Feedback control of protein expression in mammalian cells by tunable synthetic translational inhibition

Self-feedback loop-containing synthetic mRNA switches for controlled microRNA sensing

Synthetic mRNA switches are powerful cell fate manipulation tools that sense cellular input molecules to directly control protein expression at the translational level. The lack of available switch designs that can mimic the natural sophisticated protein regulation is a fundamental issue that limits the application of synthetic mRNA switches. Here we report a new set of synthetic mRNA switches by incorporating self-feedback loop machineries to dynamically control protein expression levels upon sensing cellular microRNAs. We redesigned the coding region of the switch to express output protein along with mRNA regulatory proteins. RNA-binding proteins (RBPs) and RBP-binding RNA motifs (aptamers) guide the regulatory proteins to act on their own mRNAs, enhancing or flattening the effect of microRNA sensing. Importantly, we demonstrated that the switches with the positive feedback feature can enlarge a high-or-low microRNA effect into a nearly all-or-none pattern, substantially boosting the use of synthetic mRNA switches as high-performance microRNA sensors or binary cell regulation tools. We believe these novel mRNA switch designs provide new strategies to construct complex mRNA-based genetic circuits for future molecular sensing and cell engineering.

Oral antibiotics relieve allergic asthma in post-weaning mice via reducing iNKT cells and function of ADRB2

The role of normal gut microbiota in asthma or ovalbumin (OVA)-induced asthma tolerance (OT) remains unclear. Here, we established mouse models of asthma and OT followed by 2 weeks of antibiotic treatment, to clear the gut microbiota. Antibiotic treatment was found to alleviate allergic asthma accompanied with a reduction of invariant natural killer (iNKT) cells. By RNA-seq analysis, we found that β-adrenergic receptor (ADRB) genes, including Adrb1, Adrb2, and Adrb3, were downregulated in asthmatic lungs, but these changes were reversed in OT lungs. Moreover, Adrb2 and Adrb3 were significantly upregulated in asthmatic lungs after antibiotic treatment. Surprisingly, blocking ADRB with propranolol relieved allergic asthma while reducing T helper 2 (Th2) and Treg cell numbers. Further analyses using flow cytometry and immunofluorescence showed that the protein expression level of ADRB2 was higher in asthmatic lungs than that in the control and OT lungs. Notably, dendritic cells (DCs), especially the ADRB2⁺ DCs, were increased in asthmatic lungs compared to that in the control and OT lungs. In addition, ADRB2⁺ DCs were significantly reduced following the administration of the ADRB2-specific antagonist ICI118551. Our findings suggest that antibiotic treatment can alleviate OVA-induced allergic asthma via reducing the frequency of iNKT cells and function of ADRB2.

A genetic mammalian proportional-integral feedback control circuit for robust and precise gene regulation

To survive in the harsh environments they inhabit, cells have evolved sophisticated regulatory mechanisms that can maintain a steady internal milieu or homeostasis. This robustness, however, does not generally translate to engineered genetic circuits, such as the ones studied by synthetic biology. Here, we introduce an implementation of a minimal and universal gene regulatory motif that produces robust perfect adaptation for mammalian cells, and we improve on it by enhancing the precision of its regulation.

The processes that keep a cell alive are constantly challenged by unpredictable changes in its environment. Cells manage to counteract these changes by employing sophisticated regulatory strategies that maintain a steady internal milieu. Recently, the antithetic integral feedback motif has been demonstrated to be a minimal and universal biological regulatory strategy that can guarantee robust perfect adaptation for noisy gene regulatory networks in Escherichia coli. Here, we present a realization of the antithetic integral feedback motif in a synthetic gene circuit in mammalian cells. We show that the motif robustly maintains the expression of a synthetic transcription factor at tunable levels even when it is perturbed by increased degradation or its interaction network structure is perturbed by a negative feedback loop with an RNA-binding protein. We further demonstrate an improved regulatory strategy by augmenting the antithetic integral motif with additional negative feedback to realize antithetic proportional–integral control. We show that this motif produces robust perfect adaptation while also reducing the variance of the regulated synthetic transcription factor. We demonstrate that the integral and proportional–integral feedback motifs can mitigate the impact of gene expression burden, and we computationally explore their use in cell therapy. We believe that the engineering of precise and robust perfect adaptation will enable substantial advances in industrial biotechnology and cell-based therapeutics.

PERSIST platform provides programmable RNA regulation using CRISPR endoRNases

Regulated transgene expression is an integral component of gene therapies, cell therapies and biomanufacturing. However, transcription factor-based regulation, upon which most applications are based, suffers from complications such as epigenetic silencing that limit expression longevity and reliability. Constitutive transgene transcription paired with post-transcriptional gene regulation could combat silencing, but few such RNA- or protein-level platforms exist. Here we develop an RNA-regulation platform we call "PERSIST" which consists of nine CRISPR-specific endoRNases as RNA-level activators and repressors as well as modular OFF- and ON-switch regulatory motifs. We show that PERSIST-regulated transgenes exhibit strong OFF and ON responses, resist silencing for at least two months, and can be readily layered to construct cascades, logic functions, switches and other sophisticated circuit topologies. The orthogonal, modular and composable nature of this platform as well as the ease in constructing robust and predictable gene circuits promises myriad applications in gene and cell therapies.

