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Mudugamuwa A, Roshan U, Hettiarachchi S, Cha H, Musharaf H, Kang X, Trinh QT, Xia HM, Nguyen NT, Zhang J. Periodic Flows in Microfluidics. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024:e2404685. [PMID: 39246195 DOI: 10.1002/smll.202404685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2024] [Revised: 08/24/2024] [Indexed: 09/10/2024]
Abstract
Microfluidics, the science and technology of manipulating fluids in microscale channels, offers numerous advantages, such as low energy consumption, compact device size, precise control, fast reaction, and enhanced portability. These benefits have led to applications in biomedical assays, disease diagnostics, drug discovery, neuroscience, and so on. Fluid flow within microfluidic channels is typically in the laminar flow region, which is characterized by low Reynolds numbers but brings the challenge of efficient mixing of fluids. Periodic flows are time-dependent fluid flows, featuring repetitive patterns that can significantly improve fluid mixing and extend the effective length of microchannels for submicron and nanoparticle manipulation. Besides, periodic flow is crucial in organ-on-a-chip (OoC) for accurately modeling physiological processes, advancing disease understanding, drug development, and personalized medicine. Various techniques for generating periodic flows have been reported, including syringe pumps, peristalsis, and actuation based on electric, magnetic, acoustic, mechanical, pneumatic, and fluidic forces, yet comprehensive reviews on this topic remain limited. This paper aims to provide a comprehensive review of periodic flows in microfluidics, from fundamental mechanisms to generation techniques and applications. The challenges and future perspectives are also discussed to exploit the potential of periodic flows in microfluidics.
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Affiliation(s)
- Amith Mudugamuwa
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
| | - Uditha Roshan
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
| | - Samith Hettiarachchi
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
| | - Haotian Cha
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
| | - Hafiz Musharaf
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
| | - Xiaoyue Kang
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
| | - Quang Thang Trinh
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
| | - Huan Ming Xia
- School of Mechanical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, P. R. China
| | - Nam-Trung Nguyen
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
| | - Jun Zhang
- Queensland Micro and Nanotechnology Centre, Griffith University, Brisbane, QLD, 4111, Australia
- School of Engineering and Built Environment, Griffith University, Brisbane, QLD, 4111, Australia
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2
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Cleere MM, Gardner KH. Optogenetic control of phosphate-responsive genes using single component fusion proteins in Saccharomyces cerevisiae. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.02.605841. [PMID: 39131330 PMCID: PMC11312615 DOI: 10.1101/2024.08.02.605841] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Blue light illumination can be detected by Light-Oxygen-Voltage (LOV) photosensing proteins and translated into a range of biochemical responses, facilitating the generation of novel optogenetic tools to control cellular function. Here we develop new variants of our previously described VP-EL222 light-dependent transcription factor and apply them to study the phosphate-responsive signaling (PHO) pathway in the budding yeast Saccharomyces cerevisiae, exemplifying the utilities of these new tools. Focusing first on the VP-EL222 protein itself, we quantified the tunability of gene expression as a function of light intensity and duration, and demonstrated that this system can tolerate the addition of substantially larger effector domains without impacting function. We further demonstrated the utility of several EL222-driven transcriptional controllers in both plasmid and genomic settings, using the PHO5 and PHO84 promoters in their native chromosomal contexts as examples. These studies highlight the utility of light-controlled gene activation using EL222 tethered to either artificial transcription domains or yeast activator proteins (Pho4). Similarly, we demonstrate the ability to optogenetically repress gene expression with EL222 fused to the yeast Ume6 protein. We finally investigated the effects of moving EL222 recruitment sites to different locations within the PHO5 and PHO84 promoters, as well as determining how this artificial light-controlled regulation could be integrated with the native controls dependent on inorganic phosphate (Pi) availability. Taken together, our work expands the applicability of these versatile optogenetic tools in the types of functionality they can deliver and biological questions that can be probed.
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Affiliation(s)
- Matthew M Cleere
- Structural Biology Initiative, CUNY Advanced Science Research Center, New York, NY 10031
- Biology Ph.D. Program, Graduate Center, City University of New York, New York, NY 10016
| | - Kevin H Gardner
- Structural Biology Initiative, CUNY Advanced Science Research Center, New York, NY 10031
- Biochemistry, Chemistry, and Biology Ph.D. Programs, Graduate Center, City University of New York, New York, NY 10016
- Department of Chemistry and Biochemistry, City College of New York, New York, NY 10031
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3
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Ding Q, Liu L. Reprogramming cellular metabolism to increase the efficiency of microbial cell factories. Crit Rev Biotechnol 2024; 44:892-909. [PMID: 37380349 DOI: 10.1080/07388551.2023.2208286] [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: 11/17/2022] [Accepted: 04/11/2023] [Indexed: 06/30/2023]
Abstract
Recent studies are increasingly focusing on advanced biotechnological tools, self-adjusting smart microorganisms, and artificial intelligent networks, to engineer microorganisms with various functions. Microbial cell factories are a vital platform for improving the bioproduction of medicines, biofuels, and biomaterials from renewable carbon sources. However, these processes are significantly affected by cellular metabolism, and boosting the efficiency of microbial cell factories remains a challenge. In this review, we present a strategy for reprogramming cellular metabolism to enhance the efficiency of microbial cell factories for chemical biosynthesis, which improves our understanding of microbial physiology and metabolic control. Current methods are mainly focused on synthetic pathways, metabolic resources, and cell performance. This review highlights the potential biotechnological strategy to reprogram cellular metabolism and provide novel guidance for designing more intelligent industrial microbes with broader applications in this growing field.
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Affiliation(s)
- Qiang Ding
- School of Life Sciences, Anhui University, Hefei, China
- Key Laboratory of Human Microenvironment and Precision Medicine of Anhui Higher Education Institutes, Anhui University, Hefei, Anhui, China
- Anhui Key Laboratory of Modern Biomanufacturing, Hefei, Anhui, China
| | - Liming Liu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi, China
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Hong CKY, Ramu A, Zhao S, Cohen BA. Effect of genomic and cellular environments on gene expression noise. Genome Biol 2024; 25:137. [PMID: 38790076 PMCID: PMC11127367 DOI: 10.1186/s13059-024-03277-9] [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] [Received: 12/07/2022] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND Individual cells from isogenic populations often display large cell-to-cell differences in gene expression. This "noise" in expression derives from several sources, including the genomic and cellular environment in which a gene resides. Large-scale maps of genomic environments have revealed the effects of epigenetic modifications and transcription factor occupancy on mean expression levels, but leveraging such maps to explain expression noise will require new methods to assay how expression noise changes at locations across the genome. RESULTS To address this gap, we present Single-cell Analysis of Reporter Gene Expression Noise and Transcriptome (SARGENT), a method that simultaneously measures the noisiness of reporter genes integrated throughout the genome and the global mRNA profiles of individual reporter-gene-containing cells. Using SARGENT, we perform the first comprehensive genome-wide survey of how genomic locations impact gene expression noise. We find that the mean and noise of expression correlate with different histone modifications. We quantify the intrinsic and extrinsic components of reporter gene noise and, using the associated mRNA profiles, assign the extrinsic component to differences between the CD24+ "stem-like" substate and the more "differentiated" substate. SARGENT also reveals the effects of transgene integrations on endogenous gene expression, which will help guide the search for "safe-harbor" loci. CONCLUSIONS Taken together, we show that SARGENT is a powerful tool to measure both the mean and noise of gene expression at locations across the genome and that the data generatd by SARGENT reveals important insights into the regulation of gene expression noise genome-wide.
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Affiliation(s)
- Clarice K Y Hong
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Avinash Ramu
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Siqi Zhao
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA
| | - Barak A Cohen
- The Edison Family Center for Genome Sciences and Systems Biology, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
- Department of Genetics, School of Medicine, Washington University in St. Louis, Saint Louis, MO, 63110, USA.
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5
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Le Bec M, Pouzet S, Cordier C, Barral S, Scolari V, Sorre B, Banderas A, Hersen P. Optogenetic spatial patterning of cooperation in yeast populations. Nat Commun 2024; 15:75. [PMID: 38168087 PMCID: PMC10761962 DOI: 10.1038/s41467-023-44379-5] [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: 05/17/2023] [Accepted: 12/11/2023] [Indexed: 01/05/2024] Open
Abstract
Microbial communities are shaped by complex metabolic interactions such as cooperation and competition for resources. Methods to control such interactions could lead to major advances in our ability to better engineer microbial consortia for synthetic biology applications. Here, we use optogenetics to control SUC2 invertase production in yeast, thereby shaping spatial assortment of cooperator and cheater cells. Yeast cells behave as cooperators (i.e., transform sucrose into hexose, a public good) upon blue light illumination or cheaters (i.e., consume hexose produced by cooperators to grow) in the dark. We show that cooperators benefit best from the hexoses they produce when their domain size is constrained between two cut-off length-scales. From an engineering point of view, the system behaves as a bandpass filter. The lower limit is the trace of cheaters' competition for hexoses, while the upper limit is defined by cooperators' competition for sucrose. Cooperation mostly occurs at the frontiers with cheater cells, which not only compete for hexoses but also cooperate passively by letting sucrose reach cooperators. We anticipate that this optogenetic method could be applied to shape metabolic interactions in a variety of microbial ecosystems.
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Affiliation(s)
- Matthias Le Bec
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, 75005, Paris, France
| | - Sylvain Pouzet
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, 75005, Paris, France
| | - Céline Cordier
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, 75005, Paris, France
| | - Simon Barral
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, 75005, Paris, France
| | - Vittore Scolari
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, 75005, Paris, France
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR3664, Laboratoire Dynamique du Noyau, 75005, Paris, France
| | - Benoit Sorre
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, 75005, Paris, France
| | - Alvaro Banderas
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, 75005, Paris, France.
| | - Pascal Hersen
- Institut Curie, Université PSL, Sorbonne Université, CNRS UMR168, Laboratoire Physico Chimie Curie, 75005, Paris, France.
