The Kendrick analysis for polymer mass spectrometry

Resolution-enhanced Kendrick mass defect analysis for improved mass spectrometry characterization of lignin

Lignin is a promising renewable source of valuable organic compounds and environmentally benign materials. However, its involvement in economic circulation and the creation of new biorefining technologies require an understanding of its chemical composition and structure. This problem can be overcome by applying mass spectrometry analytical techniques in combination with advanced chemometric methods for mass spectra processing. The present study is aimed at the development of mass defect filtering to characterize the chemical composition of lignin at the molecular level. This study introduces a novel approach involving resolution-enhanced Kendrick mass defect (REKMD) analysis for the processing of atmospheric pressure photoionization Orbitrap mass spectra of lignin. The set of priority Kendrick fractional base units was predefined in model experiments and provided a substantially expanding available mass defect range for the informative visualization of lignin mass spectra. The developed REKMD analysis strategy allowed to obtain the most complete data on all the homologous series typical of lignin and thus facilitated the interpretation and assignment of elemental compositions and structural formulas to oligomers detected in extremely complex mass spectra, including tandem ones. For the first time, the minor modifications (sulfation) of lignin obtained in ionic liquid-based biorefining processes were revealed.

Mass spectrometry of polymers: A tutorial review

Ever since the inception of synthetic polymeric materials in the late 19th century, the number of studies on polymers as well as the complexity of their structures have only increased. The development and commercialization of new polymers with properties fine-tuned for specific technological, environmental, consumer, or biomedical applications requires powerful analytical techniques that permit the in-depth characterization of these materials. One such method with the ability to provide chemical composition and structure information with high sensitivity, selectivity, specificity, and speed is mass spectrometry (MS). This tutorial review presents and exemplifies the various MS techniques available for the elucidation of specific structural features in a synthetic polymer, including compositional complexity, primary structure, architecture, topology, and surface properties. Key to every MS analysis is sample conversion to gas-phase ions. This review describes the fundamentals of the most suitable ionization methods for synthetic materials and provides relevant sample preparation protocols. Most importantly, structural characterizations via one-step as well as hyphenated or multidimensional approaches are introduced and demonstrated with specific applications, including surface sensitive and imaging techniques. The aim of this tutorial review is to illustrate the capabilities of MS for the characterization of large, complex polymers and emphasize its potential as a powerful compositional and structural elucidation tool in polymer chemistry.

Ring Opening Metathesis Polymerization of Cyclooctadiene and Cyclooctene with Dihydrofuran: Influence of Ru Fischer Carbene

Vinyl ethers are commonly used to deactivate Grubbs catalysts and terminate ring opening metathesis polymerization (ROMP) by forming Fischer carbene species with attenuated metathesis reactivity. However, we recently demonstrated that a cyclic enol ether, 2,3-dihydrofuran (DHF), can in fact be homopolymerized or copolymerized with norbornene derivatives. 1,5-Cyclooctadiene (COD) and cyclooctene (COE) consist of an important class of ROMP monomers, and we describe here a study of their copolymerization with DHF. Addition of DHF greatly suppressed the ROMP activity of COD and COE and resulted in significant alkene isomerization of COD. Chloranil was found to be an effective additive to prevent undesired isomerization and promote copolymerization. As a result, high molecular weight COD/COE and DHF copolymers were synthesized. Hydrolysis of the enol ether main chain linkages yields polyalkenamers with alcohol and aldehyde end groups. This study encourages further exploration of the in situ formed Ru Fischer carbene species in ROMP to access degradable polymers.

Quantitative analysis of biopolymers in lignocellulosic biomass feedstocks via laser-assisted micro-pyrolysis flowing atmospheric-pressure afterglow high-resolution ambient mass spectrometry

Herein, a diode laser-assisted micro-pyrolysis (LAMP) technique coupled with FAPA high resolution mass spectrometry (HRMS) is demonstrated for fast chemical characterization of lignocellulosic biomass feedstocks. The solid lignocellulosic biomass can be analyzed directly with minimal sample preparation. The mass spectra of the pyrolysis products are interpreted with the aid of data visualization tools such as Kendrick mass defect (KMD) plots and van Krevelen plots. Furthermore, quantitation of lignin/cellulose/hemicellulose, sugar contents of glucan/xylan/galactan/arabinan and lignin monomeric unit S/G is achieved with good accuracy and precision, through multivariate analysis methods, including partial least squares regression (PLSR) and support vector regression (SVR).

Contribution of Hydroxycinnamic Acids to Color Formation in Nonenzymatic Browning Reactions with Key Maillard Reaction Intermediates

The Maillard reaction is a vital part of food processing, involving a vast number of complex reaction pathways, resulting in high-molecular-weight colorants. So far, studies have been focused on the conversion of carbohydrates and amino compounds, but the literature elaborating the contribution of phenolic compounds to the formation of the colored end-products is still rare. The aim of this study was to characterize early reactions, underlying the formation of phenol-containing melanoidins. For this purpose, binary model systems of the prominent phenolic compounds caffeic acid and ferulic acid combined with α-dicarbonyl compounds typically formed in the Maillard reaction such as glyoxal, methylglyoxal, and diacetyl were analyzed after heat treatment. High-resolution mass spectrometry revealed that decarboxylation, aromatic electrophilic substitution, and nucleophilic addition are important reaction steps that lead to colored heterogeneous oligomers. Polymerization was favored for phenolic compounds with a high electron density in the aromatic system and for α-dicarbonyl compounds carrying aldehyde functions.

