Critical assessment of the Kendrick mass defect analysis as an innovative approach to process high resolution mass spectrometry data for environmental applications

Organochloride Speciation in Plastic Pyrolysis Oil by GC × GC Coupled to High-Resolution TOF-MS Using Scripting Expressions

The presence of chlorine (Cl) species in plastic pyrolysis oil (PPO) poses environmental and technical challenges for plastic recycling, including corrosion, catalyst deactivation, and the formation of undesired compounds during further processing of PPOs. Therefore, identifying and quantifying Cl-species is crucial to achieve PPO decontamination or avoid forming these molecules during the pyrolysis process. In this framework, a nontargeted screening methodology was developed, validated with Cl-standards spiked in a hydrocarbon mixture, and applied to a PPO sample by using comprehensive two-dimensional gas chromatography coupled with high-resolution time-of-flight mass spectrometry (GC × GC-HR-TOFMS). First, three filters were developed using scripting expressions based on exact mass differences and abundance ratios of chlorinated isotopic patterns. A strict filter permitted Cl-species detection without any false positives, but excluded a few Cl-species. Broader filters allowed the identification of additional chlorinated species, although they also brought a consequent number of false positives. Second, GC × GC-HR-TOFMS data were processed with the spectral analysis tools (SAT), an additional toolkit paired with the Leco ChromaTOF software, which helped identify MS fragments containing chlorine. SAT proved to be particularly effective in reviewing the list of potential Cl-species detected by the scripting expressions, enabling the distinction between false positives and chlorinated fragments. Screening Cl-species with filters and SAT allowed the identification of 24 organochlorides in a real PPO sample. Therefore, applying the described methodology has improved the analysis of PPO samples using GC × GC-HR-TOFMS, making the process faster and more powerful.

Fate and transformation of psychotropic drugs in urban wastewater systems and receiving rivers via the integration of targeted and suspect screening analysis

Psychotropic drugs rank among the most prescribed pharmaceuticals in the world. The ubiquitous occurrence of psychotropic drugs in the environment evoked rising concerns due to their various toxic effect on non-target organisms at low concentrations. However, the removal, transformation, and discharging of these drugs throughout wastewater treatment plants (WWTPs) have rarely been reported. Based on the targeted analysis and suspected screening, this study investigated the distribution of psychotropic drugs and their transformation products (TPs) within the entire treatment processes in WWTPs and their receiving rivers. The results indicated that 13 out of 47 psychotropic drugs are widely observed across wastewater, sludge, receiving river water, and sediment, respectively. The aqueous removal efficiencies of most psychotropic drugs exhibited their significant recalcitrance in wastewater treatment processes. For instance, venlafaxine (VEL) was slightly removed by 2.64 % and 10.8 % in these two WWTPs. The concentrations of oxazepam (OZP) and lamotrigine (LMT) dramatically increased after the overall treatment processes due to their metabolic conversion and regeneration processes, respectively. Given the recalcitrance of psychotropic drugs, the identified TPs generated within WWTPs were not abundant, but a wider variety of TPs were identified from human metabolites. A total of 25 TPs were identified via the suspect screening analysis, of which nine were newly identified. In receiving rivers, the risk quotient (RQ) presented OZP, sertraline (SER), and VEL posed high potential risks; the integration of the toxicological priority index (ToxPi) and the toxicity-weighted concentration (TWC) suggested TP-CIT-322 and TP-OCX-195 as the high-priority contaminants. Given the recalcitrance and environmental risks of psychotropic drugs and their TPs in WWTPs and environments, it is crucial for the further exploration of their effective treatment technologies and emission control strategies .

Cross-Scale Multimodal Imaging for Organic Matter in Extraterrestrial Samples

The analysis of extraterrestrial organic matter in samples returned by space missions provides a unique opportunity to study prebiotic chemistry. A comprehensive understanding of the occurrence and composition of organic matter is fundamental to unraveling its origin and evolutionary history. However, the scarcity and complexity of these materials pose considerable analytical challenges. Here, we developed a cross-scale multimodal imaging workflow that integrated mass spectrometry imaging (MSI) and vibrational spectroscopy imaging, including desorption electrospray ionization coupled quadrupole-time-of-flight mass spectrometry (DESI-Q-TOF/MS), time-of-flight secondary ion mass spectrometry (TOF-SIMS), nanoscale secondary ion mass spectrometry (NanoSIMS), focal plane array-Fourier transform infrared spectroscopy (FPA-FTIR), and optical photothermal infrared spectroscopy (O-PTIR). This workflow was applied to the Murchison meteorite, with the objective of establishing spatial associations between mineral phases, molecular composition, functional groups, and isotopic composition on a scale from the millimeter to the submicron. The spatial resolution of DESI has been improved from 100 to 200 to 20 μm, enabling spatial correlation with other imaging techniques. For the first time, the enrichment of organic matter─including CHN, CHO, and CHNO compounds and polycyclic aromatic hydrocarbons (PAHs)─in fine-grained rims (FGRs) surrounding silicate chondrules has been observed. Furthermore, the cross-scale multimodal imaging also reveals differences in organic matter composition between Ca-carbonate and phyllosilicates, as well as spatial heterogeneity within the latter. This workflow provides a new paradigm for studying the complex occurrence and composition of organic matter in various research fields, enhancing our understanding of prebiotic materials in the solar system.

