1. Biochemistry and Chemical Biology
Download icon

HspB8 prevents aberrant phase transitions of FUS by chaperoning its folded RNA-binding domain

  1. Edgar E Boczek
  2. Julius Fürsch
  3. Marie Laura Niedermeier
  4. Louise Jawerth
  5. Marcus Jahnel
  6. Martine Ruer-Gruß
  7. Kai-Michael Kammer
  8. Peter Heid
  9. Laura Mediani
  10. Jie Wang
  11. Xiao Yan
  12. Andrej Pozniakovski
  13. Ina Poser
  14. Daniel Mateju
  15. Lars Hubatsch
  16. Serena Carra
  17. Simon Alberti
  18. Anthony A Hyman
  19. Florian Stengel  Is a corresponding author
  1. Max Planck Institute of Molecular Cell Biology and Genetics, Germany
  2. Dewpoint Therapeutics GmbH, Germany
  3. University of Konstanz, Department of Biology, Germany
  4. Konstanz Research School Chemical Biology, University of Konstanz, Germany
  5. Max Planck Institute for the Physics of Complex Systems, Germany
  6. Biotechnology Center, Technische Universität Dresden, Germany
  7. Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Italy
  8. Center for Systems Biology Dresden (CSBD), Germany
Research Article
  • Cited 2
  • Views 1,372
  • Annotations
Cite this article as: eLife 2021;10:e69377 doi: 10.7554/eLife.69377

Abstract

Aberrant liquid-to-solid phase transitions of biomolecular condensates have been linked to various neurodegenerative diseases. However, the underlying molecular interactions that drive aging remain enigmatic. Here, we develop quantitative time-resolved crosslinking mass spectrometry to monitor protein interactions and dynamics inside condensates formed by the protein fused in sarcoma (FUS). We identify misfolding of the RNA recognition motif of FUS as a key driver of condensate aging. We demonstrate that the small heat shock protein HspB8 partitions into FUS condensates via its intrinsically disordered domain and prevents condensate hardening via condensate-specific interactions that are mediated by its α-crystallin domain (αCD). These αCD-mediated interactions are altered in a disease-associated mutant of HspB8, which abrogates the ability of HspB8 to prevent condensate hardening. We propose that stabilizing aggregation-prone folded RNA-binding domains inside condensates by molecular chaperones may be a general mechanism to prevent aberrant phase transitions.

Introduction

Condensate formation by liquid-liquid phase separation leads to a local density change of proteins (Banani et al., 2017; Hyman et al., 2014). Liquid condensates can harden and evolve into less dynamic states with reduced fluidity and protein movement, leading to fibrillar assemblies that are often associated with disease (Aguzzi and Altmeyer, 2016; Patel et al., 2015; Molliex et al., 2015). The molecular changes that underly these aberrant phase transitions, and the ways that cells prevent them, remain poorly understood.

Stress granules have been used as a model to study the role of phase separation in the formation of cellular condensates, as well as disease processes that arise from aberrant phase transitions. Stress granules are composed of RNA and translation factors (Guillén-Boixet et al., 2020; Yang et al., 2020; Sanders et al., 2020; Jain et al., 2016; Markmiller et al., 2018; Youn et al., 2018). There is an increasing body of evidence that the ability of stress granule proteins to phase separate forms the basis for stress granule assembly (Guillén-Boixet et al., 2020; Yang et al., 2020; Sanders et al., 2020). For instance, purified stress granule residing RNA-binding proteins (RBPs) phase separate into liquid droplets in vitro. Reconstituted droplets have physicochemical properties similar to stress granules in cells (Patel et al., 2015; Guillén-Boixet et al., 2020; Yang et al., 2020; Sanders et al., 2020). In vitro reconstituted molecular condensates are metastable and age into less dynamic amorphous drops, and fibrillar aggregates with time (Patel et al., 2015). These aggregates are reminiscent of protein aggregates seen in patients afflicted with age-related diseases such as amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). This process is referred to as molecular aging (Patel et al., 2015). Notably, the molecular aging process is accelerated by ALS-linked mutations in FUS and other RBPs (Patel et al., 2015; Molliex et al., 2015). This suggests that molecular aging of liquid condensates such as stress granules can be a disease process.

Recent studies have provided evidence for a link between stress granules and small heat shock proteins (sHSPs) (Mateju et al., 2017; Ganassi et al., 2016; Liu et al., 2020; Yu et al., 2021; Gu et al., 2020). These ATP-independent chaperones hold unfolded proteins in a refolding-competent state and both their intrinsically disordered region (IDR) and folded α-crystallin domain (αCD) contribute to this activity (Haslbeck et al., 2019). sHSPs have been shown to accumulate in stress granules that undergo an aberrant conversion from a liquid to a solid-like state (Mateju et al., 2017; Ganassi et al., 2016). Aberrant stress granules have also been linked to disease and many sHSPs are associated with neurodegenerative disorders (Vendredy et al., 2020). This suggests that chaperones, such as sHSPs, may regulate the properties of stress granules and presumably also the molecular aging process of stress granule proteins such as FUS.

FUS has been a model protein to study both aberrant and physiological phase transitions (Patel et al., 2015; Guo et al., 2018; Hofweber et al., 2018; Qamar et al., 2018; Wang et al., 2018; Yoshizawa et al., 2018; Kato et al., 2012). It contains an intrinsically disordered prion-like low complexity domain (LCD) composed of only a small subset of amino acids, an RNA-binding domain (RBD) containing intrinsically disordered RGG-rich motifs, a Zinc finger (ZnF), and a folded RNA recognition motif (RRM). It has been shown that phase separation of FUS family proteins is driven by multivalent interactions among tyrosine residues within its LCD and arginine residues of their RBDs (Qamar et al., 2018; Wang et al., 2018; Schuster et al., 2020). At least part of the LCD of FUS can assemble into amyloid fibrils (Murray et al., 2017) and the isolated FUS-LCD can adopt a hydrogel-like state that also depends on amyloid-like interactions (Kato et al., 2012). By contrast, the LCD appears to be disordered in liquid droplets, exhibiting no detectable secondary structure (Murthy et al., 2019). Similar observations have been made for the LCD of hnRNPA2 (Xiang et al., 2015). In addition to the LCD, the isolated FUS-RRM has been shown to spontaneously self-assemble into amyloid fibrils (Lu et al., 2017). However, the molecular mechanism by which proteins such as FUS undergo molecular aging are still unknown.

To determine the molecular changes during the aging of stress granule proteins such as FUS, it is critical to monitor protein-protein interactions (PPIs) and conformational dynamics within condensates. However, this has remained a major challenge. We and others showed previously that chemical crosslinking coupled to mass spectrometry (XL-MS) is well suited to map PPIs and that relative changes in crosslinking as probed by quantitative XL-MS (qXL-MS) can provide a structural understanding of protein dynamics (Yu and Huang, 2018; Sailer et al., 2018; Walker-Gray et al., 2017; Patel et al., 2017). Here, we adopt XL-MS to study condensates.

In this study, we take a biochemical approach using purified proteins to reconstitute a chaperone-mediated quality control mechanism associated with RNP granules and combine it with qXL-MS to probe PPIs inside condensates. We find that unfolding of the RRM drives FUS aging and that interaction of its folded RRM with the sHSP HspB8 slows down this aging process. Importantly, these condensate-specific interactions are altered in a disease-associated HspB8 mutant, resulting in its inability to prevent FUS aging.

Results

Quantitative and time-resolved XL-MS reveal domain-specific changes in crosslink abundances underlying condensate formation

To investigate the condensate-specific interactions of FUS after phase separation, we diluted purified FUS-G156E protein (Patel et al., 2015; Nomura et al., 2014), called FUSm throughout this manuscript, either into a low salt solution, which induces phase separation or into a high salt buffer, which prevents phase separation. After crosslinking of lysine residues and subsequent digestion, equal amounts of peptides were subjected to mass spectrometry analysis to reveal condensate-specific crosslink patterns (Figure 1A, Figure 1—figure supplement 1A, Supplementary file 1). These crosslinks can either reflect the spatial proximity of regions and protein-domains within a given protein, called intra-links, or between different proteins, called inter-links. For a detailed description of the different crosslink types see Figure 1—figure supplement 1B. When the crosslinker reacts twice within one peptide, this is called a loop-link. Additional information comes from crosslinking of one side of the crosslinker with the protein and hydrolysis on the other side. This is called a mono-link and reveals information on the accessibility of a specific lysine residue. In some cases, we can also follow links between proteins of the same species (homo-dimeric link). These are crosslinks between overlapping peptides whose sequence is unique within the protein and that must therefore originate from different copies of the same protein.

Figure 1 with 1 supplement see all
Domain-specific changes in crosslink abundances underlying condensate formation and molecular aging.

(A) Workflow of quantitative crosslinking coupled to mass spectrometry (qXL-MS) of FUSm condensates. (B) Crosslink abundance plot from reconstituted FUSm condensates. Plotted are the relative enrichment (droplet vs. non-droplet) for each unique crosslinking site (y-axis) sorted according to the known domain structure within FUSm (x-axis). Shown are only high confidence crosslinking sites (see Materials and methods for details) from three biologically independent sets of experiments (n=3; circles in different shades of gray). Please note that FUSm used throughout this manuscript contains both a C-terminal GFP used for visualization and a 5 AA N-terminal tag used for purification. All uxIDs therefore have an offset of 5 AA compared to the UniProt entry for human FUS (P35637). Crosslinking sites that were consistently upregulated or downregulated twofold or more (log2ratio≥1 or ≤−1 and FDR≤0.05) in at least two out of three biological replicate sets and in addition contained no opposing regulation in any replicate set were considered significant and are highlighted with a green (enriched in droplets) or red background rectangle (decreased in droplets). All other changes in crosslinking abundances were considered insignificant and are shown on gray background. The significance threshold of twofold enrichment is indicated as dashed red line. Dimeric links are indicated by an additional ‘−d’, loop-links by a ‘−l’ and mono-links by an ‘-mono’ at their respective unique crosslinking site. Domain structures within FUSm are color-coded as in (A). RGG refers to AAs 220–289. (C) Upper panel: workflow time-resolved quantitative XL-MS. The conversion of fresh FUSm condensates via the gel state into fibers was monitored by fluorescence microscopy. Scale bar is 10 µm. At indicated time points, aliquots of the stock solution were crosslinked for 5 min, flash-frozen in liquid nitrogen, and subsequently analyzed by MS (see Materials and methods for details). Lower panel: shown are changes of RRM crosslinks during aging that were increased during condensation (B). The logarithmic total MS1 area for each time point during aging is plotted (SDs; n=6). Domain structures within FUSm are color-coded as in (A). RRM, RNA recognition motif.

Please note that the crosslinker used throughout this manuscript, disuccinimidyl suberate (DSS), will react with primary amines and thus primarily link lysine residues within studied proteins. It is important to remember that the LCD of FUS contains no lysines and therefore our approach is not picking up interactions between and amongst the LCD domains (for information on the LCD of FUS see lysine-rich variant FUS_K9 in Figure 2—figure supplement 1G).

The most prominent feature we detected after FUSm condensation was that multiple intra-links within the RRM domain of FUSm increased inside the condensates. This suggests that there are augmented contacts within the RRM domain, indicative of a structural change. In addition, there was an increase in homo-dimeric links between RRM domains, indicative of interactions between RRM domains of different FUSm molecules. Additionally, links between the RRM domain and the nuclear localization sequence (NLS) were increased, while links within the Zinc-finger domain were decreased (Figure 1B). Taken together, these results suggest structural changes in the RRM domain accompany condensation.

Crosslinks within the RRM domain change during molecular aging

It has been shown previously that FUSm (FUS-G156E) shows an increased propensity for aggregation in vitro and in vivo (Nomura et al., 2014), resulting in slowed down internal dynamics over time (Patel et al., 2015; Nomura et al., 2014; Jawerth et al., 2020; Jawerth et al., 2018) and enabling us to study molecular aging of FUS condensates in vitro. To study protein dynamics and conformational changes during aging, we devised a time-resolved, quantitative XL-MS approach (Figure 1C) based on significantly shortened crosslinking times than conventionally used (Iacobucci et al., 2019; Figure 1—figure supplement 1C), which put us into the position to assess all stages of the aging process (Figure 1—figure supplement 1D). We then monitored the conversion of fresh FUSm condensates into fibers by fluorescence microscopy (Figure 1C). At indicated time points, the assemblies were crosslinked and analyzed by MS. We looked at 11 time points during the aging process and consistently quantified 77 crosslinks relative to fresh condensates (T1) (Supplementary file 2). A global view of all quantified crosslinking sites shows that the vast majority of changes are happening during the formation of fiber states (Figure 1—figure supplement 1E). A closer examination focusing on those crosslinks within the RRM that were increased during condensation shows that these also change during molecular aging and particularly during fiber formation (Figure 1C and Figure 1—figure supplement 1F). For instance, the link within the RRM bridging positions 339 and 362 decreases as fibers form. The general trend is for interactions between RRM domains and within RRM domains to decrease as condensates age.

