An international comprehensive benchmarking analysis of synthetic biology in China from 2015 to 2020

doi:10.1016/j.cjche.2021.05.036

中国化学工程学报 ›› 2022, Vol. 48 ›› Issue (8): 211-226.DOI: 10.1016/j.cjche.2021.05.036

An international comprehensive benchmarking analysis of synthetic biology in China from 2015 to 2020

Meiru Jiang¹, Cong Chen¹, Tao Chen¹, Chao Zhao², Zhiwen Wang¹

1. Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China;
2. Center for Biosafety Research and Strategy, Tianjin University, Tianjin 300072, China

收稿日期:2021-03-25 修回日期:2021-05-22 出版日期:2022-08-28 发布日期:2022-09-30
通讯作者: Chao Zhao,E-mail:zhao_chao@tju.edu.cn;Zhiwen Wang,E-mail:zww@tju.edu.cn
基金资助:
The research was financially supported by the National Natural Science Foundation of China (21776209, 21621004 and 21776208), Ministry of Education of the People’s Republic of China Humanities and Social Sciences Youth Foundation(21YJCZH232) and the Natural Science Foundation of Tianjin City (No. 19JCYBJC21100).

An international comprehensive benchmarking analysis of synthetic biology in China from 2015 to 2020

Meiru Jiang¹, Cong Chen¹, Tao Chen¹, Chao Zhao², Zhiwen Wang¹

1. Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (Ministry of Education), SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China;
2. Center for Biosafety Research and Strategy, Tianjin University, Tianjin 300072, China

Received:2021-03-25 Revised:2021-05-22 Online:2022-08-28 Published:2022-09-30
Contact: Chao Zhao,E-mail:zhao_chao@tju.edu.cn;Zhiwen Wang,E-mail:zww@tju.edu.cn
Supported by:
The research was financially supported by the National Natural Science Foundation of China (21776209, 21621004 and 21776208), Ministry of Education of the People’s Republic of China Humanities and Social Sciences Youth Foundation(21YJCZH232) and the Natural Science Foundation of Tianjin City (No. 19JCYBJC21100).

摘要/Abstract

摘要： As a new interdisciplinary field, synthetic biology has led to valuable innovations in the fields of medicine, chemistry, agriculture, energy and environment. In this paper, we systematically review the development status of global synthetic biology in the past six years, and make an in-depth benchmarking analysis of the field in China. With the aid of Scopus and SciVal, we analyze the scholarly output of synthetic biology in the world and individual countries, including publication distribution, popular journals and eminent institutions. Furthermore, the research focus and concepts, citation impact and collaborations are also examined using numerical index methods such as the field-weighted citation impact (FWCI) and relative activity index (RAI), showing the differences between data more intuitively. This study aims to offer a comprehensive understanding of the research status of synthetic biology in China and the world, offering a benchmarked overview of the results as a reference to guide the development of this field in the future.

关键词: Synthetic biology, Scopus, SciVal, Output, Citation impact, Collaboration

Abstract: As a new interdisciplinary field, synthetic biology has led to valuable innovations in the fields of medicine, chemistry, agriculture, energy and environment. In this paper, we systematically review the development status of global synthetic biology in the past six years, and make an in-depth benchmarking analysis of the field in China. With the aid of Scopus and SciVal, we analyze the scholarly output of synthetic biology in the world and individual countries, including publication distribution, popular journals and eminent institutions. Furthermore, the research focus and concepts, citation impact and collaborations are also examined using numerical index methods such as the field-weighted citation impact (FWCI) and relative activity index (RAI), showing the differences between data more intuitively. This study aims to offer a comprehensive understanding of the research status of synthetic biology in China and the world, offering a benchmarked overview of the results as a reference to guide the development of this field in the future.

Key words: Synthetic biology, Scopus, SciVal, Output, Citation impact, Collaboration

Meiru Jiang, Cong Chen, Tao Chen, Chao Zhao, Zhiwen Wang. An international comprehensive benchmarking analysis of synthetic biology in China from 2015 to 2020[J]. 中国化学工程学报, 2022, 48(8): 211-226.

Meiru Jiang, Cong Chen, Tao Chen, Chao Zhao, Zhiwen Wang. An international comprehensive benchmarking analysis of synthetic biology in China from 2015 to 2020[J]. Chinese Journal of Chemical Engineering, 2022, 48(8): 211-226.

