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Anastassov S, Filo M, Khammash M. Inteins: A Swiss army knife for synthetic biology. Biotechnol Adv 2024; 73:108349. [PMID: 38552727 DOI: 10.1016/j.biotechadv.2024.108349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2023] [Revised: 03/21/2024] [Accepted: 03/23/2024] [Indexed: 04/13/2024]
Abstract
Inteins are proteins found in nature that execute protein splicing. Among them, split inteins stand out for their versatility and adaptability, presenting creative solutions for addressing intricate challenges in various biological applications. Their exquisite attributes, including compactness, reliability, orthogonality, low toxicity, and irreversibility, make them of interest to various fields including synthetic biology, biotechnology and biomedicine. In this review, we delve into the inherent challenges of using inteins, present approaches for overcoming these challenges, and detail their reliable use for specific cellular tasks. We will discuss the use of conditional inteins in areas like cancer therapy, drug screening, patterning, infection treatment, diagnostics and biocontainment. Additionally, we will underscore the potential of inteins in executing basic logical operations with practical implications. We conclude by showcasing their potential in crafting complex genetic circuits for performing computations and feedback control that achieves robust perfect adaptation.
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Affiliation(s)
- Stanislav Anastassov
- Department of Biosystems Science and Engineering, ETH Zürich, Basel 4056, Switzerland
| | - Maurice Filo
- Department of Biosystems Science and Engineering, ETH Zürich, Basel 4056, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering, ETH Zürich, Basel 4056, Switzerland.
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2
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Kelly AR, Glover DJ. Information Transmission through Biotic-Abiotic Interfaces to Restore or Enhance Human Function. ACS APPLIED BIO MATERIALS 2024; 7:3605-3628. [PMID: 38729914 DOI: 10.1021/acsabm.4c00435] [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] [Indexed: 05/12/2024]
Abstract
Advancements in reliable information transfer across biotic-abiotic interfaces have enabled the restoration of lost human function. For example, communication between neuronal cells and electrical devices restores the ability to walk to a tetraplegic patient and vision to patients blinded by retinal disease. These impactful medical achievements are aided by tailored biotic-abiotic interfaces that maximize information transfer fidelity by considering the physical properties of the underlying biological and synthetic components. This Review develops a modular framework to define and describe the engineering of biotic and abiotic components as well as the design of interfaces to facilitate biotic-abiotic information transfer using light or electricity. Delineating the properties of the biotic, interface, and abiotic components that enable communication can serve as a guide for future research in this highly interdisciplinary field. Application of synthetic biology to engineer light-sensitive proteins has facilitated the control of neural signaling and the restoration of rudimentary vision after retinal blindness. Electrophysiological methodologies that use brain-computer interfaces and stimulating implants to bypass spinal column injuries have led to the rehabilitation of limb movement and walking ability. Cellular interfacing methodologies and on-chip learning capability have been made possible by organic transistors that mimic the information processing capacity of neurons. The collaboration of molecular biologists, material scientists, and electrical engineers in the emerging field of biotic-abiotic interfacing will lead to the development of prosthetics capable of responding to thought and experiencing touch sensation via direct integration into the human nervous system. Further interdisciplinary research will improve electrical and optical interfacing technologies for the restoration of vision, offering greater visual acuity and potentially color vision in the near future.
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Affiliation(s)
- Alexander R Kelly
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Dominic J Glover
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, NSW 2052, Australia
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3
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Armbruster A, Mohamed AM, Phan HT, Weber W. Lighting the way: recent developments and applications in molecular optogenetics. Curr Opin Biotechnol 2024; 87:103126. [PMID: 38554641 DOI: 10.1016/j.copbio.2024.103126] [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: 12/18/2023] [Revised: 02/27/2024] [Accepted: 03/08/2024] [Indexed: 04/02/2024]
Abstract
Molecular optogenetics utilizes genetically encoded, light-responsive protein switches to control the function of molecular processes. Over the last two years, there have been notable advances in the development of novel optogenetic switches, their utilization in elucidating intricate signaling pathways, and their progress toward practical applications in biotechnological processes, material sciences, and therapeutic applications. In this review, we discuss these areas, offer insights into recent developments, and contemplate future directions.
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Affiliation(s)
- Anja Armbruster
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123 Saarbrücken, Germany; CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, Schänzlestr. 18, 79104 Freiburg, Germany; Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104 Freiburg, Germany
| | - Asim Me Mohamed
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123 Saarbrücken, Germany
| | - Hoang T Phan
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123 Saarbrücken, Germany
| | - Wilfried Weber
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123 Saarbrücken, Germany; CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, Schänzlestr. 18, 79104 Freiburg, Germany; Saarland University, Department of Materials Science and Engineering, Campus D2 2, 66123 Saarbrücken, Germany.
