1
|
Chan DTC, Bernstein HC. Pangenomic landscapes shape performances of a synthetic genetic circuit across Stutzerimonas species. mSystems 2024:e0084924. [PMID: 39166875 DOI: 10.1128/msystems.00849-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Accepted: 07/18/2024] [Indexed: 08/23/2024] Open
Abstract
Engineering identical genetic circuits into different species typically results in large differences in performance due to the unique cellular environmental context of each host, a phenomenon known as the "chassis-effect" or "context-dependency". A better understanding of how genomic and physiological contexts underpin the chassis-effect will improve biodesign strategies across diverse microorganisms. Here, we combined a pangenomic-based gene expression analysis with quantitative measurements of performance from an engineered genetic inverter device to uncover how genome structure and function relate to the observed chassis-effect across six closely related Stutzerimonas hosts. Our results reveal that genome architecture underpins divergent responses between our chosen non-model bacterial hosts to the engineered device. Specifically, differential expression of the core genome, gene clusters shared between all hosts, was found to be the main source of significant concordance to the observed differential genetic device performance, whereas specialty genes from respective accessory genomes were not significant. A data-driven investigation revealed that genes involved in denitrification and components of trans-membrane transporter proteins were among the most differentially expressed gene clusters between hosts in response to the genetic device. Our results show that the chassis-effect can be traced along differences among the most conserved genome-encoded functions and that these differences create a unique biodesign space among closely related species.IMPORTANCEContemporary synthetic biology endeavors often default to a handful of model organisms to host their engineered systems. Model organisms such as Escherichia coli serve as attractive hosts due to their tractability but do not necessarily provide the ideal environment to optimize performance. As more novel microbes are domesticated for use as biotechnology platforms, synthetic biologists are urged to explore the chassis-design space to optimize their systems and deliver on the promises of synthetic biology. The consequences of the chassis-effect will therefore only become more relevant as the field of biodesign grows. In our work, we demonstrate that the performance of a genetic device is highly dependent on the host environment it operates within, promoting the notion that the chassis can be considered a design variable to tune circuit function. Importantly, our results unveil that the chassis-effect can be traced along similarities in genome architecture, specifically the shared core genome. Our study advocates for the exploration of the chassis-design space and is a step forward to empowering synthetic biologists with knowledge for more efficient exploration of the chassis-design space to enable the next generation of broad-host-range synthetic biology.
Collapse
Affiliation(s)
- Dennis Tin Chat Chan
- Faculty of Biosciences, Fisheries and Economics, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Hans C Bernstein
- Faculty of Biosciences, Fisheries and Economics, UiT - The Arctic University of Norway, Tromsø, Norway
- The Arctic Centre for Sustainable Energy, UiT - The Arctic University of Norway, Tromsø, Norway
| |
Collapse
|
2
|
Roehner N, Roberts J, Lapets A, Gould D, Akavoor V, Qin L, Gordon DB, Voigt C, Densmore D. GOLDBAR: A Framework for Combinatorial Biological Design. ACS Synth Biol 2024. [PMID: 39162314 DOI: 10.1021/acssynbio.4c00296] [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: 08/21/2024]
Abstract
With the rise of new DNA part libraries and technologies for assembling DNA, synthetic biologists are increasingly constructing and screening combinatorial libraries to optimize their biological designs. As combinatorial libraries are used to generate data on design performance, new rules for composing biological designs will emerge. Most formal frameworks for combinatorial design, however, do not yet support formal comparison of design composition, which is needed to facilitate automated analysis and machine learning in massive biological design spaces. To address this need, we introduce a combinatorial design framework called GOLDBAR. Compared with existing frameworks, GOLDBAR enables synthetic biologists to intersect and merge the rules for entire classes of biological designs to extract common design motifs and infer new ones. Here, we demonstrate the application of GOLDBAR to refine/validate design spaces for TetR-homologue transcriptional logic circuits, verify the assembly of a partial nif gene cluster, and infer novel gene clusters for the biosynthesis of rebeccamycin. We also discuss how GOLDBAR could be used to facilitate grammar-based machine learning in synthetic biology.
Collapse
Affiliation(s)
- Nicholas Roehner
- RTX BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - James Roberts
- Biological Design Center, Boston University, Boston, Massachusetts 02215, United States
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
| | | | - Dany Gould
- Hariri Institute for Computing, Boston University, Boston, Massachusetts 02215, United States
| | - Vidya Akavoor
- Hariri Institute for Computing, Boston University, Boston, Massachusetts 02215, United States
| | - Lucy Qin
- Hariri Institute for Computing, Boston University, Boston, Massachusetts 02215, United States
| | - D Benjamin Gordon
- The Foundry, 75 Ames Street, Cambridge, Massachusetts 02142, United States
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Christopher Voigt
- The Foundry, 75 Ames Street, Cambridge, Massachusetts 02142, United States
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, United States
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Douglas Densmore
- Biological Design Center, Boston University, Boston, Massachusetts 02215, United States
- Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts 02215, United States
| |
Collapse
|
3
|
Joshi SHN, Jenkins C, Ulaeto D, Gorochowski TE. Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology. BIODESIGN RESEARCH 2024; 6:0037. [PMID: 38919711 PMCID: PMC11197468 DOI: 10.34133/bdr.0037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 04/23/2024] [Indexed: 06/27/2024] Open
Abstract
Living cells are exquisitely tuned to sense and respond to changes in their environment. Repurposing these systems to create engineered biosensors has seen growing interest in the field of synthetic biology and provides a foundation for many innovative applications spanning environmental monitoring to improved biobased production. In this review, we present a detailed overview of currently available biosensors and the methods that have supported their development, scale-up, and deployment. We focus on genetic sensors in living cells whose outputs affect gene expression. We find that emerging high-throughput experimental assays and evolutionary approaches combined with advanced bioinformatics and machine learning are establishing pipelines to produce genetic sensors for virtually any small molecule, protein, or nucleic acid. However, more complex sensing tasks based on classifying compositions of many stimuli and the reliable deployment of these systems into real-world settings remain challenges. We suggest that recent advances in our ability to precisely modify nonmodel organisms and the integration of proven control engineering principles (e.g., feedback) into the broader design of genetic sensing systems will be necessary to overcome these hurdles and realize the immense potential of the field.
Collapse
Affiliation(s)
| | - Christopher Jenkins
- CBR Division, Defence Science and Technology Laboratory, Porton Down, Wiltshire SP4 0JQ, UK
| | - David Ulaeto
- CBR Division, Defence Science and Technology Laboratory, Porton Down, Wiltshire SP4 0JQ, UK
| | - Thomas E. Gorochowski
- School of Biological Sciences, University of Bristol, Bristol BS8 1TQ, UK
- BrisEngBio,
School of Chemistry, University of Bristol, Bristol BS8 1TS, UK
| |
Collapse
|
4
|
Fedorec AJH, Treloar NJ, Wen KY, Dekker L, Ong QH, Jurkeviciute G, Lyu E, Rutter JW, Zhang KJY, Rosa L, Zaikin A, Barnes CP. Emergent digital bio-computation through spatial diffusion and engineered bacteria. Nat Commun 2024; 15:4896. [PMID: 38851790 PMCID: PMC11162413 DOI: 10.1038/s41467-024-49264-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 05/30/2024] [Indexed: 06/10/2024] Open
Abstract
Biological computing is a promising field with potential applications in biosafety, environmental monitoring, and personalized medicine. Here we present work on the design of bacterial computers using spatial patterning to process information in the form of diffusible morphogen-like signals. We demonstrate, mathematically and experimentally, that single, modular, colonies can perform simple digital logic, and that complex functions can be built by combining multiple colonies, removing the need for further genetic engineering. We extend our experimental system to incorporate sender colonies as morphogen sources, demonstrating how one might integrate different biochemical inputs. Our approach will open up ways to perform biological computation, with applications in bioengineering, biomaterials and biosensing. Ultimately, these computational bacterial communities will help us explore information processing in natural biological systems.
Collapse
Affiliation(s)
- Alex J H Fedorec
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK.
| | - Neythen J Treloar
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Ke Yan Wen
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Linda Dekker
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Qing Hsuan Ong
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Gabija Jurkeviciute
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Enbo Lyu
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Jack W Rutter
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Kathleen J Y Zhang
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Luca Rosa
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
| | - Alexey Zaikin
- Department of Mathematics, University College London, London, WC1E 6BT, UK
- Institute for Women's Health, University College London, London, WC1E 6BT, UK
| | - Chris P Barnes
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK.
| |
Collapse
|
5
|
Sun Y, Zhang F, Ouyang Q, Luo C. The dynamic-process characterization and prediction of synthetic gene circuits by dynamic delay model. iScience 2024; 27:109142. [PMID: 38384832 PMCID: PMC10879701 DOI: 10.1016/j.isci.2024.109142] [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: 10/02/2023] [Revised: 01/17/2024] [Accepted: 02/01/2024] [Indexed: 02/23/2024] Open
Abstract
Differential equation models are widely used to describe genetic regulations, predict multicomponent regulatory circuits, and provide quantitative insights. However, it is still challenging to quantitatively link the dynamic behaviors with measured parameters in synthetic circuits. Here, we propose a dynamic delay model (DDM) which includes two simple parts: the dynamic determining part and the doses-related steady-state-determining part. The dynamic determining part is usually supposed as the delay time but without a clear formula. For the first time, we give the detail formula of the dynamic determining function and provide a method for measuring all parameters of synthetic elements (include 8 activators and 5 repressors) by microfluidic system. Three synthetic circuits were built to show that the DDM can notably improve the prediction accuracy and can be used in various synthetic biology applications.
Collapse
Affiliation(s)
- Yanhong Sun
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Fengyu Zhang
- Wenzhou Institute University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
| | - Qi Ouyang
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Chunxiong Luo
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Wenzhou Institute University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325001, China
| |
Collapse
|
6
|
Buson F, Gao Y, Wang B. Genetic Parts and Enabling Tools for Biocircuit Design. ACS Synth Biol 2024; 13:697-713. [PMID: 38427821 DOI: 10.1021/acssynbio.3c00691] [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: 03/03/2024]
Abstract
Synthetic biology aims to engineer biological systems for customized tasks through the bottom-up assembly of fundamental building blocks, which requires high-quality libraries of reliable, modular, and standardized genetic parts. To establish sets of parts that work well together, synthetic biologists created standardized part libraries in which every component is analyzed in the same metrics and context. Here we present a state-of-the-art review of the currently available part libraries for designing biocircuits and their gene expression regulation paradigms at transcriptional, translational, and post-translational levels in Escherichia coli. We discuss the necessary facets to integrate these parts into complex devices and systems along with the current efforts to catalogue and standardize measurement data. To better display the range of available parts and to facilitate part selection in synthetic biology workflows, we established biopartsDB, a curated database of well-characterized and useful genetic part and device libraries with detailed quantitative data validated by the published literature.
Collapse
Affiliation(s)
- Felipe Buson
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310058, China
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FF, U.K
| | - Yuanli Gao
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310058, China
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FF, U.K
| | - Baojun Wang
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310058, China
| |
Collapse
|
7
|
Gao Y, Wang L, Wang B. Customizing cellular signal processing by synthetic multi-level regulatory circuits. Nat Commun 2023; 14:8415. [PMID: 38110405 PMCID: PMC10728147 DOI: 10.1038/s41467-023-44256-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 12/05/2023] [Indexed: 12/20/2023] Open
Abstract
As synthetic biology permeates society, the signal processing circuits in engineered living systems must be customized to meet practical demands. Towards this mission, novel regulatory mechanisms and genetic circuits with unprecedented complexity have been implemented over the past decade. These regulatory mechanisms, such as transcription and translation control, could be integrated into hybrid circuits termed "multi-level circuits". The multi-level circuit design will tremendously benefit the current genetic circuit design paradigm, from modifying basic circuit dynamics to facilitating real-world applications, unleashing our capabilities to customize cellular signal processing and address global challenges through synthetic biology.
