Matching Items (70)
Description
Obesity and its underlying insulin resistance are caused by environmental and genetic factors. DNA methylation provides a mechanism by which environmental factors can regulate transcriptional activity. The overall goal of the work herein was to (1) identify alterations in DNA methylation in human skeletal muscle with obesity and its underlying

Obesity and its underlying insulin resistance are caused by environmental and genetic factors. DNA methylation provides a mechanism by which environmental factors can regulate transcriptional activity. The overall goal of the work herein was to (1) identify alterations in DNA methylation in human skeletal muscle with obesity and its underlying insulin resistance, (2) to determine if these changes in methylation can be altered through weight-loss induced by bariatric surgery, and (3) to identify DNA methylation biomarkers in whole blood that can be used as a surrogate for skeletal muscle.

Assessment of DNA methylation was performed on human skeletal muscle and blood using reduced representation bisulfite sequencing (RRBS) for high-throughput identification and pyrosequencing for site-specific confirmation. Sorbin and SH3 homology domain 3 (SORBS3) was identified in skeletal muscle to be increased in methylation (+5.0 to +24.4 %) in the promoter and 5’untranslated region (UTR) in the obese participants (n= 10) compared to lean (n=12), and this finding corresponded with a decrease in gene expression (fold change: -1.9, P=0.0001). Furthermore, SORBS3 was demonstrated in a separate cohort of morbidly obese participants (n=7) undergoing weight-loss induced by surgery, to decrease in methylation (-5.6 to -24.2%) and increase in gene expression (fold change: +1.7; P=0.05) post-surgery. Moreover, SORBS3 promoter methylation was demonstrated in vitro to inhibit transcriptional activity (P=0.000003). The methylation and transcriptional changes for SORBS3 were significantly (P≤0.05) correlated with obesity measures and fasting insulin levels. SORBS3 was not identified in the blood methylation analysis of lean (n=10) and obese (n=10) participants suggesting that it is a muscle specific marker. However, solute carrier family 19 member 1 (SLC19A1) was identified in blood and skeletal muscle to have decreased 5’UTR methylation in obese participants, and this was significantly (P≤0.05) predicted by insulin sensitivity.

These findings suggest SLC19A1 as a potential blood-based biomarker for obese, insulin resistant states. The collective findings of SORBS3 DNA methylation and gene expression present an exciting novel target in skeletal muscle for further understanding obesity and its underlying insulin resistance. Moreover, the dynamic changes to SORBS3 in response to metabolic improvements and weight-loss induced by surgery.
ContributorsDay, Samantha Elaine (Author) / Coletta, Dawn K. (Thesis advisor) / Katsanos, Christos (Committee member) / Mandarino, Lawrence J. (Committee member) / Shaibi, Gabriel Q. (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Rewired biological pathways and/or rewired microRNA (miRNA)-mRNA interactions might also influence the activity of biological pathways. Here, rewired biological pathways is defined as differential (rewiring) effect of genes on the topology of biological pathways between controls and cases. Similarly, rewired miRNA-mRNA interactions are defined as the differential (rewiring) effects of

Rewired biological pathways and/or rewired microRNA (miRNA)-mRNA interactions might also influence the activity of biological pathways. Here, rewired biological pathways is defined as differential (rewiring) effect of genes on the topology of biological pathways between controls and cases. Similarly, rewired miRNA-mRNA interactions are defined as the differential (rewiring) effects of miRNAs on the topology of biological pathways between controls and cases. In the dissertation, it is discussed that how rewired biological pathways (Chapter 1) and/or rewired miRNA-mRNA interactions (Chapter 2) aberrantly influence the activity of biological pathways and their association with disease.

