Lens culinaris, the common lentil, contains a lectin which has been shown to be specific for a glycoprotein saliva antigen and a glycolipoprotein serum antigen. Both the saliva and serum precipitin reactions with the lectin are directly inhibited with saccharides, especially those related to D-mannose. Electrophoresis of the serum antigen showed that it migrates as three bands, while appearing as a single band in double diffusion precipitin patterns. Quantitative studies of the saliva antigen levels by hemagglutination inhibition titration indicated a polygenic, quantitative mode of inheritance with a minimum heritability of O. 34. Blood group ABH secretor individuals were found to have a significantly lower mean saliva antigen level than nonsecretor individuals. The lectins from Pisum sativum and Canavaliafiensiformis formed precipitin bands of identity with L.culinaris lectin against saliva. C. ensiformis and L. culinaris lectins exhibited precipitin bands of partial identity against serum; and P. sativum and L. culinaris lectins exhibited a pattern of identity against serum. In addition, precipitin patterns of partial identity with the non-H lectin from Lotus tetragonolobus has been demonstrated. Using Ulex europaeus lectin in hemagglutination inhibition experiments with saliva from blood group O secretor individuals, a minimum heritability of approximately 0.40 for H antigen levels was found. A higher frequency of nonsecretor individuals was observed in the Black population compared with the White population.

Propionic acidemia is an autosomal recessively inherited disorder of organic acid metabolism caused by deficient activity of propionyl CoA carboxylase. This enzyme is required for the catabolism of the odd-chain fatty acids, the side chain of cholesterol and the amino acids: isoleucine, methionine, and threonine. Although the clinical expression of this disorder is variable, affected children usually develop ketoacidosis and hyperammonemia which may progress to seizures, coma and possibly death. Some patients may exhibit vomiting, lethargy and hypotonia in the first few weeks of life whereas others may remain asymptomatic for months or even years.(1) The degree of residual enzyme activity in the tissues from these patients does not correlate to this apparent clinical heterogeneity. The relationship between the clinical variation observed among propionyl CoA carboxylase deficient patients and the corresponding genetic and biochemical make up, is not yet understood. The aim of this project is to study the biochemical and immunological properties of propionyl CoA carboxylase in liver homogenates and fibroblast samples from several patients with propionic acidemia, to gain a better understanding of the nature of the defect in this disorder. Previous comparisons of propionyl CoA carboxylase from fibroblasts of patients with this enzyme deficiency and unaffected individuals have suggested that propionyl CoA carboxylase is structurally altered in the patients with propionic acidemia. The fibroblast lines from these patients can be categorized into two major genetic complementation groups, pccA and pccBC based on the increase in activity observed in heterokaryons formed by pairwise cell fusions.(2) In addition, the defective propionyl CoA carboxylase can be differentiated biochemically from the normal enzyme and from each compIementation group.(3) These differences suggest that the aIterations in propionyl CoA carboxylase structure in each complementation group represent mutations in different subunits. In addition, mutations within a single gene resulting slightly different enzyme structures, would explain the clinical variation within a complementation group. Therefore, biochemical differences among mutant propionyl CoA carboxylases from the same c0mp1ementation group were investigated. To provide further evidence that propionic acidemia is the result of structural alterations in propionyl CoA carboxylase, immunologic techniques were used to determine if equal quantities of cross-reacting material (CRM) were present in liver and fibrobiast homogenates from propionyl CoA carboxyIase deficient patients from the various genetic complementation groups. Antiserum prepared against purified pig heart propionyl CoA carboxylase which cross-reacts with human propionyI CoA carboxyIase and another antiserum prepared against the human biotin-containing enzymes, were compared using immunotitration techniques. These tests demonstrated that there are equal quantities of cross-reacting material in the tissue homogenates of propionic acidemia patients.(4, 5) Investigations were undertaken to biochemically characterize and evaluate the heterogeneity within the pccBC genetic complementation group. This group was chosen because previous complementation and biochemical studies with fibroblasts from the pccBC subgroups have suggested the existence of interallelic complementation in this group. (6) Specific biochemical differences among propionyl CoA carboxylases from cells belonging to patients in this group could identify heterogeneity and characterize the complementation pattern. Normal and mutant propionyl CoA carboxylase from the pccBC complementation group were highly purified and their biochemical properties were compared using their isoelectric paint, thermostabiilty, and enzyme affinity for substrates. The properties of the purified enzymes were then compared with propionyl CoA carboxylase from other mutants in this group. These comparisons demonstrated biochemical heterogeneity within the pccBC complementation group.(7) The results provide compelling evidence that the defect in propionic acidemia represents a structural alteration of propionyl CoA carboxylase in the pccA and pccBC complementation groups. In addition, the biochemical heterogeneity demonstrated within the pccBC complementation group suggests that several different structural mutations, possibly of the same subunit, are involved that result in slightly different biochemical parameters for each mutant enzyme. These structural alterations may explain the complicated complementation map for the pccBC subgroups. Since interallelic complementation is based on the heteropolymer being slightly more active than the homopolymer, different structural alterations in the mutants may interfere with their ability to participate in interallelic complementation. Furthermore, biochemical differences within the group may be reflected in the clinical phenotype of the disease and may be an indicator of the clinical variation which has been observed in these patients.

