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One library to make them all: streamlining the creation of yeast libraries via a SWAp-Tag strategy


The yeast Saccharomyces cerevisiae is ideal for systematic studies relying on collections of modified strains (libraries). Despite the significance of yeast libraries and the immense variety of available tags and regulatory elements, only a few such libraries exist, as their construction is extremely expensive and laborious. To overcome these limitations, we developed a SWAp-Tag (SWAT) method that enables one parental library to be modified easily and efficiently to give rise to an endless variety of libraries of choice. To showcase the versatility of the SWAT approach, we constructed and investigated a library of 1,800 strains carrying SWAT-GFP modules at the amino termini of endomembrane proteins and then used it to create two new libraries (mCherry and seamless GFP). Our work demonstrates how the SWAT method allows fast and effortless creation of yeast libraries, opening the door to new ways of systematically studying cell biology.

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Figure 1: The SWAT strategy enables fast and easy creation of systematic yeast libraries.
Figure 2: Using the SWAT strategy to rapidly create a seamless N′-tagged GFP library enables comparison of protein abundance under generic or native regulation.
Figure 3: Creation of an N′-SWAT library sheds new light on hundreds of endomembrane proteins.
Figure 4: Correct targeting of peroxisomal proteins is maintained by N′ GFP–tagged strains, enabling characterization of new peroxisomal proteins.
Figure 5: Rapid creation of a new N′ mCherry library exemplifies the SWAT technology and opens up opportunities for systematic colocalization studies.

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  1. Botstein, D. & Fink, G.R. Yeast: an experimental organism for 21st Century biology. Genetics 189, 695–704 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Giaever, G. et al. Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387–391 (2002).

    Article  CAS  PubMed  Google Scholar 

  3. Tarassov, K. et al. An in vivo map of the yeast protein interactome. Science 320, 1465–1470 (2008).

    Article  CAS  PubMed  Google Scholar 

  4. Huh, W.-K. et al. Global analysis of protein localization in budding yeast. Nature 425, 686–691 (2003).

    Article  CAS  PubMed  Google Scholar 

  5. Ben-Aroya, S. et al. Toward a comprehensive temperature-sensitive mutant repository of the essential genes of Saccharomyces cerevisiae. Mol. Cell 30, 248–258 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Li, Z. et al. Systematic exploration of essential yeast gene function with temperature-sensitive mutants. Nat. Biotechnol. 29, 361–367 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Mnaimneh, S. et al. Exploration of essential gene functions via titratable promoter alleles. Cell 118, 31–44 (2004).

    Article  CAS  PubMed  Google Scholar 

  8. Schuldiner, M. et al. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123, 507–519 (2005).

    CAS  PubMed  Google Scholar 

  9. Breslow, D.K. et al. A comprehensive strategy enabling high-resolution functional analysis of the yeast genome. Nat. Methods 5, 711–718 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Kanemaki, M., Sanchez-Diaz, A., Gambus, A. & Labib, K. Functional proteomic identification of DNA replication proteins by induced proteolysis in vivo. Nature 423, 720–724 (2003).

    Article  CAS  PubMed  Google Scholar 

  11. Sopko, R. et al. Mapping pathways and phenotypes by systematic gene overexpression. Mol. Cell 21, 319–330 (2006).

    Article  CAS  PubMed  Google Scholar 

  12. Sung, M.-K. et al. Genome-wide bimolecular fluorescence complementation analysis of SUMO interactome in yeast. Genome Res. 23, 736–746 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Storici, F. & Resnick, M.A. The delitto perfetto approach to in vivo site-directed mutagenesis and chromosome rearrangements with synthetic oligonucleotides in yeast. Methods Enzymol. 409, 329–345 (2006).

    Article  CAS  PubMed  Google Scholar 

  14. Baudin, A., Ozier-Kalogeropoulos, O., Denouel, A., Lacroute, F. & Cullin, C. A simple and efficient method for direct gene deletion in Saccharomyces cerevisiae. Nucleic Acids Res. 21, 3329–3330 (1993).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Wach, A., Brachat, A., Alberti-Segui, C., Rebischung, C. & Philippsen, P. Heterologous HIS3 marker and GFP reporter modules for PCR-targeting in Saccharomyces cerevisiae. Yeast 13, 1065–1075 (1997).

    Article  CAS  PubMed  Google Scholar 

  16. Yofe, I. & Schuldiner, M. Primers-4-Yeast: a comprehensive web tool for planning primers for Saccharomyces cerevisiae. Yeast 31, 77–80 (2014).

