1
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Harmer Z, Thompson JC, Cole DL, Venturelli OS, Zavala VM, McClean MN. Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro. ACS Synth Biol 2024; 13:1424-1433. [PMID: 38684225 PMCID: PMC11106771 DOI: 10.1021/acssynbio.3c00761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 03/31/2024] [Accepted: 04/18/2024] [Indexed: 05/02/2024]
Abstract
The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation, we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive split transcription factors in the budding yeast, Saccharomyces cerevisiae. We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering.
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Affiliation(s)
- Zachary
P. Harmer
- Department
of Biomedical Engineering, University of
Wisconsin−Madison, Madison, Wisconsin 53706, United States
| | - Jaron C. Thompson
- Department
of Chemical and Biological Engineering, University of Wisconsin−Madison, Madison, Wisconsin 53706, United States
- Department
of Biochemistry, University of Wisconsin−Madison, Madison, Wisconsin 53706, United States
| | - David L. Cole
- Department
of Chemical and Biological Engineering, University of Wisconsin−Madison, Madison, Wisconsin 53706, United States
| | - Ophelia S. Venturelli
- Department
of Biomedical Engineering, University of
Wisconsin−Madison, Madison, Wisconsin 53706, United States
- Department
of Chemical and Biological Engineering, University of Wisconsin−Madison, Madison, Wisconsin 53706, United States
- Department
of Biochemistry, University of Wisconsin−Madison, Madison, Wisconsin 53706, United States
- Department
of Bacteriology, University of Wisconsin−Madison, Madison, Wisconsin 53706, United States
| | - Victor M. Zavala
- Department
of Chemical and Biological Engineering, University of Wisconsin−Madison, Madison, Wisconsin 53706, United States
- Mathematics
and Computer Science Division, Argonne National
Laboratory, Lemont, Illinois 60439. United States
| | - Megan N. McClean
- Department
of Biomedical Engineering, University of
Wisconsin−Madison, Madison, Wisconsin 53706, United States
- University
of Wisconsin Carbone Cancer Center, University
of Wisconsin School of Medicine and Public Health, Madison, Wisconsin 53706, United States
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2
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Zakaria FR, Chen CY, Li J, Wang S, Payne GF, Bentley WE. Redox active plant phenolic, acetosyringone, for electrogenetic signaling. Sci Rep 2024; 14:9666. [PMID: 38671069 PMCID: PMC11053109 DOI: 10.1038/s41598-024-60191-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 04/19/2024] [Indexed: 04/28/2024] Open
Abstract
Redox is a unique, programmable modality capable of bridging communication between biology and electronics. Previous studies have shown that the E. coli redox-responsive OxyRS regulon can be re-wired to accept electrochemically generated hydrogen peroxide (H2O2) as an inducer of gene expression. Here we report that the redox-active phenolic plant signaling molecule acetosyringone (AS) can also induce gene expression from the OxyRS regulon. AS must be oxidized, however, as the reduced state present under normal conditions cannot induce gene expression. Thus, AS serves as a "pro-signaling molecule" that can be activated by its oxidation-in our case by application of oxidizing potential to an electrode. We show that the OxyRS regulon is not induced electrochemically if the imposed electrode potential is in the mid-physiological range. Electronically sliding the applied potential to either oxidative or reductive extremes induces this regulon but through different mechanisms: reduction of O2 to form H2O2 or oxidation of AS. Fundamentally, this work reinforces the emerging concept that redox signaling depends more on molecular activities than molecular structure. From an applications perspective, the creation of an electronically programmed "pro-signal" dramatically expands the toolbox for electronic control of biological responses in microbes, including in complex environments, cell-based materials, and biomanufacturing.
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Affiliation(s)
- Fauziah Rahma Zakaria
- Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA
- Institute for Bioscience and Biotechnology Research, Rockville, MD, USA
- Robert E. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD, USA
| | - Chen-Yu Chen
- Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA
- Institute for Bioscience and Biotechnology Research, Rockville, MD, USA
- Robert E. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD, USA
| | - Jinyang Li
- Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA
- Institute for Bioscience and Biotechnology Research, Rockville, MD, USA
- Robert E. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD, USA
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Sally Wang
- Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA
- Institute for Bioscience and Biotechnology Research, Rockville, MD, USA
- Robert E. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD, USA
| | - Gregory F Payne
- Institute for Bioscience and Biotechnology Research, Rockville, MD, USA.
