Abstract
Microtubule function is modulated by the tubulin code, diverse posttranslational modifications that are altered dynamically by writer and eraser enzymes1. Glutamylation—the addition of branched (isopeptide-linked) glutamate chains—is the most evolutionarily widespread tubulin modification2. It is introduced by tubulin tyrosine ligase-like enzymes and erased by carboxypeptidases of the cytosolic carboxypeptidase (CCP) family1. Glutamylation homeostasis, achieved through the balance of writers and erasers, is critical for normal cell function3,4,5,6,7,8,9, and mutations in CCPs lead to human disease10,11,12,13. Here we report cryo-electron microscopy structures of the glutamylation eraser CCP5 in complex with the microtubule, and X-ray structures in complex with transition-state analogues. Combined with NMR analysis, these analyses show that CCP5 deforms the tubulin main chain into a unique turn that enables lock-and-key recognition of the branch glutamate in a cationic pocket that is unique to CCP family proteins. CCP5 binding of the sequences flanking the branch point primarily through peptide backbone atoms enables processing of diverse tubulin isotypes and non-tubulin substrates. Unexpectedly, CCP5 exhibits inefficient processing of an abundant β-tubulin isotype in the brain. This work provides an atomistic view into glutamate branch recognition and resolution, and sheds light on homeostasis of the tubulin glutamylation syntax.
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Data availability
Atomic models and structure factors have been deposited at the Protein Data Bank under accession numbers: 8V3M, 8V3N, 8V3O and 8V3P for apo, Glu-P-Glu, Glu-P-peptide 1 and Glu-P-peptide 2 complexes, respectively. Cryo-EM maps for protofilament refinement have been deposited at the Electron Micrscopy Data Bank with accession numbers EMDB-42948 (class 1), EMDB-44544 (class 2) and EMDB-44545 (class 3). Cryo-EM maps and atomic models for CCP5 focused refinement and composite maps for the three classes have been deposited at the EMDB and PDB with accession numbers: EMDB-42950 and 8V3Q, EMDB-42971 and 8V4K (class 1), EMDB-42951 and 8V3R, EMDB-42972 and 8V4L (class 2) and EMDB-42952 and 8V3S, EMDB-42973 and 8V4M (class 3), respectively, with accompanying raw half maps. Source data are provided with this paper.
References
Roll-Mecak, A. The tubulin code in microtubule dynamics and information encoding. Dev. Cell 54, 7–20 (2020).
Edde, B. et al. Posttranslational glutamylation of alpha-tubulin. Science 247, 83–85 (1990).
Bobinnec, Y. et al. Glutamylation of centriole and cytoplasmic tubulin in proliferating non-neuronal cells. Cell Motil. Cytoskeleton 39, 223–232 (1998).
Zadra, I. et al. Chromosome segregation fidelity requires microtubule polyglutamylation by the cancer downregulated enzyme TTLL11. Nat. Commun. 13, 7147 (2022).
Gaertig, J. & Wloga, D. Ciliary tubulin and its post-translational modifications. Curr. Top. Dev. Biol. 85, 83–113 (2008).
O’Hagan, R. et al. Glutamylation regulates transport, specializes function, and sculpts the structure of cilia. Curr. Biol. 27, 3430–3441.e3436 (2017).
Zheng, P. et al. ER proteins decipher the tubulin code to regulate organelle distribution. Nature 601, 132–138 (2022).
Sun, X. et al. Loss of RPGR glutamylation underlies the pathogenic mechanism of retinal dystrophy caused by TTLL5 mutations. Proc. Natl Acad. Sci. USA 113, E2925–E2934 (2016).
Xia, P. et al. Glutamylation of the DNA sensor cGAS regulates its binding and synthase activity in antiviral immunity. Nat. Immunol. 17, 369–378 (2016).
Shashi, V. et al. Loss of tubulin deglutamylase CCP1 causes infantile‐onset neurodegeneration. EMBO J. 37, e100540 (2018).
