Integrated metabolomics and lipidomics analyses suggest the temperature-dependent lipid desaturation promotes aflatoxin biosynthesis in Aspergillus flavus

Abstract

Temperature is one of the main factors affecting aflatoxin (AF) biosynthesis in Aspergillus flavus. Previous studies showed that AF biosynthesis is elevated in A. flavus at temperatures between 28°C-30°C, while it is inhibited at temperatures above 30°C. However, little is known about the metabolic mechanism underlying temperature-regulated AF biosynthesis. In this study, we integrated metabolomic and lipidomic analyses to investigate the endogenous metabolism of A. flavus across 6 days of mycelia growth at 28°C (optimal AF production) and 37°C (no AF production). Results showed that both metabolite and lipid profiles were significantly altered at different temperatures. In particular, metabolites involved in carbohydrate and amino acid metabolism were up-regulated at 37°C on the second day but down-regulated from days three to six. Moreover, lipidomics and targeted fatty acids analyses of mycelia samples revealed a distinct pattern of lipid species and free fatty acids desaturation. High degrees of polyunsaturation of most lipid species at 28°C were positively correlated with AF production. These results provide new insights into the underlying metabolic changes in A. flavus under temperature stress.

Keywords: Aspergillus flavus; aflatoxins; lipidomics; metabolomics; temperature.

Figure 1

The physiological effect of temperature on Aspergillus flavus. (A) Mycelia phenotypes after 3 days of incubation and mycelia dry weight over 6 days. (B) Glucose and NH4⁺ contents in GMS media across 6 days. (C) The contents of AFs and kojic acid in GMS media across 6 days.

Figure 2

Multivariate statistical analysis of metabolomic data from A. flavus. (A) The classification and proportion of identified metabolites in A. flavus were obtained using GC–MS. (B) OPLS-DA score plots of GC–MS data for the T28 and T37 mycelia samples collected on the 2^nd to 6^th days. (C) Heat map showing Log₂FC values for 50 metabolites differentially accumulated between T28 and T37 mycelia samples growth from the 2^nd to 6^th days. The relative abundance of each metabolite was normalized to the mean value from the T28 samples on different days.

Figure 3

Pathway analysis and meta-analysis between the T28 and T37 mycelia samples. (A) Enrichment analysis and pathway meta-analysis of differentially accumulated primary metabolites. The enriched pathways were ranked using the pathway-level p-values (Meta.p). (B) An overview of metabolites involved in primary metabolism, showing the differences in metabolite levels among the T28-2d and T37-2d samples. (C) The relative content curves of primary metabolites. Significance was determined by the t-test. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001, ^****p < 0.0001.

Figure 4

Multivariate statistical analysis of lipidomic data from A. flavus. (A) Bar diagrams showing the number of peaks detected and lipids identified by LC–MS both in the positive and negative ion modes. (B) The number of identified lipid species in different classes. (C) OPLS-DA score plots of lipidome in mycelia samples detected by LC–MS in the positive ion mode. (D) OPLS-DA score plots of lipidome in mycelia samples detected by LC–MS in the negative ion mode. (E) Heat map showing Log₂FC values for 58 lipids differentially accumulated between the T28 and T37 mycelia samples.

Figure 5

Effects of temperature on the contents of fatty acids and the fatty acid metabolism-related genes expression. (A) The relative contents of fatty acids quantified by GC–MS. Significance was determined by the t-test. ^*p < 0.05, ^**p < 0.01, ^***p < 0.001, ^****p < 0.0001. (B) the Log₂FC of gene expression levels of fatty acid desaturases as measured via qRT-PCR.