Detection and Exclusion of False-Positive Molecular Formula Assignments via Mass Error Distributions in UHR Mass Spectra of Natural Organic Matter.

Ultrahigh resolution mass spectrometry (UHRMS) routinely detects and identifies thousands of mass peaks in complex mixtures, such as natural organic matter (NOM) and petroleum. The assignment of several chemically plausible molecular formulas (MFs) for a single accurate mass still poses a major problem for the reliable interpretation of NOM composition in a biogeochemical context. Applying sensible chemical rules for MF validation is often insufficient to eliminate multiple assignments (MultiAs)─especially for mass peaks with low abundance or if ample heteroatoms or isotopes are included - and requires manual inspection or expert judgment. Here, we present a new approach based on mass error distributions for the identification of true and false assignments among MultiAs. To this end, we used the mass error in millidalton (mDa), which was superior to the commonly used relative mass error in ppm. We developed an automatic workflow to group MultiAs based on their shared formula units and Kendrick mass defect values and to evaluate the mass error distribution. In this way, the number of valid assignments of chlorinated disinfection byproducts was increased by 8-fold as compared to only applying 37Cl/35Cl isotope ratio filters. Likewise, phosphorus-containing MFs can be differentiated against chlorine-containing MFs with high confidence. Further, false assignments of highly aromatic sulfur-containing MFs ("black sulfur") to sodium adducts in negative ionization mode can be excluded by applying our approach. Overall, MFs for mass peaks that are close to the detection limit or where naturally occurring isotopes are rare (e.g., 15N) or absent (e.g., P and F) can now be validated, substantially increasing the reliability of MF assignments and broadening the applicability of UHRMS analysis to even more complex samples and processes.

Post column infusion of an internal standard into LC-FT-ICR MS enables semi-quantitative comparison of dissolved organic matter in original samples.

Ultrahigh resolution mass spectrometry hyphenated with liquid chromatography (LC) is an emerging tool to explore the isomeric composition of dissolved organic matter (DOM). However, matrix effects limit the potential for semi-quantitative comparison of DOM molecule abundances across samples. We introduce a post-column infused internal standard (PCI-IS) for reversed-phase LC-FT-ICR MS measurements of DOM and systematically evaluate matrix effects, detector linearity and the precision of mass peak intensities. Matrix effects for model compounds spiked into freshwater DOM samples ranging from a headwater stream to a major river were reduced by 5-10% for PCI-IS corrected mass peak intensities as compared to raw (i.e., untransformed) intensities. A linear regression of PCI-IS corrected DOM mass peak intensities across a typical DOM concentration range (2-15 mg dissolved organic carbon L-1) in original, non-extracted freshwater samples demonstrates excellent linearity of the detector response (r2 > 0.9 for 98% of detected molecular formulas across retention times). Importantly, PCI-IS could compensate for 80% of matrix effects across an environmental gradient of DOM composition from groundwater to surface water. This enabled studying the ionization efficiency of DOM isomers and linking the observed differences to the biogeochemical sources. With PCI-IS original, non-extracted DOM samples can be analysed by LC-FT-ICR MS without carbon load adjustment, and mass peak intensities can be reliably used to semi-quantitatively compare isomer abundances between compositionally similar DOM samples.

How aromatic dissolved organic matter differs in competitiveness against organic micropollutant adsorption.

