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Efficient retroelement-mediated DNA writing in bacteria. Cell Syst 2021; 12:860-872.e5. [PMID: 34358440 DOI: 10.1016/j.cels.2021.07.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 11/03/2020] [Accepted: 07/09/2021] [Indexed: 10/20/2022]
Abstract
The ability to efficiently and dynamically change information stored in genomes would enable powerful strategies for studying cell biology and controlling cellular phenotypes. Current recombineering-mediated DNA writing platforms in bacteria are limited to specific laboratory conditions, often suffer from suboptimal editing efficiencies, and are not suitable for in situ applications. To overcome these limitations, we engineered a retroelement-mediated DNA writing system that enables efficient and precise editing of bacterial genomes without the requirement for target-specific elements or selection. We demonstrate that this DNA writing platform enables a broad range of applications, including efficient, scarless, and cis-element-independent editing of targeted microbial genomes within complex communities, the high-throughput mapping of spatial information and cellular interactions into DNA memory, and the continuous evolution of cellular traits.
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52
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Kiwimagi KA, Letendre JH, Weinberg BH, Wang J, Chen M, Watanabe L, Myers CJ, Beal J, Wong WW, Weiss R. Quantitative characterization of recombinase-based digitizer circuits enables predictable amplification of biological signals. Commun Biol 2021; 4:875. [PMID: 34267310 PMCID: PMC8282836 DOI: 10.1038/s42003-021-02325-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 05/24/2021] [Indexed: 12/24/2022] Open
Abstract
Many synthetic gene circuits are restricted to single-use applications or require iterative refinement for incorporation into complex systems. One example is the recombinase-based digitizer circuit, which has been used to improve weak or leaky biological signals. Here we present a workflow to quantitatively define digitizer performance and predict responses to different input signals. Using a combination of signal-to-noise ratio (SNR), area under a receiver operating characteristic curve (AUC), and fold change (FC), we evaluate three small-molecule inducible digitizer designs demonstrating FC up to 508x and SNR up to 3.77 dB. To study their behavior further and improve modularity, we develop a mixed phenotypic/mechanistic model capable of predicting digitizer configurations that amplify a synNotch cell-to-cell communication signal (Δ SNR up to 2.8 dB). We hope the metrics and modeling approaches here will facilitate incorporation of these digitizers into other systems while providing an improved workflow for gene circuit characterization.
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Affiliation(s)
- Katherine A Kiwimagi
- Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Justin H Letendre
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA
| | - Benjamin H Weinberg
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA
| | - Junmin Wang
- The Bioinformatics Graduate Program, Boston University, Boston, MA, USA
| | - Mingzhe Chen
- Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Leandro Watanabe
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA
| | - Chris J Myers
- Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT, USA
| | - Jacob Beal
- Raytheon BBN Technologies, Cambridge, MA, USA.
| | - Wilson W Wong
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA.
| | - Ron Weiss
- Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
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53
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Cao J, Novoa EM, Zhang Z, Chen WCW, Liu D, Choi GCG, Wong ASL, Wehrspaun C, Kellis M, Lu TK. High-throughput 5' UTR engineering for enhanced protein production in non-viral gene therapies. Nat Commun 2021; 12:4138. [PMID: 34230498 PMCID: PMC8260622 DOI: 10.1038/s41467-021-24436-7] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 06/14/2021] [Indexed: 12/14/2022] Open
Abstract
Despite significant clinical progress in cell and gene therapies, maximizing protein expression in order to enhance potency remains a major technical challenge. Here, we develop a high-throughput strategy to design, screen, and optimize 5' UTRs that enhance protein expression from a strong human cytomegalovirus (CMV) promoter. We first identify naturally occurring 5' UTRs with high translation efficiencies and use this information with in silico genetic algorithms to generate synthetic 5' UTRs. A total of ~12,000 5' UTRs are then screened using a recombinase-mediated integration strategy that greatly enhances the sensitivity of high-throughput screens by eliminating copy number and position effects that limit lentiviral approaches. Using this approach, we identify three synthetic 5' UTRs that outperform commonly used non-viral gene therapy plasmids in expressing protein payloads. In summary, we demonstrate that high-throughput screening of 5' UTR libraries with recombinase-mediated integration can identify genetic elements that enhance protein expression, which should have numerous applications for engineered cell and gene therapies.
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Affiliation(s)
- Jicong Cao
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eva Maria Novoa
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Center for Genomic Regulation (CRG), Barcelona, Spain
| | - Zhizhuo Zhang
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - William C W Chen
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Dianbo Liu
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Gigi C G Choi
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
- School of Biomedical Sciences, University of Hong Kong, Hong Kong, China
| | - Alan S L Wong
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
- School of Biomedical Sciences, University of Hong Kong, Hong Kong, China
| | - Claudia Wehrspaun
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Timothy K Lu
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
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54
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Litovco P, Barger N, Li X, Daniel R. Topologies of synthetic gene circuit for optimal fold change activation. Nucleic Acids Res 2021; 49:5393-5406. [PMID: 34009384 PMCID: PMC8136830 DOI: 10.1093/nar/gkab253] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Revised: 03/22/2021] [Accepted: 04/06/2021] [Indexed: 11/13/2022] Open
Abstract
Computations widely exist in biological systems for functional regulations. Recently, incoherent feedforward loop and integral feedback controller have been implemented into Escherichia coli to achieve a robust adaptation. Here, we demonstrate that an indirect coherent feedforward loop and mutual inhibition designs can experimentally improve the fold change of promoters, by reducing the basal level while keeping the maximum activity high. We applied both designs to six different promoters in E. coli, starting with synthetic inducible promoters as a proof-of-principle. Then, we examined native promoters that are either functionally specific or systemically involved in complex pathways such as oxidative stress and SOS response. Both designs include a cascade having a repressor and a construct of either transcriptional interference or antisense transcription. In all six promoters, an improvement of up to ten times in the fold change activation was observed. Theoretically, our unitless models show that when regulation strength matches promoter basal level, an optimal fold change can be achieved. We expect that this methodology can be applied in various biological systems for biotechnology and therapeutic applications.
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Affiliation(s)
- Phyana Litovco
- Department of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Natalia Barger
- Department of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Ximing Li
- Department of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Ramez Daniel
- Department of Biomedical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
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55
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Guo L, Lu J, Gao C, Zhang L, Liu L, Chen X. Dynamic control of the distribution of carbon flux between cell growth and butyrate biosynthesis in Escherichia coli. Appl Microbiol Biotechnol 2021; 105:5173-5187. [PMID: 34115183 DOI: 10.1007/s00253-021-11385-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 05/05/2021] [Accepted: 06/02/2021] [Indexed: 12/14/2022]
Abstract
Microbial cell factories offer an economic and environmentally friendly method for the biosynthesis of acetyl-CoA-derived chemicals. However, the static control of carbon flux can cause direct and indirect competition for acetyl-CoA between cell growth and chemical biosynthesis, limiting the efficiency of microbial cell factories. Herein, recombinase-based genetic circuits were developed to achieve the optimal distribution of acetyl-CoA between cell growth and butyrate biosynthesis. First, three dynamic devices-a turn-on switch, a turn-off switch, and a recombinase-based inverter (RBI)-were constructed based on Bxb1 recombinase. Then, the turn-on switch was used to dynamically control the butyrate biosynthetic pathway, which directly improved the consumption of acetyl-CoA. Next, the turn-off switch was applied to dynamically control cell growth, which indirectly enhanced the supply of acetyl-CoA. Finally, an RBI was adopted for the dynamic dual control of the distribution of acetyl-CoA between cell growth and butyrate biosynthesis. The final butyrate production rate was increased to 34 g/L, with a productivity of 0.405 g/L/h. The strategy described herein will pave the way for the development of high-performance microbial cell factories for the production of other desirable chemicals. KEY POINTS: • Competition for acetyl-CoA between cell growth and synthesis limits productivity. • Recombinase-based genetic circuits were developed to dynamic control of acetyl-CoA. • Optimal distribution of acetyl-CoA between cell growth and synthesis was achieved.
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Affiliation(s)
- Liang Guo
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, China
- International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122, China
| | - Jiaxin Lu
- School of Biotechnology, Jiangnan University, Wuxi, 214122, China
| | - Cong Gao
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, China
- International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122, China
| | - Linpei Zhang
- School of Biotechnology, Jiangnan University, Wuxi, 214122, China
| | - Liming Liu
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, China
- International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122, China
| | - Xiulai Chen
- State Key Laboratory of Food Science and Technology, Jiangnan University, 1800 Lihu Road, Wuxi, 214122, China.
- International Joint Laboratory on Food Safety, Jiangnan University, Wuxi, 214122, China.
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56
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Chao G, Travis C, Church G. Measurement of large serine integrase enzymatic characteristics in HEK293 cells reveals variability and influence on downstream reporter expression. FEBS J 2021; 288:6410-6427. [PMID: 34043859 DOI: 10.1111/febs.16037] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Revised: 04/20/2021] [Accepted: 05/25/2021] [Indexed: 11/30/2022]
Abstract
Large serine integrases (LSIs) offer tremendous potential for rapid genetic engineering as well as building biological systems capable of responding to stimuli and integrating information. Currently, there is no unified metric for directly measuring the enzymatic characteristics of LSI function, which hinders evaluation of their suitability to specific applications. Here, we present an experimental protocol for recording DNA recombination in HEK293 cells in real-time through fluorophore expression and software which fits the kinetic data to a model tailored to LSI recombination dynamics. Our model captures the activity of LSIs as three parameters: expression level (Kexp ), catalytic rate (kcat ), and substrate affinity (Kd ). The expression level and catalytic rate for phiC31 and Bxb1 varied greatly, suggesting disparate routes to high recombination efficiencies. Moreover, the expression level and substrate affinity jointly impacted downstream reporter expression, potentially by obstructing transcriptional machinery. We validated these observations by swapping between promoters and mutating key recombinase residues and DNA recognition sites to individually modulate each parameter. Our model for identifying key LSI parameters in cellulo provides insight into selecting the optimal recombinase for various applications as well as for guiding the engineering of improved LSIs.
