Engineering artificial signalling functions with proteases

Design of a Biohybrid Materials Circuit with Binary Decoder Functionality

Synthetic biology applies concepts from electrical engineering and information processing to endow cells with computational functionality. Transferring the underlying molecular components into materials and wiring them according to topologies inspired by electronic circuit boards has yielded materials systems that perform selected computational operations. However, the limited functionality of available building blocks is restricting the implementation of advanced information-processing circuits into materials. Here, a set of protease-based biohybrid modules the bioactivity of which can either be induced or inhibited is engineered. Guided by a quantitative mathematical model and following a design-build-test-learn (DBTL) cycle, the modules are wired according to circuit topologies inspired by electronic signal decoders, a fundamental motif in information processing. A 2-input/4-output binary decoder for the detection of two small molecules in a material framework that can perform regulated outputs in form of distinct protease activities is designed. The here demonstrated smart material system is strongly modular and can be used for biomolecular information processing for example in advanced biosensing or drug delivery applications.

A computational design of a programmable biological processor

Basic synthetic information processing structures, such as logic gates, oscillators and flip-flops, have already been implemented in living organisms. Current implementations of these structures have yet to be extended to more complex processing structures that would constitute a biological computer. We make a step forward towards the construction of a biological computer. We describe a model-based computational design of a biological processor that uses transcription and translation resources of the host cell to perform its operations. The proposed processor is composed of an instruction memory containing a biological program, a program counter that is used to address this memory, and a biological oscillator that triggers the execution of the next instruction in the memory. We additionally describe the implementation of a biological compiler that compiles a sequence of human-readable instructions into ordinary differential equation-based models, which can be used to simulate and analyse the dynamics of the processor. The proposed implementation presents the first programmable biological processor that exploits cellular resources to execute the specified instructions. We demonstrate the application of the described processor on a set of simple yet scalable biological programs. Biological descriptions of these programs can be produced manually or automatically using the provided compiler.

Catalyst-Based Biomolecular Logic Gates

Regulatory processes in biology can be re-conceptualized in terms of logic gates, analogous to those in computer science. Frequently, biological systems need to respond to multiple, sometimes conflicting, inputs to provide the correct output. The language of logic gates can then be used to model complex signal transduction and metabolic processes. Advances in synthetic biology in turn can be used to construct new logic gates, which find a variety of biotechnology applications including in the production of high value chemicals, biosensing, and drug delivery. In this review, we focus on advances in the construction of logic gates that take advantage of biological catalysts, including both protein-based and nucleic acid-based enzymes. These catalyst-based biomolecular logic gates can read a variety of molecular inputs and provide chemical, optical, and electrical outputs, allowing them to interface with other types of biomolecular logic gates or even extend to inorganic systems. Continued advances in molecular modeling and engineering will facilitate the construction of new logic gates, further expanding the utility of biomolecular computing.

Connecting Artificial Proteolytic and Electrochemical Signaling Systems with Caged Messenger Peptides

Enzymatic polypeptide proteolysis is a widespread and powerful biological control mechanism. Over the last few years, substantial progress has been made in creating artificial proteolytic systems where an input of choice modulates the protease activity and thereby the activity of its substrates. However, all proteolytic systems developed so far have relied on the direct proteolytic cleavage of their effectors. Here, we propose a new concept where protease biosensors with a tunable input uncage a signaling peptide, which can then transmit a signal to an allosteric protein reporter. We demonstrate that both the cage and the regulatory domain of the reporter can be constructed from the same peptide-binding domain, such as calmodulin. To demonstrate this concept, we constructed a proteolytic rapamycin biosensor and demonstrated its quantitative actuation on fluorescent, luminescent, and electrochemical reporters. Using the latter, we constructed sensitive bioelectrodes that detect the messenger peptide release and quantitatively convert the recognition event into electric current. We discuss the application of such systems for the construction of in vitro sensory arrays and in vivo signaling circuits.

Synthetic Biology: Emerging Concepts to Design and Advance Adeno-Associated Viral Vectors for Gene Therapy

Three recent approvals and over 100 ongoing clinical trials make adeno-associated virus (AAV)-based vectors the leading gene delivery vehicles in gene therapy. Pharmaceutical companies are investing in this small and nonpathogenic gene shuttle to increase the therapeutic portfolios within the coming years. This prospect of marking a new era in gene therapy has fostered both investigations of the fundamental AAV biology as well as engineering studies to enhance delivery vehicles. Driven by the high clinical potential, a new generation of synthetic-biologically engineered AAV vectors is on the rise. Concepts from synthetic biology enable the control and fine-tuning of vector function at different stages of cellular transduction and gene expression. It is anticipated that the emerging field of synthetic-biologically engineered AAV vectors can shape future gene therapeutic approaches and thus the design of tomorrow's gene delivery vectors. This review describes and discusses the recent trends in capsid and vector genome engineering, with particular emphasis on synthetic-biological approaches.

Linker Engineering in the Context of Synthetic Protein Switches and Sensors

Linkers play critical roles in the construction of synthetic protein switches and sensors as they functionally couple a receptor with an actuator. With an increasing number of molecular toolboxes and experimental strategies becoming available that can be applied to engineer protein switches and sensors with tailored response functions, optimising the connecting linkers remains an idiosyncratic and empiric process. This review aims to provide an in-depth analysis of linker motifs, the biophysical properties they confer, and how they impact the performance of synthetic protein switches and sensors while identifying trends, mechanisms, and strategies that underlie the most potent switches and sensors.

Synthetic protein switches: Combinatorial linker engineering with iFLinkC

Linker engineering constitutes a critical, yet frequently underestimated aspect in the construction of synthetic protein switches and sensors. Notably, systematic strategies to engineer linkers by predictive means remain largely elusive to date. This is primarily due to our insufficient understanding how the biophysical properties that underlie linker functions mediate the conformational transitions in artificially engineered protein switches and sensors. The construction of synthetic protein switches and sensors therefore heavily relies on experimental trial-and-error. Yet, methods for effectively generating linker diversity at the genetic level are scarce. Addressing this technical shortcoming, iterative functional linker cloning (iFLinkC) enables the combinatorial assembly of linker elements with functional domains from sequence verified repositories that are developed and stored in-house. The assembly process is highly scalable and given its recursive nature generates linker diversity in a combinatorial and exponential fashion based on a limited number of linker elements.

iFLinkC: an iterative functional linker cloning strategy for the combinatorial assembly and recombination of linker peptides with functional domains

Recent years have witnessed increasing efforts to engineer artificial biological functions through recombination of modular-organized toolboxes of protein scaffolds and parts. A critical, yet frequently neglected aspect concerns the identity of peptide linkers or spacers connecting individual domains which remain poorly understood and challenging to assemble. Addressing these limitations, iFlinkC comprises a highly scalable DNA assembly process that facilitates the combinatorial recombination of functional domains with linkers of varying length and flexibility, thereby overcoming challenges with high GC-content and the repeat nature of linker elements. The capacity of iFLinkC is demonstrated in the construction of synthetic protease switches featuring PDZ-FN3-based affinity clamps and single-chain FKBP12-FRB receptors as allosteric inputs. Library screening experiments demonstrate that linker space is highly plastic as the induction of allosterically regulated protease switches can vary from >150-fold switch-ON to >13-fold switch-OFF solely depending on the identity of the connecting linkers and relative orientation of functional domains. In addition, Pro-rich linkers yield the most potent switches contradicting the conventional use of flexible Gly-Ser linkers. Given the ease and efficiency how functional domains can be readily recombined with any type of linker, iFLinkC is anticipated to be widely applicable to the assembly of any type of fusion protein.