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Decoding the protein composition of whole nucleosomes with Nuc-MS

Abstract

Current proteomic approaches disassemble and digest nucleosome particles, blurring readouts of the ‘histone code’. To preserve nucleosome-level information, we developed Nuc-MS, which displays the landscape of histone variants and their post-translational modifications (PTMs) in a single mass spectrum. Combined with immunoprecipitation, Nuc-MS quantified nucleosome co-occupancy of histone H3.3 with variant H2A.Z (sixfold over bulk) and the co-occurrence of oncogenic H3.3K27M with euchromatic marks (for example, a >15-fold enrichment of dimethylated H3K79me2). Nuc-MS is highly concordant with chromatin immunoprecipitation-sequencing (ChIP-seq) and offers a new readout of nucleosome-level biology.

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Fig. 1: Three strategies for histone analysis, including Nuc-MS for the direct interrogation of intact nucleosomes.
Fig. 2: Nuc-MS analysis of endogenous mononucleosomes from HEK293T cells.
Fig. 3: Nuc-MS of endogenous nucleosomes prepared from cells with H3.3-FLAG-HA WT or K27M.

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Data availability

MS1, MS2 and MS3 spectra presented in the paper are available online in the MassIVE database under accession code MSV000085238 and can be visualized with Thermo Qual Browser. Source data are provided with this paper.

References

  1. Moller, J. & de Pablo, J. J. Bottom–up meets top–down: the crossroads of multiscale chromatin modeling. Biophys. J. 118, 2057–2065 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Campos, E. I. & Reinberg, D. Histones: annotating chromatin. Annu. Rev. Genet. 43, 559–599 (2009).

    Article  CAS  PubMed  Google Scholar 

  3. Bannister, A. J. & Kouzarides, T. Regulation of chromatin by histone modifications. Cell Res. 21, 381–395 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Portela, A. & Esteller, M. Epigenetic modifications and human disease. Nat. Biotechnol. 28, 1057–1068 (2010).

    Article  CAS  PubMed  Google Scholar 

  5. Patel, D. J. & Wang, Z. Readout of epigenetic modifications. Annu. Rev. Biochem. 82, 81–118 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Zink, L. M. & Hake, S. B. Histone variants: nuclear function and disease. Curr. Opin. Genet. Dev. 37, 82–89 (2016).

    Article  CAS  PubMed  Google Scholar 

  7. Ruthenburg, A. J., Li, H., Patel, D. J. & Allis, C. D. Multivalent engagement of chromatin modifications by linked binding modules. Nat. Rev. Mol. Cell Biol. 8, 983–994 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Ichikawa, Y. et al. A synthetic biology approach to probing nucleosome symmetry. eLife 6, e28836 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Voigt, P. et al. Asymmetrically modified nucleosomes. Cell 151, 181–193 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Zheng, Y., Huang, X. & Kelleher, N. L. Epiproteomics: quantitative analysis of histone marks and codes by mass spectrometry. Curr. Opin. Chem. Biol. 33, 142–150 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Shah, R. N. et al. Examining the roles of H3K4 methylation states with systematically characterized antibodies. Mol. Cell 72, 162–177 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Compton, P. D., Kelleher, N. L. & Gunawardena, J. Estimating the distribution of protein post-translational modification states by mass spectrometry. J. Proteome Res. 17, 2727–2734 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  13. Belov, M. E. et al. From protein complexes to subunit backbone fragments: a multi-stage approach to native mass spectrometry. Anal. Chem. 85, 11163–11173 (2013).

    Article  CAS  PubMed  Google Scholar 

  14. Azegami, N. et al. Conclusive evidence of the reconstituted hexasome proven by native mass spectrometry. Biochemistry 52, 5155–5157 (2013).

    Article  CAS  PubMed  Google Scholar 

  15. Lercher, L. et al. Generation of a synthetic GlcNAcylated nucleosome reveals regulation of stability by H2A-Thr101 GlcNAcylation. Nat. Commun. 6, 7978 (2015).

