Cystic Fibrosis (CF) is a genetic disorder, found with higher prevalence in the Caucasian population, affecting > 30,000 individuals in the United States and > 70,000 worldwide. Due to the astoundingly high rate of mortality among CF patients being attributed to respiratory failure brought on by chronic bacterial infections and subsequent airway inflammation, there has been a lot of focus on systematically analyzing CF lung airway communities. While it is observed traditionally that Pseudomonas aeruginosa is the most threatening and persistent CF colonizer due to high antibiotic resistance, recent studies have elicited the roles of other pathogens and it has been widely accepted the CF lung airway consists of a complex codependent community of bacteria, viruses, and fungi. To elucidate the interplay among the members of this community, within the constraint of lung uptake regime, I developed a community metabolic network model comprising of >380 metabolites obtained after modeling 39 most abundant bacterial genera across 279 sputum specimens collected from 79 individuals over 10 years from a study by LiPuma et. al. by 16S rRNA gene sequencing, accounting for >89% of reads across samples. The community metabolic model was contrasted with the 16S relative abundance data through standard data mining techniques employed for the analysis of multidimensional data. I further attempted to quantitatively analyze and elucidate the correlations among patient lung function, disease progression, community diversity, microbial compositions, and metabolic capabilities by standard classical hypothesis testing methods. Comparison through linear dimensionality reduction (PCA) of the 16S data and the model data revealed slightly higher variance explained by the model, indicating presence of relatively smaller number of metabolite-based than the 16S-based polymicrobial communities. A deeper analysis elucidated both the phenomena, consolidation of compositionally different communities due to metabolic closeness, as well as splitting of other communities into metabolically distinct clusters due to minor changes in composition and increase in diversity. Clustering of 16S-based relative abundance data and the model data revealed that the rare Burkholderia infections are metabolically distinct from other CF communities, and are heavily dominated by this genus. It was also reiterated that Achromobacter infections are highly resilient to treatment. Linear regression analysis between lung function and microbiota diversity revealed no strong correlation across the population, however, diversity was found to first increase and then subsequently decrease drastically with disease severity.

Mesoporous silica nanoparticles (MSNPs) possess large surface areas and ample pore space that can be readily modified with specific functional groups for targeted binding of bioactive materials to be transported through cellular barriers. Engineered silica nanoparticles (ESNP) have been used extensively to deliver bio-active materials to target intracellular sites, including as non-viral vectors for nucleic acid (DNA/RNA) delivery such as for siRNA induced interference. The reverse process guided by the same principles is called “nanoharvesting”, where valuable biomolecules are carried out and separated from living and functioning organisms using nano-carriers. This dissertation focuses on ESNP design principles for both applications. To investigate the bioactive materials loading, the adsorption of antioxidant flavonoids was investigated on titania (TiO2) functionalized MSNPs (mean particle diameter ~170 nm). The amount of flavonoid adsorbed onto particle surface was a strong function of active group (TiO2) grafting and a 100-fold increase in the adsorption capacity was observed relative to nonporous particles with similar TiO2 coverage. Active flavonoid was released from the particle surface using citric acid-mediated ligand displacement. Afterwards, nanoharvesting of flavonoids from plant hairy roots is demonstrated using ESNP in which TiO2 and amine functional groups are used as specific binding sites and positive surface charge source, respectively. Isolation of therapeutics was confirmed by increased pharmacological activity of the particles. After nanoharvesting, roots are found to be viable and capable of therapeutic re-synthesis. In order to identify the underlying nanoparticle uptake mechanism, TiO2 content of the plant roots was quantified with exposure to nanoparticles. Temperature (4 or 23 °C) dependent particle recovery, in which time dependent release of ESNP from plant cells showed a similar trend, indicated an energy independent process (passive transport). To achieve the selective separation and nanoharvesting of higher value therapeutics, amine functionalized MSNPs were conjugated with specific functional oligopeptides using a hetero-bifunctional linker. Fluorescence spectroscopy was used to confirm and determine binding efficiency using fluorescently attached peptides. Binding of targeted compounds was confirmed by solution depletion using liquid chromatography–mass spectrometry. The conjugation strategy is generalizable and applicable to harvest the pharmaceuticals produced in plants by selecting a specific oligopeptide that mimic the appropriate binding sites. For related gene delivery applications, the thermodynamic interaction of amine functionalized MSNPs with double-stranded (ds) RNA was investigated by isothermal titration calorimetry (ITC). The heat of interaction was significantly different for particles with larger pore size (3.2 and 7.6 nm) compared to that of small pore particles (1.6 nm) and nonporous particles. Interaction of dsRNA also depended on molecular length, as longer RNA (282 base pair) was unable to load into 1.6 nm particles, consistent with previous confocal microscopy observations. Calculated thermodynamic parameters (enthalpy, entropy and free energy of interaction) are essential to design pore size dependent dsRNA loading, protection and delivery using MSNP carriers. While seemingly diverse, the highly tunable nature of ESNP and their interactions with cells are broadly applicable, and enable facile nano-harvesting and delivery based on a continuous uptake-expulsion mechanism.

