title: Mass spectral molecular networking of living microbial colonies.
abstract: 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.
authors.affiliation: Department of Pharmacology, University of California at San Diego, La Jolla, CA 92093, USA.
authors.forename: Jeramie
authors.initials: J
authors.lastname: Watrous
authors.forename: Patrick
authors.initials: P
authors.lastname: Roach
authors.forename: Theodore
authors.initials: T
authors.lastname: Alexandrov
authors.forename: Brandi S
authors.initials: BS
authors.lastname: Heath
authors.forename: Jane Y
authors.initials: JY
authors.lastname: Yang
authors.forename: Roland D
authors.initials: RD
authors.lastname: Kersten
authors.forename: Menno
authors.initials: M
authors.lastname: van der Voort
authors.forename: Kit
authors.initials: K
authors.lastname: Pogliano
authors.forename: Harald
authors.initials: H
authors.lastname: Gross
authors.forename: Jos M
authors.initials: JM
authors.lastname: Raaijmakers
authors.forename: Bradley S
authors.initials: BS
authors.lastname: Moore
authors.forename: Julia
authors.initials: J
authors.lastname: Laskin
authors.forename: Nuno
authors.initials: N
authors.lastname: Bandeira
authors.forename: Pieter C
authors.initials: PC
authors.lastname: Dorrestein
mesh_terms: D001412:Bacillus subtilis / Q000235:genetics / Q000378:metabolism*; D001483:Base Sequence; D013058:Mass Spectrometry / Q000379:methods*; D005810:Multigene Family; D020102:Mycobacterium smegmatis / Q000235:genetics / Q000378:metabolism*; D011550:Pseudomonas aeruginosa / Q000235:genetics / Q000378:metabolism*; D048372:Streptomyces coelicolor / Q000235:genetics / Q000378:metabolism*