Monomeric Huntingtin Exon 1 Has Similar Overall Structural Features for Wild-Type and Pathological Polyglutamine Lengths

Abstract

Huntington's disease is caused by expansion of a polyglutamine (polyQ) domain within exon 1 of the huntingtin gene (Httex1). The prevailing hypothesis is that the monomeric Httex1 protein undergoes sharp conformational changes as the polyQ length exceeds a threshold of 36-37 residues. Here, we test this hypothesis by combining novel semi-synthesis strategies with state-of-the-art single-molecule Förster resonance energy transfer measurements on biologically relevant, monomeric Httex1 proteins of five different polyQ lengths. Our results, integrated with atomistic simulations, negate the hypothesis of a sharp, polyQ length-dependent change in the structure of monomeric Httex1. Instead, they support a continuous global compaction with increasing polyQ length that derives from increased prominence of the globular polyQ domain. Importantly, we show that monomeric Httex1 adopts tadpole-like architectures for polyQ lengths below and above the pathological threshold. Our results suggest that higher order homotypic and/or heterotypic interactions within distinct sub-populations of neurons, which are inevitable at finite cellular concentrations, are likely to be the main source of sharp polyQ length dependencies of HD.

Figure 1

Site-specifically dual-labeled Httex1 library for smFRET measurements. (a) General strategy for sequential labeling of Httex1 at the N-terminal residue and within the C-terminal proline-rich region spanning residues 60–90. Here, Alexa 594 is denoted as AF₅₉₄, Alexa 488 as AF₄₈₈, and silver triflate as AgOTf. (b) Unmodified dual-labeled Httex1 constructs labeled with Alexa 488 (green) at the N-terminus and Alexa 594 (red) at the indicated C-terminal position. (c) Semi-synthetic strategy for obtaining dual-labeled Httex1 proteins containing site-specific post-translational modifications within Nt17, e.g., threonine 3 (T3) phosphorylation. (d) pT3-modified dual-labeled Httex1 constructs prepared as described in (c).

Figure 2

smFRET measurements of Httex1. (a) Two-dimensional E_FRET versus S histograms for Httex1 15–49Q with acceptor labeled at position A60C, P70C, P80C, or P90C. (b) ⟨E_FRET⟩ values calculated from 2D Gaussian fits of E_FRETS versus histograms. A2C^† indicates labeling with Alexa488; P90C^‡ indicates labeling with Alexa594, and NA denotes where no construct is made. (c) Double logarithmic plot of ⟨E_FRET⟩ versus donor–acceptor amino acid spacing for the unmodified Httex1 constructs. Acceptor label positions are indicated as follows: proximal to the polyQ domain (●), within the PR domain (■), and C-terminal (▲). (d) Double logarithmic plot of ⟨E_FRET⟩ versus donor–acceptor amino acid spacing for the pT3-modified Httex1 constructs. Unmodified constructs are shown in filled shapes and pT3-modified constructs as open shapes with acceptor positions as indicated previously.

Figure 3

Test of the validity of using the Gaussian chain model to extract distances from FRET efficiencies for Httex1 as compared to denatured ubiquitin. Relative error, (⟨E_FRET^calc⟩ – ⟨E_FRET^meas⟩)/⟨E_FRET^meas⟩, between the measured (⟨E_FRET^meas⟩) and calculated (⟨E_FRET^calc⟩) FRET efficiencies as a function of (|j – i| – |j – i|_ref). Here, j is the position of the C-terminal dye and i is the position of the N-terminal dye. |j – i|_ref denotes the number of peptide bonds between dyes for the dye pair used to calculate l_p. For Httex1 constructs, l_p was determined by fitting the measured A60C ⟨E_FRET⟩ values using the Gaussian chain model. The calculated ⟨E_FRET⟩ values were determined for the other dye pairs by inserting l_p into the equation for P(r). As a control, the relative error between measured and calculated ⟨E_FRET⟩ values was calculated for ubiquitin in 8 M urea using ⟨E_FRET⟩ values from Aznauryan et al. Ubiquitin in 8 M urea (black circles) should follow uniform scaling and thus Gaussian chain models should reasonably approximate the underlying distance distributions for denatured ubiquitin. Here, the K48C-R74C construct was used as the reference construct to calculate l_p. The dashed black line denotes the mean relative error for ubiquitin in 8 M urea.

