∆F508 CFTR interactome remodelling promotes rescue of cystic fibrosis


Deletion of phenylalanine 508 of the cystic fibrosis transmembrane conductance regulator (∆F508 CFTR) is the major cause of cystic fibrosis, one of the most common inherited childhood diseases. The mutated CFTR anion channel is not fully glycosylated and shows minimal activity in bronchial epithelial cells of patients with cystic fibrosis. Low temperature or inhibition of histone deacetylases can partly rescue ∆F508 CFTR cellular processing defects and function. A favourable change of ∆F508 CFTR protein–protein interactions was proposed as a mechanism of rescue; however, CFTR interactome dynamics during temperature shift and inhibition of histone deacetylases are unknown. Here we report the first comprehensive analysis of the CFTR and ∆F508 CFTR interactome and its dynamics during temperature shift and inhibition of histone deacetylases. By using a novel deep proteomic analysis method, we identify 638 individual high-confidence CFTR interactors and discover a ∆F508 deletion-specific interactome, which is extensively remodelled upon rescue. Detailed analysis of the interactome remodelling identifies key novel interactors, whose loss promote ∆F508 CFTR channel function in primary cystic fibrosis epithelia or which are critical for CFTR biogenesis. Our results demonstrate that global remodelling of ∆F508 CFTR interactions is crucial for rescue, and provide comprehensive insight into the molecular disease mechanisms of cystic fibrosis caused by deletion of F508.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: WT and ∆F508 CFTR interactome in bronchial epithelial cells.
Figure 2: Dynamic changes of the ∆F508 CFTR interactome during temperature shift to 30 °C.
Figure 3: HDACi sensitive changes of the ∆F508 CFTR interactome.
Figure 4: RNAi and subnetworks of novel key interactors.
Figure 5: Rescue of ∆F508 CFTR channel function defect by knockdown of ∆F508 CFTR interactors in human primary CF bronchial epithelial cells and CFBE41o− cells.


  1. 1

    Dalemans, W. et al. Altered chloride ion channel kinetics associated with the ΔF508 cystic fibrosis mutation. Nature 354, 526–528 (1991)

    CAS  ADS  Article  Google Scholar 

  2. 2

    Collins, F. S. Cystic fibrosis: molecular biology and therapeutic implications. Science 256, 774–779 (1992)

    CAS  ADS  Article  Google Scholar 

  3. 3

    Watson, M. S. et al. Cystic fibrosis population carrier screening: 2004 revision of American College of Medical Genetics mutation panel. Genet. Med. 6, 387–391 (2004)

    Article  Google Scholar 

  4. 4

    World Health Organization. The Molecular Genetic Epidemiology of Cystic Fibrosis http://www.who.int/genomics/publications/en/HGN_WB_04.02_report.pdf (World Health Organization, 2004)

  5. 5

    Lukacs, G. L. et al. The ΔF508 mutation decreases the stability of cystic fibrosis transmembrane conductance regulator in the plasma membrane. Determination of functional half-lives on transfected cells. J. Biol. Chem. 268, 21592–21598 (1993)

    CAS  Google Scholar 

  6. 6

    Drumm, M. L. et al. Chloride conductance expressed by ΔF508 and other mutant CFTRs in Xenopus oocytes. Science 254, 1797–1799 (1991)

    CAS  ADS  Article  Google Scholar 

  7. 7

    Li, C. et al. The cystic fibrosis mutation (ΔF508) does not influence the chloride channel activity of CFTR. Nature Genet. 3, 311–316 (1993)

    CAS  ADS  Article  Google Scholar 

  8. 8

    Lukacs, G. L. et al. Conformational maturation of CFTR but not its mutant counterpart (ΔF508) occurs in the endoplasmic reticulum and requires ATP. EMBO J. 13, 6076–6086 (1994)

    CAS  Article  Google Scholar 

  9. 9

    Denning, G. M. et al. Processing of mutant cystic fibrosis transmembrane conductance regulator is temperature-sensitive. Nature 358, 761–764 (1992)

    CAS  ADS  Article  Google Scholar 

  10. 10

    Jensen, T. J. et al. Multiple proteolytic systems, including the proteasome, contribute to CFTR processing. Cell 83, 129–135 (1995)

