Synthetic microbe communities provide internal reference standards for metagenome sequencing and analysis

Simon A. Hardwick, Wendy Y. Chen, Ted Wong, Bindu S. Kanakamedala, Ira W. Deveson, Sarah E. Ongley, Nadia S. Santini, Esteban Marcellin, Martin A. Smith, Lars K. Nielsen, Catherine E. Lovelock, Brett A. Neilan and Tim R. Mercer ()
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Simon A. Hardwick: Garvan Institute of Medical Research
Wendy Y. Chen: Garvan Institute of Medical Research
Ted Wong: Garvan Institute of Medical Research
Bindu S. Kanakamedala: Garvan Institute of Medical Research
Ira W. Deveson: Garvan Institute of Medical Research
Sarah E. Ongley: UNSW Sydney
Nadia S. Santini: Centre for Marine Bioinnovation UNSW Sydney
Esteban Marcellin: The University of Queensland
Martin A. Smith: Garvan Institute of Medical Research
Lars K. Nielsen: The University of Queensland
Catherine E. Lovelock: The University of Queensland
Brett A. Neilan: UNSW Sydney
Tim R. Mercer: Garvan Institute of Medical Research

Nature Communications, 2018, vol. 9, issue 1, 1-10

Abstract: Abstract The complexity of microbial communities, combined with technical biases in next-generation sequencing, pose a challenge to metagenomic analysis. Here, we develop a set of internal DNA standards, termed “sequins” (sequencing spike-ins), that together constitute a synthetic community of artificial microbial genomes. Sequins are added to environmental DNA samples prior to library preparation, and undergo concurrent sequencing with the accompanying sample. We validate the performance of sequins by comparison to mock microbial communities, and demonstrate their use in the analysis of real metagenome samples. We show how sequins can be used to measure fold change differences in the size and structure of accompanying microbial communities, and perform quantitative normalization between samples. We further illustrate how sequins can be used to benchmark and optimize new methods, including nanopore long-read sequencing technology. We provide metagenome sequins, along with associated data sets, protocols, and an accompanying software toolkit, as reference standards to aid in metagenomic studies.

Date: 2018
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DOI: 10.1038/s41467-018-05555-0

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