Chemische Charakterisierung und Spurenanalytik
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Mass Spectrometry (MS) and Nuclear Magnetic Resonance Spectroscopy (NMR) are critical components of every industrial chemical process as they provide information on the concentrations of individual compounds and by-products. These processes are carried out manually and by a specialist, which takes a substantial amount of time and prevents their utilization for real-time closed-loop process control. This paper presents recent advances from two projects that use Artificial Neural Networks (ANNs) to address the challenges of automation and performance-efficient realizations of MS and NMR. In the first part, a complete toolchain has been developed to develop simulated spectra and train ANNs to identify compounds in MS. In the second part, a limited number of experimental NMR spectra have been augmented by simulated spectra to train an ANN with better prediction performance and speed than state-of-theart analysis. These results suggest that, in the context of the digital transformation of the process industry, we are now on the threshold of a possible strongly simplified use of MS and MRS and the accompanying data evaluation by machine-supported procedures, and can utilize both methods much wider for reaction and process monitoring or quality control.
MALDI-TOF-MS-Based Identification of Monoclonal Murine Anti-SARS-CoV-2 Antibodies within One Hour
(2022)
During the SARS-CoV-2 pandemic, many virus-binding monoclonal antibodies have been developed for clinical and diagnostic purposes. This underlines the importance of antibodies as universal bioanalytical reagents. However, little attention is given to the reproducibility crisis that scientific studies are still facing to date. In a recent study, not even half of all research antibodies mentioned in publications could be identified at all. This should spark more efforts in the search for practical solutions for the traceability of antibodies. For this purpose, we used 35 monoclonal antibodies against SARS-CoV-2 to demonstrate how sequence-independent antibody identification can be achieved by simple means applied to the protein. First, we examined the intact and light chain masses of the antibodies relative to the reference material NIST-mAb 8671. Already half of the antibodies could be identified based solely on these two parameters. In addition, we developed two complementary peptide mass fingerprinting methods with MALDI-TOF-MS that can be performed in 60 min and had a combined sequence coverage of over 80%. One method is based on the partial acidic hydrolysis of the protein by 5 mM of sulfuric acid at 99 degrees C. Furthermore, we established a fast way for a tryptic digest without an alkylation step. We were able to show that the distinction of clones is possible simply by a brief visual comparison of the mass spectra. In this work, two clones originating from the same immunization gave the same fingerprints. Later, a hybridoma sequencing confirmed the sequence identity of these sister clones. In order to automate the spectral comparison for larger libraries of antibodies, we developed the online software ABID 2.0. This open-source software determines the number of matching peptides in the fingerprint spectra. We propose that publications and other documents critically relying on monoclonal antibodies with unknown amino acid sequences should include at least one antibody fingerprint. By fingerprinting an antibody in question, its identity can be confirmed by comparison with a library spectrum at any time and context.
The theory of a new calibration approach for obtaining absolute isotope ratios of multi-isotopic elements without the use of any standard has been developed. The calibration approach basically uses the difference in the instrumental isotope fractionation of two different types of mass spectrometers, leading to two different fractionation lines in a three-isotope diagram. When measuring the same sample with both mass spectrometers, the different fractionation lines have one point in common: this is the ‘true’ logarithmized isotope ratio pair of the sample. Thus, the intersection of both fractionation lines provides us with the absolute isotope ratios of the sample. This theory has been tested in practice by measuring Cd and of Pb isotope ratios in the certified reference materials BAM-I012 and NIST SRM981 by thermal ionization mass spectrometry and by inductively coupled plasma mass spectrometry while varying the ionization conditions for both mass spectrometers. With this experiment, the theory could be verified, and absolute isotope ratios were obtained, which were metrologically compatible with the certified isotope ratios. The so-obtained absolute isotope ratios are biased by − 0.5% in average, which should be improved with further developments of the method. This calibration approach is universal, as it can be applied to all elements with three or more isotopes and it is not limited to the type of mass spectrometers applied; it can be applied as well to secondary ion mass spectrometry or others. Additionally, this approach provides information on the fractionation process itself via the triple-isotope fractionation exponent θ.