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Affiliation(s)
- George Chao
- Genetics Department, Harvard Medical School, Boston, MA, USA
| | - Clair Travis
- Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - George Church
- Genetics Department, Harvard Medical School, Boston, MA, USA
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57
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Li X, Rizik L, Kravchik V, Khoury M, Korin N, Daniel R. Synthetic neural-like computing in microbial consortia for pattern recognition. Nat Commun 2021; 12:3139. [PMID: 34035266 PMCID: PMC8149857 DOI: 10.1038/s41467-021-23336-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 04/19/2021] [Indexed: 11/09/2022] Open
Abstract
Complex biological systems in nature comprise cells that act collectively to solve sophisticated tasks. Synthetic biological systems, in contrast, are designed for specific tasks, following computational principles including logic gates and analog design. Yet such approaches cannot be easily adapted for multiple tasks in biological contexts. Alternatively, artificial neural networks, comprised of flexible interactions for computation, support adaptive designs and are adopted for diverse applications. Here, motivated by the structural similarity between artificial neural networks and cellular networks, we implement neural-like computing in bacteria consortia for recognizing patterns. Specifically, receiver bacteria collectively interact with sender bacteria for decision-making through quorum sensing. Input patterns formed by chemical inducers activate senders to produce signaling molecules at varying levels. These levels, which act as weights, are programmed by tuning the sender promoter strength Furthermore, a gradient descent based algorithm that enables weights optimization was developed. Weights were experimentally examined for recognizing 3 × 3-bit pattern.
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Affiliation(s)
- Ximing Li
- Department of Biomedical Engineering Technion-Israel Institute of Technology, Technion City, Haifa, Israel
| | - Luna Rizik
- Department of Biomedical Engineering Technion-Israel Institute of Technology, Technion City, Haifa, Israel
| | - Valeriia Kravchik
- Department of Biomedical Engineering Technion-Israel Institute of Technology, Technion City, Haifa, Israel
| | - Maria Khoury
- Department of Biomedical Engineering Technion-Israel Institute of Technology, Technion City, Haifa, Israel
| | - Netanel Korin
- Department of Biomedical Engineering Technion-Israel Institute of Technology, Technion City, Haifa, Israel
| | - Ramez Daniel
- Department of Biomedical Engineering Technion-Israel Institute of Technology, Technion City, Haifa, Israel.
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58
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Jiang C, Zhang Y, Wang F, Liu H. Toward Smart Information Processing with Synthetic DNA Molecules. Macromol Rapid Commun 2021; 42:e2100084. [PMID: 33864315 DOI: 10.1002/marc.202100084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 03/13/2021] [Indexed: 11/07/2022]
Abstract
DNA, a biological macromolecule, is a naturally evolved information material. From the structural point of view, an individual DNA strand can be considered as a chain of data with its bases working as single units. For decades, due to the high biochemical stability, large information storage capacity, and high recognition specificity, DNA has been recognized as an attractive material for information processing. Especially, the chemical synthesis strategies and DNA sequencing techniques have been rapidly developed recently, further enabling encoding information with synthetic DNA molecules. Herein, recent progresses are summarized on information processing based on synthetic DNA molecules from three aspects including information storage, computation, and encryption, and proposed the challenges and future development directions.
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Affiliation(s)
- Chu Jiang
- School of Chemical Science and Engineering, Key Laboratory of Advanced Civil Engineering Materials of Ministry of Education, Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, 200092, China
| | - Yinan Zhang
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, 200240, China
- Center for Molecular Design and Biomimetics, School of Molecular Sciences, The Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA
| | - Fei Wang
- School of Chemistry and Chemical Engineering, Frontiers Science Center for Transformative Molecules and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Huajie Liu
- School of Chemical Science and Engineering, Key Laboratory of Advanced Civil Engineering Materials of Ministry of Education, Shanghai Research Institute for Intelligent Autonomous Systems, Tongji University, Shanghai, 200092, China
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59
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Genetic circuits combined with machine learning provides fast responding living sensors. Biosens Bioelectron 2021; 178:113028. [DOI: 10.1016/j.bios.2021.113028] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 01/05/2021] [Accepted: 01/19/2021] [Indexed: 12/24/2022]
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60
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Yim SS, McBee RM, Song AM, Huang Y, Sheth RU, Wang HH. Robust direct digital-to-biological data storage in living cells. Nat Chem Biol 2021; 17:246-253. [PMID: 33432236 PMCID: PMC7904632 DOI: 10.1038/s41589-020-00711-4] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 10/30/2020] [Accepted: 11/12/2020] [Indexed: 02/06/2023]
Abstract
DNA has been the predominant information storage medium for biology and holds great promise as a next-generation high-density data medium in the digital era. Currently, the vast majority of DNA-based data storage approaches rely on in vitro DNA synthesis. As such, there are limited methods to encode digital data into the chromosomes of living cells in a single step. Here, we describe a new electrogenetic framework for direct storage of digital data in living cells. Using an engineered redox-responsive CRISPR adaptation system, we encoded binary data in 3-bit units into CRISPR arrays of bacterial cells by electrical stimulation. We demonstrate multiplex data encoding into barcoded cell populations to yield meaningful information storage and capacity up to 72 bits, which can be maintained over many generations in natural open environments. This work establishes a direct digital-to-biological data storage framework and advances our capacity for information exchange between silicon- and carbon-based entities.
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Affiliation(s)
- Sung Sun Yim
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Ross M McBee
- Department of Systems Biology, Columbia University, New York, NY, USA
- Department of Biological Sciences, Columbia University, New York, NY, USA
| | - Alan M Song
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Yiming Huang
- Department of Systems Biology, Columbia University, New York, NY, USA
- Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY, USA
| | - Ravi U Sheth
- Department of Systems Biology, Columbia University, New York, NY, USA
- Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY, USA
| | - Harris H Wang
- Department of Systems Biology, Columbia University, New York, NY, USA.
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA.
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61
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Park J, Lim JM, Jung I, Heo SJ, Park J, Chang Y, Kim HK, Jung D, Yu JH, Min S, Yoon S, Cho SR, Park T, Kim HH. Recording of elapsed time and temporal information about biological events using Cas9. Cell 2021; 184:1047-1063.e23. [PMID: 33539780 DOI: 10.1016/j.cell.2021.01.014] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 12/08/2020] [Accepted: 01/12/2021] [Indexed: 01/14/2023]
Abstract
DNA has not been utilized to record temporal information, although DNA has been used to record biological information and to compute mathematical problems. Here, we found that indel generation by Cas9 and guide RNA can occur at steady rates, in contrast to typical dynamic biological reactions, and the accumulated indel frequency can be a function of time. By measuring indel frequencies, we developed a method for recording and measuring absolute time periods over hours to weeks in mammalian cells. These time-recordings were conducted in several cell types, with different promoters and delivery vectors for Cas9, and in both cultured cells and cells of living mice. As applications, we recorded the duration of chemical exposure and the lengths of elapsed time since the onset of biological events (e.g., heat exposure and inflammation). We propose that our systems could serve as synthetic "DNA clocks."
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Affiliation(s)
- Jihye Park
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Jung Min Lim
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Inkyung Jung
- Division of Biostatistics, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Department of Biostatistics and Computing, Graduate School, Yonsei University, Seoul 03722, Republic of Korea
| | - Seok-Jae Heo
- Division of Biostatistics, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Department of Biostatistics and Computing, Graduate School, Yonsei University, Seoul 03722, Republic of Korea
| | - Jinman Park
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Yoojin Chang
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Hui Kwon Kim
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Dongmin Jung
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea
| | - Ji Hea Yu
- Department and Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul 03722, South Korea
| | - Seonwoo Min
- Electrical and Computer Engineering, Seoul National University, Seoul 00826, Republic of Korea
| | - Sungroh Yoon
- Electrical and Computer Engineering, Seoul National University, Seoul 00826, Republic of Korea; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 00826, Republic of Korea; Interdisciplinary Program in Artificial Intelligence, Seoul National University, Seoul 00826, Republic of Korea
| | - Sung-Rae Cho
- Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Department and Research Institute of Rehabilitation Medicine, Yonsei University College of Medicine, Seoul 03722, South Korea
| | - Taeyoung Park
- Department of Applied Statistics, Yonsei University, Seoul 03722, Republic of Korea; Department of Statistics and Data Science, Yonsei University, Seoul 03722, Republic of Korea
| | - Hyongbum Henry Kim
- Department of Pharmacology, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Brain Korea 21 Plus Project for Medical Sciences, Yonsei University College of Medicine, Seoul 03722, Republic of Korea; Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, Republic of Korea; Graduate Program of Nano Biomedical Engineering (NanoBME), Advanced Science Institute, Yonsei University, Seoul, Republic of Korea; Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
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62
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Del Valle I, Fulk EM, Kalvapalle P, Silberg JJ, Masiello CA, Stadler LB. Translating New Synthetic Biology Advances for Biosensing Into the Earth and Environmental Sciences. Front Microbiol 2021; 11:618373. [PMID: 33633695 PMCID: PMC7901896 DOI: 10.3389/fmicb.2020.618373] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 12/17/2020] [Indexed: 12/26/2022] Open
Abstract
The rapid diversification of synthetic biology tools holds promise in making some classically hard-to-solve environmental problems tractable. Here we review longstanding problems in the Earth and environmental sciences that could be addressed using engineered microbes as micron-scale sensors (biosensors). Biosensors can offer new perspectives on open questions, including understanding microbial behaviors in heterogeneous matrices like soils, sediments, and wastewater systems, tracking cryptic element cycling in the Earth system, and establishing the dynamics of microbe-microbe, microbe-plant, and microbe-material interactions. Before these new tools can reach their potential, however, a suite of biological parts and microbial chassis appropriate for environmental conditions must be developed by the synthetic biology community. This includes diversifying sensing modules to obtain information relevant to environmental questions, creating output signals that allow dynamic reporting from hard-to-image environmental materials, and tuning these sensors so that they reliably function long enough to be useful for environmental studies. Finally, ethical questions related to the use of synthetic biosensors in environmental applications are discussed.
