Engineering robust control of two-component system phosphotransfer using modular scaffolds

Engineering synthetic phosphorylation signaling networks in human cells

Protein phosphorylation signaling networks have a central role in how cells sense and respond to their environment. We engineered artificial phosphorylation networks in which reversible enzymatic phosphorylation cycles were assembled from modular protein domain parts and wired together to create synthetic phosphorylation circuits in human cells. Our design scheme enabled model-guided tuning of circuit function and the ability to make diverse network connections; synthetic phosphorylation circuits can be coupled to upstream cell surface receptors to enable fast-timescale sensing of extracellular ligands, and downstream connections can regulate gene expression. We engineered cell-based cytokine controllers that dynamically sense and suppress activated T cells. Our work introduces a generalizable approach that allows the design of signaling circuits that enable user-defined sense-and-respond function for diverse biosensing and therapeutic applications.

Engineering two-component systems for advanced biosensing: From architecture to applications in biotechnology

Two-component systems (TCSs) are prevalent signaling pathways in bacteria. These systems mediate phosphotransfer between histidine kinase and a response regulator, facilitating responses to diverse physical, chemical, and biological stimuli. Advancements in synthetic and structural biology have repurposed TCSs for applications in monitoring heavy metals, disease-associated biomarkers, and the production of bioproducts. However, the utility of many TCS biosensors is hindered by undesired performance due to the lack of effective engineering methods. Here, we briefly discuss the architectures and regulatory mechanisms of TCSs. We also summarize the recent advancements in TCS engineering by experimental or computational-based methods to fine-tune the biosensor functional parameters, such as response curve and specificity. Engineered TCSs have great potential in the medical, environmental, and biorefinery fields, demonstrating a crucial role in a wide area of biotechnology.

Engineering synthetic phosphorylation signaling networks in human cells

Protein phosphorylation signaling networks play a central role in how cells sense and respond to their environment. Here, we describe the engineering of artificial phosphorylation networks in which "push-pull" motifs-reversible enzymatic phosphorylation cycles consisting of opposing kinase and phosphatase activities-are assembled from modular protein domain parts and then wired together to create synthetic phosphorylation circuits in human cells. We demonstrate that the composability of our design scheme enables model-guided tuning of circuit function and the ability to make diverse network connections; synthetic phosphorylation circuits can be coupled to upstream cell surface receptors to enable fast-timescale sensing of extracellular ligands, while downstream connections can regulate gene expression. We leverage these capabilities to engineer cell-based cytokine controllers that dynamically sense and suppress activated T cells. Our work introduces a generalizable approach for designing and building phosphorylation signaling circuits that enable user-defined sense-and-respond function for diverse biosensing and therapeutic applications.

Engineering transmembrane signal transduction in synthetic membranes using two-component systems

Cells use signal transduction across their membranes to sense and respond to a wide array of chemical and physical signals. Creating synthetic systems which can harness cellular signaling modalities promises to provide a powerful platform for biosensing and therapeutic applications. As a first step toward this goal, we investigated how bacterial two-component systems (TCSs) can be leveraged to enable transmembrane-signaling with synthetic membranes. Specifically, we demonstrate that a bacterial two-component nitrate-sensing system (NarX-NarL) can be reproduced outside of a cell using synthetic membranes and cell-free protein expression systems. We find that performance and sensitivity of the TCS can be tuned by altering the biophysical properties of the membrane in which the histidine kinase (NarX) is integrated. Through protein engineering efforts, we modify the sensing domain of NarX to generate sensors capable of detecting an array of ligands. Finally, we demonstrate that these systems can sense ligands in relevant sample environments. By leveraging membrane and protein design, this work helps reveal how transmembrane sensing can be recapitulated outside of the cell, adding to the arsenal of deployable cell-free systems primed for real world biosensing.

Engineering whole-cell microbial biosensors: Design principles and applications in monitoring and treatment of heavy metals and organic pollutants

Biosensors have been widely used as cost-effective, rapid, in situ, and real-time analytical tools for monitoring environments. The development of synthetic biology has enabled emergence of genetically engineered whole-cell microbial biosensors. This review updates the design and optimization principles for a diverse array of whole-cell biosensors based on transcription factors (TF) including activators or repressors derived from heavy metal resistance systems, alkanes, and aromatics metabolic pathways of bacteria. By designing genetic circuits, the whole-cell biosensors could be engineered to intelligently sense heavy metals (Hg²⁺, Zn²⁺, Pb²⁺, Au³⁺, Cd²⁺, As³⁺, Ni²⁺, Cu²⁺, and UO₂²⁺) or organic compounds (alcohols, alkanes, phenols, and benzenes) through one-component or two-component system-based TFs, transduce signals through genetic amplifiers, and response as various outputs such as cell fluorescence and bioelectricity for monitoring heavy metals and organic pollutants in real conditions, synthetic curli and surface metal-binding peptides for in situ bio-sorption of heavy metals. We further review strategies that have been implemented to optimize the selectivity and correlation between ligand concentration and output signal of the TF-based biosensors, so as to meet requirements of practical applications. The optimization strategies include protein engineering to change specificities, promoter engineering to improve sensitivities, and genetic circuit-based amplification to enhance dynamic ranges via designing transcriptional amplifiers, logic gates, and feedback loops. At last, we outlook future trends in developing novel forms of biosensors.