Synthetic RNA-based post-transcriptional expression control methods and genetic circuits

RNA-based synthetic genetic circuits provide an alternative for traditional transcription-based circuits in applications where genomic integration is to be avoided. Incorporating various post-transcriptional control methods into such circuits allows for controlling the behaviour of the circuit through the detection of certain biomolecular inputs or reconstituting defined circuit behaviours, thus manipulating cellular functions. In this review, recent developments of various types of post-transcriptional control methods in mammalian cells are discussed as well as auxiliary components that allow for the creation and development of mRNA-based switches. How such post-transcriptional switches are combined into synthetic circuits as well as their applications in biomedical and preclinical settings are also described. Finally, we examine the challenges that need to be surmounted before RNA-based synthetic circuits can be reliably deployed into clinical settings.

A hierarchy of biomolecular proportional-integral-derivative feedback controllers for robust perfect adaptation and dynamic performance

Proportional-Integral-Derivative (PID) feedback controllers are the most widely used controllers in industry. Recently, the design of molecular PID-controllers has been identified as an important goal for synthetic biology and the field of cybergenetics. In this paper, we consider the realization of PID-controllers via biomolecular reactions. We propose an array of topologies offering a compromise between simplicity and high performance. We first demonstrate that different biomolecular PI-controllers exhibit different performance-enhancing capabilities. Next, we introduce several derivative controllers based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop, which can be augmented by PI-components to yield PID-controllers. We demonstrate that PID-controllers can enhance stability and dynamic performance, and can also reduce stochastic noise. Finally, we provide an experimental demonstration using a hybrid setup where in silico PID-controllers regulate a genetic circuit in single yeast cells.

Mechanobiology of immune cells: Messengers, receivers and followers in leishmaniasis aiding synthetic devices

Cytokines are influential molecules which can direct cells behavior. In this review, cytokines are referred as messengers, immune cells which respond to cytokine stimulus are referred as receivers and the immune cells which gets modulated due to their plasticity induced by infectious pathogen leishmania, are referred as followers. The advantage of plasticity of cells is taken by the parasite to switch them from parasite eliminating form to parasite survival favoring form through a process called as reciprocity which is undergone by cytokines, wherein pro-inflammatory to anti-inflammatory switch occur rendering immune cell population to switch their phenotype. Detailed study of this switch can help in identification of important targets which can help in restoring the phenotype to parasite eliminating form and this can be done through synthetic circuit, finding its wider applicability in therapeutics.

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Cytokines as messengers for governing reciprocity in infection.

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Leishmania induces reciprocity modulating the immune cells plasticity.

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Reciprocity of cytokines identifies important target for therapeutics.

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Therapeutic targets aiding the design of synthetic devices to combat infection.

A synthetic distributed genetic multi-bit counter

A design for genetically encoded counters is proposed via repressor-based circuits. An N-bit counter reads sequences of input pulses and displays the total number of pulses, modulo 2N. The design is based on distributed computation with specialized cell types allocated to specific tasks. This allows scalability and bypasses constraints on the maximal number of circuit genes per cell due to toxicity or failures due to resource limitations. The design starts with a single-bit counter. The N-bit counter is then obtained by interconnecting (using diffusible chemicals) a set of N single-bit counters and connector modules. An optimization framework is used to determine appropriate gate parameters and to compute bounds on admissible pulse widths and relaxation (inter-pulse) times, as well as to guide the construction of novel gates. This work can be viewed as a step toward obtaining circuits that are capable of finite automaton computation in analogy to digital central processing units.

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A single-bit counter is designed for a repressor-based genetic circuit

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A scalable multi-bit counter is enabled by distributing the design across cells

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A computational optimization framework is proposed to guide the design

Protein-Based Systems for Translational Regulation of Synthetic mRNAs in Mammalian Cells

Synthetic mRNAs, which are produced by in vitro transcription, have been recently attracting attention because they can express any transgenes without the risk of insertional mutagenesis. Although current synthetic mRNA medicine is not designed for spatiotemporal or cell-selective regulation, many preclinical studies have developed the systems for the translational regulation of synthetic mRNAs. Such translational regulation systems will cope with high efficacy and low adverse effects by producing the appropriate amount of therapeutic proteins, depending on the context. Protein-based regulation is one of the most promising approaches for the translational regulation of synthetic mRNAs. As synthetic mRNAs can encode not only output proteins but also regulator proteins, all components of protein-based regulation systems can be delivered as synthetic mRNAs. In addition, in the protein-based regulation systems, the output protein can be utilized as the input for the subsequent regulation to construct multi-layered gene circuits, which enable complex and sophisticated regulation. In this review, I introduce what types of proteins have been used for translational regulation, how to combine them, and how to design effective gene circuits.

Directed evolution of orthogonal RNA-RBP pairs through library-vs-library in vitro selection

RNA-binding proteins (RBPs) and their RNA ligands play many critical roles in gene regulation and RNA processing in cells. They are also useful for various applications in cell biology and synthetic biology. However, re-engineering novel and orthogonal RNA-RBP pairs from natural components remains challenging while such synthetic RNA-RBP pairs could significantly expand the RNA-RBP toolbox for various applications. Here, we report a novel library-vs-library in vitro selection strategy based on Phage Display coupled with Systematic Evolution of Ligands by EXponential enrichment (PD-SELEX). Starting with pools of 1.1 × 1012 unique RNA sequences and 4.0 × 108 unique phage-displayed L7Ae-scaffold (LS) proteins, we selected RNA-RBP complexes through a two-step affinity purification process. After six rounds of library-vs-library selection, the selected RNAs and LS proteins were analyzed by next-generation sequencing (NGS). Further deconvolution of the enriched RNA and LS protein sequences revealed two synthetic and orthogonal RNA-RBP pairs that exhibit picomolar affinity and >4000-fold selectivity.

