VTechWorks Repository :: Browsing by Author "Senger, Ryan S."

Browsing by Author "Senger, Ryan S."

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Alterations in the molecular composition of COVID-19 patient urine, detected using Raman spectroscopic/computational analysis
Robertson, John L.; Senger, Ryan S.; Talty, Janine; Du, Pang; Sayed-Issa, Amr; Avellar, Maggie L.; Ngo, Lacy T.; Gomez de la Espriella, Mariana; Fazili, Tasaduq N.; Jackson-Akers, Jasmine Y.; Guruli, Georgi; Orlando, Giuseppe (PLOS, 2022-07-01)
We developed and tested a method to detect COVID-19 disease, using urine specimens. The technology is based on Raman spectroscopy and computational analysis. It does not detect SARS-CoV-2 virus or viral components, but rather a urine ‘molecular fingerprint’, representing systemic metabolic, inflammatory, and immunologic reactions to infection. We analyzed voided urine specimens from 46 symptomatic COVID-19 patients with positive real time-polymerase chain reaction (RT-PCR) tests for infection or household contact with test-positive patients. We compared their urine Raman spectra with urine Raman spectra from healthy individuals (n = 185), peritoneal dialysis patients (n = 20), and patients with active bladder cancer (n = 17), collected between 2016–2018 (i.e., pre-COVID-19). We also compared all urine Raman spectra with urine specimens collected from healthy, fully vaccinated volunteers (n = 19) from July to September 2021. Disease severity (primarily respiratory) ranged among mild (n = 25), moderate (n = 14), and severe (n = 7). Seventy percent of patients sought evaluation within 14 days of onset. One severely affected patient was hospitalized, the remainder being managed with home/ambulatory care. Twenty patients had clinical pathology profiling. Seven of 20 patients had mildly elevated serum creatinine values (>0.9 mg/dl; range 0.9–1.34 mg/dl) and 6/7 of these patients also had estimated glomerular filtration rates (eGFR) <90 mL/min/1.73m2 (range 59–84 mL/min/1.73m2). We could not determine if any of these patients had antecedent clinical pathology abnormalities. Our technology (Raman Chemometric Urinalysis—Rametrix®) had an overall prediction accuracy of 97.6% for detecting complex, multimolecular fingerprints in urine associated with COVID-19 disease. The sensitivity of this model for detecting COVID-19 was 90.9%. The specificity was 98.8%, the positive predictive value was 93.0%, and the negative predictive value was 98.4%. In assessing severity, the method showed to be accurate in identifying symptoms as mild, moderate, or severe (random chance = 33%) based on the urine multimolecular fingerprint. Finally, a fingerprint of ‘Long COVID-19’ symptoms (defined as lasting longer than 30 days) was located in urine. Our methods were able to locate the presence of this fingerprint with 70.0% sensitivity and 98.7% specificity in leave-one-out cross-validation analysis. Further validation testing will include sampling more patients, examining correlations of disease severity and/or duration, and employing metabolomic analysis (Gas Chromatography–Mass Spectrometry [GC-MS], High Performance Liquid Chromatography [HPLC]) to identify individual components contributing to COVID-19 molecular fingerprints.
Analysis and Simulation of Switchgrass Harvest Systems for Large-scale Biofuel Production
McCullough, Devita (Virginia Tech, 2012-08-15)
In the United States, the Energy Independence and Security Act of 2007 mandates the annual production of 136 billion liters of renewable fuel in the US by 2022 (US Congress, 2007). As the nation moves towards energy independence, it is critical to address the current challenges associated with large-scale biofuel production. The biomass logistics network considered consists of three core operations: farmgate operations, highway-hauling operations, and receiving facility operations. To date, decision-making has been limited in post-production management (harvesting, in-field hauling, and storage) in farmgate operations. In this thesis, we study the impacts in the logistics network resulting from the selection of one of four harvest scenarios. A simulation model was developed, which simulated the harvest and filling of a Satellite Storage Location (SSL), using conventional hay harvest equipment, specifically, a round baler. The model evaluated the impacts of four harvest scenarios (ranging from short, October-December, to extended, July-March), on baler equipment requirements, baler utilization, and the storage capacity requirements of round bales, across a harvest production region. The production region selected for this study encompassed a 32-km radius surrounding a hypothetical bio-crude plant in Gretna, VA, and considered 141 optimally selected SSLs. The production region was divided into 6 sub-regions (i.e. tours). The total production region consisted of 15,438 ha and 682 fields. The fields ranged in size from 6 to 156 ha. Of the four scenarios examined in the analysis, each displayed similar trends across the six tours. Variations in the baler requirements that were observed among the tours resulted from variability in field size distribution, field to baler allocations, and total production area. The available work hours were found to have a significant impact on the resource requirements to fulfill harvest operations and resource requirements were greatly reduced when harvest operations were extended throughout the 9-month harvest season. Beginning harvest in July and extending harvest through March resulted in reductions in round balers ranging from 50-63%, as compared to the short harvest scenario, on a sub-regional basis. On a regional basis, beginning harvest in July and extending harvest through March resulted in baler reductions up to 58.2%, as compared to the short harvest scenario. For a 9-month harvest, harvesting approximately 50% of total switchgrass harvest in July-September, as compared to harvesting approximately 50% in October-December, resulted in reductions in round balers ranging from 33.3- 43.5%. An extended (9-month) harvest resulted in the lowest annual baler requirements, and on average lower baler utilization rates. The reduced harvest scenarios, when compared to the extended harvest scenarios, resulted in a significant increase in the number of annual balers required for harvest operations. However, among the reduced harvest scenarios (i.e. Scenario 3 and 4), the number of annual balers required for harvest operations showed significantly less variation than between the extended harvest scenarios (i.e. Scenarios 1 and 2). As a result, an increased utilization of the balers in the system, short harvest scenarios resulted in the highest average baler utilization rates. Storage capacity requirements were however found to be greater for short harvest scenarios. For the reduced harvest scenario, employing an October-December harvest window, approximately 50% of harvest was completed by the end of October, and 100% of total harvest was completed by the third month of harvest (i.e. December).
