# Megaplexed Neuronal Visualization Using Combinatorial Labeling and Iterative Staining

> **NIH NIH R01** · HARVARD UNIVERSITY · 2021 · $444,150

## Abstract

Project Summary
Neurons are organized within cellular circuits which give rise to all brain activity. An anatomical understanding
of neuronal architecture is crucial to figuring out how the brain processes information. Commonly, the
visualization of neurons has relied on labeling with different colored fluorescent proteins in order to distinguish
one from another, however a major limitation of this approach is the low diversity of colors that are available.
Because neurons can project over long distance and along complex paths, many overlapping cells will be
indistinguishable from one another when a small color palette is used. We propose technology which decouples
labelling diversity from the limitation of dye colors. We propose labeling each cell with a combination of peptides
rather than a single dye and performing iterative immunofluorescence staining which can re-use colors. Using
this technology, we will create over one million discernable labels which will be used to map the location of an
unprecedented number of cells within brain tissue.
We will perform proof of concept studies on cell lines using standard plasmid preparation and transfection
techniques (Aim 1). Next we will pursue two viral strategies to genetically label neurons (Aim 2). We will
encode peptide combinations within replication-deficient Sindbis vectors which can infect neurons rapidly and
induce high levels of peptide expression and also engineer adeno associated viruses (AAV) to deliver labels
because AAV can be administered systemically and selectively target neuronal subtypes. Together, these tools
will be used to map, in three dimensions, an entire viral injection volume (Aim 3). It is expected that the
technology developed from this proposal will have a drastic impact on cellular labelling and brain connectomics.

## Key facts

- **NIH application ID:** 10129442
- **Project number:** 5R01NS112716-02
- **Recipient organization:** HARVARD UNIVERSITY
- **Principal Investigator:** Richard E Kohman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $444,150
- **Award type:** 5
- **Project period:** 2020-04-01 → 2022-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10129442

## Citation

> US National Institutes of Health, RePORTER application 10129442, Megaplexed Neuronal Visualization Using Combinatorial Labeling and Iterative Staining (5R01NS112716-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10129442. Licensed CC0.

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