Characterizing lignins from various sources and treatment processes after optimized sample preparation techniques and analysis via ESI-HRMS and custom mass defect software tools

Sample preparation of complex, natural mixtures such as lignin prior to mass spectrometry analysis, however minimal, is a critical step in ensuring accurate and interference-free results. Modern shotgun-MS techniques, where samples are directly injected into a high-resolution mass spectrometer (HRMS) with no prior separation, usually still require basic sample pretreatment such as filtration and appropriate solvents for full dissolution and compatibility with atmospheric pressure ionization interfaces. In this study, sample preparation protocols have been established for a unique sample set consisting of a wide variety of degraded lignin samples from numerous sources and treatment processes. The samples were analyzed via electrospray (ESI)-HRMS in negative and positive ionization modes. The resulting information-rich HRMS datasets were then transformed into the mass defect space with custom R scripts as well as the open-source Constellation software as an effective way to visualize changes between the samples due to the sample preparation and ionization conditions as well as a starting point for comprehensive characterization of these varied sample sets. Optimized conditions for the four investigated lignins are proposed for ESI-HRMS analysis for the first time, giving an excellent starting point for future studies seeking to better characterize and understand these complex mixtures.

Differentiation of Four Polyvinylidene Fluoride Polymers Based on Their End Groups by DART-FT-ICR MS and Kendrick Plots

Nowadays, synthetic polymers are produced and used in many materials for different applications. Matrix-assisted laser desorption/ionization or electrospray mass spectrometry are classically used to investigate them, but these techniques require sample preparation steps, which are not always suitable for the study of insoluble or formulated polymers. Alternatively, direct real-time (DART) ionization analysis may be conducted without sample preparation. Four polyvinylidene fluoride (PVDF) polymers involving the C2H2F2 repeating unit coming from different suppliers have been analyzed by DART Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) in negative-ion mode. The obtained mass spectra systematically displayed an oligomeric distribution between m/z 400 and 1300 of [M - H]-, [M + O2]•-, and [M + NO2]- ions. Kendrick plots were used to ease the identification of PVDF end-groups and establish a difference between the samples. Both commercial PVDF polymers shared the same α+ω end groups formula, which confirmed a similar polymerization process for their synthesis. The two other PVDFs were clearly different from the commercial ones by the occurrence of specific end-groups. MS/MS and MS3 experiments were conducted to obtain structural information on these end-groups.

What's the defect? Using mass defects to study oligomerization of membrane proteins and peptides in nanodiscs with native mass spectrometry

Many membrane proteins form functional complexes that are either homo- or hetero-oligomeric. However, it is challenging to characterize membrane protein oligomerization in intact lipid bilayers, especially for polydisperse mixtures. Native mass spectrometry of membrane proteins and peptides inserted in lipid nanodiscs provides a unique method to study the oligomeric state distribution and lipid preferences of oligomeric assemblies. To interpret these complex spectra, we developed novel data analysis methods using macromolecular mass defect analysis. Here, we provide an overview of how mass defect analysis can be used to study oligomerization in nanodiscs, discuss potential limitations in interpretation, and explore strategies to resolve these ambiguities. Finally, we review recent work applying this technique to studying formation of antimicrobial peptide, amyloid protein, and viroporin complexes with lipid membranes.

A combined liquid chromatography - trapped ion mobility - tandem high-resolution mass spectrometry and multivariate analysis approach for the determination of enzymatic reactivity descriptors in biomass hydrolysates

Intermediate products such as oxygenated compounds may interfere with bioconversion kinetics of lignocellulosic biomass into bioethanol. This work presents a multidimensional approach, based on liquid chromatography (LC), trapped ion mobility spectrometry (TIMS), tandem high-resolution mass spectrometry (HRMS/MS), and multivariate analysis, for the identification of enzymatic reactivity descriptors in 22 industrial biomass samples, called hydrolysates. The first part of the study is dedicated to the improvement of the chemical diversity assessment of the hydrolysates through an original three-dimensional Van Krevelen diagram displaying the double bond equivalent (DBE) as third dimension. In a second part, the evaluation of data by multivariate data analysis allowed the discrimination of sample according to the biomass type and the level of enzymatic reactivity. In the last part, a potential descriptor of low enzymatic reactivity was selected and used in a case study. An in-depth structural analysis was performed on the feature annotated as carbohydrate derivative. Considering the intricate fragmentation spectrum exhibited by the selected feature, trapped ion mobility was employed to enhance separation prior to the HRMS/MS experiments. This final step improved data interpretation and increased the identification confidence level leading to the characterization of xylotriose, 3,5-dimethoxy-4-hydroxybenzaldehyde and 4-hydroxy-3-methoxy-cinnamaldehyde. This is the first study to present an untargeted multidimensional approach for the identification of enzymatic hydrolysis inhibitors in industrial hydrolysate samples.

Evaluating non-targeted analysis methods for chemical characterization of organic contaminants in different matrices to estimate children's exposure

BACKGROUND

Children are vulnerable to environmental exposure of contaminants due to their small size, lack of judgement skills, as well as their proximity to dust, soil, and other environmental sources. A better understanding about the types of contaminants that children are exposed to or how their bodies retain or process these compounds is needed.

OBJECTIVE

In this study, we have implemented and optimized a methodology based on non-targeted analysis (NTA) to characterize chemicals in dust, soil, urine, and in the diet (food and drinking water) of infant populations.