- Robert E. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD, USA.
| | - William E Bentley
- Fischell Department of Bioengineering, University of Maryland, College Park, MD, USA.
- Institute for Bioscience and Biotechnology Research, Rockville, MD, USA.
- Robert E. Fischell Institute for Biomedical Devices, University of Maryland, College Park, MD, USA.
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3
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Benisch M, Aoki SK, Khammash M. Unlocking the potential of optogenetics in microbial applications. Curr Opin Microbiol 2024; 77:102404. [PMID: 38039932 DOI: 10.1016/j.mib.2023.102404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 09/07/2023] [Accepted: 11/06/2023] [Indexed: 12/03/2023]
Abstract
Optogenetics is a powerful approach that enables researchers to use light to dynamically manipulate cellular behavior. Since the first published use of optogenetics in synthetic biology, the field has expanded rapidly, yielding a vast array of tools and applications. Despite its immense potential for achieving high spatiotemporal precision, optogenetics has predominantly been employed as a substitute for conventional chemical inducers. In this short review, we discuss key features of microbial optogenetics and highlight applications for understanding biology, cocultures, bioproduction, biomaterials, and therapeutics, in which optogenetics is more fully utilized to realize goals not previously possible by other methods.
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Affiliation(s)
- Moritz Benisch
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Schanzenstrasse 44, 4056 Basel, Switzerland.
| | - Stephanie K Aoki
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Schanzenstrasse 44, 4056 Basel, Switzerland.
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Schanzenstrasse 44, 4056 Basel, Switzerland.
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4
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Huang Dennis Z, Benman W, Dong L, Bugaj LJ. Rapid Optogenetic Clustering in the Cytoplasm with BcLOVclust. J Mol Biol 2024; 436:168452. [PMID: 38246410 DOI: 10.1016/j.jmb.2024.168452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 01/10/2024] [Accepted: 01/17/2024] [Indexed: 01/23/2024]
Abstract
Protein clustering is a powerful form of optogenetic control, yet remarkably few proteins are known to oligomerize with light. Recently, the photoreceptor BcLOV4 was found to form protein clusters in mammalian cells in response to blue light, although clustering coincided with its translocation to the plasma membrane, potentially constraining its application as an optogenetic clustering module. Herein we identify key amino acids that couple BcLOV4 clustering to membrane binding, allowing us to engineer a variant that clusters in the cytoplasm and does not associate with the membrane in response to blue light. This variant-called BcLOVclust-clustered over many cycles with substantially faster clustering and de-clustering kinetics compared to the widely used optogenetic clustering protein Cry2. The magnitude of clustering could be strengthened by appending an intrinsically disordered region from the fused in sarcoma (FUS) protein, or by selecting the appropriate fluorescent protein to which it was fused. Like wt BcLOV4, BcLOVclust activity was sensitive to temperature: light-induced clusters spontaneously dissolved at a rate that increased with temperature despite constant illumination. At low temperatures, BcLOVclust and Cry2 could be multiplexed in the same cells, allowing light control of independent protein condensates. BcLOVclust could also be applied to control signaling proteins and stress granules in mammalian cells. While its usage is currently best suited in cells and organisms that can be cultured below ∼30 °C, a deeper understanding of BcLOVclust thermal response will further enable its use at physiological mammalian temperatures.
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Affiliation(s)
- Zikang Huang Dennis
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William Benman
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Liang Dong
- Department of Biochemistry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lukasz J Bugaj
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Abramson Cancer Center, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute of Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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5
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Tague N, Coriano-Ortiz C, Sheets MB, Dunlop MJ. Light-inducible protein degradation in E. coli with the LOVdeg tag. eLife 2024; 12:RP87303. [PMID: 38270583 PMCID: PMC10945698 DOI: 10.7554/elife.87303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2024] Open
Abstract
Molecular tools for optogenetic control allow for spatial and temporal regulation of cell behavior. In particular, light-controlled protein degradation is a valuable mechanism of regulation because it can be highly modular, used in tandem with other control mechanisms, and maintain functionality throughout growth phases. Here, we engineered LOVdeg, a tag that can be appended to a protein of interest for inducible degradation in Escherichia coli using blue light. We demonstrate the modularity of LOVdeg by using it to tag a range of proteins, including the LacI repressor, CRISPRa activator, and the AcrB efflux pump. Additionally, we demonstrate the utility of pairing the LOVdeg tag with existing optogenetic tools to enhance performance by developing a combined EL222 and LOVdeg system. Finally, we use the LOVdeg tag in a metabolic engineering application to demonstrate post-translational control of metabolism. Together, our results highlight the modularity and functionality of the LOVdeg tag system and introduce a powerful new tool for bacterial optogenetics.
