Are the Biomedical Sciences Ready for Synthetic Biology? 2020 PDF

Document Details

Uploaded by Deleted User

University of Michigan

2020

Maxwell S. DeNies, Allen P. Liu, Santiago Schnell

Tags

synthetic biology biomedical research physiology engineering approaches

Summary

This document examines the potential of synthetic biology as a research tool in biomedical sciences. It outlines top-down and bottom-up approaches, providing examples. This paper draws on principles of engineering and computer science to design biological systems.

Full Transcript

BioMol Concepts 2020; 11: 23–31 Mini-Review Open Access Maxwell S. DeNies, Allen P. Liu, Santiago Schnell* Are the biomedical sciences ready for synthetic biology? https://doi.org/10.1515/bmc-2020...

BioMol Concepts 2020; 11: 23–31 Mini-Review Open Access Maxwell S. DeNies, Allen P. Liu, Santiago Schnell* Are the biomedical sciences ready for synthetic biology? https://doi.org/10.1515/bmc-2020-0003 received November 19, 2019; accepted January 2, 2020. Introduction Abstract: The ability to construct a functional system Discovery and engineering are two research approaches from its individual components is foundational to commonly used to understand the natural world. To understanding how it works. Synthetic biology is a date, much of our knowledge of physiology is derived broad field that draws from principles of engineering from research using a discovery mindset, which focuses and computer science to create new biological systems on unraveling a system to understand how it works. or parts with novel function. While this has drawn well- Individual components of a system are removed or deserved acclaim within the biotechnology community, modified, and observations of how the system changes are application of synthetic biology methodologies to study recorded and synthesized to create a model of the system. biological systems has potential to fundamentally change Due to the complexity of biological systems, oftentimes it how biomedical research is conducted by providing is not possible to measure all effects simultaneously, thus researchers with improved experimental control. While this strategy can be riddled with potential side effects and the concepts behind synthetic biology are not new, we limitations (technical, metrological, and biological). Yet, present evidence supporting why the current research this approach is essential and the initial step on the path environment is conducive for integration of synthetic to mechanistic understanding as it is difficult to infer how biology approaches within biomedical research. In this a system works without first identifying the individual perspective we explore the idea of synthetic biology as components. An engineer takes the opposite approach; a discovery science research tool and provide examples using well-characterized individual components to build of both top-down and bottom-up approaches that have the system from scratch. This approach is structured on already been used to answer important physiology well-known design principles and iterative improvements questions at both the organismal and molecular level. that are implemented over time. In theory, as the design evolves, we develop a greater understanding of how the Keywords: engineering approaches; design principles; overall system works. One common theme that defines mechanisms; bottom-up discovery; top-down discovery the synthetic biology field is the application of this engineering mindset to biology. Biological systems have been redesigned by repackaging individual parts into novel combinations with unique or desirable properties, *Corresponding author: Santiago Schnell, Cellular and Molecular often with applied science implications. Scientists are Biology Graduate Program, University of Michigan Medical only now beginning to take action and use synthetic School, Ann Arbor, Michigan, USA; Department of Molecular & biology as a tool for research discovery [1–6]. Integrative Physiology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, USA, E-mail: [email protected] What is synthetic biology? Maxwell S. DeNies, Cellular and Molecular Biology Graduate Program, University of Michigan Medical School, Ann Arbor, Synthetic biology is a broad field that is difficult to Michigan, USA Allen P. Liu, Cellular and Molecular Biology Graduate Program, define. Functionally, it encompasses (1) the design and University of Michigan Medical School, Ann Arbor, Michigan, USA, construction of new biological entities such as enzymes, Department of Mechanical Engineering, University of Michigan, genetic circuits (i.e. genetic logic gates that mimic Ann Arbor, Michigan, USA, Department of Biomedical Engineering, electrical circuits) and cells, (2) the reconstruction of University of Michigan, Ann Arbor, Michigan, USA, Department of existing biological systems with the goal of understanding Biophysics, University of Michigan, Ann Arbor, Michigan, USA Open Access. © 2019 Maxwell S. DeNies et al., published by De Gruyter. This work is licensed under the Creative Commons Attribution-NonCommercial NoDerivatives 4.0 License. 