Application of Far Infrared Radiation and Ethanol Vapor as Alternative Treatment Methods for Reduction of Salmonella enterica Tennessee in Dried, Ground Spices
Nimitz Jr, Stephen Clark (Virginia Tech, 2013-05-24)
The consumption of spiced food is steadily increasing, subsequently leading to increased incidence of spice-related food illnesses. Many outbreaks can be traced to human pathogens that can survive in low moisture content of spices, prompting development of additional inactivation treatments that reduce bacterial pathogens while maintaining spice quality. Spices are currently treated by fumigation with ethylene oxide, pasteurization with ionizing radiation, or steam treatment. However, these treatments exhibit flaws pertaining to consumer preference, regulatory issues, and quality degradation. In this study, two novel treatments were evaluated for reduction of Salmonella enterica Tennessee: far infrared radiation (FIR), a short time â " high temperature treatment, and pasteurization with ethanol vapor (EV). Both treatments were effective in reducing levels of Salmonella Tennessee between 3-5 logs. FIR treatment showed increased efficacy at longer treatment times with a maximum reduction of 5 log CFU/g in paprika at 24s. EV reduced Salmonella Tennessee by 3 log CFU/g within 120s when applied to inoculated paprika and black pepper without detrimentally affecting spice quality. However, the samples receiving FIR treatments suffered reductions in volatile content and color changes to the spices. High levels (up to 1% w/w) of residual ethanol were also detected on samples treated for 300s. Concluding, both treatment show similar results when comparing efficacy; however, based on the magnitude of change in volatile content associated with FIR being significantly greater than those samples receiving EV, FIR treatment requires additional research before recommending for use with dried, ground paprika, black pepper, or sage.
Application of Functional Amyloids in Morphological Control and in Self-assembled Composites
Claunch, Elizabeth Carson (Virginia Tech, 2013-05-14)
Amyloids are self-assembled protein materials containing beta-sheets. While most studies focus on amyloids as the pathogen in neurodegenerative disease, there are instances of "functional" amyloids used to preserve life. Functional amyloids serve as an inspiration in materials design. In this study, it is shown that wheat gluten (WG) and gliadin:myoglobin (Gd:My) amyloid morphology can be varied from predominantly fibrillar at low polypeptide concentration to predominantly globular at high polypeptide concentration as measured at the nanometer scale using atomic force microscopy (AFM). The ability to control the morphology of a material allows control of its properties. Fourier transform infrared (FTIR) spectroscopy shows that at low concentration, fibrils require interdigitation of methyl groups on alanine (A), isoleucine (I), leucine (L), and valine (V). At higher concentration, globules do not have the same interdigitation of methyl groups but more random hydrophobic interactions. The concentration dependence of the morphology is shown as a kinetic effect where many polypeptides aggregate very quickly through hydrophobic interactions to produce globules while smaller populations of polypeptides aggregate slowly through well-defined hydrophobic interactions to form fibrils. Functional amyloids also provide a means of creating a low energy process for composites. Poor fiber/matrix bonding and processing degradation have been observed in previous WG based composites. This study aims to improve upon these flaws by implementing a self-assembly process to fabricate self-reinforced wheat gluten composites. These composites are processed in aqueous solution at neutral pH by allowing the fibers to form in a matrix of unassembled peptides. The fiber and the matrix are formed from the same solution, thus the two components create a compatible system with ideal interfacial interaction for a composite. The fibers in the composite are about 10 microns in diameter and can be several millimeters long. It has been observed that the number of fibers present along the fracture surface influences the modulus of the composite. In this study, self-assembled wheat gluten composites are formed and then characterized with 3-point bend (3PB) mechanical testing, scanning electron microscopy (SEM), and Fourier transform infrared (FTIR) spectroscopy.
