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 .

QCScreen: a software tool for data quality control in LC-HRMS based metabolomics.

BACKGROUND: Metabolomics experiments often comprise large numbers of biological samples resulting in huge amounts of data. This data needs to be inspected for plausibility before data evaluation to detect putative sources of error e.g. retention time or mass accuracy shifts. Especially in liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics research, proper quality control checks (e.g. for precision, signal drifts or offsets) are crucial prerequisites to achieve reliable and comparable results within and across experimental measurement sequences. Software tools can support this process. RESULTS: The software tool QCScreen was developed to offer a quick and easy data quality check of LC-HRMS derived data. It allows a flexible investigation and comparison of basic quality-related parameters within user-defined target features and the possibility to automatically evaluate multiple sample types within or across different measurement sequences in a short time. It offers a user-friendly interface that allows an easy selection of processing steps and parameter settings. The generated results include a coloured overview plot of data quality across all analysed samples and targets and, in addition, detailed illustrations of the stability and precision of the chromatographic separation, the mass accuracy and the detector sensitivity. The use of QCScreen is demonstrated with experimental data from metabolomics experiments using selected standard compounds in pure solvent. The application of the software identified problematic features, samples and analytical parameters and suggested which data files or compounds required closer manual inspection. CONCLUSIONS: QCScreen is an open source software tool which provides a useful basis for assessing the suitability of LC-HRMS data prior to time consuming, detailed data processing and subsequent statistical analysis. It accepts the generic mzXML format and thus can be used with many different LC-HRMS platforms to process both multiple quality control sample types as well as experimental samples in one or more measurement sequences.

The peptaibiotics database--a comprehensive online resource.

In this work, we present the 'Peptaibiotics Database' (PDB), a comprehensive online resource, which intends to cover all Aib-containing non-ribosomal fungal peptides currently described in scientific literature. This database shall extend and update the recently published 'Comprehensive Peptaibiotics Database' and currently consists of 1,297 peptaibiotic sequences. In a literature survey, a total of 235 peptaibiotic sequences published between January 2013 and June 2014 have been compiled, and added to the list of 1,062 peptides in the recently published 'Comprehensive Peptaibiotics Database'. The presented database is intended as a public resource freely accessible to the scientific community at peptaibiotics-database.boku.ac.at. The search options of the previously published repository and the presentation of sequence motif searches have been extended significantly. All of the available search options can be combined to create complex database queries. As a public repository, the presented database enables the easy upload of new peptaibiotic sequences or the correction of existing informations. In addition, an administrative interface for maintenance of the content of the database has been implemented, and the design of the database can be easily extended to store additional information to accommodate future needs of the 'peptaibiomics community'.

GC-MS based targeted metabolic profiling identifies changes in the wheat metabolome following deoxynivalenol treatment.

Fusariumgraminearum and related species commonly infest grains causing the devastating plant disease Fusarium head blight (FHB) and the formation of trichothecene mycotoxins. The most relevant toxin is deoxynivalenol (DON), which acts as a virulence factor of the pathogen. FHB is difficult to control and resistance to this disease is a polygenic trait, mainly mediated by the quantitative trait loci (QTL) Fhb1 and Qfhs.ifa-5A. In this study we established a targeted GC-MS based metabolomics workflow comprising a standardized experimental setup for growth, treatment and sampling of wheat ears and subsequent GC-MS analysis followed by data processing and evaluation of QC measures using tailored statistical and bioinformatics tools. This workflow was applied to wheat samples of six genotypes with varying levels of Fusarium resistance, treated with either DON or water, and harvested 0, 12, 24, 48 and 96 h after treatment. The results suggest that the primary carbohydrate metabolism and transport, the citric acid cycle and the primary nitrogen metabolism of wheat are clearly affected by DON treatment. Most importantly significantly elevated levels of amino acids and derived amines were observed. In particular, the concentrations of the three aromatic amino acids phenylalanine, tyrosine, and tryptophan increased. No clear QTL specific difference in the response could be observed except a generally faster increase in shikimate pathway intermediates in genotypes containing Fhb1. The overall workflow proved to be feasible and facilitated to obtain a more comprehensive picture on the effect of DON on the central metabolism of wheat.

Severe drought stress is affecting selected primary metabolites, polyphenols, and volatile metabolites in grapevine leaves (Vitis vinifera cv. Pinot noir).

Extreme weather conditions with prolonged dry periods and high temperatures as well as heavy rain events can severely influence grapevine physiology and grape quality. The present study evaluates the effects of severe drought stress on selected primary metabolites, polyphenols and volatile metabolites in grapevine leaves. Among the 11 primary metabolites, 13 polyphenols and 95 volatiles which were analyzed, a significant discrimination between control and stressed plants of 7 primary metabolites, 11 polyphenols and 46 volatile metabolites was observed. As single parameters are usually not specific enough for the discrimination of control and stressed plants, an unsupervised (PCA) and a supervised (PLS-DA) multivariate approach were applied to combine results from different metabolic groups. In a first step a selection of five metabolites, namely citric acid, glyceric acid, ribose, phenylacetaldehyde and 2-methylbutanal were used to establish a calibration model using PLS regression to predict the leaf water potential. The model was strong enough to assign a high number of plants correctly with a correlation of 0.83. The PLS-DA provides an interesting approach to combine data sets and to provide tools for the specific evaluation of physiological plant stresses.

