Contributors | Affiliation | Role |
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Adam, Tom C. | University of California-Santa Barbara (UCSB-MSI) | Co-Principal Investigator |
Burkepile, Deron | University of California-Santa Barbara (UCSB-ERI) | Co-Principal Investigator |
Sharpton, Thomas J. | Oregon State University (OSU) | Co-Principal Investigator |
Vega Thurber, Rebecca | Oregon State University (OSU) | Co-Principal Investigator |
Epstein, Hannah E. | Oregon State University (OSU) | Scientist |
Schmeltzer, Emily R. | Oregon State University (OSU) | Scientist |
Speare, Kelly E. | University of California-Santa Barbara (UCSB-ERI) | Scientist |
Vompe, Alex Dmitry | Oregon State University (OSU) | Scientist |
Mickle, Audrey | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Relevant Materials and Methods from Vompe et al. (2023):
Our experimental study site is located on the northern forereef in Mo'orea, French Polynesia (S17° 28.386′ W149° 49.059′). Mo'orea is a tropical, volcanic high island in the Central South Pacific Ocean. A shallow, ~1 km wide lagoon and barrier reef surround the island. The forereef gradually slopes downwards toward the open ocean and is composed of coral spur and sand groove formations. At the inception of our experiment in August 2018, this reef was dominated by scleractinian corals with low abundance of fleshy macroalgae. Coral cover was 56.0 ± 1.0% (mean ± SE) and macroalgae cover was 0.8 ± 0.2% (mean ± SE).
At this site, we have an ongoing in situ experiment investigating tipping points of coral benthic and microbial ecology in response to nutrient enrichment and herbivore reduction, as in Adam et al. (2022). Briefly, our experimental platform is a factorial design at 10 m depth on the forereef, consisting of four herbivore exclosures (~1 m2 each) placed over eight natural 30-m2 reef plots. The plots are exposed to two levels of nutrient enrichment (four plots ambient/four plots enriched) and four levels of herbivory (exclosures with different size holes of 2.5 cm × 2.5 cm, 5.0 cm × 5.0 cm, 7.5 cm × 7.5 cm, or open top, with one exclosure of each herbivory condition at each plot). Nutrient enrichment was achieved in the plots via PVC tubes with Osmocote® (19-6-12, N-P-K) slow-release garden fertilizer. These tubes were wrapped in plastic mesh to contain the fertilizer. The nutrient enrichment tubes were replaced every 12–16 weeks, except for two periods during the COVID-19 pandemic when travel to Mo'orea was not possible. See Supplementary Methods (Vompe et al. 2023) for a full description of the experimental setup.
To investigate how the microbiomes of different coral species respond to environmental stress, samples of Acropora retusa, Porites lobata species complex, and Pocillopora spp. were collected over 2 years (July 2018–August 2020), 3× a year, in March, July or August, and November. Corals in the P. lobata species complex will be referred to as P. lobata below for brevity. However, we acknowledge there may be cryptic diversity in our samples (Brown et al., 2021). A nonmetric multidimensional scaling (NMDS) ordination of Bray–Curtis distances between P. lobata sample microbiomes from July 2018 suggests that the possible presence of cryptic members of the P. lobata species complex in our dataset was unlikely to affect P. lobata microbiome variation, as there are no obvious sample microbiome composition clusters. The taxonomic name Pocillopora spp. is used for this study because Pocillopora species have high cryptic diversity (Johnston et al., 2022), which makes it difficult to visually delineate among species. We selected Pocillopora spp. specimens that had consistent phenotypes similar to those now defined as Pocillopora meandrina or Haplotype 8a as described in Figure 1 of Johnston et al. (2022). Different coral species, even genotypes, tend to have distinct microbiomes (Bourne et al., 2016; Dunphy et al., 2019; Rosales et al., 2019). A NMDS ordination of Bray–Curtis distances between Pocillopora spp. sample microbiomes from July 2018 suggests that the possible presence of cryptic Pocillopora species in our dataset was unlikely to affect Pocillopora spp. microbiome variation, as there are no obvious sample microbiome composition clusters.
