle instead of LPS for the indicated periods. Data are the mean ± S.E.M. n = 10 (A), n = 7 (B), n = 4 (C), * p < 0.05, *** p < 0.0001, vs. control (without LPS), one-way ANOVA and Tukey’s multiple comparison test (A), multiple unpaired t-test (B,C). Full article ">Figure 2
The effect of LPS stimulation on the expression levels of RTP4 determined by immunofluorescent analysis. SIM-A9 microglial cells were treated without or with LPS (100 ng/mL) for the indicated periods and immunofluorescent analysis performed as described in Materials and Methods. Control cells (−) were treated with vehicle instead of LPS for 24 h. Scale bar is 10 micrometer. Data are the mean ± S.E.M. n = 144 (Control), n = 53 (LPS 6 h), n = 138 (LPS 12 h), n = 130 (LPS 24 h), n = 100 (LPS 48 h) ’n’ represents the total number of cells from 3 independent experiments. * p < 0.05, *** p < 0.0001, vs. control, one-way ANOVA and Tukey’s multiple comparison test. Full article ">Figure 3
Changes in TNFα (A), IL-1β (B), and iNOS (C) mRNA levels after LPS treatment. SIM-A9 microglial cells were treated with LPS (100 ng/mL) for the indicated periods and then collected to perform RT-qPCR analysis using selective primers targeting GAPDH (internal control), TNFα, IL-1β or iNOS. Control cells (−) were treated with a vehicle instead of LPS for indicated periods. Data are the mean ± S.E.M. n = 12 (3 and 12 h); n = 16 (6 and 24 h); n = 10 (48 h), * p < 0.05, ** p < 0.001, *** p < 0.0001, vs. control, multiple unpaired t-test. Full article ">Figure 4
Changes in IFN-α (A) and IFN-β (B) mRNA levels after LPS treatment. SIM-A9 microglial cells were treated with LPS (100 ng/mL) for the indicated periods and collected for RT-qPCR analysis as described in Methods using selective primers targeting GAPDH (internal control), IFN-α, or IFN-β. Control cells were treated with a vehicle instead of LPS for indicated periods. Data are the mean ± S.E.M. n = 12 (3, 12 h), n = 16 (6, 24 h), n = 10 (48 h), ** p < 0.001, *** p < 0.0001, vs. control, one-way ANOVA, and Tukey’s multiple comparison test. Effect of TAK242, a TLR4 inhibitor, on the increase in extracellular IFN-β levels after LPS treatment (C–E). SIM-A9 microglial cells were treated with LPS (100 ng/mL) for the indicated periods and the culture medium was collected for ELISA analysis as described in Methods. Data are the mean ± S.E.M. n = 5–6, *** p < 0.0001, vs. control, ### p < 0.0001, vs. LPS alone. Multiple unpaired t-test (A,B), one-way ANOVA and Turkey’s multiple comparison test (C–E). Full article ">Figure 5
The effect of neutralizing antibody targeting TLR4 (A), selective inhibitor of TLR4 (TAK242) (B), neutralizing antibody targeting IFNR (IFNAR-1) (C) and inhibitor of JAK (Pyridone 6) (D) on LPS-induced upregulation of RTP4 mRNA levels. SIM-A9 microglial cells were pretreated with TLR4 antibody (10 µg/mL), TAK242 (100 nM), IFNR antibody (20 ug/mL) or Pyridone 6 at indicated concentrations for 30 min before the LPS (100 ng/mL) or vehicle treatment for 6 h or 24 h which cells were collected and subjected to RT-qPCR analyses using primers that target GAPDH and RTP4. Control cells were pretreated with medium instead of antibody or inhibitor and treated with vehicle instead of LPS for 24 h. Data are the mean ± S.E.M. n = 3–7 (A), n = 5–6 (B), n = 7 (C), n = 4 (D). *** p < 0.0001, vs. control, ### p < 0.0001, vs. LPS alone. One-way ANOVA and Turkey’s multiple comparison test. Full article ">Figure 6
The effect of inhibitors of MAPK kinase (A) and PKC (B), TLR4 downstream signaling molecules, on LPS-induced upregulation of RTP4 mRNA levels. SIM-A9 microglial cells were pretreated with inhibitors at indicated concentrations for 30 min before the LPS (100 ng/mL) or vehicle treatment for 24 h after which cells were collected and subjected to RT-qPCR analyses using primers that target GAPDH and RTP4. Control cells were pretreated with medium instead of inhibitor and treated with vehicle instead of LPS for 24 h. Data are mean ± S.E.M. n = 8, * p < 0.05, *** p < 0.0001, vs. control, # p < 0.05, vs. LPS alone, n.s., not significant, one-way ANOVA and Turkey’s multiple comparison test. Full article ">Figure 7
Illustration of the TLR4 signaling pathways and the mechanism of RTP4 induction under LPS stimulation. Following LPS stimulation, TLR4 activation leads to IFN-β production in microglial cells. IFN-β is subsequently released into the extracellular compartment and transactivates IFNR, resulting in RTP4 production. ‘?’ and the dashed line indicates a pathway that has not been elucidated in this study and is thus a hypothesis here. Full article ">

17 pages, 8649 KiB

Open AccessArticle

LPS Disrupts Endometrial Receptivity by Inhibiting STAT1 Phosphorylation in Sheep

by Xing Fan, Jinzi Wei, Yu Guo, Juan Ma, Meiyu Qi, He Huang, Peng Zheng, Wenjie Jiang and Yuchang Yao

Int. J. Mol. Sci. 2024, 25(24), 13673; https://doi.org/10.3390/ijms252413673 - 21 Dec 2024

Viewed by 294

Abstract

Uterine infections reduce ruminant reproductive efficiency. Reproductive dysfunction caused by infusion of Gram-negative bacteria is characterized by the failure of embryo implantation and reduced conception rates. Lipopolysaccharide (LPS), a major component of the outer membrane of Gram-negative bacteria, is highly abortogenic. In this [...] Read more.

