Modeling of Escherichia coli growth and acetate formation under different operational conditions

Guardia, María Jesús; García‐Calvo, Eloy

doi:10.1016/s0141-0229(01)00413-6

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…In DMglucose and DM50:50, maximum growth rate, lag, and switching optical density are estimated. Because glucose catabolism produces acetate in E. coli (Guardia and Calvo 2001), switching density in DMglucose is the point where cells exhaust the supplied glucose. In DM90:10, first maximum growth rate, first lag, switching optical density, second maximum growth rate, and switching lag are estimated.…”

Section: Discussionmentioning

confidence: 99%

Experimental Evidence for Sympatric Ecological Diversification Due to Frequency-Dependent Competition in Escherichia Coli

et al. 2004

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Abstract. We investigate adaptive diversification in experimental Escherichia coli populations grown in serial batch cultures on a mixture of glucose and acetate. All 12 experimental lines were started from the same genetically uniform ancestral strain but became highly polymorphic for colony size after 1000 generations. Five populations were clearly dimorphic and thus serve as a model for an adaptive lineage split. We analyzed the ecological basis for this dimorphism by studying bacterial growth curves. All strains exhibit diauxie, that is, sequential growth on the two resources. Thus, they exhibit phenotypic plasticity, using mostly glucose when glucose is abundant, then switching to acetate when glucose concentration is low. However, the coexisting strains differ in their diauxie pattern, with one cluster in the dimorphic populations growing better in the glucose phase, and the other cluster having a much shorter lag when switching to the acetate phase. Using invasion experiments, we show that the dimorphism of these two ecological types is maintained by frequency-dependent selection. Using a mathematical model for the adaptive dynamics of diauxie behavior, we show that evolutionary branching in diauxie behavior is a plausible theoretical scenario. Our results support the hypothesis that, in our experiments, adaptive diversification from a genetically uniform ancestor occurred due to frequency-dependent ecological interactions. Our results have implications for understanding the evolution of cross-feeding polymorphism in microorganisms, as well as adaptive speciation due to frequency-dependent selection on phenotypic plasticity.

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Section: Discussionmentioning

confidence: 99%

Experimental Evidence for Sympatric Ecological Diversification Due to Frequency-Dependent Competition in Escherichia Coli

et al. 2004

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“…Diauxic growth represents the classical reprogramming of a metabolic network and has been extensively studied with mathematical modeling (Varma and Palsson, 1994b;Wong et al, 1997;Lendenmann and Egli, 1998;Guardia and Calvo, 2001). Ramkrishna and coworkers have also used the cybernetic modeling approach to model the diauxic growth of E. coli on mixtures of glucose and organic acids such as pyruvate, succinate, and fumarate (Ramakrishna et al, 1996;Narang et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

Dynamic Flux Balance Analysis of Diauxic Growth in Escherichia coli

Mahadevan

Edwards

Doyle

2002

Biophysical Journal

835

855

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Flux Balance Analysis (FBA) has been used in the past to analyze microbial metabolic networks. Typically, FBA is used to study the metabolic flux at a particular steady state of the system. However, there are many situations where the reprogramming of the metabolic network is important. Therefore, the dynamics of these metabolic networks have to be studied. In this paper, we have extended FBA to account for dynamics and present two different formulations for dynamic FBA. These two approaches were used in the analysis of diauxic growth in Escherichia coli. Dynamic FBA was used to simulate the batch growth of E. coli on glucose, and the predictions were found to qualitatively match experimental data. The dynamic FBA formalism was also used to study the sensitivity to the objective function. It was found that an instantaneous objective function resulted in better predictions than a terminal-type objective function. The constraints that govern the growth at different phases in the batch culture were also identified. Therefore, dynamic FBA provides a framework for analyzing the transience of metabolism due to metabolic reprogramming and for obtaining insights for the design of metabolic networks.

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“…The growth of E. coli on glucose and acetate exhibits the mixed-substrate growth pattern of diauxic growth. Diauxic growth has been mathematically modeled and studied earlier using various approaches such as flux balance analysis (FBA) (Varma and Palsson (1994)), cybernetic modeling (Ramakrishna et al (1996)), kinetic modeling (Xu et al (1999), Guardia and Calvo (2001), Bettenbrock et al (2006)), static optimizationbased dynamic flux balance analysis (DFBA), and dynamic optimization-based dynamic flux balance analysis (Mahadevan et al (2002)). Amongst all, the dynamic optimization-based DFBA approach appears to be a lot more promising (Hjersted and Henson (2006), Hjersted and Henson (2009)) and hence this approach has been undertaken for our present study (from now on, DFBA would imply the dynamic optimization-based DFBA).…”

Section: Introductionmentioning

confidence: 99%

Study of the growth of Escherichia coli on mixed substrates using dynamic flux balance analysis

Joy

Kremling

2010

IFAC Proceedings Volumes

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Escherichia coli produces acetate as the major by-product when grown in a batch culture medium of glucose under aerobic conditions. The secreted acetate can be used as an additional substrate for cell growth leading to a mixed-substrate growth pattern of diauxic growth. However the acetate formed can limit growth of the organism if found in high amounts in the culture medium and such a scenario necessitates the study of the growth of microorganisms on mixed substrates. Dynamic flux balance analysis has turned out to be a promising tool in capturing such scenarios of growth on mixed substrates. In this study we carry out a dynamic flux balance analysis study of the growth of Escherichia coli in a batch culture medium of glucose and acetate where the organism encounters the presence of mixed substrates. Additionally we have used a detailed metabolic network to describe the process of metabolism in the organism Escherichia coli. DFBA combined with such detailed metabolic networks can open up possibilities of preventing such harmful growth scenarios for biotechnologically useful micro-organisms.

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Modeling of Escherichia coli growth and acetate formation under different operational conditions

Cited by 6 publications

References 13 publications

Experimental Evidence for Sympatric Ecological Diversification Due to Frequency-Dependent Competition in Escherichia Coli

Experimental Evidence for Sympatric Ecological Diversification Due to Frequency-Dependent Competition in Escherichia Coli

Dynamic Flux Balance Analysis of Diauxic Growth in Escherichia coli

Study of the growth of Escherichia coli on mixed substrates using dynamic flux balance analysis

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