Total mass difference statistics algorithm: a new approach to identification of high-mass building blocks in electrospray ionization Fourier transform ion cyclotron mass spectrometry data of natural organic matter

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.

Spatial and molecular variations in forest topsoil dissolved organic matter as revealed by FT-ICR mass spectrometry

Forest soils cover about 30 % of the Earth's land surface and play a fundamental role in the global cycle of organic matter. Dissolved organic matter (DOM), the largest active pool of terrestrial carbon, is essential for soil development, microbial metabolism and nutrient cycling. However, forest soil DOM is a highly complex mixture of tens of thousands of individual compounds, which is largely composed of organic matter from primary producers, residues from microbial process and the corresponding chemical reactions. Therefore, we need a detailed picture of molecular composition in forest soil, especially the pattern of large-scale spatial distribution, which can help us understand the role of DOM in the carbon cycle. To explore the spatial and molecular variations of DOM in forest soil, we choose six major forest reserves located in different latitudes ranging in China, which were investigated by Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS). Results show that aromatic-like molecules are preferentially enriched in DOM at high latitude forest soils, while aliphatic/peptide-like, carbohydrate-like, and unsaturated hydrocarbon molecules are preferentially enriched in DOM at low latitude forest soils, besides, lignin-like compounds account for the highest proportion in all forest soil DOM. High latitude forest soils have higher aromatic equivalents and aromatic indices than low latitude forest soils, which suggest that organic matter at higher latitude forest soils preferentially contain plant-derived ingredients and are refractory to degradation while microbially derived carbon is dominant in organic matter at low latitudes. Besides, we found that CHO and CHON compounds make up the majority in all forest soil samples. Finally, we visualized the complexity and diversity of soil organic matter molecules through network analysis. Our study provides a molecular-level understanding of forest soil organic matter at large scales, which may contribute to the conservation and utilization of forest resources.

NOMspectra: An Open-Source Python Package for Processing High Resolution Mass Spectrometry Data on Natural Organic Matter

The present study introduces NOMspectra, a Python package for processing high resolution mass spectrometry data on complex systems of natural organic matter (NOM). NOM is characterized by multicomponent composition reflected as thousands of signals producing very complex patterns in high resolution mass spectra. This complexity sets special demands on the methods of data processing used for analysis. The developed NOMspectra package offers a comprehensive workflow for processing, analyzing, and visualizing information-rich mass spectra of NOM and HS including algorithms for filtering spectra, recalibrating, and assigning elemental compositions to molecular ions. Additionally, the package includes functions for calculating various molecular descriptors and methods for data visualization. A graphical user interface (GUI) has been developed to make a user-friendly interface for the proposed package.

Formulae Differences Commence a Database for Interlaboratory Studies of Natural Organic Matter

Direct comparison of high-resolution mass spectrometry (HRMS) data acquired with different instrumentation or parameters remains problematic as the derived lists of molecular species via HRMS, even for the same sample, appear distinct. This inconsistency is caused by inherent inaccuracies associated with instrumental limitations and sample conditions. Hence, experimental data may not reflect a corresponding sample. We propose a method that classifies HRMS data based on the differences in the number of elements between each pair of molecular formulae within the formulae list to preserve the essence of the given sample. The novel metric, formulae difference chains expected length (FDCEL), allowed for comparing and classifying samples measured by different instruments. We also demonstrate a web application and a prototype for a uniform database for HRMS data serving as a benchmark for future biogeochemical and environmental applications. FDCEL metric was successfully employed for both spectrum quality control and examination of samples of various nature.

Untargeted metabolomic analysis by ultra-high-resolution mass spectrometry for the profiling of new Italian wine varieties

The chemical composition of wine samples comprises numerous bioactive compounds responsible for unique flavor and health-promoting properties. Thus, it's important to have a complete overview of the metabolic profile of new wine products in order to obtain peculiar information in terms of their phytochemical composition, quality, and traceability. To achieve this aim, in this work, a mass spectrometry-based phytochemical screening was performed on seven new wine products from Villa D'Agri in the Basilicata region (Italy), i.e., Aglianico Bianco, Plavina, Guisana, Giosana, Malvasia ad acino piccolo, Colata Murro and Santa Sofia. Ultra-high-resolution mass spectrometry data were processed into absorption mode FT-ICR mass spectra, in order to remove artifacts and achieve a higher resolution and lower levels of noise. Accurate mass-to-charge ratio (m/z) values were converted into putative elemental formulas. Therefore, 2D van Krevelen diagrams were used as a tool to obtain molecular formula maps useful to perform a rapid and more comprehensive analysis of the wine sample metabolome. The presence of important metabolite classes, i.e., fatty acid derivatives, amino acids and peptides, carbohydrates and phenolic derivatives, was assessed. Moreover, the comparison of obtained metabolomic maps revealed some differences among profiles, suggesting their employment as metabolic fingerprints. This study shed some light on the metabolic composition of seven new Italian wine varieties, improving their value in terms of related bioactive compound content. Moreover, different metabolomic fingerprints were obtained for each of them, suggesting the use of molecular maps as innovative tool to ascertain their unique metabolic profile.

Mass Difference Matching Unfolds Hidden Molecular Structures of Dissolved Organic Matter

Ultrahigh-resolution Fourier transform mass spectrometry (FTMS) has revealed unprecedented details of natural complex mixtures such as dissolved organic matter (DOM) on a molecular formula level, but we lack approaches to access the underlying structural complexity. We here explore the hypothesis that every DOM precursor ion is potentially linked with all emerging product ions in FTMS² experiments. The resulting mass difference (Δm) matrix is deconvoluted to isolate individual precursor ion Δm profiles and matched with structural information, which was derived from 42 Δm features from 14 in-house reference compounds and a global set of 11 477 Δm features with assigned structure specificities, using a dataset of ∼18 000 unique structures. We show that Δm matching is highly sensitive in predicting potential precursor ion identities in terms of molecular and structural composition. Additionally, the approach identified unresolved precursor ions and missing elements in molecular formula annotation (P, Cl, F). Our study provides first results on how Δm matching refines structural annotations in van Krevelen space but simultaneously demonstrates the wide overlap between potential structural classes. We show that this effect is likely driven by chemodiversity and offers an explanation for the observed ubiquitous presence of molecules in the center of the van Krevelen space. Our promising first results suggest that Δm matching can both unfold the structural information encrypted in DOM and assess the quality of FTMS-derived molecular formulas of complex mixtures in general.

