Open Access Article
Arnab
Bandyopadhyay
,
Achinta
Sannigrahi
* and
Krishnananda
Chattopadhyay
*
Structural Biology & Bio-Informatics Division, CSIR-Indian Institute of Chemical Biology, 4, Raja S. C. Mullick Road, Kolkata 700032, India. E-mail: krish@iicb.res.in; sannigrahiachinta@gmail.com
First published on 5th February 2021
Understanding of prion aggregation in a membrane environment may help to ameliorate neurodegenerative complications caused by the amyloid forms of prions. Here, we investigated the membrane binding-induced aggregation of yeast prion protein Sup35. Using the combination of fluorescence correlation spectroscopy (FCS) at single molecule resolution and other biophysical studies, we establish that lipid composition and lipid/protein ratio are key modulators of the aggregation kinetics of Sup35. In the presence of a zwitterionic membrane (DMPC), Sup35 exhibited novel biphasic aggregation kinetics at lipid/protein ratios ranging between 20
:
1 and 70
:
1 (termed here as the optimum lipid concentration, OLC). In ratios below (low lipid concentration, LLC) and above (ELC, excess lipid concentration) that range, the aggregation was found to be monophasic. In contrast, in the presence of negatively charged membranes, we did not observe any bi-phasic aggregation kinetics in the entire range of protein to lipid ratios. Our results provide a mechanistic description of the role that membrane concentration/composition-modulated aggregation may play in neurodegenerative diseases.
There are several prion-like proteins that exist in different fungi including yeast.17 Previous studies suggested that aggregation of Sup35 prion protein may form functional beneficial amyloids for yeast since interaction of prions causes heritable traits.18 Although these yeast prion proteins are not infectious to humans, they carry the same transmissible phenotype as human prion protein. With human prions, an infectious disease propagates through a self-sustaining modification in the structure of a normal protein within the cell, seemingly without the help of any nucleic acid.19 With yeast prions, a similar mechanism yields a new heritable metabolic state, seemingly without a change in any nucleic acid. In addition, the yeast Sup35 protein contains a human prion-like domain.20 A conformation change similar to human prion protein between the PrPC and PrPSC forms has also been found with Sup35 and the proposed mechanism of the propagation of Sup35 aggregation has been found to be identical to that of mammalian prion protein.21,22 Hence, Sup35 has been used extensively and widely as a model protein to study the mechanism of the prion disease.20
Because of the presence of glycosylphosphatidylinositol (GPI)-anchor, human prion proteins are often found associated with lipid membranes.23–26 It is well acknowledged that lipids/membranes induce the aggregation of human prion proteins.24 Whatley et al. have shown that the vacuolation in nerve cells is drastically increased during prion aggregation, which further emphasizes the effect of membrane environments towards the aggregation of prion protein.27 Fei Wang et al., found that the PrP–lipid interaction can be initiated by electrostatics, which can be followed by hydrophobic interactions.14 They show that the protein–lipid interaction can convert full-length R-helix-rich PrP to a PrPSc-like conformation under physiological conditions, supporting the relevance of lipid-induced PrP conformational change to in vivo PrP conversion. Similar to its human counterpart, yeast protein Sup 35 and its interactions with lipids have also been studied. For example, Ganusova et al. and Chernova et al. have shown that lipids/membranes play a role in the aggregation of Sup35 inside yeast cells.28,29 It has been shown by different research groups that Sup35 may propagate as a prion in mammalian cells and the presence of GPI anchoring facilitates aggregate propagation between N2a cells, resembling mammalian prion behaviour.30–33
Here, we report a detailed study on the aggregation kinetics of Sup35 protein in the presence of model phospholipid vesicles using FCS and other biophysical methods. FCS offers a sensitive and convenient method to study biomolecular diffusion under single molecule resolution. In this study, we chose physiologically relevant lipids, DMPC or 1,2-dimyristoyl-sn-glycero-3-phosphocholine and DMPS or 1,2-dimyristoyl-sn-glycero-3-phospho-L-serine, since these are the most abundant components of the membranes of synaptic vesicles.34 We chose the phospholipid DMPC (14
:
0 saturated, transition temperature ∼24 °C), since it exists in the fluid phase at the physiologically relevant temperature of 37 °C.35 We understand that the use of different chain lengths of the unsaturated and saturated lipids is not ideal, and the same chain length should be used for better comparison.36 Therefore, we used DMPS lipid for studying the effect of a negative lipid component. Our work showed a noble mechanistic pathway of Sup35 aggregation, which is greatly modulated by the lipid concentration and composition.