The Applications of Raman Spectroscopy Assisted Urinalysis: Hematuria and Bladder Cancer Detection
Carswell, William Forrester (Virginia Tech, 2020-10-29)
Early detection and screening for urinary tract illnesses is a complex and widespread process which has implications for both preventative care, diagnosis, and treatment monitoring. In this paper, we investigate the use of Raman spectroscopy (RS) for the analysis of urine, a complex biological solution, for the detection of bladder cancer (BCa) and hematuria. Raman spectroscopy is a rapid, low cost, non-destructive analysis method with wide-ranging applicability due to the holistic data capturing nature of the scanning technique. Each Raman scan can be considered a 'snapshot' of the molecular makeup of the sample, and, through proper applications of algorithmic transformation and statistical analysis, many types of assessments can be performed on each sample. In this paper we address creating and utilizing a data pipeline for the purposes of analyzing and characterizing potential samples with hematuria and BCa. The algorithmic transformations utilized include baselining using either the Goldindec or ISREA methods, and intensity normalization. The statistical analysis methods utilized include principal component analysis (PCA), discriminant analysis of principal components (DAPC), analysis of variance (ANOVA), pairwise ANOVA, leave-one-out cross-validation (LOOCV), and partial least squares regression (PLSR). These components of the data pipeline serve to output qualitative or quantitative data, depending on the application. The Rametrix toolbox encompasses the tools required to transform and assess Raman spectra with PCA and DAPC. Using the Rametrix toolbox as well as ANOVA, pairwise ANOVA, and LOOCV, we were able to significantly detect the presence of bladder cancer in a specimen with 80% accuracy. Using the Rametrix toolbox, ANOVA, pairwise ANOVA, LOOCV, and PLSR, we were able to classify samples as pure urine, micro-, or macrohematuria with a greater than 91% accuracy, and quantify the amount of blood in the sample with a high correlation (R-squared value of 0.92). In combination, this style of data pipeline is shown to rapidly and accurately test for multiple symptoms or diseases using similar methodologies.
Assembly, characterization and evaluation of a 3rd generation nanoparticle based drug carrier for metastatic breast cancer treatment
Huang, Wei (Virginia Tech, 2013-06-03)
Cancer is one of the leading causes of death in the world. For women in the U.S. and the European countries, breast cancer is the most common type and it continuously threatens the lives of the patients and causes huge economic losses. Chemotherapy and endocrine therapy are the common treatments for recurrence prevention and metastatic cancer symptom palliation. However, the uses of these therapies are meanwhile largely limited because their toxic side effects and non-specificity usually lead to low quality lives of the patients. Low aqueous solubility, multi-drug resistance, degradation of drug, limited intra-tumor diffusion and etc. are other limitations of conventional chemotherapies and endocrine therapies. Nanoparticle based drug carriers were extensively studied for therapeutic drug delivery. Many carriers could be loaded with high dose of hydrophobic and hydrophilic drugs, protect the drug from the surrounding in vivo environment during the transportation, specifically target and enter the tumor cells and slowly release the drug thereafter. Advanced nanoparticle drug carriers are studied driven by the need of a more efficient drug delivery. The 3rd generation of nanoparticle based drug carriers are recently developed. They usually consist of more than one type of nanoparticles. Different part of the particle has more specialized functions. Therefore, by carefully selecting from the conventional nanoparticle carriers, a 3rd generation particle could have the properties such as high loading capacity of multiple drugs, prolonged half-life in circulation, higher tendency of accumulating at the tumor site, improved specificity to the tumor cells, higher cell uptake rate and accurately triggered controlled release, and combination of the above-mentioned properties. In our study, a paclitaxel loaded nanoparticle supported immunoliposome was assembled for metastatic breast cancer drug delivery. Functionalized single walled carbon nanohorn or poly(lactic-co-glycolic acid) was encapsulated in the polyethylene glycol (PEG) coated liposome for high drug loading and controlled release. Anti-Her2 antibody or Herceptin® was grafted onto the surface of the liposome for a higher affinity to the Her2 overexpressing breast cancer cells. Firstly, the conjugation of protein to the surface of liposome and PEGylated liposomes were investigated. Proteins with or without membrane binding domain were conjugated to liposome and PEGylated liposomes through covalent and non-covalent binding for comparison. A modified enzyme-linked immune sorbent assay was developed for surface grafted protein quantification. Secondly, the encapsulation of solid nanoparticle into PEGylated immunoliposome was investigated. Results showed a new structure of solid nanoparticle in PEGylated immunoliposome at a 1:1 ratio was formed during the repeated freeze-thawing process. Supported immunoliposomes with high homogeneity in size and structure were purified by sucrose density gradient centrifugation. Thirdly, the drug loading, triggered release, cell binding, cell uptake and cell toxicities of the supported immunoliposome were studied. Release results showed a minimum drug leakage in serum at body temperature from the particle. The release was initiated with a minor burst trigged by low pH inside the tumor cell and followed with a long term linear pattern. Cell assay results showed the highest binding affinity of the antibody or Herceptin® grafted nanoparticles to Her2 overexpressing cell lines and a lysosomal intracellular distribution of the endocytosised particles. In the final study, a fabrication process for polymeric material nanoparticles was established. The process was capable of providing accurate control of the particle size with significant high output rates, thus largely extends the scope of materials for supporting the immunoliposome.
Baculovirus stability in serum-free lyophilized and wet storage conditions
Colandro, Michelle Elizabeth (Virginia Tech, 2013-09-10)
The baculovirus expression vector system (BEVS) is an effective way to produce recombinant proteins for biopharmaceuticals. However baculovirus stocks are stored in subzero temperatures to maintain virus stability, and fetal bovine serum is commonly used in the storage solution. In an effort to lower transportation and storage costs, a storage formulation that can effectively store the baculovirus in above frozen temperatures without the use of FBS would be beneficial. In this study, DMSO, ethylene glycol, glycerol, sucrose, sorbitol, sucrose-phosphate, and sucrose-phosphate-glutamate were added to baculovirus stock at various concentrations to determine the most effective stabilizer for virus storage at 4°C. Of the seven additives studied, 1 M sorbitol most effectively preserved baculovirus stock over a period of 47 weeks stored in 4°C. Formulations that include sucrose, L-arginine, and Pluronic F68 were created to determine their effectiveness on virus stability in a freeze-dried state stored at room temperature. In a lyophilized state, 0.5 M sucrose maintained baculovirus stock stability after 5 weeks of storage. Lyophilized stocks not containing sucrose were no longer infective after 5 weeks.
