Production of Tailor-made PHA Biopolymers


In this project, the effect of intracellular regulation on nonlinear dynamics of polyhydroxyalkanoate (PHA) formation in microorganisms is studied experimentally and theoretically. PHAs are organic polymers, which are synthesized by many microorganisms under unbalanced growth conditions and serve as internal energy and carbon storage material. PHAs are an attractive material for the production of bioplastics that are biodegradable, biocompatible and do not depend on fossil resources. The production of PHAs is favored in the presence of an excess carbon source but limitation of another key nutrient such as nitrogen or phosphate. The objective of this project is to contribute to a better understanding of the underlying dynamic processes and their interactions. In the longer term, this may guide the way to improved processes and improved products.

Approach and Results

In previous theoretical and experimental work, focus was on poly(β-hydroxybutyrate) (PHB) formation in Cupriavidus necator (C. necator) with different substrates [1]. Here, a hybrid cybernetic model (HCM) was developed to describe growth under the aforementioned conditions [2]. This approach enables to incorporate information from metabolic flux analysis, process dynamics and intracellular regulation which are important during PHB formation and consumption. The model shows good agreement with independent experimental data over a wide range of operating conditions. Furthermore, the framework of population balance modeling was applied to describe variability of the cells with respect to intracellular level of PHB [3]

Current research is concerned with model-based control and intensification of PHB production. In a first step, a sophisticated model-based online measurement technique was developed that allows accurate reconstruction of PHB-level in a labscale continuous production process [4]. This approach is further used in an advanced model predictive control strategy [5]. A second project is concerned with experimental and theoretical analysis for production of tailor-made co-polymers in C. necator. Depending on the experimental conditions different co-polymers are produced. The corresponding composition affects important physical and chemical properties of the harvested bioplastics, such as brittleness and melting point. Therefore, the existing cybernetic model is extended to account for co-polymer production.


Future theoretical and experimental work will focus on

  • Production of co-polymers with defined properties
  • Biopolymer production using industrial waste and by-products

Cooperation partners

  • Prof. Dr.-Ing. Rolf Findeisen and Dr.-Ing. Lisa Carius, Otto von Guericke University Magdeburg, Chair for Systems Theory and Automatic Control
  • Dr.-Ing. Steffen Klamt and Dr. Katja Bettenbrock, Max Planck Institute for Dynamics of Complex Technical Systems, Analysis and Redesign of Biological Networks


[1] A. Franz, R. Rehner, A. Kienle, H. Grammel. Rapid selection of glucose-utilizing variants of the polyhydroxyalkanoate producer Ralstonia eutropha H16 by incubation with high substrate levels. Letters in Applied Microbiology, 54, p. 45-51, 2012.
[2] A. Franz, H.-S. Song, D. Ramkrishna, A. Kienle. Experimental and theoretical analysis of poly(β-hydroxybutyrate) formation and consumption in Ralstonia eutropha. Biochemical Engineering Journal, 55(1), p. 49 - 58, 2011.
[3] R. Dürr, A. Franz, A. Kienle. Combination of limited measurement information and multidimensional population balance. IFAC-PapersOnLine, 48(20), p. 261-266, 2015.
[4] L. Carius, J. Pohlodek;  B. Morabito;  A. Franz;  M. Mangold,  R. Findeisen, Rolf,  A. Kienle. Model-based state estimation based on hybrid cybernetic models. Proceedings to 10th IFAC Symposium on Advanced Control of Chemical Processes, 51(18), p. 197-202, 2018.
[5] B. Morabito, A. Kienle, R. Findeisen, L. Carius. Multi-mode Model Predictive Control and Estimation for Uncertain Biotechnological Processes. Proceedings to 12th IFAC Symposium on Dynamics and Control of Process Systems, submitted, 2018.

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