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PMID: 18953355 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S.

Activity motifs reveal principles of timing in transcriptional control of the yeast metabolic network.

Nature biotechnology ·Vol. 26 ·No. 11 ·2008-11-00 ·Pages 1251-9

Chechik G, Oh E, Rando O, Weissman J, Regev A, Koller D

Abstract

Significant insight about biological networks arises from the study of network motifs--overly abundant network subgraphs--but such wiring patterns do not specify when and how potential routes within a cellular network are used. To address this limitation, we introduce activity motifs, which capture patterns in the dynamic use of a network. Using this framework to analyze transcription in Saccharomyces cerevisiae metabolism, we find that cells use different timing activity motifs to optimize transcription timing in response to changing conditions: forward activation to produce metabolic compounds efficiently, backward shutoff to rapidly stop production of a detrimental product and synchronized activation for co-production of metabolites required for the same reaction. Measuring protein abundance over a time course reveals that mRNA timing motifs also occur at the protein level. Timing motifs significantly overlap with binding activity motifs, where genes in a linear chain have ordered binding affinity to a transcription factor, suggesting a mechanism for ordered transcription. Finely timed transcriptional regulation is therefore abundant in yeast metabolism, optimizing the organism's adaptation to new environmental conditions.

MeSH Terms
Gene Expression Profiling Gene Expression Regulation, Fungal Glycerol/metabolism Metabolic Networks and Pathways Pentose Phosphate Pathway RNA, Messenger/chemistry,genetics,metabolism Saccharomyces cerevisiae/genetics,metabolism,physiology Saccharomyces cerevisiae Proteins/chemistry,genetics,metabolism Time Factors Transcription, Genetic
Chemicals
RNA, Messenger Saccharomyces cerevisiae Proteins Glycerol
Authors & Affiliations
6 authors, click to expand affiliations / ORCID
Chechik Gal
Department of Computer Science, Stanford University, Stanford, California 94305, USA.
Oh Eugene
Rando Oliver
Weissman Jonathan
Regev Aviv
Koller Daphne
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Article Info
Journal
Nature biotechnology
Abbr.
Nat Biotechnol
ISSN
1546-1696
Published
2008-11-00
Pages
1251-9
Language
English
Region
United States
NLM ID
9604648
PMCID
PMC2651818
Subset
IM
Grants
NIGMS NIH HHS · R01 GM079205 · United States
NIGMS NIH HHS · R01 GM079205-01A2 · United States
Howard Hughes Medical Institute · United States
Databases
GEO
Corrections
CommentIn
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