The small heat shock protein HspB8 partitions into FUS condensates and interacts with the RRM domain

To test whether these changes in links are indeed driven by aging, we next looked for ways to slow down the aging process. sHSPs are ATP-independent chaperones and are structurally divided into IDRs and a folded chaperone domain called αCD (Carra et al., 2019). HspB8 has previously been localized to stress granules (Ganassi et al., 2016). We therefore purified HspB8 (Figure 2—figure supplement 1A) and looked at its interaction with FUSm condensates in vitro. We find that HspB8 was sequestered into reconstituted FUSm condensates (Figure 2A) and that its fluorescence signal superimposed with the FUSm-GFP signal (Figure 2B), while it did not form droplets on its own under these conditions (Figure 2—figure supplement 1B). Another closely related sHSP that has been localized to stress granules (Mateju et al., 2017), HspB1, did not accumulate inside FUSm droplets (Figure 2C, Figure 2D, Figure 2—figure supplement 1A). Using the fluorescence signal of labeled HspB8 and a calibration curve, we determined the concentration of HspB8 inside FUSm condensates to be 2.4 mM (Figure 2—figure supplement 1C and D).

Figure 2 with 1 supplement see all
The small heat shock protein HspB8 partitions into FUS condensates and interacts with the RRM domain.

(A) 0.25 µM Cy3-labeled HspB8, 4.75 µM unlabeled HspB8 (1:20 mix), and 5 µM FUSm-GFP were mixed in low salt buffer and the resulting droplets were imaged in a confocal microscope. Scale bar is 10 µm. (B) Fluorescence intensity plot profile spanning a FUSm-HspB8 droplet in (A). (C) 0.25 µM Cy3-labeled HspB1, 4.75 µM unlabeled HspB1 (1:20 mix), and 5 µM FUSm-GFP were mixed in low salt buffer and imaged in a confocal microscope. Scale bar is 10 µm. (D) Fluorescence intensity plot profile spanning a FUSm-HspB1 droplet in (C). (E) Overall crosslinking pattern of mixtures of FUSm and HspB8 that were crosslinked under condensate-inducing low salt conditions (75 mM) and separated into the dilute phase (left) and dense phase of the condensates (right) by centrifugation. Experiments were carried out in three biologically independent sets of experiments (meaning separate batches of expressed protein). For one set of experiments, each sample was independently crosslinked in triplicates and crosslinks were only considered, if they were identified in two out of three replicates with a deltaS<0.95, a minimum Id score≥20, and an ld score≥25 in at least one replicate (filtering was done on the level of the unique crosslinking site) and an FDR≤0.05. Inter-links are shown in black and the total number of identifications is indicated by the thickness of the connection. Intra-links are shown in violet, mono-links with a flag, loop links with a pointed triangle, and homo-dimeric links with a loop. (F) Representative overview of observed crosslinks between the LCD and RRM domains in FUSm and the IDR and αCD domains in HspB8 in the dilute and the dense phase as detected by XL-MS (based on (E), Figure 2—figure supplement 1F and G). αCD, α-crystallin domain; IDR, intrinsically disordered region; LCD, low complexity domain; RRM, RNA recognition motif.

We then used XL-MS, to probe PPIs between FUSm and HspB8 inside the condensates. Inter-links (crosslinks between different proteins) predominantly formed inside the dense phase of the condensates (Figure 2E, Supplementary file 3). Together with data from thermophoresis binding experiments (Figure 2—figure supplement 1E), this suggests that HspB8 specifically binds to FUSm inside and not outside condensates. We find the majority of inter-links within the droplets were formed between the αCD of HspB8 and the RRM of FUSm, and to a lesser degree the FUS-NLS. This condensate-specific and highly reproducible crosslinking pattern (Figure 2E, Figure 2—figure supplement 1F and G) was not seen when lactalbumin, a FUS-unrelated molten globule protein that unspecifically partitions into FUSm condensates (Figure 2—figure supplement 1H and I) was used as a control. Taken together, interactions between HspB8 and FUSm show a condensate-specific increase; in particular, interactions between the αCD of HspB8 and the FUSm-RRM are significantly upregulated inside condensates (Figure 2F).

HspB8 prevents hardening and fiber formation of FUS droplets and keeps them dynamic

A time-course experiment using photobleaching recovery (fluorescence recovery after photobleaching [FRAP]) revealed that in the presence of HspB8, FUSm retained its liquidity over a time span of 24 hr (Figure 3A–C, Figure 3—figure supplement 1A–D). FUSm droplets were able to fuse even after 6 hr (Figure 3D): the relaxation times of the fusion events were not affected (Figure 3E) and the drops no longer adhered to each other (Figure 3—figure supplement 1E). In addition to protecting fresh FUSm condensates from converting into fibers (Figure 3F), the chaperone prevented further conversion of pre-aged FUSm droplets, and prevented seeding of fiber growth (Figure 3G, Video 1). This correlated with the localization of HspB8 to FUSm assemblies (Figure 3—figure supplement 1F). The protective effect of HspB8 on FUSm was also observed at sub-stoichiometric HspB8 concentrations (Figure 3H).

Figure 3 with 1 supplement see all
HspB8 prevents hardening and fiber formation of FUS droplets and keeps them dynamic.

(A) FRAP experiment of fresh FUSm condensates (0 hr) and condensates incubated for 5 hr. A kymograph shown below illustrates the kinetics of the process. (B) FRAP experiment of fresh FUSm condensates mixed with HspB8 (0 hr) and condensates incubated for 5 hr. A kymograph shown below illustrates the kinetics of the process. (C) Kinetics of the FUSm aging process. Plotted are the initial slopes of the FRAP recovery curves for FUSm condensates in the absence (black) or presence of HspB8 (red). (D) Successful complete fusion events were registered over time, demonstrating the aging process of the FUSm sample in the absence (turquoise, N=40) or the presence of HspB8 (yellow, N=330). The half-life of liquid-like FUSm condensates alone was estimated to be around 1.5 hr from logistic regression. (E) The size-normalized coalescence relaxation time is an indicator for the material state of the condensates. While it increases for FUSm condensates during the hardening process, it stays constant over 6 hr in the presence of HspB8. Tweezer experiments were performed with fresh samples of 5 μM FUSm with or without 20 μM HspB8. (F) Aging process of 5 µM FUSm condensates in the absence and presence of 5 µM HspB8. In the presence of the chaperone, the droplet morphology is maintained over the whole timeframe of the experiment (12 hr). Scale bar is 10 µm. (G) Left panel: shown is the total area of droplet material (green line) or fibrous material (red line) within FUSm droplets as a function of time after FUSm droplets were added to the existing fibrous material. Spacing between data points is 30 min. Right panel: shown is the total area of droplet material (green line) and fibrous material (red line) within FUSm droplets as a function of time after FUSm droplets and HspB8 were added to the existing fibrous material. Spacing between data points is 30 min. (H) The onset of 5 µM FUSm fiber formation as a function of HspB8 concentration. FRAP, fluorescence recovery after photobleaching.

Video 1
Time lapse of FUS fiber growth.

Time-lapse movie of FUSm fiber growth in the presence and absence of HspB8. The y-direction images are scaled by a factor of 3 to match the scale bar for the other maximum projection. The histograms/contrast are automatically set using the enhance contrast command in FIJI with 0.3% saturated pixels.

In order to investigate the molecular effect of HspB8 on the hardening of FUSm, we conducted quantitative XL-MS experiments in the presence of HspB8 and looked at crosslinks between FUSm peptides. We found that previously observed crosslink patterns for pure FUSm droplets, in particular upregulated crosslinks of the FUS-RRM, were still seen in the presence of HspB8 (Figure 3—figure supplement 1G, Supplementary file 4). However, interactions between both the RRM with RGG and the RRM with the ZnF decreased, as did links within the ZnF and between the ZnF and the NLS. Our data show that HspB8 binds to the FUS-RRM also during prolonged incubation times via the αCD::RRM interface established during condensation (Figure 3—figure supplement 1H & I). This suggests that HspB8 binds to the RRM domain in condensates and prevents it from forming aberrant interactions with other domains in the protein.

The disordered region of HspB8 directs the αCD into FUS condensates for chaperoning

sHSPs consist of an αCD and flanking regions that are thought to be intrinsically disordered (Sudnitsyna et al., 2012). Disorder prediction and circular dichroism analysis revealed that HspB8 is likely to be significantly more disordered than the closely related HspB1 (Figure 4—figure supplement 1A–D). To dissect the influence of the conserved αCD and the disordered IDR on the aging process of FUSm we designed SNAP fusion constructs where we fused either only the IDR, the αCD, or full-length HspB8 to a fluorescently labeled SNAP-tag (Figure 4A). While the IDR-SNAP fusion construct was still recruited to FUSm condensates, the αCD-SNAP variant no longer partitioned (Figure 4B). A decreased partitioning of the IDR-SNAP compared to the full-length construct indicated a contribution of the αCD (Figure 4B, Figure 4—figure supplement 1E). The IDR-SNAP construct was also not active in preventing FUSm fiber formation (Figure 4C), while the αCD-SNAP construct showed slight activity at high concentrations (Figure 4—figure supplement 1F). Similarly, in a FRAP assay, the αCD-SNAP construct showed slight activity, while IDR-SNAP was inactive in preventing FUSm gelation (Figure 4—figure supplement 1G). A partitioning analysis of these variants with droplets formed only by the LCD of FUS (AA1–211) under crowding conditions revealed a similar partitioning pattern as compared to the full-length FUSm (Figure 4—figure supplement 1H), indicating that the HspB8-IDR interacts with the FUS-LCD. In order to rule out potential perturbations of HspB8 domain activity by fusion to the SNAP moiety, we designed additional swap variants of HspB8 and the closely related HspB1 (Figure 4—figure supplement 1I) and all our experiments with the HspB8-HspB1 swap variants mirrored the results with the HspB8-SNAP fusions (Figure 4—figure supplement 1J-N).

Figure 4 with 1 supplement see all
Arginines within the disordered region of HspB8 direct the α-crystallin domain into FUS condensates for chaperoning.

(A) Overview of HspB8 truncation variants used in this study. FL (full-length HspB8 fused to a SNAP-tag), αCD (HspB8 alpha-crystallin domain [AA72–196] fused to a SNAP-tag), and IDR (HspB8-N-terminus [AA1–71] fused to a SNAP-tag). (B) Partitioning of 5 µM HspB8 SNAP constructs (1:20 mix of labeled:unlabeled) into 5 µM FUSm condensates. Scale bar is 10 µm. (C) Aging assay of 5 µM FUSm condensates in the absence (ctrl) and presence of 5 µM HspB8 truncation variants. Scale bar is 10 µm. (D) Partitioning of 5 µM HspB8 (1:20 mix of labeled:unlabeled) into condensates formed by 5 µM FUS wildtype (27 Y, WT) or a variant with a reduced number of tyrosines in its IDR (17 Y). (E) Location of Arg residues in the primary structure of HspB8. 10 Arg residues are located in the N-terminus of HspB8-WT (10 R). In the HspB8-0R variant, these Arg residues are replaced by Gly residues (0 R). (F) Partitioning of 5 µM HspB8-WT or HspB8-0R variant (1:20 mix of labeled:unlabeled) into condensates formed by 5 µM FUSm. (G) HeLa Kyoto cells expressing HSPB8-WT-3xmyc or HSPB8-0R-3xmyc from a plasmid were subjected to heat shock at 43.5°C for 1 hr. Cells were fixed and stained with myc and eIF4G specific antibodies. Merged image composed of eIF4G (green) and myc (red) signals is shown. (H) The onset of 5 µM FUSm fiber formation as a function of HspB8-0R concentration. IDR, intrinsically disordered region.

In summary, these results suggest that the IDR of HspB8 targets the αCD to condensates via interaction with the LCD of phase separated FUS and that the HspB8-αCD is the active domain in preventing FUS aging.

