Quantification, extractability and stability of dissolved domoic acid within marine dissolved organic matter

The widespread diatom Pseudo-nitzschia can produce domoic acid (DA). DA is a compound with well described neurotoxic effects on vertebrates including humans known as amnesic shellfish poisoning (ASP) syndrome. It has also been suggested to serve as an organic ligand that binds to iron and copper. By binding these trace elements, DA may increase their solubility and bioavailability. In order to serve this function, DA has to be excreted and reabsorbed by the cells. Only few records of dissolved domoic acid (dDA) concentrations in the ocean exist. To accomplish quantification by ultra performance liquid chromatography (UPLC), samples have to be pre-concentrated and desalted using solid-phase extraction, a procedure commonly applied for dissolved organic matter. Our major goals were to quantify dDA in a basin-wide assessment in the East Atlantic Ocean, to determine extraction efficiencies for complexed and uncomplexed dDA, and to assess whether domoic acid is represented by its molecular formula in direct-infusion high resolution mass spectrometry. Our results showed that dDA was extracted almost quantitatively and occurred ubiquitously in the ocean surface but also in deeper (and older) water, indicating surprisingly high stability in seawater. The maximum concentration measured was 173 pmol L−1 and the average molar dDA carbon yield was 7.7 ppm. Both carbon yield and dDA concentration decreased with increasing water depth. Providing quantification of dDA in the water column, we seek to improve our understanding of toxic bloom dynamics and the mechanistic understanding of DA production

Siderophore purification with titanium dioxide nanoparticle solid phase extraction

Siderophores are metal chelators produced by microorganisms to facilitate binding and uptake of iron. The isolation and characterization of siderophores are impeded by typically low siderophore yields and the complexity of siderophore-containing extracts generated with traditional purification methods. We investigated titanium dioxide nanoparticle solid-phase extraction (TiO2 NP SPE) as a technique to selectively concentrate and purify siderophores from complex matrices for subsequent LC-MS detection and identification. TiO2 NP SPE showed a high binding capacity (15.7 ± 0.2 μmol mg−1 TiO2) for the model siderophore desferrioxamine B (DFOB) and proved robust to pH changes and the presence of EDTA. These are significant advances in comparison to immobilized metal affinity chromatography (IMAC). The TiO2 NP SPE was highly selective and recovered 77.6 ± 6.2% of DFOB spiked to a compositionally complex bacterial culture supernatant. The simple clean-up procedure removed the majority of contaminants and allowed direct detection of siderophores from the LC-MS base peak chromatogram. The ‘untargeted’ purification and analysis of an untreated supernatant of iron-deprived bacterial culture allowed for the direct identification of two known and three novel ferrioxamines. Thus, TiO2 NP SPE in combination with LC-MS offers great potential as a discovery platform for the purification and subsequent quantification or identification of novel siderophores of microbial origin

Solid-Phase Extraction of Aquatic Organic Matter: Loading-Dependent Chemical Fractionation and Self-Assembly

Dissolved organic matter (DOM) is an important component in marine and freshwater environments and plays a fundamental role in global biogeochemical cycles. In the past, optical and molecular-level analytical techniques evolved and improved our mechanistic understanding about DOM fluxes. For most molecular chemical techniques, sample desalting and enrichment is a prerequisite. Solid-phase extraction has been widely applied for concentrating and desalting DOM. The major aim of this study was to constrain the influence of sorbent loading on the composition of DOM extracts. Here, we show that increased loading resulted in reduced extraction efficiencies of dissolved organic carbon (DOC), fluorescence and absorbance, and polar organic substances. Loading-dependent optical and chemical fractionation induced by the altered adsorption characteristics of the sorbent surface (styrene divinylbenzene polymer) and increased multilayer adsorption (DOM self-assembly) can fundamentally affect biogeochemical interpretations, such as the source of organic matter. Online fluorescence monitoring of the permeate flow allowed to empirically model the extraction process and to assess the degree of variability introduced by changing the sorbent loading in the extraction procedure. Our study emphasizes that it is crucial for sample comparison to keep the relative DOC loading (DOCload [wt %]) on the sorbent always similar to avoid chemical fractionation

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

Rational: 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, respectively, 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 number of submitted peaks and reached a maximum rate 4,745 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 its visual representation. UME provides a new platform enabling an increased transparency, customization, documentation and comparability of datasets

Selective purification of catecholate, hydroxamate and α-hydroxycarboxylate siderophores with titanium dioxide affinity chromatography

