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Cited by 277Gut microbiota and healthGenomics and Phylogenetic StudiesMicrobial Community Ecology and Physiology

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Choice of bacterial DNA extraction method from fecal material influences community structure as evaluated by metagenomic analysis

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Wesolowska-Andersen, Agata, Bahl, Martin Iain, Carvalho, Vera, Kristiansen, Karsten, Sicheritz-Pontén, Thomas, Gupta, Ramneek, Licht, Tine Rask·2014·Microbiome
DOI 10.1186/2049-2618-2-19PMC PMC4063427
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Abstract

BACKGROUND: In recent years, studies on the human intestinal microbiota have attracted tremendous attention. Application of next generation sequencing for mapping of bacterial phylogeny and function has opened new doors to this field of research. However, little attention has been given to the effects of choice of methodology on the output resulting from such studies. RESULTS: IN THIS STUDY WE CONDUCTED A SYSTEMATIC COMPARISON OF THE DNA EXTRACTION METHODS USED BY THE TWO MAJOR COLLABORATIVE EFFORTS: The European MetaHIT and the American Human Microbiome Project (HMP). Additionally, effects of homogenizing the samples before extraction were addressed. We observed significant differences in distribution of bacterial taxa depending on the method. While eukaryotic DNA was most efficiently extracted by the MetaHIT protocol, DNA from bacteria within the Bacteroidetes phylum was most efficiently extracted by the HMP protocol. CONCLUSIONS: Whereas it is comforting that the inter-individual variation clearly exceeded the variation resulting from choice of extraction method, our data highlight the challenge of comparing data across studies applying different methodologies.

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Crossref · 10.1186/2049-2618-2-19