    CAS  Article  Google Scholar 

  11. 11

    Wang, X. et al. Hsp90 cochaperone Aha1 downregulation rescues misfolding of CFTR in cystic fibrosis. Cell 127, 803–815 (2006)

    CAS  Article  Google Scholar 

  12. 12

    Ward, C. L., Omura, S. & Kopito, R. R. Degradation of CFTR by the ubiquitin-proteasome pathway. Cell 83, 121–127 (1995)

    CAS  Article  Google Scholar 

  13. 13

    Hutt, D. M. et al. Reduced histone deacetylase 7 activity restores function to misfolded CFTR in cystic fibrosis. Nature Chem. Biol. 6, 25–33 (2010)

    CAS  Article  Google Scholar 

  14. 14

    Boyault, C. et al. HDAC6-p97/VCP controlled polyubiquitin chain turnover. EMBO J. 25, 3357–3366 (2006)

    CAS  Article  Google Scholar 

  15. 15

    Bruscia, E. et al. Isolation of CF cell lines corrected at ΔF508-CFTR locus by SFHR-mediated targeting. Gene Ther. 9, 683–685 (2002)

    CAS  Article  Google Scholar 

  16. 16

    Mueller, B., Klemm, E. J., Spooner, E., Claessen, J. H. & Ploegh, H. L. SEL1L nucleates a protein complex required for dislocation of misfolded glycoproteins. Proc. Natl Acad. Sci. USA 105, 12325–12330 (2008)

    CAS  ADS  Article  Google Scholar 

  17. 17

    Vij, N., Fang, S. & Zeitlin, P. L. Selective inhibition of endoplasmic reticulum-associated degradation rescues ΔF508-cystic fibrosis transmembrane regulator and suppresses interleukin-8 levels: therapeutic implications. J. Biol. Chem. 281, 17369–17378 (2006)

    CAS  Article  Google Scholar 

  18. 18

    Meacham, G. C., Patterson, C., Zhang, W., Younger, J. M. & Cyr, D. M. The Hsc70 co-chaperone CHIP targets immature CFTR for proteasomal degradation. Nature Cell Biol. 3, 100–105 (2001)

    CAS  Article  Google Scholar 

  19. 19

    Okiyoneda, T. et al. Peripheral protein quality control removes unfolded CFTR from the plasma membrane. Science 329, 805–810 (2010)

    CAS  ADS  Article  Google Scholar 

  20. 20

    Pearce, M. M., Wormer, D. B., Wilkens, S. & Wojcikiewicz, R. J. An endoplasmic reticulum (ER) membrane complex composed of SPFH1 and SPFH2 mediates the ER-associated degradation of inositol 1,4,5-trisphosphate receptors. J. Biol. Chem. 284, 10433–10445 (2009)

    CAS  Article  Google Scholar 

  21. 21

    Chu, B. W. et al. The E3 ubiquitin ligase UBE3C enhances proteasome processivity by ubiquitinating partially proteolyzed substrates. J. Biol. Chem. 288, 34575–34587 (2013)

    CAS  Article  Google Scholar 

  22. 22

    Laroia, G., Cuesta, R., Brewer, G. & Schneider, R. J. Control of mRNA decay by heat shock-ubiquitin-proteasome pathway. Science 284, 499–502 (1999)

    CAS  ADS  Article  Google Scholar 

  23. 23

    Bedford, L. et al. Depletion of 26S proteasomes in mouse brain neurons causes neurodegeneration and Lewy-like inclusions resembling human pale bodies. J. Neurosci. 28, 8189–8198 (2008)

    CAS  Article  Google Scholar 

  24. 24

    Santamaria, P. G., Finley, D., Ballesta, J. P. & Remacha, M. Rpn6p, a proteasome subunit from Saccharomyces cerevisiae, is essential for the assembly and activity of the 26 S proteasome. J. Biol. Chem. 278, 6687–6695 (2003)

    CAS  Article  Google Scholar 

  25. 25

    Callahan, M. K., Wohlfert, E. A., Menoret, A. & Srivastava, P. K. Heat-shock up-regulates lmp2 and lmp7 and enhances presentation of immunoproteasome-dependent epitopes. J. Immunol. 177, 8393–8399 (2006)

    CAS  Article  Google Scholar 

  26. 26

    Gamerdinger, M., Kaya, A. M., Wolfrum, U., Clement, A. M. & Behl, C. BAG3 mediates chaperone-based aggresome-targeting and selective autophagy of misfolded proteins. EMBO Rep. 12, 149–156 (2011)

