Data-driven modeling reveals cell behaviors controlling self-organization during Myxococcus xanthus development.

Area of Science:

• Microbiology
• Biophysics
• Developmental Biology

Background:

• Collective cell movement is vital for multicellular systems like biofilms and development.
• Understanding the physical and chemical cues guiding coordinated cell behavior remains a challenge.
• Myxococcus xanthus bacteria exhibit social behavior, forming fruiting bodies through coordinated movement.

Purpose of the Study:

• To investigate the emergent behaviors driving collective cell aggregation in Myxococcus xanthus.
• To identify individual cell behaviors that contribute to multicellular aggregation dynamics.
• To develop a method for analyzing collective cell movement without prior knowledge of biological mechanisms.

Main Methods:

• Coupled fluorescent cell tracking with data-driven computational models.
• Quantified individual cell behaviors during aggregation.
• Simulated aggregation dynamics to identify key behavioral drivers.

Main Results:

• Observed significant variations in individual cell behavior during aggregation.
• Identified decreased motility, biased movement towards centroids, and radial alignment as key aggregation-enhancing behaviors.
• Found that aggregation is robust to perturbations, with potential compensatory mechanisms.

Conclusions:

• The developed approach effectively links behavior quantification with data-driven simulations for studying collective cell movement.
• This method can be applied to complex biological systems to uncover emergent behaviors.
• Key behaviors like motility, directional bias, and alignment are critical for Myxococcus xanthus fruiting body formation.