    Article  CAS  PubMed  Google Scholar 

  17. Colleaux, L. et al. Universal code equivalent of a yeast mitochondrial intron reading frame is expressed into E. coli as a specific double strand endonuclease. Cell 44, 521–533 (1986).

    Article  CAS  PubMed  Google Scholar 

  18. Tong, A.H.Y. & Boone, C. High-throughput strain construction and systematic synthetic lethal screening in Saccharomyces cerevisiae. In Yeast Gene Analysis 2nd edn. (eds. Stansfield, I. & Stark, M.J.R.) 369–386, 706–707 (Elsevier, 2007).

  19. Khmelinskii, A., Meurer, M., Duishoev, N., Delhomme, N. & Knop, M. Seamless gene tagging by endonuclease-driven homologous recombination. PLoS One 6, e23794 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Fujita, M. & Kinoshita, T. GPI-anchor remodeling: potential functions of GPI-anchors in intracellular trafficking and membrane dynamics. Biochim. Biophys. Acta 1821, 1050–1058 (2012).

    Article  CAS  PubMed  Google Scholar 

  21. Hegde, R.S. & Bernstein, H.D. The surprising complexity of signal sequences. Trends Biochem. Sci. 31, 563–571 (2006).

    Article  CAS  PubMed  Google Scholar 

  22. Petersen, T.N., Brunak, S., von Heijne, G. & Nielsen, H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat. Methods 8, 785–786 (2011).

    Article  CAS  PubMed  Google Scholar 

  23. Käll, L., Krogh, A. & Sonnhammer, E.L.L. A combined transmembrane topology and signal peptide prediction method. J. Mol. Biol. 338, 1027–1036 (2004).

    Article  CAS  PubMed  Google Scholar 

  24. Reynolds, S.M., Käll, L., Riffle, M.E., Bilmes, J.A. & Noble, W.S. Transmembrane topology and signal peptide prediction using dynamic Bayesian networks. PLoS Comput. Biol. 4, e1000213 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Cohen, Y. & Schuldiner, M. Advanced methods for high-throughput microscopy screening of genetically modified yeast libraries. Methods Mol. Biol. 781, 127–159 (2011).

    Article  CAS  PubMed  Google Scholar 

  26. Breker, M., Gymrek, M. & Schuldiner, M. A novel single-cell screening platform reveals proteome plasticity during yeast stress responses. J. Cell Biol. 200, 839–850 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  27. Newman, J.R.S. et al. Single-cell proteomic analysis of S. cerevisiae reveals the architecture of biological noise. Nature 441, 840–846 (2006).

    Article  CAS  PubMed  Google Scholar 

  28. Picotti, P. et al. A complete mass-spectrometric map of the yeast proteome applied to quantitative trait analysis. Nature 494, 266–270 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Belle, A., Tanay, A., Bitincka, L., Shamir, R. & O'Shea, E.K. Quantification of protein half-lives in the budding yeast proteome. Proc. Natl. Acad. Sci. USA 103, 13004–13009 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Ingolia, N.T., Ghaemmaghami, S., Newman, J.R.S. & Weissman, J.S. Genome-wide analysis in vivo of translation with nucleotide resolution using ribosome profiling. Science 324, 218–223 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Barbarić, S., Münsterkötter, M., Svaren, J. & Hörz, W. The homeodomain protein Pho2 and the basic-helix-loop-helix protein Pho4 bind DNA cooperatively at the yeast PHO5 promoter. Nucleic Acids Res. 24, 4479–4486 (1996).

    Article  PubMed  PubMed Central  Google Scholar 

  32. Manney, T.R. Expression of the BAR1 gene in Saccharomyces cerevisiae: induction by the alpha mating pheromone of an activity associated with a secreted protein. J. Bacteriol. 155, 291–301 (1983).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Eden, E., Navon, R., Steinfeld, I., Lipson, D. & Yakhini, Z. GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists. BMC Bioinformatics 10, 48 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  34. Basrai, M.A., Hieter, P. & Boeke, J.D. Small open reading frames: beautiful needles in the haystack. Genome Res. 7, 768–771 (1997).

    Article  CAS  PubMed  Google Scholar 

  35. Kastenmayer, J.P. et al. Functional genomics of genes with small open reading frames (sORFs) in S. cerevisiae. Genome Res. 16, 365–373 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Hasan, S., Platta, H.W. & Erdmann, R. Import of proteins into the peroxisomal matrix. Front. Physiol. 4, 261 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Cohen, Y. et al. Peroxisomes are juxtaposed to strategic sites on mitochondria. Mol. Biosyst. 10, 1742–1748 (2014).