Our results suggest that at a particular lipid/protein ratio (defined as OLC, optimum lipid concentration from now on) the aggregation kinetics followed an interesting biphasic pattern. In contrast, the aggregation profile of Sup35 attained the monophasic nature when the aggregation occurred in the presence of high (ELC, excess lipid concentration) and low lipid/protein ratios (LLC, low lipid concentration). The kinetics is monophasic, also in the absence of lipid. The presence of a negatively charged membrane also showed the monophasic aggregation kinetics of Sup35.
This NM domain is responsible for the formation of toxic amyloid structures after a lag phase.20,40 Since the understanding of the lipid binding site would require structural insights of the protein, we developed a model structure using its sequence homology with structurally known prion proteins including that from S. pompe (Fig. S1A, ESI†) and humans (Fig. S1B, ESI†). For the model generation, we used a composite approach through iterative threading assembly refinement (ITASSER) of the Zhang lab server. This method combined threading, ab initio modelling and atomic level structure refinement methods, and the model with the best confidence score was accepted as the optimum structure (Fig. 1).
We validated the model structure using a number of computational methods. Ramachandran plot analysis (https://swift.cmbi.umcn.nl/cgi//PictureCGI.py) showed that all residues in the model occupied the generously allowed region. In the generously allowed region, 70% of the residues were found inside the favoured region (Fig. S1C, ESI†), while the rest were predominantly turns, loops and disordered. In addition to the Ramachandran analyses, we also used the proSA algorithm (https://prosa.services.came.sbg.ac.at/prosa.php) to study the overall quality of the model (Fig. S1D, ESI†), using which we compared the Z score of the present model against all other experimentally determined structures available in the current PDB database. Z score represents the deviation of total energy of the structure with respect to an energy distribution derived from random conformations. The NMR and X-ray crystal structures in Fig. S1D (ESI†) are shown using dark and light blue colours respectively, while the black dots represent the predicted model of Sup35NM. We observed that the Z score value of the predicted model was located well within the region of structures determined by X-ray methods. The plot of the local model quality predicted by the proSA program by plotting energies vs. amino acid sequence over the window of 40 residues and 10 residues showed that the energy values of all residues in our predicted model are under zero (Fig. S1E, ESI†). We estimated that the model structure would contain approximately 25% alpha helix and 2% beta sheet, while the rest would be random coil/disordered. It has been previously shown that the short prion recognition elements within the N-terminal domain (N), termed as the head and tail may form homotypic intermolecular contacts. While both regions undergo nucleation, the head region is known to acquire the productive interactions first.41
To investigate experimentally the membrane binding, we resorted to fluorescence correlation spectroscopy (FCS). For FCS experiments, we labelled the N-terminal of Sup35NM using Rhodamine Green (Rho-Sup35NM). Fig. 2B shows a typical correlation function, which was obtained from FCS experiments using 10 nM Rho-Sup35NM in an aqueous buffer at pH 7.5. In the absence of lipid, the correlation function was fit to a model containing a single diffusion component, and the goodness of the fit was established using the randomness of the residual distribution. Using the value of diffusion coefficient (D) obtained from FCS, we determined the experimental value of rH (rH,exp) for Rho-Sup35NM to be 18.5 Å. We compared the value of rH,exp with the theoretical value of rH (rH,theo), which we calculated using the Hydropro42 by inputting the model structure of Sup35NM and observed the hydrodynamic radius of Sup35NM to be 16 Å.
In the presence of zwitterionic (DMPC) and negatively charged (DMPS) SUVs, the correlation functions were fit using a model of two diffusing components in which the rapidly diffusing fast component represented the unbound monomeric protein, while the slow component would be the membrane bound protein. In the presence of different concentrations of DMPC SUVs, the values of rH corresponding to the fast (monomeric protein, 18.5 Å) and slow (membrane bound, 140 Å) components remained constant (Fig. 2C). In contrast, as we increased SUV concentrations, we observed an increase in the fraction of the membrane bound Sup35NM (slow component) with a decrease in the fraction of the free monomer (fast component) (Fig. 2D). The increase in the fraction/ratio of the membrane bound form of Sup35 with increasing concentration of lipid is shown in Fig. 2D, where the black line represents protein binding to DMPC vesicles only and the red line represents protein binding to phospholipid vesicles composed of DMPC and DMPS (50
:
1). We used a sigmoidal fitting function to fit the dependence of these fractions with DMPC concentrations to determine the values of association constant (Ka ∼ 2.7 × 103 M−1). It was observed that the presence of a negatively charged component (DMPC
:
DMPS 50
:
1), significantly increased the membrane binding affinity (Ka = 6 × 103 M−1).