Sheffer, R. et al. Biallelic variants in AGTPBP1, involved in tubulin deglutamylation, are associated with cerebellar degeneration and motor neuropathy. Eur. J. Hum. Genet. 27, 1419–1426 (2019).
Kastner, S. et al. Exome sequencing reveals AGBL5 as novel candidate gene and additional variants for retinitis pigmentosa in five Turkish families. Invest. Ophthalmol. Vis. Sci. 56, 8045–8053 (2015).
Astuti, G. D. et al. Mutations in AGBL5, encoding α-tubulin deglutamylase, are associated with autosomal recessive retinitis pigmentosa. Invest. Ophthalmol. Vis. Sci. 57, 6180–6187 (2016).
Bodakuntla, S. et al. Distinct roles of α- and β-tubulin polyglutamylation in controlling axonal transport and in neurodegeneration. EMBO J. 40, e108498 (2021).
O’Hagan, R. et al. The tubulin deglutamylase CCPP-1 regulates the function and stability of sensory cilia in C. elegans. Curr. Biol. 21, 1685–1694 (2011).
Regnard, C. et al. Polyglutamylation of nucleosome assembly proteins. J. Biol. Chem. 275, 15969–15976 (2000).
Miller, K. E. & Heald, R. Glutamylation of Nap1 modulates histone H1 dynamics and chromosome condensation in Xenopus. J. Cell Biol. 209, 211–220 (2015).
Komander, D. & Rape, M. The ubiquitin code. Annu. Rev. Biochem. 81, 203–229 (2012).
Mahalingan, K. K. et al. Structural basis for polyglutamate chain initiation and elongation by TTLL family enzymes. Nat. Struct. Mol. Biol. 27, 802–813 (2020).
van Dijk, J. et al. A targeted multienzyme mechanism for selective microtubule polyglutamylation. Mol. Cell 26, 437–448 (2007).
Tort, O. et al. The cytosolic carboxypeptidases CCP2 and CCP3 catalyze posttranslational removal of acidic amino acids. Mol. Biol. Cell 25, 3017–3027 (2014).
Wu, H. Y., Rong, Y., Correia, K., Min, J. & Morgan, J. I. Comparison of the enzymatic and functional properties of three cytosolic carboxypeptidase family members. J. Biol. Chem. 290, 1222–1232 (2015).
Rogowski, K. et al. A family of protein-deglutamylating enzymes associated with neurodegeneration. Cell 143, 564–578 (2010).
Wu, H. Y., Wei, P. & Morgan, J. I. Role of cytosolic carboxypeptidase 5 in neuronal survival and spermatogenesis. Sci. Rep. 7, 41428 (2017).
Sirajuddin, M., Rice, L. M. & Vale, R. D. Regulation of microtubule motors by tubulin isotypes and post-translational modifications. Nat. Cell Biol. 16, 335–344 (2014).
Hong, S. R. et al. Spatiotemporal manipulation of ciliary glutamylation reveals its roles in intraciliary trafficking and Hedgehog signaling. Nat. Commun. 9, 1732 (2018).
Suryavanshi, S. et al. Tubulin glutamylation regulates ciliary motility by altering inner dynein arm activity. Curr. Biol. 20, 435–440 (2010).
Szczesna, E. et al. Combinatorial and antagonistic effects of tubulin glutamylation and glycylation on katanin microtubule severing. Dev. Cell 57, 2497–2513.e2496 (2022).
Valenstein, M. L. & Roll-Mecak, A. Graded control of microtubule severing by tubulin glutamylation. Cell 164, 911–921 (2016).
Genova, M. et al. Tubulin polyglutamylation differentially regulates microtubule‐interacting proteins. EMBO J. 42, e112101 (2023).
Gomis-Ruth, F. X. Structure and mechanism of metallocarboxypeptidases. Crit. Rev. Biochem. Mol. Biol. 43, 319–345 (2008).
