1
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Chaisupa P, Wright RC. State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering. SLAS Technol 2024; 29:100113. [PMID: 37918525 PMCID: PMC11314541 DOI: 10.1016/j.slast.2023.10.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 10/18/2023] [Accepted: 10/25/2023] [Indexed: 11/04/2023]
Abstract
Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.
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Affiliation(s)
- Patarasuda Chaisupa
- Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061, United States
| | - R Clay Wright
- Department of Biological Systems Engineering, Virginia Tech, Blacksburg, VA 24061, United States; Translational Plant Sciences Center (TPSC), Virginia Tech, Blacksburg, VA 24061, United States.
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2
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Cheng L, Zhao S, Li T, Hou S, Luo Z, Xu J, Yu W, Jiang S, Monti M, Schindler D, Zhang W, Hou C, Ma Y, Cai Y, Boeke JD, Dai J. Large-scale genomic rearrangements boost SCRaMbLE in Saccharomyces cerevisiae. Nat Commun 2024; 15:770. [PMID: 38278805 PMCID: PMC10817965 DOI: 10.1038/s41467-023-44511-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 12/13/2023] [Indexed: 01/28/2024] Open
Abstract
Synthetic Chromosome Rearrangement and Modification by LoxP-mediated Evolution (SCRaMbLE) is a promising tool to study genomic rearrangements. However, the potential of SCRaMbLE to study genomic rearrangements is currently hindered, because a strain containing all 16 synthetic chromosomes is not yet available. Here, we construct SparLox83R, a yeast strain containing 83 loxPsym sites distributed across all 16 chromosomes. SCRaMbLE of SparLox83R produces versatile genome-wide genomic rearrangements, including inter-chromosomal events. Moreover, when combined with synthetic chromosomes, SCRaMbLE of hetero-diploids with SparLox83R leads to increased diversity of genomic rearrangements and relatively faster evolution of traits compared to hetero-diploids only with wild-type chromosomes. Analysis of the SCRaMbLEd strain with increased tolerance to nocodazole demonstrates that genomic rearrangements can perturb the transcriptome and 3D genome structure and consequently impact phenotypes. In summary, a genome with sparsely distributed loxPsym sites can serve as a powerful tool for studying the consequence of genomic rearrangements and accelerating strain engineering in Saccharomyces cerevisiae.
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Grants
- 32030004, 32150025 National Natural Science Foundation of China (National Science Foundation of China)
- 32001042 National Natural Science Foundation of China (National Science Foundation of China)
- 32101184 National Natural Science Foundation of China (National Science Foundation of China)
- 32122050 National Natural Science Foundation of China (National Science Foundation of China)
- 2021359 Youth Innovation Promotion Association of the Chinese Academy of Sciences (Youth Innovation Promotion Association CAS)
- National Key R&D Program of China (2022YFF1201800,2018YFA0900100), Guangdong Natural Science Funds for Distinguished Young Scholar (2021B1515020060), Guangdong Provincial Key Laboratory of Synthetic Genomics (2023B1212060054), Bureau of International Cooperation, Chinese Academy of Sciences (172644KYSB20180022), Shenzhen Science and Technology Program (KQTD20180413181837372, KQTD20200925153547003), Innovation Program of Chinese Academy of Agricultural Science and Shenzhen Outstanding Talents Training Fund.
- Guandong Basic and Applied Basic Research Foundation (2023A1515030285)
- UK Biotechnology and Biological Sciences Research Council (BBSRC) grants BB/M005690/1, BB/P02114X/1 and BB/W014483/1, Royal Society Newton Advanced Fellowship (NAF\R2\180590) and a Volkswagen Foundation “Life? Initiative” Grant (Ref. 94 771)
- US NSF grants MCB-1026068, MCB-1443299, MCB-1616111 and MCB-1921641
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Affiliation(s)
- Li Cheng
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Shijun Zhao
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Tianyi Li
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- Shenzhen Lianghe Biotechnology Co., Ltd., Shenzhen, China
| | - Sha Hou
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Zhouqing Luo
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cell Signaling Network, School of Life Sciences, Xiamen University, Xiamen, Fujian, 361102, China
| | - Jinsheng Xu
- Department of Bioinformatics, Huazhong Agricultural University, Wuhan, 430070, China
| | - Wenfei Yu
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Shuangying Jiang
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Marco Monti
- Manchester Institute of Biotechnology, University of Manchester, Manchester, M1 7DN, UK
| | - Daniel Schindler
- Manchester Institute of Biotechnology, University of Manchester, Manchester, M1 7DN, UK
| | - Weimin Zhang
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Chunhui Hou
- China State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China
| | - Yingxin Ma
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
| | - Yizhi Cai
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China
- Manchester Institute of Biotechnology, University of Manchester, Manchester, M1 7DN, UK
| | - Jef D Boeke
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, 11201, USA
| | - Junbiao Dai
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
- University of Chinese Academy of Sciences, Beijing, China.
