<p> Using soluble organic carbon in the form of dextrose as a growth limiting substrate, and pure cultures of Escherichia coli, the carbon-containing products of a completely mixed, environmentally controlled, continuous bioreactor were quantitatively analyzed in order to determine if accurate carbon balances are obtainable for a wide spectrum of bacterial growth rates, and if gaseous carbon production exhibits a correlation with bacterial growth rate. </p> <p> The techniques of experimentation and analysis were developed and refined during the course of the study. Errors were accumulated in the carbon balances, these being considered due to inaccuracies in sampling of the gaseous reactor effluent. Assessment of error significance was made statistically. Soluble and cellular carbon analyses were accurately completed. A limited correlation of gaseous carbon production rate with growth rate was demonstrated. </p> / Thesis / Master of Engineering (ME)

The rotating wall vessel (RWV) bioreactor is a well-established cell culture device for the simulation of microgravity for suspension cells and the generation of spheroids and organoids. The key to the success of these systems is the generation of a delicately maintained fluid dynamics system which induces a solid body rotation capable of suspending cells and other particles in a gentle, low-shear environment. Despite the unique capabilities of these systems, the inherently delicate nature of their fluid dynamics makes the RWV prone to multiple failure modes. One of the most frequently occurring, difficult to avoid, and deleterious modes of failure is the formation of bubbles. The appearance of even a small bubble in an RWV disrupts the crucial laminar flow shells present in the RWV, inducing a high-shear environment incapable of maintaining microgravity or producing true spheroids. The difficulty of eliminating bubbles from the RWV substantially increases the learning curve and subsequent barrier-to-entry for the use of this technology. The objective of this study is to create a novel RWV design capable of eliminating the bubble formation failure mode and to demonstrate the design’s efficacy. The tested hypothesis is: “The addition of a channel capable of segregating bubbles from the fluid body of the RWV will protect its crucial fluid dynamics system while enabling the growth of consistently sized and properly formed cell spheroids, improving ease of use of the RWV and decreasing experimental failure.” / Bioengineering

No description available.

An in vitro arterial flow bioreactor system for the generation of physiological flows in a biological environment was designed, constructed, and characterized. The design was based on models previously used to investigate the response of endothelial cells to shear. The model interfaces a bioreactor with flow elements to compose a flow loop that reproduces arterial flow conditions within the bioreactor. High-resolution (8.6 microns) time-resolved (4 ms) velocity field measurements within the bioreactor were obtained using Particle Image Velocimetry (PIV). Two physiological flows were considered, corresponding to medium human arteries at rest and exercise conditions: first, with an average Reynolds number of 150 and a Womersley parameter of 6.4, and second, with an average Reynolds number of 300 and a Womersley parameter of 9.0. Two cases were considered: first, using a smooth artery section, and second, with a confluent layer of human microvascular endothelial cells grown on the inner surface of the artery section. The instantaneous wall shear stress, time-averaged wall shear stress, and oscillatory shear index were computed from the velocity field measurements and compared for the cases with and without cells. These measurements were used to assess the value of the system for measurement of correlations between fluid dynamics and the response of biological tissue. It was determined that the flow present in such a system is not an accurate reproduction of physiological flow, and that direct measurement of the flow is necessary for accurate quantification of cellular response to fluid parameters. / Master of Science

Cellulose to lignin ratio is one of the widely used indicators of degree of landfill stabilization. This ratio shows the amount of carbohydrate or cellulose consumed by anaerobes compared to relatively inert lignin. However, the method of lignin measurement contains an intrinsic error. Plastics are contained in the landfill samples and these are characterized as lignaceous materials due to their acid-insolubility. Lignin is typically measured as the organic residue that is acid insoluble but is combustible upon ignition. Additionally lignin may degrade under anaerobic, high temperature conditions associated with wet conditions in sediments and bioreactor landfills. In this study, it has been found that the typical measure of lignin, a gravimetric measure, also includes plastics, leading to erroneous measures of both lignin and the cellulose/lignin (C/L) ratio. Typically, 100% of the plastic will be measured as lignin. Since plastic amounts to approximately 10% of landfill contents, lignin measurements will be 10% greater than actual amounts. Laboratory reactors were set up with known amounts of paper and plastic. The degradation of the cellulose and lignin in paper was measured and compared to plastics, which was collected by hand and weighed. Ratios of cellulose to plastics and lignin to plastics were obtained. It was found, based on the cellulose to plastic ratio and lignin to plastic ration that lignin degrades under anaerobic conditions although at a much slower rate than cellulose. These findings indicate that the cellulose to lignin ratio cannot be used as the sole indicator of stabilization in the landfills. The inclusion of the biochemical methane potential test data along with C/L is thought to provide a better indication of landfill stabilization. / Master of Science

