Systematic identification of trimethoprim metabolites in lettuce.

Antibiotics are some of the most widely used drugs. Their release in the environment is of great concern since their consumption is a major factor for antibiotic resistance, one of the most important threats to human health. Their occurrence and fate in agricultural systems have been extensively investigated in recent years. Yet whilst their biotic and abiotic degradation pathways have been thoroughly researched, their biotransformation pathways in plants are less understood, such as in case of trimethoprim. Although trimethoprim has been reported in the environment, its fate in higher plants still remains unknown. A bench-scale experiment was performed and 30 trimethoprim metabolites were identified in lettuce (Lactuca sativa L.), of which 5 belong to phase I and 25 to phase II. Data mining yielded a list of 1018 ions as possible metabolite candidates, which was filtered to a final list of 87 candidates. Molecular structures were assigned for 19 compounds, including 14 TMP metabolites reported for the first time. Alongside well-known biotransformation pathways in plants, additional novel pathways were suggested, namely, conjugation with sesquiterpene lactones, and abscisic acid as a part of phase II of plant metabolism. The results obtained offer insight into the variety of phase II conjugates and may serve as a guideline for studying the metabolization of other chemicals that share a similar molecular structure or functional groups with trimethoprim. Finally, the toxicity and potential contribution of the identified metabolites to the selective pressure on antibiotic resistance genes and bacterial communities via residual antimicrobial activity were evaluated.

Elucidating biotransformation pathways of ofloxacin in lettuce (Lactuca sativa L).

Antibiotics can be uptaken by plants from soil desorption or directly from irrigation water, but their metabolization pathways in plants are largely unknown. In this paper, an analytical workflow based on high-resolution mass spectrometry was applied for the systematic identification of biotransformation products of ofloxacin in lettuce. The targeted metabolites were selected by comparing the mass chromatograms of exposed with control samples using an advanced spectra-processing method (Fragment Ion Search). The innovative methodology presented allowed us to identify a total of 11 metabolites, including 5 ofloxacin metabolites that are being reported for the first time in plants. Accordingly, major transformation pathways were proposed revealing insight into how ofloxacin and related chemicals are metabolized in lettuce. Furthermore, the influence of biotransformation on potential residual antimicrobial activity of identified compounds was discussed. Human exposure to antibiotics at doses below the minimum inhibitory concentrations is crucial in human risk assessment, including food ingestion; however, in the case of ofloxacin presented results reveal that plant metabolites should also be considered so as not to underestimate their risk.

Development of a sensitive untargeted liquid chromatography-high resolution mass spectrometry screening devoted to hair analysis through a shared MS2 spectra database: A step toward early detection of new psychoactive substances.

Untargeted liquid chromatography-high resolution mass spectrometry (LC-HRMS) techniques have become indispensable tools for systematic toxicological analysis. They allow the research of an almost unlimited number of drugs within a single analytical cycle, but shared mass spectra libraries are still missing to identify newly marketed compounds, along with defined analytical procedures. This article describes the optimization, validation, and application of an untargeted screening method devoted to hair analysis using data-dependent analysis (DDA) and a shared HRMS database. This method used an ultra-high performance liquid chromatography coupled to a benchtop Orbitrap. Raw MS data were processed with Compound Discoverer software coupled to the mzCloud™ library. Optimizations were performed on blank hair spiked with 19 analytes having different physical and chemical properties. To validate the effectiveness of a shared spectra database, 20 compounds spectra were added and then retrospectively screened. Sensitivity and reliability were evaluated on 317 compounds of interest in toxicology. The method was then applied to 11 hair samples. The matrix effect range by ion suppression/enhancement was 40%-110%. The method allows the detection of 284 among the 317 screened compounds, including 72 new psychoactive substances (NPS). Lower limit of identification (LLOI) and lower limit of detection (LLOD) were 1 to 1000 pg/mg and 1 to 500 pg/mg, respectively. The method was successfully applied to 11 clinical cases and 144 compounds were identified including 24 NPS including AKB48-5F for the first time in hair. We developed and validated an LC-HRMS untargeted screening of 284 compounds and successfully applied it to 11 real hair samples.

