Synthetic biology moving into the clinic

Simulation Approach for Timing Analysis of Genetic Logic Circuits

Constructing genetic logic circuits is an application of synthetic biology in which parts of the DNA of a living cell are engineered to perform a dedicated Boolean function triggered by an appropriate concentration of certain proteins or by different genetic components. These logic circuits work in a manner similar to electronic logic circuits, but they are much more stochastic and hence much harder to characterize. In this article, we introduce an approach to analyze the threshold value and timing of genetic logic circuits. We show how this approach can be used to analyze the timing behavior of single and cascaded genetic logic circuits. We further analyze the timing sensitivity of circuits by varying the degradation rates and concentrations. Our approach can be used not only to characterize the timing behavior but also to analyze the timing constraints of cascaded genetic logic circuits, a capability that we believe will be important for design automation in synthetic biology.

Engineering Iron Responses in Mammalian Cells by Signal-Induced Protein Proximity

A new synthetic biology engineering strategy integrating chemical reactivity sensing and small molecule induced protein dimerization has been developed to generate artificial Fe²⁺ signaling circuitry to control tailored cellular events in mammalian cells. The dual function probe ABA-FE18 (Fe²⁺-sensing and protein dimerization) derived from ABA was developed and used to control gene activation, signal transduction, and cytoskeletal remodeling in response to Fe²⁺. This technology was utilized to design signal circuitry incorporating "AND" and "OR" biologic gates that enables mammalian cells to translate different combinations of Fe²⁺ and H₂O₂ signals into predefined biological outputs.

A Synthetic-Biology-Inspired Therapeutic Strategy for Targeting and Treating Hepatogenous Diabetes

Hepatogenous diabetes is a complex disease that is typified by the simultaneous presence of type 2 diabetes and many forms of liver disease. The chief pathogenic determinant in this pathophysiological network is insulin resistance (IR), an asymptomatic disease state in which impaired insulin signaling in target tissues initiates a variety of organ dysfunctions. However, pharmacotherapies targeting IR remain limited and are generally inapplicable for liver disease patients. Oleanolic acid (OA) is a plant-derived triterpenoid that is frequently used in Chinese medicine as a safe but slow-acting treatment in many liver disorders. Here, we utilized the congruent pharmacological activities of OA and glucagon-like-peptide 1 (GLP-1) in relieving IR and improving liver and pancreas functions and used a synthetic-biology-inspired design principle to engineer a therapeutic gene circuit that enables a concerted action of both drugs. In particular, OA-triggered short human GLP-1 (shGLP-1) expression in hepatogenous diabetic mice rapidly and simultaneously attenuated many disease-specific metabolic failures, whereas OA or shGLP-1 monotherapy failed to achieve corresponding therapeutic effects. Collectively, this work shows that rationally engineered synthetic gene circuits are capable of treating multifactorial diseases in a synergistic manner by multiplexing the targeting efficacies of single therapeutics.

A modular yeast biosensor for low-cost point-of-care pathogen detection

The availability of simple, specific, and inexpensive on-site detection methods is of key importance for deployment of pathogen surveillance networks. We developed a nontechnical and highly specific colorimetric assay for detection of pathogen-derived peptides based on Saccharomyces cerevisiae-a genetically tractable model organism and household product. Integrating G protein-coupled receptors with a visible, reagent-free lycopene readout, we demonstrate differential detection of major human, plant, and food fungal pathogens with nanomolar sensitivity. We further optimized a one-step rapid dipstick prototype that can be used in complex samples, including blood, urine, and soil. This modular biosensor can be economically produced at large scale, is not reliant on cold-chain storage, can be detected without additional equipment, and is thus a compelling platform scalable to global surveillance of pathogens.

Molecular Imaging in Synthetic Biology, and Synthetic Biology in Molecular Imaging

Biomedical synthetic biology is an emerging field in which cells are engineered at the genetic level to carry out novel functions with relevance to biomedical and industrial applications. This approach promises new treatments, imaging tools, and diagnostics for diseases ranging from gastrointestinal inflammatory syndromes to cancer, diabetes, and neurodegeneration. As these cellular technologies undergo pre-clinical and clinical development, it is becoming essential to monitor their location and function in vivo, necessitating appropriate molecular imaging strategies, and therefore, we have created an interest group within the World Molecular Imaging Society focusing on synthetic biology and reporter gene technologies. Here, we highlight recent advances in biomedical synthetic biology, including bacterial therapy, immunotherapy, and regenerative medicine. We then discuss emerging molecular imaging approaches to facilitate in vivo applications, focusing on reporter genes for noninvasive modalities such as magnetic resonance, ultrasound, photoacoustic imaging, bioluminescence, and radionuclear imaging. Because reporter genes can be incorporated directly into engineered genetic circuits, they are particularly well suited to imaging synthetic biological constructs, and developing them provides opportunities for creative molecular and genetic engineering.

