# Highly multiplexed single-cell proteomics

> **NIH NIH R21** · UNIVERSITY OF PENNSYLVANIA · 2020 · $184,840

## Abstract

PROJECT SUMMARY/ABSTRACT
Single-cell analysis of cell states carries tremendous potential for biological inquiry and biomedical
applications. For example, a cell's functional state may explain heterogeneous cell responses to environmental
ligands or to drugs, while an accurate catalog of the heterogeneous cell states in a tumor may ultimately
prevent incomplete drug response and drug resistance development. Although current sequencing methods
(i.e. scRNA-seq) offer transcriptional signatures of single cells, a cell's functional state is more accurately
described by its proteomic signature, for which the transcriptome is only weakly predictive. However, there are
no methods to measure single cell proteomes with comparable sensitivity and throughput to scRNAseq
because proteins cannot be amplified and sequenced like nucleic acids. Our long-term goal is to address this
gap through developing scProteome-seq, a technology to quantify 102-103 proteins and post-translational
modifications (PTMs) from ~104-105 individual cells simultaneously. scProteome-seq achieves specificity in
protein detection because it first uses single-cell western blots (scWesterns) to separate a cell's protein content
by size in a sieving gel prior to antibody probing. Sensitivity and high-throughput analysis are achieved via
separate DNA barcodes encoding a protein's location (encoding protein size and cell ID) and identity (encoding
antibody identity). The two barcodes are linked, extracted, and subsequently quantified by PCR amplification
and sequencing. In this proposal, we address the feasibility of key technological challenges to this approach in
two aims. In Aim 1, we engineer methods to spatially barcode scWestern separations gels with DNA. First,
strategies for printing and covalently attaching DNA onto gels will be developed and analyzed for efficiency and
spatial resolution. Second, DNA-modified scWestern gels will be validated for separations performance
compared to unmodified gels. In Aim 2, we develop the barcoding strategy for scProteome-seq. Barcode
sequences will be designed to enable physical coupling, gel-extraction, and amplification. Specificity and
efficiency of coupling will be optimized, and protocols for barcoding, coupling, extraction, and analysis will be
developed. Successful completion of these aims will form the foundation for full-scale development,
quantitative characterization, and ultimate deployment of scProteome-seq. We anticipate that proteomic
fingerprinting of cell states will provide significant technical advances applicable across a broad range of
fundamental and translational biomedical disciplines.

## Key facts

- **NIH application ID:** 9968291
- **Project number:** 5R21GM132831-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Lukasz Bugaj
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $184,840
- **Award type:** 5
- **Project period:** 2019-07-01 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9968291

## Citation

> US National Institutes of Health, RePORTER application 9968291, Highly multiplexed single-cell proteomics (5R21GM132831-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9968291. Licensed CC0.

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