Connecting Chemotypes and Phenotypes of Cultured Marine Microbial Assemblages by Imaging Mass Spectrometry

Since the early days of bacterial culturing over a century ago, microbiologists have known that microorganisms respond to their surroundings. Unicellular organisms rely on metabolic exchange to adapt to environmental stresses, sense colony density, occupy niches within hosts, and form biofilms. For example, Bacillus subtilis utilizes metabolic exchange to lyse neighboring microbes, including siblings, during sporulation, whereas other forms of metabolic exchange, such as the secretion of siderophores, stimulate the growth and development of Streptomyces and uncultured bacteria. Despite the importance of chemistry in biology, studies that connect chemotypes and phenotypes to adaptive microbial behavior in Petri dishes, including signaling and chemical warfare, have largely relied on indirect measurements for individual chemotypes and phenotypes. To connect the chemotypes and phenotypes in this study, we used MALDIbased imaging mass spectrometry (IMS) to observe the chemical output and metabolic exchange of a marine microbial assemblage in two dimensions. The ability to monitor the two-dimensional distribution of a wide array of metabolites simultaneously from a complex mixture of distinct organisms opens the door to comprehensive analyses of interspecies signaling interactions within a microbial assemblage in a spatial fashion. Analysis of the spatial distribution of these metabolites enables the generation of a testable hypothesis with respect to functions of the observed chemotypes, without the immediate need to know the structural characteristics. IMS provides the ability to correlate the presence of metabolites to phenotypic changes and to detect new chemotypes and/or phenotypes that cannot be observed by the naked eye. In this way, IMS enables prioritization of the molecules to be targeted for identification through proteomic and metabolomic approaches or to be subjected to mass spectrometry guided isolation and nuclear magnetic resonance based structure elucidation. Understanding of these molecular networks and interactions will illuminate how microbes respond to neighboring organisms and in turn influence and alter the growth of their neighbors. We demonstrate that IMS can be used to observe the chemical output within complex microbial assemblages. This information can then be used to prioritize the organisms and molecules for structural characterization. It is important to prioritize the molecules because the structural characterization of the molecules is one of the rate-limiting steps in our understanding of chemical cross-talk between organisms. We collected the marine microbial assemblage by scraping the slimy surface of a barnacle located on the pier of the Scripps Institution of Oceanography (University of California, San Diego), which extends into the Pacific Ocean. IMS was used to visualize the interactions between members of the microbial assemblage obtained from this barnacle and grown on solid media. Because a typical soil sample contains 10 colonyforming units (CFUs) per gram of soil, and an ocean sample typically contains 10 CFUs per milliliter of water, we anticipated that we would observe large numbers of colonies from this environmental sample. Therefore, the barnacle scrapings were serially diluted onto agar plates. Subsequently, the heterogeneous mixture of microorganisms was allowed to grow at 28 8C for 3 days (Figure 1a). Once distinct colonies were visible, a 4 cm by 2 cm region of agar was cut, laid on top of a MALDI target plate, and covered with a matrix of a-cyano-4-hydroxycinnamic acid and 2,5-dihydroxybenzoic acid. The matrix is required for the ionization of the molecules present along the surface of the sample. At the same time, the matrix effectively fixes the organisms in place when applied. Once covered with a matrix coating, the sample was subjected to IMS. IMS enables the visualization of metabolites that are secreted into the growth medium, as well as metabolites associated with the colonies themselves. Nine signals and their distributions are highlighted in Figure 1c. Each ion distribution is superimposed over the section of Figure 1a enclosed in the rectangle. Five of the signals are associated with colonies, and four are due to metabolites [*] W.-T. Liu, Prof. Dr. P. C. Dorrestein Department of Chemistry and Biochemistry University of California, San Diego Biomedical Science Building (BSB), Room 4090 9500 Gilman Drive, MC 0636, La Jolla, CA 92093-0636 (USA) E-mail: pdorrest@ucsd.edu Dr. Y.-L. Yang, Dr. Y. Xu, M. J. Meehan, Prof. Dr. B. S. Moore, Prof. Dr. N. Bandeira, Prof. Dr. P. C. Dorrestein Skaggs School of Pharmacy and Pharmaceutical Sciences University of California, San Diego, CA (USA)