Molecular switch proteins whose cycling between states is controlled by opposing regulators1,2 are central to biological signal transduction. As switch proteins function within highly connected interaction networks3, the fundamental question arises of how functional specificity is achieved when different processes share common regulators. Here we show that functional specificity of the small GTPase switch protein Gsp1 in Saccharomyces cerevisiae (the homologue of the human protein RAN)4 is linked to differential sensitivity of biological processes to different kinetics of the Gsp1 (RAN) switch cycle. We make 55 targeted point mutations to individual protein interaction interfaces of Gsp1 (RAN) and show through quantitative genetic5 and physical interaction mapping that Gsp1 (RAN) interface perturbations have widespread cellular consequences. Contrary to expectation, the cellular effects of the interface mutations group by their biophysical effects on kinetic parameters of the GTPase switch cycle and not by the targeted interfaces. Instead, we show that interface mutations allosterically tune the GTPase cycle kinetics. These results suggest a model in which protein partner binding, or post-translational modifications at distal sites, could act as allosteric regulators of GTPase switching. Similar mechanisms may underlie regulation by other GTPases, and other biological switches. Furthermore, our integrative platform to determine the quantitative consequences of molecular perturbations may help to explain the effects of disease mutations that target central molecular switches.
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The mass spectrometry proteomics data have been deposited to the PRIDE proteomics data repository with the dataset identifier PXD016338 and are available as Supplementary Tables. Raw biophysics data (cycle kinetics, circular dichroism spectroscopy and NMR), and E-MAP S-scores, scaled SGA scores and their correlations are available from https://github.com/tinaperica/Gsp1_manuscript/tree/master/Data. All other data that support the findings of this study are available within the paper and its supplementary files. Source data are provided with this paper.
Custom written R and Python scripts are available without restrictions at https://github.com/tinaperica/Gsp1_manuscript.
Ferrell, J. E. & Ha, S. H. Ultrasensitivity part I: Michaelian responses and zero-order ultrasensitivity. Trends Biochem. Sci 39, 496–503 (2014).
Goldbeter, A. & Koshland, D. E. An amplified sensitivity arising from covalent modification in biological systems. Proc. Natl Acad. Sci. USA 78, 6840–6844 (1981).
Eisenberg, D., Marcotte, E. M., Xenarios, I. & Yeates, T. O. Protein function in the post-genomic era. Nature 405, 823–826 (2000).
Rush, M. G., Drivas, G. & D’Eustachio, P. The small nuclear GTPase Ran: how much does it run? BioEssays 18, 103–112 (1996).
Collins, S. R., Schuldiner, M., Krogan, N. J. & Weissman, J. S. A strategy for extracting and analyzing large-scale quantitative epistatic interaction data. Genome Biol. 7, R63 (2006).
Braberg, H. et al. Genetic interaction mapping informs integrative structure determination of protein complexes. Science 370, eaaz4910 (2020).
Braberg, H. et al. From structure to systems: high-resolution, quantitative genetic analysis of RNA polymerase II. Cell 154, 775–788 (2013).
Dasso, M. The Ran GTPase: theme and variations. Curr. Biol. 12, R502–R508 (2002).
Bischoff, F. R. & Ponstingl, H. in The Small GTPase Ran Vol. 1 (eds Rush, M. & D’Eustachio, P.) 163–176 (Springer, 2001); https://doi.org/10.1007/978-1-4615-1501-2_9
Moore, M. S. & Blobel, G. The GTP-binding protein Ran/TC4 is required for protein import into the nucleus. Nature 365, 661–663 (1993).
Köhler, A. & Hurt, E. Exporting RNA from the nucleus to the cytoplasm. Nat. Rev. Mol. Cell Biol. 8, 761–773 (2007).
Arnaoutov, A. & Dasso, M. The Ran GTPase regulates kinetochore function. Dev. Cell 5, 99–111 (2003).
Ren, M. et al. Separate domains of the Ran GTPase interact with different factors to regulate nuclear protein import and RNA processing. Mol. Cell. Biol. 15, 2117–2124 (1995).
Costanzo, M. et al. A global genetic interaction network maps a wiring diagram of cellular function. Science 353, aaf1420 (2016).
Geyer, M. et al. Conformational states of the nuclear GTP-binding protein Ran and its complexes with the exchange factor RCC1 and the effector protein RanBP1. Biochemistry 38, 11250–11260 (1999).
