Salmonella typhimurium and Escherichia coli dissimilarity: closely related bacteria with distinct metabolic profiles

Live attenuated strains of Salmonella typhimurium have been extensively investigated as vaccines for a number of infectious diseases. However, there is still little information available concerning aspects of their metabolism. S. typhimurium and Escherichia coli show a high degree of similarity in terms of their genome contents and metabolic networks. However, this work presents experimental evidence showing that significant differences exist in their abilities to direct carbon fluxes to biomass and energy production. It is important to study the metabolism of Salmonella in order to elucidate the formation of acetate and other metabolites involved in optimizing the production of biomass, essential for the development of recombinant vaccines. The metabolism of Salmonella under aerobic conditions was assessed using continuous cultures performed at dilution rates ranging from 0.1 to 0.67 h1, with glucose as main substrate. Acetate assimilation and glucose metabolism under anaerobic conditions were also investigated using batch cultures. Chemostat cultivations showed deviation of carbon towards acetate formation, starting at dilution rates above 0.1 h1. This differed from previous findings for E. coli, where acetate accumulation was only detected at dilution rates exceeding 0.4 h1, and was due to the lower rate of acetate assimilation by S. typhimurium under aerobic conditions. Under anaerobic conditions, both microorganisms mainly produced ethanol, acetate, and formate. A genome-scale metabolic model, reconstructed for Salmonella based on an E. coli model, provided a poor description of the mixed fermentation pattern observed during Salmonella cultures, reinforcing the different patterns of carbon utilization exhibited by these closely related bacteria. This article is protected by copyright. All rights reserved.Special thanks to Amadeus Azevedo for the HPLC analyses and technical assistance. The authors acknowledge the national funding received from CNPq (Conselho Nacional de Desenvolvimento Cientifico e Tecnologico, Brazil), the international cooperation project CAPES-FCT (Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior/Brazil-Fundacao para a Ciencia e a Tecnologia/Portugal-Process 315/11), CAPES (Atracao de Jovens Talentos-Process 064922/2014-01) and to Fundacao para a Ciencia e Tecnologia the strategic funding of UID/BIO/04469/2013 unit

Control optimization of dissolved oxygen in a pressurized airlift bioreactor: its implementation on cultures of recombinant Escherichia coli.

A wide variety of industrial and therapeutic proteins is synthetized by genetically modified Escherichia coli, which is ease to cultivate and manipulate and also well characterized. However, there are only few studies regarding E. coli cultivation in the pneumatic airlift bioreactor. This reactor presents some advantages over the stirred tank, such as simpler construction, lower risk of contamination, and efficient gas-liquid dispersion with reduced power consumption. However, the lower oxygen transfer capacity in the bench-scale airlift bioreactor, in comparison to the stirred tank, justifies the use of temperature, pressure, and gas and oxygen flow rates as manipulated variables for the dissolved oxygen (DO) control. In this context, this thesis aims: (i) to develop a mathematical model that describes the production of the Pneumococcal Surface Protein A (PspA) by recombinant E. coli in a pressurized airlift reactor, taking into account oxygen transfer and uptake in the process; (ii) to perform economic optimization of the DO control; (iii) to develop an advanced DO controller integrated to state estimators. Data of E. coli cultivation in conventional and airlift reactors were used to identify and validate the models. The dynamic optimization was performed using a gradient method based on the Pontryagin's minimum principle. The developed mathematical models were able to describe the process under varying conditions of temperature and pressure. The dynamic optimization of the DO control resulted in a simple and sequential way of handling the inputs: manipulation of air flow rate, followed by system pressurization, and then air enrichment with pure oxygen. The optimum process temperature was 27 °C. A model predictive DO control was then proposed, associated to two state estimators, the extended Kalman filter (EKF) and the moving horizon estimator (MHE). They were both able to estimate satisfactorily four state variables (cell, substrate, PspA, and DO concentrations) based only on DO measurements. The control system proved to be robust in process simulations. The conclusions that arise from this thesis contribute to the area of development of non-conventional reactors and DO controllers, especially for pneumatic bioreactors, which are widely used in aerobic bioprocesses.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Devido à ampla caracterização e à facilidade de manipulação e de cultivo, diversas proteínas com aplicação industrial e terapêutica são produzidas por Escherichia coli geneticamente modificada. No entanto, poucos trabalhos envolvendo cultivo de E. coli em reator pneumático tipo airlift são encontrados. Este biorreator apresenta vantagens frente ao tanque agitado, como simplicidade de construção, menor risco de contaminação e eficiente dispersão gás-líquido com baixo consumo de energia. Entretanto, a menor capacidade de transferência de oxigênio no biorreator airlift em escala de bancada, em relação à alcançada em reator convencional, justifica a manipulação de variáveis como temperatura, pressão e vazões de ar e oxigênio no controle do oxigênio dissolvido (OD). Nesse contexto, a presente tese tem como objetivos: (i) desenvolver modelo matemático que descreva o processo de produção da Proteína A de Superfície do Pneumococo (PspA) por E. coli recombinante em reator airlift pressurizado, considerando o consumo e a transferência de oxigênio no processo; (ii) otimizar economicamente o controle do OD; (iii) desenvolver controlador avançado para o OD integrado a estimadores de estados. Foram utilizados dados de cultivos de E. coli em reatores convencional e airlift para a identificação e validação dos modelos propostos. A otimização dinâmica foi feita empregando método do gradiente baseado no Princípio do Mínimo de Pontryagin. Os modelos matemáticos desenvolvidos foram capazes de descrever o processo em condições variadas de temperatura e pressão. A otimização dinâmica do controle do OD resultou em uma heurística simples e sequencial de atuação: manipulação da vazão de ar, seguida pela pressurização do sistema e, finalmente, enriquecimento do gás de entrada com oxigênio puro. A temperatura ótima para o processo foi de 27 °C. Foi proposto então um sistema de controle preditivo para o OD, associado a dois estimadores de estado, o extended Kalman filter (EKF) e o moving horizon estimator (MHE), capazes de estimar satisfatoriamente quatro variáveis de estado (concentrações celular, de substrato, de PspA e de OD) com base apenas na medida de OD. O sistema de controle se mostrou robusto em simulações do processo. As conclusões obtidas a partir desta tese contribuem para a área de desenvolvimento de reatores não convencionais e de controladores do OD, especialmente para os biorreatores pneumáticos, que são amplamente utilizados em bioprocessos aeróbios.CAPES: 142482/2014-