1.7 Organische Spuren- und Lebensmittelanalytik
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Metabolomics
(2024)
Oxidative degradation processes of tetrabromobisphenol A (TBBPA), a brominated flame retardant (BFR) in wood, plastics and electronics, were investigated by electrochemistry (EC) coupled online to electrospray ionization mass spectrometry (ESI/MS). Oxidative phase I and II metabolites production was achieved using an electrochemical flow-through cell equipped with a boron doped diamond electrode. Structural elucidation and prediction of oxidative metabolism pathways of TBBPA according to type II ipso-substitution were based on retention time, m/z ratio in negative mode and fragmentation pattern. Using the data obtained through high resolution MS analysis and the identification of single electron transfer (SET) as the initial step of a two-electron oxidation provided the necessary information to propose a mechanism for the electrochemical oxidation of TBBPA. Oxidation reactions involving aromatic hydroxylation and β-scission were the main degradation observed when studying the electrochemical behavior of TBBPA. Computational chemistry experiments using density functional theory (DFT) allowed to identify mono-hydroxylated reaction intermediate and dismissed the mechanism involving two concurrent hydroxylation. TBBPA oxidation products were compared to known metabolites of its biological and environmental degradation confirming the ability of electrochemistry to simulate β-scission reactions.
We report an analytical methodology for the quantification of sulfur in biological molecules via a speciesunspecific postcolumn isotope dilution (online ID) approach using capillary electrophoresis (CE) coupled online with inductively coupled plasma−mass spectrometry (online ID CE/ICP−MS).
The method was optimized using a mixture of standard compounds including sulfate, methionine, cysteine, cystine, and albumin, yielding compound recoveries between 98 and 105%. The quantity of sulfur is further converted to the quantity of the compounds owing to the prior knowledge of the sulfur content in the molecules. The limit of detection and limit of quantification of sulfur in the compounds were 1.3−2.6 and 4.1−8.4 mg L−1, respectively, with a correlation coefficient of 0.99 within the concentration range of sulfur of 5−100 mg L−1. The capability of the method was extended to quantify albumin in its native matrix (i.e., in serum) using experimentally prepared serum spiked with a pure albumin standard for validation. The relative expanded uncertainty of the method for the quantification of albumin was 6.7% (k = 2). Finally, we tested the applicability of the method on real samples by the analysis of albumin in bovine and human sera. For automated data assessment, a software application (IsoCor) which was developed by us in a previous work was developed further for handling of online ID data. The method has several improvements compared to previously published setups: (i) reduced adsorption of proteins onto the capillary wall owing to a special capillary-coating procedure, (ii) baseline separation of the compounds in less than 30 min via CE, (iii) quantification of several sulfur species within one run by means of the online setup, (iv) SI traceability of the quantification results through online ID, and (v) facilitated data processing of the transient signals using the IsoCor application. Our method can be used as an accurate approach for quantification of proteins and other biological molecules via sulfur analysis in complex matrices for various fields, such as environmental, biological, and pharmaceutical studies as well as clinical diagnosis.
Sulfur is an essential element in living organisms, where it plays important roles in various biological processes, such as protein synthesis, enzyme activity, and antioxidant defense. However, the biological effects of different sulfur species can vary widely, and imbalances in sulfur speciation have been observed in a range of diseases, including cancer, Alzheimer’s disease, and diabetes.1−3 The accurate quantification of sulfur and its species in biological samples requires sensitive and selective analytical techniques. In recent years, separation techniques coupled online with inductively coupled plasma−mass spectrometry (ICP−MS) have emerged as powerful online analytical tools complementary to molecular spectrometric methods for speciation analysis of biological compounds.
External calibration4−9 and isotope dilution (ID)10−15 are common calibration approaches applied for online quantification of sulfur species in complex samples. The ID analysis is advantageous over.