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Synthetic Biology, Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
- College of Life Sciences and Oceanography, Shenzhen University, 1066 Xueyuan Rd, Shenzhen, 518055, Guangdong, China.
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3
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Chang T, Ding W, Yan S, Wang Y, Zhang H, Zhang Y, Ping Z, Zhang H, Huang Y, Zhang J, Wang D, Zhang W, Xu X, Shen Y, Fu X. A robust yeast biocontainment system with two-layered regulation switch dependent on unnatural amino acid. Nat Commun 2023; 14:6487. [PMID: 37838746 PMCID: PMC10576815 DOI: 10.1038/s41467-023-42358-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2023] [Accepted: 10/09/2023] [Indexed: 10/16/2023] Open
Abstract
Synthetic auxotrophy in which cell viability depends on the presence of an unnatural amino acid (unAA) provides a powerful strategy to restrict unwanted propagation of genetically modified organisms (GMOs) in open environments and potentially prevent industrial espionage. Here, we describe a generic approach for robust biocontainment of budding yeast dependent on unAA. By understanding escape mechanisms, we specifically optimize our strategies by introducing designed "immunity" to the generation of amber-suppressor tRNAs and developing the transcriptional- and translational-based biocontainment switch. We further develop a fitness-oriented screening method to easily obtain multiplex safeguard strains that exhibit robust growth and undetectable escape frequency (<~10-9) on solid media for 14 days. Finally, we show that employing our multiplex safeguard system could restrict the proliferation of strains of interest in a real fermentation scenario, highlighting the great potential of our yeast biocontainment strategy to protect the industrial proprietary strains.
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Affiliation(s)
- Tiantian Chang
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
- BGI Research, Shenzhen, 518083, China
| | - Weichao Ding
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China
| | - Shirui Yan
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China
| | - Yun Wang
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China
| | - Haoling Zhang
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China
| | - Yu Zhang
- BGI Research, Shenzhen, 518083, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China
| | - Zhi Ping
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China
| | - Huiming Zhang
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
- BGI Research, Shenzhen, 518083, China
| | - Yijian Huang
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
- BGI Research, Shenzhen, 518083, China
| | - Jiahui Zhang
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
- BGI Research, Shenzhen, 518083, China
| | - Dan Wang
- Guangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Science, BNU-HKBU United International College, Zhuhai, 519087, China
- BNU-HKBU United International College, Zhuhai, 519087, China
| | - Wenwei Zhang
- BGI Research, Shenzhen, 518083, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China
| | - Xun Xu
- BGI Research, Shenzhen, 518083, China
- BGI Research, Changzhou, 213299, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China
| | - Yue Shen
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China.
- BGI Research, Shenzhen, 518083, China.
- BGI Research, Changzhou, 213299, China.
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China.
| | - Xian Fu
- BGI Research, Shenzhen, 518083, China.
- BGI Research, Changzhou, 213299, China.
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China.
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4
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Maheshwari AJ, Calles J, Waterton SK, Endy D. Engineering tRNA abundances for synthetic cellular systems. Nat Commun 2023; 14:4594. [PMID: 37524714 PMCID: PMC10390467 DOI: 10.1038/s41467-023-40199-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 07/13/2023] [Indexed: 08/02/2023] Open
Abstract
Routinizing the engineering of synthetic cells requires specifying beforehand how many of each molecule are needed. Physics-based tools for estimating desired molecular abundances in whole-cell synthetic biology are missing. Here, we use a colloidal dynamics simulator to make predictions for how tRNA abundances impact protein synthesis rates. We use rational design and direct RNA synthesis to make 21 synthetic tRNA surrogates from scratch. We use evolutionary algorithms within a computer aided design framework to engineer translation systems predicted to work faster or slower depending on tRNA abundance differences. We build and test the so-specified synthetic systems and find qualitative agreement between expected and observed systems. First principles modeling combined with bottom-up experiments can help molecular-to-cellular scale synthetic biology realize design-build-work frameworks that transcend tinker-and-test.