In this thesis, we study the problem of protein side chain assignment (SCA) given multiple sources of experimental and modeling data. In particular, the mechanism of X-ray crystallography (X-ray) is re-examined using Fourier analysis, and a novel probabilistic model of X-ray is proposed for SCA's decision making. The relationship between the measurements in X-ray and the desired structure is reformulated in terms of Discrete Fourier Transform (DFT). The decision making is performed by developing a new resolution-dependent electron density map (EDM) model and applying Maximum Likelihood (ML) estimation, which simply reduces to the Least Squares (LS) solution. Calculation of the condence probability associated with this decision making is also given. One possible extension of this novel model is the real-space refinement when the continuous conformational space is used. Furthermore, we present a data fusion scheme combining multi-sources of data to solve SCA problem. The merit of our framework is the capability of exploiting multi-sources of information to make decisions in a probabilistic perspective based on Bayesian inference. Although our approach aims at SCA problem, it can be easily transplanted to solving for the entire protein structure.

Blood vessels including the arteries, veins, and capillaries are a critical and indispensable component of various organisms. Some studies estimate that if all the blood vessels present in our body are arranged in line, they would amount to a total length of approximately 60,000 miles. This distance is enough to circle the world two and a half times! In addition to being all pervasive, blood vessels perform certain key functions such as delivery of oxygen and nutrients to various tissues in the body. They also assist in the spread of diseases such as cancer. Therefore, it is important to study vessels from the point of view of tissue engineering applications. In this study, I have adapted the design of an open-source 3D printed device to create channels in Poly (ethylene glycol) Maleimide (PEG-Mal) hydrogels using the subtractive technique. The PEG-Mal hydrogels can be formed in various formulations to mimic the biophysical and biochemical properties of various tissues such as bone marrow, brain, and lung. These channels created within hydrogels can be easily perfused with physiologically relevant flow rates found in blood vessels and capillaries. Additionally, I have also optimized the hydrogel formulations to improve channel reproducibility. It was found that the number of arms of PEG-Mal contributed the most to channel reproducibility with higher success rates of channel formation in 8-arm gels when compared to 4-arm gels. Therefore, this project delineates the formation of simple in vitro channels in hydrogels which combines properties of the tissue specific extracellular matrix with hemodynamics. It is expected that such a system will find potential use in various tissue engineering and disease modeling studies.

