Theses and Dissertations

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Open Access
A kinetic model development of the M13 bacteriophage life cycle
(Colorado State University. Libraries, 2014) Smeal, Steven William, author; Fisk, Nick, advisor; Prasad, Ashok, advisor; Gentry-Weeks, Claudia, committee member
A kinetic model which can simulate the M13 bacteriophage (a virus which only infects bacteria) life-cycle was created through a set of ordinary differential equations. The M13 bacteriophage is a filamentous phage with a circular single-stranded DNA genome. The kinetic model was developed by converting the biology into ordinary differential equations through careful studying of the existing literature describing the M13 life cycle. Most of the differential equations follow simple mass-action kinetics but some have an additional function, called the Hill Function, to account for special scenarios. Whenever possible, the rate constants associated with each ordinary differential equation were based off of experimentally determined constants. The literature describing M13 viral infection did not provide all of the rate constants necessary for our model. The parameters which were not experimentally determined through literature were estimated in the model based on what is known about the process. At present, no experiments were performed by our lab to verify the model or expand on the information available in the literature. However, the M13 phage model has improved the understanding of phage biology and makes some suggestions about the unknown factors that are most important to quantitatively understanding phage biology. The kinetic model is genetically structured and simulates all well-known and major features of viral phage infection beginning when the first viral ssDNA has entered the cytoplasm and ends right before the cell is ready to divide. The model includes DNA replication, transcription, translation, mRNA processing and degradation, viral protein P2 and viral DNA interaction, viral protein P5 and viral single-strand DNA (ssDNA) interaction, P5 and mRNA interactions, and the assembly of new phage. Additionally, the model has implemented an interaction of P2 and P10, which has not been directly verified through experiments, to account for the negative effect P10 has on DNA replication. The interaction of the host cell and virus infection was not explicitly modeled, but a subset of cellular resources were set aside for phage reproduction based on experimental estimates of the metabolic burden of phage infection. Specifically, limited amount of host resources RNA polymerase, DNA polymerase 3, and ribosomes were allocated to phage reproduction. All other host resources such as nucleotides and amino acids were assumed to be in abundance and did not limit phage replication. The model was verified by comparing the output of the model to a set of existing experimental results in literature. The model reproduced both the experimentally measured levels of phage proteins and mRNA, and the timing and dynamics of virus production for the first cell cycle after infection. All of the unknown parameters were based off the model results at the end of the first cell cycle. When the model was extended to account for phage production through multiple cell divisions, the model predicts the cell has the ability to cure itself from the infection in 7 - 8 cell cycles, which we found literature supporting our results after we made the conclusions. Once the model was created we studied how host resources, RNA polymerase and ribosomes, were distributed during the infection process. We were also able to replicate an experiment describing the effects that the viral DNA binding protein P5 had on the translation of five other viral proteins in-silico. The role of P5 inhibition in the viral life-cycle is unclear and our in-depth analysis of P5 function has revealed a possible explanation of how P5 translational inhibition could be an evolutionary advantage. Additionally, we proposed a mechanism which has not been strongly suggested to exist in literature. We are anticipating the development of the model will aide in the progress of phage display on filamentous phage and we believe the current model can be easily amendable to account for other phage like phages such as Ike filamentous phage. We discuss further additions and modifications to the model that will allow more exact treatment of early events in the phage life-cycle and more explicit coupling of phage life-cycle and host biology.
Open Access
A new approach to addressing two problems in pharmacokinetics and pharmacodynamics using machine learning
(Colorado State University. Libraries, 2020) Habib, Sohaib, author; Reisfeld, Brad, advisor; Munsky, Brian, committee member; Shipman, Patrick, committee member
In this work, machine learning was applied to develop solutions for two problems related to drug pharmacokinetics (PK) and pharmacodynamics (PD). The first problem was finding a way to easily predict important pharmacological measures accurately representative of those from simulation results computed via a sophisticated model for drug absorption via oral dosing. This model (OpenCAT: Open source Compartmental And Transit model) comprises a system of differential equations describing the absorption of drugs into the gastrointestinal tract, including such factors as drug dissolution and spatially-distributed absorption, metabolism, and transport. For this problem, a machine learning framework was built to develop a self-contained random forest representation of the model predictions that could be queried for critical PK parameters such as maximum plasma concentration (Cmax), time at which the maximum concentration occurs (tmax), and the area under the concentration-time curve (AUC). The random-forest representation was able to generate predictions for the targeted PK parameters close to the solution of the original OpenCAT model over a wide range of drug characteristics. The second problem involved predicting the pharmacodynamics (cholinesterase reactivation) of antidotes for nerve agents. In this case, a machine learning framework was built to use experimental data and corresponding theoretically-derived chemical descriptors to predict the pharmacodynamics of new candidate antidotes against both tested and untested nerve agents. Overall, this project has demonstrated the utility of machine learning approaches in the fields of drug pharmacokinetics and pharmacodynamics.
