Browsing by Author "Zhang, Chenming"

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    Additive Manufacturing for Robust and Affordable Medical Devices
    Wolozny Gomez Robelo, Daniel Andre (Virginia Tech, 2016-10-18)
    Additive manufacturing in the form of 3D printing is a revolutionary technology that has developed within the last two decades. Its ability to print an object with accurate features down to the micro scale have made its use in medical devices and research feasible. A range of life-saving technologies can now go from the laboratory and into field with the application of 3D-printing. This technology can be applied to medical diagnosis of patients in at-risk populations. Living biosensors are limited by being Genetically Modified Organisms (GMOs) from being employed for medical diagnosis. However, by containing them within a 3D-printed enclosure, these technologies can serve as a vehicle to translate life-saving diagnosis technologies from the laboratory and into the field where the lower cost would allow more people to benefit from inexpensive diagnosis. Also, the GMO biosensors would be contained with a press-fit, ensuring that the living biosensors are unable to escape into the environment without user input. In addition, 3D-printing can also be applied to reduce the cost of lab-based technologies. Cell patterning technology is a target of interest for applying more cost-effective technologies, as elucidation of the variables defining cell patterning and motility may help explain the mechanics of cancer and other diseases. Through the use of a 3D-printed stamp, bacterial cells can be patterning without the use of a clean room, thus lowering the entry-barrier for researchers to explore cell patterning. With the commercialization of 3D-printing an opportunity has arisen to transition life-saving technologies into more cost-effective versions of existing technologies. This would not only allow more research into existing fields, but also to ensure that potentially life-saving technologies reach the people that need them.
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    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.
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    Assembly of Bio-Nanoparticles for Double Controlled Drug Release
    Huang, Wei; Zhang, Jianfei; Dorn, Harry C.; Zhang, Chenming (PLOS, 2013-09-06)
    A critical limiting factor of chemotherapy is the unacceptably high toxicity. The use of nanoparticle based drug carriers has significantly reduced the side effects and facilitated the delivery of drugs. Source of the remaining side effect includes (1) the broad final in vivo distribution of the administrated nanoparticles, and (2) strong basal drug release from nanoparticles before they could reach the tumor. Despite the advances in pH-triggered release, undesirable basal drug release has been a constant challenge under in vivo conditions. In this study, functionalized single walled carbon nanohorn supported immunoliposomes were assembled for paclitaxel delivery. The immunoliposomes were formulated with polyethylene glycol, thermal stable and pH sensitive phospholipids. Each nanohorn was found to be encapsulated within one immunoliposome. Results showed a highly pH dependent release of paclitaxel in the presence of serum at body temperature with minimal basal release under physiological conditions. Upon acidification, paclitaxel was released at a steady rate over 30 days with a cumulative release of 90% of the loaded drug. The drug release results proved our hypothesized double controlled release mechanism from the nanoparticles. Other results showed the nanoparticles have doubled loading capacity compared to that of traditional liposomes and higher affinity to breast cancer cells overexpressing Her2 receptors. Internalized nanoparticles were found in lysosomes.
