Protein interaction perturbation profiling at amino-acid resolution

Abstract

The identification of genomic variants in healthy and diseased individuals continues to rapidly outpace our ability to functionally annotate these variants. Techniques that both systematically assay the functional consequences of nucleotide-resolution variation and can scale to hundreds of genes are urgently required. We designed a sensitive yeast two-hybrid-based 'off switch' for positive selection of interaction-disruptive variants from complex genetic libraries. Combined with massively parallel programmed mutagenesis and a sequencing readout, this method enables systematic profiling of protein-interaction determinants at amino-acid resolution. We defined >1,000 interaction-disrupting amino acid mutations across eight subunits of the BBSome, the major human cilia protein complex associated with the pleiotropic genetic disorder Bardet–Biedl syndrome. These high-resolution interaction-perturbation profiles provide a framework for interpreting patient-derived mutations across the entire protein complex and thus highlight how the impact of disease variation on interactome networks can be systematically assessed.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: Int-Seq pipeline to identify regions mediating protein interactions at amino-acid resolution.
Figure 2: Domain-based binary interaction network of the BBSome.
Figure 3: The Int-Seq pipeline is scalable across many interactions and can identify disruptive single amino-acid mutations.
Figure 4: Int-Seq identifies the N-terminal alpha helical region of BBS8 as required for BBS9 interaction.
Figure 5: Int-Seq functionally characterizes patient-derived BBS1 mutations.
Figure 6: The amino-acid-resolution interaction landscape of the BBSome.

Accession codes

Primary accessions

BioProject

References

  1. 1

    Kircher, M. et al. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 46, 310–315 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  2. 2

    Creixell, P. et al. Pathway and network analysis of cancer genomes. Nat. Methods 12, 615–621 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  3. 3

    Woodsmith, J. & Stelzl, U. Studying post-translational modifications with protein interaction networks. Curr. Opin. Struct. Biol. 24, 34–44 (2014).

    CAS  PubMed  Article  Google Scholar 

  4. 4

    Sahni, N. et al. Widespread macromolecular interaction perturbations in human genetic disorders. Cell 161, 647–660 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. 5

    Wei, X. et al. A massively parallel pipeline to clone DNA variants and examine molecular phenotypes of human disease mutations. PLoS Genet. 10, e1004819 (2014).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  6. 6

    Kitzman, J.O., Starita, L.M., Lo, R.S., Fields, S. & Shendure, J. Massively parallel single-amino-acid mutagenesis. Nat. Methods 12, 203–206 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  7. 7

    Wrenbeck, E.E. et al. Plasmid-based one-pot saturation mutagenesis. Nat. Methods 13, 928–930 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  8. 8

    Nachury, M.V. et al. A core complex of BBS proteins cooperates with the GTPase Rab8 to promote ciliary membrane biogenesis. Cell 129, 1201–1213 (2007).

    CAS  PubMed  Article  Google Scholar 

  9. 9

    Malicki, J.J. & Johnson, C.A. The cilium: cellular antenna and central processing unit. Trends Cell Biol. 27, 126–140 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  10. 10

    Nachury, M.V., Seeley, E.S. & Jin, H. Trafficking to the ciliary membrane: how to get across the periciliary diffusion barrier? Annu. Rev. Cell Dev. Biol. 26, 59–87 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  11. 11

    Shih, H.M. et al. A positive genetic selection for disrupting protein–protein interactions: identification of CREB mutations that prevent association with the coactivator CBP. Proc. Natl. Acad. Sci. USA 93, 13896–13901 (1996).

    CAS  PubMed  Article  Google Scholar 

  12. 12

    Ear, P.H. & Michnick, S.W. A general life-death selection strategy for dissecting protein functions. Nat. Methods 6, 813–816 (2009).

    CAS  PubMed  Article  Google Scholar 

  13. 13

    Vidal, M., Braun, P., Chen, E., Boeke, J.D. & Harlow, E. Genetic characterization of a mammalian protein–protein interaction domain by using a yeast reverse two-hybrid system. Proc. Natl. Acad. Sci. USA 93, 10321–10326 (1996).