Open Access
A rapid, point of need open cow test
(Colorado State University. Libraries, 2023) Mendez, Jacy, author; Dandy, David, advisor; Henry, Chuck, committee member; Bailey, Travis, committee member; Hansen, Thomas, committee member
In the dairy industry, maintaining non-pregnant (open) cows is expensive, and may require multiple rounds of artificial insemination (AI) for a cow to become pregnant. There is a need for early pregnancy detection in dairy cows, which allows the use of protocols such as prostaglandin F2-alpha (PGF) and gonadotropin releasing hormone (GnRH) to prepare a cow for another round of breeding via AI, with an emphasis on reduced time between each breeding attempt. The current gold standard method for confirming pregnancy in cows is a rectally-guided ultrasound at day 32 after AI. Interferon-tau (IFNT) is a biomarker that can be detected during days 7-28 of pregnancy in cattle, and is expressed by the cow conceptus. The goal of this work was to develop a cow-side test utilizing IFNT as the biomarker for early cattle pregnancy detection. A lateral flow assay (LFA) was chosen and investigated due to its simplicity and ease of use, but was later adapted to utilize the enzymatic oxidation of 3,3',5,5' – Tetramethylbenzidine to amplify the signal in the test line. C-reactive protein was used to develop protocols for aspects of device development involving nitrocellulose, including antibody striping, blocking, and nitrocellulose selection. These protocols were then utilized as optimization of the lateral flow assay was conducted. The resulting LFA has a limit of detection (LOD) of 10 μg/mL, with an LOD of 100 ng/mL in a half-strip format, with some limitations imposed by false positives. This work provides a novel method of detection for pregnancy in cattle and with further development, has the potential for use by dairy farmers in their respective industry.
Open Access
A study of protective clothing to understand nanoparticle exposure and surface contamination
(Colorado State University. Libraries, 2021) Maksot, Aigerim, author; Kipper, Matt J., advisor; Tsai, Candace S., advisor; Li, Yan V., committee member
In this study, we investigated engineered nanoparticle (ENP) release associated with the contamination of personal protective clothing during the human activities of the worker wearing the ENP-contaminated protective clothing and evaluated the relative ENP retention to each used fabric type. The release of ENPs as airborne nanoparticles can cause inhalation exposure, which is the route of exposure of most concern to cause adverse health effects. The methods used were associated with four different fabric materials of contaminated laboratory coats (cotton, polypropylene, polyester/cotton blend, and Tyvek®) and three ENPs (Al2O3, carbon black and CNT). Two types of tests were performed: contamination and release experiments under two different durations (30 minutes and 6 hours of release processes). The magnitude of contamination and particle release were investigated in this study by measuring the number concentration increase and the weight change on fabric pieces. This study simulated real-life occupational exposure scenarios and was performed in cleanroom environments to investigate the effect of background aerosols on the measurements. Concentrations were measured using particle spectrometers for diameters from 10 nm to 10 μm. Collected aerosol particles and contaminated fabric surfaces were characterized using scanning electron microscopy (SEM), transmission electron microscopy (TEM), and elemental carbon analysis. The magnitude of particle release from contaminated lab coat fabric was found to vary by the type of fabric material; cotton fabric showed the highest level of particle release, followed by polyester cotton, Tyvek® and polypropylene. Moreover, Tyvek® fabric was determined as the best fabric for trapping Al2O3 and carbon black ENPs indicating less resuspension of particles and highest mass change per unit mass after aerosolization and release processes. Two dominant forces responsible for ENP adhesion on the surface of the fabric were theoretically calculated to be van der Waals force and capillary force. To sum up, Tyvek® fabric is considered the most reliable fabric against ENPs, but not durable enough to wear for the long term compared with other fabrics.
Open Access
Advective-diffusive gaseous transport in porous media: the molecular diffusion regime
(Colorado State University. Libraries, 1993) Farr, John Merritt, author; McWhorter, David B., advisor; Weeks, Edwin P., 1936-, committee member; Sunada, Daniel K., committee member; Lenz, Terry G., committee member
Traditional mathematical models for advective-diffusive transport in porous media fail to represent important physical processes when fluid density depends on composition. Such is the case for gas mixtures comprised of species with differing molecular masses, such as found in the vadose zone near chlorinated hydrocarbon sources. To address problems of this nature, a more general advection-diffusion (A-D) model is presented, which is valid for porous media with permeabilities exceeding 10-10 cm2 (where Klinkenberg and Knudsen effects are negligible). The new mathematical model is derived by thermodynamic means, based on identifying the meaning of Darcy's advective reference velocity in terms of a weighted average of species drift velocities~ The resulting model has no additional parameters, and introduces no additional complexity or nonlinearity when compared to the traditional A-D model most commonly used in hydrology and environmental science. Because the form of traditional A-D models is retained, the new formulations fit readily into existing numerical simulators for the solution of subsurface transport problems. The new model is equivalent to the Dusty-Gas Model of Mason et al. (1967) for cases where the molecular diffusion regime prevails and pressure, temperature, and forced diffusion are negligible. Further support of the model is provided by hydrodynamic analysis, accounting for the diffusive-slip flux identified by Kramers and Kistemaker (1943). The new model is analytically compared to two existing A-D models, one from the hydrology literature, where Darcy's law is assumed to yield a mass-average velocity, and one from the chemical engineering literature, where Darcy's law is assumed to yield a mole-average velocity. Significant differences are shown to exist between the three transport models. The new model is shown to match closely with the experimental data of Evans et al. (1961a), while the existing A-D models are shown to fail in this regard.
