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.
%0 Journal Article
%1 Newman2006Singlecell
%A Newman, John R. S.
%A Ghaemmaghami, Sina
%A Ihmels, Jan
%A Breslow, David K.
%A Noble, Matthew
%A DeRisi, Joseph L.
%A Weissman, Jonathan S.
%D 2006
%I Nature Publishing Group
%J Nature
%K noise proteomics yeast-gene-dup
%N 7095
%P 840--846
%R 10.1038/nature04785
%T Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise
%U http://dx.doi.org/10.1038/nature04785
%V 441
%X 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.
@article{Newman2006Singlecell,
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.},
added-at = {2018-12-02T16:09:07.000+0100},
author = {Newman, John R. S. and Ghaemmaghami, Sina and Ihmels, Jan and Breslow, David K. and Noble, Matthew and DeRisi, Joseph L. and Weissman, Jonathan S.},
biburl = {https://www.bibsonomy.org/bibtex/2ad72d111a16e7cae1e9c5035068dff6f/karthikraman},
citeulike-article-id = {635145},
citeulike-linkout-0 = {http://dx.doi.org/10.1038/nature04785},
citeulike-linkout-1 = {http://dx.doi.org/10.1038/nature04785},
citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/16699522},
citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=16699522},
day = 14,
doi = {10.1038/nature04785},
interhash = {ce3156ddf199db50cc25593a4cb79eaa},
intrahash = {ad72d111a16e7cae1e9c5035068dff6f},
issn = {0028-0836},
journal = {Nature},
keywords = {noise proteomics yeast-gene-dup},
month = may,
number = 7095,
pages = {840--846},
pmid = {16699522},
posted-at = {2010-08-16 12:24:57},
priority = {2},
publisher = {Nature Publishing Group},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise},
url = {http://dx.doi.org/10.1038/nature04785},
volume = 441,
year = 2006
}