Inflammatory autoimmune diseases like Crohn's Disease (CD) and Rheumatoid Arthritis (RA) share some of the same single nucleotide polymorphisms (SNPs) in protein tyrosine phosphatase non-receptor types 2 and 22 (PTPN2/22), which contribute to their pathogenesis. In clinical CD and RA samples, PTPN2:rs478582 and PTPN22:rs2476601 were found to exacerbate a number of inflammatory processes associated with CD and RA. To confirm the role of these SNPs in CD and RA pathogenesis, CRISPR-Cas9 was used to induce the SNPs in T-cells. Cells were also treated with the naturally occurring polyamine, spermidine, to restore PTPN2/22 function and reverse the inflammatory effects of the SNPs. The PTPN2 SNP decreased PTPN2 expression by 3.2-fold and the PTPN22 SNP decreased PTPN22 expression by 2.4-fold compared to WT T-cells. Proliferation increased by 10.2-fold in PTPN2 SNP cells and 8.4-fold in the PTPN22 SNP cells compared to WT cells. Both SNPs increased secretion levels IFN-γ and TNF-α. Additionally, 80.32% of PTPN2 SNP cells and 85.82% of PTPN22 SNP cells were activated compared to 70.48% of WT T-cells. Spermidine treatment increased PTPN2/22 expression in all cell types and was dose-dependent in cells with either SNP. Proliferation levels decreased by approximately 5-fold in spermidine treated PTPN2 SNP cells and 3.1-fold in PTPN22 SNP cells treated with 10 µM of spermidine and 12.0-fold when treated with 20 uM. IFN-γ and TNF-α secretion levels decreased with spermidine treatment in all cell groups. Lastly, T-cell activation decreased to 51.39% of PTPN2 SNP cells and 46.36% of PTPN22 SNP cells when treated with 10 µM of spermidine. These findings may explain the therapeutic response seen in CD and RA patients prescribed polyamines. This study confirms the inflammatory role of the PTPN2/22 SNPs and displays the anti-inflammatory and restorative property of spermidine for its potential therapeutic use in CD and RA patients with genetic polymorphisms.

Glioblastoma Multiforme (GBM) is the most lethal subtype of glioma (brain tumor), with a 5-year survival rate of merely 5.6% post diagnosis1. The traditional study of glioblastoma has investigated the role of multiple genes in advancing its progression, including the upregulation of Epidermal Growth Factor Receptor (EGFR). However, there is at yet little research into the epigenetic factors that control EGFR, both in the precursor astrocytes and in glioblastomas themselves2. EGFR and its regulation may play a significant role in the progression and development of GBM from astrocytes. Through modification of genomic pathways as observed in GBM, our lab generated an in vitro glioblastoma model that is representative of the pathways modulated in glioblastoma. The purpose of this study was to investigate the modulation of epigenetic factors that occurs upon conversion from astrocyte to glioblastoma-like cells using epigenetic and expression analysis methods, in hopes of revealing potential therapeutic venues for future study. The study revealed that activating marks present in astrocytes were in fact downregulated in the glioblastoma cells leading to decreased expression of wild-type EGFR mRNA. Further exploration may provide more clues as to why this modulation occurs.

