Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

ChromID identifies the protein interactome at chromatin marks

Nature Biotechnology volume 38, pages 728–736 (2020)Cite this article

Subjects

A Publisher Correction to this article was published on 17 March 2020

This article has been updated

Abstract

Chromatin modifications regulate genome function by recruiting proteins to the genome. However, the protein composition at distinct chromatin modifications has yet to be fully characterized. In this study, we used natural protein domains as modular building blocks to develop engineered chromatin readers (eCRs) selective for DNA methylation and histone tri-methylation at H3K4, H3K9 and H3K27 residues. We first demonstrated their utility as selective chromatin binders in living cells by stably expressing eCRs in mouse embryonic stem cells and measuring their subnuclear localization, genomic distribution and histone-modification-binding preference. By fusing eCRs to the biotin ligase BASU, we established ChromID, a method for identifying the chromatin-dependent protein interactome on the basis of proximity biotinylation, and applied it to distinct chromatin modifications in mouse stem cells. Using a synthetic dual-modification reader, we also uncovered the protein composition at bivalently modified promoters marked by H3K4me3 and H3K27me3. These results highlight the ability of ChromID to obtain a detailed view of protein interaction networks on chromatin.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Get just this article for as long as you need it

$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Nuclear and genomic localization indicate correct eCR interactions with the genome.
Fig. 2: Functional analysis indicates dependency on reader domains and modifications for correct eCR localization.
Fig. 3: ChromID identifies proteins associated with H3K9me3 and DNA methylation.
Fig. 4: Generation and validation of eCRs reading bivalent H3K4me3 and H3K27me3 marks.
Fig. 5: ChromID identifies the proteins associated with key chromatin marks in mESCs.

Data availability

All sequencing datasets produced in this study have been deposited in the NCBI Gene Expression Omnibus under accession number GSE128907. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD014483 and PXD017235. Additional genomics datasets used in this study include U2OS FLASH77 (GSE69149); U2OS H3K4me3 (ref. 78) (GSE87831); mESC whole-genome bisulfite sequencing79 (GSE30206); mESC TAF3 (ref. 80) (GSE30959); mESC CBX7 ref. 81) (GSE42466); mESC CBX1 (ref. 27) (GSE71114); mESC bio-tagged MBD1 (ref. 22) (GSE39610); and mESC H4K20me3 from ENCODE (SRR094944).

Change history

References

  1. Allis, C. D. & Jenuwein, T. The molecular hallmarks of epigenetic control. Nat. Rev. Genet. 17, 487–500 (2016).

    CAS  PubMed  Google Scholar 

  2. Taverna, S. D., Li, H., Ruthenburg, A. J., Allis, C. D. & Patel, D. J. How chromatin-binding modules interpret histone modifications: lessons from professional pocket pickers. Nat. Struct. Mol. Biol. 14, 1025–1040 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Musselman, C. A., Lalonde, M.-E., Côté, J. & Kutateladze, T. G. Perceiving the epigenetic landscape through histone readers. Nat. Struct. Mol. Biol. 19, 1218–1227 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Vermeulen, M. et al. Quantitative interaction proteomics and genome-wide profiling of epigenetic histone marks and their readers. Cell 142, 967–980 (2010).

    CAS  PubMed  Google Scholar 

  6. Bartke, T. et al. Nucleosome-interacting proteins regulated by DNA and histone methylation. Cell 143, 470–484 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Nikolov, M. et al. Chromatin affinity purification and quantitative mass spectrometry defining the interactome of histone modification patterns. Mol. Cell. Proteomics 10, M110.005371 (2011).

    PubMed  PubMed Central  Google Scholar 

  8. Eberl, H. C., Spruijt, C. G., Kelstrup, C. D., Vermeulen, M. & Mann, M. A map of general and specialized chromatin readers in mouse tissues generated by label-free interaction proteomics. Mol. Cell 49, 368–378 (2013).

    CAS  PubMed  Google Scholar 

  9. Spruijt, C. G. et al. Dynamic readers for 5-(hydroxy)methylcytosine and its oxidized derivatives. Cell 152, 1146–1159 (2013).

    CAS  PubMed  Google Scholar 

  10. Mittler, G., Butter, F. & Mann, M. A SILAC-based DNA protein interaction screen that identifies candidate binding proteins to functional DNA elements. Genome Res. 19, 284–293 (2008).

    PubMed  Google Scholar 

  11. Déjardin, J. & Kingston, R. E. Purification of proteins associated with specific genomic loci. Cell 136, 175–186 (2009).

    PubMed  PubMed Central  Google Scholar 

  12. Liu, X. et al. In situ capture of chromatin interactions by biotinylated dCas9. Cell 170, 1028–1043 (2017).

  13. Myers, S. A. et al. Discovery of proteins associated with a predefined genomic locus via dCas9–APEX-mediated proximity labeling. Nat. Methods 15, 437–439 (2018).

  14. Schmidtmann, E., Anton, T., Rombaut, P., Herzog, F. & Leonhardt, H. Determination of local chromatin composition by CasID. Nucleus 7, 476–484 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Fischle, W. et al. Molecular basis for the discrimination of repressive methyl-lysine marks in histone H3 by Polycomb and HP1 chromodomains. Genes Dev. 17, 1870–1881 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. Bernstein, E. et al. Mouse Polycomb proteins bind differentially to methylated histone H3 and RNA and are enriched in facultative heterochromatin. Mol. Cell. Biol. 26, 2560–2569 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Bannister, A. J. et al. Selective recognition of methylated lysine 9 on histone H3 by the HP1 chromo domain. Nature 410, 120–124 (2001).

    CAS  PubMed  Google Scholar 

  18. Lachner, M., O’Carroll, D., Rea, S., Mechtler, K. & Jenuwein, T. Methylation of histone H3 lysine 9 creates a binding site for HP1 proteins. Nature 410, 116–120 (2001).

    CAS  PubMed  Google Scholar 

  19. Vermeulen, M. et al. Selective anchoring of TFIID to nucleosomes by trimethylation of histone H3 lysine 4. Cell 131, 58–69 (2007).

    CAS  PubMed  Google Scholar 

  20. Meehan, R. R., Lewis, J. D. & Bird, A. P. Characterization of MeCP2, a vertebrate DNA binding protein with affinity for methylated DNA. Nucleic Acids Res. 20, 5085–5092 (1992).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Nan, X., Meehan, R. R. & Bird, A. Dissection of the methyl-CpG binding domain from the chromosomal protein MeCP2. Nucleic Acids Res. 21, 4886–4892 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Baubec, T., Ivanek, R., Lienert, F. & Schübeler, D. Methylation-dependent and -independent genomic targeting principles of the MBD protein family. Cell 153, 480–492 (2013).

    CAS  PubMed  Google Scholar 

  23. Pasini, D., Bracken, A. P., Hansen, J. B., Capillo, M. & Helin, K. The Polycomb group protein Suz12 is required for embryonic stem cell differentiation. Mol. Cell. Biol. 27, 3769–3779 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. Tsumura, A. et al. Maintenance of self-renewal ability of mouse embryonic stem cells in the absence of DNA methyltransferases Dnmt1, Dnmt3a and Dnmt3b. Genes Cells 11, 805–814 (2006).

    CAS  PubMed  Google Scholar 

  25. Peters, A. H. F. M. et al. Histone H3 lysine 9 methylation is an epigenetic imprint of facultative heterochromatin. Nat. Genet. 30, 77–80 (2001).

    PubMed  Google Scholar 

  26. Xu, J. et al. Super-resolution imaging of higher-order chromatin structures at different epigenomic states in single mammalian cells. Cell Rep. 24, 873–882 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Hiragami-Hamada, K. et al. Dynamic and flexible H3K9me3 bridging via HP1β dimerization establishes a plastic state of condensed chromatin. Nat. Commun. 7, 1–16 (2016).

