Using engineered scaffold interactions to reshape MAP kinase pathway signaling dynamics

Epigenetic control of pheromone MAPK signaling determines sexual fecundity in Candida albicans

Several pathogenic Candida species are capable of heritable and reversible switching between two epigenetic states, "white" and "opaque." In Candida albicans, white cells are essentially sterile, whereas opaque cells are mating-proficient. Here, we interrogate the mechanism by which the white-opaque switch regulates sexual fecundity and identify four genes in the pheromone MAPK pathway that are expressed at significantly higher levels in opaque cells than in white cells. These genes encode the β subunit of the G-protein complex (STE4), the pheromone MAPK scaffold (CST5), and the two terminal MAP kinases (CEK1/CEK2). To define the contribution of each factor to mating, C. albicans white cells were reverse-engineered to express elevated, opaque-like levels of these factors, either singly or in combination. We show that white cells co-overexpressing STE4, CST5, and CEK2 undergo mating four orders of magnitude more efficiently than control white cells and at a frequency approaching that of opaque cells. Moreover, engineered white cells recapitulate the transcriptional and morphological responses of opaque cells to pheromone. These results therefore reveal multiple bottlenecks in pheromone MAPK signaling in white cells and that alleviation of these bottlenecks enables efficient mating by these "sterile" cell types. Taken together, our findings establish that differential expression of several MAPK factors underlies the epigenetic control of mating in C. albicans We also discuss how fitness advantages could have driven the evolution of a toggle switch to regulate sexual reproduction in pathogenic Candida species.

Regulation of ASK1 signaling by scaffold and adaptor proteins

The mitogen-activated protein kinase (MAPK) signaling pathway is a three-tiered kinase cascade where mitogen-activated protein kinase kinase kinases (MAP3Ks) lead to the activation of mitogen-activated protein kinase kinases (MAP2K), and ultimately MAPK proteins. MAPK signaling can promote a diverse set of biological outcomes, ranging from cell death to proliferation. There are multiple mechanisms which govern MAPK output, such as the duration and strength of the signal, cellular localization to upstream and downstream binding partners, pathway crosstalk and the binding to scaffold and adaptor molecules. This review will focus on scaffold and adaptor proteins that bind to and regulate apoptosis signal-regulating kinase 1 (ASK1), a MAP3K protein with a critical role in mediating stress response pathways.

The directed evolution of ligand specificity in a GPCR and the unequal contributions of efficacy and affinity

G protein-coupled receptors (GPCRs) must discriminate between hundreds of related signal molecules. In order to better understand how GPCR specificity can arise from a common promiscuous ancestor, we used laboratory evolution to invert the specificity of the Saccharomyces cerevisiae mating receptor Ste2. This GPCR normally responds weakly to the pheromone of the related species Kluyveromyces lactis, though we previously showed that mutation N216S is sufficient to make this receptor promiscuous. Here, we found that three additional substitutions, A265T, Y266F and P290Q, can act together to confer a novel specificity for K. lactis pheromone. Unlike wild-type Ste2, this new variant does not rely on differences in binding affinity to discriminate against its non-preferred ligand. Instead, the mutation P290Q is critical for suppressing the efficacy of the native pheromone. These two alternative methods of ligand discrimination were mapped to specific amino acid positions on the peptide pheromones. Our work demonstrates that changes in ligand efficacy can drive changes in GPCR specificity, thus obviating the need for extensive binding pocket re-modeling.

Design of Tunable Oscillatory Dynamics in a Synthetic NF-κB Signaling Circuit

Although oscillatory circuits are prevalent in transcriptional regulation, it is unclear how a circuit's structure and the specific parameters that describe its components determine the shape of its oscillations. Here, we engineer a minimal, inducible human nuclear factor κB (NF-κB)-based system that is composed of NF-κB (RelA) and degradable inhibitor of NF-κB (IκBα), into the yeast, Saccharomyces cerevisiae. We define an oscillation's waveform quantitatively as a function of signal amplitude, rest time, rise time, and decay time; by systematically tuning RelA concentration, the strength of negative feedback, and the degradation rate of IκBα, we demonstrate that peak shape and frequency of oscillations can be controlled in vivo and predicted mathematically. In addition, we show that nested negative feedback loops can be employed to specifically tune the frequency of oscillations while leaving their peak shape unchanged. In total, this work establishes design principles that enable function-guided design of oscillatory signaling controllers in diverse synthetic biology applications.

