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In recent years mass spectrometric methods, in particular matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI) time-of-flight (TOF) mass spectrometry (MS) have become indispensable tools for analyzing molecular masses and mass distributions of polymers. Moreover, these techniques offer the advantage of being able to determine simultaneously chemical functionality, and compositional and topological distributions of polymers. Especially in combination with liquid and/or gas phase separation methods, a comprehensive polymer characterization can be achieved and the difficulties of MS to analyze chemically heterogeneous polymers, copolymers, and samples with broad molecular mass distribution can be overcome.
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.
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.
The analytical utility of a new and simple to use ionization method, matrix-assisted ionization (MAI), coupled with ion mobility spectrometry (IMS) and mass spectrometry (MS) is used to characterize a 2-armed europium(III)-containing poly(ethylene glycol) (Eu-PEG) complex directly from a crude sample. MAI was used with the matrix 1,2-dicyanobenzene, which affords low chemical background relative to matrix-assisted laser desorption/ionization (MALDI) and electrospray ionization (ESI). MAI provides high ion abundance of desired products in comparison to ESI and MALDI. Inductively coupled plasma-MS measurements were used to estimate a maximum of 10% of the crude sample by mass was the 2-arm Eu-PEG complex, supporting evidence of selective ionization of Eu-PEG complexes using the new MAI matrix, 1,2-dicyanobenzene. Multiply charged ions formed in MAI enhance the IMS gas-phase separation, especially relative to the singly charged ions observed with MALDI. Individual components are cleanly separated and readily identified, allowing characterization of the 2-arm Eu-PEG conjugate from a mixture of the 1-arm Eu-PEG complex and unreacted starting materials. Size-exclusion chromatography, liquid chromatography at critical conditions, MALDI-MS, ESI-MS, and ESI-IMS-MS had difficulties with this analysis, or failed.
Polymer deposition morphology by electrospray deposition - Modifications through distance variation
(2014)
Electrospray deposition (ESD) of highly diluted polymers was examined with regard to the deposited surface structure. Only the flight distance (flight time) onto the resulting deposited surface was varied from 20 to 200 mm.
An apparatus without any additional heating or gas flows was used. Polyacrylic acid (PAA) and polyallylamine (PAAm) in methanol were deposited on Si wafers. The polymer layers were characterized by scanning electron microscopy, X-ray photoelectron spectroscopy, derivatization reactions and Fourier transform infrared spectroscopy using a grazing incidence unit.
SEM images illustrated the changing structures of PAA and PAAm. For PAA the deposited structure changed from a smooth film (20 mm) to a film with individual droplets on the coated surface (100 mm and 200 mm), while for PAAm individual droplets can be seen at all distances. The ESD process with cascades of splitting droplets slows down for PAA after distances greater than 40 mm. In contrast, the ESD process for PAAm is nearly stopped within the first flight distance of 20 mm. Residual solvent analysis showed that most of the solvent evaporated within the first 20 mm capillary-sample distance.