Metaproteomic insights into chronic respiratory infections: Microbial community dynamics in cystic fibrosis and chronic rhinosinusitis revealed by BONCAT-FACS-MS

Abstract

Chronic respiratory bacterial infections represent a significant global health burden, exacerbated by the rising crisis of antibiotic resistance. Traditional diagnostic and treatment strategies, often relying on culture-dependent methods, often fail to capture the full spectrum of microbial activity in airway infections. This dissertation explores advanced metaproteomic techniques to address this challenge, optimizing and applying bioorthogonal non-canonical amino acid tagging combined with fluorescence-activated cell sorting and mass spectrometry (BONCAT-FACS-MS) to study polymicrobial dynamics in saliva and mucus samples from patients with cystic fibrosis (CF) and chronic rhinosinusitis (CRS). By isolating active microbial cells from complex samples, BONCAT-FACS-MS provides a deeper understanding of microbial activity in vivo, reducing host contamination limitations and allowing for a more precise analysis of microbial behavior.The optimization of BONCAT-FACS-MS for use in human mucus samples is discussed in Chapter 2, showcasing its ability to identify active microbes in complex environments where traditional metagenomic and metatranscriptomic approaches are limited. Chapter 3 applies this technique to clinical samples from patients with CF and CRS, unveiling highly dynamic microbial communities in chronic infections, with significant variation in metabolic activity between taxa. Gene Ontology analysis of the metaproteomes identified key proteins involved in energy metabolism, protein synthesis, and stress responses, offering insights into bacterial survival and persistence in hostile environments. Chapter 4 investigates the differential protein expression of Staphylococcus aureus under conditions that mimic the respiratory environment, identifying differential expression in virulence factors, metabolic regulators, and antibiotic resistance proteins in response to nutrient limitations. These data underscore the rapid adaptability of S. aureus to its environment and suggest potential therapeutic targets for disrupting key pathways critical for bacterial persistence, thereby opening new avenues for the development of effective treatment strategies. Overall, this work advances the field of microbial metaproteomics by refining BONCAT-FACS-MS and demonstrating its utility in studying active bacterial populations in vivo. The findings emphasize the importance of focusing on metabolically active subpopulations within bacterial communities, which may ultimately contribute to the development of more effective strategies for diagnosing and treating chronic infections.