Abstract

Differential abundance analysis is controversial throughout microbiome research. Gold standard approaches require laborious measurements of total microbial load, or absolute number of microorganisms, to accurately determine taxonomic shifts. Therefore, most studies rely on relative abundance data. Here, we demonstrate common pitfalls in comparing relative abundance across samples and identify two solutions that reveal microbial changes without the need to estimate total microbial load. We define the notion of “reference frames”, which provide deep intuition about the compositional nature of microbiome data. In an oral time series experiment, reference frames alleviate false positives and produce consistent results on both raw and cell-count normalized data. Furthermore, reference frames identify consistent, differentially abundant microbes previously undetected in two independent published datasets from subjects with atopic dermatitis. These methods allow reassessment of published relative abundance data to reveal reproducible microbial changes from standard sequencing output without the need for new assays.

Details

Title
Establishing microbial composition measurement standards with reference frames
Author
Morton, James T 1 ; Marotz, Clarisse 2   VIAFID ORCID Logo  ; Washburne, Alex 3 ; Silverman, Justin 4 ; Zaramela, Livia S 2   VIAFID ORCID Logo  ; Edlund, Anna 5 ; Zengler, Karsten 6   VIAFID ORCID Logo  ; Knight, Rob 7   VIAFID ORCID Logo 

1  Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA 
2  Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA 
3  Department of Microbiology and Immunology, Montana State University, Bozeman, MT, USA 
4  Program in Computational Biology and Bioinformatics, Duke University, Durham, USA; Medical Scientist Training Program, Duke University, Durham, USA; Center for Genomic and Computational Biology, Duke University, Durham, USA 
5  J. Craig Venter Institute, Genomic Medicine Group, La Jolla, CA, USA 
6  Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA; Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA 
7  Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA; Department of Computer Science & Engineering, University of California, San Diego, La Jolla, CA, USA; Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA 
Pages
1-11
Publication year
2019
Publication date
Jun 2019
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41467-019-10656-5
ProQuest document ID
2244137181
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.