1
|
McDonnell L, Evans S, Lu Z, Suchoronczak M, Leighton J, Ordeniza E, Ritchie B, Valado N, Walsh N, Antoney J, Wang C, Luna-Flores CH, Scott C, Speight R, Vickers CE, Peng B. Cyanamide-inducible expression of homing nuclease I- SceI for selectable marker removal and promoter characterisation in Saccharomyces cerevisiae. Synth Syst Biotechnol 2024; 9:820-827. [PMID: 39072146 PMCID: PMC11277796 DOI: 10.1016/j.synbio.2024.06.009] [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: 04/07/2024] [Revised: 06/27/2024] [Accepted: 06/27/2024] [Indexed: 07/30/2024] Open
Abstract
In synthetic biology, microbial chassis including yeast Saccharomyces cerevisiae are iteratively engineered with increasing complexity and scale. Wet-lab genetic engineering tools are developed and optimised to facilitate strain construction but are often incompatible with each other due to shared regulatory elements, such as the galactose-inducible (GAL) promoter in S. cerevisiae. Here, we prototyped the cyanamide-induced I- SceI expression, which triggered double-strand DNA breaks (DSBs) for selectable marker removal. We further combined cyanamide-induced I- SceI-mediated DSB and maltose-induced MazF-mediated negative selection for plasmid-free in situ promoter substitution, which simplified the molecular cloning procedure for promoter characterisation. We then characterised three tetracycline-inducible promoters showing differential strength, a non-leaky β-estradiol-inducible promoter, cyanamide-inducible DDI2 promoter, bidirectional MAL32/MAL31 promoters, and five pairs of bidirectional GAL1/GAL10 promoters. Overall, alternative regulatory controls for genome engineering tools can be developed to facilitate genomic engineering for synthetic biology and metabolic engineering applications.
Collapse
Affiliation(s)
- Liam McDonnell
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
- ARC Centre of Excellence in Synthetic Biology, Australia
| | - Samuel Evans
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
- ARC Centre of Excellence in Synthetic Biology, Australia
| | - Zeyu Lu
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
- ARC Centre of Excellence in Synthetic Biology, Australia
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Mitch Suchoronczak
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - Jonah Leighton
- School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - Eugene Ordeniza
- School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - Blake Ritchie
- School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - Nik Valado
- School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - Niamh Walsh
- School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - James Antoney
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
- ARC Centre of Excellence in Synthetic Biology, Australia
| | - Chengqiang Wang
- College of Life Sciences, Shandong Agricultural University, Taian, Shandong Province, 271018, People's Republic of China
| | - Carlos Horacio Luna-Flores
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
| | - Colin Scott
- CSIRO Environment, Black Mountain Science and Innovation Park, Canberra, ACT, 2601, Australia
| | - Robert Speight
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
- ARC Centre of Excellence in Synthetic Biology, Australia
- Advanced Engineering Biology Future Science Platform, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Black Mountain, ACT, 2601, Australia
| | - Claudia E. Vickers
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
- ARC Centre of Excellence in Synthetic Biology, Australia
| | - Bingyin Peng
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD, 4000, Australia
- ARC Centre of Excellence in Synthetic Biology, Australia
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD, 4072, Australia
| |
Collapse
|
2
|
Zhou Z, Li Z, Zhong Y, Xu S, Li Z. Engineering of the Lrp/AsnC-type transcriptional regulator DecR as a genetically encoded biosensor for multilevel optimization of L-cysteine biosynthesis pathway in Escherichia coli. Biotechnol Bioeng 2024; 121:2133-2146. [PMID: 38634289 DOI: 10.1002/bit.28716] [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: 01/11/2024] [Revised: 03/27/2024] [Accepted: 04/08/2024] [Indexed: 04/19/2024]
Abstract
L-cysteine is an important sulfur-containing amino acid being difficult to produce by microbial fermentation. Due to the lack of high-throughput screening methods, existing genetically engineered bacteria have been developed by simply optimizing the expression of L-cysteine-related genes one by one. To overcome this limitation, in this study, a biosensor-based approach for multilevel biosynthetic pathway optimization of L-cysteine from the DecR regulator variant of Escherichia coli was applied. Through protein engineering, we obtained the DecRN29Y/C81E/M90Q/M99E variant-based biosensor with improved specificity and an 8.71-fold increase in dynamic range. Using the developed biosensor, we performed high-throughput screening of the constructed promoter and RBS combination library, and successfully obtained the optimized strain, which resulted in a 6.29-fold increase in L-cysteine production. Molecular dynamics (MD) simulations and electrophoretic mobility shift analysis (EMSA) showed that the N29Y/C81E/M90Q/M99E variant had enhanced induction activity. This enhancement may be due to the increased binding of the variant to DNA in the presence of L-cysteine, which enhances transcriptional activation. Overall, our biosensor-based strategy provides a promising approach for optimizing biosynthetic pathways at multiple levels. The successful implementation of this strategy demonstrates its potential for screening improved recombinant strains.
Collapse
Affiliation(s)
- Zhiyou Zhou
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
| | - Zonglin Li
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
| | - Yahui Zhong
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
| | - Shuai Xu
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
| | - Zhimin Li
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, China
- Shanghai Collaborative Innovation Center for Biomanufacturing Technology, Shanghai, China
| |
Collapse
|
3
|
Gou Y, Li D, Zhao M, Li M, Zhang J, Zhou Y, Xiao F, Liu G, Ding H, Sun C, Ye C, Dong C, Gao J, Gao D, Bao Z, Huang L, Xu Z, Lian J. Intein-mediated temperature control for complete biosynthesis of sanguinarine and its halogenated derivatives in yeast. Nat Commun 2024; 15:5238. [PMID: 38898098 PMCID: PMC11186835 DOI: 10.1038/s41467-024-49554-w] [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: 01/01/2024] [Accepted: 06/10/2024] [Indexed: 06/21/2024] Open
Abstract
While sanguinarine has gained recognition for antimicrobial and antineoplastic activities, its complex conjugated structure and low abundance in plants impede broad applications. Here, we demonstrate the complete biosynthesis of sanguinarine and halogenated derivatives using highly engineered yeast strains. To overcome sanguinarine cytotoxicity, we establish a splicing intein-mediated temperature-responsive gene expression system (SIMTeGES), a simple strategy that decouples cell growth from product synthesis without sacrificing protein activity. To debottleneck sanguinarine biosynthesis, we identify two reticuline oxidases and facilitated functional expression of flavoproteins and cytochrome P450 enzymes via protein molecular engineering. After comprehensive metabolic engineering, we report the production of sanguinarine at a titer of 448.64 mg L-1. Additionally, our engineered strain enables the biosynthesis of fluorinated sanguinarine, showcasing the biotransformation of halogenated derivatives through more than 15 biocatalytic steps. This work serves as a blueprint for utilizing yeast as a scalable platform for biomanufacturing diverse benzylisoquinoline alkaloids and derivatives.
Collapse
Affiliation(s)
- Yuanwei Gou
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Dongfang Li
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Minghui Zhao
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Mengxin Li
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Jiaojiao Zhang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Yilian Zhou
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Feng Xiao
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Gaofei Liu
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Haote Ding
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Chenfan Sun
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Cuifang Ye
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Chang Dong
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Jucan Gao
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Di Gao
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Zehua Bao
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Lei Huang
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China
| | - Zhinan Xu
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China
| | - Jiazhang Lian
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou, China.
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou, China.
| |
Collapse
|
4
|
Joshi J, Hanson AD. A pilot oral history of plant synthetic biology. PLANT PHYSIOLOGY 2024; 195:36-47. [PMID: 38163646 PMCID: PMC11060686 DOI: 10.1093/plphys/kiad585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 09/15/2023] [Indexed: 01/03/2024]
Abstract
The whole field of synthetic biology (SynBio) is only about 20 years old, and plant SynBio is younger still. Nevertheless, within that short time, SynBio in general has drawn more scientific, philosophical, government, and private-sector interest than anything in biology since the recombinant DNA revolution. Plant SynBio, in particular, is now drawing more and more interest in relation to plants' potential to help solve planetary problems such as carbon capture and storage and replacing fossil fuels and feedstocks. As plant SynBio is so young and so fast-developing, we felt it was too soon to try to analyze its history. Instead, we set out to capture the essence of plant SynBio's origins and early development through interviews with 8 of the field's founders, representing 5 countries and 3 continents. We then distilled these founders' personal recollections and reflections into this review, centering the narrative on timelines for pivotal events, articles, funding programs, and quoting from interviews. We have archived the interview recordings and documented timeline entries. This work provides a resource for future historical scholarship.
Collapse
Affiliation(s)
- Jaya Joshi
- Department of Wood Science, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
| | - Andrew D Hanson
- Horticultural Sciences Department, University of Florida, 2550 Hull Road, Gainesville, FL 32611, USA
| |
Collapse
|
5
|
Orsi E, Schada von Borzyskowski L, Noack S, Nikel PI, Lindner SN. Automated in vivo enzyme engineering accelerates biocatalyst optimization. Nat Commun 2024; 15:3447. [PMID: 38658554 PMCID: PMC11043082 DOI: 10.1038/s41467-024-46574-4] [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: 12/21/2023] [Accepted: 03/04/2024] [Indexed: 04/26/2024] Open
Abstract
Achieving cost-competitive bio-based processes requires development of stable and selective biocatalysts. Their realization through in vitro enzyme characterization and engineering is mostly low throughput and labor-intensive. Therefore, strategies for increasing throughput while diminishing manual labor are gaining momentum, such as in vivo screening and evolution campaigns. Computational tools like machine learning further support enzyme engineering efforts by widening the explorable design space. Here, we propose an integrated solution to enzyme engineering challenges whereby ML-guided, automated workflows (including library generation, implementation of hypermutation systems, adapted laboratory evolution, and in vivo growth-coupled selection) could be realized to accelerate pipelines towards superior biocatalysts.
Collapse
Affiliation(s)
- Enrico Orsi
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kongens Lyngby, Denmark
| | | | - Stephan Noack
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich, 52425, Jülich, Germany
| | - Pablo I Nikel
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800, Kongens Lyngby, Denmark
| | - Steffen N Lindner
- Max Planck Institute of Molecular Plant Physiology, 14476, Potsdam-Golm, Germany.
- Department of Biochemistry, Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität, 10117, Berlin, Germany.
| |
Collapse
|
6
|
Wu D, Xu F, Xu Y, Huang M, Li Z, Chu J. Towards a hybrid model-driven platform based on flux balance analysis and a machine learning pipeline for biosystem design. Synth Syst Biotechnol 2024; 9:33-42. [PMID: 38234412 PMCID: PMC10793177 DOI: 10.1016/j.synbio.2023.12.004] [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: 07/18/2023] [Revised: 12/22/2023] [Accepted: 12/22/2023] [Indexed: 01/19/2024] Open
Abstract
Metabolic modeling and machine learning (ML) are crucial components of the evolving next-generation tools in systems and synthetic biology, aiming to unravel the intricate relationship between genotype, phenotype, and the environment. Nonetheless, the comprehensive exploration of integrating these two frameworks, and fully harnessing the potential of fluxomic data, remains an unexplored territory. In this study, we present, rigorously evaluate, and compare ML-based techniques for data integration. The hybrid model revealed that the overexpression of six target genes and the knockout of seven target genes contribute to enhanced ethanol production. Specifically, we investigated the influence of succinate dehydrogenase (SDH) on ethanol biosynthesis in Saccharomyces cerevisiae through shake flask experiments. The findings indicate a noticeable increase in ethanol yield, ranging from 6 % to 10 %, in SDH subunit gene knockout strains compared to the wild-type strain. Moreover, in pursuit of a high-yielding strain for ethanol production, dual-gene deletion experiments were conducted targeting glycerol-3-phosphate dehydrogenase (GPD) and SDH. The results unequivocally demonstrate significant enhancements in ethanol production for the engineered strains Δsdh4Δgpd1, Δsdh5Δgpd1, Δsdh6Δgpd1, Δsdh4Δgpd2, Δsdh5Δgpd2, and Δsdh6Δgpd2, with improvements of 21.6 %, 27.9 %, and 22.7 %, respectively. Overall, the results highlighted that integrating mechanistic flux features substantially improves the prediction of gene knockout strains not accounted for in metabolic reconstructions. In addition, the finding in this study delivers valuable tools for comprehending and manipulating intricate phenotypes, thereby enhancing prediction accuracy and facilitating deeper insights into mechanistic aspects within the field of synthetic biology.