Cerda-Costa, N. & Gomis-Ruth, F. X. Architecture and function of metallopeptidase catalytic domains. Protein Sci. 23, 123–144 (2014).
Sapio, M. R. & Fricker, L. D. Carboxypeptidases in disease: insights from peptidomic studies. Proteomics Clin. Appl. 8, 327–337 (2014).
Rodriguez de la Vega Otazo, M., Lorenzo, J., Tort, O., Aviles, F. X. & Bautista, J. M. Functional segregation and emerging role of cilia-related cytosolic carboxypeptidases (CCPs). FASEB J. 27, 424–431 (2013).
Berezniuk, I. et al. Cytosolic carboxypeptidase 5 removes α- and γ-linked glutamates from tubulin. J. Biol. Chem. 288, 30445–30453 (2013).
Redeker, V., Rossier, J. & Frankfurter, A. Posttranslational modifications of the C-terminus of α-tubulin in adult rat brain: α4 is glutamylated at two residues. Biochemistry 37, 14838–14844 (1998).
Alexander, J. E. et al. Characterization of posttranslational modifications in neuron-specific class III β-tubulin by mass spectrometry. Proc. Natl Acad. Sci. USA 88, 4685–4689 (1991).
Mukai, M. et al. Recombinant mammalian tubulin polyglutamylase TTLL7 performs both initiation and elongation of polyglutamylation on beta-tubulin through a random sequential pathway. Biochemistry 48, 1084–1093 (2009).
Chen, J. & Roll-Mecak, A. Glutamylation is a negative regulator of microtubule growth. Mol. Biol. Cell https://doi.org/10.1091/mbc.E23-01-0030 (2023).
Debs, G. E., Cha, M., Liu, X., Huehn, A. R. & Sindelar, C. V. Dynamic and asymmetric fluctuations in the microtubule wall captured by high-resolution cryoelectron microscopy. Proc. Natl Acad. Sci. USA 117, 16976–16984 (2020).
Otero, A. et al. The novel structure of a cytosolic M14 metallocarboxypeptidase (CCP) from Pseudomonas aeruginosa: a model for mammalian CCPs. FASEB J. 26, 3754–3764 (2012).
Liu, Y., Garnham, C. P., Roll-Mecak, A. & Tanner, M. E. Phosphinic acid-based inhibitors of tubulin polyglutamylases. Bioorg. Med. Chem. Lett. 23, 4408–4412 (2013).
Hanson, J. E., Kaplan, A. P. & Bartlett, P. A. Phosphonate analogues of carboxypeptidase A substrates are potent transition-state analogue inhibitors. Biochemistry 28, 6294–6305 (1989).
Kim, H. & Lipscomb, W. N. Crystal structure of the complex of carboxypeptidase A with a strongly bound phosphonate in a new crystalline form: comparison with structures of other complexes. Biochemistry 29, 5546–5555 (1990).
Christianson, D. W. & Lipscomb, W. N. Carboxypeptidase-A. Acc. Chem. Res. 22, 62–69 (1989).
Schreuder, H. et al. Isolation, co-crystallization and structure-based characterization of anabaenopeptins as highly potent inhibitors of activated thrombin activatable fibrinolysis inhibitor (TAFIa). Sci. Rep. 6, 32958 (2016).
Banerjee, A. et al. A monoclonal antibody against the type II isotype of β-tubulin. Preparation of isotypically altered tubulin. J. Biol. Chem. 263, 3029–3034 (1988).
Rudiger, M., Plessman, U., Kloppel, K. D., Wehland, J. & Weber, K. Class II tubulin, the major brain beta tubulin isotype is polyglutamylated on glutamic acid residue 435. FEBS Lett. 308, 101–105 (1992).
McKenna, E. D., Sarbanes, S. L., Cummings, S. W. & Roll-Mecak, A. The tubulin code, from molecules to health and disease. Annu. Rev. Cell Dev. Biol. 39, 331–361 (2023).
