Synthetic biology — application-oriented cell engineering

Enhancing cell-based therapies with synthetic gene circuits responsive to molecular stimuli

Synthetic biology aims to contribute to the development of next-generation patient-specific cell-based therapies for chronic diseases especially through the construction of sophisticated synthetic gene switches to enhance the safety and spatiotemporal controllability of engineered cells. Indeed, switches that sense and process specific cues, which may be either externally administered triggers or endogenous disease-associated molecules, have emerged as powerful tools for programming and fine-tuning therapeutic outputs. Living engineered cells, often referred to as designer cells, incorporating such switches are delivered to patients either as encapsulated cell implants or by infusion, as in the case of the clinically approved CAR-T cell therapies. Here, we review recent developments in synthetic gene switches responsive to molecular stimuli, spanning regulatory mechanisms acting at the transcriptional, translational, and posttranslational levels. We also discuss current challenges facing clinical translation of cell-based therapies employing these devices.

BioCloneBot: A versatile, low-cost, and open-source automated liquid handler

Liquid handler systems can provide significant benefits to researchers by automating laboratory work, however, their unaffordable price provides a steep barrier to entry. Therefore, we provide the BioCloneBot, a versatile, low-cost, and open-source automated liquid handler. This system can be easily built with 3D-printed parts and readily available commercial components. The BioCloneBot is highly adaptive to user needs and facilitates various liquid handling tasks in research and diagnostics. Its user-friendly interface and programmable nature make it suitable for a wide range of applications, from small-scale experiments to larger laboratory setups. By utilizing BioCloneBot, researchers and scientists can streamline their liquid handling processes without the financial constraints posed by traditional systems. In this paper, we detail the design, construction, and validation of BioCloneBot, showcasing its precise control, accuracy, and repeatability in various liquid handling tasks. The open-source nature of the system encourages collaboration and customization, enabling researchers to contribute and adapt the technology to specific experimental requirements.

Machine Learning and Deep Learning in Synthetic Biology: Key Architectures, Applications, and Challenges

Machine learning (ML), particularly deep learning (DL), has made rapid and substantial progress in synthetic biology in recent years. Biotechnological applications of biosystems, including pathways, enzymes, and whole cells, are being probed frequently with time. The intricacy and interconnectedness of biosystems make it challenging to design them with the desired properties. ML and DL have a synergy with synthetic biology. Synthetic biology can be employed to produce large data sets for training models (for instance, by utilizing DNA synthesis), and ML/DL models can be employed to inform design (for example, by generating new parts or advising unrivaled experiments to perform). This potential has recently been brought to light by research at the intersection of engineering biology and ML/DL through achievements like the design of novel biological components, best experimental design, automated analysis of microscopy data, protein structure prediction, and biomolecular implementations of ANNs (Artificial Neural Networks). I have divided this review into three sections. In the first section, I describe predictive potential and basics of ML along with myriad applications in synthetic biology, especially in engineering cells, activity of proteins, and metabolic pathways. In the second section, I describe fundamental DL architectures and their applications in synthetic biology. Finally, I describe different challenges causing hurdles in the progress of ML/DL and synthetic biology along with their solutions.

In Vitro Generation of Megakaryocytes from Engineered Mouse Embryonic Stem Cells

The in vitro differentiation of pluripotent stem cells into desired lineages enables mechanistic studies of cell transitions into more mature states that can provide insights into the design principles governing cell fate control. We are interested in reprogramming pluripotent stem cells with synthetic gene circuits to drive mouse embryonic stem cells (mESCs) down the hematopoietic lineage for the production of megakaryocytes, the progenitor cells for platelets. Here, we describe the methodology for growing and differentiating mESCs, in addition to inserting a transgene to observe its expression throughout differentiation. This entails four key methods: (1) growing and preparing mouse embryonic fibroblasts for supporting mESC growth and expansion, (2) growing and preparing OP9 feeder cells to support the differentiation of mESCs, (3) the differentiation of mESCs into megakaryocytes, and (4) utilizing an integrase-mediated docking site to insert transgenes for their stable integration and expression throughout differentiation. Altogether, this approach demonstrates a streamline differentiation protocol that emphasizes the reprogramming potential of mESCs that can be used for future mechanistic and therapeutic studies of controlling cell fate outcomes.