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6
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Gligorovski V, Rahi SJ. Construction and Characterization of Light-Responsive Transcriptional Systems. Methods Mol Biol 2024; 2844:261-275. [PMID: 39068346 DOI: 10.1007/978-1-0716-4063-0_18] [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: 07/30/2024]
Abstract
Optogenetic tools provide a means for controlling cellular processes that is rapid, noninvasive, and spatially and temporally precise. With the increase in available optogenetic systems, quantitative comparisons of their performances become important to guide experiments. In this chapter, we first discuss how photoreceptors can be repurposed for light-mediated control of transcription. Then, we provide a detailed protocol for characterizing light-regulated transcriptional systems in budding yeast using fluorescence time-lapse microscopy and mathematical modeling, expanding on our recent publication (Gligorovski et al., Nat Commun 14:3810, 2023).
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Affiliation(s)
- Vojislav Gligorovski
- Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Sahand Jamal Rahi
- Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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Feng H, Li F, Wang T, Xing XH, Zeng AP, Zhang C. Deep-learning-assisted Sort-Seq enables high-throughput profiling of gene expression characteristics with high precision. SCIENCE ADVANCES 2023; 9:eadg5296. [PMID: 37939173 PMCID: PMC10631719 DOI: 10.1126/sciadv.adg5296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 10/06/2023] [Indexed: 11/10/2023]
Abstract
Owing to the nondeterministic and nonlinear nature of gene expression, the steady-state intracellular protein abundance of a clonal population forms a distribution. The characteristics of this distribution, including expression strength and noise, are closely related to cellular behavior. However, quantitative description of these characteristics has so far relied on arrayed methods, which are time-consuming and labor-intensive. To address this issue, we propose a deep-learning-assisted Sort-Seq approach (dSort-Seq) in this work, enabling high-throughput profiling of expression properties with high precision. We demonstrated the validity of dSort-Seq for large-scale assaying of the dose-response relationships of biosensors. In addition, we comprehensively investigated the contribution of transcription and translation to noise production in Escherichia coli, from which we found that the expression noise is strongly coupled with the mean expression level. We also found that the transcriptional interference caused by overlapping RpoD-binding sites contributes to noise production, which suggested the existence of a simple and feasible noise control strategy in E. coli.
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Affiliation(s)
- Huibao Feng
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Fan Li
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Tianmin Wang
- Tsinghua-Peking Center for Life Sciences, School of Medicine, Tsinghua University, Beijing 100084, China
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Xin-hui Xing
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
- Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - An-ping Zeng
- Institute of Bioprocess and Biosystems Engineering, Hamburg University of Technology, Hamburg 21073, Germany
- Center of Synthetic Biology and Integrated Bioengineering, School of Engineering, Westlake University, Hangzhou 310024, China
| | - Chong Zhang
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China
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8
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Henrion L, Martinez JA, Vandenbroucke V, Delvenne M, Telek S, Zicler A, Grünberger A, Delvigne F. Fitness cost associated with cell phenotypic switching drives population diversification dynamics and controllability. Nat Commun 2023; 14:6128. [PMID: 37783690 PMCID: PMC10545768 DOI: 10.1038/s41467-023-41917-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 09/23/2023] [Indexed: 10/04/2023] Open
Abstract
Isogenic cell populations can cope with stress conditions by switching to alternative phenotypes. Even if it can lead to increased fitness in a natural context, this feature is typically unwanted for a range of applications (e.g., bioproduction, synthetic biology, and biomedicine) where it tends to make cellular response unpredictable. However, little is known about the diversification profiles that can be adopted by a cell population. Here, we characterize the diversification dynamics for various systems (bacteria and yeast) and for different phenotypes (utilization of alternative carbon sources, general stress response and more complex development patterns). Our results suggest that the diversification dynamics and the fitness cost associated with cell switching are coupled. To quantify the contribution of the switching cost on population dynamics, we design a stochastic model that let us reproduce the dynamics observed experimentally and identify three diversification regimes, i.e., constrained (at low switching cost), dispersed (at medium and high switching cost), and bursty (for very high switching cost). Furthermore, we use a cell-machine interface called Segregostat to demonstrate that different levels of control can be applied to these diversification regimes, enabling applications involving more precise cellular responses.
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Affiliation(s)
- Lucas Henrion
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Juan Andres Martinez
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Vincent Vandenbroucke
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Mathéo Delvenne
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Samuel Telek
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Andrew Zicler
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Alexander Grünberger
- Microsystems in Bioprocess Engineering, Institute of Process Engineering in Life Sciences, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Frank Delvigne
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
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9
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Delvigne F, Martinez JA. Advances in automated and reactive flow cytometry for synthetic biotechnology. Curr Opin Biotechnol 2023; 83:102974. [PMID: 37515938 DOI: 10.1016/j.copbio.2023.102974] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 06/20/2023] [Accepted: 07/03/2023] [Indexed: 07/31/2023]
Abstract
Automated flow cytometry (FC) has been initially considered for bioprocess monitoring and optimization. More recently, new physical and software interfaces have been made available, facilitating the access to this technology for labs and industries. It also comes with new capabilities, such as being able to act on the cultivation conditions based on population data. This approach, known as reactive FC, extended the range of applications of automated FC to bioprocess control and the stabilization of cocultures, but also to the broad field of synthetic and systems biology for the characterization of gene circuits. However, several issues must be addressed before automated and reactive FC can be considered standard and modular technologies.
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Affiliation(s)
- Frank Delvigne
- Terra Research and Teaching Center, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
| | - Juan A Martinez
- Terra Research and Teaching Center, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
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10
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Loman TE, Locke JCW. The σB alternative sigma factor circuit modulates noise to generate different types of pulsing dynamics. PLoS Comput Biol 2023; 19:e1011265. [PMID: 37540712 PMCID: PMC10431680 DOI: 10.1371/journal.pcbi.1011265] [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] [Received: 10/10/2022] [Revised: 08/16/2023] [Accepted: 06/12/2023] [Indexed: 08/06/2023] Open
Abstract
Single-cell approaches are revealing a high degree of heterogeneity, or noise, in gene expression in isogenic bacteria. How gene circuits modulate this noise in gene expression to generate robust output dynamics is unclear. Here we use the Bacillus subtilis alternative sigma factor σB as a model system for understanding the role of noise in generating circuit output dynamics. σB controls the general stress response in B. subtilis and is activated by a range of energy and environmental stresses. Recent single-cell studies have revealed that the circuit can generate two distinct outputs, stochastic pulsing and a single pulse response, but the conditions under which each response is generated are under debate. We implement a stochastic mathematical model of the σB circuit to investigate this and find that the system's core circuit can generate both response types. This is despite one response (stochastic pulsing) being stochastic in nature, and the other (single response pulse) being deterministic. We demonstrate that the main determinant for whichever response is generated is the degree with which the input pathway activates the core circuit, although the noise properties of the input pathway also biases the system towards one or the other type of output. Thus, our work shows how stochastic modelling can reveal the mechanisms behind non-intuitive gene circuit output dynamics.
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Affiliation(s)
- Torkel E. Loman
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
| | - James C. W. Locke
- Sainsbury Laboratory, University of Cambridge, Cambridge, United Kingdom
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11
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Gligorovski V, Sadeghi A, Rahi SJ. Multidimensional characterization of inducible promoters and a highly light-sensitive LOV-transcription factor. Nat Commun 2023; 14:3810. [PMID: 37369667 DOI: 10.1038/s41467-023-38959-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 05/24/2023] [Indexed: 06/29/2023] Open
Abstract
The ability to independently control the expression of different genes is important for quantitative biology. Using budding yeast, we characterize GAL1pr, GALL, MET3pr, CUP1pr, PHO5pr, tetOpr, terminator-tetOpr, Z3EV, blue-light inducible optogenetic systems El222-LIP, El222-GLIP, and red-light inducible PhyB-PIF3. We report kinetic parameters, noise scaling, impact on growth, and the fundamental leakiness of each system using an intuitive unit, maxGAL1. We uncover disadvantages of widely used tools, e.g., nonmonotonic activity of MET3pr and GALL, slow off kinetics of the doxycycline- and estradiol-inducible systems tetOpr and Z3EV, and high variability of PHO5pr and red-light activated PhyB-PIF3 system. We introduce two previously uncharacterized systems: strongLOV, a more light-sensitive El222 mutant, and ARG3pr, which is induced in the absence of arginine or presence of methionine. To demonstrate fine control over gene circuits, we experimentally tune the time between cell cycle Start and mitosis, artificially simulating near-wild-type timing. All strains, constructs, code, and data ( https://promoter-benchmark.epfl.ch/ ) are made available.