Graph Properties of Mass-Difference Networks for Profiling and Discrimination in Untargeted Metabolomics

Untargeted metabolomics seeks to identify and quantify most metabolites in a biological system. In general, metabolomics results are represented by numerical matrices containing data that represent the intensities of the detected variables. These matrices are subsequently analyzed by methods that seek to extract significant biological information from the data. In mass spectrometry-based metabolomics, if mass is detected with sufficient accuracy, below 1 ppm, it is possible to derive mass-difference networks, which have spectral features as nodes and chemical changes as edges. These networks have previously been used as means to assist formula annotation and to rank the importance of chemical transformations. In this work, we propose a novel role for such networks in untargeted metabolomics data analysis: we demonstrate that their properties as graphs can also be used as signatures for metabolic profiling and class discrimination. For several benchmark examples, we computed six graph properties and we found that the degree profile was consistently the property that allowed for the best performance of several clustering and classification methods, reaching levels that are competitive with the performance using intensity data matrices and traditional pretreatment procedures. Furthermore, we propose two new metrics for the ranking of chemical transformations derived from network properties, which can be applied to sample comparison or clustering. These metrics illustrate how the graph properties of mass-difference networks can highlight the aspects of the information contained in data that are complementary to the information extracted from intensity-based data analysis.

PFAS Analysis with Ultrahigh Resolution 21T FT-ICR MS: Suspect and Nontargeted Screening with Unrivaled Mass Resolving Power and Accuracy

Per- and polyfluoroalkyl substances (PFASs) are a large family of thousands of chemicals, many of which have been identified using nontargeted time-of-flight and Orbitrap mass spectrometry methods. Comprehensive characterization of complex PFAS mixtures is critical to assess their environmental transport, transformation, exposure, and uptake. Because 21 tesla (T) Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) offers the highest available mass resolving power and sub-ppm mass errors across a wide molecular weight range, we developed a nontargeted 21 T FT-ICR MS method to screen for PFASs in an aqueous film-forming foam (AFFF) using suspect screening, a targeted formula database (C, H, Cl, F, N, O, P, S; ≤865 Da), isotopologues, and Kendrick-analogous mass difference networks (KAMDNs). False-positive PFAS identifications in a natural organic matter (NOM) sample, which served as the negative control, suggested that a minimum length of 3 should be imposed when annotating CF₂-homologous series with positive mass defects. We putatively identified 163 known PFASs during suspect screening, as well as 134 novel PFASs during nontargeted screening, including a suspected polyethoxylated perfluoroalkane sulfonamide series. This study shows that 21 T FT-ICR MS analysis can provide unique insights into complex PFAS composition and expand our understanding of PFAS chemistries in impacted matrices.

Constellation: An Open-Source Web Application for Unsupervised Systematic Trend Detection in High-Resolution Mass Spectrometry Data

The increasing popularity of high-resolution mass spectrometry has led to many custom software solutions to process, interpret, and reveal information from high-resolution mass spectra. Although there are numerous software packages for peak-picking, calibration, and formula-finding, there are additional layers of information available when it comes to detecting repeated motifs from polymers or molecules with repeating structures or products of chemical or biochemical transformations that exhibit systematic, serial chemical changes of mass. Constellation is an open-source, Python-based web application that allows the user first to expand their high-resolution mass data into the mass defect space, after which a trend finding algorithm is used for supervised or unsupervised detection of repeating motifs. Many adjustable parameters allow the user to tailor their trend-search to target particular chemical moieties or repeating units, or search for all potential motifs within certain limits. The algorithm has a built-in optimization routine to provide a good starting point for the main trend finding parameters before user customization. Visualization tools allow interrogation of the data and any trends/patterns to a highly specific degree and save publication-quality images directly from the interface. As Constellation is deployed as a web application, it is easily used by anyone with a web browser; no software download or high-powered computer is required, as computations are performed on a remote high-powered data server run by our group.

Inhibition of Class A β-Lactamase (TEM-1) by Narrow Fractions of Humic Substances

Antimicrobial resistance is a global threat. The use of biologically active natural products alone or in combination with the clinically proven antimicrobial agents might be a useful strategy to fight the resistance. The scientific hypotheses of this study were twofold: (1) the natural humic substances rich in dicarboxyl, phenolic, heteroaryl, and other fragments might possess inhibitory activity against β-lactamases, and (2) this inhibitory activity might be linked to the molecular composition of the humic ensemble. To test these hypotheses, we used humic substances (HS) from different sources (coal, peat, and soil) and of different fractional compositions (humic acids, hymatomelanic acids, and narrow fractions from solid-phase extraction) for inhibiting serine β-lactamase TEM-1. Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) was used to characterize the molecular composition of all humic materials used in this study. The kinetic assay with chromogenic substrate CENTA was used for assessment of inhibitory activity. The inhibition data have shown that among all humic materials tested, a distinct activity was observed within apolar fractions of hymatomelanic acid isolated from lignite. The decrease in the hydrolysis rate in the presence of most active fractions was 42% (with sulbactam-87%). Of particular importance is that these very fractions caused a synergistic effect (2-fold) for the combinations with sulbactam. Linking the observed inhibition effects to molecular composition revealed the preferential contribution of low-oxidized aromatic and acyclic components such as flavonoid-, lignin, and terpenoid-like molecules. The binding of single low-molecular-weight components to the cryptic allosteric site along with supramolecular interactions of humic aggregates with the protein surface could be considered as a major contributor to the observed inhibition. We believe that fine fractionation of hydrophobic humic materials along with molecular modeling studies on the interaction between humic molecules and β-lactamases might contribute to the development of novel β-lactamase inhibitors of humic nature.

