Frontiers in Microbiology (Nov 2021)

Inconsistent Patterns of Microbial Diversity and Composition Between Highly Similar Sequencing Protocols: A Case Study With Reef-Building Corals

  • Hannah E. Epstein,
  • Alejandra Hernandez-Agreda,
  • Samuel Starko,
  • Julia K. Baum,
  • Rebecca Vega Thurber

DOI
https://doi.org/10.3389/fmicb.2021.740932
Journal volume & issue
Vol. 12

Abstract

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16S rRNA gene profiling (amplicon sequencing) is a popular technique for understanding host-associated and environmental microbial communities. Most protocols for sequencing amplicon libraries follow a standardized pipeline that can differ slightly depending on laboratory facility and user. Given that the same variable region of the 16S gene is targeted, it is generally accepted that sequencing output from differing protocols are comparable and this assumption underlies our ability to identify universal patterns in microbial dynamics through meta-analyses. However, discrepant results from a combined 16S rRNA gene dataset prepared by two labs whose protocols differed only in DNA polymerase and sequencing platform led us to scrutinize the outputs and challenge the idea of confidently combining them for standard microbiome analysis. Using technical replicates of reef-building coral samples from two species, Montipora aequituberculata and Porites lobata, we evaluated the consistency of alpha and beta diversity metrics between data resulting from these highly similar protocols. While we found minimal variation in alpha diversity between platform, significant differences were revealed with most beta diversity metrics, dependent on host species. These inconsistencies persisted following removal of low abundance taxa and when comparing across higher taxonomic levels, suggesting that bacterial community differences associated with sequencing protocol are likely to be context dependent and difficult to correct without extensive validation work. The results of this study encourage caution in the statistical comparison and interpretation of studies that combine rRNA gene sequence data from distinct protocols and point to a need for further work identifying mechanistic causes of these observed differences.

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