Modeling Intrinsically Disordered Proteins with Bayesian Statistics

The characterization of intrinsically disordered proteins is challenging because accurate models of these systems require a description of both their thermally accessible conformers and the associated relative stabilities or weights. These structures and weights are typically chosen such that calculated ensemble averages agree with some set of prespecified experimental measurements; however, the large number of degrees of freedom in these systems typically leads to multiple conformational ensembles that are degenerate with respect to any given set of experimental observables. In this work we demonstrate that estimates of the relative stabilities of conformers within an ensemble are often incorrect when one does not account for the underlying uncertainty in the estimates themselves. Therefore, we present a method for modeling the conformational properties of disordered proteins that estimates the uncertainty in the weights of each conformer. The Bayesian weighting (BW) formalism incorporates information from both experimental data and theoretical predictions to calculate a probability density over all possible ways of weighting the conformers in the ensemble. This probability density is then used to estimate the values of the weights. A unique and powerful feature of the approach is that it provides a built-in error measure that allows one to assess the accuracy of the ensemble. We validate the approach using reference ensembles constructed from the five-residue peptide met-enkephalin and then apply the BW method to construct an ensemble of the K18 isoform of the tau protein. Using this ensemble, we indentify a specific pattern of long-range contacts in K18 that correlates with the known aggregation properties of the sequence.National Institutes of Health (U.S.) (NIH Grant 5R21NS063185-02

Mapping interactions with the chaperone network reveals factors that protect against tau aggregation.

A network of molecular chaperones is known to bind proteins ('clients') and balance their folding, function and turnover. However, it is often unclear which chaperones are critical for selective recognition of individual clients. It is also not clear why these key chaperones might fail in protein-aggregation diseases. Here, we utilized human microtubule-associated protein tau (MAPT or tau) as a model client to survey interactions between ~30 purified chaperones and ~20 disease-associated tau variants (~600 combinations). From this large-scale analysis, we identified human DnaJA2 as an unexpected, but potent, inhibitor of tau aggregation. DnaJA2 levels were correlated with tau pathology in human brains, supporting the idea that it is an important regulator of tau homeostasis. Of note, we found that some disease-associated tau variants were relatively immune to interactions with chaperones, suggesting a model in which avoiding physical recognition by chaperone networks may contribute to disease

The Effect of a ΔK280 Mutation on the Unfolded State of a Microtubule-Binding Repeat in Tau

Tau is a natively unfolded protein that forms intracellular aggregates in the brains of patients with Alzheimer's disease. To decipher the mechanism underlying the formation of tau aggregates, we developed a novel approach for constructing models of natively unfolded proteins. The method, energy-minima mapping and weighting (EMW), samples local energy minima of subsequences within a natively unfolded protein and then constructs ensembles from these energetically favorable conformations that are consistent with a given set of experimental data. A unique feature of the method is that it does not strive to generate a single ensemble that represents the unfolded state. Instead we construct a number of candidate ensembles, each of which agrees with a given set of experimental constraints, and focus our analysis on local structural features that are present in all of the independently generated ensembles. Using EMW we generated ensembles that are consistent with chemical shift measurements obtained on tau constructs. Thirty models were constructed for the second microtubule binding repeat (MTBR2) in wild-type (WT) tau and a ΔK280 mutant, which is found in some forms of frontotemporal dementia. By focusing on structural features that are preserved across all ensembles, we find that the aggregation-initiating sequence, PHF6*, prefers an extended conformation in both the WT and ΔK280 sequences. In addition, we find that residue K280 can adopt a loop/turn conformation in WT MTBR2 and that deletion of this residue, which can adopt nonextended states, leads to an increase in locally extended conformations near the C-terminus of PHF6*. As an increased preference for extended states near the C-terminus of PHF6* may facilitate the propagation of β-structure downstream from PHF6*, these results explain how a deletion at position 280 can promote the formation of tau aggregates

Assigning Backbone NMR Resonances for Full Length Tau Isoforms: Efficient Compromise between Manual Assignments and Reduced Dimensionality

