(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

Fei He; Fromion, Vincent; Westerhoff, Hans V.
December 2013
BMC Systems Biology;2013, Vol. 7 Issue 1, p1
Academic Journal
Background Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the 'perfect' regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering.


Related Articles

  • Quantitative PCR based expression analysis on a nanoliter scale using polymer nano-well chips. Alexander Jung; Regine Schwartz; Matthias Lange; Michael Steinwand; Kenneth Livak; Hans Lehrach; Lajos Nyarsik // Biomedical Microdevices;Jun2007, Vol. 9 Issue 3, p307 

    Abstract  The analysis of gene expression is an essential element of functional genomics. Expression analysis is mainly based on DNA microarrays due to highly parallel readout and high throughput. Quantitative PCR (qPCR) based expression profiling is the gold standard for the precise...

  • Recent Computational Approaches to Understand Gene Regulation: Mining Gene Regulation In Silico. Abnizova, I.; Subhankulova, T.; Gilks, W. R. // Current Genomics;Apr2007, Vol. 8 Issue 2, p79 

    This paper reviews recent computational approaches to the understanding of gene regulation in eukaryotes. Cis-regulation of gene expression by the binding of transcription factors is a critical component of cellular physiology. In eukaryotes, a number of transcription factors often work together...

  • Lessons from a decade of integrating cancer copy number alterations with gene expression profiles. Huang, Norman; Shah, Parantu K.; Li, Cheng // Briefings in Bioinformatics;May2012, Vol. 13 Issue 3, p305 

    Over the last decade, multiple functional genomic datasets studying chromosomal aberrations and their downstream effects on gene expression have accumulated for several cancer types. A vast majority of them are in the form of paired gene expression profiles and somatic copy number alterations...

  • Sex-Specific Viability, Sex Linkage and Dominance in Genomic Imprinting. Van Cleve, Jeremy; Feldman, Marcus W. // Genetics;Jun2007, Vol. 176 Issue 2, p1101 

    Genomic imprinting is a phenomenon by which the expression of an allele at a locus depends on the parent of origin. Two different two-locus evolutionary models are presented in which a second locus modifies the imprinting status of the primary locus, which is tinder differential selection in...

  • An algorithm for chemical genomic profiling that minimizes batch effects: bucket evaluations. Shabtai, Daniel; Giaever, Guri; Nislow, Corey // BMC Bioinformatics;2012, Vol. 13 Issue 1, p1 

    Background: Chemical genomics is an interdisciplinary field that combines small molecule perturbation with traditional genomics to understand gene function and to study the mode(s) of drug action. A benefit of chemical genomic screens is their breadth; each screen can capture the sensitivity of...

  • Use of RNA interference libraries to investigate oncogenic signalling in mammalian cells. Downward, Julian // Oncogene;11/1/2004 Review, Vol. 23 Issue 51, p8376 

    Over the past decade,‘RNA interference’has emerged as a natural mechanism of silencing of gene expression. This ancient cellular antiviral response can be manipulated to provide an effective research tool to knock down the level of expression of selected target genes, providing a...

  • The Mitochondrial Genome of Higher Plants: Gene Expression Regulation. Khvorostov, I. B.; Ivanov, M. K.; Dymshits, G. M. // Molecular Biology;May2002, Vol. 36 Issue 3, p314 

    The multistep regulation of mitochondrial gene expression in higher plants is considered. Data are summarized that concern the structure and function of the transcription system, posttranscriptional changes in the mRNA structure, and other levels of expression regulation.

  • Gene association analysis: a survey of frequent pattern mining from gene expression data. Alves, Ronnie; Rodriguez-Baena, Domingo S.; Aguilar-Ruiz, Jesus S. // Briefings in Bioinformatics;Mar2010, Vol. 11 Issue 2, p210 

    Establishing an association between variables is always of interest in genomic studies. Generation of DNA microarray gene expression data introduces a variety of data analysis issues not encountered in traditional molecular biology or medicine. Frequent pattern mining (FPM) has been applied...

  • Functional embedding for the classification of gene expression profiles. Ping-Shi Wu; Müller, Hans-Georg // Bioinformatics;Feb2010, Vol. 26 Issue 4, p509 

    Motivation: Low sample size n high-dimensional large p data with n≪p are commonly encountered in genomics and statistical genetics. Ill-conditioning of the variance-covariance matrix for such data renders the traditional multivariate data analytical approaches unattractive. On the other...


Read the Article


Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics