Biophysics & Soft Matter Physics

Biological Physics of Cells

Current projects include:

  • The connection between compression waves in lipid membranes and action potentials: Experimental observations in lipid monolayers have demonstrated that compression waves travelling close to the lipid melting transition display unusual nonlinear properties, which offer a potential means of communication and computation. In particular, these nonlinear waves are strikingly similar to action potentials observed in excitable cells, an observation that points at possible novel aspects of action potentials. We use analytical and numerical tools to investigate these nonlinear compression waves, focusing on the interconnections between the mechanical, electrical, thermodynamic, and chemical aspects of the lipid membrane, embedded proteins, ions, and solvent[1-3].

  • Ion-induced volume transition in polyelectrolyte gels and its role in biology: Polyelectrolyte hydrogels are soft complex systems made of charged crosslinked macromolecules, solvent, and ions. Many types of polyelectrolyte hydrogels demonstrate an abrupt volume transition in response to minute changes of environmental stimuli, such as temperature, ionic composition, solvent quality, pH, and electric field. Similar phenomena are found abundantly in living systems, and are also widely used in various man-made applications. In this project we attempt to shed light on several distinct biological processes such as: compaction of DNA molecules, release of secretory products, and changes in the hydraulic flow in the xylem of vascular plants, by developing a dynamic physicochemical framework that accounts for the interaction of charged polymers, solvent, and ions[4].

  • Surface deformation during cellular excitability: The excitation of many cells and tissues is associated with observable mechanical changes. In neurons, deformation of the cell surface is usually revealed as a swelling followed by a contraction, with amplitudes of ∼1–10 nm. We previously demonstrated that in large excitable plant cells the rigid external layer (cell wall) hinders the underlying deformation, and observed significant cellular deformation that co-propagates with the electrical signal with amplitudes of ∼1—100 m. These transient cellular deformations are captured by an elastic model of the cell surface, suggesting that the elastic properties of the surface are crucial for the explication of the phenomenon[5,6]. Starting from very simple mechanical models, we introduce empirically motivated terms to better understand the mechanoelectrical coupling, its effect on intracellular components, and the nonelectrical information propagating to neighboring cells. The resulting models are of relevance for the description of several biological processes in their native state, as well as for the understanding of certain clinically significant pathologies (primarily neurological ones). 

  • Active transport induces drag of intracellular fluid: Active transport within the cell cytoplasm includes steady trafficking of different organelles and vesicles actively transported by motor proteins using chemical energy. We previously showed that indirect hydrodynamic interaction (flow-induced drag) that exists between actively transported cargoes and soluble particles is sufficient to account for the most relevant experimental observations pertaining to the slow-component transport in axons, which plays an important role in cell development and maintenance[7]. Further work in this area will aim to connect fundamental hydrodynamic principles with emerging properties of cell development. For instance, the rate of axonal growth might be shown to depend on delicate features of the microtubules facilitating the transport and the organelle transport rate.

Soft Matter oriented projects

  • Rare events and large deviations

Heat waves, earthquakes and floods are all rare events but nevertheless hold significance in our daily lives. Exponentially rare events are studied within large deviation theory, where the probability to observe an atypical observable x after time t is ~ exp[ -t G(x)] where G(x) is the large deviation function. The study of rare events is self evidently important on its own right, but has long been recognized as a potential framework for nonequilibrium theories.

A particularly interesting aspect of large deviation functions are dynamical phase transitions, where the large deviation function becomes singular at a critical value. This singularity is akin to a thermodynamic phase transition as it leads to a dramatic change of behaviour in the system. It is interesting to identify and characterize such dynamical phase transitions in a multitude of systems. Moreover, a fundamental question is whether dynamical phase transitions can be described solely via the Hohenberg-Halperin theory of dynamic critical phenomena [8-10].

  • Many body approach to Thermodynamic uncertainty relations and other inequalities

Inequalities play a significant role in physics from the Carnot efficiency bound to the Heisenberg inequality in quantum mechanics. In 2015, a new and exciting bound has been suggested — the thermodynamic uncertainty relation. In useful machines, a current is delivered (of particles, energy etc). Typically, we aim to minimize the fluctuations on the current. The precision of the system can be defined as the mean current squared, over the current variance. It turns out that in a large class of memoryless systems, to achieve larger precision one needs to increase the entropy production in the system. This is independent of specific design of our machine and is thus considered a fantastic tool to evaluate the feasibility of engines and their energetic cost, especially in the realm of molecular engines.

The thermodynamic uncertainty relations have been successful in describing single molecule physics, it remains a challenge to apply the results in the regime of interacting many-body systems. In the following years, the focus is shifting towards applying the uncertainty relations in many body physics, both in thermal and athermal setups[11-13].


[1] Mussel and Schneider (2021), Progress in Biophysics and Molecular Biology, 162, 101-110

[2] Mussel and Schneider (2019), Journal of the Royal Society Interface, 16: 20180743.

[3] Mussel, and Schneider (2019), Scientific Reports, 9: 2467.

[4] Mussel, Basser, and Horkay (2021), Gels, 7:20.

[5] Mussel, Fillafer, Ben-Porath, and Schneider (2017), Physical Review E 96.5: 052406.

[6] Fillafer, Mussel, Muchowski, and Schneider (2018),  Biophysical Journal 114.2: 410-418.

[7] Mussel, Zeevy, Diamant, and Nevo (2014), Biophysical Journal 106.12: 2710-2719.

[8] E. Akkermans, T. Bodineau, B. Derrida and O. Shpielberg, EPL, 103(2), 20001 (2013).

[9] O. Shpielberg and E. Akkermans, Phys. Rev. Lett. 116, 240603 (2016).

[10] O. Shpielberg, T. Nemoto, and J. Caetano, Phys. Rev. E 98, 052116 (2018)

[11] O. Shpielberg and T. Nemoto, Phys. Rev. E 100, 032104 (2019)

[12] A. Soret, O. Shpielberg and E. Akkermans, arXiv:2011.07246.

[13] O. Shpielberg and A. Pal, arXiv:2108.09979.