Prokaryotic Communities Shed by Diseased and Healthy Corals (Diploria labyrinthiformis, Pseudodiploria strigosa, Montastraea cavernosa, Colpophyllia natans, and Orbicella faveolata) into Filtered Seawater Mesocosms – Raw and Processed Data

Metadata also available as - [Outline] - [Parseable text] - [XML]

Frequently anticipated questions:

What does this data set describe?

Title:
Prokaryotic Communities Shed by Diseased and Healthy Corals (Diploria labyrinthiformis, Pseudodiploria strigosa, Montastraea cavernosa, Colpophyllia natans, and Orbicella faveolata) into Filtered Seawater Mesocosms – Raw and Processed Data
Abstract:
The files in this data release (Kellogg and others, 2023) are those referenced in the journal article by Evans and others (2023) entitled “Investigating microbial size classes associated with the transmission of stony coral tissue loss disease (SCTLD).” They contain an amplicon sequence variant (ASV) table and the raw 16S rRNA gene amplicon files from fifty-six 0.22-micrometer (µm) pore size filters, as well as six reagent blanks, three mock communities, and a 0.22-µm-filtered ultraviolet (UV)-treated seawater (FSW) control. The 0.22 µm pore size filters contained tangential flow filtration (TFF) concentrated microbial communities derived from bucket mesocosms consisting of approximately 18 liters (L) of UV-treated FSW in which either healthy or diseased corals (Diploria labyrinthiformis, Pseudodiploria strigosa, Montastraea cavernosa, Colpophyllia natans, and Orbicella faveolata) had been incubated, and a FSW control. Colonies and fragments of apparently healthy corals were collected from Florida reefs or nurseries between April 2018 and September 2020 and transported to the Smithsonian Marine Station (SMS) in Fort Pierce, Florida. These samples were transferred to indoor, temperature-controlled water tables containing FSW and maintained along with other corals as part of the SMS long-term healthy coral stock. Corals exhibiting signs consistent with stony coral tissue loss disease (SCTLD) were collected from the reef immediately prior to each experimental run (Run 1 – October 2019, Run 2 – November 2020, and Run 3 – March 2021), and transported to SMS to be placed in individual mesocosms with weighted air lines. Apparently healthy corals of the same or similar species (i.e., same genus or family) were simultaneously transferred from the SMS healthy stock tanks into identical individual mesocosms. All mesocosms were housed within outdoor water tables containing recirculating freshwater maintained at approximately 28 degrees Celsius (°C) and located under a mesh canopy to allow some sunlight attenuation. Separate “healthy” and “diseased” water tables were maintained to prevent cross-contamination between the different mesocosm types. All corals were incubated within the mesocosms for 2-5 days to enrich the water with microbes. Following the incubation period, the corals were removed from their mesocosms, and the seawater was poured through a sterilized mesh screen (200 µm for Run 1, and 106 µm for Runs 2 and 3). The water was TFF-concentrated, then sequentially passed through a sterile 0.8 µm pore size nitrocellulose filter unit (Runs 2 and 3) and a sterile 0.22 µm pore size nitrocellulose filter unit (all three runs). The 0.22 µm pore size filters were then cut from the units using ethanol-sterilized blades, with portions frozen at -20°C for later processing. Extraction of deoxyribonucleic acid (DNA) from the samples and blanks occurred between February and May 2021 at the U.S. Geological Survey St. Petersburg Coastal and Marine Science Center (USGS SPCMSC) Coral Microbial Ecology Laboratory in St. Petersburg, FL, USA using Qiagen DNeasy PowerBiofilm kits. Library preparation and DNA sequencing were conducted on July 28th, 2021 by the Michigan State University RTSF Genomics Core (East Lansing, MI) using primers 515F: GTGCCAGCMGCCGCGGTAA and 806R: GGACTACHVGGGTWTCTAAT to target the V4 variable region of the 16S ribosomal ribonucleic acid (rRNA) gene on a MiSeq sequencing system with v2 chemistry to obtain paired-end 250-base pair (bp) reads.
Supplemental_Information:
The raw data files associated with this data release have also been submitted to the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) under Bioproject number PRJNA918331.
  1. How might this data set be cited?
    Kellogg, Christina A., Evans, James S., and Voelschow, Julie J., 20230801, Prokaryotic Communities Shed by Diseased and Healthy Corals (Diploria labyrinthiformis, Pseudodiploria strigosa, Montastraea cavernosa, Colpophyllia natans, and Orbicella faveolata) into Filtered Seawater Mesocosms – Raw and Processed Data:.

    This is part of the following larger work.