Characterization of Value Added Proteins and Lipids form Microalgae
Khili, Mouna (Virginia Tech, 2013-01-30)
Microalgae have been so far identified as the major producers of organic matter through their photosynthetic activities. In the present work, Nannochloris sp. and Amphora sp., two marine microalgae, have been investigated for proteins and lipids production. Protein fraction was quantified using Bicinchoninic acid (BCA) assay. Protein content in Nannochloris sp. was 16.69 ±4.07 % of dry mass and in Amphora sp. it was 39.89 ±2.09 % of dry mass. Enzyme assays were conducted spectrophotometrically. Nannochloris sp. had malate dehydrogenase, peroxidase and catalase activities. Amphora sp. exhibited malate dehydrogenase, catalase and cytochrome C oxidase activities. These enzymes have several valuable applications in some metabolic pathways and as antioxidant nutrition additives. Besides, lipid extraction was conducted using methanol/ chloroform solvent extraction. Crude lipid extract was analyzed using gas chromatography-mass spectrometry. Lipid contents were 8.14 ±3.67 % in Nannochloris sp. and 10.48 ±1.26% on dry basis in Amphora sp., respectively. Nannochloris sp. fatty acids were composed of C16:0 and C18:0 that are valuable for biodiesel production, and É-3 C18:3, É-6 C18:2, É-6 C16:2 having great nutritional values. In Amphora sp., the fatty acids consisted of C14:0, C16:0 and C16:1 shown to be valuable for biodiesel production and É-3 C22:6 having high nutritional values. Furthermore, a single step conversion of microalgal oil to fatty acid methyl esters was carried out starting directly from lyophilized microalgae. This promising process, in situ transesterification, led to better yields of methyl esters as compared to conventional lipid extraction followed by separate transesterification.
Characterizing glucose, illumination, and nitrogen-deprivation phenotypes of Synechocystis PCC6803 with Raman spectroscopy
Tanniche, Imen; Collakova, Eva; Denbow, Cynthia J.; Senger, Ryan S. (2020-03-30)
Background. Synechocystis sp. PCC6803 is a model cyanobacterium that has been studied widely and is considered for metabolic engineering applications. Here, Raman spectroscopy and Raman chemometrics (Rametrix (TM)) were used to (i) study broad phenotypic changes in response to growth conditions, (ii) identify phenotypic changes associated with its circadian rhythm, and (iii) correlate individual Raman bands with biomolecules and verify these with more accepted analytical methods. Methods. Synechocystis cultures were grown under various conditions, exploring dependencies on light and/or external carbon and nitrogen sources. The Rametrix (TM) LITE Toolbox for MATLAB (R) was used to process Raman spectra and perform principal component analysis (PCA) and discriminant analysis of principal components (DAPC). The Rametrix (TM) PRO Toolbox was used to validate these models through leave-oneout routines that classified a Raman spectrum when growth conditions were withheld from the model. Performance was measured by classification accuracy, sensitivity, and specificity. Raman spectra were also subjected to statistical tests (ANOVA and pairwise comparisons) to identify statistically relevant changes in Synechocystis phenotypes. Finally, experimental methods, including widely used analytical and spectroscopic assays were used to quantify the levels of glycogen, fatty acids, amino acids, and chlorophyll a for correlations with Raman data. Results. PCA and DAPC models produced distinct clustering of Raman spectra, representing multiple Synechocystis phenotypes, based on (i) growth in the presence of 5 mM glucose, (ii) illumination (dark, light/dark [12 h/12 h], and continuous light at 20 mE), (iii) nitrogen deprivation (0-100%NaNO3 of native BG-11 medium in continuous light), and (iv) throughout a 24 h light/dark (12 h/12 h) circadian rhythm growth cycle. Rametrix (TM) PRO was successful in identifying glucose-induced phenotypes with 95.3% accuracy, 93.4% sensitivity, and 96.9% specificity. Prediction accuracy was above random chance values for all other studies. Circadian rhythm analysis showed a return to the initial phenotype after 24 hours for cultures grown in light/dark (12 h/12 h) cycles; this did not occur for cultures grown in the dark. Finally, correlation coefficients (R > 0.7) were found for glycogen, all amino acids, and chlorophyll a when comparing specific Raman bands to other experimental results.