Soil Organic Matter Characterization by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR MS): A Critical Review of Sample Preparation, Analysis, and Data Interpretation

The biogeochemical cycling of soil organic matter (SOM) plays a central role in regulating soil health, water quality, carbon storage, and greenhouse gas emissions. Thus, many studies have been conducted to reveal how anthropogenic and climate variables affect carbon sequestration and nutrient cycling. Among the analytical techniques used to better understand the speciation and transformation of SOM, Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS) is the only technique that has sufficient mass resolving power to separate and accurately assign elemental compositions to individual SOM molecules. The global increase in the application of FTICR MS to address SOM complexity has highlighted the many challenges and opportunities associated with SOM sample preparation, FTICR MS analysis, and mass spectral interpretation. Here, we provide a critical review of recent strategies for SOM characterization by FTICR MS with emphasis on SOM sample collection, preparation, analysis, and data interpretation. Data processing and visualization methods are presented with suggested workflows that detail the considerations needed for the application of molecular information derived from FTICR MS. Finally, we highlight current research gaps, biases, and future directions needed to improve our understanding of organic matter chemistry and cycling within terrestrial ecosystems.

Molecular Comparison of Solid-Phase Extraction and Liquid/Liquid Extraction of Water-Soluble Petroleum Compounds Produced through Photodegradation and Biodegradation by FT-ICR Mass Spectrometry

We apply two widely used extraction techniques, liquid/liquid extraction and solid-phase extraction with styrene-divinylbenzene polymer with a proprietary nonpolar surface priority pollutant (PPL) to water-soluble compounds generated through photodegradation and biodegradation of petroleum. We compare the molecular composition of bio- and photodegraded water-soluble organic (WSO) acids by 21 T negative-ion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). We highlight the compositional differences between the two extraction techniques for abiotic and biotic degradation processes and identify known toxic species (naphthenic acids) produced through hydrocarbon biodegradation identified by liquid/liquid extraction (LLE) that are not detected with solid-phase extraction (SPE) of the same sample. Photodegraded WSO compounds extracted by SPE-PPL correspond to species with higher O/C ratio and carbon number compared to LLE extracted compounds. Naphthenic acids, a recalcitrant class of nonaromatic carboxylic acids and known acute toxicants formed through biodegradation of oil, are detected in LLE extracts (up to C₃₀ and double-bond equivalents, DBE < 3) but are not detected in SPE-PPL extracts. This suggests that LLE and SPE-PPL retain different water-soluble oil species based on the dominant type of oil weathering process.

Antiviral activity of natural humic substances and shilajit materials against HIV-1: Relation to structure

Natural products, such as humic substances (HS) and shilajit, are known to possess antiviral activity. Humic-like components are often called as carriers of biological activity of shilajit. The goal of this study was to evaluate anti-HIV activity of well characterized HS isolated from coal, peat, and peloids, and compare it to that of water-soluble organic matter (OM) isolated from different samples of Shilajit. The set of humic materials included 16 samples of different fractional composition: humic acid (HA), hymatomelanic acid (HMA), fulvic acid (FA). The set of shilajit OM included 19 samples of different geographic origin and level of alteration. The HIV-1 p24 antigen assay and cell viability test were used for assessment of antiviral activity. The HIV-1 Bru strain was used to infect CEM-SS cells. The obtained EC50 values varied from 0.37 to 1.4 mg L^-1 for the humic materials, and from 14 to 142 mg L^-1 for the shilajit OM. Hence, all humic materials used in this study outcompeted largely the shilajit materials with respect to anti-HIV activity: For the humic materials, the structure-activity relationships revealed strong correlation between the EC50 values and the content of aromatic carbon indicating the most important role of aromatic structures. For shilajit OM, the reverse relationship was obtained indicating the different mechanism of shilajit activity. The FTICRMS molecular assignments were used for ChEMBL data mining in search of the active humic molecules. As potential carriers of antiviral activity were identified aromatic structures with alkyl substituents, terpenoids, N-containing analogs of typical flavonoids, and aza-podophyllotoxins. The conclusion was made that the typical humic materials and Shilajit differ greatly in molecular composition, and the humic materials have substantial preferences as a natural source of antiviral agents as compared to shilajit.

MFAssignR: Molecular formula assignment software for ultrahigh resolution mass spectrometry analysis of environmental complex mixtures

Ultrahigh resolution mass spectrometry is widely used for nontargeted analysis of complex environmental and biological mixtures, such as dissolved organic matter, due to its unparalleled ability to provide accurate mass measurements. Accurate and efficient characterization of these mixtures is critical to being better able to evaluate their effect on human health and climate. This characterization requires accurate mass signals free from isobaric interferences, instrument noise, and mass measurement biases, allowing for molecular formula identification. To address this need, an open source post-processing pipeline for ultrahigh resolution mass spectra of environmental complex mixtures software was developed. MFAssignR contains functions that perform noise estimation, ¹³C and ³⁴S polyisotopic mass filtering, mass measurement recalibration, and molecular formula assignment as part of a consistent data processing environment. Novel applications of mass defect analysis were used in the functions for noise estimation and isotope pair identification. Using formula extensions, exact mass measurements are converted to unambiguous molecular formulas via data dependent pathways, reducing a priori decisions. Optional molecular formula ambiguity and multiple non-oxygen heteroatoms are provided for custom user applications, including isotopically labeled reactive species, halogen-containing species, or tandem ultrahigh resolution mass spectrometry. This represents uncommon flexibility for an open-source software package. To evaluate the performance of MFAssignR, it was used to characterize a sample of biomass burning influenced organic aerosol and the results were compared to those from other available methods of molecular formula assignment and noise estimation. The differences between the methods are described here. Overall, the inclusion of a full pipeline of data preparation functions and the data-dependent ambiguity reductions in MFAssignR render excellent results and make MFAssignR well-suited for the consistent and efficient analysis of environmental complex mixtures. MFAssignR is publicly available via GitHub.

