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Randomized Controlled Trial
. 2019 Nov:39:63-68.
doi: 10.1016/j.annepidem.2019.09.002. Epub 2019 Sep 20.

High-throughput sequencing of pooled samples to determine community-level microbiome diversity

Kathryn J Ray  1 , Sun Y Cotter  2 , Ahmed M Arzika  3 , Jessica Kim  2 , Nameywa Boubacar  3 , Zhaoxia Zhou  2 , Lina Zhong  2 , Travis C Porco  2 , Jeremy D Keenan  4 , Thomas M Lietman  4 , Thuy Doan  5
Affiliations
Randomized Controlled Trial

High-throughput sequencing of pooled samples to determine community-level microbiome diversity

Kathryn J Ray et al. Ann Epidemiol. 2019 Nov.

Abstract

Purpose: Community-level interventions in cluster randomized controlled trials may alter the gut microbiome of individuals. The current method of estimating community diversities uses microbiome data obtained from multiple individual's specimens. Here we propose randomly pooling a number of microbiome samples from the same community into one sample before sequencing to estimate community-level microbiome diversity.

Methods: We design and analyze an experiment to compare community microbiome diversity (gamma-diversity) estimates derived from 16S rRNA gene sequencing of 1) individually sequenced specimens vs. 2) pooled specimens collected from a community. Pool sizes of 10, 20, and 40 are considered. We then compare the gamma-estimates using Pearson's correlation as well as using Bland and Altman agreement analysis for three established diversity indices including richness, Simpson's and Shannon's.

Results: The gamma-diversity estimates are highly correlated, with most being statistically significant. All correlations between all three diversity estimates are significant in the 10-pooled data. Pools comprising 40 specimens are closest to the line of agreement, but all pooled samples and individual samples fall within the 95% limits of agreement.

Conclusions: Pooling microbiome samples before DNA amplification and metagenomics sequencing to estimate community-level diversity is a viable measure to consider in population-level association research studies.

Keywords: Cluster randomized trials; Community-level diversity; Gamma diversity; Microbiome diversity; Pooling.

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Figures

Fig. 1
Fig. 1
Flow diagram.
Fig. 2
Fig. 2
(A–C): Bland and Altman plot for gamma diversity estimates using individual samples and pooled samples. The middle dotted line shows the mean difference between the estimates (expected bias). The upper and lower dotted lines show 95% limits of agreement from −1.96SD to +1.96SD.
Fig. 3
Fig. 3
PCoA plots for community or gamma diversity estimates using individual samples (triangles), pooled samples (circles). Also plotted are alpha diversity of individual samples (stars) within the community. P1-P4 are communities treated with placebo and P5-P6 are treated with antibiotics. PCoA, principal coordinates analysis.
See this image and copyright information in PMC

References

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