# Transcriptome-wide, single-molecule dynamics of RNA-protein interaction.

> **NIH NIH R21** · UNIVERSITY OF CALIFORNIA RIVERSIDE · 2021 · $184,566

## Abstract

RNA-protein interactions are a critical component of cellular function. Dynamic and coordinated binding and
release of RNA by multiple proteins underpins regulation throughout gene expression. However, our
technological capacity to visualize these dynamics on the timescales of processes such as splicing, translation,
or mRNA decay, remains limited. Transcriptome-wide methods that probe RNA-protein interactions – from
microarrays to RIP-/CLIP-seq – provide static, single-timepoint, or equilibrium snapshots. Conversely, real-time
single-molecule methods probe real-time dynamics on individual RNAs with exquisite molecular precision, but
are challenging to deploy at transcriptome scale. Single-molecule methods developed to bridge this gap have
measured protein-RNA equilibrium affinities and dissociation rates on large libraries of synthetic RNA sequences
up to ~300 nt. While these have highlighted kinetic diversity due to local RNA sequence and structure, they still
lack the ability to probe dynamics on full-length transcripts with in vivo chemical modifications, they do not directly
measure binding rates, and, importantly they have not addressed how multiple simultaneous protein-RNA
interactions coordinate. Here we propose development of a technology that circumvents these limitations,
focusing on mRNA-protein interactions. Our approach leverages direct observation of fluorescently-labeled
proteins binding and releasing tens of thousands of single mRNAs immobilized across an array of zero-mode
waveguides (ZMWs), on millisecond timescales. The ZMW-based platform offers the critical throughput,
multicolor fluorescence detection, and signal-to-noise metrics needed to advance the state of the art. The key
requisite technological breakthroughs will be made through two specific aims. In Aim 1, we will develop a
workflow to quantify the interaction dynamics of one and two proteins with a surface-immobilized Saccharomyces
cerevisiae transcriptome. We will validate this protocol in terms of reproducibility and completeness of
transcriptome capture, and the reproducibility of the kinetic data. In Aim 2 we will develop and optimize an
approach to also identify each mRNA in the experiment, allowing (multi)protein-binding dynamics to be assigned
to RNA identity. We will adopt a sequencing-by-synthesis approach, contrasting enzymatic strategies to robustly
read out RNA sequence in place. We will validate this approach by comparing the in-ZMW identified sequences
with bulk RNA-seq data for the mRNA population. The combined outcome of these Aims will be a prototype
technology and proof-of-concept for profiling (multi)protein interaction dynamics on each mRNA in the
transcriptome. This technology will complement static transcriptome-wide approaches, deepening the range of
mechanistic questions that can be asked and answered across RNA biology.

## Key facts

- **NIH application ID:** 10242848
- **Project number:** 5R21GM139056-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA RIVERSIDE
- **Principal Investigator:** Sean E O'Leary
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $184,566
- **Award type:** 5
- **Project period:** 2020-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10242848

## Citation

> US National Institutes of Health, RePORTER application 10242848, Transcriptome-wide, single-molecule dynamics of RNA-protein interaction. (5R21GM139056-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10242848. Licensed CC0.

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