Chemische Charakterisierung und Spurenanalytik
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- Comparability (2)
- Effect based Method (2)
- Estrogens (2)
- ICP-MS (2)
- Laser ablation (2)
- MS based method (2)
- Multicellular spheroid (2)
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- 1.8 Umweltanalytik (9) (entfernen)
In addition to previously reported results on the accelerated weathering of polystyrene samples (PS) containing 1 wt.% hexabromocyclododecane (HBCD), we present the first results of our investigations of polypropylene samples (PP) containing 0.1 wt.% BDE-209. All studied polymer samples were exposed to a defined weathering schedule in a climate chamber in accordance to regulation EN ISO 4892-3:2006. For the determination of BDE-209 in the collected raining water the samples were prepared in accordance to a validated protocol. Before the analyses each sample was spiked with isotopically labeled BDE-209. Subsequently the samples were extracted with isooctane. The obtained extracts were concentrated, and the resulting solutions were analyzed by GC/MS. Additionally, the total bromine content was monitored for the weathered and untreated samples using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and X-ray fluorescence analysis (XRF) as a non-destructive and rapid method. In general, the resulting data from the accelerated weathering will be compared to those from the natural weathering experiments. Here, the surfaces of the test pieces were analyzed by LA-ICP-MS and XRF as well. Moreover, soil bed tests were conducted in a well characterized model soil. This soil (boulder-clay, sand with 12 % loam, particle size in total 0.2-4 mm) is filled in a free-draining basin inside of an air-conditioned cellar. In this manner, TOC, water capacity and humidity are recorded parameters. To induce a leaching process from the samples by the raining water, the target water content is calculated to 8%. The actual humidity is measured by a tensiometer, assuring the duration of the raining period. A defined humidity is a fundamental parameter for a biological activity in the soil. The test polymers were placed up to the half in the soil. Microbial activity of the soil is monitored by a reference polymer (polyurethane) and should induce the release of HBCD and BDE-209 out of the test materials. These released analytes will be captured by passive samplers (silicone tubes) placed in a distinct distance to the polymer samples in the soil. The soil bed experiments are complementary to the weathering experiments due to the biological activity in the soil.
Warfarin, also known as Coumadin is one of the most popular anticoagulant drugs used as a therapeutic in humans to prevent thrombosis, atrial fibrosis, and fibrillation since the 1950s. Because of its ability to hinder blood from clotting by blocking vitamin K-depending carboxylation of blood clotting precursors, it is also used as a rodenticide worldwide. Until today it has been partially substituted by far more potent anticoagulant rodenticides (ARs), so-called superwarfarins. There are numerous references confirming secondary and tertiary poisoning in non-target-animals and wildlife like mammals, birds, and fish associated with ARs. Up to now relatively little is known about persistence and toxicity of transformation products of those AR in the environment and food chain. Herein, warfarin was chosen as a model compound to determine andelucidate TPs which are generated technically and under environment-like conditions. Such as the simulation of the oxidative phase I metabolism by implementing electrochemical flow cells coupled to mass spectrometry (MS). Obtained results are being compared to TPs generated by UVB-irradiation and ozonation.
Analysis and separation of degradation products and TPs were achieved by a variety of gas- and liquid chromatographic techniques coupled to (high resolution) MS.
Monitoring programs should generate high-quality data on the concentrations of substances and other pollutants in the aquatic environment to enable reliable risk assessment. Furthermore, the need for comparability over space and time is critical for analysis of trends and evaluation of restoration of natural environment. Additionally, research work and exercises at the European level have highlighted that reliable measurements of estrogenic substances at the PNEC level are still challenging to achieve. The project EDC-WFD “Metrology for monitoring endocrine disrupting compounds under the EU Water Framework Directive” aims to develop traceable analytical methods for determining endocrine disrupting compounds and their effects, with a specific focus on three estrogens of the first watch list (17-beta-estradiol (17βE2), 17-alpha-ethinylestradiol (EE2), and estrone (E1)). Estrogens 17-alpha-estradiol (17aE2) and estriol (E3) will be included to demonstrate the reliability of the developed methods - Mass Spectrometry based method and effect-based methods (EBM) - and to support the requirements of Directive 2013/39/EC, Directive 2009/90/EC and Commission Implementation Decision (EU) 2018/840, hence improving the comparability and compatibility of measurement results within Europe. During the EDC-WFD project four EBM will be deeply investigated in order to improve their rationale use and their support in water quality assessment.
Monitoring programs should generate high-quality data on the concentrations of substances and other pollutants in the aquatic environment to enable reliable risk assessment. Furthermore, the need for comparability over space and time is critical for analysis of trends and evaluation of restoration of natural environment. Additionally, research work and exercises at the European level have highlighted that reliable measurements of estrogenic substances at the PNEC level are still challenging to achieve. The project EDC-WFD “Metrology for monitoring endocrine disrupting compounds under the EU Water Framework Directive” aims to develop traceable analytical methods for determining endocrine disrupting compounds and their effects, with a specific focus on three estrogens of the first watch list (17-beta-estradiol (17βE2), 17-alpha-ethinylestradiol (EE2), and estrone (E1)). Estrogens 17-alpha-estradiol (17aE2) and estriol (E3) will be included to demonstrate the reliability of the developed methods - Mass Spectrometry based method and effect-based methods (EBM) - and to support the requirements of Directive 2013/39/EC, Directive 2009/90/EC and Commission Implementation Decision (EU) 2018/840, hence improving the comparability and compatibility of measurement results within Europe. During the EDC-WFD project four EBM will be deeply investigated in order to improve their rationale use and their support in water quality assessment.
