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Molecular interactions contributing to FUS SYGQ LC-RGG phase separation and co-partitioning with RNA polymerase II heptads

Nature Structural & Molecular Biology volume 28, pages 923–935 (2021)Cite this article

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Abstract

The RNA-binding protein FUS (Fused in Sarcoma) mediates phase separation in biomolecular condensates and functions in transcription by clustering with RNA polymerase II. Specific contact residues and interaction modes formed by FUS and the C-terminal heptad repeats of RNA polymerase II (CTD) have been suggested but not probed directly. Here we show how RGG domains contribute to phase separation with the FUS N-terminal low-complexity domain (SYGQ LC) and RNA polymerase II CTD. Using NMR spectroscopy and molecular simulations, we demonstrate that many residue types, not solely arginine-tyrosine pairs, form condensed-phase contacts via several interaction modes including, but not only sp2-π and cation-π interactions. In phases also containing RNA polymerase II CTD, many residue types form contacts, including both cation-π and hydrogen-bonding interactions formed by the conserved human CTD lysines. Hence, our data suggest a surprisingly broad array of residue types and modes explain co-phase separation of FUS and RNA polymerase II.

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Fig. 1: Domains outside the SYGQ-rich low-complexity domain contribute to FUS LLPS.
Fig. 2: The RGG3 and SYGQ LC remain disordered in a two-component condensed phase.
Fig. 3: Interactions between SYGQ LC and RGG3 in the condensed phase involve multiple residue pairs.
Fig. 4: Diverse interaction modes contribute to FUS SYGQ LC and RGG3 interactions within the condensed phase.
Fig. 5: RGG domains interact with RNA polymerase II CTD tail.
Fig. 6: Lysine residues within RNA polymerase II CTD contribute to interactions with FUS within the condensed phase.
Fig. 7: Interaction modes and impact of CTD lysine residues on RNA polymerase II CTD and FUS domain interactions.
Fig. 8: Multiple residue types and interaction modes contribute to multicomponent condensed phases of FET proteins and RNA polymerase II.

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Data availability

Chemical shift assignments for the RGG domains can be accessed using the BMRB accession 51067, 51068, 51069. Raw NMR data files can be found at https://doi.org/10.6084/m9.figshare.16598861. Source data are provided with this paper. All other data are available from the corresponding author upon reasonable request.

Code availability

Simulation software described in Methods section are publicly available and can be found at http://www.gromacs.org/ for the atomistic resolution simulations.

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Acknowledgements

We thank M. Naik for helpful advice and assistance with NMR spectroscopy and V. Ryan for helpful discussions. We thank J. Ying for creating the HSQC-ROESY-HSQC experiment. Research was supported in part by NIGMS R01GM118530 (to N.L.F.), NIGMS R01GM120537 (to J.M.), Human Frontier Science Program RGP0045/2018 (to N.L.F.). A.C.M. was supported in part by NIGMS training grant to the MCB graduate program at Brown University (T32GM136566) and NSF graduate fellowship (1644760, to A.C.M.). Use of the high-performance computing capabilities of the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the NSF grant TG-MCB-120014, is gratefully acknowledged. The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies.

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  1. These authors contributed equally: Wai Shing Tang, Nina Jovic.

Authors and Affiliations

  1. Graduate Program in Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI, USA

    Anastasia C. Murthy

  2. Graduate Program in Physics, Brown University, Providence, RI, USA

    Wai Shing Tang

  3. Artie McFerrin Department of Chemical Engineering, Texas A&M University, College Station, TX, USA

    Nina Jovic & Jeetain Mittal

  4. Department of Molecular Biology, Cell Biology, and Biochemistry, Brown University, Providence, RI, USA

    Abigail M. Janke, Da Hee Seo & Nicolas L. Fawzi

  5. Center for Biomedical Engineering, Brown University, Providence, RI, USA

    Theodora Myrto Perdikari

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Contributions

A.C.M. and N.L.F. designed, performed and analyzed data for NMR spectroscopy, phase-separation assays and microscopy. A.M.J. and D.H.S. performed fluorescence microscopy and provided reagents. T.M.P. assisted with reagents and recorded titration experiments. W.S.T., N.J. and J.M. designed and performed simulation experiments and analyzed the resulting data. A.C.M., J.M. and N.L.F. wrote the manuscript with comments from all authors.

