Dataset Information

In Silico and Experimental Evaluation of Primer Sets for Species-Level Resolution of the Vaginal Microbiota Using 16S Ribosomal RNA Gene Sequencing.

ABSTRACT: Background:Identification of bacteria in human vaginal specimens is commonly performed using 16S ribosomal RNA (rRNA) gene sequences. However, studies utilize different 16S primer sets, sequence databases, and parameters for sample and database clustering. Our goal was to assess the ability of these methods to detect common species of vaginal bacteria. Methods:We performed an in silico analysis of 16S rRNA gene primer sets, targeting different hypervariable regions. Using vaginal samples from women with bacterial vaginosis, we sequenced 16S genes using the V1-V3, V3-V4, and V4 primer sets. For analysis, we used an extended Greengenes database including 16S gene sequences from vaginal bacteria not already present. We compared results with those obtained using the SILVA 16S database. Using multiple database and sample clustering parameters, each primer set's ability to detect common vaginal bacteria at the species level was determined. We also compared these methods to the use of DADA2 for denoising and clustering of sequence reads. Results:V4 sequence reads clustered at 99% identity and using the 99% clustered, extended Greengenes database provided optimal species-level identification of vaginal bacteria. Conclusions:This study is a first step toward standardizing methods for 16S rRNA gene sequencing and bioinformatics analysis of vaginal microbiome data.

SUBMITTER: Van Der Pol WJ

PROVIDER: S-EPMC6941453 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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In Silico and Experimental Evaluation of Primer Sets for Species-Level Resolution of the Vaginal Microbiota Using 16S Ribosomal RNA Gene Sequencing.

Van Der Pol William J WJ Kumar Ranjit R Morrow Casey D CD Blanchard Eugene E EE Taylor Christopher M CM Martin David H DH Lefkowitz Elliot J EJ Muzny Christina A CA

The Journal of infectious diseases 20190101 2

<h4>Background</h4>Identification of bacteria in human vaginal specimens is commonly performed using 16S ribosomal RNA (rRNA) gene sequences. However, studies utilize different 16S primer sets, sequence databases, and parameters for sample and database clustering. Our goal was to assess the ability of these methods to detect common species of vaginal bacteria.<h4>Methods</h4>We performed an in silico analysis of 16S rRNA gene primer sets, targeting different hypervariable regions. Using vaginal ...[more]

PMID: 30535155

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Project description:Aim: 16S rRNA gene-based microbiota analyses (16S metagenomes) using next-generation sequencing (NGS) technologies are widely used to examine the microbial community composition in environmental samples. However, the sequencing capacity of NGS is sometimes insufficient to cover the whole microbial community, especially when analyzing soil and fecal microbiotas. This limitation may have hampered the detection of minority species that potentially affect microbiota formation and structure. Methods: We developed a simple method, termed 16S metagenome-DRIP (Deeper Resolution using an Inhibitory Primer), that not only enhances minority species detection but also increases the accuracy of their abundance estimation. The method relies on the inhibition of normal amplicon formation of the 16S rRNA gene of a target major (abundant) species during the first PCR step. The addition of a biotinylated primer that is complementary to the variable sequence of the V3-V4 region of the target species inhibits a normal amplification process to form an aberrant short amplicon. The fragment is then captured by streptavidin beads for removal from the reaction mixture, and the resulting mixture is utilized for the second PCR with barcode-tag primers. Thus, this method only requires two additional experimental procedures to the conventional 16S metagenome analysis. A proof-of-concept experiment was first conducted using a mock sample consisting of the genomes of 14 bacterial species. Then, the method was applied to infant fecal samples using a Bifidobacterium-specific inhibitory primer (n = 11). Results: As a result, the reads assigned to the family Bifidobacteriaceae decreased on average from 16,657 to 1718 per sample without affecting the total read counts (36,073 and 34,778 per sample for the conventional and DRIP methods, respectively). Furthermore, the minority species detection rate increased with neither affecting Bray-Curtis dissimilarity calculated by omitting the target Bifidobacterium species (median: 0.049) nor changing the relative abundances of the non-target species. While 115 amplicon sequence variants (ASVs) were unique to the conventional method, 208 ASVs were uniquely detected for the DRIP method. Moreover, the abundance estimation for minority species became more accurate, as revealed thorough comparison with the results of quantitative PCR analysis. Conclusion: The 16S metagenome-DRIP method serves as a useful technique to grasp a deeper and more accurate microbiota composition when combined with conventional 16S metagenome analysis methods.

Project description:BackgroundMolecular methods such as next-generation sequencing are actively being employed to characterize the vaginal microbiota in health and disease. Previous studies have focused on characterizing the biological variation in the microbiota, and less is known about how factors related to sampling contribute to the results. Our aim was to investigate the impact of a sampling device and anatomical sampling site on the quantitative and qualitative outcomes relevant for vaginal microbiota research. We sampled 10 Finnish women representing diverse clinical characteristics with flocked swabs, the Evalyn® self-sampling device, sterile plastic spatulas and a cervical brush that were used to collect samples from fornix, vaginal wall and cervix. Samples were compared on DNA and protein yield, bacterial load, and microbiota diversity and species composition based on Illumina MiSeq sequencing of the 16S rRNA gene. We quantified the relative contributions of sampling variables versus intrinsic variables in the overall microbiota variation, and evaluated the microbiota profiles using several commonly employed metrics such as alpha and beta diversity as well as abundance of major bacterial genera and species.ResultsThe total DNA yield was strongly dependent on the sampling device and to a lesser extent on the anatomical site of sampling. The sampling strategy did not affect the protein yield or the bacterial load. All tested sampling methods produced highly comparable microbiota profiles based on MiSeq sequencing. The sampling method explained only 2% (p-value = 0.89) of the overall microbiota variation, markedly surpassed by intrinsic factors such as clinical status (microscopy for bacterial vaginosis 53%, p = 0.0001), bleeding (19%, p = 0.0001), and the variation between subjects (11%, p-value 0.0001).ConclusionsThe results indicate that different sampling strategies yield comparable vaginal microbiota composition and diversity. Hence, past and future vaginal microbiota studies employing different sampling strategies should be comparable in the absence of other technical confounders. The Evalyn® self-sampling device performed equally well compared to samples taken by a clinician, and hence offers a good-quality microbiota sample without the need for a gynecological examination. The amount of collected sample as well as the DNA and protein yield varied across the sampling techniques, which may have practical implications for study design.

Dataset Information

In Silico and Experimental Evaluation of Primer Sets for Species-Level Resolution of the Vaginal Microbiota Using 16S Ribosomal RNA Gene Sequencing.

Publications

In Silico and Experimental Evaluation of Primer Sets for Species-Level Resolution of the Vaginal Microbiota Using 16S Ribosomal RNA Gene Sequencing.

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