Browsing by Subject "proteomics"

Now showing 1 - 5 of 5
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    Atrial Fibrillation In Older Adults: Relation To Proteomics, Risk Prediction, And Urban/Rural Disparities In Treatment And Outcomes
    (2020-07) Norby, Faye
    Atrial fibrillation (AF), a cardiac arrhythmia, is a major public health problem. AF is largely a disease of advancing age and contributes to other cardiovascular complications. Identification of novel protein biomarkers could advance understanding of AF mechanisms and may improve the prediction of incident AF. Additionally, it is unknown if disparities exist in AF treatment and outcomes in rural versus urban areas of the US. For manuscripts 1 and 2, we used data from the Atherosclerosis Risk in Communities (ARIC) study, a cohort of older-aged adults in the US. For manuscripts 3 and 4, we used a sample of Medicare beneficiaries enrolled from 2011-2016 with residential zip code categorized into 4 rural/urban areas. In the first manuscript, we examined the association of plasma proteins and identified 40 novel protein biomarkers associated with incident AF. These biomarkers provide insight into mechanistic pathways of AF development. In the second manuscript, we derived and validated a series of 5-year incident AF prediction models that are better targeted and calibrated to older populations. Incorporating biomarkers, including proteomics data, into the models improved AF risk prediction. In the third and fourth manuscripts, we examined the initiation of anticoagulation use and compared the risks of subsequent stroke, heart failure, myocardial infarction, and mortality in newly-diagnosed AF patients in rural versus urban areas. Patients in rural areas were more likely to initiate anticoagulant treatment; however, they were less likely to initiate a newer class of anticoagulants compared to those in urban areas. Those in rural areas had modestly higher risk of cardiovascular outcomes and mortality compared to those in urban areas. Proteomics aids in understanding AF mechanisms and improves risk prediction. Future research should validate our prediction models, develop meaningful ways to incorporate protein biomarkers in clinical practice, and focus on improving AF treatment in rural areas.
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    Developing accessible informatics tools for integrated genomic-proteomic data analysis
    (2019-11) Kumar, Praveen
    Mass-spectrometry (MS) based proteomics is widely used to identify and quantify proteins present in biological samples. Emerging multi-omics approaches involve integrating next-generation DNA and RNA sequencing data with MS-based proteomic data to identify novel and known protein products (proteoforms) present in a sample that could be from a single organism (proteogenomics) or a community of organisms (metaproteomics). These methods can offer a more complete molecular picture of complex biological samples used in human health and environmental studies. In these MS-based proteomics approaches, tandem-mass-spectrometry (MS/MS) data derived from peptides is matched against a database containing amino-acid sequences translated from DNA or RNA sequencing to confirm the presence of proteoforms. However, proteogenomic and metaproteomic databases are significantly larger than those used in traditional MS-based proteomics, leading to decreased sensitivity for identifying true peptide spectrum matches (PSMs) for MS/MS matched to sequences in these databases. Once peptides are identified and used to infer protein presence and quantities, there is also a need of advanced tools to compare the response of proteins to their corresponding RNA transcripts, to analyze underlying molecular mechanisms of biology and disease. Ideally, all of these informatic tools would be accessible to lab scientists within a user-friendly platform, to promote wide-adoption and impact in diverse research studies. To address these challenges, we have developed software tools and workflows in the freely-available and user-friendly Galaxy bioinformatics platform, with the objective of providing solutions to MS-based proteomics multi-omics challenges and making them accessible to others. First, we implemented a novel database sectioning method, integrating it into the suite of tools developed for the Galaxy for proteomics (Galaxy-P) project, and evaluated its utility in metaproteomics, and proteogenomics applications. Second, we created a comprehensive workflow for proteogenomics that can efficiently utilize RNA and protein data to identify novel protein variants and proteoforms. Third, we developed a Galaxy-P based tool for comparing the abundance levels of RNA and proteins for integrated analysis of quantitative transcriptomic and proteomic datasets. Collectively, this work has delivered on our goals to develop accessible and reproducible software tools and workflows for more efficient matching of MS/MS data with large databases and also improve integrated analysis of multi-omics applications that can help enable new discoveries in biological and biomedical research.