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Affiliation(s)
- Vojislav Gligorovski
- Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ahmad Sadeghi
- Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Sahand Jamal Rahi
- Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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12
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Vo HD, Forero-Quintero LS, Aguilera LU, Munsky B. Analysis and design of single-cell experiments to harvest fluctuation information while rejecting measurement noise. Front Cell Dev Biol 2023; 11:1133994. [PMID: 37305680 PMCID: PMC10250612 DOI: 10.3389/fcell.2023.1133994] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 05/10/2023] [Indexed: 06/13/2023] Open
Abstract
Introduction: Despite continued technological improvements, measurement errors always reduce or distort the information that any real experiment can provide to quantify cellular dynamics. This problem is particularly serious for cell signaling studies to quantify heterogeneity in single-cell gene regulation, where important RNA and protein copy numbers are themselves subject to the inherently random fluctuations of biochemical reactions. Until now, it has not been clear how measurement noise should be managed in addition to other experiment design variables (e.g., sampling size, measurement times, or perturbation levels) to ensure that collected data will provide useful insights on signaling or gene expression mechanisms of interest. Methods: We propose a computational framework that takes explicit consideration of measurement errors to analyze single-cell observations, and we derive Fisher Information Matrix (FIM)-based criteria to quantify the information value of distorted experiments. Results and Discussion: We apply this framework to analyze multiple models in the context of simulated and experimental single-cell data for a reporter gene controlled by an HIV promoter. We show that the proposed approach quantitatively predicts how different types of measurement distortions affect the accuracy and precision of model identification, and we demonstrate that the effects of these distortions can be mitigated through explicit consideration during model inference. We conclude that this reformulation of the FIM could be used effectively to design single-cell experiments to optimally harvest fluctuation information while mitigating the effects of image distortion.
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Affiliation(s)
- Huy D. Vo
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO, United States
| | - Linda S. Forero-Quintero
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO, United States
| | - Luis U. Aguilera
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO, United States
| | - Brian Munsky
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO, United States
- School of Biomedical Engineering, Colorado State University, Fort Collins, CO, United States
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13
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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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14
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Naseri G. A roadmap to establish a comprehensive platform for sustainable manufacturing of natural products in yeast. Nat Commun 2023; 14:1916. [PMID: 37024483 PMCID: PMC10079933 DOI: 10.1038/s41467-023-37627-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
Secondary natural products (NPs) are a rich source for drug discovery. However, the low abundance of NPs makes their extraction from nature inefficient, while chemical synthesis is challenging and unsustainable. Saccharomyces cerevisiae and Pichia pastoris are excellent manufacturing systems for the production of NPs. This Perspective discusses a comprehensive platform for sustainable production of NPs in the two yeasts through system-associated optimization at four levels: genetics, temporal controllers, productivity screening, and scalability. Additionally, it is pointed out critical metabolic building blocks in NP bioengineering can be identified through connecting multilevel data of the optimized system using deep learning.
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Affiliation(s)
- Gita Naseri
- Max Planck Unit for the Science of Pathogens, Charitéplatz 1, 10117, Berlin, Germany.
- Institut für Biologie, Humboldt-Universität zu Berlin, Philippstrasse 13, 10115, Berlin, Germany.
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15
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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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16
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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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17
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Kumar A, Baldia A, Rajput D, Kateriya S, Babu V, Dubey KK. Multiomics and optobiotechnological approaches for the development of microalgal strain for production of aviation biofuel and biorefinery. BIORESOURCE TECHNOLOGY 2023; 369:128457. [PMID: 36503094 DOI: 10.1016/j.biortech.2022.128457] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 12/02/2022] [Accepted: 12/04/2022] [Indexed: 06/17/2023]
Abstract
Demand and consumption of fossil fuels is increasing daily, and oil reserves are depleting. Technological developments are required towards developing sustainable renewable energy sources and microalgae are emerging as a potential candidate for various application-driven research. Molecular understanding attained through omics and system biology approach empowering researchers to modify various metabolic pathways of microalgal system for efficient extraction of biofuel and important biomolecules. This review furnish insight into different "advanced approaches" like optogenetics, systems biology and multi-omics for enhanced production of FAS (Fatty Acid Synthesis) and lipids in microalgae and their associated challenges. These new approaches would be helpful in the path of developing microalgae inspired technological platforms for optobiorefinery, which could be explored as source material to produce biofuels and other valuable bio-compounds on a large scale.
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Affiliation(s)
- Akshay Kumar
- School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India
| | - Anshu Baldia
- School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India
| | - Deepanshi Rajput
- School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India
| | - Suneel Kateriya
- School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India
| | - Vikash Babu
- Fermentation & Microbial Biotechnology Division, CSIR-Indian Institute of Integrative Medicine, Jammu 180001, India
| | - Kashyap Kumar Dubey
- School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India.
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18
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Delvigne F, Henrion L, Vandenbroucke V, Martinez JA. Avoiding the All-or-None Response in Gene Expression During E. coli Continuous Cultivation Based on the On-Line Monitoring of Cell Phenotypic Switching Dynamics. Methods Mol Biol 2023; 2617:103-120. [PMID: 36656519 DOI: 10.1007/978-1-0716-2930-7_7] [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: 01/20/2023]
Abstract
Different expression vectors are available for the effective production of recombinant proteins by bacterial populations. However, the productivity of such systems is limited by the inherent noise of the gene circuits used for the synthesis of recombinant products. An extreme case of cell-to-cell heterogeneity that has been previously reported for the ara- and lac-based expression systems in E. coli is the all-or-none response. According to this mode of response, two subpopulations of cells are generated, i.e., a "low-" subpopulation exhibiting a shallow expression level and a "high-" subpopulation exhibiting a high-expression level. The "low-" subpopulation can be considered as a cluster of non-producing cells contributing to the loss of productivity. Here we describe the setup, design, and operation of a continuous culture where inducer addition is operated based on microbial population dynamics. The determination of population dynamics is done based on an automated flow cytometry (FC) procedure previously denoted as segregostat. We illustrate how this setup can be used to control the activation of an ara-based expression system and avoid phenotypic diversification leading to an all-or-none response. Upon the determination of the natural frequency of the gene circuit used as an expression system, our current protocol can be set up without the requirement of a feedback controller.
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Affiliation(s)
- Frank Delvigne
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium.
| | - Lucas Henrion
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Vincent Vandenbroucke
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Juan Andres Martinez
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
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19
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Wegner SA, Barocio-Galindo RM, Avalos JL. The bright frontiers of microbial metabolic optogenetics. Curr Opin Chem Biol 2022; 71:102207. [PMID: 36103753 DOI: 10.1016/j.cbpa.2022.102207] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/29/2022] [Accepted: 08/05/2022] [Indexed: 01/27/2023]
Abstract
In recent years, light-responsive systems from the field of optogenetics have been applied to several areas of metabolic engineering with remarkable success. By taking advantage of light's high tunability, reversibility, and orthogonality to host endogenous processes, optogenetic systems have enabled unprecedented dynamical controls of microbial fermentations for chemical production, metabolic flux analysis, and population compositions in co-cultures. In this article, we share our opinions on the current state of this new field of metabolic optogenetics.We make the case that it will continue to impact metabolic engineering in increasingly new directions, with the potential to challenge existing paradigms for metabolic pathway and strain optimization as well as bioreactor operation.
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Affiliation(s)
| | | | - José L Avalos
- Department of Molecular Biology, USA; Department of Chemical and Biological Engineering, USA; The Andlinger Center for Energy and the Environment, USA; High Meadows Environmental Institute, Princeton University, Princeton NJ 08544, USA.
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20
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Abstract
The invention of the Fourier integral in the 19th century laid the foundation for modern spectral analysis methods. This integral decomposes a temporal signal into its frequency components, providing deep insights into its generating process. While this idea has precipitated several scientific and technological advances, its impact has been fairly limited in cell biology, largely due to the difficulties in connecting the underlying noisy intracellular networks to the frequency content of observed single-cell trajectories. Here we develop a spectral theory and computational methodologies tailored specifically to the computation and analysis of frequency spectra of noisy intracellular networks. Specifically, we develop a method to compute the frequency spectrum for general nonlinear networks, and for linear networks we present a decomposition that expresses the frequency spectrum in terms of its sources. Several examples are presented to illustrate how our results provide frequency-based methods for the design and analysis of noisy intracellular networks.
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Affiliation(s)
- Ankit Gupta
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland.
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21
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Kumar S, Khammash M. Platforms for Optogenetic Stimulation and Feedback Control. Front Bioeng Biotechnol 2022; 10:918917. [PMID: 35757811 PMCID: PMC9213687 DOI: 10.3389/fbioe.2022.918917] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 05/06/2022] [Indexed: 11/13/2022] Open
Abstract
Harnessing the potential of optogenetics in biology requires methodologies from different disciplines ranging from biology, to mechatronics engineering, to control engineering. Light stimulation of a synthetic optogenetic construct in a given biological species can only be achieved via a suitable light stimulation platform. Emerging optogenetic applications entail a consistent, reproducible, and regulated delivery of light adapted to the application requirement. In this review, we explore the evolution of light-induction hardware-software platforms from simple illumination set-ups to sophisticated microscopy, microtiter plate and bioreactor designs, and discuss their respective advantages and disadvantages. Here, we examine design approaches followed in performing optogenetic experiments spanning different cell types and culture volumes, with induction capabilities ranging from single cell stimulation to entire cell culture illumination. The development of automated measurement and stimulation schemes on these platforms has enabled researchers to implement various in silico feedback control strategies to achieve computer-controlled living systems—a theme we briefly discuss in the last part of this review.
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Affiliation(s)
- Sant Kumar
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Basel, Switzerland
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22
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Enhancing bioreactor arrays for automated measurements and reactive control with ReacSight. Nat Commun 2022; 13:3363. [PMID: 35690608 PMCID: PMC9188569 DOI: 10.1038/s41467-022-31033-9] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 05/31/2022] [Indexed: 12/19/2022] Open
Abstract
Small-scale, low-cost bioreactors provide exquisite control of environmental parameters of microbial cultures over long durations. Their use is gaining popularity in quantitative systems and synthetic biology. However, existing setups are limited in their measurement capabilities. Here, we present ReacSight, a strategy to enhance bioreactor arrays for automated measurements and reactive experiment control. ReacSight leverages low-cost pipetting robots for sample collection, handling and loading, and provides a flexible instrument control architecture. We showcase ReacSight capabilities on three applications in yeast. First, we demonstrate real-time optogenetic control of gene expression. Second, we explore the impact of nutrient scarcity on fitness and cellular stress using competition assays. Third, we perform dynamic control of the composition of a two-strain consortium. We combine custom or chi.bio reactors with automated cytometry. To further illustrate ReacSight's genericity, we use it to enhance plate-readers with pipetting capabilities and perform repeated antibiotic treatments on a bacterial clinical isolate.
