arXiv subjects

Eugenio Simao

Publications and source records attributed to Eugenio Simao.

4 recordsLinked to original sources

arXiv2026

Thermodynamic Constraints Drive Hierarchical Preemption in Cellular Decision-Making: A Hybrid Petri Net Framework with Application to Bacillus subtilis Sporulation

Cellular decision-making under stress involves rapid pathway selection despite energy scarcity. Here we demonstrate that thermodynamic constraints actively drive energy-efficient sporulation, where continuous metabolic sources enable system robustness through dynamic energy management. Using hybrid Petri nets (stochastic transitions with continuous sources) to model Bacillus subtilis sporulation, we show that stress conditions (ATP = 300 mM, 94% depletion) enable sporulation completion with extreme energy efficiency: 0.73 mM ATP per mature spore versus 11.6 mM ATP under normal conditions--a 16-fold efficiency gain. Despite ATP dropping to 1 mM (99.7% depletion) during the crisis, continuous ATP regeneration rescues the system, producing 67 mM mature spores (89% of normal yield) with only 49 mM total ATP consumption. This efficiency emerges from the interplay between stochastic regulatory transitions and continuous metabolic sources, where GTP accumulation (+4974 mM, 166% increase) provides an energy buffer while ATP regeneration (+240 mM) prevents complete depletion. The hybrid Petri net formalism--combining stochastic transitions for regulatory events with continuous sources for metabolic flux--extended with thermodynamic constraints through inhibitor arcs and energy-coupled rate functions, provides the mathematical foundation enabling this discovery by integrating discrete regulatory logic with continuous energy dynamics in a resource-aware concurrency model.

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arXiv2025

Unifying Weak Independence and Signal Hierarchy Theory: Extended Biological Petri Net Formalism with Application to Vibrio fischeri Quorum Sensing

Biological Petri Nets (Bio-PNs) require extensions beyond classical formalism to capture biochemical reality: multiple reactions simultaneously affect shared metabolites through convergent production or regulatory coupling, while signal places carry hierarchical control information distinct from material flow. We present a unified 13-tuple Extended Bio-PN formalism integrating two complementary theories: Weak Independence Theory (enabling coupled parallelism despite place-sharing) and Signal Hierarchy Theory (separating information flow from mass transfer). The extended definition adds signal partition (Psi subset P), arc type classification (A), regulatory structure (Sigma), environmental exchange (Theta), dependency taxonomy (Delta), heterogeneous transition types (tau), and biochemical formula tracking (rho). We formalize signal token consumption semantics through two-phase execution (enabling vs. consumption) and prove weak independence correctness for continuous dynamics. Application to Vibrio fischeri quorum sensing demonstrates how energy metabolism (ENERGY signals) orchestrates binary ON/OFF decisions through hierarchical constraint propagation to regulatory signals (LuxR-AHL complex), with 133-fold difference separating states. Analysis reveals signal saturation timing as the orchestrator forcing threshold-crossing, analogous to bacteriophage lambda lysogeny-lysis decisions. This work establishes formal foundations for modeling biological information flow in Petri nets, with implications for systems biology, synthetic circuit design, and parallel biochemical simulation.

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arXiv2025

Hierarchical Preemption: A Novel Information-Theoretic Control Mechanism in Lambda Phage Decision-Making

Biological systems organize into hierarchies to manage complexity, yet the mechanisms governing hierarchical control remain incompletely understood. Using information theory and the Lambda phage lysis-lysogeny decision as a model system, we discover that hierarchical control operates through hierarchical preemption - higher layers collapse decision space rather than blocking lower-layer signals. Through mutual information (MI) analysis of 200 stochastic simulations, we demonstrate that the UV damage sensor (RecA) achieves 2.01x information advantage over environmental signals by preempting bistable outcomes into monostable attractors (98% lysogenic or 85% lytic). Conditional MI analysis reveals that the integrator signal (CII) carries lower information when RecA is absent (saturated, 0.06 bits) than when RecA is active (subsaturated, 0.38 bits). This saturation effect demonstrates that signals orchestrate compartment behaviors by removing decision space - achieving 85-98% outcome certainty while preserving 2-15% escape routes. These findings establish a quantitative framework for hierarchical information processing in cellular decision-making.

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arXiv2025

Weak Independence and Coupled Parallelism in Biological Petri Nets

Motivation: Biological Petri Nets (Bio-PNs) model biochemical pathways where multiple reactions simultaneously affect shared metabolites through convergent production or regulatory coupling. However, classical Petri net independence theory requires transitions to share no places -- a constraint that fails to capture biological reality. This mismatch prevents parallel simulation and incorrectly flags biologically valid models as structurally problematic. Results: To resolve this fundamental limitation, we introduce weak independence -- a novel formalization distinguishing resource conflicts from biological coupling. Building on this theory, we extend the Bio-PN definition from a classical 5-tuple to a 12-tuple by adding regulatory structure, environmental exchange classification, dependency taxonomy, heterogeneous transition types, and biochemical formula tracking. This extended formalism enables systematic classification of three place-sharing modes: competitive (conflict), convergent (superposition), and regulatory (read-only). Validating our approach on 100 diverse BioModels (1,775 species, 2,234 reactions across metabolism, signaling, and gene regulation), we find that 96.93% of transition pairs exhibit weak independence -- confirming that biological networks inherently favor cooperation over competition. Our SHYpn implementation demonstrates the practical impact, achieving up to 2.6x speedup on 30% of evaluated models. Availability and Implementation: Open-source at https://github.com/simao-eugenio/shypn (MIT License).

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