For better preparing future epidemic/pandemic, important lessons can be learned from how different parts of China responded to the early COVID-19 epidemic. In this study, we comparatively analyzed the effectiveness and investigated the mechanistic insight of two highly representative cities of China in containing this epidemic by mathematical modeling. Epidemiological data of Wuhan and Wenzhou was collected from local health commission, media reports and scientific literature. We used a deterministic, compartmental SEIR model to simulate the epidemic. Specific control measures were integrated into the model, and the model was calibrated to the recorded number of hospitalized cases. In the epicenter Wuhan, the estimated number of unisolated or unidentified cases approached 5000 before the date of city closure. By implementing quarantine, a 40% reduction of within-population contact was achieved initially, and continuously increased up to 70%. The expansion of emergency units has finally reduced the mean duration from disease onset to hospital admission from 10 to 3.2 days. In contrast, Wenzhou is characterized as an emerging region with large number of primarily imported cases. Quick response effectively reduced the duration from onset to hospital admission from 20 to 6 days. This resulted in reduction of R values from initial 2.3 to 1.6, then to 1.1. A 40% reduction of contact through within-population quarantine further decreased R values until below 1 (0.5; 95% CI: 0.4–0.65). Quarantine contributes to 37% and reduction of duration from onset to hospital admission accounts for 63% to the effectiveness in Wenzhou. In Wuhan, these two strategies contribute to 54% and 46%, respectively. Thus, control measures combining reduction of duration from disease onset to hospital admission and within-population quarantine are effective for both epicenters and settings primarily with imported cases.
Abstract Hydroxyanthraquinones and anthraquinone glucoside derivatives are always considered as the active antibacterial components. In the present text, a comprehensive comparison and analysis of these compounds were performed for their structure characteristics and antibacterial effect by applying quantum chemical calculations, atoms in molecules theory and molecular docking procedure. The molecular geometric configuration, electrostatic potential, the frontier orbital energies and topological properties were analyzed. Once glucose ring is introduced into the hydroxyanthraquinone rings, almost all of the positive molecular potentials are distributed among the hydroxyl hydrogen atoms of the glucose rings. The anthraquinone glucoside compounds have generally higher intermolecular binding energies than the corresponding aglycones due to the strong interaction between the glucose rings and the surrounding amino acids. Once glucoside ring is introduced into the emodin, low electron density ρ(r) and positive Laplacian value of the O-H bond are the evidences of the highly polarized and covalently decreased bonding interactions. The type of carboxyl, hydroxyl, hydroxylmethyl groups on phenyl ring and the substituent glucose rings are important to the interactions with the topoisomerase type II enzyme DNA gyrase B.
Abstract Background and Aims HEV infection is the most common cause of liver inflammation, but the pathogenic mechanisms remain largely unclear. We aim to explore whether HEV infection activates inflammasomes, crosstalk with antiviral interferon response, and the potential of therapeutic targeting. Approach and Results We measured IL‐1β secretion, the hallmark of inflammasome activation, in serum of HEV‐infected patients and rabbits, and in cultured macrophage cell lines and primary monocyte‐derived macrophages. We found that genotypes 3 and 4 HEV infection in rabbits elevated IL‐1β production. A profound increase of IL‐1β secretion was further observed in HEV‐infected patients (1,733 ± 1,234 pg/mL; n = 70) compared to healthy persons (731 ± 701 pg/mL; n = 70). Given that macrophages are the drivers of inflammatory response, we found that inoculation with infectious HEV particles robustly triggered NOD‐like receptor family pyrin domain‐containing 3 (NLRP3) inflammasome activation in primary macrophages and macrophage cell lines. We further revealed that the ORF2 capsid protein and the formed integral viral particles are responsible for activating inflammasome response. We also identified NF‐κB signaling activation as a key upstream event of HEV‐induced NLRP3 inflammasome response. Interestingly, inflammasome activation antagonizes interferon response to facilitate viral replication in macrophages. Pharmacological inhibitors and clinically used steroids can effectively target inflammasome activation. Combining steroids with ribavirin simultaneously inhibits HEV and inflammasome response without cross‐interference. Conclusions HEV infection strongly activates NLRP3 inflammasome activation in macrophages, which regulates host innate defense and pathogenesis. Therapeutic targeting of NLRP3, in particular when combined with antiviral agents, represents a viable option for treating severe HEV infection.
