Using network analysis to discern compositional patterns in ultrahigh resolution mass spectrometry data of dissolved organic matter
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Marine dissolved organic matter (DOM) has long been recognized as a large and dynamic component of the global carbon cycle. Yet, DOM is chemical varied and complex and these attributes present challenges to the researchers interested in addressing questions about the role of DOM in global biogeochemical cycles. This project analyzed organic matter extracts from seawater with direct infusion with electrospray ionization into a Fourier transform ion cyclotron resonance mass spectrometer (ESI FT-ICR-MS). We used network analysis to quantify the number of chemical transformations between mass-to-charge values in each sample. The network of chemical transformations was calculated using the MetaNetter plug-in within Cytoscape. The chemical transformations serve as markers for the shared structural characteristics of compounds within complex dissolved organic matter. Network analysis revealed that transformations involving selected sulfur-containing moieties and isomers of amino acids were more prevalent in the deep sea than in the surface ocean. Common chemical transformations were not significantly different between the deep sea and surface ocean. Network analysis complements existing computational tools used to analyze ultrahigh resolution mass spectrometry data. This combination of ultrahigh resolution mass spectrometry with novel computational tools has identified new potential building blocks of organic compounds in the deep sea, including the unexpected importance of dissolved organic sulfur components. The method described here can be readily applied by researchers to analyze heterogeneous and complex dissolved organic matter.
Author Posting. © The Author(s), 2016. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Rapid Communications in Mass Spectrometry 30 (2016): 2388-2394, doi:10.1002/rcm.7719.