METHODS

To evaluate potential toxicological concerns associated with chemical exposure, families with children between 6 months and 6 years of age from underrepresented groups were recruited in the greater Miami area. Samples of soil, indoor dust, food, water, and urine were provided by the caregivers, prepared by different techniques (involving online SPE, ASE, USE, QuEChERs), and analyzed by liquid chromatography-high resolution mass spectrometry (LC-HRMS). Data post-processing was performed using the small molecule structure identification software, Compound Discoverer (CD) 3.3, and identified features were plotted using Kendrick mass defect plot and Van Krevelen diagrams to show unique patterns in different samples and regions of anthropogenic compound classifications.

RESULTS

The performance of the NTA workflow was evaluated using quality control standards in terms of accuracy, precision, selectivity, and sensitivity, with an average of 98.2%, 20.3%, 98.4% and 71.1%, respectively. Sample preparation was successfully optimized for soil, dust, water, food, and urine. A total of 30, 78, 103, 20 and 265 annotated features were frequently identified (detection frequency >80%) in the food, dust, soil, water, and urine samples, respectively. Common features detected in each matrix were prioritized and classified, providing insight on children's exposure to organic contaminants of concern and their potential toxicities.

IMPACT STATEMENT

Current methods to assess the ingestion of chemicals by children have limitations and are generally restricted by specific classes of targeted organic contaminants of interest. This study offers an innovative approach using non-targeted analysis for the comprehensive screening of organic contaminants that children are exposed to through dust, soil, and diet (drinking water and food).

PyC2MC: An Open-Source Software Solution for Visualization and Treatment of High-Resolution Mass Spectrometry Data

Complex molecular mixtures are encountered in almost all research disciplines, such as biomedical 'omics, petroleomics, and environmental sciences. State-of-the-art characterization of sample materials related to these fields, deploying high-end instrumentation, allows for gathering large quantities of molecular composition data. One established technological platform is ultrahigh-resolution mass spectrometry, e.g., Fourier-transform mass spectrometry (FT-MS). However, the huge amounts of data acquired in FT-MS often result in tedious data treatment and visualization. FT-MS analysis of complex matrices can easily lead to single mass spectra with more than 10,000 attributed unique molecular formulas. Sophisticated software solutions to conduct these treatment and visualization attempts from commercial and noncommercial origins exist. However, existing applications have distinct drawbacks, such as focusing on only one type of graphic representation, being unable to handle large data sets, or not being publicly available. In this respect, we developed a software, within the international complex matrices molecular characterization joint lab (IC2MC), named "python tools for complex matrices molecular characterization" (PyC2MC). This piece of software will be open-source and free to use. PyC2MC is written under python 3.9.7 and relies on well-known libraries such as pandas, NumPy, or SciPy. It is provided with a graphical user interface developed under PyQt5. The two options for execution, (1) a user-friendly route with a prepacked executable file or (2) running the main python script through a Python interpreter, ensure a high applicability but also an open characteristic for further development by the community. Both are available on the GitHub platform (https://github.com/iC2MC/PyC2MC_viewer).

Frontal Polymerizations: From Chemical Perspectives to Macroscopic Properties and Applications

The synthesis and processing of most thermoplastics and thermoset polymeric materials rely on energy-inefficient and environmentally burdensome manufacturing methods. Frontal polymerization is an attractive, scalable alternative due to its exploitation of polymerization heat that is generally wasted and unutilized. The only external energy needed for frontal polymerization is an initial thermal (or photo) stimulus that locally ignites the reaction. The subsequent reaction exothermicity provides local heating; the transport of this thermal energy to neighboring monomers in either a liquid or gel-like state results in a self-perpetuating reaction zone that provides fully cured thermosets and thermoplastics. Propagation of this polymerization front continues through the unreacted monomer media until either all reactants are consumed or sufficient heat loss stalls further reaction. Several different polymerization mechanisms support frontal processes, including free-radical, cat- or anionic, amine-cure epoxides, and ring-opening metathesis polymerization. The choice of monomer, initiator/catalyst, and additives dictates how fast the polymer front traverses the reactant medium, as well as the maximum temperature achievable. Numerous applications of frontally generated materials exist, ranging from porous substrate reinforcement to fabrication of patterned composites. In this review, we examine in detail the physical and chemical phenomena that govern frontal polymerization, as well as outline the existing applications.

Applications of MALDI-TOF-MS in structural characterization of synthetic polymers

In recent years, matrix assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) has been utilized to rapidly and precisely characterize the detailed molecular structures of synthetic polymers. This review summarizes recent progress regarding MALDI-TOF-MS for the characterization of synthetic polymers with a focus on specific important experimental aspects including sample preparation, the choice of matrix, the effects of cationizing agents and solvents, data processing and various applications. Finally, the recent trend of MALDI-TOF-MS development is discussed. We hope this review will be instructive for graduate students and junior users who need to use MALDI-TOF-MS as a necessary characterization technique for new synthetic polymers.