    CAS  Article  Google Scholar 

  27. 27

    Matsuzaki, F., Shirane, M., Matsumoto, M. & Nakayama, K. I. Protrudin serves as an adaptor molecule that connects KIF5 and its cargoes in vesicular transport during process formation. Mol. Biol. Cell 22, 4602–4620 (2011)

    CAS  Article  Google Scholar 

  28. 28

    Mitrovic, S., Ben-Tekaya, H., Koegler, E., Gruenberg, J. & Hauri, H. P. The cargo receptors Surf4, endoplasmic reticulum-Golgi intermediate compartment (ERGIC)-53, and p25 are required to maintain the architecture of ERGIC and Golgi. Mol. Biol. Cell 19, 1976–1990 (2008)

    CAS  Article  Google Scholar 

  29. 29

    Fujii, Y. et al. Surf4 modulates STIM1-dependent calcium entry. Biochem. Biophys. Res. Commun. 422, 615–620 (2012)

    CAS  Article  Google Scholar 

  30. 30

    Weng, M. T. & Luo, J. The enigmatic ERH protein: its role in cell cycle, RNA splicing and cancer. Protein Cell 4, 807–812 (2013)

    CAS  Article  Google Scholar 

  31. 31

    Forster, M. L. et al. Protein disulfide isomerase-like proteins play opposing roles during retrotranslocation. J. Cell Biol. 173, 853–859 (2006)

    CAS  Article  Google Scholar 

  32. 32

    Taguwa, S. et al. Cochaperone activity of human butyrate-induced transcript 1 facilitates hepatitis C virus replication through an Hsp90-dependent pathway. J. Virol. 83, 10427–10436 (2009)

    CAS  Article  Google Scholar 

  33. 33

    Mallery, D. L. et al. Antibodies mediate intracellular immunity through tripartite motif-containing 21 (TRIM21). Proc. Natl Acad. Sci. USA 107, 19985–19990 (2010)

    CAS  ADS  Article  Google Scholar 

  34. 34

    Behrends, C., Sowa, M. E., Gygi, S. P. & Harper, J. W. Network organization of the human autophagy system. Nature 466, 68–76 (2010)

    CAS  ADS  Article  Google Scholar 

  35. 35

    Uchida, N., Hoshino, S. & Katada, T. Identification of a human cytoplasmic poly(A) nuclease complex stimulated by poly(A)-binding protein. J. Biol. Chem. 279, 1383–1391 (2004)

    CAS  Article  Google Scholar 

  36. 36

    Fabian, M. R. et al. Mammalian miRNA RISC recruits CAF1 and PABP to affect PABP-dependent deadenylation. Mol. Cell 35, 868–880 (2009)

    CAS  Article  Google Scholar 

  37. 37

    LaCava, J. et al. RNA degradation by the exosome is promoted by a nuclear polyadenylation complex. Cell 121, 713–724 (2005)

    CAS  Article  Google Scholar 

  38. 38

    Alexandru, G. et al. UBXD7 binds multiple ubiquitin ligases and implicates p97 in HIF1α turnover. Cell 134, 804–816 (2008)

    CAS  Article  Google Scholar 

  39. 39

    McKusick, V. A. Mendelian Inheritance in Man and its online version, OMIM. Am. J. Hum. Genet. 80, 588–604 (2007)

    CAS  Article  Google Scholar 

  40. 40

    Magrane, M. & UniProt Consortium. UniProt Knowledgebase: a hub of integrated protein data. Database 2011, bar009 (2011)

  41. 41

    Tiscornia, G., Singer, O. & Verma, I. M. Production and purification of lentiviral vectors. Nature Protocols 1, 241–245 (2006)

    CAS  Article  Google Scholar 

  42. 42

    Laemmli, U. K. Cleavage of structural proteins during the assembly of the head of bacteriophage T4. Nature 227, 680–685 (1970)

    CAS  ADS  Article  Google Scholar 

  43. 43

    Galietta, L. V., Jayaraman, S. & Verkman, A. S. Cell-based assay for high-throughput quantitative screening of CFTR chloride transport agonists. Am. J. Physiol. Cell Physiol. 281, C1734–C1742 (2001)

