Untargeted profiling of tracer-derived metabolites using stable isotopic labeling and fast polarity-switching LC-ESI-HRMS

Stable isotope-assisted metabolite profiling reveals new insights into L-tryptophan chemotrophic metabolism of Rubrivivax benzoatilyticus

Anoxygenic photosynthetic bacteria (APB) are metabolically versatile, capable of surviving with an extended range of carbon and nitrogen sources. This group of phototrophic bacteria have remarkable metabolic plasticity in utilizing an array of organic compounds as carbon source/electron donors and nitrogen sources with sophisticated growth modes. Rubrivivax benzoatilyticus JA2 is one such photosynthetic bacterium utilizes L-tryptophan as nitrogen source under phototrophic growth mode and produces an array of indolic compounds of biotechnological significance. However, chemotrophic L-tryptophan metabolism is largely unexplored and studying L-tryptophan metabolism under chemotrophic mode would provide new insights into metabolic potential of strain JA2. In the present study, we employed stable-isotopes assisted metabolite profiling to unravel the L-tryptophan catabolism in Rubrivivax benzoatilyticus strain JA2 under chemotrophic (dark aerobic) conditions. Utilization of L-tryptophan as a nitrogen source for growth and simultaneous production of indole derivatives was observed in strain JA2. Liquid chromatography mass spectrometry (LC-MS) analysis of exo-metabolite profiling of carbon labeled L-tryptophan (¹³C₁₁) fed cultures of strain JA2 revealed at least seventy labeled metabolites. Of these, only fourteen metabolites were confirmed using standards, while sixteen were putative and forty metabolites remained unidentified. L-tryptophan chemotrophic catabolism revealed multiple catabolic pathways and distinct differential catabolism of L-tryptophan under chemotropic state as compared to photo-catabolism of L-tryptophan in strain JA2.

An optimization method for untargeted MS-based isotopic tracing investigations of metabolism

INTRODUCTION

Stable isotope tracer studies are increasingly applied to explore metabolism from the detailed analysis of tracer incorporation into metabolites. Untargeted LC/MS approaches have recently emerged and provide potent methods for expanding the dimension and complexity of the metabolic networks that can be investigated. A number of software tools have been developed to process the highly complex MS data collected in such studies; however, a method to optimize the extraction of valuable isotopic data is lacking.

OBJECTIVES

To develop and validate a method to optimize automated data processing for untargeted MS-based isotopic tracing investigations of metabolism.

METHODS

The method is based on the application of a suitable reference material to rationally perform parameter optimization throughout the complete data processing workflow. It was applied in the context of ¹³C-labelling experiments and with two different software, namely geoRge and X13CMS. It was illustrated with the study of a E. coli mutant impaired for central metabolism.

RESULTS

The optimization methodology provided significant gain in the number and quality of extracted isotopic data, independently of the software considered. Pascal triangle samples are well suited for such purpose since they allow both the identification of analytical issues and optimization of data processing at the same time.

CONCLUSION

The proposed method maximizes the biological value of untargeted MS-based isotopic tracing investigations by revealing the full metabolic information that is encoded in the labelling patterns of metabolites.

Transition metal cations catalyze 16O/18O exchange of catechol motifs with H218O

In the presence of Fe(iii) and several other cations, catechol motifs undergo rapid 16O/18O exchange with H218O under mild conditions. This opens up synthetic possibilities and may have implications for studies using H218O as a mechanistic probe.

Elucidation of xenoestrogen metabolism by non-targeted, stable isotope-assisted mass spectrometry in breast cancer cells

Environmental exposure to xenoestrogens, i.e., chemicals that imitate the hormone 17β-estradiol, has the potential to influence hormone homeostasis and action. Detailed knowledge of xenobiotic biotransformation processes in cell models is key when transferring knowledge learned from in vitro models to in vivo relevance. This study elucidated the metabolism of two naturally-occurring phyto- and mycoestrogens; namely genistein and zearalenone, in an estrogen receptor positive breast cancer cell line (MCF-7) with the aid of stable isotope-assisted metabolomics and the bioinformatic tool MetExtract II. Metabolism was studied in a time course experiment after 2 h, 6 h and 24 h incubation. Twelve and six biotransformation products of zearalenone and genistein were detected, respectively, clearly demonstrating the abundant xenobiotic biotransformation capability of the cells. Zearalenone underwent extensive phase-I metabolism resulting in α-zearalenol (α-ZEL), a molecule known to possess a significantly higher estrogenicity, and several phase-II metabolites (sulfo- and glycoconjugates) of the native compound and the major phase I metabolite α-ZEL. Moreover, potential adducts of zearalenone with a vitamin and several hydroxylated metabolites were annotated. Genistein metabolism resulted in sulfation, combined sulfation and hydroxylation, acetylation, glucuronidation and unexpectedly adduct formation with pentose- and hexose sugars. Kinetics of metabolite formation and subsequent excretion into the extracellular medium revealed a time-dependent increase in most biotransformation products. The untargeted elucidation of biotransformation products formed during cell culture experiments enables an improved and more meaningful interpretation of toxicological assays and has the potential to identify unexpected or unknown metabolites.

