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Bhanjan Debnath

Publications and source records attributed to Bhanjan Debnath.

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From Maxwell Fluid to Kelvin Voigt Solid: A Transient Network Model of Condensate Aging and Morphology Transition in Phase Separation

Biomolecular condensates can undergo striking changes, such as transitioning from a liquid-like to a gel- or a solid-like aggregate due to changes in molecular interactions in response to changes in the biochemical environment. The question of how modified molecular interactions lead to such a transition in the material properties and spatial organization of condensates has not yet been elucidated. To address this question, we represent the biochemical environment as a triphasic mixture comprising a liquid-like protein-rich phase, a network-like protein-rich phase, and solvent. Owing to a change in the biochemical environment, protein molecules can reversibly switch between two conformational states. In a switched conformational state, the cross-linking domains of molecules are exposed which promote transient network formation in phase separated states. We develop a transient-network model and a continuum framework that couples phase separation, molecular switching, and dynamic cross-linking to predict condensate morphology and mechanics. The transient-network model predicts that a non-aging network behaves like a Maxwell fluid. When a network slowly ages via stabilization of cross-links, it shows Maxwell-like behavior and waiting time-dependent relaxation. However, a strongly aged network shows elastic recoil like characteristic of a Kelvin-Voigt solid. Our coupled continuum model demonstrates that the interplay of molecular switching and dynamic cross-linking in network formation shapes the spatial organization of condensate phases. In summary, this work demonstrates a mechanistic route explaining how conformational switching and molecular cross-linking regulate material properties and morphology of condensates.

physics.bio-ph

Reverse segregation in dense granular flow through narrow vertical channel

Controlling flow-induced segregation in a granular mixture is highly relevant to many industrial settings. To enhance mixing or promote segregation, the continuous gravity flow of a bidisperse granular mixture through a series of narrow vertical channels with exit slots is investigated. The bidisperse mixture is composed of two different sizes of particles, but of the same density. In dense flow, segregation occurs, leading to formation of bands. The bands of large particles appear at a distance away from the walls. This finding is in contrast to that in shear-driven segregation in a dense flow where large particles segregate towards the walls. Using a phenomenological model, it has been shown that rolling and bouncing induced segregation is the dominant mechanism. When cylindrical inserts are placed to modify flow patterns, that significantly influences segregation patterns. The symmetrical placement of a cylindrical insert close to the exit slot vanishes the bands and enhances mixing. However, with two inserts placed symmetrically and close to the exit slot, the degree of segregation in the reverse direction is greatly enhanced compared to that without insert. In the former, small particles accumulate in thin regions adjacent to the walls, and large particles comprise the bulk of the domain and the flowing stream. The heap formation above the insert in a narrow channel, when the insert is close to the exit, enhances mixing in one configuration, whereas it amplifies reverse segregation in the other.

cond-mat.soft

Sequential binding-unbinding based specific interactions influence exchange dynamics and size distribution of protein condensates

The interaction lifetimes between condensate-forming biomolecules can dictate both the specificity of the condensate-forming species as well as the fluidity and exchange dynamics of these condensates. Using a heuristic modeling approach, we show that single-step vs. sequential, multistep binding-unbinding interactions between proteins can lead to similar average interaction lifetimes, but with either exponential or truncated power-law-like lifetime distributions, respectively. Combining this model with Brownian dynamics simulations, we find that the differences in these lifetime distributions influence the features of condensates, such as their fluidic nature, aging, and size distribution.

cond-mat.soft