Kendrick Mass Defect Plots Research Articles

Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Applications for Metabolomics.

Metabolomics is an interdisciplinary field that aims to study all metabolites < 1500 Da that are ubiquitously found within all organisms. Metabolomics is experiencing exponential growth and commonly relies on high-resolution mass spectrometry (HRMS). Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a form of HRMS that is particularly well suited for metabolomics research due to its exceptionally high resolution (105-106) and sensitivity with a mass accuracy in parts per billion (ppb). In this regard, FT-ICR-MS can provide valuable insights into the metabolomics analysis of complex biological systems due to unique capabilities such as the easy separation of isobaric and isomeric species, isotopic fine structure analysis, spatial resolution of metabolites in cells and tissues, and a high confidence (<1 ppm mass error) in metabolite identification. Alternatively, the large and complex data sets, long acquisition times, high cost, and limited access mainly through national mass spectrometry facilities may impede the routine adoption of FT-ICR-MS by metabolomics researchers. This review examines recent applications of FT-ICR-MS metabolomics in the search for clinical and non-human biomarkers; for the analysis of food, beverage, and environmental samples; and for the high-resolution imaging of tissues and other biological samples. We provide recent examples of metabolomics studies that highlight the advantages of FT-ICR-MS for the detailed and reliable characterization of the metabolome. Additionally, we offer some practical considerations for implementing FT-ICR-MS into a research program by providing a list of FT-ICR-MS facilities and by identifying different high-throughput interfaces, varieties of sample types, analysis methods (e.g., van Krevelen diagrams, Kendrick mass defect plot, etc.), and sample preparation and handling protocols used in FT-ICR-MS experiments. Overall, FT-ICR-MS holds great promise as a vital research tool for advancing metabolomics investigations.

Unraveling the chemical fingerprint of the Miami River sources: Insights from high-resolution mass spectrometry and nontarget analysis

This study investigated the chemical composition of waters in the heavily urbanized and historically polluted Miami River, Florida. The goal was to assess the different water sources and anthropogenic influence in this managed area using nontarget analysis (NTA) combined with high-resolution mass spectrometry (HRMS). Surface water samples were collected from 10 sites during five sampling events in the wet season of 2021 and 2022. The HRMS data was processed using Compound Discoverer™ version 3.3, and the results were analyzed using techniques including Principal Component Analysis and Kendrick Mass Defect plots. Results showed a gradient change in the chemical composition from the Everglades to Biscayne Bay endmembers. The Seybold Canal, an adjacent canal, was consistently identified as a unique source of contaminants, contributing its own specific set of tracers. Increased presence and intensity of organic contaminants along the waterway was observed, indicating significant anthropogenic influence in the area. The NTA and post-processing were evaluated for reproducibility, demonstrating robustness with a 71.2% average reproducibility for compounds detected in 3 out of 5 sampling trips. A detection frequency of 80% (4 out of 5) was the set criterion for detected compounds suggested as tracers. To prioritize samples, hierarchical cluster analysis was employed, and potential tracers for each water source were determined. Tracers included natural products and agricultural herbicides and insecticides for the Everglades, anthropogenic contaminants for the Seybold Canal, and a lack of unique tracers for Biscayne Bay. Additionally, urban-influenced contaminants such as flame retardants, insect repellents, pharmaceuticals, and non-agricultural herbicides were identified along the river. This study highlights the impact of human activities on the Miami River and demonstrates the effectiveness of NTA in differentiating and tracking water sources. The results emphasize the importance of reproducibility in NTA and provide guidance on implementing monitoring strategies by prioritizing samples based on chemical compositions.