Untargeted accurate strain-level classification of a priori unidentified organisms using tandem mass spectrometry is a challenging task. Reference databases often lack taxonomic depth, limiting peptide assignments to the species level. However, the extension with detailed strain information increases runtime and decreases statistical power. In addition, larger databases contain a higher number of similar proteomes. We present TaxIt, an iterative workflow to address the increasing search space required for MS/MS-based strain-level classification of samples with unknown taxonomic origin. TaxIt first applies reference sequence data for initial identification of species candidates, followed by automated acquisition of relevant strain sequences for low level classification. Furthermore, proteome similarities resulting in ambiguous taxonomic assignments are addressed with an abundance weighting strategy to increase the confidence in candidate taxa. For benchmarking the performance of our method, we apply our iterative workflow on several samples of bacterial and viral origin. In comparison to noniterative approaches using unique peptides or advanced abundance correction, TaxIt identifies microbial strains correctly in all examples presented (with one tie), thereby demonstrating the potential for untargeted and deeper taxonomic classification. TaxIt makes extensive use of public, unrestricted, and continuously growing sequence resources such as the NCBI databases and is available under open-source BSD license at https://gitlab.com/rki_bioinformatics/TaxIt.
Mass spectrometric Methods MC-ICP-MS and TIMS) are without doubt the working horse of stable isotope analysis. However, drawbacks of these methods include the high costs for instruments and their operation, experienced operators and elaborate chromatographic sample preparation which are time consuming.
Optical spectrometric methods are proposed as faster and low-cost alternative for the analysis of isotope ratios of selected elements by means of high-resolution continuum source molecular absorption spectrometry (HR-CS-MAS) and laser ablation molecular isotopic spectrometry (LAMIS). First, stable isotope amount compositions of boron (B) and magnesium (Mg) were determined based on the absorption spectra of in-situ generated heteronuclear diatomic molecules (MH or MX) in graphite furnace HR-CS-MAS. The use of a modular simultaneous echelle spectrograph (MOSES) helps to find the maximal isotope shift in the diatomic molecular spectra produced in a graphite furnace by using isotopic spike solutions. Isotopes of boron (10B and 11B) were studied via their hydrides for the electronic transition X 1Σ+ → A 1Π. The spectrum of a given sample is a linear combination of the 10BH molecule and its isotopologue 11BH. Therefore, the isotopic composition of samples can be calculated by a partial least square regression (PLS). For this, a spectral library was built by using samples and spikes with known isotope composition. Boron isotope ratios measured by HR-CS-MAS are identical with those measured by mass spectrometric methods at the 0.15 ‰ level. Similar results were obtained for a multiple isotope system like Mg (24Mg, 25Mg, and 26Mg), where isotope shifts of their isotopologues can be resolved in the MgF molecule for the electronic transition X 2Σ → A 2 Πi. Finally, the application of molecular spectrometry via emission by LAMIS is compared and discussed.
High-resolution mass spectrometry, either combined with gas or liquid chromatography (GC/LC-HR-MS), is currently the most powerful analytical option for broad nontargeted small molecule analysis. To transform HR-MS raw data from metabolomics or environmental studies into chemically meaningful data, several computational steps are needed, including peak detection, deconvolution of these peaks into compounds and putative identification of compounds using databases. Each of these steps can cause problems and still requires methodological advancements. Computational compound annotation as one of the steps, however, has proven particularly challenging, mainly due to the chemical diversity of organic analytes. In addition, different annotation approaches are needed for the different platforms used in HR-MS screening. We recently introduced InterpretMSSpectrum as an annotation workflow for GC-HR-MS using atmospheric pressure chemical ionization (APCI). InterpretMSSpectrum locates molecular ion, fragment and adduct peaks, calculates their most likely sum formula combination and graphically summarizes results as an annotated mass spectrum. As a complementary approach for LC-HR-MS, we presented findMAIN, which scores MS1 spectra based on explained intensity, mass accuracy and isotope charge agreement of adducts and related electrospray ionization (ESI) products to determine the neutral mass of unknown compounds. Both approaches were validated against large spectral libraries containing more than 600 compounds, for which correct annotation was achieved in over 80% of the cases. Based on the experiences from this validation, we here compare soft-ionization GC/LC-HR-MS regarding “annotatability” of unknown compounds from a computational perspective. As a main advantage for GC-HR-MS, the relatively uniform ionization behavior of commonly used trimethylsilyl (TMS) derivatives observed under APCI allowed differentiation of molecular ion peaks from in-source fragments based on relatively compact set of rules. By contrast, neutral mass inference in ESI required a more complex evaluation scheme, due to the higher diversity of ionization products observable in ESI. We demonstrate such differences by practical examples of both software packages applied to metabolomics studies and discuss the challenges connected to transferring the approaches to environmental screening.