We used far UV CD to investigate the change in protein secondary structure as a result of membrane binding.43 Far UV CD experiments show double minima at 208 nm and 222 nm suggesting an alpha helical structure (Fig. 3A). In the presence of DMPC vesicles, CD data suggested a decrease in helical structure (Fig. 3A). In the presence of negatively charged vesicles (DMPS/DMPC 50
:
1), the helical content of Sup35NM decreased further. Far UV CD data were complemented by measuring FT-IR. From the carbonyl (C
O) stretching vibrations of amide-I (beta sheet: 1633–38 cm−1, alpha helix: 1649–1656 cm−1, disordered (1644 cm−1), and turns and loops (1665–1672 cm−1), we calculated the percentages of secondary structures (Fig. 3B). We found from the FT-IR data that Sup35NM contained a 35% alpha helical structure, which was similar to the helical contents determined from the model structure (25%). Similar to what was observed with far UV CD, FT-IR analyses suggested a decrease in helical content (to 22%), as DMPC vesicles were added (Fig. 3C). The alpha-helical content of Sup35NM was found to be about 19% in the presence of a lipid vesicle composed of DMPC/DMPS 50
:
1 (Fig. 3D).
Since ThT fluorescence has small dependence on lipid concentrations (Fig. S4, ESI†), suitable background correction was used for each time point of aggregation kinetics carried out in the presence of lipids. The concentration of Sup35 protein used for the experiments was 30 μM. In our work, low lipid concentration or LLC refers to a lipid concentration below 300 μM (or lipid to protein ratio of 10
:
1). The optimum lipid concentration or OLC was between the lipid concentrations of 600 μM and 2100 μM (or between lipid to protein ratios of 20
:
1 and 70
:
1). The excess lipid concentration was above 2400 μM to 3000 μM (or between lipid to protein ratios of 80
:
1 and 100
:
1). We have grouped these lipid concentrations based on their abilities to modify the aggregation landscapes of the Sup35 protein. At a certain lipid concentration range, the aggregation landscape of Sup35 attained a novel bi-phase pattern, so we labelled it as the optimum lipid concentration. Below and above this optimum concentration, the aggregation landscape was mono-phasic, so we labelled them as low lipid concentration range and excess lipid concentration range.
In the presence of low lipid to protein ratio (LLC condition), we observed a slight increase in the rate of aggregation (the exponential increase started at an earlier time point). Interestingly, the extent of aggregation (as measured by the intensity of ThT fluorescence at the saturation phase) remained similar in both conditions (Fig. 4A). In the presence of high lipid to protein ratios of DMPC (OLC condition), both the rate and extent of Sup35NM aggregation increased as the concentration of SUVs increased (Fig. 4B). More importantly, we found that in these ratios, the aggregation kinetics consisted of two sigmoidal phases. At an ELC condition of DMPC, the rate of aggregation was slightly increased with lipid concentration with a small change in the extent of aggregation. In these ratios, the aggregation kinetics became mono-phasic again (Fig. 4C). Subsequently, we studied the aggregation kinetics in the presence of a negatively charged lipid membrane (phospholipid vesicles composed of a mixture of DMPC and DMPS in the ratio of 50
:
1). Surprisingly, it was found that the aggregation kinetics followed a monophasic character in the entire range of L/P ratio (Fig. 4D).
We then complemented ThT aggregation data using FCS. For the FCS experiments, we used 10 nM labelled protein in the presence of excess unlabelled Sup35NM for the aggregation to occur. We used three different lipid-to-protein ratios (0
:
1, 50
:
1 and 100
:
1) of DMPC SUVs. A lipid to protein ratio of 0
:
1 represents the absence of lipid. In the absence of lipids, correlation functions at different incubation times were fit to a sum of two components using the following Scheme 1:
In this scheme, the monomeric protein (denoted by P) would form aggregates (denoted by P–P) and the correlation function data could be analyzed by a two component model with the diffusion time of τD,M for the monomer (with amplitude of aM) and of τD,Agg (amplitude of aAgg) for the aggregates, respectively. As expected, aM + aAgg = 1. Similar terminology and parameter notations are used subsequently for Schemes 2 and 3 below.
