Negative autoregulation linearizes the dose–response and suppresses the heterogeneity of gene expression
| Autor: | Krešimir Josić, Rhys M. Adams, Gábor Balázsi, Dmitry Nevozhay, Kevin F. Murphy |
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| Rok vydání: | 2009 |
| Předmět: |
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Physiological Reporter gene Multidisciplinary Transcription Genetic Gene regulatory network Computational Biology Repressor Saccharomyces cerevisiae Tetracycline Biology Molecular biology Cell biology Repressor Proteins chemistry.chemical_compound chemistry Gene Expression Regulation Fungal Negative feedback Physical Sciences Gene expression Computer Simulation Gene Regulatory Networks TetR Autoregulation Gene |
| Zdroj: | Proceedings of the National Academy of Sciences. 106:5123-5128 |
| ISSN: | 1091-6490 0027-8424 |
| DOI: | 10.1073/pnas.0809901106 |
| Popis: | Although several recent studies have focused on gene autoregulation, the effects of negative feedback (NF) on gene expression are not fully understood. Our purpose here was to determine how the strength of NF regulation affects the characteristics of gene expression in yeast cells harboring chromosomally integrated transcriptional cascades that consist of the yEGFP reporter controlled by ( i ) the constitutively expressed tetracycline repressor TetR or ( ii ) TetR repressing its own expression. Reporter gene expression in the cascade without feedback showed a steep (sigmoidal) dose–response and a wide, nearly bimodal yEGFP distribution, giving rise to a noise peak at intermediate levels of induction. We developed computational models that reproduced the steep dose–response and the noise peak and predicted that negative autoregulation changes reporter expression from bimodal to unimodal and transforms the dose–response from sigmoidal to linear. Prompted by these predictions, we constructed a “linearizer” circuit by adding TetR autoregulation to our original cascade and observed a massive (7-fold) reduction of noise at intermediate induction and linearization of dose–response before saturation. A simple mathematical argument explained these findings and indicated that linearization is highly robust to parameter variations. These findings have important implications for gene expression control in eukaryotic cells, including the design of synthetic expression systems. |
| Databáze: | OpenAIRE |
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