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Compound-specific δ15N values express differences in amino acid metabolism in plants of varying lignin content

Kendall, Iain P., Woodward, Peter, Clark, Joshua P., Styring, Amy K., Hanna, John V., Evershed, Richard P.
Phytochemistry 2019 v.161 pp. 130-138
amino acid metabolism, carbon, demonstration farms, diet, ecosystems, glutamic acid, herbaceous plants, herbivores, isotope fractionation, leaves, lignin, lignin content, models, nitrogen, nuclear magnetic resonance spectroscopy, phenylalanine, protein synthesis, secondary metabolites, stable isotopes, trees, woody plants, Germany, United Kingdom
Amino acid δ15N values of foliage of various plant taxa, grown at the experimental farm stations of North Wyke, UK and Bad Lauchstädt, Germany were determined by GC-C-IRMS. The difference between δ15N values of glutamate (Glx) and phenylalanine (Phe) were found to differ significantly between woody and herbaceous plants, with mean Δ15NGlx-Phe (i.e. δ15NPhe - δ15NGlx) values of −9.3 ± 1.6‰ and −5.8 ± 2.1‰, respectively. These differences in values are hypothesised to be due to the involvement of Phe in the phenylpropanoid pathway, by which lignin and other phenolic secondary metabolites are produced, leading to isotopic fractionation and enrichment of the remaining Phe pool available for protein biosynthesis. This results in the more negative Δ15NGlx-Phe values observed in woody plants relative to herbaceous plants, as the former are assumed to produce more lignin. To test this assumption, plant leaf tissue lignin concentrations were estimated by solid state 13C cross-polarisation, magic-angle-spinning (CPMAS) NMR spectroscopy for a subset of plants, which showed that tree foliage has a higher concentration of lignin (12.6 wt%) than herbaceous foliage (6.3 wt%). The correlation of lignin concentration with Δ15NGlx-Phe values demonstrates that the difference in these values with plant type is indeed due to differential production of lignin. The ability to estimate the lignin content of plants from amino acid δ15N values will, to give one example, allow refinement of estimates of herbivore diet in present and past ecosystems, enabling more accurate environmental niche modelling.