A Quantitative Sequencing Framework for Absolute Abundance Measurements of Mucosal and Lumenal Microbial Communities
Abstract
A fundamental goal in microbiome studies is determining which microbes affect host physiology. Standard methods for determining changes in microbial taxa measure relative, rather than absolute abundances. Moreover, studies often analyze only stool, despite microbial diversity differing substantially among gastrointestinal (GI) locations. Here, we develop a quantitative framework to measure absolute abundances of individual bacterial taxa by combining the precision of digital PCR with the high-throughput nature of 16S rRNA gene amplicon sequencing. In a murine ketogenic-diet study, we compare microbial loads in lumenal and mucosal samples along the GI tract. Quantitative measurements of absolute (but not relative) abundances reveal decreases in total microbial loads on the ketogenic diet and enable us to determine the differential effects of diet on each taxon in stool and small-intestine mucosa samples. This rigorous quantitative microbial analysis framework, appropriate for diverse GI locations enables mapping microbial biogeography of the mammalian GI tract and more accurate analyses of changes in microbial taxa in microbiome studies.
Additional Information
© The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Received 15 March 2020; Accepted 20 April 2020; Published 22 May 2020. This work was supported in part by the Kenneth Rainin Foundation (2018–1207), the Army Research Office (ARO) Multidisciplinary University Research Initiative (MURI #W911NF-17-1-0402), and a National Institutes of Health Biotechnology Leadership Pre-doctoral Training Program (BLP) fellowship from Caltech's Donna and Benjamin M. Rosen Bioengineering Center (T32GM112592, to J.T.B.). We thank Elaine Hsiao and Christine Olson for helpful discussions and input on the experimental design and diets; we thank the Caltech Bioinformatics Resource Center for assistance with statistical analyses; we acknowledge the Caltech animal facility for experimental resources; we thank the Caltech Office of Laboratory Animal Resources and the veterinary technicians at Caltech for technical support; and Natasha Shelby for contributions to writing and editing this manuscript. Data availability: The complete sequencing data generated during this study are available in the National Center for Biotechnology Information Sequence Read Archive repository under study accession number PRJNA575097. Raw data for all figures are provided as Source data file. Author Contributions: J.T.B. validated limits of digital PCR assay with mock microbial communities in germ-free tissues; designed, performed, and analyzed experiments to validate accuracy of quantitative sequencing with dPCR anchoring; established the quantitative limits of an individual taxon's absolute abundance; conducted the ketogenic animal study; analyzed all data; created all figures; and wrote the paper. S.R.B. co-developed the idea of quantitative sequencing with dPCR anchoring for absolute quantification of total microbial loads and taxa absolute abundances in lumenal and mucosal samples; contributed the method for quantitative sequencing with dPCR anchoring in lumenal and mucosal samples; contributed ideas and provided support for animal study design; contributed ideas for data-analysis and representation. R.F.I. contributed to study design and manuscript preparation. The authors declare no competing interests.Attached Files
Published - s41467-020-16224-6.pdf
Submitted - 2020.02.28.970087v1.full.pdf
Supplemental Material - 41467_2020_16224_MOESM1_ESM.pdf
Supplemental Material - 41467_2020_16224_MOESM2_ESM.pdf
Supplemental Material - 41467_2020_16224_MOESM3_ESM.zip
Erratum - s41467-020-17055-1.pdf
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Additional details
- PMCID
- PMC7244552
- Eprint ID
- 101678
- Resolver ID
- CaltechAUTHORS:20200303-103834329
- Kenneth Rainin Foundation
- 2018-1207
- Army Research Office (ARO)
- W911NF-17-1-0402
- NIH Predoctoral Fellowship
- T32GM112592
- Created
-
2020-03-03Created from EPrint's datestamp field
- Updated
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2023-10-20Created from EPrint's last_modified field
- Caltech groups
- Rosen Bioengineering Center, Division of Biology and Biological Engineering (BBE)