Engineering of synthetic gene circuits for (re-)balancing physiological processes in chronic diseases

Synthetic biology is a promising multidisciplinary field that brings together experts in scientific disciplines from cell biology to engineering with the goal of constructing elements that do not occur in nature for use in various applications, such as the development of novel approaches to improving healthcare management. Current disease treatment strategies are typically based on the diagnosis of phenotypic changes, which are often the result of an accumulation of endogenous metabolic defects in the human body. These defects occur when the tight regulation of physiological processes is disturbed by genetic alterations, protein function losses, or environmental changes. Such disturbances can result in the development of serious disorders that are often associated with aberrant physiological levels of certain biomolecules (e.g., metabolites, cytokines, and growth factors), which may lead to specific pathogenic states. However, these aberrant levels can also serve as biomarkers for the precise detection and specification of disease types. Clinical interventions are often conducted during the late stages of disease pathogenesis because of a lack of early detection of these physiological disturbances, which results in disease treatment rather than prevention. Therefore, advanced therapeutic tools must be developed to link therapeutic intervention to early diagnosis. Recent advances in the field of synthetic biology have enabled the design of complex gene circuits that can be linked to a host's metabolism to autonomously detect disease-specific biomarkers and then reprogrammed to produce and release therapeutic substances in a self-sufficient and automatic fashion, thereby restoring the physiological balance of the host and preventing the progression of the disease. This concept offers a unique opportunity to design treatment protocols that could replace conventional strategies, especially for diseases with complex and recurrent dynamics, such as chronic diseases. (C) 2016 Wiley Periodicals, Inc.