ABSTRACT
Metabolomics represents an emerging and powerful discipline that provides an accurate and dynamic picture of the phenotype of bio-systems through the study of potential metabolites that could be used as therapeutic targets and for the discovery of new drugs. Hepatitis C virus (HCV) is a leading cause of liver disease worldwide, and is a major burden on public health. It is hypothesized that an animal model of HCV infection would produce unique patterns of endogenous metabolites. Herein, a method for the construction of efficient networks is presented with regard to the proteins of bear bile powder (PBBP) that protect against HCV as a case study. Ultra-performance liquid chromatography, coupled with electrospray ionization/quadrupole-time-of-flight high definition mass spectrometry (UPLC-HDMS), coupled with pattern recognition methods and computational systems analysis were integrated to obtain comprehensive metabolomic profiling and pathways of the large biological data sets. Among the regulated pathways, 38 biomarkers were identified and two unique metabolic pathways were indicated to be differentially affected in HCV animals. The results provided a systematic view of the development and progression of HCV, and also could be used to analyze the therapeutic effects of PBBP, a widely used anti-HCV medicine. The results also showed that PBBP could provide satisfactory effects on HCV infection through partially regulating the perturbed pathway. The most promising use in the near future would be to clarify the pathways for the drugs and obtain biomarkers for these pathways to help guide testable predictions, provide insights into drug action mechanisms, and enable an increase in research productivity toward metabolomic drug discovery.