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.

The Time Is Right to Focus on Model Organism Metabolomes.

Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research.

HAMMER: automated operation of mass frontier to construct in silico mass spectral fragmentation libraries.

SUMMARY: Experimental MS(n) mass spectral libraries currently do not adequately cover chemical space. This limits the robust annotation of metabolites in metabolomics studies of complex biological samples. In silico fragmentation libraries would improve the identification of compounds from experimental multistage fragmentation data when experimental reference data are unavailable. Here, we present a freely available software package to automatically control Mass Frontier software to construct in silico mass spectral libraries and to perform spectral matching. Based on two case studies, we have demonstrated that high-throughput automation of Mass Frontier allows researchers to generate in silico mass spectral libraries in an automated and high-throughput fashion with little or no human intervention required. AVAILABILITY AND IMPLEMENTATION: Documentation, examples, results and source code are available at http://www.biosciences-labs.bham.ac.uk/viant/hammer/.

Fragmentation trees for the structural characterisation of metabolites.

Metabolite identification plays a crucial role in the interpretation of metabolomics research results. Due to its sensitivity and widespread implementation, a favourite analytical method used in metabolomics is electrospray mass spectrometry. In this paper, we demonstrate our results in attempting to incorporate the potentials of multistage mass spectrometry into the metabolite identification routine. New software tools were developed and implemented which facilitate the analysis of multistage mass spectra and allow for efficient removal of spectral artefacts. The pre-processed fragmentation patterns are saved as fragmentation trees. Fragmentation trees are characteristic of molecular structure. We demonstrate the reproducibility and robustness of the acquisition of such trees on a model compound. The specificity of fragmentation trees allows for distinguishing structural isomers, as shown on a pair of isomeric prostaglandins. This approach to the analysis of the multistage mass spectral characterisation of compounds is an important step towards formulating a generic metabolite identification method.

Determination of ion structures in structurally related compounds using precursor ion fingerprinting.

Structurally-related alkaloids were analyzed by electrospray ionization/multiple stage mass spectrometry (ESI/MS(n)) at varying collision energies to demonstrate a conceptual algorithm, precursor ion fingerprinting (PIF). PIF is a new approach for interpreting and library-searching ESI mass spectra predicated on the precursor ions of structurally-related compounds and their matching product ion spectra. Multiple-stage mass spectra were compiled and constructed into "spectral trees" that illustrated the compounds' product ion spectra in their respective mass spectral stages. The precursor ions of these alkaloids were characterized and their spectral trees incorporated into an MS(n) library. These data will be used to construct a universal, searchable, and transferable library of MS(n) spectra. In addition, PIF will generate a proposed structural arrangement utilizing previously characterized ion structures, which will assist in the identification of unknown compounds.

Comparison of CID spectra of singly charged polypeptide antibiotic precursor ions obtained by positive-ion vacuum MALDI IT/RTOF and TOF/RTOF, AP-MALDI-IT and ESI-IT mass spectrometry.

Various classes of polypeptide antibiotics, including blocked linear peptides (gramicidin D), side-chain-cyclized peptides (bacitracin, viomycin, capreomycin), side-chain-cyclized depsipeptides (virginiamycin S), real cyclic peptides (tyrocidin, gramcidin S) and side-chain-cyclized lipopeptides (polymyxin B and E, amfomycin), were investigated by low-energy collision induced dissociation (LE-CID) as well as high-energy CID (HE-CID). Ion trap (IT) based instruments with different desorption/ionization techniques such as electrospray ionization (ESI), atmospheric pressure matrix-assisted laser desorption/ionization (AP-MALDI) and vacuum MALDI (vMALDI) as well as a vMALDI-time-of-flight (TOF)/curved field-reflectron instrument fitted with a gas collision cell were used. For optimum comparability of data from different IT instruments, the CID conditions were standardized and only singly charged precursor ions were considered. Additionally, HE-CID data obtained from the TOF-based instrument were acquired and compared with LE-CID data from ITs. Major differences between trap-based and TOF-based CID data are that the latter data set lacks abundant additional loss of small neutrals (e.g. ammonia, water) but contains product ions down to the immonium-ion-type region, thereby allowing the detection of even single amino-acid (even unusual amino acids) substitutions. For several polypeptide antibiotics, mass spectrometric as well as tandem mass spectrometric data are shown and discussed for the first time, and some yet undescribed minor components are also reported. De novo sequencing of unusually linked minor components of (e.g. cyclic) polypeptides is practically impossible without knowledge of the exact structure and fragmentation behavior of the major components. Finally, the described standardized CID condition constitutes a basic prerequisite for creating a searchable, annotated MS(n)-database of bioactive compounds. The applied desorption/ionization techniques showed no significant influence on the type of product ions (neglecting relative abundances of product ions formed) observed, and therefore the type of analyzer connected with the CID process mainly determines the type of fragment ions.