Arginines in the disordered region of HspB8 direct the αCD into FUS condensates

Recent studies identified interactions between tyrosines in the LCD and arginines in the RBD of FUS to be crucial for its ability to phase separate (Qamar et al., 2018; Wang et al., 2018; Schuster et al., 2020). Because HspB8 partitions into condensates formed only by the FUS-LCD (Figure 4—figure supplement 1N), we hypothesized that HspB8 could interact with tyrosines in the LCD of FUS. We tested the partitioning of HspB8 into a variant of FUS with a decreased number of tyrosines in the FUS-LCD. FUS wildtype (WT) has 27 tyrosines in its LCD. Mutating all of these to serines in the 0 Y variant abrogates phase separation, but the 17 Y FUS variant still undergoes phase separation (Wang et al., 2018; Figure 4D). Partitioning of HspB8 was significantly reduced for FUS condensates formed by the 17 Y variant (Figure 4D), suggesting that tyrosines in the FUS-LCD interact with HspB8. HspB8 has 10 arginines in its predicted IDR (Figure 4E). We exchanged these for glycines resulting in the 0 R variant of HspB8. This variant did not accumulate in FUSm droplets in vitro (Figure 4F) and did not partition into stress granules in cells, contrary to the behavior of HspB8-WT (Figure 4G). When we tested the 0 R variant of HspB8 in a FUSm aging assay we found that its ability to prevent fiber formation was completely abolished (Figure 4H).

RRM unfolding drives FUS aging and is rescued by HspB8

Next, we sought to test the consequences of the interaction between the HspB8-αCD and the FUS-RRM for FUS aging. To this end, we deleted the RRM in the variant FUSm∆RRM (∆AA285–371) and monitored its aging process in the presence and absence of HspB8 (Figure 5A, Figure 5—figure supplement 1A). First, FUSm aging was observed after 4 hr in the control condition, while co-incubation with HspB8 prevented the aging process over the time course of the experiment. Deletion of the RRM domain in FUSm∆RRM significantly slowed down aging and first aggregates were observed after 36 hr. Remarkably, HspB8 was not able to prevent aging of the FUSm∆RRM variant, indicating that HspB8 binding to the FUS-RRM is required for HspB8 to act as a chaperone for FUS. Our XL-MS data shows that the majority of inter-links between FUSm and HspB8 that were significantly increased within condensates in fact formed between the αCD of HspB8 and the RRM of FUSm (Figure 5B). Thus, while the RRM domain does not seem to be solely responsible for FUS aging, it significantly contributes to the initiation of the process.

Figure 5 with 1 supplement see all
RRM unfolding drives FUS aggregation and is rescued by HspB8.

(A) Aging process of molecular condensates containing either FUSm or the FUSm∆RRM (∆AA285–371) variant in the presence or absence of HspB8 monitored by fluorescence microscopy over time. Scale bar is 10 µm. (B) Inter-link abundances from reconstituted FUSm:HspB condensates. Plotted are the relative enrichment (droplet vs. non-droplet) for each unique crosslinking site (y-axis) sorted according to the known domain structure within FUSm and HspB8 (x-axis). Shown are only high confidence crosslinking sites (see Materials and methods for details) from five biologically independent sets of experiments (n=5; circles in different shades of gray). Crosslinking sites that were consistently upregulated or downregulated twofold or more (log2ratio≥1 or ≤−1 and FDR≤0.05) in at least two out of five biological replicate sets of experiments and in addition contained no opposing regulation in any replicate set were considered significant and are highlighted with a green (enriched in droplets) or red background rectangle (decreased in droplets). All other changes in crosslinking abundances were considered insignificant and are shown on gray background. The significance threshold of twofold enrichment is indicated as dashed red line. (C) Fluorescence microscopy images of FUSm and FUSm∆RRM variant during and after incubation under heat shock conditions. Samples were heated to 55°C for 10 min followed by a 5 min cool-down step to 25°C. Scale bar is 10 µm. (D) FUSm:HspB8 condensates were crosslinked in the presence (black) or absence (white) of a customized RNA oligonucleotide previously shown to bind to FUS (Maharana et al., 2018) and analyzed by LC-MS/MS (n=3; FDR≤0.05). RRM, RNA recognition motif.

The RRM domain of FUS is a folded domain in an otherwise disordered protein (Figure 5—figure supplement 1B). We suspected that RRM unfolding might serve as a seed for the formation of FUS aberrant conformations that would initiate FUS aggregation and fiber formation. To test this hypothesis, we performed a heat shock experiment to unfold the RRM domain of FUS (Figure 5C). The melting temperature of the isolated FUS-RRM has been reported to be 52°C (Lu et al., 2017). We prepared reactions of condensates formed by full-length FUS or FUSm∆RRM and incubated these for 10 min at 55°C to unfold the RRM. At this temperature, FUSm condensates were dissolved (Figure 5C). We then cooled down the reactions to 25°C and assessed the reactions by fluorescence microscopy. While full-length FUSm formed amorphous aggregates after cooling down from heat shock, the FUSm∆RRM variant condensed into spherical droplets (Figure 5C). This result strongly suggests that unfolding of the RRM domain is an integral part of the aging process and deletion of the RRM prevents temperature-induced aggregation of FUSm condensates.

It has been shown that RNA can bind to the FUS-RRM, prevent aging of FUS and dissolve condensates at high concentrations (Kramer et al., 2014; Maharana et al., 2018). Hence, we were wondering whether RNA exerts these effects by virtue of binding and stabilizing the RRM domain. We tested this by looking at competition between RNA and HspB8 binding to FUSm using XL-MS and crosslinked condensates of FUSm and HspB8 in the presence or absence of RNA. While the addition of RNA led to a significant decrease in the number of detected inter-links between FUSm and HspB8, it did not alter the number of intra-links within FUSm or HspB8 (Figure 5D and Figure 5—figure supplement 1C, Supplementary file 5). This result suggests that RNA and HspB8 can compete for binding to FUSm and indicates a similar mechanism by which they stabilize its RRM domain to prevent FUSm aging.

A disease-associated mutation interferes with HspB8 activity

Mutations of the lysine 141 residue in the αCD of HspB8 have been associated with Charcot-Marie Tooth disease, a currently incurable dominant autosomal disorder of the peripheral nervous system leading to muscular dystrophies (Irobi et al., 2004; Figure 6A). The mechanistic cause of the disease is still enigmatic, although experimental evidence indicates a decreased chaperone activity for HspB8-K141E (Kim et al., 2006; Carra et al., 2010; Carra et al., 2008). We introduced the K141E mutation into HspB8 and when we tested HspB8-K141E for localization to FUSm droplets, we found that it still partitioned into reconstituted FUSm droplets (Figure 6B). While the HspB8 WT was active in a FUSm aging experiment, HspB8-K141E could not prevent FUSm aging (Figure 6C) and when mixed with the WT, the mutant exerted a dominant-negative effect over the WT, preventing the WT from being active. By using FRAP, we found that the mutant was much less effective compared to the WT in keeping FUSm in a dynamic state (Figure 6D). Remarkably, the WT-mutant mix showed even lower chaperone activity, underlining the dominant-negative role of HspB8-K141E mutant over the WT (Figure 6D).

A disease-related mutation interferes with HspB8 activity.

(A) Location of the disease-related K141E mutation inside the αCD of HspB8. (B) Partitioning of 5 µM HspB8-K141E (1:20 mix of labeled:unlabeled) into condensates formed by 5 µM FUSm. Scale bar is 10 µm. (C) Aging assay of 5 µM FUSm condensates in the absence (ctrl) and presence of HspB8-WT, HspB8-K141E, or a 1:1 mix of WT and K141 mutant. Final chaperone concentrations in all reactions are 125 nM. Scale bar is 10 µm. (D) Kinetics of the aging process. Plotted are the initial slopes of the FRAP recovery curves for FUSm condensates in the absence (ctrl) and presence of HspB8-WT (red), HspB8-K141E (blue), or a 1:1 mix of WT and K141E mutant (cyan). (E) Equal amounts of FUSm:HspB8-K141E (left) or FUSm:HspB8-WT (right) were crosslinked under condensate inducing low salt conditions (75 mM NaCl). Experiments were carried out in triplicates and crosslinks were only considered, if they were identified in two out of three replicates with a deltaS<0.95, a minimum Id score≥20, and an ld score≥25 in at least one replicate (filtering was done on the level of the unique crosslinking site) and an FDR<0.05. The mutated site in HspB8-K141E is shown in red. Inter-links are shown in black and intra-links are shown in violet. Mono-links are shown with a flag, loop links with a pointed triangle, and homo-dimeric links with a loop. (F) Quantitative comparison of crosslinking patterns from HspB8-K141E and HspB8-WT condensates. Crosslinking sites that were upregulated or downregulated twofold or more (log2ratio≥1 or ≤−1 and FDR≤0.05) were considered significant and are highlighted in green (i.e., relative enrichment in FUSm:HspB8-K141E condensates) or red (i.e., relative decrease in FUSm:HspB8-K141E condensates). All other changes in crosslinking abundances were considered insignificant and are shown in gray background. αCD, α-crystallin domain; FRAP, fluorescence recovery after photobleaching.

We then performed XL-MS using the HspB8-K141E mutant. In comparison to HspB8-WT, the mutant showed an increased number of inter-links with FUSm in condensates, which suggests a stronger interaction between FUSm and the HspB8-K141E mutant (Figure 6E, Supplementary file 6). A quantitative analysis revealed that almost all mono-links within the RRM domain of FUSm were decreased upon binding of the HspB8-K141E mutant, suggesting that accessibility to these sites was hindered (Figure 6F, Supplementary file 6). Concomitantly, multiple intra-links within HspB8 bridging the N-terminus to the αCD domain were increased in the HspB8-K141E mutant (Figure 6F), an observation that is in line with a potential conformational change of the chaperone mutant upon FUS binding that brings these domains closer to each other (Sailer et al., 2018).

Discussion

In this study, we show that the molecular chaperone HspB8 can prevent a disease-associated aberrant phase transition that is mediated by the protein FUS. We show that HspB8 uses its disordered domain to partition into liquid FUS condensates and that HspB8 uses a similar molecular grammar as described previously for FUS (Wang et al., 2018). More specifically, arginine residues in the IDR of HspB8 interact with tyrosine residues in the FUS-LCD, thereby promoting the targeting of the HspB8-αCD into FUS condensates for chaperoning of the misfolding-prone RRM domain of FUS. This suggests a general principle for how the protein quality control machinery could be targeted to condensates in order to regulate misfolding-prone protein domains inside liquid condensates.

Despite the extensive work both in vivo and in vitro on proteins that phase separate, our current knowledge on how proteins are organized within condensates is limited and monitoring the transient interactions inside condensates has remained a major challenge to the field. In principle, proteomics and mass spectrometry should be an appropriate method to map condensate-specific interactions but reports using MS to study condensates remain scarce (Xiang et al., 2015; Kadavath et al., 2015; Sanulli et al., 2019). Recent studies demonstrate that proximity labeling in combination with MS is well suited to track the protein content of a specific molecular condensate (Markmiller et al., 2018; Youn et al., 2018), but falls short in charting direct PPIs or determining exact interaction sites. We and others showed previously that XL-MS is well suited to map PPIs and that relative changes in crosslinking as probed by quantitative XL-MS can provide a structural understanding of protein dynamics (Yu and Huang, 2018; Sailer et al., 2018; Walker-Gray et al., 2017; Patel et al., 2017; Iacobucci et al., 2020). Here, we adopt XL-MS to study condensates. In doing so we show with unprecedented molecular detail how protein contacts are formed within molecular condensates and demonstrate for the first-time condensate-specific client interaction.

Although the role of sHSPs in maintaining correct protein folding is intensively studied, up to now, the substrates of HspB8 have remained enigmatic (Mymrikov et al., 2017). Our crosslinking data suggests that HspB8 exerts its effect in part through the FUS-RRM domain. Misfolding of the RRM domain may represent the initial step on the pathway to forming a seed that subsequently promotes the nucleation of FUS fibrils. This may involve cross-beta sheet interactions of the LCDs via local concentration and LCD alignment. In this model, HspB8 would stabilize the fold of the RRM domain by binding to it, and by doing so maintain the liquid state of the condensates (Figure 7).

Unfolding of globular domains nucleates aberrant seeds for aggregation.

Proposed mechanism where unfolding of globular domains in otherwise disordered proteins nucleates aberrant seeds for aggregation. In this model, the unfolding of the RRM domain comprises the initial step to seed the conversion of FUS into an aberrant conformational space that consequently involves the beta-amyloid formation of the LCDs by rising their local concentration and potentially by sterically aligning them for nucleation. Molecular chaperones like HspB8 stabilize the fold of the RRM domain and maintain the dynamic liquid state of the condensate. LCD, low complexity domain; RRM, RNA recognition motif.

RRM domains are small folded entities that bind to single-stranded RNA. In humans, there are currently 745 RRM domains distributed over 446 proteins known to exist (Letunic and Bork, 2018). It has been proposed before that cells use RNA to regulate condensate formation (Maharana et al., 2018). Our data suggests that RNA and HspB8 can compete for their interaction with FUS. While this requires experimental validation in future studies, we hypothesize that some RRM domains require stabilization by binding to RNA, and in cases where no RNA is available, the chaperone HspB8 takes over this function and protects the RRM domain from unfolding and aggregation. Thus, it is a possibility that HspB8 has a general role in cell physiology in stabilizing RRM domains in condensates.