    Article  CAS  PubMed  Google Scholar 

  38. Götte, K. et al. Pex19p, a farnesylated protein essential for peroxisome biogenesis. Mol. Cell. Biol. 18, 616–628 (1998).

    Article  PubMed  PubMed Central  Google Scholar 

  39. Hettema, E.H., Girzalsky, W., van Den Berg, M., Erdmann, R. & Distel, B. Saccharomyces cerevisiae pex3p and pex19p are required for proper localization and stability of peroxisomal membrane proteins. EMBO J. 19, 223–233 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Schuldiner, M. & Zalckvar, E. Peroxisystem: harnessing systems cell biology to study peroxisomes. Biol. Cell 107, 89–97 (2015).

    Article  CAS  PubMed  Google Scholar 

  41. Schlüter, A., Real-Chicharro, A., Gabaldón, T., Sánchez-Jiménez, F. & Pujol, A. PeroxisomeDB 2.0: an integrative view of the global peroxisomal metabolome. Nucleic Acids Res. 38, D800–D805 (2010).

    Article  CAS  PubMed  Google Scholar 

  42. Yi, E.C. et al. Approaching complete peroxisome characterization by gas-phase fractionation. Electrophoresis 23, 3205–3216 (2002).

    Article  CAS  PubMed  Google Scholar 

  43. Jung, S., Marelli, M., Rachubinski, R.A., Goodlett, D.R. & Aitchison, J.D. Dynamic changes in the subcellular distribution of Gpd1p in response to cell stress. J. Biol. Chem. 285, 6739–6749 (2010).

    Article  CAS  PubMed  Google Scholar 

  44. Khmelinskii, A. & Knop, M. Analysis of protein dynamics with tandem fluorescent protein timers. Methods Mol. Biol. 1174, 195–210 (2014).

    Article  CAS  PubMed  Google Scholar 

  45. Unger, T., Jacobovitch, Y., Dantes, A., Bernheim, R. & Peleg, Y. Applications of the Restriction Free (RF) cloning procedure for molecular manipulations and protein expression. J. Struct. Biol. 172, 34–44 (2010).

    Article  CAS  PubMed  Google Scholar 

  46. Janke, C. et al. A versatile toolbox for PCR-based tagging of yeast genes: new fluorescent proteins, more markers and promoter substitution cassettes. Yeast 21, 947–962 (2004).

    Article  CAS  PubMed  Google Scholar 

  47. Brachmann, C.B. et al. Designer deletion strains derived from Saccharomyces cerevisiae S288C: a useful set of strains and plasmids for PCR-mediated gene disruption and other applications. Yeast 14, 115–132 (1998).

    Article  CAS  PubMed  Google Scholar 

  48. Gietz, R.D. & Woods, R.A. Transformation of yeast by lithium acetate/single-stranded carrier DNA/polyethylene glycol method. Methods Enzymol. 350, 87–96 (2002).

    Article  CAS  PubMed  Google Scholar 

  49. Copic, A. et al. Genomewide analysis reveals novel pathways affecting endoplasmic reticulum homeostasis, protein modification and quality control. Genetics 182, 757–769 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Schägger, H. Tricine–SDS-PAGE. Nat. Protoc. 1, 16–22 (2006).

    Article  CAS  PubMed  Google Scholar 

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M.M. and S.C. contributed equally to this work. We thank N. Steinberg for his enormous contribution to the graphical design of this manuscript, and we thank E. Levy for exciting scientific discussions. This work was supported by the European Research Council (ERC) (Consolidator grants Peroxisystem 646604 to M.S. and MITOsmORFs 648235 to N.W.), Deutsche Forschungsgemeinschaft (DFG) Collaborative Research Centres (SFB 1140 to N.W. and SFB 1036, TP10, to M.K.) and the Excellence Initiative of the German Federal & State Governments (EXC 294 BIOSS to N.W.). We also acknowledge the generous support of the Mitzutani Foundation for Glycosciences (to M.S.), the Adelis Foundation (to M.S.) and the Kahn Center for Systems Biology (to M.S.).

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Authors and Affiliations



A.K., M.M. and M.K. conceived the SWAT strategy. M.M., A.K., I.Y. and U.W. developed and implemented the method. S.B.-D. performed computational prediction of signal peptides. U.W., I.Y. and S.C. constructed the SWAT libraries (with help from O.G.) and performed all of the experiments and analysis on the systematic libraries. S.C. performed all automated robotic procedures. E.Z., C.S. and U.W. performed the low-throughput follow-up experiments. A.K., N.W., M.K. and M.S. supervised the work. I.Y., U.W., S.C. and M.S. wrote the manuscript with input from all other authors.