Synthetic Gene Expression Circuits for Designing Precision Tools in Oncology

Precision medicine in oncology needs to enhance its capabilities to match diagnostic and therapeutic technologies to individual patients. Synthetic biology streamlines the design and construction of functionalized devices through standardization and rational engineering of basic biological elements decoupled from their natural context. Remarkable improvements have opened the prospects for the availability of synthetic devices of enhanced mechanism clarity, robustness, sensitivity, as well as scalability and portability, which might bring new capabilities in precision cancer medicine implementations. In this review, we begin by presenting a brief overview of some of the major advances in the engineering of synthetic genetic circuits aimed to the control of gene expression and operating at the transcriptional, post-transcriptional/translational, and post-translational levels. We then focus on engineering synthetic circuits as an enabling methodology for the successful establishment of precision technologies in oncology. We describe significant advancements in our capabilities to tailor synthetic genetic circuits to specific applications in tumor diagnosis, tumor cell- and gene-based therapy, and drug delivery.

Complex cellular logic computation using ribocomputing devices

Synthetic biology aims to develop engineering-driven approaches to the programming of cellular functions that could yield transformative technologies. Synthetic gene circuits that combine DNA, protein, and RNA components have demonstrated a range of functions such as bistability, oscillation, feedback, and logic capabilities. However, it remains challenging to scale up these circuits owing to the limited number of designable, orthogonal, high-performance parts, the empirical and often tedious composition rules, and the requirements for substantial resources for encoding and operation. Here, we report a strategy for constructing RNA-only nanodevices to evaluate complex logic in living cells. Our 'ribocomputing' systems are composed of de-novo-designed parts and operate through predictable and designable base-pairing rules, allowing the effective in silico design of computing devices with prescribed configurations and functions in complex cellular environments. These devices operate at the post-transcriptional level and use an extended RNA transcript to co-localize all circuit sensing, computation, signal transduction, and output elements in the same self-assembled molecular complex, which reduces diffusion-mediated signal losses, lowers metabolic cost, and improves circuit reliability. We demonstrate that ribocomputing devices in Escherichia coli can evaluate two-input logic with a dynamic range up to 900-fold and scale them to four-input AND, six-input OR, and a complex 12-input expression (A1 AND A2 AND NOT A1*) OR (B1 AND B2 AND NOT B2*) OR (C1 AND C2) OR (D1 AND D2) OR (E1 AND E2). Successful operation of ribocomputing devices based on programmable RNA interactions suggests that systems employing the same design principles could be implemented in other host organisms or in extracellular settings.

The Principles of Engineering Immune Cells to Treat Cancer

Chimeric antigen receptor (CAR) T cells have proven that engineered immune cells can serve as a powerful new class of cancer therapeutics. Clinical experience has helped to define the major challenges that must be met to make engineered T cells a reliable, safe, and effective platform that can be deployed against a broad range of tumors. The emergence of synthetic biology approaches for cellular engineering is providing us with a broadly expanded set of tools for programming immune cells. We discuss how these tools could be used to design the next generation of smart T cell precision therapeutics.

Fundamental trade-offs between information flow in single cells and cellular populations

Signal transduction networks allow eukaryotic cells to make decisions based on information about intracellular state and the environment. Biochemical noise significantly diminishes the fidelity of signaling: networks examined to date seem to transmit less than 1 bit of information. It is unclear how networks that control critical cell-fate decisions (e.g., cell division and apoptosis) can function with such low levels of information transfer. Here, we use theory, experiments, and numerical analysis to demonstrate an inherent trade-off between the information transferred in individual cells and the information available to control population-level responses. Noise in receptor-mediated apoptosis reduces information transfer to approximately 1 bit at the single-cell level but allows 3-4 bits of information to be transmitted at the population level. For processes such as eukaryotic chemotaxis, in which single cells are the functional unit, we find high levels of information transmission at a single-cell level. Thus, low levels of information transfer are unlikely to represent a physical limit. Instead, we propose that signaling networks exploit noise at the single-cell level to increase population-level information transfer, allowing extracellular ligands, whose levels are also subject to noise, to incrementally regulate phenotypic changes. This is particularly critical for discrete changes in fate (e.g., life vs. death) for which the key variable is the fraction of cells engaged. Our findings provide a framework for rationalizing the high levels of noise in metazoan signaling networks and have implications for the development of drugs that target these networks in the treatment of cancer and other diseases.

