Evaluation of Glucosinolate Variation in a Collection of Turnip (Brassica rapa) Germplasm by the Analysis of Intact and Desulfo Glucosinolates

Glucosinolates (GLS) are secondary metabolites occurring in cruciferous species. These compounds are important for plant defense, human health, and the characteristic flavor of Brassica vegetables. In this study, the GLS in tubers from a collection of 48 turnip (Brassica rapa) accessions from different geographic origin were analyzed. Two different methods were used: desulfo GLS were analyzed by high-performance liquid chromatography with a photodiode array detector, and intact GLS were analyzed by accurate mass liquid chromatography–mass spectrometry. For most GLS, desulfo and intact signals correlated well, and the analytical reproducibility for individual GLS was similar for both methods. A total of 11 different GLS was monitored in the turnip tubers, through both intact and desulfo GLS analysis methods. Four clusters of accessions could be clearly distinguished based on GLS composition of the turnip tuber. Clustering based on tuber GLS differed markedly from a previously published clustering based on leaf GLS

Evaluation of Glucosinolate Variation in a Collection of Turnip (Brassica rapa) Germplasm by the Analysis of Intact and Desulfo Glucosinolates

Glucosinolates (GLS) are secondary metabolites occurring in cruciferous species. These compounds are important for plant defense, human health, and the characteristic flavor of Brassica vegetables. In this study, the GLS in tubers from a collection of 48 turnip (Brassica rapa) accessions from different geographic origin were analyzed. Two different methods were used: desulfo GLS were analyzed by high-performance liquid chromatography with a photodiode array detector, and intact GLS were analyzed by accurate mass liquid chromatography–mass spectrometry. For most GLS, desulfo and intact signals correlated well, and the analytical reproducibility for individual GLS was similar for both methods. A total of 11 different GLS was monitored in the turnip tubers, through both intact and desulfo GLS analysis methods. Four clusters of accessions could be clearly distinguished based on GLS composition of the turnip tuber. Clustering based on tuber GLS differed markedly from a previously published clustering based on leaf GLS

<i>In Silico</i> Prediction and Automatic LC–MS^<i>n</i> Annotation of Green Tea Metabolites in Urine

The colonic breakdown and human biotransformation of small molecules present in food can give rise to a large variety of potentially bioactive metabolites in the human body. However, the absence of reference data for many of these components limits their identification in complex biological samples, such as plasma and urine. We present an <i>in silico</i> workflow for automatic chemical annotation of metabolite profiling data from liquid chromatography coupled with multistage accurate mass spectrometry (LC−MS<i>ⁿ</i>), which we used to systematically screen for the presence of tea-derived metabolites in human urine samples after green tea consumption. Reaction rules for intestinal degradation and human biotransformation were systematically applied to chemical structures of 75 green tea components, resulting in a virtual library of 27 245 potential metabolites. All matching precursor ions in the urine LC–MS^<i>n</i> data sets, as well as the corresponding fragment ions, were automatically annotated by <i>in silico</i> generated (sub)­structures. The results were evaluated based on 74 previously identified urinary metabolites and lead to the putative identification of 26 additional green tea-derived metabolites. A total of 77% of all annotated metabolites were not present in the Pubchem database, demonstrating the benefit of <i>in silico</i> metabolite prediction for the automatic annotation of yet unknown metabolites in LC–MS^<i>n</i> data from nutritional metabolite profiling experiments

Modelling hybrid effects on the stiffness of aligned discontinuous composites with hybrid fibre-types

Hybrid discontinuous composites offer the possibility to tailor the composite properties for specific applications, improve their manufacturability, and reduce cost by introducing cheaper fibres. However, the mechanical behaviour of hybrid composites often shows hybrid effects which cannot be modelled by the rule-of-mixtures and are therefore challenging to predict and explain. This paper presents models to calculate the Young's modulus of different discontinuous hybrid composites, which is affected by such hybrid effects. The models are based on shear-lag and consider two types of hybrid discontinuous architectures: (i) a deterministic “brick-and-mortar” architecture consisting of perfectly staggered platelets with two different Young's moduli and thicknesses, and (ii) a stochastic architecture of aligned fibres with two different Young's moduli and diameters, with randomly allocated fibre-ends and random or organised intermingling. The models show good agreement with numerical and experimental validations; their results show that hybrid interactions between different types of fibres or platelets reduce the Young's modulus of hybrid discontinuous composites, which justifies the negative hybrid effects observed

Structural Annotation and Elucidation of Conjugated Phenolic Compounds in Black, Green, and White Tea Extracts

Advanced analytical approaches consisting of both LC-LTQ-Orbitrap Fourier transformed (FT)-MS and LC-time-of-flight-(TOF)-MS coupled to solid-phase extraction (SPE) NMR were used to obtain more insight into the complex phenolic composition of tea. On the basis of the combined structural information from (i) accurate mass fragmentation spectra, derived by using LC-Orbitrap FTMS^<i>n</i>, and (ii) proton NMR spectra, derived after LC-TOFMS triggered SPE trapping of selected compounds, 177 phenolic compounds were annotated. Most of these phenolics were glycosylated and acetylated derivatives of flavan-3-ols and flavonols. Principal component analysis based on the relative abundance of the annotated phenolic compounds in 17 commercially available black, green, and white tea products separated the black teas from the green and white teas, with epicatechin-3,5-di-<i>O</i>-gallate and prodelphinidin-<i>O</i>-gallate being among the main discriminators. The results indicate that the combined use of LC-LTQ-Orbitrap FTMS and LC-TOFMS-SPE-NMR leads to a more comprehensive metabolite description and comparison of tea and other plant samples

