Common methods for fecal sample storage in field studies yield consistent signatures of individual identity in microbiome sequencing data

Ran Blekhman, Karen Tang, Elizabeth A. Archie, Luis B. Barreiro, Zachary P. Johnson, Mark E. Wilson, Jordan Kohn, Michael L. Yuan, Laurence Gesquiere, Laura E. Grieneisen, Jenny Tung

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

Field studies of wild vertebrates are frequently associated with extensive collections of banked fecal samples - unique resources for understanding ecological, behavioral, and phylogenetic effects on the gut microbiome. However, we do not understand whether sample storage methods confound the ability to investigate interindividual variation in gut microbiome profiles. Here, we extend previous work on storage methods for gut microbiome samples by comparing immediate freezing, the gold standard of preservation, to three methods commonly used in vertebrate field studies: lyophilization, storage in ethanol, and storage in RNAlater. We found that the signature of individual identity consistently outweighed storage effects: alpha diversity and beta diversity measures were significantly correlated across methods, and while samples often clustered by donor, they never clustered by storage method. Provided that all analyzed samples are stored the same way, banked fecal samples therefore appear highly suitable for investigating variation in gut microbiota. Our results open the door to a much-expanded perspective on variation in the gut microbiome across species and ecological contexts.

Original languageEnglish (US)
Article number31519
JournalScientific reports
Volume6
DOIs
StatePublished - Aug 16 2016

Bibliographical note

Funding Information:
We gratefully acknowledge support from the National Science Foundation (IOS 1053461 to E.A.A.), National Institutes of Health (R01-GM102562 to J.T., L.B.B., and M.E.W. and 2-P2CHD065563-06 to Seth Sanders), and the Clare Boothe Luce Foundation (E.A.A.). We thank A. Tripp, J. Whitley, and J. Johnson for their support in collecting samples, M. Gearhart for assistance with computational analysis, members of the Blekhman lab for helpful discussions, and K. Amato for constructive comments on a previous version of this manuscript. This work was carried out using computing resources at the Minnesota Supercomputing Institute.

Publisher Copyright:
© The Author(s) 2016.

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