1
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Hunt JP, Free TJ, Galiardi J, Watt KM, Wood DW, Bundy BC. Streamlining the Detection of Human Thyroid Receptor Ligand Interactions with XL1-Blue Cell-Free Protein Synthesis and Beta-Galactosidase Fusion Protein Biosensors. Life (Basel) 2023; 13:1972. [PMID: 37895354 PMCID: PMC10608756 DOI: 10.3390/life13101972] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 09/22/2023] [Accepted: 09/25/2023] [Indexed: 10/29/2023] Open
Abstract
Thyroid receptor signaling controls major physiological processes and disrupted signaling can cause severe disorders that negatively impact human life. Consequently, methods to detect thyroid receptor ligands are of great toxicologic and pharmacologic importance. Previously, we reported thyroid receptor ligand detection with cell-free protein synthesis of a chimeric fusion protein composed of the human thyroid receptor beta (hTRβ) receptor activator and a β-lactamase reporter. Here, we report a 60% reduction in sensing cost by reengineering the chimeric fusion protein biosensor to include a reporter system composed of either the full-length beta galactosidase (β-gal), the alpha fragment of β-gal (β-gal-α), or a split alpha fragment of the β-gal (split β-gal-α). These biosensor constructs are deployed using E. coli XL1-Blue cell extract to (1) avoid the β-gal background activity abundant in BL21 cell extract and (2) facilitate β-gal complementation reporter activity to detect human thyroid receptor ligands. These results constitute a promising platform for high throughput screening and potentially the portable detection of human thyroid receptor ligands.
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Affiliation(s)
- J. Porter Hunt
- Department of Chemical Engineering, Brigham Young University, Provo, UT 84602, USA
| | - Tyler J. Free
- Department of Chemical Engineering, Brigham Young University, Provo, UT 84602, USA
| | - Jackelyn Galiardi
- Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Kevin M. Watt
- Department of Pediatrics, University of Utah, Salt Lake City, UT 84108, USA
| | - David W. Wood
- Department of Chemical and Biomolecular Engineering, The Ohio State University, Columbus, OH 43210, USA
| | - Bradley C. Bundy
- Department of Chemical Engineering, Brigham Young University, Provo, UT 84602, USA
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2
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Wagner L, Jules M, Borkowski O. What remains from living cells in bacterial lysate-based cell-free systems. Comput Struct Biotechnol J 2023; 21:3173-3182. [PMID: 37333859 PMCID: PMC10275740 DOI: 10.1016/j.csbj.2023.05.025] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/23/2023] [Accepted: 05/23/2023] [Indexed: 06/20/2023] Open
Abstract
Because they mimic cells while offering an accessible and controllable environment, lysate-based cell-free systems (CFS) have emerged as valuable biotechnology tools for synthetic biology. Historically used to uncover fundamental mechanisms of life, CFS are nowadays used for a multitude of purposes, including protein production and prototyping of synthetic circuits. Despite the conservation of fundamental functions in CFS like transcription and translation, RNAs and certain membrane-embedded or membrane-bound proteins of the host cell are lost when preparing the lysate. As a result, CFS largely lack some essential properties of living cells, such as the ability to adapt to changing conditions, to maintain homeostasis and spatial organization. Regardless of the application, shedding light on the black-box of the bacterial lysate is necessary to fully exploit the potential of CFS. Most measurements of the activity of synthetic circuits in CFS and in vivo show significant correlations because these only require processes that are preserved in CFS, like transcription and translation. However, prototyping circuits of higher complexity that require functions that are lost in CFS (cell adaptation, homeostasis, spatial organization) will not show such a good correlation with in vivo conditions. Both for prototyping circuits of higher complexity and for building artificial cells, the cell-free community has developed devices to reconstruct cellular functions. This mini-review compares bacterial CFS to living cells, focusing on functional and cellular process differences and the latest developments in restoring lost functions through complementation of the lysate or device engineering.
