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Unique protein interaction networks define the chromatin remodelling module of the NuRD complex.

ABSTRACT: The combination of four proteins and their paralogues including MBD2/3, GATAD2A/B, CDK2AP1 and CHD3/4/5, which we refer to as the MGCC module, form the chromatin remodelling module of the nucleosome remodelling and deacetylase (NuRD) complex. To date, mechanisms by which the MGCC module acquires paralogue-specific function and specificity have not been addressed. Understanding the protein-protein interaction (PPI) network of the MGCC subunits is essential for defining underlying mechanisms of gene regulation. Therefore, using pulldown followed by mass spectrometry analysis (PD-MS), we report a proteome-wide interaction network of the MGCC module in a paralogue-specific manner. Our data also demonstrate that the disordered C-terminal region of CHD3/4/5 is a gateway to incorporate remodelling activity into both ChAHP (CHD4, ADNP, HP1γ) and NuRD complexes in a mutually exclusive manner. We define a short aggregation-prone region (APR) within the C-terminal segment of GATAD2B that is essential for the interaction of CHD4 and CDK2AP1 with the NuRD complex. Finally, we also report an association of CDK2AP1 with the nuclear receptor co-repressor (NCOR) complex. Overall, this study provides insight into the possible mechanisms through which the MGCC module can achieve specificity and diverse biological functions.

SUBMITTER: Sharifi Tabar M

PROVIDER: S-EPMC9545347 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Unique protein interaction networks define the chromatin remodelling module of the NuRD complex.

Sharifi Tabar Mehdi M Giardina Caroline C Feng Yue Y Francis Habib H Moghaddas Sani Hakimeh H Low Jason K K JKK Mackay Joel P JP Bailey Charles G CG Rasko John E J JEJ

The FEBS journal 20210731 1

The combination of four proteins and their paralogues including MBD2/3, GATAD2A/B, CDK2AP1 and CHD3/4/5, which we refer to as the MGCC module, form the chromatin remodelling module of the nucleosome remodelling and deacetylase (NuRD) complex. To date, mechanisms by which the MGCC module acquires paralogue-specific function and specificity have not been addressed. Understanding the protein-protein interaction (PPI) network of the MGCC subunits is essential for defining underlying mechanisms of ge ...[more]

PMID: 34231305

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Project description:MotivationIdentifying functional modules in protein-protein interaction (PPI) networks may shed light on cellular functional organization and thereafter underlying cellular mechanisms. Many existing module identification algorithms aim to detect densely connected groups of proteins as potential modules. However, based on this simple topological criterion of 'higher than expected connectivity', those algorithms may miss biologically meaningful modules of functional significance, in which proteins have similar interaction patterns to other proteins in networks but may not be densely connected to each other. A few blockmodel module identification algorithms have been proposed to address the problem but the lack of global optimum guarantee and the prohibitive computational complexity have been the bottleneck of their applications in real-world large-scale PPI networks.ResultsIn this article, we propose a novel optimization formulation LCP(2) (low two-hop conductance sets) using the concept of Markov random walk on graphs, which enables simultaneous identification of both dense and sparse modules based on protein interaction patterns in given networks through searching for LCP(2) by random walk. A spectral approximate algorithm SLCP(2) is derived to identify non-overlapping functional modules. Based on a bottom-up greedy strategy, we further extend LCP(2) to a new algorithm (greedy algorithm for LCP(2)) GLCP(2) to identify overlapping functional modules. We compare SLCP(2) and GLCP(2) with a range of state-of-the-art algorithms on synthetic networks and real-world PPI networks. The performance evaluation based on several criteria with respect to protein complex prediction, high level Gene Ontology term prediction and especially sparse module detection, has demonstrated that our algorithms based on searching for LCP(2) outperform all other compared algorithms.Availability and implementationAll data and code are available at http://www.cse.usf.edu/~xqian/fmi/slcp2hop/.

Dataset Information

Unique protein interaction networks define the chromatin remodelling module of the NuRD complex.

Publications

Unique protein interaction networks define the chromatin remodelling module of the NuRD complex.

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