Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis

Gun Wook Park, Kyung Hoon Kwon, Jin Young Kim, Jeong Hwa Lee, Sung Ho Yun, Seung Il Kim, Young Mok Park, Sang Yun Cho, Young Ki Paik, Jong Shin Yoo

Research output: Contribution to journalArticle

23 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)1121-1132
Number of pages12
JournalProteomics
Volume6
Issue number4
DOIs
Publication statusPublished - 2006 Feb 1

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology

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    Park, G. W., Kwon, K. H., Kim, J. Y., Lee, J. H., Yun, S. H., Kim, S. I., Park, Y. M., Cho, S. Y., Paik, Y. K., & Yoo, J. S. (2006). Human plasma proteome analysis by reversed sequence database search and molecular weight correlation based on a bacterial proteome analysis. Proteomics, 6(4), 1121-1132. https://doi.org/10.1002/pmic.200500318