1
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Caliendo F, Vitu E, Wang J, Kuo SH, Sandt H, Enghuus CN, Tordoff J, Estrada N, Collins JJ, Weiss R. Customizable gene sensing and response without altering endogenous coding sequences. Nat Chem Biol 2024:10.1038/s41589-024-01733-y. [PMID: 39266721 DOI: 10.1038/s41589-024-01733-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 08/20/2024] [Indexed: 09/14/2024]
Abstract
Synthetic biology aims to modify cellular behaviors by implementing genetic circuits that respond to changes in cell state. Integrating genetic biosensors into endogenous gene coding sequences using clustered regularly interspaced short palindromic repeats and Cas9 enables interrogation of gene expression dynamics in the appropriate chromosomal context. However, embedding a biosensor into a gene coding sequence may unpredictably alter endogenous gene regulation. To address this challenge, we developed an approach to integrate genetic biosensors into endogenous genes without modifying their coding sequence by inserting into their terminator region single-guide RNAs that activate downstream circuits. Sensor dosage responses can be fine-tuned and predicted through a mathematical model. We engineered a cell stress sensor and actuator in CHO-K1 cells that conditionally activates antiapoptotic protein BCL-2 through a downstream circuit, thereby increasing cell survival under stress conditions. Our gene sensor and actuator platform has potential use for a wide range of applications that include biomanufacturing, cell fate control and cell-based therapeutics.
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Affiliation(s)
- Fabio Caliendo
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elvira Vitu
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Junmin Wang
- Bioinformatics Graduate Program, Boston University, Boston, MA, USA
| | - Shuo-Hsiu Kuo
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hayden Sandt
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Casper Nørskov Enghuus
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jesse Tordoff
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Neslly Estrada
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - James J Collins
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA
- Institute for Medical Engineering & Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ron Weiss
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.
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2
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Zhang K, Shen J, He G, Sun Y, Ling H, Zha H, Li H, Zhang J. A Transformative Topological Representation for Link Modeling, Prediction and Cross-Domain Network Analysis. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2024; 46:6126-6138. [PMID: 38502624 DOI: 10.1109/tpami.2024.3378729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/21/2024]
Abstract
Many complex social, biological, or physical systems are characterized as networks, and recovering the missing links of a network could shed important lights on its structure and dynamics. A good topological representation is crucial to accurate link modeling and prediction, yet how to account for the kaleidoscopic changes in link formation patterns remains a challenge, especially for analysis in cross-domain studies. We propose a new link representation scheme by projecting the local environment of a link into a "dipole plane", where neighboring nodes of the link are positioned via their relative proximity to the two anchors of the link, like a dipole. By doing this, complex and discrete topology arising from link formation is turned to differentiable point-cloud distribution, opening up new possibilities for topological feature-engineering with desired expressiveness, interpretability and generalization. Our approach has comparable or even superior results against state-of-the-art GNNs, meanwhile with a model up to hundreds of times smaller and running much faster. Furthermore, it provides a universal platform to systematically profile, study, and compare link-patterns from miscellaneous real-world networks. This allows building a global link-pattern atlas, based on which we have uncovered interesting common patterns of link formation, i.e., the bridge-style, the radiation-style, and the community-style across a wide collection of networks with highly different nature.
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3
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Rabinowitch I, Colón-Ramos DA, Krieg M. Understanding neural circuit function through synaptic engineering. Nat Rev Neurosci 2024; 25:131-139. [PMID: 38172626 DOI: 10.1038/s41583-023-00777-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/29/2023] [Indexed: 01/05/2024]
Abstract
Synapses are a key component of neural circuits, facilitating rapid and specific signalling between neurons. Synaptic engineering - the synthetic insertion of new synaptic connections into in vivo neural circuits - is an emerging approach for neural circuit interrogation. This approach is especially powerful for establishing causality in neural circuit structure-function relationships, for emulating synaptic plasticity and for exploring novel patterns of circuit connectivity. Contrary to other approaches for neural circuit manipulation, synaptic engineering targets specific connections between neurons and functions autonomously with no user-controlled external activation. Synaptic engineering has been successfully implemented in several systems and in different forms, including electrical synapses constructed from ectopically expressed connexin gap junction proteins, synthetic optical synapses composed of presynaptic photon-emitting luciferase coupled with postsynaptic light-gated channels, and artificial neuropeptide signalling pathways. This Perspective describes these different methods and how they have been applied, and examines how the field may advance.
