| Literature DB >> 35268665 |
Xiaojie Liang1, Yajun Wang1, Yuekun Li1, Wei An1, Xinru He1, Yanzhen Chen1, Zhigang Shi2, Jun He1, Ru Wan1.
Abstract
Wolfberry (Lycium barbarum L.) is an important economic crop widely grown in China. The effects of salt-alkaline stress on metabolites accumulation in the salt-tolerant Ningqi1 wolfberry fruits were evaluated across 12 salt-alkaline stress gradients. The soil pH, Na+, K+, Ca2+, Mg2+, and HCO3- contents decreased at a gradient across the salt-alkaline stress gradients. Based on the widely-targeted metabolomics approach, we identified 457 diverse metabolites, 53% of which were affected by salt-alkaline stress. Remarkably, soil salt-alkaline stress enhanced metabolites accumulation in wolfberry fruits. Amino acids, alkaloids, organic acids, and polyphenols contents increased proportionally across the salt-alkaline stress gradients. In contrast, nucleic acids, lipids, hydroxycinnamoyl derivatives, organic acids and derivatives and vitamins were significantly reduced by high salt-alkaline stress. A total of 13 salt-responsive metabolites represent potential biomarkers for salt-alkaline stress tolerance in wolfberry. Specifically, we found that constant reductions of lipids and chlorogenic acids; up-regulation of abscisic acid and accumulation of polyamines are essential mechanisms for salt-alkaline stress tolerance in Ningqi1. Overall, we provide for the first time some extensive metabolic insights into salt-alkaline stress tolerance and key metabolite biomarkers which may be useful for improving wolfberry tolerance to salt-alkaline stress.Entities:
Keywords: abiotic stress; goji berry; metabolomics; nutritional quality
Mesh:
Year: 2022 PMID: 35268665 PMCID: PMC8911562 DOI: 10.3390/molecules27051564
Source DB: PubMed Journal: Molecules ISSN: 1420-3049 Impact factor: 4.411
Figure 1Field layout and experimental condition of the study area. (A) Experimental set up. Twelve salt-alkaline gradients were collected, numbered sequentially from XZ-01 to XZ-12. Each gradient consists of 10 rows of Ningqi1 trees; (B) Positions of the salt-alkaline beach in the field; (C) Definition of the stress gradients based on 10 parallel rows of wolfberry Ningqi1 trees away from the beach; (D,E) Wolfberry Ningqi1 trees under severe salt-alkaline stress.
Soil physico–chemical properties of the study area.
| Stress Gradients | Soil Physico–Chemical Properties | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| pH | Salt | K+ | Na+ | Ca2+ | Mg2+ | Cl− | SO42− | HCO3− | |
| XZ-01 | 8.70 abcd | 33.90 a | 0.05 a | 5.78 a | 2.34 a | 2.11 a | 10.18 a | 6.32 a | 0.17 a |
| XZ-02 | 8.87 ab | 17.77 b | 0.03 b | 2.74 bc | 2.33 a | 1.03 b | 4.58 b | 5.07 b | 0.15 b |
| XZ-03 | 8.97 a | 12.83 c | 0.02 bc | 3.13 b | 0.61 cd | 0.86 bc | 4.22 b | 1.59 ef | 0.15 b |
| XZ-04 | 8.93 ab | 13.33 c | 0.02 bc | 3.31 b | 0.56 cd | 0.90 bc | 4.54 b | 1.53 ef | 0.16 ab |
| XZ-05 | 9.03 a | 8.93 de | 0.03 d | 2.10 cd | 0.64 cd | 0.51 d | 2.57 c | 1.53 ef | 0.12 cd |
| XZ-06 | 8.77 abcd | 10.53 cd | 0.04 b | 1.71 de | 1.95 ab | 0.54 d | 1.99 cd | 3.59 c | 0.13 c |
| XZ-07 | 8.90 ab | 10.87 cd | 0.05 a | 1.10 de | 1.64 b | 0.59 cd | 2.31 c | 3.34 cd | 0.16 ab |
| XZ-08 | 8.83 abc | 6.57 ef | 0.06 a | 1.24 ef | 1.04 c | 0.36 de | 1.36 cde | 2.30 de | 0.13 c |
| XZ-09 | 8.33 de | 5.30 efg | 0.05 a | 0.94 fg | 0.74 cd | 0.18 e | 1.02 de | 1.50 ef | 0.11 e |
| XZ-10 | 8.47 bcde | 4.00 fg | 0.06 a | 0.58 fgh | 0.67 cd | 0.18 e | 0.47 e | 1.38 ef | 0.10 ef |
| XZ-11 | 8.37 cde | 1.93 g | 0.05 a | 0.24 gh | 0.21 d | 0.09 e | 0.28 e | 0.61 f | 0.14 bc |
| XZ-12 | 8.17 e | 1.83 g | 0.05 a | 0.16 h | 0.23 d | 0.08 e | 0.23 e | 0.66 f | 0.15 b |
XZ-01–XZ-12 refer to the various stress gradients. A column of data under one indicator with different lowercase letter are significantly different at p < 0.05 according to S-N-K ANOVA.Salinity, K+, Na+, Ca2+, Mg2+, Cl−, SO42− and HCO3− were measured in g/kg.
