1
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Yang T, Nakanishi H, Itaka K. Development of a new caged intein for multi-input conditional translation of synthetic mRNA. Sci Rep 2024; 14:9988. [PMID: 38693346 PMCID: PMC11063168 DOI: 10.1038/s41598-024-60809-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 04/26/2024] [Indexed: 05/03/2024] Open
Abstract
mRNA medicines can be used to express therapeutic proteins, but the production of such proteins in non-target cells has a risk of adverse effects. To accurately distinguish between therapeutic target and nontarget cells, it is desirable to utilize multiple proteins expressed in each cell as indicators. To achieve such multi-input translational regulation of mRNA medicines, in this study, we engineered Rhodothermus marinus (Rma) DnaB intein to develop "caged Rma DnaB intein" that enables conditional reconstitution of full-length translational regulator protein from split fragments. By combining the caged Rma DnaB intein, the split translational regulator protein, and target protein-binding domains, we succeeded in target protein-dependent translational repression of mRNA in human cells. In addition, the caged Rma intein showed orthogonality to the previously reported Nostoc punctiforme (Npu) DnaE-based caged intein. Finally, by combining these two orthogonal caged inteins, we developed an mRNA-based logic gate that regulates translation based on the expression of multiple intracellular proteins. This study provides important information to develop safer mRNA medicines.
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Affiliation(s)
- Tingting Yang
- Department of Biofunction Research, Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University (TMDU), Tokyo, 101-0062, Japan
| | - Hideyuki Nakanishi
- Department of Biofunction Research, Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University (TMDU), Tokyo, 101-0062, Japan.
- Center for Infectious Disease Education and Research (CiDER), Osaka University, Osaka, 565-0871, Japan.
| | - Keiji Itaka
- Department of Biofunction Research, Institute of Biomaterials and Bioengineering, Tokyo Medical and Dental University (TMDU), Tokyo, 101-0062, Japan.
- Center for Infectious Disease Education and Research (CiDER), Osaka University, Osaka, 565-0871, Japan.
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2
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Mousavi R, Lobo D. Automatic design of gene regulatory mechanisms for spatial pattern formation. NPJ Syst Biol Appl 2024; 10:35. [PMID: 38565850 PMCID: PMC10987498 DOI: 10.1038/s41540-024-00361-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 03/19/2024] [Indexed: 04/04/2024] Open
Abstract
Gene regulatory mechanisms (GRMs) control the formation of spatial and temporal expression patterns that can serve as regulatory signals for the development of complex shapes. Synthetic developmental biology aims to engineer such genetic circuits for understanding and producing desired multicellular spatial patterns. However, designing synthetic GRMs for complex, multi-dimensional spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given two-dimensional spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms-including the number of genes necessary for the formation of the target spatial pattern-we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover complex genetic circuits producing spatial patterns.
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Affiliation(s)
- Reza Mousavi
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA
| | - Daniel Lobo
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA.
- Greenebaum Comprehensive Cancer Center and Center for Stem Cell Biology & Regenerative Medicine, University of Maryland, Baltimore, Baltimore, MD, USA.
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3
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Gao Y, Wang L, Wang B. Customizing cellular signal processing by synthetic multi-level regulatory circuits. Nat Commun 2023; 14:8415. [PMID: 38110405 PMCID: PMC10728147 DOI: 10.1038/s41467-023-44256-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 12/05/2023] [Indexed: 12/20/2023] Open
Abstract
As synthetic biology permeates society, the signal processing circuits in engineered living systems must be customized to meet practical demands. Towards this mission, novel regulatory mechanisms and genetic circuits with unprecedented complexity have been implemented over the past decade. These regulatory mechanisms, such as transcription and translation control, could be integrated into hybrid circuits termed "multi-level circuits". The multi-level circuit design will tremendously benefit the current genetic circuit design paradigm, from modifying basic circuit dynamics to facilitating real-world applications, unleashing our capabilities to customize cellular signal processing and address global challenges through synthetic biology.
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Affiliation(s)
- Yuanli Gao
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, China
- School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
| | - Lei Wang
- Center of Synthetic Biology and Integrated Bioengineering & School of Engineering, Westlake University, Hangzhou, 310030, China.
| | - Baojun Wang
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, China.
- Research Center for Biological Computation, Zhejiang Lab, Hangzhou, 311100, China.
