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      Phenotypic heterogeneity in metabolic traits among single cells of a rare bacterial species in its natural environment quantified with a combination of flow cell sorting and NanoSIMS

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          Abstract

          Populations of genetically identical microorganisms residing in the same environment can display marked variability in their phenotypic traits; this phenomenon is termed phenotypic heterogeneity. The relevance of such heterogeneity in natural habitats is unknown, because phenotypic characterization of a sufficient number of single cells of the same species in complex microbial communities is technically difficult. We report a procedure that allows to measure phenotypic heterogeneity in bacterial populations from natural environments, and use it to analyze N 2 and CO 2 fixation of single cells of the green sulfur bacterium Chlorobium phaeobacteroides from the meromictic lake Lago di Cadagno. We incubated lake water with 15N 2 and 13CO 2 under in situ conditions with and without NH 4 +. Subsequently, we used flow cell sorting with auto-fluorescence gating based on a pure culture isolate to concentrate C. phaeobacteroides from its natural abundance of 0.2% to now 26.5% of total bacteria. C. phaeobacteroides cells were identified using catalyzed-reporter deposition fluorescence in situ hybridization (CARD-FISH) targeting the 16S rRNA in the sorted population with a species-specific probe. In a last step, we used nanometer-scale secondary ion mass spectrometry to measure the incorporation 15N and 13C stable isotopes in more than 252 cells. We found that C. phaeobacteroides fixes N 2 in the absence of NH 4 +, but not in the presence of NH 4 + as has previously been suggested. N 2 and CO 2 fixation were heterogeneous among cells and positively correlated indicating that N 2 and CO 2 fixation activity interact and positively facilitate each other in individual cells. However, because CARD-FISH identification cannot detect genetic variability among cells of the same species, we cannot exclude genetic variability as a source for phenotypic heterogeneity in this natural population. Our study demonstrates the technical feasibility of measuring phenotypic heterogeneity in a rare bacterial species in its natural habitat, thus opening the door to study the occurrence and relevance of phenotypic heterogeneity in nature.

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          Most cited references54

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          Bacterial persistence as a phenotypic switch.

          A fraction of a genetically homogeneous microbial population may survive exposure to stress such as antibiotic treatment. Unlike resistant mutants, cells regrown from such persistent bacteria remain sensitive to the antibiotic. We investigated the persistence of single cells of Escherichia coli with the use of microfluidic devices. Persistence was linked to preexisting heterogeneity in bacterial populations because phenotypic switching occurred between normally growing cells and persister cells having reduced growth rates. Quantitative measurements led to a simple mathematical description of the persistence switch. Inherent heterogeneity of bacterial populations may be important in adaptation to fluctuating environments and in the persistence of bacterial infections.
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            Nature, nurture, or chance: stochastic gene expression and its consequences.

            Gene expression is a fundamentally stochastic process, with randomness in transcription and translation leading to cell-to-cell variations in mRNA and protein levels. This variation appears in organisms ranging from microbes to metazoans, and its characteristics depend both on the biophysical parameters governing gene expression and on gene network structure. Stochastic gene expression has important consequences for cellular function, being beneficial in some contexts and harmful in others. These situations include the stress response, metabolism, development, the cell cycle, circadian rhythms, and aging.
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              Phenotypic diversity, population growth, and information in fluctuating environments.

              Organisms in fluctuating environments must constantly adapt their behavior to survive. In clonal populations, this may be achieved through sensing followed by response or through the generation of diversity by stochastic phenotype switching. Here we show that stochastic switching can be favored over sensing when the environment changes infrequently. The optimal switching rates then mimic the statistics of environmental changes. We derive a relation between the long-term growth rate of the organism and the information available about its fluctuating environment.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                16 April 2015
                2015
                : 6
                : 243
                Affiliations
                [1] 1Department of Environmental Systems Sciences, ETH Zurich – Swiss Federal Institute of Technology Zurich, Switzerland
                [2] 2Molecular Microbial Ecology Group, Department of Environmental Microbiology, Eawag – Swiss Federal Institute of Aquatic Science and Technology Zurich, Switzerland
                [3] 3Laboratory for Biological Geochemistry, School of Architecture, Civil and Environmental Engineering, École Polytechnique Fédérale de Lausanne Lausanne, Switzerland
                [4] 4Department of Environmental Microbiology, Helmholtz-Centre for Environmental Research, Leipzig Germany
                [5] 5Department of Surface Waters, Eawag – Swiss Federal Institute of Aquatic Science and Technology, Kastanienbaum Switzerland
                [6] 6Department of Isotope Biogeochemistry, Helmholtz-Centre for Environmental Research, Leipzig Germany
                [7] 7Center for Advanced Surface Analysis, Institute of Earth Sciences, University of Lausanne, Lausanne Switzerland
                Author notes

                Edited by: Manuel Martinez Garcia, University of Alicante, Spain

                Reviewed by: Ivan Berg, Albert-Ludwigs-Universität Freiburg, Germany; Steven Singer, Lawrence Berkeley National Laboratory, USA; Jakob Pernthaler, University of Zurich, Switzerland

                *Correspondence: Frank Schreiber, Molecular Microbial Ecology Group, Department of Environmental Microbiology, Eawag – Swiss Federal Institute of Aquatic Science and Technology, Überlandstrasse 133, P.O. Box 611, 8600 Dübendorf, Zurich, Switzerland frank.schreiber@ 123456eawag.ch

                This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2015.00243
                4399338
                25932020
                0df27ef2-3bdc-459e-b069-9aafcbad3a04
                Copyright © 2015 Zimmermann, Escrig, Hübschmann, Kirf, Brand, Inglis, Musat, Müller, Meibom, Ackermann and Schreiber.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 05 January 2015
                : 12 March 2015
                Page count
                Figures: 3, Tables: 0, Equations: 0, References: 60, Pages: 11, Words: 0
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                facs,dinitrogen fixation,lago di cadagno,green sulfur bacteria,phenotypic noise,phenotypic variability,diversity,single-cell analysis

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