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    Cell-Free Biosystems Comprised of Synthetic Enzymatic Pathways: Development of Building Blocks, Immobilization of Enzymes, Stabilization of Cascade Enzymes, and Generation of Hydrogen
    Myung, Suwan (Virginia Tech, 2013-05-08)
    The production of hydrogen from low-cost abundant renewable biomass would be vital to sustainable development. Cell-free (in vitro) biosystems comprised of synthetic enzymatic pathways would be a promising biomanufacturing platform due to several advantages, such as high product yield, fast reaction rate, easy control and access, and so on. However, it is essential to produce (purified) enzymes at low costs and stabilize them for long periods to decrease biocatalyst costs. Thermophilic recombinant enzymes as building blocks were discovered and developed: fructose 1,6-bisphosphatase (FBP) from Thermotoga maritime, phosphoglucose isomerase (PGI) from Clostridium thermocellum, triose phosphate isomerase (TIM) from Thermus thermophiles and fructose bisphosphate aldolase (ALD) from T. maritima and T. thermophilus. The recombinant proteins were over-expressed in E. coli, purified and characterized. For purification and stabilization of enzymes, one-step, simple, low-cost purification and immobilization methods were developed based on simple adsorption of cellulose-binding module (CBM)-tagged protein on the external surface of high-capacity regenerated amorphous cellulose. Also, a simple, low-cost purification method of thermophilic enzymes was developed utilizing a combination of heat and ammonium sulfate precipitation. For development of cascade enzymes as building modules (biocatalyst modules), it was discovered that the presence of other enzymes/proteins had a strong synergetic effect on the stabilization of the thermolabile enzyme (e.g., PGI) due to the in vitro macromolecular crowding effect. And substrate channeling among CBM-tagged self-assembled three-enzyme complex (synthetic matabolon) immobilized on the easily-recycled cellulose-containing magnetic nanoparticles can not only increase cascade reaction rates greatly, but also decrease enzyme cost in cell-free biosystems. The high product yield and fast reaction rate of dihydrogen from sucrose was validated in a batch reaction containing fifteen enzymes comprising a non-natural synthetic pathway. The yield of dihydrogen production from 2 mM of sucrose was 96.7 % compared to theoretical yield at 37 °C. The maximum rate was increased 3.1 fold when the substrate concentration was increased from 2 to 50 mM in a fed-batch reaction. The research and development of cell-free biosystems for biomanufacturing require more efforts, especially in low-cost recombinant thermostable enzymes as building blocks, efficient cofactor recycling, enzyme and cofactor stabilization, and fast reaction rates.
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    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.
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    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.
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    Computational mining of MHC class II epitopes for the development of universal immunogenic proteins
    Saylor, Kyle; Donnan, Ben; Zhang, Chenming (PLOS, 2022)
    The human leukocyte antigen (HLA) gene complex, one of the most diverse gene complexes found in the human genome, largely dictates how our immune systems recognize pathogens. Specifically, HLA genetic variability has been linked to vaccine effectiveness in humans and it has likely played some role in the shortcomings of the numerous human vaccines that have failed clinical trials. This variability is largely impossible to evaluate in animal models, however, as their immune systems generally 1) lack the diversity of the HLA complex and/or 2) express major histocompatibility complex (MHC) receptors that differ in specificity when compared to human MHC. In order to effectively engage the majority of human MHC receptors during vaccine design, here, we describe the use of HLA population frequency data from the USA and MHC epitope prediction software to facilitate the in silico mining of universal helper T cell epitopes and the subsequent design of a universal human immunogen using these predictions. This research highlights a novel approach to using in silico prediction software and data processing to direct vaccine development efforts.
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    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.