Sustaining the global population depends upon modern agricultural practices reliant on large inputs of nitrogen (N) fertilizer, but export of excess N from agroecosystems has negative environmental consequences, such as accelerated eutrophication and associated water quality degradation. The challenges posed by diffuse and widespread nutrient pollution in agricultural drainage waters necessitate cost-effective, adaptable, and reliable solutions. In this context, enhanced denitrification approaches developed over the last several decades have produced denitrifying bioreactors that harness the ability of ubiquitous soil microorganisms to convert bioavailable N into inert N gas, thereby removing bioavailable N from an ecosystem. Denitrifying bioreactors are edge-of-field structures that consist of organic carbon substrate and support the activity of denitrifying soil bacteria that remove N from intercepted nutrient-enriched drainage waters. The potential to improve bioreactor performance and expand their application beyond the Midwest to the agriculturally significant Mid-Atlantic region was investigated with a three-pronged approach: 1) a pilot study investigating controls on N removal, 2) a laboratory study investigating controls on emission of greenhouse gases nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2), and 3) a field study of one of the first denitrifying bioreactors implemented in the Atlantic Coastal Plain. The pilot and laboratory studies tested the effect of amending woodchip bioreactors with biochar, an organic carbon pyrolysis product demonstrated to enhance microbial activity. The pilot-scale study provides evidence that either hardwood- of softwood-feedstock biochar may increase N removal in woodchip bioreactors, particularly under higher N loading. The results from the laboratory experiment suggest the particular pine-feedstock biochar tested may induce greater greenhouse gas emissions, particularly of the intermediate product of denitrification and potent GHG nitrous oxide. The field study evaluated performance of a biochar-amended woodchip bioreactor installed on a working farm. Two years of monitoring data demonstrated that the bioreactor successfully removed N from drainage waters, but at relatively low rates constrained by low N loading that occurred in the absence of fertilizer application during continuous soy cropping at the site (10.0 kg NO3--N ha-1 yr-1 or 4.86 g NO3- -N m-3 d-1 on the basis of bed volume reached the bioreactor.) Removal rates averaged 0.41 g m-3 d-1 (8.6% removal efficiency), significantly lower than average rates in systems receiving greater N loading in the Midwest, and more similar to installations in the Maryland Coastal Plain. Greenhouse gas fluxes were within the range reported for other bioreactors, and of the N removed an average of only 0.16% was emitted from the bed surface as N2O. This case study provides useful measurements of bioreactor operation under low N loading that informs the boundaries of bioreactor utility, and may have particular regional relevance. The pilot and field studies suggest that wood-based biochars may enhance N removal and may not produce problematic quantities of greenhouse gases, respectively. However, the laboratory study raises the need for caution when considering the costs and benefits amending woodchip bioreactors with biochar and accounting for the effect on greenhouse gas emissions in this calculation, because the tested pine biochar significantly increased these emissions. / PHD

An External Loop Airlift Bioreactor with a small amount (99% porosity) of stainless steel mesh packing inserted in the riser section was used for bioremediation of a phenol polluted air stream. The packing enhanced VOC and oxygen mass transfer rates and provided a large surface area for cell immobilization. Using a pure strain of Pseudomonas putida, fed-batch and continuous runs at three different dilution rates were completed with phenol in the polluted air as the only source of growth substrate. 100% phenol removal was achieved at phenol loading rates up to 33120 mg/h.m3 using only one third of the column, superior to any previously reported biodegradation rates of phenol polluted air with 100% efficiency. A mathematical model has been developed and is shown to accurately predict the transient and steady state data.