    CAS  PubMed  Article  Google Scholar 

  14. 14

    Gronemeyer, T. et al. A split-ubiquitin based strategy selecting for protein complex-interfering mutations. G3 (Bethesda) 6, 2809–2815 (2016).

    CAS  Article  Google Scholar 

  15. 15

    Gedvilaite, A. & Sasnauskas, K. Control of the expression of the ADE2 gene of the yeast Saccharomyces cerevisiae. Curr. Genet. 25, 475–479 (1994).

    CAS  PubMed  Article  Google Scholar 

  16. 16

    Worseck, J.M., Grossmann, A., Weimann, M., Hegele, A. & Stelzl, U. A stringent yeast two-hybrid matrix screening approach for protein-protein interaction discovery. Methods Mol. Biol. 812, 63–87 (2012).

    CAS  PubMed  Article  Google Scholar 

  17. 17

    Weimann, M. et al. A Y2H-seq approach defines the human protein methyltransferase interactome. Nat. Methods 10, 339–342 (2013).

    CAS  PubMed  Article  Google Scholar 

  18. 18

    Zhang, Q., Yu, D., Seo, S., Stone, E.M. & Sheffield, V.C. Intrinsic protein-protein interaction-mediated and chaperonin-assisted sequential assembly of stable bardet-biedl syndrome protein complex, the BBSome. J. Biol. Chem. 287, 20625–20635 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  19. 19

    Mourão, A., Nager, A.R., Nachury, M.V. & Lorentzen, E. Structural basis for membrane targeting of the BBSome by ARL6. Nat. Struct. Mol. Biol. 21, 1035–1041 (2014).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  20. 20

    Katoh, Y., Nozaki, S., Hartanto, D., Miyano, R. & Nakayama, K. Architectures of multisubunit complexes revealed by a visible immunoprecipitation assay using fluorescent fusion proteins. J. Cell Sci. 128, 2351–2362 (2015).

    CAS  PubMed  Article  Google Scholar 

  21. 21

    Boersma, M.D., Sadowsky, J.D., Tomita, Y.A. & Gellman, S.H. Hydrophile scanning as a complement to alanine scanning for exploring and manipulating protein-protein recognition. Application to the Bim BH3 domain. Protein Sci. 17, 1232–1240 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  22. 22

    Chen, J. et al. Molecular analysis of Bardet–Biedl syndrome families: report of 21 novel mutations in 10 genes. Invest. Ophthalmol. Vis. Sci. 52, 5317–5324 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  23. 23

    Beales, P.L. et al. Genetic interaction of BBS1 mutations with alleles at other BBS loci can result in non-Mendelian Bardet-Biedl syndrome. Am. J. Hum. Genet. 72, 1187–1199 (2003).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  24. 24

    Hegele, A. et al. Dynamic protein-protein interaction wiring of the human spliceosome. Mol. Cell 45, 567–580 (2012).

    CAS  PubMed  Article  Google Scholar 

  25. 25

    Liew, G.M. et al. The intraflagellar transport protein IFT27 promotes BBSome exit from cilia through the GTPase ARL6/BBS3. Dev. Cell 31, 265–278 (2014).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  26. 26

    Starita, L.M. et al. Massively parallel functional analysis of BRCA1 RING domain variants. Genetics 200, 413–422 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  27. 27

    Melamed, D., Young, D.L., Miller, C.R. & Fields, S. Combining natural sequence variation with high throughput mutational data to reveal protein interaction sites. PLoS Genet. 11, e1004918 (2015).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  28. 28

    Araya, C.L. et al. A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function. Proc. Natl. Acad. Sci. USA 109, 16858–16863 (2012).

    CAS  PubMed  Article  Google Scholar 

  29. 29

    Aakre, C.D. et al. Evolving new protein-protein interaction specificity through promiscuous intermediates. Cell 163, 594–606 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  30. 30

    Raman, A.S., White, K.I. & Ranganathan, R. Origins of allostery and evolvability in proteins: a case study. Cell 166, 468–480 (2016).