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    Integration Of Quantitative And Functional Proteomics To Explore The Global Functional Landscape Of Post-Translational Modifications
    (2023-07) Gong, Yao
    Proteomics explores global-scale protein functions, with post-translational modifications (PTMs) expanding proteome complexity and functionality. Significant advancements in mass spectrometry (MS)-based quantitative proteomics have expanded the scope of PTM pathways. Meanwhile, functional proteomics bridges the annotation gap by linking uncharacterized proteins with biological functions. These two fields facilitate the exploration of the vast physiological function landscape of proteins and PTMs and aid in identifying disease-specific protein targets for the early detection and curation of diseases.This research integrated the MS data analysis from quantitative proteomics and functional proteomics approaches and develop innovative bioinformatic strategies to interpret the functional landscape of PTM pathways in three aspects: up-stream enzymatic regulatory mechanisms that are responsible for adding and removing PTMs, comprehensive inventory and annotation analysis of PTM targets, and down-stream prediction of functional impacts of PTMs in protein structural stability and activities. First, to discover the up-stream enzymatic activities of a critical PTM pathway – ubiquitination, we constructed a quantitative ubiquitylome analysis algorithm and a stand-alone Python software package called UbE3-APA which is based on an interaction database for E3 ligase and ubiquitin sites to analyze the dynamics of ubiquitylome from MS-based quantitative proteomics data. The algorithm revealed the E3 ligase activity profiles of multiple global ubiquitylome studies effectively under various genetic and metabolic conditions. The algorithm developed in this project as well as a similar algorithm we developed in the Kinase Activity Profiling Analysis (KAPA) may be generally applicable to other PTM enzyme activity profiling analyses. Next, to comprehensively catalog an essential and yet under-studied oxygen-sensing posttranslational modification pathway – proline hydroxylation, we developed an online database and website platform, HypDB (https://hypdb.site), for hydroxyproline sites collection and functional annotation, while sharing the knowledge with the community. In the data collecting section, we evaluated the confidence of site-localization for identified sites and quantified their stoichiometry with corresponding MS spectra. And in the annotation section, we integrated multiple functional databases and developed bioinformatic strategies to study the enrichment of the hydroxyproline proteome in cellular pathways, structural domains, and tissue distributions at the levels of both the protein and modification site. All identified sites with annotation results were capsuled into HypDB websites, where its downloadable hydroxyproline spectra library allowed systematic data-independent DIA data analysis. Lastly, to understand the potential functional impacts of PTM in downstream pathways and protein activities, we developed bioinformatics strategies to identify the functional hydroxyproline proteome by integrated analysis of quantitative functional proteomics datasets. Our bioinformatic workflow explored the evolution conservation, protein turnover, and thermal stability profiles of hydroxyproline proteome in multiple species and different cell lines. Through individual and integrated analysis, we not only have a deeper understanding of the role of the global proline hydroxylation on protein structural stability under different conditions but also revealed significantly regulated hydroxyproline sites and substrate proteins that may serve as key targets in oxygen and metabolic sensing mechanisms in cellular activities. Collectively, this series of studies generate applicable models and novel knowledge in interpreting the functional network influenced by different PTMs.
