%0 Journal Article %A Sélem-Mojica, Nelly %A Aguilar, César %A Gutiérrez-García, Karina %A Martínez-Guerrero, Christian E. %A Barona-Gómez, Fancisco %T EvoMining reveals the origin and fate of natural product biosynthetic enzymes %D 2019 %J Microbial Genomics, %V 5 %N 12 %@ 2057-5858 %C e000260 %R https://doi.org/10.1099/mgen.0.000260 %K scytonemin biosynthesis %K evolutionary genomics %K genome mining of natural products %K specialized metabolism %K EvoMining %I Microbiology Society, %X Natural products (NPs), or specialized metabolites, are important for medicine and agriculture alike, and for the fitness of the organisms that produce them. NP genome-mining aims at extracting biosynthetic information from the genomes of microbes presumed to produce these compounds. Typically, canonical enzyme sequences from known biosynthetic systems are identified after sequence similarity searches. Despite this being an efficient process, the likelihood of identifying truly novel systems by this approach is low. To overcome this limitation, we previously introduced EvoMining, a genome-mining approach that incorporates evolutionary principles. Here, we release and use our latest EvoMining version, which includes novel visualization features and customizable databases, to analyse 42 central metabolic enzyme families (EFs) conserved throughout Actinobacteria , Cyanobacteria , Pseudomonas and Archaea. We found that expansion-and-recruitment profiles of these 42 families are lineage specific, opening the metabolic space related to ‘shell’ enzymes. These enzymes, which have been overlooked, are EFs with orthologues present in most of the genomes of a taxonomic group, but not in all. As a case study of canonical shell enzymes, we characterized the expansion and recruitment of glutamate dehydrogenase and acetolactate synthase into scytonemin biosynthesis, and into other central metabolic pathways driving Archaea and Bacteria adaptive evolution. By defining the origin and fate of enzymes, EvoMining complements traditional genome-mining approaches as an unbiased strategy and opens the door to gaining insights into the evolution of NP biosynthesis. We anticipate that EvoMining will be broadly used for evolutionary studies, and for generating predictions of unprecedented chemical scaffolds and new antibiotics. This article contains data hosted by Microreact. %U https://www.microbiologyresearch.org/content/journal/mgen/10.1099/mgen.0.000260