Multisite Enzymes as a Mechanism for Bistability in Reaction Networks

Here, we focus on a common class of enzymes that have multiple substrate binding sites (multisite enzymes) and analyze their capacity to generate bistable dynamics in the reaction networks that they are embedded in. These networks include both substrate-product-substrate cycles and substrate-to-product conversion with subsequent product consumption. Using mathematical techniques, we show that the inherent binding and catalysis reactions arising from multiple substrate-enzyme complexes create a potential for bistable dynamics in such reaction networks. We construct a generic model of an enzyme with n-substrate binding sites and derive an analytical solution for the steady-state concentration of all enzyme-substrate complexes. By studying these expressions, we obtain a mechanistic understanding of bistability, derive parameter combinations that guarantee bistability, and show how changing specific enzyme kinetic parameters and enzyme levels can lead to bistability in reaction networks involving multisite enzymes. Thus, the presented findings provide a biochemical and mathematical basis for predicting and engineering bistability in multisite enzymes.

Bacterial two-component systems as sensors for synthetic biology applications

Two-component systems (TCSs) are a ubiquitous family of signal transduction pathways that enable bacteria to sense and respond to diverse physical, chemical, and biological stimuli outside and inside the cell. Synthetic biologists have begun to repurpose TCSs for applications in optogenetics, materials science, gut microbiome engineering, and soil nutrient biosensing, among others. New engineering methods including genetic refactoring, DNA-binding domain swapping, detection threshold tuning, and phosphorylation cross-talk insulation are being used to increase the reliability of TCS sensor performance and tailor TCS signaling properties to the requirements of specific applications. There is now potential to combine these methods with large-scale gene synthesis and laboratory screening to discover the inputs sensed by many uncharacterized TCSs and develop a large new family of genetically-encoded sensors that respond to an unrivaled breadth of stimuli.

A Biosensor for Detection of Indole Metabolites

Microbially produced indole metabolites serve as a diverse family of interspecies and interkingdom signaling molecules in the context of human health, crop production, and antibiotic resistance. We mined the protein database for sensors of indole metabolites and developed a biosensor for indole-3-aldehyde (I3A). Microbially produced I3A has been associated with reducing inflammation in diseases such as ulcerative colitis by stimulating the aryl hydrocarbon receptor pathway. We engineered an E. coli strain embedded with a single plasmid carrying a chimeric two-component system that detects I3A. Our I3A receptor characterization confirmed binding site residues that contribute to the sensor's I3A detection range of 0.1-10 μM. This new I3A biosensor opens the door to sensing indole metabolites produced at various host-microbe interfaces and provides new parts for synthetic biology applications.

An engineered protein-phosphorylation toggle network with implications for endogenous network discovery

Synthetic biological networks comprising fast, reversible reactions could enable engineering of new cellular behaviors that are not possible with slower regulation. Here, we created a bistable toggle switch in Saccharomyces cerevisiae using a cross-repression topology comprising 11 protein-protein phosphorylation elements. The toggle is ultrasensitive, can be induced to switch states in seconds, and exhibits long-term bistability. Motivated by our toggle's architecture and size, we developed a computational framework to search endogenous protein pathways for other large and similar bistable networks. Our framework helped us to identify and experimentally verify five formerly unreported endogenous networks that exhibit bistability. Building synthetic protein-protein networks will enable bioengineers to design fast sensing and processing systems, allow sophisticated regulation of cellular processes, and aid discovery of endogenous networks with particular functions.

Programmable protein circuit design

A fundamental challenge in synthetic biology is to create molecular circuits that can program complex cellular functions. Because proteins can bind, cleave, and chemically modify one another and interface directly and rapidly with endogenous pathways, they could extend the capabilities of synthetic circuits beyond what is possible with gene regulation alone. However, the very diversity that makes proteins so powerful also complicates efforts to harness them as well-controlled synthetic circuit components. Recent work has begun to address this challenge, focusing on principles such as orthogonality and composability that permit construction of diverse circuit-level functions from a limited set of engineered protein components. These approaches are now enabling the engineering of circuits that can sense, transmit, and process information; dynamically control cellular behaviors; and enable new therapeutic strategies, establishing a powerful paradigm for programming biology.

An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells

Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device's output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression.

Designed Asymmetric Protein Assembly on a Symmetric Scaffold

Cellular signaling is regulated by the assembly of proteins into higher-order complexes. Bottom-up creation of synthetic protein assemblies, especially asymmetric complexes, is highly challenging. Presented here is the design and implementation of asymmetric assembly of a ternary protein complex facilitated by Rosetta modeling and thermodynamic analysis. The wild-type symmetric CT32-CT32 interface of the 14-3-3-CT32 complex was targeted, ultimately favoring asymmetric assembly on the 14-3-3 scaffold. Biochemical studies, supported by mass-balance models, allowed characterization of the parameters driving asymmetric assembly. Importantly, our work reveals that both the individual binding affinities and cooperativity between the assembling components are crucial when designing higher-order protein complexes. Enzyme complementation on the 14-3-3 scaffold highlighted that interface engineering of a symmetric ternary complex generates asymmetric protein complexes with new functions.

