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

Youngblut, Nicholas D.; Barnett, Samuel E.; Buckley, Daniel H.

doi:10.3389/fmicb.2018.00570

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

Journal Article · Wed Mar 28 00:00:00 EDT 2018 · Frontiers in Microbiology

DOI:https://doi.org/10.3389/fmicb.2018.00570· OSTI ID:1510497

Youngblut, Nicholas D. ^[1]; Barnett, Samuel E. ^[1]; Buckley, Daniel H. ^[1]

Cornell Univ., Ithaca, NY (United States)

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 in situ 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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Research Organization:: Cornell Univ., Ithaca, NY (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division

Grant/Contract Number:: SC0004486; SC0010558; SC0016364

OSTI ID:: 1510497

Alternate ID(s):: OSTI ID: 1864327

Journal Information:: Frontiers in Microbiology, Vol. 9; ISSN 1664-302X

Publisher:: Frontiers Research FoundationCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 29 works

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59 BASIC BIOLOGICAL SCIENCES
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method
microbial
community
function
SIPSim

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

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