Alzheimer’s Aβ catalyzes Tau phase separation and aggregation via early nanocluster solubilization

Domain: biology
Published: 2026-03-10
Editorial outcome: major_revision

Abstract
Extracellular amyloid-beta (Aβ) plaques and intracellular neurofibrillary tangles (NFTs) composed of hyperphosphorylated Tau are the two main pathological hallmarks of Alzheimer’s disease (AD). Although the co-occurrence and synergistic effects of Aβ and Tau are well established, the mechanisms underlying their interplay in a biomolecular condensate environment remain unclear. Here we show that Aβ40 does not undergo liquid–liquid phase separation (LLPS) but significantly enhances Tau phase separation and is recruited into Tau condensates. This recruitment alters condensate physicochemical properties, accelerates liquid-to-solid maturation, promotes Tau amyloid fibril formation, and increases Tau-mediated cytotoxicity. Notably, prior to condensate formation, Aβ40 transiently solubilizes Tau nanoclusters into smaller species. Simulations further indicate that early interactions are non-specific and mediated by Tau repeat domains, ultimately promoting pathogenic aggregation. These findings support a model wherein Aβ act as a catalyst for Tau condensation and fibrillation towards pathological aggregates by solubilizing Tau nanoclusters during early phase interactions.

Introduction
Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, with its pathology marked by extracellular amyloid-beta (Aβ) plaques and intracellular neurofibrillary tangles (NFTs) composed of Tau protein1. Aβ peptides, ranging from 39 to 43 residues, are generated through the enzymatic cleavage of amyloid precursor protein (APP) by β- and γ-secretases2. Aβ40, the predominant form in cerebrospinal fluid, differs from Aβ42 by two C-terminal residues, which enhance Aβ42's aggregation propensity and neurotoxicity3-4. Aβ peptides are intrinsically disordered, negatively charged at physiological pH, and prone to forming amyloid fibrils. Notably, Aβ plaque quantity does not correlate directly with cognitive decline severity in AD5. Conversely, NFTs strongly correlate with disease progression and cognitive impairment5. NFTs, primarily composed of Tau proteins from the microtubule-associated protein (MAP) family, impair microtubule stability and disrupt neuronal function. Alternative splicing of Tau mRNA gives rise to six distinct isoforms6. The full-length Tau441 (441 residues, positively charged at physiological pH) is the most prevalent in AD and K18, a truncated Tau variant containing only the microtubule-binding domain, readily forms fibrils7.

Although traditionally examined as separate pathological entities, growing evidence indicates that Aβ and Tau exhibit spatial and biochemical interdependence, interacting in ways that influence one other’s pathological roles in the brain8-9. While Aβ accumulates diffusely across the neocortex, tau pathology typically initiates focally in the medial temporal lobe and then spreads transneuronally to connected brain regions. This spread is facilitated by Aβ-induced neuronal hyperactivity and hyperconnectivity, which acts as a bridge between these two hallmark pathologies10. The co-localization of Aβ and Tau could facilitate the cross-seeding of pathologies where each protein influences the aggregation or misfolding of the other. Aβ induces Tau hyperphosphorylation, a critical step in NFT formation11, while Tau modulates Aβ oligomer formation and fibrillation at the oligomeric stage in vitro12. Moreover, Tau is essential for Aβ-induced neurotoxicity13, implying an active, bidirectional pathological interaction rather than a linear cascade. Despite these biochemical and pathological observations, the precise mechanisms by which Aβ influences Tau phase separation and its transition toward aggregated, disease-associated states remain poorly understood.

Liquid-liquid phase separation (LLPS), a biophysical process increasingly implicated in neurodegenerative diseases, occurs when biomolecules such as intrinsically disordered proteins (IDPs) separate from bulk solution to form dense liquid droplets14. While LLPS is crucial for cellular membrane-less compartmentalization, its dysregulation may contribute to disease pathogenesis15. Emerging evidence suggests that LLPS can be preceded by the formation of nanoscale, liquid-like clusters termed nanoclusters, formed by small oligomers16. These transient assemblies exist in dynamic equilibrium with their monomeric or oligomeric forms, but some can overcome energetic barriers to form more microscale structures, potentially serving as intermediates in the initiation of phase separation16. There is ongoing debate whether Aβ undergoes LLPS as an intermediate step prior to amyloid plaque formation. It also remains unclear whether molecular crowding agents modulate local Aβ concentrations in a manner that accelerates its fibrillization17-18. Similarly, Tau's LLPS propensity, influenced by factors such as phosphorylation and ionic strength, may facilitate NFT formation by concentrating Tau in subcellular regions19-20. Experimental evidence suggests that aberrant Tau LLPS may precede aggregation20-21, as some protein droplets transition into insoluble fibrils22-25. Hyperphosphorylation or disease-related Tau mutation condensation within cells occurs even in the normal physiological environment with the estimated intraneuronal concentration, which suggest that LLPS could be a natural mechanism for organizing tau within neurons20. However, liquid-liquid phase separation and amyloid aggregation have also been reported as independent processes26, and a definitive causal link between LLPS and amyloid formation remains elusive. Additionally, effective strategies for regulating these processes are yet to be established. The interplay between Aβ and Tau in LLPS is particularly intriguing, as their interactions may modulate the pathological deposition, co-aggregation, or toxicity of each protein. Notably, co-localization or heterotypic assemblies of Aβ and Tau during phase transitions has been observed in the brains of Alzheimer’s disease patients, suggesting a cooperative role in disease progression10, 20. Elucidating the molecular basis of this crosstalk in the environment of cellular phase or cellular-like phase is therefore critical for understanding AD pathogenesis and identifying therapeutic targets that disrupt early co-condensation and co-aggregation events.

In this study, we investigated how Aβ40 influences Tau phase separation, phase transition, aggregation, and associated cytotoxicity by employing a combination of microscopy, biochemical, and biophysical approaches. Our data of mass photometry and NMR suggest that Aβ40 initially facilitates the solubilization of Tau nanoclusters in NMR-visible states, which subsequently evolve into cytotoxic assemblies in neuroblastoma cells. Using NMR spectroscopy and molecular dynamics (MD) simulations, we characterized the atomic-level impact of Aβ40 on Tau structure, dynamics, and interactions. We further demonstrate that Aβ40 enhances Tau phase separation, accelerates liquid-to-solid transitions, and promotes amyloid fibril formation. Together, these findings provide mechanistic insights into the Aβ-Tau interplay, offering a deeper understanding of Alzheimer's disease pathogenesis and pointing toward potential therapeutic strategies targeting both LLPS and fibrillization processes.

Results
Aβ40 does not undergo LLPS
Aβ fibrillation has been widely studied, mostly with emphasis on aggregation kinetics and fibril structure27-29. However, it is not yet known whether Aβ undergoes LLPS in vitro. To evaluate the LLPS propensity of Aβ, we utilized the catGRANULE algorithm30, which predicts phase separation potential of Aβ40 based on the primary sequence properties. The predicted LLPS propensity score of 0.248 indicates a low likelihood of phase separation. Aβ40 carries a net negative charge under physiological conditions, containing six negatively charged and three positively charged residues along its sequence (Supplementary Figure 1A).

To experimentally assess Aβ40 phase separation, turbidity measurements were performed at varying protein concentrations in the presence of 10% and 15% PEG8000 as a crowding agent, with and without a 12-hour incubation period. As shown in Supplementary Figure 1B–E, no significant increase in turbidity was observed under any tested condition, suggesting that Aβ40 does not undergo LLPS. Further characterization using fluorescence microscopy with TAMRA-labeled Aβ40 (Supplementary Figure 1F) revealed the formation of aggregates rather than liquid-like droplets, reinforcing this conclusion. To investigate the material properties of these aggregates, FRAP experiments were conducted (Supplementary Figure 1G), demonstrating that Aβ40 formed solid-like aggregates rather than dynamic liquid-like condensates. Overall, our experimental observations show that, unlike Tau, Aβ40 does not form droplets under the tested conditions. This finding is consistent with catGRANULE predictions which indicate a much lower phase separation propensity of Aβ40 compared to Tau and is further supported by our coarse-grained simulations presented in the following sections.

Aβ40 promotes Tau phase separation.
The intrinsically disordered Tau exhibits a distinct multivalent charge distribution under physiological conditions (pH 7.4), as illustrated in Fig 1A. Computational predictions using the catGRANULE algorithm yielded a droplet-promoting propensity score of 1.689 for Tau30, consistent with previous studies confirming its ability to undergo phase separation20, 31.

To investigate the modulation of Tau LLPS by Aβ40, we systematically varied Aβ40 and Tau concentrations in the presence of 10% PEG8000 by using protein crystallization robotic dispenser and imager to generate a phase diagram (Fig 1B & Supplementary Figure 2). Compared to Tau alone, the presence of Aβ lowered the critical concentration required for Tau LLPS. Turbidity measurements at 350 nm further confirmed these findings, as Aβ40 alone did not increase turbidity, whereas its presence significantly enhanced Tau phase separation, resulting in a three-fold increase in absorbance compared to Tau droplets alone (Fig 1C). These results were corroborated by brightfield microscopy images (Supplementary Figure 2), which showed increased droplet formation in the presence of Aβ40.

To further investigate the co-condensation between Aβ40 and Tau, we fluorescently labeled both proteins and monitored their incorporation using fluorescence microscopy. Alexa-647-labeled Tau and TAMRA-labeled Aβ40 exhibited co-localization within the Tau droplets, indicating the recruitment of Aβ40 into Tau condensates (Fig 1D). The fusion dynamics of these droplets confirmed their liquid-like properties, as evidenced by characteristic fusion events (Fig 1E). To investigate the effect of Aβ40 on Tau droplet growth, we monitored the size of Tau droplets over time. Representative time-lapse microscopy images (Supplementary Figure 3A) show that when Tau was co-incubated with Aβ40, the formation of droplets showed a more rapid increase, with an increased number of larger droplets forming an earlier time point compared to Tau alone. The observed crossover in droplet growth kinetics (Supplementary Figure 3B) where Tau+Aβ40 droplets initially form and expand faster than Tau-only droplets but later exhibit slower growth. This reflects an early Aβ40-driven enhancement of condensate nucleation and maturation followed by reduced droplet mobility and Tau monomer depletion due to Aβ-induced liquid–solid transition and fibril formation, whereas Tau-only samples continue to enlarge through prolonged coalescence and Ostwald ripening. At late stage, the droplet diameters with or without Aβ40 reached comparable values, indicating that Aβ40 primarily influences the kinetics of phase separation rather than the final equilibrium state. Overall, Aβ40 incorporation promoted droplet maturation, leading to the formation of larger condensates.

To determine whether Aβ40 alters the material properties of Tau droplets, we conducted FRAP experiments (Fig 1F). Freshly formed Tau droplets exhibited nearly full fluorescence recovery, consistent with a dynamic liquid-like state. However, in the presence of Aβ40, fluorescence recovery was significantly reduced to approximately 50% of the initial intensity, indicating a slower molecular diffusion within the droplets and a transition toward a more gel-like or solid-like state. These findings demonstrate that Aβ40 is recruited into Tau droplets, enhances Tau phase separation and dynamical arrest.

Aβ40 accelerates Tau phase transition.
Intrinsically disordered proteins (IDPs), such as TDP-43 and FUS, form liquid droplets that gradually evolve into more viscous, gel-like states and eventually transition into amyloid-like or amorphous aggregates25, 32-34. To determine whether Tau undergoes a comparable maturation process, progressing from a liquid phase to a gel-like and ultimately an aggregated state, we did long-term time lapse imaging and analyzed the dynamical arrest of Tau droplets over time.

To evaluate the impact of Aβ40 on Tau phase transition over time, fluorescence microscopy was used to visualize condensates formed by 10 µM Tau in the presence and absence of 10 µM Aβ40 (Fig 2A-B). In the presence of Aβ40, Tau initially formed spherical droplets, which gradually transitioned into star-like droplet network by day 2, finally formed irregular and less dynamic structures by day 4. In contrast, Tau alone maintained stable phase-separated spherical droplets until day 2 then transited to the droplet network by day 4, while Aβ40 alone exhibited an aggregated, solid-like morphology over time. Quantitative analysis of the total condensate area revealed a significant increase in Tau-Aβ40 structures compared to Tau alone (Fig 2C). By day 2 and day 4, the total condensate area of Tau-Aβ40 mixtures was significantly larger than Tau alone, indicating an accelerated phase transition in the presence of Aβ40. To assess the material properties of these condensates, FRAP experiments were performed (Fig 2D–F). Tau alone exhibited rapid fluorescence recovery on day 1, suggesting a dynamic, liquid-like state (Fig 2E). However, by day 4, the fluorescence recovery was significantly reduced, indicating progressive maturation into a gel-like or solid-like state. In contrast, Tau-Aβ40 condensates displayed markedly reduced fluorescence recovery at all time points, with an even lower recovery rate observed by day 4 (Fig 2D). This suggests that Aβ40 accelerates the transition of Tau condensates from a liquid-like to a more rigid, less dynamic state and completely inhibit the molecule exchange between droplets and the surrounding medium. This maturation process closely parallels the phase transition observed in phosphorylated Tau, which exhibits a gradual reduction in molecular exchange over time20. Aβ40 alone showed minimal fluorescence recovery throughout the incubation period, consistent with the formation of solid-like aggregates rather than phase-separated droplets (Fig 2F). Taken together, these results demonstrate that Aβ40 promotes and accelerates the phase transition of Tau condensates, leading to a loss of dynamic properties and the formation of more rigid, aggregated structures over time.

Aβ40 potentiates Tau fibrillation in vitro.
The process of Tau aggregation into fibrils has been extensively characterized, with numerous studies focusing on the kinetics of aggregation and the structural properties of the resulting fibrillar assemblies35-36. A predominant approach in these investigations has involved the use of polyanionic co-factors, like heparin, to induce fibril formation37-38. To eliminate the potential confounding effect of co-factors competing with Aβ40 in modulating Tau fibrillation, we employed confocal imaging and aggregation kinetics assays conducted in the absence of co-factors and in the presence and absence of Aβ40 (Fig 2G-H). We utilized Thioflavin T (ThT) fluorescence to monitor Tau aggregation, which is widely used to detect amyloid-like protein aggregates39.