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3
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Dong H, Yang X, Shi J, Xiao C, Zhang Y. Exploring the Feasibility of Cell-Free Synthesis as a Platform for Polyhydroxyalkanoate (PHA) Production: Opportunities and Challenges. Polymers (Basel) 2023; 15:polym15102333. [PMID: 37242908 DOI: 10.3390/polym15102333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 05/12/2023] [Accepted: 05/13/2023] [Indexed: 05/28/2023] Open
Abstract
The extensive utilization of traditional petroleum-based plastics has resulted in significant damage to the natural environment and ecological systems, highlighting the urgent need for sustainable alternatives. Polyhydroxyalkanoates (PHAs) have emerged as promising bioplastics that can compete with petroleum-based plastics. However, their production technology currently faces several challenges, primarily focused on high costs. Cell-free biotechnologies have shown significant potential for PHA production; however, despite recent progress, several challenges still need to be overcome. In this review, we focus on the status of cell-free PHA synthesis and compare it with microbial cell-based PHA synthesis in terms of advantages and drawbacks. Finally, we present prospects for the development of cell-free PHA synthesis.
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Affiliation(s)
- Huaming Dong
- School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Xue Yang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Center of Technology Innovation for Synthetic Biology, Tianjin 300308, China
| | - Jingjing Shi
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Center of Technology Innovation for Synthetic Biology, Tianjin 300308, China
| | - Chunqiao Xiao
- School of Environmental Ecology and Biological Engineering, Wuhan Institute of Technology, Wuhan 430205, China
| | - Yanfei Zhang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
- National Center of Technology Innovation for Synthetic Biology, Tianjin 300308, China
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4
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Martin JP, Rasor BJ, DeBonis J, Karim AS, Jewett MC, Tyo KEJ, Broadbelt LJ. A dynamic kinetic model captures cell-free metabolism for improved butanol production. Metab Eng 2023; 76:133-145. [PMID: 36724840 DOI: 10.1016/j.ymben.2023.01.009] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 11/30/2022] [Accepted: 01/25/2023] [Indexed: 01/30/2023]
Abstract
Cell-free systems are useful tools for prototyping metabolic pathways and optimizing the production of various bioproducts. Mechanistically-based kinetic models are uniquely suited to analyze dynamic experimental data collected from cell-free systems and provide vital qualitative insight. However, to date, dynamic kinetic models have not been applied with rigorous biological constraints or trained on adequate experimental data to the degree that they would give high confidence in predictions and broadly demonstrate the potential for widespread use of such kinetic models. In this work, we construct a large-scale dynamic model of cell-free metabolism with the goal of understanding and optimizing butanol production in a cell-free system. Using a combination of parameterization methods, the resultant model captures experimental metabolite measurements across two experimental conditions for nine metabolites at timepoints between 0 and 24 h. We present analysis of the model predictions, provide recommendations for butanol optimization, and identify the aldehyde/alcohol dehydrogenase as the primary bottleneck in butanol production. Sensitivity analysis further reveals the extent to which various parameters are constrained, and our approach for probing valid parameter ranges can be applied to other modeling efforts.
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Affiliation(s)
- Jacob P Martin
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA; Center for Synthetic Biology, Northwestern University, Evanston, IL, 60208, USA; Chemistry of Life Processes Institute, Northwestern University, Evanston, IL, 60208, USA
| | - Blake J Rasor
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA; Center for Synthetic Biology, Northwestern University, Evanston, IL, 60208, USA; Chemistry of Life Processes Institute, Northwestern University, Evanston, IL, 60208, USA
| | - Jonathon DeBonis
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA
| | - Ashty S Karim
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA; Center for Synthetic Biology, Northwestern University, Evanston, IL, 60208, USA; Chemistry of Life Processes Institute, Northwestern University, Evanston, IL, 60208, USA
| | - Michael C Jewett
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA; Center for Synthetic Biology, Northwestern University, Evanston, IL, 60208, USA; Chemistry of Life Processes Institute, Northwestern University, Evanston, IL, 60208, USA
| | - Keith E J Tyo
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA; Center for Synthetic Biology, Northwestern University, Evanston, IL, 60208, USA; Chemistry of Life Processes Institute, Northwestern University, Evanston, IL, 60208, USA
| | - Linda J Broadbelt
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, 60208, USA; Center for Synthetic Biology, Northwestern University, Evanston, IL, 60208, USA.