The changes we find in the inter-link patterns between FUSm and HspB8-WT or the neuropathy-causing mutant HspB8-K141E may appear counter-intuitive at first sight as far as they suggest a higher binding affinity of the mutant for FUS than the HspB8-WT. However, as sHSPs form oligomers subunit exchange between the WT and mutant HspB8 may influence the activity of the HspB8-WT. A heterodimer with lower activity than a WT homodimer could explain the differences in activity, and we do not exclude the possibility that HspB8 (which is present in mM concentrations inside the condensates, Figure 2—figure supplement 1C and D) will form higher-order oligomers which may enhance the mutant’s effect on the WT. Our data also point to shifts in conformation and dynamics of the RRM domain after condensation and during aging and within the HspB8-K141E mutant upon RRM binding. These shifts may differentially affect the fate of the bound substrate: stabilization of the FUSm native conformation by HspB8-WT versus loss of function by the HspB8-K141E mutant with subsequent FUSm aggregation. To date, mutations in the genes coding for HspB1, HspB3, HspB5, and HspB8 have been associated with neuromuscular diseases (Vendredy et al., 2020). To what extent similar mechanisms may also affect other HspB8 mutants therefore awaits further investigation.

A mechanism by which unfolding of globular domains is controlled by chaperones inside condensates may be a process of general importance (Franzmann and Alberti, 2019). Deletion of the RRM slows down hardening but does not stop it. This suggests other driving forces such as aberrant LCD-LCD interactions that may require other types of chaperone systems to prevent them. Our study also highlights the interplay between folded domains and IDRs. A changed environment after phase separation could destabilize folded domains and require chaperones to stabilize them. Such a mechanism would necessitate many domain-specific chaperones for stabilization inside condensates.

In summary, by adapting existing XL-MS workflows, we were able to monitor PPIs and protein dynamics inside reconstituted protein condensates, thus paving the way for a deeper and more detailed structural understanding of condensate formation and aberrant phase transitions. Our study shows with unprecedented molecular detail how protein contacts are formed between a chaperone and the folded RRM of its client protein inside a condensate and therefore suggests a blueprint for how chaperones could act to stabilize biomolecular condensates in cells. More generally, our data suggests that established principles of cellular organization, such as domain-specific PPI sites, also apply to the biochemistry inside molecular condensates. Here, further work is required to expand the resolution of crosslinking mass spectrometry by developing crosslinking chemistries optimized for intrinsically disordered domains and to augment its current ability to also target condensates in vivo.

Materials and methods

Key resources table
Reagent type
(species) or
resource
DesignationSource or
reference
IdentifiersAdditional
information
Cell line (Homo-sapiens)Hela Kyoto FUS-GFP BAC linePMID:26496610
PMID:28377462
5063
Cell line (Homo-sapiens)Hela Kyoto WTPMID:264966105067
Cell line (Escherichia coli)BL21-AI One ShotThermo Fisher ScientificCat# C607003Chemically competent E. coli
Chemical compound, drugDSS-H12/D12 (BisSulfoSuccinimidylSuberate)Creative Molecules IncCat# 001S
Chemical compound, drugN,N-Dimethylformamide (DMF)Sigma-AldrichCat# D4551
Chemical compound, drugAmmonium bicarbonateSigma-AldrichCat# 09830
Chemical compound, drugUreaSigma-AldrichCat# U5378
Chemical compound, drugDTT (1,4-Dithiothreito)Carl RothCat# 6908.4
Chemical compound, drugTrypsinPromegaCat# V5113
Chemical compound, drugTCEP (Tris(2-carboxyethyl)phosphine hydrochloride)Sigma-AldrichCat# C4706-2G
(CAS 51805-45-9)
Chemical compound, drugIodoacetamideSigma-AldrichCat# I1149-5G
(CAS 144-48-9)
Chemical compound, drugSep-Pak (C18)WatersCat# WAT054960
Recombinant DNA reagentFUS-GFP (plasmid)PMID:26317470FUS-GFP expression in Sf9 cells
Recombinant DNA reagentFUS-G156E-GFP (FUSm) (plasmid)PMID:26317470FUS-G156E-GFP expression in Sf9 cells
Recombinant DNA reagentFUS-G156E-K9-GFP (FUSm_K9) (plasmid)This paperFUS-K9-GFP expression in Sf9 cells
Recombinant DNA reagentFUS-G156E-ΔRRM-GFP (FUSmΔRRM) (plasmid)This paperFUS-G156E-ΔRRM-GFP expression in Sf9 cells
Recombinant DNA reagentFUS-17Y-GFP (plasmid)This paperFUS-GFP-17Y expression in Sf9 cells
Recombinant DNA reagentFUS-LCD-GFP (plasmid)PMID:29961577FUS-LCD-GFP expression in Sf9 cells
Recombinant DNA reagentHspB8-WT (plasmid)PMID:15879436HspB8-WT expression in E. coli
Recombinant DNA reagentHspB8-K141E (plasmid)This paperHspB8-K141E expression in E. coli
Recombinant DNA reagentHspB8-SNAP (FL) (plasmid)This paperHspB8-SNAP expression in E. coli
Recombinant DNA reagentHspB8-IDR-SNAP (IDR) (plasmid)This paperHspB8-IDR-SNAP expression in E. coli
Recombinant DNA reagentHspB8-αCD-SNAP (αCD) (plasmid)This paperHspB8-αCD-SNAP expression in E. coli
Recombinant DNA reagentSNAP (plasmid)This paperSNAP expression in E. coli
Recombinant DNA reagentHspB8-IDR-HspB1-αCD (IDR8αCD1) (plasmid)This paperHspB8-IDR-HspB1-αCD expression in E. coli
Recombinant DNA reagentHspB1-IDR-HspB8-αCD (IDR8αCD1) (plasmid)This paperHspB1-IDR-HspB8-αCD expression in E. coli
Recombinant DNA reagentHspB8-0R (plasmid)This paperHspB8-0R expression in E. coli
Recombinant DNA reagentHspB8-WT-3xmyc (plasmid)This paperHspB8-WT-3xmyc expression in human cells
Recombinant DNA reagentHspB8-0R-3xmyc (plasmid)This paperHspB8-0R-3xmyc expression in human cells
AntibodyAnti-c-myc (monoclonal)Santa Cruz BiotechnologyClone 9E10IF(1:100)
AntibodyAnti-eIF4G (monoclonal)Santa Cruz BiotechnologyClone H-300IF(1:100)
AntibodyAnti-mouse Alexa Fluor 594 (monoclonal)Thermo Fisher ScientificA-21203IF(1:1000)
AntibodyAnti-rabbit Alexa Fluor 594 (monoclonal)Thermo Fisher ScientificA-21206IF(1:1000)
Software, algorithmxQuest 2.1.3PMID:24356771http://proteomics.ethz.ch/cgi-bin/xquest2_cgi/download.cgi
Software, algorithmxProphet 2.1.3PMID:24356771http://proteomics.ethz.ch/cgi-bin/xquest2_cgi/download.cgi
Software, algorithmxTract 1.0.2PMID:26501516http://proteomics.ethz.ch/cgi-bin/xtract_cgi/index.cgi
Software, algorithmxiNETPMID:25648531http://crosslinkviewer.org/
Software, algorithmpython 3.7.2 and 3.7.6https://python.org
Software, algorithmpandas 1.0.3https://pandas.pydata.org
Software, algorithmaltair 4.1.0Altair Developers, 2020https://altair-viz.github.io
Software, algorithmseaborn 0.9.0https://seaborn.pydata.org
Software, algorithmFijiPMID:22743772https://imagej.net/software/fiji/
OtherSuperdexPeptide 3.2/30GE HealthcareCat# 29-0362-31
OtherAcclaim PepMap RSLCThermo Fisher ScientificCat# P/N 164943
OtherEASY-nLC 1200 systemThermo Fisher ScientificLC140
OtherOrbitrap FusionTribridMass SpectrometerThermo Fisher Scientific
OtherDeposited Data:
MS raw files
PRIDE https://www.ebi.ac.uk/pride/PXD021114
PXD021115

Protein expression and purification

Request a detailed protocol

FUS-G156E-GFP (FUSm) was purified as described (Patel et al., 2015). HspB8 and corresponding variants were subcloned in a pET11d vector as N-terminal 3C protease-cleavable GST fusion proteins. Fusion proteins were expressed and purified from BL21 Codon RIL (Stratagene). Expression was induced by adding 0.15 mM IPTG for 4.5 hr at 37°C. Bacteria were lysed in 1× PBS, 5 mM DTT, 1 mM EDTA with EDTA-free Protease inhibitors tablet (Roche), and GST purified. Eluates were dialyzed with a 3500 Da MWCO membrane against 1× PBS, 5 mM DTT, and cleaved with PreScission protease. Cleaved off GST was removed by reverse GST purification. HspB8 proteins were subjected to ResourceQ ion-exchange chromatography, concentrated, dialyzed to HspB8 buffer (20 mM Tris, pH 7.4, 20 mM KCl, and 1 mM DTT), and validated by MS.

In vitro experiments

Request a detailed protocol

Frozen aliquots of FUSm were thawed for 10 min at room temperature (RT), cleared from aggregates by centrifugation for 1 min at 21,000×g using a 0.2 µm spin filter device. Molecular aging experiments were performed according to Alberti et al., 2018 at 5 µM FUSm in reaction buffer (20 mM Tris-HCl, pH 7.4, 75 mM KCl, 0.75% Glycerol, and 1 mM DTT). FRAP experiments were performed and analyzed according to Patel et al., 2015 at 5 µM FUSm in reaction buffer. For partitioning experiments, HspB8 and variants thereof were labeled with Cyanine-3-monosuccinimidyl ester (AAT bioquest, ABD-141) at equimolar ratio in HspB8 buffer and excess dye was removed by dialysis against HspB8 buffer with 1 mM DTT. Labeled HspB8 was mixed with unlabeled protein at a molar ratio of 1:20 and 5 µM FUSm was mixed with 5 µM total HspB8 in reaction buffer. Samples were applied into an imaging chamber with a coverslip passivated with polyethylene glycol. Fluorescence and DIC microscopy were performed on a confocal spinning disk microscope. Images were analyzed using Fiji software (Schindelin et al., 2012).

Optical tweezer experiments

Request a detailed protocol

To characterize the material state of FUSm condensates with or without HspB8, controlled fusion experiments were performed in a custom-build dual-trap optical tweezer microscope (Patel et al., 2015; Jahnel et al., 2011). 5 μM FUSm condensates were phase-separated at T0 in reaction buffer with or without 20 μM HspB8 and immediately applied to a sample chamber. Two condensate droplets were trapped in two optical traps of the same trap stiffness at low overall light intensity to minimize local heating. With the first trap stationary, the second trap was moved to bring the droplets into contact and initiate coalescence, after which both traps were kept stationary. Laser signals and bright-field microscopy images were simultaneously recorded. Signals from the two traps—equal in magnitude, opposite in sign—were combined into the differential signal, from which coalescence relaxation times were deduced (Wang et al., 2018). To quantify the coalescence dynamics and account for droplets of different sizes, the relaxation time was normalized by the geometric radius of the two fusing droplets. Successful droplet coalescence was scored as yes (Banani et al., 2017) or no (0) depending on whether the process resulted in a near-spherical shape of the final droplet within 60 s. This duration was an order of magnitude longer than the earliest coalescence relaxation times under all conditions. Coalescence success/failure data of FUSm without HspB8 were fit with a logistic regression model to estimate the half-life of liquid-like FUSm condensates.

Time-lapse microscopy of fiber growth

Request a detailed protocol

FUSm was aged in a centrifuge tube for >24 hr to allow most of the protein to convert to fibrous/aged material. A small amount of aged material was flowed into a custom-built flow cell which includes upper and lower glass surfaces; the bottom glass surface was passivated with polyethylene glycol. After incubation, the chamber was flushed with freshly formed FUSm condensates in reaction buffer either in the presence or absence of 20 µM HspB8. An image stack representing a volume of approximately 100 µm3 and a voxel size of 0.1 µm×0.1 µm×0.3 µm was acquired every 30 min using a spinning disk confocal equipped with a glycerol immersion 60× objective. In the resulting image stacks, fibers tend to be relatively dim with bright cores. To produce an image that allows for good visualization of the process of fiber growth, we smoothed each stack and subsequently applied an enhanced local contrast method (CLAHE). This method uses tiles throughout the image and calculates an appropriate contrast for each tile. We used CLAHE implemented in ImageJ with a block size of 30. For each stack, we create a maximum projection of the resulting stack that produces a single image. Finally, we used an image registration method (using the stackreg plugin in ImageJ) to remove any small translational drift which occurs through the process. The resulting movie is shown as Video 1.

