RNA Selectively Modulates Activity of Virulent Amyloid PSMα3 and Host Defense LL-37 via Phase Separation and Aggregation Dynamics
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eLife Assessment
This study presents valuable findings on the differential effects of RNA on the phase separation, aggregation dynamics, and bioactivity of PSMα3 and LL-37. The authors provide solid evidence from complementary biophysical and cell-based experiments that RNA influences peptide assembly and associated in vitro activities. The study is of interest for understanding interactions between amyloidogenic peptides and nucleic acids, although the physiological significance and some aspects of the mechanistic interpretation would benefit from further clarification.
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Abstract
Amyloids, classically associated with neurodegenerative disease, also play important roles in infection and immunity. Phenol-soluble modulins (PSMs) from Staphylococcus aureus are amyloid-forming virulence peptides that contribute to cytotoxicity, immune modulation, and biofilm stability. PSMα3 forms cross-α amyloid fibrils and shares sequence and α-helical self-assembly features with LL-37, a human host-defence peptide that forms non-amyloid α-helical assemblies. Here, we identify RNA as a context-dependent regulator of their assembly pathways and biological activity. RNA consistently reduces LL-37 cytotoxicity toward human cells without compromising its antibacterial function, suggesting a host-protective effect. In contrast, RNA preserves PSMα3 cytotoxic and antimicrobial activity over time by reshaping its assembly landscape, promoting liquid–liquid phase separation at low concentrations and stabilizing dynamic α-helical intermediates. At higher RNA concentrations, both peptides transition into distinct aggregated states, amorphous for LL-37 and fibrillar for PSMα3, correlating with divergent functional outcomes. The amyloid inhibitor EGCG abolishes the bioactivity of both peptides by redirecting assembly into non-functional aggregates, highlighting that activity depends on supramolecular architecture and reversibility rather than aggregation per se. Together, these findings establish RNA as an environmental regulator of α-helical peptide assemblies and reveal phase transitions as tuneable determinants of peptide function, with implications for microbial virulence, innate immunity, and therapeutic intervention in infectious and protein-aggregation–associated diseases.
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eLife Assessment
This study presents valuable findings on the differential effects of RNA on the phase separation, aggregation dynamics, and bioactivity of PSMα3 and LL-37. The authors provide solid evidence from complementary biophysical and cell-based experiments that RNA influences peptide assembly and associated in vitro activities. The study is of interest for understanding interactions between amyloidogenic peptides and nucleic acids, although the physiological significance and some aspects of the mechanistic interpretation would benefit from further clarification.
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Reviewer #1 (Public review):
Summary:
The manuscript by Rayan et al. aims to elucidate the role of RNA as a context-dependent modulator of liquid-liquid phase separation (LLPS), aggregation, and bioactivity of the amyloidogenic peptides PSMα3 and LL-37, motivated by their structural and functional similarities.
Strengths:
The authors combine extensive biophysical characterization with cell-based assays to investigate how RNA differentially regulates peptide aggregation states and associated cytotoxic and antimicrobial functions.
Weaknesses:
While the study addresses an interesting and timely question with potentially broad implications for host-pathogen interactions and amyloid biology, some aspects of the experimental design and data analysis require further clarification and strengthening.
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Reviewer #2 (Public review):
In this paper, Rayan et al. report that RNA influences cytotoxic activity of the staphylococcal secreted peptide cytolysin PSMalpha3 versus human cells and E. coli by impacting its aggregation. The authors used sophisticated methods of structural analysis and describe the associated liquid-liquid phase separation. They also compare to the influence of RNA on aggregation and activity of LL-37, which shows differences to that on PSMalpha3.
That RNA impacts PSM cytotoxicity when co-incubated in vitro becomes clear. However, I have two major problems with this study:
(1) The premise, as stated in the introduction and elsewhere, that PSMalpha3 amyloids are biologically functional, is highly debatable and has never been conclusively substantiated. The property that matters most for the present study, cytotoxicity, …
Reviewer #2 (Public review):
In this paper, Rayan et al. report that RNA influences cytotoxic activity of the staphylococcal secreted peptide cytolysin PSMalpha3 versus human cells and E. coli by impacting its aggregation. The authors used sophisticated methods of structural analysis and describe the associated liquid-liquid phase separation. They also compare to the influence of RNA on aggregation and activity of LL-37, which shows differences to that on PSMalpha3.
That RNA impacts PSM cytotoxicity when co-incubated in vitro becomes clear. However, I have two major problems with this study:
(1) The premise, as stated in the introduction and elsewhere, that PSMalpha3 amyloids are biologically functional, is highly debatable and has never been conclusively substantiated. The property that matters most for the present study, cytotoxicity, is generally attributed to PSM monomers, not amyloids. The likely erroneous notion that PSM amyloids are the predominant cytotoxic form is derived from an earlier study by the authors that has described a specific amyloid structure of aggregated PSMalpha3. Other authors have later produced evidence that, quite unsurprisingly, indicated that aggregation into amyloids decreases, rather than increases, PSM cytotoxicity. Unfortunately, yet other groups have in the meantime published in-vitro studies on "functional amyloids" by PSMs without critically challenging the concept of PSM amyloid "functionality". Of note, the authors' own data in the present study that show strongly decreased cytotoxicity of PSMalpha3 after prolonged incubation are in agreement with monomer-associated cytotoxicity as they can be easily explained by the removal of biologically active monomers from the solution.
In their revision and in the rebuttal, the authors have further described their concept regarding what they call "functionality" of PSMalpha3 amyloids. They now admit that monomers are the active cytolytic form, like other researchers have stressed, whereas amyloids are not. This represents a considerable difference to earlier papers in which they ascribed functionality, i.e. cytolytic capacity, to PSMalpha3 amyloids, a claim that has raised considerable controversy. Now, they use the term "functional " to describe that PSMalpha3 amyloids, while not cytolytic, can be reversed to a cytolytic monomeric state, calling them a "dynamic reservoir". There is no evidence that such a reservoir is necessary for the cytolytic activity of the monomers to be established; also, there is no evidence that in a biological system, such an amyloid reservoir exists. To continue calling PSMalpha3 amyloids "functional" based on this - considerably changed - concept of the authors appears inappropriate, given the finally admitted absence of cytolytic activity of the PSM amyloids in addition to the continuing complete lack of evidence of any biological relevance of PSM amyloid formation.
(2) That RNA may interfere with PSM aggregation and influence activity is not very surprising, given that PSM attachment to nucleic acids - while not studied in as much detail as here - has been described. Importantly, it does not become clear whether this effect has biologically significant consequences beyond influencing, again not surprisingly, cytotoxicity in vitro. The authors do show in nice microscopic analyses that labeled PSMalpha3 attaches to nuclei when incubated with HeLa cells. However, given that the cells are killed rapidly by membrane perturbation by the applied PSM concentrations, it remains unclear and untested whether the attachment to nucleic acids in dying cells makes any contribution to PSM-induced cell death or has any other biological significance.
Overall, the findings can be explained in a much more straightforward way with the common concept of cytotoxicity being due to monomeric PSMs, and the impact of nucleic acids on cytotoxicity being due to lowering of the concentration of that active form by RNA attachment. Further limiting the significance of the findings, whether this interaction has any biological significance on the physiology or infectivity of the PSM producer remains largely unexplored.
Further remarks:
• Circumstantial evidence based on the "amyloid inhibitor", EGCG: The results with EGCG, which has been shown to have a moderate amyloid-reducing effect on PSMalpha 1 and PSMalpha4, should not be taken as evidence for amyloid-based cytotoxicity. While increased concentrations of EGCG reduced the cytotoxic effect of PSMalpha3, it is not convincingly shown that this is due to a lower concentration of amyloid vs. monomeric PSM.
• It is appreciated that the authors refrain from presenting the unsubstantiated concept of "functional" PSM amyloids in the discussion. However, wording in that direction must also be removed from other parts of the manuscript (e.g. "bioactive fibrillar polymorphs". "The formation of cross-alpha amyloids has been correlated with toxic activity", etc.), generally refraining from uncritically implying that amyloid formation underlies PSM biological activity, and rather discussing that the much more likely explanation of the findings is a lowering of cytolytically active, monomeric PSM concentration.
• Discussion: "PSM alpha3 interaction with nucleic acids within human cells ...supports a comparable mechanism...". Delete. Unsubstantiated.
• The authors should cite papers that have argued against their hypothesis and not only their own manuscripts.
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Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public review):
Summary:
The manuscript by Rayan et al. aims to elucidate the role of RNA as a context-dependent modulator of liquid-liquid phase separation (LLPS), aggregation, and bioactivity of the amyloidogenic peptides PSMα3 and LL-37, motivated by their structural and functional similarities.
Strengths:
The authors combine extensive biophysical characterization with cell-based assays to investigate how RNA differentially regulates peptide aggregation states and associated cytotoxic and antimicrobial functions.
Weaknesses:
While the study addresses an interesting and timely question with potentially broad implications for host-pathogen interactions and amyloid biology, several aspects of the experimental design and data …
Author response:
The following is the authors’ response to the original reviews.
Public Reviews:
Reviewer #1 (Public review):
Summary:
The manuscript by Rayan et al. aims to elucidate the role of RNA as a context-dependent modulator of liquid-liquid phase separation (LLPS), aggregation, and bioactivity of the amyloidogenic peptides PSMα3 and LL-37, motivated by their structural and functional similarities.
Strengths:
The authors combine extensive biophysical characterization with cell-based assays to investigate how RNA differentially regulates peptide aggregation states and associated cytotoxic and antimicrobial functions.
Weaknesses:
While the study addresses an interesting and timely question with potentially broad implications for host-pathogen interactions and amyloid biology, several aspects of the experimental design and data analysis require further clarification and strengthening.
