SynBioFromLeukipposInstitute

Living organisms employ endogenous negative feedback loops to maintain homeostasis despite environmental fluctuations. A pressing open challenge in Synthetic Biology is to design and implement synthetic circuits to control host cells' behavior, in order to regulate and maintain desired conditions. To cope with the high degree of circuit complexity required to accomplish this task and the intrinsic modularity of classical control schemes, we suggest the implementation of synthetic endogenous feedback loops across more than one cell population. The distribution of the sensing, computation, and actuation functions required to achieve regulation across different cell populations within a consortium allows the genetic engineering in a particular cell to be reduced, increases the robustness, and makes it possible to reuse the synthesized modules for different control applications. Here, we analyze, in-silico, the design of a synthetic feedback controller implemented across two cell populations in a consortium. We study the effects of distributing the various functions required to build a control system across two populations, prove the robustness and modularity of the strategy described, and provide a computational proof-of-concept of its feasibility.

Synthetic biology has seen an explosive growth in the capability of engineering artificial gene circuits from transcription factors (TFs), particularly in bacteria. However, most artificial networks still employ the same core set of TFs (for example LacI, TetR and cI). The TFs mostly function via repression and it is difficult to integrate multiple inputs in promoter logic. Here we present to our knowledge the first set of dual activator-repressor switches for orthogonal logic gates, based on bacteriophage λ cI variants and multi-input promoter architectures. Our toolkit contains 12 TFs, flexibly operating as activators, repressors, dual activator-repressors or dual repressor-repressors, on up to 270 synthetic promoters. To engineer non cross-reacting cI variants, we design a new M13 phagemid-based system for the directed evolution of biomolecules. Because cI is used in so many synthetic biology projects, the new set of variants will easily slot into the existing projects of other groups, greatly expanding current engineering capacities.

In diabetes, cells in the pancreas called β cells are either absent or do not produce the correct amount of insulin to regulate blood glucose levels. Jörg Stelling and Martin Fussenegger at the Swiss Federal Institute of Technology Zurich in Basel and their colleagues genetically modified human kidney cells to enable the cells to detect blood glucose levels and produce an appropriate amount of either insulin or another hormone called GLP-1, which stimulates insulin production. The cells brought blood sugar levels down to normal when implanted into mice with type 1 or type 2 diabetes, without notable adverse effects.

Several high value added therapeutic biomolecules and their precursors exist in nature but yet to be discovered to fight against severe deadly diseases. Rapid emergence of drug resistance phenomena creates additional alarming situation and driving force to alleviate novel drug discoveries as earliest. Microscopic bugs, animals, and medicinal plants are the major source of novel therapeutic biomolecules generations following extraction, characterization, screening, and large scale production. However, conventional methodologies have not yet been shown great efficacy to generate novel drugs as far economical and industrial standpoints. To this end, the current review has shown a promising route that is combinatorial approach of synthetic biology and metabolic engineering for novel drug discovery. Though synthetic microbial metabolism is in its infancy but holds an enormous potential to battle against antibiotic resistance via providing high value added therapeutic biomolecules in near future. In conclusion, synthetic biology and metabolic engineering could be a potential avenue for novel drugs generations.

Synthetic biology envisages the engineering of man-made living biomachines from standardized components that can perform pre-defined functions in a (self-)controlled manner. Different research strategies and interdisciplinary efforts are pursued to implement engineering principles to biology. The "top-down" strategy exploits nature's incredible diversity of existing, natural parts to construct synthetic compositions of genetic, metabolic or signalling networks with predictable and controllable properties. This mainly application-driven approach results in living factories that produce drugs, biofuels, biomaterials and fine chemicals and results in living pills that are based on engineered cells with the capacity to autonomously detect and treat disease states in vivo. In contrast, the "bottom-up" strategy seeks to be independent of existing living systems by designing biological systems from scratch and synthesizing artificial biological entities not found in nature. This more knowledge-driven approach investigates the reconstruction of minimal biological systems that are capable of performing basic biological phenomena, such as self-organization, self-replication and self-sustainability. Moreover, the syntheses of artificial biological units, such as synthetic nucleotides or amino acids, and their implementation into polymers inside living cells currently set the boundaries between natural and artificial biological systems. In particular, the in vitro design, synthesis and transfer of complete genomes into host cells and the application of efficient genome-wide intervention techniques point to the future of synthetic biology: the creation of living designer cells with tailored desirable properties for biomedicine and biotechnology.

Engineered T cells are currently in clinical trials to treat patients with cancer, solid organ transplants, and autoimmune diseases. However, the field is still in its infancy. The design, and manufacturing, of T cell therapies is not standardized and is performed mostly in academic settings by competing groups. Reliable methods to define dose and pharmacokinetics of T cell therapies need to be developed. As of mid-2016, there are no US Food and Drug Administration (FDA)-approved T cell therapeutics on the market, and FDA regulations are only slowly adapting to the new technologies. Further development of engineered T cell therapies requires advances in immunology, synthetic biology, manufacturing processes, and government regulation. In this review, we outline some of these challenges and discuss the contributions that pathologists can make to this emerging field.

