Targeting Hydrophobic Residues in the Alpha-Synuclein NAC Domain Disrupts Aggregation and Seed-Competent Fibril Formation

doi:10.21203/rs.3.rs-5191089/v1

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Targeting Hydrophobic Residues in the Alpha-Synuclein NAC Domain Disrupts Aggregation and Seed-Competent Fibril Formation

https://doi.org/10.21203/rs.3.rs-5191089/v1

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Alpha-synuclein (αSyn) is a 14 kDa soluble and intrinsically disordered protein ubiquitously expressed in neurons. It plays a crucial role in synucleinopathies, where insoluble fibrils contribute to neurotoxicity and disease progression. The formation of these fibrils and their ability to seed further aggregation are central to αSyn pathology. Our study focused on the hydrophobic non-amyloid component (NAC) region of αSyn. Using full-length NAC peptide and its truncated variants, inhibitory peptides, and a combination of experimental and computational approaches, we demonstrate that the 68GAVV71 region and residues adjacent to it, such as T72, T75, and A76, are essential for αSyn aggregation and its prion-like behavior. Inhibitor peptides that target the hydrophobic region effectively block αSyn dimerization and aggregation into seed-competent fibrils. Molecular dynamics simulations revealed that the peptide inhibitor disrupted hydrophobic interactions within the NAC domain, preventing stable β-sheet structure formation. These results show that the 68GAVV71 stretch in the NAC domain is critical for αSyn aggregation into prion-like fibrils and could be a potential molecular target for treating synucleinopathies.

Neurobiology of Disease

General Cell Biology & Physiology

Molecular Biology

Computational Biology

alpha-synuclein

amyloid fibril

neurodegeneration

parkinson’s disease

prion-like spreading

Amyloid fibrils of alpha-synuclein (αSyn) are associated with dementia with Lewy bodies (DLB), multiple system atrophy, and Parkinson's disease ^[1–3]. These fibrils have been linked to neuronal death and neuroinflammation in cellular models ^[4,5]. αSyn aggregates show prion-like behavior, seeding further aggregation of native αSyn ^[6,7]. Beyond neurological diseases, αSyn is associated with cancers, suggesting a potential overlap in disease mechanisms ^[8,9]. Therefore, understanding the role of αSyn in one disease may help identify biomarkers and therapeutics for both diseases ^[10].

αSyn comprises an N-terminal lipid-binding αhelix (1–60 aa), a non-amyloid component (NAC) region (61–95 aa), and a C-terminal acidic tail (96–140 aa). The N-terminal region harbors several mutation sites, such as A53T, A30P, and E46K, linked to familial Parkinson's disease ^[11]. The non-NAC (P1 and P2) region is suggested to initiate αSyn aggregation by synergizing with the NAC and C-terminal regions ^[12]. However, the NAC domain forms the core folded region of αSyn aggregates, playing a critical role in the aggregation process ^[13–16]. Glu83 (E83) in the NAC acts as a negative regulator of amyloid formation, and mutations at this site, such as E83Q, accelerate aggregation and increase toxicity, as observed in DLB ^[2,17].

The 68–76 stretch in the NAC region ^[18], which includes the 68GAVV71, is critical for αSyn aggregation and toxicity. Previous studies have shown that this hydrophobic sequence promotes the formation of toxic β-sheet structures, which are essential for fibril formation and cytotoxicity ^[18]. While studies have examined the broader 68–76 region, focusing specifically on shorter regions allowed us to investigate the specific hydrophobic interactions responsible for initiating aggregation. Understanding the role of specific residues is crucial, as even minor changes in this highly conserved sequence can significantly impact aggregation dynamics and toxicity ^[17,18]. We show that truncation of 68GAVV71 residues abolishes aggregation propensity of the NAC domain, and targeting this region inhibits the seeding competency of αSyn fibrils - findings not previously reported. These findings underscore the potential of the 68GAVV71 stretch as a target for developing therapeutics for synucleinopathies.

Truncation and pH Modulate Aggregation Kinetics of NAC and its Truncated Variants

Six distinct NAC peptides were generated by truncating specific regions of the NAC domain. The most extended peptide, NAC35 (61–95), consisted of the entire residues of the NAC domain, whereas the shortest peptide, NAC8 (72–79), consisted of only eight residues (Fig. 1a). The aggregation kinetics of these peptides were monitored by a thioflavin T (ThT) binding assay. Among all the peptides, only NAC35, NAC16, and NAC11 showed time-dependent aggregation kinetics (Fig. 1b). The presence of β-sheet-rich aggregates in assay wells was also confirmed by fluorescence microscopy (Fig. S1). Notably, ThT curves of both NAC16 and NAC11 rapidly increased to a peak with a short plateau but then decreased back towards the starting point (Fig. 1b). This atypical behavior may be linked to the formation of large aggregates that precipitate and decrease monomer concentrations in the sample, as noted by others for Aβ aggregation ^[19]. The aggregation lag time was calculated from the ThT readings between 0 and 10 h, as this window corresponded to when the aggregation curves of NAC35, NAC16, and NAC11 reached their maximum peak. The shorter aggregation lag time of NAC16 and NAC11 compared to NAC35 suggests that specific residues in NAC16 and NAC11 contribute to the rapid initiation of the aggregation process, likely due to enhanced nucleation dynamics (Fig. 1c).

These results show that truncating residues 61–62 and 79–95 (NAC16) or 61–67 and 79–95 (NAC11) increases the aggregation tendency of the NAC. Importantly, residues 68GAVV71 are crucial for NAC aggregation, as their truncation completely abolishes aggregation, as seen with NAC17 (79–95), NAC12 (71–82), and NAC8 (72–79). This aligns with previous work showing that the 71VTGVTAVAQKTV82 region is essential for αSyn aggregation ^[20]. While this region promotes aggregation in NAC35 (61–95), it is insufficient alone, as demonstrated by the non-aggregating behavior of NAC12 (71–82). In contrast, NAC16 (63–78) and NAC11 (68–78), which contain parts of this region and additional residues, do aggregate, suggesting that residues flanking 71VTGVTAVAQKTV82, particularly in NAC16 and NAC11, are critical for the aggregation process.

