AgentCell: a digital single-cell assay for bacterial chemotaxis

Abstract

We have developed AgentCell, a model using agent-based technology to study the relationship between stochastic intracellular processes and behavior of individual cells. As a test-bed for our approach we use bacterial chemotaxis, one of the best characterized biological systems. In this model, each bacterium is an agent equipped with its own chemotaxis network, motors and flagella. Swimming cells are free to move in a 3D environment. Digital chemotaxis assays reproduce experimental data obtained from both single cells and bacterial populations.

Overview of Mathematical Approaches Used to Model Bacterial Chemotaxis I: The Single Cell

“…Agent based models of bacterial chemotaxis have been developed by Kreft et al (1998), Emonet et al (2005), and Bray et al (2007). Such models allow attributes of individual cell behavior to be measured on the population scale and are computational in nature; each cell has a set of defined rules which it follows.…”

“…Such models allow attributes of individual cell behavior to be measured on the population scale and are computational in nature; each cell has a set of defined rules which it follows. Although Kreft et al (1998) and Emonet et al (2005) used a similar modeling methodology, their approaches contrast in a number of ways. The simulator developed by Kreft et al (1998) (BacSim) focused on the cellular metabolism and the effect that cell size and division have on the population.…”

“…On the single scale, their model accounted for substrate uptake, metabolism, the maintenance of cell biomass, cell volume and surface area, cell diffusion, and the growth of the colony. In contrast, the simulator developed by Emonet et al (2005) (AgentCell) included a description of receptor dynamics, the intracellular phosphotransfer network, and the motor and flagellum response. Kreft et al (1998) note that random variation in the maximum size of the cell causes the population to become more asynchronous than random variation in cell size at division.…”

“…They note that spatial heterogeneity in the available nutrient concentration does not generally cause asynchrony in the population, but results in sub-populations of the main population which grow at different rates, thus giving the appearance of asynchrony. Emonet et al (2005) considered the effect that stochastic variation in the intracellular signaling pathway may have on the population scale, their work motivated by the experimental evidence of Korobkova et al (2004). The phosphorylation signal pathway is implemented using the stochastic molecular simulator StochSim (Morton-Firth et al, 1999).…”

A computational model of chemotaxis-based cell aggregation

“…These models analyze changes in expression levels of proteins and other chemical compounds within a cell (Tomita et al, 1999) to predict cellular behavior such as growth, signaling, proliferation, differentiation and death (Christopher et al, 2004;Slepchenko et al, 2003). These approaches have been used to simulate several intracellular processes such as energy production and phospholipid synthesis (Tomita et al, 1999), and to simulate intracellular calcium dynamics and nucleocytoplasmic transport (Slepchenko et al, 2003) as well as intercellular processes like bacterial chemotaxis (Emonet et al, 2005). A more detailed approach to modeling and simulation of gene-gene, geneprotein and protein-protein interactions focuses on sporulation, metabolismic activity, signaling, sensing and apoptosis (Bio-SPICE, 2008), while a more general approach to cell simulation provides a modular meta-algorithm that can incorporate any time-driven simulation algorithm (Takahashi et al, 2004).…”