Mass Spectra Of Metabolites Research Articles

Reusability report: Annotating metabolite mass spectra with domain-inspired chemical formula transformers

Reusability report: Annotating metabolite mass spectra with domain-inspired chemical formula transformers

Annotating metabolite mass spectra with domain-inspired chemical formula transformers

Annotating metabolite mass spectra with domain-inspired chemical formula transformers

A preliminary metabolites identification of a novel compound with \u03b2-adrenolytic activity

BackgroundThe identification of main metabolites and assessment of renal excretion of a novel compound with β-adrenolytic activity (2RS)-1-(1H-indol-4-yloxy)-3-((2-(2-methoxyphenoxy)ethyl)amino)propan-2-ol, briefly called (RS)-9 or 2F109, were studied in vivo in rat serum, urine, faeces, liver, intestine, lungs and kidneys, and in vitro in rat liver microsomes.MethodsStructures of the metabolites have been developed by comparing the high-resolution product ion mass spectra of metabolites and the parent compound based on the differences in mass values of main fragments. Quantitative analysis of (RS)-9 was done using a system of liquid chromatography coupled with a triple quadrupole mass spectrometer API 2000. Identification studies of predicted metabolites were made by a high-resolution mass spectrometer LTQ XL Orbitrap Discovery and using a Roxy™ system, for online electrochemical mimicry of oxidative metabolism by cytochrome P450s connected to QTRAP 5500.ResultsFor (RS)-9 (m/z 357.2084) phase I metabolites derived from oxidation process: hydroxyl derivatives (m/z 373.2470) and dihydroxyl derivatives (m/z 389.4318), and phase II metabolites: N-methylated compound (m/z 371.1612), O-glucuronide (m/z 533.5118), and sulfate (m/z 437.2350) were identified.Conclusion(RS)-9 was extensively metabolised to several phase I and II metabolites, and renal excretion was a minor route in its elimination.Graphic abstract

The application of rapid evaporative ionization mass spectrometry in the analysis of Drosophila species-a potential new tool in entomology.

There is increasing emphasis on the use of new analytical approaches in subject analysis and classification, particularly in respect to minimal sample preparation. Here, we demonstrate that rapid evaporative ionization mass spectrometry (REIMS), a method that captures metabolite mass spectra after rapid combustive degradation of an intact biological specimen, generates informative mass spectra from several arthropods, and more specifically, is capable of discerning differences between species and sex of several adult Drosophila species. A model including five Drosophila species, built using pattern recognition, achieves high correct classification rates (over 90%) using test datasets and is able to resolve closely related species. The ease of discrimination of male and female specimens also demonstrates that sex-specific differences reside in the REIMS metabolite patterns, whether analysed across all five species or specifically for D. melanogaster. Further, the same approach can correctly discriminate and assign Drosophila species at the larval stage, where these are morphologically highly similar or identical. REIMS offers a novel approach to insect typing and analysis, requiring a few seconds of data acquisition per sample and has considerable potential as a new tool for the field biologist.

Adduct annotation in liquid chromatography/high-resolution mass spectrometry to enhance compound identification

Annotation and interpretation of full scan electrospray mass spectra of metabolites is complicated by the presence of a wide variety of ions. Not only protonated, deprotonated, and neutral loss ions but also sodium, potassium, and ammonium adducts as well as oligomers are frequently observed. This diversity challenges automatic annotation and is often poorly addressed by current annotation tools. In many cases, annotation is integrated in metabolomics workflows and is based on specific chromatographic peak-picking tools. We introduce mzAdan, a nonchromatography-based multipurpose standalone application that was developed for the annotation and exploration of convolved high-resolution ESI-MS spectra. The tool annotates single or multiple accurate mass spectra using a customizable adduct annotation list and outputs a list of [M+H]+ candidates. MzAdan was first tested with a collection of 408 analytes acquired with flow injection analysis. This resulted in 402 correct [M+H]+ identifications and, with combinations of sodium, ammonium, and potassium adducts and water and ammonia losses within a tolerance of 10 mmu, explained close to 50% of the total ion current. False positives were monitored with mass accuracy and bias as well as chromatographic behavior which led to the identification of adducts with calcium instead of the expected potassium. MzAdan was then integrated in a workflow with XCMS for the untargeted LC-MS data analysis of a 52 metabolite standard mix and a human urine sample. The results were benchmarked against three other annotation tools, CAMERA, findMAIN, and CliqueMS: findMAIN and mzAdan consistently produced higher numbers of [M+H]+ candidates compared with CliqueMS and CAMERA, especially with co-eluting metabolites. Detection of low-intensity ions and correct grouping were found to be essential for annotation performance.Graphical abstract

Software Supporting a Workflow of Quantitative Dynamic Flux Maps Estimation in Central Metabolism from SIRM Experimental Data.

Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.

MIDcor, an R-program for deciphering mass interferences in mass spectra of metabolites enriched in stable isotopes

BackgroundTracing stable isotopes, such as 13C using various mass spectrometry (MS) methods provides a valuable information necessary for the study of biochemical processes in cells. However, extracting such information requires special care, such as a correction for naturally occurring isotopes, or overlapping mass spectra of various components of the cell culture medium. Developing a method for a correction of overlapping peaks is the primary objective of this study.ResultsOur computer program-MIDcor (free at https://github.com/seliv55/mid_correct) written in the R programming language, corrects the raw MS spectra both for the naturally occurring isotopes and for the overlapping of peaks corresponding to various substances. To this end, the mass spectra of unlabeled metabolites measured in two media are necessary: in a minimal medium containing only derivatized metabolites and chemicals for derivatization, and in a complete cell incubated medium. The MIDcor program calculates the difference (D) between the theoretical and experimentally measured spectra of metabolites containing only the naturally occurring isotopes. The result of comparison of D in the two media determines a way of deciphering the true spectra. (1) If D in the complete medium is greater than that in the minimal medium in at least one peak, then unchanged D is subtracted from the raw spectra of the labeled metabolite. (2) If D does not depend on the medium, then the spectrum probably overlaps with a derivatized fragment of the same metabolite, and D is modified proportionally to the metabolite labeling. The program automatically reaches a decision regarding the way of correction. For some metabolites/fragments in the case (2) D was found to decrease when the tested substance was 13C labeled, and this isotopic effect also can be corrected automatically, if the user provides a measured spectrum of the substance in which the 13C labeling is known a priori.ConclusionUsing the developed program improves the reliability of stable isotope tracer data analysis.

Identification of in vitro and in vivo human metabolites of the new psychoactive substance nitracaine by liquid chromatography coupled to quadrupole time-of-flight mass spectrometry

The purpose of this work was to investigate the in vitro metabolism of nitracaine, a new psychoactive substance, using human liver microsome incubations, to evaluate the cytochrome P450 (CYP) enzyme isoforms responsible for the phase-I metabolism and to compare the information from the in vitro experiments with data resulting from an authentic user's urine sample. Accurate mass spectra of metabolites were obtained using liquid chromatography-quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) and were used in the structural identification of metabolites. Two major and three minor phase-I metabolites were identified from the in vitro experiments. The observed phase-I metabolites were formed through N-deethylation, N,N-deethylation, N-hydroxylation, and de-esterification, with CYP2B6 and CYP2C19 being the main enzymes catalyzing their formation. One glucuronidated product was identified in the phase-II metabolism experiments. All of these metabolites are reported for the first time in this study except the N-deethylation product. All the in vitro metabolites except the minor N,N-deethylation product were also present in the human urine sample, thus demonstrating the reliability of the in vitro experiments in the prediction of the in vivo metabolism of nitracaine. In addition to the metabolites, three transformation products (p-nitrobenzoic acid, p-aminobenzoic acid, and 3-(diethylamino)-2,2-dimethylpropan-1-ol) were identified, as well as several glucuronides and glutamine derived of them.

MSClust: a tool for unsupervised mass spectra extraction of chromatography-mass spectrometry ion-wise aligned data

Mass peak alignment (ion-wise alignment) has recently become a popular method for unsupervised data analysis in untargeted metabolic profiling. Here we present MSClust—a software tool for analysis GC–MS and LC–MS datasets derived from untargeted profiling. MSClust performs data reduction using unsupervised clustering and extraction of putative metabolite mass spectra from ion-wise chromatographic alignment data. The algorithm is based on the subtractive fuzzy clustering method that allows unsupervised determination of a number of metabolites in a data set and can deal with uncertain memberships of mass peaks in overlapping mass spectra. This approach is based purely on the actual information present in the data and does not require any prior metabolite knowledge. MSClust can be applied for both GC–MS and LC–MS alignment data sets.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-011-0368-2) contains supplementary material, which is available to authorized users.

