# Advanced Microscopy Tools for Ultra-High Throughput Spatially Resolved Single-Cell Transcriptomics

> **NIH NIH R21** · BOSTON CHILDREN'S HOSPITAL · 2021 · $194,973

## Abstract

The discovery and mapping of cell types used to be slow and painstaking work but with the advent of single-cell
transcriptomic techniques, such as single-cell RNA sequencing, this task can now be accomplished with relative
ease. It is possible to discover and comprehensively catalog cell types from essentially any tissue while
measuring, genome-wide, the molecular expression that gives rise to cellular function. This exciting ability is
driving transformative, multi-agency efforts to catalog all cell types in humans and other model organisms, and
these efforts promise to expand our understanding of tissue function both in health as well as in diseases such
as cancer. However, the ambition of these atlas efforts still exceeds the capabilities of existing techniques: single-
cell RNA sequencing provides limited insight into the spatial organization of tissues and can only characterize a
small fraction of the tens to hundreds of millions of cells within even relatively small tissues. By contrast, image-
based approaches to single-cell transcriptomics directly image a large fraction of the expressed transcriptome
within cells in their native tissue context and, thus, provide spatial context to single-cell measurements; however,
image-based approaches also do not have the throughput needed to characterize the substantial tissue volumes
or cell numbers demanded by cell atlases efforts and more broad biological endeavors. As such, no current
technique can meet the throughput demands of these ambitious cell atlas efforts, and the transformative promise
they offer for expanding our understanding of disease remain largely out of reach.
 Here we will meet the demand for ultra-high-throughput single-cell techniques by substantially improving the
throughput of an image-based approach that we helped pioneer—multiplexed error robust fluorescence in situ
hybridization (MERFISH). This technique simultaneously identifies hundreds to thousands of different RNA
molecules in single cells using single-molecule fluorescence imaging and can characterize tens of thousands of
cells per day across ~mm3 tissue volumes. We will increase the throughput of this technique by two orders of
magnitude, allowing measurements of thousands of genes within ~5 million cells per day across ~100 mm3 tissue
volumes. We will achieve this increase in imaging bandwidth by combining 1) a novel camera bank system that
uses 16 cameras rather than 1 per microscope with 2) an improved DNA-origami-based amplification system
that will increase the brightness of single-molecules by ~100-fold to allow faster frame rates. In parallel, we will
develop the improved microscope-control and analysis software and the data-transfer hardware required for the
rapid transfer, long-term storage, and fast analysis of the tens of TB of data produced per day by this new imaging
platform. Together the advances we propose will create a single-cell transcriptomics technique that is unrivaled
in its ability to characte...

## Key facts

- **NIH application ID:** 10145627
- **Project number:** 5R21CA249728-02
- **Recipient organization:** BOSTON CHILDREN'S HOSPITAL
- **Principal Investigator:** Jeffrey Moffitt
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $194,973
- **Award type:** 5
- **Project period:** 2020-04-15 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10145627

## Citation

> US National Institutes of Health, RePORTER application 10145627, Advanced Microscopy Tools for Ultra-High Throughput Spatially Resolved Single-Cell Transcriptomics (5R21CA249728-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10145627. Licensed CC0.

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