Tools and applications in synthetic biology

ADR-13051; No of Pages 15 Advanced Drug Delivery Reviews xxx (2016) xxx–xxx

Contents lists available at ScienceDirect

Advanced Drug Delivery Reviews journal homepage: www.elsevier.com/locate/addr

Tools and applications in synthetic biology☆ I. Cody MacDonald, Tara L. Deans ⁎ Department of Bioengineering, University of Utah, Salt Lake City, UT 84112, United States

a r t i c l e

i n f o

Article history: Received 17 April 2016 Received in revised form 15 August 2016 Accepted 17 August 2016 Available online xxxx Keywords: Synthetic biology Genetic circuits Cell therapy Gene networks

a b s t r a c t 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. © 2016 Elsevier B.V. All rights reserved.

Contents 1. 2.

Introduction . . . . . . . . . . . . . . . Tools in synthetic biology . . . . . . . . . 2.1. Genetic circuit induction . . . . . . 2.2. Synthetic transcription factors . . . 2.3. Genome engineering . . . . . . . 2.4. Cellular computation and memory . 2.5. Riboregulators . . . . . . . . . . 2.6. Biomaterials . . . . . . . . . . . 3. Applications in synthetic biology . . . . . 3.1. Biological sensing . . . . . . . . . 3.1.1. Cell-based sensors . . . . . 3.1.2. Paper based cell-free sensors 3.2. Sense and respond . . . . . . . . 3.3. Delivery platforms . . . . . . . . . 4. Conclusions . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . .

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1. Introduction Cells are complex and dynamic systems that have the remarkable ability to continuously sense, integrate, and store relevant physiological

☆ This review is part of the Advanced Drug Delivery Reviews theme issue on “Synthetic Biology: Innovative approaches for pharmaceutics and drug delivery”. ⁎ Corresponding author at: Department of Bioengineering, University of Utah, Biopolymers Research Building, 108B, 20 South 2030 East, Salt Lake City, UT 84112, United States. E-mail address: [email protected] (T.L. Deans).

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and biological information throughout their lives. Each cell constantly processes the many surrounding signals to make decisions on its differentiation state, migration, and metabolic rate. The complexity of gene expression systems can be simplified by considering genetic networks composed of subsets of simpler parts, or modules. Modules are defined as individual gene expression parts that can be independently characterized and used to build novel genetic circuits. This simplification is the foundation of synthetic biology where engineering paradigms are applied in rational and systematic ways to produce predictable and robust systems to understand mechanisms of cellular function [1]. Synthetic biology is an engineering discipline that has evolved to produce

http://dx.doi.org/10.1016/j.addr.2016.08.008 0169-409X/© 2016 Elsevier B.V. All rights reserved.

Please cite this article as: I.C. MacDonald, T.L. Deans, Tools and applications in synthetic biology, Adv. Drug Deliv. Rev. (2016), http://dx.doi.org/ 10.1016/j.addr.2016.08.008

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an exciting genetic toolbox for the implementation of gene control over dynamic regulatory systems to interrogate natural biological phenomena, and enable the programming of cells to execute novel functions [2–7]. Similar to electrical engineers who build electric circuits out of resistors, capacitors, and switches to implement a controlled and desired electrical output, synthetic biologists program cells using DNA, RNA, and proteins to execute desired genetic outputs. It is well understood that cells live in a complex environment where they are constantly assessing the many signals that surround them [8,9]. The natural evolution of biological life has been to create increasingly robust natural genetic networks to sense the environment and carry out advantageous responses. Therefore, a goal of many synthetic biologists is to use this approach to harness the intricate complexity of cells for the purpose of creating programmed therapeutic cells capable of autonomously controlling and modulating both intrinsic (within cells), and extrinsic (outside cells) signals to fight against disease. To accomplish this, there are three major efforts in synthetic biology that include engineering cells to: i) function as sensors to sense and report on the presence of specific molecules that can discriminate between cell states (i.e. healthy vs. diseased/damaged), ii) sense a specific molecule and/or cell state and respond by producing a regulated dose of therapeutic biomolecules, and iii) function in various delivery platforms (Fig. 1). Altogether, these efforts require an understanding of cell signaling pathways, gene regulatory mechanisms, cell–cell and cell-extracellular matrix (ECM) communication, and the production and delivery of various therapeutic agents (Fig. 2A–E). In an effort to engineer cells as therapeutic entities, synthetic biologists continue to build novel genetic tools and circuits to re-engineering cells to perform specific tasks [4,10–23]. One of the most powerful tools that molecular biology has produced is the ability to turn genes on and off at our discretion (Fig. 3A). However, the principle difference between molecular biology and synthetic biology is that synthetic biology assembles parts from molecular biology (e.g. repressor proteins) to build novel genetic architectures that perform complex functions (Fig. 3B). These functions include dynamic gene expression,

