The 2003 global outbreak of progressive respiratory failure was caused by a newly emerged virus, severe acute respiratory syndrome coronavirus (SARS-CoV). In contrast to many well-studied enveloped viruses that assemble and bud at the plasma membrane, coronaviruses assemble by budding into the lumen of the endoplasmic reticulum-Golgi intermediate compartment and are released from the cell by exocytosis. For this to occur, the viral envelope proteins must be efficiently targeted to the Golgi region of the secretory pathway. Although the envelope protein (E) makes up only a small percentage of the viral envelope, it plays an important, as-yet-undefined role in virus production. To dissect the targeting of the SARS-CoV E protein to the Golgi region, we exogenously expressed the protein and various mutants from cDNA and determined their localization using immunofluorescence microscopy and biochemical assays. We show that the cytoplasmic tail of the SARS-CoV E protein is sufficient to redirect a plasma membrane protein to the Golgi region. Through site-directed mutagenesis, we demonstrate that a predicted beta-hairpin structural motif in the tail is sufficient for Golgi complex localization of a reporter protein. This motif is conserved in E proteins of beta and gamma coronaviruses (formerly referred to as group 2 and 3 coronaviruses), where it also functions as a Golgi complex-targeting signal. Dissecting the mechanism of targeting of the SARS-CoV E protein will lead to a better understanding of its role in the assembly and release of virions.

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This work provides, for the first time, indirect evidence of HEV transmission by pooled plasma and warrants further studies.

Quick and accurate genotyping of hepatitis C virus (HCV) is becoming increasingly important for clinical management of chronic infection and as an epidemiological marker. Furthermore, the incidence of HCV infection with mixed genotypes has clinical significance that is not addressed by most genotyping methods. We have developed a fluorescence-based genotyping assay called primer-specific extension analysis (PSEA) for the most prevalent HCV genotypes and have demonstrated the capacity of PSEA-HCV for detecting mixedgenotype HCV infections. PSEA-HCV detects genotype-specific sequence differences in the 5 untranslated region of HCV in products amplified by the COBAS AMPLICOR HCV Test, v2.0. Simulated mixed HCV infection of plasma with RNase-resistant RNA controls demonstrates that PSEA-HCV can detect as many as five genotypes in one specimen. Furthermore, in dual-genotype simulations, PSEA-HCV can unequivocally detect both genotypes, with one genotype representing only 3.1% of the mixture (313/10,000 IU in starting plasma). Compared to INNO-LiPA HCV II, both assays determined the same genotype for 191/199 (96%) patient specimens (175 subtype and 16 genotype-only identifications). Following the initial evaluation, PSEA-HCV was used routinely to genotype HCV from patient specimens submitted to our laboratory (n ‫؍‬ 312). Seventeen (5.4%) mixed infections were identified. The distribution of single-infection HCV genotypes in our population was 60.9% type 1 (n ‫؍‬ 190), 12.8% type 2 (n ‫؍‬ 40), 20.2% type 3 (n ‫؍‬ 63), 0.3% type 4 (n ‫؍‬ 1), and 0.3% other (n ‫؍‬ 1). In conclusion, PSEA-HCV provides an inexpensive, high-throughput screening tool for rapid genotyping of HCV while reliably identifying mixed HCV infections.Infection by hepatitis C virus (HCV) is the leading cause of chronic liver disease worldwide (19). The overall prevalence of HCV infection in the United States is 1.8%, with most of the patients unaware of their infection and at risk for developing cirrhosis and hepatocellular carcinoma (15,21). HCV is a positive-sense, single-stranded RNA virus that displays extensive genetic heterogeneity (1). At least six major HCV genotypes comprising numerous, more closely related subtypes have been identified (26). HCV genotypes display significant differences in their global distribution and prevalence, making genotyping a useful method for determining the source of HCV transmission in an infected localized population (11). Furthermore, in addition to viral load and liver histology, the genotype of the infecting HCV strain appears to be an important determinant of the severity and aggressiveness of liver infection, as well as patient response to antiviral therapy (26). Consequently, several methods for genotyping HCV have been developed, including direct DNA sequencing (2, 5, 6), typespecific PCR (17), restriction fragment length polymorphism (16), line probe assays (22, 23), primer-specific and mispair extension analysis (7,8), heteroduplex mobility analysis by temperature gradient capillary electrophoresis (14)...

We report the design and the performance of a two-chamber thin-layer electrochemical device for in situ potential-dependent liquid NMR measurement. Liquid NMR spectra, simultaneously recorded with cyclic voltammetry (CV), have been obtained to reveal molecular changes with potentials scanning. As a proof of concept, redox properties of 1,4-benzoquinone based systems have been investigated, and a π dimerization has been identified by combining both in situ and ex situ NMR analyses. This work provides a new approach for spectroelectrochemistry, which will contribute to developing electrochemical NMR (EC-NMR) as an important tool for the analysis of electrochemical process at a molecular level.

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Purpose An L2‐regularization based postprocessing method is proposed and tested for removal of residual or unsuppressed water signals in proton MR spectroscopic imaging (MRSI) data recorded from the human brain at 3T. Methods Water signals are removed by implementation of the L2 regularization using a synthesized water‐basis matrix that is orthogonal to metabolite signals of interest in the spectral dimension. Simulated spectra with variable water amplitude and in vivo brain MRSI datasets were used to demonstrate the proposed method. Results were compared with two commonly‐used postprocessing methods for removing water signals. Results The L2 method yielded metabolite signals that were close to true values for the simulated spectra. Residual/unsuppressed water signals in human brain short‐ and long‐echo time MRSI datasets were efficiently removed by the proposed method allowing good quality metabolite maps to be reconstructed with minimized contamination from water signals. Significant differences of the creatine signal were observed between brain long‐echo time MRSI without and with water saturation, attributable to the previously described magnetization transfer effect. Conclusions With usage of a synthesized water matrix generated based on reasonable prior knowledge about water and metabolite resonances, the L2 method is shown to be an effective way to remove water signals from MRSI of the human brain.