HCV core protein subcellular localization: Analysis by confocal and electron microscopy and correlation with the cell cycle . *Liver cancer and molecular virology, Inserm U370, Paris, France. IDepartment of Virology II. National Institute of Health, Tokyo, Japan. $Laboratoire de Biologie et Ultrastructure du Noyau, CNRS UPR 272, Villejuif, France

Hepatology ◽  
1995 ◽  
Vol 22 (4) ◽  
pp. A332 ◽  
Keyword(s):  
Electron Microscopy ◽  
Cell Cycle ◽  
Liver Cancer ◽  
Subcellular Localization ◽  
Core Protein ◽  
Protein Subcellular Localization ◽  
Molecular Virology ◽  
Hcv Core Protein ◽  
Localization Analysis ◽  
Confocal And Electron Microscopy

scholarly journals Molecular basis of subcellular localization of HCV core protein

2008 ◽  
Vol 16 (4) ◽  
pp. 221-224 ◽  
Author(s):  
T. Suzuki ◽  
Y. Matsuura ◽  
T. Harada ◽  
R. Suzuki ◽  
I. Saito ◽  
...  
Keyword(s):  
Subcellular Localization ◽  
Molecular Basis ◽  
Core Protein ◽  
Hcv Core Protein

scholarly journals The Native Form and Maturation Process of Hepatitis C Virus Core Protein

1998 ◽  
Vol 72 (7) ◽  
pp. 6048-6055 ◽  
Author(s):  
Kohichiroh Yasui ◽  
Takaji Wakita ◽  
Kyoko Tsukiyama-Kohara ◽  
Shin-Ichi Funahashi ◽  
Masumi Ichikawa ◽  
...  
Keyword(s):  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Subcellular Localization ◽  
Core Protein ◽  
Expression System ◽  
Molecular Size ◽  
Laser Scanning Microscopy ◽  
Confocal Laser ◽  
Hcv Core Protein ◽  
Core Proteins

ABSTRACT The maturation and subcellular localization of hepatitis C virus (HCV) core protein were investigated with both a vaccinia virus expression system and CHO cell lines stably transformed with HCV cDNA. Two HCV core proteins, with molecular sizes of 21 kDa (p21) and 23 kDa (p23), were identified. The C-terminal end of p23 is amino acid 191 of the HCV polyprotein, and p21 is produced as a result of processing between amino acids 174 and 191. The subcellular localization of the HCV core protein was examined by confocal laser scanning microscopy. Although HCV core protein resided predominantly in the cytoplasm, it was also found in the nucleus and had the same molecular size as p21 in both locations, as determined by subcellular fractionation. The HCV core proteins had different immunoreactivities to a panel of monoclonal antibodies. Antibody 5E3 stained core protein in both the cytoplasm and the nucleus, C7-50 stained core protein only in the cytoplasm, and 499S stained core protein only in the nucleus. These results clearly indicate that the p23 form of HCV core protein is processed to p21 in the cytoplasm and that the core protein in the nucleus has a higher-order structure different from that of p21 in the cytoplasm. HCV core protein in sera of patients with HCV infection was analyzed in order to determine the molecular size of genuinely processed HCV core protein. HCV core protein in sera was found to have exactly the same molecular weight as the p21 protein. These results suggest that p21 core protein is a component of native viral particles.

Maytansine-Induced Mitotic Arrest in Human Lymphoblasts

1977 ◽  
Vol 35 ◽  
pp. 460-461
Author(s):  
Tai-Te Chao ◽  
John Sullivan ◽  
Awtar Krishan
Keyword(s):  
Electron Microscopy ◽  
Cell Cycle ◽  
Transmission Electron Microscopy ◽  
Tubulin Polymerization ◽  
Vinca Alkaloids ◽  
Antimitotic Activity ◽  
Transmission Electron ◽  
Flow Microfluorometry ◽  
Brain Tubulin