Next, NAC35, NAC16, and NAC11 aggregates were characterized by atomic force microscopy (AFM) and transmission electron microscopy (TEM). The imaging revealed fibrillar aggregates for all three peptides, with noticeable morphological differences (Fig. 1d). NAC35 and NAC16 formed clumped fibrils with elongated tangles. In contrast, NAC11 aggregated into densely aggregated fibrils organized into sticky bundles, lacking elongated tangles. No fibrillar or other aggregated structures were detected by AFM in NAC17, NAC12, and NAC8 samples collected after 48 h of aggregation assay (Fig. S2).

An 8-anilinonaphthalene-1-sulfonic acid (ANS) assay, which detects exposed hydrophobic regions ^[21], was performed to investigate how pH variations affect NAC35, NAC16, and NAC11 aggregation behavior and to determine if pH changes could induce NAC17, NAC12, and NAC8 aggregation. Altering the pH did not affect the aggregation tendency of NAC17, NAC12, and NAC8, which did not aggregate in the neutral buffer (Fig. 1e-g). In contrast, aggregating NAC35 in the basic buffer (pH 8.0) increased the aggregation lag time, while the acidic buffer shortened the lag time of aggregation (Fig. 1e-h). For NAC16 and NAC11, the lag time of aggregation increased in both basic and acidic buffers compared to the neutral buffer (Fig. 1e-g, i, j). The contrasting aggregation behavior of NAC35, compared to NAC16 and NAC11, particularly under acidic conditions, suggests that residues outside the core hydrophobic stretch (68–78) may influence the aggregation process differently. A previous study has identified the role of hydrophobic stretches, including residues 71–82 or 74–79, in αSyn amyloid formation ^[17]. Our results extend this by showing that residues beyond the core 71–82 stretch, such as those in NAC35, also contribute to its aggregation behavior, particularly under pH variations. This highlights the complexity of αSyn aggregation and underscores the importance of considering the entire NAC region - not just the core hydrophobic stretch - in understanding αSyn aggregation dynamics.

Solubility Does Not Explain the Lack of Aggregation of NAC17, NAC12, and NAC8

Next, UV-Vis spectrophotometry was performed to confirm the solubility and presence of NAC17, NAC12, and NAC8 peptides in the solution, ruling out solubility issues as a reason for their lack of aggregation. All peptides were aggregated without ThT for 48 h. Aggregated samples were collected at 24 h and 48 h of aggregation, or peptides were aggregated for 48 h, and the contents of the assay well were pooled and separated into soluble and insoluble fractions by pelleting assay. Analysis of samples collected at 24 and 48 h show that NAC17, NAC12, and NAC8 remained solubilized throughout the experiment, as demonstrated by their stable absorbance values over time (Fig. 2a). In contrast, the absorbance spectra of NAC35, NAC16, and NAC11 exhibited noticeable shifts between 0–48 h (Fig. 2a), indicating aggregation. Further analysis revealed a clear difference between the spectra of soluble and insoluble fractions for NAC35, NAC16, and NAC11. This difference was absent for NAC17, NAC12, and NAC8 (Fig. 2b). Overall, these absorbance data indicate that NAC17, NAC12, and NAC8 remain in solution, but unlike NAC35, NAC16, and NAC11 do not aggregate.

Raman Spectroscopy Confirms β-Sheet Changes in NAC35, NAC16, and NAC11 Fibrils

Since truncated NAC peptides aggregated rapidly, biochemical analysis of their aggregates is challenging. To overcome the caveat, we used Raman spectroscopy to examine the conformational properties of NAC fibrils. Raman spectra of monomers of all three peptides show characteristic amide I (@1675 cm^− 1, labeled as 4), amide II (@1552 cm^− 1, labeled as 3), and amide III (@1252 cm^− 1, labeled as 2) bands of peptides and proteins (Fig. 3). The presence of these bands confirm the typical peptide structures, where the amide I band corresponds to C = O stretching vibrations, the amide II band is related to N-H bending and C-N stretching, and the amide III band involves N-H in-plane bending and C-N stretching ^[22]. All these signals are considerably altered in aggregated samples of NAC35, NAC16, and NAC11, including an increase in amide signal intensities and the appearance of new spectral features, such as skeletal signals in the region 900–1000 cm^− 1 and changes in the structure of amide III region between 1250–1350 cm^− 1 (Fig. 3a-c). These alterations suggest interactions associated with peptide aggregation, similar to findings observed with αSyn aggregation ^[23]. The increased intensity in these amide bands indicates structural changes, likely due to interactions among peptides forming new higher-order structures, such as β-sheet aggregates ^[22].

A red shift in the position of the amide I band for NAC35 (Fig. 3a) suggests a shift towards lower energy, which often occurs when β-sheet structures are formed ^[22,23]. The width of the amide I bands of aggregated samples of NAC16 and NAC11 changed from 15 to 24 cm^− 1 and 12 to 20 cm^− 1, respectively, indicating the formation of β-sheet secondary structures but to a lower extent compared to NAC35. The spectral band at 1004 cm^− 1 (labeled as 1) possibly originated from phosphate-buffered saline (PBS).

Overall, Raman spectra of NAC35, NAC16, and NAC11 show structural changes, marked by the increase in amide band intensities and new spectral signals, which are similar to the alterations seen in αSyn, where amide bands reflect the transition to higher-order β-sheet structures during aggregation ^[22].

Seeding Competency of NAC35, NAC16 and NAC11 Fibrils

Following the observation of β-sheet structural changes in aggregated NAC35, NAC16, and NAC11 by Raman spectrometry, we examined the ability of these aggregates to act as seeds. Monomeric αSyn was incubated with preformed fibrils of NAC35, NAC16, and NAC11 at a 4:1 molar ratio, and the aggregation was monitored by ThT assay. Preformed αSyn fibrils were used as a positive control, which resulted in the highest ThT fluorescence, indicating their robust seeding activity (Fig. 4a). NAC35 fibrils, while less effective than αSyn fibrils, were still capable of efficiently promoting the aggregation of αSyn monomers (Fig. 4a). In contrast, NAC16 and NAC11 fibrils showed no seeding activity.