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    Consistent Fabrication of Ultrasmall PLGA Nanoparticles and their Potential Biomedical Applications
    Lohneis, Taylor Paige (Virginia Tech, 2019-12-04)
    Nanotechnology and its potential for biomedical applications has become an area of increasing interest over the last few decades. Specifically, ultrasmall nanoparticles, ranging in size from 5 to 50 nm, are highly sought after for their physical and chemical properties and their ability to be easily transmitted though the bloodstream. By adjusting the material properties, size, surface potential, morphology, surface modifications, and more, of nanoparticles, it is possible to tailor them to a specific use in biomedical areas such as drug and gene delivery, biodetection of pathogens or proteins, and tissue engineering. The aim of this study was to fabricate ultrasmall poly-(lactic-co-glycolic acid) nanoparticles (PLGA NPs) using a quick and easy nanoprecipitation method1, with some modifications, for general use in various biomedical areas. Nanoprecipitation of two solutions – PLGA dissolved in acetonitrile and aqueous poly(vinyl alcohol) (PVA) – at varying concentrations produced ultrasmall nanoparticles that range in size, on average, from 10 to 30 nm. By the data collected from this study, a selection method can be used to choose a desired PLGA nanoparticle size given a potential biomedical application. The desired nanoparticle can be fabricated using specific concentrations of the two nanoprecipitation solutions. Size of the ultrasmall PLGA NPs was characterized by dynamic light scattering (DLS) and confirmed by transmission electron microscopy (TEM). Spherical morphology of the PLGA NPs was also proved by TEM. By generalizing the ultrasmall PLGA NP fabrication process, the idea is that these NPs will be able to be used in various biomedical applications depending on the goal of the furthered study. As an example of potential application, ~15 to 20 nm PLGA NPs were consistently fabricated for use as virus-like particle (VLP) scaffolds. Following formation, PLGA NPs were introduced to modified human papillomavirus (HPV) protein during protein refolding and assembly into virus-like particles (VLPs) via buffer exchange. The size of the VLPs was monitored with and without PLGA nanoparticles present in solution during the refolding process and TEM images were collected to confirm encapsulation.
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    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.
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    Cracking the code of cathepsin S: Structural determinants of specificity switching
    DeHority, Riley Ambrose (Virginia Tech, 2025-01-09)
    Cathepsin S is a cysteine protease in the papain family that digests antigens as part of the adaptive immune response, activates receptors, and is associated with extracellular matrix degradation in autoimmune diseases and cancer. A comprehensive review of the literature revealed potential pH- and redox-dependent specificity switches in the proteolytic specificity of cathepsin S. These were investigated through the digestion of peptides across a variety of pH and redox conditions. These experiments confirmed both pH- and redox-dependent patterns of proteolytic specificity, with narrowed specificity in alkaline and oxidizing conditions. An analysis of publicly available structures of cathepsin S identified a lysine residue which descends into the S3 pocket of the active site above pH 7.0, acting as a pH-dependent gate. Energy minimization of crystal structures show disorder in the loops which make up the active site of the protein, which increases in disorder when the disulfide bonds on the surface of cathepsin S are reduced. This is explored as a potential mechanism for the redox-dependent specificity identified in the digest experiments. These specificity switches may contribute to pathological structural damage attributed to cathepsin S, as pH and redox dysregulation are features of several cathepsin S-associated diseases.
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    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.
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    Designs of Antigen Structure and Composition for Improved Protein-Based Vaccine Efficacy
    Saylor, Kyle; Gillam, Francis; Lohneis, Taylor; Zhang, Chenming (2020-02-24)
    Today, vaccinologists have come to understand that the hallmark of any protective immune response is the antigen. However, it is not the whole antigen that dictates the immune response, but rather the various parts comprising the whole that are capable of influencing immunogenicity. Protein-based antigens hold particular importance within this structural approach to understanding immunity because, though different molecules can serve as antigens, only proteins are capable of inducing both cellular and humoral immunity. This fact, coupled with the versatility and customizability of proteins when considering vaccine design applications, makes protein-based vaccines (PBVs) one of today's most promising technologies for artificially inducing immunity. In this review, we follow the development of PBV technologies through time and discuss the antigen-specific receptors that are most critical to any immune response: pattern recognition receptors, B cell receptors, and T cell receptors. Knowledge of these receptors and their ligands has become exceptionally valuable in the field of vaccinology, where today it is possible to make drastic modifications to PBV structure, from primary to quaternary, in order to promote recognition of target epitopes, potentiate vaccine immunogenicity, and prevent antigen-associated complications. Additionally, these modifications have made it possible to control immune responses by modulating stability and targeting PBV to key immune cells. Consequently, careful consideration should be given to protein structure when designing PBVs in the future in order to potentiate PBV efficacy.
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    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.
