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. 2024 Mar 4;13(5):796.
doi: 10.3390/foods13050796.

UPLC-ESI-MS/MS-Based Analysis of Various Edible Rosa Fruits Concerning Secondary Metabolites and Evaluation of Their Antioxidant Activities

Ming Ni  1   2   3 , Junlei Chen  2   3 , Mao Fu  2   3 , Huanyang Li  2   3 , Shengqian Bu  2   3 , Xiaojiang Hao  2   3   4 , Wei Gu  2   3
Affiliations

UPLC-ESI-MS/MS-Based Analysis of Various Edible Rosa Fruits Concerning Secondary Metabolites and Evaluation of Their Antioxidant Activities

Ming Ni et al. Foods. .

Abstract

The genus Rosa is globally popular with well-established applications since it has a high edible and medicinal value. However, relatively limited research has been conducted on the composition and quality of wild Rosa fruits. The present study aimed to compare the properties and chemical components of five wild edible Rosa fruits, Rosa roxburghii, Rosa sterilis, Rosa laevigata, Rosa davurica, and Rosa sericea. The UPLC-ESI-MS/MS approach identified the key metabolites among the five Rosa fruits as flavonoids, phenolic acids, and organic acids. The main differential metabolites among the five fruits are flavonoids (22.29-45.13%), phenolic acids (17-22.27%), and terpenoids (7.7-24%), respectively. In total, 125 compounds served as potential markers for the five Rosa species. Differential metabolic pathways of five Rosa fruits were analyzed using the KEGG approach. Rosa laevigata fruits showed the highest total polysaccharide (TPS) content of 64.48 g/100 g. All the five Rosa extracts effectively decreased the levels of malondialdehyde while increasing the activities of superoxide dismutase and glutathione peroxidase in the H2O2-induced HaCaT cell model, demonstrating high potential for antioxidant development. Our findings suggest that the five studied Rosa fruits exhibit biological activity and edible value worth further exploration.