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Affiliation(s)
- Nathan Tague
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Biological Design Center, Boston UniversityBostonUnited States
| | - Cristian Coriano-Ortiz
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Biological Design Center, Boston UniversityBostonUnited States
| | - Michael B Sheets
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Biological Design Center, Boston UniversityBostonUnited States
| | - Mary J Dunlop
- Department of Biomedical Engineering, Boston UniversityBostonUnited States
- Biological Design Center, Boston UniversityBostonUnited States
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6
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Harmer ZP, Thompson JC, Cole DL, Zavala VM, McClean MN. Dynamic Multiplexed Control and Modeling of Optogenetic Systems Using the High-Throughput Optogenetic Platform, Lustro. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.19.572411. [PMID: 38187522 PMCID: PMC10769237 DOI: 10.1101/2023.12.19.572411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
The ability to control cellular processes using optogenetics is inducer-limited, with most optogenetic systems responding to blue light. To address this limitation we leverage an integrated framework combining Lustro, a powerful high-throughput optogenetics platform, and machine learning tools to enable multiplexed control over blue light-sensitive optogenetic systems. Specifically, we identify light induction conditions for sequential activation as well as preferential activation and switching between pairs of light-sensitive spit transcription factors in the budding yeast, Saccharomyces cerevisiae . We use the high-throughput data generated from Lustro to build a Bayesian optimization framework that incorporates data-driven learning, uncertainty quantification, and experimental design to enable the prediction of system behavior and the identification of optimal conditions for multiplexed control. This work lays the foundation for designing more advanced synthetic biological circuits incorporating optogenetics, where multiple circuit components can be controlled using designer light induction programs, with broad implications for biotechnology and bioengineering. Graphical abstract
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7
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Tague N, Coriano-Ortiz C, Sheets MB, Dunlop MJ. Light inducible protein degradation in E. coli with the LOVdeg tag. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.25.530042. [PMID: 36865169 PMCID: PMC9980293 DOI: 10.1101/2023.02.25.530042] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2023]
Abstract
Molecular tools for optogenetic control allow for spatial and temporal regulation of cell behavior. In particular, light controlled protein degradation is a valuable mechanism of regulation because it can be highly modular, used in tandem with other control mechanisms, and maintain functionality throughout growth phases. Here, we engineered LOVdeg, a tag that can be appended to a protein of interest for inducible degradation in Escherichia coli using blue light. We demonstrate the modularity of LOVdeg by using it to tag a range of proteins, including the LacI repressor, CRISPRa activator, and the AcrB efflux pump. Additionally, we demonstrate the utility of pairing the LOVdeg tag with existing optogenetic tools to enhance performance by developing a combined EL222 and LOVdeg system. Finally, we use the LOVdeg tag in a metabolic engineering application to demonstrate post-translational control of metabolism. Together, our results highlight the modularity and functionality of the LOVdeg tag system, and introduce a powerful new tool for bacterial optogenetics.
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8
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Kumar S, Anastassov S, Aoki SK, Falkenstein J, Chang CH, Frei T, Buchmann P, Argast P, Khammash M. Diya - A universal light illumination platform for multiwell plate cultures. iScience 2023; 26:107862. [PMID: 37810238 PMCID: PMC10551653 DOI: 10.1016/j.isci.2023.107862] [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] [Received: 03/28/2023] [Revised: 07/25/2023] [Accepted: 09/06/2023] [Indexed: 10/10/2023] Open
Abstract
Recent progress in protein engineering has established optogenetics as one of the leading external non-invasive stimulation strategies, with many optogenetic tools being designed for in vivo operation. Characterization and optimization of these tools require a high-throughput and versatile light delivery system targeting micro-titer culture volumes. Here, we present a universal light illumination platform - Diya, compatible with a wide range of cell culture plates and dishes. Diya hosts specially designed features ensuring active thermal management, homogeneous illumination, and minimal light bleedthrough. It offers light induction programming via a user-friendly custom-designed GUI. Through extensive characterization experiments with multiple optogenetic tools in diverse model organisms (bacteria, yeast, and human cell lines), we show that Diya maintains viable conditions for cell cultures undergoing light induction. Finally, we demonstrate an optogenetic strategy for in vivo biomolecular controller operation. With a custom-designed antithetic integral feedback circuit, we exhibit robust perfect adaptation and light-controlled set-point variation using Diya.
