Biological systems display remarkable complexity that is not properly accounted for in small, reductionistic models. Increasingly, big data approaches using genomics, proteomics, metabolomics etc. are being applied to predicting and modifying the emergent phenotypes produced by complex biological systems. In this research, several novel tools were developed to assist in the acquisition and analysis of biological big data for a variety of applications. In total, two entirely new tools were created and a third, relatively new method, was evaluated by applying it to questions of clinical importance. 1) To assist in the quantification of metabolites at the subcellular level, a strategy for localized in-vivo enzymatic assays was proposed. A proof of concept for this strategy was conducted in which the local availability of acetyl-CoA in the peroxisomes of yeast was quantified by the production of polyhydroxybutyrate (PHB) using three heterologous enzymes. The resulting assay demonstrated the differences in acetyl-CoA availability in the peroxisomes under various culture conditions and genetic alterations. 2) To assist in the design of genetically modified microbe strains that are stable over many generations, software was developed to automate the selection of gene knockouts that would result in coupling cellular growth with production of a desired chemical. This software, called OptQuick, provides advantages over contemporary software for the same purpose. OptQuick can run considerably faster and uses a free optimization solver, GLPK. Knockout strategies generated by OptQuick were compared to case studies of similar strategies produced by contemporary programs. In these comparisons, OptQuick found many of the same gene targets for knockout. 3) To provide an inexpensive and non-invasive alternative for bladder cancer screening, Raman-based urinalysis was performed on clinical urine samples using RametrixTM software. RametrixTM has been previously developed and employed to other urinalysis applications, but this study was the first instance of applying this new technology to bladder cancer screening. Using a pool of 17 bladder cancer positive urine samples and 39 clinical samples exhibiting a range of healthy or other genitourinary disease phenotypes, RametrixTM was able to detect bladder cancer with a sensitivity of 94% and a specificity of 54%. 4) Methods for urine sample preservation were tested with regard to their effect on subsequent analysis with RametrixTM. Specifically, sterile filtration was tested as a potential method for extending the duration at which samples may be kept at room temperature prior to Raman analysis. Sterile filtration was shown to alter the chemical profile initially, but did not prevent further shifts in chemical profile over time. In spite of this, both unfiltered and filtered urine samples alike could be used for screening for chronic kidney disease or bladder cancer even after being stored for 2 weeks at room temperature, making sterile filtration largely unnecessary. / Doctor of Philosophy / Biological systems display remarkable complexity that is not properly accounted for in conventional, reductionistic models. Thus, there is a growing trend in biological studies to use computational analysis on large databases of information such as genomes containing thousands of genes or chemical profiles containing thousands of metabolites in a single cell. In this research, several new tools were developed to assist with gathering and processing large biological datasets. In total, two entirely new tools were created and a third, relatively new method, was evaluated by applying it to questions of medical importance. The first two tools are for bioengineering applications. Bioengineers often want to understand the complex chemical network of a cell’s metabolism and, ultimately, alter that network so as to force the cell to make more of a desired chemical like a biofuel or medicine. The first tool discussed in this dissertation offers a way to measure the concentration of key chemicals within a cell. Unlike previous methods for measuring these concentrations, however, this method limits its search to a specific compartment within the cell, which is important to many bioengineering strategies. The second technology discussed in this paper uses computer simulations of the cells entire metabolism to determine what genetic alterations might lead to better produce a chemical of interest. The third tool involves analyzing the chemical makeup of urine samples to screen for diseases such as bladder cancer. Two studies were conducted with this third tool. The first study shows that Raman spectroscopy can distinguish between bladder cancer and related diseases. The second v study addresses whether sterilizing the urine samples through filtration is necessary to preserve the samples for analysis. It was found that filtration was neither beneficial nor necessary.