MALINTO: A New MALDI Interpretation Tool for Enhanced Peak Assignment and Semiquantitative Studies of Complex Synthetic Polymers

The newly developed MALDI interpretation tool ("MALINTO") allows for the accelerated characterization of complex synthetic polymers via MALDI mass spectrometry. While existing software provides solutions for simple polymers like poly(ethylene glycol), polystyrene, etc., they are limited in their application on polycondensates synthesized from two different kinds of monomers (e.g., diacid and diol in polyesters). In addition to such A₂ + B₂ polycondensates, MALINTO covers branched and even multicyclic polymer systems. Since the MALINTO software works based on input data of monomers/repeating units, end groups, and adducts, it can be applied on polymers whose components are previously known or elucidated. Using these input data, a list with theoretically possible polymer compositions and resulting m/z values is calculated, which is further compared to experimental mass spectrometry data. For optional semiquantitative studies, peak areas are allocated according to their assigned polymer composition to evaluate both comonomer and terminating group ratios. Several tools are implemented to avoid mistakes, for example, during peak assignment. In the present publication, the functions of MALINTO are described in detail and its broad applicability on different linear polymers as well as branched and multicyclic polycondensates is demonstrated. Fellow researchers will benefit from the accelerated peak assignment using the freely available MALINTO software and might be encouraged to explore the potential of MALDI mass spectrometry for (semi)quantitative applications.

New algorithms demonstrate untargeted detection of chemically meaningful changing units and formula assignment for HRMS data of polymeric mixtures in the open-source constellation web application

The field of high-resolution mass spectrometry (HRMS) and ancillary hyphenated techniques comprise a rapidly expanding and evolving area. As popularity of HRMS instruments grows, there is a concurrent need for tools and solutions to simplify and automate the processing of the large and complex datasets that result from these analyses. Constellation is one such of these tools, developed by our group over the last two years to perform unsupervised trend detection for repeating, polymeric units in HRMS data of complex mixtures such as natural organic matter, oil, or lignin. In this work, we develop two new unsupervised algorithms for finding chemically-meaningful changing units in HRMS data, and incorporate a molecular-formula-finding algorithm from the open-source CoreMS software package, both demonstrated here in the Constellation software environment. These algorithms are evaluated on a collection of open-source HRMS datasets containing polymeric analytes (PEG 400 and NIST standard reference material 1950, both metabolites in human plasma, as well as a swab extract containing polymers), and are able to successfully identify all known changing units in the data, including assigning the correct formulas. Through these new developments, we are excited to add to a growing body of open-source software specialized in extracting useful information from complex datasets without the high costs, technical knowledge, and processor-demand typically associated with such tools.

Novel Ambient Oxidation Trends in Fingerprint Aging Discovered by Kendrick Mass Defect Analysis

A Kendrick mass defect (KMD) plot is an efficient way to disperse complex high-resolution mass spectral data in a visually informative two-dimensional format which allows for the rapid assignment of compound classes that differ by heteroatom content and/or unsaturation. Fingerprint lipid oxidation has the potential to be used to estimate the time since deposition of a fingerprint, but the mass spectra become extremely complex as the lipids degrade. We apply KMD plot analysis for the first time to sebaceous fingerprints aged for 0-7 days to characterize lipid degradation processes analyzed by MALDI-MS. In addition to the ambient ozonolysis of fingerprint lipids previously reported, we observed unique spectral features associated with epoxides and medium chain fatty acid degradation products that are correlated with fingerprint age. We propose an ambient epoxidation mechanism via a peroxyl radical intermediate and the prevalence of omega-10 fatty acyl chains in fingerprint lipids to explain the features observed by the KMD plot analysis. Our hypotheses are supported by an aging experiment performed in a sparse ozone condition and on-surface Paternò-Büchi reaction. A comprehensive understanding of fingerprint degradation processes, afforded by the KMD plots, provides crucial insights for considering which ions to monitor and which to avoid, when creating a robust model for time since deposition of fingerprints.

Differential Organic Contaminant Ionization Source Detection and Identification in Environmental Waters by Nontargeted Analysis

The development of nontargeted analysis (NTA) methods to assess environmental contaminants of emerging concern, which are not commonly monitored, is paramount, especially when no previous knowledge on the identity of the pollution source is available. We compared complementary ionization techniques, namely electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI), in the detection and identification of organic contaminants in tap and surface waters from South Florida. Furthermore, the performance of a simple rationalized NTA method was assessed by analyzing 10 complex mixtures as part of the US Environmental Protection Agency's Non-targeted Analysis Collaborative Trial interlaboratory study, where limitations of the NTA approach have been identified (e.g., number of employed databases, false positives). Different water bodies displayed unique chemical features that can be used as chemical fingerprints for source tracking and discrimination. The APCI technique detected at least threefold as many chemical features as ESI in environmental water samples, corroborating the fact that APCI is more energetic and can ionize certain classes of compounds that are traditionally difficult to ionize by liquid chromatography-mass spectrometry. Kendrick mass defect plots and Van Krevelen diagrams were applied to elucidate unique patterns and theoretical chemical space regions of anthropogenic organic compounds belonging to homologous series or similar classes covered by ESI and APCI. Overall, APCI and ESI were established as complementary, expanding the detected NTA chemical space which would otherwise be underestimated by a single ionization source operated in a single polarity setting. Environ Toxicol Chem 2022;41:1154-1164. © 2021 SETAC.

Optimized micro-sampling and computational analysis for SERS identification of red organic dyes on prints

The goals of this study were to develop a robust methodology and data analysis procedure to identify red dyes in artwork where dye collection is inaccessible by traditional methods. With Surface-Enhanced Raman Spectroscopy (SERS) it is possible to obtain identifying molecular information from dilute and degraded dyes. A minimally invasive, soft-mechanical sampling method to gently contact printed paper is described; using a customized polymeric hydrogel surface with an exposure area of about 1 mm², micrometer-diameter colorant particles were collected. To validate that the sample collection methodology is minimally invasive, test papers were photographed before and after sampling under UV and white light; and DART-MS analysis of the sampled area was conducted. A reference library of SERS spectra from binder (hide glue), dyes (safflower, sappan, and madder), and binder-dye mixtures was built and used by a spectral-matching genetic algorithm (GA). Fifty individual GA runs returned results that precisely matched at least one dye component in 48-50 of the 50 runs, and matched both dyes in a mixture between 29 and 50 of the 50 runs. Finally, in an artwork application, the methodologies were demonstrated on micro-samples from three areas of an 18th century Japanese woodblock print by Suzuki Harunobu in the collection of the Portland Art Museum, on which, madder dyes were positively identified. Conclusions and extensions from this work are expected to contribute to the body of knowledge about 18th c. Japanese woodblock prints.