To assess the influence of Aβ40 on Tau fibrillation within a phase-separated droplet state, we conducted ThT staining (Fig 2G) and fibrillation kinetics (Fig 2H) in the presence of 10% PEG8000. There is no ThT positive signal observed in Tau alone sample. However, a strong ThT signal was detected only in the co-condensate of Tau with Aβ40, indicating the presence of β-sheet-rich amyloid aggregates (Fig 2G). Similarly, in the fibrillation kinetics, the co-incubation of Tau and Aβ40 (blue) resulted in a significant increase in ThT fluorescence and no lag phase, suggesting that Aβ40 facilitates Tau fibrillation in the droplet state (Fig 2H). Together, these results demonstrate that Aβ40 accelerated Tau fibrillation within droplets which serve as a precursor for Tau aggregation.

Molecular insights into the interaction between Tau and Aβ40.
Molecular interactions play a crucial role in driving the phase separation and aggregation of Tau and other IDPs20, 24-25. To gain high-resolution insights into the interaction between Tau and Aβ40 at monomeric or condensate states, we performed 2D 15N-1H heteronuclear single quantum coherence (HSQC) NMR spectroscopy using 100 µM isotopically labelled 15N-Tau in the presence and absence of Aβ40 and compared the cross-peak intensities and chemical shift perturbations (Fig 3). The experiments were conducted at 283 K to minimize proton signal loss due to solvent exchange40. In the absence of PEG, equimolar addition of Aβ40, which did not form droplets and confirmed via microscopy, resulted in a global increase in cross-peak intensity by approximately 30%-40% (Fig 3A-C). This observation suggests that Aβ40 shifts the equilibrium of Tau by dissolving NMR-invisible Tau nanoclusters. This observation is further supported by mass photometry analysis (Supplementary Figure 6). Aβ40 at both 5 µM and 25 µM formed small nanoclusters with predominant mass distributions at ~90 kDa and ~84 kDa, respectively. Minor higher-order species were observed around 149–150 kDa, but overall Aβ40 exhibited limited multimerization for nanocluster formation under these conditions. In contrast, Tau showed a broader distribution of higher molecular weight nanocluster species. Tau formed nanoclusters with peaks at 123 kDa, and 182 kDa, indicating enhanced multimerization and nanocluster formation. Upon co-incubation of 5 µM Tau with increasing concentrations of Aβ40 (2.5–25 µM), a notable reduction in Tau nanocluster size and abundance was observed. The resulting mass distributions showed significantly diminished higher-order assemblies compared to Tau alone. These data suggest that Aβ40 interferes with or dissolves Tau nanoclusters, likely through competitive interactions or hetero-oligomer formation that impedes Tau self-association. These findings are consistent with our previous studies using 15N-Aβ NMR measurements, which demonstrated that Tau solubilizes Aβ oligomers12. Notably, only minimal chemical shift perturbations were observed, with slight perturbations detected in the PHF6* (residues 275–280) region. However, these structural and global conformational changes were not detectable by CD spectroscopy (Supplementary Figure 7). To further obtain insights into the interaction between Tau and Aβ40 at condensate state, 2D 15N-1H HSQC NMR spectroscopy was performed. The addition of 10% PEG resulted in the droplet formation, as confirmed by microscopy. Residue-specific analysis showed minor chemical shift perturbations (Supplementary Figure 5). The minimal chemical shift perturbations likely result from conformational compaction within the droplet state induced by excluded volume effects from PEG, rather than direct interaction41. Upon the equimolar addition of Aβ40 in the presence of 10% PEG, cross-peak intensities exhibited a global increase of approximately 50% (Fig 3D-F). This suggests that PEG partially contributes Aβ40-induced dissolution of Tau nanoclusters. Moreover, Aβ40 induced enhanced chemical shift perturbations in multiple regions, particularly PHF6*, the R4 domain (residues 340–370), and the broader N-terminal region (Fig 3E). These observations imply enhancement Aβ40–Tau interactions by increasing the effective local concentration and facilitating transient contacts, thereby promoting condensate formation. Furthermore, crowding effects likely contribute to reduced NMR intensities by stabilizing certain bound states or slowing conformational exchange dynamics. Collectively, our findings suggest that while Aβ40 and Tau interact with similar binding patterns in both aqueous and condensate phases, their interactions are markedly stronger within the condensate environment.

Molecular mechanisms underlying the enhancement of Tau phase separation by Aβ40.
MD simulations have been widely used to elucidate the mechanisms underlying protein phase separation and the phase behaviors42-47. To investigate how Aβ40 solubilizes Tau and then enhances Tau phase separation at the molecular level, we conducted MD simulations on three systems: Tau alone, Aβ40 alone, and a mixture of Tau and Aβ40 (Tau-Aβ40). Each simulation began from a phase coexistence state, featuring a preformed dense phase and an initially empty dilute phase, as done in previous studies48-51.

Tau alone demonstrated a strong propensity for phase separation across a broad temperature range (280-330 K), with a gradual decline as temperature increased (Fig 4A). At 340 K, phase separation dropped sharply compared to at 330 K and was completely lost above this temperature. In contrast, Aβ40 only phase separate at very low (<300 K) temperature and did not exhibit phase separation at 300 K or higher temperatures (Fig 4B). When both proteins were present, they co-phase separated into a dense phase containing both Tau and Aβ40, while a significant portion of Aβ40 were distributed in the dilute phase (Fig 4C). Increasing temperature weakened the phase separation capability of the Tau-Aβ40 system, with complete mixing occurring above 340 K (Fig 4C). We observed that, below 340 K, the dense phase formed by the Tau-Aβ40 mixture was more compact than that formed by Tau alone at each temperature, indicating a higher dense-phase density. This observation is further supported by density profile analyses as described below (Fig 4D-E). In the Tau alone system, the density plateau progressively declined with temperature increasing, alongside an increase in dilute-phase density. At temperatures above 340 K, this plateau disappeared, resulting in a uniform density profile consistent with a complete loss of phase separation (Fig 4D). A similar trend was observed for the Tau-Aβ40 system, with consistently, albeit slightly, higher dense-phase densities than Tau alone system at all temperatures, suggesting an enhancement in phase separation propensity (Fig 4F). Fitting the density profiles to the critical equation yielded upper critical solution temperature (UCST) of 347 K for the Tau system and 351 K for the Tau-Aβ40 system (Supplementary Table 1). This difference in critical temperature (4.2 K) is comparable to those reported in previous coarse-grained simulations assessing differences in phase separation capability between protein systems52-53. For example, the D290V mutation, which experimentally reduces the phase separation capability of hnRNPA2, leads to a ~1% (~3 K) decrease in critical temperature in HPS simulations5. Removal of a C-terminal β-sheet-rich motif of α-synuclein results in a ~5 K decrease in critical temperature of phase separation in HPS simulations53. We then calculated the saturation concentration of Tau to further quantify the impact of Aβ40 on the phase separation capability of Tau. This metric has been widely used to evaluate the phase separation capabilities of protein systems54-57. Our calculations show that the saturation concentration of Tau molecules in the presence of Aβ40 is markedly lower than in the absence of Aβ40 near physiological temperature (290-320 K), indicating that Aβ40 enhances the phase separation propensity of Tau. To assess the dynamics of the condensates, we followed previous studies48, 58 and extracted the dense phases from the final state of the phase-coexistence simulations and placed them into cubic simulation boxes (Supplementary Figure 8). The dense phases were then simulated for 5 μs at 310 K in the NVT ensemble. Using the last 1 μs of each trajectory, we calculated the mean square displacement (MSD) for Tau molecules in the Tau-alone and Tau-Aβ40 systems, as well as the MSD for Aβ40 molecules in the Tau-Aβ40 system. The MSD values for Tau molecules display a non-linear behavior with lag time, suggesting sub-diffusive behaviors (Fig 4H). Fitting MSD curves to power-law diffusion equation MSD = K τ^α yields a smaller diffusion exponent for Tau molecules within the Tau-Aβ40 condensate (0.494±0.001) compared to those within Tau-alone condensate (0.500±0.001), indicating that the presence of Aβ40 reduces the fluidity of Tau molecules within the condensate. Furthermore, the MSD of Aβ40 in the Tau-Aβ40 system is significantly larger than that of Tau and follows a diffusive behavior characterized by the Stokes-Einstein relation (MSD = 6Dτ) with a diffusive coefficient (D) of 1.696±0.004 nm2/ns (Fig 4I). These observations suggest that Aβ40 molecules remain highly dynamic within the condensate while reducing the dynamics of Tau molecules, thereby providing further support for the Aβ40-induced acceleration of Tau phase transition observed in our experiments.

To elucidate the molecular forces governing the Aβ40-enhanced Tau phase separation, we performed interaction analyses on Tau alone and Tau-Aβ40 systems. In both systems, the number of intermolecular contacts was more than twice that of intramolecular contacts (Fig 5A), and intramolecular contacts predominantly occurred between residues in close sequence proximity (Supplementary Figure 9). The presence of Aβ40 led to a marked enhancement of intermolecular contacts but a slight increase of intramolecular contacts (Fig 5A), suggesting that Tau promotes intermolecular interactions within the Tau-Aβ40 system.

In the Tau alone system, strong intermolecular interactions were observed between residues 40-120 in the N-terminal region and residues 120-400 containing the 4R repeat domain, residues 244-369 (Fig 5B) which are respectively enriched in negatively and positively charged residues (Supplementary Figure 10A). This suggests a key role of electrostatic attraction in Tau LLPS. Residue-accumulated contact numbers revealed broad contributions from many residues, including both charged residues and those with high hydrophobicity scores (Fig 5B, Supplementary Figure 11 & 10B), indicating the involvement of multiple interaction types. To further dissect these contributions, we calculated the accumulated contact numbers of different residue types. Our calculations indicated that charged residues were the primary drivers of Tau phase separation, with hydrophobic and polar residues also making nonnegligible contributions (Fig 5C). The significance of polar residues in promoting phase separation has also been reported in a recent study on FUS, another intrinsically disordered protein59.

In the Tau-Aβ40 system, the inter-Tau contact pattern closely resembled that observed in the Tau alone system but showed increased contact numbers across most residue pairs (Fig 5D & Supplementary Figure 11), suggesting that the presence of Aβ40 globally enhanced intermolecular interactions between Tau molecules, in particular the interactions between the 4R repeat domain and the N-terminal region. We further analyzed the interactions between Tau and Aβ40. High contact numbers were observed for hydrophobic-residue-rich regions of Aβ40, i.e., residues 15-22 ( QKLVFFAE ) and residues 30-40 ( AIIGLMVGGVV ) (Fig 5D & S12). Analysis of accumulated contact numbers for each residue type showed that charged residues of Tau protein dominate Tau-Aβ40 interactions followed by polar and hydrophobic residues, while hydrophobic residues of Aβ40 dominate the Tau-Aβ40 interaction followed by charged residues (Fig 5E). In addition, intermolecular interactions between Aβ40 molecules were relatively weak (Supplementary Figure 13), suggesting a minimal contribution to phase separation. Together, these results demonstrate that Aβ40 interacts with Tau mainly through an interplay of hydrophobic and electrostatic interactions.

Collectively, our simulations revealed that, Aβ40 engages with Tau through its charged and hydrophobic residues, thereby promoting Tau-Tau intermolecular electrostatic interactions, and, to a lesser extent, hydrophobic and polar interactions. These combined effects ultimately enhance the phase separation of Tau.

Aβ40 promote Tau induced toxicity.
To further explore how Aβ40 affects the toxicity of Tau aggregates in these environments, we used the A11 antibody, which specifically detects toxic amyloid aggregates with β-sheet structures60, to assess aggregate toxicity under experimental conditions. For Aβ40 alone, increasing its concentration resulted in more intense sample dots (Fig 6A), indicating higher toxicity. A similar trend was observed in SH-SY5Y cell viability assays, with increasing Aβ40 concentrations correlating with increased toxicity (Fig 6C). When Tau was co-incubated with Aβ40, the resulting aggregates showed a trend toward slightly increased toxicity compared to Tau alone, although the difference was not statistically significant (Fig. 6B). Interestingly, even as the Tau: Aβ40 ratio increased, the overall toxicity remained relatively unchanged (Fig 6B). At the cellular level, Aβ40-Tau co-aggregates at a 1:1 molar ratio displayed similar toxicity to Tau alone. Surprisingly, as the Aβ40 proportion increased, a slight reduction in toxicity was observed (Fig 6C). This suggests that Aβ40 may partially disassemble Tau aggregates into monomers, thereby reducing their cytotoxic potential. Then we used fluorophore-labeled proteins to check if these proteins go in cells. We found that co-incubation with Tau increased intracellular Aβ40 signal (Supplementary Figure 14A-B), which parallels the higher toxicity observed for the mixture relative to Aβ40 alone. Both Aβ and Tau can damage cellular membranes and promote internalization61-63 and Aβ40 renders Tau more soluble, promoting Tau to associate with the cell membrane to form oligomers. These oligomers then insert into the lipid bilayer, increase membrane permeability, and in turn facilitate Aβ40 uptake. Further studies are required to validate this mechanism.

Given that the cellular environment is inherently crowded, 10% PEG 8000 was used to mimic artificial cellular environment in vitro, as described in previous studies64. Under this crowding condition, Aβ40 aggregates became more toxic in a concentration-dependent manner, both in dot blot analysis and cell viability assays (Fig 6E & F). More importantly, when Tau was co-incubated with Aβ40 in this environment, the resulting aggregates exhibited threefold higher toxicity than Tau alone (Fig 6E). Additionally, as the Tau-Aβ40 ratio increased, the toxicity escalated further. Consistently, in SH-SY5Y cells, Aβ40-Tau condensates exhibited higher toxicity compared to Tau alone (Fig 6F). Due to the high toxicity of the co-condensates, a slight increase in cell viability was observed as the Tau-Aβ40 ratio increased. These findings suggest that Aβ40 enhances Tau toxicity by promoting its phase separation, leading to the formation of more toxic aggregates with more rigid structures, a phenomenon similar to that observed in a previous study65.

In short, LLPS plays a critical role in modulating Aβ40 and Tau co-aggregation toxicity. In the absence of PEG, Aβ40 appears to dissolve Tau aggregates into monomers, thereby reducing co-aggregate toxicity. However, In the presence of PEG, Aβ40 accelerates Tau LLPS, resulting in the formation of highly toxic aggregates. The results above indicate that Aβ40 and Tau follow distinct co-aggregation pathways under crowded versus uncrowded conditions. This aligns with our previous observations, further supporting the role of Aβ40 in driving Tau aggregation and toxicity under different conditions.

Methods
Tau purification
The purification of recombinant full-length human Tau protein (Uniport P10636-8) was conducted following established protocols75. E. coli BL21 (DE3) cells were cultured in LB medium supplemented with ampicillin (100 mg/L). Protein expression was induced with 0.4 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) at 0.6–0.8 of OD600, followed by incubation at 37°C for 2 hours. Cells were harvested by centrifugation, and the resulting pellets were stored at −20°C prior to purification. For purification, Tau pellets were resuspended in 50 mM sodium phosphate buffer, 2.5 mM EDTA, pH 6.2. Following sonication, lysates were centrifuged at 5000 × g for 30 minutes to remove insoluble components. The supernatants were subjected to heat treatment at 75°C for 15 minutes, followed by centrifugation at 25,000 × g for 20 minutes. The supernatant was loaded onto a Hi-Trap SP FF cation-exchange chromatography column (Cytiva) and eluted using a NaCl gradient. Protein was identified via SDS-PAGE and dialyzed against 20 mM ammonium bicarbonate buffer before lyophilization. Protein concentrations were determined by UV absorption at 274 nm, using extinction coefficients of 7600 M⁻¹ cm⁻¹ for Tau.

To label Tau with 15N isotopes, the E. coli BL21 (DE3) culture expressing Tau protein was grown in a M9 minimal medium with 15NH4Cl. Purification process is same as without labeled protein.
Fluorescent labeling of Tau was performed with an Alexa Fluor™ 647 C2 Maleimide dye (Catalog number A20347, ThermoFisher Scientific, USA) was followed the manufactory protocol.

Aβ40 sample preparation
Recombinant Aβ40 was purchased from AlexoTech, Umeå, Sweden (cat: AB-100-10). The 1mg of Aβ40 were dissolved to a concentration of 461 μM in 10 mM NaOH, and then sonicated in an ice-water bath for 1 min. The samples were filtered with a 0.22 μm centrifuge filter at 4 °C and aliquoted on ice and kept in a -80 °C. TAMRA Fluorescent labelled Aβ40 was purchased from Cayman Chemical (cat: 27413).

ThT fluorescence assay
To investigate amyloid fibrillation kinetics, 15 μM Tau was incubated with or without Aβ40 peptides in the presence of 50 μM Thioflavin T (ThT). All samples were prepared on ice, and 15 μL of each was transferred into a 384-well Black/Clear Bottom plate (cat: 242764, ThermoFisher) and sealed. Kinetics assays were performed using a PHERAstar FSX microplate reader (BMG LABTECH, Germany), recording fluorescence every 10 minutes with excitation and emission wavelengths of 430 nm and 480 nm, respectively. Assays were conducted in five replicates under shaking conditions (280 rpm) at 37°C in 50 mM PB with 150 mM NaCl (pH 7.4).

LLPS
The LLPS experiments were conducted using an LCP crystallization plate. All protein stock solutions were prepared on ice, and protein mixtures were pre-mixed at specific concentrations. Sample dispensing was performed using a multi-channel pipetting robot (Mosquito, SPT Labtech), where 200 nL of protein solution was mixed in a 1:1 ratio with buffer to achieve varying protein and PEG-8000 concentrations. Each condition was tested in at least three replicates. The plates were sealed, incubated at 20°C, and imaged using a Rock Imager microscope (Formulatrix). Droplet size and area were quantified using Fiji software.

Fluorescence imaging and FRAP analysis in vitro
Fluorophore-labeled LLPS experiments were conducted using a Stellaris microscope (Leica Microsystems, Germany). Droplet formation was achieved by mixing 5% labeled protein with 95% unlabeled protein, following the same sample preparation protocol as the unlabeled system. LCP plates were retrieved from the Rock Imager system and mounted onto the Stellaris microscope. Imaging was performed using a 647 nm laser line and a 63× oil-immersion lens. Color crosstalk was tested and found to be negligible under our conditions.

Fluorescence recovery after photobleaching (FRAP) experiments were carried out on the same microscope in FRAP mode. For each droplet, a selected region of interest (ROI) was bleached using 60% laser intensity for 2 s. Post-bleach time-lapse images were acquired at a frame rate of 1 s for 60 frames and analyzed using the FRAP_profiler_v2 plugin developed by the Hardin lab in Fiji76. Fluorescence intensities were recorded for two ROIs: ROI1 (photo-bleached region) and ROI2 (unbleached region, used for background correction). The recovery time constant was determined by fitting the corrected fluorescence intensities to a single-exponential model.

Turbidity measurements
The turbidity was measured in a PHERAstar FSX microplate reader (BMG LABTECH, Germany) in 384-well Black/Clear Bottom plates (cat: 242764, ThermoFisher) of both fresh samples at room temperature. All samples were prepared on ice, and 30 μL of each sample was transferred to each well. The background absorbance was subtracted from the sample measurements, measured with 6 replicates and presented as average. The protein concentration and buffer condition were presented in the figure legend.

NMR
The NMR experiments were performed on a 700 MHz Bruker spectrometer equipped with a triple resonance cryogenic probe. 100 μM 15N-Tau protein in 20 mM sodium phosphate (pH 6.3) alone or using a 1:1 Tau: Aβ40 molar ratio was used. Additional experiments were performed with 10% (w/vol) PEG8000 for LLPS conditions using 100 μM 15N-Tau. The experiments were performed at 283 K with 90/10 H2O/D2O. The spectra with and without Aβ40, both in aqueous solution and during LLPS conditions were compared by (1) calculating the relative intensities based on the amplitude intensities and (2) determination of the chemical shift perturbations (csc). The csc were calculated from Equation below:
Δδ = ((( ΔδN)^2 + (ΔδH)^2) /2)^1/2 (1)
The cross-peak assignment of Tau (BMRB ID 50701) was achieved by a comparison to published work77, Data were processed and analyzed with software’s Topspin v.4.2.0 (Bruker) and Poky78(University of Colorado Denver).

Dot blot
Protein samples including Aβ40, Tau, and Tau-Aβ40 mixtures were prepared on ice. All samples were incubated at 37°C for 2 hours in 50 mM PB, 150 mM NaCl, pH 7.4, with or without 10% PEG8000. Subsequently, 3 µL of each sample was transferred onto a nitrocellulose membrane (Cat. No. 10600124; Amersham). The membrane was then blocked with 5% non-fat milk in TBS-T (20 mM Tris-HCl, 0.8% NaCl, 0.1% Tween 20, pH 7.4) for 1 hour at room temperature, followed by overnight incubation at 4°C with the primary antibody A11 (kindly provided by Prof. Rakez Kayed’s group and used at a 1:1,000 dilution). After three washes with TBS-T (10 minutes each), the membrane was incubated with a goat anti-rabbit IgG H&L (HRP) secondary antibody (Thermo Fisher Scientific, catalog no. 3246, 1:5000 dilution) for 1 hour at room temperature. Following three additional washes with TBS-T, the membrane was developed using of the chemiluminescent substrate LumiGLO (Chemiluminescent Substrate Kit). The specificity of the primary antibodies used in this study has been previously validated, as described in the literature60, and manufacturer datasheets.

Cell viability
SH-SY5Y human neuroblastoma cells (female) were obtained from Abcam (catalog number ab275475) and used for cell viability and cytotoxicity assays. Cell line authentication was not independently performed in this study. The identity of the cell line was assured by the supplier. The cells were cultured in Dulbecco’s Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 1% penicillin/streptomycin. The cells were maintained in a humidified incubator at 37°C with 5% CO₂. For the experiment, cells were seeded into a 96-well plate at a density of 10,000 cells per well and allowed to adhere for 24 hours. Aβ40, Tau, Tau: Aβ40 at ratios: 1:1 and 1:2 were prepared. All samples were pre-incubated at 37°C for 2 hours in 50 mM PB, 150 mM NaCl, pH 7.4, with or without 10% PEG8000. These pre-incubated samples were then added to the culture medium and incubated with the cells for 48 hours. Each condition was tested in triplicate. Cell viability was assessed using the CellTiter-Glo® Luminescent Cell Viability Assay Kit (Promega). For a 96-well plate, 100 µL of kit reagent was added per well. The plate was then shaken for 2 minutes and incubated at room temperature for 10 minutes. Luminescence was measured using a PHERAstar FSX microplate reader (BMG LABTECH). The intensity of the luminescent signal corresponded to cell viability, with higher luminescence indicating greater cell survival.

Confocal images for cell uptake
SH-SY5Y cells were seeded at a density of 10,000 cells per well in 96-well plates. For visualization, Alexa Fluor 647–labeled Tau and TAMRA-labeled Aβ40 were included at 1% of the total protein concentration. Protein samples containing 15 µM Aβ40, 15 µM Tau, or a mixture of 15 µM Aβ40 and 15 µM Tau were pre-incubated at 37 °C for 2 h before being transferred to the cell culture medium. After 24 h of incubation, cells were washed three times with PBS (10 min each wash) at room temperature. Confocal images were acquired using a 20× objective. Red fluorescence signal indicates Tau protein, and green fluorescence singal indicates Aβ40 protein. Scale bar: 20 µm.

Mass photometry
Mass photometry Mass photometry was conducted using the OneMP mass photometer (Refeyn, UK) following a previous protocal75. Rectangular glass slides and self-adhesive silicone wells were cleaned following the manufacturer's protocol, involving three cycles of washing with isopropanol and Milli-Q water. After drying, the glass slides were mounted onto a 100X oil immersion objective, and the silicone well was affixed to facilitate sample loading. For calibration, β-Amylase (monomer: 56 kDa, dimer: 112 kDa, tetramer: 224 kDa) and Thyroglobulin (monomer: 335 kDa, dimer: 670 kDa) served as standard proteins. Background subtraction was performed with buffer solution. Calibration was conducted using a laser for 120 seconds under optimized auto-exposure settings.

To monitor Aβ40 and Tau nanocluster formation over time, proteins were perpared in a 50 mM PB, 150 mM NaCl buffer (pH 7.4) to a total volume of 50 μL in a 1.5 mL Eppendorf tube. For mass photometry measurements, 18 μL of the buffer was loaded onto the silicone well, followed by autofocusing. Subsequently, 2 μL of sample was added to achieve a final concentration, and mass measurements were performed with the laser for 60 seconds.

Data analysis was conducted using DiscoverMP software. Molecular weight estimations were based on the contrast values of individual landing events captured across multiple frames, generating a contrast-to-molecular weight (MW) calibration curve. Histograms of detected particles were fitted with Gaussian functions to determine the average MW of the samples. The detection limit for protein molecular weight was approximately 40 kDa, so individual Aβ40 monomers (~4 kDa) were not visible, while nanoclusters larger than 40 kDa were expected to be detectable.

Coarse-grained molecular dynamics simulations
The full-length Tau and Aβ40 molecules were modeled as elastic chains of coarse-grained beads and each bead corresponds to a single residue44. Sequential beads were connected by a harmonic bond with an equilibrium bond length of 0.38 nm and a spring constant of 1000 kJ/mol/nm. The nonbonded interactions in the model incorporated a Lenard-Jones term, utilizing the Hydropathy Scale (HPS) potential originally developed by the Mittal group43 based on hydrophobicity scores calculated by Kapcha and Rossky79.

Φ_nb(r) = 4ε[(σ/r)^12 - (σ/r)^6] + (1-λ)ε, r ≤ 2^(1/6)σ
Φ_nb(r) = 4λε[(σ/r)^12 - (σ/r)^6], otherwise

The long-range electrostatic interactions were accounted for using a Coulomb term with Debye screening, with the relative permittivity denoted as D.
E_ij(r) = (q_i q_j / 4πε_0 D r) * exp(-r / λ_D)

The Debye length λ was set according to the Debye-Hückel formula where I corresponds to the ion strength which was set as 150 mM NaCl.
λ_D = sqrt(ε_r ε_0 k_B T / 2 e^2 I)

To assess the LLPS capability of the Tau alone, Aβ40 alone and Tau-Aβ40 systems, we conducted direct coexistence simulations. The initial configurations of Tau/ Aβ40 systems were generated by placing 80/160 chains of Tau/Aβ40 into a cuboid box with the centroids of the chains positioned at the grid points of a 4×4×5/5×5×7 evenly distributed grid. The initial configurations of Tau-Aβ40 systems were generated by splicing the above-mentioned Tau and Aβ40 simulation box. The configuration of each Tau or Aβ40 chain was generated via random walk, with the maximum distance from the centroid restricted to within 4 nm (for Tau) or 2 nm (for Aβ40). Each system was relaxed at a constant temperature of 150 K and a constant pressure of 1 bar using a Berendsen barostat, resulting in a compressed simulation box. Subsequently, the box was expanded in the z-direction by a factor of ten, creating a slab-like box. The temperature was then gradually increased to the target temperature at a rate of 0.2 K/ns in the NVT ensemble. The production run was conducted for 3.0 μs using a Langevin thermostat with a relaxation time of 5 ps and a time step of 10 fs. All simulations were carried out utilizing the HOOMD-Blue 2.9 package80 on GPU cards. Trajectory analyses were carried out using our in-house-developed tools. The densities of the dense and dilute phases were obtained by fitting the density profiles to the following equation, where z₀ denotes the midpoint of the interface between the two phases, and w represents the interfacial width.
ρ(z) = (ρ_dense + ρ_dilute) / 2 - (ρ_dense - ρ_dilute) / 2 * tanh[(z - z₀) / 2w]

We then determined the critical temperature by fitting the densities of the dense and dilute phases to the following critical equation, where A is a universal fitting parameter and β is the critical exponent, fixed at 0.365, corresponding to the universality class of the three-dimensional Heisenberg model.
ρ_dense - ρ_dilute = A(T_C - T)^β

The error bars for the densities shown in the phase diagram represent the 95% confidence intervals of the fitted density values for the two phases, while those for the critical temperature correspond to the 95% confidence intervals of the fitted critical temperature values. The cutoff for two residues forming a contact is calculated by 1.2*(σ_i+σ_j)/2, in which σ_i and σ_j refer to the effective particle size defined as the distance at which the LJ potential equals zero81-82. The number of contacts between two protein molecules was defined as the number of intermolecular bead pairs within this cutoff distance. Reported contact numbers for Tau-Tau and Tau-Aβ pairs were normalized by the total number of Tau molecules in the system, while contact numbers for Aβ-Aβ pairs were normalized by the total number of Aβ molecules. To estimate the error bars for intermolecular and intramolecular contact numbers, we calculated the contact number for four equal segments of the final 1 μs of the trajectory. The error bars correspond to the minimum and maximum contact number values obtained from these four segments. The categorization of the 20 amino acids into hydrophobic, charged, polar, and other groups follows a previous study50, with both hydrophobic and aromatic residues classified as hydrophobic for simplification.

