Integrated Transcriptomics and Metabolomics Provide Insight into Degeneration-Related Molecular Mechanisms of Morchella importuna During Repeated Subculturing

Abstract

This study investigated Morchella importuna strain degeneration during repeated subculturing and employed metabolomics, transcriptomics, and other techniques to explore its molecular mechanisms. Significant metabolic and transcriptional differences were observed between normal mycelia (NM) and degenerated mycelia (DG). Metabolomic analysis revealed 699 differentially expressed metabolites (DEMs) that were predominantly enriched in secondary metabolite biosynthesis pathways, particularly flavonoids and indole alkaloids. Total flavonoid content was markedly higher in NM than in DG, with most flavonoid compounds showing reduced levels in degenerated strains. Transcriptomic profiling revealed 2691 differentially expressed genes (DEGs), primarily associated with metabolic pathways and genetic information processing. Integrated analysis showed that metabolic dynamics were regulated by DEGs, with pyruvate metabolism being significantly enriched. The FunBGCeX tool identified biosynthetic gene clusters (BGCs) in the M. importuna genome, highlighting the critical role of the non-reducing polyketide synthase (NR-PKS) gene in flavonoid biosynthesis. This gene exhibited significantly downregulated expression in DG strains. These findings indicate that M. importuna degeneration resulted from systemic dysregulation of gene expression networks and metabolic pathway reorganization. The results presented herein also provide theoretical insights into degeneration mechanisms and potential prevention strategies for this edible fungus.

Keywords: Morchella importuna; mechanisms; non-reducing polyketide synthase; strain degeneration.

Figure 1

Morphological characteristics and comparative overview of all of the metabolites of Morchella importuna. Photos of representative phenotypes of normal (NM) and degenerate (DG) mycelia of M. importuna grown on Potato Dextrose (a) and Potato Dextrose Agar (b) media. (c) PCA of metabolite compositions between NM and DG mycelia of M. importuna. (d) Classification of metabolites.

Figure 2

Metabolomics analysis between normal and degenerate mycelia of Morchella importuna. (a) Volcano plot of the DEMs of NM and DG groups. (b) Statistical analysis of differentially expressed metabolites (DEMs). Total: total DEMs; Up: upregulated metabolites; Down: downregulated metabolites. (c) KEGG enrichment analysis of the DEMs (Counts > 3) in NM vs. DG. The size of the dots represents the number of metabolites, while the color represents the p-value.

Figure 3

Transcriptomics analysis between normal and degenerate mycelia of Morchella importuna. (a) PCA of the gene expression profiles of all of the samples. (b) Pearson correlation analysis of all of the transcriptome samples. (c) Distribution of CPM values across samples. (d) Volcano plot of the DEGs of NM and DG groups. (e) KEGG enrichment analysis of the DEGs in NM vs. DG. The size of the dots represents the number of genes, while the color represents the p-value.

Figure 4

Integrated metabolomics and transcriptomics analysis of Morchella importuna. (a) Nine quadrant plots for correlation analysis between NM and DG. Numbers 1–9 represent different quadrants, respectively. Purple indicates both DEGs and DEMs show significant changes (|Log2(foldchange)| ≥ 1); Green indicates only DEMs show significant changes (|Log2(foldchange)| ≥ 1) while DEGs show non-significant changes (|Log2(foldchange)| < 1); Yellow indicates only DEGs show significant changes (|Log2(foldchange)| ≥ 1) while DEMs show non-significant changes (|Log2(foldchange)| < 1); Red indicates neither DEGs nor DEMs show significant changes (|Log2(foldchange)| < 1). (b) KEGG pathway enrichment analysis of the DEGs and DEMs between NM and DG.

Figure 5

Analysis and qRT-PCR validation of NR-PKS gene from Morchella importuna. Relative expression levels of the NR-PKS gene obtained by qRT-PCR (a); Counts per million (CPM) values from nanopore sequencing (b). T tests were used to identify significant differences between the relative expression level and CPM value. Each value is presented as the mean ± SD.