    CAS  PubMed  Article  Google Scholar 

  31. 31

    Melamed, D., Young, D.L., Gamble, C.E., Miller, C.R. & Fields, S. Deep mutational scanning of an RRM domain of the Saccharomyces cerevisiae poly(A)-binding protein. RNA 19, 1537–1551 (2013).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  32. 32

    Majithia, A.R. et al. Prospective functional classification of all possible missense variants in PPARG. Nat. Genet. 48, 1570–1575 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  33. 33

    Trigg, S.A. et al. CrY2H-seq: a massively multiplexed assay for deep-coverage interactome mapping. Nat. Methods 14, 819–825 (2017).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34

    Wang, X. et al. Three-dimensional reconstruction of protein networks provides insight into human genetic disease. Nat. Biotechnol. 30, 159–164 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  35. 35

    Mosca, R. et al. dSysMap: exploring the edgetic role of disease mutations. Nat. Methods 12, 167–168 (2015).

    CAS  PubMed  Article  Google Scholar 

  36. 36

    Creixell, P. et al. Unmasking determinants of specificity in the human kinome. Cell 163, 187–201 (2015).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  37. 37

    Perica, T. et al. Evolution of oligomeric state through allosteric pathways that mimic ligand binding. Science 346, 1254346 (2014).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  38. 38

    Babu, M.M. The contribution of intrinsically disordered regions to protein function, cellular complexity, and human disease. Biochem. Soc. Trans. 44, 1185–1200 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  39. 39

    Boycott, K.M., Vanstone, M.R., Bulman, D.E. & MacKenzie, A.E. Rare-disease genetics in the era of next-generation sequencing: discovery to translation. Nat. Rev. Genet. 14, 681–691 (2013).

    CAS  PubMed  Article  Google Scholar 

  40. 40

    Abu-Safieh, L. et al. In search of triallelism in Bardet––Biedl syndrome. Eur. J. Hum. Genet. 20, 420–427 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. 41

    Davis, E.E. et al. TTC21B contributes both causal and modifying alleles across the ciliopathy spectrum. Nat. Genet. 43, 189–196 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. 42

    Zhang, Y. et al. BBS mutations modify phenotypic expression of CEP290-related ciliopathies. Hum. Mol. Genet. 23, 40–51 (2014).

    PubMed  Article  CAS  Google Scholar 

  43. 43

    Lehner, B. Genotype to phenotype: lessons from model organisms for human genetics. Nat. Rev. Genet. 14, 168–178 (2013).

    CAS  PubMed  Article  Google Scholar 

  44. 44

    Apelt, L. et al. Systematic protein-protein interaction analysis reveals intersubcomplex contacts in the nuclear pore complex. Mol. Cell Proteomics 15, 2594–2606 (2016).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  45. 45

    Murphy, K.F., Balázsi, G. & Collins, J.J. Combinatorial promoter design for engineering noisy gene expression. Proc. Natl. Acad. Sci. USA 104, 12726–12731 (2007).

    CAS  PubMed  Article  Google Scholar 

  46. 46

    Voth, W.P., Richards, J.D., Shaw, J.M. & Stillman, D.J. Yeast vectors for integration at the HO locus. Nucleic Acids Res. 29, E59 (2001).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  47. 47

    Zhong, Q. et al. Edgetic perturbation models of human inherited disorders. Mol. Syst. Biol. 5, 321 (2009).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  48. 48

    Woodsmith, J., Apelt, L., Casado-Medrano, V., Özkan, Z., Timmermann, B. & Stelzl, U. Protocol Exchange https://doi.org/10.1038/protex.2017.110.

  49. 49

    Rumble, S.M. et al. SHRiMP: accurate mapping of short color-space reads. PLoS Comput. Biol. 5, e1000386 (2009).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank T. Schwartz and K. Knockenhauer (MIT, Boston) for providing cDNA fragments of BBsome subunits. We also thank members of the Sequencing Core Facility at the Max-Planck Institute for Molecular Genetics for technical assistance. The work was supported by the Max-Planck Society and the University of Graz.

