Localization and signal intensities of hydroxycinnamic acid derivatives and hordatines in germinating barley.

<p>Top: Localization of p-coumaroylagmatine (CA) as representative for hydroxycinnamic acid amides and hordatine B as representative for hordatines that co-localized to hordatine B when occurring in the same modification state. Intensity maps depict the non-glycosylated (<i>m/z</i> 581), glycosylated (<i>m/z</i> 743), and disaccharide-modified form (<i>m/z</i> 905) at three time points during germination (0d: non-germinated barley, G3d: three days germinated, G5d: five days germination) in longitudinal and transversal section plane. Hordatines were not detected in cross sections in non-germinated barley. The last panel shows an overlay of the three modification forms. Ion intensities were normalized to the TIC, the highest relative intensity was set to 100%. Middle panel: Average mass spectra from annotated embryo measurement regions (right) in non-germinated (green), three days (blue) and five days (red) germinated barley. Bottom: Mass spectrum with indicated peaks of hydroxycinnamic acid amides as hordatine precursors (<i>m/z</i> 250–350) and of hordatine A, B, C, and D (D not detected, grey font), hydroxylated hordatines (-OH), and hexose-modified derivates (Hex / 2 Hex) at <i>m/z</i> 550–1000. CA: coumaroylagmatine, FA: feruloylagmatine, CA-OH / FA-OH: hydroxylated CA and FA.</p

Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging

<div><p>MALDI mass spectrometry imaging was performed to localize metabolites during the first seven days of the barley germination. Up to 100 mass signals were detected of which 85 signals were identified as 48 different metabolites with highly tissue-specific localizations. Oligosaccharides were observed in the endosperm and in parts of the developed embryo. Lipids in the endosperm co-localized in dependency on their fatty acid compositions with changes in the distributions of diacyl phosphatidylcholines during germination. 26 potentially antifungal hordatines were detected in the embryo with tissue-specific localizations of their glycosylated, hydroxylated, and O-methylated derivates. In order to reveal spatio-temporal patterns in local metabolite compositions, multiple MSI data sets from a time series were analyzed in one batch. This requires a new preprocessing strategy to achieve comparability between data sets as well as a new strategy for unsupervised clustering. The resulting spatial segmentation for each time point sample is visualized in an interactive cluster map and enables simultaneous interactive exploration of all time points. Using this new analysis approach and visualization tool germination-dependent developments of metabolite patterns with single MS position accuracy were discovered. This is the first study that presents metabolite profiling of a cereals’ germination process over time by MALDI MSI with the identification of a large number of peaks of agronomically and industrially important compounds such as oligosaccharides, lipids and antifungal agents. Their detailed localization as well as the MS cluster analyses for on-tissue metabolite profile mapping revealed important information for the understanding of the germination process, which is of high scientific interest.</p></div

Unsupervised spatial segmentation of eight independent MALDI MSI analyses covering the first days of barley germination using WHIDE.

<p>A: Image scans with outlines of labeled seed compartments. B: Cluster analysis of all mass spectra of the whole grain areas. C: Cluster analysis of all mass spectra of the embryo areas as annotated in A. D: Cluster analysis of all mass spectra of the endosperm as annotated in A. E: Effect of the cluster granularity (7, 21, 56 clusters) on mapping results, exemplarily shown for four days germinated barley (G4d) from analysis B. The visualized cluster, granularity was set to 7 in A, B, and C to assign clear cluster profiles (right panels). 93 <i>m/z</i> values were selected for spatial segmentation in all analyses. Their contribution to the distinct clusters is indicated by the bar size in the right panels; for <i>m/z</i> identification see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150208#pone.0150208.t001" target="_blank">Table 1</a>. For an interactive exploration of the results in WHIDE see <a href="https://ani.cebitec.uni-bielefeld.de/barleymsi" target="_blank">https://ani.cebitec.uni-bielefeld.de/barleymsi</a>.</p

The barley germination process: Seedling development and sampling time points.

<p>A) Time scheme of mini malting of the <i>Optic</i> barley at 16°C for the collection of samples. Arrows indicate sampling time points with their sample name. 0d: raw barley, S: steeping, G: germination day, K: kilned malt (K not used for MSI). W: water, A: air rest, K1: kilning at 45°C (7h), K2: kilning at 65°C (17 h). B) Growth of the barley seeds during malting. Barley (0d, <i>T</i> = 1), steeped barley (S1d, <i>T</i> = 2), three of the five time points during germination (G1d, G3d, G5d (<i>T</i> = 4,6,8)) and final kilned malt (K1d) are shown as representatives. Main seed organs and compartments are indicated at the raw barley seed.</p

Detected and identified compounds from MS imaging of barley seeds.

<p>Detected and identified compounds from MS imaging of barley seeds.</p

Localization of oligosaccharides in barley during germination.

<p>A) Cryo-sections of non-germinated (0d) and three day germinated (G3d) barley. B) Average mass spectrum of all MS acquired from germinated barley with [M+Na]⁺ (red) and [M+K]⁺ (blue) ions of oligosaccharides. *DP: degree of polymerization. C) Intensity heat maps of oligosaccharides with three, six, and nine hexoses in sodium [M+Na]⁺ and potassium [M+H]⁺ adducts in ungerminated barley (0d) and after three days of germination (G3d). MS intensities were normalized to the TIC of each mass spectrum; the highest relative intensity of all MS was set to 100%. The distributions of these compounds at all time points of the germination process are provided as <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0150208#pone.0150208.s005" target="_blank">S5 Fig</a>.</p

Discovering Regulated Metabolite Families in Untargeted Metabolomics Studies

The identification of metabolites by mass spectrometry constitutes a major bottleneck which considerably limits the throughput of metabolomics studies in biomedical or plant research. Here, we present a novel approach to analyze metabolomics data from untargeted, data-independent LC-MS/MS measurements. By integrated analysis of MS¹ abundances and MS/MS spectra, the identification of regulated metabolite families is achieved. This approach offers a global view on metabolic regulation in comparative metabolomics. We implemented our approach in the web application “MetFamily”, which is freely available at http://msbi.ipb-halle.de/MetFamily/. MetFamily provides a dynamic link between the patterns based on MS¹-signal intensity and the corresponding structural similarity at the MS/MS level. Structurally related metabolites are annotated as metabolite families based on a hierarchical cluster analysis of measured MS/MS spectra. Joint examination with principal component analysis of MS¹ patterns, where this annotation is preserved in the loadings, facilitates the interpretation of comparative metabolomics data at the level of metabolite families. As a proof of concept, we identified two trichome-specific metabolite families from wild-type tomato <i>Solanum habrochaites</i> LA1777 in a fully unsupervised manner and validated our findings based on earlier publications and with NMR