1
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Eisenhut P, Marx N, Borsi G, Papež M, Ruggeri C, Baumann M, Borth N. Manipulating gene expression levels in mammalian cell factories: An outline of synthetic molecular toolboxes to achieve multiplexed control. N Biotechnol 2024; 79:1-19. [PMID: 38040288 DOI: 10.1016/j.nbt.2023.11.003] [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: 10/02/2023] [Revised: 11/06/2023] [Accepted: 11/26/2023] [Indexed: 12/03/2023]
Abstract
Mammalian cells have developed dedicated molecular mechanisms to tightly control expression levels of their genes where the specific transcriptomic signature across all genes eventually determines the cell's phenotype. Modulating cellular phenotypes is of major interest to study their role in disease or to reprogram cells for the manufacturing of recombinant products, such as biopharmaceuticals. Cells of mammalian origin, for example Chinese hamster ovary (CHO) and Human embryonic kidney 293 (HEK293) cells, are most commonly employed to produce therapeutic proteins. Early genetic engineering approaches to alter their phenotype have often been attempted by "uncontrolled" overexpression or knock-down/-out of specific genetic factors. Many studies in the past years, however, highlight that rationally regulating and fine-tuning the strength of overexpression or knock-down to an optimum level, can adjust phenotypic traits with much more precision than such "uncontrolled" approaches. To this end, synthetic biology tools have been generated that enable (fine-)tunable and/or inducible control of gene expression. In this review, we discuss various molecular tools used in mammalian cell lines and group them by their mode of action: transcriptional, post-transcriptional, translational and post-translational regulation. We discuss the advantages and disadvantages of using these tools for each cell regulatory layer and with respect to cell line engineering approaches. This review highlights the plethora of synthetic toolboxes that could be employed, alone or in combination, to optimize cellular systems and eventually gain enhanced control over the cellular phenotype to equip mammalian cell factories with the tools required for efficient production of emerging, more difficult-to-express biologics formats.
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Affiliation(s)
- Peter Eisenhut
- Austrian Centre of Industrial Biotechnology (acib GmbH), Muthgasse 11, 1190 Vienna, Austria
| | - Nicolas Marx
- BOKU University of Natural Resources and Life Sciences, Institute of Animal Cell Technology and Systems Biology, Muthgasse 18, 1190 Vienna, Austria.
| | - Giulia Borsi
- BOKU University of Natural Resources and Life Sciences, Institute of Animal Cell Technology and Systems Biology, Muthgasse 18, 1190 Vienna, Austria
| | - Maja Papež
- Austrian Centre of Industrial Biotechnology (acib GmbH), Muthgasse 11, 1190 Vienna, Austria; BOKU University of Natural Resources and Life Sciences, Institute of Animal Cell Technology and Systems Biology, Muthgasse 18, 1190 Vienna, Austria
| | - Caterina Ruggeri
- BOKU University of Natural Resources and Life Sciences, Institute of Animal Cell Technology and Systems Biology, Muthgasse 18, 1190 Vienna, Austria
| | - Martina Baumann
- Austrian Centre of Industrial Biotechnology (acib GmbH), Muthgasse 11, 1190 Vienna, Austria
| | - Nicole Borth
- Austrian Centre of Industrial Biotechnology (acib GmbH), Muthgasse 11, 1190 Vienna, Austria; BOKU University of Natural Resources and Life Sciences, Institute of Animal Cell Technology and Systems Biology, Muthgasse 18, 1190 Vienna, Austria.
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2
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Bachhav B, de Rossi J, Llanos CD, Segatori L. Cell factory engineering: Challenges and opportunities for synthetic biology applications. Biotechnol Bioeng 2023; 120:2441-2459. [PMID: 36859509 PMCID: PMC10440303 DOI: 10.1002/bit.28365] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 02/14/2023] [Accepted: 02/27/2023] [Indexed: 03/03/2023]
Abstract
The production of high-quality recombinant proteins is critical to maintaining a continuous supply of biopharmaceuticals, such as therapeutic antibodies. Engineering mammalian cell factories presents a number of limitations typically associated with the proteotoxic stress induced upon aberrant accumulation of off-pathway protein folding intermediates, which eventually culminate in the induction of apoptosis. In this review, we will discuss advances in cell engineering and their applications at different hierarchical levels of control of the expression of recombinant proteins, from transcription and translational to posttranslational modifications and subcellular trafficking. We also highlight challenges and unique opportunities to apply modern synthetic biology tools to the design of programmable cell factories for improved biomanufacturing of therapeutic proteins.
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Affiliation(s)
- Bhagyashree Bachhav
- Department of Chemical and Biochemical Engineering, Rice University, Houston, United States
| | - Jacopo de Rossi
- Systems, Synthetic, and Physical Biology, Rice University, Houston, United States
| | - Carlos D. Llanos
- Systems, Synthetic, and Physical Biology, Rice University, Houston, United States
| | - Laura Segatori
- Department of Chemical and Biochemical Engineering, Rice University, Houston, United States
- Systems, Synthetic, and Physical Biology, Rice University, Houston, United States
- Department of Bioengineering, Rice University, Houston, United States
- Department of Biosciences, Rice University, Houston, United States
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3
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Merljak E, Malovrh B, Jerala R. Segmentation strategy of de novo designed four-helical bundles expands protein oligomerization modalities for cell regulation. Nat Commun 2023; 14:1995. [PMID: 37031229 PMCID: PMC10082849 DOI: 10.1038/s41467-023-37765-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/30/2023] [Indexed: 04/10/2023] Open
Abstract
Protein-protein interactions govern most biological processes. New protein assemblies can be introduced through the fusion of selected proteins with di/oligomerization domains, which interact specifically with their partners but not with other cellular proteins. While four-helical bundle proteins (4HB) have typically been assembled from two segments, each comprising two helices, here we show that they can be efficiently segmented in various ways, expanding the number of combinations generated from a single 4HB. We implement a segmentation strategy of 4HB to design two-, three-, or four-chain combinations for the recruitment of multiple protein components. Different segmentations provide new insight into the role of individual helices for 4HB assembly. We evaluate 4HB segmentations for potential use in mammalian cells for the reconstitution of a protein reporter, transcriptional activation, and inducible 4HB assembly. Furthermore, the implementation of trimerization is demonstrated as a modular chimeric antigen receptor for the recognition of multiple cancer antigens.