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Affiliation(s)
- Ithai Rabinowitch
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Daniel A Colón-Ramos
- Wu Tsai Institute, Department of Neuroscience and Department of Cell Biology, Yale University School of Medicine, New Haven, CT, USA
| | - Michael Krieg
- ICFO - Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Castelldefels, Spain
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4
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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: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [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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5
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Yang X, Rocks JW, Jiang K, Walters AJ, Rai K, Liu J, Nguyen J, Olson SD, Mehta P, Collins JJ, Daringer NM, Bashor CJ. Engineering synthetic phosphorylation signaling networks in human cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.11.557100. [PMID: 37745327 PMCID: PMC10515791 DOI: 10.1101/2023.09.11.557100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Protein phosphorylation signaling networks play a central role in how cells sense and respond to their environment. Here, we describe the engineering of artificial phosphorylation networks in which "push-pull" motifs-reversible enzymatic phosphorylation cycles consisting of opposing kinase and phosphatase activities-are assembled from modular protein domain parts and then wired together to create synthetic phosphorylation circuits in human cells. We demonstrate that the composability of our design scheme enables model-guided tuning of circuit function and the ability to make diverse network connections; synthetic phosphorylation circuits can be coupled to upstream cell surface receptors to enable fast-timescale sensing of extracellular ligands, while downstream connections can regulate gene expression. We leverage these capabilities to engineer cell-based cytokine controllers that dynamically sense and suppress activated T cells. Our work introduces a generalizable approach for designing and building phosphorylation signaling circuits that enable user-defined sense-and-respond function for diverse biosensing and therapeutic applications.
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Affiliation(s)
- Xiaoyu Yang
- Department of Bioengineering, Rice University; Houston, TX 77030, USA
- Graduate Program in Systems, Synthetic and Physical Biology, Rice University; Houston, TX 77030, USA
| | - Jason W. Rocks
- Department of Physics, Boston University; Boston, MA 02215, USA
| | - Kaiyi Jiang
- Department of Bioengineering, Rice University; Houston, TX 77030, USA
| | - Andrew J. Walters
- Department of Bioengineering, Rice University; Houston, TX 77030, USA
- Graduate Program in Bioengineering, Rice University; Houston, TX 77030, USA
- Department of Pediatric Surgery, McGovern Medical School, University of Texas Health Science Center at Houston; Houston, TX 77030, USA
| | - Kshitij Rai
- Graduate Program in Systems, Synthetic and Physical Biology, Rice University; Houston, TX 77030, USA
| | - Jing Liu
- Department of Bioengineering, Rice University; Houston, TX 77030, USA
| | - Jason Nguyen
- Department of Bioengineering, Rice University; Houston, TX 77030, USA
| | - Scott D. Olson
- Department of Pediatric Surgery, McGovern Medical School, University of Texas Health Science Center at Houston; Houston, TX 77030, USA
| | - Pankaj Mehta
- Department of Physics, Boston University; Boston, MA 02215, USA
- Biological Design Center, Boston University; Boston, MA 02215, USA
- Faculty of Computing and Data Science, Boston University; Boston, MA 02215, USA
| | - James J. Collins
- Institute for Medical Engineering and Science, Department of Biological Engineering, and Synthetic Biology Center, Massachusetts Institute of Technology; Cambridge, MA 02139, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02142, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University; Boston, MA 02115, USA
| | - Nichole M Daringer
- Department of Biomedical Engineering, Rowan University; Glassboro, NJ 08028, USA
| | - Caleb J. Bashor
- Department of Bioengineering, Rice University; Houston, TX 77030, USA
- Department of Biosciences, Rice University; Houston, TX 77030, USA
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6
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Zhu I, Piraner DI, Roybal KT. Synthesizing a Smarter CAR T Cell: Advanced Engineering of T-cell Immunotherapies. Cancer Immunol Res 2023; 11:1030-1043. [PMID: 37429007 PMCID: PMC10527511 DOI: 10.1158/2326-6066.cir-22-0962] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2022] [Revised: 03/15/2023] [Accepted: 06/02/2023] [Indexed: 07/12/2023]
Abstract
The immune system includes an array of specialized cells that keep us healthy by responding to pathogenic cues. Investigations into the mechanisms behind immune cell behavior have led to the development of powerful immunotherapies, including chimeric-antigen receptor (CAR) T cells. Although CAR T cells have demonstrated efficacy in treating blood cancers, issues regarding their safety and potency have hindered the use of immunotherapies in a wider spectrum of diseases. Efforts to integrate developments in synthetic biology into immunotherapy have led to several advancements with the potential to expand the range of treatable diseases, fine-tune the desired immune response, and improve therapeutic cell potency. Here, we examine current synthetic biology advances that aim to improve on existing technologies and discuss the promise of the next generation of engineered immune cell therapies.
