From DNA to targeted therapeutics: bringing synthetic biology to the clinic

Multicellular artificial neural network-type architectures demonstrate computational problem solving

Here, we report a modular multicellular system created by mixing and matching discrete engineered bacterial cells. This system can be designed to solve multiple computational decision problems. The modular system is based on a set of engineered bacteria that are modeled as an 'artificial neurosynapse' that, in a coculture, formed a single-layer artificial neural network-type architecture that can perform computational tasks. As a demonstration, we constructed devices that function as a full subtractor and a full adder. The system is also capable of solving problems such as determining if a number between 0 and 9 is a prime number and if a letter between A and L is a vowel. Finally, we built a system that determines the maximum number of pieces of a pie that can be made for a given number of straight cuts. This work may have importance in biocomputer technology development and multicellular synthetic biology.

Implementing re-configurable biological computation with distributed multicellular consortia

The use of synthetic biological circuits to deal with numerous biological challenges has been proposed in several studies, but its implementation is still remote. A major problem encountered is the complexity of the cellular engineering needed to achieve complex biological circuits and the lack of general-purpose biological systems. The generation of re-programmable circuits can increase circuit flexibility and the scalability of complex cell-based computing devices. Here we present a new architecture to produce reprogrammable biological circuits that allow the development of a variety of different functions with minimal cell engineering. We demonstrate the feasibility of creating several circuits using only a small set of engineered cells, which can be externally reprogrammed to implement simple logics in response to specific inputs. In this regard, depending on the computation needs, a device composed of a number of defined cells can generate a variety of circuits without the need of further cell engineering or rearrangements. In addition, the inclusion of a memory module in the circuits strongly improved the digital response of the devices. The reprogrammability of biological circuits is an intrinsic capacity that is not provided in electronics and it may be used as a tool to solve complex biological problems.

Engineering mammalian living materials towards clinically relevant therapeutics

Engineered living materials represent a new generation of human-made biotherapeutics that are highly attractive for a myriad of medical applications. In essence, such cell-rich platforms provide encodable bioactivities with extended lifetimes and environmental multi-adaptability currently unattainable in conventional biomaterial platforms. Emerging cell bioengineering tools are herein discussed from the perspective of materializing living cells as cooperative building blocks that drive the assembly of multiscale living materials. Owing to their living character, pristine cellular units can also be imparted with additional therapeutically-relevant biofunctionalities. On this focus, the most recent advances on the engineering of mammalian living materials and their biomedical applications are herein outlined, alongside with a critical perspective on major roadblocks hindering their realistic clinical translation. All in all, transposing the concept of leveraging living materials as autologous tissue-building entities and/or self-regulated biotherapeutics opens new realms for improving precision and personalized medicine strategies in the foreseeable future.

Emerging regulatory challenges of next-generation synthetic biology

Cell-free synthetic biology is a rapidly developing biotechnology with the potential to solve the world's biggest problems; however, this promise also has implications for global biosecurity and biosafety. Given the current situation of COVID-19 and its economic impact, capitalizing on the potential of cell-free synthetic biology from an economic, biosafety, and biosecurity perspective contributes to our preparedness for the next pandemic, and urges the development of appropriate policies and regulations, together with the necessary mitigation technologies. Proactive involvement from scientists is necessary to avoid misconceptions and assist in the policymaking process.

Metabolic engineering generates a transgene-free safety switch for cell therapy

Safeguard mechanisms can ameliorate the potential risks associated with cell therapies but currently rely on the introduction of transgenes. This limits their application owing to immunogenicity or transgene silencing. We aimed to create a control mechanism for human cells that is not mediated by a transgene. Using genome editing methods, we disrupt uridine monophosphate synthetase (UMPS) in the pyrimidine de novo synthesis pathway in cell lines, pluripotent cells and primary human T cells. We show that this makes proliferation dependent on external uridine and enables us to control cell growth by modulating the uridine supply, both in vitro and in vivo after transplantation in xenograft models. Additionally, disrupting this pathway creates resistance to 5-fluoroorotic acid, which enables positive selection of UMPS-knockout cells. We envision that this approach will add an additional level of safety to cell therapies and therefore enable the development of approaches with higher risks, especially those that are intended for limited treatment durations.

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.