Collapse
Affiliation(s)
| | | | - Yaying Xu
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, People's Republic of China
| | - Mingzhi Huang
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, People's Republic of China
| | - Zhimin Li
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, People's Republic of China
| | - Ju Chu
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, 130 Meilong Road, Shanghai, 200237, People's Republic of China
| |
Collapse
|
7
|
Grob A, Enrico Bena C, Di Blasi R, Pessina D, Sood M, Yunyue Z, Bosia C, Isalan M, Ceroni F. Mammalian cell growth characterisation by a non-invasive plate reader assay. Nat Commun 2024; 15:57. [PMID: 38167870 PMCID: PMC10761699 DOI: 10.1038/s41467-023-44396-4] [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: 04/05/2023] [Accepted: 12/12/2023] [Indexed: 01/05/2024] Open
Abstract
Automated and non-invasive mammalian cell analysis is currently lagging behind due to a lack of methods suitable for a variety of cell lines and applications. Here, we report the development of a high throughput non-invasive method for tracking mammalian cell growth and performance based on plate reader measurements. We show the method to be suitable for both suspension and adhesion cell lines, and we demonstrate it can be adopted when cells are grown under different environmental conditions. We establish that the method is suitable to inform on effective drug treatments to be used depending on the cell line considered, and that it can support characterisation of engineered mammalian cells over time. This work provides the scientific community with an innovative approach to mammalian cell screening, also contributing to the current efforts towards high throughput and automated mammalian cell engineering.
Collapse
Affiliation(s)
- Alice Grob
- Department of Chemical Engineering, Imperial College London, London, UK
- Imperial College Centre for Synthetic Biology, Imperial College London, London, UK
| | - Chiara Enrico Bena
- Italian Institute for Genomic Medicine, Torino, Italy
- Université Paris-Saclay (INRAE), AgroParisTech, Micalis Institute, 78350, Jouy-en-Josas, France
| | - Roberto Di Blasi
- Department of Chemical Engineering, Imperial College London, London, UK
- Imperial College Centre for Synthetic Biology, Imperial College London, London, UK
| | - Daniele Pessina
- Department of Chemical Engineering, Imperial College London, London, UK
| | - Matthew Sood
- Department of Chemical Engineering, Imperial College London, London, UK
| | - Zhou Yunyue
- Department of Life Sciences, Imperial College London, London, United Kingdom
| | - Carla Bosia
- Italian Institute for Genomic Medicine, Torino, Italy.
- Department of Applied Science and Technology, Politecnico di Torino, Torino, Italy.
| | - Mark Isalan
- Imperial College Centre for Synthetic Biology, Imperial College London, London, UK.
- Department of Life Sciences, Imperial College London, London, United Kingdom.
| | - Francesca Ceroni
- Department of Chemical Engineering, Imperial College London, London, UK.
- Imperial College Centre for Synthetic Biology, Imperial College London, London, UK.
| |
Collapse
|
8
|
Stephenson A, Lastra L, Nguyen B, Chen YJ, Nivala J, Ceze L, Strauss K. Physical Laboratory Automation in Synthetic Biology. ACS Synth Biol 2023; 12:3156-3169. [PMID: 37935025 DOI: 10.1021/acssynbio.3c00345] [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: 11/09/2023]
Abstract
Synthetic Biology has overcome many of the early challenges facing the field and is entering a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches. The need for automation and standardization to enable reproducible, scalable, and translatable research has become increasingly accepted in recent years, and many of the hardware and software tools needed to address these challenges are now in place or under development. However, the lack of connectivity between DBTL modules and barriers to access and adoption remain significant challenges to realizing the full potential of lab automation. In this review, we characterize and classify the state of automation in synthetic biology with a focus on the physical automation of experimental workflows. Though fully autonomous scientific discovery is likely a long way off, impressive progress has been made toward automating critical elements of experimentation by combining intelligent hardware and software tools. It is worth questioning whether total automation that removes humans entirely from the loop should be the ultimate goal, and considerations for appropriate automation versus total automation are discussed in this light while emphasizing areas where further development is needed in both contexts.
Collapse
Affiliation(s)
- Ashley Stephenson
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
- Microsoft Research, Redmond, Washington 98052, United States
| | - Lauren Lastra
- Microsoft Research, Redmond, Washington 98052, United States
| | - Bichlien Nguyen
- Microsoft Research, Redmond, Washington 98052, United States
| | - Yuan-Jyue Chen
- Microsoft Research, Redmond, Washington 98052, United States
| | - Jeff Nivala
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Luis Ceze
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
| | - Karin Strauss
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States
- Microsoft Research, Redmond, Washington 98052, United States
| |
Collapse
|
9
|
Shaw WM, Khalil AS, Ellis T. A Multiplex MoClo Toolkit for Extensive and Flexible Engineering of Saccharomyces cerevisiae. ACS Synth Biol 2023; 12:3393-3405. [PMID: 37930278 PMCID: PMC10661031 DOI: 10.1021/acssynbio.3c00423] [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: 07/13/2023] [Revised: 09/06/2023] [Accepted: 09/11/2023] [Indexed: 11/07/2023]
Abstract
Synthetic biology toolkits are one of the core foundations on which the field has been built, facilitating and accelerating efforts to reprogram cells and organisms for diverse biotechnological applications. The yeast Saccharomyces cerevisiae, an important model and industrial organism, has benefited from a wide range of toolkits. In particular, the MoClo Yeast Toolkit (YTK) enables the fast and straightforward construction of multigene plasmids from a library of highly characterized parts for programming new cellular behavior in a more predictable manner. While YTK has cultivated a strong parts ecosystem and excels in plasmid construction, it is limited in the extent and flexibility with which it can create new strains of yeast. Here, we describe a new and improved toolkit, the Multiplex Yeast Toolkit (MYT), that extends the capabilities of YTK and addresses strain engineering limitations. MYT provides a set of new integration vectors and selectable markers usable across common laboratory strains, as well as additional assembly cassettes to increase the number of transcriptional units in multigene constructs, CRISPR-Cas9 tools for highly efficient multiplexed vector integration, and three orthogonal and inducible promoter systems for conditional programming of gene expression. With these tools, we provide yeast synthetic biologists with a powerful platform to take their engineering ambitions to exciting new levels.
Collapse
Affiliation(s)
- William M. Shaw
- Biological
Design Center, Boston University, Boston, Massachusetts 02215, United States
- Department
of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
- Department
of Bioengineering, Imperial College London, London SW7 2AZ, U.K.
- Imperial
College Centre for Synthetic Biology, Imperial
College London, London SW7 2AZ, U.K.
| | - Ahmad S. Khalil
- Biological
Design Center, Boston University, Boston, Massachusetts 02215, United States
- Department
of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
- Wyss
Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts 02215, United States
| | - Tom Ellis
- Department
of Bioengineering, Imperial College London, London SW7 2AZ, U.K.
- Imperial
College Centre for Synthetic Biology, Imperial
College London, London SW7 2AZ, U.K.
| |
Collapse
|
10
|
Foo JL, Kitano S, Susanto AV, Jin Z, Lin Y, Luo Z, Huang L, Liang Z, Mitchell LA, Yang K, Wong A, Cai Y, Cai J, Stracquadanio G, Bader JS, Boeke JD, Dai J, Chang MW. Establishing chromosomal design-build-test-learn through a synthetic chromosome and its combinatorial reconfiguration. CELL GENOMICS 2023; 3:100435. [PMID: 38020970 PMCID: PMC10667554 DOI: 10.1016/j.xgen.2023.100435] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 08/19/2023] [Accepted: 10/06/2023] [Indexed: 12/01/2023]
Abstract
Chromosome-level design-build-test-learn cycles (chrDBTLs) allow systematic combinatorial reconfiguration of chromosomes with ease. Here, we established chrDBTL with a redesigned synthetic Saccharomyces cerevisiae chromosome XV, synXV. We designed and built synXV to harbor strategically inserted features, modified elements, and synonymously recoded genes throughout the chromosome. Based on the recoded chromosome, we developed a method to enable chrDBTL: CRISPR-Cas9-mediated mitotic recombination with endoreduplication (CRIMiRE). CRIMiRE allowed the creation of customized wild-type/synthetic combinations, accelerating genotype-phenotype mapping and synthetic chromosome redesign. We also leveraged synXV as a "build-to-learn" model organism for translation studies by ribosome profiling. We conducted a locus-to-locus comparison of ribosome occupancy between synXV and the wild-type chromosome, providing insight into the effects of codon changes and redesigned features on translation dynamics in vivo. Overall, we established synXV as a versatile reconfigurable system that advances chrDBTL for understanding biological mechanisms and engineering strains.
Collapse
Affiliation(s)
- Jee Loon Foo
- NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, Singapore 117456, Singapore
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Wilmar-NUS Corporate Laboratory (WIL@NUS), National University of Singapore, Singapore 117599, Singapore
| | - Shohei Kitano
- NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, Singapore 117456, Singapore
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Wilmar-NUS Corporate Laboratory (WIL@NUS), National University of Singapore, Singapore 117599, Singapore
| | - Adelia Vicanatalita Susanto
- NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, Singapore 117456, Singapore
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Wilmar-NUS Corporate Laboratory (WIL@NUS), National University of Singapore, Singapore 117599, Singapore
| | - Zhu Jin
- NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, Singapore 117456, Singapore
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Wilmar-NUS Corporate Laboratory (WIL@NUS), National University of Singapore, Singapore 117599, Singapore
| | - Yicong Lin
- CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics and Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, 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
| | - Zhouqing Luo
- CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics and Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Linsen Huang
- CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics and Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, 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
| | - Zhenzhen Liang
- CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics and Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, 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
| | - Leslie A. Mitchell
- Institute for Systems Genetics, NYU Langone Health, New York, NY 10016, USA
| | - Kun Yang
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY 11201, USA
| | - Adison Wong
- NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, Singapore 117456, Singapore
- Singapore Institute of Technology, 10 Dover Drive, Singapore 138683, Singapore
| | - Yizhi Cai
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK
| | - Jitong Cai
- High-Throughput Biological Center and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Giovanni Stracquadanio
- High-Throughput Biological Center and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
- School of Biological Sciences, The University of Edinburgh, Edinburgh EH9 3BF, UK
| | - Joel S. Bader
- High-Throughput Biological Center and Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Jef D. Boeke
- Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY 10016, USA
- Institute for Systems Genetics, NYU Langone Health, New York, NY 10016, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY 11201, USA
| | - Junbiao Dai
- CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics and Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, 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
| | - Matthew Wook Chang
- NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, Singapore 117456, Singapore
- Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597, Singapore
- Wilmar-NUS Corporate Laboratory (WIL@NUS), National University of Singapore, Singapore 117599, Singapore
| |
Collapse
|
11
|
Dykstra CB, Pyne ME, Martin VJJ. CRAPS: Chromosomal-Repair-Assisted Pathway Shuffling in Yeast. ACS Synth Biol 2023; 12:2578-2587. [PMID: 37584634 DOI: 10.1021/acssynbio.3c00170] [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: 08/17/2023]
Abstract
A fundamental challenge of metabolic engineering involves assembling and screening vast combinations of orthologous enzymes across a multistep biochemical pathway. Current pathway assembly workflows involve combining genetic parts ex vivo and assembling one pathway configuration per tube or well. Here, we present CRAPS, Chromosomal-Repair-Assisted Pathway Shuffling, an in vivo pathway engineering technique that enables the self-assembly of one pathway configuration per cell. CRAPS leverages the yeast chromosomal repair pathway and utilizes a pool of inactive, chromosomally integrated orthologous gene variants corresponding to a target multistep pathway. Supplying gRNAs to the CRAPS host activates the expression of one gene variant per pathway step, resulting in a unique pathway configuration in each cell. We deployed CRAPS to build more than 1000 theoretical combinations of a four-step carotenoid biosynthesis network. Sampling the CRAPS pathway space yielded strains with distinct color phenotypes and carotenoid product profiles. We anticipate that CRAPS will expedite strain engineering campaigns by enabling the generation and sampling of vast biochemical spaces.