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Figure 1 Schematic representation of the study design. A: Comparison of the HMP and MetaHIT DNA extraction methods, and B: comparison of homogenized and scraped samples.
Figure 1 Schematic representation of the study design. A: Comparison of the HMP and MetaHIT DNA extraction methods, and B: comparison of homogenized and scraped samples.CC BY · PubMed Central
Figure 2 Summary of read mapping to known reference genome sequences of different taxonomic groups. As expected, the highest numbers of reads could be mapped to known bacterial genomes, with a slightly higher number of reads mapped with the HMP method (P = 0.0212). Despite overall low number of reads mapped to eukaryotic organism reference genomes, the differences in read counts attributed to the DNA extraction methods were highly significant, with the MetaHIT method resulting in a higher number of reads of eukaryotic origin in all cases. P-values were calculated with two-way ANOVA.
Figure 2 Summary of read mapping to known reference genome sequences of different taxonomic groups. As expected, the highest numbers of reads could be mapped to known bacterial genomes, with a slightly higher number of reads mapped with the HMP method (P = 0.0212). Despite overall low number of reads mapped to eukaryotic organism reference genomes, the differences in read counts attributed to the DNA extraction methods were highly significant, with the MetaHIT method resulting in a higher number of reads of eukaryotic origin in all cases. P-values were calculated with two-way ANOVA.CC BY · PubMed Central
Figure 3 Comparison of abundance estimations for bacterial genera with MetaHIT and HMP methods. (A) Relative abundance of the most prevalent bacterial genera with MetaHIT and HMP DNA extraction methods. The horizontal line is plotted at a value of 0.5, corresponding to equal abundance of a given genus detected by both methods. (B) Estimated abundance of the 25 most abundant bacterial genera with established taxonomy mapping shows clear differences for several genera. The most significant differences are observed for Bacteroidetes; for three out of six cases the HMP method resulted in higher numbers of reads mapped to respective species. (*:P < 0.05; **:P < 0.01; ***:P < 0.001).
Figure 3 Comparison of abundance estimations for bacterial genera with MetaHIT and HMP methods. (A) Relative abundance of the most prevalent bacterial genera with MetaHIT and HMP DNA extraction methods. The horizontal line is plotted at a value of 0.5, corresponding to equal abundance of a given genus detected by both methods. (B) Estimated abundance of the 25 most abundant bacterial genera with established taxonomy mapping shows clear differences for several genera. The most significant differences are observed for Bacteroidetes; for three out of six cases the HMP method resulted in higher numbers of reads mapped to respective species. (*:P < 0.05; **:P < 0.01; ***:P < 0.001).CC BY · PubMed Central
Figure 4 Hierarchical clustering. (A) Read counts mapped to the 25 most abundant bacterial genera for the three samples with three replicates for the two DNA extraction methods. Overall, the biggest observable difference results from between-sample variability, and regardless of the DNA extraction method used, the bacterial abundance profile can be assigned to the right individual. (B) Read counts mapped to the 25 most abundant bacterial genera for comparison of the effect of homogenizing and scraping of the samples. All the replicates were extracted from the same biological sample with the same DNA extraction method (HMP); therefore, the only source of variation comes from homogenizing or scraping of the samples before DNA extraction. As shown by the branch length in the sample clustering dendrogram, we observe higher between-replicate variability in the case of scraped samples.
Figure 4 Hierarchical clustering. (A) Read counts mapped to the 25 most abundant bacterial genera for the three samples with three replicates for the two DNA extraction methods. Overall, the biggest observable difference results from between-sample variability, and regardless of the DNA extraction method used, the bacterial abundance profile can be assigned to the right individual. (B) Read counts mapped to the 25 most abundant bacterial genera for comparison of the effect of homogenizing and scraping of the samples. All the replicates were extracted from the same biological sample with the same DNA extraction method (HMP); therefore, the only source of variation comes from homogenizing or scraping of the samples before DNA extraction. As shown by the branch length in the sample clustering dendrogram, we observe higher between-replicate variability in the case of scraped samples.CC BY · PubMed Central
Figure 5 Read mapping to the human gut microbiome reference sequence catalogues. We observe significantly higher numbers of raw sequencing reads mapping to both reference catalogs for DNA extracted with the HMP method. For both extraction methods, more reads mapped to the MetaHIT catalog, suggesting that this catalog serves as a more complete representation of the gut microbiome. (*:P < 0.05; **:P < 0.01).
Figure 5 Read mapping to the human gut microbiome reference sequence catalogues. We observe significantly higher numbers of raw sequencing reads mapping to both reference catalogs for DNA extracted with the HMP method. For both extraction methods, more reads mapped to the MetaHIT catalog, suggesting that this catalog serves as a more complete representation of the gut microbiome. (*:P < 0.05; **:P < 0.01).CC BY · PubMed Central
Figure 6 Comparison of the gene catalog for different replicates of the two DNA extraction methods. (A) For each individual a total gene catalog was created using all six replicates, resulting in total number of genes shown in the second row. The following rows show the numbers and percentage of the genes from the total gene catalog present in the gene catalogs for the individual replicates. (B) Schematic representation of the total gene catalog for one of the studied individuals, showing overlap of the genes discovered by all, some or none of the replicates with the HMP and MetaHIT methods. (C) Taxonomy annotation at the genus level for the genes specific to each method, that is, detected in all three replicates from one method, but none of the replicates from the other method. (D) Functional category annotation for the genes specific to each method.
Figure 6 Comparison of the gene catalog for different replicates of the two DNA extraction methods. (A) For each individual a total gene catalog was created using all six replicates, resulting in total number of genes shown in the second row. The following rows show the numbers and percentage of the genes from the total gene catalog present in the gene catalogs for the individual replicates. (B) Schematic representation of the total gene catalog for one of the studied individuals, showing overlap of the genes discovered by all, some or none of the replicates with the HMP and MetaHIT methods. (C) Taxonomy annotation at the genus level for the genes specific to each method, that is, detected in all three replicates from one method, but none of the replicates from the other method. (D) Functional category annotation for the genes specific to each method.CC BY · PubMed Central
Figure 7 Rarefaction curve. Rarefaction curve created for the purpose of this study and showing the number of genes from the total gene catalog that could be discovered with increasing numbers of raw sequencing reads. The rarefaction curves for each individual group together in the plot, showing much more variation in gene content between individuals than variation attributed to the DNA extraction method.
Figure 7 Rarefaction curve. Rarefaction curve created for the purpose of this study and showing the number of genes from the total gene catalog that could be discovered with increasing numbers of raw sequencing reads. The rarefaction curves for each individual group together in the plot, showing much more variation in gene content between individuals than variation attributed to the DNA extraction method.CC BY · PubMed Central

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Metadata

Authors
Wesolowska-Andersen, A., Bahl, M. I., Carvalho, V., Kristiansen, K., Sicheritz-Pontén, T., Gupta, R., & Licht, T. R.
Affiliations
  • Technical University of Denmark (DK)
  • University of Copenhagen (DK)
Corresponding author
  • Gupta, Ramneek
  • Licht, Tine Rask
ORCID
Venue
Microbiome
Publisher
Springer Science and Business Media LLC
Published
2014-06-05
Volume
2
Issue
1
Pages
19-19
ISSN
2049-2618 (ISSN-L)
DOI
10.1186/2049-2618-2-19
PMC
PMC4063427
OpenAlex
W2161919313
Cited by
277
References
28
Citations by year
2026: 19 · 2025: 19 · 2024: 15 · 2023: 19 · 2022: 17 · 2021: 31 · 2020: 26 · 2019: 23 · 2018: 29 · 2017: 32 · 2016: 30 · 2015: 15 · 2014: 1
FWCI
10.65
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Microbiome (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Technical University of Denmark, DTU Orbit (Technical University of Denmark, DTU) (submittedVersion, other-oa)
Funders
Strategic Research Council
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
  • Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
Keywords
bacterial DNA extraction, fecal microbiota, human gut microbiome, extraction method comparison, sample homogenization, Bacteroidetes, bacterial community structure, inter-study comparability

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