Seven Golden Rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry

Stable Isotope-Assisted Plant Metabolomics: Investigation of Phenylalanine-Related Metabolic Response in Wheat Upon Treatment With the Fusarium Virulence Factor Deoxynivalenol

The major Fusarium mycotoxin deoxynivalenol (DON) is a virulence factor in wheat and has also been shown to induce defense responses in host plant tissue. In this study, global and tracer labeling with 13C were combined to annotate the overall metabolome of wheat spikes and to evaluate the response of phenylalanine-related pathways upon treatment with DON. At anthesis, spikes of resistant and susceptible cultivars as well as two related near isogenic wheat lines (NILs) differing in the presence/absence of the major resistance QTL Fhb1 were treated with 1 mg DON or water (control), and samples were collected at 0, 12, 24, 48, and 96 h after treatment (hat). A total of 172 Phe-derived wheat constituents were detected with our untargeted approach employing 13C-labeled phenylalanine and subsequently annotated as flavonoids, lignans, coumarins, benzoic acid derivatives, hydroxycinnamic acid amides (HCAAs), as well as peptides. Ninety-six hours after the DON treatment, up to 30% of the metabolites biosynthesized from Phe showed significantly increased levels compared to the control samples. Major metabolic changes included the formation of precursors of compounds implicated in cell wall reinforcement and presumed antifungal compounds. In addition, also dipeptides, which presumably are products of proteolytic degradation of truncated proteins generated in the presence of the toxin, were significantly more abundant upon DON treatment. An in-depth comparison of the two NILs with correlation clustering of time course profiles revealed some 70 DON-responsive Phe derivatives. While several flavonoids had constitutively different abundance levels between the two NILs differing in resistance, other Phe-derived metabolites such as HCAAs and hydroxycinnamoyl quinates were affected differently in the two NILs after treatment with DON. Our results suggest a strong activation of the general phenylpropanoid pathway and that coumaroyl-CoA is mainly diverted towards HCAAs in the presence of Fhb1, whereas the metabolic route to monolignol(-conjugates), lignans, and lignin seems to be favored in the absence of the Fhb1 resistance quantitative trait loci.

Stable Isotope-Assisted Plant Metabolomics: Combination of Global and Tracer-Based Labeling for Enhanced Untargeted Profiling and Compound Annotation

Untargeted approaches and thus biological interpretation of metabolomics results are still hampered by the reliable assignment of the global metabolome as well as classification and (putative) identification of metabolites. In this work we present an liquid chromatography-mass spectrometry (LC-MS)-based stable isotope assisted approach that combines global metabolome and tracer based isotope labeling for improved characterization of (unknown) metabolites and their classification into tracer derived submetabolomes. To this end, wheat plants were cultivated in a customized growth chamber, which was kept at 400 ± 50 ppm 13CO2 to produce highly enriched uniformly 13C-labeled sample material. Additionally, native plants were grown in the greenhouse and treated with either 13C9-labeled phenylalanine (Phe) or 13C11-labeled tryptophan (Trp) to study their metabolism and biochemical pathways. After sample preparation, liquid chromatography-high resolution mass spectrometry (LC-HRMS) analysis and automated data evaluation, the results of the global metabolome- and tracer-labeling approaches were combined. A total of 1,729 plant metabolites were detected out of which 122 respective 58 metabolites account for the Phe- and Trp-derived submetabolomes. Besides m/z and retention time, also the total number of carbon atoms as well as those of the incorporated tracer moieties were obtained for the detected metabolite ions. With this information at hand characterization of unknown compounds was improved as the additional knowledge from the tracer approaches considerably reduced the number of plausible sum formulas and structures of the detected metabolites. Finally, the number of putative structure formulas was further reduced by isotope-assisted annotation tandem mass spectrometry (MS/MS) derived product ion spectra of the detected metabolites. A major innovation of this paper is the classification of the metabolites into submetabolomes which turned out to be valuable information for effective filtering of database hits based on characteristic structural subparts. This allows the generation of a final list of true plant metabolites, which can be characterized at different levels of specificity.

Suspect, non-target and target screening of emerging pollutants using data independent acquisition: Assessment of a Mediterranean River basin

A single workflow based on three approaches (target, suspected and non-target screening) using liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (LC-QTOF-MS) in data independent acquisition mode (DIA) was developed to assess the presence of emerging pollutants (EPs) in water and sediments from a Mediterranean River Basin. Identification of potential contaminants was based on mass accuracy, isotopic ratio pattern, theoretical fragmentation, and retention time using Waters UNIFI software. In the suspect screening against a library containing 2200 components, 68 contaminants were tentatively identified, 6 of which were confirmed and quantified with analytical standards. Non-target screening (NTS) required additional manual processing and the aid of an on-line database (ChemSpider) to tentatively identify compounds. Eprosartan, an antihypertensive drug not included in the library used for suspected screening, was confirmed and semi-quantified. The identification of Eprosartan proved the workflow to be functional for NTS. Target screening of 171 pesticides and 33 pharmaceuticals and personal care products (PPCPs) including the compounds confirmed using suspect (6) and non target (1) screening achieved monitoring of the most abundant contaminants from the head to the mouth of the Turia basin to establish their spatial distribution. QTOF-MS screening versatility with its high-resolution capability allows for a comprehensive assessment of EPs in the aquatic environment.

Applications of MicroArrays for Mass Spectrometry (MAMS) in Single-Cell Metabolomics

The metabolic network is the endpoint in the flow of information that begins with the "gene" and ends with "phenotype" (observable function) of the cell. Previously, due to the variety of metabolites analyzed inside cells, the metabolomic measurements were performed with samples including multiple cells. Unfortunately, this sampling process may mask important metabolic phenomena, such as cell-to-cell heterogeneity. For these studies, we must use analytical techniques that can robustly deliver reproducible results with single-cell sensitivity. In this chapter, we summarize laser-based methods for single-cell analysis and a novel approach of MicroArrays for Mass Spectrometry (or MAMS) is described in full detail. This particular type of microarrays was tailored for the study of cells grown in liquid medium using multiple-analytical read-outs, such as optical and laser desorption/ionization (LDI) or MALDI mass spectrometry.

Nontarget profiling of organic compounds in a temporal series of hydraulic fracturing flowback and produced waters

Hydraulic fracturing (HF) flowback and produced water (FPW) can be toxic to aquatic life but its chemical content is largely unknown, variable and complex. Seven FPW samples were collected from a HF operation in the Duvernay Formation (Alberta, Canada) over 30 days of flowback and characterized by a nontarget workflow based on high performance liquid chromatography - high resolution mass spectrometry (HRMS). A modified Kendrick mass defect plot and MS/MS spectral interpretation revealed seven series of homologues composed of ethylene oxide (i.e. -CH₂CH₂O-), among which a series of aldehydes was proposed as degradation products of polyethylene glycols, and two series of alkyl ethoxylate carboxylates could be proprietary HF additives. Many other ions were confidently assigned a formula by accurate mass measurement and were subsequently prioritized for identification by matching to records in ChemSpider and the US EPA's CompTox Chemistry Dashboard. Quaternary ammonium compounds, amine oxides, organophosphorous compounds, phthalate diesters and hydroxyquinoline were identified with high confidence by MS/MS spectra (Level 3), matching to reference spectra in MassBank (Level 2) or to authentic standards (Level 1). Temporal trends showed that most of the compounds declined in abundance over the first nine days of flowback, except for phthalate diesters and hydroxyquinoline that were still observed on Day 30 and had disappearance half-lives of 61 and 91 days, respectively. All the compounds followed first-order disappearance kinetics in flowback, except for polyoxygenated acids which followed second-order kinetics. This analysis and the workflow, based largely on public on-line databases, enabled profiling of complex organic compounds in HF-FPW, and will likely be useful for further understanding the toxicity and chemical fate of HF-FPW.