Collapse
Affiliation(s)
- Christien B Dykstra
- Department of Biology, Concordia University, Montréal, Quebec, Canada H4B 1R6
- Centre for Applied Synthetic Biology, Concordia University, Montréal, Quebec, Canada H4B 1R6
| | - Michael E Pyne
- Department of Biology, Concordia University, Montréal, Quebec, Canada H4B 1R6
- Centre for Applied Synthetic Biology, Concordia University, Montréal, Quebec, Canada H4B 1R6
| | - Vincent J J Martin
- Department of Biology, Concordia University, Montréal, Quebec, Canada H4B 1R6
- Centre for Applied Synthetic Biology, Concordia University, Montréal, Quebec, Canada H4B 1R6
| |
Collapse
|
12
|
Liu J, Hu Y, Gu W, Lan H, Zhang Z, Jiang L, Xu X. Research progress on the application of cell-free synthesis systems for enzymatic processes. Crit Rev Biotechnol 2023; 43:938-955. [PMID: 35994247 DOI: 10.1080/07388551.2022.2090314] [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: 10/13/2021] [Revised: 02/24/2022] [Accepted: 04/09/2022] [Indexed: 11/03/2022]
Abstract
Cell-free synthesis systems can complete the transcription and translation process in vitro to produce complex proteins that are difficult to be expressed in traditional cell-based systems. Such systems also can be used for the assembly of efficient localized multienzyme cascades to synthesize products that are toxic to cells. Cell-free synthesis systems provide a simpler and faster engineering solution than living cells, allowing unprecedented design freedom. This paper reviews the latest progress on the application of cell-free synthesis systems in the field of enzymatic catalysis, including cell-free protein synthesis and cell-free metabolic engineering. In cell-free protein synthesis: complex proteins, toxic proteins, membrane proteins, and artificial proteins containing non-natural amino acids can be easily synthesized by directly controlling the reaction conditions in the cell-free system. In cell-free metabolic engineering, the synthesis of desired products can be made more specific and efficient by designing metabolic pathways and screening biocatalysts based on purified enzymes or crude extracts. Through the combination of cell-free synthesis systems and emerging technologies, such as: synthetic biology, microfluidic control, cofactor regeneration, and artificial scaffolds, we will be able to build increasingly complex biomolecule systems. In the next few years, these technologies are expected to mature and reach industrialization, providing innovative platforms for a wide range of biotechnological applications.
Collapse
Affiliation(s)
- Jie Liu
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing, China
| | - Yongqi Hu
- School of Life Sciences, Nanjing Normal University, Nanjing, China
| | - Wanyi Gu
- School of Life Sciences, Nanjing Normal University, Nanjing, China
| | - Haiquan Lan
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing, China
| | - Zhidong Zhang
- Institute of Microbiology, Xinjiang Academy of Agricultural Sciences, Urumqi, China
| | - Ling Jiang
- College of Food Science and Light Industry, Nanjing Tech University, Nanjing, China
| | - Xian Xu
- School of Food Science and Pharmaceutical Engineering, Nanjing Normal University, Nanjing, China
| |
Collapse
|
13
|
Yu T, Boob AG, Singh N, Su Y, Zhao H. In vitro continuous protein evolution empowered by machine learning and automation. Cell Syst 2023; 14:633-644. [PMID: 37224814 DOI: 10.1016/j.cels.2023.04.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 11/19/2022] [Accepted: 04/20/2023] [Indexed: 05/26/2023]
Abstract
Directed evolution has become one of the most successful and powerful tools for protein engineering. However, the efforts required for designing, constructing, and screening a large library of variants can be laborious, time-consuming, and costly. With the recent advent of machine learning (ML) in the directed evolution of proteins, researchers can now evaluate variants in silico and guide a more efficient directed evolution campaign. Furthermore, recent advancements in laboratory automation have enabled the rapid execution of long, complex experiments for high-throughput data acquisition in both industrial and academic settings, thus providing the means to collect a large quantity of data required to develop ML models for protein engineering. In this perspective, we propose a closed-loop in vitro continuous protein evolution framework that leverages the best of both worlds, ML and automation, and provide a brief overview of the recent developments in the field.
Collapse
Affiliation(s)
- Tianhao Yu
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, Urbana, IL, USA; NSF Molecule Maker Lab Institute, Urbana, IL, USA
| | - Aashutosh Girish Boob
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, Urbana, IL, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Nilmani Singh
- DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Yufeng Su
- NSF Molecule Maker Lab Institute, Urbana, IL, USA; Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
| | - Huimin Zhao
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA; Carl R. Woese Institute for Genomic Biology, Urbana, IL, USA; NSF Molecule Maker Lab Institute, Urbana, IL, USA; DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.
| |
Collapse
|
14
|
Zhang XE, Liu C, Dai J, Yuan Y, Gao C, Feng Y, Wu B, Wei P, You C, Wang X, Si T. Enabling technology and core theory of synthetic biology. SCIENCE CHINA. LIFE SCIENCES 2023; 66:1742-1785. [PMID: 36753021 PMCID: PMC9907219 DOI: 10.1007/s11427-022-2214-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/04/2022] [Indexed: 02/09/2023]
Abstract
Synthetic biology provides a new paradigm for life science research ("build to learn") and opens the future journey of biotechnology ("build to use"). Here, we discuss advances of various principles and technologies in the mainstream of the enabling technology of synthetic biology, including synthesis and assembly of a genome, DNA storage, gene editing, molecular evolution and de novo design of function proteins, cell and gene circuit engineering, cell-free synthetic biology, artificial intelligence (AI)-aided synthetic biology, as well as biofoundries. We also introduce the concept of quantitative synthetic biology, which is guiding synthetic biology towards increased accuracy and predictability or the real rational design. We conclude that synthetic biology will establish its disciplinary system with the iterative development of enabling technologies and the maturity of the core theory.
Collapse
Affiliation(s)
- Xian-En Zhang
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Chenli Liu
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Junbiao Dai
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Yingjin Yuan
- Frontiers 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.
| | - Caixia Gao
- State Key Laboratory of Plant Cell and Chromosome Engineering, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Yan Feng
- State Key Laboratory of Microbial Metabolism, Shanghai Jiao Tong University, Shanghai, 200240, China.
| | - Bian Wu
- State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Ping Wei
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| | - Chun You
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, 300308, China.
| | - Xiaowo Wang
- Ministry of Education Key Laboratory of Bioinformatics; Center for Synthetic and Systems Biology; Bioinformatics Division, Beijing National Research Center for Information Science and Technology; Department of Automation, Tsinghua University, Beijing, 100084, China.
| | - Tong Si
- Faculty of Synthetic Biology, Shenzhen Institute of Advanced Technology, Shenzhen, 518055, China.
- Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
| |
Collapse
|
15
|
Gurdo N, Volke DC, McCloskey D, Nikel PI. Automating the design-build-test-learn cycle towards next-generation bacterial cell factories. N Biotechnol 2023; 74:1-15. [PMID: 36736693 DOI: 10.1016/j.nbt.2023.01.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 01/15/2023] [Accepted: 01/22/2023] [Indexed: 02/04/2023]
Abstract
Automation is playing an increasingly significant role in synthetic biology. Groundbreaking technologies, developed over the past 20 years, have enormously accelerated the construction of efficient microbial cell factories. Integrating state-of-the-art tools (e.g. for genome engineering and analytical techniques) into the design-build-test-learn cycle (DBTLc) will shift the metabolic engineering paradigm from an almost artisanal labor towards a fully automated workflow. Here, we provide a perspective on how a fully automated DBTLc could be harnessed to construct the next-generation bacterial cell factories in a fast, high-throughput fashion. Innovative toolsets and approaches that pushed the boundaries in each segment of the cycle are reviewed to this end. We also present the most recent efforts on automation of the DBTLc, which heralds a fully autonomous pipeline for synthetic biology in the near future.
Collapse
Affiliation(s)
- Nicolás Gurdo
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens, Lyngby, Denmark
| | - Daniel C Volke
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens, Lyngby, Denmark
| | - Douglas McCloskey
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens, Lyngby, Denmark
| | - Pablo Iván Nikel
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2800 Kongens, Lyngby, Denmark.
| |
Collapse
|
16
|
Hu R, Fu L, Chen Y, Chen J, Qiao Y, Si T. Protein engineering via Bayesian optimization-guided evolutionary algorithm and robotic experiments. Brief Bioinform 2023; 24:6958505. [PMID: 36562723 DOI: 10.1093/bib/bbac570] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Revised: 11/14/2022] [Accepted: 11/22/2022] [Indexed: 12/24/2022] Open
Abstract
Directed protein evolution applies repeated rounds of genetic mutagenesis and phenotypic screening and is often limited by experimental throughput. Through in silico prioritization of mutant sequences, machine learning has been applied to reduce wet lab burden to a level practical for human researchers. On the other hand, robotics permits large batches and rapid iterations for protein engineering cycles, but such capacities have not been well exploited in existing machine learning-assisted directed evolution approaches. Here, we report a scalable and batched method, Bayesian Optimization-guided EVOlutionary (BO-EVO) algorithm, to guide multiple rounds of robotic experiments to explore protein fitness landscapes of combinatorial mutagenesis libraries. We first examined various design specifications based on an empirical landscape of protein G domain B1. Then, BO-EVO was successfully generalized to another empirical landscape of an Escherichia coli kinase PhoQ, as well as simulated NK landscapes with up to moderate epistasis. This approach was then applied to guide robotic library creation and screening to engineer enzyme specificity of RhlA, a key biosynthetic enzyme for rhamnolipid biosurfactants. A 4.8-fold improvement in producing a target rhamnolipid congener was achieved after examining less than 1% of all possible mutants after four iterations. Overall, BO-EVO proves to be an efficient and general approach to guide combinatorial protein engineering without prior knowledge.
