This dataset represents a comprehensive untargeted gas chromatography–mass spectrometry (GC–MS) metabolomic analysis of the reef-dwelling sea urchin Diadema antillarum, conducted to investigate how gut microbial and dietary interactions reflect site-specific contamination and environmental stress across Puerto Rican reef ecosystems. Sampling was performed during the dry season (January–March 2024) [DIFFERENT from TIME in METHODS??] to minimize seasonal confounders such as terrestrial runoff a...
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This dataset is one of ___ datasets from a study investigating sea urchins and associated water and sediment samples from four shallow reef ecosystems in coastal waters surrounding Puerto Rico. All analyses were conducted by the PRINBRE Metabolomics Research Core at the University of Puerto Rico, Medical Sciences Campus, in collaboration with marine biologists from the Institute of Tropical Ecosystem Studies. The study is part of a broader initiative to integrate marine ecology with chemical ecology and metabolomics.
This dataset presents metabolomic profiling data for samples collected from reef ecosystems in coastal waters surrounding Puerto Rico. Specific collection sites included shallow reef habitats known for high biodiversity and ecological sensitivity in Dorado, Luquillo, and Culebra. This study used untargeted gas chromatography-mass spectrometry (GC/MS) metabolomics to analyze gut metabolites of Diadema antillarum collected from four sites in Puerto Rico: Cerro Gordo (n=6), Sardinera (n=9), Punta Bandera (n=7), and Culebra (n=11) and water samples.
Chorna, N., Toledo-Hernandez, C., Ruiz-Diaz, C. P., Kardas, E., Godoy-Vitorino, F. (2025) Metabolite and microbiota data from sea urchin specimens and seawater samples collected in 2023 from four locations in coastal waters of Puerto Rico. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2025-10-10 [if applicable, indicate subset used]. http://lod.bco-dmo.org/id/dataset/986552 [access date]
Terms of Use
This dataset is licensed under Creative Commons Attribution 4.0.
If you wish to use this dataset, it is highly recommended that you contact the original principal investigators (PI). Should the relevant PI be unavailable, please contact BCO-DMO (info@bco-dmo.org) for additional guidance. For general guidance please see the BCO-DMO Terms of Use document.