Maytansine, a novel ansa macrolide (1), has potent anti-tumor and antimitotic activity (2, 3). It blocks cell cycle traverse in mitosis with resultant accumulation of metaphase cells (4). Inhibition of brain tubulin polymerization in vitro by maytansine has also been reported (3). The C-mitotic effect of this drug is similar to that of the well known Vinca- alkaloids, vinblastine and vincristine. This study was carried out to examine the effects of maytansine on the cell cycle traverse and the fine struc- I ture of human lymphoblasts.Log-phase cultures of CCRF-CEM human lymphoblasts were exposed to maytansine concentrations from 10-6 M to 10-10 M for 18 hrs. Aliquots of cells were removed for cell cycle analysis by flow microfluorometry (FMF) (5) and also processed for transmission electron microscopy (TEM). FMF analysis of cells treated with 10-8 M maytansine showed a reduction in the number of G1 cells and a corresponding build-up of cells with G2/M DNA content.

An efficient transient assays system using Agrobacterium-mediated transformation of onion (Allium cepa) epidermal cells

2020 ◽  
Vol 80 (03) ◽  
Author(s):  
Yu-Miao Zhang ◽  
Jun Wang ◽  
Tao Wu
Keyword(s):  
Subcellular Localization ◽  
Protein Interaction ◽  
Protein Interactions ◽  
Epidermal Cells ◽  
Cyclin Dependent Kinase ◽  
Protein Subcellular Localization ◽  
Protein Protein Interactions ◽  
Efficient System ◽  
Protein Protein Interaction ◽  
Onion Epidermal Cells

In this study, the Agrobacterium infection medium, infection duration, detergent, and cell density were optimized. The sorghum-based infection medium (SbIM), 10-20 min infection time, addition of 0.01% Silwet L-77, and Agrobacterium optical density at 600 nm (OD600), improved the competence of onion epidermal cells to support Agrobacterium infection at >90% efficiency. Cyclin-dependent kinase D-2 (CDKD-2) and cytochrome c-type biogenesis protein (CYCH), protein-protein interactions were localized. The optimized procedure is a quick and efficient system for examining protein subcellular localization and protein-protein interaction.

pLoc_bal-mPlant: Predict Subcellular Localization of Plant Proteins by General PseAAC and Balancing Training Dataset

2019 ◽  
Vol 24 (34) ◽  
pp. 4013-4022 ◽  
Author(s):  
Xiang Cheng ◽  
Xuan Xiao ◽  
Kuo-Chen Chou
Keyword(s):  
Subcellular Localization ◽  
Basic Research ◽  
Training Dataset ◽  
Sequence Information ◽  
Plant Proteins ◽  
Protein Subcellular Localization ◽  
Computational Tools ◽  
Validation Tests ◽  
User Friendly ◽  
Better Than

Knowledge of protein subcellular localization is vitally important for both basic research and drug development. With the avalanche of protein sequences emerging in the post-genomic age, it is highly desired to develop computational tools for timely and effectively identifying their subcellular localization based on the sequence information alone. Recently, a predictor called “pLoc-mPlant” was developed for identifying the subcellular localization of plant proteins. Its performance is overwhelmingly better than that of the other predictors for the same purpose, particularly in dealing with multi-label systems in which some proteins, called “multiplex proteins”, may simultaneously occur in two or more subcellular locations. Although it is indeed a very powerful predictor, more efforts are definitely needed to further improve it. This is because pLoc-mPlant was trained by an extremely skewed dataset in which some subsets (i.e., the protein numbers for some subcellular locations) were more than 10 times larger than the others. Accordingly, it cannot avoid the biased consequence caused by such an uneven training dataset. To overcome such biased consequence, we have developed a new and bias-free predictor called pLoc_bal-mPlant by balancing the training dataset. Cross-validation tests on exactly the same experimentconfirmed dataset have indicated that the proposed new predictor is remarkably superior to pLoc-mPlant, the existing state-of-the-art predictor in identifying the subcellular localization of plant proteins. To maximize the convenience for the majority of experimental scientists, a user-friendly web-server for the new predictor has been established at http://www.jci-bioinfo.cn/pLoc_bal-mPlant/, by which users can easily get their desired results without the need to go through the detailed mathematics.

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