Conjugated Protein Domains as Engineered Scaffold Proteins

Assembly of proteins into higher-order complexes generates specificity and selectivity in cellular signaling. Signaling complex formation is facilitated by scaffold proteins that use modular scaffolding domains, which recruit specific pathway enzymes. Multimerization and recombination of these conjugated native domains allows the generation of libraries of engineered multidomain scaffold proteins. Analysis of these engineered proteins has provided molecular insight into the regulatory mechanism of the native scaffold proteins and the applicability of these synthetic variants. This topical review highlights the use of engineered, conjugated multidomain scaffold proteins on different length scales in the context of synthetic signaling pathways, metabolic engineering, liquid-liquid phase separation, and hydrogel formation.

The Relationship between Effective Molarity and Affinity Governs Rate Enhancements in Tethered Kinase-Substrate Reactions

Scaffold proteins are thought to accelerate protein phosphorylation reactions by tethering kinases and substrates together, but there is little quantitative data on their functional effects. To assess the contribution of tethering to kinase reactivity, we compared intramolecular and intermolecular kinase reactions in a minimal model system. We found that tethering can enhance reaction rates in a flexible tethered kinase system and that the magnitude of the effect is sensitive to the structure of the tether. The largest effective molarity we obtained was ∼0.08 μM, which is much lower than the effects observed in small molecule model systems and other tethered protein reactions. We further demonstrated that the tethered intramolecular reaction only makes a significant contribution to the observed rates when the scaffolded complex assembles at concentrations below the effective molarity. These findings provide a quantitative framework that can be applied to understand endogenous protein scaffolds and engineer synthetic networks.

Ancient origins of allosteric activation in a Ser-Thr kinase

A myriad of cellular events are regulated by allostery; therefore, evolution of this process is of fundamental interest. Here, we use ancestral sequence reconstruction to resurrect ancestors of two colocalizing proteins, Aurora A kinase and its allosteric activator TPX2 (targeting protein for Xklp2), to experimentally characterize the evolutionary path of allosteric activation. Autophosphorylation of the activation loop is the most ancient activation mechanism; it is fully developed in the oldest kinase ancestor and has remained stable over 1 billion years of evolution. As the microtubule-associated protein TPX2 appeared, efficient kinase binding to TPX2 evolved, likely owing to increased fitness by virtue of colocalization. Subsequently, TPX2-mediated allosteric kinase regulation gradually evolved. Surprisingly, evolution of this regulation is encoded in the kinase and did not arise by a dominating mechanism of coevolution.

Manipulation of Bacterial Signaling Using Engineered Histidine Kinases

Two-component systems allow bacteria to respond to changes in environmental or cytosolic conditions through autophosphorylation of a histidine kinase (HK) and subsequent transfer of the phosphate group to its downstream cognate response regulator (RR). The RR then elicits a cellular response, commonly through regulation of transcription. Engineering two-component system signaling networks provides a strategy to study bacterial signaling mechanisms related to bacterial cell survival, symbiosis, and virulence, and to develop sensory devices in synthetic biology. Here we focus on the principles for engineering the HK to identify unknown signal inputs, test signal transmission mechanisms, design small molecule sensors, and rewire two-component signaling networks.

Engineering DNA recognition and allosteric response properties of TetR family proteins by using a module-swapping strategy

The development of synthetic biological systems requires modular biomolecular components to flexibly alter response pathways. In previous studies, we have established a module-swapping design principle to engineer allosteric response and DNA recognition properties among regulators in the LacI family, in which the engineered regulators served as effective components for implementing new cellular behavior. Here we introduced this protein engineering strategy to two regulators in the TetR family: TetR (UniProt Accession ID: P04483) and MphR (Q9EVJ6). The TetR DNA-binding module and the MphR ligand-binding module were used to create the TetR-MphR. This resulting hybrid regulator possesses DNA-binding properties of TetR and ligand response properties of MphR, which is able to control gene expression in response to a molecular signal in cells. Furthermore, we studied molecular interactions between the TetR DNA-binding module and MphR ligand-binding module by using mutant analysis. Together, we demonstrated that TetR family regulators contain discrete and functional modules that can be used to build biological components with novel properties. This work highlights the utility of rational design as a means of creating modular parts for cell engineering and introduces new possibilities in rewiring cellular response pathways.

Engineering repressors with coevolutionary cues facilitates toggle switches with a master reset

Engineering allosteric transcriptional repressors containing an environmental sensing module (ESM) and a DNA recognition module (DRM) has the potential to unlock a combinatorial set of rationally designed biological responses. We demonstrated that constructing hybrid repressors by fusing distinct ESMs and DRMs provides a means to flexibly rewire genetic networks for complex signal processing. We have used coevolutionary traits among LacI homologs to develop a model for predicting compatibility between ESMs and DRMs. Our predictions accurately agree with the performance of 40 engineered repressors. We have harnessed this framework to develop a system of multiple toggle switches with a master OFF signal that produces a unique behavior: each engineered biological activity is switched to a stable ON state by different chemicals and returned to OFF in response to a common signal. One promising application of this design is to develop living diagnostics for monitoring multiple parameters in complex physiological environments and it represents one of many circuit topologies that can be explored with modular repressors designed with coevolutionary information.