Henriksen, P. et al. Proteome-wide analysis of lysine acetylation suggests its broad regulatory scope in Saccharomyces cerevisiae. Mol. Cell. Proteomics 11, 1510–1522 (2012).
de Boor, S. et al. Small GTP-binding protein Ran is regulated by posttranslational lysine acetylation. Proc. Natl Acad. Sci. USA 112, E3679–E3688 (2015).
Besray Unal, E. et al. Systems level expression correlation of Ras GTPase regulators. Cell Commun. Signal. 16, 46 (2018).
Görlich, D., Seewald, M. J. & Ribbeck, K. Characterization of Ran-driven cargo transport and the RanGTPase system by kinetic measurements and computer simulation. EMBO J. 22, 1088–1100 (2003).
Barr, F. A. Review series: Rab GTPases and membrane identity: causal or inconsequential? J. Cell Biol. 202, 191–199 (2013).
Levy, E. D. A simple definition of structural regions in proteins and its use in analyzing interface evolution. J. Mol. Biol. 403, 660–670 (2010).
Rojas, A. M., Fuentes, G., Rausell, A. & Valencia, A. The Ras protein superfamily: evolutionary tree and role of conserved amino acids. J. Cell Biol. 196, 189–201 (2012).
Collins, S. R., Roguev, A. & Krogan, N. J. Quantitative genetic interaction mapping using the E-MAP approach. Methods Enzymol. 470, 205–231 (2010).
Schuldiner, M. et al. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123, 507–519 (2005).
Giaever, G. et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387–391 (2002).
Collins, S. R. et al. Functional dissection of protein complexes involved in yeast chromosome biology using a genetic interaction map. Nature 446, 806–810 (2007).
Cherry, J. M. et al. SGD: Saccharomyces Genome Database. Nucleic Acids Res. 26, 73–79 (1998).
Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate—a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995).
Benjamini, Y. & Yekutieli, D. The control of the false discovery rate in multiple testing under dependency. Ann. Stat. 29, 1165–1188, 1124 (2001).
Jäger, S. et al. Global landscape of HIV–human protein complexes. Nature 481, 365–370 (2011).
Jäger, S. et al. Purification and characterization of HIV–human protein complexes. Methods 53, 13–19 (2011).
Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).
Cox, J. et al. Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol. Cell. Proteomics 13, 2513–2526 (2014).
Teo, G. et al. SAINTexpress: improvements and additional features in Significance Analysis of INTeractome software. J. Proteomics 100, 37–43 (2014).
Choi, M. et al. MSstats: an R package for statistical analysis of quantitative mass spectrometry-based proteomic experiments. Bioinformatics 30, 2524–2526 (2014).
Studier, F. W. Protein production by auto-induction in high density shaking cultures. Protein Expression Purif. 41, 207–234 (2005).
Markley, J. L. et al. Recommendations for the presentation of NMR structures of proteins and nucleic acids—IUPAC-IUBMB-IUPAB Inter-Union Task Group on the Standardization of Data Bases of Protein and Nucleic Acid Structures Determined by NMR Spectroscopy. J. Biomol. NMR 12, 1–23 (1998).
Mishra, A. K. & Lambright, D. G. High-throughput assay for profiling the substrate specificity of Rab GTPase-activating proteins. Methods Mol. Biol. 1298, 47–60 (2015).
Goudar, C. T., Sonnad, J. R. & Duggleby, R. G. Parameter estimation using a direct solution of the integrated Michaelis–Menten equation. Biochim. Biophys. Acta 1429, 377–383 (1999).
Malaby, A. W. et al. Methods for analysis of size-exclusion chromatography–small-angle X-ray scattering and reconstruction of protein scattering. J. Appl. Crystallogr. 48, 1102–1113 (2015).
Klebe, C., Bischoff, F. R., Ponstingl, H. & Wittinghofer, A. Interaction of the nuclear GTP-binding protein Ran with its regulatory proteins RCC1 and RanGAP1. Biochemistry 34, 639–647 (1995).
We thank R. Ordonez for contributions to the design of mutations; C. Melero, D. Jeon, S. Mathur, R. D. Kim and K. Kundert for technical help; M. Jaime Garza for contributions to the conformational analysis by NMR; C. Ryan for advice on E-MAP analysis; and D. Agard, G. Narlikar, J. Fraser and J. M. Thornton for discussions. This work was supported by a grant from the National Institutes of Health (R01-GM117189) to T.K. and a Sir Henry Wellcome Postdoctoral Fellowship (101614/Z/13/Z) to T.P. C.J.P.M. is a UCSF Discovery Fellow. T.K. is a Chan Zuckerberg Biohub investigator.
