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Developing genomic models for cancer prevention and treatment stratificationGusenleitner, Daniel 12 February 2016 (has links)
Malignant tumors remain one of the leading causes of mortality with over 8.2 million deaths worldwide in 2012. Over the last two decades, high-throughput profiling of the human transcriptome has become an essential tool to investigate molecular processes involved in carcinogenesis. In this thesis I explore how gene expression profiling (GEP) can be used in multiple aspects of cancer research, including prevention, patient stratification and subtype discovery.
The first part details how GEP could be used to supplement or even replace the current gold standard assay for testing the carcinogenic potential of chemicals. This toxicogenomic approach coupled with a Random Forest algorithm allowed me to build models capable of predicting carcinogenicity with an area under the curve of up to 86.8% and provided valuable insights into the underlying mechanisms that may contribute to cancer development.
The second part describes how GEP could be used to stratify heterogeneous populations of lymphoma patients into therapeutically relevant disease sub-classes, with a particular focus on diffuse large B-cell lymphoma (DLBCL). Here, I successfully translated established biomarkers from the Affymetrix platform to the clinically relevant Nanostring nCounter© assay. This translation allowed us to profile custom sets of transcripts from formalin-fixed samples, transforming these biomarkers into clinically relevant diagnostic tools.
Finally, I describe my effort to discover tumor samples dependent on altered metabolism driven by oxidative phosphorylation (OxPhos) across multiple tissue types. This work was motivated by previous studies that identified a therapeutically relevant OxPhos sub-type in DLBCL, and by the hypothesis that this stratification might be applicable to other solid tumor types. To that end, I carried out a transcriptomics-based pan-cancer analysis, derived a generalized PanOxPhos gene signature, and identified mTOR as a potential regulator in primary tumor samples.
High throughput GEP coupled with statistical machine learning methods represent an important toolbox in modern cancer research. It provides a cost effective and promising new approach for predicting cancer risk associated to chemical exposure, it can reduce the cost of the ever increasing drug development process by identifying therapeutically actionable disease subtypes, and it can increase patients’ survival by matching them with the most effective drugs. / 2016-12-01T00:00:00Z
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Investigating Strategies to Enhance Microbial Production of and Tolerance Towards Aromatic BiochemicalsJanuary 2019 (has links)
abstract: Aromatic compounds have traditionally been generated via petroleum feedstocks and have wide ranging applications in a variety of fields such as cosmetics, food, plastics, and pharmaceuticals. Substantial improvements have been made to sustainably produce many aromatic chemicals from renewable sources utilizing microbes as bio-factories. By assembling and optimizing native and non-native pathways to produce natural and non-natural bioproducts, the diversity of biochemical aromatics which can be produced is constantly being improved upon. One such compound, 2-Phenylethanol (2PE), is a key molecule used in the fragrance and food industries, as well as a potential biofuel. Here, a novel, non-natural pathway was engineered in Escherichia coli and subsequently evaluated. Following strain and bioprocess optimization, accumulation of inhibitory acetate byproduct was reduced and 2PE titers approached 2 g/L – a ~2-fold increase over previously implemented pathways in E. coli. Furthermore, a recently developed mechanism to
allow E. coli to consume xylose and glucose, two ubiquitous and industrially relevant microbial feedstocks, simultaneously was implemented and systematically evaluated for its effects on L-phenylalanine (Phe; a precursor to many microbially-derived aromatics such as 2PE) production. Ultimately, by incorporating this mutation into a Phe overproducing strain of E. coli, improvements in overall Phe titers, yields and sugar consumption in glucose-xylose mixed feeds could be obtained. While upstream efforts to improve precursor availability are necessary to ultimately reach economically-viable production, the effect of end-product toxicity on production metrics for many aromatics is severe. By utilizing a transcriptional profiling technique (i.e., RNA sequencing), key insights into the mechanisms behind styrene-induced toxicity in E. coli and the cellular response systems that are activated to maintain cell viability were obtained. By investigating variances in the transcriptional response between styrene-producing cells and cells where styrene was added exogenously, better understanding on how mechanisms such as the phage shock, heat-shock and membrane-altering responses react in different scenarios. Ultimately, these efforts to diversify the collection of microbially-produced aromatics, improve intracellular precursor pools and further the understanding of cellular response to toxic aromatic compounds, give insight into methods for improved future metabolic engineering endeavors. / Dissertation/Thesis / Doctoral Dissertation Chemical Engineering 2019
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Integrative Computational Genomics Based Approaches to Uncover the Tissue-Specific Regulatory Networks in Development and DiseaseSrivastava, Rajneesh 03 1900 (has links)
Indiana University-Purdue University Indianapolis (IUPUI) / Regulatory protein families such as transcription factors (TFs) and RNA Binding Proteins (RBPs) are increasingly being appreciated for their role in regulating the respective targeted genomic/transcriptomic elements resulting in dynamic transcriptional (TRNs) and post-transcriptional regulatory networks (PTRNs) in higher eukaryotes. The mechanistic understanding of these two regulatory network types require a high resolution tissue-specific functional annotation of both the proteins as well as their target sites. This dissertation addresses the need to uncover the tissue-specific regulatory networks in development and disease. This work establishes multiple computational genomics based approaches to further enhance our understanding of regulatory circuits and decipher the associated mechanisms at several layers of biological processes. This study potentially contributes to the research community by providing valuable resources including novel methods, web interfaces and software which transforms our ability to build high-quality regulatory binding maps of RBPs and TFs in a tissue specific manner using multi-omics datasets. The study deciphered the broad spectrum of temporal and evolutionary dynamics of the transcriptome and their regulation at transcriptional and post transcriptional levels. It also advances our ability to functionally annotate hundreds of RBPs and their RNA binding sites across tissues in the human genome which help in decoding the role of RBPs in the context of disease phenotype, networks, and pathways.
