Engineering improved productivity of 1,4-butanediol in E. coli – a kinetic modeling approach

Microbial cell factories are becoming a norm for commercially viable production of chemicals for pharmaceutical, biotechnology, food and beverage industries. However, engineering of microbial cell factories requires a simultaneous optimization of several criteria such as productivity, yield, titer, stress tolerance, all the while retaining the efficient, cost-effective and robust process. One of the most prominent examples where a rational metabolic engineering strategy played a key role is in the production of 1,4-butanediol (BDO) in E. coli. In this study, we used the ORACLE (Optimization and Risk Analysis of Complex Living Entities) framework to analyze possible enhancements of the E. coli strain engineered for improved production of BDO. ORACLE framework allowed us to integrate thermodynamics, available omics and kinetic data into a population of large-scale kinetic models. Analysis of the engineered E. coli strain led to the identification of three critical modules within the metabolic network which contained the enzymes that primarily control the fluxes leading to BDO production. The enzymes in these modules are focused around: a) central glycolysis, b) the lower branch of tricarboxyclic acid cycle, and c) novel BDO production route. However, the manipulation of the enzymes in the identified modules - while possibly leading to the increased BDO production - had complex effects on other intracellular states like redox state, energy charge, cofactor levels, cellular growth and byproduct formation. We used the large-scale kinetic models generated by ORACLE to postulate successfully metabolic engineering alternatives for optimal performance with reduced byproduct secretion and fine-tuned redox balance, energy charge and cofactor levels. While in the current study, the aim was to improve BDO production, the methodology presented here can readily be applied to other products and organisms of interest.

Exploring enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models

Stefano Andreozzi, Anirikh Chakrabarti, Vassily Hatzimanikatis, Ljubisa Miskovic, Keng Cher Soh

Engineering of microbial cell factories requires a simultaneous optimization of several criteria such as productivity, yield, titer, stress tolerance, all the while retaining the efficient, cost-effective and robust process. One of the most prominent examples where a rational metabolic engineering strategy played a key role is in the production of 1,4-butanediol (BDO) in E. coli. In this study, we used the ORACLE (Optimization and Risk Analysis of Complex Living Entities) framework to analyze the physiology of metabolically engineered E. coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed the population of these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid cycle and the novel BDO production route. We also identified targets for metabolic engineering for improved BDO production and yield, while constraining other intracellular states within desired bounds. We further analyzed these models to predict the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth and byproduct formation. The conclusions of the performed analysis are consistent with the experimentally tested designs, and these results demonstrate the potential and effectiveness of ORACLE for the design of microbial cell factories.

2015

Exploring enhancement of 1,4-butanediol production in recombinant E. coli using Large-scale kinetic models

Stefano Andreozzi, Anirikh Chakrabarti, Vassily Hatzimanikatis, Ljubisa Miskovic

Rational metabolic engineering methods are increasingly employed in designing the commercially viable processes for the production of chemicals relevant to pharmaceutical, biotechnology, and food and beverage industries. With the growing availability of omics data and of methodologies capable to integrate the available data into models, mathematical modeling and computational analysis are becoming important in designing recombinant cellular organisms and optimizing cell performance with respect to desired criteria. In this contribution, we used the computational framework ORACLE[1] (Optimization and Risk Analysis of Complex Living Entities) to analyze the physiology of recombinant E. coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid cycle and the novel BDO production route. We further analyzed these models to predict the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth and byproduct formation. We also identified targets for metabolic engineering for improved BDO production and yield, while taking into consideration other intracellular states. The conclusions of the performed analysis are consistent with the experimentally tested designs, and these results demonstrate the potential and effectiveness of ORACLE for the design of microbial cell factories.

2016

Metabolic control analysis of the central carbon pathway in optimally grown E. coli

Stefano Andreozzi, Vassily Hatzimanikatis, Ljubisa Miskovic, Keng Cher Soh

The engineering of the metabolism requires the building of reliable kinetic models of the metabolic pathways through the integration of the information from heterogeneous data sources. Unfortunately, the quantitative knowledge about fluxes, mechanisms or kinetic parameters of the constituent reactions of the metabolic network is most of the times uncertain or missing, due to limitations in the measurement techniques of the relevant biological properties of the cell and variability in experimental conditions. In this contribution, we employ ORACLE (Optimization and Risk Analysis of Complex Living Entities), the computational framework for the analysis and optimization of metabolic networks that addresses these issues. ORACLE allows us to generate populations of kinetic models that account explicitly for the physico-chemical and thermodynamic features and constraints of metabolic networks. We show how ORACLE incorporates fluxomics and metabolomics data and constraints into the central carbon core model of E. coli to uncover its possible steady state behaviors, when the cells are cultivated under the physiological condition of optimal growth on different carbon sources, both anaerobically and aerobically. Alternative cases of possible intracellular flux and thermodynamic states, corresponding to the given experimental data, are identified and subsequently the kinetic analysis is performed to evaluate how the control over fluxes and concentrations is distributed over the metabolic network. We demonstrate that ORACLE methodology provides guidance for metabolic engineering in spite of uncertain/missing information in the local/global properties of the metabolic network, integrating a statistical account on the semi-quantitative available data with consistent thermodynamic information and plausible hypotheses.

2012

Exploring enhancement of 1,4-butanediol production in recombinant E. coli using Large-scale kinetic models

Stefano Andreozzi, Anirikh Chakrabarti, Vassily Hatzimanikatis, Ljubisa Miskovic

2016