High-Resolution Liquid Chromatography Tandem Mass Spectrometry Enables Large Scale Molecular Characterization of Dissolved Organic Matter

Dissolved organic matter (DOM) is arguably one of the most complex exometabolomes on earth, and is comprised of thousands of compounds, that together contribute more than 600×1015 g carbon. This reservoir is primarily the product of interactions between the upper ocean’s microbial food web, yet abiotic processes that occur over millennia have also modified many of its molecules. The compounds within this reservoir play important roles in determining the rate and extent of element exchange between inorganic reservoirs and the marine biosphere, while also mediating microbe-microbe interactions. As such, there has been a widespread effort to characterize DOM using high-resolution analytical methods including nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS). To date, molecular information in DOM has been primarily obtained through calculated molecular formulas from exact mass. This approach has the advantage of being non-targeted, accessing the inherent complexity of DOM. Molecular structures are however still elusive and the most commonly used instruments are costly. More recently, tandem mass spectrometry has been employed to more precisely identify DOM components through comparison to library mass spectra. Here we describe a data acquisition and analysis workflow that expands the repertoire of high-resolution analytical approaches available to access the complexity of DOM molecules that are amenable to electrospray ionization (ESI) MS. We couple liquid chromatographic separation, with tandem MS (LC-MS/MS) and a data analysis pipeline, that integrates peak extraction from extracted ion chromatograms (XIC), molecular formula calculation and molecular networking. This provides more precise structural characterization. Although only around 1% of detectable DOM compounds can be annotated through publicly available spectral libraries, community-wide participation in populating and annotating DOM datasets could rapidly increase the annotation rate and should be broadly encouraged. Our analysis also identifies shortcomings of the current data analysis workflow that need to be addressed by the community in the future. This work will lay the foundation for an integrative, non-targeted molecular analysis of DOM which, together with next generation sequencing, meta-proteomics and physical data, will pave the way to a more comprehensive understanding of the role of DOM in structuring marine ecosystems.