Introduction of Premature Stop Codons as an Evolutionary Strategy To Rescue Signaling Network Function

The cellular concentrations of key components of signaling networks are tightly regulated, as deviations from their optimal ranges can have negative effects on signaling function. For example, overexpression of the yeast mating pathway mitogen-activated protein kinase (MAPK) Fus3 decreases pathway output, in part by sequestering individual components away from functional multiprotein complexes. Using a synthetic biology approach, we investigated potential mechanisms by which selection could compensate for a decrease in signaling activity caused by overexpression of Fus3. We overexpressed a library of random mutants of Fus3 and used cell sorting to select variants that rescued mating pathway activity. Our results uncovered that one remarkable way in which selection can compensate for protein overexpression is by introducing premature stop codons at permitted positions. Because of the low efficiency with which premature stop codons are read through, the resulting cellular concentration of active Fus3 returns to values within the range required for proper signaling. Our results underscore the importance of interpreting genotypic variation at the systems rather than at the individual gene level, as mutations can have opposite effects on protein and network function.

A Model of a Synthetic Biological Communication Interface between Mammalian Cells and Mechatronic Systems

The creation of communication interfaces between abiotic and biotic systems represents a significant research challenge. In this work, we design and model a system linking the biochemical signaling pathways of mammalian cells to the actions of a mobile robotic prosthesis. We envision this system as a robotic platform carrying an optically monitored bioreactor that harbors mammalian cells. The cellular, optical signal is captured by an onboard fluorescent microscope and converted into an electronic signal. We first present a design for the overall cell-robot system, with a specific focus on the design of the synthetic gene networks needed for the system. We use these synthetic networks to encode motion commands within the cell's endogenous, oscillatory calcium signaling pathways. We then describe a potential system whereby this oscillatory signal could be outputted and monitored as a change in cellular fluorescence. Next, we use the changes resulting from the synthetic biological modifications as new parameters in a simulation of a well-established mathematical model for intracellular calcium signaling. The resulting signal is processed in the frequency domain, with specific frequencies activating cognate robot motion subroutines.

Identifying ultrasensitive HGF dose-response functions in a 3D mammalian system for synthetic morphogenesis

Nonlinear responses to signals are widespread natural phenomena that affect various cellular processes. Nonlinearity can be a desirable characteristic for engineering living organisms because it can lead to more switch-like responses, similar to those underlying the wiring in electronics. Steeper functions are described as ultrasensitive, and can be applied in synthetic biology by using various techniques including receptor decoys, multiple co-operative binding sites, and sequential positive feedbacks. Here, we explore the inherent non-linearity of a biological signaling system to identify functions that can potentially be exploited using cell genome engineering. For this, we performed genome-wide transcription profiling to identify genes with ultrasensitive response functions to Hepatocyte Growth Factor (HGF). We identified 3,527 genes that react to increasing concentrations of HGF, in Madin-Darby canine kidney (MDCK) cells, grown as cysts in 3D collagen cell culture. By fitting a generic Hill function to the dose-responses of these genes we obtained a measure of the ultrasensitivity of HGF-responsive genes, identifying a subset with higher apparent Hill coefficients (e.g. MMP1, TIMP1, SNORD75, SNORD86 and ERRFI1). The regulatory regions of these genes are potential candidates for future engineering of synthetic mammalian gene circuits requiring nonlinear responses to HGF signalling.

The Saccharomyces cerevisiae pheromone-response is a metabolically active stationary phase for bio-production

The growth characteristics and underlying metabolism of microbial production hosts are critical to the productivity of metabolically engineered pathways. Production in parallel with growth often leads to biomass/bio-product competition for carbon. The growth arrest phenotype associated with the Saccharomyces cerevisiae pheromone-response is potentially an attractive production phase because it offers the possibility of decoupling production from population growth. However, little is known about the metabolic phenotype associated with the pheromone-response, which has not been tested for suitability as a production phase. Analysis of extracellular metabolite fluxes, available transcriptomic data, and heterologous compound production (para-hydroxybenzoic acid) demonstrate that a highly active and distinct metabolism underlies the pheromone-response. These results indicate that the pheromone-response is a suitable production phase, and that it may be useful for informing synthetic biology design principles for engineering productive stationary phase phenotypes.

Engineering dynamical control of cell fate switching using synthetic phospho-regulons

Many cells can sense and respond to time-varying stimuli, selectively triggering changes in cell fate only in response to inputs of a particular duration or frequency. A common motif in dynamically controlled cells is a dual-timescale regulatory network: although long-term fate decisions are ultimately controlled by a slow-timescale switch (e.g., gene expression), input signals are first processed by a fast-timescale signaling layer, which is hypothesized to filter what dynamic information is efficiently relayed downstream. Directly testing the design principles of how dual-timescale circuits control dynamic sensing, however, has been challenging, because most synthetic biology methods have focused solely on rewiring transcriptional circuits, which operate at a single slow timescale. Here, we report the development of a modular approach for flexibly engineering phosphorylation circuits using designed phospho-regulon motifs. By then linking rapid phospho-feedback with slower downstream transcription-based bistable switches, we can construct synthetic dual-timescale circuits in yeast in which the triggering dynamics and the end-state properties of the ON state can be selectively tuned. These phospho-regulon tools thus open up the possibility to engineer cells with customized dynamical control.

