Kinetic Models in Industrial Biotechnology
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Metabolic Engineering ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 1 Contents lists available at ScienceDirect 2 3 4 Metabolic Engineering 5 6 journal homepage: www.elsevier.com/locate/ymben 7 8 9 Minireview 10 11 – 12 Kinetic models in industrial biotechnology Improving cell 13 factory performance 14 15 Joachim Almquist a,b,n, Marija Cvijovic c,d, Vassily Hatzimanikatis e, Jens Nielsen b, 16 a Q1 17 Mats Jirstrand 18 a Fraunhofer-Chalmers Centre, Chalmers Science Park, SE-412 88 Göteborg, Sweden 19 b Systems and Synthetic Biology, Department of Chemical and Biological Engineering, Chalmers University of Technology, SE-412 96 Göteborg, Sweden c ̈ 20 Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, SE-412 96 Go teborg, Sweden d Mathematical Sciences, University of Gothenburg, SE-412 96 Göteborg, Sweden 21 Q4 e Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Federale de Lausanne, CH 1015 Lausanne, Switzerland 22 23 24 article info abstract 25 26 Article history: An increasing number of industrial bioprocesses capitalize on living cells by using them as cell factories 27 Received 11 September 2013 that convert sugars into chemicals. These processes range from the production of bulk chemicals in 28 Received in revised form yeasts and bacteria to the synthesis of therapeutic proteins in mammalian cell lines. One of the tools in 29 7 March 2014 the continuous search for improved performance of such production systems is the development and Accepted 9 March 2014 30 application of mathematical models. To be of value for industrial biotechnology, mathematical models 31 should be able to assist in the rational design of cell factory properties or in the production processes in 32 Keywords: which they are utilized. Kinetic models are particularly suitable towards this end because they are Mathematical modeling capable of representing the complex biochemistry of cells in a more complete way compared to most 33 Kinetic models other types of models. They can, at least in principle, be used to in detail understand, predict, and 34 Dynamic models evaluate the effects of adding, removing, or modifying molecular components of a cell factory and for 35 Parameter estimation supporting the design of the bioreactor or fermentation process. However, several challenges still remain 36 Cell factory Industrial biotechnology before kinetic modeling will reach the degree of maturity required for routine application in industry. 37 Here we review the current status of kinetic cell factory modeling. Emphasis is on modeling 38 methodology concepts, including model network structure, kinetic rate expressions, parameter estima- 39 tion, optimization methods, identifiability analysis, model reduction, and model validation, but several 40 applications of kinetic models for the improvement of cell factories are also discussed. 41 & 2014 The Authors Published by Elsevier Inc. On behalf of International Metabolic Engineering Society. 42 This is an open access article under the CC BY-NC-SA license 43 (http://creativecommons.org/licenses/by-nc-sa/3.0/). 44 67 45 68 46 1. Introduction 2010 to 75 billion liters produced in 2012, but it has also resulted 69 47 in the introduction of novel processes for the production of 70 48 Throughout the World there is a desire to move towards chemicals that can be used for the production of polymers, e.g. 71 49 sustainable production of energy, fuels, materials and chemicals, lactic acid that goes into poly-lactate and 1,3 propanediol that goes 72 s 50 and biobased production of transportation fuels and chemicals is into Sorona . With these successes the chemical industry is 73 fi 51 expected to contribute signi cantly towards reaching this objec- looking into the development of other processes for the produc- 74 fi 52 tive. This has resulted in the advancement of industrial biotech- tion of platform chemicals that can nd application in the 75 53 nology, where microbial fermentation is used for the conversion of manufacturing of solvents and polymers. Traditionally the fermen- 76 54 bio-based feedstocks to fuels and chemicals (Nielsen and Jewett, tation industry used naturally producing microorganisms, but 77 55 2008; Tang and Zhao, 2009; Otero and Nielsen, 2010; Du et al., today there is a focus on using a few microorganisms, often 78 56 2011; Sauer and Mattanovich, 2012). Not only has this resulted in a referred to as platform cell factories, and then engineering their 79 fi fi 57 signi cant expansion of traditional processes such as bioethanol metabolism such that they ef ciently can produce the chemical of 80 58 production, which has increased from 10 billion liters produced in interest. This engineering process is referred to as metabolic 81 59 engineering, and it involves the introduction of directed genetic 82 fi 60 modi cations. Due to the complexity of microbial metabolism, 83 n both due to the large number of interacting reactions and the 61 Corresponding author at: Fraunhofer-Chalmers Centre, Chalmers Science Park, 84 62 SE-412 88 Göteborg, Sweden. complex regulation, there has been an increasing focus on the 85 fi 63 E-mail address: [email protected] (J. Almquist). use of mathematical models for the identi cation of metabolic 86 64 87 http://dx.doi.org/10.1016/j.ymben.2014.03.007 65 1096-7176/& 2014 The Authors Published by Elsevier Inc. On behalf of International Metabolic Engineering Society. This is an open access article under the CC BY-NC-SA 88 66 license (http://creativecommons.org/licenses/by-nc-sa/3.0/). 