Quantification and statistical analysis
All statistical analysis was performed in GraphPad Prism or Origin. Data are presented as mean ± SEM (standard error of the mean) from at least three independent biological replicates, unless indicated otherwise. Statistical significance between experimental groups was analyzed either by two-tailed Student’s t-test or one-way ANOVA followed by Bonferroni’s multiple comparison.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "In this manuscript the authors have investigated the interplay of Aβ40 peptides with Tau protein that drives the liquid-solid transitions of Tau protein droplets. The authors have employed various experimental techniques such as fluorescence microscopy, FRAP, turbidity measurements, NMR to qualify and quantify Tau aggregation phenotype in the presence of Aβ40 peptides, and performed coarse-grained molecular dynamics (MD) simulations to understand the protein interactions at the residue level.\nKey results: The authors claim that Aβ40 promotes Tau phase separation and accelerates its phase transition to form amyloid like solid aggregates. Through MD simulations, they showed that Aβ40 and Tau interact mainly through electrostatic and hydrophobic interactions. They also claim that in the absence of crowders, addition of Aβ40 reduced cell toxicity, while in the presence of crowders (PEG), Aβ40 increased cell toxicity. Based on the observations, the authors have proposed a mechanism where Aβ40 can interact with Tau to keep it in its monomeric form. However, in the presence of crowders, Aβ40 also promotes the phase separation and transition of tau proteins, leading to disease pathology.\nOverall, the manuscript is well-written and presents some interesting results. However, there are several conceptual and technical points, which call into question the certain conclusions of the work.\nMajor comments:\n1. The phrase “Aβ40 does not undergo LLPS” has little meaning from a thermodynamic standpoint. Since phase separation is a thermodynamic process, the conditions must be specified. Also the authors used the catGRANULE algorithm to predict whether Aβ40 undergoes LLPS. conditions is this algorithm predicting the phase separation propensity for? Related to that, what does the score from this algorithm mean. Is there a maximum/minimum value one can expect? Is there a threshold score that makes something undergo LLPS (say under physiological conditions)? The details there are quite vague and it is difficult to appreciate what exactly is being predicted.\n2. I find it difficult to see how the droplet area comparisons with and without Aβ40 directly demonstrate accelerated kinetics of droplet formation. Aβ40 alone produces droplets with a notably different topology than Tau alone (see Fig. 2A). Thus, the observed differences in droplet areas could largely reflect intrinsic differences in droplet morphology rather than kinetic effects. Consequently, additional evidence beyond droplet area measurements is required to substantiate the claim that Aβ40 accelerates the kinetics of Tau droplet formation.\n3. From the coarse-grained MD simulations that authors claim that the dense-phase density in the presence of Aβ40 is greater than when Aβ40 is absent. However, the phase diagram in Figure 4F show practically identical dense-phase densities for both systems. Therefore, their results do not support this claim. Furthermore, there are no error bars shown in the figure. What is the error associated with the critical point estimate? It is likely that the 2 K difference in Tc is within the uncertainty. Based on the results presented so far, it does not seem, from a thermodynamic standpoint, that the Aβ40 is having a significant impact.\n4. Lines 366-368: “When Tau was co-incubated with Aβ40, the aggregates displayed slightly increased toxicity compared to Tau alone (Fig 6B).” The difference there does not seem significant. They are both within the errors.\n5. Fig. 1F: At what time point of the droplet formations were the FRAP measurements performed? Something that seems contradictory to me is that the Tau droplet sizes increase rapidly in the presence of Aβ40 due to coalescence (indicating liquid-like nature), while at the same time FRAP measurements are showing arrested dynamics. I would not have expected the two to be true at the same time. Were the FRAP measurements performed long aier (example, a day) the large droplets were already formed? Also, are similar FRAP measurements performed for Aβ40 to confirm that all the dynamics are arrested?\n6. Fig. S9, Line 309 – 313: (1) In the MSD calculation for the Tau+Aβ40, were the proteins treated separately? Tau is significantly longer than Aβ40, which could lead to varying diffusion coefficient for the two species. It might be useful to separate the two to be accurate and maybe get some useful insight. (2) How exactly were the diffusion coefficient measured? Did the authors assume diffusive behavior and use the Stokes-Einstein relation? If so, that might be wrong since the MSD curves are clearly not linear and indicate sub-diffusive behavior (as expected). In that case one should be able to fit the MSD curve to < r²(τ) > = K τ^α. Overall, the details on how the MSD calculations were done are lacking. What ensemble was used, how long were the simulations etc?\n7. Line 317-318: Provide more information as to how the interaction analysis was performed. Was a distance threshold used? If so, what was it? Also, were the contact maps normalized in Fig. 5? Between residues 200-300 the contact maps have some contact values almost equal to 1. Does this mean that those residue pairs were in contact most of the time?\nMinor comments:\n1. Figure 6 B/E or C/F: Invert either the intensity or the cell viability so that both quantities vary in the same direction. This will make the comparison of B and C and E and F more straightforward.\n2. Lines 155-156: Which figures correspond to the brightfield microscopy images that is being alluded to?\n3. Fig. 1A: Indicate the sequence of the Tau protein that has been used (and the uniport id). Is it P10636-8?\n4. Line 169-170: There is a typo. Instead of “with or with” it should be “with or without”\n5. Fig. 2H: The legend markers should be made larger.\n6. Line 249: Sentence reads odd. Missing word here “formed relatively nanocluster”?\n7. Line 274: Typo. Instead of “imply that enhancement Aβ40–Tau interactions”, it should be “imply enhancement of Aβ40–Tau interactions.”\n8. Fig. 5C: It would be helpful if you could indicate in the caption what the letters ‘H’, ‘P’, ‘C’, ‘O’ represent.\n9. Line 333 – 335: “Our calculations indicated that charged residues were the primary drivers of Tau phase separation, followed by polar residues, with hydrophobic residues also making nonnegligible contributions (Fig 5C).” The way this sentence is written, it seems that the accumulated contact numbers for the electrostatic interactions are much larger than the other ones (polar and hydrophobic). However, from the figure the polar contacts are almost equal to the electrostatic ones and closely followed by the hydrophobic interactions. The sentence could perhaps be framed in a different manner.", "reviewer_2": "The paper is both interesting and timely. The observation of the acceleration of the LLPS of Tau in the presence of Aβ would be of great interest to those study Alzheimer’s disease. The potential crosstalk of Tau/ Aβ in AD is nicely addressed here. There are a number of issues that might be modified to clarify the message in the paper.\nCritics:\n1) Why do the authors only use AΒ40 ? Why not AΒ42 ? It seems that these could have been carried out in parallel ?\n2) Aβ is recruited into Tau condensates in this study. The authors state that Aβ and tau may be co-localised in the brain and cite a couple of papers. Are they proposing that this interaction is a switch to initiate Tau aggregation and propagation as observed in Alzheimer’s disease or do they really expect Aβ to be found in most fibrils ? This message might be implicit in the paper but it is not explicit – Tau is involved in over 20 neurodegenerative diseases and it’s cryo-EM structure has been solved for many of these diseases. Is Aβ40 the switch to drive Tau to one of these forms ? It is a pity that the study could not have also been carried out using phospho-Tau, but that is a complicated thing to do.\n3) In a previous paper, the group collaborated with another NMR team, that time using N-labelled Aβ and unlabeled Tau. The conclusion of that paper was that Tau inhibited Aβ aggregation by (i) monomerizing soluble oligomers into monomers with a weak affinity for Tau and (ii) binding to higher affinity Aβ fibrils to prevent further oligomerization by a kind of capping mechanism. Here they suggest that Aβ has the same monomerizing effect on small Tau nanoclusters. This is briefly touched on in the discussion. I think this message could be expanded upon to explain how you can have both of these effects and the role of the differing concentrations of each protein.\n4) The conditions tested for LLPS of Aβ are very limited. LLPS of Aβ has been shown previously- but under acidic conditions. Do these conditions ever occur under physiological conditions ?\n5) What about colour crosstalk of Alexa647 excited by TAMRA excitation ? Could the authors give a bit more information about those experiments to clarify how they were carried out.\n6) The NMR data does seem to confirm the mass photometry data, however it gives very limited information on protein structure and interaction. The weak CSPs are unconvincing in terms of which residues really bind Aβ. The only vague information on structure is the Thioflavin data which is hardly conclusive. While the NMR data itself is not to be criticized, the lack of structural data is the weakest point of the paper. It would be very useful to have complementary structural data. Would it be possible to have Cryo-EM data of the aggregates ? Or failing that, some Circular Dichroism or Infra-Red data ?\n7) From 216 – the authors talk About papers studying the effects on structure by polyanions. However the authors themselves give no structural information on their experiments other than a positive Thioflavin signal. As far as I am aware, the cryo-EM structure of Tau induced by mixing with 2 small beads is unknown. Have the authors any insight on the structure induced by their aggregation experiments ?\n8) The authors carry out toxicity experiments on a cell line. Do the proteins enter the cells in the cell experiments ? Do they remain together ? Have they had a look using their fluorophore labelled proteins ?\nEnglish errors:\n78 biomolecule should be biomolecules\n92 disease-related mutations Tau should be “disease-related tau mutation”\n169/170 with or with should be ”with or without”\n187 remove “the” from we did the long term\n241 isotopically labelled (labelled missing)\n249 - A word or words are missing from this phrase.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Response: We sincerely thank the reviewer for their thorough assessment of our manuscript.\nMajor comments:\n1. The phrase “Aβ40 does not undergo LLPS” has little meaning from a thermodynamic standpoint. Since phase separation is a thermodynamic process, the conditions must be specified. Also the authors used the catGRANULE algorithm to predict whether Aβ40 undergoes LLPS. conditions is this algorithm predicting the phase separation propensity for? Related to that, what does the score from this algorithm mean. Is there a maximum/minimum value one can expect? Is there a threshold score that makes something undergo LLPS (say under physiological conditions)? The details there are quite vague and it is difficult to appreciate what exactly is being predicted.\nResponse: We appreciate the reviewer’s insightful comments regarding the statement on Aβ40 LLPS, as well as the need to clarify the interpretation of catGRANULE predictions.\nClarification of phrasing: We agree that the phrase “Aβ40 does not undergo LLPS” is imprecise. What we meant is that under the conditions tested in our experiments (buffer: 50 mM PB, 150 mM NaCl pH 7.4, Aβ40 concentration: 20, 50, 100 µM, 10% and 15% PEG8000 as a crowding agent, with or without 12h incubation), Aβ40 did not form condensates detectable by fluorescence microscopy or turbidity measurements. We have revised the text accordingly to specify the experimental conditions under which this observation holds true.\ncatGRANULE algorithm details: catGRANULE predicts the propensity of a protein sequence to form condensates by integrating sequence features such as intrinsic disorder and low-complexity regions (Bolognesi et al., 2016; Klus et al., 2014). The scores are relative values rather than absolute thermodynamic quantities. 1) There is no fixed “maximum/minimum” score, but higher scores indicate stronger predicted phase-separation propensity. 2) Importantly, catGRANULE does not model specific solution conditions (e.g., salt, crowding, pH), so the prediction should be interpreted as a sequence-intrinsic tendency, not as a definitive thermodynamic prediction under physiological conditions.\nWe have now specified in the Results that catGRANULE predictions provide a sequence-based propensity score and that experimental validation is required to confirm LLPS under specific conditions. The phrasing in the Results has been adjusted to:\n“Overall, our experimental observations show that, unlike Tau, Aβ40 does not form droplets under the tested conditions. This finding is consistent with catGRANULE predictions which indicate a much lower phase separation propensity of Aβ40 compared to Tau, and is further supported by our coarse-grained simulations presented in the following sections.” (Page 4, line 139-143)\n2. I find it difficult to see how the droplet area comparisons with and without Aβ40 directly demonstrate accelerated kinetics of droplet formation. Aβ40 alone produces droplets with a notably different topology than Tau alone (see Fig. 2A). Thus, the observed differences in droplet areas could largely reflect intrinsic differences in droplet morphology rather than kinetic effects. Consequently, additional evidence beyond droplet area measurements is required to substantiate the claim that Aβ40 accelerates the kinetics of Tau droplet formation.\nResponse: We thank the reviewer for this insightful comment. We agree that differences in droplet area alone may not provide sufficient evidence to establish accelerated kinetics, since they could also reflect intrinsic morphological differences. To address this concern: 1) FRAP measurements (Fig 2D-E): We observed that Tau droplets formed with Aβ40 exhibit reduced fluorescence recovery compared to Tau-only droplets, consistent with a more rapid liquid-to-solid transition. 2) time lapse imaging of Tau-Aβ40 droplet formation: we observed that the maturation of Tau-Aβ40 droplet is faster than Tau alone droplet and we quantify the diameter to establish the droplet formation kinetics in Fig S3A-B.\nTogether, these assays complement the microscopy data and support the interpretation of accelerated kinetics rather than purely morphological effects.\nFigure S3. Aβ40 accelerates Tau LLPS in vitro.\nA, Representative time lapse images of phase separated droplets of Tau with or without Aβ40 in the presence of 10% PEG. Scale bar in the images is 20 µm.