Abstract
Nitrogen and phosphorus limitation affect the growth, development, and productivity of lettuce, which exert a marked influence on metabolites. To compare the influence of low-nitrogen and low-phosphorus stresses on various metabolites of lettuce leaves, experiments were performed under three conditions of treatment—low-nitrogen stress, low-phosphorus stress, and normal samples. Metabolomic analyses were conducted based on ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Principle components analysis yielded distinctive clustering information among the holistic samples; fold change analysis, t-test and orthogonal partial least square discriminant analysis were used for the selection of metabolic biomarkers. Ten pathways were selected which were significantly enriched by metabolic biomarkers. Metabolic biomarkers were screened by fold change (FC) value, p-value and variable importance in the projection (VIP) value, low-nitrogen and low-phosphorus stresses caused an increase in 16 metabolites (FC > 2, p-value < 0.05, VIP > 1) and a decrease in 26 metabolites (FC < 0.5, p-value < 0.05, VIP > 1). Outside of these, our results showed that inositol, p-hydroxybenzoic acid, stachyose, dinoseb, and 7, 8-dihydroxycoumarin increase in low-nitrogen stress samples. Low-phosphorus stress caused accumulation of citrate, isocitrate, l-5-oxoproline, succinate, and histamine, which may be considered potential metabolic biomarkers. The metabolites could be used to monitor the nitrogen and phosphorus status of lettuce and to guide appropriate fertilization regimens.
Highlights
Mineral nutrients, such as nitrogen and phosphorus, frequently limit plant growth [1].Nitrogen limitation directly influences the biosynthesis of compounds, such as proteins, vitamins, phytohormones, co-enzymes, chlorophyll, and nucleic acids [2,3]
quality control (QC) samples were visualized using total ion current, which indicated that the instrumental analysis of all samples was strong and the peak capacity was large, so the retention time was reproducible
To observe the overall distribution of samples, the Principal component analysis (PCA) was considered an unsupervised model to operate without any anthropogenic factors, which was conducive to understanding the holistic data and eliminating abnormal samples
Summary
Mineral nutrients, such as nitrogen and phosphorus, frequently limit plant growth [1]. Nitrogen limitation directly influences the biosynthesis of compounds, such as proteins, vitamins, phytohormones, co-enzymes, chlorophyll, and nucleic acids [2,3]. Phosphorus is a component of many cellular molecules and plays an essential role in structural maintenance [4]. Studies have focused on topics such as the nutritional deficit of plants through the differences of surface macro characteristics, such as height, length, and color [6]; the differences of micro characteristics such as leaf surface roughness and texture [7]; the differences of the internal microstructure such as stomata, sponges and palisade tissues; and the differences of macromolecular compounds such as chlorophyll and lutein [8,9,10]. The diagnosis of cancer is based on tissue, cell, and molecule level. The detection of metabolic biomarkers at the molecular level can realize early warning [11], which is of great significance to Agriculture 2020, 10, 406; doi:10.3390/agriculture10090406 www.mdpi.com/journal/agriculture
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