Emergent Homeostasis and Degeneracy From Multi-Dimensional Attractors

Area of Science:

• Systems Biology
• Theoretical Biology
• Biophysics

Background:

• Biological systems exhibit homeostasis, maintaining stability against perturbations and noise.
• Traditional models explain homeostasis via explicit control mechanisms regulating specific variables.
• An alternative perspective is needed to capture emergent properties of complex biological systems.

Purpose of the Study:

• To propose and support the collective dynamics perspective for understanding biological homeostasis.
• To demonstrate how homeostasis can emerge spontaneously from high-dimensional interactions.
• To reframe control theory as a projection of a more comprehensive multi-dimensional system.

Main Methods:

• Developing theoretical models based on collective dynamics.
• Analyzing high-dimensional phase space and attractor manifolds.
• Conducting a meta-analysis of single-cell growth and division datasets across various organisms and conditions.

Main Results:

• Homeostasis emerges from collective interactions, forming limiting manifolds in phase space.
• Multi-dimensional attractor manifolds collectively constrain system components, reducing the need for individual variable control.
• Null directions on manifolds provide degenerate states, enhancing flexibility while preserving functionality.
• Single-cell growth and division data support the collective dynamics model.

Conclusions:

• Homeostasis can be understood as an emergent property of collective dynamics, not solely dependent on explicit control.
• The collective dynamics perspective offers a more complete framework for biological stability.
• Control theory can be viewed as a low-dimensional representation of these complex, multi-dimensional systems.