Next, αSyn fibrils formed in the presence of preformed fibrillar seeds were collected after 72 h of aggregation and separated into insoluble fractions by pelleting assay. Dot blot analysis corroborated the ThT results, showing that NAC35 fibrils significantly promoted αSyn aggregation and increased the formation of insoluble fibrils (Fig. 4b, c). Additionally, performed NAC35 fibrils, like αSyn fibrils, significantly promoted αSyn dimerization (Fig. 4d, e). Overall, these results indicate that while the 68GAVV71 region is crucial for NAC aggregation, additional residues beyond this core, particularly those in 79–95 in NAC35, may promote strong hydrophobic interactions and enhance fibril stability, both of which are necessary for seeding competency ^[24,25]. Although NAC16 and NAC11 showed β-sheet structural changes, the lack of these additional hydrophobic residues likely resulted in not seed-competent fibrils. The instability of NAC16 and NAC11 fibrils (Fig. 1b) may contribute to their reduced effectiveness as seeds for further aggregation. These results highlight that while β-sheet formation is necessary, fibril stability is equally critical for seeding competency, likely due to the contribution of additional residues (79–95) in promoting strong hydrophobic interactions ^[24,25].

Inhibitory Peptides Targeting NAC Domain Reduce αSyn Dimerization and Aggregation

The role of the NAC domain in the aggregation of αSyn was further investigated by applying inhibitory peptides designed to interact with this region. We selected the KISVRV peptide, known to target the critical hydrophobic region of αSyn (residues 70 to 75) and effectively inhibit fibril formation while dissolving pre-formed oligomers ^[26]. To this end, we used three variants of KISVRV peptide: D-amino acid peptide (PD), L-amino acid peptide (PL), and Peptide B (PB), all sharing the core sequence KISVRVRRRRRR. These peptides differ in their amino acid configurations and terminal modifications: PD contains D-amino acids, PL contains L-amino acids, and PB is unmodified except for an acetylated C-terminus (Fig. 5a).

The affinity of PD, PL, PB, and a scrambled control peptide (PS) for αSyn was determined by microscale thermophoresis (MST). The scrambled peptide (PS) contains the same amino acids as the active peptides but in a randomized sequence. MST results showed a higher affinity of all inhibitor peptides for full-length αSyn than the PS peptide (Fig. 5b, Fig. S4). The binding K_d of inhibitor peptides to αSyn at different temperatures revealed tight binding for PD and PL. In contrast, significant fluctuations in K_d were observed for PS peptides at various temperatures, indicating non-specific binding (data not shown).

The effect of inhibitors on αSyn aggregation was evaluated by incubating αSyn with PD, PL, and PB at a 1:2 molar ratio and then monitoring aggregation by ThT assay. The kinetics data revealed that PD, PL, and PB are highly effective in inhibiting αSyn aggregation (Fig. 5c). To quantify the extent of inhibition, the final ThT reading for each treatment was normalized to that of the control group, providing a relative comparison of amyloid fibril formation. This analysis revealed that all inhibitors significantly reduced αSyn fibrils compared to the control (Fig. 5d). The increase in αSyn aggregation in the presence of PS is likely due to its non-specific binding (Fig. 5d); however, PS did not affect fibril morphology (Fig. S5). PD, PL, PB, and PS peptides showed no signs of self-aggregation (Fig. S6).

TEM analysis corroborated ThT results, showing reduced fibril density in the presence of inhibitors (Fig. 5e-h). Further, αSyn fibrils formed without inhibitors displayed a clear twisted morphology, notably reduced by inhibitors, mainly PB (Fig. 5e-h). Additionally, PB significantly reduced fibril width compared to control fibrils (Fig. 5i). The fibril width distributions further highlight the distinct effects of PD, PL, and PB inhibitors (Fig. 5j-m). Control fibrils display a relatively consistent width, while the PD and PL inhibitors reduce the fibril width and alter the distribution to varying extents (Fig. 5j-l). Notably, PB showed the most pronounced effect, resulting in a more uniform population of thinner fibrils (Fig. 5m).

Next, αSyn fibrils formed in the presence of inhibitor peptides were collected at the end of the aggregation assay and separated into soluble and insoluble fractions by pelleting assay. Dot blot analysis showed a significant decrease in insoluble αSyn fibrils in the presence of inhibitor peptides (Fig. 5n, o). Coomassie staining was then used to investigate the presence of dimers in αSyn insoluble fractions. Quantification of the dimer-to-monomer band ratio showed that all inhibitors significantly reduced αSyn dimerization (Fig. 5p, q).

Overall, inhibitory peptides targeting the hydrophobic NAC region elucidated the role of NAC residues in aggregation. Notably, these peptides reduce dimerization, reducing the formation of insoluble αSyn fibrils and affecting fibril width and morphology differently, with PB showing the most potent effects on fibril structure and aggregation.

Inhibitor Peptides Targeting αSyn Hydrophobic Region Impede Seeding Competency of Fibrils

In familial Parkinson's disease, mutations in αSyn, such as A53T, affect dimer formation and accelerate aggregation by rapidly nucleating competent species and continuously elongating fibrils with increasing seed amounts, potentially explaining the early onset of Parkinson's disease ^[1]. Based on our findings that PD, PL, and PB inhibitors reduce αSyn dimerization, we next investigated the seeding competency of αSyn fibrils formed with or without inhibitors. We used HEK293T biosensor cells stably expressing αSyn (A53T) CFP/YFP-tagged fusion proteins for this study ^[27]. The intracellular seeding was quantified using confocal microscopy by counting CFP/YFP inclusions and verified by FRET flow cytometry, following the method described in the original study ^[27].

