Browsing by Subject "Microarray"

Now showing 1 - 8 of 8
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    Development and testing of gene expression biomarkers for gonadal dysgenesis in conjunction with the US EPA endocrine disruptor screening program's Tier 2 larval amphibian growth and development assay
    (2014-04) Haselman, Jonathan Thomas
    The Endocrine Disrupter Screening Program of US EPA has recently developed a Tier 2 testing guideline using model amphibian species Xenopus laevis. The Larval Amphibian Growth and Development Assay assesses a chemical's endocrine-related effects in vivo and generates concentration-response information for ecological risk-assessment. Currently, the assay relies on histopathological evaluations for identifying endocrine-related reproductive effects. However, histopathology can seldom define the chemical mode of action and is not easily interpreted in the context of risk assessment when the effects are minimal to moderate. This study explores the use of gene expression biomarkers in the gonad that could potentially inform a chemical's mode of action and detect adverse reproductive effects that are otherwise uncharacterized by histopathology. To identify candidate biomarkers, global expression was analyzed in differentiating ovary and testis tissues of Xenopus tropicalis. Genetic programs responsible for reproductive maturation in gonad tissues were characterized and provided a foundation from which specific genes could be selected proximal to a model chemical's known mode of action. Four genes were selected within the putative androgen molecular network to evaluate as biomarkers of the anti-androgen mode of action characteristic of a common fungicide, prochloraz. Following continuous exposure to prochloraz throughout embryonic, larval and juvenile development in Xenopus laevis, assessments of growth, liver and kidney pathology, and reproductive development were made. To evaluate the predictive capabilities of the candidate genes, one gonad was kept in situ for histopathological evaluations while the other was processed for mRNA analyses. Results indicate that prochloraz exposure caused metabolic toxicity in the liver and kidney; it caused testis degeneration coincident with the onset of androgen-mediated spermatogenesis and inhibited regression of Müllerian ducts. Two of the four candidate genes showed increases in expression at the high test concentration and appeared to be predictive of an anti-androgen-induced adaptive response. The behavior of these biomarkers stimulated valuable discussion and generated testable hypotheses to better understand the evolution of molecular mechanisms driving gonad development in a cross-species context. This study provides a model for expression-based biomarker development in endocrine tissues and offers direction toward enhanced ecological risk-assessment.
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    Genomic analysis of regulatory mechanisms involved in secondary metabolite production.
    (2010-09) Castro-Melchor, Marlene
    Many secondary metabolites have beneficial uses for humans. In addition to their use as antibacterial and antifungal agents, secondary metabolites have been used as immunosuppressants, anti-tumor agents, and antiparasitics. Most of the secondary metabolites known today are produced by filamentous fungi or by members of the Streptomyces genus. Production of secondary metabolites by microorganisms involves a complex, dynamic system, with interconnected elements acting at different levels. Diverse tools were used in this work to explore regulation of secondary metabolite production, mostly in Streptomyces. The tools have a common characteristic: they either generate large amounts of data, or require large amounts of data. Regulation of secondary metabolite production in Streptomyces coelicolor was analyzed at the genome level, by using network modules inferred from a large transcriptome dataset. The upstream sequence of the elements in the network modules was searched for the presence of consensus sequences, and these results combined with information on known interactions, binding sites, and functional relatedness. The combination of this information resulted in a set of twenty networks that have a high likelihood of representing true interactions and represent a starting point for further experimental studies. The characteristics of high productivity were analyzed by comparing the genomes of two strains of the clavulanic acid producer Streptomyces clavuligerus. One of the strains is a high producer of clavulanic acid. Next generation sequence data was used to perform a genome-wide screening to identify all the differences between the two genomes. In addition to mutations in genes involved in β-lactam antibiotic production or their upstream region, structural differences were detected between the two strains. Next generation sequencing technologies were also used to assemble a draft genome for the curdlan producer Agrobacterium sp. ATCC 31749. Curdlan production mimics that of secondary metabolites, it is triggered under starvation conditions. These varied approaches exemplify some of the paths that can lead to a better understanding of secondary metabolism and its regulation.
