# A biochemical approach towards subcellular, label-free molecular imaging

> **NIH NIH DP2** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2023 · $1,372,964

## Abstract

ABSTRACT
Mass spectrometry-based spatial analysis has enabled label-free investigation of a broad range of endogenous
biomolecules—lipids, peptides/proteins, metabolites, and glycans—in intact biological and clinical specimens.
Rapid development in this area has contributed enormously to the current spatial omics research. However,
the routine spatial resolution of MALDI-based mass spectrometry imaging, arguably one of the most widely
used mass spectrometry imaging techniques today, is about tens of micrometers on a conventional mass
spectrometer. This resolution limit imposes a roadblock towards label-free analyses of specimens at single-cell
or subcellular level in existing mass spectrometry laboratories.
Recent development of expansion microscopy has seen considerable success in generating fluorescence
images of biological structures beyond the intrinsic spatial resolution of an optical system. Such capability has
led to democratization of super-resolution fluorescence microscopy in biological and clinical laboratories.
However, current expansion microscopy protocols and chemistries are not compatible with mass spectrometry
imaging or analyses.
The main objective of this proposal is to establish a biochemical process of sample expansion to push the
spatial resolution of existing mass spectrometry imaging pipelines to the subcellular regime, namely, to a few
micrometers and beyond. Towards this goal, we will develop a sample polymerization and digestion protocol
optimized for mass spectrometry imaging, in which the endogenous lipids and proteins are tethered to a
swelling polymer network and can be subsequently analyzed on a MALDI mass spectrometer. Our
experimental approaches include (1) development of a biochemical pipeline of tissue polymerization and
expansion for lipid mass spectrometry imaging; (2) extension of the pipeline to multiplexed lipid and protein
detection and imaging. Successful completion of this proposal will provide the community with a label-free,
subcellular-resolution molecular imaging modality without modifying the existing instrumentation.

## Key facts

- **NIH application ID:** 10686627
- **Project number:** 1DP2MH136390-01
- **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO
- **Principal Investigator:** Ruixuan Gao
- **Activity code:** DP2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $1,372,964
- **Award type:** 1
- **Project period:** 2023-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10686627

## Citation

> US National Institutes of Health, RePORTER application 10686627, A biochemical approach towards subcellular, label-free molecular imaging (1DP2MH136390-01). Retrieved via AI Analytics 2026-05-27 from https://api.ai-analytics.org/grant/nih/10686627. Licensed CC0.

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