Nontargeted approaches using metabolomics to analyze metabolites that occur in the oceans is less developed than those for terrestrial and limnic ecosystems. One of the challenges in marine metabolomics is that salt limits metabolite analysis in seawater to methods requiring salt removal. Building on previous sample preparation methods for metabolomics, we developed SeaMet, which overcomes the limitations of salt on metabolite detection. Considering that the oceans contain the largest dissolved organic matter pool on Earth, describing the marine metabolome using nontargeted approaches is critical for understanding the drivers behind element cycles, biotic interactions, ecosystem function, and atmospheric CO2 storage. Our method complements both targeted marine metabolomic investigations as well as other “omics” (e.g., genomics, transcriptomics, and proteomics) approaches by providing an avenue for studying the chemical interaction between marine microbes and their habitats.

We report here that a straightforward change of the standard derivatization procedure for GC–MS metabolomics is leading to a strong increase in metabolite signal intensity. Drying samples between methoxymation and trimethylsilylation significantly increased signals by two- to tenfold in extracts of yeast cells, plant and animal tissue, and human urine. This easy step reduces the cost of sample material and the need for expensive new hardware.

9All life exchanges molecules with its environment. While these metabolites are commonly 10 measured in terrestrial and limnic ecosystems, the presence of salt in marine habitats has 11 hampered quantitative analyses of the ocean metabolome. To overcome these limitations, we 12 developed SeaMet, a gas chromatography-mass spectrometry (GC-MS) method that detects 13 hundreds of metabolites down to nano-molar concentrations in less than one milliliter of 14 seawater. Using a set of metabolites dissolved in artificial seawater to benchmark our method, 15 we show metabolite signal detection increased on average across ions by 324 fold in comparison 16 to standard GC-MS methods. Our observed signal improvement occurred across tested 17 metabolite classes and provides reproducible and quantifiable results. To showcase the 18 capabilities of our method, we used SeaMet to explore the production and consumption of 19 metabolites during culture of a heterotrophic bacteria that is widespread in the North Sea. Our

We report here that a straightforward change of standard derivatization procedure for GC-MS metabolomics is leading to a strong increase in metabolite signal intensity. Drying samples between methoxymation and trimethylsilylation significantly increased signals by two-to tenfold in extracts of yeast cells, plant and animal tissue and human urine. This easy step reduces the cost of sample material and the need for expensive new hardware.