Regardless of its ban in agricultural use, the triazine derivative terbutryn is still used as a biocide against biofouling in building materials, such as façade colors and roof tiles. From there, it is washed off and may contaminate soil and surface waters, where it shows ecotoxicological behavior. For understanding of these leaching processes, analytical methods that can detect terbutryn in traces are necessary. In contrast to separation methods (Gas (GC) or liquid chromatography (LC)) coupled to mass spectrometry (MS), enzyme immunoassays (EIAs) have proven to be adequate tools for environmental monitoring. Compared to GC-or LC-MS, they are cheap, require only limited time and experimental expertise and enable high throughput. For quantification of terbutryn, EIAs have been established, with a limit of detection (LOD) of 50 ng L-1. For leaching experiments however, a lower LOD would be advantageous.
For detection of terbutryn we developed a direct competitive ELISA based on a monoclonal antibody: Terbutryn and an enzyme-terbutryn conjugate (“tracer”) compete for the binding sites of the immobilized antibody. The bound tracer converts a colourless substrate into a blue-coloured product, which can be detected via spectrophotometry. For quantification of terbutryn, a sigmoidal calibration curve is used. For establishing of the EIA, a new tracer based on a terbutryn surrogate (“hapten”) was synthesized. After optimization of the experimental conditions, the immunoassay exhibited a more than ten-fold increased sensitivity (LOD: 3 ng L-1), high stability against sample compounds (Ca2+, NaCl) and lower cross-reactivities against structurally related compounds, than reported before. Analysis of spiked samples was possible with high precision (inter-assay CV: < 10 %) and accuracy (recoveries from spiked samples: 89 % ± 10%). We therefore propose it as quick and reliable method for leaching studies of terbutryn out of building materials.
Metallic nanoparticles (NPs) are currently applied in a variety of consumer products and are also attractive for medical applications. With their widespread use, the potential for human exposure to NPs — either intended or unintended — is increasing. Therefore, many studies have evaluated the toxicity and transport mechanism of NPs. In comparison with two-dimensional cultured cells, multicellular spheroids (MCS) look promising to be used as a three-dimensional cellular model, having unique advantages in nanoparticle studies due to the fact that interactions with excreted extracellular matrix can be investigated. Fibroblast cells are one of the most important cell systems to express a microenvironment by excreting an abundant extracellular matrix. For bioimaging laser ablation inductively coupled-plasma mass spectrometry (LA-ICP-MS) is used in this investigation to study the interaction of metallic NPs with MCS for multi-element detection offering a wide dynamic range. As a mass spectrometer we have applied a time-of-flight (TOF) instrument for (quasi-) simultaneous detection of all isotopes of elements of interest.
The aim of this study is to investigate the localization of silver (Ag) NPs exposed to fibroblast MCSs by means of LA-ICP-TOF-MS. In addition, for demonstrating elemental microscopy we chose phosphorous (31P) and iron (56Fe) to visualize regions of enriched extracellular matrix and single cells, respectively. In this presentation, we show that exposed Ag NPs are highly accumulated at the same position of single cells in an outer rim of fibroblast MCSs.
Comparing Nontargeted LC-MS Methods by Co-visualizing Linear Dynamic Range and Chemical Coverage
(2019)
INTRODUCTION
Biological and environmental samples contain thousands of small molecule species that all vary in chemical properties and concentration range. Identifying and quantifying all these chemical entities remains a long-term goal in metabolomics and related systems approaches. Due to its broad selectivity, nontargeted LC-MS is usually the method of choice for broad chemical screening. Optimizing nontargeted LC-MS methods, however, is less straightforward than for targeted methods where sensitivity, specificity, linearity etc. serve as well-established performance criteria. We therefore investigated linear dynamic range (LDR) and chemical classification as alternative performance criteria to guide nontargeted method development.
EXPERIMENTAL METHODS
LDR was defined as the linear portion of a feature’s response curve over multiple concentration levels. Comparing the LDR of features across methods can be expected to be significantly more robust than comparing signal intensities for a single concentration. To determine LDR for all features, a computational workflow was implemented in the R programming language. For estimating the linear portion of a curve, several mathematical approaches including linear, non-linear and piecewise linear regression were evaluated. Chemical classification was based on ClassyFire, which computes chemical classes for a given structure. To avoid false classifications for incorrectly annotated compounds, we took the following statistical approach. For each compound, multiple likely annotation hypotheses were derived using a recently described workflow[2]. All annotation hypotheses were submitted to ClassyFire and obtained classifications were ranked by frequency. The most frequently suggested class was kept for further analysis. Finally, LDR and chemical classes were visualized together on a molecular network, which was constructed using the well-established MS/MS similarity approach.