Genetic switches exhibit multistability, form the basis of epigenetic memory, and are found in natural decision making systems, such as cell fate determination in developmental pathways. Synthetic genetic switches can be used for recording the presence of different environmental signals, for changing phenotype using synthetic inputs and as building blocks for higher-level sequential logic circuits. Understanding how multistable switches can be constructed and how they function within larger biological systems is therefore key to synthetic biology.
RESULTS:
Here we present a new computational tool, called StabilityFinder, that takes advantage of sequential Monte Carlo methods to identify regions of parameter space capable of producing multistable behaviour, while handling uncertainty in biochemical rate constants and initial conditions. The algorithm works by clustering trajectories in phase space, and iteratively minimizing a distance metric. Here we examine a collection of models of genetic switches, ranging from the deterministic Gardner toggle switch to stochastic models containing different positive feedback connections. We uncover the design principles behind making bistable, tristable and quadristable switches, and find that rate of gene expression is a key parameter. We demonstrate the ability of the framework to examine more complex systems and examine the design principles of a three gene switch. Our framework allows us to relax the assumptions that are often used in genetic switch models and we show that more complex abstractions are still capable of multistable behaviour.
CONCLUSIONS:
Our results suggest many ways in which genetic switches can be enhanced and offer designs for the construction of novel switches. Our analysis also highlights subtle changes in correlation of experimentally tunable parameters that can lead to bifurcations in deterministic and stochastic systems. Overall we demonstrate that StabilityFinder will be a valuable tool in the future design and construction of novel gene networks.

The use of lead in manufacturing has decreased significantly over the last few decades. However, previous widespread use of lead-containing products and their incorrect disposal has resulted in environmental contamination. Accumulation of harmful quantities of lead pose a threat to all living organisms, through inhalation, ingestion, or direct contact, resulting in lead poisoning. This study utilized synthetic biology principles to develop plasmid-based whole-cell bacterial biosensors for detection of lead. The genetic element of the lead biosensor construct consists of pbrR, which encodes the regulatory protein, together with its divergent promoter region and a promoterless gfp. GFP expression is controlled by PbrR in response to the presence of lead. The lead biosensor genetic element was cloned onto a low-copy number broad host range plasmid, which can stably exist in a range of laboratory and environmental isolates, including Pseudomonas, Shewanella, and Enterobacter. The biosensors constructed were found to be sensitive, rapid, and specific and could, as such, serve as monitoring tools for lead-contaminated water.

From cyanobacteria to human, sustained oscillations coordinate important biological functions. Although much has been learned concerning the sophisticated molecular mechanisms underlying biological oscillators, design principles linking structure and functional behavior are not yet fully understood. Here we explore design principles of biological oscillators from a multiobjective optimization perspective, taking into account the trade-offs between conflicting performance goals or demands. We develop a comprehensive tool for automated design of oscillators, based on multicriteria global optimization that allows two modes: (i) the automatic design (forward problem) and (ii) the inference of design principles (reverse analysis problem). From the perspective of synthetic biology, the forward mode allows the solution of design problems that mimic some of the desirable properties appearing in natural oscillators. The reverse analysis mode facilitates a systematic exploration of the design space based on Pareto optimality concepts. The method is illustrated with two case studies: the automatic design of synthetic oscillators from a library of biological parts, and the exploration of design principles in 3-gene oscillatory systems.

To achieve synthetic control over how a cell responds to other cells or the extracellular environment, it is important to reliably engineer proteins that can traffic and span the plasma membrane. Using a modular approach to assemble proteins, we identified the minimum necessary components required to engineer such membrane-spanning proteins with predictable orientation in mammalian cells.
RESULTS:
While a transmembrane domain (TM) fused to the N-terminus of a protein is sufficient to traffic it to the endoplasmic reticulum (ER), an additional signal peptidase cleavage site downstream of this TM enhanced sorting out of the ER. Next, a second TM in the synthetic protein helped anchor and accumulate the membrane-spanning protein on the plasma membrane. The orientation of the components of the synthetic protein were determined through measuring intracellular Ca2+ signaling using the R-GECO biosensor and through measuring extracellular quenching of yellow fluorescent protein variants by saturating acidic and salt conditions.
CONCLUSIONS:
This work forms the basis of engineering novel proteins that span the plasma membrane to potentially control intracellular responses to extracellular conditions.

Recent developments in synthetic biology enable one-step implementation of entire metabolic pathways in industrial microorganisms. A similarly radical remodelling of central metabolism could greatly accelerate fundamental and applied research, but is impeded by the mosaic organization of microbial genomes. To eliminate this limitation, we propose and explore the concept of "pathway swapping," using yeast glycolysis as the experimental model. Construction of a "single-locus glycolysis" Saccharomyces cerevisiae platform enabled quick and easy replacement of this yeast's entire complement of 26 glycolytic isoenzymes by any alternative, functional glycolytic pathway configuration. The potential of this approach was demonstrated by the construction and characterization of S. cerevisiae strains whose growth depended on two nonnative glycolytic pathways: a complete glycolysis from the related yeast Saccharomyces kudriavzevii and a mosaic glycolysis consisting of yeast and human enzymes. This work demonstrates the feasibility and potential of modular, combinatorial approaches to engineering and analysis of core cellular processes.

The 30 years since the inception of Chemical Research in Toxicology, game-changing advances in chemical and molecular biology, the fundamental disciplines underpinning molecular toxicology, have been made. While these have led to important advances in the study of mechanisms by which chemicals damage cells and systems, there has been less focus on applying these advances to prediction, detection, and mitigation of toxicity. Over the last ∼15 years, synthetic biology, the repurposing of biological "parts" in systems engineered for useful ends, has been explored in other areas of the biomedical and life sciences, for such applications as detecting metabolites, drug discovery and delivery, investigating disease mechanisms, improving medical treatment, and producing useful chemicals. These examples provide models for the application of synthetic biology to toxicology, which, for the most part, has not yet benefited from such approaches. In this perspective, we review the synthetic biology approaches that have been applied to date and speculate on possible short to medium term and "blue sky" aspirations for synthetic biology, particularly in clinical and environmental toxicology. Finally, we point out key hurdles that must be overcome for the full potential of synthetic biology to be realized.