Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published April 18, 2016 | Supplemental Material + Published
Journal Article Open

Characterization of microbial associations with methanotrophic archaea and sulfate-reducing bacteria through statistical comparison of nested Magneto-FISH enrichments

Abstract

Methane seep systems along continental margins host diverse and dynamic microbial assemblages, sustained in large part through the microbially mediated process of sulfate-coupled Anaerobic Oxidation of Methane (AOM). This methanotrophic metabolism has been linked to consortia of anaerobic methane-oxidizing archaea (ANME) and sulfate-reducing bacteria (SRB). These two groups are the focus of numerous studies; however, less is known about the wide diversity of other seep associated microorganisms. We selected a hierarchical set of FISH probes targeting a range of Deltaproteobacteria diversity. Using the Magneto-FISH enrichment technique, we then magnetically captured CARD-FISH hybridized cells and their physically associated microorganisms from a methane seep sediment incubation. DNA from nested Magneto-FISH experiments was analyzed using Illumina tag 16S rRNA gene sequencing (iTag). Enrichment success and potential bias with iTag was evaluated in the context of full-length 16S rRNA gene clone libraries, CARD-FISH, functional gene clone libraries, and iTag mock communities. We determined commonly used Earth Microbiome Project (EMP) iTAG primers introduced bias in some common methane seep microbial taxa that reduced the ability to directly compare OTU relative abundances within a sample, but comparison of relative abundances between samples (in nearly all cases) and whole community-based analyses were robust. The iTag dataset was subjected to statistical co-occurrence measures of the most abundant OTUs to determine which taxa in this dataset were most correlated across all samples. Many non-canonical microbial partnerships were statistically significant in our co-occurrence network analysis, most of which were not recovered with conventional clone library sequencing, demonstrating the utility of combining Magneto-FISH and iTag sequencing methods for hypothesis generation of associations within complex microbial communities. Network analysis pointed to many co-occurrences containing putatively heterotrophic, candidate phyla such as OD1, Atribacteria, MBG-B, and Hyd24-12 and the potential for complex sulfur cycling involving Epsilon-, Delta-, and Gammaproteobacteria in methane seep ecosystems.

Additional Information

© 2016 Trembath-Reichert et al. Distributed under Creative Commons CC-BY 4.0. Submitted 12 January 2016; Accepted 18 March 2016; Published 18 April 2016. We thank the crew of the R/V Atlantis and DSV JASON II, as well as Abigail Green-Saxena and Joshua Steele for assistance with optimization of the Magneto-FISH protocol and Stephanie Connon for assistance with sequencing. We also are grateful to Katherine Dawson, Emil Ruff, and two anonymous reviewers for providing comments on this manuscript. Funding: This research is funded by the Department of Energy, Office of Science, Office of Biological and Environmental Research (DE-SC0003940) and the Gordon and Betty Moore Foundation through Grant GBMF 3780 (both to VJO). ETR was supported by a NIH/NRSA Training Grant (5 T32 GM07616). Funding for DHC was provided in part by an NSF Graduate Research Fellowship. Samples were collected with funding from the National Science Foundation (BIO-OCE 0825791; to VJO). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Author Contributions: Elizabeth Trembath-Reichert conceived and designed the experiments, performed the experiments, analyzed the data, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper. David H. Case conceived and designed the experiments, performed the experiments, reviewed drafts of the paper. Victoria J. Orphan contributed reagents/materials/analysis tools, designed the experiments, reviewed drafts of the paper. Data availability: The following information was supplied regarding data availability: GenBank sequences: AprA ( KT280505– KT280517), DsrA ( KT280518– KT280533), McrA ( KT280534– KT280581), Archaeal 16S rRNA ( KT280582– KT280632), Bacterial 16S rRNA ( KT280633– KT280909), SoxB ( KT280910– KT280928) SRA: accession SAMN03879962, BioSample: SAMN03879962, Sample name: PC47 (5133–5137) mixed slurry. The authors declare there are no competing interests.

Attached Files

Published - peerj-1913.pdf

Supplemental Material - SupFig1_methods.pdf

Supplemental Material - SupTable1_DNA_seqs.docx

Supplemental Material - SupTable2_MockComm.docx

Supplemental Material - SupTable3_SeqProc.docx

Supplemental Material - SupTable4_errorrates.docx

Supplemental Material - SupTable5_networkoccr.docx

Supplemental Material - supFig2_all.pdf

Files

peerj-1913.pdf
Files (17.4 MB)
Name Size Download all
md5:ac4bddad1e97931a23d70929b8a63310
9.5 MB Preview Download
md5:99f5d100fef16a3d1b0e5f4d10d822a2
12.4 kB Download
md5:b53105742275355b21ceeec271390c76
7.1 MB Preview Download
md5:daeda5b5ec0d8da6b8404c647104d094
120.4 kB Download
md5:642c2b78a202b58327d0bc1d6126074a
43.6 kB Download
md5:57812094eb268d00f59cb857494c3f44
100.1 kB Download
md5:53ebe5fa45c11f5080971c0f9ea540bf
372.9 kB Preview Download
md5:3bcea661c0a7a20a4ebad66b383c6054
79.3 kB Download

Additional details

Created:
August 20, 2023
Modified:
October 23, 2023