Measures of Cystic Fibrosis Airway Microbiota during Periods of Clinical Stability

Abstract

Rationale: Differences in cystic fibrosis (CF) airway microbiota between periods of clinical stability and exacerbation of respiratory symptoms have been investigated in efforts to better understand microbial triggers of CF exacerbations. Prior studies have often relied on a single sample or a limited number of samples to represent airway microbiota. However, the variability in airway microbiota during periods of clinical stability is not well known.Objectives: To determine the temporal variability of measures of airway microbiota during periods of clinical stability, and to identify factors associated with this variability.Methods: Sputum samples (N = 527), obtained daily from six adults with CF during 10 periods of clinical stability, underwent sequencing of the V4 region of the bacterial 16S ribosomal RNA gene. The variability in airway microbiota among samples within each period of clinical stability was calculated as the average of the Bray-Curtis similarity measures of each sample to every other sample within the same period. Outlier samples were defined as samples outside 1.5 times the interquartile range within a baseline period with respect to the average Bray-Curtis similarity. Total bacterial load was measured with droplet digital polymerase chain reaction.Results: The variation in Bray-Curtis similarity and total bacterial load among samples within the same baseline period was greater than the variation observed in technical replicate control samples. Overall, 6% of samples were identified as outliers. Within baseline periods, changes in bacterial community structure occurred coincident with changes in maintenance antibiotics (P < 0.05, analysis of molecular variance). Within subjects, bacterial community structure changed between baseline periods (P < 0.01, analysis of molecular variance). Sample-to-sample similarity within baseline periods was greater with fewer interval days between sampling.Conclusions: During periods of clinical stability, airway bacterial community structure and bacterial load vary among daily sputum samples from adults with CF. This day-to-day variation has bearing on study design and interpretation of results, particularly in analyses that rely on single samples to represent periods of interest (e.g., clinical stability vs. pulmonary exacerbation). These data also emphasize the importance of accounting for maintenance antibiotic use and granularity of sample collection in studies designed to assess the dynamics of CF airway microbiota relative to changes in clinical state.

Keywords: airway infection; cystic fibrosis; microbiome.

Figure 1.

Sample-to-sample similarity of airway microbiota within baseline periods compared with control samples. Ten baseline periods in six subjects (labeled 1–6) are shown, with multiple baseline periods from the same subject (subjects 2 and 5) labeled a–d. Each point represents the average pairwise Bray-Curtis similarity of that sample to all other samples within that baseline period. Medians and interquartile ranges of all samples within each baseline period and within DNA sequencing control samples (technical replicates of sputum samples [TR1] and generous donor samples [TR2]) are shown. Average pairwise Bray-Curtis similarity of samples is significantly less than average pairwise Bray-Curtis similarity of DNA sequencing control samples within all but one baseline period (P < 0.001 for all baseline periods except baseline 6 [P = 0.262], linear mixed model).

Figure 2.

Total bacterial load within baseline periods. Subjects and baseline periods are labeled as in Figure 1. Each sample point represents the average of droplet digital polymerase chain reaction (ddPCR) measurements run in duplicate. The medians and interquartile ranges of total 16S rRNA gene copy ddPCR measurements of samples in each baseline period are shown.

Figure 3.

Bacterial community structure and changes in maintenance antibiotics. Bray-Curtis–based nonmetric multidimensional scaling (nMDS) plots of samples from each baseline period during which the subject had a change in maintenance antibiotic use are shown. Points are colored by maintenance antibiotic regimen. The centroids of the clusters (black points) significantly differ between maintenance antibiotic regimens (P < 0.05 for all plots, analysis of molecular variance).

Figure 4.

Bacterial community structure changes between baseline periods within the same subjects. Bray-Curtis–based nonmetric multidimensional scaling (nMDS) plots of samples from multiple baseline periods are shown for (A) subject 2 and (B) subject 5. Below each plot is a timeline of the duration (days) of each baseline period (above the line) and the duration separating the baseline periods (below the line). Baseline periods are color coded, and centroids of each baseline period are designated by letter. The centroid of the clusters within each subject significantly differs between baseline periods (P < 0.01, analysis of molecular variance).

Figure 5.

Sample-to-sample similarity measures based on sampling interval. Medians and interquartile ranges of all possible pairwise comparisons of Bray-Curtis similarity within each baseline period are shown at select pairwise intervals. Pairwise comparisons of samples from different maintenance antibiotic regimens (yellow points) are shown separately from comparisons of samples from the same maintenance antibiotic regimens (gray points). Bray-Curtis similarity significantly decreases with increasing sampling intervals (P = 0.048; 95% confidence interval, −0.002, −0.0003; linear mixed model).