Ikegami, K. et al. TTLL7 is a mammalian beta-tubulin polyglutamylase required for growth of MAP2-positive neurites. J. Biol. Chem. 281, 30707–30716 (2006).
Garnham, C. P. et al. Multivalent microtubule recognition by tubulin tyrosine ligase-like family glutamylases. Cell 161, 1112–1123 (2015).
Garnham, C. P., Yu, I., Li, Y. & Roll-Mecak, A. Crystal structure of tubulin tyrosine ligase-like 3 reveals essential architectural elements unique to tubulin monoglycylases. Proc. Natl Acad. Sci. USA 114, 6545–6550 (2017).
Kormendi, V., Szyk, A., Piszczek, G. & Roll-Mecak, A. Crystal structures of tubulin acetyltransferase reveal a conserved catalytic core and the plasticity of the essential N terminus. J. Biol. Chem. 287, 41569–41575 (2012).
Szyk, A. et al. Molecular basis for age-dependent microtubule acetylation by tubulin acetyltransferase. Cell 157, 1405–1415 (2014).
Shida, T., Cueva, J. G., Xu, Z., Goodman, M. B. & Nachury, M. V. The major α-tubulin K40 acetyltransferase αTAT1 promotes rapid ciliogenesis and efficient mechanosensation. Proc. Natl Acad. Sci. USA 107, 21517–21522 (2010).
Skultetyova, L. et al. Human histone deacetylase 6 shows strong preference for tubulin dimers over assembled microtubules. Sci. Rep. 7, 11547 (2017).
Szyk, A., Deaconescu, A. M., Piszczek, G. & Roll-Mecak, A. Tubulin tyrosine ligase structure reveals adaptation of an ancient fold to bind and modify tubulin. Nat. Struct. Mol. Biol. 18, 1250–1258 (2011).
Aillaud, C. et al. Vasohibins/SVBP are tubulin carboxypeptidases (TCPs) that regulate neuron differentiation. Science 358, 1448–1453 (2017).
Li, F. et al. Cryo-EM structure of VASH1-SVBP bound to microtubules. eLife 9, e58157 (2020).
Mahalingan, K. K. et al. Structural basis for α-tubulin-specific and modification state-dependent glutamylation. Nat. Chem. Biol. https://doi.org/10.1038/s41589-024-01599-0 (2024).
Wolff, A. et al. Distribution of glutamylated alpha and beta-tubulin in mouse tissues using a specific monoclonal antibody, GT335. Eur. J. Cell Biol. 59, 425–432 (1992).
Vemu, A., Garnham, C. P., Lee, D. Y. & Roll-Mecak, A. Generation of differentially modified microtubules using in vitro enzymatic approaches. Methods Enzymol. 540, 149–166 (2014).
Vemu, A., Atherton, J., Spector, J. O., Moores, C. A. & Roll-Mecak, A. Tubulin isoform composition tunes microtubule dynamics. Mol. Biol. Cell 28, 3564–3572 (2017).
Ziolkowska, N. E. & Roll-Mecak, A. In vitro microtubule severing assays. Methods Mol. Biol. 1046, 323–334 (2013).
Bieling, P. et al. CLIP-170 tracks growing microtubule ends by dynamically recognizing composite EB1/tubulin-binding sites. J. Cell Biol. 183, 1223–1233 (2008).
Chen, J. et al. α-Tubulin tail modifications regulate microtubule stability through selective effector recruitment, not changes in intrinsic polymer dynamics. Dev. Cell 56, 2016–2028.e2014 (2021).
Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).
Kelley, L. A., Mezulis, S., Yates, C. M., Wass, M. N. & Sternberg, M. J. The Phyre2 web portal for protein modeling, prediction and analysis. Nat. Protoc. 10, 845–858 (2015).
Kabsch, W. Integration, scaling, space-group assignment and post-refinement. Acta Crystallogr. D 66, 133–144 (2010).