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Affiliation(s)
- Ilenne Del Valle
- Systems, Synthetic, and Physical Biology Graduate Program, Rice University, Houston, TX, United States
| | - Emily M. Fulk
- Systems, Synthetic, and Physical Biology Graduate Program, Rice University, Houston, TX, United States
| | - Prashant Kalvapalle
- Systems, Synthetic, and Physical Biology Graduate Program, Rice University, Houston, TX, United States
| | - Jonathan J. Silberg
- Department of BioSciences, Rice University, Houston, TX, United States
- Department of Bioengineering, Rice University, Houston, TX, United States
- Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX, United States
| | - Caroline A. Masiello
- Department of BioSciences, Rice University, Houston, TX, United States
- Department of Earth, Environmental and Planetary Sciences, Rice University, Houston, TX, United States
- Department of Chemistry, Rice University, Houston, TX, United States
| | - Lauren B. Stadler
- Department of Civil and Environmental Engineering, Rice University, Houston, TX, United States
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63
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Vasilev RA, Chernikovich VY, Evteeva MA, Sakharov DA, Patrushev MV. Synthetic Biology: Current State and Applications. MOLECULAR GENETICS, MICROBIOLOGY AND VIROLOGY 2021. [DOI: 10.3103/s0891416821010079] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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64
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Abstract
Engineered biocircuits designed with biological components have the capacity to expand and augment living functions. Here we demonstrate that proteases can be integrated into digital or analog biocircuits to process biological information. We first construct peptide-caged liposomes that treat protease activity as two-valued (i.e., signal is 0 or 1) operations to construct the biological equivalent of Boolean logic gates, comparators and analog-to-digital converters. We use these modules to assemble a cell-free biocircuit that can combine with bacteria-containing blood, quantify bacteria burden, and then calculate and unlock a selective drug dose. By contrast, we treat protease activity as multi-valued (i.e., signal is between 0 and 1) by controlling the degree to which a pool of enzymes is shared between two target substrates. We perform operations on these analog values by manipulating substrate concentrations and combine these operations to solve the mathematical problem Learning Parity with Noise (LPN). These results show that protease activity can be used to process biological information by binary Boolean logic, or as multi-valued analog signals under conditions where substrate resources are shared.
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Affiliation(s)
- Brandon Alexander Holt
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, GA, 30332, USA
| | - Gabriel A Kwong
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, GA, 30332, USA.
- Parker H. Petit Institute of Bioengineering and Bioscience, Atlanta, GA, 30332, USA.
- Institute for Electronics and Nanotechnology, Georgia Tech, Atlanta, GA, 30332, USA.
- Integrated Cancer Research Center, Georgia Tech, Atlanta, GA, 30332, USA.
- The Georgia Immunoengineering Consortium, Emory University and Georgia Tech, Atlanta, GA, 30332, USA.
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65
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Zúñiga A, Guiziou S, Mayonove P, Meriem ZB, Camacho M, Moreau V, Ciandrini L, Hersen P, Bonnet J. Rational programming of history-dependent logic in cellular populations. Nat Commun 2020; 11:4758. [PMID: 32958811 PMCID: PMC7506022 DOI: 10.1038/s41467-020-18455-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 07/24/2020] [Indexed: 12/16/2022] Open
Abstract
Genetic programs operating in a history-dependent fashion are ubiquitous in nature and govern sophisticated processes such as development and differentiation. The ability to systematically and predictably encode such programs would advance the engineering of synthetic organisms and ecosystems with rich signal processing abilities. Here we implement robust, scalable history-dependent programs by distributing the computational labor across a cellular population. Our design is based on standardized recombinase-driven DNA scaffolds expressing different genes according to the order of occurrence of inputs. These multicellular computing systems are highly modular, do not require cell-cell communication channels, and any program can be built by differential composition of strains containing well-characterized logic scaffolds. We developed automated workflows that researchers can use to streamline program design and optimization. We anticipate that the history-dependent programs presented here will support many applications using cellular populations for material engineering, biomanufacturing and healthcare.
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Affiliation(s)
- Ana Zúñiga
- Centre de Biochimie Structurale (CBS), INSERM U154, CNRS UMR5048, University of Montpellier, Montpellier, France
| | - Sarah Guiziou
- Centre de Biochimie Structurale (CBS), INSERM U154, CNRS UMR5048, University of Montpellier, Montpellier, France
- Department of Biology, University of Washington, Seattle, WA, 98195, USA
| | - Pauline Mayonove
- Centre de Biochimie Structurale (CBS), INSERM U154, CNRS UMR5048, University of Montpellier, Montpellier, France
| | - Zachary Ben Meriem
- Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie Duquet, 75013, Paris, France
| | - Miguel Camacho
- Centre de Biochimie Structurale (CBS), INSERM U154, CNRS UMR5048, University of Montpellier, Montpellier, France
| | - Violaine Moreau
- Centre de Biochimie Structurale (CBS), INSERM U154, CNRS UMR5048, University of Montpellier, Montpellier, France
| | - Luca Ciandrini
- Centre de Biochimie Structurale (CBS), INSERM U154, CNRS UMR5048, University of Montpellier, Montpellier, France
- Laboratoire Charles Coulomb (L2C), University of Montpellier & CNRS, Montpellier, France
| | - Pascal Hersen
- Laboratoire Matière et Systèmes Complexes, UMR 7057 CNRS & Université Paris Diderot, 10 rue Alice Domon et Léonie Duquet, 75013, Paris, France
- Laboratoire Physico Chimie Curie, UMR168, Institut Curie, Paris, France
| | - Jerome Bonnet
- Centre de Biochimie Structurale (CBS), INSERM U154, CNRS UMR5048, University of Montpellier, Montpellier, France.
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66
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Abstract
The ability to detect disease early and deliver precision therapy would be transformative for the treatment of human illnesses. To achieve these goals, biosensors that can pinpoint when and where diseases emerge are needed. Rapid advances in synthetic biology are enabling us to exploit the information-processing abilities of living cells to diagnose disease and then treat it in a controlled fashion. For example, living sensors could be designed to precisely sense disease biomarkers, such as by-products of inflammation, and to respond by delivering targeted therapeutics in situ. Here, we provide an overview of ongoing efforts in microbial biosensor design, highlight translational opportunities, and discuss challenges for enabling sense-and-respond precision medicines.
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Affiliation(s)
- Maria Eugenia Inda
- MIT Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Timothy K. Lu
- MIT Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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67
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Höllerer S, Papaxanthos L, Gumpinger AC, Fischer K, Beisel C, Borgwardt K, Benenson Y, Jeschek M. Large-scale DNA-based phenotypic recording and deep learning enable highly accurate sequence-function mapping. Nat Commun 2020; 11:3551. [PMID: 32669542 PMCID: PMC7363850 DOI: 10.1038/s41467-020-17222-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2020] [Accepted: 06/13/2020] [Indexed: 01/23/2023] Open
Abstract
Predicting effects of gene regulatory elements (GREs) is a longstanding challenge in biology. Machine learning may address this, but requires large datasets linking GREs to their quantitative function. However, experimental methods to generate such datasets are either application-specific or technically complex and error-prone. Here, we introduce DNA-based phenotypic recording as a widely applicable, practicable approach to generate large-scale sequence-function datasets. We use a site-specific recombinase to directly record a GRE's effect in DNA, enabling readout of both sequence and quantitative function for extremely large GRE-sets via next-generation sequencing. We record translation kinetics of over 300,000 bacterial ribosome binding sites (RBSs) in >2.7 million sequence-function pairs in a single experiment. Further, we introduce a deep learning approach employing ensembling and uncertainty modelling that predicts RBS function with high accuracy, outperforming state-of-the-art methods. DNA-based phenotypic recording combined with deep learning represents a major advance in our ability to predict function from genetic sequence.
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Affiliation(s)
- Simon Höllerer
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland
| | - Laetitia Papaxanthos
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland
- Swiss Institute of Bioinformatics, 4058, Basel, Switzerland
| | - Anja Cathrin Gumpinger
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland
- Swiss Institute of Bioinformatics, 4058, Basel, Switzerland
| | - Katrin Fischer
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland
| | - Christian Beisel
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland
| | - Karsten Borgwardt
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland.
- Swiss Institute of Bioinformatics, 4058, Basel, Switzerland.
| | - Yaakov Benenson
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland.
| | - Markus Jeschek
- Department of Biosystems Science and Engineering, ETH Zurich, 4058, Basel, Switzerland.
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68
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Gomide MS, Sales TT, Barros LRC, Limia CG, de Oliveira MA, Florentino LH, Barros LMG, Robledo ML, José GPC, Almeida MSM, Lima RN, Rehen SK, Lacorte C, Melo EO, Murad AM, Bonamino MH, Coelho CM, Rech E. Genetic switches designed for eukaryotic cells and controlled by serine integrases. Commun Biol 2020; 3:255. [PMID: 32444777 PMCID: PMC7244727 DOI: 10.1038/s42003-020-0971-8] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Accepted: 04/28/2020] [Indexed: 11/16/2022] Open
Abstract
Recently, new serine integrases have been identified, increasing the possibility of scaling up genomic modulation tools. Here, we describe the use of unidirectional genetic switches to evaluate the functionality of six serine integrases in different eukaryotic systems: the HEK 293T cell lineage, bovine fibroblasts and plant protoplasts. Moreover, integrase activity was also tested in human cell types of therapeutic interest: peripheral blood mononuclear cells (PBMCs), neural stem cells (NSCs) and undifferentiated embryonic stem (ES) cells. The switches were composed of plasmids designed to flip two different genetic parts driven by serine integrases. Cell-based assays were evaluated by measurement of EGFP fluorescence and by molecular analysis of attL/attR sites formation after integrase functionality. Our results demonstrate that all the integrases were capable of inverting the targeted DNA sequences, exhibiting distinct performances based on the cell type or the switchable genetic sequence. These results should support the development of tunable genetic circuits to regulate eukaryotic gene expression.
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Affiliation(s)
- Mayna S Gomide
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
- Department of Cell Biology, Institute of Biological Science, University of Brasília, Brasília, 70910900, DF, Brazil
- School of Medicine, Federal University of Juiz de Fora, Juiz de Fora, 36036900, MG, Brazil
| | - Thais T Sales
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
- Department of Cell Biology, Institute of Biological Science, University of Brasília, Brasília, 70910900, DF, Brazil
| | - Luciana R C Barros
- Molecular Carcinogenesis Program, Research Coordination, National Cancer Institute (INCA), Rio de Janeiro, 20231050, RJ, Brazil
| | - Cintia G Limia
- Molecular Carcinogenesis Program, Research Coordination, National Cancer Institute (INCA), Rio de Janeiro, 20231050, RJ, Brazil
| | - Marco A de Oliveira
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
- Department of Cell Biology, Institute of Biological Science, University of Brasília, Brasília, 70910900, DF, Brazil
| | - Lilian H Florentino
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
| | - Leila M G Barros
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
| | - Maria L Robledo
- Molecular Carcinogenesis Program, Research Coordination, National Cancer Institute (INCA), Rio de Janeiro, 20231050, RJ, Brazil
| | - Gustavo P C José
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
| | - Mariana S M Almeida
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
| | - Rayane N Lima
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
| | - Stevens K Rehen
- D'Or Institute for Research and Education (IDOR), Rio de Janeiro, 22281100, RJ, Brazil
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, 21941902, RJ, Brazil
| | - Cristiano Lacorte
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
| | - Eduardo O Melo
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
- Graduation Program in Biotechnology, Federal University of Tocantins, Gurupi, 77402970, TO, Brazil
| | - André M Murad
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil
| | - Martín H Bonamino
- Molecular Carcinogenesis Program, Research Coordination, National Cancer Institute (INCA), Rio de Janeiro, 20231050, RJ, Brazil.