Qualitative characterization of oxygen-containing compounds in fuel extracts by using (-) electrospray ionization coupled to a linear quadrupole ion trap/orbitrap mass spectrometer

Qualitative characterization of oxygen-containing compounds (OCCs) in fuels is imperative, as these compounds detrimentally influence fuel stability. Hence, development of analytical methods that enable thorough qualitative information will likely enhance correlations between composition and fuel failures. In this work, (-) electrospray ionization (ESI)coupled to a linear quadrupole ion trap/orbitrap mass spectrometer provided detailed qualitative analysis of OCCs in jet fuels, marine gas oil (MGO)and diesel. The high resolving power and mass accuracy of the orbitrap and soft ionization of ESI advanced the current OCC qualitative knowledge of fuels as the number of OCCs classes identified exceeded previous works. Up to nine, twenty and nine different homologue ion series (i.e.,ions with the same empirical formula (e.g.,CnH2n-7O) but differ by 14 Da (m/z 149, 163, 177, etc.)) were detected in the jet fuels, diesel and MGO, respectively. Additional detailed qualitative information included the average ring and double equivalent values, carbon numbers and molecular weights for the detected OCCs in each fuel. With limited fragmentation of ions, Kendrick Mass Defectplots were made that enabled straightforward comparison of the OCC compositions offuels. Clear qualitative differences were noted among the different types of fuels (i.e.,jet fuels compared to diesel) and when the threejet fuels were compared to each other. As the method demonstrated proficiency at providing detailed compositional information, it may be employed for future storage and thermal stress testing of fuels to monitor and evaluate compositional changes. Overall, the method demonstrated qualitative proficiency and may be used to establish important links between composition and fuel stability; this is a critical prerequisite for improving fuel quality.

Structural Elucidation of Intact Rough-type Lipopolysaccharides Using Field Asymmetric Ion Mobility Spectrometry and Kendrick Mass Defect Plots.

Lipopolysaccharides (LPSs) are a hallmark virulence factor of Gram-negative bacteria. They are complex, structurally heterogeneous mixtures due to variations in number, type, and position of their simplest units: fatty acids and monosaccharides. Thus, LPS structural characterization by traditional mass spectrometry (MS) methods is challenging. Here, we describe the benefits of field asymmetric ion mobility spectrometry (FAIMS) for analysis of an intact R-type lipopolysaccharide complex mixture (lipooligosaccharide; LOS). Structural characterization was performed using Escherichia coli J5 (Rc mutant) LOS, a TLR4 agonist widely used in glycoconjugate vaccine research. FAIMS gas-phase fractionation improved the (S/N) ratio and number of detected LOS species. Additionally, FAIMS allowed the separation of overlapping isobars facilitating their tandem MS characterization and unequivocal structural assignments. In addition to FAIMS gas-phase fractionation benefits, extra sorting of the structurally related LOS molecules was further accomplished using Kendrick mass defect (KMD) plots. Notably, a custom KMD base unit of [Na-H] created a highly organized KMD plot that allowed identification of interesting and novel structural differences across the different LOS ion families, i.e., ions with different acylation degrees, oligosaccharides composition, and chemical modifications. Defining the composition of a single LOS ion by tandem MS along with the organized KMD plot structural network was sufficient to deduce the composition of 181 LOS species out of 321 species present in the mixture. The combination of FAIMS and KMD plots allowed in-depth characterization of the complex LOS mixture and uncovered a wealth of novel information about its structural variations.

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

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. 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. 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. 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. 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).

Qualitative characterization of nitrogen-containing compounds in jet and diesel fuel extracts by using (+) electrospray ionization coupled to a linear quadrupole ion trap/orbitrap mass spectrometer