Here, we report a comparative study of different sum parameter analysis methods for the extraction of per- and polyfluoroalkyl substances (PFAS) from manufactured consumer products, which can be measured by combustion ion chromatography (CIC). Therefore, a hydrolysis-based extraction method was further developed, which accounts for the addition of hydrolyzable covalently bound polyfluoroalkylated side-chain polymers (SFPs) to the extractable organic fluorine portion of the mass balance proposed as "hydrolyzable organically bound fluorine" (HOF). To test this hypothesis, the method was applied to 39 different consumer products containing fluoropolymers or monomeric PFAS taken from four different categories: outdoor textiles, paper packaging, carpeting, and permanent baking sheets. We also evaluated the method's efficiency by extracting four synthesized fluorotelomer polyacrylate reference compounds. The total fluorine (TF) and extractable organically bound fluorine (EOF) values were measured through CIC using established protocols. The TF values ranged from sub-ppb to %-levels, depending on the compound class. All samples showed results for hydrolyzed organofluorine (HOF) between 0.03 and 76.3 μg/g, while most EOF values were lower (<LOD to 58.1 μg/g). Moreover, the methods were contrasted with the "total hydrolyzable precursor" (THP) assay analyzed using gas-chromatography coupled mass spectrometry (GC-MS), which yielded concentrations of 6:2–10:2 fluorotelomer alcohols (<LOD-568 μg/g) for textile and paper samples. Furthermore, targeted analytical investigation of 25 compounds via liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) was conducted and accounted for significantly lower sum amounts (<LOD-0.98 μg PFAS/g). To estimate the fluorine mass balance of all methods, the fluorine levels of target analytical data were calculated and compared to the sum parameter values and evaluated. Finally, the efficiency of the extraction method was approximated by the recovery analysis of four selected SFP model compounds compared to their TF values, yielding 36.7–74.0% after extraction and 3.8–36.3% after processing the extract for the HOF sum parameter.
Volatile organic compounds (VOCs) are of interest in many different fields. Among them are food and fragrance analysis, environmental and atmospheric research, industrial applications, security or medical and life science. In the past, the characterization of these compounds was mostly performed via sample collection and off-site analysis with gas chromatography coupled to mass spectrometry (GC-MS) as the gold standard. While powerful, this method also has several drawbacks such as being slow, expensive, and demanding on the user. For decades, intense research has been dedicated to find methods for fast VOC analysis on-site with time and spatial resolution. We present the working principles of the most important, utilized, and researched technologies for this purpose and highlight important publications from the last five years. In this overview, non-selective gas sensors, electronic noses, spectroscopic methods, miniaturized gas chromatography, ion mobility spectrometry and direct injection mass spectrometry are covered. The advantages and limitations of the different methods are compared. Finally, we give our outlook into the future progression of this field of research.
Ergot alkaloids are a group of toxic compounds, formed by fungi on infested grasses. In 2022, the European Commission set into effect maximum levels for the sum of the twelve major ergot alkaloids in multiple foods. To facilitate the laborious and costly individual quantification of the twelve major ergot alkaloids by HPLC–MS/MS or -FLD, we recently reported a sum parameter method (SPM) for ergot alkaloid quantification. Here, derivatization to lysergic acid hydrazide—a derivative of the mutual ergoline backbone in all ergot alkaloids—allowed simplified determination of all ergot alkaloids in flour via HPLC-FLD. For the measurement of more complex matrices like processed foods, we now developed a MS/MS-based SPM. Two internal standards (IS), isotopically labelled at different positions of the molecule, were synthesized and employed in the MS/MS-measurements. Method performance using either the 13CD3-labelled or the 15N2-labelled IS was evaluated on naturally contaminated rye and wheat flour samples as well as on processed food matrices. Employing the 13CD3-labelled IS leads to lower variances and better consistency with the reference data (obtained by the FLD-based SPM) in flour samples compared to the 15N2-labelled IS. The novel method significantly improves the measurement of ergot alkaloids in complex food matrices, due to their increased selectivity and thus lower interferences. Furthermore, the application of isotope labelled IS obviates the need for time-consuming steps like the determination of recovery rate based, matrix specific correction factors as described in the MS/MS-based European standard method for ergot alkaloid quantification (EN 17425).
A collaborative trial involving 16 participants from nine European countries was conducted within the NORMAN network in efforts to harmonise suspect and non-target screening of environmental contaminants in whole fish samples of bream (Abramis brama). Participants were provided with freeze-dried, homogenised fish samples from a contaminated and a reference site, extracts (spiked and non-spiked) and reference sample preparation protocols for liquid chromatography (LC) and gas chromatography (GC) coupled to high resolution mass spectrometry (HRMS). Participants extracted fish samples using their in-house sample preparation method and/or the protocol provided. Participants correctly identified 9-69% of spiked compounds using LC-HRMS and 20-60% of spiked compounds using GC-HRMS. From the contaminated site, suspect screening with participants’ own suspect lists led to putative identification of on average ~145 and ~20 unique features per participant using LC-HRMS and GC-HRMS, respectively, while non-target screening identified on average ~42 and ~56 unique features per participant using LC-HRMS and GC-HRMS, respectively. Within the same sub-group of sample preparation method, only a few features were identified by at least two participants in suspect screening (16 features using LC-HRMS, 0 features using GC-HRMS) and non-target screening (0 features using LC-HRMS, 2 features using GC-HRMS). The compounds identified had log octanol/water partition coefficient (KOW) values ranging from -9.9 to 16 and mass-to-charge ratio (m/z) of 68 to 761 (LC-HRMS and GC-HRMS). A significant linear trend was found between log KOW and m/z for the GC-HRMS data. Overall, these findings indicate that differences in screening results are mainly due to the data analysis workflows used by different participants. Further work is needed to harmonise the results obtained when applying suspect and non-target screening approaches to environmental biota samples.
