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 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.
Newman
John R S
JR
Howard Hughes Medical Institute, San Francisco, California, USA. jrsnewman@alum.mit.edu
Ghaemmaghami
Sina
S
Ihmels
Jan
J
Breslow
David K
DK
Noble
Matthew
M
DeRisi
Joseph L
JL
Weissman
Jonathan S
JS
D003470:Culture Media / Q000494:pharmacology; D005434:Flow Cytometry; D020543:Proteome / Q000235:genetics / Q000378:metabolism*; D040901:Proteomics; D012331:RNA, Fungal / Q000235:genetics / Q000378:metabolism; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D015203:Reproducibility of Results; D012441:Saccharomyces cerevisiae / Q000166:cytology* / Q000187:drug effects / Q000235:genetics / Q000378:metabolism*; D029701:Saccharomyces cerevisiae Proteins / Q000235:genetics / Q000378:metabolism*; D013269:Stochastic Processes; D013997:Time Factors
D003470:Culture Media; D020543:Proteome; D012331:RNA, Fungal; D012333:RNA, Messenger; D029701:Saccharomyces cerevisiae Proteins