Effect of various salinity gradients on key wolfberry leaf and fruit traits.
| Salt Stress Gradients | Leaf Traits | Fruit Traits | |||
|---|---|---|---|---|---|
| Length (cm) | Width (cm) | Weight (g) | Longitudinal Diameter (cm) | Transverse Diameter (cm) | |
| XZ-06 | 4.03 a | 0.95 a | 0.49 a | 1.25 a | 0.92 a |
| XZ-07 | 4.26 a | 1.05 a | 0.48 a | 1.43 a | 0.92 a |
| XZ-08 | 4.89 ab | 1.13 ab | 0.36 a | 1.16 a | 0.83 a |
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| XZ-10 | 4.37 a | 1.22 b | 0.83 b | 1.61 b | 1.00 b |
| XZ-11 | 5.07 b | 1.33 b | 0.79 b | 1.51 b | 0.94 ab |
| XZ-12 | 5.14 b | 1.28 b | 0.86 b | 1.70 b | 1.02 b |
Length = mean length; Width = mean width; weight = mean weight; Longitudinal diameter = mean longitudinal diameter; Transverse diameter = mean transverse diameter; XZ-01–XZ-012 refer to the various salt stress gradients of the wolfberry Ningqi1 trees. A column of data under one indicator with different lowercase letter are significantly different at p < 0.05 according to S-N-K ANOVA. The bolded values represent threshold of salinity tolerance.
Figure 2Metabolites detected in ripe wolfberry fruits based on metabolite compound clustering.
Figure 3Profiles of metabolites in ripe fruits of wolfberry from 6 stress gradients. (A) Hierarchical clustering heatmap of metabolites based on ion intensity; and (B) principal component analysis (PCA). Six salt-alkaline gradients were collected, numbered sequentially from XZ-06 to XZ-12. Mix represents the mixed samples used for quality control. Log2 fold change of the metabolite ion intensity were used in the analyses. The salt-alkaline stress gradients were schematized below the PCA from the highest (XZ-06) to the lowest (XZ-12).
Figure 4Major metabolite classes comparison between the different salt-alkaline stress gradients. These classes encompass approximately 80% of the total metabolites detected in the wolfberry fruits. Six salt-alkaline gradients were collected, numbered sequentially from XZ-01 06 to XZ-12. The salt-alkaline stress gradients were schematized below the line graphs from the highest (XZ-06) to the lowest (XZ-12).
