Experimental and theoretical analysis of poly(β-hydroxybutyrate) formation and consumption in Ralstonia eutropha
Highlights
► We model PHB degradation as well as consumption in R. eutropha. ► We extended the HCM approach to take internal metabolites explicitly into account. ► Possibility of multiple steady states in continuous bio reactor were investigated. ► Influence of PHB consumption is analyzed and found to be crucial at low dilution rate.
Introduction
Poly(β-hydroxybutyrate) (PHB) is an organic polymer, which can be synthesized by many microorganisms and which serves as internal energy and carbon reserve material. Ralstonia eutropha is a well known bacterium for producing PHB [2]. It can accumulate PHB to more than 80% of its cell dry weight [3]. R. eutropha has been re-classified several times in the past. The history of classification includes the genera Hydrogenomonas, Alcaligenes, Ralstonia, Wautersia and recently Cupriavidus necator. To avoid confusion, we will use the name Ralstonia throughout, since it is still commonly used in the literature, including very recent articles.
Production of PHB is favored under limitation of key nutrients such as nitrogen, phosphate or oxygen. PHB belongs to the group of polyhydroxyalkanoates (PHA) and provides an attractive source of bioplastics that are biodegradable, biocompatible and do not depend on fossil resources.
PHB production in R. eutropha has previously been modeled by a few researchers. These models can be divided into two classes: (a) models which do not consider internal regulation, e.g. [4], [5] and (b) models which do consider cell internal regulation. Internal regulation can be included into modeling by the cybernetic framework, which was introduced by Ramkrishna and co-workers [6], [7], [8]. The cybernetic approach for modeling PHB production in R. eutropha was used by Yoo and Kim [9]. They have used a very simple unstructured model and compared their results with unstructured non-cybernetic models of Mulchandani et al. [5] and Asenjo and Suk [4]. Their model could successfully predict PHB production, but did not include the underlying metabolic processes. Gadkar et al. [10] addressed this discrepancy and used a structured cybernetic model to develop a model predictive control for continuous PHB production. Although they considered the metabolic pathways by which the carbon and nitrogen sources are utilized these pathways are still lumped. The cybernetic model by Pinto and Immanuel [11] is also based on a very simplified metabolic network with less complexity than the model of Gadkar et al. [10] and was used for bifurcation analysis. It was shown, that the model structure admits multiple steady states in a continuous bio reactor, depending on the parameter values.
All these models are based on a more or less simplified metabolic network and either neglect PHB consumption or have fitted parameter to experimental data which do not contain any significant PHB consumption. But since PHB is an internal storage material, it is appropriate to consider its metabolism as a cycle of synthesis and consumption.
In the current work the PHB consumption is included into a cybernetic model and experiments were performed which show significant consumption to gain more reliable parameters. Additionally an expanded metabolic network is considered to include more internal metabolic information. The model is based on the state of the art hybrid cybernetic approach (HCM) by Kim et al. [1]. The HCM approach allows a systematic derivation of the model equations from elementary mode analysis [12]. It is based on quasi-stationarity of internal metabolites, which are eliminated from the model equations. However, this approach is not suitable for PHB production, since PHB is an internal metabolite, which has to be included explicitly into the model equations. In contrast to this, the more detailed approach by Young et al. [13] takes the dynamics of internal metabolites into account and could also handle synthesis and consumption of PHB. But this approach is computationally more expensive and requires detailed information about internal kinetics, which might be hard to obtain in particular for larger networks. To overcome these limitations this article presents a compromise between the standard HCM and the cybernetic modeling approach by Young et al. [13], by taking the dynamics of a few internal metabolites explicitly into account, while for most of the internal metabolites the quasi-steady state approximation is still applied.
It is shown that the model is in good agreement with experimental observations, where PHB formation and consumption are stimulated separately.
In industrial production usually fed batch or continuous processes are used. While fed batch processes allow for higher biomass and product yield, a continuous process can also be advantageous due to longer periods of operating time, which can reduce production costs. However, in continuous operating mode metabolic reactions will occur simultaneously, which can lead to nonlinear phenomenas, e.g. oscillations [14], [15], multiple steady states [16], [17], [18], etc.