Open Access
An economic and environmental assessment of guayule resin co-products for a US natural rubber industry
(Colorado State University. Libraries, 2023) Silagy, Brooke, author; Reardon, Kenneth, advisor; Quinn, Jason C., advisor; Kipper, Matthew, committee member; Bradley, Thomas, committee member
Guayule (Parthenium argentatum) is a natural rubber producing desert shrub that has the potential to be grown in semi-arid areas with limited water resources. Numerous studies have examined the costs and environmental impacts associated with guayule rubber production. These studies identified the need for additional value from the rubber co-products, specifically the resin, for sustainable and commercial viability of the biorefinery concept. This study developed process models for resin-based essential oils, insect repellant, and adhesive co-products that are integrated with sustainability assessments to understand the commercial viability. A techno-economic analysis and cradle-to-gate life cycle assessment (LCA) of these three different co-product pathways assumed a facility processing 66 tonnes/day of resin (derived from the processing of 1428 tonnes per day of guayule biomass) and included resin separation through co-product formation. The evaluation outcomes were integrated into an established guayule rubber production model to assess the economic potential and environmental impact of the proposed guayule resin conversion concepts. The minimum selling price for rubber varied by co-product: $3.54 per kg for essential oil, $3.40 per kg for insect repellent, and $1.69 per kg for resin blend adhesive. The resin blend adhesive co-product pathway had the lowest greenhouse gas emissions. These findings show a pathway that supports the development of a biorefining concept based on resin-based adhesives that can catalyze a US based natural rubber industry.
Open Access
Application of alcohols in spark ignition engines
(Colorado State University. Libraries, 2018) Aghahossein Shirazi, Saeid, author; Reardon, Kenneth, advisor; Foust, Thomas, committee member; Dandy, David, committee member; Marchese, Anthony, committee member; Windom, Bret, committee member
Replacing petroleum fuels with sustainable biofuels is a viable option for mitigation of climate change. Alcohols are the most common biofuels worldwide and can be produced biologically from sugary, starchy and lignocellulosic biomass feedstocks. Alcohols are particularly attractive options as fuels for spark ignition engines due to the high octane values of these molecules and their positive influence on performance and emissions. In the context of the US Department of Energy's Co-Optimization of Fuels and Engines (Co-Optima) initiative, a systematic product design methodology was developed to identify alcohols that might be suitable for blending with gasoline for use in spark ignition engines. A detailed database of 943 molecules was established including all possible molecular structures of saturated linear, branched, and cyclic alcohols (C1-C10) with one hydroxyl group. An initial decision framework for removing problematic compounds was devised and applied. Next, the database and decision framework were used to evaluate alcohols suitable for blending in gasoline for spark ignition engines. Three scenarios were considered: (a) low-range (less than 15 vol%) blends with minimal constraints; (b) ideal low-range blends; and (c) high-range (greater than 40 vol%) blends. A dual-alcohol blending approach has been tested. In addition, the azeotropic volatility behavior and mixing/sooting potential of the single and dual-alcohol gasoline blends were studied by monitoring the distillation composition evolution and coupling this with results of a droplet evaporation model. Although nearly all of the work done on alcohol-gasoline blends has been on single-alcohol blends, the results of this study suggest that dual-alcohol blends can overcome many of the limitations of single-alcohol blends to provide a broader spectrum of advantaged properties. A third study focused on the possibility of replacing anhydrous ethanol fuel with hydrous ethanol at the azeotrope composition, which can result in significant energy and cost savings during production. In this collaborative study, the thermophysical properties and evaporation dynamics of a range of hydrous and anhydrous ethanol blends with gasoline were characterized. The results showed that hydrous ethanol blends have the potential to be used in current internal combustion engines as a drop-in fuel with few or no modifications.
Open Access
Applications of advanced self-consistent field calculations in nanostructured polymeric systems
(Colorado State University. Libraries, 2009) Meng, Dong, author; Wang, Qiang (David), advisor
The polymer self-consistent field (SCF) theory have gained great success in many systems, especially for the study of inhomogeneous nanostructured polymers. During my PhD study, I have applied real-space SCF calculations with high accuracy to mainly two categories of nanostructured polymers: The first part of this dissertation is focused on the study of self-assembled nanostructures of diblock copolymers (DBC) under nano-confinement. We first examined in detail the so-called "hard-surface" effects, originated from the impenetrable confining surfaces, on the phase behavior of confined DBC systems, where improving the numerical performance of SCF calculations with such effects is also discussed. We then studied in detail the self-assembled morphology of symmetric DBC confined between two homogeneous planner surfaces, where the effects of surface preference and film thickness are investigated and novel complex morphologies are found. Finally, we considered the directed assembly of DBC on topologically and chemically nano-patterned substrates, where well-ordered complex nanostructures can be obtained by controlling the substrate pattern. In the second part of the dissertation, stimuli-response of polymer brushes (chains end-grafted onto a fiat substrate) is investigated. We first studied the thermal response of poly-NIPAM brushes in water, and found that the temperature where the largest thermal response occurs is governed by the chain-grafting density, while the magnitude of the thermal response is controlled by the polymer chain length. We then studied the solvent-response of uncharged DBC brushes and found that the copolymer composition is the key factor in switching the brush surface-layer composition by different solvent treatments; our SCF results agree well with available experimental measurements. Finally, we investigated the stimuli-response of charged DBC. Given the vast parameter space encountered here, we conducted our study based on the uncharged DBC brushes and explored the effects of charge fraction on polymer chains, solution pH and ionic strength, and applied electric fields on the brush surface-switching; this work reveals the complex interplay between different stimuli in such systems. A list of all my published papers and manuscripts in preparation for publication is included at the end of this dissertation, where all the details of my SCF calculations can be found.