Exposure to hepatitis E virus (HEV) bears a high risk of developing chronic infection in immunocompromised patients, including organ transplant recipients and cancer patients. We aim to identify effective anti-HEV therapies through screening and repurposing safe-in-human broad-spectrum antiviral agents. In this study, a safe-in-human broad-spectrum antiviral drug library comprising of 94 agents was used. Upon screening, we identified gemcitabine, a widely used anti-cancer drug, as a potent inhibitor of HEV replication. The antiviral effect was confirmed in a range of cell culture models with genotype 1 and 3 HEV strains. As a cytidine analog, exogenous supplementation of pyrimidine nucleosides effectively reversed the antiviral activity of gemcitabine, but the level of pyrimidine nucleosides per se does not affect HEV replication. Surprisingly, similar to interferon-alpha (IFNα) treatment, gemcitabine activates STAT1 phosphorylation. This subsequently triggers activation of interferon-sensitive response element (ISRE) and transcription of interferon-stimulated genes (ISGs). Cytidine or uridine effectively inhibits gemcitabine-induced activation of ISRE and ISGs. As expected, JAK inhibitor 1 blocked IFNα, but not gemcitabine-induced STAT1 phosphorylation, ISRE/ISG activation, and anti-HEV activity. These effects of gemcitabine were completely lost in STAT1 knockout cells. In summary, gemcitabine potently inhibits HEV replication by triggering interferon-like response through STAT1 phosphorylation but independent of Janus kinases. This represents a non-canonical antiviral mechanism, which utilizes the innate defense machinery that is distinct from the classical interferon response. These results support repurposing gemcitabine for treating hepatitis E, especially for HEV-infected cancer patients, leading to dual anti-cancer and antiviral effects.
Human coronavirus NL63 (HCoV-NL63) mainly affects young children and immunocompromised patients, causing morbidity and mortality in a subset of patients. Since no specific treatment is available, this study aims to explore the anti-SARS-CoV-2 agents including favipiravir and remdesivir for treating HCoV-NL63 infection. We first successfully modelled the 3D structure of HCoV-NL63 RNA-dependent RNA polymerase (RdRp) based on the experimentally solved SARS-CoV-2 RdRp structure. Molecular docking indicated that favipiravir has similar binding affinities to SARS-CoV-2 and HCoV-NL63 RdRp with LibDock scores of 75 and 74, respectively. The LibDock scores of remdesivir to SARS-CoV-2 and HCoV-NL63 were 135 and 151, suggesting that remdesivir may have a higher affinity to HCoV-NL63 compared to SARS-CoV-2 RdRp. In cell culture models infected with HCoV-NL63, both favipiravir and remdesivir significantly inhibited viral replication and production of infectious viruses. Overall, remdesivir compared to favipiravir is more potent in inhibiting HCoV-NL63 in cell culture. Importantly, there is no evidence of resistance development upon long-term exposure to remdesivir. Furthermore, combining favipiravir or remdesivir with the clinically used antiviral cytokine interferon-alpha resulted in synergistic effects. These findings provided a proof-of-concept that anti-SARS-CoV-2 drugs, in particular remdesivir, have the potential to be repurposed for treating HCoV-NL63 infection.
The nonstructural protein 5A (NS5A) of the bovine viral diarrhea virus (BVDV) is a monotopic membrane protein. This protein can anchor to the cell membrane by an in-plane amphipathic ⍺-helix, which participates in the viral replication complex. In this study, the effects of synonymous codon usage pattern of NS5A and the overall transfer RNA (tRNA) abundance in cells on the formation of the in-plane membrane anchor of NS5A were analyzed, based on NS5A coding sequences of different BVDV genotypes. BVDV NS5A coding sequences represent the most potential for BVDV genotyping. Moreover, the nucleotide usage of BVDV NS5A dominates the genotype-specific pattern of synonymous codon usage. There is an obvious relationship between synonymous codon usage bias and the spatial conformation of the in-plane membrane anchor. Furthermore, the overall tRNA abundance profiling displays that codon positions with a high level of tRNA abundance are more than ones with a low level of tRNA abundance in the in-plane membrane anchor, implying that high translation speed probably acts on the spatial conformation of in-plane membrane anchor of BVDV NS5A. These results give a new opinion on the effect of codon usage bias in the formation of the in-plane membrane anchor of BVDV NS5A.