The occurrence of multiple steady states in a PHB production process with R. eutropha was discussed by Pinto and Immanuel [11] based on a simplified model. Following their idea, the model is therefore afterwards used to investigate the possibility of multiple steady states in a continuous bio reactor. It is shown that multiple steady states are unlikely to occur in practice for this specific system. Furthermore, the influence of PHB consumption is analyzed, which is usually of minor importance in a batch process, since there is usually sufficient carbon source available and PHB will not be consumed. But in continuous processes PHB consumption can have crucial influence, as shown in this study. Even in a fed batch process PHB consumption can be of great importance if other growth essential nutrients than carbon are fed to the fermenter and PHB consumption will be stimulated. It is therefore necessary to include PHB consumption into modeling, if a fed batch or continuous process is used.
Section snippets
Microorganisms and medium
The organism used throughout this study, R. eutropha (DSM 428, ATCC 17699, NCIB 10442) was obtained from DSMZ GmbH Braunschweig, Germany, as vacuum dried culture. The strain was cultivated with the medium given in Table 1. All chemicals were from Carl Roth GmbH (Karlsruhe, Germany).
Cultivation conditions
R. eutropha was grown heterotrophically in a 7 L fermenter (Biostat C, Sartorius, BBI Systems, Melsungen, Germany) with a 5 L working volume. The temperature was kept constant at 30 ° C and the pH was automatically
PHB synthesis and consumption
Most models in literature have neglected PHB consumption since they are usually interested only in the synthesis of PHB. However, consumption might be crucial, especially in continuous processes, since it may lower the yield of PHB and degradable PHB can be viewed as an additional substrate. Even in fed batch processes PHB consumption has to be considered if nutrients are fed to the fermenter which will stimulate growth. To identify model parameters experiments were done which include both, the
Acknowledgments
A. Franz and A. Kienle appreciate the financial support of the German Federal Ministry for Education and Research (BMBF) under the FORSYS program. The technical support of Ruxandra Rehner during the experiments is greatly acknowledged.
References (34)
- et al.
Cybernetic model of the growth dynamics of Saccharomyces cerevisiae in batch and continuous cultures
J. Biotechnol.
(1999) - et al.
Dynamics and modeling on fermentative production of poly (beta-hydroxybutyric acid) from sugars via lactate by a mixed culture of Lactobacillus delbrueckii and Alcaligenes eutrophus
J. Biotechnol.
(1999) - et al.
Phbv production by Ralstonia eutropha in a continuous stirred tank reactor
Process. Biochem.
(2005) - et al.
Optimization of nutrient feed concentration and addition time for production of poly(beta-hydroxybutyrate)
Enzyme Microb. Technol.
(2006) - et al.
Nonlinear computation in DIVA–methods and applications
Chem. Eng. Sci.
(2000) - et al.
Multiplicity and stability of steady states in continuous bioreactors: dissection of cybernetic models
Chem. Eng. Sci.
(2001) Simulation and optimisation of PHB production in fed-batch culture of Ralstonia eutropha
Process. Biochem.
(2004)- et al.
A hybrid model of anaerobic E. coli GJT001: combination of elementary flux modes and cybernetic variables
Biotechnol. Prog.
(2008) - et al.
Ralstonia eutropha strain H16 as model organism for PHA metabolism and for biotechnological production of technically interesting biopolymers
J. Mol. Microbiol. Biotechnol.
(2009) - et al.
Occurrence, metabolism, metabolic role, and industrial uses of bacterial polyhydroxyalkanoates
Microbiol. Rev.
(1990)
Kinetics and models for the bioconversion of methane into an intracellular polymer poly-beta-hydroxybutyrate
Biotechnol. Bioeng. Symp.
Substrate-inhibition kinetics for microbial-growth and synthesis of poly-beta-hydroxybutyric acid by Alcaligenes eutrophus ATCC-17697
Appl. Microbiol. Biotechnol.
Cybernetic modeling of microbial growth on multiple substrates
Biotechnol. Bioeng.
A cybernetic perspective of microbial growth
ACS Symp. Ser.
Are microbes optimal strategists
Biotechnol. Prog.
Cybernetic model for synthesis of poly-beta-hydroxybutyric acid in Alcaligenes eutrophus
Biotechnol. Bioeng.
Cybernetic model predictive control of a continuous bioreactor with cell recycle
Biotechnol. Prog.
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