re-wiring endogenous pathways to produce biomolecules, controlling cell populations, reporting on the state of various environments, and performing Boolean logic functions. Recombinases have been used by molecular biologists for years for the generation of transgenic and knockout mice (Fig. 3C), whereas synthetic biologists use recombinases to build genetic circuits that are capable of programming cells to store memory, and to perform mathematical computations and higherorder functions like disease identification [22,24–30] (Fig. 3D). Lastly, genome editing using nucleases (e.g. CRISPR/Cas9) enables targeted cutting of genomic DNA (Fig. 3E), and synthetic biologists have layered CRISPR/Cas9 parts to enable multilevel control of gene expression (Fig. 3F). Boolean logic gates (AND, OR, XOR, etc.) are at the core of programming cells with many advanced functions including decisionmaking capabilities based on inputs from the intrinsic and extrinsic cues for regulating target genes, where the processing of inputs have thresholds states of ‘0’ or ‘1’ (‘OFF’ or ‘ON’ respectively) (Fig. 2F) [31]. These cells have the potential to drastically improve current therapeutic approaches for diagnosing and treating diseased and damaged tissue by facilitating the delivery of a variety of biomolecules specifically targeted to sites of disease/injury, and can be delivered at controlled levels in response to the degree of disease/injury. Our understanding of how to program cells using gene circuits has been expanded remarkably over the last decade. It is impossible to summarize all of the pioneering work that has contributed to increase our knowledge of implementing synthetic biology within cells, or the vast number of applications that synthetic biology has the potential to improve. In this review, we discuss many of the genetic tools that synthetic biologists use, as well as their role in targeted therapeutic strategies and applications in human health. We begin these topics by summarizing the current tools in synthetic biology that include genetic circuit induction, synthetic transcription factors, genome engineering, riboregulators, and biomaterials. We then discuss how these tools are used for programming cellular computation, memory, and Boolean logic. Next we discuss applications in synthetic biology such as biological sensors, programming cells to sense and respond to disease, and highlight impactful delivery platforms within synthetic biology. Finally, we consider the future prospects and challenges for these technologies. 2. Tools in synthetic biology Reliable control of gene expression is critical to achieving functional genetic circuits in cells, and is the first step in engineering cells with new functions. The field of synthetic biology is inspired by engineering genetic circuits that function either independently within cells, or together as integrated devices with cells' natural biological networks. To establish independent function within cells, genetic circuits are often designed to be orthogonal to the host, where the control elements for regulating genetic circuits do not exist in the host signaling pathways. The underlying Boolean logic gates built into genetic circuits to dictate the timing, duration, and functionality of these circuits can be controlled with defined triggered inputs. In the following subsections, we discuss research tools used in molecular biology and genetic engineering. These tools represent the parts, or modules, that synthetic biologists use to engineer genetic circuits for sophisticated control of cell function. 2.1. Genetic circuit induction

Fig. 1. Approaches for engineering programmed therapeutic cells. Efforts in synthetic biology include building genetic circuits that function as sensors to report on the presence of specific molecules (blue), sense specific molecules and respond by producing a regulated dose of therapeutic biomolecules (green), and enable the functionality of genetic circuits in various delivery platforms (yellow).

Much of the early work in synthetic biology was rooted in the realization that genetic circuits can be constructed using the assembly of gene regulatory parts to reprogram cells [32]. Two such examples are the bacterial repressor proteins, LacI and TetR. By placing the proteins' binding domains within promoter regions, it is possible to control downstream gene expression. These regulatory proteins have been converted into efficient gene expression controllers in mammalian cells by fusing them to transcriptional regulatory domains. For example,



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Fig. 2. Genetic circuit function. Synthetic biologists engineer genetic circuits that can be activated by various inputs including A. small molecules and B. light. C. Cells programmed with genetic circuits have control centers that enable the controlled and predictable cell behavior that include D. cell–cell and cell-ECM communication, E. dynamic gene expression, and F. Boolean logic operations.

when fused to a transcriptional activator domain (e.g. VP16), these transcription factors can activate transcription from a eukaryotic promoter that has been engineered to contain their corresponding DNA operator sequences. Alternatively, when fused to a transcriptional repressor domain (e.g. KRAB), transcription factors can block transcription. The effects of the LacI and TetR regulatory proteins can be reversed by adding the small molecule inducers, isopropyl β-D-1thiogalactopyranoside (IPTG) and tetracycline, respectively. When these inducers are added to the media, they bind to their regulatory proteins, which causes conformational changes in the regulatory proteins and prevents binding to operator sequences to permit gene expression. These tools allow flexibility of gene expression that has been demonstrated to function in mammalian cell culture and in mice [33,34]. Small molecule gene expression systems are among the many parts that synthetic biologists use to engineer genetic circuits that function as toggle switches [35–38], oscillators [39–42], and cells that demonstrate programmable Boolean logic (Fig. 2) [43]. Additionally, quorum sensing has been used extensively in synthetic biology to induce and control dynamic genetic circuits [12,44,45]. The assembly and function of these and other small molecule induction genetic circuits have been extensively reviewed elsewhere [46–53]. Small molecule inducers are efficient at activating populations of cells in a culturing flask, however, small molecule inducers contain inherent limitations due to a lack of spatial and temporal resolution, in addition to the difficulty in controlling genetic circuits in vivo. Recently, the study of multidrug resistance efflux pumps has been shown to have both predictable and unexpected effects on small molecule inducer control of genetic circuit outputs [54]. These limitations have been addressed by the development of optogenetics, a technology in which light activates genetic signaling pathways via light-sensitive proteins [55]. Light-sensitive proteins include UV-light receptors, blue-light sensing LOV (light, oxygen, or voltage) domains, cryptochrome receptors, red- and green-sensing phytochromes, and rhodopsins, which have been engineered to control endogenous biological activity in a

light-dependent manner [56–63]. Synthetic biologists have recently engineered genetic circuits that are capable of responding to light [64–68], which is advantageous because it allows spatial and temporal resolution of gene expression to enable precise control of genetic activation that can be used for other biomedical engineering applications, which are discussed later in this review [69,70].