Characterizing metabolic stress-induced phenotypes of Synechocystis PCC6803 with Raman spectroscopy
Tanniche, Imen; Collakova, Eva; Denbow, Cynthia J.; Senger, Ryan S. (2020-03-30)
Background. During their long evolution, Synechocystis sp. PCC6803 developed a remarkable capacity to acclimate to diverse environmental conditions. In this study, Raman spectroscopy and Raman chemometrics tools (Rametrix (TM)) were employed to investigate the phenotypic changes in response to external stressors and correlate specific Raman bands with their corresponding biomolecules determined with widely used analytical methods. Methods. Synechocystis cells were grown in the presence of (i) acetate (7.5-30 mM), (ii) NaCl (50-150 mM) and (iii) limiting levels of MgSO4 (0-62.5 mM) in BG-11 media. Principal component analysis (PCA) and discriminant analysis of PCs (DAPC) were performed with the Rametrix (TM) LITE Toolbox for MATLABR (R). Next, validation of these models was realized via Rametrix (TM) PRO Toolbox where prediction of accuracy, sensitivity, and specificity for an unknown Raman spectrum was calculated. These analyses were coupled with statistical tests (ANOVA and pairwise comparison) to determine statistically significant changes in the phenotypic responses. Finally, amino acid and fatty acid levels were measured with well-established analytical methods. The obtained data were correlated with previously established Raman bands assigned to these biomolecules. Results. Distinguishable clusters representative of phenotypic responses were observed based on the external stimuli (i.e., acetate, NaCl, MgSO4, and controls grown on BG-11 medium) or its concentration when analyzing separately. For all these cases, Rametrix (TM) PRO was able to predict efficiently the corresponding concentration in the culture media for an unknown Raman spectra with accuracy, sensitivity and specificity exceeding random chance. Finally, correlations (R > 0.7) were observed for all amino acids and fatty acids between well-established analytical methods and Raman bands.
Characterizing the Phenotypic Responses of Escherichia coli to Multiple 4-Carbon Alcohols with Raman Spectroscopy
Zu, Theresah N. K.; Athamneh, Ahmad I. M.; Senger, Ryan S. (MDPI, 2016-01-25)
The phenotypic responses of E. coli cells exposed to 1.2% (v/v) of 1-butanol, 2-butanol, isobutanol, tert-butanol, and 1,4-butanediol were studied in near real-time using Raman spectroscopy. A method of “chemometric fingerprinting” was employed that uses multivariate statistics (principal component analysis and linear discriminant analysis) to identify E. coli phenotypic changes over a 180 min post-treatment time-course. A toxicity study showed extreme variability among the reduction in culture growth, with 1-butanol showing the greatest toxicity and 1,4-butanediol showing relatively no toxicity. Chemometric fingerprinting showed distinct phenotype clusters according to the type of alcohol: (i) 1-butanol and 2-butanol (straight chain alcohols); (ii) isobutanol and tert-butanol (branched chain alcohols); and (iii) control and 1,4-butanediol (no terminal alkyl end) treated cells. While the isobutanol and tert-butanol treated cells led to similar phenotypic responses, isobutanol was significantly more toxic. In addition, the phenotypic response was found to take place largely within 60 min of culture treatment; however, significant responses (especially for 1,4-butanediol) were still occurring at 180 min post-treatment. The methodology presented here identified different phenotypic responses to seemingly similar 4-carbon alcohols and can be used to study phenotypic responses of virtually any cell type under any set of environmental conditions or genetic manipulations.
Coenzyme engineering of NAD(P)+ dependent dehydrogenases
Huang, Rui (Virginia Tech, 2017-12-11)
Coenzyme nicotinamide adenine dinucleotide (NAD, including the oxidized form-- NAD+ and reduced form--NADH) and the phosphorylated form--nicotinamide adenine dinucleotide phosphate (NADP, including NADP+ and NADPH) are two of the most important biological electron carriers. Most NAD(P) dependent redox enzymes show a preference of either NADP or NAD as an electron acceptor or donor depending on their unique metabolic roles. In biocatalysis, the low enzymatic activities with unnatural coenzymes have made it difficult to replace costly NADP with economically advantageous NAD or other biomimetic coenzyme for catalysis. This is a significant challenge that must be addressed should in vitro biocatalysis be a viable option for the practical production of low-value biocommodities (i.e., biohydrogen). There is a significant need to first address the coenzyme selectivity of the NADP-dependent dehydrogenases and evolve mutated enzymes that accept biomimetic coenzymes. This is a major focus of this dissertation. Establishment of efficient screening methods to identify beneficial mutants from an enzymatic library is the most challenging task of coenzyme engineering of dehydrogenases. To fine tune the coenzyme preference of dehydrogenases to allow economical hydrogen production, we developed a double-layer Petri-dish based screening method to identify positive mutant of the Moorella thermoacetica 6PGDH (Moth6PGDH) with a more than 4,278-fold reversal of coenzyme selectivity from NADP+ to NAD+. This method was also used to screen the thermostable mutant of a highly active glucose 6-phosphate dehydrogenase from the mesophilic host Zymomonas mobilis. The resulting best mutant Mut 4-1 showed a more than 124-fold improvement of half-life times at 60oC without compromising the specific activity. The screening method was further upgraded for the coenzyme engineering of Thermotaga maritima 6PGDH (Tm6PGDH) on the biomimetic coenzyme NMN+. Through six-rounds of directed evolution and screening, the best mutant showed a more than 50-fold improvement in catalytic efficiency on NMN+ and a more than 6-fold increased hydrogen productivity rate from 6-phosphogluconate and NMN+ compared to those of wild-type enzyme. Together, these results demonstrated the effectiveness of screening methods developed in this research for coenzyme engineering of NAD(P) dependent dehydrogenase and efficient use of the less costly coenzyme in ivSB based hydrogen production.
