Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.
Skip to main content

A global protein survey is needed to gain systems-level insights into mammalian cell signaling and information flow. Human Jurkat T leukemic cells are one of the most important model systems for T cell signaling study, but no comprehensive proteomics survey has been carried out in this cell type. In the present study we combined subcellular fractionation, multiple protein enrichment methods, and replicate tandem mass spectrometry analyses to determine the protein expression pattern in a single Jurkat cell type. The proteome dataset was evaluated by comparison with the genome-wide mRNA expression pattern in the same cell type. A total of 5381 proteins were identified by mass spectrometry with high confidence. Rigorous comparison of RNA and protein expression afforded removal of the false positive identifications and redundant entries but rescued the proteins identified by a single high scoring peptide, resulting in the final identification of 6471 unique gene products among which 98% of the corresponding transcripts were detected with high probability. Using hierarchical clustering of the protein expression patterns in five subcellular fractions (cytosol, light membrane, heavy membrane, mitochondria, and nuclei), the primary subcellular localization of 2241 proteins was assigned with high confidence including 792 previously uncharacterized proteins. This proteome landscape can serve as a useful platform for systems-level understanding of organelle composition and cellular functions in human T cells.

Original publication

DOI

10.1074/mcp.M700017-MCP200

Type

Journal article

Journal

Mol Cell Proteomics

Publication Date

08/2007

Volume

6

Pages

1343 - 1353

Keywords

Gene Expression Profiling, Humans, Jurkat Cells, Leukemia, Proteome, Software, T-Lymphocytes