@phdthesis{Vafadarnejad2022,
  author    = {Vafadarnejad, Ehsan},
  title     = {Implementation and application of bioinformatics methods to analyze and visualize single-cell RNA-sequencing data},
  doi       = {10.25972/OPUS-26925},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-269258},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2022},
  abstract  = {RNA sequencing (RNA-seq) has become a transformative method to profile genome-wide gene expression and whole transcriptome analysis over the last decade. In recent years, with the development of new technologies, it has become possible to study gene expression at single-cell level. This new advances in single-cell RNA-sequencing has revolutionized the way scientists study biological processes. Single-cell RNA-sequencing has been used in different areas to better understand the underlying mechanisms of biological processes. In particular, single-RNA-sequencing is a suitable method to study infectious diseases. Infection is composed of heterogeneous mechanisms on either the host or pathogen side and the best way to understand the heterogeneity of these mechanisms and how they interact with each other is to study infectious diseases at the single-cell level. Studying infection processes at the single-cell level can reveal not only the heterogeneity but also the dynamics of infection and the interplay between the host and pathogen at the molecular level. In this thesis, we implemented and applied different single-cell RNA-seq technologies to better understand infectious diseases. In the present work, we conducted four independent but related research works to shed light on different aspects of infection biology: ● We took advantage of this novel technology to study the consequences of RSV infection on primary human epithelial cells. The primary human epithelial cells were collected from six donors and cultured in air liquid interface (ALI) cell culture inoculated with respiratory syncytial virus (RSV). In this project, we discovered ciliated cells as the susceptible cell types in RSV infection. We applied viral load as an indicator of infection progression and used it to reconstruct the dynamics of host response to RSV infection. Reconstruction of the dynamics of infection revealed many host genes and pathways that were suppressed or induced as a result of RSV infection. Pathways related to innate immune response and interferon response were suppressed during the progression of infection and on the other hand pathways like protein targeting to endoplasmic reticulum and apoptosis were induced. ● We developed a new method which is capable of sequencing the transcriptome of a bacterium at the single-cell level and potentially can help us to characterize the bacterial heterogeneity during the course of infection. In this research project, bacteria were cultured in three different culture conditions namely Late stationary phase, Anaerobic shock and NaCl shock and we used a poly(A)-independent single-cell RNA-sequencing protocol to sequence bacteria at the single-cell level. In this work, we report the faithful capture of growth-dependent gene expression patterns in individual Salmonella and Pseudomonas bacteria. The results of our analysis showed that not only we could capture transcripts across different RNA classes but also our method is capable of discerning the transcriptome of bacteria across different culture conditions. ● We used single-cell RNA-sequencing technology to characterize the immune cells landscape over the course of atherosclerosis. Atherosclerosis is considered a cardiac disease which is highly related to infections and previous infections with bacteria or viruses is considered as a risk factor for atherosclerosis. We performed single-cell RNA sequencing of aortic CD45+ cells extracted from healthy and atherosclerotic aorta of mice. We managed to find certain cell populations which were specifically present in atherosclerotic mice. One of the atheroschelorotic populations was previously undescribed TREM2high macrophages showing enrichment in Trem2 gene expression. This population of macrophages seemed to be involved in functions like lipid metabolism and catabolism and lesion calcification. This work revealed the phenotypic heterogeneity and immune cells landscape of different immune cell populations at different stages of atherosclerosis. Our work paves the way to better describe the relation between different infectious diseases and cardiovascular diseases. ● We developed a web-based platform called Infection Atlas to browse and visualize single-cell RNA-sequencing data. Infection Atlas platform provides a user-friendly interface to study different aspects of infectious diseases at the single-cell level and can potentially promote targeted approaches to intervene in infectious diseases. This platform which is available at infection-atlas.org in the short term provides a user-friendly interface to browse and visualize different aspects of infectious diseases and in the long-term is expected to be a comprehensive atlas of infection in human and mouse across different tissues and different pathogens. Overall, in this thesis we provide a framework to study infectious diseases at the single cell level with providing novel data analysis methods and this thesis paves the way for future studies to study host-pathogen encounters at the single-cell level.},
  subject      = {Einzelzellanalyse},
  language  = {en}
}