The rapidly emerging human health crisis associated with the Zika virus (ZIKV) epidemic and its link to severe complications highlights the growing need to identify the mechanisms by which ZIKV accesses hosts. Interferon response protects host cells against viral infection, while the cellular factors that mediate this defense are the products of interferon-stimulated genes (ISGs). Although hundreds of ISGs have been identified, only a few have been characterized for their antiviral potential, target specificity and mechanisms of action. In this work, we focused our investigation on the possible antiviral effect of a novel ISG, C19orf66 in response to ZIKV infection and the associated mechanisms. We found that ZIKV infection could induce C19orf66 expression in ZIKV-permissive cells, and such an overexpression of C19orf66 remarkably suppressed ZIKV replication. Conversely, the depletion of C19orf66 led to a significant increase in viral replication. Furthermore, C19orf66 was found to interact and co-localize with ZIKV nonstructural protein 3 (NS3), thus inducing NS3 degradation via a lysosome-dependent pathway. Taken together, this study identified C19orf66 as a novel ISG that exerts antiviral effects against ZIKV by specifically degrading a viral nonstructural protein. These findings uncovered an intriguing mechanism of C19orf66 that targeting NS3 protein of ZIKV, providing clues for understanding the actions of innate immunity, and affording the possible availability of new drug targets that can be used for therapeutic intervention. "Guangdong Te Zhi program" youth science and technology talent of project (2015TQ01R281); Guangdong MEDP Fund Author summary ZIKV represents a serious threat to global health with particular relevance to microcephaly and other congenital abnormalities in newborns, and Guillain-Barré syndrome, meningoencephalitis, multi-organ failure in adults. Despite the global health threat of Zika virus infection, there is currently no vaccine or effective antiviral therapy available for the disease. As widely recognized, interferon signaling is key to establishing a strong antiviral state in host cells, mainly mediated through the anti-viral effects of numerous interferon-stimulated genes (ISGs). This work described our novel finding of the antiviral effect of a novel ISG, C19orf66, and its underlying mechanisms. We identified C19orf66 as a novel ISG that exerts antiviral effects against ZIKV by specifically interacting and colocalizing with the ZIKV nonstructural (NS) protein NS3, which inducing NS3 degradation via a lysosome-dependent pathway. Thus, this work broadens the understanding of the pivotal roles of C19orf66 in the interaction between the host and ZIKV, which might further provide a rational basis for developing novel anti-ZIKV strategies. PLOS NEGLECTED TROPICAL DISEASESC19orf66 suppresses ZIKV replication by target viral NS3 PLOS Neglected Tropical Diseases | https://doi.org/10.
Recent evidence indicates that miR-17–92 family might be an essential prognostic biomarker for human cancers. However, results are still inconsistent. We therefore performed a meta-analysis to evaluate the predictive role of miR-17–92 family in human cancer prognosis. We searched literatures published before March 31th, 2017 inPubMed, Cochrane and Embase databases. Twenty six studies were included in our analyses. The overall hazard ratios (HRs) showed that high expression level of miR-17-92 family was a predictor of poor overall survival (OS): adjusted HRs = 1.71, 95% confidence intervals (CIs): 1.39–2.11, p < 0.00001, and poor disease-free survival (DFS): adjusted HRs = 2.29, 95% CIs: 1.41–3.72, p = 0.0008. However, no association between miR-17-92 family expression and cancer progress-free survival (PFS) was found (p > 0.05). Subgroup analyses showed that high expression of miR-17-92 family was associated with poor OS (adjusted HRs = 1.89, 95% CIs: 1.43–2.49, p < 0.00001) and DFS (adjusted HRs = 2.83, 95% CIs: 1.59–5.04, p = 0.0003) among the Asian, and no association was found for the Caucasian (p > 0.05). Besides, the HRs of miR-17-92 family high expression in tissue and serum samples was 1.68 (1.35–2.09) and 2.20 (1.08–4.46) for OS, and 1.73 (0.80–3.74) and 3.37 (2.25–5.02) for DFS. It also found that high expression of miR-17-92 family predicted a poor OS in breast cancer, esophageal squamous cell carcinoma, lymphoma and other cancers. Findings suggest that miR-17-92 family can be an effective predictor for prognosis prediction in cancer patients.