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Affiliation(s)
| | - Jonathan Calles
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Sean K Waterton
- Department of Biology, Stanford University, Stanford, CA, 94305, USA
| | - Drew Endy
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
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5
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Takeoka M, Hoki Y, Yoshinaka T, Hirano K, Mitsui Y, Doi T, Takemura A, Asano T, Katoh R, Nose A, Kozaki D. Multi-Functional Separation Mode-Ion Chromatography Using L-Pyroglutamic Acid Eluent for Simultaneous Determination of Sugars, Organic Acids, and Ethanol during Multiple Parallel Fermentation of Rice Wine. JOURNAL OF THE AMERICAN SOCIETY OF BREWING CHEMISTS 2023. [DOI: 10.1080/03610470.2022.2158437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Affiliation(s)
- Marino Takeoka
- Department of Chemistry and Biotechnology, Faculty of Science and Technology, Kochi University, Kochi, Japan
| | | | - Taichi Yoshinaka
- Department of Brewing, Tsukasa Botan Brewing Company, Limited, Kochi, Japan
| | - Kentarou Hirano
- Department of Brewing, Tsukasa Botan Brewing Company, Limited, Kochi, Japan
| | - Yuta Mitsui
- Department of Chemistry and Biotechnology, Faculty of Science and Technology, Kochi University, Kochi, Japan
| | | | - Akihiko Takemura
- Department of Brewing, Tsukasa Botan Brewing Company, Limited, Kochi, Japan
| | - Tohru Asano
- Department of Brewing, Tsukasa Botan Brewing Company, Limited, Kochi, Japan
| | | | - Akira Nose
- Department of Nutritional Science, Faculty of Human Ecology, Yasuda Women’s University, Hiroshima, Japan
| | - Daisuke Kozaki
- Department of Chemistry and Biotechnology, Faculty of Science and Technology, Kochi University, Kochi, Japan
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6
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Reconfiguring the Challenge of Biological Complexity as a Resource for Biodesign. mSphere 2022; 7:e0054722. [PMID: 36472448 PMCID: PMC9769621 DOI: 10.1128/msphere.00547-22] [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] Open
Abstract
Biological complexity is widely seen as the central, intractable challenge of engineering biology. Yet this challenge has been constructed through the field's dominant metaphors. Alternative ways of thinking-latent in progressive experimental approaches, but rarely articulated as such-could instead position complexity as engineering biology's greatest resource. We outline how assumptions about engineered microorganisms have been built into the field, carried by entrenched metaphors, even as contemporary methods move beyond them. We suggest that alternative metaphors would better align engineering biology's conceptual infrastructure with the field's move away from conventionally engineering-inspired methods toward biology-centric ones. Innovating new conceptual frameworks would also enable better aligning scientific work with higher-level conversations about that work. Such innovation-thinking about how engineering microbes might be more like user-centered design than like programming a computer or building a car-could highlight complexity as a resource to leverage, not a problem to erase or negate.