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Affiliation(s)
- Estera Merljak
- Department of Synthetic Biology and Immunology, National Institute of Chemistry, Ljubljana, Slovenia
- Interdisciplinary Doctoral Programme of Biomedicine, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Benjamin Malovrh
- Department of Synthetic Biology and Immunology, National Institute of Chemistry, Ljubljana, Slovenia
| | - Roman Jerala
- Department of Synthetic Biology and Immunology, National Institute of Chemistry, Ljubljana, Slovenia.
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4
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Lopez-Morales J, Vanella R, Kovacevic G, Santos MS, Nash MA. Titrating Avidity of Yeast-Displayed Proteins Using a Transcriptional Regulator. ACS Synth Biol 2023; 12:419-431. [PMID: 36728831 PMCID: PMC9942200 DOI: 10.1021/acssynbio.2c00351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Yeast surface display is a valuable tool for protein engineering and directed evolution; however, significant variability in the copy number (i.e., avidity) of displayed variants on the yeast cell wall complicates screening and selection campaigns. Here, we report an engineered titratable display platform that modulates the avidity of Aga2-fusion proteins on the yeast cell wall dependent on the concentration of the anhydrotetracycline (aTc) inducer. Our design is based on a genomic Aga1 gene copy and an episomal Aga2-fusion construct both under the control of an aTc-dependent transcriptional regulator that enables stoichiometric and titratable expression, secretion, and display of Aga2-fusion proteins. We demonstrate tunable display levels over 2-3 orders of magnitude for various model proteins, including glucose oxidase enzyme variants, mechanostable dockerin-binding domains, and anti-PDL1 affibody domains. By regulating the copy number of displayed proteins, we demonstrate the effects of titratable avidity levels on several specific phenotypic activities, including enzyme activity and cell adhesion to surfaces under shear flow. Finally, we show that titrating down the display level allows yeast-based binding affinity measurements to be performed in a regime that avoids ligand depletion effects while maintaining small sample volumes, avoiding a well-known artifact in yeast-based binding assays. The ability to titrate the multivalency of proteins on the yeast cell wall through simple inducer control will benefit protein engineering and directed evolution methodology relying on yeast display for broad classes of therapeutic and diagnostic proteins of interest.
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Affiliation(s)
- Joanan Lopez-Morales
- Department
of Chemistry, University of Basel, Basel 4058, Switzerland,Swiss
Nanoscience Institute, University of Basel, Basel 4056, Switzerland,Department
of Biosystems Science and Engineering, ETH
Zurich, Basel 4058, Switzerland
| | - Rosario Vanella
- Department
of Chemistry, University of Basel, Basel 4058, Switzerland,Department
of Biosystems Science and Engineering, ETH
Zurich, Basel 4058, Switzerland
| | - Gordana Kovacevic
- Department
of Chemistry, University of Basel, Basel 4058, Switzerland,Department
of Biosystems Science and Engineering, ETH
Zurich, Basel 4058, Switzerland
| | - Mariana Sá Santos
- Department
of Chemistry, University of Basel, Basel 4058, Switzerland,Department
of Biosystems Science and Engineering, ETH
Zurich, Basel 4058, Switzerland
| | - Michael A. Nash
- Department
of Chemistry, University of Basel, Basel 4058, Switzerland,Swiss
Nanoscience Institute, University of Basel, Basel 4056, Switzerland,Department
of Biosystems Science and Engineering, ETH
Zurich, Basel 4058, Switzerland,
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5
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Khor JM, Ettensohn CA. An optimized Tet-On system for conditional control of gene expression in sea urchins. Development 2023; 150:dev201373. [PMID: 36607745 PMCID: PMC10108607 DOI: 10.1242/dev.201373] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 11/28/2022] [Indexed: 01/07/2023]
Abstract
Sea urchins and other echinoderms are important experimental models for studying developmental processes. The lack of approaches for conditional gene perturbation, however, has made it challenging to investigate the late developmental functions of genes that have essential roles during early embryogenesis and genes that have diverse functions in multiple tissues. The doxycycline-controlled Tet-On system is a widely used molecular tool for temporally and spatially regulated transgene expression. Here, we optimized the Tet-On system to conditionally induce gene expression in sea urchin embryos. Using this approach, we explored the roles the MAPK signaling plays in skeletogenesis by expressing genes that perturb the pathway specifically in primary mesenchyme cells during later stages of development. We demonstrated the wide utility of the Tet-On system by applying it to a second sea urchin species and in cell types other than the primary mesenchyme cells. Our work provides a robust and flexible platform for the spatiotemporal regulation of gene expression in sea urchins, which will considerably enhance the utility of this prominent model system.