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

An untargeted metabolomics workflow for the detection of metabolites derived from endogenous or exogenous tracer substances is presented. To this end, a recently developed stable isotope-assisted LC-HRMS-based metabolomics workflow for the global annotation of biological samples has been further developed and extended. For untargeted detection of metabolites arising from labeled tracer substances, isotope pattern recognition has been adjusted to account for nonlabeled moieties conjugated to the native and labeled tracer molecules. Furthermore, the workflow has been extended by (i) an optional ion intensity ratio check, (ii) the automated combination of positive and negative ionization mode mass spectra derived from fast polarity switching, and (iii) metabolic feature annotation. These extensions enable the automated, unbiased, and global detection of tracer-derived metabolites in complex biological samples. The workflow is demonstrated with the metabolism of (13)C9-phenylalanine in wheat cell suspension cultures in the presence of the mycotoxin deoxynivalenol (DON). In total, 341 metabolic features (150 in positive and 191 in negative ionization mode) corresponding to 139 metabolites were detected. The benefit of fast polarity switching was evident, with 32 and 58 of these metabolites having exclusively been detected in the positive and negative modes, respectively. Moreover, for 19 of the remaining 49 phenylalanine-derived metabolites, the assignment of ion species and, thus, molecular weight was possible only by the use of complementary features of the two ion polarity modes. Statistical evaluation showed that treatment with DON increased or decreased the abundances of many detected metabolites.

Automated LC-HRMS(/MS) approach for the annotation of fragment ions derived from stable isotope labeling-assisted untargeted metabolomics.

Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native (12)C- and uniformly (13)C (U-(13)C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-(13)C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research.

The comprehensive peptaibiotics database.

Peptaibiotics are nonribosomally biosynthesized peptides, which - according to definition - contain the marker amino acid α-aminoisobutyric acid (Aib) and possess antibiotic properties. Being known since 1958, a constantly increasing number of peptaibiotics have been described and investigated with a particular emphasis on hypocrealean fungi. Starting from the existing online 'Peptaibol Database', first published in 1997, an exhaustive literature survey of all known peptaibiotics was carried out and resulted in a list of 1043 peptaibiotics. The gathered information was compiled and used to create the new 'The Comprehensive Peptaibiotics Database', which is presented here. The database was devised as a software tool based on Microsoft (MS) Access. It is freely available from the internet at http://peptaibiotics-database.boku.ac.at and can easily be installed and operated on any computer offering a Windows XP/7 environment. It provides useful information on characteristic properties of the peptaibiotics included such as peptide category, group name of the microheterogeneous mixture to which the peptide belongs, amino acid sequence, sequence length, producing fungus, peptide subfamily, molecular formula, and monoisotopic mass. All these characteristics can be used and combined for automated search within the database, which makes The Comprehensive Peptaibiotics Database a versatile tool for the retrieval of valuable information about peptaibiotics. Sequence data have been considered as to December 14, 2012.

Isotope-assisted screening for iron-containing metabolites reveals a high degree of diversity among known and unknown siderophores produced by Trichoderma spp.

Due to low iron availability under environmental conditions, many microorganisms excrete iron-chelating agents (siderophores) to cover their iron demands. A novel screening approach for the detection of siderophores using liquid chromatography coupled to high-resolution tandem mass spectrometry was developed to study the production of extracellular siderophores of 10 wild-type Trichoderma strains. For annotation of siderophores, an in-house library comprising 422 known microbial siderophores was established. After 96 h of cultivation, 18 different iron chelators were detected. Four of those (dimerum acid, fusigen, coprogen, and ferricrocin) were identified by measuring authentic standards. cis-Fusarinine, fusarinine A and B, and des-diserylglycylferrirhodin were annotated based on high-accuracy mass spectral analysis. In total, at least 10 novel iron-containing metabolites of the hydroxamate type were found. On average Trichoderma spp. produced 12 to 14 siderophores, with 6 common to all species tested. The highest number (15) of siderophores was detected for the most common environmental opportunistic and strongly fungicidic species, Trichoderma harzianum, which, however, did not have any unique compounds. The tropical species T. reesei had the most distinctive pattern, producing one unique siderophore (cis-fusarinine) and three others that were present only in T. harzianum and not in other species. The diversity of siderophores did not directly correlate with the antifungal potential of the species tested. Our data suggest that the high diversity of siderophores produced by Trichoderma spp. might be the result of further modifications of the nonribosomal peptide synthetase (NRPS) products and not due to diverse NRPS-encoding genes.