Automated Feature Mining for Two-Dimensional Liquid Chromatography Applied to Polymers Enabled by Mass Remainder Analysis

A fast algorithm for automated feature mining of synthetic (industrial) homopolymers or perfectly alternating copolymers was developed. Comprehensive two-dimensional liquid chromatography–mass spectrometry data (LC × LC–MS) was utilized, undergoing four distinct parts within the algorithm. Initially, the data is reduced by selecting regions of interest within the data. Then, all regions of interest are clustered on the time and mass-to-charge domain to obtain isotopic distributions. Afterward, single-value clusters and background signals are removed from the data structure. In the second part of the algorithm, the isotopic distributions are employed to define the charge state of the polymeric units and the charge-state reduced masses of the units are calculated. In the third part, the mass of the repeating unit (i.e., the monomer) is automatically selected by comparing all mass differences within the data structure. Using the mass of the repeating unit, mass remainder analysis can be performed on the data. This results in groups sharing the same end-group compositions. Lastly, combining information from the clustering step in the first part and the mass remainder analysis results in the creation of compositional series, which are mapped on the chromatogram. Series with similar chromatographic behavior are separated in the mass-remainder domain, whereas series with an overlapping mass remainder are separated in the chromatographic domain. These series were extracted within a calculation time of 3 min. The false positives were then assessed within a reasonable time. The algorithm is verified with LC × LC–MS data of an industrial hexahydrophthalic anhydride-derivatized propylene glycol-terephthalic acid copolyester. Afterward, a chemical structure proposal has been made for each compositional series found within the data.

A Short-Cut Data Mining Method for the Mass Spectrometric Characterization of Block Copolymers

A new data mining approach as a short cut method is given for the determination of the copolymer composition from mass spectra. Our method simplifies the copolymer mass spectra by reduction of the number of mass peaks. The proposed procedure, namely the selection of the mass peaks, which is based on the most abundant peak of the mass spectrum, can be performed manually or more efficiently using our recently invented Mass-remainder analysis (MARA). The considerable reduction of the MS spectra also simplifies the calculation of the copolymer quantities for instance the number- and weight-average molecular weights (Mn and Mw, respectively), polydispersity index (Đ = Mw/Mn), average molar fraction (cA) and weight fraction (wA) of the comonomer A and so on. These copolymer properties are in line with those calculated by a reference method taking into account all the mass peaks of the copolymer distribution. We also suggest a highly efficient method and template for the determination of the composition drift by processing the reduced mass spectra.

Kendrick Mass Defect Variation to Decipher Isotopic Labeling in Brain Metastases Studied by Mass Spectrometry Imaging

Besides many other applications, isotopic labeling is commonly used to decipher the metabolism of living biological systems. By giving a stable isotopically labeled compound as a substrate, the biological system will use this labeled nutrient as it would with a regular substrate and incorporate stable heavy atoms into new metabolites. Utilizing mass spectrometry, by comparing heavy atom enriched isotopic profiles and naturally occurring ones, it is possible to identify these metabolites and deduce valuable information about metabolism and biochemical pathways. The coupling of this approach with mass spectrometry imaging (MSI) allows one then to obtain 2D maps of metabolisms used by living specimens. As metabolic networks are convoluted, a global overview of the isotopically labeled data set to detect unexpected metabolites is crucial. Unfortunately, due to the complexity of MSI spectra, such untargeted processing approaches are difficult to decipher. In this technical note, we demonstrate the potential of a variation around the Kendrick analysis concept to detect the incorporation of stable heavy atoms into metabolites. The Kendrick analysis uses as a base unit the difference between the mass of the most abundant isotope and the mass of the corresponding stable isotopic tracer (namely, ¹²C and ¹³C). The resulting Kendrick plot offers an alternative method to process the MSI data set with a new perspective allowing for the rapid detection of the ¹³C-enriched metabolites and separating unrelated compounds. This processing method of MS data could therefore be a useful tool to decipher isotopic labeling and study metabolic networks, especially as it does not require advanced computational capabilities.

Mass spectrometry of the soot left after ethylene oxide explosion answers some questions on the crash of Polish Air Force Flight 101

The Polish TU 154M plane, Polish Air Force Flight 101, had crashed near Smolensk on 10th of April 2010. The crash was investigated by The Interstate Aviation Committee, whose conclusions were questioned by a number of Polish scientists. The cause of the crash still appears to be incompletely documented and requires additional evidence. In this paper, investigations of a solid material eluted from a piece of cloth of one of the victims of the crash are described. High resolution mass spectrometry was applied to analyze the soot left after controlled ethylene oxide (EO) explosions, performed under different conditions. These included electric ignition of EO vapors in a large volume steel container, and explosions of glass tubes filled with liquid EO, stimulated by thermally initiated explosions of pentaerythritol tetranitrate (PETN). One of these explosions was conducted in the vessel used for the electric ignition of EO and the other in a hermetically locked, small volume container. It was shown that the soot comprises a set of C₂ H₄ O homopolymers and copolymers whose characteristic MS patterns are condition-dependent. The MS spectrum of the postcrash sample referred to above reveals a number of polymers that are also present in the soot obtained in PETN-initiated ethylene oxide explosions. It can be concluded that the piece of cloth was subjected to an EO explosion initiated by an explosion of energetic material, possibly PETN. Similar control experiments with ethylene glycol (EG) showed that the polymers identified in the investigated postcrash sample could not originate from exploding EG.