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7
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Bartoszewicz JM, Nasri F, Nowicka M, Renard BY. Detecting DNA of novel fungal pathogens using ResNets and a curated fungi-hosts data collection. Bioinformatics 2022; 38:ii168-ii174. [PMID: 36124807 DOI: 10.1093/bioinformatics/btac495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/08/2022] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Emerging pathogens are a growing threat, but large data collections and approaches for predicting the risk associated with novel agents are limited to bacteria and viruses. Pathogenic fungi, which also pose a constant threat to public health, remain understudied. Relevant data remain comparatively scarce and scattered among many different sources, hindering the development of sequencing-based detection workflows for novel fungal pathogens. No prediction method working for agents across all three groups is available, even though the cause of an infection is often difficult to identify from symptoms alone. RESULTS We present a curated collection of fungal host range data, comprising records on human, animal and plant pathogens, as well as other plant-associated fungi, linked to publicly available genomes. We show that it can be used to predict the pathogenic potential of novel fungal species directly from DNA sequences with either sequence homology or deep learning. We develop learned, numerical representations of the collected genomes and visualize the landscape of fungal pathogenicity. Finally, we train multi-class models predicting if next-generation sequencing reads originate from novel fungal, bacterial or viral threats. CONCLUSIONS The neural networks trained using our data collection enable accurate detection of novel fungal pathogens. A curated set of over 1400 genomes with host and pathogenicity metadata supports training of machine-learning models and sequence comparison, not limited to the pathogen detection task. AVAILABILITY AND IMPLEMENTATION The data, models and code are hosted at https://zenodo.org/record/5846345, https://zenodo.org/record/5711877 and https://gitlab.com/dacs-hpi/deepac. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Jakub M Bartoszewicz
- Hasso Plattner Institute for Digital Engineering, Digital Engineering Faculty, University of Potsdam, Potsdam 14482, Germany.,Department of Mathematics and Computer Science, Free University of Berlin, Berlin 14195, Germany
| | - Ferdous Nasri
- Hasso Plattner Institute for Digital Engineering, Digital Engineering Faculty, University of Potsdam, Potsdam 14482, Germany.,Department of Mathematics and Computer Science, Free University of Berlin, Berlin 14195, Germany
| | - Melania Nowicka
- Hasso Plattner Institute for Digital Engineering, Digital Engineering Faculty, University of Potsdam, Potsdam 14482, Germany.,Department of Mathematics and Computer Science, Free University of Berlin, Berlin 14195, Germany
| | - Bernhard Y Renard
- Hasso Plattner Institute for Digital Engineering, Digital Engineering Faculty, University of Potsdam, Potsdam 14482, Germany
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8
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Huang C, Wang C, Luo Y. Research progress of pathway and genome evolution in microbes. Synth Syst Biotechnol 2022; 7:648-656. [PMID: 35224232 PMCID: PMC8857405 DOI: 10.1016/j.synbio.2022.01.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 12/23/2021] [Accepted: 01/06/2022] [Indexed: 12/16/2022] Open
Abstract
Microbes can produce valuable natural products widely applied in medicine, food and other important fields. Nevertheless, it is usually challenging to achieve ideal industrial yields due to low production rate and poor toxicity tolerance. Evolution is a constant mutation and adaptation process used to improve strain performance. Generally speaking, the synthesis of natural products in microbes is often intricate, involving multiple enzymes or multiple pathways. Individual evolution of a certain enzyme often fails to achieve the desired results, and may lead to new rate-limiting nodes that affect the growth of microbes. Therefore, it is inevitable to evolve the biosynthetic pathways or the whole genome. Here, we reviewed the pathway-level evolution including multi-enzyme evolution, regulatory elements engineering, and computer-aided engineering, as well as the genome-level evolution based on several tools, such as genome shuffling and CRISPR/Cas systems. Finally, we also discussed the major challenges faced by in vivo evolution strategies and proposed some potential solutions.
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Affiliation(s)
- Chaoqun Huang
- Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Chang Wang
- Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Yunzi Luo
- Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
- Georgia Tech Shenzhen Institute, Tianjin University, Tangxing Road 133, Nanshan District, Shenzhen, 518071, China
- Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin University, Tianjin, 300072, China
- Corresponding author. Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China.
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9
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Engineering eukaryote-like regulatory circuits to expand artificial control mechanisms for metabolic engineering in Saccharomyces cerevisiae. Commun Biol 2022; 5:135. [PMID: 35173283 PMCID: PMC8850539 DOI: 10.1038/s42003-022-03070-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Accepted: 01/20/2022] [Indexed: 12/22/2022] Open
Abstract
Temporal control of heterologous pathway expression is critical to achieve optimal efficiency in microbial metabolic engineering. The broadly-used GAL promoter system for engineered yeast (Saccharomyces cerevisiae) suffers from several drawbacks; specifically, unintended induction during laboratory development, and unintended repression in industrial production applications, which decreases overall production capacity. Eukaryotic synthetic circuits have not been well examined to address these problems. Here, we explore a modularised engineering method to deploy new genetic circuits applicable for expanding the control of GAL promoter-driven heterologous pathways in S. cerevisiae. Trans- and cis- modules, including eukaryotic trans-activating-and-repressing mechanisms, were characterised to provide new and better tools for circuit design. A eukaryote-like tetracycline-mediated circuit that delivers stringent repression was engineered to minimise metabolic burden during strain development and maintenance. This was combined with a novel 37 °C induction circuit to relief glucose-mediated repression on the GAL promoter during the bioprocess. This delivered a 44% increase in production of the terpenoid nerolidol, to 2.54 g L-1 in flask cultivation. These negative/positive transcriptional regulatory circuits expand global strategies of metabolic control to facilitate laboratory maintenance and for industry applications.