Collapse
Affiliation(s)
- Yuanli Gao
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, China
- School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3FF, UK
| | - Lei Wang
- Center of Synthetic Biology and Integrated Bioengineering & School of Engineering, Westlake University, Hangzhou, 310030, China.
| | - Baojun Wang
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, 310058, China.
- Research Center for Biological Computation, Zhejiang Lab, Hangzhou, 311100, China.
| |
Collapse
|
8
|
Li J, Zhang H, Li D, Liu YJ, Bayer EA, Cui Q, Feng Y, Zhu P. Structure of the transcription open complex of distinct σ I factors. Nat Commun 2023; 14:6455. [PMID: 37833284 PMCID: PMC10575876 DOI: 10.1038/s41467-023-41796-4] [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: 03/22/2023] [Accepted: 09/15/2023] [Indexed: 10/15/2023] Open
Abstract
Bacterial σI factors of the σ70-family are widespread in Bacilli and Clostridia and are involved in the heat shock response, iron metabolism, virulence, and carbohydrate sensing. A multiplicity of σI paralogues in some cellulolytic bacteria have been shown to be responsible for the regulation of the cellulosome, a multienzyme complex that mediates efficient cellulose degradation. Here, we report two structures at 3.0 Å and 3.3 Å of two transcription open complexes formed by two σI factors, SigI1 and SigI6, respectively, from the thermophilic, cellulolytic bacterium, Clostridium thermocellum. These structures reveal a unique, hitherto-unknown recognition mode of bacterial transcriptional promoters, both with respect to domain organization and binding to promoter DNA. The key characteristics that determine the specificities of the σI paralogues were further revealed by comparison of the two structures. Consequently, the σI factors represent a distinct set of the σ70-family σ factors, thus highlighting the diversity of bacterial transcription.
Collapse
Affiliation(s)
- Jie Li
- CAS Key Laboratory of Biofuels, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Engineering Laboratory of Single Cell Oil, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Energy Institute, 266101, Qingdao, Shandong, China
- Qingdao New Energy Shandong Laboratory, 266101, Qingdao, Shandong, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Haonan Zhang
- University of Chinese Academy of Sciences, 100049, Beijing, China
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
| | - Dongyu Li
- University of Chinese Academy of Sciences, 100049, Beijing, China
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China
| | - Ya-Jun Liu
- CAS Key Laboratory of Biofuels, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Engineering Laboratory of Single Cell Oil, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Energy Institute, 266101, Qingdao, Shandong, China
- Qingdao New Energy Shandong Laboratory, 266101, Qingdao, Shandong, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Edward A Bayer
- Department of Biomolecular Sciences, The Weizmann Institute of Science, 7610001, Rehovot, Israel
- Department of Life Sciences and the National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, 8499000, Beer-Sheva, Israel
| | - Qiu Cui
- CAS Key Laboratory of Biofuels, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Engineering Laboratory of Single Cell Oil, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China
- Shandong Energy Institute, 266101, Qingdao, Shandong, China
- Qingdao New Energy Shandong Laboratory, 266101, Qingdao, Shandong, China
- University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Yingang Feng
- CAS Key Laboratory of Biofuels, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China.
- Shandong Provincial Key Laboratory of Synthetic Biology, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China.
- Shandong Engineering Laboratory of Single Cell Oil, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, 266101, Qingdao, Shandong, China.
- Shandong Energy Institute, 266101, Qingdao, Shandong, China.
- Qingdao New Energy Shandong Laboratory, 266101, Qingdao, Shandong, China.
- University of Chinese Academy of Sciences, 100049, Beijing, China.
| | - Ping Zhu
- University of Chinese Academy of Sciences, 100049, Beijing, China.
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China.
| |
Collapse
|
9
|
Rao Y, Wang J, Yang X, Xie X, Zhan Y, Ma X, Cai D, Chen S. A novel toolbox for precise regulation of gene expression and metabolic engineering in Bacillus licheniformis. Metab Eng 2023; 78:159-170. [PMID: 37307865 DOI: 10.1016/j.ymben.2023.06.004] [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: 02/01/2023] [Revised: 05/15/2023] [Accepted: 06/05/2023] [Indexed: 06/14/2023]
Abstract
Despite industrial bio-manufacturing progress using Bacillus licheniformis, the absence of a well-characterized toolbox allowing precise regulation of multiple genes limits its expansion for basic research and application. Here, a novel gene expression toolbox (GET) was developed for precise regulation of gene expression and high-level production of 2-phenylethanol. Firstly, we established a novel promoter core region mosaic combination model to combine, characterize and analyze different core regions. Characterization and orthogonal design of promoter ribbons allowed convenient construction of an adaptable and robust GET, gene gfp expression intensity was 0.64%-16755.77%, with a dynamic range of 2.61 × 104 times, which is the largest regulatory range of GET in Bacillus based on modification of promoter P43. Then we verified the protein and species universality of GET using different proteins expressed in B. licheniformis and Bacillus subtilis. Finally, the GET for 2-phenylethanol metabolic breeding, resulting in a plasmid-free strain producing 6.95 g/L 2-phenylethanol with a yield and productivity of 0.15 g/g glucose and 0.14 g/L/h, respectively, the highest de novo synthesis yield of 2-phenylethanol reported. Taken together, this is the first report elucidating the impact of mosaic combination and tandem of multiple core regions to initiate transcription and improve the output of proteins and metabolites, which provides strong support for gene regulation and diversified product production in Bacillus.
Collapse
Affiliation(s)
- Yi Rao
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, PR China
| | - Jiaqi Wang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, PR China
| | - Xinyuan Yang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, PR China
| | - Xinxin Xie
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, PR China
| | - Yangyang Zhan
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, PR China
| | - Xin Ma
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, PR China
| | - Dongbo Cai
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, PR China.
| | - Shouwen Chen
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, PR China.
| |
Collapse
|
10
|
Sharon JA, Dasrath C, Fujiwara A, Snyder A, Blank M, O'Brien S, Aufdembrink LM, Engelhart AE, Adamala KP. Trumpet is an operating system for simple and robust cell-free biocomputing. Nat Commun 2023; 14:2257. [PMID: 37080970 PMCID: PMC10119096 DOI: 10.1038/s41467-023-37752-x] [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: 11/08/2022] [Accepted: 03/30/2023] [Indexed: 04/22/2023] Open
Abstract
Biological computation is becoming a viable and fast-growing alternative to traditional electronic computing. Here we present a biocomputing technology called Trumpet: Transcriptional RNA Universal Multi-Purpose GatE PlaTform. Trumpet combines the simplicity and robustness of the simplest in vitro biocomputing methods, adding signal amplification and programmability, while avoiding common shortcomings of live cell-based biocomputing solutions. We have demonstrated the use of Trumpet to build all universal Boolean logic gates. We have also built a web-based platform for designing Trumpet gates and created a primitive processor by networking several gates as a proof-of-principle for future development. The Trumpet offers a change of paradigm in biocomputing, providing an efficient and easily programmable biological logic gate operating system.
Collapse
Affiliation(s)
- Judee A Sharon
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Chelsea Dasrath
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Aiden Fujiwara
- Department of Computer Science, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Alessandro Snyder
- Department of Computer Science, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Mace Blank
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Sam O'Brien
- Department of Computer Science, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Lauren M Aufdembrink
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Aaron E Engelhart
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Katarzyna P Adamala
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA.
| |
Collapse
|
11
|
Park JH, Bassalo MC, Lin GM, Chen Y, Doosthosseini H, Schmitz J, Roubos JA, Voigt CA. Design of Four Small-Molecule-Inducible Systems in the Yeast Chromosome, Applied to Optimize Terpene Biosynthesis. ACS Synth Biol 2023; 12:1119-1132. [PMID: 36943773 PMCID: PMC10127285 DOI: 10.1021/acssynbio.2c00607] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Abstract
The optimization of cellular functions often requires the balancing of gene expression, but the physical construction and screening of alternative designs are costly and time-consuming. Here, we construct a strain of Saccharomyces cerevisiae that contains a "sensor array" containing bacterial regulators that respond to four small-molecule inducers (vanillic acid, xylose, aTc, IPTG). Four promoters can be independently controlled with low background and a 40- to 5000-fold dynamic range. These systems can be used to study the impact of changing the level and timing of gene expression without requiring the construction of multiple strains. We apply this approach to the optimization of a four-gene heterologous pathway to the terpene linalool, which is a flavor and precursor to energetic materials. Using this approach, we identify bottlenecks in the metabolic pathway. This work can aid the rapid automated strain development of yeasts for the bio-manufacturing of diverse products, including chemicals, materials, fuels, and food ingredients.
Collapse
Affiliation(s)
- Jong Hyun Park
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, Massachusetts 02139, United States
| | - Marcelo C Bassalo
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, Massachusetts 02139, United States
| | - Geng-Min Lin
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, Massachusetts 02139, United States
| | - Ye Chen
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, Massachusetts 02139, United States
| | - Hamid Doosthosseini
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, Massachusetts 02139, United States
| | - Joep Schmitz
- DSM Science & Innovation, Biodata & Translational Sciences, P.O. Box 1, 2600 MA Delft, The Netherlands
| | - Johannes A Roubos
- DSM Science & Innovation, Biodata & Translational Sciences, P.O. Box 1, 2600 MA Delft, The Netherlands
| | - Christopher A Voigt
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, 500 Technology Square, Cambridge, Massachusetts 02139, United States
| |
Collapse
|
12
|
Qin C, Xiang Y, Liu J, Zhang R, Liu Z, Li T, Sun Z, Ouyang X, Zong Y, Zhang HM, Ouyang Q, Qian L, Lou C. Precise programming of multigene expression stoichiometry in mammalian cells by a modular and programmable transcriptional system. Nat Commun 2023; 14:1500. [PMID: 36932109 PMCID: PMC10023750 DOI: 10.1038/s41467-023-37244-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 03/09/2023] [Indexed: 03/19/2023] Open
Abstract
Context-dependency of mammalian transcriptional elements has hindered the quantitative investigation of multigene expression stoichiometry and its biological functions. Here, we describe a host- and local DNA context-independent transcription system to gradually fine-tune single and multiple gene expression with predictable stoichiometries. The mammalian transcription system is composed of a library of modular and programmable promoters from bacteriophage and its cognate RNA polymerase (RNAP) fused to a capping enzyme. The relative expression of single genes is quantitatively determined by the relative binding affinity of the RNAP to the promoters, while multigene expression stoichiometry is predicted by a simple biochemical model with resource competition. We use these programmable and modular promoters to predictably tune the expression of three components of an influenza A virus-like particle (VLP). Optimized stoichiometry leads to a 2-fold yield of intact VLP complexes. The host-independent orthogonal transcription system provides a platform for dose-dependent control of multiple protein expression which may be applied for advanced vaccine engineering, cell-fate programming and other therapeutic applications.
Collapse
Affiliation(s)
- Chenrui Qin
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, 100871, Beijing, China
- Peking-Tsinghua Joint Center for Life Sciences, Peking University, 100871, Beijing, China
| | - Yanhui Xiang
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China
| | - Jie Liu
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China
| | - Ruilin Zhang
- Yuanpei College, Peking University, 100871, Beijing, China
| | - Ziming Liu
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China
| | - Tingting Li
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China
| | - Zhi Sun
- College of Life Science, University of Chinese Academy of Science, 100149, Beijing, China
| | - Xiaoyi Ouyang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, 100871, Beijing, China
| | | | | | - Qi Ouyang
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, 100871, Beijing, China
| | - Long Qian
- Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, 100871, Beijing, China.
| | - Chunbo Lou
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, 518055, Shenzhen, China.
