ArticleMicrobial cell factories2019
Towards creating an extended metabolic model (EMM) for E. coli using enzyme promiscuity prediction and metabolomics data.
Article in Microbial cell factories, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed, 25 citations in OpenAlex.
- Enzyme promiscuity in the field of synthetic biology applied to white biotechnology: Opportunities and weaknesses.Biodesign research · 2025Review
- Extending PROXIMAL to predict degradation pathways of phenolic compounds in the human gut microbiota.NPJ systems biology and applications · 2024Article
- Vibrio natriegens genome-scale modeling reveals insights into halophilic adaptations and resource allocation.Molecular systems biology · 2023Article
- Using graph neural networks for site-of-metabolism prediction and its applications to ranking promiscuous enzymatic products.Bioinformatics (Oxford, England) · 2023Article
- MINE 2.0: enhanced biochemical coverage for peak identification in untargeted metabolomics.Bioinformatics (Oxford, England) · 2022Article
- Carbon-negative production of acetone and isopropanol by gas fermentation at industrial pilot scale.Nature biotechnology · 2022Article
- Approaches for completing metabolic networks through metabolite damage and repair discovery.Current opinion in systems biology · 2021Review
- Enzyme Promiscuity Prediction Using Hierarchy-Informed Multi-Label Classification.Bioinformatics (Oxford, England) · 2021Article
- Analysis of metabolic network disruption in engineered microbial hosts due to enzyme promiscuity.Metabolic engineering communications · 2021Article
- Pathway-Activity Likelihood Analysis and Metabolite Annotation for Untargeted Metabolomics Using Probabilistic Modeling.Metabolites · 2020Article
- Biological Filtering and Substrate Promiscuity Prediction for Annotating Untargeted Metabolomics.Metabolites · 2020Article
- The era of big data: Genome-scale modelling meets machine learning.Computational and structural biotechnology journal · 2020Review
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundMetabolic 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 Escherichia 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 may have not been documented in iML1515 or other databases. We provide detailed analysis of 23 predicted reactions and 16 associated metabolites. Interestingly, nine of these metabolites, which are in ECMDB, have not previously been documented in any other E. coli databases. Four of the predicted reactions provide putative transformations parallel to those already in iML1515. We suggest adding predicted metabolites and reactions to iML1515 to create an extended metabolic model (EMM) for E. coli.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.