Chemische Charakterisierung und Spurenanalytik
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Metabolomics
(2024)
Solid wastewater-based fertilizers were screened for per- and polyfluoroalkyl substances (PFAS) by the extractable organic fluorine (EOF) sum parameter method. The EOF values for ten sewage sludges from Germany and Switzerland range from 154 to 7209 mg kg−1. For thermal treated sewage sludge and struvite the EOF were lower with values up to 121 mg kg−1. Moreover, the application of PFAS targeted
and suspect screening analysis of selected sewage sludge samples showed that only a small part of the EOF sum parameter values can be explained by the usually screened legacy PFAS. The hitherto unknown part of EOF sum parameter contains also fluorinated pesticides, pharmaceutical and aromatic compounds. Because these partly fluorinated compounds can degrade to (ultra-)short PFAS in wastewater treatment plants they should be considered as significant sources of organic fluorine in the environment. The combined results of sum parameter analysis and suspect screening reveal the need to update current regulations, such as the German fertilizer ordinance, to focus not solely on a few selected PFAS such as perfluorooctane sulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) but
consider an additional sum parameter approach as a more holistic alternative. Moreover, diffusion gradient in thin-films (DGT) passive samplers were utilized as an alternative simplified extraction method for PFAS in solid wastewater-based fertilizers and subsequently quantified via combustion ion chromatography. However, the DGT method was less sensitive and only comparable to the EOF values
of the fertilizers in samples with >150 mg kg−1, because of different diffusion properties for various PFAS, but also kinetic exchange limitations.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer-based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
Towards Unbiased Evaluation of Ionization Performance in LC-HRMS Metabolomics Method Development
(2022)
As metabolomics increasingly finds its way from basic science into applied and regulatory environments, analytical demands on nontargeted mass spectrometric detection methods continue to rise. In addition to improved chemical comprehensiveness, current developments aim at enhanced robustness and repeatability to allow long-term, inter-study, and meta-analyses. Comprehensive metabolomics relies on electrospray ionization (ESI) as the most versatile ionization technique, and recent liquid chromatography-high resolution mass spectrometry (LC-HRMS) instrumentation continues to overcome technical limitations that have hindered the adoption of ESI for applications in the past. Still, developing and standardizing nontargeted ESI methods and instrumental setups remains costly in terms of time and required chemicals, as large panels of metabolite standards are needed to reflect biochemical diversity. In this paper, we investigated in how far a nontargeted pilot experiment, consisting only of a few measurements of a test sample dilution series and comprehensive statistical analysis, can replace conventional targeted evaluation procedures. To examine this potential, two instrumental ESI ion source setups were compared, reflecting a common scenario in practical method development. Two types of feature evaluations were performed, (a) summary statistics solely involving feature intensity values, and (b) analyses additionally including chemical interpretation.
Results were compared in detail to a targeted evaluation of a large metabolite standard panel. We reflect on the advantages and shortcomings of both strategies in the context of current harmonization initiatives in the metabolomics field.
The investigation of metabolic fluxes and metabolite distributions within cells by means of tracer molecules is a valuable tool to unravel the complexity of biological systems. Technological advances in mass spectrometry (MS) technology such as atmospheric pressure chemical ionization (APCI) coupled with high resolution (HR), not only allows for highly sensitive analyses but also broadens the usefulness of tracer‐based experiments, as interesting signals can be annotated de novo when not yet present in a compound library. However, several effects in the APCI ion source, i.e., fragmentation and rearrangement, lead to superimposed mass isotopologue distributions (MID) within the mass spectra, which need to be corrected during data evaluation as they will impair enrichment calculation otherwise. Here, we present and evaluate a novel software tool to automatically perform such corrections. We discuss the different effects, explain the implemented
algorithm, and show its application on several experimental datasets. This adjustable tool is available as an R package from CRAN.
MACC1 is a prognostic and predictive metastasis biomarker for more than 20 solid Cancer entities. However, its role in cancer metabolism is not sufficiently explored. Here, we report on how MACC1 impacts the use of glucose, glutamine, lactate, pyruvate and fatty acids and show the comprehensive analysis of MACC1-driven metabolic networks. We analyzed concentrationdependent changes in nutrient use, nutrient depletion, metabolic tracing employing 13C-labeled substrates, and in vivo studies. We found that MACC1 permits numerous effects on cancer
metabolism. Most of those effects increased nutrient uptake. Furthermore, MACC1 alters metabolic pathways by affecting metabolite production or turnover from metabolic substrates. MACC1 supports use of glucose, glutamine and pyruvate via their increased depletion or altered distribution within metabolic pathways. In summary, we demonstrate that MACC1 is an important regulator of metabolism in cancer cells.
Lipid droplets, the dynamic organelles that store Triglycerides (TG) and cholesterol esters (CE), are highly accumulated in colon cancer cells. This work studies the TG and CE subspecies profile in colon carcinoma cell lines, SW480 derived from primary tumor, and SW620 derived from a metastasis of the same tumor. It was previously reported that the total TG and CE content is dramatically higher in SW620 cells; however, TG and CE subspecies profile has not been investigated in detail. The work presented here confirms that the total TG and CE Content is significantly higher in the SW620 cells. Moreover, the fatty acid (FA) composition of TG is significantly altered in the SW620 cells, with significant decrease in the abundance of saturated triglycerides. This resulted in a significantly decreased TG saturation index in the SW620 cells. The saturation index of CE was also significantly decreased in the SW620 cells.
Molekülmassenspektrometrie entwickelt sich weg von klassischer Target- hin zu Nontarget-Analytik. Elementmassenspektrometrie liefert hohe Ortsauflösung beim Element-Imaging und analysiert einzelne Zellen. Aufgrund der Fortschritte bei den Geräten für Timeof-Flight-Massenspektrometrie mit induktiv gekoppeltem Plasma (ICPToF-MS) lässt sich das gesamte Periodensystem der Elemente in kurzen transienten Signalen quasi-simultan massenspektrometrisch erfassen.
Cancer cell lipid class homeostasis is altered under nutrient-deprivation but stable under hypoxia
(2019)
Background: Cancer cells modify the balance between fatty acid (FA) synthesis and uptake under metabolic stress, induced by oxygen/nutrient deprivation. These modifications were shown to alter the levels of individual triglyceride (TG) or phospholipid sub-species. To attain a holistic overview of the lipidomic profiles of cancer cells under stress we performed a broad lipidomic assay, comprising 244 lipids from six major classes. This assay allowed us to perform robust analyses and assess the changes in averages of broader lipid-classes, stratified on the basis of saturation index of their fatty-acyl side chains.
Methods: Global lipidomic profiling using Liquid Chromatography-Mass Spectrometry was performed to assess lipidomic profiles of biologically diverse cancer cell lines cultivated under metabolically stressed conditions.
Results: Neutral lipid compositions were markedly modified under serum-deprived conditions and, strikingly, the cellular level of triglyceride subspecies decreased with increasing number of double bonds in their fatty acyl chains.
In contrast and unexpectedly, no robust changes were observed in lipidomic profiles of hypoxic (2% O2) cancer cells despite concurrent changes in proliferation rates and metabolic gene expression.
Conclusions: Serum-deprivation significantly affects lipidomic profiles of cancer cells. Although, the levels of individual lipid moieties alter under hypoxia (2% O2), the robust averages of broader lipid classes remain unchanged.