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C-BERST: defining subnuclear proteomic landscapes at genomic elements with dCas9–APEX2

Nature Methods volume 15, pages 433–436 (2018)Cite this article

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Abstract

Mapping proteomic composition at distinct genomic loci in living cells has been a long-standing challenge. Here we report that dCas9–APEX2 biotinylation at genomic elements by restricted spatial tagging (C-BERST) allows the rapid, unbiased mapping of proteomes near defined genomic loci, as demonstrated for telomeres and centromeres. C-BERST enables the high-throughput identification of proteins associated with specific sequences, thereby facilitating annotation of these factors and their roles.

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Fig. 1: Using C-BERST to biotinylate telomere-associated proteins in living human cells.
Fig. 2: Successful capture of α-satellite-associated proteomes in live human cells by C-BERST.

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References

  1. Davies, J. O., Oudelaar, A. M., Higgs, D. R. & Hughes, J. R. Nat. Methods 14, 125–134 (2017).

    Article  PubMed  CAS  Google Scholar 

  2. Dominguez, A. A., Lim, W. A. & Qi, L. S. Nat. Rev. Mol. Cell Biol. 17, 5–15 (2016).

    Article  PubMed  CAS  Google Scholar 

  3. Roux, K. J., Kim, D. I., Raida, M. & Burke, B. J. Cell Biol. 196, 801–810 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  4. Schmidtmann, E., Anton, T., Rombaut, P., Herzog, F. & Leonhardt, H. Nucleus 7, 476–484 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  5. Liu, X. et al. Cell 170, 1028–1043 (2017).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  6. Hung, V. et al. Mol. Cell 55, 332–341 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  7. Rhee, H. W. et al. Science 339, 1328–1331 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Chen, B. et al. Cell 155, 1479–1491 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Ma, H. et al. Proc. Natl. Acad. Sci. USA 112, 3002–3007 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Cesare, A. J. & Reddel, R. R. Nat. Rev. Genet. 11, 319–330 (2010).

    Article  PubMed  CAS  Google Scholar 

  11. Banaszynski, L. A., Chen, L. C., Maynard-Smith, L. A., Ooi, A. G. & Wandless, T. J. Cell 126, 995–1004 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  12. Knight, S. C. et al. Science 350, 823–826 (2015).

    Article  PubMed  CAS  Google Scholar 

  13. Garcia-Exposito, L. et al. Cell Rep. 17, 1858–1871 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  14. Déjardin, J. & Kingston, R. E. Cell 136, 175–186 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Buxton, K. E. et al. J. Proteome Res. 16, 3433–3442 (2017).

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  16. Chen, B. et al. Nucleic Acids Res. 44, e75 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Foltz, D. R. et al. Nat. Cell Biol. 8, 458–469 (2006).

    Article  PubMed  CAS  Google Scholar 

  18. Verdaasdonk, J. S. & Bloom, K. Nat. Rev. Mol. Cell Biol. 12, 320–332 (2011).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. Carmena, M., Wheelock, M., Funabiki, H. & Earnshaw, W. C. Nat. Rev. Mol. Cell Biol. 13, 789–803 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Kabeche, L., Nguyen, H. D., Buisson, R. & Zou, L. Science 359, 108–114 (2018).

    Article  PubMed  CAS  Google Scholar 

  21. Ma, H. et al. J. Cell Biol. 214, 529–537 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Follit, J. A., Tuft, R. A., Fogarty, K. E. & Pazour, G. J. Mol. Biol. Cell 17, 3781–3792 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Nagano, T. et al. Nature 502, 59–64 (2013).

    Article  PubMed  CAS  Google Scholar 

  24. Zhang, Z., Theurkauf, W. E., Weng, Z. & Zamore, P. D. Silence 3, 9 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Kelstrup, C. D. et al. J. Proteome Res. 13, 6187–6195 (2014).