Context-aware synthetic biology by controller design: Engineering the mammalian cell

The rise of systems biology has ushered a new paradigm: the view of the cell as a system that processes environmental inputs to drive phenotypic outputs. Synthetic biology provides a complementary approach, allowing us to program cell behavior through the addition of synthetic genetic devices into the cellular processor. These devices, and the complex genetic circuits they compose, are engineered using a design-prototype-test cycle, allowing for predictable device performance to be achieved in a context-dependent manner. Within mammalian cells, context effects impact device performance at multiple scales, including the genetic, cellular, and extracellular levels. In order for synthetic genetic devices to achieve predictable behaviors, approaches to overcome context dependence are necessary. Here, we describe control systems approaches for achieving context-aware devices that are robust to context effects. We then consider cell fate programing as a case study to explore the potential impact of context-aware devices for regenerative medicine applications.

Overcoming the design, build, test bottleneck for synthesis of nonrepetitive protein-RNA cassettes

We apply an oligo-library and machine learning-approach to characterize the sequence and structural determinants of binding of the phage coat proteins (CPs) of bacteriophages MS2 (MCP), PP7 (PCP), and Qβ (QCP) to RNA. Using the oligo library, we generate thousands of candidate binding sites for each CP, and screen for binding using a high-throughput dose-response Sort-seq assay (iSort-seq). We then apply a neural network to expand this space of binding sites, which allowed us to identify the critical structural and sequence features for binding of each CP. To verify our model and experimental findings, we design several non-repetitive binding site cassettes and validate their functionality in mammalian cells. We find that the binding of each CP to RNA is characterized by a unique space of sequence and structural determinants, thus providing a more complete description of CP-RNA interaction as compared with previous low-throughput findings. Finally, based on the binding spaces we demonstrate a computational tool for the successful design and rapid synthesis of functional non-repetitive binding-site cassettes.

Phage-coat proteins can be used to build synthetic biology parts. Here the authors use an oligo library and machine learning to predict and verify sequences based on binding scores.

Using sliding mode observers to estimate BtuB concentration from measured vitamin B12 concentration

A simple model for the B12-riboswitch regulatory network in Escherichia coli is first described and the same analysis is applied when changing the strain to Salmonella enterica. Model validation is undertaken by linking the dynamics of the riboswitch model to bacterial growth and comparing the results obtained with in vivo experimental measurements. Measurements of bacterial growth are relatively straightforward to obtain experimentally, but experimental measurements relating to the operation of the riboswitch are more difficult. Using the validated model, sliding mode observer design methods are used to estimate BtuB given measurements of the concentration of vitamin B12. The sliding mode approach is selected because of its inherent robustness properties as well as for the ease of implementation. Validation of the estimates of BtuB produced by the observer is undertaken by comparing the BtuB and vitamin B12 concentrations estimated from the observer with green fluorescent protein production and the concentration of vitamin B12 obtained experimentally. These experimental results also provide further validation of the underpinning mathematical model. The results establish that using a sliding mode observer as a soft sensor is a useful approach to explore the operation of a vitamin B12 riboswitch given measurements of the concentration of vitamin B12.

The Molecular Floodgates of Stress-Induced Senescence Reveal Translation, Signalling and Protein Activity Central to the Post-Mortem Proteome

The transitioning of cells during the systemic demise of an organism is poorly understood. Here, we present evidence that organismal death is accompanied by a common and sequential molecular flood of stress-induced events that propagate the senescence phenotype, and this phenotype is preserved in the proteome after death. We demonstrate activation of “death” pathways involvement in diseases of ageing, with biochemical mechanisms mapping onto neurological damage, embryonic development, the inflammatory response, cardiac disease and ultimately cancer with increased significance. There is sufficient bioavailability of the building blocks required to support the continued translation, energy, and functional catalytic activity of proteins. Significant abundance changes occur in 1258 proteins across 1 to 720 h post-mortem of the 12-week-old mouse mandible. Protein abundance increases concord with enzyme activity, while mitochondrial dysfunction is evident with metabolic reprogramming. This study reveals differences in protein abundances which are akin to states of stress-induced premature senescence (SIPS). The control of these pathways is significant for a large number of biological scenarios. Understanding how these pathways function during the process of cellular death holds promise in generating novel solutions capable of overcoming disease complications, maintaining organ transplant viability and could influence the findings of proteomics through “deep-time” of individuals with no historically recorded cause of death.

Auto-regulatory feedback by RNA-binding proteins

RNA-binding proteins (RBPs) are key regulators in post-transcriptional control of gene expression. Mutations that alter their activity or abundance have been implicated in numerous diseases such as neurodegenerative disorders and various types of cancer. This highlights the importance of RBP proteostasis and the necessity to tightly control the expression levels and activities of RBPs. In many cases, RBPs engage in an auto-regulatory feedback by directly binding to and influencing the fate of their own mRNAs, exerting control over their own expression. For this feedback control, RBPs employ a variety of mechanisms operating at all levels of post-transcriptional regulation of gene expression. Here we review RBP-mediated autogenous feedback regulation that either serves to maintain protein abundance within a physiological range (by negative feedback) or generates binary, genetic on/off switches important for e.g. cell fate decisions (by positive feedback).