In silico fragmentation for computer assisted identification of metabolite mass spectra.

BackgroundMass spectrometry has become the analytical method of choice in metabolomics research. The identification of unknown compounds is the main bottleneck. In addition to the precursor mass, tandem MS spectra carry informative fragment peaks, but the coverage of spectral libraries of measured reference compounds are far from covering the complete chemical space. Compound libraries such as PubChem or KEGG describe a larger number of compounds, which can be used to compare their in silico fragmentation with spectra of unknown metabolites.ResultsWe created the MetFrag suite to obtain a candidate list from compound libraries based on the precursor mass, subsequently ranked by the agreement between measured and in silico fragments. In the evaluation MetFrag was able to rank most of the correct compounds within the top 3 candidates returned by an exact mass query in KEGG. Compared to a previously published study, MetFrag obtained better results than the commercial MassFrontier software. Especially for large compound libraries, the candidates with a good score show a high structural similarity or just different stereochemistry, a subsequent clustering based on chemical distances reduces this redundancy. The in silico fragmentation requires less than a second to process a molecule, and MetFrag performs a search in KEGG or PubChem on average within 30 to 300 seconds, respectively, on an average desktop PC.ConclusionsWe presented a method that is able to identify small molecules from tandem MS measurements, even without spectral reference data or a large set of fragmentation rules. With today's massive general purpose compound libraries we obtain dozens of very similar candidates, which still allows a confident estimate of the correct compound class. Our tool MetFrag improves the identification of unknown substances from tandem MS spectra and delivers better results than comparable commercial software. MetFrag is available through a web application, web services and as java library. The web frontend allows the end-user to analyse single spectra and browse the results, whereas the web service and console application are aimed to perform batch searches and evaluation.

Towards de novo identification of metabolites by analyzing tandem mass spectra

Mass spectrometry is among the most widely used technologies in proteomics and metabolomics. Being a high-throughput method, it produces large amounts of data that necessitates an automated analysis of the spectra. Clearly, database search methods for protein analysis can easily be adopted to analyze metabolite mass spectra. But for metabolites, de novo interpretation of spectra is even more important than for protein data, because metabolite spectra databases cover only a small fraction of naturally occurring metabolites: even the model plant Arabidopsis thaliana has a large number of enzymes whose substrates and products remain unknown. The field of bio-prospection searches biologically diverse areas for metabolites which might serve as pharmaceuticals. De novo identification of metabolite mass spectra requires new concepts and methods since, unlike proteins, metabolites possess a non-linear molecular structure. In this work, we introduce a method for fully automated de novo identification of metabolites from tandem mass spectra. Mass spectrometry data is usually assumed to be insufficient for identification of molecular structures, so we want to estimate the molecular formula of the unknown metabolite, a crucial step for its identification. The method first calculates all molecular formulas that explain the parent peak mass. Then, a graph is build where vertices correspond to molecular formulas of all peaks in the fragmentation mass spectra, whereas edges correspond to hypothetical fragmentation steps. Our algorithm afterwards calculates the maximum scoring subtree of this graph: each peak in the spectra must be scored at most once, so the subtree shall contain only one explanation per peak. Unfortunately, finding this subtree is NP-hard. We suggest three exact algorithms (including one fixed parameter tractable algorithm) as well as two heuristics to solve the problem. Tests on real mass spectra show that the FPT algorithm and the heuristics solve the problem suitably fast and provide excellent results: for all 32 test compounds the correct solution was among the top five suggestions, for 26 compounds the first suggestion of the exact algorithm was correct. http://www.bio.inf.uni-jena.de/tandemms

Systematic Identification of Conserved Metabolites in GC/MS Data for Metabolomics and Biomarker Discovery

Analysis of metabolomic profiling data from gas chromatography-mass spectrometry (GC/MS) measurements usually relies upon reference libraries of metabolite mass spectra to structurally identify and track metabolites. In general, techniques to enumerate and track unidentified metabolites are nonsystematic and require manual curation. We present a method and software implementation, freely available at http://spectconnect.mit.edu, that can systematically detect components that are conserved across samples without the need for a reference library or manual curation. We validate this approach by correctly identifying the components in a known mixture and the discriminating components in a spiked mixture. Finally, we demonstrate an application of this approach with a brief analysis of the Escherichia coli metabolome. By systematically cataloguing conserved metabolite peaks prior to data analysis methods, our approach broadens the scope of metabolomics and facilitates biomarker discovery.