参考文献

[1] M.Z. Ding, B.Z. Li, Y. Wang, Z.X. Xie, D. Liu, Y.J. Yuan, Advances in important research directions of synthetic biology, Synth. Biol. J. 1 (2020) 7-28
[2] Z.Q. Li, P. Xu, B. Liu, Present situation analysis and development trend forecast of industrial biotechnology industry in China, Biotechnol. Bus. (2017) (6)7–16.(in Chinese)
[3] V. Chubukov, A. Mukhopadhyay, C.J. Petzold, J.D. Keasling, H.G. Martín, Synthetic and systems biology for microbial production of commodity chemicals, NPJ Syst Biol Appl 2 (2016) 16009. https://www.ncbi.nlm.nih.gov/pubmed/28725470/
[4] C.E. Nakamura, G.M. Whited, Metabolic engineering for the microbial production of 1, 3-propanediol, Curr Opin Biotechnol 14 (5) (2003) 454–459. https://www.ncbi.nlm.nih.gov/pubmed/14580573/
[5] H.W. Liu, T. Lu, Autonomous production of 1, 4-butanediol via a de novo biosynthesis pathway in engineered Escherichia coli, Metab Eng 29 (2015) 135–141. https://www.ncbi.nlm.nih.gov/pubmed/25796335/
[6] J.D. Keasling, Synthetic biology for synthetic chemistry, ACS Chem Biol 3 (1) (2008) 64–76. https://www.ncbi.nlm.nih.gov/pubmed/18205292/
[7] S. Ausl?nder, D. Ausl?nder, M. Fussenegger, Synthetic biology-the synthesis of biology, Angew Chem Int Ed Engl 56 (23) (2017) 6396–6419. https://www.ncbi.nlm.nih.gov/pubmed/27943572/
[8] C.A. Hutchison 3rd, R.Y. Chuang, V.N. Noskov, N. Assad-Garcia, T.J. Deerinck, M.H. Ellisman, J. Gill, K. Kannan, B.J. Karas, L. Ma, J.F. Pelletier, Z.Q. Qi, R.A. Richter, E.A. Strychalski, L.J. Sun, Y. Suzuki, B. Tsvetanova, K.S. Wise, H.O. Smith, J.I. Glass, C. Merryman, D.G. Gibson, J.C. Venter, Design and synthesis of a minimal bacterial genome, Science 351 (6280) (2016) aad6253. https://www.ncbi.nlm.nih.gov/pubmed/27013737/
[9] S. Gleizer, R. Ben-Nissan, Y.M. Bar-On, N. Antonovsky, E. Noor, Y. Zohar, G. Jona, E. Krieger, M. Shamshoum, A. Bar-Even, R. Milo, Conversion of escherichia coli to generate all biomass carbon from CO2, Cell 179 (6) (2019) 1255–1263.e12. https://www.ncbi.nlm.nih.gov/pubmed/31778652/
[10] L. Steffens, E. Pettinato, T.M. Steiner, A. Mall, S. K?nig, W. Eisenreich, I.A. Berg, High CO2 levels drive the TCA cycle backwards towards autotrophy, Nature 592 (7856) (2021) 784–788. https://www.ncbi.nlm.nih.gov/pubmed/33883741/
[11] Z.Q. Wen, N.P. Minton, Y. Zhang, Q. Li, J.L. Liu, Y. Jiang, S. Yang, Enhanced solvent production by metabolic engineering of a twin-clostridial consortium, Metab Eng 39 (2017) 38–48. https://www.ncbi.nlm.nih.gov/pubmed/27794465/
[12] T. Yu, Y.J. Zhou, M.T. Huang, Q.L. Liu, R. Pereira, F. David, J. Nielsen, Reprogramming yeast metabolism from alcoholic fermentation to lipogenesis, Cell 174 (6) (2018) 1549–1558.e14. https://www.ncbi.nlm.nih.gov/pubmed/30100189/
[13] Z.W. Zhu, Y.T. Hu, P.G. Teixeira, R. Pereira, Y. Chen, V. Siewers, J. Nielsen, Multidimensional engineering of Saccharomyces cerevisiae for efficient synthesis of medium-chain fatty acids, Nat. Catal. 3 (1) (2020) 64–74. http://dx.doi.org/10.1038/s41929-019-0409-1
[14] Pang Y, Zhao Y, Li S, Zhao Y, Li J, Hu Z, Zhang C, Xiao D, Yu A, Engineering the oleaginous yeast Yarrowia lipolytica to produce limonene from waste cooking oil, Biotechnol Biofuels 12 (2019) 241. https://www.ncbi.nlm.nih.gov/pubmed/31624503/
[15] Y.R. Li, S.J. Li, K. Thodey, I. Trenchard, A. Cravens, C.D. Smolke, Complete biosynthesis of noscapine and halogenated alkaloids in yeast, Proc Natl Acad Sci USA 115 (17) (2018) E3922–E3931. https://www.ncbi.nlm.nih.gov/pubmed/29610307/
[16] K. R?ssger, G. Charpin-El-Hamri, M. Fussenegger, A closed-loop synthetic gene circuit for the treatment of diet-induced obesity in mice, Nat Commun 4 (2013) 2825. https://www.ncbi.nlm.nih.gov/pubmed/24281397/