Photoreactivity of humic-like polyphenol material under irradiation with different wavelengths explored by FTICR MS and deuteromethylation

The goal of this study was to establish reactivity of lignin-derived synthetic polyphenolic material under irradiation by ultraviolet (254 nm) and visible (460 and 525 nm) light in order to deeper examine relationships between the optical properties of this complex mixture and its individual constituents. In all photoirradiation experiments, blue shift of the fluorescence spectrum was observed. We aimed at understanding whether these changes could be explained on the basis of the chromophore interactions hypothesis, which implies destruction of electron-acceptor pairs via free radical transformations to be responsible for the alteration of optical properties. For this, changes in molecular composition were explored by Fourier transform ion cyclotron resonance mass spectrometry. Irradiation with UV resulted in a pronounced oxidation of polyphenols, which was manifested in the van Krevelen diagram by the formation of components with higher O/C ratio. At the same time, irradiation by visible light had led to the appearance of more condensed molecules depleted of oxygen. Consideration of changes in relative contribution of 500 most abundant components in polyphenol materials revealed higher transformation yields under UV light as compared to the visible light. Further studies using deuteromethylation followed by Fourier transform ion cyclotron resonance mass spectrometry enabled to enumerate the number of carboxylic groups in individual components of the parent polyphenol material. It was shown that at all wavelengths irradiation mainly impacted carboxylic-rich unsaturated and aromatic compounds, which can be considered as strong electron-acceptors. We suggest that their transformation is responsible for the blue shift of fluorescence spectrum, thus emphasizing the role of chromophore interaction mechanism of the optical properties formation.

Optical Properties of Soil Dissolved Organic Matter Are Related to Acidic Functions of Its Components as Revealed by Fractionation, Selective Deuteromethylation, and Ultrahigh Resolution Mass Spectrometry

The goal of this study was to establish a relationship between the optical properties of soil dissolved organic matter (DOM) and acidic functions carried out by its individual constituents. We obtained 12 fractions of DOM samples using sequential solid phase extraction on nonionic sorbent at steadily lowered pH values: 7, 5, 3, 2, which correspond to low bounds of pK_a values of phenols, aliphatic, and aromatic carboxylic acids, and ketoacids. The structural studies were conducted with the use of NMR and selective deuteromethylation of isolated fractions coupled to ultrahigh resolution mass spectrometry. First, a gradual shift of molecular compositions was observed from reduced components to aromatic oxidized compounds isolated at pH 7 and 2, respectively. Changes in molecular compositions were accompanied by a red shift of fluorescence spectra. Further application of deuteromethylation enabled us to distinguish DOM constituents with different amounts of carboxylic groups. Moreover, identification of structural isomers in a single DOM sample was achieved. Statistical analysis revealed that red shift of fluorescence is facilitated by the increase of a contribution of aromatic poly(carboxylic acid)s with high conjugation lengths. Additionally, analysis of the labeled fractionated permafrost thaw DOM directly showed carboxyl-rich alicyclic molecules, while the same components from lower-latitude DOM were assigned to lignin-like species.

Signatures of Molecular Unification and Progressive Oxidation Unfold in Dissolved Organic Matter of the Ob-Irtysh River System along Its Path to the Arctic Ocean

The Ob-Irtysh River system is the seventh-longest one in the world. Unlike the other Great Siberian rivers, it is only slightly impacted by the continuous permafrost in its low flow. Instead, it drains the Great Vasyugan mire, which is the world largest swamp, and receives huge load of the Irtysh waters which drain the populated lowlands of the East Siberian Plain. The central challenge of this paper is to understand the processes responsible for molecular transformations of natural organic matter (NOM) in the Ob-Irtysh river system along the South-North transect. For solving this task, the NOM was isolated from the water samples collected along the 3,000 km transect using solid-phase extraction. The NOM samples were further analyzed using high resolution mass spectrometry and optical spectroscopy. The obtained results have shown a distinct trend both in molecular composition and diversity of the NOM along the South-North transect: the largest diversity was observed in the Southern "swamp-wetland" stations. The samples were dominated with humic and lignin-like components, and enriched with aminosugars. After the Irtysh confluence, the molecular nature of NOM has changed drastically: it became much more oxidized and enriched with heterocyclic N-containing compounds. These molecular features are very different from the aliphatics-rich permafrost NOM. They witnesses much more conservative nature of the NOM discharged into the Arctic by the Ob-Irtysh river system. In general, drastic reduction in molecular diversity was observed in the northern stations located in the lower Ob flow.

Structural investigation of coal humic substances by selective isotopic exchange and high-resolution mass spectrometry

Here, we report the application of a selective liquid-phase hydrogen/deuterium exchange (HDX) coupled to ultra-high resolution FTICR MS for structural investigations of individual constituents of humic substances (HS) isolated from three coal samples of different geographical origin. Selectivity was achieved by conducting reactions in DCl or NaOD solutions for catalyzing HDX in aromatic ring and side-chain positions with enhanced C-H acidity, respectively. FTICR MS analysis showed a significant overlap of molecular compositions in the HS samples under study, with 2000 common formulae. Using HDX, we demonstrated that the determined common formulae are presented by different structural isomers. We found that aromatic compounds varied both in the substitution pattern and the number of aromatic protons. Depending on the sample, lignin components with the same molecular formulae were composed of coumaryl, coniferyl or sinapyl moieties. Enumeration of HDX series for the 800 most abundant compounds showed that the results of HDX agreed well with the model structures suggested for humic components occupying a van Krevelen plot. In addition, we explored chemical transformations, which could connect individual constituents of coal HS. These transformations included hydrolysis of a guaiacyl moiety and reduction of a catechol unit, which corresponds to the conversion of a coniferyl fragment into a coumaryl unit. The obtained results were supportive of the hypothesis of the reducing humification pathway suggested for lignin transformation in the environment. The conclusion was made that the molecular ensemble of coal HS is composed of individual constituents produced at different humification stages.

Rigorous Physicochemical Framework for Metal Ion Binding by Aqueous Nanoparticulate Humic Substances: Implications for Speciation Modeling by the NICA-Donnan and WHAM Codes

Latest knowledge on the reactivity of charged nanoparticulate complexants toward aqueous metal ions is discussed in mechanistic detail. We present a rigorous generic description of electrostatic and chemical contributions to metal ion binding by nanoparticulate complexants, and their dependence on particle size, particle type (i.e., reactive sites distributed within the particle body or confined to the surface), ionic strength of the aqueous medium, and the nature of the metal ion. For the example case of soft environmental particles such as fulvic and humic acids, practical strategies are delineated for determining intraparticulate metal ion speciation, and for evaluating intrinsic chemical binding affinities and heterogeneity. The results are compared with those obtained by popular codes for equilibrium speciation modeling (namely NICA-Donnan and WHAM). Physicochemical analysis of the discrepancies generated by these codes reveals the a priori hypotheses adopted therein and the inappropriateness of some of their key parameters. The significance of the characteristic time scales governing the formation and dissociation rates of metal-nanoparticle complexes in defining the relaxation properties and the complete equilibration of the metal-nanoparticulate complex dispersion is described. The dynamic features of nanoparticulate complexes are also discussed in the context of predictions of the labilities and bioavailabilities of the metal species.

