Enzyme promiscuity shapes adaptation to novel growth substrates. Issue 4 (8th April 2019) - Guzmán, Gabriela I; Sandberg, Troy E; LaCroix, Ryan A; Nyerges, Ákos; Papp, Henrietta; de Raad, Markus; King, Zachary A; Hefner, Ying; Northen, Trent R; Notebaart, Richard A; Pál, Csaba; Palsson, Bernhard O; et al.
Abstract: Evidence suggests that novel enzyme functions evolved from low‐level promiscuous activities in ancestral enzymes. Yet, the evolutionary dynamics and physiological mechanisms of how such side activities contribute to systems‐level adaptations are not well characterized. Furthermore, it remains untested whether knowledge of an organism's promiscuous reaction set, or underground metabolism, can aid in forecasting the genetic basis of metabolic adaptations. Here, we employ a computational model of underground metabolism and laboratory evolution experiments to examine the role of enzyme promiscuity in the acquisition and optimization of growth on predicted non‐native substrates in Escherichia coli K‐12 MG1655. After as few as approximately 20 generations, evolved populations repeatedly acquired the capacity to grow on five predicted non‐native substrates—D‐lyxose, D‐2‐deoxyribose, D‐arabinose, m‐tartrate, and monomethyl succinate. Altered promiscuous activities were shown to be directly involved in establishing high‐efficiency pathways. Structural mutations shifted enzyme substrate turnover rates toward the new substrate while retaining a preference for the primary substrate. Finally, genes underlying the phenotypic innovations were accurately predicted by genome‐scale model simulations of metabolism with enzyme promiscuity. Synopsis: Computational modeling of underground metabolism, laboratory evolution and omics analyses reveal that enzyme promiscuity can play a major role during adaptation to new growth environments and indicate that the genes underlying the phenotypic innovations can be predicted. Enzyme promiscuity can confer a fitness benefit in novel growth environments and open routes for achieving innovative growth states. Mutation events which enable growth on non‐native carbon sources can be structural or regulatory in nature and single mutation events related to a promiscuous activity can be sufficient to support growth while some cases require multiple mutations. Metabolic network analysis and constraint‐based modeling can predict adaptation to non‐native carbon sources through promiscuous enzyme activities. Laboratory evolution can be used to select for enzymes with structural mutations enabling an improved substrate affinity for a non‐native carbon source. Abstract : Computational modeling of underground metabolism, laboratory evolution and omics analyses reveal that enzyme promiscuity can play a major role during adaptation to new growth environments and indicate that the genes underlying the phenotypic innovations can be predicted.