SIPSim: A Modeling Toolkit to Predict Accuracy and Aid Design of DNA-SIP Experiments

DNA Stable isotope probing (DNA-SIP) is a powerful method that links identity to function within microbial communities. The combination of DNA-SIP with multiplexed high throughput DNA sequencing enables simultaneous mapping of assimilation dynamics for thousands of microbial taxonomic units. Hence,...

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Bibliographic Details
Published inFrontiers in microbiology Vol. 9; p. 570
Main Authors Youngblut, Nicholas D, Barnett, Samuel E, Buckley, Daniel H
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Research Foundation 28.03.2018
Frontiers Media S.A
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Summary:DNA Stable isotope probing (DNA-SIP) is a powerful method that links identity to function within microbial communities. The combination of DNA-SIP with multiplexed high throughput DNA sequencing enables simultaneous mapping of assimilation dynamics for thousands of microbial taxonomic units. Hence, high throughput sequencing enabled SIP has enormous potential to reveal patterns of carbon and nitrogen exchange within microbial food webs. There are several different methods for analyzing DNA-SIP data and despite the power of SIP experiments, it remains difficult to comprehensively evaluate method accuracy across a wide range of experimental parameters. We have developed a toolset (SIPSim) that simulates DNA-SIP data, and we use this toolset to systematically evaluate different methods for analyzing DNA-SIP data. Specifically, we employ SIPSim to evaluate the effects that key experimental parameters (e.g., level of isotopic enrichment, number of labeled taxa, relative abundance of labeled taxa, community richness, community evenness, and beta-diversity) have on the specificity, sensitivity, and balanced accuracy (defined as the product of specificity and sensitivity) of DNA-SIP analyses. Furthermore, SIPSim can predict analytical accuracy and power as a function of experimental design and community characteristics, and thus should be of great use in the design and interpretation of DNA-SIP experiments.
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SC0004486; SC0010558; SC0016364
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division
Edited by: Eoin L. Brodie, Lawrence Berkeley National Laboratory (LBNL), United States
This article was submitted to Terrestrial Microbiology, a section of the journal Frontiers in Microbiology
Reviewed by: Martin Taubert, Friedrich Schiller Universität Jena, Germany; Michael Pester, Deutsche Sammlung von Mikroorganismen und Zellkulturen (DSMZ), Germany; Ember Morrissey, West Virginia University, United States
ISSN:1664-302X
1664-302X
DOI:10.3389/fmicb.2018.00570