GC⁻MS-Based Nontargeted and Targeted Metabolic Profiling Identifies Changes in the Lentinula edodes Mycelial Metabolome under High-Temperature Stress

Abstract

To clarify the physiological mechanism of the Lentinula edodes (L. edodes) response to high-temperature stress, two strains of L. edodes with different tolerances were tested at different durations of high temperature, and the results showed that there were significant changes in their phenotypes and physiology. To further explore the response mechanism, we established a targeted GC-MS-based metabolomics workflow comprising a standardized experimental setup for growth, treatment and sampling of L. edodes mycelia, and subsequent GC-MS analysis followed by data processing and evaluation of quality control (QC) measures using tailored statistical and bioinformatic tools. This study identified changes in the L. edodes mycelial metabolome following different time treatments at high temperature based on nontargeted metabolites with GC-MS and further adopted targeted metabolomics to verify the results of the analysis. After multiple statistical analyses were carried out using SIMCA software, 74 and 108 differential metabolites were obtained, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the metabolic pathways with significant changes included those related to the following: amino acid metabolism, the glycolysis pathway, the tricarboxylic acid (TCA) cycle, and sugar metabolism. Most amino acids and carbohydrates enriched in these metabolic pathways were upregulated in strain 18, downregulated in strain 18N44, or the synthesis in strain 18 was higher than that in strain 18N44. This result was consistent with the physiological phenotypic characteristics of the two strains under high-temperature stress and revealed the reason why strain 18N44 was more heat-sensitive. At the same time, under high temperature, the decrease of intermediate products in glycolysis and the TCA cycle resulted in carbon starvation and insufficient energy metabolism, thus inhibiting the growth of L. edodes. In addition, the results also showed that the metabolites produced by different L. edodes strains under high-temperature stress were basically the same. However, different strains had species specificity, so the changes in the content of metabolites involved in the response to high-temperature stress were different. This provides a theoretical basis for further understanding the mechanism of the L. edodes response to high temperature and can be used to establish an evaluation system of high-temperature-resistant strains and lay the foundation for molecular breeding of new L. edodes strains resistant to high temperature.

Keywords: GC-MS; Lentinula edodes; high temperature stress; metabolomics.

Figure 1

Heat stress inhibited the growth of Lentinula edodes mycelia. (A) Two strains of L. edodes were cultured on PDA plates for 6 d and then exposed to 37 °C for 0 to 24 h followed by 6 days at 25 °C. (B) The morphology of mycelial growth for the entire 13 days (blue line) and the following 6 days at 25 °C (after heat stress) (red line) is shown. (C) Microscopically, the mycelial morphology changed after 24 h of heat stress. Vegetative hyphae were removed from actively growing colonies, suspended in Fluorescent Brightener 28, and detected under a microscope. (D) Recovery of the mycelial growth rate of L. edodes after heat stress. The values are the means ± SD of three independent experiments.

Figure 2

Determination of physiological indices of L. edodes mycelium under high stress. (A) Change in the mycelial conductivity of L. edodes under high stress. (B) Changes in the malondialdehyde (MDA) content of L. edodes after heat stress. The values are the means ± SD of three independent experiments.

Figure 3

(A) (strain 18) and (B) (strain 18N44) samples were aligned with the original peak of total ion current; seven repeated samples were taken for each treatment.

Figure 4

SIMCA software (V14) was used to perform multivariate variable pattern recognition for the normalized data. (A) Principal component analysis score plot of two strains treated at different times and quality control samples. (B,C) Score plot of partial least square discriminant analysis (PLS-DA) and orthogonal partial least square discriminant analysis (OPLS-DA) derived from the GC–MS profiles of serum samples obtained from the heat stress (4 h) group versus the normal control (0 h) group. (D) Response ordering test for the OPLS-DA model. (B–D) show strain 18 at 4 h versus 0 h as an example, and others are shown in Supplementary Materials.

Figure 5

Venn diagram and heat map of different metabolites. (A,C) Venn diagram analysis of different metabolites from strains 18 and 18N44 under different heat stress durations. (B,D) Using Venn diagram analysis results, the heat map shows the significantly different metabolite changes of strains 18 and 18N44 under different heat stress times.

Figure 6

Pathway enrichment analysis of metabolites. A color-coded bar on the right represents the levels of significance. The green color indicates extremely significant levels at (p < 0.01), while red color indicates significant levels at (p < 0.05). The circles represent the number of metabolites involved or enriched in the pathway. Enrich factor refers to the ratio of the number of differential metabolites expressed in the corresponding pathway to the total number of metabolites annotated by the pathway. The greater the value the greater is the degree of the enrichment.

Figure 7

Schematic overview of some important metabolites and major metabolic pathways related to amino acid and energy metabolism in heat-stressed L. edodes mycelia. Strain 18 upregulation, strain 18 downregulation. Strain 18N44 upregulation, strain 18N44 downregulation. Gray indicates no significantly different metabolic.

Figure 8

Verification of targeted metabolomics for the content changes of 12 metabolites. The targeted content determination result of 12 metabolites. The values are the means ± SD of three independent experiments. Note: Red bars with standard errors represent the content level determined by targeted GC–MS-based metabolomics (left Y-axis). Broken lines indicate the relative expression level determined by nontargeted GC–MS-based metabolomics (right Y-axis). All 12 metabolites were derived from strain 18.