RESULTS AND DISCUSSION
For technical validation of the workflow, several hundred curve fits obtained from the different regression models were reviewed visually. Piecewise linear regression performed the most reliably with respect to the heterogeneous curve shapes of ‘real-life’ features. Validation of chemical classification was performed against a compound library, which showed that 90% of ~450 library compounds were correctly classified using the described approach. Two liquid chromatography methods (HILIC, RPC) as well as two electrospray ionization variants (low/high-temperature ESI) applied to urinary metabolomics were exemplarily studied to test the workflow. Molecular network visualization indicated that of all analytical setups, HILIC/high temperature ESI performed best in terms of high LDR achieved over a wide range of compound classes. Despite one order of magnitude lower sensitivity, HILIC/low temperature ESI showed similar chemical coverage, except for organic nitrogen compounds that were underrepresented compared to high-temperature ESI. Both RPC setups were inferior to the HILIC setups in terms of high-LDR features, supporting previous findings for the given matrix. The higher relative representation of benzenoids and lipids in RPC demonstrated that the workflow successfully captured expected selectivity differences between chromatographies.
CONCLUSION
When comparing nontargeted LC-MS methods for optimization purposes, ideally all available quantitative and qualitative information should be integrated. The present workflow follows this idea. Visualizing LDR and chemical classes of all features on a molecular network quickly indicated differences in method selectivity that were otherwise difficult to spot. As an automated approach, it is easily applied to repeated optimization steps, enabling effective optimization strategies.
Nontargeted high-resolution mass spectrometry (HRMS) is widely used for small molecule screening in biotic or abiotic samples. However, HRMS approaches like metabolomics or environmental nontarget screening currently still lack confidence in chemical annotation, i.e. computational structure assignment to all measured mass signals. As a crucial step within the annotation pipeline, molecular weight inference (MWI) deduces a compound’s intact mass from diagnostic mass differences between MS1 peaks, allowing precise database queries in subsequent steps. As the common practice of considering all possible ionization products such as adducts, multimers, multiple charges etc. in MWI suffers from high false positive rates, we aimed at selecting candidate ionization products in a chemically sensitive way. Generally, electrospray ionization produces different types of adducts depending on chromatographic system and sample matrix, necessitating application-specific optimization for optimum MWI performance. To avoid, however, the tedious and potentially biased manual data curation connected to optimization, we established an R-based workflow for automating this task. The workflow consists of two parts. Part 1 creates an MS1 spectral library by performing peak detection, spectral deconvolution and target peak assignment based on density estimation. Part 2 analyzes ion relationships within the library and returns a list of detected ionization products ranked by their frequency. We applied the workflow to a commercial 634-compound library that was acquired for two chromatographic methods (reverse phase, RP; hydrophilic liquid interaction chromatographic, HILIC) and the two ESI modes (positive, negative). As expected, different frequency distributions of ionization products were found for the two chromatographies. Interestingly, however, some of the differences were expected in terms of solvent chemistries (e.g. [M+NH4]+ in ammonium formate-buffered HILIC) while others indicated more complex ion competition (e.g. abundant [M+K]+, [M+2K-H]+ in HILIC). This demonstrated the relevance of this empirical approach. We further show that MWI accuracy clearly benefitted from derived optimized adduct lists – by adding filters or weighting terms – and present FDR calculations supporting this observation. We conclude that chemistry-aware compound annotation based on the combination of high-throughput library acquisition and statistical analysis holds significant potential for further improvements in nontargeted small molecule HRMS.
We have applied laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) with subcellular resolution as an elemental mass microscope to investigate the distributions of Ag nanoparticles (NP) in a 3-dimentional multicellular spheroid (MCS) model. The production of MCS has been optimized by changing the seeding cell number (500 to 40,000 cells) and the growth period (1 to 10 days). Incubations of MCS with Ag nanoparticle suspensions were performed with a concentration of 5 µg mL-1 for 24 hours. Thin-sections of the Eosin stained MCS were analysed by elemental mass microscopy using LA-ICP-MS to image distributions of 109Ag, 31P, 63Cu, 66Zn and 79Br. A calibration using NP suspensions was applied to convert the measured Ag intensity into the number of particles being present in each measurement pixel. The numbers of NP determined ranged from 30 up to 4,000 particles in an enrichment zone. The particle distribution was clearly correlated to 31P, 66Zn and 79Br and was localized in an outer rim of proliferating cells (confirmed by DAPI) with a width of about two-single cell diameters. For the highest seeding cell number NPs were only detected in this outer rim, whereas small molecules as for instance 79Br and 109Ag ions were detected in the core of the MCS as well. Aniline blue staining demonstrated that this outer rim was rich in collagen structures in which fibroblast cells were embedded and a thin-membrane was visible which separated the core from the biological active cell layer functioning as biological barriers for NP transport. In this presentation, we will show the possibility using this 3-dimensional model for toxicological and medical applications.