and showcases its power to unveil the cell's intricate 3D architecture, with a particular focus on the actin cytoskeleton. Published in Current Opinion in Cell Biology, the review exemplifies how cryo-ET has begun to open a new frontier in the visualization of the inner workings of cells in increasingly complex samples, from single cells to whole organisms.
The tool: While cryo-electron microscopy (cryo-EM) and in particular single-particle analysis have undoubtedly revolutionized the analysis of macromolecular structures, traditional methods often only analyze isolated components, thereby neglecting their cellular context. Cryo-ET overcomes this obstacle by enabling the study of macromolecules within their native environment at sub-nanometer resolution, thus allowing researchers to decipher the spatial arrangement and interactions of cellular components, which is crucial for understanding the "molecular sociology of the cell".
Status Quo: Cryo-ET has expanded the scientists’ ability to explore the 3D organization of the cytoskeleton in the cytosol of eukaryotic cells, but detecting short or crosslinked filaments in dense (sub)cellular compartments remains a challenge. Fortunately, ongoing research is actively addressing these limitations - with notable advances in automated data acquisition and reconstruction, deep learning-based tomogram annotation tools, as well as new sample preparation procedures to explore larger samples, emerging at a rapid pace.
Outlook: Focusing on the actin field, rapid advances in state-of-the-art cryo-ET will soon open up new avenues for exploring previously undescribed actin systems and to visualize elusive structures such as nuclear actin filaments. This will allow for gaining novel insights into cell adhesion, migration and invasion processes in their native 3D context, a crucial step towards understanding complex cellular dynamics. Beyond the realm of actin, modern cryo-ET unlocks the potential for high-throughput analysis of larger and more complex samples, including organoids and tissues. Deep learning algorithms will become powerful allies, enabling meaningful analysis of rich cellular tomograms. Importantly, the synergy between cryo-ET and computational tools paves the way for large-scale studies, accelerating scientific discovery.