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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.
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.
The development of an automated miniaturized analytical system that allows for the rapid monitoring of carbamazepine (CBZ) levels in serum and wastewater is proposed. Molecular recognition of CBZ was achieved through its selective interaction with microbeads carrying anti-CBZ antibodies. The proposed method combines the advantages of the micro-bead injection spectroscopy and of the flow-based platform lab-on-valve for implementation of automatic immunosorbent renewal, rendering a new recognition surface for each sample. The sequential (or simultaneous) perfusion of CBZ and the horseradish peroxidase-labelled CBZ through the microbeads is followed by real-time on-column Monitoring of substrate (3,30,5,50-tetramethylbenzidine) oxidation by colorimetry. The evaluation of the initial oxidation rate and also the absorbance value at a fixed time point provided a linear response versus the logarithm of the CBZ concentration. Under the selected assay conditions, a single analysis was completed after only 11 min, with a quantification range between 1.0 and 50 µg L⁻¹. Detection of CBZ levels in undiluted wastewater samples was feasible after a simple filtration step while good recoveries were attained for spiked certified human serum, analyzed without sample clean-up.
The efficiency, relatively low cost and eco-friendly nature of hydrogen peroxide-assisted photocatalysis treatment procedures are significant advantages over conventional techniques for wastewater remediation. Herein, we evaluate the behaviour of g-cyclodextrin (g-CD) immobilised on either bare or chitosan (CS)–functionalised Fe3O4 nanoparticles, for photodegrading Bisphenol A (BPA) in ultrapure water and in real wastewater samples. The BPA removal efficiencies with Fe3O4/g-CD and Fe3O4/CS/g-CD were compared with those of Fe3O4/b-CD, and were monitored under UVA irradiation at near-neutral pH. The addition of H2O2 at low concentrations (15 mmol L-1) significantly increased BPA photodegradation in the presence of each nanocomposite. The highest catalytic activity was shown by both Fe3O4/g-CD and Fe3O4/CS/g-CD nanocomposites (,60 and 27%BPA removal in ultrapure water and real wastewater effluent, respectively). Our findings reveal the superior performance of g-CD-functionalised Fe3O4 relative to that of Fe3O4/b-CD. The use of CD-based nanocomposites as photocatalytic materials could be an attractive option in the pre- or post-treatment stage of wastewaters by advanced oxidation processes before or after biological treatment.
High photoluminescence of shortwave infrared-emitting anisotropic surface charged gold nanoclusters
(2019)
Incorporating anisotropic surface charges on atomically precise gold nanoclusters (Au NCs) led to a strong absorption in the nearinfrared region and could enable the formation of self-assembled Au NCs xhibiting an intense absorption band at ∼1000 nm. This surface modification showed a striking enhancement of the photoluminescence in the Shortwave Infrared (SWIR) region with a quantum yield as high as 6.1% in water.
Aldehyde moieties on 2D-supports or microand nanoparticles can function as anchor groups for the attachment of biomolecules or as reversible binding sites for proteins on cell surfaces. The use of aldehyde-based materials in bioanalytical and medical settings calls for reliable methods to detect and quantify this functionality. We report here on a versatile concept to quantify the accessible aldehyde moieties on particle surfaces through the specific binding and subsequent release of small reporter molecules such as fluorescent dyes and nonfluorescent chromophores utilizing acylhydrazone formation as a reversible covalent labeling strategy. This is representatively demonstrated for a set of polymer microparticles with different aldehyde labeling densities. Excess reporter molecules can be easily removed by washing, eliminating inaccuracies caused by unspecific adsorption to hydrophobic surfaces. Cleavage of hydrazones at acidic pH assisted by a carbonyl trap releases the fluorescent reporters rapidly and quasi-quantitatively and allows for their fluorometric detection at low concentration. Importantly, this strategy separates the signal-generating molecules from the bead surface. This circumvents common issues associated with light scattering and signal distortions that are caused by binding-induced changes in reporter fluorescence as well as quenching dye−
dye interactions on crowded particle surfaces. In addition, we demonstrate that the release of a nonfluorescent chromophore via disulfide cleavage and subsequent quantification by absorption spectroscopy gives comparable results, verifying that both assays
are capable of rapid and sensitive quantification of aldehydes on microbead surfaces. These strategies enable a quantitative
comparison of bead batches with different functionalization densities, and a qualitative prediction of their coupling efficiencies in bioconjugations, as demonstrated in reductive amination reactions with Streptavidin.
Lead isotopes are a well-established tool to trace the geographic origin of samples and artefacts in archaeology and geochemistry. In archaeology, lead isotopes are often applied to gain information on the provenance of the used ores especially in lead and silver artefacts. The assignment of a specific and unambiguous provenance in most cases is not possible or at least hindered due to several limitations such as ore deposits overlapping in their lead isotopic composition, a large spread within one ore deposit or a missing overlap with known mining sites. Such difficult cases can only be solved by using information from sources being independent of the isotope data. This information can be of chemical nature such as concentrations of key elements or they can be of archaeological nature such as cultural or trade route information.Within this study, we combined lead isotope data of ores and artefacts with silver mass fractions in the ore deposits, Au/Ag-ratios in ores and artefacts and finally archaeological Information on the cultural context in the Mediterranean and Anatolian Region. This approach enabled us to significantly reduce the potential number of mining regions. Finally, the potential sources could be narrowed down to the three remaining locations the Central Taurus, Arap Dağ and the Eastern Troad. Beneath these three locations, the Central Taurus shows the highest probability for the geographic origin of the galena which has been used to create the Trojan silver artefacts.