Advances in the biomedical field require functional materials and processes that can lead to devices that are biocompatible, and biodegradable while maintaining high performance and mechanical conformability. In this context, a current shift in focus is towards natural polymers as not only the structural but also functional components of such devices. This poses material-specific functionalization and fabrication related questions in the design and fabrication of such systems. Silk protein biopolymers from the silkworm show tremendous promise in this regard due to intrinsic properties: mechanical performance, optical transparency, biocompatibility, biodegradability, processability, and the ability to entrap and stabilize biomolecules. The unique ensemble of properties indicates opportunities to employ this material into numerous biomedical applications. However, specific processing, functionalization, and fabrication techniques are required to make a successful transition from the silk cocoon to silk-based devices. This research is focused on these challenges to form silk-based functional material and devices for application in areas of therapeutics, bio-optics, and bioelectronics. To make silk proteins mechanically conformable to biological tissues, the first exploration is directed towards the realization of precisely micro-patterned silk proteins in flexible formats. The optical properties of silk proteins are investigated by showing the angle-dependent iridescent behavior of micropatterned proteins, and developing soft micro-optical devices for light concentration and focusing. The optical characteristics and fabrication process reported in the work can lead to the future application of silk proteins in flexible optics and electronics. The microfabrication process of silk proteins is further extended to form shape-defined silk protein microparticles. Here, the specificity of shape and the ability to form monodisperse shapes can be used as shape encoded efficient cargo and contrast agents. Also, these particles can efficiently entrap and stabilize biomolecules for drug delivery and bioimaging applications. Next, a smart confluence of silk sericin and a synthetic functional polymer PEDOT:PSS is shown. The composite materials obtained have synergistic effects from both polymers. Silk proteins impart biodegradability and patternability, while the intrinsically conductive PEDOT:PSS imparts electrical conductivity and electrochemical activity. Conductive micro architectures on rigid as well as flexible formats are shown via a green, water-based fabrication process. The applications of the composite are successfully demonstrated by realizing biosensing and energy storage devices on rigid or flexible forms. The versatility of the approach will lead to the development of a variety of applications such as in bio-optics, bioelectronics, and in the fundamental study of cellular bio electrogenic environments. Finally, to expand the applicability of reported functional polymers and composites beyond the microscale, a method for silk nano-patterning via electron beam lithography is explored. The technique enables one-step fabrication of user defined structures at the submicron and nano-scales. By virtue of acrylate chemistry, a very low energetic beam and dosage are required to form silk nano-architectures. Also, the process can form both positive and negative features depending on the dosage. The fabrication platform can also form nano scale patterns of the conductive composite. The conductive measurements confirm the formation of conductive nanowires and the ability of silk sericin to entrap PEDOT:PSS particles in nanoscale features.

Microalgae can be grown on municipal wastewater media to both treat the wastewater and produce feedstock for algae biofuel production. However the reliability of treatment must be demonstrated, as well as high areal algae productivity on recycled wastewater media and efficient sedimentation harvesting. This processes was studied at pilot scale in the present research. A pilot facility was operated with nine CO2-supplemented raceway ponds, each with a 33-m2 surface area and a 0.3-m depth, continuously from March 6, 2013 through September 24, 2014. The ponds were operated as three sets of triplicates with two sets continuously fed primary-clarified municipal wastewater at either a 2-day or 3-day hydraulic residence time (HRT), and one set fed the clarified effluent of the 3-day pond set. This second pond-in-series was operated with a 3-day HRT. Areal biomass productivity is reported as gross and net, the former based only on biomass in the pond effluents and the latter subtracting the volatile suspended solids in the influent from those in the effluent. An estimate was also made of autotrophic biomass productivity, as differentiated from heterotrophic growth. Over a year, net productivity averaged 83 metric tons per hectare per year (MT/ha-yr) for the 2-day HRT ponds, 52 MT/ha-yr for the 3-day HRT ponds, and 44 MT/ha-yr for the 3-day HRT ponds receiving clarified effluent of the first set of 3-day HRT ponds (i.e., recycled water). The lower net productivity of the pond receiving water recycling was attributed to two factors. First, the relatively high influent suspended solids concentrations were subtracted from the effluent suspended solids concentrations before net productivity was calculated. Second, the recycled water contained less soluble organic matter than the primary-clarified wastewater leading to less heterotrophic biomass production. The accumulation of inhibitory allelochemicals is a possible third cause of lower productivity , but no specific information was collected on allelopathy. Algae were harvested from pond effluent by sedimentation, with harvest efficiency most affected by the extent of natural bioflocculation occurring in the ponds. Some forms of bioflocculation are thought to be mediated by bacteria, which often make-up a substantial fraction of the settled flocs. Pond samples settled in 1-L Imhoff cones averaged/L total suspended solids after 24 hours of settling; but all ponds fell short of meeting an averaged/L total suspended solids after a 2 hour interval which would be ideally achieved for wastewater effluent. No relationship was seen between settling performance and the bacterial content of flocs. Soluble carbonaceous biochemical oxygen demand (scBOD5) removal by the raceway ponds was sufficient to meet wastewater treatment requirements year around. Influent scBOD5 concentrations averaged 83 mg/L, and the effluent averaged 5.1 mg/L and 4.2 mg/L for the 2-day and 3-day HRT pond sets, respectively. The variable with the greatest influence on productivity in all pond sets, and settling performance in the recycled water pond set, was season (i.e., co-correlated variables of solar insolation and pond temperature). Neither productivity nor settling appeared to be related to prominent algae genera or prevalence of grazers. The high net productivity achieved with a growth medium of primary clarifier effluent and the generally high settleability of algal-bacterial flocs indicate a good potential for algae wastewater treatment and biofuel production. However, the settling of algae grown on recycled water needs improvement to achieve the full potential of wastewater-grown algae biofuel production.