Integrated Probabilistic Annotation: A Bayesian-Based Annotation Method for Metabolomic Profiles Integrating Biochemical Connections, Isotope Patterns, and Adduct Relationships

In a typical untargeted metabolomics experiment, the huge amount of complex data generated by mass spectrometry necessitates automated tools for the extraction of useful biological information. Each metabolite generates numerous mass spectrometry features. The association of these experimental features to the underlying metabolites still represents one of the major bottlenecks in metabolomics data processing. While certain identification (e.g., by comparison to authentic standards) is always desirable, it is usually achievable only for a limited number of compounds, and scientists often deal with a significant amount of putatively annotated metabolites. The confidence in a specific annotation is usually assessed by considering different sources of information (e.g., isotope patterns, adduct formation, chromatographic retention times, and fragmentation patterns). IPA (integrated probabilistic annotation) offers a rigorous and reproducible method to automatically annotate metabolite profiles and evaluate the resulting confidence of the putative annotations. It is able to provide a rigorous measure of our confidence in any putative annotation and is also able to update and refine our beliefs (i.e., background prior knowledge) by incorporating different sources of information in the annotation process, such as isotope patterns, adduct formation and biochemical relations. The IPA package is freely available on GitHub ( https://github.com/francescodc87/IPA ), together with the related extensive documentation.

Isotopic Distributions

Isotopic information determined by mass spectrometry can be used in a wide variety of applications. Broadly speaking these could be classified as "passive" applications, meaning that they use naturally occurring isotopic information, and "active" applications, meaning that the isotopic distributions are manipulated in some way. The classic passive application is the determination of chemical composition by comparing observed isotopic patterns of molecules to theoretically calculated isotopic patterns. Active applications include isotope exchange experiments of a variety of types, as well as isotope labeling in tracing studies and to provide references for quantitation. Regardless of the type of application considered, the problem of theoretical calculation of isotopic patterns almost invariably arises. This chapter reviews a number of application examples and computational approaches for isotopic studies in mass spectrometry.

One Among Millions: The Chemical Space of Nucleic Acid-Like Molecules

Biology encodes hereditary information in DNA and RNA, which are finely tuned to their biological functions and modes of biological production. The central role of nucleic acids in biological information flow makes them key targets of pharmaceutical research. Indeed, other nucleic acid-like polymers can play similar roles to natural nucleic acids both in vivo and in vitro; yet despite remarkable advances over the last few decades, much remains unknown regarding which structures are compatible with molecular information storage. Chemical space describes the structures and properties of molecules that could exist within a given molecular formula or other classification system. Using structure generation methods, we explore nucleic acid analogues within the formula ranges BC_3-7H_5-15O_2-4 and BC_3-6H_5-15N_1-2O_0-4, where B is a recognition element (e.g., a nucleobase). Other restrictions included two obligatory points of attachment for inclusion into a linear polymer and substructures predicting chemical stability. These sets contain 86,007 (CHO) and 75,309 (CHNO) compositionally isomeric structures, representing 706,568 CHO and 454,422 CHNO stereoisomers, that diversely and densely occupy this space. These libraries point toward there being large spaces of unexplored chemistry relevant to pharmacology and biochemistry and efforts to understand the origins of life.

Combination of Isotope Labeling and Molecular Networking of Tandem Mass Spectrometry Data To Reveal 69 Unknown Metabolites Produced by Penicillium nordicum

The secondary metabolome of Penicillium nordicum is poorly documented despite its frequent detection on contaminated food and its capacity to produce toxic metabolites such as ochratoxin A. To characterize metabolites produced by this fungi, we combined a full stable isotopes labeling with the dereplication of tandem mass spectrometry (MS/MS) data by molecular networking. First, the untargeted metabolomic analysis by high-resolution mass spectrometry of a double stable isotope labeling of P. nordicum enabled the specific detection of its metabolites and the unambiguous determination of their elemental composition. Analyses showed that infection of substrate by P. nordicum lead to the production of at least 92 metabolites and that 69 of them were completely unknown. Then, curated molecular networks of MS/MS data were generated with GNPS and MetGem, specifically on the features of interest, which allowed highlighting 13 fungisporin-related metabolites that had not previously been identified in this fungus and 8 that had never been observed in any fungus. The structures of the unknown compounds, namely, a native fungisporin and seven linear peptides, were characterized by tandem mass spectrometry experiments. The analysis of P. nordicum growing on its natural substrates, i.e. pork ham, turkey ham, and cheese, demonstrated that 10 of the known fungisporin-related metabolites and three of the new metabolites were also synthesized. Thus, the curation of data for molecular networking using a specific detection of metabolites of interest with stable isotopes labeling allowed the discovery of new metabolites produced by the food contaminant P. nordicum.

Newly Identified AhR-Active Compounds in the Sediments of an Industrial Area Using Effect-Directed Analysis

Effect-directed analysis was used to identify previously unidentified aryl hydrocarbon receptor (AhR) agonists in sediments collected from a highly industrialized area of Ulsan Bay, Korea. The specific objectives were to (i) investigate potent fractions of sediment extracts using the H4IIE-luc bioassay, (ii) determine the concentrations of known AhR agonists (polycyclic aromatic hydrocarbons (PAHs) and styrene oligomers (SOs)), (iii) identify previously unreported AhR agonists in fractions by use of GC-QTOFMS, and (iv) evaluate contributions of individual compounds to overall AhR-mediated potencies, found primarily in fractions containing aromatics with log K_ow 5-8. Greater concentrations of PAHs and SOs were also found in those fractions. On the basis of GC-QTOFMS and GC-MSD analyses, 16 candidates for AhR agonists were identified in extracts of sediments. Of these, seven compounds, including 1-methylchrysene, benzo[j]fluoranthene, 3-methylchrysene, 5-methylbenz[a]anthracene, 11H-benzo[b]fluorene, benzo[b]naphtho[2,3-d]furan, and benzo[b]naphtho[2,1-d]thiophene, exhibited significant AhR activity. Relative potency values of newly identified AhR agonists were found to be greater than or comparable to that of benzo[a]pyrene (BaP). The potency balance analysis showed that newly identified AhR agonists explained 0.07-16% of bioassay-derived BaP-EQs. These chemicals were widely distributed in industrial sediments; thus, it is of immediate importance to conduct studies on sources and potential effects of those chemicals.

Metallophores associated with Trichodesmium erythraeum colonies from the Gulf of Aqaba

Trichodesmium is a globally important marine nitrogen fixing cyanobacteria which forms colonies and utilizes atmospherically derived dust as a source for the limiting micro-nutrient iron. Here we report the identification of metallophores isolated from incubations of natural Trichodesmium colonies collected from the Gulf of Aqaba in the Red Sea. Three of our compounds were identified as the ferrioxamine siderophores B, E, and G. The remaining fifteen metallophores had mass to charge ratios that, to our knowledge, are not common to known siderophores. Putative sum formulas suggest most of these compounds were not structurally related to each other. We also found that the novel metallophores readily formed complexes with aluminium and were less specific for iron than the ferrioxamines. In our incubations of Trichodesmium colonies, the abundance of ten of the novel metallophores positively correlated with Trichodesmium biomass, but not with bacterial biomass, whilst ferrioxamine siderophores were more strongly associated with bacterial biomass. We identified ferrioxamines and our novel metallophores in filtered surface seawater samples from the Gulf of Aqaba. However, our novel metallophores were only observed in the surface seawater sample collected at the time of highest Trichodesmium abundance, while ferrioxamines were observed even when Trichodesmium was not present. We hypothesize that the novel metallophores were specifically associated with Trichodesmium colonies. Together with the bacterially produced ferrioxamines they likely contribute to a distinctive "ligandosphere" surrounding the Trichodesmium colonies, with potential implications for metal homeostasis within the colony environment.