UltraMassExplorer: a browser-based application for the evaluation of high-resolution mass spectrometric data

RATIONALE

High-resolution mass spectrometry (HRMS) with high sample throughput has become an important analytical tool for the analysis of highly complex samples and data processing has become a major challenge for the user community. Evaluating direct-infusion HRMS data without automated tools for batch processing can be a time-consuming step in the analytical pipeline. Therefore, we developed a new browser-based software tool for processing HRMS data.

METHODS

The software, named UltraMassExplorer (UME), was written in the R programming language using the shiny library to build the graphical user interface. The performance of the integrated formula library search algorithm was tested using HRMS data derived from analyses of up to 50 extracts of marine dissolved organic matter.

RESULTS

The software supports the processing of lists of calibrated masses of neutral, protonated or deprotonated molecules, with masses of up to 700 Da and a mass accuracy <3 ppm. In the performance test, the number of assigned peaks per second increased with the number of submitted peaks and reached a maximum rate of 4745 assigned peaks per second.

CONCLUSIONS

UME offers a complete data evaluation pipeline comprising a fast molecular formula assignment algorithm allowing for the swift reanalysis of complete datasets, advanced filter functions and the export of data, metadata and publication-quality graphics. Unique to UME is a fast and interactive connection between data and their visual representation. UME provides a new platform enabling an increased transparency, customization, documentation and comparability of datasets.

Separation of Benzoic and Unconjugated Acidic Components of Leonardite Humic Material Using Sequential Solid-Phase Extraction at Different pH Values as Revealed by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and Correlation Nuclear Magnetic Resonance Spectroscopy

Here, we report on sequential solid-phase extraction of leonardite hymatomelanic acid (CHM) on a non-ionic sorbent at four steadily lowered pH values: 7, 5, 3, and 2, yielding fractions with different acidic properties. Using nuclear magnetic resonance (NMR) spectroscopy and ultrahigh-resolution mass spectrometry, we revealed a gradual shift of dominating scaffolds in the fractions of CHM from reduced saturated to oxidized aromatic compounds. An increase on the average aromaticity of the CHM fractions was accompanied by a red shift in fluorescence spectra. These results were supported by heteronuclear single quantum coherence and heteronuclear multiple bond correlation NMR experiments. We have demonstrated that the CHM fraction isolated at pH 5 was dominated by aliphatic carboxyl carriers, while the pH 3 fraction was dominated by aromatic carboxyl acids. The developed fractionation technique will enable deeper insight on structure-property relationships and the design of the humic-based materials with tailored reactive properties.

Novel water-soluble lignin derivative BP-Cx-1: identification of components and screening of potential targets in silico and in vitro

Identification of molecular targets and mechanism of action is always a challenge, in particular – for natural compounds due to inherent chemical complexity. BP-Cx-1 is a water-soluble modification of hydrolyzed lignin used as the platform for a portfolio of innovative pharmacological products aimed for therapy and supportive care of oncological patients. The present study describes a new approach, which combines in vitro screening of potential molecular targets for BP-Cx-1 using Diversity Profile - P9 panel by Eurofins Cerep (France) with a search of possible active components in silico in ChEMBL - manually curated chemical database of bioactive molecules with drug-like properties. The results of diversity assay demonstrate that BP-Cx-1 has multiple biological effects on neurotransmitters receptors, ligand-gated ion channels and transporters. Of particular importance is that the major part of identified molecular targets are involved in modulation of inflammation and immune response and might be related to tumorigenesis. Characterization of molecular composition of BP-Cx-1 with Fourier Transform Ion Cyclotron Resonance Mass Spectrometry and subsequent identification of possible active components by searching for molecular matches in silico in ChEMBL indicated polyphenolic components, nominally, flavonoids, sapogenins, phenanthrenes, as the major carriers of biological activity of BP-Cx-1. In vitro and in silico target screening yielded overlapping lists of proteins: adenosine receptors, dopamine receptor DRD4, glucocorticoid receptor, serotonin receptor 5-HT1, prostaglandin receptors, muscarinic cholinergic receptor, GABAA receptor. The pleiotropic molecular activities of polyphenolic components are beneficial in treatment of multifactorial disorders such as diseases associated with chronic inflammation and cancer.

Synthesis of carboxylated styrene polymer for internal calibration of Fourier transform ion cyclotron resonance mass-spectrometry of humic substances

We report synthesis and application of the novel carboxylated styrene for internal calibration of Fourier transform ion cyclotron resonance mass-spectra of humic substances. The calibrant was synthesized in five steps from acetylsalicylic acid (aspirin) followed by spontaneous polymerization of vinyl salicylic acid. Aromatic nature of the prepared polymer enabled its simultaneous analysis in the presence of the Suwannee River fulvic acid without using dual-spray approach. The major advantage of the calibrant proposed in this study is a lack of suppression of humic substances signals and maintenance of peak intensity distribution. The appropriate calibration resulted in an increased number of unambiguous identification in Suwannee River fulvic acid. Thanks to the higher mass accuracy, it was also possible to refine attribution of the CHOS species to hydrolysable tannins as opposed to the erroneous previous assignment to the condensed tannins.