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Affiliation(s)
- Iowis Zhu
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94143, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA 94143, USA
- These authors contributed equally
| | - Dan I. Piraner
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94143, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA 94143, USA
- These authors contributed equally
| | - Kole T. Roybal
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA 94143, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA 94143, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA 94158, USA 8Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
- Gladstone UCSF Institute for Genetic Immunology, San Francisco, CA 94107, USA
- UCSF Cell Design Institute, San Francisco, CA 94158, USA
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7
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Zhang C, Liu H, Li X, Xu F, Li Z. Modularized synthetic biology enabled intelligent biosensors. Trends Biotechnol 2023; 41:1055-1065. [PMID: 36967259 DOI: 10.1016/j.tibtech.2023.03.005] [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: 12/29/2022] [Revised: 02/27/2023] [Accepted: 03/06/2023] [Indexed: 03/29/2023]
Abstract
Biosensors that sense the concentration of a specified target and produce a specific signal output have become important technology for biological analysis. Recently, intelligent biosensors have received great interest due to their adaptability to meet sophisticated demands. Advances in developing standard modules and carriers in synthetic biology have shed light on intelligent biosensors that can implement advanced analytical processing to better accommodate practical applications. This review focuses on intelligent synthetic biology-enabled biosensors (SBBs). First, we illustrate recent progress in intelligent SBBs with the capability of computation, memory storage, and self-calibration. Then, we discuss emerging applications of SBBs in point-of-care testing (POCT) and wearable monitoring. Finally, future perspectives on intelligent SBBs are proposed.
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Affiliation(s)
- Chao Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R. China
| | - Hao Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R. China
| | - Xiujun Li
- Department of Chemistry and Biochemistry, University of Texas at El Paso, 500 West University Ave, El Paso, TX 79968, USA
| | - Feng Xu
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R. China.
| | - Zedong Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, P.R. China; Bioinspired Engineering and Biomechanics Center (BEBC), Xi'an Jiaotong University, Xi'an 710049, P.R. China; TFX Group-Xi'an Jiaotong University Institute of Life Health, Xi'an 710049, P.R. China.
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8
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Gyorgy A, Menezes A, Arcak M. A blueprint for a synthetic genetic feedback optimizer. Nat Commun 2023; 14:2554. [PMID: 37137895 PMCID: PMC10156725 DOI: 10.1038/s41467-023-37903-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 04/05/2023] [Indexed: 05/05/2023] Open
Abstract
Biomolecular control enables leveraging cells as biomanufacturing factories. Despite recent advancements, we currently lack genetically encoded modules that can be deployed to dynamically fine-tune and optimize cellular performance. Here, we address this shortcoming by presenting the blueprint of a genetic feedback module to optimize a broadly defined performance metric by adjusting the production and decay rate of a (set of) regulator species. We demonstrate that the optimizer can be implemented by combining available synthetic biology parts and components, and that it can be readily integrated with existing pathways and genetically encoded biosensors to ensure its successful deployment in a variety of settings. We further illustrate that the optimizer successfully locates and tracks the optimum in diverse contexts when relying on mass action kinetics-based dynamics and parameter values typical in Escherichia coli.
