Biology subjects

Sunol, A. M.

Publications and source records attributed to Sunol, A. M..

4 recordsLinked to original sources

bioRxiv2024

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

The crowded bacterial cytoplasm is comprised 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 (-2160 to +1800 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 sub-diffusive 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 sub-diffusion arises from geometrical confinement within the nucleoid and by the cell boundary.

biophysics↗

bioRxiv2023

Pre-loading of translation molecules onto ribosomes speeds transport and protein synthesis in Escherichia coli

Translating ribosomes must wait after each elongation step for a new ternary complex (EF-Tu{middle dot}aa-tRNA{middle dot}GTP) to arrive, facilitating rapid codon recognition testing. We recently showed that this wait-time rate-limits elongation in Escherichia coli due to competitive combinatoric searching through crowded cytoplasm by thousands of E. colis 42 unique ternary complexes. Here, we investigate whether ribosomal L12 subunits pool translation molecules to reduce this wait time. We mimic transport and reactions underlying elongation in a physiologically accurate, physically-resolved model of crowded cytoplasm. We find that L12 pre-loading as much as doubles translation rate by reducing diffusive search time. But more L12 is not always better: faster-growing bacteria tend to have fewer L12. We resolve this apparent contradiction by demonstrating tradeoffs between binding and novel sampling as a function of copy number in E. coli. Variable L12 copy numbers may thus have evolved for fast or slow bacterial growth as complementary survival strategies.

biophysics↗

bioRxiv2022

Ultra-weak protein-protein interactions can modulate proteome-wide searching and binding

Research on protein-protein interaction (PPIs) tends to focus on high affinity interactions. Weaker interactions (Kd >1M) recently understood as contributing to intracellular phase separation suggest that even-weaker PPIs might also matter in as-yet unknown ways. However, ultra-weak PPIs (Kd >1mM) are not readily accessible by in vivo techniques. Here we use protein electrostatics to estimate PPI strengths and spatially-resolved dynamic simulations to investigate the potential impacts of ultra-weak PPIs within dense protein suspensions. We find that ultra-weak PPIs can drive formation of transient clusters that last long enough to enable enzyme-catalyzed reactions and accelerate the sampling of protein associations. We apply our method to Mycoplasma genitalium, finding that ultra-weak PPIs should be ubiquitous among cytoplasmic proteins. We also predict that the proteome-wide interactome can be shifted to favor binding-dominant ultra-weak PPIs via the introduction of a few charged protein complexes. We speculate that ultra-weak PPIs could contribute to cellular fitness by facilitating sampling and colloidal-scale transport of proteins involved in biological processes, including protein synthesis.

biophysics↗

bioRxiv2021

Molecular transport and packing underlie increasing ribosome productivity in faster growing cells

Faster growing cells must synthesize proteins more quickly. Increased ribosome abundance only partly accounts for increases in total protein synthesis rates. The productivity of individual ribosomes must increase too, almost doubling by an unknown mechanism. Prior models point to diffusive transport as a limiting factor but surface a paradox: faster growing cells are more crowded, yet crowding slows diffusion. We suspected physical crowding, transport, and stoichiometry, considered together, might reveal a more nuanced explanation. To investigate, we built a first-principles physics-based model of E. coli cytoplasm in which Brownian motion and diffusion arise directly from physical interactions between individual molecules of finite size, density, and physiological abundance. Using our microscopically-detailed model, we predict that physical transport of individual ternary complexes accounts for ~80% of translation elongation latency. We also find that volumetric crowding increases at faster growth even as cytoplasmic mass density remains relatively constant. Despite slowed diffusion, we predict that improved proximity between ternary complexes and ribosomes wins out, illustrating a simple physics-based mechanism for how individual elongating ribosomes become more productive. We speculate how crowding imposes a physical limit on growth rate and undergirds cellular behavior more broadly. Unfitted colloidal-scale modeling offers systems biology a complementary "physics engine" for exploring how cellular-scale behaviors arise from physical transport and reactions among individual molecules.

biophysics↗