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5
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Rasor BJ, Chirania P, Rybnicky GA, Giannone RJ, Engle NL, Tschaplinski TJ, Karim AS, Hettich RL, Jewett MC. Mechanistic Insights into Cell-Free Gene Expression through an Integrated -Omics Analysis of Extract Processing Methods. ACS Synth Biol 2023; 12:405-418. [PMID: 36700560 DOI: 10.1021/acssynbio.2c00339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Cell-free systems derived from crude cell extracts have developed into tools for gene expression, with applications in prototyping, biosensing, and protein production. Key to the development of these systems is optimization of cell extract preparation methods. However, the applied nature of these optimizations often limits investigation into the complex nature of the extracts themselves, which contain thousands of proteins and reaction networks with hundreds of metabolites. Here, we sought to uncover the black box of proteins and metabolites in Escherichia coli cell-free reactions based on different extract preparation methods. We assess changes in transcription and translation activity from σ70 promoters in extracts prepared with acetate or glutamate buffer and the common post-lysis processing steps of a runoff incubation and dialysis. We then utilize proteomic and metabolomic analyses to uncover potential mechanisms behind these changes in gene expression, highlighting the impact of cold shock-like proteins and the role of buffer composition.
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Affiliation(s)
- Blake J Rasor
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States.,Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States.,Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, United States
| | - Payal Chirania
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States.,Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, Tennessee 37996, United States
| | - Grant A Rybnicky
- Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States.,Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, United States.,Interdisciplinary Biological Sciences Graduate Program, Northwestern University, Evanston, Illinois 60208, United States
| | - Richard J Giannone
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Nancy L Engle
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Timothy J Tschaplinski
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Ashty S Karim
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States.,Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States.,Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, United States
| | - Robert L Hettich
- Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, United States
| | - Michael C Jewett
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, Illinois 60208, United States.,Chemistry of Life Processes Institute, Northwestern University, Evanston, Illinois 60208, United States.,Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, United States.,Robert H. Lurie Comprehensive Cancer Center, Northwestern University, Chicago, Illinois 60611, United States.,Simpson Querrey Institute, Northwestern University, Chicago, Illinois 60611, United States
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6
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Patterson AT, Styczynski MP. Rapid and Finely-Tuned Expression for Deployable Sensing Applications. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2023; 186:141-161. [PMID: 37316621 DOI: 10.1007/10_2023_223] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Organisms from across the tree of life have evolved highly efficient mechanisms for sensing molecules of interest using biomolecular machinery that can in turn be quite valuable for the development of biosensors. However, purification of such machinery for use in in vitro biosensors is costly, while the use of whole cells as in vivo biosensors often leads to long sensor response times and unacceptable sensitivity to the chemical makeup of the sample. Cell-free expression systems overcome these weaknesses by removing the requirements associated with maintaining living sensor cells, allowing for increased function in toxic environments and rapid sensor readout at a production cost that is often more reasonable than purification. Here, we focus on the challenge of implementing cell-free protein expression systems that meet the stringent criteria required for them to serve as the basis for field-deployable biosensors. Fine-tuning expression to meet these requirements can be achieved through careful selection of the sensing and output elements, as well as through optimization of reaction conditions via tuning of DNA/RNA concentrations, lysate preparation methods, and buffer conditions. Through careful sensor engineering, cell-free systems can continue to be successfully used for the production of tightly regulated, rapidly expressing genetic circuits for biosensors.
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Affiliation(s)
- Alexandra T Patterson
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Mark P Styczynski
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, GA, USA.