2.2. Synthetic transcription factors Natural transcription networks are at the core of many fundamental molecular functions that dictate the health and behavior of cells. As synthetic biologists continue to improve their tools to control cell behavior, many are turning to the natural transcriptional networks within cells to understand how cells control these networks, in addition to finding endogenous triggers to activate genetic circuits [71,72]. These novel triggers can be used to control genetic circuits to identify disease, engineer new cellular functions, and program cells with autonomous decision-making. Significant effort is underway to interrogate endogenous DNA sequences to better understand the relationship between genotype, cellular function, and disease. Zinc finger (ZF) proteins and transcription activator-like effectors (TALEs) are two examples of DNA targeting proteins that recognize and bind to DNA to alter transcription in host cells. ZF proteins are composed of approximately 30 amino acids and bind to 3–4 base pairs of DNA with varying selectivity. Fusing multiple ZF protein domains together enables the construction of synthetic ZF proteins that recognize 9–18 DNA base pairs in length, allowing for specific sequences to be targeted in the genome [73,74] (Fig. 4A). TALE proteins, on the other hand, can be designed to bind to 7–34 base pair DNA sequences by connecting the TALE DNA-binding repeat domains (Fig. 4B). These advances enabled ZFs and TALEs to be engineered to bind to desired DNA sequences and regulate the expression of endogenous genes [75]. Furthermore, when ZFs and TALE proteins are fused to transcriptional activators or repressors,


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Fig. 3. Differences between molecular biology and synthetic biology. A. Genetic repressors and activators are commonly used by molecular biologists, whereas B. synthetic biologists use these parts to assemble genetic circuits to perform Boolean logic operations, and/or dynamic gene expression including a) genetic toggle switches, and b) switches that are capable of tight gene expression. C. Recombinases are used to carry out deletions, translocations, inversions, and insertions in DNA. The generation of transgenic and knockout mice uses recombinases (e.g. Cre/Lox) to enable a) genetic reporting and b) gene knockout animals. D. Synthetic biologists use recombinases to a) program Boolean logic operations in cells and b) encode long-term memory. E. Genome editing using nucleases (e.g. CRISPR/Cas9) enables the targeted cutting of DNA. F. Layering CRISPR/Cas9 enables multi-level control of gene expression.

they can be used to manipulate endogenous genes, making them exciting options for interrogating these genes (Fig. 4A and B) [76,77]. More recently, clustered regulatory interspaced short palindromic repeats (CRISPR)/Cas9 transcription factors (CRISPR-TFs) and Cas9

proteins have been engineered to remove the nuclease activity (dCas9). The dCas9 enables programmable transcriptional regulation of promoters in bacterial and mammalian cells to direct both the activation and repression of natural and artificial promoters (Fig. 4C).



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Fig. 4. Programmable DNA binding domains. A. ZFs and B. TALEs are DNA targeting molecules consisting of protein modules that recognize and bind to specific DNA base pairs. C. CRISPRTFs complex with gRNAs to target and bind a DNA sequence. Modular domains allow for activators and repressors to be fused to protein, creating synthetic transcription factors.

This is accomplished with the rational engineering of guide RNAs (gRNAs) that undergo complementary base pairing with target DNA sites. When gRNAs and Cas9 are expressed in the same cell, they form a complex that is recruited to genomic DNA sharing a complementarity sequence to the gRNA [78]. Furthermore, endogenous gene expression can be activated, repressed, or tuned by directing multiple CRISPR-TFs to different positions in natural promoters [79–81]. Recently, the Cas9 synthetic transcription factors have been demonstrated to specifically target and improve the activation of gene expression in mouse neural cells, suggesting a possible method to reprogram cells in vivo for regenerative medicine applications [82–84]. The key strength to utilizing the CRISPR system for synthetic transcription factors lies in the sequence specificity in which they function, in addition to their sequence guided nature to direct cellular behavior in a deterministic fashion. Moreover, CRISPR-TFs have become widely used due to the ease of engineering the gRNAs to target specific genomic locations for transcriptional modulation. The continued advancement of synthetic transcription factors marks an exciting time for the field of synthetic biology. Synthetic transcription factors have expanded the toolkit with increased modules to disrupt, rewire, and mimic natural networks [5,85]. These synthetic parts are critical for the design of genetic circuits that monitor and respond to the endogenous changes in natural transcription that dictate the health of cells and tissues. Furthermore, orthogonal synthetic transcription factors can be constructed to wire genetic circuits in vivo that will play an important role in determining transcriptional components, modules and circuitry needed to implement sophisticated behaviors in cells [71].

2.3. Genome engineering Targeted genome editing, as seen with the creation of genetic knockout and transgenic mice, has proven to be critical for developing and testing hypotheses based on genetics [86–88]. The discovery of programmable DNA nucleases has provided scientists with the ability to probe, regulate, and manipulate a wide range of organisms and cell types that have the potential to be used as a therapy for genetic diseases. Zinc-finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and CRISPR-Cas9 represent a powerful array of tools that can bind to and cleave DNA sequences at a DNA locus of interest (Fig. 5A–C) [89–93]. These nucleases enable efficient and precise genetic modifications by inducing targeted DNA double-stranded breaks, which stimulate cellular DNA repair mechanisms including nonhomologous end joining (NHEJ) and homology-directed repair (HR) (Fig. 5D) [94,95]. These double stranded breaks trigger DNA repair mechanisms that ultimately enable endogenous gene editing, gene deletions, and gene mutations [96]. The CRISPR-Cas9 system has quickly become a revolutionary tool in genome engineering that utilizes customizable gRNAs and the RNA-guided nuclease, Cas9 [97–101]. If Cas9 recognizes the correct protospacer adjacent motif (PAM) sequence immediately following the target sequence, it will bind to the DNA and introduce double stranded breaks in the target DNA, initiating internal repair mechanisms [102] (Fig. 5D). This technology was originally discovered in prokaryotes, and has also been shown to function in other organisms including eukaryotes for genome editing and gene control [103,104]. However, maximizing the usefulness and therapeutic relevance of these tools requires precisely controlling their activity to


