De novo design of bioactive protein switches.

Allosteric regulation of protein function is widespread in biology, but is challenging for de novo protein design as it requires the explicit design of multiple states with comparable free energies. Here we explore the possibility of designing switchable protein systems de novo, through the modulation of competing inter- and intramolecular interactions. We design a static, five-helix 'cage' with a single interface that can interact either intramolecularly with a terminal 'latch' helix or intermolecularly with a peptide 'key'. Encoded on the latch are functional motifs for binding, degradation or nuclear export that function only when the key displaces the latch from the cage. We describe orthogonal cage-key systems that function in vitro, in yeast and in mammalian cells with up to 40-fold activation of function by key. The ability to design switchable protein functions that are controlled by induced conformational change is a milestone for de novo protein design, and opens up new avenues for synthetic biology and cell engineering.

Distinct timescales of RNA regulators enable the construction of a genetic pulse generator.

To build complex genetic networks with predictable behaviors, synthetic biologists use libraries of modular parts that can be characterized in isolation and assembled together to create programmable higher-order functions. Characterization experiments and computational models for gene regulatory parts operating in isolation are routinely used to predict the dynamics of interconnected parts and guide the construction of new synthetic devices. Here, we individually characterize two modes of RNA-based transcriptional regulation, using small transcription activating RNAs (STARs) and clustered regularly interspaced short palindromic repeats interference (CRISPRi), and show how their distinct regulatory timescales can be used to engineer a composed feedforward loop that creates a pulse of gene expression. We use a cell-free transcription-translation system (TXTL) to rapidly characterize the system, and we apply Bayesian inference to extract kinetic parameters for an ordinary differential equation-based mechanistic model. We then demonstrate in simulation and verify with TXTL experiments that the simultaneous regulation of a single gene target with STARs and CRISPRi leads to a pulse of gene expression. Our results suggest the modularity of the two regulators in an integrated genetic circuit, and we anticipate that construction and modeling frameworks that can leverage this modularity will become increasingly important as synthetic circuits increase in complexity.

Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression.

Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.

Computational design of small transcription activating RNAs for versatile and dynamic gene regulation.

A longstanding goal of synthetic biology has been the programmable control of cellular functions. Central to this is the creation of versatile regulatory toolsets that allow for programmable control of gene expression. Of the many regulatory molecules available, RNA regulators offer the intriguing possibility of de novo design-allowing for the bottom-up molecular-level design of genetic control systems. Here we present a computational design approach for the creation of a bacterial regulator called Small Transcription Activating RNAs (STARs) and create a library of high-performing and orthogonal STARs that achieve up to ~ 9000-fold gene activation. We demonstrate the versatility of these STARs-from acting synergistically with existing constitutive and inducible regulators, to reprogramming cellular phenotypes and controlling multigene metabolic pathway expression. Finally, we combine these new STARs with themselves and CRISPRi transcriptional repressors to deliver new types of RNA-based genetic circuitry that allow for sophisticated and temporal control of gene expression.

Achieving large dynamic range control of gene expression with a compact RNA transcription-translation regulator.

RNA transcriptional regulators are emerging as versatile components for genetic network construction. However, these regulators suffer from incomplete repression in their OFF state, making their dynamic range less than that of their protein counterparts. This incomplete repression causes expression leak, which impedes the construction of larger synthetic regulatory networks as leak propagation can interfere with desired network function. To address this, we demonstrate how naturally derived antisense RNA-mediated transcriptional regulators can be configured to regulate both transcription and translation in a single compact RNA mechanism that functions in Escherichia coli. Using in vivo gene expression assays, we show that a combination of transcriptional termination and ribosome binding site sequestration increases repression from 85% to 98%, or activation from 10-fold to over 900-fold, in response to cognate antisense RNAs. We also show that orthogonal repressive versions of this mechanism can be created through engineering minimal antisense RNAs. Finally, to demonstrate the utility of this mechanism, we use it to reduce network leak in an RNA-only cascade. We anticipate these regulators will find broad use as synthetic biology moves beyond parts engineering to the design and construction of more sophisticated regulatory networks.