# Laser particles-based spatiotemporal and dynamic single-cell multiomics

> **NIH NIH K99** · MASSACHUSETTS GENERAL HOSPITAL · 2024 · $136,110

## Abstract

Project Summary/Abstract
Cells are the basic unit of life. Cells are very dynamic: they change over time and locations, respond to different
environments, and interact with other cells. Over the past decade, single-cell biology has witnessed enormous
growth owing to massive technical advances, such as single-cell sequencing, multi-omics, and spatial omics.
However, obtaining dynamic dimensions of live cells along with their multi-omic information at the single-cell
resolution is currently difficult and certainly not possible on large scales. Here, we propose a novel cell barcoding
technology that has the potential to enable us to collect live information of cells and connect the data to their
detailed omics information. This technology makes use of laser particles (LPs) with unique optical barcodes
for >100,000 channels, each containing a unique DNA barcode. The “dual-barcoding” will allow us to optically
track live cells under a microscope while they are in their natural environment or in culture, acquire their live
information, harvest the cells, acquire the omics information of the same cells by droplet-based next-generation
single-cell sequencing, and then combine the live imaging and omics data at the single cell resolution.
Furthermore, our technique can be upgraded to multi-omics modalities, combining multiple layers of information
from the genome, epigenome, transcriptome, and proteome, together with morphological, locational, functional,
and behavioral data. We will apply the method to study sentinel lymph node (SLN) metastasis of cancer cells in
vivo. The acquired in vivo single-cell imaging and multi-omics data will provide an unprecedented picture of the
cancer cell lymphatic metastasis process. This project has two specific aims. Aim 1 will develop an optical-and-
DNA “dual” barcoding strategy for droplet-based single-cell sequencing. Aim 2 will apply the method to study
breast cancer SLN metastasis in vivo. During the K99 period, the applicant will receive additional training to
expand her experience and shape her independence in the following areas: (1) LPs and optical barcoding, (2)
LP imaging and in vivo mouse imaging, and (3) single-cell sequencing and multi-omics. This proposal is under
the combined mentorship of Dr. Andy Yun (LP technology, optics, and imaging) and Dr. Ralph Weissleder
(cancer biology, in vivo imaging, and system biology), and a team of experts as advisors for single-cell
sequencing and bioinformatics. The interdisciplinary research environment at Massachusetts General Hospital
and Harvard Medical School will significantly facilitate the proposed study. If successful, the proposed study will
offer a new paradigm for “dynamic” single-cell analysis, with unprecedented speed and throughput, enabling
multi-omics modalities for the profiling of proteins, RNAs, and DNAs at the single-cell level, together with cells’
dynamic phenotype information, enable spatial-omics profiling at the 3D resolution without the need f...

## Key facts

- **NIH application ID:** 10897238
- **Project number:** 5K99HG013129-02
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Yue Jane Wu
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $136,110
- **Award type:** 5
- **Project period:** 2023-08-01 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10897238

## Citation

> US National Institutes of Health, RePORTER application 10897238, Laser particles-based spatiotemporal and dynamic single-cell multiomics (5K99HG013129-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10897238. Licensed CC0.

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