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4
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Makri Pistikou AM, Cremers GAO, Nathalia BL, Meuleman TJ, Bögels BWA, Eijkens BV, de Dreu A, Bezembinder MTH, Stassen OMJA, Bouten CCV, Merkx M, Jerala R, de Greef TFA. Engineering a scalable and orthogonal platform for synthetic communication in mammalian cells. Nat Commun 2023; 14:7001. [PMID: 37919273 PMCID: PMC10622552 DOI: 10.1038/s41467-023-42810-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 10/23/2023] [Indexed: 11/04/2023] Open
Abstract
The rational design and implementation of synthetic mammalian communication systems can unravel fundamental design principles of cell communication circuits and offer a framework for engineering of designer cell consortia with potential applications in cell therapeutics. Here, we develop the foundations of an orthogonal, and scalable mammalian synthetic communication platform that exploits the programmability of synthetic receptors and selective affinity and tunability of diffusing coiled-coil peptides. Leveraging the ability of coiled-coils to exclusively bind to a cognate receptor, we demonstrate orthogonal receptor activation and Boolean logic operations at the receptor level. We show intercellular communication based on synthetic receptors and secreted multidomain coiled-coils and demonstrate a three-cell population system that can perform AND gate logic. Finally, we show CC-GEMS receptor-dependent therapeutic protein expression. Our work provides a modular and scalable framework for the engineering of complex cell consortia, with the potential to expand the aptitude of cell therapeutics and diagnostics.
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Affiliation(s)
- Anna-Maria Makri Pistikou
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Glenn A O Cremers
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Bryan L Nathalia
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Theodorus J Meuleman
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Center for Living Technologies, Eindhoven-Wageningen-Utrecht Alliance, Utrecht, The Netherlands
| | - Bas W A Bögels
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Bruno V Eijkens
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Anne de Dreu
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Maarten T H Bezembinder
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Oscar M J A Stassen
- Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Carlijn C V Bouten
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Maarten Merkx
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Roman Jerala
- Department of Synthetic Biology and Immunology, National Institute of Chemistry, Ljubljana, Slovenia
- EN-FIST Centre of Excellence, Ljubljana, Slovenia
| | - Tom F A de Greef
- Laboratory of Chemical Biology, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
- Institute for Complex Molecular Systems, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
- Computational Biology Group, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
- Laboratory for Cell and Tissue Engineering, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
- Center for Living Technologies, Eindhoven-Wageningen-Utrecht Alliance, Utrecht, The Netherlands.
- Institute for Molecules and Materials, Radboud University, Nijmegen, The Netherlands.
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5
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Bao T, Qian Y, Xin Y, Collins JJ, Lu T. Engineering microbial division of labor for plastic upcycling. Nat Commun 2023; 14:5712. [PMID: 37752119 PMCID: PMC10522701 DOI: 10.1038/s41467-023-40777-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 08/09/2023] [Indexed: 09/28/2023] Open
Abstract
Plastic pollution is rapidly increasing worldwide, causing adverse impacts on the environment, wildlife and human health. One tempting solution to this crisis is upcycling plastics into products with engineered microorganisms; however, this remains challenging due to complexity in conversion. Here we present a synthetic microbial consortium that efficiently degrades polyethylene terephthalate hydrolysate and subsequently produces desired chemicals through division of labor. The consortium involves two Pseudomonas putida strains, specializing in terephthalic acid and ethylene glycol utilization respectively, to achieve complete substrate assimilation. Compared with its monoculture counterpart, the consortium exhibits reduced catabolic crosstalk and faster deconstruction, particularly when substrate concentrations are high or crude hydrolysate is used. It also outperforms monoculture when polyhydroxyalkanoates serves as a target product and confers flexible tuning through population modulation for cis-cis muconate synthesis. This work demonstrates engineered consortia as a promising, effective platform that may facilitate polymer upcycling and environmental sustainability.
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Affiliation(s)
- Teng Bao
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Yuanchao Qian
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Yongping Xin
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - James J Collins
- Department of Biological Engineering and Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Longwood, MA, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Ting Lu
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- Department of Physics, University of Illinois Urbana-Champaign, Urbana, IL, USA.
- National Center for Supercomputing Applications, Urbana, IL, 61801, USA.
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6
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Short AE, Kim D, Milner PT, Wilson CJ. Next generation synthetic memory via intercepting recombinase function. Nat Commun 2023; 14:5255. [PMID: 37644045 PMCID: PMC10465543 DOI: 10.1038/s41467-023-41043-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 08/22/2023] [Indexed: 08/31/2023] Open
Abstract
Here we present a technology to facilitate synthetic memory in a living system via repurposing Transcriptional Programming (i.e., our decision-making technology) parts, to regulate (intercept) recombinase function post-translation. We show that interception synthetic memory can facilitate programmable loss-of-function via site-specific deletion, programmable gain-of-function by way of site-specific inversion, and synthetic memory operations with nested Boolean logical operations. We can expand interception synthetic memory capacity more than 5-fold for a single recombinase, with reconfiguration specificity for multiple sites in parallel. Interception synthetic memory is ~10-times faster than previous generations of recombinase-based memory. We posit that the faster recombination speed of our next-generation memory technology is due to the post-translational regulation of recombinase function. This iteration of synthetic memory is complementary to decision-making via Transcriptional Programming - thus can be used to develop intelligent synthetic biological systems for myriad applications.