Characterization of the PRODUCTION of ANTHOCYANIN PIGMENT 1 Arabidopsis dominant mutant using DLEMMA dual isotope labeling approach

Stable isotope labeling has emerged as a valuable tool for metabolite identification and quantification. In this study, we employed DLEMMA, a dual stable isotope labeling approach to identify and track phenylpropanoid pathway in Arabidopsis thaliana. Three forms of phenylalanine (Phe), including unlabeled, Phe¹³C₆ and Phe¹³C₆²H_5, were used as feeding precursors. The unique isotopic pattern obtained from MS spectra significantly simplified data processing and facilitated global mining of Phe-derived metabolites. Following this approach, we have identified 35 phenylalanine-derived metabolites with high confidence. We next compared phenylpropanoids contents between leaves of wild type (WT) and the dominant PRODUCTION OF ANTHOCYANIN PIGMENT 1 (pap1-D) Arabidopsis thaliana mutant using a combined sample matrices and label-swap approach. This approach was designed to correct any unequal matrix effects between the two divergent samples, and any possible uneven label incorporation efficiency between the two differently labeled Phe precursors. Thirty of the 35 identified metabolites were found differential between WT and pap1-D leaves. Our results shown that the ectopic PAP1 expression led to significant accumulation of cyanidin-type anthocyanins, quercetin-type flavonols and hydroxycinnamic acids and their glycosylated derivatives. While levels of kaempferol glycosides and a hydroxycinnamic acid amide were reduced in the pap1-D leaves.

Metabolic Profiling by UPLC-Orbitrap-MS/MS of Liver from C57BL/6 Mice with DSS-Induced Inflammatory Bowel Disease

Liver disorder often occurs in patients with inflammatory bowel disease (IBD); however, the changes in IBD-induced liver disorder at the intrinsic molecular level (chiefly metabolites) and therapeutic targets are still poorly characterized. First, a refined and translationally relevant model of DSS chronic colitis in C57BL/6 mice was established, and cecropin A and antibiotics were used as interventions. We found that the levels of tumor necrosis factor (TNF)-α, interleukin (IL)-1β, and IL-6 in the liver tissues of mice were highly increased in the context of DSS treatment but were lowered by cecropin A and antibiotics. Subsequently, an untargeted metabolomics analysis was performed by UPLC–Orbitrap–MS/MS to reveal the metabolic profile and attempt to find the potential therapeutic targets of the liver disorders that occur in IBD. Notably, 133 metabolites were identified by an integrated database. Metabolism network and pathway analyses demonstrated that the metabolic disturbance of the liver in IBD mice was mainly enriched in bile acid metabolism, arachidonic acid metabolism, amino acid metabolism, and steroid hormone biosynthesis, while those disturbances were regulated or reversed through cecropin A and antibiotic treatment. Furthermore, the top 20 metabolites, such as glutathione, maltose, arachidonic acid, and thiamine, were screened as biomarkers via one-way analysis of variance (one-way ANOVA, p < 0.05) coupled with variable importance for project values (VIP >1) of orthogonal partial least-squares discriminant analysis (OPLS-DA), which could be upregulated or downregulated with the cecropin A and antibiotics treatment. Spearman correlation analysis showed that the majority of the biomarkers have a significant correlation with cytokines (TNF-α, IL-1β, IL-6, and IL-10), indicating that those biomarkers may act as potential targets to interact directly or indirectly with cecropin A and antibiotics to affect liver inflammation. Collectively, our results extend the understanding of the molecular alteration of liver disorders occurring in IBD and offer an opportunity for discovering potential therapeutic targets in the IBD process.

Metabolism of a Bioorthogonal PET Tracer Candidate [19F/18F]SiFA-Tetrazine in Mouse Liver Microsomes: Biotransformation Pathways and Defluorination Investigated by UHPLC-HRMS

Organofluorosilicon based ¹⁸F-radiolabeling is an efficient method for incorporating fluorine-18 into ¹⁸F-radiopharmaceuticals for positron emission tomography (PET) by ¹⁹F/¹⁸F isotopic exchange (IE). The first PET radiopharmaceutical, ¹⁸F-SiFAlin-TATE, radiolabeled with a silicon-based [¹⁸F]fluoride acceptor (SiFA), namely, a para-substituted di-tert-butyl[¹⁸F]fluorosilylbenzene, has entered clinical trials, and is paving the way for other potential [¹⁸F]SiFA-labeled radiopharmaceuticals for diagnostic use. In this study, we report the in vitro metabolism of an oxime-linked SiFA tetrazine (SiFA–Tz), a new PET-radiotracer candidate, recently evaluated for pretargeted PET imaging and macromolecule labeling. Metabolism of SiFA–Tz was studied in mouse liver microsomes (MLM) for elucidating its major biotransformation pathways. Nontargeted screening by ultrahigh performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) was utilized for detection of unknown metabolites. The oxime bond between the SiFA and Tz groups forms two geometric (E/Z) isomers, which underwent the same biotransformations, but unexpectedly with different kinetics. In total, nine proposed metabolites of SiFA–Tz from phase I and II reactions were detected, five of which were defluorinated in MLMs, elucidating the metabolic pathway leading to previously reported defluorination of [¹⁸F]SiFA–Tz in vivo. Based on the HRMS studies a biotransformation pathway is proposed: hydroxylation (+O) to tert-butyl group adjacent to the silicon, followed by oxidative defluorination (+OH/-F) cleaving the fluorine off the silicon. Interestingly, eight proposed metabolites of a reduced dihydrotetrazine analogue, SiFA–H₂Tz, from phase I and II reactions were additionally detected. To the best of our knowledge, this is the first reported comprehensive investigation of enzyme mediated metabolic pathway of tetrazines and para-substituted di-tert-butylfluorosilylbenzene fluoride acceptors, providing novel structural information on the biotransformation and fragmentation patterns of radiotracers bearing these structural motifs. By investigating the metabolism preceding defluorination, structurally optimized new SiFA compounds can be designed for expanding the portfolio of efficient ¹⁹F/¹⁸F isotopic exchange labeling probes for PET imaging.

Novel analytical methods to study the fate of mycotoxins during thermal food processing

Food processing can lead to a reduction of contaminants, such as mycotoxins. However, for food processing operations where thermal energy is employed, it is often not clear whether a reduction of mycotoxins also results in a mitigation of the toxicological impact. This is often due to the reason that the formed degradation products are not characterized and data on their toxicity is scarce. From the perspective of an analytical chemist, the elucidation of the fate of a contaminant in a complex food matrix is extremely challenging. An overview of the analytical approaches is given here, and the application and limitations are exemplified based on cases that can be found in recent literature. As most studies rely on targeted analysis, it is not clear whether the predetermined set of compounds differs from the degradation products that are actually formed during food processing. Although untargeted analysis allows for the elucidation of the complete spectrum of degradation products, only one such study is available so far. Further pitfalls include insufficient precision, natural contamination with masked forms of mycotoxins and interferences that are caused by the food matrix. One topic that is of paramount importance for both targeted and untargeted approaches is the availability of reference standards to identity and quantity the formed degradation products. Our vision is that more studies need to be published that characterize the formed degradation products, collect data on their toxicity and thereby complete the knowledge about the mycotoxin mitigating effect during food processing.

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.

Characterization of Phase I and Glucuronide Phase II Metabolites of 17 Mycotoxins Using Liquid Chromatography-High-Resolution Mass Spectrometry

Routine mycotoxin biomonitoring methods do not include many mycotoxin phase I and phase II metabolites, which may significantly underestimate mycotoxin exposure especially for heavily metabolized mycotoxins. Additional research efforts are also needed to measure metabolites in vivo after exposure and to establish which mycotoxin metabolites should be prioritized for the inclusion during large-scale biomonitoring efforts. The objective of this study was to perform human in vitro microsomal incubations of 17 mycotoxins and systematically characterize all resulting metabolites using liquid chromatography-high-resolution mass spectrometry (LC-HRMS). The results obtained were then used to build a comprehensive LC-MS library and expand a validated 17-mycotoxin method for exposure monitoring to screening of additional 188 metabolites, including 100 metabolites reported for the first time. The final method represents one of the most comprehensive LC-HRMS methods for mycotoxin biomonitoring or metabolism/fate studies.

Profiling the Metabolism of Human Cells by Deep 13C Labeling

Studying metabolic activities in living cells is crucial for understanding human metabolism, but facile methods for profiling metabolic activities in an unbiased, hypothesis-free manner are still lacking. To address this need, we here introduce the deep-labeling method, which combines a custom ¹³C medium with high-resolution mass spectrometry. A proof-of-principle study on human cancer cells demonstrates that deep labeling can identify hundreds of endogenous metabolites as well as active and inactive pathways. For example, protein and nucleic acids were almost exclusively de novo synthesized, while lipids were partly derived from serum; synthesis of cysteine, carnitine, and creatine was absent, suggesting metabolic dependencies; and branched-chain keto acids (BCKAs) were formed and metabolized to short-chain acylcarnitines, but did not enter the tricarboxylic acid cycle. Remarkably, BCKAs could substitute for essential amino acids to support growth. The deep-labeling method may prove useful to map metabolic phenotypes across a range of cell types and conditions.

