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Global analysis of protein expression in yeast

Author

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  • Sina Ghaemmaghami

    (University of California–San Francisco
    University of California–San Francisco)

  • Won-Ki Huh

    (University of California–San Francisco
    Biochemistry & Biophysics, University of California–San Francisco)

  • Kiowa Bower

    (University of California–San Francisco
    University of California–San Francisco)

  • Russell W. Howson

    (University of California–San Francisco
    Biochemistry & Biophysics, University of California–San Francisco)

  • Archana Belle

    (University of California–San Francisco
    Biochemistry & Biophysics, University of California–San Francisco)

  • Noah Dephoure

    (University of California–San Francisco
    Biochemistry & Biophysics, University of California–San Francisco)

  • Erin K. O'Shea

    (University of California–San Francisco
    Biochemistry & Biophysics, University of California–San Francisco)

  • Jonathan S. Weissman

    (University of California–San Francisco
    University of California–San Francisco)

Abstract

The availability of complete genomic sequences and technologies that allow comprehensive analysis of global expression profiles of messenger RNA1,2,3 have greatly expanded our ability to monitor the internal state of a cell. Yet biological systems ultimately need to be explained in terms of the activity, regulation and modification of proteins—and the ubiquitous occurrence of post-transcriptional regulation makes mRNA an imperfect proxy for such information. To facilitate global protein analyses, we have created a Saccharomyces cerevisiae fusion library where each open reading frame is tagged with a high-affinity epitope and expressed from its natural chromosomal location. Through immunodetection of the common tag, we obtain a census of proteins expressed during log-phase growth and measurements of their absolute levels. We find that about 80% of the proteome is expressed during normal growth conditions, and, using additional sequence information, we systematically identify misannotated genes. The abundance of proteins ranges from fewer than 50 to more than 106 molecules per cell. Many of these molecules, including essential proteins and most transcription factors, are present at levels that are not readily detectable by other proteomic techniques nor predictable by mRNA levels or codon bias measurements.

Suggested Citation

  • Sina Ghaemmaghami & Won-Ki Huh & Kiowa Bower & Russell W. Howson & Archana Belle & Noah Dephoure & Erin K. O'Shea & Jonathan S. Weissman, 2003. "Global analysis of protein expression in yeast," Nature, Nature, vol. 425(6959), pages 737-741, October.
    • Handle: RePEc:nat:nature:v:425:y:2003:i:6959:d:10.1038_nature02046
    DOI: 10.1038/nature02046
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    1. Jae Kyoung Kim & Eduardo D Sontag, 2017. "Reduction of multiscale stochastic biochemical reaction networks using exact moment derivation," PLOS Computational Biology, Public Library of Science, vol. 13(6), pages 1-24, June.
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    11. Shinsuke Ohnuki & Yoshikazu Ohya, 2018. "High-dimensional single-cell phenotyping reveals extensive haploinsufficiency," PLOS Biology, Public Library of Science, vol. 16(5), pages 1-23, May.
    12. Ying Xiong & Weijing Han & Chunhua Xu & Jing Shi & Lisha Wang & Taoli Jin & Qi Jia & Ying Lu & Shuxin Hu & Shuo-Xing Dou & Wei Lin & Terence R. Strick & Shuang Wang & Ming Li, 2024. "Single-molecule reconstruction of eukaryotic factor-dependent transcription termination," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    13. Rok Grah & Tamar Friedlander, 2020. "The relation between crosstalk and gene regulation form revisited," PLOS Computational Biology, Public Library of Science, vol. 16(2), pages 1-24, February.
    14. Yang-Nim Park & David Morales & Emily H Rubinson & Daniel Masison & Evan Eisenberg & Lois E Greene, 2012. "Differences in the Curing of [PSI+] Prion by Various Methods of Hsp104 Inactivation," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-15, June.
    15. Morgane Boone & Pathmanaban Ramasamy & Jasper Zuallaert & Robbin Bouwmeester & Berre Moer & Davy Maddelein & Demet Turan & Niels Hulstaert & Hannah Eeckhaut & Elien Vandermarliere & Lennart Martens & , 2021. "Massively parallel interrogation of protein fragment secretability using SECRiFY reveals features influencing secretory system transit," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    16. Anneke Brümmer & Carlos Salazar & Vittoria Zinzalla & Lilia Alberghina & Thomas Höfer, 2010. "Mathematical Modelling of DNA Replication Reveals a Trade-off between Coherence of Origin Activation and Robustness against Rereplication," PLOS Computational Biology, Public Library of Science, vol. 6(5), pages 1-13, May.
    17. Hyunju Cho & Yumeng Liu & SangYoon Chung & Sowmya Chandrasekar & Shimon Weiss & Shu-ou Shan, 2024. "Dynamic stability of Sgt2 enables selective and privileged client handover in a chaperone triad," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
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    20. Alexey A Gritsenko & Marc Hulsman & Marcel J T Reinders & Dick de Ridder, 2015. "Unbiased Quantitative Models of Protein Translation Derived from Ribosome Profiling Data," PLOS Computational Biology, Public Library of Science, vol. 11(8), pages 1-26, August.
    21. Emma Pierson & the GTEx Consortium & Daphne Koller & Alexis Battle & Sara Mostafavi, 2015. "Sharing and Specificity of Co-expression Networks across 35 Human Tissues," PLOS Computational Biology, Public Library of Science, vol. 11(5), pages 1-19, May.
    22. Ulises H. Guzman & Henriette Aksnes & Rasmus Ree & Nicolai Krogh & Magnus E. Jakobsson & Lars J. Jensen & Thomas Arnesen & Jesper V. Olsen, 2023. "Loss of N-terminal acetyltransferase A activity induces thermally unstable ribosomal proteins and increases their turnover in Saccharomyces cerevisiae," Nature Communications, Nature, vol. 14(1), pages 1-16, December.

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