Correlations between soil physico–chemical properties and major metabolites in wolfberry fruits.
| Amino Acid Derivatives | Polyphenols | Hydroxycinnamoyl Derivatives | Lipids | Nucleic Acid Derivatives | Organic Acids | Vitamins | Alkaloids | |
|---|---|---|---|---|---|---|---|---|
| pH |
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| −0.49 | −0.18 | −0.49 |
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| Salt |
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| −0.39 | −0.32 |
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| K+ | −0.14 | −0.49 | 0.04 | 0.07 | −0.37 | 0.30 |
| −0.37 |
| Na+ |
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| −0.49 | −0.42 |
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| Ca2+ |
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| −0.30 | −0.27 |
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| Mg2+ |
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| −0.33 | −0.20 |
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| Cl− |
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| −0.44 | −0.35 |
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| SO42− |
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| −0.34 | −0.25 |
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| HCO3− | 0.29 | 0.11 | −0.13 | 0.38 | 0.30 | 0.25 | 0.07 | 0.23 |
Values in bold refer to either * significant (p ˂ 0.05); ** very significant (p ˂ 0.001); and/or *** highly significant (p ˂ 0.0001) computed using Standard Linear Pearson Correlation.
Figure 5(A) Number of upregulated and downregulated differentially accumulated metabolites (DAM) between the different stress gradients. The blue line shows the difference in total DAMs content between the stress gradients. The green line represents the upregulated while the red line represents downregulated DAMs, respectively. (B) Venn diagram showing the number of shared and common DAMs between the different compared salt-alkaline stress gradients.
Consistently and differentially accumulated metabolites between wolfberry fruits from six salt-alkaline stress gradients.
| Metabolite Class | Compound | Log2 Fold Change | |||||
|---|---|---|---|---|---|---|---|
| XZ-06 vs. XZ-07 | XZ-06 vs. XZ-08 | XZ-06 vs. XZ-09 | XZ-06 vs. XZ-10 | XZ-06 vs. XZ-11 | XZ-06 vs. XZ-12 | ||
| Polyamine | N-p-Coumaroyl putrescine | −0.772 | −1.081 | −1.237 | −1.272 | −1.478 | −1.987 |
| Phenolamides | N′-p-Coumaroyl putrescine | −0.58 | −1.288 | −1.342 | −1.449 | −1.838 | −2.444 |
| Phytohormone | Abscisic acid | −0.991 | −2.348 | −2.376 | −2.014 | −2.304 | −2.982 |
| Phytohormones | (+)-cis,trans-Abscisic acid | −0.931 | −2.472 | −2.296 | −1.916 | −2.469 | −2.743 |
| Quinate and derivatives | Cryptochlorogenic acid | −0.269 | 1.8 | 2.209 | 1.539 | 2.253 | 3.678 |
| Quinate and derivatives | Chlorogenic acid (3-O-Caffeoylquinic acid) | −3.187 | 2.006 | 2.641 | 1.668 | 2.445 | 3.922 |
| - | Dopamine hydrochloride | −0.654 | 1.064 | 2.194 | 1.489 | 2.142 | 3.902 |
| Fatty acid | LPC(1-acyl 18:2) | 2.504 | 1.38 | 2.194 | 3.116 | 2.655 | 3.987 |
| Lipids_glycerophospholipids | LysoPC 16:2 (2n isomer) | 2.104 | 1.392 | 1.768 | 2.378 | 1.889 | 3.921 |
| Lipids_glycerophospholipids | LysoPC 18:3 (2n isomer) | 1.86 | 1.015 | 1.551 | 2.12 | 1.904 | 3.077 |
| Lipids_glycerophospholipids | LysoPC 15:1 | 2.096 | 1.023 | 1.768 | 1.822 | 1.878 | 3.604 |
| Lipids_glycerophospholipids | LysoPC 16:1 (2n isomer) | 1.987 | 1.052 | 1.618 | 2.413 | 2.445 | 2.811 |
| Benzoic acid derivatives | 2,5-dihydroxy benzoic acid O-hexoside (Gentisic acid) | 1.187 | 0.575 | 1.238 | 1.454 | 2.477 | 2.824 |
Figure 6Summary of the metabolic responses to salt-alkaline stress in Lycium barbarum fruit. Under salt-alkaline stress, several classes of metabolites are upregulated or downregulated: salt-alkaline responsive metabolites. Thirteen metabolites are constitutively differentially accumulated across various salt-alkaline stress gradients: salt-alkaline stress biomarkers. The black arrow stands for upregulated metabolites while the red arrow stands for downregulated metabolites.