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Affiliation(s)
- Andras Gyorgy
- Division of Engineering, New York University Abu Dhabi, Abu Dhabi, UAE.
| | - Amor Menezes
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA
| | - Murat Arcak
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
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9
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Ferreira SS, Anderson CE, Antunes MS. A logical way to reprogram plants. Biochem Biophys Res Commun 2023; 654:80-86. [PMID: 36898227 DOI: 10.1016/j.bbrc.2023.02.080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 02/27/2023] [Indexed: 03/06/2023]
Abstract
Living cells constantly monitor their external and internal environments for changing conditions, stresses or developmental cues. Networks of genetically encoded components sense and process these signals following pre-defined rules in such a way that specific combinations of the presence or absence of certain signals activate suitable responses. Many biological signal integration mechanisms approximate Boolean logic operations, whereby presence or absence of signals are computed as variables with values described as either true or false, respectively. Boolean logic gates are commonly used in algebra and in computer sciences, and have long been recognized as useful information processing devices in electronic circuits. In these circuits, logic gates integrate multiple input values and produce an output signal according to pre-defined Boolean logic operations. Recent implementation of these logic operations using genetic components to process information in living cells has allowed genetic circuits to enable novel traits with decision-making capabilities. Although several literature reports describe the design and use of these logic gates to introduce new functions in bacterial, yeast and mammalian cells, similar approaches in plants remain scarce, likely due to challenges posed by the complexity of plants and the lack of some technological advances, e.g., species-independent genetic transformation. In this mini review, we have surveyed recent reports describing synthetic genetic Boolean logic operators in plants and the different gate architectures used. We also briefly discuss the potential of deploying these genetic devices in plants to bring to fruition a new generation of resilient crops and improved biomanufacturing platforms.
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Affiliation(s)
- Savio S Ferreira
- Department of Biological Sciences, University of North Texas, Denton, TX, 76203, USA; BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA.
| | - Charles E Anderson
- Department of Biological Sciences, University of North Texas, Denton, TX, 76203, USA; BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA.
| | - Mauricio S Antunes
- Department of Biological Sciences, University of North Texas, Denton, TX, 76203, USA; BioDiscovery Institute, University of North Texas, Denton, TX, 76203, USA.
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10
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Ji J, Hossain MS, Krueger EN, Zhang Z, Nangia S, Carpentier B, Martel M, Nangia S, Mozhdehi D. Lipidation Alters the Structure and Hydration of Myristoylated Intrinsically Disordered Proteins. Biomacromolecules 2023; 24:1244-1257. [PMID: 36757021 PMCID: PMC10017028 DOI: 10.1021/acs.biomac.2c01309] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/25/2023] [Indexed: 02/10/2023]
Abstract
Lipidated proteins are an emerging class of hybrid biomaterials that can integrate the functional capabilities of proteins into precisely engineered nano-biomaterials with potential applications in biotechnology, nanoscience, and biomedical engineering. For instance, fatty-acid-modified elastin-like polypeptides (FAMEs) combine the hierarchical assembly of lipids with the thermoresponsive character of elastin-like polypeptides (ELPs) to form nanocarriers with emergent temperature-dependent structural (shape or size) characteristics. Here, we report the biophysical underpinnings of thermoresponsive behavior of FAMEs using computational nanoscopy, spectroscopy, scattering, and microscopy. This integrated approach revealed that temperature and molecular syntax alter the structure, contact, and hydration of lipid, lipidation site, and protein, aligning with the changes in the nanomorphology of FAMEs. These findings enable a better understanding of the biophysical consequence of lipidation in biology and the rational design of the biomaterials and therapeutics that rival the exquisite hierarchy and capabilities of biological systems.