Triggering signaling pathways using F-actin self-organization

The spatiotemporal organization of proteins within cells is essential for cell fate behavior. Although it is known that the cytoskeleton is vital for numerous cellular functions, it remains unclear how cytoskeletal activity can shape and control signaling pathways in space and time throughout the cell cytoplasm. Here we show that F-actin self-organization can trigger signaling pathways by engineering two novel properties of the microfilament self-organization: (1) the confinement of signaling proteins and (2) their scaffolding along actin polymers. Using in vitro reconstitutions of cellular functions, we found that both the confinement of nanoparticle-based signaling platforms powered by F-actin contractility and the scaffolding of engineered signaling proteins along actin microfilaments can drive a signaling switch. Using Ran-dependent microtubule nucleation, we found that F-actin dynamics promotes the robust assembly of microtubules. Our in vitro assay is a first step towards the development of novel bottom-up strategies to decipher the interplay between cytoskeleton spatial organization and signaling pathway activity.

Variable Dependence of Signaling Output on Agonist Occupancy of Ste2p, a G Protein-coupled Receptor in Yeast

We report here on the relationship between ligand binding and signaling responses in the yeast pheromone response pathway, a well characterized G protein-coupled receptor system. Responses to agonist (α-factor) by cells expressing widely varying numbers of receptors depend primarily on fractional occupancy, not the absolute number of agonist-bound receptors. Furthermore, the concentration of competitive antagonist required to inhibit α-factor-dependent signaling is more than 10-fold higher than predicted based on the known ligand affinities. Thus, responses to a particular number of agonist-bound receptors can vary greatly, depending on whether there are unoccupied or antagonist-bound receptors present on the same cell surface. This behavior does not appear to be due to pre-coupling of receptors to G protein or to the Sst2p regulator of G protein signaling. The results are consistent with a signaling response that is determined by the integration of positive signals from agonist-occupied receptors and inhibitory signals from unoccupied receptors, where the inhibitory signals can be diminished by antagonist binding.

Ultrasensitive Negative Feedback Control: A Natural Approach for the Design of Synthetic Controllers

Many of the most important potential applications of Synthetic Biology will require the ability to design and implement high performance feedback control systems that can accurately regulate the dynamics of multiple molecular species within the cell. Here, we argue that the use of design strategies based on combining ultrasensitive response dynamics with negative feedback represents a natural approach to this problem that fully exploits the strongly nonlinear nature of cellular information processing. We propose that such feedback mechanisms can explain the adaptive responses observed in one of the most widely studied biomolecular feedback systems—the yeast osmoregulatory response network. Based on our analysis of such system, we identify strong links with a well-known branch of mathematical systems theory from the field of Control Engineering, known as Sliding Mode Control. These insights allow us to develop design guidelines that can inform the construction of feedback controllers for synthetic biological systems.

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

Evolution of a G protein-coupled receptor response by mutations in regulatory network interactions

All cellular functions depend on the concerted action of multiple proteins organized in complex networks. To understand how selection acts on protein networks, we used the yeast mating receptor Ste2, a pheromone-activated G protein-coupled receptor, as a model system. In Saccharomyces cerevisiae, Ste2 is a hub in a network of interactions controlling both signal transduction and signal suppression. Through laboratory evolution, we obtained 21 mutant receptors sensitive to the pheromone of a related yeast species and investigated the molecular mechanisms behind this newfound sensitivity. While some mutants show enhanced binding affinity to the foreign pheromone, others only display weakened interactions with the network's negative regulators. Importantly, the latter changes have a limited impact on overall pathway regulation, despite their considerable effect on sensitivity. Our results demonstrate that a new receptor–ligand pair can evolve through network-altering mutations independently of receptor–ligand binding, and suggest a potential role for such mutations in disease.

Co-evolution of a new receptor-ligand pair will affect the downstream signal transduction network. Here, the authors use experimental evolution of yeast mating receptor Ste2 to show the effect of enhanced binding affinity and weakened interactions with the network's negative regulators on protein evolution.

Control theory meets synthetic biology

The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The description especially highlights technical challenges that uniquely arise from the need to implement control designs within a new hardware setting, along with implemented or proposed solutions. Some engineering solutions employing complex feedback control schemes are also described, which, however, still require a deeper theoretical analysis of stability, performance and robustness properties. Overall, this paper should help synthetic biologists become familiar with feedback control concepts as they can be used in their application area. At the same time, it should provide some domain knowledge to control theorists who wish to enter the rising and exciting field of synthetic biology.