All colonies of each coral species appeared healthy when initially selected for microbiome sampling. Live tissue on these focal colonies was repeatedly sampled throughout the study regardless of subsequent visual phenotype, as long as live tissue remained. Live tissue was sampled at haphazardly chosen locations on the colonies at each time point. For A. retusa and Pocillopora spp., haphazardly chosen live branch tips were sampled. For P. lobata, live tissue was sampled from haphazardly chosen locations around the center of the colony. Coral samples were collected in July 2018, November 2018, March 2019, August 2019, November 2019, March 2020, and August 2020, covering a 28-month period. Additional coral colonies were sampled in November 2018, March 2019, and August 2019 to increase sample sizes and to account for initial focal colony mortality. Colonies of each species were also added to the dataset in March 2020 and August 2020 to restore sample size due to colony mortality. Bleaching and mortality data for coral colonies added to the microbiome sampling effort after the start of the experiment were collected retroactively. This was possible because these corals were already present in the exclosures and data could be collected from our photomosaic time series from before they were added to the microbiome sampling effort.
During each sampling event, coral fragments <1 cm3 were snipped from each of the focal colonies using bone cutters that were flame-sterilized with 95% ethanol at the surface. Corals were sampled between 08:00 and 14:00 h to help minimize diel microbiome variation. Fragments were immediately placed in sterile 207 mL Whirl-Paks. This volume of sample is sufficient to produce accurate microbiome data without significantly damaging the focal colony (Zaneveld et al., 2016). Upon surfacing, Whirl-paks were placed on ice and transported to shore (~15 min) then transferred to Qiagen DNeasy PowerSoil lysis matrix tubes, containing a guanidinium thiocyanate preservative, using 95% ethanol flame-sterilized forceps. Tubes were stored at −40°C prior to transport on Techni Ice to Oregon State University where they were stored at −80°C until further processing.
The V4 region of the 16S rRNA gene was amplified using 515F and 806RB primers from total DNA, then barcoded, purified, and sequenced (Apprill et al., 2015; Parada et al., 2016). Microbiome sequence library generation, sequence processing, and quality control were done as in Williams et al. (2022) with some modifications. See the Supplementary Methods (Vompe et al. 2023) for full protocols and conditions. All microbiome analyses were performed in R v4.2.2, using functions from base R and “tidyverse” (Wickham et al., 2019), as well as functions from a suite of packages developed for microbiome analyses, including “phyloseq” (McMurdie & Holmes, 2013), “vegan” (Oksanen et al., 2022), and Analysis of Compositions of Microbiomes with Bias Correction (ANCOM-BC) in the “ANCOMBC” package (Lin & Peddada, 2020; Vompe et al., 2023).
- Import "complete sample data.xlsx" into BCO-DMO system
- Split lat_lon field into Latitude and Longitude, with negative values for S and W
- Remove original lat_lon field
- Export file "954262_v1_microbiome_accession_info.csv"
Taxonomic names checked using the World Register of Marine Species Taxa Match tool on 2025-04-15. All names matched a known name exactly.
File |
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954262_v1_microbiome_accession_info.csv (Comma Separated Values (.csv), 498.65 KB) MD5:7dd8d3d8ca6c1ae594c0e6d5913e863a Primary data file for dataset ID 954262, version 1 |
File |
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Supporting Information filename: gcb17088-sup-0001-datas1.pdf (Portable Document Format (.pdf), 3.53 MB) MD5:7a0e20ad5f034647d1c6233790734638 The supporting information from Vompe et al. (2023), referenced in the submission. This file contains further details about data collection and analyses. |
Parameter | Description | Units |
Sample | Unique sample name, containing the Illumina MiSeq lane, placeholder sample number, the Nextera barcode sequences, and the unique sample number | unitless |
Date_MonthYear | Collection date given as the month and year | unitless |
Coral_Code | Code for the host coral species sampled (Aret = Acropora retusa, Plob = Porites lobata, Poc = Pocillopora) | unitless |
Herbivory | Consumer pressure level generated by the experimental exclosures (1x1, 2x2, 3x3, open) | unitless |
Nutrients | Enrichment condition in the exclosures (Nutrient or Ambient) | unitless |
Plot | Unique plot containing a set of coral exclosures (A1, A2, B3, B4, C1, C3, D2, or D4) | unitless |
Tag | Unique colony identifier (numeric) | unitless |