    Article  PubMed  CAS  Google Scholar 

  26. Keller, A., Nesvizhskii, A. I., Kolker, E. & Aebersold, R. Anal. Chem. 74, 5383–5392 (2002).

    Article  PubMed  CAS  Google Scholar 

  27. Nesvizhskii, A. I., Keller, A., Kolker, E. & Aebersold, R. Anal. Chem. 75, 4646–4658 (2003).

    Article  PubMed  CAS  Google Scholar 

  28. Smyth, G. K. Stat. Appl. Genet. Mol. Biol. 3, e3 (2004).

    Article  Google Scholar 

  29. Benjamini, Y. & Hochberg, Y. J. R. Stat. Soc. Series B Methodol. 57, 289–300 (1995).

    Google Scholar 

  30. Gao, X. D. et al. Protoc. Exch. https://doi.org/10.1038/protex.2018.036 (2018).

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Acknowledgements

We are grateful to all members of the Sontheimer, Wolfe, and Dekker labs for advice and discussions; T. Fazzio, S. Bhaduri, and M. Green for helpful feedback; H. Ma, T. Wu, D. Grünwald, and T. Pederson (University of Massachusetts Medical School, Worcester, MA, USA) for reagents; the Flow Cytometry Core Facility at UMass Medical School for cell sorting; and L. Zhu for assistance with figure preparation. This work was supported by the US National Institutes of Health (4D Nucleome grant U54 DK107980 to J.D., S.A.W., and E.J.S.).

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Authors and Affiliations

  1. RNA Therapeutics Institute, University of Massachusetts Medical School, Worcester, MA, USA

    Xin D. Gao, Li-Chun Tu, Aamir Mir, Tomás Rodriguez, Yuehe Ding & Erik J. Sontheimer

  2. Proteomics and Mass Spectrometry Facility, University of Massachusetts Medical School, Worcester, MA, USA

    John Leszyk & Scott A. Shaffer

  3. Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA

    John Leszyk, Job Dekker, Scott A. Shaffer & Scot A. Wolfe

  4. Program in Systems Biology, University of Massachusetts Medical School, Worcester, MA, USA

    Job Dekker

  5. Howard Hughes Medical Institute, University of Massachusetts Medical School, Worcester, MA, USA

    Job Dekker

  6. Department of Molecular, Cell and Cancer Biology, University of Massachusetts Medical School, Worcester, MA, USA

    Lihua Julie Zhu & Scot A. Wolfe

  7. Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA

    Lihua Julie Zhu

  8. Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA, USA

    Lihua Julie Zhu & Erik J. Sontheimer

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  1. Xin D. Gao
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Contributions

X.D.G. and E.J.S. conceived the study. X.D.G., L.-C.T., A.M., T.R., J.D., S.A.S., S.A.W., and E.J.S. designed experiments. X.D.G. and T.R. performed C-BERST and ChIP-seq experiments, and S.A.S. and J.L. designed and conducted mass spectrometry procedures. X.D.G. and L.-C.T. processed fluorescence images; A.M. processed flow cytometry data; A.M. and T.R. processed ChIP-seq data; X.D.G., Y.D., J.L., and S.A.S. processed mass spectrometry data; and L.J.Z. conducted statistical analyses. All authors interpreted the data. X.D.G. and E.J.S. wrote the manuscript, and all authors contributed to revision and editing of the manuscript.

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Correspondence to Erik J. Sontheimer.

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Integrated supplementary information

Supplementary Figure 1 Inducible dSpyCas9–mCherry–APEX2 expression.

(a) The dSpyCas9-mCherry-APEX2 and sgRNA lentiviral expression constructs. Top: dSpyCas9-mCherry-APEX2 under the control of the pCMV_TetO inducible promoter. The mCherry fusion is included to enable quantification of dSpyCas9 expression level as well as its subcellular localization. NLS, nuclear localization signal; LTR, long terminal repeat; DD, Shield1-repressible degradation domain. Bottom: sgRNA/TetR/BFP expression construct. pU6, U6 promoter; pPGK, PGK promoter; sgTelo, telomere-targeting sgRNA; sgNS, non-specific sgRNA; tetR, tet repressor; P2A, 2A self-cleaving peptide; BFP, blue fluorescent protein. (b) Flow cytometry was used to measure the percentage of mCherry+ and BFP+ double-positive cells under different induction conditions. Stable U2OS cells expressing sgTelo (top row) or sgNS (bottom row) were exposed to three conditions for 21h before flow cytometry: no inducers (left), dox only (2 µg/ml, middle), or a combination of dox (2 µg/ml) and Shield1 (250 nM) (right). Cyan: untransduced cells; red: transduced cells. With both sgRNAs, dox and Shield1 in combination yield the highest percentages of double-positive cells. Specific percentages of mCherry+, BFP+ cells are indicated in each plot from one experiment. (c) Live-cell imaging of clonal cells derived from the sgTelo P1 population (see (d)). When inducers are omitted, dSpyCas9-mCherry-APEX2 expression and telomeric accumulation are not observed. Scale bar, 5 µm. Three independent experiments were performed (n ≥ 25 cells examined). (d) FACS sorting of mCherry- and BFP-positive cells. The P1 population corresponds to high BFP (as a surrogate for sgRNA and TetR) and low mCherry expression, providing optimal signal-to-noise ratio to maximize the fraction of telomere-localized dSpyCas9-mCherry-APEX2. Three independent experiments were performed.