Utilizing High-Resolution Mass Spectrometry Data Mining Strategy in R Programming Language for Rapid Annotation of Absorbed Prototypes and Metabolites of Gypenosides

The rapid and accurate annotation of the complex compounds and metabolites in natural products remains a significant challenge. In this study, we developed an integrated strategy to efficiently and accurately profile both the prototypes and metabolites of natural products in vivo. And this was achieved by establishing a gypenosides constituent database and utilizing R programming language to combine sample selection, virtual metabolite database construction, polygon mass defect filtering, and Kendrick mass defect filtering. In addition, the annotation strategy was successfully applied to identify the prototypes and metabolites of gypenosides in mice serum. As a case study, gypenoside LXXV was used to validate the feasibility of this approach. The results demonstrated 36 prototypes and 108 metabolites were annotated from the serum by the established annotation strategy. The prototype and eight metabolites of gypenoside LXXV were further confirmed, indicating that the proposed strategy is available. This study provides a novel approach for the rapid and accurate identification of prototypes and metabolites of natural products and offers new insights into the metabolic processes of gypenosides in vivo.

Chemical characterization of polymer and chloride content in waste plastic materials using pyrolysis - direct analysis in real time - high-resolution mass spectrometry

The increasing global demand for plastic has raised the need for effective waste plastic management due to its long lifetime and resistance to environmental degradation. There is a need for rapid plastic identification to improve the mechanical waste plastic sorting process. This study presents a novel application of Temperature-Programmed Desorption-Direct Analysis in Real Time-High Resolution Mass Spectrometry (TPD-DART-HRMS) that enables rapid characterization of various plastics. This technique was applied on four commercially available reference polymers (polyethylene, polypropylene, polystyrene, polyvinyl chloride) as well as three "waste" plastic samples of mixed origin. These waste plastic samples were obtained as discards from various industrial processes with limited analytical characterization data. Through the application of CH2 Kendrick mass defect (KMD) grouping, characteristic trends in the mass spectra of each sample were identified, allowing for a simplified numerical comparison. This approach utilized a robust statistical approach using the Tanimoto coefficient, allowing for the quantitative measures of similarity between standards and unknown samples. The application of this mathematical evaluation methodology was used to identify plastic types and to distinguish structurally similar polymers. Additionally, we report that a chloride ion clustering effect with copper substrate can identify chlorinated polymer PVC (polyvinyl chloride) utilizing pyro-(-)DART-HRMS mode. PVC polymer is of particular interest in recycling due to its high chloride content, which can present technical challenges for some types of recycling. We found that chloride ion clusters are a good screening marker for the presence of chlorinated polymers in mixed waste plastic samples. This study can possibly help advance rapid and accurate analytical techniques for identifying the composition of waste plastics to advance the effectiveness of the waste plastic sorting process.

Investigating the chemical space coverage of multiple chromatographic and ionization methods using non-targeted analysis on surface and drinking water collected using passive sampling

