Reference : Integrated omics for the identification of key functionalities in biological wastewat...

	Document type :	Scientific journals : Article
	Discipline(s) :	Life sciences : Biochemistry, biophysics & molecular biology Life sciences : Biotechnology Life sciences : Environmental sciences & ecology Life sciences : Microbiology
	To cite this reference:	http://hdl.handle.net/10993/20067

Title :	Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities
Language :	English
Author, co-author :	Narayanasamy, Shaman [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Muller, Emilie [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Sheik, Abdul [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
	Wilmes, Paul [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Publication date :	12-Feb-2015
Journal title :	Microbial Biotechnology
Publisher :	Blackwell
Peer reviewed :	Yes (verified by ORBilu)
Audience :	International
ISSN :	1751-7915
e-ISSN :	1751-7907
City :	Oxford
Country :	United Kingdom
Abstract :	[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.
Research centres :	Luxembourg Centre for Systems Biomedicine (LCSB): Eco-Systems Biology (Wilmes Group)
Funders :	Fonds National de la Recherche - FnR
Name of the research project :	R-AGR-0369-1 > ATTRACT FNR/A09/03 Sysbionama > 01/02/2010 - 31/01/2015 > WILMES Paul
Target :	Researchers ; Professionals ; Students
Permalink :	http://hdl.handle.net/10993/20067
DOI :	10.1111/1751-7915.12255

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