# Transformative microscopes to image across spatiotemporal scales

> **NIH NIH R35** · UT SOUTHWESTERN MEDICAL CENTER · 2021 · $390,567

## Abstract

Project abstract
How molecular organization and activity leads to tissue level outcomes is, arguably, one
of the big remaining open questions in biology. Bridging these two areas is key to
biomedical advances, yet is technically challenging because we cannot observe with
molecular precision at the tissue scale. While optical microscopy is the method of choice
to observe architecture and dynamics within living cells and organisms, it has
fundamental limitations in spatiotemporal resolution and optical penetration depth. Thus
our most detailed observations of cellular dynamics and ultrastructure have been limited
to single cells that were far removed from their physiological context.
Here I propose to significantly expand the reach of super-resolution microscopy to
encompass tissues and whole model organisms. This lies far outside of the capabilities
of the current state of the art and requires significant progress in volumetric acquisition
speed, sensitivity and optical penetration depth. I propose to advance the field by
combining three different fields of microscopy. Some of these combinations are non-trivial
and thus have not been experimentally tractable so far. I propose novel concepts that can
bridge these different fields and overcome technical and fundamental limitations.
Furthermore, a novel adaptive sampling approach that only images the most informative
voxels at the highest resolution will overcome fundamental barriers to high-resolution
imaging over large volumes. I hypothesize that my new instrumentation combined with
an intelligent sampling strategt can improve acquisition speed up to 100 fold while
reducing phototoxicity and data storage needs. The resulting new microscope technology
will dramatically speed up high-resolution imaging over large volumes and hence will
enable large volume imaging experiments that have been prohibited by either lack of
spatial resolution, optical penetration depth or acquisition speed.

## Key facts

- **NIH application ID:** 10238052
- **Project number:** 5R35GM133522-03
- **Recipient organization:** UT SOUTHWESTERN MEDICAL CENTER
- **Principal Investigator:** Reto Paul Fiolka
- **Activity code:** R35 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $390,567
- **Award type:** 5
- **Project period:** 2019-09-20 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10238052

## Citation

> US National Institutes of Health, RePORTER application 10238052, Transformative microscopes to image across spatiotemporal scales (5R35GM133522-03). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10238052. Licensed CC0.

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