Computation and Numerics in Neurostimulation
Dougherty, Edward T. (Virginia Tech, 2015-05-07)
Neurostimulation continues to demonstrate tremendous success as an intervention for neurodegenerative diseases, including Parkinson's disease, in addition to a range of other neurological and psychiatric disorders. In an effort to enhance the medical efficacy and comprehension of this form of brain therapy, modeling and computational simulation are regarded as valuable tools that enable in silico experiments for a range of neurostimulation research endeavours. To fully realize the capacities of neurostimulation simulations, several areas within computation and numerics need to be considered and addressed. Specifically, simulations of neurostimulation that incorporate (i) computational efficiency, (ii) application versatility, and (iii) characterizations of cellular-level electrophysiology would be highly propitious in supporting advancements in this medical treatment. The focus of this dissertation is on these specific areas. First, preconditioners and iterative methods for solving the linear system of equations resulting from finite element discretizations of partial differential equation based transcranial electrical stimulation models are compared. Second, a software framework designed to efficiently support the range of clinical, biomedical, and numerical simulations utilized within the neurostimulation community is presented. Third, a multiscale model that couples transcranial direct current stimulation administrations to neuronal transmembrane voltage depolarization is presented. Fourth, numerical solvers for solving ordinary differential equation based ligand-gated neurotransmitter receptor models are analyzed. A fundamental objective of this research has been to accurately emulate the unique medical characteristics of neurostimulation treatments, with minimal simplification, thereby providing optimal utility to the scientific research and medical communities. To accomplish this, numerical simulations incorporate high-resolution, MRI-derived three-dimensional head models, real-world electrode configurations and stimulation parameters, physiologically-based inhomogeneous and anisotropic tissue conductivities, and mathematical models accepted by the brain modeling community. It is my hope that this work facilitates advancements in neurostimulation simulation capabilities, and ultimately helps improve the understanding and treatment of brain disease.
Computational Evaluation and Structure-based Design for Potentiation of Nicotine Vaccines
Saylor, Kyle Lucas (Virginia Tech, 2020-10-08)
Existing therapeutic options for the alleviation of nicotine addiction have been largely ineffective at stemming the tide of tobacco use. Immunopharmacotherapy, or vaccination, is a promising, alternate therapy that is currently being explored. Results from previous studies indicate that nicotine vaccines (NVs) are effective in subjects that achieve high drug-specific antibody titers, though overall efficacy has not been observed. Consequently, improvement of these vaccines is necessary before they can achieve approval for human use. In this report, three separate approaches towards NV potentiation are explored. The first approach applied physiologically-based pharmacokinetic (PBPK) modeling to better assess NV potential. Rat and human physiological and pharmacological parameters were obtained from literature and used to construct compartmentalized models for nicotine and cotinine distribution. These models were then calibrated and validated using data obtained from literature. The final models verified the therapeutic potential of the NV concept, identified four key parameters associated with vaccine success, and established correlates for success that could be used to evaluate future NVs prior to clinical trials. In the second approach, conjugate NV scaffoldings were engineered by using wild-type (WT) and chimeric human papilloma (HPV) 16 L1 protein virus-like particles (VLPs). The chimeric protein was created by removing the last 34 C-terminal residues from the WT protein and then incorporating a multi-epitope insert that could universally target major histocompatibility complex (MHC) class II molecules. The proteins were subsequently expressed in E. coli and purified using a multi-step process. Comparisons between the separation outcomes revealed that the insert was able to modulate individual process outcomes and improve overall yield without inhibiting VLP assembly. In the third approach, commonly used carrier proteins were computationally mined for their MHC class II epitope content using human leukocyte antigen (HLA) population frequency data and MHC epitope prediction software. The most immunogenic epitopes were concatenated with interspacing cathepsin cleavage sequences and the resulting protein was re-evaluated using the earlier methods. This work represents the first ever in silico design of chimeric antigens that could potentially target all of the major HLA DQ and HLA DR allotypes found in humans.
Computational Modeling of Planktonic and Biofilm Metabolism
Guo, Weihua (Virginia Tech, 2017-10-16)
Most of microorganisms are ubiquitously able to live in both planktonic and biofilm states, which can be applied to dissolve the energy and environmental issues (e.g., producing biofuels and purifying waste water), but can also lead to serious public health problems. To better harness microorganisms, plenty of studies have been implemented to investigate the metabolism of planktonic and/or biofilm cells via multi-omics approaches (e.g., transcriptomics and proteomics analysis). However, these approaches are limited to provide the direct description of intracellular metabolism (e.g., metabolic fluxes) of microorganisms. Therefore, in this study, I have applied computational modeling approaches (i.e., 13C assisted pathway and flux analysis, flux balance analysis, and machine learning) to both planktonic and biofilm cells for better understanding intracellular metabolisms and providing valuable biological insights. First, I have summarized recent advances in synergizing 13C assisted pathway and flux analysis and metabolic engineering. Second, I have applied 13C assisted pathway and flux analysis to investigate the intracellular metabolisms of planktonic and biofilm cells. Various biological insights have been elucidated, including the metabolic responses under mixed stresses in the planktonic states, the metabolic rewiring in homogenous and heterologous chemical biosynthesis, key pathways of biofilm cells for electricity generation, and mechanisms behind the electricity generation. Third, I have developed a novel platform (i.e., omFBA) to integrate multi-omics data with flux balance analysis for accurate prediction of biological insights (e.g., key flux ratios) of both planktonic and biofilm cells. Fourth, I have designed a computational tool (i.e., CRISTINES) for the advanced genome editing tool (i.e., CRISPR-dCas9 system) to facilitate the sequence designs of guide RNA for programmable control of metabolic fluxes. Lastly, I have also accomplished several outreaches in metabolic engineering. In summary, during my Ph.D. training, I have systematically applied computational modeling approaches to investigate the microbial metabolisms in both planktonic and biofilm states. The biological findings and computational tools can be utilized to guide the scientists and engineers to derive more productive microorganisms via metabolic engineering and synthetic biology. In the future, I will apply 13C assisted pathway analysis to investigate the metabolism of pathogenic biofilm cells for reducing their antibiotic resistance.
