A theory of optimal differential gene expression

• Published in: BioSystems Vol. 76; no. 1; pp. 261 - 278
• Main Authors: Liebermeister, Wolfram, Klipp, Edda, Schuster, Stefan, Heinrich, Reinhart
• Format: Journal Article
• Language: English
• Published: Ireland Elsevier Ireland Ltd 01.08.2004
• Subjects: Adaptation, Physiological - physiology; Animals; Cell Physiological Phenomena; Feedback - physiology; Gene expression; Gene Expression Regulation - physiology; Gene function; Genes, Regulator - genetics; Genetic regulation; Humans; Linear model; Metabolic control analysis; Models, Genetic; Multienzyme Complexes - metabolism; Optimality principle; Signal Transduction - physiology; Transcription Factors - metabolism; Gene function; Optimality principle; Gene expression; Genetic regulation; Linear model; Metabolic control analysis
• ISSN: 0303-2647; 1872-8324
• DOI: 10.1016/j.biosystems.2004.05.022

We investigate a model of optimal regulation, intended to describe large-scale differential gene expression. Relations between the optimal expression patterns and the function of genes are deduced from an optimality principle: the regulators have to maximise a fitness function which they influence directly via a cost term, and indirectly via their control on important cell variables, such as metabolic fluxes. According to the model, the optimal linear response to small perturbations reflects the regulators’ functions, namely their linear influences on the cell variables. The optimal behaviour can be realised by a linear feedback mechanism. Known or assumed properties of response coefficients lead to predictions about regulation patterns. A symmetry relation predicted for deletion experiments is verified with gene expression data. Where the optimality assumption is valid, our results justify the use of expression data for functional annotation and for pathway reconstruction and suggest the use of linear factor models for the analysis of gene expression data.