Exploring Non-Equilibrium Biological Functions: Capsular Self-Oscillating Gels as a Model for Cell-Membrane Fluctuations

In the ever-evolving field of materials science, researchers continually seek to develop innovative and novel materials and systems that can mimic and shed light on complex biological phenomena. The study of cell-membrane fluctuations, or CMFs, represents one such fascinating area of investigation. CMFs are dynamic, non-equilibrium processes that occur in biological cells, involving the deformations and oscillations of cell membranes in response to various stimuli. Understanding and replicating CMFs have far-reaching implications, from advancing our knowledge of fundamental biological processes to designing new biomimetic materials and devices. In a new study published in the peer-reviewed Journal Materials Horizons led by Won Seok Lee, Takafumi Enomoto, Aya Mizutani Akimoto and Professor Ryo Yoshida from the Department of Materials Engineering, School of Engineering at The University of Tokyo presented a novel experimental model for CMFs, using Capsular Self-Oscillating Gels (C-SOGs) as a platform. This study opens up exciting possibilities for exploring non-equilibrium biological functions and could pave the way for innovative applications in engineering and biology.

To appreciate the significance of the C-SOG model, it is essential to grasp the concept of non-equilibrium biological functions. Many biological processes occur under conditions far from equilibrium, where systems actively exchange energy, matter, or information with their surroundings. A prime example of non-equilibrium biological functions is CMFs. Cells are not passive entities but rather dynamic systems that can adapt to external stimuli and exhibit fluctuating behaviors. CMFs are driven by the exchange of energy or nutrients from the cell’s surroundings, leading to deformations in the cell membrane. These fluctuations are essential for various cellular processes, and understanding them is crucial for unraveling the mysteries of biology.

The authors introduced an exciting model system for CMFs using C-SOGs. These gels are composed of poly(NIPAAm-co-NAPMAm) layers synthesized on millimeter-sized spherical Alg/Ca core beads, which are subsequently dissolved to create hollow capsules. The uniqueness of this model lies in its ability to replicate CMF-like fluctuations solely through the Belousov-Zhabotinsky (BZ) chemical reaction. By conjugating Ru(bpy)3–NHS to the gel layers, the researchers were able to induce layer fluctuation behaviors resembling CMFs.

One of the important features of the new model is the division between thermal and nonthermal effects on gel fluctuations. Due to the enlarged millimeter-scale and increased amplitude compared to CMFs, thermal fluctuations become negligible. This separation provides researchers with a clear distinction and allows them to focus solely on the nonthermal active factors driving the fluctuations. This is a critical advantage of the C-SOG model, as it simplifies the study of CMFs by isolating the relevant parameters.

Another key advantage of the C-SOG model is the ability to manipulate parameters such as BZ substrate concentration, temperature, and light intensity to modulate the amplitude and period of gel fluctuations. This manipulation provides invaluable insights into how these factors influence CMFs. For example, the study revealed that reduced BZ substrate concentration led to slower BZ chemical reactions, ultimately resulting in suppressed gel fluctuation amplitudes. This finding underscores the importance of understanding how external factors can affect the dynamics of CMFs in biological cells.

In addition to parameter manipulation, the authors discussed the analysis of fluctuation noise in the C-SOG system. Fluctuation noise can arise from various sources, including non-homogeneities in the gel microstructure and the structural properties of the capsules themselves. This noise analysis is crucial for understanding how noise impacts CMFs and offers insights into controlling it for practical applications. By addressing fluctuation noise, researchers can work towards creating a more accurate model of CMFs. The C-SOG model effectively separates thermal and nonthermal contributions to CMFs. This separation is vital because the strength and effect of thermal and active energies can be similar on small nanometer or micrometer scales, making it challenging to build active parameter-driven models. By operating at a larger millimeter-scale, the C-SOG model provides a clearer understanding of the nonthermal active contributions to CMFs. This distinction simplifies the study of CMFs and allows researchers to focus on the factors that matter most.

The research team also explored the dependence of fluctuations on chemical substrates involved in the BZ reaction. This is reminiscent of how ATP (adenosine triphosphate) affects CMFs in biological cells. The concentration of chemical substrates, including oxidants and reductants, was found to influence the gel shape fluctuations in the C-SOGs. This observation suggests that the C-SOG model could provide insights into the influence of nonthermal active contributions on membrane fluctuations in biological cells.

The C-SOG model for CMFs developed by Professor Ryo Yoshida  and colleagues opens up exciting possibilities for future research and applications. Several avenues of exploration emerge from this study, for example: researchers could investigate how the elasticity of gel layers affects fluctuations, both experimentally and theoretically. Understanding the role of layer elasticity could provide valuable insights into CMFs and help design biomimetic materials with tailored properties. It would be also possible to achieve volumetric oscillation without the external addition of acid which could be a significant advancement. This effort aligns with a biomimetic approach, striving to mimic biological processes more faithfully. Moreover, introducing a Ru(bpy)3 concentration gradient to the C-SOGs could enable the controlled propagation of the BZ chemical wave. This controlled propagation could offer a more convenient platform for studying the cause-and-effect relationship of active contributions to membrane fluctuations. In conclusion, the C-SOG model represents an important step forward in our quest to understand and replicate non-equilibrium biological functions such as CMFs.