Uterine infections reduce ruminant reproductive efficiency. Reproductive dysfunction caused by infusion of Gram-negative bacteria is characterized by the failure of embryo implantation and reduced conception rates. Lipopolysaccharide (LPS), a major component of the outer membrane of Gram-negative bacteria, is highly abortogenic. In this study, the effects of LPS infusion on the endometrial receptivity of sheep were studied during three critical periods of embryo implantation. The results showed that LPS infusion on d12, d16, and d20 of pregnancy in vivo interfered with the expression of prostaglandins (PGs) and affected the expression of adhesion-related factors (ITGB1/3/5, SPP1), key implantation genes (HOXA10, HOXA11 and LIF), and progestational elongation genes (ISG15, RSAD2 and CXCL10) during embryo implantation. In addition, after LPS infusion on d12, d16, and d20, the phosphorylation level of STAT1 significantly decreased and the protein expression level of IRF9 significantly increased on d12, suggesting that LPS infusion in sheep impairs endometrial receptivity through the JAK2/STAT1 pathway. Sheep endometrial epithelial cells were treated with 17 β-estrogen, progesterone, and/or interferon-tau in vitro to mimic the receptivity of the endometrium during early pregnancy for validation. LPS and the p-STAT1 inhibitor fludarabine were both added to the model, which resulted in reduced p-STAT1 protein expression, significant inhibition of PGE2/PGF2α, and significant suppression of the expression of key embryo implantation genes. Collectively, these results indicate that LPS infusion in sheep on d12, d16, and d20 impairs endometrial receptivity through the JAK2/STAT1 pathway, which is responsible for LPS-associated pregnancy failure. Full article

(This article belongs to the Section Molecular Biology)

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Figure 1
Effect of LPS on prostaglandin expression in sheep endometrium. (A) The secretion of PGE2 and PGF2α in endometrial tissue was measured on d12, d16, and d20 of pregnancy using an ELISA kit. (B) The secretion of PGE2 and PGF2α in endometrial tissue was measured on d12, d16, and d20 of pregnancy using an ELISA kit. (C) The ratio of PGE2 and PGF2α in endometrial tissue on d12, d16, and d20 of pregnancy. (D) The rate-limiting enzymes PTGS1, PTGS2 (E), PTGES (F), and PGFS (G) of synthesized PGs in endometrial tissue on d12, d16, and d20 of pregnancy were measured by real-time quantitative PCR. All data are presented as the mean ± SEM, n ≥ 3; * p < 0.05; ** p < 0.01. Full article ">Figure 2
Effect of LPS on endometrial receptivity genes in sheep. (A) The pro-conceptus elongation gene ISG15, RSAD2 (B), and CXCL10 (C) on d12, d16, and d20 of pregnancy in endometrial tissue were measured by real-time quantitative PCR. (D) The adhesion molecules ITGB1, ITGB3 (E), ITGB5 (F), SPP1 (G), and MUC1 (H) on d12 of pregnancy in endometrial tissue were measured by real-time quantitative PCR. (I) The endometrial receptivity markers HOXA10, HOXA11 (J), and LIF (K) on d12 of pregnancy in endometrial tissue were measured by real-time quantitative PCR. All data are presented as the mean ± SEM, n ≥ 3; * p < 0.05; ** p < 0.01. Full article ">Figure 3
LPS affected JAK2/STAT1 pathways. (A) The protein level of p-JAK2, T-JAK2, p-STAT1, T-STAT1, and IRF9 on d12, d16, and d20 of pregnancy in sheep endometrial tissue. (B) p-JAK2/β-actin, T-JAK2/β-actin (C), and p-JAK2/T-JAK2 (D) ratio on d12, d16, and d20 of pregnancy in sheep endometrial tissue. (E) p-STAT1/β-actin, T-STAT1/β-actin (F), and p-STAT1/T-STAT1 (G) ratio on d12, d16, and d20 of pregnancy in sheep endometrial tissue. (H) The IRF9/β-actin ratio on d12, d16, and d20 of pregnancy in sheep endometrial tissue. All data are presented as the mean ± SEM, n ≥ 3; * p < 0.05; ** p < 0.01. Full article ">Figure 4
Establishment of a receptive sheep endometrial epithelial cell model for sheep. (A) Confocal microscopy was used to observe the morphology of sEECs. Red: Cy3-labeled cytokeratin 18 protein; blue, DAPI-labeled nuclei; scale bar: 20 µm. (B) Expression of ISG15 was measured under different concentrations in sEECs. (C–E) The endometrial receptivity-related genes ISG15, RSAD2, CXCL10, HOXA10, HOXA11, LIF, ESR1, ESR2, and PGR in sEECs were measured by real-time quantitative PCR. GAPDH (sheep) was used as the reference gene in all samples. sEECs: sheep endometrial epithelial cells. All data are presented as the mean ± SEM, n ≥ 3; * p < 0.05; ** p < 0.01. Full article ">Figure 5
Effect of LPS or fludarabine treatment on the expression of endometrial receptivity-related genes under hormone treatment. (A) The protein level of p-STAT1 and T-STAT1 in sEECs. (B) The secretion of PGE2 and PGF2α in sEECs. (C–E) The pro-conceptus elongation genes ISG15, RSAD2, CXCL10, adhesion molecules ITGB1/3/5, MUC1, SPP1, and receptivity markers HOXA10, HOXA11, LIF mRNA expression levels in sEECs. GAPDH (sheep) was used as the reference gene in all samples. (F) Confocal microscope images of SPP1 expression in four treatment groups. Red: Cy3-labeled SPP1 protein; blue, DAPI-labeled nuclei; scale bar: 20 µm. All data are presented as the mean ± SEM, n ≥ 3; * p < 0.05; ** p < 0.01. Full article ">Figure 6
Schematic characterization of the cellular mechanism of LPS infusion effects on endometrial receptivity in sheep during early pregnancy. LPS blocked the effect of IFN-τ in the three stages of sheep embryo implantation and impaired the endometrial receptivity, which is characterized by interfering with the secretion of prostaglandins, hindering the elongation of the conceptus, and reducing the adhesion of the embryo by inhibiting the phosphorylation of STAT1. Full article ">

