PROJECT SUMMARY/ABSTRACT Lindsay Caverly, MD is a pediatric pulmonologist and scientist at the University of Michigan. This K23 proposal will complete Dr. Caverly's training towards her long-term career goal of improving the health of children with lung diseases through a better understanding of the lung microbial ecology. This proposal will build on Dr. Caverly's previously acquired expertise in pulmonary pathophysiology and nontuberculous mycobacterial (NTM) infection to provide her with new expertise in clinical research methodology and computational biology. In the proposed project, she will integrate her established and newly-acquired skills to elucidate the role of airway microbiota in the pathogenesis of NTM infection in individuals with cystic fibrosis (CF). This research and training will be guided by her primary mentor, John J. LiPuma MD, co-mentor Patrick D. Schloss PhD, and an advisory board of accomplished senior scientists with expertise in clinical research methods, computational biology, microbial ecology, and biostatistics, and success in mentoring junior physician-scientists. Dr. Caverly's three year plan includes formal coursework to obtain a Master's Degree in Bioinformatics, professional development activities, and progressively independent research. Although NTM pulmonary infections cause significant morbidity and mortality for individuals with CF, the determinants of NTM pulmonary disease, including risk factors for NTM infection and variables impacting disease progression, are largely unknown. The increasing appreciation that CF airways harbor complex microbial communities provides an opportunity to investigate the role of airway microbiota in the pathogenesis of NTM disease. Aim 1 will test the hypothesis that changes in the structure and metabolic activities of CF airway microbiota precede and predict NTM infection, while Aim 2 will test the hypothesis that features of the structure and metabolic activities CF airway microbiota predict clinical course after NTM infection. To complete these aims, Dr. Caverly will capitalize on an existing repository of CF sputum samples and linked clinical data. She will also execute a prospective, observational study of individuals with CF to complement the existing samples, gain expertise in clinical research methods, and build a repository of CF sputum samples and clinical data for future studies. Dr. Caverly will use state-of-the art DNA sequencing and metabolomics platforms to characterize the structure and metabolic activities of CF airway microbiota, and will integrate the microbial and clinical data using novel analytic techniques of computational biology to build predictive models of patient-relevant outcomes. Dr. Caverly anticipates that these results will have an important positive impact in informing risk prediction for NTM infection, guiding clinical decision making, and illuminating novel biology. This K23 award will establish a foundation for a programmatic line of research...