Colloid physics regulate life-essential processes in biological cells. A grand challenge of systems biology is an understanding of cells so complete that all cellular behavior can be determined from the composition and dynamics of constituent biomolecules. Advances in computation and experiments have enabled progress toward this goal, from atomistic models of proteins to de novo synthesis of entire genomes. Connecting single-molecule to cellular behavior requires bridging processes that operate over nanoseconds and nanometers to those spanning minutes and microns. But the physical details and dynamics of this intermediate realm are largely abstracted away in single-cell assays and whole-cell kinetics models.

Colloidal physics, which defines the intermediate physico-chemical dynamics of suspensions like cytoplasm, links molecular-scale phenomena like van der Waals forces to cellular-scale diffusion, self-assembly, and aggregation. We use colloid physics to understand how biomolecules instantiate whole-cell behavior; our approach is to select model biological processes – those essential to cell function, conserved across cell types, and implicated in disease – and then to explicitly represent all associated biomolecules.

To study our hypothesis that colloidal mechanisms beyond Brownian motion regulate mRNA translation outside the ribosome in E. coli, we built a novel bio-colloidal framework with nanometer resolution that explicitly represents the transport dynamics of individual biomolecules as they interact and react over whole-cell-function time scales [Maheshwari et al., Cell, in review], the first colloidally accurate model of mRNA translation. We showed that Brownian motion is essential but insufficient to recover experimentally measured elongation rates; we proposed and tested new colloidal mechanisms that close the gap. This is a general framework for discovering how colloid physics predict biological behavior, which can access systems biology timescales by using a kinetics acceleration scheme that takes advantage of reaction timescales being much longer than those of diffusive mixing. Our findings demonstrate the effectiveness of colloidal biology in representing cell processes and illustrates the effectiveness of theoretical modeling in cell biology.