Activated carbon is employed for the adsorption of organic micropollutants (OMPs) from water, typically present in concentrations ranging from ng L-1 to µg L-1. However, the efficacy of OMP removal is considerably deteriorated due to competitive adsorption from background dissolved organic matter (DOM), present at substantially higher concentrations in mg L-1. Interpreting the characteristics of competitive DOM is crucial in predicting OMP adsorption efficiencies across diverse natural waters. Molecular weight (MW), aromaticity, and polarity influence DOM competitiveness. Although the aromaticity-related metrics, such as UV254, of low MW DOM were proposed to correlate with DOM competitiveness, the method suffers from limitations in understanding the interplay of polarity and aromaticity in determining DOM competitiveness. Here, we elucidate the intricate influence of aromaticity and polarity in low MW DOM competition, spanning from a fraction level to a compound level, by employing direct sample injection liquid chromatography coupled with ultrahigh-resolution Fourier-transform ion cyclotron resonance mass spectrometry. Anion exchange resin pre-treatment eliminated 93% of UV254-active DOM, predominantly aromatic and polar DOM, and only minimally alleviated DOM competition. Molecular characterization revealed that nonpolar molecular formulas (constituting 26% PAC-adsorbable DOM) with medium aromaticity contributed more to the DOM competitiveness. Isomer-level analysis indicated that the competitiveness of highly aromatic LMW DOM compounds was strongly counterbalanced by increased polarity. Strong aromaticity-derived π-π interaction cannot facilitate the competitive adsorption of hydrophilic DOM compounds. Our results underscore the constraints of depending solely on aromaticity-based approaches as the exclusive interpretive measure for DOM competitiveness. In a broader context, this study demonstrates an effect-oriented DOM analysis, elucidating counterbalancing interactions of DOM molecular properties from fraction to compound level.

Direct Analysis of Marine Dissolved Organic Matter Using LC-FT-ICR MS.

Marine dissolved organic matter (DOM) is an important component of the global carbon cycle, yet its intricate composition and the sea salt matrix pose major challenges for chemical analysis. We introduce a direct injection, reversed-phase liquid chromatography ultrahigh resolution mass spectrometry approach to analyze marine DOM without the need for solid-phase extraction. Effective separation of salt and DOM is achieved with a large chromatographic column and an extended isocratic aqueous step. Postcolumn dilution of the sample flow with buffer-free solvents and implementing a counter gradient reduced salt buildup in the ion source and resulted in excellent repeatability. With this method, over 5,500 unique molecular formulas were detected from just 5.5 nmol carbon in 100 µL of filtered Arctic Ocean seawater. We observed a highly linear detector response for variable sample carbon concentrations and a high robustness against the salt matrix. Compared to solid-phase extracted DOM, our direct injection method demonstrated superior sensitivity for heteroatom-containing DOM. The direct analysis of seawater offers fast and simple sample preparation and avoids fractionation introduced by extraction. The method facilitates studies in environments, where only minimal sample volume is available e.g. in marine sediment pore water, ice cores, or permafrost soil solution. The small volume requirement also supports higher spatial (e.g., in soils) or temporal sample resolution (e.g., in culture experiments). Chromatographic separation adds further chemical information to molecular formulas, enhancing our understanding of marine biogeochemistry, chemodiversity, and ecological processes.

A Temporal Graph Model to Predict Chemical Transformations in Complex Dissolved Organic Matter.

Dissolved organic matter (DOM) is a complex mixture of thousands of natural molecules that undergo constant transformation in the environment, such as sunlight induced photochemical reactions. Despite molecular level resolution from ultrahigh resolution mass spectrometry (UHRMS), trends of mass peak intensities are currently the only way to follow photochemically induced molecular changes in DOM. Many real-world relationships and temporal processes can be intuitively modeled using graph data structures (networks). Graphs enhance the potential and value of AI applications by adding context and interconnections allowing the uncovering of hidden or unknown relationships in data sets. We use a temporal graph model and link prediction to identify transformations of DOM molecules in a photo-oxidation experiment. Our link prediction algorithm simultaneously considers educt removal and product formation for molecules linked by predefined transformation units (oxidation, decarboxylation, etc.). The transformations are further weighted by the extent of intensity change and clustered on the graph structure to identify groups of similar reactivity. The temporal graph is capable of identifying relevant molecules subject to similar reactions and enabling to study their time course. Our approach overcomes previous data evaluation limitations for mechanistic studies of DOM and leverages the potential of temporal graphs to study DOM reactivity by UHRMS.

Data evaluation strategy for identification of key molecular formulas in dissolved organic matter as proxies for biogeochemical reactivity based on abundance differences from ultrahigh resolution mass spectrometry.