    CAS  Article  Google Scholar 

  44. 44

    Pankow, S., Bamberger, C., Calzolari, D., Bamberger, A. & Yates, J. R. Characterization of membrane protein interactomes by Co-interacting Protein Identification Technology (CoPIT). Protocol Exchange (submitted)

  45. 45

    Washburn, M. P., Wolters, D. & Yates, J. R. III. Large-scale analysis of the yeast proteome by multidimensional protein identification technology. Nature Biotechnol. 19, 242–247 (2001)

    CAS  Article  Google Scholar 

  46. 46

    Xu, T. et al. ProLuCID, a fast and sensitive tandem mass spectra-based protein identification program. Mol. Cell Proteom. 5, S174 (2006)

    Google Scholar 

  47. 47

    Elias, J. E., Haas, W., Faherty, B. K. & Gygi, S. P. Comparative evaluation of mass spectrometry platforms used in large-scale proteomics investigations. Nature Methods 2, 667–675 (2005)

    CAS  Article  Google Scholar 

  48. 48

    Cociorva, D., Tabb, D. L. & Yates, J. R. in Current Protocols in Bioinformatics (ed. Bateman, A. et al.) Ch. 13, Unit 13.4 (Wiley, 2007)

  49. 49

    Li, X. J., Zhang, H., Ranish, J. A. & Aebersold, R. Automated statistical analysis of protein abundance ratios from data generated by stable-isotope dilution and tandem mass spectrometry. Analyt. Chem. 75, 6648–6657 (2003)

    CAS  Article  Google Scholar 

  50. 50

    Ranish, J. A. et al. Identification of TFB5, a new component of general transcription and DNA repair factor IIH. Nature Genet. 36, 707–713 (2004)

    CAS  Article  Google Scholar 

  51. 51

    Montojo, J. et al. GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop. Bioinformatics 26, 2927–2928 (2010)

    CAS  Article  Google Scholar 

  52. 52

    Pavlopoulos, G. A., Hooper, S. D., Sifrim, A., Schneider, R. & Aerts, J. Medusa: a tool for exploring and clustering biological networks. BMC Res. Notes 4, 384 (2011)

    Article  Google Scholar 

  53. 53

    Breitkreutz, B. J., Stark, C. & Tyers, M. Osprey: a network visualization system. Genome Biol 4, R22 (2003)

    Article  Google Scholar 

  54. 54

    Park, S. K., Venable, J. D., Xu, T. & Yates, J. R., 3rd . A quantitative analysis software tool for mass spectrometry-based proteomics. Nature Methods 5, 319–322 (2008)

    CAS  Article  Google Scholar 

  55. 55

    Suzuki, R. & Shimodaira, H. Pvclust: an R package for assessing the uncertainty in hierarchical clustering. Bioinformatics 22, 1540–1542 (2006)

    CAS  Article  Google Scholar 

Download references


We thank A. Bamberger for many discussions on statistical analysis, and D. Cociorva and T. Xu for making DTASelect 2.1 available and for suggestions and comments on data analysis strategies. We further thank D. Hutt and D. Roth for discussion. This work was supported by National Institutes of Health grants 5R01HL079442-08 (to J.R.Y. and W.E.B.), P01AG031097 (to J.R.Y.), P41 GM103533 (to J.R.Y.), HHSN268201000035C (to J.R.Y.), and a Cystic Fibrosis Foundation mass spectrometry fellowship BALCH050X6 (to S.P. and J.R.Y.). M.L.-A. holds a postdoctoral fellowship from Fonds de recherche du Québec - Nature et technologies. W.E.B. is supported by National Institutes of Health grants R01HL095524 and R01DK051870 and Tobacco-Related Disease Research Program grant 23TRU0012.

Author information




Analysed data are available at http://sealion.scripps.edu/pint?project=CFTR (‘CFTR’ dataset). Raw files have been deposited in ProteomeXchange under accession number PXD002722. S.P. and C.B. developed experimental methods and performed all experiments, data analysis and mass spectrometric (MS) measurements. C.B. and S.P. developed and performed statistical analysis. D.C. and C.B. developed Radial Topology Viewer. M.L.-A. performed and wrote the methods detailing the hierarchical clustering. S.M.B. developed and maintains Proteomics INTegrator (PINT). J.R.Y., W.E.B., S.P. and C.B. designed the study. S.P., C.B. and J.R.Y. wrote the paper.

