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Ribosomes catalyze protein synthesis by cycling through various functional states. These states have been extensively characterized in vitro, yet their distribution in actively translating human cells remains elusive. Here, we optimized a cryo-electron tomography-based approach and resolved ribosome structures inside human cells with a local resolution of up to 2.5 angstroms. These structures revealed the distribution of functional states of the elongation cycle, a Z tRNA binding site and the dynamics of ribosome expansion segments. In addition, we visualized structures of Homoharringtonine, a drug for chronic myeloid leukemia treatment, within the active site of the ribosome and found that its binding reshaped the landscape of translation. Overall, our work demonstrates that structural dynamics and drug effects can be assessed at near-atomic detail within human cells.
Cryo-electron tomography (cryo-ET) is a powerful method to elucidate subcellular architecture and to structurally analyse biomolecules in situ by subtomogram averaging (STA). Specimen thickness is a key factor affecting cryo-ET data quality. Cells that are too thick for transmission imaging can be thinned by cryo-focused-ion-beam (cryo-FIB) milling. However, optimal specimen thickness for cryo-ET on lamellae has not been systematically investigated. Furthermore, the ions used to ablate material can cause damage in the lamellae, thereby reducing STA resolution. Here, we systematically benchmark the resolution depending on lamella thickness and the depth of the particles within the sample. Up to ca. 180 nm, lamella thickness does not negatively impact resolution. This shows that there is no need to generate very thin lamellae and thickness can be chosen such that it captures major cellular features. Furthermore, we show that gallium-ion-induced damage extends to depths of up to 30 nm from either lamella surface.
Cryo-electron tomography (CryoET) resolves individual macromolecules inside living cells. However, the complex composition and high density of cells challenge the faithful identification of features in tomograms. Here, we capitalize on recent advances in electron tomography and demonstrate that 3D template matching (TM) localizes a wide range of structures inside crowded eukaryotic cells with confidence 10 to 100-fold above the noise level. We establish a TM pipeline with systematically tuned parameters for automated, objective and comprehensive feature identification. High-fidelity and high-confidence localizations of nuclear pore complexes, vaults, ribosomes, proteasomes, lipid membranes and microtubules, and individual subunits, demonstrate that TM is generic. We resolve ~100-kDa proteins, connect the functional states of complexes to their cellular localization, and capture vaults carrying ribosomal cargo in situ. By capturing individual molecular events inside living cells with defined statistical confidence, high-confidence TM greatly speeds up the CryoET workflow and sets the stage for visual proteomics.