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Watrous, Jeramie; Roach, Patrick; Alexandrov, Theodore; Heath, Brandi S.; Yang, Jane Y.; Kersten, Roland D.; van der Voort, Menno; Pogliano, Kit; Gross, Harald; Raaijmakers, Jos M.; Moore, Bradley S.; Laskin, Julia; Bandeira, Nuno; Dorrestein, Pieter C.

Mass spectral molecular networking of living microbial colonies

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  • Media type: E-Article
  • Title: Mass spectral molecular networking of living microbial colonies
  • Contributor: Watrous, Jeramie; Roach, Patrick; Alexandrov, Theodore; Heath, Brandi S.; Yang, Jane Y.; Kersten, Roland D.; van der Voort, Menno; Pogliano, Kit; Gross, Harald; Raaijmakers, Jos M.; Moore, Bradley S.; Laskin, Julia; Bandeira, Nuno; Dorrestein, Pieter C.
  • Published: Proceedings of the National Academy of Sciences, 2012
  • Published in: Proceedings of the National Academy of Sciences, 109 (2012) 26
  • Language: English
  • DOI: 10.1073/pnas.1203689109
  • ISSN: 0027-8424; 1091-6490
  • Origination:
  • Footnote:
  • Description: Integrating the governing chemistry with the genomics and phenotypes of microbial colonies has been a “holy grail” in microbiology. This work describes a highly sensitive, broadly applicable, and cost-effective approach that allows metabolic profiling of live microbial colonies directly from a Petri dish without any sample preparation. Nanospray desorption electrospray ionization mass spectrometry (MS), combined with alignment of MS data and molecular networking, enabled monitoring of metabolite production from live microbial colonies from diverse bacterial genera, including Bacillus subtilis, Streptomyces coelicolor, Mycobacterium smegmatis , and Pseudomonas aeruginosa . This work demonstrates that, by using these tools to visualize small molecular changes within bacterial interactions, insights can be gained into bacterial developmental processes as a result of the improved organization of MS/MS data. To validate this experimental platform, metabolic profiling was performed on Pseudomonas sp. SH-C52, which protects sugar beet plants from infections by specific soil-borne fungi [R. Mendes et al. (2011) Science 332:1097–1100]. The antifungal effect of strain SH-C52 was attributed to thanamycin, a predicted lipopeptide encoded by a nonribosomal peptide synthetase gene cluster. Our technology, in combination with our recently developed peptidogenomics strategy, enabled the detection and partial characterization of thanamycin and showed that it is a monochlorinated lipopeptide that belongs to the syringomycin family of antifungal agents. In conclusion, the platform presented here provides a significant advancement in our ability to understand the spatiotemporal dynamics of metabolite production in live microbial colonies and communities.
  • Access State: Open Access