Image analysis to identify droplets and fibers

Request a detailed protocol

The identification of fibers and droplets in images was carried out using custom-made scripts in MATLAB. In short, each image is resized eight times using a bicubic interpolation. An image is subsequently automatically thresholded using Otsu’s method through the imthresh command. Objects are identified as regions of connected pixels. Any objects which intersect the picture border or are very small are discarded from further analysis. Fibrous objects are identified as either objects with an eccentricity above 0.7 or, if the eccentricity is low, as objects that have a roughness above 6.4 pixels. The eccentricity is found by fitting an ellipse to a connected region and is defined as the ratio of the distance between the foci of the ellipse and its major axis length (implemented using the eccentricity argument in the regionprops command). To determine the roughness, each object is fit by a circle. The roughness is defined as the mean distance between the object border and the circular fit. Objects with low surface roughness as well as low eccentricity were considered droplets. All objects and their subsequent classification are also reviewed finally by eye to ensure that the parameters for the images are set properly.

Immunostaining of sHSPs in stressed cells

Request a detailed protocol

HeLa Kyoto WT (Identifier 5067) and HeLa Kyoto FUS-GFP (Identifier 5063) BAC cells were cultured in Dulbecco's modified Eagle's medium containing 4.5 g/L glucose (Gibco Life Technologies) supplemented with 10% fetal bovine serum, 100 U/ml Penicillin+100 μg/ml Streptomycin. 250 μg/ml Geneticin (all Gibco Life Technologies) was added to the HeLa Kyoto FUS-GFP BAC cells. Cells were maintained at 37°C in a 5% CO2 incubator (Thermo Fisher Scientific). HeLa Kyoto FUS-GFP BAC cells were described previously (Mateju et al., 2017). For immunostaining of HspB8-WT and HspB8-0R in stress granules, HeLa Kyoto cells were transfected with 200 ng of plasmids coding for HspB8-0R-3xmyc or HSPB8-WT-3xmyc using Lipofectamine 2000 (Life Technologies) following the manufacturer's instructions. 24 hr post-transfection, cells were subjected to heat shock in a water bath at 43.5°C for 1 hr. Cells were fixed with 3.7% formaldehyde for 9 min at RT and permeabilized with acetone for 5 min at −20°C and stained with c-Myc (9E10, Santa Cruz Biotechnology) and eIF4G (H-300, Santa Cruz Biotechnology) specific antibodies. Secondary antibodies used were anti-mouse Alexa Fluor 594 (A-21203, Thermo Fisher Scientific) and anti-rabbit Alexa Fluor 488 (A-21206, Thermo Fisher Scientific).

Crosslinking of molecular condensates

Request a detailed protocol

Frozen aliquots of FUSm and FUSm_K9 protein stored in 50 mM Tris-HCl pH 7.5, 500 mM KCl, 5% Glycerol, and 1 mM DTT were thawed for 10 min at RT, cleared from aggregates by centrifugation for 1 min at 21,000×g using a 0.2 µm spin filter device and subsequently diluted in water to a low salt solution (final concentration of 75 mM KCl) to induce phase separation or into a high salt solution (final concentration of 500 mM KCl) to prevent phase separation. In order to reconstitute FUSm:HspB8 condensates HspB8-WT or HspB8-K141E mutant were added to FUSm condensates at equal mass ratio and subsequently incubated on ice for 10 min to allow for sufficient mixing. Molecular condensates were crosslinked by addition of 0.9 mM H12/D12 DSS (Creative Molecules) (Figure 2E, Figure 2—figure supplement 1I), 1.9 mM (Figures 1B, C, 6E and F, Figure 2—figure supplement 1F and G), or 1.5 mM (Figure 5D) at a molar ratio crosslinker to lysines of ~3.6, ~2.3, or ~3.6, respectively, for 30 min at 37°C shaking at 650 rpm in a Thermomixer (Eppendorf). Protein samples were quenched by the addition of ammonium bicarbonate to a final concentration of 50 mM and either directly evaporated to dryness or after an additional centrifugation step for 60 min at 21,000×g in order to separate the dense phase of the condensates from the dilute phase. The dilute phase containing supernatant was transferred to a fresh tube and both phases were evaporated to dryness. Thus, samples were subjected to MS analysis either directly after adjustment of the high salt/low salt solution containing mixtures of essentially dilute phase or dense phase of the condensates (Figures 1B, C, 5B, 6E and F, Figure 2—figure supplement 1F & G, Figure 3—figure supplement 1G) or after an additional separating step by centrifugation fully separating reconstituted droplets that had formed under low salt solution from the remaining dilute phase as described above (Figures 2E, 5B and D, Figure 2—figure supplement 1I, Figure 3—figure supplement 1G). For a detailed description, also of the lysine-rich variant FUS_K9 see also legend Figure 2—figure supplement 1G.

Crosslinking coupled to mass spectrometry (XL-MS)

Request a detailed protocol

Crosslinked samples were processed essentially as described (Leitner et al., 2014). In short, the dried protein samples were denatured in 8 M Urea, reduced by the addition of 2.5 mM TCEP at 37°C for 30 min, and subsequently alkylated using 5 mM Iodacetamid at RT for 30 min in the dark. Samples were digested by the addition of 2% (w/w) trypsin (Promega) overnight at 37°C after adding 50 mM ammonium hydrogen carbonate to a final concentration of 1 M urea. Digested peptides were separated from the solution and retained by a C18 solid-phase extraction system (SepPak Vac 1cc tC18 [50 mg cartridges, Waters]) and eluted in 50% ACN, 0.1% FA. After desalting the peptides were evaporated to dryness and stored at −20°C. Dried peptides were reconstituted in 30% ACN, 0.1% TFA, and then separated by size exclusion chromatography on a Superdex 30 increase 3.2/300 (GE Life Science) to enrich for crosslinked peptides. The three early-eluting fractions were collected for MS measurement, evaporated to dryness, and reconstituted in 5% ACN, 0.1% FA. Concentrations were normalized by A215 nm measurement to ensure equal amounts of dilute and dense phase and peptides separated on a PepMap C18 2 µM, 50 µM×150 mm (Thermo Fisher Scientific) using a gradient of 5–35% ACN for 45 min. MS measurement was performed on an Orbitrap Fusion Tribrid mass spectrometer (Thermo Fisher Scientific) in data dependent acquisition mode with a cycle time of 3 s. The full scan was done in the Orbitrap with a resolution of 120,000, a scan range of 400–1500 m/z, AGC Target 2.0e5, and injection time of 50 ms. Monoisotopic precursor selection and dynamic exclusion were used for precursor selection. Only precursor charge states of 3–8 were selected for fragmentation by collision-induced dissociation using 35% activation energy. MS2 was carried out in the ion trap in normal scan range mode, AGC target 1.0e4, and injection time of 35 ms. Data were searched using xQuest in ion-tag mode. Carbamidomethylation (+57.021 Da) was used as a static modification for cysteine. As database the sequences of the measured recombinant proteins along with reversed and shuffled sequences were used for the FDR calculation by xProphet.

Experiments were carried out in three biologically independent sets of experiments (meaning separate batches of expressed protein). For one set of experiments, each sample was independently crosslinked in triplicates and each of these was measured in technical duplicates. Crosslinks were only considered, if they were identified in two out of three replicates with a deltaS<0.95, a minimum Id score≥20, and an ld score≥25 in at least one replicate (filtering was done on the level of the unique crosslinking site), and an FDR≤0.05 as calculated by xProphet for at least one replicate.

Quantitation of crosslinked peptides from condensates (qXL-MS)

Quantitation

Request a detailed protocol

Initial processing of identified crosslinked peptides for quantitation was performed essentially as described (Sailer et al., 2018). In short, the chromatographic peaks of identified crosslinks were integrated and summed up over different peak groups for quantification by xTract (taking different charge states and different unique crosslinked peptides for each unique crosslinking site into account). Only high-confidence crosslinks that fulfilled the above introduced criteria were selected for further quantitative analysis.

The resulting bagcontainer.details.stats.xls file was used as an input for in-house scripts developed for this manuscript. The bag container contains all experimental observations on a peptide level as extracted by xTract (e.g., peptide mass, charge state, the extracted MS1 peak area, and any violations assigned by xTract). Missing observations were replaced by imputation with random values drawn from a normal distribution based on our experimental distribution. Here, the log-normal experimental distribution of measured MS1 peak areas was converted to a normal distribution by log2-conversion. Of the resulting normal distribution, the mean and standard deviations were determined. The mean was shifted downward while the width was decreased in order to obtain the distribution to draw imputed values from, following the same procedure and parameters as described for Perseus (Tyanova et al., 2016) (width: 0.3 and down shift: 1.8).

Data were additionally filtered using a light-heavy filter as described (Walzthoeni et al., 2015) and peptides with a light-heavy log2ratio<−1 or >1 were excluded from further analysis. Experiments were normalized by their mean MS1 peak area using the mean of all experiments as reference. The ratio of each experiment compared to the reference was computed and all observed MS1 areas were multiplied by this experiment-specific ratio to receive the same mean for all experiments. In addition, replicates were normalized within each experiment. Thus, the mean of each biological and technical replicate within an experiment was shifted to the mean of an experiment in the same way as described above.

In the next step, log2ratios were calculated as the difference between the log2-converted MS1 peak areas (instead of the ratio). Here, the MS1 area for each experiment was shifted into a log2 scale after all summing operations but before taking any means, allowing us to calculate meaningful standard deviations between biological replicates and to avoid the influence of outliers in the original log-normal scale. P-value calculations were otherwise performed as described (Walzthoeni et al., 2015), with one notable exception: MS1 peak areas were not split by technical replicates in order to avoid artificially improved p-values with increasing numbers of technical replicates. FDR values were p-values corrected for multiple testing, following the Benjamini–Hochberg procedure.

Significance

Request a detailed protocol

Only high-confidence crosslinking sites (see above) that were detected reliably and consistently with a deltaS<0.95, a minimum Id score≥20, and a ld score≥25 in at least one replicate (filtering was done on the level of the unique crosslinking site), and an FDR≤0.05 were used for quantitation. Changes in crosslinking abundances were throughout the paper quantified against the dilute phase (i.e., relative enrichment within droplets is shown in green; relative decrease in red). Only crosslinking sites that were upregulated or downregulated twofold or more (log2ratio≥1 or ≤−1 and FDR≤0.05) in at least two biological replicate sets of experiments and in addition contained no opposing regulation in any replicate set were considered significant.

Time-resolved quantitative crosslinking coupled to mass spectrometry

Request a detailed protocol

Fresh FUSm condensates formed under low salt (75 mM KCl) conditions were left shaking at 650 rpm in a Thermomixer (Eppendorf) at 28°C and monitored by fluorescence microscopy at regular intervals until conversion into fibers. The stock solution was aliquoted prior to dilution into low salt buffer to induce condensation and aliquots (n=3) were crosslinked for 5 min and flash-frozen in liquid nitrogen at indicated time points: T1–T6 (0 hr, 20 min, 40 min, 1 hr, 1 hr 20 min, 1 hr 40 min; condensates), T7–T9 (2 hr 20 min, 2 hr 40 min, 3 hr; gels), and T10–T11 (12 hr and 24 hr; fibers). While thawing, 1M ammonium bicarbonate was added to a final concentration of 50 mM and samples were evaporated to dryness. Crosslinks were subsequently identified and quantified exactly as described above.

Visualization of Crosslink data

Request a detailed protocol

In order to both validate and visualize the crosslink information, multiple in-house scripts have been written. The visualization scripts either interface directly with the quantitation script described above or use xTract-like output for an input. In either case, the filtering and significance criteria as described above for the quantitation script were used. Crosslink data were transformed via pandas (version 1.0.3) for assessment. Figures 1B and 5B, Figure 3—figure supplement 1G were created with altair (version 4.1.0) running on Python version 3.7.6. Figure 1C and Figure 1—figure supplement 1A (left and right Panel) were created with seaborn (version 0.9.0) running on python (version 3.7.2). Figure 1—figure supplement 1A (middle panel) was created using the in-built pandas dataframe plot functions.

RNA competition assay

Request a detailed protocol

FUSm:HspB8 condensates were prepared as described and either incubated with RNA oligonucleotide PrD (Maharana et al., 2018) in sub-stoichiometric amounts (three times molar excess of FUSm) or equal volume of water. Samples were checked by microscopy before crosslinking to ensure that the addition of RNA did not dissolve the condensates. The dense phase of the condensates was separated from the dilute phase by centrifugation and the concentration normalized prior to MS measurement as described above.

Data availability

All data generated or analysed during this study are included in this published article (and its supplementary information files). The MS data (raw files, xQuest, xTract and in-house quantitation output files) have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD021114 and PXD021115.