Open Access
Bioconversion of lipid-extracted algal biomass into ethanol
(Colorado State University. Libraries, 2016) Mirsiaghi, Mona, author; Reardon, Kenneth F., advisor; Peebles, Christie, committee member; Peers, Graham, committee member; Smith, Gordon, committee member
Energy security, high atmospheric greenhouse gas levels, and issues associated with fossil fuel extraction are among the incentives for developing alternative and renewable energy resources. Biofuels, produced from a wide range of feedstocks, have the potential to reduce greenhouse gas emissions. In particular, the use of microalgae as a feedstock has received a high level of interest in recent years. Microalgal biofuels are promising replacement for fossil fuels and have the potential to displace petroleum-based fuels while decrease greenhouse gas emissions. The primary focus of research and development toward algal biofuels has been on the production of biodiesel or renewable diesel from the lipid fraction, with use of the non-lipid biomass fraction for production of biogas, electricity, animal feed, or fertilizer. Since the non-lipid fraction, consisting of mainly carbohydrates and proteins, comprises approximately half of the algal biomass, our approach is biological conversion of the lipid-extracted algal biomass (LEAB) into fuels. We used LEAB from Nannochloropsis salina, and ethanol was the model product. The first step in conversion of LEAB to ethanol was deconstruction of the cell wall into fermentable substrates by using different acids or enzymes. Sugar release yields and rates were compared for different treatments. One-step sulfuric acid hydrolysis had the highest yield of released sugars, while the one-step hydrochloric acid treatment had the highest sugar release rate. Enzymatic hydrolysis produced acceptable sugar release rates and yields but enzymes designed for algal biomass deconstruction are still needed. Proteins were deconstructed using a commercially available protease. The hydrolysate, containing the released sugars, peptides, and amino acids, was used as a fermentation medium with no added nutrients. Three ethanologenic microorganisms were used for fermentation: two strains of Saccharomyces cerevisiae (JAY270 and ATCC 26603) and Zymomonas mobilis ATCC 10988. Ethanol yields and productivities were compared. Among the studied microorganisms, JAY270 had the highest ethanol yield while Z. mobilis had the lowest yield for most of the studied conditions. A protease treatment improved the biomass and ethanol yields of JAY270 by providing more carbon and nitrogen. To increase ethanol productivity, a continuous fermentation approach was adapted. Continuous stirred tank reactors have increased productivity over batch systems due to lower idle time. The downtime associated with batch fermentation is the time it takes for empting, cleaning, and filling the reactor. Productivity in the continuous fermentation was limited by the growth characteristics of the microorganism since at high flow rates, with washout occurring below a critical residence time. To overcome the washout problem, the use of an immobilized cell reactor was explored. The performance (ethanol productivity) of free and immobilized cells was compared using an enzymatic hydrolysate of LEAB. Higher ethanol productivities were observed for the continuous immobilized cell reactor compared to the stirred tank reactor.
Open Access
Biodegradation of dinitrotoluene by Pseudomonas PR7 in a fluidized bed bioreactor
(Colorado State University. Libraries, 1997) Whitty, Katherine Keesling, author; Reardon, Kenneth F., advisor; Murphy, Vincent G., committee member; Linden, James C., committee member
2,4-Dinitrotoluene (DNT) has been listed as a priority pollutant by the U. S. EPA. It is a waste product in the production of 2,4,6- trinitrotoluene (TNT) and toluene diisocyanate. Pseudomonas PR7 is able to completely degrade DNT via an oxidative pathway. Batch suspended-cell experiments were performed in order to determine the maximum specific growth rate Pmax/ and the Monod half-saturation constant. Ks. Parameter values of μmax = 0.1 h-1 and Ks = 14 mg/L were obtained by fitting experimental data to the Monod model. Immobilized-cell experiments in a fluidized-bed bioreactor (FBB) were performed in order to determine volumetric DNT degradation rate v for the biodegradation of DNT. A fluidized-bed bioreactor was chosen for study because (1) immobilization of cells onto particles allows for greater cell retention, and (2) fluidization of particles allows for mixing within the reactor. Greater cell retention allows for higher flow rates of liquid through the reactor and adequate mixing can alleviate the problem of low oxygen availability and other accumulation or depletion problems which occur in packed beds. Fluidization of immobilized cells in the FBB was achieved by the upflow of air and liquid. Data from residence time distribution (RTD) analysis of the FBB suggests that it behaves as a stirred tank reactor with small plug-flow regions and dead zones. The fluidized-bed bioreactor performance was compared with that of suspended-cell experiments and packed-bed experiments through direct comparison of DNT loading versus degradation rates. It was found that the fluidized-bed bioreactor performed as well as a previously reported system consisting of a packed-bed column in series with a stirred-tank reactor in one experiment using diatomaceous earth particles as the immobilization medium. The FBB did not perform as well as the packed-bed system in subsequent experiments using polycarbonate particles.
