Unique aspects of the structure and dynamics of elementary Iβ cellulose microfibrils revealed by computational simulations

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Abstract

The question of how many chains an elementary cellulose microfibril contains is critical to understanding the molecular mechanism(s) of cellulose biosynthesis and regulation. Given the hexagonal nature of the cellulose synthase rosette, it is assumed that the number of chains must be a multiple of six. We present molecular dynamics simulations on three different models of Ib cellulose microfibrils, 18, 24, and 36 chains, to investigate their structure and dynamics in a hydrated environment. The 36-chain model stays in a conformational space that is very similar to the initial crystalline phase, while the 18- and 24-chain models sample a conformational space different from the crystalline structure yet similar to conformations observed in recent high-temperature molecular dynamics simulations. Major differences in the conformations sampled between the different models result from changes to the tilt of chains in different layers, specifically a second stage of tilt, increased rotation about the O2-C2 dihedral, and a greater sampling of non-TG exocyclic conformations, particularly the GG conformation in center layers and GT conformation in solvent-exposed exocyclic groups. With a reinterpretation of nuclear magnetic resonance data, specifically for contributions made to the C6 peak, data from the simulations suggest that the 18- and 24-chain structures are more viable models for an elementary cellulose microfibril, which also correlates with recent scattering and diffraction experimental data. These data inform biochemical and molecular studies that must explain how a six-particle cellulose synthase complex rosette synthesizes microfibrils likely comprised of either 18 or 24 chains.

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Oehme, D. P., Downton, M. T., Doblin, M. S., Wagner, J., Gidley, M. J., & Bacic, A. (2015). Unique aspects of the structure and dynamics of elementary Iβ cellulose microfibrils revealed by computational simulations. Plant Physiology, 168(1), 3–17. https://doi.org/10.1104/pp.114.254664

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