- College of Life Science, University of Chinese Academy of Science, 100149, Beijing, China.
| |
Collapse
|
13
|
Chen X, Wang T, Guan Y, Ouyang Q, Lou C, Qian L. The Topological Characteristics of Biological Ratio-Sensing Networks. Life (Basel) 2023; 13:life13020351. [PMID: 36836707 PMCID: PMC9965423 DOI: 10.3390/life13020351] [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: 12/28/2022] [Revised: 01/12/2023] [Accepted: 01/21/2023] [Indexed: 01/31/2023] Open
Abstract
Ratio sensing is a fundamental biological function observed in signal transduction and decision making. In the synthetic biology context, ratio sensing presents one of the elementary functions for cellular multi-signal computation. To investigate the mechanism of the ratio-sensing behavior, we explored the topological characteristics of biological ratio-sensing networks. With exhaustive enumeration of three-node enzymatic and transcriptional regulatory networks, we found that robust ratio sensing was highly dependent on network structure rather than network complexity. Specifically, a set of seven minimal core topological structures and four motifs were deduced to be capable of robust ratio sensing. Further investigations on the evolutionary space of robust ratio-sensing networks revealed highly clustered domains surrounding the core motifs which suggested their evolutionary plausibility. Our study revealed the network topological design principles of ratio-sensing behavior and provided a design scheme for constructing regulatory circuits with ratio-sensing behavior in synthetic biology.
Collapse
Affiliation(s)
- Xinmao Chen
- School of Physics, Peking University, Beijing 100871, China
| | - Tianze Wang
- Center for Quantitative Biology, Peking University, Beijing 100871, China
| | - Ying Guan
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Qi Ouyang
- School of Physics, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Peking University, Beijing 100871, China
- Correspondence: (Q.O.); (C.L.); (L.Q.)
| | - Chunbo Lou
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
- Correspondence: (Q.O.); (C.L.); (L.Q.)
| | - Long Qian
- Center for Quantitative Biology, Peking University, Beijing 100871, China
- Correspondence: (Q.O.); (C.L.); (L.Q.)
| |
Collapse
|
14
|
Gilliot PA, Gorochowski TE. Design and Analysis of Massively Parallel Reporter Assays Using FORECAST. Methods Mol Biol 2023; 2553:41-56. [PMID: 36227538 DOI: 10.1007/978-1-0716-2617-7_3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Machine learning is revolutionizing molecular biology and bioengineering by providing powerful insights and predictions. Massively parallel reporter assays (MPRAs) have emerged as a particularly valuable class of high-throughput technique to support such algorithms. MPRAs enable the simultaneous characterization of thousands or even millions of genetic constructs and provide the large amounts of data needed to train models. However, while the scale of this approach is impressive, the design of effective MPRA experiments is challenging due to the many factors that can be varied and the difficulty in predicting how these will impact the quality and quantity of data obtained. Here, we present a computational tool called FORECAST, which can simulate MPRA experiments based on fluorescence-activated cell sorting and subsequent sequencing (commonly referred to as Flow-seq or Sort-seq experiments), as well as carry out rigorous statistical estimation of construct performance from this type of experimental data. FORECAST can be used to develop workflows to aid the design of MPRA experiments and reanalyze existing MPRA data sets.
Collapse
|
15
|
Xu K, Tong Y, Li Y, Tao J, Rao S, Li J, Zhou J, Liu S. Autoinduction Expression Modules for Regulating Gene Expression in Bacillus subtilis. ACS Synth Biol 2022; 11:4220-4225. [PMID: 36468943 DOI: 10.1021/acssynbio.2c00304] [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: 12/12/2022]
Abstract
Although quorum sensing (QS) promoters that can autonomously activate gene expression have been identified and engineered in Bacillus subtilis, researchers focus on quantifying individual promoters while ignoring the interaction between other genetic regulatory elements. Here, we constructed the autoinduction expression modules consisting of promoters responsive to QS ComQXPA, ribosome binding sites (RBSs), and terminators. Using superfolder green fluorescent protein (sfGFP) as a reporter gene, three individual element libraries were generated from 945 promoters, 12,000 RBSs, and 425 terminators by random mutation, de novo design, and database mining strategies, respectively. Then, the efficiency of three libraries in regulating gene expression was further enhanced by engineering the core region of each optimal element. After hybridizing the element libraries, the generated expression modules exhibited a 627-fold range in regulating gene expression without significantly affecting the autoinduction initiation. Here, the hybrid modules with broad expression strength may benefit the application of QS-based autoinduction systems in B. subtilis.
Collapse
Affiliation(s)
- Kuidong Xu
- National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University, Wuxi 214122, China.,Science Center for Future Foods, Jiangnan University, Wuxi 214122, China.,Jiangsu Provisional Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China
| | - Yi Tong
- National Engineering Research Center for Corn Deep Processing, Jilin COFCO Biochemical Co. Ltd, Changchun 130033, China
| | - Yi Li
- National Engineering Research Center for Corn Deep Processing, Jilin COFCO Biochemical Co. Ltd, Changchun 130033, China
| | - Jin Tao
- National Engineering Research Center for Corn Deep Processing, Jilin COFCO Biochemical Co. Ltd, Changchun 130033, China
| | - Shengqi Rao
- College of Food Science and Engineering, Yangzhou University, Yangzhou, Jiangsu 214122, China
| | - Jianghua Li
- Science Center for Future Foods, Jiangnan University, Wuxi 214122, China.,School of Biotechnology, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China
| | - Jingwen Zhou
- National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University, Wuxi 214122, China.,Science Center for Future Foods, Jiangnan University, Wuxi 214122, China.,Jiangsu Provisional Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China
| | - Song Liu
- National Engineering Research Center for Cereal Fermentation and Food Biomanufacturing, Jiangnan University, Wuxi 214122, China.,Science Center for Future Foods, Jiangnan University, Wuxi 214122, China
| |
Collapse
|
16
|
Sun Y, Zhang F, Li L, Chen K, Wang S, Ouyang Q, Luo C. Two-Layered Microfluidic Devices for High-Throughput Dynamic Analysis of Synthetic Gene Circuits in E. coli. ACS Synth Biol 2022; 11:3954-3965. [PMID: 36283074 DOI: 10.1021/acssynbio.2c00307] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Escherichia coli is a common chassis for synthetic gene circuit studies. In addition to the dose-response of synthetic gene circuits, the analysis of dynamic responses is also an important part of the future design of more complicated synthetic systems. Recently, microfluidic-based methods have been widely used for the analysis of gene expression dynamics. Here, we established a two-layered microfluidic platform for the systematic characterization of synthetic gene circuits (eight strains in eight different culture environments could be observed simultaneously with a 5 min time resolution). With this platform, both dose responses and dynamic responses with a high temporal resolution could be easily derived for further analysis. A controlled environment ensures the stability of the bacterial growth rate, excluding changes in gene expression dynamics caused by changes of the growth dilution rate. The precise environmental switch and automatic micrograph shooting ensured that there was nearly no time lag between the inducer addition and the data recording. We studied four four-node incoherent-feedforward-loop (IFFL) networks with different operators using this device. The experimental results showed that as the effect of inhibition increased, two of the IFFL networks generated pulselike dynamic gene expressions in the range of the inducer concentrations, which was different from the dynamics of the two other circuits with only a simple pattern of rising to the platform. Through fitting the dose-response curves and the dynamic response curves, corresponding parameters were derived and introduced to a simple model that could qualitatively explain the generation of pulse dynamics.
Collapse
Affiliation(s)
- Yanhong Sun
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of Physics, Peking University, Beijing100871, China
| | - Fengyu Zhang
- School of Life Sciences and Peking-Tsinghua Center for Life Sciences, Peking University, Beijing100871, China
| | - Lusi Li
- Academy of Advanced Interdisciplinary Studies, Peking University, Beijing100871, China
| | - Kaiyue Chen
- Wenzhou Institute University of Chinese Academy of Sciences, Wenzhou, Zhejiang325001, China
| | - Shujing Wang
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of Physics, Peking University, Beijing100871, China
| | - Qi Ouyang
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of Physics, Peking University, Beijing100871, China.,Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China
| | - Chunxiong Luo
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics School of Physics, Peking University, Beijing100871, China.,Center for Quantitative Biology, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China.,Wenzhou Institute University of Chinese Academy of Sciences, Wenzhou, Zhejiang325001, China
| |
Collapse
|
17
|
Rao Y, Yang J, Wang J, Yang X, Zhang M, Zhan Y, Ma X, Cai D, Wang Z, Chen S. Minimization and optimization of α-amylase terminator for heterologous protein production in Bacillus licheniformis. BIORESOUR BIOPROCESS 2022; 9:108. [PMID: 38647575 PMCID: PMC10992175 DOI: 10.1186/s40643-022-00597-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 09/28/2022] [Indexed: 11/10/2022] Open
Abstract
Terminators serve as the regulatory role in gene transcription termination; however, few researches about terminator optimization have been conducted, which leads to the lack of available and universal terminator for gene expression regulation in Bacillus. To solve this problem and expand synthetic biology toolbox of Bacillus licheniformis, the terminator T1 of endogenous α-amylase gene (amyL) was characterized in this research, with a termination efficiency of 87.81%. Then, we explored and optimized the termination strength of terminator T1 from four aspects: the distance between stop codon and terminator, GC content at the bottom of stem structure, loop size, and U-tract length, and the best terminator T24 was attained by combination optimization strategy, which termination efficiency was increased to 97.97%, better than the commonly used terminator T7 (T7P) from Escherichia coli. Finally, terminator T24 was applied to protein expression, which, respectively, led to 33.00%, 25.93%, and 11.78% increases of green fluorescence intensity, red fluorescence intensity, and keratinase activity, indicating its universality in protein expression. Taken together, this research not only expands a plug-and-play synthetic biology toolbox in B. licheniformis but also provides a reference for the artificial design of versatile intrinsic terminator.
Collapse
Affiliation(s)
- Yi Rao
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China
| | - Jingyao Yang
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China
| | - Jiaqi Wang
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China
| | - Xinyuan Yang
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China
| | - Mengxi Zhang
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China
| | - Yangyang Zhan
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China
| | - Xin Ma
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China
| | - Dongbo Cai
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China
| | - Zhangqian Wang
- Hubei Engineering Research Center for Deep Processing of Green Se-Rich Agricultural Products, School of Modern Industry for Selenium Science and Engineering, National R&D Center for Se-Rich Agricultural Products Processing, Wuhan Polytechnic University, Wuhan, 430023, People's Republic of China.
| | - Shouwen Chen
- State Key Laboratory of Biocatalysis and Enzyme EngineeringEnvironmental Microbial Technology Center of Hubei ProvinceCollege of Life Sciences, Hubei University, 368 Youyi Avenue, Wuchang District, Wuhan, 430062, Hubei, People's Republic of China.
