The Impact of Persistent Bacterial Bronchitis on the Pulmonary Microbiome of Children

Persistent bacterial bronchitis (PBB) is a leading cause of chronic cough in young children and yet the condition is poorly understood. Current management involves prolonged antibiotic treatment, however, early diagnosis is key to improving patient outcomes. <div>This study investigated the differences in the bacterial community in the lower respiratory tract of healthy children compared to those with PBB, using both blind and non-blind lung brushings. The less invasive blind brushing method was shown to provide robust data regarding the lower airways microbiome in this condition and thus provides an opportunity to further our understanding of the dynamics of the lower airways microbiome in health and disease.</div

Table of patient demographics for cases (PBB) and controls.

<p>Table of patient demographics for cases (PBB) and controls.</p

Ordered bar chart of the top 20 OTUs present in both the mother of study children less than 2 years old and their children.

<p>This subgroup includes both healthy children (red) and those diagnosed with PBB (blue). Mothers are indicated in green. Samples are ordered by a Bray Curtis dissimilarity hierarchical cluster, shown above. Key to colours used for each genus is included. Lower bar plot indicates the log10 copies per μl as calculated by qPCR.</p

Ordered bar chart of the top 20 OTUs present in both the blind and non-blind brushings.

<p>Samples are ordered by a Bray Curtis dissimilarity hierarchical cluster shown by the top plot. Key to colours used for each genus is included. Identical patient numbers indicate samples were taken from the same individual. Sample type is indicated in the labelling beneath the graph with red indicating blind brush and blue indicating non-blind brush.</p

Epidemiologic characteristics of the children investigated in the study.

<p>Epidemiologic characteristics of the children investigated in the study.</p

Differences in bacterial 16S rRNA sequences from throat swabs of infants in rural Ecuador with non-infectious wheeze and healthy controls.

*<p>Results are shown for the lowest level of taxonomic identification achieved. Only groups with more than 100 sequences and statistically significant differences are shown. <i>P</i> values are corrected for multiple comparisons.</p

Phylogenetic tree and Heatmap of bacterial 16S rRNA sequences derived from throat swabs.

<p>Total sequence counts for individual operational taxonomic units (OTUs) are shown in the right column. Taxonomy assignments at the phylum level are shown in the inner column and colour coded. Intrusions of different colours within particular phyla indicate discrepancies between the phylogenetic and database classifications.</p

Phylogenetic identification of <i>Haemophilus</i> OTUs.

<p>Phylogenetic analysis of the 16S rRNA sequences of the OTUs assigned taxonomically to <i>Haemophilus</i> genus (OTUs 32, 108, 162 and 190, shown in Red) together with reference <i>Haemophilus</i> sequences from the SILVA database, using the ARB alignment editor. The scale bar indicates 10% sequence divergence, and NCBI accession numbers are included. The tree was rooted with a near neighbour outgroup constructed with sequences from <i>Morganella morganii</i>, <i>Proteus mirabilis</i> and <i>Providencia stuartii</i>.</p

Shannon diversity collector curves.

<p>Multiple rarefaction curves were collated from each sample’s Shannon diversity index. The graphic shows the estimated diversity plotted against the number of sequences per sample. Each line represents one sample. The plateau in each estimated diversity curve indicates the minimum number of sequences to capture diversity. For all samples the plateau was achieved at approximately 320 sequences (red vertical line), well below our chosen rarefaction threshold of 969 sequences (blue line).</p

Alpha and Beta diversity comparisons between Cases and Controls.

<p>A) Scatter dot plot comparing cases versus controls values of chao1 richness index. B) Scatter dot plot comparing values of Shannon diversity index. C) Scatter dot plot comparing equitability evenness index. D) Unweighted UNIFRAC Principal Coordinate Analysis (PCoA) plot comparing presence/absence metrics. E) Weighted UNIFRAC Principal Coordinate Analysis (PCoA) plot comparing presence/absence metrics and abundance.</p