The authors declare no competing interests.
Peer review information Nature thanks Katrin Rittinger and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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Extended data figures and tables
Interface residues are categorized as interface core, rim, and support positions (see Supplementary Methods) and provided in Supplementary Table 2. a–f, Structures of RAN (Gsp1) in partner-bound conformations with interface residues coloured by partner protein. All mutated Gsp1 residues are shown as spheres.: a, Srm1 (GEF) interface core (dark teal) and interface rim and support (light teal) PDB 1I2M; b, Rna1 (GAP) interface core (dark orange) and interface rim and support (light orange) PDB 1K5D; c, Ntf2 interface core (dark purple) and interface rim and support (light purple) PDB 1A2K; d, Residues that are in both the core of the Yrb1 and Yrb2 interfaces (dark yellow), and in only one of the two interfaces (light yellow) PDB 1K5D; e, Srp1 interface core (dark pink) and interface rim and support (light pink) PDB 1WA5; f, Residues that are in the core of four or more (dark green), two to three (green) and one (light green) karyopherin interface. Karyopherins are: Kap95, Crm1, Los1, Kap104, Msn5, Cse1, Mtr10. PDB 2BKU. g, Location of Gsp1 residues in partner interfaces. Residues within 5 Å of the nucleotide, in the canonical P-loop, or in the switch I or II regions22 were not mutated. Residues belonging to the switch I, switch II, and C-terminal α helix are indicated by dark navy bars. Chosen Gsp1 point mutation substitutions are provided in Supplementary Table 3.
Extended Data Fig. 2 Endogenous expression levels of Gsp1 in S. cerevisiae strains with genomically integrated GSP1 point mutations profiled by western blot.
a, Expression data for strong mutants, defined as mutants with nine or more significant GIs. b, Expression data for weak mutants, defined as mutants with fewer than nine significant GIs. In a, and b, bar heights indicate averages over two or more biological replicates (n) grown on separate days (except for T34D which has only one biological replicate), with error bars indicating one standard deviation for n >= 3. Overlaid points indicate individual biological replicates (each an average over at least 12 technical replicates per biological replicate for wild-type and MAT:α strains, and between one and six technical replicates per biological replicate for mutant strains). Expression levels are relative to the expression levels of wild-type Gsp1 protein with clonNAT resistance marker (WT) shown as red dashed lines (relative expression of 1). MAT:α is the starting S. cerevisiae strain (see Supplementary Methods). c, Distributions of average relative expression levels for strong and weak mutants. Each point is as in a and b. Horizontal pink bars indicate the mean of the point distributions.
Extended Data Fig. 3 GI profiles of the 56 GSP1 strains (wild-type GSP1 with clonNAT cassette and 55 point mutants).
Negative S-score (blue) represents synthetic sick or synthetic lethal GIs, positive S-score (yellow) represents suppressive or epistatic GIs; neutral S-scores (no significant GI) are shown in black. Gsp1 point mutants and S. cerevisiae genes are hierarchically clustered by Pearson correlation. GSP1 mutants fall into two clusters: a cluster of 23 strong mutants with nine or more significant GIs and 32 weak mutants with fewer than nine significant GIs.
Extended Data Fig. 4 Functional profiles of GSP1 mutants cannot be explained solely by the positions of mutations in interfaces.
a, Locations of mutated residues in structurally characterized interfaces. ΔrASA is the difference in accessible surface area of a residue upon binding, relative to an empirical maximum for the solvent accessible surface area of each amino acid residue type (see Supplementary Methods). b, GI profiles of GSP1 mutants group S. cerevisiae genes by biological processes and complexes, such as the dynein/dynactin pathway, SWR1 complex, the Hog1 signalling pathway, mRNA splicing, mitochondrial proteins, and the Rpd3L histone deacetylase complex. c, Distributions of Pearson correlations between the GI profiles of strong GSP1 mutants and alleles of Gsp1 direct interaction partners with available co-complex crystal structures (left) and strong GSP1 mutants and alleles of all other S. cerevisiae genes (right).d, Distributions of Pearson correlations between the GI profiles of Gsp1 interaction partners and strong and weak GSP1 mutants if mutation is (black and light purple) or is not (grey and dark purple) in the interface with that partner. Teal violin plot on the right represents the distribution of all other Pearson correlations between GSP1 mutants and S. cerevisiae genes. In c and d, point size indicates the false discovery rate adjusted one-sided (positive) p-value of Pearson correlation, and pink bars indicate the mean of the point distributions; n denotes the number of GSP1 point mutant-gene GI profile correlations in each category. Data for strong mutants are also shown in Fig. 1e and included here for comparison.
