Modelagem e otimização da cromatografia de troca aniônica no processo de produção de proteína de pneumococo

• Ano de defesa: 2019
• Autor(a) principal: Benedini, Leandro Junqueira
• Orientador(a): Zangirolami, Teresa Cristina
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus São Carlos
• Programa de Pós-Graduação: Programa de Pós-Graduação em Engenharia Química - PPGEQ
• Palavras-chave em Português: Escherichia coli; Proteínas recombinantes; Cromatografia de troca aniônica; Modelagem matemática; Modelo do equilíbrio dispersivo
• Palavras-chave em Inglês: Recombinant proteins; Anion exchange chromatography; Mathematical modeling; Equilibrium dispersive model
• Área do conhecimento CNPq: ENGENHARIAS::ENGENHARIA QUIMICA
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/12201

Pneumococcus surface protein A (PspA) is a lactoferrin-binding protein that can be found on the surface of Streptococcus pneumoniae. The use of this protein as a carrier in the formulation of conjugate vaccines contributes to the protection against infections such as pneumonia, sinusitis and meningitis. Recently, the Butantan Institute developed a purification process for PspA4Pro produced by cultures of Escherichia coli BL21 (DE3) pET37b + PspA4Pro. Although the results achieved in terms of purity were satisfactory, it was observed a significant loss of the product during the purification, especially in anion exchange chromatography, the most expensive step in the downstream process. In this context, the present work aims to model and simulate this operation, developing an applicable methodology to model complex mixtures. In the first stage of this work, clarified cell extracts obtained from E. coli biomass produced under different cultivation conditions were purified. Anion exchange chromatography was performed on the Akta Avant 150 system and the samples were analyzed by Bradford methodology and band densitometry. The process was modeled by the EMSO software (Environment for modeling, simulation and optimization) and the modified Langmuir and the steric mass action isotherms were separately tested along with the equilibrium dispersive model to estimate the parameters and validate the models, proving to be adequate to simulate the process. The steric mass action isotherm was also used to simulate the chromatography of a virtual sample, with the parameters of PspA4Pro and the protein impurities separately adjusted. The simulation results were compared with the results of an experimental elution. In both cases it was observed that PspA4Pro eluted at the beginning of the peak, showing similarity between the simulation and experiment profiles and allowing to establish an alternative purification scheme that provided PspA4Pro at a purity of 82.8%, representing an increase of 34% when compared to the original purification process. In the second stage of this work, different experiments involving modifications in ionic elution forces and in the processed protein mass were tested on the column and a cross-validation methodology was applied. Simulations demonstrated that the chromatographic column could process twice the protein without loss of quality of the obtained PspA4Pro. These results were experimentally confirmed, providing a specific yield of 22 x 10-3 g PspA4Pro.mLresin-1 with purity of 81.2%, which was higher than the specific yield of 10 x 10-3 gPspA4Pro.mLresin-1 with purity of 73,9% obtained at the original process. In the last stage of this work, the cross validation methodology was once again used to separately estimate the PspA4Pro and the protein impurities parameters. The results of the simulations once again showed the tendency of PspA4Pro to elute at the beginning of the peak, but in variable profiles according to the applied ionic force, enabling the identification of alternative elution strategies. The best results were obtained by applying lower ionic forces, leading to a significant increase of purity (91.0%) without reduction of specific yield (9.7 x 10-3 gPspA4Pro.mLresin-1). The conclusions of this work show that it is possible to use mathematical models to describe chromatographic processes and to increase efficiency, even when complex mixtures are being processed, such as cell extracts with recombinant proteins. This approach facilitates systematic process analysis and allows a better understanding of actual purification operations.