Maximization of non-idle enzymes improves the coverage of the estimated maximal in vivo enzyme catalytic rates in Escherichia coli

Motivation: Constraint-based modeling approaches allow the estimation of maximal in vivo enzyme catalytic rates that can serve as proxies for enzyme turnover numbers. Yet, genome-scale flux profiling remains a challenge in deploying these approaches to catalogue proxies for enzyme catalytic rates across organisms. Results: Here, we formulate a constraint-based approach, termed NIDLE-flux, to estimate fluxes at a genome-scale level by using the principle of efficient usage of expressed enzymes. Using proteomics data from Escherichia coli, we show that the fluxes estimated by NIDLE-flux and the existing approaches are in excellent qualitative agreement (Pearson correlation > 0.9). We also find that the maximal in vivo catalytic rates estimated by NIDLE-flux exhibits a Pearson correlation of 0.74 with in vitro enzyme turnover numbers. However, NIDLE-flux results in a 1.4-fold increase in the size of the estimated maximal in vivo catalytic rates in comparison to the contenders. Integration of the maximum in vivo catalytic rates with publically available proteomics and metabolomics data provide a better match to fluxes estimated by NIDLE-flux. Therefore, NIDLE-flux facilitates more effective usage of proteomics data to estimate proxies for kcatomes. Supplementary information: Supplementary data are available at Bioinformatics online.

Automated summary

The study introduces a constraint-based approach named NIDLE-flux to estimate fluxes at a genome-scale level by efficiently using expressed enzymes. Results show that the fluxes estimated by NIDLE-flux are in excellent qualitative agreement with existing approaches, and the maximal in vivo catalytic rates estimated by NIDLE-flux exhibit a relatively larger size compared to contenders. Integrating the maximum in vivo catalytic rates with publicly available proteomics and metabolomics data provides a better match to fluxes estimated by NIDLE-flux.