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Affiliation(s)
- Jingjing Ji
- Department
of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York 13244, United States
| | - Md Shahadat Hossain
- Department
of Chemistry, Syracuse University, Syracuse, New York 13244, United States
| | - Emily N. Krueger
- Department
of Chemistry, Syracuse University, Syracuse, New York 13244, United States
| | - Zhe Zhang
- Department
of Chemistry, Syracuse University, Syracuse, New York 13244, United States
| | - Shivangi Nangia
- Department
of Chemistry, University of Hartford, West Hartford, Connecticut 06117, United States
| | - Britnie Carpentier
- Department
of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York 13244, United States
| | - Mae Martel
- Department
of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York 13244, United States
| | - Shikha Nangia
- Department
of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York 13244, United States
- BioInspired
Syracuse: Institute for Material and Living Systems, Syracuse University, Syracuse, New York 13244, United States
| | - Davoud Mozhdehi
- Department
of Biomedical and Chemical Engineering, Syracuse University, Syracuse, New York 13244, United States
- Department
of Chemistry, Syracuse University, Syracuse, New York 13244, United States
- BioInspired
Syracuse: Institute for Material and Living Systems, Syracuse University, Syracuse, New York 13244, United States
- Department
of Biology, Syracuse University, Syracuse, New York 13244, United States
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11
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Nieves M, Buschiazzo A, Trajtenberg F. Structural features of sensory two component systems: a synthetic biology perspective. Biochem J 2023; 480:127-140. [PMID: 36688908 DOI: 10.1042/bcj20210798] [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: 10/13/2022] [Revised: 01/05/2023] [Accepted: 01/06/2023] [Indexed: 01/24/2023]
Abstract
All living organisms include a set of signaling devices that confer the ability to dynamically perceive and adapt to the fluctuating environment. Two-component systems are part of this sensory machinery that regulates the execution of different genetic and/or biochemical programs in response to specific physical or chemical signals. In the last two decades, there has been tremendous progress in our molecular understanding on how signals are detected, the allosteric mechanisms that control intramolecular information transmission and the specificity determinants that guarantee correct wiring. All this information is starting to be exploited in the development of new synthetic networks. Connecting multiple molecular players, analogous to programming lines of code, can provide the resources to build new sophisticated biocomputing systems. The Synthetic Biology field is starting to revolutionize several scientific fields, such as biomedicine and agriculture, propelling the development of new solutions. Expanding the spectrum of available nanodevices in the toolbox is key to unleash its full potential. This review aims to discuss, from a structural perspective, how to take advantage of the vast array of sensor and effector protein modules involved in two-component systems for the construction of new synthetic circuits.
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Affiliation(s)
- Marcos Nieves
- Laboratory of Molecular and Structural Microbiology, Institut Pasteur de Montevideo, Montevideo, Uruguay
| | - Alejandro Buschiazzo
- Laboratory of Molecular and Structural Microbiology, Institut Pasteur de Montevideo, Montevideo, Uruguay
- Département de Microbiologie, Institut Pasteur, Paris, France
| | - Felipe Trajtenberg
- Laboratory of Molecular and Structural Microbiology, Institut Pasteur de Montevideo, Montevideo, Uruguay
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12
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Wang S, Garcia-Ojalvo J, Elowitz MB. Periodic spatial patterning with a single morphogen. Cell Syst 2022; 13:1033-1047.e7. [PMID: 36435178 DOI: 10.1016/j.cels.2022.11.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Revised: 07/13/2022] [Accepted: 11/02/2022] [Indexed: 11/26/2022]
Abstract
During multicellular development, periodic spatial patterning systems generate repetitive structures, such as digits, vertebrae, and teeth. Turing patterning provides a foundational paradigm for understanding such systems. The simplest Turing systems are believed to require at least two morphogens to generate periodic patterns. Here, using mathematical modeling, we show that a simpler circuit, including only a single diffusible morphogen, is sufficient to generate long-range, spatially periodic patterns that propagate outward from transient initiating perturbations and remain stable after the perturbation is removed. Furthermore, an additional bistable intracellular feedback or operation on a growing cell lattice can make patterning robust to noise. Together, these results show that a single morphogen can be sufficient for robust spatial pattern formation and should provide a foundation for engineering pattern formation in the emerging field of synthetic developmental biology.
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Affiliation(s)
- Sheng Wang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Jordi Garcia-Ojalvo
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Michael B Elowitz
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA; Howard Hughes Medical Institute, California Institute of Technology, Pasadena, CA 91125, USA.