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Affiliation(s)
- Jian Ming Khor
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Charles A. Ettensohn
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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6
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Moschner C, Wedd C, Bakshi S. The context matrix: Navigating biological complexity for advanced biodesign. Front Bioeng Biotechnol 2022; 10:954707. [PMID: 36082163 PMCID: PMC9445834 DOI: 10.3389/fbioe.2022.954707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 06/29/2022] [Indexed: 12/05/2022] Open
Abstract
Synthetic biology offers many solutions in healthcare, production, sensing and agriculture. However, the ability to rationally engineer synthetic biosystems with predictable and robust functionality remains a challenge. A major reason is the complex interplay between the synthetic genetic construct, its host, and the environment. Each of these contexts contains a number of input factors which together can create unpredictable behaviours in the engineered biosystem. It has become apparent that for the accurate assessment of these contextual effects a more holistic approach to design and characterisation is required. In this perspective article, we present the context matrix, a conceptual framework to categorise and explore these contexts and their net effect on the designed synthetic biosystem. We propose the use and community-development of the context matrix as an aid for experimental design that simplifies navigation through the complex design space in synthetic biology.
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7
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Wang Y, Liu Y, Li J, Chen Y, Liu S, Zhong C. Engineered living materials (ELMs) design: From function allocation to dynamic behavior modulation. Curr Opin Chem Biol 2022; 70:102188. [PMID: 35970133 DOI: 10.1016/j.cbpa.2022.102188] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 06/14/2022] [Accepted: 07/05/2022] [Indexed: 11/17/2022]
Abstract
Natural materials possess many distinctive "living" attributes, such as self-growth, self-healing, environmental responsiveness, and evolvability, that are beyond the reach of many existing synthetic materials. The emerging field of engineered living materials (ELMs) takes inspiration from nature and harnesses engineered living systems to produce dynamic and responsive materials with genetically programmable functionalities. Here, we identify and review two main directions for the rational design of ELMs: first, engineering of living materials with enhanced performances by incorporating functional material modules, including engineered biological building blocks (proteins, polysaccharides, and nucleic acids) or well-defined artificial materials; second, engineering of smart ELMs that can sense and respond to their surroundings by programming dynamic cellular behaviors regulated via cell-cell or cell-environment interactions. We next discuss the strengths and challenges of current ELMs and conclude by providing a perspective of future directions in this promising area.
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Affiliation(s)
- Yanyi Wang
- Center for Materials Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Cas Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Yi Liu
- Center for Materials Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Cas Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; School of Physical Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Jing Li
- Center for Materials Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Cas Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Yue Chen
- Center for Materials Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Cas Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Sizhe Liu
- Center for Materials Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Cas Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, 518107, China
| | - Chao Zhong
- Center for Materials Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China; Cas Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
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8
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de Cesare I, Salzano D, di Bernardo M, Renson L, Marucci L. Control-Based Continuation: A New Approach to Prototype Synthetic Gene Networks. ACS Synth Biol 2022; 11:2300-2313. [PMID: 35729740 PMCID: PMC9295158 DOI: 10.1021/acssynbio.1c00632] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
Abstract
![]()
Control-Based Continuation
(CBC) is a general and systematic method
to carry out the bifurcation analysis of physical experiments. CBC
does not rely on a mathematical model and thus overcomes the uncertainty
introduced when identifying bifurcation curves indirectly through
modeling and parameter estimation. We demonstrate, in silico, CBC applicability to biochemical processes by tracking the equilibrium
curve of a toggle switch, which includes additive process noise and
exhibits bistability. We compare the results obtained when CBC uses
a model-free and model-based control strategy and show that both can
track stable and unstable solutions, revealing bistability. We then
demonstrate CBC in conditions more representative of an in
vivo experiment using an agent-based simulator describing
cell growth and division, cell-to-cell variability, spatial distribution,
and diffusion of chemicals. We further show how the identified curves
can be used for parameter estimation and discuss how CBC can significantly
accelerate the prototyping of synthetic gene regulatory networks.
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Affiliation(s)
- Irene de Cesare
- Engineering Mathematics Department, University of Bristol, Bristol BS8 1TW, U.K.,Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Naples, Italy
| | - Davide Salzano
- Engineering Mathematics Department, University of Bristol, Bristol BS8 1TW, U.K.,Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Naples, Italy
| | - Mario di Bernardo
- Department of Electrical Engineering and Information Technologies, University of Naples Federico II, 80125 Naples, Italy
| | - Ludovic Renson
- Department of Mechanical Engineering, Imperial College London, London SW7 2BX, U.K
| | - Lucia Marucci
- Engineering Mathematics Department, University of Bristol, Bristol BS8 1TW, U.K.,BrisSynBio, University of Bristol, Bristol BS8 1TQ, U.K.,School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1UB, U.K
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9
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Baskar R, Chen AF, Favaro P, Reynolds W, Mueller F, Borges L, Jiang S, Park HS, Kool ET, Greenleaf WJ, Bendall SC. Integrating transcription-factor abundance with chromatin accessibility in human erythroid lineage commitment. CELL REPORTS METHODS 2022; 2:100188. [PMID: 35463156 PMCID: PMC9017139 DOI: 10.1016/j.crmeth.2022.100188] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 01/20/2022] [Accepted: 03/01/2022] [Indexed: 01/01/2023]
Abstract
Master transcription factors (TFs) directly regulate present and future cell states by binding DNA regulatory elements and driving gene-expression programs. Their abundance influences epigenetic priming to different cell fates at the chromatin level, especially in the context of differentiation. In order to link TF protein abundance to changes in TF motif accessibility and open chromatin, we developed InTAC-seq, a method for simultaneous quantification of genome-wide chromatin accessibility and intracellular protein abundance in fixed cells. Our method produces high-quality data and is a cost-effective alternative to single-cell techniques. We showcase our method by purifying bone marrow (BM) progenitor cells based on GATA-1 protein levels and establish high GATA-1-expressing BM cells as both epigenetically and functionally similar to erythroid-committed progenitors.
