Trifunctional cross-linker for mapping protein-protein interaction networks and comparing protein conformational states

  1. Dan Tan
  2. Qiang Li
  3. Mei-Jun Zhang
  4. Chao Liu
  5. Chengying Ma
  6. Pan Zhang
  7. Yue-He Ding
  8. Sheng-Bo Fan
  9. Li Tao
  10. Bing Yang
  11. Xiangke Li
  12. Shoucai Ma
  13. Junjie Liu
  14. Boya Feng
  15. Xiaohui Liu
  16. Hong-Wei Wang
  17. Si-Min He
  18. Ning Gao
  19. Keqiong Ye
  20. Meng-Qiu Dong  Is a corresponding author
  21. Xiaoguang Lei
  1. Peking Union Medical College, Chinese Academy of Medical Sciences, China
  2. National Institute of Biological Sciences, China
  3. Institute of Computing Technology, Chinese Academy of Sciences, China
  4. Tsinghua University, China
  5. Chinese Academy of Medical Sciences, Peking Union Medical College, China
  6. Tianjin University, China

Abstract

To improve chemical cross-linking of proteins coupled with mass spectrometry (CXMS), we developed a lysine-targeted enrichable cross-linker containing a biotin tag for affinity purification, a chemical cleavage site to separate cross-linked peptides away from biotin after enrichment, and a spacer arm that can be labeled with stable isotopes for quantitation. By locating the flexible proteins on the surface of 70S ribosome, we show that this trifunctional cross-linker is effective at attaining structural information not easily attainable by crystallography and electron microscopy. From a crude Rrp46 immunoprecipitate, it helped identify two direct binding partners of Rrp46 and 15 protein-protein interactions (PPIs) among the co-immunoprecipitated exosome subunits. Applying it to E. coli and C. elegans lysates, we identified 3130 and 893 inter-linked lysine pairs, representing 677 and 121 PPIs. Using a quantitative CXMS workflow we demonstrate that it can reveal changes in the reactivity of lysine residues due to protein-nucleic acid interaction.

Article and author information

Author details

  1. Dan Tan

    Graduate Program, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  2. Qiang Li

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  3. Mei-Jun Zhang

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  4. Chao Liu

    Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  5. Chengying Ma

    Ministry of Education Key Laboratory of Protein Sciences, School of Life Sciences, Tsinghua University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  6. Pan Zhang

    Graduate Program, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  7. Yue-He Ding

    Graduate Program, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  8. Sheng-Bo Fan

    Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  9. Li Tao

    Graduate Program, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  10. Bing Yang

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  11. Xiangke Li

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  12. Shoucai Ma

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  13. Junjie Liu

    Ministry of Education Key Laboratory of Protein Sciences, School of Life Sciences, Tsinghua University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  14. Boya Feng

    Ministry of Education Key Laboratory of Protein Sciences, School of Life Sciences, Tsinghua University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  15. Xiaohui Liu

    College of Pharmaceutical Science and Technology, Tianjin University, Tianjin, China
    Competing interests
    The authors declare that no competing interests exist.
  16. Hong-Wei Wang

    Ministry of Education Key Laboratory of Protein Sciences, School of Life Sciences, Tsinghua University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  17. Si-Min He

    Key Lab of Intelligent Information Processing of Chinese Academy of Sciences, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  18. Ning Gao

    Ministry of Education Key Laboratory of Protein Sciences, School of Life Sciences, Tsinghua University, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  19. Keqiong Ye

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.
  20. Meng-Qiu Dong

    Graduate Program, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
    For correspondence
    dongmengqiu@nibs.ac.cn
    Competing interests
    The authors declare that no competing interests exist.
  21. Xiaoguang Lei

    National Institute of Biological Sciences, Beijing, China
    Competing interests
    The authors declare that no competing interests exist.

Copyright

© 2016, Tan et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 9,470
    views
  • 2,363
    downloads
  • 110
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Dan Tan
  2. Qiang Li
  3. Mei-Jun Zhang
  4. Chao Liu
  5. Chengying Ma
  6. Pan Zhang
  7. Yue-He Ding
  8. Sheng-Bo Fan
  9. Li Tao
  10. Bing Yang
  11. Xiangke Li
  12. Shoucai Ma
  13. Junjie Liu
  14. Boya Feng
  15. Xiaohui Liu
  16. Hong-Wei Wang
  17. Si-Min He
  18. Ning Gao
  19. Keqiong Ye
  20. Meng-Qiu Dong
  21. Xiaoguang Lei
(2016)
Trifunctional cross-linker for mapping protein-protein interaction networks and comparing protein conformational states
eLife 5:e12509.
https://doi.org/10.7554/eLife.12509

Share this article

https://doi.org/10.7554/eLife.12509

Further reading

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Yamato Niitani, Kohei Matsuzaki ... Michio Tomishige
    Research Article

    The two identical motor domains (heads) of dimeric kinesin-1 move in a hand-over-hand process along a microtubule, coordinating their ATPase cycles such that each ATP hydrolysis is tightly coupled to a step and enabling the motor to take many steps without dissociating. The neck linker, a structural element that connects the two heads, has been shown to be essential for head–head coordination; however, which kinetic step(s) in the chemomechanical cycle is ‘gated’ by the neck linker remains unresolved. Here, we employed pre-steady-state kinetics and single-molecule assays to investigate how the neck-linker conformation affects kinesin’s motility cycle. We show that the backward-pointing configuration of the neck linker in the front kinesin head confers higher affinity for microtubule, but does not change ATP binding and dissociation rates. In contrast, the forward-pointing configuration of the neck linker in the rear kinesin head decreases the ATP dissociation rate but has little effect on microtubule dissociation. In combination, these conformation-specific effects of the neck linker favor ATP hydrolysis and dissociation of the rear head prior to microtubule detachment of the front head, thereby providing a kinetic explanation for the coordinated walking mechanism of dimeric kinesin.

    1. Structural Biology and Molecular Biophysics
    Christopher T Schafer, Raymond F Pauszek III ... David P Millar
    Research Article

    The canonical chemokine receptor CXCR4 and atypical receptor ACKR3 both respond to CXCL12 but induce different effector responses to regulate cell migration. While CXCR4 couples to G proteins and directly promotes cell migration, ACKR3 is G-protein-independent and scavenges CXCL12 to regulate extracellular chemokine levels and maintain CXCR4 responsiveness, thereby indirectly influencing migration. The receptors also have distinct activation requirements. CXCR4 only responds to wild-type CXCL12 and is sensitive to mutation of the chemokine. By contrast, ACKR3 recruits GPCR kinases (GRKs) and β-arrestins and promiscuously responds to CXCL12, CXCL12 variants, other peptides and proteins, and is relatively insensitive to mutation. To investigate the role of conformational dynamics in the distinct pharmacological behaviors of CXCR4 and ACKR3, we employed single-molecule FRET to track discrete conformational states of the receptors in real-time. The data revealed that apo-CXCR4 preferentially populates a high-FRET inactive state, while apo-ACKR3 shows little conformational preference and high transition probabilities among multiple inactive, intermediate and active conformations, consistent with its propensity for activation. Multiple active-like ACKR3 conformations are populated in response to agonists, compared to the single CXCR4 active-state. This and the markedly different conformational landscapes of the receptors suggest that activation of ACKR3 may be achieved by a broader distribution of conformational states than CXCR4. Much of the conformational heterogeneity of ACKR3 is linked to a single residue that differs between ACKR3 and CXCR4. The dynamic properties of ACKR3 may underly its inability to form productive interactions with G proteins that would drive canonical GPCR signaling.