Spatial Molecular Architecture of the Microbial Community of a Peltigera Lichen

Microbial mat
DOI: 10.1128/msystems.00139-16 Publication Date: 2016-12-21T01:50:25Z
ABSTRACT
Microbes are commonly studied as individual species, but they exist mixed assemblages in nature. At present, we know very little about the spatial organization of molecules, including natural products that produced within these microbial networks. Lichens represent a particularly specialized type symbiotic assemblage which component microorganisms together. These composite typically comprised several types representing phylogenetically diverse life forms, fungi, photosymbionts, bacteria, and other microbes. Here, employed matrix-assisted laser desorption ionization-time flight (MALDI-TOF) imaging mass spectrometry to characterize distributions small molecules Peltigera lichen. In order probe how organized localized consortium, analytes were annotated assigned their respective producer using spectrometry-based molecular networking metagenome sequencing. The analysis not only reveals an ordered layering lichen also supports compartmentalization unique functions attributed various layers. include chemical defense (e.g., antibiotics), light-harvesting associated with cyanobacterial outer layer chlorophyll), energy transfer sugars) surrounding sun-exposed layer, carbohydrates may serve structural or storage function observed higher intensities non-sun-exposed areas complex carbohydrates). IMPORTANCE Microbial communities have evolved over centuries live symbiotically. direct visualization such at functional level presents challenge. Overcoming this challenge allow one visualize specific involved symbiosis define roles shaping community structure. study, examined diversity genes taxa presence biosynthetic gene clusters by metagenomic sequencing organic components spectrometry. This approach allowed identification chemically distinct sections organism. Using our multipronged approach, fungal products, previously reported from lichens, identified two different layers visualized level.
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