Corresponding authors

Correspondence to Sandra Pankow or John R. Yates III.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 CoPIT workflow and results.

a, Schematic overview of the Co-PIT workflow. Top: cell lysates for IP were prepared from ≥4 × 107 lung epithelial cells (CFBE41o− or HBE41o−) with emphasis on extracting both cytoplasmic and membrane protein interactors of CFTR, pre-cleared before co-IP with anti-CFTR antibody 3G11. Proteins eluted from the beads were purified by methanol/chloroform precipitation and digested with trypsin, before loading onto a MudPIT column and online MudPIT data acquisition. Bottom: resulting spectra were searched with ProLuCID and search results filtered with DTASelect 2.1 to a protein false positive rate of <1% before normalization and further statistical analysis of the data set. Core CFTR interactomes were determined by modelling the distribution functions of control and sample IPs, and applying corresponding confidence scores and abundance filters. Corresponding networks were graphed using Radial Topology Viewer and differential comparison performed. Data are stored in the PINT tool. b, Improved recovery of CFTR and interactors. Western blot depicting improved recovery of ∆F508 CFTR from CFBE41o− cells with TNI buffer compared with different lysis buffers. A, B and C indicate the different CFTR glycoforms. c, Western blot showing enhanced recovery of ∆F508 CFTR from beads after co-IP with detergent and heat aided low pH elution compared with other directly MS-compatible elution methods. Lane entitled ‘Wang et al. 2006’: elution conditions as described in ref. 11. Gly, glycine. d, Enhanced sensitivity of the CFTR co-IP and chromatography is reflected by enhanced spectral counts for CFTR itself and well-established interactors such as HSP70 and HSP90. e, Comparison between the CFTR interactome reported in ref. 11 and this study (Supplementary Table 4). Thirty-three of the reported 38 interactions in Calu-3 cells were recovered; 20 were confirmed as highly confident interactions (innermost circle) and 13 as medium confident interactions in this study, achieving an almost complete overlap of the two data sets. f, Table showing the recovery of CFTR and exemplary, well-characterized interactors in co-IPs of WT CFTR (BHK cells (from ref. 11) or HBE41o− cells (this study)). g, Sequence coverage of the CFTR protein with MS. Green background indicates identified amino acids whereas orange highlights putative transmembrane (TM) domains of CFTR numbered from 1 to 12. h, Frequency distribution of all rpec determined for the experimental condition WT CFTR to control condition. Individual points (black dots) indicate the individual values. The two-term Gaussian fit is shown in grey. The individual Gaussian describing the distribution of non-specific binding is coloured in brown, whereas the Gaussian describing the enrichment for weak specific interactors is indicated in light green. The black arrow marks the rpec determined for CFTR, the bait protein. Right: example P values for well-known CFTR interactors (light green) and proteins commonly identified as background in co-IP experiments (light brown). Threshold for a high-confidence ∆F508-CFTR interactor was calculated at ≥0.92.

Extended Data Figure 2 CFTR interactome and validation of novel interactors.

a, Network representation of the ∆F508 CFTR interactome in a radial topography map. The colour and relative distance to CFTR in the centre reflect the confidence P of an identified protein to be a specific CFTR interactor. Left: no filters were applied and all recovered proteins from the IPs are depicted. Right: core interactome of ∆F508 CFTR (P > 0.92). Distance and colour indicate the confidence of an identified protein to be a specific CFTR interactor. b, Overlay of the interactome data with protein expression profiling data shows that observed interactome differences between WT and ∆F508 CFTR are unrelated to expression changes between HBE41o− and CFBE41o− cells. The volcano plot displays the fold change and log10(P) for 4,563 proteins quantified with tandem mass tag (TMT) in the expression profiling experiment. Core interactors of CFTR (529 proteins) that were not differentially regulated between the two cell lines are displayed in blue whereas significantly altered core interactors (r ≥ two-fold, P < 0.01) are displayed in red. c, Western blotting of CFTR IPs confirms specific interaction of CFTR with the novel interaction partners TRIM21, LGALS3BP and PTPLAD1 in CFBE41o- or HBE41o− cells. Results indicate similar binding of WT and ∆F508 CFTR with TRIM21 and LGALS3BP, and confirm enhanced binding of PTPLAD1 with ∆F508 CFTR. d, CFTR co-IPs confirm CFTR interaction with TRIM21, PTPLAD1 and LGALS3BP in primary lung epithelial cells carrying either the ∆F508 or the F508S mutation from a patient with CF. Control: CFTR null CFBE41o− cell line. e, Ubiquitin (UBB/UBC) recovery is increased in ∆F508 CFTR co-IPs. Error bars indicate mean ± s.d. f, CoPIT confidence scores and observed fold changes for TRIM21, LGALS3BP and PTPLAD1 match recovery in the IP western blot. g, Reciprocal co-IP using newly identified, endogenous interactors as bait confirms interaction of TRIM21, LGALS3BP and PTPLAD1 with ∆F508 CFTR and confirms differential binding of PTPLAD1 to WT and ∆F508 CFTR. Control, null: CFTR null CFBE41o− cell line; mock: beads only—IP with no antibody added.

