title: Evolutionary Conservation of Bacterial Essential Metabolic Genes across All Bacterial Culture Media.
abstract: One of the basic postulates of molecular evolution is that functionally important genes should evolve slower than genes of lesser significance. Essential genes, whose knockout leads to a lethal phenotype are considered of high functional importance, yet whether they are truly more conserved than nonessential genes has been the topic of much debate, fuelled by a host of contradictory findings. Here we conduct the first large-scale study utilizing genome-scale metabolic modeling and spanning many bacterial species, which aims to answer this question. Using the novel Media Variation Analysis, we examine the range of conservation of essential vs. nonessential metabolic genes in a given species across all possible media. We are thus able to obtain for the first time, exact upper and lower bounds on the levels of differential conservation of essential genes for each of the species studied. The results show that bacteria do exhibit an overall tendency for differential conservation of their essential genes vs. their non-essential ones, yet this tendency is highly variable across species. We show that the model bacterium E. coli K12 may or may not exhibit differential conservation of essential genes depending on its growth medium, shedding light on previous experimental studies showing opposite trends.
authors.affiliation: The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
authors.forename: Oren
authors.initials: O
authors.lastname: Ish-Am
authors.affiliation: National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, United States of America.
authors.forename: David M
authors.initials: DM
authors.lastname: Kristensen
authors.affiliation: The Blavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel; The Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel; Dept. of Computer Science and the Center for Bioinformatics & Computational Biology, the University of Maryland, Maryland, United States of America.
authors.forename: Eytan
authors.initials: E
authors.lastname: Ruppin
mesh_terms: D000465:Algorithms; D017124:Conserved Sequence; D003470:Culture Media / Q000378:metabolism*; D004926:Escherichia coli / Q000235:genetics* / Q000378:metabolism*; D019143:Evolution, Molecular; D005798:Genes, Bacterial; D020043:Genes, Essential; D008660:Metabolism / Q000235:genetics; D008954:Models, Biological; D015203:Reproducibility of Results
chemical_list: D003470:Culture Media