Winn, M. D. et al. Overview of the CCP4 suite and current developments. Acta Crystallogr. D 67, 235–242 (2011).
McCoy, A. J. et al. Phaser crystallographic software. J. Appl. Crystallogr. 40, 658–674 (2007).
Afonine, P. V. et al. Towards automated crystallographic structure refinement with phenix.refine. Acta Crystallogr. D 68, 352–367 (2012).
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).
Varadi, M. et al. AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models. Nucleic Acids Res. 50, D439–D444 (2022).
Emsley, P. & Cowtan, K. Coot: model-building tools for molecular graphics. Acta Crystallogr. D 60, 2126–2132 (2004).
Liebschner, D. et al. Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix. Acta Crystallogr. D 75, 861–877 (2019).
Afonine, P. V. et al. New tools for the analysis and validation of cryo-EM maps and atomic models. Acta Crystallogr. D 74, 814–840 (2018).
Morin, A. et al. Collaboration gets the most out of software. eLife 2, e01456 (2013).
Meyer, P. A. et al. Data publication with the structural biology data grid supports live analysis. Nat. Commun. 7, 10882 (2016).
Scheres, S. H. RELION: implementation of a Bayesian approach to cryo-EM structure determination. J. Struct. Biol. 180, 519–530 (2012).
He, S. & Scheres, S. H. W. Helical reconstruction in RELION. J. Struct. Biol. 198, 163–176 (2017).
Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).
Zhang, K. Gctf: Real-time CTF determination and correction. J. Struct. Biol. 193, 1–12 (2016).
Cook, A. D., Manka, S. W., Wang, S., Moores, C. A. & Atherton, J. A microtubule RELION-based pipeline for cryo-EM image processing. J. Struct. Biol. 209, 107402 (2020).
Sanchez-Garcia, R. et al. DeepEMhancer: a deep learning solution for cryo-EM volume post-processing. Commun. Biol. 4, 874 (2021).
Pettersen, E. F. et al. UCSF Chimera—a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).
Pettersen, E. F. et al. UCSF ChimeraX: Structure visualization for researchers, educators, and developers. Protein Sci. 30, 70–82 (2021).
Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. eLife 7, e42166 (2018).
Croll, T. I. ISOLDE: a physically realistic environment for model building into low-resolution electron-density maps. Acta Crystallogr. D 74, 519–530 (2018).
Barad, B. A. et al. EMRinger: side chain-directed model and map validation for 3D cryo-electron microscopy. Nat. Methods 12, 943–946 (2015).
Sobolev, O. V. et al. A global Ramachandran score identifies protein structures with unlikely stereochemistry. Structure 28, 1249–1258.e1242 (2020).
Zhang, R., LaFrance, B. & Nogales, E. Separating the effects of nucleotide and EB binding on microtubule structure. Proc. Natl Acad. Sci. USA 115, E6191–E6200 (2018).
Banerjee, A., Bovenzi, F. A. & Bane, S. L. High-resolution separation of tubulin monomers on polyacrylamide minigels. Anal. Biochem. 402, 194–196 (2010).
Sklenar, V., Piotto, M., Leppik, R. & Saudek, V. Gradient-tailored water suppression for H1-N15 Hsqc experiments optimized to retain full sensitivity. J. Magn. Reson. 102, 241–245 (1993).
Delaglio, F. et al. NMRPipe: a multidimensional spectral processing system based on UNIX pipes. J. Biomol. NMR 6, 277–293 (1995).
Acknowledgements
The authors thank D.-Y. Lee for mass spectrometry access and advice; H. Wang and U. Baxa for help with cryo-EM data collection; D. Hoover for computational support; and G. E. Debs for advice on protofilament refinement. This work utilized the computational resources of the NIH HPC Biowulf cluster (http://hpc.nih.gov). M.E.T. is supported by the Natural Sciences and Engineering Research Council of Canada (NSERC). N.T. is supported by the intramural programme of the National Heart, Lung, and Blood Institute (NHLBI). A.R-M. is supported by the intramural programs of the National Institute of Neurological Disorders and Stroke (NINDS) and NHLBI.