The development of analytical methods for the characterization of nitrogen-containing compounds (NCCs) in liquid transportation fuels are critical, as these compounds adversely affect fuel storage and thermal stability. In this work, (+) electrospray ionization coupled to a linear quadrupole ion trap/orbitrap mass spectrometer provided detailed chemical analysis of the NCCs in jet and diesel fuels. Upon methanol extractions of the individual fuels (three jet fuels and one diesel), the methanol layer was diluted and injected into the ESI source where protonation was the dominant ionization reaction for the NCCs, which exhibited little to no fragmentation. Kendrick mass defect plots were constructed to facilitate chemical characterization. Many chemical classes of NCCs (i.e., alkylamines, pyridines, indoles, quinolines, carbazoles) were identified in the jet and diesel fuel extracts. Compositional differences were observed when the jet fuel extracts were compared to each other and when compared to the diesel extract. For example, the most abundant NCCs in Jet fuel 1 had empirical formulas of CnH(2n)N (decahydroquinolines/decahydroisoquinolines) and CnH(2n-6)N (indolines/tetrahydroquinolines/tetrahydroisoquinolines). Conversely, the most abundant NCCs in Jet fuel 2 had empirical formulas of CnH(2n-6)N and CnH(2n-10)N (quinolines/isoquinolines/naphthylamines) while the most abundant NCCs in Jet fuel 3 had empirical formulas of CnH(2n+4)N (alkylamines). The ionized NCCs derived from the jet fuels had wider carbon number ranges than compared to those reported in previous studies. The average molecular weights, ring and double bond equivalent values and total carbon numbers for the ionized NCCs in the four extracts ranged from 192.8–215.3 Da, 1.7–5.0 and 13.5–14.8, respectively. Further, the average carbon number for each homologue ion series (ions with the same empirical formula but differ by 14 Da) were determined. Collision-activated dissociation was also investigated to evaluate its efficacy at providing structural elucidation and isomeric differentiation for ionized NCCs. Overall, the high-resolution mass spectrometry measurements provided thorough chemical characterization that may aid in linking NCC compositions to storage and thermal stability failures and advance the current understanding of issues concerning fuel incompatibility upon the mixing of different fuels.

Kendrick mass defect analysis-based data mining technique for trace components in polyolefins observed by pyrolysis-gas chromatography/high-resolution mass spectrometry

Pyrolysis gas chromatography/mass spectrometry (Py-GC/MS) is utilized as an effective technique to characterize additives and degradation products of polyolefins. However, non-target analysis of trace components buried in complex chromatograms or mass spectra is a difficult task without prior information on sample composition. In this report, we propose a data mining method that extracts meaningful trace components by combining Py-GC/time-of-flight MS (Py-GC/TOFMS) and Kendrick mass defect (KMD) analysis. In our first demonstration, we characterized the additives in the polyethylene (PE) cap of a polyethylene terephthalate (PET) beverage bottle using Py-GC/TOFMS. The summed mass spectrum, built by summing all the mass spectra over the entire range of the pyrogram, was converted to a two-dimensional KMD plot. Specific dots on the KMD plot at a distance from the dots relating to a series of hydrocarbon-derived fragment ions suggested the presence of additives. The types of additives could be identified by a library search for the extracted ion chromatograms (EICs) derived from the corresponding mass of the specific dots. The second demonstration was related to the detection of oxidized products in polypropylene (PP) resin. A “Remainders of KM” (RKM) plot was able to highlight the presence of a series of fragment ions of trace PP pyrolysates with one and two oxygen atoms. Relative peak intensities of the ions containing oxygen atoms were useful as an oxidation index to evaluate the degree of degradation in the very early stages of degradation.

Characterization of styrene/methyl methacrylate/n-butyl acrylate terpolymer with Kendrick mass defect analysis in electrospray ionization-ion mobility spectrometry-mass spectrometry.