Major Comments:
(1) In Figure 1A, the author showed "stronger binding affinity" based on shifts at lower peptide concentrations, but no quantitative binding parameters (e.g., apparent Kd, fraction bound, or densitometric analysis) are presented. This claim would be better supported by including: (i) A binding curve with quantification of free vs bound RNA band intensities (ii) Replicates and error estimates (mean {plus minus} SD).
We thank the reviewer for this suggestion. To quantitatively support the binding differences observed in Figure 1A, we have now performed densitometric analysis of the EMSA data and included the results in Figure S1. The analysis showed that the Kd for PSMα3 binding to polyAU and polyA RNA is in the same order of magnitude but lower for the polyAU, indicating a stronger binding. A description was added to the results in lines 137-145 of the revised version.
(2) The authors report droplet formation at low RNA (50 ng/µL) but protein aggregation at high RNA (400 ng/µL) through fluorescence microscopy. However, no intermediate RNA concentrations (e.g., 100-300 ng/µL) are tested or discussed, leaving a critical gap in understanding the full phase diagram and transition mechanisms.
Our initial choice of 50 ng/µL (low RNA) and 400 ng/µL (high RNA) was guided by a broader RNA titration performed by turbidity measurements across 0, 10, 20, 50, 100, 200, and 400 ng/µL (Figure S2 in the revised version). In this screen, turbidity increased up to 50 ng/µL and then decreased dose-dependently from 100–400 ng/µL. We interpret this non-monotonic behavior as consistent with a transition from a droplet rich regime (maximal light scattering at intermediate dense-phase volume) toward conditions where assemblies become larger and/or more compact and sediment out of the optical path. This is described in lines 158-161 of the revised version.
Of note, additional intermediate RNA conditions (100 and 200 ng/µL) are included in Figure S14 (of the revised version). While these experiments were performed under the heat-shock perturbation, they nevertheless support the central point that RNA tunes assembly state across intermediate concentrations rather than producing a binary low/high outcome.
Importantly, we agree with the reviewer that a full phase diagram would be the most rigorous way to define the transition mechanism. However, establishing csat and constructing a complete phase diagram would require systematic measurements of dilute-phase concentrations (e.g., centrifugation/quantification or fluorescence calibration), controlled ionic strength titrations, and time-resolved mapping, which is beyond the scope of the present study. We have therefore revised the text to avoid implying that we provide a complete phase diagram. Instead, we frame our results as a qualitative with multi-assay characterization showing that RNA concentration drives a shift from liquid-like condensates (at low RNA) toward solid-like assemblies (at high RNA), with an intermediate regime suggested by the turbidity transition and supported by additional imaging under stress. Finally, to address the “critical gap” concern directly, we add a sentence (lines 239-241) stating that: “Future work will be required to quantitatively define the phase boundaries and delineate the dominant mechanisms, such as sedimentation, dissolution, or coarsening/aging, across intermediate RNA concentrations”.
(3) Additionally, the behaviour of PSMα3 in the absence of RNA under LLPS conditions is not shown. Without protein-only data, it is difficult to assess if droplets are RNA-induced or if protein has a weak baseline LLPS that RNA tunes. The saturation concentration (csat) for PSMα3 phase separation, either in the absence or presence of RNA, should be reported.
In response to the reviewer’s request, we have added Figure 2F, which shows PSMα3 alone in the absence of RNA under the same conditions. PSMα3 does not form droplets in this condition, indicating that condensate formation is RNA-dependent in the tested conditions. This is referred to in the text in lines 190-193 of the revised version. Please see our response about determining the csat in the response to the previous comment.
(4) For a convincing LLPS claim, it is important to show: Quantitative FRAP curves (mobile fraction and half-time of recovery) rather than only microscopy images and qualitative statements.
We have included quantitative FRAP analysis in Figure S4 of the revised version, showing normalized recovery curves along with extracted mobile fractions and half-times of recovery (t₁/₂). These quantitative measurements support the dynamic nature of the PSMα3–RNA. This is referred to in the text in lines 179-184 of the revised version.
(5) The manuscript highly relies on fluorescence microscopy to show colocalization. However, the colocalization is presented in a qualitative manner only. The manuscript would benefit from the inclusion of quantitative metrics (e.g., Pearson's correlation coefficient, Manders' overlap coefficients, or intensity correlation analysis).
In response, we have added quantitative colocalization analysis to the revised manuscript. Specifically, we now report Pearson’s correlation coefficients and Manders’ overlap coefficients for the dual-channel fluorescence microscopy datasets in Figure S5 of the revised version. These metrics provide an objective measure of co-distribution and complement the qualitative imaging.
The analysis supports that at low RNA concentrations (droplet/condensate conditions), PSMα3 and RNA show strong colocalization, consistent with RNA being incorporated within, or closely associated with, the peptide-rich phase. In contrast, at high RNA concentrations, where the assemblies are more solid-like/amyloid-positive, the quantitative coefficients decrease, consistent with reduced overlap and an apparent spatial demixing in which RNA becomes partially excluded from the peptide-rich structures. This is referred to in the text in lines 194-203 of the revised version.
(6) In Figures 3 B and 3C, the contrast between "no AT630 at 30 min, strong at 2 h" (50 ng/μL) and "strong at 30 min" (400 ng/μL) is compelling, but a simple quantification (e.g., mean fluorescence intensity per area) would greatly increase rigor.
We have included quantitative analysis of AmyTracker630 fluorescence intensity in Figure S6 of the revised version, reporting the mean fluorescence intensity per area for the indicated conditions and time points. This quantification supports the qualitative differences observed in Figures 3B and 3C. This is now referred to in the text in lines 233-236 of the revised version.
(7) In Figure S3 ssCD data, if possible, indicate whether the α-helical signal increases with RNA concentration or shows a non-linear dependence, which might link to the LLPS vs solid aggregate regimes.
The ssCD spectra displayed in Figure S7 in the revised version (corresponding to Figure S3 in the original submission) show that the α-helical signature of PSMα3 is markedly enhanced in the presence of RNA compared to peptide alone, as evidenced by increased signal intensity, deeper minima, and more pronounced spectral features characteristic of α-helical structure. Importantly, this enhancement is more pronounced at 400 ng/µL Poly(AU) RNA than at 50 ng/µL, particularly after 2 hours of coincubation, indicating that RNA concentration influences the stabilization of α-helical assemblies. This is now more specifically detailed in the text in lines 258-263 of the revised version.
We note that solid-state CD does not allow direct quantitative deconvolution of secondary structure content (e.g., % helix) in the same manner as solution CD, due to sample anisotropy, scattering, and orientation effects inherent to dried or aggregated films. Consequently, our interpretation is qualitative rather than strictly quantitative. The ssCD data therefore suggest a non-linear dependence on RNA concentration, rather than a simple linear dose–response. This is also expected considering that phase transition, suggested by the other findings, is intrinsically non-linear.
(8) In Figure 5B, FRAP recovery in dying cells may reflect artifactual mobility rather than biological relevance. Additionally, the absence of quantification data limits interpretation; providing recovery curves would clarify relevance.”
We added quantitative FRAP analysis of the effect on PSMα3 within HeLa cells, shown in Figure S8 of the revised version. Compared to PSMα3 assemblies in vitro, nucleolar PSMα3 exhibits slower fluorescence recovery and a reduced mobile fraction. The nucleolus represents a highly crowded, RNA-rich cellular environment, which is expected to impose additional constraints on molecular mobility and likely contributes to the slower recovery kinetics observed in cells. This is now more specifically detailed in the text in lines 324-333 and discussed in lines 597-607 of the revised version.
(9) The narrative conflates cytotoxicity endpoints (membrane damage, PI staining, aggregates) with localization data (nucleolar foci), creating ambiguity about whether nucleolar targeting drives toxicity or is a consequence of cell death. Separating toxicity assessment from localization analysis, or clearly demonstrating that nucleolar accumulation precedes cytotoxicity, would resolve this ambiguity.
We thank the reviewer for raising this important point. We agree that, in the current dataset, cytotoxicity readouts (membrane damage, PI staining, aggregate formation) and subcellular localization (nucleolar accumulation) are observed in close temporal proximity, which limits our ability to unambiguously assign causality. In the experiments presented here, PSMα3 was applied at concentrations known to induce rapid membrane disruption and cytotoxicity in HeLa cells. Under these conditions, PSMα3 accumulates on cellular membranes and penetrates into the cell and nucleus on very short timescales (seconds to minutes), likely preceding the temporal resolution accessible by standard live-cell fluorescence microscopy. As a result, nucleolar accumulation and cytotoxic endpoints are detected essentially concurrently, precluding a definitive determination of whether nucleolar association actively drives toxicity or occurs as a downstream consequence of membrane permeabilization and cell damage.
We therefore emphasize that, in this study, nucleolar localization is presented as a phenomenological observation consistent with RNA-rich compartment association, rather than as a demonstrated causal mechanism of cytotoxicity. We have revised the Discussion (lines 597-607) to clarify this distinction and to avoid implying that nucleolar targeting is the primary driver of cell death.
We agree that resolving this ambiguity would require systematic time-resolved and concentration-dependent experiments, including analysis at sub-toxic PSMα3 concentrations below the membrane-disruptive threshold, combined with orthogonal imaging approaches. Such experiments are planned for future work but are beyond the scope of the present study.
(10) In Figure 8, to strengthen the LLPS assignment for LL-37, additional evidence, such as FRAP analysis or observation of droplet fusion events, would be valuable. This is particularly relevant given that the heat shock conditions (65 °C for 15 minutes) could potentially induce partial denaturation or nonspecific coacervation.