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J.C. purified proteins, obtained crystals, collected X-ray and cryo-EM data, processed data, solved and refined all structures and performed assays. E.A.Z. supervised and performed cryo-EM processing. J.M.G. performed and interpreted NMR experiments. A.S. purified proteins and performed peptide assays. Y.L. synthesized inhibitors. M.E.T. supervised Y.L. N.T. interpreted NMR experiments. A.R.-M. initiated, coordinated and supervised the project. J.C. and A.R.M. analysed structures, interpreted data and wrote the manuscript.
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Extended data figures and tables
Extended Data Fig. 1 X-ray crystal structures of the CCP5 catalytic core.
a. Ribbon diagram showing the X-ray structure of the catalytic core of human CCP5. N-terminal domain, orange; Carboxypeptidase C-terminal domain, green; Dotted lines indicate unresolved regions. b, c. The internal loop (res. 339–424) deletion does not affect deglutamyation activity with a β-tubulin peptide (βI(E441): DATAEEEEDFGEEA(E)EEA) (b) or preference for the β-tubulin tail (c). Enzyme at 5 nM and peptides (α peptide: VDSVEGEG(E)EEGEEY; β-peptide: DATAEEEEDFGEEA(E)EEA) 10 μM in both (b) and (c). Bars represent mean and S.E.M. n = 3 independent experiments. d. Ribbon diagram showing the X-ray structure of the catalytic core of human CCP5 bound to the Glu-P-peptide 1 analog. CCP5 colored as in (a). Analog shown in ball-and-stick. Scissile glutamate, pink; branch glutamate, cyan. e. CCP5 apo (grey), CCP5:Glu-P-Glu (light blue) and CCP5:Glu-P-peptide 1 (colored as in a) crystal structures superposed on their carboxypeptidase domains. Analogs shown in ball-and-stick and colored as in (d).
Extended Data Fig. 2 Cryo-EM image processing and map resolution and quality for CCP5 focused refinement.
a. Raw micrograph of CCP5 decorated microtubules. b. Initial image processing was performed in RELION. 4643 movies were motion corrected and summed; high-quality micrographs were selected based on CTF estimation and visual inspection for manual picking of microtubule segments. A microtubule RELION-based pipeline (MiRP) was used to determine protofilament number, microtubule polarity, identify seam position and generate a C1 reconstruction. CCP5, gold, binds every 80 Å along the microtubule lattice, grey. Protofilament refinement with a custom mask that covered one protofilament yielded a map of higher quality for tubulin, but not CCP5. c. Focused classification of CCP5 generated three classes with good definition. Refinement of these three classes resulted in maps with resolutions of 3.1 Å (class #1), 3.4 Å (class #2) and 3.6 Å (class #3). See Methods for additional details. d. Fourier shell correlation (FSC) curves for the single protofilament reconstruction and three CCP5 focused reconstructions indicate their nominal resolution. FSC estimates were calculated at the 0.143 criterion. e. Microtubule reconstruction using the single protofilament refinement protocol color-coded by local resolution. f. CCP5 focused reconstructions color-coded by local resolution for class #1, #2 and #3. g, h. Cryo-EM maps showing fit of the CCP5 X-ray apo model (g) and the local map quality (h) for classes #1, #2 and #3.
Extended Data Fig. 3 Protofilament map resolution and quality.
a. Fourier shell correlation (FSC) curves for the single protofilament reconstructions performed for each class. FSC estimates were calculated at 0.143 criterion. b. Protofilament reconstructions color-coded by local resolution for classes #1, #2 and #3. c. Cryo-EM maps showing the local map quality of α and β tubulin in all three classes. d. Lumen (top) and side view (bottom) of back reconstructed, non-subtracted particles using alignment information from the protofilament refinement for class #1, #2 and #3 (Methods). The S9-S10 loop in α and β-tubulin is highlighted with white ovals; α- and β-tubulin can be differentiated by the length of the S9-S10 loop: in α-tubulin the loop is extended, in β-tubulin the loop is short.
