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Aspergillus niger Environmental Isolates and Their Specific Diversity Through Metabolite Profiling.

ABSTRACT: We present a biological profile of 16 Aspergillus niger environmental isolates from different types of soils and solid substrates across a pH range, from an ultra-acidic (<3.5) to a very strongly alkaline (>9.0) environment. The soils and solid substrates also differ in varying degrees of anthropic pollution, which in most cases is caused by several centuries of mining activity at old mining sites, sludge beds, ore deposits, stream sediments, and coal dust. The values of toxic elements (As, Sb, Zn, Cu, Pb) very often exceed the limit values. The isolates possess different macro- and micromorphological features. All the identifications of Aspergillus niger isolates were confirmed by molecular PCR analysis and their similarity was expressed by RAMP analysis. The biochemical profile of isolates based on FF-MicroPlate tests from the Biolog system showed identical biochemical reactions in 50 tests, while in 46 tests the utilisation reactions differed. The highest similarity of strains isolated from substrates with the same pH, as well as the most suitable biochemical tests for analysis of the phenotypic similarity of isolated strains, were confirmed when evaluating the biochemical profile using multicriterial analysis in the Canoco program. The isolates were screened for mycotoxin production by thin-layer chromatography (TLC), as well. Two of them were able to synthesise ochratoxin A, while none produced fumonisins under experimental conditions. Presence of toxic compounds in contaminated sites may affect environmental microscopic fungi and cause the genome alteration, which may result in changes of their physiology, including the production of different (secondary) metabolites, such as mycotoxins.

SUBMITTER: Simonovicova A

PROVIDER: S-EPMC8261049 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Aspergillus tubingensis is an important pathogen of economically important crops. Different biotic stresses strongly influence the balance of metabolites in plants. The aim of this study was to understand the function and response of resistance associated metabolites which, in turn are involved in many secondary metabolomics pathways to influence defense mechanism of cotton plant. Analysis of non-targeted metabolomics using ultra high performance liquid chromatography-mass spectrometry (UPLC-MS) revealed abundant accumulation of key metabolites including flavonoids, phenylpropanoids, terpenoids, fatty acids and carbohydrates, in response to leaf spot of cotton. The principal component analysis (PCA), orthogonal partial least squares discriminant analysis (OPLS-DA) and partial least squares discriminant analysis (PLS-DA) score plots illustrated the evidences of variation between two varieties of cotton under mock and pathogen inoculated treatments. Primary metabolism was affected by the up regulation of pyruvate and malate and by the accumulation of carbohydrates like cellobiose and inulobiose. Among 241 resistance related (RR) metabolites, 18 were identified as resistance related constitutive (RRC) and 223 as resistance related induced (RRI) metabolites. Several RRI metabolites, identified in the present study were the precursors for many secondary metabolic pathways. These included phenylpropanoids (stilbenes and furanocoumarin), flavonoids (phlorizin and kaempferol), alkaloids (indolizine and acetylcorynoline) and terpenoids (azelaic acid and oleanolic acid). Our results demonstrated that secondary metabolism, primary metabolism and energy metabolism were more active in resistant cultivar, as compared to sensitive cultivar. Differential protein and fatty acid metabolism was also depicted in both cultivars. Accumulation of these defense related metabolites in resistant cotton cultivar and their suppression in susceptible cotton cultivar revealed the reason of their respective tolerance and susceptibility against A. tubingensis.

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Aspergillus niger Environmental Isolates and Their Specific Diversity Through Metabolite Profiling.

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