20 pages, 2447 KiB

Open AccessArticle

Genes Associated with the Immune System Affected by Ionizing Radiation and Estrogen in an Experimental Breast Cancer Model

by Gloria M. Calaf, Debasish Roy, Lilian Jara, Carmen Romero and Leodan A. Crispin

Biology 2024, 13(12), 1078; https://doi.org/10.3390/biology13121078 - 20 Dec 2024

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Abstract

Breast cancer is a global health issue that, when in the metastasis stage, is characterized by the lack of estrogen receptor-α, the progesterone receptor, and human epidermal growth receptor expressions. The present study analyzed the differential gene expression related to the immune system [...] Read more.

Breast cancer is a global health issue that, when in the metastasis stage, is characterized by the lack of estrogen receptor-α, the progesterone receptor, and human epidermal growth receptor expressions. The present study analyzed the differential gene expression related to the immune system affected by ionizing radiation and estrogen in cell lines derived from an experimental breast cancer model that was previously developed; where the immortalized human breast epithelial cell line MCF-10F, a triple-negative breast cancer cell line, was exposed to low doses of high linear energy transfer α particle radiation (150 keV/μm), it subsequently grew in the presence or absence of 17β-estradiol. Results indicated that interferon-related developmental regulator 1 gene expression was affected in the estrogen-treated cell line; this interferon, as well as the Interferon-Induced Transmembrane protein 2, and the TNF alpha-induced Protein 6 gene expression levels were higher than the control in the Alpha3 cell line. Furthermore, the interferon-related developmental regulator 1, the Interferon-Induced Transmembrane protein 2, the TNF alpha-induced Protein 6, the Nuclear Factor Interleukin 3-regulated, and the Interferon-Gamma Receptor 1 showed high expression levels in the Alpha5 cell line, and the Interferon Regulatory Factor 6 was high in the Tumor2 cell line. Additionally, to further strengthen these data, publicly available datasets were analyzed. This analysis was conducted to assess the correlation between estrogen receptor alpha expression and the genes mentioned above in breast cancer patients, the differential gene expression between tumor and normal tissues, the immune infiltration level, the ER status, and the survival outcome adjusted by the clinical stage factor. It can be concluded that the genes of the interferon family and Tumor Necrosis factors can be potential therapeutic targets for breast cancer, since they are active before tumor formation as a defense of the body under radiation or estrogen effects. Full article

22 pages, 2994 KiB

Open AccessReview

Apolipoprotein-L Functions in Membrane Remodeling

by Etienne Pays

Cells 2024, 13(24), 2115; https://doi.org/10.3390/cells13242115 - 20 Dec 2024

Viewed by 253

Abstract

The mammalian Apolipoprotein-L families (APOLs) contain several isoforms of membrane-interacting proteins, some of which are involved in the control of membrane dynamics (traffic, fission and fusion). Specifically, human APOL1 and APOL3 appear to control membrane remodeling linked to pathogen infection. Through its association [...] Read more.

The mammalian Apolipoprotein-L families (APOLs) contain several isoforms of membrane-interacting proteins, some of which are involved in the control of membrane dynamics (traffic, fission and fusion). Specifically, human APOL1 and APOL3 appear to control membrane remodeling linked to pathogen infection. Through its association with Non-Muscular Myosin-2A (NM2A), APOL1 controls Golgi-derived trafficking of vesicles carrying the lipid scramblase Autophagy-9A (ATG9A). These vesicles deliver APOL3 together with phosphatidylinositol-4-kinase-B (PI4KB) and activated Stimulator of Interferon Genes (STING) to mitochondrion–endoplasmic reticulum (ER) contact sites (MERCSs) for the induction and completion of mitophagy and apoptosis. Through direct interactions with PI4KB and PI4KB activity controllers (Neuronal Calcium Sensor-1, or NCS1, Calneuron-1, or CALN1, and ADP-Ribosylation Factor-1, or ARF1), APOL3 controls PI(4)P synthesis. PI(4)P is required for different processes linked to infection-induced inflammation: (i) STING activation at the Golgi and subsequent lysosomal degradation for inflammation termination; (ii) mitochondrion fission at MERCSs for induction of mitophagy and apoptosis; and (iii) phagolysosome formation for antigen processing. In addition, APOL3 governs mitophagosome fusion with endolysosomes for mitophagy completion, and the APOL3-like murine APOL7C is involved in phagosome permeabilization linked to antigen cross-presentation in dendritic cells. Similarly, APOL3 can induce the fusion of intracellular bacterial membranes, and a role in membrane fusion can also be proposed for endothelial APOLd1 and adipocyte mAPOL6, which promote angiogenesis and adipogenesis, respectively, under inflammatory conditions. Thus, different APOL isoforms play distinct roles in membrane remodeling associated with inflammation. Full article

(This article belongs to the Special Issue Evolution, Structure, and Functions of Apolipoproteins L)

