Synthetic immune signaling

A successful immune response against pathogens requires the activation of different cell types of the immune system. These activation processes are difficult to study by classical biochemical and genetic methods alone. In this review we describe how approaches of synthetic biology, such as rebuilding of minimal functional signaling systems and the design of new molecules acting as signaling switches, can be used to get a deeper insight into the signaling mechanism of immune cells. In particular, the interaction of receptors with signal-transducing elements can be studied in detail with these new methods. In addition, sophisticated synthetic immune receptors are being tested in the clinic for gene therapy against certain cancer types.     

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.     

Molecular diversity--the toolbox for synthetic gene switches and networks

The rapid development of synthetic biology is a paradigm of how the molecular diversity of naturally occurring gene control components can be used to design synthetic control devices and gene networks that provide precisely programmed transgene expression dynamics in space and time. Here we offer an overview on recent advances in the modular design of trigger-inducible mammalian expression devices that are either responsive by exogenous stimuli such as chemicals and physical cues or controlled by endogenous metabolites driving prosthetic circuits to treat metabolic disorders in a self-sufficient manner. Compatible genetic switches can also be assembled to synthetic gene networks that show highly complex expression dynamics such as temporally resolved band-detect functions or oscillating transgene expression profiles. The ongoing metagenomic discovery and characterization of the unexplored sequence space is constantly increasing the molecular diversity in fundamental control components that fuels the further development of synthetic biology.     

“Toehold Switches; a foothold for Synthetic Biology”

Toehold switches are de novo designed riboregulators that contain two RNA components interacting through linear-linear RNA interactions, regulating the gene expression. These are highly versatile, exhibit excellent orthogonality, wide dynamic range, and are highly programmable, so can be used for various applications in synthetic biology. In this review, we summarized and discussed the design characteristics and benefits of toehold switch riboregulators over conventional riboregulators. We also discussed applications and recent advancements of toehold switch riboregulators in various fields like gene editing, DNA nanotechnology, translational repression, and diagnostics (detection of microRNAs and some pathogens). Toehold switches, therefore, furnished advancement in synthetic biology applications in various fields with their prominent features.     

Synthetic therapeutic gene circuits in mammalian cells

In the emerging field of synthetic biology, scientists are focusing on designing and creating functional devices, systems, and organisms with novel functions by engineering and assembling standardised biological building blocks. The progress of synthetic biology has significantly advanced the design of functional gene networks that can reprogram metabolic activities in mammalian cells and provide new therapeutic opportunities for future gene- and cell-based therapies. In this review, we describe the most recent advances in synthetic mammalian gene networks designed for biomedical applications, including how these synthetic therapeutic gene circuits can be assembled to control signalling networks and applied to treat metabolic disorders, cancer, and immune diseases. We conclude by discussing the various challenges and future prospects of using synthetic mammalian gene networks for disease therapy.     

Synthetic biology: new strategies for directing design

The advancement of synthetic biology is thanks, in large part, to continuing improvements in DNA synthesis. The expansion of synthetic biology into the realm of metabolic engineering has shifted the focus from simply making novel synthetic biological parts to answering the question of how we employ these biological parts to construct genomes that ultimately give rise to useful phenotypes. Much like protein engineering, the answer to this will be arrived at following the combination of rational design and evolutionary approaches. This review will highlight some of the new DNA synthesis-enabled search methods and discuss the application of such methods to the creation of synthetic gene networks and genomes.     

Modeling genetic switches with positive feedback loops

In this paper, we develop a new methodology to design synthetic genetic switch networks with multiple genes and time delays, by using monotone dynamical systems. We show that the networks with only positive feedback loops have no stable oscillation but stable equilibria whose stability is independent of the time delays. In other words, such systems have ideal properties for switch networks and can be designed without consideration of time delays, because the systems can be reduced from functional spaces to Euclidian spaces. Therefore, we can ensure that the designed switches function correctly even with uncertain delays. We first prove the basic properties of the genetic networks composed of only positive feedback loops, and then propose a procedure to design the switches, which drastically simplifies analysis of the switches and makes theoretical analysis and design tractable even for large-scaled systems. Finally, to demonstrate our theoretical results, we show biologically plausible examples by designing a synthetic genetic switch with experimentally well investigated lacI, tetR, and cI genes for numerical simulation.     

