Diffusion within the Cytoplasm: A Mesoscale Model of Interacting Macromolecules

Abstract

Recent experiments carried out in the dense cytoplasm of living cells have highlighted the importance of proteome composition and nonspecific intermolecular interactions in regulating macromolecule diffusion and organization. Despite this, the dependence of diffusion-interaction on physicochemical properties such as the degree of poly-dispersity and the balance between steric repulsion and nonspecific attraction among macromolecules was not systematically addressed. In this work, we study the problem of diffusion-interaction in the bacterial cytoplasm, combining theory and experimental data to build a minimal coarse-grained representation of the cytoplasm, which also includes, for the first time to our knowledge, the nucleoid. With stochastic molecular-dynamics simulations of a virtual cytoplasm we are able to track the single biomolecule motion, sizing from 3 to 80 nm, on submillisecond-long trajectories. We demonstrate that the size dependence of diffusion coefficients, anomalous exponents, and the effective viscosity experienced by biomolecules in the cytoplasm is fine-tuned by the intermolecular interactions. Accounting only for excluded volume in these potentials gives a weaker size-dependence than that expected from experimental data. On the contrary, adding nonspecific attraction in the range of 1-10 thermal energy units produces a stronger variation of the transport properties at growing biopolymer sizes. Normal and anomalous diffusive regimes emerge straightforwardly from the combination of high macromolecular concentration, poly-dispersity, stochasticity, and weak nonspecific interactions. As a result, small biopolymers experience a viscous cytoplasm, while the motion of big ones is jammed because the entanglements produced by the network of interactions and the entropic effects caused by poly-dispersity are stronger.

Molecular simulations of cellular processes

“…12-15 μm 2 /s) at fixed macromolecule size indicates that transport is influenced by the different local environments within the MG cytoplasm. A similar scatter was also observed in a mesoscale E. coli cytoplasm model, composed of nonspecifically interacting biopolymers (Trovato and Tozzini 2014), suggesting that diffusion in the MG cytoplasm is sensitive to the local distribution of enthalpies. An interesting result of the MG simulations is the fast decrease of the diffusion coefficients of small molecules as a function of their size.…”

“…To overcome some limitations of previous cytoplasm models, namely the absence of the genetic material and the moderate cell-specificity of the inter-molecular interactions (Bicout and Field 1996;Boström et al 2001;Curtis and Lue 2006;Ando et al 2016), Trovato and Tozzini (2014) devised an original strategy to parameterize the nonspecific associations characteristic of E. coli. For the first time, the authors represented also the nucleoid, in addition to 12 species of macromolecules, therefore spanning three orders of magnitude in macromolecule size (Fig.…”

“…1a). In the first step of the force field parameterization, the interactions between any two spherical biomolecules were fitted on the energies calculated employing a coarse-grained model with E. coli characteristic amino acid distributions (see Trovato et al 2013 andTozzini 2014 for details). These interactions were refined in the subsequent phase, until the calculated diffusion coefficients of all macromolecules approached a cell-scale reference curve (Fig.…”

“…However, the largest effect of favorable interactions is experienced during diffusion (Saxton 1996;Putzel et al 2014;Peixoto et al 2015;Bucciarelli et al 2016;Smith et al 2016). Indeed, by allowing the macromolecules of a model bacterial cytoplasm to associate transiently, computer simulations have predicted a consistent motion slowdown that inert crowders were unable to explain (Trovato and Tozzini 2014). …”

Morphing Graphene-Based Systems for Applications: Perspectives from Simulations

“…In the cases under discussion, multi-scaling mainly involves the two basic levels of representations, namely the "ab initio" quantum chemistry (QM) level, with explicit electrons capable of describing the chemistry of the system, and the classical "molecular mechanics" (MM) representing the interatomic interactions with empirical force fields (FF). Super-atomic descriptions are also "natural" in specific cases: For instance, fullerenes were sometimes treated with a Coarse Grained sphere-of-beads model [22] similar to that used for biomolecules [23]. For the graphene sheets, conversely, a natural low-resolution representation is a 2D membrane endowed with appropriate mechanical properties [24], analogously to those used for biological membranes.…”