A cryo-ET view of the nuclear periphery of a HeLa cell. Credit: From Mahamid, J. et al. Science 351, 969–972 (2016). Reprinted with permission from AAAS.

Single-particle cryo-electron microscopy (cryo-EM) has gotten a lot of attention for recent technical advances that enable it to help solve macromolecular structures at near-atomic resolution, an achievement we celebrated as the Method of the Year 2015. These methodological developments are also benefitting cellular ultrastructure imaging using cryo-electron tomography (cryo-ET).

In a cryo-ET study, a biological sample—a cell, tissue, or organism—is flash frozen, thinned to an appropriate thickness, and then imaged using an electron microscope. The freezing process preserves the sample in a hydrated, close-to-native state. Multiple images are captured as the sample is tilted along an axis. The images are then aligned and merged using computational techniques to reconstruct a three-dimensional picture, or tomogram.

With its capability to obtain nanometer-scale information about macromolecular complexes in their native cellular environment, cryo-ET provides a bridge between light microscopy and in vitro structure determination methods. This is important because many complexes cannot be purified, and knowing both the structure and location of macromolecular complexes is crucial for understanding cellular function.

Biological material is very sensitive to radiation damage by an electron beam, however, so researchers have had to devise many ways to improve resolution without destroying samples. Recent hardware developments vital for enhancing the resolution of single-particle cryo-EM, including direct electron detectors and novel phase plates, are also improving cryo-ET imaging. Computational tricks originally developed for cryo-EM, such as beam-induced motion correction algorithms and subtomogram averaging, also help sharpen structural features visualized by cryo-ET. These developments synergize with advances in cryo-ET sample preparation, most notably the application of focused ion beam (FIB) milling to thin samples to ideal thicknesses for imaging.

In principle, cryo-ET can image the entire proteome of a cell, but new data analysis methods are needed to parse such dense pictures. In one promising approach, called template matching, a template structure is used to locate matching structures in the tomogram. While this method has been successful for mapping the locations of relatively large structures such as ribosomes, sensitivity and accuracy improvements are needed for its broader applicability. We look forward to the development of new approaches that will enable in situ structural biology on a proteomic scale.