Rewiring bacterial two-component systems by modular DNA-binding domain swapping

Two-component systems (TCSs) are the largest family of multi-step signal transduction pathways and valuable sensors for synthetic biology. However, most TCSs remain uncharacterized or difficult to harness for applications. Major challenges are that many TCS output promoters are unknown, subject to cross-regulation, or silent in heterologous hosts. Here, we demonstrate that the two largest families of response regulator DNA-binding domains can be interchanged with remarkable flexibility, enabling the corresponding TCSs to be rewired to synthetic output promoters. We exploit this plasticity to eliminate cross-regulation, un-silence a gram-negative TCS in a gram-positive host, and engineer a system with over 1,300-fold activation. Finally, we apply DNA-binding domain swapping to screen uncharacterized Shewanella oneidensis TCSs in Escherichia coli, leading to the discovery of a previously uncharacterized pH sensor. This work should accelerate fundamental TCS studies and enable the engineering of a large family of genetically encoded sensors with diverse applications.

Designing bacterial signaling interactions with coevolutionary landscapes

Selecting amino acids to design novel protein-protein interactions that facilitate catalysis is a daunting challenge. We propose that a computational coevolutionary landscape based on sequence analysis alone offers a major advantage over expensive, time-consuming brute-force approaches currently employed. Our coevolutionary landscape allows prediction of single amino acid substitutions that produce functional interactions between non-cognate, interspecies signaling partners. In addition, it can also predict mutations that maintain segregation of signaling pathways across species. Specifically, predictions of phosphotransfer activity between the Escherichia coli histidine kinase EnvZ to the non-cognate receiver Spo0F from Bacillus subtilis were compiled. Twelve mutations designed to enhance, suppress, or have a neutral effect on kinase phosphotransfer activity to a non-cognate partner were selected. We experimentally tested the ability of the kinase to relay phosphate to the respective designed Spo0F receiver proteins against the theoretical predictions. Our key finding is that the coevolutionary landscape theory, with limited structural data, can significantly reduce the search-space for successful prediction of single amino acid substitutions that modulate phosphotransfer between the two-component His-Asp relay partners in a predicted fashion. This combined approach offers significant improvements over large-scale mutations studies currently used for protein engineering and design.

Core signalling motif displaying multistability through multi-state enzymes

Bistability, and more generally multistability, is a key system dynamics feature enabling decision-making and memory in cells. Deciphering the molecular determinants of multistability is thus crucial for a better understanding of cellular pathways and their (re)engineering in synthetic biology. Here, we show that a key motif found predominantly in eukaryotic signalling systems, namely a futile signalling cycle, can display bistability when featuring a two-state kinase. We provide necessary and sufficient mathematical conditions on the kinetic parameters of this motif that guarantee the existence of multiple steady states. These conditions foster the intuition that bistability arises as a consequence of competition between the two states of the kinase. Extending from this result, we find that increasing the number of kinase states linearly translates into an increase in the number of steady states in the system. These findings reveal, to our knowledge, a new mechanism for the generation of bistability and multistability in cellular signalling systems. Further the futile cycle featuring a two-state kinase is among the smallest bistable signalling motifs. We show that multi-state kinases and the described competition-based motif are part of several natural signalling systems and thereby could enable them to implement complex information processing through multistability. These results indicate that multi-state kinases in signalling systems are readily exploited by natural evolution and could equally be used by synthetic approaches for the generation of multistable information processing systems at the cellular level.

A Visual Language for Protein Design

As protein engineering becomes more sophisticated, practitioners increasingly need to share diagrams for communicating protein designs. To this end, we present a draft visual language, Protein Language, that describes the high-level architecture of an engineered protein with easy-to-draw glyphs, intended to be compatible with other biological diagram languages such as SBOL Visual and SBGN. Protein Language consists of glyphs for representing important features (e.g., globular domains, recognition and localization sequences, sites of covalent modification, cleavage and catalysis), rules for composing these glyphs to represent complex architectures, and rules constraining the scaling and styling of diagrams. To support Protein Language we have implemented an extensible web-based software diagram tool, Protein Designer, that uses Protein Language in a "drag and drop" interface for visualization and computer-aided-design of engineered proteins, as well as conversion of annotated protein sequences to Protein Language diagrams and figure export. Protein Designer can be accessed at http://biocad.ncl.ac.uk/protein-designer/ .

Mycobacterium tuberculosis universal stress protein Rv2623 interacts with the putative ATP binding cassette (ABC) transporter Rv1747 to regulate mycobacterial growth