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Affiliation(s)
- Reema Baskar
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Cancer Biology Program, Stanford University, Stanford, CA 94305, USA
| | - Amy F. Chen
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Patricia Favaro
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Warren Reynolds
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Fabian Mueller
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Luciene Borges
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Sizun Jiang
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Hyun Shin Park
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
| | - Eric T. Kool
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
- ChEM-H Institute, Stanford University, Stanford, CA 94305, USA
| | - William J. Greenleaf
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
- Department of Applied Physics, Stanford University, Stanford, CA 94305, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Sean C. Bendall
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
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10
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Protease-controlled secretion and display of intercellular signals. Nat Commun 2022; 13:912. [PMID: 35177637 PMCID: PMC8854555 DOI: 10.1038/s41467-022-28623-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 02/03/2022] [Indexed: 02/07/2023] Open
Abstract
To program intercellular communication for biomedicine, it is crucial to regulate the secretion and surface display of signaling proteins. If such regulations are at the protein level, there are additional advantages, including compact delivery and direct interactions with endogenous signaling pathways. Here we create a modular, generalizable design called Retained Endoplasmic Cleavable Secretion (RELEASE), with engineered proteins retained in the endoplasmic reticulum and displayed/secreted in response to specific proteases. The design allows functional regulation of multiple synthetic and natural proteins by synthetic protease circuits to realize diverse signal processing capabilities, including logic operation and threshold tuning. By linking RELEASE to additional sensing and processing circuits, we can achieve elevated protein secretion in response to "undruggable" oncogene KRAS mutants. RELEASE should enable the local, programmable delivery of intercellular cues for a broad variety of fields such as neurobiology, cancer immunotherapy and cell transplantation.
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11
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Pedone E, Failli M, Gambardella G, De Cegli R, La Regina A, di Bernardo D, Marucci L. β-catenin perturbations control differentiation programs in mouse embryonic stem cells. iScience 2022; 25:103756. [PMID: 35128356 PMCID: PMC8804270 DOI: 10.1016/j.isci.2022.103756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/09/2021] [Accepted: 01/07/2022] [Indexed: 11/06/2022] Open
Abstract
The Wnt/β-catenin pathway is involved in development, cancer, and embryonic stem cell (ESC) maintenance; its dual role in stem cell self-renewal and differentiation is still controversial. Here, by applying an in vitro system enabling inducible gene expression control, we report that moderate induction of transcriptionally active exogenous β-catenin in β-catenin null mouse ESCs promotes epiblast-like cell (EpiLC) derivation in vitro. Instead, in wild-type cells, moderate chemical pre-activation of the Wnt/β-catenin pathway promotes EpiLC in vitro derivation. Finally, we suggest that moderate β-catenin levels in β-catenin null mouse ESCs favor early stem cell commitment toward mesoderm if the exogenous protein is induced only in the “ground state” of pluripotency condition, or endoderm if the induction is maintained during the differentiation. Overall, our results confirm previous findings about the role of β-catenin in pluripotency and differentiation, while indicating a role for its doses in promoting specific differentiation programs. Moderate β-catenin levels promote EpiLCs derivation in vitro Chemical pre-activation of the Wnt pathway enhances ESC-EpiLC transition β-catenin overexpression tips the balance between mesoderm and endoderm Cell fate is influenced by the extent of β-catenin induction
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12
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Kassaw TK, Paton AJ, Peers G. Episome-Based Gene Expression Modulation Platform in the Model Diatom Phaeodactylum tricornutum. ACS Synth Biol 2022; 11:191-204. [PMID: 35015507 DOI: 10.1021/acssynbio.1c00367] [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: 01/24/2023]
Abstract
Chemically inducible gene expression systems have been an integral part of the advanced synthetic genetic circuit design and are employed for precise dynamic control over genetically engineered traits. However, the current systems for controlling transgene expression in most algae are limited to endogenous promoters that respond to different environmental factors. We developed a highly efficient, tunable, and reversible episome-based transcriptional control system in the model diatom alga, Phaeodactylum tricornutum. We assessed the time- and dose-response dynamics of each expression system using a reporter protein (eYFP) as a readout. Using our circuit configuration, we found two inducible expression systems with a high dynamic range and confirmed the suitability of an episome expression platform for synthetic biological applications in diatoms. These systems are controlled by the presence of β-estradiol and digoxin. Addition of either chemical to transgenic strains activates transcription with a dynamic range of up to ∼180-fold and ∼90-fold, respectively. We demonstrated that our episome-based transcriptional control systems are tunable and reversible in a dose- and time-dependent manner. Using droplet digital polymerase chain reaction (PCR), we also confirmed that inducer-dependent transcriptional activation starts within minutes of inducer application without any detectable transcript in the uninduced controls. The system described here expands the molecular and synthetic biology toolkits in algae and will facilitate future gene discovery and metabolic engineering efforts.