Modular engineering of cellular signaling proteins and networks

Living cells respond to their environment using networks of signaling molecules that act as sensors, information processors, and actuators. These signaling systems are highly modular at both the molecular and network scales, and much evidence suggests that evolution has harnessed this modularity to rewire and generate new physiological behaviors. Conversely, we are now finding that, following nature's example, signaling modules can be recombined to form synthetic tools for monitoring, interrogating, and controlling the behavior of cells. Here we highlight recent progress in the modular design of synthetic receptors, optogenetic switches, and phospho-regulated proteins and circuits, and discuss the expanding role of combinatorial design in the engineering of cellular signaling proteins and networks.

Mammalian synthetic biology: emerging medical applications

In this review, we discuss new emerging medical applications of the rapidly evolving field of mammalian synthetic biology. We start with simple mammalian synthetic biological components and move towards more complex and therapy-oriented gene circuits. A comprehensive list of ON-OFF switches, categorized into transcriptional, post-transcriptional, translational and post-translational, is presented in the first sections. Subsequently, Boolean logic gates, synthetic mammalian oscillators and toggle switches will be described. Several synthetic gene networks are further reviewed in the medical applications section, including cancer therapy gene circuits, immuno-regulatory networks, among others. The final sections focus on the applicability of synthetic gene networks to drug discovery, drug delivery, receptor-activating gene circuits and mammalian biomanufacturing processes.

Docking interactions: cell-cycle regulation and beyond

In budding yeast, the mating pathway activates Far1 to inhibit G1 cyclins in complex with the cyclin-dependent kinase (Cln-Cdk). Yet, the molecular mechanism has remained largely unclear for over 20 years. A recent report helps shed light on this regulation.

A synthetic gene circuit for measuring autoregulatory feedback control

Autoregulatory feedback loops occur in the regulation of molecules ranging from ATP to MAP kinases to zinc. Negative feedback loops can increase a system's robustness, while positive feedback loops can mediate transitions between cell states. Recent genome-wide experimental and computational studies predict hundreds of novel feedback loops. However, not all physical interactions are regulatory, and many experimental methods cannot detect self-interactions. Our understanding of regulatory feedback loops is therefore hampered by the lack of high-throughput methods to experimentally quantify the presence, strength and temporal dynamics of autoregulatory feedback loops. Here we present a mathematical and experimental framework for high-throughput quantification of feedback regulation and apply it to RNA binding proteins (RBPs) in yeast. Our method is able to determine the existence of both direct and indirect positive and negative feedback loops, and to quantify the strength of these loops. We experimentally validate our model using two RBPs which lack native feedback loops and by the introduction of synthetic feedback loops. We find that RBP Puf3 does not natively participate in any direct or indirect feedback regulation, but that replacing the native 3'UTR with that of COX17 generates an auto-regulatory negative feedback loop which reduces gene expression noise. Likewise, RBP Pub1 does not natively participate in any feedback loops, but a synthetic positive feedback loop involving Pub1 results in increased expression noise. Our results demonstrate a synthetic experimental system for quantifying the existence and strength of feedback loops using a combination of high-throughput experiments and mathematical modeling. This system will be of great use in measuring auto-regulatory feedback by RNA binding proteins, a regulatory motif that is difficult to quantify using existing high-throughput methods.

Synthetic biology: insights into biological computation

Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology.

Deriving Heterospecific Self-Assembling Protein-Protein Interactions Using a Computational Interactome Screen

Interactions between naturally occurring proteins are highly specific, with protein-network imbalances associated with numerous diseases. For designed protein–protein interactions (PPIs), required specificity can be notoriously difficult to engineer. To accelerate this process, we have derived peptides that form heterospecific PPIs when combined. This is achieved using software that generates large virtual libraries of peptide sequences and searches within the resulting interactome for preferentially interacting peptides. To demonstrate feasibility, we have (i) generated 1536 peptide sequences based on the parallel dimeric coiled-coil motif and varied residues known to be important for stability and specificity, (ii) screened the 1,180,416 member interactome for predicted T_m values and (iii) used predicted T_m cutoff points to isolate eight peptides that form four heterospecific PPIs when combined. This required that all 32 hypothetical off-target interactions within the eight-peptide interactome be disfavoured and that the four desired interactions pair correctly. Lastly, we have verified the approach by characterising all 36 pairs within the interactome. In analysing the output, we hypothesised that several sequences are capable of adopting antiparallel orientations. We subsequently improved the software by removing sequences where doing so led to fully complementary electrostatic pairings. Our approach can be used to derive increasingly large and therefore complex sets of heterospecific PPIs with a wide range of potential downstream applications from disease modulation to the design of biomaterials and peptides in synthetic biology.