Keywords: Rosa laevigata; Rosa roxburghii; Rosa sericea; antioxidant activity; metabolic profiling.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Figure 1
Figure 1
Morphology of five rose hips.
Figure 2
Figure 2
(A) Score plot of principle component analysis (PCA) in five samples with quality control sample, and (B) score plot of PCA without quality control sample. GC_1, RRT-F; GC_2, RSS-F; GC_3, RLM-F; GC_4, RDP-F; GC_5, RSL-F.
Figure 3
Figure 3
(A) The HCA heat map analysis of Rosa samples with clustering and (B) with compound classifications. The color indicates the level of accumulation of each metabolite, from low (green) to high (red). GC_1, RRT-F; GC_2, RSS-F; GC_3, RLM-F; GC_4, RDP-F; GC_5, RSL-F.
Figure 4
Figure 4
(A,C,E,G) Score plot generated from orthogonal partial least squares discriminant analysis (OPLS-DA), and (B,D,F,H) OPLS-DA models of five samples. (A,B) RRT-F vs. RSS-F; (C,D) RRT-F vs. RLM-F; (E,F) RRT-F vs. RDP-F; (G,H) RRT-F vs. RSL-F.
Figure 5
Figure 5
(A) The upregulated and downregulated metabolites from Rosa sterilis fruit (RSS-F), Rosa laevigata fruit (RLM-F), Rosa davurica fruit (RDP-F), and Rosa sericea fruit (RSL-F) compared with Rosa roxburghii fruit (RRT-F). (B) The upregulated and downregulated flavonoids, (C) phenolic acids, and (D) triterpenoids from RSS-F, RLM-F, RDP-F, RSL-F compared with RRT-F.
Figure 6
Figure 6
Comparing the relative contents of differentially expressed flavonoids with the highest total content in five rose hips based on their peak area. Kaemp 3-Glu, kaempferol 3-O-β-d-(6″-O-(E)-p-coumaroyl) glucopyranoside; 6-hydroxy l-7-O-Glu, 6-hydroxykaempferol-7-O-glucoside. Different letters on the bars represent significant differences between Rosa fruits samples (p < 0.05) analyzed via a post hoc Tukey’s test.
Figure 6
Figure 6
Comparing the relative contents of differentially expressed flavonoids with the highest total content in five rose hips based on their peak area. Kaemp 3-Glu, kaempferol 3-O-β-d-(6″-O-(E)-p-coumaroyl) glucopyranoside; 6-hydroxy l-7-O-Glu, 6-hydroxykaempferol-7-O-glucoside. Different letters on the bars represent significant differences between Rosa fruits samples (p < 0.05) analyzed via a post hoc Tukey’s test.
Figure 7
Figure 7
Comparing the relative contents of differentially expressed phenolic acids with the highest total content in five rose hips based on their peak area. 3-O-Galloyl-Glu, 3-O-Galloyl-β-D-glucose; 6-O-Galloyl-Glu, 6-O-Galloyl-β-D-glucose; 2-O-Galloyl-Glu, 2-O-Galloyl-β-D-glucose; 1-O-Galloyl-Glu, 1-O-Galloyl-β-D-glucose; 3,4,5-Glu, 3,4,5-trimethoxyphenyl-β-D-glucopyranoside; 5-Hydroxy-MF, 5-hydroxymethylfurfural. Different letters on the bars represent significant differences between Rosa fruits samples (p < 0.05) analyzed via a post hoc Tukey’s test.
Figure 7
Figure 7
Comparing the relative contents of differentially expressed phenolic acids with the highest total content in five rose hips based on their peak area. 3-O-Galloyl-Glu, 3-O-Galloyl-β-D-glucose; 6-O-Galloyl-Glu, 6-O-Galloyl-β-D-glucose; 2-O-Galloyl-Glu, 2-O-Galloyl-β-D-glucose; 1-O-Galloyl-Glu, 1-O-Galloyl-β-D-glucose; 3,4,5-Glu, 3,4,5-trimethoxyphenyl-β-D-glucopyranoside; 5-Hydroxy-MF, 5-hydroxymethylfurfural. Different letters on the bars represent significant differences between Rosa fruits samples (p < 0.05) analyzed via a post hoc Tukey’s test.
Figure 8
Figure 8
Comparing the relative contents of differentially expressed terpenoids with the highest total content in five rose hips based on their peak area. Different letters on the bars represent significant differences between Rosa fruits samples (p < 0.05) analyzed via the post hoc Tukey’s test.
Figure 9
Figure 9
The top five potential markers with highest content in five samples.
Figure 10
Figure 10
(A,B,C,D) KEGG enrichment map and (E,F,G,H) differential abundance score map of different metabolites in five samples. (I,J,K,L) KEGG bar plot of DEMs in five samples. (A,E,I) RSS-F vs. RRT-F; (B,F,J) RLM-F vs. RRT-F; (C,G,K) RDP-F vs. RRT-F; (D,H,L) RSL-F vs. RRT-F.
Figure 10
Figure 10
(A,B,C,D) KEGG enrichment map and (E,F,G,H) differential abundance score map of different metabolites in five samples. (I,J,K,L) KEGG bar plot of DEMs in five samples. (A,E,I) RSS-F vs. RRT-F; (B,F,J) RLM-F vs. RRT-F; (C,G,K) RDP-F vs. RRT-F; (D,H,L) RSL-F vs. RRT-F.
Figure 10
Figure 10
(A,B,C,D) KEGG enrichment map and (E,F,G,H) differential abundance score map of different metabolites in five samples. (I,J,K,L) KEGG bar plot of DEMs in five samples. (A,E,I) RSS-F vs. RRT-F; (B,F,J) RLM-F vs. RRT-F; (C,G,K) RDP-F vs. RRT-F; (D,H,L) RSL-F vs. RRT-F.
Figure 11
Figure 11
(A) Effects of samples on the cellular viabilities in HaCaT cells. (B) Recovery effect of samples on HaCaT cells damaged by H2O2. (C) Enhancing effects of Rosa samples on SOD viability and (D) GSH-Px enzyme viability in cellular lysates of HaCaT keratinocytes. (E) Rosa samples influenced the MDA levels in H2O2-damaged HaCaT cells. VC (0.1 mg/mL) was used as a positive control. #, p < 0.05 versus the blank control. *, p < 0.05; **, p < 0.01; ***, p < 0.001 versus the non-treated control.
Figure 12
Figure 12
Correlation index between antioxidant activities and the potential markers (flavonoids and phenolic acids). The numbers represent the compounds in Supplementary Table S5. The red color indicates the positive correlation, the blue color indicates the negative correlation, and the blank represents no correlation. The size of the circle represents the significance of the corresponding correlation.
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