    Kellogg, Christina A., Evans, James S., and Voelschow, Julie J., 20230801, Prokaryotic Communities Shed by Diseased and Healthy Coral (Diploria labyrinthiformis, Pseudodiploria strigosa, Montastraea cavernosa, Colpophyllia natans, and Orbicella faveolata) into Filtered Seawater Mesocosms - Raw and Processed Data: U.S. Geological Survey data release doi:10.5066/P9LRIX9E, U.S. Geological Survey - St. Petersburg Coastal and Marine Science Center, St. Petersburg, Florida.

    Online Links:

  2. What geographic area does the data set cover?
    West_Bounding_Coordinate: -84.474
    East_Bounding_Coordinate: -80.3106
    North_Bounding_Coordinate: 42.7228
    South_Bounding_Coordinate: 27.45956
    Description_of_Geographic_Extent: Florida, Michigan
  3. What does it look like?
  4. Does the data set describe conditions during a particular time period?
    Beginning_Date: Apr-2018
    Ending_Date: 06-May-2022
    Currentness_Reference:
    ground condition
  5. What is the general form of this data set?
    Geospatial_Data_Presentation_Form: FASTQ and tabular digital data
  6. How does the data set represent geographic features?
    1. How are geographic features stored in the data set?
    2. What coordinate system is used to represent geographic features?
  7. How does the data set describe geographic features?
    Entity_and_Attribute_Overview:
    Please refer to the "README" file, README_SCTLD_FullFilterSet.txt, for detailed descriptions of the contents of the raw, processed and ASV data files. Additional information is contained in the minimum information about a marker sequence (MIMARKS) compliant metadata (SCTLD_FullFilterSet_MIMARKS), as well as the SRA metadata (SCTLD_FullFilterSet_SRA_metadata). The MIMARKS and SRA metadata files are available for download in the Supplemental Information section of the data release webpage (doi:10.5066/P9LRIX9E).
    Entity_and_Attribute_Detail_Citation:
    The entity and attribute information were generated by the individual and/or agency identified as the originator of the dataset. Please review the rest of the metadata record for additional details and information.

Who produced the data set?

  1. Who are the originators of the data set? (may include formal authors, digital compilers, and editors)
    • Christina A. Kellogg
    • James S. Evans
    • Julie J. Voelschow
  2. Who also contributed to the data set?
  3. To whom should users address questions about the data?
    Christina A. Kellogg
    U.S. Geological Survey
    Research Microbiologist
    600 4th St. South
    St. Petersburg, Florida
    United States

    727-502-8128 (voice)
    ckellogg@usgs.gov

Why was the data set created?

The purpose of this experiment was to investigate the size class of microorganism(s) associated with SCTLD transmission. This dataset represents the prokaryotic community shed by SCTLD-diseased and apparently healthy coral (Diploria labyrinthiformis, Pseudodiploria strigosa, Montastraea cavernosa, Colpophyllia natans, and Orbicella faveolata) into mesocosms as part of this study.

How was the data set created?

  1. From what previous works were the data drawn?
    (Becker and others, 2021) (source 1 of 1)
    Becker, Cynthia C., Brandt, Marilyn, Miller, Carolyn A., and Apprill, Amy, 20210825, Microbial bioindicators of Stony Coral Tissue Loss Disease identified in corals and overlying waters using a rapid field-based sequencing approach: Environmental Microbiology Volume 24(3).

    Online Links:

