Skip to main content

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

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.

Author information

Affiliations

Authors

Consortia

Corresponding authors

Correspondence to J Van Reeuwijk or Q Lu.

Rights and permissions

Open Access  This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made.

The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/.

The Creative Commons Public Domain Dedication waiver (https://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Boldt, K., Van Reeuwijk, J., Lu, Q. et al. Systematic exploration of the ciliary protein landscape by large-scale affinity proteomics. Cilia 4, P89 (2015). https://doi.org/10.1186/2046-2530-4-S1-P89

Download citation

Keywords

  • Protein Network
  • Human Embryonic Kidney Cell
  • Ciliary Function
  • Bioinformatic Algorithm
  • Important Framework