Dynamic product-precursor relationships underlie cuticular lipid accumulation on maize silks

Abstract

ABSTRACTThe hydrophobic cuticle is the first line of defense between aerial portions of a plant and the external environment. On maize silks, the cuticular cutin matrix is infused with cuticular lipids, consisting of a homologous series of very-long-chain fatty acids (VLCFAs), aldehydes, and hydrocarbons that serve as precursors, intermediates, and end-products of the elongation, reduction, and decarbonylation reactions of the hydrocarbon-producing pathway. To deconvolute the potentially confounding impacts of the silk microenvironment and silk development on the hydrocarbon-producing pathway, spatio-temporal cuticular lipid profiling was conducted on the agronomically important inbreds B73 and Mo17, and their reciprocal hybrids. Statistical interrogation via multivariate analyses of the metabolite abundances of the hydrocarbon-producing pathway demonstrate that the cellular VLCFA pool is positively correlated with the cuticular lipid metabolome, and this metabolome is primarily affected by the silk microenvironment and the plant genotype. Moreover, genotype has a major effect on the pathway, with increased cuticular hydrocarbon and concomitant reduction of cuticular VLCFA accumulation on B73 silks, suggesting that conversion of VLCFAs to hydrocarbons is more effective in B73 than Mo17. Statistical modeling of the ratios between cuticular hydrocarbons and cuticular VLCFAs reveals the complexity of the product-precursor ratio relationship, demonstrating a significant role of precursor chain length. Longer-chain VLCFAs are preferentially utilized as precursors for hydrocarbon biosynthesis. Collectively, these findings demonstrate maize silks as an effective and novel system for dissection of the complex dynamics of cuticular lipid accumulation in plants.One-sentence SummaryThe product-precursor ratios in the cuticular hydrocarbon-producing pathway are impacted by fatty acid precursor chain length, plant genotype and the spatio-temporal dynamic gradients of maize silks.