[17] L. Li, S.J. Lee, Q.P. Yuan, W.T. Im, S.C. Kim, N.S. Han, Production of bioactive ginsenoside Rg3(S) and compound K using recombinant Lactococcus lactis, J Ginseng Res 42 (4) (2018) 412–418. https://www.ncbi.nlm.nih.gov/pubmed/30337801/
[18] Luo X, Reiter MA, d'Espaux L, Wong J, Denby CM, Lechner A, Zhang Y, Grzybowski AT, Harth S, Lin W, Lee H, Yu C, Shin J, Deng K, Benites VT, Wang G, Baidoo EEK, Chen Y, Dev I, Petzold CJ, Keasling JD, Complete biosynthesis of cannabinoids and their unnatural analogues in yeast, Nature 567 (7746) (2019) 123–126. https://www.ncbi.nlm.nih.gov/pubmed/30814733/
[19] P. Srinivasan, C.D. Smolke, Biosynthesis of medicinal tropane alkaloids in yeast, Nature 585 (7826) (2020) 614–619. https://www.ncbi.nlm.nih.gov/pubmed/32879484/
[20] H.J. Wagner, S. Kemmer, R. Engesser, J. Timmer, W. Weber, Biofunctionalized materials featuring feedforward and feedback circuits exemplified by the detection of botulinum toxin A, Adv Sci (Weinh) 6 (4) (2019) 1801320. https://www.ncbi.nlm.nih.gov/pubmed/30828524/
[21] S. Roy, J.W. Rhim, Fabrication of cellulose nanofiber-based functional color indicator film incorporated with shikonin extracted from Lithospermum erythrorhizon root, Food Hydrocoll. 114 (2021) 106566. http://dx.doi.org/10.1016/j.foodhyd.2020.106566
[22] D.X. Wei, J.W. Dao, G.Q. Chen, A micro-ark for cells: highly open porous polyhydroxyalkanoate microspheres as injectable scaffolds for tissue regeneration, Adv. Mater. 30 (31) (2018) 1802273. https://doi.org/10.1002/adma.201802273
[23] Y.J. Zhang, Z.T. Zhou, L. Sun, Z. Liu, X.X. Xia, T.H. Tao, “genetically engineered” biofunctional triboelectric nanogenerators using recombinant spider silk, Adv Mater 30 (50) (2018) e1805722
[24] P. Mohammadi, A.S. Aranko, C.P. Landowski, O. Ikkala, K. Jaudzems, W. Wagermaier, M.B. Linder, Biomimetic composites with enhanced toughening using silk-inspired triblock proteins and aligned nanocellulose reinforcements, Sci Adv 5 (9) (2019) eaaw2541
[25] J.F. Huang, S.Y. Liu, C. Zhang, X.Y. Wang, J.H. Pu, F. Ba, S. Xue, H.F. Ye, T.X. Zhao, K. Li, Y.Y. Wang, J.C. Zhang, L.H. Wang, C.H. Fan, T.K. Lu, C. Zhong, Programmable and printable Bacillus subtilis biofilms as engineered living materials, Nat Chem Biol 15 (1) (2019) 34–41. https://www.ncbi.nlm.nih.gov/pubmed/30510190/
[26] Z.Y. Chen, X.X. Sun, Y. Li, Y.J. Yan, Q.P. Yuan, Metabolic engineering of Escherichia coli for microbial synthesis of monolignols, Metab Eng 39 (2017) 102–109. https://www.ncbi.nlm.nih.gov/pubmed/27816771/
[27] W.M. Zhang, T. Zhang, M. Song, Z.X. Dai, S.J. Zhang, F.X. Xin, W.L. Dong, J.F. Ma, M. Jiang, Metabolic engineering of escherichia coli for high yield production of succinic acid driven by methanol, ACS Synth Biol 7 (12) (2018) 2803–2811. https://www.ncbi.nlm.nih.gov/pubmed/30300546/
[28] Y.J. Li, B. Huang, H. Wu, Z.M. Li, Q. Ye, Y.P. Zhang, Production of succinate from acetate by metabolically engineered escherichia coli, ACS Synth Biol 5 (11) (2016) 1299–1307. https://www.ncbi.nlm.nih.gov/pubmed/27088218/
[29] L. Guo, W.W. Diao, C. Gao, G.P. Hu, Q. Ding, C. Ye, X.L. Chen, J. Liu, L.M. Liu, Engineering Escherichia coli lifespan for enhancing chemical production, Nat. Catal. 3 (3) (2020) 307–318. https://www.nature.com/articles/s41929-019-0411-7
[30] W.N. Li, L. Ma, X.L. Shen, J. Wang, Q. Feng, L.X. Liu, G.J. Zheng, Y.J. Yan, X.X. Sun, Q.P. Yuan, Targeting metabolic driving and intermediate influx in lysine catabolism for high-level glutarate production, Nat Commun 10 (1) (2019) 3337. https://www.ncbi.nlm.nih.gov/pubmed/31350399/
[31] S. Khan, H. Tombuloglu, S.E. Hassanein, S. Rehman, A. Bozkurt, E. Cevik, S. Abdel-Ghany, G. Nabi, A. Ali, H. Sabit, Coronavirus diseases 2019: Current biological situation and potential therapeutic perspective, Eur. J. Pharmacol. 886 (2020) 173447. http://dx.doi.org/10.1016/j.ejphar.2020.173447
