Transcriptome sequencing, microarray, and proteomic analyses reveal cellular and metabolic impact of hepatitis C virus infection in vitro.
Hepatitis C virus (HCV) is a major cause of liver disease but the full impact of HCV infection on the hepatocyte is poorly understood. RNA sequencing (RNA-Seq) is a novel method to analyze the full transcriptional activity of a cell or tissue, thus allowing new insight into the impact of HCV infection. We conducted the first full-genome RNA-Seq analysis in a host cell to analyze infected and noninfected cells, and compared this to microarray and proteomic analyses. The combined power of the triple approach revealed that HCV infection affects a number of previously unreported canonical pathways and biological functions, including pregnane X receptor/retinoic acid receptor activation as a potential host antiviral response, and integrin-linked kinase signaling as an entry factor. This approach also identified several mechanisms implicated in HCV pathogenesis, including an increase in reactive oxygen species. HCV infection had a broad effect on cellular metabolism, leading to increases in cellular cholesterol and free fatty acid levels, associated with a profound and specific decrease in cellular glucose levels.


CONCLUSIONS
RNA-Seq technology, especially when combined with established methods, demonstrated that HCV infection has potentially wide-ranging effects on cellular gene and protein expression. This in vitro study indicates a substantial metabolic impact of HCV infection and highlights new mechanisms of virus-host interaction which may be highly relevant to pathogenesis in vivo.
Woodhouse
Stephen D
SD
Oxford Glycobiology Institute, Department of Biochemistry, University of Oxford, Oxford, UK. Stephen.woodhouse@bioch.ox.ac.uk
Narayan
Ramamurthy
R
Latham
Sally
S
Lee
Sheena
S
Antrobus
Robin
R
Gangadharan
Bevin
B
Luo
Shujun
S
Schroth
Gary P
GP
Klenerman
Paul
P
Zitzmann
Nicole
N
D002478:Cells, Cultured; D020869:Gene Expression Profiling; D006526:Hepatitis C / Q000235:genetics* / Q000378:metabolism*; D046228:Microarray Analysis; D020543:Proteome
D020543:Proteome