Cytometric fingerprinting for analyzing microbial intracommunity structure variation and identifying subcommunity function

• Published in: Nature protocols Vol. 8; no. 1; pp. 190 - 202
• Main Authors: Koch, Christin, Günther, Susanne, Desta, Adey F, Hübschmann, Thomas, Müller, Susann
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.01.2013; Nature Publishing Group
• Subjects: 49/31; 631/1647/1407/1492; 631/1647/2230; 631/326/2565; Alternative energy sources; Analytical Chemistry; Bacteria - cytology; Bacteria - genetics; Biodiversity; Biological Techniques; Cell growth; Cellular Microenvironment; Computational Biology/Bioinformatics; Environmental monitoring; Ethiopia; Flow cytometry; Flow Cytometry - methods; Genetic aspects; Health aspects; Identification and classification; Life Sciences; Light scattering; Methods; Microarrays; Microbial activity; Microbial colonies; Microbial Interactions; Microorganisms; Organic Chemistry; Phylogenetics; Physiological aspects; Polymerase Chain Reaction - methods; Polymorphism, Restriction Fragment Length; Protocol; Soil microbiology; Waste Water - microbiology; Ethiopia; Germany; Addis Ababa Ethiopia
• ISSN: 1754-2189; 1750-2799
• DOI: 10.1038/nprot.2012.149

Functions of complex natural microbial communities are realized by single cells that contribute differently to the overall performance of a community. Usually, molecular and, more recently, deep-sequencing techniques are used for detailed but resource-consuming phylogenetic or functional analyses of microbial communities. Here we present a method for analyzing dynamic community structures that rapidly detects functional (rather than phylogenetic) coherent subcommunities by monitoring changes in cell-specific and abiotic microenvironmental parameters. The protocol involves the use of flow cytometry to analyze elastic light scattering and fluorescent cell labeling, with subsequent determination of cell gate abundance and finally the creation of a cytometric community fingerprint. Abiotic parameter analysis data are correlated with the dynamic cytometric fingerprint to obtain a time-bound functional heat map. The map facilitates the identification of activity hot spots in communities, which can be further resolved by subsequent cell sorting of key subcommunities and concurrent phylogenetic analysis (terminal restriction fragment length polymorphism, tRFLP). The cytometric fingerprint information is based on gate template settings and the functional heat maps are created using an R script. Cytometric fingerprinting and evaluation can be accomplished in 1 d, and additional subcommunity composition information can be obtained in a further 6 d.