24 Maxwell S. DeNies et al: Are the biomedical sciences ready for synthetic biology? mechanism, and/or (3) the redesign of existing biological Examples of top-down synthetic systems. In the first point, synthetic biology is similar to synthetic organic chemistry ; its main goal is to biology harness biological processes and knowledge to create Many investigators within the physiology and biomedical new materials or capabilities not found in nature. Those sciences community have already begun to take adopting the second and third point view synthetic biology advantage of top-down synthetic biology tools to advance as the next generation of biological reconstitution as its their research. This is most evident in optogenetics. new approaches and capabilities allow researchers to ask Pioneered by Deisseroth, Boyden, and colleagues [20–22], deeper questions pertaining to molecular mechanisms, optogenetics is one example where top-down approaches the origins of life, and the design of a minimal cell have been implemented at both the organismal and capable of harnessing the basic principles of life. molecular levels to control and modify signaling activities Another view is that synthetic biology represents the in individual cells [23, 24] as well as to gain insight into promise of systems biology, providing the tools necessary specific neuronal circuitry and brain activity function in to interpret and interrogate the molecular insights rodents [23, 25] and zebrafish. Recently, Swift et al. derived from increasingly complex systems-level data. utilized channelrhodopsin to modulate locus coeruleus Regardless of definition, the tools and concepts afforded activity in rats and showed they can predictably control by synthetic biology have great potential to contribute to sleep spindle formation and consequently interfere with the biomedical sciences. REM (rapid eye movement) and NREM (non rapid eye movement) sleep. They found that these changes directly impacted rat memory formation and that by preventing Top-down synthetic biology sleep spindle formation, rats were no longer able to reliably recall learned tasks. These experiments would The field of synthetic biology can be divided into two not have been possible without the use of their synthetic broad domains based on research strategy - top-down and biology approach as the degree of accuracy and precision bottom-up [9, 10]. Top-down approaches aim to harness required to modulate a specific part of the brain is not biological phenomenon to engineer a predictable response feasible using other methods such as drug perturbation or to an input. Compared to traditional biomedical research genetic knockdown. approaches, this allows for improved experimental While the aforementioned optogenetic approaches control over how biological processes are measured have played a major role in linking neuron activity to and/or modulated. To accomplish this, researchers specific actions, prior knowledge of the underlying often redesign and modify well-characterized biological neuronal circuitry is necessary. To overcome this components for their advantage. This could be expressing limitation, multiple groups have devised strategies that optogenetically sensitive ion channel to modulate neuron utilize calcium flux (commonly observed upon neuron function, or designing a molecular sensor to monitor activation) and light activation to investigate activity- cell signaling events in real-time. Early examples of this dependent neuronal processes. An initial iteration of methodology include the development of a genetic toggle this was CaMPARI, an engineered photo-switchable switch and a genetic oscillator in bacteria [12, 13]. fluorescent protein that irreversibly switches from green More recently, researchers have focused on modifying to red light emission upon binding calcium (i.e. neuron organisms to have new capabilities by designing genetic activation) in the presence of light (Figure 1A). As circuits that integrate multiple signals via logic gates a proof-of-concept, researchers expressed CaMPARI and couple sensing with a biological readout such ubiquitously in the Drosophila brain. By applying light to as fluorescence or biological activity [14–17]. From a specific brain regions while exposing flies to a panel of biotechnology viewpoint, considerable advancements in odors, researchers were able to identify specific neurons chimeric antigen receptor T cells (CAR-T) and other smart involved with the odor sensory response by looking for immunotherapies that contain self-regulating control neurons that had switched from green to red fluorescence elements have been made possible by similar top-down (Figure 1B, C). synthetic biology approaches [18, 19]. One limitation of this approach is that it cannot be coupled to a downstream effector. Recently, researchers in the Ting group developed a similar tool that couples neuron activity to a transcriptional response. Similarly Maxwell S. DeNies et al: Are the biomedical sciences ready for synthetic biology? 