Open Access
Bioelectrochemical production of graphene oxide using bacteria as biocatalysts
(Colorado State University. Libraries, 2019) Nunez Hernandez, Diana Marcela, author; De Long, Susan, advisor; Kipper, Matt, committee member; Sambur, Justin, committee member
The demand for production of graphene oxide (GO), which is a precursor for large-scale production of graphene, has been increasing due to the broad array of uses of both nanomaterials. Due to the unique electrical and mechanical properties of these 2D nanomaterials, applications in composites have shown enhancements by contributing a tunable energetic band gap, high strength, and high transparency among other features. The tunable band gap of the graphene derivatives is one of the key properties of these nanomaterials. By varying the size of the energetic band gap (in eV) between the conduction and valence bands, resistance can be decreased to promote electron flow in the material lattice. A large energetic band gap (insulators) means more resistance for electron flow. Being able to control the band gap of a nanomaterial, allows for many applications in batteries, supercapacitors, and semiconductors being the most promising applications for these nanomaterials. Other applications include flexible electronics, renewable energy, drug delivery, contaminant removal, sensors, and more. Unfortunately, large-scale production of graphene using current methods is challenging due to low yield, impurities, high cost, high energy input, slow production rates and/or hazardous chemical reactants and wastes. For this study, the focus was on the bioelectrochemical production of GO (BEGO) as a novel technology for producing these nanomaterials with low energy input, inexpensive and non-hazardous reagents at standard conditions, and using microbes as biocatalysts. The BEGO process consists of a single-chamber microbial electrosynthesis cell (MES) that uses a graphite rod anode and a cathode (carbon cloth or stainless steel) to drive redox reactions. This MES can be operated at low voltage in a three-electrode (-0.8-1.4V vs. Ag/AgCl), or two-electrode system (~3.1V DC), with bacteria inoculated in a phosphate media solution. During this study, the BEGO process was investigated to advance understanding of the production process and the properties of the BEGO nanomaterial produced. To achieve this, the objectives established include: 1) developing methods for purifying and quantifying the nanomaterial during the production process in the complex aqueous-phase reactor matrix, 2) identifying key physical and chemical properties of the nanomaterial product using various spectroscopy and microscopy techniques, and 3) analyzing the microbial communities present in the reactors and in the graphite anode biofilm. To quantify the BEGO and estimate production rates, different spectrophotometric and gravimetric methods were used. Ultraviolet-visible spectroscopy (UV-Vis) at 229 nm was found to be the best method. This wavelength is specific to GO as it corresponds to the π → π * transitions of aromatic C-C bonds comprising the majority of the molecule, regardless of the oxidation state. Different centrifugation and filtration protocols were compared to purify the BEGO out of the complex matrix. For quantification methods in solution, centrifugation at 10,000 x g for 15 minutes was found to be the most effective method for removal of large particles and biological material, with BEGO remaining in solution. For material characterization, various techniques were used to identify the functional groups present and the morphology of the BEGO sheets. It was found through Fourier transform infrared spectroscopy (FT-IR) and UV-Vis, that the nanomaterial contained less carboxyl/carbonyl groups than GO produced by the traditional Hummers' method. Raman spectroscopy and thermogravimetric analysis (TGA) showed high disorder and weight loss events consistent with known GO spectra. Microscopy analysis revealed the BEGO process yields sheet sizes of a few hundred nm to 1-2 µm in lateral dimensions. Transparency and Fast Fourier transform (FFT) images indicate the BEGO consists of only single-layered to few-layered structures, which are needed for downstream applications. The microbial analysis was done on bioreactors with different inocula sources. DNA and RNA were extracted from both the bulk liquid media and the rod biofilm. At the end of the operation period, microbial communities in the bioreactors had diverged from the inoculum source. Microbial communities in the BEGO producing reactors consisted of both aerobic and anaerobic microorganisms. The most abundant genera on the rod biofilm were the unknown Comamonadaceae (10-11%), Hydrogenophaga (9-21%), Methyloversatilis (15-22%), and Pseudomonas (11-36%) all from the Proteobacteria phylum. Thus, these microbial phylotypes may play a key role in catalyzing BEGO production, enabling this novel and sustainable approach to nanomaterial synthesis.
Open Access
"Biofilmomics": functional protein expression in biofilm biotechnologies revealed by quantitative proteomics
(Colorado State University. Libraries, 2020) Chignell, Jeremy, author; Reardon, Kenneth, advisor; De Long, Susan, advisor; Peebles, Christie, committee member; Sharvelle, Sybil, committee member
Microbial biotechnologies that utilize biofilms often exhibit superior performance compared with planktonic systems. Many details of biofilm metabolism that drive those improvements in performance remain unclear. Only recently have molecular tools emerged that can provide a holistic picture of life in a complex biosystem like a biofilm for the purposes of answering questions on a system level. The purpose of this work was to address four fundamental questions about protein expression in biofilms: what kind of protein expression is distinctive to biofilms? Which biofilm proteins are associated with a function of interest? How does co-culture with another species affect biofilm-related protein expression? When during multi-species biofilm development does a function of interest emerge and who in the community is responsible? Label-free quantitative proteomics was used in conjunction with physiological experimentation to address these four questions. In the first study we found that L. delbrueckii lactis protein expression in flow-cell biofilms was 31% more diverse than in planktonic cultures, and proteins related to catalytic activity were significantly increased in biofilms at the expense of proteins for cell motility and replication. Roles for riboflavin and fatty acid metabolism suggested modulations in redox functions and membrane turnover during life in a biofilm. The second study compared protein expression by S. onedensis MR-1 in electricity-generating biofilms with that in aerobic biofilms from the same microbial fuel cell reactor. Three novel proteins associated with electricity generation were identified, in addition to proteomic evidence of aerobic metabolism by anode biofilm cells. The latter result was shown to be consistent with kinetics of oxygen depletion and bulk cell growth in the MFC, suggesting operational conditions to reduce this bulk cell growth and thereby reduce fouling of the cathode and improve overall Coulombic efficiency of the single-chamber MFC system. In the third study, it was discovered through proteomic and physiological experiments that a virulent phenotype associated with biofilm formation was triggered in P. putida when co-cultured with B. atrophaeus. Dramatic shifts in protein expression at the initial trigger point of virulent biofilm formation by P. putida are described. Finally, a comparison of the meta-proteomes of microbial fuel cell biofilms at different stages of development indicated that proteins in metabolic pathways for carbon storage and competitive inhibition are differentially expressed when the biofilm becomes electrochemically active. Meta-proteomics and 16S rRNA gene sequencing agreed that it is possible for a microbial fuel cell community to maintain high diversity (and therefore potentially higher resilience) while generating electricity at levels comparable to a MFC community dominated by Geobacter. Each of these chapters was prepared as an independent manuscript, though the themes were integrated by the overall theme of quantifying differential protein expression in biofilms in order to reveal new details about their development and functionality. Since the performance of many engineered biosystems—including those that employ biofilms—often can be controlled adequately at an operational level, an attitude persists that any additional molecular investigation is superfluous. The work presented here provides evidence for the opposite viewpoint: a rich understanding of the molecular mechanisms behind biofilm functionality can inform strategies for continuous system improvement and suggest new capabilities and biotechnological applications of biofilms.