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Figure 1
Structural features of APOL1 and APOL3. The colored cylinders represent different α-helices, some of which are numbered, according to Ultsch et al. [<a href="#B5-cells-13-02115" class="html-bibr">5</a>]. HC1, HC2 = hydrophobic clusters 1, 2; LZ1, LZ2 = leucine zippers 1, 2; CRAC-1, CRAC-2 = cholesterol recognition amino acid consensuses 1, 2 (represented by red stars); TM = potential transmembrane hairpin helix; MAD = membrane-addressing domain. At acidic pH, the APOL1 TM hairpin can form weak anion pores, but pH neutralization confers high cation conductance. HC2 amino acids involved in pore pH-gating are highlighted in yellow. The boxes illustrate the folding of the N- and C-terminal APOL1 domains. In the isolated N-terminal domain, helix 5 can adopt two positions, preventing (bound) or not preventing (open) helix 4 accessibility [<a href="#B5-cells-13-02115" class="html-bibr">5</a>]. APOL1 SID represents the Smallest Interacting Domain between N- and C-terminal regions. This interaction, driven by LZ1-LZ2 pairing, is affected either by acidic conditions, as in trypanosome endosomes, or by LZ2 mutations, as in the natural G1 or G2 variants. In APOL3, LZ2 interacts with helix 5. Full article ">Figure 2
APOL2 sequence comparison with APOL1 and APOL3. Hydrophobic residues characterizing HC2 and LZ2 are highlighted in violet and pink, respectively. APOL1 CRAC-2 residues are boxed. Key APOL2 HC2 and LZ2 differences from APOL1 are in orange and red, respectively. The boxed sequence alignments show antisense pairing between helix 5 and LZ2, based on hydrophobic heptad repeats (highlighted in green). Full article ">Figure 3
WT or C-terminal variant APOL1 interactions and activities. The same symbols and colors as in <a href="#cells-13-02115-f001" class="html-fig">Figure 1</a>. In the last scheme, hypothetical cation driving to the membrane pore at neutral pH [<a href="#B14-cells-13-02115" class="html-bibr">14</a>] is symbolized by a dotted red arrow. Full article ">Figure 4
APOL3 interactions and activities. The same symbols, colors and numbers as in <a href="#cells-13-02115-f001" class="html-fig">Figure 1</a>. NCS1 and CALN1 are alternative APOL3 binders activating or inhibiting PI4KB, depending on calcium concentration. ARF1 binds to APOL3, and inflammation-mediated ARF1 activation promotes its binding to PI4KB, possibly dissociating APOL3-PI4KB interaction. VAMP8 interacts with both helices 4–5 and MAD, promoting membrane fusion. Full article ">Figure 5
Intracellular traffic of proteins involved in infection-induced changes in membrane dynamics. Detection of pathogen DNA triggers the synthesis of cyclic GMP-AMP (cGAMP), which binds to STING and disrupts STING-cholesterol interactions, allowing STING binding to PI(4)P for translocation to the Golgi. In the Golgi, STING undergoes oligomerization, which induces IFN-I inflammatory signaling. IFN-I activates ARF1, leading to STING, PI4KB and APOL3 dissociation from the Golgi in ATG9A vesicles trafficking to MERCSs, promoting membrane fission and fusion events linked to auto/mitophagy and apoptosis. This pathway allows inflammation termination due to STING autophagic degradation. Through association with NM2A and PHB2, APOL1 could direct ATG9A vesicles to MERCSs, where mitophagy is initiated. Red stars represent cholesterol interactions. The double-arrowed black dotted line represents the involvement of endolysosomes in both mitochondrion fission and autophagosome formation by ATG9A vesicles. Full article ">Figure 6
Sequence alignment between human APOL3 (above) and mouse APOL7c (below), using Clustal Omega (<a href="https://www.ebi.ac.uk/Tools/msa/clustalo/" target="_blank">https://www.ebi.ac.uk/Tools/msa/clustalo/</a> (accessed on 4 November 2024)). Insertion of clustered acidic residues, highlighted in red, characterizes the murine APOL7 family. Full article ">Figure 7
The two APOL1-like domains of APOLd1. Positively charged residues of helix 5 are highlighted in red, and the two helices of the putative transmembrane domain are highlighted in blue, with acidic residues in green. Hydrophobic residues characterizing the HC2 and LZ2 helices are highlighted in violet and pink, respectively. The amino acids involved in pH gating of the APOL1 pore are highlighted in yellow. The APOL1 residues defining CRAC-2 are boxed, and the loop sequences between the two helices of the double-stranded HC2-LZ2 helix hairpin are in bold. The boxed sequence alignment shows antisense pairing between APOLd1 helix 5 and LZ2, based on hydrophobic heptad repeats (highlighted in green). Full article ">

11 pages, 4549 KiB

Open AccessArticle

Immune Response to SARS-CoV-2 XBB.1.5 and JN.1 Variants Following XBB.1.5 Booster Vaccination in Liver Transplant Recipients

by Philippa von der Schulenburg, Georg M. N. Behrens, Markus Hoffmann, Alexandra Linke, Inga Nehlmeier, Amy Madeleine Kempf, Metodi Stankov, Marc Lütgehetmann, Jacqueline Jahnke-Triankowski, Marylyn M. Addo, Lutz Fischer, Ansgar W. Lohse, Stefan Pöhlmann, Julian Schulze zur Wiesch and Martina Sterneck

Viruses 2024, 16(12), 1942; https://doi.org/10.3390/v16121942 - 19 Dec 2024

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Abstract

Background/Objectives: The efficacy of monovalent BNT162b2 Omicron XBB.1.5 booster vaccination in liver transplant recipients (LTRs) has yet to be described, particularly regarding the immune response to emerging variants like JN.1. Methods: This study evaluated humoral and cellular immune responses in 34 liver transplant [...] Read more.

