Non-equilibrium scaling behavior in active biological networks

Recent experiments indicate non-equilibrium activity in a host of biological systems, including chromosomes, cell membranes, and the cytoplasm. Measuring and quantifying non-equilibrium dynamics in such systems is a major challenge in biophysics, due to their many-body nature and the limited number of variables accessible in an experiment. We investigate what information concerning the system’s non-equilibrium state can be extracted by non-invasively tracking a subset of degrees of freedom. To this end, we develop a general, yet simple stochastic model of soft elastic networks with a heterogeneous distribution of activities, representing internal enzymatic force generation. With this model, we determine the scaling behavior of non-equilibrium dynamics from the phase space currents of tracer particles with varying spatial separations in the system. Our results provide insight into how internal driving by enzymatic activity generates non-equilibrium dynamics on different length scales in a variety of biological systems, including polymers, membranes and networks.