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. 2016 Jul 26:9:365.
doi: 10.1186/s13104-016-2171-7.

The effect of DNA extraction methodology on gut microbiota research applications

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The effect of DNA extraction methodology on gut microbiota research applications

Konstantinos Gerasimidis et al. BMC Res Notes. .

Abstract

Background: The effect that traditional and modern DNA extraction methods have on applications to study the role of gut microbiota in health and disease is a topic of current interest. Genomic DNA was extracted from three faecal samples and one probiotic capsule using three popular methods; chaotropic (CHAO) method, phenol/chloroform (PHEC) extraction, proprietary kit (QIAG). The performance of each of these methods on DNA yield and quality, microbiota composition using quantitative PCR, deep sequencing of the 16S rRNA gene, and sequencing analysis pipeline was evaluated.

Results: The CHAO yielded the highest and the QIAG kit the lowest amount of double-stranded DNA, but the purity of isolated nucleic acids was better for the latter method. The CHAO method yielded a higher concentration of bacterial taxa per mass (g) of faeces. Sequencing coverage was higher in CHAO method but a higher proportion of the initial sequencing reads were retained for assignments to operational taxonomic unit (OTU) in the QIAG kit compared to the other methods. The QIAG kit appeared to have longer trimmed reads and shorter regions of worse quality than the other two methods. A distinct separation of α-diversity indices between different DNA extraction methods was not observed. When compositional dissimilarities between samples were explored, a strong separation was observed according to sample type. The effect of the extraction method was either marginal (Bray-Curtis distance) or none (unweighted Unifrac distance). Taxon membership and abundance in each sample was independent of the DNA extraction method used.

Conclusions: We have benchmarked several DNA extraction methods commonly used in gut microbiota research and their differences depended on the downstream applications intended for use. Caution should be paid when the intention is to pool and analyse samples or data from studies which have used different DNA extraction methods.

Keywords: 16S rRNA gene; Benchmarking; DNA extraction; Diversity; Metagenomics; PCR.

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Figures

Fig. 1
Fig. 1
Effect of DNA extraction method on double stranded DNA yield, nucleic acids quality metrics and quantitative PCR analysis. The CHAO method gave the maximum concentration of amplicons per mass (g) of faecal samples (a). While PHEC method had the highest double stranded DNA concentration (bottom left) for the probiotic capsule, the absorbance ratio 260/280 indicated that the extracted nucleic acids were of low purity (top left). Right panel (b) shows the 16S rRNA amplicon copies in qPCR analysis. ED, AB, IM correspond to the three faecal sample and VSL to the proprietary probiotic capsule ID respectively
Fig. 2
Fig. 2
Effect of DNA method on each step of typical bioinformatics analysis pipeline. The left and right columns show organisation by per method and per sample basis, respectively. In terms of the total useful reads that are mapped to OTU, QIAG kit performed better than the other two methods as roughly 50 % of the reads were mapped to OTUs during the construction stage (see Additional file 2 : Table S1 for actual read numbers and Additional file 1 : Figure S1 summary statistics). In terms of quality trimming, QIAG lost more reads than the other two methods. ED, AB, IM correspond to the three faecal sample and VSL to the proprietary probiotic capsule ID respectively
Fig. 3
Fig. 3
The effect of the DNA extraction methods on various microbial α-diversity community estimates. ED, AB, IM correspond to the three faecal sample and VSL to the proprietary probiotic capsule ID respectively
Fig. 4
Fig. 4
The effect of the DNA extraction methods on the compositional similarity using different β-diversity measures. a considers using Bray-Curtis distance based on OTU abundances alone, and b unweighted Unifrac distance. c, d are then the resulting beta diversity estimates using the BAT package. The lightest shade/smallest value in a given row/column represents the most similar sample in terms of community profile. ED, AB, IM correspond to the three faecal sample and VSL to the proprietary probiotic capsule ID respectively. Technical replicates represented by 1 and 2 in the sample names
Fig. 5
Fig. 5
Stacked barplot of 20 most abundant OTUs from each sample along with taxonomic assignment at genus level where feasible. All sample types had distinct community signatures with different kits agreeing on community members and their ordering. Note that we have collated all other OTUs together in the “Others” category. ED, AB, IM correspond to the three faecal sample and VSL to the proprietary probiotic capsule ID respectively
Fig. 6
Fig. 6
Heatmap of OTU abundances from each sample when binned at family a level using RDP classifier and when binned at species b level by blasting the sequences against NCBI database. The samples on x-axis are ordered by sample types and the colours were assigned in the log-transformed abundance scale. The OTUs were put in the “__Unknowns__” class when no taxonomic assignment was available at family or species level. ED, AB, IM correspond to the three faecal sample and VSL to the proprietary probiotic capsule ID respectively

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