Multiple non-targeted analysis tools were used to look for a broad range of possible chemical contaminants present in surface and drinking water using liquid chromatography separation and high-resolution mass spectrometry detection, including both quadrupole time of flight (Q-ToF) and Orbitrap instruments. Two chromatographic techniques were evaluated on an LC-Q-ToF with electrospray ionization in both positive and negative modes: (1) the traditionally used reverse phase C18 and (2) the hydrophilic interaction liquid chromatography (HILIC) aimed to capture more polar contaminants that may be present in water. Multiple ionization modes were evaluated with an LC-Orbitrap, including electrospray (ESI) and atmospheric pressure chemical ionization (APCI), also in both positive and negative modes. A suspect screening library of over 1300 possible environmental contaminants, including pesticides, pharmaceuticals, personal care products, illicit drugs/drugs of abuse, and various anthropogenic markers was made with experimentally collected data with the LC-Q-ToF with both column types, with 227 chemicals being retained by the HILIC column. The non-targeted methods using multiple chromatographic and ionization modes were applied to environmental water samples collected with polar organic chemical integrative samplers (POCIS), including surface water upstream and downstream from wastewater effluent discharge, and the downstream drinking water intake and treated drinking water for three distinct sampling events. For the LC-Q-ToF, 442 chemical features were detected on the C18 column and 91 with the HILIC column in the POCIS extracts, while 556 features were found on the Orbitrap workflow by ESI and 131 features detected by APCI. Over 100 chemicals were tentatively identified by suspect screening and database searching. The comprehensive and systematic evaluation of these methods serve as a step in characterizing the chemical space covered when utilizing different chromatography and ionization methods, or different instrument workflows on complex environmental mixtures.

Consolidating two-dimensional liquid chromatography-high-resolution tandem mass spectrometry (LC×LC-HRMS/MS) technique for the non-targeted analysis of poly- and perfluorinated substances: A trial on aqueous film-forming foams

To date, poly- and perfluoroalkyl substances (PFAS) represent a real threat for their environmental persistence, wide physicochemical variability, and their potential toxicity. Thus far a large portion of these chemicals remain structurally unknown. These chemicals, therefore, require the implementation of complex non-targeted analysis workflows using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) for their comprehensive detection and monitoring. This approach, even though comprehensive, does not always provide the much-needed analytical resolution for the analysis of complex PFAS mixtures such as fire-fighting aqueous film-forming foams (AFFFs). This study consolidates the advantages of the LC×LC technique hyphenated with high-resolution tandem mass spectrometry (HRMS/MS) for the identification of PFAS in AFFF mixtures. A total of 57 PFAS homolog series (HS) were identified in 3M and Orchidee AFFF mixtures thanks to the (i) high chromatographic peak capacity (n'2D,c ~ 300) and the (i) increased mass domain resolution provided by the "remainder of Kendrick Mass" (RKM) analysis on the HRMS data. Then, we attempted to annotate the PFAS of each HS by exploiting the available reference standards and the FluoroMatch workflow in combination with the RKM defect by different fluorine repeating units, such as CF2, CF2O, and C2F4O. This approach resulted in 12 identified PFAS HS, including compounds belonging to the HS of perfluoroalkyl carboxylic acids (PFACAs), perfluoroalkyl sulfonic acids (PFASAs), (N-pentafluoro(5)sulfide)-perfluoroalkane sulfonates (SF5-PFASAs), N-sulfopropyldimethylammoniopropyl perfluoroalkane sulfonamides (N-SPAmP-FASA), and N-carboxymethyldimethylammoniopropyl perfluoroalkane sulfonamide (N-CMAmP-FASA). The annotated categories of perfluoroalkyl aldehydes and chlorinated PFASAs represent the first record of PFAS HS in the investigated AFFF samples.

Development of an integrated strategy for comprehensive characterization of Sinomenii Caulis extract and metabolites in rats based on UPLC/Q-TOF-MS

Sinomenii Caulis (SC), a commonly used traditional Chinese medicine for its therapeutic effects on rheumatoid arthritis, contains rich chemical components. At present, most studies mainly focus on sinomenine, with little research on other alkaloids. In this study, a comprehensive profile of compounds in SC extract, and biological samples of rats (including bile, urine, feces, and plasma) after oral administration of SC extract was conducted via ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF-MS). The fragmentation patterns and potential biotransformation pathways of six main types of alkaloids in SC were summarized, and the corresponding characteristic product ions, relative ion intensity, and neutral losses were obtained to achieve rapid classification and identification of complex components of SC from in vitro to in vivo. As a result, a total of 114 alkaloid compounds were identified, including 12 benzyl alkaloids, 4 isoquinolone alkaloids, 32 aporphine alkaloids, 28 protoberberine alkaloids, 34 morphinan alkaloids and 4 organic amine alkaloids. After administration of SC extract to rats, a total of 324 prototypes and metabolites were identified from rat plasma, urine, feces and bile, including 81 aporphines, 95 protoberberines, 117 morphinans and 31 benzylisoquinolines. The main types of metabolites were demethylation, hydrogenation, dehydrogenation, aldehydation, oxidation, methylation, sulfate esterification, glucuronidation, glucose conjugation, glycine conjugation, acetylation, and dihydroxylation. In summary, this integrated strategy provides an additional approach for the incomplete identification caused by compound diversity and low abundance, laying the foundation for the discovery of new bioactive compounds of SC against rheumatoid arthritis.

