Managing contamination and diverse bacterial loads in 16S rRNA deep sequencing of clinical samples - implications of the law of small numbers. Managing contamination in 16S deep sequencing

In this article, we investigate patterns of microbial DNA contamination in targeted 16S rRNA amplicon sequencing (16S deep sequencing) and demonstrate how this can be used to filter background bacterial DNA in diagnostic microbiology. We also investigate the importance of sequencing depth.We first determined the patterns of contamination by performing repeat 16S deep sequencing of negative and positive extraction controls. This process identified a few bacterial species dominating across all replicates but also a high inter-sample variability among low-abundant contaminant species in replicates split before PCR amplification. Replicates split after PCR amplification yielded almost identical sequencing results.Based on these observations we suggest using the abundance of the most dominant contaminant species to define a threshold in each clinical sample from where identifications with lower abundancies possibly represent contamination. We evaluated this approach by sequencing of a diluted, staggered mock community and of bile samples from 41 patients with acute cholangitis and non-infectious bile duct stenosis. All clinical samples were sequenced twice using different sequencing depths. We were able to demonstrate that (i) the high inter-sample variability between sequencing replicates is caused by events occurring before or during the PCR-amplification step; (ii) knowledge about the most dominant contaminant species can be used to establish sample-specific cutoffs for reliable identifications; (iii) Below the level of the most abundant contaminant it rapidly becomes very demanding to reliably discriminate between background and true findings; (iv) adequate sequencing depth can only be claimed when the analysis also picks up background contamination.