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Affiliation(s)
- Andrew E Short
- Georgia Institute of Technology, School of Chemical and Biomolecular Engineering, Atlanta, GA, USA
| | - Dowan Kim
- Georgia Institute of Technology, School of Chemical and Biomolecular Engineering, Atlanta, GA, USA
| | - Prasaad T Milner
- Georgia Institute of Technology, School of Chemical and Biomolecular Engineering, Atlanta, GA, USA
| | - Corey J Wilson
- Georgia Institute of Technology, School of Chemical and Biomolecular Engineering, Atlanta, GA, USA.
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7
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Jones RD, Qian Y, Ilia K, Wang B, Laub MT, Del Vecchio D, Weiss R. Author Correction: Robust and tunable signal processing in mammalian cells via engineered covalent modification cycles. Nat Commun 2023; 14:4775. [PMID: 37553375 PMCID: PMC10409853 DOI: 10.1038/s41467-023-40559-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/10/2023] Open
Affiliation(s)
- Ross D Jones
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Yili Qian
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Katherine Ilia
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Benjamin Wang
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Michael T Laub
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Domitilla Del Vecchio
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
| | - Ron Weiss
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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8
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Anastassov S, Filo M, Chang CH, Khammash M. A cybergenetic framework for engineering intein-mediated integral feedback control systems. Nat Commun 2023; 14:1337. [PMID: 36906662 PMCID: PMC10008564 DOI: 10.1038/s41467-023-36863-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 02/21/2023] [Indexed: 03/13/2023] Open
Abstract
The ability of biological systems to tightly regulate targeted variables, despite external and internal disturbances, is known as Robust Perfect Adaptation (RPA). Achieved frequently through biomolecular integral feedback controllers at the cellular level, RPA has important implications for biotechnology and its various applications. In this study, we identify inteins as a versatile class of genetic components suitable for implementing these controllers and present a systematic approach for their design. We develop a theoretical foundation for screening intein-based RPA-achieving controllers and a simplified approach for modeling them. We then genetically engineer and test intein-based controllers using commonly used transcription factors in mammalian cells and demonstrate their exceptional adaptation properties over a wide dynamic range. The small size, flexibility, and applicability of inteins across life forms allow us to create a diversity of genetic RPA-achieving integral feedback control systems that can be used in various applications, including metabolic engineering and cell-based therapy.
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Affiliation(s)
- Stanislav Anastassov
- Department of Biosystems Science and Engineering, ETH Zürich, 4058, Basel, Switzerland
| | - Maurice Filo
- Department of Biosystems Science and Engineering, ETH Zürich, 4058, Basel, Switzerland
| | - Ching-Hsiang Chang
- Department of Biosystems Science and Engineering, ETH Zürich, 4058, Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering, ETH Zürich, 4058, Basel, Switzerland.
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9
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Williams RL, Murray RM. Integrase-mediated differentiation circuits improve evolutionary stability of burdensome and toxic functions in E. coli. Nat Commun 2022; 13:6822. [PMID: 36357387 PMCID: PMC9649629 DOI: 10.1038/s41467-022-34361-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 10/22/2022] [Indexed: 11/12/2022] Open
Abstract
Advances in synthetic biology, bioengineering, and computation allow us to rapidly and reliably program cells with increasingly complex and useful functions. However, because the functions we engineer cells to perform are typically burdensome to cell growth, they can be rapidly lost due to the processes of mutation and natural selection. Here, we show that a strategy of terminal differentiation improves the evolutionary stability of burdensome functions in a general manner by realizing a reproductive and metabolic division of labor. To implement this strategy, we develop a genetic differentiation circuit in Escherichia coli using unidirectional integrase-recombination. With terminal differentiation, differentiated cells uniquely express burdensome functions driven by the orthogonal T7 RNA polymerase, but their capacity to proliferate is limited to prevent the propagation of advantageous loss-of-function mutations that inevitably occur. We demonstrate computationally and experimentally that terminal differentiation increases duration and yield of high-burden expression and that its evolutionary stability can be improved with strategic redundancy. Further, we show this strategy can even be applied to toxic functions. Overall, this study provides an effective, generalizable approach for protecting burdensome engineered functions from evolutionary degradation.
