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Article

Effect of Bacterial Amyloid Protein Phenol−Soluble Modulin Alpha 3 on the Aggregation of Amyloid Beta Protein Associated with Alzheimer’s Disease

by
Bushu Peng
,
Shaoying Xu
,
Yue Liang
,
Xiaoyan Dong
* and
Yan Sun
*
Department of Biochemical Engineering, School of Chemical Engineering and Technology, Key Laboratory of Systems Bioengineering and Frontiers Science Center for Synthetic Biology (Ministry of Education), Tianjin University, Tianjin 300350, China
*
Authors to whom correspondence should be addressed.
Biomimetics 2023, 8(6), 459; https://doi.org/10.3390/biomimetics8060459
Submission received: 20 August 2023 / Revised: 24 September 2023 / Accepted: 26 September 2023 / Published: 1 October 2023
(This article belongs to the Special Issue Biomimetic Peptides and Proteins)
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Abstract

:
Since the proposal of the brainstem axis theory, increasing research attention has been paid to the interactions between bacterial amyloids produced by intestinal flora and the amyloid β−protein (Aβ) related to Alzheimer’s disease (AD), and it has been considered as the possible cause of AD. Therefore, phenol−soluble modulin (PSM) α3, the most virulent protein secreted by Staphylococcus aureus, has attracted much attention. In this work, the effect of PSMα3 with a unique cross−α fibril architecture on the aggregation of pathogenic Aβ40 of AD was studied by extensive biophysical characterizations. The results proposed that the PSMα3 monomer inhibited the aggregation of Aβ40 in a concentration−dependent manner and changed the aggregation pathway to form granular aggregates. However, PSMα3 oligomers promoted the generation of the β−sheet structure, thus shortening the lag phase of Aβ40 aggregation. Moreover, the higher the cross−α content of PSMα3, the stronger the effect of the promotion, indicating that the cross−α structure of PSMα3 plays a crucial role in the aggregation of Aβ40. Further molecular dynamics (MD) simulations have shown that the Met1−Gly20 region in the PSMα3 monomer can be combined with the Asp1−Ala2 and His13−Val36 regions in the Aβ40 monomer by hydrophobic and electrostatic interactions, which prevents the conformational conversion of Aβ40 from the α−helix to β−sheet structure. By contrast, PSMα3 oligomers mainly combined with the central hydrophobic core (CHC) and the C−terminal region of the Aβ40 monomer by weak H−bonding and hydrophobic interactions, which could not inhibit the transition to the β−sheet structure in the aggregation pathway. Thus, the research has unraveled molecular interactions between Aβ40 and PSMα3 of different structures and provided a deeper understanding of the complex interactions between bacterial amyloids and AD−related pathogenic Aβ.

1. Introduction

Alzheimer’s disease (AD), one of the most common neurodegenerative diseases, is widely recognized as the major cause of dementia. The pathological feature of AD is the plaques formed between neurons in the brain by abnormal levels of the amyloid β−protein (Aβ) and the intracellular neurofibrillary tangles caused by the hyperphosphorylation of tau [1,2,3]. The amyloids cascade hypothesis suggests that Aβ deposition triggers neuronal dysfunction and death in the brain associated with the disease [4]. In recent years, increasing evidence has identified that the gastrointestinal tract and the central nervous system can be bi−directionally linked through the microbiota–gut–brain axis, indicating potentially common pathogenic mechanisms among these diseases. Thus, the intestinal microbiota not only modulates the gastrointestinal tract, but also influences the function and development of the brain. It has been discovered that gut dysbiosis is linked to neurodegenerative diseases, such as AD, depression, and Parkinson’s disease [5,6,7,8,9,10,11]. Studies have shown that the interaction of bacterial amyloids produced by intestinal flora and pathogenic amyloids related to neurodegenerative diseases may be one of the main triggers of AD [12,13]. Recent studies on bacterial amyloids have shown that CsgA, the major subunit of bacterial amyloids curli secreted by Escherichia coli, could accelerate the formation of Aβ40 fibrils in vitro [14]. The FapC amyloid fragment has been shown to accelerate Aβ aggregation, inducing the neurotoxicity and pathological features of AD [15]. These results demonstrate that bacterial amyloids can interact with pathogenic amyloids, potentially influencing the development of neurodegenerative diseases through a novel mechanism of amyloidosis. However, the specific mechanisms behind the interaction between bacterial amyloids and Aβ remain elusive and require further exploration.
Phenol−soluble modulins (PSMs) are amphiphilic peptides with a wide range of cytolytic activities, and they serve as an important virulence factor secreted by Staphylococcus aureus (S. aureus), a representative member of the intestinal flora. The PSM peptides play an important role in stabilizing the biofilm structure by enhancing the biofilm matrix, resisting mechanical stress, and degrading enzyme catabolism [16]. PSMα3 is the most cytotoxic and soluble of the PSM peptides [17] and has attracted much attention because of its cross−α fibril structure [13]. The unique conformation of PSMα3 potentiates its toxicity to human cells [18]. The cross−α structure is a newly discovered self−assembly pattern that differs from the typical β−sheet structure. It exhibits an accumulation of α−helix structures perpendicular to the fibril axis (Figure S1) [19]. Previous studies have shown that PSM peptides can selectively cross−seed each other, indicating complex interactions between different PSM peptides [20]. A model has been proposed to describe the complex interaction among various PSM peptides in biofilm formation. The rapidly aggregated PSMα3 accelerates the assembly of PSMα1, and PSMα1 accelerates the aggregation of the remaining PSM peptides [20]. PSM monomers can aggregate into bacterial functional amyloids and cross−seed each other, accelerating the aggregation process. However, the effect of PSMα3 produced by S. aureus with a unique cross−α structure on the aggregation of Aβ remains poorly understood.
Therefore, the effect of PSMα3 on the aggregation process of Aβ40 was investigated in this study, using various experimental methods such as Thioflavin T (ThT) fluorescence assays, circular dichroism (CD) experiments, and atomic force microscopy (AFM). Moreover, the interaction mechanism between PSMα3 and Aβ40 was analyzed via molecular dynamics (MD) simulations to reveal the influencing mechanism of the intestinal flora on AD at the molecular level.

2. Materials and Methods

2.1. Materials

Aβ40 (>95%) was provided by GL Biochem (Shanghai, China). PSMα3 (>95%) was provided by ZiYu Biotech (Shanghai, China). 1,1,1,3,3,3−Hexafluoro−2−propanol (HFIP) and ThT were provided by Sigma (St. Louis, MO, USA). Antibodies 6E10 and OC were obtained from Covance (Dedham, MA, USA). Secondary antibodies anti−mouse IgG and anti−rabbit IgG were provided by Beyotime (Shanghai, China).

2.2. Preparation of Aβ40 and PSMα3 Monomers

Aβ40 was pretreated according to the literature [21]. Aβ40 was dissolved in HFIP at a concentration of 1.0 mg/mL and placed stably at 4 °C for 2 h. The solution was then ultrasonicated for 20 min in an ice bath to destroy the Aβ40 aggregates. Then, a freeze dryer (FreeZone, Labconco, Kansas City, MI, USA) was used to remove HFIP to obtain fluffy flocculent Aβ40, which was stored at −20 °C. PSMα3 was treated by the same procedure as Aβ40 and stored at −20 °C until the beginning of the experiment to ensure PSMα3 was in a monomeric conformation [21]. For use, Aβ40 and PSMα3 monomers were dissolved in NaOH (20 mM) and ultrasonicated for 5 min, then centrifugated at 16,000× g for 20 min at 4 °C. Then, the peptides were diluted to a final concentration of 25 μM with HEPES buffer (30 mM, pH 7.4).

2.3. Preparation of PSMα3 Seeds

The PSMα3 monomer was incubated in an air−bath shaker at 130 rpm and 37 °C for different times (1 to 24 h) and then centrifugated at 16,000× g for 20 min at 4 °C. PSMα3 seed suspension was obtained by adding PSMα3 solution into HEPES buffer at a concentration of 5 μM.

2.4. ThT Fluorescence Assay

A 200 μL sample containing Aβ40, PSMα3, and equimolar ThT was mixed evenly and added to 96−well plates at a concentration of 25 μM for both Aβ40 and ThT, and the concentration of PSMα3 seeds was 5 μM. The samples were incubated in a fluorescence plate reader (PerkinElmer, LS55, Waltham, MA, USA) with shaking at 30 min intervals at 37 °C. The ThT emission fluorescence at 480 nm was measured by excitation wavelengths at 440 nm. At least three parallel groups were set up for each experiment and the results were averaged after subtracting the corresponding background.