The COVID-19 pandemic is spreading at unprecedented pace among the Middle East and neighboring countries. This region is geographically, economically, politically, culturally and religiously a very sensitive area, which impose unique challenges for effective control of this epidemic. These challenges include compromised healthcare systems, prolonged regional conflicts and humanitarian crises, suboptimal levels of transparency and cooperation, and frequent religious gatherings. These factors are interrelated and collectively determine the response to the pandemic in this region. Here, we in-depth emphasize these challenges and take a glimpse of possible solutions towards mitigating the spread of COVID-19.
The BTB-ZF (broad-complex, tramtrack and bric-à-brac–zinc finger) proteins play essential roles in the development of the immune system.1 Transcriptional repressor Zbtb1is one of the BTB-ZF members essential for lymphocyte development2, 3 and NKp46+ ROR-gamma-T+ innate lymphoid cell (ILC3) development.4 Although the mechanisms by which Zbtb1 promote lymphoid development have been investigated,5, 6 many questions are still unsolved, especially for T-cell development. T cells require IL-7 signalling throughout their life, including maturation, differentiation and survival in peripheral lymphoid tissues.7 Both B and T cells developmental block were seen in the mice deficient for IL-7 receptor α-chain (IL-7Rα).8 Interestingly, enforced expression of Bcl-2 restored T-cell development but not B cell in IL-7Rα−/− mice,9, 10 however, Bcl-2 overexpression in the ScanT (Zbtb1 mutant) mice restored B cell but only early T-cell development.5 In this study, the interplay between Zbtb1 and IL-7Rα was dissected during T-cell development. At first we decided to evaluate the regulation of Zbtb1 expression by IL-7Rα signalling during T-cell development in vitro. We chose D1 cell line as a simplified research model, which was an IL-7 (interleukin-7)-dependent thymic cell line derived from a p53−/− mouse. According to the surface maker expression by flow cytometry, D1 is a DN1(double negative, stage 1)-like cell line, which is CD44+CD25−IL-7Rα+(Figure S1A). D1 cells were maintained in complete medium with 10 ng/mL IL-7. To test the impact of IL-7Rα signalling on Zbtb1 expression, D1 cells were starved overnight by IL-7 deprivation, and then re-stimulated with 10 ng/mL IL-7. The Zbtb1 mRNA level reached the peak after IL-7 deprivation overnight. However, the Zbtb1 transcripts down-regulated after IL-7 re-stimulation, with the lowest level at 4 hours adding IL-7 (Figure 1A). In order to investigate the effect of IL-7Rα signalling on Zbtb1 expression in vivo, we utilized the mice deficient for IL-7Rα and IL-7Rα−/− compound with IL-7Rα transgene under the control of human CD2 promoter (T cell-specific). We sorted double positive (DP), CD4 single positive (SP) and CD8SP thymocytes from wild-type C57BL/6 and IL-7Rα mutant mice mentioned above (Figure 1B), then performed RT-qPCR assay. We found Zbtb1 expression level were elevated in all cell types in IL-7Rα−/− compared to wild-type. However, Zbtb1 transcripts were down-regulated in all cell types of mice with IL-7Rα−/− compound with IL-7Rα transgene. These data suggest that the transcription of Zbtb1 can be negatively regulated by IL-7Rα signalling. Next we investigated the effect of Zbtb1 on IL-7Rα expression. We transduced the D1 cells with either retroviral vector Mir-CTR or Zbtb1-overexpressing retrovirus, and sorted the GFP+ cells to establish the stable cell line (Figure 1D). The Zbtb1 overexpression in Mir30-P2A-Zbtb1 stable cell line was confirmed by RT-qPCR (Figure 1E). We deprived IL-7 from culture medium of D1 cells overnight, re-stimulated with different concentration of IL-7, and then analysed