Reference : Integrated omics for the identification of key functionalities in biological wastewat...
Scientific journals : Article
Life sciences : Biochemistry, biophysics & molecular biology
Life sciences : Biotechnology
Life sciences : Environmental sciences & ecology
Life sciences : Microbiology
http://hdl.handle.net/10993/20067
Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities
English
Narayanasamy, Shaman mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Muller, Emilie mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Sheik, Abdul mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Wilmes, Paul mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
12-Feb-2015
Microbial Biotechnology
Blackwell
Yes (verified by ORBilu)
International
1751-7915
1751-7907
Oxford
United Kingdom
[en] Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single ‘omes’. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure–function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications.
Luxembourg Centre for Systems Biomedicine (LCSB): Eco-Systems Biology (Wilmes Group)
Fonds National de la Recherche - FnR
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/20067
10.1111/1751-7915.12255

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