25 Figure 1: Recent top-down synthetic biology approaches to study biology. A. Schematic representation of CaMPARI technique. B. Proposed experimental design to use CaMPARI to study activity dependent neuronal circuitry in Drosophila. C. Cartoon of Drosophila brain illustrating potential result from CaMPARI study depicted in B. As is illustrated, the entire brain is fluorescently green however, upon activation of CaMPARI specific regions of the brain responsible for a response to a stimulus are switched to red fluorescence emission. D. Schematic of the FLARE technology. E. Proposed experimental strategy illustrating FLARE’s record and replay ability in neurons. Panels for this figure were adapted from Fosque et al 2015 (panels A-C) and Wang et al 2017 (panels D&E). to CaMPARI, FLARE (Fast Light- and Activity-Regulated indicative of an activated neuron (Figure 1E). This Expression) requires high calcium and light for activity. is a powerful proof-of-concept as FLARE allowed the However, unlike CaMPAIR where activation is solely researchers to not only identify activated neurons but also linked to a change in fluorescence, FLARE activation leads the ability to manipulate them afterwards. to a change in downstream transcription. Briefly, neuron In addition to optogenetic approaches, researchers activation results in a calcium influx, which leads to the recently developed a cellular memory system (MEMOIR) coupling of a TEV protease to the membrane tethered that records cellular history using a fluorescent readout LOV domain-protected transcription factor (Figure 1D).. One of the major limitations of lineage tracing At this time, steric hindrance prevents protease cleavage experiments is that spatial information is lost. To overcome and functional transcription factor release (Figure 1D). this issue, the researchers introduced a series of identical However, upon light activation, this is relieved and DNA sequences (i.e. coined scratchpads) that each had protease cleavage results in the release of a functional an associated unique barcode identification sequence. transcription factor that is able to activate transcription of Next they used the stochastic gene editing capabilities a desired target (Figure 1D). Compared to CaMPARI, of CRISPR-Cas9 to randomly and irreversibly mutate the FLARE allows researchers access to additional tools originally identical scratch pads to generate of record beyond fluorescent proteins to study downstream neuron of cellular history. As a readout, single molecule RNA activities. An interesting application of this is illustrated fluorescence in situ hybridization probes (smFISH) were in Figure 1E. In this example, researchers coupled FLARE used to simultaneously detect scratchpads and unique activity to the transcription of an Opsin (light sensitive barcodes in single cells allowing them to determine protein) and after 18hrs Opsin was activated using red light the lineage of individual cells within a mouse embryo to trigger an increase in calcium indicator fluorescence – stem cell population simultaneously via direct imaging 26 Maxwell S. DeNies et al: Are the biomedical sciences ready for synthetic biology?. Future applications of this approach could include approaches within the organoid space are nicely review modifying this system to record other cellular events and by Morsut and Davies. could be accomplished by coupling CRISPR-Cas9 activity At the molecular level, recent research has focused to biological sensor to measure a specific biological on developing liposomes (asymmetric or symmetric process. phospholipid double emulsion vesicles) with defined At the single cell physiology level, several groups input-output relationships [44, 45]. This is the initial have engineered sensors and other synthetic constructs in phase in the development of synthetic organelles or mammalian cells to detect changes in cell signaling [30– cells and represents a major first step in overcoming 33], as well as interrogate the role of protein localization the limitation of traditional bulk in vitro reconstitution in regulating these processes [34, 35]. One clever use of experiments. In contrast to traditional approaches, by synthetic biology to study cell signaling dynamics, pattern conducting experiments within liposomes, researchers formation, and differentiation was the development are able to better recapitulate the spatiotemporal of the synthetic Notch (SynNotch) circuit. Using regulation of a cell or organelle, which is necessary for the Notch receptor as a base (due to the simplicity and understanding more complicated biological mechanisms direct transcription response to ligand activation), the that have spatiotemporal elements. In addition to Lim lab replaced the extracellular ligand-binding motif democratizing liposome generation, microfluidic devices and intracellular transcription-regulating motif with have also been used to generate nested liposomes that user-defined protein domains that recognize “synthetic more closely resemble cellular structures. For more ligands”. The result was a chimeric receptor capable of information, a nice review of the properties of liposomes sensing an exogenous extracellular signal and translating and polymersomes