Abstract:

This dataset contains molecular data on bacterial associates of corals (Antipatharia, Scleractinia, Gorgonians) including 16s tag sequencing from the northern Gulf of Mexico. With this data, we first address the question of whether Leiopathes glaberrima contains a stable and characteristic microbiome, and compare this with the microbes found in sediment and water samples from their habitat. Next, we ask whether the microbiome population differs across space and/or among color morphotypes. Community composition is measured as the relative abundances of bacterial Operational Taxonomic Unit (OTUs) in each sample.

Suggested Citation:

Iliana Baums. 2020. Bacterial Associates of Corals: 16s sequences collected in the northern Gulf of Mexico, 2010-10-22 to 2014-07-01. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/n7-634b-tk35

Purpose:

To determine if Leiopathes glaberrima has a distinctive microbiome that differs from the surrounding water and sediment.

Data Parameters and Units:

sample_name; organism (bacteria); host (host coral); isolation_source (BOEM lease block); collection_date (dd-mon-yy); depth (m) lat_lon (latitude and longitude; degree North and degree West) description; host_color (host coral color, red, white), treatment (oil, dispersant, control, oil and dispersant) colony_number (animal used across treatments) biosample_accession (NCBI SRA biosample accession number), bioproject_accession (NCBI SRA bioproject accession number); library_ID design_description (target region of 16S gene) filename1 (sequencing library name); filename2 (sequencing library name).

Methods:

Samples of Red and white Leiopathes glaberrima coral colonies were collected from 3 sites in the Gulf of Mexico-Vioska Knoll 826 (VK826), Vioska Knoll 906 (VK906) and Green Canyon 140 (GC140. Samples were preserved in RNALater. Samples of water filters and sediments were collected from 4 locations Water filters and sediment samples were collected from four locations in the Gulf of Mexico: VK906, Atwater Valley 357 (AT357), Green Canyon 234 (GC234), and Mississippi Canyon 751 (MC751). With the use of a syringe 0.5 mL fractions were extracted and fixed overnight in 1.8% formaldehyde in 1X PBS at 4°C. Samples were processed by centrifugation and resuspension in phosphate-buffered saline (PBS) followed by storage at 20 ^o^C 1:1 PBS/ethanol. the PowerSoil DNA extraction kit (MO BIO, CA USA) was used to extract DNA from coral samples, water filters, and soil samples. 16S tag sequencing was performed. The modified 27F (5’TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGAGAGTTTGATCMTGGCTCAG3’) and 355R (5’GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGCTGCCTCCCGTAGGAGT3’) primers were used to amplify the V2 region of the 16S rDNA gene (Rodriguez-Lanetty et al. 2013). The Illumina MiSeq platform was used to sequence samples. RNA was extracted and analyzed from 4 L. glaberrima colonies in order to expand the information gained through the analysis of 16S phylotypes to include bacterial genes expressed. The MicrobEnrich (ThermoFisher, MA USA) and RiboZero (Epicentre, WI USA) kits were used for the extraction and processing of 2 red and 2 white L. glaberrima colonies. Mothur was used to perform Raw DNA reads trimming, assembling, collapsing, and quality-control (Schloss et al. 2009). Other reads were sorted using Silva-NGS (Quast et al. 2013) and uncollapsed using in-house python scripts. Using the NMDS and ANOSIM functions in the R package “vegan” combined data from the Mothur files with the sequence names from the Silva-NGS output was analyzed. Using a modified pipeline Leimena et al. (2013) RNA data were analyzed. Reads that had been collapsed, clipped, trimmed, and quality-filtered using the fastx toolkit were compared to Silva and Rfam rRNA databases using SortMeRNA to remove rRNA sequences (Kopylova et al. 2012, as described in Leimena et al. 2013). Other reads were compared to the NCBI nr database using BLASTX. Bacterial reads were analyzed using the R package “DESeq” (Anders and Huber 2012) after mapping and annotation using BLAST2Go.

Instruments:

MiSeq Illumina (Illumina, CA USA) HiSeq 2000 (Illumina, CA USA) Large volume water transfer pump (McClane Labs, MA USA).

Provenance and Historical References:

Anders, S., & Huber, W. (2012). Differential expression of RNA-Seq data at the gene level–the DESeq package. Heidelberg, Germany: European Molecular Biology Laboratory (EMBL), 10, f1000research. Kopylova, E., Noé, L., & Touzet, H. (2012). SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics, 28(24), 3211–3217. doi:10.1093/bioinformatics/bts611 Leimena, M. M., Ramiro-Garcia, J., Davids, M., van den Bogert, B., Smidt, H., Smid, E. J., … Kleerebezem, M. (2013). A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets. BMC Genomics, 14(1), 530. doi:10.1186/1471-2164-14-530 Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., … Glöckner, F. O. (2012). The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Research, 41(D1), D590–D596. doi:10.1093/nar/gks1219 Rodriguez-Lanetty, M., Granados-Cifuentes, C., Barberan, A., Bellantuono, A. J., & Bastidas, C. (2013). Ecological Inferences from a deep screening of the Complex Bacterial Consortia associated with the coral, Porites astreoides. Molecular Ecology, 22(16), 4349–4362. doi:10.1111/mec.12392 Schloss, P. D., Westcott, S. L., Ryabin, T., Hall, J. R., Hartmann, M., Hollister, E. B., … Weber, C. F. (2009). Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities. Applied and Environmental Microbiology, 75(23), 7537–7541. doi:10.1128/aem.01541-09

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