αSyn (100 µM) was incubated with 200 µM PD, PL, and PB for 72 h, after which the samples were collected and either used as a total fraction or separated into insoluble fractions by pelleting assay. Biosensor cells were transduced with 1 µM total or insoluble fractions for 72 h. Fluorescent CFP/YFP inclusions were not observed in the absence of exogenous fibrils (Fig. 6a) or when cells were transduced with fibrils without the TurboFect transfection reagent (Fig. 6a; Fig. S8), consistent with previous findings that liposome-mediated transduction is necessary to induce seeding ^[27]. Cells transduced with fibrils formed in the presence of inhibitor peptides exhibited significantly fewer CFP/YFP inclusions than those transduced with control total or insoluble αSyn fibrils (Fig. 6b-d). PB was the most effective in reducing the seed competency of αSyn fibrils compared to the other inhibitors (Fig. 6c, d). The inhibitor peptides alone did not induce seeding, as cells transduced with only the inhibitors showed no CFP/YFP inclusions (Fig. S8).

We verified confocal microscopy results using FRET cytometry, which also showed reduced seed competency of αSyn fibrils formed in the presence of inhibitors (Fig. 6e; Fig. S8). Given that the prion-like behavior of αSyn fibrils relies on their structural features ^[28–30], the loss of seeding competency in fibrils formed in the presence of inhibitors underscores the importance of these structural disruptions. The FRET cytometry data corroborated our CFP/YFP inclusion count results, further confirming the reliability of inclusion counting as demonstrated in this study and supported by a previous study ^[31].

Inhibitor peptides Specifically Delay Nucleation of NAC16 and NAC11 Aggregation

To understand the specific effects of inhibitors on NAC aggregation, we used NAC35 and its truncated variants (NAC16 and NAC11). Peptides (100 µM) were incubated with or without 100 µM inhibitor peptides, and aggregation was monitored by ThT assay in neutral buffer. The results demonstrate region-specific effects of inhibitor peptides on NAC35, NAC16, and NAC11 aggregation. For NAC35, the inhibitors shortened the lag time of aggregation (Fig. 6a, d). In contrast, the inhibitors increased the lag time of aggregation of the truncated NAC16 and NAC11 (Fig. 6b, c, e, f). However, despite the shortened lag time of NAC35 aggregation, the total amount of amyloid fibrils formed was significantly reduced in the presence of inhibitors (Fig. 6g). These results suggest that inhibitors likely target the hydrophobic 68GAVV71 region or nearby residues, where hydrophobic interactions critical for nucleation of aggregation occurs ^[17]. This presumption is supported by the distinct responses observed with NAC16 and NAC11, which have fewer hydrophobic residues than NAC35. The significant delay in aggregating these truncated NAC peptides in the presence of inhibitors possibly indicates the disruption of hydrophobic interaction inhibits nucleation.

In contrast, NAC35 showed a shortened lag time in the presence of inhibitors. The extended sequence of NAC35 (61–95) could result in partial aggregation before the inhibitors fully engage with the critical hydrophobic residues, particularly 68GAVV71. The subsequent interference with fibril growth by the inhibitors possibly then disrupts fibril elongation and maturation processes, as evidenced by the overall reduction in amyloid fibril formation.

PB Inhibitor Targets 68GAVV71 in NAC to Disrupt αSyn Aggregation and Seeding Competency

We next selected the PB inhibitor for further investigation due to its better effectiveness in reducing seeding competency and its higher activity against truncated NAC peptides. MD simulations revealed possible mechanisms by which PB inhibits αSyn aggregation by affecting NAC stability, aggregation behavior, and specific residue interactions. Changes in the root mean squared deviations (RMSD) were initially analyzed to confirm system stability during the simulation, which showed lower RMSD values (Fig. 8a). NAC35, which contains more amino acids compared to NAC16 and NAC11, exhibited greater fluctuations in the simulation, indicating that the extended peptide length contributed to reduced structural stability. After adding the PB inhibitor to the simulation, the RMSD values and their fluctuations increased for all NAC peptides. This suggests that PB disrupted the aggregation and caused the NAC peptides to deviate further from their initial conformations, leading to continued structural instability.

Next, mean squared displacements (MSD) were analyzed, showing a higher slope for NAC peptides in the presence of PB compared to NAC alone, indicating increased diffusion, which supports the anti-aggregation effects of PB (Fig. 8b). Solvent-accessible surface area (SASA) analysis further revealed a decrease in SASA of NAC peptides during aggregation (Fig. 8c). This decrease was more pronounced in the NAC alone systems compared to NAC + PB systems, suggesting that PB inhibits the compactness of NAC peptides during the aggregation, with PB exerting the most potent effect on NAC11 compared to NAC16 and NAC35. The increased diffusion and reduced compaction in the presence of PB explain the enhanced susceptibility of NAC16 (63–78) and NAC11 (68–78) to inhibition. Their truncated sequences likely expose key hydrophobic residues, allowing PB to block the interactions necessary for aggregation more effectively. The SASA of PB remained relatively stable throughout the simulation, indicating that PB maintained its structural stability without undergoing significant conformational changes or aggregation, consistent with experimental data showing that PB does not aggregate on its own (Fig. S6). Molecular coordination frames of PB alone and NAC peptides with PB at T = 0 ns and T = 100 ns show the stability of PB over time and its interactions with the NAC peptides, which contribute to the inhibition of NAC35, NAC16, and NAC11 aggregation (Fig. 8e-h).

Further residue-level analysis revealed key self-aggregation sites in NAC35, NAC16, and NAC11, in addition to resides involved in PB interactions (Table 1). In NAC35, the most frequently interacting residues were 63VTQ65, 67GGAVVTGVTA76, and 79QKTV82. In NAC16, these interacting residues included 63VTNVGGAV70 and 75TA76, while in NAC11, these consisted of 69AVVTGVTA76. PB interacted with multiple residues in NAC35, including G67, A69, V70, and T72, within the region critical for aggregation. For NAC16, PB binding residues extended from T64 to V77, while for NAC11, PB primarily interacted with the 69AVVT72 stretch.