HPLC-high-resolution mass spectrometry with polarity switching for increasing throughput of human in vitro cocktail drug-drug interaction assay

AIM

Evaluation of HPLC-high-resolution mass spectrometry (HPLC-HRMS) full scan with polarity switching for increasing throughput of human in vitro cocktail drug-drug interaction assay.

MATERIALS & METHODS

Microsomal incubates were analyzed using a high resolution and high mass accuracy Q-Exactive mass spectrometer to collect integrated qualitative and quantitative (qual/quant) data.

RESULTS

Within assay, positive-to-negative polarity switching HPLC-HRMS method allowed quantification of eight and two probe compounds in the positive and negative ionization modes, respectively, while monitoring for LOR and its metabolites.

CONCLUSION

LOR-inhibited CYP2C19 and showed higher activity for CYP2D6, CYP2E1 and CYP3A4. Overall, LC-HRMS-based nontargeted full scan quantitation allowed to improve the throughput of the in vitro cocktail drug-drug interaction assay.

Tracing the Biotransformation of Polycyclic Aromatic Hydrocarbons in Contaminated Soil Using Stable Isotope-Assisted Metabolomics

Biotransformation of organic pollutants may result in the formation of oxidation products more toxic than the parent contaminants. However, to trace and identify those products, and the metabolic pathways involved in their formation, is still challenging within complex environmental samples. We applied stable isotope-assisted metabolomics (SIAM) to PAH-contaminated soil collected from a wood treatment facility. Soil samples were separately spiked with uniformly ¹³C-labeled fluoranthene, pyrene, or benzo[a]anthracene at a level below that of the native contaminant, and incubated for 1 or 2 weeks under aerobic biostimulated conditions. Combining high-resolution mass spectrometry and automated SIAM workflows, chemical structures of metabolites and metabolic pathways in the soil were proposed. Ring-cleavage products, including previously unreported intermediates such as C₁₁H₁₀O₆ and C₁₅H₁₂O₅, were detected originating from fluoranthene and benzo[a]anthracene, respectively. Sulfate conjugates of dihydroxy compounds were found as major metabolites of pyrene and benzo[a]anthracene, suggesting the potential role of fungi in their biotransformation in soils. A series of unknown N-containing metabolites were identified from pyrene, but their structural elucidation requires further investigation. Our results suggest that SIAM can be successfully applied to understand the fate of organic pollutants in environmental samples, opening lines of evidence for novel mechanisms of microbial transformation within such complex matrices.

Stable Isotope-Assisted Metabolic Profiling Reveals Growth Mode Dependent Differential Metabolism and Multiple Catabolic Pathways of l-Phenylalanine in Rubrivivax benzoatilyticus JA2

Anoxygenic phototrophic bacteria are metabolically versatile and survive under different growth modes using diverse organic compounds, yet their metabolic diversity is largely unexplored. In the present study, we employed stable-isotope-assisted metabolic profiling to unravel the l-phenylalanine catabolism in Rubrivivax benzoatilyticus JA2 under varying growth modes. Strain JA2 grows under anaerobic and aerobic conditions by utilizing l-phenylalanine as a nitrogen source. Furthermore, ring-labeled ¹³C₆-phenylalanine feeding followed by liquid chromatography-mass spectrometry exometabolite profiling revealed 60 labeled metabolic features (M + 6, M + 12, and M + 18) derived solely from l-phenylalanine, of which 11 were identified, 7 putatively identified, and 42 unidentified under anaerobic and aerobic conditions. However, labeled metabolites were significantly higher in aerobic compared to anaerobic conditions. Furthermore, detected metabolites and enzyme activities indicated multiple l-phenylalanine catabolic routes mainly Ehrlich, homogentisate-dependent melanin, benzenoid, and unidentified pathways operating under anaerobic and aerobic conditions in strain JA2. Interestingly, the study indicated l-phenylalanine-dependent and independent benzenoid biosynthesis in strain JA2 and a differential flux of l-phenylalanine to Ehrlich and benzenoid pathways under anaerobic and aerobic conditions. Additionally, unidentified labeled metabolites strongly suggest the presence of unknown phenylalanine catabolic routes in strain JA2. Overall, the study uncovered the l-phenylalanine catabolic diversity in strain JA2 and demonstrated the potential of stable isotope-assisted metabolomics in unraveling the hidden metabolic repertoire.

