This is the first study in which the interaction of a microtubule-associated protein has been evaluated by direct single-molecule observations in living neurons. The data imply a novel kiss-and-hop mechanism of tau–microtubule interaction, rationalizing how tau can regulate microtubule dynamics without interfering with axonal transport.

Niewidok et al. analyze the distribution and dynamics of RNA-binding proteins (RBPs) with single-molecule resolution in living neuronal cells, providing direct support for liquid droplet behavior of stress granules in living cells and revealing transient binding of RBPs in nanocores.

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

We present a correlation-driven molecular dynamics (CDMD) method for automated refinement of atomistic models into cryo-electron microscopy (cryo-EM) maps at resolutions ranging from near-atomic to subnanometer. It utilizes a chemically accurate force field and thermodynamic sampling to improve the real-space correlation between the modeled structure and the cryo-EM map. Our framework employs a gradual increase in resolution and map-model agreement as well as simulated annealing, and allows fully automated refinement without manual intervention or any additional rotamer- and backbone-specific restraints. Using multiple challenging systems covering a wide range of map resolutions, system sizes, starting model geometries and distances from the target state, we assess the quality of generated models in terms of both model accuracy and potential of overfitting. To provide an objective comparison, we apply several well-established methods across all examples and demonstrate that CDMD performs best in most cases.

Circular dichroism (CD) spectroscopy is a highly sensitive but low-resolution technique to study the structure of proteins. Combined with molecular modeling or other complementary techniques, CD spectroscopy can provide essential information at higher resolution. To this end, we introduce a new computational method to calculate the electronic circular dichroism spectra of proteins from a structural model or ensemble using the average secondary structure composition and a precalculated set of basis spectra. The method is designed for model validation to estimate the error of a given protein structural model based on the measured CD spectrum. We compared the predictive power of our method to that of existing algorithms, namely, DichroCalc and PDB2CD, and found that it predicts CD spectra more accurately.Our results indicate that the derived basis sets are robust to both experimental errors in the reference spectra and the choice of the secondary structure classification algorithm. For over 80% of the globular reference proteins, our basis sets accurately predict the experimental spectrum solely from their secondary structure composition. For the remaining 20%, correcting for intensity normalization considerably improves the prediction power. Additionally, we show that the predictions for short peptides and an example complex of intrinsically disordered proteins strongly benefit from accounting for side-chain contributions and structural flexibility.

Microtubules (MTs) are key components of the cytoskeleton and play a central role in cell division and development. MT assembly is known to be associated with a structural change in αβ-tubulin dimers from kinked to straight conformations. How GTP binding renders individual dimers polymerization-competent, however, is still unclear. Here, we have characterized the conformational dynamics and energetics of unassembled tubulin using atomistic molecular dynamics and free energy calculations. Contrary to existing allosteric and lattice models, we find that GTP-tubulin favors a broad range of almost isoenergetic curvatures, whereas GDP-tubulin has a much lower bending flexibility. Moreover, irrespective of the bound nucleotide and curvature, two conformational states exist differing in location of the anchor point connecting the monomers that affects tubulin bending, with one state being strongly favored in solution. Our findings suggest a new combined model in which MTs incorporate and stabilize flexible GTP-dimers with a specific anchor point state.

Fluorescence decay after photoactivation (FDAP) and fluorescence recovery after photobleaching (FRAP) are well established approaches for studying the interaction of the microtubule (MT)-associated protein tau with MTs in neuronal cells. Previous interpretations of FDAP/FRAP data have revealed dwell times of tau on MTs in the range of several seconds. However, this is difficult to reconcile with a dwell time recently measured by single-molecule analysis in neuronal processes that was shorter by two orders of magnitude. Questioning the validity of previously used phenomenological interpretations of FDAP/FRAP data, we have generalized the standard two-state reaction-diffusion equations by 1), accounting for the parallel and discrete arrangement of MTs in cell processes (i.e., homogeneous versus heterogeneous distribution of tau-binding sites); and 2), explicitly considering both active (diffusion upon MTs) and passive (piggybacking upon MTs at rates of slow axonal transport) motion of bound tau. For some idealized cases, analytical solutions were derived. By comparing them with the full numerical solution and Monte Carlo simulations, the respective validity domains were mapped. Interpretation of our FDAP data (from processes of neuronally differentiated PC12 cells) in light of the heterogeneous formalism yielded independent estimates for the association (∼2 ms) and dwell (∼100 ms) times of tau to/on a single MT rather than in an MT array. The dwell time was shorter by orders of magnitude than that in a previous report where a homogeneous topology of MTs was assumed. We found that the diffusion of bound tau was negligible in vivo, in contrast to an earlier report that tau diffuses along the MT lattice in vitro. Methodologically, our results demonstrate that the heterogeneity of binding sites cannot be ignored when dealing with reaction-diffusion of cytoskeleton-associated proteins. Physiologically, the results reveal the behavior of tau in cellular processes, which is noticeably different from that in vitro.

A refined FDAP approach is used to analyze tau’s behavior in axon-like processes. A conserved C-terminal pseudorepeat and disease-like pseudohyperphosphorylation critically influence tau’s microtubule interaction. The results contribute to an understanding of pathological processes that lead to tau’s redistribution during disease.