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A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis

Nature volume 494, pages 266–270 (2013)Cite this article

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Abstract

Experience from different fields of life sciences suggests that accessible, complete reference maps of the components of the system under study are highly beneficial research tools. Examples of such maps include libraries of the spectroscopic properties of molecules, or databases of drug structures in analytical or forensic chemistry. Such maps, and methods to navigate them, constitute reliable assays to probe any sample for the presence and amount of molecules contained in the map. So far, attempts to generate such maps for any proteome have failed to reach complete proteome coverage1,2,3. Here we use a strategy based on high-throughput peptide synthesis and mass spectrometry to generate an almost complete reference map (97% of the genome-predicted proteins) of the Saccharomyces cerevisiae proteome. We generated two versions of this mass-spectrometric map, one supporting discovery-driven (shotgun)3,4 and the other supporting hypothesis-driven (targeted)5,6 proteomic measurements. Together, the two versions of the map constitute a complete set of proteomic assays to support most studies performed with contemporary proteomic technologies. To show the utility of the maps, we applied them to a protein quantitative trait locus (QTL) analysis7, which requires precise measurement of the same set of peptides over a large number of samples. Protein measurements over 78 S. cerevisiae strains revealed a complex relationship between independent genetic loci, influencing the levels of related proteins. Our results suggest that selective pressure favours the acquisition of sets of polymorphisms that adapt protein levels but also maintain the stoichiometry of functionally related pathway members.

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Figure 1: Generation of a reference mass-spectrometric map for the yeast proteome.
Figure 2: Composition and use of the spectral libraries.
Figure 3: Quantitative trait analysis from the targeted proteomic data set.

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Acknowledgements

This project has been funded in part by ETH Zurich, the Swiss National Science Foundation (3100A0-107679), the National Heart, Lung and Blood Institute, National Institutes of Health (N01-HV-28179), the National Science Foundation MRI (grant 0923536), the Luxembourg Centre for Systems Biomedicine and the University of Luxembourg, and by SystemsX.ch, the Swiss initiative for systems biology. P.P. is supported by a Foerderungsprofessur grant from the Swiss National Science Foundation (PP00P3_133670), by a European Union Seventh Framework Program Reintegration grant (FP7-PEOPLE-2010-RG-277147) and by a Promedica Stiftung (2-70669-11), H. L. is supported by the University Grant Council of the Hong Kong Special Administrative Region Government, China (HKUST DAG08/09.EG02). A.B. is supported by the Klaus Tschira Foundation and by a European Union FP7 HEALTH grant (HEALTH-F4-2008-223539). R.A. is supported by the European Research Council (ERC-2008-AdG 233226) and by SystemsX.ch, the Swiss Initiative for Systems Biology.

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Author notes

  1. Paola Picotti, Mathieu Clément-Ziza and Henry Lam: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich CH-8093, Switzerland,

    Paola Picotti, Hannes Röst, Oliver Rinner, Lukas Reiter, Qin Shen, Andreas Frei, Bernd Wollscheid & Ruedi Aebersold

  2. Department of Biology, Institute of Biochemistry, ETH Zurich, Zurich CH-8093, Switzerland,

    Paola Picotti

  3. Biotechnology Centre, Technische Universitaet Dresden, D-01069 Dresden, Germany,

    Mathieu Clément-Ziza, Jacob J. Michaelson & Andreas Beyer

  4. Department of Chemical and Biomolecular Engineering and Division of Biomedical Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong,

    Henry Lam

  5. Institute for Systems Biology, Seattle, 98103, Washington, USA

    David S. Campbell, Eric W. Deutsch, Zhi Sun, Ulrike Kusebauch & Robert L. Moritz

  6. Proteomics Core Facility Biozentrum, University of Basel, Klingelbergstrasse 50/70, CH-4056 Basel, Switzerland,

    Alexander Schmidt

  7. Biognosys AG, Zurich CH-8093, Switzerland,

    Oliver Rinner & Lukas Reiter

  8. Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, 200031, China

    Qin Shen

  9. Max Planck Institute of Molecular Cell Biology and Genetics, D-01307 Dresden, Germany,

    Simon Alberti

  10. Competence Center for Systems Physiology and Metabolic Diseases, Zurich CH-8093, Switzerland,

    Ruedi Aebersold

  11. Faculty of Science, University of Zurich, Zurich CH-8057, Switzerland,

    Ruedi Aebersold

Authors
  1. Paola Picotti
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  2. Mathieu Clément-Ziza
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Contributions

P.P. and M.C.-Z. carried out the experiments; M.C.-Z., H.L., E.W.D., O.R., L.R., P.P., J.J.M., A.B. and R.A. conceived the data analysis pipeline; P.P., M.C.-Z., H.L., D.S.C., A.S., E.W.D., H.R., Z.S., O.R., L.R., J.J.M. and Q.S. analysed the data; A.S., A.F., Q.S. and U.K. performed mass-spectrometry measurements; P.P., A.B., M.C.-Z., S.A. and R.A. designed the experiments; P.P., M.C.-Z., A.B., H.L., H.R., S.A. and R.A. wrote the manuscript; B.W. and R.L.M. supervised part of the project; and R.A., A.B. and P.P. supervised the project.

Corresponding authors

Correspondence to Paola Picotti, Andreas Beyer or Ruedi Aebersold.

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Competing interests

O.R. and L.R. are employees of Biognosys AG, Switzerland.

Supplementary information

Supplementary Information

This file contains a Supplementary Discussion, Supplementary Figures 1-20, Supplementary Text and Data, Supplementary Tables 1-4, Supplementary Methods and additional references. (PDF 3718 kb)

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Picotti, P., Clément-Ziza, M., Lam, H. et al. A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis. Nature 494, 266–270 (2013). https://doi.org/10.1038/nature11835

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