Topological Characterization of Coordination-Driven Self-assembly Complexes: Applications of Ion Mobility-Mass Spectrometry

Coordination-driven self-assembly (CDSA) is increasingly used to synthesize coordination complexes containing metal-centered electron acceptors and typically nitrogen-containing electron donors. Characterization of the structures obtained from CDSA via crystallographic or spectroscopic means is limited due to difficulties in forming single crystals for X-ray studies and overlapping precursor and product signals in NMR. Here, we employ ion mobility-mass spectrometry (IM-MS), which provides a direct measure of size and shape of the CDSA complexes, to study the intact reaction products of a rhomboid-shaped complex. This approach negates the need for product isolation and crystallization and allows for tracking of the product distribution as a function of time. A potential challenge of IM-MS is that the size/shape of the observed CDSA complexes can vary with internal energy; however, we show that proper tuning of the instrument reduces the effects of collisional activation thereby allowing for retention of ion conformations that reflect solution-phase ion structures. Graphical Abstract.

A classification of liquid chromatography mass spectrometry techniques for evaluation of chemical composition and quality control of traditional medicines

Natural products (NPs) and traditional medicines (TMs) are used for treatment of various diseases and also to develop new drugs. However, identification of drug leads within the immense biodiversity of living organisms is a challenging task that requires considerable time, labor, and computational resources as well as the application of modern analytical instruments. LC-MS platforms are widely used for both drug discovery and quality control of TMs and food supplements. Moreover, a large dataset generated during LC-MS analysis contains valuable information that could be extracted and handled by means of various data mining and statistical tools. Novel sophisticated LC-MS based approaches are being introduced every year. Therefore, this review is prepared for the scientists specialized in pharmacognosy and analytical chemistry of NPs as well as working in related areas, in order to navigate them in the world of diverse LC-MS based techniques and strategies currently employed for NP discovery and dereplication, quality control, pattern recognition and sample comparison, and also in targeted and untargeted metabolomic studies. The suggested classification system includes the following LC-MS based procedures: elemental composition determination, isotopic fine structure analysis, mass defect filtering, de novo identification, clustering of the compounds in Molecular Networking (MN), diagnostic fragment ion (or neutral loss) filtering, manual dereplication using MS/MS data, database-assisted peak annotation, annotation of spectral trees, MS fingerprinting, feature extraction, bucketing of LC-MS data, peak profiling, predicted metabolite screening, targeted quantification of biomarkers, quantitative analysis of multi-component system, construction of chemical fingerprints, multi-targeted and untargeted metabolite profiling.

Examination of molecular space and feasible structures of bioactive components of humic substances by FTICR MS data mining in ChEMBL database

Humic substances (HS) are complex natural mixtures comprising a large variety of compounds produced during decomposition of decaying biomass. The molecular composition of HS is extremely diverse as it was demonstrated with the use of high resolution mass spectrometry. The building blocks of HS are mostly represented by plant-derived biomolecules (lignins, lipids, tannins, carbohydrates, etc.). As a result, HS show a wide spectrum of biological activity. Despite that, HS remain a 'biological activity black-box' due to unknown structures of constituents responsible for the interaction with molecular targets. In this study, we investigated the antiviral activity of eight HS fractions isolated from peat and coal, as well as of two synthetic humic-like materials. We determined molecular compositions of the corresponding samples using ultra-high resolution Fourier-transform ion cyclotron resonance mass-spectrometry (FTICR MS). Inhibitory activity of HS was studied with respect to reproduction of tick-borne encephalitis virus (TBEV), which is a representative of Flavivirus genus, and to a panel of enteroviruses (EVs). The samples of natural HS inhibited TBEV reproduction already at a concentration of 1 µg/mL, but they did not inhibit reproduction of EVs. We found that the total relative intensity of FTICR MS formulae within elemental composition range commonly attributed to flavonoid-like structures is correlating with the activity of the samples. In order to surmise on possible active structural components of HS, we mined formulae within FTICR MS assignments in the ChEMBL database. Out of 6502 formulae within FTICR MS assignments, 3852 were found in ChEMBL. There were more than 71 thousand compounds related to these formulae in ChEMBL. To support chemical relevance of these compounds to natural HS we applied the previously developed approach of selective isotopic exchange coupled to FTICR MS to obtain structural information on the individual components of HS. This enabled to propose compounds from ChEMBL, which corroborated the labeling data. The obtained results provide the first insight onto the possible structures, which comprise antiviral components of HS and, respectively, can be used for further disclosure of antiviral activity mechanism of HS.

MetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis

We present a new update to MetaboAnalyst (version 4.0) for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since the last major update in 2015, MetaboAnalyst has continued to evolve based on user feedback and technological advancements in the field. For this year's update, four new key features have been added to MetaboAnalyst 4.0, including: (1) real-time R command tracking and display coupled with the release of a companion MetaboAnalystR package; (2) a MS Peaks to Pathways module for prediction of pathway activity from untargeted mass spectral data using the mummichog algorithm; (3) a Biomarker Meta-analysis module for robust biomarker identification through the combination of multiple metabolomic datasets and (4) a Network Explorer module for integrative analysis of metabolomics, metagenomics, and/or transcriptomics data. The user interface of MetaboAnalyst 4.0 has been reengineered to provide a more modern look and feel, as well as to give more space and flexibility to introduce new functions. The underlying knowledgebases (compound libraries, metabolite sets, and metabolic pathways) have also been updated based on the latest data from the Human Metabolome Database (HMDB). A Docker image of MetaboAnalyst is also available to facilitate download and local installation of MetaboAnalyst. MetaboAnalyst 4.0 is freely available at http://metaboanalyst.ca.

Guidelines for unequivocal structural identification of compounds with biological activity of significance in food chemistry (IUPAC Technical Report)

Isolation of endogenous constituents of foods is generally performed in order to elucidate the biological activity of individual compounds and their role with respect to factors such as organoleptic qualities, health and nutritional benefits, plant protection against herbivores, pathogens and competition, and presence of toxic constituents. However, unless such compounds are unequivocally defined with respect to structure and purity, any biological activity data will be compromised. Procedures are therefore proposed for comprehensive elucidation of food-based organic structures using modern spectroscopic and spectrometric techniques. Also included are guidelines for the experimental details and types of data that should be reported in order for subsequent investigators to repeat and validate the work. Because food chemistry usually involves interdisciplinary collaboration, the purpose is to inform chemists and scientists from different fields, such as biological sciences, of common standards for the type and quality of data to be presented in elucidating and reporting structures of biologically active food constituents. The guidelines are designed to be understandable to chemists and non-chemists alike. This will enable unambiguous identification of compounds and ensure that the biological activity is based on a secure structural chemistry foundation.

Molecular characteristics of dissolved organic matter transformed by O3 and O3/H2O2 treatments and the effects on formation of unknown disinfection by-products

We investigated semiquantitative changes in almost 1000 dissolved organic matter (DOM) features during oxidation with 1 mg of O₃ per liter (mg O₃/L), 4 mg O₃/L, or 4 mg O₃/L + 2.5 mg of H₂O₂ per liter (advanced oxidation process, AOP) by unknown screening analysis with Orbitrap mass spectrometry. The consequential effects on formation of unknown disinfection by-products (DBPs) by chlorination were evaluated in laboratory-scale experiments. Several hundred unsaturated DOM features with positive oxygen-subtracted double bond equivalents per carbon ((DBE-O)/C) were decomposed by the ozone-only treatment and AOP. The AOP decomposed some saturated (negative (DBE-O)/C)) and reduced molecules, which had negative carbon oxidation states (C_os). Several hundred saturated oxidation by-products were detected after ozonation and the AOP. After chlorination, the samples pre-treated with ozone alone resulted in higher formation of unknown DBPs than the AOP pre-treated sample or the sample without oxidation. Over half of the DBP precursors, estimated by electrophilic substitution, were not totally decomposed by any oxidation process, but they were increased after the ozone-only process and AOP. DBP precursors produced by the ozone-only process or AOP formed unique unknown DBPs. Therefore, post-treatment processes after oxidation and before chlorination are important to minimize formation of unknown DBPs.