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    Development of Virus-like particles (VLPs) Based Vaccines Against Porcine Reproductive and  Respiratory Syndrome Virus (PRRSV) and Porcine Epidemic Diarrhea Virus (PEDV)
    Lu, Yi (Virginia Tech, 2020-03-16)
    Porcine reproductive and respiratory syndrome virus (PRRSV) and porcine epidemic diarrhea virus (PEDV) are two of the most prevalent swine pathogens that have impacted the global swine industry for decades. Both are RNA viruses with increasing heterogeneity over the years, making a vaccine solution ever so challenging. Modified live-attenuated vaccines (MLVs) have been the most common approach, but the long-term safety regarding their potential for pathogenic reversion still needs to be addressed. Subunit based vaccines have been the focus of numerous development studies around the world with renewed interest in their promising prospects in both safety and efficacy. Our lab has developed a unique approach to use hepatitis B virus core capsid protein (HBcAg) as a vaccine delivery vehicle for either PRRSV or PEDV viral epitope antigens. Recombinantly produced HBcAg forms an icosahedral capsid virus-like particle (VLP) that has 240 repeats in a single assembled particle. By inserting different epitope antigens from these porcine pathogens into the particle, we can achieve repetitive antigen presentation to the host's immune system by taking advantage of the polymeric nature of VLP. The first animal study evaluated the efficacy of 4 VLP based vaccine candidates against PRRSV in mice. These 4 vaccines incorporated 2 B-cell epitopes (61QAAIEVYEPGRS72 and 89ELGFVVPPGLSS100) and 2 T-cell epitopes (117LAALICFVIRLAKNC131 and 149KGRLYRWRSPVIIEK163) from PRRSV structural proteins GP3 and GP5 respectively. Candidate GP3-4 was able to stimulate a significant viral neutralizing response in mouse sera against two PRRSV strains, one being heterologous, demonstrating its potential of cross-protection against PRRSV. The second animal study took an optimized VLP vaccine candidate against PEDV from previous development studies in mice, and assessed its efficacy through a comprehensive pregnant gilt vaccination and neonatal piglet challenge model. The vaccine candidate incorporated B-cell epitope 748YSNIGVCK755 from the PEDV spike protein. It was able to elicit significant viral neutralization antibody titer in gilt milk at 3 days post-farrowing (DPF), and provided nursing piglets with clinical relief in terms of morbidity, viral shedding, small intestinal lesions, and 10 days post-challenge (DPC) survival rate.
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    Discovery of a Novel Microalgal Strain Scenedesmus Sp. A6 and Exploration of Its Potential as a Microbial Cell Factory
    Guimaraes Braga da Silva, Pedro Ivo (Virginia Tech, 2018-08-14)
    Microalgae are photosynthetic organisms considered to be one of the most promising high-value chemicals and biofuel-producing organisms. However, there are several challenges for the widespread implementation of industrial processes using microalgae. The work presented in this dissertation proposes solutions to the different challenges involving the use of microalgae as microbial cell factories. To investigate the application of anaerobic digestion as a way to generate nutrients for microbial growth, salmon offal was used as substrate for anaerobic digestion, and soil from a flooded run-off pond on the Virginia Tech campus in Blacksburg, VA. A fast reduction in volatile solids and the short-chain fatty acid production profile is favorable for the growth of microalgae. A novel algae strain Scenedesmus sp. A6 was isolated from a decorative waterfountain in a hotel in Madison, IN. Mixotrophic growth trials were conducted using wastewater from the salmon offal digestion, that demostrated the A6 isolate grows six times faster in the wastewater then autotrophically. Bioassays of ethanolic cell extracts of A6 cultures demonstrated antimicrobial activity against E. coli cells at concentrations above 50 µg/ml. Genome sequencing and assembly revealed multiple copies of genes involved with acetate and ammonia metabolism, and several genes involved with secondary metabolite synthesis. An alternative to the high capital investment of photobioreactors for the cultivation of microalgae is the use of open-source and open-hardware bioreactor controller. Here, the concept of an open-hardwate bioreactor control called ``BioBrain'' is introduced. The BioBrain device is based on the Arduino Mega micro-controller board, and is capable of monitoring and controlling culture conditions during simple strain characterization studies, with an estimated construction cost of less than $800 USD. Finally, a new primer design tool for the ligation-independant cloning technique 𝜆-PCR was developed called lambdaPrimeR. The contributions of this work are the discovery and development of different tools that can overcome the challenges of the use of microalgae as microbial cell factories in industrial processes.