Corresponding authors

Correspondence to Ido Yofe, Silvia Chuartzman, Anton Khmelinskii or Maya Schuldiner.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 The SWAp-Tag (SWAT) strategy is also suitable for C′ protein tagging and swapping.

(a) The C’ Swap-tag (SWAT) acceptor tagging module contains several components: the restriction site for the I-SceI endonuclease (SceI), a URA3 selection marker (URA3), a truncated Hygromycin B selection marker (HYGΔn), and a generic terminator, and are flanked by two generic sequences for homologous recombination that also serve as linkers for protein fusion (L3 and L4). (b) Donor plasmid features (top), which, after swapping, result in several types of tagged-gene libraries (bottom).

Supplementary Figure 2 Several types of tag-swap strategies can be implemented to achieve desired protein-tagging states.

(a) An example for a seamless tag swap. The galactose induced gene GAL2 was tagged with an N’ swat module containing a GFP (SWAT-GFP), and was replaced by a seamless mCherry donor plasmid. GFP-Gal2 that is under control of the constitutive S.p NOP1 promoter in the SWAT-GFP cassette is expressed under both glucose and galactose containing media. Following swapping the native GAL2 promoter is restored leaving a seamless mCherry tag (N’). All four images are overlay images of both GFP and mCherry channels, to portray that only the GFP tag is seen before the swap, and only the mCherry tag in seen post swap. (b) An example for selection reconstitution and tag swap. SSP120 was tagged with an N’ swat module containing a GFP and the Kar2 signal peptide (SWAT-SP-GFP), and was replaced by a HYGΔc::TEF2pr-mCherry donor plasmid. After swapping using Hygromycin the SP-GFP module was replaced by an mCherry tag with no SP, resulting in the loss of the GFP signal (left) and the expression of a mis-localized, cytoplasmic, mCherry-Ssp120 fusion protein. (c) An example for selection and tag swap. The three indicated genes were N’ tagged with the SWAT-GFP module, replaced by NAT::Tef2pr-mCherry donor plasmid. After swapping the GFP tag was replaced with the mCherry, resulting in the loss of the GFP signal (left) and expression of the mCherry fused proteins (right). (d) Comparison of seamless tagging efficiency with N’-SWAT and C’-SWAT acceptor sites. Strains carrying a GAL1pr-I-SceI construct and expressing the indicated proteins of interest (POI) tagged with N’-SWAT (SWAT-POI) or C’-SWAT (POI-SWAT) acceptor modules were transformed with seamless mCherry donor plasmids. Distributions of single cell fluorescence intensities were measured with flow cytometry the indicated step of the swapping procedure (1-3). The percentage of cells with fluorescence above background is indicated under the plots. Fluorescence intensities of strains expressing POI-mCherry fusions are shown for comparison. Scale bars, 5 µm.

Supplementary Figure 3 Computational prediction of Saccharomyces cerevisiae proteins bearing a signal peptide.

In order to perform correct N’ tagging and swapping of proteins containing an N’ signal peptide, prediction of the presence and cleavage site of this motif was performed for all yeast proteins using three prediction algorithms- SignalP, Phobius and Philius. The Venn diagram illustrates that a signal peptide was predicted by all programs for 277 proteins, while some predictions were only predicted by some of the programs. We tagged all proteins predicted to contain a SP by at least two programs with a SWAT module that contained the Kar2 SP.

Supplementary Figure 4 Seamless swapping of SWAT-GFP cassettes is validated by PCR.

Validation (check) PCRs were performed for three picked clones containing a SWAT-GFP tagged HMG2 gene before and after swapping with a seamless GFP donor plasmid. Induction of the I-SceI endonuclease by plating on galactose, results in a mixture of un-swapped and swapped conditions. Further application of two rounds of negative selection by 5FOA, completely abolishes the un-swapped condition, leaving only the swapped one demonstrating that this is a robust process that gives rise to homogenous populations of cells.

Supplementary Figure 5 Seamless swapping of SWAT-GFP cassettes is an efficient and accurate process.

Seamless GFP swap results in a homogenous population. Distribution of single cell protein abundance in strains of the SWAT-GFP library before (generic promoter, purple) and after (native promoter, grey) seamless swapping. Protein abundance was measured by microscopy, and strains were selected randomly, spanning a wide range of protein abundance under native regulation. White circles show the medians; polygons represent density estimates of data and extend to extreme values.

Supplementary Figure 6 Systematic characterization of signal peptide–guided proteins by the SWAp-Tag system uncovers three new condition-specific secreted proteins.

