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Advancing Translational Bioinformati...

Ghimire, Shreya,

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Advancing Translational Bioinformatics: Techniques for Addressing Research Barriers /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Advancing Translational Bioinformatics: Techniques for Addressing Research Barriers // Shreya Ghimire.
Author:	Ghimire, Shreya,
Description:	1 electronic resource (158 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-08, Section: B.
Contained By:	Dissertations Abstracts International86-08B.
Subject:	Bioinformatics. -
Online resource:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31761332
ISBN:	9798302853394

Advancing Translational Bioinformatics: Techniques for Addressing Research Barriers /
Ghimire, Shreya,

Advancing Translational Bioinformatics: Techniques for Addressing Research Barriers /Shreya Ghimire. - 1 electronic resource (158 pages)

Source: Dissertations Abstracts International, Volume: 86-08, Section: B.

Translational bioinformatics (TBI) is an interdisciplinary field at the intersection of bioinformatics, clinical research, and data science, aiming to bridge the gap between bench research and clinical application. It integrates molecular information (DNA, RNA, proteins, and lipids) with clinical data (patients, diseases, symptoms, lab tests, drugs etc.) turning scientific discoveries into actionable clinical insights. Despite its potential, TBI faces several challenges including data integration, biomarker validation, reproducibility, computational complexity, and time-resources constraints. This thesis tackles some of these challenges by leveraging current and emerging technologies to develop new methods for studying complex diseases.While RNA-seq library preparation costs have gradually decreased, RNA extraction remains a major bottleneck to scalability. In Chapter 2, I address this issue by developing a novel cost-effective, high-quality RNA extraction-free method for large-scale transcriptome profiling of adherent cell cultures. By combining a direct lysis buffer compatible with cDNA synthesis with a streamlined RNA-seq library prep method (Smart-3SEQ), I examined drug-induced effects on primary human dermal fibroblasts (DFs). I showed the success of our novel approach by achieving all quality control criteria and high gene counts correlation with standard Illumina TruSeq method.In Chapter 3, I highlight the need for non-invasive cellular models that integrates genetic, epigenetic, and metabolic alterations at an individual level to study complex disorders like sporadic Parkinson's disease (sPD). Using our method to generate RNA-seq data, I identified abnormalities present in people with sPD using non-neuronal DFs samples. I found that 1) transcriptional dysregulation in sPD matches the gene expression patterns of DFs from people with familial PD, suggesting a common underlying cellular defect in all PD cases and 2) sPD DFs have dysregulated oxidative phosphorylation pathway. I validated these findings by assessing mitochondrial function in DFs and nasal epithelial cells, emphasizing their potential as minimally invasive non-neuronal cellular models for studying PD mechanisms.In Chapter 4, given the recent COVID-19 pandemic, I explored the role of asthma associated type 2 cytokine IL-13-induced inflammation, on various stages of SARS-CoV-2 infection using both murine (in vivo) and primary human airway epithelial (HAE; in vitro) culture models. I found that IL-13 protects HAE against SARS-CoV-2 infection in vitro by decreasing viral receptor (ACE2) expressing ciliated cells but worsens disease severity in mice through prostaglandin-mediated eicosanoid signaling, offering valuable insights for future treatments of respiratory virus-induced lung diseases. I also generated an atlas of the effects of type 2 and type 17- induced inflammation on the time course of cellular responses of air-liquid interface primary HAE to SARS-CoV-2 at the single cell level; a dataset containing 48 samples from three human subjects, useful to the scientific community.Overall, my findings offer significant contributions to the fields of neurodegenerative disease and viral infection research, providing new avenues for studying diseases with minimal invasion and improving therapeutic approaches. By addressing some of the key challenges in TBI, this thesis paves the way for more effective and scalable methods in both research and clinical applications, potentially accelerating the translation of scientific discoveries into real-world healthcare solutions.

English

ISBN: 9798302853394Subjects--Topical Terms:

553671
Bioinformatics.
Subjects--Index Terms:

Computational biology

Advancing Translational Bioinformatics: Techniques for Addressing Research Barriers /
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502 $b Ph.D. $c The University of Iowa $d 2024.
520 $a Translational bioinformatics (TBI) is an interdisciplinary field at the intersection of bioinformatics, clinical research, and data science, aiming to bridge the gap between bench research and clinical application. It integrates molecular information (DNA, RNA, proteins, and lipids) with clinical data (patients, diseases, symptoms, lab tests, drugs etc.) turning scientific discoveries into actionable clinical insights. Despite its potential, TBI faces several challenges including data integration, biomarker validation, reproducibility, computational complexity, and time-resources constraints. This thesis tackles some of these challenges by leveraging current and emerging technologies to develop new methods for studying complex diseases.While RNA-seq library preparation costs have gradually decreased, RNA extraction remains a major bottleneck to scalability. In Chapter 2, I address this issue by developing a novel cost-effective, high-quality RNA extraction-free method for large-scale transcriptome profiling of adherent cell cultures. By combining a direct lysis buffer compatible with cDNA synthesis with a streamlined RNA-seq library prep method (Smart-3SEQ), I examined drug-induced effects on primary human dermal fibroblasts (DFs). I showed the success of our novel approach by achieving all quality control criteria and high gene counts correlation with standard Illumina TruSeq method.In Chapter 3, I highlight the need for non-invasive cellular models that integrates genetic, epigenetic, and metabolic alterations at an individual level to study complex disorders like sporadic Parkinson's disease (sPD). Using our method to generate RNA-seq data, I identified abnormalities present in people with sPD using non-neuronal DFs samples. I found that 1) transcriptional dysregulation in sPD matches the gene expression patterns of DFs from people with familial PD, suggesting a common underlying cellular defect in all PD cases and 2) sPD DFs have dysregulated oxidative phosphorylation pathway. I validated these findings by assessing mitochondrial function in DFs and nasal epithelial cells, emphasizing their potential as minimally invasive non-neuronal cellular models for studying PD mechanisms.In Chapter 4, given the recent COVID-19 pandemic, I explored the role of asthma associated type 2 cytokine IL-13-induced inflammation, on various stages of SARS-CoV-2 infection using both murine (in vivo) and primary human airway epithelial (HAE; in vitro) culture models. I found that IL-13 protects HAE against SARS-CoV-2 infection in vitro by decreasing viral receptor (ACE2) expressing ciliated cells but worsens disease severity in mice through prostaglandin-mediated eicosanoid signaling, offering valuable insights for future treatments of respiratory virus-induced lung diseases. I also generated an atlas of the effects of type 2 and type 17- induced inflammation on the time course of cellular responses of air-liquid interface primary HAE to SARS-CoV-2 at the single cell level; a dataset containing 48 samples from three human subjects, useful to the scientific community.Overall, my findings offer significant contributions to the fields of neurodegenerative disease and viral infection research, providing new avenues for studying diseases with minimal invasion and improving therapeutic approaches. By addressing some of the key challenges in TBI, this thesis paves the way for more effective and scalable methods in both research and clinical applications, potentially accelerating the translation of scientific discoveries into real-world healthcare solutions.
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650 4 $a Bioinformatics. $3 553671
650 4 $a Systematic biology. $3 3173492
650 4 $a Molecular biology. $3 517296
653 $a Computational biology
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710 2 $a The University of Iowa. $b Informatics. $e degree granting institution. $3 3826165
720 1 $a Pezzulo, Alejandro A. $e degree supervisor.
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