Please note that P–P in the above equation indicates a multimolecular aggregate, and not necessarily a dimer. Since FCS data analyses required multiple components and the number of components varied for different conditions, we determined the values of average diffusion times (τDav) from individual components using eqn (5). Fig. 5D shows the variations of τD,av with time in the absence of lipids. The values of τD,av increased with incubation time following sigmoidal aggregation kinetics. Comparing the aggregation kinetics monitored by ThT fluorescence and FCS, we noted that they did not superimpose. Although the kinetics measured by both methods saturated approximately at similar hours, ThT monitored kinetics is hyperbolic, while the FCS monitored one is sigmoidal (Fig. S5, ESI†). In order to get further insights into this difference, we have plotted in Fig. 5G, the fractional population of the monomer (P) and (P–P) aggregates with respect to incubation time. As observed in Fig. 5G, the amplitude of the aggregated component increased in a sigmoidal fashion, while that of the monomer decreased. The data suggest that the difference (hyperbolic in ThT fluorescence vs. sigmoidal in FCS, Fig. S5, ESI†) comes from a relatively small fraction of ThT active aggregates at the beginning of the aggregation kinetics. Further studies would be needed to further characterize the nature of these early aggregates.
Under OLC conditions of DMPC (lipids to protein ratio of 50
:
1), the correlation functions were initially fit to a two-component diffusion model. Under this condition, the variation of the amplitude of the aggregated component with incubation time followed two-phase aggregation kinetics (Fig. 5E), the trend of which was similar to that observed with ThT fluorescence. We used the following equation scheme (Scheme 2) to analyse the FCS data obtained under this condition.
We can ignore τD,L because the lipid is not labelled and hence free lipid would not contribute to the correlation function. In this condition (OLC), the protein remained mostly free at the zero time point and at room temperature, and hence τD,P–L can also be ignored. The first part of Scheme 2 assumes the formation of protein–protein aggregates, which binds to the lipid in the second part. The component analyses from the FCS fit show the decrease in the amplitude of the monomeric protein as the amplitude of an intermediate aggregate species (P–P) formed. The amplitude of the intermediate decreased with time, as a final aggregated species (P–P–L) started forming (Fig. 5H).
In contrast, in the presence of high DMPC concentration (ELC condition of DMPC, lipids to protein concentration of 100
:
1), we did not see any variation in the amplitude of the aggregated component with incubation time. As a matter of fact, the correlation functions obtained in this condition were fit optimally using a single component, and the amplitude of this component remained unaltered with incubation time (Fig. 5I). The following Scheme 3 was used to analyse the FCS data for this condition.
The species (P–L)n indicates the possibility of combining several protein–lipid complexes, which do not seem to be happening. The species P–P′–L is also an aggregated protein species, which is bound to lipid molecules (see Scheme 2 above). Since FCS data are fit to only one component diffusion model, the analyses suggest that the species P–L (monomeric protein bound to lipid) and P–P′–L (a protein aggregate bound to the lipid) have similar values of rH. This condition is satisfied when a fibril-like aggregate is wrapped around a large lipid molecule, in which condition there would not be much difference between a lipid bound monomer and a lipid bound aggregate. In the next section, we used AFM to validate this possibility.
We used AFM to substantiate the above FCS analyses in the absence and presence of membranes.45 Control DMPC SUVs showed a round-shaped morphology of the diameter ∼180 nm (Fig. 6A and L in Scheme 2 above). In the absence of the membrane, Sup35NM (P in Scheme 1) formed aggregates of elongated fibrillar shape (Fig. 6B and P–P in Scheme 1). The average length of Sup35NM fibrils was found to be ∼2.5 μm with a height of 3.4 nm (Fig. 6B). In the presence of DMPC under the OLP condition, AFM images at the first plateau (∼100 hours) (Fig. 6C) suggested the coexistence of few fragmented fibrils (P–P) along with intact lipid vesicles (L). AFM images at the second plateau (∼200 hours) clearly show the association of the vesicles with the fibrillar aggregates forming a “curved-branched” morphology (Fig. 6D). Similar morphology of Sup35NM aggregates were observed in the presence of negatively charged vesicles (DMPC
:
DMPS, 50
:
1) at the saturation level (∼100 hours) of aggregation (Fig. 6E). The average size/length of Sup35NM aggregates was found to be ∼1.8 μm in the presence of a membrane (15 nm in height). At the ELP conditions, tiny fragmented Sup35 fibrils associated with lipid vesicles were observed. AFM imaging showed spherical species of free lipid-like particles (Fig. 6F), which were bound onto protein aggregates.
