Biophysical Society Thematic Meeting | Riga 2026

Active and Responsive Soft Matter: From Biological to Engineered Systems

Friday Speaker Abstracts

ACCESSING ACTIVE MECHANICS IN LIVING SYSTEMS FROM PASSIVE PARTICLE TRAJECTORIES Timo Betz 1 ; 1 University of Göttingen, 3rd Institute of Physics, Göttingen, Germany Many living systems operate far from equilibrium, where active processes continuously drive mechanical fluctuations. However, extracting these non-equilibrium contributions from passive particle trajectories remains a major challenge, as standard observables such as the mean squared displacement often fail to distinguish thermal from active motion. Here, we present a framework to access active mechanics in living systems directly from passive particle tracking data. We first discuss the challenges of quantifying mechanical properties at the micro- and nanoscale in complex biological environments, and illustrate how passive trajectories can report on intracellular transport, cytosolic fluidization during cell division, and mechanical phenotyping across cell types. Building on this, we introduce a novel observable, the mean-back relaxation (MBR), which captures time-asymmetric features of particle motion and provides direct access to non-equilibrium dynamics. Unlike conventional trajectory-based measures, MBR enables the detection of broken detailed balance even in regimes where standard analyses remain insensitive. We demonstrate that this approach yields a robust and quantitative measure of activity in both controlled experimental systems and living cells, thereby providing a unified route to infer active viscoelastic mechanics from passive observations.

ENVIRONMENT-DRIVEN ACTIVE MATTER Daniel A Fletcher 1 ; 1 UC Berkeley, Berkeley, CA, USA

Conventional active matter, such as migrating cells and developing tissues, relies on internal energy consumption to generate forces and navigate complex landscapes. In contrast, environment-driven active matter utilizes a fundamentally distinct paradigm. Lacking internal metabolic machinery or complex intracellular signaling networks, these particles achieve directed transport by chemically and physically modifying their surroundings. Taking Influenza A virus as inspiration, we explore how surface-bound proteins extract free energy directly from the local environment to drive persistent motion and autonomous gradient sensing. Collectively, populations of these particles exhibit emergent behaviors mediated by a shared environmental memory left behind in the modified landscape. This work highlights how localized, environment dependent interactions can drive transport, expanding our understanding of viral motion and guiding the design of autonomous synthetic particles capable of navigating complex biological environments.

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