\nB, Quantification of the diameter of droplets corresponding to A. The total number of droplets accounted is n=15 from 3 independent microscopy images.\n3. From the coarse-grained MD simulations that authors claim that the dense-phase density in the presence of Aβ40 is greater than when Aβ40 is absent. However, the phase diagram in Figure 4F show practically identical dense-phase densities for both systems. Therefore, their results do not support this claim. Furthermore, there are no error bars shown in the figure. What is the error associated with the critical point estimate? It is likely that the 2 K difference in Tc is within the uncertainty. Based on the results presented so far, it does not seem, from a thermodynamic standpoint, that the Aβ40 is having a significant impact.\nResponse: We thank the reviewer for raising these insightful questions. The density profiles (Fig 4D-E) show that, near physiological temperature (290-320 K), the dense-phase densities of the Tau-Aβ40 system are noticeably higher than those of the Tau-alone system. During the course of revision, to further support the impact of Aβ40 on the phase separation capability of Tau, we introduced an additional metric, saturation concentration, which has been widely used to assess the phase separation propensity of protein systems1-4. Our calculations reveal that, near physiological temperature (290-320 K), the saturation concentration of Tau molecules in the presence of Aβ40 is markedly lower than in its absence, providing further evidence that Aβ40 notably enhances the phase separation capability of Tau.\nThe phase diagrams (Fig 4F) show that the critical temperature of the Tau-Aβ40 system is ~4.2 K higher than that of the Tau-alone system. This temperature difference is comparable to those reported in previous coarse-grained simulations assessing differences in phase separation capability between protein systems. For example, the D290V mutation, which experimentally reduces the phase separation capability of hnRNPA2, leads to a ~1% (~3 K) decrease in critical temperature in HPS simulations5. Removal of a C-terminal β-sheet-rich motif of α-synuclein results in a ~5 K decrease in critical temperature of phase separation in HPS simulations6. We acknowledge the absence of error bars in the original phase diagram. We have revised Figure 4F to include uncertainties and added an additional table (Table S1) to include the 95% confidence intervals of the critical temperature values. The uncertainties are 0.1 K for the Tau-alone system and 0.3 K for the Tau-Aβ40 system, both of which are considerably smaller than the observed 4.2 K difference between the two systems. Taken together, these analyses provide further evidence that Aβ40 notably enhances the phase separation propensity of Tau. The manuscript has been revised accordingly.\n“We then calculated the saturation concentration of Tau to further quantify the impact of Aβ40 on the phase separation capability of Tau. This metric has been widely used to evaluate the phase separation capabilities of protein systems 1-4. Our calculations show that the saturation concentration of Tau molecules in the presence of Aβ40 is markedly lower than in the absence of Aβ40 near physiological temperature (290-320 K), indicating that Aβ40 enhances the phase separation propensity of Tau.” (Page 8, line 318-324)\n“This difference in critical temperature (4.2 K) is comparable to those reported in previous coarse-grained simulations assessing differences in phase separation capability between protein systems5-6. For example, the D290V mutation, which experimentally reduces the phase separation capability of hnRNPA2, leads to a ~1% (~3 K) decrease in critical temperature in HPS simulations5. Removal of a C-terminal β-sheet-rich motif of α-synuclein results in a ~5 K decrease in critical temperature of phase separation in HPS simulations6.” (Page 8, line 313-318)\nMethod section: “The saturation concentration of Tau molecules is obtained by fitting the density profiles of Tau molecules to the Landau-Ginzburg free energy model, 𝜌(𝑧) = 0.5(𝜌 −𝜌 )∙[tanh(𝑧−𝑧 ⁄𝜉)], where z0 and 𝜉 are fitting parameters that respectively correspond to the phase boundary and the correlation length.” (Page 37, line 969-972)\nIn addition, we have made the following changes to Figure 4 to improve readability. First, we added snapshots at 280, 290, and 360 K to Figures 4A-C to match the density profiles shown in Figures 4D-E. Second, because the original snapshots were taken from the final frame of each simulation, which was not always representative of the overall phase behavior, we replaced them with more representative frames. Accordingly, the figure caption has been revised from “final simulation snapshots” to “representative simulation snapshots.” The main text has also been updated accordingly.\nReferences:\n1. Regy, Roshan Mammen, et al. \"Sequence dependent phase separation of protein-polynucleotide mixtures elucidated using molecular simulations.\" Nucleic acids research 48.22 (2020): 12593-12603.\n2. Martin, Erik W., et al. \"A multi-step nucleation process determines the kinetics of prion-like domain phase separation.\" Nature communications 12.1 (2021): 4513.\n3. Zhang, Yumeng, et al. \"Toward accurate simulation of coupling between protein secondary structure and phase separation.\" Journal of the American Chemical Society 146.1 (2023): 342-357.\n4. Kang, Wen Bin, et al. \"Multi-scale molecular simulation of random peptide phase separation and its extended-to-compact structure transition driven by hydrophobic interactions.\" Soft Matter 19.41 (2023): 7944-7954.\n5. Ryan, Veronica H., et al. \"Mechanistic view of hnRNPA2 low-complexity domain structure, interactions, and phase separation altered by mutation and arginine methylation.\" Molecular cell 69.3 (2018): 465-479.\n6. Tang, Yiming, et al. \"Dissecting the Molecular Determinants of α‐synuclein Phase Separation and Condensate Aging: The Pivotal Role of β‐Sheet‐Rich Motifs.\" Advanced Science (2025): e11545.\nA-C, Representative simulation snapshots of Tau alone (A), Aβ40 alone (B) and Tau-Aβ40 (C) systems at six different temperatures.\nD-E, Density profiles along the z-axis at eight temperature points for the Tau alone (D) and Tau-Aβ40 (E) systems.\nF, Phase diagrams of the Tau and Tau-Aβ40 systems with critical temperatures obtained by fitting to critical equation.\nG, The saturation concentration of Tau molecules of the Tau alone and Tau-Aβ40 systems.\nH-I, MSD of Tau molecules within Tau alone and Tau-Aβ40 condensates (H) and that of Aβ40 molecules within Tau-Aβ40 condensate.\nTable S1. Fitting of density profiles to critical function 𝒚(𝒕) = (𝚫𝝆)𝟏/𝜷 = 𝒌𝑻−𝒌𝑻 . The confidence bounds of each parameter are provided in the brackets.\nSystem 𝑘 (×106 mg⁄mL⁄K) 𝑇 (K)\nTau alone 5.98 (5.93, 6.04) 347.30 (347.26, 347.35)\nTau-Aβ40 5.85 (5.68, 5.99) 351.50 (351.31, 351.86)\n4. Lines 366-368: “When Tau was co-incubated with Aβ40, the aggregates displayed slightly increased toxicity compared to Tau alone (Fig 6B).” The difference there does not seem significant. They are both within the errors.\nResponse: We thank the reviewer for pointing this out. We agree that the difference in toxicity between Tau alone and Tau co-incubated with Aβ40 is small and falls within experimental error. We have revised the text to avoid overinterpreting this trend.\n“When Tau was co-incubated with Aβ40, the resulting aggregates showed a trend toward slightly increased toxicity compared to Tau alone, although the difference was not statistically significant (Fig. 6B).” (Page 9, line 391-394)\n5. Fig. 1F: At what time point of the droplet formations were the FRAP measurements performed? Something that seems contradictory to me is that the Tau droplet sizes increase rapidly in the presence of Aβ40 due to coalescence (indicating liquid-like nature), while at the same time FRAP measurements are showing arrested dynamics. I would not have expected the two to be true at the same time. Were the FRAP measurements performed long aier (example, a day) the large droplets were already formed? Also, are similar FRAP measurements performed for Aβ40 to confirm that all the dynamics are arrested?\nResponse: We thank the reviewer for this insightful comment. The FRAP measurements shown in Fig. 1F were performed at 1 day after droplet formation, when droplets had already reached their approximate equilibrium size. While rapid coalescence initially reflects the liquid-like nature of Tau droplets, it is known that these droplets can undergo aging, leading to slow or arrested internal dynamics over time (e.g., Wegmann et al., 2018). Therefore, the coalescence we observed does not contradict the FRAP results, which capture internal molecular mobility rather than droplet fusion.\nFRAP measurements on Aβ40 were also performed and are shown in Fig. S4. These data indicate that there is less fluorescence recovery for Aβ40 FRAP behavior, confirming that the arrested dynamics in Tau+Aβ40 droplets.\n6. Fig. S9, Line 309 – 313: (1) In the MSD calculation for the Tau+Aβ40, were the proteins treated separately? Tau is significantly longer than Aβ40, which could lead to varying diffusion coefficient for the two species. It might be useful to separate the two to be accurate and maybe get some useful insight. (2) How exactly were the diffusion coefficient measured? Did the authors assume diffusive behavior and use the Stokes-Einstein relation? If so, that might be wrong since the MSD curves are clearly not linear and indicate sub-diffusive behavior (as expected). In that case one should be able to fit the MSD curve to < 𝑟²(𝜏) > = 𝐾 𝜏𝛼. Overall, the details on how the MSD calculations were done are lacking. What ensemble was used, how long were the simulations etc?\nResponse: We thank the reviewer for this insightful question. In our original manuscript, we calculated the MSD of protein molecules based on phase-coexistence simulations preformed in slab-like simulation boxes. However, during the revision process, we learned that previous studies on MSD characterizations for biomolecular condensates are typically calculated from pure dense phases1-2, which were generated using cubic simulation boxes. We thus conducted additional simulations of the dense phase for both Tau alone and Tau-Aβ40 systems, starting from preformed dense phases taken from the final frame of the original phase-coexistence simulations (Figure S8). We then recalculated the MSD curves using the last 1 μs of each simulation trajectory.\nFor the Tau-alone system, we calculated the MSD curve for all Tau molecules, whereas for the Tau-Aβ40 system, we separately calculated the MSD curves for Tau and Aβ40 molecules. Our results indicate that the MSD values for Tau molecules in the Tau-Aβ40 system are smaller than those in the Tau-alone system (Figure 4H), suggesting that the presence of Aβ40 reduces the fluidity of Tau molecules within the condensate. Additionally, the MSD of Aβ40 in the Tau-Aβ40 system is significantly larger than that of Tau (Figure 4H-I), indicating higher dynamics for Aβ40 molecules. Interestingly, we observed that the MSD curves for Tau in both systems are not linear (Figure 4H), while the MSD curve for Aβ40 is linear (Figure 4I) with respect to lag time. This suggests that Tau molecules exhibit sub-diffusive behavior, whereas Aβ40 molecules follow diffusive behavior. We thus revise the calculation of diffusion coefficient for Tau and Aβ40 molecules by fitting to power-law diffusion equation (𝑀𝑆𝐷 = 𝐾 𝜏𝛼) and Stokes-Einstein relation (𝑀𝑆𝐷 = 6𝐷𝜏), respectively. To highlight the importance of the MSD analysis, we have moved the corresponding figures from the Supporting Information to the main text (Figure 4H-I). In addition, we have revised the manuscript to provide details on the MSD calculations.\n“To assess the dynamics of the condensates, we followed previous studies1-2 and extracted the dense phases from the final state of the phase-coexistence simulations and placed them into cubic simulation boxes (Fig S8). The dense phases were then simulated for 5 μs at 310 K in the NVT ensemble. Using the last 1 μs of each trajectory, we calculated the mean square displacement (MSD) for Tau molecules in the Tau-alone and Tau-Aβ40 systems, as well as the MSD for Aβ40 molecules in the Tau-Aβ40 system. The MSD values for Tau molecules display a non-linear behavior with lag time, suggesting sub-diffusive behaviors (Fig 4H). Fitting MSD curves to power-law diffusion equation 𝑀𝑆𝐷 = 𝐾 𝜏𝛼 yields a smaller diffusion exponent for Tau molecules within the Tau-Aβ40 condensate (0.494±0.001) compared to those within Tau-alone condensate (0.500±0.001), indicating that the presence of Aβ40 reduces the fluidity of Tau molecules within the condensate. Furthermore, the MSD of Aβ40 in the Tau-Aβ40 system is significantly larger than that of Tau and follows a diffusive behavior characterized by the Stokes-Einstein relation (𝑀𝑆𝐷 = 6𝐷𝜏) with a diffusive coefficient (D) of 1.696±0.004 nm2/ns (Fig 4I). These observations suggest that Aβ40 molecules remain highly dynamic within the condensate while reducing the dynamics of Tau molecules, thereby providing further support for the Aβ40-induced acceleration of Tau phase transition observed in our experiments.” (Page 8, line 324-341)\nFigure S8. Snapshots at three representative time points from simulations of a preformed Tau condensate (A) and a Tau-Aβ40 condensate (B) in a cubic simulation box.\nFigure 4. H-I, MSD of Tau molecules within Tau alone and Tau-Aβ40 condensates (H) and that of Aβ40 molecules within Tau-Aβ40 condensate.\nReferences:\n1. Sundaravadivelu Devarajan, Dinesh, et al. \"Sequence-dependent material properties of biomolecular condensates and their relation to dilute phase conformations.\" Nature Communications 15.1 (2024): 1912.\n2. Galvanetto, Nicola, et al. \"Material properties of biomolecular condensates emerge from nanoscale dynamics.\" Proceedings of the National Academy of Sciences 122.23 (2025): e2424135122.\n6\n7. Line 317-318: Provide more information as to how the interaction analysis was performed. Was a distance threshold used? If so, what was it? Also, were the contact maps normalized in Fig. 5? Between residues 200-300 the contact maps have some contact values almost equal to 1. Does this mean that those residue pairs were in contact most of the time?\nResponse: We have added a paragraph in the Methods section to describe the interaction analysis details, including the distance threshold and normalization methods.\n\"Interaction analyses were conducted using a bead-to-bead distance cutoff of 0.8 nm. The number of contacts between two molecules was defined as the number of intermolecular bead pairs within this cutoff distance. Reported contact numbers for Tau-Tau and Tau-Aβ pairs were normalized by the total number of Tau molecules in the system, while contact numbers for Aβ-Aβ pairs were normalized by the total number of Aβ molecules.\" (Page 37, line 972-977)\nWe would like to point out that the color bars in Figures 5B and 5D range from 0 to 0.86, rather than from 0 to 1. Therefore, the contact probabilities of all residue pairs are not nearly equal to 1, as might be mistakenly inferred.\nFigure 5.\nB, Inter-molecular contact numbers between each pair of Tau residues in the Tau system. The accumulated contribution of each Tau residue to inter-molecular contacts is shown on the right.