(a) Protein secretion was assayed for all SWAT-SP-GFP strains either under regulation of a generic (top) or native (bottom) promoter and signal peptide. Images are an overlay of the αGFP antibody (green) and auto-fluorescence to verify presence of the colony (red). For the complete secretion measurements see Supplementary Table 5. (b) Some proteins, such as Bgl2, show high levels of expression and secretion under both generic and native regulation, while others, such as Hor7 show higher expression and secretion levels under native regulation. A subset of proteins are only secreted in unique conditions and therefore were only expressed and secreted under regulation of the generic promoter such as BAR1 (mating type specific) and Pho5 (phosphate depletion). Three uncharacterized proteins behaved in the same manner and were therefore classified as condition specific secreted, and were named Css1, Css2, and Css3. Images of the secretion assay (right) are as described for panel a, with four repeats for each gene. Scale bars, 5 µm.

Supplementary Figure 7 Clustering of protein abundance and secretion levels identifies conditionally expressed and secreted proteins.

(a) Clustering was performed for three parameters measured for the SWAT-SP-GFP library: Protein abundance under native regulatory factors (promoter and signal peptide) and protein secretion levels under generic or native regulation (array before or after seamless GFP swap). Protein abundance was measured by microscopy and given as median GFP intensity. Secretion level was measured by western blot and given as ratio of GFP and auto-fluorescence. (b) A cluster of proteins presenting high secretion levels under generic regulation and low secretion and intra-cellular protein abundance under their native regulation. This cluster (“Induced secretion” in panel a) shows a high enrichment of “response to stimulus” GO annotation (purple dots). This enrichment indicates that many proteins may be expressed and secreted under specific conditions. Three unstudied proteins (purple arrows) were found in this cluster and were named as condition specified secretion (Css1-3) proteins.

Supplementary Figure 8 Original images of western blots shown in Figure 4e.

Red boxes indicate approximate image sections used for the figure.

Supplementary Figure 9 The N′ SWAT-GFP library complements the previous C′-tagged GFP library.

(a) Table demonstrating the distribution of localization differences between N′ and C′ tagging reveals that the most prevalent cases are ones where tagging on either side conferred a cytosolic localization, possibly due to interference of the tag with targeting signals, while the other showed targeting to a specific organelle. For all localization assignments please see (Supplementary Table 4). N′ tag – SWAT-GFP library, C′ tag – original GFP collection. (b) Different localizations of proteins when tagged at their N′ or C′ are explained by interference of targeting/processing motifs by the tag. Seven groups of proteins with C′ processing signals indeed tend to have different localization assignments between the N′ and C′ tagged libraries. Images illustrate that for such proteins, while the C′ GFP tag causes an abnormal, cytosolic localization, the N′ GFP tag confers correct targeting of the proteins to organelles. Retrieval motifs include: HDEL, KDEL, KKXX, KXKXX, and XXRR. Scale bars, 5 µm.

Supplementary Figure 10 The N′ and C′ GFP libraries are complementary.

Proteins that were assigned different intracellular localizations when tagged at their N vs. C termini, were compared to GO ontology obtained from previous knowledge. It was found that ~30% comply with the N’ localization, while about another 30% with the C’ localization, and the rest either contain a GO term for both N’ and C’ assignments or for none. This demonstrates the importance of having complementary libraries for studying yeast cell biology. N’ tag – SWAT-GFP library, C’ tag – original GFP collection4.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–10 and Supplementary Tables 1 and 2 (PDF 1196 kb)

Supplementary Table 3

Signal peptide predictions by three softwares. (XLSX 389 kb)

Supplementary Table 4

Strains of the SWAT libraries: subcellular localization and signal intensity according to microscopy image analysis. (XLSX 141 kb)

Supplementary Table 5

Protein-secretion assay results. (XLSX 62 kb)

Supplementary Table 6

List of small open reading frames (smORFs) and their identified localization by N′ and C′ GFP tagging. (XLSX 40 kb)

Supplementary Table 7

Colocalization of SWAT-GFP library proteins with PEX3-RFP. (XLSX 10 kb)

Supplementary Table 8

Colocalization of proteins in the mating progeny of N′ SWAT-GFP and the ‘swapped’ N′-mCherry libraries. (XLSX 13 kb)

Supplementary Table 9

List of primers used for N′ SWAT module amplification and validation of correct insertion. (XLSX 228 kb)

Supplementary Data 1

Sequences of SWAT tagging and donor plasmids. (ZIP 457 kb)

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Yofe, I., Weill, U., Meurer, M. et al. One library to make them all: streamlining the creation of yeast libraries via a SWAp-Tag strategy. Nat Methods 13, 371–378 (2016).

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