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minimize their off-target effects. For this reason, significant effort is underway to develop methods for genetically, chemically, and optically controlling the activity of these genome-editing proteins. For example, the CRISPR-Cas9 system has been modified to control Cas9 and gRNA activity with small molecule inducers to temporally remove genes during differentiation to enhance cell fate outcomes [105], control cell death [106], and develop a conditional transgenic mouse line for inducible genome editing [107]. Another approach for controlling the activation of Cas9 is by using split Cas9 halves [108]. In this method, the addition of a small molecule inducer mediates the dimerization of the split Cas9 halves, restoring the Cas9 activity. Recently, CRISPR regulatory devices were layered to create functional cascading circuits to enable multi-level control of gene expression [109] and the multiplexed protein and gRNAs from a single transcript, in addition to CRISPR RNA scaffolds that allow for distinct gene regulatory actions in a modular fashion (Fig. 3F) [110]. Engineered therapeutic cells programmed to autonomously sense and respond to the environment have important implications in medicine. However, a significant challenge facing synthetic biology is to efficiently integrate genetic circuits into the appropriate location within a host genome, while maintaining the genetic integrity of both the circuit and host. Therefore, computational approaches to predict circuit function and reliability are underway to address genetic circuit reliability and long-term stability [111–115]. Until recently, it was difficult to imagine how synthetic biologists could implement the complexity of genetic circuit function in the human body. With genome editing nucleases, targeting capabilities, and the ability of biomaterials to facilitate the delivery of genetic circuits in vivo, next generation treatment strategies are becoming a reality. 2.4. Cellular computation and memory Cells have the natural ability to sense multiple signals within their environment, perform computations, store information, and execute behaviors based on this information [8,116]. Harnessing these capabilities is a primary goal of many synthetic biologists in order to achieve biological control of cells for next-generation therapeutics, diagnostics, and biomanufacturing applications [117–123]. The ability to convert transient molecular signals that a cell experiences into genome encoded memory would enable synthetic biologists to track a variety of biological phenomena at the molecular level. This memory would capture what cells experience in their native environments (i.e. changes in the ECM, the presence/absence of other cells, levels of proteins) as they undergo differentiation, wound repair, and/or disease progression. Cellular memory would provide critical insight into how and when important cell decisions are made at the molecular level that can be used for early disease diagnostics and intervention. Furthermore, identifying threshold levels of various molecules that affect healthy cell states will help reveal the molecular characteristics that govern the differences between healthy and diseased states, offering targeted therapeutic interventions. Several approaches have been taken to build synthetic memory, including genetic switches that incorporate feedback loops (Fig. 6A) [124–126], and where a memory state corresponds to the dominance of one repressor (Fig. 6B) [24,25,35,36,127–129]. A second approach is based on the premise that genomic DNA provides an optimal setting for storing information in living cells, using recombinases that confer a permanent genomic alteration (Fig. 6C) [28,29,31,118,130]. Recombinases function by binding two recognition sequences and recombine or invert the DNA between the two sites; a method that has been used for decades in mice for gene targeting to evaluate gene

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function. Synthetic biologists are using synthetic memory in cells to convert transient cellular events into detectable memories encoded into the genome to better understand how small modifications can account for changes in cellular phenotype, including cell fate decisions, and molecular changes during the onset and duration of disease (Fig. 6D). 2.5. Riboregulators Riboregulators are RNA-based switches of complementary sequences that form a stem-loop structure, restricting access to a ribosome-binding site (RBS) within the sequence to prevent translation [131,132]. These switches are activated by a trigger sequence homologous to the hairpin, and trigger binding opens up the stem-loop structure, allowing ribosome binding to take place and the initiation of translation (Fig. 7A). Depending on the presence or absence of the trigger sequence, target gene expression can be switched on or off. Recently, toehold riboregulator switches were engineered to interact with the region around the translational start site of the mRNA of interest, instead of the RBS [133] (Fig. 7B). The toehold design enables a significantly more diverse set of riboregulator sequences for the controlled translation of a reporter gene, often GFP or LacZ for ease of detection. 2.6. Biomaterials Biomaterials play an important role in serving as implants to support cells for cell transplantation, enhancing tissue regeneration, cell transplantation, and advancing our understanding of cell–cell and cellECM interactions [134–139]. Altogether, these studies have improved our ability to investigate the relationships within healthy and diseased tissue environments for the purpose of developing novel therapies. The 3D environment a biomaterial provides constitutes a powerful tool for cell growth and has rapidly advanced our ability to investigate the coordinated interactions of many cellular phenomena. Biomaterials recapitulate the in vivo setting more completely than traditional 2D cultures, where cells are grown in monolayers [140,141]. While biomaterials provide a 3D environment characteristic of in vivo settings, mimicking and controlling the interplay between intrinsic (gene expression) and extrinsic (signals from other cells and the ECM) remain challenging due to the dynamic nature and timing of gene expression during complex cellular events. These challenges can be addressed by interfacing synthetic biology with biomaterials [142]. In this 2013 study, the authors demonstrated that adding inducers to the media activated gene expression in cells harboring genetic circuits that were encapsulated into hydrogels, or grown on the surface of hard scaffolds (Fig. 8B). The authors also engineered genetically interactive biomaterials that link gene network inducers to various materials typically used in tissue engineering studies. These novel biomaterials create microenvironments that are capable of controlling intrinsic and extrinsic cellular events to facilitate spatial and temporal control of gene expression [143,144]. Using principles of controlled release, genetic inducers were incorporated into biomaterials using click chemistry, a versatile and compatible method to chemically functionalize materials [143]. In one study, genetic inducers were covalently linked to the hydrogel network via ester bonds. When the ester bonds undergo hydrolysis, they cleave and release the inducer molecules allowing for its cellular uptake, which activates gene expression in the surrounding cells containing genetic circuits (Fig. 8C). In a second study, genetic inducers were linked to hydrogels via photolabile bonds, which were cleaved only in the presence of 302 nm of light [144], allowing for spatial and temporal control of gene expression (Fig. 8D). Altogether, these studies demonstrate that combining biomaterials and

Fig. 5. Targeted genome engineering. A. ZFNs and B. TALENs are nucleases which bind and cut specific DNA sequences. DNA is cut when two FokI nucleases dimerize around double stranded DNA. C. Cas9 forms a complex with gRNAs to bind and cut a double stranded DNA sequence. D. Programmable nucleases cause DSBs and induce NHEJ or HDR. Templates with homology arms can be added to take advantage of natural HDR mechanisms to either modify single nucleotides or insert a new sequence.


