Dynamic change in promoter activation during lysine biosynthesis in Escherichia coli cells

Ou, Jianhong; Yamada, Tadashi; Nagahisa, Keisuke; Hirasawa, Takashi; Furusawa, Chikara; Yomo, Tetsuya; Shimizu, Hiroshi

doi:10.1039/b711035a

Cited by 15 publications

(12 citation statements)

References 25 publications

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“…A sequential or "just-in-time" pattern in enzyme expression was found in the Serine, Methionine and Arginine pathways. Additional experimental evidence revealing temporal modulation in the Lysine pathway has been recently reported (Ou et al, 2008). These experiments provide metabolic instances of the generally accepted fact that specific temporal patterns in gene expression appear in the operation of a range of cellular functions, including complex molecular assemblies (Kalir et al, 2001) and organism development (Leng and Müller, 2006).…”

Section: Introductionmentioning

confidence: 75%

Sequential Activation of Metabolic Pathways: a Dynamic Optimization Approach

et al. 2009

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The regulation of cellular metabolism facilitates robust cellular operation in the face of changing external conditions. The cellular response to this varying environment may include the activation or inactivation of appropriate metabolic pathways. Experimental and numerical observations of sequential timing in pathway activation have been reported in the literature. It has been argued that such patterns can be rationalized by means of an underlying optimal metabolic design. In this paper we pose a dynamic optimization problem that accounts for time-resource minimization in pathway activation under constrained total enzyme abundance. The optimized variables are time-dependent enzyme concentrations that drive the pathway to a steady state characterized by a prescribed metabolic flux. The problem formulation addresses unbranched pathways with irreversible kinetics. Neither specific reaction kinetics nor fixed pathway length are assumed.In the optimal solution, each enzyme follows a switching profile between zero and maximum concentration, following a temporal sequence that matches the pathway topology. This result provides an analytic justification of the sequential activation previously described in the literature. In contrast with the existent numerical approaches, the activation sequence is proven to be optimal for a generic class of monomolecular kinetics. This class includes, but is not limited to, Mass Action, Michaelis-Menten, Hill, and some Power-law models. This suggests that sequential enzyme expression may be a common feature of metabolic regulation, as it is a robust property of optimal pathway activation.

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Section: Introductionmentioning

confidence: 75%

Sequential Activation of Metabolic Pathways: a Dynamic Optimization Approach

et al. 2009

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“…Without excluding the numerous phenomena occurring at the transcriptional level, and considering the properties of GFPmut2, proteolysis can be involved in the fluorescence drop associated with scale-down effect. Indeed, GFPmut2 is a fast folding mutant of the original protein with a high stability, and it is generally assumed that the lifetime of this protein is longer than the cell cycle [ 51 ]. In our case, segregation phenomena, i.e.…”

Section: Discussionmentioning

confidence: 99%

Bioreactor mixing efficiency modulates the activity of a prpoS::GFP reporter gene in E. coli

et al. 2009

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Background: Extensive studies have shown that up-scaling of bioprocesses has a significant impact on the physiology of the microorganisms. Among the factors associated with the fluid dynamics of the bioreactor, concentration gradients induced by loss of the global mixing efficiency associated with the increasing scale is the main phenomena leading to strong physiological modifications at the level of the microbial population. These changes are not fully understood since they involve complex physiological mechanisms. In this work, we intend to investigate, at the single cell level, the expression of the rpoS gene associated with the stress response of E. coli. The cultures of the reporter strain have been performed in a small scale reactor as well as in a series of scaled-down bioreactors able to induce extracellular perturbations with increasing level of magnitude.

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“…These authors also showed that in the arginine, methionine and serine systems, the earlier the enzyme is involved in a pathway, the shorter is the response time and the higher the maximal promoter activity of the corresponding gene. Evidences of temporal distribution of enzymes were also found in the lysine biosynthesis pathway by E. coli [12]. Chechik et al [13] proposed the notion of activity motif to systematically study the dynamic behavior of metabolic networks.…”

Section: Introductionmentioning

confidence: 99%

Global dynamic optimization approach to predict activation in metabolic pathways

et al. 2014

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BackgroundDuring the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been succesfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework.ResultsIn this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results.ConclusionsThe proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints.

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Dynamic change in promoter activation during lysine biosynthesis in Escherichia coli cells

Cited by 15 publications

References 25 publications

Sequential Activation of Metabolic Pathways: a Dynamic Optimization Approach

Sequential Activation of Metabolic Pathways: a Dynamic Optimization Approach

Bioreactor mixing efficiency modulates the activity of a prpoS::GFP reporter gene in E. coli

Global dynamic optimization approach to predict activation in metabolic pathways

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