The molecular composition of dissolved organic matter (DOM) is of relevance for global carbon cycling and important for drinking water processing also. The detection of variation of DOM composition as function of time and space from a methodological viewpoint is essential to observe DOM processing and was addressed so far. High resolution concerning DOM quality was achieved with Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS). However almost none of the existing FTICR-MS data sets were evaluated addressing the fate of single mass features / molecular formulas (MFs) abundance during experiments. In contrast to former studies we analyze the function of MF abundance of time and space for such MFs which are present in all samples and which were formerly claimed as recalcitrant in not all but a great number of studies. For the first time the reactivity of MFs was directly compared by their abundance differences using a simple equation, the relative intensity difference (δRI). Search strategies to find out the maximum δRI values are introduced. The corresponding MFs will be regarded as key MFs (KEY-MFs). In order to test this new approach data from a recent photo degradation experiment were combined with monitoring surveys conducted in two drinking water reservoirs. The δRI values varied over one order of magnitude (more than five-fold). MFs like C9H12O6 and C10H14O6 revealed high biogeochemical reactivity as photo products. Some of the KEY-MFs were identical with MFs identified as disinfection byproducts precursors in recent studies. Other KEY-MFs were oxygen-rich and relatively unsaturated (poly-phenol-like) and hence relevant to flocculation procedures.

Isotopically labeled ozone: A new approach to elucidate the formation of ozonation products.

As ozonation becomes a widespread treatment for removal of chemicals of emerging concern from wastewater treatment plant effluents, there are increasing concerns regarding the formation of ozonation products (OPs), and their possible impacts on the aquatic environment and eventually human health. In this study, a novel method was developed that utilizes heavy oxygen (18O2) for the production of heavy ozone ([18O1]O2, [18O2]O1, [18O3]) to actively label OPs from oxygen transfer reactions. To establish and validate this new approach, venlafaxine with a well-described oxygen transfer reaction (tertiary amine -> N-oxide) was chosen as a model compound. Observed 18O/16O ratios in the major OP venlafaxine N-oxide (NOV) correlated with expected 18O purities based on tracer experiments. These results confirmed the successful labeling with heavy oxygen and furthermore demonstrate the potential to monitor NOV as an indicator of 18O/16O ratios during ozonation. As a next step, 18O/16O ratios were used to elucidate the formation mechanism of previously described OPs from sulfamethoxazole (SMX). Seven OPs were detected including the frequently described nitro-SMX, which was formed with a maximum yield of 3.2% (of initial SMX). With the successful labeling of six of the seven OPs from sulfamethoxazole, it was possible to confirm their previously proposed formation pathways, and to distinguish oxygen transfer from electron transfer reactions. 18O/16O ratios in OPs indicate that hydroxylation of the aromatic ring and formation of nitro-groups mostly follows oxygen transfer reactions, while electron transfer reactions initiate the formation of hydroxylamine and the abstraction of NH2 leading to catechol.

Stable isotope labeling for detection of ozonation byproducts in effluent organic matter with FT-ICR-MS.

Despite effluent organic matter (EfOM) being a major consumer of ozone during wastewater treatment, little is known about ozonation byproducts (OBPs) produced from EfOM. To unambiguously identify OBPs, heavy ozone was used to ozonate EfOM, resulting in 18O labeled and unlabeled OBPs. Labeled OBPs mostly represent a single 18O transfer and were classified as either direct or indirect OBPs based on the 18O/16O intensity ratios of the isotopologues. Of the 929 labeled OBPs, 84 were unequivocally classified as direct OBPs. The remainder suggest a major contribution by indirect, hydroxyl radical induced formation of OBPs in EfOM. Overall, labelled OBPs possess a low degree of unsaturation and contributed most to OBP peak intensity - marking them as potential end products. A few direct and indirect OBPs with high peak intensity containing 18O and heteroatoms (N, S) were fragmented with CID FT-ICR-MS/MS and screened for indicative neutral losses carrying heavy oxygen. The neutral loss screening was used to detect the 18O location on the OBP and indicate the original functional group in EfOM based on known reaction mechanisms. We identified sulfoxide and sulfonic acid functional groups in selected OBPs - implying the presence of reduced sulfur in EfOM molecules - while no evidence for nitrogen containing functional groups reacting with ozone was found.