2.5. AFM Experiments

The Aβ40 monomer (25 μM) solution was cultured with or without the PSMα3 monomer and PSMα3 seeds at 37 °C for 100 h. The 50 μL samples were dropped on a flat mica sheet, and then other impurities were carefully washed away with ultrapure water after 10 min. The morphological characteristics of the samples were observed using atomic force microscopy (CSPM5500, Benyuan, Guangzhou, China). The pixels of the images were set to 1024 × 1024, and at least three separate areas of each sample were scanned by AFM to ensure consistency.

2.6. CD Experiments

The secondary structure of Aβ40 aggregates (25 μM) cultured with or without PSMα3 was examined by a CD spectrometer (J−810, JASCO, Tokyo, Japan). The samples were incubated in an air bath shaker for 100 h and then placed in a quartz cell with a 1 mm optical range. The CD spectra were scanned between 260 nm and 190 nm continuously at 100 nm/min with a bandwidth of 1 nm. The CD spectra were averaged from three parallel samples after subtracting the background.

2.7. Dot−Blot Assays

Ten microliters of Aβ40 (25 μM) co−cultured with or without the PSMα3 monomer and seeds was spotted on a nitrocellulose membrane and dried at room temperature for 1 h. The membrane was blocked with 10% skimmed milk for 1 h. After washing three times with TBS−T buffer (20 mM Tris−HCl, 150 mM NaCl, and 0.05% Tween 20, pH 7.4), the membranes were incubated with the Aβ sequence−specific 6E10 antibody (1:1000) and Aβ fibril−specific OC antibody (1:1000) for 1 h at room temperature and washed three times with TBS−T buffer. The membranes were then incubated with horseradish peroxidase−labeled anti−mouse IgG (1:2000) or anti−rabbit IgG (1:2000) for 1 h at room temperature and washed three times with TBS−T buffer. Finally, color development was performed with an ECL chemiluminescence kit (Beyotime, Shanghai, China). Images were taken using a chemiluminescence imaging system (SH−Compact 523, Shenhua, Hangzhou, China).

2.8. MD Simulations

The structures of Aβ40 (PBD ID: 1BA4) [22] and PSMα3 (PBD ID: 5I55) [19] were selected as the templates. The initial structure of the PSMα3 monomer was taken from a PSMα3 fibrous structure formed by a set of twenty helices (PBD ID: 5I55) [19], and one of the helices was selected as the template. To construct a PSMα3 oligomer model, three PSMα3 monomers were placed in parallel with a minimum distance of 1.0 nm to construct an isolated trimeric system [23]. The complex system was formed by docking Aβ40 and PSMα3 using AutoDock Vina [24]. All systems were simulated using the GROMACS 5.1.4 software package [25] with the AMBER 99SB force field [26]. The periodic simulation box was created and the minimum distance from the molecule to the edge of the box was set to 1 nm. The solvent water molecule TIP3P [27] was then filled in the system and Na+ and Cl− ions were added to neutralize the electrostatic charges of the simulated systems. The systems were then optimized by energy minimization and performed a solvent equilibrium in 50,000 steps at a constant NVT of 100 ps and 300 K, followed by a pressure equilibrium of 100 ps at NPT conditions. The MD simulations were then performed for 50 ns with a step size of 1 fs. Previous studies have shown that a simulation time of 50 ns is sufficient to bring the complex to equilibrium and to illustrate conformational transitions in peptides [28,29]. The free binding energy between Aβ40 and PSMα3 was calculated by g_mmpbsa [30]. Pymol was used to obtain snapshots. Three independent MD simulations were carried out for each system.

3. Results and Discussion

3.1. Effects of the PSMα3 Monomer on Aβ40 Aggregation

It has been reported that the cross−α structure of PSMα3 fibrils can specifically bind to the amyloid dye ThT and produce enhanced fluorescence [18]. Here, the aggregation kinetic of PSMα3 was measured by a ThT fluorescence assay. The aggregation of PSMα3 was observed as an immediate increase in ThT fluorescence intensity without a significant lag phase. The ThT fluorescence intensity peaked around 2.5 h and then gradually decreased until it reached equilibrium (Figure S2a). The aggregation of PSMα3 was different from the standard sigmoidal kinetic behavior of Aβ40 [31,32], consistent with previous results [20,33]. Studies have shown that newly formed PSMα3 aggregates are unstable, but they can stabilize the structure by lateral association during aggregation [20]. The CD spectra showed a negative peak at 216 nm (typical β−sheet signal) for Aβ40 aggregates, indicative of a β−sheet−rich structure (Figure S2b). In contrast, the CD spectra of PSMα3 aggregates showed a minimum at 222 nm, implying a reduced helicity of the α−helical structure [34]. Combined with the results of ThT fluorescence experiments in Figure S2a, the above results suggested that PSMα3 formed the cross−α structure composed of an α−helix, which could bind to the amyloid dye ThT [18]. This is consistent with the results of X−ray diffraction spectroscopy and Fourier transform infrared spectroscopy [19,34].
The morphological characteristics of the Aβ40 and PSMα3 aggregates were examined using AFM. Aβ40 formed elongated fibrils after 72 h (Figure S2c), consistent with previous results [35]. However, PSMα3 formed granular aggregates (Figure S2c), different from the elongated fibril structures reported in the literature [19,34]. This was because differences in experimental conditions, such as peptide concentration, buffer ionic strength, pH, and shaking conditions, can affect the morphology of PSMα3 aggregates. Overall, these results demonstrate differences in structure and morphology between Aβ40 and PSMα3 aggregates.
To explore whether PSMα3 plays a role in Aβ40 aggregation, the kinetics of Aβ40 aggregation cultured with different concentrations of the PSMα3 monomer was monitored (Figure 1a,b). It can be seen that the maximum ThT fluorescence intensity of Aβ40 significantly decreased (Figure 1a), and the lag phase prolonged (Table S1) with increasing the concentration of the PSMα3 monomer. The kinetic curves of 0 to 20 h in Figure 1a are magnified in Figure 1b, allowing a clearer observation of the short time changes in the ThT fluorescence intensity. Interestingly, when Aβ40: PSMα3 > 1:1, the aggregation of Aβ40 still followed the sigmoidal kinetic curve with reduced ThT fluorescence. The aggregation of Aβ40 appeared to be completely inhibited by the addition of equal concentrations of the PSMα3 monomer (purple line in Figure 1a). However, when Aβ40: PSMα3 < 1:1, the aggregation kinetics of Aβ40 no longer fitted the typical sigmoidal curve but tended to follow the aggregation kinetics of PSMα3 itself (green and blue lines in Figure 1a). This indicates that the ratio of Aβ40 to PSMα3 monomer influenced the type of aggregation. The amyloids with a higher amount than the other in the mixture dominated the aggregation dynamics and determined the amyloids aggregation pathway. To further explore the mechanism of inhibition, the relevant kinetic parameters, including knk+ (related to the primary pathway) and k2k+ (related to the secondary pathway), were calculated using the Amylofit program [36]. The results revealed that both the knk+ and k2k+ values decreased in the presence of the PSMα3 monomer, while the k2k+ value decreased more significantly (Figure S3a). It indicated that the PSMα3 monomer mainly inhibited the secondary pathway of unseeded Aβ40 aggregation.
The morphology of Aβ40 incubated with different concentrations of the PSMα3 monomer is shown in Figure 1c. When Aβ40: PSMα3 > 1:1, the total density of fibrils detected by AFM decreased and gradually transformed into sparse short fibrils or some granular aggregates. When Aβ40: PSMα3 < 1:1, no fibrous structures can be observed (Figure 1c). This is consistent with the ThT fluorescence assay (Figure 1a), indicating that the PSMα3 monomer inhibited the aggregation of Aβ40 in a concentration−dependent manner and could change the aggregation pathway of Aβ40.
The inhibitory effect of the PSMα3 monomer on Aβ40 aggregation was further demonstrated by dot−blot assays with antibody 6E10 (Aβ1–16 sequence−specific) and antibody OC (fibril−specific) (Figure S4). The 6E10 antibody recognizes the Aβ1–16 sequence, and all of the Aβ species can be stained by it [37]. By staining with 6E10, there was no change in spot size or darkness in any Aβ or Aβ−PSMα3 species at 0 h and 100 h, indicating the stable presence of Aβ during incubation (Figure S4a). At the beginning of incubation (0 h), Aβ fibrils were rarely detected by antibody OC in the presence or absence of the PSMα3 monomer (Figure S4b, left). The OC−positive dots were detected in Aβ40 only after 100 h of incubation, indicating the formation of a large number of Aβ fibrils, consistent with the previous results [38]. However, after co−cultivation with the PSMα3 monomer, the positive response was significantly reduced by increasing the PSMα3 concentration (Figure S4b, right), indicating that the PSMα3 monomer significantly inhibited the formation of Aβ40 fibrils, which was in agreement with the ThT and AFM results (Figure 1).
According to the above results, it can be concluded that the cross−interaction between the PSMα3 monomer and the Aβ40 monomer resulted in the formation of non−fibrillar heterogeneous aggregates (Figure 1c), similar to the hetero−oligomers formed by Aβ and human islet amyloid polypeptide (hIAPP) [39,40] or tau [41]. These heterogeneous structures interfered with the conformational transitions of Aβ40, resulting in reduced ThT fluorescence (Figure 1a). Moreover, Aβ40 and PSMα3 monomers were reported to retain α−helix and disordered structures during the initial stages of aggregation [19,22]. The diversity and instability of structures hindered their common nucleation process, resulting in difficult cross−seeding with each other, and thus leading to an increased lag phase [42].