Synthetic biology uses cells as its computing substrate, often based on the genetic circuit concept. In this Perspective, the authors argue that existing synthetic biology approaches based on classical models of computation limit the potential of biocomputing, and propose that living organisms have under-exploited capabilities.

Programmable bacteria induce durable tumor regression and systemic antitumor immunity

Synthetic biology is driving a new era of medicine through the genetic programming of living cells^1,2. This transformative approach allows for the creation of engineered systems that intelligently sense and respond to diverse environments, ultimately adding specificity and efficacy that extends beyond the capabilities of molecular-based therapeutics^3–6. One particular focus area has been the engineering of bacteria as therapeutic delivery systems to selectively release therapeutic payloads in vivo^7–11. Here, we engineered a non-pathogenic E. coli to specifically lyse within the tumor microenvironment and release an encoded nanobody antagonist of CD47 (CD47nb)¹², an anti-phagocytic receptor commonly overexpressed in several human cancers^13,14. We show that delivery of CD47nb by tumor-colonizing bacteria increases activation of tumor-infiltrating T cells, stimulates rapid tumor regression, prevents metastasis, and leads to long-term survival in a syngeneic tumor model. Moreover, we report that local injection of CD47nb bacteria stimulates systemic tumor antigen–specific immune responses that reduce the growth of untreated tumors – providing, to the best of our knowledge, the first demonstration of an abscopal effect induced by an engineered bacterial immunotherapy. Thus, engineered bacteria may be used for safe and local delivery of immunotherapeutic payloads leading to systemic antitumor immunity.

Regulation of T cell proliferation with drug-responsive microRNA switches

As molecular and cellular therapies advance in the clinic, the role of genetic regulation is becoming increasingly important for controlling therapeutic potency and safety. The emerging field of mammalian synthetic biology provides promising tools for the construction of regulatory platforms that can intervene with endogenous pathways and control cell behavior. Recent work has highlighted the development of synthetic biological systems that integrate sensing of molecular signals to regulated therapeutic function in various disease settings. However, the toxicity and limited dosing of currently available molecular inducers have largely inhibited translation to clinical settings. In this work, we developed synthetic microRNA-based genetic systems that are controlled by the pharmaceutical drug leucovorin, which is readily available and safe for prolonged administration in clinical settings. We designed microRNA switches to target endogenous cytokine receptor subunits (IL-2Rβ and γ_c) that mediate various signaling pathways in T cells. We demonstrate the function of these control systems by effectively regulating T cell proliferation with the drug input. Each control system produced unique functional responses, and combinatorial targeting of multiple receptor subunits exhibited greater repression of cell growth. This work highlights the potential use of drug-responsive genetic control systems to improve the management and safety of cellular therapeutics.

Co-evolution of physical and social sciences in synthetic biology

Emerging technologies research often covers various perspectives in disciplines and research areas ranging from hard sciences, engineering, policymaking, and sociology. However, the interrelationship between these different disciplinary domains, particularly the physical and social sciences, often occurs many years after a technology has matured and moved towards commercialization. Synthetic biology may serve an exception to this idea, where, since 2000, the physical and the social sciences communities have increasingly framed their research in response to various perspectives in biological engineering, risk assessment needs, governance challenges, and the social implications that the technology may incur. This paper reviews a broad collection of synthetic biology literature from 2000-2016, and demonstrates how the co-development of physical and social science communities has grown throughout synthetic biology's earliest stages of development. Further, this paper indicates that future co-development of synthetic biology scholarship will assist with significant challenges of the technology's risk assessment, governance, and public engagement needs, where an interdisciplinary approach is necessary to foster sustainable, risk-informed, and societally beneficial technological advances moving forward.

Synthetic biology toolkits and applications in Saccharomyces cerevisiae

Synthetic biologists construct biological components and systems to look into biological phenomena and drive a myriad of practical applications that aim to tackle current global challenges in energy, healthcare and the environment. While most tools have been established in bacteria, particularly Escherichia coli, recent years have seen parallel developments in the model yeast strain Saccharomyces cerevisiae, one of the most well-understood eukaryotic biological system. Here, we outline the latest advances in yeast synthetic biology tools based on a framework of abstraction hierarchies of parts, circuits and genomes. In brief, the creation and characterization of biological parts are explored at the transcriptional, translational and post-translational levels. Using characterized parts as building block units, the designing of functional circuits is elaborated with examples. In addition, the status and potential applications of synthetic genomes as a genome level platform for biological system construction are also discussed. In addition to the development of a toolkit, we describe how those tools have been applied in the areas of drug production and screening, study of disease mechanisms, pollutant sensing and bioremediation. Finally, we provide a future outlook of yeast as a workhorse of eukaryotic genetics and a chosen chassis in this field.

