Fourier transform ion cyclotron resonance mass spectral characterization of metal‐humic binding

Abstract

The interaction between metals and naturally occurring humic substances and the thereby induced issues of bioavailability and hydrogeochemical turnover of metal ions in natural waters have been the subject of intense study for decades. Traditional bulk techniques to investigate metal-humic binding (e.g. potentiometry and inductively coupled plasma mass spectrometry (ICP-MS)) can provide quantitative results for the relative abundance and distribution of metal species in humic samples and/or overall binding constants. The shortcoming of these bulk techniques is the absence of structural detail. Ultra-high-resolution mass spectrometry, currently the only technique demonstrated to resolve individual humic ions, is not generally employed to provide the missing qualitative information primarily because the identification of metal complexes within the already complex mixtures of humic substances is non-trivial and time-consuming to the extent of eliminating any possibility for real-time manipulation of chelated analytes. Here, it is demonstrated that with tailored selection of the metal ion, it is possible to visually identify large numbers of metal-humic complexes ( approximately 500 for Be2+, approximately 1100 for Mn2+, and approximately 1500 for Cr3+) in real-time as the spectra are being acquired. Metal ions are chosen so that they form primarily even-m/z complexes with humic ions. These even-m/z complexes stand out in the spectrum and can readily be characterized based on molecular formulae, which here revealed for example that Suwannee River fulvic acid (SRFA) complexes encompassed primarily highly oxygenated fulvic acids of relatively low double-bond equivalence. Facile, real-time identification of even-m/z metal-humic complexes additionally allows for the specific selection of metal-humic complexes for MS(n) analysis and in-trap ion-neutral reactions enabling investigation of metal-humic complex structure. MS/MS data were collected to demonstrate the potential of the technique as well as highlight some of the remaining challenges.

Fe- and Cu-Complex Formation with Artificial Ligands Investigated by Ultra-High Resolution Fourier-Transform ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS): Implications for Natural Metal-Organic Complex Studies

“…Based on the signal intensities of the detected compounds (Figures 1, 2), we can identify several common trends for all tested ligand types: Overall, highest FT-ICR-MS signal responses were found for methanol-water mixtures, and selective ionization of metal-organic complexes in pure water solutions did not play an important role. In contrast to Stenson (2009), and in line with Silva et al (2009), we suggest that for metal-ligand measurements, the enhanced ionization efficiency due to the methanol matrix outweighs any potential advantage of a selective ionization of metal-containing compounds predicted for samples made up with pure water only. Furthermore, it appears that Fe-ligand complexes benefitted most from the addition of aq.…”

“…Thus, conditional stability constants derived from FT-ICR-MS measurements likely do not capture the complexation properties of the original water sample, although they can be used in several other ways, for example to determine ligand concentrations, intercalibrate FT-ICR-MS and CLE-ACSV, or link metal binding of SPE-ligands to other SPE-DOM characteristics such as elemental composition of detected molecules. SPE-ligands can also be spiked with excess trace metals concentrations, and in past studies, compounds, which newly occurred in DOM mass spectra after metal salt additions, have been identified as metal-organic complexes, and confirmed by isotopic pattern recognition and/or molecular formulae assignment ("presence-absence check, " (McCormack et al, 2003;Mawji et al, 2008;Stenson, 2009;Velasquez et al, 2011)). However, the study presented here confirms previous reports (e.g., Reinoso-Maset et al, 2012) that the response factors of metal-organic compounds, as well as uncomplexed ligands, can be selectively sensitive toward changes in the sample matrix, for example through additives in trace metals solutions (for example NO − 3 , Na + , or Cl − ), the trace metals themselves, and enhancement/suppression effects of bases such as aq.…”

“…For example, the complexing behavior of citrate, an important natural metal chelator which forms highly diverse species with iron under different pH and stoichiometry conditions, has been studied by ESI-MS in comparison with complementary techniques, such as spectrophotometric titrations and chemical modeling (Gautier-Luneau et al, 2005;Nischwitz and Michalke, 2009;Silva et al, 2009;Bertoli et al, 2015). In parallel to these studies on artificial metal-organic compounds under well-constrained conditions, ESI-MS has recently been applied to identify unknown metal-binding ligands isolated from natural waters, which ubiquitously occur as a component of natural dissolved organic matter (DOM), and which govern the mobility and availability of bioactive trace metals such as iron (Fe) and copper (Cu) (McCormack et al, 2003;Ross et al, 2003;Mawji et al, 2008Mawji et al, , 2011Stenson, 2009;Velasquez et al, 2011). Although the number of studies in the field is scarce, they have shown that ESI-MS is currently the only technique with the potential to study a large number of metalorganic complexes simultaneously at the molecular level: ESI-MS and in particular ESI-FT-ICR-MS (Electrospray-ionization Fourier-transform ion cyclotron resonance mass spectrometry) are capable of resolving the high complexity of DOM, where thousands of unique compounds occur at pico-to nanomolar concentrations (Repeta, 2015).…”

Chromatographic methods for the isolation, separation and characterisation of dissolved organic matter

“…1 Key to a greater understanding of the complex system of biogeochemical processes involved in the formation and removal of DOM is an understanding of the exact nature of DOM itself. 22,[32][33][34][35][36][37][38][39][40][41][42][43][44][45][46] The above functional groups are found within major classes of compounds, such as amino acids, proteins, peptides, sugars, amino-sugars, carboxylic rich alicyclic molecules (CRAM), materials derived from linear terpenoids (MDLT), neutral lipids, DNA, RNA, and sterols. 1 shows the research papers published annually based upon an article title search (Scopus) using the term 'dissolved organic matter').…”

“…[145][146][147][148][149][150] Further to this, it is oen difficult to identify and isolate signals derived from artefacts, which can derive not only from the extraction or chromatographic stage, but also from the ion source. 166,[170][171][172] On the basis of previously developed HR-MS methods, 42,156 Stenson et al, targeting humic substances within a Suwannee river fulvic acid standard, 162 presented the separation of DOM isomers through RP-LC-HR-MS. Ions with identical formulae were found within different chromatographic fractions and analysed using the above H/D exchange protocol, providing for isotope differentiation. 44,131,154,155 Kendrick mass analysis plots and van Krevelen diagrams are commonly used in describing DOM composition and are a valuable aid in simplifying the enormous amount of data generated from these experiments.…”