Xu Wang1,2*- 1Cancer Research Institute, Pancreatic Cancer Institute, Fudan University Shanghai Cancer Center, Shanghai, China
- 2Shanghai Pancreatic Cancer Institute, Shanghai Key Laboratory of Radiation Oncology, Fudan University, Shanghai, China
Editorial on the Research Topic
Synthetic biology in Vertebrate Model system: New clinical and preclinical translational applications
Synthetic biology represented the conceptual and technological merging of life science with engineering and information science, with the goal of enabling scientists to rationally create, design, and manipulate life with programmable functions. For more than half a century, the typical chassis cells of synthetic biology were E. coli and S. cerevisiae, and many synthetic circuits have been developed and poised to transform those cells into productive tools in the biotechnology and medicine industry (Cameron et al., 2014). However, the field of synthetic biology has expanded rapidly in the past decade (Meng and Ellis, 2020), and vertebrate cells including human cells have become novel platforms for integrating synthetic technologies, including genome editing (Shalem et al., 2014), light/chemical-sensing circuitry (Deisseroth, 2011), ligand/antigen-controlled circuitry (Morsut et al., 2016; Melenhorst et al., 2022), multi-unit transgenesis (Cai et al., 2013), etc. As time goes on, the current boarder of synthetic biology field becomes vague, and synthetic technologies are present across multiple aspects of biomedical research.
Here we gathered several experts in synthetic biology as the editorial group, Wang Yongming’s laboratory was dedicated to the optimization of gene editing technologies, and have developed several novel tools including SlugCas9 (Hu et al., 2021) and SchCas9 (Wang et al., 2022) for potential applications in gene therapy. Zhao Yuzhen’s laboratory has developed several artificial and genetically encoded fluorescent sensors, including NAD+/NADH sensors, to reveal metabolic dynamics in living model organisms (Zhao et al., 2015; Zou et al., 2020). In my laboratory, we have generated several transgenic vertebrate cancer models using synthetic sequences, which were composed of multiple regulatory units like “LeGo” blocks (Yao et al., 2018; Fei et al., 2019; Fei et al., 2021). We also employed ligand-controlled synNotch receptor and antigen-recognizing CAR receptor to engineer human T cells, which were programmed to attack human cancer cells or animal cells expressing human cancer antigens (Wang et al., 2021). In addition, we designed double-humanized animal models carrying semi-immortalized primary xenografts, and aligned the models in three-dimensional printed chips, followed by automatic drug screening and high-throughput imaging analysis, as a proof of concept combining both synthetic animal models and customer-made abiotic structures (Wu et al., 2023). Together, these experiences formed the original idea for this topic, in which we hoped to include a diversity of synthetic elements from different research backgrounds.
In the research topic, Wang Zhu’s laboratory reviewed their progress in using multi-target CRISPR/Cas9 technology to generate animal models of prostatitis and prostate cancer (PCa), and employing synthetic circuits to genetically trace the cell-of-origin of PCa (Bleeker et al.), representing the application of synthetic cellular/genetic circuits in vertebrate systems. Another work combined GBM cell culture with biocompatible elastic materials to build a synthetic encephaloid model for brain stiffness mimicking and drug screening, representing the contribution of abiotic materials to the engineering and modeling of complex biological systems (Wang et al.). Beyond this topic, other researchers may pick up these synthetic blocks and make their own synthetic models for different purposes and applications.
In general, engineering of synthetic biology in vertebrate systems remains challenging, including multiple levels of regulation, fluid cell fate determination, and complex multicellular interactions. Nevertheless, the current elements of synthetic biology have formed a foundation or library for studying the spatiotemporal dynamics of diseases and for developing relevant diagnostic or therapeutic approaches, and we are looking forward to much more significant progress in their clinical and preclinical translational applications.
Author contributions
XW contributed to conception and writing of this editorial.
Funding
This work was supported by National Natural Science Foundation of China 81402582 and 82172884, and Shanghai Natural Science Foundation 18ZR1404500.