The following data sets were generated
    1. Boczek EE
    (2021) PRIDE
    ID PXD021114. HspB8 prevents aberrant phase transitions of FUS by chaperoning its folded RNA binding domain.
    1. Boczek EE
    (2021) PRIDE
    ID PXD021115. HspB8 prevents aberrant phase transitions of FUS by chaperoning its folded RNA binding domain.

References

Decision letter

  1. Volker Dötsch
    Senior and Reviewing Editor; Goethe University, Germany
  2. Henning Urlaub
    Reviewer; University Medical Center Göttingen, Germany
  3. Justin LP Benesch
    Reviewer; University of Oxford, United Kingdom
  4. Volker Dötsch
    Reviewer; Goethe University, Germany

Our editorial process produces two outputs: i) public reviews designed to be posted alongside the preprint for the benefit of readers; ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Acceptance summary:

The transition from a more liquid like phase to a solid phase of liquid-liquid phase separated condensates is an important disease mechanism. Here the authors use an innovative approach to study the effect of chaperones to counteract this aging process which is of great importance for understanding the molecular details of aggregation prone diseases. The methodological novelty of this approach is the use of protein-protein crosslinking to study the conformation of the RNA-binding domain of FUS in condensates in the absence and presence of HspB8.

Decision letter after peer review:

Thank you for submitting your article "HspB8 prevents aberrant phase transitions of FUS by chaperoning its folded RNA binding domain" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by Volker Dötsch as the Senior and Reviewing Editor and Reviewer #3. The following individuals involved in review of your submission have agreed to reveal their identity: Henning Urlaub (Reviewer #1); Justin L.P. Benesch (Reviewer #2).

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1) How is it possible to discriminate between intramolecular and intermolecular crosslinks, especially when the crosslinks were created within aggregates of proteins such as, in this case, FUS? Does the RRM indeed change its conformation, or does it simply interact with RRMs of other FUS molecules? Is the spacer of DSS not too long to allow any conclusion about the structure of such small domains as the RRM or Zn-finger, in particular for a protein prone to aggregation?

2) The authors titrated the crosslinker according to the numbers of lysine residues present in the two proteins HspB8 and FUS. They should discuss, or at least state, the concentration of the crosslinking reagent within the condensates compared with the concentration outside the condensate phase; this statement should include the correlation between the concentration of the crosslinker in the condensate and the protein concentration(s) inside and outside the condensates. (The authors used a 2.7 fold molar excess of crosslinker over lysine residues in the proteins – however, they should also state the concentrations as molarity.) A very high concentration of a chemical crosslinker could in principle grossly distort the structure of a protein, as has been observed in several studies; this might diminish the value of crosslinking as an indicator of protein condensation, and the authors should address this. Monitoring crosslinking in a concentration-dependent manner would have also been beneficial.

3) The exclusive use of a lysine-reactive crosslinker limits the resolution of monitoring intra- and inter-protein interactions. Although the authors state explicitly that they use a lysine-directed crosslinker solely because there are no lysine residues in the disordered regions of FUS, it is not clear why the authors did not also use crosslinkers reactive toward groups other than the amino group. Such crosslinkers could possibly have been useful to study protein interactions that are salt-sensitive. Indeed, the LCD of FUS is not suitable for applying lysine-reactive or carboxy-reactive crosslinkers; better suited to this would be (for example) ruthenium (II) tris-bipyridine, which connects tyrosine residues, and it is precisely tyrosine(s) in the LCD that seem(s) to be crucial for protein condensation. Furthermore, protein-protein crosslinking by UV light has been described and is attributed to covalent Y-Y links.

In particular: (i) Have the authors considered the use of different endoproteinases (such as chymotrypsin) in order to obtain a comprehensive sequence coverage of crosslinked peptides? (ii) Why have the authors not taken into account serine, threonine and tyrosine as crosslinking sites of DSS. It has been reported that DSS is also reactive toward these amino acids.

Related: The LCD of FUS contains the N-terminus of the protein – a primary amine. Are no cross-links seen to this?

4) Figure 5A: droplets formed by FUSm-ΔRRM are significantly larger than those formed by FUSm. Addition of Hsp8B seem to make them larger still (clearly obvious for the "36h" time point). Some questions are raised: What fraction of the FUSm is present the droplets/fibres and what fraction remains in solution? Is HspB8 present in the condensates as well? Complementary experiments using labelled HspB8 are necessary to clarify this.

5) The hypothesis that RNA and HspB8 compete for the interaction with FUS is interesting; however, the data supporting this are preliminary and the question requires more thorough investigation for example by pulldown experiments.

6) Can the authors rule out that the differences seen between FUS in low and high salt is not due to the salt concentration per se, but due to the phase separation? While unlikely, but it could be that DSS does not penetrate the FUS-rich phase, and cross-links are only observed between species in the FUS-poor phase (which still contains FUS, albeit at lower concentrations). Can the authors rule this out?

7) The ACD-snap and IDR-snap experiments are a bit confusing – the ACD doesn't partition, yet appears to have some activity? While the IDR region doesn't partition nearly as well as the full-length, the N-terminal regions of sHSPs are frequently unstable c.f. aggregation – are the authors sure that the IDR-snap construct is stable – and if not, might this explain the difference?

8) HSPB8 likes to dimerize. Nonetheless, it is hard to explain the "dominant negative" effect seen in the mixture of WT/mutant. Do the authors have an explanation – perhaps due to some higher-order oligomerisation..? Or difference in partitioning..?

Related: While most of the experiments described in tis manuscript provide detailed structural, mechanistic information, the paragraph on the CMT mutant HspB8-K141E is less insightful and remains pretty vague. It seems counterintuitive that stronger binding of the mutant prevents the aging of the droplets and the transition to a more solid-like phase. Here more data or at least a more detailed discussion with a reasonable model would be helpful.

9) The authors analysed the data using the search engine xQuest, which requires a pair of non- and isotopically labelled crosslinkers for confident identification of crosslinked peptides. The data already acquired are probably unsuitable for other crosslink search engines (35 ms ion accumulation time and ion-trap analyser for MS2). In general, I consider the crosslinking data acquired in this work by CID in the ion trap to be of insufficient quality. Have the authors attempted to acquire a data set with high-resolution MS2 and to use more modern search engines with relaxed crosslinker specificity?

https://doi.org/10.7554/eLife.69377.sa1

Author response

Essential revisions:

1) How is it possible to discriminate between intramolecular and intermolecular crosslinks, especially when the crosslinks were created within aggregates of proteins such as, in this case, FUS? Does the RRM indeed change its conformation, or does it simply interact with RRMs of other FUS molecules? Is the spacer of DSS not too long to allow any conclusion about the structure of such small domains as the RRM or Zn-finger, in particular for a protein prone to aggregation?

This is an important remark by the reviewer. We cannot generally discriminate between intra crosslinks and interlinks between homo-oligomers and we also did not want to be suggestive of this; we can however discriminate for a specific subset of those.

We had tried to get this important point across in the legend to Figure S1A:

“XL-MS cannot readily discriminate if a crosslink has formed within one polypeptide chain (defined as intra-link, vide supra) or between homodimers or even higher oligomers of the same protein. This is usually not a problem, but in the case of the high protein concentrations within condensates it may play a role. However, as we detect virtually all shown intra-links within FUSm and HspB8 also under the relatively low-concentration regime of the dilute phase, it is fair to assume that at least a major part of the observed changes occurs within intra-links as usually defined – e.g. occurring within one FUSm polypeptide chain – as we assume in the current version of the manuscript. For some specific intra-links, we do however know that they must have occurred between different molecules of the same protein; these are crosslinks between overlapping peptides whose sequence is unique within the protein and that must therefore originate from different copies of the same protein (homodimeric link).”

These dimeric links are also indicated by a “d” in all figures – see for example Figure 1B.

At least this subset of homodimeric links – some of which we can follow in detail during both condensation and aging (see Figure 1B and 1C) – tells us that there must be heightened contacts between different RRM molecules within the dense phase of the condensates (which was admittedly also not an entirely unexpected result, given the high concentration of the condensates). Moreover, we also detect virtually all links specified as intralinks already in the dilute phase, suggesting that their increase can at least not only be due to heightened RRM contacts between different FUS molecules in the dense phase of the condensates. The same line of arguments can be applied to the aging time-course, as we observe here a decrease in dimeric intra-links and have also detected virtually all intra-links both in the dilute and dense phase (see Figure S1D), which again indicates that they should at least partially have emanated from monomeric intra-links.

We would also like to point out that we are very aware of the fact of that molecular condensates are particularly critical protein assemblies that require extra care. This is why we have analyzed critical experiments in high redundancy, e.g. as biological triplicate experiments, that each consist of 3 independently crosslinked replicates (which were additionally all measured as technical duplicates) (see Figure 2E).

We also fully agree with the reviewer that it is not possible to directly assign a specific conformational status to a crosslinking pattern, even though our work has demonstrated that changes in intralink pattern can reflect conformational changes (PMID: 30361475). This is why we tried very carefully throughout our manuscript to NOT directly assign a specific conformation status with the observed change in crosslinking pattern within the RRM.

For example:

“This suggests that there are augmented contacts within the RRM domain, indicative of a structural change. In addition, there was an increase in homo-dimeric links between RRM domains, indicative of interactions between RRM domains of different FUSm molecules.”

However, our main point is, that the majority of changes in crosslink abundance that we observe takes place WITHIN the RRM.

This fact, in combination with all the follow-up biochemical and molecular characterization on the folding status of the RRM in Figure 5 and 6, lead us to conclude that there is likely indeed a conformation change taking place in the RRM during condensation and in particularly during aging – which can be prevented by binding of HspB8; which is again in line with our crosslinking data, as we for example show in Figure S3I that the crosslinking pattern within the RRM does NOT change after binding of HspB8.

We also respectfully disagree that the linker that was employed in this study is too long to allow any conclusion about the structure of such small domains as the RRM or Zn-finger. We know from previous work that the linker used in this study covers distances up to 30 Å well, with a particular focus on distances from 12 to 15 Å (PMID: 22286754).

These are also the likely distances to be covered within the RRM and between HspB8 and FUS- RRM and FUS ZnF, as for example mapping our identified crosslinks to the existing NMR structure of the RRM of FUS (PDB 2LCW) demonstrates an excellent fit (i.e. we can map 8 out of 8 identified crosslinks, covering distances from 12 to 31 Å) and shows that also small distances can be covered by our crosslinker DSS H12/D12 (Author response figure 1).

Author response image 1
Mapping identified cross-links identified using the crosslinker DSS H12/D12 onto the NMR structure of the RRM of FUS (PDB 2LCW).

2) The authors titrated the crosslinker according to the numbers of lysine residues present in the two proteins HspB8 and FUS. They should discuss, or at least state, the concentration of the crosslinking reagent within the condensates compared with the concentration outside the condensate phase; this statement should include the correlation between the concentration of the crosslinker in the condensate and the protein concentration(s) inside and outside the condensates. (The authors used a 2.7 fold molar excess of crosslinker over lysine residues in the proteins – however, they should also state the concentrations as molarity.) A very high concentration of a chemical crosslinker could in principle grossly distort the structure of a protein, as has been observed in several studies; this might diminish the value of crosslinking as an indicator of protein condensation, and the authors should address this. Monitoring crosslinking in a concentration-dependent manner would have also been beneficial.

We apologize for this oversight and have now specified and corrected the used molar excess of added crosslinker for each experiment and have also added molar concentrations (see updated experimental procedures). It is unfortunately not possible to directly measure the concentration of the crosslinker within the dense phase of the condensate and the dilute phase. We are nevertheless confident that this has not been a problem, as our experiments demonstrate that we obtain a similar amount of intralinks within the dense phase of the condensate and the dilute phase (see Figure 2E, Figures S2 F, G and E), which is a good indication that sufficient amounts of crosslinker were present in either of the phases.

We also agree with the reviewer that there are reports showing that an excess of crosslinker can lead to distortions in protein conformation. However, we respectfully disagree that high concentrations of a chemical crosslinker regularly or even generally distort the structure of a protein. More importantly, we did not employ high doses of crosslinker in our study, as we were operating within a regime of ~ 1 to 2 mM crosslinker (see updated experimental procedures for details) and such a conventional and widely accepted crosslinker concentration range (PMID:31045356). Moreover, as the protein concentration within the dense phase of the condensates is even higher (Figures S2C and S2D), the likelihood of possible distortions is even lower there.

As suggested by the reviewer, we have now monitored crosslinking in a concentration-dependent manner and our data shows that there are no apparent differences in crosslink behavior and crosslinking yields within the crosslinker concentration range that was used in this study – i.e. 1 to 2 mM DSS (Author response image 2).