An External Loop Airlift Bioreactor with a small amount (99% porosity) of stainless steel mesh packing inserted in the riser section was used for bioremediation of a phenol polluted air stream. The packing enhanced VOC and oxygen mass transfer rates and provided a large surface area for cell immobilization. Using a pure strain of Pseudomonas putida, fed-batch and continuous runs at three different dilution rates were completed with phenol in the polluted air as the only source of growth substrate. 100% phenol removal was achieved at phenol loading rates up to 33120 mg/h.m3 using only one third of the column, superior to any previously reported biodegradation rates of phenol polluted air with 100% efficiency. A mathematical model has been developed and is shown to accurately predict the transient and steady state data.

Disposable technology has gained increasing acceptance in the biopharmaceutical industry over the last decade, and provides many advantages over conventional stainless steel equipment. Disposable rocking bioreactors (RBs) are widely employed for cultivation of recombinant mammalian and insect cell lines, although the perception of inadequate mass transfer has prevented their application to bioprocesses based on microbial platforms. In an effort to thoroughly evaluate the suitability of disposable RBs for cultivation of aerobic microorganisms, a comparative study of one-dimensional (1D) and two-dimensional (2D) disposable RBs, and the conventional stirred tank reactor (STR) was performed. The comparison involved: 1) physical characterization of oxygen mass transfer efficiency and mixing intensity, 2) batch cultivation of Escherichia coli BL21 for comparison of growth characteristics, and 3) batch cultivation of recombinant E. coli BL21 expressing a clinical therapeutic, hCD83ext (the extracytoplasmic domain of human CD83). Oxygen mass transfer (evaluated as the mass transfer coefficient, kLa) was comparable between the 1D RB and STR (approximately 150 h-1) at low working volume (WV), declining linearly with increasing WV, while kLa was highest in the 2D RB for all tested WVs, providing the maximum kLa (394 h-1) at 3 L WV. Fast mixing (t95 of 8-20 s) was observed in all three systems for water and aqueous carboxymethylcellulose (CMC) solutions. Batch growth characteristics of E. coli BL21 were similar in each system, although acetate accumulation was significant in the 1D RB. Batch production of GST-hCD83ext (glutathione S-transferase-hCD83ext fusion protein) resulted in similar soluble protein yields and inclusion body formation between bioreactors. Although cell growth and protein expression were comparable between all bioreactors, the 1D RB is not considered a suitable cultivation system for E. coli under experimental conditions given the significant acetate accumulation observed and high supplemental oxygen requirement for low cell density cultures. On the other hand, considering its formidable mass transfer capacity and overall performance in batch cultivations, the CELL-tainer® is an attractive alternative to the STR for cultivation of recombinant E. coli expressing high value therapeutic proteins.