3.2. Effect of PSMα3 Seeds on Aβ40 Aggregation

The secondary nucleation mechanism of Aβ suggests that preformed fibril seeds of Aβ could accelerate its aggregation process [43]. In addition, several different disease−associated misfolded proteins, such as hIAPP [44], tau [45], and α−synuclein [46], could also hybridize with Aβ and promote amyloids formation. Studies have shown that the main molecular mechanism for the formation of PSM peptides was secondary nucleation with selective cross−seeding ability [20]. To investigate whether PSMα3 seeds accelerate Aβ aggregation through cross−seeding, thereby aggravating AD, cross−seeding experiments were performed using 20% preformed PSMα3 seeds added to the Aβ40 monomer. It was observed that the aggregation of Aβ40 incubated with PSMα3 seeds fitted the sigmoidal kinetic curve with no significant change in the maximum ThT fluorescence intensity (Figure 2a). The results indicated that the PSMα3 seeds had weak effects on the aggregation pathway and the formation of the β−sheet structure of Aβ40. However, compared to the non−seeded aggregation, the lag phase of Aβ40 incubated with PSMα3 seeds significantly decreased (Table S2). The aggregation of Aβ40 incubated with PSMα3 seeds cultured for 2.5 h showed the shortest lag phase (~33.8 h), indicating that the PSMα3 seeds cultured for 2.5 h showed the most significant promotion effect on Aβ40 aggregation. This might be because the ThT fluorescence intensity peaked at 2.5 h in the aggregation kinetic curve of PSMα3 (Figure S2a), indicating that PSMα3 contained the highest content of the cross−α structure after 2.5 h of aggregation. A kinetic analysis revealed a significant increase in knk+ and a slight decrease in k2k+ in the presence of the PSMα3 seeds (Figure S3b). Similarly, the PSMα3 seeds at 2.5 h showed the highest knk+ value, in agreement with the lag phase results (Table S2). These results confirmed that the PSMα3 seeds decreased the lag phase of Aβ40 by promoting the primary pathway, which was different from the role of the PSMα3 monomer (Figure 1a). This may be due to the fact that the PSMα3 seeds were formed by the cross−α structures, which were highly similar to the β−sheet structures [19]. The PSMα3 seeds could serve as templates to facilitate cross−seeding and promote the formation of β−sheet structures, thus accelerating the aggregation of Aβ40 [47]. Meanwhile, the promotion effect of the PSMα3 seeds on Aβ40 aggregation was correlated with the content of the cross−α structure. The higher content of the cross−α structure, the more obvious the promotion effect of the PSMα3 seeds.
To investigate the effect of the PSMα3 seeds on the secondary structure of Aβ40, the CD spectra of Aβ40 induced by the PSMα3 seeds were recorded (Figure 2b). They showed a minimum at approximately 216 nm, and the peak intensity was close to that of Aβ40 cultured alone (Figure 2b). The contents of different secondary structures were calculated from the CD spectrum (Table 1), and it was observed that the content of α−helix structures slightly increased after co−culture with the PSMα3 seeds. This might be because the main secondary structure of the PSMα3 aggregates is α−helix [34] (Figure S2b), thus increasing the content of the α−helix structure in the mixed system. In contrast, the changes in the content of the β−sheet structure were not obvious (~70%) (Table 1), indicating that the PSMα3 seeds had little effect on the content of the β−sheet structure in the Aβ40 aggregates. But compared with the PSMα3 seeds of other incubation times, the cross−seeding of Aβ40 and PSMα3 seeds at 2.5 h had the highest content of α−helix structures (29.3%) and the lowest content of β−sheet structures (63.6%). This also indicated that PSMα3 seeds cultured for 2.5 h contained the highest content of cross−α, consistent with the aggregation kinetics of PSMα3 (Figure S2a). Their interaction with Aβ40 had the most significant impact, which affected the conformational transitions of Aβ40, increased the content of the α−helix structure, and decreased the content of the β−sheet structure. Further observation of the aggregate morphology showed that Aβ40 induced by PSMα3 seeds forms more fibrils than Aβ40 alone, indicating that the PSMα3 seeds promoted the formation of Aβ40 fibrils. Dot−blot assays also showed that Aβ40 co−cultured with PSMα3 seeds exhibited significant OC−positive dots unaffected by increasing the incubation time with the PSMα3 seeds, indicating the substantial formation of Aβ fibrils (Figure S5), consistent with the results of ThT and AFM experiments (Figure 2).

3.3. Molecular Docking of PSMα3 and Aβ40 Monomer

To analyze the PSMα3 monomer (PSMα3m) and oligomer (PSMα3o) binding to Aβ40 at the molecular level, the corresponding composite models were constructed by docking the PSMα3m (PBD ID: 5I55) [19] or the PSMα3o with the Aβ40 monomer (PBD ID: 1BA4) [22] using AutoDock Vina. The docking results demonstrated that the best binding conformation of the Aβ40−PSMα3m complex had a binding free energy of −6.2 kcal/mol in the top 10 binding conformations (Table S3), similar to the binding energies of Aβ and other amyloids, such as Aβ and the hIAPP monomer (~−6.4 kcal/mol) [48,49]. In contrast, the best binding conformation of the Aβ40−PSMα3o complex had a binding free energy of −13.0 kcal/mol (Table S4), over 2.1−fold higher than that of the Aβ40−PSMα3m complex, implying that the PSMα3o binds to the Aβ40 monomer to form a more stable complex than the PSMα3m. This might be because the Aβ40 monomer and the PSMα3m are mostly in α−helix and disordered conformations [36]; the structural disorder and dynamic instability led to difficulties in their binding. However, the PSMα3o formed a stable cross−α structure [23], which facilitated a more stable binding to the Aβ40 monomer.

