Theoretical investigation of a genetic switch for metabolic adaptation

Membrane transporters carry key metabolites across the cell membrane and, from a resource standpoint, are hypothesized to be produced when necessary. The expression of membrane transporters in metabolic pathways is often upregulated by the transporter substrate. In E. coli, such systems include for...

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Veröffentlicht in:PloS one 2020-05, Vol.15 (5), p.e0226453-e0226453
Hauptverfasser: Laxhuber, Kathrin S, Morrison, Muir J, Chure, Griffin, Belliveau, Nathan M, Strandkvist, Charlotte, Naughton, Kyle L, Phillips, Rob
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container_title PloS one
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creator Laxhuber, Kathrin S
Morrison, Muir J
Chure, Griffin
Belliveau, Nathan M
Strandkvist, Charlotte
Naughton, Kyle L
Phillips, Rob
description Membrane transporters carry key metabolites across the cell membrane and, from a resource standpoint, are hypothesized to be produced when necessary. The expression of membrane transporters in metabolic pathways is often upregulated by the transporter substrate. In E. coli, such systems include for example the lacY, araFGH, and xylFGH genes, which encode for lactose, arabinose, and xylose transporters, respectively. As a case study of a minimal system, we build a generalizable physical model of the xapABR genetic circuit, which features a regulatory feedback loop via membrane transport (positive feedback) and enzymatic degradation (negative feedback) of an inducer. Dynamical systems analysis and stochastic simulations show that the membrane transport makes the model system bistable in certain parameter regimes. Thus, it serves as a genetic "on-off" switch, enabling the cell to only produce a set of metabolic enzymes when the corresponding metabolite is present in large amounts. We find that the negative feedback from the degradation enzyme does not significantly disturb the positive feedback from the membrane transporter. We investigate hysteresis in the switching and discuss the role of cooperativity and multiple binding sites in the model circuit. Fundamentally, this work explores how a stable genetic switch for a set of enzymes is obtained from transcriptional auto-activation of a membrane transporter through its substrate.
doi_str_mv 10.1371/journal.pone.0226453
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Fundamentally, this work explores how a stable genetic switch for a set of enzymes is obtained from transcriptional auto-activation of a membrane transporter through its substrate.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>32379825</pmid><doi>10.1371/journal.pone.0226453</doi><tpages>e0226453</tpages><orcidid>https://orcid.org/0000-0002-8104-3525</orcidid><orcidid>https://orcid.org/0000-0002-0768-7234</orcidid><oa>free_for_read</oa></addata></record>
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subjects Adaptation
Adaptation, Physiological - genetics
Arabinose
Binding Sites
Bioengineering
Biological Transport - genetics
Biology
Biology and Life Sciences
Cell membranes
Circuits
Computer simulation
Degradation
E coli
Engineering and Technology
Enzymes
Escherichia coli
Escherichia coli - genetics
Escherichia coli - metabolism
Escherichia coli Proteins - genetics
Escherichia coli Proteins - metabolism
Feedback
Feedback loops
Feedback, Physiological
Gene expression
Gene Expression Regulation, Bacterial
Gene Regulatory Networks
Genes
Genes, Switch
Genetic aspects
Genetic regulation
Genetic research
Lactose
Membrane proteins
Membrane Transport Proteins - genetics
Membrane Transport Proteins - metabolism
Membranes
Metabolic pathways
Metabolic regulation
Metabolism
Metabolites
Models, Biological
Monosaccharides
Negative feedback
Pentosyltransferases - genetics
Pentosyltransferases - metabolism
Physics
Physiological aspects
Positive feedback
Promoter Regions, Genetic
Proteins
Ribonucleosides - metabolism
RNA, Messenger - metabolism
Stochastic Processes
Stochasticity
Substrates
Systems analysis
Trans-Activators - genetics
Trans-Activators - metabolism
Transcription (Genetics)
Transcription activation
Transcription factors
Transcription, Genetic
Transport
Transport proteins
Xanthines
title Theoretical investigation of a genetic switch for metabolic adaptation
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