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Affiliation(s)
- Rory L. Williams
- grid.20861.3d0000000107068890Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125 US ,grid.266093.80000 0001 0668 7243Present Address: Department of Biomedical Engineering, University of California Irvine, Irvine, CA 92697 US
| | - Richard M. Murray
- grid.20861.3d0000000107068890Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125 US
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10
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Joshi SHN, Yong C, Gyorgy A. Inducible plasmid copy number control for synthetic biology in commonly used E. coli strains. Nat Commun 2022; 13:6691. [PMID: 36335103 PMCID: PMC9637173 DOI: 10.1038/s41467-022-34390-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 10/21/2022] [Indexed: 11/06/2022] Open
Abstract
The ability to externally control gene expression has been paradigm shifting for all areas of biological research, especially for synthetic biology. Such control typically occurs at the transcriptional and translational level, while technologies enabling control at the DNA copy level are limited by either (i) relying on a handful of plasmids with fixed and arbitrary copy numbers; or (ii) require multiple plasmids for replication control; or (iii) are restricted to specialized strains. To overcome these limitations, we present TULIP (TUnable Ligand Inducible Plasmid): a self-contained plasmid with inducible copy number control, designed for portability across various Escherichia coli strains commonly used for cloning, protein expression, and metabolic engineering. Using TULIP, we demonstrate through multiple application examples that flexible plasmid copy number control accelerates the design and optimization of gene circuits, enables efficient probing of metabolic burden, and facilitates the prototyping and recycling of modules in different genetic contexts.
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Affiliation(s)
- Shivang Hina-Nilesh Joshi
- grid.440573.10000 0004 1755 5934Division of Engineering, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
| | - Chentao Yong
- grid.440573.10000 0004 1755 5934Division of Engineering, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates ,grid.137628.90000 0004 1936 8753Department of Chemical and Biomolecular Engineering, New York University, New York, NY USA
| | - Andras Gyorgy
- grid.440573.10000 0004 1755 5934Division of Engineering, New York University Abu Dhabi, Abu Dhabi, United Arab Emirates
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11
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Zhang Q, Azarin SM, Sarkar CA. Model-guided engineering of DNA sequences with predictable site-specific recombination rates. Nat Commun 2022; 13:4152. [PMID: 35858965 PMCID: PMC9300676 DOI: 10.1038/s41467-022-31538-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 06/22/2022] [Indexed: 11/09/2022] Open
Abstract
Site-specific recombination (SSR) is an important tool in synthetic biology, but its applications are limited by the inability to predictably tune SSR reaction rates. Facile rate manipulation could be achieved by modifying the DNA substrate sequence; however, this approach lacks rational design principles. Here, we develop an integrated experimental and computational method to engineer the DNA attachment sequence attP for predictably modulating the inversion reaction mediated by the recombinase Bxb1. After developing a qPCR method to measure SSR reaction rate, we design, select, and sequence attP libraries to inform a machine-learning model that computes Bxb1 inversion rate as a function of attP sequence. We use this model to predict reaction rates of attP variants in vitro and demonstrate their utility in gene circuit design in Escherichia coli. Our high-throughput, model-guided approach for rationally tuning SSR reaction rates enhances our understanding of recombinase function and expands the synthetic biology toolbox.
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Affiliation(s)
- Qiuge Zhang
- grid.17635.360000000419368657Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, MN 55455 USA
| | - Samira M. Azarin
- grid.17635.360000000419368657Department of Chemical Engineering and Materials Science, University of Minnesota, Minneapolis, MN 55455 USA
| | - Casim A. Sarkar
- grid.17635.360000000419368657Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455 USA
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12
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Abstract
Protein complexes are the fundamental units of many biological functions. Despite their many advantages, one major adverse impact of protein complexes is accumulations of unassembled subunits that may disrupt other processes or exert cytotoxic effects. Synthesis of excess subunits can be inhibited via negative feedback control or they can be degraded more efficiently than assembled subunits, with this latter being termed cooperative stability. Whereas controlled synthesis of complex subunits has been investigated extensively, how cooperative stability acts in complex formation remains largely unexplored. To fill this knowledge gap, we have built quantitative models of heteromeric complexes with or without cooperative stability and compared their behaviours in the presence of synthesis rate variations. A system displaying cooperative stability is robust against synthesis rate variations as it retains high dimer/monomer ratios across a broad range of parameter configurations. Moreover, cooperative stability can alleviate the constraint of limited supply of a given subunit and makes complex abundance more responsive to unilateral upregulation of another subunit. We also conducted an in silico experiment to comprehensively characterize and compare four types of circuits that incorporate combinations of negative feedback control and cooperative stability in terms of eight systems characteristics pertaining to optimality, robustness and controllability. Intriguingly, though individual circuits prevailed for distinct characteristics, the system with cooperative stability alone achieved the most balanced performance across all characteristics. Our study provides theoretical justification for the contribution of cooperative stability to natural biological systems and represents a guideline for designing synthetic complex formation systems with desirable characteristics.
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Affiliation(s)
- Kuan-Lun Hsu
- Institute of Molecular Biology, Academia Sinica, 128 Academia Road, Section 2, Taipei, Taiwan
| | - Hsueh-Chi S Yen
- Institute of Molecular Biology, Academia Sinica, 128 Academia Road, Section 2, Taipei, Taiwan
| | - Chen-Hsiang Yeang
- Institute of Statistical Science, Academia Sinica, 128 Academia Road, Section 2, Taipei, Taiwan.