Tools and applications in synthetic biology

Advances in synthetic biology have enabled the engineering of cells with genetic circuits in order to program cells with new biological behavior, dynamic gene expression, and logic control. This cellular engineering progression offers an array of living sensors that can discriminate between cell states, produce a regulated dose of therapeutic biomolecules, and function in various delivery platforms. In this review, we highlight and summarize the tools and applications in bacterial and mammalian synthetic biology. The examples detailed in this review provide insight to further understand genetic circuits, how they are used to program cells with novel functions, and current methods to reliably interface this technology in vivo; thus paving the way for the design of promising novel therapeutic applications.

Synthetic Bax-Anti Bcl2 combination module actuated by super artificial hTERT promoter selectively inhibits malignant phenotypes of bladder cancer

BACKGROUND

The synthetic biology technology which enhances the specificity and efficacy of treatment is a novel try in biomedical therapy during recent years. A high frequency of somatic mutations was shown in the human telomerase reverse transcriptase (hTERT) promoter in bladder cancer, indicating that a mutational hTERT promoter might be a tumor-specific element for bladder cancer therapy. In our study, we aimed to construct a synthetic combination module driven by a super artificial hTERT promoter and to investigate its influence on the malignant phenotypes of bladder cancer.

METHODS

The dual luciferase assay system was used to verify the driven efficiency and tumor-specificity of the artificial hTERT promoter and to confirm the relationship between ETS-1 and the driven efficiency of the artificial hTERT promoter. CCK-8 assay and MTT assay were used to test the effects of the Bax-Anti Bcl2 combination module driven by the artificial hTERT promoter on cell proliferation. Simultaneously, the cell apoptosis was detected by the caspase 3ELISA assay and the flow cytometry analysis after transfection. The results of CCK-8 assay and MTT assay were analyzed by ANOVA. The independent samples t-test was used to analyze other data.

RESULTS

We demonstrated that the artificial hTERT promoter had a higher driven efficiency which might be regulated by transcription factor ETS-1 in bladder cancer cells, compared with wild-type hTERT promoter. Meanwhile, the artificial hTERT promoter showed a strong tumor-specific effect. The cell proliferation inhibition and apoptosis induction were observed in artificial hTERT promoter- Bax-Anti Bcl2 combination module -transfected bladder cancer 5637 and T24 cells, but not in the module -transfected normal human fibroblasts.

CONCLUSION

This module offers us a useful synthetic biology platform to inhibit the malignant phenotypes of bladder cancer in a more specific and effective way.

Spatial and functional heterogeneities shape collective behavior of tumor-immune networks

Tumor growth involves a dynamic interplay between cancer cells and host cells, which collectively form a tumor microenvironmental network that either suppresses or promotes tumor growth under different conditions. The transition from tumor suppression to tumor promotion is mediated by a tumor-induced shift in the local immune state, and despite the clinical challenge this shift poses, little is known about how such dysfunctional immune states are initiated. Clinical and experimental observations have indicated that differences in both the composition and spatial distribution of different cell types and/or signaling molecules within the tumor microenvironment can strongly impact tumor pathogenesis and ultimately patient prognosis. How such “functional” and “spatial” heterogeneities confer such effects, however, is not known. To investigate these phenomena at a level currently inaccessible by direct observation, we developed a computational model of a nascent metastatic tumor capturing salient features of known tumor-immune interactions that faithfully recapitulates key features of existing experimental observations. Surprisingly, over a wide range of model formulations, we observed that heterogeneity in both spatial organization and cell phenotype drove the emergence of immunosuppressive network states. We determined that this observation is general and robust to parameter choice by developing a systems-level sensitivity analysis technique, and we extended this analysis to generate other parameter-independent, experimentally testable hypotheses. Lastly, we leveraged this model as an in silico test bed to evaluate potential strategies for engineering cell-based therapies to overcome tumor associated immune dysfunction and thereby identified modes of immune modulation predicted to be most effective. Collectively, this work establishes a new integrated framework for investigating and modulating tumor-immune networks and provides insights into how such interactions may shape early stages of tumor formation.

