Culture-independent studies of cystic fibrosis lung microbiota have provided few mechanistic insights into the polymicrobial basis of disease. Deciphering the specific contributions of individual taxa to CF pathogenesis requires comprehensive understanding of their ecophysiology at the site of infection. We hypothesize that only a subset of CF microbiota are translationally active and that these activities vary between subjects. Here, we apply bioorthogonal non-canonical amino acid tagging (BONCAT) to visualize and quantify bacterial translational activity in expectorated sputum. We report that the percentage of BONCAT-labeled (i.e. active) bacterial cells varies substantially between subjects (6-56%). We use fluorescence-activated cell sorting (FACS) and genomic sequencing to assign taxonomy to BONCAT-labeled cells. While many abundant taxa are indeed active, most bacterial species detected by conventional molecular profiling show a mixed population of both BONCAT-labeled and unlabeled cells, suggesting heterogeneous growth rates in sputum. Differentiating translationally active subpopulations adds to our evolving understanding of CF lung disease and may help guide antibiotic therapies targeting bacteria most likely to be susceptible.
AbstractCulture-independent studies of cystic fibrosis lung microbiota have provided few mechanistic insights into the polymicrobial basis of disease. Deciphering the specific contributions of individual taxa to CF pathogenesis requires a comprehensive understanding of theirin situecophysiology. We applied bioorthogonal non-canonical amino acid tagging (BONCAT), a ‘click’ chemistry-based metabolic labeling approach, to quantify and visualize translational activity among CF microbiota. Using BONCAT-based fluorescent imaging on sputum collected from stable CF subjects, we reveal that only a subset of bacteria are translationally active. We also combined BONCAT with fluorescent activated cell sorting (FACS) and 16S rRNA gene sequencing to assign taxonomy to the active subpopulation and found that the most dominant taxa are indeed translationally active. On average, only ∼12-18% of bacterial cells were BONCAT labeled, suggesting a heterogeneous growth strategy widely employed by most airway microbiota. Differentiating translationally active populations from those that are dormant adds to our evolving understanding of the polymicrobial basis of CF lung disease and may help guide patient-specific therapeutic strategies targeting active bacterial populations that are most likely to be susceptible.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.