CRISPR and the Rebirth of Synthetic Biology

Emergence of novel genome engineering technologies such as clustered regularly interspaced short palindromic repeat (CRISPR) has refocused attention on unresolved ethical complications of synthetic biology. Biosecurity concerns, deontological issues and human right aspects of genome editing have been the subject of in-depth debate; however, a lack of transparent regulatory guidelines, outdated governance codes, inefficient time-consuming clinical trial pathways and frequent misunderstanding of the scientific potential of cutting-edge technologies have created substantial obstacles to translational research in this area. While a precautionary principle should be applied at all stages of genome engineering research, the stigma of germline editing, synthesis of new life forms and unrealistic presentation of current technologies should not arrest the transition of new therapeutic, diagnostic or preventive tools from research to clinic. We provide a brief review on the present regulation of CRISPR and discuss the translational aspect of genome engineering research and patient autonomy with respect to the "right to try" potential novel non-germline gene therapies.

Autonomy and Fear of Synthetic Biology: How Can Patients' Autonomy Be Enhanced in the Field of Synthetic Biology? A Qualitative Study with Stable Patients

We analyzed stable patients' views regarding synthetic biology in general, the medical application of synthetic biology, and their potential participation in trials of synthetic biology in particular. The aim of the study was to find out whether patients' views and preferences change after receiving more detailed information about synthetic biology and its clinical applications. The qualitative study was carried out with a purposive sample of 36 stable patients, who suffered from diabetes or gout. Interviews were transcribed verbatim, translated and fully anonymized. Thematic analysis was applied in order to examine stable patients' attitudes towards synthetic biology, its medical application, and their participation in trials. When patients were asked about synthetic biology in general, most of them were anxious that something uncontrollable could be created. After a concrete example of possible future treatment options, patients started to see synthetic biology in a more positive way. Our study constitutes an important first empirical insight into stable patients' views on synthetic biology and into the kind of fears triggered by the term "synthetic biology." Our results show that clear and concrete information can change patients' initial negative feelings towards synthetic biology. Information should thus be transmitted with great accuracy and transparency in order to reduce irrational fears of patients and to minimize the risk that researchers present facts too positively for the purposes of persuading patients to participate in clinical trials. Potential participants need to be adequately informed in order to be able to autonomously decide whether to participate in human subject research involving synthetic biology.

Evolution of a split RNA polymerase as a versatile biosensor platform

Biosensors that transduce target chemical and biochemical inputs into genetic outputs are essential for bioengineering and synthetic biology. Current biosensor design strategies are often limited by a low signal-to-noise ratio, the extensive optimization required for each new input, and poor performance in mammalian cells. Here we report the development of a proximity-dependent split RNA polymerase (RNAP) as a general platform for biosensor engineering. After discovering that interactions between fused proteins modulate the assembly of a split T7 RNAP, we optimized the split RNAP components for protein-protein interaction detection by phage-assisted continuous evolution (PACE). We then applied the resulting activity-responsive RNAP (AR) system to create biosensors that can be activated by light and small molecules, demonstrating the 'plug-and-play' nature of the platform. Finally, we validated that ARs can interrogate multidimensional protein-protein interactions and trigger RNA nanostructure production, protein synthesis, and gene knockdown in mammalian systems, illustrating the versatility of ARs in synthetic biology applications.

A Synthetic Mammalian Therapeutic Gene Circuit for Sensing and Suppressing Inflammation

Inflammation, which is a highly regulated host response against danger signals, may be harmful if it is excessive and deregulated. Ideally, anti-inflammatory therapy should autonomously commence as soon as possible after the onset of inflammation, should be controllable by a physician, and should not systemically block beneficial immune response in the long term. We describe a genetically encoded anti-inflammatory mammalian cell device based on a modular engineered genetic circuit comprising a sensor, an amplifier, a "thresholder" to restrict activation of a positive-feedback loop, a combination of advanced clinically used biopharmaceutical proteins, and orthogonal regulatory elements that linked modules into the functional device. This genetic circuit was autonomously activated by inflammatory signals, including endogenous cecal ligation and puncture (CLP)-induced inflammation in mice and serum from a systemic juvenile idiopathic arthritis (sIJA) patient, and could be reset externally by a chemical signal. The microencapsulated anti-inflammatory device significantly reduced the pathology in dextran sodium sulfate (DSS)-induced acute murine colitis, demonstrating a synthetic immunological approach for autonomous anti-inflammatory therapy.