Supplementary Figure 2 Specific telomere targeting by dSpyCas9–mCherry–APEX2.

(a) Live-cell imaging of telomere localization by dSpyCas9-mCherry-APEX2 in U2OS cells, using the P1-sorted population defined by the FACS workflow in Supplementary Fig. 1d. dSpyCas9-mCherry-APEX2 exhibited telomeric foci with sgTelo but not with sgNS. Representative images are from three independent experiments (n ≥ 25 cells examined). (b) Immunostaining of telomeric marker protein with primary anti-TERF2IP and secondary antibody conjugated with Alexa 488. Colocalization of dSpyCas9-mCherry-APEX2 foci with TERF2IP is observed (n ≥ 25 cells examined) from one experiment. Scale bar, 5 µm.

Supplementary Figure 3 dCas9–mCherry–APEX2 targets telomeres and enables restricted biotinylation of endogenous proteins.

(a) Fluorescence imaging of dSpyCas9-mCherry-APEX2 labeling in cells. Stable sgTelo and sgNS cells were labeled live as described in (a) or were only supplemented with H2O2 as a no-labeling control. Cells were then fixed and stained with neutravidin conjugated with OG488 to visualize biotinylated proteins. dCas9-mCherry-APEX2 localization are indicated by mCherry fluorescence. Two independent experiments were performed (n ≥ 25 cells examined). Scale bar, 5 µm. (b) anti-mCherry chromatin immunoprecipitation shows genome-wide binding of sgTelo-programmed dSpyCas9-mCherry-APEX2. The reads were trimmed by adaptor removal and filtering. The percentage of total trimmed reads that include at least one (TTAGGG)4 telomeric sequence (the minimum length required for complete sgTelo complementarity) is shown. Values were averaged from two independent experiments, except for the U2OS ChIP-seq, which was only performed onc.e

Supplementary Figure 4 Successful capture of telomere-associated proteins in living human cells by C-BERST using label-free quantification (LFQ).

(a) Top: Western blot analysis of dSpyCas9-mCherry-APEX2 biotinylation, as detected by streptavidin-HRP. sgRNAs, BP treatment, and H2O2 treatment are indicated at the top of each lane. Anti-mCherry was used to detect dSpyCas9-mCherry-APEX2 (middle), and anti-HDAC1 was used as a loading control (bottom). (b) Coomassie-stained SDS-PAGE of total protein from isolated nuclei following biotin labeling. (c) Silver-stained SDS-PAGE of biotin-labeled proteins enriched with streptavidin-coated beads. In a-c, the mobilities of protein markers (in kDa) are indicated on the left of each panel. Representative images of (a)-(c) are from two independent experiments. (d) Volcano plot of C-BERST-labeled, telomere-associated proteins in U2OS cells. Intensity-based absolute quantification (iBAQ) values from the MS analyses were calculated for each identified protein for all three samples (sgTelo + H2O2, sgTelo - H2O2, and sgNS + H2O2). 143 proteins (indicated by blue and red) are statistically enriched [Benjamini-Hochberg (BH)-adjusted p value < 0.05] in the sgTelo + H2O2 sample, relative to both control samples. The 30 proteins indicated by blue dots (with identities provided) are previously defined as either telomere-associated proteins or ALT pathway components. These include all six shelterin components.

Supplementary Figure 5 SILAC workflow.

(a) Schematic diagram of SILAC workflow. Cells were grown in different isotope culture media for at least five passages. dSpyCas9-mCherry-APEX2 proteins were induced by dox and Shield1 21 hours before biotinylation. Following biotinylation and nuclei isolation, cell lysates were sonicated and mixed in a 1:1:1 ratio. (b) Anti-mCherry was used to detect dSpyCas9-mCherry-APEX2 (top), and anti-HDAC1 was used as a loading control (bottom) in the western blot analysis. Representative images are from two independent experiments.

Supplementary Figure 6 C-BERST hits reveal strong functional associations with proteins that are important for ALT pathways.