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10
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Szymanski E. Words Are Essential, but Underexamined, Research Tools for Microbes and Microbiomes. mSystems 2021; 6:e0076921. [PMID: 34463574 DOI: 10.1128/msystems.00769-21] [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: 11/20/2022] Open
Abstract
Language constitutes an essential set of scientific construction tools, not only for communicating knowledge, but for conceptualizing the world. Metaphors in particular, as conventions that guide and reproduce analogical reasoning, merit attention that they largely do not receive. My research addresses this deficit by examining how metaphors for handling microbes shape possibilities for working with yeast and bacteria in synthetic biology, microbiome research, and other fields that reconfigure what microbes can be. Though poised to reexamine assumptions, these fields routinely rest on metaphors and other language tools that quietly embed ways of thinking that may work against wider aims-for example, imagining bacteria as imperfect machines that should therefore be rendered increasingly passive and controllable. Researchers, therefore, need to examine how language tools structure their observations and expectations so that the tools they choose are appropriate for the work they want to do.
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Affiliation(s)
- Erika Szymanski
- Department of English, Colorado State University, Fort Collins, Colorado, USA
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11
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Pujari I, Thomas A, Sankar Babu V. Native and non-native host assessment towards metabolic pathway reconstructions of plant natural products. ACTA ACUST UNITED AC 2021; 30:e00619. [PMID: 33996523 PMCID: PMC8091882 DOI: 10.1016/j.btre.2021.e00619] [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: 09/14/2020] [Revised: 04/05/2021] [Accepted: 04/11/2021] [Indexed: 11/16/2022]
Abstract
Plant metabolic networks are highly complex. Engineering the phytochemical pathways fully in heterologous hosts is challenging. Single plant cells with amplified multiple fission enable homogeneity. Homogeneity and high cell division rate can facilitate stable product scale-up.
Plant-based biopreparations are reasonably priced and are devoid of viral, prion and endotoxin contaminants. However, synthesizing these natural plant products by chemical methods is quite expensive. The structural complexity of plant-derived natural products poses a challenge for chemical synthesis at a commercial scale. Failure of commercial-scale synthesis is the chief reason why metabolic reconstructions in heterologous hosts are inevitable. This review discusses plant metabolite pathway reconstructions experimented in various heterologous hosts, and the inherent challenges involved. Plants as native hosts possess enhanced post-translational modification ability, along with rigorous gene edits, unlike microbes. To achieve a high yield of metabolites in plants, increased cell division rate is one of the requisites. This improved cell division rate will promote cellular homogeneity. Incorporation and maintenance of plant cell synchrony, in turn, can program stable product scale-up.
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Affiliation(s)
- Ipsita Pujari
- Department of Plant Sciences, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
| | - Abitha Thomas
- Department of Plant Sciences, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
| | - Vidhu Sankar Babu
- Department of Plant Sciences, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India
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12
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Simons M. Synthetic biology as a technoscience: The case of minimal genomes and essential genes. STUDIES IN HISTORY AND PHILOSOPHY OF SCIENCE 2021; 85:127-136. [PMID: 33966767 DOI: 10.1016/j.shpsa.2020.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Accepted: 09/24/2020] [Indexed: 06/12/2023]
Abstract
This article examines how minimal genome research mobilizes philosophical concepts such as minimality and essentiality. Following a historical approach the article aims to uncover what function this terminology plays and which problems are raised by them. Specifically, four historical moments are examined, linked to the work of Harold J. Morowitz, Mitsuhiro Itaya, Eugene Koonin and Arcady Mushegian, and J. Craig Venter. What this survey shows is a historical shift away from historical questions about life or descriptive questions about specific organisms towards questions that explore biological possibilities: what are possible forms of minimal genomes, regardless of whether they exist in nature? Moreover, it highlights a fundamental ambiguity at work in minimal genome research between a universality claim and a standardization claim: does a minimal genome refer to the minimal gene set for any organism whatsoever? Or does it refer rather to a gene set that will provide stable, robust and predictable behaviour, suited for biotechnological applications? Two diagnoses are proposed for this ambiguity: a philosophical diagnosis of how minimal genome research either misunderstands the ontology of biological entities or philosophically misarticulates scientific practice. Secondly, a historical diagnosis that suggests that this ambiguity is part of a broader shift towards technoscience.