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7
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Gonzales D, Yandrapalli N, Robinson T, Zechner C, Tang TYD. Cell-Free Gene Expression Dynamics in Synthetic Cell Populations. ACS Synth Biol 2022; 11:205-215. [PMID: 35057626 PMCID: PMC8787815 DOI: 10.1021/acssynbio.1c00376] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Indexed: 11/29/2022]
Abstract
The ability to build synthetic cellular populations from the bottom-up provides the groundwork to realize minimal living tissues comprising single cells which can communicate and bridge scales into multicellular systems. Engineered systems made of synthetic micron-sized compartments and integrated reaction networks coupled with mathematical modeling can facilitate the design and construction of complex and multiscale chemical systems from the bottom-up. Toward this goal, we generated populations of monodisperse liposomes encapsulating cell-free expression systems (CFESs) using double-emulsion microfluidics and quantified transcription and translation dynamics within individual synthetic cells of the population using a fluorescent Broccoli RNA aptamer and mCherry protein reporter. CFE dynamics in bulk reactions were used to test different coarse-grained resource-limited gene expression models using model selection to obtain transcription and translation rate parameters by likelihood-based parameter estimation. The selected model was then applied to quantify cell-free gene expression dynamics in populations of synthetic cells. In combination, our experimental and theoretical approaches provide a statistically robust analysis of CFE dynamics in bulk and monodisperse synthetic cell populations. We demonstrate that compartmentalization of CFESs leads to different transcription and translation rates compared to bulk CFE and show that this is due to the semipermeable lipid membrane that allows the exchange of materials between the synthetic cells and the external environment.
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Affiliation(s)
- David
T. Gonzales
- Max
Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Center
for Systems Biology Dresden, 01307 Dresden, Germany
| | | | - Tom Robinson
- Max
Planck Institute of Colloids and Interfaces, 14476 Potsdam, Germany
| | - Christoph Zechner
- Max
Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Center
for Systems Biology Dresden, 01307 Dresden, Germany
- Physics
of Life, Cluster of Excellence, TU Dresden, 01603 Dresden, Germany
| | - T-Y. Dora Tang
- Max
Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany
- Center
for Systems Biology Dresden, 01307 Dresden, Germany
- Physics
of Life, Cluster of Excellence, TU Dresden, 01603 Dresden, Germany
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8
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Fackler N, Heijstra BD, Rasor BJ, Brown H, Martin J, Ni Z, Shebek KM, Rosin RR, Simpson SD, Tyo KE, Giannone RJ, Hettich RL, Tschaplinski TJ, Leang C, Brown SD, Jewett MC, Köpke M. Stepping on the Gas to a Circular Economy: Accelerating Development of Carbon-Negative Chemical Production from Gas Fermentation. Annu Rev Chem Biomol Eng 2021; 12:439-470. [PMID: 33872517 DOI: 10.1146/annurev-chembioeng-120120-021122] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Owing to rising levels of greenhouse gases in our atmosphere and oceans, climate change poses significant environmental, economic, and social challenges globally. Technologies that enable carbon capture and conversion of greenhouse gases into useful products will help mitigate climate change by enabling a new circular carbon economy. Gas fermentation usingcarbon-fixing microorganisms offers an economically viable and scalable solution with unique feedstock and product flexibility that has been commercialized recently. We review the state of the art of gas fermentation and discuss opportunities to accelerate future development and rollout. We discuss the current commercial process for conversion of waste gases to ethanol, including the underlying biology, challenges in process scale-up, and progress on genetic tool development and metabolic engineering to expand the product spectrum. We emphasize key enabling technologies to accelerate strain development for acetogens and other nonmodel organisms.