Corresponding authors

Correspondence to Jeetain Mittal or Nicolas L. Fawzi.

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Competing interests

N.L.F. is a member of the Scientific Advisory Board of Dewpoint Therapeutics LLC. A.C.M. is currently employed by Genentech. The authors declare no other competing interests.

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Peer review information Nature Structural & Molecular Biology thanks the anonymous reviewers for their contribution to the peer review of this work. Beth Moorefield was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 RGG lysine variants are still capable of LLPS.

a) DIC micrographs of 5 μM MBP-FUS FL WT, RGG1 R9xK, RGG2 R8xK, and RGG3 R10xK after cleavage of the N-terminal MBP solubility tag by addition of TEV protease (left) or in the absence of TEV protease (right) in buffer containing 1 M sodium chloride. Scale bars are 20 μm. b) Turbidity over time of 5 μM MBP-FUS FL WT, RGG1 R9xK, RGG2 R8xK, and RGG3 R10xK after cleavage of the N-terminal MBP solubility tag by addition of TEV protease in buffer containing 1 M sodium chloride over time. The data are blanked to samples lacking TEV protease. Data are plotted as mean ± s.d of measurements from n = 3 replicates in one representative data set out of two independent experiments. c) DIC micrographs of 5 μM MBP-FUS FL WT, RGG1 R9xK, RGG2 R8xK, and RGG3 R10xK after cleavage of the N-terminal MBP solubility tag by addition of TEV protease (left) or in the absence of TEV protease (right) in the presence of 1:1 mass equivalents of total yeast RNA. Scale bars are 20 μm. d) Turbidity of 5 μM MBP-FUS FL WT, RGG1 R9xK, RGG2 R8xK, and RGG3 R10xK in the presence of 1:0, 1:1 and 1:2 total yeast RNA over time. The data are blanked to samples lacking TEV protease. Data are plotted as mean mean ± s.d. of measurements from n = 3 replicates in one representative data set out of two independent experiments.

Source data

Extended Data Fig. 2 The RGG domains weakly interact with the SYGQ LC.

a) 15N chemical shift perturbations and intensity differences of the SYGQ LC in the presence of increasing concentrations of MBP-RGG1, MBP-RGG2, MBP-RGG3 or MBP alone (negative control). Intensity data are normalized to a SYGQ LC alone control and are plotted as mean mean ± s.d. of baseline noise for each spectrum as estimate of uncertainty in one representative data set out of two independent experiments. b) 15N chemical shift perturbations and intensity differences of RGG1, RGG2, or RGG3 with increasing concentrations of MBP-SYGQ LC. The data are relative to RGG1, RGG2 or RGG3 alone controls. The asterisks for the RGG1 and RGG2 titrations with MBP indicate where the data are normalized to the 1:1 condition. Gray bars represent RGG motifs. Black dots correspond to resonances that are unassigned, while gray dots represent resonances that are assigned but not resolved due to overlap. Intensity data are plotted as mean ± s.d. of baseline noise for each spectrum as estimate of uncertainty in one representative data set. C) Average 15N chemical shift perturbations across all positions in SYGQ LC in the presence of ten times excess MBP-RGG1, MBP-RGG2, MBP-RGG3 or MBP alone (negative control) (full data points presented in a). Data are plotted as mean ± s.e.m. in one representative data set out of two independent experiments. d) Average 15N chemical shift perturbations across all positions in RGG1, RGG2 or RGG3 in the presence of ten times excess MBP-SYGQ LC or MBP alone (negative control) (full data points presented in b). Data are plotted as mean ± s.e.m. in one representative data set out of two independent experiments.