Non-target (NT) mass spectrometry techniques play a crucial role in metabolomics applications, particularly in areas such as environmental safety. Soft ionization methods, such as electrospray ionization (ESI), are commonly employed due to their ability to generate spectra containing molecular ions, aiding in the identification of unknown peaks. However, ESI may fail to ionize certain compounds effectively, resulting in their absence in NT approaches. In contrast, hard ionization methods like electron impact (EI) can ionize a wide range of compounds but often lack information about the molecular ion. Although extensive databases of EI spectra exist, their nominal mass resolution (NR) limits their utility for modern high-resolution (HR) EI mass spectrometers. Here, the often-applied conversion of HR spectra to nominal mass leads to the loss of unique characteristics, i.e. by grouping distinct masses into more ambiguous nominal masses.
Our study aims to (i) quantify the negative impact of such a binning approach and (ii) develop a machine learning (ML) tool capable of enhancing existing nominal mass spectral libraries. In the initial phase, we employed the RECETOX Exposome HR-[EI+]-MS library to assess the influence of HR spectra on identification. We compared the dot product of each spectrum against all others, utilizing bin sizes of 0.001 and 1 Da. The difference in dot product between the second-best candidate and the query spectrum (the best candidate, with a score of 1) was calculated for both HR and nominal mass spectra. Subsequently, we explored the application of ML techniques to predict HR spectra from nominal mass spectra using the before mentioned dataset.
Preliminary findings demonstrate the potential of high-resolution spectral libraries. As anticipated, HR spectra consistently exhibited lower similarity scores for the second candidate. This observation likely stems from the high redundancy and resulting ambiguity associated with nominal masses. Even after eliminating spectra containing multiple HR masses mapped to the same nominal mass, the aforementioned trend persisted. Furthermore, initial investigations into ML have revealed its ability to predict up to 40% of HR masses within a 10 mDa precision window.
Per- and polyfluoroalkyl substances (PFAS) are a large group of organofluorine surfactants used in the formulations of thousands of consumer goods. The continuous use of PFAS in household products and the discharge of PFAS from industrial plants into the sewer system have been resulted in contaminated effluents and sewage sludge from wastewater treatment plants (WWTPs) which became an important pathway for PFAS into the environment. Because sewage sludge is often used as fertilizer its application on agricultural soils has been observed as significant input path for PFAS into our food chain. To produce high-quality phosphorus fertilizers for a circular economy from sewage sludge, PFAS and other pollutants (e.g. pesticides and pharmaceuticals) must be separated from sewage sludge. Normally, PFAS are analyzed using PFAS protocols typically with time-consuming extraction steps and LC-MS/MS target quantification. However, for screening of PFAS contaminations in wastewater-based fertilizers also the DGT technique can be used for the PFAS extraction. Afterwards, combustion ion chromatography (CIC) can be applied to analyze the “total” amount of PFAS on the DGT binding layer. The DGT method was less sensitive and only comparable to the extractable organic fluorine (EOF) method values of the fertilizers in samples with >150 µg/kg, because of different diffusion properties for various PFAS, but also kinetic exchange limitations. However, the DGT approach has the advantage that almost no sample preparation is necessary. Moreover, the PFAS adsorption on the DGT binding layer was investigated via surface sensitive spectroscopical methods, such as Fourier-transform infrared (FT-IR) and fluorine K-edge X-ray absorption near-edge structure (XANES) spectroscopy.
Thermo-Desorption Gas Chromatography-Mass Spectrometry (TD-GC-MS) was used to investigate the thermal degradation of two different polyurethanes (PU). PU samples were heated at different heating rates and the desorbed products were collected in a cold injection system and thereafter submitted to GC-MS. Prospects and limitations of the detection and quantification of semi-volatile degradation products were investigated. A temperature dependent PU depolymerization was
found at temperatures above 200 °C proved by an increasing release of 1,4-butanediol and methylene diphenyl diisocyanate (MDI) representing the main building blocks of both polymers. Their release was monitored quantitatively based on external calibration with authentic compounds. Size Exclusion Chromatography (SEC) of the residues obtained after thermodesorption confirmed the initial competitive degradation mechanism indicating an equilibrium of crosslinking and depolymerization as previously suggested. Matrix-Assisted Laser Desorption Ionization (MALDI) mass spectrometry of SEC fractions of thermally degraded PUs provided additional hints on degradation mechanism.