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"Insights into S. aureus infection physiology through -omics approaches"

Carolyn Ibberson headshot
Dr. Carolyn Ibberson
School of Biological Sciences
Georgia Institute of Technology
Online via Zoom
Type of Event:
Department Seminars


Chronic infections place a significant burden on healthcare systems, requiring over $20 billion in treatment annually in the United States alone. Notably, chronic infections are frequently polymicrobial and are often recalcitrant to antibiotic treatment, through a process termed “synergy”. Despite the clinical importance, many key features of bacterial physiology in chronic infections, including the molecular mechanisms and impacts of microbe-microbe interactions, remain understudied, in part due to the challenge of assessing bacterial physiology in the human host. My work aims to address this challenge, focused on the human pathogen Staphylococcus aureus, a leading cause of human infection worldwide and a significant cause of both morbidity and mortality. Specifically, I ask foundational questions about how S. aureus, causes disease and persists in human infection, both by using validated experimental models of infection and by directly analyzing human clinical samples. In my previous work, I found co-infection altered the requirement for ~6% (192 genes) of the S. aureus genome when compared to mono-infection in three different infection models, indicating global changes in S. aureus metabolism in response to another microbe, highlighting the importance of microbe-microbe interactions in mediating bacterial physiology in vivo. In addition, I recently performed the first large scale assessment of S. aureus physiology in situ in chronic human infection and found remarkable conservation of S. aureus gene expression in the cystic fibrosis (CF) lung across patients using RNA-seq, despite numerous epidemiological differences. With this data, I inferred the metabolic state and nutritional environment of S. aureus in CF sputum including iron scarcity, carbohydrate use, and virulence factor production. Further, through a machine learning framework, I defined a ‘human CF lung transcriptome signature’ – 32 genes whose transcription distinguishes human CF sputum from other in vivo and in vitro environments, primarily consisting of genes involved in metabolism and virulence – and was able to apply these findings to make an in vitro model more similar to CF infection. Ongoing work further explores mechanisms that allow S. aureus to establish and persist in chronic polymicrobial infections, including CF, osteomyelitis, and chronic wounds, centered on the role of microbe-microbe interactions.

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