Browsing by Subject "16S"
  • Dataset
    Cyanobacteria cultures used to generate DNA reference library from samples collected from sites in Alpena and Monroe, Michigan and Palm Coast, Florida between May and June 2022.
    (Biological and Chemical Oceanography Data Management Office (BCO-DMO). Contact: bco-dmo-data@whoi.edu, 2023-10-17) Casamatta, Dale ; Hamsher, Sarah ; Biddanda, Bopaiah
    These data are the information for each of the cultures generated from samples collected from three sites in Alpena, Michigan, one site in Monroe, Michigan, and one site in Palm Coast, Florida. Data are for cultures sequenced using Sanger sequencing and include taxonomic identification, location and sample type for samples used to develop the cultures. Each of these cultures was developed from high-sulfur, low-oxygen environments formed by underwater sinkholes and springs that create extreme habitats populated by microbial mat communities. Our study investigated previously undescribed diatom diversity in these habitats. Sequences from these cultures contribute to tying molecular data to morphologically identified isolates, providing a bridge between these two data types that can be used to improve metabarcoding analyses. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/911338
  • Article
    Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys
    (American Society for Microbiology, 2015-12-22) Walters, William ; Hyde, Embriette R. ; Berg-Lyons, Donna ; Ackermann, Gail ; Humphrey, Greg ; Parada, Alma ; Gilbert, Jack A. ; Jansson, Janet K. ; Caporaso, J. Gregory ; Fuhrman, Jed A. ; Apprill, Amy ; Knight, Rob
    Designing primers for PCR-based taxonomic surveys that amplify a broad range of phylotypes in varied community samples is a difficult challenge, and the comparability of data sets amplified with varied primers requires attention. Here, we examined the performance of modified 16S rRNA gene and internal transcribed spacer (ITS) primers for archaea/bacteria and fungi, respectively, with nonaquatic samples. We moved primer bar codes to the 5′ end, allowing for a range of different 3′ primer pairings, such as the 515f/926r primer pair, which amplifies variable regions 4 and 5 of the 16S rRNA gene. We additionally demonstrated that modifications to the 515f/806r (variable region 4) 16S primer pair, which improves detection of Thaumarchaeota and clade SAR11 in marine samples, do not degrade performance on taxa already amplified effectively by the original primer set. Alterations to the fungal ITS primers did result in differential but overall improved performance compared to the original primers. In both cases, the improved primers should be widely adopted for amplicon studies.
  • Article
    Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton
    (Inter-Research, 2015-06-04) Apprill, Amy ; McNally, Sean ; Parsons, Rachel ; Weber, Laura
    High-throughput sequencing of small subunit ribosomal RNA (SSU rRNA) genes from marine environments is a widely applied method used to uncover the composition of microbial communities. We conducted an analysis of surface ocean waters with the commonly employed hypervariable 4 region SSU rRNA gene primers 515F and 806R, and found that bacteria belonging to the SAR11 clade of Alphaproteobacteria, a group typically making up 20 to 40% of the bacterioplankton in this environment, were greatly underrepresented and comprised <4% of the total community. Using the SILVA reference database, we found a single nucleotide mismatch to nearly all SAR11 subclades, and revised the 806R primer so that it increased the detection of SAR11 clade sequences in the database from 2.6 to 96.7%. We then compared the performance of the original and revised 806R primers in surface seawater samples, and found that SAR11 comprised 0.3 to 3.9% of sequences with the original primers and 17.5 to 30.5% of the sequences with the revised 806R primer. Furthermore, an investigation of seawater obtained from aquaria revealed that SAR11 sequences acquired with the revised 806R primer were more similar to natural cellular abundances of SAR11 detected using fluorescence in situ hybridization counts. Collectively, these results demonstrate that a minor adjustment to the 806R primer will greatly increase detection of the globally abundant SAR11 clade in marine and lake environments, and enable inclusion of this important bacterial lineage in experimental and environmental-based studies.
  • Article
    Oligotyping : differentiating between closely related microbial taxa using 16S rRNA gene data
    (John Wiley & Sons, 2013-10-23) Eren, A. Murat ; Maignien, Lois ; Sul, Woo Jun ; Murphy, Leslie G. ; Grim, Sharon L. ; Morrison, Hilary G. ; Sogin, Mitchell L.
    Bacteria comprise the most diverse domain of life on Earth, where they occupy nearly every possible ecological niche and play key roles in biological and chemical processes. Studying the composition and ecology of bacterial ecosystems and understanding their function are of prime importance. High-throughput sequencing technologies enable nearly comprehensive descriptions of bacterial diversity through 16S ribosomal RNA gene amplicons. Analyses of these communities generally rely upon taxonomic assignments through reference data bases or clustering approaches using de facto sequence similarity thresholds to identify operational taxonomic units. However, these methods often fail to resolve ecologically meaningful differences between closely related organisms in complex microbial data sets. In this paper, we describe oligotyping, a novel supervised computational method that allows researchers to investigate the diversity of closely related but distinct bacterial organisms in final operational taxonomic units identified in environmental data sets through 16S ribosomal RNA gene data by the canonical approaches. Our analysis of two data sets from two different environments demonstrates the capacity of oligotyping at discriminating distinct microbial populations of ecological importance. Oligotyping can resolve the distribution of closely related organisms across environments and unveil previously overlooked ecological patterns for microbial communities. The URL http://oligotyping.org offers an open-source software pipeline for oligotyping.