Caliciviral protein-based artificial translational activator for mammalian gene circuits with RNA-only delivery

Synthetic RNA-based gene circuits enable sophisticated gene regulation without the risk of insertional mutagenesis. While various RNA binding proteins have been used for translational repression in gene circuits, the direct translational activation of synthetic mRNAs has not been achieved. Here we develop Caliciviral VPg-based Translational activator (CaVT), which activates the translation of synthetic mRNAs without the canonical 5'-cap. The level of translation can be modulated by changing the locations, sequences, and modified nucleosides of CaVT-binding motifs in the target mRNAs, enabling the simultaneous translational activation and repression of different mRNAs with RNA-only delivery. We demonstrate the efficient regulation of apoptosis and genome editing by tuning translation levels with CaVT. In addition, we design programmable CaVT that responds to endogenous microRNAs or small molecules, achieving both cell-state-specific and conditional translational activation from synthetic mRNAs. CaVT will become an important tool in synthetic biology for both biological studies and future therapeutic applications.

Cell-Free Protein Synthesis as a Prototyping Platform for Mammalian Synthetic Biology

The field of mammalian synthetic biology is expanding quickly, and technologies for engineering large synthetic gene circuits are increasingly accessible. However, for mammalian cell engineering, traditional tissue culture methods are slow and cumbersome, and are not suited for high-throughput characterization measurements. Here we have utilized mammalian cell-free protein synthesis (CFPS) assays using HeLa cell extracts and liquid handling automation as an alternative to tissue culture and flow cytometry-based measurements. Our CFPS assays take a few hours, and we have established optimized protocols for small-volume reactions using automated acoustic liquid handling technology. As a proof-of-concept, we characterized diverse types of genetic regulation in CFPS, including T7 constitutive promoter variants, internal ribosomal entry sites (IRES) constitutive translation-initiation sequence variants, CRISPR/dCas9-mediated transcription repression, and L7Ae-mediated translation repression. Our data shows simple regulatory elements for use in mammalian cells can be quickly prototyped in a CFPS model system.

Synthetic switch to minimize CRISPR off-target effects by self-restricting Cas9 transcription and translation

CRISPR/Cas9 is a powerful genome editing system but uncontrolled Cas9 nuclease expression triggers off-target effects and even in vivo immune responses. Inspired by synthetic biology, here we built a synthetic switch that self-regulates Cas9 expression not only in the transcription step by guide RNA-aided self-cleavage of cas9 gene, but also in the translation step by L7Ae:K-turn repression system. We showed that the synthetic switch enabled simultaneous transcriptional and translational repression, hence stringently attenuating the Cas9 expression. The restricted Cas9 expression induced high efficiency on-target indel mutation while minimizing the off-target effects. Furthermore, we unveiled the correlation between Cas9 expression kinetics and on-target/off-target mutagenesis. The synthetic switch conferred detectable Cas9 expression and concomitant high frequency on-target mutagenesis at as early as 6 h, and restricted the Cas9 expression and off-target effects to minimal levels through 72 h. The synthetic switch is compact enough to be incorporated into viral vectors for self-regulation of Cas9 expression, thereby providing a novel 'hit and run' strategy for in vivo genome editing.

Synthetic negative feedback circuits using engineered small RNAs

Negative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) are non-coding RNA molecules that can inhibit translation of target messenger RNAs (mRNAs). In this work, we modelled, built and validated two synthetic negative feedback circuits that use rationally-designed sRNAs for the first time. The first circuit builds upon the well characterised tet-based autorepressor, incorporating an externally-inducible sRNA to tune the effective feedback strength. This allows more precise fine-tuning of the circuit output in contrast to the sigmoidal, steep input–output response of the autorepressor alone. In the second circuit, the output is a transcription factor that induces expression of an sRNA, which inhibits translation of the mRNA encoding the output, creating direct, closed-loop, negative feedback. Analysis of the noise profiles of both circuits showed that the use of sRNAs did not result in large increases in noise. Stochastic and deterministic modelling of both circuits agreed well with experimental data. Finally, simulations using fitted parameters allowed dynamic attributes of each circuit such as response time and disturbance rejection to be investigated.

Genetic circuits to engineer tissues with alternative functions

Persistent and complex problems arising with respect to human physiology and pathology have led to intense investigation into therapies and tools that permit more targeted outcomes and biomimetic responses to pathological conditions. A primary goal in mammalian synthetic biology is to build genetic circuits that exert fine control over cell behavior for next-generation biomedical applications. In pursuit of this, synthetic biologists have engineered cells endowed with genetic circuits with sensor that are capable of reacting to a variety of stimuli and responding with targeted behavior. Here, we highlight how synthetic biology approaches are being used to program cells with novel functions for therapeutic applications, and how they can be used in stem cells to improve differentiation outcomes. These approaches open the possibilities for engineering synthetic tissues for employing personalized medicine and to develop next-generation biomedical therapies.

Adaptive information processing of network modules to dynamic and spatial stimuli

BACKGROUND

Adaptation and homeostasis are basic features of information processing in cells and seen in a broad range of contexts. Much of the current understanding of adaptation in network modules/motifs is based on their response to simple stimuli. Recently, there have also been studies of adaptation in dynamic stimuli. However a broader synthesis of how different circuits of adaptation function, and which circuits enable a broader adaptive behaviour in classes of more complex and spatial stimuli is largely missing.

