Analysis of Oceanic Systems by TM-DART-QTOF-MS-Based Seaomics

NICOLÁS ZABALEGUI; MALENA MANZI; ANTOINE DEPOORTER; NATHALIE HAYECK; MARIE ROVERETTO; CHUNLIN LI; MANUELA VAN PINXTEREN; HARTMUT HERRMANN; CHRISTIAN GEORGE; MARÍA EUGENIA MONGE

Congreso; ASMS Reboot 2020; 2020

Introduction ? Limit 120 words (no formatting except for super-/sub-script and italics)The ocean surface chemical composition influences physicochemical processes occurring at the air-water interface. The sea surface microlayer (SML) covers up to 70 % of the Earth?s surface and is enriched in dissolved organic matter. An improved chemical characterization of the SML is highly desirable to understand its contribution into atmospheric composition, air quality and climate change. Soft ambient ion generation techniques offer alternative mass spectrometry-based applications for surface analysis with little to no sample preparation, addressing high-throughput analytical challenges in untargeted metabolomics workflows. In particular, direct analysis in real time (DART) appears as an attractive technique to interrogate seawater samples with no need of desalinization processes.Methods ? Limit 120 words (no formatting except for super-/sub-script and italics)SML and underlying water (ULW) samples (n=22, 10 paired samples) were collected during a field campaign at the Cape Verde islands. Samples were lyophilized and reconstituted in acetonitrile (concentration factor=6.67). System suitability samples, blanks, pooled quality control samples, and commercial seawater samples were analyzed with the study samples. A DART® SVP ionization source (IonSense Inc.), coupled to a Xevo G2S QTOF mass spectrometer (Waters Corp.) by means of a VAPUR® interface flange, was operated with a transmission mode (TM) geometry in negative ion mode, using He at 300 °C. Unsupervised and supervised multivariate statistical models were built to discriminate sample classes. Putative identification of discriminant features was based on accurate masses, isotopic patterns and fragmentation patterns from TM-DART-QTOF-MS/MS experiments. Preliminary data ? Limit 300 words (no formatting except for super-/sub-script and italics)A TM-DART-QTOF-MS-based untargeted metabolomics method addressed as seaomics allowed a comprehensive screening of seawater samples with no need of desalination. Data curation involved correcting inter-mesh effects through a quality control sample-based robust locally estimated scatterplot smoothing signal correction method using pooled quality control (QC) samples; discarding features with RSD>30% in pooled QC samples; retaining features with 5-fold average intensity in samples compared to process and solvent blanks; and retaining signals with a clear isotopic pattern, and those monoisotopic peaks with intensity >103 in the continuum spectra. The curated data matrix with 51 features was normalized. By means of multivariate statistical methods a panel of 11 ionic species that were present in both SML and ULW samples was isolated and allowed differentiating seawater samples according to their collection depth (i.e., SML or ULW). Putative identification of these discriminant features was supported considering the possible ionic species detected according to the ionization mechanisms operating in a negative mode DART ion source. Tentative identification of discriminant species enriched at SML samples suggested that fatty alcohols, halogenated compounds, and oxygenated boron-containing organic compounds were available at the surface of seawater samples for water-air transfer processes. In addition, a lab-to-the-field approach was applied to evaluate on-site the secondary organic aerosol (SOA) formation potency of a subset of SML samples (n=5) that were also analyzed by the TM-DART-QTOF-MS seaomics approach. Features with the largest weight in differentiating SML samples that led to particle formation from those that did not in field experiments were putatively identified, suggesting that samples that led to particle formation were enriched on boron-containing organic compounds. Combined results from TM-DART-QTOF-MS and on-site SOA formation testing experiments illustrate the capabilities of this approach to identifying organic compounds involved in aerosol formation processes at the water/air interface.Novel aspect ? Limit 20 words (no formatting except for super-/sub-script and italics)This strategy provides new opportunities for analyzing seawater organic matter content and discovering compounds involved in aerosol formation processes.