This dissertation proposes two PageRank-based analytical methods, Pathways of Topological Rank Analysis (PoTRA) and miR2Pathway, discussed in Chapter 1 and Chapter 2, respectively. PoTRA focuses on detecting pathways with an altered number of hub genes in corresponding pathways between two phenotypes. The basis for PoTRA is that the loss of connectivity is a common topological trait of cancer networks, as well as the prior knowledge that a normal biological network is a scale-free network whose degree distribution follows a power law where a small number of nodes are hubs and a large number of nodes are non-hubs. However, from normal to cancer, the process of the network losing connectivity might be the process of disrupting the scale-free structure of the network, namely, the number of hub genes might be altered in cancer compared to that in normal samples. Hence, it is hypothesized that if the number of hub genes is different in a pathway between normal and cancer, this pathway might be involved in cancer. MiR2Pathway focuses on quantifying the differential effects of miRNAs on the activity of a biological pathway when miRNA-mRNA connections are altered from normal to disease and rank disease risk of rewired miRNA-mediated biological pathways. This dissertation explores how rewired gene-gene interactions and rewired miRNA-mRNA interactions lead to aberrant activity of biological pathways, and rank pathways for their disease risk. The two methods proposed here can be used to complement existing genomics analysis methods to facilitate the study of biological mechanisms behind disease at the systems-level.
ContributorsLi, Chaoxing (Author) / Dinu, Valentin (Thesis advisor) / Kuang, Yang (Thesis advisor) / Liu, Li (Committee member) / Wang, Xiao (Committee member) / Arizona State University (Publisher)
Created2017
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Description
Understanding intratumor heterogeneity and their driver genes is critical to

designing personalized treatments and improving clinical outcomes of cancers. Such

investigations require accurate delineation of the subclonal composition of a tumor, which

to date can only be reliably inferred from deep-sequencing data (>300x depth). The

resulting algorithm from the work presented here, incorporates an

Understanding intratumor heterogeneity and their driver genes is critical to

designing personalized treatments and improving clinical outcomes of cancers. Such

investigations require accurate delineation of the subclonal composition of a tumor, which

to date can only be reliably inferred from deep-sequencing data (>300x depth). The

resulting algorithm from the work presented here, incorporates an adaptive error model

into statistical decomposition of mixed populations, which corrects the mean-variance

dependency of sequencing data at the subclonal level and enables accurate subclonal

discovery in tumors sequenced at standard depths (30-50x). Tested on extensive computer

simulations and real-world data, this new method, named model-based adaptive grouping

of subclones (MAGOS), consistently outperforms existing methods on minimum

sequencing depth, decomposition accuracy and computation efficiency. MAGOS supports

subclone analysis using single nucleotide variants and copy number variants from one or

more samples of an individual tumor. GUST algorithm, on the other hand is a novel method

in detecting the cancer type specific driver genes. Combination of MAGOS and GUST

results can provide insights into cancer progression. Applications of MAGOS and GUST

to whole-exome sequencing data of 33 different cancer types’ samples discovered a

significant association between subclonal diversity and their drivers and patient overall

survival.
ContributorsAhmadinejad, Navid (Author) / Liu, Li (Thesis advisor) / Maley, Carlo (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2019
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Description
ABSTRACT

Domestic dogs have assisted humans for millennia. However, the extent to which these helpful behaviors are prosocially motivated remains unclear. To assess the propensity of pet dogs to spontaneously and actively rescue distressed humans, this study tested whether sixty pet dogs would release their seemingly trapped owners from a large

ABSTRACT

Domestic dogs have assisted humans for millennia. However, the extent to which these helpful behaviors are prosocially motivated remains unclear. To assess the propensity of pet dogs to spontaneously and actively rescue distressed humans, this study tested whether sixty pet dogs would release their seemingly trapped owners from a large box. To examine the causal mechanisms that shaped this behavior, the readiness of each dog to open the box was tested in three conditions: 1) the owner sat in the box and called for help (“Distress” test), 2) an experimenter placed high-value food rewards in the box (“Food” test), and 3) the owner sat in the box and calmly read aloud (“Reading” test).

Dogs were as likely to release their distressed owner as to retrieve treats from inside the box, indicating that rescuing an owner may be a highly rewarding action for dogs. After accounting for ability, dogs released the owner more often when the owner called for help than when the owner read aloud calmly. In addition, opening latencies decreased with test number in the Distress test but not the Reading test. Thus, rescuing the owner could not be attributed solely to social facilitation, stimulus enhancement, or social contact-seeking behavior.

Dogs displayed more stress behaviors in the Distress test than in the Reading test, and stress scores decreased with test number in the Reading test but not in the Distress test. This evidence of emotional contagion supports the hypothesis that rescuing the distressed owner was an empathetically-motivated prosocial behavior. Success in the Food task and previous (in-home) experience opening objects were both strong predictors of releasing the owner. Thus, prosocial behavior tests for dogs should control for physical ability and previous experience.
ContributorsVan Bourg, Joshua Lazar (Author) / Wynne, Clive D (Thesis advisor) / Gilby, Ian C (Committee member) / Aktipis, C. Athena (Committee member) / Arizona State University (Publisher)
Created2019
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Description
All biological processes like cell growth, cell differentiation, development, and aging requires a series of steps which are characterized by gene regulation. Studies have shown that gene regulation is the key to various traits and diseases. Various factors affect the gene regulation which includes genetic signals, epigenetic tracks, genetic variants,