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23
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Henrion L, Delvenne M, Bajoul Kakahi F, Moreno-Avitia F, Delvigne F. Exploiting Information and Control Theory for Directing Gene Expression in Cell Populations. Front Microbiol 2022; 13:869509. [PMID: 35547126 PMCID: PMC9081792 DOI: 10.3389/fmicb.2022.869509] [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: 02/04/2022] [Accepted: 04/06/2022] [Indexed: 11/13/2022] Open
Abstract
Microbial populations can adapt to adverse environmental conditions either by appropriately sensing and responding to the changes in their surroundings or by stochastically switching to an alternative phenotypic state. Recent data point out that these two strategies can be exhibited by the same cellular system, depending on the amplitude/frequency of the environmental perturbations and on the architecture of the genetic circuits involved in the adaptation process. Accordingly, several mitigation strategies have been designed for the effective control of microbial populations in different contexts, ranging from biomedicine to bioprocess engineering. Technically, such control strategies have been made possible by the advances made at the level of computational and synthetic biology combined with control theory. However, these control strategies have been applied mostly to synthetic gene circuits, impairing the applicability of the approach to natural circuits. In this review, we argue that it is possible to expand these control strategies to any cellular system and gene circuits based on a metric derived from this information theory, i.e., mutual information (MI). Indeed, based on this metric, it should be possible to characterize the natural frequency of any gene circuits and use it for controlling gene circuits within a population of cells.
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Affiliation(s)
- Lucas Henrion
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Mathéo Delvenne
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Fatemeh Bajoul Kakahi
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Fabian Moreno-Avitia
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Frank Delvigne
- Microbial Processes and Interactions (MiPI), Terra Research and Teaching Centre, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
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24
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Abstract
Microscopy image analysis has recently made enormous progress both in terms of accuracy and speed thanks to machine learning methods and improved computational resources. This greatly facilitates the online adaptation of microscopy experimental plans using real-time information of the observed systems and their environments. Applications in which reactiveness is needed are multifarious. Here we report MicroMator, an open and flexible software for defining and driving reactive microscopy experiments. It provides a Python software environment and an extensible set of modules that greatly facilitate the definition of events with triggers and effects interacting with the experiment. We provide a pedagogic example performing dynamic adaptation of fluorescence illumination on bacteria, and demonstrate MicroMator’s potential via two challenging case studies in yeast to single-cell control and single-cell recombination, both requiring real-time tracking and light targeting at the single-cell level. In microscopy, applications in which reactiveness is needed are multifarious. Here the authors report MicroMator, a Python software package for reactive experiments, which they use for applications requiring real-time tracking and light-targeting at the single-cell level.
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25
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Optogenetic tools for microbial synthetic biology. Biotechnol Adv 2022; 59:107953. [DOI: 10.1016/j.biotechadv.2022.107953] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 03/09/2022] [Accepted: 04/04/2022] [Indexed: 12/22/2022]
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26
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Guerra P, Vuillemenot LA, Rae B, Ladyhina V, Milias-Argeitis A. Systematic In Vivo Characterization of Fluorescent Protein Maturation in Budding Yeast. ACS Synth Biol 2022; 11:1129-1141. [PMID: 35180343 PMCID: PMC8938947 DOI: 10.1021/acssynbio.1c00387] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
![]()
Fluorescent protein
(FP) maturation can limit the accuracy with
which dynamic intracellular processes are captured and reduce the in vivo brightness of a given FP in fast-dividing cells.
The knowledge of maturation timescales can therefore help users determine
the appropriate FP for each application. However, in vivo maturation rates can greatly deviate from in vitro estimates that are mostly available. In this work, we present the
first systematic study of in vivo maturation for
12 FPs in budding yeast. To overcome the technical limitations of
translation inhibitors commonly used to study FP maturation, we implemented
a new approach based on the optogenetic stimulations of FP expression
in cells grown under constant nutrient conditions. Combining the rapid
and orthogonal induction of FP transcription with a mathematical model
of expression and maturation allowed us to accurately estimate maturation
rates from microscopy data in a minimally invasive manner. Besides
providing a useful resource for the budding yeast community, we present
a new joint experimental and computational approach for characterizing
FP maturation, which is applicable to a wide range of organisms.
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Affiliation(s)
- Paolo Guerra
- Molecular Systems Biology, Groningen Biomolecular Sciences & Biotechnology Institute, University of Groningen, 9747 AG Groningen, Netherlands
| | - Luc-Alban Vuillemenot
- Molecular Systems Biology, Groningen Biomolecular Sciences & Biotechnology Institute, University of Groningen, 9747 AG Groningen, Netherlands
| | - Brady Rae
- Molecular Systems Biology, Groningen Biomolecular Sciences & Biotechnology Institute, University of Groningen, 9747 AG Groningen, Netherlands
| | - Valeriia Ladyhina
- Molecular Systems Biology, Groningen Biomolecular Sciences & Biotechnology Institute, University of Groningen, 9747 AG Groningen, Netherlands
| | - Andreas Milias-Argeitis
- Molecular Systems Biology, Groningen Biomolecular Sciences & Biotechnology Institute, University of Groningen, 9747 AG Groningen, Netherlands
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27
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Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression. Cell Syst 2022; 13:353-364.e6. [PMID: 35298924 DOI: 10.1016/j.cels.2022.02.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 11/18/2021] [Accepted: 02/17/2022] [Indexed: 12/27/2022]
Abstract
Cells live in constantly changing environments and employ dynamic signaling pathways to transduce information about the signals they encounter. However, the mechanisms by which dynamic signals are decoded into appropriate gene expression patterns remain poorly understood. Here, we devise networked optogenetic pathways that achieve dynamic signal processing functions that recapitulate cellular information processing. Exploiting light-responsive transcriptional regulators with differing response kinetics, we build a falling edge pulse detector and show that this circuit can be employed to demultiplex dynamically encoded signals. We combine this demultiplexer with dCas9-based gene networks to construct pulsatile signal filters and decoders. Applying information theory, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state. Finally, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway. Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications.
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28
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29
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Hoffman SM, Tang AY, Avalos JL. Optogenetics Illuminates Applications in Microbial Engineering. Annu Rev Chem Biomol Eng 2022; 13:373-403. [PMID: 35320696 DOI: 10.1146/annurev-chembioeng-092120-092340] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Optogenetics has been used in a variety of microbial engineering applications, such as chemical and protein production, studies of cell physiology, and engineered microbe-host interactions. These diverse applications benefit from the precise spatiotemporal control that light affords, as well as its tunability, reversibility, and orthogonality. This combination of unique capabilities has enabled a surge of studies in recent years investigating complex biological systems with completely new approaches. We briefly describe the optogenetic tools that have been developed for microbial engineering, emphasizing the scientific advancements that they have enabled. In particular, we focus on the unique benefits and applications of implementing optogenetic control, from bacterial therapeutics to cybergenetics. Finally, we discuss future research directions, with special attention given to the development of orthogonal multichromatic controls. With an abundance of advantages offered by optogenetics, the future is bright in microbial engineering. Expected final online publication date for the Annual Review of Chemical and Biomolecular Engineering, Volume 13 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Shannon M Hoffman
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, USA; , ,
| | - Allison Y Tang
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, USA; , ,
| | - José L Avalos
- Department of Chemical and Biological Engineering, Princeton University, Princeton, New Jersey, USA; , , .,The Andlinger Center for Energy and the Environment, Department of Molecular Biology, and High Meadows Environmental Institute, Princeton University, Princeton, New Jersey, USA
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30
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Zhu D, Johnson HJ, Chen J, Schaffer DV. Optogenetic Application to Investigating Cell Behavior and Neurological Disease. Front Cell Neurosci 2022; 16:811493. [PMID: 35273478 PMCID: PMC8902366 DOI: 10.3389/fncel.2022.811493] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 01/04/2022] [Indexed: 11/13/2022] Open
Abstract
Cells reside in a dynamic microenvironment that presents them with regulatory signals that vary in time, space, and amplitude. The cell, in turn, interprets these signals and accordingly initiates downstream processes including cell proliferation, differentiation, migration, and self-organization. Conventional approaches to perturb and investigate signaling pathways (e.g., agonist/antagonist addition, overexpression, silencing, knockouts) are often binary perturbations that do not offer precise control over signaling levels, and/or provide limited spatial or temporal control. In contrast, optogenetics leverages light-sensitive proteins to control cellular signaling dynamics and target gene expression and, by virtue of precise hardware control over illumination, offers the capacity to interrogate how spatiotemporally varying signals modulate gene regulatory networks and cellular behaviors. Recent studies have employed various optogenetic systems in stem cell, embryonic, and somatic cell patterning studies, which have addressed fundamental questions of how cell-cell communication, subcellular protein localization, and signal integration affect cell fate. Other efforts have explored how alteration of signaling dynamics may contribute to neurological diseases and have in the process created physiologically relevant models that could inform new therapeutic strategies. In this review, we focus on emerging applications within the expanding field of optogenetics to study gene regulation, cell signaling, neurodevelopment, and neurological disorders, and we comment on current limitations and future directions for the growth of the field.