\nD, Inter-molecular contact numbers between each Tau residue and each Tau/Aβ40 residue in the Tau-Aβ40 system. The accumulated contribution of each Tau residue to inter-molecular contacts is shown on the right.\nMinor comments:\n1. Figure 6 B/E or C/F: Invert either the intensity or the cell viability so that both quantities vary in the same direction. This will make the comparison of B and C and E and F more straightforward.\nResponse: We thank the reviewer for this helpful suggestion. In Fig. 6C/F, we have now inverted cell viability to cell toxicity, which makes the comparison more straightforward.\n8\n“Consistently, in SH-SY5Y cells, Aβ40-Tau condensates exhibited higher toxicity compared to Tau alone (Fig 6F). Due to the high toxicity of the co-condensates, a slight increase in cell viability was observed as the Tau-Aβ40 ratio increased.” (Page 10, lines 414-417)\nFigure legend updated in Figure 6: “SH-SY5Y cell toxicity under various conditions, including different concentrations of Aβ40, Tau, Tau: Aβ40 at 1:1 and 1:2 molar ratios in the presence of 10% PEG8000. All samples were pre-incubated at 37 °C for 2 hours, prior to a 48-hour incubation with cells. Buffer: 50 mM PB, 150 mM NaCl, pH 7.4. Statistical significance was determined by t-test (**p < 0.01, ***p < 0.001, ****p < 0.0001)” (Page 21, lines 681-685)\n2. Lines 155-156: Which figures correspond to the brightfield microscopy images that is being alluded to?\nResponse: We thank the reviewer for pointing it out. The brightfield microscopy images correspond to Figure S2. We have revised sentence to ensure that readers can directly connect the description to the corresponding figure.\n9\n“These results were corroborated by brightfield microscopy images (Fig S2), which showed increased droplet formation in the presence of Aβ40.” (Page 4, line 158-159)\n3. Fig. 1A: Indicate the sequence of the Tau protein that has been used (and the uniport id). Is it P10636-8?\nResponse: We thank the reviewer for this point. We used the full-length human Tau protein that uniport id is P10636-8. We have now indicated Uniport ID in the figure legend of Fig. 1A and in the Methods section for clarity.\n4. Line 169-170: There is a typo. Instead of “with or with” it should be “with or without”\nResponse: We have corrected the phrase to “with or without” in the revised manuscript.\n5. Fig. 2H: The legend markers should be made larger.\nResponse: We have now increased the size of the legend markers in Fig. 2H in the revised figure to improve readability.\n6. Line 249: Sentence reads odd. Missing word here “formed relatively nanocluster”?\nResponse: Thanks. We have rewritten “Aβ40 at both 5 µM and 25 µM formed small nanoclusters with predominant mass distributions at ~90 kDa and ~84 kDa, respectively” in the revised manuscript.\n7. Line 274: Typo. Instead of “imply that enhancement Aβ40–Tau interactions”, it should be “imply enhancement of Aβ40–Tau interactions.”\nResponse: Thanks. We have corrected it in the revised manuscript.\n8. Fig. 5C: It would be helpful if you could indicate in the caption what the letters ‘H’, ‘P’, ‘C’, ‘O’ represent.\nResponse: The figure caption has been revised accordingly.\n“C, Accumulated contact numbers of each Tau residue type with all residues, i.e., polar (P), charged (C), hydrophobic (H), and other (O) residues, in the Tau alone system.”\n9. Line 333 – 335: “Our calculations indicated that charged residues were the primary drivers of Tau phase separation, followed by polar residues, with hydrophobic residues also making nonnegligible contributions (Fig 5C).” The way this sentence is written, it seems that the accumulated contact numbers for the electrostatic interactions are much larger than the other ones (polar and hydrophobic). However, from the figure the polar contacts are almost equal to the electrostatic ones and closely followed by the hydrophobic interactions. The sentence could perhaps be framed in a different manner.\nResponse: The sentence has been revised accordingly.\n“Our calculations indicated that charged and polar residues were the primary drivers of Tau phase separation, with hydrophobic residues also making nonnegligible contributions (Fig 5C).”\nThe paper is both interesting and timely. The observation of the acceleration of the LLPS of Tau in the presence of Aβ would be of great interest to those study Alzheimer’s disease. The potential crosstalk of Tau/ Aβ in AD is nicely addressed here. There are a number of issues that might be modified to clarify the message in the paper.\nResponse: We sincerely thank the reviewer for their positive evaluation of our work.\nCritics:\n1. Why do the authors only use Aβ40? Why not Aβ42? It seems that these could have been carried out in parallel?\nResponse: We thank the reviewer for raising this important point. In this study, we focused on Aβ40 for two main reasons: 1) Experimental tractability: Aβ42 is substantially more aggregation prone than Aβ40. This presents technical challenges in maintaining monomeric or low molecular weight oligomeric Aβ42 long enough to systematically study its effects on Tau phase separation across the same timescales and conditions. For this reason, we prioritized Aβ40 to establish a clear experimental framework before extending the approach to Aβ42. 2) Physiological abundance: Aβ40 is the most abundant isoform of Aβ in the human brain and cerebrospinal fluid, accounting for ~80–90% of total Aβ peptides, whereas Aβ42 constitutes ~5–10%. Thus, we considered Aβ40 to be a highly relevant Aβ variant starting point for studying Tau–Aβ crosstalk under near-physiological conditions.\n2. Aβ is recruited into Tau condensates in this study. The authors state that Aβ and tau may be co-localized in the brain and cite a couple of papers. Are they proposing that this interaction is a switch to initiate Tau aggregation and propagation as observed in Alzheimer’s disease or do they really expect Aβ to be found in most fibrils? This message might be implicit in the paper but it is not explicit – Tau is involved in over 20 neurodegenerative diseases and it’s cryo-EM structure has been solved for many of these diseases. Is Aβ40 the switch to drive Tau to one of these forms? It is a pity that the study could not have also been carried out using phospho-Tau, but that is a complicated thing to do.\nResponse: We thank the reviewer for raising this important conceptual point. Our intention is not to propose that Aβ40 is universally incorporated into Tau fibrils or that it serves as a singular “switch” to drive Tau into a specific fibril polymorph. Instead, our data suggest that Aβ40 can modulate the phase behavior of Tau, lowering the barrier for Tau to undergo LLPS and promoting its transition toward solid-like aggregates under crowding conditions. This supports a model where Aβ40 acts as a co-factor that facilitates Tau condensation and aggregation, rather than being an obligatory structural component of Tau fibrils.\nBased on current research in this field, Aβ aggregation is thought to occur at early stages of the disease, and ultimately gives way to the formation of tau tangles (Tripathi T, et al. Biochemistry. 2020). The evidence doesn't strongly support that Aβ is found as a major component in most mature tau fibrils. The current evidence more strongly supports Aβ as playing a critical role in dissolving tau aggregation rather than being a persistent component of mature tau aggregates (Wallin C, et al. JACS. 2018). The co-localization observed in brain tissue may reflect this early interaction phase rather than stable co-incorporation into fibrils. We agree with the reviewer that Tau is implicated in more than 20 neurodegenerative diseases, each with distinct fibril polymorphs revealed by cryo-EM. In the context of Alzheimer’s disease, Aβ and Tau pathology are closely linked and co-localization has been observed. Aβ40 may act as a switch that drives Tau into one or multiple fibrillar forms, as observed in different diseases. However, further cryo-EM studies will be necessary to validate these effects on Tau fibril polymorphs, which are beyond the scope of the present study. In the present work, our 11\ndata support an initial phase in which Aβ first solubilizes Tau and subsequently promotes its liquid–solid transition under crowding conditions.\nRegarding phosphorylated Tau, we fully agree with the reviewer that this is a highly relevant and interesting direction, given the central role of phosphorylation in Tau pathology. Due to technical limitations and the complexity of producing site-specifically phosphorylated Tau, we restricted this study to unmodified Tau although phosphorylated Tau is more closely mimic the pathological state.\n3. In a previous paper, the group collaborated with another NMR team, that time using N-labelled Aβ and unlabeled Tau. The conclusion of that paper was that Tau inhibited Aβ aggregation by (i) monomerizing soluble oligomers into monomers with a weak affinity for Tau and (ii) binding to higher affinity Aβ fibrils to prevent further oligomerization by a kind of capping mechanism. Here they suggest that Aβ has the same monomerizing effect on small Tau nanoclusters. This is briefly touched on in the discussion. I think this message could be expanded upon to explain how you can have both of these effects and the role of the differing concentrations of each protein.\nResponse: We thank the reviewer for this thoughtful comment and for drawing attention to our previous work. Indeed, in our earlier NMR study, we reported that Tau interacts with Aβ through two distinct modes: (i) weak interactions with soluble Aβ oligomers that promote their partial disassembly into monomers, and (ii) higher-affinity interactions with Aβ fibrils that limit further elongation through a capping-like mechanism. In the present study, we observed a complementary phenomenon, whereby Aβ₄₀ acts on small, dissolving Tau nanoclusters to maintain a more monomeric state. Together, these findings suggest that Tau–Aβ interactions are inherently bidirectional and context-dependent. Our data indicate a biphasic process: at early stages, transient and weak heterotypic interactions between Tau and Aβ promote mutual solubilization of nascent assemblies, leading to an initial increase in monomeric species for both proteins. Over time, however, these solubilized Tau–Aβ complexes can evolve toward more stable, aggregation-prone states, facilitating Tau phase separation and transition. This temporal shift likely reflects a continuum from dynamic, reversible contacts to more persistent, aggregation-favoring interactions, thus reconciling the dual “monomerizing” and “stabilizing” effects observed across studies. We have now expanded the Discussion to explicitly link these findings.\n“In our previous study, we demonstrated that Tau interacts with Aβ through two distinct modes12: weak interactions with soluble Aβ oligomers, which promote their partial disassembly into monomers, and higher-affinity interactions with Aβ fibrils, which inhibit further aggregation through a capping-like mechanism. In the present study, we observed a complementary phenomenon in which Aβ40 can act on dissolving small Tau nanoclusters and remaining a more monomeric state. Together, these results suggest that Tau–Aβ interactions are inherently bidirectional. Our data reveal a biphasic process: in the early stage, Tau and Aβ mutually solubilize each other's nascent assemblies through transient, weak interactions, leading to an initial increase in monomeric of both proteins. However, over time, these solubilized Tau–Aβ complexes promote Tau phase separation and transition, suggesting that the initial solubilization effect is followed by a phase where heterotypic interactions facilitate rather than inhibit aggregate maturation. This temporal transition may reflect the evolution from dynamic, reversible interactions to more stable, aggregation-prone complexes.” (page 13, line 529-542)\n4. The conditions tested for LLPS of Aβ are very limited. LLPS of Aβ has been shown previously- but under acidic conditions. Do these conditions ever occur under physiological conditions?\nResponse: We thank the reviewer for highlighting this important point. Indeed, prior studies have reported that Aβ peptides can undergo LLPS under acidic conditions, which differs from 12\nthe near-neutral physiological pH of the cellular environment. Our study focused on physiological buffer conditions (pH ~7.4), where we did not observe droplet formation of Aβ40 alone.\n5. What about colour crosstalk of Alexa647 excited by TAMRA excitation ? Could the authors give a bit more information about those experiments to clarify how they were carried out.\nResponse: We thank the reviewer for this helpful comment. We carefully considered the possibility of spectral crosstalk between TAMRA and Alexa647 in our microscopy experiments. To address this: 1) Control measurements were performed with samples containing only Alexa647-labeled Tau and excited with the TAMRA excitation wavelength. These controls showed negligible signal, confirming that direct excitation of Alexa647 under TAMRA illumination is minimal. 2) Sequential imaging was used to acquire TAMRA and Alexa647 channels separately, further minimizing potential bleed-through.\nAs shown in our microscopy setup, TAMRA and Alexa647 were excited and detected in fully separated channels. TAMRA was excited with a 561 nm laser and detected between 570–630 nm, while Alexa647 was excited with a 638 nm laser and detected above 650 nm. The two detection windows were separated by a spectral gap (630–650 nm) to avoid bleed-through.\nWe have now clarified these experimental details in the Methods section and added a statement that color crosstalk was tested and found to be negligible under our conditions.\n6. The NMR data does seem to confirm the mass photometry data, however it gives very limited information on protein structure and interaction. The weak CSPs are unconvincing in terms of which residues really bind Aβ. The only vague information on structure is the Thioflavin data which is hardly conclusive. While the NMR data itself is not to be criticized, the lack of structural data is the weakest point of the paper. It would be very useful to have complementary structural data. Would it be possible to have Cryo-EM data of the aggregates ? Or failing that, some Circular Dichroism or Infra-Red data ?\nResponse: We thank the reviewer for this valuable comment. We agree that additional structural information would strengthen our conclusions. To address this, we have now performed Circular Dichroism (CD) spectroscopy on Tau in the presence and absence of Aβ40. As we showed previously (Wallin C, et al. JACS. 2018), the results indicate that the mixed samples don’t show a significant increase in negative ellipticity around 200 nm compared to 13\nthe added values of Tau alone and Aβ alone. This suggests that CD may not be sufficiently sensitive to detect the formation of soluble nanoclusters.\nFurthermore, distinguishing between Aβ and Tau oligomers in the mixture is challenging by AFM and cryo-EM, as demonstrated in our previous study (Wallin C, et al. JACS. 2018). To assess the overall structural impact, we employed mass photometry (Fig. S6), which reveals that Aβ influences Tau oligomer formation.