Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1128/mSphere.00564-17
Licence creative commons licence
Title (Primary) Ecological stability properties of microbial communities assessed by flow cytometry
Author Liu, Z.; Cichocki, N.; Bonk, F.; Günther, S.; Schattenberg, F.; Harms, H.; Centler, F.; Müller, S.
Source Titel mSphere
Year 2018
Department UMB
Volume 3
Issue 1
Page From e00564-17
Language englisch
Supplements https://msphere.asm.org/content/msph/3/1/e00564-17/DC1/embed/inline-supplementary-material-1.pdf?download=true
https://msphere.asm.org/content/msph/3/1/e00564-17/DC2/embed/inline-supplementary-material-2.pdf?download=true
https://msphere.asm.org/content/msph/3/1/e00564-17/DC3/embed/inline-supplementary-material-3.mov?download=true
https://msphere.asm.org/content/msph/3/1/e00564-17/DC4/embed/inline-supplementary-material-4.pdf?download=true
https://msphere.asm.org/content/msph/3/1/e00564-17/DC5/embed/inline-supplementary-material-5.pdf?download=true
https://msphere.asm.org/content/msph/3/1/e00564-17/DC6/embed/inline-supplementary-material-6.pdf?download=true
https://msphere.asm.org/content/msph/3/1/e00564-17/DC7/embed/inline-supplementary-material-7.pdf?download=true
UFZ wide themes RU3;
Abstract Natural microbial communities affect human life in countless ways, ranging from global biogeochemical cycles to the treatment of wastewater and health via the human microbiome. In order to probe, monitor, and eventually control these communities, fast detection and evaluation methods are required. In order to facilitate rapid community analysis and monitor a community’s dynamic behavior with high resolution, we here apply community flow cytometry, which provides single-cell-based high-dimensional data characterizing communities with high acuity over time. To interpret time series data, we draw inspiration from macroecology, in which a rich set of concepts has been developed for describing population dynamics. We focus on the stability paradigm as a promising candidate to interpret such data in an intuitive and actionable way and present a rapid workflow to monitor stability properties of complex microbial ecosystems. Based on single-cell data, we compute the stability properties resistance, resilience, displacement speed, and elasticity. For resilience, we also introduce a method which can be implemented for continuous online community monitoring. The proposed workflow was tested in a long-term continuous reactor experiment employing both an artificial and a complex microbial community, which were exposed to identical short-term disturbances. The computed stability properties uncovered the superior stability of the complex community and demonstrated the global applicability of the protocol to any microbiome. The workflow is able to support high temporal sample densities below bacterial generation times. This may provide new opportunities to unravel unknown ecological paradigms of natural microbial communities, with applications to environmental, biotechnological, and health-related microbiomes.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=20078
Liu, Z., Cichocki, N., Bonk, F., Günther, S., Schattenberg, F., Harms, H., Centler, F., Müller, S. (2018):
Ecological stability properties of microbial communities assessed by flow cytometry
mSphere 3 (1), e00564-17 10.1128/mSphere.00564-17