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Naturally occurring protein–protein interactions (PPIs) are highly specific.

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For designed PPIs, however, specificity can be notoriously difficult to engineer.

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We have computationally screened a vast interactome to derive four heterospecific PPIs.

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Eight peptides form four heterospecific coiled coils; all 32 off targets are disfavoured.

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The method can derive larger and increasingly complex sets of heterospecific PPIs

Engineering dynamic cell cycle control with synthetic small molecule-responsive RNA devices

Background

The cell cycle plays a key role in human health and disease, including development and cancer. The ability to easily and reversibly control the mammalian cell cycle could mean improved cellular reprogramming, better tools for studying cancer, more efficient gene therapy, and improved heterologous protein production for medical or industrial applications.

Results

We engineered RNA-based control devices to provide specific and modular control of gene expression in response to exogenous inputs in living cells. Specifically, we identified key regulatory nodes that arrest U2-OS cells in the G0/1 or G2/M phases of the cycle. We then optimized the most promising key regulators and showed that, when these optimized regulators are placed under the control of a ribozyme switch, we can inducibly and reversibly arrest up to ~80 % of a cellular population in a chosen phase of the cell cycle. Characterization of the reliability of the final cell cycle controllers revealed that the G0/1 control device functions reproducibly over multiple experiments over several weeks.

Conclusions

To our knowledge, this is the first time synthetic RNA devices have been used to control the mammalian cell cycle. This RNA platform represents a general class of synthetic biology tools for modular, dynamic, and multi-output control over mammalian cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s13036-015-0019-7) contains supplementary material, which is available to authorized users.

Proteomic identification of novel cytoskeletal proteins associated with TbPLK, an essential regulator of cell morphogenesis in Trypanosoma brucei

Trypanosoma brucei is the causative agent of African sleeping sickness, a devastating disease endemic to sub-Saharan Africa with few effective treatment options. The parasite is highly polarized, including a single flagellum that is nucleated at the posterior of the cell and adhered along the cell surface. These features are essential and must be transmitted to the daughter cells during division. Recently we identified the T. brucei homologue of polo-like kinase (TbPLK) as an essential morphogenic regulator. In the present work, we conduct proteomic screens to identify potential TbPLK binding partners and substrates to better understand the molecular mechanisms of kinase function. These screens identify a cohort of proteins, most of which are completely uncharacterized, which localize to key cytoskeletal organelles involved in establishing cell morphology, including the flagella connector, flagellum attachment zone, and bilobe structure. Depletion of these proteins causes substantial changes in cell division, including mispositioning of the kinetoplast, loss of flagellar connection, and prevention of cytokinesis. The proteins identified in these screens provide the foundation for establishing the molecular networks through which TbPLK directs cell morphogenesis in T. brucei.

Control of mRNA decapping by positive and negative regulatory elements in the Dcp2 C-terminal domain

Decapping commits an mRNA to complete degradation and promotes general 5' to 3' decay, nonsense-mediated decay (NMD), and transcript-specific degradation. In Saccharomyces cerevisiae, a single decapping enzyme composed of a regulatory subunit (Dcp1) and a catalytic subunit (Dcp2) targets thousands of distinct substrate mRNAs. However, the mechanisms controlling this enzyme's in vivo activity and substrate specificity remain elusive. Here, using a genetic approach, we show that the large C-terminal domain of Dcp2 includes a set of conserved negative and positive regulatory elements. A single negative element inhibits enzymatic activity and controls the downstream functions of several positive elements. The positive elements recruit the specific decapping activators Edc3, Pat1, and Upf1 to form distinct decapping complexes and control the enzyme's substrate specificity and final activation. Our results reveal unforeseen regulatory mechanisms that control decapping enzyme activity and function in vivo, and define roles for several decapping activators in the regulation of mRNA decapping.

Cytokinetic Abscission: Timing the Separation

New work identifies components of the abscission checkpoint that prevent premature severing of the bridge connecting cells at the end of cell division. Kinase activities allow the membrane remodeling machinery to take their mark, but prevent them from leaving the starting block.

Artificial cell-cell communication as an emerging tool in synthetic biology applications

Cell-cell communication is a widespread phenomenon in nature, ranging from bacterial quorum sensing and fungal pheromone communication to cellular crosstalk in multicellular eukaryotes. These communication modes offer the possibility to control the behavior of an entire community by modifying the performance of individual cells in specific ways. Synthetic biology, i.e., the implementation of artificial functions within biological systems, is a promising approach towards the engineering of sophisticated, autonomous devices based on specifically functionalized cells. With the growing complexity of the functions performed by such systems, both the risk of circuit crosstalk and the metabolic burden resulting from the expression of numerous foreign genes are increasing. Therefore, systems based on a single type of cells are no longer feasible. Synthetic biology approaches with multiple subpopulations of specifically functionalized cells, wired by artificial cell-cell communication systems, provide an attractive and powerful alternative. Here we review recent applications of synthetic cell-cell communication systems with a specific focus on recent advances with fungal hosts.