Semi-quantitative non-target analysis of water with liquid chromatography/high-resolution mass spectrometry: How far are we?

Combining high-resolution mass spectrometry (HRMS) with liquid chromatography (LC) has considerably increased the capability of analytical chemistry. Among others, it has stimulated the growth of the non-target analysis, which aims at identifying compounds without their preceding selection. This approach is already widely applied in various fields, such as metabolomics, proteomics, etc. The applicability of LC/HRMS-based non-target analysis in environmental analyses, such as water studies, would be beneficial for understanding the environmental fate of polar pollutants and evaluating the health risks exposed by the new emerging contaminants. During the last five to seven years the use of LC/HRMS-based non-target analysis has grown rapidly. However, routine non-target analysis is still uncommon for most environmental monitoring agencies and environmental scientists. The main reasons are the complicated data processing and the inability to provide quantitative information about identified compounds. The latter shortcoming follows from the lack of standard substances, considered so far as the soul of each quantitative analysis for the newly discovered pollutants. To overcome this, non-target analyses could be combined with semi-quantitation. This Perspective aims at describing the current methods for non-target analysis, the possibilities and challenges of standard substance-free semi-quantitative analysis, and proposes tools to join these two fields together.

Small Molecule Isotope Resolved Formula Enumeration: A Methodology for Assigning Isotopologues and Metabolite Formulas in Fourier Transform Mass Spectra

Improvements in Fourier transform mass spectrometry (FT-MS) enable increasingly more complex experiments in the field of metabolomics. What is directly detected in FT-MS spectra are spectral features (peaks) that correspond to sets of adducted and charged forms of specific molecules in the sample. The robust assignment of these features is an essential step for MS-based metabolomics experiments, but the sheer complexity of what is detected and a variety of analytically introduced variance, errors, and artifacts has hindered the systematic analysis of complex patterns of observed peaks with respect to isotope content. We have developed a method called SMIRFE that detects small biomolecules and determines their elemental molecular formula (EMF) using detected sets of isotopologue peaks sharing the same EMF. SMIRFE does not use a database of known metabolite formulas; instead a nearly comprehensive search space of all isotopologues within a mass range is constructed and used for assignment. This search space can be tailored for different isotope labeling patterns expected in different stable isotope tracing experiments. Using consumer-level computing equipment, a large search space of 2000 Da was constructed, and assignment performance was evaluated and validated using verified assignments on a pair of peak lists derived from spectra containing unlabeled and ¹⁵N-labeled versions of amino acids derivatized using ethylchloroformate. SMIRFE identified 18 of 18 predicted derivatized EMFs, and each assignment was evaluated statistically and assigned an e-value representing the probability to occur by chance.

"-Omics" workflow for paleolimnological and geological archives: A review

"-Omics" is a powerful screening method with applications in molecular biology, toxicology, wildlife biology, natural product discovery, and many other fields. Genomics, proteomics, metabolomics, and lipidomics are common examples included under the "-omics" umbrella. This screening method uses combinations of untargeted, semi-targeted, and targeted analyses paired with data mining to facilitate researchers' understanding of the genome, proteins, and small organic molecules in biological systems. Recently, however, the use of "-omics" has expanded into the fields of geology, specifically petrology, and paleolimnology. Specifically, untargeted analyses stand to transform these fields as petroleomics, and sediment-"omics" become more prevalent. "-Omics" facilitates the visualization of small molecule profiles from environmental matrices (i.e. oil and sediment). Small molecule profiles can provide improved understanding of small molecules distributions throughout the environment, and how those compositions can change depending on conditions (i.e. climate change, weathering, etc.). "-Omics" also facilities discovery of next-generation biomarkers that can be used for oil source identification and as proxies for reconstructing past environmental changes. Untargeted analyses paired with data mining and multivariate statistical analyses represents a powerful suite of tools for hypothesis generation, and new method development for environmental reconstructions. Here we present an introduction to "-omics" methodology, technical terms, and examples of applications to paleolimnology and petrology. The purpose of this review is to highlight the important considerations at each step in the "-omics" workflow to produce high quality and statistically powerful data for petrological and paleolimnological applications.

Rapid screening methods for yeast sub-metabolome analysis with a high-resolution ion mobility quadrupole time-of-flight mass spectrometer

RATIONALE

The wide chemical diversity and complex matrices inherent to metabolomics still pose a challenge to current analytical approaches for metabolite screening. Although dedicated front-end separation techniques combined with high-resolution mass spectrometry set the benchmark from an analytical point of view, the increasing number of samples and sample complexity demand for a compromise in terms of selectivity, sensitivity and high-throughput analyses.

METHODS

Prior to low-field drift tube ion mobility (IM) separation and quadrupole time-of-flight mass spectrometry (QTOFMS) detection, rapid ultrahigh-performance liquid chromatography separation was used for analysis of different concentration levels of dansylated metabolites present in a yeast cell extract. For identity confirmation of metabolites at the MS2 level, an alternating frame approach was chosen and two different strategies were tested: a data-independent all-ions acquisition and a quadrupole broad band isolation (Q-BBI) directed by IM drift separation.

RESULTS

For Q-BBI analysis, the broad mass range isolation was successfully optimized in accordance with the distinctive drift time to m/z correlation of the dansyl derivatives. To guarantee comprehensive sampling, a broad mass isolation window of 70 Da was employed. Fragmentation was performed via collision-induced dissociation, applying a collision energy ramp optimized for the dansyl derivatives. Both approaches were studied in terms of linear dynamic range and repeatability employing ethanolic extracts of Pichia pastoris spiked with 1 μM metabolite mixture. Example data obtained for histidine and glycine showed that drift time precision (<0.01 to 0.3% RSD, n = 5) compared very well with the data reported in an earlier IM-TOFMS-based study.

CONCLUSIONS

Chimeric mass spectra, inherent to data-independent analysis approaches, are reduced when using a drift time directed Q-BBI approach. Additionally, an improved linear dynamic working range was observed, representing, together with a rapid front-end separation, a powerful approach for metabolite screening.

The Structure and Function of Major Plant Metabolite Modifications

Plants produce a myriad of structurally and functionally diverse metabolites that play many different roles in plant growth and development and in plant response to continually changing environmental conditions as well as abiotic and biotic stresses. This metabolic diversity is, to a large extent, due to chemical modification of the basic skeletons of metabolites. Here, we review the major known plant metabolite modifications and summarize the progress that has been achieved and the challenges we are facing in the field. We focus on discussing both technical and functional aspects in studying the influences that various modifications have on biosynthesis, degradation, transport, and storage of metabolites, as well as their bioactivity and toxicity. Finally, we discuss some emerging insights into the evolution of metabolic pathways and metabolite functionality.