- Vice-Presidency of Research and Biological Collections (VPPCB), FIOCRUZ - Oswaldo Cruz Foundation Institute, Rio de Janeiro, 21040900, RJ, Brazil.
| | - Cintia M Coelho
- Department of Genetic and Morphology, Institute of Biological Science, University of Brasília, Brasília, 70910900, DF, Brazil.
| | - Elibio Rech
- Brazilian Agriculture Research Corporation - Embrapa - Genetic Resources and Biotechnology - CENARGEN, Brasília, 70770917, DF, Brazil.
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69
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Chen Z, Kibler RD, Hunt A, Busch F, Pearl J, Jia M, VanAernum ZL, Wicky BIM, Dods G, Liao H, Wilken MS, Ciarlo C, Green S, El-Samad H, Stamatoyannopoulos J, Wysocki VH, Jewett MC, Boyken SE, Baker D. De novo design of protein logic gates. Science 2020; 368:78-84. [PMID: 32241946 DOI: 10.1126/science.aay2790] [Citation(s) in RCA: 119] [Impact Index Per Article: 29.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 03/05/2020] [Indexed: 12/16/2022]
Abstract
The design of modular protein logic for regulating protein function at the posttranscriptional level is a challenge for synthetic biology. Here, we describe the design of two-input AND, OR, NAND, NOR, XNOR, and NOT gates built from de novo-designed proteins. These gates regulate the association of arbitrary protein units ranging from split enzymes to transcriptional machinery in vitro, in yeast and in primary human T cells, where they control the expression of the TIM3 gene related to T cell exhaustion. Designed binding interaction cooperativity, confirmed by native mass spectrometry, makes the gates largely insensitive to stoichiometric imbalances in the inputs, and the modularity of the approach enables ready extension to three-input OR, AND, and disjunctive normal form gates. The modularity and cooperativity of the control elements, coupled with the ability to de novo design an essentially unlimited number of protein components, should enable the design of sophisticated posttranslational control logic over a wide range of biological functions.
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Affiliation(s)
- Zibo Chen
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.,Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Ryan D Kibler
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.,Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Andrew Hunt
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Florian Busch
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA.,Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH 43210, USA
| | - Jocelynn Pearl
- Altius Institute for Biomedical Sciences, Seattle, WA 98195, USA
| | - Mengxuan Jia
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA.,Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH 43210, USA
| | - Zachary L VanAernum
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA.,Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH 43210, USA
| | - Basile I M Wicky
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.,Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - Galen Dods
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Hanna Liao
- Altius Institute for Biomedical Sciences, Seattle, WA 98195, USA
| | - Matthew S Wilken
- Altius Institute for Biomedical Sciences, Seattle, WA 98195, USA
| | - Christie Ciarlo
- Altius Institute for Biomedical Sciences, Seattle, WA 98195, USA
| | - Shon Green
- Altius Institute for Biomedical Sciences, Seattle, WA 98195, USA
| | - Hana El-Samad
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA 94158, USA.,Chan-Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - John Stamatoyannopoulos
- Altius Institute for Biomedical Sciences, Seattle, WA 98195, USA.,Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.,Department of Medicine, Division of Oncology, University of Washington, Seattle, WA 98109, USA
| | - Vicki H Wysocki
- Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210, USA.,Resource for Native Mass Spectrometry Guided Structural Biology, The Ohio State University, Columbus, OH 43210, USA
| | - Michael C Jewett
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA.,Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60208, USA.,Center for Synthetic Biology, Northwestern University, Evanston, IL 60208, USA
| | - Scott E Boyken
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA.,Institute for Protein Design, University of Washington, Seattle, WA 98195, USA
| | - David Baker
- Department of Biochemistry, University of Washington, Seattle, WA 98195, USA. .,Institute for Protein Design, University of Washington, Seattle, WA 98195, USA.,Howard Hughes Medical Institute, University of Washington, Seattle, WA 98195, USA
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70
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Bernabé-Orts JM, Quijano-Rubio A, Vazquez-Vilar M, Mancheño-Bonillo J, Moles-Casas V, Selma S, Gianoglio S, Granell A, Orzaez D. A memory switch for plant synthetic biology based on the phage ϕC31 integration system. Nucleic Acids Res 2020; 48:3379-3394. [PMID: 32083668 PMCID: PMC7102980 DOI: 10.1093/nar/gkaa104] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 02/07/2020] [Accepted: 02/10/2020] [Indexed: 02/07/2023] Open
Abstract
Synthetic biology has advanced from the setup of basic genetic devices to the design of increasingly complex gene circuits to provide organisms with new functions. While many bacterial, fungal and mammalian unicellular chassis have been extensively engineered, this progress has been delayed in plants due to the lack of reliable DNA parts and devices that enable precise control over these new synthetic functions. In particular, memory switches based on DNA site-specific recombination have been the tool of choice to build long-term and stable synthetic memory in other organisms, because they enable a shift between two alternative states registering the information at the DNA level. Here we report a memory switch for whole plants based on the bacteriophage ϕC31 site-specific integrase. The switch was built as a modular device made of standard DNA parts, designed to control the transcriptional state (on or off) of two genes of interest by alternative inversion of a central DNA regulatory element. The state of the switch can be externally operated by action of the ϕC31 integrase (Int), and its recombination directionality factor (RDF). The kinetics, memory, and reversibility of the switch were extensively characterized in Nicotiana benthamiana plants.
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Affiliation(s)
- Joan Miquel Bernabé-Orts
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
| | - Alfredo Quijano-Rubio
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
| | - Marta Vazquez-Vilar
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
| | - Javier Mancheño-Bonillo
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
| | - Victor Moles-Casas
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
| | - Sara Selma
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
| | - Silvia Gianoglio
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
| | - Antonio Granell
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
| | - Diego Orzaez
- Instituto de Biología Molecular y Celular de Plantas (IBMCP). CSIC - Universidad Politécnica de Valencia. Camino de Vera s/n, 46022 Valencia, Spain
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71
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Soleimany AP, Bhatia SN. Activity-Based Diagnostics: An Emerging Paradigm for Disease Detection and Monitoring. Trends Mol Med 2020; 26:450-468. [PMID: 32359477 DOI: 10.1016/j.molmed.2020.01.013] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 01/20/2020] [Accepted: 01/28/2020] [Indexed: 12/26/2022]
Abstract
Diagnostics to accurately detect disease and monitor therapeutic response are essential for effective clinical management. Bioengineering, chemical biology, molecular biology, and computer science tools are converging to guide the design of diagnostics that leverage enzymatic activity to measure or produce biomarkers of disease. We review recent advances in the development of these 'activity-based diagnostics' (ABDx) and their application in infectious and noncommunicable diseases. We highlight efforts towards both molecular probes that respond to disease-specific catalytic activity to produce a diagnostic readout, as well as diagnostics that use enzymes as an engineered component of their sense-and-respond cascade. These technologies exemplify how integrating techniques from multiple disciplines with preclinical validation has enabled ABDx that may realize the goals of precision medicine.
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Affiliation(s)
- Ava P Soleimany
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Harvard Graduate Program in Biophysics, Harvard University, Boston, MA, USA
| | - Sangeeta N Bhatia
- Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA; Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA, USA; Wyss Institute at Harvard, Cambridge, MA, USA; Howard Hughes Medical Institute, Cambridge, MA, USA.
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72
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Farzadfard F, Gharaei N, Higashikuni Y, Jung G, Cao J, Lu TK. Single-Nucleotide-Resolution Computing and Memory in Living Cells. Mol Cell 2020; 75:769-780.e4. [PMID: 31442423 DOI: 10.1016/j.molcel.2019.07.011] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2018] [Revised: 05/07/2019] [Accepted: 07/08/2019] [Indexed: 12/22/2022]
Abstract
The ability to process and store information in living cells is essential for developing next-generation therapeutics and studying biology in situ. However, existing strategies have limited recording capacity and are challenging to scale. To overcome these limitations, we developed DOMINO, a robust and scalable platform for encoding logic and memory in bacterial and eukaryotic cells. Using an efficient single-nucleotide-resolution Read-Write head for DNA manipulation, DOMINO converts the living cells' DNA into an addressable, readable, and writable medium for computation and storage. DOMINO operators enable analog and digital molecular recording for long-term monitoring of signaling dynamics and cellular events. Furthermore, multiple operators can be layered and interconnected to encode order-independent, sequential, and temporal logic, allowing recording and control over the combination, order, and timing of molecular events in cells. We envision that DOMINO will lay the foundation for building robust and sophisticated computation-and-memory gene circuits for numerous biotechnological and biomedical applications.
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Affiliation(s)
- Fahim Farzadfard
- Synthetic Biology Group, Research Laboratory of Electronics, Department of Electrical Engineering & Computer Science and Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; MIT Synthetic Biology Center, 500 Technology Square, Cambridge MA 02139, USA; MIT Microbiology Graduate Program, 77 Massachusetts Avenue, Cambridge MA 02139, USA.
| | - Nava Gharaei
- MCO Graduate Program, Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA 02138, USA
| | - Yasutomi Higashikuni
- Synthetic Biology Group, Research Laboratory of Electronics, Department of Electrical Engineering & Computer Science and Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; MIT Synthetic Biology Center, 500 Technology Square, Cambridge MA 02139, USA
| | - Giyoung Jung
- Synthetic Biology Group, Research Laboratory of Electronics, Department of Electrical Engineering & Computer Science and Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; MIT Synthetic Biology Center, 500 Technology Square, Cambridge MA 02139, USA; Harvard-MIT Division of Health Sciences and Technology, 77 Massachusetts Ave, Cambridge, MA 02139, USA
| | - Jicong Cao
- Synthetic Biology Group, Research Laboratory of Electronics, Department of Electrical Engineering & Computer Science and Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; MIT Synthetic Biology Center, 500 Technology Square, Cambridge MA 02139, USA
| | - Timothy K Lu
- Synthetic Biology Group, Research Laboratory of Electronics, Department of Electrical Engineering & Computer Science and Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; MIT Synthetic Biology Center, 500 Technology Square, Cambridge MA 02139, USA; MIT Microbiology Graduate Program, 77 Massachusetts Avenue, Cambridge MA 02139, USA.