Correlating antisense RNA performance with thermodynamic calculations
Tanniche, Imen (Virginia Tech, 2013-02-08)
Antisense RNA (asRNA) strategies are identified as an effective and specific method for gene down-regulation at the post-transcriptional level. In this study, the major purpose is to find a correlation between the expression level and minimum free energy to enable the design of specific asRNA fragments. The thermodynamics of asRNA and mRNA hybridization were computed based on the fluorescent protein reporter genes. Three different fluorescent proteins (i) green fluorescent protein (GFP), (ii) cyan fluorescent protein (CFP) and (iii) yellow fluorescent protein (YFP) were used as reporters. Each fluorescent protein was cloned into the common pUC19 vector. The asRNA fragments were randomly amplified and the resulted antisense DNA fragments were inserted into the constructed plasmid under the control of an additional inducible plac promoter and terminator. The expression levels of fluorescent reporter protein were determined in real time by plate reader. Different results have been observed according to the fluorescent protein and the antisense fragment sequence. The CFP expression level was decreased by 50 to 78% compared to the control. However, with the GFP, the down-regulation did not exceed 30% for the different constructs used. For certain constructs, the effect was the opposite of expected and the expression level was increased. In addition, the YFP showed a weak signal compared to growth media, therefore the expression level was hard to be defined. Based on these results, a thermodynamic model to describe the relationship between the particular asRNA used and the observed expression level of the fluorescent reporter was developed. The minimum free energy and binding percentage of asRNA-mRNA complex were computed by NUPACK software. The expression level was drawn as a function of the minimum free energy. The results showed a weak correlation, but linear trends were observed for low energy values and low expression levels the CFP gene. The linear aspect is not verified for higher energy values. These findings suggest that the lower the energy is, the more stable is the complex asRNA-mRNA and therefore more reduction of the expression is obtained. Meanwhile, the non-linearity involves that there are other parameters to be investigated to improve the mathematical correlation. This model is expected to offer the chance to "fine-tune" asRNA effectiveness and subsequently modulate gene expression and redirect metabolic pathways toward the desired component. In addition, the investigation of the localization of antisense binding indicates that there are some regions that favors the hybridization and promote hence the down-regulation mechanisms.
Degenerate oligonucleotide primed amplification of genomic DNA for combinatorial screening libraries and strain enrichment
Freedman, Benjamin Gordon (Virginia Tech, 2014-12-22)
Combinatorial approaches in metabolic engineering can make use of randomized mutations and/or overexpression of randomized DNA fragments. When DNA fragments are obtained from a common genome or metagenome and packaged into the same expression vector, this is referred to as a DNA library. Generating quality DNA libraries that incorporate broad genetic diversity is challenging, despite the availability of published protocols. In response, a novel, efficient, and reproducible technique for creating DNA libraries was created in this research based on whole genome amplification using degenerate oligonucleotide primed PCR (DOP-PCR). The approach can produce DNA libraries from nanograms of a template genome or the metagenome of multiple microbial populations. The DOP-PCR primers contain random bases, and thermodynamics of hairpin formation was used to design primers capable of binding randomly to template DNA for amplification with minimal bias. Next-generation high-throughput sequencing was used to determine the design is capable of amplifying up to 98% of template genomic DNA and consistently out-performed other DOP-PCR primers. Application of these new DOP-PCR amplified DNA libraries was demonstrated in multiple strain enrichments to isolate genetic library fragments capable of (i) increasing tolerance of E. coli ER2256 to toxic levels of 1-butanol by doubling the growth rate of the culture, (ii) redirecting metabolism to ethanol and pyruvate production (over 250% increase in yield) in Clostridium cellulolyticum when consuming cellobiose, and (iii) enhancing L-arginine production when used in conjunction with a new synthetic gene circuit.
Detection of Environmental Contaminants in Water Utilizing Raman Scanning for E. coli Phenotype Changes
Flick, Hunter James (Virginia Tech, 2019-05-30)
Raman spectroscopy and its counterpart surface-enhanced Raman scattering (SERS) have proven to be effective methods for detecting miniscule changes in the phenotypes of E. coli and other single-celled organisms to aid in the detection of new strains for industrial use and discovery of new antibiotics. The purpose of this study is to develop a method to quickly and accurately detect contaminants in water samples through phenotype changes in E. coli measured through SERS. Contaminated Luria-Bertani (LB) media was inoculated with LB with an OD600 of 1, grown for two hours, and then dried on a flat piece of aluminum foil. These samples were then Raman scanned and processed to determine contaminant-induced changes to the phenotypes of the E. coli. Three types of tests were run to show the effectiveness of this method: single-component, multicomponent, and impure water sources. In single-component tests, it was found that differences due to NaCl contamination could be detected to 5.0E-9 weight percent (wt %), ethanol (EtOH) to 5.0E-7 volumetric percent (% v/v), citric acid (CA) to 2.8E-4 wt %, acetic acid (AA) to 2.6E-4 wt %, kanamycin to 2.5E-11 wt %, ampicillin to 2.5E-10 wt %, CoCl2 to trace amounts, and silver nanoparticles (AgNP) to 5.2E-7 wt %. Many of these are below the detection limits of analytical instrumentation, but their effects on E. coli phenotypes were detectable by Raman spectroscopy. Multicomponent tests showed that in a mixture, the most toxic or most concentrated contaminants have the most effect on cell phenotype. However, it was shown that similar concentrations of similar contaminants may be difficult to discern with current methods. This behavior was also seen in the impure water samples, showing that tap water behaves the closest to a DI control, followed by running water, and finally stagnant bodies. This new method of monitoring E. coli phenotypes with Raman spectroscopy as a biosensor shows promise for the fast, portable, and accurate determination of environmental contaminants with a broad-spectrum and very low detection limits.
