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Research Vacancy
Application Deadline: 04/11/2008

Job Description

This research focuses on the development of dynamic metabolic model for heterologous protein production by Streptomyces lividans consistent with cell metabolism but with manageable complexity to enable model-based optimization and control of the production process in bioreactors. Data and insights generated by metabolic flux analysis under steady state and dynamic conditions are exploited for model development but are also useful for improved strain engineering.

The potential of Streptomyces as an industrial host for production of heterologous proteins has been proven in the past decade. Heterologous genes are usually linked to signal peptides of strongly expressed/secreted endogenous Streptomyces proteins. Signal peptides act as address tags specifically recognizing the Sec-translocase positioned on the cell membrane. Within the secdependent secretion system, SecA (a precursor protein stimulated ATPase) is the molecular motor driving translocation. Given that the central metabolism is the most important source of energy within a cell, a proper balancing of the energy flux towards growth and maintenance processes, and towards protein secretion, plays a crucial role in optimization of protein production. By exploring two target proteins, mouse Tumor Necrosis Factor alpha (mTNF) and Jonesia sp. Xyloglucanase (Xeg), we can identify generic next to protein-specific phenomena.

Aim is to unravel the impact of the bioreactor environment on the central metabolism and protein production properties of S. lividans by means of metabolic flux analysis. Knowledge will gradually be built up by analyzing metabolic fluxes under steady state and subsequently under dynamic conditions. The impact of protein synthesis and secretion on the carbon and energy metabolism and on the flux dynamics under changing process conditions can be deduced. First the published metabolic reaction network of S. coelicolor is verified for S. lividans in well-designed 13C-labelling experiments. Based on the 13C-labelling distribution resulting from the consumption of labelled substrate, the intracellular fluxes and topology of the reaction network is deduced. This knowledge will be further used in MFA based on the reaction stoichiometry and net conversion rates. Various limiting conditions will be tested under steady state conditions. Conditions with significant impact on the metabolic balance between biomass formation and protein production are further investigated under dynamic conditions. Dynamic experiments include steady state experiments with various shifts in dilution rates and fed-batch experiments during which the transition between substrate excess and limitation can be studied. The dynamics of the intracellular metabolites will be followed during transition zones by frequent sampling. In all stages, techniques of optimal experimental design will be used to guarantee identifiability and accurate flux estimation.

Further Requirements:

This position is targeted at candidates from non-EEA countries (European Economic Area = European Union + Iceland, Liechtenstein and Norway). Applications are invited from enthusiastic graduates with an excellent study track record. We offer a challenging research environment and an intense experience leading to a PhD degree.

Further Information: http://cit.kuleuven.be/en/research.php

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