# Administrative Supplement for AbbeLight SAFe M90 automated, multicolor, optically perfect TIRF imaging: The RNA nanomachines of the gene expression machinery dissected at the single molecule level

> **NIH NIH R35** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $249,713

## Abstract

This supplement will critically update the instrumentation available for the parent R35 MIRA award, entitled The
RNA nanomachines of gene expression dissected at the single molecule level. The central features of the
proposed instrumentation, the AbbeLight SAFe M90 plug-in imaging module, are its versatility, turnkey
readiness, and ease of use for automated, multicolor, optimized total internal reflection fluorescence (TIRF) and
highly inclined and laminated optical sheet (HILO) imaging of live and fixed mammalian cells. These features
will not only increase the information content and throughput of our measurements, but also greatly facilitate
access to these methods by the diverse group of junior and senior coworkers in the PI's group. Funding will
critically complement two recent NIH investments into the parent grant. First, we used a recent administrative
supplement to install a Cytosurge FluidFM OMNIUM, a versatile, turnkey instrument for injecting, sampling, and
manipulating the content of live mammalian cells. Second, we will use funds from the parent grant to update our
15-year old objective-type TIRF microscope (O-TIRFM) body for our intracellular single-molecule, high-resolution
localization and counting (iSHiRLoC) technology. Our MIRA grant aims to dissect the mechanisms of the
nanoscale RNA machines of gene expression at the single molecule level, so far focusing on bacterial
riboswitches and the yeast spliceosome. Combining the high-performance, ultra-wide-field, multicolor
capabilities and automation of the AbbeLight SAFe M90 imaging module with the upgrade of the O-TIRFM body
and the FluidFM OMNIUM semi-automated cell injector will transform our ability to incorporate studies of the
intracellular miRNA-guided silencing machinery into the parent grant. Building on our group's 25-year expertise
in this space, we then aim to: 1.) Apply our established mechanistic enzymology approaches to an ever broader
set of RNAs involved in regulating transcription, translation and splicing, seizing the opportunities arising from
the continuing discoveries of new functional RNAs; and 2.) Push the limits of our approaches to be able to probe
increasingly complex biological contexts and mechanisms, realizing opportunities for unprecedented discoveries
where individual RNA nanomachines interact. In pursuit of these aims, we will address the unifying hypothesis
that dynamic RNA structures are a major determinant of the outcomes of gene expression, as exemplified by
the fact that transient miRNA:mRNA interactions lead to the regulation of protein translation in mammalian cells.
To address this hypothesis, we have developed a suite of intracellular single particle tracking approaches
wherein we inject fluorophore labeled RNAs at defined time points and image them at the single molecule level
with high spatiotemporal resolution and multiple colors, an approach whose multiplexing and throughput will be
drastically expanded by integrating the AbbeLight SAFe...

## Key facts

- **NIH application ID:** 11098821
- **Project number:** 3R35GM131922-06S1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** NILS G WALTER
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $249,713
- **Award type:** 3
- **Project period:** 2019-05-01 → 2029-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11098821

## Citation

> US National Institutes of Health, RePORTER application 11098821, Administrative Supplement for AbbeLight SAFe M90 automated, multicolor, optically perfect TIRF imaging: The RNA nanomachines of the gene expression machinery dissected at the single molecule level (3R35GM131922-06S1). Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nih/11098821. Licensed CC0.

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