MetExtract II: A Software Suite for Stable Isotope-Assisted Untargeted Metabolomics

Stable isotope labeling (SIL) techniques have the potential to enhance different aspects of liquid chromatography–high-resolution mass spectrometry (LC-HRMS)-based untargeted metabolomics methods including metabolite detection, annotation of unknown metabolites, and comparative quantification. In this work, we present MetExtract II, a software toolbox for detection of biologically derived compounds. It exploits SIL-specific isotope patterns and elution profiles in LC-HRMS(/MS) data. The toolbox consists of three complementary modules: M1 (AllExtract) uses mixtures of uniformly highly isotope-enriched and native biological samples for selective detection of the entire accessible metabolome. M2 (TracExtract) is particularly suited to probe the metabolism of endogenous or exogenous secondary metabolites and facilitates the untargeted screening of tracer derivatives from concurrently metabolized native and uniformly labeled tracer substances. With M3 (FragExtract), tandem mass spectrometry (MS/MS) fragments of corresponding native and uniformly labeled ions are evaluated and automatically assigned with putative sum formulas. Generated results can be graphically illustrated and exported as a comprehensive data matrix that contains all detected pairs of native and labeled metabolite ions that can be used for database queries, metabolome-wide internal standardization, and statistical analysis. The software, associated documentation, and sample data sets are freely available for noncommercial use at http://metabolomics-ifa.boku.ac.at/metextractII.

Development of a Data-Independent Targeted Metabolomics Method for Relative Quantification Using Liquid Chromatography Coupled with Tandem Mass Spectrometry

Quantitative metabolomics approaches can significantly improve the repeatability and reliability of metabolomics investigations but face critical technical challenges, owing to the vast number of unknown endogenous metabolites and the lack of authentic standards. The present study contributes to the development of a novel method known as "data-independent targeted quantitative metabolomics" (DITQM), which was used to investigate the label-free quantitative metabolomics of multiple known and unknown metabolites in biofluid samples. This approach initially involved the acquisition of MS/MS data for all metabolites in biosamples using a sequentially stepped targeted MS/MS (sst-MS/MS) method, in which multiple product ion scans were performed by selecting all ions in the targeted mass ranges as the precursor ions. Subsequently, scheduled multiple reaction monitoring (MRM) by LC-MS/MS of the metabolome was established for 1658 characteristic ion pairs of 1324 metabolites. For sensitive and accurate quantification of these metabolites, mixed calibration curves were generated using sequentially diluted standard reference plasma samples using established MRM methods. Relative concentrations of all metabolites in each sample were calculated without using individual authentic standards. To evaluate the reliability and applicability of this new method, the performance of DITQM was validated by comparison to absolute quantification of 12 acylcarnitines using authentic standards and traditional metabolomics analysis for lung cancer. The results proved that the DITQM protocol is more reliable and can significantly improve clustering effects and repeatability in biomarker discovery. In this study, we established a novel methodology to standardize and quantify large-scale metabolome, providing a new choice for metabolomics research and its clinical applications.

Nontargeted Identification of Reactive Metabolite Protein Adducts

Metabolic bioactivation of many different chemicals results in the formation of highly reactive compounds (chemically reactive metabolites, CRMs) that can lead to toxicity via binding to macromolecular targets (e.g., proteins or DNA). There is a need to develop robust, rapid, and nontargeted analytical techniques to determine the identity of the protein targets of CRMs and their sites of modification. Here, we introduce a nontargeted methodology capable of determining both the identity of a CRM formed from an administered compound as well as the protein targets modified by the reactive metabolite in a single experiment without prior information. Acetaminophen (N-acetyl-p-aminophenol, APAP) and ¹³C₆-APAP were incubated with rat liver microsomes, which are known to bioactivate APAP to the reactive metabolite N-acetyl-p-benzoquinone imine (NAPQI). Global tryptic digestion followed by liquid chromatographic/mass spectrometric (LC/MS) analysis was used to locate "twin" ion peaks of peptides adducted by NAPQI and for shotgun proteomics via tandem mass spectrometry (MS/MS). By the development of blended data analytics software called Xenophile, the identity of the amino acid residue that was adducted can be established, which eliminates the need for specific parametrization of protein database search algorithms. This combination of experimental design and data analysis software allows the identity of a CRM, the protein target, and the amino acid residues that are modified to be rapidly established directly from experimental data. Xenophile is freely available from https://github.com/mgleeming/Xenophile .

Novel sulphur-containing imatinib metabolites found by untargeted LC-HRMS analysis