Developing New Modalities for Biosensing using Synthetic Biology
Zhang, Ruihua (Virginia Tech, 2015-06-29)
Biosensors are devices that use biological components to detect important analytes. Biosensing systems have various applications in areas such as medicine, environmental monitoring, and process control. Classical biosensors are often based on bacteria or purified enzymes that have limitations on efficiency or stability. I have developed several new biosensors to overcome these disadvantages. Two preliminary biosensors were first created based on the extremely strong and specific interaction between biotin and (strept)avidin. Both biosensors showed high sensitivity and reliability for measuring biotin with detection limits of 50-1000 pg/ml and 20-100 ng/ml, respectively. Following these, a new biosensor was developed by coupling a mobile, functionalized microsurface with cell-free expression approaches. This biosensor demonstrated a dynamic range of 1- 100 ng/ml. In addition, I also explored the possibility of combining these biosensing systems with engineered living cells. By leveraging the tools of synthetic biology, a genetic circuit was designed, constructed, and inserted into bacteria for enhanced biotin biosynthesis in vivo. Upon induction, a 17-fold increase in biotin production was measured in the engineered cells in comparison to wild type cells using the biosensors created herein. These new biosensors, particularly the mobile biosensing modality, form a building block for advanced biosensing and drug delivery systems due to enhancements in mobility and specificity. In the future, these biosensing and cellular production systems could impact a range of fields ranging from biomedicine to environmental monitoring.
The Development of a Thermodynamic Model for Antisense RNA Design and an Electro-transformation Protocol to Introduce Auxotrophic Genes for Enhancing Eicosapentaenoic Acid Yield from Pythium irregulare
Yue, Yang (Virginia Tech, 2011-12-07)
Eicosapentaenoic acid (EPA, C20:5, n-3) is a long chain crucial unsaturated fatty acid, essential for the regulation of critical biological functions in humans. Its benefits include the therapeutic treatment of cardiovascular disease, schizophrenia and Alzheimer's disease. The fungus Pythium irregulare (ATCC 10951) has great potential as a natural EPA producer. In this study, the electroporation conditions for P. irregulare were determined. The auxotrophic selectable genes ura, trp and his were respectively cloned into the plasmid pESC to construct shuttle vectors. Electroporation with 2.0kV and a 0.2cm cuvette was applied as the most effective condition for heterogeneous genes transformation. The yield and content of EPA and other components of total fatty acids (TFA) were further determined by the FAME approach with GC, as well as the analysis of biomass. The EPA content in P. irregulare with heterologous pESC-TRP vector reached 16.68 mg/g if cultured in auxotrophic medium, which showed a 52.33% increase compared to the wild-type P. irregulare. The maximum of EPA yield was 98.52 mg/L from P. irregulare containing the pESC-URA plasmid, a 32.28% increase over the wild-type. However, the maximum cell dried weight of these two organisms were respectively 6.13g/L and 5.3g/L, significantly less than the 6.80g/L of the wild-type. Not only was a feasible approach detected to electro-transform and increase the EPA yield of P. irregulare, this study also inferred that Ï -6 route was mainly involved in the EPA biosynthesis in this organism. An antisense RNA (asRNA) thermodynamic model was developed to design new asRNA constructs capable of fine-tuning gene expression knockdown. The asRNA technology is now identified as an effective and specific method for regulating microbial gene expression at the posttranscriptional level. This is done by targeting mRNA molecules. Although the study of regulation by small RNAs is advanced in eukaryotes, the regulation of expression through artificially introducing antisense oligodeoxynucleotides into host is still being developed in prokaryotes. To study the thermodynamics of asRNA and mRNA binding, (i) the fluorescence protein genes GFP and mCherry were separately cloned into the common pUC19 vector and (ii) antisense GFP and antisense mCherry DNA fragments were randomly amplified and inserted into the constructed plasmid under the control of an additional plac promoter and terminator. The expression level of fluorescence reporter proteins was determined by plate reader in this combinatorial study. A thermodynamic model to describe the relationship between asRNA binding and observed expression level was created. The study indicates two factors that minimum binding energy of the asRNA-mRNA complex and the percentage of asRNA binding mRNA were crucial for regulating the expression level. The correlation relationship between gene expression level and binding percentage multiplied by the minimum binding energy was found to show a good correlation between the thermodynamic parameters and the observed level of gene expression. The model has the potential to predict the sequence of asRNA and the approach will ultimately be applied to cyanobacteria to increase lipids production. Here, the long-term approach is to build metabolic switches from asRNA that can turn "on/off" various cellular programs and metabolic pathways at will in a fine-tuned manner. This will allow engineers to control metabolic activity in response to reactor conditions.

Browsing by Author "Senger, Ryan S."

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