[32] J. Joung, A. Ladha, M. Saito, N.G. Kim, A.E. Woolley, M. Segel, R.P.J. Barretto, A. Ranu, R.K. MacRae, G. Faure, E.I. Ioannidi, R.N. Krajeski, R. Bruneau, M.W. Huang, X.G. Yu, J.Z. Li, B.D. Walker, D.T. Hung, A.L. Greninger, K.R. Jerome, J.S. Gootenberg, O.O. Abudayyeh, F. Zhang, Detection of SARS-CoV-2 with SHERLOCK one-pot testing, N Engl J Med 383 (15) (2020) 1492–1494. https://www.ncbi.nlm.nih.gov/pubmed/32937062/
[33] H. Deng, Analysis on development trends associate with synthetic biology of China in recent years, Compet. Intell. (2020) 16(3)32–40. (in Chinese)
[34] S. Wisner, Synthetic biology investment reached a new record of nearly $8 billion in 2020 — What does this mean for 2021?, 2020 Synbiobeta market report 2021, 2021[2021-02-13], Available from: https://synbiobeta.com/synthetic-biology-investment-set-a-nearly-8-billion-record-in-2020-what-does-this-mean-for-2021/. https://synbiobeta.com/synthetic-biology-investment-set-a-nearly-8-billion-record-in-2020-what-does-this-mean-for-2021/
[35] Y. Shen, Y. Wang, T. Chen, F. Gao, J.H. Gong, D. Abramczyk, R. Walker, H.C. Zhao, S.H. Chen, W. Liu, Y.S. Luo, C.A. Müller, A. Paul-Dubois-Taine, B. Alver, G. Stracquadanio, L.A. Mitchell, Z.Q. Luo, Y.Q. Fan, B.J. Zhou, B. Wen, F.J. Tan, Y.J. Wang, J. Zi, Z.X. Xie, B.Z. Li, K. Yang, S.M. Richardson, H. Jiang, C.E. French, C.A. Nieduszynski, R. Koszul, A.L. Marston, Y.J. Yuan, J. Wang, J.S. Bader, J.B. Dai, J.D. Boeke, X. Xu, Y.Z. Cai, H.M. Yang, Deep functional analysis of synII, a 770-kilobase synthetic yeast chromosome, Science 355 (6329) (2017) eaaf4791. https://www.ncbi.nlm.nih.gov/pubmed/28280153/
[36] Shao Y, Lu N, Wu Z, Cai C, Wang S, Zhang LL, Zhou F, Xiao S, Liu L, Zeng X, Zheng H, Yang C, Zhao Z, Zhao G, Zhou JQ, Xue X, Qin Z, Creating a functional single-chromosome yeast, Nature 560 (7718) (2018) 331–335. https://www.ncbi.nlm.nih.gov/pubmed/30069045/
[37] X.L. Ma, Q.Y. Zhang, Q.L. Zhu, W. Liu, Y. Chen, R. Qiu, B. Wang, Z.F. Yang, H.Y. Li, Y.R. Lin, Y.Y. Xie, R.X. Shen, S.F. Chen, Z. Wang, Y.L. Chen, J.X. Guo, L.T. Chen, X.C. Zhao, Z.C. Dong, Y.G. Liu, A robust CRISPR/Cas9 system for convenient, high-efficiency multiplex genome editing in monocot and dicot plants, Mol Plant 8 (8) (2015) 1274–1284. https://www.ncbi.nlm.nih.gov/pubmed/25917172/
[38] Y. Wang, Y. Liu, J. Liu, Y.M. Guo, L.W. Fan, X.M. Ni, X.M. Zheng, M. Wang, P. Zheng, J.B. Sun, Y.H. Ma, MACBETH: Multiplex automated Corynebacterium glutamicum base editing method, Metab Eng 47 (2018) 200–210. https://www.ncbi.nlm.nih.gov/pubmed/29580925/
[39] A.R. Lu, J.M. Wang, W.H. Sun, W.R. Huang, Z.M. Cai, G.P. Zhao, J. Wang, Reprogrammable CRISPR/dCas9-based recruitment of DNMT1 for site-specific DNA demethylation and gene regulation, Cell Discov 5 (2019) 22. https://www.ncbi.nlm.nih.gov/pubmed/31016028/
[40] D.Y. Liu, C. Huang, J.X. Guo, P.J. Zhang, T. Chen, Z.W. Wang, X.M. Zhao, Development and characterization of a CRISPR/Cas9n-based multiplex genome editing system for Bacillus subtilis, Biotechnol Biofuels 12 (2019) 197. https://www.ncbi.nlm.nih.gov/pubmed/31572493/
[41] Y.K. Wu, Y.F. Liu, X. Lv, J.H. Li, G.C. Du, L. Liu, CAMERS-B: CRISPR/Cpf1 assisted multiple-genes editing and regulation system for Bacillus subtilis, Biotechnol Bioeng 117 (6) (2020) 1817–1825. https://www.ncbi.nlm.nih.gov/pubmed/32129468/
[42] W. Shen, J. Zhang, B.N. Geng, M.Y. Qiu, M.M. Hu, Q. Yang, W.W. Bao, Y.B. Xiao, Y.L. Zheng, W.F. Peng, G.M. Zhang, L.X. Ma, S.H. Yang, Establishment and application of a CRISPR-Cas12a assisted genome-editing system in Zymomonas mobilis, Microb Cell Fact 18 (1) (2019) 162. https://www.ncbi.nlm.nih.gov/pubmed/31581942/
[43] S.X. Wang, Y. Zong, Q.P. Lin, H.W. Zhang, Z.Z. Chai, D.D. Zhang, K.L. Chen, J.L. Qiu, C.X. Gao, Precise, predictable multi-nucleotide deletions in rice and wheat using APOBEC-Cas9, Nat Biotechnol 38 (12) (2020) 1460–1465. https://www.ncbi.nlm.nih.gov/pubmed/32601432/