as well as generation methods was it into a desirable transcriptional output. Due to the recently published by Ridear et al.. direct transcription response of these chimeric receptors, Improved reliability and utility of cell-free expression co-expressing different circuits is readily possible. systems (i.e. coupled transcription-translation reactions Applications of this approach have facilitated research (TXTL)) , are a second major advancement within into cell signaling circuitry, pattern formation and cell bottom-up synthetic biology that has great potential to differentiation in both cell culture and organoid models impact biomedical research. While cell-free lysates have [36–41]. been used for more than 50 years , recent advancements have made these approaches increasingly feasible. Cell-free expression systems are composed of a crude cell Bottom-up synthetic biology lysate without the nucleus or plasma membrane fractions. Lysates are then supplemented with genetic circuits, RNA polymerase as well as metabolic building blocks In contrast to top-down approaches, bottom-up synthetic (NTPs/Amino Acids) that allow for the simultaneous biology aims to assemble biological systems from scratch. transcription and translation of a target gene (Figure Unlike natural systems where it can be difficult to 2A). The inclusion of lipid membranes and organelles, predict experimental crosstalk and outcomes, bottom-up such as ER microsomes, in mammalian cell-free lysates approaches provide superior experimental control by have made the synthesis and functional reconstitution clearly defining experimental inputs and assumptions. of difficult-to-purify cell membrane proteins increasingly Organoids are one area of bottom-up synthetic biology possible (Figure 2A, B). Additionally, while in vitro in which groups of cells rather than proteins are utilized reconstitution has been used for years , the ability to as building blocks to reconstitute a synthetic tissue or encapsulate cell-free lysate with specific genetic circuits, organ. Introducing control elements via synthetic within liposomes or other artificial structures, have gene circuits within organoids allows researchers the made this technology increasingly useful as a model to ability to more closely mimic developmental processes study minimal cells or membrane bound organelle-like such as differentiation and pattern formation [3, 42, 43]. structures with spatiotemporal resolution. By comparing synthetic to natural processes, researchers are able to better understand the evolutionary origins and conserved mechanisms underlying these processes with greater control than methods that rely on systematically breaking the system to understand how components interact. Recent advancements using synthetic biology Maxwell S. DeNies et al: Are the biomedical sciences ready for synthetic biology? 27 Figure 2: Bottom-up synthetic biology approaches to study biology. A. Cell-free expression system schematic. Cell lysate is collected from a desired cell type – bacterial or mammalian – and supplemented amino acids, energy mix (NTPs), cofactors, salts, RNA polymerase, and your desired cell-free expression system compatible plasmid. Incubation a specified temperature results in the production of the desired protein (encoded by the plasmid). Experiments can be conducted in bulk or encapsulated within double emulsion vesicles (i.e. liposomes) B. Experimental strategy for the investigation of the SUN1 and SUN2 topology on artificial nuclear membranes. Initially silica beads are incubated with SUVs to generate model artificial nuclear membranes (ANMs). Afterwards, ANMs are incubated with cell-free lysate containing plasmids encoding the SUN1 or SUN2 genes, which upon protein synthesis, leads to the functional reconstitution of the SUN proteins on ANMs. Panel B was adapted from Majumder et al 2018. Examples of bottom-up synthetic an external stimulus is translated to intra-vesicular biology information. For many applications, this is critical as the ability to transfer information between different compartments is foundational to many biological systems. Bottom-up synthetic biology approaches have been used Bottom-up synthetic biology has also been used to to create artificial biological functions in liposomes that recapitulate natural processes to better understand the mirror natural biological processes. By encapsulating cell- molecular mechanism of a particular process. Researchers free lysate within liposomes, researchers have been able to recently used a mammalian cell-free expression system generate artificial input and output relationships within a to study the nuclear membrane architecture of the LINC synthetic vesicle. Early advances in this space have used complex (Linker of Nucleoskeleton and Cytoskeleton) on mechanical sensing as a proof-of-principle application. artificial nuclear membranes (ANMs) not readily feasible In one example, cell-free lysate with a nested genetic using traditional cell biology techniques. WT and circuit was encapsulated within phospholipid liposomes. mutant SUN1 and SUN2 proteins (components of LINC The genetic