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13
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Jones RD, Qian Y, Ilia K, Wang B, Laub MT, Del Vecchio D, Weiss R. Robust and tunable signal processing in mammalian cells via engineered covalent modification cycles. Nat Commun 2022; 13:1720. [PMID: 35361767 PMCID: PMC8971529 DOI: 10.1038/s41467-022-29338-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Accepted: 02/16/2022] [Indexed: 02/06/2023] Open
Abstract
Engineered signaling networks can impart cells with new functionalities useful for directing differentiation and actuating cellular therapies. For such applications, the engineered networks must be tunable, precisely regulate target gene expression, and be robust to perturbations within the complex context of mammalian cells. Here, we use bacterial two-component signaling proteins to develop synthetic phosphoregulation devices that exhibit these properties in mammalian cells. First, we engineer a synthetic covalent modification cycle based on kinase and phosphatase proteins derived from the bifunctional histidine kinase EnvZ, enabling analog tuning of gene expression via its response regulator OmpR. By regulating phosphatase expression with endogenous miRNAs, we demonstrate cell-type specific signaling responses and a new strategy for accurate cell type classification. Finally, we implement a tunable negative feedback controller via a small molecule-stabilized phosphatase, reducing output expression variance and mitigating the context-dependent effects of off-target regulation and resource competition. Our work lays the foundation for establishing tunable, precise, and robust control over cell behavior with synthetic signaling networks.
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Affiliation(s)
- Ross D Jones
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Yili Qian
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Katherine Ilia
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Benjamin Wang
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Michael T Laub
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Domitilla Del Vecchio
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
| | - Ron Weiss
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Electrical Engineering and Computer Science Department, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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14
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Gerhardt KP, Rao SD, Olson EJ, Igoshin OA, Tabor JJ. Independent control of mean and noise by convolution of gene expression distributions. Nat Commun 2021; 12:6957. [PMID: 34845228 PMCID: PMC8630168 DOI: 10.1038/s41467-021-27070-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 11/03/2021] [Indexed: 11/28/2022] Open
Abstract
Gene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from individual promoters. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer low and high noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.
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Affiliation(s)
- Karl P Gerhardt
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Satyajit D Rao
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Evan J Olson
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Oleg A Igoshin
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
- Department of Biosciences, Rice University, 6100 Main Street, Houston, TX, 77005, USA
- Center for Theoretical Biophysics, Rice University, 6100 Main Street, Houston, TX, 77005, USA
- Department of Chemistry, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Jeffrey J Tabor
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA.
- Department of Biosciences, Rice University, 6100 Main Street, Houston, TX, 77005, USA.
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15
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Vidiella B, Guillamon A, Sardanyés J, Maull V, Pla J, Conde N, Solé R. Engineering self-organized criticality in living cells. Nat Commun 2021; 12:4415. [PMID: 34285228 DOI: 10.1038/s41467-021-24695-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 06/22/2021] [Indexed: 02/06/2023] Open
Abstract
Complex dynamical fluctuations, from intracellular noise, brain dynamics or computer traffic display bursting dynamics consistent with a critical state between order and disorder. Living close to the critical point has adaptive advantages and it has been conjectured that evolution could select these critical states. Is this the case of living cells? A system can poise itself close to the critical point by means of the so-called self-organized criticality (SOC). In this paper we present an engineered gene network displaying SOC behaviour. This is achieved by exploiting the saturation of the proteolytic degradation machinery in E. coli cells by means of a negative feedback loop that reduces congestion. Our critical motif is built from a two-gene circuit, where SOC can be successfully implemented. The potential implications for both cellular dynamics and behaviour are discussed.
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16
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Abstract
Bacteria can be harnessed to synthesise high-value chemicals. A promising strategy for increasing productivity uses inducible control systems to switch metabolism from growth to chemical synthesis once a large population of cell factories are generated. However, use of expensive chemical inducers limits scalability of this approach for biotechnological applications. Switching using cheap nutrients is an appealing alternative, but their tightly regulated uptake and consumption again limits scalability. Here, using mathematical models of fatty acid uptake in E. coli as an exemplary case study, we unravel how the cell's native regulation and program of induction can be engineered to minimise inducer usage. We show that integrating positive feedback loops into the circuitry creates an irreversible metabolic switch, which, requiring only temporary induction, drastically reduces inducer usage. Our proposed switch should be widely applicable, irrespective of the product of interest, and brings closer the realization of scalable and sustainable microbial chemical production.
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Affiliation(s)
- Ahmad A Mannan
- Warwick Integrative Synthetic Biology Centre, School of Engineering, University of Warwick, Coventry, CV4 7AL, United Kingdom
| | - Declan G Bates
- Warwick Integrative Synthetic Biology Centre, School of Engineering, University of Warwick, Coventry, CV4 7AL, United Kingdom.
