Matching Items (21)
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This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develo

This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develop a gene regulatory pathway, and 2) utilize this pathway to determine suitable drug therapeutics for prevention and treatment. Using a Gene Set Enrichment Analysis (GSEA), a set of 1000 gene identifiers from a Mayo Clinic database was analyzed to determine the most significant genetic variants related to insulin signaling pathways involved in Type II Diabetes. The following genes were identified: NRAS, KRAS, PIK3CA, PDE3B, TSC1, AKT3, SOS1, NEU1, PRKAA2, AMPK, and ACC. In an extensive literature review and cross-analysis with Kegg and Reactome pathway databases, novel SNPs located on these gene variants were identified and used to determine suitable drug therapeutics for treatment. Overall, understanding how genetic mutations affect target gene function related to Type II Diabetes disease pathology is crucial to the development of effective diagnosis and treatment. This project provides new insight into the molecular basis of the Type II Diabetes, serving to help untangle the regulatory complexity of the disease and aid in the advancement of diagnosis and treatment. Keywords: Type II Diabetes mellitus, Gene Set Enrichment Analysis, genetic variants, KEGG Insulin Pathway, gene-regulatory pathway
ContributorsBucklin, Lindsay (Co-author) / Davis, Vanessa (Co-author) / Holechek, Susan (Thesis director) / Wang, Junwen (Committee member) / Nyarige, Verah (Committee member) / School of Human Evolution & Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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Description
This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develo

This research project investigated known and novel differential genetic variants and their associated molecular pathways involved in Type II diabetes mellitus for the purpose of improving diagnosis and treatment methods. The goal of this investigation was to 1) identify the genetic variants and SNPs in Type II diabetes to develop a gene regulatory pathway, and 2) utilize this pathway to determine suitable drug therapeutics for prevention and treatment. Using a Gene Set Enrichment Analysis (GSEA), a set of 1000 gene identifiers from a Mayo Clinic database was analyzed to determine the most significant genetic variants related to insulin signaling pathways involved in Type II Diabetes. The following genes were identified: NRAS, KRAS, PIK3CA, PDE3B, TSC1, AKT3, SOS1, NEU1, PRKAA2, AMPK, and ACC. In an extensive literature review and cross-analysis with Kegg and Reactome pathway databases, novel SNPs located on these gene variants were identified and used to determine suitable drug therapeutics for treatment. Overall, understanding how genetic mutations affect target gene function related to Type II Diabetes disease pathology is crucial to the development of effective diagnosis and treatment. This project provides new insight into the molecular basis of the Type II Diabetes, serving to help untangle the regulatory complexity of the disease and aid in the advancement of diagnosis and treatment.
ContributorsDavis, Vanessa Brooke (Co-author) / Bucklin, Lindsay (Co-author) / Holechek, Susan (Thesis director) / Wang, Junwen (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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High throughput transcriptome data analysis like Single-cell Ribonucleic Acid sequencing (scRNA-seq) and Circular Ribonucleic Acid (circRNA) data have made significant breakthroughs, especially in cancer genomics. Analysis of transcriptome time series data is core in identifying time point(s) where drastic changes in gene transcription are associated with homeostatic to non-homeostatic cellular

High throughput transcriptome data analysis like Single-cell Ribonucleic Acid sequencing (scRNA-seq) and Circular Ribonucleic Acid (circRNA) data have made significant breakthroughs, especially in cancer genomics. Analysis of transcriptome time series data is core in identifying time point(s) where drastic changes in gene transcription are associated with homeostatic to non-homeostatic cellular transition (tipping points). In Chapter 2 of this dissertation, I present a novel cell-type specific and co-expression-based tipping point detection method to identify target gene (TG) versus transcription factor (TF) pairs whose differential co-expression across time points drive biological changes in different cell types and the time point when these changes are observed. This method was applied to scRNA-seq data sets from a SARS-CoV-2 study (18 time points), a human cerebellum development study (9 time points), and a lung injury study (18 time points). Similarly, leveraging transcriptome data across treatment time points, I developed methodologies to identify treatment-induced and cell-type specific differentially co-expressed pairs (DCEPs). In part one of Chapter 3, I presented a pipeline that used a series of statistical tests to detect DCEPs. This method was applied to scRNA-seq data of patients with non-small cell lung cancer (NSCLC) sequenced across cancer treatment times. However, this pipeline does not account for correlations among multiple single cells from the same sample and correlations among multiple samples from the same patient. In Part 2 of Chapter 3, I presented a solution to this problem using a mixed-effect model. In Chapter 4, I present a summary of my work that focused on the cross-species analysis of circRNA transcriptome time series data. I compared circRNA profiles in neonatal pig and mouse hearts, identified orthologous circRNAs, and discussed regulation mechanisms of cardiomyocyte proliferation and myocardial regeneration conserved between mouse and pig at different time points.
ContributorsNyarige, Verah Mocheche (Author) / Liu, Li (Thesis advisor) / Wang, Junwen (Thesis advisor) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not