[44] D.D. Zhao, J. Li, S.W. Li, X.Q. Xin, M.Z. Hu, M.A. Price, S.J. Rosser, C.H. Bi, X.L. Zhang, Glycosylase base editors enable C-to-A and C-to-G base changes, Nat. Biotechnol. 39 (1) (2021) 35–40. http://dx.doi.org/10.1038/s41587-020-0592-2
[45] C. Gao, J.S. Hou, P. Xu, L. Guo, X.L. Chen, G.P. Hu, C. Ye, H. Edwards, J. Chen, W. Chen, L.M. Liu, Programmable biomolecular switches for rewiring flux in Escherichia coli, Nat Commun 10 (1) (2019) 3751. https://www.ncbi.nlm.nih.gov/pubmed/31434894/
[46] L. Qin, S.X. Dong, J. Yu, X.Y. Ning, K. Xu, S.J. Zhang, L. Xu, B.Z. Li, J. Li, Y.J. Yuan, C. Li, Stress-driven dynamic regulation of multiple tolerance genes improves robustness and productive capacity of Saccharomyces cerevisiae in industrial lignocellulose fermentation, Metab Eng 61 (2020) 160–170. https://www.ncbi.nlm.nih.gov/pubmed/32553944/
[47] Y. Xu, Z. Zhao, W.H. Tong, Y.M. Ding, B. Liu, Y.X. Shi, J.C. Wang, S.M. Sun, M. Liu, Y.H. Wang, Q.S. Qi, M. Xian, G. Zhao, An acid-tolerance response system protecting exponentially growing Escherichia coli, Nat Commun 11 (1) (2020) 1496. https://www.ncbi.nlm.nih.gov/pubmed/32198415/
[48] C.G. Xu, R.R. Huang, L. Teng, X.Y. Jing, J.Q. Hu, G.Z. Cui, Y.L. Wang, Q. Cui, J. Xu, Cellulosome stoichiometry in Clostridium cellulolyticum is regulated by selective RNA processing and stabilization, Nat Commun 6 (2015) 6900. https://www.ncbi.nlm.nih.gov/pubmed/25908225/
[49] X.H. Xu, X.L. Li, Y.F. Liu, Y.L. Zhu, J.H. Li, G.C. Du, J. Chen, R. Ledesma-Amaro, L. Liu, Pyruvate-responsive genetic circuits for dynamic control of central metabolism, Nat Chem Biol 16 (11) (2020) 1261–1268. https://www.ncbi.nlm.nih.gov/pubmed/32895497/
[50] X.Y. Lu, Y.W. Liu, Y.Q. Yang, S.S. Wang, Q. Wang, X.Y. Wang, Z.H. Yan, J. Cheng, C. Liu, X. Yang, H. Luo, S. Yang, J.R. Gou, L.Z. Ye, L.N. Lu, Z.D. Zhang, Y. Guo, Y. Nie, J.P. Lin, S. Li, C.G. Tian, T. Cai, B.Z. Zhuo, H.W. Ma, W. Wang, Y.H. Ma, Y.J. Liu, Y. Li, H.F. Jiang, Constructing a synthetic pathway for acetyl-coenzyme A from one-carbon through enzyme design, Nat Commun 10 (1) (2019) 1378. https://www.ncbi.nlm.nih.gov/pubmed/30914637/
[51] C. Ye, Q.L. Luo, L. Guo, C. Gao, N. Xu, L. Zhang, L.M. Liu, X.L. Chen, Improving lysine production through construction of an Escherichia coli enzyme-constrained model, Biotechnol Bioeng 117 (11) (2020) 3533–3544. https://www.ncbi.nlm.nih.gov/pubmed/32648933/
[52] X. Yang, Q.Q. Yuan, H. Luo, F.R. Li, Y.F. Mao, X. Zhao, J.W. Du, P.S. Li, X.Z. Ju, Y.Y. Zheng, Y. Chen, Y.W. Liu, H.F. Jiang, Y.H. Yao, H.W. Ma, Y.H. Ma, Systematic design and in vitro validation of novel one-carbon assimilation pathways, Metab Eng 56 (2019) 142–153. https://www.ncbi.nlm.nih.gov/pubmed/31491544/
[53] Y. Li, X.J. Zhu, X.Y. Zhang, J. Fu, Z.W. Wang, T. Chen, X.M. Zhao, Characterization of genome-reduced Bacillus subtilis strains and their application for the production of guanosine and thymidine, Microb Cell Fact 15 (2016) 94. https://www.ncbi.nlm.nih.gov/pubmed/27260256/
[54] X.R. Jiang, X. Yan, L.P. Yu, X.Y. Liu, G.Q. Chen, Hyperproduction of 3-hydroxypropionate by Halomonas bluephagenesis, Nat Commun 12 (1) (2021) 1513. https://www.ncbi.nlm.nih.gov/pubmed/33686068/
[55] Y. Wang, L.T. Hu, H. Huang, H. Wang, T.M. Zhang, J. Chen, G.C. Du, Z. Kang, Eliminating the capsule-like layer to promote glucose uptake for hyaluronan production by engineered Corynebacterium glutamicum, Nat Commun 11 (1) (2020) 3120. https://www.ncbi.nlm.nih.gov/pubmed/32561727/
[56] T. Ma, B. Shi, Z.L. Ye, X.W. Li, M. Liu, Y. Chen, J. Xia, J. Nielsen, Z.X. Deng, T.G. Liu, Lipid engineering combined with systematic metabolic engineering of Saccharomyces cerevisiae for high-yield production of lycopene, Metab Eng 52 (2019) 134–142. https://www.ncbi.nlm.nih.gov/pubmed/30471360/