The effect of root hairs on exudate composition: a comparative non-targeted metabolomics approach.

Root exudation is a major pathway of organic carbon input into soils. It affects soil physical properties, element solubility as well as speciation, and impacts the microbial community in the rhizosphere. Root exudates contain a large number of primary and secondary plant metabolites, and the amount and composition are highly variable depending on plant species and developmental stage. Detailed information about exudate composition will allow for a better understanding of exudate-driven rhizosphere processes and their feedback loops. Although non-targeted metabolomics by high-resolution mass spectrometry is an established tool to characterize root exudate composition, the extent and depth of the information obtained depends strongly on the analytical approach applied. Here, two genotypes of Zea mays L., differing in root hair development, were used to compare six mass spectrometric approaches for the analysis of root exudates. Reversed-phase liquid chromatography and hydrophilic interaction liquid chromatography combined with time-of-flight mass spectrometry (LC-TOF-MS), as well as direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR-MS), were applied with positive and negative ionization mode. By using the same statistical workflow, the six approaches resulted in different numbers of detected molecular features, ranging from 176 to 889, with a fraction of 48 to 69% of significant features (fold change between the two genotypes of > 2 and p-value < 0.05). All approaches revealed the same trend between genotypes, namely up-regulation of most metabolites in the root hair defective mutant (rth3). These results were in agreement with the higher total carbon and nitrogen exudation rate of the rth3-mutant as compared to the corresponding wild-type maize (WT). However, only a small fraction of features were commonly found across the different analytical approaches (20-79 features, 13-31% of the rth3-mutant up-regulated molecular formulas), highlighting the need for different mass spectrometric approaches to obtain a more comprehensive view into the composition of root exudates. In summary, 111 rth3-mutant up-regulated compounds (92 different molecular formulas) were detected with at least two different analytical approaches, while no WT up-regulated compound was found by both, LC-TOF-MS and DI-FT-ICR-MS. Zea mays L. exudate features obtained with multiple analytical approaches in our study were matched against the metabolome database of Zea mays L. (KEGG) and revealed 49 putative metabolites based on their molecular formula.

Multi-Class Cancer Subtyping in Salivary Gland Carcinomas with MALDI Imaging and Deep Learning.

Salivary gland carcinomas (SGC) are a heterogeneous group of tumors. The prognosis varies strongly according to its type, and even the distinction between benign and malign tumor is challenging. Adenoid cystic carcinoma (AdCy) is one subgroup of SGCs that is prone to late metastasis. This makes accurate tumor subtyping an important task. Matrix-assisted laser desorption/ionization (MALDI) imaging is a label-free technique capable of providing spatially resolved information about the abundance of biomolecules according to their mass-to-charge ratio. We analyzed tissue micro arrays (TMAs) of 25 patients (including six different SGC subtypes and a healthy control group of six patients) with high mass resolution MALDI imaging using a 12-Tesla magnetic resonance mass spectrometer. The high mass resolution allowed us to accurately detect single masses, with strong contributions to each class prediction. To address the added complexity created by the high mass resolution and multiple classes, we propose a deep-learning model. We showed that our deep-learning model provides a per-class classification accuracy of greater than 80% with little preprocessing. Based on this classification, we employed methods of explainable artificial intelligence (AI) to gain further insights into the spectrometric features of AdCys.

Legacy Effects of Sorption Determine the Formation Efficiency of Mineral-Associated Soil Organic Matter.

