An unexpected INAD PDZ tandem-mediated PLCβ binding in Drosophila photo receptors

  1. Fei Ye
  2. Yuxin Huang
  3. Jianchao Li
  4. Yuqian Ma
  5. Chensu Xie
  6. Zexu Liu
  7. Xiaoying Deng
  8. Jun Wan
  9. Tian Xue
  10. Wei Liu  Is a corresponding author
  11. Mingjie Zhang  Is a corresponding author
  1. Hong Kong University of Science and Technology, Hong Kong
  2. Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, China
  3. University of Science and Technology of China, China

Abstract

INAD assembles key enzymes of Drosophila compound eye photo-transduction pathway into a supramolecular complex, supporting efficient and fast light signaling. However, the molecular mechanism governing the interaction between INAD and NORPA (phospholipase Cβ, PLCβ), a key step for the fast kinetics of the light signaling, is not known. Here, we show that the NORPA C-terminal coiled-coil domain and PDZ-binding motif (CC-PBM) synergistically bind to INAD PDZ45 tandem with an unexpected mode and unprecedentedly high affinity. Guided by the INAD/NORPA complex structure, we discover that INADL is likely a mammalian counterpart of INAD. The INADL PDZ89 tandem specifically binds to PLCβ4 with a strikingly similar mode to that of the INAD/NORPA complex as revealed by the structure of the INADL PDZ89/PLCβ4 CC-PBM complex. Therefore, our study suggests that the highly specific PDZ tandem/PLCβ interactions are an evolutionarily conserved mechanism in PLCβ signaling of the animal kingdom.

Data availability

Diffraction data have been deposited at PDB under the accession numbers 6IRB, 6IRC, 6IRD, and 6IRE.

The following data sets were generated

Article and author information

Author details

  1. Fei Ye

    Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, Hong Kong
    Competing interests
    No competing interests declared.
  2. Yuxin Huang

    Biomedical Research Institute, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen, China
    Competing interests
    No competing interests declared.
  3. Jianchao Li

    Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, Hong Kong
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-8921-1626
  4. Yuqian Ma

    School of Life Sciences, University of Science and Technology of China, Hefei, China
    Competing interests
    No competing interests declared.
  5. Chensu Xie

    Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, Hong Kong
    Competing interests
    No competing interests declared.
  6. Zexu Liu

    Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, Hong Kong
    Competing interests
    No competing interests declared.
  7. Xiaoying Deng

    Biomedical Research Institute, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen, China
    Competing interests
    No competing interests declared.
  8. Jun Wan

    Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, Hong Kong
    Competing interests
    No competing interests declared.
  9. Tian Xue

    School of Life Sciences, University of Science and Technology of China, Hefei, China
    Competing interests
    No competing interests declared.
  10. Wei Liu

    Biomedical Research Institute, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen, China
    For correspondence
    liuwei@sphmc.org
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8250-2562
  11. Mingjie Zhang

    Division of Life Science, State Key Laboratory of Molecular Neuroscience, Hong Kong University of Science and Technology, Hong Kong, Hong Kong
    For correspondence
    mzhang@ust.hk
    Competing interests
    Mingjie Zhang, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9404-0190

Funding

Minister of Science and Technology of China (2014CB910204)

  • Mingjie Zhang

Research Grant Council of Hong Kong (C6004-17)

  • Mingjie Zhang

Shenzhen Basic Research Grant (JCYJ20170411090807530)

  • Wei Liu

Shenzhen Basic Research Grant (JCYJ20160427185712266)

  • Wei Liu

National Natural Science Foundation of China (31670765)

  • Wei Liu

National Natural Science Foundation of China (31870746)

  • Wei Liu

Chinese Academy of Sciences Key Project (XDPB10)

  • Tian Xue

Chinese Academy of Sciences Key Project (XDB02010000)

  • Tian Xue

Research Grant Council of Hong Kong (AoE-M09-12)

  • Mingjie Zhang

National Key R&D Program of China (2016YFA0501903)

  • Mingjie Zhang

Natural Science Foundation of Guangdong Province (2016A030312016)

  • Mingjie Zhang

Shenzhen Basic Research Grant (JCYJ20160229153100269)

  • Wei Liu

National Natural Science Foundation of China (81790644)

  • Tian Xue

Chinese Academy of Sciences Key Project (XDA16020603)

  • Tian Xue

National Key Basic Research Program of China (2016YFA0400900)

  • Tian Xue

GRF grant from RGC of Hong Kong (16104518)

  • Fei Ye

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2018, Ye 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

  • 1,119
    views
  • 210
    downloads
  • 10
    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. Fei Ye
  2. Yuxin Huang
  3. Jianchao Li
  4. Yuqian Ma
  5. Chensu Xie
  6. Zexu Liu
  7. Xiaoying Deng
  8. Jun Wan
  9. Tian Xue
  10. Wei Liu
  11. Mingjie Zhang
(2018)
An unexpected INAD PDZ tandem-mediated PLCβ binding in Drosophila photo receptors
eLife 7:e41848.
https://doi.org/10.7554/eLife.41848

Share this article

https://doi.org/10.7554/eLife.41848

Further reading

    1. Structural Biology and Molecular Biophysics
    Manming Xu, Sarath Chandra Dantu ... Shozeb Haider
    Research Article

    The relationship between protein dynamics and function is essential for understanding biological processes and developing effective therapeutics. Functional sites within proteins are critical for activities such as substrate binding, catalysis, and structural changes. Existing computational methods for the predictions of functional residues are trained on sequence, structural, and experimental data, but they do not explicitly model the influence of evolution on protein dynamics. This overlooked contribution is essential as it is known that evolution can fine-tune protein dynamics through compensatory mutations either to improve the proteins’ performance or diversify its function while maintaining the same structural scaffold. To model this critical contribution, we introduce DyNoPy, a computational method that combines residue coevolution analysis with molecular dynamics simulations, revealing hidden correlations between functional sites. DyNoPy constructs a graph model of residue–residue interactions, identifies communities of key residue groups, and annotates critical sites based on their roles. By leveraging the concept of coevolved dynamical couplings—residue pairs with critical dynamical interactions that have been preserved during evolution—DyNoPy offers a powerful method for predicting and analysing protein evolution and dynamics. We demonstrate the effectiveness of DyNoPy on SHV-1 and PDC-3, chromosomally encoded β-lactamases linked to antibiotic resistance, highlighting its potential to inform drug design and address pressing healthcare challenges.

    1. Biochemistry and Chemical Biology
    2. Structural Biology and Molecular Biophysics
    Andrew P Latham, Longchen Zhu ... Bin Zhang
    Research Article

    The phase separation of intrinsically disordered proteins is emerging as an important mechanism for cellular organization. However, efforts to connect protein sequences to the physical properties of condensates, that is, the molecular grammar, are hampered by a lack of effective approaches for probing high-resolution structural details. Using a combination of multiscale simulations and fluorescence lifetime imaging microscopy experiments, we systematically explored a series of systems consisting of diblock elastin-like polypeptides (ELPs). The simulations succeeded in reproducing the variation of condensate stability upon amino acid substitution and revealed different microenvironments within a single condensate, which we verified with environmentally sensitive fluorophores. The interspersion of hydrophilic and hydrophobic residues and a lack of secondary structure formation result in an interfacial environment, which explains both the strong correlation between ELP condensate stability and interfacial hydrophobicity scales, as well as the prevalence of protein-water hydrogen bonds. Our study uncovers new mechanisms for condensate stability and organization that may be broadly applicable.