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bioRxiv · 10.1101/2024.03.05.583461

Understanding flux switching in metabolic networks through an analysis of synthetic lethals

Abstract

Biological systems are extremely robust and exhibit high levels of redundancy for multiple cellular functions. Some of this redundancy manifests as alternative pathways in metabolism. Synthetic double lethals in metabolic networks comprise pairs of reactions, which, when deleted simultaneously, abrogate cell growth. However, when one reaction from such pairs is removed, the cell reroutes its metabolites through alternative pathways. Very little is known about the set of reactions through which fluxes are rerouted. Analysing this redistribution would help us to uncover the linkage between the reactions in a synthetic double lethal and also understand the complexity underlying the reroutings. Studying synthetic lethality in the context of pathogenic bacteria can offer valuable insights into therapeutic interventions. In this work, we propose a constraint-based approach to unravel these alternate pathways and complex interdependencies within and across metabolic modules. The approach involves a generic optimisation that minimises the extent of rerouting between two reaction deletions, corresponding to synthetic lethal pairs. We also include a systematic analysis of synthetic lethals by identifying the reaction classes that make up these synthetic lethals. We applied our computational workflow to several existing high-quality genome-scale models to show that these rerouted reactions span across metabolic modules, thereby illustrating the complexity and uniqueness of metabolism. Our results provide interesting insights into the organisation of metabolic networks and their redundancy. The algorithm is available at https://github.com/RamanLab/minRerouting. Contact: kraman@iitm.ac.in

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BibTeXRIS

Manojna, S., Malpani, T., Mohite, O. S., Nath, S., Raman, K.. 2024-03-09. Understanding flux switching in metabolic networks through an analysis of synthetic lethals. https://doi.org/10.1101/2024.03.05.583461

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