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73
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Guo L, Diao W, Gao C, Hu G, Ding Q, Ye C, Chen X, Liu J, Liu L. Engineering Escherichia coli lifespan for enhancing chemical production. Nat Catal 2020. [DOI: 10.1038/s41929-019-0411-7] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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74
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Tanna T, Schmidt F, Cherepkova MY, Okoniewski M, Platt RJ. Recording transcriptional histories using Record-seq. Nat Protoc 2020; 15:513-539. [DOI: 10.1038/s41596-019-0253-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2019] [Accepted: 10/08/2019] [Indexed: 01/17/2023]
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75
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Abstract
Molecular data storage is an attractive alternative for dense and durable information storage, which is sorely needed to deal with the growing gap between information production and the ability to store data. DNA is a clear example of effective archival data storage in molecular form. In this Review, we provide an overview of the process, the state of the art in this area and challenges for mainstream adoption. We also survey the field of in vivo molecular memory systems that record and store information within the DNA of living cells, which, together with in vitro DNA data storage, lie at the growing intersection of computer systems and biotechnology.
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Affiliation(s)
- Luis Ceze
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.
| | - Jeff Nivala
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - Karin Strauss
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.,Microsoft Research, Redmond, WA, USA
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76
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Olorunniji FJ, Lawson-Williams M, McPherson AL, Paget JE, Stark WM, Rosser SJ. Control of ϕC31 integrase-mediated site-specific recombination by protein trans-splicing. Nucleic Acids Res 2019; 47:11452-11460. [PMID: 31667500 PMCID: PMC6868429 DOI: 10.1093/nar/gkz936] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Revised: 09/30/2019] [Accepted: 10/07/2019] [Indexed: 11/13/2022] Open
Abstract
Serine integrases are emerging as core tools in synthetic biology and have applications in biotechnology and genome engineering. We have designed a split-intein serine integrase-based system with potential for regulation of site-specific recombination events at the protein level in vivo. The ϕC31 integrase was split into two extein domains, and intein sequences (Npu DnaEN and Ssp DnaEC) were attached to the two termini to be fused. Expression of these two components followed by post-translational protein trans-splicing in Escherichia coli generated a fully functional ϕC31 integrase. We showed that protein splicing is necessary for recombination activity; deletion of intein domains or mutation of key intein residues inactivated recombination. We used an invertible promoter reporter system to demonstrate a potential application of the split intein-regulated site-specific recombination system in building reversible genetic switches. We used the same split inteins to control the reconstitution of a split Integrase-Recombination Directionality Factor fusion (Integrase-RDF) that efficiently catalysed the reverse attR x attL recombination. This demonstrates the potential for split-intein regulation of the forward and reverse reactions using the integrase and the integrase-RDF fusion, respectively. The split-intein integrase is a potentially versatile, regulatable component for building synthetic genetic circuits and devices.
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Affiliation(s)
- Femi J Olorunniji
- School of Pharmacy and Biomolecular Sciences, Faculty of Science, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool L3 3AF, UK
| | - Makeba Lawson-Williams
- School of Pharmacy and Biomolecular Sciences, Faculty of Science, Liverpool John Moores University, James Parsons Building, Byrom Street, Liverpool L3 3AF, UK
| | - Arlene L McPherson
- Institute of Molecular, Cell and Systems Biology, University of Glasgow, Bower Building, Glasgow G12 8QQ, UK
| | - Jane E Paget
- UK Centre for Mammalian Synthetic Biology at the Institute of Quantitative Biology, Biochemistry, and Biotechnology, SynthSys, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3JD, UK.,Institute for Bioengineering, University of Edinburgh, Faraday Building, The King's Buildings, Edinburgh, 2 EH9 3DW, UK
| | - W Marshall Stark
- Institute of Molecular, Cell and Systems Biology, University of Glasgow, Bower Building, Glasgow G12 8QQ, UK
| | - Susan J Rosser
- UK Centre for Mammalian Synthetic Biology at the Institute of Quantitative Biology, Biochemistry, and Biotechnology, SynthSys, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3JD, UK.,Institute for Bioengineering, University of Edinburgh, Faraday Building, The King's Buildings, Edinburgh, 2 EH9 3DW, UK
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77
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Kim J, Zhou Y, Carlson PD, Teichmann M, Chaudhary S, Simmel FC, Silver PA, Collins JJ, Lucks JB, Yin P, Green AA. De novo-designed translation-repressing riboregulators for multi-input cellular logic. Nat Chem Biol 2019; 15:1173-1182. [PMID: 31686032 PMCID: PMC6864284 DOI: 10.1038/s41589-019-0388-1] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2018] [Accepted: 09/10/2019] [Indexed: 01/24/2023]
Abstract
Efforts to construct synthetic biological circuits with more complex functions have often been hindered by the idiosyncratic behavior, limited dynamic range, and crosstalk of commonly utilized parts. Here, we employ de novo RNA design to develop two high-performance translational repressors with sensing and logic capabilities. These synthetic riboregulators, termed toehold repressors and three-way junction (3WJ) repressors, detect transcripts with nearly arbitrary sequences, repress gene expression by up to 300-fold, and yield orthogonal sets of up to 15 devices. Automated forward engineering is used to improve toehold repressor dynamic range and SHAPE-Seq is applied to confirm the designed switching mechanism of 3WJ repressors in living cells. We integrate the modular repressors into biological circuits that execute universal NAND and NOR logic and evaluate the four-input expression NOT ((A1 AND A2) OR (B1 AND B2)) in Escherichia coli. These capabilities make toehold and 3WJ repressors valuable new tools for biotechnological applications.
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Affiliation(s)
- Jongmin Kim
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.,Integrative Biosciences and Biotechnology, Pohang University of Science and Technology, Pohang, Gyeongbuk, Republic of Korea
| | - Yu Zhou
- Biodesign Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, Tempe, AZ, USA.,School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Paul D Carlson
- Robert F. Smith School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, NY, USA.,Center for Synthetic Biology, Northwestern University, Evanston, IL, USA
| | - Mario Teichmann
- Physics Department E14 and ZNN/WSI, Technische Universität München, Garching, Germany
| | - Soma Chaudhary
- Biodesign Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, Tempe, AZ, USA.,School of Molecular Sciences, Arizona State University, Tempe, AZ, USA
| | - Friedrich C Simmel
- Physics Department E14 and ZNN/WSI, Technische Universität München, Garching, Germany.,Nanosystems Initiative Munich, Munich, Germany
| | - Pamela A Silver
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.,Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - James J Collins
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.,Institute for Medical Engineering and Science, Department of Biological Engineering, and Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.,Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Julius B Lucks
- Center for Synthetic Biology, Northwestern University, Evanston, IL, USA.,Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA
| | - Peng Yin
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA. .,Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
| | - Alexander A Green
- Biodesign Center for Molecular Design and Biomimetics, The Biodesign Institute, Arizona State University, Tempe, AZ, USA. .,School of Molecular Sciences, Arizona State University, Tempe, AZ, USA.
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78
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Weinberg BH, Cho JH, Agarwal Y, Pham NTH, Caraballo LD, Walkosz M, Ortega C, Trexler M, Tague N, Law B, Benman WKJ, Letendre J, Beal J, Wong WW. High-performance chemical- and light-inducible recombinases in mammalian cells and mice. Nat Commun 2019; 10:4845. [PMID: 31649244 PMCID: PMC6813296 DOI: 10.1038/s41467-019-12800-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 09/30/2019] [Indexed: 11/10/2022] Open
Abstract
Site-specific DNA recombinases are important genome engineering tools. Chemical- and light-inducible recombinases, in particular, enable spatiotemporal control of gene expression. However, inducible recombinases are scarce due to the challenge of engineering high performance systems, thus constraining the sophistication of genetic circuits and animal models that can be created. Here we present a library of >20 orthogonal inducible split recombinases that can be activated by small molecules, light and temperature in mammalian cells and mice. Furthermore, we engineer inducible split Cre systems with better performance than existing systems. Using our orthogonal inducible recombinases, we create a genetic switchboard that can independently regulate the expression of 3 different cytokines in the same cell, a tripartite inducible Flp, and a 4-input AND gate. We quantitatively characterize the inducible recombinases for benchmarking their performances, including computation of distinguishability of outputs. This library expands capabilities for multiplexed mammalian gene expression control.
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Affiliation(s)
- Benjamin H Weinberg
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Jang Hwan Cho
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Yash Agarwal
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - N T Hang Pham
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Leidy D Caraballo
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Maciej Walkosz
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Charina Ortega
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Micaela Trexler
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Nathan Tague
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Billy Law
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - William K J Benman
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Justin Letendre
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA
| | - Jacob Beal
- Raytheon BBN Technologies, Cambridge, MA, 02138, USA.
| | - Wilson W Wong
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, 02215, USA.
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79
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Steel H, Papachristodoulou A. Low-Burden Biological Feedback Controllers for Near-Perfect Adaptation. ACS Synth Biol 2019; 8:2212-2219. [PMID: 31500408 DOI: 10.1021/acssynbio.9b00125] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
The robustness and reliability of synthetic biological systems can be substantially improved by the introduction of feedback control architectures that parallel those employed in traditional engineering disciplines. One common control goal is adaptation (or disturbance rejection), which refers to a system's ability to maintain a constant output despite variation in some of its constituent processes (as frequently occurs in noisy cellular environments) or external perturbations. In this paper, we propose and analyze a control architecture that employs integrase and excisionase proteins to invert regions of DNA and an mRNA-mRNA annihilation reaction. Combined, these components approximate the functionality of a switching controller (as employed in classical control engineering) with three distinct operational modes. We demonstrate that this system is capable of near-perfect adaptation to variation in rates of both transcription and translation and can also operate without excessive consumption of cellular resources. The system's steady-state behavior is analyzed, and limits on its operating range are derived. Deterministic simulations of its dynamics are presented and are then extended to the stochastic case, which treats biochemical reactions as discrete events.
