Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis.
In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.
Park
Gun Wook
GW
Proteomics Team, Korea Basic Science Institute, Yusung-Ku, Daejeon, Korea.
Kwon
Kyung-Hoon
KH
Kim
Jin Young
JY
Lee
Jeong Hwa
JH
Yun
Sung-Ho
SH
Kim
Seung Il
SI
Park
Young Mok
YM
Cho
Sang Yun
SY
Paik
Young-Ki
YK
Yoo
Jong Shin
JS
D001798:Blood Proteins / Q000032:analysis*; D002853:Chromatography, Liquid; D030562:Databases, Protein; D006801:Humans; D013058:Mass Spectrometry; D008970:Molecular Weight; D010446:Peptide Fragments / Q000032:analysis; D020543:Proteome / Q000032:analysis*; D040901:Proteomics; D016958:Pseudomonas putida / Q000378:metabolism*
D001798:Blood Proteins; D010446:Peptide Fragments; D020543:Proteome