学位论文详细信息
Probing pseudomonas aeruginosa physiology during infection using –omics techniques, phenotypic assays and mouse models
Pseudomonas aeruginosa;Glutathione;Antibiotics;Pneumonia;Chronic wound;Burn wound;Chemostats;Transcriptomics;Proteomics
Michie, Kelly Leorah ; Whiteley, Marvin Biology Botchwey, Edward Brown, Sam Gibson, Greg Goldberg, Joanna B. ; Whiteley, Marvin
University:Georgia Institute of Technology
Department:Biology
关键词: Pseudomonas aeruginosa;    Glutathione;    Antibiotics;    Pneumonia;    Chronic wound;    Burn wound;    Chemostats;    Transcriptomics;    Proteomics;   
Others  :  https://smartech.gatech.edu/bitstream/1853/63652/1/MICHIE-DISSERTATION-2020.pdf
美国|英语
来源: SMARTech Repository
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【 摘 要 】

The opportunistic pathogen Pseudomonas aeruginosa causes severe disease in people with compromised immune systems or co-morbidities such as diabetes or cystic fibrosis. Since even intense antibiotic regimens are often ineffective, there is a great need to better understand P. aeruginosa infection biology. Our first research goal was to elucidate the role of glutathione (GSH) biosynthesis for P. aeruginosa during infection. GSH is a major cellular antioxidant that is important for protection from oxidative stress. We found that GSH biosynthesis provides protection against some antimicrobials, such as bleach and ciprofloxacin. We also discovered that GSH biosynthesis provides a modest fitness benefit to P. aeruginosa in a mouse model of acute pneumonia, but not in chronic wound, abscess, and burn wound mouse models. Our second research goal was to characterize the transcriptomic and proteomic signatures of growth rate in P. aeruginosa. Growth rate has significant impacts on cellular physiology, from cell size to stress tolerance. We cultured P. aeruginosa at four different growth rates using a chemostat, and quantified mRNA and protein abundances using RNA-seq and proteomics mass spectrometry, respectively. We observed modest correlations between mRNA and protein expression. We also discovered that there was greater variation in mRNA expression compared to protein expression, and that mRNA expression was more strongly affected by changes in growth rate. We calculated protein-to-mRNA ratios, or conversion factors, which could be used to more accurately predict protein abundance from RNA-seq data. The information presented in this work may be useful for better understanding, and ultimately treating, P. aeruginosa infections.

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