5 research outputs found
An FD-LC-MS/MS Proteomic Strategy for Revealing Cellular Protein Networks: A Conditional Superoxide Dismutase 1 Knockout Cells
<div><p>Systems biology aims to understand biological phenomena in terms of complex biological and molecular interactions, and thus proteomics plays an important role in elucidating protein networks. However, many proteomic methods have suffered from their high variability, resulting in only showing altered protein names. Here, we propose a strategy for elucidating cellular protein networks based on an FD-LC-MS/MS proteomic method. The strategy permits reproducible relative quantitation of differences in protein levels between different cell populations and allows for integration of the data with those obtained through other methods. We demonstrate the validity of the approach through a comparison of differential protein expression in normal and conditional superoxide dismutase 1 gene knockout cells and believe that beginning with an FD-LC-MS/MS proteomic approach will enable researchers to elucidate protein networks more easily and comprehensively.</p> </div
Schematic illustration of the FD-LC-MS/MS proteomic method.
<p>After fluorogenic derivatization, the protein mixtures are separated by HPLC, and proteins exhibiting significant differential expression are isolated and identified using nano-HPLC-MS/MS and database searching.</p
Predicted protein networks in SOD1(−) cells.
<p>Protein networks for denaturation, refolding, decomposition, ATP-consumption and -production. Arrows indicate increased (up) and decreased (down) expression. The (+) and (−) signs indicate enhancement or suppression, respectively, of cellular processes in response to changes in protein expression. The abbreviated protein names are in Table S1. GR: glucocorticoid receptor.</p
Simplified scheme for the proposed strategy.
<p>Using the method, protein expression changes caused by a particular stimulus are quantified. The resulting data are integrated with other data and a diagram of predicted protein networks is constructed.</p
Classification of identified proteins.
<p>Functional classification of differentially expressed proteins identified in this study. The most significant changes were observed with proteins involved in mediating protein folding. ND: No Data.</p