Photochemically Induced Bound Residue Formation of Carbamazepine with Dissolved Organic Matter

More than 400 new nitrogen containing products were detected upon experimental sunlight photolysis of the pharmaceutical carbamazepine (CBZ) in the presence of dissolved organic matter (DOM) by Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). These products were presumably formed through covalent binding of CBZ phototransformation products with DOM molecules. About 50% of these newly formed bound residues contained one nitrogen atom and had a molecular mass between 375 and 525 Da, which was 150 to 200 Da higher than for an average DOM molecule. In addition, a previously unknown CBZ phototransformation product, 3-quinolinecarboxylic acid (3-QCA), was identified by liquid chromatography high resolution tandem mass spectrometry (LC-HRMS/MS). 3-QCA was likely formed through oxidative ring cleavage and subsequent decarboxylation of acridine, a well-known phototransformation product of CBZ. Collision induced dissociation experiments and Kendrick mass defect analyses corroborated that about 160 of the new products were formed via covalent binding of 3-QCA with DOM molecules of above-average O/C and H/C ratios. Experiments at lower CBZ concentration suggested that the importance of bound residue formation increases with increasing DOM/CBZ ratios. Photochemically induced bound residue formation of polar contaminants with DOM in the aqueous phase is thus a disregarded pathway along which contaminants can be transformed in the environment. The method presented here offers a new possibility to study the formation of bound residues, which may be of relevance also for other transformation processes in natural waters where radical intermediates are generated.

Nontargeted homologue series extraction from hyphenated high resolution mass spectrometry data

BACKGROUND

A large proportion of polar anthropogenic compounds routinely released into the environment comprises homologue series, i.e., sets of chemicals differing in a repeating chemical unit. Using analytical techniques such as liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS), these compounds are readily measurable as signal sets with characteristic differences in mass and typically retention time. However, and despite such distinct characteristics, no computational approach for the direct, simultaneous and untargeted detection of all such signal sets comprising both LC and HRMS information has to date been presented.

RESULTS

A fast two-staged approach has been developed to extract LC-HRMS signal patterns which can be indicative of homologous analytes. In a first stage, a k-d tree representation of picked LC-HRMS peaks is used to extract all feasible 3-tuples of peaks with restrictions in, e.g., mass defect differences. A second stage then recombines these 3-tuples to larger series tuples while ensuring smooth changes in their retention time characteristics. This unsupervised approach was evaluated for ten effluent samples from Swiss sewage treatment plants (STPs), in both positive and negative electrospray-ionization.

CONCLUSIONS

Beside recovering all continuous series of previously identified homologues, substantial fractions of nontargeted peaks could subsequently be assigned into very diverse peak series, although assignments were often not unique. The latter ambiguities were resolved by a self-organizing map technique and revealed both distinctive series meshing and rivaling combinatorial solutions in the presence of isobaric or gapped series peaks. When comparing STPs, several ubiquitous yet partially low-frequent series mass differences emerged and may prioritize future identification efforts. The presented algorithm is freely available as part of the R package nontarget and as a user-friendly web-interface at www.envihomolog.eawag.ch.Graphical AbstractSearch for systematic series indicative of homologous compounds is based on a partitioned representation of LC-HRMS signal characteristics. This nontargeted search first extracts series triplets in a nearest-neighbour walk and then recombines them to larger ones. For illustration, the two dimensions involving mass defect characteristics are represented by one only.

Enumeration of carboxyl groups carried on individual components of humic systems using deuteromethylation and Fourier transform mass spectrometry

Here, we report a novel approach to enumeration of carboxylic groups carried by individual molecules of humic substances using selective chemical modification and isotopic labeling (deuteromethylation) and high-resolution electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI FTICR MS). Esterification was conducted with a use of thionyl chloride-deuteromethanol reagent under mild conditions to avoid transesterification. The deuteromethylated products were subjected to solid phase extraction using PPL Bond Elute cartridges prior to FTICR MS analysis. An amount of carboxyl groups in the individual molecular component was estimated from the length of identified deuteromethylation series. The method allowed for discerning between compounds with close elemental compositions possessing different protolytic properties. We found that different carboxylic moieties occupy distinct regions in molecular space of humic substances (HS) projected onto Van Krevelen diagram. These locations do not depend on the source of the humic material and can be assigned to carboxyl-rich alicyclic molecules (5 to 6 COOH), hydrolyzable tannins (3-4 COOH), lignins (1 to 2 COOH), condensed tannins and lignans (0 to 1 COOH), and carbohydrates (0 COOH). At the same time, the alignment pattern of these carboxylated species along the structural evolution lines in Van Krevelen diagrams was characteristic to the specific transformation processes undergone by the humic materials in the different environments. The obtained data enable mapping of molecular ensemble of HS with regards to their specific acidic compartments and might be used for directed fractionation of HS. Graphical abstract Selective isotopic labeling followed by FTICR MS enables discerning between humic molecules with close elemental compositions carrying different numbers of carboxylic groups.

Using network analysis to discern compositional patterns in ultrahigh-resolution mass spectrometry data of dissolved organic matter

RATIONALE

Marine dissolved organic matter (DOM) has long been recognized as a large and dynamic component of the global carbon cycle. Yet, DOM is chemically varied and complex and these attributes present challenges to researchers interested in addressing questions about the role of DOM in global biogeochemical cycles.

METHODS

Organic matter extracts from seawater were analyzed by direct infusion with electrospray ionization into a Fourier transform ion cyclotron resonance mass spectrometer. Network analysis was used 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 DOM.

RESULTS

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.

CONCLUSIONS

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 DOM. Copyright © 2016 John Wiley & Sons, Ltd.

The Role of Ultrahigh Resolution Fourier Transform Mass Spectrometry (FT-MS) in Astrobiology-Related Research: Analysis of Meteorites and Tholins

It is an important but also a challenging analytical problem to understand the chemical composition and structure of prebiotic organic matter that is present in extraterrestrial materials. Its formation, evolution and content in the building blocks ("seeds") for more complex molecules, such as proteins and DNA, are key questions in the field of exobiology. Ultrahigh resolution mass spectrometry is one of the best analytical techniques that can be applied because it provides reliable information on the chemical composition and structure of individual components of complex organic mixtures. Prebiotic organic material is delivered to Earth by meteorites or generated in laboratories in simulation (model) experiments that mimic space or atmospheric conditions. Recent representative examples for ultrahigh resolution mass spectrometry studies using Fourier-transform (FT) mass spectrometers such as Orbitrap and ion cyclotron resonance (ICR) mass spectrometers are shown and discussed in the present article, including: (i) the analysis of organic matter of meteorites; (ii) modeling atmospheric processes in ICR cells; and (iii) the structural analysis of laboratory made tholins that might be present in the atmosphere and surface of Saturn's largest moon, Titan.

