Production and characterization of Chitin-Glucan Complex by Komagataella pastoris

This thesis was focused on the production, extraction and characterization of chitin:β-glucan complex (CGC). In this process, glycerol byproduct from the biodiesel industry was used as carbon source. The selected CGC producing yeast was Komagataella pastoris (formerly known as Pichia pastoris), due the fact that to achieved high cell densities using as carbon source glycerol from the biodiesel industry. Firstly, a screening of K. pastoris strains was performed in shake flask assays, in order to select the strain of K. pastoris with better performance, in terms of growth, using glycerol as a carbon source. K. pastoris strain DSM 70877 achieved higher final cell densities (92-97 g/l), using pure glycerol (99%, w/v) and in glycerol from the biodiesel industry (86%, w/v), respectively, compared to DSM 70382 strain (74-82 g/l). Based on these shake flask assays results, the wild type DSM 70877 strain was selected to proceed for cultivation in a 2 l bioreactor, using glycerol byproduct (40 g/l), as sole carbon source. Biomass production by K. pastoris was performed under controlled temperature and pH (30.0 ºC and 5.0, respectively). More than 100 g/l biomass was obtained in less than 48 h. The yield of biomass on a glycerol basis was 0.55 g/g during the batch phase and 0.63 g/g during the fed-batch phase. In order to optimize the downstream process, by increasing extraction and purification efficiency of CGC from K. pastoris biomass, several assays were performed. It was found that extraction with 5 M NaOH at 65 ºC, during 2 hours, associated to neutralization with HCl, followed by successive washing steps with deionised water until conductivity of ≤20μS/cm, increased CGC purity. The obtained copolymer, CGCpure, had a chitin:glucan molar ratio of 25:75 mol% close to commercial CGC samples extracted from A. niger mycelium, kiOsmetine from Kitozyme (30:70 mol%). CGCpure was characterized by solid-state Nuclear Magnetic Resonance (NMR) spectroscopy and Differential Scanning Calorimetry (DCS), revealing a CGC with higher purity than a CGC commercial (kiOsmetine). In order to optimize CGC production, a set of batch cultivation experiments was performed to evaluate the effect of pH (3.5–6.5) and temperature (20–40 ºC) on the specific cell growth rate, CGC production and polymer composition. Statistical tools (response surface methodology and central composite design) were used. The CGC content in the biomass and the volumetric productivity (rp) were not significantly affected within the tested pH and temperature ranges. In contrast, the effect of pH and temperature on the CGC molar ratio was more pronounced. The highest chitin: β-glucan molar ratio (> 14:86) was obtained for the mid-range pH (4.5-5.8) and temperatures (26–33 ºC). The ability of K. pastoris to synthesize CGC with different molar ratios as a function of pH and temperature is a feature that can be exploited to obtain tailored polymer compositions.(...)

Models and tools for value systems analysis in collaborative environments

Dissertation to obtain the degree of Doctor in Electrical and Computer Engineering, specialization of Collaborative Networks

Production and Characterization of the biological activity of peptides obtained via hydrolysis from whey proteins by cardosins

Dissertation presented to obtain the Ph.D degree in Biochemistry, Engineering and Technological Sciences

Exopolysaccharide production by Enterobacter A47: optimization of cultivation conditions and study of polymer functional properties

Dissertação para obtenção do Grau de Mestre em Biotecnologia

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.