surface IL-7Rα level at different time post-stimulation. We found that Zbtb1 overexpression can down-regulate IL-7Rα under sub-optimal IL-7 concentration (1 ng/mL) (Figure 1F,G). In order to address the impact of Zbtb1 on IL-7Rα during T-cell development in vivo, we gated different sub-population in thymocytes (Figure S1B). Consistent with previous report, IL-7Rα level in wild-type thymus up-regulated from ETP to DN2a stage, gradually reduced to undetectable level in DP stage, then recovered in SP stage (Figure S1C). Interestingly, we found that ScanT thymocytes expressed higher level of IL-7Rα compared to wild-type thymocytes during T-cell development, including ETP, intermediate DN1 to DN2 stage (intDN1-DN2) and DN2 stage (Figure 1H). The cell size of ETP, intDN1-DN2 and DN2 thymocytes seemed to be smaller in ScanT mice, indicating that they are less proliferative than that of wild-type (Figure S1D). The IL-7Rα level of TCRβhi thymocytes in ScanT mice was also higher than that of their wild-type littermates, although the percentage of TCRβhi thymocytes in ScanT mice was severely reduced (Figure 1I). Furthermore, we generated Zbtb1 transgenic mice in which expression of Zbtb1 was driven by T-cell specific hCD2 promoter. Among four transgenic mouse line generated, only D2 line successfully overexpressed Zbtb1 in CD4 T cells compared to C57BL/6 in both mRNA and protein level (Figure 1J). The total number of thymocytes was comparable between wild-type and hCD2-Zbtb1 transgenic mice. However, the IL-7Rα level in CD4SP and CD8SP thymocytes of transgenic mice was lower than that of wild-type mice (Figure 1K). In the spleen, both CD4SP and CD8SP cells from transgenic mice expressed lower level of IL-7Rα than that of wild-type mice. Surprisingly, the number of CD8SP spleenocytes in hCD2-Zbtb1 transgenic mice was greatly reduced, while the number of CD4SP spleenocytes was comparable (Figure 1L). The reduction in the number of CD8SP spleenocytes in ScanT mice was not due to unregulated expression of Bcl2, although CD8SP spleenocytes had lower level of IL-7Rα in ScanT mice compared to wild-type counterpart (Figure S1E). Altogether, our results suggest that Zbtb1 and IL-7Rα signalling can regulate each other during T-cell development. IL-7Rα signalling negatively regulate Zbtb1, and vice versa. Detailed molecular mechanisms by which Zbtb1 regulate IL-7Rα expression in T cells are still under investigation. This work was supported by the National Natural Science Foundation of China (31700763, 81760287), The Science and Technology Fund Program of Gansu Province for Young Investigators (17JR5RA277), Gansu Provincial Science and Technology Grant (1504WKCA094), Innovative Research Team in University (IRT_17R88), Ministry of Science and Technology Assistance Project Grant (KY201501005), The State Key Laboratory of Veterinary Etiological Biology, Lanzhou Veterinary Research Institute, Chinese Academy of Agricultural Sciences (SKLVEB2016KFKT013), The Open Fund of Ministry of Education Key Laboratory of Molecular Microbiology and Technology, Nankai University, The Central Universities deriving from the Northwest Minzu University (31920170165), The Fundamental Research Funds for the Central Universities (zyz2012070) and The Introduction of Talent Research Projects from the Northwest Minzu University (xbmuyjrcs201611). We thank Dr. Scott K. Durum for providing D1 cell line, Dr. Jung-Hyun Park for providing the IL-7Rα−/− mice, IL-7Rα−/− compound with IL-7Rα transgene mice, Dr. Alfred Singer for critical suggestions and Dr. S. Sharrow, L. Granger and T. Adams for flow cytometry and cell sorting. The authors confirm that there are no conflicts of interest. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.
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