[57] R.Z. Tian, Y.F. Liu, Y.T. Cao, Z.J. Zhang, J.H. Li, L. Liu, G.C. Du, J. Chen, Titrating bacterial growth and chemical biosynthesis for efficient N-acetylglucosamine and N-acetylneuraminic acid bioproduction, Nat Commun 11 (1) (2020) 5078. https://www.ncbi.nlm.nih.gov/pubmed/33033266/
[58] W. Kang, T. Ma, M. Liu, J.L. Qu, Z.J. Liu, H.W. Zhang, B. Shi, S. Fu, J.C. Ma, L.T.F. Lai, S.C. He, J.N. Qu, S. Wing-Ngor Au, B. Ho Kang, W.C. Yu Lau, Z.X. Deng, J. Xia, T.G. Liu, Modular enzyme assembly for enhanced cascade biocatalysis and metabolic flux, Nat Commun 10 (1) (2019) 4248. https://www.ncbi.nlm.nih.gov/pubmed/31534134/
[59] W. Dessie, W.M. Zhang, F.X. Xin, W.L. Dong, M. Zhang, J.F. Ma, M. Jiang, Succinic acid production from fruit and vegetable wastes hydrolyzed by on-site enzyme mixtures through solid state fermentation, Bioresour Technol 247 (2018) 1177–1180. https://www.ncbi.nlm.nih.gov/pubmed/28941663/
[60] T.Y. Hu, J.W. Zhou, Y.R. Tong, P. Su, X.L. Li, Y. Liu, N. Liu, X.Y. Wu, Y.F. Zhang, J.D. Wang, L.H. Gao, L.C. Tu, Y. Lu, Z.Q. Jiang, Y.J. Zhou, W. Gao, L.Q. Huang, Engineering chimeric diterpene synthases and isoprenoid biosynthetic pathways enables high-level production of miltiradiene in yeast, Metab Eng 60 (2020) 87–96. https://www.ncbi.nlm.nih.gov/pubmed/32268192/
[61] J.S. Barrot, Research impact and productivity of Southeast Asian countries in language and linguistics, Scientometrics 110 (1) (2017) 1–15. http://dx.doi.org/10.1007/s11192-016-2163-3
[62] L.Q. Wen, Y. Lu, H. Li, S.Y. Long, J.Y. Li, Detecting of Research Front Topic in Artificial Intelligence Based on SciValProceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture. Manchester United Kingdom, 2020.
[63] D.M. Kochetkov, A correlation analysis of normalized indicators of citation, 2018, https://www.researchgate.net/publication/326735072_A_Correlation_Analysis_of_Normalized_Indicators_of_Citation/download.
[64] A. Purkayastha, E. Palmaro, H.J. Falk-Krzesinski, J. Baas, Comparison of two article-level, field-independent citation metrics: Field-Weighted Citation Impact (FWCI) and Relative Citation Ratio (RCR), J. Informetrics 13 (2) (2019) 635–642. http://dx.doi.org/10.1016/j.joi.2019.03.012
[65] M.K. Verma, R. Shukla, Mapping the research trends on information literacy of selected countries during 2008 2017 A scientometric analysis, DESIDOC Jl. Lib. Info. Technol. 39 (3) (2019) 125–130. https://doi.org/10.14429/djlit.39.3.14007
[66] C. Chen, T. Chen, Z.W. Wang, X.M. Zhao, A comparative analysis of China and other countries in metabolic engineering: Output, impact and collaboration, Chin. J. Chem. Eng. 30 (2021) 37–45. http://dx.doi.org/10.1016/j.cjche.2020.12.007
[67] E. Preuschl , M. Tampier , T. Schermer , A. Baca , Introduction of the relative activity index: Towards a fair method to score school children's activity using smartphones . Proceedings of the 10th International Symposium on Computer Science in Sports (ISCSS). Cham : Springer International Publishing , 2015 : 153 – 156
[68] M. Abbas, T. Robalo Nunes, R. Martischang, W. Zingg, A. Iten, D. Pittet, S. Harbarth, Nosocomial transmission and outbreaks of coronavirus disease 2019: the need to protect both patients and healthcare workers, Antimicrob Resist Infect Control 10 (1) (2021) 7. https://www.ncbi.nlm.nih.gov/pubmed/33407833/
[69] Q.S. Du, W. Hong, Y. Zu, Grant and funding for synthetic biology at NSFC from 2010 to 2019, Synth. Biol. J. 1 (2020) 385-394
[70] W.J. Zhang, Policy priorities of Japan's “Integrated Innovation Strategy 2019”, Scitech in China (2020) 102-104
[71] J.Y. Ma, F. Jiang, L.J. Gu, X. Zheng, X. Lin, C.Y. Wang, Patterns of the network of cross-border university research collaboration in the Guangdong-Hong Kong-Macao greater bay area, Sustainability 12 (17) (2020) 6846. https://doi.org/10.3390/su12176846