Overall, MD simulation results provide further clarity, showing that PB interacts with critical residues, including 68GAVV71 in the NAC domain, and suggest that PB interaction with these residues is essential for disrupting αSyn aggregation and reducing the seeding activity of the formed fibrils.

Table 1

List of the amino acids in NAC involved in self-aggregation and interactions with PB inhibitor. Molecular interaction maps showing the interacting residues are provided in **Fig. S10-15**.
NAC VARIANTS	SELF-AGGREGATION RESIDUES	PB INTERACTION RESIDUES
NAC35	63VTQ65, 67GGAVVTGVTA76, and 79QKTV82	G67, 69AV70, T72, 74VT75, and 82VEG84
NAC16	63VTNVGGAV70, and 75TA76	T64, 66VGG68, 70VVT72, and V77
NAC11	69AVVTGVTA76	69AVVT72

In this study, we provided a detailed examination of the hydrophobic NAC domain (residues 61–95) in αSyn aggregation, focusing on the critical residues 68GAVV71. Our findings demonstrate that while the 71VTGVTAVAQKTV82 region promotes aggregation, it is insufficient alone, as shown by the lack of aggregation in NAC12 (71–82). In contrast, including flanking residues in NAC16 (63–78) and NAC11 (68–78) facilitated aggregation, highlighting the importance of regions outside the core. NAC35 (61–95) exhibited a stronger aggregation propensity and formed seed-competent fibrils, confirming that residues beyond 68GAVV71 are necessary for promoting stable fibrils and seeding activity. Inhibitory peptides targeting the NAC domain effectively blocked αSyn aggregation, with PB particularly effective in disrupting hydrophobic interactions mediated by 68GAVV71. Our study on the NAC region advances the understanding of the molecular mechanisms of αSyn aggregation, thus presenting 68GAVV71 in the NAC domain as a potential molecular target for αSyn pathology.

NAC and inhibitor peptides and recombinant human αSyn (A53T) protein

NAC35, NAC17, NAC16, NAC12, NAC11, and NAC8 peptides were custom-designed and synthesized by GenScript Biotech (Piscataway, NJ, United States). The purity of the peptides was ≥ 95%. The lyophilized peptides were dissolved in sterile DMSO according to the manufacturer’s instructions and stored at -80°C until further use. The concentrations of the dissolved peptides were determined by UV spectrometry at 280 nm.

PD, PL, and PB inhibitory peptides were purchased from Mimotopes (Victoria, Australia). The inhibitor peptides were dissolved in sterile MilliQ water and stored at -80°C until use. The expression and purification of recombinant human αSyn (A53T) protein was done as described previously ^[32].

ThT and ANS fluorescence-based aggregation kinetics assays

The aggregation of NAC peptides was monitored using ThT and ANS binding assays ^[33]. Briefly, NAC peptides stored at -80°C were thawed on ice and centrifuged at 13,000 rpm for 45 seconds on a benchtop centrifuge. A reaction mixture containing 25–100 µΜ NAC peptides and 15 µΜ ThT (Sigma-Aldrich, Cat. # T3516-5G) or 40 µM 8-anilino-1-naphthalenesulfonic acid (ANS; Sigma-Aldrich, Cat. # A1028-5G) was prepared in 1× phosphate-buffered saline (PBS) at either pH 4.2, 7.2 or 8.0 on ice. The reaction mixture (40 µL) was then dispensed into a clear-bottom, black 384-well plate (Revvity, Waltham, MA, United States), and the plate was sealed with a TopSealA-PLUS (Revvity) to prevent evaporation. The aggregation kinetics was monitored on an EnSpire Multimode Plate Reader (Revvity) at 37°C and a constant agitation of 1000 rpm. To prevent condensation in the assay plate, the upper heater temperature in the plate reader was set to 2°C warmer than the lower heater temperature. ThT (Ex: 460–490 nm, Em: 500–550 nm) and ANS (Ex: 390 nm, Em: 475 nm) fluorescence readings were recorded every 5–10 minutes for 48–72 hours. ThT and ANS fluorescence readings from respective kinetics assays were normalized to the lower and higher relative fluorescence intensity values in the dataset using GraphPad Prism software (version 10; Boston, MA, United States) to generate normalized ThT and ANS plots. The lag time of aggregation was determined by fitting a Boltzmann sigmoidal equation to the fluorescence data in OriginPro 2024 (OriginLab Corporation, Northampton, MA, United States).

Effect of inhibitor peptides on αSyn and NAC aggregation

Recombinant αSyn (A53T) was incubated with PD, PL, PB, or scrambled peptides at a 1:2 molar ratio (100–150 µM αSyn:200–300 µM inhibitor) in the presence of 50 µM ThT. The incubation was performed at 37°C with constant agitation at 850 rpm in a Turbo Thermo Shaker (TMS-200; Allsheng, Hangzhou, China). The formation of amyloid fibrils was monitored by measuring ThT fluorescence over 72 h, as described previously ^[32].

NAC peptides were incubated with inhibitor peptides at a 1:1 molar ratio (100 µM NAC:100 µM inhibitor peptide), and their aggregation was monitored using the ThT assay, as detailed in the previous section.

Pelleting assay and fibril concentration quantification

Recombinant αSyn (100–150 µM) was aggregated with or without inhibitor peptides (1:2 molar ratio) in 100 µL per well of a 96-well ViewPlate (Revvity; Part no. # 6005225) at 37°C in a PST-60HL Thermostat Plate Shaker (Biosan, Riga, Latvia) with constant agitation at 1000 rpm. After 72 h, the contents of each well were collected and transferred into Eppendorf tubes. Twenty percent of the supernatant was stored as the ‘total fraction,’ and the remaining sample was centrifuged at 65,000 × g for 1 h at room temperature on a benchtop centrifuge. The supernatant was collected as the ‘soluble fraction’ and transferred to fresh tubes. The pellet was resuspended in 80 µL of 1× PBS (pH 7.2) and centrifuged again at 65,000 × g for 1 h. After discarding the second supernatant, the pellet was resuspended in 8 µL of 1× PBS (pH 7.2) to make a 10× concentrated ‘insoluble fraction.’

