Changes in Metabolites Produced in Wheat Plants Against Water-Deficit Stress

Abstract

Drought stress can adversely affect the seed germination and seedling growth of wheat plants. This study analyzed the effect of drought on seed germination and the morphological parameters of seedlings from ten winter wheat genotypes. The primary focus was to elucidate the effects of two drought intensities on metabolic status in wheat seedlings. The findings suggest that most wheat genotypes exhibited a significant reduction in germination and growth traits under severe drought, while the genotype Srpanjka exhibited less reduction under both drought conditions. Out of 668 metabolic features, 54 were altered under 10% PEG stress and 140 under 20% PEG stress, with 48 commonly shared between these two stress intensities. This study demonstrated that the metabolic response of shoots to 10% PEG stress contrasts with that of 20% PEG stress. Some growth metabolites, such as oxalic acid, sophorose, and turanose, showed the highest positive increase under both stresses, while butanoic acid, tropic acid, glycine, propionic acid, and phosphonoacetic acid decreased. It is suggested that the accumulation of amino acids, such as proline, contributed to the drought tolerance of the plants. Among all organic acids, succinic and aspartic acids particularly increased the plant response to mild and severe drought stress, respectively. Our results suggest that different metabolites in wheat seedlings enhance the potential ability of wheat to cope with drought stress in the early growth stages by activating a rapid and comprehensive tolerance mechanism. This discovery presents a new approach for enhancing wheat tolerance to abiotic stress, including water deficit.

Keywords: GC-MS; abiotic stress; drought stress; metabolic profiling; winter wheat.

Figure 1

Germination energy (A), percentage of germination (B), shoot length (C), and root length (D) of ten winter wheat genotypes under control and two polyethylene glycol (PEG) treatments (T1-10% and T2-20%). Data are average values of ten biological replicates ± SD. Significant differences among treatments, for each genotype, separately, were assessed by the Fisher LSD test. Trait means with the same letter do not significantly differ at p < 0.05.

Figure 2

Fresh weight of shoots (A), dry weight of shoots (B), fresh weight of shoots (C), and dry weight of roots (D) of ten winter wheat genotypes under control and two polyethylene glycol (PEG) treatments (T1-10% and T2-20%). Data are average values of ten biological replicates ± SD. Significant differences among treatments for each genotype, separately, were assessed by the Fisher LSD test. Trait means with the same letter do not significantly differ at p < 0.05.

Figure 3

Significant analysis of metabolites (SAM) plot. The green points represent metabolite features that are differentially regulated between control and 10% PEG treatment (A) and 20% PEG treatment (B). The solid diagonal line represents “observed = expected”. The more the variable deviates from the “observed = expected”, the more likely it is to be significant.

Figure 4

Top 25 metabolites with highest/lowest correlation coefficient from Pearson’s correlation test between control and 10% polyethylene glycol (PEG) treatment (A) and control and 20% PEG treatment (B). Each row represents the most significant variable identified from the test (p < 0.05).

Figure 5

Partial least square discriminant analysis (PLS-DA) in seedlings of ten wheat genotypes under control and two drought conditions (T1 and T2). Samples at control and drought treatments did not overlap with each other indicating an altered state of metabolite levels in the wheat seedlings.