    Article  CAS  PubMed  Google Scholar 

  16. Jin, C. et al. H3.3/H2A.Z double variant-containing nucleosomes mark ‘nucleosome-free regions’ of active promoters and other regulatory regions. Nat. Genet. 41, 941–945 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Cui, K. et al. Chromatin signatures in multipotent human hematopoietic stem cells indicate the fate of bivalent genes during differentiation. Cell Stem Cell 4, 80–93 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Talasz, H., Lindner, H. H., Sarg, B. & Helliger, W. Histone H4-lysine 20 monomethylation is increased in promoter and coding regions of active genes and correlates with hyperacetylation. J. Biol. Chem. 280, 38814–38822 (2005).

    Article  CAS  PubMed  Google Scholar 

  19. Svensson, J. P. et al. A nucleosome turnover map reveals that the stability of histone H4 Lys20 methylation depends on histone recycling in transcribed chromatin. Genome Res. 25, 872–883 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Lulla, R. R., Saratsis, A. M. & Hashizume, R. Mutations in chromatin machinery and pediatric high-grade glioma. Sci. Adv. 2, e1501354 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Herz, H.-M. et al. Histone H3 lysine-to-methionine mutants as a paradigm to study chromatin signaling. Science 345, 1065–1070 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Brumbaugh, J. et al. Inducible histone K-to-M mutations are dynamic tools to probe the physiological role of site-specific histone methylation in vitro and in vivo. Nat. Cell Biol. 21, 1449–1461 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Piunti, A. et al. Therapeutic targeting of polycomb and BET bromodomain proteins in diffuse intrinsic pontine gliomas. Nat. Med. 23, 493–500 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Taylor, G. C. A., Eskeland, R., Hekimoglu-Balkan, B., Pradeepa, M. M. & Bickmore, W. A. H4K16 acetylation marks active genes and enhancers of embryonic stem cells, but does not alter chromatin compaction. Genome Res. 23, 2053–2065 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Nguyen, A. T. & Zhang, Y. The diverse functions of Dot1 and H3K79 methylation. Genes Dev. 25, 1345–1358 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Sweet, S. M. M., Li, M., Thomas, P. M., Durbin, K. R. & Kelleher, N. L. Kinetics of re-establishing H3K79 methylation marks in global human chromatin. J. Biol. Chem. 285, 32778–32786 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Wang, Y. et al. Histone variants H2A.Z and H3.3 coordinately regulate PRC2-dependent H3K27me3 deposition and gene expression regulation in mES cells. BMC Biol. 16, 107 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Lowe, B. R., Maxham, L. A., Hamey, J. J., Wilkins, M. R. & Partridge, J. F. Histone H3 mutations: an updated view of their role in chromatin deregulation and cancer. Cancers 11, 660 (2019).

    Article  CAS  PubMed Central  Google Scholar 

  29. Talbert, P. B. & Henikoff, S. Histone variants—ancient wrap artists of the epigenome. Nat. Rev. Mol. Cell Biol. 11, 264–275 (2010).

    Article  CAS  PubMed  Google Scholar 

  30. Skene, P. J. & Henikoff, S. An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. eLife 6, e21856 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  31. Huang, C. et al. H3.3–H4 tetramer splitting events feature cell-type specific enhancers. PLoS Genet. 9, e1003558 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Zhao, Z. & Shilatifard, A. Epigenetic modifications of histones in cancer. Genome Biol. 20, 245 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  33. Luger, K., Mader, A. W., Richmond, R. K., Sargent, D. F. & Richmond, T. J. Crystal structure of the nucleosome core particle at 2.8 Å resolution. Nature 389, 251–260 (1997).

    Article  CAS  PubMed  Google Scholar 

  34. Lee, T. I., Johnstone, S. E. & Young, R. A. Chromatin immunoprecipitation and microarray-based analysis of protein location. Nat. Protoc. 1, 729–748 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Vo, B. et al. Inactivation of Ezh2 upregulates Gfi1 and drives aggressive Myc-driven Group 3 medulloblastoma. Cell Rep. 18, 2907–2917 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Andrews, S. FastQC: a quality control tool for high throughput sequence data. Babraham Bioinformatics http://www.bioinformatics.babraham.ac.uk/projects/fastqc (2010).

  37. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zhang, Y. et al. Model-based Analysis of ChIP-seq (MACS). Genome Biol. 9, R137 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Ross-Innes, C. S. et al. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 481, 389–393 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Yu, G., Wang, L.-G., Han, Y. & He, Q.-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160–W165 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Edgar, R., Domrachev, M. & Lash, A. E. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 30, 207–210 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Schachner, L. F., Lee, A. & Kelleher, N. L. Protocol for decoding the protein composition of whole nucleosomes with Nuc-MS: sample preparation, data acquisition and analysis. Protocol Exchange https://doi.org/10.21203/rs.3.pex-1288/v1 (2020).

