Spatio-temporal analysis of metabolite profiles during barley germination

Kölling J, Gorzolka K, Niehaus K, Nattkemper TW. Spatio-temporal analysis of metabolite profiles during barley germination. Presented at the German Conference on Bioinformatics (GCB), Bielefeld, Germany

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

Gorzolka K, Kölling J, Nattkemper TW, Niehaus K. Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging. PLOS ONE. 2016;11(3): e0150208.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

Calcium‐dependent protein kinase 5 links calcium signaling with N‐hydroxy‐l‐pipecolic acid‐ and SARD1‐dependent immune memory in systemic acquired resistance

Systemic acquired resistance (SAR) prepares infected plants for faster and stronger defense activation upon subsequent attacks. SAR requires an information relay from primary infection to distal tissue and the initiation and maintenance of a self‐maintaining phytohormone salicylic acid (SA)‐defense loop. In spatial and temporal resolution, we show that calcium‐dependent protein kinase CPK5 contributes to immunity and SAR. In local basal resistance, CPK5 functions upstream of SA synthesis, perception, and signaling. In systemic tissue, CPK5 signaling leads to accumulation of SAR‐inducing metabolite N‐hydroxy‐L‐pipecolic acid (NHP) and SAR marker genes, including Systemic Acquired Resistance Deficient 1 (SARD1) Plants of increased CPK5, but not CPK6, signaling display an ‘enhanced SAR’ phenotype towards a secondary bacterial infection. In the sard1‐1 background, CPK5‐mediated basal resistance is still mounted, but NHP concentration is reduced and enhanced SAR is lost. The biochemical analysis estimated CPK5 half maximal kinase activity for calcium, K50 [Ca2+], to be c. 100 nM, close to the cytoplasmic resting level. This low threshold uniquely qualifies CPK5 to decode subtle changes in calcium, a prerequisite to signal relay and onset and maintenance of priming at later time points in distal tissue. Our data explain why CPK5 functions as a hub in basal and systemic plant immunity

Spatio-temporal investigation of the barley malting process by proteome, metabolome, and MALDI MS imgaging analyses

Gorzolka K. Spatio-temporal investigation of the barley malting process by proteome, metabolome, and MALDI MS imgaging analyses. Bielefeld; 2013

MALDI mass spectrometry imaging of formalin-fixed paraffin-embedded tissues in clinical research

The molecular investigation of archived formalin-fixed, paraffin-embedded (FFPE) tissue samples provides the chance to obtain molecular patterns as indicatives for treatment and clinical end points. MALDI mass spectrometry imaging is capable of localizing molecules like proteins and peptides in tissue sections and became a favorite platform for the targeted and non-targeted approaches, especially in clinical investigations for biomarker research. In FFPE tissues the recovery of proteomic information is constrained by fixation-induced cross-links of proteins. The promising new insights obtained from FFPE in combination with the comprehensive patients’ data caused much progress in the optimization of MS imaging protocols to investigate FFPE samples. This review presents the past and current research in MALDI MS imaging of FFPE tissues, demonstrating the improvement of analyses, their actual limitations, but also the promising future perspectives for histopathological and tissue-based research

Computational workflow to study the seasonal variation of secondary metabolites in nine different bryophytes

In Eco-Metabolomics interactions are studied of non-model organisms in their natural environment and relations are made between biochemistry and ecological function. Current challenges when processing such metabolomics data involve complex experiment designs which are often carried out in large field campaigns involving multiple study factors, peak detection parameter settings, the high variation of metabolite profiles and the analysis of non-model species with scarcely characterised metabolomes. Here, we present a dataset generated from 108 samples of nine bryophyte species obtained in four seasons using an untargeted liquid chromatography coupled with mass spectrometry acquisition method (LC/MS). Using this dataset we address the current challenges when processing Eco-Metabolomics data. Here, we also present a reproducible and reusable computational workflow implemented in Galaxy focusing on standard formats, data import, technical validation, feature detection, diversity analysis and multivariate statistics. We expect that the representative dataset and the reusable processing pipeline will facilitate future studies in the research field of Eco-Metabolomics

Seasonal variation of secondary metabolites in nine different bryophytes

Bryophytes occur in almost all land ecosystems and contribute to global biogeochemical cycles, ecosystem functioning, and influence vegetation dynamics. As growth and biochemistry of bryophytes are strongly dependent on the season, we analyzed metabolic variation across seasons with regard to ecological characteristics and phylogeny. Using bioinformatics methods, we present an integrative and reproducible approach to connect ecology with biochemistry. Nine different bryophyte species were collected in three composite samples in four seasons. Untargeted liquid chromatography coupled with mass spectrometry (LC/MS) was performed to obtain metabolite profiles. Redundancy analysis, Pearson's correlation, Shannon diversity, and hierarchical clustering were used to determine relationships among species, seasons, ecological characteristics, and hierarchical clustering. Metabolite profiles of Marchantia polymorpha and Fissidens taxifolius which are species with ruderal life strategy (R‐selected) showed low seasonal variability, while the profiles of the pleurocarpous mosses and Grimmia pulvinata which have characteristics of a competitive strategy (C‐selected) were more variable. Polytrichum strictum and Plagiomnium undulatum had intermediary life strategies. Our study revealed strong species‐specific differences in metabolite profiles between the seasons. Life strategies, growth forms, and indicator values for light and soil were among the most important ecological predictors. We demonstrate that untargeted Eco‐Metabolomics provide useful biochemical insight that improves our understanding of fundamental ecological strategies

Darrprozess: Heterogene Malztrocknung und ihre Folgen

Gorzolka K, Booer C, Walker C, Niehaus K. Darrprozess: Heterogene Malztrocknung und ihre Folgen. Brauwelt. 2014;(24-25):738-742.MALZHOMOGENITÄT | Der Darrprozess ist ein elementarer Vorgang bei der Malzherstellung. Er beendet die Keimungsphase der Mälzung durch Wasserentzug und macht das Malz lagerfähig. Außerdem trägt er zur Bildung von Farb- und Aromakomponenten bei. Durch die Temperatur, die Feuchtigkeit und die Dauer des Darrens wird die Malzsorte festgelegt. Der vorliegende Beitrag untersucht die Auswirkungen verzögerter Trocknungsbedingungen in großen Darrchargen mit hohen Schichtenlagen auf die Aroma- und Metabolit-Profile des Malzes

Interactive and dynamic web-based visual exploration of high dimensional bioimages with real time clustering

Rathke M, Kölling J, Gorzolka K, Niehaus K, Nattkemper TW. Interactive and dynamic web-based visual exploration of high dimensional bioimages with real time clustering. Presented at the German Conference on Bioinformatics (GCB), Bielefeld, Germany.Web browsers and web applications have become common tools in bioinformatics over the past decades. Many existing web applications revolve around server-client interaction, where heavy computational tasks are often outsourced to the server and the presentation is handled on the the client-side. However, more recent additions to the web browser technology embrace the capability of handling more complex operations on the client-side itself, cutting out most of the server-client interaction except for data loading. This paper contributes to the exploration of the potential of approaches to implement and speed up computational expensive tasks, like image cluster analysis, within a client-side web browser environment. The experimental results, incorporating the well known k-means algorithm which serves as a platform for various parallelization approaches, indicate the possibility to achieve real time image clustering. Especially for the available MALDI-MSI data set the results look promising. Despite good results of multi-threading approaches, algorithmic approaches appear to be relevant too. Therefore advancements in accelerating the k-means algorithm itself are considered