All biological processes like cell growth, cell differentiation, development, and aging requires a series of steps which are characterized by gene regulation. Studies have shown that gene regulation is the key to various traits and diseases. Various factors affect the gene regulation which includes genetic signals, epigenetic tracks, genetic variants, etc. Deciphering and cataloging these functional genetic elements in the non-coding regions of the genome is one of the biggest challenges in precision medicine and genetic research. This thesis presents two different approaches to identifying these elements: TreeMap and DeepCORE. The first approach involves identifying putative causal genetic variants in cis-eQTL accounting for multisite effects and genetic linkage at a locus. TreeMap performs an organized search for individual and multiple causal variants using a tree guided nested machine learning method. DeepCORE on the other hand explores novel deep learning techniques that models the relationship between genetic, epigenetic and transcriptional patterns across tissues and cell lines and identifies co-operative regulatory elements that affect gene regulation. These two methods are believed to be the link for genotype-phenotype association and a necessary step to explaining various complex diseases and missing heritability.
ContributorsChandrashekar, Pramod Bharadwaj (Author) / Liu, Li (Thesis advisor) / Runger, George C. (Committee member) / Dinu, Valentin (Committee member) / Arizona State University (Publisher)
Created2020
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Description
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
Description

We present results from experiments at the Linac Coherent Light Source (LCLS) demonstrating that serial femtosecond crystallography (SFX) can be performed to high resolution (~2.5 Å) using protein microcrystals deposited on an ultra-thin silicon nitride membrane and embedded in a preservation medium at room temperature. Data can be acquired at

We present results from experiments at the Linac Coherent Light Source (LCLS) demonstrating that serial femtosecond crystallography (SFX) can be performed to high resolution (~2.5 Å) using protein microcrystals deposited on an ultra-thin silicon nitride membrane and embedded in a preservation medium at room temperature. Data can be acquired at a high acquisition rate using x-ray free electron laser sources to overcome radiation damage, while sample consumption is dramatically reduced compared to flowing jet methods. We achieved a peak data acquisition rate of 10 Hz with a hit rate of ~38%, indicating that a complete data set could be acquired in about one 12-hour LCLS shift using the setup described here, or in even less time using hardware optimized for fixed target SFX. This demonstration opens the door to ultra low sample consumption SFX using the technique of diffraction-before-destruction on proteins that exist in only small quantities and/or do not produce the copious quantities of microcrystals required for flowing jet methods.

ContributorsHunter, Mark S. (Author) / Segelke, Brent (Author) / Messerschmidt, Marc (Author) / Williams, Garth J. (Author) / Zatsepin, Nadia (Author) / Barty, Anton (Author) / Benner, W. Henry (Author) / Carlson, David B. (Author) / Coleman, Matthew (Author) / Graf, Alexander (Author) / Hau-Riege, Stefan P. (Author) / Pardini, Tommaso (Author) / Seibert, M. Marvin (Author) / Evans, James (Author) / Boutet, Sebastien (Author) / Frank, Matthias (Author) / College of Liberal Arts and Sciences (Contributor)
Created2014-08-12
Description

Photosynthesis, a process catalysed by plants, algae and cyanobacteria converts sunlight to energy thus sustaining all higher life on Earth. Two large membrane protein complexes, photosystem I and II (PSI and PSII), act in series to catalyse the light-driven reactions in photosynthesis. PSII catalyses the light-driven water splitting process, which

Photosynthesis, a process catalysed by plants, algae and cyanobacteria converts sunlight to energy thus sustaining all higher life on Earth. Two large membrane protein complexes, photosystem I and II (PSI and PSII), act in series to catalyse the light-driven reactions in photosynthesis. PSII catalyses the light-driven water splitting process, which maintains the Earth’s oxygenic atmosphere. In this process, the oxygen-evolving complex (OEC) of PSII cycles through five states, S0 to S4, in which four electrons are sequentially extracted from the OEC in four light-driven charge-separation events. Here we describe time resolved experiments on PSII nano/microcrystals from Thermosynechococcus elongatus performed with the recently developed technique of serial femtosecond crystallography. Structures have been determined from PSII in the dark S1 state and after double laser excitation (putative S3 state) at 5 and 5.5 Å resolution, respectively. The results provide evidence that PSII undergoes significant conformational changes at the electron acceptor side and at the Mn4CaO5 core of the OEC. These include an elongation of the metal cluster, accompanied by changes in the protein environment, which could allow for binding of the second substrate water molecule between the more distant protruding Mn (referred to as the ‘dangler’ Mn) and the Mn3CaOx cubane in the S2 to S3 transition, as predicted by spectroscopic and computational studies. This work shows the great potential for time-resolved serial femtosecond crystallography for investigation of catalytic processes in biomolecules.