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Affiliation(s)
- Massimiliano Simons
- Ghent University, Department of Philosophy and Moral Sciences, Blandijnberg 2, BE-9000, Ghent, Belgium.
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Chen R, Yang S, Zhang L, Zhou YJ. Advanced Strategies for Production of Natural Products in Yeast. iScience 2020; 23:100879. [PMID: 32087574 PMCID: PMC7033514 DOI: 10.1016/j.isci.2020.100879] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2019] [Revised: 01/27/2020] [Accepted: 01/28/2020] [Indexed: 12/30/2022] Open
Abstract
Natural products account for more than 50% of all small-molecule pharmaceutical agents currently in clinical use. However, low availability often becomes problematic when a bioactive natural product is promising to become a pharmaceutical or leading compound. Advances in synthetic biology and metabolic engineering provide a feasible solution for sustainable supply of these compounds. In this review, we have summarized current progress in engineering yeast cell factories for production of natural products, including terpenoids, alkaloids, and phenylpropanoids. We then discuss advanced strategies in metabolic engineering at three different dimensions, including point, line, and plane (corresponding to the individual enzymes and cofactors, metabolic pathways, and the global cellular network). In particular, we comprehensively discuss how to engineer cofactor biosynthesis for enhancing the biosynthesis efficiency, other than the enzyme activity. Finally, current challenges and perspective are also discussed for future engineering direction.
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Affiliation(s)
- Ruibing Chen
- Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China; Department of Pharmaceutical Botany, School of Pharmacy, Naval Medical University, Shanghai 200433, China
| | - Shan Yang
- Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Lei Zhang
- Department of Pharmaceutical Botany, School of Pharmacy, Naval Medical University, Shanghai 200433, China; Biomedical Innovation R&D Center, School of Medicine, Shanghai University, Shanghai 200444, China
| | - Yongjin J Zhou
- Division of Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China; CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China; Dalian Key Laboratory of Energy Biotechnology, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.
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Alperstein L, Gardner JM, Sundstrom JF, Sumby KM, Jiranek V. Yeast bioprospecting versus synthetic biology-which is better for innovative beverage fermentation? Appl Microbiol Biotechnol 2020; 104:1939-1953. [PMID: 31953561 DOI: 10.1007/s00253-020-10364-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 12/30/2019] [Accepted: 01/09/2020] [Indexed: 01/08/2023]
Abstract
Producers often utilise some of the many available yeast species and strains in the making of fermented alcoholic beverages in order to augment flavours, aromas, acids and textural properties. But still, the demand remains for more yeasts with novel phenotypes that not only impact sensory characteristics but also offer process and engineering advantages. Two strategies for finding such yeasts are (i) bioprospecting for novel strains and species and (ii) genetic modification of known yeasts. The latter enjoys the promise of the emerging field of synthetic biology, which, in principle, would enable scientists to create yeasts with the exact phenotype desired for a given fermentation. In this mini review, we compare and contrast advances in bioprospecting and in synthetic biology as they relate to alcoholic fermentation in brewing and wine making. We explore recent advances in fermentation-relevant recombinant technologies and synthetic biology including the Yeast 2.0 Consortium, use of environmental yeasts, challenges, constraints of law and consumer acceptance.
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Affiliation(s)
- Lucien Alperstein
- Department of Wine & Food Science, The University of Adelaide, PMB1, Glen Osmond, 5064, South Australia, Australia
| | - Jennifer M Gardner
- Department of Wine & Food Science, The University of Adelaide, PMB1, Glen Osmond, 5064, South Australia, Australia
| | - Joanna F Sundstrom
- Department of Wine & Food Science, The University of Adelaide, PMB1, Glen Osmond, 5064, South Australia, Australia.,Australian Research Council Training Centre for Innovative Wine Production, Urrbrae, South Australia, Australia
| | - Krista M Sumby
- Department of Wine & Food Science, The University of Adelaide, PMB1, Glen Osmond, 5064, South Australia, Australia.,Australian Research Council Training Centre for Innovative Wine Production, Urrbrae, South Australia, Australia
| | - Vladimir Jiranek
- Department of Wine & Food Science, The University of Adelaide, PMB1, Glen Osmond, 5064, South Australia, Australia. .,Australian Research Council Training Centre for Innovative Wine Production, Urrbrae, South Australia, Australia.