The approaches developed in this dissertation is scalable and adaptable to further investigate the tissue specific regulators in any biological systems. Overall, this study contributes towards accelerating the progress in molecular diagnostics and drug target identification using regulatory network analysis method in disease and pathophysiology.
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SINGLE-CELL TRANSCRIPTOMICS OF HUMAN PANCREATIC ISLETS IN DIABETES AND ΒETA CELL DIFFERENTIATIONWeng, Chen 21 June 2021 (has links)
No description available.
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Connectivity Analysis of Single-cell RNA-seq Derived Transcriptional SignaturesMahi, Naim January 2020 (has links)
No description available.
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Defining Behavioral and Transcriptomic Signatures Associated with Opioid Craving in Male and Female RatsMayberry, Hannah Louise January 2022 (has links)
Opioid use disorder is a chronic, relapsing disease, with more than 85% of individuals experiencing a relapse episode within one year. One common reason patients relapse is due to intense cravings, which are defined as the compulsive urge to use the drug. In fact, craving was recently added to the DSM criteria for substance use disorder diagnosis. Counterintuitively, cravings intensify over the course of extended abstinence, especially in response to drug-paired cues, a phenomenon known as “incubation of craving”. This contributes to difficulty in maintaining long-term sobriety. The mesocorticolimbic reward pathway facilitates self-administration and cue-induced incubation of craving for drugs of abuse and natural rewards, such as sucrose. In particular, the shell sub-region of the nucleus accumbens is a critical brain region involved in context/cue-mediated reward seeking. In the experiments described here, we utilized an incubation of craving model, in which male and female rats self-administered opioids (morphine or heroin) or sucrose for 10 days. Sucrose served as an important control for delineating drug-induced changes from those caused in response to natural rewards, which are not the intended target of potential treatments. Reward delivery was paired with a cue light that was later used to elicit craving. After self-administration, rats underwent brief (one day) or extended (30 days) forced abstinence. One or 30 days later, they were returned to the chambers for a “cue test”, in which responses on the previously reward-associated lever triggered cue presentation, but no contingent reward. We used this model to further delineate behavioral and affective changes that accompany increased opioid craving in late abstinence, as well as molecular alterations underlying craving in rats that did not undergo a cue test. We found an opioid-specific behavioral signature in which peak opioid craving is accompanied by decreased grooming and hyperactivity in both sexes. We tracked the female estrous cycle throughout, as these fluctuations in reproductive hormones (akin to the menstrual cycle) are shown to affect cocaine- and nicotine-related behaviors. We found no differences between females in different phases of the estrous cycle in terms of self-administration, nor craving. RNA sequencing of the nucleus accumbens shell revealed robust changes in gene expression that occurred across extended abstinence, though the genes themselves were altered in a sex- and reinforcer-specific manner. In general, we found many behavioral and molecular changes that were unique to sex and reinforcer (sucrose versus opioids). This is promising in terms of identifying opioid-specific targets that are unlikely to affect the natural reward system in both sexes. Changes in gene expression in the brain are mediated in part by epigenetic processes that influence access of transcriptional machinery to DNA. Acetylation of histone tails, the proteins around which DNA is wrapped and packaged in the nucleus, have been identified as permissive marks that facilitate long-lasting changes in transcriptomics in response to environmental insults. Opioids promote increased acetylation, which may contribute to some of the reported changes here. We tested the efficacy of JQ1, a treatment that interferes with the read-out of opioid-induced acetylated marks, at attenuating heroin self-administration. When administered as an intracerebroventricular microinjection on self-administration day 11, JQ1 had no effect on subsequent heroin taking in either sex, suggesting that it may not be suitable as a systemic treatment at the dose given. These studies lay the groundwork for future studies to administer other treatments throughout abstinence, based on the opioid-specific genes and pathways identified here, to reduce cue-induced heroin craving and the accompanying suite of behaviors in males and females. / Psychology