Functional Demonstration of Reverse Transsulfuration in the Mycobacterium tuberculosis Complex Reveals That Methionine Is the Preferred Sulfur Source for Pathogenic Mycobacteria

Methionine can be used as the sole sulfur source by the Mycobacterium tuberculosis complex although it is not obvious from examination of the genome annotation how these bacteria utilize methionine. Given that genome annotation is a largely predictive process, key challenges are to validate these predictions and to fill in gaps for known functions for which genes have not been annotated. We have addressed these issues by functional analysis of methionine metabolism. Transport, followed by metabolism of (35)S methionine into the cysteine adduct mycothiol, demonstrated the conversion of exogenous methionine to cysteine. Mutational analysis and cloning of the Rv1079 gene showed it to encode the key enzyme required for this conversion, cystathionine gamma-lyase (CGL). Rv1079, annotated metB, was predicted to encode cystathionine gamma-synthase (CGS), but demonstration of a gamma-elimination reaction with cystathionine as well as the gamma-replacement reaction yielding cystathionine showed it encodes a bifunctional CGL/CGS enzyme. Consistent with this, a Rv1079 mutant could not incorporate sulfur from methionine into cysteine, while a cysA mutant lacking sulfate transport and a methionine auxotroph was hypersensitive to the CGL inhibitor propargylglycine. Thus, reverse transsulfuration alone, without any sulfur recycling reactions, allows M. tuberculosis to use methionine as the sole sulfur source. Intracellular cysteine was undetectable so only the CGL reaction occurs in intact mycobacteria. Cysteine desulfhydrase, an activity we showed to be separable from CGL/CGS, may have a role in removing excess cysteine and could explain the ability of M. tuberculosis to recycle sulfur from cysteine, but not methionine.

Metabolites of an orally active antimicrobial prodrug, 2,5-bis(4-amidinophenyl)furan-bis-O-methylamidoxime, identified by liquid chromatography/tandem mass spectrometry.

DB75 (2,5-bis(4-amidinophenyl)furan) is a promising antimicrobial agent against African trypanosomiasis and Pneumocystis carinii pneumonia. However, it suffers from poor oral activity in rodent models for both infections. In contrast, a novel prodrug of DB75, 2,5-bis(4-amidinophenyl)furan-bis-O-methylamidoxime (DB289), has excellent oral activity. DB289 is currently undergoing clinical investigation as a candidate drug to treat primary stage African trypanosomiasis and Pneumocystis carinii pneumonia. In this study, metabolites of DB289 formed after incubation with freshly isolated rat hepatocytes were characterized using liquid chromatography/ion trap mass spectrometry. Administration of DB289 and octadeuterated DB289 in a 1 : 1 mixture greatly facilitated metabolite identification by providing isotope patterns with twin ions separated by 8 m/z units in the ratio 1 : 1, in the extracted ion chromatograms of molecular ions and in the product ion mass spectra of metabolites. Ten metabolites were identified. Series of O-demethylations and N-dehydroxylations led to the metabolic activation of DB289 to DB75 with the production of four intermediate phase I metabolites. Phase II glucuronidation and sulfation led to the formation of four glucuronide and one sulfate metabolites.