Open Access
Brush-like surface using heparin/chitosan based nanoparticles for blood-contacting applications
(Colorado State University. Libraries, 2013) Nijjar, Rajvir Singh, author; Kipper, Matt, advisor; Bailey, Travis, committee member; Reynolds, Melissa, committee member
With increasing applications of biomedical implants, it is crucial to develop surfaces that are blood compatible, meaning they do not induce platelet or protein adhesion. Many implants that are currently used to treat a wide range of problems have one major drawback, they can induce thrombosis. The endothelial glycocalyx plays a crucial role in preventing thrombosis. Based on this idea, we set out to develop a surface that has a brush-like structure similar to that of the endothelial glycocalyx. We developed the surface by adsorbing negatively charged heparin/chitosan polyelectrolyte complex nanoparticles onto a heparin/tri-methylchitosan polyelectrolyte multilayer. The surface was then characterized using surface plasmon resonance (SPR), quartz crystal microbalance (QCM), atomic force microsocopy (AFM), scanning electron microscope (SEM), and polarization modulation-infrared reflection absorption spectroscopy (PM-IRRAS). Using these techniques we confirmed that we had created a surface with brush- like structure. Our hypothesis that the nanoparticles on the surface swell and form a brush-like structure when exposed to physiological conditions seems to be correct, as a result, we feel the surface we have developed could have a wide range of applications in the biomedical field.
Open Access
Characterizing biological systems: quantitative methods for synthetic genetic circuits in plants and intracellular mechanics
(Colorado State University. Libraries, 2018) Xu, Wenlong, author; Prasad, Ashok, advisor; Medford, June I., committee member; Reardon, Kenneth F., committee member; Munsky, Brian E., committee member
To view the abstract, please see the full text of the document.
Open Access
Computational modeling of the pharmacokinetics and pharmacodynamics of selected xenobiotics
(Colorado State University. Libraries, 2016) Zurlinden, Todd J., author; Reisfeld, Brad, advisor; Hays, Sean, committee member; Shipman, Patrick, committee member; Munsky, Brian, committee member
The determination of important endpoints in toxicology and pharmacology continues to involve the acquisition of large amounts of data through resource-intensive experimental studies involving a large number of resources. Because of this, only a small fraction of chemicals in the environment and marketplace can reasonably be evaluated for safety, and many promising drug candidates must be eliminated from consideration based on inadequate evaluation. Promisingly, advances in biologically-based computational models are beginning to allow researchers to estimate these endpoints and make useful extrapolations using a limited set of experimental data. The work described in this dissertation examined how computational models can provide meaningful insight and quantitation of important pharmacological and toxicological endpoints related to toxicity and pharmacological efficacy. To this end, physiologically-based pharmacokinetic and pharmacodynamic models were developed and applied for several pharmaceutical agents and environmental toxicants to predict significant, and diverse, biological endpoints. First, physiologically-based modeling allowed for the evaluation of various dosing regimens of rifapentine, a drug that is showing great promise for the treatment of tuberculosis, by comparing lung-specific concentration predictions to experimentally-derived thresholds for antibacterial activity. Second, physiologically-based pharmacokinetic modeling, coupled with Bayesian inference, was used as part of a methodology to characterize genetic differences in acetaminophen pharmacokinetics and also to help clinicians predict an ingested dose of this drug under overdose conditions. Third, a methodology for using physiologically-based pharmacokinetic modeling to predict health-based cognitive endpoints was demonstrated for chronic exposure to chlorpyrifos, an organophosphorus insecticide. The environmental public health indicators derived from this work allowed for biomarkers of exposure to be used to predict neurobehavioral changes following long-term exposure to this chemical. Finally, computational modeling was used to develop a mechanistically-plausible pharmacodynamic model for hepatoprotective and pro-inflammatory events to relate trichloroethylene dosing conditions to observed pathologies associated with auto-immune hepatitis.