Untargeted metabolite profiling using high-resolution mass spectrometry coupled with liquid chromatography (LC-HRMS), followed by data analysis with the Compound Discoverer 2.0™ software, was used to study the metabolism of imatinib in humans with chronic myeloid leukemia. Plasma samples from control (drug-free) and patient (treated with imatinib) groups were analyzed in full-scan mode and the unknown ions occurring only in the patient group were then, as potential imatinib metabolites, subjected to multi-stage fragmentation in order to elucidate their structure. The application of an untargeted approach, as described in this study, enabled the detection of 24 novel structurally unexpected metabolites. Several sulphur-containing compounds, probably originating after the reaction of reactive intermediates of imatinib with endogenous glutathione, were found and annotated as cysteine and cystine adducts. In the proposed mechanism, the cysteine adducts were formed after the rearrangement of piperazine moiety to imidazoline. On the contrary, in vivo S-N exchange occurred in the case of the cystine adducts. In addition, N-O exchange was observed in the collision cell in the course of the fragmentation of the cystine adducts. The presence of sulphur in the cysteine and cystine conjugates was proved by means of ultra-high resolution measurements using Orbitrap Elite. The detection of metabolites derived from glutathione might improve knowledge about the disposition of imatinib towards bioactivation and help to improve understanding of the mechanism of its hepatotoxicity or nephrotoxicity in humans.

A relative quantitative positive/negative ion switching method for untargeted lipidomics via high resolution LC-MS/MS from any biological source

INTRODUCTION

Advances in high-resolution mass spectrometry have created renewed interest for studying global lipid biochemistry in disease and biological systems.

OBJECTIVES

Here, we present an untargeted 30 min. LC-MS/MS platform that utilizes positive/negative polarity switching to perform unbiased data dependent acquisitions (DDA) via higher energy collisional dissociation (HCD) fragmentation to profile more than 1000-1500 lipid ions mainly from methyl-tert-butyl ether (MTBE) or chloroform:methanol extractions.

METHODS

The platform uses C18 reversed-phase chromatography coupled to a hybrid QExactive Plus/HF Orbitrap mass spectrometer and the entire procedure takes ~10 h from lipid extraction to identification/quantification for a data set containing 12 samples (~4 h for a single sample). Lipids are identified by both accurate precursor ion mass and fragmentation features and quantified using Lipid-Search and Elements software.

RESULTS

Using this approach, we are able to profile intact lipid ions from up to 18 different main lipid classes and 66 subclasses. We show several studies from different biological sources, including cultured cancer cells, resected tissues from mice such as lung and breast tumors and biological fluids such as plasma and urine.

CONCLUSIONS

Using mouse embryonic fibroblasts, we showed that TSC2-/- KD significantly abrogates lipid biosynthesis and that rapamycin can rescue triglyceride (TG) lipids and we show that SREBP-/- shuts down lipid biosynthesis significantly via mTORC1 signaling pathways. We show that in mouse EGFR driven lung tumors, a large number of TGs and phosphatidylmethanol (PMe) lipids are elevated while some phospholipids (PLs) show some of the largest decrease in lipid levels from ~ 2000 identified lipid ions. In addition, we identified more than 1500 unique lipid species from human blood plasma.

Metabolism of HT-2 Toxin and T-2 Toxin in Oats

The Fusarium mycotoxins HT-2 toxin (HT2) and T-2 toxin (T2) are frequent contaminants in oats. These toxins, but also their plant metabolites, may contribute to toxicological effects. This work describes the use of ¹³C-assisted liquid chromatography-high-resolution mass spectrometry for the first comprehensive study on the biotransformation of HT2 and T2 in oats. Using this approach, 16 HT2 and 17 T2 metabolites were annotated including novel glycosylated and hydroxylated forms of the toxins, hydrolysis products, and conjugates with acetic acid, putative malic acid, malonic acid, and ferulic acid. Further targeted quantitative analysis was performed to study toxin metabolism over time, as well as toxin and conjugate mobility within non-treated plant tissues. As a result, HT2-3-O-β-d-glucoside was identified as the major detoxification product of both parent toxins, which was rapidly formed (to an extent of 74% in HT2-treated and 48% in T2-treated oats within one day after treatment) and further metabolised. Mobility of the parent toxins appeared to be negligible, while HT2-3-O-β-d-glucoside was partly transported (up to approximately 4%) through panicle side branches and stem. Our findings demonstrate that the presented combination of untargeted and targeted analysis is well suited for the comprehensive elucidation of mycotoxin metabolism in plants.

MetMatch: A Semi-Automated Software Tool for the Comparison and Alignment of LC-HRMS Data from Different Metabolomics Experiments

Due to its unsurpassed sensitivity and selectivity, LC-HRMS is one of the major analytical techniques in metabolomics research. However, limited stability of experimental and instrument parameters may cause shifts and drifts of retention time and mass accuracy or the formation of different ion species, thus complicating conclusive interpretation of the raw data, especially when generated in different analytical batches. Here, a novel software tool for the semi-automated alignment of different measurement sequences is presented. The tool is implemented in the Java programming language, it features an intuitive user interface and its main goal is to facilitate the comparison of data obtained from different metabolomics experiments. Based on a feature list (i.e., processed LC-HRMS chromatograms with mass-to-charge ratio (m/z) values and retention times) that serves as a reference, the tool recognizes both m/z and retention time shifts of single or multiple analytical datafiles/batches of interest. MetMatch is also designed to account for differently formed ion species of detected metabolites. Corresponding ions and metabolites are matched and chromatographic peak areas, m/z values and retention times are combined into a single data matrix. The convenient user interface allows for easy manipulation of processing results and graphical illustration of the raw data as well as the automatically matched ions and metabolites. The software tool is exemplified with LC-HRMS data from untargeted metabolomics experiments investigating phenylalanine-derived metabolites in wheat and T-2 toxin/HT-2 toxin detoxification products in barley.

