Macromolecular interactions and geometrical confinement determine the 3D diffusion of ribosome-sized particles in live Escherichia coli cells

Abstract

The crowded bacterial cytoplasm is composed of biomolecules that span several orders of magnitude in size and electrical charge. This complexity has been proposed as the source of the rich spatial organization and apparent anomalous diffusion of intracellular components, although this has not been tested directly. Here, we use biplane microscopy to track the 3D motion of self-assembled bacterial genetically encoded multimeric nanoparticles (bGEMs) with tunable size (20 to 50 nm) and charge (-3,240 to +2,700 e) in live Escherichia coli cells. To probe intermolecular details at spatial and temporal resolutions beyond experimental limits, we also developed a colloidal whole-cell model that explicitly represents the size and charge of cytoplasmic macromolecules and the porous structure of the bacterial nucleoid. Combining these techniques, we show that bGEMs spatially segregate by size, with small 20-nm particles enriched inside the nucleoid, and larger and/or positively charged particles excluded from this region. Localization is driven by entropic and electrostatic forces arising from cytoplasmic polydispersity, nucleoid structure, geometrical confinement, and interactions with other biomolecules including ribosomes and DNA. We observe that at the timescales of traditional single molecule tracking experiments, motion appears subdiffusive for all particle sizes and charges. However, using computer simulations with higher temporal resolution, we find that the apparent anomalous exponents are governed by the region of the cell in which bGEMs are located. Molecular motion does not display anomalous diffusion on short time scales and the apparent subdiffusion arises from geometrical confinement within the nucleoid and by the cell boundary.

Keywords: anomalous diffusion; bacterial cytoplasm; biophysics; microbiology.

Fig. 1.

3D-SPT experiments and whole-cell colloidal simulations probe macromolecular dynamics in E. coli. (A) Sample bacterial cell imaged through biplane microscopy. In biplane microscopy two focal planes are imaged simultaneously (schematic, Left). Three snapshots are shown (images, Right) from left to right in Plane 1 (top row) and Plane 2 (bottom row). The bacterial membrane is labeled in dark blue and the DNA is stained in magenta. Cell and nucleoid envelopes are outlined in white and red, respectively. The bGEM nanoparticle (green) is initially in focus in Plane 1 (top row, Left); as it moves through the cell, it comes into focus on Plane 2 (bottom row, Right). (B) Sample 3D trajectory for a 50-nm particle. (C) yz projection of the trajectory shows the particle is primarily excluded from the cell’s nucleoid. (D) Whole-cell colloidal model of E. coli, cross-sectional view, dynamic simulation snapshot. The nucleoid (magenta, outlined in red) is interpenetrated and surrounded by a polydisperse cytoplasm, confined by a cellular membrane (blue). The cytoplasm consists of negatively (gray) and positively (white) charged native crowders (which represent proteins, ternary complexes, transcription factors, ribosomal subunits, etc.), negatively charged ribosomes and polysomes (yellow), and bGEMs (green) at physiological abundances and densities (, –54). The dynamical motion of individual bGEMs (green sphere, zoomed-in view, Right) is tracked in simulation and compared to the 3D particle traces from experiments. Each particle moves via Brownian motion and interacts directly and physically with other macromolecules, the nucleoid, and the cell membrane.

Fig. 2.

Macromolecular localization in E. coli depends on size. (A) xy and yz 2D histograms of 20-nm (3,750 localizations), 40-nm (9,500 localizations), and 50-nm (24,000 localizations) tracers in Top, Middle, and Bottom images, respectively. Cell sizes are normalized. Brighter intensity shows more localization. Contrast adjusted linearly to improve visibility. Average nucleoid region (red dashed line) and cell periphery (solid white line) are highlighted. (B) Experimental probability distribution of finding a particle at a particular radial position from the center of the cell. Radial density distributions shift toward the cell periphery as tracer size increases. The stars indicate statistical significance of the Kolmogorov–Smirnoff test comparing the distributions. Specifically, *** indicates P-value < 0.001. (C) Nucleoid occupation time (defined as total number of timepoints in the nucleoid divided by length of the trajectory) decreases with tracer size. The agreement between experiment (black) and simulations (red) is excellent. (D) Percent of voids in the nucleoid large enough to permit passage of a tracer of size a, for a range of tracer sizes shown on the horizontal axis. Error bars in the pore-size distribution due to thermal fluctuations of the DNA molecules are not visible in the plot. The corresponding values are presented in SI Appendix, Fig. S7C. Inset: Simulation snapshot of the interconnected nucleoid network with pores that permit penetration of a bGEM of size 20-nm (orange), 40-nm (light blue), and 50-nm (purple) highlighted. All bGEM sizes studied here can fit in some pores of the nucleoid, but smaller bGEMs (colored circles, Inset) can penetrate more of the void distribution.

Fig. 3.

Electrostatic interactions between bGEMS and other cytoplasm macromolecules determine the localization of bGEMS. (A) xy and yz 2D histograms from experiments for 40-nm bGEMs of charge of −3,240 e (7,500 localizations), −1,260 e (9,500 localizations), and +2,700 e (11,000 localizations) in Top, Middle, and Bottom images, respectively. Brighter intensity shows more localization. Contrast adjusted linearly to improve visibility. Average nucleoid region (red dashed line) and cell periphery (solid white line) are highlighted. (B) Experimental probability distribution of finding a particle at a particular radial position from the center of the cell. Radial density distributions shift toward the cell periphery as net charge increases. The stars indicate statistical significance of the Kolmogorov–Smirnoff test comparing the distributions. Specifically, ** indicates P-value < 0.005 and *** indicates P-value < 0.001. (C) Nucleoid occupation time for experiment (black) and simulations (red) shows good agreement. Negatively charged bGEMS spend ≈40% of their time inside the nucleoid, much more than positively charged bGEMs (≈25%). (D) The normalized mean coordination number (average number of neighboring negative crowders, positive crowders, nucleic acids, and ribosomes per GEM divided by that of a GEM with zero net charge) obtained from simulation quantifies macromolecular interactions and shows that positively charged bGEMS bind to ribosomes, explaining why they spend less time inside the nucleoid. Strongly negative particles form clusters with surrounding positively charged crowders, yielding a larger effective particle size yet still manage to enter the nucleoid. In contrast, only strong interactions with ribosomes outside the nucleoid and DNA inside the nucleoid definitively segregate biomolecules either inside (DNA-bound) or outside (ribosome-bound) the nucleoid. Insets: Simulation snapshots for (Left) −3,240 e, (Middle) −1,260 e, and (Right) +2,700 e bGEMs.

Fig. 4.

Macromolecular dynamics are governed by size and charge. (A) 3D experimental mean square displacement (MSD) for all bGEM sizes and charges as a function of lag time. Motion appears subdiffusive with an exponent smaller than 1 (dashed black line) for all particles. Inset: Particles experience different confinement volumes based on size. (B) MSD from whole-cell colloidal simulations for all bGEM sizes and charges as a function of lag time. Dynamics at shorter timescales have a power-law exponent much closer to unity. (C) Experimental MSD normalized by diffusion coefficients obtained from probabilistic simulations of the excluded volume nucleoid as a function of lag time shows that the power-law exponent of diffusion for each particle size and charge is explained by a confined random walk in the cellular region the particle occupies. (D) 2D (x,y) MSD of ribosomes and bGEMs as a function of lag time. Qualitative agreement between these data from bGEMs and previously published ribosomal species diffusion data [reproduced with permission from Bakshi et al. (22)] indicates that bGEMs serve as good probes of biophysical dynamics of large particles in E. coli.