Long-Range Interactions Between Neighboring Nanoparticles Tuned by Confining Membranes

Abstract

Membrane tubes, a class of soft biological confinement for ubiquitous transport intermediates, are essential for cell trafficking and intercellular communication. However, the confinement interaction and directional migration of diffusive nanoparticles (NPs) are widely dismissed as improbable due to the surrounding environment compressive force. Here, combined with the mechanics analysis of nanoparticles (such as extracellular vesicles, EVs) to study their interaction in confinement, we perform dissipative particle dynamics (DPD) simulations to construct a model that is as large as possible to clarify the submissive behavior of NPs. Both molecular simulations and mechanical analysis revealed that the interactions between NPs are controlled by confinement deformation and the centroid distance of the NPs. When the centroid distance exceeds a threshold value, the degree of crowding variation becomes invalid for NPs motion. The above conclusions are further supported by the observed dynamics of multiple NPs under confinement. These findings provide new insights into the physical mechanism, revealing that the confinement squeeze generated by asymmetric deformation serves as the key factor governing the directional movement of the NPs. Therefore, the constraints acting on NPs differ between rigid confinement and soft confinement environments, with NPs maintaining relative stillness in rigid confinement.

Keywords: confining membrane; dissipative particle dynamics simulations; long-range interactions; nanoparticles.

Figure 1

Initial configuration of the simulation system: rigid confinement space and soft confinement space. The vesicle model represents soft particle transport in confinement: H_eff represents the effective separation between the two membranes, and L_cd represents the centroid distance between two vesicles.

Figure 2

Different pathways of vesicle transport in soft confinement and rigid confinement. (a,b) Typical snapshots of the vesicle transport process: (a) rigid confinement H_eff = 12 r_c, L_init-cd = 50 r_c; (b) soft confinement H_eff = 12 r_c, L_init-cd = 50 r_c. (L_init-cd is the initial distance between the vesicles in confinement); (c) comparison of the time evolution of L_cd (the distance between the vesicles in confinement).

Figure 3

Effect of the initial effective separation between the two membranes (H_eff) and the initial distance between the mass centers of the two vesicles (L_init-cd) on the transport of vesicles in soft confinement. (a–d) Typical dynamic process of vesicle transport under different conditions: (a) H_eff = 12 r_c, L_init-cd = 50 r_c; (b) H_eff = 16 r_c, L_init-cd = 50 r_c; (c) H_eff = 23 r_c, L_init-cd = 50 r_c; (d) H_eff = 12 r_c, L_init-cd = 100 r_c. (e) shows the time evolution of the L_cd variation between the vesicles under different confinement conditions.

Figure 4

Phase diagram of vesicle transport in soft confinement as a function of H_eff and L_init-cd.

Figure 5

(a) Deformation of the upper confinement membrane along the Z direction at the simulation time of t = 48 ns. (b) The vesicles are frozen, and the final state deformation of the upper confinement membrane with different L_init-cd variations along the Z direction.

Figure 6

(a) Schematic diagram showing the interaction between two neighboring nanoparticles (F) induced by the asymmetric deformation of soft confinement. (b) The horizontal component of the resultant force F as a function of the initial distance between the two vesicles. In this figure, H_eff = 12 r_c.

Figure 7

(a,b) Typical dynamic snapshots of three or four vesicles in confinement: H_eff = 12 r_c, L_init-cd = 50 r_c. (c) The position of the vesicles varies as a function of the simulation time, and the vertical coordinate represents the center-of-mass coordinate of the vesicle in the x direction: the red color represents three vesicles in the confined space, and the black color represents four vesicles in the confined space.