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

New Insights into the Seasonal Variation of DOM Quality of a Humic-Rich Drinking-Water Reservoir—Coupling 2D-Fluorescence and FTICR MS Measurements

Long-term changes in dissolved organic matter (DOM) quality, especially in humic-rich raw waters, may lead to intensive adaptions in drinking-water processing. However, seasonal DOM quality changes in standing waters are poorly understood. To fill this gap, the DOM quality of a German drinking water reservoir was investigated on a monthly basis by Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS) measurements and 2D fluorescence for 18 months. FTICR MS results showed seasonal changes of molecular formula (MF) intensities, indicating photochemical transformation of DOM as a significant process for DOM quality variation. For an assessment of the two humic-like components, identified by parallel factor analysis (PARAFAC) of excitation–emission matrices (EEM), their loadings were Spearman’s rank-correlated with the intensities of the FTICR MS-derived MF. One of the two PARAFAC components correlated to oxygenrich and relatively unsaturated MF identified as easily photo-degradable, also known as coagulants in flocculation processes. The other PARAFAC component showed opposite seasonal fluctuations and correlated with more saturated MF identified as photo-products with some of them being potential precursors of disinfection byproducts. Our study indicated the importance of elucidating both the chemical background and seasonal behavior of DOM if raw water-quality control is implemented by bulk optical parameters

Dissolved organic matter in continental hydro-geothermal systems: insights from two hot springs of the East African Rift valley

Little is known about the quantity and quality of dissolved organic matter (DOM) in waters from continental geothermal systems, with only a few reports available from the Yellowstone US National Park. In this study, we explored the chemodiversity of DOM in water samples collected from two geothermal hot springs from the Kenyan East African Rift Valley, a region extremely rich in fumaroles, geysers, and spouting springs, located in close proximity to volcanic lakes. The DOM characterization included in-depth assessments performed by negative electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). Reduced, saturated and little aromatic DOM compounds were dominant in the hot spring waters collected from either the Ol Njorowa gorge (ON) or the south shore of the soda-saline Lake Elementaita (ELM). Oxygen-poor and sulfur-bearing DOM molecules prevailed in ON, probably reflecting abiotic sulfurization from sulfide-rich geofluids. Nitrogen-bearing aliphatic and protein-like molecules were abundant in ELM, possibly perfusing through the organic-rich sediments of the adjacent Lake Elementaita. Notably, the heat-altered DOM of ancient autochthonous derivation could represent an overlooked source of aliphatic organic carbon for connected lentic environments, with a potential direct impact on nutrient cycling in lakes that receive geothermal water inputs

Calculating density of water in geochemical lake stratification models

To model chemically stratified lakes numerically, chemical transformations must be reflected in the density function. In this contribution, partial molal volumes are used to calculate density from the chemical composition of lake water. Such values have been evaluated for cations and anions separately, to facilitate an easy implementation into geochemical stratification models for lakes. Coefficients for temperature dependence and variation for higher ionic strengths were evaluated from previously published data. An algorithm RHOMV to calculate density with a second order approximation for temperature dependence and ionic strength dependence is proposed. The accuracy is tested for seawater composition. We conclude that this approach delivers a representation of density based on the actual chemical composition of the lake water, which is accurate enough for most limnological purposes. The implementation of RHOMV into geochemical stratification models facilitates the numerical tackling of pressing questions, such as meromixis or double diffusive features or altered circulation patterns of lakes due to changing climate or change of use

Temporal graph model on DOM (tegrom)

<p>tegrom version from 20. october 2023</p>If you use this software, please cite it as below

High-Field FTICR-MS Data Evaluation of Natural Organic Matter: Are CHON₅S₂ Molecular Class Formulas Assigned to ¹³C Isotopic <i>m</i>/<i>z</i> and in Reality CHO Components?

The analysis of dissolved organic matter (DOM) using high-field Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) poses challenges in molecular formula assignment. The consideration of ¹³C isotopes provides new insights into the consistent elemental formula solutions. Modern software helps to overcome misinterpretation, but false assignments of molecular classes to mass peaks have rarely been elucidated until now. It will be demonstrated that this can be important with formula assignments comprising exactly five nitrogen and two sulfur atoms in DOM data sets: the molecular class CHON₅S₂. The existence of such components in DOM under tripeptide Met–His–Cys formed with the formula C₁₄H₂₃O₄N₅S₂ cannot be excluded; however, components containing 5 N and 2 S should be suspected to not be highly abundant. The true elemental compositions of such unusual “N₅S₂ moieties” were calculated using Suwannee River fulvic acid (SRFA) data from the literature and one data set from acidic pit lake pore water. The replacement of a H₃N₅S₂ moiety with a ¹³C₁¹²C₅O₄ moiety explained more than 95% of the questionable “N₅S₂ moieties”. This finding was proved by calculation of δ¹³C‰ values from relative peak intensities