89 Please cite this article as: Almquist, J., et al., Kinetic models in industrial biotechnology – Improving cell factory performance. Metab. Eng. (2014), http://dx.doi.org/10.1016/j.ymben.2014.03.007i 2 J. Almquist et al. / Metabolic Engineering ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 1 engineering targets (Patil et al., 2004; Cvijovic et al., 2011; may be stationary or close to stationary, such as cell metabolism 67 2 Wiechert and Noack, 2011; Soh et al., 2012). during exponential phase, since they can relate the properties of a 68 3 Industrial biotechnology can benefit from mathematical mod- (quasi) steady-state to the kinetic properties of the model 69 4 els by using them to understand, predict, and optimize the components. 70 5 properties and behavior of cell factories (Tyo et al., 2010). With This review looks at the work-flow and methods for setting up, 71 6 valid models, improvement strategies can be discovered and analyzing, and using kinetic models, focusing on models and 72 7 evaluated in silico, saving both time and resources. Popular modeling methodology with relevance for industrial biotechnol- 73 8 application of models thus includes using them to suggest targets ogy. The paper is divided into three main parts. The first part 74 9 for metabolic engineering leading to increases in yield, titer, and discusses and describes different aspects of the model building 75 10 productivity of a desired product. Since these quantities not only procedure, including defining the model focus, how to set up a 76 11 depend on the genetic constitution of cells but to a large extent model structure, determine parameter values and validate the 77 12 also on how the cells are utilized, models can additionally play a model. The second part looks at how kinetic models have been 78 13 critical role in the optimization and control of the bioreactor and used once they are set up. Applications of kinetic cell factory 79 14 fermentation processes. Other possible model focus includes models for improving production, substrate utilization, product 80 15 expanding the range of cell factory substrates, minimizing the quality, and process design are reviewed. In the last part, a number 81 16 formation of undesired by-products, increasing product quality, of advantages and challenges of kinetic modeling are listed and 82 17 and guidance in the choice of cell factory when introducing a some future perspectives of kinetic modeling in biotechnology are 83 18 novel product. discussed. A complete overview of the organization can be found 84 19 Many biological processes or systems of importance to biotech- in Table 1. To increase the readability, especially for readers who 85 20 nology, such as the metabolism of a cell culture during a fed-batch are not experienced modelers, parts of the material which are of 86 21 process, cellular stress responses, or the decision making during the technical or mathematical nature are displayed in special boxes. 87 22 cell cycle, are non-stationary in their nature. These systems are The models and methods on which this review has been based 88 23 characterized by their dependence on time and the fact that the have been supplied by the partners of SYSINBIO (Systems Biology 89 24 effect of inputs to the systems depends on the systems history. The as a Driver for Industrial Biotechnology, a coordination and 90 25 most common way of modeling such dynamic systems is to set up support action funded by the European commission within the 91 26 mathematical expressions for the rates at which biochemical reac- seventh framework programme) and through a thorough litera- 92 27 tions of the systems are taking place. The reaction kinetics are then ture review. 93 28 used to form mass balance equations which in turn describe the 94 29 temporal behavior of all biochemical species present in the modeled 95 30 system. Mathematical models of this type are usually referred to as 96 31 kinetic models but the literature sometimes tends to use the terms 2. Setting up kinetic models – Modeling framework 97 32 dynamic and kinetic models interchangeably due to their largely 98 33 overlapping concepts as far as biological models are concerned. The kinetic modeling procedure can be divided into a number 99 34 Reaction kinetics being the fundamental building block of kinetic of steps which are illustrated in Fig.