Dataset Information

Dissolved metabolites from the Bermuda Atlantic Time-series Study: 2016-2019

ABSTRACT:

Organic carbon in seawater plays a significant role in the global carbon cycle. The concentration and composition of dissolved organic carbon, operationally defined in this project as organic carbon that passes through a 0.2 µm filter, reflect the actions of the biological community and chemical reactions that occur in seawater. Here, we repeatedly sampled the oligotrophic northwest Sargasso Sea in the vicinity of the Bermuda Atlantic Time-Series Study site (BATS) to quantitatively follow select known compounds within the pool of dissolved organic matter in the upper 1000 meters of the water column over a four-year period. Metabolite concentrations revealed patterns with depth and time with most metabolites showing surface enrichment and lower concentrations with depth. Select metabolites had a pattern of increased and decreased concentrations throughout the year, which was observed in each of the years sampled. Vitamins, including pantothenic acid, biotin, and riboflavin, presented annual increases in the winter period when mixed layer depths are deepest. Light-sensitive riboflavin also showed significant decreases during daylight hours under diel sampling. The metabolites examined in this study are all components of central carbon metabolism. By examining these metabolites at finer resolution and in a relatively long time series, we have clues on microbial actions in marine systems, data which are fundamental to understanding the chemical response of marine systems to future changes in climate.

INSTRUMENT(S): Liquid Chromatography MS - positive, Liquid Chromatography MS - negative

SUBMITTER: Krista Longnecker

PROVIDER: MTBLS2356 | MetaboLights | 2022-02-09

REPOSITORIES: MetaboLights

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			Action	DRS
	MTBLS2356	Other
	FILES	Other
	a_MTBLS2356_LC-MS_negative__metabolite_profiling.txt	Txt
	a_MTBLS2356_LC-MS_positive__metabolite_profiling.txt	Txt
	files-all.json	Other

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Dissolved metabolites from the Bermuda Atlantic Time-series Study: 2016-2019

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