Author information

Affiliations

Authors

Contributions

U.S. supervised the project. J.W., L.A., V.C.-M. and Z.Ö. created the yeast strains. J.W. and L.A. performed the Y2H BBSome network construction. J.W. and U.S. developed the Int-Seq experimental protocol. J.W. performed the Int-Seq experimental protocol, Y2H mutant validation, LUMIER experiments and fluorescence microscopy. B.T. contributed tools and reagents. J.W. designed and undertook all bioinformatics analysis and figure generation. J.W. and U.S. wrote the paper. All authors contributed to paper feedback.

Corresponding authors

Correspondence to Jonathan Woodsmith or Ulrich Stelzl.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Construction of a sensitive TetR mediated auxotrophic “off-switch”.

A Production of the Tet repressor in yeast when conjugated to either the LexA4 or LexA8 promoter DNA binding sequences. B Increasing the number of LexA8::TetR copies in the yeast correlates with an increased repression of yeast growth in response to two protein pairs that do interact (+) or two protein pairs that do not (-) interact. C Identification of the minimal ADE2 promoter sequence that can maintain wild type yeast growth in the absence of an external adenine source. Truncation of the TGCCTC boxes resulted in yeast that grew more slowly and with a red coloration, indicative of insufficient adenine production and unhealthy yeast. Further truncation towards the TATA box resulted in almost total cessation of growth. D Increasing the number of TetO sequences in the ADE2 promoter increases the ADE2 repression mediated by the TetR. E Examples of the final Int-Seq strain differential growth signals observed in response to protein pairs that do (+) or do not (−) interact.

Supplementary Figure 2 Domain architecture and construct sizes of the BBSome components used in Y2H screen.

Supplementary Figure 3 Coverage and percentage of total mutations sequenced in the Y2H vector libraries.

150mer sequence reads were grouped based on the number of mis-match mutations they contained (1,2,3,4 or ≥5). To generate high confidence estimations, each individual mutation was counted only if ≥3 sequences were observed in the sequencing results. Red circles in each diagram represent the libraries generated using a random mutagenesis protocol. A The proportion of amino acids targeted by mutagenesis that contained either a programmed A,K or E mutation. B The proportion of all potential programmed AKE mutations present in the final mutant libraries. C The proportion of all other mutations contained in the final mutant libraries.

Supplementary Figure 4 Sequencing counts of BBS7 mutant Y2H vector library.

Box plots of each amino acid codon representing the number of times each codon was sequenced as a mutation across all positions in the Y2H construct.

Supplementary Figure 5 Comprehensive validation of the BBSome Int-Seq data.

A Majority of individual point mutants generated in BBS1 reconfirm in both a single pairwise Y2H experiment and in a LUMIER-style medium throughput experiment. Y2H panel numbers correspond to the indicated mutants in the LUMIER experiment.* = BBS1 G516A not tested in LUMIER experiments. B Comprehensive LUMIER style experiments reconfirm the Int-Seq data in an orthologous experimental system. LUMIER data is a representative result from two independent experiments. Each bar plot represents the average signal from triplicate transfections, with the error bars representing the highest and lowest values. C Expression analysis of protein-A tagged wild type and mutant constructs used in LUMIER-style experiments. Constructs that show a significantly decreased expression in comparison to the corresponding wild type are marked with a line underneath the lane. * represents non-specific band in each lane.

Supplementary Figure 6 Detailed depiction of the BBS4-BBS18 interaction.

Int-Seq identifies the central, highly mutated TPR domain containing region of BBS4 as essential for BBS18 interaction. A The C terminal half of BBS4 interacted with the full length BBS18 construct and was subject to Int-Seq analysis. BBS4 has seven annotated TPR domains, three of which C terminal of the centre of the protein are highly annotated with disease causing mutations. B While the total number of mutations sequenced spans the entire BBS4 construct, the majority of the signal is carried across the three central TPR domains. Inset: Two individual BBS4 mutations were validated as disrupting the BBS4-BBS18 interaction C The full length of the small 104 amino acid BBSome subunit BBS18 was subject to Int-Seq analysis. Two individual BBS18 mutations were validated as disrupting the BBS18-BBS4 interaction. D The secondary structure, predicted disorder, solvent accessibility and enriched mutagenic profile across the full length of BBS18.