Author response image 2
Monitoring crosslinking in a concentration-dependent shows no apparent differences in crosslink behavior and crosslinking yield in the range used in this study, i.

e. 1 to 2 mM DSS (see updated experimental procedures).

3) The exclusive use of a lysine-reactive crosslinker limits the resolution of monitoring intra- and inter-protein interactions. Although the authors state explicitly that they use a lysine-directed crosslinker solely because there are no lysine residues in the disordered regions of FUS, it is not clear why the authors did not also use crosslinkers reactive toward groups other than the amino group. Such crosslinkers could possibly have been useful to study protein interactions that are salt-sensitive. Indeed, the LCD of FUS is not suitable for applying lysine-reactive or carboxy-reactive crosslinkers; better suited to this would be (for example) ruthenium (II) tris-bipyridine, which connects tyrosine residues, and it is precisely tyrosine(s) in the LCD that seem(s) to be crucial for protein condensation. Furthermore, protein-protein crosslinking by UV light has been described and is attributed to covalent Y-Y links.

In particular: (i) Have the authors considered the use of different endoproteinases (such as chymotrypsin) in order to obtain a comprehensive sequence coverage of crosslinked peptides? (ii) Why have the authors not taken into account serine, threonine and tyrosine as crosslinking sites of DSS. It has been reported that DSS is also reactive toward these amino acids.

Related: The LCD of FUS contains the N-terminus of the protein – a primary amine. Are no cross-links seen to this?

We had taken known side-reactions to serine, tyrosine and threonine into account – without any significant gain in information in regard to covering the LCD (Author response image 3).

Author response image 3
Comparison of crosslinks within FUS when exclusively lysine-lysine crosslinks (upper panel) or additionally side reactions to serine, tyrosine and threonine are taken into account (lower panel) (n=3).

Taking side-reactions into account did indeed increase the overall number of detected cross-links, including links within the IDR of HspB8 and the ZnF of FUS; however, the overall gain in information was not significant and comes, at least in our experience, at the prize of a higher likelihood of false-assigned crosslinks. We had therefore decided to not consider side-reactions for our study (Supplementary Data1 Revision).

We had also carried out UV-linking using Sulfo-SDA in combination with chymotrypsin as alternative endoproteinase with no significant gain in information, as it worked very well for HspB8, but unfortunately not for FUS and thus decided to not employ it in our study (Author response image 4). Still, and reassuringly, also in this case our finding that crosslinks formed between the αCD of HspB8 and the RRM of FUSm within condensates could be confirmed.

Author response image 4
Overall crosslinking pattern from a mixture of recombinant FUSm and HspB8 under condensate inducing low salt (75 mM KCl) conditions that were UV crosslinked using Sulfo-SDA and searched using StavroX/MeroX (including side reactions to serine, tyrosine and threonine) after digestion with chymotrypsin.

We had also used chymotrypsin and AspN as additional endoproteinases in our “standard” approach using DSS and the xQuest/xProphet pipeline. While the use of chymotrypsin worked well for HspB8, we did unfortunately detect only a rather limited number of crosslinks in FUS, which is why we again decided to not use it for our study (Author response image 5). Similar results had been achieved for AspN (Author response image 5). Still, we were again able to detect crosslinks that had formed between the αCD of HspB8 and the RRM of FUSm.

Author response image 5
Overall crosslinking pattern from mixtures of recombinant FUSm and HspB8 under condensate inducing low salt (75 mM NaCl) conditions that were digested using either chymotrypsin (interlinks are shown in black and Intralinks, monolinks and loop links in violet (n=3)) or AspN as endoproteinases (all links are shown in orange (n=1)).

This lack of suitable endoproteinases for in-depth characterization of the FUS-LCD unfortunately also limited the use of covalent Y-Y linkers, as suggested by the reviewer:

The reviewer is also fully correct in pointing out that the LCD of FUS contains a primary amine in its N-terminus and we did indeed find crosslinks to it. We nevertheless had decided to leave this data out as we have no valid information on the LCD otherwise – see above.

For all these reasons we had designed the FUSm_K9 mutant, as it allowed for a full coverage of the LCD. Excitingly, it confirmed our finding that the crosslinks that had formed between the αCD of HspB8 and the RRM of FUSm were condensate-specific (Figure S2G).

Details of the FUS K9_mutant and the obtained results can be found in the respective figure legend Figure S2G:

“As FUSm contains no lysine residues within its LCD which are amenable to our NHS-ester crosslinker, we generated a FUSm variant with an additional “26” lysines in the LCD (FUSm_K9), which resembles FUSm in its condensation behavior even though it does not exhibit a similar ageing phenotype. We find that in the dense phase of the condensates the number of inter-links between the LCD of FUSm and both the IDR and the αCD of HspB8 was strongly increased, confirming previous results on the role of the LCD during phase separation. However, only inter-links between the αCD of HspB8 and the RRM of FUSm were exclusively detected inside the condensates.”

4) Figure 5A: droplets formed by FUSm-ΔRRM are significantly larger than those formed by FUSm. Addition of Hsp8B seem to make them larger still (clearly obvious for the "36h" time point). Some questions are raised: What fraction of the FUSm is present the droplets/fibres and what fraction remains in solution? Is HspB8 present in the condensates as well? Complementary experiments using labelled HspB8 are necessary to clarify this.

We have now compared the propensity to form droplets of the FUSm-ΔRRM mutant with FUSm (Author response image 6), demonstrating that FUSm-ΔRRM has a lower csat than FUSm and explaining why droplets formed by FUSm-ΔRRM are significantly larger than those formed by FUSm.

Author response image 6
Comparison of condensation behavior of FUSm and FUSm-ΔRRM.

Addition of Hsp8B which is present in mM concentrations inside the condensates (Figures S2C and S2D) adds a lot of material to the droplets, which explains their enlargement.

As suggested by the reviewer we have also carried out complementary experiments using labelled HspB8, which we have now added as Figure S5A in the manuscript, which clearly show that HspB8 was present in the condensates as well.

5) The hypothesis that RNA and HspB8 compete for the interaction with FUS is interesting; however, the data supporting this are preliminary and the question requires more thorough investigation for example by pulldown experiments.

We agree with the reviewer that the current data in support of our hypothesis that RNA and HspB8 compete for their interaction with FUS is somewhat preliminary and requires experimental validation in future studies. However, interaction/binding studies as suggested by the reviewer are very challenging in condensates and will likely not be quantitative. For example, we have tried to monitor both HspB8 levels in the dilute and dense phase by SDS-PAGE after adding different amounts of RNA and also tried to monitor aging of FUSm and FUSm∆RRM under increasing amounts of RNA. However, as the amount of RNA itself influences condensate formation and as condensate formation is additionally somewhat dependent on the exact composition of the pool of added RNAs, the data was inconclusive and did not permit a quantitative statement. We therefore feel that although the suggested experiment is interesting in its own right, it is clearly beyond the scope of the present manuscript.

However, in order to get this important point across more clearly (i.e. the current rather hypothetical status of our investigations and the need for future investigations), we have amended the manuscript to write:

“This result suggests that RNA and HspB8 may compete for binding to FUSm and indicate a similar mechanism by which they stabilize its RRM domain to prevent FUSm aging.”

and extended our discussion to write:

“It has been proposed before that cells use RNA to regulate condensate formation. Our data suggests that RNA and HspB8 can compete for their interaction with FUS. While this requires experimental validation in future studies, we hypothesize that some RRM domains require stabilization by binding to RNA and in cases where no RNA is available, the chaperone HspB8 takes over this function and protects the RRM domain from unfolding and aggregation.”

We hope that this is a satisfactory solution for the reviewer; however, in case the reviewer should insist, we would be willing to completely remove Figure 5D from our manuscript prior to publication.

6) Can the authors rule out that the differences seen between FUS in low and high salt is not due to the salt concentration per se, but due to the phase separation? While unlikely, but it could be that DSS does not penetrate the FUS-rich phase, and cross-links are only observed between species in the FUS-poor phase (which still contains FUS, albeit at lower concentrations). Can the authors rule this out?

In our workflow we have included a centrifugation step after we crosslink to fully separate the dense phase of the condensates from the dilute phase. This extra step guarantees that we analyze dilute phase and dense separately and that the crosslinks detected in the dense phase must indeed stem from proteins that were located within the condensate (Figure 2E).

In these experiments we did also NOT change the salt concentration (i.e. we only used the low salt concentration of 75 mM to induce condensation in the first place). This already rules out that the differences in cross-links were due to a change in salt concentration. Moreover, in our control experiments (see Figure S2F) – where we indeed used low salt vs high-salt conditions without additional centrifugation – we identify the same crosslinking pattern (including the condensate-specific enrichment of links between the HspB8-αCD and the FUSm-RRM) as we detect without centrifugation, again corroborating that our crosslinker is able to penetrate the FUS-rich phase and that differences in crosslinking are not due to a change in salt concentration. The comparability of our “centrifugation“ and „salt“ experiments is additionally underpinned by Figure S3G which shows that also our quantitative crosslinking data are highly comparable between these conditions.

We apologize that this important point was not evident from the manuscript and was likely caused by an inadequate description of our experimental procedures, which we have therefore amended.

7) The ACD-snap and IDR-snap experiments are a bit confusing – the ACD doesn't partition, yet appears to have some activity? While the IDR region doesn't partition nearly as well as the full-length, the N-terminal regions of sHSPs are frequently unstable c.f. aggregation – are the authors sure that the IDR-snap construct is stable – and if not, might this explain the difference?

The residual activity of the ACD-SNAP construct may be explained by the fact that this variant somewhat partitions into the FUS droplets as shown in Figure S4E and into FUS-LCD droplets as shown in Figure S4H. ACD-SNAP still shows about 18% of partitioning in comparison to the full-length HspB8-SNAP (Figure S4E). Considering that the concentration of the full-length HspB8 protein inside the FUS condensates is about 2.4 mM (Figures S2C and S2D), a lowered partitioning of the ACD-SNAP variant to 18% reflects a concentration of 0.4 mM inside the condensate. This fact could well explain the observation that the ACD-SNAP shows residual chaperone activity towards FUS inside the condensates (Figure S4F). These results are further supported by the fact that the swap variant with a HspB1-IDR fused to the HspB8-ACD (IDR1ACD8) shows a similar effect (Figure S4M and S4N). We did not observe aggregation of the IDR-SNAP variant during protein purification or our experiments. A possible explanation of the results may be related to the oligomeric state of HspB8 inside the droplets. Dimerization/oligomerization of HspB8 may play a role in increasing multivalency of interactions with itself and with FUS and thus have an influence on its partition coefficient. As the IDR-SNAP construct lacks the dimerization competent αCD, this may contribute to a reduced partitioning of this variant.

8) HSPB8 likes to dimerize. Nonetheless, it is hard to explain the "dominant negative" effect seen in the mixture of WT/mutant. Do the authors have an explanation – perhaps due to some higher-order oligomerisation..? Or difference in partitioning..?

Related: While most of the experiments described in tis manuscript provide detailed structural, mechanistic information, the paragraph on the CMT mutant HspB8-K141E is less insightful and remains pretty vague. It seems counterintuitive that stronger binding of the mutant prevents the aging of the droplets and the transition to a more solid-like phase. Here more data or at least a more detailed discussion with a reasonable model would be helpful.

It is indeed a well-known fact that sHSPs form oligomers and it is therefore a possibility that subunit exchange between the wildtype and mutant HspB8 takes place, which may influence the activity of the HspB8-WT. A heterodimer with lower activity than a wildtype homodimer could explain the differences in activity, and we do not exclude the possibility that HspB8 (which is present in mM concentrations inside the condensates, Figures S2C and S2D) will form higher order oligomers which may enhance the mutant’s effect on the wildtype.

Moreover, our data indicates that the mutant has a higher affinity for FUS than the wildtype (as suggested by the stronger binding) which could lead to an at least partial displacement of the HspB8 wildtype by the mutant. We reasoned that this in turn could result in a conformational change – or the stabilization of such a change – within FUS that affects its aging behavior. A notion that is again at least partially supported by changes that we detect in our crosslinking data that support a conformational change within the RRM of FUS during both condensation and aging (Figure 1B and 1C) and within the HspB8 mutant upon binding of the FUS RRM (Figure 6F).

“Concomitantly, multiple intra-links within HspB8 bridging the N-terminus to the αCD domain were increased in the HspB8-K141E mutant (Figure 6F), an observation that is in line with a potential conformational change of the chaperone mutant upon FUS binding that brings these domains closer to each other.”

The reviewer is however fully right in pointing out that currently this is mostly speculation and future research will be needed to shed light on this question. This is also why we write in the discussion:

“To what extent similar mechanisms may also affect other HspB8 mutants therefore awaits further investigation.”