Synthesis of copolymer is one of the major approaches to establish sophisticated polymers. In copolymer analysis in mass spectrometry (MS), an increase in the number of monomer unit species and/or the polymer molecular weight results in complex mass spectra, and a method is required to solve this problem. In this study, electrospray ionization-ion mobility spectrometry-mass spectrometry was employed to analyze styrene/methyl methacrylate/n-butyl acrylate (St/MMA/nBA) terpolymers via Kendrick mass defect (KMD) analysis. An expanded Fourier transform-based noise reduction method for the copolymer was developed to improve the decrease in the signal/noise ratio observed in the higher m/z region. Low-mass terpolymers (0.7kDa) were identified by comparing the observed and theoretical results using a two-dimensional KMD plot. For the 1.5 kDa terpolymer, the signal overlap, of which KMD value was not matched with the theoretical one, was interpreted by the shift from the theoretical value in the KMD plot. For the 3.0 kDa terpolymers, the compositional candidates were determined by the prediction based on the compositional information of low-mass terpolymers previously analyzed. The 4.5kDa terpolymer was interpreted after the expanded noise filtering. The terpolymers, whose molecular weight was up to 4.5kDa, were successfully characterized at a molecular level. The dependency of the St/MMA/nBA composition on molecular weight was observed; that is, the nBA content decreased with an increase in the molecular weight.

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.

Detecting Water Constituents Unique to Septic Tanks as a Wastewater Source in the Environment by Nontarget Analysis: South Florida's Deering Estate Rehydration Project Case Study.

The present study has generated a workflow based on nontarget analysis (NTA) with Compound Discoverer Ver 3.1 to characterize a set of source-discriminating compounds identified in water samples from locations in South Florida (USA), particularly those describing a freshwater environment (Everglades based), urban impacted areas (septic tank driven), and coastal (Biscayne Bay) endmembers in and around the Charles Deering Estate property in the Village of Palmetto Bay. Waters from an interconnected managed canal system were assessed to evaluate the influence of localized emissions. Septic tank effluents influence the water in many Southeast Florida environments due to their diminished onsite treatment capacity based on the limestone-dominated geology and canal systems providing a relatively unobstructed connection pathway. Through a combination of high-resolution mass spectrometry and statistical analyses, a set of tracers and indicators was determined (azelaic acid, decanophenone, galaxolidone, methyl violet, monoolein, metoprolol, and 1-stearoylglycerol). Tentatively identified compounds were generally assigned to various categories such as dyes, personal care products, and pharmaceuticals. The NTA Compound Discoverer Ver 3.1 compound data (presented as principal component analysis and Kendrick mass defect plots) showed apparent differences between wastewater-influenced sites and non-wastewater-influenced sites along with the ranked "Top10" compounds found at each location. Waters from different locations were also compared using the presence of sucralose to further inform the NTA. The most septic-influenced site contained 3594 ± 94 ng/L of sucralose with concentrations declining steadily and reaching the lowest concentrations in Biscayne Bay of 122 ± 94 ng/L. The sucralose concentrations provided further evidence of septic influence on this system. Sucralose was determined to be a conservative tracer between the freshwater and coastal sources and complementary to other probable unique tracers of septic tank effluent identified by the NTA. Environ Toxicol Chem 2022;41:1165-1178. © 2022 SETAC.

Three-Dimensional Mass Spectral Imaging of Polymers Via Laser-Assisted Micro-Pyrolysis Program with Flowing Atmospheric-Pressure Afterglow Ambient Mass Spectrometry.

Herein, a novel diode laser-assisted micro-pyrolysis program (LAMP) technique is demonstrated and coupled with flowing atmospheric-pressure afterglow ambient mass spectrometry for instantaneously profiling polymers and polymer additives. Laser power modulation allows thermal separation of additives and different pyrolysis products, as shown through positive- and negative-mode high-resolution mass spectra and Kendrick mass defect plots of homopolymers, copolymers, polymer blends, and complex polymer samples. LAMP allows much faster temperature control through real-time duty cycle changes and gives significantly better spatial confinement compared to typical resistive heating pyrolysis approaches. Finally, MS imaging, with lateral and depth resolution, is demonstrated for a complex polymer pressure-sensitive adhesive tape sample.

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.

Development of a peak extraction method using the high-resolution matrix-assisted laser desorption/ionization time-of-flight mass spectrometry and machine learning techniques: Analysis of peak shapes.

