The wealth of human genome sequence information now available, coupled with technological advances in robotics, nanotechnology, mass spectrometry, and information systems, has given rise to a method of scientific inquiry known as functional genomics. By using these technologies to survey gene expression and protein production on a near global scale, the goal of functional genomics is to assign biological function to genes with currently unknown roles in physiology. This approach carries particular appeal in disease research, where it can uncover the function of previously unknown genes and molecular pathways that are directly involved in disease progression. With this knowledge may come improved diagnostic techniques, prognostic capabilities, and novel therapeutic approaches. In this regard, the continuing evolution of proteomic technologies has resulted in an increasingly greater impact of proteome studies in many areas of research and hepatology is no exception. Our laboratory has been extremely active in this area, applying both genomic and proteomic technologies to the analysis of virus-host interactions in several systems, including the study of hepatitis C virus (HCV) infection and HCV-associated liver disease. Since proteomic technologies are foreign to many hepatologists (and to almost everyone else), this article will provide an overview of proteomic methods and technologies and describe how they are being used to study liver function and disease. (HEPATOLOGY 2006;44:299-308.)
T he flow of biological information-from DNA to RNA to protein-immediately suggests that any view of a biological system that stops at the tier of nucleic acids will be incomplete. This is evidenced by the often poor to moderate correlation (e.g., Ο½40% concordance) between the relative expression abundance of a gene and its biologically active protein product. [1][2][3][4] Factors contributing to this disparity may include differences in the rates of synthesis and half-lives for an mRNA and the protein it encodes. Additionally, mRNA measurements can not predict phenotypic protein variations resulting from down-stream regulatory events (e.g., modification, interaction with other proteins, subcellular distribution, and activity) that confer or modify protein function. 5,6 Moreover, the limited presence of mRNA in body fluids restricts identification of clinically relevant disease biomarkers to the measurement of secreted proteins in these samples. It therefore appears essential that the proteins expressed in a cell or tissue are also analyzed and related to gene expression measurements on the mRNA level to provide the full picture of a biological process.
A comprehensive proteomic analysis requires characterization of the many diverse properties of a protein, all of which can impact cellular function and contribute to altered cellular states. Much of the initial proteomics effort has centered on cataloging the proteins expressed in a cell or tissue and identifying alterations in protein levels that occur in response to physiologic cues or environmental perturbations. This approach, termed "global comparative quantitative protein profiling", can be utilized for a variety of research applications. For example, studies in-Abbreviations: MS, mass spectrometry; MALDI, matrix assisted laser desorption ionization; ESI, electrospray ionization; 2D PAGE, two dimensional polyacrylamide gel electrophoresis; FTICR, fourier transform ion cyclotron resonance; MS/ MS, tandem mass spectrometry; LC-MS/MS, liquid chromatography tandem mass spectrometry; LC-MS, liquid chromatography mass spectrometry; AMT, accurate mass and time.