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Fig. 6. Approaches for engineering cellular memory. A. Positive feedback where a transcription factor (TF) activates its own transcription, leading to a permanent ON state. B. Toggle switches possess two repressors (R1 and R2) that turn each other off, leading to a bistable transcription state. Adding inducers can flip the transcriptional states. C. DNA based memory in which activation of an integrase leads to alternating DNA states D. Memory element to monitor environmental signals in vivo. i) In the absence of ATc, TetR represses the production of cro in the trigger element, and cI represses the procuction of cro and LacZ in the memory element. ii) In the presence of ATc, TetR is repressed, which allows the transcription of cro in the trigger element. iii) The activation of cro in the trigger element flips the memory element switch to repress cI, allowing the transcription of cro and LacZ.

synthetic biology enables the construction of 3D microenvironments that are capable of controlling both intrinsic and extrinsic cellular events in highly defined engineered niches. 3. Applications in synthetic biology Advances in synthetic biology have the potential to generate new therapeutics to augment, or address shortcomings of traditional drug delivery methods [145–149]. For example, pharmaceuticals are typically administered orally or intravenously and enter the systemic circulation, often causing significant deleterious side effects to otherwise healthy tissue. Programmed therapeutic cells that remain off until sensing a pathological state and respond with an appropriately tuned therapeutic biomolecule have the potential to establish next-generation therapeutics to treat human disease. This cell therapy approach facilitates the delivery of a variety of potentially therapeutic biomolecules that can

be specifically targeted to sites of disease/injury, delivered at controlled levels in response to the degree of disease/injury, and applied to short-lived therapeutic biomolecules that are not stable enough to be administered systemically. In this section, we review efforts in synthetic biology to sense biomolecules, systems to sense and respond to specific biological cues, and delivery platforms used to interface synthetic biology with therapeutic applications. 3.1. Biological sensing Synthetic biology is poised to supply a wealth of tools that are capable of functioning as sensors to interrogate intrinsic and extrinsic cellular events for identification of disease. The design and construction of genetic circuits offer broad molecular detection modalities, enable dynamic reporting, and have the potential to provide real-time surveillance of disease progression [150–152]. Altogether, these sensors

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Gene of Interest

Fig. 7. Riboregulator activation. A. Cis-repressed mRNA (crRNA) forms a stem-loop structure to prevent translation of the gene of interest. Upon addition of trans-activating RNA (taRNA), the crRNA undergoes a conformational change to unfold the stem-loop and expose the RBS for translation. B. The toehold riboregulator has a switch RNA which forms a stem-loop structure with a RBS within the loop to prevent ribosome binding and limit sequence constraints. Addition of trigger RNA disrupts the stem-loop structure, enabling translation of the gene of interest via the RBS.



9

A. Interfacing synthetic biology with biomaterials Activation by inducer

Cell encapsulation

Genetic output

B. Inducer added to media Inducer addition

C. Hydrolytic bond

Change in pH

D. Photolabile bond

Exposure to 302nm light

Fig. 8. Interfacing synthetic biology with biomaterials. A. Schematic of genetic circuit activation in PEG hydrogels. B. Cells harboring genetic circuits that are encapsulated in PEG (gray lines, ) hydrogels can be activated when by adding inducer molecules (orange stars, ) to the media. C. Ester bonds (blue dashed lines, ) undergo hydrolysis to release inducer molecules and activate genetic circuits within the surrounding cells. D. Photolabile bonds (green lines, ), when exposed to 302 nm light, cleave inducer molecules from the hydrogel network to activate a genetic circuit within surrounding cells.

identify molecules using genetic circuits that are coupled to a measurable output, including cell-based and cell-free strategies to enable the rapid response and reporting of specific molecules. 3.1.1. Cell-based sensors Diseased or aberrant physiological states emit unique signals that are detected by other cells and can be identified by diagnostics. Genetic circuits have been built to process and report on environmental inputs that are capable of performing Boolean logic operations [153], in addition to functioning as oscillators [39–42], toggle switches [35,36,154], pulse generators [41,155], and time-delay [156] of gene expression. The introduction of such circuits into various cell types is a promising avenue for diagnostics and cell-based therapies. For example, studies have shown that when injected into the body, bacteria naturally colonize and preferentially grow in tumor microenvironments without adversely affecting the health of the host, making them an attractable vehicle for diagnostic and therapeutic approaches [157–160]. Specifically, a study using high resolution in vivo bioluminescent imaging showed

that engineered bioluminescent bacteria and implanted bioluminescent tumors co-localize 11 days after IV administration of the engineered bacteria in mice that allow for visualization of tumor growth [161]. Recently, attenuated bacteria were engineered to create a remarkably sensitive diagnostic tool for liver cancer [162]. To accomplish this, orally administered probiotics were engineered to express LacZ and the luxABCDE operon. After ingestion, these engineered bacteria rapidly move across the gastrointestinal tract to the liver and amplify within the tumors. The resident bacteria express high levels of LacZ, which cleaves injected substrates that are filtered out by the renal system to be detected in the urine. Adding to the specificity of biological sensing, synthetic biologists have engineered genetic circuits that are capable of implementing Boolean logic operations (e.g. correct tissue AND disease present) that can integrate multiple inputs to achieve more accurate sensing [163, 164]. A recent study demonstrated that small regulatory microRNAs (miRNAs) could be used to selectively identify cell types, and classifying healthy vs. cancerous by a miRNA expression signature [165]. In this