Background/Objectives: The efficacy of monovalent BNT162b2 Omicron XBB.1.5 booster vaccination in liver transplant recipients (LTRs) has yet to be described, particularly regarding the immune response to emerging variants like JN.1. Methods: This study evaluated humoral and cellular immune responses in 34 liver transplant recipients (LTRs) with varying SARS-CoV-2 immune histories before and after receiving a BNT162b2 Omicron XBB.1.5 booster vaccination. The assessment involved variant-specific serology, pseudovirus neutralization tests, and Interferon-γ release assays. Results: Participants had a median of four prior vaccinations, with 91.2% having a history of infection. Post-vaccination, significant increases in both Wuhan anti-S and Omicron-specific IgG antibodies and improved neutralization of B.1, XBB.1.5, and JN.1 pseudovirus particles were observed. Also, T-cell responses significantly increased post-vaccination. However, 17.6% of LTRs had no neutralizing antibodies against XBB.1.5 and JN.1, while 100% of healthy controls did. Shortly after vaccination, 18% of patients developed mild COVID-19. These LTRs had particularly low immune responses at baseline. Conclusions: The monovalent XBB.1.5 booster improved overall SARS-CoV-2-specific immunity. However, some LTRs still showed low or undetectable immune responses, indicating that ongoing monitoring and further booster doses are necessary in this high-risk group. Full article

(This article belongs to the Section Viral Immunology, Vaccines, and Antivirals)

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Figure 1
(A,B) Concentrations of Wuhan-Hu-1 S-specific IgG and Omicron S-specific IgG in plasma of all LTRs (n = 34) taken before and after vaccination with BNT162b2 Omicron XBB.1.5 vaccine or after vaccination and infection. (C,D) Concentrations of Wuhan-Hu-1 S-specific IgG and Omicron S-specific IgG in plasma in all LTRs with sole vaccination taken before and after vaccination with BNT162b2 Omicron XBB.1.5 vaccine (n = 28). (E,F) Concentrations of Wuhan-Hu-1 S-specific IgG and Omicron S-specific IgG in plasma in LTRs with breakthrough infection shortly after vaccination taken before vaccination with BNT162b2 Omicron XBB.1.5 vaccine and after vaccination and infection (n = 6). Paired T-test performed statistical significance (*** = p < 0.001). Red dots represent individual LTRs, grey lines connect paired data points for the same LTR. Abbreviations: IgG: immunoglobulin G; Vac: vaccination; S: spike. Full article ">Figure 2
(A–C) Analysis of neutralization capacity of antibodies before and after XBB.1.5 vaccination or vaccination and infection against B.1, XBB.1.5, and JN.1 in LTRs. Wilcoxon signed-rank test assessed statistical significance (ns = p > 0.05; ** = p < 0.01; *** = p < 0.001). For graphical reasons, plasma samples below the limit of detection were set at bottom of axis. Grey dots, green squares, and purple triangles represent the individual responses of LTRs to B.1, XBB.1.5, and JN.1, respectively. Columns indicate the geometric mean NT50 values. Abbreviations: LTRs: liver transplant recipients; GMT: geometric mean titer; Recipr: reciprocal. Full article ">Figure 3
Scattergram with individual interferon-gamma (IFN- γ) levels before and after XBB.1.5 vaccination. The Mann–Whitney Test performed statistical analysis (* = p < 0.05). The blue circles represent IFN- γ levels in individual LTRs. Solid lines represent median and interquartile range. Dotted lines represent cut-off values with interferon-gamma (IFN-γ) levels of <100 mlU/mL being negative, 100–200 mlU/mL being low positive, and >200 mlU/mL being high-positive. Abbreviations: LTRs: liver transplant recipients; IFN- γ: interferon-gamma; Vac: vaccination. Full article ">

14 pages, 1822 KiB

Open AccessReview

Functional Involvement of Signal Transducers and Activators of Transcription in the Pathogenesis of Influenza A Virus

by Shasha Liu, Feng Qiu, Rongrong Gu and Erying Xu

Int. J. Mol. Sci. 2024, 25(24), 13589; https://doi.org/10.3390/ijms252413589 - 19 Dec 2024

Viewed by 271

Abstract

Signal transducers and activators of transcription (STATs) function both as signal transducers and transcription regulators. STAT proteins are involved in the signaling pathways of cytokines and growth factors; thus, they participate in various life activities and play especially critical roles in antiviral immunity. [...] Read more.

Signal transducers and activators of transcription (STATs) function both as signal transducers and transcription regulators. STAT proteins are involved in the signaling pathways of cytokines and growth factors; thus, they participate in various life activities and play especially critical roles in antiviral immunity. Convincing evidence suggests that STATs can establish innate immune status through multiple mechanisms, efficiently eliminating pathogens. STAT1 and STAT2 can activate the antiviral status by regulating the interferon (IFN) signal. In turn, suppressor of cytokine signaling-1 (SOCS1) and SOCS3 can modulate the activation of STATs and suppress the excessive antiviral immune response. STAT3 not only regulates the IFN signal, but also transduces Interleukin-6 (IL-6) to stimulate the host antiviral response. The function of STAT4 and STAT5 is related to CD4+ T helper (Th) cells, and the specific mechanism of STAT5 remains to be studied. STAT6 mainly exerts antiviral effects by mediating IL-4 and IL-13 signaling. Here, we reviewed the recent findings regarding the critical roles of STATs in the interactions between the host and viral infection, especially influenza A virus (IAV) infection. We also discuss the molecular mechanisms underlying their functions in antiviral responses. Full article

(This article belongs to the Section Molecular Microbiology)

