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Mol Microbiol. 2017 Mar;103(5):818-828. doi: 10.1111/mmi.13591. Epub 2017 Jan 10.

Probing bacterial cell biology using image cytometry.

Author information

1
Department of Physics, University of Washington, Seattle, WA, 98195, USA.
2
Department of Physics, Central Washington University, Ellensburg, WA, 98926, USA.
3
Department of Microbiology, University of Washington, Seattle, WA, 98195, USA.
4
Department of Bioengineering, University of Washington, Seattle, WA, 98195, USA.

Abstract

Advances in automated fluorescence microscopy have made snapshot and time-lapse imaging of bacterial cells commonplace, yet fundamental challenges remain in analysis. The vast quantity of data collected in high-throughput experiments requires a fast and reliable automated method to analyze fluorescence intensity and localization, cell morphology and proliferation as well as other descriptors. Inspired by effective yet tractable methods of population-level analysis using flow cytometry, we have developed a framework and tools for facilitating analogous analyses in image cytometry. These tools can both visualize and gate (generate subpopulations) more than 70 cell descriptors, including cell size, age and fluorescence. The method is well suited to multi-well imaging, analysis of bacterial cultures with high cell density (thousands of cells per frame) and complete cell cycle imaging. We give a brief description of the analysis of four distinct applications to emphasize the broad applicability of the tool.

PMID:
27935200
PMCID:
PMC5663501
DOI:
10.1111/mmi.13591
[Indexed for MEDLINE]
Free PMC Article

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