    Google Scholar 

  28. Yap, K. L. et al. Molecular interplay of the noncoding RNA ANRIL and methylated histone H3 lysine 27 by Polycomb CBX7 in transcriptional silencing of INK4a. Mol. Cell 38, 662–674 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  29. Jørgensen, H. F., Ben-Porath, I. & Bird, A. P. Mbd1 is recruited to both methylated and nonmethylated CpGs via distinct DNA binding domains. Mol. Cell. Biol. 24, 3387–3395 (2004).

    PubMed  PubMed Central  Google Scholar 

  30. Brown, K. et al. The molecular basis of variable phenotypic severity among common missense mutations causing Rett syndrome. Hum. Mol. Genet. 25, 558–570 (2016).

    CAS  PubMed  Google Scholar 

  31. Feller, C., Forné, I., Imhof, A. & Becker, P. B. Global and specific responses of the histone acetylome to systematic perturbation. Mol. Cell 57, 559–571 (2015).

    CAS  PubMed  Google Scholar 

  32. Schotta, G. et al. A silencing pathway to induce H3-K9 and H4-K20 trimethylation at constitutive heterochromatin. Genes Dev. 18, 1251–1262 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Fischle, W. et al. Regulation of HP1–chromatin binding by histone H3 methylation and phosphorylation. Nat. Cell Biol. 438, 1116–1122 (2005).

    CAS  Google Scholar 

  34. Roux, K. J., Kim, D. I., Raida, M. & Burke, B. A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells. J. Cell Biol. 196, 801–810 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Kim, D. I. et al. An improved smaller biotin ligase for BioID proximity labeling. Mol. Biol. Cell 27, 1188–1196 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Ramanathan, M. et al. RNA–protein interaction detection in living cells. Nat. Meth. 15, 207–212 (2018).

    CAS  Google Scholar 

  37. Saksouk, N. et al. Redundant mechanisms to form silent chromatin at pericentromeric regions rely on BEND3 and DNA methylation. Mol. Cell 56, 580–594 (2014).

    CAS  PubMed  Google Scholar 

  38. Tachibana, M. et al. G9a histone methyltransferase plays a dominant role in euchromatic histone H3 lysine 9 methylation and is essential for early embryogenesis. Genes Dev. 16, 1779–1791 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Peters, A. H. et al. Partitioning and plasticity of repressive histone methylation states in mammalian chromatin. Mol. Cell 12, 1577–1589 (2003).

    CAS  PubMed  Google Scholar 

  40. Tchasovnikarova, I. A. et al. Epigenetic silencing by the HUSH complex mediates position-effect variegation in human cells. Science 348, 1481–1485 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Goldberg, A. D. et al. Distinct factors control histone variant H3.3 localization at specific genomic regions. Cell 140, 678–691 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Agarwal, N. et al. MeCP2 interacts with HP1 and modulates its heterochromatin association during myogenic differentiation. Nucleic Acids Res. 35, 5402–5408 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Arita, K. et al. Recognition of modification status on a histone H3 tail by linked histone reader modules of the epigenetic regulator UHRF1. Proc. Natl Acad. Sci. USA 109, 12950–12955 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  44. Ueda, J., Tachibana, M., Ikura, T. & Shinkai, Y. Zinc finger protein Wiz links G9a/GLP histone methyltransferases to the co-repressor molecule CtBP. J. Biol. Chem. 281, 20120–20128 (2006).

    CAS  PubMed  Google Scholar 

  45. Nozawa, R.-S. et al. Human POGZ modulates dissociation of HP1α from mitotic chromosome arms through Aurora B activation. Nat. Cell Biol. 12, 719–727 (2010).

    CAS  PubMed  Google Scholar 

  46. Yin, Y. et al. Impact of cytosine methylation on DNA binding specificities of human transcription factors. Science 356, eaaj2239-17 (2017).