pH-Responsive Elastin-Like Polypeptide Designer Condensates

Biomolecular condensates are macromolecular complexes formed by liquid-liquid phase separation. They regulate key biological functions by reversibly compartmentalizing molecules in cells, in a stimulus-dependent manner. Designing stimuli-responsive synthetic condensates is crucial for engineering compartmentalized synthetic cells that are able to mimic spatiotemporal control over the biochemical reactions. Here, we design and test a family of condensate-forming, pH-responsive elastin-like polypeptides (ELPs) that form condensates above critical pH values ranging between 4 and 7, for temperatures between 20 and at 37 °C. We show that the condensation occurs rapidly, in sharp pH intervals (ΔpH < 0.3). For eventual applications in engineering synthetic cell compartments, we demonstrate that multiple types of pH-responsive ELPs can form mixed condensates inside micron-sized vesicles. When genetically fused with enzymes, receptors, and signaling molecules, these pH-responsive ELPs could be potentially used as pH-switchable functional condensates for spatially controlling biochemistry in engineered synthetic cells.

Synthetic biology-inspired cell engineering in diagnosis, treatment, and drug development

The fast-developing synthetic biology (SB) has provided many genetic tools to reprogram and engineer cells for improved performance, novel functions, and diverse applications. Such cell engineering resources can play a critical role in the research and development of novel therapeutics. However, there are certain limitations and challenges in applying genetically engineered cells in clinical practice. This literature review updates the recent advances in biomedical applications, including diagnosis, treatment, and drug development, of SB-inspired cell engineering. It describes technologies and relevant examples in a clinical and experimental setup that may significantly impact the biomedicine field. At last, this review concludes the results with future directions to optimize the performances of synthetic gene circuits to regulate the therapeutic activities of cell-based tools in specific diseases.

In vitro generation of megakaryocytes from engineered mouse embryonic stem cells

The in vitro differentiation of pluripotent stem cells into desired lineages enables mechanistic studies of cell transitions into more mature states that can provide insights into the design principles governing cell fate control. We are interested in reprogramming pluripotent stem cells with synthetic gene circuits to drive mouse embryonic stem cells (mESCs) down the hematopoietic lineage for the production of megakaryocytes, the progenitor cells for platelets. Here, we describe the methodology for growing and differentiating mESCs, in addition to inserting a transgene to observe its expression throughout differentiation. This entails four key methods: (1) growing and preparing mouse embryonic fibroblasts for supporting mESC growth and expansion, (2) growing and preparing OP9 feeder cells to support the differentiation of mESCs, (3) the differentiation of mESCs into megakaryocytes, and (4) utilizing an integrase mediated docking site to insert transgenes for their stable integration and expression throughout differentiation. Altogether, this approach demonstrates a streamline differentiation protocol that emphasizes the reprogramming potential of mESCs that can be used for future mechanistic and therapeutic studies of controlling cell fate outcomes.

Synthetic Biology Design as a Paradigm Shift toward Manufacturing Affordable Adeno-Associated Virus Gene Therapies

Gene therapy has demonstrated enormous potential for changing how we combat disease. By directly engineering the genetic composition of cells, it provides a broad range of options for improving human health. Adeno-associated viruses (AAVs) represent a leading gene therapy vector and are expected to address a wide range of conditions in the coming decade. Three AAV therapies have already been approved by the FDA to treat Leber's congenital amaurosis, spinal muscular atrophy, and hemophilia B. Yet these therapies cost around $850,000, $2,100,000, and $3,500,000, respectively. Such prices limit the broad applicability of AAV gene therapy and make it inaccessible to most patients. Much of this problem arises from the high manufacturing costs of AAVs. At the same time, the field of synthetic biology has grown rapidly and has displayed a special aptitude for addressing biomanufacturing problems. Here, we discuss emerging efforts to apply synthetic biology design to decrease the price of AAV production, and we propose that such efforts could play a major role in making gene therapy much more widely accessible.

Synthetic Biology Meets Machine Learning

This chapter outlines the myriad applications of machine learning (ML) in synthetic biology, specifically in engineering cell and protein activity, and metabolic pathways. Though by no means comprehensive, the chapter highlights several prominent computational tools applied in the field and their potential use cases. The examples detailed reinforce how ML algorithms can enhance synthetic biology research by providing data-driven insights into the behavior of living systems, even without detailed knowledge of their underlying mechanisms. By doing so, ML promises to increase the efficiency of research projects by modeling hypotheses in silico that can then be tested through experiments. While challenges related to training dataset generation and computational costs remain, ongoing improvements in ML tools are paving the way for smarter and more streamlined synthetic biology workflows that can be readily employed to address grand challenges across manufacturing, medicine, engineering, agriculture, and beyond.