- Fujian Provincial Key Laboratory of Eco-Industrial Green Technology, College of Ecological and Resource Engineering, Wuyi University, Nanping, 354300, Wuyishan, People's Republic of China.
| |
Collapse
|
18
|
Guan Y, Chen X, Shao B, Ji X, Xiang Y, Jiang G, Xu L, Lin Z, Ouyang Q, Lou C. Mitigating Host Burden of Genetic Circuits by Engineering Autonegatively Regulated Parts and Improving Functional Prediction. ACS Synth Biol 2022; 11:2361-2371. [PMID: 35772024 DOI: 10.1021/acssynbio.2c00073] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Mitigating unintended interferences between circuits and host cells is key to realize applications of synthetic regulatory systems both for bacteria and mammalian cells. Here, we demonstrated that growth burden and circuit dysregulation occurred in a concentration-dependent manner for specific transcription factors (CymR*/CymR) in E.coli, and direct negative feedback modules were able to control the concentration of CymR*/CymR, mitigate growth burden, and restore circuit functions. A quantitative design scheme was developed for circuits embedded with autorepression modules. Four key parameters were theoretically identified to determine the performance of autoregulated switches and were experimentally modified by fine-tuning promoter architectures and cooperativity. Using this strategy, we synthesized a number of switches and demonstrated its improvement of product titers and host growth controlling the complex deoxyviolacein biosynthesis pathway. Furthermore, we restored functions of a dysregulated multilayer NOR gate by integrating autorepression modules. Our work provides a blueprint for engineering host-adaptable synthetic systems.
Collapse
Affiliation(s)
- Ying Guan
- Department of Chemical Engineering, Tsinghua University, Beijing 100871, China.,Center for Quantitative Biology, Peking-Tsinghua Joint Center for Life Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Xinmao Chen
- Center for Quantitative Biology, Peking-Tsinghua Joint Center for Life Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Bin Shao
- Center for Quantitative Biology, Peking-Tsinghua Joint Center for Life Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Xiangyu Ji
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Science, University of Chinese Academy of Science, Beijing 100149, China
| | - Yanhui Xiang
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Guoqiang Jiang
- Department of Chemical Engineering, Tsinghua University, Beijing 100871, China
| | - Lina Xu
- National Protein Science Facility, Tsinghua University, Beijing 100871, China
| | - Zhanglin Lin
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Qi Ouyang
- Center for Quantitative Biology, Peking-Tsinghua Joint Center for Life Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Chunbo Lou
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,College of Life Science, University of Chinese Academy of Science, Beijing 100149, China
| |
Collapse
|
19
|
A microfluidic optimal experimental design platform for forward design of cell-free genetic networks. Nat Commun 2022; 13:3626. [PMID: 35750678 PMCID: PMC9232554 DOI: 10.1038/s41467-022-31306-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Accepted: 06/14/2022] [Indexed: 12/20/2022] Open
Abstract
Cell-free protein synthesis has been widely used as a “breadboard” for design of synthetic genetic networks. However, due to a severe lack of modularity, forward engineering of genetic networks remains challenging. Here, we demonstrate how a combination of optimal experimental design and microfluidics allows us to devise dynamic cell-free gene expression experiments providing maximum information content for subsequent non-linear model identification. Importantly, we reveal that applying this methodology to a library of genetic circuits, that share common elements, further increases the information content of the data resulting in higher accuracy of model parameters. To show modularity of model parameters, we design a pulse decoder and bistable switch, and predict their behaviour both qualitatively and quantitatively. Finally, we update the parameter database and indicate that network topology affects parameter estimation accuracy. Utilizing our methodology provides us with more accurate model parameters, a necessity for forward engineering of complex genetic networks. Characterization of cell-free genetic networks is inherently difficult. Here the authors use optimal experimental design and microfluidics to improve characterization, demonstrating modularity and predictability of parts in applied test cases.
Collapse
|
20
|
Novel switchable ECF sigma factor transcription system for improving thaxtomin A production in Streptomyces. Synth Syst Biotechnol 2022; 7:972-981. [PMID: 35756964 PMCID: PMC9194655 DOI: 10.1016/j.synbio.2022.05.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 05/30/2022] [Accepted: 05/31/2022] [Indexed: 11/23/2022] Open
Abstract
The application of the valuable natural product thaxtomin A, a potent bioherbicide from the potato scab pathogenic Streptomyces strains, has been greatly hindered by the low yields from its native producers. Here, we developed an orthogonal transcription system, leveraging extra-cytoplasmic function (ECF) sigma (σ) factor 17 (ECF17) and its cognate promoter Pecf17, to express the thaxtomin gene cluster and improve the production of thaxtomin A. The minimal Pecf17 promoter was determined, and a Pecf17 promoter library with a wide range of strengths was constructed. Furthermore, a cumate inducible system was developed for precise temporal control of the ECF17 transcription system in S. venezuelae ISP5230. Theoretically, the switchable ECF17 transcription system could reduce the unwanted influences from host and alleviate the burdens introduced by overexpression of heterologous genes. The yield of thaxtomin A was significantly improved to 202.1 ± 15.3 μ g/mL using the switchable ECF17 transcription system for heterologous expression of the thaxtomin gene cluster in S. venezuelae ISP5230. Besides, the applicability of this transcription system was also tested in Streptomyces albus J1074, and the titer of thaxtomin A was raised to as high as 239.3 ± 30.6 μg/mL. Therefore, the inducible ECF17 transcription system could serve as a complement of the generally used transcription systems based on strong native constitutive promoters and housekeeping σ factors for the heterologous expression of valuable products in diverse Streptomyces hosts.
Collapse
|
21
|
Chakraborty D, Rengaswamy R, Raman K. Designing Biological Circuits: From Principles to Applications. ACS Synth Biol 2022; 11:1377-1388. [PMID: 35320676 DOI: 10.1021/acssynbio.1c00557] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Genetic circuit design is a well-studied problem in synthetic biology. Ever since the first genetic circuits─the repressilator and the toggle switch─were designed and implemented, many advances have been made in this area of research. The current review systematically organizes a number of key works in this domain by employing the versatile framework of generalized morphological analysis. Literature in the area has been mapped on the basis of (a) the design methodologies used, ranging from brute-force searches to control-theoretic approaches, (b) the modeling techniques employed, (c) various circuit functionalities implemented, (d) key design characteristics, and (e) the strategies used for the robust design of genetic circuits. We conclude our review with an outlook on multiple exciting areas for future research, based on the systematic assessment of key research gaps that have been readily unravelled by our analysis framework.
Collapse
Affiliation(s)
- Debomita Chakraborty
- Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Centre for Integrative Biology and Systems medicinE (IBSE), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Robert Bosch Centre for Data Science and Articial Intelligence (RBCDSAI), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
| | - Raghunathan Rengaswamy
- Centre for Integrative Biology and Systems medicinE (IBSE), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Robert Bosch Centre for Data Science and Articial Intelligence (RBCDSAI), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Department of Chemical Engineering, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
| | - Karthik Raman
- Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Centre for Integrative Biology and Systems medicinE (IBSE), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Robert Bosch Centre for Data Science and Articial Intelligence (RBCDSAI), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
| |
Collapse
|
22
|
Sun Z, Wei W, Zhang M, Shi W, Zong Y, Chen Y, Yang X, Yu B, Tang C, Lou C. Synthetic robust perfect adaptation achieved by negative feedback coupling with linear weak positive feedback. Nucleic Acids Res 2022; 50:2377-2386. [PMID: 35166832 PMCID: PMC8887471 DOI: 10.1093/nar/gkac066] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 01/15/2022] [Accepted: 01/25/2022] [Indexed: 12/21/2022] Open
Abstract
Unlike their natural counterparts, synthetic genetic circuits are usually fragile in the face of environmental perturbations and genetic mutations. Several theoretical robust genetic circuits have been designed, but their performance under real-world conditions has not yet been carefully evaluated. Here, we designed and synthesized a new robust perfect adaptation circuit composed of two-node negative feedback coupling with linear positive feedback on the buffer node. As a key feature, the linear positive feedback was fine-tuned to evaluate its necessity. We found that the desired function was robustly achieved when genetic parameters were varied by systematically perturbing all interacting parts within the topology, and the necessity of the completeness of the topological structures was evaluated by destroying key circuit features. Furthermore, different environmental perturbances were imposed onto the circuit by changing growth rates, carbon metabolic strategies and even chassis cells, and the designed perfect adaptation function was still achieved under all conditions. The successful design of a robust perfect adaptation circuit indicated that the top-down design strategy is capable of predictably guiding bottom-up engineering for robust genetic circuits. This robust adaptation circuit could be integrated as a motif into more complex circuits to robustly implement more sophisticated and critical biological functions.
Collapse
Affiliation(s)
- Zhi Sun
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Weijia Wei
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Mingyue Zhang
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China.,School of Physics, Peking University, Beijing 100871, China
| | - Wenjia Shi
- Department of Applied Physics, School of Sciences, Xi'an University of Technology, Xi'an 710048, China
| | | | - Yihua Chen
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100149, China
| | - Xiaojing Yang
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China
| | - Bo Yu
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China
| | - Chao Tang
- Center for Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing100871, China.,School of Physics, Peking University, Beijing 100871, China
| | - Chunbo Lou
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100149, China
| |
Collapse
|
23
|
Development of Synthetic DNA Circuit and Networks for Molecular Information Processing. NANOMATERIALS 2021; 11:nano11112955. [PMID: 34835719 PMCID: PMC8625377 DOI: 10.3390/nano11112955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 11/23/2022]
Abstract
Deoxyribonucleic acid (DNA), a genetic material, encodes all living information and living characteristics, e.g., in cell, DNA signaling circuits control the transcription activities of specific genes. In recent years, various DNA circuits have been developed to implement a wide range of signaling and for regulating gene network functions. In particular, a synthetic DNA circuit, with a programmable design and easy construction, has become a crucial method through which to simulate and regulate DNA signaling networks. Importantly, the construction of a hierarchical DNA circuit provides a useful tool for regulating gene networks and for processing molecular information. Moreover, via their robust and modular properties, DNA circuits can amplify weak signals and establish programmable cascade systems, which are particularly suitable for the applications of biosensing and detecting. Furthermore, a biological enzyme can also be used to provide diverse circuit regulation elements. Currently, studies regarding the mechanisms and applications of synthetic DNA circuit are important for the establishment of more advanced artificial gene regulation systems and intelligent molecular sensing tools. We therefore summarize recent relevant research progress, contributing to the development of nanotechnology-based synthetic DNA circuits. By summarizing the current highlights and the development of synthetic DNA circuits, this paper provides additional insights for future DNA circuit development and provides a foundation for the construction of more advanced DNA circuits.
Collapse
|
24
|
Anderson DA, Voigt CA. Competitive dCas9 binding as a mechanism for transcriptional control. Mol Syst Biol 2021; 17:e10512. [PMID: 34747560 PMCID: PMC8574044 DOI: 10.15252/msb.202110512] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 10/10/2021] [Accepted: 10/11/2021] [Indexed: 12/24/2022] Open
Abstract
Catalytically dead Cas9 (dCas9) is a programmable transcription factor that can be targeted to promoters through the design of small guide RNAs (sgRNAs), where it can function as an activator or repressor. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one can block, displace, or augment the activity of the other. Here, we implemented this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. When designed to target a promoter, this led to 27-fold repression and complete derepression. This system was also capable of ratiometric input comparison over two orders of magnitude. Additionally, we used this mechanism for promoter sequence-independent control by adopting it for elongation control, achieving 8-fold repression and 4-fold derepression. This work demonstrates a new genetic control mechanism that could be used to build analog circuit or implement cis-regulatory logic on CRISPRi-targeted native genes.