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13
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Brophy JAN, Magallon KJ, Duan L, Zhong V, Ramachandran P, Kniazev K, Dinneny JR. Synthetic genetic circuits as a means of reprogramming plant roots. Science 2022; 377:747-751. [PMID: 35951698 DOI: 10.1126/science.abo4326] [Citation(s) in RCA: 58] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
The shape of a plant's root system influences its ability to reach essential nutrients in the soil and to acquire water during drought. Progress in engineering plant roots to optimize water and nutrient acquisition has been limited by our capacity to design and build genetic programs that alter root growth in a predictable manner. We developed a collection of synthetic transcriptional regulators for plants that can be compiled to create genetic circuits. These circuits control gene expression by performing Boolean logic operations and can be used to predictably alter root structure. This work demonstrates the potential of synthetic genetic circuits to control gene expression across tissues and reprogram plant growth.
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Affiliation(s)
- Jennifer A N Brophy
- Department of Biology, Stanford University, Stanford, CA, USA.,Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | - Lina Duan
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Vivian Zhong
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | | | - Kiril Kniazev
- Department of Biology, Stanford University, Stanford, CA, USA
| | - José R Dinneny
- Department of Biology, Stanford University, Stanford, CA, USA
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14
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Buecherl L, Myers CJ. Engineering genetic circuits: advancements in genetic design automation tools and standards for synthetic biology. Curr Opin Microbiol 2022; 68:102155. [PMID: 35588683 DOI: 10.1016/j.mib.2022.102155] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 04/08/2022] [Accepted: 04/11/2022] [Indexed: 01/23/2023]
Abstract
Synthetic biology (SynBio) is a field at the intersection of biology and engineering. Inspired by engineering principles, researchers use defined parts to build functionally defined biological circuits. Genetic design automation (GDA) allows scientists to design, model, and analyze their genetic circuits in silico before building them in the lab, saving time, and resources in the process. Establishing SynBio's future is dependent on GDA, since the computational approach opens the field to a broad, interdisciplinary community. However, challenges with part libraries, standards, and software tools are currently stalling progress in the field. This review first covers recent advancements in GDA, followed by an assessment of the challenges ahead, and a proposed automated genetic design workflow for the future.
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Affiliation(s)
- Lukas Buecherl
- Biomedical Engineering Program, University of Colorado Boulder, 1111 Engineering Drive, Boulder, 80309 CO, United States
| | - Chris J Myers
- Department of Electrical, Computer, and Energy Engineering, University of Colorado Boulder, 425 UCB, Boulder, 80309 CO, United States.
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Kretschmer S, Kortemme T. Advances in the Computational Design of Small-Molecule-Controlled Protein-Based Circuits for Synthetic Biology. PROCEEDINGS OF THE IEEE. INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS 2022; 110:659-674. [PMID: 36531560 PMCID: PMC9754107 DOI: 10.1109/jproc.2022.3157898] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Synthetic biology approaches living systems with an engineering perspective and promises to deliver solutions to global challenges in healthcare and sustainability. A critical component is the design of biomolecular circuits with programmable input-output behaviors. Such circuits typically rely on a sensor module that recognizes molecular inputs, which is coupled to a functional output via protein-level circuits or regulating the expression of a target gene. While gene expression outputs can be customized relatively easily by exchanging the target genes, sensing new inputs is a major limitation. There is a limited repertoire of sensors found in nature, and there are often difficulties with interfacing them with engineered circuits. Computational protein design could be a key enabling technology to address these challenges, as it allows for the engineering of modular and tunable sensors that can be tailored to the circuit's application. In this article, we review recent computational approaches to design protein-based sensors for small-molecule inputs with particular focus on those based on the widely used Rosetta software suite. Furthermore, we review mechanisms that have been harnessed to couple ligand inputs to functional outputs. Based on recent literature, we illustrate how the combination of protein design and synthetic biology enables new sensors for diverse applications ranging from biomedicine to metabolic engineering. We conclude with a perspective on how strategies to address frontiers in protein design and cellular circuit design may enable the next generation of sense-response networks, which may increasingly be assembled from de novo components to display diverse and engineerable input-output behaviors.