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Affiliation(s)
- Danqing Zhu
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, United States
| | - Hunter J. Johnson
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, United States
- Graduate Program in Bioengineering, University of California, San Francisco, San Francisco, CA, United States
- Graduate Program in Bioengineering, University of California, Berkeley, Berkeley, CA, United States
| | - Jun Chen
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, United States
| | - David V. Schaffer
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, United States
- Department of Bioengineering, University of California, Berkeley, Berkeley, CA, United States
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, United States
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA, United States
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, United States
- *Correspondence: David V. Schaffer
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31
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Wang Z, Yan Y, Zhang H. Design and Characterization of an Optogenetic System in Pichia pastoris. ACS Synth Biol 2022; 11:297-307. [PMID: 34994189 DOI: 10.1021/acssynbio.1c00422] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Pichia pastoris (P. pastoris) is the workhorse in the commercial production of many valuable proteins. Traditionally, the regulation of gene expression in P. pastoris is achieved through induction by methanol which is toxic and flammable. The emerging optogenetic technology provides an alternative and cleaner gene regulation method. Based on the photosensitive protein EL222, we designed a novel "one-component" optogenetic system. The highest induction ratio was 79.7-fold under blue light compared to the group under darkness. After switching cells from dark to blue illumination, the system induced expression in just 1 h. Only 2 h after the system was switched back to the darkness from blue illumination, the target gene expression was inactivated 5-fold. The induction intensity of the optogenetic system is positively correlated with the dose and periodicity of blue illumination, and it has good spatial control. These results provide the first credible case of optogenetically induced protein expression in P. pastoris.
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Affiliation(s)
- Zhiqian Wang
- Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, MOE Key Laboratory of Molecular Biophysics, Wuhan 430074, People’s Republic of China
| | - Yunjun Yan
- Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, MOE Key Laboratory of Molecular Biophysics, Wuhan 430074, People’s Republic of China
| | - Houjin Zhang
- Department of Biotechnology, College of Life Science and Technology, Huazhong University of Science and Technology, MOE Key Laboratory of Molecular Biophysics, Wuhan 430074, People’s Republic of China
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32
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Gerhardt KP, Rao SD, Olson EJ, Igoshin OA, Tabor JJ. Independent control of mean and noise by convolution of gene expression distributions. Nat Commun 2021; 12:6957. [PMID: 34845228 PMCID: PMC8630168 DOI: 10.1038/s41467-021-27070-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 11/03/2021] [Indexed: 11/28/2022] Open
Abstract
Gene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from individual promoters. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer low and high noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.
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Affiliation(s)
- Karl P Gerhardt
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Satyajit D Rao
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Evan J Olson
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Oleg A Igoshin
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA
- Department of Biosciences, Rice University, 6100 Main Street, Houston, TX, 77005, USA
- Center for Theoretical Biophysics, Rice University, 6100 Main Street, Houston, TX, 77005, USA
- Department of Chemistry, Rice University, 6100 Main Street, Houston, TX, 77005, USA
| | - Jeffrey J Tabor
- Department of Bioengineering, Rice University, 6100 Main Street, Houston, TX, 77005, USA.
- Department of Biosciences, Rice University, 6100 Main Street, Houston, TX, 77005, USA.
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33
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Lee JB, Caywood LM, Lo JY, Levering N, Keung AJ. Mapping the dynamic transfer functions of eukaryotic gene regulation. Cell Syst 2021; 12:1079-1093.e6. [PMID: 34469745 DOI: 10.1016/j.cels.2021.08.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 05/26/2021] [Accepted: 08/04/2021] [Indexed: 11/19/2022]
Abstract
Biological information can be encoded within the dynamics of signaling components, which has been implicated in a broad range of physiological processes including stress response, oncogenesis, and stem cell differentiation. To study the complexity of information transfer across the eukaryotic promoter, we screened 119 dynamic conditions-modulating the pulse frequency, amplitude, and pulse width of light-regulating the binding of an epigenome editor to a fluorescent reporter. This system revealed tunable gene expression and filtering behaviors and provided a quantification of the limit to the amount of information that can be reliably transferred across a single promoter as ∼1.7 bits. Using a library of over 100 orthogonal chromatin regulators, we further determined that chromatin state could be used to tune mutual information and expression levels, as well as completely alter the input-output transfer function of the promoter. This system unlocks the information-rich content of eukaryotic gene regulation.
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Affiliation(s)
- Jessica B Lee
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27606, USA
| | - Leandra M Caywood
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27606, USA
| | - Jennifer Y Lo
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27606, USA
| | - Nicholas Levering
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27606, USA
| | - Albert J Keung
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC 27606, USA.
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34
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A light tunable differentiation system for the creation and control of consortia in yeast. Nat Commun 2021; 12:5829. [PMID: 34611168 PMCID: PMC8492667 DOI: 10.1038/s41467-021-26129-7] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 09/07/2021] [Indexed: 02/08/2023] Open
Abstract
Artificial microbial consortia seek to leverage division-of-labour to optimize function and possess immense potential for bioproduction. Co-culturing approaches, the preferred mode of generating a consortium, remain limited in their ability to give rise to stable consortia having finely tuned compositions. Here, we present an artificial differentiation system in budding yeast capable of generating stable microbial consortia with custom functionalities from a single strain at user-defined composition in space and in time based on optogenetically-driven genetic rewiring. Owing to fast, reproducible, and light-tunable dynamics, our system enables dynamic control of consortia composition in continuous cultures for extended periods. We further demonstrate that our system can be extended in a straightforward manner to give rise to consortia with multiple subpopulations. Our artificial differentiation strategy establishes a novel paradigm for the creation of complex microbial consortia that are simple to implement, precisely controllable, and versatile to use.
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35
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Kumar S, Rullan M, Khammash M. Rapid prototyping and design of cybergenetic single-cell controllers. Nat Commun 2021; 12:5651. [PMID: 34561433 PMCID: PMC8463601 DOI: 10.1038/s41467-021-25754-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 08/26/2021] [Indexed: 12/22/2022] Open
Abstract
The design and implementation of synthetic circuits that operate robustly in the cellular context is fundamental for the advancement of synthetic biology. However, their practical implementation presents challenges due to low predictability of synthetic circuit design and time-intensive troubleshooting. Here, we present the Cyberloop, a testing framework to accelerate the design process and implementation of biomolecular controllers. Cellular fluorescence measurements are sent in real-time to a computer simulating candidate stochastic controllers, which in turn compute the control inputs and feed them back to the controlled cells via light stimulation. Applying this framework to yeast cells engineered with optogenetic tools, we examine and characterize different biomolecular controllers, test the impact of non-ideal circuit behaviors such as dilution on their operation, and qualitatively demonstrate improvements in controller function with certain network modifications. From this analysis, we derive conditions for desirable biomolecular controller performance, thereby avoiding pitfalls during its biological implementation.
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Affiliation(s)
- Sant Kumar
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Marc Rullan
- 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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36
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Tan D, Chen R, Mo Y, Gu S, Ma J, Xu W, Lu X, He H, Jiang F, Fan W, Wang Y, Chen X, Huang W. Quantitative control of noise in mammalian gene expression by dynamic histone regulation. eLife 2021; 10:65654. [PMID: 34379055 PMCID: PMC8357418 DOI: 10.7554/elife.65654] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 06/23/2021] [Indexed: 12/11/2022] Open
Abstract
Fluctuation ('noise') in gene expression is critical for mammalian cellular processes. Numerous mechanisms contribute to its origins, yet the mechanisms behind large fluctuations that are induced by single transcriptional activators remain elusive. Here, we probed putative mechanisms by studying the dynamic regulation of transcriptional activator binding, histone regulator inhibitors, chromatin accessibility, and levels of mRNAs and proteins in single cells. Using a light-induced expression system, we showed that the transcriptional activator could form an interplay with dual functional co-activator/histone acetyltransferases CBP/p300. This interplay resulted in substantial heterogeneity in H3K27ac, chromatin accessibility, and transcription. Simultaneous attenuation of CBP/p300 and HDAC4/5 reduced heterogeneity in the expression of endogenous genes, suggesting that this mechanism is universal. We further found that the noise was reduced by pulse-wide modulation of transcriptional activator binding possibly as a result of alternating the epigenetic states. Our findings suggest a mechanism for the modulation of noise in synthetic and endogenous gene expression systems.
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Affiliation(s)
- Deng Tan
- School of Life Sciences, Southern University of Science and Technology, Shenzhen, China.,Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon, Hong Kong, China
| | - Rui Chen
- School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Yuejian Mo
- School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Shu Gu
- School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Jiao Ma
- School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Wei Xu
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Xibin Lu
- Core Research Facilities, Southern University of Science and Technology, Shenzhen, China
| | - Huiyu He
- School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Fan Jiang
- Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Weimin Fan
- School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Yili Wang
- Core Research Facilities, Southern University of Science and Technology, Shenzhen, China
| | - Xi Chen
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
| | - Wei Huang
- School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
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37
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Engineering AraC to make it responsive to light instead of arabinose. Nat Chem Biol 2021; 17:817-827. [PMID: 33903769 DOI: 10.1038/s41589-021-00787-6] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 03/19/2021] [Indexed: 02/02/2023]
Abstract
The L-arabinose-responsive AraC and its cognate PBAD promoter underlie one of the most often used chemically inducible prokaryotic gene expression systems in microbiology and synthetic biology. Here, we change the sensing capability of AraC from L-arabinose to blue light, making its dimerization and the resulting PBAD activation light-inducible. We engineer an entire family of blue light-inducible AraC dimers in Escherichia coli (BLADE) to control gene expression in space and time. We show that BLADE can be used with pre-existing L-arabinose-responsive plasmids and strains, enabling optogenetic experiments without the need to clone. Furthermore, we apply BLADE to control, with light, the catabolism of L-arabinose, thus externally steering bacterial growth with a simple transformation step. Our work establishes BLADE as a highly practical and effective optogenetic tool with plug-and-play functionality-features that we hope will accelerate the broader adoption of optogenetics and the realization of its vast potential in microbiology, synthetic biology and biotechnology.