circuit encoded a mechanosensitive channel complex) were individually and co-expressed using membrane protein (MscL) and G-GECO, a genetically mammalian cell-free lysate and allowed to integrate into encoded calcium sensor. When liposomes were exposed ANMs (Figure 2B). Utilizing a protease protection assay to hypo-osmotic shock, an influx of calcium through and comparing WT and mutant receptors, the authors activated MscL channels was reversibly detected by were able to reveal topology differences between SUN1 G-GECO fluorescence. Due to the membrane lipid and SUN2. To test the functionality of this artificial charge, diffusion of calcium into liposomes was solely model of the LINC complex, the authors reconstituted dependent on MscL expression and osmotic shock. KASH-binding SUN proteins for the first time. This study This example highlights two important proof-of-principle showcases the potential of using synthetic platforms to concepts that exemplify of the utility of bottom-up better understand molecular mechanisms and highlights synthetic biology. Firstly, it showcases that difficult-to- how recent advancements in synthetic biology are purify membrane proteins can be functionally produced responsible for growth in this area. using the cell-free expression system. Secondly, while this is a simple mechanism, it is an example of where 28 Maxwell S. DeNies et al: Are the biomedical sciences ready for synthetic biology? Cell-free expression systems have also been used either include or have been influenced by RNA sequencing for rapid prototyping. Recent work from the Noireaux data sets and the power of this technology is beginning to lab showcased the utility this technology to rapidly test be realized within the biomedical sciences. CRISPR-Cas efficacy in vitro before verifying results in There are many parallels between the research a more complex experimental system. To do so, environment that enabled the rise of high-throughput CRISPR-Cas machinery was expressed using the cell-free sequencing technologies and the current environment expression system with linear DNA targets and guide in the synthetic biology. Facilitated by the development RNAs. Using a fluorescent readout for CRISPR efficacy of software tools that aid in genetic circuits and sensors they were able to quickly screen guide RNAs for efficacy. design [55, 56], new molecular cloning strategies to This approach was further used to characterize the effects generate difficult-to-construct plasmids, and increased of CRISPR inhibitory proteins as well as to quickly identify utility of high-throughput screening technologies, have CRISPR PAM sequences without the need for transfection all enable researchers ability to test new ideas with optimization - a common nuisance when characterizing unprecedented speed [56, 58]. Decreasing costs of these new Cas proteins. Furthermore, by removing services via commercial suppliers have also played a an additional layer of variability when conducting role in this trend. Additionally, for bottom-up synthetic experiments in cells or an organism, this approach is able biology, reproducible and accessible cell-free expression to distinguish between CRISPR-Cas or application-specific system lysates are now widely accessible through both issues such as transfection efficacy or unintended side commercial suppliers (NEB PURExpress and Thermo effects. Fisher Expressway) as well as via standardized protocols Future applications of bottom-up synthetic biology that make producing a variety of cell lysates in-house may permit investigation of proteins that are lethal or feasible for every lab [48, 59–65]. These developments have to limit crosstalk between signaling cascades that are rapidly increased the user-friendliness of using synthetic difficult to untangle. Additionally, immunodepletion of biology methodologies for academic researchers. Given specific proteins or isolation of specific organelles from these recent advancements, it is surprising that synthetic cell-free lysates (pioneered with Xenopus egg extracts biology approaches are not more commonly used research [52, 53]) may provide researchers with the ability to more tools within the biomedical research community. easily study how a protein or process interacts within the larger system without long-term side effects such as transcriptional reprogramming possible with knockdown or genetic knockout experiments. Challenges facing synthetic biology approaches within physiology Are we ready to adopt synthetic There are several challenges that we still face when applying synthetic biology methodologies to new biology in basic science? Lessons systems. As is true with any engineering process or assay, from the rise of high-throughput standardization and component modularity remain areas of improvement. Central to this is the ability to measure sequencing technologies things accurately and reliably. Recognizing the importance of measurement accuracy and reproducibility to synthetic As noted by others [1–5, 54], the biotechnology applications biology, a new joint initiative between NIST, Stanford, and of synthetic biology