10


genetic circuit design, the programmed conditional detection of the miRNA profile of cancer cells drives the expression of a reporter gene (e.g. GFP) that indicates the presence of cancer. More recently, a study designed ZF domains fused to split intein halves to bind adjacent recognition sequences and activate intein splicing (Fig. 9) [166]. Inteins are small segments of proteins that are capable of excising themselves and rejoining the flanking regions (exteins) with a peptide bond. Previous studies have shown that small molecules can be used to induce intein function to activate proteins via splicing [167,168]. In these studies, the addition of a small molecule, rampamycin, causes dimerization of FKBP and FRB protein domains that were fused to intein peptides. This dimerization brings the two inteins together and results in controlled splicing of the split protein. Using this concept, two ZF domains recognize base pairs in a continuous sequence and bind DNA adjacent to one another to allowing for intein complementation and splicing (Fig. 9). The authors screen the presence of a DNA sequence that, upon recognition, resulted in the splicing of a synthetic ZF-transcription factor to alter expression of a desired gene within a response circuit. This response circuit can be engineered to output a range of proteins to guide cells toward apoptosis or producing a therapeutic molecule. In addition to diagnosing disease, efforts are underway to discover what cells experience in their native environment, with the goal of designing cells to provide a record of changes that take place within their environment at the onset of disease and as disease progresses. Understanding molecular changes within cells will provide critical insight into how and when disease takes place. This information may offer novel targets for pharmaceutical intervention to prevent, slow, or cure disease. To accomplish this, cells are programmed with sensing, counting, and memory storage capabilities. Specifically, programming cells with memory using genetic circuits can capture what cells experience in their native environments. For example, in a recent study, bacteria were engineered to sense and remember exposure to the chemical anhydrotetracycline (ATc) in the mouse gut [169]. These engineered bacteria had genetic circuits containing the bistable bacteriophage lambda repressor protein cI/cro switch (memory element), and an ATc sensitive promoter (trigger element) that is activated in the presence of ATc [170] (Fig. 6D). The default setting of the memory element is the cI state. Analysis of fecal samples from mice with ATc in their drinking water demonstrated that bacteria stably switched to the cro state, whereas those with no ATc in the water remain in the cI

state. This exciting recording system demonstrates bacteria's potential to be engineered for diagnostics and environmental monitoring in healthy and diseased states, in addition to monitoring changes as a disease progresses. 3.1.2. Paper based cell-free sensors The discovery that synthetic biology does not require an intact cell is pushing synthetic biology boundaries. Two general systems exist to produce desired cell-free products: synthetic enzyme pathways (SEPs), and crude extract cell-free systems (CECFs). SEPs consist of a set of purified enzymes engineered in a metabolic pathway to produce only the desired product, and are highly relevant in metabolite production, however, this method is difficult to design and implement due to the high cost per reaction [171,172]. The CECF approach involves lysing cells and removing cellular debris and DNA, leaving the crude extracts containing metabolites and enzymes (Fig. 10A). Components of cellfree extracts are sufficient for metabolic processes, transcription, and translation to facilitate protein production and metabolite synthesis. Methods for obtaining consistent, robust, and high-throughput extracts have recently been established [173], making cell-free synthetic biology an exciting avenue for diagnosing complex diseases. With the addition of necessary metabolites and coding sequences, the cell-free system can be activated to produce a desired therapeutic protein product. More detailed reviews on cell free systems have recently been published [174–176]. Recently, a new concept emerged to use synthetic biology in a cellfree system by putting synthetic gene circuits onto paper to allow for rapid detection applications (Fig. 10B) [177]. This method uses the commercially available PT7 expression system consisting of ribosomes and 35 bacterial proteins [178] freeze dried onto 2 mm filter paper discs for use as diagnostic sensors. These sensors are stable for long-term storage at room temperature and are activated by rehydration. In this study, the authors demonstrated both the viability of the system and the enormous potential of combining cell-free and paper-based systems. Using toehold riboregulators (Fig. 7B) to recognize a particular target RNA within a sample, the paper-based system activates gene translation. Most notably, this system was demonstrated to function as a sensor for the Ebola virus in less than twelve hours at $21 USD per sensor. In this study, riboregulator sensors were designed with a toehold complimentary to 36 separate nucleotide regions of Ebola mRNAs, and upon binding, a LacZ mediated color change takes place

Split Intein Zinc Finger Trimers

Activating Domain Zinc Finger Binding Sites

GOI

Response Circuit

ZFs bind DNA Intein Splicing of ZF-TF

Gene activation by ZF-TF GOI

GFP Apoptosis Therapeutic

Fig. 9. ZF binding, intein splicing and gene activation. ZF sensor complexes recognize and bind to adjacent 9 bp sequences, initiating intein splicing. ZF spliced with an activating domain create a ZF-transcription factor able to specifically bind upstream of an engineered GOI and initiate gene expression. This GOI can range from GFP to indicate infected cells to a therapeutic protein to help combat an infection.



11

A. Cellular Machinery

RNA Polymerase

Cell-Free Extract

Lyse & Spin

Ribosome Protein

C.

B.