Collapse
Affiliation(s)
- Daniel A Anderson
- Synthetic Biology CenterDepartment of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Christopher A Voigt
- Synthetic Biology CenterDepartment of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| |
Collapse
|
25
|
Chen Z, Sun J, Guan Y, Li M, Lou C, Wu B. Engineered DNase-inactive Cpf1 variants to improve targeting scope for base editing in E. coli. Synth Syst Biotechnol 2021; 6:326-334. [PMID: 34632125 PMCID: PMC8484740 DOI: 10.1016/j.synbio.2021.09.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 08/17/2021] [Accepted: 09/03/2021] [Indexed: 12/26/2022] Open
Abstract
The development of base editing (BE) technology has opened a new avenue for research studies in bacteriology, particularly for bacterial species in which the DNA double-strand breaks (DSBs) introduced by CRISPR/Cas system would lead to cell death. However, a major limitation of BE-mediated gene editing is the restricted editable sites in the target bacterial genome due to highly diverse genomic compositions, such as GC content. Herein, we developed a broad-spectrum DNase-inactive Cpf1 (dCpf1) variant from Francisella novicida (bsdFnCpf1) through directed evolution. The resulting optimized mutant showed a substantially expanded targeting range, including previously non-canonical protospacer-adjacent motifs (PAMs), especially the GC-rich PAMs. Cytidine deaminase APOBEC1 and uracil DNA glycosylase inhibitor (UGI) were fused with bsdFnCpf1 to achieve specific C to T mutations at multiple target sites with canonical or non-canonical PAMs in the E. coli genome without compromising cell growth. We anticipate that bsdFnCpf1 could be applied for multiplex gene regulation and BE in species that have been reported to be suitable for Cpf1.
Collapse
Affiliation(s)
- Zehua Chen
- CAS Key Laboratory of Microbial Physiological & Metabolic Engineering and State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Jinyuan Sun
- CAS Key Laboratory of Microbial Physiological & Metabolic Engineering and State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.,College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100149, China
| | - Ying Guan
- Tsinghua University, Beijing, 100084, China
| | - Ming Li
- CAS Key Laboratory of Microbial Physiological & Metabolic Engineering and State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Chunbo Lou
- CAS Key Laboratory of Microbial Physiological & Metabolic Engineering and State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Bian Wu
- CAS Key Laboratory of Microbial Physiological & Metabolic Engineering and State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China
| |
Collapse
|
26
|
Zhu Y, Li Y, Xu Y, Zhang J, Ma L, Qi Q, Wang Q. Development of bifunctional biosensors for sensing and dynamic control of glycolysis flux in metabolic engineering. Metab Eng 2021; 68:142-151. [PMID: 34610458 DOI: 10.1016/j.ymben.2021.09.011] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 09/30/2021] [Accepted: 09/30/2021] [Indexed: 11/30/2022]
Abstract
Glycolysis is the primary metabolic pathway in all living organisms. Maintaining the balance of glycolysis flux and biosynthetic pathways is the crucial matter involved in the microbial cell factory. Few regulation systems can address the issue of metabolic flux imbalance in glycolysis. Here, we designed and constructed a bifunctional glycolysis flux biosensor that can dynamically regulate glycolysis flux for overproduction of desired biochemicals. A series of positive-and negative-response biosensors were created and modified for varied thresholds and dynamic ranges. These engineered glycolysis flux biosensors were verified to be able to characterize in vivo fructose-1,6-diphosphate concentration. Subsequently, the biosensors were applied for fine-tuning glycolysis flux to effectively balance the biosynthesis of two chemicals: mevalonate and N-acetylglucosamine. A glycolysis flux-dynamically controlled Escherichia coli strain achieved a 111.3 g/L mevalonate titer in a 1L fermenter.
Collapse
Affiliation(s)
- Yuan Zhu
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, PR China
| | - Ying Li
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, PR China
| | - Ya Xu
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, PR China
| | - Jian Zhang
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, PR China
| | - Linlin Ma
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, PR China
| | - Qingsheng Qi
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, PR China; CAS Key Lab of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, 266101, PR China.
| | - Qian Wang
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, 266237, PR China.
| |
Collapse
|
27
|
Rao Y, Li P, Xie X, Li J, Liao Y, Ma X, Cai D, Chen S. Construction and Characterization of a Gradient Strength Promoter Library for Fine-Tuned Gene Expression in Bacillus licheniformis. ACS Synth Biol 2021; 10:2331-2339. [PMID: 34449215 DOI: 10.1021/acssynbio.1c00242] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Bacillus licheniformis DW2 is an important industrial strain for bacitracin production, and it is also used for biochemical production, however, the lack of effective toolkit for precise regulation of gene expression hindered its application seriously. Here, a gradient strength promoter library was constructed based on bacitracin synthetase gene cluster promoter PbacA. First, different PbacA promoter variants were constructed via coupling PbacA with various 5'-UTRs, and expression ranges of 32.6-741.8% were attained among these promoters. Then, three promoters, PUbay (strong), PbacA (middle), and PUndh (weakest), were applied for red fluorescent protein (RFP) and keratinase expression assays, and these promoters were proven to have good universality for different proteins. Second, the promoter of bacitracin synthetase gene cluster was replaced by these three promoters, and bacitraicn titer was enhanced by 14.62% when PUbay was applied, which was decreased by 98.05% under the mediation of PUndh compared with that of the original strain DW2. Third, promoters PUbay, PUyvgO, and PUndh were selected to regulate the expression levels of critical genes that are responsible for pucheriminic acid synthesis, and pucheriminic acid yield was increased by 194.1% via manipulating synthetic and competitive pathways. Finally, promoters PUbay, PbacA, and PUndh were applied for green fluorescent protein (GFP) and RFP expression in Escherichia coli, and consistent effects were attained based on our results. Taken together, a gradient strength promoter library was constructed in this research, which provided an effective toolkit for fine-tuning gene expression and reprogramming metabolite metabolic flux in B. licheniformis.
Collapse
Affiliation(s)
- Yi Rao
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, People's Republic of China
| | - Peifen Li
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, People's Republic of China
| | - Xinxin Xie
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, People's Republic of China
| | - Jiemin Li
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, People's Republic of China
| | - Yongqing Liao
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, People's Republic of China
| | - Xin Ma
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, People's Republic of China
| | - Dongbo Cai
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, People's Republic of China
| | - Shouwen Chen
- State Key Laboratory of Biocatalysis and Enzyme Engineering, Environmental Microbial Technology Center of Hubei Province, College of Life Sciences, Hubei University, Wuhan, 430062, People's Republic of China
- Fujian Provincial Key Laboratory of Eco-Industrial Green Technology, College of Ecological and Resource Engineering, Wuyi University, Wuyishan 354300, People's Republic of China
| |
Collapse
|
28
|
Round JW, Robeck LD, Eltis LD. An Integrative Toolbox for Synthetic Biology in Rhodococcus. ACS Synth Biol 2021; 10:2383-2395. [PMID: 34428025 DOI: 10.1021/acssynbio.1c00292] [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] [Indexed: 11/30/2022]
Abstract
The development of microbial cell factories requires robust synthetic biology tools to reduce design uncertainty and accelerate the design-build-test-learn process. Herein, we developed a suite of integrative genetic tools to facilitate the engineering of Rhodococcus, a genus of bacteria with considerable biocatalytic potential. We first created pRIME, a modular, copy-controlled integrative-vector, to provide a robust platform for strain engineering and characterizing genetic parts. This vector was then employed to benchmark a series of strong promoters. We found PM6 to be the strongest constitutive rhodococcal promoter, 2.5- to 3-fold stronger than the next in our study, while overall promoter activities ranged 23-fold between the weakest and strongest promoters during exponential growth. Next, we used an optimized variant of PM6 to develop hybrid-promoters and integrative vectors to allow for tetracycline-inducible gene expression in Rhodococcus. The best of the resulting hybrid-promoters maintained a maximal activity of ∼50% of PM6 and displayed an induction factor of ∼40-fold. Finally, we developed and implemented a uLoop-derived Golden Gate assembly strategy for high-throughput DNA assembly in Rhodococcus. To demonstrate the utility of our approaches, pRIME was used to engineer Rhodococcus jostii RHA1 to grow on vanillin at concentrations 10-fold higher than what the wild-type strain tolerated. Overall, this study provides a suite of tools that will accelerate the engineering of Rhodococcus for various biocatalytic applications, including the sustainable production of chemicals from lignin-derived aromatics.
Collapse
Affiliation(s)
- James W. Round
- Department of Microbiology and Immunology, Life Sciences Institute, The University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Logan D. Robeck
- Department of Microbiology and Immunology, Life Sciences Institute, The University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| | - Lindsay D. Eltis
- Department of Microbiology and Immunology, Life Sciences Institute, The University of British Columbia, Vancouver, British Columbia V6T 1Z3, Canada
| |
Collapse
|
29
|
Yang M, Yang F, Chen W, Liu S, Qiu L, Chen J. Bacteria-mediated cancer therapies: opportunities and challenges. Biomater Sci 2021; 9:5732-5744. [PMID: 34313267 DOI: 10.1039/d1bm00634g] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
In recent years, cancer therapy strategies utilizing live tumor-targeting bacteria have presented unique advantages. Engineered bacteria have the particular ability to distinguish tumors from normal tissues with less toxicity. Live bacteria are naturally capable of homing to tumors, resulting in high levels of local colonization because of insufficient oxygen and low pH in the tumor microenvironment. Bacteria initiate their antitumor effects by directly killing the tumor or by activating innate and adaptive antitumor immune responses. The bacterial vectors can be reprogrammed following advanced DNA synthesis, sophisticated genetic bioengineering, and biosensors to engineer microorganisms with complex functions, and then produce and deliver anticancer agents based on clinical needs. However, because of the lack of knowledge on the mechanisms and side effects of microbial cancer therapy, developing such smart microorganisms to treat or prevent cancer remains a significant challenge. In this review, we summarized the potential, status, opportunities and challenges of this growing field. We illustrated the mechanism of tumor regression induced by engineered bacteria and discussed the recent advances in the application of bacteria-mediated cancer therapy to improve efficacy, safety and drug delivery. Finally, we shared our insights into the future directions of tumor-targeting bacteria in cancer therapy.
Collapse
Affiliation(s)
- Meiyang Yang
- School of Pharmaceutical Sciences, Jiangnan University, Wuxi 214122, PR China.
| | | | | | | | | | | |
Collapse
|
30
|
Kuang C, Zeng W, Qian M, Liu X. Liquid-Phase Exfoliated Few-Layer Iodine Nanosheets for High-Rate Lithium-Iodine Batteries. Chempluschem 2021; 86:865-869. [PMID: 34114370 DOI: 10.1002/cplu.202100166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 05/23/2021] [Indexed: 12/22/2022]
Abstract
Rechargeable lithium-iodine (Li-iodine) batteries attract significant attention owning to their high energy density, wide abundance and low cost of iodine resources. However, iodine suffers from low electrical conductivity and high solubility in aprotic electrolyte, leading to fast capacity degradation, low columbic efficiency, as well as poor rate capability. Herein, we propose a simple method for the large-scale production of two-dimensional (2D) few-layer iodine nanosheets (FLINs) via liquid-phase exfoliation of iodine in deionized water. 2D FLINs could effectively improve rate capability by providing sufficient active sites and shortening the Li ion diffusion path. Meanwhile, graphene oxide (GO)@carbon nanotubes (CNT) hosts are designed to suppress the dissolution of iodine and enhance the electrical conductivity. GO@CNT@FLINs film exhibits excellent rate capability (220 mAh g-1 at 0.2 A g-1 and 96 mAh g-1 at 8 A g-1 ) and outstanding cycle stability (93.2 mAh g-1 at 2 A g-1 after 1000 cycles) for lithium storage due to the synergistic effects of GO@CNT hosts and 2D structure of FLINs. The controllable synthesis of FLINs provides a bright prospect for achieving high rate capability of Li-iodine batteries and is of utmost importance to potential large-scale applications.
