Production of Recombinant Trichoderma Reesei Endoglucanase Protein CEL7B by Using Kluyveromyces Lactis

This research is about producing recombinant Trichoderma reesei endoglucanase Cel7B by using Kluyveromyces lactis, transformed with chromosomally integrated Cel7B cDNA, as a host cell (K. lactis Cel7B). Cel7B is one of the glycoside hydrolyze family of proteins that are produced by T. reesei. Cel7B together with other endoglucanases, exoglucanases, and â-glucosidases hydrolyze cellulose to glucose, which can then be fermented to biofuels or other value-added products. The research objective of this MS project is to examine favorable fermentation conditions for recombinant Cel7B enzyme production and improved activity. Production of enzyme on different types of media was examined, and the activity of the enzyme was measured by using different tools or procedures. The first condition tested for was using different concentrations of galactose as a carbon and energy source; however galactose also acts as a potent promoter of recombinant Cel7B expression in K. lactis Cel7B. The purpose of this method is to determine the relationship between production of enzyme with increasing sugar concentration. The second culture condition test was using different types of media: a complex medium-yeast extract, peptone, galactose (YPGal); a minimal medium-yeast nitrogen base (YNB) with galactose; and a minimal medium with supplement-yeast nitrogen base with casamino acid (YBC), a nitrogen source, with galactose. The third condition was using different types of reactors or fermenters: a small reactor (shake flask) and a larger automated bioreactor (BioFlo 3000 fermenter). The purpose of this method is to determine the quantity of the protein produced by using different environments of production. Different tools to determine the presence and activity of Cel7B enzyme were used. For the presence of enzyme, sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was used. Secondly, to detect enzyme activity, the carboxymethyl cellulose- 3,5-dinitrosalicylic acid (CMC- DNS) assay was employed. SDS-PAGE showed that the enzyme band was at 67 kDa, which is larger than native Cel7B (52 kDa.), likely due to over glycolylation during post-translational processing in K. lactis. For the different types of media used in our fermentation, recombinant Cel7B was produced from yeast extract peptone galactose (YPGal), and yeast nitrogen base with casamino acid (YBC), but was not produced and no activity was detected from yeast nitrogen base (YNB). This experiment concluded that the Cel7B production requires the amino acid resources as part of fermentation medium. In experiments where recombinant Cel7B net activity was measured at 1% galactose initial concentration in YPGal and YBC media, higher enzyme activity was detected for the complex medium YPGal. Higher activity of recombinant Cel7B was detected for flask culture in 2% galactose compared to 1% galactose for YBC medium. Two bioreactor experiments were conducted under these culture conditions at 30°C, pH 7.0, dissolved oxygen of 50% of saturation, and 250 rpm agitation (variable depending on DO control) K. lactis-Cel7B yeast growth curves were quite reproducible with maximum optical density (O.D) at 600 nm of between 7 and 8 (when factoring dilution of 10:1). Galactose was consumed rapidly during the first 15 hours of bioreactor culture and recombinant Cel7B started to appear in the culture at 10-15 hours and increased thereafter up to a maximum of between 0.9 and 1.6 mg/mL/hr in these experiments. These bioreactor enzyme activity results are much higher than comparable experiments conducted with flask-scale culture (0.5 mg/mL/hr). In order to achieve the highest recombinant Cel7B activity from batch culture of K. lactis-Cel7B, based on this research it is best to use a complex medium, 2% initial galactose concentration, and an automated bioreactor where good control of temperature, pH, and dissolved oxygen can be achieved.

Regulation of bone marrow stem cells through oscillatory shear stresses - A heart valve tissue engineering perspective

Heart valve disease occurs in adults as well as in pediatric population due to age-related changes, rheumatic fever, infection or congenital condition. Current treatment options are limited to mechanical heart valve (MHV) or bio-prosthetic heart valve (BHV) replacements. Lifelong anti-coagulant medication in case of MHV and calcification, durability in case of BHV are major setbacks for both treatments. Lack of somatic growth of these implants require multiple surgical interventions in case of pediatric patients. Advent of stem cell research and regenerative therapy propose an alternative and potential tissue engineered heart valves (TEHV) treatment approach to treat this life threatening condition. TEHV has the potential to promote tissue growth by replacing and regenerating a functional native valve. Hemodynamics play a crucial role in heart valve tissue formation and sustained performance. The focus of this study was to understand the role of physiological shear stress and flexure effects on de novo HV tissue formation as well as resulting gene and protein expression. A bioreactor system was used to generate physiological shear stress and cyclic flexure. Human bone marrow mesenchymal stem cell derived tissue constructs were exposed to native valve-like physiological condition. Responses of these tissue constructs to the valve-relevant stress states along with gene and protein expression were investigated after 22 days of tissue culture. We conclude that the combination of steady flow and cyclic flexure helps support engineered tissue formation by the co-existence of both OSS and appreciable shear stress magnitudes, and potentially augment valvular gene and protein expression when both parameters are in the physiological range. ^

Movement effects on the flow physics and nutrient delivery in engineered valvular tissues