Using plasma membrane nanoclusters to build better signaling circuits

Cellular signaling pathways do not simply transmit data; they integrate and process signals to operate as switches, oscillators, logic gates, memory modules and many other types of control system. These complex processing capabilities enable cells to respond appropriately to the myriad of external cues that direct growth and development. The idea that crosstalk and feedback loops are used as control systems in biological signaling networks is well established. Signaling networks are also subject to exquisite spatial regulation, yet how spatial control modulates signal outputs is less well understood. Here, we explore the spatial organization of two different signal transduction circuits: receptor tyrosine kinase activation of the mitogen-activated protein kinase module; and glycosylphosphatidylinositol-anchored receptor activation of phospholipase C. With regards to these pathways, recent results have refocused attention on the crucial role of lipid rafts and plasma membrane nanodomains in signal transmission. We identify common design principals that highlight how the spatial organization of signal transduction circuits can be used as a fundamental control mechanism to modulate system outputs in vivo.     

Phenotypic Heterogeneity Generated by Histidine Kinase-Based Signaling Networks

A complex relationship exists between environmental factors, signaling networks and phenotypic individuality in bacteria. In this review, we will focus on the organization, function and control points of multiple-input histidine kinase-based signaling cascades as a source of phenotypic heterogeneity. In particular, we will examine the quorum sensing cascade in Vibrio harveyi and the pyruvate sensor network in Escherichia coli. We will describe and compare these histidine kinase-based signaling networks in terms of robustness, the molecular mechanisms of signal transduction and the role of RNA switches. Finally, we will discuss the biological significance of phenotypic heterogeneity for the respective bacteria in relation to environmental factors.     

Signaling cross-talk during development: Context-specific networking of Notch,NF-κB and JNK signaling pathways in Drosophila

Multicellular organisms depend on a handful of core signaling pathways that regulate a variety of cell fate choices. Often these relatively simple signals integrate to form a large and complex signaling network to achieve a distinct developmental fate in a context-specific manner. Various pathway-dependent and independent events control the assembly of signaling complexes. Notch pathway is one such conserved signaling mechanism that integrates with other signaling pathways to exhibit a context-dependent pleiotropic output. To understand how Notch signaling provides a spectrum of distinct outputs, it is important to understand various regulatory switches involved in mediating signaling cross-talk of Notch with other pathways. Here, we review our current understanding as to how Notch signal integrates with JNK and NF-κB signaling pathways in Drosophila to regulate various developmental events such as sensory organ precursor formation, innate immunity, dorsal closure, establishment of planar cell polarity as well as during proliferation and tumor progression. We highlight the importance of conserved signaling molecules during these cross-talks and debate further possibilities of novel switches that may be involved in mediating these cross-talk events.     

Design Principles of a Genetic Alarm Clock

Turning genes on and off is a mechanism by which cells and tissues make phenotypic decisions. Gene network motifs capable of supporting two or more steady states and thereby providing cells with a plurality of possible phenotypes are referred to as genetic switches. Modeled on the bases of naturally occurring genetic networks, synthetic biologists have successfully constructed artificial switches, thus opening a door to new possibilities for improvement of the known, but also the design of new synthetic genetic circuits. One of many obstacles to overcome in such efforts is to understand and hence control intrinsic noise which is inherent in all biological systems. For some motifs the noise is negligible; for others, fluctuations in the particle number can be comparable to its average. Due to their slowed dynamics, motifs with positive autoregulation tend to be highly sensitive to fluctuations of their chemical environment and are in general very noisy, especially during transition (switching). In this article we use stochastic simulations (Gillespie algorithm) to model such a system, in particular a simple bistable motif consisting of a single gene with positive autoregulation. Due to cooperativety, the dynamical behavior of this kind of motif is reminiscent of an alarm clock – the gene is (nearly) silent for some time after it is turned on and becomes active very suddenly. We investigate how these sudden transitions are affected by noise and show that under certain conditions accurate timing can be achieved. We also examine how promoter complexity influences the accuracy of this timing mechanism.     