RESULTS

We study the response of a variety of adaptive circuits to time-varying stimuli such as ramps, periodic stimuli and static and dynamic spatial stimuli. We find that a variety of responses can be seen in ramp stimuli, making this a basis for discriminating between even similar circuits. We also find that a number of circuits adapt exactly to ramp stimuli, and dissect these circuits to pinpoint what characteristics (architecture, feedback, biochemical aspects, information processing ingredients) allow for this. These circuits include incoherent feedforward motifs, inflow-outflow motifs and transcritical circuits. We find that changes in location in such circuits where a signal acts can result in non-adaptive behaviour in ramps, even though the location was associated with exact adaptation in step stimuli. We also demonstrate that certain augmentations of basic inflow-outflow motifs can alter the behaviour of the circuit from exact adaptation to non-adaptive behaviour. When subject to periodic stimuli, some circuits (inflow-outflow motifs and transcritical circuits) are able to maintain an average output independent of the characteristics of the input. We build on this to examine the response of adaptive circuits to static and dynamic spatial stimuli. We demonstrate how certain circuits can exhibit a graded response in spatial static stimuli with an exact maintenance of the spatial mean-value. Distinct features which emerge from the consideration of dynamic spatial stimuli are also discussed. Finally, we also build on these results to show how different circuits which show any combination of presence or absence of exact adaptation in ramps, exact mainenance of time average output in periodic stimuli and exact maintenance of spatial average of output in static spatial stimuli may be realized.

CONCLUSIONS

By studying a range of network circuits/motifs on one hand and a range of stimuli on the other, we isolate characteristics of these circuits (structural) which enable different degrees of exact adaptive and homeostatic behaviour in such stimuli, how they may be combined, and also identify cases associated with non-homeostatic behaviour. We also reveal constraints associated with locations where signals may act to enable homeostatic behaviour and constraints associated with augmentations of circuits. This consideration of multiple experimentally/naturally relevant stimuli along with circuits of adaptation of relevance in natural and engineered biology, provides a platform for deepening our understanding of adaptive and homeostatic behaviour in natural systems, bridging the gap between models of adaptation and experiments and in engineering homeostatic synthetic circuits.

A Synthetic Close-Loop Controller Circuit for the Regulation of an Extracellular Molecule by Engineered Bacteria

Feedback control is ubiquitous in biological systems. It can also play a crucial role in the design of synthetic circuits implementing novel functions in living systems, to achieve self-regulation of gene expression, noise reduction, rise time decrease, or adaptive pathway control. Despite in vitro, in vivo, and ex vivo implementations have been successfully reported, the design of biological close-loop systems with quantitatively predictable behavior is still a major challenge. In this work, we tested a model-based bottom-up design of a synthetic close-loop controller in engineered Escherichia coli, aimed to automatically regulate the concentration of an extracellular molecule, N-(3-oxohexanoyl)-L-homoserine lactone (HSL), by rewiring the elements of heterologous quorum sensing/quenching networks. The synthetic controller was successfully constructed and experimentally validated. Relying on mathematical model and experimental characterization of individual regulatory parts and enzymes, we evaluated the predictability of the interconnected system behavior in vivo. The culture was able to reach an HSL steady-state level of 72 nM, accurately predicted by the model, and showed superior capabilities in terms of robustness against cell density variation and disturbance rejection, compared with a corresponding open-loop circuit. This engineering-inspired design approach may be adopted for the implementation of other close-loop circuits for different applications and contribute to decreasing trial-and-error steps.

Unique Archaeal Small RNAs

Advances in genome-wide sequence technologies allow for detailed insights into the complexity of RNA landscapes of organisms from all three domains of life. Recent analyses of archaeal transcriptomes identified interaction and regulation networks of noncoding RNAs in this understudied domain. Here, we review current knowledge of small, noncoding RNAs with important functions for the archaeal lifestyle, which often requires adaptation to extreme environments. One focus is RNA metabolism at elevated temperatures in hyperthermophilic archaea, which reveals elevated amounts of RNA-guided RNA modification and virus defense strategies. Genome rearrangement events result in unique fragmentation patterns of noncoding RNA genes that require elaborate maturation pathways to yield functional transcripts. RNA-binding proteins, e.g., L7Ae and LSm, are important for many posttranscriptional control functions of RNA molecules in archaeal cells. We also discuss recent insights into the regulatory potential of their noncoding RNA partners.

Synthetic switch-based baculovirus for transgene expression control and selective killing of hepatocellular carcinoma cells

Baculovirus (BV) holds promise as a vector for anticancer gene delivery to combat the most common liver cancer-hepatocellular carcinoma (HCC). However, in vivo BV administration inevitably results in BV entry into non-HCC normal cells, leaky anticancer gene expression and possible toxicity. To improve the safety, we employed synthetic biology to engineer BV for transgene expression regulation. We first uncovered that miR-196a and miR-126 are exclusively expressed in HCC and normal cells, respectively, which allowed us to engineer a sensor based on distinct miRNA expression signature. We next assembled a synthetic switch by coupling the miRNA sensor and RNA binding protein L7Ae for translational repression, and incorporated the entire device into a single BV. The recombinant BV efficiently entered HCC and normal cells and enabled cis-acting transgene expression control, by turning OFF transgene expression in normal cells while switching ON transgene expression in HCC cells. Using pro-apoptotic hBax as the transgene, the switch-based BV selectively killed HCC cells in separate culture and mixed culture of HCC and normal cells. These data demonstrate the potential of synthetic switch-based BV to distinguish HCC and non-HCC normal cells for selective transgene expression control and killing of HCC cells.