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    Domain-based Bioinformatics Analysis and Molecular Insights for the Autoregulatory Mechanism of Phafin2
    Hasan, Mahmudul (Virginia Tech, 2024-08-19)
    Phafin2, an adaptor protein, is involved in various cellular processes, such as apoptosis, autophagy, endosomal cargo transportation, and macropinocytosis. Two domains, namely, PH and FYVE, contribute to Phafin2's cell membrane binding. Phafin2 also contains a poly aspartic acid (polyD) motif in its C-terminal region that can specifically autoinhibit the PH domain binding to membrane phosphatidylinositol 3-phosphate (PtdIns3P). Firstly, the study investigated the domain-based evolutionary pattern of PH, FYVE, and polyD motif of Phafin2 among its orthologs and Phafin2- like proteins. Using different bioinformatics tools and resources, it was concluded that the polyD motif only evolved in Phafin2 and PH- or both PH-FYVE-containing proteins of animals, highlighting the association in cellular functions that might have evolved uniquely in animals. Moreover, PH domain-free FYVE-containing proteins lack polyD motifs. Secondly, intramolecular autoregulatory and membrane binding properties of Phafin2 were studied by employing liposome co-sedimentation assay, isothermal titration calorimetry, and nuclear magnetic resonance spectroscopy. The residues Gly38, Lys45, Leu45, Lys51, Ala52, and Arg53 of the PH domain form a positively charged binding pocket that can bind the negatively charged polyD motif. The mutated Phafin2 PH domain (K51A/R53C and R53C) was unable to bind to synthetic polyD peptides, establishing the significance of those residues for the interaction between the PH domain and polyD motif. Moreover, the study also concluded that Phafin2-mediated membrane binding is not curvature-dependent.
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    Effect of de novo peptide properties on self-assembling large amyloid fibers
    Rippner, Caitlin Marie Weigand (Virginia Tech, 2013-05-14)
    Amyloid aggregation involves the spontaneous formation of fibers from misfolded proteins. This process requires low energy input, results in robust fibers, and is thus of interest from a materials manufacturing perspective. The effect of glutamine content and hydrophobicity of template peptides on amyloid aggregation of a template-peptide system involving myoglobin was studied at near-physiological conditions by Fourier transform infrared spectroscopy, atomic force microscopy, field emission scanning electron microscopy, and nanoindentation. Hydrophobic interactions were found to be important for controlled hierarchical fiber growth via a cooperative mechanism, with the largest effect in myoglobin mixtures. Hydrophobic packing increased for most systems as aggregation progressed. The largest changes in structure occurred upon drying. When myoglobin was present with the highest glutamine-containing template (P7), the high glutamine peptide was not effective as a template, since it appeared to prefer self-catalysis. A low level of glutamine in some unordered templates was insufficient for amyloid development. However, templating was more important in glutamine-free templates mixed with myoglobin, which formed fibers with a surprisingly high elastic modulus. This may have been due to template patterning. Nanoindentation results confirmed that glutamine blocks were not necessary for strong intermolecular interactions and cooperative fibril formation.
