Quantitative Characterization of Metastability and Heterogeneity of Amyloid Aggregates

Abstract

Amyloids are heterogeneous assemblies of extremely stable fibrillar aggregates of proteins. Although biological activities of the amyloids are dependent on its conformation, quantitative evaluation of heterogeneity of amyloids has been difficult. Here we use disaggregation of the amyloids of tetramethylrhodamine-labeled Aβ (TMR-Aβ) to characterize its stability and heterogeneity. Disaggregation of TMR-Aβ amyloids, monitored by fluorescence recovery of TMR, was negligible in native buffer even at low nanomolar concentrations but the kinetics increased exponentially with addition of denaturants such as urea or GdnCl. However, dissolution of TMR-Aβ amyloids is different from what is expected in the case of thermodynamic solubility. For example, the fraction of soluble amyloids is found to be independent of total concentration of the peptide at all concentrations of the denaturants. Additionally, soluble fraction is dependent on growth conditions such as temperature, pH, and aging of the amyloids. Furthermore, amyloids undissolved in a certain concentration of the denaturant do not show any further dissolution after dilution in the same solvent; instead, these require higher concentrations of the denaturant. Taken together, our results indicate that amyloids are a heterogeneous ensemble of metastable states. Furthermore, dissolution of each structurally homogeneous member requires a unique threshold concentration of denaturant. Fraction of soluble amyloids as a function of concentration of denaturants is found to be sigmoidal. The sigmoidal curve becomes progressively steeper with progressive seeding of the amyloids, although the midpoint remains unchanged. Therefore, heterogeneity of the amyloids is a major determinant of the steepness of the sigmoidal curve. The sigmoidal curve can be fit assuming a normal distribution for the population of the amyloids of various kinetic stabilities. We propose that the mean and the standard deviation of the normal distribution provide quantitative estimates of mean kinetic stability and heterogeneity, respectively, of the amyloids in a certain preparation.

Figure 1

Disaggregation of TMR-Aβ42 amyloids monitored by FCS in PBS (A–C) and in 4 M GdnCl (D–F). (A and D) FCS autocorrelation data, G(τ) (open circles) and the fits using Eq. 1 assuming single diffusing species (solid lines). Autocorrelation data were recorded every 30 s. However, traces recorded every 2 min are shown here for clarity of presentation. (B and E) Photon count rates (squares) and concentrations (circles) obtained from analysis of the autocorrelation data. (C and F) Circles represent hydrodynamic radii (R_h) obtained from analysis of the autocorrelation data, and the solid lines represent the mean of all the measured values of R_h. Total concentration of amyloids used here is 60 nM (monomer equivalent). Clearly, R_h of solubilized TMR-Aβ corresponds to the size of the monomeric peptide (see Fig. S2). To see this figure in color, go online.

Figure 2

Time course of disaggregation of TMR-Aβ42 amyloids in urea (A–C) and in GdnCl (D–F) monitored by TMR fluorescence. (A and D) Kinetics of disaggregation in 0–9 M urea (and in 0–7 M GdnCl). Solid lines are fits using double exponentials. (B and E) Natural logarithm of apparent initial rate constants of disaggregation (ln(k_-)) calculated using Eq. 3 from the kinetic data. Solid lines are linear fits. (C and F) Fraction of dissolved peptide measured at different time points between 10 and 42 h for urea (and between 0.5 and 25 h for GdnCl). Disaggregation reaches near completion within 42 h in urea and 18 h in GdnCl. The concentration of amyloids used here is 30 nM (monomer equivalent). To see this figure in color, go online.

Figure 3

Relationship between soluble (C_soluble) and total concentrations (C_total). (A) C_soluble versus C_total of TMR-Aβ fibrils in 0–6 M GdnCl; open circles represent the data and solid lines are linear fits. Soluble peptide concentrations were calculated from TMR fluorescence. (B) Soluble fraction (C_soluble/C_total) as a function of GdnCl concentration. Clearly, fraction dissolved (i.e., C_soluble/C_total) is independent of the total concentration of the amyloids. Total concentrations of amyloids used here are 25, 50, 99, 197, and 389 nM. To see this figure in color, go online.

Figure 4

Effects of temperature, pH, and aging on stability of the TMR-Aβ amyloids. (A) Soluble fraction as a function of [GdnCl] for amyloids prepared at 25°C (square) and 37°C (circle). (B) Amyloids prepared at pH 5.7 (square) and pH 7.4 (circle). (C) Amyloids aged for 2 days (square), 2 months (circle), and 4 months (triangle). Solid lines are fits using Eq. 5. Clearly, soluble fractions depend strongly on preparation conditions. Concentration of amyloids used here is 50 nM (monomer equivalent). To see this figure in color, go online.

Figure 5

Time course of disaggregation of TMR-Aβ42 amyloids preincubated in 3 M (A) and 4 M GdnCl (B). Aliquots of 5 μM amyloid fibril stock were preincubated in 3 and 4 M GdnCl for 24 h at RT. Kinetics of TMR fluorescence were recorded after 50-fold dilution of the GdnCl-incubated amyloids in different concentrations of GdnCl. The symbols represent data and the solid lines are guide for the eye. Clearly, the amyloids preincubated in 3 M (or 4 M) GdnCl do not dissolve any further in 3 M (or 4 M) GdnCl. Kinetics observed here is much slower than those observed in Fig 2, A and D. To see this figure in color, go online.

Figure 6

Effects of progressive seeding on denaturant-dependent disaggregation of amyloids. Soluble fraction (C_soluble/C_total) as a function of [GdnCl] using TMR-Aβ42 amyloids prepared without seeding (squares) and with third generation (circles) and fifth generation (triangles) of progressive seeding. Solid lines are fits using Eq. 5. Clearly, steepness of the sigmoid curves increases with progressive seeding whereas the midpoints remain unchanged. To see this figure in color, go online.

Figure 7

Distribution of the amyloids classified based on the threshold concentration of GdnCl (ρ^∗_GdnCl) required to dissolve a particular homogeneous population of the amyloids. Gaussian distributions (Eq. 4) are calculated using the values of 〈ρ〉 and σ obtained from fitting of the data presented in Figs. 4, A–C, and 6 using Eq. 5 (see Tables S1 and S2). Clearly, the distributions shift to higher stabilities from 25°C to 37°C (A), from pH 5.7 to pH 7.4 (B) and with aging from 2 days to 4 months (C). The distribution becomes narrower with progressive seeding whereas the mid points remain the same (D).

Figure 8

A simplified scheme for denaturant-dependent disaggregation of amyloids. Circles, triangles, and squares represent three structurally distinct metastable states of the amyloids. Dots represent monomeric peptides. Here threshold concentrations (ρ^∗) of GdnCl required for disaggregation of circles, triangles, and squares are 2, 4, and 6 M respectively. Shape of the sigmoidal curve depends on the stabilities and the population distribution of the structurally distinct forms of the amyloids. To see this figure in color, go online.