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15
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Brown DM, Glass JI. Technology used to build and transfer mammalian chromosomes. Exp Cell Res 2020; 388:111851. [PMID: 31952951 DOI: 10.1016/j.yexcr.2020.111851] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2019] [Revised: 01/09/2020] [Accepted: 01/14/2020] [Indexed: 01/05/2023]
Abstract
In the near twenty-year existence of the human and mammalian artificial chromosome field, the technologies for artificial chromosome construction and installation into desired cell types or organisms have evolved with the rest of modern molecular and synthetic biology. Medical, industrial, pharmaceutical, agricultural, and basic research scientists seek the as yet unrealized promise of human and mammalian artificial chromosomes. Existing technologies for both top-down and bottom-up approaches to construct these artificial chromosomes for use in higher eukaryotes are very different but aspire to achieve similar results. New capacity for production of chromosome sized synthetic DNA will likely shift the field towards more bottom-up approaches, but not completely. Similarly, new approaches to install human and mammalian artificial chromosomes in target cells will compete with the microcell mediated cell transfer methods that currently dominate the field.
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Bizzarri M, Cassanelli S, Dušková M, Sychrová H, Solieri L. A set of plasmids carrying antibiotic resistance markers and Cre recombinase for genetic engineering of nonconventional yeast Zygosaccharomyces rouxii. Yeast 2019; 36:711-722. [PMID: 31414502 DOI: 10.1002/yea.3438] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 07/23/2019] [Accepted: 08/04/2019] [Indexed: 01/23/2023] Open
Abstract
The so-called nonconventional yeasts are becoming increasingly attractive in food and industrial biotechnology. Among them, Zygosaccharomyces rouxii is known to be halotolerant, osmotolerant, petite negative, and poorly Crabtree positive. These traits and the high fermentative vigour make this species very appealing for industrial and food applications. Nevertheless, the biotechnological exploitation of Z. rouxii has been biased by the low availability of genetic engineering tools and the recalcitrance of this yeast towards the most conventional transformation procedures. Centromeric and episomal Z. rouxii plasmids have been successfully constructed with prototrophic markers, which limited their usage to auxotrophic strains, mainly derived from the Z. rouxii haploid type strain Centraalbureau voor Schimmelcultures (CBS) 732T . By contrast, the majority of industrially promising Z. rouxii yeasts are prototrophic and allodiploid/aneuploid strains. In order to expand the genetic tools for manipulating these strains, we developed two centromeric and two episomal vectors harbouring KanMXR and ClonNATR as dominant drug resistance markers, respectively. We also constructed the plasmid pGRCRE that allows the Cre recombinase-mediated marker recycling during multiple gene deletions. As proof of concept, pGRCRE was successfully used to rescue the kanMX-loxP module in Z. rouxii ATCC 42981 G418-resistant mutants previously constructed by replacing the MATαP expression locus with the loxP-kanMX-loxP cassette.
