Upper airways microbiota in antibiotic-naïve wheezing and healthy infants from the tropics of rural Ecuador

Abstract

Background: Observations that the airway microbiome is disturbed in asthma may be confounded by the widespread use of antibiotics and inhaled steroids. We have therefore examined the oropharyngeal microbiome in early onset wheezing infants from a rural area of tropical Ecuador where antibiotic usage is minimal and glucocorticoid usage is absent.

Materials and methods: We performed pyrosequencing of amplicons of the polymorphic bacterial 16S rRNA gene from oropharyngeal samples from 24 infants with non-infectious early onset wheezing and 24 healthy controls (average age 10.2 months). We analyzed microbial community structure and differences between cases and controls by QIIME software.

Results: We obtained 76,627 high quality sequences classified into 182 operational taxonomic units (OTUs). Firmicutes was the most common and diverse phylum (71.22% of sequences) with Streptococcus being the most common genus (49.72%). Known pathogens were found significantly more often in cases of infantile wheeze compared to controls, exemplified by Haemophilus spp. (OR=2.12, 95% Confidence Interval (CI) 1.82-2.47; P=5.46×10(-23)) and Staphylococcus spp. (OR=124.1, 95%CI 59.0-261.2; P=1.87×10(-241)). Other OTUs were less common in cases than controls, notably Veillonella spp. (OR=0.59, 95%CI=0.56-0.62; P=8.06×10(-86)).

Discussion: The airway microbiota appeared to contain many more Streptococci than found in Western Europe and the USA. Comparisons between healthy and wheezing infants revealed a significant difference in several bacterial phylotypes that were not confounded by antibiotics or use of inhaled steroids. The increased prevalence of pathogens such as Haemophilus and Staphylococcus spp. in cases may contribute to wheezing illnesses in this age group.

Figure 1. Phylogenetic tree and Heatmap of bacterial 16S rRNA sequences derived from throat swabs.

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.

Figure 2. Shannon diversity collector curves.

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).

Figure 3. Phylogenetic identification of Haemophilus OTUs.

Phylogenetic analysis of the 16S rRNA sequences of the OTUs assigned taxonomically to Haemophilus genus (OTUs 32, 108, 162 and 190, shown in Red) together with reference Haemophilus 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 Morganella morganii, Proteus mirabilis and Providencia stuartii.

Figure 4. Alpha and Beta diversity comparisons between Cases and Controls.

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.