We have previously shown that the Mycobacterium tuberculosis universal stress protein Rv2623 regulates mycobacterial growth and may be required for the establishment of tuberculous persistence. Here, yeast two-hybrid and affinity chromatography experiments have demonstrated that Rv2623 interacts with one of the two forkhead-associated domains (FHA I) of Rv1747, a putative ATP-binding cassette transporter annotated to export lipooligosaccharides. FHA domains are signaling protein modules that mediate protein-protein interactions to modulate a wide variety of biological processes via binding to conserved phosphorylated threonine (pT)-containing oligopeptides of the interactors. Biochemical, immunochemical and mass spectrometric studies have shown that Rv2623 harbors pT and specifically identified threonine 237 as a phosphorylated residue. Relative to wild-type Rv2623 (Rv2623WT), a mutant protein in which T237 has been replaced with a non-phosphorylatable alanine (Rv2623T237A) exhibits decreased interaction with the Rv1747 FHA I domain and diminished growth-regulatory capacity. Interestingly, compared to WT bacilli, an M. tuberculosis Rv2623 null mutant (ΔRv2623) displays enhanced expression of phosphatidyl-myo-inositol mannosides (PIMs), while the ΔRv1747 mutant expresses decreased levels of PIMs. Animal studies have previously shown that ΔRv2623 is hypervirulent, while ΔRv1747 is growth-attenuated. Collectively, these data have provided evidence that Rv2623 interacts with Rv1747 to regulate mycobacterial growth; and this interaction is mediated via the recognition of the conserved Rv2623 pT237-containing FHA-binding motif by the Rv1747 FHA I domain. The divergent aberrant PIM profiles and the opposing in vivo growth phenotypes of ΔRv2623 and ΔRv1747, together with the annotated lipooligosaccharide exporter function of Rv1747, suggest that Rv2623 interacts with Rv1747 to modulate mycobacterial growth by negatively regulating the activity of Rv1747; and that Rv1747 might function as a transporter of PIMs. Because these glycolipids are major mycobacterial cell envelope components that can impact on the immune response, our findings raise the possibility that Rv2623 may regulate bacterial growth, virulence, and entry into persistence, at least in part, by modulating the levels of bacillary PIM expression, perhaps through negatively regulating the Rv1747-dependent export of the immunomodulatory PIMs to alter host-pathogen interaction, thereby influencing the fate of M. tuberculosis in vivo.

An operational view of intercellular signaling pathways

Animal cells use a conserved repertoire of intercellular signaling pathways to communicate with one another. These pathways are well-studied from a molecular point of view. However, we often lack an "operational" understanding that would allow us to use these pathways to rationally control cellular behaviors. This requires knowing what dynamic input features each pathway perceives and how it processes those inputs to control downstream processes. To address these questions, researchers have begun to reconstitute signaling pathways in living cells, analyzing their dynamic responses to stimuli, and developing new functional representations of their behavior. Here we review important insights obtained through these new approaches, and discuss challenges and opportunities in understanding signaling pathways from an operational point of view.

Synthetic Protein Switches: Theoretical and Experimental Considerations

Synthetic protein switches with tailored response functions are finding increasing applications as tools in basic research and biotechnology. With a number of successful design strategies emerging, the construction of synthetic protein switches still frequently necessitates an integrated approach that combines detailed biochemical and biophysical characterization in combination with high-throughput screening to construct tailored synthetic protein switches. This is increasingly complemented by computational strategies that aim to reduce the need for costly empirical optimization and thus facilitate the protein design process. Successful computational design approaches range from analyzing phylogenetic data to infer useful structural, biophysical, and biochemical information to modeling the structure and function of proteins ab initio. The following chapter provides an overview over the theoretical considerations and experimental approaches that have been successful applied in the construction of synthetic protein switches.

Using Sub-Network Combinations to Scale Up an Enumeration Method for Determining the Network Structures of Biological Functions

Deduction of biological regulatory networks from their functions is one of the focus areas of systems biology. Among the different techniques used in this reverse-engineering task, one powerful method is to enumerate all candidate network structures to find suitable ones. However, this method is severely limited by calculation capability: due to the brute-force approach, it is infeasible for networks with large number of nodes to be studied using traditional enumeration method because of the combinatorial explosion. In this study, we propose a new reverse-engineering technique based on the enumerating method: sub-network combinations. First, a complex biological function is divided into several sub-functions. Next, the three-node-network enumerating method is applied to search for sub-networks that are able to realize each of the sub-functions. Finally, complex whole networks are constructed by enumerating all possible combinations of sub-networks. The optimal ones are selected and analyzed. To demonstrate the effectiveness of this new method, we used it to deduct the network structures of a Pavlovian-like function. The whole Pavlovian-like network was successfully constructed by combining robust sub-networks, and the results were analyzed. With sub-network combination, the complexity has been largely reduced. Our method also provides a functional modular view of biological systems.

Synthetic Lipid-Containing Scaffolds Enhance Production by Colocalizing Enzymes

Subcellular organization is critical for isolating, concentrating, and protecting biological activities. Natural subcellular organization is often achieved using colocalization of proteins on scaffold molecules, thereby enhancing metabolic fluxes and enabling coregulation. Synthetic scaffolds extend these benefits to new biological processes and are typically constructed from proteins or nucleic acids. To expand the range of available building materials, we use a minimal set of components from the lipid-encapsulated bacteriophage ϕ6 to form synthetic lipid-containing scaffolds (SLSs) in E. coli. Analysis of diffusive behavior by particle tracking in live cells indicates that SLSs are >20 nm in diameter; furthermore, density measurements demonstrate that SLSs contain a mixture of lipids and proteins. The fluorescent proteins mCitrine and mCerulean can be colocalized to SLSs. To test for effects on enzymatic production, we localized two enzymes involved in indigo biosynthesis to SLSs. We observed a scaffold-dependent increase in indigo production, showing that SLSs can enhance the production of a commercially relevant metabolite.

