Web of microbes (WoM): a curated microbial exometabolomics database for linking chemistry and microbes

Background

As microbiome research becomes increasingly prevalent in the fields of human health, agriculture and biotechnology, there exists a need for a resource to better link organisms and environmental chemistries. Exometabolomics experiments now provide assertions of the metabolites present within specific environments and how the production and depletion of metabolites is linked to specific microbes. This information could be broadly useful, from comparing metabolites across environments, to predicting competition and exchange of metabolites between microbes, and to designing stable microbial consortia. Here, we introduce Web of Microbes (WoM; freely available at: http://webofmicrobes.org), the first exometabolomics data repository and visualization tool.

Description

WoM provides manually curated, direct biochemical observations on the changes to metabolites in an environment after exposure to microorganisms. The web interface displays a number of key features: (1) the metabolites present in a control environment prior to inoculation or microbial activation, (2) heatmap-like displays showing metabolite increases or decreases resulting from microbial activities, (3) a metabolic web displaying the actions of multiple organisms on a specified metabolite pool, (4) metabolite interaction scores indicating an organism’s interaction level with its environment, potential for metabolite exchange with other organisms and potential for competition with other organisms, and (5) downloadable datasets for integration with other types of -omics datasets.

Conclusion

We anticipate that Web of Microbes will be a useful tool for the greater research community by making available manually curated exometabolomics results that can be used to improve genome annotations and aid in the interpretation and construction of microbial communities.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1256-y) contains supplementary material, which is available to authorized users.

Staphylococcus aureus methicillin resistance detected by HPLC-MS/MS targeted metabolic profiling

Recently, novel bioanalytical methods, such as NMR and mass spectrometry based metabolomics approaches, have started to show promise in providing rapid, sensitive and reproducible detection of Staphylococcus aureus antibiotic resistance. Here we performed a proof-of-concept study focused on the application of HPLC-MS/MS based targeted metabolic profiling for detecting and monitoring the bacterial metabolic profile changes in response to sub-lethal levels of methicillin exposure. One hundred seventy-seven targeted metabolites from over 20 metabolic pathways were specifically screened and one hundred and thirty metabolites from in vitro bacterial tests were confidently detected from both methicillin susceptible and methicillin resistant Staphylococcus aureus (MSSA and MRSA, respectively). The metabolic profiles can be used to distinguish the isogenic pairs of MSSA strains from MRSA strains, without or with sub-lethal levels of methicillin exposure. In addition, better separation between MSSA and MRSA strains can be achieved in the latter case using principal component analysis (PCA). Metabolite data from isogenic pairs of MSSA and MRSA strains were further compared without and with sub-lethal levels of methicillin exposure, with metabolic pathway analyses additionally performed. Both analyses suggested that the metabolic activities of MSSA strains were more susceptible to the perturbation of the sub-lethal levels of methicillin exposure compared to the MRSA strains.