3.4. MD Simulations on PSMα3 and Aβ40 Monomers and Their Complex

To investigate the effects of the PSMα3m on the conformational transitions of Aβ40, the optimal conformation of the Aβ40−PSMα3m complex was selected as the initial conformation, and 50 ns MD simulations were performed with Aβ40 or the PSMα3m alone as the control for comparison. The root mean square deviation (RMSD) was calculated first to assess the stability of the simulated systems. As shown in the RMSD plots (Figure 3a), the RMSD values of all three systems initially increased rapidly and then stabilized after 30 ns at around 0.4 nm, 0.8 nm, and 0.9 nm, respectively, indicating that all three systems reached equilibrium within 20 ns. It can be seen that the initial equilibrium speed of the Aβ40−PSMα3m complex was slower than that of Aβ40 alone, and its RMSD value was higher than that of Aβ40 alone. These results indicate that the PSMα3m affected the conformational changes of Aβ40 in the initial stage of the simulations and reduced system stability.
To identify the key residues during the interaction between the PSMα3m and the Aβ40 monomer, the root mean square fluctuation (RMSF) of residues in the last 20 ns of the MD simulations was calculated. It was found that the RMSF values of Aβ40 residues in the Aβ40−PSMα3m complex were generally smaller than that of Aβ40 alone (Figure 3b), indicating that the tight binding of the PSMα3m reduced the flexibility of residue fluctuations of Aβ40. Moreover, the fluctuations of the Asp1−His6 and His14−Val36 regions in Aβ40 significantly decreased by the presence of the PSMα3m, indicating that the PSMα3m exhibits a stronger impact on these regions. These results suggested that the PSMα3m tightly bound the Asp1−His6 and His14−Val36 regions in Aβ40 and exhibited a disruptive effect on the Asp23−Lys28 salt bridge in Aβ40. Hydrophobic interactions and the salt bridge have been reported to play a critical role in stabilizing the structure of Aβ fibrils [50]. The disruption of the salt bridge prevented the formation of the β−sheet structure, thus reducing the structural stability of Aβ40 [51].
Furthermore, other structural parameters of different systems were analyzed to estimate the fast conformational transitions of Aβ40. The results showed that the binding of the PSMα3m increased the radius of gyration (Rg) and the solvent−accessible surface area (SASA) of Aβ40 (Table S5), indicating that the PSMα3m changed the conformational denseness of Aβ40 and increased the exposure of the contact area to the solvent, thus destabilizing the system, consistent with the RMSD results (Figure 3a). In addition, the PSMα3m reduced the number of intramolecular hydrogen bonds (H−bonds) of Aβ40 (Table S5), which was detrimental to maintaining the structural stability of Aβ40 [52].
To observe the effect of the PSMα3m on the structure of the Aβ40 monomer, snapshots of Aβ40 and the Aβ40−PSMα3m complex in the initial and equilibrium states were extracted (Figure 3c,d). The conformational transitions from the initial α−helix structure to a random coil structure were observed in the Aβ40 monomer, which is a critical step in forming a highly ordered β−sheet structure for Aβ aggregation [53]. However, the α−helix structure of Aβ40 in the Aβ40−PSMα3m complex was well preserved (Figure 3d), indicating that the PSMα3m inhibited the conformational transitions of the Aβ40 monomer.
The content of secondary structures in the equilibrium state showed that Aβ40 alone contained only 13.8% of the α−helix structure and 4.5% of the β−bridge structure (Table S6), which was a transition structure that transformed into the β−sheet structure [54]. The results indicate that the Aβ40 monomer transformed from the α−helix to the coil structure, and then formed the β−sheet structure, which is consistent with previous studies [55,56]. However, the binding of the PSMα3m resulted in a higher content of the α−helix structure (36.3%) than that of Aβ40 alone, accompanied by a decrease in the content of coil (29.1%) and turn structures (24.1%), and the β−bridge structure was not formed (Table S6). These results showed that the PSMα3m inhibited the conformational transitions of Aβ40 from the α−helix structure to coil and turn structures, thus suppressing the formation of β−sheet structures, which prolonged the lag phase of Aβ40 and inhibited the fibrillization of Aβ40 (Figure 1a and Table S1).
To demonstrate how the PSMα3m inhibits the conformational transitions of Aβ40, we investigated the changes in secondary structure during the whole MD simulation. For Aβ40 alone, the α−helix structures in the Gln15−Ala30 region were rapidly transformed into the coil and turn structures after 20 ns, and the β−bridge was formed in the Phe4−Ser8 region after 40 ns (Figure S6a), consistent with the previous findings [55,56]. In contrast, the Gln15−Asp23 regions maintained their initial α−helix structure during the 50 ns MD simulation in the Aβ40−PSMα3m system. The regions of Val12−Gln15, which had the coil structure in the initial state, transformed into α−helix after 10 ns (Figure S6b). Moreover, no β−sheet or β−bridge structures were detected during the whole 50 ns MD simulations. It is known that the maintenance of the α−helix structure inhibits the aggregation of Aβ into toxic oligomers [57]. Therefore, the PSMα3m inhibited Aβ40 aggregation by stabilizing the formation of α−helix structures and suppressing the generation of β−sheet structures.
To further investigate the intermolecular interactions between the PSMα3m and the Aβ40 monomer, the binding free energy between the PSMα3m and the Aβ40 monomer was calculated. The simulated trajectory of the last 20 ns was collected and calculated by the molecular mechanic Poisson–Boltzmann surface area (MM−PBSA) method [30]. The binding free energy between the PSMα3m and the Aβ40 monomer was −270.7 kJ/mol (Table S7), indicating a high affinity of the PSMα3m and the Aβ40 monomer [48,49]. An analysis of the contribution of each energy component showed that van der Waals hydrophobic energy (ΔGvdw = −373.5 kJ/mol) and electrostatic energy (ΔGelec = −963.9 kJ/mol) were contributing more to the binding than other energies (Table S7), indicating that hydrophobic and electrostatic interactions play a critical role in the binding of the PSMα3m to the Aβ40 monomer. The free energy was decomposed to search for the key residues in the interaction between the PSMα3m and the Aβ40 monomer. As shown in Figure 4, Asp1 and Leu17 of Aβ40 and Met1, Glu2, Phe3, Leu7, Leu14, and Phe18 of the PSMα3m contributed greatly to the binding of the PSMα3m to the Aβ40 monomer (binding free energy < −15.0 kJ/mol), in which the van der Waals force and electrostatic interactions were the main contributors (Table S8).
It is known that the aggregation of Aβ is mainly controlled by hydrophobic interactions and H−bonding [58]. Six H−bonds were observed between the Aβ40 monomer and the PSMα3m, which were mainly located at the N−terminal of Aβ40 (Figure S7a). It has been reported that the flexibility of the N−terminal plays a significant role in the aggregation and toxicity of Aβ [59]. This implies that the PSMα3m could alter the aggregation tendency of Aβ40 by decreasing the flexibility of the N−terminal. Moreover, the Aβ40 monomer is negatively charged [22], while the PSMα3m is positively charged [19]. The opposite charges lead to strong electrostatic interactions between Aβ40 and the PSMα3m, which facilitated their stable binding. In addition, some hydrophobic residues (Met1, Phe3, Leu7, Leu14, and Phe18) of the PSMα3m could provide hydrophobic interactions with the Aβ40 monomer. Therefore, the hydrophobic and electrostatic interactions between the PSMα3m and the Aβ40 monomer promote the tight binding and inhibit the conformational transitions of the Aβ40 monomer.

3.5. MD Simulations on Interactions between PSMα3 Oligomer and Aβ40 Monomer

To examine the effect of the PSMα3o on the conformational transitions of the Aβ40 monomer, the interaction of the PSMα3o with the Aβ40 monomer was analyzed using MD simulations (Figure 5). The RMSD value of the PSMα3o−Aβ40 system was stabilized at around 0.8 nm after 40 ns, indicating that the system reached equilibrium thereafter (Figure 5a). Similar to the PSMα3m, the PSMα3o increased Rg and SASA values and decreased the number of intramolecular H−bonds of the Aβ40 monomer (Table S5), making the whole system unstable, and the RMSD values increased (Figure 5a). The RMSF value of the N−terminal residues of Aβ40 increased (Figure 5b), indicating that the PSMα3o increases the N−terminal flexibility of Aβ40 to accelerate the conformational transitions of Aβ40 [59]. Moreover, the PSMα3o significantly decreased the RMSF value of the Tyr10−Val40 region in Aβ40 (Figure 5b), indicating that the PSMα3o mainly interacted with this region and suppressed the dynamic fluctuation of the residues.
Notably, the Aβ40−PSMα3o complex at the equilibrium state (50 ns) formed a characteristic turn−like structure in Aβ40 (Figure 5c), which was different from the Aβ40−PSMα3m system (Figure 3d). It is known that this turn−like structure stabilizes the β−turn−β structure and promotes the formation of the folding core for Aβ fibrillation [36,60]. From the content of secondary structures at equilibrium, it was found that the β−bridge structure (0.5%) was still present in the Aβ40−PSMα3o system (Table S6), which was formed in the Phe4−Ser8 region of Aβ40 (Figure S6c), indicating that the PSMα3o could not inhibit the formation of the β−sheet structures in Aβ40. This is consistent with the results of the ThT fluorescence and CD experiments (Figure 2a and Table 1), as the PSMα3o did not significantly affect the maximum ThT fluorescence intensity or the content of the β−sheet structure of Aβ40, which also suggested that the PSMα3o weakly affected the conformational transitions of the Aβ40 monomer. Furthermore, the MM−PBSA results showed that the binding energy of the PSMα3o to the Aβ40 monomer was −135.5 kJ/mol, significantly lower than the PSMα3m to the Aβ40 monomer (−270.7 kJ/mol) (Table S7). This is mainly due to the significantly weaker van der Waals hydrophobic energy between Aβ40 and the PSMα3o (−251.0 kJ/mol) than the PSMα3m (−373.5 kJ/mol). Free energy decomposition showed that the PSMα3o mainly combined with the central hydrophobic core (CHC) and the C−terminal region of Aβ40 (His13−Val36) (Figure 6a), which plays a decisive role in the Aβ oligomerization [50]. It can be found that some hydrophobic residues (Leu7, Phe10, and Phe18) of the PSMα3o contributed significantly to the high binding energy, although their contribution was generally lower than that of the PSMα3m (Figure 6b). In addition, only one stable H−bond was observed in the Aβ40−PSMα3o complex (Figure S7b), indicating that the H−bonding between the Aβ40 monomer and the PSMα3o was much weaker than for the PSMα3m. These results suggest that the weaker H−bonding and hydrophobic interactions resulted in a lower binding energy of the PSMα3o to the Aβ40 monomer than that of the PSMα3m, leading to the weak effect of the PSMα3o on the conformational transitions of Aβ40.
According to the above studies, it may be concluded that electrostatic and hydrophobic interactions contributed to the binding of the PSMα3m to the Aβ40 monomer. PSMα3m had a high binding affinity for the Aβ40 monomer, with a total of six H−bonds formed between the two monomers, and some hydrophobic residues (Met1, Phe3, Leu7, Leu14, and Phe18) of the PSMα3m provided hydrophobic interactions with Aβ40. The hydrophobic interactions and H−bonding led to the tight binding of the PSMα3m to the Aβ40 monomer and inhibited the conformational transitions of Aβ40 from the α−helix to β−sheet structure. In contrast, the PSMα3o only formed one stable H−bond with the Aβ40 monomer, and the weaker H−bonding and hydrophobic interactions resulted in a lower binding free energy of the PSMα3o to the Aβ40 monomer, leading to the small role of the PSMα3o in inhibiting the formation of the β−sheet structure in Aβ40.