Microalgae are considered one of the most promising feedstocks for biofuel production for the future. The most efficient way to produce vast amounts of algal biomass is the use of closed tubular photobioreactors (PBR). The heat requirement for a given system is a major concern since the best algae growth rates are obtained between 25-30 °C, depending on the specific strain. A procedure to determine temperature influence on algal growth rates was developed for a lab-scale PBR system using the species Chlorella. A maximum growth rate of 1.44 doublings per day at 29 °C (optimal temperature) was determined. In addition, a dynamic mathematical model was developed to simulate heating and cooling energy requirements of tubular PBRs for any desired location. Operating the model with hourly weather data as input, heating and cooling loads can be calculated early in the planning stage of a project. Furthermore, the model makes it possible to compare the operation inside a greenhouse to the outdoor operations, and consequently provides fundamental information for an economic feasibility study. The best configuration for a specific location can be evaluated easily. The model was exemplary tested for a hypothetical 100,000 l photobioreactor located in San Luis Obispo, California, U.S.A. Average algae productivity rates of 23% and 67% for outdoor and indoor PBR operations, respectively, were obtained. Actual energy loads (heating and cooling) needed to maintain the PBR at optimal temperature were determined and compared. Sensitivity analyses had been performed for abrupt temperature and solar radiation steps, PBR row distances, ground reflectivities, and ventilation rates of the greenhouse. An optimal row distance of 0.75 m was determined for the specific PBR. The least amount of energy was needed for a ground reflectivity of 20%. The ventilation rate had no major influence on the productivity rate of the system. Results demonstrated the importance of a simulation model as well as the economic impact of a sophisticated heat management system. Energy savings due to an optimized heat management system will eventually increase proficiency of the systems, which will support a new sustainable industry and future developmental potential.

Microcirculatory vessels are lined by endothelial cells (ECs) which are surrounded by a single or multiple layer of smooth muscle cells (SMCs). Spontaneous and agonist induced spatiotemporal calcium (Ca2+) events are generated in ECs and SMCs, and regulated by complex bi-directional signaling between the two layers which ultimately determines the vessel tone. The contractile state of microcirculatory vessels is an important factor in the determination of vascular resistance, blood flow and blood pressure. This dissertation presents theoretical insights into some of the important and currently unresolved phenomena in microvascular tone regulation. Compartmental and continuum models of isolated EC and SMC, coupled EC-SMC and a multi-cellular vessel segment with deterministic and stochastic descriptions of the cellular components were developed, and the intra- and inter-cellular spatiotemporal Ca2+ mobilization was examined. Coupled EC-SMC model simulations captured the experimentally observed localized subcellular EC Ca2+ events arising from the opening of EC transient receptor vanilloid 4 (TRPV4) channels and inositol triphosphate receptors (IP3Rs). These localized EC Ca2+ events result in endothelium-derived hyperpolarization (EDH) and Nitric Oxide (NO) production which transmit to the adjacent SMCs to ultimately result in vasodilation. The model examined the effect of heterogeneous distribution of cellular components and channel gating kinetics in determination of the amplitude and spread of the Ca2+ events. The simulations suggested the necessity of co-localization of certain cellular components for modulation of EDH and NO responses. Isolated EC and SMC models captured intracellular Ca2+ wave like activity and predicted the necessity of non-uniform distribution of cellular components for the generation of Ca2+ waves. The simulations also suggested the role of membrane potential dynamics in regulating Ca2+ wave velocity. The multi-cellular vessel segment model examined the underlying mechanisms for the intercellular synchronization of spontaneous oscillatory Ca2+ waves in individual SMC. From local subcellular events to integrated macro-scale behavior at the vessel level, the developed multi-scale models captured basic features of vascular Ca2+ signaling and provide insights for their physiological relevance. The models provide a theoretical framework for assisting investigations on the regulation of vascular tone in health and disease.