Reducing equivalents were extracted from in vitro photosynthesis and used to drive cell-free and enzyme-free biochemical reduction reactions in this research. To investigate photosynthetic electron flow, an algal extract dense in chloroplasts was made from the microalga Scenedesmus sp. A6. The algal extract was subjugated to a variety of environmental parameters and exogenous quinones in order to optimize electron extraction. To monitor electron extraction and donation to metabolites, a novel assay was created that monitored the chemiluminescence (CL) produced by superoxide radicals formed during the process. In particular, these formed when a reduced exogenous quinone oxidized spontaneously. Our studies found that calcium chloride improved the reduction of low redox potential mediators along with prolonged exposure to red light. Other salts and environmental conditions examined had diverse effects on the quinones based on structure, redox potential, and site of electron extraction. We next applied our assay for monitoring the reduction of different metabolites. The CL recorded for different metabolites was compared to the Gibbs free energy of reduction and a highly correlated relationship was found. The assay was then applied to the reduction of metabolites via the oxidation of glucose in an alkaline environment. To exhibit the diverse application of the CL assay, urine of healthy individuals, patients with chronic kidney disease (CKD), and patients with bladder cancer (BCa) were characterized through their interactions with different quinones. The CL output was compared to that of SurineTM and urea followed by ANOVA analysis. Statistically significant differences were found for all quinones with 1,2-napthoquinone-4-sulfonate (NQS) producing significant differences between all groups examined. Monitoring algal phenotypes for biofuels or photosynthetic output requires arduous protocols and advanced instrumentation. Both of these energy producing options were explored along with rapid, high-throughput protocols for measuring reduction reactions. To monitor the phenotypes and health of our microalgae, Raman microscopy was applied to algal cultures of Scenedesmus sp. A6 grown under stress. Statistically unique phenotypes were found based on environmental factors during cell growth. ANOVA analysis determined the effect of stressors that caused significant change to algal phenotypes related to photosynthesis and lipids. / Doctor of Philosophy / Photosynthesis is the process by which plants and algae harness sunlight to convert CO2 to plant mass. Photosynthesis is performed in the chloroplast which can excite electrons and use them to generate energy. Detecting how much energy a chloroplast can produce and what chemicals effect the chloroplast requires complex procedures with complicated instruments. In this thesis the chloroplast from the microalgae Scenedesmus sp. A6 were isolated to evaluate how they are affected by different chemicals in the environment using a new, rapid and robust assay. Then, a group of chemicals called quinones were used to steal electrons (plant energy), and this process was optimized in this research. The purpose of stealing this plant energy from photosynthesis was so it could be re-directed into synthesizing valuable chemicals that are normally produced from fossil fuels. A new sensor was also developed in this research that would "light-up" the environment whenever this plant energy (electron) stealing process was successful allowing us to measure the efficiency of this energy transfer. Once a quinone stole an electron, it would spontaneously give up the electron to oxygen, creating an unstable molecule that could then react with the chemical luminol, forming a strong luminescence (light) signal. We found that calcium chloride greatly enhanced a quinone's ability to harvest electrons from the chloroplast. We also reported unique effects caused by salt, magnesium, phosphate, a mild detergent, and changing the amount of light the chloroplast would receive. This information was then used to transfer electrons from the chloroplast to make new valuable chemicals. We found that electrons could be donated to multiple chemicals using a quinone, chloroplasts, and light. We were also able to take electrons from glucose with our quinones when glucose was in an environment with a high pH. Electrons from glucose could also be donated to chemicals of interest using quinones. In addition, Quinones were used once more to find differences in the urine composition of healthy individuals and those with chronic kidney disease or bladder cancer. The urine from healthy individuals produced a unique luminescence signal when interacting with the quinones. Thus, quinones could be used for rapidly detecting changes in a patient's kidney and bladder function. We also developed a new method for detecting changes in the health of an algal culture. Algal cultures are used for producing biofuel, food, and pharmaceuticals, therefore it is imperative to track the growth of a culture to avoid contamination and algal death. Scenedesmus sp. A6 was exposed to chemicals harmful to algal health to see how these chemicals caused the algae to grow differently. Raman spectroscopy was used to collect data on algae grown under different conditions. The Raman spectra obtained then underwent statistical analysis to determine the chemicals that had the greatest impact on algal function. Methyl viologen, nickel sulfate, salt, and light exposure had the greatest impact on the algae.