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Affiliation(s)
- Nick Fackler
- LanzaTech Inc., Skokie, Illinois 60077, USA; , , , , , ,
| | | | - Blake J Rasor
- Department of Chemical and Biological Engineering, Chemistry of Life Processes Institute, and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, USA; , , , , , ,
| | - Hunter Brown
- Department of Chemical and Biological Engineering, Chemistry of Life Processes Institute, and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, USA; , , , , , ,
| | - Jacob Martin
- Department of Chemical and Biological Engineering, Chemistry of Life Processes Institute, and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, USA; , , , , , ,
| | - Zhuofu Ni
- Department of Chemical and Biological Engineering, Chemistry of Life Processes Institute, and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, USA; , , , , , ,
| | - Kevin M Shebek
- Department of Chemical and Biological Engineering, Chemistry of Life Processes Institute, and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, USA; , , , , , ,
| | - Rick R Rosin
- LanzaTech Inc., Skokie, Illinois 60077, USA; , , , , , ,
| | - Séan D Simpson
- LanzaTech Inc., Skokie, Illinois 60077, USA; , , , , , ,
| | - Keith E Tyo
- Department of Chemical and Biological Engineering, Chemistry of Life Processes Institute, and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, USA; , , , , , ,
| | - Richard J Giannone
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA; ,
| | - Robert L Hettich
- Chemical Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA; ,
| | | | - Ching Leang
- LanzaTech Inc., Skokie, Illinois 60077, USA; , , , , , ,
| | - Steven D Brown
- LanzaTech Inc., Skokie, Illinois 60077, USA; , , , , , ,
| | - Michael C Jewett
- Department of Chemical and Biological Engineering, Chemistry of Life Processes Institute, and Center for Synthetic Biology, Northwestern University, Evanston, Illinois 60208, USA; , , , , , , .,Robert H. Lurie Comprehensive Cancer Center and Simpson Querrey Institute, Northwestern University, Chicago, Illinois 60611, USA
| | - Michael Köpke
- LanzaTech Inc., Skokie, Illinois 60077, USA; , , , , , ,
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9
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Batista AC, Soudier P, Kushwaha M, Faulon J. Optimising protein synthesis in cell‐free systems, a review. ENGINEERING BIOLOGY 2021; 5:10-19. [PMID: 36968650 PMCID: PMC9996726 DOI: 10.1049/enb2.12004] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 12/03/2020] [Accepted: 12/09/2020] [Indexed: 12/25/2022] Open
Abstract
Over the last decades, cell-free systems have been extensively used for in vitro protein expression. A vast range of protocols and cellular sources varying from prokaryotes and eukaryotes are now available for cell-free technology. However, exploiting the maximum capacity of cell free systems is not achieved by using traditional protocols. Here, what are the strategies and choices one can apply to optimise cell-free protein synthesis have been reviewed. These strategies provide robust and informative improvements regarding transcription, translation and protein folding which can later be used for the establishment of individual best cell-free reactions per lysate batch.
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Affiliation(s)
- Angelo C. Batista
- Université Paris‐Saclay INRAE AgroParisTech Micalis Institute Jouy‐en‐Josas France
| | - Paul Soudier
- Université Paris‐Saclay INRAE AgroParisTech Micalis Institute Jouy‐en‐Josas France
| | - Manish Kushwaha
- Université Paris‐Saclay INRAE AgroParisTech Micalis Institute Jouy‐en‐Josas France
| | - Jean‐Loup Faulon
- Université Paris‐Saclay INRAE AgroParisTech Micalis Institute Jouy‐en‐Josas France
- SYNBIOCHEM Center School of Chemistry Manchester Institute of Biotechnology The University of Manchester Manchester UK
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10
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Foster CJ, Wang L, Dinh HV, Suthers PF, Maranas CD. Building kinetic models for metabolic engineering. Curr Opin Biotechnol 2020; 67:35-41. [PMID: 33360621 DOI: 10.1016/j.copbio.2020.11.010] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 11/09/2020] [Accepted: 11/22/2020] [Indexed: 12/16/2022]
Abstract
Kinetic formalisms of metabolism link metabolic fluxes to enzyme levels, metabolite concentrations and their allosteric regulatory interactions. Though they require the identification of physiologically relevant values for numerous parameters, kinetic formalisms uniquely establish a mechanistic link across heterogeneous omics datasets and provide an overarching vantage point to effectively inform metabolic engineering strategies. Advances in computational power, gene annotation coverage, and formalism standardization have led to significant progress over the past few years. However, careful interpretation of model predictions, limited metabolic flux datasets, and assessment of parameter sensitivity remain as challenges. In this review we highlight fundamental considerations which influence model quality and prediction, advances in methodologies, and success stories of deploying kinetic models to guide metabolic engineering.