Self-adjusting synthetic gene circuit for correcting insulin resistance

By using tools from synthetic biology, sophisticated genetic devices can be assembled to reprogram mammalian cell activities. Here, we demonstrate that a self-adjusting synthetic gene circuit can be designed to sense and reverse the insulin-resistance syndrome in different mouse models. By functionally rewiring the mitogen-activated protein kinase (MAPK) signalling pathway to produce MAPK-mediated activation of the hybrid transcription factor TetR-ELK1, we assembled a synthetic insulin-sensitive transcription-control device that self-sufficiently distinguished between physiological and increased blood insulin levels and correspondingly fine-tuned the reversible expression of therapeutic transgenes from synthetic TetR-ELK1-specific promoters. In acute experimental hyperinsulinemia, the synthetic insulin-sensing designer circuit reversed the insulin-resistance syndrome by coordinating expression of the insulin-sensitizing compound adiponectin. Engineering synthetic gene circuits to sense pathologic markers and coordinate the expression of therapeutic transgenes may provide opportunities for future gene- and cell-based treatments of multifactorial metabolic disorders.

Engineering robust and tunable spatial structures with synthetic gene circuits

Controllable spatial patterning is a major goal for the engineering of biological systems. Recently, synthetic gene circuits have become promising tools to achieve the goal; however, they need to possess both functional robustness and tunability in order to facilitate future applications. Here we show that, by harnessing the dual signaling and antibiotic features of nisin, simple synthetic circuits can direct Lactococcus lactis populations to form programmed spatial band-pass structures that do not require fine-tuning and are robust against environmental and cellular context perturbations. Although robust, the patterns are highly tunable, with their band widths specified by the external nisin gradient and cellular nisin immunity. Additionally, the circuits can direct cells to consistently generate designed patterns, even when the gradient is driven by structured nisin-producing bacteria and the patterning cells are composed of multiple species. A mathematical model successfully reproduces all of the observed patterns. Furthermore, the circuits allow us to establish predictable structures of synthetic communities and controllable arrays of cellular stripes and spots in space. This study offers new synthetic biology tools to program spatial structures. It also demonstrates that a deep mining of natural functionalities of living systems is a valuable route to build circuit robustness and tunability.

Bacterial genome engineering and synthetic biology: combating pathogens

BACKGROUND

The emergence and prevalence of multidrug resistant (MDR) pathogenic bacteria poses a serious threat to human and animal health globally. Nosocomial infections and common ailments such as pneumonia, wound, urinary tract, and bloodstream infections are becoming more challenging to treat due to the rapid spread of MDR pathogenic bacteria. According to recent reports by the World Health Organization (WHO) and Centers for Disease Control and Prevention (CDC), there is an unprecedented increase in the occurrence of MDR infections worldwide. The rise in these infections has generated an economic strain worldwide, prompting the WHO to endorse a global action plan to improve awareness and understanding of antimicrobial resistance. This health crisis necessitates an immediate action to target the underlying mechanisms of drug resistance in bacteria.

RESEARCH

The advent of new bacterial genome engineering and synthetic biology (SB) tools is providing promising diagnostic and treatment plans to monitor and treat widespread recalcitrant bacterial infections. Key advances in genetic engineering approaches can successfully aid in targeting and editing pathogenic bacterial genomes for understanding and mitigating drug resistance mechanisms. In this review, we discuss the application of specific genome engineering and SB methods such as recombineering, clustered regularly interspaced short palindromic repeats (CRISPR), and bacterial cell-cell signaling mechanisms for pathogen targeting. The utility of these tools in developing antibacterial strategies such as novel antibiotic production, phage therapy, diagnostics and vaccine production to name a few, are also highlighted.

CONCLUSIONS

The prevalent use of antibiotics and the spread of MDR bacteria raise the prospect of a post-antibiotic era, which underscores the need for developing novel therapeutics to target MDR pathogens. The development of enabling SB technologies offers promising solutions to deliver safe and effective antibacterial therapies.

Synthetic biology platform technologies for antimicrobial applications

The growing prevalence of antibiotic resistance calls for new approaches in the development of antimicrobial therapeutics. Likewise, improved diagnostic measures are essential in guiding the application of targeted therapies and preventing the evolution of therapeutic resistance. Discovery platforms are also needed to form new treatment strategies and identify novel antimicrobial agents. By applying engineering principles to molecular biology, synthetic biologists have developed platforms that improve upon, supplement, and will perhaps supplant traditional broad-spectrum antibiotics. Efforts in engineering bacteriophages and synthetic probiotics demonstrate targeted antimicrobial approaches that can be fine-tuned using synthetic biology-derived principles. Further, the development of paper-based, cell-free expression systems holds promise in promoting the clinical translation of molecular biology tools for diagnostic purposes. In this review, we highlight emerging synthetic biology platform technologies that are geared toward the generation of new antimicrobial therapies, diagnostics, and discovery channels.