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Transcriptomic Analysis of Early B-Cell Development in the Chicken EmbryoNuthalapati, Nikhil Krishna 14 December 2018 (has links)
The chicken bursa of Fabricius is a primary lymphoid tissue important for B-cell development. Our long-term goal is to understand the role of bursal microenvironment in an early B-cell differentiation event initiating repertoire development through immunoglobulin gene-conversion in the chick embryo. We hypothesize that early bursal B-cell differentiation is guided by signals through cytokine receptors. Our theory is based on previous evidence for expression of the receptor tyrosine kinase superfamily members and interleukin receptors in unseparated populations of bursal B-cells and bursal tissue. Knowledge of the expressed genes that are responsible for B-cell differentiation is a prerequisite for understanding the bursal microenvironment’s function. This project uses transcriptomic analysis to examine gene expression across an early B-cell differentiation event. RNA-seq was performed with total RNA isolated from developing B-cells at embryonic day (ED) 16 and ED 19 (n=3). Approximately 90 million high quality clean reads where obtained from the cDNA libraries. The analysis revealed differentially expressed genes involved in Wnt signaling pathway, Jak-STAT pathway, metabolic pathways, tyrosine metabolism, Toll-like receptor signaling pathway, MAPK signaling pathway, and cellhesion molecules. The transcripts for surface receptors, signal transduction and transcription factors identified in this study represent gene candidates for controlling B-cell differentiation in response to bursal microenvironmental factors.
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Development of computational tools and resources for systems biology of bacterial pathogensKumar, Ranjit 06 August 2011 (has links)
Bacterial pathogens are a major cause of diseases in human, agricultural plants and farm animals. Even after decades of research they remain a challenge to health care as they are known to rapidly evolve and develop resistance to the existing drugs. Systems biology is an emerging area of research where all of the components of the system, their interactions, and the dynamics can be studied in a comprehensive, quantitative, and integrative fashion to generate predictive models. When applied to bacterial pathogenesis, systems biology approaches will help identify potential novel molecular targets for drug discovery. A pre-requisite for conducting systems analysis is the identification of the building blocks of the system i.e. individual components of the system (structural annotation), identification of their functions (functional annotation) and identification of the interactions among the individual components (interaction prediction). In the context of bacterial pathogenesis, it is necessary to identify the host-pathogen interactions. This dissertation work describes computational resources that enable comprehensive systems level study of host pathogen system to enhance our understanding of bacterial pathogenesis. It specifically focuses on improving the structural and functional annotation of pathogen genomes as well as identifying host-pathogen interactions at a genome scale. The novel contributions of this dissertation towards systems biology of bacterial pathogens include three computational tools/resources. “TAAPP” (Tiling array analysis pipeline for prokaryotes) is a web based tool for the analysis of whole genome tiling array data for bacterial pathogens. TAAPP helps improve the structural annotation of bacterial genomes. “ISO-IEA” (Inferred from sequence orthology - Inferred from electronic annotation) is a tool that can be used for the functional annotation of any sequenced genome. “HPIDB” (Host pathogen interaction database) is developed with data a mining capability that includes host-pathogen interaction prediction. The new knowledge gained due to the implementation of these tools is the description of the non coding RNA as well as a computationally predicted host-pathogen interaction network for the human respiratory pathogen Streptococcus pneumoniae. In summary, the computation tools and resources developed in this dissertation study will enable building systems biology models of bacterial pathogens.
