Metabolomics and Transcriptomics Reveal the Effects of Different Fermentation Times on Antioxidant Activities of Ophiocordyceps sinensis

Abstract

Ophiocordyceps sinensis is a fungus that is cultured through fermentation from wild Chinese cordyceps. While studies have examined its metabolites, the evaluation of its antioxidant capacity remains to be conducted. The antioxidant results of O. sinensis indicate that the ferric ion-reducing antioxidant power (FRAP), antioxidant capacity (2.74 ± 0.12 μmol Trolox/g), 2,2-diphenyl-1-picrylhydrazyl (DPPH•) free radical scavenging rate (60.21 ± 0.51%), and the hydroxyl free radical scavenging rate (91.83 ± 0.68%) reached a maximum on day 30. Using LC-MS/MS to measure the metabolites on D24, D30, and D36, we found that the majority of the differential accumulated metabolites (DAMs) primarily accumulate in lipids, organoheterocyclic compounds, and organic acids and their derivatives. Notably, the DAMs exhibiting high peaks include acetylcarnitine, glutathione, linoleic acid, and L-propionylcarnitine, among others. The transcriptome analysis results indicate that the differentially expressed genes (DEGs) exhibiting high expression peaks on D30 primarily included lnaA, af470, and ZEB1; high expression peaks on D24 comprised SPBC29A3.09c and YBT1; high expression peaks on D36 included dtxS1, PA1538, and katG. The combined analysis revealed significant and extremely significant positive and negative correlations between all the DAMs and DEGs. The primary enriched pathways (p < 0.05) included glutathione metabolism, tryptophan metabolism, carbon metabolism, biosynthesis of secondary metabolites, and phenylalanine metabolism. The metabolic pathway map revealed that the DAMs and DEGs influencing the antioxidant activity of O. sinensis were significantly up-regulated on D30 but down-regulated on D36. The correlation analysis suggests that an increase in the content of DEGs and DAMs promotes an increase in the levels of enzyme and non-enzyme substances, ultimately enhancing the antioxidant capacity of O. sinensis. These findings serve as a reference of how DAMs and DEGs affect the antioxidant activity of O. sinensis. This may contribute to the enhanced development and application of O. sinensis.

Keywords: LC-MS/MS; Ophiocordyceps sinensis; antioxidant activity; transcriptome; untargeted metabolomics.

Figure 1

Ophiocordyceps sinensis at different fermentation times. (A) Antioxidant activity of 2,2-diphenyl-1-picrylhydrazyl radical scavenging rate (DPPH•), hydroxyl free radical scavenging rate (•OH), and superoxide anion radical scavenging rate (O₂^•−). (B) Antioxidant activity of ferric ion-reducing antioxidant power (FRAP). (C) Changes in SOD activity with O. sinensis at different fermentation times. (D) Changes in POD activity with O. sinensis. (E) Changes in CAT activity with O. sinensis. (F) Changes in GSH-Px activity with O. sinensis. (G) Changes in flavonoid with O. sinensis. (H) Changes in polysaccharide with O. sinensis. Analysis of Variance (ANOVA) shows that different lowercase letters indicate significant differences between samples at the 0.05 level.

Figure 2

The metabolites detected on D24, D30, and D36 samples. (A) Metabolite superclass classification on D24, D30, and D36. (B) Cluster analysis of all metabolites is presented, with the abscissa representing various fermentation times and the ordinate indicating the relative content of metabolites. (C) PCA of D24, D30, D36, and QC.

Figure 3

The differential accumulated metabolites (DAMs) analysis on D24, D30, and D36. (A) Venn diagram of metabolites detected on D24 vs. D30, D24 vs. D36, and D36 vs. D30. (B) Superclass classification of the 462 key metabolites.

Figure 4

Changes in the peak area of differential accumulated metabolites (DAMs) for different superclasses. The DAMs of (A) alkaloids and derivatives, (B) phenylpropanoids and polyketides, (C) nucleosides, nucleotides, and analogues, (D) organic nitrogen compounds detected in O. sinensis at different fermentation times (D24, D30, and D36). The horizontal coordinate represents the DAMs, and the vertical coordinate is the peak area of the DAMs.

Figure 5

Principal component analysis and correlation analysis of 3 samples. (A) Sample correlation test. Redder colors indicate higher correlation; bluer colors indicate lower correlation. (B) PCA.

Figure 6

Identification of differentially expressed genes. (A) D24 vs. D30, (B) D24 vs. D36, (C) D36 vs. D30, (D) Venn diagrams for 3 comparison groups. (E) The differentially expressed genes (DEGs) detected in O. sinensis at different fermentation times (D24, D30, and D36). The horizontal coordinate represents the DEGs, and the vertical coordinate is the peak area of the DEGs.

Figure 7

Correlation clustering heatmap. Red represents positive correlation, blue represents negative correlation. **, p values < 0.01; *, p values < 0.05. (A) Differential accumulated metabolites (DAMs) and differentially expressed genes (DEGs) correlation analysis. Each row represents one DAM, and each column represents one DEG. (B) Enzymatic, non-enzymatic, and antioxidant indicator correlation analysis.

Figure 8

Overview of differential accumulated metabolites (DAMs) and differentially expressed genes (DEGs) mapping to key Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in pairwise comparisons of D24 vs. D30, D24 vs. D36, and D36 vs. D30. Red triangles indicate significant up-regulation between groups; green triangles indicate significant down-regulation; blue triangles indicate both up-regulation and down-regulation; gray triangles represent insignificant differences in detected DAMs or differentially expressed genes (DEGs). The other shapes have the same color explanation as before. Solid arrows represent facilitation, gray solid boxes represent DAMs, and red dotted boxes represent DEGs.

Figure 9

The qRT-PCR validation of 11 differentially expressed genes (DEGs).