Collapse
Affiliation(s)
- Chengwei Kuang
- College of Materials Science and Engineering, Chongqing University, Chongqing, 400030, P. R. China
| | - Wen Zeng
- College of Materials Science and Engineering, Chongqing University, Chongqing, 400030, P. R. China
| | - Mengmeng Qian
- Key Laboratory of Environmental Science and Engineering, School of Material Science & Engineering, Beijing Institute of Technology, Beijing, 100081, P. R. China
| | - Xiaoyu Liu
- College of Applied Science and Technology, Beijing Union University, Beijing, 100012, P. R. China
| |
Collapse
|
31
|
Harnessing the central dogma for stringent multi-level control of gene expression. Nat Commun 2021; 12:1738. [PMID: 33741937 PMCID: PMC7979795 DOI: 10.1038/s41467-021-21995-7] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Accepted: 02/18/2021] [Indexed: 11/17/2022] Open
Abstract
Strictly controlled inducible gene expression is crucial when engineering biological systems where even tiny amounts of a protein have a large impact on function or host cell viability. In these cases, leaky protein production must be avoided, but without affecting the achievable range of expression. Here, we demonstrate how the central dogma offers a simple solution to this challenge. By simultaneously regulating transcription and translation, we show how basal expression of an inducible system can be reduced, with little impact on the maximum expression rate. Using this approach, we create several stringent expression systems displaying >1000-fold change in their output after induction and show how multi-level regulation can suppress transcriptional noise and create digital-like switches between ‘on’ and ‘off’ states. These tools will aid those working with toxic genes or requiring precise regulation and propagation of cellular signals, plus illustrate the value of more diverse regulatory designs for synthetic biology. Inducible gene expression systems should minimise leaky output and offer a large achievable range of expression. Here, the authors regulate transcription and translation together to suppress noise and create digital-like responses, while maintaining a large expression range in vivo and in vitro.
Collapse
|
32
|
Young R, Haines M, Storch M, Freemont PS. Combinatorial metabolic pathway assembly approaches and toolkits for modular assembly. Metab Eng 2020; 63:81-101. [PMID: 33301873 DOI: 10.1016/j.ymben.2020.12.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 11/16/2020] [Accepted: 12/03/2020] [Indexed: 12/18/2022]
Abstract
Synthetic Biology is a rapidly growing interdisciplinary field that is primarily built upon foundational advances in molecular biology combined with engineering design principles such as modularity and interoperability. The field considers living systems as programmable at the genetic level and has been defined by the development of new platform technologies and methodological advances. A key concept driving the field is the Design-Build-Test-Learn cycle which provides a systematic framework for building new biological systems. One major application area for synthetic biology is biosynthetic pathway engineering that requires the modular assembly of different genetic regulatory elements and biosynthetic enzymes. In this review we provide an overview of modular DNA assembly and describe and compare the plethora of in vitro and in vivo assembly methods for combinatorial pathway engineering. Considerations for part design and methods for enzyme balancing are also presented, and we briefly discuss alternatives to intracellular pathway assembly including microbial consortia and cell-free systems for biosynthesis. Finally, we describe computational tools and automation for pathway design and assembly and argue that a deeper understanding of the many different variables of genetic design, pathway regulation and cellular metabolism will allow more predictive pathway design and engineering.
Collapse
Affiliation(s)
- Rosanna Young
- Department of Infectious Disease, Sir Alexander Fleming Building, South Kensington Campus, Imperial College London, SW7 2AZ, UK
| | - Matthew Haines
- Department of Infectious Disease, Sir Alexander Fleming Building, South Kensington Campus, Imperial College London, SW7 2AZ, UK
| | - Marko Storch
- Department of Infectious Disease, Sir Alexander Fleming Building, South Kensington Campus, Imperial College London, SW7 2AZ, UK; London Biofoundry, Imperial College Translation & Innovation Hub, London, W12 0BZ, UK
| | - Paul S Freemont
- Department of Infectious Disease, Sir Alexander Fleming Building, South Kensington Campus, Imperial College London, SW7 2AZ, UK; London Biofoundry, Imperial College Translation & Innovation Hub, London, W12 0BZ, UK; UK DRI Care Research and Technology Centre, Imperial College London, Hammersmith Campus, Du Cane Road, London, W12 0NN, UK.
| |
Collapse
|
33
|
Pyruvate-responsive genetic circuits for dynamic control of central metabolism. Nat Chem Biol 2020; 16:1261-1268. [DOI: 10.1038/s41589-020-0637-3] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2019] [Accepted: 07/30/2020] [Indexed: 02/05/2023]
|
34
|
Biosynthesis of functional polyhydroxyalkanoates by engineered Halomonas bluephagenesis. Metab Eng 2020; 59:119-130. [DOI: 10.1016/j.ymben.2020.02.005] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Revised: 02/07/2020] [Accepted: 02/25/2020] [Indexed: 11/23/2022]
|
35
|
Zhang R, Li J, Melendez-Alvarez J, Chen X, Sochor P, Goetz H, Zhang Q, Ding T, Wang X, Tian XJ. Topology-dependent interference of synthetic gene circuit function by growth feedback. Nat Chem Biol 2020; 16:695-701. [PMID: 32251409 PMCID: PMC7246135 DOI: 10.1038/s41589-020-0509-x] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 02/28/2020] [Indexed: 11/21/2022]
Abstract
Growth-mediated feedback between synthetic gene circuits and host organisms leads to diverse emerged behaviors, including growth bistability and enhanced ultrasensitivity. However, the range of possible impacts of growth feedback on gene circuits remains underexplored. Here, we mathematically and experimentally demonstrated that growth feedback affects the functions of memory circuits in a network topology-dependent way. Specifically, the memory of the self-activation switch is quickly lost due to the growth-mediated dilution of the circuit products. Decoupling of growth feedback reveals its memory, manifested by its hysteresis property across a broad range of inducer concentration. On the contrary, the toggle switch is more refractory to growth-mediated dilution and can retrieve its memory after the fast-growth phase. The underlying principle lies in the different dependence of active and repressive regulations in these circuits on the growth-mediated dilution. Our results unveil the topology-dependent mechanism on how growth-mediated feedback influences the behaviors of gene circuits.
Collapse
Affiliation(s)
- Rong Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Jiao Li
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.,Department of Food Science and Nutrition, Zhejiang University, Hangzhou, Zhejiang, China
| | - Juan Melendez-Alvarez
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Xingwen Chen
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Patrick Sochor
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Hanah Goetz
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Qi Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA
| | - Tian Ding
- Department of Food Science and Nutrition, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiao Wang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ, USA.
| |
Collapse
|
36
|
Shin J, Zhang S, Der BS, Nielsen AAK, Voigt CA. Programming Escherichia coli to function as a digital display. Mol Syst Biol 2020; 16:e9401. [PMID: 32141239 PMCID: PMC7058928 DOI: 10.15252/msb.20199401] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 02/04/2020] [Accepted: 02/07/2020] [Indexed: 01/18/2023] Open
Abstract
Synthetic genetic circuits offer the potential to wield computational control over biology, but their complexity is limited by the accuracy of mathematical models. Here, we present advances that enable the complete encoding of an electronic chip in the DNA carried by Escherichia coli (E. coli). The chip is a binary-coded digit (BCD) to 7-segment decoder, associated with clocks and calculators, to turn on segments to visualize 0-9. Design automation is used to build seven strains, each of which contains a circuit with up to 12 repressors and two activators (totaling 63 regulators and 76,000 bp DNA). The inputs to each circuit represent the digit to be displayed (encoded in binary by four molecules), and output is the segment state, reported as fluorescence. Implementation requires an advanced gate model that captures dynamics, promoter interference, and a measure of total power usage (RNAP flux). This project is an exemplar of design automation pushing engineering beyond that achievable "by hand", essential for realizing the potential of biology.
Collapse
Affiliation(s)
- Jonghyeon Shin
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Shuyi Zhang
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Bryan S Der
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Alec AK Nielsen
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Christopher A Voigt
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| |
Collapse
|
37
|
Fang C, Li L, Shen L, Shi J, Wang S, Feng Y, Zhang Y. Structures and mechanism of transcription initiation by bacterial ECF factors. Nucleic Acids Res 2020; 47:7094-7104. [PMID: 31131408 PMCID: PMC6648896 DOI: 10.1093/nar/gkz470] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2019] [Revised: 05/09/2019] [Accepted: 05/17/2019] [Indexed: 01/25/2023] Open
Abstract
Bacterial RNA polymerase (RNAP) forms distinct holoenzymes with extra-cytoplasmic function (ECF) σ factors to initiate specific gene expression programs. In this study, we report a cryo-EM structure at 4.0 Å of Escherichia coli transcription initiation complex comprising σE-the most-studied bacterial ECF σ factor (Ec σE-RPo), and a crystal structure at 3.1 Å of Mycobacterium tuberculosis transcription initiation complex with a chimeric σH/E (Mtb σH/E-RPo). The structure of Ec σE-RPo reveals key interactions essential for assembly of E. coli σE-RNAP holoenzyme and for promoter recognition and unwinding by E. coli σE. Moreover, both structures show that the non-conserved linkers (σ2/σ4 linker) of the two ECF σ factors are inserted into the active-center cleft and exit through the RNA-exit channel. We performed secondary-structure prediction of 27,670 ECF σ factors and find that their non-conserved linkers probably reach into and exit from RNAP active-center cleft in a similar manner. Further biochemical results suggest that such σ2/σ4 linker plays an important role in RPo formation, abortive production and promoter escape during ECF σ factors-mediated transcription initiation.
Collapse
Affiliation(s)
- Chengli Fang
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lingting Li
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liqiang Shen
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Jing Shi
- Department of Biochemistry and Molecular Biology, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Sheng Wang
- Computational Bioscience Research Center (CBRC), King Abdullah University of Science and Technology (KAUST) Thuwal, 23955, Saudi Arabia
| | - Yu Feng
- Department of Biochemistry and Molecular Biology, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Yu Zhang
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| |
Collapse
|
38
|
Wei Z, Chen C, Liu YJ, Dong S, Li J, Qi K, Liu S, Ding X, Ortiz de Ora L, Muñoz-Gutiérrez I, Li Y, Yao H, Lamed R, Bayer EA, Cui Q, Feng Y. Alternative σI/anti-σI factors represent a unique form of bacterial σ/anti-σ complex. Nucleic Acids Res 2019; 47:5988-5997. [PMID: 31106374 PMCID: PMC6582324 DOI: 10.1093/nar/gkz355] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 04/21/2019] [Accepted: 04/26/2019] [Indexed: 12/18/2022] Open
Abstract
The σ70 family alternative σI factors and their cognate anti-σI factors are widespread in Clostridia and Bacilli and play a role in heat stress response, virulence, and polysaccharide sensing. Multiple σI/anti-σI factors exist in some lignocellulolytic clostridial species, specifically for regulation of components of a multienzyme complex, termed the cellulosome. The σI and anti-σI factors are unique, because the C-terminal domain of σI (SigIC) and the N-terminal inhibitory domain of anti-σI (RsgIN) lack homology to known proteins. Here, we report structure and interaction studies of a pair of σI and anti-σI factors, SigI1 and RsgI1, from the cellulosome-producing bacterium, Clostridium thermocellum. In contrast to other known anti-σ factors that have N-terminal helical structures, RsgIN has a β-barrel structure. Unlike other anti-σ factors that bind both σ2 and σ4 domains of the σ factors, RsgIN binds SigIC specifically. Structural analysis showed that SigIC contains a positively charged surface region that recognizes the promoter -35 region, and the synergistic interactions among multiple interfacial residues result in the specificity displayed by different σI/anti-σI pairs. We suggest that the σI/anti-σI factors represent a distinctive mode of σ/anti-σ complex formation, which provides the structural basis for understanding the molecular mechanism of the intricate σI/anti-σI system.
