Biodiversity in targeted metabolomics analysis of filamentous fungal pathogens by 1H NMR-based studies

Abstract

The taxonomical classification among fungi kingdom in the last decades was evolved. In this work the targeted metabolomics study based on 1H NMR spectroscopy combined with chemometrics tools was reported to be useful for differentiation of three model of fungal strains, which represent various genus of Ascomycota (Aspergillus pallidofulvus, Fusarium oxysporum, Geotrichum candidum) were selected in order to perform metabolomics studies. Each tested species, revealed specific metabolic profile of primary endo-metabolites. The species of A. pallidofulvus is represented by the highest concentration of glycerol, glucitol and Unk5. While, F. oxysporum species is characterised by increased level of propylene glycol, ethanol, 4-aminobutyrate, succinate, xylose, Unk1 and Unk4. In G. candidum, 3-methyl-2-oxovalerate, glutamate, pyruvate, glutamine and citrate were elevated. Additionally, a detailed analysis of metabolic changes among A. pallidofulvus, F. oxysporum and G. candidum showed that A. pallidofulvus seems to be the most pathogenic fungi. The obtained results demonstrated that targeted metabolomics analysis could be utilized in the future as a supporting taxonomical tool for currently methods.Graphical Abstract

Intracellular Metabolomics Switching Alters Extracellular Acid Production and Insoluble Phosphate Solubilization Behavior in Penicillium oxalicum

“…The metabolites involved in phosphatidylcholine synthesis (acetylcholine and choline) were balanced based on the levels of Sol-P control, but phosphorylcholine and sn-glycerol 3-phosphoethanolamine (sn-glycerol 3-PEA) were significantly increased (FC values > 2), especially under TP exposure-and this appeared to be related to Sol-P control (Figure 4 and Figure S8). One reasonable explanation for this pattern is that all of the metabolites involved in lipid biosynthesis to form cellular membranes, the observed biomass switches (TP > IP > Sol-P in Figure S1) were consistent with the phospholipid metabolites that were observed to be released in all of the treatments [34]. Therefore, to a large extent, the up-regulation of phospholipid metabolism could promote the formation of the membrane and reflect the production of biomass eventually.…”

Metabolic Plasticity of Candida albicans in Response to Different Environmental Conditions

“…Yeasts represent the best eukaryotic model, and comparative analyses of their metabolic profiles under different experimental conditions, in the presence of drugs, or when using genetically manipulated strains have provided precious hints at the molecular level [ 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 ]. The combination of the pathogenic microorganisms’ metabolome with the infection-associated changes in the host’s metabolism is expected to offer a more complete comprehension of the infective process [ 41 , 42 , 43 , 44 , 45 , 46 ].…”

Catch the wave: Metabolomic analyses in human pathogenic fungi

“… An overview of the metabolomics approaches utilized to date in human pathogenic fungi, with a primary focus on Aspergillus , Candida , Cryptococcus , and Mucor spp. In Aspergillus , metabolomic studies were used to identify secondary metabolites and biomarkers as a means to improve earlier detection and diagnosis of aspergillosis [ 4 , 5 , 10 , 11 , 15 – 17 , 40 , 41 ]. To date, metabolomics approaches have not been utilized to investigate the primary metabolism of Aspergillus spp., which has been the main focus of C .…”

“…A study searching for novel aspergillosis-specific biomarkers compared the secreted metabolites from 30 strains of several pathogenic fungi and identified a novel Aspergillus -specific linear tetrapeptide named aspergitide [ 16 ]. Another work utilized metabolomic-based approaches to improve the taxonomical identification of common human fungal pathogens [ 17 ]. A total of 45 primary metabolites from A .…”