Connecting the Sequence-Space of Bacterial Signaling Proteins to Phenotypes Using Coevolutionary Landscapes

Two-component signaling (TCS) is the primary means by which bacteria sense and respond to the environment. TCS involves two partner proteins working in tandem, which interact to perform cellular functions whereas limiting interactions with non-partners (i.e., cross-talk). We construct a Potts model for TCS that can quantitatively predict how mutating amino acid identities affect the interaction between TCS partners and non-partners. The parameters of this model are inferred directly from protein sequence data. This approach drastically reduces the computational complexity of exploring the sequence-space of TCS proteins. As a stringent test, we compare its predictions to a recent comprehensive mutational study, which characterized the functionality of 20⁴ mutational variants of the PhoQ kinase in Escherichia coli We find that our best predictions accurately reproduce the amino acid combinations found in experiment, which enable functional signaling with its partner PhoP. These predictions demonstrate the evolutionary pressure to preserve the interaction between TCS partners as well as prevent unwanted cross-talk. Further, we calculate the mutational change in the binding affinity between PhoQ and PhoP, providing an estimate to the amount of destabilization needed to disrupt TCS.

Rewiring MAP kinases in Saccharomyces cerevisiae to regulate novel targets through ubiquitination

Evolution has often copied and repurposed the mitogen-activated protein kinase (MAPK) signaling module. Understanding how connections form during evolution, in disease and across individuals requires knowledge of the basic tenets that govern kinase-substrate interactions. We identify criteria sufficient for establishing regulatory links between a MAPK and a non-native substrate. The yeast MAPK Fus3 and human MAPK ERK2 can be functionally redirected if only two conditions are met: the kinase and substrate contain matching interaction domains and the substrate includes a phospho-motif that can be phosphorylated by the kinase and recruit a downstream effector. We used a panel of interaction domains and phosphorylation-activated degradation motifs to demonstrate modular and scalable retargeting. We applied our approach to reshape the signaling behavior of an existing kinase pathway. Together, our results demonstrate that a MAPK can be largely defined by its interaction domains and compatible phospho-motifs and provide insight into how MAPK-substrate connections form.

DOI:http://dx.doi.org/10.7554/eLife.15200.001

Nature has evolved a number of ways to link signals from a cell’s environment, like the concentration of a hormone, to the behavior of that cell. These new connections often form by reusing certain common signaling components, such as mitogen-activated protein kinases. These enzymes – referred to as MAPKs for short – are activated by specific signals and alter the activity of target proteins in the cell by adding a phosphate group to them: a process called phosphorylation. These connections thus dictate how cells respond to their environments – and consequently, disruptions to the connections are a common source of disease.

Groves, Khakhar et al. set out to understand how connections can be made between a MAPK and a new target protein to gain insights into how these links emerge through evolution and how they might break in disease. Their approach focused on one of the ways that phosphorylation can alter the activity of a target protein: marking it for degradation. Experiments with budding yeast showed that a MAPK could only achieve this if two conditions are met. First, the target protein and kinase need to bind to each other. Second, the target needs to contain a site that when phosphorylated is subsequently recognized by the cell’s protein degradation machinery.

By engineering proteins so that they fulfilled these two criteria, Groves, Khakhar et al. created new connections between a yeast MAPK called Fus3 or a human MAPK called ERK2 and a variety of targets. The results showed that the parts of the proteins involved in the interaction step could be completely separate from the parts that are involved in the phosphorylation step. This suggests that connections between kinases and their targets can be rewired simple by mixing together parts of other existing proteins. Finally, Groves, Khakhar et al. confirmed that engineered connections between kinases and targets could predictably change how yeast cells responded to a hormone that normally controls the yeast’s reproductive cycle.

Together these results bring us one step closer to understanding how cells assemble the signaling pathways that they use to process information. However further work is needed to see if these findings can be generalized to other signaling components, and if so, to explore if new connections can be built to yield more complicated cellular behaviors.

DOI:http://dx.doi.org/10.7554/eLife.15200.002

Protein Calligraphy: A New Concept Begins To Take Shape

The ability to assemble molecules into supramolecular architectures of controllable size and symmetry is a long sought after goal of nanotechnology and material engineering. Proteins are particularly attractive for molecular assembly due to their inherent molecular recognition and self-assembly capabilities. Advances in the computational prediction of protein folding and quaternary assembly have enabled the design of proteins that self-assemble into complex yet predictable shapes. These protein nanostructures are opening new possibilities in biomaterials, metabolic engineering, molecular delivery, tissue engineering, and a plethora of nanomaterials. Images of protein constructs assembled from simpler structures draw comparison to characters of calligraphy. In both cases, elaborate designs emerge from basic subunits, resulting in the translation of form into function with a high degree of artistry.

Molecular Buffers Permit Sensitivity Tuning and Inversion of Riboswitch Signals

Predictable integration of foreign biological signals and parts remains a key challenge in the systematic engineering of synthetic cellular actuations, and general methods to improve signal transduction and sensitivity are needed. To address this problem we modeled and built a molecular signal buffer network in Saccharomyces cerevisiae inspired by chemical pH buffer systems. The molecular buffer system context-insulates a riboswitch enabling synthetic control of colony formation and modular signal manipulations. The riboswitch signal is relayed to a transcriptional activation domain of a split transcription factor, while interacting DNA-binding domains mediate the transduction of signal and form an interacting molecular buffer. The molecular buffer system enables modular signal inversion through integration with repressor modules. Further, tuning of input sensitivity was achieved through perturbation of the buffer pair ratio guided by a mathematical model. Such buffered signal tuning networks will be useful for domestication of RNA-based sensors enabling tunable outputs and library-wide selections for drug discovery and metabolic engineering.

