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B3 Influence of the environome on the morphology and productivity of filamentous fungi (Aspergillus niger)

(Hempel/Krull)

In various biological processes, filamentous fungi like Aspergillus niger are used for the production of biotechnological substances due to their secretion efficiency. In submerged cultivation, the productivity of these microorganisms is highly dependent on the morphological characteristics, either as freely dispersed mycelia or as distinct pellets of aggregated biomass (Fig. 1). Mycelial growth of filamentous fungi is linked with procedural disadvantages, for instance a high viscosity of the cultivation broth and therefore a low nutrient supply due to insufficient mixing. In comparison, cultivation broths with distinct pellets show Newtonian flow behaviour, but disadvantages related to a limited nutrient availability within the core of the biopellets can occur. Hence, in every biotechnological process, the optimal morphology varies due to specific product properties and cannot be generalised. The morphological characteristics of fungi are exceedingly influenced by the environome consisting of the physicochemical, especially the pH-value, and fluid dynamic cultivation conditions inside the bioreactor.

 

Fig. 1: Different morphological characteristics of Aspergillus niger (volumetric power input P/V = 100 W m-3), a) biopellet at pH 5,5 after a cultivation period of 32 h, b) free dispersed mycelia at pH 3 after 24 h, c) morphology after an initial growth at pH 3 for 8 h, subsequent pH-shift to pH 5,5 and further cultivation for 24 h
 

At present, chemical engineering as well as molecular biology methods and results of the former subprojects B2 (Hempel/Horm) and B3 (Hempel/Krull) regarding the influence of the environome on the morphogenesis of the filamentous mould A. niger and protein production should be merged within the current project B3 (Krull/ Hempel). The superior objective is a holistic model of the cultivation process as well as the optimisation of protein synthesis and secretion in biological processes with filamentous microorganisms. Based on intracellular reactions up to physicochemical and fluid dynamic phenomena at a macroscopic level, which determine the fungal morphology, the morphogenesis of mycelial growth and pellet formation via the previous analysed primary, secondary and possible further aggregation steps ought to be completely covered by population balancing and verified by different particle size analysis techniques.

Furthermore, parallels of the well studied non-biological clay-polymer-floc-system to A. niger should be drawn to gain insights of the mechanical forces which may affect the biomass. For this purpose, previous simulation methods and data of fluid dynamics within the bioreactor, which are generated with Computional Fluid Dynamics (CFD) and verified by Particle Image Velocimetry (PIV) (Fig. 2), ought to be linked to the shear stress of the examined clay-polymer-floc-system. The resulting integral data of the mechanical forces are to be correlated with local CFD-data to obtain a fluiddynamic model of shear stress of filamentous microorganisms in stirred tank reactors. Moreover, the dynamic processes of growth, aggregation and breakup during submerged cultivations ought to be connected by population balancing.

 

Fig. 2: Comparison of simulation data (CFD, coloured area scheme)
and PIV data (contour lines):
Turbulent kinetic energy (TKE) of a stirrer blade plane
 

In addition, protein synthesis and secretion as well as the gene expression of stress and morphology markers is analysed and quantified by real time-PCR, enzyme activity tests, fluorescence measurement or ELISA assays on a molecular level, respectively. Based on these transcription, translation and secretion data of production, bottlenecks within the complex production path from gene to product should be identified. Macroscopic observed growth phenomena as well as growth abnormality and limitations should be predicted by gene expression data of morphogenesis markers. Furthermore, a cooperation with the subprojects B4 (Jahn/Nörtemann/Jänsch) and B9 (Münch/Schomburg) aims for advanced models of intracellular processes including the complex production path from gene to product which then could be fused with the fluid dynamic models.


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