In response to this comment, we have added FRAP analysis of LL-37 assemblies in the revised manuscript (Figure S12), including representative images and corresponding fluorescence recovery curves. The FRAP measurements show minimal fluorescence recovery over the acquisition window, indicating that the LL-37–RNA assemblies formed under these conditions are largely immobile and solid-like, rather than liquid-like droplets. This is now referred to in the text in lines 458-462 of the revised version.
Reviewer #2 (Public review):
In this paper, Rayan et al. report that RNA influences cytotoxic activity of the staphylococcal secreted peptide cytolysin PSMalpha3 versus human cells and E. coli by impacting its aggregation. The authors used sophisticated methods of structural analysis and described the associated liquid-liquid phase separation. They also compare the influence of RNA on the aggregation and activity of LL-37, which shows differences from that on PSMalpha3.
Strengths:
That RNA impacts PSM cytotoxicity when co-incubated in vitro becomes clear.
Weaknesses:
I have two major and fundamental problems with this study:
(1) The premise, as stated in the introduction and elsewhere, that PSMalpha3 amyloids are biologically functional, is highly debatable and has never been conclusively substantiated. The property that matters most for the present study, cytotoxicity, is generally attributed to PSM monomers, not amyloids. The likely erroneous notion that PSM amyloids are the predominant cytotoxic form is derived from an earlier study by the authors that has described a specific amyloid structure of aggregated PSMalpha3. Other authors have later produced evidence that, quite unsurprisingly, indicated that aggregation into amyloids decreases, rather than increases, PSM cytotoxicity. Unfortunately, yet other groups have, in the meantime, published in-vitro studies on "functional amyloids" by PSMs without critically challenging the concept of PSM amyloid "functionality". Of note, the authors' own data in the present study, which show strongly decreased cytotoxicity of PSMalpha3 after prolonged incubation, are in agreement with monomer-associated cytotoxicity as they can be easily explained by the removal of biologically active monomers from the solution.
We thank the reviewer for this important critique and agree that direct cytotoxicity is most plausibly mediated by soluble PSM species, while extensive fibrillation generally reduces toxicity by depleting these forms, a conclusion supported by our data and by other studies (e.g., Zheng et al 2018 and Yao et al 2019). We do not propose mature amyloid fibrils as the primary toxic entities. Rather, we use the term functional amyloid in a regulatory sense, consistent with other biological amyloids whose fibrillar states modulate activity (e.g., hormone storage amyloids or RNA-binding proteins).
In line with emerging findings, we interpret PSMα3 toxicity as arising from a dynamic assembly process rather than from a single static molecular species. We previously showed that PSMα3 forms cross-α fibrils that are thermodynamically and mechanically less stable than cross-β amyloids and readily disassemble upon heat stress, fully restoring cytotoxic activity (Rayan et al., 2023). This behavior contrasts with PSMα1, which forms highly stable cross-β fibrils that do not recover activity after heat shock, suggesting that the limited thermostability of PSMα3 is an evolved feature enabling reversible switching between inactive (stored) and active states.
Consistent with this view, both PSMα1 and PSMα3 are cytotoxic in their soluble states, yet mutants unable to fibrillate lose activity, indicating that fibrillation is required but not itself the toxic end state (Tayeb-Fligelman et al., 2017, 2020; Malishev et al., 2018). Our other studies further show that cytotoxicity toward human cells correlates with inherent or lipid-induced α-helical assemblies, rather than with inert β-sheet amyloids (RagonisBachar et al., 2022, 2026; Salinas 2020, Bücker 2022). Together, these findings support a model in which membrane-associated, dynamic α-helical assembly, which requires continuous exchange between soluble species and growing fibrils, drives membrane disruption, potentially through lipid recruitment or extraction, analogous to mechanisms proposed for human amyloids such as islet amyloid polypeptide (Sparr et al., 2004).
In the present study, we further show that RNA reshapes this dynamic landscape: while PSMα3 alone progressively loses activity upon incubation, co-incubation with RNA preserves cytotoxicity by stabilizing bioactive polymorphs and condensate-like states, whereas high RNA concentrations promote solid aggregation but nevertheless preserve activity. Thus, aggregation is neither inherently functional nor toxic, but context dependent and environmentally regulated. Taken together, our data support a model in which PSMα3 amyloids act as a dynamic reservoir, enabling S. aureus to tune virulence by reversibly shifting between dormant and active states in response to environmental cues such as heat or RNA.
This is now discussed in lines 56-76 and 523-553 of the revised version.
(2) That RNA may interfere with PSM aggregation and influence activity is not very surprising, given that PSM attachment to nucleic acids - while not studied in as much detail as here - has been described. Importantly, it does not become clear whether this effect has biologically significant consequences beyond influencing, again not surprisingly, cytotoxicity in vitro. The authors do show in nice microscopic analyses that labeled PSMalpha3 attaches to nuclei when incubated with HeLa cells. However, given that the cells are killed rapidly by membrane perturbation by the applied PSM concentrations, it remains unclear and untested whether the attachment to nucleic acids in dying cells makes any contribution to PSM-induced cell death or has any other biological significance.
We thank the reviewer for this important point and agree that PSM–nucleic acid interactions are not unexpected and that our data do not support a direct intracellular role for RNA binding in mediating cytotoxicity. Accordingly, we do not propose nucleolar or nuclear association of PSMα3 as a causal mechanism of cell death. At the concentrations used, PSMα3 induces rapid membrane disruption, and nucleic acid association is observed along with membrane attachment, precluding conclusions about intracellular function. This limitation is now explicitly clarified in the revised manuscript. The biological significance of our findings lies instead in extracellular and environmental contexts, where PSMα3 encounters abundant nucleic acids, such as RNA or DNA released from damaged host cells or present in biofilms as now addressed in lines 622631. Our data show that RNA modulates PSMα3 aggregation trajectories, shifting the balance between liquid-like condensates and solid aggregates, and thereby regulates the persistence and timing of cytotoxic activity. In this framework, RNA acts as a context dependent regulator of virulence, rather than as an intracellular cytotoxic cofactor, an aspect which would be studied in depth in future work. This is now addressed in the text in lines 597-607 of the revised version.
Reviewer #3 (Public review):
Summary:
The manuscript by Rayan et al. aims to investigate the role of RNA in modulating both virulent amyloid and host-defense peptides, with the objective of understanding their self-assembly mechanisms, morphological features, and aggregation pathways.
Strengths:
The overall content is well-structured with a logical flow of ideas that effectively conveys the research objectives.
Weaknesses:
(1) Figure 2 displays representative FRAP images demonstrating fluorescence recovery within seconds. To gain a more comprehensive understanding of how recovery after photobleaching varies under different conditions, it is recommended to supplement these images with corresponding quantitative fluorescence recovery curves for analysis.
In response to this comment, we have supplemented the representative FRAP images with quantitative fluorescence recovery curves, reporting normalized recovery kinetics for the indicated conditions. These data are now provided in Figure S4 of the revised manuscript, allowing direct comparison of recovery behavior across conditions (shown by microscopy in Figure 2). In addition, we have included quantitative FRAP analyses for the cellular imaging shown in Figure 5 (presented in Figure S8) and for LL-37 assemblies formed under heat-shock conditions (Figure S12). Together, these additions provide a quantitative framework for interpreting the FRAP results and strengthen the distinction between liquid-like and solid-like assembly states.
(2) Ostwald ripening typically leads to the shrinkage or even disappearance of smaller droplets, accompanied by the further growth of large droplets. However, the droplet size in Figure 2D decreases significantly after 2 h of incubation. This observation prompts the question, what is the driving force underlying RNA-regulated phase separation and phase transition?”
We thank the reviewer for this observation. Across multiple samples, we consistently observe a coexistence of small droplets and larger aggregates, rather than systematic growth of larger droplets at the expense of smaller ones or a uniform decrease in droplet size. In addition, the timescales examined do not allow us to reliably assess whether diffusion-driven droplet coalescence is fast enough to draw firm conclusions about droplet size evolution. This is now addressed in the text in lines 181-184 of the revised version.
A decrease in droplet size over time is nevertheless observed in some instances and is more consistent with a time-dependent conversion of initially liquid-like condensates into more solid-like assemblies, which would reduce molecular mobility and suppress droplet coalescence. In parallel, progressive fibril formation may act as a sink for soluble peptide, leading to partial dissolution or shrinkage of less mature condensates. Together, these observations are consistent with a non-equilibrium aging process, in which RNAregulated assemblies evolve from dynamic condensates toward more solid structures rather than following equilibrium Ostwald ripening.
(3) The manuscript aims to study the role of RNA in modulating PSMα3 aggregation by using solution-state NMR to obtain residue-specific structural information. The current NMR data, as described in the method and figure captions, were recorded in the absence of RNA. Whether RNA binding induces conformational changes of PSMα3, and how these changes alter the NMR spectra? Also, the sequential NOE walk between neighboring residues can be annotated on the spectrum for clarity.
The solution-state NMR experiments were performed specifically to characterize the potential binding of EGCG to PSMα3. Due to the strong tendency of PSMα3 to undergo rapid aggregation and line broadening upon RNA addition, solution state NMR spectra in the presence of RNA could not be obtained at sufficient quality for residue-specific analysis. As suggested, we have updated and annotated the sequential NOE walk between neighboring residues on the relevant NOESY spectra to improve clarity.
(4) The authors claim that LL-37 shares functional, sequence, and structural similarities with PSMα3. However, no droplet formation was observed of LL-37 in the presence of RNA only. The authors then applied thermal stress to induce phase separation of LL-37. What are the main factors contributing to the different phase behaviors exhibited by LL37 and PSMα3? What are the differences in the conformation of amyloid aggregates and the kinetics of aggregation between the condensation-induced aggregation in the presence of RNA and the conventional nucleation-elongation process in the absence of RNA for these two proteins?
