Towards a Genomically Detailed Minimal Cell Model
Jordan Atlas, Cornell University
The question of "What is essential for life?" is one of the most fundamental questions we face. Understanding and identifying the regulatory and organizational concepts central to life is aided by the complete reconstruction of whole-cell models in silico. Systems biology investigates the behavior of all of the elements in a biological system while it is functioning. As a systems biology approach, the Minimal Cell Model (MCM) depicts the total functionality of a minimal cell and its explicit response to perturbations in its environment.
A minimal cell is defined as a prokaryote containing the minimum number of genes for growth and replication with ample access to nutritional resources. We aim to complete a genomically-detailed MCM that addresses all the metabolic and non-metabolic features of a chemoheterotrophic bacterial cell. While the original MCM used chemically lumped pseudospecies (Castellanos et al., Biotech. Bioeng., 97(2), p. 397, 2006), the complete MCM will use concentrations of individual chemical species and mass balances on each species based on known biochemical reaction data.
An initial step in this approach was the development of a whole-cell coarse-grained model which explicitly links DNA replication, metabolism, and cell geometry with the external environment. A hybrid model was then constructed from chemically-detailed and genome-specific subsystems, called modules, which were inserted into the original coarse-grained model. The project proposed here includes two main parts: 1) To establish a genomically-detailed MCM by implementing expression of the minimal gene set proposed by Gil et al. (MMBR, 68(3), p.518, 2004) within our hybrid cell-modeling framework, and 2) To deduce a set of computationally derived cell-modeling heuristics useful for synthetic biology. Overall we expect to develop a dynamic modeling framework to integrate genomic detail within functionally complete hybrid bacterial cell models.
Abstract Author(s): Jordan C. Atlas, and Michael L. Shuler