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Accurate prediction of gene feedback circuit behavior from component properties

A basic assumption underlying synthetic biology is that analysis of genetic circuit elements, such as regulatory proteins and promoters, can be used to understand and predict the behavior of circuits containing those elements. To test this assumption, we used time-lapse fluorescence microscopy to qu...

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Detalles Bibliográficos
Autores principales: Rosenfeld, Nitzan, Young, Jonathan W, Alon, Uri, Swain, Peter S, Elowitz, Michael B
Formato: Texto
Lenguaje:English
Publicado: Nature Publishing Group 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2132446/
https://www.ncbi.nlm.nih.gov/pubmed/18004276
http://dx.doi.org/10.1038/msb4100185
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author Rosenfeld, Nitzan
Young, Jonathan W
Alon, Uri
Swain, Peter S
Elowitz, Michael B
author_facet Rosenfeld, Nitzan
Young, Jonathan W
Alon, Uri
Swain, Peter S
Elowitz, Michael B
author_sort Rosenfeld, Nitzan
collection PubMed
description A basic assumption underlying synthetic biology is that analysis of genetic circuit elements, such as regulatory proteins and promoters, can be used to understand and predict the behavior of circuits containing those elements. To test this assumption, we used time-lapse fluorescence microscopy to quantitatively analyze two autoregulatory negative feedback circuits. By measuring the gene regulation functions of the corresponding repressor–promoter interactions, we accurately predicted the expression level of the autoregulatory feedback loops, in molecular units. This demonstration that quantitative characterization of regulatory elements can predict the behavior of genetic circuits supports a fundamental requirement of synthetic biology.
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spelling pubmed-21324462007-12-12 Accurate prediction of gene feedback circuit behavior from component properties Rosenfeld, Nitzan Young, Jonathan W Alon, Uri Swain, Peter S Elowitz, Michael B Mol Syst Biol Report A basic assumption underlying synthetic biology is that analysis of genetic circuit elements, such as regulatory proteins and promoters, can be used to understand and predict the behavior of circuits containing those elements. To test this assumption, we used time-lapse fluorescence microscopy to quantitatively analyze two autoregulatory negative feedback circuits. By measuring the gene regulation functions of the corresponding repressor–promoter interactions, we accurately predicted the expression level of the autoregulatory feedback loops, in molecular units. This demonstration that quantitative characterization of regulatory elements can predict the behavior of genetic circuits supports a fundamental requirement of synthetic biology. Nature Publishing Group 2007-11-13 /pmc/articles/PMC2132446/ /pubmed/18004276 http://dx.doi.org/10.1038/msb4100185 Text en Copyright © 2007, EMBO and Nature Publishing Group http://creativecommons.org/licenses/by-nc-nd/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits distribution, and reproduction in any medium, provided the original author and source are credited. This license does not permit commercial exploitation or the creation of derivative works without specific permission.
spellingShingle Report
Rosenfeld, Nitzan
Young, Jonathan W
Alon, Uri
Swain, Peter S
Elowitz, Michael B
Accurate prediction of gene feedback circuit behavior from component properties
title Accurate prediction of gene feedback circuit behavior from component properties
title_full Accurate prediction of gene feedback circuit behavior from component properties
title_fullStr Accurate prediction of gene feedback circuit behavior from component properties
title_full_unstemmed Accurate prediction of gene feedback circuit behavior from component properties
title_short Accurate prediction of gene feedback circuit behavior from component properties
title_sort accurate prediction of gene feedback circuit behavior from component properties
topic Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2132446/
https://www.ncbi.nlm.nih.gov/pubmed/18004276
http://dx.doi.org/10.1038/msb4100185
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