Dataset Information

Proteome-wide identification of WRN-interacting proteins in untreated and nuclease-treated samples.

ABSTRACT: Werner syndrome (WS) is characterized by the premature onset of several age-associated pathologies. The protein defective in WS patients (WRN) is a helicase/exonuclease involved in DNA repair, replication, telomere maintenance, and transcription. Here, we present the results of a large-scale proteome analysis to determine protein partners of WRN. We expressed fluorescent tagged-WRN (eYFP-WRN) in human 293 embryonic kidney cells and detected interacting proteins by co-immunoprecipitation from cell extract. We identified by mass spectrometry 220 nuclear proteins that complexed with WRN. This number was reduced to 40 when broad-spectrum nucleases were added to the lysate. We consider these 40 proteins as directly interacting with WRN. Some of these proteins have previously been shown to interact with WRN, whereas most are new partners. Among the top 15 hits, we find the new interactors TMPO, HNRNPU, RPS3, RALY, RPS9 DDX21, and HNRNPM. These proteins are likely important components in understanding the function of WRN in preventing premature aging and deserve further investigation. We have confirmed endogenous WRN interaction with endogenous RPS3, a ribosomal protein with endonuclease activities involved in oxidative DNA damage recognition. Our results suggest that the use of nucleases during cell lysis severely restricts interacting protein partners and thus enhances specificity.

SUBMITTER: Lachapelle S

PROVIDER: S-EPMC4586248 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature

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Proteome-wide identification of WRN-interacting proteins in untreated and nuclease-treated samples.

Lachapelle Sophie S Gagné Jean-Philippe JP Garand Chantal C Desbiens Myriam M Coulombe Yan Y Bohr Vilhelm A VA Hendzel Michael J MJ Masson Jean-Yves JY Poirier Guy G GG Lebel Michel M

Journal of proteome research 20110216 3

Werner syndrome (WS) is characterized by the premature onset of several age-associated pathologies. The protein defective in WS patients (WRN) is a helicase/exonuclease involved in DNA repair, replication, telomere maintenance, and transcription. Here, we present the results of a large-scale proteome analysis to determine protein partners of WRN. We expressed fluorescent tagged-WRN (eYFP-WRN) in human 293 embryonic kidney cells and detected interacting proteins by co-immunoprecipitation from cel ...[more]

PMID: 21210717

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Project description:Self-interacting proteins, whose two or more copies can interact with each other, play important roles in cellular functions and the evolution of protein interaction networks (PINs). Knowing whether a protein can self-interact can contribute to and sometimes is crucial for the elucidation of its functions. Previous related research has mainly focused on the structures and functions of specific self-interacting proteins, whereas knowledge on their overall properties is limited. Meanwhile, the two current most common high throughput protein interaction assays have limited ability to detect self-interactions because of biological artifacts and design limitations, whereas the bioinformatic prediction method of self-interacting proteins is lacking. This study aims to systematically study and predict self-interacting proteins from an overall perspective. We find that compared with other proteins the self-interacting proteins in the structural aspect contain more domains; in the evolutionary aspect they tend to be conserved and ancient; in the functional aspect they are significantly enriched with enzyme genes, housekeeping genes, and drug targets, and in the topological aspect tend to occupy important positions in PINs. Furthermore, based on these features, after feature selection, we use logistic regression to integrate six representative features, including Gene Ontology term, domain, paralogous interactor, enzyme, model organism self-interacting protein, and betweenness centrality in the PIN, to develop a proteome-wide prediction model of self-interacting proteins. Using 5-fold cross-validation and an independent test, this model shows good performance. Finally, the prediction model is developed into a user-friendly web service SLIPPER (SeLf-Interacting Protein PrEdictoR). Users may submit a list of proteins, and then SLIPPER will return the probability_scores measuring their possibility to be self-interacting proteins and various related annotation information. This work helps us understand the role self-interacting proteins play in cellular functions from an overall perspective, and the constructed prediction model may contribute to the high throughput finding of self-interacting proteins and provide clues for elucidating their functions.

Dataset Information

Proteome-wide identification of WRN-interacting proteins in untreated and nuclease-treated samples.

Publications

Proteome-wide identification of WRN-interacting proteins in untreated and nuclease-treated samples.

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