Metabolite Identification Using Automated Comparison of High-Resolution Multistage Mass Spectral Trees

Multistage mass spectrometry (MS^<i>n</i>) generating so-called spectral trees is a powerful tool in the annotation and structural elucidation of metabolites and is increasingly used in the area of accurate mass LC/MS-based metabolomics to identify unknown, but biologically relevant, compounds. As a consequence, there is a growing need for computational tools specifically designed for the processing and interpretation of MS^<i>n</i> data. Here, we present a novel approach to represent and calculate the similarity between high-resolution mass spectral fragmentation trees. This approach can be used to query multiple-stage mass spectra in MS spectral libraries. Additionally the method can be used to calculate structure–spectrum correlations and potentially deduce substructures from spectra of unknown compounds. The approach was tested using two different spectral libraries composed of either human or plant metabolites which currently contain 872 MS^<i>n</i> spectra acquired from 549 metabolites using Orbitrap FTMS^<i>n</i>. For validation purposes, for 282 of these 549 metabolites, 765 additional replicate MS^<i>n</i> spectra acquired with the same instrument were used. Both the dereplication and de novo identification functionalities of the comparison approach are discussed. This novel MS^<i>n</i> spectral processing and comparison approach increases the probability to assign the correct identity to an experimentally obtained fragmentation tree. Ultimately, this tool may pave the way for constructing and populating large MS^<i>n</i> spectral libraries that can be used for searching and matching experimental MS^<i>n</i> spectra for annotation and structural elucidation of unknown metabolites detected in untargeted metabolomics studies

Phylogenetic analysis of Asteraceae GAO genes and five chicory CYP71 P450 ESTs.

<p>Chicory candidate 3368 was later identified as <i>Cichorium intybus costunolide synthase</i> (<i>CiCOS</i>). Amino acid seuqences of <i>GAOs</i> were obtained from cDNAs deposited at the NCBI. <i>LsGAO</i> germacrene A oxidase from <i>Lactuca sativa</i> (GU198171) or from <i>Cichorium intybus</i> (<i>Ci</i>; GU256644), <i>Helianthus annuus</i> (<i>Ha</i>; GU256646), <i>Saussurea costus</i> (<i>Sc</i>; GU256645) and <i>Barnadesia. spinosa</i> (<i>Bs</i>; GU256647). Bootstrap values are shown in frequency values from 1000 replicates.</p

Germacrene A production in yeast.

<p>A yeast culture transformed by either <i>CiGAS-long</i>, <i>CiGAS-short </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0023255#pone.0023255-Bouwmeester1" target="_blank">[20]</a>, or <i>TpGAS </i><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0023255#pone.0023255-Majdi1" target="_blank">[23]</a>. Induced yeast culture medium was extracted and analysed by GC-MS.</p

Structural Elucidation and Quantification of Phenolic Conjugates Present in Human Urine after Tea Intake

In dietary polyphenol exposure studies, annotation and identification of urinary metabolites present at low (micromolar) concentrations are major obstacles. To determine the biological activity of specific components, it is necessary to have the correct structures and the quantification of the polyphenol-derived conjugates present in the human body. We present a procedure for identification and quantification of metabolites and conjugates excreted in human urine after single bolus intake of black or green tea. A combination of a solid-phase extraction (SPE) preparation step and two high pressure liquid chromatography (HPLC)-based analytical platforms was used, namely, accurate mass fragmentation (HPLC-FTMSⁿ) and mass-guided SPE-trapping of selected compounds for nuclear magnetic resonance spectroscopy (NMR) measurements (HPLC-TOFMS-SPE-NMR). HPLC-FTMSⁿ analysis led to the annotation of 138 urinary metabolites, including 48 valerolactone and valeric acid conjugates. By combining the results from MSⁿ fragmentation with the one-dimensional (1D)-¹H NMR spectra of HPLC-TOFMS-SPE-trapped compounds, we elucidated the structures of 36 phenolic conjugates, including the glucuronides of 3′,4′-di- and 3′,4′,5′-trihydroxyphenyl-γ-valerolactone, three urolithin glucuronides, and indole-3-acetic acid glucuronide. We also obtained 26 h-quantitative excretion profiles for specific valerolactone conjugates. The combination of the HPLC-FTMSⁿ and HPLC-TOFMS-SPE-NMR platforms results in the efficient identification and quantification of less abundant phenolic conjugates down to nanomoles of trapped amounts of metabolite corresponding to micromolar metabolite concentrations in urine

Headspace analysis of volatiles emitted from agro-infiltrated <i>Nicotiana benthamiana</i> leaves.

<p>A, GC-MS chromatograms are shown for the volatiles emitted from <i>N.benthamiana</i> leaves infiltrated with the indicated genes. Line a is a negative control, line b and c display the different amount of compound 1 (germacrene A) produced by <i>N. benthamiana</i> leaves infiltrated with <i>TpGAS</i> with different targeting signals: <i>mTpGAS</i>, mitochondrial targeting; c<i>TpGAS</i>, cytosolic targeting. Line d shows that compound 1 which is produced upon <i>mTpGAS</i> agro-infiltration disappears upon agro-infiltration with <i>CiGAO</i>. Agro-infiltration with <i>CiGAO</i> alone does not induce any volatile formation (Line e). B, the mass fragmentation patterns of compound 1 (a) and a β-elemene from the Wiley library (b). C, cope rearrangement of germacrene A to β-elemene by heat.</p