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Figure 1
Arrangement of chromosomal localization and structure of STAT proteins. (A) The arrangement of IFITM gene clusters in humans, chickens, and mice. Arrows indicate the direction of transcription. Exons are represented as color, and introns are in gray. (B) The structure of STAT proteins. STAT proteins are composed of the following domains: N-terminal domain (ND), the convoluted helical domain (CCD), DNA-binding structural domain (DBD), linker domain (LD), Src homology 2 (SH2) domain, and carboxy-terminal transactivating domain (TAD). The STAT proteins consist of six members: STAT1, which possesses two splicing variants (STAT1a and STAT1b), STAT2 and STAT3, which also include two splicing variants (STAT3a and STAT3b), and STAT4, STAT5α, STAT5β, and STAT6. Full article ">Figure 2
Schematic diagram for STATs against influenza A virus (IAV) infection. Host-specific pathogen recognition receptors (PRRs), such as RIG-I, MDA5, TLR3, and TLR7, recognize conserved components of IAV and then transmit signals to corresponding adaptor proteins, such as MAVS, TRIF, and MyD88. These adaptor proteins subsequently activate a series of transcription factors, such as IRF3, IRF7, and NF-κB, triggering the expression of cytokines, including IFNs. The influenza virus fusion peptide of hemagglutinin and M2 protein evokes STING pathways to induce IFNβ-expression. The interaction between cytokines and cytokine receptors (CRs) leads to JAK signal transduction, which activates transcription factor STATs. Activated STATs are transferred into the nucleus to regulate the expression of IFN-stimulated genes (ISGs). The dashed blue line represents the nuclear membrane of the cell. Full article ">

15 pages, 1685 KiB

Open AccessReview

Strategies Used by SARS-CoV-2 to Evade the Innate Immune System in an Evolutionary Perspective

by Hong Fan, Mingfu Tian, Siyu Liu, Chenglin Ye, Zhiqiang Li, Kailang Wu and Chengliang Zhu

Pathogens 2024, 13(12), 1117; https://doi.org/10.3390/pathogens13121117 - 17 Dec 2024

Viewed by 488

Abstract

By the end of 2019, the COVID-19 pandemic, resulting from the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), had diffused widely across the globe, with 770 million infected individuals and over 7 million deaths reported. In addition to its high infectivity and pathogenicity [...] Read more.

By the end of 2019, the COVID-19 pandemic, resulting from the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), had diffused widely across the globe, with 770 million infected individuals and over 7 million deaths reported. In addition to its high infectivity and pathogenicity and its rapid mutation rate, the unique capacity of SARS-CoV-2 to circumvent the immune system has also contributed to the widespread nature of this pandemic. SARS-CoV-2 elicits the onset of innate immune system activation and initiates antiviral responses once it has infected the host. While battling the host’s immune responses, SARS-CoV-2 has established many countermeasures to evade attack and clearance. As the exploration of SARS-CoV-2 continues, substantial evidence has revealed that the 29 proteins synthesized by the SARS-CoV-2 genome are integral to the viral infection process. They not only facilitate viral replication and transmission, but also assist SARS-CoV-2 in escaping the host’s immune defenses, positioning them as promising therapeutic targets that have attracted considerable attention in recent studies. This review summarizes the manner in which SARS-CoV-2 interfaces with the innate immune system, with a particular focus on the continuous evolution of SARS-CoV-2 and the implications of mutations. Full article

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17 pages, 4794 KiB

Open AccessArticle

White Tea Reduces Dyslipidemia, Inflammation, and Oxidative Stress in the Aortic Arch in a Model of Atherosclerosis Induced by Atherogenic Diet in ApoE Knockout Mice

by Merve Huner Yigit, Mehtap Atak, Ertugrul Yigit, Zehra Topal Suzan, Mehmet Kivrak and Huseyin Avni Uydu

Pharmaceuticals 2024, 17(12), 1699; https://doi.org/10.3390/ph17121699 - 17 Dec 2024

Viewed by 309

Abstract

Objective: In this study, we aimed to evaluate the potential effects of white tea (WT) in the atherosclerosis process characterized by oxidative stress, inflammation, and dyslipidemia. Methods: In our study, apolipoprotein E knockout (ApoE^−/−) mice (RRID: IMSR_JAX:002052) and C57BL/6J mice (RRID: [...] Read more.

Objective: In this study, we aimed to evaluate the potential effects of white tea (WT) in the atherosclerosis process characterized by oxidative stress, inflammation, and dyslipidemia. Methods: In our study, apolipoprotein E knockout (ApoE^−/−) mice (RRID: IMSR_JAX:002052) and C57BL/6J mice (RRID: IMSR_JAX:000664) were used. In the atherosclerosis model induced by an atherogenic diet (AD), WT was administered via oral gavage at two different concentrations. The animals were sacrificed by decapitation under anesthesia, and their serum and aortic tissues were collected. Total cholesterol (TC), triglyceride (TG), interleukin (IL)-1β, IL-6, IL-10, IL-12, tumor necrosis factor-α (TNF-α), interferon-γ, myeloperoxidase, paraoxonase-1, lipoprotein-associated phospholipase A2, oxidized low-density lipoprotein (Ox-LDL), lectin-like oxidized LDL receptor (LOX-1), a disintegrin, and metalloprotease (ADAM) 10 and 17 activities were determined via colorimetric, enzyme-linked immunoassay, and fluorometric methods. Results: WT supplementation decreased serum Ox-LDL, LOX-1, TC, and TG levels by approximately 50%. TNF- and IL-6 levels were reduced by approximately 30% in the aortic arch. In addition, ADAM10/17 enzyme activities were found to be reduced by approximately 25%. However, no change in the AD-induced fibrotic cap structure was observed in the aortic root. Conclusions: The findings indicate that white tea effectively reduced oxidative stress, inflammation, and dyslipidemia in atherosclerosis but does not affect atheroma plaque morphology. Full article

(This article belongs to the Special Issue The Role of Phytochemicals in Aging and Aging-Related Diseases)