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17
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Tas H, Grozinger L, Stoof R, de Lorenzo V, Goñi-Moreno Á. Contextual dependencies expand the re-usability of genetic inverters. Nat Commun 2021; 12:355. [PMID: 33441561 PMCID: PMC7806840 DOI: 10.1038/s41467-020-20656-5] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2020] [Accepted: 12/02/2020] [Indexed: 01/29/2023] Open
Abstract
The implementation of Boolean logic circuits in cells have become a very active field within synthetic biology. Although these are mostly focussed on the genetic components alone, the context in which the circuit performs is crucial for its outcome. We characterise 20 genetic NOT logic gates in up to 7 bacterial-based contexts each, to generate 135 different functions. The contexts we focus on are combinations of four plasmid backbones and three hosts, two Escherichia coli and one Pseudomonas putida strains. Each gate shows seven different dynamic behaviours, depending on the context. That is, gates can be fine-tuned by changing only contextual parameters, thus improving the compatibility between gates. Finally, we analyse portability by measuring, scoring, and comparing gate performance across contexts. Rather than being a limitation, we argue that the effect of the genetic background on synthetic constructs expands functionality, and advocate for considering context as a fundamental design parameter.
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Affiliation(s)
- Huseyin Tas
- grid.428469.50000 0004 1794 1018Systems Biology Department, Centro Nacional de Biotecnologia-CSIC, Campus de Cantoblanco, Madrid, 28049 Spain
| | - Lewis Grozinger
- grid.1006.70000 0001 0462 7212School of Computing, Newcastle University, Newcastle Upon Tyne, NE4 5TG UK
| | - Ruud Stoof
- grid.1006.70000 0001 0462 7212School of Computing, Newcastle University, Newcastle Upon Tyne, NE4 5TG UK
| | - Victor de Lorenzo
- grid.428469.50000 0004 1794 1018Systems Biology Department, Centro Nacional de Biotecnologia-CSIC, Campus de Cantoblanco, Madrid, 28049 Spain
| | - Ángel Goñi-Moreno
- grid.1006.70000 0001 0462 7212School of Computing, Newcastle University, Newcastle Upon Tyne, NE4 5TG UK ,grid.419190.40000 0001 2300 669XCentro de Biotecnología y Genómica de Plantas (CBGP, UPM-INIA), Universidad Politénica de Madrid (UPM), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Campus de Montegancedo-UPM, 28223 Pozuelo de Alarcón, Madrid, Spain
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18
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Jones RD, Qian Y, Siciliano V, DiAndreth B, Huh J, Weiss R, Del Vecchio D. An endoribonuclease-based feedforward controller for decoupling resource-limited genetic modules in mammalian cells. Nat Commun 2020; 11:5690. [PMID: 33173034 PMCID: PMC7656454 DOI: 10.1038/s41467-020-19126-9] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 09/18/2020] [Indexed: 12/17/2022] Open
Abstract
Synthetic biology has the potential to bring forth advanced genetic devices for applications in healthcare and biotechnology. However, accurately predicting the behavior of engineered genetic devices remains difficult due to lack of modularity, wherein a device's output does not depend only on its intended inputs but also on its context. One contributor to lack of modularity is loading of transcriptional and translational resources, which can induce coupling among otherwise independently-regulated genes. Here, we quantify the effects of resource loading in engineered mammalian genetic systems and develop an endoribonuclease-based feedforward controller that can adapt the expression level of a gene of interest to significant resource loading in mammalian cells. Near-perfect adaptation to resource loads is facilitated by high production and catalytic rates of the endoribonuclease. Our design is portable across cell lines and enables predictable tuning of controller function. Ultimately, our controller is a general-purpose device for predictable, robust, and context-independent control of gene expression.
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Affiliation(s)
- Ross D Jones
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Yili Qian
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Velia Siciliano
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Instituto Italiano di Tecnologia, Napoli, 80125, Italy
| | - Breanna DiAndreth
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Jin Huh
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Ron Weiss
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
| | - Domitilla Del Vecchio
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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19
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Frei T, Cella F, Tedeschi F, Gutiérrez J, Stan GB, Khammash M, Siciliano V. Characterization and mitigation of gene expression burden in mammalian cells. Nat Commun 2020; 11:4641. [PMID: 32934213 PMCID: PMC7492461 DOI: 10.1038/s41467-020-18392-x] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2020] [Accepted: 08/18/2020] [Indexed: 12/19/2022] Open
Abstract
Despite recent advances in circuit engineering, the design of genetic networks in mammalian cells is still painstakingly slow and fraught with inexplicable failures. Here, we demonstrate that transiently expressed genes in mammalian cells compete for limited transcriptional and translational resources. This competition results in the coupling of otherwise independent exogenous and endogenous genes, creating a divergence between intended and actual function. Guided by a resource-aware mathematical model, we identify and engineer natural and synthetic miRNA-based incoherent feedforward loop (iFFL) circuits that mitigate gene expression burden. The implementation of these circuits features the use of endogenous miRNAs as elementary components of the engineered iFFL device, a versatile hybrid design that allows burden mitigation to be achieved across different cell-lines with minimal resource requirements. This study establishes the foundations for context-aware prediction and improvement of in vivo synthetic circuit performance, paving the way towards more rational synthetic construct design in mammalian cells.
