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An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli

Given the vast behavioral repertoire and biological complexity of even the simplest organisms, accurately predicting phenotypes in novel environments and unveiling their biological organization is a challenging endeavor. Here, we present an integrative modeling methodology that unifies under a commo...

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Detalles Bibliográficos
Autores principales: Carrera, Javier, Estrela, Raissa, Luo, Jing, Rai, Navneet, Tsoukalas, Athanasios, Tagkopoulos, Ilias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299492/
https://www.ncbi.nlm.nih.gov/pubmed/24987114
http://dx.doi.org/10.15252/msb.20145108
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author Carrera, Javier
Estrela, Raissa
Luo, Jing
Rai, Navneet
Tsoukalas, Athanasios
Tagkopoulos, Ilias
author_facet Carrera, Javier
Estrela, Raissa
Luo, Jing
Rai, Navneet
Tsoukalas, Athanasios
Tagkopoulos, Ilias
author_sort Carrera, Javier
collection PubMed
description Given the vast behavioral repertoire and biological complexity of even the simplest organisms, accurately predicting phenotypes in novel environments and unveiling their biological organization is a challenging endeavor. Here, we present an integrative modeling methodology that unifies under a common framework the various biological processes and their interactions across multiple layers. We trained this methodology on an extensive normalized compendium for the gram-negative bacterium Escherichia coli, which incorporates gene expression data for genetic and environmental perturbations, transcriptional regulation, signal transduction, and metabolic pathways, as well as growth measurements. Comparison with measured growth and high-throughput data demonstrates the enhanced ability of the integrative model to predict phenotypic outcomes in various environmental and genetic conditions, even in cases where their underlying functions are under-represented in the training set. This work paves the way toward integrative techniques that extract knowledge from a variety of biological data to achieve more than the sum of their parts in the context of prediction, analysis, and redesign of biological systems.
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spelling pubmed-42994922015-01-20 An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli Carrera, Javier Estrela, Raissa Luo, Jing Rai, Navneet Tsoukalas, Athanasios Tagkopoulos, Ilias Mol Syst Biol Articles Given the vast behavioral repertoire and biological complexity of even the simplest organisms, accurately predicting phenotypes in novel environments and unveiling their biological organization is a challenging endeavor. Here, we present an integrative modeling methodology that unifies under a common framework the various biological processes and their interactions across multiple layers. We trained this methodology on an extensive normalized compendium for the gram-negative bacterium Escherichia coli, which incorporates gene expression data for genetic and environmental perturbations, transcriptional regulation, signal transduction, and metabolic pathways, as well as growth measurements. Comparison with measured growth and high-throughput data demonstrates the enhanced ability of the integrative model to predict phenotypic outcomes in various environmental and genetic conditions, even in cases where their underlying functions are under-represented in the training set. This work paves the way toward integrative techniques that extract knowledge from a variety of biological data to achieve more than the sum of their parts in the context of prediction, analysis, and redesign of biological systems. Blackwell Publishing Ltd 2014-07-01 /pmc/articles/PMC4299492/ /pubmed/24987114 http://dx.doi.org/10.15252/msb.20145108 Text en © 2014 The Authors. Published under the terms of the CC BY 4.0 license http://creativecommons.org/licenses/by/4.0/ This is an open access article under the terms of the Creative Commons Attribution 4.0 License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Articles
Carrera, Javier
Estrela, Raissa
Luo, Jing
Rai, Navneet
Tsoukalas, Athanasios
Tagkopoulos, Ilias
An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli
title An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli
title_full An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli
title_fullStr An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli
title_full_unstemmed An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli
title_short An integrative, multi-scale, genome-wide model reveals the phenotypic landscape of Escherichia coli
title_sort integrative, multi-scale, genome-wide model reveals the phenotypic landscape of escherichia coli
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4299492/
https://www.ncbi.nlm.nih.gov/pubmed/24987114
http://dx.doi.org/10.15252/msb.20145108
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