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Cilia

, 4:P89 | Cite as

Systematic exploration of the ciliary protein landscape by large-scale affinity proteomics

  • K Boldt
  • J Van Reeuwijk
  • Q Lu
  • K Koutroumpas
  • N Horn
  • S Van Beersum
  • Y Texier
  • TM Nguyen
  • JR Willer
  • E.U. The Syscilia Consortium
  • N Katsanis
  • F Képès
  • RB Russell
  • M Ueffing
  • R Roepman
Open Access
Poster presentation
  • 353 Downloads

Keywords

Protein Network Human Embryonic Kidney Cell Ciliary Function Bioinformatic Algorithm Important Framework 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Objective

Mutations in different ciliopathy-associated genes often result in overlapping clinical phenotypes, which can in part be explained by disruption of overlapping functional protein modules. In this study we conducted large-scale affinity proteomics in a systems biology-based approach to boost insights into the assembly of these ciliary modules, and their connectivity in larger functional protein networks: the ciliary protein interaction landscape. This provides an important framework to deconvolute the pathways and processes that drive ciliopathies, and to understand the general importance of ciliary function for cellular homeostasis.

Methods

Using more than 220 known and potential ciliary proteins as baits, fused to the Strep/FLAG-tandem affinity purification tag (SF-TAP), we purified protein complexes from human embryonic kidney cells (HEK293T), which were analysed by mass spectrometry. In parallel, specific modules were scrutinized for binary interactions by yeast two-hybrid analyses. Existing and newly developed bioinformatic algorithms were employed to validate the confidence of the identified interactions and to define functional modules.

Results

We obtained low, medium and high confidence sets of protein interactions and modules. From this data we could assign novel components to known ciliary modules such as the anterograde and retrograde intraflagellar transport modules and the dynein-2 module. Due to the strong focus on ciliary proteins as baits and the integration of data from various sources, we could also identify several new modules, potentially with cilia-associated functions in health and disease.

Conclusion

Our systems oriented approach, employing affinity proteomics to define the ciliary network has resulted in a comprehensive description of known and candidate ciliary protein networks and modules, which can serve as a resource for candidate ciliopathy proteins and our understanding of pathogenic mechanisms underlying ciliopathies.

Copyright information

© Boldt et al. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Authors and Affiliations

  • K Boldt
    • 1
  • J Van Reeuwijk
    • 2
    • 3
  • Q Lu
    • 4
  • K Koutroumpas
    • 5
  • N Horn
    • 1
  • S Van Beersum
    • 2
    • 3
  • Y Texier
    • 6
  • TM Nguyen
    • 2
    • 3
  • JR Willer
    • 7
  • E.U. The Syscilia Consortium
    • 8
  • N Katsanis
    • 7
  • F Képès
    • 5
  • RB Russell
    • 4
  • M Ueffing
    • 1
  • R Roepman
    • 2
    • 3
  1. 1.Division of Experimental Ophthalmology and Medical Proteome CenterEberhard-Karls Universität TübingenTübingenGermany
  2. 2.Department of Human GeneticsRadboud University Medical CenterNijmegenThe Netherlands
  3. 3.Radboud Institute for Molecular Life SciencesRadboud University NijmegenNijmegenThe Netherlands
  4. 4.Cell Networks, Bioquant, Cluster of ExcellenceUniversity of HeidelbergHeidelbergGermany
  5. 5.Institute of Systems and Synthetic Biology, Genopole, CNRSUniversité d'EvryEvryFrance
  6. 6.Research Unit Molecular EpigeneticsHelmholtz Zentrum MünchenMunichGermany
  7. 7.Center for Human Disease Modeling, Department of Cell BiologyDuke UniversityDurhamUSA
  8. 8.Syscilia, Radboud Institute for Molecular Life SciencesRadboud University NijmegenNijmegenThe Netherlands

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