Supplementary Figure 7 Detailed depiction of the BBS5 Int-Seq defined amino acids required for maintenance of the BBS9 interaction.

A The full length clone of BBS5 interacted with the full length BBS9 construct and was subject to Int-Seq analysis. BBS5 has one N terminal annotated GLUE domain and one C terminal annotated PH domain. B While the total number of mutations sequenced is strongly biased towards the C terminus of the BBS5 construct, the largest signal is carried towards the N terminus of the construct, with further clusters distributed towards the middle and C terminal section. Inset: Thee individual mutations were validated as disrupting the BBS5-BBS9 interaction (MTs 1,2,4), with one null mutation showing no-effect on the interaction (MT 3).

Supplementary Figure 8 Detailed depiction of the amino acids required to maintain the BBS2-7-9 core subnetwork.

A The C terminal domain of BBS7 is required for the BBS2 interactions and was subject to Int-Seq analysis. The majority of mutant enrichment is distributed across an alpha helical region in the mid-section of the domain. Inset: Four individual mutations were validated as disrupting the BBS5-BBS9 interaction (MTs 1-3,5), with one Int-Seq null mutation showing no-effect on the interaction (MT 4). *for visualisation purposes the axis limits exclude a single mutation peak. B The C terminal domain of BBS2 is required for the BBS9 and 7 interactions and was subject to Int-Seq analysis. The majority of mutant enrichment is distributed across an alpha helical region in the mid-section of the domain. Inset: Five individual mutations were disrupted both the BBS7 and BBS9 interaction. *for visualisation purposes the axis limits exclude a single mutation peak. C The C terminal domain of BBS9 is required for the BBS1,4 and 2 interactions and was subject to Int-Seq analysis. The majority of mutant enrichment is distributed across a beta sheet region towards the C terminus of the domain. Inset: Three individual Int-Seq identified mutations showed distinct interaction patterns with BBS1,BBS2 and BBS4.

Supplementary Figure 9 DNA constructs that comprise the Int-Seq system.

A pAG25 construct containing 2 copies of the LexA8::TetR_NLS in parallel for insertion in the MET2 locus of the yeast genome via homologous recombination. B Schematic diagram of the final synthetic ADE2 promoter with inserted restriction sites annotated. The first two tet operators were inserted via overlap stitch PCR. For the other three tet operators, a restriction site was first cloned into the promoter sequence (AvrII, SacI and NcoI). This allowed restriction digestion of the promoter sequence, removal of wild type sequence and insertion of a synthetic promoter sequence containing the tet operator in place of the wild type DNA sequence.

Supplementary Figure 10 Enriched mutant identification from next generation sequencing data.

A To expedite the alignment of obtained sequences, unique 150mers were collated in parallel to unique sequences pairs. B Unique 150mers were aligned against wild type BBS genes using the SCHRiMP software package. C Enrichment scores were calculated using a linear model for each mutant codon across all positions using the R statistical analysis environment. D Unique paired end sequences containing each identified enriched mutation were collated to identify co-segregating mutations. E The proportion of read pairs containing only the enriched mutation were plotted against the proportion of read pairs that contained the secondary mutation with the highest recall statistics. This enabled filtering of the data to remove sequences that contain co-segregating mutations (F), while retaining sequences that showed only a single enriched mutation across the gene body (G). H These sequences were then collated into a final profile through summing the enrichment across all identified mutations at any given residue.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–10 (PDF 2028 kb)

Life Sciences Reporting Summary (PDF 130 kb)

Supplementary Protocol

Step-by-step Int-Seq Protocol (PDF 259 kb)

Supplementary Data 1

Int-Seq analysis summary tables and individual interaction mutant enrichment scoring matrices. (XLSX 760 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Woodsmith, J., Apelt, L., Casado-Medrano, V. et al. Protein interaction perturbation profiling at amino-acid resolution. Nat Methods 14, 1213–1221 (2017). https://doi.org/10.1038/nmeth.4464

Download citation

Further reading

Search

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing