Scalable and multiplexed recorders of gene regulation dynamics across weeks.
Published version
Peer-reviewed
Repository URI
Repository DOI
Type
Change log
Authors
Abstract
Gene expression is dynamically controlled by gene regulatory networks comprising multiple regulatory components to mediate cellular functions1. An ideal tool for analysing these processes would track multi-component dynamics with both spatiotemporal resolution and scalability within the same cells, a capability not yet achieved. Here we present CytoTape, a genetically encoded, physiologically compatible, modular protein tape recorder for multiplexed and spatiotemporally scalable recording of gene regulation dynamics continuously for up to 3 weeks, with single-cell, up to minutes-scale resolution. CytoTape uses a flexible, thread-like, elongating intracellular protein self-assembly engineered via computationally assisted rational design, built on our earlier XRI technology2. We demonstrate 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-dependent 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.
Description
Acknowledgements: We thank D. Cable, D. Cai, W. Dong, J. Dudley, F. Levet, C. Ma, W. Wang, M. Widener, J. Yang and B. Ye for discussion. L.Z. thanks the Michigan Neuroscience Institute Postdoctoral Advancement Program and the eLife Ambassadors Program. M.L. and D.W. acknowledge NSF-IIS-2239688. E.S.B. acknowledges National Institutes of Health (NIH) 1R01EB024261, R01AG087374, 1R01AG070831 and R01MH122971, L. Yang and the Howard Hughes Medical Institute. C.L. is supported by the NIH Director’s New Innovator Award (DP2MH140133), the Glenn Foundation for Medical Research and American Federation for Aging Research Grant Award for Junior Faculty, the Whitehall Foundation and the Klingenstein Fellowship Award in Neuroscience. C.L. and D.J.C. are supported by the Chan Zuckerberg Initiative Collaborative Pairs Pilot Project Award.
Keywords
Journal Title
Conference Name
Journal ISSN
1476-4687