System-based strategies for p53 recovery

The authors have proposed a systems theory-based novel drug design approach for the p53 pathway. The pathway is taken as a dynamic system represented by ordinary differential equations-based mathematical model. Using control engineering practices, the system analysis and subsequent controller design is performed for the re-activation of wild-type p53. p53 revival is discussed for both modes of operation, i.e. the sustained and oscillatory. To define the problem in control system paradigm, modification in the existing mathematical model is performed to incorporate the effect of Nutlin. Attractor point analysis is carried out to select the suitable domain of attraction. A two-loop negative feedback control strategy is devised to drag the system trajectories to the attractor point and to regulate cellular concentration of Nutlin, respectively. An integrated framework is constituted to incorporate the pharmacokinetic effects of Nutlin in the cancerous cells. Bifurcation analysis is also performed on the p53 model to see the conditions for p53 oscillation.

Programming gene and engineered-cell therapies with synthetic biology

Gene and engineered-cell therapies promise to treat diseases by genetically modifying cells to carry out therapeutic tasks. Although the field has had some success in treating monogenic disorders and hematological malignancies, current approaches are limited to overexpression of one or a few transgenes, constraining the diseases that can be treated with this approach and leading to potential concerns over safety and efficacy. Synthetic gene networks can regulate the dosage, timing, and localization of gene expression and therapeutic activity in response to small molecules and disease biomarkers. Such "programmable" gene and engineered-cell therapies will provide new interventions for incurable or difficult-to-treat diseases.

Controllable molecular motors engineered from myosin and RNA

Engineering biomolecular motors can provide direct tests of structure-function relationships and customized components for controlling molecular transport in artificial systems ¹ or in living cells ² . Previously, synthetic nucleic acid motors ^3-5 and modified natural protein motors ^6-10 have been developed in separate complementary strategies to achieve tunable and controllable motor function. Integrating protein and nucleic-acid components to form engineered nucleoprotein motors may enable additional sophisticated functionalities. However, this potential has only begun to be explored in pioneering work harnessing DNA scaffolds to dictate the spacing, number and composition of tethered protein motors ^11-15 . Here, we describe myosin motors that incorporate RNA lever arms, forming hybrid assemblies in which conformational changes in the protein motor domain are amplified and redirected by nucleic acid structures. The RNA lever arm geometry determines the speed and direction of motor transport and can be dynamically controlled using programmed transitions in the lever arm structure ^7,9 . We have characterized the hybrid motors using in vitro motility assays, single-molecule tracking, cryo-electron microscopy and structural probing ¹⁶ . Our designs include nucleoprotein motors that reversibly change direction in response to oligonucleotides that drive strand-displacement ¹⁷ reactions. In multimeric assemblies, the controllable motors walk processively along actin filaments at speeds of 10-20 nm s^-1. Finally, to illustrate the potential for multiplexed addressable control, we demonstrate sequence-specific responses of RNA variants to oligonucleotide signals.

A Synthetic Circuit for Mercury Bioremediation Using Self-Assembling Functional Amyloids

Synthetic biology approaches to bioremediation are a key sustainable strategy to leverage the self-replicating and programmable aspects of biology for environmental stewardship. The increasing spread of anthropogenic mercury pollution into our habitats and food chains is a pressing concern. Here, we explore the use of programmed bacterial biofilms to aid in the sequestration of mercury. We demonstrate that by integrating a mercury-responsive promoter and an operon encoding a mercury-absorbing self-assembling extracellular protein nanofiber, we can engineer bacteria that can detect and sequester toxic Hg²⁺ ions from the environment. This work paves the way for the development of on-demand biofilm living materials that can operate autonomously as heavy-metal absorbents.

Synthetic mRNA devices that detect endogenous proteins and distinguish mammalian cells

Synthetic biology has great potential for future therapeutic applications including autonomous cell programming through the detection of protein signals and the production of desired outputs. Synthetic RNA devices are promising for this purpose. However, the number of available devices is limited due to the difficulty in the detection of endogenous proteins within a cell. Here, we show a strategy to construct synthetic mRNA devices that detect endogenous proteins in living cells, control translation and distinguish cell types. We engineered protein-binding aptamers that have increased stability in the secondary structures of their active conformation. The designed devices can efficiently respond to target proteins including human LIN28A and U1A proteins, while the original aptamers failed to do so. Moreover, mRNA delivery of an LIN28A-responsive device into human induced pluripotent stem cells (hiPSCs) revealed that we can distinguish living hiPSCs and differentiated cells by quantifying endogenous LIN28A protein expression level. Thus, our endogenous protein-driven RNA devices determine live-cell states and program mammalian cells based on intracellular protein information.

RIP-Seq Suggests Translational Regulation by L7Ae in Archaea

L7Ae is a universal archaeal protein that recognizes and stabilizes kink-turn (k-turn) motifs in RNA substrates. These structural motifs are widespread in nature and are found in many functional RNA species, including ribosomal RNAs. Synthetic biology approaches utilize L7Ae/k-turn interactions to control gene expression in eukaryotes. Here, we present results of comprehensive RNA immunoprecipitation sequencing (RIP-Seq) analysis of genomically tagged L7Ae from the hyperthermophilic archaeon Sulfolobus acidocaldarius. A large set of interacting noncoding RNAs was identified. In addition, several mRNAs, including the l7ae transcript, were found to contain k-turn motifs that facilitate L7Ae binding. In vivo studies showed that L7Ae autoregulates the translation of its mRNA by binding to a k-turn motif present in the 5′ untranslated region (UTR). A green fluorescent protein (GFP) reporter system was established in Escherichia coli and verified conservation of L7Ae-mediated feedback regulation in Archaea. Mobility shift assays confirmed binding to a k-turn in the transcript of nop5-fibrillarin, suggesting that the expression of all C/D box sRNP core proteins is regulated by L7Ae. These studies revealed that L7Ae-mediated gene regulation evolved in archaeal organisms, generating new tools for the modulation of synthetic gene circuits in bacteria.

