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Smart Laser Capturing Microscope for Genome Wide Single Cell Spatial Transcriptomics

Award Number: R01HG014004
ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 01/08/2025
PERIOD OF PERFORMANCE END DATE: 12/31/2028

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Smart Laser Capturing Microscope for Genome Wide Single Cell Spatial Transcriptomics - PROJECT SUMMARY We introduce an innovative AI-Assisted Laser Capture Microdissection (AI-LCM) approach for Spatial Transcriptomics, designed to overcome the limitations of existing spatial biology methods. Current techniques like MERFISH, Visium, and traditional LCM have distinct strengths, but they fall short in providing both single- cell resolution and genome-wide coverage efficiently. Our AI-LCM technique combines microscopy, Next Generation Sequencing (NGS), and LCM to enable high-throughput, comprehensive spatial transcriptomics analysis. Our method utilizes DNA nanoballs tagged with unique molecular identifiers (UMIs), readable via both microscopy and NGS. This dual-readout allows for an 'imaging-followed-by-sequencing' workflow, ensuring each cell's omics profile is linked to its spatial coordinate through the UMI-tagged nanoballs. We will achieve this through three strategic aims: 1. Optimizing in situ generation and sequencing of DNA nanoballs for diverse sample types. 2. Enhancing AI-assisted LCM to efficiently dissociate nanoball-tagged single cells at high- throughput. 3. Refining sequencing protocols to accommodate nanoballs, linking genomic data with precise spatial origins. This approach promises true single-cell spatial resolution with genome-wide coverage, exploiting the dual-functionality of DNA nanoballs for concurrent processing of thousands of cells, vastly improving LCM's throughput. Building on established technologies, our protocol is both feasible and innovative. DNA nanoballs are already integral in microscopy-based spatial transcriptomics, and LCM's robustness for single-cell profiling is well-documented. Our integration of microscopy and genomics draws on the PIs' extensive experience in commercial SBS products, automated microscopy, and AI-based image analysis. The proposed AI-LCM method not only aims to transcend the boundaries of existing spatial transcriptomics but also seeks to expand the possibilities for a wide range of single-cell assays, adding valuable spatial context to complex genomic data. This project stands to revolutionize the field by providing a novel tool for comprehensive, high-resolution mapping of cellular environments.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $392,500 )
2026	2026	UNIVERSITY OF CALIFORNIA IRVINE	160 ALDRICH HALL	IRVINE	CA	92697	ORANGE	USA	Human Genome Research	000	2	1/22/2026	NON-COMPETING CONTINUATION	$392,500
														Subtotal = $392,500

Issue Date FY: 2025 ( Subtotal = $289,900 )
2025	2025	UNIVERSITY OF CALIFORNIA IRVINE	160 ALDRICH HALL	IRVINE	CA	92697	ORANGE	USA	Human Genome Research	001	1	4/23/2025	NEW	$28,990
2025	2025	UNIVERSITY OF CALIFORNIA IRVINE	160 ALDRICH HALL	IRVINE	CA	92697	ORANGE	USA	Human Genome Research	000	1	1/8/2025	NEW	$260,910
														Subtotal = $289,900

Grand Total All Awards = $682,400

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Smart Laser Capturing Microscope for Genome Wide Single Cell Spatial Transcriptomics

Award Number: R01HG014004

ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 01/08/2025

PERIOD OF PERFORMANCE END DATE: 12/31/2028

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