Genome-Scale Metabolic Models

Genome-scale metabolic models of microbial metabolism can be used to predict which strain manipulations can improve the production of bioproducts of interest. Potential strain manipulations include reaction deletion, reaction addition, gene deletion or overexpression, and nutrient supplementation. Growth-coupled strain design algorithms search for a set of manipulations that must produce some amount of bioproduct in order to grow, thus ensuring a strain that is evolutionary stable.

Bayesian Metabolic Control Analysis 

Our Bayesian Metabolic Control Analysis capabilities leverage our expertise to identify which native or non-native enzymes are most likely to improve bioproduct titers, rates and yields. ABF teams have successfully applied the model’s predictive metabolic flux control coefficients to a variety of species.

13C Metabolic Flux Analysis

The gold standard for measuring intracellular metabolic fluxes, 13C Metabolic Flux Analysis provides valuable insights into bottlenecks and side reactions, helping to maximize carbon utilization and titers, rates, and yields. ABF researchers have demonstrated that combining 13C metabolic flux analysis with genome-scale metabolic models provides a rigorous and comprehensive understanding of cell metabolism. 

Pangenomic Analysis

Our pangenomic analysis capabilities allow us to search tens of thousands of complete microbial genomic sequences for metabolic and regulatory mechanisms that can serve as solutions to biodesign problems. 

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Publications

• Advances in genome-scale metabolic models of industrially important fungi
• Bayesian inference of metabolic kinetics from genome-scale multiomics data
• A Method to Constrain Genome-Scale Models with 13C Labeling Data