Evidence map›Paper›PMID 31635933›Full record

Trial reportAnnals of epidemiology2019

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

Kathryn J Ray, Sun Y Cotter, Ahmed M Arzika, Jessica Kim, Nameywa Boubacar, Zhaoxia Zhou, Lina Zhong, Travis C Porco, Jeremy D Keenan, Thomas M Lietman and 1 more

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Annals of epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Trial
  4. Article
  5. Microbiota variation inMicrobiology spectrum · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Wastewater Metavirome Diversity: Exploring Replicate Inconsistencies and Bioinformatic Tool Disparities.International journal of environmental research and public health · 2025
    Article
  14. Article
  15. Preliminary profile of the gut microbiota from amerindians in the Brazilian amazon experiencing a process of transition to urbanization.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2024
    Article
  16. Article
  17. Article
  18. Article
  19. Therapeutic Effects ofMicroorganisms · 2023
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Kathryn J RayFrancis I. Proctor Foundation, San Francisco; UCSF Epidemiology and Biostatistics, University of California, San Francisco.
Sun Y CotterFrancis I. Proctor Foundation, San Francisco.
Ahmed M ArzikaThe Carter Center Niger, Republique du Niger, Niger.
Jessica KimFrancis I. Proctor Foundation, San Francisco.
Nameywa BoubacarThe Carter Center Niger, Republique du Niger, Niger.
Zhaoxia ZhouFrancis I. Proctor Foundation, San Francisco.
Lina ZhongFrancis I. Proctor Foundation, San Francisco.
Travis C PorcoFrancis I. Proctor Foundation, San Francisco.
Jeremy D KeenanFrancis I. Proctor Foundation, San Francisco; UCSF Epidemiology and Biostatistics, University of California, San Francisco; UCSF Department of Ophthalmology, University of California, San Francisco.
Thomas M LietmanFrancis I. Proctor Foundation, San Francisco; UCSF Epidemiology and Biostatistics, University of California, San Francisco; UCSF Department of Ophthalmology, University of California, San Francisco.
Thuy DoanFrancis I. Proctor Foundation, San Francisco; UCSF Department of Ophthalmology, University of California, San Francisco. Electronic address: Thuy.Doan@ucsf.edu.

Funding

Ocular Surface Microbiome, Virome, and Pathogens in Ophthalmic Disease and HealthK08EY026986 · NEI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI DOAN, THUY A · 2016 to 2020
$1.2M
NEI NIH HHS K08 EY026986
6 · The paper itself

Abstract

purposeCommunity-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.

methodsWe 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.

resultsThe 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.

conclusionsPooling 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.

Indexed as

Administration, OralAnti-Bacterial AgentsAzithromycinBacteriaBiodiversityChild, PreschoolFemaleGastrointestinal MicrobiomeGastrointestinal TractHigh-Throughput Nucleotide SequencingHumansInfantInfant, NewbornMaleMetagenomicsMicrobiotaAnti-Bacterial AgentsAzithromycinPlacebosRNA, Ribosomal, 16SCluster randomized trialsCommunity-level diversityGamma diversityMicrobiome diversityPooling

Identifiers

PMID31635933
PMCPMC6996001

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.