Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations
Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations
While we have good understanding of bacterial metabolism at the population level, we know little about the metabolic behavior of individual cells: do single cells in clonal populations sometimes specialize on different metabolic pathways? Such metabolic specialization could be driven by stochastic gene expression and could provide individual cells with growth benefits of specialization. We measured the degree of phenotypic specialization in two parallel metabolic pathways, the assimilation of glucose and arabinose. We grew Escherichia coli in chemostats, and used isotope-labeled sugars in combination with nanometer-scale secondary ion mass spectrometry and mathematical modeling to quantify sugar assimilation at the single-cell level. We found large variation in metabolic activities between single cells, both in absolute assimilation and in the degree to which individual cells specialize in the assimilation of different sugars. Analysis of transcriptional reporters indicated that this variation was at least partially based on cell-to-cell variation in gene expression. Metabolic differences between cells in clonal populations could potentially reduce metabolic incompatibilities between different pathways, and increase the rate at which parallel reactions can be performed.
Adaptation, Physiological, Arabinose/metabolism, Carbohydrate Metabolism, Escherichia coli/growth & development, Gene Expression, Genes, Bacterial, Glucose/metabolism, Metabolic Networks and Pathways, Phenotype, Single-Cell Analysis
e1007122
Nikolic, Nela
88a8f576-d9e2-4eb6-9219-39b7065963d3
Schreiber, Frank
996cc9b1-c439-4fae-8a46-43b94608d034
Dal Co, Alma
aa4e559a-182f-4b42-8dea-7a288fd4ecaf
Kiviet, Daniel J
29786ecf-f541-4229-beb0-f6a5f3ce561b
Bergmiller, Tobias
8516eb85-1635-4163-a39b-1794de87502b
Littmann, Sten
5430fff4-6d58-4fa2-9af4-3f48cce399c0
Kuypers, Marcel M M
0034c6b4-471c-4b8b-845a-7fac94bff243
Ackermann, Martin
de1a844c-aba8-4d8b-aad4-7b61bc597c16
December 2017
Nikolic, Nela
88a8f576-d9e2-4eb6-9219-39b7065963d3
Schreiber, Frank
996cc9b1-c439-4fae-8a46-43b94608d034
Dal Co, Alma
aa4e559a-182f-4b42-8dea-7a288fd4ecaf
Kiviet, Daniel J
29786ecf-f541-4229-beb0-f6a5f3ce561b
Bergmiller, Tobias
8516eb85-1635-4163-a39b-1794de87502b
Littmann, Sten
5430fff4-6d58-4fa2-9af4-3f48cce399c0
Kuypers, Marcel M M
0034c6b4-471c-4b8b-845a-7fac94bff243
Ackermann, Martin
de1a844c-aba8-4d8b-aad4-7b61bc597c16
Nikolic, Nela, Schreiber, Frank, Dal Co, Alma, Kiviet, Daniel J, Bergmiller, Tobias, Littmann, Sten, Kuypers, Marcel M M and Ackermann, Martin
(2017)
Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations.
PLoS Genetics, 13 (12), .
(doi:10.1371/journal.pgen.1007122).
Abstract
While we have good understanding of bacterial metabolism at the population level, we know little about the metabolic behavior of individual cells: do single cells in clonal populations sometimes specialize on different metabolic pathways? Such metabolic specialization could be driven by stochastic gene expression and could provide individual cells with growth benefits of specialization. We measured the degree of phenotypic specialization in two parallel metabolic pathways, the assimilation of glucose and arabinose. We grew Escherichia coli in chemostats, and used isotope-labeled sugars in combination with nanometer-scale secondary ion mass spectrometry and mathematical modeling to quantify sugar assimilation at the single-cell level. We found large variation in metabolic activities between single cells, both in absolute assimilation and in the degree to which individual cells specialize in the assimilation of different sugars. Analysis of transcriptional reporters indicated that this variation was at least partially based on cell-to-cell variation in gene expression. Metabolic differences between cells in clonal populations could potentially reduce metabolic incompatibilities between different pathways, and increase the rate at which parallel reactions can be performed.
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Published date: December 2017
Keywords:
Adaptation, Physiological, Arabinose/metabolism, Carbohydrate Metabolism, Escherichia coli/growth & development, Gene Expression, Genes, Bacterial, Glucose/metabolism, Metabolic Networks and Pathways, Phenotype, Single-Cell Analysis
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Local EPrints ID: 488032
URI: http://eprints.soton.ac.uk/id/eprint/488032
ISSN: 1553-7390
PURE UUID: f368af34-3df2-47ba-8962-c2eae05bfd29
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Date deposited: 12 Mar 2024 18:21
Last modified: 18 Mar 2024 04:18
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Author:
Nela Nikolic
Author:
Frank Schreiber
Author:
Alma Dal Co
Author:
Daniel J Kiviet
Author:
Tobias Bergmiller
Author:
Sten Littmann
Author:
Marcel M M Kuypers
Author:
Martin Ackermann
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