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38
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Nguyen TM, Telek S, Zicler A, Martinez JA, Zacchetti B, Kopp J, Slouka C, Herwig C, Grünberger A, Delvigne F. Reducing phenotypic instabilities of a microbial population during continuous cultivation based on cell switching dynamics. Biotechnol Bioeng 2021; 118:3847-3859. [PMID: 34129251 DOI: 10.1002/bit.27860] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 06/11/2021] [Accepted: 06/12/2021] [Indexed: 12/19/2022]
Abstract
Predicting the fate of individual cells among a microbial population (i.e., growth and gene expression) remains a challenge, especially when this population is exposed to very dynamic environmental conditions, such as those encountered during continuous cultivation. Indeed, the dynamic nature of a continuous cultivation process implies the potential diversification of the microbial population resulting in genotypic and phenotypic heterogeneity. The present work focused on the induction of the arabinose operon in Escherichia coli as a model system to study this diversification process in continuous cultivations. As a preliminary step, the green fluorescent protein (GFP) level triggered by an arabinose-inducible ParaBAD promoter was tracked by flow cytometry in chemostat cultivations with glucose-arabinose co-feeding. For a wide range of glucose-arabinose co-feeding concentrations in the chemostats, the simultaneous occurrence of GFP positive and negative subpopulation was observed. In the second set of experiments, continuous cultivation was performed by adding glucose continuously and arabinose based on the capability of individual cells to switch from low GFP to high GFP expression states, performed with a technology setup called segregostat. In the segregostat cultivation mode, on-line flow cytometry analysis was used for adjusting the arabinose/glucose transitions based on the phenotypic switching profiles of the microbial population. This strategy allowed finding an appropriate arabinose pulsing frequency, leading to prolonged maintenance of the induction level with a limited increase in the phenotypic diversity for more than 60 generations. The results suggest that the steady forcing of individual cells into a given phenotypic trajectory may not be the best strategy for controlling cell populations. Instead, allowing individual cells to switch periodically around a predefined threshold seems to be a more robust strategy leading to oscillations, but within a predictable cell population behavior range.
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Affiliation(s)
- Thai M Nguyen
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Samuel Telek
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Andrew Zicler
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Juan A Martinez
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Boris Zacchetti
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
| | - Julian Kopp
- Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Vienna, Austria
| | - Christoph Slouka
- Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Vienna, Austria
| | - Christoph Herwig
- Christian Doppler Laboratory for Mechanistic and Physiological Methods for Improved Bioprocesses, Institute of Chemical, Environmental and Biological Engineering, Vienna University of Technology, Vienna, Austria.,Research Division Biochemical Engineering, Institute of Chemical Environmental and Bioscience Engineering, Vienna University of Technology, Vienna, Austria
| | - Alexander Grünberger
- Multiscale Bioengineering, Technical Faculty, Bielefeld Germany & CeBiTec, Bielefeld University, Bielefeld, Germany
| | - Frank Delvigne
- Terra Research and Teaching Centre, Microbial Processes and Interactions (MiPI), Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
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39
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Oh TJ, Fan H, Skeeters SS, Zhang K. Steering Molecular Activity with Optogenetics: Recent Advances and Perspectives. Adv Biol (Weinh) 2021; 5:e2000180. [PMID: 34028216 PMCID: PMC8218620 DOI: 10.1002/adbi.202000180] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Revised: 12/14/2020] [Indexed: 12/24/2022]
Abstract
Optogenetics utilizes photosensitive proteins to manipulate the localization and interaction of molecules in living cells. Because light can be rapidly switched and conveniently confined to the sub-micrometer scale, optogenetics allows for controlling cellular events with an unprecedented resolution in time and space. The past decade has witnessed an enormous progress in the field of optogenetics within the biological sciences. The ever-increasing amount of optogenetic tools, however, can overwhelm the selection of appropriate optogenetic strategies. Considering that each optogenetic tool may have a distinct mode of action, a comparative analysis of the current optogenetic toolbox can promote the further use of optogenetics, especially by researchers new to this field. This review provides such a compilation that highlights the spatiotemporal accuracy of current optogenetic systems. Recent advances of optogenetics in live cells and animal models are summarized, the emerging work that interlinks optogenetics with other research fields is presented, and exciting clinical and industrial efforts to employ optogenetic strategy toward disease intervention are reported.
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Affiliation(s)
- Teak-Jung Oh
- 600 South Mathews Avenue, 314 B Roger Adams Laboratory, Urbana, IL, 61801, USA
| | - Huaxun Fan
- 600 South Mathews Avenue, 314 B Roger Adams Laboratory, Urbana, IL, 61801, USA
| | - Savanna S Skeeters
- 600 South Mathews Avenue, 314 B Roger Adams Laboratory, Urbana, IL, 61801, USA
| | - Kai Zhang
- 600 South Mathews Avenue, 314 B Roger Adams Laboratory, Urbana, IL, 61801, USA
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40
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Lunz D. On rapid oscillations driving biological processes at disparate timescales. Phys Biol 2021; 18:036002. [PMID: 33418553 DOI: 10.1088/1478-3975/abd9db] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
We consider a generic biological process described by a dynamical system, subject to an input signal with a high-frequency periodic component. The rapid oscillations of the input signal induce inherently multiscale dynamics, motivating order-reduction techniques. It is intuitive that the system behaviour is well approximated by its response to the averaged input signal. However, changes to the high-frequency component that preserve the average signal are beyond the reach of such intuitive reasoning. In this study, we explore system response under the influence of such an input signal by exploiting the timescale separation between high-frequency input variations and system response time. Employing the asymptotic method of multiple scales, we establish that, in some circumstances, the intuitive approach is simply the leading-order asymptotic contribution. We focus on higher-order corrections that capture the response to the details of the high-frequency component beyond its average. This approach achieves a reduction in system complexity while providing valuable insight into the structure of the response to the oscillations. We develop the general theory for nonlinear systems, while highlighting the important case of systems affine in the state and the input signal, presenting examples of both discrete and continuum state spaces. Importantly, this class of systems encompasses biochemical reaction networks described by the chemical master equation and its continuum approximations. Finally, we apply the framework to a nonlinear system describing mRNA translation and protein expression previously studied in the literature. The analysis shines new light on several aspects of the system quantification and both extends and simplifies results previously obtained.
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Affiliation(s)
- Davin Lunz
- INRIA Saclay-Île de France, 91120 Palaiseau, France.,École Polytechnique, CMAP 91128 Palaiseau, France.,Institut Pasteur, 75015 Paris, France
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41
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Christie JM, Zurbriggen MD. Optogenetics in plants. THE NEW PHYTOLOGIST 2021; 229:3108-3115. [PMID: 33064858 DOI: 10.1111/nph.17008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Accepted: 09/18/2020] [Indexed: 06/11/2023]
Abstract
The last two decades have witnessed the emergence of optogenetics; a field that has given researchers the ability to use light to control biological processes at high spatiotemporal and quantitative resolutions, in a reversible manner with minimal side-effects. Optogenetics has revolutionized the neurosciences, increased our understanding of cellular signalling and metabolic networks and resulted in variety of applications in biotechnology and biomedicine. However, implementing optogenetics in plants has been less straightforward, given their dependency on light for their life cycle. Here, we highlight some of the widely used technologies in microorganisms and animal systems derived from plant photoreceptor proteins and discuss strategies recently implemented to overcome the challenges for using optogenetics in plants.
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Affiliation(s)
- John M Christie
- Institute of Molecular, Cell and Systems Biology, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Matias D Zurbriggen
- Institute of Synthetic Biology and CEPLAS, University of Duesseldorf, Duesseldorf, 40225, Germany
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42
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Baumschlager A, Khammash M. Synthetic Biological Approaches for Optogenetics and Tools for Transcriptional Light-Control in Bacteria. Adv Biol (Weinh) 2021; 5:e2000256. [PMID: 34028214 DOI: 10.1002/adbi.202000256] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 01/11/2021] [Indexed: 12/22/2022]
Abstract
Light has become established as a tool not only to visualize and investigate but also to steer biological systems. This review starts by discussing the unique features that make light such an effective control input in biology. It then gives an overview of how light-control came to progress, starting with photoactivatable compounds and leading up to current genetic implementations using optogenetic approaches. The review then zooms in on optogenetics, focusing on photosensitive proteins, which form the basis for optogenetic engineering using synthetic biological approaches. As the regulation of transcription provides a highly versatile means for steering diverse biological functions, the focus of this review then shifts to transcriptional light regulators, which are presented in the biotechnologically highly relevant model organism Escherichia coli.