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Affiliation(s)
- Charles J Foster
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA
| | - Lin Wang
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA
| | - Hoang V Dinh
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, The Pennsylvania State University, Univesity Park, PA, USA
| | - Patrick F Suthers
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, The Pennsylvania State University, Univesity Park, PA, USA
| | - Costas D Maranas
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA, USA.
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11
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Adhikari A, Vilkhovoy M, Vadhin S, Lim HE, Varner JD. Effective Biophysical Modeling of Cell Free Transcription and Translation Processes. Front Bioeng Biotechnol 2020; 8:539081. [PMID: 33324619 PMCID: PMC7726328 DOI: 10.3389/fbioe.2020.539081] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 11/02/2020] [Indexed: 12/18/2022] Open
Abstract
Transcription and translation are at the heart of metabolism and signal transduction. In this study, we developed an effective biophysical modeling approach to simulate transcription and translation processes. The model, composed of coupled ordinary differential equations, was tested by comparing simulations of two cell free synthetic circuits with experimental measurements generated in this study. First, we considered a simple circuit in which sigma factor 70 induced the expression of green fluorescent protein. This relatively simple case was then followed by a more complex negative feedback circuit in which two control genes were coupled to the expression of a third reporter gene, green fluorescent protein. Many of the model parameters were estimated from previous biophysical studies in the literature, while the remaining unknown model parameters for each circuit were estimated by minimizing the difference between model simulations and messenger RNA (mRNA) and protein measurements generated in this study. In particular, either parameter estimates from published studies were used directly, or characteristic values found in the literature were used to establish feasible ranges for the parameter estimation problem. In order to perform a detailed analysis of the influence of individual model parameters on the expression dynamics of each circuit, global sensitivity analysis was used. Taken together, the effective biophysical modeling approach captured the expression dynamics, including the transcription dynamics, for the two synthetic cell free circuits. While, we considered only two circuits here, this approach could potentially be extended to simulate other genetic circuits in both cell free and whole cell biomolecular applications as the equations governing the regulatory control functions are modular and easily modifiable. The model code, parameters, and analysis scripts are available for download under an MIT software license from the Varnerlab GitHub repository.
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Affiliation(s)
- Abhinav Adhikari
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
| | - Michael Vilkhovoy
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
| | - Sandra Vadhin
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
| | - Ha Eun Lim
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
| | - Jeffrey D Varner
- Robert Frederick Smith School of Chemical and Biomolecular Engineering, College of Engineering, Cornell University, Ithaca, NY, United States
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12
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Lavickova B, Laohakunakorn N, Maerkl SJ. A partially self-regenerating synthetic cell. Nat Commun 2020; 11:6340. [PMID: 33311509 PMCID: PMC7733450 DOI: 10.1038/s41467-020-20180-6] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 11/16/2020] [Indexed: 01/16/2023] Open
Abstract
Self-regeneration is a fundamental function of all living systems. Here we demonstrate partial molecular self-regeneration in a synthetic cell. By implementing a minimal transcription-translation system within microfluidic reactors, the system is able to regenerate essential protein components from DNA templates and sustain synthesis activity for over a day. By quantitating genotype-phenotype relationships combined with computational modeling we find that minimizing resource competition and optimizing resource allocation are both critically important for achieving robust system function. With this understanding, we achieve simultaneous regeneration of multiple proteins by determining the required DNA ratios necessary for sustained self-regeneration. This work introduces a conceptual and experimental framework for the development of a self-replicating synthetic cell.
