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. 2014 Sep 16;2:31.
doi: 10.1186/2049-2618-2-31. eCollection 2014.

16S rRNA Gene Pyrosequencing of Reference and Clinical Samples and Investigation of the Temperature Stability of Microbiome Profiles

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Free PMC article

16S rRNA Gene Pyrosequencing of Reference and Clinical Samples and Investigation of the Temperature Stability of Microbiome Profiles

Jun Hang et al. Microbiome. .
Free PMC article

Abstract

Background: Sample storage conditions, extraction methods, PCR primers, and parameters are major factors that affect metagenomics analysis based on microbial 16S rRNA gene sequencing. Most published studies were limited to the comparison of only one or two types of these factors. Systematic multi-factor explorations are needed to evaluate the conditions that may impact validity of a microbiome analysis. This study was aimed to improve methodological options to facilitate the best technical approaches in the design of a microbiome study. Three readily available mock bacterial community materials and two commercial extraction techniques, Qiagen DNeasy and MO BIO PowerSoil DNA purification methods, were used to assess procedures for 16S ribosomal DNA amplification and pyrosequencing-based analysis. Primers were chosen for 16S rDNA quantitative PCR and amplification of region V3 to V1. Swabs spiked with mock bacterial community cells and clinical oropharyngeal swabs were incubated at respective temperatures of -80°C, -20°C, 4°C, and 37°C for 4 weeks, then extracted with the two methods, and subjected to pyrosequencing and taxonomic and statistical analyses to investigate microbiome profile stability.

Results: The bacterial compositions for the mock community DNA samples determined in this study were consistent with the projected levels and agreed with the literature. The quantitation accuracy of abundances for several genera was improved with changes made to the standard Human Microbiome Project (HMP) procedure. The data for the samples purified with DNeasy and PowerSoil methods were statistically distinct; however, both results were reproducible and in good agreement with each other. The temperature effect on storage stability was investigated by using mock community cells and showed that the microbial community profiles were altered with the increase in incubation temperature. However, this phenomenon was not detected when clinical oropharyngeal swabs were used in the experiment.

Conclusions: Mock community materials originated from the HMP study are valuable controls in developing 16S metagenomics analysis procedures. Long-term exposure to a high temperature may introduce variation into analysis for oropharyngeal swabs, suggestive of storage at 4°C or lower. The observed variations due to sample storage temperature are in a similar range as the intrapersonal variability among different clinical oropharyngeal swab samples.