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Affiliation(s)
- Armin Baumschlager
- Department of Biosystems Science and Engineering (D-BSSE), ETH-Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH-Zürich, Mattenstrasse 26, Basel, 4058, Switzerland
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43
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Li T, Chen X, Qian Y, Shao J, Li X, Liu S, Zhu L, Zhao Y, Ye H, Yang Y. A synthetic BRET-based optogenetic device for pulsatile transgene expression enabling glucose homeostasis in mice. Nat Commun 2021; 12:615. [PMID: 33504786 PMCID: PMC7840992 DOI: 10.1038/s41467-021-20913-1] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Accepted: 12/21/2020] [Indexed: 12/26/2022] Open
Abstract
Pulsing cellular dynamics in genetic circuits have been shown to provide critical capabilities to cells in stress response, signaling and development. Despite the fascinating discoveries made in the past few years, the mechanisms and functional capabilities of most pulsing systems remain unclear, and one of the critical challenges is the lack of a technology that allows pulsatile regulation of transgene expression both in vitro and in vivo. Here, we describe the development of a synthetic BRET-based transgene expression (LuminON) system based on a luminescent transcription factor, termed luminGAVPO, by fusing NanoLuc luciferase to the light-switchable transcription factor GAVPO. luminGAVPO allows pulsatile and quantitative activation of transgene expression via both chemogenetic and optogenetic approaches in mammalian cells and mice. Both the pulse amplitude and duration of transgene expression are highly tunable via adjustment of the amount of furimazine. We further demonstrated LuminON-mediated blood-glucose homeostasis in type 1 diabetic mice. We believe that the BRET-based LuminON system with the pulsatile dynamics of transgene expression provides a highly sensitive tool for precise manipulation in biological systems that has strong potential for application in diverse basic biological studies and gene- and cell-based precision therapies in the future.
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Affiliation(s)
- Ting Li
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
- School of Pharmacy, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
| | - Xianjun Chen
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
- School of Pharmacy, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yajie Qian
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
- School of Pharmacy, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
| | - Jiawei Shao
- Synthetic Biology and Biomedical Engineering Laboratory, Biomedical Synthetic Biology Research Center, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Dongchuan Road 500, Shanghai, 200241, China
| | - Xie Li
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
- School of Pharmacy, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
| | - Shuning Liu
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
- School of Pharmacy, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
| | - Linyong Zhu
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
| | - Yuzheng Zhao
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
- School of Pharmacy, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China
| | - Haifeng Ye
- Synthetic Biology and Biomedical Engineering Laboratory, Biomedical Synthetic Biology Research Center, Shanghai Key Laboratory of Regulatory Biology, Institute of Biomedical Sciences and School of Life Sciences, East China Normal University, Dongchuan Road 500, Shanghai, 200241, China.
| | - Yi Yang
- Optogenetics & Synthetic Biology Interdisciplinary Research Center, State Key Laboratory of Bioreactor Engineering, Shanghai Collaborative Innovation Center for Biomanufacturing Technology, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China.
- School of Pharmacy, East China University of Science and Technology, 130 Mei Long Road, Shanghai, 200237, China.
- CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China.
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44
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Bonny AR, Fonseca JP, Park JE, El-Samad H. Orthogonal control of mean and variability of endogenous genes in a human cell line. Nat Commun 2021; 12:292. [PMID: 33436569 PMCID: PMC7804932 DOI: 10.1038/s41467-020-20467-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 11/25/2020] [Indexed: 12/11/2022] Open
Abstract
Stochastic fluctuations at the transcriptional level contribute to isogenic cell-to-cell heterogeneity in mammalian cell populations. However, we still have no clear understanding of the repercussions of this heterogeneity, given the lack of tools to independently control mean expression and variability of a gene. Here, we engineer a synthetic circuit to modulate mean expression and heterogeneity of transgenes and endogenous human genes. The circuit, a Tunable Noise Rheostat (TuNR), consists of a transcriptional cascade of two inducible transcriptional activators, where the output mean and variance can be modulated by two orthogonal small molecule inputs. In this fashion, different combinations of the inputs can achieve the same mean but with different population variability. With TuNR, we achieve low basal expression, over 1000-fold expression of a transgene product, and up to 7-fold induction of the endogenous gene NGFR. Importantly, for the same mean expression level, we are able to establish varying degrees of heterogeneity in expression within an isogenic population, thereby decoupling gene expression noise from its mean. TuNR is therefore a modular tool that can be used in mammalian cells to enable direct interrogation of the implications of cell-to-cell variability.
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Affiliation(s)
- Alain R Bonny
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - João Pedro Fonseca
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
- Amyris Bio Products Portugal, Porto, Portugal
| | - Jesslyn E Park
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Hana El-Samad
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, 94158, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
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45
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Zhao EM, Lalwani MA, Lovelett RJ, García-Echauri SA, Hoffman SM, Gonzalez CL, Toettcher JE, Kevrekidis IG, Avalos JL. Design and Characterization of Rapid Optogenetic Circuits for Dynamic Control in Yeast Metabolic Engineering. ACS Synth Biol 2020; 9:3254-3266. [PMID: 33232598 PMCID: PMC10399620 DOI: 10.1021/acssynbio.0c00305] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
The use of optogenetics in metabolic engineering for light-controlled microbial chemical production raises the prospect of utilizing control and optimization techniques routinely deployed in traditional chemical manufacturing. However, such mechanisms require well-characterized, customizable tools that respond fast enough to be used as real-time inputs during fermentations. Here, we present OptoINVRT7, a new rapid optogenetic inverter circuit to control gene expression in Saccharomyces cerevisiae. The circuit induces gene expression in only 0.6 h after switching cells from light to darkness, which is at least 6 times faster than previous OptoINVRT optogenetic circuits used for chemical production. In addition, we introduce an engineered inducible GAL1 promoter (PGAL1-S), which is stronger than any constitutive or inducible promoter commonly used in yeast. Combining OptoINVRT7 with PGAL1-S achieves strong and light-tunable levels of gene expression with as much as 132.9 ± 22.6-fold induction in darkness. The high performance of this new optogenetic circuit in controlling metabolic enzymes boosts production of lactic acid and isobutanol by more than 50% and 15%, respectively. The strength and controllability of OptoINVRT7 and PGAL1-S open the door to applying process control tools to engineered metabolisms to improve robustness and yields in microbial fermentations for chemical production.
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Affiliation(s)
- Evan M. Zhao
- Department of Chemical and Biological Engineering, Hoyt Laboratory
101, Princeton University, William Street, Princeton, New Jersey 08544, United States
| | - Makoto A. Lalwani
- Department of Chemical and Biological Engineering, Hoyt Laboratory
101, Princeton University, William Street, Princeton, New Jersey 08544, United States
| | - Robert J. Lovelett
- Department of Chemical and Biological Engineering, Hoyt Laboratory
101, Princeton University, William Street, Princeton, New Jersey 08544, United States
- Department of Chemical and Biomolecular Engineering, 221 Maryland
Hall, Johns Hopkins University, 2400 N. Charles Street, Baltimore, Maryland 21218, United States
| | - Sergio A. García-Echauri
- Department of Chemical and Biological Engineering, Hoyt Laboratory
101, Princeton University, William Street, Princeton, New Jersey 08544, United States
| | - Shannon M. Hoffman
- Department of Chemical and Biological Engineering, Hoyt Laboratory
101, Princeton University, William Street, Princeton, New Jersey 08544, United States
| | - Christopher L. Gonzalez
- Department of Chemical and Biological Engineering, Hoyt Laboratory
101, Princeton University, William Street, Princeton, New Jersey 08544, United States
| | - Jared E. Toettcher
- Department of Molecular Biology, 140 Lewis Thomas Laboratory, Princeton University, Washington Road, Princeton, New Jersey 08544, United States
| | - Ioannis G. Kevrekidis
- Department of Chemical and Biological Engineering, Hoyt Laboratory
101, Princeton University, William Street, Princeton, New Jersey 08544, United States
- Department of Chemical and Biomolecular Engineering, 221 Maryland
Hall, Johns Hopkins University, 2400 N. Charles Street, Baltimore, Maryland 21218, United States
| | - José L. Avalos
- Department of Chemical and Biological Engineering, Hoyt Laboratory
101, Princeton University, William Street, Princeton, New Jersey 08544, United States
- Department of Molecular Biology, 140 Lewis Thomas Laboratory, Princeton University, Washington Road, Princeton, New Jersey 08544, United States
- The Andlinger Center for Energy and the Environment, Princeton University, 86 Olden Street, Princeton, New Jersey 08544, United States
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46
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Figueroa D, Rojas V, Romero A, Larrondo LF, Salinas F. The rise and shine of yeast optogenetics. Yeast 2020; 38:131-146. [PMID: 33119964 DOI: 10.1002/yea.3529] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 10/20/2020] [Accepted: 10/22/2020] [Indexed: 12/11/2022] Open
Abstract
Optogenetics refers to the control of biological processes with light. The activation of cellular phenomena by defined wavelengths has several advantages compared with traditional chemically inducible systems, such as spatiotemporal resolution, dose-response regulation, low cost, and moderate toxic effects. Optogenetics has been successfully implemented in yeast, a remarkable biological platform that is not only a model organism for cellular and molecular biology studies, but also a microorganism with diverse biotechnological applications. In this review, we summarize the main optogenetic systems implemented in the budding yeast Saccharomyces cerevisiae, which allow orthogonal control (by light) of gene expression, protein subcellular localization, reconstitution of protein activity, and protein sequestration by oligomerization. Furthermore, we review the application of optogenetic systems in the control of metabolic pathways, heterologous protein production and flocculation. We then revise an example of a previously described yeast optogenetic switch, named FUN-LOV, which allows precise and strong activation of the target gene. Finally, we describe optogenetic systems that have not yet been implemented in yeast, which could therefore be used to expand the panel of available tools in this biological chassis. In conclusion, a wide repertoire of optogenetic systems can be used to address fundamental biological questions and broaden the biotechnological toolkit in yeast.
