Postulating Modes of Action of Compounds with Antimicrobial Activities through Metabolomics Analysis

Use of GC-MS based metabolic fingerprinting for fast exploration of fungicide modes of action

BACKGROUND

The widespread occurrence of fungicide resistance in fungal plant pathogens requires the development of new compounds with different mode(s) of action (MOA) to avoid cross resistance. This will require a rapid method to identify MOAs.

RESULTS

Here, gas chromatography-mass spectrometry (GC-MS) based metabolic fingerprinting was used to elucidate the MOAs of fungicides. Botrytis cinerea, an important pathogen of vegetables and flowers, can be inhibited by a wide range of chemical fungicides with different MOAs. A sensitive strain of B. cinerea was exposed to EC₅₀ concentrations of 13 fungicides with different known MOAs and one with unknown MOA. The mycelial extracts were analyzed for their "metabolic fingerprint" using GC-MS. A comparison among the GC-MS vector' profiles of cultures treated with fungicides were performeded. A model based on hierarchical clustering was established which allowed these antifungal compounds to be distinguished and classified coinciding with their MOAs. Thus, metabolic fingerprinting represents a rapid, convenient, and information-rich method for classifying the MOAs of antifungal substances. The biomarkers of fungicide MOAs were also established by an analysis of variance and included succinate for succinate dehydrogenase inhibitors and cystathionine for methionine synthesis inhibitors. Using the metabolic model and the common perturbation of metabolites, the new fungicide SYP-14288 was identified as having the same MOA as fluazinam.

CONCLUSION

This study provides a comprehensive database of the metabolic perturbations of B. cinerea induced by diverse MOA inhibitors and highlights the utility of metabolic fingerprinting for defining MOAs, which will assist in the development and optimization of new fungicides.

Comparative mass spectrometry-based metabolomics strategies for the investigation of microbial secondary metabolites

Covering: 2000 to 2016The labor-intensive process of microbial natural product discovery is contingent upon identifying discrete secondary metabolites of interest within complex biological extracts, which contain inventories of all extractable small molecules produced by an organism or consortium. Historically, compound isolation prioritization has been driven by observed biological activity and/or relative metabolite abundance and followed by dereplication via accurate mass analysis. Decades of discovery using variants of these methods has generated the natural pharmacopeia but also contributes to recent high rediscovery rates. However, genomic sequencing reveals substantial untapped potential in previously mined organisms, and can provide useful prescience of potentially new secondary metabolites that ultimately enables isolation. Recently, advances in comparative metabolomics analyses have been coupled to secondary metabolic predictions to accelerate bioactivity and abundance-independent discovery work flows. In this review we will discuss the various analytical and computational techniques that enable MS-based metabolomic applications to natural product discovery and discuss the future prospects for comparative metabolomics in natural product discovery.

Staphylococcus aureus metabolic response to changing environmental conditions - a metabolomics perspective

Microorganisms preserve their metabolic function against a wide range of external perturbations including biotic or abiotic factors by utilizing cellular adaptations to maintain cell homeostasis. Functional genomics aims to detect such adaptive alterations on the level of transcriptome, proteome and metabolome to understand system wide changes and to identify interactions between the different levels of biochemical organization. Microbial metabolomics measures metabolites, the direct biochemical response to the environment, and is pivotal to the understanding of the variability and dynamics of bacterial cell metabolism. Metabolomics can measure many different types of compounds including primary metabolites, secondary metabolites, second messengers, quorum sensing compounds and others, which all contribute to the complex bacterial response to an environmental change. Recent data confirmed that many metabolic processes in pathogenic bacteria are linked to virulence and invasive capabilities. Deciphering bacterial metabolism in response to specific environmental conditions and in specific genetic backgrounds will help map the complex network between the metabolome and the other "-omes". Here, we will review a selection of case studies for the pathogenic Gram-positive bacterium Staphylococcus aureus and summarize the current state of metabolomics literature covering staphylococci metabolism under different physiological states.

Determination of antiprotozoal drug mechanisms by metabolomics approaches

The discovery, development and optimal utilization of pharmaceuticals can be greatly enhanced by knowledge of their modes of action. However, many drugs currently on the market act by unknown mechanisms. Untargeted metabolomics offers the potential to discover modes of action for drugs that perturb cellular metabolism. Development of high resolution LC-MS methods and improved data analysis software now allows rapid detection of drug-induced changes to cellular metabolism in an untargeted manner. Several studies have demonstrated the ability of untargeted metabolomics to provide unbiased target discovery for antimicrobial drugs, in particular for antiprotozoal agents. Furthermore, the utilization of targeted metabolomics techniques has enabled validation of existing hypotheses regarding antiprotozoal drug mechanisms. Metabolomics approaches are likely to assist with optimization of new drug candidates by identification of drug targets, and by allowing detailed characterization of modes of action and resistance of existing and novel antiprotozoal drugs.