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Identification of lignin and polysaccharide modifications in Populus wood by chemometric analysis of 2D NMR spectra from dissolved cell walls
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
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2009 (English)In: Molecular Plant, ISSN 1674-2052, Vol. 2, no 5, 933-942 p.Article in journal (Refereed) Published
Abstract [en]

2D (13)C-(1)H HSQC NMR spectroscopy of acetylated cell walls in solution gives a detailed fingerprint that can be used to assess the chemical composition of the complete wall without extensive degradation. We demonstrate how multivariate analysis of such spectra can be used to visualize cell wall changes between sample types as high-resolution 2D NMR loading spectra. Changes in composition and structure for both lignin and polysaccharides can subsequently be interpreted on a molecular level. The multivariate approach alleviates problems associated with peak picking of overlapping peaks, and it allows the deduction of the relative importance of each peak for sample discrimination. As a first proof of concept, we compare Populus tension wood to normal wood. All well established differences in cellulose, hemicellulose, and lignin compositions between these wood types were readily detected, confirming the reliability of the multivariate approach. In a second example, wood from transgenic Populus modified in their degree of pectin methylesterification was compared to that of wild-type trees. We show that differences in both lignin and polysaccharide composition that are difficult to detect with traditional spectral analysis and that could not be a priori predicted were revealed by the multivariate approach. 2D NMR of dissolved cell wall samples combined with multivariate analysis constitutes a novel approach in cell wall analysis and provides a new tool that will benefit cell wall research.

Place, publisher, year, edition, pages
2009. Vol. 2, no 5, 933-942 p.
Keyword [en]
Aspen, biostatistics, cell walls, multivariate data analysis, NMR spectroscopy, tension wood
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:umu:diva-26780DOI: 10.1093/mp/ssp047PubMedID: 19825670OAI: oai:DiVA.org:umu-26780DiVA: diva2:274104
Available from: 2009-10-27 Created: 2009-10-27 Last updated: 2013-09-11Bibliographically approved
In thesis
1. Multivariate Analysis of 2D-NMR Spectroscopy: Applications in wood science and metabolomics
Open this publication in new window or tab >>Multivariate Analysis of 2D-NMR Spectroscopy: Applications in wood science and metabolomics
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Wood is our most important renewable resource. We need better quality and quantity both according to the wood itself and the processes that are using wood as a raw material. Hence, the understanding of the chemical composition of the wood is of high importance. Improved and new methods for analyzing wood are important to achieve better knowledge about both refining processes and raw material. The combination of NMR and multivariate analyses (MVA) is a powerful method for these analyses but so far it has been limited mainly to 1D NMR. In this project, we have developed methods for combining 2D NMR and MVA in both wood analysis and metabolomics. This combination was used to compare samples from normal wood and tension wood, and also trees with a down regulation of a pectin responsible gene. Dissolving pulp was also examined using the same combination of 2D-NMR and MVA, together with FT-IR and solid state 13C CP-MAS NMR. Here we focused on the difference between wood type (softwood and hardwood), process type (sulfite and sulfate) and viscosity. These methods confirmed and added knowledge about the dissolving pulp. Also reactivity was compared in relation to morphology of the cellulose and pulp composition. Based on the method and software used in the wood analysis projects, a new method called HSQC-STOCSY was developed. This method is especially suited for assignment of substances in complex mixtures. Peaks in 2D NMR spectra that correlate between different samples are plotted in correlation plots resembling regular NMR spectra. These correlation plots have great potential in identifying individual components in complex mixtures as shown here in a metabolic data set. This method could potentially also be used in other areas such as drug/target analyses, protein dynamics and assignment of wood spectra.

Place, publisher, year, edition, pages
Umeå: Umeå Universitet, 2013. 56 p.
Keyword
2D NMR, HSQC, cellulose, ligning, STOCSY, HSQC-STOCSY, crystallinity
National Category
Chemical Sciences
Research subject
biological chemistry
Identifiers
urn:nbn:se:umu:diva-80201 (URN)978-91-7459-728-8 (ISBN)
Public defence
2013-10-04, KBC-huset, KB3B1, Umeå universitet, Umeå, 13:00 (Swedish)
Opponent
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Available from: 2013-09-13 Created: 2013-09-11 Last updated: 2013-09-11Bibliographically approved

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