# Cryo-EM grid preparation using gas dynamic virtual nozzles

> **NIH NIH R43** · MICROGRADIENT FLUIDICS LLC · 2020 · $168,086

## Abstract

Project Summary
Recent advances in cryo-electron microscopy (cryoEM), such as the development of
direct detectors, automation and 3D particle reconstruction algorithms, have
transformed structural biology by enabling investigators to obtain near atomic resolution
structures without the need to grow crystals. A significant challenge that limits the wider
applicability of cryoEM as a structural tool is the preparation of suitable samples in thin
(< 100 nm) layers of vitreous ice in the approximately micron-sized holes of a substrate
grid. This arises from the large surface-area-to-volume ratio of the thin aqueous layers
prior to freezing of the thin liquid layer in a cryogen. Biological macromolecules
preferentially localize to the air-water interface in the thin liquid layer, giving rise to
preferred orientations or, in some cases, denaturation. A significant development in
overcoming this problem has been the development of droplet based approaches to
depositing samples on the grids. This minimizes the dwell time of the protein in the
water layer, i.e., the time between spotting of the sample on the grid and plunge-
freezing of the liquid layer. The spot-to-plunge time of state-of-the-art instrumentation
(~10 ms), however, is still nearly three orders of magnitude longer than the time for
diffusion of sample to the air-water interface (~ 10-100 microseconds). The proposed
instrument will use thin liquid jets formed using gas dynamic virtual nozzles (GDVN)
together with an ultrarapid (~50 m/s) plunging system to reduce the spot-to-plunge time
to the microsecond regime. By minimizing this time to less than the diffusion time to the
air-water interface, preferential orientation and degradation issues can be minimized.
Additionally, the device has the potential to precisely control the ice layer thickness and
readily adapt to time-resolved studies. Successful development has the potential to
significantly widen the biological macromolecules and scientific questions that can be
addressed by high-resolution structure determination using single particle cryoEM.

## Key facts

- **NIH application ID:** 10009848
- **Project number:** 1R43GM137642-01
- **Recipient organization:** MICROGRADIENT FLUIDICS LLC
- **Principal Investigator:** Osman Bilsel
- **Activity code:** R43 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $168,086
- **Award type:** 1
- **Project period:** 2020-04-01 → 2021-09-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10009848

## Citation

> US National Institutes of Health, RePORTER application 10009848, Cryo-EM grid preparation using gas dynamic virtual nozzles (1R43GM137642-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10009848. Licensed CC0.

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