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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.20037 |
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| _version_ | 1866911173478187008 |
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| author | Batista-Tomás, A. R. Díaz-Faloh, C. Mulet, R. |
| author_facet | Batista-Tomás, A. R. Díaz-Faloh, C. Mulet, R. |
| contents | Cell cultures exhibit rich and complex behaviors driven by dynamic metabolic interactions among cells. In this work, we present a model that captures these interactions through a framework inspired by statistical mechanics. Using Monte Carlo simulations, we explore the equilibrium and dynamical properties of a population of cells arranged in a two-dimensional lattice, where each cell is characterized by fluxes of three reactions: glucose consumption ($g$), respiration ($r$), and waste production/absorption ($w$). The system minimizes an energy function influenced by competitive ($J_g > 0$) and cooperative ($J_w < 0$) couplings between cells. Our results reveal three distinct phases: a competitive phase dominated by glucose competition, a cooperative phase marked by ordered waste exchange, and a disordered phase with local-scale cooperation. By incorporating evolutionary dynamics, we demonstrate how initially non-interacting cells can develop effective metabolic interactions, leading to heterogeneous cultures sustained by cross-feeding. These findings are further supported by analytical solutions derived using mean-field approximations. The model provides insights into how environmental constraints and stochastic fluctuations shape community structures, offering a versatile approach to study several emergent phenomena in biological systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_20037 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Evolutionary emergent metabolic interactions in cell cultures: A Statistical Mechanics point of view Batista-Tomás, A. R. Díaz-Faloh, C. Mulet, R. Biological Physics 82C05, 92D25, 92C42 Cell cultures exhibit rich and complex behaviors driven by dynamic metabolic interactions among cells. In this work, we present a model that captures these interactions through a framework inspired by statistical mechanics. Using Monte Carlo simulations, we explore the equilibrium and dynamical properties of a population of cells arranged in a two-dimensional lattice, where each cell is characterized by fluxes of three reactions: glucose consumption ($g$), respiration ($r$), and waste production/absorption ($w$). The system minimizes an energy function influenced by competitive ($J_g > 0$) and cooperative ($J_w < 0$) couplings between cells. Our results reveal three distinct phases: a competitive phase dominated by glucose competition, a cooperative phase marked by ordered waste exchange, and a disordered phase with local-scale cooperation. By incorporating evolutionary dynamics, we demonstrate how initially non-interacting cells can develop effective metabolic interactions, leading to heterogeneous cultures sustained by cross-feeding. These findings are further supported by analytical solutions derived using mean-field approximations. The model provides insights into how environmental constraints and stochastic fluctuations shape community structures, offering a versatile approach to study several emergent phenomena in biological systems. |
| title | Evolutionary emergent metabolic interactions in cell cultures: A Statistical Mechanics point of view |
| topic | Biological Physics 82C05, 92D25, 92C42 |
| url | https://arxiv.org/abs/2509.20037 |