Beta-Amyloid(Aβ) plaques and tau protein tangles in the brain are now widely recognized as the defining hallmarks of Alzheimer’s disease (AD), followed by structural atrophy detectable on brain magnetic resonance imaging (MRI) scans. However, current methods to detect Aβ/tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (positron emission tomography (PET)). And one of the particular neurodegenerative regions is the hippocampus to which the influence of Aβ/tau on has been one of the research projects focuses in the AD pathophysiological progress. In this dissertation, I proposed three novel machine learning and statistical models to examine subtle aspects of the hippocampal morphometry from MRI that are associated with Aβ /tau burden in the brain, measured using PET images. The first model is a novel unsupervised feature reduction model to generate a low-dimensional representation of hippocampal morphometry for each individual subject, which has superior performance in predicting Aβ/tau burden in the brain. The second one is an efficient federated group lasso model to identify the hippocampal subregions where atrophy is strongly associated with abnormal Aβ/Tau. The last one is a federated model for imaging genetics, which can identify genetic and transcriptomic influences on hippocampal morphometry. Finally, I stated the results of these three models that have been published or submitted to peer-reviewed conferences and journals.
ContributorsWu, Jianfeng (Author) / Wang, Yalin (Thesis advisor) / Li, Baoxin (Committee member) / Liang, Jianming (Committee member) / Wang, Junwen (Committee member) / Wu, Teresa (Committee member) / Arizona State University (Publisher)
Created2022
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This dissertation presents three novel algorithms with real-world applications to genomic oncology. While the methodologies presented here were all developed to overcome various challenges associated with the adoption of high throughput genomic data in clinical oncology, they can be used in other domains as well. First, a network informed feature

This dissertation presents three novel algorithms with real-world applications to genomic oncology. While the methodologies presented here were all developed to overcome various challenges associated with the adoption of high throughput genomic data in clinical oncology, they can be used in other domains as well. First, a network informed feature ranking algorithm is presented, which shows a significant increase in ability to select true predictive features from simulated data sets when compared to other state of the art graphical feature ranking methods. The methodology also shows an increased ability to predict pathological complete response to preoperative chemotherapy from genomic sequencing data of breast cancer patients utilizing domain knowledge from protein-protein interaction networks. Second, an algorithm that overcomes population biases inherent in the use of a human reference genome developed primarily from European populations is presented to classify microsatellite instability (MSI) status from next-generation-sequencing (NGS) data. The methodology significantly increases the accuracy of MSI status prediction in African and African American ancestries. Finally, a single variable model is presented to capture the bimodality inherent in genomic data stemming from heterogeneous diseases. This model shows improvements over other parametric models in the measurements of receiver-operator characteristic (ROC) curves for bimodal data. The model is used to estimate ROC curves for heterogeneous biomarkers in a dataset containing breast cancer and cancer-free specimen.
ContributorsSaul, Michelle (Author) / Dinu, Valentin (Thesis advisor) / Liu, Li (Committee member) / Wang, Junwen (Committee member) / Arizona State University (Publisher)
Created2021
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The probiotic effects of Lactobacillus reuteri have been speculated to partly depend on its capacity to produce the antimicrobial substance reuterin during the reduction of glycerol in the gut. In this study, the potential of this process to protect human intestinal epithelial cells against infection with Salmonella enterica serovar Typhimurium