Extended Data Fig. 4 Microtubule complexes reveal β-tubulin tail recognition by CCP5.
a, b. CCP5 bound to the microtubule, class#2 (a) and class#3 (b). Contour level as in Fig. 2b (σ = 4.3). CCP5 N and catalytic domains colored in orange and green, respectively. α- and β-tubulin, blue and magenta, respectively. c, d. CCP5 binds between two protofilaments and recognizes the β-tubulin tail in its active site, class#2 (c) and class#3 (d). CCP5 and tubulin colored as in (a). e, f. Density for the branch glutamate and branch-point glutamate as well as flanking β-tubulin tail residues is visible in both class #2 (e) and #3 (f). The tubulin tail bends sharply at the +1 position. g-i. Side views of CCP5:microtubule complexes, class#1 (g), class#2 (h) and class#3 (i) showing how CCP5 translocates and pivots on the microtubule while bound to the β-tail. The beginning of the intrinsically disordered α-tubulin tail, C-terminal to α-tubulin helix H12, is indicated with a red asterisk. The CCP5 active site is indicated by an oval. The shortest trajectory for the α-tail to reach the CCP5 active site is denoted in blue dashed lines and its length is calculated assuming α-tail travels above CCP5 surface. The α-tail is too far away from the of CCP5 active site to be efficiently processed, consistent with the activity assays which show preferential removal of glutamates from β-tubulin (Fig. 2d).
Extended Data Fig. 5 CCP5 tail binding interface is highly conserved among CCP5 but variable compared to CCP1.
a. CCP5 molecular surface color-coded based on sequence identity among CCP5 (Supplementary Fig. 4). b. CCP5 surface color-coded based on sequence identity among human, mouse, zebrafish, Chlamydomonas and Tetrahymena CCP5 and CCP1. c. Close-up view of the tubulin tail binding interface showing high conservation between CCP1 and 5 for scissile branch glutamate recognition and a non-conserved molecular surface for tubulin tail binding.
Extended Data Fig. 6 Structure of CCP5 with a βII peptide analog with a glutamate branch at E435 shows no density for the peptide mainchain.
a. Structure of the Glu-P-peptide 2 transition state analog. b. CCP5 active site bound to the Glu-P-peptide 2 analog shows density only for the branch and branch-point glutamates. Scissile branch glutamate, pink, branch-point glutamate, cyan. |Fo| – |Fc| density before the addition of the analog shown as black mesh and contoured at 3.0σ. c. CCP5 active site bound to the Glu-P-peptide 2 analog colored as in (b). |Fo | – |Fc| density before the addition of the analog shown as black mesh and contoured at 2.0σ. No continuous density can be seen for the peptide mainchain. For reference, the position of the Glu-P-peptide 1 analog is shown in the active site in grey ball-and-stick representation. Data for three Glu-P-peptide 2 complex crystals were collected and none showed density for the peptide mainchain. d. Superposition of CCP5 in the CCP5:Glu-P-peptide 1 crystal structure (transition state complex; light grey) with class #1 CCP5:microtubule structure (substrate binding complex; color-coded as in Fig. 2) in which we modeled the βII-tubulin Phe436 at position +1. In the substrate bound structure R303 (green) is displaced relative to the position it occupies in the transition state complex structure (light grey). In the latter, the R303 side chain coordinates the phosphonate. In that conformation it would clash severely with the bulky Phe sidechain at the +1 pos. of the substrate. Cryo-EM map for the β-tubulin tail and CCP5 R303 sidechain contoured at 4.3σ.
