Maximizing multi-reaction dependencies provides more accurate and precise predictions of intracellular fluxes than the principle of parsimony

Intracellular fluxes represent a joint outcome of cellular transcription and translation and reflect the availability and usage of nutrients from the environment. While approaches from the constraint-based metabolic framework can accurately predict cellular phenotypes, such as growth and exchange rates with the environment, accurate prediction of intracellular fluxes remains a pressing problem. Parsimonious flux balance analysis (pFBA) has become an approach of choice to predict intracellular fluxes by employing the principle of efficient usage of protein resources. Nevertheless, comparative analyses of intracellular flux predictions from pFBA against fluxes estimated from labeling experiments remain scarce. Here, we posited that steady-state flux distributions derived from the principle of maximizing multi-reaction dependencies are of improved accuracy and precision than those resulting from pFBA. To this end, we designed a constraint-based approach, termed complex-balanced FBA (cbFBA), to predict steady-state flux distributions that support the given specific growth rate and exchange fluxes. We showed that the steady-state flux distributions resulting from cbFBA in comparison to pFBA show better agreement with experimentally measured fluxes from 17 Escherichia coli strains and are more precise, due to the smaller space of alternative solutions. We also showed that the same principle holds in eukaryotes by comparing the predictions of pFBA and cbFBA against experimentally derived steady-state flux distributions from 26 knock-out mutants of Saccharomyces cerevisiae. Furthermore, our results showed that intracellular fluxes predicted by cbFBA provide better support for the principle of minimizing metabolic adjustment between mutants and wild types. Together, our findings point that other principles that consider the dynamics and coordination of steady states may govern the distribution of intracellular fluxes. Data on intracellular fluxes in biological systems provide a snapshot of the rates of underlying reactions and activity of metabolic pathways. However, capturing the activity of reactions and pathways is very resource-intensive, precluding widespread usage of fluxes in understanding of cellular physiology. Therefore, approaches for accurate and precise prediction of intracellular fluxes can propel the usage of intracellular fluxes in diverse biotechnological application that require the identification of reaction targets. Here, we propose a constraint-based approach, termed complex-balanced flux balance analysis, based on the principle of maximizing multi-reaction dependencies. By using data sets of intracellular fluxes in strains of two model organisms, Escherichia coli and Saccharomyces cerevisiae, we show that the predictions from our approach are more accurate and precise in comparison to a widely used approach relying on the principle of parsimonious usage of cellular resources. Therefore, our results suggest that other cellular principles, related to properties of steady state fluxes, such as multi-reaction dependencies, may shape cellular physiology.

Automated summary

Research findings suggest that steady-state flux distributions derived from maximizing multi-reaction dependencies principle are more accurate and precise compared to traditional predictions. This indicates that other cellular principles may influence the distribution of intracellular fluxes. Data on intracellular fluxes provide snapshots of the rates of underlying reactions and metabolic pathway activity, but capturing this data is resource-intensive.