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Affiliation(s)
- Harrison Steel
- Dept of Engineering Science, University of Oxford, Oxford OX1 3PJ, U.K
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80
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Kim SG, Noh MH, Lim HG, Jang S, Jang S, Koffas MAG, Jung GY. Molecular parts and genetic circuits for metabolic engineering of microorganisms. FEMS Microbiol Lett 2019; 365:5059574. [PMID: 30052915 DOI: 10.1093/femsle/fny187] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2018] [Accepted: 07/24/2018] [Indexed: 12/17/2022] Open
Abstract
Microbial conversion of biomass into value-added biochemicals is a highly sustainable process compared to petroleum-based production. In this regard, microorganisms have been engineered via simple overexpression or deletion of metabolic genes to facilitate the production. However, the producer microorganisms require complex regulatory circuits to maximize productivity and performance. To address this issue, diverse genetic circuits have been developed that allow cells to minimize their metabolic burden, overcome metabolic imbalances and respond to a dynamically changing environment. In this review, we briefly explain the basic strategy for constructing genetic circuits by assembling molecular parts such as input, operation and output modules. Next, we describe recent applications of the circuits in the metabolic engineering of microorganisms to improve biochemical production. Beyond those achievements, genetic circuits will facilitate more innovative approaches to future strain development through mining and engineering new genetic elements and improving the complexity of genetic circuit design.
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Affiliation(s)
- Seong Gyeong Kim
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea
| | - Myung Hyun Noh
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea
| | - Hyun Gyu Lim
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea
| | - Sungho Jang
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea
| | - Sungyeon Jang
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea
| | - Mattheos A G Koffas
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, 110 8th Street, Troy 12180, USA
| | - Gyoo Yeol Jung
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, Korea
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81
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Nora LC, Westmann CA, Guazzaroni ME, Siddaiah C, Gupta VK, Silva-Rocha R. Recent advances in plasmid-based tools for establishing novel microbial chassis. Biotechnol Adv 2019; 37:107433. [PMID: 31437573 DOI: 10.1016/j.biotechadv.2019.107433] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2018] [Revised: 07/11/2019] [Accepted: 08/16/2019] [Indexed: 12/28/2022]
Abstract
A key challenge for domesticating alternative cultivable microorganisms with biotechnological potential lies in the development of innovative technologies. Within this framework, a myriad of genetic tools has flourished, allowing the design and manipulation of complex synthetic circuits and genomes to become the general rule in many laboratories rather than the exception. More recently, with the development of novel technologies such as DNA automated synthesis/sequencing and powerful computational tools, molecular biology has entered the synthetic biology era. In the beginning, most of these technologies were established in traditional microbial models (known as chassis in the synthetic biology framework) such as Escherichia coli and Saccharomyces cerevisiae, enabling fast advances in the field and the validation of fundamental proofs of concept. However, it soon became clear that these organisms, although extremely useful for prototyping many genetic tools, were not ideal for a wide range of biotechnological tasks due to intrinsic limitations in their molecular/physiological properties. Over the last decade, researchers have been facing the great challenge of shifting from these model systems to non-conventional chassis with endogenous capacities for dealing with specific tasks. The key to address these issues includes the generation of narrow and broad host plasmid-based molecular tools and the development of novel methods for engineering genomes through homologous recombination systems, CRISPR/Cas9 and other alternative methods. Here, we address the most recent advances in plasmid-based tools for the construction of novel cell factories, including a guide for helping with "build-your-own" microbial host.
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Affiliation(s)
- Luísa Czamanski Nora
- Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | - Cauã Antunes Westmann
- Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | - María-Eugenia Guazzaroni
- Faculty of Philosophy, Science and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | | | - Vijai Kumar Gupta
- ERA Chair of Green Chemistry, Department of Chemistry and Biotechnology, School of Science, Tallinn University of Technology, 12618 Tallinn, Estonia
| | - Rafael Silva-Rocha
- Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil.
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82
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Gao C, Xu P, Ye C, Chen X, Liu L. Genetic Circuit-Assisted Smart Microbial Engineering. Trends Microbiol 2019; 27:1011-1024. [PMID: 31421969 DOI: 10.1016/j.tim.2019.07.005] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 06/27/2019] [Accepted: 07/19/2019] [Indexed: 12/22/2022]
Abstract
Rapid advances in DNA synthesis, genetic manipulation, and biosensors have greatly improved the ability to engineer microorganisms with complex functions. By accurately integrating quality biosensors and complex genetic circuits, recently emerged smart microorganisms have enabled exciting opportunities for dissecting complex signaling networks and making responses without artificial intervention. However, because of the lack of design principles, developing such smart microorganisms remains challenging. In this review, we propose the concept of smart microbial engineering (SME) and describe the general features of basic SME, including the circuit architecture, components, and design process. We also summarize the latest SME achievements, remaining challenges, and potential solutions in this growing field.
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Affiliation(s)
- Cong Gao
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Peng Xu
- Chemical, Biochemical, and Environmental Engineering, University of Maryland Baltimore County, Baltimore, MD 21250, USA
| | - Chao Ye
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Xiulai Chen
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Liming Liu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi 214122, China.
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83
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Abstract
DNA outperforms most conventional storage media in terms of information retention time, physical density, and volumetric coding capacity. Advances in synthesis and sequencing technologies have enabled implementations of large synthetic DNA databases with impressive storage capacity and reliable data recovery. Several robust DNA storage architectures featuring random access, error correction, and content rewritability have been constructed with the potential for scalability and cost reduction. We survey these recent achievements and discuss alternative routes for overcoming the hurdles of engineering practical DNA storage systems. We also review recent exciting work on in vivo DNA memory including intracellular recorders constructed by programmable genome editing tools. Besides information storage, DNA could serve as a versatile molecular computing substrate. We highlight several state-of-the-art DNA computing techniques such as strand displacement, localized hybridization chain reactions, and enzymatic reaction networks. We summarize how these simple primitives have facilitated rational designs and implementations of in vitro DNA reaction networks that emulate digital/analog circuits, artificial neural networks, or nonlinear dynamic systems. We envision these modular primitives could be strategically adapted for sophisticated database operations and massively parallel computations on DNA databases. We also highlight in vivo DNA computing modules such as CRISPR logic gates for building scalable genetic circuits in living cells. To conclude, we discuss various implications and challenges of DNA-based storage and computing, and we particularly encourage innovative work on bridging these two areas of research to further explore molecular parallelism and near-data processing. Such integrated molecular systems could lead to far-reaching applications in biocomputing, security, and medicine.
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84
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Ishiguro S, Mori H, Yachie N. DNA event recorders send past information of cells to the time of observation. Curr Opin Chem Biol 2019; 52:54-62. [PMID: 31200335 DOI: 10.1016/j.cbpa.2019.05.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2019] [Revised: 04/26/2019] [Accepted: 05/10/2019] [Indexed: 11/17/2022]
Abstract
While current omics and single cell technologies have enabled measurements of high-resolution molecular snapshots of cells at a large scale, these technologies all require destruction of samples and prevent us from analyzing dynamic changes in molecular profiles, phenotypes, and behaviors of individual cells in a complex system. One possible direction to overcome this issue is the development of a cell-embedded 'event recorder' system, whereby molecular and phenotypic information of a cell(s) can be obtained at the time of observation with their past event information stored in 'heritable polymers' of the same cell. This concept has been demonstrated by many synthetic cellular circuits that monitor and transmit a certain set of environmental and intracellular signals into DNA, and have now been further accelerated by recent CRISPR-related technologies. Notably, the discovery of the RT-Cas1-Cas2 system, which acquires sequences of cellular transcripts into a specific host genomic region, has enabled recording of a broader range of molecular profile histories in the DNA tapes of cells, to understand the dynamics of complex biological processes that cannot be addressed by current technologies.
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Affiliation(s)
- Soh Ishiguro
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan; Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0035, Japan; Graduate School of Media and Governance, Keio University, Fujisawa 252-0882, Japan
| | - Hideto Mori
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan; Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0035, Japan; Graduate School of Media and Governance, Keio University, Fujisawa 252-0882, Japan
| | - Nozomu Yachie
- Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo 153-8904, Japan; Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0035, Japan; Graduate School of Media and Governance, Keio University, Fujisawa 252-0882, Japan; Department of Biological Sciences, School of Science, The University of Tokyo, Tokyo 113-0033, Japan; PRESTO, Japan Science and Technology Agency (JST), Tokyo 153-8904, Japan.
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85
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Zhao J, Pokhilko A, Ebenhöh O, Rosser SJ, Colloms SD. A single-input binary counting module based on serine integrase site-specific recombination. Nucleic Acids Res 2019; 47:4896-4909. [PMID: 30957849 PMCID: PMC6511857 DOI: 10.1093/nar/gkz245] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 03/24/2019] [Accepted: 03/26/2019] [Indexed: 01/09/2023] Open
Abstract
A device that counts and records the number of events experienced by an individual cell could have many uses in experimental biology and biotechnology. Here, we report a DNA-based 'latch' that switches between two states upon each exposure to a repeated stimulus. The key component of the latch is a DNA segment whose orientation is inverted by the actions of ϕC31 integrase and its recombination directionality factor (RDF). Integrase expression is regulated by an external input, while RDF expression is controlled by the state of the latch, such that the orientation of the invertible segment switches efficiently each time the device receives an input pulse. Recombination occurs over a time scale of minutes after initiation of integrase expression. The latch requires a delay circuit, implemented with a transcriptional repressor expressed in only one state, to ensure that each input pulse results in only one inversion of the DNA segment. Development and optimization of the latch in living cells was driven by mathematical modelling of the recombination reactions and gene expression regulated by the switch. We discuss how N latches built with orthogonal site-specific recombination systems could be chained together to form a binary ripple counter that could count to 2N - 1.