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Kinet R, Richelle A, Colle M, Demaegd D, von Stosch M, Sanders M, Sehrt H, Delvigne F, Goffin P. Giving the cells what they need when they need it: Biosensor-based feeding control. Biotechnol Bioeng 2024; 121:1271-1283. [PMID: 38258490 DOI: 10.1002/bit.28657] [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: 07/28/2023] [Revised: 12/11/2023] [Accepted: 01/04/2024] [Indexed: 01/24/2024]
Abstract
"Giving the cells exactly what they need, when they need it" is the core idea behind the proposed bioprocess control strategy: operating bioprocess based on the physiological behavior of the microbial population rather than exclusive monitoring of environmental parameters. We are envisioning to achieve this through the use of genetically encoded biosensors combined with online flow cytometry (FCM) to obtain a time-dependent "physiological fingerprint" of the population. We developed a biosensor based on the glnA promoter (glnAp) and applied it for monitoring the nitrogen-related nutritional state of Escherichia coli. The functionality of the biosensor was demonstrated through multiple cultivation runs performed at various scales-from microplate to 20 L bioreactor. We also developed a fully automated bioreactor-FCM interface for on-line monitoring of the microbial population. Finally, we validated the proposed strategy by performing a fed-batch experiment where the biosensor signal is used as the actuator for a nitrogen feeding feedback control. This new generation of process control, -based on the specific needs of the cells, -opens the possibility of improving process development on a short timescale and therewith, the robustness and performance of fermentation processes.
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Affiliation(s)
| | | | | | | | | | | | - Hannah Sehrt
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Frank Delvigne
- TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Philippe Goffin
- Molecular and Cellular Biology, University of Brussels, Brussels, Belgium
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5
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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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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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Harmer Z, McClean MN. Lustro: High-Throughput Optogenetic Experiments Enabled by Automation and a Yeast Optogenetic Toolkit. ACS Synth Biol 2023; 12:1943-1951. [PMID: 37434272 PMCID: PMC10368012 DOI: 10.1021/acssynbio.3c00215] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Indexed: 07/13/2023]
Abstract
Optogenetic systems use genetically encoded light-sensitive proteins to control cellular processes. This provides the potential to orthogonally control cells with light; however, these systems require many design-build-test cycles to achieve a functional design and multiple illumination variables need to be laboriously tuned for optimal stimulation. We combine laboratory automation and a modular cloning scheme to enable high-throughput construction and characterization of optogenetic split transcription factors in Saccharomyces cerevisiae. We expand the yeast optogenetic toolkit to include variants of the cryptochromes and enhanced Magnets, incorporate these light-sensitive dimerizers into split transcription factors, and automate illumination and measurement of cultures in a 96-well microplate format for high-throughput characterization. We use this approach to rationally design and test an optimized enhanced Magnet transcription factor with improved light-sensitive gene expression. This approach is generalizable to the high-throughput characterization of optogenetic systems across a range of biological systems and applications.
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Affiliation(s)
- Zachary
P. Harmer
- Department
of Biomedical Engineering, University of
Wisconsin−Madison, Madison, Wisconsin 53706, 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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Sosa-Carrillo S, Galez H, Napolitano S, Bertaux F, Batt G. Maximizing protein production by keeping cells at optimal secretory stress levels using real-time control approaches. Nat Commun 2023; 14:3028. [PMID: 37231013 DOI: 10.1038/s41467-023-38807-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 05/17/2023] [Indexed: 05/27/2023] Open
Abstract
Optimizing the production of recombinant proteins is a problem of major industrial and pharmaceutical importance. Secretion of the protein by the host cell considerably simplifies downstream purification processes. However, for many proteins, this is also the limiting production step. Current solutions involve extensive engineering of the chassis cell to facilitate protein trafficking and limit protein degradation triggered by excessive secretion-associated stress. Here, we propose instead a regulation-based strategy in which induction is dynamically adjusted to an optimal strength based on the current stress level of the cells. Using a small collection of hard-to-secrete proteins, a bioreactor-based platform with automated cytometry measurements, and a systematic assay to quantify secreted protein levels, we demonstrate that the secretion sweet spot is indicated by the appearance of a subpopulation of cells that accumulate high amounts of proteins, decrease growth, and face significant stress, that is, experience a secretion burnout. In these cells, adaptations capabilities are overwhelmed by a too strong production. Using these notions, we show for a single-chain antibody variable fragment that secretion levels can be improved by 70% by dynamically keeping the cell population at optimal stress levels using real-time closed-loop control.
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Affiliation(s)
| | - Henri Galez
- Institut Pasteur, Inria, Université Paris Cité, 75015, Paris, France
| | - Sara Napolitano
- Institut Pasteur, Inria, Université Paris Cité, 75015, Paris, France
| | - François Bertaux
- Institut Pasteur, Inria, Université Paris Cité, 75015, Paris, France
- Lesaffre International, 101 rue de Menin, Marcq-en-Baroeul, France
| | - Gregory Batt
- Institut Pasteur, Inria, Université Paris Cité, 75015, Paris, France.
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Harmer ZP, McClean MN. Lustro: High-throughput optogenetic experiments enabled by automation and a yeast optogenetic toolkit. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.07.536078. [PMID: 37066312 PMCID: PMC10104134 DOI: 10.1101/2023.04.07.536078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Optogenetic systems use genetically-encoded light-sensitive proteins to control cellular processes. This provides the potential to orthogonally control cells with light, however these systems require many design-build-test cycles to achieve a functional design and multiple illumination variables need to be laboriously tuned for optimal stimulation. We combine laboratory automation and a modular cloning scheme to enable high-throughput construction and characterization of optogenetic split transcription factors in Saccharomyces cerevisiae . We expand the yeast optogenetic toolkit to include variants of the cryptochromes and Enhanced Magnets, incorporate these light-sensitive dimerizers into split transcription factors, and automate illumination and measurement of cultures in a 96-well microplate format for high-throughput characterization. We use this approach to rationally design and test an optimized Enhanced Magnet transcription factor with improved light-sensitive gene expression. This approach is generalizable to high-throughput characterization of optogenetic systems across a range of biological systems and applications.
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