Sorption of dissolved organic matter (DOM) is one major pathway in the formation of mineral-associated organic matter (MOM), but there is little information on how previous sorption events feedback to later ones by leaving their imprint on mineral surfaces and solutions ("legacy effect"). In order to conceptualize the role of legacy effects in MOM formation, we conducted sequential sorption experiments with kaolinite and gibbsite as minerals and DOM derived from forest floor materials. The MOM formation efficiency leveled off upon repeated addition of identical DOM solutions to minerals due to the retention of highly sorptive organic molecules (primarily aromatic, nitrogen-poor, hydrogen-poor, and oxygen-rich molecules), which decreased the sorption site availability and simultaneously modified the mineral surface charge. Organic-organic interactions as postulated in multilayer models played a negligible role in MOM formation. Continued exchange between DOM and MOM molecules upon repeated sorption altered the DOM composition but not the MOM formation efficiencies. Sorption-induced depletion of high-affinity compounds from solutions further decreased the MOM formation efficiencies to pristine minerals. Overall, the interplay between the differential sorptivities of DOM components and the mineral surface chemistry explains the legacy effects that contribute to the regulation of fluxes and the distribution of organic matter in the soil.

Discovery of Polar Ozonation Byproducts via Direct Injection of Effluent Organic Matter with Online LC-FT-ICR-MS.

Effluent organic matter (EfOM), a major ozone consumer during wastewater ozonation, is a complex mixture of natural and anthropogenic organic molecules. Ozonation of EfOM adds to molecular complexity by introducing polar and potentially mobile ozonation byproducts (OBPs). Currently, nontargeted direct infusion (DI) ultrahigh resolution mass spectrometry (e.g. FT-ICR-MS) is used to study OBPs but requires sample extraction, limiting the accessible polarity range of OBPs. To better understand the impact of ozonation on EfOM and the formation of polar OBPs, nonextracted effluent was analyzed by direct injection onto a reversed-phase liquid chromatography system (RP-LC) online hyphenated with an FT-ICR-MS. Over four times more OBPs were detected in nonextracted EfOM compared to effluent extracted with solid phase extraction and measured with DI-FT-ICR-MS (13817 vs 3075). Over 1500 highly oxygenated OBPs were detected exclusively in early eluting fractions of nonextracted EfOM, indicating polar OBPs. Oxygenation of these newly discovered OBPs is higher than previously found, with an average molecular DBE-O value of -3.3 and O/C ratio of 0.84 in the earliest eluting OBP fractions. These polar OBPs are consistently lost during extraction but may play an important role in understanding the environmental impact of ozonated EfOM. Moreover, 316 molecular formulas classified as nonreactive to ozone in DI-FT-ICR-MS can be identified with LC-FT-ICR-MS as isomers with varying degrees of reactivity, providing for the first time experimental evidence of differential reactivity of complex organic matter isomers with ozone.

Aromaticity Index with Improved Estimation of Carboxyl Group Contribution for Biogeochemical Studies.

Natural organic matter (NOM) components measured with ultrahigh-resolution mass spectrometry (UHRMS) are often assessed by molecular formula-based indices, particularly related to their aromaticity, which are further used as proxies to explain biogeochemical reactivity. An aromaticity index (AI) is calculated mostly with respect to carboxylic groups abundant in NOM. Here, we propose a new constrained AIcon based on the measured distribution of carboxylic groups among individual NOM components obtained by deuteromethylation and UHRMS. Applied to samples from diverse sources (coal, marine, peat, permafrost, blackwater river, and soil), the method revealed that the most probable number of carboxylic groups was two, which enabled to set a reference point n = 2 for carboxyl-accounted AIcon calculation. The examination of the proposed AIcon showed the smallest deviation to the experimentally determined index for all NOM samples under study as well as for individual natural compounds obtained from the Coconut database. In particular, AIcon performed better than AImod for all compound classes in which aromatic moieties are expected: aromatics, condensed aromatics, and unsaturated compounds. Therefore, AIcon referenced with two carboxyl groups is preferred over conventional AI and AImod for biogeochemical studies where the aromaticity of compounds is important to understand the transformations and fate of NOM compounds.