Synthesis of model humic substances: a mechanistic study using controllable H/D exchange and Fourier transform ion cyclotron resonance mass spectrometry

The products of the oxidative coupling of phenols are frequently used as synthetic analogues to natural humic substances (HS) for biomedical research. However, their molecular compositions and exact structures remain largely unknown. The objective of this study was to develop a novel approach for the molecular-level analysis of phenolic polymerisates that is capable of inventorying molecular constituents and resolving their distinct structural formulas. For this purpose, we have synthesized the model HS using the oxidative coupling of a specifically designed phenylpropanoic monomer, 3-(4-hydroxy-3-methoxyphenyl)-3-oxopropionic acid, to hydroquinone. We have characterized the synthesized model HS using high resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR MS), (1)H NMR spectroscopy, and controllable hydrogen/deuterium (H/D) exchange. We succeeded in the molecular inventory of the model HS. The assigned molecular formulas occupied the substantial space of CHO compositions in the Van Krevelen diagram with a maximum density found in the regions of tannins and lignins, resembling those of natural HS. To identify the exact structural formulas of the individual constituents in the model HS, we have applied selective H/D exchange of non-labile backbone protons by a choice of basic or acidic catalytic conditions followed by FTICR MS. The determined formulas allowed us to verify the proposed pathways of hydroxylation and carboxylation in the course of the phenolic coupling and to identify the acetylation of aromatic rings as an important side reaction. We conclude that the proposed analytical approach may be used to identify the molecular carriers of biological activity within the phenolic polymerisates and eventually within natural HS.

Atmospheric Oxidation of Squalene: Molecular Study Using COBRA Modeling and High-Resolution Mass Spectrometry

Squalene is a major component of skin and plant surface lipids and is known to be present at high concentrations in indoor dust. Its high reactivity toward ozone makes it an important ozone sink and a natural protectant against atmospheric oxidizing agents. While the volatile products of squalene ozonolysis are known, the condensed-phase products have not been characterized. We present an analysis of condensed-phase products resulting from an extensive oxidation of squalene by ozone probed by electrospray ionization (ESI) high-resolution mass spectrometry (HR-MS). A complex distribution of nearly 1300 peaks assignable to molecular formulas is observed in direct infusion positive ion mode ESI mass spectra. The distribution of peaks in the mass spectra suggests that there are extensive cross-coupling reactions between hydroxy-carbonyl products of squalene ozonolysis. To get additional insights into the mechanism, we apply a Computational Brewing Application (COBRA) to simulate the oxidation of squalene in the presence of ozone, and compare predicted results with those observed by the HR-MS experiments. The system predicts over one billion molecular structures between 0 and 1450 Da, which correspond to about 27 000 distinct elemental formulas. Over 83% of the squalene oxidation products inferred from the mass spectrometry data are matched by the simulation. The simulation indicates a prevalence of peroxy groups, with hydroxyl and ether groups being the second-most important O-containing functional groups formed during squalene oxidation. These highly oxidized products of squalene ozonolysis may accumulate on indoor dust and surfaces and contribute to their redox capacity.

A Novel and Intuitive Method of Displaying and Interacting with Mass Difference Information: Application to Oligonucleotide Drug Impurities

A new method is presented for determining relationships between components in complex analytical systems. The method uses the mass differences between peaks in high resolution electrospray ionization (ESI) mass spectra. It relates peaks that share common mass differences. The method is based on the fundamental assumption that peaks in the spectra having the same exact mass difference are related by the same chemical moiety/substructure. Moreover, the presence (or absence/loss) of the same chemical moiety from a series of molecules may reflect similarities in the mechanisms of formation of each molecule. The determined mass differences in the spectra are used to automatically differentiate the types of components in the samples. Contour plots and summary plots of the summed total ion signal as a function of the mass difference are generated, which form powerful tools for the rapid and automated determination of the components in the samples and for comparisons with other samples. For the first time, in this work a unique profile contour plot has been developed that permits the interactive interrogation of the mass range by mass difference data matrix to obtain valuable information about components that share a common mechanism of formation, and all possible mechanisms of formation linked to a selected precursor molecule. The method can be used as an additional and complementary method to the existing analytical methods to determine relationships between components in complex chemical systems.

Molecular mapping of sorbent selectivities with respect to isolation of Arctic dissolved organic matter as measured by Fourier transform mass spectrometry

The objectives of this study were to identify molecular features characteristic to arctic DOM from the Kolyma River basin and to elucidate structural imprints induced by a choice of the sorption technique. To achieve this goal, DOM was isolated from the Kolyma River basin with a use of three nonionic sorbents: Amberlite XAD-8 resin, PPL- and C18 - SPE cartridges, and one anion exchanging resin-diethylaminoethyl (DEAE) -cellulose. The structural studies were conducted with a use of electrospray ionization Fourier Transform Ion Cyclotron Resonance (ESI FT-ICR) mass spectrometry and liquid state (1)H NMR spectroscopy. The DOM isolates obtained with a use of PPL and C18 cartridges were characterized with higher content of aliphatic compounds as compared to XAD-8 and DEAE-isolates. In total, for all arctic DOM isolates we observed predominance of hydrogen saturated compounds with high H/C values of identified formulas from FT-ICR MS data. (1)H NMR spectroscopy studies have confirmed this trend and revealed high contribution of alkyl-chain protons into the spectral density of the arctic DOM reaching 43% for PPL isolates.

Analysis of aquatic-phase natural organic matter by optimized LDI-MS method

The composition and physiochemical properties of aquatic-phase natural organic matter (NOM) are most important problems for both environmental studies and water industry. Laser desorption/ionization (LDI) mass spectrometry facilitated successful examinations of NOM, as humic and fulvic acids in NOM are readily ionized by the nitrogen laser. In this study, hydrophobic NOMs (HPO NOMs) from river, reservoir and waste water were characterized by this technique. The effect of analytical variables like concentration, solvent composition and laser energy was investigated. The exact masses of small molecular NOM moieties in the range of 200-1200 m/z were determined in reflectron mode. In addition, spectra of post-source-decay experiments in this range showed that some compounds from different natural NOMs had the same fragmental ions. In the large mass range of 1200-15,000 Da, macromolecules and their aggregates were found in HPO NOMs from natural waters. Highly humic HPO exhibited mass peaks larger than 8000 Da. On the other hand, the waste water and reservoir water mainly had relatively smaller molecules of about 2000 Da. The LDI-MS measurements indicated that highly humic river waters were able to form large aggregates and membrane foulants, while the HPO NOMs from waste water and reservoir water were unlikely to form large aggregates.