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Affiliation(s)
- Tessema K. Kassaw
- Department of Biology, Colorado State University, Fort Collins, Colorado 80523, United States
| | - Andrew J. Paton
- Department of Biology, Colorado State University, Fort Collins, Colorado 80523, United States
| | - Graham Peers
- Department of Biology, Colorado State University, Fort Collins, Colorado 80523, United States
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13
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Kavaliauskaitė J, Kazlauskaitė A, Lazutka JR, Mozolevskis G, Stirkė A. Pulsed Electric Fields Alter Expression of NF-κB Promoter-Controlled Gene. Int J Mol Sci 2021; 23:ijms23010451. [PMID: 35008875 PMCID: PMC8745616 DOI: 10.3390/ijms23010451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 12/19/2021] [Accepted: 12/29/2021] [Indexed: 11/16/2022] Open
Abstract
The possibility to artificially adjust and fine-tune gene expression is one of the key milestones in bioengineering, synthetic biology, and advanced medicine. Since the effects of proteins or other transgene products depend on the dosage, controlled gene expression is required for any applications, where even slight fluctuations of the transgene product impact its function or other critical cell parameters. In this context, physical techniques demonstrate optimistic perspectives, and pulsed electric field technology is a potential candidate for a noninvasive, biophysical gene regulator, exploiting an easily adjustable pulse generating device. We exposed mammalian cells, transfected with a NF-κB pathway-controlled transcription system, to a range of microsecond-duration pulsed electric field parameters. To prevent toxicity, we used protocols that would generate relatively mild physical stimulation. The present study, for the first time, proves the principle that microsecond-duration pulsed electric fields can alter single-gene expression in plasmid context in mammalian cells without significant damage to cell integrity or viability. Gene expression might be upregulated or downregulated depending on the cell line and parameters applied. This noninvasive, ligand-, cofactor-, nanoparticle-free approach enables easily controlled direct electrostimulation of the construct carrying the gene of interest; the discovery may contribute towards the path of simplification of the complexity of physical systems in gene regulation and create further synergies between electronics, synthetic biology, and medicine.
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Affiliation(s)
- Justina Kavaliauskaitė
- Laboratory of Bioelectrics, Center for Physical Sciences and Technology, Sauletekio Ave. 3, LT-10257 Vilnius, Lithuania; (J.K.); (A.K.)
- Department of Botany and Genetics, Institute of Biosciences, Life Sciences Center, Vilnius University, Sauletekio Ave. 7, LT-10222 Vilnius, Lithuania;
| | - Auksė Kazlauskaitė
- Laboratory of Bioelectrics, Center for Physical Sciences and Technology, Sauletekio Ave. 3, LT-10257 Vilnius, Lithuania; (J.K.); (A.K.)
- Department of Botany and Genetics, Institute of Biosciences, Life Sciences Center, Vilnius University, Sauletekio Ave. 7, LT-10222 Vilnius, Lithuania;
| | - Juozas Rimantas Lazutka
- Department of Botany and Genetics, Institute of Biosciences, Life Sciences Center, Vilnius University, Sauletekio Ave. 7, LT-10222 Vilnius, Lithuania;
| | - Gatis Mozolevskis
- Laboratory of Prototyping of Electronic and Photonic Devices, Institute of Solid State Physics, University of Latvia, Kengaraga Str. 8, LV-1063 Riga, Latvia;
| | - Arūnas Stirkė
- Laboratory of Bioelectrics, Center for Physical Sciences and Technology, Sauletekio Ave. 3, LT-10257 Vilnius, Lithuania; (J.K.); (A.K.)
- Laboratory of Prototyping of Electronic and Photonic Devices, Institute of Solid State Physics, University of Latvia, Kengaraga Str. 8, LV-1063 Riga, Latvia;
- Correspondence:
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14
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Pedone E, de Cesare I, Zamora-Chimal CG, Haener D, Postiglione L, La Regina A, Shannon B, Savery NJ, Grierson CS, di Bernardo M, Gorochowski TE, Marucci L. Cheetah: A Computational Toolkit for Cybergenetic Control. ACS Synth Biol 2021; 10:979-989. [PMID: 33904719 DOI: 10.1021/acssynbio.0c00463] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Advances in microscopy, microfluidics, and optogenetics enable single-cell monitoring and environmental regulation and offer the means to control cellular phenotypes. The development of such systems is challenging and often results in bespoke setups that hinder reproducibility. To address this, we introduce Cheetah, a flexible computational toolkit that simplifies the integration of real-time microscopy analysis with algorithms for cellular control. Central to the platform is an image segmentation system based on the versatile U-Net convolutional neural network. This is supplemented with functionality to robustly count, characterize, and control cells over time. We demonstrate Cheetah's core capabilities by analyzing long-term bacterial and mammalian cell growth and by dynamically controlling protein expression in mammalian cells. In all cases, Cheetah's segmentation accuracy exceeds that of a commonly used thresholding-based method, allowing for more accurate control signals to be generated. Availability of this easy-to-use platform will make control engineering techniques more accessible and offer new ways to probe and manipulate living cells.
