title: Computational evaluation of cellular metabolic costs successfully predicts genes whose expression is deleterious.
abstract: Gene suppression and overexpression are both fundamental tools in linking genotype to phenotype in model organisms. Computational methods have proven invaluable in studying and predicting the deleterious effects of gene deletions, and yet parallel computational methods for overexpression are still lacking. Here, we present Expression-Dependent Gene Effects (EDGE), an in silico method that can predict the deleterious effects resulting from overexpression of either native or foreign metabolic genes. We first test and validate EDGE's predictive power in bacteria through a combination of small-scale growth experiments that we performed and analysis of extant large-scale datasets. Second, a broad cross-species analysis, ranging from microorganisms to multiple plant and human tissues, shows that genes that EDGE predicts to be deleterious when overexpressed are indeed typically down-regulated. This reflects a universal selection force keeping the expression of potentially deleterious genes in check. Third, EDGE-based analysis shows that cancer genetic reprogramming specifically suppresses genes whose overexpression impedes proliferation. The magnitude of this suppression is large enough to enable an almost perfect distinction between normal and cancerous tissues based solely on EDGE results. We expect EDGE to advance our understanding of human pathologies associated with up-regulation of particular transcripts and to facilitate the utilization of gene overexpression in metabolic engineering.
authors.affiliation: The Blavatnik School of Computer Science, Sackler School of Medicine, and Department of Molecular Microbiology and Biotechnology, Faculty of Life Sciences, Tel-Aviv University, Tel-Aviv 69978, Israel.
authors.forename: Allon
authors.initials: A
authors.lastname: Wagner
authors.forename: Raphy
authors.initials: R
authors.lastname: Zarecki
authors.forename: Leah
authors.initials: L
authors.lastname: Reshef
authors.forename: Camelia
authors.initials: C
authors.lastname: Gochev
authors.forename: Rotem
authors.initials: R
authors.lastname: Sorek
authors.forename: Uri
authors.initials: U
authors.lastname: Gophna
authors.forename: Eytan
authors.initials: E
authors.lastname: Ruppin
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D015870:Gene Expression / Q000235:genetics*; D020869:Gene Expression Profiling / Q000379:methods; D015972:Gene Expression Regulation, Neoplastic / Q000235:genetics; D006801:Humans; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D008957:Models, Genetic
keywords: constraint-based modeling; flux balance analysis; horizontal gene transfer; metabolic modeling; systems metabolic engineering