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Paper des Monats
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The ability to controllably move gaseous ions is an essential aspect of ion-based spectrometry (e.g., mass spectrometry and ion mobility spectrometry) as well as materials processing. At higher pressures, ion motion is largely governed by diffusion and multiple collisions with neutral gas molecules. Thus, high-pressure ion optics based on electrostatics require large fields, radio frequency drives, complicated geometries, and/or partially transmissive grids that become contaminated. Here, we demonstrate that low-power standing acoustic waves can be used to guide, block, focus, and separate beams of ions akin to electrostatic ion optics. Ions preferentially travel through the static-pressure regions (“nodes”) while neutral gas does not appear to be impacted by the acoustic field structure and continues along a straight trajectory. This acoustic ion manipulation (AIM) approach has broad implications for ion manipulation techniques at high pressure, while expanding our fundamental understanding of the behavior of ions in gases.
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.
Isotope Ratio Analysis
(2023)
Data file (RData) containing measurement data recorded during the production process of the Certified Reference Material BAM-A001 containing Polycyclic Aromatic Hydrocarbons (PAH) in olive oil. The data can be most conveniently openend using the Shiny-App eCerto which is accessible at https://www.bam.de/eCerto.
Mistle: bringing spectral library predictions to metaproteomics with an efficient search index
(2023)
Motivation: Deep learning has moved to the forefront of tandem mass spectrometry-driven proteomics and authentic prediction for peptide fragmentation is more feasible than ever. Still, at this point spectral prediction is mainly used to validate database search results or for confined search spaces. Fully predicted spectral libraries have not yet been efficiently adapted to large search space problems that often occur in metaproteomics or proteogenomics.
Results: In this study, we showcase a workflow that uses Prosit for spectral library predictions on two common metaproteomes and implement an indexing and search algorithm, Mistle, to efficiently identify experimental mass spectra within the library. Hence, the workflow emulates a classic protein sequence database search with protein digestion but builds a searchable index from spectral predictions as an in-between step.
We compare Mistle to popular search engines, both on a spectral and database search level, and provide evidence that this approach is more accurate than a database search using MSFragger. Mistle outperforms other spectral library search engines in terms of run time and proves to be extremely memory efficient with a 4- to 22-fold decrease in RAM usage. This makes Mistle universally applicable to large search spaces, e.g. covering comprehensive sequence databases of diverse microbiomes.
Availability and implementation: Mistle is freely available on GitHub at https://github.com/BAMeScience/Mistle.
A fast method for microplastic detection is thermal extraction desorption‐gas chromatography/mass spectrometry (TED‐GC/MS), which uses polymer‐specific thermal decomposition products as marker compounds to determine polymer mass contents in environmental samples. So far, matrix impacts of different environmental matrices on TED‐GC/MS performance had not yet been assessed systematically. Therefore, three solid freshwater matrices representing different aquatic bodies with varying organic matter contents were spiked with a total of eight polymers. Additionally, for the first time, the two biodegradable polymers polybutylene adipate terephthalate (PBAT) and polylactide (PLA) were analysed using TED‐GC/MS. The methodological focus of this work was on detectability, quality of signal formation as well as realisation of quantification procedures and determination of the limit of detection (LOD) values. Overall, TED‐GC/MS allowed the unambiguous detection of the environmentally most relevant polymers analysed, even at low mass contents: 0.02 wt% for polystyrene (PS), 0.04 wt% for the tyre component styrene butadiene rubber (SBR) and 0.2 wt% for polypropylene (PP), polyethylene (PE) and PBAT. Further, all obtained LOD values were increased in all matrices compared to the neat polymer without matrix. The LOD of the standard polymers were increased similarly (PS: 0.21–0.34 μg, SBR: 0.27–0.38 μg, PP: 0.32–0.36 μg, PMMA: 0.64–1.30 μg, PET: 0.90–1.37 μg, PE: 3.80–6.99 μg) and their decompositions by radical scission processes were not significantly influenced by the matrices. In contrast, matrixspecific LOD increases of both biodegradable polymers PBAT (LOD: 1.41–7.18 μg) and PLA (0.84–20.46 μg) were observed, probably due to their hetero‐functional character and interactions with the matrices. In conclusion, the TED‐GC/MS performance is not solely determined by the type of the polymers but also by the composition of the matrix.
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.
The combination of acoustically levitated droplets, mid-IR laser evaporation, and subsequent post-ionization by secondary electrospray ionization was applied for monitoring the enzymatic digestion of various proteins. Acoustically levitated droplets are an ideal, wall-free model reactor, readily allowing compartmentalized microfluidic trypsin digestions. Time-resolved interrogation of the droplets yielded real-time information on the progress of the reaction and thus provided insights into reaction kinetics. After 30 min of digestion in the acoustic levitator, the obtained protein sequence coverages were identical to the reference overnight digestions. Importantly, our results clearly demonstrate that the applied experimental setup can be used for the real-time investigation of chemical reactions. Furthermore, the described methodology only uses a fraction of the typically applied amounts of solvent, analyte, and trypsin. Thus, the results exemplify the use of acoustic levitation as a green analytical chemistry alternative to the currently used batch reactions.
Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly
(2023)
Monoclonal antibodies are biotechnologically produced proteins with various applications in research, therapeutics and diagnostics. Their ability to recognize and bind to specific molecule structures makes them essential research tools and therapeutic agents. Sequence information of antibodies is helpful for understanding antibody–antigen interactions and ensuring their affinity and specificity. De novo protein sequencing based on mass spectrometry is a valuable method to obtain the amino acid sequence of peptides and proteins without a priori knowledge. In this study, we evaluated six recently developed de novo peptide sequencing algorithms (Novor, pNovo 3, DeepNovo, SMSNet, PointNovo and Casanovo), which were not specifically designed for antibody data. We validated their ability to identify and assemble antibody sequences on three multi-enzymatic data sets. The deep learning-based tools Casanovo and PointNovo showed an increased peptide recall across different enzymes and data sets compared with spectrum-graph-based approaches. We evaluated different error types of de novo peptide sequencing tools and their performance for different numbers of missing cleavage sites, noisy spectra and peptides of various lengths. We achieved a sequence coverage of 97.69–99.53% on the light chains of three different antibody data sets using the de Bruijn assembler ALPS and the predictions from Casanovo. However, low sequence coverage and accuracy on the heavy chains demonstrate that complete de novo protein sequencing remains a challenging issue in proteomics that requires improved de novo error correction, alternative digestion strategies and hybrid approaches such as homology search to achieve high accuracy on long protein sequences.
Probability based taxonomic profiling of viral and microbiome samples using PepGM and Unipept
(2022)
In mass spectrometry based proteomics, protein homology leads to many shared peptides within and between species. This complicates
taxonomic inference in samples of unknown taxonomic origin. PepGM uses a graphical model for taxonomic profiling of viral proteomes and
metaproteomic datasets providing taxonomic confidence scores. To build the graphical model, a list of potentially present taxa needs to be
inferred. To this end, we integrate Unipept, which enables the fast querying of potentially present taxa. Together, they allow for taxonomic
inference with statistically sound confidence scores.