Phenotype-centric modeling for elucidation of biological design principles

Abstract

A recently developed ‘phenotype-centric’ modeling strategy combines four innovations with the potential to advance our understanding of complex biological systems: (1) a rigorous mathematical definition of biochemical phenotypes, (2) a method for enumerating the phenotypic repertoire based on the biomolecular network architecture, (3) an integrated suite of computational algorithms for the efficient prediction of parameter values and analysis of the phenotypic repertoire, and (4) a user-focused environment for navigating the resulting space of phenotypes and identifying biologically relevant features and system design principles. These innovations will facilitate deterministic and stochastic simulations that require parameter values, will accelerate both hypothesis discrimination in systems biology and the design cycle in synthetic biology. Here we first review the fundamental definition of biochemical phenotype that enables this new modeling strategy and give an overview of the strategy using a simple system from phage λ to provide an example of a global design principle. Second, we illustrate this approach in more detail with an application to a common network architecture involving positive and negative feedback. We report system design principles related to the global tolerances of this system's phenotypes. Finally, we apply the phenotype-centric strategy to a logic network and compare the results with those obtained from a Boolean approach. Mechanistic and Boolean models have well-documented complementary advantages and disadvantages. Mechanistic models have the advantage of being biologically realistic; however, they also are limited by the large number of kinetic parameters whose values are largely unknown. Boolean models have the advantage of being parameter free; however, they also are limited by the absence of well-known physical and chemical constraints. We show that the phenotype-centric modeling strategy combines advantages of both.