[72] T. Danino, A. Prindle, G.A. Kwong, M. Skalak, H. Li, K. Allen, J. Hasty, S.N. Bhatia, Programmable probiotics for detection of cancer in urine, Sci Transl Med 7 (289) (2015) 289ra84. https://www.ncbi.nlm.nih.gov/pubmed/26019220/
[73] R.H. Fang, A.V. Kroll, W.W. Gao, L.F. Zhang, Cell membrane coating nanotechnology, Adv. Mater. 30 (23) (2018) 1706759. https://doi.org/10.1002/adma.201706759
[74] M.A. Rudd, Scientists' perspectives on global ocean research priorities, Front. Mar. Sci. 1 (2014) 36
[75] J. Xu, A. Mills, 10 years of China's comprehensive health reform: a systems perspective, Health Policy Plan 34 (6) (2019) 403–406. https://www.ncbi.nlm.nih.gov/pubmed/31257418/
[76] Y.F. Wu, D.X. Yin, K. Abbasi, China's medical research revolution, BMJ 360 (2018) k547. https://www.ncbi.nlm.nih.gov/pubmed/29437660/
[77] B. Du?í , B. Frantál , M. Simon Rojo , The geography of urban agriculture: New trends and challenges, Morav , Geogr. Rep. 25 ( 3 ) ( 2017 ) 130 – 138
[78] S. Passel, E. Massetti, R. Mendelsohn, A ricardian analysis of the impact of climate change on European agriculture, Environ. Resour. Econ. 67 (4) (2017) 725–760. http://dx.doi.org/10.1007/s10640-016-0001-y
[79] H. Hottenrott, C. Lawson, A first look at multiple institutional affiliations: a study of authors in Germany, Japan and the UK, Scientometrics 111 (1) (2017) 285–295. https://www.ncbi.nlm.nih.gov/pubmed/28386152/
[80] L.J. Sweetlove, A.R. Fernie, The role of dynamic enzyme assemblies and substrate channelling in metabolic regulation, Nat. Commun. 9 (1) (2018) 1–12. http://dx.doi.org/10.1038/s41467-018-04543-8
[81] Z.N. Chen, Frontiers and Innovation of biomedicine in the new era, China Food & Drug Administration Magazine 11 (2019) 8-13
[82] P.M. Davis, Reward or persuasion? The battle to define the meaning of a citation, Learn. Pub. 22 (1) (2009) 5–11. https://doi.org/10.1087/095315108x378712
[83] D. Chicco, G. Jurman, The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation, BMC Genomics 21 (1) (2020) 6. https://www.ncbi.nlm.nih.gov/pubmed/31898477/
[84] M.B. Gawande, A. Goswami, T. Asefa, H.Z. Guo, A.V. Biradar, D.L. Peng, R. Zboril, R.S. Varma, Core-shell nanoparticles: synthesis and applications in catalysis and electrocatalysis, Chem Soc Rev 44 (21) (2015) 7540–7590. https://www.ncbi.nlm.nih.gov/pubmed/26288197/
[85] C.S. Wagner, T.A. Whetsell, S. Mukherjee, International research collaboration: Novelty, conventionality, and atypicality in knowledge recombination, Res. Policy 48 (5) (2019) 1260–1270. http://dx.doi.org/10.1016/j.respol.2019.01.002
[86] R.K. Pan, K. Kaski, S. Fortunato, World citation and collaboration networks: uncovering the role of geography in science, Sci Rep 2 (2012) 902. https://www.ncbi.nlm.nih.gov/pubmed/23198092/
[87] J. Adams, The rise of research networks, Nature 490 (7420) (2012) 335–336. http://dx.doi.org/10.1038/490335a
[88] A.A. Cheng, T.K. Lu, Synthetic biology: an emerging engineering discipline, Annu Rev Biomed Eng 14 (2012) 155–178. https://www.ncbi.nlm.nih.gov/pubmed/22577777/
[89] S.L. Greer, B. Trump, Regulation and regime: the comparative politics of adaptive regulation in synthetic biology, Policy Sci. 52 (4) (2019) 505–524. http://dx.doi.org/10.1007/s11077-019-09356-0
[90] S.Y. Sun, Z. Xie, K.T. Yu, B.Q. Jiang, S.W. Zheng, X.T. Pan, COVID-19 and healthcare system in China: challenges and progression for a sustainable future, Global Health 17 (1) (2021) 14. https://www.ncbi.nlm.nih.gov/pubmed/33478558/
[91] A.K. Singh, G.M. Kishore, H.B. Pakrasi, Emerging platforms for co-utilization of one-carbon substrates by photosynthetic organisms, Curr Opin Biotechnol 53 (2018) 201–208. https://www.ncbi.nlm.nih.gov/pubmed/29510332/

