CoChat
Sign Up
Cited by 157Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and ApplicationsBioinformatics and Genomic Networks

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

Reliable identification of protein-protein interactions by crosslinking mass spectrometry

Open access
Lenz, Swantje, Sinn, Ludwig R., O’Reilly, Francis J., Fischer, Lutz, Wegner, Fritz, Rappsilber, Juri·2021·Nature Communications
DOI 10.1038/s41467-021-23666-zPMC PMC8196013

Published version of a preprint

Open this paper in CoChat — free accountOpen PDF

Abstract

Protein-protein interactions govern most cellular pathways and processes, and multiple technologies have emerged to systematically map them. Assessing the error of interaction networks has been a challenge. Crosslinking mass spectrometry is currently widening its scope from structural analyses of purified multi-protein complexes towards systems-wide analyses of protein-protein interactions (PPIs). Using a carefully controlled large-scale analysis of Escherichia coli cell lysate, we demonstrate that false-discovery rates (FDR) for PPIs identified by crosslinking mass spectrometry can be reliably estimated. We present an interaction network comprising 590 PPIs at 1% decoy-based PPI-FDR. The structural information included in this network localises the binding site of the hitherto uncharacterised protein YacL to near the DNA exit tunnel on the RNA polymerase.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1038/s41467-021-23666-z

Cites

4 of 4 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Flagged first, then by citations

Show all 4 references

Research works printed but not linked: 52

  1. O’Reilly, F. J. & Rappsilber, J. Cross-linking mass spectrometry: methods and applications in structural, molecular and systems biology. Nat. Struct. Mol. Biol. 25, 1000–1008 (2018). · DOI
  2. Chavez, J. D., Keller, A., Zhou, B., Tian, R. & Bruce, J. E. Cellular interactome dynamics during paclitaxel treatment. Cell Rep. 29, 2371–2383.e5 (2019). · DOI
  3. Steigenberger, B., Pieters, R. J., Heck, A. J. R. & Scheltema, R. A. PhoX: an IMAC-enrichable cross-linking reagent. ACS Cent. Sci. 5, 1514–1522 (2019). · DOI
  4. Chen, Z.-L. et al. A high-speed search engine pLink 2 with systematic evaluation for proteome-scale identification of cross-linked peptides. Nat. Commun. 10, 3404 (2019). · DOI
  5. Mendes, M. L. et al. An integrated workflow for crosslinking mass spectrometry. Mol. Syst. Biol. 15, e8994 (2019). · DOI
  6. Ryl, P. S. J. et al. In situ structural restraints from crosslinking mass spectrometry in human mitochondria. J. Proteome Res. https://doi.org/10.1021/acs.jproteome.9b00541 (2019). · DOI
  7. Gonzalez-Lozano, M. A. et al. Stitching the synapse: cross-linking mass spectrometry into resolving synaptic protein interactions. Sci. Adv. 6, eaax5783 (2020). · DOI
  8. Makepeace, K. A. T. et al. Improving identification of in-organello protein-protein interactions using an affinity-enrichable, isotopically coded, and mass spectrometry-cleavable chemical crosslinker. Mol. Cell. Proteomics 19, 624–639 (2020). · DOI
  9. Bartolec, T. K. et al. Cross-linking mass spectrometry analysis of the yeast nucleus reveals extensive protein-protein interactions not detected by systematic two-hybrid or affinity purification-mass spectrometry. Anal. Chem. 92, 1874–1882 (2020). · DOI
  10. Linden, A. et al. A cross-linking mass spectrometry approach defines protein interactions in yeast mitochondria. Mol. Cell. Proteomics https://doi.org/10.1074/mcp.RA120.002028 (2020). · DOI
  11. Götze, M., Iacobucci, C., Ihling, C. H. & Sinz, A. A simple cross-linking/mass spectrometry workflow for studying system-wide protein interactions. Anal. Chem. 91, 10236–10244 (2019). · DOI
  12. Yugandhar, K. et al. MaXLinker: proteome-wide cross-link identifications with high specificity and sensitivity. Mol. Cell. Proteomics 19, 554–568 (2020). · DOI
  13. Maiolica, A. et al. Structural analysis of multiprotein complexes by cross-linking, mass spectrometry, and database searching. Mol. Cell. Proteomics 6, 2200–2211 (2007). · DOI
  14. Walzthoeni, T. et al. False discovery rate estimation for cross-linked peptides identified by mass spectrometry. Nat. Methods 9, 901–903 (2012). · DOI
  15. Fischer, L. & Rappsilber, J. Quirks of error estimation in cross-linking/mass spectrometry. Anal. Chem. 89, 3829–3833 (2017). · DOI
  16. Fischer, L. & Rappsilber, J. False discovery rate estimation and heterobifunctional cross-linkers. PLoS ONE 13, e0196672 (2018). · DOI
  17. Yang, B. et al. Identification of cross-linked peptides from complex samples. Nat. Methods 9, 904–906 (2012). · DOI
  18. Keller, A., Chavez, J. D., Felt, K. C. & Bruce, J. E. Prediction of an upper limit for the fraction of interprotein cross-links in large-scale in vivo cross-linking studies. J. Proteome Res. 18, 3077–3085 (2019). · DOI
  19. Beveridge, R., Stadlmann, J., Penninger, J. M. & Mechtler, K. A synthetic peptide library for benchmarking crosslinking-mass spectrometry search engines for proteins and protein complexes. Nat. Commun. 11, 742 (2020). · DOI
  20. Leitner, A. et al. Towards increased reliability, transparency and accessibility in cross-linking mass spectrometry. Structure 28, 1259–1268 (2020). · DOI
  21. Schmidt, A. et al. The quantitative and condition-dependent Escherichia coli proteome. Nat. Biotechnol. 34, 104–110 (2016). · DOI
  22. Belsom, A., Schneider, M., Fischer, L., Brock, O. & Rappsilber, J. Serum albumin domain structures in human blood serum by mass spectrometry and computational biology. Mol. Cell. Proteomics 15, 1105–1116 (2016). · DOI
  23. Matzinger, M., Kandioller, W., Doppler, P., Heiss, E. H. & Mechtler, K. Fast and highly efficient affinity enrichment of Azide-A-DSBSO cross-linked peptides. J. Proteome Res. 19, 2071–2079 (2020). · DOI
  24. Chen, Z. A. & Rappsilber, J. Quantitative cross-linking/mass spectrometry to elucidate structural changes in proteins and their complexes. Nat. Protoc. 14, 171–201 (2019). · DOI
  25. Yugandhar, K., Wang, T.-Y., Wierbowski, S. D., Shayhidin, E. E. & Yu, H. Structure-based validation can drastically underestimate error rate in proteome-wide cross-linking mass spectrometry studies. Nat. Methods 17, 985–988 (2020). · DOI
  26. Giese, S. H., Belsom, A., Sinn, L., Fischer, L. & Rappsilber, J. Noncovalently associated peptides observed during liquid chromatography-mass spectrometry and their effect on cross-link analyses. Anal. Chem. 91, 2678–2685 (2019). · DOI
  27. Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008). · DOI · Paper page
  28. Tyanova, S. et al. The Perseus computational platform for comprehensive analysis of (prote)omics data. Nat. Methods 13, 731–740 (2016). · DOI · Paper page