A butterfly's chemical key to various ant forts: intersection-odour or aggregate-odour multi-host mimicry?

Deception is a crucial yet incompletely understood strategy of social parasites. In central Europe, the Mountain Alcon Blue, Maculinea rebeli, a highly endangered butterfly, parasitises several Myrmica ant species. Caterpillars gain access to host nests probably by faking the ants' odour. We analysed gas chromatography-mass spectrometry data of body surface hydrocarbons of pre-adoption and hibernated larvae of Maculinea rebeli and of their host species Myrmica sabuleti and M. schencki. Data were ordinated by different methods, based on similarities in the relative quantities of compounds between chromatograms. The two Myrmica species exhibit species-specific profiles. The Maculinea rebeli pre-adoption larva has a complex profile that simultaneously contains species-specific substances of the two investigated host species. This evidence leads to the interpretation that, in central Europe, Maculinea rebeli is predisposed for multi-host use by the chemical signature of its pre-adoption larva. The Maculinea rebeli larva clearly does not rely on an "intersection-odour" of compounds common to all host ant species, but synthesises an "aggregate-odour" containing specific compounds of each of the investigated hosts. We term this previously unknown chemical strategy "aggregate-odour multi-host mimicry".

Electron ionization mass spectrometric study of monomeric models of O-polysaccharides of Vibrio cholerae O:1, serotypes Ogawa and Inaba.

Fragmentation mechanisms of electron ionization (EI) mass spectrometry of the title compounds have been elucidated by high-resolution (HR) mass spectrometric measurements of the elemental composition and measurements of the metastable transitions (B(2)/E, CID). The experimental results were interpreted with the help of Mass Frontier 3.0 software, which aided the elucidation of fragmentation mechanisms and helped to deduce structures of the ions formed. Characteristic under the conditions of EI-MS measurement was the production of protonated adducts. Three distinct pathways observed include the formation of oxonium type ions, the conjugated transfer of electrons in the pyranose ring, and cleavage of the acylamide side chains. By applying the results obtained, the molecular mass, as well as the structures of both the saccharide and acylamide side chain involved in related substances, can be determined.

Cuticular hydrocarbons of Tetramorium ants from central Europe: analysis of GC-MS data with self-organizing maps (SOM) and implications for systematics.

Cuticular hydrocarbons were extracted from workers of 63 different nests of five species of Tetramorium ants (Hymenoptera: Formicidae) from Austria, Hungary, and Spain. The GC-MS data were classified (data mining) by self-organizing maps (SOM). SOM neurons derived from primary neuron separation were subjected to hierarchical SOM (HSOM) and were grouped to neuron areas on the basis of vicinity in the hexagonal output grid. While primary neuron separation and HSOM resulted in classifications on a level more sensitive than species differences, neuron areas resulted in chemical phenotypes apparently of the order of species. These chemical phenotypes have implications for systematics: while the chemical phenotypes for T. ferox and T. moravicum correspond to morphological determination, in T. caespitum and T. impurum a total of six chemical phenotypes is found. Three hypotheses are discussed to explain this disparity between morphological and chemical classifications, including in particular the possibility of hybridization and the existence of cryptic species. Overall, the GC-MS profiles classified by SOM prove to be a practical alternative to morphological determination (T. ferox, T. moravicum) and indicate the need to revisit systematics (T. caespitum, T. impurum).