Environmental flexibility does not explain metabolic robustness

Abstract

Cells show remarkable resilience against genetic and environmental perturbations. However, its evolutionary origin remains obscure. In order to leverage methods of systems biology for examining cellular robustness, a computationally accessible way of quantification is needed. Here, we present an unbiased metric of structural robustness in genome-scale metabolic models based on concepts prevalent in reliability engineering and fault analysis. The probability of failure (PoF) is defined as the (weighted) portion of all possible combinations of loss-of-function mutations that disable network functionality. It can be exactly determined if all essential reactions, synthetic lethal pairs of reactions, synthetic lethal triplets of reactions etc. are known. In theory, these minimal cut sets (MCSs) can be calculated for any network, but for large models the problem remains computationally intractable. Herein, we demonstrate that even at the genome scale only the lowest-cardinality MCSs are required to efficiently approximate the PoF with reasonable accuracy. Building on an improved theoretical understanding, we analysed the robustness of 489 E. coli, Shigella, Salmonella, and fungal genome-scale metabolic models (GSMMs). In contrast to the popular “congruence theory”, which explains the origin of genetic robustness as a byproduct of selection for environmental flexibility, we found no correlation between network robustness and the diversity of growth-supporting environments. On the contrary, our analysis indicates that amino acid synthesis rather than carbon metabolism dominates metabolic robustness.

SysMod: the ISCB community for data-driven computational modelling and multi-scale analysis of biological systems

“…During the second day, a stochastic spatio-temporal model of DNA replication that incorporates experimental genome structural data and protein mobility dynamics and probabilistic activation firing was presented ( Windhager et al , 2019 ). The final talk gave a metric to exploit concepts of reliability engineering, elementary flux modes, and minimal cut sets to calculate the robustness of E.coli , Shigella , Salmonella and fungal genome-scale metabolic models ( Libiseller-Egger et al , 2020 ). In this context, the amino-acid metabolism was stated to be more fragile than the central carbon metabolism.…”

Synthetic Control of Metabolic States in Pseudomonas putida by Tuning Polyhydroxyalkanoate Cycle

“…In other words, the PHA cycle might be a metabolic capacitor connecting catabolism and anabolism with P. putida ’s central metabolism. Such cycles have been defined as robustness cycles ( 27 – 30 ).…”