Over the course of tumor growth, cancer cells interact with normal cells via processes that are difficult to understand by experiment alone. This challenge is particularly pronounced at early stages of tumor formation, when experimental observation is most limited. Elucidating such interactions could inform both understanding of cancer and clinical practice. To address this need we developed a computational model capturing the current understanding of how individual metastatic tumor cells and immune cells sense and contribute to the tumor environment, which in turn enabled us to investigate the complex, collective behavior of these systems. Surprisingly, we discovered that tumor escape from immune control was enhanced by the existence of small differences (or heterogeneities) in the responses of individual immune cells to their environment, as well as by heterogeneities in the way that cells and the molecules they secrete are arranged in space. These conclusions held true over a range of model formulations, suggesting that this is a general feature of these tumor-immune networks. Finally, we used this model as a test bed to evaluate potential strategies for enhancing immunological control of early tumors, ultimately predicting that specifically modulating tumor-associated immune dysfunction may be more effective than simply enhanced tumor killing.

Engineering Escherichia coli for light-activated cytolysis of mammalian cells

By delivering payloads in response to specific exogenous stimuli, smart bacterial therapeutics have the potential to overcome many limitations of conventional therapies, including poor targeting specificity and dosage control in current cancer treatments. Although not yet explored as a trigger for bacterial drug delivery, light is an ideal induction mechanism because it offers fine spatiotemporal control and is easily and safely administered. Using recent advances in optogenetics, we have engineered two strains of Escherichia coli to secrete a potent mammalian cytotoxin in response to blue or red light. The tools in this study demonstrate the initial feasibility of light-activated bacterial therapeutics for applications such as tumor cytolysis, and their modular nature should enable simple substitution of other payloads of interest.

Systematic transfer of prokaryotic sensors and circuits to mammalian cells

Prokaryotic regulatory proteins respond to diverse signals and represent a rich resource for building synthetic sensors and circuits. The TetR family contains >10(5) members that use a simple mechanism to respond to stimuli and bind distinct DNA operators. We present a platform that enables the transfer of these regulators to mammalian cells, which is demonstrated using human embryonic kidney (HEK293) and Chinese hamster ovary (CHO) cells. The repressors are modified to include nuclear localization signals (NLS) and responsive promoters are built by incorporating multiple operators. Activators are also constructed by modifying the protein to include a VP16 domain. Together, this approach yields 15 new regulators that demonstrate 19- to 551-fold induction and retain both the low levels of crosstalk in DNA binding specificity observed between the parent regulators in Escherichia coli, as well as their dynamic range of activity. By taking advantage of the DAPG small molecule sensing mediated by the PhlF repressor, we introduce a new inducible system with 50-fold induction and a threshold of 0.9 μM DAPG, which is comparable to the classic Dox-induced TetR system. A set of NOT gates is constructed from the new repressors and their response function quantified. Finally, the Dox- and DAPG- inducible systems and two new activators are used to build a synthetic enhancer (fuzzy AND gate), requiring the coordination of 5 transcription factors organized into two layers. This work introduces a generic approach for the development of mammalian genetic sensors and circuits to populate a toolbox that can be applied to diverse applications from biomanufacturing to living therapeutics.

Synthetic mammalian trigger-controlled bipartite transcription factors

Synthetic biology has significantly advanced the design of synthetic control devices, gene circuits and networks that can reprogram mammalian cells in a trigger-inducible manner. Prokaryotic helix-turn-helix motifs have become the standard resource to design synthetic mammalian transcription factors that tune chimeric promoters in a small molecule-responsive manner. We have identified a family of Actinomycetes transcriptional repressor proteins showing a tandem TetR-family signature and have used a synthetic biology-inspired approach to reveal the potential control dynamics of these bi-partite regulators. Daisy-chain assembly of well-characterized prokaryotic repressor proteins such as TetR, ScbR, TtgR or VanR and fusion to either the Herpes simplex transactivation domain VP16 or the Krueppel-associated box domain (KRAB) of the human kox-1 gene resulted in synthetic bi- and even tri-partite mammalian transcription factors that could reversibly program their individual chimeric or hybrid promoters for trigger-adjustable transgene expression using tetracycline (TET), γ-butyrolactones, phloretin and vanillic acid. Detailed characterization of the bi-partite ScbR-TetR-VP16 (ST-TA) transcription factor revealed independent control of TET- and γ-butyrolactone-responsive promoters at high and double-pole double-throw (DPDT) relay switch qualities at low intracellular concentrations. Similar to electromagnetically operated mechanical DPDT relay switches that control two electric circuits by a fully isolated low-power signal, TET programs ST-TA to progressively switch from TetR-specific promoter-driven expression of transgene one to ScbR-specific promoter-driven transcription of transgene two while ST-TA flips back to exclusive transgene 1 expression in the absence of the trigger antibiotic. We suggest that natural repressors and activators with tandem TetR-family signatures may also provide independent as well as DPDT-mediated control of two sets of transgenes in bacteria, and that their synthetic transcription-factor analogs may enable the design of compact therapeutic gene circuits for gene and cell-based therapies.