Direct Imaging of Plant Metabolites in the Rhizosphere Using Laser Desorption Ionization Ultra-High Resolution Mass Spectrometry.

The interplay of rhizosphere components such as root exudates, microbes, and minerals results in small-scale gradients of organic molecules in the soil around roots. The current methods for the direct chemical imaging of plant metabolites in the rhizosphere often lack molecular information or require labeling with fluorescent tags or isotopes. Here, we present a novel workflow using laser desorption ionization (LDI) combined with mass spectrometric imaging (MSI) to directly analyze plant metabolites in a complex soil matrix. Undisturbed samples of the roots and the surrounding soil of Zea mays L. plants from either field- or laboratory-scale experiments were embedded and cryosectioned to 100 µm thin sections. The target metabolites were detected with a spatial resolution of 25 µm in the root and the surrounding soil based on accurate masses using ultra-high mass resolution laser desorption ionization Fourier-transform ion cyclotron resonance mass spectrometry (LDI-FT-ICR-MS). Using this workflow, we could determine the rhizosphere gradients of a dihexose (e.g., sucrose) and other plant metabolites (e.g., coumaric acid, vanillic acid). The molecular gradients for the dihexose showed a high abundance of this metabolite in the root and a strong depletion of the signal intensity within 150 µm from the root surface. Analyzing several sections from the same undisturbed soil sample allowed us to follow molecular gradients along the root axis. Benefiting from the ultra-high mass resolution, isotopologues of the dihexose could be readily resolved to enable the detection of stable isotope labels on the compound level. Overall, the direct molecular imaging via LDI-FT-ICR-MS allows for the first time a non-targeted or targeted analysis of plant metabolites in undisturbed soil samples, paving the way to study the turnover of root-derived organic carbon in the rhizosphere with high chemical and spatial resolution.

Conditioning Film and Early Biofilm Succession on Plastic Surfaces.

In the context of environmental plastic pollution, it is still under debate if and how the "plastisphere", a plastic-specific microbial community, emerges. In this study, we tested the hypothesis that the first conditioning film of dissolved organic matter (DOM) sorbs selectively to polymer substrates and that microbial attachment is governed in a substrate-dependent manner. We investigated the adsorption of stream water-derived DOM to polyethylene terephthalate (PET), polystyrene (PS), and glass (as control) including UV-weathered surfaces by Fourier-transform ion cyclotron mass spectrometry. Generally, the saturated, high-molecular mass and thus more hydrophobic fraction of the original stream water DOM preferentially adsorbed to the substrates. The UV-weathered polymers adsorbed more polar, hydrophilic OM as compared to the dark controls. The amplicon sequencing data of the initial microbial colonization process revealed a tendency of substrate specificity for biofilm attachment after 24 h and a clear convergence of the communities after 72 h of incubation. Conclusively, the adsorbed OM layer developed depending on the materials' surface properties and increased the water contact angles, indicating higher surface hydrophobicity as compared to pristine surfaces. This study improves our understanding of molecular and biological interactions at the polymer/water interface that are relevant to understand the ecological impact of plastic pollution on a community level.

High concentrations of dissolved biogenic methane associated with cyanobacterial blooms in East African lake surface water.

The contribution of oxic methane production to greenhouse gas emissions from lakes is globally relevant, yet uncertainties remain about the levels up to which methanogenesis can counterbalance methanotrophy by leading to CH4 oversaturation in productive surface waters. Here, we explored the biogeochemical and microbial community variation patterns in a meromictic soda lake, in the East African Rift Valley (Kenya), showing an extraordinarily high concentration of methane in oxic waters (up to 156 µmol L-1). Vertical profiles of dissolved gases and their isotopic signature indicated a biogenic origin of CH4. A bloom of Oxyphotobacteria co-occurred with abundant hydrogenotrophic and acetoclastic methanogens, mostly found within suspended aggregates promoting the interactions between Bacteria, Cyanobacteria, and Archaea. Moreover, aggregate sedimentation appeared critical in connecting the lake compartments through biomass and organic matter transfer. Our findings provide insights into understanding how hydrogeochemical features of a meromictic soda lake, the origin of carbon sources, and the microbial community profiles, could promote methane oversaturation and production up to exceptionally high rates.