Collapse
Affiliation(s)
- Ruyun Hu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Lihao Fu
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen 518055, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yongcan Chen
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen 518055, China
| | - Junyu Chen
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yu Qiao
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Tong Si
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,CAS Key Laboratory for Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen 518055, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
17
|
Daboussi F, Lindley ND. Challenges to Ensure a Better Translation of Metabolic Engineering for Industrial Applications. Methods Mol Biol 2023; 2553:1-20. [PMID: 36227536 DOI: 10.1007/978-1-0716-2617-7_1] [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: 06/16/2023]
Abstract
Metabolic engineering has evolved towards creating cell factories with increasingly complex pathways as economic criteria push biotechnology to higher value products to provide a sustainable source of speciality chemicals. Optimization of such pathways often requires high combinatory exploration of best pathway balance, and this has led to increasing use of high-throughput automated strain construction platforms or novel optimization techniques. In addition, the low catalytic efficiency of such pathways has shifted emphasis from gene expression strategies towards novel protein engineering to increase specific activity of the enzymes involved so as to limit the metabolic burden associated with excessively high pressure on ribosomal machinery when using massive overexpression systems. Metabolic burden is now generally recognized as a major hurdle to be overcome with consequences on genetic stability but also on the intensified performance needed industrially to attain the economic targets for successful product launch. Increasing awareness of the need to integrate novel genetic information into specific sites within the genome which not only enhance genetic stability (safe harbors) but also enable maximum expression profiles has led to genome-wide assessment of best integration sites, and bioinformatics will facilitate the identification of most probable landing pads within the genome.To facilitate the transfer of novel biotechnological potential to industrial-scale production, more attention, however, has to be paid to engineering metabolic fitness adapted to the specific stress conditions inherent to large-scale fermentation and the inevitable heterogeneity that will occur due to mass transfer limitations and the resulting deviation away from ideal conditions as seen in laboratory-scale validation of the engineered cells. To ensure smooth and rapid transfer of novel cell lines to industry with an accelerated passage through scale-up, better coordination is required form the onset between the biochemical engineers involved in process technology and the genetic engineers building the new strain so as to have an overall strategy able to maximize innovation at all levels. This should be one of our key objectives when building fermentation-friendly chassis organisms.
Collapse
Affiliation(s)
- Fayza Daboussi
- Toulouse White Biotechnology, Toulouse cedex 4, France
- Toulouse Biotechnology Institute, Toulouse cedex 4, France
| | - Nic D Lindley
- Toulouse White Biotechnology, Toulouse cedex 4, France.
- Toulouse Biotechnology Institute, Toulouse cedex 4, France.
- ASTAR Singapore Institute of Food and Biotechnology Innovation (SIFBI), Singapore, Singapore.
| |
Collapse
|
18
|
Volk MJ, Tran VG, Tan SI, Mishra S, Fatma Z, Boob A, Li H, Xue P, Martin TA, Zhao H. Metabolic Engineering: Methodologies and Applications. Chem Rev 2022; 123:5521-5570. [PMID: 36584306 DOI: 10.1021/acs.chemrev.2c00403] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.
Collapse
Affiliation(s)
- Michael J Volk
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Vinh G Tran
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Shih-I Tan
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Chemical Engineering, National Cheng Kung University, Tainan 70101, Taiwan
| | - Shekhar Mishra
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Zia Fatma
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Aashutosh Boob
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Hongxiang Li
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Pu Xue
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Teresa A Martin
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Huimin Zhao
- Department of Chemical and Biomolecular Engineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,DOE Center for Advanced Bioenergy and Bioproducts Innovation, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Chemistry, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| |
Collapse
|
19
|
Guo E, Fu L, Fang X, Xie W, Li K, Zhang Z, Hong Z, Si T. Robotic Construction and Screening of Lanthipeptide Variant Libraries in Escherichia coli. ACS Synth Biol 2022; 11:3900-3911. [PMID: 36379012 DOI: 10.1021/acssynbio.2c00344] [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: 11/16/2022]
Abstract
Lanthipeptides are a major class of ribosomally synthesized and post-translationally modified peptides (RiPPs) characterized by thioether cross-links called lanthionine (Lan) and methyllanthionine (MeLan). Previously, we developed a method to produce mature lanthipeptides in recombinant Escherichia coli, but manual steps hinder large-scale analogue screening. Here we devised an automated workflow for creating and screening variant libraries of haloduracin, a two-component class II lanthipeptide. An integrated work cell of a synthetic biology foundry was programmed to robotically execute DNA library construction, host transformation, peptide production, mass spectrometry analysis, and activity screening by agar diffusion assay. For recombinantly produced Halα peptides, the sequence-activity relationship of 380 single-residue variants and >1300 triple-residue combinatorial variants were rapidly analyzed in microplates within weeks. The peptide expression levels in E. coli were also visualized via robotic creation and analysis of GFP-lanthipeptide fusions for select peptide mutants. Following shake-flask fermentation and purification, one Halα mutant was confirmed with enhanced specific antimicrobial activity relative to the wild-type peptide. Overall, this approach may be generally applicable for the high-throughput characterization and engineering of RiPP natural products.
Collapse
Affiliation(s)
- Erpeng Guo
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,BGI-Shenzhen, Shenzhen 518083, China
| | - Lihao Fu
- CAS Key Laboratory of Quantitative Engineering 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 100049, China
| | - Xiaoting Fang
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Wenhao Xie
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Keyi Li
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhiyu Zhang
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Zhilai Hong
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,BGI-Shenzhen, Shenzhen 518083, China
| | - Tong Si
- CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,BGI-Shenzhen, Shenzhen 518083, China.,University of Chinese Academy of Sciences, Beijing 100049, China.,Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Shenzhen 518055, China
| |
Collapse
|
20
|
Li S, An J, Li Y, Zhu X, Zhao D, Wang L, Sun Y, Yang Y, Bi C, Zhang X, Wang M. Automated high-throughput genome editing platform with an AI learning in situ prediction model. Nat Commun 2022; 13:7386. [PMID: 36450740 PMCID: PMC9712529 DOI: 10.1038/s41467-022-35056-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 11/17/2022] [Indexed: 12/05/2022] Open
Abstract
A great number of cell disease models with pathogenic SNVs are needed for the development of genome editing based therapeutics or broadly basic scientific research. However, the generation of traditional cell disease models is heavily dependent on large-scale manual operations, which is not only time-consuming, but also costly and error-prone. In this study, we devise an automated high-throughput platform, through which thousands of samples are automatically edited within a week, providing edited cells with high efficiency. Based on the large in situ genome editing data obtained by the automatic high-throughput platform, we develop a Chromatin Accessibility Enabled Learning Model (CAELM) to predict the performance of cytosine base editors (CBEs), both chromatin accessibility and the context-sequence are utilized to build the model, which accurately predicts the result of in situ base editing. This work is expected to accelerate the development of BE-based genetic therapies.
Collapse
Affiliation(s)
- Siwei Li
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Jingjing An
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Yaqiu Li
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Xiagu Zhu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- College of Biotechnology, Tianjin University of Science and Technology, Tianjin, China
| | - Dongdong Zhao
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Lixian Wang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Yonghui Sun
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yuanzhao Yang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- College of Biotechnology, Tianjin University of Science and Technology, Tianjin, China
| | - Changhao Bi
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
| | - Xueli Zhang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
| | - Meng Wang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, China.
- School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China.
| |
Collapse
|
21
|
Wang H, He Y, Jian M, Fu X, Cheng Y, He Y, Fang J, Li L, Zhang D. Breaking the Bottleneck in Anticancer Drug Development: Efficient Utilization of Synthetic Biology. Molecules 2022; 27:7480. [PMID: 36364307 PMCID: PMC9656990 DOI: 10.3390/molecules27217480] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Revised: 10/20/2022] [Accepted: 10/24/2022] [Indexed: 08/13/2024] Open
Abstract
Natural products have multifarious bioactivities against bacteria, fungi, viruses, cancers and other diseases due to their diverse structures. Nearly 65% of anticancer drugs are natural products or their derivatives. Thus, natural products play significant roles in clinical cancer therapy. With the development of biosynthetic technologies, an increasing number of natural products have been discovered and developed as candidates for clinical cancer therapy. Here, we aim to summarize the anticancer natural products approved from 1950 to 2021 and discuss their molecular mechanisms. We also describe the available synthetic biology tools and highlight their applications in the development of natural products.
Collapse
Affiliation(s)
- Haibo Wang
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Yu He
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Meiling Jian
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Xingang Fu
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Yuheng Cheng
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Yujia He
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Jun Fang
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Lin Li
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Dan Zhang
- Department of Laboratory Medicine, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
- Sichuan Provincial Key Laboratory for Human Disease Gene Study, Sichuan Provincial People’s Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu 610072, China
| |
Collapse
|
22
|
Ko SC, Cho M, Lee HJ, Woo HM. Biofoundry Palette: Planning-Assistant Software for Liquid Handler-Based Experimentation and Operation in the Biofoundry Workflow. ACS Synth Biol 2022; 11:3538-3543. [PMID: 36173735 DOI: 10.1021/acssynbio.2c00390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Lab automation has facilitated synthetic biology applications in an automated workflow, and biofoundry facilities have enabled automated high-throughput experiments of gene cloning and genome engineering to be conducted following a precise experimental design and protocol. However, before-experiment procedures in biofoundry applications have been underdetermined. We aimed to develop a Python-based planning-assistant software, namely Biofoundry Palette, for liquid handler-based experimentation and operation in the biofoundry workflow. Depending on the synthetic biology project, variable information and content information may vary; the Biofoundry Palette provides precise information for the before-experiment units for each process module in the biofoundry workflow. As a demonstration, more than 200 unique information sets, generated by Biofoundry Palette, were used in automated gene cloning or pathway construction. The information on planning and management can potentially help the operator faithfully execute the biofoundry workflow after securing the before-experiment unit, thereby lowering the risk of human errors and performing successful biofoundry operations for synthetic biology applications.
Collapse
Affiliation(s)
- Sung Cheon Ko
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea.,Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Mingu Cho
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Hyun Jeong Lee
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea.,Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Han Min Woo
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea.,Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| |
Collapse
|
23
|
Yilmaz S, Nyerges A, van der Oost J, Church GM, Claassens NJ. Towards next-generation cell factories by rational genome-scale engineering. Nat Catal 2022. [DOI: 10.1038/s41929-022-00836-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
|
24
|
Romantseva E, Alperovich N, Ross D, Lund SP, Strychalski EA. Effects of DNA template preparation on variability in cell-free protein production. Synth Biol (Oxf) 2022; 7:ysac015. [PMID: 36046152 PMCID: PMC9425043 DOI: 10.1093/synbio/ysac015] [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] [Received: 01/13/2022] [Revised: 07/01/2022] [Accepted: 08/12/2022] [Indexed: 08/08/2023] Open
Abstract
DNA templates for protein production remain an unexplored source of variability in the performance of cell-free expression (CFE) systems. To characterize this variability, we investigated the effects of two common DNA extraction methodologies, a postprocessing step and manual versus automated preparation on protein production using CFE. We assess the concentration of the DNA template, the quality of the DNA template in terms of physical damage and the quality of the DNA solution in terms of purity resulting from eight DNA preparation workflows. We measure the variance in protein titer and rate of protein production in CFE reactions associated with the biological replicate of the DNA template, the technical replicate DNA solution prepared with the same workflow and the measurement replicate of nominally identical CFE reactions. We offer practical guidance for preparing and characterizing DNA templates to achieve acceptable variability in CFE performance.
Collapse
Affiliation(s)
| | - Nina Alperovich
- National Institute of Standards and Technology, Gaithersburg, MD USA
| | - David Ross
- National Institute of Standards and Technology, Gaithersburg, MD USA
| | - Steven P Lund
- National Institute of Standards and Technology, Gaithersburg, MD USA
| | | |
Collapse
|
25
|
Malcı K, Watts E, Roberts TM, Auxillos JY, Nowrouzi B, Boll HO, Nascimento CZSD, Andreou A, Vegh P, Donovan S, Fragkoudis R, Panke S, Wallace E, Elfick A, Rios-Solis L. Standardization of Synthetic Biology Tools and Assembly Methods for Saccharomyces cerevisiae and Emerging Yeast Species. ACS Synth Biol 2022; 11:2527-2547. [PMID: 35939789 PMCID: PMC9396660 DOI: 10.1021/acssynbio.1c00442] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
![]()
As redesigning organisms using engineering principles
is one of
the purposes of synthetic biology (SynBio), the standardization of
experimental methods and DNA parts is becoming increasingly a necessity.
