# Development of Single-Cell Multiplex in Situ Tagging Microtechnology for Comprehensive Profiling of Functionally Diverse Subpopulations and Their Signaling Pathways

> **NIH NIH R01** · STATE UNIVERSITY NEW YORK STONY BROOK · 2021 · $312,274

## Abstract

Project Summary
Recent studies based on single-cell analysis have underscored a far greater diversity of cells within a tissue
ecosystem than suspected. Subsets of cells have frequently been found to be critical in the onset and
progression of a wide range of systemic diseases. The advent of next-generation sequencing techniques
makes single-cell genomics and single-cell transcriptomics broadly accessible. However, no equivalent
platform is available yet for investigating single-cell functional proteomics. It has been well known for decades
that functional proteins are essential for most cellular processes, and they are widely used as phenotyping
markers and drug targets. The current state-of-the-art single-cell protein profiling tools only measure dozens of
proteins per cell, which is not enough to cover the wide spectrum of the functional proteome. We have recently
innovated a multiplex in situ tagging (MIST) technique based on a compact monolayer of DNA-encoded
microparticles through successive rounds of labeling and imaging. This technique can easily achieve a
multiplexity of tens of thousands using a common fluorescence microscope and a simple procedure that can
be executed in a typical biological laboratory setting. Our preliminary data show that the MIST array covers an
area ~10,000 times smaller than the prevailing microarray, without compromising high sensitivity at ~100
molecules per cell. The MIST array will be integrated with our portable stand-sit microchip that can handle
primary cell samples and make proteins in single cells available for analysis. The three aims we propose
include: (1) Create an integrated technology combining MIST with stand-sit microchip for highly multiplexed
analysis of functional proteins in >10,000 single cells; (2) Validate our technology by quantifying 150 signaling
proteins and surface markers from mouse primary peripheral blood mononuclear cells; and (3) Develop a
framework for data analysis to visualize high-dimensional data, classify cell subtypes by both functions and
phenotypes, and determine the signaling networks of each subtype. To the end, we will have a robust,
inexpensive, and user-friendly single-cell functional proteomic tool that can routinely measure ~100-1,000
proteins per cell with a high sensitivity and a high throughput. This project will enable the implementation of
single-cell functional proteomics as a common tool in the broader biomedical community. The application of
this technology will generate influential results as single-cell transcriptomics does to the biomedical sciences.

## Key facts

- **NIH application ID:** 10167730
- **Project number:** 5R01GM128984-05
- **Recipient organization:** STATE UNIVERSITY NEW YORK STONY BROOK
- **Principal Investigator:** Jun Wang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $312,274
- **Award type:** 5
- **Project period:** 2018-08-01 → 2023-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10167730

## Citation

> US National Institutes of Health, RePORTER application 10167730, Development of Single-Cell Multiplex in Situ Tagging Microtechnology for Comprehensive Profiling of Functionally Diverse Subpopulations and Their Signaling Pathways (5R01GM128984-05). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10167730. Licensed CC0.

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