A Concerted Action of Hepatitis C Virus P7 and Nonstructural Protein 2 Regulates Core Localization at the Endoplasmic Reticulum and Virus Assembly

Hepatitis C virus (HCV) assembly remains a poorly understood process. Lipid droplets (LDs) are thought to act as platforms for the assembly of viral components. The JFH1 HCV strain replicates and assembles in association with LD-associated membranes, around which viral core protein is predominantly detected. In contrast, despite its intrinsic capacity to localize to LDs when expressed individually, we found that the core protein of the high-titer Jc1 recombinant virus was hardly detected on LDs of cell culture-grown HCV (HCVcc)-infected cells, but was mainly localized at endoplasmic reticulum (ER) membranes where it colocalized with the HCV envelope glycoproteins. Furthermore, high-titer cell culture-adapted JFH1 virus, obtained after long-term culture in Huh7.5 cells, exhibited an ER-localized core in contrast to non-adapted JFH1 virus, strengthening the hypothesis that ER localization of core is required for efficient HCV assembly. Our results further indicate that p7 and NS2 are HCV strain-specific factors that govern the recruitment of core protein from LDs to ER assembly sites. Indeed, using expression constructs and HCVcc recombinant genomes, we found that p7 is sufficient to induce core localization at the ER, independently of its ion-channel activity. Importantly, the combined expression of JFH1 or Jc1 p7 and NS2 induced the same differential core subcellular localization detected in JFH1- vs. Jc1-infected cells. Finally, results obtained by expressing p7-NS2 chimeras between either virus type indicated that compatibilities between the p7 and the first NS2 trans-membrane domains is required to induce core-ER localization and assembly of extra- and intra-cellular infectious viral particles. In conclusion, we identified p7 and NS2 as key determinants governing the subcellular localization of HCV core to LDs vs. ER and required for initiation of the early steps of virus assembly

Assessing the Robustness of Bel1D for Inverting TEM Data

Subsurface is of prime importance for many geological and hydrogeological applications. Geophysical methods offer an economical alternative for investigating the subsurface compared to costly boreholes investigation methods. Geophysics provides a wide range of approaches that can models of the subsurface, traditionally by inversion process. Basically, there are two types of the inversion deterministic and stochastic inversion. The difference between them is the extent of uncertainty in their results. Deterministic inversion is very certain which have no ability to generate any uncertainty, on the other hand stochastic inversion are often very expensive. In this research Firstly, we tried to find out the effect of time and space discretization on the posterior models or on the uncertainty quantification of models generated in BEL1D. Secondly, we discussed the importance of prior selection and thirdly, we tried to quantify the salinity of the TDEM data taken in Vietnam south central province which have been facing saltwater intrusions problem for many years particularly in Binah Thuan province) by combining a new stochastic approach called Bayesian evidential learning 1D imaging (BEL1D) with SimPEG (an open-source python package for solving the electromagnetic forward and inverse problem) as a forward solver. BEL1D bypasses the inversion step by generating random samples from the prior model distribution (with predefined ranges for thickness, electrical conductivity, and salinity for the different layers). It then directly generates the corresponding data to learn a direct statistical relationship between data and model parameters. From this relationship, BEL1D can generate posterior models fitting the field observed data, without additional forward model computations, making it a very efficient way to stochastically solve the inverse problem. The output of BEL1D shows the range of uncertainty for subsurface models. It enables to identify which model parameters are sensitive and can thus be accurately estimated from TDEM data. In our case, it reveals the uncertainty on the depth of fresh saline interface as well as the total dissolved solid content of groundwater. The application of BELID together with SimPEG for stochastic TDEM inversion is a very efficient approach as it allows to estimate the uncertainty at a limited cost. We thus expect our approach to be also valuable for the inversion of airborne data sets

Hepatitis C virus genotypes in different regions of the former Soviet Union (Russia, Belarus, Moldova, and Uzbekistan)

The prevalence of HCV genotypes in four republics of the former Soviet Union (Russia, Belarus, Moldova, and Uzbekistan) was investigated. Overall, 197 HCV isolates from 66 blood donors and 131 patients with chronic hepatitis were typed. Viral sequences from sera of infected subjects were amplified by nested RT-PCR using primers from the core region and typed by one or two techniques: (1) DNA enzyme immunoassay (DEIA) and (2) PCR with a set of type-specific primers. Only three major HCV genotypes were identified in this study population. HCV 1b was found to be the predominant virus type both among blood donors and chronic hepatitis patients, followed by 3a, 2a, and 1a (chronic hepatitis patients: 1b-82%; 3a-10%; 2a-4%, 1a-5% and 2c-1%; blood donors: 1b-77%; 3a-17%; and 2a-6%). No significant difference in genotype distribution was observed between different countries or between blood donors and chronic hepatitis patients within the same country. Results of the genotyping procedures were confirmed by direct sequencing of 216 nt PCR fragments corresponding to part of HCV core gene. Phylogenetic analysis of HCV 1b sequences from this study and from the Genbank demonstrated that the sequences from the former Soviet Union do not form evolutionary lineage(s) different from those of strains of the same subtype circulating in other geographical regions