Fundamental Design Principles for Transcription-Factor-Based Metabolite Biosensors
Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape t...
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Published in | ACS synthetic biology Vol. 6; no. 10; pp. 1851 - 1859 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Chemical Society
20.10.2017
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Subjects | |
Online Access | Get full text |
ISSN | 2161-5063 2161-5063 |
DOI | 10.1021/acssynbio.7b00172 |
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Abstract | Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose–response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism. |
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AbstractList | Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose-response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism. Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose-response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism.Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose-response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism. |
Author | Liu, Di Zhang, Fuzhong Oyarzún, Diego A Mannan, Ahmad A |
AuthorAffiliation | Imperial College London Department of Mathematics Washington University in St. Louis Department of Energy, Environmental & Chemical Engineering |
AuthorAffiliation_xml | – name: Washington University in St. Louis – name: Department of Mathematics – name: Imperial College London – name: Department of Energy, Environmental & Chemical Engineering |
Author_xml | – sequence: 1 givenname: Ahmad A surname: Mannan fullname: Mannan, Ahmad A organization: Imperial College London – sequence: 2 givenname: Di surname: Liu fullname: Liu, Di organization: Washington University in St. Louis – sequence: 3 givenname: Fuzhong orcidid: 0000-0001-6979-7909 surname: Zhang fullname: Zhang, Fuzhong email: fzhang@seas.wustl.edu organization: Washington University in St. Louis – sequence: 4 givenname: Diego A orcidid: 0000-0002-0381-5278 surname: Oyarzún fullname: Oyarzún, Diego A email: d.oyarzun@imperial.ac.uk organization: Imperial College London |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/28763198$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Biosensing Techniques - methods Metabolic Engineering - methods Promoter Regions, Genetic - genetics Synthetic Biology - methods Transcription Factors - genetics Transcription Factors - metabolism |
Title | Fundamental Design Principles for Transcription-Factor-Based Metabolite Biosensors |
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