14] Isolation and identification of vitamin D metabolites

Publisher Summary This chapter describes the isolation and identification of vitamin D metabolites. A successful isolation and identification of a vitamin D metabolite usually consists of extraction, prepurification (optional), several high-performance liquid chromatography (HPLC) procedures, ultraviolet (UV) absorbance spectroscopy, mass spectrometry (MS), chemical derivatization, and may include proton nuclear magnetic resonance (NMR) spectrometry. HPLC is the best method known for the resolution and purification of vitamin D metabolites. A number of dissimilar vitamin D derivatives comigrate in a single HPLC system. This emphasizes the need for more than one system in determining coidentity or for comparing metabolites from biological sources to those obtained in vitro from known precursors. The UV spectra of vitamin D and its metabolites having the 5,6- cis geometry obtained in ethanol are smooth curves with one absorbance maximum at 265 nm and a molar absorptivity, ɛ , of 18,200 for D 3 , and 19,200 for D 2 . Vitamin D metabolites produce strong positive ions in the chemical ionization mode. The nature of the positive ion chemical ionization (PCI) spectra is dependent on the reagent gas. NMR spectroscopy can be a powerful aid in identifying new metabolites but is not used frequently because it requires larger amounts of sample (10–500 μ g) than MS (25–200 ng) and because the mass spectra of metabolites and their derivatives usually provide conclusive structural evidence. Nevertheless, the NMR spectra of vitamin D compounds have distinctive signals that are diagnostic of the alkene protons, the side chain substitution, and the A-ring substitution.

Mass spectra of metabolites of 1-(tetrahydro-2-furanyl)-5-fluorouracil and related compounds

The mass spectra of metabolites of the antitumour agent 1-(tetrahydro-2-furanyl)-5-fluorouracil and their related compounds were measured by field desorption, chemical ionization and electron impact methods. The molecular ions of these compounds were observed in all methods. In the electron impact mass spectra of hydroxylated 1-(tetrahydro-2-furanyl)-5-fluorouracil and 5-fluorouracil-nucleosides, which differ in the position of the hydroxyl group on the tetrahydrofuran ring or sugar ring, the patterns of fragment ions formed by transition of labile hydrogens were extremely effective for determination of the structures of these compounds. Furthermore, the characteristic fragment ions produced by the retro Diels–Alder decomposition of the 5-fluorouracil skeleton provided useful information for determining the position of the substituent on the 5-fluorouracil skeleton.

The twin ion technique for detection of metabolites by gas chromatography-mass spectrometry: Intermediates in estrogen biosynthesis

[4- 14C + 7-D 0.44]Androstenedione and [4- 14C + 7β-D 0.42]testosterone were prepared. When they were examined by mass spectrometry, the above proportion of deuterium and protium forms resulted in mass spectra in which the molecular ion (M +) and (M + + 1) were of equal intensity. Fragment ions that contained deuterium were also twins. When doubly-labeled androstenedione and testosterone were used as substrates for the aromatizing enzymes of human placenta, the mass spectra of metabolites were characteristically labeled and thus readily distinguished from unlabeled material. Metabolites were quantitated by counting 14C. 17β,19-Dihydroxyandrost-4-en-3-one, 19-hydroxyandrost-4-ene-3,17-dione, 17β-hydroxy-3-oxoandrost-4-en-19-al, 3,17-dioxoandrost-4-en-19-al, estradiol-17β, and estrone were isolated, identified by their mass spectra, and quantitated following incubation of doubly-labeled androstenedione and testosterone with human placental microsomes.

Metabolism of 1-( -methylallylthiocarbamoyl)-2-methylthiocarbamoylhydrazine (methallibure) in cattle.

The metabolism of 1-(α-methylallylthiocarb-14C-amoyl)-2-methylthiocarbamoylhydrazine (14C methallibure) was studied in lactating cows. Recoveries of 14C in urine, feces and milk after an oral dose of 14C methallibure were 79, 14.4 and 1.5%, respectively (average of three trials). Urinary metabolites were isolated using solvent extraction and various types of chromatography. Identities of metabolites were based on matching infrared and mass spectra of metabolites with spectra of authentic compounds, thin-layer chromatography or by deductive interpretation of mass spectra. The metabolites identified and their approximate abundance (as a per cent of total 14C in urine) were methallibure, 2%; 2-methylamino-5-(α-methylallylamino)-1,3,4-thiadiazole, 20–25%; 2-methylamino-5-amino-1,3,4-thiadiazole, 9–12%; 2,5-diamino-1,3,4-thiadiazole, 9–12%; 3-methylmercapto-4-methyl-5-(α-methylallylamino)-1,2,4-triazole, <1%, 3-mercapto-4-methyl-5-(α-methylallylamino)-1,2,4-triazole, <1%; 2-amino-5-(α-methylallylamino)-1,3,4-thiadiazole, <1%. Excretion and metabolism of 14C methallibure is similar in the cow and gilt.