We appreciate this important question and have clarified both the basis of the comparison and the origin of the divergent phase behaviors of LL-37 and PSMα3. While PSMα3 and LL-37 share key properties as short, cationic, amphipathic α-helical peptides that self-assemble and interact with nucleic acids, they differ fundamentally in their assembly architectures. PSMα3 is an amyloidogenic peptide that forms cross-α amyloid fibrils, in which α-helices stack perpendicular to the fibril axis. In contrast, LL-37 can form fibrillar or sheet-like assemblies (observed in cryo grids), but these lack canonical amyloid features without clear cross-α or cross-β amyloid order, as so far observed by crystal structures. This is now clarified in different parts of the text of the revised version. Thus, the comparison between the two peptides is functional and physicochemical rather than implying identical amyloid mechanisms. These structural differences likely underlie their distinct phase behaviors.
Because LL-37 does not follow a classical amyloid nucleation–elongation pathway, and high-resolution structural information (e.g., cryo-EM) is currently lacking, partly due to its sheet-like, non-twisted morphology (unpublished results), it is not possible to directly compare aggregation kinetics or nucleation mechanisms between LL-37 and PSMα3. It is possible that amyloidogenic systems such as PSMα3 exhibit greater flexibility in prefibrillar and fibrillar polymorphism, enabling RNA-regulated phase behavior, whereas non amyloid assemblies such as LL-37 are more prone to stress-induced solid aggregation. We note that this interpretation is necessarily tentative and does not imply a general rule, but rather reflects differences evident in the present system.
Recommendations for the authors:
Reviewer #1 (Recommendations for the authors):
Minor Comments:
(1) In the abstract, replacing the word "overriding" with "counteracting" may provide a scientifically neutral tone.
In the course of revision, the abstract was substantially rewritten to more precisely convey the mechanistic framework and key conclusions of the study. As part of this rewrite, the term "overriding" was removed and the language throughout was revised to adopt a more scientifically neutral tone, consistent with the reviewer's suggestion.
(2) In abstract, the final sentence is ambitious but heavy. It may benefit from being split into two shorter sentences, for example:
"These findings establish RNA as a potent, context-dependent modulator of both virulent amyloids and host-defense peptides. They further reveal phase transitions as tunable regulators of peptide activity and potential therapeutic targets across infectious and neurodegenerative diseases."
As part of the broader abstract revision, the final sentence was restructured and the abstract as a whole was rewritten to improve clarity and readability, in the spirit of the reviewer's recommendation.
(3) In the Introduction section,
The phenol-soluble modulins (PSMs) produced by Staphylococci contain amyloid-forming short peptides which play multiple functional roles...", consider "Staphylococcal phenolsoluble modulins (PSMs) are short, amyloidogenic peptides that perform multiple roles central to pathogenesis....
In accordance with the suggestion, the sentence has been revised.
(4) To improve narrative flow in the final paragraph of the Introduction, a short bridging sentence could be added, such as:
"Given these nucleic acid interactions, we next examined whether RNA can drive phase separation or structural reorganization of these amyloidogenic peptides."
We thank the reviewer for this helpful suggestion. It provided an opportunity to clarify an important distinction between the two peptides studied. While LL-37 can self-assemble into higher-order α-helical structures, it is not amyloidogenic, in contrast to PSMα3. We therefore revised the bridging sentence in the final paragraph of the Introduction to read: “Given their shared cationic, amphipathic α-helical character, but distinct amyloidogenic properties, we sought to examine whether RNA differentially influences the assembly landscapes and bioactivity of PSMα3 and LL-37. “
(5) The rationale for selecting Poly(A) and Poly(AU) would benefit from further clarification. It would be helpful to specify whether these RNAs are intended to model particular host or bacterial RNA species, such as AU-rich elements, rRNA-like sequences, or mRNA-like contexts.
Poly(A) and Poly(AU) RNAs were selected as simplified, well-defined model RNAs to probe general peptide–RNA interactions in an unbiased manner, as no prior information was available regarding whether such interactions occur or which specific RNA species might be involved. This rationale is now clarified in the revised text (lines 128–131).
These RNAs are not intended to represent a single biological transcript, but rather generic RNA features relevant to both host and bacterial contexts, including single-stranded homopolymeric regions and AU-rich elements commonly found in mRNAs and stress srelated RNAs. The use of such reductionist RNA models to study RNA–protein interactions, phase behavior, and RNA-modulated aggregation is well established. We nevertheless agree that RNA sequence and structure may influence peptide assembly and activity, and future studies will address sequence-specific and biologically derived RNAs.
(6) In Figure 1A, essential EMSA controls- RNA alone, peptide alone, and a nonspecific peptide or PSMα3 should be included to distinguish specific complexes from artifacts, even if presented in the supplementary information. In addition, a competition assay using unlabeled RNA would help confirm binding specificity and rule out predominantly nonspecific electrostatic interactions; these data could also be reported in the supplementary figures.
An RNA-alone control is already included in Figure 1A of the revised version. The first lane (“0 µM”) shows free Poly(A) or Poly(AU) RNA in the absence of peptide and serves as the negative control against which PSMα3-induced mobility shifts are evaluated. A peptide-alone EMSA cannot be performed, as PSMα3 is highly cationic and does not migrate into the gel in the absence of RNA; moreover, EMSA in this format reports on RNA mobility rather than peptide migration.
With respect to binding specificity, we compared Poly(A) and Poly(AU) RNAs and observed distinct binding behaviors, which would not be expected for purely nonspecific electrostatic interactions. In addition, the extracted Hill coefficients (>1) are consistent with cooperative binding, further arguing against simple charge-driven association. Finally, the RNA-dependent association of PSMα3 is independently supported by fluorescence microscopy and quantitative colocalization analyses, which corroborate the EMSA results. Together, these orthogonal approaches support the relevance of the observed peptide–RNA interactions.
(7) In Figure 1B, there is a time mismatch between EMSA (30 minutes) and TEM (2 hours). If aggregation progresses over time, the EMSA pattern at 2 hours may differ. This point could be acknowledged or experimentally addressed, as RNA-peptide assemblies may evolve from liquid-like condensates to more solid aggregates.
The EMSA and TEM experiments were intentionally performed at different time points to capture distinct stages of the PSMα3–RNA assembly process. The EMSA assay (30 minutes) was designed to probe early RNA–peptide complex formation and binding interactions, before extensive higher-order aggregation occurs. At this stage, we aim to detect mobility shifts reflecting complex formation rather than mature assemblies. In contrast, TEM was performed after 2 hours to visualize later-stage structural outcomes, including fibrillation and morphological reorganization. As aggregation progresses over time, the assemblies evolve from early RNA–peptide complexes into more ordered fibrillar structures, which are best assessed by electron microscopy at later time points. To improve clarity and avoid potential confusion, we have streamlined Figure 1 to focus on the EMSA data, which specifically addresses early binding events. The TEM data were removed from Figure 1 and are now presented in Figure 3, where later-stage structural transitions and fibrillation are shown more comprehensively and in the appropriate mechanistic context.
(8) In Figure 1B, if feasible, complementing TEM with a confirmatory fibril assay (e.g., ThT kinetics) under the same conditions would strengthen the conclusion that the morphology difference is robust, but it is not mandatory.
We attempted to perform ThT fibrillation kinetics under the same RNA containing conditions; however, these assays were not informative for this system. PSMα3 aggregates extremely rapidly, producing an immediate and steep increase in ThT fluorescence (Fig. S9 in the revised version), which prevents reliable resolution of RNA dependent differences in aggregation kinetics or lag phases. In addition, Poly(AU) RNA interferes with ThT readout through electrostatic interactions between the negatively charged RNA and the cationic dye, as well as through RNA-induced changes in fibril morphology, both of which complicate quantitative interpretation of fluorescence kinetics. Based on these technical constraints and prior experience with RNA–amyloid systems, ThT kinetics under identical RNA conditions would not provide a robust or interpretable confirmation of the morphological differences observed by TEM.
(9) In Figure 1B, PSMα3 alone control is missing in TEM images.
A TEM image of PSMα3 alone is included in Figure 3, where we systematically present fibrillation outcomes across different RNA concentrations alongside the peptide-only control. Figure 1 was streamlined to focus on early RNA– peptide interactions assessed by EMSA, whereas Figure 3 provides a comprehensive TEM analysis of later-stage structural outcomes. This organization was chosen to clearly separate early binding events from subsequent assembly transitions and to avoid redundant presentation of TEM images under similar conditions.
(10) Although it is experimentally practical to focus on Poly(AU), the justification is very one-sided. The Poly(A) condition, which yields amorphous aggregates, may be equally informative for understanding toxicity, LLPS, or nonfibrillar states and could be discussed more explicitly.
We agree that Poly(A)-induced amorphous aggregation is informative for understanding non fibrillar assembly states. However, the primary aim of this study was to dissect RNA-dependent regulation of fibrillar assembly and phase behavior, which is most clearly captured using Poly(AU). Poly(A) was therefore included as a comparative condition rather than as a focus for detailed mechanistic analysis. A more systematic comparison of different RNA classes and their effects on non fibrillar states and toxicity is an important direction for future work but is beyond the scope of the present study.
(11) To improve readability of the manuscript, the main text should follow the order of the figure panels (e.g., A, B, C, D, and E) and numbers (Figure 1, 2...) sequentially, so that readers can easily align with the corresponding images.