Microbial transformation of virus-induced dissolved organic matter from picocyanobacteria: coupling of bacterial diversity and DOM chemodiversity

Picocyanobacteria make up half of the ocean's primary production, and they are subjected to frequent viral infection. Viral lysis of picocyanobacteria is a major driving force converting biologically fixed carbon into dissolved organic carbon (DOC). Viral-induced dissolved organic matter (vDOM) released from picocyanobacteria provides complex organic matter to bacterioplankton in the marine ecosystem. In order to understand how picocyanobacterial vDOM are transformed by bacteria and the impact of this process on bacterial community structure, viral lysate of picocyanobacteria was incubated with coastal seawater for 90 days. The transformation of vDOM was analyzed by ultrahigh-resolution mass spectrometry and the shift of bacterial populations analyzed using high-throughput sequencing technology. Addition of picocyanobacterial vDOM introduced abundant nitrogen components into the coastal water, which were largely degraded during the 90 days' incubation period. However, some DOM signatures were accumulated and the total assigned formulae number increased over time. In contrast to the control (no addition of vDOM), bacterial community enriched with vDOM changed markedly with increased biodiversity indices. The network analysis showed that key bacterial species formed complex relationship with vDOM components, suggesting the potential correspondence between bacterial populations and DOM molecules. We demonstrate that coastal bacterioplankton are able to quickly utilize and transform lysis products of picocyanobacteria, meanwhile, bacterial community varies with changing chemodiverisity of DOM. vDOM released from picocyanobacteria generated a complex labile DOM pool, which was converted to a rather stable DOM pool after microbial processing in the time frame of days to weeks.

Exploring the Occurrence and Temporal Variation of ToxCast Chemicals in Fine Particulate Matter Using Suspect Screening Strategy

Existence of emerging contaminants in the environment is of great importance for health risk assessment. The consensus on categories and numbers of the emerging contaminants in airborne fine particulate matter (PM_2.5) is still extremely deficient. In this study, an in-house data set was constructed containing 890 unique ToxCast (Phase I and Phase II) chemicals. Occurrence and temporal variation of the chemicals was investigated by a suspect screening workflow in 60 PM_2.5 samples from January to December of 2016 in Beijing. Eighty-nine compounds were identified in 12 substance categories, which covered a broad range of physicochemical properties. Quantification/semiquantification results showed that phthalates, phenols, and carboxylic esters were the three most predominant categories, with mean concentrations of 7.82, 4.42, and 4.11 ng/m³, respectively. Four diverse temporal variation patterns were discerned, which could be explained by correlations of chemical concentrations (or instrumental responses) with meteorological parameters. An extended retrospective suspect screening was also performed to reveal the presence of several analogues of the identified chemicals that were not included in the data set. Another 75 pollutants were tentatively recognized, and comparison of estimated composition profiles based on instrumental responses suggested the identified ToxCast chemicals are a notable subset of typical emerging contaminants. The results might facilitate ranking of organic pollutants with active biological effects in PM_2.5 samples.

Advances in Chemical and Biological Methods to Identify Microorganisms-From Past to Present

Fast detection and identification of microorganisms is a challenging and significant feature from industry to medicine. Standard approaches are known to be very time-consuming and labor-intensive (e.g., culture media and biochemical tests). Conversely, screening techniques demand a quick and low-cost grouping of bacterial/fungal isolates and current analysis call for broad reports of microorganisms, involving the application of molecular techniques (e.g., 16S ribosomal RNA gene sequencing based on polymerase chain reaction). The goal of this review is to present the past and the present methods of detection and identification of microorganisms, and to discuss their advantages and their limitations.

Occurrence and Degradation Potential of Fluoroalkylsilane Substances as Precursors of Perfluoroalkyl Carboxylic Acids

Polyfluoroalkylsilanes (PFASis) are a class of artificial chemicals with wide applications in surface coating, which arouse attention due to their hydrophobic/oleophobic properties and potential biological effects. In this study, a robust high-resolution mass spectrometry method through direct injection into a Fourier transform ion cyclotron resonance instrument was established, with the aid of CF₂-scaled Kendrick mass defect analysis and isotope fine structure elucidation. The occurrence of 8:2 polyfluoroalkyl trimethoxysilane (8:2 PTrMeOSi) and 8:2 polyfluoroalkyl triethoxysilane (8:2 PTrEtOSi), as well as their cationic adducts, solvent substitutions, and other compound analogues, were identified in commercial antifingerprint liquid products. In the hydroxyl radical-based total oxidizable precursor assay, differential molar yields of products were observed with regard to varied PFASi carbon-chain lengths and terminal groups. The yields of perfluoroalkyl carboxylic acids (PFCAs) from 8:2 PTrMeOSi conversion were the highest (92 ± 9%, n = 3), with the C ( n - 1) perfluoroheptanoic acid (PFHpA, 49 ± 11%, n = 3) as the dominating product. Distinct conversion of 8:2 PTrMeOSi in the simulated solar exposure experiments found that C ( n) perfluorooctanoic acid (PFOA, 0.6 ± 0.04 ‰, n = 3) was predominant, and 8:2 fluorotelomer carboxylic acid (8:2 FTCA, 0.59 ± 0.08‰, n = 3), 8:2 fluorotelomer unsaturated carboxylic acid (8:2 FTUCA, 0.09 ± 0.00‰, n = 3) intermediates were also observed. To our knowledge, this is the first report regarding the occurrence and degradation potential of several fluoroalkylsilane substances as PFCA precursors.

Data-Driven UPLC-Orbitrap MS Analysis in Astrochemistry

Meteorites have been found to be rich and highly diverse in organic compounds. Next to previous direct infusion high resolution mass spectrometry experiments (DI-HR-MS), we present here data-driven strategies to evaluate UPLC-Orbitrap MS analyses. This allows a comprehensive mining of structural isomers extending the level of information on the molecular diversity in astrochemical materials. As a proof-of-concept study, Murchison and Allende meteorites were analyzed. Both, global organic fingerprint and specific isomer analyses are discussed. Up to 31 different isomers per molecular composition are present in Murchison suggesting the presence of ≈440,000 different compounds detected therein. By means of this time-resolving high resolution mass spectrometric method, we go one step further toward the characterization of chemical structures within complex extraterrestrial mixtures, enabling a better understanding of organic chemical evolution, from interstellar ices toward small bodies in the Solar System.

Optimization of the Data Treatment Steps of a Non-targeted LC-MS-Based Workflow for the Identification of Trace Chemical Residues in Honey

Non-targeted screening (e.g., suspected-target) is emerging as an attractive tool to investigate the occurrence of contaminants in food. The sample preparation and instrument analysis steps are known to influence the identification of analytes with non-targeted workflows, especially for complex matrices. However, for methods based on mass spectrometry, the impact of the post-analysis data treatment (e.g., feature extraction) on the capacity to correctly identify a contaminant at trace level is currently not well understood. The aim of the study was to investigate the influence of seven post-analysis data treatment parameters on the non-targeted identification of trace contaminants in honey using high-performance liquid chromatography coupled to hybrid quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS). Seven compounds reported as veterinary drugs for honeybees were applied as model compounds. Among the parameters studied, the expansion window for chromatogram extraction and the average scans included in the spectra influenced significantly the identification process results. The optimized data treatment was applied to the non-targeted screening of veterinary drugs, pesticides, and other contaminants in 55 honey samples as a proof of concept. Among the 43 compounds included in a library of honey-related compounds that was used for screening, eight compounds were tentatively identified in at least one honey sample. The tentative identity of two of these compounds (tylosin A and hydroxymethylfurfural) was further confirmed with analytical standards. Graphical Abstract.

Multi-residue quantification and screening of emerging organic micropollutants in the Belgian Part of the North Sea by use of Speedisk extraction and Q-Orbitrap HRMS

Knowledge about the occurrence of emerging organic micropollutants in the marine environment is still very limited, especially when focusing on the Belgian Part of the North Sea (BPNS). This study therefore optimized and validated a Speedisk® based SPE and LC-Q-Orbitrap HRMS method to tackle the challenge of measuring the expected ultra-trace concentrations in seawater. This method was applied to 18 samples collected at different locations in the open sea and harbor of the BPNS. Forty-eight compounds, among which several pharmaceuticals, personal care products or pesticides described in the EU Watchlist, were detected - some for the first time in seawater - at concentrations ranging up to 156 ng L^-1. Moreover, the untargeted screening potential of the newly developed HRMS method was highlighted by revealing the presence of up to 1300 unknown components in a single sample and by assigning molecular formulae to those components demonstrating high discriminative potential between samples.