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Affiliation(s)
- Simon Kretschmer
- Department of Bioengineering and Therapeutic Sciences, University of California at San Francisco, San Francisco, CA 94158 USA, and affiliated with the California Quantitative Biosciences Institute (QBI) at UCSF, San Francisco, CA 94158 USA
| | - Tanja Kortemme
- Department of Bioengineering and Therapeutic Sciences, University of California at San Francisco, San Francisco, CA 94158 USA, and affiliated with the California Quantitative Biosciences Institute (QBI) at UCSF, San Francisco, CA 94158 USA
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Li ZJ, Zhang ZX, Xu Y, Shi TQ, Ye C, Sun XM, Huang H. CRISPR-Based Construction of a BL21 (DE3)-Derived Variant Strain Library to Rapidly Improve Recombinant Protein Production. ACS Synth Biol 2022; 11:343-352. [PMID: 34919397 DOI: 10.1021/acssynbio.1c00463] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Escherichia coli BL21 (DE3) is the most widely used host for recombinant protein expression. However, not every protein can be highly expressed in BL21 (DE3), so individual optimization strategies are often required for different proteins, which is time-consuming and difficult to apply rapidly for industrial production. Constructing more hosts is a good choice to enrich protein expression selection. The expression level of T7 RNAP is the core control node of the pET expression system, so regulating its expression level is an effective way of improving the production of difficult-to-express proteins. Various BL21 (DE3)-derived variant hosts with different translation levels of T7 RNAP could be obtained by changing the ribosomal binding site (RBS) sequences of T7 RNAP in a genome. Here, a BL21 (DE3)-derived variant strain library with different RBS sequences of T7 RNAP was constructed using a base editor and CRISPR-Cas9. Notably, the CRISPR-Cas9 system combined with degenerate primers enabled the construction of an RBS library with 87.5% of the theoretical coverage in single editing, which is more convenient and efficient than the use of a base editor. The expression level of a target gene in the variant strain library ranged from 28 to 220% of the parental strain. Furthermore, a high-throughput host-screening platform for recombinant protein production was constructed, which enabled us to obtain the best expression host for certain target proteins in only 3 days. As a proof of concept, the production of all eight difficult-to-express proteins was greatly improved, including autolytic protein, membrane proteins, antimicrobial peptides, and hardly soluble proteins. Among them, the expression of glucose dehydrogenase in the best host exhibited a 298-fold increase compared to the parental strain. This strategy is simple and effective, requires no advanced equipment, and can be carried out in any laboratory.
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Affiliation(s)
- Zi-Jia Li
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, 2 Xuelin Road, Qixia District, Nanjing 210023, People’s Republic of China
| | - Zi-Xu Zhang
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, 2 Xuelin Road, Qixia District, Nanjing 210023, People’s Republic of China
| | - Yan Xu
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, 2 Xuelin Road, Qixia District, Nanjing 210023, People’s Republic of China
| | - Tian-Qiong Shi
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, 2 Xuelin Road, Qixia District, Nanjing 210023, People’s Republic of China
| | - Chao Ye
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, 2 Xuelin Road, Qixia District, Nanjing 210023, People’s Republic of China
| | - Xiao-Man Sun
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, 2 Xuelin Road, Qixia District, Nanjing 210023, People’s Republic of China
| | - He Huang
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, 2 Xuelin Road, Qixia District, Nanjing 210023, People’s Republic of China
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, No. 30 South Puzhu Road, Nanjing 211816, People’s Republic of China
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de Nadal E, Posas F. OUP accepted manuscript. FEMS Yeast Res 2022; 22:6543702. [PMID: 35254447 PMCID: PMC8953452 DOI: 10.1093/femsyr/foac013] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 02/28/2022] [Accepted: 03/03/2022] [Indexed: 11/15/2022] Open
Affiliation(s)
- Eulàlia de Nadal
- Corresponding author: Institute for Research in Biomedicine (IRB Barcelona) Parc Científic de Barcelona c/ Baldiri Reixac, 10. 08028 Barcelona - Spain. E-mail:
| | - Francesc Posas
- Corresponding author: Institute for Research in Biomedicine (IRB Barcelona) Parc Científic de Barcelona c/ Baldiri Reixac, 10. 08028 Barcelona - Spain. E-mail:
