alexa Large-scale identification of proteins expressed in mouse embryonic stem cells.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Proteomics & Bioinformatics

Author(s): Nagano K, Taoka M, Yamauchi Y, Itagaki C, Shinkawa T,

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Abstract A protein subset expressed in the mouse embryonic stem (ES) cell line, E14-1, was characterized by mass spectrometry-based protein identification technology and data analysis. In total, 1790 proteins including 365 potential nuclear and 260 membrane proteins were identified from tryptic digests of total cell lysates. The subset contained a variety of proteins in terms of physicochemical characteristics, subcellular localization, and biological function as defined by Gene Ontology annotation groups. In addition to many housekeeping proteins found in common with other cell types, the subset contained a group of regulatory proteins that may determine unique ES cell functions. We identified 39 transcription factors including Oct-3/4, Sox-2, and undifferentiated embryonic cell transcription factor I, which are characteristic of ES cells, 88 plasma membrane proteins including cell surface markers such as CD9 and CD81, 44 potential proteinaceous ligands for cell surface receptors including growth factors, cytokines, and hormones, and 100 cell signaling molecules. The subset also contained the products of 60 ES-specific and 41 stemness genes defined previously by the DNA microarray analysis of Ramalho-Santos et al. (Ramalho-Santos et al., Science 2002, 298, 597-600), as well as a number of components characteristic of differentiated cell types such as hematopoietic and neural cells. We also identified potential post-translational modifications in a number of ES cell proteins including five Lys acetylation sites and a single phosphorylation site. To our knowledge, this study provides the largest proteomic dataset characterized to date for a single mammalian cell species, and serves as a basic catalogue of a major proteomic subset that is expressed in mouse ES cells. This article was published in Proteomics and referenced in Journal of Proteomics & Bioinformatics

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