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Affiliation(s)
- Jia Zhao
- Institute of Molecular, Cell and Systems Biology, University of Glasgow, Bower Building, Glasgow G12 8QQ, Scotland
| | - Alexandra Pokhilko
- Institute of Molecular, Cell and Systems Biology, University of Glasgow, Bower Building, Glasgow G12 8QQ, Scotland
| | - Oliver Ebenhöh
- Cluster of Excellence on Plant Sciences (CEPLAS), Heinrich-Heine-University, Universitätsstraße 1, D-40225 Düsseldorf, Germany,Institute of Quantitative and Theoretical Biology, Heinrich-Heine-University Düsseldorf, Universitätsstraße 1, D-40225 Düsseldorf, Germany
| | - Susan J Rosser
- SynthSys - Synthetic and Systems Biology, School of Biological Sciences, University of Edinburgh, CH Waddington Building, The King’s Buildings, Mayfield Road, Edinburgh EH9 3JD, Scotland,Correspondence may also be addressed to Susan J. Rosser. Tel. +44 131 650 50 86;
| | - Sean D Colloms
- Institute of Molecular, Cell and Systems Biology, University of Glasgow, Bower Building, Glasgow G12 8QQ, Scotland,To whom correspondence should be addressed. Tel: +44 141 330 6236; Fax: +44 141 330 4878;
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86
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Ahan RE, Saltepe B, Apaydin O, Seker UOS. Cellular Biocatalysts Using Synthetic Genetic Circuits for Prolonged and Durable Enzymatic Activity. Chembiochem 2019; 20:1799-1809. [DOI: 10.1002/cbic.201800767] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Revised: 03/08/2019] [Indexed: 11/11/2022]
Affiliation(s)
- Recep Erdem Ahan
- UNAM-Institute of Materials Science and NanotechnologyNational Nanotechnology Research Center Bilkent University 06800 Ankara Turkey
| | - Behide Saltepe
- UNAM-Institute of Materials Science and NanotechnologyNational Nanotechnology Research Center Bilkent University 06800 Ankara Turkey
| | - Onur Apaydin
- UNAM-Institute of Materials Science and NanotechnologyNational Nanotechnology Research Center Bilkent University 06800 Ankara Turkey
| | - Urartu Ozgur Safak Seker
- UNAM-Institute of Materials Science and NanotechnologyNational Nanotechnology Research Center Bilkent University 06800 Ankara Turkey
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87
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Xia PF, Ling H, Foo JL, Chang MW. Synthetic genetic circuits for programmable biological functionalities. Biotechnol Adv 2019; 37:107393. [PMID: 31051208 DOI: 10.1016/j.biotechadv.2019.04.015] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Revised: 04/09/2019] [Accepted: 04/28/2019] [Indexed: 02/06/2023]
Abstract
Living organisms evolve complex genetic networks to interact with the environment. Due to the rapid development of synthetic biology, various modularized genetic parts and units have been identified from these networks. They have been employed to construct synthetic genetic circuits, including toggle switches, oscillators, feedback loops and Boolean logic gates. Building on these circuits, complex genetic machines with capabilities in programmable decision-making could be created. Consequently, these accomplishments have led to novel applications, such as dynamic and autonomous modulation of metabolic networks, directed evolution of biological units, remote and targeted diagnostics and therapies, as well as biological containment methods to prevent release of engineered microorganisms and genetic materials. Herein, we outline the principles in genetic circuit design that have initiated a new chapter in transforming concepts to realistic applications. The features of modularized building blocks and circuit architecture that facilitate realization of circuits for a variety of novel applications are discussed. Furthermore, recent advances and challenges in employing genetic circuits to impart microorganisms with distinct and programmable functionalities are highlighted. We envision that this review gives new insights into the design of synthetic genetic circuits and offers a guideline for the implementation of different circuits in various aspects of biotechnology and bioengineering.
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Affiliation(s)
- Peng-Fei Xia
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore
| | - Hua Ling
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore
| | - Jee Loon Foo
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore.
| | - Matthew Wook Chang
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore.
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88
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Ahan RE, Kırpat BM, Saltepe B, Şeker UÖŞ. A Self-Actuated Cellular Protein Delivery Machine. ACS Synth Biol 2019; 8:686-696. [PMID: 30811932 DOI: 10.1021/acssynbio.9b00062] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Engineered bacterial cells have great promise to solve global problems, yet they are hampered by a lack of convenient strategy for controlled protein release. A well-controlled protein translocation through cellular membranes is essential for cell-based protein delivery. Here we have developed a controlled protein release system by programming a bacterial autotransporter system named Ag43. Ag43 protein is engineered by adding a protease digestion site between its translocation and cargo domains. Once it is displayed on the cell surface, we managed to release the cargo proteins in defined conditions by processing environmental signals. The protein release in terms of time and quantity can be controlled through changing the inducer conditions. We thought that the release system can be adopted for complex genetic circuitries due to its simplicity. We implemented the protein release system to develop a cellular device that is able to release proteins in a sequence response to ordered chemical signals. We envision that development of genetically controlled protein release systems will improve the applications of synthetic organisms in cell based therapies, especially for cases with a need for controlled protein release using the cues from the biological environment.
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Affiliation(s)
- Recep Erdem Ahan
- UNAM−National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey
- Institute of Materials Science and Nanotechnology, Bilkent University, 06800 Ankara, Turkey
| | - Büşra Merve Kırpat
- UNAM−National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey
- Institute of Materials Science and Nanotechnology, Bilkent University, 06800 Ankara, Turkey
| | - Behide Saltepe
- UNAM−National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey
- Institute of Materials Science and Nanotechnology, Bilkent University, 06800 Ankara, Turkey
| | - Urartu Özgür Şafak Şeker
- UNAM−National Nanotechnology Research Center, Bilkent University, 06800 Ankara, Turkey
- Institute of Materials Science and Nanotechnology, Bilkent University, 06800 Ankara, Turkey
- Neuroscience Graduate Program, Bilkent University, 06800 Ankara, Turkey
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89
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Abstract
Living cells communicate information about physiological conditions by producing signaling molecules in a specific timed manner. Different conditions can result in the same total amount of a signaling molecule, differing only in the pattern of the molecular concentration over time. Such temporally coded information can be completely invisible to even state-of-the-art molecular sensors with high chemical specificity that respond only to the total amount of the signaling molecule. Here, we demonstrate design principles for circuits with temporal specificity, that is, molecular circuits that respond to specific temporal patterns in a molecular concentration. We consider pulsatile patterns in a molecular concentration characterized by three fundamental temporal features: time period, duty fraction, and number of pulses. We develop circuits that respond to each one of these features while being insensitive to the others. We demonstrate our design principles using general chemical reaction networks and with explicit simulations of DNA strand displacement reactions. In this way, our work develops building blocks for temporal pattern recognition through molecular computation.
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Affiliation(s)
- Jackson O’Brien
- The James Franck Institute and Department of Physics, University of Chicago, Chicago, Illinois 60637, United States
| | - Arvind Murugan
- The James Franck Institute and Department of Physics, University of Chicago, Chicago, Illinois 60637, United States
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90
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Millacura FA, Largey B, French CE. ParAlleL: A Novel Population-Based Approach to Biological Logic Gates. Front Bioeng Biotechnol 2019; 7:46. [PMID: 30949475 PMCID: PMC6437039 DOI: 10.3389/fbioe.2019.00046] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2018] [Accepted: 02/27/2019] [Indexed: 01/27/2023] Open
Abstract
In vivo logic gates have proven difficult to combine into larger devices. Our cell-based logic system, ParAlleL, decomposes a large circuit into a collection of small subcircuits working in parallel, each subcircuit responding to a different combination of inputs. A final global output is then generated by a combination of the responses. Using ParAlleL, for the first time a completely functional 3-bit full adder and full subtractor were generated using Escherichia coli cells, as well as a calculator-style display that shows a numeric result, from 0 to 7, when the proper 3 bit binary inputs are introduced into the system. ParAlleL demonstrates the use of a parallel approach for the design of cell-based logic gates that facilitates the generation and analysis of complex processes, without the need for complex genetic engineering.
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Affiliation(s)
- Felipe A Millacura
- School of Biological Sciences, Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh, United Kingdom
| | - Brendan Largey
- School of Biological Sciences, Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh, United Kingdom
| | - Christopher E French
- School of Biological Sciences, Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Edinburgh, United Kingdom
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91
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Affiliation(s)
- David S Glass
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Uri Alon
- Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot 76100, Israel.
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92
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Zañudo JGT, Guinn MT, Farquhar K, Szenk M, Steinway SN, Balázsi G, Albert R. Towards control of cellular decision-making networks in the epithelial-to-mesenchymal transition. Phys Biol 2019; 16:031002. [PMID: 30654341 PMCID: PMC6405305 DOI: 10.1088/1478-3975/aaffa1] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
We present the epithelial-to-mesenchymal transition (EMT) from two perspectives: experimental/technological and theoretical. We review the state of the current understanding of the regulatory networks that underlie EMT in three physiological contexts: embryonic development, wound healing, and metastasis. We describe the existing experimental systems and manipulations used to better understand the molecular participants and factors that influence EMT and metastasis. We review the mathematical models of the regulatory networks involved in EMT, with a particular emphasis on the network motifs (such as coupled feedback loops) that can generate intermediate hybrid states between the epithelial and mesenchymal states. Ultimately, the understanding gained about these networks should be translated into methods to control phenotypic outcomes, especially in the context of cancer therapeutic strategies. We present emerging theories of how to drive the dynamics of a network toward a desired dynamical attractor (e.g. an epithelial cell state) and emerging synthetic biology technologies to monitor and control the state of cells.
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Affiliation(s)
- Jorge Gómez Tejeda Zañudo
- Department of Physics, Pennsylvania State University, University Park, PA 16802, USA
- Department of Medical Oncology, Dana-Farber Cancer Center, Boston, MA 02215, USA
- Cancer Program, Eli and Edythe L. Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - M. Tyler Guinn
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11794 USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
- Stony Brook Medical Scientist Training Program, 101 Nicolls Road, Stony Brook, NY 11794, USA
| | - Kevin Farquhar
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Mariola Szenk
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11794 USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Steven N. Steinway
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Gábor Balázsi
- Biomedical Engineering Department, Stony Brook University, Stony Brook, NY 11794 USA
- Laufer Center for Physical and Quantitative Biology, Stony Brook University, Stony Brook, NY 11794, USA
| | - Réka Albert
- Department of Physics, Pennsylvania State University, University Park, PA 16802, USA
- Department of Biology, Pennsylvania State University, University Park, PA 16802, USA
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93
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Jusiak B, Jagtap K, Gaidukov L, Duportet X, Bandara K, Chu J, Zhang L, Weiss R, Lu TK. Comparison of Integrases Identifies Bxb1-GA Mutant as the Most Efficient Site-Specific Integrase System in Mammalian Cells. ACS Synth Biol 2019; 8:16-24. [PMID: 30609349 DOI: 10.1021/acssynbio.8b00089] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Phage-derived integrases can catalyze irreversible, site-specific integration of transgenic payloads into a chromosomal locus, resulting in mammalian cells that stably express transgenes or circuits of interest. Previous studies have demonstrated high-efficiency integration by the Bxb1 integrase in mammalian cells. Here, we show that a point mutation (Bxb1-GA) in Bxb1 target sites significantly increases Bxb1-mediated integration efficiency at the Rosa26 locus in Chinese hamster ovary cells, resulting in the highest integration efficiency reported with a site-specific integrase in mammalian cells. Bxb1-GA point mutant sites do not cross-react with Bxb1 wild-type sites, enabling their use in applications that require orthogonal pairs of target sites. In comparison, we test the efficiency and orthogonality of ϕC31 and Wβ integrases, and show that Wβ has an integration efficiency between those of Bxb1-GA and wild-type Bxb1. Our data present a toolbox of integrases for inserting payloads such as gene circuits or therapeutic transgenes into mammalian cell lines.