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Affiliation(s)
- Barbora Lavickova
- Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Nadanai Laohakunakorn
- Institute of Quantitative Biology, Biochemistry, and Biotechnology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Sebastian J Maerkl
- Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
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13
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Müller J, Siemann-Herzberg M, Takors R. Modeling Cell-Free Protein Synthesis Systems-Approaches and Applications. Front Bioeng Biotechnol 2020; 8:584178. [PMID: 33195146 PMCID: PMC7655533 DOI: 10.3389/fbioe.2020.584178] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 09/29/2020] [Indexed: 01/03/2023] Open
Abstract
In vitro systems are ideal setups to investigate the basic principles of biochemical reactions and subsequently the bricks of life. Cell-free protein synthesis (CFPS) systems mimic the transcription and translation processes of whole cells in a controlled environment and allow the detailed study of single components and reaction networks. In silico studies of CFPS systems help us to understand interactions and to identify limitations and bottlenecks in those systems. Black-box models laid the foundation for understanding the production and degradation dynamics of macromolecule components such as mRNA, ribosomes, and proteins. Subsequently, more sophisticated models revealed shortages in steps such as translation initiation and tRNA supply and helped to partially overcome these limitations. Currently, the scope of CFPS modeling has broadened to various applications, ranging from the screening of kinetic parameters to the stochastic analysis of liposome-encapsulated CFPS systems and the assessment of energy supply properties in combination with flux balance analysis (FBA).
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Affiliation(s)
| | | | - Ralf Takors
- Institute of Biochemical Engineering, University of Stuttgart, Stuttgart, Germany
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Laohakunakorn N. Cell-Free Systems: A Proving Ground for Rational Biodesign. Front Bioeng Biotechnol 2020; 8:788. [PMID: 32793570 PMCID: PMC7393481 DOI: 10.3389/fbioe.2020.00788] [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: 04/30/2020] [Accepted: 06/22/2020] [Indexed: 11/13/2022] Open
Abstract
Cell-free gene expression systems present an alternative approach to synthetic biology, where biological gene expression is harnessed inside non-living, in vitro biochemical reactions. Taking advantage of a plethora of recent experimental innovations, they easily overcome certain challenges for computer-aided biological design. For instance, their open nature renders all their components directly accessible, greatly facilitating model construction and validation. At the same time, these systems present their own unique difficulties, such as limited reaction lifetimes and lack of homeostasis. In this Perspective, I propose that cell-free systems are an ideal proving ground to test rational biodesign strategies, as demonstrated by a small but growing number of examples of model-guided, forward engineered cell-free biosystems. It is likely that advances gained from this approach will contribute to our efforts to more reliably and systematically engineer both cell-free as well as living cellular systems for useful applications.
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Affiliation(s)
- Nadanai Laohakunakorn
- School of Biological Sciences, Institute of Quantitative Biology, Biochemistry, and Biotechnology, University of Edinburgh, Edinburgh, United Kingdom
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Abstract
Cell-free systems are a widely used research tool in systems and synthetic biology and a promising platform for manufacturing of proteins and chemicals. In the past, cell-free biology was primarily used to better understand fundamental biochemical processes. Notably, E. coli cell-free extracts were used in the 1960s to decipher the sequencing of the genetic code. Since then, the transcription and translation capabilities of cell-free systems have been repeatedly optimized to improve energy efficiency and product yield. Today, cell-free systems, in combination with the rise of synthetic biology, have taken on a new role as a promising technology for just-in-time manufacturing of therapeutically important biologics and high-value small molecules. They have also been implemented at an industrial scale for the production of antibodies and cytokines. In this review, we discuss the evolution of cell-free technologies, in particular advancements in extract preparation, cell-free protein synthesis, and cell-free metabolic engineering applications. We then conclude with a discussion of the mathematical modeling of cell-free systems. Mathematical modeling of cell-free processes could be critical to addressing performance bottlenecks and estimating the costs of cell-free manufactured products.
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