a, Schematic representation of the affinity purification mass spectrometry (AP-MS) experiment to determine the abundance of pulled-down protein interaction partners of wild type and mutant Gsp1. The change in abundance of partner proteins pulled down with Gsp1 mutants in b, c, and d is represented as log2-transformed fold change (FC) between abundance of a partner pulled-down with a Gsp1 mutant versus pulled-down with wild-type Gsp1 (log2(abundance(PREY)MUT/abundance(PREY)WT). To account for possible tag effects, the fold change in prey abundance was always computed relative to the wild-type protein with the corresponding tag. Decreased abundance compared to pull-down with wild-type Gsp1 is annotated in red and increased abundance in blue. The log2-transformed fold change values are capped at +/− 4. b, Amino- and c, -carboxy terminally 3xFLAG-tagged Gsp1 point mutants (rows) and prey proteins identified by AP-MS (columns) hierarchically clustered by the log2-transformed fold change in prey abundance. d, Prey proteins pulled down by both amino- and carboxy-terminal tagged constructs. Left semi-circle represents an amino-terminal 3xFLAG-tagged Gsp1 point mutant, and right semi-circle represents carboxy-terminal 3xFLAG-tagged Gsp1 point mutant. Semi-circle size is proportional to the significance of the log2-transformed fold change (false discovery rate adjusted p-value) of the prey abundance in pulled-down complexes with a Gsp1 mutant compared to complexes with the wild-type Gsp1. Overall we identified 316 high-confidence prey partner proteins, with the amino- and carboxy-terminally tagged Gsp1 mutants pulling down 264 and 103 preys, respectively, including 51 overlapping preys. The difference in preys identified by experiments with N- or C-terminal tags illustrates the sensitivity of the interaction network to perturbation of Gsp1.
Extended Data Fig. 6 Gsp1 interface mutations rewire interactions with the core regulators Srm1 and Rna1.
a, b, Protein-protein interactions between interface mutants of Gsp1 and Gsp1 partners for which there are co-complex X-ray crystal structures (core regulators Srm1 and Rna1, and effectors Yrb1, Kap95, Pse1, and Srp1). Change in pulled-down prey partner abundance is expressed as log2(PREY abundanceMUT/PREY abundanceWT)). N-3xFL and C-3xFL labelled mutants are tagged with an amino- or carboxy-terminal triple FLAG tag, respectively, and partners are coloured as indicated. a, Bar plot depicting changes in pulled-down prey partner abundance when the point mutation is in the core of the Gsp1 interface with the prey partner. b, Bar plot depicting all changes in pulled-down prey partner abundance for core regulators Srm1 and Rna1, and effectors Yrb1, Kap95, Pse1, and Srp1, regardless whether the mutation is directly in the interface core with the partner or not. c, Distribution showing the variation in log2-transformed fold change in abundance of all prey proteins pulled down with the Gsp1 mutants, as defined by interquartile range (IQR) across mutants. Values for core partners shown as arrows (Rna1 orange, Srm1 teal, Yrb1 yellow, Kap95 green, Pse1 light green, Srp1 pink). Mean and +1 standard deviation of IQR values are highlighted with a dark grey and a light grey arrow, respectively. The extent to which the abundance of the two cycle regulators Rna1 and Srm1 changed across the Gsp1 point mutants is larger than the change for an average prey protein. All IQR values are provided in Supplementary Table 5. d, Position of T34 with respect to the interfaces with Rna1 (GAP, orange surface, PDB 1K5D), Srm1 (GEF, teal surface, PDB 2I1M), and Yrb1 (yellow surface, PDB 1K5D). As the coordinates for T34 are not resolved in the 2I1M structure, in all three structures the pink spheres show the residue location in the aligned 1K5D structure. Gsp1: navy cartoon; GTP nucleotide: stick representation. Residues that were mutated in the Rna1 and Srm1 interfaces are shown in sphere representation and are coloured in orange (Rna1, left) or teal (Srm1, middle).
