# New strategies for molecular cell-type labeling in volume electron microscopy

> **NIH NIH RF1** · UNIVERSITY OF CONNECTICUT STORRS · 2022 · $1,059,661

## Abstract

Project Summary
 Recent years have seen major breakthroughs in methodology for studying two complex yet
fundamental aspects of brain structure: synaptic connectivity patterns and the heterogeneous distribution of
molecules. Due to an ongoing technical barrier that has endured for decades, advances in circuit imaging and
molecular imaging have progressed almost entirely in parallel, and there are still no routine methods for
integrating molecular information into synaptic circuit maps. Imaging brain structure with enough resolution to
visualize synapses requires electron microscopy (EM), and EM is not compatible with the standard methods
used to identify molecules by light microscopy. It is clear from biochemical data that highly multiplexed labeling
of proteins and RNA transcripts will be necessary to generate comprehensive maps of the brain’s molecular
structure. To address this need, a number of approaches aiming to extend the spatial resolution and limits of
multiplexed labeling of fluorescence microscopy have been developed. The resolution of EM is still orders of
magnitude higher than any light-level technique, however, and EM remains the only modality that reveals
structural details. EM also presents a unique opportunity for molecular labeling. EM image volumes are
reconstructed from serial ultrathin sections, and by applying a different probe to each section a large number of
molecules can be localized in a single structure – hundreds or more in the case of a neuron. In contrast to
tissue specimens used in light microscopy, ultrathin EM sections are not readily amenable to simple
immunohistochemistry (IHC) or in situ hybridization (ISH) protocols. A major reason for this is incompatibility
between sample preparation practices: the strong fixatives and dense embedding resins used in EM damage
or occlude molecular targets, while the harsh treatments used to facilitate molecular detection degrade fine
tissue structure. The problem can be circumvented by the use of specially engineered transgenic reporters, but
these do not solve the problem of detecting endogenous molecules in large numbers. In this project, we will
draw on long-established methods from the EM and histology fields to develop an unconventional approach to
labeling EM sections, and apply this approach to identify molecular cell and synapse types using three different
workflows. Our strategy employs removable embedding media, which are standard in light microscopy and
which, contrary to traditional assumptions, we have found to be perfectly compatible with EM imaging. To
maximize efficiency and flexibility in imaging workflows, we will develop labeling protocols that prioritize
resolution, sensitivity, and throughput to different degrees. If successful, this project will produce methods
uniquely capable of combining EM-level structural imaging with multiplexed labeling of endogenous molecules,
and will dramatically increase the depth of information obtained from EM volume recons...

## Key facts

- **NIH application ID:** 10413454
- **Project number:** 1RF1MH129269-01
- **Recipient organization:** UNIVERSITY OF CONNECTICUT STORRS
- **Principal Investigator:** LINNAEA E OSTROFF
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,059,661
- **Award type:** 1
- **Project period:** 2022-09-01 → 2026-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10413454

## Citation

> US National Institutes of Health, RePORTER application 10413454, New strategies for molecular cell-type labeling in volume electron microscopy (1RF1MH129269-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10413454. Licensed CC0.

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