Time is ripe: maturation of metabolomics in chronobiology

Sleep and circadian rhythms studies have recently benefited from metabolomics analyses, uncovering new connections between chronobiology and metabolism. From untargeted mass spectrometry to quantitative nuclear magnetic resonance spectroscopy, a diversity of analytical approaches has been applied for biomarker discovery in the field. In this review we consider advances in the application of metabolomics technologies which have uncovered significant effects of sleep and circadian cycles on several metabolites, namely phosphatidylcholine species, medium-chain carnitines, and aromatic amino acids. Study design and data processing measures essential for detecting rhythmicity in metabolomics data are also discussed. Future developments in these technologies are anticipated vis-à-vis validating early findings, given metabolomics has only recently entered the ring with other systems biology assessments in chronometabolism studies.

Metabolomics: Bridging the Gap between Pharmaceutical Development and Population Health

Metabolomics has emerged as an essential tool for studying metabolic processes, stratification of patients, as well as illuminating the fundamental metabolic alterations in disease onset, progression, or response to therapeutic intervention. Metabolomics materialized within the pharmaceutical industry as a standalone assay in toxicology and disease pathology and eventually evolved towards aiding in drug discovery and pre-clinical studies via supporting pharmacokinetic and pharmacodynamic characterization of a drug or a candidate. Recent progress in the field is illustrated by coining of the new term—Pharmacometabolomics. Integration of data from metabolomics with large-scale omics along with clinical, molecular, environmental and behavioral analysis has demonstrated the enhanced utility of deconstructing the complexity of health, disease, and pharmaceutical intervention(s), which further highlight it as an essential component of systems medicine. This review presents the current state and trend of metabolomics applications in pharmaceutical development, and highlights the importance and potential of clinical metabolomics as an essential part of multi-omics protocols that are directed towards shaping precision medicine and population health.

Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics

Metabolomics, along with other "omics" approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.

Investigation of signaling molecules and metabolites found in crustacean hemolymph via in vivo microdialysis using a multifaceted mass spectrometric platform

Neurotransmitters (NTs) are endogenous signaling molecules that play an important role in regulating various physiological processes in animals. Detection of these chemical messengers is often challenging due to their low concentration levels and fast degradation rate in vitro. In order to address these challenges, herein we employed in vivo microdialysis (MD) sampling to study NTs in the crustacean model Cancer borealis. Multifaceted separation tools, such as CE and ion mobility mass spectrometry (MS) were utilized in this work. Small molecules were separated by different mechanisms and detected by MALDI mass spectrometric imaging (MALDI-MSI). Performance of this separation-based MSI platform was also compared to LC-ESI-MS. By utilizing both MALDI and ESI-MS, a total of 208 small molecule NTs and metabolites were identified, of which 39 were identified as signaling molecules secreted in vivo. In addition, the inherent property of sub microscale sample consumption using CE enables shorter time of MD sample collection. Temporal resolution of MD was improved by approximately tenfold compared to LC-ESI-MS, indicating the significant advantage of applying separation-assisted MALDI-MS imaging platform.

Developments in mycotoxin analysis: an update for 2014-2015

This review summarises developments in the determination of mycotoxins over a period between mid-2014 and mid-2015. In tradition with previous articles of this series, analytical methods to determine aflatoxins, Alternaria toxins, ergot alkaloids, fumonisins, ochratoxins, patulin, trichothecenes and zearalenone are covered in individual sections. Advances in proper sampling strategies are discussed in a dedicated section, as are new methods used to analyse botanicals and spices and newly developed LC-MS based multi-mycotoxin methods. The critical review aims to briefly discuss the most important developments and trends in mycotoxin determination as well as to address shortcomings of current methodologies.