Extended Data Fig. 7 Effect of Gsp1 point mutations on the in vitro efficiency of GAP-mediated GTP hydrolysis and GEF-mediated nucleotide exchange.
a, kcat and b, Km values of GAP-mediated GTP hydrolysis of wild-type and point mutant Gsp1. Error bars represent the standard deviation of the kcat and the Km parameters from the integrated Michaelis-Menten fit for n ≥ 3 replicates. c, kcat and d, Km of GEF-mediated nucleotide exchange of wild-type and point mutant Gsp1. Inset shows the Km bar plot for all but the four mutants with the highest Km (K101R, R108L, R108I, and R108Y). Error bars represent the value plus/minus the standard error of the Michaelis-Menten fit to data from n ≥ 17 measurements at different substrate concentrations. a, b, c, d, Dotted lines indicate the wild-type values. Dark blue bar denotes the wild-type Gsp1, and orange and teal bars highlight the residues that are in the core of the interface with the GAP and GEF, respectively. e, Comparison of relative change in catalytic efficiencies of GAP-mediated GTP hydrolysis (orange bars) and GEF-mediated nucleotide exchange (teal bars) defined as kcatMUT/KmMUT / kcatWT/KmWT. Grey line indicates a three-fold increase compared to wild type and black line indicates a three-fold decrease compared to wild type. Error bars represent the added standard error of the mean (for GAP) or standard error of the fit (for GEF) values of the mutant and the wild-type efficiency (kcat/Km) values. Mutations not in the interface core with the GAP both increased (3-fold, R108G mutant) and decreased (3 to 10-fold, T34E/Q/A/G, R78K, D79S/A, R108I, and R112S mutants) the catalytic efficiency kcat/Km of GAP-mediated GTP hydrolysis, compared to wild-type Gsp1. As expected, mutations in the interface core with the GEF (K101, and R108) decreased the catalytic efficiency of GEF-mediated nucleotide exchange >40-fold. However, other mutations not in the GEF interface core (R78K, R112S, Y157A) also decreased the efficiency notably (3- to 10-fold).
Extended Data Fig. 8 Gsp1 interface mutations act allosterically to modulate the rate of GTP hydrolysis.
a, Annotated 1D 31P NMR spectrum of wild-type Gsp1 loaded with GTP. Peak areas are computed over intervals shown and normalized to the GTPβ bound peak. The peaks from left to right correspond to: free phosphate (Pi), β phosphate of GDP bound to Gsp1 (GDPβbound), β phosphate of free (unbound) GDP (GDPβfree), γ phosphate of GTP bound to Gsp1 in conformation 1 (γ1), γ phosphate of GTP bound to Gsp1 in conformation 2 (γ2), α phosphate of bound or unbound GDP or GTP, β phosphate of GTP bound to Gsp1 (GTPβbound), β phosphate of free (unbound) GTP (GTPβfree). b, Rate of intrinsic GTP hydrolysis of wild-type Gsp1 and mutants. Dotted line indicates wild-type value. Error bars represent the standard deviations from n ≥ 3 replicates (dots). c, Natural log-transformed exchange equilibrium constant between the γ2 and γ1 conformations plotted against the relative rate of intrinsic GTP hydrolysis represented as a natural logarithm of the ratio of the rate for the mutant over the rate of the wild type. The pink line is a linear fit. Error bars represent the standard deviation from n ≥ 3 replicates of intrinsic GTP hydrolysis measurements. d, Location of Y157, H141, and Q147 (pink spheres) in the Crm1 interface (grey surface, PDB 3M1I). Gsp1: navy cartoon; GTP nucleotide: yellow stick representation. e, Location of T34 (pink spheres) in the interface with Yrb1 (grey surface, PDB 1K5D). Distances from the γ phosphate of GTP to the residue α-carbon are indicated below the residue numbers in d and e.
Extended Data Fig. 9 Relative prey protein abundance overlaid onto the effects of each mutation on relative in vitro efficiencies of GAP-mediated GTP hydrolysis and GEF-mediated nucleotide exchange.