Collapse
Affiliation(s)
- Zhen Wei
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Chao Chen
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
| | - Ya-Jun Liu
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
| | - Sheng Dong
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
| | - Jie Li
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Kuan Qi
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shiyue Liu
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoke Ding
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
| | - Lizett Ortiz de Ora
- Department of Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel
| | - Iván Muñoz-Gutiérrez
- Department of Biomolecular Sciences, The Weizmann Institute of Science, Rehovot, Israel
| | - Yifei Li
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
| | - Hongwei Yao
- High-Field Nuclear Magnetic Resonance Center, Xiamen University, 422 South Siming Road, Xiamen 361005, China
| | - Raphael Lamed
- Department of Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel
| | - Edward A Bayer
- Department of Biomolecular Sciences, The Weizmann Institute of Science, Rehovot, Israel
| | - Qiu Cui
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
| | - Yingang Feng
- CAS Key Laboratory of Biofuels, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Shandong Provincial Key Laboratory of Energy Genetics, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- Qingdao Engineering Laboratory of Single Cell Oil, Qingdao Institute of BioEnergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao 266101, China
- To whom correspondence should be addressed. Tel: +86 532 80662706; Fax: +86 532 80662707;
| |
Collapse
|
39
|
Kent R, Dixon N. Contemporary Tools for Regulating Gene Expression in Bacteria. Trends Biotechnol 2019; 38:316-333. [PMID: 31679824 DOI: 10.1016/j.tibtech.2019.09.007] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 09/16/2019] [Accepted: 09/17/2019] [Indexed: 12/14/2022]
Abstract
Insights from novel mechanistic paradigms in gene expression control have led to the development of new gene expression systems for bioproduction, control, and sensing applications. Coupled with a greater understanding of synthetic burden and modern creative biodesign approaches, contemporary bacterial gene expression tools and systems are emerging that permit fine-tuning of expression, enabling greater predictability and maximisation of specific productivity, while minimising deleterious effects upon cell viability. These advances have been achieved by using a plethora of regulatory tools, operating at all levels of the so-called 'central dogma' of molecular biology. In this review, we discuss these gene regulation tools in the context of their design, prototyping, integration into expression systems, and biotechnological application.
Collapse
Affiliation(s)
- Ross Kent
- Manchester Institute of Biotechnology and School of Chemistry, University of Manchester, Manchester, UK
| | - Neil Dixon
- Manchester Institute of Biotechnology and School of Chemistry, University of Manchester, Manchester, UK.
| |
Collapse
|
40
|
Pinto D, Vecchione S, Wu H, Mauri M, Mascher T, Fritz G. Engineering orthogonal synthetic timer circuits based on extracytoplasmic function σ factors. Nucleic Acids Res 2019; 46:7450-7464. [PMID: 29986061 PMCID: PMC6101570 DOI: 10.1093/nar/gky614] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Accepted: 06/26/2018] [Indexed: 01/02/2023] Open
Abstract
The rational design of synthetic regulatory circuits critically hinges on the availability of orthogonal and well-characterized building blocks. Here, we focus on extracytoplasmic function (ECF) σ factors, which are the largest group of alternative σ factors and hold extensive potential as synthetic orthogonal regulators. By assembling multiple ECF σ factors into regulatory cascades of varying length, we benchmark the scalability of the approach, showing that these ‘autonomous timer circuits’ feature a tuneable time delay between inducer addition and target gene activation. The implementation of similar timers in Escherichia coli and Bacillus subtilis shows strikingly convergent circuit behavior, which can be rationalized by a computational model. These findings not only reveal ECF σ factors as powerful building blocks for a rational, multi-layered circuit design, but also suggest that ECF σ factors are universally applicable as orthogonal regulators in a variety of bacterial species.
Collapse
Affiliation(s)
- Daniela Pinto
- Institute of Microbiology, Technische Universität (TU) Dresden, 01062 Dresden, Germany
| | - Stefano Vecchione
- LOEWE-Center for Synthetic Microbiology (SYNMIKRO), Philipps-Universität Marburg, 35032 Marburg, Germany
| | - Hao Wu
- LOEWE-Center for Synthetic Microbiology (SYNMIKRO), Philipps-Universität Marburg, 35032 Marburg, Germany
| | - Marco Mauri
- LOEWE-Center for Synthetic Microbiology (SYNMIKRO), Philipps-Universität Marburg, 35032 Marburg, Germany
| | - Thorsten Mascher
- Institute of Microbiology, Technische Universität (TU) Dresden, 01062 Dresden, Germany
| | - Georg Fritz
- LOEWE-Center for Synthetic Microbiology (SYNMIKRO), Philipps-Universität Marburg, 35032 Marburg, Germany
| |
Collapse
|
41
|
Gao C, Xu P, Ye C, Chen X, Liu L. Genetic Circuit-Assisted Smart Microbial Engineering. Trends Microbiol 2019; 27:1011-1024. [PMID: 31421969 DOI: 10.1016/j.tim.2019.07.005] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 06/27/2019] [Accepted: 07/19/2019] [Indexed: 12/22/2022]
Abstract
Rapid advances in DNA synthesis, genetic manipulation, and biosensors have greatly improved the ability to engineer microorganisms with complex functions. By accurately integrating quality biosensors and complex genetic circuits, recently emerged smart microorganisms have enabled exciting opportunities for dissecting complex signaling networks and making responses without artificial intervention. However, because of the lack of design principles, developing such smart microorganisms remains challenging. In this review, we propose the concept of smart microbial engineering (SME) and describe the general features of basic SME, including the circuit architecture, components, and design process. We also summarize the latest SME achievements, remaining challenges, and potential solutions in this growing field.
Collapse
Affiliation(s)
- Cong Gao
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Peng Xu
- Chemical, Biochemical, and Environmental Engineering, University of Maryland Baltimore County, Baltimore, MD 21250, USA
| | - Chao Ye
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Xiulai Chen
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China
| | - Liming Liu
- State Key Laboratory of Food Science and Technology, Jiangnan University, Wuxi 214122, China; Key Laboratory of Industrial Biotechnology, Ministry of Education, Jiangnan University, Wuxi 214122, China; National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University, Wuxi 214122, China.
| |
Collapse
|
42
|
Pan L, Hu Y, Ding T, Xie C, Wang Z, Chen Z, Yang J, Zhang C. Aptamer-based regulation of transcription circuits. Chem Commun (Camb) 2019; 55:7378-7381. [PMID: 31173001 DOI: 10.1039/c9cc03141c] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
We propose synthetic DNA/RNA transcription circuits based on specific aptamer recognition. By mimicking transcription factor regulation, combined with specific enzyme/DNA aptamer binding, multiple biomolecules including DNA, RNA, polymerase, restriction enzymes and methylase were used as regulators. In addition, multi-level cascading networks and methylation-switch circuits were also established. This regulation strategy has the potential to expand the toolkit of in vitro synthetic biology.
Collapse
Affiliation(s)
- Linqiang Pan
- Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China, School of Automation, Huazhong University of Science and Technology, Wuhan 430074, P. R. China.
| | | | | | | | | | | | | | | |
Collapse
|
43
|
Niu G, Li W. Next-Generation Drug Discovery to Combat Antimicrobial Resistance. Trends Biochem Sci 2019; 44:961-972. [PMID: 31256981 DOI: 10.1016/j.tibs.2019.05.005] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 05/30/2019] [Accepted: 05/31/2019] [Indexed: 12/16/2022]
Abstract
The widespread emergence of antibiotic-resistant pathogens poses a severe threat to public health. This problem becomes even worse with a coincident decline in the supply of new antibiotics. Conventional bioactivity-guided natural product discovery has failed to meet the urgent need for new antibiotics, largely due to limited resources and high rediscovery rates. Recent advances in cultivation techniques, analytical technologies, and genomics-based approaches have greatly expanded our access to previously underexploited microbial sources. These strategies will enable us to access new reservoirs of microorganisms and unleash their chemical potentials, thus opening new opportunities for the discovery of next-generation drugs to address the growing concerns of antimicrobial resistance.
Collapse
Affiliation(s)
- Guoqing Niu
- Biotechnology Research Center, Southwest University, Chongqing 400715, China; Chongqing Key Laboratory of Plant Resource Conservation and Germplasm Innovation, Southwest University, Chongqing 400715, China; State Cultivation Base of Crop Stress Biology for Southern Mountainous Land, Academy of Agricultural Sciences, Southwest University, Chongqing 400715, China.
| | - Wenli Li
- Key Laboratory of Marine Drugs, Ministry of Education of China, School of Medicine and Pharmacy, Ocean University of China, Qingdao 266003, China; Laboratory for Marine Drugs and Bioproducts, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China.
| |
Collapse
|
44
|
Noh M, Yoo SM, Yang D, Lee SY. Broad-Spectrum Gene Repression Using Scaffold Engineering of Synthetic sRNAs. ACS Synth Biol 2019; 8:1452-1461. [PMID: 31132322 DOI: 10.1021/acssynbio.9b00165] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Gene expression regulation in broad-spectrum range is critical for constructing cell factories and genetic circuits to balance and control system-wide fluxes. Synthetic small regulatory RNAs (sRNAs) effectively regulate gene expression at the translational level by modulating an mRNA-binding chance and sRNA abundance; however, it can control target gene expression only within the limit of the intrinsic repression ability of sRNAs. Here, we systematically mutated a SgrS scaffold as a model sRNA by dividing the Hfq-binding module of the sRNA into the three regions: the A/U-rich sequence, the stem, and the hairpin loop, and examined how efficiently the mutants suppressed DsRed2 expression. By doing this, we found that a scaffold with an altered A/U-rich sequence (CUUU) and stem length and that with altered A/U-rich sequence (GCAC) showed a 3-fold stronger and a 3-fold weaker repression than the original scaffold, respectively. For practical application of altered scaffolds, proof-of-concept experiments were performed by constructing a library of 67 synthetic sRNAs with the strongest scaffold, each one targeting a different rationally selected gene, and using this library to enhance cadaverine production in Escherichia coli, yielding in 27% increase (1.67 g/L in flask cultivation, 13.7 g/L in fed-batch cultivation). Synthetic sRNAs with engineered sRNA scaffolds could be useful in modulating gene expression for strain improvement.
Collapse
Affiliation(s)
- Minho Noh
- Department of Chemical and Biomolecular Engineering (BK21 Plus Program), KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Seung Min Yoo
- School of Integrative Engineering, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea
- BioProcess Engineering Research Center, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Dongsoo Yang
- Department of Chemical and Biomolecular Engineering (BK21 Plus Program), KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
- Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Sang Yup Lee
- Department of Chemical and Biomolecular Engineering (BK21 Plus Program), KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
- BioProcess Engineering Research Center, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
- Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory, KAIST, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| |
Collapse
|
45
|
Gilman J, Singleton C, Tennant RK, James P, Howard TP, Lux T, Parker DA, Love J. Rapid, Heuristic Discovery and Design of Promoter Collections in Non-Model Microbes for Industrial Applications. ACS Synth Biol 2019; 8:1175-1186. [PMID: 30995831 DOI: 10.1021/acssynbio.9b00061] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Well-characterized promoter collections for synthetic biology applications are not always available in industrially relevant hosts. We developed a broadly applicable method for promoter identification in atypical microbial hosts that requires no a priori understanding of cis-regulatory element structure. This novel approach combines bioinformatic filtering with rapid empirical characterization to expand the promoter toolkit and uses machine learning to improve the understanding of the relationship between DNA sequence and function. Here, we apply the method in Geobacillus thermoglucosidasius, a thermophilic organism with high potential as a synthetic biology chassis for industrial applications. Bioinformatic screening of G. kaustophilus, G. stearothermophilus, G. thermodenitrificans, and G. thermoglucosidasius resulted in the identification of 636 100 bp putative promoters, encompassing the genome-wide design space and lacking known transcription factor binding sites. Eighty of these sequences were characterized in vivo, and activities covered a 2-log range of predictable expression levels. Seven sequences were shown to function consistently regardless of the downstream coding sequence. Partition modeling identified sequence positions upstream of the canonical -35 and -10 consensus motifs that were predicted to strongly influence regulatory activity in Geobacillus, and artificial neural network and partial least squares regression models were derived to assess if there were a simple, forward, quantitative method for in silico prediction of promoter function. However, the models were insufficiently general to predict pre hoc promoter activity in vivo, most probably as a result of the relatively small size of the training data set compared to the size of the modeled design space.