Hydrolysis mechanism of methyl parathion evidenced by Q-Exactive mass spectrometry

Organophosphorus pesticides (OPPs), a kind of widely used pesticides, are currently attracting great attention due to their adverse effects on human central nervous systems, particularly in children. Although the hydrolysis behavior of OPPs has been studied well, its hydrolysis mechanism remained controversial, especially at various pH conditions, partly due to their relatively complex structures and abundant moieties that were prone to be attacked by nucleophiles. The Q-Exactive mass spectrometer, part of those hybrid high-resolution mass spectrometers (HRMS), was used to determine hydrolysis products of methyl parathion (MP), a kind of OPPs in situ buffer aqueous solution with pH ranging from 1 to 13 in this study. Most of the complex hydrolysis products of MP were identified due to the high sensitivity and accuracy of HRMS. The results demonstrated that the hydrolysis rate and pathway of MP were strong pH dependent. With the increase of pH, the hydrolysis rate of MP increased, and two different reaction mechanisms were identified: SN (2)@P pathway dominated the hydrolysis process at high pH (e.g., pH ≥ 11) while SN (2)@C was the main behavior at low pH (e.g., pH ≤ 9). This study helps understand the hydrolysis mechanism of OPPs at various pH and extends the use of Q-Exactive mass spectrometry in identifying organic pollutants and their degradation products in environmental matrices.

Tracing the metabolism of HT-2 toxin and T-2 toxin in barley by isotope-assisted untargeted screening and quantitative LC-HRMS analysis

An extensive study of the metabolism of the type A trichothecene mycotoxins HT-2 toxin and T-2 toxin in barley using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) is reported. A recently developed untargeted approach based on stable isotopic labelling, LC-Orbitrap-MS analysis with fast polarity switching and data processing by MetExtract software was combined with targeted LC-Q-TOF-MS(/MS) analysis for metabolite structure elucidation and quantification. In total, 9 HT-2 toxin and 13 T-2 toxin metabolites plus tentative isomers were detected, which were successfully annotated by calculation of elemental formulas and further LC-HRMS/MS measurements as well as partly identified with authentic standards. As a result, glucosylated forms of the toxins, malonylglucosides, and acetyl and feruloyl conjugates were elucidated. Additionally, time courses of metabolite formation and mass balances were established. For absolute quantification of those compounds for which standards were available, the method was validated by determining apparent recovery, signal suppression, or enhancement and extraction recovery. Most importantly, T-2 toxin was rapidly metabolised to HT-2 toxin and for both parent toxins HT-2 toxin-3-O-β-glucoside was identified (confirmed by authentic standard) as the main metabolite, which reached its maximum already 1 day after toxin treatment. Graphical Abstract Isotope-assisted untargeted screening of HT-2 toxin and T-2 toxin metabolites in barley.

Metabolism of the Fusarium Mycotoxins T-2 Toxin and HT-2 Toxin in Wheat

To investigate the metabolic fate of HT-2 toxin (HT2) and T-2 toxin (T2) in wheat (Triticum aestivum L.), an untargeted metabolomics study utilizing stable isotopic labeling and liquid chromatography-high resolution mass spectrometry was performed. In total, 11 HT2 and 12 T2 derived in planta biotransformation products were annotated putatively. In addition to previously reported mono- and diglucosylated forms of HT2, evidence for the formation of HT2-malonyl-glucoside and feruloyl-T2, as well as acetylation and deacetylation products in wheat was obtained for the first time. To monitor the kinetics of metabolite formation, a time course experiment was conducted involving the Fusarium head blight susceptible variety Remus and the resistant cultivar CM-82036. Biotransformation reactions were observed already at the earliest tested time point (6 h after treatment), and formed metabolites showed different kinetic profiles. After ripening, less than 15% of the toxins added to the plants were determined to be unmetabolized.

High-resolution twin-ion metabolite extraction (HiTIME) mass spectrometry: nontargeted detection of unknown drug metabolites by isotope labeling, liquid chromatography mass spectrometry, and automated high-performance computing

The metabolic fate of a compound can often determine the success of a new drug lead. Thus, significant effort is directed toward identifying the metabolites formed from a given molecule. Here, an automated and nontargeted procedure is introduced for detecting drug metabolites without authentic metabolite standards via the use of stable isotope labeling, liquid chromatography mass spectrometry (LC/MS), and high-performance computing. LC/MS of blood plasma extracts from rats that were administered a 1:1 mixture of acetaminophen (APAP) and (13)C6-APAP resulted in mass spectra that contained "twin" ions for drug metabolites that were not detected in control spectra (i.e., no APAP administered). Because of the development of a program (high-resolution twin-ion metabolite extraction; HiTIME) that can identify twin-ions in high-resolution mass spectra without centroiding (i.e., reduction of mass spectral peaks to single data points), 9 doublets corresponding to APAP metabolites were identified. This is nearly twice that obtained by use of existing programs that make use of centroiding to reduce computational cost under these conditions with a quadrupole time-of-flight mass spectrometer. By a manual search for all reported APAP metabolite ions, no additional twin-ion signals were assigned. These data indicate that all the major metabolites of APAP and multiple low-abundance metabolites (e.g., acetaminophen hydroxy- and methoxysulfate) that are rarely reported were detected. This methodology can be used to detect drug metabolites without prior knowledge of their identity. HiTIME is freely available from https://github.com/bjpop/HiTIME .