Background Centipeda minima (L.) A. Br. et Aschers, known as Ebushicao (EBSC) in Chinese, has long been used in traditional Chinese medicine for dispelling wind, clearing orifices, detoxification and swelling. Although the traditional use of EBSC involves the whole plant, during harvesting and processing, separation of the stems, leaves, flowers and roots often occurs. However, there are few studies on its medicinal parts. Objective A strategy combining high performance liquid chromatography (HPLC) fingerprinting and multivariate classification techniques are here proposed for the comparison of roots, stems, leaves, and flowers of EBSC. Method The roots, stems, leaves, and flowers of EBSC samples were analyzed and compared based on HPLC fingerprints combined with chemometrics, including hierarchical cluster analysis (HCA), principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and back propagation artificial neural network (BP-ANN). Chemical markers were screened using PLS-DA, and the contents of representative ingredients were determined by an HPLC method. Results The HCA and PCA provided clear discrimination of roots, stems, leaves and flowers. Moreover, the PLS-DA model and BP-ANN were established to verify the classification results and showed a greater ability to predict new samples. Four representative chemical markers were screened out, and the content of these markers in flowers and leaves was higher than that in stems and roots, and the difference was significant. Conclusion Combining HPLC fingerprinting and multi-component chemical pattern recognition technology can be used to distinguish different parts of EBSC. The results indicated that brevilin A, quercetin, rutin and chlorogenic acid, the important active components of EBSC, were mainly present in the leaves and flowers. This is of great significance for the differentiation and identification of the different medicinal parts of EBSC, as well as for the effectiveness of drug usage in clinical practice.
Introduction: The characteristics of chemical components or groups of chemical components in traditional Chinese medicines (TCMs) determine their clinical efficacy.Quality markers (Q-markers) is of great significance for standardizing the quality control system of TCM. Objectives:We aimed to develop a new strategy to discover potential Q-markers of TCM by integrating chemometrics, network pharmacology, and molecular docking, using Centipeda minima (also known as ebushicao [EBSC]) as an example.Materials and methods: First, fingerprints of different batches of EBSC and its counterfeit Arenaria oreophila (also known as zaozhui [ZZ]) were established. Second, chemometric analysis was conducted to determine the influence of varying authenticity/ batches of herbs on quality and the chemical markers were screened out. Third, network pharmacology and molecular docking simulations were used to verify the relationship between active ingredients and targets. Lastly, potential Q-markers were selected based on TCM theory. Results:The chemical profiles of EBSC and ZZ were investigated. It was found that different batches of EBSC have differences in chemical composition. Based on our chemometric analysis, chlorogenic acid, rutin, isochlorogenic acid A, quercetin, arnicolide D, and brevilin A were selected as candidate active ingredients. ATIL6, EGFR, CASP3, MYC, HIF1A, and VEGFA were the main targets. Molecular docking was used to verify the binding ability. Based on the concept of Q-marker, arnicolide D and brevilin A were identified as potential Q-markers for EBSC.Conclusions: Our strategy could be used as a practical approach to discover Qmarkers of TCM to evaluate overall chemical consistency.
Physalis alkekengi L. var. franchetii (PALF) is a traditional Chinese medicine, which is well known for its antimicrobial, anti-inflammatory, antipyretic, and expectorant properties. Its fruits and fruiting calyxes are used as dietary supplements and traditional herbs in China. However, the quality of calyxes is uneven, and it is prone to getting moldy or moth-eaten during storage. High-performance liquid chromatography (HPLC) fingerprints and multivariate chemometric methods were combined to evaluate quality, and three representative compounds were chosen as the quality markers (Q-markers). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) provided a clear discrimination of PALF samples. Through further verification by partial least squares discriminant analysis (PLS-DA), backpropagation artificial neural network (BP-ANN), machine learning, and combination with the determination of the content, biology, and pharmacology effect judgment, galuteolin, rutin, and physalin O could be used as Q-markers that their contents affect the quality of PALF grade evaluation. A simple method was established to rapidly assess the quality of PALF that is important for its clinical application and storage and provide a reference for evaluating the quality of materials used in Chinese medicine.
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