Abstract
MS-based quantitative proteomics is widely used for large scale identification of proteins. However, an integrated approach that offers comprehensive proteome coverage, a tool for the quick categorization of the identified proteins, and a standardized biological study method is needed for helping the researcher focus on investigating the proteins with biologically important functions. In this study, we utilized isobaric tagging for relative and absolute quantification (iTRAQ)-based quantitative differential LC/MS/MS, functional annotation with a proprietary gene ontology tool (Molecular Annotation by Gene Ontology (MANGO)), and standard biochemical methods to identify proteins related to neuronal differentiation in nerve growth factor-treated rat pheochromocytoma (PC12) cells, which serve as a representative model system for studying neuronal biological processes. We performed MS analysis by using both nano-LC-MALDI-MS/MS and nano-LC-ESI-MS/MS for maximal proteome coverage. Of 1,482 non-redundant proteins semiquantitatively identified, 72 were differentially expressed with 39 up- and 33 down-regulated, including 64 novel nerve growth factor-responsive PC12 proteins. Gene ontology analysis of the differentially expressed proteins by MANGO indicated with statistical significance that the up-regulated proteins were mostly related to the biological processes of cell morphogenesis, apoptosis/survival, and cell differentiation. Some of the up-regulated proteins of unknown function, such as PAIRBP1, translationally controlled tumor protein, prothymosin alpha, and MAGED1, were further analyzed to validate their significant functions in neuronal differentiation by immunoblotting and immunocytochemistry using each antibody combined with a specific short interfering RNA technique. Knockdown of these proteins caused abnormal cell morphological changes, inhibition of neurite formation, and cell death during each course of the differentiation, confirming their important roles in neurite formation and survival of PC12 cells. These results show that our iTRAQ-MANGO-biological analysis framework, which integrates a number of standard proteomics strategies, is effective for targeting and elucidating the functions of proteins involved in the cellular biological process being studied.