# Temporally scalable recording of brain-wide single-cell physiology

> **NIH NIH DP2** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $1,345,424

## Abstract

Abstract
Many fundamental questions in neuroscience and neurological disorders, such as those associated with
learning, memory, sleep, aging, and disease progression, would benefit greatly from a technology that enables
brain-wide single-cell readout of signaling activities and gene expression changes over extended time periods
(over weeks, months, to even years). Current single-cell physiology recording methods require external
interfacing to live cells, either optically (via fluorescent probes plus microscopy) or electrically (via electrical
probes). It has been a major challenge to perform long-term optical imaging in vivo beyond several hours, due
to fast photobleaching of fluorescent probes. Electrical probes, on the other hand, often induce unwanted long-
term immune response after implantation and do not support measurement of intracellular signaling and gene
expression activities. In addition, these single-cell recording methods do not support large-scale readout
across the whole brain, while modalities that can image whole brains, such as ultrasound, MRI, and CT, lack
single-cell resolutions. We aim to bridge this technological gap by developing a genetically encoded,
temporally scalable ‘protein ticker tape’ recording system, to enable long-term, brain-wide recording of single-
cell physiology in vivo without any external interfacing to live cells. In our prior work, we found it is possible to
record and store cell physiology histories over time, such as gene expression histories, along elongating
protein self-assemblies in live cells (analogous to tree rings permanently storing wood’s growth conditions), for
subsequent single-cell readout in situ via simple post-mortem tissue processing and imaging techniques. In
this project, we will leverage our expertise in protein engineering and neurotechnology development to
transform this protein ticker tape concept into a technological solution that enables brain-wide single-cell
physiology recording over long (up to a year) and scalable periods of time, where the recording duration is
externally defined by users. We will first engineer novel protein assemblies, via an AI-powered protein design
approach, to boost the information storage capacity and recording precision of protein ticker tapes. Next, we
will employ chemical and light dependent expression systems to externally control the elongation speed of the
protein self-assembly, to enable various recording durations (from a day to a year) externally defined by users.
Finally, we will couple protein ticker tapes to promoters and synthetic expression systems that respond to
signaling events, transcription factor activities, circadian rhythms, and gene expression levels, to enable
recording of these cell physiological events separately and in parallel. We will genetically deliver these protein
ticker tapes in single cells across living mouse brains to characterize and validate their performance, fidelity,
and safety to cells and tissue, follow...

## Key facts

- **NIH application ID:** 10907260
- **Project number:** 1DP2MH140133-01
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Changyang Linghu
- **Activity code:** DP2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $1,345,424
- **Award type:** 1
- **Project period:** 2024-09-10 → 2027-09-09

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10907260

## Citation

> US National Institutes of Health, RePORTER application 10907260, Temporally scalable recording of brain-wide single-cell physiology (1DP2MH140133-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10907260. Licensed CC0.

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