Open Access
Control of polymer network structure and degradation
(Colorado State University. Libraries, 2017) Yaghoubi Rad, Ima, author; Stansbury, Jeffrey W., advisor; Kipper, Matthew J., advisor; James, Susan P., committee member; Bailey, Travis S., committee member
This thesis presents work performed evaluating controlled degradation in polymeric networks via incorporation of nanogels either as precursor or as a component of pseudo-interpenetrating polymeric networks. These polymeric crosslinked nanoparticles have applications in drug/gene delivery, cell imaging, and inert or functional prepolymer nano-fillers, therefore controlling their molecular weight (size) and structural properties are mandatory requirements. In addition to the primary effects of reactant selection on the nanogel formation, the solvent used and the agitation rate can provide additional parameters to control nanogel size. This work also develops a practical understanding of polymer characteristics and degradation kinetics of networks constructed from reactive nanogels with regiospecifically degradable linkages. Analogous non-degradable control structures are also prepared for each experimental condition. Clear, monolithic photopolymers are prepared from 50 wt% solvent-based dispersions of the reactive nanogels. The results of equilibrium swelling, mass loss, and compressive modulus (dry/swollen) demonstrate interplay between hydrophilic/hydrophobic effects, labile linkage location, and the crosslinking density that appears to dominate many of predicted property trends. The introduction of hydrolytically degradable linkages (PLA) into the internal crosslink structure of the nanogel promotes greater hydrophobic character compared to PLA placement in external reactive side chains. Consequently, nanogel-based networks with shorter hydrophilic crosslinker and lower crosslinker concentration show lower mass swelling rate, higher Tg, and lower compressive modulus reduction. Nanogels unlock an immense potential in designing superior alternatives for accepted materials with significantly reduced network heterogeneity compared to conventional hydrogels, which ultimately appoint them as novel candidates for controlled drug delivery and tissue engineering applications. Another part of this work demonstrates the effects of nano-scale pre-crosslinked hydrophobic particles as additive to model labile monomer on hydrolytic degradation. The modification of hydrolytically vulnerable polymers through the intimate integration of secondary networks based on styrenic nanogel structures is intended to reduce or even eliminate hydrolytic degradation potential. Nanogel addition at any level produces reduction in network swelling and mass loss proportional to nanogel content. The flexural modulus and ultimate transverse strength of nanogel-loaded resin monomer (TEGDMA) does not change compared to neat resin homopolymer as one control material in addition to the homopolymer of PEG2000PLADMA, which includes polylactic acid segments in the crosslinks. The use of a monomer-swollen highly crosslinked hydrophobic nanogel offers a versatile platform from which hydrolytic and potentially enzymatic degradation can be suppressed in a variety of applications such as polymer-based dental restoratives while retaining resin formulation, handling and mechanical properties. Some of the most important challenges in processing high performance materials are their high viscosity and limited solubility as a result of high molecular weight, intermolecular interactions, and rigid monomeric structure. Alternatively, high strength thermoset materials formed by ambient photopolymerization are limited in their performance by incomplete, vitrification-limited conversion, and relatively low glass transition temperature. In non-biological applications, significant effort has been focused on improving processing techniques and advanced machinery, and notably trivial attention has been paid to upgrade molecular structure of the resins. On the other hand, in biological applications photocuring is the perfect choice since applying high temperatures is practically impossible. As a result, another objective of this work was to develop an alternative photocurable material with enhanced processability, yet retaining thermal and mechanical properties of conventional resins. The average diameter of these polymeric particles is less than 20 nm with glass transition temperatures greater than 200 °C. These paradoxical properties trace back to molecular-level rearrangements of the same monomeric building blocks used in current thermoplastic/thermoset resins.
Open Access
Cooperative design of a water quality monitoring system for the Big Thompson River Watershed, Colorado
(Colorado State University. Libraries, 1999) Greve, Adrienne I., author; Loftis, Jim C., advisor; Ward, Robert, committee member; Laituri, Melinda, committee member
Water from the Big Thompson River and the Colorado-Big Thompson Project (a trans-mountain diversion of Colorado River water to the Big Thompson River) is a valuable resource to the North Front Range region of Colorado. The water is utilized for many purposes (e.g. municipal, irrigation, industrial, recreation, and ecosystem health). Over half a million people depend on the Big Thompson system for drinking water. In recent years a slow decline in water quality has been observed at some locations, particularly in reservoirs lower in the watershed. This trend, coupled with increased pressure to provide accurate data about water quality, has lead a group of stakeholders in the Big Thompson Watershed to seek a better way in which to monitor and manage their water, through cooperation. Stakeholders within the Big Thompson Watershed, who make up a group called the Big Thompson Watershed Forum (BTWF), formed a partnership with Colorado State University to design a water quality monitoring network. The design process was broken down into five steps: objectives, variables, monitoring locations, sampling frequency, and cost analysis. Each step was completed in a cooperative manner, through a series of meetings with BTWF members. The meetings provided an opportunity for members of the BTWF to shape the monitoring system based upon concerns and priorities specific to the watershed. The resulting water quality network is governed by five objectives. The objectives address regulatory requirements within the watershed, eutrophication of reservoirs, and the estimation of loads, spatial trends, and temporal trends. A variable list of 38 water quality parameters was defined as the minimum group of variables that meet the informational goals laid out in the objectives. The list included 12 inorganic variables, nine metals, five organic parameters, seven microbiological variables, and five field parameters. Monitoring locations were defined based on the objective list, already existing monitoring sites, and watershed hydrology (e.g. mixing distance, confluence locations, diversions). Thirty-nine monitoring locations were chosen; 29 moving water sites and 10 reservoir sites. Each site was given a priority rating of high or low. The group of 31 high priority sites is the smallest network that satisfies the needs of all BTWF participants. The seven low priority monitoring locations will be sampled if financially feasible. Sampling frequency was determined on a seasonal basis. Three seasons were determined based on annual flow and water temperature cycles. It was originally hoped that historical data could be used to estimate background variability, allowing the sample size required for a specified level of accuracy in mean and trend detection to be determined. Only 11, of the 38 variables on the variable list, had historical data available, and only three, of the 11, had enough data to accurately estimate background variability. Sampling frequencies for variables with inadequate historical data were based a maximum frequency set for each season. During seasons one and two, no variable is to be sampled at a frequency higher than twice a month except for biological parameters. The maximum frequency during season three is monthly. The cost estimate step was utilized as a feasibility check on the monitoring program. The aim for the cooperative monitoring program was more thorough information for the same or less cost. If the monitoring program cost exceeded the sum of all current monitoring budgets, adjustments were made in variables, monitoring sites, and sampling frequency. The final cost estimate was $405,259.00 per year, roughly the same as the $401,500.00 currently spent. In order for an undertaking such as this design and monitoring program to succeed, all participants must be willing to compromise and devote large amounts of time in order to allow for a truly cooperative effort. Those individuals most active in the design process typically represented local entities. The resulting monitoring network therefore gave higher priority to local water quality concerns, highlighting the differences between local informational needs and those defined by state and federal governments. The monitoring system currently includes a set of objectives, variable list, monitoring network, and sample frequency. They have been developed, discussed, and agreed upon by all BTWF participants. The completion of the monitoring network indicates that the BTWF is on its way towards the final goal of a long-term monitoring program operated by, and benefiting all agencies involved.
