Colloidal stability of the living cell

Abstract

Cellular function is generally depicted at the level of functional pathways and detailed structural mechanisms, based on the identification of specific protein-protein interactions. For an individual protein searching for its partner, however, the perspective is quite different: The functional task is challenged by a dense crowd of nonpartners obstructing the way. Adding to the challenge, there is little information about how to navigate the search, since the encountered surrounding is composed of protein surfaces that are predominantly "nonconserved" or, at least, highly variable across organisms. In this study, we demonstrate from a colloidal standpoint that such a blindfolded intracellular search is indeed favored and has more fundamental impact on the cellular organization than previously anticipated. Basically, the unique polyion composition of cellular systems renders the electrostatic interactions different from those in physiological buffer, leading to a situation where the protein net-charge density balances the attractive dispersion force and surface heterogeneity at close range. Inspection of naturally occurring proteomes and in-cell NMR data show further that the "nonconserved" protein surfaces are by no means passive but chemically biased to varying degree of net-negative repulsion across organisms. Finally, this electrostatic control explains how protein crowding is spontaneously maintained at a constant level through the intracellular osmotic pressure and leads to the prediction that the "extreme" in halophilic adaptation is not the ionic-liquid conditions per se but the evolutionary barrier of crossing its physicochemical boundaries.

Keywords: cellular organization; electrostatics; halophilic adaptation; ion screening; protein–protein interactions.

Fig. 1.

Dimensions and forces of biological macromolecules. (A) Colloidal description of particles (R ≥ 100 nm) yielding kinetic stability through a high repulsive association barrier. (B) Relative sizes of ribosomes and proteins, constituting the dominant fraction of soluble cytoplasmic components. (C) The separation distance (h) regimes of the balancing forces that modulate protein–protein interactions in vivo.

Fig. 2.

Crowding, properties, and motions of proteins in E. coli cells. (A) It is kinetically favorable for the cell to be compact to ensure short diffusion paths, but not so compact that the diffusional motion becomes restricted. Judging by E. coli, the optimal balance is at protein concentrations around 350 mg/mL (25, 26). Crowding panel reprinted from ref. , which is licensed under CC BY 4.0. (B) Hydrodynamic radii of soluble proteins in E. coli. (C) Protein size shows a slanted correlation with net charge. (D) Upon rescaling to surface net-charge density, the distribution becomes approximately normal. (E) Normalized protein motion in the E. coli cytosol as measured by in-cell NMR rotation-correlation times. The projection is along the data plane and shows the dependence on negative net-charge density and the protein-dipole moment. Data include >130 surface mutations of three proteins: bacterial TTHA (blue), human HAH1 (red), and human SOD1-barrel (green). Panel adapted from ref. . (F) Differences in ion composition between the extracellular medium and the E. coli cytosol.

Fig. 3.

Description of intracellular protein–protein interactions. (A) Dimensions of typical E. coli proteins, where the effective Debye screening length (λ_D) exceeds the protein–protein separation (h). (B) Schematic single layer (n = 7) of the interaction network, outlining the spatial parameters of SI Appendix and Eqs. 1–5. The resulting interaction potential for E. coli proteins is shown in Fig. 4.

Fig. 4.

Intracellular interaction potential calculated from the average characteristics of the E. coli proteome (SI Appendix). (A) The interaction potential of the E. coli proteins calculated from the asymptotic form in Eq. 3, valid for intermediate and longer range. (B) Corresponding potential at the high-charge limit, exemplifying the increased repulsion at short range between proteins at the extreme negative side of the E. coli net-charge density distribution (Fig. 2). In both cases, the proteins lack the deep association minima and large kinetic barriers of larger colloidal particles, suggesting that the protein–protein encounters are maintained at thermodynamic equilibrium (cf. Fig. 1).

Fig. 5.

Minimum of effective screening length (λ_s) yields an electrostatic “eclipse” around [NaCl] = 1 M. (A) Up to ∼[NaCl] = 1 M, the screening length follows conventional Debye–Hückel decline, whereas in the ionic-liquid regime it restores due to ion–ion correlations (44, 46). Between these limits is an “eclipse” where the electrostatic interactions are severely mitigated at λ_s < 0.5 nm. (B) Since long- and medium-range charge interactions seem crucial for cellular function, intracellular salt concentrations around the electrostatic “eclipse” are expected to be most unfavorable. Correspondingly, there is a minimum in the distribution of proteome net-charge densities separating Halobacteria from other organisms.