Toolbox for the Extraction and Quantification of Ochratoxin A and Ochratoxin Alpha Applicable for Different Pig and Poultry Matrices.

Ochratoxin A (OTA) is one of the major mycotoxins causing severe effects on the health of humans and animals. Ochratoxin alpha (OTα) is a metabolite of OTA, which is produced through microbial or enzymatic hydrolysis, and one of the preferred routes of OTA detoxification. The methods described here are applicable for the extraction and quantification of OTA and OTα in several pig and poultry matrices such as feed, feces/excreta, urine, plasma, dried blood spots, and tissue samples such as liver, kidney, muscle, skin, and fat. The samples are homogenized and extracted. Extraction is either based on a stepwise extraction using ethyl acetate/sodium hydrogencarbonate/ethyl acetate or an acetonitrile/water mixture. Quantitative analysis is based on reversed-phase liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Method validation was successfully performed and the linearity, limit of quantification, accuracy, precision as well as the stability of the samples, were evaluated. The analyte recovery of the spiked samples was between 80 and 120% (80-150% for spiked concentrations ≤ 1 ng/g or ng/mL) and the relative standard deviation was ≤ 15%. Therefore, we provide a toolbox for the extraction and quantification of OTA and OTα in all relevant pig and poultry matrices.

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.

metaMS: an open-source pipeline for GC-MS-based untargeted metabolomics.

Untargeted metabolomics are rapidly becoming an important tool for studying complex biological samples. Gas chromatography-mass spectrometry (GC-MS) is the most widely used analytical technology for metabolomic analysis of compounds that are volatile or can be chemically derivatised into volatile compounds. Unfortunately, data processing and analysis are not straightforward and the field is dominated by vendor-supplied software that does not always allow easy integration for large laboratories with different instruments. This paper presents an open-source pipeline for high-throughput GC-MS data processing, written in the R language and available as package metaMS. It features rapid annotation using in-house databases, and also provides support for building and validating such databases. The results are presented in simple-to-use tables, summarising the relative concentrations of identified compounds and unknowns in all samples. The use of the pipeline is illustrated using three experimental data sets.

Quantitative metabolic profiling of grape, apple and raspberry volatile compounds (VOCs) using a GC/MS/MS method.

Nowadays the trend in analytical chemistry is clearly towards the creation of multiple methods with extended coverage, enabling the determination of many different classes of compounds in a single analysis in which virtually all classes of different compounds are included in a single run. The aim of this study was to develop and validate a versatile and selective GC/MS/MS method for metabolite profiling of volatile compounds in apples, raspberries and grapes. Validation of the method was performed in terms of the limit of detection, limit of quantification, linearity range, and inter and intraday precision. Confirmation of the identity of the compounds in samples was carried out by checking compliance of the q/Q ratio of samples and reference standards. The multiple reaction monitoring with selection of two transition ions, one for quantification and one for confirmation, provided excellent selectivity and sensitivity, using the q/Q ratio as a confirmatory parameter. A multi target method was developed and validated for the simultaneous quantification and confirmation of 160 volatile compounds of raspberries, apples and grapes. The main classes were esters (42), alcohols (32), monoterpenes (31), aldehydes (17), ketones (12), norisoprenoids (8), acids (8), sesquiterpenes (7), pyrazines (3) and ethers (1) allowing the detection and quantification of 69 compounds in apples, 122 in grapes and 42 in raspberries. Moreover, the method developed can be easily extended to volatile compounds in other fruits and can therefore be widely used for quantification/profiling studies in the field of fruit aroma.

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments.

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.

Establishment and application of a metabolomics workflow for identification and profiling of volatiles from leaves of Vitis vinifera by HS-SPME-GC-MS.