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Extended Data Fig. 3 Assigned spectra of FUS RGG domains and impact of RGG mutations on weak interactions with SYGQ LC.

a-c) Assigned 1H-15N HSQC spectra of FUS RGG1, RGG2 or RGG3 in the dispersed phase. d) 15N chemical shift perturbations and intensity differences of 30 μM SYGQ LC in the presence of 300 μM of MBP-RGG3 WT, R10xK or R10xS. Intensity data are normalized to a SYGQ LC alone control and are plotted as mean ± s.d. of baseline noise for each spectrum as estimate of uncertainty in one representative data set. e) Average 15N chemical shift perturbations of SYGQ LC in the presence of ten times excess MBP-RGG3 WT, R10xK or R10xS (full data points presented in d). Data are plotted as mean ± s.e.m. in one representative data set. f) 15N transverse relaxation rate constant values for SYGQ LC in the presence of ten times excess of MBP (negative control), MBP-RGG1, MBP-RGG2 or MBP-RGG3. Data are plotted as mean ± propagated best-fit parameter confidence interval equal to 1 s.d in one representative data set.

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Extended Data Fig. 4 Composition of fragments used for all-atom simulations.

a) Amino acid content of the SYGQ LC and fragments 11-54 and 120-163 used for all-atom simulations. b) Amino acid content of the FUS RGG domains. Fragments used for all-atom simulations (RGG1 220-267, RGG2 372-419 and RGG3 454-501) contain similar amino acid compositions to their experimental counterparts. c) Amino acid content of RNA polymerase C-terminal tail heptads 27-52. d) 15N spin relaxation parameters for FUS RGG3 in the dispersed phase from experiment and simulations. The segments used for simulations are shorter, explaining the discrepancies at the termini. Experimental data are plotted as mean ± propagated best-fit parameter confidence interval equal to 1 s.d in one representative data set of two independent experiments. Simulated data are plotted as mean ± s.e.m of n = 12 independent trajectories launched from randomly selected equilibrated ensemble members. E) Free energy landscape as a function of van der Waals contacts formed between hydrophobic atoms in FUS 11-54 or FUS 120-163 and RGG1, RGG2 or RGG3 from simulations. The use of different 44-amino acid fragments of FUS LC in the simulations produces differences in the energy landscapes, suggesting that the amino acid variation between the fragments used can have an impact on the number of contacts. Data are plotted as mean ± s.e.m of n = 5 equal divisions of the total data set from one data set with n = 16 independent replicas using PTWTE. F) Radius of gyration distribution of three different 44-residue long RGG fragments in single-chain simulations. The differences in compaction within the simulation system reflects the differences in amino acid composition of each RGG fragment. Data are plotted as mean ± s.e.m of n = 5 equal divisions of the total data set as in (e).

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Extended Data Fig. 5 NOEs within a two-component condensed phase containing FUS SYGQ LC and RGG3.

a) NOE build-up curve (NOE intensity vs mixing time, τm) from 4D HSQC–NOESY-HSQC experiments. No diagonal peaks are present in these HSQC-NOESY-HSQC spectra, so data were collected as one-dimensional experiments and presented here as integration over the resonance envelope. Each experiment was performed once. b) 2D-planes from a 13C-HSQC-NOESY-15N-HSQC experiment recorded with a NOESY mixing time of 50 ms. c) Intermolecular ROEs from SYGQ LC are observed for arginine and other residue types including glycine in the 2-component condensed phase. 2D-projection from a 4D HSQC-NOESY-HSQC (250 ms mixing time; unscaled and scaled to match ROE) and HSQC-ROESY-HSQC (5 kHz spin lock / mixing for 20 ms). ROESY spin lock mixing time was limited due to more rapid transverse relaxation rate as compared to the NOESY mixing time, as the magnetization is longitudinal during the NOE transfer but transverse during the spin-locked ROE transfer. Experiments performed once. d) 1H-13C HSQC of FUS RGG3 in the dispersed phase. e) NOE signal intensity quantification from a 12C-filtered, 13C-edited NOESY-HSQC experiment presented in Fig. 3c. Intensity data for one representative experiment are plotted as mean ± s.d. of baseline noise for each plane as estimate of uncertainty in one representative data set.