Collapse
Affiliation(s)
- James Gilman
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| | - Chloe Singleton
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| | - Richard K. Tennant
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| | - Paul James
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| | - Thomas P. Howard
- School of Natural and Environmental Sciences, Newcastle University, Devonshire Building, Newcastle-upon-Tyne NE1 7RU, U.K
| | - Thomas Lux
- Plant Genome and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Munich 85764, Germany
| | - David A. Parker
- Biodomain, Shell Technology Center Houston, 3333 Highway 6 South, Houston, Texas 77082-3101, United States
| | - John Love
- The BioEconomy Centre, Biosciences, College of Life and Environmental Sciences, Stocker Road, University of Exeter, Exeter EX4 4QD, U.K
| |
Collapse
|
46
|
Yao Y, Zhang W, Zhang M, Jin S, Guo Y, Zu Y, Ren K, Wang K, Chen G, Lou C, Wu Q. A Direct RNA-to-RNA Replication System for Enhanced Gene Expression in Bacteria. ACS Synth Biol 2019; 8:1067-1078. [PMID: 31070362 DOI: 10.1021/acssynbio.8b00521] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
A long-standing objective of metabolic engineering has been to exogenously increase the expression of target genes. In this research, we proposed the permanent RNA replication system using DNA as a template to store genetic information in bacteria. We selected Qβ phage as the RNA replication prototype and made many improvements to achieve target gene expression enhancement directly by increasing mRNA abundance. First, we identified the endogenous gene Rnc, the knockout of which significantly improved the RNA replication efficiency. Second, we elucidated the essential elements for RNA replication and optimized the system to make it more easily applicable. Combined with optimization of the host cell and the system itself, we developed a stable RNA-to-RNA replication tool to directly increase the abundance of the target mRNA and subsequently the target protein. Furthermore, it was proven efficient in enhancing the expression of specific proteins and was demonstrated to be applicable in metabolic engineering. Our system has the potential to be combined with any of the existing methods for increasing gene expression.
Collapse
Affiliation(s)
- Yi Yao
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Wenhui Zhang
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Min Zhang
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Shouhong Jin
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Yingying Guo
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Peking-Tsinghua Center for Life Sciences, School of Life Science, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China
| | - Yumeng Zu
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Kang Ren
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Kun Wang
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Guoqiang Chen
- Peking-Tsinghua Center for Life Sciences, School of Life Science, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China
- MOE Key Lab of Industrial Biocatalysis, Tsinghua University, Beijing 100081, China
| | - Chunbo Lou
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering and Institute of Microbiology, State Key Laboratory of Microbial Resources, Institute of Microbiology Chinese Academy of Sciences, Beijing 100101, China
| | - Qiong Wu
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China
| |
Collapse
|
47
|
Abstract
Synthetic biology has undergone dramatic advancements for over a decade, during which it has expanded our understanding on the systems of life and opened new avenues for microbial engineering. Many biotechnological and computational methods have been developed for the construction of synthetic systems. Achievements in synthetic biology have been widely adopted in metabolic engineering, a field aimed at engineering micro-organisms to produce substances of interest. However, the engineering of metabolic systems requires dynamic redistribution of cellular resources, the creation of novel metabolic pathways, and optimal regulation of the pathways to achieve higher production titers. Thus, the design principles and tools developed in synthetic biology have been employed to create novel and flexible metabolic pathways and to optimize metabolic fluxes to increase the cells’ capability to act as production factories. In this review, we introduce synthetic biology tools and their applications to microbial cell factory constructions.
Collapse
|
48
|
Shen R, Yin J, Ye JW, Xiang RJ, Ning ZY, Huang WZ, Chen GQ. Promoter Engineering for Enhanced P(3HB- co-4HB) Production by Halomonas bluephagenesis. ACS Synth Biol 2018; 7:1897-1906. [PMID: 30024739 DOI: 10.1021/acssynbio.8b00102] [Citation(s) in RCA: 68] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Promoters for the expression of heterologous genes in Halomonas bluephagenesis are quite limited, and many heterologous promoters function abnormally in this strain. Pporin, a promoter of the strongest expressed protein porin in H. bluephagenesis, is one of the few promoters available for heterologous expression in H. bluephagenesis, yet it has a fixed transcriptional activity that cannot be tuned. A stable promoter library with a wide range of activities is urgently needed. This study reports an approach to construct a promoter library based on the Pporin core region, namely, from the -35 box to the transcription start site, a spacer and an insulator. Saturation mutagenesis was conducted inside the promoter core region to significantly increase the diversity within the promoter library. The promoter library worked in both E. coli and H. bluephagenesis, covering a wide range of relative transcriptional strengths from 40 to 140 000. The library is therefore suitable for the transcription of many different heterologous genes, serving as a platform for protein expression and fine-tuned metabolic engineering of H. bluephagenesis TD01 and its derivative strains. H. bluephagenesis strains harboring the orfZ gene encoding 4HB-CoA transferase driven by selected promoters from the library were constructed, the best one produced over 100 g/L cell dry weight containing 80% poly(3-hydroxybutyrate- co-11 mol % 4-hydroxybutyrate) with a productivity of 1.59 g/L/h after 50 h growth under nonsterile fed-batch conditions. This strain was found the best for P(3HB- co-4HB) production in the laboratory scale.
Collapse
Affiliation(s)
- Rui Shen
- MOE Key Lab of Bioinformatics, School of Life Science, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
| | - Jin Yin
- MOE Key Lab of Bioinformatics, School of Life Science, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
| | - Jian-Wen Ye
- MOE Key Lab of Bioinformatics, School of Life Science, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
| | | | - Zhi-Yu Ning
- MOE Key Lab of Bioinformatics, School of Life Science, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
| | - Wu-Zhe Huang
- MOE Key Lab of Bioinformatics, School of Life Science, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
| | - Guo-Qiang Chen
- MOE Key Lab of Bioinformatics, School of Life Science, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing 100084, China
- Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China
| |
Collapse
|
49
|
Li T, Dong Y, Zhang X, Ji X, Luo C, Lou C, Zhang HM, Ouyang Q. Engineering of a genetic circuit with regulatable multistability. Integr Biol (Camb) 2018; 10:474-482. [DOI: 10.1039/c8ib00030a] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Affiliation(s)
- Tingting Li
- Centre for Quantitative Biology and Peking-Tsinghua Joint Centre for Life Sciences, Peking University, Beijing 100871, China
| | - Yiming Dong
- Centre for Quantitative Biology and Peking-Tsinghua Joint Centre for Life Sciences, Peking University, Beijing 100871, China
| | - Xuanqi Zhang
- Centre for Quantitative Biology and Peking-Tsinghua Joint Centre for Life Sciences, Peking University, Beijing 100871, China
| | - Xiangyu Ji
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100871, China
| | - Chunxiong Luo
- Centre for Quantitative Biology and Peking-Tsinghua Joint Centre for Life Sciences, Peking University, Beijing 100871, China
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing 100871, China
| | - Chunbo Lou
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100871, China
| | - Haoqian M. Zhang
- Centre for Quantitative Biology and Peking-Tsinghua Joint Centre for Life Sciences, Peking University, Beijing 100871, China
- Bluepha Co., Ltd., Beijing 102206, China
| | - Qi Ouyang
- Centre for Quantitative Biology and Peking-Tsinghua Joint Centre for Life Sciences, Peking University, Beijing 100871, China
- The State Key Laboratory for Artificial Microstructures and Mesoscopic Physics, School of Physics, Peking University, Beijing 100871, China
| |
Collapse
|
50
|
Hou J, Zeng W, Zong Y, Chen Z, Miao C, Wang B, Lou C. Engineering the Ultrasensitive Transcription Factors by Fusing a Modular Oligomerization Domain. ACS Synth Biol 2018; 7:1188-1194. [PMID: 29733626 DOI: 10.1021/acssynbio.7b00414] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The dimerization and high-order oligomerization of transcription factors has endowed them with cooperative regulatory capabilities that play important roles in many cellular functions. However, such advanced regulatory capabilities have not been fully exploited in synthetic biology and genetic engineering. Here, we engineered a C-terminally fused oligomerization domain to improve the cooperativity of transcription factors. First, we found that two of three designed oligomerization domains significantly increased the cooperativity and ultrasensitivity of a transcription factor for the regulated promoter. Then, seven additional transcription factors were used to assess the modularity of the oligomerization domains, and their ultrasensitivity was generally improved, as assessed by their Hill coefficients. Moreover, we also demonstrated that the allosteric capability of the ligand-responsive domain remained intact when fusing with the designed oligomerization domain. As an example application, we showed that the engineered ultrasensitive transcription factor could be used to significantly improve the performance of a "stripe-forming" gene circuit. We envision that the oligomerization modules engineered in this study could act as a powerful tool to rapidly tune the underlying response profiles of synthetic gene circuits and metabolic pathway controllers.
Collapse
Affiliation(s)
- Junran Hou
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering and Institute of Microbiology, State Key Laboratory of Microbial Resources, Institute of Microbiology Chinese Academy of Sciences, Beijing, 100101, China
- College of Life Science, University of Chinese Academy of Science, Beijing, 100149, China
| | - Weiqian Zeng
- Institute of Molecular Precision Medicine, The Xiangya Hospital, Central South University, Changsha, Hunan 410008, P. R. China
| | - Yeqing Zong
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering and Institute of Microbiology, State Key Laboratory of Microbial Resources, Institute of Microbiology Chinese Academy of Sciences, Beijing, 100101, China
- College of Life Science, University of Chinese Academy of Science, Beijing, 100149, China
| | - Zehua Chen
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering and Institute of Microbiology, State Key Laboratory of Microbial Resources, Institute of Microbiology Chinese Academy of Sciences, Beijing, 100101, China
- College of Life Science, University of Chinese Academy of Science, Beijing, 100149, China
| | - Chensi Miao
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering and Institute of Microbiology, State Key Laboratory of Microbial Resources, Institute of Microbiology Chinese Academy of Sciences, Beijing, 100101, China
- College of Life Sciences, University of Science and Technology of China, Hefei, 230027, China
| | - Baojun Wang
- School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3FF, U.K
- Centre for Synthetic and System Biology, University of Edinburgh, Edinburgh, EH9 3FF, U.K
| | - Chunbo Lou
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering and Institute of Microbiology, State Key Laboratory of Microbial Resources, Institute of Microbiology Chinese Academy of Sciences, Beijing, 100101, China
- College of Life Science, University of Chinese Academy of Science, Beijing, 100149, China
- College of Life Sciences, University of Science and Technology of China, Hefei, 230027, China
| |
Collapse
|