We have revised the manuscript to improve alignment between the main text and the figures, adjusting panel ordering and numbering where appropriate so that the text now follows the figure panels and figure numbers more sequentially. These changes were made to enhance readability while maintaining a logical visual flow within the figures.
(12) In the result section of Figure 2, the analogy to Ddx4-like systems is a helpful concept, but should be clearly framed as an analogy, not evidence. It would be more accurate to say that the behavior is "conceptually similar to" those systems, while noting that the molecular context is significantly different.
We have revised the text to explicitly frame the comparison to Ddx4-like systems as a conceptual analogy rather than evidence: lines 158-161 in the revised version.
(13) In Figure 4, inclusion of positive and negative controls to validate assay performance (e.g., untreated bacteria or HeLa cells, lysis buffer, media alone) would strengthen confidence in the bioactivity measurements.
We wish to clarify that appropriate positive and negative controls were included in all bioactivity assays and were used to normalize the data presented in Figure 4. For the HeLa cytotoxicity assay (LDH), untreated cells were used to determine spontaneous LDH release (negative control), and cells treated with the manufacturer supplied lysis buffer were used to determine maximum LDH release (positive control). The percent cytotoxicity shown in Figure 4B was calculated relative to these internal controls, as described in the Methods. For the antibacterial assay (PrestoBlue), wells containing E. coli without peptide served as the positive control for 100% viability, while wells containing sterile LB medium alone were used as blanks. Viability values in Figure 4A were normalized to these controls. We have ensured that the Methods section explicitly describes these controls to reinforce confidence in the bioactivity measurements.
(14) To enhance clarity, consider presenting the RNA concentration and time-dependent effects on PSMα3 bioactivity in a comparison table within the main text or as a supplementary figure.
We appreciate this suggestion and carefully considered presenting the data in tabular form. However, we found that graphical representation more effectively conveys the trends, transitions, and comparative patterns between conditions. A table would not adequately capture these relationships.
Reviewer #2 (Recommendations for the authors):
Further remarks:
(1) Circumstantial evidence based on the "amyloid inhibitor", EGCG: The results with EGCG, which has been shown to have a moderate amyloid-reducing effect on PSMalpha 1 and PSMalpha4, should not be taken as evidence for amyloid-based cytotoxicity. While increased concentrations of EGCG reduced the cytotoxic effect of PSMalpha3, it is not convincingly shown that this is due to a lower concentration of amyloid vs. monomeric PSM.
We agree that the effects of EGCG should not be interpreted as evidence for amyloid fibrils being the cytotoxic species. Our data instead support a mechanism in which EGCG primarily targets soluble PSMα3, thereby redirecting its assembly pathway and depleting bioactive species. Specifically, solution-state NMR (Fig. 7) shows that EGCG binds defined residues of monomeric PSMα3, consistent with sequestration of soluble peptide rather than selective inhibition of fibrils. Complementary light and electron microscopy, together with kinetic measurements, indicate that EGCG does not simply stabilize monomers but instead diverts PSMα3 into amorphous, non-functional aggregates, as visualized by TEM (Fig. 6B) and reflected in altered ThT responses (Fig. S9). Importantly, these EGCG-induced aggregates are non-cytotoxic (Fig. 6A/C) and fail to associate with membranes or cells, in contrast to untreated PSMα3, which forms membrane-associated assemblies and induces disruption (newly added Movies S1-S2). Thus, EGCG potentially reduces cytotoxicity by remodeling the aggregation landscape and depleting active soluble species, rather than by selectively inhibiting specific fibril formation. This clarification is now added to the Discussion in lines 554-564 of the revised version.
(2) It is appreciated that the authors refrain from presenting the unsubstantiated concept of "functional" PSM amyloids in the discussion. However, wording in that direction must also be removed from other parts of the manuscript (e.g. "bioactive fibrillar polymorphs". "The formation of cross-alpha amyloids has been correlated with toxic activity", etc.), generally refraining from uncritically implying that amyloid formation underlies PSM biological activity, and rather discussing that the much more likely explanation of the findings is a lowering of cytolytically active, monomeric PSM concentration.
As detailed in our response to Major Comment #1, we agree that uncritical language implying that amyloid fibrils themselves are the cytotoxic species should be avoided. Accordingly, we have revised the manuscript to consistently frame amyloid formation in regulatory terms. Aggregation, depending on context, modulates activity by altering the availability, persistence, and assembly pathways of these species. Distinct aggregation states are therefore presented as correlated with, but not equivalent to, cytotoxic activity, and as components of a dynamic assembly landscape rather than as direct toxic entities.
(3) Discussion: "PSM alpha3 interaction with nucleic acids within human cells ...supports a comparable mechanism...". Please delete this as it is unsubstantiated.
We agree that the original phrasing overstated the evidence. The sentence was removed and the Discussion was revised to clearly frame nucleolar accumulation as a phenomenological observation reflecting PSMα3's intrinsic nucleic acid–binding capacity, rather than as evidence for a comparable intracellular mechanism. Specifically, the revised Discussion (lines 597–607) states that nucleolar localization is "unlikely to represent a distinct intracellular toxic mechanism" and instead "reflects binding competence within RNA-rich compartments following cellular entry." The biological relevance of this interaction, particularly at sub-cytotoxic concentrations, is noted as an open question requiring further investigation.
(4) The authors should also cite papers that have argued against their central hypothesis of "functional" PSM amyloids.
We thank the reviewer for this suggestion. Accordingly, we have revised the manuscript to explicitly cite and discuss studies that argue against amyloid fibrils as the primary cytotoxic species, and that instead attribute PSM cytotoxicity to soluble or membrane-associated forms. These perspectives are now incorporated in the Discussion to provide a balanced view of the field and to clarify how our findings align with, and differ from, existing models of PSM activity.
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eLife Assessment
This study investigates how RNA molecules modulate phase separation, aggregation, and cytotoxicity of the staphylococcal virulent peptide PSMα3 and the human host‑defence peptide LL‑37 using an array of biophysical and cell‑based assays. If validated, these findings would be important, as they suggest that nucleic acids can tune the material state and bioactivity of amyloids, with implications for host-pathogen interactions and for the design of therapeutics that target phase behaviour. However, the evidence is incomplete: many key claims rest on qualitative imaging and contested assumptions about "functional" amyloids, and the absence of quantitative binding data, phase diagrams, and appropriate controls limits confidence in the conclusions.
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Reviewer #1 (Public review):
Summary:
The manuscript by Rayan et al. aims to elucidate the role of RNA as a context-dependent modulator of liquid-liquid phase separation (LLPS), aggregation, and bioactivity of the amyloidogenic peptides PSMα3 and LL-37, motivated by their structural and functional similarities.
Strengths:
The authors combine extensive biophysical characterization with cell-based assays to investigate how RNA differentially regulates peptide aggregation states and associated cytotoxic and antimicrobial functions.
Weaknesses:
While the study addresses an interesting and timely question with potentially broad implications for host-pathogen interactions and amyloid biology, several aspects of the experimental design and data analysis require further clarification and strengthening.
Major Comments:
(1) In Figure 1A, the …
Reviewer #1 (Public review):
Summary:
The manuscript by Rayan et al. aims to elucidate the role of RNA as a context-dependent modulator of liquid-liquid phase separation (LLPS), aggregation, and bioactivity of the amyloidogenic peptides PSMα3 and LL-37, motivated by their structural and functional similarities.
Strengths:
The authors combine extensive biophysical characterization with cell-based assays to investigate how RNA differentially regulates peptide aggregation states and associated cytotoxic and antimicrobial functions.
Weaknesses:
While the study addresses an interesting and timely question with potentially broad implications for host-pathogen interactions and amyloid biology, several aspects of the experimental design and data analysis require further clarification and strengthening.
Major Comments:
(1) In Figure 1A, the author showed "stronger binding affinity" based on shifts at lower peptide concentrations, but no quantitative binding parameters (e.g., apparent Kd, fraction bound, or densitometric analysis) are presented. This claim would be better supported by including: (i) A binding curve with quantification of free vs bound RNA band intensities (ii) Replicates and error estimates (mean {plus minus} SD).
(2) The authors report droplet formation at low RNA (50 ng/µL) but protein aggregation at high RNA (400 ng/µL) through fluorescence microscopy. However, no intermediate RNA concentrations (e.g., 100-300 ng/µL) are tested or discussed, leaving a critical gap in understanding the full phase diagram and transition mechanisms. Additionally, the behaviour of PSMα3 in the absence of RNA under LLPS conditions is not shown. Without protein-only data, it is difficult to assess if droplets are RNA-induced or if protein has a weak baseline LLPS that RNA tunes. The saturation concentration (csat) for PSMα3 phase separation, either in the absence or presence of RNA, should be reported.
(3) For a convincing LLPS claim, it is important to show: Quantitative FRAP curves (mobile fraction and half-time of recovery) rather than only microscopy images and qualitative statements.
(4) The manuscript highly relies on fluorescence microscopy to show colocalization. However, the colocalization is presented in a qualitative manner only. The manuscript would benefit from the inclusion of quantitative metrics (e.g., Pearson's correlation coefficient, Manders' overlap coefficients, or intensity correlation analysis).
(5) In Figures 3 B and 3C, the contrast between "no AT630 at 30 min, strong at 2 h" (50 ng/μL) and "strong at 30 min" (400 ng/μL) is compelling, but a simple quantification (e.g., mean fluorescence intensity per area) would greatly increase rigor.
(6) In Figure S3 ssCD data, if possible, indicate whether the α-helical signal increases with RNA concentration or shows a non-linear dependence, which might link to the LLPS vs solid aggregate regimes.
(7) In Figure 5B, FRAP recovery in dying cells may reflect artifactual mobility rather than biological relevance. Additionally, the absence of quantification data limits interpretation; providing recovery curves would clarify relevance.
