Publication Date:
2022-01-18
Description:
A powerful data mining tool was developed which allows detailed analysis of microbial metabolite fingerprints. This approach was applied to HRMS data obtained from the fermentation of eight actinomycetes treated with subinhibitory concentrations of six different antibiotics in order to monitor stimulations in secondary metabolite production. Each strain was fermented in medium containing a) no antibiotic b) a quarter of its specific MIC (MIC/4) and c) a 400 fold dilution of its MIC (MIC/400). The production of 21 ions was stimulated as response to antibiotic exposure. All of them were characterized as specific adduction products (as consequence of the ionisation process) and their predicted molecular formula was compared with formulas of known compounds. A portion of 9 identified adducts could not be found in commercial databases and is considered to be putatively new. Chloramphenicol, penicillin G and actinomycin D induced most secondary metabolites in the selected actinomycete strains and therefore might be considered for further research. Known effects like the expression of silent genes coding for the siderophore ferrioxamine, the enhanced expression of streptophenazines in response to antibiotic treatment and the stimulation of many unidentified compounds was demonstrated. Additionally it was shown that Kitosatospora griseola MF730-N6 is capable of performing the glycosylation of the ionophor nigericin. It could be demonstrated that the supplementation of subinhibitory concentrations of antibiotics to actinomycete fermentations can activate silent gene cluster expression and is therefore a valuable technique in drug discovery programs. The results of this study represent the unexplored potential and hidden metabolic capacity of both new and well-studied organisms.
Keywords:
Course of study: MSc Biological Oceanography
Type:
Thesis
,
NonPeerReviewed
Format:
text
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