Abstract
Identifying the building blocks of mammalian tissues is a precondition for understanding their function. In particular, global and quantitative analysis of the proteome of mammalian tissues would point to tissue-specific mechanisms and place the function of each protein in a whole-organism perspective. We performed proteomic analyses of 28 mouse tissues using high-resolution mass spectrometry and used a mix of mouse tissues labeled via stable isotope labeling with amino acids in cell culture as a “spike-in” internal standard for accurate protein quantification across these tissues. We identified a total of 7,349 proteins and quantified 6,974 of them. Bioinformatic data analysis showed that physiologically related tissues clustered together and that highly expressed proteins represented the characteristic tissue functions. Tissue specialization was reflected prominently in the proteomic profiles and is apparent already in their hundred most abundant proteins. The proportion of strictly tissue-specific proteins appeared to be small. However, even proteins with household functions, such as those in ribosomes and spliceosomes, can have dramatic expression differences among tissues. We describe a computational framework with which to correlate proteome profiles with physiological functions of the tissue. Our data will be useful to the broad scientific community as an initial atlas of protein expression of a mammalian species.
Highlights
From the ‡Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany; ¶Department of Human Molecular Genetics and Biochemistry, Tel Aviv University, Tel Aviv, Israel; ʈDepartment of Physiology, University of Tuebingen, 72076 Tuebingen, Germany; **Proteome Center Tuebingen, University of Tuebingen, 72076 Tuebingen, Germany; ‡‡Science for Life Laboratory, Royal Institute of Technology, Stockholm, Sweden; §§Science for Life Laboratory, Department of Immunology, Genetics and Pathology, Uppsala, Sweden
In “shotgun” proteomics, proteins are digested to peptides, and the peptides are analyzed via liquid chromatography coupled to mass spectrometry (LCMS/Mass spectrometry (MS))
Analysis of the data with MaxQuant software [24] and the Andromeda search engine [25] identified 7,349 proteins at a false discovery rate of 1% and quantified 6,974 of them. These data represent a catalogue of expressed mouse proteins and their profiles across the mouse tissues
Summary
Tamar Geiger‡§¶, Ana Velic‡§ʈ, Boris Macek‡§**, Emma Lundberg‡‡, Caroline Kampf§§, Nagarjuna Nagaraj‡, Mathias Uhlen‡‡, Juergen Cox‡, and Matthias Mann‡. Global analyses of mouse tissues have previously been performed mainly on the mRNA level using microarray or deep sequencing technologies [1, 2]. These methods can provide a near-comprehensive view of the biological system at the transcriptional level, mRNA levels do not necessarily predict protein expression levels and miss an important determinant of biological function. Stable isotope labeling with amino acids in cell culture (SILAC) is generally considered as the most accurate technology for relative protein quantification. We provide a deep proteomic map of the proteins and functions across these tissues and highlight key regulators of tissue specificity
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