16S ribosomal RNA (rRNA) gene sequences are commonly analyzed for taxonomic and phylogenetic purposes because they contain variable regions that help distinguish genera. However, intra-genus classification is difficult due to high sequence similarity among closely related species. The biological impact of nucleotide variants in 16S variable regions are often unknown and hence their sequence differences are weighted evenly during classification, which provides poor species identity confidence. In this dissertation, I determined that analysis of intra-genus 16S allelic variants can provide species information and that nucleotide changes in 16S rRNA variable regions can impact ribosome quality. In one study, I analyzed ribosomal gene sequences, including 16S variable regions, to identify microbes that can spoil different retail draft beers. Based on relative sequence abundance changes of variable region sequences, I determined that certain bacteria preferred growth on draft lines rather than beers. Sequences of certain species were consistently detected at ratios indicative of their 16S gene copies, suggesting they came from specific strains. In a second study, I computationally interrogated 16S variable sequences in closely related genera Escherichia and Shigella and discovered that certain species could be differentiated. I demonstrated that Escherichia coli ribosomes were compromised when they carried 16S rRNA with these species-informative nucleotides, suggesting that variable region nucleotides may be constrained to respective species. In a third study, metagenomic sequencing was used to identify organisms that resided on cables submerged off the coast of Florida. Relative abundances of DNA for putative polymer-degrading organisms reduced over time and DNA for putative polymer-degrading enzymes were present at low relative abundance. Altogether, this dissertation shows the capabilities of DNA-based microbial identification and suggests that acknowledgment 16S alleles can improve intra-genus bacterial classification.

The overall aim of the studies described herein was to evaluate genetic variation in cattle fertility traits for development of genetic and genomic predictors in breeding strategies. Results from these experiments suggest that improvements in fertility through genetic selection are a possible approach to increase reproductive efficiency. Experiment 1 evaluated the development of genetic parameters associated with multiple ovulation and embryo transfer schemes in an attempt to assist producers in identifying animals with greater genetic merit for these protocols. This study confirmed that genetic selection of donors or sires appears to be a potential approach to improve efficiency of MOET procedures. Although low heritability would slow the progress, results shown in this work suggest that genetic improvement in fertility by selection for embryo transfer traits is possible. Experiment 2 evaluated fertility traits in Argentinean Holstein cattle in order to develop fertility genetic predictors for utilization in breeding strategies. The dollar fertility index ($F) included age to first calving (AFC) as a measure of initial reproductive performance and calving interval (CI) as an indicator of conception rate and success of early insemination. Values for $F ranged from -$76.6 to $139.4 in the current Holstein population. Results indicated substantial variation in fertility traits, suggesting that genetic selection would be highly effective in improving fertility.

MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression and play an essential role in phenotype development. The regulation mechanism behind miRNA reveals insight into gene expression and gene regulation. Transcription Start Site(TSS) is the key to studying gene expression. However, the TSSs of miRNAs can be thousands of nucleotides away from the precursor miRNAs, which makes it hard to be detected by conventional RNA-Seq experiments. Some previous methods tried to take advantage of sequencing data using sequence features or integrated epigenetic markers, but resulted in either not condition-specific or low-resolution prediction. Furthermore, the availability of a large amount of Single-Cell RNA-Seq(scRNA-Seq) data provides remarkable opportunities for studying gene regulatory mechanisms at single-cell resolution. Incorporating the gene regulatory mechanisms can assist with cell type identification and state discovery from scRNA-Seq data. In this dissertation, we studied computational modeling of gene transcription initialization and expression, including two novel approaches to identify TSSs with various type of conditions and one case study at the single-cell level. Firstly, we studied how TSS can be identified based on Cap Analysis Gene Expression (CAGE) experiments data using the thriving Deep Learning Neural Network. We used a control model to study the Deepbind binding score features that the protein binding motif model can improve overall prediction performance. Furthermore, comparing data from unseen cell lines showed better performance than existing tools. Secondly, to better predict the TSSs of miRNA in a condition-specific manner, we built D-miRT, a two-steam convolutional neural network based on integrated low-resolution epigenetic features and high-resolution sequence features. D-miRT outperformed all baseline models and demonstrated high accuracy for miRNA TSS prediction tasks. Compared with the most recent approaches on cell-specific miRNA TSS identification using cell lines that were unseen to the model training processes, D-miRT also showed superior performance. Thirdly, to study gene transcription initialization and regulation from single-cell perspective, we developed INSISTC, an unsupervised machine learning-based approach that incorporated network structure information for single-cell type classification. In contrast to other clustering algorithms, we showed that INSISTC with the SC3 algorithm provides cluster number estimation. Future studies on gene expression and regulation will benefit from INSISTC's adaptability with regard to the kinds of biological networks that can be used.