Upgrading biomaterials with synthetic biological modules for advanced medical applications

One key aspect of synthetic biology is the development and characterization of modular biological building blocks that can be assembled to construct integrated cell-based circuits performing computational functions. Likewise, the idea of extracting biological modules from the cellular context has led to the development of in vitro operating systems. This principle has attracted substantial interest to extend the repertoire of functional materials by connecting them with modules derived from synthetic biology. In this respect, synthetic biological switches and sensors, as well as biological targeting or structure modules, have been employed to upgrade functions of polymers and solid inorganic material. The resulting systems hold great promise for a variety of applications in diagnosis, tissue engineering, and drug delivery. This review reflects on the most recent developments and critically discusses challenges concerning in vivo functionality and tolerance that must be addressed to allow the future translation of such synthetic biology-upgraded materials from the bench to the bedside.

Grand challenges in space synthetic biology

Space synthetic biology is a branch of biotechnology dedicated to engineering biological systems for space exploration, industry and science. There is significant public and private interest in designing robust and reliable organisms that can assist on long-duration astronaut missions. Recent work has also demonstrated that such synthetic biology is a feasible payload minimization and life support approach as well. This article identifies the challenges and opportunities that lie ahead in the field of space synthetic biology, while highlighting relevant progress. It also outlines anticipated broader benefits from this field, because space engineering advances will drive technological innovation on Earth.

A Synthetic Multicellular Memory Device

Changing environments pose a challenge to living organisms. Cells need to gather and process incoming information, adapting to changes in predictable ways. This requires in particular the presence of memory, which allows different internal states to be stored. Biological memory can be stored by switches that retain information on past and present events. Synthetic biologists have implemented a number of memory devices for biological applications, mostly in single cells. It has been shown that the use of multicellular consortia provides interesting advantages to implement biological circuits. Here we show how to build a synthetic biological memory switch using an eukaryotic consortium. We engineered yeast cells that can communicate and retain memory of changes in the extracellular environment. These cells were able to produce and secrete a pheromone and sense a different pheromone following NOT logic. When the two strains were cocultured, they behaved as a double-negative-feedback motif with memory. In addition, we showed that memory can be effectively changed by the use of external inputs. Further optimization of these modules and addition of other cells could lead to new multicellular circuits that exhibit memory over a broad range of biological inputs.

Synchronized cycles of bacterial lysis for in vivo delivery

The pervasive view of bacteria as strictly pathogenic has given way to an appreciation of the widespread prevalence of beneficial microbes within the human body^1–3. Given this milieu, it is perhaps inevitable that some bacteria would evolve to preferentially grow in environments that harbor disease and thus provide a natural platform for the development of engineered therapies^4–6. Such therapies could benefit from bacteria that are programmed to limit bacterial growth while continually producing and releasing cytotoxic agents in situ^7–10. Here, we engineer a clinically relevant bacterium to lyse synchronously at a threshold population density and to release genetically encoded cargo. Following quorum lysis, a small number of surviving bacteria reseed the growing population, thus leading to pulsatile delivery cycles. We use microfluidic devices to characterize the engineered lysis strain and we demonstrate its potential as a drug delivery platform via co-culture with human cancer cells in vitro. As a proof of principle, we track the bacterial population dynamics in ectopic syngeneic colorectal tumors in mice. The lysis strain exhibits pulsatile population dynamics in vivo, with mean bacterial luminescence that remained two orders of magnitude lower than an unmodified strain. Finally, guided by previous findings that certain bacteria can enhance the efficacy of standard therapies¹¹, we orally administer the lysis strain, alone or in combination with a clinical chemotherapeutic, to a syngeneic transplantation model of hepatic colorectal metastases. We find that the combination of both circuit-engineered bacteria and chemotherapy leads to a notable reduction of tumor activity along with a marked survival benefit over either therapy alone. Our approach establishes a methodology for leveraging the tools of synthetic biology to exploit the natural propensity for certain bacteria to colonize disease sites.

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.

Repurposing a Prokaryotic Toxin-Antitoxin System for the Selective Killing of Oncogenically Stressed Human Cells

Prokaryotes express intracellular toxins that pass unnoticed to carrying cells until coexpressed antitoxin partners are degraded in response to stress. Although not evolved to function in eukaryotes, one of these toxins, Kid, induces apoptosis in mammalian cells, an effect that is neutralized by its cognate antitoxin, Kis. Here we engineered this toxin-antitoxin pair to create a synthetic system that becomes active in human cells suffering a specific oncogenic stress. Inspired by the way Kid becomes active in bacterial cells, we produced a Kis variant that is selectively degraded in human cells expressing oncoprotein E6. The resulting toxin-antitoxin system functions autonomously in human cells, distinguishing those that suffer the oncogenic insult, which are killed by Kid, from those that do not, which remain protected by Kis. Our results provide a framework for developing personalized anticancer strategies avoiding off-target effects, a challenge that has been hardly tractable by other means thus far.