The synthetic biology community focusing on the engineering of Saccharomyces cerevisiae has been in the foreground in this
area, conceiving several well-characterized SynBio toolkits widely
adopted by the community. In this review, the molecular methods and
toolkits developed for S. cerevisiae are discussed
in terms of their contributions to the required standardization efforts.
In addition, the toolkits designed for emerging nonconventional yeast
species including Yarrowia lipolytica, Komagataella
phaffii, and Kluyveromyces marxianus are
also reviewed. Without a doubt, the characterized DNA parts combined
with the standardized assembly strategies highlighted in these toolkits
have greatly contributed to the rapid development of many metabolic
engineering and diagnostics applications among others. Despite the
growing capacity in deploying synthetic biology for common yeast genome
engineering works, the yeast community has a long journey to go to
exploit it in more sophisticated and delicate applications like bioautomation.
Collapse
Affiliation(s)
- Koray Malcı
- Institute for Bioengineering, School of Engineering, University of Edinburgh, Kings Buildings, EH9 3BF Edinburgh, United Kingdom.,Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Kings Buildings, EH9 3BD Edinburgh, United Kingdom
| | - Emma Watts
- School of Biological Sciences, University of Edinburgh, Kings Buildings, EH9 3JW Edinburgh, United Kingdom
| | | | - Jamie Yam Auxillos
- Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Kings Buildings, EH9 3BD Edinburgh, United Kingdom.,Institute of Cell Biology, School of Biological Sciences, University of Edinburgh, Kings Buildings, EH9 3FF Edinburgh, United Kingdom
| | - Behnaz Nowrouzi
- Institute for Bioengineering, School of Engineering, University of Edinburgh, Kings Buildings, EH9 3BF Edinburgh, United Kingdom.,Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Kings Buildings, EH9 3BD Edinburgh, United Kingdom
| | - Heloísa Oss Boll
- Department of Genetics and Morphology, Institute of Biological Sciences, University of Brasília, Brasília, Federal District 70910-900, Brazil
| | | | - Andreas Andreou
- Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Kings Buildings, EH9 3BD Edinburgh, United Kingdom
| | - Peter Vegh
- Edinburgh Genome Foundry, University of Edinburgh, Kings Buildings, Edinburgh EH9 3BF, United Kingdom
| | - Sophie Donovan
- Edinburgh Genome Foundry, University of Edinburgh, Kings Buildings, Edinburgh EH9 3BF, United Kingdom
| | - Rennos Fragkoudis
- Edinburgh Genome Foundry, University of Edinburgh, Kings Buildings, Edinburgh EH9 3BF, United Kingdom
| | - Sven Panke
- Department of Biosystems Science and Engineering, ETH Zürich, 4058 Basel, Switzerland
| | - Edward Wallace
- Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Kings Buildings, EH9 3BD Edinburgh, United Kingdom.,Institute of Cell Biology, School of Biological Sciences, University of Edinburgh, Kings Buildings, EH9 3FF Edinburgh, United Kingdom
| | - Alistair Elfick
- Institute for Bioengineering, School of Engineering, University of Edinburgh, Kings Buildings, EH9 3BF Edinburgh, United Kingdom.,Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Kings Buildings, EH9 3BD Edinburgh, United Kingdom
| | - Leonardo Rios-Solis
- Institute for Bioengineering, School of Engineering, University of Edinburgh, Kings Buildings, EH9 3BF Edinburgh, United Kingdom.,Centre for Synthetic and Systems Biology (SynthSys), University of Edinburgh, Kings Buildings, EH9 3BD Edinburgh, United Kingdom.,School of Natural and Environmental Sciences, Newcastle University, Newcastle upon Tyne NE1 7RU, United Kingdom
| |
Collapse
|
26
|
Zhang S, Zhu J, Fan S, Xie W, Yang Z, Si T. Directed evolution of a cyclodipeptide synthase with new activities via label-free mass spectrometric screening. Chem Sci 2022; 13:7581-7586. [PMID: 35872818 PMCID: PMC9241961 DOI: 10.1039/d2sc01637k] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2022] [Accepted: 06/01/2022] [Indexed: 12/12/2022] Open
Abstract
Directed evolution is a powerful approach to engineer enzymes via iterative creation and screening of variant libraries. However, assay development for high-throughput mutant screening remains challenging, particularly for new catalytic activities. Mass spectrometry (MS) analysis is label-free and well suited for untargeted discovery of new enzyme products but is traditionally limited by slow speed. Here we report an automated workflow for directed evolution of new enzymatic activities via high-throughput library creation and label-free MS screening. For a proof of concept, we chose to engineer a cyclodipeptide synthase (CDPS) that synthesizes diketopiperazine (DKP) compounds with therapeutic potential. In recombinant Escherichia coli, site-saturation mutagenesis (SSM) and error-prone PCR (epPCR) libraries expressing CDPS mutants were automatically created and cultivated on an integrated work cell. Culture supernatants were then robotically processed for matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) MS analysis at a rate of 5 s per sample. The resulting mass spectral data were processed via custom computational algorithms, which performed a multivariant analysis of 108 theoretical mass-to-charge (m/z) values of 190 possible DKP molecules within a mass window of 115–373 Da. An F186L CDPS mutant was isolated to produce cyclo(l-Phe–l-Val), which is undetectable in the product profile of the wild-type enzyme. This robotic, label-free MS screening approach may be generally applicable to engineering other enzymes with new activities in high throughput. A robotic workflow for directed evolution of new enzymatic activities via high-throughput library creation and label-free MS screening.![]()
Collapse
Affiliation(s)
- Songya Zhang
- CAS Key Lib Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 China
| | - Jing Zhu
- CAS Key Lib Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 China
| | - Shuai Fan
- The Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 1000050 China
| | - Wenhao Xie
- CAS Key Lib Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 China
| | - Zhaoyong Yang
- The Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences and Peking Union Medical College Beijing 1000050 China
| | - Tong Si
- CAS Key Lib Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences Shenzhen 518055 China
| |
Collapse
|
27
|
Balagurunathan B, Ling H, Choi WJ, Chang MW. Potential use of microbial engineering in single-cell protein production. Curr Opin Biotechnol 2022; 76:102740. [PMID: 35660478 DOI: 10.1016/j.copbio.2022.102740] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/08/2022] [Accepted: 04/28/2022] [Indexed: 12/16/2022]
Abstract
Single-cell proteins (SCPs) have been widely used in human food and animal feed applications, still, there are challenges in their production and commercialization. Recently, advances in microbial synthetic biology, genomic engineering, and biofoundry technologies have offered capabilities to effectively and rapidly engineer microorganisms for improving the productivity, nutritional, and functional quality of SCPs. In this review, we discuss various synthetic biology, genomic engineering, and biofoundry tools that can be harnessed for SCP production and genetic modification. We also describe the current and potential applications of genetic modification in producing intermediate feedstocks, as well as biomass-based and multifunctional SCPs. Finally, we discuss the technological and policy-control related challenges encountered when deploying genetic modification in SCP production for animal feed and human food applications.
Collapse
Affiliation(s)
- Balaji Balagurunathan
- Singapore Institute of Food and Biotechnology Innovation, Agency for Science, Technology and Research (A⁎STAR) 1, Pesek Road, Jurong Island, 627833, Singapore.
| | - Hua Ling
- NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore; Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; Wilmar-NUS Corporate Laboratory (WIL@NUS), National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore.
| | - Won Jae Choi
- Singapore Institute of Food and Biotechnology Innovation, Agency for Science, Technology and Research (A⁎STAR) 1, Pesek Road, Jurong Island, 627833, Singapore; NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore; Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; Institute of Chemical and Engineering Sciences, Agency for Science, Technology and Research in Singapore (A⁎STAR), 1 Pesek Road, Jurong Island, Singapore 627833, Singapore; Singapore Institute of Technology, 10 Dover Dr, Singapore 138683, Singapore
| | - Matthew Wook Chang
- NUS Synthetic Biology for Clinical and Technological Innovation (SynCTI), National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore; Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, 28 Medical Drive, Singapore 117456, Singapore; Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore; Wilmar-NUS Corporate Laboratory (WIL@NUS), National University of Singapore, 14 Medical Drive, Singapore 117599, Singapore.
| |
Collapse
|
28
|
Yang Y, Mao Y, Wang R, Li H, Liu Y, Cheng H, Shi Z, Wang Y, Wang M, Zheng P, Liao X, Ma H. AutoESD: a web tool for automatic editing sequence design for genetic manipulation of microorganisms. Nucleic Acids Res 2022; 50:W75-W82. [PMID: 35639727 PMCID: PMC9252779 DOI: 10.1093/nar/gkac417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 04/20/2022] [Accepted: 05/09/2022] [Indexed: 11/30/2022] Open
Abstract
Advances in genetic manipulation and genome engineering techniques have enabled on-demand targeted deletion, insertion, and substitution of DNA sequences. One important step in these techniques is the design of editing sequences (e.g. primers, homologous arms) to precisely target and manipulate DNA sequences of interest. Experimental biologists can employ multiple tools in a stepwise manner to assist editing sequence design (ESD), but this requires various software involving non-standardized data exchange and input/output formats. Moreover, necessary quality control steps might be overlooked by non-expert users. This approach is low-throughput and can be error-prone, which illustrates the need for an automated ESD system. In this paper, we introduce AutoESD (https://autoesd.biodesign.ac.cn/), which designs editing sequences for all steps of genetic manipulation of many common homologous-recombination techniques based on screening-markers. Notably, multiple types of manipulations for different targets (CDS or intergenic region) can be processed in one submission. Moreover, AutoESD has an entirely cloud-based serverless architecture, offering high reliability, robustness and scalability which is capable of parallelly processing hundreds of design tasks each having thousands of targets in minutes. To our knowledge, AutoESD is the first cloud platform enabling precise, automated, and high-throughput ESD across species, at any genomic locus for all manipulation types.
Collapse
Affiliation(s)
- Yi Yang
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yufeng Mao
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Ruoyu Wang
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Haoran Li
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Ye Liu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Haijiao Cheng
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Zhenkun Shi
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Yu Wang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Meng Wang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Ping Zheng
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Xiaoping Liao
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China
| | - Hongwu Ma
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
29
|
Gurdo N, Volke DC, Nikel PI. Merging automation and fundamental discovery into the design–build–test–learn cycle of nontraditional microbes. Trends Biotechnol 2022; 40:1148-1159. [DOI: 10.1016/j.tibtech.2022.03.004] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 03/12/2022] [Accepted: 03/16/2022] [Indexed: 12/29/2022]
|
30
|
Kang DH, Ko SC, Heo YB, Lee HJ, Woo HM. RoboMoClo: A Robotics-Assisted Modular Cloning Framework for Multiple Gene Assembly in Biofoundry. ACS Synth Biol 2022; 11:1336-1348. [PMID: 35167276 DOI: 10.1021/acssynbio.1c00628] [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: 11/30/2022]
Abstract
Efficient and versatile DNA assembly frameworks have had an impact on promoting synthetic biology to build complex biological systems. To accelerate system development, laboratory automation (or biofoundry) provides an opportunity to construct organisms and DNA assemblies via computer-aided design. However, a modular cloning (MoClo) system for multiple DNA assemblies limits the biofoundry workflow in terms of simplicity and feasibility by preparing the number of cloning materials such as destination vectors prior to the automation process. Herein, we propose robot-assisted MoClo (RoboMoClo) to accelerate a synthetic biology project with multiple gene expressions at the biofoundry. The architecture of the RoboMoClo framework provides a hybrid strategy of hierarchical gene assembly and iterative gene assembly, and fewer destination vectors compared with other MoClo systems. An industrial bacterium, Corynebacterium glutamicum, was used as a model host for RoboMoClo. After building a biopart library (promoter and terminator; level 0) and evaluating its features (level 1), various transcriptional directions in multiple gene assemblies (level 2) were studied using the RoboMoClo vectors. Among the constructs, the convergent construct exhibited potential transcriptional interference through the collision of RNA polymerases. To study design of experiment-guided lycopene biosynthesis in C. glutamicum (levels 1, 2, and 3), the biofoundry-assisted multiple gene assembly was demonstrated as a proof-of-concept by constructing various sub-pathway units (level 2) and pathway units (level 3) for C. glutamicum. The RoboMoClo framework provides an improved MoClo toolkit for laboratory automation in a synthetic biology application.
