  Eukaryotic cells are mechanically supported by a polymer network called the
cytoskeleton, which consumes chemical energy to dynamically remodel its
structure. Recent experiments in vivo have revealed that this remodeling
occasionally happens through anomalously large displacements, reminiscent of
earthquakes or avalanches. These cytoskeletal avalanches might indicate that
the cytoskeleton's structural response to a changing cellular environment is
highly sensitive, and they are therefore of significant biological interest.
However, the physics underlying "cytoquakes" is poorly understood. Here, we use
agent-based simulations of cytoskeletal self-organization to study fluctuations
in the network's mechanical energy. We robustly observe non-Gaussian statistics
and asymmetrically large rates of energy release compared to accumulation in a
minimal cytoskeletal model. The large events of energy release are found to
correlate with large, collective displacements of the cytoskeletal filaments.
We also find that the changes in the localization of tension and the
projections of the network motion onto the vibrational normal modes are
asymmetrically distributed for energy release and accumulation. These results
imply an avalanche-like process of slow energy storage punctuated by fast,
large events of energy release involving a collective network rearrangement. We
further show that mechanical instability precedes cytoquake occurrence through
a machine learning model that dynamically forecasts cytoquakes using the
vibrational spectrum as input. Our results provide the first connection between
the cytoquake phenomenon and the network's mechanical energy and can help guide
future investigations of the cytoskeleton's structural susceptibility.