Fast and facile preparation of nanostructured silicon surfaces for laser desorption/ionization mass spectrometry of small compounds

RATIONALE

Many important biological processes rely on specific biomarkers (such as metabolites, drugs, proteins or peptides, carbohydrates, lipids, ...) that need to be monitored in various fluids (blood, plasma, urine, cell cultures, tissue homogenates, …). Although mass spectrometry (MS) hyphenated to liquid chromatography (LC) is widely accepted as a 'gold-standard' method for identifying such synthetic chemicals or biological products, their robust fast sensitive detection from complex matrices still constitutes a highly challenging matter.

METHODS

In order to circumvent the constraints intrinsic to LC/MS technology in terms of prior sample treatment, analysis time and overall method development to optimize ionization efficiency affecting the detection threshold, we investigated laser desorption/ionization mass spectrometry (LDI-MS) by directly depositing the sample under study onto cheap inert nanostructures made of silicon to perform straightforward sensitive and rapid screening of targeted low mass biomarkers on a conventional MALDI platform.

RESULTS

The investigated silicon nanostructures were found to act as very efficient ion-promoting surfaces exhibiting high performance for the detection of different classes of organic compounds, including glutathione, glucose, peptides and antibiotics. Achieving such broad detection was compulsory to develop a SALDI-MS-based pre-screening tool.

CONCLUSIONS

The key contribution of the described analytical strategy consists of designing inert surfaces that are fast (minute preparation) and cheap to produce, easy to handle and able to detect small organic compounds in matrix-free LDI-MS prerequisite for biomarkers pre-screening from body fluids without the recourse of any separation step.

Targeted and non-targeted forensic profiling of black powder substitutes and gunshot residue using gradient ion chromatography - high resolution mass spectrometry (IC-HRMS)

A novel and simplified gradient IC-HRMS approach is presented in this work for forensic profiling of ionic energetic material residues, including low-order explosives and gunshot residue (GSR). This new method incorporated ethanolic eluents to facilitate direct coupling of IC and HRMS without auxiliary post-column infusion pumps that are traditionally used to assist with gas phase transfer. Ethanolic eluents also enabled better integration with an in-service protocol for direct analysis of high-order organic explosives by IC-HRMS, without requiring solvent exchange before injection. Excellent method performance was achieved, enabling both full scan qualitative and quantitative analysis, as required. In particular, linearity for 19 targeted compounds yielded R² > 0.99 across several orders of magnitude, with trace analysis possible at the low-mid pg level. Reproducibility and mass accuracies were also excellent, with peak area %RSDs <10%, t_R %RSDs <0.4% and δ_m/z < 3 ppm. The method was applied to targeted analysis of latent fingermarks and swabbed hand sweat samples to determine contact with a black-powder substitute containing nitrate, benzoate and perchlorate. When combined with principal component analysis (PCA), the effect of time since handling on recorded signals could be interpreted further in order to support forensic investigations. In a second, non-targeted application, PCA using full scan IC-HRMS data enabled classification of GSR from three different types of ammunition. An additional 20 markers of GSR were tentatively identified in silico, in addition to the 15 anions detected during targeted analysis. This new approach therefore streamlines and adds consistency and flexibility to forensic analysis of ionic energetic material. Furthermore, it also has implications for targeted, non-targeted and suspect screening applications in other fields by expanding the separation space to low molecular weight inorganic and organic anions.

Identifying Per- and Polyfluorinated Chemical Species with a Combined Targeted and Non-Targeted-Screening High-Resolution Mass Spectrometry Workflow

Historical and emerging per- and polyfluoroalkyl substances (PFASs) have garnered significant interest from the public and government agencies from the local to federal levels. The continuing evolution of PFAS chemistries presents a challenge to the environmental monitoring, where ongoing development of targeted methods necessarily lags the discovery of new chemical compounds. There is a need, therefore, to have forward-looking methodologies that can detect emerging and unexpected compounds, monitor these species over time, and resolve details of their chemical structure to enable future work in human health. To this end, non-targeted analysis by high-resolution mass spectrometry offers a broad base detection approach that can be combined with almost any sample preparation scheme and provides significant capabilities for compound identification after detection. Herein, we describe a solid-phase extraction (SPE) based sample concentration method tuned for shorter chain and more hydrophilic PFAS chemistries, such as per fluorinated ether acids and sulfonates, and describe analysis of samples prepared in this fashion in both targeted and non-targeted modes. Targeted methods provide superior quantification when reference standards are available but are intrinsically limited to expected compounds when performing analysis. In contrast, a non-targeted approach can identify the presence of unexpected compounds and provide some information about their chemical structure. Information about chemical features can be used to correlate compounds across sample locations and track abundance and occurrence over time.

Standardization procedures for real-time breath analysis by secondary electrospray ionization high-resolution mass spectrometry

Despite the attractiveness of breath analysis as a non-invasive means to retrieve relevant metabolic information, its introduction into routine clinical practice remains a challenge. Among all the different analytical techniques available to interrogate exhaled breath, secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS) offers a number of advantages (e.g., real-time, yet wide, metabolome coverage) that makes it ideal for untargeted and targeted studies. However, so far, SESI-HRMS has relied mostly on lab-built prototypes, making it difficult to standardize breath sampling and subsequent analysis, hence preventing further developments such as multi-center clinical studies. To address this issue, we present here a number of new developments. In particular, we have characterized a new SESI interface featuring real-time readout of critical exhalation parameters such as CO₂, exhalation flow rate, and exhaled volume. Four healthy subjects provided breath specimens over a period of 1 month to characterize the stability of the SESI-HRMS system. A first assessment of the repeatability of the system using a gas standard revealed a coefficient of variation (CV) of 2.9%. Three classes of aldehydes, namely 4-hydroxy-2-alkenals, 2-alkenals and 4-hydroxy-2,6-alkedienals―hypothesized to be markers of oxidative stress―were chosen as representative metabolites of interest to evaluate the repeatability and reproducibility of this breath analysis analytical platform. Median and interquartile ranges (IQRs) of CVs for CO₂, exhalation flow rate, and exhaled volume were 3.2% (1.5%), 3.1% (1.9%), and 5.0% (4.6%), respectively. Despite the high repeatability observed for these parameters, we observed a systematic decay in the signal during repeated measurements for the shorter fatty aldehydes, which eventually reached a steady state after three/four repeated exhalations. In contrast, longer fatty aldehydes showed a steady behavior, independent of the number of repeated exhalation maneuvers. We hypothesize that this highly molecule-specific and individual-independent behavior may be explained by the fact that shorter aldehydes (with higher estimated blood-to-air partition coefficients; approaching 100) mainly get exchanged in the airways of the respiratory system, whereas the longer aldehydes (with smaller estimated blood-to-air partition coefficients; approaching 10) are thought to exchange mostly in the alveoli. Exclusion of the first three exhalations from the analysis led to a median CV (IQR) of 6.7 % (5.5 %) for the said classes of aldehydes. We found that such intra-subject variability is in general much lower than inter-subject variability (median relative differences between subjects 48.2%), suggesting that the system is suitable to capture such differences. No batch effect due to sampling date was observed, overall suggesting that the intra-subject variability measured for these series of aldehydes was biological rather than technical. High correlations found among the series of aldehydes support this notion. Finally, recommendations for breath sampling and analysis for SESI-HRMS users are provided with the aim of harmonizing procedures and improving future inter-laboratory comparisons.