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13 pages, 1660 KiB

Open AccessArticle

Interferon-α Inhibits NET Formation in Neutrophils Derived from Patients with Myeloproliferative Neoplasms in a Neutrophil Sub-Population-Specific Manner

by Shirly Partouche, Idan Goldberg, Erez Halperin, Bahaa Atamna, Adi Shacham-Abulafia, Saar Shapira, Aladin Samara, Ayala Gover-Proaktor, Avi Leader, Galia Spectre, Pia Raanani, Galit Granot and Ofir Wolach

Int. J. Mol. Sci. 2024, 25(24), 13473; https://doi.org/10.3390/ijms252413473 - 16 Dec 2024

Viewed by 402

Abstract

Neutrophils and neutrophil extracellular traps (NETs) contribute to thrombosis and hyperinflammation in myeloproliferative neoplasms (MPN). High-density neutrophils (HDNs) and low-density neutrophils (LDNs) have recently been characterized as distinct neutrophil sub-populations with distinct morphological and functional properties. We aim to study the kinetics of [...] Read more.

Neutrophils and neutrophil extracellular traps (NETs) contribute to thrombosis and hyperinflammation in myeloproliferative neoplasms (MPN). High-density neutrophils (HDNs) and low-density neutrophils (LDNs) have recently been characterized as distinct neutrophil sub-populations with distinct morphological and functional properties. We aim to study the kinetics of NET formation and inhibition with interferon-α (IFNα) in neutrophils derived from patients with MPN as compared to matched healthy controls. Ex vivo NET formation was assessed by neutrophil-elastase activity, neutrophil-associated nucleosomes, myeloperoxidase (MPO), and citrullinated histone H3 content. IFNα significantly inhibited NET formation in neutrophils derived from MPN patients. Neutrophil sub-population analysis demonstrated that HDNs drive the increase in NET formation as compared to LDNs in patients and in healthy controls and are effectively inhibited by IFNα, an effect that is lost in LDNs. In conclusion, we demonstrate that in MPN, HDNs drive excess NET formation and are more sensitive to IFNα inhibition. These observations uncover unique neutrophil sub-population biology and dynamics in MPN. Full article

(This article belongs to the Special Issue The Emerging Role of Neutrophils in Cancer: Molecular Aspects of Plasticity and Potential Therapeutic Targets)

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Figure 1

Figure 1
IFNα decreases NET formation in neutrophils derived from patients with MPN. (a) ELISA quantification of released nucleosomes by neutrophils from 10 MPN patients and from 3 healthy controls following activation with PMA with or w/o IFNα treatment. * p ≤ 0.03. (b) Confocal microscopy images of neutrophils from a representative PV patient and from a healthy control exposed to PMA with or w/o IFNα. Neutrophils were immunostained with anti-MPO (pink) and DAPI (blue). Magnification ×4. Scale bar = 100 μm. Full article ">Figure 2
HDNs are more susceptible to NET formation and are inhibited by IFNα. (a) Expression of CXCR4, as measured by FACS analysis, in HDNs and LDNs from a representative PV patient (upper panel) and a healthy control (lower panel). (b) Change in neutrophil elastase activity in HDNs and LDNs derived from MPN patients (n = 13) and matched healthy controls (n = 4) following stimulation with PMA for 4 h with or w/o exposure to IFNα. Blue arrows designate a decrease and red arrows designate an increase in elastase activity following exposure to IFNα. (c) Neutrophil elastase activity in MPN neutrophil-sub-population (n = 13) compared with healthy controls neutrophil-sub-population quantified by ELISA. (d) ELISA quantification of released nucleosomes by HDNs and LDNs from MPN patients (n = 12) and from healthy controls (n = 4) with or w/o treatment of IFNα. * p ≤ 0.03, ** p ≤ 0.002. Full article ">Figure 3
IFNα reduces citrullinated histone H3 burden in HDNs derived from patients with MPN. (a) Representative images of HDNs and LDNs derived from a patient with PV and a healthy control, exposed to PMA with and w/o IFNα. Neutrophils were immuno-stained with anti-histone H3 (citrulline R2 + R8 + R17, green) and with DAPI (blue). Magnification ×20. Scale bar = 100 μm. (b) Bar graphs showing the mean values of binary area fraction of citrullinated histone staining in HDNs and LDNs from patients and from healthy controls. The results are presented as the surface covered by citrullinated histone relative to the surface covered by cells (n = 6), * p ≤ 0.05. Full article ">

17 pages, 2849 KiB

Open AccessArticle

Orally Administered Lactobacilli Strains Modulate Alveolar Macrophages and Improve Protection Against Respiratory Superinfection

by Leonardo Albarracin, Stefania Dentice Maidana, Kohtaro Fukuyama, Mariano Elean, Julio Nicolás Argañaraz Aybar, Yoshihito Suda, Keita Nishiyama, Haruki Kitazawa and Julio Villena

Biomolecules 2024, 14(12), 1600; https://doi.org/10.3390/biom14121600 - 14 Dec 2024

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Abstract

Orally administered immunomodulatory lactobacilli can stimulate respiratory immunity and enhance the resistance to primary infections with bacterial and viral pathogens. However, the potential beneficial effects of immunomodulatory lactobacilli against respiratory superinfection have not been evaluated. In this work, we showed that the feeding [...] Read more.