Therapeutic cell engineering: designing programmable synthetic genetic circuits in mammalian cells

Cell therapy approaches that employ engineered mammalian cells for on-demand production of therapeutic agents in the patient's body are moving beyond proof-of-concept in translational medicine. The therapeutic cells can be customized to sense user-defined signals, process them, and respond in a programmable and predictable way. In this paper, we introduce the available tools and strategies employed to design therapeutic cells. Then, various approaches to control cell behaviors, including open-loop and closed-loop systems, are discussed. We also highlight therapeutic applications of engineered cells for early diagnosis and treatment of various diseases in the clinic and in experimental disease models. Finally, we consider emerging technologies such as digital devices and their potential for incorporation into future cell-based therapies.

Synthetic biology as driver for the biologization of materials sciences

Materials in nature have fascinating properties that serve as a continuous source of inspiration for materials scientists. Accordingly, bio-mimetic and bio-inspired approaches have yielded remarkable structural and functional materials for a plethora of applications. Despite these advances, many properties of natural materials remain challenging or yet impossible to incorporate into synthetic materials. Natural materials are produced by living cells, which sense and process environmental cues and conditions by means of signaling and genetic programs, thereby controlling the biosynthesis, remodeling, functionalization, or degradation of the natural material. In this context, synthetic biology offers unique opportunities in materials sciences by providing direct access to the rational engineering of how a cell senses and processes environmental information and translates them into the properties and functions of materials. Here, we identify and review two main directions by which synthetic biology can be harnessed to provide new impulses for the biologization of the materials sciences: first, the engineering of cells to produce precursors for the subsequent synthesis of materials. This includes materials that are otherwise produced from petrochemical resources, but also materials where the bio-produced substances contribute unique properties and functions not existing in traditional materials. Second, engineered living materials that are formed or assembled by cells or in which cells contribute specific functions while remaining an integral part of the living composite material. We finally provide a perspective of future scientific directions of this promising area of research and discuss science policy that would be required to support research and development in this field.

Synthetic biology for improving cell fate decisions and tissue engineering outcomes

Synthetic biology is a relatively new field of science that combines aspects of biology and engineering to create novel tools for the construction of biological systems. Using tools within synthetic biology, stem cells can then be reprogrammed and differentiated into a specified cell type. Stem cells have already proven to be largely beneficial in many different therapies and have paved the way for tissue engineering and regenerative medicine. Although scientists have made great strides in tissue engineering, there still remain many questions to be answered in regard to regeneration. Presented here is an overview of synthetic biology, common tools built within synthetic biology, and the way these tools are being used in stem cells. Specifically, this review focuses on how synthetic biologists engineer genetic circuits to dynamically control gene expression while also introducing emerging topics such as genome engineering and synthetic transcription factors. The findings mentioned in this review show the diverse use of stem cells within synthetic biology and provide a foundation for future research in tissue engineering with the use of synthetic biology tools. Overall, the work done using synthetic biology in stem cells is in its early stages, however, this early work is leading to new approaches for repairing diseased and damaged tissues and organs, and further expanding the field of tissue engineering.

Numerical operations in living cells by programmable RNA devices

Integrated bioengineering systems can make executable decisions according to the cell state. To sense the state, multiple biomarkers are detected and processed via logic gates with synthetic biological devices. However, numerical operations have not been achieved. Here, we show a design principle for messenger RNA (mRNA) devices that recapitulates intracellular information by multivariate calculations in single living cells. On the basis of this principle and the collected profiles of multiple microRNA activities, we demonstrate that rationally programmed mRNA sets classify living human cells and track their change during differentiation. Our mRNA devices automatically perform multivariate calculation and function as a decision-maker in response to dynamic intracellular changes in living cells.

A Novel Synthetic Toehold Switch for MicroRNA Detection in Mammalian Cells

MicroRNAs (miRNA or miR) are short noncoding RNA of about 21-23 nucleotides that play critical roles in multiple aspects of biological processes by mediating translational repression through targeting messenger RNA (mRNA). Conventional methods for miRNA detection, including RT-PCR and Northern blot, are limited due to the requirement of cell disruption. Here, we developed a novel synthetic toehold switch, inspired by the toehold switches developed for bacterial systems, to detect endogenous and exogenously expressed miRNAs in mammalian cells, including HEK 293, HeLa, and MDA-MB-231 cells. Transforming growth factor β-induced miR-155 expression in MDA-MB-231 cells could be detected by the synthetic toehold switch. The experimental results showed the dynamic range of current design of toehold switch is about two. Furthermore, we tested multiplex detection of miR-155 and miR-21 in HEK 293 cells by using miR-155 and miR-21 toehold switches. These toehold switches provide a modest level of orthogonality and could be optimized to achieve a better dynamic range. Our experimental results demonstrate the capability of miRNA toehold switch for detecting and visualizing miRNA expression in mammalian cells, which may potentially lead to new therapeutic or diagnostic applications.