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    High-throughput transcriptomic analysis of resource-poor mammalian cell lines for recombinant protein production
    (2013-10) Johnson, Kathryn Christine
    Over the past 30 years, mammalian cell culture has enabled the production of recombinant protein therapeutics for treatment of a broad range of debilitating or life-threatening diseases. Continual improvements in cell and process engineering have facilitated the attainment of once unheard-of product titers, and improvements in molecular analysis techniques and process analytic technologies have been employed with great success for cell culture process characterization. High-throughput transcriptomic analysis tools such as microarrays and next-generation RNA sequencing (RNA-seq) provide access to gene expression information by simultaneously measuring the expression levels of tens of thousands of genes. However, until recently such tools have not been used to their full advantage in mammalian cell culture processes due to limitations in available reference sequences for the industrially important Chinese hamster ovary (CHO) and baby hamster kidney (BHK) cell lines. We employed high-throughput RNA sequencing in several CHO cell lines to identify and interrogate a class of small non-coding RNAs called microRNAs (miRNAs), which mediate post-transcriptional repression of protein-coding genes. We annotated and analyzed the expression and genomic conservation of several hundred of these small RNAs. We also employed RNA sequencing to build a comprehensive reference transcriptome for a recombinant protein-producing BHK cell lines. We utilized the BHK reference sequence to enable analysis of gene expression levels in the BHK cell line and two Syrian hamster tissues. We designed an expression microarray from the BHK sequence and utilized it to analyze the transcriptome profiles of BHK cells at several time points in perfusion culture at manufacturing scale. Implementation of several functional analysis tools revealed a consistent time-dependent change in the transcriptome profile that involved down-regulation of extracellular matrix components and changes to calcium signaling genes. The transcriptomic reference sequences we developed in this research and the detailed studies they have enabled will enhance our ability to understand and further optimize cell culture processes.
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    Incorporating biological knowledge of genes into microarry data analysis.
    (2009-04) Tai, Feng
    Microarray data analysis has become one of the most active research areas in bioinformatics in the past twenty years. An important application of microarray technology is to reveal relationships between gene expression profiles and various clinical phenotypes. A major characteristic in microarray data analysis is the so called "large p, small n" problem, which makes it difficult for parameter estimation. Most of the traditional statistical methods developed in this area target to overcome this difficulty. The most popular technique is to utilize an L1 norm penalty to introduce sparsity into the model. However, most of those traditional statistical methods for microarray data analysis treat all genes equally, as for usual covariates. Recent development in gene functional studies have revealed complicated relationships among genes from biological perspectives. Genes can be categorized into biological functional groups or pathways. Such biological knowledge of genes along with microarray gene expression profiles provides us the information of relationships not only between gene and clinical outcomes but also among the genes. Utilizing such information could potentially improve the predictive power and gene selection. The importance of incorporating biological knowledge into analysis has been increasingly recognized in recent years and several new methods have been developed. In our study, we focus on incorporating biological information, such as the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, into microarray data analysis for the purpose of prediction. Our first method aims implement this idea by specifying different L1 penalty terms for different gene functional groups. Our second method models a covariance matrix for the genes by assuming stronger within-group correlations and weaker between-group correlations. The third method models spatial correlations among the genes over a gene network in a Bayesian framework.
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    Phosphorylated and SUMO-deficient progesterone receptors drive proliferative gene signatures during breast cancer progression.
    (2012-07) Knutson, Todd Philip
    Introduction: Progesterone receptors (PR) are emerging as important breast cancer drivers. Phosphorylation events common to breast cancer cells impact PR transcriptional activity, in part by direct phosphorylation. PR-B but not PR-A isoforms are phosphorylated on Ser294 by MAPK and CDK2. Phospho-Ser294 PRs are resistant to ligand-dependent Lys388 SUMOylation (i.e. a repressive modification). Antagonism of PR SUMOylation by mitogenic protein kinases provides a mechanism for derepression (i.e. transcriptional activation) of target genes. As a broad range of PR protein expression is observed clinically, a PR gene signature would provide a valuable marker of PR contribution to early breast cancer progression. Methods: Global gene expression patterns were measured in T47D and MCF-7 breast cancer cells expressing either wild-type (SUMOylation-capable) or K388R (SUMOylation-deficient) PRs and subjected to pathway analysis. Gene sets were validated by RT-qPCR. Recruitment of coregulators and histone methylation levels were determined by chromatin immunoprecipitation. Changes in cell proliferation and survival were determined by MTT and western blotting. Finally, human breast tumor cohort datasets were probed to identify PR-associated gene signatures; metagene analysis was employed to define survival rates in patients whose tumors express a PR gene signature. Results: “SUMO-sensitive” PR target genes (i.e. repressed by PR SUMOylation) primarily include genes required for proliferative and pro-survival signaling. DeSUMOylated K388R receptors are preferentially recruited to enhancer regions of derepressed genes (i.e. MSX2, RGS2, MAP1A, and PDK4) along with the steroid receptor coactivator, CBP, and MLL2, a histone methyltransferase mediator of nucleosome remodeling. PR SUMOylation blocks these events, suggesting that SUMO modification of PR prevents interactions with mediators of early chromatin remodeling at “closed” enhancer regions. SUMO-deficient (phospho-Ser294) PR gene signatures are significantly associated with ERBB2-positive luminal breast tumors and predictive of early metastasis and shortened survival. Treatment with antiprogestin or MEK inhibitor abrogated expression of SUMO-sensitive PR targetgenes and inhibited proliferation in BT-474 (ER+/PR+/ERBB2+) breast cancer cells. Conclusions: We conclude that reversible PR SUMOylation/deSUMOylation profoundly alters target gene selection in breast cancer cells. Phosphorylation-induced PR deSUMOylation favors a permissive chromatin environment via recruitment of CBP and MLL2. Patients whose ER+/PR+ tumors are driven by hyperactive (i.e. derepressed) phospho-PRs may benefit from endocrine (antiestrogen) therapies that contain an antiprogestin. Supplementary files: The supplementary files presented in this dissertation are fully described in the appendices. They include: (A) Antibodies used in this study, (B) PCR primer sets used in this study, (C) Genes differentially regulated by wild-type and SUMO-deficient PR, (D) Overlapping lists of PR-dependent target genes from previously described gene expression microarrays, (E) The PR ligand-dependent (LD) and ligand-independent (LI) KR>WT gene signatures, (F) Breast tumor Oncomine concepts associated with the LD KR>WT gene signature.