Synthetic Biology: A Unifying View and Review Using Analog Circuits

We review the field of synthetic biology from an analog circuits and analog computation perspective, focusing on circuits that have been built in living cells. This perspective is well suited to pictorially, symbolically, and quantitatively representing the nonlinear, dynamic, and stochastic (noisy) ordinary and partial differential equations that rigorously describe the molecular circuits of synthetic biology. This perspective enables us to construct a canonical analog circuit schematic that helps unify and review the operation of many fundamental circuits that have been built in synthetic biology at the DNA, RNA, protein, and small-molecule levels over nearly two decades. We review 17 circuits in the literature as particular examples of feedforward and feedback analog circuits that arise from special topological cases of the canonical analog circuit schematic. Digital circuit operation of these circuits represents a special case of saturated analog circuit behavior and is automatically incorporated as well. Many issues that have prevented synthetic biology from scaling are naturally represented in analog circuit schematics. Furthermore, the deep similarity between the Boltzmann thermodynamic equations that describe noisy electronic current flow in subthreshold transistors and noisy molecular flux in biochemical reactions has helped map analog circuit motifs in electronics to analog circuit motifs in cells and vice versa via a `cytomorphic' approach. Thus, a body of knowledge in analog electronic circuit design, analysis, simulation, and implementation may also be useful in the robust and efficient design of molecular circuits in synthetic biology, helping it to scale to more complex circuits in the future.

In vivo characterization of the scaffold activity of flotillin on the membrane kinase KinC of Bacillus subtilis

Scaffold proteins are ubiquitous chaperones that bind to proteins and facilitate the physical interaction of the components of signal transduction pathways or multi-enzymic complexes. In this study, we used a biochemical approach to dissect the molecular mechanism of a membrane-associated scaffold protein, FloT, a flotillin-homologue protein that is localized in functional membrane microdomains of the bacterium Bacillus subtilis. This study provides unambiguous evidence that FloT physically binds to and interacts with the membrane-bound sensor kinase KinC. This sensor kinase activates biofilm formation in B. subtilis in response to the presence of the self-produced signal surfactin. Furthermore, we have characterized the mechanism by which the interaction of FloT with KinC benefits the activity of KinC. Two separate and synergistic effects constitute this mechanism: first, the scaffold activity of FloT promotes more efficient self-interaction of KinC and facilitates dimerization into its active form. Second, the selective binding of FloT to KinC prevents the occurrence of unspecific aggregation between KinC and other proteins that may generate dead-end intermediates that could titrate the activity of KinC. Flotillin proteins appear to play an important role in prokaryotes in promoting effective binding of signalling proteins with their correct protein partners.

A fungicide-responsive kinase as a tool for synthetic cell fate regulation

Engineered biological systems that precisely execute defined tasks have major potential for medicine and biotechnology. For instance, gene- or cell-based therapies targeting pathogenic cells may replace time- and resource-intensive drug development. Engineering signal transduction systems is a promising, yet presently underexplored approach. Here, we exploit a fungicide-responsive heterologous histidine kinase for pathway engineering and synthetic cell fate regulation in the budding yeast Saccharomyces cerevisiae. Rewiring the osmoregulatory Hog1 MAPK signalling system generates yeast cells programmed to execute three different tasks. First, a synthetic negative feedback loop implemented by employing the fungicide-responsive kinase and a fungicide-resistant derivative reshapes the Hog1 activation profile, demonstrating how signalling dynamics can be engineered. Second, combinatorial integration of different genetic parts including the histidine kinases, a pathway activator and chemically regulated promoters enables control of yeast growth and/or gene expression in a two-input Boolean logic manner. Finally, we implemented a genetic ‘suicide attack’ system, in which engineered cells eliminate target cells and themselves in a specific and controllable manner. Taken together, fungicide-responsive kinases can be applied in different constellations to engineer signalling behaviour. Sensitizing engineered cells to existing chemicals may be generally useful for future medical and biotechnological 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.

