Metabolic Integration as Biological Information Processing: A Unified Framework of Non-Equilibrium Thermodynamics, Causal Fluxomics, and Algorithmic Individuality

This manuscript presents a unified theoretical framework that reconceptualizes metabolism as a non-equilibrium information-processing system. The author argues that four canonical gaps in metabolic science—systemic coordination, individual variation, pathological dysregulation, and methodological limitations—stem from the absence of a unifying physical theory. The proposed framework integrates concepts from stochastic thermodynamics, algorithmic information theory, and causal network science to address this deficiency. At its core, the theory posits that metabolic networks are dissipative structures governed by the principle of minimum entropy production under functional constraints. This means pathways evolve to be maximally efficient while satisfying biological demands like growth and homeostasis. Within this model, inter-organ communication is reframed as "metabolic message passing," where circulating metabolites act as information carriers in a distributed inference system. Individual metabolic identity, or the "metabotype," is defined by its algorithmic complexity, representing the shortest computational program that describes the person’s unique genome-microbiome-environment interactions. Consequently, metabolic disease is understood as "informational decoherence"—a decoupling of energy flow from physiological purpose. For example, the Warburg effect in cancer is interpreted as a shift to "structural dissipation" (biomass) over "functional dissipation" (ATP for work), while neurodegeneration is modeled as a failure of energetic inference in the brain. The paper culminates in a proposed "Metabolic Free Energy Principle," which suggests that organisms minimize a trade-off between thermodynamic cost, prediction error, and complexity. This synthesis provides a rigorous foundation for a new generation of "thermodynamically aware precision medicine," aimed at restoring the causal and informational integrity of the entire metabolic network.