    PubMed  PubMed Central  Google Scholar 

  47. Mikkelsen, T. S. et al. Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448, 553–560 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Yang, X.-C., Burch, B. D., Yan, Y., Marzluff, W. F. & Dominski, Z. FLASH, a proapoptotic protein involved in activation of caspase-8, is essential for 3′ end processing of histone pre-mRNAs. Mol. Cell 36, 267–278 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Doyon, Y., Selleck, W., Lane, W. S., Tan, S. & Côté, J. Structural and functional conservation of the Nua4 histone acetyltransferase complex from yeast to humans. Mol. Cell. Biol. 24, 1884–1896 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  51. Ravens, S., Yu, C., Ye, T., Stierle, M. & Tora, L. Tip60 complex binds to active Pol II promoters and a subset of enhancers and co-regulates the c-Myc network in mouse embryonic stem cells. Epigenetics Chromatin 8, 45 (2015).

  52. Whetstine, J. R. et al. Reversal of histone lysine trimethylation by the JMJD2 family of histone demethylases. Cell 125, 467–481 (2006).

    CAS  PubMed  Google Scholar 

  53. Das, P. P. et al. Distinct and combinatorial functions of Jmjd2b/Kdm4b and Jmjd2c/Kdm4c in mouse embryonic stem cell identity. Mol. Cell 53, 32–48 (2014).

    CAS  PubMed  Google Scholar 

  54. Horton, J. R. et al. Enzymatic and structural insights for substrate specificity of a family of jumonji histone lysine demethylases. Nat. Struct. Mol. Biol. 17, 38–43 (2010).

    CAS  PubMed  Google Scholar 

  55. Aranda, S., Mas, G. & Di Croce, L. Regulation of gene transcription by Polycomb proteins. Sci. Adv. 1, e1500737 (2015).

    PubMed  PubMed Central  Google Scholar 

  56. Williams, K. et al. TET1 and hydroxymethylcytosine in transcription and DNA methylation fidelity. Nature 473, 343–348 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. Delachat, A. M. F. et al. Engineered multivalent sensors to detect coexisting histone modifications in living stem cells. Cell Chem. Biol. 25, 51–56 (2018).

    CAS  PubMed  Google Scholar 

  58. Mauser, R., Kungulovski, G., Keup, C., Reinhardt, R. & Jeltsch, A. Application of dual reading domains as novel reagents in chromatin biology reveals a new H3K9me3 and H3K36me2/3 bivalent chromatin state. Epigenetics Chromatin 10, 45 (2017).

  59. Tekel, S. J. et al. Tandem histone-binding domains enhance the activity of a synthetic chromatin effector. ACS Synth. Biol. 7, 842–852 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Flemr, M. & Bühler, M. Single-step generation of conditional knockout mouse embryonic stem cells. Cell Rep. 12, 709–716 (2015).

  61. Bibel, M., Richter, J., Lacroix, E. & Barde, Y.-A. Generation of a defined and uniform population of CNS progenitors and neurons from mouse embryonic stem cells. Nat. Protoc. 2, 1034–1043 (2007).

    CAS  PubMed  Google Scholar 

  62. Abad, M. A. et al. Borealin–nucleosome interaction secures chromosome association of the chromosomal passenger complex. J. Cell Biol. 218, 3912–3925 (2019).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Manzo, M. et al. Isoform-specific localization of DNMT3A regulates DNA methylation fidelity at bivalent CpG islands. EMBO J. 36, 3421–3434 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Gaidatzis, D., Lerch, A., Hahne, F. & Stadler, M. B. QuasR: quantification and annotation of short reads in R. Bioinformatics 31, 1130–1132 (2015).

    CAS  PubMed  Google Scholar 

  65. Derrien, T. et al. Fast computation and applications of genome mappability. PLoS One 7, e30377 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Heintzman, N. D. et al. Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome. Nat. Genet. 39, 311–318 (2007).

    CAS  PubMed  Google Scholar 

  67. Ernst, J. & Kellis, M. Chromatin-state discovery and genome annotation with ChromHMM. Nat. Protoc. 12, 2478–2492 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. Akalin, A., Franke, V., Vlahoviček, K., Mason, C. E. & Schübeler, D. Genomation: a toolkit to summarize, annotate and visualize genomic intervals. Bioinformatics 31, 1127–1129 (2014).

