Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes

Abstract

BackgroundPan-bacterial 16S rRNA microbiome surveys performed with massively parallel DNA sequencing technologies have transformed community microbiological studies. Current 16S profiling methods, however, fail to provide sufficient taxonomic resolution and accuracy to adequately perform species-level associative studies for specific conditions. This is due to the amplification and sequencing of only short 16S rRNA gene regions, typically providing for only family- or genus-level taxonomy. Moreover, sequencing errors often inflate the number of taxa present. Pacific Biosciences’ (PacBio’s) long-read technology in particular suffers from high error rates per base. Herein, we present a microbiome analysis pipeline that takes advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error correct full-length bacterial 16S rRNA genes, which provides high-fidelity species-level microbiome data.ResultsAnalysis of a mock community with 20 bacterial species demonstrated 100% specificity and sensitivity with regard to taxonomic classification. Examination of a 250-plus species mock community demonstrated correct species-level classification of > 90% of taxa, and relative abundances were accurately captured. The majority of the remaining taxa were demonstrated to be multiply, incorrectly, or incompletely classified. Using this methodology, we examined the microgeographic variation present among the microbiomes of six sinonasal sites, by both swab and biopsy, from the anterior nasal cavity to the sphenoid sinus from 12 subjects undergoing trans-sphenoidal hypophysectomy. We found greater variation among subjects than among sites within a subject, although significant within-individual differences were also observed. Propiniobacterium acnes (recently renamed Cutibacterium acnes) was the predominant species throughout, but was found at distinct relative abundances by site.ConclusionsOur microbial composition analysis pipeline for single-molecule real-time 16S rRNA gene sequencing (MCSMRT, https://github.com/jpearl01/mcsmrt) overcomes deficits of standard marker gene-based microbiome analyses by using CCS of entire 16S rRNA genes to provide increased taxonomic and phylogenetic resolution. Extensions of this approach to other marker genes could help refine taxonomic assignments of microbial species and improve reference databases, as well as strengthen the specificity of associations between microbial communities and dysbiotic states.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0569-2) contains supplementary material, which is available to authorized users.

Non-specific amplification of human DNA is a major challenge for 16S rRNA gene sequence analysis

“…The Pacific BioSciences SMRT platform has seen the greatest promise in this regard with the implementation of "Circular Consensus Sequencing" in conjunction with denoising algorithms, allowing for the production of long reads of high quality 24 . Earl et al showed that this new method using degenerate primers targeting the entire 16S rRNA gene, still resulted in off target amplification of the human genome 25 . This study also noted that this off target amplification was related to the ratio of human to bacterial DNA.…”

Evaluation of microbial communities in peels of Brazilian tropical fruits by amplicon sequence analysis

“…Of comparable importance is the discrimination of bacterial communities at species level although the discrimination of fungal communities was just possible at phylum and genus levels in the present study. The use of 16S rRNA gene for the discrimination of bacterial community at species level was demonstrated in another similar study [33], while the use of ITS rRNA gene for the discrimination of fungal communities at genera level is more reliable than at species level [34]. As the present study was based on the analysis of sequenced DNA amplicons, a culture-based microbiological investigation should be conducted to determine the load of fruit peel microorganisms, thereby supplement the present analysis.…”

Taxonomic classification method for metagenomics based on core protein families with Core-Kaiju

“…We highlight that other microbiome sequencing approaches exist beyond metagenomics or 16S amplicons on a MiSeq (integrated instrument performing clonal amplification and sequencing), for example PacBio long-read sequencing ( 62 ). Earl and collaborators ( 63 ) used a CAMI dataset to test the accuracy of this method and it is therefore possible to indirectly compare Core-Kaiju with PacBio through their results. Also in this case we found that our method gives a slightly higher R 2 score for the genera abundances composition, confirming the competitiveness of Core-Kaiju even with the long-read sequencing technologies, such as PacBio.…”