Journal of Energy Bioscience 2024, Vol.15, No.1, 28-31 http://bioscipublisher.com/index.php/jeb 28 Scientific Commentary Open Access Deciphering the Structural Complexity of Populus Secondary Cell Walls: Implications for Biomass Conversion Efficiency Francis Burke The BioSci Publisher, Richmond, British Columbia, Canada Corresponding email: Francis.burke@sophiapublisher.com Journal of Energy Bioscience, 2024, Vol.15, No.1 doi: 10.5376/jeb.2024.15.0004 Received: 05 Jan., 2024 Accepted: 08 Feb., 2024 Published: 19 Feb., 2024 Copyright © 2024 Burke, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Burke F., 2024, Deciphering the structural complexity of Populus secondary cell walls: implications for biomass conversion efficiency, Journal of Energy Bioscience, 15(1): 28-31 (doi: 10.5376/jeb.2024.15.0004) The paper titled "Atomistic, macromolecular model of the Populus secondary cell wall informed by solid-state NMR" was published on January 3, 2024, in the open-access journal Science Advances, under the Science Publishing Group. The authors, Bennett Addison, Lintao Bu, Vivek Bharadwaj, Meagan F. Crowley, Anne E. Harman-Ware, Michael F. Crowley, Yannick J. Bomble, and Peter N. Ciesielski are from National Renewable Energy Laboratory and the Colorado School of Mines in Golden, CO, USA. The study presents an atomistic macromolecular model of the secondary cell wall (SCW) in Populus wood, focusing on the interactions and configurations of cellulose, hemicelluloses, and lignin. Utilizing solid-state nuclear magnetic resonance (ssNMR) measurements, the research investigates the structural configurations and intermolecular interactions within the SCW. This information is used to develop and refine molecular models through molecular dynamics (MD) simulations, enhancing the understanding of the SCW's architecture and informing biomass deconstruction strategies. 1 Interpretation of Experimental Data The research highlight the spatial arrangement and interactions of cellulose, xylan, and lignin within the SCW. The 1D 1H-13C MultiCP-MAS ssNMR spectrum identifies distinct environments for cellulose and indicates the presence of acetylated xylan and lignin. Selective 1D MultiCP-DARR difference data quantify polymer-polymer contacts at the nanometer scale, showing how magnetization moves between carbon environments, providing crucial distance information for constructing accurate molecular models. Figure 1 presents a comprehensive analysis of lignified Populus secondary cell walls (SCWs) using 1D 1H-13C MultiCP-MAS solid-state NMR (ssNMR). The spectrum delineates the chemical environments of the primary polymers: cellulose (gray), xylan (blue), and lignin (green), with specific regions assigned to their characteristic peaks. Cellulose's assignments include peaks for C1, C2, C3, C5, and C6 carbons. Xylan is highlighted by signals corresponding to acetylation and glucuronic acid residues. Lignin's spectrum reveals syringyl (S) and guaiacyl (G) units, identified through their aromatic and side-chain carbons, including the notable β-O-4 linkages. The black trace represents the raw data, while the red trace shows the fitted model, illustrating the accuracy of the spectral deconvolution informed by the combined 1D and 2D ssNMR data. This detailed spectral analysis aids in understanding the complex structural composition and interactions within Populus SCWs. Figure 3 illustrates atomistic models of Populus secondary cell walls (SCWs) with various arrangements of cellulose, xylan, and lignin. The left panel shows several model variants, named based on the arrangement of hemicellulose and lignin. For instance, model "a" has all xylan bound to cellulose, while "b" models have 70% xylan bound to cellulose and 30% interspersed with lignin. The right panel presents a polar plot comparing the percentage of sink atoms within 1 nm of source atoms in these models against experimental ssNMR spin-diffusion data. The models vary in their alignment with experimental data, indicating different structural proximities within SCWs.
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