None of these are fully

working applications as yet. Clearly, with more ‘moving parts’, needs for high specificity of function, and persistence in complex competitive environments, they have been harder to implement and these designs would benefit from a degree of trustworthy engineering beyond what we can currently deliver effectively. Most skepticism of the synthetic biology agenda stems from the criticism that there is too much unknown about the biological system to be engineered and the effects of and on the environment Selleck Z VAD FMK in which it is to be deployed for a predictable engineering approach to be possible. While it is likely true that the levels of uncertainty in biological engineering will be larger

than in any other engineering discipline, we argue that it is not a hopeless venture and systematization of the field will enable predictably functioning designs. One of the controversial tenets of some synthetic biologists is that a reliable engineering field rests, at least in part, on the community agreeing to use well-characterized and ‘standardized’ parts and hosts. We, and others, have reviewed DAPT ic50 why this is so elsewhere and outlined much of the desiderata for such parts including tunability, orthogonality, scalability and more [21]. For gene expression in particular there has been an efflorescence of such families of standardized parts or modular strategies for creation of scalable functional regulators. Most of these affect transcription or translation initiation [22••, 23, 24, 25 and 26] or elongation [27, 28, 29, 30 and 31] though emerging standards are beginning to include elements that

mediate transcriptional termination [32 and 33], orthogonal protein–protein interactions for controlling metabolic pathway flux [34] and signaling [35] and targeted elements for controlling transcript [36] and protein degradation. The results of these have been the ability to predictably create circuits of increasing complexity but even these remain relatively small (2–5 input logic gates and Teicoplanin memory circuits [37, 38•, 39 and 40]). Ideally, each of these families provides not only building blocks for complex circuits but also represents controlled variations of key performance variables, such as promoter strength, that can be used in formal design-of-experiment protocols to rationally search a parameter space for optimal function [41]. Since the behavior of even these small circuits can be sensitive to changes in media/environment, host background, and configuration of elements on a replicon, characterization of their variable behavior across contexts is necessary.