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    Role of microRNAs in mediating pancreatic cancer response to triptolide
    (2013-04) MacKenzie, Tiffany Noelle
    Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest malignancies, is resistant to current chemotherapies. We previously showed that triptolide inhibits PDAC cell growth in vitro and blocks metastatic spread in vivo. Triptolide downregulates heat shock protein 70 (HSP70), a molecular chaperone upregulated in several tumor types. This study investigates the mechanism by which triptolide inhibits HSP70. As microRNAs (miRNAs) are becoming increasingly recognized as negative regulators of gene expression, we tested whether triptolide regulates HSP70 via miRNAs. Here we show that triptolide, as well as quercetin but not gemcitabine, upregulated miR-142-3p in PDAC cells (MIA PaCa-2, Capan-1, and S2-013). Ectopic expression of miR-142-3p inhibited cell proliferation, measured by Electric Cell-substrate Impedance Sensing, and decreased HSP70 expression, measured by real-time PCR and immunoblotting, compared with controls. We demonstrated that miR-142-3p directly binds to the 3’UTR of HSP70, and that this interaction is important as HSP70 overexpression rescued miR-142-3p-induced cell death. We found that miR-142-3p regulates HSP70 independently of heat shock factor 1. Furthermore, Minnelide, a water soluble prodrug of triptolide, induced the expression of miR-142-3p in vivo. This is the first description of an miRNA-mediated mechanism of HSP70 regulation in cancer, making miR-142-3p an attractive target for PDAC therapeutic intervention.
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    Statistical methods for multi-class differential gene expression detection
    (2011-11) Cao, Xiting
    One of the major goals of microarray data analysis is to identify differentially expressed genes. In cancer studies, RNA is extracted from the tissue samples of cancer patients (case class) and healthy people (control class) to obtain the gene expression data and genes that are dierentially expressed between case and control are identied to be candidate biomarkers which could undergo further studies. More often, we encounter situations where gene expression between more than two classes are being compared instead of the traditional case/control setup, e.g., multiple disease stages or dierent experimental conditions. In this dissertation, the problem of identifying dierentially expressed genes in a multi-class comparison setting will be addressed. To identify the dierentially expressed genes, it is important to select a test statistic to rank the genes, and common approaches usually summarize each gene expression into a univariate test statistic and nd a critical value for the ranking statistics to claim which gene is dierentially expressed. In the dissertation, a univariate test statistic (the moderated F-statistics) is rst used as a summary statistic and its distribution is empirically estimated using maximum likelihood. After that, A multivariate test statistic is proposed as a summary statistic for each gene and both parametric and non-parametric empirical Bayes approaches are adopted to rank the genes. The performances of the proposed methods are illustrated by extensive simulation studies and application to public microarray datasets. The results show that the proposed methods have better detection power than the commonly used approaches when controlling false discovery rates at the same level.
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    Transcriptome Meta Data Compilation for Chinese hamster tissues and CHO cell lines
    (2016-06-06) Vishwanathan, Nandita; Yongky, Andrew; Johnson, Kathryn C; Fu, Hsu-Yuan; Jacob, Nithya M; Le, Huong; Bandyopadhyay, Arpan; wshu@umn.edu; Hu, Wei-Shou; University of Minnesota Department of Chemical Engineering and Material Sciences, Hu Group
    Transcriptomics is increasingly being used on Chinese hamster ovary (CHO) cells to unveil physiological insights related to their performance during production processes. The rich transcriptome data can be exploited to provide impetus for systems investigation such as modeling the central carbon metabolism or glycosylation pathways, or even building genome-scale models. To harness the power of transcriptome assays, we assembled and annotated a set of RNA-Seq data from multiple CHO cell lines and Chinese hamster tissues, and constructed a DNA microarray. These tools were used to measure the transcript expression of tissues (liver, brain, ovary), 3 parental cell lines (DG44, DXB11, CHO-K1) and 16 recombinant cell lines. Transcript expression levels for tissues and cell lines have been compiled as an excel spreadsheet to allow for a rapid survey of transcript levels of different genes.