(8) The narrative conflates cytotoxicity endpoints (membrane damage, PI staining, aggregates) with localization data (nucleolar foci), creating ambiguity about whether nucleolar targeting drives toxicity or is a consequence of cell death. Separating toxicity assessment from localization analysis, or clearly demonstrating that nucleolar accumulation precedes cytotoxicity, would resolve this ambiguity.
(9) In Figure 8, to strengthen the LLPS assignment for LL-37, additional evidence, such as FRAP analysis or observation of droplet fusion events, would be valuable. This is particularly relevant given that the heat shock conditions (65{degree sign}C for 15 minutes) could potentially induce partial denaturation or nonspecific coacervation.
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Reviewer #2 (Public review):
In this paper, Rayan et al. report that RNA influences cytotoxic activity of the staphylococcal secreted peptide cytolysin PSMalpha3 versus human cells and E. coli by impacting its aggregation. The authors used sophisticated methods of structural analysis and described the associated liquid-liquid phase separation. They also compare the influence of RNA on the aggregation and activity of LL-37, which shows differences from that on PSMalpha3.
Strengths:
That RNA impacts PSM cytotoxicity when co-incubated in vitro becomes clear.
Weaknesses:
I have two major and fundamental problems with this study:
(1) The premise, as stated in the introduction and elsewhere, that PSMalpha3 amyloids are biologically functional, is highly debatable and has never been conclusively substantiated. The property that matters most …
Reviewer #2 (Public review):
In this paper, Rayan et al. report that RNA influences cytotoxic activity of the staphylococcal secreted peptide cytolysin PSMalpha3 versus human cells and E. coli by impacting its aggregation. The authors used sophisticated methods of structural analysis and described the associated liquid-liquid phase separation. They also compare the influence of RNA on the aggregation and activity of LL-37, which shows differences from that on PSMalpha3.
Strengths:
That RNA impacts PSM cytotoxicity when co-incubated in vitro becomes clear.
Weaknesses:
I have two major and fundamental problems with this study:
(1) The premise, as stated in the introduction and elsewhere, that PSMalpha3 amyloids are biologically functional, is highly debatable and has never been conclusively substantiated. The property that matters most for the present study, cytotoxicity, is generally attributed to PSM monomers, not amyloids. The likely erroneous notion that PSM amyloids are the predominant cytotoxic form is derived from an earlier study by the authors that has described a specific amyloid structure of aggregated PSMalpha3. Other authors have later produced evidence that, quite unsurprisingly, indicated that aggregation into amyloids decreases, rather than increases, PSM cytotoxicity. Unfortunately, yet other groups have, in the meantime, published in-vitro studies on "functional amyloids" by PSMs without critically challenging the concept of PSM amyloid "functionality". Of note, the authors' own data in the present study, which show strongly decreased cytotoxicity of PSMalpha3 after prolonged incubation, are in agreement with monomer-associated cytotoxicity as they can be easily explained by the removal of biologically active monomers from the solution.
(2) That RNA may interfere with PSM aggregation and influence activity is not very surprising, given that PSM attachment to nucleic acids - while not studied in as much detail as here - has been described. Importantly, it does not become clear whether this effect has biologically significant consequences beyond influencing, again not surprisingly, cytotoxicity in vitro. The authors do show in nice microscopic analyses that labeled PSMalpha3 attaches to nuclei when incubated with HeLa cells. However, given that the cells are killed rapidly by membrane perturbation by the applied PSM concentrations, it remains unclear and untested whether the attachment to nucleic acids in dying cells makes any contribution to PSM-induced cell death or has any other biological significance.
Overall, the findings can be explained in a much more straightforward way with the common concept of cytotoxicity being due to monomeric PSMs, and the impact of nucleic acids on cytotoxicity being due to lowering of the concentration of that active form by RNA attachment. Further limiting the significance of the findings, whether this interaction has any biological significance on the physiology or infectivity of the PSM producer remains largely unexplored.
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Reviewer #3 (Public review):
Summary:
The manuscript by Rayan et al. aims to investigate the role of RNA in modulating both virulent amyloid and host-defense peptides, with the objective of understanding their self-assembly mechanisms, morphological features, and aggregation pathways.
Strengths:
The overall content is well-structured with a logical flow of ideas that effectively conveys the research objectives.
Weaknesses:
(1) Figure 2 displays representative FRAP images demonstrating fluorescence recovery within seconds. To gain a more comprehensive understanding of how recovery after photobleaching varies under different conditions, it is recommended to supplement these images with corresponding quantitative fluorescence recovery curves for analysis.
(2) Ostwald ripening typically leads to the shrinkage or even disappearance of …
Reviewer #3 (Public review):
Summary:
The manuscript by Rayan et al. aims to investigate the role of RNA in modulating both virulent amyloid and host-defense peptides, with the objective of understanding their self-assembly mechanisms, morphological features, and aggregation pathways.
Strengths:
The overall content is well-structured with a logical flow of ideas that effectively conveys the research objectives.
Weaknesses:
(1) Figure 2 displays representative FRAP images demonstrating fluorescence recovery within seconds. To gain a more comprehensive understanding of how recovery after photobleaching varies under different conditions, it is recommended to supplement these images with corresponding quantitative fluorescence recovery curves for analysis.
(2) Ostwald ripening typically leads to the shrinkage or even disappearance of smaller droplets, accompanied by the further growth of large droplets. However, the droplet size in Figure 2D decreases significantly after 2 h of incubation. This observation prompts the question, what is the driving force underlying RNA-regulated phase separation and phase transition?
(3) The manuscript aims to study the role of RNA in modulating PSMα3 aggregation by using solution-state NMR to obtain residue-specific structural information. The current NMR data, as described in the method and figure captions, were recorded in the absence of RNA. Whether RNA binding induces conformational changes of PSMα3, and how these changes alter the NMR spectra? Also, the sequential NOE walk between neighboring residues can be annotated on the spectrum for clarity.
(4) The authors claim that LL-37 shares functional, sequence, and structural similarities with PSMα3. However, no droplet formation was observed of LL-37 in the presence of RNA only. The authors then applied thermal stress to induce phase separation of LL-37. What are the main factors contributing to the different phase behaviors exhibited by LL-37 and PSMα3? What are the differences in the conformation of amyloid aggregates and the kinetics of aggregation between the condensation-induced aggregation in the presence of RNA and the conventional nucleation-elongation process in the absence of RNA for these two proteins?
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Author response:
We thank the reviewers for their thoughtful and constructive comments, which greatly helped us to clarify, quantify, and strengthen both our findings and interpretations. Below, we provide a point-by-point response to each comment and describe the corresponding changes made.
Public Reviews:
Reviewer #1 (Public review):
Summary:
The manuscript by Rayan et al. aims to elucidate the role of RNA as a context-dependent modulator of liquid-liquid phase separation (LLPS), aggregation, and bioactivity of the amyloidogenic peptides PSMα3 and LL-37, motivated by their structural and functional similarities.
Strengths:
The authors combine extensive biophysical characterization with cell-based assays to investigate how RNA differentially regulates peptide aggregation states and associated cytotoxic and antimicrobial functions.
Weak…
Author response:
We thank the reviewers for their thoughtful and constructive comments, which greatly helped us to clarify, quantify, and strengthen both our findings and interpretations. Below, we provide a point-by-point response to each comment and describe the corresponding changes made.
Public Reviews:
Reviewer #1 (Public review):
Summary:
The manuscript by Rayan et al. aims to elucidate the role of RNA as a context-dependent modulator of liquid-liquid phase separation (LLPS), aggregation, and bioactivity of the amyloidogenic peptides PSMα3 and LL-37, motivated by their structural and functional similarities.
Strengths:
The authors combine extensive biophysical characterization with cell-based assays to investigate how RNA differentially regulates peptide aggregation states and associated cytotoxic and antimicrobial functions.
Weaknesses:
While the study addresses an interesting and timely question with potentially broad implications for host-pathogen interactions and amyloid biology, several aspects of the experimental design and data analysis require further clarification and strengthening.
Major Comments:
(1) In Figure 1A, the author showed "stronger binding affinity" based on shifts at lower peptide concentrations, but no quantitative binding parameters (e.g., apparent Kd, fraction bound, or densitometric analysis) are presented. This claim would be better supported by including: (i) A binding curve with quantification of free vs bound RNA band intensities ,(ii) Replicates and error estimates (mean {plus minus} SD).
We thank the reviewer for this suggestion. To quantitatively support the binding differences observed in Figure 1A, we have now performed densitometric analysis of the EMSA data and included the results in Figure S1. The analysis showed that the Kd for PSMα3 binding to polyAU and polyA RNA is in the same order of magnitude but lower for the polyAU, indicating a stronger binding. A description was added to the results in lines 137-145 of the revised version.
(2) The authors report droplet formation at low RNA (50 ng/µL) but protein aggregation at high RNA (400 ng/µL) through fluorescence microscopy. However, no intermediate RNA concentrations (e.g., 100-300 ng/µL) are tested or discussed, leaving a critical gap in understanding the full phase diagram and transition mechanisms.
Our initial choice of 50 ng/µL (low RNA) and 400 ng/µL (high RNA) was guided by a broader RNA titration performed by turbidity measurements across 0, 10, 20, 50, 100, 200, and 400 ng/µL (Figure S2 in the revised version). In this screen, turbidity increased up to 50 ng/µL and then decreased dose-dependently from 100–400 ng/µL. We interpret this non-monotonic behavior as consistent with a transition from a dropletrich regime (maximal light scattering at intermediate dense-phase volume) toward conditions where assemblies become larger and/or more compact and sediment out of the optical path. This is described in lines 158-161 of the revised version.