Figures

Figure 1
Figure 1
Microbial mock community reference materials from BEI Resources used in the study to evaluate laboratory and data analysis procedures. The sample information was referred from product information sheets or certificates of analysis for the materials. (1) A cell mixture of 22 different bacterial species was made to contain 1 × 108 colony-forming units/ml (cfu/ml) of each species. (2) A mixture of genomic DNA from 21 different bacterial species. Individual DNA extracts were quantified by using Qubit Fluorometer and mixed based on the genome size and the copy number of 16S ribosomal RNA genes in each genome to have equal-molar 16S rDNA copies for each species. (3) A mixture of genomic DNA from 21 different bacterial species containing unequal-molar 16S rRNA genes for each species. Individual DNA concentrations were determined by Qubit Fluorometer. Species with relative abundance (16S rDNA copy) of approximate 20%, 2%, 0.2%, and 0.02% were indicated by shading in blue, orange, gray, and green, respectively. (4) Gram-negative and Gram-positive bacteria are shown in black and blue fonts, respectively.
Figure 2
Figure 2
Oligonucleotides used in the study. The nucleotide positions for the primers and probe were numbered corresponding to the 1,542-bp 16S rRNA gene (rrnA) for Escherichia coli str. K-12 substr. MG1655 (NC_000913, nucleotide 4035531 to 4037072). Degenerate nucleotides are shown in bold, Y for C or T, M for A or C. Sequences in blue, 454 sequencing system primers A or B. Sequences in red, 454 sequencing key for amplicon sequencing. The underlined sequence is the barcode, for which 454 Rapid Library Multiplex Identifiers (RLMIDs) was used. RL1 is shown as an example.
Figure 3
Figure 3
Workflow for data analysis of the respiratory microbiome. QIIME-based analysis is performed in three steps: (1) pre-processing, (2) taxonomy classification, and (3) computation of diversity and visualization. Further statistical analysis of the data is performed in R programming environment.
Figure 4
Figure 4
Normalization of PCR amplification by choosing PCR cycle number close to the Ct value. Throat swabs from healthy volunteers were extracted with Qiagen DNeasy (D) or MO BIO PowerSoil (M). DNA extracts were subjected to 16S gene TaqMan qPCR and subsequent PCR using a cycle number of 20, 25, or 30 based on individual sample's qPCR Ct value. PCR amplicons were quantified by PicoGreen dsDNA assay. DNA concentrations for DNA extracts (blue markers and axis) and PCR amplicons (red markers and axis) are shown in 16S gene copies/μl in the same scale. DNA sample name, 08S1M as an example, depicts the subject number (08), swab number (S1), and extraction method (M).
Figure 5
Figure 5
Relative bacterial abundance determined by OTU from 454 pyrosequencing analysis. HM-278D and HM-279D were amplified by PCR for 20 cycles, respectively. Data for mock community DNA equal-molar mix used in HMP studies (HMP-MC) were from the HMP Data Analysis and Coordination Center (DACC) and NCBI. All data were analyzed using the QIIME-based pipeline, with classification of operational taxonomic units (OTUs) to bacterial genus level. Left panel, mock community DNA equal-molar mix. Right panel, mock community DNA staggered-molar mix. Projected, the relative bacterial abundance calculated based on DNA quantities used in making the HM-278D and HM-279D.
Figure 6
Figure 6
Storage temperature comparisons for Qiagen DNeasy and MO BIO PowerSoil DNA extraction methods for the mock bacterial community HM-280. Identical samples from the mock community were stored at four different temperatures and extracted after 4 weeks using the two methods, Qiagen DNeasy and MO BIO PowerSoil. Microbial profiles at the genus level were estimated using QIIME. Overall, samples were well preserved at lower temperatures for both methods, whereas significant differences were observed at 37°C.
Figure 7
Figure 7
Diversity of microbiome profiles with storage temperatures and extraction methods for the mock bacterial community HM-280. The principal coordinate analysis is based on the weighted UniFrac distances between the microbiome profiles. Equal aliquots of the mock bacterial community were stored for 4 weeks at four different temperatures, extracted by two methods, and amplified in three PCR replicates. Each coordinate axis explains the specified percent of the total community variability.
Figure 8
Figure 8
Variability of oropharyngeal microbiome profiles with storage temperatures. (A) Variability of oropharyngeal microbiome profiles with storage temperatures for the MO BIO PowerSoil extraction method. Four specimens were collected from each subject and stored for 4 weeks at different temperatures. Microbiome profiles at the genus level were estimated using QIIME. The figure presents the principal coordinate analysis based on the weighted UniFrac distances between these microbiome profiles. Each coordinate axis explains the specified percent of the total community variability. (B) Variability of oropharyngeal microbiome profiles with storage temperatures for the Qiagen DNeasy extraction method. Four specimens were collected from each subject and stored for four weeks at different temperatures. Microbiome profiles at the genus level were estimated using QIIME. The figure presents the principal coordinate analysis based on the weighted UniFrac distances between these microbiome profiles. Each coordinate axis explains the specified percent of the total community variability.

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References

    1. Blaser M, Bork P, Fraser C, Knight R, Wang J. The microbiome explored: recent insights and future challenges. Nat Rev Microbiol. 2013;11(3):213–217. doi: 10.1038/nrmicro2973. - DOI - PubMed
    1. Caporaso JG, Lauber CL, Costello EK, Berg-Lyons D, Gonzalez A, Stombaugh J, Knights D, Gajer P, Ravel J, Fierer N, Gordon JI, Knight R. Moving pictures of the human microbiome. Genome Biol. 2011;12(5):R50. doi: 10.1186/gb-2011-12-5-r50. - DOI - PMC - PubMed
    1. Costello EK, Lauber CL, Hamady M, Fierer N, Gordon JI, Knight R. Bacterial community variation in human body habitats across space and time. Science. 2009;326(5960):1694–1697. doi: 10.1126/science.1177486. - DOI - PMC - PubMed
    1. Zhou Y, Gao H, Mihindukulasuriya KA, La Rosa PS, Wylie KM, Vishnivetskaya T, Podar M, Warner B, Tarr PI, Nelson DE, Fortenberry JD, Holland MJ, Burr SE, Shannon WD, Sodergren E, Weinstock GM. Biogeography of the ecosystems of the healthy human body. Genome Biol. 2013;14(1):R1. doi: 10.1186/gb-2013-14-1-r1. - DOI - PMC - PubMed
    1. Human Microbiome Project C. A framework for human microbiome research. Nature. 2012;486(7402):215–221. doi: 10.1038/nature11209. - DOI - PMC - PubMed

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