only capture a subset of its scientific industry (JIMB - https://jimb.stanford.edu/) has recently utility and that the transition from being a niche field been established with the goal of improving metrology to widely used scientific approach is necessary for the within the biological sciences and initially focusing in realization of its full potential. A similar evolution occurred synthetic biology and genomics. with rise of high-throughput sequencing (genomics, RNA For top-down approaches, off-target effects as well as sequencing etc.). Although the human genome project was specificity of reagents or genetic circuits are particularly completed in the early 2000s, for many, high-throughput important to consider. The leakiness of expression and sequencing technologies remained out of reach because of switch-like behavior of sensors can have consequential limited access to technology, required expertise, and cost. implications on the accuracy of measurements. As these methods have become increasingly accessible Researchers developing these technologies have spent over the intervening years, many research hypotheses significant time investigating these areas to limit the effects Maxwell S. DeNies et al: Are the biomedical sciences ready for synthetic biology? 29 of these challenges by including additional “insulators” to Fellowship Program and University of Michigan Rackham genetic circuits (commonly accounted for in sensor design Pre-Doctoral Fellowship. APL acknowledges support software tools) as well as modeling the compatibility of from National Science Foundation (1612917, 1844132, and multi-layer circuit designs [55, 58]. Recognizing these 1817909). Additionally, we would like to thank Mariana limitations, researchers have utilized irreversible methods Schnell for help with making the figure illustrations. events such as cleavage or DNA mutagenesis as readouts We would also like to thank Sagardip Majumder, to decrease measurement stochasticity. Matthias Truttmann, Carol Elias, and Suzanne Moenter Areas of improvement in bottom-up synthetic biology for constructive comments during the writing of the can be further sub-divided. To improve liposome stability, manuscript. the use of buffers with potential compatibility issues with other components remains an area of improvement. One report found that the use of polyvinyl alcohol precipitated some of the cell-free expression components in liposomes References. Oftentimes this limitation can be overcome by making 1. Bashor CJ, Horwitz AA, Peisajovich SG, Lim WA. Rewiring predictable changes to buffer composition. Robustness cells: synthetic biology as a tool to interrogate the of liposome generation protocols is also an area from organizational principles of living systems. Annu Rev Biophys. improvement as the strengths and weaknesses of each 2010;39(1):515–37. approach need to be considered for each application. For 2. Elowitz M, Lim WA. Build life to understand it. Nature. 2010 Dec;468(7326):889–90. cell-free expression systems, while the list of different cell- 3. Davies J. Using synthetic biology to explore principles of free lysates generated from different cell types continues development. Development. 2017 Apr;144(7):1146–58. to grow, it is still limited and can become an issue if cell 4. Ganzinger KA, Schwille P. More from less - bottom-up type specific processes are studied. Additionally, the reconstitution of cell biology. J Cell Sci. 2019 efficacy of the cell-free systems to synthesize all proteins Feb;132(4):jcs227488. 5. Liu AP. The rise of bottom-up synthetic biology and cell-free (very large or difficult to fold) remains largely unknown biology. Phys Biol. 2019 May;16(4):040201. and may require special modifications to ensure proper 6. Mathur M, Xiang JS, Smolke CD. Mammalian synthetic biology folding or modification for protein activity. for studying the cell. J Cell Biol. 2017 Jan;216(1):73–82. 7. Yeh BJ, Lim WA. Synthetic biology: lessons from the history of synthetic organic chemistry. Nat Chem Biol. 2007 Sep;3(9):521–5. Conclusion 8. Noireaux V, Maeda YT, Libchaber A. Development of an artificial cell, from self-organization to computation and self- As stated by Elowitz and Lim, to understand life we reproduction. Proc Natl Acad Sci USA. 2011 Mar;108(9):3473– 80. need to create it. An essential part of transitioning 9. Roberts MA, Cranenburgh RM, Stevens MP, Oyston PC. from observation to understanding is the ability to Synthetic biology: biology by design. Microbiology. 2013 predict and harness knowledge to create or resynthesize Jul;159(Pt 7):1219–20. important concepts. The potential to use synthetic biology 10. Schwille P. Jump-starting life? Fundamental aspects of methodologies to answer outstanding questions in synthetic biology. J Cell Biol. 2015 Aug;210(5):687–90. 11. Gardner TS, Cantor CR, Collins JJ. Construction of a physiology is great. Continually improving methodologies, genetic toggle switch in Escherichia coli. Nature. 2000 decreasing investment, and access to resources have Jan;403(6767):339–42. democratized synthetic biology and transformed what 12. Elowitz MB, Leibler S. A synthetic oscillatory network of was initially a niche field, into a powerful tool to study transcriptional regulators. Nature. 