Engineering a Chemical Switch into the Light-driven Proton Pump Proteorhodopsin by Cysteine Mutagenesis and Thiol Modification

For applications in synthetic biology, for example, the bottom-up assembly of biomolecular nanofactories, modules of specific and controllable functionalities are essential. Of fundamental importance in such systems are energizing modules, which are able to establish an electrochemical gradient across a vesicular membrane as an energy source for powering other modules. Light-driven proton pumps like proteorhodopsin (PR) are excellent candidates for efficient energy conversion. We have extended the versatility of PR by implementing an on/off switch based on reversible chemical modification of a site-specifically introduced cysteine residue. The position of this cysteine residue in PR was identified by structure-based cysteine mutagenesis combined with a proton-pumping assay using E. coli cells overexpressing PR and PR proteoliposomes. The identified PR mutant represents the first light-driven proton pump that can be chemically switched on/off depending on the requirements of the molecular system.

Molecular circuits for dynamic noise filtering

The invention of the Kalman filter is a crowning achievement of filtering theory-one that has revolutionized technology in countless ways. By dealing effectively with noise, the Kalman filter has enabled various applications in positioning, navigation, control, and telecommunications. In the emerging field of synthetic biology, noise and context dependency are among the key challenges facing the successful implementation of reliable, complex, and scalable synthetic circuits. Although substantial further advancement in the field may very well rely on effectively addressing these issues, a principled protocol to deal with noise-as provided by the Kalman filter-remains completely missing. Here we develop an optimal filtering theory that is suitable for noisy biochemical networks. We show how the resulting filters can be implemented at the molecular level and provide various simulations related to estimation, system identification, and noise cancellation problems. We demonstrate our approach in vitro using DNA strand displacement cascades as well as in vivo using flow cytometry measurements of a light-inducible circuit in Escherichia coli.

Genetic circuit design automation

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

Detection of pathological biomarkers in human clinical samples via amplifying genetic switches and logic gates

Whole-cell biosensors have several advantages for the detection of biological substances and have proven to be useful analytical tools. However, several hurdles have limited whole-cell biosensor application in the clinic, primarily their unreliable operation in complex media and low signal-to-noise ratio. We report that bacterial biosensors with genetically encoded digital amplifying genetic switches can detect clinically relevant biomarkers in human urine and serum. These bactosensors perform signal digitization and amplification, multiplexed signal processing with the use of Boolean logic gates, and data storage. In addition, we provide a framework with which to quantify whole-cell biosensor robustness in clinical samples together with a method for easily reprogramming the sensor module for distinct medical detection agendas. Last, we demonstrate that bactosensors can be used to detect pathological glycosuria in urine from diabetic patients. These next-generation whole-cell biosensors with improved computing and amplification capacity could meet clinical requirements and should enable new approaches for medical diagnosis.

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

Spatiotemporal dynamics of distributed synthetic genetic circuits

We propose and study models of two distributed synthetic gene circuits, toggle-switch and oscillator, each split between two cell strains and coupled via quorum-sensing signals. The distributed toggle switch relies on mutual repression of the two strains, and oscillator is comprised of two strains, one of which acts as an activator for another that in turn acts as a repressor. Distributed toggle switch can exhibit mobile fronts, switching the system from the weaker to the stronger spatially homogeneous state. The circuit can also act as a biosensor, with the switching front dynamics determined by the properties of an external signal. Distributed oscillator system displays another biosensor functionality: oscillations emerge once a small amount of one cell strain appears amid the other, present in abundance. Distribution of synthetic gene circuits among multiple strains allows one to reduce crosstalk among different parts of the overall system and also decrease the energetic burden of the synthetic circuit per cell, which may allow for enhanced functionality and viability of engineered cells.

Gastrointestinal Microbiota and Colon Cancer

The human gut microbiota plays a major role in the development and maintenance of good health. Many recent studies have attempted to define links between microbiota residents, their function and the development of colorectal cancer (CRC). Gut microbiota drive the development of inflammation within the colon and such inflammation is implicated in colonic neoplastic development. Although the precise mechanisms through which the microbiota is involved in cancer development remain elusive, the message is clear: the microbiota contributes to cancer risk by influencing a number of key host processes. It is also recognized that we have the ability to influence the role of the gut microbiota by considering our nutritional intake. We have always known that 'we are what we eat' but it is also true that 'they (our gut microbiota) are what we eat'. We therefore have a huge opportunity to positively influence our health through microbial manipulation. There is now a clear need to move past defining the constituents of the gastrointestinal microbiota and to focus more on understanding the functional capabilities of the resident microbial community and how this impacts on host health. One such emerging concept is the development of microbial biofilms which can form in the gut in conjunction with CRC tissue. By better understanding of the interaction between the host and its resident microbiota, in the context of health and cancer development, we will open new therapeutic and diagnostic opportunities for reducing the CRC global health burden.