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    Mechanisms of decay and interspecific interactions of white and brown rot fungi
    (2018-04) Presley, Gerald
    Wood is the largest source of biotic carbon on earth and the principle drivers of its decay are basidiomycete fungi. The biochemical mechanisms of wood decay by basidiomycete fungi are fundamental processes in forest ecosystems that dictate carbon evolution rates, soil organic matter deposition, and overall ecosystem function. These decay mechanisms are also unique in their ability to efficiently convert recalcitrant woody biomass to fermentable sugars and can serve as a biological template for industrial lignocellulose conversion to make renewable biofuels more economical. However, basidiomycete wood decay mechanisms are not fully understood and therefore not replicable in vitro, due in part to a lack of understanding of how decay mechanisms change throughout the progression of decay. In addition, gene transcripts and proteins used to facilitate decay are produced in concert with other biomolecules with non-degradative functions which makes resolution of degradative genes difficult. This dissertation contributes to resolving these problems by describing the temporal progression of decay among several species of wood-degrading basidiomycetes and functionally categorizing genes and secreted proteins involved in mediating interspecific interactions. This was done by first spatially resolving decay into a temporal sequence by growing model brown-rot fungi directionally on thin wood wafers. This system was used to co-localize changes in fungal physiology with chemical changes in wood substrates and the production of fungal metabolites to identify the functional significance of those physiological changes. The same wafer culture design was then used to resolve changes in fungal secretomes between two phylogenetically disparate brown-rot species over the course of decay using proteomics co-localized with lignocellulose-degrading enzyme assays. Interspecific differences were further investigated by comparing decay performance of the same two fungi on a Poales substrate, sorghum bagasse. Sorghum decay rates along with component removal and enzyme assays were monitored during decay to determine the genetic and biochemical basis of substrate preferences of the two species. Temporal alterations to fungal secretomes were compared among several model white and brown-rot fungi as well. Comparative proteomics concurrent with lignocellulose-degrading enzyme assays were used to identify common patterns among both rot types, as well as interspecific variability of decay mechanisms within species. Finally, changes in gene expression, protein secretion, and enzyme activity profiles in response to fungal competitors were described by modifying the thin wood wafer microcosms to incorporate two brown-rot species grown in opposition to one another. Resolution of decay into a sequence revealed a biphasic decay mechanism in brown-rot fungi delineated by early stage, non-hydrolytic pretreatment followed by later stage glycoside hydrolase-mediated saccharification. Proteomic investigation confirmed this pattern by showing later stage secretomes contain a greater proportion of glycoside hydrolases and their activities than earlier stages of decay. Brown-rot secretomes varied considerably by species as did their ability to degrade sorghum bagasse, likely due to a difference in the ability to hydrolyze ferulic acid esters present in sorghum biomass. Comparison of white and brown-rot secretomes identified a common segregation of decay into a biphasic decay mechanism characterized by high lignolysis, in white-rot fungi, upon wood colonization followed by later stage glycoside hydrolase secretion in both decay types. Considerable interspecific variability in decay mechanism within decay types was also detected, with the white-rot species producing different suites of ligninolytic enzymes and brown-rot species diverging in the types of glycoside hydrolases produced. Investigation of interspecific interactions identified several proteins exclusively produced during the interaction of two brown-rot species as well as identifying the general downregulation of lignocellulose-degrading genes during the interaction. In addition, comparative transcriptomics identified two different interaction strategies employed by species and implicates several secondary metabolite-synthesizing genes in facilitating interspecific interactions. Overall, this work contributes toward functional categorization of a wide range of basidiomycete proteins and provides a better understanding of decay mechanisms and interspecific interactions in these understudied organisms.
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    Seasonal Metabolism Of Brown Adipose Tissue And Brain Mitochondria In The Thirteen-Lined Ground Squirrel (Ictidomys tridecemlineatus)
    (2015-08) Ballinger, Mallory
    During the hibernation season, thirteen-lined ground squirrels (Ictidomys tridecemlineatus) regularly cycle between bouts of torpor and interbout arousal (IBA). This presents a unique seasonal change in energy requirements in both the brain and brown adipose tissue (BAT). We hypothesized that brain and BAT mitochondria undergo a seasonal change in function to accommodate the variable energy demands of hibernation. To test this hypothesis, we examined mitochondrial bioenergetics of brain and BAT in thirteen-lined ground squirrels across five time points: summer, fall, torpor, IBA and spring. Through various molecular and functional analyses, we found significant increases in mitochondrial oxidative capacities of both brain and BAT during torpor and IBA. Overall, brain and BAT mitochondrial bioenergetics are not static across the year, and our studies suggest that these two tissues function efficiently during the hibernation season, when extreme physiological changes are occurring. These studies provide improved understanding of the overall energy requirements of a hibernator.