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Affiliation(s)
- Timothy Frei
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
| | - Federica Cella
- Istituto Italiano di Tecnologia-IIT, Largo Barsanti e Matteucci, Naples, 80125, Italy
- University of Genoa, Genoa, 16132, Italy
| | - Fabiana Tedeschi
- Istituto Italiano di Tecnologia-IIT, Largo Barsanti e Matteucci, Naples, 80125, Italy
| | - Joaquín Gutiérrez
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
| | - Guy-Bart Stan
- Department of Bioengineering and Centre for Synthetic Biology, Imperial College London, London, SW7 2AZ, UK
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, Basel, 4058, Switzerland.
| | - Velia Siciliano
- Istituto Italiano di Tecnologia-IIT, Largo Barsanti e Matteucci, Naples, 80125, Italy.
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20
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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21
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Bartoli V, Meaker GA, di Bernardo M, Gorochowski TE. Tunable genetic devices through simultaneous control of transcription and translation. Nat Commun 2020; 11:2095. [PMID: 32350250 PMCID: PMC7190835 DOI: 10.1038/s41467-020-15653-7] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 03/20/2020] [Indexed: 02/07/2023] Open
Abstract
Synthetic genetic circuits allow us to modify the behavior of living cells. However, changes in environmental conditions and unforeseen interactions with the host cell can cause deviations from a desired function, resulting in the need for time-consuming reassembly to fix these issues. Here, we use a regulatory motif that controls transcription and translation to create genetic devices whose response functions can be dynamically tuned. This allows us, after construction, to shift the on and off states of a sensor by 4.5- and 28-fold, respectively, and modify genetic NOT and NOR logic gates to allow their transitions between states to be varied over a >6-fold range. In all cases, tuning leads to trade-offs in the fold-change and the ability to distinguish cellular states. This work lays the foundation for adaptive genetic circuits that can be tuned after their physical assembly to maintain functionality across diverse environments and design contexts.
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Affiliation(s)
- Vittorio Bartoli
- BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, UK
- Department of Engineering Mathematics, University of Bristol, Woodland Road, Bristol, UK
| | - Grace A Meaker
- School of Biosciences, Cardiff University, Museum Avenue, Cardiff, UK
| | - Mario di Bernardo
- BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, UK
- Department of Engineering Mathematics, University of Bristol, Woodland Road, Bristol, UK
- Department of Electrical Engineering and Information Technology, University of Naples Federico II, Via Claudio 21, Napoli, Italy
| | - Thomas E Gorochowski
- BrisSynBio, University of Bristol, Life Sciences Building, Tyndall Avenue, Bristol, UK.
- School of Biological Sciences, University of Bristol, Tyndall Avenue, Bristol, UK.
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22
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Fontana J, Dong C, Kiattisewee C, Chavali VP, Tickman BI, Carothers JM, Zalatan JG. Effective CRISPRa-mediated control of gene expression in bacteria must overcome strict target site requirements. Nat Commun 2020; 11:1618. [PMID: 32238808 PMCID: PMC7113249 DOI: 10.1038/s41467-020-15454-y] [Citation(s) in RCA: 54] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 03/04/2020] [Indexed: 11/09/2022] Open
Abstract
In bacterial systems, CRISPR-Cas transcriptional activation (CRISPRa) has the potential to dramatically expand our ability to regulate gene expression, but we lack predictive rules for designing effective gRNA target sites. Here, we identify multiple features of bacterial promoters that impose stringent requirements on CRISPRa target sites. Notably, we observe narrow, 2-4 base windows of effective sites with a periodicity corresponding to one helical turn of DNA, spanning ~40 bases and centered ~80 bases upstream of the TSS. However, we also identify two features suggesting the potential for broad scope: CRISPRa is effective at a broad range of σ70-family promoters, and an expanded PAM dCas9 allows the activation of promoters that cannot be activated by S. pyogenes dCas9. These results provide a roadmap for future engineering efforts to further expand and generalize the scope of bacterial CRISPRa.