Siderophores, high affinity iron chelators, play a key role in the uptake of iron by microorganisms and regulate many biological functions. Siderophores are categorized by their chelating group, e.g., catecholates, hydroxamates, α-hydroxycarboxylates. Natural concentrations of siderophores are often either too low or sample matrices are too complex for direct analysis by, e.g., liquid chromatography – mass spectrometry. Therefore, both concentration and purification are prerequisite for reliable analyses. However, a chromatographic technique that is selective for all siderophore classes and affords high levels of purification is lacking. We developed a titanium dioxide affinity chromatography (TDAC) solid-phase extraction (SPE) that affords the selective purification of these siderophore classes from complex sample matrices with recoveries up to 82%. The one-step purification removed most non-ligand sample ‘contaminants’, therefore, affording the straightforward identification of siderophore peaks in base peak chromatograms. As a proof of concept, the bioinformatic processing, dereplication of known features and selection of significant features in the TDAC eluates afforded a fast identification of six novel siderophores (woodybactines) from bacterial supernatants. We propose TDAC SPE as a fast and cost-effective methodology to screen for known or discover novel siderophores in natural samples in combination with untargeted bioinformatic processing by, e.g., XCMS. The method is scalable and yielded large amounts of highly purified siderophores from bacterial culture supernatants, providing an effective quantitative sample clean-up for, e.g., NMR structure elucidation

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

ULTRAMASSEXPLORER: A BROWSER-BASED APPLICATION FOR THE EVALUATION OF HIGH RESOLUTION MASS SPECTROMETRIC DATA

In the evaluation of high-resolution mass spectrometric data a considerable amount of time and computational power can be spent on matching molecular formulas to the neutral mass of measured ions. During the evaluation of multiple samples using the classical combinatory approach based on molecular building blocks and nested loops, the time consuming step of calculating the molecular mass may be repeated for the same molecular formula multiple times. To avoid repetitive calculations, we implemented a formula library based search approach into our data evaluation pipeline. In our approach, the step of calculating molecular formulas and corresponding masses is limited to the process of building a library. The library calculation requires an a priori definition of the maximum molecular mass and the isotopes contained, e.g. formulas in the mass range of ≤ 650 Da consisting of 12C, 1H, 14N, 16O, 31P, 32S, 13C, and 34S. The subsequent matching process is based on scrolling through a mass-sorted formula library and comparison with a mass-sorted list of measured peaks. The time required for processing is primarily a function of the size of the formula library. Consequently, at constant library size, the matching algorithm becomes more efficient with increasing number of supplied peaks (up to 4700 formula assignments s-1 on a standard workstation) and is thus particularly suited for processing large datasets. We implemented the matching algorithm into our R Shiny based interactive, evaluation software UltraMassExplorer (UME). In combination with the graphical user interface of UME, our algorithm provides the basis for fast and reproducible (re-)analysis of complete sample sets with currently up to 400,000 peaks in a user friendly, integrated environment. The code of our open-source algorithm is available through the UME website [1]. References [1] www.awi.de/en/um

Molecular Composition of Dissolved Organic Matter in the Changjiang (Yangtze River) – Imprints of Anthropogenic Impact

Understanding the biogeochemical transformation of dissolved organic matter (DOM) across fluvial networks will ultimately help to predict anthropogenic influences. To date, few studies have evaluated the anthropogenic impact on the spatial and temporal changes of DOM composition in large river systems. Here, FT-ICR-MS combined with excitation-emission matrix spectroscopy (EEMs) and biomarkers were applied to resolve chemical differences of DOM collected from the Changjiang basin at different hydrological and environmental conditions. PCA and cluster analysis illustrated that samples collected from lake systems and northern and southern tributaries differed from the two batches of main stream samples, particularly due to higher contribution of nitrogen and sulfur containing compounds. Correlation of land-use information along the tributaries with different PCA loadings indicated that agricultural, forest and wetland areas and wastewater discharge control the composition of DOM within these subregions. Higher heteroatom content (especially CHONx) in the low discharge period (2009) may be contributed by paddy soil leaching into groundwater. The relative peak magnitude of sulfur containing formulas was elevated during flood season (2010), which may be related to pollutions in areas of high population density. In addition, lignin phenol concentrations were higher in the flood season because of elevated soil erosion. Consequently, land use and human activities can strongly alter the quality and composition of DOM in watersheds flowing through densely populated regions, which may also impact or influence the riverine carbon flux in anthropogenically disturbed river systems