Collapse
Affiliation(s)
- Dong Hun Kang
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
- Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Sung Cheon Ko
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
- Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Yu Been Heo
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
- Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Hyun Jeong Lee
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
- Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| | - Han Min Woo
- Department of Food Science and Biotechnology, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
- Biofoundry Research Center, Sungkyunkwan University (SKKU), 2066 Seobu-ro, Jangan-gu, Suwon 16419, Republic of Korea
| |
Collapse
|
31
|
Strategies to increase tolerance and robustness of industrial microorganisms. Synth Syst Biotechnol 2022; 7:533-540. [PMID: 35024480 PMCID: PMC8718811 DOI: 10.1016/j.synbio.2021.12.009] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 12/17/2021] [Accepted: 12/17/2021] [Indexed: 01/06/2023] Open
Abstract
The development of a cost-competitive bioprocess requires that the cell factory converts the feedstock into the product of interest at high rates and yields. However, microbial cell factories are exposed to a variety of different stresses during the fermentation process. These stresses can be derived from feedstocks, metabolism, or industrial production processes, limiting production capacity and diminishing competitiveness. Improving stress tolerance and robustness allows for more efficient production and ultimately makes a process more economically viable. This review summarises general trends and updates the most recent developments in technologies to improve the stress tolerance of microorganisms. We first look at evolutionary, systems biology and computational methods as examples of non-rational approaches. Then we review the (semi-)rational approaches of membrane and transcription factor engineering for improving tolerance phenotypes. We further discuss challenges and perspectives associated with these different approaches.
Collapse
|
32
|
Tellechea-Luzardo J, Otero-Muras I, Goñi-Moreno A, Carbonell P. Fast biofoundries: coping with the challenges of biomanufacturing. Trends Biotechnol 2022; 40:831-842. [PMID: 35012773 DOI: 10.1016/j.tibtech.2021.12.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/13/2021] [Accepted: 12/13/2021] [Indexed: 11/16/2022]
Abstract
Biofoundries are highly automated facilities that enable the rapid and efficient design, build, test, and learn cycle of biomanufacturing and engineering biology, which is applicable to both research and industrial production. However, developing a biofoundry platform can be expensive and time consuming. A biofoundry should grow organically, starting from a basic platform but with a vision for automation, equipment interoperability, and efficiency. By thinking about strategies early in the process through process planning, simulation, and optimization, bottlenecks can be identified and resolved. Here, we provide a survey of technological solutions in biofoundries and their advantages and limitations. We explore possible pathways towards the creation of a functional, early-phase biofoundry, and strategies towards long-term sustainability.
Collapse
Affiliation(s)
- Jonathan Tellechea-Luzardo
- Institute of Industrial Control Systems and Computing (AI2), Universitat Politécnica de València (UPV), 46022 València, Spain
| | - Irene Otero-Muras
- Institute for Integrative Systems Biology I2SysBio, Universitat de València-CSIC, Catedrático Agustín Escardino Benlloch 9, Paterna, 46980 València, Spain
| | - Angel Goñi-Moreno
- Centro de Biotecnología y Genómica de Plantas, Universidad Politécnica de Madrid, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria, Pozuelo de Alarcón, 28223 Madrid, Spain
| | - Pablo Carbonell
- Institute of Industrial Control Systems and Computing (AI2), Universitat Politécnica de València (UPV), 46022 València, Spain.
| |
Collapse
|
33
|
Multiplexed direct detection of barcoded protein reporters on a nanopore array. Nat Biotechnol 2022; 40:42-46. [PMID: 34385692 PMCID: PMC8766897 DOI: 10.1038/s41587-021-01002-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 06/28/2021] [Indexed: 02/07/2023]
Abstract
Detection of specific proteins using nanopores is currently challenging. To address this challenge, we developed a collection of over twenty nanopore-addressable protein tags engineered as reporters (NanoporeTERs, or NTERs). NTERs are constructed with a secretion tag, folded domain and a nanopore-targeting C-terminal tail in which arbitrary peptide barcodes can be encoded. We demonstrate simultaneous detection of up to nine NTERs expressed in bacterial or human cells using MinION nanopore sensor arrays.
Collapse
|
34
|
Sanford PA, Woolston BM. Synthetic or natural? Metabolic engineering for assimilation and valorization of methanol. Curr Opin Biotechnol 2021; 74:171-179. [PMID: 34952430 DOI: 10.1016/j.copbio.2021.12.001] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 11/23/2021] [Accepted: 12/01/2021] [Indexed: 01/01/2023]
Abstract
Single carbon (C1) substrates such as methanol are gaining increasing attention as cost-effective and environmentally friendly microbial feedstocks. Recent impressive metabolic engineering efforts to import C1 catabolic pathways into the non-methylotrophic bacterium Escherichia coli have led to synthetic strains growing on methanol as the sole carbon source. However, the growth rate and product yield in these strains remain inferior to native methylotrophs. Meanwhile, an ever-expanding genetic engineering toolbox is increasing the tractability of native C1 utilizers, raising the question of whether it is best to use an engineered strain or a native host for the microbial assimilation of C1 substrates. Here we provide perspective on this debate, using recent work in E. coli and the methylotrophic acetogen Eubacterium limosum as case studies.
Collapse
Affiliation(s)
- Patrick A Sanford
- Northeastern University, Department of Chemical Engineering, 360 Huntington Avenue, 223 Cullinane, United States
| | - Benjamin M Woolston
- Northeastern University, Department of Chemical Engineering, 360 Huntington Avenue, 223 Cullinane, United States.
| |
Collapse
|
35
|
Zhou S, Wu Y, Xie ZX, Jia B, Yuan YJ. Directed genome evolution driven by structural rearrangement techniques. Chem Soc Rev 2021; 50:12788-12807. [PMID: 34651628 DOI: 10.1039/d1cs00722j] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Directed genome evolution simulates the process of natural evolution at the genomic level in the laboratory to generate desired phenotypes. Here we review the applications of recent technological advances in genome writing and editing to directed genome evolution, with a focus on structural rearrangement techniques. We highlight how these techniques can be used to generate diverse genotypes, and to accelerate the evolution of phenotypic traits. We also discuss the perspectives of directed genome evolution.
Collapse
Affiliation(s)
- Sijie Zhou
- Frontier Science Center for Synthetic Biology (Ministry of Education), Tianjin University, Tianjin, 300072, China. .,Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Yi Wu
- Frontier Science Center for Synthetic Biology (Ministry of Education), Tianjin University, Tianjin, 300072, China. .,Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Ze-Xiong Xie
- Frontier Science Center for Synthetic Biology (Ministry of Education), Tianjin University, Tianjin, 300072, China. .,Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Bin Jia
- Frontier Science Center for Synthetic Biology (Ministry of Education), Tianjin University, Tianjin, 300072, China. .,Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| | - Ying-Jin Yuan
- Frontier Science Center for Synthetic Biology (Ministry of Education), Tianjin University, Tianjin, 300072, China. .,Key Laboratory of Systems Bioengineering (Ministry of Education), School of Chemical Engineering and Technology, Tianjin University, Tianjin, 300072, China
| |
Collapse
|
36
|
Yang Y, Mao Y, Liu Y, Wang R, Lu H, Li H, Luo J, Wang M, Liao X, Ma H. GEDpm-cg: Genome Editing Automated Design Platform for Point Mutation Construction in Corynebacterium glutamicum. Front Bioeng Biotechnol 2021; 9:768289. [PMID: 34722482 PMCID: PMC8554027 DOI: 10.3389/fbioe.2021.768289] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 10/07/2021] [Indexed: 11/13/2022] Open
Abstract
Advances in robotic system-assisted genome editing techniques and computer-aided design tools have significantly facilitated the development of microbial cell factories. Although multiple separate software solutions are available for vector DNA assembly, genome editing, and verification, by far there is still a lack of complete tool which can provide a one-stop service for the entire genome modification process. This makes the design of numerous genetic modifications, especially the construction of mutations that require strictly precise genetic manipulation, a laborious, time-consuming and error-prone process. Here, we developed a free online tool called GEDpm-cg for the design of genomic point mutations in C. glutamicum. The suicide plasmid-mediated counter-selection point mutation editing method and the overlap-based DNA assembly method were selected to ensure the editability of any single nucleotide at any locus in the C. glutamicum chromosome. Primers required for both DNA assembly of the vector for genetic modification and sequencing verification were provided as design results to meet all the experimental needs. An in-silico design task of over 10,000 single point mutations can be completed in 5 min. Finally, three independent point mutations were successfully constructed in C. glutamicum guided by GEDpm-cg, which confirms that the in-silico design results could accurately and seamlessly be bridged with in vivo or in vitro experiments. We believe this platform will provide a user-friendly, powerful and flexible tool for large-scale mutation analysis in the industrial workhorse C. glutamicum via robotic/software-assisted systems.
Collapse
Affiliation(s)
- Yi Yang
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Yufeng Mao
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Ye Liu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Ruoyu Wang
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Hui Lu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Haoran Li
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Jiahao Luo
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Meng Wang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Xiaoping Liao
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| | - Hongwu Ma
- Biodesign Center, Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
| |
Collapse
|
37
|
Plahar HA, Rich TN, Lane SD, Morrell WC, Springthorpe L, Nnadi O, Aravina E, Dai T, Fero MJ, Hillson NJ, Petzold CJ. BioParts-A Biological Parts Search Portal and Updates to the ICE Parts Registry Software Platform. ACS Synth Biol 2021; 10:2649-2660. [PMID: 34449214 DOI: 10.1021/acssynbio.1c00263] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Capturing, storing, and sharing biological DNA parts data are integral parts of synthetic biology research. Here, we detail updates to the ICE biological parts registry software platform that enable these processes, describe our implementation of the Web of Registries concept using ICE, and establish Bioparts, a search portal for biological parts available in the public domain. The Web of Registries enables standalone ICE installations to securely connect and form a distributed parts database. This distributed database allows users from one registry to query and access plasmid, strain, (DNA) part, plant seed, and protein entry types in other connected registries. Users can also transfer entries from one ICE registry to another or make them publicly accessible. Bioparts, the new search portal, combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically.
