Abstract:
This dataset contains metabolomic data and fingerprints of deep-sea coral species and populations obtained aboard the E/V Nautilus cruises NA057 and NA058 in the northern Gulf of Mexico from 2015-04-22 to 2015-05-11 and on 2015-07-15 with other methods such as SCUBA diving. Untargeted liquid chromatography-mass spectrometry was used to examine the metabolomic diversity of Callogorgia delta, across three sites in the northern Gulf of Mexico. This data was contrasted with that of Stichopathes sp., Leiopathes glaberrima, Lophelia pertusa, and a shallow-water species, Acropora palmata. Metabolomic fingerprints were species-specific and differed in metabolic richness which C. delta being the least diverse and Lophelia pertusa being the most diverse. The dataset also includes the date, latitudes and longitudes of the sampling locations, and the cruise documentation for the E/V Nautilus cruises NA057 (leg 1) and NA058 (leg 2) led by chief scientists Dr. Chuck Fisher and Dr. Erik Cordes respectively. This dataset supports the publication: Vohsen, Samuel A., Charles R. Fisher, and Iliana B. Baums. 2019. Metabolomic richness and fingerprints of deep-sea coral species and populations. Metabolomics, 15(34). doi:10.1007/s11306-019-1500-y.
Suggested Citation:
Vohsen, Sam. 2020. Metabolomic data and fingerprints of deep-sea coral species and populations obtained aboard the E/V Nautilus cruises NA057 and NA058 in the Gulf of Mexico from 2015-04-22 to 2015-05-11 and 2015-07-15. Distributed by: GRIIDC, Harte Research Institute, Texas A&M University–Corpus Christi. doi:10.7266/n7-n3hr-pz39
Data Parameters and Units:
Features are characterized by a mass-to-charge ratio (m/z) in amu (ranging from 0-1500 amu) and a retention time (rt) in minutes or seconds ranging from 0 to 20 minutes. The intensity of each feature in each sample is given. It is a measure of relative abundance or concentration of that feature within a sample. Fold is the fold change in the intensity of the feature peak between sample groups.
Please note that the date of sample collection with SCUBA diving was conducted on 2015-07-15 and not 2020-07-15.
Methods:
Corals were collected via SCUBA (French Reef, Sand Island Reef) or via remotely operated vehicle (MC885, MC751, GC234, MC344, VK906) and kept at their collection temperature until flash freezing in liquid nitrogen. Samples were extracted in extraction solution (0.1% formic acid, 45% isopropanol, 35% acetonitrile, 20% H2O, 10mM Ammonium formate) and run on an AB Sciex 5600 TripleTOF® mass spectrometer. Lipid ion separation was accomplished using an ACQUITY CSH C18 column (100 mm x 2.1 mm, 1.7 μm particle size) and a gradient elution program with aqueous acetonitrile and isopropanol (10-60%) at a flow rate of 225 µl/min. All samples were run in both positive and negative electrospray ionization modes. Ion peaks were identified and aligned using MS-DIAL (version 2.82). Putative identities for ions were annotated by comparing fragmentation spectra of samples to the database. Samples were internally normalized by the total intensity of all putatively identified ions for each sample. Normalized ion intensities and peaks identified by MS-DIAL were exported for statistical analysis in R. Species profiles were compared using Principal Component Analysis (PCA) on log10 transformed and Pareto scaled normalized ion areas. To compare metabolomic richness, ions were considered to be present in a colony only if a peak was detected in both replicates and considered absent only if absent in both replicates. Since species and site collections differed in sample size, datasets were rarefied to enable more robust comparisons. Analysis of similarity (ANOSIM) was used to compare the profiles of all species to Callogorgia delta. Clustering analysis was performed using Euclidean distance and Ward’s clustering criterion.
Instruments:
AB SCIEX 5600 TripleTOF® mass spectrometer (<2ppm); ACQUITY CSH C18 (130Å, 1.7 μm, 2.1 mm x 30 mm); Remotely Operated Vehicle (ROV).
Error Analysis:
Ion redundancy due to adducts and isotopologues was reduced to limit its influence on measures of diversity such as richness. Ions resulting from the same metabolite were identified and reduced to a single representative ion. A set of criteria to group ions were constructed based on the mass spectral feature list optimizer: MS-FLO (DeFelice et al. 2017). Redundant pairs of ions were identified if their difference in masses matched the mass difference between known ion types. Positive ions investigated included [M+H]+, [M+NH4]+, [M+Na]+, [M+CH3OH]+, [M+K]+, [M+ACN+H]+, [M+2Na-H]+, [M+isopropanol+H]+, [M+ACN+Na]+, [M+2K-H]+, [M+DMSO+H]+, [M+2ACN+H]+, and [M+isopropanol+Na+H]+. Negative ions investigated included [M-H2O-H]-, [M-H]-, [M+Na-2H]-, [M+Cl]-, [M+K-2H]-, [M+FA-H]-, [M+Hac-H]-, [M+Br]-, and [M+TFA-H]-. All combinations of these adducts were screened. A pair of ions was considered redundant if their difference in mass was within 0.02 amu of the difference in mass of known ion types, their difference in retention time did not exceed 0.1 minute, and their signal intensities had a correlation greater than 0.75. Signal intensity correlations only utilized samples in which both ions were present. When a pair met all criteria, the ion with the smaller mass was retained unless it was a [M-H20-H]- ion in which case this ion was dropped. For example, the [M-H]- ion would be retained after identifying the pair [M-H]- and [M+Cl-]-. Similarly, the [M+Na]+ ion would be retained after identifying the pair [M+Na]+ and [M+K]+ when no [M+H]+ was detected. This filtering procedure was designed to be conservative by removing all known adducts and isotopologues at the cost of dropping some non-redundant ions.
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