Microbiota and metabolite profiling reveal specific alterations in bacterial community structure and environment in the cystic fibrosis airway during exacerbation

Abstract

Chronic polymicrobial infections of the lung are the foremost cause of morbidity and mortality in cystic fibrosis (CF) patients. The composition of the microbial flora of the airway alters considerably during infection, particularly during patient exacerbation. An understanding of which organisms are growing, their environment and their behaviour in the airway is of importance for designing antibiotic treatment regimes and for patient prognosis. To this end, we have analysed sputum samples taken from separate cohorts of CF and non-CF subjects for metabolites and in parallel, and we have examined both isolated DNA and RNA for the presence of 16S rRNA genes and transcripts by high-throughput sequencing of amplicon or cDNA libraries. This analysis revealed that although the population size of all dominant orders of bacteria as measured by DNA- and RNA- based methods are similar, greater discrepancies are seen with less prevalent organisms, some of which we associated with CF for the first time. Additionally, we identified a strong relationship between the abundance of specific anaerobes and fluctuations in several metabolites including lactate and putrescine during patient exacerbation. This study has hence identified organisms whose occurrence within the CF microbiome has been hitherto unreported and has revealed potential metabolic biomarkers for exacerbation.

Figure 1. Relative abundances of bacterial orders identified as operational taxonomic units (OTUs) from the sequence reads generated from sputum samples of CF patients presenting with exacerbation.

The coloured segments of each bar represent the proportion of reads mapping to different bacterial orders. Percentage of sequences from total DNA (A) or total transcribed RNA (B) are described. Details of clinical parameters and microbiological assessment of each of the sputum samples collected are described in Table S3. Total bacterial density in each sputum sample examined is indicated as 16S rRNA copies/ml sputum as measured by quantitative PCR.

Figure 2. Identification of anaerobic bacterial populations among sputum samples from CF patients presenting with exacerbation.

Percentage sequences from DNA-based (A) and RNA-based (B) approaches are described. The coloured segments of each bar represent the proportion of reads mapping to different anaerobic bacterial orders.

Figure 3. Prevalence of emerging CF bacterial pathogens among sputum samples from CF patients suffering exacerbation.

Percentage of sequences from DNA-based (A) or RNA-based (B) approaches are delineated. The coloured segments of each bar represent the proportion of reads mapping to different bacterial orders.

Figure 4. Bacterial community structures of samples from stable CF patients and those presenting with exacerbation as plotted based on Bray–Curtis (BC) distance metric.

Each community from each sample is represented as a filled circle and coloured by class (green – total DNA extracted from CF patients presenting with exacerbation; red – total RNA extracted from CF patients presenting with exacerbation; magenta – total DNA extracted from stable CF patients; cyan – total RNA extracted from stable CF patients). BC sample clusters are based on the distribution of the bacterial orders found in an individual sample. A confirmation of differences between samples was validated using the ade4 permutation test. This determined the statistical significance of the BC; the ellipses represent the 95% confidence region.

Figure 5. Representative HPLC trace of metabolites from sputum taken from a CF patient during a period of stability (A) and presenting with pulmonary exacerbation (B).

Regions are labelled to indicate a range were metabolites of interest that were recovered from samples. Specific concentrations of metabolites identified are detailed in Tables S4 and S5.

Figure 6. Concentrations of lactate (i), pyruvate (ii), putrescine (iii) and palmitate (iv) detected in sputum samples taken from 26 CF patients during a period of stability and presenting with pulmonary exacerbation (A).

Each dot represents an individual patient. Data are given as the average values measured in triplicate (metabolite concentrations are described as µM unless otherwise stated and means ± standard deviations are reported). (B) PLS-DA plots of metabolite profile of sputum taken from 26 CF patients during a period of stability and presenting with pulmonary exacerbation. Stable subjects (green) vs. exacerbated subjects (red); R² = 0.95, Q² = 0.93 for a two-component model. The ellipses represent the 95% confidence region. Permutation tests (n = 1,000) validated the model (p<0.001).