Combining matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS) and Kendrick mass defect (KMD) analysis is a powerful tool for visualizing polymers in complex mass spectra. The identification of minor polymers by KMD analysis requires reduction of the broad noise peaks often observed in the low-mass region. A machine-learning model was created using pix2pixHD. It converts an original mass spectrum into a pseudo-mass spectrum that contains only the original peaks at m/z positions that the model judges as sharp single-component peaks. It reduces noise by selecting only the m/z and intensity values from the original spectrum's peak list that correspond to peaks in the pseudo-mass spectrum. A machine-learning model was applied to a low-concentration polymer mass spectrum observed at m/z <2000. Extracting single-component peaks from the mass spectrum made the minor polymer series appear clearly in the KMD plot. The technique facilitated mass spectrometric imaging of the ultraviolet degradation of polyethylene terephthalate by plotting the polymers' spatial distributions. It could also distinguish between polymer series (before and after degradation) to identify their separate spatial distributions. A machine-learning method for peak extraction from high-resolution MALDI-TOFMS was developed. Single-component peaks of the mass spectrum were distinguished from noise peaks by their peak shapes. Combining with KMD analysis facilitated the identification of minor polymer series in complex mass spectra.

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.

Non-target analysis of organic waste amended agricultural soils: Characterization of added organic pollution

Amendment of soil with organic urban and animal wastes can keep arable soil fertile without the need for synthetic fertilizers. However, pollutants present in these types of waste might be carried into the soil with unintended consequences for the environment. We studied an experimental agricultural plot, which had been amended with either synthetic inorganic fertilizers, human urine, manure, or wastewater treatment sludge at very high rates. We applied chemical non-target analysis to characterize present organic micropollutants, intending to compare treatments and highlight suspects of environmental concern. Soil samples were prepared by pressurized liquid and purified with solid-phase extraction before analysis with nanoflow ultra-high performance liquid chromatography coupled to high-resolution Orbitrap tandem mass spectrometry. Automated elucidation with two mass spectral libraries, multiple large chemical databases and environmental NORMAN suspect lists was able to annotate (level 3 and level 2) ∼ 20% of the 2306 detected features. A following principal component- and differential-analysis could separate the soil treatment groups’ pollution profiles and highlight high relative abundance features. From cattle manure, natural compounds such as bile acids and steroids were found. Human urine led to pollution with common pharmaceuticals such as metoprolol and propranolol. The highest number was added by wastewater treatment sludge, with 25 significant contaminants, spanning blood pressure regulators, antidepressants, synthetic steroids and sleep medication. Furthermore, using Kendrick mass defect plots, a series of polypropylene glycols could be revealed in the soil. Non-target analysis appears to be a promising method to characterize organic pollutants in soils.

A data mining method from pyrolyzed products: Pyrolysis-gas chromatography-photoionization-high resolution time-of-flight mass spectrometry and kendrick mass defect analysis for polymer semiconductor poly(3-hexylthiophene)

Structural analysis of polymer semiconductors is important to improve their properties but applicable method is limited due to insolubility. Here an efficient and comprehensive data mining method for such materials is developed by using pyrolysis-gas chromatography- high resolution mass spectrometry (Py-GC-HRMS). Py-GC-HRMS analysis of a polymer semiconductor poly(3-hexylthiophene) (P3HT) was performed and pyrogram with vast number of peaks was obtained. Normally in analysis of Py-GC-HRMS results, a mass spectrum is obtained for one peak in chromatogram. In one of our techniques, the mass spectra in wide time range were integrated to one mass spectrum including the information of over 300 compounds. Analysis of the mass spectrum could be using Kendrick mass defect (KMD) analysis. By making KMD plots, the compounds categorized into 29 groups depending on the structures of thiophene derivative moieties. As a result, chemical composition analysis for 29 compounds lead to peak assignment for 277 compounds in short time. Furthermore, these compounds could be categorized depending on different structural features (e.g., number of sulfur atoms, degree of unsaturation) by using appropriate divisors, leading to understanding of relationship between structural features of compounds and their retention time. The measurement without GC column provided the similar information about compounds, although the information of the retention time was lost. These methods can be one of key analysis method for insoluble polymer materials.