Batch | Identifier of Illumina MiSeq run (R1, R2, or R3) | unitless |
Run | NCBI SRA SRR identifier | unitless |
AssayType | Type of DNA sequencing performed | unitless |
AvgSpotLen | Total across paired reads | unitless |
Bases | Number of bases in the sample | unitless |
BioProject | NCBI SRA BioProject containing the sequences from these samples | unitless |
BioSample | SAMN identifier for each sample | unitless |
BioSampleModel | Type of metagenomic survey | unitless |
Bytes | Total size of the sequencing data files | bytes |
CenterName | Institution where sequencing was conducted | unitless |
Collection_Date | Collection date given as [year]-[month] | unitless |
Consent | Availability of the data | unitless |
DATASTORE_filetype | Available file types for downloading the raw sequencing data | unitless |
DATASTORE_provider | Organizations linked to this repository | unitless |
DATASTORE_region | Data storage region | unitless |
env_broad_scale | General description of the sampling environment | unitless |
env_local_scale | Specific description of the sampling environment at the local scale | unitless |
env_medium | Medium from which DNA was isolated (Coral Tissue or PCR water) | unitless |
Experiment | NCBI SRA SRX identifier | unitless |
geo_loc_name_country | Region where sample was collected | unitless |
geo_loc_name_country_continent | Continent where sample was collected | unitless |
geo_loc_name | Specific name of sampling environment | unitless |
Host | Most accurate possible host taxonomy | unitless |
Instrument | Instrument for DNA sequencing | unitless |
Latitude | Latitude of collection, South is negative | decimal degrees |
Longitude | Longitude of collection, West is negative | decimal degrees |
LibraryName | Equivalent to 'Sample' | unitless |
LibraryLayout | Type of amplicon sequencing performed | unitless |
LibrarySelection | Selection to perform amplicon sequencing | unitless |
LibrarySource | DNA source type | unitless |
Organism | Organism type (coral reef metagenome or indoor metagenome) | unitless |
Platform | Platform for sequencing | unitless |
ReleaseDate | Public release date for the raw sequencing data | unitless |
create_date | Date the dataset was initially uploaded to the NCBI SRA | unitless |
version | Version of the public dataset | unitless |
SRA_Study | SRA study Identifier | unitless |
unique_sample_identifier | A unique number identifying each sample | unitless |
Dataset-specific Instrument Name | Illumina MiSeq System |
Generic Instrument Name | Automated DNA Sequencer |
Dataset-specific Description | The V4 region of the 16S rRNA gene was amplified using 515F and 806RB primers from total DNA, then barcoded, purified, and sequenced (Apprill et al., 2015; Parada et al., 2016). Microbiome sequence library generation, sequence processing, and quality control were done as in Williams et al. (2022) with some modifications. |
Generic Instrument Description | A DNA sequencer is an instrument that determines the order of deoxynucleotides in deoxyribonucleic acid sequences. |
Dataset-specific Instrument Name | bone cutters |
Generic Instrument Name | bone cutter |
Dataset-specific Description | During each sampling event, coral fragments less than 1 cm3 were snipped from each of the focal colonies using bone cutters that were flame-sterilized with 95% ethanol at the surface. |
Generic Instrument Description | A bone cutter is a surgical instrument used to cut bones or coral fragments. |
Dataset-specific Instrument Name | Eppendorf Benchtop Centrifuge 5430 |
Generic Instrument Name | Centrifuge |
Generic Instrument Description | A machine with a rapidly rotating container that applies centrifugal force to its contents, typically to separate fluids of different densities (e.g., cream from milk) or liquids from solids. |
Dataset-specific Instrument Name | Thermo Fisher Scientific Owl A3-1 Large-Gel Electrophoresis System |
Generic Instrument Name | Electrophoresis Chamber |
Dataset-specific Description | Thermo Fisher Scientific Owl A3-1 Large-Gel Electrophoresis System. A Gel Transilluminator was also used. |
Generic Instrument Description | General term for an apparatus used in clinical and research laboratories to separate charged colloidal particles (or molecules) of varying size through a medium by applying an electric field. |
Dataset-specific Instrument Name | Invitrogen Qubit 4 Fluorometer |
Generic Instrument Name | Qubit fluorometer |
Dataset-specific Description | Invitrogen Qubit 4 Fluorometer |
Generic Instrument Description | Benchtop fluorometer. The Invitrogen Qubit Fluorometer accurately and quickly measures the concentration of DNA, RNA, or protein in a single sample. It can also be used to assess RNA integrity and quality.