For in vitro seeding assay, αSyn (100 µM), NAC35 (100 µM), NAC16 (200 µM), and NAC11 (200 µM) peptides were aggregated without ThT for 48–72 h. After incubation, the contents of assay wells were pooled to 100 µL in Eppendorf tubes and centrifuged to separate into soluble and insoluble fractions as described above. The formation of fibrils was confirmed by mixing 10 µL of aggregated sample with 15 µM ThT and reading the signal using the EnSpire Multimode Plate Reader (Revvity).

The concentration of the total fraction was measured using the Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific Inc., Waltham, MA, United States, Cat. # 23225). To estimate αSyn fibril concentration in the insoluble fraction, the decrease in monomer concentration in the soluble fraction was used by measuring the concentration before and after aggregation. The difference was used to estimate the concentration of fibrils formed.

In vitro seeding assay

αSyn (100 µM) was incubated with 25 µM insoluble fractions (preformed fibrils) of αSyn, NAC35, NAC16, and NAC11 in a 100–150 µL volume per well of a 96-well ViewPlate in the presence of 50 µM ThT at 37°C in a PST-60HL Plate Shaker-Thermostat with constant agitation (1000 rpm). ThT fluorescence was recorded every 4 h for the first 12 h and then every 24 h for 72 h.

After 72 h of aggregation, the contents of each well were collected and processed by the pelleting assay to obtain soluble and insoluble fractions. The insoluble fractions were then used for dot blot analysis and Coomassie gel staining.

Coomassie gel staining

The soluble and 10× concentrated insoluble fractions were mixed with 2× Laemmli buffer [62.5 mM Tris-HCl (pH 6.8), 25% (w/v) glycerol, 2% SDS, and 0.01% Bromophenol Blue, supplemented with 5% (v/v) 2-mercaptoethanol] and boiled at 95°C for 5 min. Sixteen µL of the insoluble fraction and an equal volume of soluble fraction were then subjected to electrophoresis using Mini-PROTEAN TGX 4–20% Precast gels (Bio-Rad, Cat. # 4561095) in Tris/glycine/SDS running buffer (Bio-Rad).

Gels were fixed in 50% methanol (v/v) and 10% acetic acid (v/v) for 1 h, stained with Coomassie Brilliant Blue R-250 Staining Solution (Bio-Rad, Cat. # 1610436EDU) for 12 h at 4°C with gentle agitation, and destained in deionized water. Gel images were acquired using a Gel Doc XR + Gel Documentation System (Bio-Rad, California, United States), and densitometry was performed using the ImageJ software (Bethesda, Maryland, United States).

Dot blot analysis

Dot blot analysis was performed using the insoluble fractions of αSyn fibrils formed in the absence or presence of inhibitor peptides or preformed fibrils. Five µL of the insoluble fraction (2.5 µL first, allowed to dry completely, then another 2.5 µL) was spotted onto a nitrocellulose membrane (Bio-Rad, Cat. # 1620147), pre-divided into uniform circular grids, and allowed to dry for 10 min at room temperature. The membrane was then blocked for 1 h with 5% bovine serum albumin (BSA) in 1× Tris-buffered saline with 0.05% Tween® 20 (TBST), followed by 3× washes with TBST. The membrane was then incubated for 1 h with anti-α-Synuclein (D37A6) rabbit monoclonal antibody (Cell Signaling Technology, Inc., Danvers, MA, United States, Cat. # 4179) at a 1:2000 dilution in 5% BSA/TBST. After 3× washes with TBST, the blot was incubated with Alexa Fluor™ 647 Goat anti-Rabbit IgG (Thermo Fisher Scientific; Cat. # A-21245) at a 1:5000 dilution for 1 h. The blot was imaged using the Gel Doc XR + Gel Documentation System, and densitometry was performed using ImageJ.

UV-vis spectrophotometry

NAC peptides (100 µM) were aggregated without ThT for 48 h. Samples were collected at 24 h intervals and transferred to a 384-well SpectraPlate (Revvity). Alternatively, after 48 h of complete aggregation, the contents of assay wells were pooled to a total volume of 100 µL for pelleting assay. Equal volumes of soluble and insoluble fractions were resuspended in 1× PBS (pH 7.2) at a 1:1 ratio in a 384-well SpectraPlate. UV-Vis absorption spectra from 400 to 600 nm were acquired using an EnSpire Multimode Plate Reader (Revvity) with a resolution of 10 nm.

Atomic force microscopy

NAC peptide aggregates, collected after 48 h of the aggregation assay, were added dropwise onto a freshly cleaved 10 mm AFM mica disc (Ted Pella, Inc., Redding, CA, United States) and air-dried for 10 min at room temperature. The mica discs were washed five times with deionized water sterilized using a 0.22 µm sterile syringe filter (Merck Millipore, Burlington, MA, United States) and then dried for 10–15 min at room temperature. AFM imaging was performed as previously described ^[33], using the SCANASYST AIR probe (tip radius: 2 nm, spring constant: 0.4 N/m).

Raman spectroscopy

NAC peptide monomers and samples aggregated for 48 h were subjected to Raman analysis. The Raman system used was equipped with a green laser operating at 532 nm with a power of 1 mW measured on the sample. The exposition time was set to 3s, and spectra were averaged from 28 micro-scans. Each sample was placed on CaF₂ microscopy glass (Crystan Ltd., Poole, Dorset, UK) and measured at ten randomly selected spots. The spectral data were processed using a Python script (version 3.11). First, the fluorescent background was removed by subtracting a polynomial function (n = 5), and then the spectra were smoothed using the Savitzky-Golay method.

