Synthetic protein circuits for programmable control of mammalian cell death

Creators: Xia, Shiyu; Lu, Andrew C.; Tobin, Victoria; Luo, Kaiwen; Moeller, Lukas; Shon, D. Judy; Du, Rongrong; Linton, James M.; Sui, Margaret; Horns, Felix; Elowitz, Michael B.¹

1. California Institute of Technology

Abstract

Natural cell death pathways such as apoptosis and pyroptosis play dual roles: they eliminate harmful cells and modulate the immune system by dampening or stimulating inflammation. Synthetic protein circuits capable of triggering specific death programs in target cells could similarly remove harmful cells while appropriately modulating immune responses. However, cells actively influence their death modes in response to natural signals, making it challenging to control death modes. Here, we introduce naturally inspired “synpoptosis” circuits that proteolytically regulate engineered executioner proteins and mammalian cell death. These circuits direct cell death modes, respond to combinations of protease inputs, and selectively eliminate target cells. Furthermore, synpoptosis circuits can be transmitted intercellularly, offering a foundation for engineering synthetic killer cells that induce desired death programs in target cells without self-destruction. Together, these results lay the groundwork for programmable control of mammalian cell death.

Copyright and License

Acknowledgement

We thank Hao Wu, Zhibin Zhang, Carlos Lois, Zibo Chen, Xiaojing Gao, Charles Evavold, Edward Miao, Cornelius Taabazuing, and Tian-Min Fu for discussion; Jacob Parres-Gold, Dongyang Li, Bo Gu, Sheng Wang, Leah Santat, Jo Leonardo, and all other members of the Elowitz lab for critical feedback and administrative support; Liam Healy, Pietro Fontana, Bingfei Yu, Florian Schmidt, and Mikhail Shapiro for sharing experimental materials; and Inna-Marie Strazhnik for graphical design. This work is supported by the National Institutes of Health grant R01EB030015, Caltech Rothenberg Innovation Initiative grant 25570017, and the Howard Hughes Medical Institute. S.X. is supported by the Jane Coffin Childs Memorial Fund for Medical Research and the Joan A. Steitz Fund. A.C.L. is supported by the Paul and Daisy Soros Fellowship for New Americans and the Taiwanese Ministry of Education. V.T. is supported by the National Institutes of Health F30 fellowship 1F30OD036190-01. M.S. received a Fulbright Scholarship and a Caltech Susan D. Murakami Summer Undergraduate Research Fellowship. F.H. is supported by the Helen Hay Whitney Foundation, the Caltech Chen Postdoctoral Fellowship, and the Burroughs Wellcome Fund. M.B.E. is a Howard Hughes Medical Institute Investigator. We sincerely apologize for incomplete citations due to the interdisciplinary nature of this work.

Contributions

S.X. and M.B.E. conceived and designed the study. M.B.E. directed and supervised the study. S.X., A.C.L., V.T., K.L., L.M., D.J.S., R.D., J.M.L., M.S., and F.H. performed or assisted with experiments and analyzed data. S.X. and M.B.E. wrote the manuscript with input from all authors.

Conflict of Interest

A patent application related to this work has been filed by the California Institute of Technology. M.B.E. is a scientific advisory board member or consultant at TeraCyte, Primordium, and Spatial Genomics.

Additional Information

During the preparation of this work, the authors used ChatGPT (version 4, OpenAI) to assist with figure plotting using the Jupyter Notebook (jupyter.org). After using ChatGPT, the authors thoroughly reviewed and edited the content as needed. The authors take full responsibility for the content of the publication.

Files

1-s2.0-S0092867424003477-main.pdf

Files (7.3 MB)

	All versions	This version
Views	0	0
Downloads	1	1
Data volume	7.3 MB	7.3 MB