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Bacterial–fungal interactions (BFIs) can shape the structure of microbial communities, but the small molecules mediating these BFIs are often understudied. We explored various optimization steps for our microbial culture and chemical extraction protocols for bacterial–fungal co-cultures, and liquid chromatography-tandem mass spectrometry (LC-MS/MS) revealed that metabolomic profiles are mainly comprised of fungi derived features, indicating that fungi are the key contributors to small molecules in BFIs. LC-inductively coupled plasma MS (LC-ICP-MS) and MS/MS based dereplication using database searching revealed the presence of several known fungal specialized metabolites and structurally related analogues in these extracts, including siderophores such as desferrichrome, desferricoprogen, and palmitoylcoprogen. Among these analogues, a novel putative coprogen analogue possessing a terminal carboxylic acid motif was identified from Scopulariopsis sp. JB370, a common cheese rind fungus, and its structure was elucidated via MS/MS fragmentation. Based on these findings, filamentous fungal species appear to be capable of producing multiple siderophores with potentially different biological roles ( i.e. various affinities for different forms of iron). These findings highlight that fungal species are important contributors to microbiomes via their production of abundant specialized metabolites and that elucidating their role in complex communities should continue to be a priority.
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BLANKA: an Algorithm for Blank Subtraction in Mass Spectrometry of Complex Biological Samples
Multispecies microbiome systems are known to be closely linked to human, animal, and plant life processes. The growing field of metabolomics presents the opportunity to detect changes in overall metabolomic profiles of microbial species interactions. These metabolomic changes provide insight into function of metabolites as they correlate to different species presence and the observed phenotypic changes, but detection of subtle changes is often difficult in samples with complex backgrounds. Natural environments such as soil and food contain many molecules that convolute mass spectrometry-based analyses, and identification of microbial metabolites amongst environmental metabolites is an informatics problem we begin to address here. Our microbes are grown on solid or liquid cheese curd media. This medium, which is necessary for microbial growth, contains high amounts of salts, lipids, and casein breakdown products which make statistical analyses using LC-MS/MS data difficult due to the high background from the media. We have developed a simple algorithm to carry out background subtraction from microbes grown on solid or liquid cheese curd media to aid in our ability to conduct statistical analyses so that we may prioritize metabolites for further structure elucidation.
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- PAR ID:
- 10094991
- Date Published:
- Journal Name:
- Journal of The American Society for Mass Spectrometry
- ISSN:
- 1044-0305
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1007/s13361-019-02185-8
