Scalable and multiplexed recorders of gene regulation dynamics across weeks
TL;DR
CytoTape is a genetically encoded protein recorder enabling multiplexed, spatiotemporal tracking of gene regulation dynamics for up to three weeks in single cells. It records multiple transcription factors and gene activities, with applications extended to in vivo brain studies.
Key Takeaways
- •CytoTape allows continuous, multiplexed recording of gene regulation dynamics with single-cell resolution over weeks.
- •It can simultaneously track up to five transcription factor activities and gene transcriptional activities in mammalian cells.
- •The technology reveals correlations between transcriptional trajectories, history, and signal integration in single cells.
- •CytoTape-vivo extends this capability to in vivo brain studies, recording gene expression histories across thousands of neurons.
- •The toolkit provides a scalable platform for analyzing cell physiological processes both in vitro and in vivo.
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Abstract
Gene expression is dynamically regulated by gene regulatory networks comprising multiple regulatory components to mediate cellular functions1. An ideal tool for analyzing these processes would track multiple-component dynamics with both spatiotemporal resolution and scalability within the same cells, a capability not yet achieved. Here, we present CytoTape, a genetically encoded, modular protein tape recorder for multiplexed and spatiotemporally scalable recording of gene regulation dynamics continuously for up to three weeks, physiologically compatible, with single-cell, minutes-scale resolution. CytoTape employs a flexible, thread-like, elongating intracellular protein self-assembly engineered via computationally assisted rational design, built on earlier XRI technology2. We demonstrated its utility across multiple mammalian cell types, achieving simultaneous recording of five transcription factor activities and gene transcriptional activities. CytoTape reveals that divergent transcriptional trajectories correlate with transcriptional history and signal integration, and that distinct immediate early genes (IEGs) exhibit complex temporal correlations within single cells. We further extended CytoTape into CytoTape-vivo for scalable, spatiotemporally resolved single-cell recording in the living brain, enabling simultaneous weeks-long recording of doxycycline- and IEG promoter-dependent gene expression histories across up to 14,123 neurons spanning multiple brain regions per mouse. Together, the CytoTape toolkit establishes a versatile platform for scalable and multiplexed analysis of cell physiological processes in vitro and in vivo.
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Author information
These authors contributed equally: Lirong Zheng, Dongqing Shi, Yixiao Yan
Authors and Affiliations
Department of Cell and Developmental Biology, Medical School, University of Michigan, Ann Arbor, MI, USA
Lirong Zheng, Dongqing Shi, Yixiao Yan, Jormay Lim, Yongjie Hou, William C. Joesten, Mehul Gautam & Changyang Linghu
Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA
Lirong Zheng, Dongqing Shi, Yixiao Yan, Jormay Lim, Yongjie Hou, William C. Joesten, Mehul Gautam & Changyang Linghu
Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
Bingxin Zhou & Pietro Liò
McGovern Institute for Brain Research and Departments of Brain and Cognitive Sciences, Media Arts and Sciences, and Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
Bobae An, Eung Chang Kim & Edward S. Boyden
Department of Computer Science, Boston College, Boston, MA, USA
Jason K. Adhinarta, Michael Lin & Donglai Wei
Nash Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
BumJin Ko & Denise J. Cai
Kresge Hearing Research Institute and Department of Otolaryngology-Head and Neck Surgery, University of Michigan, Ann Arbor, MI, USA
Elie D. M. Huez & Michael T. Roberts
Department of Chemistry, University of Michigan, Ann Arbor, MI, USA
Emily G. Klyder
Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, USA
Boxuan Chang
Departments of Urology and Pathology, University of Michigan, Ann Arbor, MI, USA
Sethuramasundaram Pitchiaya
Yang Tan Collective and Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
Edward S. Boyden
Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA
Changyang Linghu
- Lirong Zheng
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- Dongqing Shi
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- Yixiao Yan
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- Bingxin Zhou
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- Jormay Lim
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- Yongjie Hou
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- Bobae An
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- Jason K. Adhinarta
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