UMICIS

Uncultivated Microbes In Situ - a Computational Biology Approach to Determine Molecular Capabilities and Ecological Roles

 Coordinatore UNIVERSITAET ZUERICH 

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 Nazionalità Coordinatore Switzerland [CH]
 Totale costo 1˙129˙800 €
 EC contributo 1˙129˙800 €
 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-2009-StG
 Funding Scheme ERC-SG
 Anno di inizio 2010
 Periodo (anno-mese-giorno) 2010-02-01   -   2016-01-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    UNIVERSITAET ZUERICH

 Organization address address: Raemistrasse 71
city: ZURICH
postcode: 8006

contact info
Titolo: Prof.
Nome: Christian
Cognome: Von Mering
Email: send email
Telefono: +41 44 634 5350
Fax: +41 44 634 5351

CH (ZURICH) hostInstitution 1˙129˙800.00

Mappa


 Word cloud

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functions    distinct    situ    computational    gene    communities    ecology    cultivation    community    microbial    sequencing    microbes    natural    dna    molecular    techniques    data    expression   

 Obiettivo del progetto (Objective)

'Most of nature s biodiversity, and many potentially useful metabolic capabilities, remain hidden among the vast numbers of uncharacterized environmental microbes. Because cultivation is still not possible for most of these microbes, cultivation-independent molecular techniques such as polymerase chain reaction (PCR), fluorescent in situ hybridization (FISH), or shotgun DNA sequencing have been used in order to study their function and ecology in their natural habitats. However, none of the above techniques have so far been sufficient for any systematic assignment of molecular functions to distinct microbial lineages. Thus, most of the molecular ecology of natural microbes remains elusive. Here, we propose a computational meta-analysis and synthesis of existing and newly generated molecular sequence data sampled directly from the environment combining DNA sequencing data (metagenomics), and proteome expression data (metaproteomics). This analysis will be coupled to computational modelling of genome content evolution at the community level. We will aim to assess how gene repertoires of microbial communities, and their taxonomic compositions, change across distinct environments, in response to changed conditions, and through time. We plan to address fundamental questions in microbial ecology, including the extent of cooperation among members of the communities, stability of community composition at evolutionary timescales, the importance of lateral gene transfers, the extent of functional adaptation/regulation in situ, and whether gene occurrence and expression patterns are diagnostic of community functions and ecological status.'

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