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

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...

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Autores principales: Gorzolka, Karin, Kölling, Jan, Nattkemper, Tim W., Niehaus, Karsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4777520/
https://www.ncbi.nlm.nih.gov/pubmed/26938880
http://dx.doi.org/10.1371/journal.pone.0150208
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author Gorzolka, Karin
Kölling, Jan
Nattkemper, Tim W.
Niehaus, Karsten
author_facet Gorzolka, Karin
Kölling, Jan
Nattkemper, Tim W.
Niehaus, Karsten
author_sort Gorzolka, Karin
collection PubMed
description 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.
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spelling pubmed-47775202016-03-10 Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging Gorzolka, Karin Kölling, Jan Nattkemper, Tim W. Niehaus, Karsten PLoS One Research Article 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. Public Library of Science 2016-03-03 /pmc/articles/PMC4777520/ /pubmed/26938880 http://dx.doi.org/10.1371/journal.pone.0150208 Text en © 2016 Gorzolka et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Gorzolka, Karin
Kölling, Jan
Nattkemper, Tim W.
Niehaus, Karsten
Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging
title Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging
title_full Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging
title_fullStr Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging
title_full_unstemmed Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging
title_short Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging
title_sort spatio-temporal metabolite profiling of the barley germination process by maldi ms imaging
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4777520/
https://www.ncbi.nlm.nih.gov/pubmed/26938880
http://dx.doi.org/10.1371/journal.pone.0150208
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