Untargeted LC-MS metabolomic studies of Asteraceae species to discover inhibitors of Leishmania major dihydroorotate dehydrogenase

INTRODUCTION

Interesting data about the family Asteraceae as a new source of Leishmania major dihydroorotate dehydrogenase (LmDHODH) inhibitors are presented. This key macromolecular target for parasites causing neglected diseases catalyzes the fourth reaction of the de novo pyrimidine biosynthetic pathway, which takes part in major cell functions, including DNA and RNA biosynthesis.

OBJECTIVES

We aimed to (1) determine LmDHODH inhibitor candidates, revealing the type of chemistry underlying such bioactivity, and (2) predict the inhibitory potential of extracts from new untested plant species, classifying them as active or inactive based on their LC-MS based metabolic fingerprints.

METHODS

Extracts from 150 species were screened for the inhibition of LmDHODH, and untargeted UHPLC-(ESI)-HRMS metabolomic studies were carried out in combination with in silico approaches.

RESULTS

The IC₅₀ values determined for a subset of 59 species ranged from 148 µg mL^-1 to 9.4 mg mL^-1. Dereplication of the metabolic fingerprints allowed the identification of 48 metabolites. A reliable OPLS-DA model (R² > 0.9, Q² > 0.7, RMSE_CV < 0.3) indicated the inhibitor candidates; nine of these metabolites were identified using data from isolated chemical standards, one of which-4,5-di-O-E-caffeoylquinic acid (IC₅₀ 73 µM)-was capable of inhibiting LmDHODH. The predictive OPLS model was also effective, with 60% correct predictions for the test set.

CONCLUSION

Our approach was validated for (1) the discovery of LmDHODH inhibitors or interesting starting points for the optimization of new leishmanicides from Asteraceae species and (2) the prediction of extracts from untested species, classifying them as active or inactive.

HILIC-Enabled 13C Metabolomics Strategies: Comparing Quantitative Precision and Spectral Accuracy of QTOF High- and QQQ Low-Resolution Mass Spectrometry

Dynamic ¹³C-tracer-based flux analyses of in vivo reaction networks still require a continuous development of advanced quantification methods applying state-of-the-art mass spectrometry platforms. Utilizing alkaline HILIC chromatography, we adapt strategies for a systematic quantification study in non- and ¹³C-labeled multicomponent endogenous Corynebacterium glutamicum extracts by LC-QTOF high resolution (HRMS) and LC-QQQ tandem mass spectrometry (MS/MS). Without prior derivatization, a representative cross-section of 17 central carbon and anabolic key intermediates were analyzed with high selectivity and sensitivity under optimized ESI-MS settings. In column detection limits for the absolute quantification range were between 6.8-304.7 (QQQ) and 28.7-881.5 fmol (QTOF) with comparable linearities (3-5 orders of magnitude) and enhanced precision using QQQ-MRM detection. Tailor-made preparations of uniformly (U)¹³C-labeled cultivation extracts for isotope dilution mass spectrometry enabled the accurate quantification in complex sample matrices and extended linearities without effect on method parameters. Furthermore, evaluation of metabolite-specific m+1-to-m+0 ratios (ISR_1:0) in non-labeled extracts exhibited sufficient methodical spectral accuracies with mean deviations of 3.89 ± 3.54% (QTOF) and 4.01 ± 3.01% (QQQ). Based on the excellent HILIC performance, conformity analysis of time-resolved isotopic enrichments in ¹³C-tracer experiments revealed sufficient spectral accuracy for QQQ-SIM detection. However, only QTOF-HRMS ensures determination of the full isotopologue space in complex matrices without mass interferences.

MetaboAnalystR 2.0: From Raw Spectra to Biological Insights

Global metabolomics based on high-resolution liquid chromatography mass spectrometry (LC-MS) has been increasingly employed in recent large-scale multi-omics studies. Processing and interpretation of these complex metabolomics datasets have become a key challenge in current computational metabolomics. Here, we introduce MetaboAnalystR 2.0 for comprehensive LC-MS data processing, statistical analysis, and functional interpretation. Compared to the previous version, this new release seamlessly integrates XCMS and CAMERA to support raw spectral processing and peak annotation, and also features high-performance implementations of mummichog and GSEA approaches for predictions of pathway activities. The application and utility of the MetaboAnalystR 2.0 workflow were demonstrated using a synthetic benchmark dataset and a clinical dataset. In summary, MetaboAnalystR 2.0 offers a unified and flexible workflow that enables end-to-end analysis of LC-MS metabolomics data within the open-source R environment.

Mass defect filtering for suspect screening of halogenated environmental chemicals: A case study of chlorinated organophosphate flame retardants

RATIONALE

Organophosphate flame retardants (OPFRs) are a class of flame retardants widely found in environmental and biological matrices that have been extensively studied due to their adverse health effects in humans. OPFRs are loosely bound chemicals that can detach from treated products and be released into indoor and outdoor environments, where they have the potential to further undergo transformation and degradation processes, in particular the chlorinated OPFRs (Cl-PFRs). Their detection remains a moving target for analysts, and traditional targeted mass spectrometry methods are suitable only for those compounds with authentic standards.

METHODS

Mass defect filter (MDF) is a strategy to filter molecular features using thresholds applied to the mass defect value of a target ion or molecular feature of interest. We have developed an MDF strategy for the detection and tentative identification of twelve potential Cl-PFR transformation products in a study mixture of six known Cl-PFRs using MS/MS data acquired on a high-resolution mass spectrometer. Most compounds in the Cl-PFRs family share a ClO₄ P group as a core structure, of which modification results in a significant shift in the exact masses of the resulting compounds but show only a minimal shift in their mass defects. Subsequently, the MDF strategy was employed to tentatively identify Cl-PFRs retrospectively in six human urine samples that had previously been analyzed.

RESULTS

MDF in combination with product ion filtering for the characteristic [H₂ O₃ P]⁺ and [H₄ O₄ P]⁺ ions and neutral loss filtering for the characteristic C_n H_2n-x Cl_x group resulted in revealing suspects and homologues in the Cl-PFRs family. Furthermore, the MDF of the product ions detected additional Cl-PFR-related compounds that differed significantly in the exact masses of both precursor and product ions but had minimal shift in the mass defects of product ions. The mass defect of one or more common product ions helped to detect a few Cl-PFR analogs that had not been identified by MDF of the core structure precursor ion.

CONCLUSIONS

MDF helped to detect some Cl-PFRs present in lower concentrations, which went undetected without data filters. MDF also helped to detect chromatographic peaks for Cl-PFR homologues that are likely structural analogs that resulted from impurities and/or derivatives and transformation products. The methodology was applied to demonstrate and tentatively detect known and suspect Cl-PFRs in human urine samples retrospectively.

De novo structure determination of 3-((3-aminopropyl)amino)-4-hydroxybenzoic acid, a novel and abundant metabolite in Acinetobacter baylyi ADP1

INTRODUCTION

Metabolite identification remains a major bottleneck in the understanding of metabolism. Many metabolomics studies end up with unknown compounds, leaving a landscape of metabolites and metabolic pathways to be unraveled. Therefore, identifying novel compounds within a metabolome is an entry point into the 'dark side' of metabolism.

OBJECTIVES

This work aimed at elucidating the structure of a novel metabolite that was first detected in the soil bacterium Acinetobacter baylyi ADP1 (ADP1).

METHODS

We used high resolution multi-stage tandem mass spectrometry for characterizing the metabolite within the metabolome. We purified the molecule for 1D- and 2D-NMR (¹H, ¹³C, ¹H-¹H-COSY, ¹H-¹³C-HSQC, ¹H-¹³C-HMBC and ¹H-¹⁵N-HMBC) analyses. Synthetic standards were chemically prepared from MS and NMR data interpretation.