Mechanical conditioning has been shown to promote tissue formation in a wide variety of tissue engineering efforts. However the underlying mechanisms by which external mechanical stimuli regulate cells and tissues are not known. This is particularly relevant in the area of heart valve tissue engineering (HVTE) owing to the intense hemodynamic environments that surround native valves. Some studies suggest that oscillatory shear stress (OSS) caused by steady flow and scaffold flexure play a critical role in engineered tissue formation derived from bone marrow derived stem cells (BMSCs). In addition, scaffold flexure may enhance nutrient (e.g. oxygen, glucose) transport. In this study, we computationally quantified the i) magnitude of fluid-induced shear stresses; ii) the extent of temporal fluid oscillations in the flow field using the oscillatory shear index (OSI) parameter, and iii) glucose and oxygen mass transport profiles. Noting that sample cyclic flexure induces a high degree of oscillatory shear stress (OSS), we incorporated moving boundary computational fluid dynamic simulations of samples housed within a bioreactor to consider the effects of: 1) no flow, no flexure (control group), 2) steady flow-alone, 3) cyclic flexure-alone and 4) combined steady flow and cyclic flexure environments. We also coupled a diffusion and convention mass transport equation to the simulated system. We found that the coexistence of both OSS and appreciable shear stress magnitudes, described by the newly introduced parameter OSI-:τ: explained the high levels of engineered collagen previously observed from combining cyclic flexure and steady flow states. On the other hand, each of these metrics on its own showed no association. This finding suggests that cyclic flexure and steady flow synergistically promote engineered heart valve tissue production via OSS, so long as the oscillations are accompanied by a critical magnitude of shear stress. In addition, our simulations showed that mass transport of glucose and oxygen is enhanced by sample movement at low sample porosities, but did not play a role in highly porous scaffolds. Preliminary in-house in vitro experiments showed that cell proliferation and phenotype is enhanced in OSI-:τ: environments.^

Mixing theory for culture and harvest in bioreactors of human mesenchymal stem cells on microcarriers

The use of human mesenchymal stem cells (hMSCs) in regenerative medicine is a potential major advance for the treatment of many medical conditions, especially with the use of allogeneic therapies where the cells from a single donor can be used to treat ailments in many patients. Such cells must be grown attached to surfaces and for large scale production, it is shown that stirred bioreactors containing ~200 μm particles (microcarriers) can provide such a surface. It is also shown that the just suspended condition, agitator speed NJS, provides a satisfactory condition for cell growth by minimizing the specific energy dissipation rate, εT, in the bioreactor whilst still meeting the oxygen demand of the cells. For the cells to be used for therapeutic purposes, they must be detached from the microcarriers before being cryopreserved. A strategy based on a short period (~7 min) of very high εT, based on theories of secondary nucleation, is effective at removing >99% cells. Once removed, the cells are smaller than the Kolmogorov scale of turbulence and hence not damaged. This approach is shown to be successful for culture and detachment in 4 types of stirred bioreactors from 15 mL to 5 L.

Evolutionary algorithms for the modeling of bioreactors

This work aims to study the application of Genetic Algorithms in anaerobic digestion modeling, in particular when using dynamical models. Along the work, different types of bioreactors are shown, such as batch, semi-batch and continuous, as well as their mathematical modeling. The work intendeds to estimate the parameter values of two biological reaction model. For that, simulated results, where only one output variable, the produced biogas, is known, are fitted to the model results. For this reason, the problems associated with reverse optimization are studied, using some graphics that provide clues to the sensitivity and identifiability associated with the problem. Particular solutions obtained by the identifiability analysis using GENSSI and DAISY softwares are also presented. Finally, the optimization is performed using genetic algorithms. During this optimization the need to improve the convergence of genetic algorithms was felt. This need has led to the development of an adaptation of the genetic algorithms, which we called Neighbored Genetic Algorithms (NGA1 and NGA2). In order to understand if this new approach overcomes the Basic Genetic Algorithms (BGA) and achieves the proposed goals, a study of 100 full optimization runs for each situation was further developed. Results show that NGA1 and NGA2 are statistically better than BGA. However, because it was not possible to obtain consistent results, the Nealder-Mead method was used, where the initial guesses were the estimated results from GA; Algoritmos Evolucionários para a Modelação de Bioreactores Resumo: Neste trabalho procura-se estudar os algoritmos genéticos com aplicação na modelação da digestão anaeróbia e, em particular, quando se utilizam modelos dinâmicos. Ao longo do mesmo, são apresentados diferentes tipos de bioreactores, como os batch, semi-batch e contínuos, bem como a modelação matemática dos mesmos. Neste trabalho procurou-se estimar o valor dos parâmetros que constam num modelo de digestão anaeróbia para o ajustar a uma situação simulada onde apenas se conhece uma variável de output, o biogas produzido. São ainda estudados os problemas associados à optimização inversa com recurso a alguns gráficos que fornecem pistas sobre a sensibilidade e identifiacabilidade associadas ao problema da modelação da digestão anaeróbia. São ainda apresentadas soluções particulares de idenficabilidade obtidas através dos softwares GENSSI e DAISY. Finalmente é realizada a optimização do modelo com recurso aos algoritmos genéticos. No decorrer dessa optimização sentiu-se a necessidade de melhorar a convergência e, portanto, desenvolveu-se ainda uma adaptação dos algoritmos genéticos a que se deu o nome de Neighboured Genetic Algorithms (NGA1 e NGA2). No sentido de se compreender se as adaptações permitiam superar os algoritmos genéticos básicos e atingir as metas propostas, foi ainda desenvolvido um estudo em que o processo de optimização foi realizado 100 vezes para cada um dos métodos, o que permitiu concluir, estatisticamente, que os BGA foram superados pelos NGA1 e NGA2. Ainda assim, porque não foi possivel obter consistência nos resultados, foi usado o método de Nealder-Mead utilizado como estimativa inicial os resultados obtidos pelos algoritmos genéticos.