Metabolism is an open thermodynamic system characterized by mass, energy, and information exchanges with the environment. Many environmental and internal signals are initially processed by metabolic reactions before they can influence transcription and translation. Yet, the capacity of metabolic networks to process and transmit information remains largely unexplored. Here, the linear noise approximation (LNA) is applied to a reversible, enzyme-catalyzed reaction to estimate its channel capacity and constraints thereon. It is shown that perturbations to metabolite concentrations cannot be propagated through reactions operating away from equilibrium. As a result, thermodynamically unfavourable reactions - such as those required for anabolism - are structurally constrained to limit information flow in metabolic networks. However, the substrates of such reactions can maximally transfer information via non-reactive binding, as in regulatory interactions. This provides a mechanism by which information transfer can be maintained across metabolic conditions. Bioinformatic evidence supporting the hypothesis that metabolism has evolved to conserve information flow in varied conditions will be presented, and implications of these results for goal-directedness within the metabolism-first hypothesis of the origin of life will be discussed.
Organizers and speakers at this event acknowledge a humanitarian crisis in Palestine. Read the humanitarian statement here.