Enzyme Sequestration as a Tuning Point in Controlling Response Dynamics of Signalling Networks

Signalling networks result from combinatorial interactions among many enzymes and scaffolding proteins. These complex systems generate response dynamics that are often essential for correct decision-making in cells. Uncovering biochemical design principles that underpin such response dynamics is a prerequisite to understand evolved signalling networks and to design synthetic ones. Here, we use in silico evolution to explore the possible biochemical design space for signalling networks displaying ultrasensitive and adaptive response dynamics. By running evolutionary simulations mimicking different biochemical scenarios, we find that enzyme sequestration emerges as a key mechanism for enabling such dynamics. Inspired by these findings, and to test the role of sequestration, we design a generic, minimalist model of a signalling cycle, featuring two enzymes and a single scaffolding protein. We show that this simple system is capable of displaying both ultrasensitive and adaptive response dynamics. Furthermore, we find that tuning the concentration or kinetics of the sequestering protein can shift system dynamics between these two response types. These empirical results suggest that enzyme sequestration through scaffolding proteins is exploited by evolution to generate diverse response dynamics in signalling networks and could provide an engineering point in synthetic biology applications.

Genetic circuit design automation

Computation can be performed in living cells by DNA-encoded circuits that process sensory information and control biological functions. Their construction is time-intensive, requiring manual part assembly and balancing of regulator expression. We describe a design environment, Cello, in which a user writes Verilog code that is automatically transformed into a DNA sequence. Algorithms build a circuit diagram, assign and connect gates, and simulate performance. Reliable circuit design requires the insulation of gates from genetic context, so that they function identically when used in different circuits. We used Cello to design 60 circuits forEscherichia coli(880,000 base pairs of DNA), for which each DNA sequence was built as predicted by the software with no additional tuning. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts), and across all circuits 92% of the output states functioned as predicted. Design automation simplifies the incorporation of genetic circuits into biotechnology projects that require decision-making, control, sensing, or spatial organization.

Unlimited multistability and Boolean logic in microbial signalling

The ability to map environmental signals onto distinct internal physiological states or programmes is critical for single-celled microbes. A crucial systems dynamics feature underpinning such ability is multistability. While unlimited multistability is known to arise from multi-site phosphorylation seen in the signalling networks of eukaryotic cells, a similarly universal mechanism has not been identified in microbial signalling systems. These systems are generally known as two-component systems comprising histidine kinase (HK) receptors and response regulator proteins engaging in phosphotransfer reactions. We develop a mathematical framework for analysing microbial systems with multi-domain HK receptors known as hybrid and unorthodox HKs. We show that these systems embed a simple core network that exhibits multistability, thereby unveiling a novel biochemical mechanism for multistability. We further prove that sharing of downstream components allows a system with n multi-domain hybrid HKs to attain 3n steady states. We find that such systems, when sensing distinct signals, can readily implement Boolean logic functions on these signals. Using two experimentally studied examples of two-component systems implementing hybrid HKs, we show that bistability and implementation of logic functions are possible under biologically feasible reaction rates. Furthermore, we show that all sequenced microbial genomes contain significant numbers of hybrid and unorthodox HKs, and some genomes have a larger fraction of these proteins compared with regular HKs. Microbial cells are thus theoretically unbounded in mapping distinct environmental signals onto distinct physiological states and perform complex computations on them. These findings facilitate the understanding of natural two-component systems and allow their engineering through synthetic biology.

Design of Protein-Peptide Interaction Modules for Assembling Supramolecular Structures in Vivo and in Vitro

Synthetic biology and protein origami both require protein building blocks that behave in a reliable, predictable fashion. In particular, we require protein interaction modules with known specificity and affinity. Here, we describe three designed TRAP (Tetratricopeptide Repeat Affinity Protein)-peptide interaction pairs that are functional in vivo. We show that each TRAP binds to its cognate peptide and exhibits low cross-reactivity with the peptides bound by the other TRAPs. In addition, we demonstrate that the TRAP-peptide interactions are functional in many cellular contexts. In extensions of these designs, we show that the binding affinity of a TRAP-peptide pair can be systematically varied. The TRAP-peptide pairs we present thus represent a powerful set of new building blocks that are suitable for a variety of applications.