Tau protein is the longest disordered protein for which nearly complete backbone NMR resonance assignments have been reported. Full-length tau protein was initially assigned using a laborious combination of bootstrapping assignments from shorter tau fragments and conventional triple resonance NMR experiments. Subsequently it was reported that assignments of comparable quality could be obtained in a fully automated fashion from data obtained using reduced dimensionality NMR (RDNMR) experiments employing a large number of indirect dimensions. Although the latter strategy offers many advantages, it presents some difficulties if manual intervention, confirmation, or correction of the assignments is desirable, as may often be the case for long disordered and degenerate polypeptide sequences. Here we demonstrate that nearly complete backbone resonance assignments for full-length tau isoforms can be obtained without resorting either to bootstrapping from smaller fragments or to very high dimensionality experiments and automation. Instead, a set of RDNMR triple resonance experiments of modest dimensionality lend themselves readily to efficient and unambiguous manual assignments. An analysis of the backbone chemical shifts obtained in this fashion indicates several regions in full length tau with a notable propensity for helical or strand-like structure that are in good agreement with previous observations

Pseudo-acetylation of multiple sites on human Tau proteins alters Tau phosphorylation and microtubule binding, and ameliorates amyloid beta toxicity

Tau is a microtubule-associated protein that is highly soluble and natively unfolded. Its dysfunction is involved in the pathogenesis of several neurodegenerative disorders including Alzheimer's disease (AD), where it aggregates within neurons. Deciphering the physiological and pathogenic roles of human Tau (hTau) is crucial to further understand the mechanisms leading to its dysfunction in vivo. We have used a knock-out/knock-in strategy in Drosophila to generate a strain with hTau inserted into the endogenous fly tau locus and expressed under the control of the endogenous fly tau promoter, thus avoiding potential toxicity due to genetic over-expression. hTau knock-in (KI) proteins were expressed at normal, endogenous levels, bound to fly microtubules and were post-translationally modified, hence displaying physiological properties. We used this new model to investigate the effects of acetylation on hTau toxicity in vivo. The simultaneous pseudo-acetylation of hTau at lysines 163, 280, 281 and 369 drastically decreased hTau phosphorylation and significantly reduced its binding to microtubules in vivo. These molecular alterations were associated with ameliorated amyloid beta toxicity. Our results indicate acetylation of hTau on multiple sites regulates its biology and ameliorates amyloid beta toxicity in vivo

The proline-rich domain of tau plays a role in interactions with actin

<p>Abstract</p> <p>Background</p> <p>The microtubule-associated protein tau is able to interact with actin and serves as a cross-linker between the microtubule and actin networks. The microtubule-binding domain of tau is known to be involved in its interaction with actin. Here, we address the question of whether the other domains of tau also interact with actin.</p> <p>Results</p> <p>Several tau truncation and deletion mutants were constructed, namely N-terminal region (tauN), proline-rich domain (tauPRD), microtubule binding domain (tauMTBD) and C-terminal region (tauC) truncation mutants, and microtubule binding domain (tauΔMTBD) and proline-rich domain/microtubule binding domain (tauΔPRD&MTBD) deletion mutants. The proline-rich domain truncation mutant (tauPRD) and the microtubule binding domain deletion mutant (tauΔMTBD) promoted the formation of actin filaments. However, actin assembly was not observed in the presence of the N-terminal and C-terminal truncation mutants. These results indicate that the proline-rich domain is involved in the association of tau with G-actin. Furthermore, results from co-sedimentation, solid phase assays and electron microscopy showed that the proline-rich domain is also capable of binding to F-actin and inducing F-actin bundles. Using solid phase assays to analyze apparent dissociation constants for the binding of tau and its mutants to F-actin resulted in a sequence of affinity for F-actin: tau >> microtubule binding domain > proline-rich domain. Moreover, we observed that the proline-rich domain was able to associate with and bundle F-actin at physiological ionic strength.</p> <p>Conclusion</p> <p>The proline-rich domain is a functional structure playing a role in the association of tau with actin. This suggests that the proline-rich domain and the microtubule-binding domain of tau are both involved in binding to and bundling F-actin.</p

Common Features at the Start of the Neurodegeneration Cascade

A single-molecule study reveals that neurotoxic proteins share common structural features that may trigger neurodegeneration, thus identifying new targets for therapy and diagnosis