A unicellular walker controlled by a microtubule-based finite-state machine

Area of Science:

• Cellular Biology
• Biophysics
• Theoretical Biology

Background:

• Cells are complex systems where behavior emerges from molecular interactions.
• Computation offers a framework for understanding cellular complexity, but its embodiment in cells is not well understood.
• Finite-state machine models are a key computational theory.

Purpose of the Study:

• To investigate if cellular locomotion can be modeled as a finite-state machine.
• To explore the computational principles underlying cell movement.
• To identify the physical mechanisms governing cellular gait.

Main Methods:

• Observed and analyzed the walking behavior of the ciliate Euplotes eurystomus.
• Identified discrete gait states and transitions.
• Conducted simulations and perturbative experiments on microtubule fiber systems.

Main Results:

• Cellular walking involves regulated transitions between discrete gait states.
• Transitions exhibit a pattern of high-probability, irreversible steps and low-probability, symmetric steps.
• Microtubule fiber structure and dynamics are linked to gait transitions and coordination.
• Perturbations demonstrated the role of fibers in mechanical gait control.

Conclusions:

• The walking behavior of Euplotes eurystomus demonstrates finite-state-machine-like processing.
• Cellular gait control has a mechanical basis mediated by microtubule fibers.
• This work provides a framework for applying computational theories to cellular behaviors.