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Extended Data Fig. 6 Contacts between FUS SYGQ LC and RGG domains.

a) Total intermolecular contact propensities from two-chain simulations of SYGQ LC11-54 and RGG1220-267 binned by residue position (left), binned by residue type (center), and binned by residue type and normalized by residue frequency (right). Plots represent the total number of contacts for a particular residue position. Bars represent the total number of contacts for a particular residue type. Residues colored in gray occur in the sequence less than three times. (For A,B,C: Data are plotted as mean ± s.e.m of (left) n = 5 equal divisions of the total 16 replica PTWTE data set, (middle) total contact propensities, or (right) normalized total contact propensities from one representative data set out of two independent experiments.) b) Inter-residue contact propensities from two-chain simulations of SYGQ LC11-54 and RGG2372-419 binned by residue position (left), binned by residue type (center), and binned by residue type and normalized by residue frequency (right). Curved plots represent the total contact propensities for each residue. Bars represent the total number of contacts for a particular residue type. Gray bars represent residue types that occur less than three times in the sequence. c) Inter-residue contact propensities from two-chain simulations of SYGQ LC11-54 and RGG3454-501 binned by residue position. Plots represent the total contact propensities for each residue. Corresponding residue typed binned and frequency normalized plots (matching middle and right plots, respectively, for B and C) are presented in main text Fig. 3d,e. d) Total sp2/π interactions (left) and normalized by all VdW contacts (right) where all geometries are included (only distance-based definition) in two-chain simulations of SYGQ LC11-54 or SYGQ LC120-163 with RGG1, RGG2 or RGG3. The data are binned for π-π (top, lightest), sp2−π (middle, lighter) and sp2−sp2 (bottom) contacts. Data are plotted as mean ± s.e.m of n = 5 equal divisions of the total data set. e,f) Top fifteen interacting amino acid pairs in order of highest to lowest contact frequency (left to right) SYGQ LC11-54 or SYGQ LC120-163 with RGG1 or RGG2. The fraction of pairs showing hydrogen bonds, sp2/π, and cation-π contacts out of the total pairs with van der Waals interactions is indicated.

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Extended Data Fig. 7 Contacts within a three-component phase containing FUS SYGQ LC and RGG3 and RNAP2 CTD.

a) Chemical shift perturbations and signal intensity changes for 15N-RNA polymerase II CTD in the presence of increasing concentrations of FUS RGG3. Intensity data are plotted as mean ± s.d. of baseline noise for each spectrum as estimate of uncertainty in one representative data set. b) Free energy landscape of van der Waals contacts between hydrophobic atoms between RNAP2 CTD and FUS SYGQ LC or RGG3 from two-chain simulations. Data are plotted as mean ± s.e.m of n = 5 equal divisions of the total data set from one representative data set. c) 1H-15N HSQC of RNA polymerase II CTD in the dispersed (orange) and condensed (green) phases. d) NOE signal intensity quantification from a 12C-filtered, 13C-edited NOESY-HSQC experiment presented in Fig. 6b. Intensity data are plotted as mean ± s.d. of baseline noise for each plane as estimate of uncertainty in one representative data set out of two independent experiments. Inter-residue contact propensities from two-chain simulations of RNAP2 CTD1853-1896 and e) FUS SYGQ LC11-54 or f) RGG3 binned by residue position. Plots represent the total number of contacts for a particular residue position. Data are plotted as mean ± s.e.m of n = 5 equal divisions of the total data set from one representative data set.

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Murthy, A.C., Tang, W.S., Jovic, N. et al. Molecular interactions contributing to FUS SYGQ LC-RGG phase separation and co-partitioning with RNA polymerase II heptads. Nat Struct Mol Biol 28, 923–935 (2021). https://doi.org/10.1038/s41594-021-00677-4

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