Abstract
To investigate the microbiota of the healthy external auditory canal (EAC) culture-independently and to evaluate the usefulness of the swabbing method in collecting EAC microbiota samples. Cohort study. Fifty healthy asymptomatic working-age volunteers. Samples were harvested with DNA-free swabs from the volunteers' EACs. Amplicon sequencing of the 16S rRNA gene was used to characterize the microbial communities in the samples. The swabbing method is feasible for EAC microbiota sample collection. The analyzed 41 samples came from 27 female and 14 male subjects; 4 samples were excluded due to recent antimicrobial treatment and 5 because of low sequence count or suspected contaminant microbes. The four most frequent amplicon sequence variants in the microbiota data were Staphylococcus auricularis, Propionibacterium acnes, Alloiococcus otitis, and Turicella otitidis. Typically, the dominant amplicon sequence variant in a sample was one of the most frequent bacteria, but there were also subjects where the dominant species was not among the most frequent ones. The genus Alloiococcus was least common in females who reported cleaning their ears. Subjects with a high relative abundance of Alloiococcus typically had a low abundance of Staphylococcus, which may be a sign of the two being competing members of the microbial community. The most common bacteria in the microbiome of the healthy EAC were Staphylococcus auricularis, Propionibacterium acnes, Alloiococcus otitis, and Turicella otitidis. The EAC microbiota seems more diverse and individualized than previously thought. Also, ear cleaning habits seem to alter the EAC microbiome.
Highlights
There are a total of 10,266,925 sequence reads and a total of 3,767 unique Amplicon Sequence Variants (ASVs) in the data
ASVs represent microbes that have an identical V3-V4 16S rRNA sequence according to the analysis run with dada2, version 1.7.7
# Subsampled to the same number of reads per sample: ear_ASV_final_R
Summary
Load required packages: library("kableExtra") library("phyloseq") library("ggplot2") library("gridExtra") library("reshape2") library("decontam") library("vegan") library("tools") library("dplyr") library("cluster") library("clusterSim") library("ade4") library("adegraphics") library("DESeq2"). # Function for relative abundance tables and bar charts relAbundChart
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