Saturday, November 23, 2024
11/23/2024
ABSTRACT Cystic fibrosis (CF) is characterized by the formation of thick mucus in the lung leading to chronic infection of various pathogens that are prone to developing antibiotic tolerance. Despite effective modulator therapy (HEMT) that improves lung function and many clinical outcomes, HEMT does not eliminate chronic, antibiotic-tolerant lung infections, the major cause of morbidity and mortality in CF. Although most people with CF (pwCF) have multispecies lung infections, almost all published studies focus on single-species infection models. Thus, polymicrobial-host interactions in CF are not completely understood, especially under physiologically relevant conditions such as anoxia typical of mucus plugs. The overarching goal of our work is to use in vitro models to gain insight into how polymicrobial infections develop in pwCF. Bacterial pathogens have been shown to secrete membrane vesicles (bEVs) that diffuse through the CF mucus to deliver virulence factors such as DNA, RNA, and proteins to their targets. As recent studies have shown that the first exposure to bacterial products alters DNA methylation and gene silencing that affect subsequent exposures, our hypothesis is that pwCF develop chronic infections in part due to epigenetic changes caused by preexposure to CF pathogens that reduce the HBEC immune response to infection over time. This application aims to characterize the effects of an in vitro model of CF polymicrobial infection on human bronchial epithelial cells (HBEC) with preexposure to bEVs secreted by the common CF pathogen Staphylococcus aureus. The polymicrobial culture contains four prevalent and abundant CF pathogens: Pseudomonas aeruginosa, S. aureus, Streptococcus sanguinis, and Prevotella melanogenica. Using transcriptomic and proteomic analysis, cytokine analysis, ATAC-Seq, and DNA methylation analysis, this study aims to elucidate the host HBEC response to treatment with bEVs. This study will contribute to our understanding of host-pathogen interactions in the CF lung and potentially identify novel therapeutic targets during infection. This project will provide the applicant with a broad range of both bioinformatic and lab techniques that will provide a strong foundation for her long-term goal of becoming an academic researcher.
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