The probiotic effects of Lactobacillus reuteri have been speculated to partly depend on its capacity to produce the antimicrobial substance reuterin during the reduction of glycerol in the gut. In this study, the potential of this process to protect human intestinal epithelial cells against infection with Salmonella enterica serovar Typhimurium was investigated. We used a three-dimensional (3-D) organotypic model of human colonic epithelium that was previously validated and applied to study interactions between S. Typhimurium and the intestinal epithelium that lead to enteric salmonellosis. Using this model system, we show that L. reuteri protects the intestinal cells against the early stages of Salmonella infection and that this effect is significantly increased when L. reuteri is stimulated to produce reuterin from glycerol. More specifically, the reuterin-containing ferment of L. reuteri caused a reduction in Salmonella adherence and invasion (1 log unit), and intracellular survival (2 log units). In contrast, the L. reuteri ferment without reuterin stimulated growth of the intracellular Salmonella population with 1 log unit. The short-term exposure to reuterin or the reuterin-containing ferment had no observed negative impact on intestinal epithelial cell health. However, long-term exposure (24 h) induced a complete loss of cell-cell contact within the epithelial aggregates and compromised cell viability. Collectively, these results shed light on a potential role for reuterin in inhibiting Salmonella-induced intestinal infections and may support the combined application of glycerol and L. reuteri. While future in vitro and in vivo studies of reuterin on intestinal health should fine-tune our understanding of the mechanistic effects, in particular in the presence of a complex gut microbiota, this the first report of a reuterin effect on the enteric infection process in any mammalian cell type.

Created2012-05-31
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This study presents the first global transcriptional profiling and phenotypic characterization of the major human opportunistic fungal pathogen, Candida albicans, grown in spaceflight conditions. Microarray analysis revealed that C. albicans subjected to short-term spaceflight culture differentially regulated 452 genes compared to synchronous ground controls, which represented 8.3% of the analyzed

This study presents the first global transcriptional profiling and phenotypic characterization of the major human opportunistic fungal pathogen, Candida albicans, grown in spaceflight conditions. Microarray analysis revealed that C. albicans subjected to short-term spaceflight culture differentially regulated 452 genes compared to synchronous ground controls, which represented 8.3% of the analyzed ORFs. Spaceflight-cultured C. albicans–induced genes involved in cell aggregation (similar to flocculation), which was validated by microscopic and flow cytometry analysis. We also observed enhanced random budding of spaceflight-cultured cells as opposed to bipolar budding patterns for ground samples, in accordance with the gene expression data. Furthermore, genes involved in antifungal agent and stress resistance were differentially regulated in spaceflight, including induction of ABC transporters and members of the major facilitator family, downregulation of ergosterol-encoding genes, and upregulation of genes involved in oxidative stress resistance.

Finally, downregulation of genes involved in actin cytoskeleton was observed. Interestingly, the transcriptional regulator Cap1 and over 30% of the Cap1 regulon was differentially expressed in spaceflight-cultured C. albicans. A potential role for Cap1 in the spaceflight response of C. albicans is suggested, as this regulator is involved in random budding, cell aggregation, and oxidative stress resistance; all related to observed spaceflight-associated changes of C. albicans. While culture of C. albicans in microgravity potentiates a global change in gene expression that could induce a virulence-related phenotype, no increased virulence in a murine intraperitoneal (i.p.) infection model was observed under the conditions of this study. Collectively, our data represent an important basis for the assessment of the risk that commensal flora could play during human spaceflight missions. Furthermore, since the low fluid-shear environment of microgravity is relevant to physical forces encountered by pathogens during the infection process, insights gained from this study could identify novel infectious disease mechanisms, with downstream benefits for the general public.

Created2013-12-04
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Astronauts are exposed to a unique combination of stressors during spaceflight, which leads to alterations in their physiology and potentially increases their susceptibility to disease, including infectious diseases. To evaluate the potential impact of the spaceflight environment on the regulation of molecular pathways mediating cellular stress responses, we performed a

Astronauts are exposed to a unique combination of stressors during spaceflight, which leads to alterations in their physiology and potentially increases their susceptibility to disease, including infectious diseases. To evaluate the potential impact of the spaceflight environment on the regulation of molecular pathways mediating cellular stress responses, we performed a first-of-its-kind pilot study to assess spaceflight-related gene-expression changes in the whole blood of astronauts. Using an array comprised of 234 well-characterized stress-response genes, we profiled transcriptomic changes in six astronauts (four men and two women) from blood preserved before and immediately following the spaceflight. Differentially regulated transcripts included those important for DNA repair, oxidative stress, and protein folding/degradation, including HSP90AB1, HSP27, GPX1, XRCC1, BAG-1, HHR23A, FAP48, and C-FOS. No gender-specific differences or relationship to number of missions flown was observed. This study provides a first assessment of transcriptomic changes occurring in the whole blood of astronauts in response to spaceflight.