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Affiliation(s)
- Sant Kumar
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Stanislav Anastassov
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Stephanie K. Aoki
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Johannes Falkenstein
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Ching-Hsiang Chang
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Timothy Frei
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Peter Buchmann
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Paul Argast
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058 Basel, Switzerland
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9
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Klumpe HE, Lugagne JB, Khalil AS, Dunlop MJ. Deep Neural Networks for Predicting Single-Cell Responses and Probability Landscapes. ACS Synth Biol 2023; 12:2367-2381. [PMID: 37467372 DOI: 10.1021/acssynbio.3c00203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/21/2023]
Abstract
Engineering biology relies on the accurate prediction of cell responses. However, making these predictions is challenging for a variety of reasons, including the stochasticity of biochemical reactions, variability between cells, and incomplete information about underlying biological processes. Machine learning methods, which can model diverse input-output relationships without requiring a priori mechanistic knowledge, are an ideal tool for this task. For example, such approaches can be used to predict gene expression dynamics given time-series data of past expression history. To explore this application, we computationally simulated single-cell responses, incorporating different sources of noise and alternative genetic circuit designs. We showed that deep neural networks trained on these simulated data were able to correctly infer the underlying dynamics of a cell response even in the presence of measurement noise and stochasticity in the biochemical reactions. The training set size and the amount of past data provided as inputs both affected prediction quality, with cascaded genetic circuits that introduce delays requiring more past data. We also tested prediction performance on a bistable auto-activation circuit, finding that our initial method for predicting a single trajectory was fundamentally ill-suited for multimodal dynamics. To address this, we updated the network architecture to predict the entire distribution of future states, showing it could accurately predict bimodal expression distributions. Overall, these methods can be readily applied to the diverse prediction tasks necessary to predict and control a variety of biological circuits, a key aspect of many synthetic biology applications.
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Affiliation(s)
- Heidi E Klumpe
- Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
- Biological Design Center, Boston University, Boston, Massachusetts 02215, United States
| | - Jean-Baptiste Lugagne
- Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
- Biological Design Center, Boston University, Boston, Massachusetts 02215, United States
| | - Ahmad S Khalil
- Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
- Biological Design Center, Boston University, Boston, Massachusetts 02215, United States
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02115, United States
| | - Mary J Dunlop
- Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
- Biological Design Center, Boston University, Boston, Massachusetts 02215, United States
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10
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Alba Burbano D, Cardiff RAL, Tickman BI, Kiattisewee C, Maranas CJ, Zalatan JG, Carothers JM. Engineering activatable promoters for scalable and multi-input CRISPRa/i circuits. Proc Natl Acad Sci U S A 2023; 120:e2220358120. [PMID: 37463216 PMCID: PMC10374173 DOI: 10.1073/pnas.2220358120] [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: 11/30/2022] [Accepted: 06/13/2023] [Indexed: 07/20/2023] Open
Abstract
Dynamic, multi-input gene regulatory networks (GRNs) are ubiquitous in nature. Multilayer CRISPR-based genetic circuits hold great promise for building GRNs akin to those found in naturally occurring biological systems. We develop an approach for creating high-performing activatable promoters that can be assembled into deep, wide, and multi-input CRISPR-activation and -interference (CRISPRa/i) GRNs. By integrating sequence-based design and in vivo screening, we engineer activatable promoters that achieve up to 1,000-fold dynamic range in an Escherichia coli-based cell-free system. These components enable CRISPRa GRNs that are six layers deep and four branches wide. We show the generalizability of the promoter engineering workflow by improving the dynamic range of the light-dependent EL222 optogenetic system from 6-fold to 34-fold. Additionally, high dynamic range promoters enable CRISPRa systems mediated by small molecules and protein-protein interactions. We apply these tools to build input-responsive CRISPRa/i GRNs, including feedback loops, logic gates, multilayer cascades, and dynamic pulse modulators. Our work provides a generalizable approach for the design of high dynamic range activatable promoters and enables classes of gene regulatory functions in cell-free systems.