4. Conclusions

We have explored the effect of PSMα3, a bacterial amyloid with a unique cross−α structure, on the aggregation kinetics, molecular structures, and conformational transitions of the Aβ40 monomer using experimental and computational approaches. The results showed that the PSMα3 monomer inhibits Aβ40 aggregation in a concentration−dependent manner, prolongs its aggregation lag phase, and redirects the aggregation pathway of Aβ40 to form granular structures. In contrast, the PSMα3 oligomer promotes the generation of the β−sheet structure and shortens the lag phase of Aβ40 aggregation. The cross−α structure of PSMα3 plays an important role in the aggregation of Aβ40. The higher the cross−α content of PSMα3, the more obvious the promotion effect on the aggregation of Aβ40. MD simulations further support these observations and identify the key regions and amino acid residues of Aβ40 and PSMα3 in the interactions. The PSMα3 monomer binds to the Asp1−Ala2 and His13−Val36 regions in the Aβ40 monomer via hydrophobic and electrostatic interactions, which prevents the conformational transitions of Aβ40 from the initial α−helix structure to the β−sheet structure. In contrast, the PSMα3 oligomer mainly binds to the CHC and the C−terminal region of the Aβ40 monomer through weak H−bonding and hydrophobic interactions, resulting in a weak role in the conformational transitions of Aβ40. This work reveals different interactions between PSMα3 and Aβ40, providing deeper insights into the complex interactions between bacterial amyloids and AD−associated pathogenic Aβ.
Since the formation of cross−α fibrils by PSMα3 enhances the toxicity to human cells [18] and promotes the formation of the β−sheet structures of Aβ40, subsequent studies should direct towards examining the co−aggregation of PSMα3 and Aβ40 in vivo. In addition, it has been shown that some amyloid−derived fragments with cross−seeding capacity can bind to amyloids and inhibit its aggregation [61,62]. The PSMα3 monomer has a strong affinity for Aβ40 and can significantly inhibit the formation of the β−sheet structure, and its derived fragments may serve as potential inhibitors of Aβ aggregation in vivo. The new findings may provide molecular insights into a potential association between AD and the intestinal flora and provide a potential strategy for the design of amyloids inhibitors based on cross−seeding.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/biomimetics8060459/s1, Table S1: Maximum ThT fluorescence intensity (ymax) and lag phase time (Tlag) of aggregation kinetics of Aβ40 (25 μM) with different concentrations of the PSMα3 monomer; Table S2: Maximum ThT fluorescence intensity (ymax) and lag phase time (Tlag) of aggregation kinetics of Aβ40 (25 μM) incubated without or with PSMα3 seeds; Table S3: Top 10 binding energies of the PSMα3m−Aβ40 complex calculated by molecular docking using Autodock Vina; Table S4: Top 10 binding energies of PSMα3o and Aβ40 calculated by molecular docking using Autodock Vina; Table S5: Structural parameters of the Aβ40 monomer in different systems in the equilibrium state; Table S6: Secondary structure composition of the Aβ40 monomer in different systems in the equilibrium state; Table S7: Binding free energy components of the Aβ40−PSMα3m and Aβ40−PSMα3o systems calculated using the MM−PBSA method; Table S8: Energy components of key residues of Aβ40−PSMα3m system; Figure S1: Crystal structure of PSMα3 (PBD ID: 5I55); Figure S2: Aggregation kinetics of PSMα3; Figure S3: Relative kinetic rate constants of Aβ40 aggregation in the presence of the PSMα3 monomer or PSMα3 seeds; Figure S4: Effects of the PSMα3 monomer at different concentrations on the formation of Aβ40 (25 μM) fibrils at 0 h and 100 h; Figure S5: Effects of PSMα3 seeds (5 μM) at 1 h, 2.5 h, and 24 h on the formation of Aβ40 (25 μM) fibrils at 0 h and 100 h; Figure S6: The secondary structure components of Aβ40 during the 50 ns MD simulations in Aβ40 only, Aβ40−PSMα3m, and Aβ40−PSMα3o systems; Figure S7: H−bonds between the Aβ40 monomer and PSMα3m or PSMα3o. Reference [63] is cited in the supplementary materials.

Author Contributions

Conceptualization, X.D. and Y.S.; formal analysis, B.P. and Y.L.; funding acquisition, X.D. and Y.S.; investigation, B.P. and Y.L.; writing—original draft, B.P. and S.X.; writing—review and editing, B.P., S.X., X.D. and Y.S. All authors have read and agreed to the published version of the manuscript.

Funding

This work was funded by the National Natural Science Foundation of China (no. 21978207).