Manufactured by Invitrogen, Carlsbad, CA, USA (Invitrogen is one of several brands under the Thermo Fisher Scientific corporation.) |
Dataset-specific Instrument Name | Vortex |
Generic Instrument Name | Shaker |
Dataset-specific Description | Used with Qiagen Bead Beater Vortex Attachment |
Generic Instrument Description | A Shaker is a piece of lab equipment used to mix, blend, or to agitate substances in tube(s) or flask(s) by shaking them, which is mainly used in the fields of chemistry and biology. A shaker contains an oscillating board which is used to place the flasks, beakers, test tubes, etc. |
Dataset-specific Instrument Name | Thermocycler |
Generic Instrument Name | Thermal Cycler |
Dataset-specific Description | The V4 region of the 16S rRNA gene was amplified using 515F and 806RB primers from total DNA, then barcoded, purified, and sequenced (Apprill et al., 2015; Parada et al., 2016). |
Generic Instrument Description | A thermal cycler or "thermocycler" is a general term for a type of laboratory apparatus, commonly used for performing polymerase chain reaction (PCR), that is capable of repeatedly altering and maintaining specific temperatures for defined periods of time. The device has a thermal block with holes where tubes with the PCR reaction mixtures can be inserted. The cycler then raises and lowers the temperature of the block in discrete, pre-programmed steps. They can also be used to facilitate other temperature-sensitive reactions, including restriction enzyme digestion or rapid diagnostics.
(adapted from http://serc.carleton.edu/microbelife/research_methods/genomics/pcr.html) |
NSF Award Abstract:
Coral reefs are some of the most diverse, yet most imperiled, ecosystems on the planet. Global change has driven the decline of corals worldwide with many reefs now lacking corals and being overrun by macroalgae. This research examines the impacts of several factors of thermal stress, overfishing of important herbivorous fishes, and nutrient pollution on the health of corals and their ability to recover after large coral-killing disturbances. Importantly, the investigators address the impacts of global change on the coral microbiome, the microbes that associate with corals and impact coral health. The overarching hypothesis is that factors such as overfishing and nutrient pollution impact coral health via impacts to their microbes. This 6-year experiment on the coral reefs of Mo’orea, French Polynesia examines what levels of herbivory, mostly by parrotfishes and surgeonfishes, are needed to provide resistance and resilience of corals and their microbiomes when reefs are exposed to elevated nutrients and ocean temperatures. Notably, the team tests how local stressors (overfishing, nutrient pollution) potentially interact with global stressors (climate change and rising ocean temperatures) to impact coral reef health. This research may yield insight into how to manage local factors (reducing fishing, mitigating nutrient pollution) to help corals survive the global stress of climate change. The field experiment provides a realistic platform to test questions about how local management of fisheries can alter reef health and provides data about the recoverability of reefs should new water quality management be put into place. This interdisciplinary work trains a new generation of both marine ecologists and microbiologists, including one postdoctoral researcher, two graduate students, as well as numerous undergraduates. The main international outreach effort is to map the microbiome of the island of Mo’orea. Mo’orea is approximately 130 square-kilometers in area and has five major watersheds that transport sediment and nutrients to the nearshore coral reef ecosystems. Thus poor stewardship of these watersheds likely contributes to the local phase shifts currently occurring in several areas of the lagoon. Therefore the team has engaged the local community to help collect microbiome samples from 50 terrestrial, 50 stream, 25 coastal sites, and 25 offshore sites around the island. The sampling effort is generating an island-wide map of the microbial communities associated with the soils, streams, and coastal waters that can be linked to adjacent coral reef health - The Moorea Microbiome! As part of this outreach effort, the team also collaborates with filmmakers to make a trilingual (English, French, and Tahitian) film about the project to serve as local engagement and teaching tool to help educate school groups and different stakeholders about both the seen and unseen connections between land and sea on their island.
On the island of Mo’orea, French Polynesia, coral communities have exhibited strikingly different trajectories, with some reefs recovering from disturbances and others undergoing protracted coral decline, accompanied by an increase in macroalgae. This diversity in coral community dynamics makes Mo’orea an excellent model system for testing why some reefs are resilient and return to abundant coral while others are not and undergo persistent phase shifts to macroalgal dominance. This 6-year experiment will measure the dynamics of benthic communities, coral demography, and the coral microbiome across seasonal change in ocean temperature, allowing the team to (1) link changes in coral microbiomes (e.g., a rise in pathogenic bacteria) to the trajectories of coral decline or recovery and (2) link nutrients, herbivory, and temperature to phase shifts in both benthic communities and coral microbiomes. Importantly, the team is testing the resistance of phase shifts of benthic communities and coral microbiomes by measuring their changes after removing the nutrient enrichment treatment at the end of year 3 and tracking recovery of the system for 3 more years. Thus, this project begins to answer whether reef and microbial community phase shifts can be easily reversed once they occur. Many studies have focused on the factors that disassemble coral reef communities, but this is the first to examine how reef communities can be reassembled from the microbiome upwards.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) | |
NSF Division of Ocean Sciences (NSF OCE) |