Of note, additional intermediate RNA conditions (100 and 200 ng/µL) are included in Figure S14 (of the revised version). While these experiments were performed under the heat-shock perturbation, they nevertheless support the central point that RNA tunes assembly state across intermediate concentrations rather than producing a binary low/high outcome.
Importantly, we agree with the reviewer that a full phase diagram would be the most rigorous way to define the transition mechanism. However, establishing csat and constructing a complete phase diagram would require systematic measurements of dilute-phase concentrations (e.g., centrifugation/quantification or fluorescence calibration), controlled ionic strength titrations, and time-resolved mapping, which is beyond the scope of the present study. We have therefore revised the text to avoid implying that we provide a complete phase diagram. Instead, we frame our results as a qualitative with multi-assay characterization showing that RNA concentration drives a shift from liquid-like condensates (at low RNA) toward solid-like assemblies (at high RNA), with an intermediate regime suggested by the turbidity transition and supported by additional imaging under stress. Finally, to address the “critical gap” concern directly, we add a sentence (lines 239-241) stating that: “Future work will be required to quantitatively define the phase boundaries and delineate the dominant mechanisms, such as sedimentation, dissolution, or coarsening/aging, across intermediate RNA concentrations.
(3) Additionally, the behaviour of PSMα3 in the absence of RNA under LLPS conditions is not shown. Without protein-only data, it is difficult to assess if droplets are RNA-induced or if protein has a weak baseline LLPS that RNA tunes. The saturation concentration (csat) for PSMα3 phase separation, either in the absence or presence of RNA, should be reported.
In response to the reviewer’s request, we have added Figure 2F, which shows PSMα3 alone in the absence of RNA under the same conditions. PSMα3 does not form droplets in this condition, indicating that condensate formation is RNA-dependent in the tested conditions. This is referred to in the text in lines 190-193 of the revised version. Please see our response about determining the csat in the response to the previous comment.
(4) For a convincing LLPS claim, it is important to show: Quantitative FRAP curves (mobile fraction and half-time of recovery) rather than only microscopy images and qualitative statements.
We have included quantitative FRAP analysis in Figure S4 of the revised version, showing normalized recovery curves along with extracted mobile fractions and half-times of recovery (t₁/₂). These quantitative measurements support the dynamic nature of the PSMα3–RNA. This is referred to in the text in lines 179-184 of the revised version.
(5) The manuscript highly relies on fluorescence microscopy to show colocalization. However, the colocalization is presented in a qualitative manner only. The manuscript would benefit from the inclusion of quantitative metrics (e.g., Pearson's correlation coefficient, Manders' overlap coefficients, or intensity correlation analysis).
In response, we have added quantitative colocalization analysis to the revised manuscript. Specifically, we now report Pearson’s correlation coefficients and Manders’ overlap coefficients for the dual-channel fluorescence microscopy datasets in Figure S5 of the revised version. These metrics provide an objective measure of codistribution and complement the qualitative imaging.
The analysis supports that at low RNA concentrations (droplet/condensate conditions), PSMα3 and RNA show strong colocalization, consistent with RNA being incorporated within, or closely associated with, the peptide-rich phase. In contrast, at high RNA concentrations, where the assemblies are more solid-like/amyloid-positive, the quantitative coefficients decrease, consistent with reduced overlap and an apparent spatial demixing in which RNA becomes partially excluded from the peptide-rich structures. This is referred to in the text in lines 194-203 of the revised version.
(6) In Figures 3 B and 3C, the contrast between "no AT630 at 30 min, strong at 2 h" (50 ng/μL) and "strong at 30 min" (400 ng/μL) is compelling, but a simple quantification (e.g., mean fluorescence intensity per area) would greatly increase rigor.
We have included quantitative analysis of AmyTracker630 fluorescence intensity in Figure S6 of the revised version, reporting the mean fluorescence intensity per area for the indicated conditions and time points. This quantification supports the qualitative differences observed in Figures 3B and 3C. This is now referred to in the text in lines 233-236 of the revised version.
(7) In Figure S3 ssCD data, if possible, indicate whether the α-helical signal increases with RNA concentration or shows a non-linear dependence, which might link to the LLPS vs solid aggregate regimes.
The ssCD spectra displayed in Figure S7 in the revised version (corresponding to Figure S3 in the original submission) show that the α-helical signature of PSMα3 is markedly enhanced in the presence of RNA compared to peptide alone, as evidenced by increased signal intensity, deeper minima, and more pronounced spectral features characteristic of α-helical structure. Importantly, this enhancement is more pronounced at 400 ng/µL Poly(AU) RNA than at 50 ng/µL, particularly after 2 hours of coincubation, indicating that RNA concentration influences the stabilization of α-helical assemblies. This is now more specifically detailed in the text in lines 258-263 of the revised version.
We note that solid-state CD does not allow direct quantitative deconvolution of secondary structure content (e.g., % helix) in the same manner as solution CD, due to sample anisotropy, scattering, and orientation effects inherent to dried or aggregated films. Consequently, our interpretation is qualitative rather than strictly quantitative. The ssCD data therefore suggest a non-linear dependence on RNA concentration, rather than a simple linear dose–response. This is also expected considering that phase transition, suggested by the other findings, is intrinsically non-linear.
(8) In Figure 5B, FRAP recovery in dying cells may reflect artifactual mobility rather than biological relevance. Additionally, the absence of quantification data limits interpretation; providing recovery curves would clarify relevance.
We added quantitative FRAP analysis of the effect on PSMα3 within HeLa cells, shown in Figure S8 of the revised version. Compared to PSMα3 assemblies in vitro, nucleolar PSMα3 exhibits slower fluorescence recovery and a reduced mobile fraction. The nucleolus represents a highly crowded, RNA-rich cellular environment, which is expected to impose additional constraints on molecular mobility and likely contributes to the slower recovery kinetics observed in cells. This is now more specifically detailed in the text in lines 324-333 and discussed in lines 597-607 of the revised version.
(9) The narrative conflates cytotoxicity endpoints (membrane damage, PI staining, aggregates) with localization data (nucleolar foci), creating ambiguity about whether nucleolar targeting drives toxicity or is a consequence of cell death. Separating toxicity assessment from localization analysis, or clearly demonstrating that nucleolar accumulation precedes cytotoxicity, would resolve this ambiguity.
We thank the reviewer for raising this important point. We agree that, in the current dataset, cytotoxicity readouts (membrane damage, PI staining, aggregate formation) and subcellular localization (nucleolar accumulation) are observed in close temporal proximity, which limits our ability to unambiguously assign causality. In the experiments presented here, PSMα3 was applied at concentrations known to induce rapid membrane disruption and cytotoxicity in HeLa cells. Under these conditions, PSMα3 accumulates on cellular membranes and penetrates into the cell and nucleus on very short timescales (seconds to minutes), likely preceding the temporal resolution accessible by standard live-cell fluorescence microscopy. As a result, nucleolar accumulation and cytotoxic endpoints are detected essentially concurrently, precluding a definitive determination of whether nucleolar association actively drives toxicity or occurs as a downstream consequence of membrane permeabilization and cell damage.
We therefore emphasize that, in this study, nucleolar localization is presented as a phenomenological observation consistent with RNA-rich compartment association, rather than as a demonstrated causal mechanism of cytotoxicity. We have revised the Discussion (lines 597-607) to clarify this distinction and to avoid implying that nucleolar targeting is the primary driver of cell death.
We agree that resolving this ambiguity would require systematic time-resolved and concentration-dependent experiments, including analysis at sub-toxic PSMα3 concentrations below the membrane-disruptive threshold, combined with orthogonal imaging approaches. Such experiments are planned for future work but are beyond the scope of the present study.
(10) In Figure 8, to strengthen the LLPS assignment for LL-37, additional evidence, such as FRAP analysis or observation of droplet fusion events, would be valuable. This is particularly relevant given that the heat shock conditions (65 °C for 15 minutes) could potentially induce partial denaturation or nonspecific coacervation.
In response to this comment, we have added FRAP analysis of LL-37 assemblies in the revised manuscript (Figure S12), including representative images and corresponding fluorescence recovery curves. The FRAP measurements show minimal fluorescence recovery over the acquisition window, indicating that the LL-37–RNA assemblies formed under these conditions are largely immobile and solid-like, rather than liquid-like droplets. This is now referred to in the text in lines 458-462 of the revised version.
Reviewer #2 (Public review):
In this paper, Rayan et al. report that RNA influences cytotoxic activity of the staphylococcal secreted peptide cytolysin PSMalpha3 versus human cells and E. coli by impacting its aggregation. The authors used sophisticated methods of structural analysis and described the associated liquid-liquid phase separation. They also compare the influence of RNA on the aggregation and activity of LL-37, which shows differences from that on PSMalpha3.
Strengths:
That RNA impacts PSM cytotoxicity when co-incubated in vitro becomes clear.
Weaknesses:
I have two major and fundamental problems with this study:
(1) The premise, as stated in the introduction and elsewhere, that PSMalpha3 amyloids are biologically functional, is highly debatable and has never been conclusively substantiated. The property that matters most for the present study, cytotoxicity, is generally attributed to PSM monomers, not amyloids. The likely erroneous notion that PSM amyloids are the predominant cytotoxic form is derived from an earlier study by the authors that has described a specific amyloid structure of aggregated PSMalpha3. Other authors have later produced evidence that, quite unsurprisingly, indicated that aggregation into amyloids decreases, rather than increases, PSM cytotoxicity. Unfortunately, yet other groups have, in the meantime, published in-vitro studies on "functional amyloids" by PSMs without critically challenging the concept of PSM amyloid "functionality". Of note, the authors' own data in the present study, which show strongly decreased cytotoxicity of PSMalpha3 after prolonged incubation, are in agreement with monomer-associated cytotoxicity as they can be easily explained by the removal of biologically active monomers from the solution.