2000 Jan;403(6767):335–8. biomedical science. The goal of this manuscript was to 13. Danino T, Mondragón-Palomino O, Tsimring L, Hasty J. present evidence for why the rise of synthetic biology A synchronized quorum of genetic clocks. Nature. 2010 Jan;463(7279):326–30. applications within physiology is imminent. Whether 14. Nandagopal N, Elowitz MB. Synthetic biology: integrated gene you study electrophysiology, pattern formation, stem cell circuits. Science. 2011 Sep;333(6047):1244–8. differentiation, or cell and molecular physiology, it is time 15. Lim WA. Designing customized cell signalling circuits. Nat Rev to consider synthetic biology as a useful technique to Mol Cell Biol. 2010 Jun;11(6):393–403. advance your science. 16. Khalil AS, Collins JJ. Synthetic biology: applications come of age. Nat Rev Genet. 2010 May;11(5):367–79. 17. Weinberg BH, Pham NT, Caraballo LD, Lozanoski T, Engel A, Acknowledgements: MSD thanks support from the Bhatia S, et al. Large-scale design of robust genetic circuits National Science Foundation Graduate Research 30 Maxwell S. DeNies et al: Are the biomedical sciences ready for synthetic biology? with multiple inputs and outputs for mammalian cells. Nat 34. Kornmann B, Currie E, Collins SR, Schuldiner M, Nunnari J, Biotechnol. 2017 May;35(5):453–62. Weissman JS, et al. An ER-mitochondria tethering complex 18. Caliendo F, Dukhinova M, Siciliano V. Engineered Cell-Based revealed by a synthetic biology screen. Science. 2009 Therapeutics: Synthetic Biology Meets Immunology. Front Jul;325(5939):477–81. Bioeng Biotechnol. 2019 Mar;7:43. 35. Rost BR, Schneider-Warme F, Schmitz D, Hegemann 19. Roybal KT, Williams JZ, Morsut L, Rupp LJ, Kolinko I, Choe JH, et P. Optogenetic Tools for Subcellular Applications in al. Engineering T Cells with Customized Therapeutic Response Neuroscience. Neuron. 2017 Nov;96(3):572–603. Programs Using Synthetic Notch Receptors. Cell. 2016 36. Morsut L, Roybal KT, Xiong X, Gordley RM, Coyle SM, Thomson Oct;167(2):419–432.e16. M, et al. Engineering Customized Cell Sensing and Response 20. Deisseroth K, Feng G, Majewska AK, Miesenböck G, Ting Behaviors Using Synthetic Notch Receptors. Cell. 2016 A, Schnitzer MJ. Next-generation optical technologies for Feb;164(4):780–91. illuminating genetically targeted brain circuits. J Neurosci. 37. Santorelli M, Lam C, Morsut L. Synthetic development: building 2006 Oct;26(41):10380–6. mammalian multicellular structures with artificial genetic 21. Adamantidis AR, Zhang F, Aravanis AM, Deisseroth K, programs. Curr Opin Biotechnol. 2019 Oct;59:130–40. de Lecea L. Neural substrates of awakening probed with 38. Lin G, Chen Y, Slack JM. Imparting regenerative capacity optogenetic control of hypocretin neurons. Nature. 2007 to limbs by progenitor cell transplantation. Dev Cell. 2013 Nov;450(7168):420–4. Jan;24(1):41–51. 22. Zhang F, Wang LP, Boyden ES, Deisseroth K. 39. Guye P, Ebrahimkhani MR, Kipniss N, Velazquez JJ, Schoenfeld Channelrhodopsin-2 and optical control of excitable cells. Nat E, Kiani S, et al. Genetically engineering self-organization of Methods. 2006 Oct;3(10):785–92. human pluripotent stem cells into a liver bud-like tissue using 23. Johnson HE, Toettcher JE. Signaling Dynamics Control Cell Fate Gata6. Nat Commun. 2016 Jan;7(1):10243. in the Early Drosophila Embryo. Dev Cell. 2019 Feb;48(3):361– 40. Prochazka L, Benenson Y, Zandstra PW. Synthetic gene circuits 370.e3. and cellular decision-making in human pluripotent stem cells. 24. Toettcher JE, Gong D, Lim WA, Weiner OD. Light-based feedback Curr Opin Syst Biol. 2017;5:93–103. for controlling intracellular signaling dynamics. Nat Methods. 41. Saxena P, Heng BC, Bai P, Folcher M, Zulewski H, Fussenegger 2011 Sep;8(10):837–9. M. A programmable synthetic lineage-control network that 25. Swift KM, Gross BA, Frazer MA, Bauer DS, Clark KJ, Vazey differentiates human IPSCs into glucose-sensitive insulin- EM, et al. Abnormal Locus Coeruleus Sleep Activity Alters secreting beta-like cells. Nat Commun. 2016 Apr;7(1):11247. Sleep Signatures of Memory Consolidation and Impairs 42. Johnson MB, March AR, Morsut L. Engineering multicellular Place Cell Stability and Spatial Memory. Curr Biol. 2018 systems: using synthetic biology to control tissue self- Nov;28(22):3599–3609.e4. organization. Curr Opin Biomed Eng. 2017 Dec;4:163–73. 26. Andalman AS, Burns VM, Lovett-Barron M, Broxton M, Poole 43. Yin X, Mead BE, Safaee H, Langer R, Karp JM, Levy O. B, Yang SJ, et al. Neuronal Dynamics Regulating Brain and Engineering Stem Cell Organoids. Cell Stem Cell. 2016 Behavioral State Transitions. Cell. 2019 May;177(4):970–985. Jan;18(1):25–38. e20. 44. Majumder S, Garamella J, Wang YL, DeNies M, Noireaux V, Liu 27. Fosque BF, Sun Y, Dana H, Yang CT, Ohyama T, Tadross MR, AP. Cell-sized mechanosensitive and biosensing compartment et al. Neural circuits. Labeling of active neural circuits in programmed with DNA. Chem Commun (Camb). 2017 vivo with designed calcium integrators. Science. 2015 Jun;53(53):7349–52. Feb;347(6223):755–60. 