Abstract
Biotin proximity labeling has largely extended the toolbox of mass spectrometry-based interactomics. To date, BirA, engineered BirA variants, or other biotinylating enzymes have been widely applied to characterize protein interactions. By implementing chromatin purification-based methods the genome-wide interactome of proteins can be defined. However, acquiring a high-resolution interactome of a single genomic locus preferably by multiplexed measurements of several distinct genomic loci in parallel remains challenging. We recently developed CasID, a novel approach where the catalytically inactive Cas9 (dCas9) is coupled to the promiscuous biotin ligase BirA (BirA∗). With CasID, first the local proteome at repetitive telomeric, major satellite, and minor satellite regions was determined. With more efficient biotin ligases and sensitive mass spectrometry, others have successfully identified the chromatin composition at even smaller genomic, non-repetitive regions of a few hundred base pairs in length. Here, we summarize the most recent developments towards interactomics at a single genomic locus and provide a step-by-step protocol based on the CasID approach.
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References
Wierer M, Mann M (2016) Proteomics to study DNA-bound and chromatin-associated gene regulatory complexes. Hum Mol Genet 25:R106–R114. https://doi.org/10.1093/hmg/ddw208
Kustatscher G, KLH W, Furlan C, Rappsilber J (2014) Chromatin enrichment for proteomics. Nat Protoc 9:2090–2099. https://doi.org/10.1038/nprot.2014.142
Ginno PA, Burger L, Seebacher J et al (2018) Cell cycle-resolved chromatin proteomics reveals the extent of mitotic preservation of the genomic regulatory landscape. Nat Commun 9:4048. https://doi.org/10.1038/s41467-018-06007-5
Federation AJ, Nandakumar V, Wang H et al (2018) Quantification of nuclear protein dynamics reveals chromatin remodeling during acute protein degradation.bioRxiv 345686. https://doi.org/10.1101/345686.
Déjardin J, Kingston RE (2009) Purification of proteins associated with specific genomic Loci. Cell 136:175–186. https://doi.org/10.1016/j.cell.2008.11.045
Fujita T, Asano Y, Ohtsuka J et al (2013) Identification of telomere-associated molecules by engineered DNA-binding molecule-mediated chromatin immunoprecipitation (enChIP). Sci Rep 3:3171. https://doi.org/10.1038/srep03171
Schmidtmann E, Anton T, Rombaut P et al (2016) Determination of local chromatin composition by CasID. Nucleus 7:476–484. https://doi.org/10.1080/19491034.2016.1239000
Kim DI, Jensen SC, Noble KA et al (2016) An improved smaller biotin ligase for BioID proximity labeling. Mol Biol Cell 27:1188–1196. https://doi.org/10.1091/mbc.E15-12-0844
Roux KJ, Kim DI, Raida M, Burke B (2012) A promiscuous biotin ligase fusion protein identifies proximal and interacting proteins in mammalian cells. J Cell Biol 196:801–810. https://doi.org/10.1083/jcb.201112098
Papageorgiou DN, Demmers J, Strouboulis J (2013) NP-40 reduces contamination by endogenous biotinylated carboxylases during purification of biotin tagged nuclear proteins. Protein Expr Purif 89:80–83. https://doi.org/10.1016/j.pep.2013.02.015
Lobingier BT, Hüttenhain R, Eichel K et al (2017) An approach to spatiotemporally resolve protein interaction networks in living cells. Cell 169:350–360.e12. https://doi.org/10.1016/j.cell.2017.03.022
Trinkle-Mulcahy L (2019) Recent advances in proximity-based labeling methods for interactome mapping. F1000Res 8. https://doi.org/10.12688/f1000research.16903.1