Characterizing changes of dissolved organic matter composition with the use of distinct feeds in recirculating aquaculture systems via high-resolution mass spectrometry

Recirculating aquaculture systems (RAS) are a new alternative to traditional aquaculture approaches, allowing full control over the fish production conditions, while reducing the water demand. The reduction of water exchange leads to an accumulation of dissolved organic matter (DOM) that can have potential effects on water quality, fish welfare and system performance. Despite the growing awareness of DOM in aquaculture, scarce scientific information exists for understanding the composition and transformation of DOM in RAS. In this study, a non-targeted approach using ultra-performance liquid chromatography coupled to a hybrid quadrupole-time of flight mass spectrometer (UPLC-QTOF-MS) was used to characterize compositional changes of low molecular weight (LMW) DOM in RAS, when operated under two different feed types. A total of 1823 chemicals were identified and the majority of those contained a CHON chemical group in their structure. Changes in the composition of LMW-DOM in RAS waters were observed when the standard feed was switched to RAS feed. The DOM with the use of standard feed, consisted mainly of lignin/CRAM-like, CHO and CHOS chemical groups, while the DOM that used RAS feed, was mainly composed by unsaturated hydrocarbon, CHNO and CHNOS chemical groups. The Bray-Curtis dissimilarity cluster demonstrated differences in the composition of DOM from RAS and was associated to the type of feed used. When the RAS feed was used, the Kendrick mass defect plots of –CH2- homologous units in the pump-sump (after the water treatment) showed a high removal capacity for CHNO, CHNOS and halogenated chemicals with high Kendrick mass defect, KMD > 0.7. To our knowledge, this is the first report of LMW-DOM characterization of RAS by high-resolution mass spectrometry (HRMS).

Comparative LC-MS analysis of tropolone alkaloids from in vitro cultures and native sources of Gloriosa superba by Kendrick mass defect plots.

Gloriosa superba L. is a promising antitumoural plant species as a source of colchicinoids. Ethnobotanical applications of G. superba are associated with different plant parts such as leaves, seeds, fruits, tuber and the whole plant. A comparative phytochemical study of purified extracts from in vitro cultures and native tubers of G. superba was carried out by ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HR-MS) in combination with the mass defect filtering (MDF) technique. The individual compounds were tentatively annotated using database correlations, retention time (Rt), accurate m/z data obtained by electrospray ionisation (ESI) (+)-HR-MS, proposed elemental composition, ring double bond equivalent (RDBeq) values and HR-MS/MS fragmentation patterns. Moreover, the identification was based on transforming the exact mass ratio (m/z) for the protonated molecular ions [М + Н]+ of the observed metabolites in Kendrick nominal masses (NKMs) and calculation of the Kendrick mass defect (KMD), which made it possible to graphically present the ion peaks in Kendrick plots. Building Kendrick plots allows easy differentiation of small structural differences such as methylation or demethylation of compounds from the same homologous series. In this way, a wide range of tropolone alkaloids was characterised. A greater variety was observed in in vitro cultures, compared to native sources. This LC-MS analysis unambiguously demonstrated the presence of tropolone alkaloids in in vitro cultures of G. superba. This approach of LC-MS data interpretation can be used to understand complex mass spectra such as those of plant extracts.

Multistep Analysis of Diol-LC-ESI-HRMS Data Reveals Proanthocyanidin Composition of Complex Plant Extracts (PAComics).