In order to emphasize these important points even further, we have now removed any speculative parts from the Results section, and have amended the discussion of the manuscript to now write:

“The changes we find in the inter-link patterns between FUSm and HspB8-WT or the neuropathy-causing mutant HspB8-K141E may appear counter-intuitive at first sight as far as they suggest a higher binding affinity of the mutant for FUS than the HspB8-WT. However, as sHSPs form oligomers subunit exchange between the wildtype and mutant HspB8 may influence the activity of the HspB8-WT. A heterodimer with lower activity than a wildtype homodimer could explain the differences in activity, and we do not exclude the possibility that HspB8 (which is present in mM concentrations inside the condensates, Figures S2C and S2D) will form higher order oligomers which may enhance the mutant’s effect on the wildtype. Our data also point to shifts in conformation and dynamics of the RRM domain after condensation and during aging and within the HspB8-K141E mutant upon RRM binding. These shifts may differentially affect the fate of the bound substrate: stabilization of the FUSm native conformation by HspB8-WT versus loss of function by the HspB8-K141E mutant with subsequent FUSm aggregation. (….) To what extent similar mechanisms may also affect other HspB8 mutants therefore awaits further investigation.”

9) The authors analysed the data using the search engine xQuest, which requires a pair of non- and isotopically labelled crosslinkers for confident identification of crosslinked peptides. The data already acquired are probably unsuitable for other crosslink search engines (35 ms ion accumulation time and ion-trap analyser for MS2). In general, I consider the crosslinking data acquired in this work by CID in the ion trap to be of insufficient quality. Have the authors attempted to acquire a data set with high-resolution MS2 and to use more modern search engines with relaxed crosslinker specificity?

We respectfully disagree that crosslinking data acquired by CID in an ion trap leads per se to data of insufficient quality. A notion that is also shared in the latest and first community-wide crosslinking study (PMID:31045356), where the approach chosen in this manuscript is explicitly mentioned as being lege artis, see page 6958:

“Some strategies provide additional layers of evidence that can be used to better control the error rate. For example, isotope-coded, noncleavable linkers provide two independent measures of precursor and fragment masses and charge state information for fragments independent of MS resolution”.

We also would like to point out that during the time-point where we have started this project, the approach used by us was the only one available that allowed for the automatic quantification of crosslink data.

As suggested by the reviewer we have nevertheless acquired new data from samples of FUS::HspB8 condensates using high-resolution MS2 and searched them independently using the search engines pLink2 (PMID: 31363125) and MeroX (PMID: 31283178) (Author response image 7). Author response image 7 shows an excellent overlap between the different approaches, where virtually all crosslinks detected by our approach could be validated by the high-resolution acquisition strategy and the different search engines. While pLink2 detects overall more crosslinks than xQuest, the question if this is due to an improved acquisition strategy or rather a higher false-discovery rate, as shown previously for pLink2 (PMID: 32029734), can remain open at this point, as the data clearly confirms that the data generated by the approach used for this manuscript consists of valid and highly reproducible crosslinks. A similar argument can be made for the comparison with MeroX, in which case xQuest is able to detect a larger number of crosslinks.

Author response image 7
Comparison of detected crosslinks from FUS/HspB8 condensates at an FDR < 0.

05 using either a high/low acquisition strategy and xQuest as a search engine or a high/high strategy and plink2 (A) or MeroX (B) as search engine. Please note that due to technical reasons the comparison with MeroX included only inter- and intraprotein crosslinks, while the comparison with pLink2 additionally comprised mono links and loop links.

Moreover, to hopefully dissipate any remaining reservations of the reviewer we have additionally validated our data by parallel reaction monitoring (PRM). As the reviewer knows, this targeted approach is highly sensitive and will with very high certainty confirm if a specific peptide was present within a sample or not. We randomly chose 20 unique crosslinking sites (uxIDs) from our dataset and were able to validate all the tested uxIDs from our dataset by PRM (Author response image 8).

Author response image 8
Shown are select transitions for crosslinked peptide pairs of FUS.

In total, our assay contained 100 transitions and while a few isolated transitions did not result in conclusive traces, we could validate all tested uxIDs from our dataset by PRM.

We hope that this data convinces the reviewer not only that the crosslinking data acquired in this work is of sufficient quality but that acquiring crosslinking data using the ion trap and isotope-coded noncleanable linkers is generally a good strategy to obtain high-quality crosslink information from in-vitro condensates in order to probe protein-protein interactions.

https://doi.org/10.7554/eLife.69377.sa2

Article and author information

Author details

  1. Edgar E Boczek

    1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Dewpoint Therapeutics GmbH, Dresden, Germany
    Contribution
    Conceptualization, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Julius Fürsch
    Competing interests
    is currently an employee of Dewpoint Therapeutics
  2. Julius Fürsch

    1. University of Konstanz, Department of Biology, Konstanz, Germany
    2. Konstanz Research School Chemical Biology, University of Konstanz, Konstanz, Germany
    Contribution
    Conceptualization, Formal analysis, Investigation, Methodology, Writing - original draft, Writing - review and editing
    Contributed equally with
    Edgar E Boczek
    Competing interests
    No competing interests declared
  3. Marie Laura Niedermeier

    1. University of Konstanz, Department of Biology, Konstanz, Germany
    2. Konstanz Research School Chemical Biology, University of Konstanz, Konstanz, Germany
    Contribution
    Conceptualization, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  4. Louise Jawerth

    1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
    Contribution
    Formal analysis, Validation, Investigation, Methodology, Writing - review and editing
    Competing interests
    No competing interests declared
  5. Marcus Jahnel

    1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Biotechnology Center, Technische Universität Dresden, Dresden, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  6. Martine Ruer-Gruß

    Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  7. Kai-Michael Kammer

    1. University of Konstanz, Department of Biology, Konstanz, Germany
    2. Konstanz Research School Chemical Biology, University of Konstanz, Konstanz, Germany
    Contribution
    Software, Formal analysis, Investigation, Visualization
    Competing interests
    No competing interests declared
  8. Peter Heid

    1. University of Konstanz, Department of Biology, Konstanz, Germany
    2. Konstanz Research School Chemical Biology, University of Konstanz, Konstanz, Germany
    Contribution
    Software, Formal analysis, Validation, Investigation, Visualization
    Competing interests
    No competing interests declared
  9. Laura Mediani

    Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
    Contribution
    Validation, Investigation
    Competing interests
    No competing interests declared
  10. Jie Wang

    Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  11. Xiao Yan

    Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  12. Andrej Pozniakovski

    Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  13. Ina Poser

    1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Dewpoint Therapeutics GmbH, Dresden, Germany
    Contribution
    Investigation
    Competing interests
    is currently an employee of Dewpoint Therapeutics
  14. Daniel Mateju

    Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared
  15. Lars Hubatsch

    1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Max Planck Institute for the Physics of Complex Systems, Dresden, Germany
    Contribution
    Investigation
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1934-7437
  16. Serena Carra

    Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
    Contribution
    Conceptualization, Supervision, Funding acquisition
    Competing interests
    No competing interests declared
  17. Simon Alberti

    1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Biotechnology Center, Technische Universität Dresden, Dresden, Germany
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    is a shareholder, consultant and member of the scientific advisory board for Dewpoint Therapeutics
  18. Anthony A Hyman

    1. Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
    2. Center for Systems Biology Dresden (CSBD), Dresden, Germany
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    Competing interests
    is cofounder, shareholder, consultant and member of the scientific advisory board for Dewpoint Therapeutics.
  19. Florian Stengel

    1. University of Konstanz, Department of Biology, Konstanz, Germany
    2. Konstanz Research School Chemical Biology, University of Konstanz, Konstanz, Germany
    Contribution
    Conceptualization, Formal analysis, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Writing - original draft, Project administration, Writing - review and editing
    For correspondence
    Florian.Stengel@uni-konstanz.de
    Competing interests
    is a consultant and member of the scientific advisory board for Dewpoint Therapeutics.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1447-4509

Funding

Deutsche Forschungsgemeinschaft (STE 2517/1-1)

  • Florian Stengel

Universität Konstanz (Chemicals and small Equipment Purchase)

  • Florian Stengel

Deutsche Forschungsgemeinschaft (Cluster of Excellence "Physics of Life")

  • Simon Alberti
  • Anthony A Hyman

EU Joint Programme – Neurodegenerative Disease Research (Neurodegenerative Disease Research (JPND))

  • Serena Carra
  • Simon Alberti

Fondazione Italiana di Ricerca per la Sclerosi Laterale Amiotrofica (Granulopathy and MLOpathy)

  • Serena Carra

Ministero degli Affari Esteri e della Cooperazione Internazionale (Dissolve_ALS)

  • Serena Carra

Ministry of Education, University and Research (E91I18001480001)

  • Serena Carra

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

The authors thank the Protein Expression Purification and Characterization Facility, the Light Microscopy Facility and the Mass Spectrometry Facility at the Max Planck Institute of Molecular Cell Biology and Genetics in Dresden, the Bioimaging Centre (BIC) at the University of Konstanz, and the Centro Interdipartimentale Grandi Strumenti (CIGS) at the University of Modena and Reggio Emilia. The authors thank Marit Leuschner and Anne Schwager for their assistance with cell culture. The authors thank members of the Alberti, Hyman and Stengel Labs, and Dewpoint Therapeutics for helpful discussions and critical reading of the manuscript. This work was supported by the Konstanz Research School Chemical Biology (KoRS-CB) and the Cluster of Excellence ‘Physics of Life’, TU Dresden, Dresden, Germany. SA and SC are grateful for the EU Joint Programme—Neurodegenerative Disease Research (JPND) project. SC acknowledges funding from AriSLA Foundation (Granulopathy and MLOpathy), MAECI (Dissolve_ALS), and MIUR (Departments of excellence 2018–2022; E91I18001480001). FS is funded by the Emmy Noether Programme of the DFG (STE 2517/1-1).

Senior and Reviewing Editor

  1. Volker Dötsch, Goethe University, Germany

Reviewers

  1. Henning Urlaub, University Medical Center Göttingen, Germany
  2. Justin LP Benesch, University of Oxford, United Kingdom
  3. Volker Dötsch, Goethe University, Germany

Publication history

  1. Preprint posted: April 13, 2021 (view preprint)
  2. Received: April 13, 2021
  3. Accepted: August 27, 2021
  4. Accepted Manuscript published: September 6, 2021 (version 1)
  5. Version of Record published: October 12, 2021 (version 2)

Copyright

© 2021, Boczek et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,372
    Page views
  • 271
    Downloads
  • 2
    Citations

Article citation count generated by polling the highest count across the following sources: Crossref, PubMed Central, Scopus.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Download citations (links to download the citations from this article in formats compatible with various reference manager tools)

Open citations (links to open the citations from this article in various online reference manager services)

  1. Further reading

Further reading

    1. Biochemistry and Chemical Biology
    2. Computational and Systems Biology
    Dhruva Katrekar et al.
    Tools and Resources

    Adenosine deaminases acting on RNA (ADARs) can be repurposed to enable programmable RNA editing, however their enzymatic activity on adenosines flanked by a 5' guanosine is very low, thus limiting their utility as a transcriptome engineering toolset. To address this issue, we first performed a novel deep mutational scan of the ADAR2 deaminase domain, directly measuring the impact of every amino acid substitution across 261 residues, on RNA editing. This enabled us to create a domain wide mutagenesis map while also revealing a novel hyperactive variant with improved enzymatic activity at 5'-GAN-3' motifs. However, exogenous delivery of ADAR enzymes, especially hyperactive variants, leads to significant transcriptome wide off-targeting. To solve this problem, we engineered a split ADAR2 deaminase which resulted in 1000-fold more specific RNA editing as compared to full-length deaminase overexpression. We anticipate that this systematic engineering of the ADAR2 deaminase domain will enable broader utility of the ADAR toolset for RNA biotechnology and therapeutic applications.

    1. Biochemistry and Chemical Biology
    2. Cell Biology
    Keith F DeLuca et al.
    Tools and Resources Updated

    Antibodies are indispensable tools used for a large number of applications in both foundational and translational bioscience research; however, there are drawbacks to using traditional antibodies generated in animals. These include a lack of standardization leading to problems with reproducibility, high costs of antibodies purchased from commercial sources, and ethical concerns regarding the large number of animals used to generate antibodies. To address these issues, we have developed practical methodologies and tools for generating low-cost, high-yield preparations of recombinant monoclonal antibodies and antibody fragments directed to protein epitopes from primary sequences. We describe these methods here, as well as approaches to diversify monoclonal antibodies, including customization of antibody species specificity, generation of genetically encoded small antibody fragments, and conversion of single chain antibody fragments (e.g. scFv) into full-length, bivalent antibodies. This study focuses on antibodies directed to epitopes important for mitosis and kinetochore function; however, the methods and reagents described here are applicable to antibodies and antibody fragments for use in any field.