Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise

A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast...

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Published in	Nature Vol. 441; no. 7095; pp. 840 - 846
Main Authors	Newman, J.R.S, Ghaemmaghami, S, Ihmels, J, Breslow, D.K, Noble, M, DeRisi, J.L, Weissman, J.S
Format	Journal Article
Language	English
Published	London Nature Publishing 15.06.2006 Nature Publishing Group
Subjects	Biological and medical sciences cells Cellular biology Culture Media - pharmacology Deoxyribonucleic acid DNA Flow Cytometry Fundamental and applied biological sciences. Psychology fungal proteins Measurement techniques Microbiology Mycological methods and techniques used in mycology Mycology Noise protein composition Proteins proteome Proteome - genetics Proteome - metabolism Proteomics Reproducibility of Results Ribonucleic acid RNA RNA, Fungal - genetics RNA, Fungal - metabolism RNA, Messenger - genetics RNA, Messenger - metabolism Saccharomyces cerevisiae Saccharomyces cerevisiae - cytology Saccharomyces cerevisiae - drug effects Saccharomyces cerevisiae - genetics Saccharomyces cerevisiae - metabolism Saccharomyces cerevisiae Proteins - genetics Saccharomyces cerevisiae Proteins - metabolism single-cell proteome Stochastic Processes Time Factors yeasts Fungi Yeast Investigation method Proteome Ascomycetes Saccharomyces cerevisiae Protein Thallophyta
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Abstract	A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of >2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation.
AbstractList	A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of >2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation. A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of 2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation. [PUBLICATION ABSTRACT] A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring protein abundances and their variation. Here we present a strategy that pairs high-throughput flow cytometry and a library of GFP-tagged yeast strains to monitor rapidly and precisely protein levels at single-cell resolution. Bulk protein abundance measurements of >2,500 proteins in rich and minimal media provide a detailed view of the cellular response to these conditions, and capture many changes not observed by DNA microarray analyses. Our single-cell data argue that noise in protein expression is dominated by the stochastic production/destruction of messenger RNAs. Beyond this global trend, there are dramatic protein-specific differences in noise that are strongly correlated with a protein's mode of transcription and its function. For example, proteins that respond to environmental changes are noisy whereas those involved in protein synthesis are quiet. Thus, these studies reveal a remarkable structure to biological noise and suggest that protein noise levels have been selected to reflect the costs and potential benefits of this variation.
Audience	Academic
Author	DeRisi, J.L Ghaemmaghami, S Noble, M Newman, J.R.S Ihmels, J Breslow, D.K Weissman, J.S
Author_xml	– sequence: 1 fullname: Newman, J.R.S – sequence: 2 fullname: Ghaemmaghami, S – sequence: 3 fullname: Ihmels, J – sequence: 4 fullname: Breslow, D.K – sequence: 5 fullname: Noble, M – sequence: 6 fullname: DeRisi, J.L – sequence: 7 fullname: Weissman, J.S
BackLink	http://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=17859025$$DView record in Pascal Francis https://www.ncbi.nlm.nih.gov/pubmed/16699522$$D View this record in MEDLINE/PubMed
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ContentType	Journal Article
Copyright	2006 INIST-CNRS COPYRIGHT 2006 Nature Publishing Group Copyright Nature Publishing Group Jun 15, 2006
Copyright_xml	– notice: 2006 INIST-CNRS – notice: COPYRIGHT 2006 Nature Publishing Group – notice: Copyright Nature Publishing Group Jun 15, 2006
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Snippet	A major goal of biology is to provide a quantitative description of cellular behaviour. This task, however, has been hampered by the difficulty in measuring...
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SubjectTerms	Biological and medical sciences cells Cellular biology Culture Media - pharmacology Deoxyribonucleic acid DNA Flow Cytometry Fundamental and applied biological sciences. Psychology fungal proteins Measurement techniques Microbiology Mycological methods and techniques used in mycology Mycology Noise protein composition Proteins proteome Proteome - genetics Proteome - metabolism Proteomics Reproducibility of Results Ribonucleic acid RNA RNA, Fungal - genetics RNA, Fungal - metabolism RNA, Messenger - genetics RNA, Messenger - metabolism Saccharomyces cerevisiae Saccharomyces cerevisiae - cytology Saccharomyces cerevisiae - drug effects Saccharomyces cerevisiae - genetics Saccharomyces cerevisiae - metabolism Saccharomyces cerevisiae Proteins - genetics Saccharomyces cerevisiae Proteins - metabolism single-cell proteome Stochastic Processes Time Factors yeasts
Title	Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise
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