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Affiliation(s)
- Melissa Bizzarri
- Department of Life Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy
| | - Stefano Cassanelli
- Department of Life Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy
| | - Michala Dušková
- Department of Membrane Transport, Institute of Physiology, Czech Academy of Sciences, Prague, Czech Republic
| | - Hana Sychrová
- Department of Membrane Transport, Institute of Physiology, Czech Academy of Sciences, Prague, Czech Republic
| | - Lisa Solieri
- Department of Life Sciences, University of Modena and Reggio Emilia, Reggio Emilia, Italy
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Xia PF, Ling H, Foo JL, Chang MW. Synthetic genetic circuits for programmable biological functionalities. Biotechnol Adv 2019; 37:107393. [PMID: 31051208 DOI: 10.1016/j.biotechadv.2019.04.015] [Citation(s) in RCA: 66] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2018] [Revised: 04/09/2019] [Accepted: 04/28/2019] [Indexed: 02/06/2023]
Abstract
Living organisms evolve complex genetic networks to interact with the environment. Due to the rapid development of synthetic biology, various modularized genetic parts and units have been identified from these networks. They have been employed to construct synthetic genetic circuits, including toggle switches, oscillators, feedback loops and Boolean logic gates. Building on these circuits, complex genetic machines with capabilities in programmable decision-making could be created. Consequently, these accomplishments have led to novel applications, such as dynamic and autonomous modulation of metabolic networks, directed evolution of biological units, remote and targeted diagnostics and therapies, as well as biological containment methods to prevent release of engineered microorganisms and genetic materials. Herein, we outline the principles in genetic circuit design that have initiated a new chapter in transforming concepts to realistic applications. The features of modularized building blocks and circuit architecture that facilitate realization of circuits for a variety of novel applications are discussed. Furthermore, recent advances and challenges in employing genetic circuits to impart microorganisms with distinct and programmable functionalities are highlighted. We envision that this review gives new insights into the design of synthetic genetic circuits and offers a guideline for the implementation of different circuits in various aspects of biotechnology and bioengineering.
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Affiliation(s)
- Peng-Fei Xia
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore
| | - Hua Ling
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore
| | - Jee Loon Foo
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore.
| | - Matthew Wook Chang
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore.
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Abstract
With the rapid development of DNA synthesis and next-generation sequencing, synthetic biology that aims to standardize, modularize, and innovate cellular functions, has achieved vast progress. Here we review key advances in synthetic biology of the yeast Saccharomyces cerevisiae, which serves as an important eukaryal model organism and widely applied cell factory. This covers the development of new building blocks, i.e., promoters, terminators and enzymes, pathway engineering, tools developments, and gene circuits utilization. We will also summarize impacts of synthetic biology on both basic and applied biology, and end with further directions for advancing synthetic biology in yeast.
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Affiliation(s)
- Zihe Liu
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, College of Life Science and Technology, Beijing Key Laboratory of Bioprocess , Beijing University of Chemical Technology , Beijing 100029 , China
| | - Yueping Zhang
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, College of Life Science and Technology, Beijing Key Laboratory of Bioprocess , Beijing University of Chemical Technology , Beijing 100029 , China
| | - Jens Nielsen
- Beijing Advanced Innovation Center for Soft Matter Science and Engineering, College of Life Science and Technology, Beijing Key Laboratory of Bioprocess , Beijing University of Chemical Technology , Beijing 100029 , China.,Department of Biology and Biological Engineering , Chalmers University of Technology , Gothenburg SE41296 , Sweden.,Novo Nordisk Foundation Center for Biosustainability , Technical University of Denmark , Kongens Lyngby DK2800 , Denmark
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Blount BA, Ellis T. The Synthetic Genome Summer Course. Synth Biol (Oxf) 2018; 3:ysy020. [PMID: 32995526 PMCID: PMC7445779 DOI: 10.1093/synbio/ysy020] [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: 09/03/2018] [Revised: 11/02/2018] [Accepted: 11/09/2018] [Indexed: 12/04/2022] Open
Abstract
The Synthetic Genome Summer Course was convened with the aim of teaching a wide range of researchers the theory and practical skills behind recent advances in synthetic biology and synthetic genome science, with a focus on Sc2.0, the synthetic yeast genome project. Through software workshops, tutorials and research talks from leading members of the field, the 30 attendees learnt about relevant principles and techniques that they were then able to implement first-hand in laboratory-based practical sessions. Participants SCRaMbLEd semi-synthetic yeast strains to diversify heterologous pathways, used automation to build combinatorial pathway libraries and used CRISPR to debug fitness defects caused by synthetic chromosome design changes. Societal implications of synthetic chromosomes were explored and industrial stakeholders discussed synthetic biology from a commercial standpoint. Over the 5 days, participants gained valuable insight and acquired skills to aid them in future synthetic genome research.
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Affiliation(s)
- Benjamin A Blount
- Imperial College Centre for Synthetic Biology, Imperial College London, London, UK
- Department of Bioengineering, Imperial College London, London, UK
| | - Tom Ellis
- Imperial College Centre for Synthetic Biology, Imperial College London, London, UK
- Department of Bioengineering, Imperial College London, London, UK
- Corresponding author: E-mail:
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