Circumvention of Learning Increases Intoxication Efficacy of Nematicidal Engineered Bacteria

Synthetic biology holds promise to engineer systems to treat diseases. One critical, yet underexplored, facet of designing such systems is the interplay between the system and the pathogen. Understanding this interplay may be critical to increasing efficacy and overcoming resistance against the system. Using the principles of synthetic biology, we engineer a strain of Escherichia coli to attract and intoxicate the nematode Caenorhabditis elegans. Our bacteria are engineered with a toxin module, which intoxicates the nematode upon ingestion, and an attraction module, which serves to attract and increase the feeding rate of the nematodes. When independently implemented, these modules successfully intoxicate and attract the worms, respectively. However, in combination, the efficacy of our bacteria is significantly reduced due to aversive associative learning in C. elegans. Guided by mathematical modeling, we dynamically regulate module induction to increase intoxication by circumventing learning. Our results detail the creation of a novel nematicidal bacterium that may have application against nematodes, unravel unique constraints on circuit dynamics that are governed by C. elegans physiology, and add to the growing list of design and implementation considerations associated with synthetic biology.

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.

A gene network engineering platform for lactic acid bacteria

Recent developments in synthetic biology have positioned lactic acid bacteria (LAB) as a major class of cellular chassis for applications. To achieve the full potential of LAB, one fundamental prerequisite is the capacity for rapid engineering of complex gene networks, such as natural biosynthetic pathways and multicomponent synthetic circuits, into which cellular functions are encoded. Here, we present a synthetic biology platform for rapid construction and optimization of large-scale gene networks in LAB. The platform involves a copy-controlled shuttle for hosting target networks and two associated strategies that enable efficient genetic editing and phenotypic validation. By using a nisin biosynthesis pathway and its variants as examples, we demonstrated multiplex, continuous editing of small DNA parts, such as ribosome-binding sites, as well as efficient manipulation of large building blocks such as genes and operons. To showcase the platform, we applied it to expand the phenotypic diversity of the nisin pathway by quickly generating a library of 63 pathway variants. We further demonstrated its utility by altering the regulatory topology of the nisin pathway for constitutive bacteriocin biosynthesis. This work demonstrates the feasibility of rapid and advanced engineering of gene networks in LAB, fostering their applications in biomedicine and other areas.

Coupling spatial segregation with synthetic circuits to control bacterial survival

Engineered bacteria have great potential for medical and environmental applications. Fulfilling this potential requires controllability over engineered behaviors and scalability of the engineered systems. Here, we present a platform technology, microbial swarmbot, which employs spatial arrangement to control the growth dynamics of engineered bacteria. As a proof of principle, we demonstrated a safeguard strategy to prevent unintended bacterial proliferation. In particular, we adopted several synthetic gene circuits to program collective survival in Escherichia coli: the engineered bacteria could only survive when present at sufficiently high population densities. When encapsulated by permeable membranes, these bacteria can sense the local environment and respond accordingly. The cells inside the microbial swarmbot capsules will survive due to their high densities. Those escaping from a capsule, however, will be killed due to a decrease in their densities. We demonstrate that this design concept is modular and readily generalizable. Our work lays the foundation for engineering integrated and programmable control of hybrid biological–material systems for diverse applications.

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.

gEFM: An Algorithm for Computing Elementary Flux Modes Using Graph Traversal

Computational methods to engineer cellular metabolism promise to play a critical role in producing pharmaceutical, repairing defective genes, destroying cancer cells, and generating biofuels. Elementary Flux Mode (EFM) analysis is one such powerful technique that has elucidated cell growth and regulation, predicted product yield, and analyzed network robustness. EFM analysis, however, is a computationally daunting task because it requires the enumeration of all independent and stoichiometrically balanced pathways within a cellular network. We present in this paper an EFM enumeration algorithm, termed graphical EFM or gEFM. The algorithm is based on graph traversal, an approach previously assumed unsuitable for enumerating EFMs. The approach is derived from a pathway synthesis method proposed by Mavrovouniotis et al. The algorithm is described and proved correct. We apply gEFM to several networks and report runtimes in comparison with other EFM computation tools. We show how gEFM benefits from network compression. Like other EFM computational techniques, gEFM is sensitive to constraint ordering; however, we are able to demonstrate that knowledge of the underlying network structure leads to better constraint ordering. gEFM is shown to be competitive with state-of-the-art EFM computational techniques for several networks, but less so for networks with a larger number of EFMs.