Figure 4

Conformational properties derived from simulated ensembles that match all three smFRET ⟨E_FRET⟩ values for a given polyQ length. (a–e) Distance maps quantify the average distance between all pairs of residues (in Å) for 15Q, 23Q, 37Q, 43Q, and 49Q, respectively. The hotter the color, the farther the average distance between a pair of residues. Tadpole-like architectures consisting of an Nt17-polyQ head and a PR domain tail are observed for all Httex1 constructs. (f–j) Normalized R_g distributions for the reweighted conformational ensembles of 15Q, 23Q, 37Q, 43Q, and 49Q, respectively. Here, R_g is normalized by √N, where N is the number of residues in the construct. Insets depict highly probable conformations that are consistent with a given R_g/√N value. In these snapshots, glutamine is shown in orange, proline in purple, negatively charged residues in red, positively charged residues in blue, hydrophobic residues in black, non-glutamine polar residues in green, and glycine and histidine in pink. (k) Comparison of normalized R_g distributions for all polyQ lengths. As the polyQ length increases a continuous decrease in the distribution of R_g/√N values is observed. This is a result of the increased presence of a globular polyQ domain and is visually observed from the snapshots in panels f–j. (l) The average R_g/√N as a function of polyQ length. Error bars denote the standard error of the mean calculated over three independent simulations. (m) Scaling of the mean size (⟨R_g⟩) of the polyQ domain as a function of polyQ length. The line shows the best fit to the equation ln(⟨R_g⟩) = ln(α) + ν ln(N). Here, ν = 0.36 and α = 2.62 Å. Error bars denote the standard error of the mean for three independent simulations. (n) Probability that Nt17-Q_n adopts globular conformations. The probability was calculated from two-dimensional histograms of R_g/N^1/3 and asphericity, δ. Specifically, the probability was calculated by summing the density within the two-dimensional region defined by 2.5 Å ≤ R_g/N^1/3 < 3.5 Å and 0 ≤ δ < 0.26. The error bars correspond to the standard error of the mean over three independent simulations. (o) Two-dimensional histogram of R_g/N^1/3 and δ for the polyQ-PR domains of Httex1 49Q. The red rectangle corresponds to the region that corresponds to globular conformations as defined above. For all polyQ lengths the probability of polyQ-PR domains adopting globular conformations is negligible.

Figure 5

Proposed influences of tadpole-like monomeric Httex1. The top row shows the proposed impact of monomeric Httex1 on heterotypic interactions. Green, orange, and purple symbols and edges depict interactions of monomeric Httex1 through Nt17, polyQ, and the PR domain, respectively. As polyQ length increase, we propose that the number and strengths of heterotypic interactions can increase, vis-à-vis the wild-type, due to the increased prominence of the globular polyQ domain in the tadpole-like architecture of monomeric Httex1. The bottom row shows the proposed impact of polyQ length on homotypic interactions that drive the aggregation and phase separation of Httex1. The total cellular concentration of Httex1 is denoted as c_t. For the wild-type, we propose that c_t < c_F, where c_F is the saturation concentration that has to be crossed to drive the formation of insoluble, fibrillar aggregates. Conversely, polyQ expansions lead to a reversal whereby c_t > c_F, and hence, depending on the gap between c_F and c_t, there is an increasing driving force for forming large fibrillar aggregates. The tadpole-like structures of monomeric Httex1 determine the overall bottlebrush architecture of the aggregates, whereas nucleated conformational changes within Httex1 determine the intermolecular interfaces and the strengths of aggregates, including fibrils.^,