The word cybernetics has its roots in the Greek word \kybernetes" or \steers-man" and was coined by Norbert Wiener in 1948 to describe \the science of control and communication, in the animal and the machine". The discipline focuses on the way various complex systems (animals/machines) steer towards/maintain their goals utilizing information, models and control actions in the face of various disturbances. For a given animal/machine, cybernetics considers all the possible behaviors that the animal/machine can exhibit and then enquires about the constraints that result in a particular behavior. The thesis focuses on the application of principles of cybernetics to the modeling and optimization of bioreactors and lies at the interface of systems engineering and biology. Specifically, it lies at the interface of control theory and the growth behavior exhibited by microorganisms. The hypothesis of the present work is that the principles and tools of control theory can give novel insights into the growth behavior of microorganisms and that the growth behavior exhibited by microorganisms can in turn provide insights for the development of principles and tools of control theory. Mathematical models for the growth of microorganisms such as stoichiometric, optimal and cybernetic assume that microorganisms have evolved to become optimal with respect to certain cellular goals or objectives. Typical cellular goals used in the literature are the maximization of instantaneous/short term objectives such biomass yield, instantaneous growth rate, instantaneous ATP production rate etc. Since microorganisms live in a dynamic world, it is expected that the microorganisms have evolved towards maximizing long term goals. In the literature, it is often assumed that the maximization of a short term cellular goal results in the maximization of the long term cellular goal. However, in the systems engineering literature, it has long been recognized that the maximization of a short term goal does not necessarily result in the maximization of the long term goal. For example, maximization of product production in a fed-batch bioreactor involves two separate phases: a first phase in which the growth of microorganisms is maximized and a second phase in which the production of product is maximized. An analogous situation arises when the bacterium E. coli passes through the digestive tract of mammals wherein it first encounters the sugar lactose in the proximal portions and the sugar maltose in the distal portions. Mitchell et al. (2009) have experimentally shown that when E. coli encounters the sugar lactose, it expresses the genes of maltose operons anticipatorily which reduces its growth rate on lactose. This regulatory strategy of E. coli has been termed asymmetric anticipatory regulation (AAR) and is shown to be beneficial for long term cellular fitness by Mitchell et al. (2009). The cybernetic modeling framework for the growth of microorganisms, developed by Ramakrishna and co-workers, is extended in the present thesis for modeling the AAR strategy of E. coli. The developed model accurately captures the experimental observations of the AAR phenomenon, reveals the inherent advantages of the cybernetic modeling framework over other frameworks in explaining the AAR phenomenon, while at the same time suggesting a scope for the generalization of the cybernetic framework. As cybernetics is interested in all the possible behaviors that a machine (which is, in the present case, microorganism) can exhibit, a rigorous analysis of the optimal dynamic growth behavior of microorganisms under various constraints is carried out next using the methods of optimal control theory. An optimal control problem is formulated using a generalized version of the unstructured Monod model with the objective of maximization of cellular concentration at a fixed final time. Optimal control analysis of the above problem reveals that the long term objective of maximization of cellular concentration at a final time is equivalent to maximization of instantaneous growth rate for the growth of microorganisms under various constraints in a two substrate batch environment. In addition, reformulation of the above optimal control problem together with its necessary conditions of optimality reveals the existence of generalized governing dynamic equations of the structured cybernetic modeling framework. The dynamic behavior of the generalized equations of the cybernetic modeling framework is analyzed further to gain insights into the growth of microorganisms. For growth of microorganisms on a single growth limiting carbon substrate, the analysis reveals that the cybernetic model exhibits linear growth behavior, similar to that of the unstructured Contois model at high cellular concentrations, under appropriate constraints. During the growth of microorganisms on multiple substitutable substrates, the analysis reveals the existence of simple correlations that quantitatively predict the mixed substrate maximum specific growth rate from single substrate maximum specific growth rates during simultaneous consumption of the substrates in several cases. Further analysis of the cybernetic model of the growth of S. cerevisiae on the mixture of glucose and galactose reveals that S. cerevisiae exhibits sub-optimal dynamic growth with a long diauxic lag phase and suggests the possibility for S. cerevisiae to grow optimally with a significantly reduced diauxic lag period. Since cybernetics is interested in understanding the constraints under which a particular machine (microorganism) exhibits a particular behavior, a methodology is then developed for inferring the internal constraints experienced by the microorganisms from experimental data. The methodology is used for inferring the internal constraints experienced by E. coli during its growth on the mixture of glycerol and lactose. An interesting question in the study of the growth behavior of microorganisms concerns the objective that the microorganisms optimize. Several studies aim to determine these cellular objectives experimentally. A similar question that is relevant to the optimization of fed-batch bioreactors is \what are the objectives that are to be optimized by the feed flow rate in various time intervals for the optimization of a final objective?" It was mentioned previously that the maximization of product production in a fed-batch bioreactor involves maximization of growth of microorganisms first and the maximization of product production later. However, such guidelines can only be stated for relatively simple bioreactor optimization problems and no such guidelines exist for sufficiently complex problems. For complex problems, the answer to the above question requires the formulation and solution of a genetic programming problem which can be quite challenging. An alternative numerical solution methodology is developed in the present thesis to address the above question. The solution methodology involves the specification of bioreactor objectives in terms of the bioreactor trajectory in the state space of substrate concentration-volume. The equivalent control law of the sliding mode control technique is used for finding the inlet feed ow rate that tracks the bioreactor trajectory accurately. The search for the best bioreactor trajectory is carried out using the stochastic search technique genetic algorithm. The effectiveness of the developed solution methodology in determining the optimal bioreactor trajectory is demonstrated using three challenging bioreactor optimization problems.