Journal
NATURE PROTOCOLS
Volume 15, Issue 9, Pages 2788-2812Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/s41596-020-0362-0
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Funding
- Central Innovation Programme for SMEs (ZIM) of the Federal Ministry of Economic Affairs and Energy Germany (BMWi
- INAR-ABOS) [16KN043222]
- European Regional Development Funds (EFRE-Europe Funds Saxony) [100192205]
- Helmholtz Association within RP Renewable Energies
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Flow cytometry is used to track dynamics in microbial communities and link these changes with ecological parameters. This protocol describes how to prepare a fixed microbial cytometric mock community to standardize results over large-scale studies. Flow cytometry has recently established itself as a tool to track short-term dynamics in microbial community assembly and link those dynamics with ecological parameters. However, instrumental configurations of commercial cytometers and variability introduced through differential handling of the cells and instruments frequently cause data set variability at the single-cell level. This is especially pronounced with microorganisms, which are in the lower range of optical resolution. Although alignment beads are valuable to generally minimize instrumental noise and align overall machine settings, an artificial microbial cytometric mock community (mCMC) is mandatory for validating lab workflows and enabling comparison of data between experiments, thus representing a necessary reference standard for the reproducible cytometric characterization of microbial communities, especially in long-term studies. In this study, the mock community consisted of two Gram-positive and two Gram-negative bacterial strains, which can be assembled with respective subsets of cells, including spores, in any selected ratio or concentration. The preparation of the four strains takes a maximum of 5 d, and the stains are storable with either PFA/ethanol fixation at -20 degrees C or drying at 4 degrees C for at least 6 months. Starting from this stock, an mCMC can be assembled within 1 h. Fluorescence staining methods are presented and representatively applied with two high-resolution cell sorters and three benchtop flow cytometers. Benchmarked data sets allow the use of bioinformatic evaluation procedures to decode community behavior or convey qualified cell sorting decisions for subsequent high-resolution sequencing or proteomic routines.
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