What biophysics studies are life phenomena, and therefore in most cases they are nonequilibrium. The central topic of statistical physics is also shifting towards nonequilibrium phenomena. However, the connections between biophysics and nonequilibrium statistical physics are still limited. One reason for this is that both fields have increasingly specialized in different directions: In biophysics, experimental techniques allow us to measure increasing amounts of data, so we are able to study more and more complex phenomena, while in nonequilibrium statistical physics, recent developments in mathematical techniques have led to increasingly rigorous mathematical approaches. Thus, few attempts have been made to find “right size” phenomena that can serve as an interface between the two fields. If a theory at the interface is found, the exchange between the two fields will progress and physics may be able to enter a new phase.
In this seminar, I would like to introduce two examples of our attempts to explore the interface between biophysics and nonequilibrium statistical physics. One is the mitochondrial alignment. Mitochondria are critical organelles in eukaryotes that produce the energy currency ATP. In nerve axons, mitochondria are known to align at almost regular intervals to maintain a constant ATP concentration, but little is known about the mechanism. We show that ATP production and ATP-dependent nondirectional movement of mitochondria are sufficient for alignment, even without an explicit repulsive force between them. This is similar to thermodynamic forces driven by thermal fluctuations, even generated by nonequilibrium processes.
Also, I introduce the new theoretical concept, the Enzymatic Mpemba effect. Increasing the enzyme concentration generally speeds up enzymatic reactions. However, I show that increasing the enzyme concentration can also slow down the relaxation to the equilibrium state, and mechanism for this slowing is similar the Mpemba effect.
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