ContributorsKupitz, Christopher (Author) / Basu, Shibom (Author) / Grotjohann, Ingo (Author) / Fromme, Raimund (Author) / Zatsepin, Nadia (Author) / Rendek, Kimberly (Author) / Hunter, Mark (Author) / Shoeman, Robert L. (Author) / White, Thomas A. (Author) / Wang, Dingjie (Author) / James, Daniel (Author) / Yang, Jay-How (Author) / Cobb, Danielle (Author) / Reeder, Brenda (Author) / Sierra, Raymond G. (Author) / Liu, Haiguang (Author) / Barty, Anton (Author) / Aquila, Andrew L. (Author) / Deponte, Daniel (Author) / Kirian, Richard (Author) / Bari, Sadia (Author) / Bergkamp, Jesse (Author) / Beyerlein, Kenneth R. (Author) / Bogan, Michael J. (Author) / Caleman, Carl (Author) / Chao, Tzu-Chiao (Author) / Conrad, Chelsie (Author) / Davis, Katherine M. (Author) / Department of Chemistry and Biochemistry (Contributor)
Created2014-09-11
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Description

It has been suggested that the extended intensity profiles surrounding Bragg reflections that arise when a series of finite crystals of varying size and shape are illuminated by the intense, coherent illumination of an x-ray free-electron laser may enable the crystal’s unit-cell electron density to be obtained ab initio via

It has been suggested that the extended intensity profiles surrounding Bragg reflections that arise when a series of finite crystals of varying size and shape are illuminated by the intense, coherent illumination of an x-ray free-electron laser may enable the crystal’s unit-cell electron density to be obtained ab initio via well-established iterative phasing algorithms. Such a technique could have a significant impact on the field of biological structure determination since it avoids the need for a priori information from similar known structures, multiple measurements near resonant atomic absorption energies, isomorphic derivative crystals, or atomic-resolution data. Here, we demonstrate this phasing technique on diffraction patterns recorded from artificial two-dimensional microcrystals using the seeded soft x-ray free-electron laser FERMI. We show that the technique is effective when the illuminating wavefront has nonuniform phase and amplitude, and when the diffraction intensities cannot be measured uniformly throughout reciprocal space because of a limited signal-to-noise ratio.

ContributorsKirian, Richard (Author) / Bean, Richard J. (Author) / Beyerlein, Kenneth R. (Author) / Barthelmess, Miriam (Author) / Yoon, Chun Hong (Author) / Wang, Fenglin (Author) / Capotondi, Flavio (Author) / Pedersoli, Emanuele (Author) / Barty, Anton (Author) / Chapman, Henry N. (Author) / College of Liberal Arts and Sciences (Contributor)
Created2015-02-12
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Description

Microbes in the gastrointestinal tract are under selective pressure to manipulate host eating behavior to increase their fitness, sometimes at the expense of host fitness. Microbes may do this through two potential strategies: (i) generating cravings for foods that they specialize on or foods that suppress their competitors, or (ii)

Microbes in the gastrointestinal tract are under selective pressure to manipulate host eating behavior to increase their fitness, sometimes at the expense of host fitness. Microbes may do this through two potential strategies: (i) generating cravings for foods that they specialize on or foods that suppress their competitors, or (ii) inducing dysphoria until we eat foods that enhance their fitness. We review several potential mechanisms for microbial control over eating behavior including microbial influence on reward and satiety pathways, production of toxins that alter mood, changes to receptors including taste receptors, and hijacking of the vagus nerve, the neural axis between the gut and the brain. We also review the evidence for alternative explanations for cravings and unhealthy eating behavior. Because microbiota are easily manipulatable by prebiotics, probiotics, antibiotics, fecal transplants, and dietary changes, altering our microbiota offers a tractable approach to otherwise intractable problems of obesity and unhealthy eating.

ContributorsAlcock, Joe (Author) / Maley, Carlo C. (Author) / Aktipis, C. Athena (Author) / College of Liberal Arts and Sciences (Contributor)
Created2014-10-01