Recording of cellular physiological histories along optically readable self-assembling protein chains
Author(s)
Linghu, Changyang; An, Bobae; Shpokayte, Monika; Celiker, Orhan T; Shmoel, Nava; Zhang, Ruihan; Zhang, Chi; Park, Demian; Park, Won Min; Ramirez, Steve; Boyden, Edward S; ... Show more Show less
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<jats:title>Abstract</jats:title><jats:p>Observing cellular physiological histories is key to understanding normal and disease-related processes. Here we describe expression recording islands—a fully genetically encoded approach that enables both continual digital recording of biological information within cells and subsequent high-throughput readout in fixed cells. The information is stored in growing intracellular protein chains made of self-assembling subunits, human-designed filament-forming proteins bearing different epitope tags that each correspond to a different cellular state or function (for example, gene expression downstream of neural activity or pharmacological exposure), allowing the physiological history to be read out along the ordered subunits of protein chains with conventional optical microscopy. We use expression recording islands to record gene expression timecourse downstream of specific pharmacological and physiological stimuli in cultured neurons and in living mouse brain, with a time resolution of a fraction of a day, over periods of days to weeks.</jats:p>
Date issued
2023-01-02Department
Massachusetts Institute of Technology. Department of Brain and Cognitive SciencesJournal
Nature Biotechnology
Publisher
Springer Science and Business Media LLC
Citation
Linghu, Changyang, An, Bobae, Shpokayte, Monika, Celiker, Orhan T, Shmoel, Nava et al. 2023. "Recording of cellular physiological histories along optically readable self-assembling protein chains." Nature Biotechnology.
Version: Final published version