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    Efficiency of Interferon-γ in Activating Dendritic Cells and Its Potential Synergy with Toll-like Receptor Agonists
    Bian, Yuanzhi; Walter, Debra L.; Zhang, Chenming (MDPI, 2023-05-19)
    Interferon-γ (IFN-γ) is a cytokine that plays an important role in immune regulation, especially in the activation and differentiation of immune cells. Toll-like receptors (TLRs) are a family of pattern-recognition receptors that sense structural motifs related to pathogens and alert immune cells to the invasion. Both IFN-γ and TLR agonists have been used as immunoadjuvants to augment the efficacy of cancer immunotherapies and vaccines against infectious diseases or psychoactive compounds. In this study, we aimed to explore the potential of IFN-γ and TLR agonists being applied simultaneously to boost dendritic cell activation and the subsequent antigen presentation. In brief, murine dendritic cells were treated with IFN-γ and/or the TLR agonists, polyinosinic–polycytidylic acid (poly I:C), or resiquimod (R848). Next, the dendritic cells were stained for an activation marker, a cluster of differentiation 86 (CD86), and the percentage of CD86-positive cells was measured by flow cytometry. From the cytometric analysis, IFN-γ efficiently stimulated a considerable number of the dendritic cells, while the TLR agonists by themselves could merely activate a few compared to the control. The combination of IFN-γ with poly I:C or R848 triggered a higher amount of dendritic cell activation than IFN-γ alone. For instance, 10 ng/mL IFN-γ with 100 µg/mL poly I:C achieved 59.1% cell activation, which was significantly higher than the 33.4% CD86-positive cells obtained by 10 ng/mL IFN-γ. These results suggested that IFN-γ and TLR agonists could be applied as complementary systems to promote dendritic cell activation and antigen presentation. There might be a synergy between the two classes of molecules, but further investigation is warranted to ascertain the interaction of their promotive activities.
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    Exploring candidate genes and rhizosphere microbiome in relation to iron cycling in Andean potatoes
    Xiao, Hua (Virginia Tech, 2017-06-05)
    Fe biofortification of potato is a promising strategy to prevent Fe deficiency worldwide either through traditional breeding or biotechnological approaches. These approaches require the identification of candidate genes to uptake, transport and store Fe in potato tubers. We employed multiple approaches including SNP genotyping, QTL analysis, identifying genes orthologous to Arabidopsis ferrome, yeast complementation assay and genetic transformation to avoid the limitation from a single approach. We revealed several candidate genes potentially associated with potato plant Fe acquisition, PGSC0003DMG400024976 (metal transporter), PGSC0003DMG400013297 (oligopeptide transporter), PGSC0003DMG400021155 (IRT1) and IRTunannotated (an ortholog to the IRT gene that is not annotated in the potato genome). The microorganisms in the rhizosphere react intensely with the various metabolites released by plant roots in a variety of ways such as positive, negative, and neutral. These interactions can influence the uptake and transport of micronutrients in the plant roots. Therefore, the contribution of soil microorganisms in the rhizosphere to improve Fe supply of plants may play a key role in Fe biofortification, especially under real world field-based soil scenarios. We thus investigated rhizosphere microbial community diversity in Andean potato landraces to understand the role of plant-microbial interaction in potato Fe nutrient cycling. From the analysis of the high-throughput Illumina sequences of 16S and ITS region of ribosomal RNA gene, we found that both potato landraces with low and high Fe content in tubers and a landrace on which low or high Fe content fertilizer was applied to the leaf surface had large impacts on the rhizosphere fungal community composition. Indicator species analysis (ISA) indicated that Operational Taxonomic Units (OTUs) contributing most to these impacts were closely related to Eurotiomycetes and Leotiomycetes in the phylum Ascomycota, Glomeromycetes in the phylum Glomeromycota and Microbotryomycetes in the phylum Basidiomycota. Lots of species from these groups have been shown to regulate plant mineral nutrient cycling. Our research revealed potential candidate genes and fungal taxa involved in the potato plant Fe nutrient dynamics, which provides new insights into crop management and breeding strategies for sustainable Fe fortification in agricultural production.