Due to their biocompatibility and parallel data processing, DNA computational devices are highly desired for applications in diagnosis and treatment of cancer, infectious and genetic diseases. Much like in modern electronic devices, DNA computation is based on the logic gates - by directly interacting with DNA or RNA input molecules, they produce a specific output depending on their embedded logic function. This work is devoted to the development of functional parts of a future DNA nanorobot for biomedical applications. Specifically, we used DNA nanotechnology and the concept of multicomponent DNA probes to develop three parts of the DNA nanorobot: computing, actuating, and sensing. The computation function was addressed by developing construct with two integrated NAND gates, capable of processing three different DNA or RNA inputs. The second "smart" construct produces actuating function – cleavage of RNA for housekeeping gene in response to recognition of RNA inputs, generated by cancer cells. The third construct is an original DNA "Cephalopod-tile", with improved sensing function, capable of recognizing highly structured biological analytes, such as 16S rRNA of E.coli, as well as increasing hybridization kinetics with targets up to 465 times. These nanoconstructs contributed to development of original DNA nanomachine with OR logic function for treatment of cancer. Theses for Defense 1. Computing: It is possible to design tile-associated DNA NAND logic gates that can be integrated in communicating circuits. 2. Actuating: It is possible to create a DNA nano-construction that can cut out a marker fragment from a longer RNA sequence and use it as an activator for triggering cleavage of another RNA sequence. 3. Sensing: A DNA probe equipped with analyte capture function can increase hybridization rates between DNA and RNA analytes. 4. Sensing, computation, and actuating: It is possible to design multifunctional DNA nanomachines with sensing, computation, and therapeutic modules.

Gene expression is an essential mechanism for physical and mental development of human. Aberrant regulation of gene expression creates abnormality in human body than can lead to complicated diseases. Gene expression can be regulated at any stage from the chromatin unfolding stage to post-translation stage of protein. In this study, we focused on two important factors of gene expression regulation that participate in the gene expression process at the transcription and the post-transcriptional stages; enhancer-promoter interactions and miRNA-mRNA interactions. The enhancer-promoter interactions are difficult to detect due to the large distance between the enhancer and promoter region and cell-specific activity of the interactions. The cell-specific interactions have not been well studied due to inconsistent feature availability in different cells. We designed a tool that considers a large variety of enhancer-promoter interaction features in different cell lines, can deal with missing features, and can predict cell-specific interactions with better accuracy than the available tools. By analyzing the cell-specific interactions from different sources we also found that enhancers-promoter interactions are shared in groups. MiRNA-mRNA interactions are more complicated in human than other organism because of the imperfectness of the interactions and the smaller size and complex target choosing strategy of the miRNA. Available miRNA target prediction tools, designed on canonical features, often suffer from low accuracy with the new experimentally supported datasets. These tools do not consider the position-wise binding preference and relationship between adjacent positions and regions of the miRNA sequence. Here, we designed a Markov-model based feature to capture this position wise information from experimental data sets, which can be incorporated with any prediction tool to improve the performance of the tool.

Until recently, complete understanding of the endogenous activity of pathologically relevant genes was out of reach and research was confined to in situ work, plasmid-based constructs and artificial model systems. The development and expansion of the CRISPR/Cas9 genome editing technique has enabled us to explore the molecular underpinnings of gene activation using the cell's own endogenous regulatory environment. In this work, we report on the development of a novel tool to monitor the endogenous activity of a causative gene in Parkinson's disease, a-synuclein. We use CRISPR/Cas9 to insert a highly sensitive engineered luciferase at the C-terminal of a-synuclein and assessed its responses to stimuli. Our system responds to epigenetic stimuli, which was unable to be recapitulated by previously available gene activity assays. After development of a sensitive detection tool for epigenetic stimuli, we focused on developed a modular suite of epigenetic writers and erasers by modification of the SunTag protein tagging system and used catalytically dead Cas9 (dCas9) to direct our modular epigenetic toolkit to individual genes. We show that our toolkit of epigenetic effectors successfully writes epigenetic information in a site-specific manner. Using the sensitive a-synuclein reporter we previously developed, we screen the promoter region of this pathologically relevant gene at high resolution and identify the most effective areas for epigenetic intervention in this cell line. These tools allow us to dissect and understand the endogenous regulatory mechanisms of almost any gene targetable by Cas9 in ways that were not previously available may prove to be an effective strategy for persistently altering pathologic transcriptional activity. This system offers a strong tool for to dissect and understand underlying epigenetic architecture and opens potential new avenues for therapeutic strategies for various disease conditions.