Appropriate degree of trust: deriving confidence metrics for automatic peak assignment in high-resolution mass spectrometry

Techniques for deriving confidence metrics for the reliability of automatically assigned elemental formulas in complex spectra, from high-resolution mass spectrometers, are described. These metrics can help an analyst to place an appropriate degree of trust in the results obtained from automated spectral analysis of, for example, natural organic materials. To provide these metrics of confidence, common mass spectrometric tests for reliability of peak assignment (mass accuracy/error, relative ion abundance, and rings-plus-double-bonds equivalence) are combined with novel confidence metrics based on the interconnectivity and consistency of a mass difference or mass defect based peak inference network and on the confidence of the initial library matches. These are shown to provide improved peak assignment confidence over manual or simple automatic assignment methods.

Use of an artificial immune system derived method for the charge state assignment of small-molecule mass spectra

Knowing the charge state of an ion in a mass spectrum is crucial to being able to assign a formula to it. For many small-molecule peaks in complex mass spectra, the intensities of the isotopic peaks are too low to allow the charge state to be calculated from isotopic spacings, which is the basis of the conventional method of determining the charge state of an ion. A novel artificial intelligence derived method for identifying the charge state of ions, in the absence of any isotopic information or a series of charge states, has been developed using an artificial immune system approach. This technique has been tested against synthetic and real data sets and has proven successful in identifying the majority of multiply charged ions, thereby significantly improving the peak assignment rate and confidence.

An overview of the methods used in the characterisation of natural organic matter (NOM) in relation to drinking water treatment

Natural organic matter (NOM) is found in all surface, ground and soil waters. During recent decades, reports worldwide show a continuing increase in the color and NOM of the surface water, which has an adverse affect on drinking water purification. For several practical and hygienic reasons, the presence of NOM is undesirable in drinking water. Various technologies have been proposed for NOM removal with varying degrees of success. The properties and amount of NOM, however, can significantly affect the process efficiency. In order to improve and optimise these processes, the characterisation and quantification of NOM at different purification and treatment processes stages is important. It is also important to be able to understand and predict the reactivity of NOM or its fractions in different steps of the treatment. Methods used in the characterisation of NOM include resin adsorption, size exclusion chromatography (SEC), nuclear magnetic resonance (NMR) spectroscopy, and fluorescence spectroscopy. The amount of NOM in water has been predicted with parameters including UV-Vis, total organic carbon (TOC), and specific UV-absorbance (SUVA). Recently, methods by which NOM structures can be more precisely determined have been developed; pyrolysis gas chromatography-mass spectrometry (Py-GC-MS), multidimensional NMR techniques, and Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). The present review focuses on the methods used for characterisation and quantification of NOM in relation to drinking water treatment.

Kendrick-analogous network visualisation of ion cyclotron resonance Fourier transform mass spectra: improved options for the assignment of elemental compositions and the classification of organic molecular complexity

Here, we propose a novel computational and visual approach for the analysis of high field Fourier transform ion cyclotron resonance mass spectra (FTICR/MS) based on successive and multiple atomic and Kendrick analogous mass difference analyses. Compositional networks based on elemental compositions and functional networks based on selected functional groups equivalents enable improved assignment options of elemental composition and classification of organic complexity with tunable validation windows. The approach is demonstrated through the analysis of a 12T FTICR mass spectrum of an intricate water soluble extract of a secondary organic aerosol with a previously established abundance in CHNOS molecules.

Targeted and non-targeted boron complex formation followed by electrospray Fourier transform ion cyclotron mass spectrometry: a novel approach for identifying boron esters with natural organic matter

The formation of boron esters was investigated in peat-soluble humified materials with a detailed molecular-level description of boron-organic interactions. Thousands of individually baseline separated signals were obtained from the analysis of natural organic matter of peat samples, using Fourier transform ion cyclotron resonance mass spectrometry. This technique offers unsurpassed isotope-specific mass resolution that can lead to precise molecular formula assignments by means of mathematical data analysis and visualisation techniques, such as mass defect (Kendrick) or elemental ratio (van Krevelen) plots. The analysis of potential boron binding structures within the sample of natural organic matter was described based on prior results. Herein, we describe an algorithm that can be used to effectively distinguish and filter complexes through data obtained from boron-enriched systems with highly intricate mass spectra, such as natural organic matter.

Mass spectrometric characterization of black tea thearubigins leading to an oxidative cascade hypothesis for thearubigin formation

Thearubigins are the most abundant group of phenolic pigments found in black tea, accounting for an estimated 60-70% of the solids in a typical black tea infusion. Fifty years ago the term thearubigins was first introduced and to date the chemical nature of the thearubigins remains largely unresolved, if not mysterious, despite numerous attempts made to clarify their structure. Thearubigins isolated from 15 commercial black teas have been analyzed using a strategy combining standard chemical characterization along with a series of modern complementary mass spectrometry techniques, including MALDI-TOF-MS, FTICR-MS, LC/TOF-MS and LC/MS/MS. Fifteen molecular formulas have been matched to constituents of fresh tea leaf that have survived processing and 21 to dimeric transformation products such as theasinensins, theaflavins, theaflavates, theanaphthoquinones, theacitrins and oolongtheanins, which were further confirmed by ESI MS/MS. MALDI-TOF-MS data revealed an average of 5000 additional thearubigin components in the mass range between m/z 1000 to 2100 clearly defining the molecular weight range of the thearubigin fraction. Six selected samples have for the first time been analyzed by electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). FT-ICR-MS data revealed the presence of a maximum of 9428 peaks in the mass range 300 to 1000 m/z and molecular formulas were assigned to 1517 of them. Data interpretation strategies developed for petrolomics studies (van Krevelen and Kendrick analyses) have for the first time been applied to black tea thearubigins and a novel interpretation protocol has been developed to refine these procedures for the investigation of complex mixtures, leading to a novel hypothesis for the formation and structure of the black tea thearubigins named oxidative cascade hypothesis.