{{nav.loginGreeting}}
  • Get data
      • Occurrences
      • GBIF API
      • Species
      • Datasets
      • Occurrence snapshots
      • Hosted portals
      • Trends
  • How-to
    • Share data

      • Quick-start guide
      • Dataset classes
      • Data hosting
      • Standards
      • Become a publisher
      • Data quality
      • Data papers
    • Use data

      • Featured data use
      • Citation guidelines
      • GBIF citations
      • Citation widget
      • Guides and documentation
  • Tools
    • Publishing

      • IPT
      • Data validator
      • GeoPick
      • New data model
      • GRSciColl
      • Suggest a dataset
      • Metabarcoding data toolkit
    • Data access and use

      • Hosted portals
      • Scientific collections
      • Data processing
      • Derived datasets
      • rgbif
      • pygbif
      • MAXENT
      • Tools catalogue
    • GBIF labs

      • Species matching
      • Name parser
      • Sequence ID
      • Relative observation trends
      • GBIF data blog
  • Community
    • Network

      • Participant network
      • Nodes
      • Publishers
      • Network contacts
      • Community forum
      • alliance for biodiversity knowledge
    • Volunteers

      • Mentors
      • Ambassadors
      • Translators
      • Citizen scientists
    • Activities

      • Capacity development
      • Programmes & projects
      • Training and learning resources
      • Data Use Club
      • Living Atlases
  • About
    • Inside GBIF

      • What is GBIF?
      • Become a member
      • Governance
      • Strategic framework
      • Work Programme
      • Funders
      • Partnerships
      • Release notes
      • Contacts
    • News & outreach

      • News
      • Subscribe
      • Events
      • Awards
      • Science Review
      • Data use
      • Thematic communities
  • User profile

Deep sequencing of a DMSP-degrading gene (dmdA) in a coastal bacterioplankton community

Dataset homepage

Citation

MGnify (2019). Deep sequencing of a DMSP-degrading gene (dmdA) in a coastal bacterioplankton community. Sampling event dataset https://doi.org/10.15468/xwp5sj accessed via GBIF.org on 2025-05-16.

Description

Ten primer pairs targeting environmental clades of the dimethylsulfoniopropionate (DMSP) demethylase protein, DmdA, were designed using an iterative bioinformatic approach that took advantage of >1700 dmdA sequences captured in marine metagenomic datasets. Using the bioinformatically-optimized primer pairs, dmdA genes were amplified from free-living coastal bacterioplankton samples and sequenced using 454 technology. An average of 6,400 amplicons per primer pair represented almost 800 clusters of environmental dmdA sequences, with clusters defined conservatively at >90% nucleotide sequence identity (~95% protein identity). Systematic comparisons of primer performance showed that degenerate and inosine-based primers did not perform better than specific primer sets in retrieving dmdA diversity, and sometimes captured a lower diversity of sequences from the same DNA sample. The specific primer sets were used to compare dmdA diversity in free-living versus particle-associated bacteria in southeastern U.S. coastal waters. Hundreds of different dmdA clusters were found in both size fractions, with Roseobacter-like and SAR11-like sequences dominating both. The free-living fraction had a higher diversity of dmdA clusters overall, though clusters retrieved by a given primer set were largely shared (52-88%) across the two size fractions, and most sequences were affiliated with these shared clusters (~90%). Despite evidence from 16S rRNA-based taxonomic surveys that free-living bacterioplankton are a considerably less diverse subset of particle-associated bacteria at this site, this seems not to be the case for a widespread bacterial gene mediating sulfur transformations.

Sampling Description

Sampling

Ten primer pairs targeting environmental clades of the dimethylsulfoniopropionate (DMSP) demethylase protein, DmdA, were designed using an iterative bioinformatic approach that took advantage of >1700 dmdA sequences captured in marine metagenomic datasets. Using the bioinformatically-optimized primer pairs, dmdA genes were amplified from free-living coastal bacterioplankton samples and sequenced using 454 technology. An average of 6,400 amplicons per primer pair represented almost 800 clusters of environmental dmdA sequences, with clusters defined conservatively at >90% nucleotide sequence identity (~95% protein identity). Systematic comparisons of primer performance showed that degenerate and inosine-based primers did not perform better than specific primer sets in retrieving dmdA diversity, and sometimes captured a lower diversity of sequences from the same DNA sample. The specific primer sets were used to compare dmdA diversity in free-living versus particle-associated bacteria in southeastern U.S. coastal waters. Hundreds of different dmdA clusters were found in both size fractions, with Roseobacter-like and SAR11-like sequences dominating both. The free-living fraction had a higher diversity of dmdA clusters overall, though clusters retrieved by a given primer set were largely shared (52-88%) across the two size fractions, and most sequences were affiliated with these shared clusters (~90%). Despite evidence from 16S rRNA-based taxonomic surveys that free-living bacterioplankton are a considerably less diverse subset of particle-associated bacteria at this site, this seems not to be the case for a widespread bacterial gene mediating sulfur transformations.

Method steps

  1. Pipeline used: https://www.ebi.ac.uk/metagenomics/pipelines/4.1

Taxonomic Coverages

Geographic Coverages

Bibliographic Citations

Contacts

originator
University of Georgia
metadata author
University of Georgia
administrative point of contact
University of Georgia
What is GBIF? API FAQ Newsletter Privacy Terms and agreements Citation Code of Conduct Acknowledgements
Contact GBIF Secretariat Universitetsparken 15 DK-2100 Copenhagen Ø Denmark
GBIF is a Global Core Biodata Resource