Proanthocyanidins (PACs) are complex oligomeric or polymeric phenolic biopolymers composed of flavan-3-ol building blocks. PACs exert manifold functional bioactivities and are assessed as bioactive ingredients in a variety of food products, beverages, medicinal plants, and phytopharmaceuticals. Although analytical methods for PACs with low degree of polymerization (DP) are well established, a lack of methods for the detailed analysis of higher oligomers and polymers from complex plant extracts is obvious. For this, the present study investigated PAC-enriched extracts from four different plants, traditionally used for medical purpose (Lime flower, Hawthorn leaf and flower, Japanese Wisteria fruits without seeds, and Common Sorrel herb). PACs were separated on diol stationary-phase high-performance liquid chromatography according to the respective DP and detected by fluorescence and quadrupole time-of-flight mass spectrometry (qTOF-MS). The qTOF-MS contour plots [tR → m/z] provided a sufficient overview on the respective PAC distribution. Subsequently, high-resolution mass spectrometry data were used for Kendrick mass defect (KMD) analysis, with (epi)catechin, the main flavan-3-ol unit in PACs, as the reference unit. The resulting KMD plots enabled an elucidation of the general polymer chain composition with regard to DP, building blocks, and potential secondary modifications (e.g., galloylation). Subsequently, analysis of MS2 fragmentation patterns of PAC oligomers confirmed the structural features obtained from the KMD plots. While Lime flower contained oligomeric A- and B-type PACs, composed of (epi)catechin and (epi)afzelechin, Japanese Wisteria fruit contained PACs consisting of three different hydroxylated flavan-3-ols. Cinchonains, A-type PACs, and B-type PACs were detected in the Hawthorn plant material. Galloylated oligo- and polymeric PACs were detected in Common Sorrel herb. This multistep analysis reveals collective insights into the PAC composition of the extracts. The protocol offers a fast and reliable methodology to be used in a standard laboratory. On the other hand, this methodology reaches its limits for higher oligomeric PACs, and further optimization is necessary for a better detection of the polymers, as the optimal DP cluster detection depends on the resolution of diol stationary-phase chromatography and is therefore limited.

Halogenated organic contaminants of concern in urban-influenced waters of Lake Ontario, Canada: Passive sampling with targeted and non-targeted screening

Passive samplers are useful tools for monitoring hydrophobic, persistent, and potentially bioaccumulative contaminants in the environment. In this study, low density polyethylene passive samplers were deployed in urban-influenced and background nearshore freshwaters of northwestern Lake Ontario and analyzed for a broad range of both legacy halogenated organic contaminants (HOCs) and halogenated flame retardants (HFRs). Non-targeted analysis was conducted for screening additional halogenated substances. For most compounds, concentrations were greatest in the industrialized Hamilton Harbour and more generally at sites that have stronger influences of wastewater effluent discharges and stormwater run-off through rivers and creeks. Polychlorinated biphenyls (PCBs) remain the dominant class of HOCs in water, with dissolved-phase concentrations ranging from 10 to 4100 pg/L (ΣPCBs), followed by polybrominated diphenylethers (ΣPBDEs; 14–960 pg/L) and the organochlorine pesticides (OCPs; 22–290 pg/L). Several non-PBDE brominated flame retardants (nBFRs) and chlorinated Dechlorane-related compounds were detected, with hexabromocyclododecanes (ΣHBCDD; sum of 3 diastereoisomers) the most abundant (1.0–21 pg/L). Non-targeted screening of samples by high resolution mass spectrometry using Kendrick mass defect plots for data analysis indicated that several other halogenated compounds were present in waters at relatively high abundances compared to the flame retardants, based on semi-quantitative estimates. These included methyl-triclosan, four halogenated anisoles (2,4,6-tribromoanisole, dimethyl-trichloroanisole, pentachloroanisole, and pentachlorothioanisole), and pentachloro-aniline. Dissolved-phase methyl-triclosan was estimated to contribute up to approximately 40% of the summed target HOC concentrations. Polyethylene passive samplers provided an excellent medium for both non-targeted screening of HOCs not currently included in monitoring programs and tracking brominated and chlorinated chemicals slated for reductions in uses and emissions through international (Stockholm Convention) and binational (Great Lakes) agreements.