ΔT Genetic Circuit & Sample RNA

Cellular Machinery

Fig. 10. Cell-free and paper-based systems. A. Bacteria are grown up in culture, lysed, and centrifuged to remove cellular debris. The resulting supernatant contains the cellular machinery necessary for in vitro RNA and protein synthesis. Cellular machinery within the extract includes RNA polymerases, ribosomes, and other proteins necessary to perform desired in vitro tasks. B. Cell-free extracts are added to paper disks creating a platform for synthetic circuitry and diagnostics. C. Synthetic toehold riboregulator designed to recognize Ebola RNA sequence is designed and added to the cell-free paper based system. Presence of Ebola RNA leads to riboregulator binding and activation of LacZ expression, resulting in color change from yellow to purple for diagnosis.

on the paper disc (Fig. 10C). This paper-based system is designed to give a quantitative readout with a plate reader, a cell phone camera, or a qualitative readout using colorimetric changes visible by eye. Using synthetic biology in a paper-based cell-free platform is widely applicable for diagnostics in the developing world due to its robust setup, ease of use and readout, and low cost [179]. Furthermore, refrigeration, specialized equipment and incubators are not required. With a robust paperbased cell-free system that can be paired with synthetic biology designs, the authors have initiated a new genre of diagnostic tests. 3.2. Sense and respond Genetic circuits have been developed to couple sensing with a therapeutic response [180]. For example, in two separate studies, genetic circuits were shown to improve the stability of insulin and glucose levels in diabetic mice. In the first study, a light controlled genetic circuit was engineered to control the secretion of the glucagon-like peptide 1 (GLP-1), a potent hyperglycemic hormone [181]. The design of this genetic circuit included the controlled ectopic expression of melanopsin, a human vitamin-A-dependent G protein coupled receptor that is normally expressed in retinal ganglion cells. Upon exposure to blue light, melanopsin expression is induced, which leads to an intracellular calcium surge that causes a cascade of signaling events to initiate the transcription of GLP-1 [70,182]. In the second study, a genetic circuit was engineered to produce insulin in response to decreasing pH levels by using a cAMP responsive promoter to demonstrate the controlled production of insulin when environmental pH dropped below the physiological range [182]. When cells harboring this genetic circuit were implanted into type 1 diabetic mice, the engineered cells returned insulin and glucose levels to the same level as that of healthy mice. Cancer is the collection of a large group of diseases characterized by uncontrolled cellular proliferation, and these abnormal cells can invade nearby healthy tissues as well as spread to other organs. Finding new therapies for treating and eliminating cancer is critical. However, a significant shortcoming in many current cancer treatments is the inability to distinguish and eliminate cancerous cells from the surrounding healthy tissue. Therefore, recognizing unique identifiers of cancer such as the tumor microenvironment, metabolic states of cancer cells, and

unique mRNA/gene expression patterns is essential for establishing advanced cancer therapies. For example, synthetic biologists have taken advantage of the fact that tumor microenvironments are hypoxic by building genetic circuits that are capable of sensing the hypoxic environment and respond by invading and lysing cancerous cells [183]. Recently, the expression of the prodrug, gancilclovir, was controlled by genetic circuits that function as AND gates to selectively kill cancer cells [19,164]. Similarly, two previously discussed synthetic biology systems can be re-engineered to have a therapeutic response. In one study, a HeLa cancer cell profile was established that included sets of HeLa-high and HeLa-low markers that were substantially different from healthy cells to construct a genetic circuit miRNA cell classifier that functions to detect the high/low state of miRNAs. This classifier was programmed to identify HeLa cancer cells and induce apoptosis through production of the hBax protein killing cancer cells [165]. Likewise, the ZF-based DNA sensor was engineered to replace the reporter gene with desired response elements such as initiating apoptosis in response to the identification of specific sequences in virally infected cells (Fig. 9). Altogether, these genetic tools have been developed to enhance treatment specificity by sensing disease and responding with a therapeutic outcome. 3.3. Delivery platforms Early efforts to use cells as therapeutic devices included their encapsulation into various biomaterials to bypass complications of the immune response when using allogeneic and/or xenogeneic cell sources [184,185]. Many biomaterials provide an optimal environment for cell survival because small molecules and nutrients move freely between the native tissue and the encapsulated cells [186–190]. For this reason, the implantation of genetically modified cells encapsulated within biomaterials presents an exciting alternative for therapeutic gene circuit delivery. Encapsulation offers several advantages compared to direct gene delivery by effectively isolating the genetically modified cells from host tissues to provide safety mechanisms in the event of known and unknown immunogenic side effects. To date, much work has been done to highlight the synthetic biology opportunities linking novel inputs to functional outputs from implanted


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cells encapsulated within biomaterials. Opportunities include encapsulated cells to study and treat metabolic disorders, diabetes, and obesity. A recent study demonstrated systemic induction of genetic circuits for the spatial and temporal control of gene expression in vivo [143]. Cells harboring a genetic circuit controlling GFP expression responding to exposure to the small molecule inducer, IPTG, were seeded on sponges and hydrogels and implanted in various locations in mice. After the addition of IPTG to the drinking water, GFP induction was initiated. The level of transgene expression was directly regulated by IPTG concentration and could easily be tuned by dosing varying amounts of IPTG to the water. Altogether, these studies demonstrate that integrating synthetic biology and materials science enable the delivery of genetic circuits that are capable of regulating the activity of genetic circuits in vivo (Fig. 11). 4. Conclusions Our understanding of how to program cells using gene circuits has advanced remarkably over the past decade. The field of synthetic biology continues to expand the genetic toolbox of dynamic regulatory systems that implement genetic control to interrogate natural biological phenomena. Because the future of this technology requires an understanding of cellular complexity, many synthetic biologists have turned to the achievements in systems biology for elucidating genetic signatures and biomarkers associated with diseased cells and environments. Therefore, collaborations between systems biologists and synthetic biologists are critical for accelerating both our understanding of biological systems and our ability to engineer cells. In this regard, interfacing computational predictions of gene network function with the tools built by synthetic biologists will accelerate both our understanding of complex biological systems, and our ability to quantitatively engineer cells that will undoubtedly lead to scientific discovery. The promise of stem cells to treat and cure disease is fundamental to the excitement surrounding cell-based therapies. The first demonstration of stem cells curing disease took place in 1968 when hematopoietic stem cells were taken from a healthy patient's bone marrow and transferred to an unrelated diseased patient [191]. Bone marrow transplantation is currently the most widely used, and undoubtedly the most successful, application of stem cell therapy in the clinic because it is able to regenerate all cells of the blood system including immune cells, red blood cells, and platelets. Because of this success, much work has focused on cell-based therapies for regenerating and repairing damaged tissue [192,193], using stem cells to secrete proteins and paracrine factors to augment the natural healing process [194–196], and the generation of CAR-T cells that have engineered receptors designed to target cancer cells [197–199]. Altogether, these important advances have provided invaluable insights for clinicians and scientists

