Virtual Tissues and Developmental Systems Biology

Cells in developing tissues must integrate and respond to highly dynamic information in the form of metabolic intermediates, genetic signals, and molecular gradients. Understanding the cellular decision-making process, and how these decisions may be perturbed by genetic errors or environmental disruptions to invoke abnormal development, requires a fundamental understanding of how developing tissues are organized and controlled at a systems level. Computational (in silico) models of the embryo may have future applications for mechanistic understanding and predictive modeling of developmental toxicity. Such models would incorporate extensive knowledge of system structure, network state relations, kinetic parameters, and cellular computation. These models would utilize high-content data from genome-based studies, and high-throughput data from in vitro screens, to understand many of the genes, signaling pathways, and biochemical reactions that orchestrate a morphogenetic series of events in the embryo. Dynamic ‘virtual tissue’ models that utilize cross-scale information about developmental processes and quantitative data on prenatal developmental toxicities could someday be used to simulate how embryos might react to chemical exposure and better characterize chemical mode of action for complex exposure scenarios in silico. Current testing strategies for developmental (and reproductive) toxicity evaluation are expensive, are time-consuming, use a lot of animals, do not cover all possible health end points or life stage sensitivities, and are often studied at dosages too high for basing regulatory decisions. This chapter will review the field of virtual tissues and computational systems biology with emphasis on developmental toxicity.