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Affiliation(s)
- Elisa Pedone
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- School of Cellular and Molecular Medicine, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
| | - Irene de Cesare
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
| | - Criseida G. Zamora-Chimal
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
| | - David Haener
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
| | - Lorena Postiglione
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
| | - Antonella La Regina
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- School of Cellular and Molecular Medicine, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
| | - Barbara Shannon
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
| | - Nigel J. Savery
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- School of Biochemistry, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
| | - Claire S. Grierson
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- School of Biological Sciences, University of Bristol, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
| | - Mario di Bernardo
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- Department of EE and ICT, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy
| | - Thomas E. Gorochowski
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
- School of Biological Sciences, University of Bristol, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
| | - Lucia Marucci
- Department of Engineering Mathematics, University of Bristol, Ada Lovelace Building, University Walk, BS8 1TW Bristol, United Kingdom
- School of Cellular and Molecular Medicine, University of Bristol, Biomedical Sciences Building, University Walk, BS8 1TD Bristol, United Kingdom
- BrisSynBio, Life Sciences Building, Tyndall Avenue, BS8 1TQ Bristol, United Kingdom
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15
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de Cesare I, Zamora-Chimal CG, Postiglione L, Khazim M, Pedone E, Shannon B, Fiore G, Perrino G, Napolitano S, di Bernardo D, Savery NJ, Grierson C, di Bernardo M, Marucci L. ChipSeg: An Automatic Tool to Segment Bacterial and Mammalian Cells Cultured in Microfluidic Devices. ACS OMEGA 2021; 6:2473-2476. [PMID: 33553865 PMCID: PMC7859942 DOI: 10.1021/acsomega.0c03906] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Accepted: 11/20/2020] [Indexed: 05/14/2023]
Abstract
Extracting quantitative measurements from time-lapse images is necessary in external feedback control applications, where segmentation results are used to inform control algorithms. We describe ChipSeg, a computational tool that segments bacterial and mammalian cells cultured in microfluidic devices and imaged by time-lapse microscopy, which can be used also in the context of external feedback control. The method is based on thresholding and uses the same core functions for both cell types. It allows us to segment individual cells in high cell density microfluidic devices, to quantify fluorescent protein expression over a time-lapse experiment, and to track individual mammalian cells. ChipSeg enables robust segmentation in external feedback control experiments and can be easily customized for other experimental settings and research aims.
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Affiliation(s)
- Irene de Cesare
- Department
of Engineering Mathematics, University of
Bristol, Woodland Road, Bristol BS8 1UB, U.K.
| | - Criseida G. Zamora-Chimal
- Department
of Engineering Mathematics, University of
Bristol, Woodland Road, Bristol BS8 1UB, U.K.
- BrisSynBio,
Life Sciences Building, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, U.K.
| | - Lorena Postiglione
- Department
of Engineering Mathematics, University of
Bristol, Woodland Road, Bristol BS8 1UB, U.K.
| | - Mahmoud Khazim
- Department
of Engineering Mathematics, University of
Bristol, Woodland Road, Bristol BS8 1UB, U.K.
- School
of Cellular and Molecular Medicine, University
of Bristol, University Walk, Bristol BS8 1TD, U.K.
| | - Elisa Pedone
- Department
of Engineering Mathematics, University of
Bristol, Woodland Road, Bristol BS8 1UB, U.K.
- School
of Cellular and Molecular Medicine, University
of Bristol, University Walk, Bristol BS8 1TD, U.K.
| | - Barbara Shannon
- BrisSynBio,
Life Sciences Building, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, U.K.
- School
of Biochemistry, University of Bristol, University Walk, Bristol BS8 1TD, U.K.
| | - Gianfranco Fiore
- Department
of Engineering Mathematics, University of
Bristol, Woodland Road, Bristol BS8 1UB, U.K.
- BrisSynBio,
Life Sciences Building, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, U.K.
| | - Giansimone Perrino
- Telethon
Institute of Genetic and Medicine Via Campi Flegrei 34, 80078 Pozzuoli, Italy
| | - Sara Napolitano
- Telethon
Institute of Genetic and Medicine Via Campi Flegrei 34, 80078 Pozzuoli, Italy
| | - Diego di Bernardo
- Telethon
Institute of Genetic and Medicine Via Campi Flegrei 34, 80078 Pozzuoli, Italy
- Department
of Chemical, Materials and Industrial Production Engineering, University of Naples Federico II, 80125 Naples, Italy
| | - Nigel J. Savery
- BrisSynBio,
Life Sciences Building, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, U.K.
- School
of Biochemistry, University of Bristol, University Walk, Bristol BS8 1TD, U.K.
| | - Claire Grierson
- BrisSynBio,
Life Sciences Building, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, U.K.
- School
of Biological Sciences, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, U.K.
| | - Mario di Bernardo
- Department
of Engineering Mathematics, University of
Bristol, Woodland Road, Bristol BS8 1UB, U.K.
- BrisSynBio,
Life Sciences Building, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, U.K.
- Department
of EE and ICT, University of Naples Federico
II, Via Claudio 21, 80125 Naples, Italy
| | - Lucia Marucci
- Department
of Engineering Mathematics, University of
Bristol, Woodland Road, Bristol BS8 1UB, U.K.
- BrisSynBio,
Life Sciences Building, University of Bristol, Tyndall Avenue, Bristol BS8 1TQ, U.K.
- School
of Cellular and Molecular Medicine, University
of Bristol, University Walk, Bristol BS8 1TD, U.K.
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16
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Bonny AR, Fonseca JP, Park JE, El-Samad H. Orthogonal control of mean and variability of endogenous genes in a human cell line. Nat Commun 2021; 12:292. [PMID: 33436569 PMCID: PMC7804932 DOI: 10.1038/s41467-020-20467-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 11/25/2020] [Indexed: 12/11/2022] Open
Abstract
Stochastic fluctuations at the transcriptional level contribute to isogenic cell-to-cell heterogeneity in mammalian cell populations. However, we still have no clear understanding of the repercussions of this heterogeneity, given the lack of tools to independently control mean expression and variability of a gene. Here, we engineer a synthetic circuit to modulate mean expression and heterogeneity of transgenes and endogenous human genes. The circuit, a Tunable Noise Rheostat (TuNR), consists of a transcriptional cascade of two inducible transcriptional activators, where the output mean and variance can be modulated by two orthogonal small molecule inputs. In this fashion, different combinations of the inputs can achieve the same mean but with different population variability. With TuNR, we achieve low basal expression, over 1000-fold expression of a transgene product, and up to 7-fold induction of the endogenous gene NGFR. Importantly, for the same mean expression level, we are able to establish varying degrees of heterogeneity in expression within an isogenic population, thereby decoupling gene expression noise from its mean. TuNR is therefore a modular tool that can be used in mammalian cells to enable direct interrogation of the implications of cell-to-cell variability.