2. Optogenetics

1. Feeding

3. Sense and Respond

Inducer

Fig. 11. Control of encapsulated cells in-vivo. Engineered cells within biomaterials can be controlled in vivo by feeding the animal inducer, activating the genetic circuit with light, or designing the genetic circuit to sense a physiologic state and respond with therapy.

to start to understand the complexity of immune rejection, the importance of detecting small physiological changes that may lead to disease, and the need to monitor how cells interface within the body. Medicine is anticipated to benefit greatly from cells that are engineered with the ability to integrate multiple inputs, discriminate between cell states, and respond appropriately to combat disease/ injury. We envision that with better tools and well-characterized parts, synthetic biologists will develop revolutionary new therapies to better understand disease progression and advance medical applications. Furthermore, engineered cells that have the ability to detect, record, and report on the environmental landscape in vivo will provide new insights to understand aberrant physiology and disease progression that will lead to valuable diagnostics to identify diseases early and develop new therapeutics to treat diseases, before the emergence of deleterious symptoms. Many of the systems presented in this review represent proof of principle approaches to detect harmful signals or disease. Another key aspect of synthetic biology is to ensure reproducibility of systems across cell types and applications. Synthetic biology can encounter difficulties with variable circuit efficacy when circuits are introduced across different organisms and cell lines. Focusing on using standardized circuit elements that have been proven to function in multiple bacterial or mammalian hosts will increase ease of development as well as ensure therapies reach patients faster. Furthermore, implementing multiple genetic circuits capable of Boolean logic will enable programming of a genetically interactive material that supports successive cellular events in a spatial and temporal manner. As we continue to advance our ability to engineer cells harboring genetic circuits that can function in various delivery platforms, we move toward the reality of commonly prescribed cell-based therapeutics. Acknowledgments We gratefully acknowledge the funding from the University of Utah startup funds, the National Science Foundation CAREER Program, and the Office of Naval Research Young Investigator Program. References [1] J.M. Callura, C.R. Cantor, J.J. Collins, Genetic switchboard for synthetic biology applications, Proc. Natl. Acad. Sci. U. S. A. 109 (2012) 5850–5855. [2] N. Nandagopal, M.B. Elowitz, Synthetic biology: integrated gene circuits, Science 333 (2011) 1244–1248. [3] D. Sprinzak, M.B. Elowitz, Reconstruction of genetic circuits, Nature 438 (2005) 443–448. [4] C.C. Guet, M.B. Elowitz, W. Hsing, S. Leibler, Combinatorial synthesis of genetic networks, Science 296 (2002) 1466–1470. [5] M. Elowitz, W.A. Lim, Build life to understand it, Nature 468 (2010) 889–890. [6] C.J. Bashor, A.A. Horwitz, S.G. Peisajovich, W.A. Lim, Rewiring cells: synthetic biology as a tool to interrogate the organizational principles of living systems, Annu. Rev. Biophys. 39 (2010) 515–537. [7] N.J. Guido, X. Wang, D. Adalsteinsson, D. McMillen, J. Hasty, C.R. Cantor, T.C. Elston, J.J. Collins, A bottom-up approach to gene regulation, Nature 439 (2006) 856–860. [8] C.G. Bowsher, P.S. Swain, Environmental sensing, information transfer, and cellular decision-making, Curr. Opin. Biotechnol. 28C (2014) 149–155. [9] T.L. Deans, J.H. Elisseeff, The life of a cell: probing the complex relationships with the world, Cell Stem Cell 6 (2010) 499–501. [10] F. Lienert, J.J. Lohmueller, A. Garg, P.A. Silver, Synthetic biology in mammalian cells: next generation research tools and therapeutics, Nat. Rev. Mol. Cell Biol. 15 (2014) 95–107. [11] N. Anesiadis, H. Kobayashi, W.R. Cluett, R. Mahadevan, Analysis and design of a genetic circuit for dynamic metabolic engineering, ACS Synth. Biol. 2 (2013) 442–452. [12] S. Basu, Y. Gerchman, C.H. Collins, F.H. Arnold, R. Weiss, A synthetic multicellular system for programmed pattern formation, Nature 434 (2005) 1130–1134. [13] S. Basu, R. Mehreja, S. Thiberge, M.T. Chen, R. Weiss, Spatiotemporal control of gene expression with pulse-generating networks, Proc. Natl. Acad. Sci. U. S. A. 101 (2004) 6355–6360. [14] T. Bulter, S.G. Lee, W.W. Wong, E. Fung, M.R. Connor, J.C. Liao, Design of artificial cell–cell communication using gene and metabolic networks, Proc. Natl. Acad. Sci. U. S. A. 101 (2004) 2299–2304. [15] J.M. Callura, D.J. Dwyer, F.J. Isaacs, C.R. Cantor, J.J. Collins, Tracking, tuning, and terminating microbial physiology using synthetic riboregulators, Proc. Natl. Acad. Sci. U. S. A. 107 (2010) 15898–15903.


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