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SensiPath: computer-aided design of sensing-enabling metabolic pathways

Genetically-encoded biosensors offer a wide range of opportunities to develop advanced synthetic biology applications. Circuits with the ability of detecting and quantifying intracellular amounts of a compound of interest are central to whole-cell biosensors design for medical and environmental appl...

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Autores principales: Delépine, Baudoin, Libis, Vincent, Carbonell, Pablo, Faulon, Jean-Loup
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741204/
https://www.ncbi.nlm.nih.gov/pubmed/27106061
http://dx.doi.org/10.1093/nar/gkw305
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author Delépine, Baudoin
Libis, Vincent
Carbonell, Pablo
Faulon, Jean-Loup
author_facet Delépine, Baudoin
Libis, Vincent
Carbonell, Pablo
Faulon, Jean-Loup
author_sort Delépine, Baudoin
collection PubMed
description Genetically-encoded biosensors offer a wide range of opportunities to develop advanced synthetic biology applications. Circuits with the ability of detecting and quantifying intracellular amounts of a compound of interest are central to whole-cell biosensors design for medical and environmental applications, and they also constitute essential parts for the selection and regulation of high-producer strains in metabolic engineering. However, the number of compounds that can be detected through natural mechanisms, like allosteric transcription factors, is limited; expanding the set of detectable compounds is therefore highly desirable. Here, we present the SensiPath web server, accessible at http://sensipath.micalis.fr. SensiPath implements a strategy to enlarge the set of detectable compounds by screening for multi-step enzymatic transformations converting non-detectable compounds into detectable ones. The SensiPath approach is based on the encoding of reactions through signature descriptors to explore sensing-enabling metabolic pathways, which are putative biochemical transformations of the target compound leading to known effectors of transcription factors. In that way, SensiPath enlarges the design space by broadening the potential use of biosensors in synthetic biology applications.
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spelling pubmed-57412042018-01-05 SensiPath: computer-aided design of sensing-enabling metabolic pathways Delépine, Baudoin Libis, Vincent Carbonell, Pablo Faulon, Jean-Loup Nucleic Acids Res Web Server issue Genetically-encoded biosensors offer a wide range of opportunities to develop advanced synthetic biology applications. Circuits with the ability of detecting and quantifying intracellular amounts of a compound of interest are central to whole-cell biosensors design for medical and environmental applications, and they also constitute essential parts for the selection and regulation of high-producer strains in metabolic engineering. However, the number of compounds that can be detected through natural mechanisms, like allosteric transcription factors, is limited; expanding the set of detectable compounds is therefore highly desirable. Here, we present the SensiPath web server, accessible at http://sensipath.micalis.fr. SensiPath implements a strategy to enlarge the set of detectable compounds by screening for multi-step enzymatic transformations converting non-detectable compounds into detectable ones. The SensiPath approach is based on the encoding of reactions through signature descriptors to explore sensing-enabling metabolic pathways, which are putative biochemical transformations of the target compound leading to known effectors of transcription factors. In that way, SensiPath enlarges the design space by broadening the potential use of biosensors in synthetic biology applications. Oxford University Press 2016-07-08 2016-04-22 /pmc/articles/PMC5741204/ /pubmed/27106061 http://dx.doi.org/10.1093/nar/gkw305 Text en © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Web Server issue
Delépine, Baudoin
Libis, Vincent
Carbonell, Pablo
Faulon, Jean-Loup
SensiPath: computer-aided design of sensing-enabling metabolic pathways
title SensiPath: computer-aided design of sensing-enabling metabolic pathways
title_full SensiPath: computer-aided design of sensing-enabling metabolic pathways
title_fullStr SensiPath: computer-aided design of sensing-enabling metabolic pathways
title_full_unstemmed SensiPath: computer-aided design of sensing-enabling metabolic pathways
title_short SensiPath: computer-aided design of sensing-enabling metabolic pathways
title_sort sensipath: computer-aided design of sensing-enabling metabolic pathways
topic Web Server issue
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5741204/
https://www.ncbi.nlm.nih.gov/pubmed/27106061
http://dx.doi.org/10.1093/nar/gkw305
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