Cryo-EM | SPT Labtech

The role of cryo-EM within ‘integrative’ structural biology

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Cryo-EM is an important tool as part of a new era of ‘integrative’ structural biology bringing together multiple techniques to build a more comprehensive picture of dynamic processes at both a cellular and molecular level.

While the technique is increasingly adopted to tackle increasingly challenging structural biology projects, there remain opportunities to optimize workflows and overcome bottlenecks through automation.

Understanding how biomolecules function and interact is fundamental to biochemistry. This knowledge underpins fundamental research for developing new medicines and acquiring insight into the causes of infectious diseases.

Freezing samples to protect them from electron beams in Transmission Electron Microscopy (TEM) enables the study of intricate biological structures ranging from individual biomolecules to whole cells.

Recent technological advancements have led to significant gains in higher quality structures and cryo-EM becoming the go-to method for structural biologists. Sample preservation in vitrified ice (vitrification) is widely acknowledged as the first step in the cryogenic electron microscopy (Cryo-EM) workflow. However, before sample preparation, researchers must consider the sample quality and determine its suitability for high-resolution structure determination.

A robust understanding of these critical considerations and the correct instrumentation is vital before beginning any CryoEM project to ensure its subsequent success.

Read our blog series on getting started in sample preparation for single particle cryo-EM

Certainly, sample preparation is a recognized and as yet unresolved bottleneck in the conventional cryo-EM workflow. A standard cryo-EM workflow involves an iterative process of freezing many grids of varying quality and then screening for successful specimens using a cryogenic electron microscope. This process requires the manual handling of small, fragile grids under cryogenic conditions. The quality of resulting specimen grids is often user-dependent leading to poor consistency. Furthermore, substantial researcher experience with cryo-EM is necessary to determine ‘good’ or 'bad' sample quality as outcomes tend to be inconsistent and varied.

The main obstacle to routine structure determination of single particles by high-resolution cryo-EM remains protein adsorption to the air-water interface. It is best practice to avoid air bubbles while handling bulk protein solutions due to denaturation at the air-water interface (AWI).

In the context of thin-film formation for sample vitrification, the increased AWI surface area leads to undesirable effects such as limited particle orientation and distribution, degradation, and aggregation.

In the traditional cryo-EM sample preparation workflow, blotting is the process of removing excess aqueous sample from the grid with filter paper prior to vitrification. Inherently a difficult process to control, users must take into consideration the risks that this poses to their results.

Blotting risks sample integrity

Although commonly used, its effects on sample integrity remain to relatively be poorly defined and understood. It is difficult to know how shear forces, as well as changes to buffer concentration due to evaporation, affect individual particles. To add to the uncertainty, these effects are coupled with the often-harmful influence of the air water interface (AWI), which risks alignment of orientation, as well as particle dissociation or even denaturation.

Researchers are still trying to untangle the relationship between all these forces at play, and to better understand exactly how individual samples are adversely affected by blotting.

Blotting risks image resolution

Blotting leaves behind an uneven residual fluid layer, and therefore produces an uneven ice layer following vitrification. Ice thickness is a critical factor in image resolution, and as such, it is very difficult to reliably achieve optimal grid preparation with blotting. This oftens results in suboptimal output image resolution, wasting valuable time and resource at the microscope.