Harbouring public good mutants within a pathogen population can increase both fitness and virulence

Existing theory, empirical, clinical and field research all predict that reducing the virulence of individuals within a pathogen population will reduce the overall virulence, rendering disease less severe. Here, we show that this seemingly successful disease management strategy can fail with devastating consequences for infected hosts. We deploy cooperation theory and a novel synthetic system involving the rice blast fungus Magnaporthe oryzae. In vivo infections of rice demonstrate that M. oryzae virulence is enhanced, quite paradoxically, when a public good mutant is present in a population of high-virulence pathogens. We reason that during infection, the fungus engages in multiple cooperative acts to exploit host resources. We establish a multi-trait cooperation model which suggests that the observed failure of the virulence reduction strategy is caused by the interference between different social traits. Multi-trait cooperative interactions are widespread, so we caution against the indiscriminant application of anti-virulence therapy as a disease-management strategy.

A synthetic mammalian network to compute population borders based on engineered reciprocal cell-cell communication

Background

Multicellular organisms depend on the exchange of information between specialized cells. This communication is often difficult to decipher in its native context, but synthetic biology provides tools to engineer well-defined systems that allow the convenient study and manipulation of intercellular communication networks.

Results

Here, we present the first mammalian synthetic network for reciprocal cell-cell communication to compute the border between a sender/receiver and a processing cell population. The two populations communicate via L-tryptophan and interleukin-4 to highlight the population border by the production of a fluorescent protein. The sharpness of that visualized edge can be adjusted by modulating key parameters of the network.

Conclusions

We anticipate that this network will on the one hand be a useful tool to gain deeper insights into the mechanisms of tissue formation in nature and will on the other hand contribute to our ability to engineer artificial tissues.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0252-1) contains supplementary material, which is available to authorized users.

A Panel of Protease-Responsive RNA Polymerases Respond to Biochemical Signals by Production of Defined RNA Outputs in Live Cells

RNA is an attractive biomolecule for biosensing and engineering applications due to its information storage capacity and ability to drive gene expression or knockdown. However, methods to link chemical signals to the production of specific RNAs are lacking. Here, we develop protease-responsive RNA polymerases (PRs) as a strategy to encode multiple specific proteolytic events in defined sequences of RNA in live mammalian cells. This work demonstrates that RNAP-based molecular recording devices can be deployed for multimodal analyses of biochemical activities or to trigger gene circuits using measured signaling events.

Implantable synthetic cytokine converter cells with AND-gate logic treat experimental psoriasis

Psoriasis is a chronic inflammatory skin disease characterized by a relapsing-remitting disease course and correlated with increased expression of proinflammatory cytokines, such as tumor necrosis factor (TNF) and interleukin 22 (IL22). Psoriasis is hard to treat because of the unpredictable and asymptomatic flare-up, which limits handling of skin lesions to symptomatic treatment. Synthetic biology-based gene circuits are uniquely suited for the treatment of diseases with complex dynamics, such as psoriasis, because they can autonomously couple the detection of disease biomarkers with the production of therapeutic proteins. We designed a mammalian cell synthetic cytokine converter that quantifies psoriasis-associated TNF and IL22 levels using serially linked receptor-based synthetic signaling cascades, processes the levels of these proinflammatory cytokines with AND-gate logic, and triggers the corresponding expression of therapeutic levels of the anti-inflammatory/psoriatic cytokines IL4 and IL10, which have been shown to be immunomodulatory in patients. Implants of microencapsulated cytokine converter transgenic designer cells were insensitive to simulated bacterial and viral infections as well as psoriatic-unrelated inflammation. The designer cells specifically prevented the onset of psoriatic flares, stopped acute psoriasis, improved psoriatic skin lesions and restored normal skin-tissue morphology in mice. The antipsoriatic designer cells were equally responsive to blood samples from psoriasis patients, suggesting that the synthetic cytokine converter captures the clinically relevant cytokine range. Implanted designer cells that dynamically interface with the patient's metabolism by detecting specific disease metabolites or biomarkers, processing their blood levels with synthetic circuits in real time, and coordinating immediate production and systemic delivery of protein therapeutics may advance personalized gene- and cell-based therapies.