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Affiliation(s)
- Alain R Bonny
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - João Pedro Fonseca
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
- Amyris Bio Products Portugal, Porto, Portugal
| | - Jesslyn E Park
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Hana El-Samad
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
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17
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Khazim M, Pedone E, Postiglione L, di Bernardo D, Marucci L. A Microfluidic/Microscopy-Based Platform for on-Chip Controlled Gene Expression in Mammalian Cells. Methods Mol Biol 2021; 2229:205-219. [PMID: 33405224 DOI: 10.1007/978-1-0716-1032-9_10] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Applications of control engineering to mammalian cell biology have been recently implemented for precise regulation of gene expression. In this chapter, we report the main experimental and computational methodologies to implement automatic feedback control of gene expression in mammalian cells using a microfluidics/microscopy platform.
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Affiliation(s)
- Mahmoud Khazim
- Department of Engineering Mathematics, University of Bristol, Bristol, UK
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
- BrisSynBio, Bristol, UK
| | - Elisa Pedone
- Department of Engineering Mathematics, University of Bristol, Bristol, UK
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
- BrisSynBio, Bristol, UK
| | - Lorena Postiglione
- Department of Engineering Mathematics, University of Bristol, Bristol, UK
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
- BrisSynBio, Bristol, UK
| | | | - Lucia Marucci
- Department of Engineering Mathematics, University of Bristol, Bristol, UK.
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK.
- BrisSynBio, Bristol, UK.
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18
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19
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Marucci L, Barberis M, Karr J, Ray O, Race PR, de Souza Andrade M, Grierson C, Hoffmann SA, Landon S, Rech E, Rees-Garbutt J, Seabrook R, Shaw W, Woods C. Computer-Aided Whole-Cell Design: Taking a Holistic Approach by Integrating Synthetic With Systems Biology. Front Bioeng Biotechnol 2020; 8:942. [PMID: 32850764 PMCID: PMC7426639 DOI: 10.3389/fbioe.2020.00942] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2020] [Accepted: 07/21/2020] [Indexed: 01/03/2023] Open
Abstract
Computer-aided design (CAD) for synthetic biology promises to accelerate the rational and robust engineering of biological systems. It requires both detailed and quantitative mathematical and experimental models of the processes to (re)design biology, and software and tools for genetic engineering and DNA assembly. Ultimately, the increased precision in the design phase will have a dramatic impact on the production of designer cells and organisms with bespoke functions and increased modularity. CAD strategies require quantitative models of cells that can capture multiscale processes and link genotypes to phenotypes. Here, we present a perspective on how whole-cell, multiscale models could transform design-build-test-learn cycles in synthetic biology. We show how these models could significantly aid in the design and learn phases while reducing experimental testing by presenting case studies spanning from genome minimization to cell-free systems. We also discuss several challenges for the realization of our vision. The possibility to describe and build whole-cells in silico offers an opportunity to develop increasingly automatized, precise and accessible CAD tools and strategies.
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Affiliation(s)
- Lucia Marucci
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.,School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom.,Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom
| | - Matteo Barberis
- Systems Biology, School of Biosciences and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom.,Centre for Mathematical and Computational Biology, CMCB, University of Surrey, Guildford, United Kingdom.,Synthetic Systems Biology and Nuclear Organization, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Jonathan Karr
- Icahn Institute for Data Science and Genomic Technology, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Oliver Ray
- Department of Computer Science, University of Bristol, Bristol, United Kingdom
| | - Paul R Race
- Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom.,School of Biochemistry, University of Bristol, Bristol, United Kingdom
| | - Miguel de Souza Andrade
- Brazilian Agricultural Research Corporation/National Institute of Science and Technology - Synthetic Biology, Brasília, Brazil.,Department of Cell Biology, Institute of Biological Sciences, University of Brasília, Brasília, Brazil
| | - Claire Grierson
- Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom.,School of Biological Sciences, University of Bristol, Bristol, United Kingdom
| | - Stefan Andreas Hoffmann
- Manchester Institute of Biotechnology, The University of Manchester, Manchester, United Kingdom
| | - Sophie Landon
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom.,Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom
| | - Elibio Rech
- Brazilian Agricultural Research Corporation/National Institute of Science and Technology - Synthetic Biology, Brasília, Brazil
| | - Joshua Rees-Garbutt
- Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom.,School of Biological Sciences, University of Bristol, Bristol, United Kingdom
| | - Richard Seabrook
- Elizabeth Blackwell Institute for Health Research (EBI), University of Bristol, Bristol, United Kingdom
| | - William Shaw
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Christopher Woods
- Bristol Centre for Synthetic Biology (BrisSynBio), University of Bristol, Bristol, United Kingdom.,School of Chemistry, University of Bristol, Bristol, United Kingdom
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20
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Gorochowski TE, Hauert S, Kreft JU, Marucci L, Stillman NR, Tang TYD, Bandiera L, Bartoli V, Dixon DOR, Fedorec AJH, Fellermann H, Fletcher AG, Foster T, Giuggioli L, Matyjaszkiewicz A, McCormick S, Montes Olivas S, Naylor J, Rubio Denniss A, Ward D. Toward Engineering Biosystems With Emergent Collective Functions. Front Bioeng Biotechnol 2020; 8:705. [PMID: 32671054 PMCID: PMC7332988 DOI: 10.3389/fbioe.2020.00705] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Accepted: 06/05/2020] [Indexed: 12/31/2022] Open
Abstract
Many complex behaviors in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans many length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modeling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modeling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviors offers a means to take synthetic biology beyond single molecules or cells and toward the creation of systems with functions that can only emerge from collectives at multiple scales.