45. Caschera F, Noireaux V. Compartmentalization of an all-E. coli 28. Wang W, Wildes CP, Pattarabanjird T, Sanchez MI, Glober GF, Cell-Free Expression System for the Construction of a Minimal Matthews GA, et al. A light- and calcium-gated transcription Cell. Artif Life. 2016;22(2):185–95. factor for imaging and manipulating activated neurons. Nat 46. Deng NN, Yelleswarapu M, Zheng L, Huck WT. Microfluidic Biotechnol. 2017 Sep;35(9):864–71. Assembly of Monodisperse Vesosomes as Artificial Cell 29. Frieda KL, Linton JM, Hormoz S, Choi J, Chow KK, Singer Models. J Am Chem Soc. 2017 Jan;139(2):587–90. ZS, et al. Synthetic recording and in situ readout of lineage 47. Rideau E, Dimova R, Schwille P, Wurm FR, Landfester K. information in single cells. Nature. 2017 Jan;541(7635):107–11. Liposomes and polymersomes: a comparative review towards 30. Regot S, Hughey JJ, Bajar BT, Carrasco S, Covert MW. High- cell mimicking. Chem Soc Rev. 2018 Nov;47(23):8572–610. sensitivity measurements of multiple kinase activities in live 48. Carlson ED, Gan R, Hodgman CE, Jewett MC. Cell-free protein single cells. Cell. 2014 Jun;157(7):1724–34. synthesis: applications come of age. Biotechnol Adv. 2012 31. Koudelková L, Pataki AC, Tolde O, Pavlik V, Nobis M, Gemperle Sep-Oct;30(5):1185–94. J, et al. Novel FRET-Based Src Biosensor Reveals Mechanisms 49. Nirenberg MW, Matthaei JH. The dependence of cell-free of Src Activation and Its Dynamics in Focal Adhesions. Cell protein synthesis in E. coli upon naturally occurring or Chem Biol. 2019 Feb;26(2):255–268.e4. synthetic polyribonucleotides. Proc Natl Acad Sci USA. 1961 32. Miura H, Matsuda M, Aoki K. Development of a FRET biosensor Oct;47(10):1588–602. with high specificity for Akt. Cell Struct Funct. 2014;39(1):9–20. 50. Majumder S, Willey PT, DeNies MS, Liu AP, Luxton GW. 33. Miyamoto T, Rho E, Sample V, Akano H, Magari M, Ueno T, et al. A synthetic biology platform for the reconstitution and Compartmentalized AMPK signaling illuminated by genetically mechanistic dissection of LINC complex assembly. J Cell Sci. encoded molecular sensors and actuators. Cell Rep. 2015 2018 Oct;132(4):jcs219451. Apr;11(4):657–70. 51. Marshall R, Maxwell CS, Collins SP, Jacobsen T, Luo ML, Begemann MB, et al. Rapid and Scalable Characterization of Maxwell S. DeNies et al: Are the biomedical sciences ready for synthetic biology? 31 CRISPR Technologies Using an E. coli Cell-Free Transcription- Translation System. Mol Cell. 2018 Jan;69(1):146–157.e3. 52. Jenness C, Wynne DJ, Funabiki H. Protein Immunodepletion and Complementation in Xenopus laevis Egg Extracts. Cold Spring Harb Protoc. 2018 Sep;2018(9):pdb.prot097113. 53. Petry S, Pugieux C, Nédélec FJ, Vale RD. Augmin promotes meiotic spindle formation and bipolarity in Xenopus egg extracts. Proc Natl Acad Sci USA. 2011 Aug;108(35):14473–8. 54. Bashor CJ, Collins JJ. Understanding Biological Regulation Through Synthetic Biology. Annu Rev Biophys. 2018 May;47(1):399–423. 55. Nielsen AA, Der BS, Shin J, Vaidyanathan P, Paralanov V, Strychalski EA, et al. Genetic circuit design automation. Science. 2016 Apr;352(6281):aac7341. 56. Appleton E, Madsen C, Roehner N, Densmore D. Design Automation in Synthetic Biology. Cold Spring Harb Perspect Biol. 2017 Apr;9(4):a023978. 57. Gibson DG, Young L, Chuang RY, Venter JC, Hutchison CA 3rd, Smith HO. Enzymatic assembly of DNA molecules up to several hundred kilobases. Nat Methods. 2009 May;6(5):343–5. 58. Brophy JA, Voigt CA. Principles of genetic circuit design. Nat Methods. 2014 May;11(5):508–20. 59. Swartz J. Developing cell-free biology for industrial applications. J Ind Microbiol Biotechnol. 2006 Jul;33(7):476– 85. 60. Chong S. Overview of cell-free protein synthesis: historic landmarks, commercial systems, and expanding applications. Curr Protoc Mol Biol. 2014;108:16.30.1–16.30.11. doi:10.1002/0471142727.mb1630s108 61. Sun ZZ, Hayes CA, Shin J, Caschera F, Murray RM, Noireaux V. Protocols for implementing an Escherichia coli based TX-TL cell-free expression system for synthetic biology. J Vis Exp. 2013 Sep;50762(79):e50762. 62. Anderson MJ, Stark JC, Hodgman CE, Jewett MC. Energizing eukaryotic cell-free protein synthesis with glucose metabolism. FEBS Lett. 2015 Jul;589(15):1723–7. 63. Martin RW, Majewska NI, Chen CX, Albanetti TE, Jimenez RB, Schmelzer AE, et al. Development of a CHO-Based Cell-Free Platform for Synthesis of Active Monoclonal Antibodies. ACS Synth Biol. 2017 Jul;6(7):1370–9. 64. Garamella J, Marshall R, Rustad M, Noireaux V. The All E. coli TX-TL Toolbox 2.0: A Platform for Cell-Free Synthetic Biology. ACS Synth Biol. 2016 Apr;5(4):344–55. 65. Shin J, Noireaux V. An E. coli cell-free expression toolbox: application to synthetic gene circuits and artificial cells. ACS Synth Biol. 2012 Jan;1(1):29–41. 66. Joint Initiative for Metrology in Biology. NIST https://www.nist. gov/jimb. Accessed 13 Jan 2020. 67. Ho KK, Lee JW, Durand G, Majumder S, Liu AP. Protein aggregation with poly(vinyl) alcohol surfactant reduces double emulsion-encapsulated mammalian cell-free expression. PLoS One. 2017 Mar;12(3):e0174689.

Use Quizgecko on...
Browser
Browser