Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift.

ABSTRACT: Inferring genome-scale metabolic networks in emerging model organisms is challenged by incomplete biochemical knowledge and partial conservation of biochemical pathways during evolution. Therefore, specific bioinformatic tools are necessary to infer biochemical reactions and metabolic structures that can be checked experimentally. Using an integrative approach combining genomic and metabolomic data in the red algal model Chondrus crispus, we show that, even metabolic pathways considered as conserved, like sterols or mycosporine-like amino acid synthesis pathways, undergo substantial turnover. This phenomenon, here formally defined as "metabolic pathway drift," is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if th

SUBMITTER: Belcour A 

PROVIDER: S-EPMC6997860 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature