Statistical inference of scale dependent biological activity using carbon nanotubes

Systems built from energy consuming components often exhibit an intimate relationship between structure and function. In biological systems, irreversible, yet stochastic, molecular interactions form dissipative structures, such as cytoskeletal networks, which mediate scale-dependent processes. However, due to a lack of methods able to quantify time reversal asymmetry, their dynamics remain poorly characterized. By measuring time reversal asymmetry encoded in the conformational dynamics of filamentous single walled carbon nanotubes (SWNTs) embedded in the actomyosin network of Xenopus egg extract, we characterize the scale dependence of mechanical activity. Our method is sensitive to distinct perturbations at the molecular level and can thus probe the interplay between microscopic structure and emergence of larger scale nonequilibrium activity. We characterize the dynamics of a semiflexible polymer embedded in a viscoelastic medium to contextualize our results in terms of key physical parameters. Our analysis provides a general tool to characterize steady state nonequilibrium activity in high dimensional spaces.