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Affiliation(s)
- Diego Alba Burbano
- Department of Chemical Engineering, University of Washington, Seattle, WA98195
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
| | - Ryan A. L. Cardiff
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Benjamin I. Tickman
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Cholpisit Kiattisewee
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Cassandra J. Maranas
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Jesse G. Zalatan
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
- Department of Chemistry, University of Washington, Seattle, WA98195
| | - James M. Carothers
- Department of Chemical Engineering, University of Washington, Seattle, WA98195
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
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11
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Sweeney K, McClean MN. Transcription factor localization dynamics and DNA binding drive distinct promoter interpretations. Cell Rep 2023; 42:112426. [PMID: 37087734 DOI: 10.1016/j.celrep.2023.112426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 02/17/2023] [Accepted: 04/07/2023] [Indexed: 04/24/2023] Open
Abstract
Environmental information may be encoded in the temporal dynamics of transcription factor (TF) activation and subsequently decoded by gene promoters to enact stimulus-specific gene expression programs. Previous studies of this behavior focused on the encoding and decoding of information in TF nuclear localization dynamics, yet cells control the activity of TFs in myriad ways, including by regulating their ability to bind DNA. Here, we use light-controlled mutants of the yeast TF Msn2 as a model system to investigate how promoter decoding of TF localization dynamics is affected by changes in the ability of the TF to bind DNA. We find that yeast promoters directly decode the light-controlled localization dynamics of Msn2 and that the effects of changing Msn2 affinity on that decoding behavior are highly promoter dependent, illustrating how cells could regulate TF localization dynamics and DNA binding in concert for improved control of gene expression.
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Affiliation(s)
- Kieran Sweeney
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA
| | - Megan N McClean
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA; University of Wisconsin Carbone Cancer Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
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12
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Benisch M, Benzinger D, Kumar S, Hu H, Khammash M. Optogenetic closed-loop feedback control of the unfolded protein response optimizes protein production. Metab Eng 2023; 77:32-40. [PMID: 36914087 DOI: 10.1016/j.ymben.2023.03.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 03/03/2023] [Accepted: 03/05/2023] [Indexed: 03/13/2023]
Abstract
In biotechnological protein production processes, the onset of protein unfolding at high gene expression levels leads to diminishing production yields and reduced efficiency. Here we show that in silico closed-loop optogenetic feedback control of the unfolded protein response (UPR) in S. cerevisiae clamps gene expression rates at intermediate near-optimal values, leading to significantly improved product titers. Specifically, in a fully-automated custom-built 1L-photobioreactor, we used a cybergenetic control system to steer the level of UPR in yeast to a desired set-point by optogenetically modulating the expression of α-amylase, a hard-to-fold protein, based on real-time feedback measurements of the UPR, resulting in 60% higher product titers. This proof-of-concept study paves the way for advanced optimal biotechnology production strategies that diverge from and complement current strategies employing constitutive overexpression or genetically hardwired circuits.
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Affiliation(s)
- Moritz Benisch
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Dirk Benzinger
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland; The Francis Crick Institute, 1 Midland Road, London, NW1 1AT, UK
| | - Sant Kumar
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Hanrong Hu
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland.