BioJazz: in silico evolution of cellular networks with unbounded complexity using rule-based modeling

Systems biologists aim to decipher the structure and dynamics of signaling and regulatory networks underpinning cellular responses; synthetic biologists can use this insight to alter existing networks or engineer de novo ones. Both tasks will benefit from an understanding of which structural and dynamic features of networks can emerge from evolutionary processes, through which intermediary steps these arise, and whether they embody general design principles. As natural evolution at the level of network dynamics is difficult to study, in silico evolution of network models can provide important insights. However, current tools used for in silico evolution of network dynamics are limited to ad hoc computer simulations and models. Here we introduce BioJazz, an extendable, user-friendly tool for simulating the evolution of dynamic biochemical networks. Unlike previous tools for in silico evolution, BioJazz allows for the evolution of cellular networks with unbounded complexity by combining rule-based modeling with an encoding of networks that is akin to a genome. We show that BioJazz can be used to implement biologically realistic selective pressures and allows exploration of the space of network architectures and dynamics that implement prescribed physiological functions. BioJazz is provided as an open-source tool to facilitate its further development and use. Source code and user manuals are available at: http://oss-lab.github.io/biojazz and http://osslab.lifesci.warwick.ac.uk/BioJazz.aspx.

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.

Plant synthetic biology

Plant synthetic biology is an emerging field that combines engineering principles with plant biology toward the design and production of new devices. This emerging field should play an important role in future agriculture for traditional crop improvement, but also in enabling novel bioproduction in plants. In this review we discuss the design cycles of synthetic biology as well as key engineering principles, genetic parts, and computational tools that can be utilized in plant synthetic biology. Some pioneering examples are offered as a demonstration of how synthetic biology can be used to modify plants for specific purposes. These include synthetic sensors, synthetic metabolic pathways, and synthetic genomes. We also speculate about the future of synthetic biology of plants.

Differential genetic interactions of yeast stress response MAPK pathways

Genetic interaction screens have been applied with great success in several organisms to study gene function and the genetic architecture of the cell. However, most studies have been performed under optimal growth conditions even though many functional interactions are known to occur under specific cellular conditions. In this study, we have performed a large-scale genetic interaction analysis in Saccharomyces cerevisiae involving approximately 49 × 1,200 double mutants in the presence of five different stress conditions, including osmotic, oxidative and cell wall-altering stresses. This resulted in the generation of a differential E-MAP (or dE-MAP) comprising over 250,000 measurements of conditional interactions. We found an extensive number of conditional genetic interactions that recapitulate known stress-specific functional associations. Furthermore, we have also uncovered previously unrecognized roles involving the phosphatase regulator Bud14, the histone methylation complex COMPASS and membrane trafficking complexes in modulating the cell wall integrity pathway. Finally, the osmotic stress differential genetic interactions showed enrichment for genes coding for proteins with conditional changes in phosphorylation but not for genes with conditional changes in gene expression. This suggests that conditional genetic interactions are a powerful tool to dissect the functional importance of the different response mechanisms of the cell.

Applications of Cas9 as an RNA-programmed RNA-binding protein

The Streptococcus pyogenes CRISPR-Cas system has gained widespread application as a genome editing and gene regulation tool as simultaneous cellular delivery of the Cas9 protein and guide RNAs enables recognition of specific DNA sequences. The recent discovery that Cas9 can also bind and cleave RNA in an RNA-programmable manner indicates the potential utility of this system as a universal nucleic acid-recognition technology. RNA-targeted Cas9 (RCas9) could allow identification and manipulation of RNA substrates in live cells, empowering the study of cellular gene expression, and could ultimately spawn patient- and disease-specific diagnostic and therapeutic tools. Here we describe the development of RCas9 and compare it to previous methods for RNA targeting, including engineered RNA-binding proteins and other types of CRISPR-Cas systems. We discuss potential uses ranging from live imaging of transcriptional dynamics to patient-specific therapies and applications in synthetic biology.

Engineering protocells: prospects for self-assembly and nanoscale production-lines

The increasing ease of producing nucleic acids and proteins to specification offers potential for design and fabrication of artificial synthetic "organisms" with a myriad of possible capabilities. The prospects for these synthetic organisms are significant, with potential applications in diverse fields including synthesis of pharmaceuticals, sources of renewable fuel and environmental cleanup. Until now, artificial cell technology has been largely restricted to the modification and metabolic engineering of living unicellular organisms. This review discusses emerging possibilities for developing synthetic protocell "machines" assembled entirely from individual biological components. We describe a host of recent technological advances that could potentially be harnessed in design and construction of synthetic protocells, some of which have already been utilized toward these ends. More elaborate designs include options for building self-assembling machines by incorporating cellular transport and assembly machinery. We also discuss production in miniature, using microfluidic production lines. While there are still many unknowns in the design, engineering and optimization of protocells, current technologies are now tantalizingly close to the capabilities required to build the first prototype protocells with potential real-world applications.

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.