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Long, J.M.; Holtzman, D.M. Alzheimer disease: An update on pathobiology and treatment strategies. Cell 2019, 179, 312–339. [Google Scholar] [CrossRef] [PubMed]
  2. Zhang, H.; Ng, K.P.; Therriault, J.; Kang, M.S.; Pascoal, T.A.; Rosa−Neto, P.; Gauthier, S. Cerebrospinal fluid phosphorylated tau, visinin-like protein-1, and chitinase-3-like protein 1 in mild cognitive impairment and Alzheimer’s disease. Transl. Neurodegener. 2018, 7, 23. [Google Scholar] [CrossRef] [PubMed]
  3. D’Arrigo, J.S. Targeting early dementia: Using lipid cubic phase nanocarriers to cross the blood-brain barrier. Biomimetics 2018, 3, 4. [Google Scholar] [CrossRef] [PubMed]
  4. Karran, E.; Mercken, M.; De Strooper, B. The amyloid cascade hypothesis for Alzheimer’s disease: An appraisal for the development of therapeutics. Nat. Rev. Drug Discov. 2011, 10, 698–712. [Google Scholar] [CrossRef]
  5. Du, X.G.; Wang, X.Y.; Geng, M.Y. Alzheimer’s disease hypothesis and related therapies. Transl. Neurodegener. 2018, 7, 2. [Google Scholar] [CrossRef]
  6. Jiang, C.M.; Huang, P.R.; Liu, Z.; Zhao, B. The gut microbiota and Alzheimer’s disease. Alzheimers Dis. 2017, 58, 1–15. [Google Scholar] [CrossRef]
  7. Feng, M.; Hou, T.S.; Zhou, M.Z.; Cen, Q.Y.; Yi, T.; Bai, J.F.; Zeng, Y.; Liu, Q.; Zhang, C.S.; Zhang, Y.J. Gut microbiota may be involved in Alzheimer’s disease pathology by dysregulating pyrimidine metabolism in APP/PS1 mice. Front. Aging Neurosci. 2022, 14, 967747. [Google Scholar] [CrossRef]
  8. Szablewski, L. Human gut microbiota in health and Alzheimer’s disease. Alzheimers Dis. 2018, 62, 549–559. [Google Scholar] [CrossRef]
  9. Chandra, S.; Alam, M.T.; Dey, J.; Sasidharan, B.C.P.; Ray, U.; Srivastava, A.K.; Gandhi, S.; Tripathi, P.P. Healthy gut, healthy brain: The gut microbiome in neurodegenerative disorders. Curr. Top. Med. Chem. 2020, 20, 1142–1153. [Google Scholar] [CrossRef]
  10. Cryan, J.F.; O’Riordan, K.J.; Cowan, C.S.M.; Sandhu, K.V.; Bastiaanssen, T.F.S.; Boehme, M.; Codagnone, M.G.; Cussotto, S.; Fulling, C.; Golubeva, A.V.; et al. The microbiota-gut-brain axis. Physiol. Rev. 2019, 99, 1877–2013. [Google Scholar] [CrossRef]
  11. Sasmita, A.O. Modification of the gut microbiome to combat neurodegeneration. Rev. Neurosci. 2019, 30, 795–805. [Google Scholar] [CrossRef]
  12. Chen, S.G.; Stribinskis, V.; Rane, M.J.; Demuth, D.R.; Gozal, E.; Roberts, A.M.; Jagadapillai, R.; Liu, R.L.; Choe, K.W.; Shivakumar, B.; et al. Exposure to the functional bacterial amyloid protein curli enhances alpha-Synuclein aggregation in aged fischer 344 rats and caenorhabditis elegans. Sci. Rep. 2016, 6, 34477. [Google Scholar] [CrossRef] [PubMed]
  13. Friedland, R.P.; Chapman, M.R. The role of microbial amyloid in neurodegeneration. PLoS Pathog. 2017, 13, e1006654. [Google Scholar] [CrossRef] [PubMed]
  14. Perov, S.; Lidor, O.; Salinas, N.; Golan, N.; Tayeb-Fligelman, E.; Deshmukh, M.; Willbold, D.; Landau, M. Structural insights into curli CsgA cross-beta fibril architecture inspire repurposing of anti-amyloid compounds as anti-biofilm agents. PLoS Pathog. 2019, 15, e1007978. [Google Scholar] [CrossRef]
  15. Javed, I.; Zhang, Z.Z.; Adamcik, J.; Andrikopoulos, N.; Li, Y.H.; Otzen, D.E.; Lin, S.J.; Mezzenga, R.; Davis, T.P.; Ding, F.; et al. Accelerated amyloid beta pathogenesis by bacterial amyloid FapC. Adv. Sci. 2020, 7, 2001299. [Google Scholar] [CrossRef] [PubMed]
  16. Schwartz, K.; Syed, A.K.; Stephenson, R.E.; Rickard, A.H.; Boles, B.R. Functional amyloids composed of phenol soluble modulins stabilize Staphylococcus aureus biofilms. PLoS Pathog. 2012, 8, e1002744. [Google Scholar] [CrossRef]
  17. Cheung, G.Y.C.; Kretschmer, D.; Queck, S.Y.; Joo, H.S.; Wang, R.; Duong, A.C.; Nguyen, T.H.; Bach, T.H.L.; Porter, A.R.; DeLeo, F.R.; et al. Insight into structure-function relationship in phenol-soluble modulins using an alanine screen of the phenol-soluble modulin (PSM) α3 peptide. Faseb. J. 2014, 28, 153–161. [Google Scholar] [CrossRef]
  18. Laabei, M.; Jamieson, W.D.; Yang, Y.; van den Eisen, J.; Jenkins, A.T.A. Investigating the lytic activity and structural properties of Staphylococcus aureus phenol soluble modulin (PSM) peptide toxins. Biochim. Biophys. Acta-Biomembr. 2014, 1838, 3153–3161. [Google Scholar] [CrossRef]
  19. Tayeb-Fligelman, E.; Tabachnikov, O.; Moshe, A.; Goldshmidt-Tran, O.; Sawaya, M.R.; Coquelle, N.; Colletier, J.P.; Landau, M. The cytotoxic Staphylococcus aureus PSMα3 reveals a cross-α amyloid-like fibril. Science 2017, 355, 831–833. [Google Scholar] [CrossRef]
  20. Zaman, M.; Andreasen, M. Cross-talk between individual phenol-soluble modulins in Staphylococcus aureus biofilm enables rapid and efficient amyloid formation. Elife 2020, 9, e59776. [Google Scholar] [CrossRef]
  21. Festa, G.; Mallamace, F.; Sancesario, G.M.; Corsaro, C.; Mallamace, D.; Fazio, E.; Arcidiacono, L.; Garcia Sakai, V.; Senesi, R.; Preziosi, E. Aggregation states of Aβ1–40, Aβ1–42 and Aβp3–42 amyloid beta peptides: A SANS Study. Int. J. Mol. Sci. 2019, 20, 4126. [Google Scholar] [CrossRef] [PubMed]
  22. Boopathi, S.; Kolandaivel, P. Role of zinc and copper metal ions in amyloid beta-peptides Abeta(1-40) and Abeta(1-42) aggregation. RSC Adv. 2014, 4, 38951–38965. [Google Scholar] [CrossRef]
  23. Das, M.; Dash, S.; Bhargava, B.L. Computational studies of fibrillation induced selective cytotoxicity of cross-alpha amyloid—Phenol soluble modulin α3. Chem. Phys. 2020, 535, 110777. [Google Scholar] [CrossRef]
  24. Trott, O.; Olson, A.J. Software news and update AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Comput Chem. 2010, 31, 455–461. [Google Scholar]
  25. Pronk, S.; Pall, S.; Schulz, R.; Larsson, P.; Bjelkmar, P.; Apostolov, R.; Shirts, M.R.; Smith, J.C.; Kasson, P.M.; van der Spoel, D.; et al. GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit. Bioinf. 2013, 29, 845–854. [Google Scholar] [CrossRef]
  26. Hornak, V.; Abel, R.; Okur, A.; Strockbine, B.; Roitberg, A.; Simmerling, C. Comparison of multiple amber force fields and development of improved protein backbone parameters. Proteins Struct. Funct. Bioinf. 2006, 65, 712–725. [Google Scholar] [CrossRef]
  27. Steinczinger, Z.; Jovari, P.; Pusztai, L. Comparison of 9 classical interaction potentials of liquid water: Simultaneous reverse monte carlo modeling of X-ray and neutron diffraction results and partial radial distribution functions from computer simulations. J. Mol. Liq. 2017, 228, 19–24. [Google Scholar] [CrossRef]
  28. Dzubiella, J. Salt-specific stability and denaturation of a short salt-bridge forming α-helix. J. Am. Chem. Soc. 2008, 130, 14000–14007. [Google Scholar] [CrossRef]
  29. Triguero, L.; Singh, R.; Prabhakar, R. Comparative molecular dynamics studies of wild-type and oxidized forms of full-length Alzheimer amyloid-β peptides Aβ(1-40) and Aβ(1-42). J. Phys. Chem. B 2008, 112, 7123–7131. [Google Scholar] [CrossRef]
  30. Kumari, R.; Kumar, R.; Lynn, A. g_mmpbsa-a GROMACS tool for high-throughput MM-PBSA calculations. J. Chem. Inf. Model. 2014, 54, 1951–1962. [Google Scholar] [CrossRef]