ContributorsBarrila, Jennifer (Author) / Ott, C. Mark (Author) / LeBlanc, Carly (Author) / Mehta, Satish K. (Author) / Crabbe, Aurelie (Author) / Stafford, Phillip (Author) / Pierson, Duane L. (Author) / Nickerson, Cheryl (Author) / ASU Biodesign Center Immunotherapy, Vaccines and Virotherapy (Contributor) / Biodesign Institute (Contributor)
Created2016-12-08
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Bismuth drugs, despite being clinically used for decades, surprisingly remain in use and effective for the treatment of Helicobacter pylori infection, even for resistant strains when co-administrated with antibiotics. However, the molecular mechanisms underlying the clinically sustained susceptibility of H. pylori to bismuth drugs remain elusive. Herein, we report that

Bismuth drugs, despite being clinically used for decades, surprisingly remain in use and effective for the treatment of Helicobacter pylori infection, even for resistant strains when co-administrated with antibiotics. However, the molecular mechanisms underlying the clinically sustained susceptibility of H. pylori to bismuth drugs remain elusive. Herein, we report that integration of in-house metalloproteomics and quantitative proteomics allows comprehensive uncovering of the bismuth-associated proteomes, including 63 bismuth-binding and 119 bismuth-regulated proteins from Helicobacter pylori, with over 60% being annotated with catalytic functions. Through bioinformatics analysis in combination with bioassays, we demonstrated that bismuth drugs disrupted multiple essential pathways in the pathogen, including ROS defence and pH buffering, by binding and functional perturbation of a number of key enzymes. Moreover, we discovered that HpDnaK may serve as a new target of bismuth drugs to inhibit bacterium-host cell adhesion. The integrative approach we report, herein, provides a novel strategy to unveil the molecular mechanisms of antimicrobial metals against pathogens in general. This study sheds light on the design of new types of antimicrobial agents with multiple targets to tackle the current crisis of antimicrobial resistance.

ContributorsWang, Yuchuan (Author) / Hu, Ligang (Author) / Xu, Feng (Author) / Quan, Quan (Author) / Lai, Yau-Tsz (Author) / Xia, Wei (Author) / Yang, Ya (Author) / Chang, Yuen-Yan (Author) / Yang, Xinming (Author) / Chai, Zhifang (Author) / Wang, Junwen (Author) / Chu, Ivan K. (Author) / Li, Hongyan (Author) / Sun, Hongzhe (Author) / College of Health Solutions (Contributor)
Created2017-04-19
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Competing endogenous RNAs (ceRNAs) are RNA molecules that sequester shared microRNAs (miRNAs) thereby affecting the expression of other targets of the miRNAs. Whether genetic variants in ceRNA can affect its biological function and disease development is still an open question. Here we identified a large number of genetic variants that

Competing endogenous RNAs (ceRNAs) are RNA molecules that sequester shared microRNAs (miRNAs) thereby affecting the expression of other targets of the miRNAs. Whether genetic variants in ceRNA can affect its biological function and disease development is still an open question. Here we identified a large number of genetic variants that are associated with ceRNA's function using Geuvaids RNA-seq data for 462 individuals from the 1000 Genomes Project. We call these loci competing endogenous RNA expression quantitative trait loci or ‘cerQTL’, and found that a large number of them were unexplored in conventional eQTL mapping. We identified many cerQTLs that have undergone recent positive selection in different human populations, and showed that single nucleotide polymorphisms in gene 3΄UTRs at the miRNA seed binding regions can simultaneously regulate gene expression changes in both cis and trans by the ceRNA mechanism. We also discovered that cerQTLs are significantly enriched in traits/diseases associated variants reported from genome-wide association studies in the miRNA binding sites, suggesting that disease susceptibilities could be attributed to ceRNA regulation. Further in vitro functional experiments demonstrated that a cerQTL rs11540855 can regulate ceRNA function. These results provide a comprehensive catalog of functional non-coding regulatory variants that may be responsible for ceRNA crosstalk at the post-transcriptional level.

ContributorsLi, Mulin Jun (Author) / Zhang, Jian (Author) / Liang, Qian (Author) / Xuan, Chenghao (Author) / Wu, Jiexing (Author) / Jiang, Peng (Author) / Li, Wei (Author) / Zhu, Yun (Author) / Wang, Panwen (Author) / Fernandez, Daniel (Author) / Shen, Yujun (Author) / Chen, Yiwen (Author) / Kocher, Jean-Pierre A. (Author) / Yu, Ying (Author) / Sham, Pak Chung (Author) / Wang, Junwen (Author) / Liu, Jun S. (Author) / Liu, X. Shirley (Author) / College of Health Solutions (Contributor)
Created2017-05-02