\nFigure S7. CD spectroscopy measurements of Tau, Aβ, and their mixture. Far-UV CD spectra comparing 10 μM Tau alone (red), 10 μM Aβ alone (blue), Tau alone + Aβ alone signal (magenta) and the Tau-Aβ mixture (black). CD measurements were performed in the far-UV region (190-260 nm) and data are averaged from 3 triplicates and expressed as circular dichroism signal (mdeg). Buffer condition: 50 mM PB, 150 mM NaCl, pH 7.4.\n“However, these structural and global conformational changes were not detectable by CD spectroscopy (Fig. S7).” (Page 7, line 266-267)\n7. From 216 – the authors talk About papers studying the effects on structure by polyanions. However the authors themselves give no structural information on their experiments other than a positive Thioflavin signal. As far as I am aware, the cryo-EM structure of Tau induced by mixing with 2 small beads is unknown. Have the authors any insight on the structure induced by their aggregation experiments ?\nResponse: We thank the reviewer for this insightful comment. We agree that high-resolution structural characterization of the Tau fibrils formed under our experimental conditions would provide valuable information. However, this question is beyond the scope of the present study, which was focused on the interplay between Aβ40 and Tau during phase separation and aggregation.\nThe cryo-EM structure of Tau fibrils induced by glass beads has not yet been resolved, and we therefore cannot make direct structural assignments for the aggregates observed here.\nWe fully agree that this is an important and interesting direction, and we are currently pursuing such structural studies as part of our next project.\n14\n8. The authors carry out toxicity experiments on a cell line. Do the proteins enter the cells in the cell experiments ? Do they remain together ? Have they had a look using their fluorophore labelled proteins ?\nResponse: We thank the reviewer for this insightful question. In additional imaging experiments using fluorophore-labeled proteins, we observed that both Aβ40 and Tau can enter cell, as shown in Fig. S14 A. However, because overall cell condition declined after 24h of protein incubation and imaging through plastic 96-well plates limited resolution, the Tau signal was faint, making it difficult to assess Tau alone and Tau/Aβ40 colocalization in cell. Then we only calculated the total Aβ40 fluorescence of each image in the Aβ40 alone and Aβ40+Tau systems. As shown in Fig. S14B, co-incubation with Tau increased intracellular Aβ40 signal, which parallels the higher toxicity observed for the mixture relative to Aβ40 alone (Fig. 6C). We hypothesize that Aβ40 renders Tau more soluble, promoting Tau to associate with the cell membrane to form oligomers. These oligomers then insert into the lipid bilayer, increase membrane permeability, and in turn facilitate Aβ40 uptake. This is consistent with prior reports that Aβ and Tau can damage cellular membranes and promote internalization. (Fernandez-Perez EJ, et al. Curr Pharm Des. 2016; Flach K, et, al. J Biol Chem. 2012; Jones EM, et, al. Biochemistry. 2012).\n“Then we used fluorophore-labeled proteins to check if these proteins go into cells. We found that co-incubation with Tau increased intracellular Aβ40 signal (Fig.S14A-B), which parallels the higher toxicity observed for the mixture relative to Aβ40 alone. Both Aβ and Tau can damage cellular membranes and promote internalization and Aβ40 renders Tau more soluble, promoting Tau to associate with the cell membrane to form oligomers. These oligomers then insert into the lipid bilayer, increase membrane permeability, and in turn facilitate Aβ40 uptake. Further studies are required to validate this mechanism.” (Page 10, line399-405)\nFigure S14. (A) Representative confocal images of SH-SY5Y cells after 24 h incubation with 15 µM Aβ40, 15 µM Tau, or a mixture of 15 µM Aβ40 and 15 µM Tau. Aβ40 was detected in the TAMRA channel (shown in green) and Tau in the Alexa 647 channel (shown in red). Left column: transmitted light/fluorescence overlay; middle: TAMRA channel; right: Alexa 647 channel. Scale bar, 20 µm. (B) Quantification of total Aβ40 fluorescence intensity in the Aβ40 alone and Aβ40+Tau groups shown in (A).\nEnglish errors:\n78 biomolecule should be biomolecules\nResponse: Corrected it in the revised manuscript (page 2, line 78).\n92 disease-related mutations Tau should be “disease-related tau mutation”\nResponse: Corrected it in the revised manuscript (page 3, line 92-93).\n169/170 with or with should be ”with or without”\nResponse: Rephrased to “with or without” in the revised manuscript (page 4, line 169-170).\n187 remove “the” from we did the long term\nResponse: Removed it in the revised manuscript.\n241 isotopically labelled (labelled missing)\nResponse: Added “labelled” in the revised manuscript (page 6, line 241).\n249 - A word or words are missing from this phrase.\nResponse: We have rewritten “Aβ40 at both 5 µM and 25 µM formed small nanoclusters with predominant mass distributions at ~90 kDa and ~84 kDa” in the revised manuscript (page 6, line 249).\nReviewer #3 (Remarks to the Author):\nI co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nResponse: We thank the reviewer and the co-reviewer for their careful evaluation of our manuscript.\n16"}, {"round": 2, "reviewer_comments": {"reviewer_1": "I would like to thank the authors for addressing the previous comments. There are a few points which need further clarification or justification.\nFrom major comments:\nPoint 2. Fig. S3 (B): Tracking droplet diameters seems like a reasonable method to quantify droplet formation kinetics, assuming that key parameters are held constant (such as protein and crowder concentration). I assume that there is 10 µM Tau and 10% PEG in both the cases. In this specific measurement, it appears that the slope for the diameter growth for Tau was considerably lower compared to Tau+Aß. But after 4 hours, the slope of the Tau only case is considerably larger than the latter. How should one understand this difference?\nPoint 3. How were the errors in the critical point estimates determined? Also figure 4F still does not include error bars for the other points (dense and dilute phase measurement). Without these details, I am not convinced by the 0.1 to 0.3 K error for Tc.\nPoint 7. What is the justification for the 0.8nm cut off? Ideally, the cutoff should be based on residue-residue sigma values and not some arbitrary value. That is, a larger cutoff for pairs that have a larger sigma and smaller ones for pairs with lower sigma.\nForm minor comments:\nPoint 5. The marker size in the legend could be further increased (The scatter points can remain as is).\nPoint 9. The reframed sentence is more or less same as the previous version and does not address the issue. The contact numbers for the different residue types are not that different and are possibly within error bars of each other. This leads me to an additional comment: There are no error bars on any of the bar plots in Fig. 5. I believe that the error bars are essential to support/deny the authors claims that polar and charged residues are the primary drivers of phase separation in their study. I suspect that the error bars would indicate that the contact numbers are within error limits of each other.", "reviewer_2": "The authors have addressed the concerns raised in a satisfactory manner.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Response: We thank the reviewer and the co-reviewer for their careful evaluation of our manuscript.\nPoint 2. Fig. S3 (B): Tracking droplet diameters seems like a reasonable method to quantify droplet formation kinetics, assuming that key parameters are held constant (such as protein and crowder concentration). I assume that there is 10 µM Tau and 10% PEG in both the cases. In this specific measurement, it appears that the slope for the diameter growth for Tau was considerably lower compared to Tau+Aß. But after 4 hours, the slope of the Tau only case is considerably larger than the latter. How should one understand this difference?\nResponse: We thank the reviewer for this insightful comment. As shown in Fig. S3, the kinetics of droplet growth differ between Tau and Tau+Aβ40. During the early stage, Tau+Aβ40 droplets form and grow more rapidly, suggesting that Aβ facilitates condensate formation and initial growth. However, after 4 h, the growth rate of Tau-only droplets becomes higher, resulting in larger droplets at later time points.\nThis crossover likely reflects a shift in the dominant mechanism of droplet maturation. The early acceleration observed in Tau+Aβ40 samples result from rapid recruitment of Tau into numerous small droplets, as supported by microscopy imaging (Fig. S3) and turbidity measurements (Fig. 1C). Further Aβ40 promotes liquid–solid phase transition, as indicated by FRAP analyses (Fig. 1F, Fig. 2D–F, and Fig. S4), and enhance fibril formation, consistent with ThT kinetics (Fig. 2H). Together, these effects lead to depletion of soluble Tau monomers and reduced droplet mobility, thereby slowing further growth after 4 h. In contrast, Tau-only samples display slower condensates formation with more droplet mobility at early stage and undergo more extensive coalescence and Ostwald ripening, resulting in continued droplet enlargement at later time points. We have added the text below to our manuscript (in the end of Page 4)\n“The observed crossover in droplet growth kinetics (Fig S3B) where Tau+Aβ40 droplets initially form and expand faster than Tau-only droplets, but later exhibit slower growth. This reflects an early Aβ40-driven enhancement of condensate nucleation and maturation followed by reduced droplet mobility and Tau monomer depletion due to Aβ-induced liquid–solid transition and fibril formation, whereas Tau-only samples continue to enlarge through prolonged coalescence and Ostwald ripening.”\nPoint 3. How were the errors in the critical point estimates determined? Also figure 4F still does not include error bars for the other points (dense and dilute phase measurement). Without these details, I am not convinced by the 0.1 to 0.3 K error for Tc.\nResponse: We apologize for the insufficient details for our density calculations. We have revised the Methods section to include a detailed description of how the following quantities were determined, including the dense and dilute phase densities, critical temperatures, and their associated error bars. In addition, Figure 4F has been updated to display the corresponding error bars.\n1\n“The densities of the dense and dilute phases were obtained by fitting the density profiles to the following equation, where z₀ denotes the midpoint of the interface between the two phases, and w represents the interfacial width.\n𝜌 +𝜌 𝜌 −𝜌 𝑧−𝑧\n𝑑𝑒𝑛𝑠𝑒 𝑑𝑖𝑙𝑢𝑡𝑒 𝑑𝑒𝑛𝑠𝑒 𝑑𝑖𝑙𝑢𝑡𝑒 0\n𝜌(𝑧) = − ∙tanh[ ]\n2 2 𝑤\nWe then determined the critical temperature by fitting the densities of the dense and dilute phases to the following critical equation, where A is a universal fitting parameter and β is the critical exponent, fixed at 0.365, corresponding to the universality class of the three-dimensional Heisenberg model.\n𝜌 −𝜌 = 𝐴(𝑇−𝑇 )𝛽\n𝑑𝑒𝑛𝑠𝑒 𝑑𝑖𝑙𝑢𝑡𝑒 𝐶\nThe error bars for the densities shown in the phase diagram represent the 95% confidence intervals of the fitted density values for the two phases, while those for the critical temperature correspond to the 95% confidence intervals of the fitted critical temperature values.”\nA-C, Representative simulation snapshots of Tau alone (A), Aβ40 alone (B) and Tau-Aβ40 (C) systems at six different temperatures.\nD-E, Density profiles along the z-axis at eight temperature points for the Tau alone (D) and Tau-Aβ40 (E) systems.\nF, Phase diagrams of the Tau and Tau-Aβ40 systems with critical temperatures obtained by fitting to critical equation.\nG, The saturation concentration of Tau molecules of Tau alone and Tau-Aβ40 systems.\nH-I, MSD of Tau molecules within Tau alone and Tau-Aβ40 condensates (H) and that of Aβ40 molecules within Tau-Aβ40 condensate.\nPoint 7. What is the justification for the 0.8nm cut off? Ideally, the cutoff should be based on residue-residue sigma values and not some arbitrary value. That is, a larger cutoff for pairs that have a larger sigma and smaller ones for pairs with lower sigma.\nResponse: We use a universal cutoff of 0.8 nm for calculating both intra- and intermolecular interactions. This choice is consistent with previous computational studies of protein folding, protein-membrane, and intra-protein interactions using single-bead-per-residue coarse-grained (CG) protein force fields [1-3]. These studies have shown that a cutoff of 0.8 nm reliably captures the effective residue-residue interaction strength in such CG protein models, and that the folding rates are largely insensitive to cutoff values up to 1.0 nm [3]. Therefore, we adopted a cutoff of 0.8 nm in our study. We have added a discussion in the revised Methods section.\n“Interaction analyses were conducted using a bead-to-bead distance cutoff of 0.8 nm. This choice is consistent with previous computational studies of protein folding, protein-membrane, and intra-protein interactions using single-bead-per-residue coarse-grained (CG) protein force fields [1-3]. These studies have shown that a cutoff of 0.8 nm reliably captures the effective residue-residue interaction strength in such CG protein models, and that the folding rates are largely insensitive to cutoff values up to 1.0 nm [3]. Therefore, we adopted a cutoff of 0.8 nm in our study.”\n1. Souza, P. C. T., et al. (2025). GōMartini 3: From large conformational changes in proteins to environmental bias corrections. Nature Communications, 16(1), 4051.\n2. Fuglebakk, E., Reuter, N., & Hinsen, K. (2013). Evaluation of protein elastic network models based on an analysis of collective motions. Journal of Chemical Theory and Computation, 9(12), 5618–5628.\n3. Zhou, H., & Zhou, Y. (2002). Folding rate prediction using total contact distance. Biophysical Journal, 82(1), 458–463.\nForm minor comments:\nPoint 5. The marker size in the legend could be further increased (The scatter points can remain as is).\nResponse: We thank the reviewer for this helpful suggestion. We have increased the marker size further in the Fig. 2H to improve visibility, while keeping the scatter point sizes in the plots unchanged as recommended.\nPoint 9. The reframed sentence is more or less same as the previous version and does not address the issue. The contact numbers for the different residue types are not that different and are possibly within error bars of each other. This leads me to an additional comment: There are no error bars on any of the bar plots in Fig. 5. I believe that the error bars are essential to support/deny the authors claims that polar and charged residues are the primary drivers of phase separation in their study. I suspect that the error bars would indicate that the contact numbers are within error limits of each other.\nResponse: We thank the reviewer for pointing out the missing error bars in Figure 5. We have now added error bars to all bar plots in Figure 5 and Figure S13. The updated figures confirm that the polar and charged residues of Tau make a higher contribution to intermolecular interactions. These results support that polar and charged residues are the primary drivers of phase separation. The Methods section has been revised accordingly.