  31. Jamasbi, E.; Hossain, M.A.; Tan, M.; Separovic, F.; Ciccotosto, G.D. Fluorescence imaging of the interaction of amyloid beta 40 peptides with live cells and model membrane. Biochim. Biophys. Acta-Biomembr. 2018, 1860, 1609–1615. [Google Scholar] [CrossRef] [PubMed]
  32. Xue, C.; Lin, T.Y.W.; Chang, D.; Guo, Z.F. Thioflavin T as an amyloid dye: Fibril quantification, optimal concentration and effect on aggregation. Soc. Open Sci. 2017, 4, 160696. [Google Scholar] [CrossRef] [PubMed]
  33. Le, K.Y.; Villaruz, A.E.; Zheng, Y.; He, L.; Fisher, E.L.; Nguyen, T.H.; Ho, T.V.; Yeh, A.J.; Joo, H.S.; Cheung, G.Y.C.; et al. Role of phenol-soluble modulins in Staphylococcus epidermidis biofilm formation and infection of indwelling medical devices. J. Mol. Biol. 2019, 431, 3015–3027. [Google Scholar] [CrossRef]
  34. Tayeb-Fligelman, E.; Salinas, N.; Tabachnikov, O.; Landau, M. Staphylococcus aureus PSMα3 cross-α fibril polymorphism and determinants of cytotoxicity. Structure 2020, 28, 301–313. [Google Scholar] [CrossRef]
  35. Bertini, I.; Gonnelli, L.; Luchinat, C.; Mao, J.F.; Nesi, A. A new structural model of Abeta(40) fibrils. J. Am. Chem. Soc. 2011, 133, 16013–16022. [Google Scholar] [CrossRef]
  36. Meisl, G.; Kirkegaard, J.; Arosio, P.; Michaels, T.; Vendruscolo, M.; Dobson, C.; Linse, S.; Knowles, T. Molecular mechanisms of protein aggregation from global fitting of kinetic models. Nat. Protoc. 2016, 11, 252–272. [Google Scholar] [CrossRef]
  37. Du, W.J.; Guo, J.J.; Gao, M.T.; Hu, S.Q.; Dong, X.Y.; Han, Y.F.; Liu, F.F.; Jiang, S.; Sun, Y. Brazilin inhibits amyloid β-protein fibrillogenesis, remodels amyloid fibrils and reduces amyloid cytotoxicity. Sci. Rep. 2015, 5, 7992. [Google Scholar] [CrossRef] [PubMed]
  38. Pryor, N.E.; Moss, M.A.; Hestekin, C.N. Capillary electrophoresis for the analysis of the effect of sample preparation on early stages of Abeta(1-40) aggregation. Electrophoresis 2014, 35, 1814–1820. [Google Scholar] [CrossRef] [PubMed]
  39. Adem, K.; Shanti, A.; Srivastava, A.; Homouz, D.; Thomas, S.; Khair, M.; Stefanini, C.; Chan, V.; Kim, T.; Lee, S. Linking Alzheimer’s disease and type 2 diabetes: Characterization and inhibition of cytotoxic Aβ and IAPP hetero-aggregates. Front. Mol. Biosci. 2022, 9, 842582. [Google Scholar] [CrossRef]
  40. Ge, X.W.; Yang, Y.; Sun, Y.X.; Cao, W.G.; Ding, F. Islet amyloid polypeptide promotes amyloid-beta aggregation by binding-induced helix-unfolding of the amyloidogenic core. ACS Chem. Neurosci. 2018, 9, 967–975. [Google Scholar] [CrossRef]
  41. Ilitchev, A.I.; Giarnmona, M.J.; Schwarze, J.N.; Buratto, S.K.; Bowers, M.T. Zinc-induced conformational transitions in human islet amyloid polypeptide and their role in the inhibition of amyloidosis. J. Phys. Chem. B 2018, 122, 9852–9859. [Google Scholar] [CrossRef] [PubMed]
  42. Ren, B.P.; Zhang, Y.X.; Zhang, M.Z.; Liu, Y.L.; Zhang, D.; Gong, X.; Feng, Z.Q.; Tang, J.X.; Chang, Y.; Zheng, J. Fundamentals of cross-seeding of amyloid proteins: An introduction. J. Phys. Chem. B 2019, 7, 7267–7282. [Google Scholar] [CrossRef] [PubMed]
  43. Cohen, S.I.A.; Linse, S.; Luheshi, L.M.; Hellstrand, E.; White, D.A.; Rajah, L.; Otzen, D.E.; Vendruscolo, M.; Dobson, C.M.; Knowles, T.P.J. Proliferation of amyloid-beta 42 aggregates occurs through a secondary nucleation mechanism. Proc. Natl. Acad. Sci. USA 2013, 110, 9758–9763. [Google Scholar] [CrossRef] [PubMed]
  44. Bharadwaj, P.; Solomon, T.; Sahoo, B.R. Amylin and beta amyloid proteins interact to form amorphous heterocomplexes with enhanced toxicity in neuronal cells. Sci. Rep. 2020, 10, 10356. [Google Scholar] [CrossRef]
  45. Guo, J.P.; Arai, T.; Miklossy, J.; McGeer, P.L. Abeta and tau form soluble complexes that may promote self aggregation of both into the insoluble forms observed in Alzheimer’s disease. Proc. Natl. Acad. Sci. USA 2006, 103, 1953–1958. [Google Scholar] [CrossRef]
  46. Mandal, P.K.; Pettegrew, J.W.; Masliah, E.; Hamilton, R.L.; Mandal, R. Interaction between A beta peptide and alpha synuclein: Molecular mechanisms in overlapping pathology of Alzheimer’s and Parkinson’s in dementia with Lewy body disease. Neurosci. Res. 2006, 31, 1153–1162. [Google Scholar]
  47. Sampson, T.R.; Challis, C.; Jain, N.; Moiseyenko, A.; Ladinsky, M.S.; Shastri, G.G.; Thron, T.; Needham, B.D.; Horvath, I.; Debelius, J.W.; et al. A gut bacterial amyloid promotes alpha-synuclein aggregation and motor impairment in mice. Elife 2020, 9, e53111. [Google Scholar] [CrossRef]
  48. Li, X.H.; Lao, Z.H.; Zou, Y.; Dong, X.W.; Li, L.; Wei, G.H. Mechanistic Insights into the co-aggregation of Aβ and hIAPP: An all-atom molecular dynamic study. J. Phys. Chem. B 2021, 125, 2050–2060. [Google Scholar] [CrossRef]
  49. Raz, Y.; Miller, Y. Interactions between Aβ and mutated tau lead to polymorphism and induce aggregation of Aβ-mutated tau oligomeric complexes. PLoS ONE 2013, 8, e73303. [Google Scholar] [CrossRef]
  50. Bhattacharya, S.; Xu, L.; Thompson, D. Molecular simulations reveal terminal group mediated stabilization of helical conformers in both amyloid-beta 42 and α-Synuclein. ACS Chem. Neurosci. 2019, 10, 2830–2842. [Google Scholar] [CrossRef]
  51. Hou, S.; Gu, R.X.; Wei, D.Q. Inhibition of beta-amyloid channels with a drug candidate wgx-50 revealed by molecular dynamics simulations. J. Chem. Inf. Model. 2017, 57, 2811–2821. [Google Scholar] [CrossRef] [PubMed]
  52. Xu, S.Y.; Wang, W.J.; Dong, X.Y.; Sun, Y. Molecular insight into Cu2+-induced conformational transitions of amyloid beta-protein from fast kinetic analysis and molecular dynamics simulations. ACS Chem. Neurosci. 2021, 12, 300–310. [Google Scholar] [CrossRef] [PubMed]
  53. Nie, R.Z.; Dang, M.Z.; Li, K.K.; Peng, J.M.; Du, J.; Zhang, M.Y.; Li, C.M. A-type EGCG dimer, a new proanthocyanidins dimer from persimmon fruits, interacts with the amino acid residues of Abeta(40) which possessed high aggregation-propensity and strongly inhibits its amyloid fibrils formation. J. Funct. Foods 2019, 52, 492–504. [Google Scholar] [CrossRef]
  54. Carter, P.; Andersen, C.A.F.; Rost, B. DSSPcont: Continuous secondary structure assignments for proteins. Nucleic Acids Res. 2003, 31, 3293–3295. [Google Scholar] [CrossRef]
  55. Saini, R.K.; Thakur, H.; Goyal, B. Effect of piedmont mutation (L34V) on the structure, dynamics, and aggregation of Alzheimer’s abeta(40) peptide. J. Mol. Graphics Modell. 2020, 97, 107571. [Google Scholar] [CrossRef]
  56. Linh, N.H.; Thu, T.T.M.; Tu, L.; Hu, C.K.; Li, M.S. Impact of mutations at C-terminus on structures and dynamics of Abeta 40 and Abeta 42: A molecular simulation study. J. Phys. Chem. B 2017, 121, 4341–4354. [Google Scholar] [CrossRef]
  57. Kocis, P.; Tolar, M.; Yu, J.; Sinko, W.; Ray, S.; Blennow, K.; Fillit, H.; Hey, J.A. Elucidating the Abeta 42 anti-aggregation mechanism of action of tramiprosate in Alzheimer’s Disease: Integrating molecular analytical methods, pharmacokinetic and clinical data. CNS Drugs 2017, 31, 495–509. [Google Scholar] [CrossRef]