Extended Data Fig. 7 Conformation of unmodified and monoglutamylated β tubulin tail peptides in solution.
a, b. HNHα J-couplings (JHNHα) (a) and sequential to intra HαHN NOE intensity ratios (b) for unmodified (blue) and monoglutamylated (red) βII(E440) tubulin tail peptides. Bars represent estimated errors. For J-couplings, the side chain cross peaks to the amide are all split by the same J-coupling. A subset of spectrally well-resolved residues were used to calculate for each residue the rms deviation of the J-coupling measured for the crosspeaks. The largest of these rms deviations, 0.4. Hz, was used as the estimated error for all the J-coupling values. A similar approach was used for the HαHN ratios by comparing the ratios using different multiplet components of the HαHN peaks for a subset of well-resolved residues, yielding an estimated error of 0.3. c, d. Alpha (c) and amide (d) regions of the NOESY spectrum of the unbound βII(E435) peptide. The two red-dashed ovals indicate where the contact signals would appear if the peptide were to adopt the conformation observed in the CCP5:Glu-P-peptide 1 structure. The off-diagonal NOE cross peaks in (d) were used for assignment of sequential residues, and their moderate intensity rules out beta-strand secondary structure. The splitting of the signals in the x-dimension corresponds to the HNHα J-coupling. e, f. HNHα J-couplings (JHNHα) (e) and sequential to intra HαHN NOE intensity ratios (f) for unmodified (blue) and monoglutamylated (red) βII(E435) tubulin tail peptides. Bars represent estimated errors determined as detailed in legend for panels (a) and (b). g, h. Alpha (g) and amide (h) regions of the NOESY spectrum of the unbound βI(E441) peptide. The two red-dashed ovals indicate where the contact signals would appear if the peptide were to adopt the conformation observed in the CCP5:Glu-P-peptide 1 structure. The off-diagonal NOE cross peaks in (b) were used for assignment of sequential residues, and their moderate intensity rules out beta-strand secondary structure. The splitting of the signals in the x-dimension corresponds to the HNHα J-coupling. i, j. HNHα J-couplings (JHNHα) (i) and sequential to intra HαHN NOE intensity ratios (j) for unmodified (blue) and monoglutamylated (red) βI(E441) tubulin tail peptides. Bars represent estimated errors determined as detailed in legend for panels (a) and (b).
Extended Data Fig. 8 Conformation of monoglutamylated α1A/B(E445) tubulin tail peptides in solution.
a, b. Alpha (a) and amide (b) regions of the NOESY spectrum of the unbound α1A/B(E445) peptide. The red-dashed ovals indicate where the contact signals would appear if the peptide were to adopt the conformation observed in the CCP5:Glu-P-peptide 1 structure. Because the residue in the +3 position is a glycine, it has two potential alpha peaks, 2a and 2b. The weak, off-center signal in the region of peak 2b is likely from G(−3), which has alpha resonances similar to G(+3). The off-diagonal NOE cross peaks in (b) were used for assignment of sequential residues, and their moderate intensity rules out beta-strand secondary structure. The splitting of the signals in the x-dimension corresponds to the HNHα J-coupling. c, d. HNHα J-couplings (JHNHα) plot (c) and Sequential to intra HαHN NOE intensity ratios (d) of monoglutamylated α1A/B(E445) tubulin tail peptide. Bars represent estimated errors determined as detailed in legend for panels (a) and (b).
Supplementary information
Supplementary Information
Supplementary Tables 1 and 2 and Supplementary Figs 1–11.
Supplementary Video 1
Cryo-EM reconstruction of CCP5 bound to the microtubule, classes 1, 2 and 3.
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Chen, J., Zehr, E.A., Gruschus, J.M. et al. Tubulin code eraser CCP5 binds branch glutamates by substrate deformation. Nature 631, 905–912 (2024). https://doi.org/10.1038/s41586-024-07699-0
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DOI: https://doi.org/10.1038/s41586-024-07699-0
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