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Genome Biol. 2008 Apr 10;9(4):R72. doi: 10.1186/gb-2008-9-4-r72.

Perceiving molecular evolution processes in Escherichia coli by comprehensive metabolite and gene expression profiling.

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  • 1International NRW Graduate School in Bioinformatics and Genome Research, Bielefeld University, D-33594 Bielefeld, Germany. cvijayen@cebitec.uni-bielefeld.de



Evolutionary changes that are due to different environmental conditions can be examined based on the various molecular aspects that constitute a cell, namely transcript, protein, or metabolite abundance. We analyzed changes in transcript and metabolite abundance in evolved and ancestor strains in three different evolutionary conditions - excess nutrient adaptation, prolonged stationary phase adaptation, and adaptation because of environmental shift - in two different strains of bacterium Escherichia coli K-12 (MG1655 and DH10B).


Metabolite profiling of 84 identified metabolites revealed that most of the metabolites involved in the tricarboxylic acid cycle and nucleotide metabolism were altered in both of the excess nutrient evolved lines. Gene expression profiling using whole genome microarray with 4,288 open reading frames revealed over-representation of the transport functional category in all evolved lines. Excess nutrient adapted lines were found to exhibit greater degrees of positive correlation, indicating parallelism between ancestor and evolved lines, when compared with prolonged stationary phase adapted lines. Gene-metabolite correlation network analysis revealed over-representation of membrane-associated functional categories. Proteome analysis revealed the major role played by outer membrane proteins in adaptive evolution. GltB, LamB and YaeT proteins in excess nutrient lines, and FepA, CirA, OmpC and OmpA in prolonged stationary phase lines were found to be differentially over-expressed.


In summary, we report the vital involvement of energy metabolism and membrane-associated functional categories in all of the evolutionary conditions examined in this study within the context of transcript, outer membrane protein, and metabolite levels. These initial data obtained may help to enhance our understanding of the evolutionary process from a systems biology perspective.

[PubMed - indexed for MEDLINE]
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