Transmission electron microscopy

Specimens of NAC35, NAC16, and NAC11 aggregates for transmission electron microscopy were prepared on glow-discharged carbon-coated copper grids and negatively stained with 2% uranyl acetate. Electron microscopy was performed on a Tecnai G2 F20 microscope (FEI Technologies, Hillsboro, United States) with an Eagle 4K CCD camera (FEI Technologies) at 29,232× magnification. The pixel size at the specimen level after binning the images to 2,048 x 2,048 pixels was 1.14 nm. Approximately 20 micrographs of each specimen were recorded and evaluated.

Alternatively, a small drop of the suspension (2–10 µL) is loaded on a glow-discharged (plasma-treated) carbon-coated grid. After 1 minute of incubation, the sample solution was removed from the grid by blotting with filter paper, followed immediately by adding 2–10 µL negative stain solution. After 1 minute, the stain was removed by aspiration carefully using a filter paper on the edge of the grid. The images were then recorded at the Zernike Institute for Advanced Materials, University of Groningen, Netherlands, using a CM100 TWIN Transmission Electron Microscope (Philips, Amsterdam, Netherlands) equipped with a side-mounted Veleta Camera (Olympus, Tokyo, Japan) and processed in the iTEM software suite (Olympus). Fibril width was measured using the software ImageJ.

Microscale thermophoresis

Purified αSyn was dialyzed against 0.01 M phosphate-buffered saline (PBS), pH 7.4. The binding affinity of the inhibitor peptide was measured by microscale thermophoresis (MST) using a Nanotemper Monolith NT.115 instrument (Nanotemper Technologies GmbH, Munich, Germany). Recombinant αSyn was freshly labeled with the Monolith His-Tag RED-tris-NTA labeling dye according to the manufacturer’s protocol (Nanotemper Technologies GmbH). Measurements were conducted in MST buffer (50 mM Tris, 250 mM NaCl, pH 7.0) using standard capillaries (K002; Nanotemper Technologies GmbH). The final concentration of the labeled αSyn in the assay was 50 nM. Binding reactions were incubated on ice for 5 minutes, then centrifuged at 20,000 x g before loading into the standard glass capillaries (Monolith NTCapillaries, Nano Temper Technologies GmbH). All the measurements were performed with the LED set to 20% intensity and the MST power set to 50%. The laser on-time was 30 seconds, and the laser off-time was 5 seconds.

Fibril transduction of biosensor cells

HEK293T αSyn (A53T)-CFP/YFP biosensor cells were kindly provided by Dr. Marc Diamond from the University of Texas Southwestern Medical Center (Dallas, TX, United States). The cells were maintained in complete growth media consisting of 88% Dulbecco's Modified Eagle's growth medium (Lonza, Cat. # 12–604F), supplemented with 10% (v/v) fetal bovine serum (Thermo Fisher Scientific Inc., Cat. # A5256701), 10 mM HEPES (Serana Europe GmbH, Brandenburg, Germany; Cat # BSL-001-100ML), 1% (v/v) GlutaMAX™ Supplement (Thermo Fisher Scientific Inc., Cat. # 35050061), and 1% (v/v) Penicillin-Streptomycin Solution (Thermo Fisher Scientific Inc., Cat. # 15140130). Cells were maintained at 37°C in a humidified incubator with 5% CO₂/atmospheric air and routinely tested for mycoplasma contamination.

Cells were plated in 96-well Phenoplate (Revvity, Cat. #6057802; 5,000 cells per 100 µL) or 24-well plate (20,000 cells per 1 mL) in complete growth media. Both plates were pre-coated overnight with 50 µg/mL Poly-ᴅ-Lysine (Sigma-Aldrich, Cat. # P6407). After plating, the plates were left at room temperature for 30 minutes to enhance cell spreading before returning them to the incubator. The following day, cells were transfected with 1 µM αSyn fibrils from one of the two fractions: the total fraction (containing both monomers and fibrils) or the insoluble fraction (containing primarily fibrils). These fractions were prepared by aggregating αSyn with or without inhibitors, followed by pelleting assay (see Pelleting Assay section).

Transfection mixtures were prepared by combining 1 µM of the total fraction or insoluble fraction, or an equivalent concentration of only inhibitor peptides, in 20 µL (for 96-well plate) or 100 µL (for 24-well plate) of Opti-MEM™ I Reduced Serum Medium (Thermo Fisher Scientific Inc., Cat. #11058021), supplemented with 0.5 µL (96-well plate) or 4 µL (24-well plate) TurboFect™ Transfection Reagent (Thermo Fisher Scientific Inc., Cat. # R0531). The mixture was briefly vortexed and incubated at room temperature for 15 min before adding to cells. Controls included mixtures with Opti-MEM and TurboFect™ but without αSyn, or Opti-MEM and αSyn but without TurboFect™. Before the transfection mixtures, αSyn samples were sonicated using Branson Ultrasonic™ Sonifier Cup Horns (Marshall Scientific, Hampton, NH, United States) with settings: 50% amplitude, 30 seconds ON, 10 seconds OFF, for a total of 1 min, to break fibrils into smaller fragments.

Twenty µL (for 96-well plate) or 100 µL (for 24-well plate) of transfection mixture was added dropwise to the cells, and the plate was gently tapped to mix the contents. After 72 h, cells were either fixed directly in the plates for imaging or harvested using 0.5%Trypsin-EDTA (Thermo Fisher Scientific Inc., Cat. # 15400054) and then fixed with 2% paraformaldehyde (Electron Microscopy Services, Hatfield, PA, United States, Cat. # 15714-1L) for 10 min at room temperature. Fixed cells in 96-well plates were washed once with 1× PBS and stained with 10 µM Hoechst-33342 nuclear dye (Invitrogen, Cat. #H21492) diluted in PBS for 10 min at room temperature. To preserve the cells for imaging, a 1% glycerol solution prepared in deionized water was added to each well. For flow cytometric analysis, trypsinized cells from 3 wells per experiment condition were pooled, fixed with 2% paraformaldehyde, washed once with PBS, and then resuspended in PBS for further processing.

