6 research outputs found

    Selective One-Dimensional \u3csup\u3e13\u3c/sup\u3eC-\u3csup\u3e13\u3c/sup\u3eC Spin-Diffusion Solid-State Nuclear Magnetic Resonance Methods to Probe Spatial Arrangements in Biopolymers including Plant Cell Walls, Peptides, and Spider Silk

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    © 2020 American Chemical Society. All rights reserved. Two-dimensional (2D) and 3D through-space 13C-13C homonuclear spin-diffusion techniques are powerful solid-state nuclear magnetic resonance (NMR) tools for extracting structural information from 13C-enriched biomolecules, but necessarily long acquisition times restrict their applications. In this work, we explore the broad utility and underutilized power of a chemical shift-selective one-dimensional (1D) version of a 2D 13C-13C spin-diffusion solid-state NMR technique. The method, which is called 1D dipolar-assisted rotational resonance (DARR) difference, is applied to a variety of biomaterials including lignocellulosic plant cell walls, microcrystalline peptide fMLF, and black widow dragline spider silk. 1D 13C-13C spin-diffusion methods described here apply in select cases in which the 1D 13C solid-state NMR spectrum displays chemical shift-resolved moieties. This is analogous to the selective 1D nuclear Overhauser effect spectroscopy (NOESY) experiment utilized in liquid-state NMR as a faster (1D instead of 2D) and often less ambiguous (direct sampling of the time domain data, coupled with increased signal averaging) alternative to 2D NOESY. Selective 1D 13C-13C spin-diffusion methods are more time-efficient than their 2D counterparts such as proton-driven spin diffusion (PDSD) and dipolar-assisted rotational resonance. The additional time gained enables measurements of 13C-13C spin-diffusion buildup curves and extraction of spin-diffusion time constants TSD, yielding detailed structural information. Specifically, selective 1D DARR difference buildup curves applied to 13C-enriched hybrid poplar woody stems confirm strong spatial interaction between lignin and acetylated xylan polymers within poplar plant secondary cell walls, and an interpolymer distance of ∼0.45-0.5 nm was estimated. Additionally, Tyr/Gly long-range correlations were observed on isotopically enriched black widow spider dragline silks

    High Throughput Screening Technologies in Biomass Characterization

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    Biomass analysis is a slow and tedious process and not solely due to the long generation time for most plant species. Screening large numbers of plant variants for various geno-, pheno-, and chemo-types, whether naturally occurring or engineered in the lab, has multiple challenges. Plant cell walls are complex, heterogeneous networks that are difficult to deconstruct and analyze. Macroheterogeneity from tissue types, age, and environmental factors makes representative sampling a challenge and natural variability generates a significant range in data. Using high throughput (HTP) methodologies allows for large sample sets and replicates to be examined, narrowing in on more precise data for various analyses. This review provides a comprehensive survey of high throughput screening as applied to biomass characterization, from compositional analysis of cell walls by NIR, NMR, mass spectrometry, and wet chemistry to functional screening of changes in recalcitrance via HTP thermochemical pretreatment coupled to enzyme hydrolysis and microscale fermentation. The advancements and development of most high-throughput methods have been achieved through utilization of state-of-the art equipment and robotics, rapid detection methods, as well as reduction in sample size and preparation procedures. The computational analysis of the large amount of data generated using high throughput analytical techniques has recently become more sophisticated, faster and economically viable, enabling a more comprehensive understanding of biomass genomics, structure, composition, and properties. Therefore, methodology for analyzing large datasets generated by the various analytical techniques is also covered

    The effect of coumaryl alcohol incorporation on the structure and composition of lignin dehydrogenation polymers

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    Abstract Background Lignin dehydrogenation polymers (DHPs) are polymers generated from phenolic precursors for the purpose of studying lignin structure and polymerization processes Methods Here, DHPs were synthesized using a Zutropfverfahren method with horseradish peroxidase and three lignin monomers, sinapyl (S), coumaryl (H), and coniferyl (G) alcohols, in the presence of hydrogen peroxide. The H monomer was reacted with G and a 1:1 molar mixture of S:G monomers at H molar compositions of 0, 5, 10, and 20 mol% to study how the presence of the H monomer affected the structure and composition of the recovered polymers. Results At low H concentrations, solid-state NMR spectra suggest that the H and G monomers interact to form G:H polymers that have a lower average molecular weight than the solely G-based polymer or the G:H polymer produced at higher H concentrations. Solid-state NMR and pyrolysis–MBMS analyses suggest that at higher H concentrations, the H monomer primarily self-polymerizes to produce clusters of H-based polymer that are segregated from clusters of G- or S:G-based polymers. Thioacidolysis generally showed higher recoveries of thioethylated products from S:G or S:G:H polymers made with higher H content, indicating an increase in the linear ether linkages. Conclusions Overall, the experimental results support theoretical predictions for the reactivity and structural influences of the H monomer on the formation of lignin-like polymers
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