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Technology I: Label-free MS based quantitation

In this method, the relative abundance of a protein is calculated based on the method published by Griffin et al.(1). The relative intensity of each protein samples is measured based on combined MS intensity of peptide and the intensity of peptide fragments from CID (collision induced fragmentation) process in MS/MS. We have developed a proprietary software package for the quantitation of relative protein ratio in the label-free proteomics. The method can be used for many different kinds of protein samples, including primary cell samples, tissues and blood samples. Based on the study, the method can accurately predict protein amount >80% of the time.

Technology II: SILAC Based Proteomic Analysis

In SILAC method (Stable Isotope Labeling by Amino Acids in Cell Culture), protein samples are differentially labeled in cell culture with a cell culture media containing normal and stable isotope C13 incorporated amino acids (Lysine and Argentine).  The differentially labeled cells can be combined with cell lysis and protein isolation. So variation introduced during protein isolation steps can be eliminated. A stable isotope-labeled protein should behave the same chemically or biologically as the normal proteins except a slight difference in mass.  So the method can give an accurate measurement of the ratio of a protein between two samples. We have developed proprietary software tools for the analysis of proteomic data from SILIC labeled samples. The limitation of SILIC method is 1).Normally it can’t be used in the proteomic analysis of tissue, blood samples or primary cell lines; 2). The cost of isotope replaced cell culture medium is quite high.



1.      Griffin, N., Yu, J., Long, F., Oh P., Shore S., Li, Y.,  Koziol J., & Schnitzer, J., Label-free, normalized quantification of complex mass spectrometry data for proteomic analysis (2010) Nature Biotechnology 28, 83-91 .

2.      Blagoev, B., Kratchmarova, I., Ong, S. E., Nielsen, M., Foster, L. J. and Mann, M,. A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling. (2003). Nature Biotechnology. 21, 315-318.