Abstract
AbstractBackgroundMetabolic models are indispensable in guiding cellular engineering and in advancing our understanding of systems biology. As not all enzymatic activities are fully known and/or annotated, metabolic models remain incomplete, resulting in suboptimal computational analysis and leading to unexpected experimental results. We posit that one major source of unaccounted metabolism is promiscuous enzymatic activity. It is now well-accepted that most, if not all, enzymes are promiscuous – i.e., they transform substrates other than their primary substrate. However, there have been no systematic analyses of genome-scale metabolic models to predict putative reactions and/or metabolites that arise from enzyme promiscuity.ResultsOur workflow utilizes PROXIMAL – a tool that uses reactant-product transformation patterns from the KEGG database – to predict putative structural modifications due to promiscuous enzymes. Using iML1515 as a model system, we first utilized a computational workflow, referred to as Extended Metabolite Model Annotation (EMMA), to predict promiscuous reactions catalyzed, and metabolites produced, by natively encoded enzymes in E. coli. We predict hundreds of new metabolites that can be used to augment iML1515. We then validated our method by comparing predicted metabolites with the Escherichia coli Metabolome Database (ECMDB).ConclusionsWe utilized EMMA to augment the iML1515 metabolic model to more fully reflect cellular metabolic activity. This workflow uses enzyme promiscuity as basis to predict hundreds of reactions and metabolites that may exist in E. coli but have not been documented in iML1515 or other databases. Among these, we found that 17 metabolites have previously been documented in E. coli metabolomics studies. Further, 6 of these metabolites are not documented for any other E. coli metabolic model (e.g. KEGG, EcoCyc). The corresponding reactions should be added to iML1515 to create an Extended Metabolic Model (EMM). Other predicted metabolites and reactions can guide future experimental metabolomics studies. Further, our workflow can easily be applied to other organisms for which comprehensive genome-scale metabolic models are desirable.
Publisher
Cold Spring Harbor Laboratory
Reference57 articles.
1. Metabolic engineering of microorganisms for biofuels production: from bugs to synthetic biology to fuels
2. When plants produce not enough or at all: metabolic engineering of flavonoids in microbial hosts;Frontiers in plant science,2015
3. George KW , Alonso-Gutierrez J , Keasling JD , Lee TS. Isoprenoid drugs, biofuels, and chemicals— artemisinin, farnesene, and beyond. Biotechnology of Isoprenoids: Springer; 2015. p. 355–89.
4. Engineering microbial factories for synthesis of value-added products;Journal of industrial microbiology & biotechnology,2011
5. Furusawa C , Horinouchi T , Hirasawa T , Shimizu H. Systems metabolic engineering: the creation of microbial cell factories by rational metabolic design and evolution. Future Trends in Biotechnology: Springer; 2012. p. 1–23.