Blood serum is a complex body fluid that contains various proteins ranging in concentration over at least 9 orders of magnitude. Using a combination of mass spectrometry technologies with improvements in sample preparation, we have performed a proteomic analysis with submilliliter quantities of serum and increased the measurable concentration range for proteins in blood serum beyond previous reports. We have detected 490 proteins in serum by on-line reversed-phase microcapillary liquid chromatography coupled with ion trap mass spectrometry. To perform this analysis, immunoglobulins were removed from serum using protein A/G, and the remaining proteins were digested with trypsin. Resulting peptides were separated by strong cation exchange chromatography into distinct fractions prior to analysis. This separation resulted in a 3-5-fold increase in the number of proteins detected in an individual serum sample. With this increase in the number of proteins identified we have detected some lower abundance serum proteins (ng/ml range) including human growth hormone, interleukin-12, and prostate-specific antigen. We also used SEQUEST to compare different protein databases with and without filtering. This comparison is plotted to allow for a quick visual assessment of different databases as a subjective measure of analytical quality. With this study, we have performed the most extensive analysis of serum proteins to date and laid the foundation for future refinements in the identification of novel protein biomarkers of disease.
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Department of Computer Science, Purdue University, West LafayetteDepartment of Computer Science, Purdue University, West Lafayette
Manchanda S.
Meyer M.
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Department of Statistics and Mathematics, Purdue University, West Lafayette, INDepartment of Computer Science, Purdue University, West Lafayette
Meyer M.
Li Q.
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Institute of Biophysics, Chinese Academy of Sciences, BeijingDepartment of Computer Science, Purdue University, West Lafayette
Li Q.
Liang K.
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Institute of Biophysics, Chinese Academy of Sciences, BeijingDepartment of Computer Science, Purdue University, West Lafayette
Liang K.
Li Y.
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Institute of Biophysics, Chinese Academy of Sciences, BeijingDepartment of Computer Science, Purdue University, West Lafayette
Li Y.
Kong N.
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Weldon School of Biomedical Engineering, Purdue University, 206 S. Martin Jischke Dr, West Lafayette, 47906, INDepartment of Computer Science, Purdue University, West Lafayette