    Type_of_Source_Media: SCTLD bioindicator ASVs
    Source_Contribution:
    Compare SCTLD bioindicator ASVs to identify 100% sequence identity matches between Becker and others (2021) and this data release.
  2. How were the data generated, processed, and modified?
    Date: 01-Sep-2020 (process 1 of 10)
    Healthy coral collection: Healthy corals used to create these samples were collected from various reefs and nurseries throughout Florida between April 2018 and September 2020 and were maintained in indoor temperature-controlled water tables containing UV-treated and 0.22 µm-filtered seawater at the SMS.
    Date: 22-Mar-2021 (process 2 of 10)
    SCTLD coral collection: Immediately prior to each of the three experimental runs (Run 1 was conducted in October 2019, Run 2 was conducted in November 2020, and Run 3 was conducted in March 2021), fragments of SCTLD-symptomatic corals were collected by divers from Florida reefs, transported to SMS, and transferred directly into individual mesocosm buckets containing ~18 L of the UV-treated FSW and a weighted air line for water circulation and oxygenation.
    Date: 26-Mar-2021 (process 3 of 10)
    Initial sample preparation: For all three experimental runs, as the diseased corals were transferred into their mesocosms, healthy corals of the same or similar species were transferred from their indoor water tables, into identical individual mesocosms. All mesocosms were housed within outdoor water tables containing recirculating freshwater maintained at ~28°C and located under a mesh canopy to allow some sunlight attenuation. Separate “healthy” and “diseased” water tables were maintained to prevent cross-contamination between the different mesocosm types. All corals were incubated within these mesocosms for 2-5 days to enrich the water with microbes.
    Date: 28-Mar-2021 (process 4 of 10)
    Sample preparation: Following the 2-5 day incubation period, each coral colony was removed from its mesocosm, and the remaining seawater was filtered through an ethanol-sterilized 200 µm (Run 1) or 106 µm (Runs 2 & 3) mesh screen to remove particulates. Using a peristaltic pump, the water from each mesocosm was then pumped through a TFF manifold containing five Centramate 100 kiloDalton (kDa) filter cassettes, as described by Evans and others (2022). Anything larger than 100 kDa (including microorganisms) was retained within the sample, while anything smaller than 100 kDa was filtered out (Paul and others, 1991). For all three runs, healthy corals were processed first, then the TFF system was flushed with bleach solution for one hour and held overnight permeated with bleach solution. Once the TFF system was disinfected, the diseased corals were processed in the same manner as the healthy.
    Date: 28-Mar-2021 (process 5 of 10)
    Size fractionation: TFF-concentrated water, along with the FSW control, was sequentially passed through a sterile filter unit containing a 50 millimeter (mm) 0.8 µm pore size cellulose nitrate membrane filter (Runs 2 & 3) and a sterile filter unit containing a ~47 mm 0.22 µm pore size nitrocellulose membrane filter (Runs 1, 2, & 3). The 0.22 µm filters were cut from the filter units using an ethanol-sterilized razor blade, with a portion of each filter frozen at -20°C for later processing.
    Date: 06-May-2021 (process 6 of 10)
    DNA extraction: Between February and May 2021, at the Coral Microbial Ecology Laboratory in St. Petersburg, FL, USA, DNA was extracted from the frozen portions of all 0.22 µm pore size filters using Qiagen DNeasy Power Biofilm kits (Qiagen, 2020). The Quickstart protocol (v. November 2016) was followed, except bead beating was performed on a BioSpec Products Mini Beadbeater at 2500 revolutions per minute (rpm) instead of on a PowerLyzer 24 Homogenizer at 3200 rpm. Blanks using kit reagents were also extracted, and positive controls (MSA-3001 ABRF-MGRG 10 Strain Even Mix Genomic Material, ATCC) were incorporated for downstream processing.
    Date: 28-Jul-2021 (process 7 of 10)
    Sequencing: Library preparation and DNA sequencing were conducted in July, 2021 by the Michigan State University RTSF Genomics Core (East Lansing, MI) for amplicon library preparation and sequencing. The universal 16S (V4 region) primers 515F: GTGCCAGCMGCCGCGGTAA and 806R: GGACTACHVGGGTWTCTAAT were used to target the V4 variable region of the 16S rRNA gene on a MiSeq sequencing system with v2 chemistry to obtain paired-end 250-bp reads. Bases were called via Illumina Real Time Analysis (v1.18.54), with all output demultiplexed and converted to fastq files via Illumina Bcl2fastq (v2.20.0). Person who carried out this activity:
    Michigan State University RTSF Genomics Core
    612 Wilson Road, S-18B
    East Lansing, MI
    United States

    N/A (voice)
    gtsf@msu.edu
    Data sources produced in this process:
    • SCTLD_FullFilterSet_raw_data.zip
    Date: 06-May-2022 (process 8 of 10)
    Data analysis: Demultiplexed sequences were imported into QIIME2 (v. 2022.2) and denoised with DADA2 under default parameters, with truncation set to position 200. Taxonomy was assigned using a pre-trained naïve Bayes classifier SILVA-138-99-515-806 (Bokulich and others, 2018; Robeson and others, 2021) and sequences matching chloroplasts or mitochondria were removed from the final table. A phylogenetic tree was generated using MAFFT (v. 7.0) and FastTree 2. An unrarefied amplicon sequence variant (ASV) table was generated. Data sources produced in this process:
    • SCTLD_FullFilterSet_ASV_Table.zip
    • SCTLD_FullFilterSet_ASV_Table_Eukaryota.zip
    Date: 07-Apr-2023 (process 9 of 10)
    Data analysis: BLASTn comparisons were run through the NCBI website to identify ASVs detected in this study that represent 100% sequence identity matches for the overlapping region of SCTLD bioindicator ASVs (Becker and others, 2021) from the U.S. Virgin Islands and disease-associated ASVs from Florida SCTLD studies. Data sources used in this process:
    • (Becker and others, 2021)
    Data sources produced in this process:
    • SCTLD_FullFilterSet_SCTLD_bioindicators.zip
    Date: 07-Apr-2023 (process 10 of 10)
    Data analysis: Differential abundance analyses were performed using the analysis of composition of microbiomes, or 'ANCOM' (Mandal and others, 2015) analysis plugin (QIIME2 version 2022.2) of the ASV table "SCTLD_FullFilterSet_ASV_Table" was used to produce differential abundance analysis. Sequence IDs, W values, and whether the null hypothesis is rejected are indicated, along with percent abundance of each sequence ID for each percentile (0%, 25%, 50%, 75%, and 100%) for diseased and healthy mesocosms. Data sources produced in this process:
    • SCTLD_FullFilterSet_ANCOM_results.zip
  3. What similar or related data should the user be aware of?
    Evans, James S., Paul, Valerie J., Ushijima, Blake, Pitts, Kelly A., and Kellogg, Christina A., 202308, Investigating microbial size classes associated with the transmission of stony coral tissue loss disease (SCTLD): PeerJ Volume 11, Article 15836.