The contamination of the environment, accidental or intentional, in particular with chemical toxins such as industrial chemicals and chemical warfare agents has increased public fear. There is a critical requirement for the continuous detection of toxins present at very low levels in the environment. Indeed, some ultra-sensitive analytical techniques already exist, for example chromatography and mass spectroscopy, which are approved by the US Environmental Protection Agency for the detection of toxins. However, these techniques are limited to the detection of known toxins. Cellular expression of genomic and proteomic biomarkers in response to toxins allows monitoring of known as well as unknown toxins using Polymerase Chain Reaction and Enzyme Linked Immunosensor Assays. However, these molecular assays allow only the endpoint (extracellular) detection and use labels such as fluorometric, colorimetric and radioactive, which increase chances of uncertainty in detection. Additionally, they are time, labor and cost intensive. These technical limitations are unfavorable towards the development of a biosensor technology for continuous detection of toxins. Federal agencies including the Departments of Homeland Security, Agriculture, Defense and others have urged the development of a detect-to-protect class of advanced biosensors, which enable environmental surveillance of toxins in resource-limited settings. In this study a Surface-Enhanced Raman Spectroscopy (SERS) immunosensor, aka a SERS-linked immunosensor assay (SLISA), has been developed. Colloidal silver nanoparticles (Ag NPs) were used to design a flexible SERS immunosensor. The SLISA proof-of-concept biosensor was validated by the measurement of a dose dependent expression of RAD54 and HSP70 proteins in response to H2O2 and UV. A prototype microchip, best suited for SERS acquisition, was fabricated using an on-chip SLISA to detect RAD54 expression in response to H2O2. A dose-response relationship between H2O2 and RAD54 is established and correlated with EPA databases, which are established for human health risk assessment in the events of chemical exposure. SLISA outperformed ELISA by allowing RISE (rapid, inexpensive, simple and effective) detection of proteins within 2 hours and 3 steps. It did not require any label and provided qualitative information on antigen-antibody binding. SLISA can easily be translated to a portable assay using a handheld Raman spectrometer and it can be used in resource-limited settings. Additionally, this is the first report to deliver Ag NPs using TATHA2, a fusogenic peptide with cell permeability and endosomal rupture release properties, for rapid and high levels of Ag NPs uptake into yeast without significant toxicity, prerequisites for the development of the first intracellular SERS immunosensor.

The American Cancer Society predicts that 1,665,540 people will be diagnosed with cancer, and 585,720 people will die from cancer in 2014. One of the most common types of cancer in the United States is skin cancer. Melanoma alone is predicted to account for 10,000 of the cancer related deaths in 2014. As a highly mobile and aggressive form of cancer, melanoma is difficult to fight once it has metastasized through the body. Early detection in such varieties of cancer is critical in improving survival rates in afflicted patients. Present methods of detection rely on visual examination of suspicious regions of tissue via various forms of biopsies. Accurate assessment of cancerous cells via this method are subjective, and often unreliable in the early stages of cancer formation when only few cancer cells are forming. With fewer cancer cells, it is less likely that a cancer cell will appear in a biopsied tissue. This leads to a lower detection rate, even when cancer is present. This lack of detection when cancer is in fact present is referred to as a false negative. False negatives can have a highly detrimental effect on treating the cancer as soon as possible. More accurate methods of detecting cancer in early stages, in a nonsubjective form would alleviate these problems. A proposed alternative to visual examination of biopsied legions is to utilize fluorescent nanocrystalline biomarker constructs to directly attach to the abnormal markers found on cancerous tissues. Quantum dots (QDs) are hydrophobic nanoscale crystals composed of semiconducting materials which fluoresce when exposed to specific wavelengths of radiation, most commonly in the form of an ultraviolet light source. The QD constructs generated were composed of cadmium-selenium (CdSe) cores encapsulated with zinc-sulfide (ZnS) shells. These QDs were then encapsulated with phospholipids in an effort to create a hydrophilic particle which could interact with polar fluids as found within the human body. The goal of this thesis is to develop a method for the solubilization, encapsulation, and initial functionalization of CdSe/ZnS QDs. The first stage of this thesis focused on the generation of CdSe/ZnS QDs and the fluorescence differences between unshelled and shelled QDs. The second stage focused on utilizing the shelled QDs to generate hydrophilic constructs by utilizing phospholipids to bind with the QDs. Analysis via spectroscopy was performed in an effort to characterize the difference in QDs both prior to and after the encapsulation process. The method generated provides insight on fluorescence trends and the encapsulation of QDs in polar substances. Future research focusing on the repeatability of the process, introducing the QD constructs to a biological material, and eventual interaction with cancer cells are the next steps in generating a new technique to target and reveal skin cancer cells in the earliest possible stages without using a biopsy.