Extended Data Figure 3 Overview of drug treatment, siRNA-mediated knockdown and temperature shift experiments.

a, Schematic showing the experimental outline. b, Hierarchical clustering analysis of the CFTR core interactomes shows that the ΔF508 CFTR interaction profile clusters with high significance with those of ∆F508 CFTR at 1 h and 6 h temperature shifts to 30 °C (mutant cluster), whereas temperature shift to 30 °C for 24 h and temperature shift to 30 °C for 24 h with reversal cause the respective ∆F508 CFTR interaction profiles to significantly cluster with that of WT CFTR. Bootstrap values (10,000 samplings) are given for each tree node. Significant (bootstrap value > 90, yellow) and highly significant clusters (bootstrap value > 95, red) are coloured on the dendrogram. The heat map indicates the relative protein abundance values measured by MS as negative log10 ratios of interactors relative to CFTR. White in the heat map indicates that no interaction was observed. c, Expression of different heat-shock proteins. The western blot shows expression of HSP90 (encoded by HSP90AA1 and HSP90AB1), GRP78 (HSPA5), GRP94 (HSP90B1) and HSP70 (HSPA1) during temperature shift to 30 °C. All data are from independent biological replicates, WT (n = 7), ∆F508 (n = 8), SAHA (n = 4), TSA (n = 4), HDAC7 (n = 3), Cmpd 4a (n = 3).

Extended Data Figure 4 Interaction profiles of proteins selected for the RNAi screen.

a, Observed interaction profiles of selected candidates and CFTR (bottom) and expected candidate profiles (top). b, Lentiviral infection rates were greater than 97% after 48 h in CFBE41o− cells as indicated by control green fluorescent protein (GFP) infection.

Extended Data Figure 5 Western blot detection of ∆F508 CFTR upon RNAi of interactors.

∆F508 CFTR was detected 48–72 h after lentiviral shRNA infection using the 3G11 antibody or 24.1 antibody (lowest left panel). Rescue is indicated by appearance of band C. Detection of β-actin served as loading control. Samples on the same blot represent parallel infections. Samples in the lower three left panels were lysed initially in TNI buffer, whereas samples in the other panels were lysed directly in 2× Laemmli sample buffer as described in Methods. Scr, scrambled non-target shRNA.

Extended Data Figure 6 Co-localization of novel interactors with ∆F508 CFTR.

a, Each panel contains immunofluorescence staining of CFTR (red), interactor as indicated (green), nuclei (DAPI) and the merged picture. Scale bars, 10 μm. b, WT and ∆F508 CFTR were detected by immunofluorescence staining (green) in HBE41o− and CFBE41o− cells, respectively. Arrows points to WT CFTR at the plasma membrane of control cells. c, Schematic of a cell depicting sequential (spatio-temporal) regulation of ∆F508 CFTR protein biogenesis by the interactors targeted in the shRNA screen. Functional classification of interactors is indicated by shape and colour. Proteins detected in co-localization studies are marked in bold.

