Aspergillus niger Environmental Isolates and Their Specific Diversity Through Metabolite Profiling

Front Microbiol. 2021 Jun 23:12:658010. doi: 10.3389/fmicb.2021.658010. eCollection 2021.

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.

Keywords: Aspergillus niger environmental isolates; Biolog FF MicroplateTM; extrolite profile; molecular analyses; multi-criteria data analysis.