:
1, 50
:
1 and 100
:
1) of DMPC vesicles. Three different concentrations of each aggregate sample were used for the assay to trace the dose-dependent cell viability (Fig. S2A, ESI†). The error bars represent the standard deviation. A slight reduction in the cell viability (89% viability) was observed, while the cells were treated with only lipid vesicles. The viable cell population was found to be higher for the treatment of the aggregates in the absence of membrane (lipid/protein ratio of 0
:
1), than that in the presence of membrane in the lipid/protein ratio of 50
:
1. In contrast, cell viability was found to be the highest after treatment with aggregates that were formed in the presence of membrane with a lipid/protein ratio of 100
:
1. For each ratio, a successive decrease in the viable cell population was observed with an increase in the concentration of aggregates. The presented results suggest that there was a nice correlation between the cellular toxicity and the lipid/protein ratio, with a DMPC L/P ratio of 100
:
1 being the least toxic and an L/P ratio of 50
:
1 having the highest toxicity toward the mammalian cells.
These experiments were further complemented by calcein release assay using a dye entrapped model membrane system. A calcein release assay suggested the fast release and rupture of the membrane by the aggregates formed in the presence of a membrane at the L/P ratio of 50
:
1 (release 83%), (Fig. S2B, ESI†). The rate and extent of dye release was significantly dropped when entrapped vesicles were treated with aggregates formed in the presence of membrane at the L/P of 100
:
1 (release 60%), whereas Sup35NM aggregates formed in the absence of DMPC SUVs showed intermediate release and rupture of the membrane (release 72%). It may be mentioned that the toxicity experiments have been carried out in mammalian neuroblastoma cell lines and these experiments do not represent viability measurements in yeast.
:
1 is a convenient example of a boundary condition of the self-association regime, in which membrane binding is completely absent. AFM images of Sup35NM aggregates in the absence of a membrane looked like elongated fibrils. Next, the conditions with lipid to protein ratios of 50
:
1 and 100
:
1 (where the membrane was present) were convenient examples, which showed that the membrane binding regime and aggregation regimes modulated each other depending on the lipid to protein ratio. At a lipid to protein ratio of 100
:
1 with DMPC vesicles (ELC condition), where there was an excess amount of lipids, the AFM image showed the existence of a crowd of lipid vesicles associated with tiny fragmented fibrils. However, at a lipid to protein ratio of 50
:
1 for DMPC vesicles (OLC condition), AFM analysis unveiled that a stretch consisting of oligomers was formed initially, which got elongated on the surface of the DMPC vesicles exhibiting curvy and branched fibrillar structures, which were found to protrude around the lipid vesicles. We performed ITC experiments and found that the binding isotherm showed greater binding affinity for protein–protein interactions in comparison to Sup35NM–membrane interactions (Fig. S3, ESI†). Moreover, lipid molecules (under OLC conditions) might provide the increased local concentration of protein molecules, which in turn facilitated the short chain fibril formation of Sup35NM. Hence, we believe that, at the initial stage of aggregation, protein–protein interactions predominate over protein–membrane interactions producing oligomeric ensembles of protein molecules. With time, these short chain fibrils interacted with the membrane and formed higher order fibrils. As discussed before, FCS analysis at different time points of Sup35NM aggregation in the presence of DMPC vesicles (at a lipid to protein ratio of 50
:
1) shows the existence of various Sup35NM populations (Fig. 5H). At around 0 hour, a high amount of monomeric population (amplitude of the fast component) of Sup35NM was present. With time, the monomeric protein gave rise to protein–protein aggregates (amplitude of the second component). During the ∼100th hour, the monomeric population was minimized with a significant increase in the population of protein–protein aggregates. With a further increase of incubation time, these protein–protein aggregates started binding to the membrane surface resulting in the formation of membrane-associated protein aggregates (amplitudes of the third component). Thus, at the final point of aggregation, the population of membrane-associated protein aggregates was dominantly higher than the population of protein–protein aggregates.
