Neuroprotective Effects of San-Huang-Xie-Xin-Tang in the MPP+/MPTP Models of Parkinson's Disease In Vitro and In Vivo

San-Huang-Xie-Xin-Tang (SHXT), composed of Coptidis rhizoma, Scutellariae radix, and Rhei rhizoma, is a traditional Chinese medicine used for complementary and alternative therapy of cardiovascular and neurodegenerative diseases via its anti-inflammatory and antioxidative effects. The aim of this study is to investigate the protective effects of SHXT in the 1–methyl–4–phenylpyridinium (MPP+)/1–methyl–4–phenyl–1,2,3,6–tetrahydropyridine (MPTP) models of Parkinson's disease. Rat primary mesencephalic neurons and mouse Parkinson disease model were used in this study. Oxidative stress was induced by MPP+ in vitro and MPTP in vivo. In MPP+-treated mesencephalic neuron cultures, SHXT significantly increased the numbers of TH-positive neurons. SHXT reduced apoptotic signals (cytochrome and caspase) and apoptotic death. MPP+-induced gp91phox activation and ROS production were attenuated by SHXT. In addition, SHXT increased the levels of GSH and SOD in MPP+-treated neurons. In MPTP animal model, SHXT markedly increased TH-positive neurons in the substantia nigra pars compacta (SNpc) and improved motor activity of mice. In conclusion, the present results reveal the evidence that SHXT possesses beneficial protection against MPTP-induced neurotoxicity in this model of Parkinson's disease via its antioxidative and antiapoptotic effects. SHXT might be a potentially alternative and complementary medicine for neuroprotection

Protein subcellular localization prediction based on compartment-specific features and structure conservation

BACKGROUND: Protein subcellular localization is crucial for genome annotation, protein function prediction, and drug discovery. Determination of subcellular localization using experimental approaches is time-consuming; thus, computational approaches become highly desirable. Extensive studies of localization prediction have led to the development of several methods including composition-based and homology-based methods. However, their performance might be significantly degraded if homologous sequences are not detected. Moreover, methods that integrate various features could suffer from the problem of low coverage in high-throughput proteomic analyses due to the lack of information to characterize unknown proteins. RESULTS: We propose a hybrid prediction method for Gram-negative bacteria that combines a one-versus-one support vector machines (SVM) model and a structural homology approach. The SVM model comprises a number of binary classifiers, in which biological features derived from Gram-negative bacteria translocation pathways are incorporated. In the structural homology approach, we employ secondary structure alignment for structural similarity comparison and assign the known localization of the top-ranked protein as the predicted localization of a query protein. The hybrid method achieves overall accuracy of 93.7% and 93.2% using ten-fold cross-validation on the benchmark data sets. In the assessment of the evaluation data sets, our method also attains accurate prediction accuracy of 84.0%, especially when testing on sequences with a low level of homology to the training data. A three-way data split procedure is also incorporated to prevent overestimation of the predictive performance. In addition, we show that the prediction accuracy should be approximately 85% for non-redundant data sets of sequence identity less than 30%. CONCLUSION: Our results demonstrate that biological features derived from Gram-negative bacteria translocation pathways yield a significant improvement. The biological features are interpretable and can be applied in advanced analyses and experimental designs. Moreover, the overall accuracy of combining the structural homology approach is further improved, which suggests that structural conservation could be a useful indicator for inferring localization in addition to sequence homology. The proposed method can be used in large-scale analyses of proteomes

Expression and immunogenicity of secreted forms of bovine ephemeral fever virus glycoproteins applied to subunit vaccine development

This study was support by grants from the Taiwan Ministry of Science and Technology (MOST-106-2911-I-020-501; MOST-107-2313-B-020-011-MY3) and the UK Biotechnology and Biological Sciences Research Council (BB/P025080/1).Aims  Vaccines for bovine ephemeral fever virus (BEFV) are available but are difficult to produce, expensive, or suffer from genetic instability. Therefore, we designed constructs encoding C-terminally truncated forms (transmembrane anchoring region deleted) of glycoproteins G and GNS such that they were secreted from the cell into the media to achieve high-level antigen expression, correct glycosylation pattern, and enable further simple purification with the V5 epitope tag. Methods and Results  In this study, synthetic biology was employed to create membrane-bound and secreted forms of G and GNS glycoprotein. Mammalian cell culture was employed as an antigen expression platform, and the secreted forms of G and GNS protein were easily purified from media by using a highly effective, single-step method. The V5 epitope tag was genetically fused to the C-termini of the proteins, enabling detection of the antigen through immunoblotting and immunomicroscopy. Our data demonstrated that the C-terminally truncated form of the G glycoprotein was efficiently secreted from cells into the cell media. Moreover, the immunogenicity was confirmed in mice test. Conclusions  The immuno-dot blots showed that the truncated G glycoprotein was present in the total cell extract, and was clearly secreted into the media, consistent with the western blotting data and live-cell images. Our strategy presented the expression of secreted, epitope-tagged, forms of the BEFV glycoproteins such that appropriately glycosylated forms of BEFV G protein was secreted from the BHK-21 cells. This indicates that high-level expression of secreted G glycoprotein is a feasible strategy for large-scale production of vaccines and improving vaccine efficacy. Significance and Impact of the Study The antigen expression strategy designed in this study can produce high-quality recombinant protein and reduce the amount of antigen used in the vaccine.PostprintPeer reviewe

High expression FUT1 and B3GALT5 is an independent predictor of postoperative recurrence and survival in hepatocellular carcinoma.

Cancer may arise from dedifferentiation of mature cells or maturation-arrested stem cells. Previously we reported that definitive endoderm from which liver was derived, expressed Globo H, SSEA-3 and SSEA-4. In this study, we examined the expression of their biosynthetic enzymes, FUT1, FUT2, B3GALT5 and ST3GAL2, in 135 hepatocellular carcinoma (HCC) tissues by qRT-PCR. High expression of either FUT1 or B3GALT5 was significantly associated with advanced stages and poor outcome. Kaplan Meier survival analysis showed significantly shorter relapse-free survival (RFS) for those with high expression of either FUT1 or B3GALT5 (P = 0.024 and 0.001, respectively) and shorter overall survival (OS) for those with high expression of B3GALT5 (P = 0.017). Combination of FUT1 and B3GALT5 revealed that high expression of both genes had poorer RFS and OS than the others (P < 0.001). Moreover, multivariable Cox regression analysis identified the combination of B3GALT5 and FUT1 as an independent predictor for RFS (HR: 2.370, 95% CI: 1.505-3.731, P < 0.001) and OS (HR: 2.153, 95% CI: 1.188-3.902, P = 0.012) in HCC. In addition, the presence of Globo H, SSEA-3 and SSEA-4 in some HCC tissues and their absence in normal liver was established by immunohistochemistry staining and mass spectrometric analysis