Regulating synthetic gene networks in 3D materials

Combining synthetic biology and materials science will enable more advanced studies of cellular regulatory processes, in addition to facilitating therapeutic applications of engineered gene networks. One approach is to couple genetic inducers into biomaterials, thereby generating 3D microenvironments that are capable of controlling intrinsic and extrinsic cellular events. Here, we have engineered biomaterials to present the genetic inducer, IPTG, with different modes of activating genetic circuits in vitro and in vivo. Gene circuits were activated in materials with IPTG embedded within the scaffold walls or chemically linked to the matrix. In addition, systemic applications of IPTG were used to induce genetic circuits in cells encapsulated into materials and implanted in vivo. The flexibility of modifying biomaterials with genetic inducers allows for patterned placement of these inducers that can be used to generate distinct patterns of gene expression. Together, these genetically interactive materials can be used to characterize genetic circuits in environments that more closely mimic cells' natural 3D settings, to better explore complex cell-matrix and cell-cell interactions, and to facilitate therapeutic applications of synthetic biology.

Mapping the environmental fitness landscape of a synthetic gene circuit

Gene expression actualizes the organismal phenotypes encoded within the genome in an environment-dependent manner. Among all encoded phenotypes, cell population growth rate (fitness) is perhaps the most important, since it determines how well-adapted a genotype is in various environments. Traditional biological measurement techniques have revealed the connection between the environment and fitness based on the gene expression mean. Yet, recently it became clear that cells with identical genomes exposed to the same environment can differ dramatically from the population average in their gene expression and division rate (individual fitness). For cell populations with bimodal gene expression, this difference is particularly pronounced, and may involve stochastic transitions between two cellular states that form distinct sub-populations. Currently it remains unclear how a cell population's growth rate and its subpopulation fractions emerge from the molecular-level kinetics of gene networks and the division rates of single cells. To address this question we developed and quantitatively characterized an inducible, bistable synthetic gene circuit controlling the expression of a bifunctional antibiotic resistance gene in Saccharomyces cerevisiae. Following fitness and fluorescence measurements in two distinct environments (inducer alone and antibiotic alone), we applied a computational approach to predict cell population fitness and subpopulation fractions in the combination of these environments based on stochastic cellular movement in gene expression space and fitness space. We found that knowing the fitness and nongenetic (cellular) memory associated with specific gene expression states were necessary for predicting the overall fitness of cell populations in combined environments. We validated these predictions experimentally and identified environmental conditions that defined a “sweet spot” of drug resistance. These findings may provide a roadmap for connecting the molecular-level kinetics of gene networks to cell population fitness in well-defined environments, and may have important implications for phenotypic variability of drug resistance in natural settings.

It is common belief that the properties of cells depend on their environment and on the genes they carry. Yet, many cases exist where individual cells in the same environment behave very differently, despite sharing the same genes. This creates a problem when we try to explain the behavior of a cell population based on the genes these cells carry. For example, it is difficult to predict how fast the overall number of cells increases based on the genes they all carry if some cells divide much faster than others. We addressed this problem using a synthetic gene circuit that could randomly allocate cells into drug resistant and drug sensitive states. We could control the fractions of cells and the time they resided in these states by adding an inducer to the growth solution. After measuring how fast cells transitioned between these two states, and how fast they grew in inducer and drug alone, we predicted computationally how fast they should grow when both inducer and drug are present. We validated experimentally these predictions and found a “sweet spot” of drug resistance where cells grew fastest in the presence of drugs.