(a) C-BERST specifically detects components of multiple complexes and factors implicated in ALT pathways. Proteins denoted by double asterisks were significantly enriched (BH-adjusted p value < 0.01) and meet the SILAC cut-off log2 fold change ≥ 2.5 in the sgTelo labeling sample, relative to the sgNS labeling samples (H/M) ratio (see Supplementary Table 3). Proteins denoted by single asterisks were also detected but with lower degrees of significance (BH-adjusted p value < 0.05) in the sgTelo labeling sample (Supplementary Table 3). Proteins denoted by a hashtag were enriched and statistically significant in LFQ. Components of the RAD9/RAD1/HUS1 complex (see Supplementary Table 3) were not detected. (b) Gene Ontology-Biological Process (GO-BP) analysis on the 55 telomeric/ALT proteins identified by C-BERST. The x-axis is the -log10 p value (BH-adjusted) for the C-BERST-detected proteins associated with each GO term given on the left. The 20 most statistically significant GO terms are displayed.

Supplementary Figure 7 Comparison of C-BERST telomeric datasets with data from other proteomic approaches.

(a) Venn diagram of statistically enriched (BH-adjusted p value < 0.01 in Fig. 1b) telomeric proteins from ALT+ human cells, as detected by C-BERST (red), PICh (purple), and TERF1-BirA* BioID (green). 32 proteins from the C-BERST proteome were also detected by PICh, BioID, or both. (b) The 18 proteins found by telomeric C-BERST, BioID, and PICh are highly enriched in the C-BERST telomere proteome. To our knowledge, SLX4IP (denoted in red) has not been validated previously as telomere- or ALT-associated.

Supplementary Figure 8 Validation of novel telomeric factors.

(a) Coimmunostaining of TERF2 (telomeric marker protein) and SLX4IP protein. Primary goat anti-TERF2 and rabbit anti-SLX4IP were used to detect endogenous TERF2 and SLX4IP in the fixed U2OS cells. Secondary donkey anti-goat conjugated with Alexa 647 and mouse anti-rabbit conjugated with CruzFluorTM 488 were then incubated with cells. Data are from one experiment (n ≥ 25 cells examined). Scale bar, 5 µm. (b) Western blot analysis of exogenous, turboGFP-tagged SLX4IP or RPA3 expression, in comparison with the corresponding endogenous protein. ~0.2 x 105 U2OS cells transfected with SLX4IP-turboGFP or RPA3-turboGFP expression plasmid were lysed in 1x RIPA lysis buffer, and proteins were resolved by SDS-PAGE. Western blots were probed by primary SLX4IP or RPA3 antibody and anti-rabbit secondary antibody conjugated with HRP. The gel lanes shown in each panel were cropped from identical exposures of the same western blot membranes from one experiment.

Supplementary Figure 9 Extension of C-BERST proteomic profiling to centromeric α-satellite repeats.

(a) Schematic diagram of alpha satellite repeat position and arrangement at a centromere. (b) Live-cell imaging of centromere localization by dSpyCas9-mCherry-APEX2 in U2OS cells, using the P1-sorted population defined by the FACS workflow in Supplementary Fig. 1d. dSpyCas9-mCherry-APEX2 exhibited centromeric foci with sgAlpha but not with sgNS. Data are from one experiment (n ≥ 25 cells examined). Scale bar, 5 µm. (c) Western blot analysis of dSpyCas9-mCherry-APEX2 expression using anti-mCherry to detect dSpyCas9-mCherry-APEX2 (top). Anti-HDAC1 was used as a loading control (bottom). Two independent experiments were performed. (d) Streptavidin-HRP blotting analysis of biotinylated proteins in sgAlpha- and sgNS-expressing cells. Untransduced U2OS cells were used as a control. Two independent experiments were performed.

Supplementary Figure 10 C-BERST hits reveal strong functional association with centromere function and maintenance.

(a) Venn diagram of statistically enriched (BH-adjusted p value < 0.01) 460 centromeric proteins from U2OS cells, as detected by C-BERST (red), and 90 centromeric proteins from K562 cells, as detected by HyCCAPP (cyan) (see text). 31 proteins from the C-BERST proteome were detected by both. (b) Gene Ontology-Biological Process (GO-BP) analysis on 460 centromeric proteins identified by C-BERST. The x-axis is the -log10 p value (BH-adjusted) for the C-BERST-detected proteins associated with each GO term given on the left. The 15 most statistically significant GO terms are displayed.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–10 and Supplementary Notes 1–6

Reporting Summary

Supplementary Table 1

LFQ-telomere data

Supplementary Table 2

Literature-reported telomeric factors

Supplementary Table 3

SILAC-telomere data

Supplementary Table 4

SILAC-centromere data

Supplementary Table 5

Literature-reported centromeric factors

Supplementary Table 6

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Gao, X.D., Tu, LC., Mir, A. et al. C-BERST: defining subnuclear proteomic landscapes at genomic elements with dCas9–APEX2. Nat Methods 15, 433–436 (2018). https://doi.org/10.1038/s41592-018-0006-2

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