Comparison of Boiling and Robotics Automation Method in DNA Extraction for Metagenomic Sequencing of Human Oral Microbes

<div><p>The rapid improvement of next-generation sequencing performance now enables us to analyze huge sample sets with more than ten thousand specimens. However, DNA extraction can still be a limiting step in such metagenomic approaches. In this study, we analyzed human oral microbes to compare the performance of three DNA extraction methods: PowerSoil (a method widely used in this field), QIAsymphony (a robotics method), and a simple boiling method. Dental plaque was initially collected from three volunteers in the pilot study and then expanded to 12 volunteers in the follow-up study. Bacterial flora was estimated by sequencing the V4 region of 16S rRNA following species-level profiling. Our results indicate that the efficiency of PowerSoil and QIAsymphony was comparable to the boiling method. Therefore, the boiling method may be a promising alternative because of its simplicity, cost effectiveness, and short handling time. Moreover, this method was reliable for estimating bacterial species and could be used in the future to examine the correlation between oral flora and health status. Despite this, differences in the efficiency of DNA extraction for various bacterial species were observed among the three methods. Based on these findings, there is no “gold standard” for DNA extraction. In future, we suggest that the DNA extraction method should be selected on a case-by-case basis considering the aims and specimens of the study.</p></div

Description of samples used in this study.

<p>Description of samples used in this study.</p

Correlation coefficient (<i>r</i>) matrix among assigned microbes for each sample.

<p>Upper right half represents correlation coefficients based on a logarithm-converted value. Lower left half represents those on linear value. Descriptions of each sample are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154389#pone.0154389.t001" target="_blank">Table 1</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0154389#pone.0154389.g001" target="_blank">Fig 1</a>.</p

Variation of DNA extraction efficiency using each method.

<p>Variation of DNA extraction efficiency using each method.</p

3D plot resulting from principal coordinate analysis derived from 12 samples and the six different boiling methods.

<p>Dots with respective colors indicate they are from the same sample.</p

2D plot resulting from principal component analysis.

<p>A) Plot based on logarithm-converted values for the 25 samples. B) Plot based on the 19 samples from volunteer A enclosed by the dashed circle in panel A. C) Plot based on linear values for the 25 samples. D) Plot based on the 19 samples from volunteer A enclosed by the dashed circle in panel C. Horizontal and vertical axis represent PC1 and PC2, respectively. Sampling day numbers of volunteer A are shown as numerals.</p

Index of α-diversity for each DNA extraction method.

<p>Index of α-diversity for each DNA extraction method.</p

Inter-Individual Differences in the Oral Bacteriome Are Greater than Intra-Day Fluctuations in Individuals

<div><p>Given the advent of massively parallel DNA sequencing, human microbiome is analyzed comprehensively by metagenomic approaches. However, the inter- and intra-individual variability and stability of the human microbiome remain poorly characterized, particularly at the intra-day level. This issue is of crucial importance for studies examining the effects of microbiome on human health. Here, we focused on bacteriome of oral plaques, for which repeated, time-controlled sampling is feasible. Eighty-one supragingival plaque subjects were collected from healthy individuals, examining multiple sites within the mouth at three time points (forenoon, evening, and night) over the course of 3 days. Bacterial composition was estimated by 16S rRNA sequencing and species-level profiling, resulting in identification of a total of 162 known bacterial species. We found that species compositions and their relative abundances were similar within individuals, and not between sampling time or tooth type. This suggests that species-level oral bacterial composition differs significantly between individuals, although the number of subjects is limited and the intra-individual variation also occurs. The majority of detected bacterial species (98.2%; 159/162), however, did not fluctuate over the course of the day, implying a largely stable oral microbiome on an intra-day time scale. In fact, the stability of this data set enabled us to estimate potential interactions between rare bacteria, with 40 co-occurrences supported by the existing literature. In summary, the present study provides a valuable basis for studies of the human microbiome, with significant implications in terms of biological and clinical outcomes.</p></div