Abstract
Aspergillus pachycristatus is an industrially important fungus for the production of the antifungal echinocandin B and is closely related to model organism A. nidulans. Its secondary metabolism is largely unknown except for the production of echinocandin B and sterigmatocystin. We constructed mutants for three genes that regulate secondary metabolism in A. pachycristatus NRRL 11440, and evaluated the secondary metabolites produced by wild type and mutants strains. The secondary metabolism was explored by metabolic networking of UPLC-HRMS/MS data. The genes and metabolites of A. pachycristatus were compared to those of A. nidulans FGSC A4 as a reference to identify compounds and link them to their encoding genes. Major differences in chromatographic profiles were observable among the mutants. At least 28 molecules were identified in crude extracts that corresponded to nine characterized gene clusters. Moreover, metabolic networking revealed the presence of a yet unexplored array of secondary metabolites, including several undescribed fellutamides derivatives. Comparative reference to its sister species, A. nidulans, was an efficient way to dereplicate known compounds, whereas metabolic networking provided information that allowed prioritization of unknown compounds for further metabolic exploration. The mutation of global regulator genes proved to be a useful tool for expanding the expression of metabolic diversity in A. pachycristatus.
Highlights
Secondary metabolites from fungi are a plentiful and valuable source of molecules that exhibit a wide range of chemical structures and biological activities
Remarkable qualitative differences were evident among them indicating changes in secondary metabolism
It was possible to observe the appearance of several peaks in 4Apc.veA and 4Apc.mcrA
Summary
Secondary metabolites from fungi are a plentiful and valuable source of molecules that exhibit a wide range of chemical structures and biological activities. Development and application of efficient methods for molecular dereplication in complex samples with minimal sample work-up are needed to guide the decision-making process One such method employs untargeted liquid chromatography coupled to tandem high-resolution mass spectrometry (LC-HRMS/MS) and takes advantage of both high-resolution monoisotopic mass measurements and MS/MS fragmentation profiles to generate data which can be used to detect and Molecules 2020, 25, 913; doi:10.3390/molecules25040913 www.mdpi.com/journal/molecules. The significant amounts of data generated are interrogated against databases to identify known substances without the need for purification of each individual component These spectra can further be used as input for generation of molecular networks, clusters of known and unknown molecules linked based on similarities found in their MS and MS/MS spectra, allowing for the classification of a large number of molecules, including previously unidentified substances [4]
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