RESULTS

We determined the de novo structure of a previously unreported metabolite: 3-((3-aminopropyl)amino)-4-hydroxybenzoic acid. The proposed structure was validated by comparison to a synthetic standard. With a concentration in the millimolar range, this compound appears as a major metabolite in ADP1, which we anticipate to participate to an unsuspected metabolic pathway. This novel metabolite was also detected in another γ-proteobacterium.

CONCLUSION

Structure elucidation of this abundant and novel metabolite in ADP1 urges to decipher its biosynthetic pathway and cellular function.

Application of metabolomics and molecular networking in investigating the chemical profile and antitrypanosomal activity of British bluebells (Hyacinthoides non-scripta)

Bulb, leaf, scape and flower samples of British bluebells (Hyacinthoides non-scripta) were collected regularly for one growth period. Methanolic extracts of freeze-dried and ground samples showed antitrypanosomal activity, giving more than 50% inhibition, for 20 out of 41 samples. High-resolution mass spectrometry was used in the dereplication of the methanolic extracts of the different plant parts. The results revealed differences in the chemical profile with bulb samples being distinctly different from all aerial parts. High molecular weight metabolites were more abundant in the flowers, shoots and leaves compared to smaller molecular weight ones in the bulbs. The anti-trypanosomal activity of the extracts was linked to the accumulation of high molecular weight compounds, which were matched with saponin glycosides, while triterpenoids and steroids occurred in the inactive extracts. Dereplication studies were employed to identify the significant metabolites via chemotaxonomic filtration and considering their previously reported bioactivities. Molecular networking was implemented to look for similarities in fragmentation patterns between the isolated saponin glycoside at m/z 1445.64 [M + formic-H]- equivalent to C64H104O33 and the putatively found active metabolite at m/z 1283.58 [M + formic-H]- corresponding to scillanoside L-1. A combination of metabolomics and bioactivity-guided approaches resulted in the isolation of a norlanostane-type saponin glycoside with antitrypanosomal activity of 98.9% inhibition at 20 µM.

HaloSeeker 1.0: A User-Friendly Software to Highlight Halogenated Chemicals in Nontargeted High-Resolution Mass Spectrometry Data Sets

In the present work, we address the issue of nontargeted screening of organohalogenated chemicals in complex matrixes. A global strategy aiming to seek halogenated signatures in full-scan high-resolution mass spectrometry (HRMS) fingerprints was developed. The resulting all-in-one user-friendly application, HaloSeeker 1.0, was developed to promote the accessibility of associated in-house bioinformatics tools to a large audience. The ergonomic web user interface avoids any interactions with the coding component while allowing interactions with the data, including peak detection (features), deconvolution, and comprehensive accompanying manual review for chemical formula assignment. HaloSeeker 1.0 was successfully applied to a marine sediment HRMS data set acquired on a liquid chromatography-heated electrospray ionization [LC-HESI(-)] Orbitrap instrument ( R = 140 000 at m/z 200). Among the 4532 detected features, 827 were paired and filtered in 165 polyhalogenated clusters. HaloSeeker was also compared to three similar tools and showed the best performances. HaloSeeker's ability to filter and investigate halogenated signals was demonstrated and illustrated by a potential homologue series with C₁₂H _xBr _yCl _zO₂ as a putative general formula.

An Organic Chemist's Guide to Electrospray Mass Spectrometric Structure Elucidation

Tandem mass spectrometry is an important tool for structure elucidation of natural and synthetic organic products. Fragmentation of odd electron ions (OE⁺) generated by electron ionization (EI) was extensively studied in the last few decades, however there are only a few systematic reviews available concerning the fragmentation of even-electron ions (EE⁺/EE⁻) produced by the currently most common ionization techniques, electrospray ionization (ESI) and atmospheric pressure chemical ionization (APCI). This review summarizes the most important features of tandem mass spectra generated by collision-induced dissociation fragmentation and presents didactic examples for the unexperienced users.

UltraMassExplorer: a browser-based application for the evaluation of high-resolution mass spectrometric data

RATIONALE

High-resolution mass spectrometry (HRMS) with high sample throughput has become an important analytical tool for the analysis of highly complex samples and data processing has become a major challenge for the user community. Evaluating direct-infusion HRMS data without automated tools for batch processing can be a time-consuming step in the analytical pipeline. Therefore, we developed a new browser-based software tool for processing HRMS data.

METHODS

The software, named UltraMassExplorer (UME), was written in the R programming language using the shiny library to build the graphical user interface. The performance of the integrated formula library search algorithm was tested using HRMS data derived from analyses of up to 50 extracts of marine dissolved organic matter.

RESULTS

The software supports the processing of lists of calibrated masses of neutral, protonated or deprotonated molecules, with masses of up to 700 Da and a mass accuracy <3 ppm. In the performance test, the number of assigned peaks per second increased with the number of submitted peaks and reached a maximum rate of 4745 assigned peaks per second.

CONCLUSIONS

UME offers a complete data evaluation pipeline comprising a fast molecular formula assignment algorithm allowing for the swift reanalysis of complete datasets, advanced filter functions and the export of data, metadata and publication-quality graphics. Unique to UME is a fast and interactive connection between data and their visual representation. UME provides a new platform enabling an increased transparency, customization, documentation and comparability of datasets.

Taxonomically Informed Scoring Enhances Confidence in Natural Products Annotation

Mass spectrometry (MS) offers unrivalled sensitivity for the metabolite profiling of complex biological matrices encountered in natural products (NP) research. The massive and complex sets of spectral data generated by such platforms require computational approaches for their interpretation. Within such approaches, computational metabolite annotation automatically links spectral data to candidate structures via a score, which is usually established between the acquired data and experimental or theoretical spectral databases (DB). This process leads to various candidate structures for each MS features. However, at this stage, obtaining high annotation confidence level remains a challenge notably due to the extensive chemodiversity of specialized metabolomes. The design of a metascore is a way to capture complementary experimental attributes and improve the annotation process. Here, we show that integrating the taxonomic position of the biological source of the analyzed samples and candidate structures enhances confidence in metabolite annotation. A script is proposed to automatically input such information at various granularity levels (species, genus, and family) and complement the score obtained between experimental spectral data and output of available computational metabolite annotation tools (ISDB-DNP, MS-Finder, Sirius). In all cases, the consideration of the taxonomic distance allowed an efficient re-ranking of the candidate structures leading to a systematic enhancement of the recall and precision rates of the tools (1.5- to 7-fold increase in the F1 score). Our results clearly demonstrate the importance of considering taxonomic information in the process of specialized metabolites annotation. This requires to access structural data systematically documented with biological origin, both for new and previously reported NPs. In this respect, the establishment of an open structural DB of specialized metabolites and their associated metadata, particularly biological sources, is timely and critical for the NP research community.

Identification of Unknown Metabolomics Mixture Compounds by Combining NMR, MS, and Cheminformatics

Metabolomics aims at the comprehensive identification of metabolites in complex mixtures to characterize the state of a biological system and elucidate their roles in biochemical pathways. For many biological samples, a large number of spectral features observed by NMR spectroscopy and mass spectrometry (MS) belong to unknowns, i.e., these features do not belong to metabolites that have been previously identified, and their spectral information is not available in databases. By combining NMR, MS, and combinatorial cheminformatics, the analysis of unknowns can be pursued in complex mixtures requiring minimal purification. This chapter describes the SUMMIT MS/NMR approach covering sample preparation, NMR and MS data collection and processing, and the identification of likely unknowns with the use of cheminformatics tools and the prediction of NMR spectral properties.