High-Resolution Mass Spectrometry and Nontraditional Mass Defect Analysis of Brominated Historical Pigments

The implementation of high-resolution mass spectrometry systems offers new possibilities for the analysis of complex art samples such as historical oil paintings. However, these multicomponent systems generate large and complex data sets that require advanced visualization tools to aid interpretation, especially when no chromatographic separation is performed. In the context of this research, it was crucial to propose a data analysis tool to identify the products generated during the synthesis, drying, and aging of historical pigments. This study reports for the first time a nontraditional mass defect analysis of oil paint samples containing a fugitive brominated-organic pigment, eosin or geranium lake, by using direct infusion electrospray ionization in combination with a high-resolution Orbitrap mass spectrometer. The use of nontraditional Kendrick mass defect plots is presented in this study as a processing and visualization tool to recognize brominated species based on their specific mass defect and isotope pattern. The results demonstrate that this approach could provide valuable molecular compositional information on the degradation pathways of this pigment. We anticipate that mass defect analysis will become highly relevant in future degradation studies of many more historical organic pigments.

Characterizing the Chemical Landscape in Commercial E-Cigarette Liquids and Aerosols by Liquid Chromatography-High-Resolution Mass Spectrometry

The surge in electronic cigarette (e-cig) use in recent years has raised questions on chemical exposures that may result from vaping. Previous studies have focused on measuring known toxicants, particularly those present in traditional cigarettes, while fewer have investigated unknown compounds and transformation products formed during the vaping process in these diverse and constantly evolving products. The primary aim of this work was to apply liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemical fingerprinting techniques for the characterization of e-liquids and aerosols from a selection of popular e-cig products. We conducted nontarget and quantitative analyses of tobacco-flavored e-liquids and aerosols generated using four popular e-cig products: one disposable, two pod, and one tank/mod. Aerosols were collected using a condensation device and analyzed in solution alongside e-liquids by LC-HRMS. The number of compounds detected increased from e-liquids to aerosols in three of four commercial products, as did the proportion of condensed-hydrocarbon-like compounds, associated with combustion. Kendrick mass defect analysis suggested that some of the additional compounds detected in aerosols belonged to homologous series resulting from decomposition of high-molecular-weight compounds during vaping. Lipids in inhalable aerosols have been associated with severe respiratory effects, and lipid-like compounds were observed in aerosols as well as e-liquids analyzed. Six potentially hazardous additives and contaminants, including the industrial chemical tributylphosphine oxide and the stimulant caffeine, were identified and quantified in the e-cig liquids and aerosols analyzed. The obtained findings demonstrate the potential of nontarget LC-HRMS to identify previously unknown compounds and compound classes in e-cig liquids and aerosols, which is critical for the assessment of chemical exposures resulting from vaping.

Reactive Desorption Electrospray Ionization Mass Spectrometry To Determine Intrinsic Degradability of Poly(lactic-co-glycolic acid) Chains

Because of its speed, sensitivity, and ability to scrutinize individual species, mass spectrometry (MS) has become an essential tool in analytical strategies aimed at studying the degradation behavior of polyesters. MS analyses can be performed prior to the degradation event for structural characterization of initial substrates or after it has occurred to measure the decreasing size of products as a function of time. Here, we show that MS can also be usefully employed during the degradation process by online monitoring the chain solvolysis induced by reactive desorption electrospray ionization (DESI). Cleavage of ester bonds in random copolymers of lactic acid (LA) and glycolic acid (GA) was achieved by electrospraying methanol-containing NaOH onto the substrates. Experimental conditions were optimized to generate methanolysis products of high abundance so that mass spectra can be conveniently processed using Kendrick-based approaches. The same reactive-DESI performance was demonstrated for two sample preparations, solvent casting for soluble samples or pressed pellets for highly crystalline substrates, permitting to compare polymers with LA/GA ratios ranging from 100/0 to 5/95. Analysis of sample fractions collected by size exclusion chromatography showed that methanolysis occurs independently of the original chain size, so data recorded for poly(LA-co-GA) (PLAGA) copolymers with the average molecular weight ranging from 10 to 180 kDa could be safely compared. The average mass of methanolysis products was observed to decrease linearly (R² = 0.9900) as the GA content increases in PLAGA substrates, consistent with the susceptibility of ester bonds toward solvolysis being higher in GA than in LA. Because DESI only explores the surface of solids, these data do not reflect bulk degradability of the copolymers but, instead, their relative degradability at the molecular level. Based on a "reactive-DESI degradability scale" such as that established here for PLAGA, the proposed method offers interesting perspectives to qualify intrinsic degradability of different polyesters and evaluate their erosion susceptibility or to determine the degradability of those polymers known to degrade via erosion only.