Confocal imaging

Cells were imaged using a high-content imaging system (Cell Voyager 7000S; Yokogawa, Tokyo, Japan) with a 20× objective. CFP/YFP inclusions of αSyn (A53T) were detected using a 488 nm laser line (Ex = 460–490 nm, Em = 500–550 nm), while Hoechst-33342-stained nuclei were detected using the 405 nm laser line (Ex = 360–400 nm, Em = 410–480 nm). At least 10 focal areas per well were imaged for each experimental replicate. Acquired images were processed using Signals Image Artist (Revvity). The number of cells quantified by Hoechst-stained nuclei and the number of CFP/YFP inclusions used to quantify intracellular seeding were analyzed using an image analysis script in Signals Image Artist (see Appendix S1 above). The total number of inclusions per well was normalized to cell confluence.

Flow cytometry

Cells were analyzed on a FACSAria II Sorpe flow cytometer (BD Biosciences, Franklin Lakes, NJ, United States). Initially, 50,000 cells were acquired to set up gating. Dead cells and debris were excluded using forward scatter versus side scatter gating. Intact cells were then gated and analyzed in the blue/green channels. The gating strategy to identify cells with aggregates (P2 gate) was based on the expression levels of fluorescent protein tags (CFP/YFP). YFP was excited with a 488 nm laser, and emission was detected by a 525/50 nm (green) bandpass filter. CFP was excited with a 445 nm laser, and emission was detected by a 530/30 nm (blue) bandpass filter. The integrated FRET density, as previously described ^[27], was calculated by multiplying the percentage of FRET-positive cells by their median fluorescence intensity within the FRET-positive gate. This density was then normalized for fibril-treated groups relative to untreated controls (cells not exposed to fibrils). Data analysis was performed using BD FACSDiva™ Software.

Molecular dynamics simulation

MD simulations were conducted using the GROMACS package (version 2023) with parameters from the GROMOS-53A6 force field. The molecular structures of peptides were obtained from the Swiss-Model web server (swissmodel.expasy.org). Equimolar ratios of PB and NAC35, NAC16, and NAC11 were randomly placed in the simulation boxes. The system was solvated with the extended simple point charge (SPC/E) water model. Following electrical neutralization, energy minimization was performed using the steepest descent algorithm until the maximum force on atoms was below 10 kJ/mol/nm. The temperature was maintained at 300 K and pressure at 1 bar using a V-rescaling thermostat and Parrinello-Rahman barostat, respectively. Short-range non-bonded interactions were calculated with a cutoff of 1.2 nm for both Columbic and non-Columbic forces. The simulation proceeded for 100 ns using the leapfrog algorithm, based on pre-experimental MD. Two-dimensional illustrations were created with LigPlot software, and three-dimensional illustrations were generated using VMD software.

Statistics

Data are presented as mean ± SEM (n ≥ 2 independent experiments, unless stated otherwise). One-way ANOVA tests were utilized to compare means across multiple groups within a single factor. Multiple comparisons for ANOVA tests were performed using Tukey's. Statistical significance was set at P < 0.05.

Supporting Information

Supplementary figures and tables are provided in the Supplementary Information.

Acknowledgements

This work was supported in parts by the infrastructural projects (CZ-OPENSCREEN – LM2023052; EATRIS-CZ – LM2023053), the Czech biobank network (BBMRI - LM2023033), large RI Project (Czech-BioImaging – LM2023050; LM2018129), the projects National Institute for Cancer Research (Program EXCELES, ID Project No. LX22NPO5102) and National Institute for Neurological Research (Program EXCELES, ID Project No. LX22NPO5107) - Funded by the European Union - Next Generation EU from the Ministry of Education, Youth and Sports of the Czech Republic (MEYS), project TN02000109 (Personalized Medicine: From Translational Research into Biomedical Applications is co-financed with the state support of the Technology Agency of the Czech Republic as part of the National Centers of Competence Program), and the Grant Agency of the Czech Republic (Grant # 23-06301J). The authors acknowledge the research council of Tarbiat Modares University. MN and SH were visiting scientists at Palacky University, supported by the European Commission through a grant (VIDEC: 872195). We thank Dr. Marc Diamond at the University of Texas Southwestern Medical Center for providing alpha-synuclein biosensor cells.

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The authors declare no competing interests.

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Targeting Hydrophobic Residues in the Alpha-Synuclein NAC Domain Disrupts Aggregation and Seed-Competent Fibril Formation

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Abstract

Figures

Introduction

Results and Discussion

Solubility Does Not Explain the Lack of Aggregation of NAC17, NAC12, and NAC8

Raman Spectroscopy Confirms β-Sheet Changes in NAC35, NAC16, and NAC11 Fibrils

Seeding Competency of NAC35, NAC16 and NAC11 Fibrils

Inhibitory Peptides Targeting NAC Domain Reduce αSyn Dimerization and Aggregation

Inhibitor Peptides Targeting αSyn Hydrophobic Region Impede Seeding Competency of Fibrils

Inhibitor peptides Specifically Delay Nucleation of NAC16 and NAC11 Aggregation

PB Inhibitor Targets 68GAVV71 in NAC to Disrupt αSyn Aggregation and Seeding Competency

Conclusion

Experimental Method

NAC and inhibitor peptides and recombinant human αSyn (A53T) protein

ThT and ANS fluorescence-based aggregation kinetics assays

Effect of inhibitor peptides on αSyn and NAC aggregation

Pelleting assay and fibril concentration quantification

In vitro seeding assay

Coomassie gel staining

Dot blot analysis

UV-vis spectrophotometry

Atomic force microscopy

Raman spectroscopy

Transmission electron microscopy

Microscale thermophoresis

Fibril transduction of biosensor cells

Confocal imaging

Flow cytometry

Molecular dynamics simulation

Statistics

Declarations

Supporting Information

Acknowledgements

References

Additional Declarations

Supplementary Files

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