Simple synthetic protein scaffolds can create adjustable artificial MAPK circuits in yeast and mammalian cells

As hubs for eukaryotic cell signaling, scaffold proteins are attractive targets for engineering and manipulating signaling circuits. We designed synthetic scaffolds with a repeated PDZ domain that interacted with engineered kinases of the mitogen-activated protein kinase (MAPK) cascade involved in yeast mating to investigate how modular interactions mediate kinase cascades. The synthetic scaffolds functioned as logic gates of signaling circuits. We replaced the endogenous yeast scaffold Ste5 with designer scaffolds with a variable numbers of a PDZ domain that bound kinases or phosphatases engineered with a PDZ-binding motif. Although association with the membrane was necessary for pathway activity, surprisingly, mating responses occurred when the circuit contained a scaffold with only two PDZ domains, which could only bind two of the three kinases simultaneously. Additionally, the three tiers of the MAPK pathway exhibited decreasing positional plasticity from the top [MAPK kinase kinase (MAPKKK)] to the bottom (MAPK) tier such that binding of a MAPKKK, but not a MAPK, from the osmoregulatory pathway or protein kinase C pathway to the synthetic scaffold activated a reporter of the mating response. We also showed that the output duration and intensity could be altered by recruiting phosphatases or varying the affinity of the recruited proteins for the scaffold and that a designer MAPK scaffold functioned in mammalian cells. Thus, this synthetic approach with designer scaffolds should enable the rational manipulation or engineering of signaling pathways and provide insight into the functional roles of scaffold proteins.

Evolution of synthetic signaling scaffolds by recombination of modular protein domains

Signaling scaffolds are proteins that interact via modular domains with multiple partners, regulating signaling networks in space and time and providing an ideal platform from which to alter signaling functions. However, to better exploit scaffolds for signaling engineering, it is necessary to understand the full extent of their modularity. We used a directed evolution approach to identify, from a large library of randomly shuffled protein interaction domains, variants capable of rescuing the signaling defect of a yeast strain in which Ste5, the scaffold in the mating pathway, had been deleted. After a single round of selection, we identified multiple synthetic scaffold variants with diverse domain architectures, able to mediate mating pathway activation in a pheromone-dependent manner. The facility with which this signaling network accommodates changes in scaffold architecture suggests that the mating signaling complex does not possess a single, precisely defined geometry into which the scaffold has to fit. These relaxed geometric constraints may facilitate the evolution of signaling networks, as well as their engineering for applications in synthetic biology.

Synthetic tunable amplifying buffer circuit in E. coli

While predictable design of a genetic circuit's output is a major goal of synthetic biology, it remains a significant challenge because DNA binding sites in the cell affect the concentration of available transcription factors (TF). To mitigate this problem, we propose to use a TF that results from the (reversible) phosphorylation of protein substrate as a circuit's output. We demonstrate that by comparatively increasing the amounts of substrate and phosphatase, the TF concentration becomes robust to the presence of DNA binding sites and can be kept at a desired value. The circuit's input/output gain can, in turn, be tuned by changing the relative amounts of the substrate and phosphatase, realizing an amplifying buffer circuit with tunable gain. In our experiments in E. coli, we employ phospho-NRI as the output TF, phosphorylated by the NRII kinase, and dephosphorylated by the NRII phosphatase. Amplifying buffer circuits such as ours could be used to insulate a circuit's output from the context, bringing synthetic biology one step closer to modular design.

Avoidance of truncated proteins from unintended ribosome binding sites within heterologous protein coding sequences

Genetic sequences ported into non-native hosts for synthetic biology applications can gain unexpected properties. In this study, we explored sequences functioning as ribosome binding sites (RBSs) within protein coding DNA sequences (CDSs) that cause internal translation, resulting in truncated proteins. Genome-wide prediction of bacterial RBSs, based on biophysical calculations employed by the RBS calculator, suggests a selection against internal RBSs within CDSs in Escherichia coli, but not those in Saccharomyces cerevisiae. Based on these calculations, silent mutations aimed at removing internal RBSs can effectively reduce truncation products from internal translation. However, a solution for complete elimination of internal translation initiation is not always feasible due to constraints of available coding sequences. Fluorescence assays and Western blot analysis showed that in genes with internal RBSs, increasing the strength of the intended upstream RBS had little influence on the internal translation strength. Another strategy to minimize truncated products from an internal RBS is to increase the relative strength of the upstream RBS with a concomitant reduction in promoter strength to achieve the same protein expression level. Unfortunately, lower transcription levels result in increased noise at the single cell level due to stochasticity in gene expression. At the low expression regimes desired for many synthetic biology applications, this problem becomes particularly pronounced. We found that balancing promoter strengths and upstream RBS strengths to intermediate levels can achieve the target protein concentration while avoiding both excessive noise and truncated protein.

Using synthetic RNAs as scaffolds and regulators

The natural versatility of RNA makes it an ideal substrate for bioengineering. Its structural properties and predictable base-pairing permit its use as molecular scaffold, and its ability to interact with nucleic acids, proteins and small molecules confers a regulatory potential that can be harvested to design RNA regulators in diverse contexts.

Design and implementation of a biomolecular concentration tracker

As a field, synthetic biology strives to engineer increasingly complex artificial systems in living cells. Active feedback in closed loop systems offers a dynamic and adaptive way to ensure constant relative activity independent of intrinsic and extrinsic noise. In this work, we use synthetic protein scaffolds as a modular and tunable mechanism for concentration tracking through negative feedback. Input to the circuit initiates scaffold production, leading to colocalization of a two-component system and resulting in the production of an inhibitory antiscaffold protein. Using a combination of modeling and experimental work, we show that the biomolecular concentration tracker circuit achieves dynamic protein concentration tracking in Escherichia coli and that steady state outputs can be tuned.