Lambert J-P, Tucholska M, Go C et al (2015) Proximity biotinylation and affinity purification are complementary approaches for the interactome mapping of chromatin-associated protein complexes. J Proteomics 118:81–94. https://doi.org/10.1016/j.jprot.2014.09.011
Lam SS, Martell JD, Kamer KJ et al (2015) Directed evolution of APEX2 for electron microscopy and proximity labeling. Nat Methods 12:51–54. https://doi.org/10.1038/nmeth.3179
Branon TC, Bosch JA, Sanchez AD et al (2018) Efficient proximity labeling in living cells and organisms with TurboID. Nat Biotechnol 36:880–887. https://doi.org/10.1038/nbt.4201
Gao XD, Tu L-C, Mir A et al (2018) C-BERST: defining subnuclear proteomic landscapes at genomic elements with dCas9-APEX2. Nat Methods 15:433–436. https://doi.org/10.1038/s41592-018-0006-2
Myers SA, Wright J, Peckner R et al (2018) Discovery of proteins associated with a predefined genomic locus via dCas9-APEX-mediated proximity labeling. Nat Methods 15:437–439. https://doi.org/10.1038/s41592-018-0007-1
Qiu W, Xu Z, Zhang M et al (2019) Determination of local chromatin interactions using a combined CRISPR and peroxidase APEX2 system. Nucleic Acids Res 47:e52. https://doi.org/10.1093/nar/gkz134
Anton T, Bultmann S, Leonhardt H, Markaki Y (2014) Visualization of specific DNA sequences in living mouse embryonic stem cells with a programmable fluorescent CRISPR/Cas system. Nucleus 5:163–172. https://doi.org/10.4161/nucl.28488
Li X, Burnight ER, Cooney AL et al (2013) piggyBac transposase tools for genome engineering. Proc Natl Acad Sci U S A 110:E2279–E2287. https://doi.org/10.1073/pnas.1305987110
Kowarz E, Löscher D, Marschalek R (2015) Optimized Sleeping Beauty transposons rapidly generate stable transgenic cell lines. Biotechnol J 10:647–653. https://doi.org/10.1002/biot.201400821
Rappsilber J, Mann M, Ishihama Y (2007) Protocol for micro-purification, enrichment, pre-fractionation and storage of peptides for proteomics using StageTips. Nat Protoc 2:1896–1906. https://doi.org/10.1038/nprot.2007.261
Scheltema RA, Mann M (2012) SprayQc: a real-time LC–MS/MS quality monitoring system to maximize uptime using off the shelf components. J Proteome Res 11:3458–3466. https://doi.org/10.1021/pr201219e
Cox J, Mann M (2008) MaxQuant enables high peptide identification rates, individualized ppb-range mass accuracies and proteome-wide protein quantification. Nat Biotechnol 26:1367
Cox J, Neuhauser N, Michalski A et al (2011) Andromeda: a peptide search engine integrated into the MaxQuant environment. J Proteome Res 10:1794–1805. https://doi.org/10.1021/pr101065j
Cox J, Hein MY, Luber CA et al (2014) Accurate proteome-wide label-free quantification by delayed normalization and maximal peptide ratio extraction, termed MaxLFQ. Mol Cell Proteomics 13:2513–2526. https://doi.org/10.1074/mcp.M113.031591
Tyanova S, Temu T, Sinitcyn P et al (2016) The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat Methods 13:731
Acknowledgments
EU and MDB are fellows of the International Max Planck Research School for Molecular Life Sciences (IMPRS-LS). EU is supported by the research training group 1721 (RTG 1721), a graduate school of the Deutsche Forschungsgemeinschaft (DFG). The work on chromatin composition is supported by the DFG (SFB 1064/A17 to HL).
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Ugur, E., Bartoschek, M.D., Leonhardt, H. (2020). Locus-Specific Chromatin Proteome Revealed by Mass Spectrometry-Based CasID. In: Hancock, R. (eds) The Nucleus . Methods in Molecular Biology, vol 2175. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0763-3_9
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DOI: https://doi.org/10.1007/978-1-0716-0763-3_9
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