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Affiliation(s)
- Barbara Jusiak
- Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Kalpana Jagtap
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Leonid Gaidukov
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Xavier Duportet
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Kalpanie Bandara
- Cell Line Development, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Andover, Massachusetts 01810, United States
| | - Jianlin Chu
- Cell Line Development, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Andover, Massachusetts 01810, United States
| | - Lin Zhang
- Cell Line Development, Biotherapeutics Pharmaceutical Sciences, Pfizer Inc., Andover, Massachusetts 01810, United States
| | - Ron Weiss
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Timothy K. Lu
- Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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94
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Abstract
Australia is well positioned to conduct clinical trials in phage-based technology. Despite challenges with translating phage therapy to mainstream medicine, our regulations are designed for safe and innovative development. Recent success indicates that Australia is ideal for conducting further phage clinical trials. There are also expert clinical research organisations and generous tax incentives.
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95
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Venayak N, Raj K, Jaydeep R, Mahadevan R. An Optimized Bistable Metabolic Switch To Decouple Phenotypic States during Anaerobic Fermentation. ACS Synth Biol 2018; 7:2854-2866. [PMID: 30376634 DOI: 10.1021/acssynbio.8b00284] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Metabolic engineers aim to genetically modify microorganisms to improve their ability to produce valuable compounds. Despite the prevalence of growth-coupled production processes, these strategies can significantly limit production rates. Instead, rates can be improved by decoupling and optimizing growth and production independently, and operating with a growth stage followed by a production stage. Here, we implement a bistable transcriptional controller to decouple and switch between these two states. We optimize the controller in anaerobic conditions, typical of industrial fermentations, to ensure stability and tight expression control, while improving switching dynamics. The stability of this controller can be maintained through a simulated seed train scale-up from 5 mL to 500 000 L, indicating industrial feasibility. Finally, we demonstrate a two-stage production process using our optimal construct to improve the instantaneous rate of lactate production by over 50%, motivating the use of these systems in broad metabolic engineering applications.
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Affiliation(s)
- Naveen Venayak
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3H7, Canada
| | - Kaushik Raj
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3H7, Canada
| | - Rohil Jaydeep
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3H7, Canada
| | - Radhakrishnan Mahadevan
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3H7, Canada
- The Institute of Biomaterials & Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3H7, Canada
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96
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Venayak N, von Kamp A, Klamt S, Mahadevan R. MoVE identifies metabolic valves to switch between phenotypic states. Nat Commun 2018; 9:5332. [PMID: 30552335 PMCID: PMC6294006 DOI: 10.1038/s41467-018-07719-4] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 11/02/2018] [Indexed: 01/29/2023] Open
Abstract
Metabolism is highly regulated, allowing for robust and complex behavior. This behavior can often be achieved by controlling a small number of important metabolic reactions, or metabolic valves. Here, we present a method to identify the location of such valves: the metabolic valve enumerator (MoVE). MoVE uses a metabolic model to identify genetic intervention strategies which decouple two desired phenotypes. We apply this method to identify valves which can decouple growth and production to systematically improve the rate and yield of biochemical production processes. We apply this algorithm to the production of diverse compounds and obtained solutions for over 70% of our targets, identifying a small number of highly represented valves to achieve near maximal growth and production. MoVE offers a systematic approach to identify metabolic valves using metabolic models, providing insight into the architecture of metabolic networks and accelerating the widespread implementation of dynamic flux redirection in diverse systems.
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Affiliation(s)
- Naveen Venayak
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, ON, M5S 3E5, Canada
| | - Axel von Kamp
- Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, 39106, Magdeburg, Germany
| | - Steffen Klamt
- Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstraße 1, 39106, Magdeburg, Germany
| | - Radhakrishnan Mahadevan
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College Street, Toronto, ON, M5S 3E5, Canada. .,Institute of Biomaterials and Biomedical Engineering, University of Toronto, 164, College Street, Toronto, ON, M5S 3G9, Canada.
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97
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Chu D, Spinney RE. A thermodynamically consistent model of finite-state machines. Interface Focus 2018; 8:20180037. [PMID: 30443334 DOI: 10.1098/rsfs.2018.0037] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/14/2018] [Indexed: 01/26/2023] Open
Abstract
Finite-state machines (FSMs) are a theoretically and practically important model of computation. We propose a general, thermodynamically consistent model of FSMs and characterize the resource requirements of these machines. We model FSMs as time-inhomogeneous Markov chains. The computation is driven by instantaneous manipulations of the energy levels of the states. We calculate the entropy production of the machine, its error probability, and the time required to complete one update step. We find that a sequence of generalized bit-setting operations is sufficient to implement any FSM.
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Affiliation(s)
- Dominique Chu
- School of Computing, University of Kent, Canterbury CT2 7NF, UK
| | - Richard E Spinney
- Centre for Complex Systems, The University of Sydney, Sydney, New South Wales 2006, Australia
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98
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Li L, Wei K, Liu X, Wu Y, Zheng G, Chen S, Jiang W, Lu Y. aMSGE: advanced multiplex site-specific genome engineering with orthogonal modular recombinases in actinomycetes. Metab Eng 2018; 52:153-167. [PMID: 30529239 DOI: 10.1016/j.ymben.2018.12.001] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2018] [Revised: 11/27/2018] [Accepted: 12/04/2018] [Indexed: 11/18/2022]
Abstract
Chromosomal integration of genes and pathways is of particular importance for large-scale and long-term fermentation in industrial biotechnology. However, stable, multi-copy integration of long DNA segments (e.g., large gene clusters) remains challenging. Here, we describe a plug-and-play toolkit that allows for high-efficiency, single-step, multi-locus integration of natural product (NP) biosynthetic gene clusters (BGCs) in actinomycetes, based on the innovative concept of "multiple integrases-multiple attB sites". This toolkit consists of 27 synthetic modular plasmids, which contain single- or multi-integration modules (from two to four) derived from five orthogonal site-specific recombination (SSR) systems. The multi-integration modules can be readily ligated into plasmids containing large BGCs by Gibson assembly, which can be simultaneously inserted into multiple native attB sites in a single step. We demonstrated the applicability of this toolkit by performing stabilized amplification of acetyl-CoA carboxylase genes to facilitate actinorhodin biosynthesis in Streptomyces coelicolor. Furthermore, using this toolkit, we achieved a 185.6% increase in 5-oxomilbemycin titers (from 2.23 to 6.37 g/L) in Streptomyces hygroscopicus via the multi-locus integration of the entire 5-oxomilbemycin BGC (72 kb) (up to four copies). Compared with previously reported methods, the advanced multiplex site-specific genome engineering (aMSGE) method does not require the introduction of any modifications into host genomes before the amplification of target genes or BGCs, which will drastically simplify and accelerate efforts to improve NP production. Considering that SSR systems are widely distributed in a variety of industrial microbes, this novel technique also promises to be a valuable tool for the enhanced biosynthesis of other high-value bioproducts.
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Affiliation(s)
- Lei Li
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Keke Wei
- School of Pharmacy, Fudan University, Shanghai 201203, China; Department of Biochemistry, Shanghai Institute of Pharmaceutical Industry, Shanghai 201210, China
| | - Xiaocao Liu
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China; School of Life Science, Henan University, Kaifeng 475004, China
| | - Yuanjie Wu
- Department of Biochemistry, Shanghai Institute of Pharmaceutical Industry, Shanghai 201210, China
| | - Guosong Zheng
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Shaoxin Chen
- Department of Biochemistry, Shanghai Institute of Pharmaceutical Industry, Shanghai 201210, China
| | - Weihong Jiang
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China; Jiangsu National Synergetic Innovation Center for Advanced Materials, SICAM, Nanjing 210009, China.
| | - Yinhua Lu
- College of Life Sciences, Shanghai Normal University, Shanghai 200232, China.
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99
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Purcell O, Wang J, Siuti P, Lu TK. Encryption and steganography of synthetic gene circuits. Nat Commun 2018; 9:4942. [PMID: 30467337 PMCID: PMC6250736 DOI: 10.1038/s41467-018-07144-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Accepted: 10/10/2018] [Indexed: 12/29/2022] Open
Abstract
Synthetic biologists use artificial gene circuits to control and engineer living cells. As engineered cells become increasingly commercialized, it will be desirable to protect the intellectual property contained in these circuits. Here, we introduce strategies to hide the design of synthetic gene circuits, making it more difficult for an unauthorized third party to determine circuit structure and function. We present two different approaches: the first uses encryption by overlapping uni-directional recombinase sites to scramble circuit topology and the second uses steganography by adding genes and interconnections to obscure circuit topology. We also discuss a third approach: to use synthetic genetic codes to mask the function of synthetic circuits. For each approach, we discuss relative strengths, weaknesses, and practicality of implementation, with the goal to inspire further research into this important and emerging area.
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Affiliation(s)
- Oliver Purcell
- Synthetic Biology Center, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, MA, 02139, USA
| | - Jerry Wang
- Synthetic Biology Center, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, MA, 02139, USA
| | - Piro Siuti
- Synthetic Biology Center, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, MA, 02139, USA
| | - Timothy K Lu
- Synthetic Biology Center, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, MA, 02139, USA. .,Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA. .,Research Laboratory of Electronics, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA, 02139, USA.
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100
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Abstract
Measuring biological data across time and space is critical for understanding complex biological processes and for various biosurveillance applications. However, such data are often inaccessible or difficult to directly obtain. Less invasive, more robust and higher-throughput biological recording tools are needed to profile cells and their environments. DNA-based cellular recording is an emerging and powerful framework for tracking intracellular and extracellular biological events over time across living cells and populations. Here, we review and assess DNA recorders that utilize CRISPR nucleases, integrases and base-editing strategies, as well as recombinase and polymerase-based methods. Quantitative characterization, modelling and evaluation of these DNA-recording modalities can guide their design and implementation for specific application areas.
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Affiliation(s)
- Ravi U Sheth
- Department of Systems Biology, Columbia University Medical Center, New York, NY, USA
- Integrated Program in Cellular, Molecular and Biomedical Studies, Columbia University, New York, NY, USA
| | - Harris H Wang
- Department of Systems Biology, Columbia University Medical Center, New York, NY, USA.
- Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA.
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