Collapse
Affiliation(s)
- Hector A. Plahar
- DOE Agile BioFoundry, Emeryville, California 94608 ,United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Thomas N. Rich
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- TeselaGen Biotechnology Inc., San Francisco, California 94107, United States
| | - Stephen D. Lane
- DOE Agile BioFoundry, Emeryville, California 94608 ,United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- Sandia National Laboratories, Livermore, California 94550, United States
| | - William C. Morrell
- DOE Agile BioFoundry, Emeryville, California 94608 ,United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- Sandia National Laboratories, Livermore, California 94550, United States
| | - Leanne Springthorpe
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Oge Nnadi
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Elena Aravina
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Tiffany Dai
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- TeselaGen Biotechnology Inc., San Francisco, California 94107, United States
| | - Michael J. Fero
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- TeselaGen Biotechnology Inc., San Francisco, California 94107, United States
| | - Nathan J. Hillson
- DOE Agile BioFoundry, Emeryville, California 94608 ,United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| | - Christopher J. Petzold
- DOE Agile BioFoundry, Emeryville, California 94608 ,United States
- DOE Joint BioEnergy Institute, Emeryville, California 94608, United States
- Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, California 94720, United States
| |
Collapse
|
38
|
Dudley QM, Cai YM, Kallam K, Debreyne H, Carrasco Lopez JA, Patron NJ. Biofoundry-assisted expression and characterization of plant proteins. Synth Biol (Oxf) 2021; 6:ysab029. [PMID: 34693026 PMCID: PMC8529701 DOI: 10.1093/synbio/ysab029] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 08/25/2021] [Accepted: 09/09/2021] [Indexed: 12/29/2022] Open
Abstract
Many goals in synthetic biology, including the elucidation and refactoring of biosynthetic pathways and the engineering of regulatory circuits and networks, require knowledge of protein function. In plants, the prevalence of large gene families means it can be particularly challenging to link specific functions to individual proteins. However, protein characterization has remained a technical bottleneck, often requiring significant effort to optimize expression and purification protocols. To leverage the ability of biofoundries to accelerate design-built-test-learn cycles, we present a workflow for automated DNA assembly and cell-free expression of plant proteins that accelerates optimization and enables rapid screening of enzyme activity. First, we developed a phytobrick-compatible Golden Gate DNA assembly toolbox containing plasmid acceptors for cell-free expression using Escherichia coli or wheat germ lysates as well as a set of N- and C-terminal tag parts for detection, purification and improved expression/folding. We next optimized automated assembly of miniaturized cell-free reactions using an acoustic liquid handling platform and then compared tag configurations to identify those that increase expression. We additionally developed a luciferase-based system for rapid quantification that requires a minimal 11-amino acid tag and demonstrate facile removal of tags following synthesis. Finally, we show that several functional assays can be performed with cell-free protein synthesis reactions without the need for protein purification. Together, the combination of automated assembly of DNA parts and cell-free expression reactions should significantly increase the throughput of experiments to test and understand plant protein function and enable the direct reuse of DNA parts in downstream plant engineering workflows.
Collapse
Affiliation(s)
- Quentin M Dudley
- Engineering Biology, Earlham Institute, Norwich Research Park, Norwich, Norfolk UK
| | - Yao-Min Cai
- Engineering Biology, Earlham Institute, Norwich Research Park, Norwich, Norfolk UK
| | - Kalyani Kallam
- Engineering Biology, Earlham Institute, Norwich Research Park, Norwich, Norfolk UK
| | - Hubert Debreyne
- Engineering Biology, Earlham Institute, Norwich Research Park, Norwich, Norfolk UK
| | | | - Nicola J Patron
- Engineering Biology, Earlham Institute, Norwich Research Park, Norwich, Norfolk UK
| |
Collapse
|
39
|
Orsi E, Claassens NJ, Nikel PI, Lindner SN. Growth-coupled selection of synthetic modules to accelerate cell factory development. Nat Commun 2021; 12:5295. [PMID: 34489458 PMCID: PMC8421431 DOI: 10.1038/s41467-021-25665-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 08/23/2021] [Indexed: 11/18/2022] Open
Abstract
Synthetic biology has brought about a conceptual shift in our ability to redesign microbial metabolic networks. Combining metabolic pathway-modularization with growth-coupled selection schemes is a powerful tool that enables deep rewiring of the cell factories’ biochemistry for rational bioproduction.
Collapse
Affiliation(s)
- Enrico Orsi
- Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany
| | - Nico J Claassens
- Laboratory of Microbiology, Wageningen University, Wageningen, The Netherlands
| | - Pablo I Nikel
- The Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | - Steffen N Lindner
- Max Planck Institute of Molecular Plant Physiology, Potsdam-Golm, Germany.
| |
Collapse
|
40
|
Currin A, Parker S, Robinson CJ, Takano E, Scrutton NS, Breitling R. The evolving art of creating genetic diversity: From directed evolution to synthetic biology. Biotechnol Adv 2021; 50:107762. [PMID: 34000294 PMCID: PMC8299547 DOI: 10.1016/j.biotechadv.2021.107762] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 04/21/2021] [Accepted: 04/25/2021] [Indexed: 12/31/2022]
Abstract
The ability to engineer biological systems, whether to introduce novel functionality or improved performance, is a cornerstone of biotechnology and synthetic biology. Typically, this requires the generation of genetic diversity to explore variations in phenotype, a process that can be performed at many levels, from single molecule targets (i.e., in directed evolution of enzymes) to whole organisms (e.g., in chassis engineering). Recent advances in DNA synthesis technology and automation have enhanced our ability to create variant libraries with greater control and throughput. This review highlights the latest developments in approaches to create such a hierarchy of diversity from the enzyme level to entire pathways in vitro, with a focus on the creation of combinatorial libraries that are required to navigate a target's vast design space successfully to uncover significant improvements in function.
Collapse
Affiliation(s)
- Andrew Currin
- Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, United Kingdom.
| | - Steven Parker
- Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, United Kingdom
| | - Christopher J Robinson
- Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, United Kingdom
| | - Eriko Takano
- Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, United Kingdom
| | - Nigel S Scrutton
- Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, United Kingdom
| | - Rainer Breitling
- Manchester Centre for Synthetic Biology of Fine and Speciality Chemicals (SYNBIOCHEM), Manchester Institute of Biotechnology, The University of Manchester, Manchester M1 7DN, United Kingdom.
| |
Collapse
|
41
|
Sajid M, Stone SR, Kaur P. Recent Advances in Heterologous Synthesis Paving Way for Future Green-Modular Bioindustries: A Review With Special Reference to Isoflavonoids. Front Bioeng Biotechnol 2021; 9:673270. [PMID: 34277582 PMCID: PMC8282456 DOI: 10.3389/fbioe.2021.673270] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2021] [Accepted: 05/27/2021] [Indexed: 12/12/2022] Open
Abstract
Isoflavonoids are well-known plant secondary metabolites that have gained importance in recent time due to their multiple nutraceutical and pharmaceutical applications. In plants, isoflavonoids play a role in plant defense and can confer the host plant a competitive advantage to survive and flourish under environmental challenges. In animals, isoflavonoids have been found to interact with multiple signaling pathways and have demonstrated estrogenic, antioxidant and anti-oncologic activities in vivo. The activity of isoflavonoids in the estrogen pathways is such that the class has also been collectively called phytoestrogens. Over 2,400 isoflavonoids, predominantly from legumes, have been identified so far. The biosynthetic pathways of several key isoflavonoids have been established, and the genes and regulatory components involved in the biosynthesis have been characterized. The biosynthesis and accumulation of isoflavonoids in plants are regulated by multiple complex environmental and genetic factors and interactions. Due to this complexity of secondary metabolism regulation, the export and engineering of isoflavonoid biosynthetic pathways into non-endogenous plants are difficult, and instead, the microorganisms Saccharomyces cerevisiae and Escherichia coli have been adapted and engineered for heterologous isoflavonoid synthesis. However, the current ex-planta production approaches have been limited due to slow enzyme kinetics and traditionally laborious genetic engineering methods and require further optimization and development to address the required titers, reaction rates and yield for commercial application. With recent progress in metabolic engineering and the availability of advanced synthetic biology tools, it is envisaged that highly efficient heterologous hosts will soon be engineered to fulfill the growing market demand.
Collapse
Affiliation(s)
| | | | - Parwinder Kaur
- UWA School of Agriculture and Environment, University of Western Australia, Perth, WA, Australia
| |
Collapse
|
42
|
Burgos-Morales O, Gueye M, Lacombe L, Nowak C, Schmachtenberg R, Hörner M, Jerez-Longres C, Mohsenin H, Wagner H, Weber W. Synthetic biology as driver for the biologization of materials sciences. Mater Today Bio 2021; 11:100115. [PMID: 34195591 PMCID: PMC8237365 DOI: 10.1016/j.mtbio.2021.100115] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 05/16/2021] [Accepted: 05/18/2021] [Indexed: 01/16/2023] Open
Abstract
Materials in nature have fascinating properties that serve as a continuous source of inspiration for materials scientists. Accordingly, bio-mimetic and bio-inspired approaches have yielded remarkable structural and functional materials for a plethora of applications. Despite these advances, many properties of natural materials remain challenging or yet impossible to incorporate into synthetic materials. Natural materials are produced by living cells, which sense and process environmental cues and conditions by means of signaling and genetic programs, thereby controlling the biosynthesis, remodeling, functionalization, or degradation of the natural material. In this context, synthetic biology offers unique opportunities in materials sciences by providing direct access to the rational engineering of how a cell senses and processes environmental information and translates them into the properties and functions of materials. Here, we identify and review two main directions by which synthetic biology can be harnessed to provide new impulses for the biologization of the materials sciences: first, the engineering of cells to produce precursors for the subsequent synthesis of materials. This includes materials that are otherwise produced from petrochemical resources, but also materials where the bio-produced substances contribute unique properties and functions not existing in traditional materials. Second, engineered living materials that are formed or assembled by cells or in which cells contribute specific functions while remaining an integral part of the living composite material. We finally provide a perspective of future scientific directions of this promising area of research and discuss science policy that would be required to support research and development in this field.
Collapse
Affiliation(s)
- O. Burgos-Morales
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
| | - M. Gueye
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
| | - L. Lacombe
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
| | - C. Nowak
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
| | - R. Schmachtenberg
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
| | - M. Hörner
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
| | - C. Jerez-Longres
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
- Spemann Graduate School of Biology and Medicine - SGBM, University of Freiburg, Freiburg, 79104, Germany
| | - H. Mohsenin
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
| | - H.J. Wagner
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
- Department of Biosystems Science and Engineering - D-BSSE, ETH Zurich, Basel, 4058, Switzerland
| | - W. Weber
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
- Spemann Graduate School of Biology and Medicine - SGBM, University of Freiburg, Freiburg, 79104, Germany
| |
Collapse
|
43
|
Rapid in vitro prototyping of O-methyltransferases for pathway applications in Escherichia coli. Cell Chem Biol 2021; 28:876-886.e4. [PMID: 33957079 DOI: 10.1016/j.chembiol.2021.04.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Revised: 02/20/2021] [Accepted: 04/16/2021] [Indexed: 11/22/2022]
Abstract
O-Methyltransferases are ubiquitous enzymes involved in biosynthetic pathways for secondary metabolites such as bacterial antibiotics, human catecholamine neurotransmitters, and plant phenylpropanoids. While thousands of putative O-methyltransferases are found in sequence databases, few examples are functionally characterized. From a pathway engineering perspective, however, it is crucial to know the substrate and product ranges of the respective enzymes to fully exploit their catalytic power. In this study, we developed an in vitro prototyping workflow that allowed us to screen ∼30 enzymes against five substrates in 3 days with high reproducibility. We combined in vitro transcription/translation of the genes of interest with a microliter-scale enzymatic assay in 96-well plates. The substrate conversion was indirectly measured by quantifying the consumption of the S-adenosyl-L-methionine co-factor by time-resolved fluorescence resonance energy transfer rather than time-consuming product analysis by chromatography. This workflow allowed us to rapidly prototype thus far uncharacterized O-methyltransferases for future use as biocatalysts.