Conflict of interest
The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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References
Bleeker, J., and Wang, Z. A. (2022). Applications of vertebrate models in studying prostatitis and inflammation-associated prostatic diseases. Front. Mol. Biosci. 9, 898871. doi:10.3389/fmolb.2022.898871
Cai, D., Cohen, K. B., Luo, T., Lichtman, J. W., and Sanes, J. R. (2013). Improved tools for the Brainbow toolbox. Nat. Methods 10 (6), 540–547. doi:10.1038/nmeth.2450
Cameron, D. E., Bashor, C. J., and Collins, J. J. (2014). A brief history of synthetic biology. Nat. Rev. Microbiol. 12 (5), 381–390. doi:10.1038/nrmicro3239
Fei, F., Sun, S., Li, Q., Pei, Z., Wang, L., Zhang, R., et al. (2021). Combinatorial normalization of liver-derived cytokine pathways alleviates hepatic tumor-associated cachexia in zebrafish. Cancer Res. 81 (4), 873–884. doi:10.1158/0008-5472.CAN-20-2818
Fei, F., Wang, L., Sun, S., Lv, K., Yao, Y., Wang, J., et al. (2019). Transgenic strategies to generate heterogeneous hepatic cancer models in zebrafish. J. Mol. Cell Biol. 11 (11), 1021–1023. doi:10.1093/jmcb/mjz083
Hu, Z., Zhang, C., Wang, S., Gao, S., Wei, J., Li, M., et al. (2021). Discovery and engineering of small SlugCas9 with broad targeting range and high specificity and activity. Nucleic Acids Res. 49 (7), 4008–4019. doi:10.1093/nar/gkab148
Melenhorst, J. J., Chen, G. M., Wang, M., Porter, D. L., Chen, C., Collins, M. A., et al. (2022). Decade-long leukaemia remissions with persistence of CD4(+) CAR T cells. Nature 602 (7897), 503–509. doi:10.1038/s41586-021-04390-6
Meng, F., and Ellis, T. (2020). The second decade of synthetic biology: 2010-2020. Nat. Commun. 11 (1), 5174. doi:10.1038/s41467-020-19092-2
Morsut, L., Roybal, K. T., Xiong, X., Gordley, R. M., Coyle, S. M., Thomson, M., et al. (2016). Engineering customized cell sensing and response behaviors using synthetic notch receptors. Cell 164 (4), 780–791. doi:10.1016/j.cell.2016.01.012
Shalem, O., Sanjana, N. E., Hartenian, E., Shi, X., Scott, D. A., Mikkelson, T., et al. (2014). Genome-scale CRISPR-Cas9 knockout screening in human cells. Science 343 (6166), 84–87. doi:10.1126/science.1247005
Wang, L., Long, J., Chen, H., Sun, S., Lv, K., Li, Q., et al. (2021). Manipulation of focal Wnt activity via synthetic cells in a double-humanized zebrafish model of tumorigenesis. Int. J. Cancer 148 (11), 2815–2824. doi:10.1002/ijc.33458
Wang, S., Mao, H., Hou, L., Hu, Z., Wang, Y., Qi, T., et al. (2022). Compact SchCas9 recognizes the simple NNGR PAM. Adv. Sci. (Weinh) 9 (4), e2104789. doi:10.1002/advs.202104789
Wu, C., Hu, B., Wang, L., Wu, X., Gu, H., Dong, H., et al. (2023). Assessment of stromal SCD-induced drug resistance of PDAC using 3D-printed zPDX model chips. iScience 26 (1), 105723. doi:10.1016/j.isci.2022.105723
Yao, Y., Sun, S., Wang, J., Fei, F., Dong, Z., Ke, A. W., et al. (2018). Canonical wnt signaling remodels lipid metabolism in zebrafish hepatocytes following ras oncogenic insult. Cancer Res. 78 (19), 5548–5560. doi:10.1158/0008-5472.CAN-17-3964
Zhao, Y., Hu, Q., Cheng, F., Su, N., Wang, A., Zou, Y., et al. (2015). SoNar, a highly responsive NAD+/NADH sensor, allows high-throughput metabolic screening of anti-tumor agents. Cell Metab. 21 (5), 777–789. doi:10.1016/j.cmet.2015.04.009
Keywords: synthetic biology, vertebrate model, biology circuit, non-biological structure, cell therapy
Citation: Wang X (2023) Editorial: Synthetic biology in Vertebrate Model system: New clinical and preclinical translational applications. Front. Mol. Biosci. 10:1117896. doi: 10.3389/fmolb.2023.1117896
Received: 07 December 2022; Accepted: 30 January 2023;
Published: 03 February 2023.
Edited and reviewed by:
William C. Cho, QEH, Hong Kong SAR, ChinaCopyright © 2023 Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Xu Wang, wangxu2013@fudan.edu.cn