Design of the SPIROMICS Study of Early COPD Progression: SOURCE Study.

The biological mechanisms leading some tobacco-exposed individuals to develop early-stage chronic obstructive pulmonary disease (COPD) are poorly understood. This knowledge gap hampers development of disease-modifying agents for this prevalent condition. Accord-ingly, with National Heart, Lung and Blood Institute support, we initiated the SPIROMICS Study of Early COPD Progression (SOURCE), a multicenter observational cohort study of younger individuals with a history of cigarette smoking and thus at-risk for, or with, early-stage COPD. Our overall objectives are to identify those who will develop COPD earlier in life, characterize them thoroughly, and by contrasting them to those not developing COPD, define mechanisms of disease progression. SOURCE utilizes the established SPIROMICS clinical network. Its goal is to enroll n=649 participants, ages 30-55 years, all races/ethnicities, with ≥10 pack-years cigarette smoking, in either Global Initiative for Chronic Obstructive Lung Disease (GOLD) groups 0-2 or with Preserved Ratio Impaired Spirometry (PRISm); and an additional n=40 never-smoker controls. Participants undergo baseline and three-year follow-up visits, each including high-resolution computed tomography; respiratory oscillometry and spirometry (pre- and post-bronchodilator administration), exhaled breath condensate (baseline only); and extensive biospecimen collection, including sputum induction. Symptoms, interim healthcare utilization, and exacerbations are captured every six months via follow-up phone calls. An embedded bronchoscopy sub-study involving n=100 participants (including all never-smokers) will allow collection of lower airway samples for genetic, epigenetic, genomic, immunological, microbiome, mucin analyses, and basal cell culture. SOURCE should provide novel insights into the natural history of lung disease in younger individuals with a smoking history, and its biological basis.

Mucus polymer concentration and in vivo adaptation converge to define the antibiotic response of Pseudomonas aeruginosa during chronic lung infection.

The airway milieu of individuals with muco-obstructive airway diseases (MADs) is defined by the accumulation of dehydrated mucus due to hyperabsorption of airway surface liquid and defective mucociliary clearance. Pathological mucus becomes progressively more viscous with age and disease severity due to the concentration and overproduction of mucin and accumulation of host-derived extracellular DNA (eDNA). Respiratory mucus of MADs provides a niche for recurrent and persistent colonization by respiratory pathogens, including Pseudomonas aeruginosa, which is responsible for the majority of morbidity and mortality in MADs. Despite high concentration inhaled antibiotic therapies and the absence of antibiotic resistance, antipseudomonal treatment failure in MADs remains a significant clinical challenge. Understanding the drivers of antibiotic tolerance is essential for developing more effective treatments that eradicate persistent infections. The complex and dynamic environment of diseased airways makes it difficult to model antibiotic efficacy in vitro. We aimed to understand how mucin and eDNA concentrations, the two dominant polymers in respiratory mucus, alter the antibiotic tolerance of P. aeruginosa. Our results demonstrate that polymer concentration and molecular weight affect P. aeruginosa survival post antibiotic challenge. Polymer-driven antibiotic tolerance was not explicitly associated with reduced antibiotic diffusion. Lastly, we established a robust and standardized in vitro model for recapitulating the ex vivo antibiotic tolerance of P. aeruginosa observed in expectorated sputum across age, underlying MAD etiology, and disease severity, which revealed the inherent variability in intrinsic antibiotic tolerance of host-evolved P. aeruginosa populations. IMPORTANCE: Antibiotic treatment failure in Pseudomonas aeruginosa chronic lung infections is associated with increased morbidity and mortality, illustrating the clinical challenge of bacterial infection control. Understanding the underlying infection environment, as well as the host and bacterial factors driving antibiotic tolerance and the ability to accurately recapitulate these factors in vitro, is crucial for improving antibiotic treatment outcomes. Here, we demonstrate that increasing concentration and molecular weight of mucin and host eDNA drive increased antibiotic tolerance to tobramycin. Through systematic testing and modeling, we identified a biologically relevant in vitro condition that recapitulates antibiotic tolerance observed in ex vivo treated sputum. Ultimately, this study revealed a dominant effect of in vivo evolved bacterial populations in defining inter-subject ex vivo antibiotic tolerance and establishes a robust and translatable in vitro model for therapeutic development.

Isolation of Membrane Bound Mucins from Human Bronchial Epithelial Cells.

Membrane-bound mucins constitute a large portion of the periciliary layer of lung epithelial surfaces, and thus play an important role in many aspects of innate defense. The biophysical and biochemical properties of the membrane-bound mucins have important implications for mucociliary clearance, viral penetration, and potential therapeutics delivered to the airway surface. Hence, isolating them and determining these properties is important in understanding airways disease and ultimately in developing treatments. Here, we describe a method using isopycnic centrifugation to enrich and isolate shed membrane-bound mucins from the washings of human bronchial epithelial cell cultures.

Imaging of Mucin Networks with Atomic Force Microscopy.

Mucin networks serve as the structural scaffold of mucus and play a significant role in determining its biophysical properties. Thus, characterizing the organization, macromolecular structure, and interactions within these networks is a key step in understanding the parameters that govern mucus functionality in both health and disease. Atomic force microscopy (AFM) is uniquely suited to study mucin networks; AFM can clearly resolve nanometer-sized features, does not require fixation or metallization, and can be performed in air or aqueous solutions. In this chapter we describe protocols to image mucin networks using AFM. First, we describe two protocols to enrich and isolate mucin samples in preparation for AFM imaging. Next, we detail a protocol to deposit the samples onto a mica substrate. Finally, we give general tips to optimize and troubleshoot AFM imaging of mucin networks.