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<strong>Investigating the biochemical evolution and metabolic connections of shikonin biosynthesis in </strong><em><strong>Lithospermum erythrorhizon</strong></em>Thiti Suttiyut (15403820) 08 May 2023 (has links)
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<p>Shikonin is 1,4-naphthoquinones produced exclusively in Boraginaceae species. The compound and its derivatives are predominantly made in roots where they function in mediating plant-plant (allelopathic) and plant-microbe interactions. Moreover, this compound has been a target for drug development due to its strong anti-cancer properties. Our genome assembly and analysis of <em>Lithospermum erythrorhizon</em> uncovered metabolic innovation events that contributed to the evolution of the shikonin biosynthesis. This metabolic innovation also reveals the evolutionary link between shikonin biosynthesis and ubiquinone biosynthesis, one of the central metabolism functions in aerobic cellular respiration. To explore additional links between these two pathways, we used a transcriptome-based network analysis which uncovered a shikonin gene network model that predicts strong associations between primary metabolic pathway genes and known shikonin biosynthesis genes, as well as links with uncharacterized genes. <em>L. erythrorhizon</em> geranyldiphosphate (GPP) synthase (<em>LeGPPS</em>) is one of the candidates predicted by the network analysis, of which encodes a cytoplasmic enzyme shown in vitro to produce GPP. Knocking down of <em>LeGPPS</em> in <em>L. erythrorhizon </em>hairy roots (<em>LeGPPSi </em>lines) results in reduced shikonin content. This result provides functional evidence that cytoplasmic LeGPPS supplies GPP precursor to the shikonin biosynthesis. <em>LeGPPSi </em>lines also increased ubiquinone content, further supporting our hypothesis on the metabolic and evolutionary connection between shikonin and ubiquinone biosynthesis. Further RNA-seq analysis of the <em>LeGPPSi</em> line showed that downregulating <em>LeGPPS</em> significantly reduces the expression of benzenoid/phenylpropanoid genes, indicating the presence of factors that coordinately regulate the pathways providing the 4-hydroxybenzoic acid and GPP precursors to the shikonin pathway. In addition to <em>LeGPPS</em>, we also found<em> ubiquinone biosynthesis protein COQ4-like </em>gene (<em>LeCOQ4-L</em>) which provided another evolutionary link between shikonin and ubiquinone biosynthesis. The enzymatic activity of canonical COQ4 is unknown. In yeast, the protein is essential for ubiquinone biosynthesis and its metabolon formation. With the existing connections between shikonin and ubiquinone biosynthesis, if LeCOQ4 functions in the same manner as yeast COQ4, it is possible that <em>LeCOQ4-L </em>has an analogous function in shikonin biosynthesis as a structural protein for stabilizing biosynthesis metabolon. This leads us to the characterization of<em> COQ4</em> ortholog in Arabidopsis (<em>AtCOQ4</em>) to gain insight into its functional mechanism. Characterization of <em>atcoq4 </em>T-DNA mutant line showed that reduced <em>AtCOQ4</em> expression resulted in reduced ubiquinone. Further subcellular localization study revealed that AtCOQ4 and <em>LeCOQ4-L</em> localize in mitochondria without conventional transit peptide. We also performed pull-down assay to identify AtCOQ4 interactors which might be the missing enzymes that cannot be identified based on homology. 80 potential AtCOQ4 interactors were found including proteins like AtCHLM, GRIM-19, and AtSSLs. However, further study is needed to verify the protein interactions captured by pull-down assay. Taken all together, our study sheds light on the metabolic innovations that give rise to shikonin biosynthesis from ubiquinone biosynthesis and provide insight into the dynamics of the metabolic networks.</p>
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Big Data Meta-Analyses of Transcriptional Responses of Human Samples to Orthohantavirus Infection and Shotgun Metagenomics From Crohn's Disease Patients.Krapohl, John L. 11 August 2022 (has links)
Hantavirus is a dangerous zoonotic viral pathogen that is found across Asia, Europe, and the Americas. This virus causes a range of symptoms from flu-like malaise to heart failure and death. It is normally transmitted to humans via the aerosolized feces or urine of infected rodents. Currently, there are no known treatments for the disease, and it continues to threaten human health in endemic areas. In order to identify possible future therapeutic targets, we ran a meta-analysis of existing transcriptomic data collected from infected human tissue. Several genes and cellular pathways were identified, in addition to several potential therapeutics that warrant additional testing as potential future therapeutics for hantavirus infection. Such genes include, but are not limited to SLC27A3, NOG, AMIGO1, NUSAP1, and CDC25C which have not been previously associated with hantavirus infection. In addition, we identified that RIG-I and MDA5-associated anti-viral response genes are downregulated, while downstream elements of these pathways are upregulated, indicative of immune activation via alternate pathways. Finally, among the potential therapeutics we identified are dinaciclib, alvodicib, and ruxolitinib, which limit cellular replication, as well as ruxolitinib, baricitinib, and tofacitinib, which target other human intracellular pathways that may aid in successful viral infection. Crohn's disease is an autoimmune disorder that affects the digestive system of more than six million people worldwide, with most cases found in North America and Europe. Although the disease can occur throughout the entire digestive tract, the classical sign of disease progression is inflammation of the intestine. There are a number of factors that have been associated with the onset and progression of the disease including diet, antibiotics, stress, and bacterial infections, but no putative cause has been found. As diet and the gut biome play a significant role in disease progression, we aimed to find commonalities in the gut microbiomes of Crohn's patients, even when located in different geographical areas.
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