Tandem mass spectrometry represents an important analytical tool to unravel molecular structures and to study the gas-phase behavior of organic molecules. Besides commonly used methods like collision-induced dissociation and electron capture or transfer dissociation, new ultraviolet light–based techniques have the potential to synergistically add to the activation methods. Here, we present a new simple, yet robust, experimental design for polychromatic activation of trapped ions using the 115–160 nm output of a commercially available deuterium lamp. The resulting continuous dissociative excitation with photons of a wide energy range from 7.7 to 10.8 eV is studied for a comprehensive set of analyte classes in both positive and negative ion modes. While being simple, affordable, compact, and of low maintenance, the new setup initiates fragmentation of most precursor ions via their known dissociation pathways. Additionally, some new fragmentation patterns were discovered. Especially, electron loss and electron capture reactions with subsequent fragmentations were observed. For oligonucleotides, peptides, carbohydrates, and organic dyes, in comparison to collision-induced dissociation, a significantly wider fragment distribution was obtained, resulting in an information increase. Since the individual photons carry enough energy to post-ionize the nascent fragments, a permanent vacuum ultraviolet light exposure inside the ion trap potentially goes along with a general increase in detection capability.
In this study, the thermal decomposition of 1,3,5-tris-(2,3-dibromopropyl)-1,3,5-triazine-2,4,6-trione (TDBPTAZTO) and 2,4,6-tris-(2,4,6-tribromo-phenoxy)-1,3,5-triazine (TTBP-TAZ) were investigated for the first time by thermogravimetric analysis. Both compounds were thermal degraded between 225 and 350 °C (TDBP-TAZTO) as well as 300 and 400 °C (TTBP-TAZ).
As a result, mass loss (%) of 98.5% for TTBP-TAZ and 95.4% for TDBP-TAZTO at 600 °C under N2 were observed. The major pyrolytic degradation products of TTBP-TAZ were formed in a single step and identified by FTIR analysis as 2,4,6-tribromophenol and further bromine-substituted aromatic compounds. In comparison, TDBP-TAZTO was pyrolytic degraded in two steps, whereby on the first step the release of hydrogen Bromide and 1,3,5-triallyl-1,3,5-triazine-2,4,6-trione could be detected. In the second minor step, isocyanic acid could be additionally identified.
Subsequently, the obtained products of the TGA-FTIR measurements were used for a targeted search for mass fragments in mass spectrometry measurements. For TTBP-TAZ, only the degradation product 1,3,5-tribromobenzene could be detected by MS/MS analyzes. No comparable thermal degradation products, except hydrogen bromide, were observed in the MS/MS spectra of TDBP-TAZTO. Therefore, the search of further mass fragments was not possible compared to the findings of the TGA-FTIR measurements.
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.
Screening of one-bead-one-compound (OBOC) libraries is a proven procedure for the identification of protein-binding ligands. The demand for binders with high affinity and specificity towards various targets has surged in the biomedical and pharmaceutical field in recent years. The traditional peptide screening involves tedious steps such as affinity selection, bead picking, sequencing, and characterization. Herein, we present a high-throughput “all-on-one chip” system to avoid slow and technically complex bead picking steps. On a traditional glass slide provided with an electrically conductive tape, beads of a combinatorial peptide library are aligned and immobilized by application of a precision sieve. Subsequently, the chip is incubated with a fluorophore-labeled target protein. In a fluorescence scan followed by matrix-assisted laser desorption/ionization (MALDI)-time of flight (TOF) mass spectrometry, high-affinity binders are directly and unambiguously sequenced with high accuracy without picking of the positive beads. The use of an optimized ladder sequencing approach improved the accuracy of the de-novo sequencing step to nearly 100%. The new technique was validated by employing a FLAG-based model system, identifying new peptide binders for the monoclonal M2 anti-FLAG antibody, and was finally utilized to search for IgG-binding peptides. In the present format, more than 30,000 beads can be screened on one slide.