    Online Links:

    Qiagen, 20200131, Qiagen DNeasy PowerBiofilm kit handbook.

    Online Links:

    Evans, James S., Paul, Valerie J., Ushijima, Blake, and Kellogg, Christina A., 20220208, Combining tangential flow filtration and size fractionation of mesocosm water as a method for the investigation of waterborne coral diseases: Biology Methods and Protocols Volume 7(1).

    Online Links:

    Other_Citation_Details: Pages 1-8
    Paul, John H., Jiang, Sunny C., and Rose, Joan B., 19910801, Concentration of viruses and dissolved DNA from aquatic environments by vortex flow filtration: Applied and Environmental Microbiology Volume 57(8).

    Online Links:

    Other_Citation_Details: Pages 2197-2204
    Bokulich, Nicholas A., Kaehler, Benjamin D., Rideout, Jai Ram, Dillon, Matthew, Bolyen, Evan, Knight, Rob, Huttley, Gavin A., and Caporaso, J. Gregory, 20180517, Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin: Microbiome Volume 6(90).

    Online Links:

    Robeson, Michael S. II, O'Rourke, Devon R., Kaehler, Benjamin D., Ziemski, Michal, Dillion, Matthew R., Foster, Jeffrey T., and Bokulich, Nicholas A., 20211108, RESCRIPt: Reproducible sequence taxonomy reference database management: PLOS Computational Biology Volume 17(11).

    Online Links:

    Mandal, Siddhartha, Treuren, Will Van, White, Richard A., Eggesbo, Merete, Knight, Rob, and Peddada, Shyamal D., 20150529, Analysis of composition of microbiomes: a novel method for studying microbial composition: Microbial Ecology in Health and Disease Article: 27663.

    Online Links:

How reliable are the data; what problems remain in the data set?

  1. How well have the observations been checked?
    No formal attribute accuracy tests were conducted.
  2. How accurate are the geographic locations?
  3. How accurate are the heights or depths?
  4. Where are the gaps in the data? What is missing?
    Dataset is considered complete for the information presented, as described in the abstract.
  5. How consistent are the relationships among the observations, including topology?
    No formal logical consistency tests were conducted.

How can someone get a copy of the data set?

Are there legal restrictions on access or use of the data?
Access_Constraints None. Please see 'Distribution Info' for details.
Use_Constraints None. Users are advised to read the dataset's metadata thoroughly to understand appropriate use and data limitations.
  1. Who distributes the data set? (Distributor 1 of 1)
    Christina A. Kellogg
    U.S. Geological Survey
    Research Microbiologist
    600 4th St. South
    St. Petersburg, Florida
    United States

    727-502-8128 (voice)
    ckellogg@usgs.gov
  2. What's the catalog number I need to order this data set?
  3. What legal disclaimers am I supposed to read?
    Unless otherwise stated, all data, metadata and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. Although these data and associated metadata have been reviewed for accuracy and completeness and approved for release by the U.S. Geological Survey (USGS), no warranty expressed or implied is made regarding the display or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty.
  4. How can I download or order the data?

Who wrote the metadata?

Dates:
Last modified: 01-Aug-2023
Metadata author:
Christina A. Kellogg
U.S. Geological Survey
Research Microbiologist
600 4th St. South
St. Petersburg, Florida
United States

727-502-8128 (voice)
ckellogg@usgs.gov
Metadata standard:
FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata (FGDC-STD-001.1-1999)
This page is <https://cmgds.marine.usgs.gov/catalog/spcmsc/SCTLD_FullFilterSet_FGDC_metadata.faq.html>
Generated by mp version 2.9.51 on Tue Aug 1 16:26:20 2023