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Affiliation(s)
- David Figueroa
- Instituto de Bioquímica y Microbiología, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile.,ANID - Millennium Science Initiative - Millennium Institute for Integrative Biology (iBIO), Santiago, Chile
| | - Vicente Rojas
- ANID - Millennium Science Initiative - Millennium Institute for Integrative Biology (iBIO), Santiago, Chile.,Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Andres Romero
- ANID - Millennium Science Initiative - Millennium Institute for Integrative Biology (iBIO), Santiago, Chile.,Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Luis F Larrondo
- ANID - Millennium Science Initiative - Millennium Institute for Integrative Biology (iBIO), Santiago, Chile.,Departamento de Genética Molecular y Microbiología, Facultad de Ciencias Biológicas, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Francisco Salinas
- Instituto de Bioquímica y Microbiología, Facultad de Ciencias, Universidad Austral de Chile, Valdivia, Chile.,ANID - Millennium Science Initiative - Millennium Institute for Integrative Biology (iBIO), Santiago, Chile
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47
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Pouzet S, Banderas A, Le Bec M, Lautier T, Truan G, Hersen P. The Promise of Optogenetics for Bioproduction: Dynamic Control Strategies and Scale-Up Instruments. Bioengineering (Basel) 2020; 7:E151. [PMID: 33255280 PMCID: PMC7712799 DOI: 10.3390/bioengineering7040151] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/11/2020] [Accepted: 11/19/2020] [Indexed: 12/18/2022] Open
Abstract
Progress in metabolic engineering and synthetic and systems biology has made bioproduction an increasingly attractive and competitive strategy for synthesizing biomolecules, recombinant proteins and biofuels from renewable feedstocks. Yet, due to poor productivity, it remains difficult to make a bioproduction process economically viable at large scale. Achieving dynamic control of cellular processes could lead to even better yields by balancing the two characteristic phases of bioproduction, namely, growth versus production, which lie at the heart of a trade-off that substantially impacts productivity. The versatility and controllability offered by light will be a key element in attaining the level of control desired. The popularity of light-mediated control is increasing, with an expanding repertoire of optogenetic systems for novel applications, and many optogenetic devices have been designed to test optogenetic strains at various culture scales for bioproduction objectives. In this review, we aim to highlight the most important advances in this direction. We discuss how optogenetics is currently applied to control metabolism in the context of bioproduction, describe the optogenetic instruments and devices used at the laboratory scale for strain development, and explore how current industrial-scale bioproduction processes could be adapted for optogenetics or could benefit from existing photobioreactor designs. We then draw attention to the steps that must be undertaken to further optimize the control of biological systems in order to take full advantage of the potential offered by microbial factories.
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Affiliation(s)
- Sylvain Pouzet
- Laboratoire Physico Chimie Curie, Institut Curie, PSL Research University, CNRS UMR168, 26 rue d’Ulm, 75005 Paris, France; (A.B.); (M.L.B.)
- Sorbonne Université, 75005 Paris, France
- Laboratoire MSC, UMR7057, Université Paris Diderot-CNRS, 75013 Paris, France
| | - Alvaro Banderas
- Laboratoire Physico Chimie Curie, Institut Curie, PSL Research University, CNRS UMR168, 26 rue d’Ulm, 75005 Paris, France; (A.B.); (M.L.B.)
- Sorbonne Université, 75005 Paris, France
- Laboratoire MSC, UMR7057, Université Paris Diderot-CNRS, 75013 Paris, France
| | - Matthias Le Bec
- Laboratoire Physico Chimie Curie, Institut Curie, PSL Research University, CNRS UMR168, 26 rue d’Ulm, 75005 Paris, France; (A.B.); (M.L.B.)
- Sorbonne Université, 75005 Paris, France
- Laboratoire MSC, UMR7057, Université Paris Diderot-CNRS, 75013 Paris, France
| | - Thomas Lautier
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, 31400 Toulouse, France; (T.L.); (G.T.)
- Singapore Institute of Food and Biotechnology Innovation, Agency for Science Technology and Research, Singapore 138673, Singapore
| | - Gilles Truan
- Toulouse Biotechnology Institute, Université de Toulouse, CNRS, INRAE, INSA, 31400 Toulouse, France; (T.L.); (G.T.)
| | - Pascal Hersen
- Laboratoire Physico Chimie Curie, Institut Curie, PSL Research University, CNRS UMR168, 26 rue d’Ulm, 75005 Paris, France; (A.B.); (M.L.B.)
- Sorbonne Université, 75005 Paris, France
- Laboratoire MSC, UMR7057, Université Paris Diderot-CNRS, 75013 Paris, France
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48
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Ilan Y, Spigelman Z. Establishing patient-tailored variability-based paradigms for anti-cancer therapy: Using the inherent trajectories which underlie cancer for overcoming drug resistance. Cancer Treat Res Commun 2020; 25:100240. [PMID: 33246316 DOI: 10.1016/j.ctarc.2020.100240] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Revised: 10/30/2020] [Accepted: 11/16/2020] [Indexed: 06/11/2023]
Abstract
Drug resistance is a major obstacle for successful therapy of many malignancies and is affecting the loss of response to chemotherapy and immunotherapy. Tumor-related compensatory adaptation mechanisms contribute to the development of drug resistance. Variability is inherent to biological systems and altered patterns of variability are associated with disease conditions. The marked intra and inter patient tumor heterogeneity, and the diverse mechanism contributing to drug resistance in different subjects, which may change over time even in the same patient, necessitate the development of personalized dynamic approaches for overcoming drug resistance. Altered dosing regimens, the potential role of chronotherapy, and drug holidays are effective in cancer therapy and immunotherapy. In the present review we describe the difficulty of overcoming drug resistance in a dynamic system and present the use of the inherent trajectories which underlie cancer development for building therapeutic regimens which can overcome resistance. The establishment of a platform wherein patient-tailored variability signatures are used for overcoming resistance for ensuing long term sustainable improved responses is presented.
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Affiliation(s)
- Yaron Ilan
- Department of Medicine, Hebrew University-Hadassah Medical Center, Jerusalem, Israel.
| | - Zachary Spigelman
- Department of Hematology and Oncology, Lahey Hospital and Beth Israel Medical Center, MA, USA
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49
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Qi H, Li X, Jin Z, Simmen T, Shuai J. The Oscillation Amplitude, Not the Frequency of Cytosolic Calcium, Regulates Apoptosis Induction. iScience 2020; 23:101671. [PMID: 33196017 PMCID: PMC7644924 DOI: 10.1016/j.isci.2020.101671] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 08/15/2020] [Accepted: 10/08/2020] [Indexed: 01/06/2023] Open
Abstract
Although a rising concentration of cytosolic Ca2+ has long been recognized as an essential signal for apoptosis, the dynamical mechanisms by which Ca2+ regulates apoptosis are not clear yet. To address this, we constructed a computational model that integrates known biochemical reactions and can reproduce the dynamical behaviors of Ca2+-induced apoptosis as observed in experiments. Model analysis shows that oscillating Ca2+ signals first convert into gradual signals and eventually transform into a switch-like apoptotic response. Via the two processes, the apoptotic signaling pathway filters the frequency of Ca2+ oscillations effectively but instead responds acutely to their amplitude. Collectively, our results suggest that Ca2+ regulates apoptosis mainly via oscillation amplitude, rather than frequency, modulation. This study not only provides a comprehensive understanding of how oscillatory Ca2+ dynamically regulates the complex apoptotic signaling network but also presents a typical example of how Ca2+ controls cellular responses through amplitude modulation.
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Affiliation(s)
- Hong Qi
- Complex Systems Research Center, Shanxi University, Taiyuan 030006, China.,Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention, Shanxi University, Taiyuan 030006, China
| | - Xiang Li
- Department of Physics, Xiamen University, Xiamen 361005, China.,State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, Xiamen University, Xiamen 361102, China.,National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361102, China
| | - Zhen Jin
- Complex Systems Research Center, Shanxi University, Taiyuan 030006, China.,Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention, Shanxi University, Taiyuan 030006, China
| | - Thomas Simmen
- Faculty of Medicine and Dentistry, Department of Cell Biology, University of Alberta, Edmonton, AB T6G2H7, Canada
| | - Jianwei Shuai
- Department of Physics, Xiamen University, Xiamen 361005, China.,State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, Xiamen University, Xiamen 361102, China.,National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen 361102, China
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50
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Chen X, Zhang C, Lindley ND. Metabolic Engineering Strategies for Sustainable Terpenoid Flavor and Fragrance Synthesis. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2020; 68:10252-10264. [PMID: 31865696 DOI: 10.1021/acs.jafc.9b06203] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Terpenoids derived from plant material are widely applied in the flavor and fragrance industry. Traditional extraction methods are unsustainable, but microbial synthesis offers a promising solution to attain efficient production of natural-identical terpenoids. Overproduction of terpenoids in microbes requires careful balancing of the synthesis pathway constituents within the constraints of host cell metabolism. Advances in metabolic engineering have greatly facilitated overcoming the challenges of achieving high titers, rates, and yields (TRYs). The review summarizes recent development in the molecular biology toolbox to achieve high TRYs for terpenoid biosynthesis, mainly in the two industrial platform microorganisms: Escherichia coli and Saccharomyces cerevisiae. The biosynthetic pathways, including alternative pathway designs, are briefly introduced, followed by recently developed methodologies used for pathway, genome, and strain optimization. Integrated applications of these tools are important to achieve high "TRYs" of terpenoid production and pave the way for translating laboratory research into successful commercial manufacturing.
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Affiliation(s)
- Xixian Chen
- Biotransformation Innovation Platform, Agency for Science, Technology and Research (A*STAR), 61 Biopolis Drive, Singapore 138673
| | - Congqiang Zhang
- Biotransformation Innovation Platform, Agency for Science, Technology and Research (A*STAR), 61 Biopolis Drive, Singapore 138673
| | - Nicholas D Lindley
- Biotransformation Innovation Platform, Agency for Science, Technology and Research (A*STAR), 61 Biopolis Drive, Singapore 138673
- TBI, Université de Toulouse, CNRS, INRA, INSA,31077 Toulouse, France
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