  29. Horne, J. E. et al. Rapid mapping of protein interactions using tag-transfer photocrosslinkers. Angew. Chem. Int. Ed. 57, 16688–16692 (2018). · DOI
  30. Leitner, A. et al. Expanding the chemical cross-linking toolbox by the use of multiple proteases and enrichment by size exclusion chromatography. Mol. Cell. Proteomics 11, M111.014126 (2012). · DOI
  31. Giese, S. H., Belsom, A. & Rappsilber, J. Optimized fragmentation regime for diazirine photo-cross-linked peptides. Anal. Chem. 88, 8239–8247 (2016). · DOI
  32. Kolbowski, L., Mendes, M. L. & Rappsilber, J. Optimizing the parameters governing the fragmentation of cross-linked peptides in a tribrid mass spectrometer. Anal. Chem. 89, 5311–5318 (2017). · DOI
  33. Chambers, M. C. et al. A cross-platform toolkit for mass spectrometry and proteomics. Nat. Biotechnol. 30, 918–920 (2012). · DOI
  34. Lenz, S., Giese, S. H., Fischer, L. & Rappsilber, J. In-search assignment of monoisotopic peaks improves the identification of cross-linked peptides. J. Proteome Res. 17, 3923–3931 (2018). · DOI
  35. Szklarczyk, D. et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 47, D607–D613 (2019). · DOI · Paper page
  36. Keseler, I. M. et al. The EcoCyc database: reflecting new knowledge about Escherichia coli K-12. Nucleic Acids Res. 45, D543–D550 (2017). · DOI
  37. Goddard, T. D. et al. UCSF ChimeraX: Meeting modern challenges in visualization and analysis. Protein Sci. 27, 14–25 (2018). · DOI · Paper page
  38. Sobti, M. et al. Cryo-EM structures of the autoinhibited E. coli ATP synthase in three rotational states. elife 5, e21598 (2016). · DOI · Paper page
  39. Vanden Broeck, A., Lotz, C., Ortiz, J. & Lamour, V. Cryo-EM structure of the complete E. coli DNA gyrase nucleoprotein complex. Nat. Commun. 10, 4935 (2019). · DOI
  40. Fei, X., Ye, X., LaRonde, N. A. & Lorimer, G. H. Formation and structures of GroEL:GroES2 chaperonin footballs, the protein-folding functional form. Proc. Natl Acad. Sci. USA 111, 12775–12780 (2014). · DOI
  41. Liu, B., Zuo, Y. & Steitz, T. A. Structural basis for transcription reactivation by RapA. Proc. Natl Acad. Sci. USA 112, 2006–2010 (2015). · DOI
  42. Abdelkareem, M. ’men et al. Structural basis of transcription: RNA polymerase backtracking and its reactivation. Mol. Cell 75, 298–309.e4 (2019). · DOI
  43. Said, N. et al. Structural basis for λN-dependent processive transcription antitermination. Nat. Microbiol 2, 17062 (2017). · DOI
  44. Guo, X. et al. Structural basis for NusA stabilized transcriptional pausing. Mol. Cell 69, 816–827.e4 (2018). · DOI
  45. Feng, Y. et al. Structural basis of transcription inhibition by CBR hydroxamidines and CBR pyrazoles. Structure 23, 1470–1481 (2015). · DOI
  46. Iacobucci, C. et al. Carboxyl-photo-reactive MS-cleavable cross-linkers: unveiling a hidden aspect of diazirine-based reagents. Anal. Chem. 90, 2805–2809 (2018). · DOI
  47. Yang, J. & Zhang, Y. I-TASSER server: new development for protein structure and function predictions. Nucleic Acids Res. 43, W174–W181 (2015). · DOI
  48. van Zundert, G. C. P. & Bonvin, A. M. J. J. DisVis: quantifying and visualizing accessible interaction space of distance-restrained biomolecular complexes. Bioinformatics 31, 3222–3224 (2015). · DOI
  49. Kang, J. Y. et al. Structural basis for transcript elongation control by NusG family universal regulators. Cell 173, 1650–1662.e14 (2018). · DOI
  50. Sali, A. & Blundell, T. L. Comparative protein modelling by satisfaction of spatial restraints. J. Mol. Biol. 234, 779–815 (1993). · DOI · Paper page
  51. Pettersen, E. F. et al. UCSF Chimera–a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004). · DOI
  52. Okuda, S. et al. jPOSTrepo: an international standard data repository for proteomes. Nucleic Acids Res. 45, D1107–D1111 (2017). · DOI

Cited by

Sorted by citations

See all 157

Metadata

Authors
Lenz, S., Sinn, L. R., O’Reilly, F. J., Fischer, L., Wegner, F., & Rappsilber, J.
Affiliations
  • Technische Universität Berlin (DE)
  • Wellcome Centre for Cell Biology (GB)
Corresponding author
Rappsilber, Juri
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2021-06-11
Volume
12
Issue
1
Pages
3564-3564
ISSN
2041-1723 (ISSN-L)
DOI
10.1038/s41467-021-23666-z
PMC
PMC8196013
OpenAlex
W3166761727
Cited by
157
References
4
Citations by year
2026: 28 · 2025: 25 · 2024: 45 · 2023: 28 · 2022: 19 · 2021: 9
FWCI
9.23
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Communications (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
Funders
Deutsche Forschungsgemeinschaft (426290502, 392923329/GRK2473)
Topics
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
  • Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Keywords
protein-protein interaction, cross-linking mass spectrometry, false discovery rate, interaction networks, Escherichia coli, RNA polymerase, binding site identification, protein complex structure
MeSH terms
Escherichia coli, Mass Spectrometry, Proteome, Protein Interaction Mapping, Escherichia coli Proteins, Protein Interaction Maps

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review