Collapse
|
44
|
Pretorius IS. Tasting the terroir of wine yeast innovation. FEMS Yeast Res 2021; 20:5674549. [PMID: 31830254 PMCID: PMC6964221 DOI: 10.1093/femsyr/foz084] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 11/27/2019] [Indexed: 12/14/2022] Open
Abstract
Wine is an archetypal traditional fermented beverage with strong territorial and socio-cultural connotations. Its 7000 year history is patterned by a tradition of innovation. Every value-adding innovation − whether in the vineyard, winery, supply chain or marketplace − that led to the invention of a new tradition spurred progress and created a brighter future from past developments. In a way, wine traditions can be defined as remembered innovations from the distant past − inherited knowledge and wisdom that withstood the test of time. Therefore, it should not be assumed a priori that tradition and innovation are polar opposites. The relations between the forces driven by the anchors of tradition and the wings of innovation do not necessarily involve displacement, conflict or exclusiveness. Innovation can strengthen wine tradition, and the reinvention of a tradition-bound practice, approach or concept can foster innovation. In cases where a paradigm-shifting innovation disrupts a tradition, the process of such an innovation transitioning into a radically new tradition can become protracted while proponents of divergent opinions duke it out. Sometimes these conflicting opinions are based on fact, and sometimes not. The imperfections of such a debate between the ‘ancients’ and the ‘moderns’ can, from time to time, obscure the line between myth and reality. Therefore, finding the right balance between traditions worth keeping and innovations worth implementing can be complex. The intent here is to harness the creative tension between science fiction and science fact when innovation's first-principles challenge the status quo by re-examining the foundational principles about a core traditional concept, such as terroir. Poignant questions are raised about the importance of the terroir (biogeography) of yeasts and the value of the microbiome of grapes to wine quality. This article imagines a metaphorical terroir free from cognitive biases where diverse perspectives can converge to uncork the effervescent power of territorial yeast populations as well as ‘nomadic’ yeast starter cultures. At the same time, this paper also engages in mental time-travel. A future scenario is imagined, explored, tested and debated where terroir-less yeast avatars are equipped with designer genomes to safely and consistently produce, individually or in combination with region-specific wild yeasts and or other starter cultures, high-quality wine according to the preferences of consumers in a range of markets. The purpose of this review is to look beyond the horizon and to synthesize a link between what we know now and what could be. This article informs readers where to look without suggesting what they must see as a way forward. In the context of one of the world's oldest fermentation industries − steeped in a rich history of tradition and innovation − the mantra here is: respect the past, lead the present and secure the future of wine.
Collapse
Affiliation(s)
- I S Pretorius
- ARC Centre of Excellence in Synthetic Biology, Macquarie University, 19 Eastern Road, North Ryde, Sydney, NSW 2109, Australia
| |
Collapse
|
45
|
David F, Davis AM, Gossing M, Hayes MA, Romero E, Scott LH, Wigglesworth MJ. A Perspective on Synthetic Biology in Drug Discovery and Development-Current Impact and Future Opportunities. SLAS DISCOVERY 2021; 26:581-603. [PMID: 33834873 DOI: 10.1177/24725552211000669] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The global impact of synthetic biology has been accelerating, because of the plummeting cost of DNA synthesis, advances in genetic engineering, growing understanding of genome organization, and explosion in data science. However, much of the discipline's application in the pharmaceutical industry remains enigmatic. In this review, we highlight recent examples of the impact of synthetic biology on target validation, assay development, hit finding, lead optimization, and chemical synthesis, through to the development of cellular therapeutics. We also highlight the availability of tools and technologies driving the discipline. Synthetic biology is certainly impacting all stages of drug discovery and development, and the recognition of the discipline's contribution can further enhance the opportunities for the drug discovery and development value chain.
Collapse
Affiliation(s)
- Florian David
- Department of Biology and Biological Engineering, Division of Systems and Synthetic Biology, Chalmers University of Technology, Gothenburg, Sweden
| | - Andrew M Davis
- Discovery Sciences, Biopharmaceutical R&D, AstraZeneca, Cambridge, UK
| | - Michael Gossing
- Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Martin A Hayes
- Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Elvira Romero
- Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Louis H Scott
- Discovery Sciences, Biopharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | | |
Collapse
|
46
|
Zulkower V. Computer-Aided Design and Pre-validation of Large Batches of DNA Assemblies. METHODS IN MOLECULAR BIOLOGY (CLIFTON, N.J.) 2021; 2229:157-166. [PMID: 33405220 DOI: 10.1007/978-1-0716-1032-9_6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Type-2S restriction enzymes allow the routine assembly of large batches of synthetic constructs from individual genetic parts. However, design flaws in the part sequence can cause assembly failures, incurring troubleshooting costs and project delays. As a result, the careful design and checking of the assembly plan is often a bottleneck of large assembly projects, and may require computational support. This chapter demonstrates the use of two free and open-source web applications accelerating this task by automating genetic part design and simulating type-2S cloning to detect potential assembly issues.
Collapse
Affiliation(s)
- Valentin Zulkower
- Edinburgh Genome Foundry, SynthSys, School of Biological Sciences, University of Edinburgh, Edinburgh, UK.
| |
Collapse
|
47
|
Joint Universal Modular Plasmids: A Flexible Platform for Golden Gate Assembly in Any Microbial Host. Methods Mol Biol 2021; 2205:255-273. [PMID: 32809204 DOI: 10.1007/978-1-0716-0908-8_15] [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] [Indexed: 04/07/2023]
Abstract
Modular cloning standards based on Golden Gate DNA assembly allow for construction of complex DNA constructs over several rounds of assembly. Despite being reliable and automation-friendly, each standard uses a specific set of vectors, requiring researchers to generate new tool kits for novel hosts and cloning applications. JUMP vectors (Valenzuela-Ortega and French, bioRxiv 799585, 2019) combine the robustness of modular cloning standards with the Standard European Vector Architecture and a flexible design that allows researchers to easily modify the vector backbone via secondary cloning sites. This flexibility allows for JUMP vectors to be used in a wide variety of applications and hosts.
Collapse
|
48
|
Tenhaef N, Stella R, Frunzke J, Noack S. Automated Rational Strain Construction Based on High-Throughput Conjugation. ACS Synth Biol 2021; 10:589-599. [PMID: 33593066 DOI: 10.1021/acssynbio.0c00599] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Molecular cloning is the core of synthetic biology, as it comprises the assembly of DNA and its expression in target hosts. At present, however, cloning is most often a manual, time-consuming, and repetitive process that highly benefits from automation. The automation of a complete rational cloning procedure, i.e., from DNA creation to expression in the target host, involves the integration of different operations and machines. Examples of such workflows are sparse, especially when the design is rational (i.e., the DNA sequence design is fixed and not based on randomized libraries) and the target host is less genetically tractable (e.g., not sensitive to heat-shock transformation). In this study, an automated workflow for the rational construction of plasmids and their subsequent conjugative transfer into the biotechnological platform organism Corynebacterium glutamicum is presented. The whole workflow is accompanied by a custom-made software tool. As an application example, a rationally designed library of transcription factor-biosensors based on the regulator Lrp was constructed and characterized. A sensor with an improved dynamic range was obtained, and insights from the screening provided evidence for a dual regulator function of C. glutamicum Lrp.
Collapse
Affiliation(s)
- Niklas Tenhaef
- Institute of Bio- and Geosciences − IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich 52425, Germany
| | - Robert Stella
- Institute of Bio- and Geosciences − IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich 52425, Germany
| | - Julia Frunzke
- Institute of Bio- and Geosciences − IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich 52425, Germany
| | - Stephan Noack
- Institute of Bio- and Geosciences − IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich 52425, Germany
- Bioeconomy Science Center (BioSC), Forschungszentrum Jülich, Jülich 52425, Germany
| |
Collapse
|
49
|
Ferguson AL, Ranganathan R. 100th Anniversary of Macromolecular Science Viewpoint: Data-Driven Protein Design. ACS Macro Lett 2021; 10:327-340. [PMID: 35549066 DOI: 10.1021/acsmacrolett.0c00885] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The design of synthetic proteins with the desired function is a long-standing goal in biomolecular science, with broad applications in biochemical engineering, agriculture, medicine, and public health. Rational de novo design and experimental directed evolution have achieved remarkable successes but are challenged by the requirement to find functional "needles" in the vast "haystack" of protein sequence space. Data-driven models for fitness landscapes provide a predictive map between protein sequence and function and can prospectively identify functional candidates for experimental testing to greatly improve the efficiency of this search. This Viewpoint reviews the applications of machine learning and, in particular, deep learning as part of data-driven protein engineering platforms. We highlight recent successes, review promising computational methodologies, and provide an outlook on future challenges and opportunities. The article is written for a broad audience comprising both polymer and protein scientists and computer and data scientists interested in an up-to-date review of recent innovations and opportunities in this rapidly evolving field.
Collapse
Affiliation(s)
- Andrew L. Ferguson
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
| | - Rama Ranganathan
- Pritzker School of Molecular Engineering, University of Chicago, Chicago, Illinois 60637, United States
- Center for Physics of Evolving Systems, University of Chicago, Chicago, Illinois 60637, United States
- Biochemistry and Molecular Biology, University of Chicago, Chicago, Illinois 60637, United States
| |
Collapse
|
50
|
Valenzuela-Ortega M, French C. Joint universal modular plasmids (JUMP): a flexible vector platform for synthetic biology. Synth Biol (Oxf) 2021; 6:ysab003. [PMID: 33623824 PMCID: PMC7889407 DOI: 10.1093/synbio/ysab003] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Revised: 12/08/2020] [Accepted: 12/22/2020] [Indexed: 12/21/2022] Open
Abstract
Generation of new DNA constructs is an essential process in modern life science and biotechnology. Modular cloning systems based on Golden Gate cloning, using Type IIS restriction endonucleases, allow assembly of complex multipart constructs from reusable basic DNA parts in a rapid, reliable and automation-friendly way. Many such toolkits are available, with varying degrees of compatibility, most of which are aimed at specific host organisms. Here, we present a vector design which allows simple vector modification by using modular cloning to assemble and add new functions in secondary sites flanking the main insertion site (used for conventional modular cloning). Assembly in all sites is compatible with the PhytoBricks standard, and vectors are compatible with the Standard European Vector Architecture (SEVA) as well as BioBricks. We demonstrate that this facilitates the construction of vectors with tailored functions and simplifies the workflow for generating libraries of constructs with common elements. We have made available a collection of vectors with 10 different microbial replication origins, varying in copy number and host range, and allowing chromosomal integration, as well as a selection of commonly used basic parts. This design expands the range of hosts which can be easily modified by modular cloning and acts as a toolkit which can be used to facilitate the generation of new toolkits with specific functions required for targeting further hosts.
Collapse
Affiliation(s)
- Marcos Valenzuela-Ortega
- Centre for Systems and Synthetic Biology, School of Biological Sciences, University of Edinburgh, Roger Land Building, Alexander Crum Brown Road, Edinburgh EH9 3FF, UK
| | - Christopher French
- Centre for Systems and Synthetic Biology, School of Biological Sciences, University of Edinburgh, Roger Land Building, Alexander Crum Brown Road, Edinburgh EH9 3FF, UK.,Zhejiang University-University of Edinburgh Joint Research Centre for Engineering Biology, International Campus, Zhejiang University, Haining, Zhejiang 314400, China
| |
Collapse
|