INTRODUCTION: Volatile organic compounds (VOCs) occurring in leaves of plants carry information about the physiological state of the plant. Monitoring of VOCs assists in detecting plant stress before visible signs are present. OBJECTIVE: To establish and apply a simple workflow for the automated extraction, measurement and annotation/identification of Vitis vinifera cv. Pinot Noir leaf metabolites. METHODOLOGY: Leaf samples were harvested, cooled with liquid nitrogen and homogenised under cooled conditions. VOCs were extracted and enriched by solid phase microextraction (SPME) and analysed by GC-MS. Samples were measured on two columns with different polarity of stationary phases. Mass spectral deconvolution and identification was done by AMDIS software. Strict identification criteria were applied: match factor ≥ 90; relative retention index deviation ≤ 2% from reference value on both columns. Data of two sampling dates were analysed with multivariate statistics. RESULTS: We found ~600 components in a single chromatogram. Applying the mentioned criteria resulted in annotation of 63 metabolites of which 47 were confirmed with authentic standards. For the majority of the compounds technical variability was < < 40% (RSD), biological variability among plants was 7-119%. Principal component analysis (PCA) scores plot of leaf samples from two different sampling dates showed two clearly separated clusters. The presented workflow enabled for the first time the detection and identification of 19 metabolites that have so far not been described for Vitis spp. CONCLUSION: The developed workflow enabled the identification of grapevine leaf metabolites, which allowed the separation of leaves from two sampling dates by PCA.

Evaluation of settled floor dust for the presence of microbial metabolites and volatile anthropogenic chemicals in indoor environments by LC-MS/MS and GC-MS methods.

This study reports on detection of a large number of biological and anthropogenic pollutants using LC-MS/MS and GC-MS technologies in settled floor dust (SFD). The latter technique was applied to obtain a general picture on the presence of microbial as well as non-microbial volatile organic compounds, whereas the targeted LC-MS/MS analysis focused on identification of species specific secondary metabolites. In the absence of moisture monitoring data the relevance of finding of stachybotrylactam and other metabolites of tertiary colonizers are confined only to accidental direct exposure to SFD. To the best of our knowledge 30 of the 71 identified volatile organic compounds (VOCs) are newly reported in SFD matrix. Coordinated application of "AMDIS and Spectconnect" was found beneficial for the evaluation and identification of prime volatile pollutants in complex environmental samples. Principal component analysis (PCA) of peak areas of 18 microbial volatile organic compounds (MVOCs) resulted in identification of nonanal as potential MVOC marker. Two more volatiles toluene and 1-tetradecanol though had discriminative influence, are not regarded as MVOC markers, considering their probable alternate origin from paints and cosmetics, respectively.

The volatile metabolome of grapevine roots: first insights into the metabolic response upon phylloxera attack.

Many plant species respond to herbivore attack by an increased formation of volatile organic compounds. In this preliminary study we analysed the volatile metabolome of grapevine roots [Teleki 5C (Vitis berlandieri Planch. × Vitis riparia Michx.)] with the aim to gain insight into the interaction between phylloxera (Daktulosphaira vitifoliae Fitch; Hemiptera: Phylloxeridae) and grapevine roots. In the first part of the study, headspace solid phase microextraction (HS-SPME) coupled to gas chromatography - mass spectrometry (GC-MS) was used to detect and identify volatile metabolites in uninfested and phylloxera-infested root tips of the grapevine rootstock Teleki 5C. Based on the comparison of deconvoluted mass spectra with spectra databases as well as experimentally derived retention indices with literature values, 38 metabolites were identified, which belong to the major classes of plant volatiles including C6-compounds, terpenes (including modified terpenes), aromatic compounds, alcohols and n-alkanes. Based on these identified metabolites, changes in root volatiles were investigated and resulted in metabolite profiles caused by phylloxera infestation. Our preliminary data indicate that defence related pathways such as the mevalonate and/or alternative isopentenyl pyrophosphate-, the lipoxygenase- (LOX) as well as the phenylpropanoid pathway are affected in root galls as a response to phylloxera attack.