Wancheng Zhao, Debkumar Debnath, Isha Gautam, Liyanage D. Fernando, Tuo Wang
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引用次数: 0
Abstract
Solid-state nuclear magnetic resonance (ssNMR) measurements of intact cell walls and cellular samples often generate spectra that are difficult to interpret due to the presence of many coexisting glycans and the structural polymorphism observed in native conditions. To overcome this analytical challenge, we present a statistical approach for analyzing carbohydrate signals using high-resolution ssNMR data indexed in a carbohydrate database. We generate simulated spectra to demonstrate the chemical shift dispersion and compare this with experimental data to facilitate the identification of important fungal and plant polysaccharides, such as chitin and glucans in fungi and cellulose, hemicellulose, and pectic polymers in plants. We also demonstrate that chemically distinct carbohydrates from different organisms may produce almost identical signals, highlighting the need for high-resolution spectra and validation of resonance assignments. Our study provides a means to differentiate the characteristic signals of major carbohydrates and allows us to summarize currently undetected polysaccharides in plants and fungi, which may inspire future investigations.
期刊介绍:
MRC is devoted to the rapid publication of papers which are concerned with the development of magnetic resonance techniques, or in which the application of such techniques plays a pivotal part. Contributions from scientists working in all areas of NMR, ESR and NQR are invited, and papers describing applications in all branches of chemistry, structural biology and materials chemistry are published.
The journal is of particular interest not only to scientists working in academic research, but also those working in commercial organisations who need to keep up-to-date with the latest practical applications of magnetic resonance techniques.