  69. Feller, C. et al. Histone epiproteomic profiling distinguishes oligodendroglioma, IDH-mutant and 1p/19q co-deleted from IDH-mutant astrocytoma and reveals less tri-methylation of H3K27 in oligodendrogliomas. Acta Neuropathol. 139, 211–213 (2019).

    PubMed  Google Scholar 

  70. Barkow-Oesterreicher, S., Türker, C. & Panse, C. FCC—an automated rule-based processing tool for life science data. Source Code Biol. Med. 8, 3 (2013).

    PubMed  PubMed Central  Google Scholar 

  71. 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).

    CAS  PubMed  Google Scholar 

  72. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016).

    CAS  PubMed  Google Scholar 

  73. Tusher, V. G., Tibshirani, R. & Chu, G. Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl Acad. Sci. USA 98, 5116–5121 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Wiśniewski, J. R., Zougman, A., Nagaraj, N. & Mann, M. Universal sample preparation method for proteome analysis. Nat. Methods 6, 359–362 (2009).

    PubMed  Google Scholar 

  75. Tsou, C.-C. et al. DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics. Nat. Methods 12, 258–264 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  76. Szklarczyk, D. et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607–D613 (2019).

    CAS  PubMed  Google Scholar 

  77. Sokolova, M. et al. Genome-wide screen of cell-cycle regulators in normal and tumor cells identifies a differential response to nucleosome depletion. Cell Cycle 16, 189–199 (2017).

    CAS  PubMed  Google Scholar 

  78. Ibarra, A., Benner, C., Tyagi, S., Cool, J. & Hetzer, M. W. Nucleoporin-mediated regulation of cell identity genes. Genes Dev. 30, 2253–2258 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Stadler, M. B. et al. DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 480, 490–495 (2011).

    CAS  PubMed  Google Scholar 

  80. Liu, Z., Scannell, D. R., Eisen, M. B. & Tjian, R. Control of embryonic stem cell lineage commitment by core promoter factor, TAF3. Cell 146, 720–731 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Morey, L., Aloia, L., Cozzuto, L., Benitah, S. A. & Di Croce, L. RYBP and Cbx7 define specific biological functions of Polycomb complexes in mouse embryonic stem cells. Cell Rep. 3, 60–69 (2013).

    CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank D. Schübeler (FMI, Basel) for providing the Dnmt-TKO embryonic stem cell line and P. A. Khavari (Stanford) for cDNA encoding the BASU biotin ligase. Furthermore, we thank B. Roschitzki, J. Grossmann, T. Kockmann, P. Knobel, M. Majchrzak and R. Klemm for initial discussions on biotin-ID methods and MS detection. We would like to thank members of the Functional Genomics Center Zurich for high-throughput sequencing and MS support, members of the Centre for Microscopy and Image Analysis for their support and the Science IT team at the University of Zurich for providing the computational infrastructure. We are grateful to the Edinburgh Protein Production Facility for their support. We thank V. Major for help with cloning and K. Webb for help with histone purification. Furthermore, we thank M. Altmeyer, A. Krebs, D. Schübeler and members of the Baubec laboratory for their critical input on the manuscript. The authors would like to acknowledge the following support: Swiss National Science Foundation 157488 and 180345 to T.B. and 107679 to R.A.; Swiss Initiative in Systems Biology (SystemsX.ch) 2015/322 to T.B.; ERC-AdvGr 670821-Proteomics 4D to R.A.; ERC-STG 639253 to P.V.; Innovative Medicines Initiative (EU/EFPIA) ULTRA-DD grant 115766 to R.A; Wellcome Trust (104175/Z/14/Z, Sir Henry Dale Fellowship) to P.V.; EMBO long-term fellowships to N.S. and C.F.; a UZH Forschungskredit fellowship to N.S.; a UZH Candoc fellowship to C.A.; Wellcome Trust Doctoral Studentship 105244 to E.B.; and Wellcome Trust core funding 203149 and 101527/Z/13/Z to Wellcome Centre for Cell Biology and Edinburgh Protein Production Facility, respectively.