We thank the reviewer for this important critique and agree that direct cytotoxicity is most plausibly mediated by soluble PSM species, while extensive fibrillation generally reduces toxicity by depleting these forms, a conclusion supported by our data and by other studies (e.g., Zheng et al 2018 and Yao et al 2019). We do not propose mature amyloid fibrils as the primary toxic entities. Rather, we use the term functional amyloid in a regulatory sense, consistent with other biological amyloids whose fibrillar states modulate activity (e.g., hormone storage amyloids or RNA-binding proteins).
In line with emerging findings, we interpret PSMα3 toxicity as arising from a dynamic assembly process rather than from a single static molecular species. We previously showed that PSMα3 forms cross-α fibrils that are thermodynamically and mechanically less stable than cross-β amyloids and readily disassemble upon heat stress, fully restoring cytotoxic activity (Rayan et al., 2023). This behavior contrasts with PSMα1, which forms highly stable cross-β fibrils that do not recover activity after heat shock, suggesting that the limited thermostability of PSMα3 is an evolved feature enabling reversible switching between inactive (stored) and active states.
Consistent with this view, both PSMα1 and PSMα3 are cytotoxic in their soluble states, yet mutants unable to fibrillate lose activity, indicating that fibrillation is required but not itself the toxic end state (Tayeb-Fligelman et al., 2017, 2020; Malishev et al., 2018). Our other studies further show that cytotoxicity toward human cells correlates with inherent or lipid-induced α-helical assemblies, rather than with inert β-sheet amyloids (RagonisBachar et al., 2022, 2026; Salinas 2020, Bücker 2022). Together, these findings support a model in which membrane-associated, dynamic α-helical assembly, which requires continuous exchange between soluble species and growing fibrils, drives membrane disruption, potentially through lipid recruitment or extraction, analogous to mechanisms proposed for human amyloids such as islet amyloid polypeptide (Sparr et al., 2004).
In the present study, we further show that RNA reshapes this dynamic landscape: while PSMα3 alone progressively loses activity upon incubation, co-incubation with RNA preserves cytotoxicity by stabilizing bioactive polymorphs and condensate-like states, whereas high RNA concentrations promote solid aggregation but nevertheless preserve activity. Thus, aggregation is neither inherently functional nor toxic, but context-dependent and environmentally regulated. Taken together, our data support a model in which PSMα3 amyloids act as a dynamic reservoir, enabling S. aureus to tune virulence by reversibly shifting between dormant and active states in response to environmental cues such as heat or RNA.
This is now discussed in lines 56-76 and 523-553 of the revised version.
(2) That RNA may interfere with PSM aggregation and influence activity is not very surprising, given that PSM attachment to nucleic acids - while not studied in as much detail as here - has been described. Importantly, it does not become clear whether this effect has biologically significant consequences beyond influencing, again not surprisingly, cytotoxicity in vitro. The authors do show in nice microscopic analyses that labeled PSMalpha3 attaches to nuclei when incubated with HeLa cells. However, given that the cells are killed rapidly by membrane perturbation by the applied PSM concentrations, it remains unclear and untested whether the attachment to nucleic acids in dying cells makes any contribution to PSM-induced cell death or has any other biological significance.
We thank the reviewer for this important point and agree that PSM–nucleic acid interactions are not unexpected and that our data do not support a direct intracellular role for RNA binding in mediating cytotoxicity. Accordingly, we do not propose nucleolar or nuclear association of PSMα3 as a causal mechanism of cell death. At the concentrations used, PSMα3 induces rapid membrane disruption, and nucleic acid association is observed along with membrane attachment, precluding conclusions about intracellular function. This limitation is now explicitly clarified in the revised manuscript. The biological significance of our findings lies instead in extracellular and environmental contexts, where PSMα3 encounters abundant nucleic acids, such as RNA or DNA released from damaged host cells or present in biofilms as now addressed in lines 622631. Our data show that RNA modulates PSMα3 aggregation trajectories, shifting the balance between liquid-like condensates and solid aggregates, and thereby regulates the persistence and timing of cytotoxic activity. In this framework, RNA acts as a context-dependent regulator of virulence, rather than as an intracellular cytotoxic cofactor, an aspect which would be studied in depth in future work. This is now addressed in the text in lines 597-607 of the revised version.
Reviewer #3 (Public review):
Summary:
The manuscript by Rayan et al. aims to investigate the role of RNA in modulating both virulent amyloid and host-defense peptides, with the objective of understanding their self-assembly mechanisms, morphological features, and aggregation pathways.
Strengths:
The overall content is well-structured with a logical flow of ideas that effectively conveys the research objectives.
Weaknesses:
(1) Figure 2 displays representative FRAP images demonstrating fluorescence recovery within seconds. To gain a more comprehensive understanding of how recovery after photobleaching varies under different conditions, it is recommended to supplement these images with corresponding quantitative fluorescence recovery curves for analysis.
In response to this comment, we have supplemented the representative FRAP images with quantitative fluorescence recovery curves, reporting normalized recovery kinetics for the indicated conditions. These data are now provided in Figure S4 of the revised manuscript, allowing direct comparison of recovery behavior across conditions (shown by microscopy in Figure 2). In addition, we have included quantitative FRAP analyses for the cellular imaging shown in Figure 5 (presented in Figure S8) and for LL-37 assemblies formed under heat-shock conditions (Figure S12). Together, these additions provide a quantitative framework for interpreting the FRAP results and strengthen the distinction between liquid-like and solid-like assembly states.
(2) Ostwald ripening typically leads to the shrinkage or even disappearance of smaller droplets, accompanied by the further growth of large droplets. However, the droplet size in Figure 2D decreases significantly after 2 h of incubation. This observation prompts the question, what is the driving force underlying RNA-regulated phase separation and phase transition?
We thank the reviewer for this observation. Across multiple samples, we consistently observe a coexistence of small droplets and larger aggregates, rather than systematic growth of larger droplets at the expense of smaller ones or a uniform decrease in droplet size. In addition, the timescales examined do not allow us to reliably assess whether diffusion-driven droplet coalescence is fast enough to draw firm conclusions about droplet size evolution. This is now addressed in the text in lines 181-184 of the revised version.
A decrease in droplet size over time is nevertheless observed in some instances and is more consistent with a time-dependent conversion of initially liquid-like condensates into more solid-like assemblies, which would reduce molecular mobility and suppress droplet coalescence. In parallel, progressive fibril formation may act as a sink for soluble peptide, leading to partial dissolution or shrinkage of less mature condensates. Together, these observations are consistent with a non-equilibrium aging process, in which RNAregulated assemblies evolve from dynamic condensates toward more solid structures rather than following equilibrium Ostwald ripening.
(3) The manuscript aims to study the role of RNA in modulating PSMα3 aggregation by using solution-state NMR to obtain residue-specific structural information. The current NMR data, as described in the method and figure captions, were recorded in the absence of RNA. Whether RNA binding induces conformational changes of PSMα3, and how these changes alter the NMR spectra? Also, the sequential NOE walk between neighboring residues can be annotated on the spectrum for clarity.
The solution-state NMR experiments were performed specifically to characterize the potential binding of EGCG to PSMα3. Due to the strong tendency of PSMα3 to undergo rapid aggregation and line broadening upon RNA addition, solutionstate NMR spectra in the presence of RNA could not be obtained at sufficient quality for residue-specific analysis. As suggested, we have updated and annotated the sequential NOE walk between neighboring residues on the relevant NOESY spectra to improve clarity.
(4) The authors claim that LL-37 shares functional, sequence, and structural similarities with PSMα3. However, no droplet formation was observed of LL-37 in the presence of RNA only. The authors then applied thermal stress to induce phase separation of LL-37. What are the main factors contributing to the different phase behaviors exhibited by LL37 and PSMα3? What are the differences in the conformation of amyloid aggregates and the kinetics of aggregation between the condensation-induced aggregation in the presence of RNA and the conventional nucleation-elongation process in the absence of RNA for these two proteins?”
We appreciate this important question and have clarified both the basis of the comparison and the origin of the divergent phase behaviors of LL-37 and PSMα3. While PSMα3 and LL-37 share key properties as short, cationic, amphipathic α-helical peptides that self-assemble and interact with nucleic acids, they differ fundamentally in their assembly architectures. PSMα3 is an amyloidogenic peptide that forms cross-α amyloid fibrils, in which α-helices stack perpendicular to the fibril axis. In contrast, LL-37 can form fibrillar or sheet-like assemblies (observed in cryo grids), but these lack canonical amyloid features without clear cross-α or cross-β amyloid order, as so far observed by crystal structures. This is now clarified in different parts of the text of the revised version. Thus, the comparison between the two peptides is functional and physicochemical rather than implying identical amyloid mechanisms. These structural differences likely underlie their distinct phase behaviors.
Because LL-37 does not follow a classical amyloid nucleation–elongation pathway, and high-resolution structural information (e.g., cryo-EM) is currently lacking, partly due to its sheet-like, non-twisted morphology (unpublished results), it is not possible to directly compare aggregation kinetics or nucleation mechanisms between LL-37 and PSMα3. It is possible that amyloidogenic systems such as PSMα3 exhibit greater flexibility in prefibrillar and fibrillar polymorphism, enabling RNA-regulated phase behavior, whereas nonamyloid assemblies such as LL-37 are more prone to stress-induced solid aggregation. We note that this interpretation is necessarily tentative and does not imply a general rule, but rather reflects differences evident in the present system.
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