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Affiliation(s)
- Jason Fontana
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, 98195, WA, USA
| | - Chen Dong
- Department of Chemistry, University of Washington, Seattle, 98195, WA, USA
| | - Cholpisit Kiattisewee
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, 98195, WA, USA
| | - Venkata P Chavali
- Department of Chemical Engineering, University of Washington, Seattle, 98195, WA, USA
| | - Benjamin I Tickman
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, 98195, WA, USA
| | - James M Carothers
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, 98195, WA, USA.
- Department of Chemical Engineering, University of Washington, Seattle, 98195, WA, USA.
- Center for Synthetic Biology, University of Washington, Seattle, 98195, WA, USA.
| | - Jesse G Zalatan
- Department of Chemistry, University of Washington, Seattle, 98195, WA, USA.
- Department of Chemical Engineering, University of Washington, Seattle, 98195, WA, USA.
- Center for Synthetic Biology, University of Washington, Seattle, 98195, WA, USA.
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23
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Hudson AJ, Wieden HJ. Rapid generation of sequence-diverse terminator libraries and their parameterization using quantitative Term-Seq. Synth Biol (Oxf) 2019; 4:ysz026. [PMID: 32995547 PMCID: PMC7445774 DOI: 10.1093/synbio/ysz026] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Accepted: 10/03/2019] [Indexed: 01/09/2023] Open
Abstract
Synthetic biology and the rational design and construction of biological devices require vast numbers of characterized biological parts, as well as reliable design tools to build increasingly complex, multigene architectures. Design principles for intrinsic terminators have been established; however, additional sequence-structure studies are needed to refine parameters for termination-based genetic devices. We report a rapid single-pot method to generate libraries of thousands of randomized bidirectional intrinsic terminators and a modified quantitative Term-Seq (qTerm-Seq) method to simultaneously identify terminator sequences and measure their termination efficiencies (TEs). Using qTerm-Seq, we characterize hundreds of additional strong terminators (TE > 90%) with some terminators reducing transcription read-through by up to 1000-fold in Escherichia coli. Our terminator library and qTerm-Seq pipeline constitute a flexible platform enabling identification of terminator parts that can achieve transcription termination not only over a desired range but also to investigate their sequence-structure features, including for specific genetic and application contexts beyond the common in vivo systems such as E. coli.
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Affiliation(s)
- Andrew J Hudson
- Alberta RNA Research and Training Institute (ARRTI), University of Lethbridge, Lethbridge, Alberta, Canada.,Department of Biological Sciences, University of Lethbridge, Lethbridge, Alberta, Canada
| | - Hans-Joachim Wieden
- Alberta RNA Research and Training Institute (ARRTI), University of Lethbridge, Lethbridge, Alberta, Canada.,Department of Chemistry and Biochemistry, University of Lethbridge, Lethbridge, Alberta, Canada
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24
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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: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [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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25
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Chassin H, Müller M, Tigges M, Scheller L, Lang M, Fussenegger M. A modular degron library for synthetic circuits in mammalian cells. Nat Commun 2019; 10:2013. [PMID: 31043592 PMCID: PMC6494899 DOI: 10.1038/s41467-019-09974-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Accepted: 04/04/2019] [Indexed: 01/26/2023] Open
Abstract
Tight control over protein degradation is a fundamental requirement for cells to respond rapidly to various stimuli and adapt to a fluctuating environment. Here we develop a versatile, easy-to-handle library of destabilizing tags (degrons) for the precise regulation of protein expression profiles in mammalian cells by modulating target protein half-lives in a predictable manner. Using the well-established tetracycline gene-regulation system as a model, we show that the dynamics of protein expression can be tuned by fusing appropriate degron tags to gene regulators. Next, we apply this degron library to tune a synthetic pulse-generating circuit in mammalian cells. With this toolbox we establish a set of pulse generators with tailored pulse lengths and magnitudes of protein expression. This methodology will prove useful in the functional roles of essential proteins, fine-tuning of gene-expression systems, and enabling a higher complexity in the design of synthetic biological systems in mammalian cells.
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Affiliation(s)
- Hélène Chassin
- 0000 0001 2156 2780grid.5801.cDepartment of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, CH-4058 Basel, Switzerland
| | - Marius Müller
- Cilag AG, Hochstrasse 201, CH-8200 Schaffhausen, Switzerland
| | - Marcel Tigges
- Cilag AG, Hochstrasse 201, CH-8200 Schaffhausen, Switzerland
| | - Leo Scheller
- 0000 0001 2156 2780grid.5801.cDepartment of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, CH-4058 Basel, Switzerland
| | - Moritz Lang
- 0000000404312247grid.33565.36Institute of Science and Technology Austria, A-3400 Klosterneuburg, Austria
| | - Martin Fussenegger
- 0000 0001 2156 2780grid.5801.cDepartment of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, CH-4058 Basel, Switzerland ,0000 0004 1937 0642grid.6612.3Faculty of Science, University of Basel, Mattenstrasse 26, CH-4058 Basel, Switzerland
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