title: Lateral acquisition of genes is affected by the friendliness of their products.
abstract: A major factor in the evolution of microbial genomes is the lateral acquisition of genes that evolved under the functional constraints of other species. Integration of foreign genes into a genome that has different components and circuits poses an evolutionary challenge. Moreover, genes belonging to complex modules in the pretransfer species are unlikely to maintain their functionality when transferred alone to new species. Thus, it is widely accepted that lateral gene transfer favors proteins with only a few protein-protein interactions. The propensity of proteins to participate in protein-protein interactions can be assessed using computational methods that identify putative interaction sites on the protein. Here we report that laterally acquired proteins contain significantly more putative interaction sites than native proteins. Thus, genes encoding proteins with multiple protein-protein interactions may in fact be more prone to transfer than genes with fewer interactions. We suggest that these proteins have a greater chance of forming new interactions in new species, thus integrating into existing modules. These results reveal basic principles for the incorporation of novel genes into existing systems.
authors.affiliation: Department of Molecular Microbiology and Biotechnology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Tel Aviv 69978, Israel. urigo@tauex.tau.ac.il
authors.forename: Uri
authors.initials: U
authors.lastname: Gophna
authors.forename: Yanay
authors.initials: Y
authors.lastname: Ofran
mesh_terms: D000220:Adaptation, Biological / Q000235:genetics*; D000595:Amino Acid Sequence; D019295:Computational Biology; D030562:Databases, Protein; D048168:Escherichia coli K12; D019143:Evolution, Molecular; D022761:Gene Transfer, Horizontal / Q000235:genetics*; D023281:Genomics / Q000379:methods; D054730:Protein Interaction Domains and Motifs / Q000235:genetics*; D016415:Sequence Alignment; D018709:Statistics, Nonparametric; D049490:Systems Biology / Q000379:methods