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Rocca A, Kholodenko BN. Can Systems Biology Advance Clinical Precision Oncology? Cancers (Basel) 2021; 13:6312. [PMID: 34944932 PMCID: PMC8699328 DOI: 10.3390/cancers13246312] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2021] [Accepted: 12/10/2021] [Indexed: 12/13/2022] Open
Abstract
Precision oncology is perceived as a way forward to treat individual cancer patients. However, knowing particular cancer mutations is not enough for optimal therapeutic treatment, because cancer genotype-phenotype relationships are nonlinear and dynamic. Systems biology studies the biological processes at the systems' level, using an array of techniques, ranging from statistical methods to network reconstruction and analysis, to mathematical modeling. Its goal is to reconstruct the complex and often counterintuitive dynamic behavior of biological systems and quantitatively predict their responses to environmental perturbations. In this paper, we review the impact of systems biology on precision oncology. We show examples of how the analysis of signal transduction networks allows to dissect resistance to targeted therapies and inform the choice of combinations of targeted drugs based on tumor molecular alterations. Patient-specific biomarkers based on dynamical models of signaling networks can have a greater prognostic value than conventional biomarkers. These examples support systems biology models as valuable tools to advance clinical and translational oncological research.
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Affiliation(s)
- Andrea Rocca
- Hygiene and Public Health, Local Health Unit of Romagna, 47121 Forlì, Italy
| | - Boris N. Kholodenko
- Systems Biology Ireland, School of Medicine, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland
- Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, D04 V1W8 Dublin, Ireland
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT 06520, USA
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Synthetic Protein Circuits and Devices Based on Reversible Protein-Protein Interactions: An Overview. Life (Basel) 2021; 11:life11111171. [PMID: 34833047 PMCID: PMC8623019 DOI: 10.3390/life11111171] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/25/2021] [Accepted: 10/26/2021] [Indexed: 12/30/2022] Open
Abstract
Protein-protein interactions (PPIs) contribute to regulate many aspects of cell physiology and metabolism. Protein domains involved in PPIs are important building blocks for engineering genetic circuits through synthetic biology. These domains can be obtained from known proteins and rationally engineered to produce orthogonal scaffolds, or computationally designed de novo thanks to recent advances in structural biology and molecular dynamics prediction. Such circuits based on PPIs (or protein circuits) appear of particular interest, as they can directly affect transcriptional outputs, as well as induce behavioral/adaptational changes in cell metabolism, without the need for further protein synthesis. This last example was highlighted in recent works to enable the production of fast-responding circuits which can be exploited for biosensing and diagnostics. Notably, PPIs can also be engineered to develop new drugs able to bind specific intra- and extra-cellular targets. In this review, we summarize recent findings in the field of protein circuit design, with particular focus on the use of peptides as scaffolds to engineer these circuits.
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Billerbeck S. Synthetic biological toggle circuits that respond within seconds and teach us new biology. Synth Biol (Oxf) 2021; 6:ysab027. [PMID: 34522786 PMCID: PMC8434798 DOI: 10.1093/synbio/ysab027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 08/27/2021] [Indexed: 11/19/2022] Open
Affiliation(s)
- Sonja Billerbeck
- Molecular Microbiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Groningen, The Netherlands
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21
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Engineered protein-protein toggle network. Nat Methods 2021; 18:990. [PMID: 34480157 DOI: 10.1038/s41592-021-01269-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Kholodenko BN, Okada M. Reengineering protein-phosphorylation switches. Science 2021; 373:25-26. [PMID: 34210865 PMCID: PMC8327301 DOI: 10.1126/science.abj5028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
Phosphorylation circuits operate as logic gates that rapidly toggle a system between two stable states
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Affiliation(s)
- Boris N Kholodenko
- Systems Biology Ireland, School of Medicine and Medical Science, University College Dublin, Belfield, Dublin 4, Ireland.
- Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Ireland
- Department of Pharmacology, Yale University School of Medicine, New Haven, CT, USA
| | - Mariko Okada
- Institute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japan.
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