Author information

Authors and Affiliations

  1. Department of Molecular Mechanism of Disease, University of Zurich, Zurich, Switzerland

    Rodrigo Villaseñor, Ramon Pfaendler, Christina Ambrosi, Stefan Butz, Sara Giuliani, Nina Schmolka, Massimiliano Manzo, Joël Wirz & Tuncay Baubec

  2. Life Science Zurich Graduate School, University of Zurich and ETH Zurich, Zurich, Switzerland

    Christina Ambrosi, Stefan Butz, Annika L. Gable & Massimiliano Manzo

  3. Wellcome Centre for Cell Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, UK

    Elana Bryan, Thomas W. Sheahan & Philipp Voigt

  4. Institute of Molecular Life Sciences and Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland

    Annika L. Gable & Christian von Mering

  5. Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland

    Christian Feller & Ruedi Aebersold

  6. Faculty of Science, University of Zurich, Zurich, Switzerland

    Ruedi Aebersold

Authors
  1. Rodrigo Villaseñor
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ramon Pfaendler
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Christina Ambrosi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Stefan Butz
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Sara Giuliani
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Elana Bryan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Thomas W. Sheahan
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Annika L. Gable
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Nina Schmolka
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Massimiliano Manzo
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Joël Wirz
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Christian Feller
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Christian von Mering
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Ruedi Aebersold
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Philipp Voigt
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Tuncay Baubec
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

R.V. and T.B. conceived and designed the study. R.V., R.P., N.S., M.M. and T.B. developed tools and protocols. R.V., R.P., S.B., S.G., C.A. and J.W. generated cell lines and performed experiments. C.F. and R.A. designed and performed LC–MS experiments, analyzed data and interpreted results for histone PTM detection. A.L.G. performed STRING network analysis with supervision from C.v.M. E.B. and T.S. performed nucleosome reconstitution and interaction experiments under supervision from P.V. R.V., R.P., M.M. and T.B. analyzed data. R.V. and T.B. wrote the manuscript with input from all authors.

Corresponding author

Correspondence to Tuncay Baubec.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

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

Supplementary information

Supplementary Information

Supplementary Figs. 1–15

Reporting Summary

Supplementary Table 1

Dentified proximal interactome at H3K4me3, H3K27me3, H3K9me3 and bivalently marked H3K4me3/H3K27me3 sites. Identified proteins from ChromID experiments using histone modification eCRs, including log2FC, P values and a Boolean indicator if called significant.

Supplementary Table 2

Identified proximal interactome at 5-methyl-CpG DNA methylated sites. Identified proteins from ChromID experiments using the 5-methyl-CpG-specific eCR, including log2FC, P values and a Boolean indicator if called significant.

Supplementary Table 3

Estimation of protein abundance by data-independent acquisition in eCR-expressing cells. Protein abundance is based on average intensities calculated from the top three peptides per protein.

Supplementary Video 1

Time-lapse fluorescence imaging of proliferating eGFP+ control cells. Cells undergoing division at one selected region were imaged at 5‐min intervals for approximately 12.5 h. The video was generated using FIJI (version 2.0.0) and the Bio-Formats Importer plugin. An appropriate xy region and a single z plane were selected for further image series analysis and display. Scale bar, 5 µm.

Supplementary Video 2

Time-lapse fluorescence imaging of proliferating H3K27me3-reader cells. Cells undergoing division at one selected region were imaged at 5‐min intervals for approximately 12.5 h. The video was generated using FIJI (version 2.0.0) and the Bio-Formats Importer plugin. An appropriate xy region and a single z plane were selected for further image series analysis and display. Scale bar, 5 µm.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Villaseñor, R., Pfaendler, R., Ambrosi, C. et al. ChromID identifies the protein interactome at chromatin marks. Nat Biotechnol 38, 728–736 (2020). https://doi.org/10.1038/s41587-020-0434-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41587-020-0434-2

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research