L7Ae is an essential archaeal protein that is known to structure ribosomal RNAs and small RNAs (sRNAs) by binding to their kink-turn motifs. Here, we utilized RIP-Seq methodology to achieve a first global analysis of RNA substrates for L7Ae. Several novel interactions with noncoding RNA molecules (e.g., with the universal signal recognition particle RNA) were discovered. In addition, L7Ae was found to bind to mRNAs, including its own transcript’s 5′ untranslated region. This feedback-loop control is conserved in most archaea and was incorporated into a reporter system that was utilized to control gene expression in bacteria. These results demonstrate that L7Ae-mediated gene regulation evolved originally in archaeal organisms. The feedback-controlled reporter gene system can easily be adapted for synthetic biology approaches that require strict gene expression control.

Mammalian synthetic biology for studying the cell

Synthetic biology is advancing the design of genetic devices that enable the study of cellular and molecular biology in mammalian cells. These genetic devices use diverse regulatory mechanisms to both examine cellular processes and achieve precise and dynamic control of cellular phenotype. Synthetic biology tools provide novel functionality to complement the examination of natural cell systems, including engineered molecules with specific activities and model systems that mimic complex regulatory processes. Continued development of quantitative standards and computational tools will expand capacities to probe cellular mechanisms with genetic devices to achieve a more comprehensive understanding of the cell. In this study, we review synthetic biology tools that are being applied to effectively investigate diverse cellular processes, regulatory networks, and multicellular interactions. We also discuss current challenges and future developments in the field that may transform the types of investigation possible in cell biology.

Design of a Synthetic Integral Feedback Circuit: Dynamic Analysis and DNA Implementation

The design and implementation of regulation motifs ensuring robust perfect adaptation are challenging problems in synthetic biology. Indeed, the design of high-yield robust metabolic pathways producing, for instance, drug precursors and biofuels, could be easily imagined to rely on such a control strategy in order to optimize production levels and reduce production costs, despite the presence of environmental disturbance and model uncertainty. We propose here a motif that ensures tracking and robust perfect adaptation for the controlled reaction network through integral feedback. Its metabolic load on the host is fully tunable and can be made arbitrarily close to the constitutive limit, the universal minimal metabolic load of all possible controllers. A DNA implementation of the controller network is finally provided. Computer simulations using realistic parameters demonstrate the good agreement between the DNA implementation and the ideal controller dynamics.

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.

Engineering Gene Circuits for Mammalian Cell-Based Applications

Synthetic gene switches are basic building blocks for the construction of complex gene circuits that transform mammalian cells into useful cell-based machines for next-generation biotechnological and biomedical applications. Ligand-responsive gene switches are cellular sensors that are able to process specific signals to generate gene product responses. Their involvement in complex gene circuits results in sophisticated circuit topologies that are reminiscent of electronics and that are capable of providing engineered cells with the ability to memorize events, oscillate protein production, and perform complex information-processing tasks. Microencapsulated mammalian cells that are engineered with closed-loop gene networks can be implanted into mice to sense disease-related input signals and to process this information to produce a custom, fine-tuned therapeutic response that rebalances animal metabolism. Progress in gene circuit design, in combination with recent breakthroughs in genome engineering, may result in tailored engineered mammalian cells with great potential for future cell-based therapies.

Implementing Nonlinear Feedback Controllers Using DNA Strand Displacement Reactions

We show how an important class of nonlinear feedback controllers can be designed using idealized abstract chemical reactions and implemented via DNA strand displacement (DSD) reactions. Exploiting chemical reaction networks (CRNs) as a programming language for the design of complex circuits and networks, we show how a set of unimolecular and bimolecular reactions can be used to realize input-output dynamics that produce a nonlinear quasi sliding mode (QSM) feedback controller. The kinetics of the required chemical reactions can then be implemented as enzyme-free, enthalpy/entropy driven DNA reactions using a toehold mediated strand displacement mechanism via Watson-Crick base pairing and branch migration. We demonstrate that the closed loop response of the nonlinear QSM controller outperforms a traditional linear controller by facilitating much faster tracking response dynamics without introducing overshoots in the transient response. The resulting controller is highly modular and is less affected by retroactivity effects than standard linear designs.

The solution structural ensembles of RNA kink-turn motifs and their protein complexes

With the growing number of crystal structures of RNA and RNA-protein complexes, a critical next step is understanding the dynamic solution behavior of these entities in terms of conformational ensembles and energy landscapes. To this end, we have used X-ray scattering interferometry (XSI) to probe the ubiquitous RNA kink-turn motif and its complexes with the canonical kink-turn binding protein L7Ae. XSI revealed that the folded kink-turn is best described as a restricted conformational ensemble. The ions present in solution alter the nature of this ensemble, and protein binding can perturb the kink-turn ensemble without collapsing it to a unique state. This study demonstrates how XSI can reveal structural and ensemble properties of RNAs and RNA-protein complexes and uncovers the behavior of an important RNA-protein motif. This type of information will be necessary to understand, predict and engineer the behavior and function of RNAs and their protein complexes.

Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks

The ability to adapt to stimuli is a defining feature of many biological systems and critical to maintaining homeostasis. While it is well appreciated that negative feedback can be used to achieve homeostasis when networks behave deterministically, the effect of noise on their regulatory function is not understood. Here, we combine probability and control theory to develop a theory of biological regulation that explicitly takes into account the noisy nature of biochemical reactions. We introduce tools for the analysis and design of robust homeostatic circuits and propose a new regulation motif, which we call antithetic integral feedback. This motif exploits stochastic noise, allowing it to achieve precise regulation in scenarios where similar deterministic regulation fails. Specifically, antithetic integral feedback preserves the stability of the overall network, steers the population of any regulated species to a desired set point, and adapts perfectly. We suggest that this motif may be prevalent in endogenous biological circuits and useful when creating synthetic circuits.

RNA-based gene circuits for cell regulation

A major goal of synthetic biology is to control cell behavior. RNA-mediated genetic switches (RNA switches) are devices that serve this purpose, as they can control gene expressions in response to input signals. In general, RNA switches consist of two domains: an aptamer domain, which binds to an input molecule, and an actuator domain, which controls the gene expression. An input binding to the aptamer can cause the actuator to alter the RNA structure, thus changing access to translation machinery. The assembly of multiple RNA switches has led to complex gene circuits for cell therapies, including the selective killing of pathological cells and purification of cell populations. The inclusion of RNA binding proteins, such as L7Ae, increases the repertoire and precision of the circuit. In this short review, we discuss synthetic RNA switches for gene regulation and their potential therapeutic applications.

Biomolecular implementation of a quasi sliding mode feedback controller based on DNA strand displacement reactions

A fundamental aim of synthetic biology is to achieve the capability to design and implement robust embedded biomolecular feedback control circuits. An approach to realize this objective is to use abstract chemical reaction networks (CRNs) as a programming language for the design of complex circuits and networks. Here, we employ this approach to facilitate the implementation of a class of nonlinear feedback controllers based on sliding mode control theory. We show how a set of two-step irreversible reactions with ultrasensitive response dynamics can provide a biomolecular implementation of a nonlinear quasi sliding mode (QSM) controller. We implement our controller in closed-loop with a prototype of a biological pathway and demonstrate that the nonlinear QSM controller outperforms a traditional linear controller by facilitating faster tracking response dynamics without introducing overshoots in the transient response.

Multilevel Regulation and Translational Switches in Synthetic Biology

In contrast to the versatility of regulatory mechanisms in natural systems, synthetic genetic circuits have been so far predominantly composed of transcriptionally regulated modules. This is about to change as the repertoire of foundational tools for post-transcriptional regulation is quickly expanding. We provide an overview of the different types of translational regulators: protein, small molecule and ribonucleic acid (RNA) responsive and we describe the new emerging circuit designs utilizing these tools. There are several advantages of achieving multilevel regulation via translational switches and it is likely that such designs will have the greatest and earliest impact in mammalian synthetic biology for regenerative medicine and gene therapy applications.

Gene dosage imbalances: action, reaction, and models

Single-gene deletions, duplications, and misregulation, as well as aneuploidy, can lead to stoichiometric imbalances within macromolecular complexes and cellular networks, causing their malfunction. Such alterations can be responsible for inherited or somatic genetic disorders including Mendelian diseases, aneuploid syndromes, and cancer. We review the effects of gene dosage alterations at the transcriptomic and proteomic levels, and the various responses of the cell to counteract their effects. Furthermore, we explore several biochemical models and ideas that can provide the rationale for treatments modulating the effects of gene dosage imbalances.

Synthetic feedback control using an RNAi-based gene-regulatory device

Background

Homeostasis within mammalian cells is achieved through complex molecular networks that can respond to changes within the cell or the environment and regulate the expression of the appropriate genes in response. The development of biological components that can respond to changes in the cellular environment and interface with endogenous molecules would enable more sophisticated genetic circuits and greatly advance our cellular engineering capabilities.

Results

Here we describe a platform that combines a ligand-responsive ribozyme switch and synthetic miRNA regulators to create an OFF genetic control device based on RNA interference (RNAi). We developed a mathematical model to highlight important design parameters in programming the quantitative performance of RNAi-based OFF control devices. By modifying the ribozyme switch integrated into the system, we demonstrated RNAi-based OFF control devices that respond to small molecule and protein ligands, including the oncogenic protein E2F1. We utilized the OFF control device platform to build a negative feedback control system that acts as a proportional controller and maintains target intracellular protein levels in response to increases in transcription rate.

Conclusions

Our work describes a novel genetic device that increases the level of silencing from a miRNA in the presence of a ligand of interest, effectively creating an RNAi-based OFF control device. The OFF switch platform has the flexibility to be used to respond to both small molecule and protein ligands. Finally, the RNAi-based OFF switch can be used to implement a negative feedback control system, which maintains target protein levels around a set point level. The described RNAi-based OFF control device presents a powerful tool that will enable researchers to engineer homeostasis in mammalian cells.

Electronic supplementary material

The online version of this article (doi:10.1186/s13036-015-0002-3) contains supplementary material, which is available to authorized users.

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.