Online Counter Gradient LC-FT-ICR-MS Enables Detection of Highly Polar Natural Organic Matter Fractions.

Natural organic matter (NOM) is a highly complex mixture of natural organic molecules. The recent developments in NOM molecular characterization methods have shown that ESI-FT-ICR hyphenated with liquid chromatography (LC) is a promising approach to also obtain chemical information (such as polarity and molecular size) about NOM molecules. However, due to changing solvent composition during gradient elution in LC-FT-ICR-MS, ionization conditions also change throughout the chromatographic separation process. In this study, we applied a post-LC column counter gradient (CG) to ensure stable solvent conditions for transient ESI-MS signals. Suwanee River Fulvic Acid (SRFA) standard and a peat pore water were used as representative dissolved NOM samples for method development and validation. Our results show that in polar NOM fractions (which elute with <50% methanol) the TIC intensity and number of assigned molecular formulas were increased by 48% and 20%, as compared to the standard gradient (SG) method. Further application of a Q-isolation and selective ion accumulation for low abundance fractions revealed over 3 times more molecular formulas (especially for CHNO, CHOS, CHNOS formula classes) than in full scan mode. The number of detected highly polar NOM compounds (with elemental ratios H/C < 1, O/C > 0.6) were more than 20 times larger for CG-LC mode as compared to direct infusion (DI) (5715 vs 266 MF). We conclude that the application of a postcolumn counter gradient in LC-FT-ICR-MS analyses of NOM offers novel insight into the most polar fractions of NOM which are inaccessible in conventional DI measurements.

Improved Understanding of Dissolved Organic Matter Processing in Freshwater Using Complementary Experimental and Machine Learning Approaches.

Dissolved organic matter plays an important role in aquatic ecosystems and poses a major problem for drinking water production. However, our understanding of DOM reactivity in natural systems is hampered by its complex molecular composition. Here, we used Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) and data from two independent studies to disentangle DOM reactivity based on photochemical and microbial-induced transformations. Robust correlations of FT-ICR-MS peak intensities with chlorophyll a and solar irradiation were used to define 9 reactivity classes for 1277 common molecular formulas. Germany's largest drinking water reservoir was sampled for 1 year, and DOM processing in stratified surface waters could be attributed to photochemical transformations during summer months. Microbial DOM alterations could be distinguished based on correlation coefficients with chlorophyll a and often shared molecular features (elemental ratios and mass) with photoreactive compounds. In particular, many photoproducts and some microbial products were identified as potential precursors of disinfection byproducts. Molecular DOM features were used to further predict molecular reactivity for the remaining compounds in the data set based on a random forest model. Our method offers an expandable classification approach to integrate the reactivity of DOM from specific environments and link it to molecular properties and chemistry.

Refinement of Compound Aromaticity in Complex Organic Mixtures by Stable Isotope Label Assisted Ultrahigh-Resolution Mass Spectrometry.

Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) provides a unique opportunity for molecular analysis of natural complex mixtures. In many geochemical and environmental studies structure-propertry relations are based solely on the elemental compositional information. Several calculated parameters were proposed to increase reliability of structural attribution, among which aromaticity indices (AI and AImod) are widely used. Herein, we applied a combination of selective labeling reactions in order to obtain direct structural information on the individual components of lignin-derived polyphenolic material. Carboxylic (COOH), carbonyl (C═O), and hydroxyl (OH) groups were enumerated by esterification, reducing, and acetylation reactions, respectively, followed by FTICR MS analyses. Obtained information was enabled to constrain aromaticity accounting for the carbon skeleton only. We found that actual aromaticity of components may be both higher or lower than approximated values depending on the abundance of COOH, C═O, and OH groups. The results are of importance for the geochemical community studying terrestrial NOM with structural gradients.