Open Access
Data analysis reporting protocols for ground water quality monitoring in the San Luis Valley, Colorado
(Colorado State University. Libraries, 1995) Goetz, Lacey R., author; Ward, Robert C., advisor; Loftis, Jim, committee member; Cardon, Grant, committee member
This thesis investigates the concept of designing a regional, long term, ground water quality information system that complies with all of the laws and regulations applicable and provides information needed by water resource managers, water users, and the general public for the upper, unconfined aquifer in the San Luis Valley, Colorado. A set of “Integrated Information Goals” was developed by Bagenstos (1994) and provides the foundation for this thesis. The laws forming the bases of the information goals are examined further to provide a rationale for translating the information goals into quantifiable statements. These statements are subsequently examined to determine if statistical analysis is required and to develop statistical goals where needed. Statistical methods for handling the data to meet the statistical goals are suggested. Via this exercise, monitoring activities and subsequent data analyses are directly linked to the information goals by the data analysis protocols developed. Reports currently generated that include information about the quality of the water in the upper aquifer of the San Luis Valley are reviewed, along with EPA’s requirements for reporting ground water quality and recommendations for preparing reports presented by the Intergovernmental Task Force on Monitoring. A report format is suggested and samples of graphics for quick and easy conveyance of water quality information sought are provided. This exercise provides the people of the San Luis Valley with a method for ensuring the monitoring system is productive because the final product is defined prior to implementation of the monitoring system. The purpose of this thesis is to demonstrate how to link monitoring activities to legislation, ensuring the accountability of monitoring systems, and providing scientifically defensible information that meets the needs of resource managers and water users.
Open Access
Deactivation of ZSM-5 during catalytic fast pyrolysis of biomass
(Colorado State University. Libraries, 2018) Stanton, Alexander R., author; Reardon, Kenneth, advisor; Iisa, Kristiina, advisor; Dandy, David, committee member; Marchese, Anthony, committee member; Smith, Gordon, committee member
To view the abstract, please see the full text of the document.
Open Access
Dependence of the formation factor on the unsaturated hydraulic properties of porous media
(Colorado State University. Libraries, 1995) Lorentz, Simon A., author; McWhorter, David B., advisor; Ward, Robert C., committee member; Durnford, Deanna, committee member; Warner, James W., committee member
Mathematical models of the hydraulic conductivity are used extensively to predict the movement of liquids in porous media. Included in these models is a description of the physics of flow as well as the nature of the conduits in which the liquids move through the medium. Since these flow channels comprise a complex network of pathways and have significantly varying geometries, the mathematical models developed assume a simplified arrangement and geometry of the flow channels which is termed the formation factor. The simplifications are derived from experimentally determined behavior of the porous media. These simplifications are generalized and used to describe the hydraulic conductivity of all porous media. The pore size distribution information is used to estimate the effective hydraulic radius of the medium. The effects of channel network and geometry are modelled by generalized relationships derived from experimentally determined formation factors or from unsaturated hydraulic conductivity observations. The dependence of the formation factor on the properties of porous media has not been studied. It is hypothesized that the effects of the channel network and geometry are a function of the pore size distribution or other properties of the porous medium and are thus material specific. It is proposed that a better understanding of the behavior of the hydraulics in porous media can be gained by determining the relationship between the channel geometry and the pore size distribution or other properties. Therefore, the specific purpose of this study is to: -Derive a simple mathematical model that describes both the unsaturated hydraulic conductivity as well as the formation factor that represents the channel geometry; -Determine the pore size distribution and other porous media properties, the formation factors and hydraulic conductivities at various saturations by laboratory experiments on two soils with significantly different pore size distributions; -Test the model’s capability to predict both the formation factor and hydraulic conductivity of the soils so that conclusions can be made about the dependency of the channel geometry or formation factor on the pores size properties of the media; and -Develop a generalized relationship for the formation factor using porous media properties. The results of the study indicate that the formation factor increases with increasing pore size distribution index. It also is apparent, however, that the pore formation factor is not uniquely dependant on the pore size distribution index and that the relative size of the pores also may contribute to the dependency of the formation factor on the unsaturated properties of the porous media. In addition, it has been determined that the dynamic flow process is influenced by the formation factor to a greater degree than is the static ion diffusion process.