The impact of horizontal gene transfer in shaping operons and protein interaction networks – direct evidence of preferential attachment
1 Banting & Best Department of Medical Research (BBDMR), Donnelly Centre for Cellular & Biomolecular Research (CCBR), University of Toronto, 160 College Street, Toronto, ON M5S 3E1, Canada
2 Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 3E1, Canada
BMC Evolutionary Biology 2008, 8:23 doi:10.1186/1471-2148-8-23Published: 24 January 2008
Despite the prevalence of horizontal gene transfer (HGT) in bacteria, to this date there were few studies on HGT in the context of gene expression, operons and protein-protein interactions. Using the recently available data set on the E. coli protein-protein interaction network, we sought to explore the impact of HGT on genome structure and protein networks.
We classified the E. coli genes into three categories based on their evolutionary conservation: a set of 2158 Core genes that are shared by all E. coli strains, a set of 1044 Non-core genes that are strain-specific, and a set of 1053 genes that were putatively acquired by horizontal transfer. We observed a clear correlation between gene expressivity (measured by Codon Adaptation Index), evolutionary rates, and node connectivity between these categories of genes. Specifically, we found the Core genes are the most highly expressed and the most slowly evolving, while the HGT genes are expressed at the lowest level and evolve at the highest rate. Core genes are the most likely and HGT genes are the least likely to be member of the operons. In addition, we found the Core genes on average are more highly connected than Non-core and HGT genes in the protein interaction network, however the HGT genes displayed a significantly higher mean node degree than the Core and Non-core genes in the defence COG functional category. Interestingly, HGT genes are more likely to be connected to Core genes than expected by chance, which suggest a model of differential attachment in the expansion of cellular networks.
Results from our analysis shed light on the mode and mechanism of the integration of horizontally transferred genes into operons and protein interaction networks.