Extended Data Figure 7 ∆F508 CFTR detection in primary bronchial epithelial cells upon RNAi of key interactors.

a, Quantification of the ∆F508 CFTR ion channel activity (as fold change of the ∆Isc relative to non-target shRNA) compared with the ratio of band C to band A/B in primary cells from a patient with CF or from a healthy donor (WT). Error bars indicate mean ± s.e.m. b, Representative trace of forskolin (10 μM, F) and genistein (50 μM, G) activated, WT CFTR short-circuit current (Isc) in a 30 d ALI culture from a healthy donor. CFTR inhibitor 172 (I) indicates specificity of the measured Isc for CFTR. c, Western blot of 28- to 30-day-old primary human bronchial epithelial Snapwell cultures from patients with CF (DHBE) indicates formation of band C after specific knockdown of PABPC1, YBX1, PTBP1, TRIM21, PTPLAD1 and SURF4 with different shRNAs. Tubulin, β-actin or Na+/K+-ATPase was used as a loading control. Knockdown of PABPC1 and PTPLAD1 was verified by western blotting with the respective antibodies. NT sh, non-target shRNA.

Extended Data Figure 8 Halide assay results for CFTR chloride channel activity in stable cell clones.

a, CFTR chloride channel activity was measured in HBE41o−, CFBE41o− and CFBE41o− cells with stable knockdown of LGALS3BP (clone 13) or PTPLAD1 (clone 24). Activity was measured by sodium-iodide-mediated quenching of a halide-sensitive Venus YFP. Time-lapse experiments show the iodide influx after pre-incubation of cells with 50 μM genistein. Additional stimulation with forskolin was performed 15 s after addition of sodium iodide. Representative single cell traces are shown. Inset shows the fitted constant for fluorescence decay time for each trace. b, Western blot showing the negative influence of LGALS3BP knockdown on ∆F508 CFTR protein stability. Clones 13.1 and 13.2 are two independent CFBE41o− clones that stably express an shRNA against LGALS3BP. The knockdown was validated by detection of LGALS3BP. c, Western blot showing increased production of ∆F508 CFTR band C in CFBE41o− cell clone 24 stably expressing an shRNA against PTPLAD1. The knockdown was validated by detection of PTPLAD1. Detection of β-actin served as loading control. Scr, scrambled non-target shRNA.

Extended Data Figure 9 Percentage of CFTR interactors associated with known protein misfolding and other prevalent diseases.

Bar graph showing the fraction of the interactome associated with genetic diseases listed in OMIM. Percentages next to the disease name indicate the percentage of ∆F508 CFTR-specific interactors involved in these diseases. Interactors causative of Alzheimer disease and other neurodegenerative diseases such as Leigh syndrome are enriched in the ∆F508 CFTR interactome. ‘Other’ indicates diseases not fitting into one of the other categories listed.

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-7, Supplementary Results and Discussion, Supplementary References, details for Supplementary Tables 1-15 (see separate excel files) and full size gel images for Figure 2b and Extended Data Figures 1, 2c, 2d, 2g, 3, 5, 7c, 8b. (PDF 3206 kb)

Supplementary Tables 1-3

CFTR core interactome (see Supplementary Information file for more details). (XLSX 574 kb)

Supplementary Table 4

Comparison of the interactome from Wang et al, 2006 84 with this study (see Supplementary Information file for more details). (XLSX 68 kb)

Supplementary Tables 5, 6

Table 5: ΔF508 CFTR-mutation specific interactome; Table S6: ΔF508 CFTR-mutation specific degradation network (see Supplementary Information file for more details). (XLSX 21 kb)

Supplementary Tables 7-13

Tables 7-10: Temporal remodeling of the ΔF508 CFTR interactome during temperature shift to 30°C; Tables 11-13: Alterations of the ΔF508 CFTR interactome upon treatment with SAHA for 24 h (Table 11), upon treatment with TSA for 24 h (Table 12) and upon siRNA-mediated knockdown of HDAC7 in CFBE41ocells (Table 13) (see Supplementary Information file for more details). (XLSX 315 kb)

Supplementary Table 14

Table S14. Enrichment of different cellular components in either the wt or the ΔF508 CFTR interactome using GO-analysis (GoMiner) (see Supplementary Information file for more details). (XLSX 10 kb)

Supplementary Table 15

shRNA sequences used for knockdown of identified interactors are identified by their TRC ID number. (XLSX 44 kb)

Supplementary Data

This zipped file contains supplementary Data files 1-8. (ZIP 19626 kb)

PowerPoint slides

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Pankow, S., Bamberger, C., Calzolari, D. et al. ∆F508 CFTR interactome remodelling promotes rescue of cystic fibrosis. Nature 528, 510–516 (2015). https://doi.org/10.1038/nature15729

Download citation

Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Sign up for the Nature Briefing newsletter for a daily update on COVID-19 science.
Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing