## 3 Results
### Annotation Results of Differentially Expressed Metabolites  
Drawing upon the metabolite categorization data from the HMDB database, our investigation entailed the statistical mapping of annotated differential metabolisms (Figure 6A). This analysis shed light on the categorization of the specific biological processes of _T. ganhajun_ metabolites. Metabolite fractions exhibiting a significant number of differences (>100) included carboxylic acids and derivatives, fatty acids, organooxygen compounds, and prepol lipids, with organic acids constituting over 19% and fatty acids making up 17%. These lipids, crucial for protein recognition and signal transduction at the cell membrane, are likely associated with the formation of the fruiting body, which involves extensive cell division and heightened lipid metabolism. Figure 5: Insights from differential multiple analysis and OPLS-DA: (**A**) KEGG-annotated results for all growth stages. Up-regulated metabolites are depicted in red and down-regulated metabolites are represented in green. (**B**) Results of the OPLS-DA model, revealing groupings of metabolites at different developmental stages. This sophisticated analysis enhances our understanding of the intricate metabolic changes during various stages. (**C**) OPLS-DA model permutation test results. The horizontal axis measures similarity with the original model, while the vertical axis represents values of R2Y or Q2. A value of 1 indicates alignment with the original model in the horizontal coordinate. Blue dot represents R2Y; red dot represents Q2 of model after Y replacement. The dashed line is the fitted regression line. If both R2Y and Q2 are smaller than the corresponding values of the original model, indicated by all points on the left side of graph (permutation test) being lower than the point at 1 (original model), the model is valid. This insightful analysis allows us to validate the robustness and reliability of the OPLS-DA model. Figure 6: _Cont._  
KEGG annotation (Figure 6B) revealed metabolites exhibiting significant quantitative differences. Notably, there was a substantial enrichment in the biosynthesis of plant secondary metabolites (9.96%), followed closely by the purine metabolism and pyrimidine metabolism, accounting for 7.93% and 5.49%, respectively. Additionally, there were high percentages of certain amino acids and biosynthesized compounds among all differentially expressed metabolites (DEMs). Beyond those merely supporting growth, complex compounds were formed that are intricately involved in the biological processes of cell differentiation and reproductive development. By leveraging ClusterProfiler ([[https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html](https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html)]([https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html](https://bioconductor.org/packages/release/bioc/html/clusterProfiler.html))) for the KEGG annotation of differential metabolites (Figure 6C) and generating a network diagram (Figure 6D), it was found that the differential metabolic pathways were notably enriched in the GM vs. GPM phase, which included flavonoid and folate biosynthesis. This indicates a resemblance to the early development of this species. Flavonoids, which are mostly found in plants and are mostly bound to sugars in the form of glycosides or carbon sugar groups, synthesize phytochrome [34]. Folate is involved in vitamin synthesis, providing the necessary substances for producing enzymes and immune-enhancing effects, and offering sufficient trace elements for cells to fulfill all basic life activities. In GM vs. GSM, pathways including folate biosynthesis, porphyrin metabolism, cyanoamino acid metabolism, and biosynthesis of type II polyketide products were found to be enriched.