During the progression of infections from initial onset to chronic lung infections in cystic fibrosis (CF), P. aeruginosa (Pa) and Staphylococcus aureus (Sa) acquire antibiotic resistance and lose virulence factors, both of which have been correlated to late stage infections, higher risk for hospitalization, and lung function decline. Therefore, these infection phenotypes may serve as prognostic indicators of patient outcomes and disease progression. However, accurately measuring infection phenotypes is significantly impeded by poor access to lower-respiratory specimens and an inability to faithfully recapitulate bacterial lung infection phenotypes in the clinical microbiology lab. Our goal is to identify volatile biomarkers that can be used to non-invasively phenotype Pa and Sa directly from lung specimens in order to track lung disease progression.
In her Postdoctoral research, Bean demonstrated that volatile metabolites can be used to differentiate Pa strains and Sa antimicrobial resistance phenotypes in vivo. Building upon these data, at ASU we are intensively investigating the metabolic signatures of Pa and Sa adaptation in chronic lung infections through the analysis of CF lung specimens from early and late-stage infection in both a cross-sectional and longitudinal analysis. We are genotyping, phenotyping, and metabotyping isolates to identify specific biomarkers of mucoidy, motility, quorum sensing deficiency, antibiotic resistance, and small colony variants that translate across the diversity of clinical strains we encounter. Portions of this work have been funded by a NHLBI R01 grant (2021 – 2026).
Trenton J. Davis, Ava V. Karanjia, Charity N. Bhebhe, Sarah B. West, Matthew Richardson, Heather D. Bean. (2020) Pseudomonas aeruginosa volatilome characteristics and adaptations in chronic cystic fibrosis lung infections. mSphere. 5, e00843-20. Link
Alex Gifford, Sven Willger, Emily Dolben, Lisa Moulton, Dana Dorman, Heather D. Bean, Jane E. Hill, Thomas Hampton, Alix Ashare, Deborah A. Hogan. (2016) The use of a multiplex transcript method for the analysis of the Pseudomonas aeruginosa gene expression profiles in the cystic fibrosis lung. Infection and Immunity. 84, 2995-3006. Link
Heather D. Bean*, Jiangjiang Zhu*, Jackson C. Sengle, Jane E. Hill. (2014) Identifying methicillin-resistant Staphylococcus aureus (MRSA) lung infections in mice via breath analysis using secondary electrospray ionization-mass spectrometry (SESI-MS). Journal of Breath Research. 8, 041001. [*co-first authors] Publisher Featured Article Link
Using GCxGC-TOFMS and chemometrics for studying microbial evolution in chronic infections
LECO GCxGC Symposium 2020
Discovering volatile biomarkers using GCxGC-TOFMS: Detecting and phenotyping infections directly from lung samples
American Society for Mass Spectrometry Conference 2016