Characterization of the abn2(yxiA) encoding a Bacillus subtilis GH43 arabinanase, Abn2, and its role in arabino-polysaccharides degradation.

Journal of Bacteriology (Junho 2008) 4272-4280

The effect of water inorganic matrix in ibuprofen adsorption onto activated carbon for water and wastewater treatment

Dissertação para obtenção do Grau de Mestre em Engenharia Química e Bioquímica

Spatial neighborhood matrix computation: Inverse distance weighted versus binary contiguity

Paper presented at Geo-Spatial Crossroad GI_Forum, Salzburg, Austria.

Development of mixed matrix membranes with metal - organic framework and ionic liquids for biogas upgrading

Dissertation presented to Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa for obtaining the master degree in Membrane Engineering

The additive effects in matrix dispersed liquid crystals

Dissertation presented at Faculdade de Ciências e Tecnologia from Universidade Nova de Lisboa to obtain the degree of Master in Chemical and Biochemical Engineering

Synthesis of precursors of the rare 3-O-methylmannose polysaccharides present in Nontuberculous Mycobacteria

3-O-methylmannose polysaccharides (MMPs) are cytoplasmic carbohydrates synthesized by mycobacteria, which play important intracellular roles, such as for example in metabolism regulation. An important way to confirm if the inhibition of the synthesis of these polysaccharides will critically affect the survival of mycobacteria is the study of the biosynthetic pathways from these molecules on these microorganisms. The purpose of this work is the efficient synthesis of three saccharides, which are rare cellular precursors from the biosynthesis of the mycobacterial polysaccharides, allowing its study. In order to obtain these molecules, a chemical strategy to connect two precursors was used. This process is called chemical glycosylation and its importance will be highlighted as an important alternative to enzymatic glycosylation. The first objective was the synthesis of the disaccharides Methyl (3-O-methyl-α-D-mannopyranosyl)-(1→4)-3-O-methyl-α-D-mannopyranoside and (3-O-Methyl-α-D-mannopyra- nosyl)-(1→4)-3-O-methyl-(α/β)-D-mannopyranose. The mannose precursors were prepared before the glycosylation reaction. The same mannosyl donor was used in the preparation of both molecules and its efficient synthesis was achieved using a 8 step synthetic route from D-mannose. A different mannosyl acceptor was used in the synthesis of each disaccharide and their syntheses were also efficient, the first one a 4 step synthetic route from α-methyl-D-mannose and the second one as an intermediate from the synthesis of the mannosyl donor. The stereoselective preparation of these disaccharides was performed successfully. The second and last objective of the proposed work was the synthesis of the tetrasaccharide methyl (3-O-methyl-α-D-mannopyranosyl-(1→4)-3-O-methyl-α-D-mannopyra- nosyl-(1→4)-3-O-methyl-α-D-mannopyranosyl-(1→4)-3-O-methyl-α-D-mannopyranoside. The disaccharide acceptor and donor to be linked through a stereoselective glycosidic reaction had to be first synthesized. Several synthetic strategies were studied. Neither the precursors nor the tetrasaccharide were synthesized, but a final promising synthetic route for its preparation has been proposed.

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.