Synthetic Tet-inducible small hairpin RNAs targeting hTERT or Bcl-2 inhibit malignant phenotypes of bladder cancer T24 and 5637 cells

Small hairpin RNA (shRNA) can inhibit the malignant phenotypes of tumor cell through ribonucleic acid interference (RNAi). However, it is hardly to be regulated and it may induce few phenotypic changes. Here, we build a type of tetracycline (Tet)-inducible vectors which can achieve regulatable expression of shRNA in a time-dependent manner by using synthetic biology approach. In order to prove the effectiveness of this device, we chose hTERT and Bcl-2 as target genes and test the utility of the device on 5637 and T24 cell lines. The experiments show that the Tet-inducible small hairpin RNA can effectively suppress their target genes and generate anti-cancer effects on both 5637 and T24 cell lines. The device we build not only can inhibit proliferation but also can induce apoptosis and suppress migration of the bladder cancer cell lines 5637 and T24. The Tet-inducible small hairpin RNAs may provide a novel strategy for the treatment of human bladder cancer in the future.

Human Microbiome Engineering: The Future and Beyond

Microbial flora of skin and mucosal surface are vital component of human biology. Current research indicates that this microbial constellation, rather than being inert commensals, has greater implications in health and disease. They play essential role in metabolism, immunity, inflammation, neuro-endocrine regulation and even moderate host response to cancer. Genetic engineering was a major breakthrough in medical research in 1970's and it opened up newer dimensions in vaccinology, large-scale synthesis of bio-molecule and drug development. Engineering human microbiome is a novel concept. Recombinant DNA technology can be employed to modify the genome of critical components of resident microflora to achieve unprecedented goals.

Dynamical disease: Challenges for nonlinear dynamics and medicine

Dynamical disease refers to illnesses that are associated with striking changes in the dynamics of some bodily function. There is a large literature in mathematics and physics which proposes mathematical models for the physiological systems and carries out analyses of the properties of these models using nonlinear dynamics concepts involving analyses of the stability and bifurcations of attractors. This paper discusses how these concepts can be applied to medicine.

Decoding genome-wide GadEWX-transcriptional regulatory networks reveals multifaceted cellular responses to acid stress in Escherichia coli

The regulators GadE, GadW and GadX (which we refer to as GadEWX) play a critical role in the transcriptional regulation of the glutamate-dependent acid resistance (GDAR) system in Escherichia coli K-12 MG1655. However, the genome-wide regulatory role of GadEWX is still unknown. Here we comprehensively reconstruct the genome-wide GadEWX transcriptional regulatory network and RpoS involvement in E. coli K-12 MG1655 under acidic stress. Integrative data analysis reveals that GadEWX regulons consist of 45 genes in 31 transcription units and 28 of these genes were associated with RpoS-binding sites. We demonstrate that GadEWX directly and coherently regulate several proton-generating/consuming enzymes with pairs of negative-feedback loops for pH homeostasis. In addition, GadEWX regulate genes with assorted functions, including molecular chaperones, acid resistance, stress response and other regulatory activities. These results show how GadEWX simultaneously coordinate many cellular processes to produce the overall response of E. coli to acid stress.

GadEWX regulons play a critical role in transcription regulation in response to acid stress. By reconstructing genome-wide GadEWX transcriptional network, here the authors show how GadEWX simultaneously coordinates many other cellular processes to produce the overall response of E. coli to acid stress.

Exploring Host-Microbiome Interactions using an in Silico Model of Biomimetic Robots and Engineered Living Cells

The microbiome's underlying dynamics play an important role in regulating the behavior and health of its host. In order to explore the details of these interactions, we created an in silico model of a living microbiome, engineered with synthetic biology, that interfaces with a biomimetic, robotic host. By analytically modeling and computationally simulating engineered gene networks in these commensal communities, we reproduced complex behaviors in the host. We observed that robot movements depended upon programmed biochemical network dynamics within the microbiome. These results illustrate the model's potential utility as a tool for exploring inter-kingdom ecological relationships. These systems could impact fields ranging from synthetic biology and ecology to biophysics and medicine.

Engineered Phagemids for Nonlytic, Targeted Antibacterial Therapies

The increasing incidence of antibiotic-resistant bacterial infections is creating a global public health threat. Because conventional antibiotic drug discovery has failed to keep pace with the rise of resistance, a growing need exists to develop novel antibacterial methodologies. Replication-competent bacteriophages have been utilized in a limited fashion to treat bacterial infections. However, this approach can result in the release of harmful endotoxins, leading to untoward side effects. Here, we engineer bacterial phagemids to express antimicrobial peptides (AMPs) and protein toxins that disrupt intracellular processes, leading to rapid, nonlytic bacterial death. We show that this approach is highly modular, enabling one to readily alter the number and type of AMPs and toxins encoded by the phagemids. Furthermore, we demonstrate the effectiveness of engineered phagemids in an in vivo murine peritonitis infection model. This work shows that targeted, engineered phagemid therapy can serve as a viable, nonantibiotic means to treat bacterial infections, while avoiding the health issues inherent to lytic and replicative bacteriophage use.