\n“To estimate the error bars for intermolecular and intramolecular contact numbers, we calculated the contact number for four equal segments of the final 1 μs of the trajectory. The error bars correspond to the minimum and maximum contact number values obtained from these four segments.”\nFigure 5. Molecular interactions driving the phase separation of Tau in the absence and presence of Aβ40.\nA, Intra-molecular and inter-molecular contact numbers in the Tau system and Tau-Aβ40 systems.\nB, Inter-molecular contact numbers between each pair of Tau residues in the Tau system. The accumulated contribution of each Tau residue to inter-molecular contacts is shown on the right.\nC, Accumulated contact numbers of each Tau residue type with all residues, i.e., polar (P), charged (C), hydrophobic (H), and other (O) residues, in the Tau alone system.\nD, Inter-molecular contact numbers between each Tau residue and each Tau/Aβ40 residue in the Tau-Aβ40 system. The accumulated contribution of each Tau residue to inter-molecular contacts is shown on the right.\nE, Accumulated contact numbers of each pair of residue types in the Tau-Aβ40 system. Contributions of each Tau residue type in Tau-Tau interaction, each Tau and Aβ40 residue type in Tau-Aβ40 interaction.\nFigure S13. Accumulated inter-Aβ40 contact numbers of each pair of Aβ40 residue types in the Tau-Aβ40 system."}, {"round": 3, "reviewer_comments": {"reviewer_1": "I would like to thank the authors for addressing my comments and answering my previous questions. After going through the responses, I still have some concerns about the contact analysis that has been performed:\nPoint 7. The primary concern about using a universal cutoff distance to determine contacts still holds. The three specific references that the authors have mentioned are not appropriate for the simulations/analysis performed in this study.\n(a) Souza, P. C. T., et al. (2025). GōMartini 3: From large conformational changes in proteins to environmental bias corrections. Nature Communications, 16(1), 4051. This paper involves GōMartini simulations which are different from the CG HPS simulations, not just in terms of the resolution but also the underlying concept. In Gō simulations, there is a template ‘native’ structure and the ‘contacts’ are defined relative to that structure. This is different from the contacts in the current study.\n(b) Fuglebakk, E., Reuter, N., & Hinsen, K. (2013). Evaluation of protein elastic network models based on an analysis of collective motions. Journal of Chemical Theory and Computation, 9(12), 5618–5628. This paper uses elastic network models which are again different from the CG HPS simulations performed in the current study. Also, from a cursory look, the 0.8 nm cutoff that they mention is regarding the bonds in the model, not residue-residue contacts.\n(c) Zhou, H., & Zhou, Y. (2002). Folding rate prediction using total contact distance. Biophysical Journal, 82(1), 458–463. This paper talks about “total contact distance” which is a combination of “contact order” and “long range order”. This has nothing to do with the coarse-grained HPS simulations that have been performed in the current study.\nIn my opinion, the references stated are inaccurate given the coarse-grained simulations that have been performed and therefore the reasoning for the 0.8 nm cutoff does not hold true. Instead, the authors should use residue specific cut-offs as is the norm. As an example, please refer to this paper: “Feito, Alejandro, et al. \"Capturing single-molecule properties does not ensure accurate prediction of biomolecular phase diagrams.\" Molecular Physics 122.21-22 (2024): e2425757.” See Supplementary material section SVI, where a cut-off of 1.2 ij has been used.\nHaving said that, it would also be my recommendation to the authors to go through the references once more to make sure that they are accurate.\nPoint 9.\nFig. 5C, x-labels are missing. Since the contact analysis was erroneous, we cannot make any comment on the contact maps and therefore the subsequent analysis presented in Fig. 5.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "Author reply: We sincerely thank the reviewer for the careful reading of our manuscript/response letter and for the thoughtful, detailed comments. We have addressed the concerns and have recalculated the inter-residue contacts using the residue-specific cutoff schemes suggested by the reviewer. The revised analyses lead to a more solid conclusion that charged residues are the primary drivers of Tau phase separation. Due to the change in cutoff scheme, the three citations related to the global cutoff of 0.8 nm have been removed in the revised manuscript.\nPoint 7. The primary concern about using a universal cutoff distance to determine contacts still holds. The three specific references that the authors have mentioned are not appropriate for the simulations/analysis performed in this study.\n(a) Souza, P. C. T., et al. (2025). GōMartini 3: From large conformational changes in proteins to environmental bias corrections. Nature Communications, 16(1), 4051. This paper involves GōMartini simulations which are different from the CG HPS simulations, not just in terms of the resolution but also the underlying concept. In Gō simulations, there is a template ‘native’ structure and the ‘contacts’ are defined relative to that structure. This is different from the contacts in the current study.\n(b) Fuglebakk, E., Reuter, N., & Hinsen, K. (2013). Evaluation of protein elastic network models based on an analysis of collective motions. Journal of Chemical Theory and Computation, 9(12), 5618–5628. This paper uses elastic network models which are again different from the CG HPS simulations performed in the current study. Also, from a cursory look, the 0.8 nm cutoff that they mention is regarding the bonds in the model, not residue-residue contacts.\n(c) Zhou, H., & Zhou, Y. (2002). Folding rate prediction using total contact distance. Biophysical Journal, 82(1), 458–463. This paper talks about “total contact distance” which is a combination of “contact order” and “long range order”. This has nothing to do with the coarse-grained HPS simulations that have been performed in the current study.\nAuthor reply: We agree with the reviewer that the simulation setups and force fields in the cited references differ from those used in our work. In the original manuscript, our intention in citing these studies was not to suggest that GōMartini, elastic network models, or contact-order analyses are directly comparable to the coarse-grained HPS framework. Rather, we aimed to illustrate that a cutoff distance of 0.8 nm is a commonly used threshold for identifying noncovalent residue-residue contacts in protein systems.\nIn the first reference, a “native contact” was defined when two backbone beads (separated by at least two residues) lies within a cutoff distance of 0.8 nm, and a harmonic elastic bond was added between them to maintain native structures. Similarly, in the second reference, the 0.8 nm threshold was employed to identify residue pairs forming “native contact” when constructing elastic network bonds. In both studies, these “bonds” are not chemical bonds but soft constraints introduced to maintain native structures, and the 0.8 nm cutoff is used as a criterion of a native noncovalent interaction formation.\nIn the third reference, the calculation of total contact distance (defined to predict protein folding rates) requires a residue-contact cutoff (R ) and a residue separation cutoff (l ). By comparing cut cut\nprediction results obtained under a wide range of R values with experimental data, it was found cut\nthat the results were largely insensitive to the residue-contact cutoff selected. This insensitivity lends further support to the suitability of using a cutoff near 0.8 nm as a reasonable indicator of residue-residue contact.\nIn my opinion, the references stated are inaccurate given the coarse-grained simulations that have been performed and therefore the reasoning for the 0.8 nm cutoff does not hold true. Instead, the authors should use residue specific cut-offs as is the norm. As an example, please refer to this paper: “Feito, Alejandro, et al. \"Capturing single-molecule properties does not ensure accurate prediction of biomolecular phase diagrams.\" Molecular Physics 122.21-22 (2024): e2425757.” See Supplementary material section SVI, where a cut-off of 1.2 ij has been used. Having said that, it would also be my recommendation to the authors to go through the references once more to make sure that they are accurate.\nAuthor reply: We sincerely thank the reviewer for this insightful suggestion and for pointing us to the relevant reference. By searching the literature, we found that both global cutoff schemes and residue-specific cutoff schemes have been employed to determine residue-residue contacts/interactions in HPS simulations. Some examples are given below.\nFor the global cutoff approaches, Kang et al. performed CG HPS simulations to investigate the phase behavior of random peptide chains containing arginine and isoleucine, and defined a contact between two chains when the distance between any pair of beads was less than 0.68 nm [1]. Zippo et al. used a one-bead-per-residue HPS model to study the phase separation of wild-type and phosphorylated TDP-43 and employed a global cutoff distance of 1.0 nm to determine inter-residue contacts/interactions [2]. For the residue-specific cutoff approaches, in the study of RNA-mediated phase separation of FUS protein, Tejedor et al. defined interactions using a residue-specific cutoff of 1.2σ [3]. Likewise, in the Molecular Physics (122.21-22 (2024): e2425757) paper, a residue-specific cutoff distance of 1.2σ was also used to characterize residue-residue interactions in hnRNPA1 [4]. The residue-specific cutoff scheme enables precise measurement of residue-residue interactions by accounting for the size of each individual residue. In contrast, the global cutoff scheme offers a rough but easy-to-implement estimation of such interactions by using a universal cutoff value.\nFollowing this reviewer’s suggestion, we have revised our calculations of intra- and intermolecular contact numbers using a residue-specific cutoff of 1.2σ. While the overall interaction patterns in the Tau-alone and Tau-Aβ40 systems remain qualitatively unchanged regardless of the cutoff scheme, the revised calculations highlight the dominant contributions of charged residues in Tau-involved interactions, whose contact numbers are significantly higher than those of other residue types, demonstrating the leading role of electrostatic interactions in Tau and Tau-Aβ40 phase separation. The importance of electrostatic interaction is also clearly seen in residue-residue contact maps (Figure 5B and 5D). We have revised the manuscript accordingly.\nFor Tau-alone system: “To further dissect these contributions, we calculated the accumulated contact numbers of different residue types. Our calculations indicated that charged residues were the primary drivers of Tau phase separation, with hydrophobic and polar residues also making nonnegligible contributions (Fig 5C).”\nFor Tau-Aβ40 system: “High contact numbers were observed for hydrophobic-residue-rich regions of Aβ40, i.e., residues 15-22 ( QKLVFFAE ) and residues 30-40 ( AIIGLMVGGVV ) 15 22 30 40 (Fig 5D & S12). Analysis of accumulated contact numbers for each residue type showed that charged residues of Tau protein dominate Tau-Aβ40 interactions followed by polar and hydrophobic residues, while hydrophobic residues of Aβ40 dominate the Tau-Aβ40 interaction followed by charged residues (Fig 5E). In addition, intermolecular interactions between Aβ40 molecules were relatively weak (Fig S13), suggesting a minimal contribution to phase separation. Together, these results demonstrate that Aβ40 interacts with Tau mainly through an interplay of hydrophobic and electrostatic interactions.”\nFor the summary: “Collectively, our simulations revealed that, Aβ40 engages with Tau through its charged and hydrophobic residues, thereby promoting Tau-Tau intermolecular electrostatic interactions, and, to a lesser extent, hydrophobic and polar interactions. These combined effects ultimately enhance the phase separation of Tau.”\nThe Method section: “The cutoff for two residues forming a contact is calculated by 1.2*(σ+σ)/2, i j in which σ and σ refer to the effective particle size defined as the distance at which the LJ potential i j equals zero [3-4]. The number of contacts between two protein molecules was defined as the number of intermolecular bead pairs within this cutoff distance.”\nFigure 5. Molecular interactions driving the phase separation of Tau in the absence and presence of Aβ40.\nA, Intra-molecular and inter-molecular contact numbers in the Tau system and Tau-Aβ40 systems.\nB, Inter-molecular contact numbers between each pair of Tau residues in the Tau system. The accumulated contribution of each Tau residue to inter-molecular contacts is shown on the right.\nC, Accumulated contact numbers of each Tau residue type with all residues, i.e., charged (C), hydrophobic (H), polar (P), and other (O) residues, in the Tau alone system.\nD, Inter-molecular contact numbers between each Tau residue and each Tau/Aβ40 residue in the Tau-Aβ40 system. The accumulated contribution of each Tau residue to inter-molecular contacts is shown on the right.\nE, Accumulated contact numbers of each pair of residue types in the Tau-Aβ40 system. Contributions of each Tau residue type in Tau-Tau interaction, each Tau and Aβ40 residue type in Tau-Aβ40 interaction.\nFigure S13. Accumulated inter-Aβ40 contact numbers of each pair of Aβ40 residue types in the Tau-Aβ40 system.\nReferences:\n1. Kang W B, Bao L, Zhang K, et al. Multi-scale molecular simulation of random peptide phase separation and its extended-to-compact structure transition driven by hydrophobic interactions[J]. Soft Matter, 2023, 19(41): 7944-7954.\n2. Zippo E, Dormann D, Speck T, et al. Molecular simulations of enzymatic phosphorylation of disordered proteins and their condensates[J]. Nature Communications, 2025, 16(1): 4649.\n3. Tejedor A R, Sanchez-Burgos I, Estevez-Espinosa M, et al. Protein structural transitions critically transform the network connectivity and viscoelasticity of RNA-binding protein condensates but RNA can prevent it[J]. Nature communications, 2022, 13(1): 5717.\n4. Feito A, Sanchez-Burgos I, Rey A, et al. Capturing single-molecule properties does not ensure accurate prediction of biomolecular phase diagrams[J]. Molecular Physics, 2024, 122(21-22): e2425757.\nPoint 9.\nFig. 5C, x-labels are missing. Since the contact analysis was erroneous, we cannot make any comment on the contact maps and therefore the subsequent analysis presented in Fig. 5.\nAuthor reply: The missing x-labels in Fig. 5C have now been added. In addition, the contact analysis has been revised using the residue-specific cutoff scheme, as detailed in our response to the previous question."}, {"round": 4, "reviewer_comments": {"reviewer_1": "I would like to thank the authors for addressing my concerns regarding the usage of universal cutoff distance for the contact analysis. I am happy that the revised analysis strengthens the message of the analysis. After this revision, I am happy to recommend the manuscript for publication.", "reviewer_3": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": ""}]

Decision letter