Synthetic genetic circuits for programmable biological functionalities

Living organisms evolve complex genetic networks to interact with the environment. Due to the rapid development of synthetic biology, various modularized genetic parts and units have been identified from these networks. They have been employed to construct synthetic genetic circuits, including toggle switches, oscillators, feedback loops and Boolean logic gates. Building on these circuits, complex genetic machines with capabilities in programmable decision-making could be created. Consequently, these accomplishments have led to novel applications, such as dynamic and autonomous modulation of metabolic networks, directed evolution of biological units, remote and targeted diagnostics and therapies, as well as biological containment methods to prevent release of engineered microorganisms and genetic materials. Herein, we outline the principles in genetic circuit design that have initiated a new chapter in transforming concepts to realistic applications. The features of modularized building blocks and circuit architecture that facilitate realization of circuits for a variety of novel applications are discussed. Furthermore, recent advances and challenges in employing genetic circuits to impart microorganisms with distinct and programmable functionalities are highlighted. We envision that this review gives new insights into the design of synthetic genetic circuits and offers a guideline for the implementation of different circuits in various aspects of biotechnology and bioengineering.     

Modeling of signaling networks

Biochemical networks, including those containing signaling pathways, display a wide range of regulatory properties. These include the ability to propagate information across different time scales and to function as switches and oscillators. The mechanisms underlying these complex behaviors involve many interacting components and cannot be understood by experiments alone. The development of computational models and the integration of these models with experiments provide valuable insight into these complex systems-level behaviors. Here we review current approaches to the development of computational models of biochemical networks and describe the insights gained from models that integrate experimental data, using three examples that deal with ultrasensitivity, flexible bistability and oscillatory behavior. These types of complex behavior from relatively simple networks highlight the necessity of using theoretical approaches in understanding higher order biological functions.     

Network medicine

To more effectively target complex diseases like cancer, diabetes and schizophrenia, we may need to rethink our strategies for drug development and the selection of molecular targets for pharmacological treatments. Here, we discuss the potential use of protein signaling networks as the targets for new therapeutic intervention. We argue that by targeting the architecture of aberrant signaling networks associated with cancer and other diseases new therapeutic strategies can be implemented. Transforming medicine into a network driven endeavour will require quantitative measurements of cell signaling processes; we will describe how this may be performed and combined with new algorithms to predict the trajectories taken by a cellular system either in time or through disease states. We term this approach, network medicine.     

Off the beaten paths: alternative and crosstalk regulation of Rho GTPases

Rho proteins are small GTPases of the Ras superfamily that regulate a wide variety of biological processes, ranging from gene expression to cell migration. Mechanistically, the major Rho GTPases function as molecular switches cycling between an inactive GDP-bound and an active GTP-bound conformation, although several Rho proteins spontaneously exchange nucleotides or are simply devoid of GTPase activity. For over a decade, RhoGEFs and RhoGAPs have been established as the mainstream regulators of Rho proteins, respectively flipping the switch on or off. However, regulation by GEFs and GAPs leaves several fundamental questions on the operation of the Rho switch unanswered, indicating that the regulation of Rho proteins does not rely exclusively on RhoGEFs and RhoGAPs. Recent evidence indeed suggests that Rho GTPases are finely tuned by multiple alternative regulatory mechanisms, including post-translational modifications and protein degradation, as well as crosstalk mechanisms between Rho proteins. Here we review these alternative mechanisms and discuss how they alter Rho protein function and signaling. We also envision how the classic binary Rho switch may indeed function more like a switchboard with multiple switches and dials that can all contribute to the regulation of Rho protein function.     

PKC and PLA2: Probing the complexities of the calcium network

Lipid signaling and phosphorylation cascades are fundamental to calcium signaling networks. In this review, we will discuss the recent laboratory findings for the phospholipase A₂ (PLA₂)/protein kinase C (PKC) pathway within cellular calcium networks. The complexity and connectivity of these ubiquitous cellular signals make interpretation of experimental results extremely challenging. We present here computational methods which have been developed to conquer such complex data, and how they can be used to make models capable of accurately predicting cellular responses within multiple calcium signaling pathways. We propose that information obtained from network analysis and computational techniques provides a rich source of knowledge which can be directly translated to the laboratory benchtop.     

Protein interaction networks in medicine and disease

The physical interaction of proteins is subject to intense investigation that has revealed that proteins are assembled into large densely connected networks. In this review, we will examine how signaling pathways can be combined to form higher order protein interaction networks. By using network graph theory, these interaction networks can be further analyzed for global organization, which has revealed unique aspects of the relationships between protein networks and complex biological phenotypes. Moreover, several studies have shown that the structure and dynamics of protein networks are disturbed in complex diseases such as cancer progression. These relationships suggest a novel paradigm for treatment of complex multigenic disease where the protein interaction network is the target of therapy more so than individual molecules within the network.