Approaches to Heterogeneity in Native Mass Spectrometry

Native mass spectrometry (MS) is aimed at preserving and determining the native structure, composition, and stoichiometry of biomolecules and their complexes from solution after they are transferred into the gas phase. Major improvements in native MS instrumentation and experimental methods over the past few decades have led to a concomitant increase in the complexity and heterogeneity of samples that can be analyzed, including protein-ligand complexes, protein complexes with multiple coexisting stoichiometries, and membrane protein-lipid assemblies. Heterogeneous features of these biomolecular samples can be important for understanding structure and function. However, sample heterogeneity can make assignment of ion mass, charge, composition, and structure very challenging due to the overlap of tens or even hundreds of peaks in the mass spectrum. In this review, we cover data analysis, experimental, and instrumental advances and strategies aimed at solving this problem, with an in-depth discussion of theoretical and practical aspects of the use of available deconvolution algorithms and tools. We also reflect upon current challenges and provide a view of the future of this exciting field.

Phytosterols and Novel Triterpenes Recovered from Industrial Fermentation Coproducts Exert In Vitro Anti-Inflammatory Activity in Macrophages

The unstoppable growth of human population that occurs in parallel with all manufacturing activities leads to a relentless increase in the demand for resources, cultivation land, and energy. In response, currently, there is significant interest in developing strategies to optimize any available resources and their biowaste. While solutions initially focused on recovering biomolecules with applications in food, energy, or materials, the feasibility of synthetic biology in this field has been demonstrated in recent years. For instance, it is possible to genetically modify Saccharomyces cerevisiae to produce terpenes for commercial applications (i.e., against malaria or as biodiesel). But the production process, similar to any industrial activity, generates biowastes containing promising biomolecules (from fermentation) that if recovered may have applications in different areas. To test this hypothesis, in the present study, the lipid composition of by-products from the industrial production of β-farnesene by genetically modified Saccharomyces cerevisiae are studied to identify potentially bioactive compounds, their recovery, and finally, their stability and in vitro bioactivity. The assayed biowaste showed the presence of triterpenes, phytosterols, and 1-octacosanol which were recovered through molecular distillation into a single fraction. During the assayed stability test, compositional modifications were observed, mainly for the phytosterols and 1-octacosanol, probably due to oxidative reactions. However, such changes did not affect the in vitro bioactivity in macrophages, where it was found that the obtained fraction decreased the production of TNF-α and IL-6 in lipopolysaccharide (LPS)-induced inflammation.

Decrypting bacterial polyphenol metabolism in an anoxic wetland soil

Microorganisms play vital roles in modulating organic matter decomposition and nutrient cycling in soil ecosystems. The enzyme latch paradigm posits microbial degradation of polyphenols is hindered in anoxic peat leading to polyphenol accumulation, and consequently diminished microbial activity. This model assumes that polyphenols are microbially unavailable under anoxia, a supposition that has not been thoroughly investigated in any soil type. Here, we use anoxic soil reactors amended with and without a chemically defined polyphenol to test this hypothesis, employing metabolomics and genome-resolved metaproteomics to interrogate soil microbial polyphenol metabolism. Challenging the idea that polyphenols are not bioavailable under anoxia, we provide metabolite evidence that polyphenols are depolymerized, resulting in monomer accumulation, followed by the generation of small phenolic degradation products. Further, we show that soil microbiome function is maintained, and possibly enhanced, with polyphenol addition. In summary, this study provides chemical and enzymatic evidence that some soil microbiota can degrade polyphenols under anoxia and subvert the assumed polyphenol lock on soil microbial metabolism.

Normalized Mass Maps in Three-Dimensional Space Combining Kendrick-like Values with Chromatographic Separation for Enhanced Data Deconvolution

The incorporation of retention-time information into a fully rotatable and interactive three-dimensional (3D), "Kendrick-like" normalized mass map (NMM) using a single software platform is reported. Surprising discoveries were made about the elution pattern of block ethoxylate-propoxylate oligomers (ca. 2800 Da) in the supercritical fluid after combined SFC-Orbitrap FTMS analysis. The 3D NMM also facilitated identification of impurities using interactive graphics tools within the map. By selecting map glyphs, associated reconstructed ion chromatograms were automatically generated. Last, since Kendrick and Kendrick-like mapping (NMM) are chemical-formula-based, incorporating retention time in 3D space allows the possibility of resolving isomers in the map.

Characterization of water-soluble synthetic polymeric substances in wastewater using LC-HRMS/MS

Synthetic water-soluble polymeric materials are widely employed in e.g. cleaning detergents, personal care products, paints or textiles. Accordingly, these compounds reach sewage treatment plants and may enter receiving waters and the aquatic environment. Characteristically, these molecules show a polydisperse molecular weight distribution, comprising multiple repeating units, i.e. a homologous series (HS). Their analysis in environmentally relevant samples has received some attention over the last two decades, however, the majority of previous studies focused on surfactants and a molecular weight range <1000 Da. To capture a wider range on the mass versus polarity plane and extend towards less polar contaminants, a workflow was established using three different ionization strategies, namely conventional electrospray ionization, atmospheric pressure photoionization and atmospheric pressure chemical ionization. The data evaluation consisted of suspect screening of ca. 1200 suspect entries and a non-target screening of HS with pre-defined accurate mass differences using ca. 400 molecular formulas of repeating units of HS as input and repeating retention time shifts as HS indicator. To study the fate of these water-soluble polymeric substances in the wastewater treatment process, the different stages, i.e. after primary and secondary clarifier, and after ozonation followed by sand filtration, were sampled at a Swiss wastewater treatment plant. Remaining with two different ionization interfaces, ESI and APPI, in both polarities, a non-targeted screening approach led to a total number of 146 HS (each with a minimum number of 4 members), with a molecular mass of up to 1200 detected in the final effluent. Of the 146 HS, ca 15% could be associated with suspect hits and approximately 25% with transformation products of suspects. Tentative characterization or probable chemical structure could be assigned to almost half of the findings. In positive ionization mode various sugar derivatives with differing side chains, for negative mode structures with sulfonic acids, could be characterized. The number of detected HS decreased significantly over the three treatment stages. For HS detectable also in the biological and oxidative treatment stages, a change in HS distribution towards to lower mass range was often observed.