Genetic circuits to engineer tissues with alternative functions

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

History, Current State, and Emerging Applications of Industrial Biotechnology

The past 150 years have seen remarkable discoveries, rapidly growing biological knowledge, and giant technological leaps providing biotechnological solutions for healthcare, food production, and other societal needs. Genetic engineering, miniaturization, and ever-increasing computing power, in particular, have been key technological drivers for the past few decades. Looking ahead, the eventual transition from fossil resources to biomass and CO₂ demands a shift toward a 'bio-economy' based on novel production processes and engineered organisms.

Comparison of Integrases Identifies Bxb1-GA Mutant as the Most Efficient Site-Specific Integrase System in Mammalian Cells

Phage-derived integrases can catalyze irreversible, site-specific integration of transgenic payloads into a chromosomal locus, resulting in mammalian cells that stably express transgenes or circuits of interest. Previous studies have demonstrated high-efficiency integration by the Bxb1 integrase in mammalian cells. Here, we show that a point mutation (Bxb1-GA) in Bxb1 target sites significantly increases Bxb1-mediated integration efficiency at the Rosa26 locus in Chinese hamster ovary cells, resulting in the highest integration efficiency reported with a site-specific integrase in mammalian cells. Bxb1-GA point mutant sites do not cross-react with Bxb1 wild-type sites, enabling their use in applications that require orthogonal pairs of target sites. In comparison, we test the efficiency and orthogonality of ϕC31 and Wβ integrases, and show that Wβ has an integration efficiency between those of Bxb1-GA and wild-type Bxb1. Our data present a toolbox of integrases for inserting payloads such as gene circuits or therapeutic transgenes into mammalian cell lines.

Modular Antigen-Specific T-cell Biofactories for Calibrated In Vivo Synthesis of Engineered Proteins

An artificial cell-signaling pathway is developed that capitalizes on the T-cell's innate extravasation ability and transforms it into a vector (T-cell Biofactory) for synthesizing calibrated amounts of engineered proteins in vivo. The modularity of this pathway enables reprogramming of the T-cell Biofactory to target biomarkers on different disease cells, e.g. cancer, viral infections, autoimmune disorders. It can be expected that the T-cell Biofactory leads to a "living drug" that extravasates to the disease sites, assesses the disease burden, synthesizes the calibrated amount of engineered therapeutic proteins upon stimulation by the diseased cells, and reduces targeting of normal cells.

Binary addition in a living cell based on riboregulation

Synthetic biology aims at (re-)programming living cells like computers to perform new functions for a variety of applications. Initial work rested on transcription factors, but regulatory RNAs have recently gained much attention due to their high programmability. However, functional circuits mainly implemented with regulatory RNAs are quite limited. Here, we report the engineering of a fundamental arithmetic logic unit based on de novo riboregulation to sum two bits of information encoded in molecular concentrations. Our designer circuit robustly performs the intended computation in a living cell encoding the result as fluorescence amplitudes. The whole system exploits post-transcriptional control to switch on tightly silenced genes with small RNAs, together with allosteric transcription factors to sense the molecular signals. This important result demonstrates that regulatory RNAs can be key players in synthetic biology, and it paves the way for engineering more complex RNA-based biocomputers using this designer circuit as a building block.

Bottom-up approaches in synthetic biology and biomaterials for tissue engineering applications

Synthetic biologists use engineering principles to design and construct genetic circuits for programming cells with novel functions. A bottom-up approach is commonly used to design and construct genetic circuits by piecing together functional modules that are capable of reprogramming cells with novel behavior. While genetic circuits control cell operations through the tight regulation of gene expression, a diverse array of environmental factors within the extracellular space also has a significant impact on cell behavior. This extracellular space offers an addition route for synthetic biologists to apply their engineering principles to program cell-responsive modules within the extracellular space using biomaterials. In this review, we discuss how taking a bottom-up approach to build genetic circuits using DNA modules can be applied to biomaterials for controlling cell behavior from the extracellular milieu. We suggest that, by collectively controlling intrinsic and extrinsic signals in synthetic biology and biomaterials, tissue engineering outcomes can be improved.

