Dissertation
Advancing translational bioinformatics: techniques for addressing research barriers
University of Iowa
Doctor of Philosophy (PhD), University of Iowa
Autumn 2024
DOI: 10.25820/etd.007573
Abstract
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.
Details
- Title: Subtitle
- Advancing translational bioinformatics: techniques for addressing research barriers
- Creators
- Shreya Ghimire
- Contributors
- Alejandro A Pezzulo (Advisor)David A Stoltz (Committee Member)Eric B Taylor (Committee Member)Richard J Smith (Committee Member)Todd E Scheetz (Committee Member)
- Resource Type
- Dissertation
- Degree Awarded
- Doctor of Philosophy (PhD), University of Iowa
- Degree in
- Informatics (Bioinformatics and Computational Biology)
- Date degree season
- Autumn 2024
- DOI
- 10.25820/etd.007573
- Publisher
- University of Iowa
- Number of pages
- xvi, 140 pages
- Copyright
- Copyright 2024 Shreya Ghimire
- Language
- English
- Date submitted
- 12/02/2024
- Description illustrations
- illustrations, tables, graphs
- Description bibliographic
- Includes bibliographical references (pages 110-121).
- Public Abstract (ETD)
Translational bioinformatics (TBI) research integrates molecular information (DNA, RNA, proteins, and lipids) with clinical data (patients, diseases, lab tests, drugs etc.) turning scientific discoveries into healthcare tools. Despite its potential, TBI faces challenges like managing complex data, validating biomarkers, reproducibility, and high costs. This thesis tackles some of these hurdles by using current and emerging technologies to develop new methods for studying complex diseases.
Although RNA sequencing costs have gradually decreased, RNA extraction remains a major bottleneck for large-scale studies. In Chapter 2, I address this issue by developing a faster, cheaper, high-quality RNA-extraction free method for profiling large number of samples in parallel. Chapter 3 highlights the need for non-invasive cellular models to study complex disorders like sporadic Parkinson's disease (sPD). Using our method to generate RNA-seq data, I identified dysregulation in mitochondrial respiration pathway in people with sPD using nonneuronal dermal fibroblasts (DFs) samples and confirmed this finding by assessing mitochondrial function in DFs and nasal cells, showing new ways to study PD with minimal invasion. In Chapter 4, I explored how pre-existing inflammation affects epithelial response to SARS-CoV-2 infection. Our findings suggests that asthma-associated cytokine (IL-13) protects airway epithelial cells from SARS-CoV-2 infection in vitro but worsens the disease in mice (in vivo), offering new insights for treating respiratory virus-induced lung diseases.
Overall, my findings offer scalable solutions and minimally invasive methods for studying complex diseases and developing potential therapies, advancing the translation of scientific discoveries into healthcare.
- Academic Unit
- IDGP in Informatics
- Record Identifier
- 9984774456902771
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