Orally administered immunomodulatory lactobacilli can stimulate respiratory immunity and enhance the resistance to primary infections with bacterial and viral pathogens. However, the potential beneficial effects of immunomodulatory lactobacilli against respiratory superinfection have not been evaluated. In this work, we showed that the feeding of infant mice with Lacticaseibacillus rhamnosus CRL1505 or Lactiplantibacillus plantarum MPL16 strains can reduce susceptibility to the secondary pneumococcal infection produced after the activation of TLR3 in the respiratory tract or after infection with RVS. The treatment of mice with CRL1505 or MPL16 strains by the oral route improved the production of interferons in the respiratory tract, differentially modulated the balance of pro- and anti-inflammatory cytokines, reduced bacterial replication, and diminished lung damage. Additionally, we demonstrated that orally administered lactobacilli confer longstanding protection against secondary Streptococcus pneumoniae infection and that this effect would be mediated by the stimulation of trained alveolar macrophages. This work contributes to revealing the mechanisms involved in the modulation of the gut–lung axis by beneficial microbes by demonstrating that specific lactobacilli strains, through the stimulation of the common mucosal immune system, would be able to support the development of trained alveolar macrophages that would confer longstanding protection against secondary bacterial challenges produced after a primary inflammatory event in the respiratory mucosa. Full article

(This article belongs to the Section Natural and Bio-derived Molecules)

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Figure 1
Effect of Lacticaseibacillus rhamnosus CRL1505 and Lactiplantibacillus plantarum CRL1506 on respiratory superinfection. Infant mice were fed L. rhamnosus CRL1505 or L. plantarum CRL1506 for 5 days and stimulated with poly(I:C) on days 7, 8, and 9 (A) or challenged with respiratory syncytial virus (RSV) on day 7 (B) via the nasal route. Five days later, mice were nasally infected with Streptococcus pneumoniae. The pneumococcal cell counts in lung and blood, the concentration of BAL albumin, and the activity of BAL LDH were determined 2 days after S. pneumoniae infection. The results are shown as mean ± SD. Significant differences are shown compared to the control group at p < 0.05 (*) or p < 0.01 (**). Full article ">Figure 2
Effect of lactobacilli on respiratory superinfection. Infant mice were fed L. rhamnosus CRL1505, IBL027, CRL489, L. plantarum CRL1506, or MPL16 for 5 days and stimulated with poly(I:C) on days 7, 8, and 9 via the nasal route. Five days later, mice were nasally infected with Streptococcus pneumoniae. The pneumococcal cell counts in lung and blood, the concentration of BAL albumin, the activity of BAL LDH (A), and the concentrations of BAL IFN-β, IFN-γ, and IL-10 (B) were determined 2 days after S. pneumoniae infection. The results are shown as mean ± SD. Significant differences are shown compared to the control group at p < 0.05 (*) or p < 0.01 (**). Full article ">Figure 3
Effect of lactobacilli on AMphs cytokine production. Infant mice were fed L. rhamnosus CRL1505, IBL027, CRL489, L. plantarum CRL1506, or MPL16 for 5 days and stimulated with poly(I:C) on days 7, 8, and 9 via the nasal route. Five days later, AMphs were isolated from BAL samples, cultured, and in vitro challenged with Streptococcus pneumoniae. The concentrations of IFN-β, IFN-γ, IL-6, IL-10, IL-12, and IL-27 were evaluated on AMph supernatants after 24 h. (A) Cytokine production of AMphs from L. rhamnosus CRL1505 and L. plantarum MPL16. The results are shown as mean ± SD. Significant differences were shown compared to the respective basal levels without pneumococcal challenge at p < 0.05 (†). Significant differences were shown compared to the control group at p < 0.05 (*). (B) Heatmap shows the variations in the concentration of cytokines of all experimental groups in relation to the control. Full article ">Figure 4
Effect of lactobacilli on AMphs MHC-II expression. Infant mice were fed L. rhamnosus CRL1505, IBL027, CRL489, L. plantarum CRL1506, or MPL16 for 5 days and stimulated with poly(I:C) on days 7, 8, and 9 via the nasal route. Five days later, mice were nasally infected with Streptococcus pneumoniae. The numbers of CD45+CD11c+SiglecF+ and CD11c+SiglecF+MHC-II+ cells in BAL were determined on the last day of lactobacilli treatment (basal) and 2 days after poly(I:C) stimulation and S. pneumoniae infection. The results are shown as mean ± SD. Significant differences are shown compared to the control group at p < 0.05 (*). Full article ">Figure 5
Effect of lactobacilli on respiratory superinfection. Infant mice were fed L. rhamnosus CRL1505, IBL027, CRL489, L. plantarum CRL1506, or MPL16 for 5 days and stimulated with poly(I:C) on days 7, 8, and 9 via the nasal route. For the evaluation of long-term protection, 5, 10, 15, or 20 days after the last administration of poly(I:C), mice were nasally infected with Streptococcus pneumoniae. The pneumococcal cell counts in lung and blood, the concentration of BAL albumin, the activity of BAL LDH (A), and the concentrations of BAL IFN-β, IFN-γ and IL-10 (B) were determined 2 days after S. pneumoniae infection. The results are shown as mean ± SD. Significant differences are shown compared to the control group at p < 0.05 (*) or p < 0.01 (**). (C) Heatmap shows the variations in the parameters evaluated for all experimental groups in relation to the controls. Full article ">Figure 6
Effect of lactobacilli on respiratory superinfection. Infant mice were fed L. rhamnosus CRL1505, IBL027, CRL489, L. plantarum CRL1506, or MPL16 for 5 days and stimulated with poly(I:C) on days 7, 8, and 9 via the nasal route. Twenty days after the last administration of poly(I:C), mice were nasally infected with Streptococcus pneumoniae. (A) The number of macrophages and neutrophils and the concentrations of TNF-α and CCL2 in BAL samples were determined 3, 6, 12, 24, 32, 48, and 54 h after S. pneumoniae infection. The results are shown as mean ± SD. Significant differences are shown compared to the control group at p < 0.05 (*) (B) Heatmap shows the variations in the parameters evaluated at hours 24 and 48 of all experimental groups in relation to the control. Full article ">

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