GENPHENBACT

Genetic and Phenotypic Modelling of Bacterial Evolution

 Coordinatore INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE (INSERM) 

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 Nazionalità Coordinatore France [FR]
 Totale costo 1˙485˙600 €
 EC contributo 1˙485˙600 €
 Programma FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Code Call ERC-2012-StG_20111109
 Funding Scheme ERC-SG
 Anno di inizio 2013
 Periodo (anno-mese-giorno) 2013-05-01   -   2018-04-30

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE (INSERM)

 Organization address address: 101 Rue de Tolbiac
city: PARIS
postcode: 75654

contact info
Titolo: Dr.
Nome: Olivier Antoine
Cognome: Tenaillon
Email: send email
Telefono: 33-1-5727-7504

FR (PARIS) hostInstitution 1˙485˙600.00
2    INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE (INSERM)

 Organization address address: 101 Rue de Tolbiac
city: PARIS
postcode: 75654

contact info
Titolo: Ms.
Nome: Laurence
Cognome: Lomme
Email: send email
Telefono: +33 1 43 62 27 00
Fax: +33 1 43 62 27 01

FR (PARIS) hostInstitution 1˙485˙600.00

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

maps    experimental    organism    phenotype    organismal    evolution    complexity    network    metabolic    connect    phenotypic    biology    bacterial    gene    fgma    genetic    models    human    genotype    model    uncover    species   

 Obiettivo del progetto (Objective)

'The dramatic success of infectious agents comes from their ability to adapt to both immune and pharmaceutical selective pressures. To uncover the dynamics of bacterial adaptation, experimental evolution has been widely used, focusing mostly on organismal fitness. Many of the observation derived from these experiments have been captured by Fisher's Geometric model of Adaptation (FGMA). Despite its success, this top-down phenotypic model is relatively abstract. In fact, its most important parameter, the number of independent phenotypes an organism expose to the action of natural selection, or phenotypic complexity, remains completely disconnected from a genetic perspective. More recently, bottom-up genotype to phenotype maps from system biology have provided an alternative to unravel the constraints regulating bacterial evolution. In the present project, I want to connect these different approaches. The interpretation of system biology models in terms of FGMA will (i) uncover the genetic determinants of phenotypic complexity, giving more genetic context to FGMA, and, (ii) transpose our understanding of evolution through FGMA to complex genotype to phenotype maps. Four different levels of integration will be used: the gene, the metabolic network, the organism and the species. I will use -antibiotic resistance gene, TEM1, to connect thermodynamic models of protein evolution to FGMA, and characterize the phenotypic complexity of a single gene, -computational models of metabolic network and experimental modification of a biochemical pathway regulation to assess the meaning of phenotypic complexity in networks, -in vitro and in vivo experimental evolution coupled with genome sequencing and mutant reconstruction to assess the molecular bases of changes in beneficial mutation rates during organismal adaptation, - faeces of well characterised human twins to assess the factors of the human gut's environment that shape the genetic diversity of the Escherichia coli species.'

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