Microbes are commonly studied as individual species, but they exist as mixed assemblages in nature. At present, we know very little about the spatial organization of the molecules, including natural products that are produced within these microbial networks. Lichens represent a particularly specialized type of symbiotic microbial assemblage in which the component microorganisms exist together. These composite microbial assemblages are typically comprised of several types of microorganisms representing phylogenetically diverse life forms, including fungi, photosymbionts, bacteria, and other microbes. Here, we employed matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) imaging mass spectrometry to characterize the distributions of small molecules within a Peltigera lichen. In order to probe how small molecules are organized and localized within the microbial consortium, analytes were annotated and assigned to their respective producer microorganisms using mass spectrometry-based molecular networking and metagenome sequencing. The spatial analysis of the molecules not only reveals an ordered layering of molecules within the lichen but also supports the compartmentalization of unique functions attributed to various layers. These functions include chemical defense (e.g., antibiotics), light-harvesting functions associated with the cyanobacterial outer layer (e.g., chlorophyll), energy transfer (e.g., sugars) surrounding the sunexposed cyanobacterial layer, and carbohydrates that may serve a structural or storage function and are observed with higher intensities in the non-sun-exposed areas (e.g., complex carbohydrates).
Bibliographical noteFunding Information:
We acknowledge support for this work from the European Union Seventh Frame-work Program (grant 305259 to S.S., T.A., and P.C.D.) and the EU Framework Programme Horizon 2020 (grant 634402 to T.A.). L.S. was supported by the National Institutes of Health IRACDA K12 GM068524 award. T.L.-K. was supported by the United States–Israel Binational Agricultural Research and Development Fund, Vaadia-BARD FI-494-13. A.G. was supported by St. Petersburg State University, St. Petersburg, Russia (grant number 15.61.951.2015). The Collaborative Mass Spectrometry Center was partially funded by Bruker and NIH grant GMS10RR029121 (P.C.D.). H.M., P.C.D., and P.A.P. were supported by the U.S. National Institutes of Health (grant 2-P41-GM103484).
This work, including the efforts of Tal Luzzatto-Knaan, was funded by Binational Agriculture Research and Development Fund (FI-494-13). This work, including the efforts of Alexey Gurevich, was funded by St. Petersburg State University, Russia (15.61.951.2015). This work, including the efforts of Stefan Schiffler and Theodore Alexandrov, was funded by Europeon Union Seventh Framework Program (305259). This work, including the efforts of Laura M. Sanchez, was funded by National Institute of Health IRACDA (GM068524). This work, including the efforts of Theodore Alexandrov, was funded by EC | Horizon 2020 (EU Framework Programme for Research and Innovation) (634402). This work, including the efforts of Hosein Mohimani and Pavel A. Pevzner, was funded by the U.S. National Institutes of Health (2-P41-GM103484).
The authors acknowledge support for this work by European Union Seventh Framework Program (grant 305259 to S.S., T.A., P.C.D.) and EU Framework Programme Horizon 2020 (grant 634402 to T.A.). L.M.S. was supported by National Institutes of Health IRACDA K12 GM068524 award. T.L.-K. was supported by the United States - Israel Binational Agricultural Research and Development Fund, Vaadia-BARD FI-494-13. The Collaborative Mass Spectrometry Center was partially funded by Bruker and NIH grant GMS10RR029121 (P.C.D.).
Copyright © 2016 Garg et al.
- Mass spectrometry
- Microbial assemblages
- Natural products
ASJC Scopus subject areas
- Ecology, Evolution, Behavior and Systematics
- Modeling and Simulation
- Molecular Biology
- Computer Science Applications