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Article

Halobacterium salinarum NRC-1 PeptideAtlas: Toward Strategies for Targeted Proteomics and Improved Proteome Coverage

Supporting Info

Phu T. Van^†^‡, Amy K. Schmid^†, Nichole L. King^†, Amardeep Kaur^†, Min Pan^†, Kenia Whitehead^†, Tie Koide^†, Marc T. Facciotti^†^§, Young Ah Goo^†^∥, Eric W. Deutsch^†, David J. Reiss^†, Parag Mallick^⊥ and Nitin S. Baliga*^†^#

Institute for Systems Biology, 1441 North 34th Street, Seattle, Washington 98103, Departments of Biology, Microbiology, and Medicinal Chemistry, University of Washington, Seattle, Washington 98195, and Spielberg Family Center for Applied Proteomics, Cedars-Sinai Medical Center, 8750 West Beverly Boulevard, Los Angeles, California 90048

J. Proteome Res., 2008, 7 (9), pp 3755–3764

DOI: 10.1021/pr800031f

Publication Date (Web): July 25, 2008

†

Institute for Systems Biology.

‡

Department of Biology, University of Washington.

Current affiliation: Department of Biomedical Engineering and Genome Center, University of California, Davis, One Shields Drive, Davis, California 95616.

∥

Department of Medicinal Chemistry, University of Washington.

⊥

Cedars-Sinai Medical Center.

* To whom correspondence should be addressed. Nitin S. Baliga, Telephone, 206-732-1266; Fax, 206-732-1299; E-mail, nbaliga@systemsbiology.org.

Department of Microbiology, University of Washington.

Abstract

The relatively small numbers of proteins and fewer possible post-translational modifications in microbes provide a unique opportunity to comprehensively characterize their dynamic proteomes. We have constructed a PeptideAtlas (PA) covering 62.7% of the predicted proteome of the extremely halophilic archaeon Halobacterium salinarum NRC-1 by compiling approximately 636 000 tandem mass spectra from 497 mass spectrometry runs in 88 experiments. Analysis of the PA with respect to biophysical properties of constituent peptides, functional properties of parent proteins of detected peptides, and performance of different mass spectrometry approaches has highlighted plausible strategies for improving proteome coverage and selecting signature peptides for targeted proteomics. Notably, discovery of a significant correlation between absolute abundances of mRNAs and proteins has helped identify low abundance of proteins as the major limitation in peptide detection. Furthermore, we have discovered that iTRAQ labeling for quantitative proteomic analysis introduces a significant bias in peptide detection by mass spectrometry. Therefore, despite identifying at least one proteotypic peptide for almost all proteins in the PA, a context-dependent selection of proteotypic peptides appears to be the most effective approach for targeted proteomics.

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