Study on Enzyme Activity and Metabolomics during Culture of Liquid Spawn of Floccularia luteovirens

Abstract

To comprehensively investigate the physiological characteristics and metabolic processes of the mycelium of Floccularia luteovirens (F. luteovirens), a wild edible fungus unique to the plateau region, we conducted an in-depth analysis of the mycelium enzyme activity and metabolites during different culture periods. The activity of seven enzymes all followed a trend of initially increasing and then decreasing. The intra- and extracellular activity peaks of three hydrolases-amylase, protease, and cellulase-all occurred on the 20th day, except for the extracellular amylase, which peaked on the 15th day. In contrast, the peak activity of laccase occurred on the 10th day. Moreover, three types of oxidoreductases in the mycelium (catalase (CAT), superoxide dismutase (SOD), and 2,3,5-triphenyltetrazolium chloride (TTC)-dehydrogenase (TTC-DH)) also exhibited significant changes in activity. CAT and SOD activity reached their maximum on the 20th day, whereas TTC-DH showed high activity on both the 10th and 20th days. Through a comprehensive assessment of the evolving trends of these physiological parameters, we determined that the optimal cultivation cycle for F. luteovirens liquid spawn is 20 days. An untargeted metabolomic analysis revealed that 3569 metabolites were detected in the F. luteovirens mycelium, including a variety of secondary metabolites and functional components, with terpenoids being particularly abundant, accounting for 148 types. By comparing three different culture stages (10 days, 20 days, and 30 days), 299, 291, and 381 metabolites, respectively, showed different accumulation patterns in the comparison groups of 10d vs. 20d, 20d vs. 30d, and 10d vs. 30d. These differential metabolites were primarily concentrated in carboxylic acids and their derivatives, fatty acyl groups, organic oxygen compounds, and lipid compounds. In addition, there were several amino acids whose abundance continued to grow during culturing. The metabolism of amino acids greatly affects mycelium growth and development. This research delineates the interplay between mycelium growth and metabolism, offering empirical support for a cultivation strategy for liquid F. luteovirens, and an exploration of its metabolites for potential applications.

Keywords: Floccularia luteovirens; enzyme activity; liquid spawn; metabolomics.

Figure 1

Morphology and 4 physiological indexes of F. luteovirens liquid spawn at different culture periods. (A) Morphology of F. luteovirens liquid spawn in shaker bottles at different periods; (B) mycelium biomass dry weight and pH of culture medium; (C) polysaccharide content; and (D) soluble protein content. Different lowercase letters in figure indicate significant differences at p < 0.05 level.

Figure 2

The activity of 7 enzymes of F. luteovirens liquid spawn during different culture periods. (A) Amylase activity; (B) protease activity; (C) cellulase activity; (D) laccase activity; (E) CAT and SOD activity; and (F) TTC-DH activity. Different lowercase letters in the figure indicate significant differences at the p < 0.05 level.

Figure 3

Analysis of total metabolites in mycelium of F. luteovirens. (A) Venn diagram; (B) classification pie chart; (C) statistical bar chart of number of partial bioactive compounds; and (D) pie chart of terpenoid classification.

Figure 4

PCA score plot. (A) Graph of PCA score for GCMS assay; (B) graph of PCA score for LCMS assay. Points of the same color represent six replicas.

Figure 5

OPLS-DA score plot. (A) Plot of OPLS-DA scores for F.l-10d vs. F.l-20d using GCMS analysis; (B) plot of OPLS-DA scores for F.l-20d vs. F.l-30d using GCMS analysis; (C) plot of OPLS-DA scores for F.l-10d vs. F.l-30d using GCMS analysis; (D) plot of OPLS-DA scores for F.l-10d vs. F.l-20d using LCMS analysis; (E) plot of OPLS-DA scores for F.l-20d vs. F.l-30d using LCMS analysis; (F) plot of OPLS-DA scores for F.l-10d vs. F.l-30d using LCMS analysis. Points of same color represent six replicas.

Figure 6

OPLS permutation test plot. (A) Plot of permutation test for F.l-10d vs. F.l-20d using GCMS analysis; (B) plot of permutation test for F.l-20d vs. F.l-30d using GCMS analysis; (C) plot of permutation test for F.l-10d vs. F.l-30d using GCMS analysis; (D) plot of permutation test for F.l-10d vs. F.l-20d using LCMS analysis; (E) plot of permutation test for F.l-20d vs. F.l-30d using LCMS analysis; (F) plot of permutation test for F.l-10d vs. F.l-30d using LCMS analysis.

Figure 7

Differential metabolite volcano map and differential metabolite cluster heat map. (A) Fl-10d vs. Fl-20d differential metabolite volcano map; (B) Fl-10d vs. Fl-20d differential metabolite cluster heat map; (C) Fl-20d vs. Fl-30d differential metabolite volcano map; (D) FL-20d vs. FL-30d differential metabolite cluster heat map; (E) Fl-10d vs. Fl-30d differential metabolite volcano map; and (F) Fl-10d vs. Fl-30d differential metabolite cluster heat map.

Figure 8

Clustering heat map of differential metabolites common to all three sample groups.

Figure 9

KEGG enrichment analysis map of differential metabolites among groups. (A) Fl-10d vs. Fl-20d KEGG enrichment analysis; (B) Fl-20d vs. Fl-30d KEGG enrichment analysis; (C) Fl-10d vs. Fl-30d KEGG enrichment analysis; (D) KEGG enriched metabolic pathway map of differential metabolites common to three groups and with increasing content over culture time.