  45. Zhang, Z. & Marshall, A. G. A universal algorithm for fast and automated charge state deconvolution of electrospray mass-to-charge ratio spectra. J. Am. Soc. Mass Spectrom. 9, 225–233 (1998).

    Article  CAS  PubMed  Google Scholar 

  46. Marty, M. T. et al. Bayesian deconvolution of mass and ion mobility spectra: from binary interactions to polydisperse ensembles. Anal. Chem. 87, 4370–4376 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Fellers, R. T. et al. ProSight Lite: graphical software to analyze top–down mass spectrometry data. Proteomics 15, 1235–1238 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Fornelli, L. et al. Accurate sequence analysis of a monoclonal antibody by top–down and middle–down orbitrap mass spectrometry applying multiple ion activation techniques. Anal. Chem. 90, 8421–8429 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Bland, J. M. & Altman, D. G. Multiple significance tests: the Bonferroni method. BMJ 310, 170 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Kafader, J. O. et al. Multiplexed mass spectrometry of individual ions improves measurement of proteoforms and their complexes. Nat. Methods 17, 391–394 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by the National Institute of General Medical Sciences (P41 GM108569) for the National Resource for Translational and Developmental Proteomics at Northwestern University and NIH grants S10OD025194 and RF1AG063903 (Kelleher laboratory) and R44GM116584, R44CA212733 and R44CA214076 (EpiCypher). L.F.S. is a Gilliam Fellow of the Howard Hughes Medical Institute. Research in this publication is also supported by Thermo Fisher Scientific and a fellowship associated with the Chemistry of Life Processes Predoctoral Training grant T32GM105538 at Northwestern University. A.P. is supported by the Transition to Independence grant K99CA234434-01. We also thank M. Senko, P. Compton, C. Koo, L. Szymczak and M. McAnnally for technical assistance and S. Judge and A. Rosenzweig for providing thoughtful suggestions to improve the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

L.F.S. performed Nuc-MS data acquisition and analysis. K.J. assisted with proteoform quantitation and MS analysis. A.P., M.A.M., A.S.L. and A.S. prepared and made available H3.3K27M-FLAG and H3.3WT-FLAG mononucleosomes. M.A.M. and M.I. conducted and analyzed ChIP-seq experiments. J.O.K. assisted with acquisition of multiplexed I2MS data on endogenous nucleosomes. M.J.M., M.A.C., J.M.B. and S.A.H. assisted with synthesis, purification and verification of modified nucleosomes. M.-C.K. coordinated modified nucleosome synthesis and provided insightful feedback on the manuscript. L.F.S. and N.L.K. conceived the project and wrote the manuscript.

Corresponding author

Correspondence to Neil L. Kelleher.

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Competing interests

N.L.K. serves as a consultant to Thermo Fisher Scientific. EpiCypher is a commercial developer and supplier of reagents, including the recombinant semi-synthetic modified nucleosomes (dNucs) used in this study. The other authors declare no competing interests.

Additional information

Peer review information Arunima Singh was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–19, Tables 1–3 and Protocol.

Reporting Summary

Supplementary Data 1

Statistical source data and analysis for quantitative comparison of two equimolar synthetic Nucs presented in Supplementary Fig. 4b.

Supplementary Data 2

Statistical source data and analysis for quantitative comparison of H3.3 and HEK293T bulk Nucs presented in Supplementary Fig. 9.

Supplementary Data 3

Statistical source data and analysis for quantitative comparison of H3.3K27M fragments that localize to K79me2 in Supplementary Fig. 14.

Supplementary Data 4

Uncropped western blots for data presented in Supplementary Fig. 17.

Source data

Source Data Fig. 3

Statistical source data and analysis for quantitative comparison of H3.3K27M and WT Nucs presented in Fig. 3c–e.

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Schachner, L.F., Jooß, K., Morgan, M.A. et al. Decoding the protein composition of whole nucleosomes with Nuc-MS. Nat Methods 18, 303–308 (2021). https://doi.org/10.1038/s41592-020-01052-9

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