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.

Metabolites rapid-annotation in mice by comprehensive method of virtual polygons and Kendric mass loss filtering: A case study of Dendrobium nobile Lindl

With significant advancements in high-resolution mass spectrometry, there has been a substantial increase in the amount of chemical component data acquired from natural products. Therefore, the rapid and efficient extraction of valuable mass spectral information from large volumes of high-resolution mass spectrometry data holds crucial significance. This study illustrates a targeted annotation of the metabolic products of alkaloid and sesquiterpene components from Dendrobium nobile (D. nobile) aqueous extract in mice serum through the integration of an in-houses database, R programming, a virtual metabolic product library, polygonal mass defect filtering, and Kendrick mass defect strategies. The research process involved initially establishing a library of alkaloids and sesquiterpenes components and simulating 71 potential metabolic reactions within the organism using R programming, thus creating a virtual metabolic product database. Subsequently, employing the virtual metabolic product library allowed for polygonal mass defect filtering, rapidly screening 1705 potential metabolites of alkaloids and 3044 potential metabolites of sesquiterpenes in the serum. Furthermore, based on the chemical composition database of D. nobile and online mass spectrometry databases, 95 compounds, including alkaloids, sesquiterpenes, and endogenous components, were characterized. Finally, utilizing Kendrick mass defect analysis in conjunction with known alkaloids and sesquiterpenes targeted screening of 209 demethylation, methylation, and oxidation products in phase I metabolism, and 146 glucuronidation and glutathione conjugation products in phase II metabolism. This study provides valuable insights for the rapid and accurate annotation of chemical components and their metabolites in vivo within natural products.

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.

Transformation products of antibacterial drugs in environmental water: Identification approaches based on liquid chromatography-high resolution mass spectrometry

In recent years, the presence of antibiotics in the aquatic environment has caused increasing concern for the possible consequences on human health and ecosystems, including the development of antibiotic-resistant bacteria. However, once antibiotics enter the environment, mainly through hospital and municipal discharges and the effluents of wastewater treatment plants, they can be subject to transformation reactions, driven by both biotic (e.g. microorganism and mammalian metabolisms) and abiotic factors (e.g. oxidation, photodegradation, and hydrolysis). The resulting transformation products (TPs) can be less or more active than their parent compounds, therefore the inclusion of TPs in monitoring programs should be mandatory. However, only the reference standards of a few known TPs are available, whereas many other TPs are still unknown, due to the high diversity of possible transformation reactions in the environment. Modern high-resolution mass spectrometry (HRMS) instrumentation is now ready to tackle this problem through suspect and untargeted screening approaches. However, for handling the large amount of data typically encountered in the analysis of environmental samples, these approaches also require suitable processing workflows and accurate tandem mass spectra interpretation. The compilation of a suspect list containing the possible monoisotopic masses of TPs retrieved from the literature and/or from laboratory simulated degradation experiments showed unique advantages. However, the employment of in silico prediction tools could improve the identification reliability. In this review, the most recent strategies relying on liquid chromatography-HRMS for the analysis of environmental TPs of the main antibiotic classes were examined, whereas TPs formed during water treatments or disinfection were not included.

Multi-class analysis of 100 drug residues in cosmetics using high-performance liquid chromatography-quadrupole time-of-flight high-resolution mass spectrometry

Cosmetics are an important aspect of the lives of many people. With an increasing demand for cosmetics, consumers pay more attention to their efficacy and composition. To improve their efficacy, prohibited substances, such as hormones, glucocorticoids, antibiotics, antifungals and antihistamines, may be added to cosmetics. We developed a rapid method for the multi-class analysis of drug residues in toner and lotion cosmetic samples using high-performance liquid chromatography coupled with quadrupole time-of-flight high-resolution mass spectrometry (HPLC-Q-TOF-HRMS). The primary variables in the extraction and purification steps were studied to minimize the interference of the sample matrix. The non-information-dependent sequential window acquisition of all theoretical fragment ion spectra (SWATH®) mode was used to improve the data acquisition efficiency. The secondary product ion peak areas were used for quantification to obtain a satisfactory matrix effects. The validation experiments confirmed that the developed method exhibited good linearity (5-200 ng/L) with correlation coefficients (R) ≥ 0.9902. Our developed method was then successfully applied to 92 real cosmetic samples. The calibration curve established by this method can be used for retrospective quantitative analysis over long durations without re-calibration. This method is efficient and suitable for screening and controlling multi-class prohibited substances in the cosmetics industry to reduce potential risks.