Quantitation of MUC5AC and MUC5B by Stable Isotope Labeling Mass Spectrometry.

Mucins MUC5AC and MUC5B are large glycoproteins that play an essential role in the innate defense of epithelial surfaces and their quantitation in biological samples would be informative about the health status of the tissue/samples they are derived from. However, they are difficult to study and quantify with traditional methods such as ELISA and western blot, due to their size, heterogeneity, and high degree of glycosylation. We successfully implemented a stable isotope labeling mass spectrometry approach for absolute quantification of mucin macromolecules. Here, in detail, we describe this accurate and sensitive liquid chromatography and mass spectrometry (LC-MS) method applied for both MUC5AC and MUC5B quantification in diverse and complex biological samples.

Loss of Airway Phylogenetic Diversity Is Associated with Clinical and Pathobiological Markers of Disease Development in Chronic Obstructive Pulmonary Disease.

Rationale: The airway microbiome has the potential to shape chronic obstructive pulmonary disease (COPD) pathogenesis, but its relationship to outcomes in milder disease is unestablished. Objectives: To identify sputum microbiome characteristics associated with markers of COPD in participants of the Subpopulations and Intermediate Outcome Measures of COPD Study (SPIROMICS). Methods: Sputum DNA from 877 participants was analyzed using 16S ribosomal RNA gene sequencing. Relationships between baseline airway microbiota composition and clinical, radiographic, and mucoinflammatory markers, including longitudinal lung function trajectory, were examined. Measurements and Main Results: Participant data represented predominantly milder disease (Global Initiative for Chronic Obstructive Lung Disease stage 0-2 obstruction in 732 of 877 participants). Phylogenetic diversity (i.e., range of different species within a sample) correlated positively with baseline lung function, decreased with higher Global Initiative for Chronic Obstructive Lung Disease stage, and correlated negatively with symptom burden, radiographic markers of airway disease, and total mucin concentrations (P < 0.001). In covariate-adjusted regression models, organisms robustly associated with better lung function included Alloprevotella, Oribacterium, and Veillonella species. Conversely, lower lung function, greater symptoms, and radiographic measures of small airway disease were associated with enrichment in members of Streptococcus, Actinobacillus, Actinomyces, and other genera. Baseline sputum microbiota features were also associated with lung function trajectory during SPIROMICS follow-up (stable/improved, decline, or rapid decline groups). The stable/improved group (slope of FEV1 regression ⩾66th percentile) had greater bacterial diversity at baseline associated with enrichment in Prevotella, Leptotrichia, and Neisseria species. In contrast, the rapid decline group (FEV1 slope ⩽33rd percentile) had significantly lower baseline diversity associated with enrichment in Streptococcus species. Conclusions: In SPIROMICS, baseline airway microbiota features demonstrate divergent associations with better or worse COPD-related outcomes.

Mucus polymer concentration and in vivo adaptation converge to define the antibiotic response of Pseudomonas aeruginosa during chronic lung infection.

The airway milieu of individuals with muco-obstructive airway diseases (MADs) is defined by the accumulation of dehydrated mucus due to hyperabsorption of airway surface liquid and defective mucociliary clearance. Pathological mucus becomes progressively more viscous with age and disease severity due to the concentration and overproduction of mucin and accumulation of host-derived extracellular DNA (eDNA). Respiratory mucus of MADs provides a niche for recurrent and persistent colonization by respiratory pathogens, including Pseudomonas aeruginosa , which is responsible for the majority of morbidity and mortality in MADs. Despite high concentration inhaled antibiotic therapies and the absence of antibiotic resistance, antipseudomonal treatment failure in MADs remains a significant clinical challenge. Understanding the drivers of antibiotic recalcitrance is essential for developing more effective treatments that eradicate persistent infections. The complex and dynamic environment of diseased airways makes it difficult to model antibiotic efficacy in vitro . We aimed to understand how mucin and eDNA concentrations, the two dominant polymers in respiratory mucus, alter the antibiotic tolerance of P. aeruginosa . Our results demonstrate that polymer concentration and molecular weight affect P. aeruginosa survival post antibiotic challenge. Polymer-driven antibiotic tolerance was not explicitly associated with reduced antibiotic diffusion. Lastly, we established a robust and standardized in vitro model for recapitulating the ex vivo antibiotic tolerance of P. aeruginosa observed in expectorated sputum across age, underlying MAD etiology, and disease severity, which revealed the inherent variability in intrinsic antibiotic tolerance of host-evolved P. aeruginosa populations. Importance: Antibiotic treatment failure in Pseudomonas aeruginosa chronic lung infections is associated with increased morbidity and mortality, illustrating the clinical challenge of bacterial infection control. Understanding the underlying infection environment, as well as the host and bacterial factors driving antibiotic tolerance and the ability to accurately recapitulate these factors in vitro , is crucial for improving antibiotic treatment outcomes. Here, we demonstrate that increasing concentration and molecular weight of mucin and host eDNA drive increased antibiotic tolerance to tobramycin. Through systematic testing and modeling, we identified a biologically relevant in vitro condition that recapitulates antibiotic tolerance observed in ex vivo treated sputum. Ultimately, this study revealed a dominant effect of in vivo evolved bacterial populations in defining inter-subject ex vivo antibiotic tolerance and establishes a robust and translatable in vitro model for therapeutic development.