To obtain a mechanistic insight into this phenomenon, DMPC vesicles with an L/P ratio of 100
:
1 (ELC condition) was added to the pre-aggregated Sup35NM and incubated for further aggregation, which showed a biphasic aggregation profile with ThT-fluorescence assay (Fig. S6A, ESI†). This result further confirmed that the already preformed Sup35NM aggregates were further elongated on the surface of the vesicles. CD experiments of the pre-aggregated Sup35NM samples were found to exhibit predominantly beta-sheet conformation as confirmed by the existence of a major component at 216 nm (Fig. S6B, ESI†). Addition of DMPC vesicles at the L/P ratio of 100
:
1, significantly altered the secondary conformation from beta sheet to alpha helix. As discussed earlier in the case of alpha synuclein,46 this change in conformation may happen due to dissociation of some Sup35NM protein molecules from the fibrils to populate the lipid-bound monomeric α-helical state.
Nevertheless, Sup35NM aggregation was also significantly modulated by the lipid composition of the membrane. We found that the increase in the negatively charged component (DMPS) significantly increased the aggregation propensity of the protein. It is interesting to note that the biphasic behaviour (observed with zwitterionic lipids) disappeared when the negatively charged lipid composition was introduced even at an L/P ratio of 50
:
1. This happened because the presence of anionic lipid component appreciably increased the binding affinity of Sup35NM towards the phospholipid membrane.
We have shown that a good correlation exists between membrane binding affinity, the ability of the aggregates towards pore formation and their extent of cytotoxicity in mammalian cells. The extent of membrane deformation and pore formation correlated well with the reduction in cell viability in mammalian cells.
:
1 and 70
:
1 (at OLC) whereas, the ratio above OLC (ELC) and negatively charged membrane reverted back the amyloid kinetics to monophasic. This variation in kinetics appeared due to the slight change in membrane binding affinity and protein/lipid stoichiometry. We have shown that a good correlation exists among different parameters i.e. membrane binding affinity, protein aggregation, the ability of the aggregates towards pore formation and their extent of cytotoxicity in mammalian cells. The extent of membrane deformation and pore formation correlated well with the reduction in cell viability. Aggregates formed in the presence of a membrane were significantly more toxic in nature than those formed in the absence of a membrane. So, our results have provided a mechanistic description of membrane concentration/composition-modulated aggregation of Sup35NM and shed some light on aggregation-moderated membrane deformation, which is associated with neuronal diseases.
000 rpm for 10 minutes. The soluble fraction obtained thereafter was carefully removed and allowed to bind to Ni–NTA agarose resin. The Ni–NTA column was washed with 40 ml of wash buffer (20 mM Tris–HCl, 500 mM NaCl and 50 mM imidazole, pH 8.0) followed by elution with 20 mM Tris HCl, 500 mM NaCl and 500 mM imidazole, pH 8.0. The eluted fractions were pulled according to their tentative protein contents as per their absorbance at 280 nm. The post-elution fractions were subjected to dialysis in a 20 mM Na–phosphate buffer pH 7.5. In all our protein concentration measurements, UV-VIS was deployed and Sup35NM concentration was determined by considering the monomeric molar extinction coefficient of 29
000
M−1
cm−1 at 280
nm. The identity of the protein was confirmed by SDS PAGE.
:
0 to 1
:
100. Aliquots were thereafter subjected to ThT addition and fluorescence measurements were taken using an integration time of 0.3 s. The steady state fluorescence was monitored using an excitation wavelength of 450 nm, and the values of emission intensity at 485 nm were recorded.
![]() | (1) |
ln(55.5 K) and hence the entropic contribution can be estimated as follows: ΔG = ΔH − TΔS. Here, the concentration of water of 55.5 M was used to correct the unit of K to molar fraction.
![]() | (2) |
![]() | (3) |
![]() | (4) |
Calculation of the average diffusion time was carried out using eqn (5), where A1 and τ1 are the amplitudes and diffusion times of the fast component and A2 and τ2 are the amplitudes and diffusion times of the slow component, respectively.
![]() | (5) |
We have followed the procedure of Middleton et al. for the calculation of the percentages of the bound/free Sup35.51
Footnote |
| † Electronic supplementary information (ESI) available: Validation of the model structure of Sup35NM, aggregate-induced differential toxicity of Sup35NM in the absence and presence of DMPC vesicles, ITC experiments, ThT fluorescence showing binding of ThT to lipid vesicles, average diffusion time of aggregates superimposed with ThT fluorescence intensity, mechanistic insight on Sup35NM aggregation, OPM server results table and secondary derivative of the absorbance data of the FTIR spectra. See DOI: 10.1039/d0cb00203h |
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