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Affiliation(s)
| | - Sabine Hauert
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom
| | - Jan-Ulrich Kreft
- School of Biosciences and Institute of Microbiology and Infection and Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom
| | - Lucia Marucci
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom
| | - Namid R. Stillman
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom
| | - T.-Y. Dora Tang
- Max Plank Institute of Molecular Cell Biology and Genetics, Dresden, Germany
- Physics of Life, Cluster of Excellence, Technische Universität Dresden, Dresden, Germany
| | - Lucia Bandiera
- School of Engineering, University of Edinburgh, Edinburgh, United Kingdom
| | - Vittorio Bartoli
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom
| | | | - Alex J. H. Fedorec
- Division of Biosciences, University College London, London, United Kingdom
| | - Harold Fellermann
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Alexander G. Fletcher
- Bateson Centre and School of Mathematics and Statistics, University of Sheffield, Sheffield, United Kingdom
| | - Tim Foster
- School of Biosciences and Institute of Microbiology and Infection and Centre for Computational Biology, University of Birmingham, Birmingham, United Kingdom
| | - Luca Giuggioli
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom
| | | | - Scott McCormick
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom
| | - Sandra Montes Olivas
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom
| | - Jonathan Naylor
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Ana Rubio Denniss
- Department of Engineering Mathematics, University of Bristol, Bristol, United Kingdom
| | - Daniel Ward
- School of Biological Sciences, University of Bristol, Bristol, United Kingdom
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21
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Scott HL, Buckner N, Fernandez-Albert F, Pedone E, Postiglione L, Shi G, Allen N, Wong LF, Magini L, Marucci L, O'Sullivan GA, Cole S, Powell J, Maycox P, Uney JB. A dual druggable genome-wide siRNA and compound library screening approach identifies modulators of parkin recruitment to mitochondria. J Biol Chem 2020; 295:3285-3300. [PMID: 31911436 PMCID: PMC7062187 DOI: 10.1074/jbc.ra119.009699] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2019] [Revised: 12/20/2019] [Indexed: 01/07/2023] Open
Abstract
Genetic and biochemical evidence points to an association between mitochondrial dysfunction and Parkinson's disease (PD). PD-associated mutations in several genes have been identified and include those encoding PTEN-induced putative kinase 1 (PINK1) and parkin. To identify genes, pathways, and pharmacological targets that modulate the clearance of damaged or old mitochondria (mitophagy), here we developed a high-content imaging-based assay of parkin recruitment to mitochondria and screened both a druggable genome-wide siRNA library and a small neuroactive compound library. We used a multiparameter principal component analysis and an unbiased parameter-agnostic machine-learning approach to analyze the siRNA-based screening data. The hits identified in this analysis included specific genes of the ubiquitin proteasome system, and inhibition of ubiquitin-conjugating enzyme 2 N (UBE2N) with a specific antagonist, Bay 11-7082, indicated that UBE2N modulates parkin recruitment and downstream events in the mitophagy pathway. Screening of the compound library identified kenpaullone, an inhibitor of cyclin-dependent kinases and glycogen synthase kinase 3, as a modulator of parkin recruitment. Validation studies revealed that kenpaullone augments the mitochondrial network and protects against the complex I inhibitor MPP+. Finally, we used a microfluidics platform to assess the timing of parkin recruitment to depolarized mitochondria and its modulation by kenpaullone in real time and with single-cell resolution. We demonstrate that the high-content imaging-based assay presented here is suitable for both genetic and pharmacological screening approaches, and we also provide evidence that pharmacological compounds modulate PINK1-dependent parkin recruitment.
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Affiliation(s)
- Helen L Scott
- Bristol Medical School, University of Bristol, Bristol BS8 1TD, United Kingdom
| | - Nicola Buckner
- Bristol Medical School, University of Bristol, Bristol BS8 1TD, United Kingdom
| | | | - Elisa Pedone
- Department of Engineering and Mathematics, University of Bristol, Bristol BS8 1TD, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1TD, United Kingdom
| | - Lorena Postiglione
- Department of Engineering and Mathematics, University of Bristol, Bristol BS8 1TD, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol BS8 1TD, United Kingdom
| | - Gongyu Shi
- Bristol Medical School, University of Bristol, Bristol BS8 1TD, United Kingdom
| | - Nicholas Allen
- School of Biosciences, Cardiff University, Cardiff CF10 3AX, United Kingdom
| | - Liang-Fong Wong
- Bristol Medical School, University of Bristol, Bristol BS8 1TD, United Kingdom
| | - Lorenzo Magini
- Bristol Medical School, University of Bristol, Bristol BS8 1TD, United Kingdom
| | - Lucia Marucci
- Department of Engineering and Mathematics, University of Bristol, Bristol BS8 1TD, United Kingdom; BrisSynBio, Bristol BS8 1QU, United Kingdom
| | - Gregory A O'Sullivan
- Takeda Cambridge Ltd., Cambridge Science Park, Cambridge CB4 0PZ, United Kingdom
| | - Sarah Cole
- Takeda Ventures, Inc., 61 Aldwych, London WC2B 4A, United Kingdom
| | - Justin Powell
- Takeda Cambridge Ltd., Cambridge Science Park, Cambridge CB4 0PZ, United Kingdom
| | - Peter Maycox
- Takeda Ventures, Inc., 61 Aldwych, London WC2B 4A, United Kingdom
| | - James B Uney
- Bristol Medical School, University of Bristol, Bristol BS8 1TD, United Kingdom.
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