An international comprehensive benchmarking analysis of synthetic biology in China from 2015 to 2020

An international comprehensive benchmarking analysis of synthetic biology in China from 2015 to 2020

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 13

编辑推荐

Metrics

本文评价

[1]	Xueying Zhu, Zhaoyang Zhang, Bin Jia, Yingjin Yuan. Current advances of biocontainment strategy in synthetic biology[J]. 中国化学工程学报, 2023, 56(4): 141-151.
[2]	Chao Zhang, Huifang Xing, Liangrong Yang, Pengfei Fei, Huizhou Liu. Development trend and prospect of solid phase extraction technology[J]. 中国化学工程学报, 2022, 42(2): 245-255.
[3]	Wenqiang Li, Wentao Sun, Chun Li. Engineered microorganisms and enzymes for efficiently synthesizing plant natural products[J]. 中国化学工程学报, 2021, 29(2): 62-73.
[4]	Cong Chen, Tao Chen, Zhiwen Wang, Xueming Zhao. A comparative analysis of China and other countries in metabolic engineering: Output, impact and collaboration[J]. 中国化学工程学报, 2021, 29(2): 37-45.
[5]	Yanfeng Liu, Xiaomin Dong, Bin Wang, Rongzhen Tian, Jianghua Li, Long Liu, Guocheng Du, Jian Chen. Food synthetic biology-driven protein supply transition: From animal-derived production to microbial fermentation[J]. 中国化学工程学报, 2021, 29(2): 29-36.
[6]	Yang Zhang, Jing Yu, Yilu Wu, Mingda Li, Yuxuan Zhao, Haowen Zhu, Changjing Chen, Meng Wang, Biqiang Chen, Tianwei Tan. Efficient production of chemicals from microorganism by metabolic engineering and synthetic biology[J]. 中国化学工程学报, 2021, 29(2): 14-28.
[7]	Nan Jiang, Lianju Ma, Yuan Lu. Cell-free synthetic biology in the new era of enzyme engineering[J]. 中国化学工程学报, 2020, 28(11): 2810-2816.
[8]	Xinlei Wei, Pingping Han, Chun You. Facilitation of cascade biocatalysis by artificial multi-enzyme complexes—A review[J]. 中国化学工程学报, 2020, 28(11): 2799-2809.
[9]	Xingxing Li, Jiageng Li, Bolun Yang, Yong Zhang. Dynamic analysis on methanation reactor using a double-input-multi-output linearized model[J]. , 2015, 23(2): 389-397.
[10]	Shijian Dong, Tao Liu, Mingzhong Li, Yi Cao. Iterative identification of output error model for industrial processes with time delay subject to colored noise[J]. Chinese Journal of Chemical Engineering, 2015, 23(12): 2005-2012.
[11]	Weiming Shao, Xuemin Tian, Ping Wang. Local Partial Least Squares Based Online Soft Sensing Method for Multi-output Processes with Adaptive Process States Division[J]. , 2014, 22(7): 828-836.
[12]	张燕, 梁秀霞, 杨鹏, 陈增强, 袁著祉. Modeling and Control of Nonlinear Discrete-time Systems Based on Compound Neural Networks[J]. , 2009, 17(3): 454-459.
[13]	傅永峰, 苏宏业, 褚健. 基于混合建模技术的复合肥养分含量MIMO软测量模型[J]. , 2007, 15(4): 554-559.