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13
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Pouzet S, Cruz-Ramón J, Le Bec M, Cordier C, Banderas A, Barral S, Castaño-Cerezo S, Lautier T, Truan G, Hersen P. Optogenetic control of beta-carotene bioproduction in yeast across multiple lab-scales. Front Bioeng Biotechnol 2023; 11:1085268. [PMID: 36814715 PMCID: PMC9939774 DOI: 10.3389/fbioe.2023.1085268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 01/16/2023] [Indexed: 02/09/2023] Open
Abstract
Optogenetics arises as a valuable tool to precisely control genetic circuits in microbial cell factories. Light control holds the promise of optimizing bioproduction methods and maximizing yields, but its implementation at different steps of the strain development process and at different culture scales remains challenging. In this study, we aim to control beta-carotene bioproduction using optogenetics in Saccharomyces cerevisiae and investigate how its performance translates across culture scales. We built four lab-scale illumination devices, each handling different culture volumes, and each having specific illumination characteristics and cultivating conditions. We evaluated optogenetic activation and beta-carotene production across devices and optimized them both independently. Then, we combined optogenetic induction and beta-carotene production to make a light-inducible beta-carotene producer strain. This was achieved by placing the transcription of the bifunctional lycopene cyclase/phytoene synthase CrtYB under the control of the pC120 optogenetic promoter regulated by the EL222-VP16 light-activated transcription factor, while other carotenogenic enzymes (CrtI, CrtE, tHMG) were expressed constitutively. We show that illumination, culture volume and shaking impact differently optogenetic activation and beta-carotene production across devices. This enabled us to determine the best culture conditions to maximize light-induced beta-carotene production in each of the devices. Our study exemplifies the stakes of scaling up optogenetics in devices of different lab scales and sheds light on the interplays and potential conflicts between optogenetic control and metabolic pathway efficiency. As a general principle, we propose that it is important to first optimize both components of the system independently, before combining them into optogenetic producing strains to avoid extensive troubleshooting. We anticipate that our results can help designing both strains and devices that could eventually lead to larger scale systems in an effort to bring optogenetics to the industrial scale.
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Affiliation(s)
- Sylvain Pouzet
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France
| | - Jessica Cruz-Ramón
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France
| | - Matthias Le Bec
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France
| | - Céline Cordier
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France
| | - Alvaro Banderas
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France
| | - Simon Barral
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France
| | - Sara Castaño-Cerezo
- Toulouse Biotechnology Institute, Université de Toulouse, Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche pour l′Agriculture, l′Alimentation et l′Environnement (INRAE), Institut National des Sciences Appliquées (INSA), Toulouse, France
| | - Thomas Lautier
- Toulouse Biotechnology Institute, Université de Toulouse, Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche pour l′Agriculture, l′Alimentation et l′Environnement (INRAE), Institut National des Sciences Appliquées (INSA), Toulouse, France,CNRS@CREATE, Singapore Institute of Food and Biotechnology Innovation, Agency for Science Technology and Research, Singapore, Singapore
| | - Gilles Truan
- Toulouse Biotechnology Institute, Université de Toulouse, Centre National de la Recherche Scientifique (CNRS), Institut National de Recherche pour l′Agriculture, l′Alimentation et l′Environnement (INRAE), Institut National des Sciences Appliquées (INSA), Toulouse, France
| | - Pascal Hersen
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, Paris, France,*Correspondence: Pascal Hersen,
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14
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Gutiérrez Mena J, Kumar S, Khammash M. Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback. Nat Commun 2022; 13:4808. [PMID: 35973993 PMCID: PMC9381578 DOI: 10.1038/s41467-022-32392-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 07/29/2022] [Indexed: 12/19/2022] Open
Abstract
Communities of microbes play important roles in natural environments and hold great potential for deploying division-of-labor strategies in synthetic biology and bioproduction. However, the difficulty of controlling the composition of microbial consortia over time hinders their optimal use in many applications. Here, we present a fully automated, high-throughput platform that combines real-time measurements and computer-controlled optogenetic modulation of bacterial growth to implement precise and robust compositional control of a two-strain E. coli community. In addition, we develop a general framework for dynamic modeling of synthetic genetic circuits in the physiological context of E. coli and use a host-aware model to determine the optimal control parameters of our closed-loop compositional control system. Our platform succeeds in stabilizing the strain ratio of multiple parallel co-cultures at arbitrary levels and in changing these targets over time, opening the door for the implementation of dynamic compositional programs in synthetic bacterial communities.
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Affiliation(s)
- Joaquín Gutiérrez Mena
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Sant Kumar
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland.
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15
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Harmer ZP, McClean MN. Evaluation of Benzinger et al.: Optogenetic circuits for dynamic signal processing. Cell Syst 2022; 13:347-348. [PMID: 35588696 DOI: 10.1016/j.cels.2022.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
One snapshot of the peer review process for "Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression" (Benzinger et al., 2022).
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Affiliation(s)
- Zachary P Harmer
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA; Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA; University of Wisconsin Carbone Cancer Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Megan N McClean
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI, USA; Cellular and Molecular Biology Graduate Program, University of Wisconsin-Madison, Madison, WI, USA; University of Wisconsin Carbone Cancer Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
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