Environmental metabolomics : databases and tools for data analysis

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Marine Chemistry 177 (2015): 366–373, doi:10.1016/j.marchem.2015.06.012.
Metabolomics is the study of small molecules, or ‘metabolites’, that are the end products of biological processes. While -omics technologies such as genomics, transcriptomics, and proteomics measure the metabolic potential of organisms, metabolomics provides detailed information on the organic compounds produced during metabolism and found within cells and in the environment. Improvements in analytical techniques have expanded our understanding of metabolomics and developments in computational tools have made metabolomics data accessible to a broad segment of the scientific community. Yet, metabolomics methods have only been applied to a limited number of projects in the marine environment. Here, we review analysis techniques for mass spectrometry data and summarize the current state of metabolomics databases. We then describe a boutique database developed in our laboratory for efficient data analysis and selection of mass spectral targets for metabolite identification. The code to implement the database is freely available on GitHub (https://github.com/joefutrelle/domdb). Data organization and analysis are critical, but often under-appreciated, components of metabolomics research. Future advances in environmental metabolomics will take advantage of continued development of new tools that facilitate analysis of large metabolomics datasets.
The field data populating the database comes from scientific cruises funded by grants from the National Science Foundation to EBK and KL (Atlantic Ocean, OCE-1154320) and E.V. Armbrust (Pacific Ocean, OCE-1205233). The laboratory experiment with coastal seawater was funded by a grant from the Gulf of Mexico Research Initiative to EBK and H.K. White. The laboratory experiments with microbial isolates and the database development are funded by the Gordon and Betty Moore Foundation through Grant GBMF3304 to EBK.