  58. Bartling, C.R.O.; Jensen, T.M.T.; Henry, S.M.; Colliander, A.L.; Sereikaite, V.; Wenzler, M.; Jain, P.; Maric, H.M.; Harpsoe, K.; Pedersen, S.W.; et al. Targeting the APP-Mint2 protein-protein interaction with a peptide-based inhibitor reduces amyloid-beta formation. J. Am. Chem. Soc. 2021, 143, 891–901. [Google Scholar] [CrossRef]
  59. Urbanc, B. Flexible N-termini of amyloid beta-protein oligomers: A link between structure and activity? Isr. J. Chem. 2017, 57, 651–664. [Google Scholar] [CrossRef]
  60. Miller, Y.; Ma, B.Y.; Nussinov, R. The unique Alzheimer’s beta-amyloid triangular fibril has a cavity along the fibril axis under physiological conditions. J. Am. Chem. Soc. 2011, 133, 2742–2748. [Google Scholar] [CrossRef]
  61. Andreetto, E.; Yan, L.M.; Caporale, A.; Kapurniotu, A. Dissecting the role of single regions of an IAPP mimic and IAPP in inhibition of Abeta 40 amyloid formation and cytotoxicity. ChemBioChem. 2011, 12, 1313–1322. [Google Scholar] [CrossRef] [PubMed]
  62. Aftabizadeh, M.; Tatarek-Nossol, M.; Andreetto, E.; El Bounkari, O.; Kipp, M.; Beyer, C.; Kapurniotu, A. Blocking inflammasome activation caused by betaamyloid peptide (Abeta) and islet amyloid polypeptide (IAPP) through an IAPP mimic. ACS Chem. Neurosci. 2019, 10, 3703–3717. [Google Scholar] [CrossRef] [PubMed]
  63. Belsare, K.D.; Wu, H.; Mondal, D.; Bond, A.; Castillo, E.; Jin, J.; Jo, H.; Roush, A.E.; Pilla, K.B.; Sali, A.; et al. Soluble TREM2 inhibits secondary nucleation of Aβ fibrillization and enhances cellular uptake of fibrillar Aβ. Proc. Natl. Acad. Sci. USA 2022, 119, e2114486119. [Google Scholar] [CrossRef] [PubMed]
Biomimetics 08 00459 g001
Figure 1. Effect of the PSMα3 monomer on Aβ40 aggregation: (a) aggregation kinetics of Aβ40 (25 μM) cultured with or without the PSMα3 monomer at different concentrations measured by ThT fluorescence assay; (b) the enlarged version of the dotted frame area in (a); (c) AFM images of Aβ40 aggregates cultured with or without the PSMα3 monomer of different concentrations at 37 °C for 100 h.
Figure 1. Effect of the PSMα3 monomer on Aβ40 aggregation: (a) aggregation kinetics of Aβ40 (25 μM) cultured with or without the PSMα3 monomer at different concentrations measured by ThT fluorescence assay; (b) the enlarged version of the dotted frame area in (a); (c) AFM images of Aβ40 aggregates cultured with or without the PSMα3 monomer of different concentrations at 37 °C for 100 h.
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Figure 2. Effect of PSMα3 seeds on Aβ40 aggregation: (a) aggregation kinetics of Aβ40 (25 μM) cultured without or with PSMα3 seeds (5 μM) at 1 h, 2.5 h, 5 h, and 24 h measured by ThT fluorescence assays for 100 h; (b) CD spectra of Aβ40 aggregates cultured with or without PSMα3 seeds at 1 h, 2.5 h, 5 h, and 24 h for 100 h; (c) AFM images of Aβ40 cultured with or without PSMα3 seeds at 37 °C for 100 h.
Figure 2. Effect of PSMα3 seeds on Aβ40 aggregation: (a) aggregation kinetics of Aβ40 (25 μM) cultured without or with PSMα3 seeds (5 μM) at 1 h, 2.5 h, 5 h, and 24 h measured by ThT fluorescence assays for 100 h; (b) CD spectra of Aβ40 aggregates cultured with or without PSMα3 seeds at 1 h, 2.5 h, 5 h, and 24 h for 100 h; (c) AFM images of Aβ40 cultured with or without PSMα3 seeds at 37 °C for 100 h.
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Figure 3. MD simulations of the PSMα3 monomer (PSMα3m) and the Aβ40 monomer and their complex: (a) RMSD of Aβ40, PSMα3, and Aβ40−PSMα3m complex; (b) RMSF of each residue of Aβ40 without or with PSMα3m; (c,d) initial (0 ns) and equilibrium (50 ns) states of (c) Aβ40 and (d) Aβ40−PSMα3m complex. Blue and purple represent the Aβ40 monomer and PSMα3m, respectively.
Figure 3. MD simulations of the PSMα3 monomer (PSMα3m) and the Aβ40 monomer and their complex: (a) RMSD of Aβ40, PSMα3, and Aβ40−PSMα3m complex; (b) RMSF of each residue of Aβ40 without or with PSMα3m; (c,d) initial (0 ns) and equilibrium (50 ns) states of (c) Aβ40 and (d) Aβ40−PSMα3m complex. Blue and purple represent the Aβ40 monomer and PSMα3m, respectively.
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Figure 4. Energy decomposition diagram of each amino acid residue in the Aβ40−PSMα3m complex.
Figure 4. Energy decomposition diagram of each amino acid residue in the Aβ40−PSMα3m complex.
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Figure 5. MD simulations of Aβ40−PSMα3 oligomer (PSMα3o) complex: (a) RMSD of Aβ40 and Aβ40−PSMα3o system; (b) RMSF of each amino acid residue of Aβ40 without or with PSMα3o; (c) initial (0 ns) and equilibrium (50 ns) states of the Aβ40−PSMα3o system. Blue and purple represent the Aβ40 monomer and PSMα3o, respectively.
Figure 5. MD simulations of Aβ40−PSMα3 oligomer (PSMα3o) complex: (a) RMSD of Aβ40 and Aβ40−PSMα3o system; (b) RMSF of each amino acid residue of Aβ40 without or with PSMα3o; (c) initial (0 ns) and equilibrium (50 ns) states of the Aβ40−PSMα3o system. Blue and purple represent the Aβ40 monomer and PSMα3o, respectively.
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Figure 6. Energy decomposition diagram of each residue of (a) Aβ40 and (b) PSMα3o. Blue and red represent residues of Aβ40 in the Aβ40−PSMα3m and Aβ40−PSMα3o complexes, respectively. Green, yellow and blue separately represent the three chains of PSMα3o.
Figure 6. Energy decomposition diagram of each residue of (a) Aβ40 and (b) PSMα3o. Blue and red represent residues of Aβ40 in the Aβ40−PSMα3m and Aβ40−PSMα3o complexes, respectively. Green, yellow and blue separately represent the three chains of PSMα3o.
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Table 1. Secondary structure distributions of Aβ40 aggregates incubated with PSMα3 seeds of different culture times calculated from the CD spectrum.
Table 1. Secondary structure distributions of Aβ40 aggregates incubated with PSMα3 seeds of different culture times calculated from the CD spectrum.
Sample (%)α−Helixβ−SheetTurnOthers
Aβ401074.43.811.8
with PSMα3 seeds at 1 h7.873.21.217.9
with PSMα3 seeds at 2.5 h29.363.67.10
with PSMα3 seeds at 5 h14.281.93.80
with PSMα3 seeds at 24 h18.379.12.60
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Peng, B.; Xu, S.; Liang, Y.; Dong, X.; Sun, Y. Effect of Bacterial Amyloid Protein Phenol−Soluble Modulin Alpha 3 on the Aggregation of Amyloid Beta Protein Associated with Alzheimer’s Disease. Biomimetics 2023, 8, 459. https://doi.org/10.3390/biomimetics8060459

AMA Style

Peng B, Xu S, Liang Y, Dong X, Sun Y. Effect of Bacterial Amyloid Protein Phenol−Soluble Modulin Alpha 3 on the Aggregation of Amyloid Beta Protein Associated with Alzheimer’s Disease. Biomimetics. 2023; 8(6):459. https://doi.org/10.3390/biomimetics8060459

Chicago/Turabian Style

Peng, Bushu, Shaoying Xu, Yue Liang, Xiaoyan Dong, and Yan Sun. 2023. "Effect of Bacterial Amyloid Protein Phenol−Soluble Modulin Alpha 3 on the Aggregation of Amyloid Beta Protein Associated with Alzheimer’s Disease" Biomimetics 8, no. 6: 459. https://doi.org/10.3390/biomimetics8060459

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