A simple and highly efficient protocol for 13C-labeling of plant cell wall for structural and quantitative analyses via solid-state nuclear magnetic resonance - Tasleem Javaid; Akshayaa Venkataraghavan; Matrika Bhattarai; Debkumar Debnath; Wancheng Zhao; Tuo Wang; Ahmed Faik (Plant Methods)
Abstract Background Plant cell walls are made of a complex network of interacting polymers that play a critical role in plant development and responses to environmental changes. Thus, improving plant biomass and fitness requires the elucidation of the structural organization of plant cell walls in their native environment. The 13C-based multi-dimensional solid-state nuclear magnetic resonance (ssNMR) has been instrumental in revealing the structural information of plant cell walls through 2D and 3D correlation spectral analyses. However, the requirement of enriching plants with 13C limits the applicability of this method. To our knowledge, there is only a very limited set of methods currently available that achieve high levels of 13C-labeling of plant materials using 13CO2, and most of them require large amounts of 13CO2 in larger growth chambers. Results In this study, a simplified protocol for 13C-labeling of plant materials is introduced that allows ca 60% labeling of the cell walls, as quantified by comparison with commercially labeled samples. This level of 13C-enrichment is sufficient for all conventional 2D and 3D correlation ssNMR experiments for detailed analysis of plant cell wall structure. The protocol is based on a convenient and easy setup to supply both 13C-labeled glucose and 13CO2 using a vacuum-desiccator. The protocol does not require large amounts of 13CO2. Conclusion This study shows that our 13C-labeling of plant materials can make the accessibility to ssNMR technique easy and affordable. The derived high-resolution 2D and 3D correlation spectra are used to extract structural information of plant cell walls. This helps to better understand the influence of polysaccharide-polysaccharide interaction on plant performance and allows for a more precise parametrization of plant cell wall models.