Synthetic gene circuits for the detection, elimination and prevention of disease

In living organisms, naturally evolved sensors that constantly monitor and process environmental cues trigger corrective actions that enable the organisms to cope with changing conditions. Such natural processes have inspired biologists to construct synthetic living sensors and signalling pathways, by repurposing naturally occurring proteins and by designing molecular building blocks de novo, for customized diagnostics and therapeutics. In particular, designer cells that employ user-defined synthetic gene circuits to survey disease biomarkers and to autonomously re-adjust unbalanced pathological states can coordinate the production of therapeutics, with controlled timing and dosage. Furthermore, tailored genetic networks operating in bacterial or human cells have led to cancer remission in experimental animal models, owing to the network's unprecedented specificity. Other applications of designer cells in infectious, metabolic and autoimmune diseases are also being explored. In this Review, we describe the biomedical applications of synthetic gene circuits in major disease areas, and discuss how the first genetically engineered devices developed on the basis of synthetic-biology principles made the leap from the laboratory to the clinic.

Bacterial Microcolonies in Gel Beads for High-Throughput Screening of Libraries in Synthetic Biology

Synthetic biologists increasingly rely on directed evolution to optimize engineered biological systems. Applying an appropriate screening or selection method for identifying the potentially rare library members with the desired properties is a crucial step for success in these experiments. Special challenges include substantial cell-to-cell variability and the requirement to check multiple states (e.g., being ON or OFF depending on the input). Here, we present a high-throughput screening method that addresses these challenges. First, we encapsulate single bacteria into microfluidic agarose gel beads. After incubation, they harbor monoclonal bacterial microcolonies (e.g., expressing a synthetic construct) and can be sorted according their fluorescence by fluorescence activated cell sorting (FACS). We determine enrichment rates and demonstrate that we can measure the average fluorescent signals of microcolonies containing phenotypically heterogeneous cells, obviating the problem of cell-to-cell variability. Finally, we apply this method to sort a pBAD promoter library at ON and OFF states.

Cross-Regulation of an Artificial Metalloenzyme

Cross-regulation of complex biochemical reaction networks is an essential feature of living systems. In a biomimetic spirit, we report on our efforts to program the temporal activation of an artificial metalloenzyme via cross-regulation by a natural enzyme. In the presence of urea, urease slowly releases ammonia that reversibly inhibits an artificial transfer hydrogenase. Addition of an acid, which acts as fuel, allows to maintain the system out of equilibrium.

Near-infrared optogenetic pair for protein regulation and spectral multiplexing

Multifunctional optogenetic systems are in high demand for use in basic and biomedical research. Near-infrared-light-inducible binding of bacterial phytochrome BphP1 to its natural PpsR2 partner is beneficial for simultaneous use with blue-light-activatable tools. However, applications of the BphP1-PpsR2 pair are limited by the large size, multidomain structure and oligomeric behavior of PpsR2. Here, we engineered a single-domain BphP1 binding partner, Q-PAS1, which is three-fold smaller and lacks oligomerization. We exploited a helix-PAS fold of Q-PAS1 to develop several near-infrared-light-controllable transcription regulation systems, enabling either 40-fold activation or inhibition. The light-induced BphP1-Q-PAS1 interaction allowed modification of the chromatin epigenetic state. Multiplexing the BphP1-Q-PAS1 pair with a blue-light-activatable LOV-domain-based system demonstrated their negligible spectral crosstalk. By integrating the Q-PAS1 and LOV domains in a single optogenetic tool, we achieved tridirectional protein targeting, independently controlled by near-infrared and blue light, thus demonstrating the superiority of Q-PAS1 for spectral multiplexing and engineering of multicomponent systems.

Rapid generation of hypomorphic mutations

Hypomorphic mutations are a valuable tool for both genetic analysis of gene function and for synthetic biology applications. However, current methods to generate hypomorphic mutations are limited to a specific organism, change gene expression unpredictably, or depend on changes in spatial-temporal expression of the targeted gene. Here we present a simple and predictable method to generate hypomorphic mutations in model organisms by targeting translation elongation. Adding consecutive adenosine nucleotides, so-called polyA tracks, to the gene coding sequence of interest will decrease translation elongation efficiency, and in all tested cell cultures and model organisms, this decreases mRNA stability and protein expression. We show that protein expression is adjustable independent of promoter strength and can be further modulated by changing sequence features of the polyA tracks. These characteristics make this method highly predictable and tractable for generation of programmable allelic series with a range of expression levels.