Mass Spectral Filtering by Mass-Remainder Analysis (MARA) at High Resolution and Its Application to Metabolite Profiling of Flavonoids

Flavonoids represent an important class of secondary metabolites because of their potential health benefits and functions in plants. We propose a novel method for the comprehensive flavonoid filtering and screening based on direct infusion mass spectrometry (DIMS) analysis. The recently invented data mining procedure, the multi-step mass-remainder analysis (M-MARA) technique is applied for the effective mass spectral filtering of the peak rich spectra of natural herb extracts. In addition, our flavonoid-filtering algorithm facilitates the determination of the elemental composition. M-MARA flavonoid-filtering uses simple mathematical and logical operations and thus, it can easily be implemented in a regular spreadsheet software. A huge benefit of our method is the high speed and the low demand for computing power and memory that enables the real time application even for tandem mass spectrometric analysis. Our novel method was applied for the electrospray ionization (ESI) DIMS spectra of various herb extract, and the filtered mass spectral data were subjected to chemometrics analysis using principal component analysis (PCA).

Tandem Mass-Remainder Analysis of Industrially Important Polyether Polyols

The characteristics of the polyalkylene oxide polyether polyols highly influence the properties of final polyurethane products. As a novel approach, in order to gain structural information, the recently invented data mining procedures, namely the Mass-remainder analysis (MARA) and the Multistep Mass-remainder analysis (M-MARA) are successfully applied for the processing of tandem mass spectrometry (MS/MS) data of various industrially important polyether polyols. M-MARA yields an ultra-simplified graphical representation of the MS/MS spectra and sorts the product ions based on their double bond equivalent (DBE) values. The maximum DBE values unambiguously differentiate among the various polyether polyols. Accordingly, the characteristic DBE values were 0, 1 for the linear diol polyethers, 0, 1, 2 for the three-arm, and 0, 1 2, 3, 4 for the six-arm polyether polyols. In addition, it was also found that the characteristic collision energy necessary for the optimum fragmentation yield depended linearly on the molecular weight of the polyols. This relationship offers an easy way for instrument tuning to gain structural information.

Mass Spectrometry-Based Analytical Strategy for Comprehensive Molecular Characterization of Biodegradable Poly(lactic-co-glycolic Acid) Copolymers

An analytical methodology with mass spectrometry as the core technique was developed for precise characterization of end groups, size, and co-monomeric composition of poly(lactic-co-glycolic acid) (PLGA) copolymers, as a preliminary step to qualify their biodegradability. Four PLGA samples were studied, with GA molar content varying from 0 to 50% and M_w ranging from 18 to 75 kg mol^-1 according to the supplier. Size exclusion chromatography (SEC) and liquid state nuclear magnetic resonance (NMR) were used as either complementary or validation techniques. As confirmed by tandem mass spectrometry (MS/MS) experiments, macrocycles were most prominent in the low mass range. Nevertheless, elemental compositions derived from high resolution (HR) mass measurements of linear species were consistent with chain terminations revealed by NMR. Off-line coupling of SEC with matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) permitted calibration curves to be built based on absolute molecular weights and, although slightly overestimated, so-obtained M_n and M_w values compared well with SEC and NMR results. Homogeneity of the co-monomeric content of all chains within each PLGA sample was demonstrated using surface-assisted laser desorption/ionization in a reactive mode (reactive-SALDI), a newly developed technique that takes advantage of residual acid on desorption ionization using through-hole alumina membrane (DIUTHAME) chips to induce dissociation of high-molecular-weight polymers containing cleavable C-O bonds. All HRMS data were best handled with Kendrick analysis, which helped reveal minor species and allowed automated computation of congested mass spectra.

Kendrick Analysis and Complex Isotopic Patterns: A Case Study of the Compositional Analysis of Pristine and Heated Polybrominated Flame Retardants by High-Resolution MALDI Mass Spectrometry

The Kendrick analysis is used for the processing and visualization of mass spectra obtained from polymers containing C, H, O and/or Si with simple isotopic patterns (monoisotope=lightest isotope=most intense isotope for short chains). In the case of heteroatoms with complex isotopic patterns, the impact of the chosen isotope on point alignments in Kendrick plots has not been examined extensively. Rich isotopic patterns also make the evaluation of the mass and nature of the repeating unit and end-groups more difficult from the mass spectrum in the case of unknown samples due to the number of peaks and the absence of a monoisotopic peak. Using a polybrominated polycarbonate as running example, we report that horizontal point alignments can be obtained in a Kendrick plot using the mass of the most abundant isotope instead of the monoisotopic mass as is usually done. Rotating the plot (“reverse Kendrick analysis”) helps to accurately evaluate the mass of the most abundant isotope of the repeating unit, as well as the nature of the brominated neutral expelled upon gentle heating (debromination or dehydrobromination). The whole procedure is then applied to the characterization of an unknown polybrominated flame retardant in an industrial formulation before and after heating.