Relative GAP-mediated hydrolysis and GEF-mediated exchange efficiencies are plotted as ln(kcatMUT/KmMUT/kcatWT/KmWT). Mutants that affect the efficiency (kcat/Km) of GEF-catalysed nucleotide exchange more than the efficiency of GAP-catalysed GTP hydrolysis are above the diagonal, and the mutants that affect the GAP-catalysed hydrolysis are below the diagonal. Left semi-circle represents an amino-terminal 3xFLAG-tagged Gsp1 point mutant, and right semi-circle represents a carboxy-terminal 3xFLAG-tagged Gsp1 point mutant, relative to wild-type Gsp1 with the corresponding tag. a, Colour represents log2-transformed ratio of GAP and GEF abundance fold change for each Gsp1 point mutant compared to wild type defined as log2((abundance(Rna1)MUT/abundance(Rna1)WT)/(abundance(Srm1)MUT/abundance(Srm1)WT)). Orange coloured mutants pull-down relatively less Rna1 (GAP) and teal mutants less Srm1 (GEF). b-f, Colour represents the log-transformed ratio of mutant and wild type pulled-down prey protein represented as log2(PREY abundanceMUT/PREY abundanceWT). Log-transformed relative abundance values are capped at +/− 4. Decreased prey abundance from AP-MS in pulled-down complexes with a mutant Gsp1 compared to complexes with the wild-type Gsp1 is represented in red and increased abundance in blue. Prey proteins: b, Rna1 (GAP); c, Srm1 (GEF); d, Yrb1; e, Kap95, and f, Vps71. Yrb1 follows a pattern similar to that of Rna1 (GAP), whereas Kap95 and Vps71 are similar to Srm1 (GEF).
Heat maps of the false discovery rate adjusted one-sided (positive) p-values of the Pearson correlations between the GI profiles of 22 strong GSP1 point mutants and GI profiles of knock-outs or knock-downs of S. cerevisiae genes from Ref. 14. The p-value is represented as a white to grey range as in Fig. 4a. Genes are organized in gene sets based on their biological function (Methods). The line plots above the heat maps are the same as in Fig. 4c. a, GSP1 point mutants and alleles of Gsp1 binding partners with available co-complex X-ray crystal structures, and S. cerevisiae genes involved in nuclear transport of RNA and proteins. b, GSP1 point mutants and S. cerevisiae genes involved in transcription regulation or 5′ mRNA capping. c, GSP1 point mutants and S. cerevisiae genes involved in the cytoplasm-to-vacuole targeting (CVT) pathway, and actin, tubulin, and cell polarity.
This file contains the Supplementary Discussion, Supplementary Methods, Supplementary Figures 1–16, Supplementary Tables 1–9 and Supplementary References.
Genetic interaction (GI) data from the E-MAP screens. This file contains genetic interaction (GI) scores (S-scores) from the E-MAP screens of 56 S. cerevisiae strains (wild type and 55 GSP1 point mutants).
Pairwise Pearson correlations of profiles between SGA genes and GSP1 point mutants, with associated P values. This file contains the Pearson correlation coefficients and accompanying P values for correlations between genetic interaction profiles of GSP1 point mutants and the genetic interaction profiles of S. cerevisiae alleles from the CellMap SGA dataset published in ref. 14.
Affinity purification mass spectrometry (AP-MS) data reported as fold change and significance value, as well as a list of significant interaction hits. This file contains two tables. Table 1 contains the affinity purification mass spectrometry (AP-MS) data for Gsp1 point mutants. The data in the table are the output from MSstats35 (see Supplementary Methods) and report on the abundance of the pulled-down protein, the log-transformed fold change of the abundance compared to the wild type with the appropriate 3×Flag tag, and the accompanying FDR-adjusted P value. The data are provided for both the global and equalized median normalization methods available. Table 2 contains the list of high-confidence interaction partners of Gsp1 from our AP-MS experiments (as determined by SAINTexpress (ref. 34), see Supplementary Methods).
Supplementary Data 4 S. cerevisiae genes from the SGA data with significant positive correlations with GSP1 mutants organized by biological functions into gene sets. This file provides a list of S. cerevisiae alleles from the SGA dataset whose GI profiles have significant correlations with the GI profiles of GSP1 mutants (see Methods). The genes were manually grouped into ‘gene sets’ according to their biological function (as annotated in the Saccharomyces Genome Database, https://www.yeastgenome.org).
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Perica, T., Mathy, C.J.P., Xu, J. et al. Systems-level effects of allosteric perturbations to a model molecular switch. Nature 599, 152–157 (2021). https://doi.org/10.1038/s41586-021-03982-6