A comprehensive functional map of the hepatitis C virus genome provides a resource for probing viral proteins.

UnlabelledPairing high-throughput sequencing technologies with high-throughput mutagenesis enables genome-wide investigations of pathogenic organisms. Knowledge of the specific functions of protein domains encoded by the genome of the hepatitis C virus (HCV), a major human pathogen that contributes to liver disease worldwide, remains limited to insight from small-scale studies. To enhance the capabilities of HCV researchers, we have obtained a high-resolution functional map of the entire viral genome by combining transposon-based insertional mutagenesis with next-generation sequencing. We generated a library of 8,398 mutagenized HCV clones, each containing one 15-nucleotide sequence inserted at a unique genomic position. We passaged this library in hepatic cells, recovered virus pools, and simultaneously assayed the abundance of mutant viruses in each pool by next-generation sequencing. To illustrate the validity of the functional profile, we compared the genetic footprints of viral proteins with previously solved protein structures. Moreover, we show the utility of these genetic footprints in the identification of candidate regions for epitope tag insertion. In a second application, we screened the genetic footprints for phenotypes that reflected defects in later steps of the viral life cycle. We confirmed that viruses with insertions in a region of the nonstructural protein NS4B had a defect in infectivity while maintaining genome replication. Overall, our genome-wide HCV mutant library and the genetic footprints obtained by high-resolution profiling represent valuable new resources for the research community that can direct the attention of investigators toward unidentified roles of individual protein domains.ImportanceOur insertional mutagenesis library provides a resource that illustrates the effects of relatively small insertions on local protein structure and HCV viability. We have also generated complementary resources, including a website (http://hangfei.bol.ucla.edu) and a panel of epitope-tagged mutant viruses that should enhance the research capabilities of investigators studying HCV. Researchers can now detect epitope-tagged viral proteins by established antibodies, which will allow biochemical studies of HCV proteins for which antibodies are not readily available. Furthermore, researchers can now quickly look up genotype-phenotype relationships and base further mechanistic studies on the residue-by-residue information from the functional profile. More broadly, this approach offers a general strategy for the systematic functional characterization of viruses on the genome scale

High-Resolution Functional Profiling Hepatitis C Virus Genome

Hepatitis C virus (HCV) is a major cause of human liver diseases and the mortality associated with chronic infection has been increasing due to lack of effective treatments. Thus, better understanding the functional domains in the virus genome and their contributions to viral-host interactions will shed light on novel drug development.In an attempt to systematically map the anti-interferon (IFN) functional domains in HCV genome, we established a genetic profiling platform by combining high-throughput mutagenesis and next-generation sequencing. An IFN-α screen performed with a 15-nucleotide random insertion library identified four regions with increased IFN-sensitivity when mutated. Further analyzing the N-terminus of core in a secondary screen with saturation mutagenesis revealed that phenylalanine 24 is essential for inhibiting STAT1 phosphorylation thereby blocking IFN signaling transduction. The genomic IFN-α screen suggested that p7 is a novel immune evasion protein. To interrogate the mechanism that governs p7 counteracting the IFN response, a cDNA library screen of liver-specific interferon-stimulated genes was conducted, and individual effect of 107 genes on p7 mutant virus replication was determined. The screen showed that virus with p7 knockout is more sensitive to IFI6-16 over-expression. Further analysis demonstrated a physical interaction between p7 and IFI6-16, suggesting p7 may target IFI6-16 to actively suppress innate immune response.The same concept of systematic profiling approach was applied to determine the residues interacting with Daclatasvir, which was identified as an effective NS5A inhibitor. Quantitatively examining the fitness of a saturation mutant library within domain IA of NS5A upon the drug treatment uncovered potential drug-interaction residues. Epistatic interactions among these residues are correlated with genotype-specific differences in drug-sensitivity. Remarkably, the fitness score of all possible substitutions and their drug-sensitivity allow for systematical mapping of the genetic barriers and prediction of evolutionary paths for potentially emerging resistances. Taken together, we have profiled the HCV genome to define the essential residues for evading host immune responses or mediating drug interactions. We suggest that the genetic profiling platform described in this thesis can be generally applied in interrogating virus-host interactions and chemical-target interactions, which will provide comprehensive knowledge on new therapeutic strategies to overcome persistent HCV infection

DIFFERENTIABLE SINGULAR COHOMOLOGY RELATED TO FOLIATION(Foliations and K-theory)

This paper presents an empirical survey study. We propose a model to examine the individual and joint effects of the three components of intellectual capital (i.e., human, social, and structural capital) on process innovation and mass customisation (MC) capability. The hypotheses are empirically tested using structural equation modelling and data collected from 645 manufacturing plants in 10 countries/regions. The results show that human and social capital are positively associated with structural capital. Human capital directly improves both process innovation and MC capability. The direct effect of social capital on MC capability and that of structural capital on process innovation are positive and significant. Moreover, process innovation is positively associated with MC capability. In addition, we find that structural capital mediates human and social capital’s effects on process innovation, and process innovation mediates human and structural capital’s effects on MC capability. This study contributes to the literature by providing insights into how human, social, and structural capital jointly improve process innovation and MC capability, as well as how the different types of knowledge residing in a manufacturer affect MC capability development

On-chip cytometry using plasmonic nanoparticle enhanced lensfree holography.

Computational microscopy tools, in particular lensfree on-chip imaging, provide a large field-of-view along with a long depth-of-field, which makes it feasible to rapidly analyze large volumes of specimen using a compact and light-weight on-chip imaging architecture. To bring molecular specificity to this high-throughput platform, here we demonstrate the use of plasmon-resonant metallic nanoparticles to automatically recognize different cell types based on their plasmon-enhanced lensfree holograms, detected and reconstructed over a large field-of-view of e.g., ~24 mm²

Rational Design and Adaptive Management of Combination Therapies for Hepatitis C Virus Infection

International audienceRecent discoveries of direct acting antivirals against Hepatitis C virus (HCV) have raised hopes of effective treatment via combination therapies. Yet rapid evolution and high diversity of HCV populations, combined with the reality of suboptimal treatment adherence, make drug resistance a clinical and public health concern. We develop a general model incorporating viral dynamics and pharmacokinetics/ pharmacodynamics to assess how suboptimal adherence affects resistance development and clinical outcomes. We derive design principles and adaptive treatment strategies, identifying a high-risk period when missing doses is particularly risky for de novo resistance, and quantifying the number of additional doses needed to compensate when doses are missed. Using data from large-scale resistance assays , we demonstrate that the risk of resistance can be reduced substantially by applying these principles to a combination therapy of daclatasvir and asunaprevir. By providing a mechanistic framework to link patient characteristics to the risk of resistance, these findings show the potential of rational treatment design