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Big data in biology

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26
Apr
Dv, 26/04/2013 - 13:54

Big data in biology

PRESS RELEASE
 
BIG DATA IN BIOLOGY

Centre for Genomic Regulation (CRG) researchers show how clever interpretation of large data sets lead to knowledge gain in biomedical research.
 
New approaches are necessary to make sense of the increasing amount of available diverse and large-scale biological data sets. In a series of three publications, CRG reseachers explore novel ways how data on gene expression, protein abundance and metabolites from a single model organism can be integrated and analysed. They use hypothesis-driven approaches and mathematical modelling to reveal a fine grained, dynamic picture of the inner workings of the pathogenic bacterium Mycoplasma pneumoniae

Comparing a detailed mathematical model of the entire cellular metabolism with experimental data led to the unexpected finding that M. pneumoniae only uses a small fraction of available energy for growth. Most of it is spent on so-called maintenance tasks, allowing the bacterium to survive in adverse growth environments. The authors saved time and resources by using their model to identify essential genes and to show how the Mycoplama pneumoniae metabolism lost redundant pathways during evolution.

They also measured supply and demand of central cellular building blocks by quantifying free nucleobases and amino acids in the growth medium and inside Mycoplasma pneumoniae cells and integrating their results with the cellular DNA, RNA and protein content. Measuring the speed of glycolysis, the abundance of glycolysis intermediates and relating those to the respective abundances of enzymes involved in this central metabolic pathway allowed the authors to determine their activity in vivo.

Mycoplasma pneumoniae is a simple, genome reduced bacterium, ideally suited for large-scale, organism wide studies. The now published results demonstrate the power of integrating large, quantitative biological data sets to gain additional understanding of important cellular processes and functions. The work exemplifies the use of Big Data in biomedical research and contributes to the Big Data Week, a global festival of data with Barcelona being one of the central hubs.

Most of the now published work was led by Tobias Maier and carried out in the laboratory of Luis Serrano from the Centre for Genomic Regulation (CRG) in Barcelona in collaboration with Ricardo Gutierrez from the UPF and IMIM as well as with Eduard Sabido of the CRG proteomics unit. Co-authors are further affiliated with the Humboldt University in Berlin and the Helmholtz Centre in Braunschweig, Germany.

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For further information, please contact: Laia Cendrós, Press officer, Centre for Genomic Regulation (CRG). Tel. +34 93 316 02 37.