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Quantitative microbial ecology through stable isotope probing

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1 Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, United States
2 Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, United States
3 Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA
4 School of Medicine, Department of Pathology, The Johns Hopkins University, Baltimore, MD, United States
5 Pathogen Genomics Division, Center for Microbiomics and Human Health, Translational Genomics Research Center, Flagstaff, AZ, USA
6 Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, United States
7 Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC, United States
8 Pathogen Genomics Division, Center for Food Microbiology and Environmental Health, Translational Genomics Institute, Flagstaff, AZ, USA
DOI
10.7287/peerj.preprints.1282v1
Published
Accepted
Subject Areas
Ecology, Ecosystem Science, Microbiology, Molecular Biology
Keywords
stable isotope probing, oxygen-18, biodiversity, 18O-H2O, soil carbon cycle, ecosystem functioning, microbial ecology
Copyright
© 2015 Hungate et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Hungate BA, Mau RL, Schwartz E, Caporaso JG, Dijkstra P, van Gestel N, Koch BJ, Liu CM, McHugh TA, Marks JC, Morrissey EM, Price LB. 2015. Quantitative microbial ecology through stable isotope probing. PeerJ PrePrints 3:e1282v1

Abstract

Bacteria grow and transform elements at different rates, yet quantifying this variation in the environment is difficult. Determining isotope enrichment with fine taxonomic resolution after exposure to isotope tracers could help, but there are few suitable techniques. We propose a modification to Stable Isotope Probing (SIP) that enables determining the isotopic composition of DNA from individual bacterial taxa after exposure to isotope tracers. In our modification, after isopycnic centrifugation, DNA is collected in multiple density fractions, and each fraction is sequenced separately. Taxon specific density curves are produced for labeled and non-labeled treatments, from which the shift in density for each individual taxon in response to isotope labeling is calculated. Expressing each taxon’s density shift relative to that taxon’s density measured without isotope enrichment accounts for the influence of nucleic acid composition on density and isolates the influence of isotope tracer assimilation. The shift in density translates quantitatively to isotopic enrichment. Because this revision to SIP allows quantitative measurements of isotope enrichment, we propose to call it quantitative Stable Isotope Probing (qSIP). We demonstrate qSIP using soil incubations, in which soil bacteria exhibited strong taxonomic variation in 18O and 13C composition after exposure to 18O-H2O or 13C-glucose. Addition of glucose increased assimilation of 18O into DNA from 18O-H2O. However, the increase in 18O assimilation was greater than expected based on utilization of glucose-derived carbon alone, because glucose addition indirectly stimulated bacteria to utilize other substrates for growth. This example illustrates the benefit of a quantitative approach to stable isotope probing.

Author Comment

This manuscript is under review in the journal, Applied and Environmental Microbiology.

Supplemental Information

QIIME code for bioinformatics and statistical results from the bioinformatics procedures

This file contains the code used in QIIME to analyze the sequencing data, including all steps used in that analysis. This file also contains a table (Table S1), which summarizes results from the bioinformatics statistics.

DOI: 10.7287/peerj.preprints.1282v1/supp-1

Additional Information

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

Bruce A Hungate conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Rebecca L Mau conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Egbert Schwartz conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

J Gregory Caporaso conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Paul Dijkstra conceived and designed the experiments, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Natasja van Gestel conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Benjamin J Koch conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Cindy M Liu conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Theresa A McHugh conceived and designed the experiments, performed the experiments, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Jane C Marks conceived and designed the experiments, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Ember M Morrissey conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Lance B Price conceived and designed the experiments, wrote the paper, reviewed drafts of the paper.

DNA Deposition

The following information was supplied regarding the deposition of DNA sequences:

The sequencing data are deposited at MG-RAST. The project ID is 14151.

The website of the archive is https://metagenomics.anl.gov/

The citation describing the resource is:

Meyer F, Paarmann D, D'Souza M, Olson R, Glass EM, Kubal M, Paczian T, Rodriguez A, Stevens R, Wilke A, Wilkening J, Edwards RA. 2008. The metagenomics RAST server - a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9:386.

Data Deposition

The following information was supplied regarding the deposition of related data:

A table with raw qPCR data will be published with the final manuscript. A supplementary file with the code used to process sequencing data will also be published with the final manuscript.

Funding

This research was supported by grants from the National Science Foundation (EAR-1124078 and DEB-1321792) and the Department of Energy’s Biological Systems Science Division, Program in Genomic Science. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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