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RNF8 mediates NONO degradation following UV-induced DNA damage to properly terminate ATR-CHK1 checkpoint signaling

ABSTRACT: RNF8 is a key E3 ubiquitin ligase functioning in both DSB- and UV-induced DDR, identification of additional substrates will help further elucidate its role in DNA damage signaling. To identify substrates of ubiquitin ligases, we have recently devised a method based on proximity-dependent biotin labeling. In this method, an E3 ubiquitin ligase of interest is expressed as a fusion to Escherichia coli biotin ligase BirA together with a biotin acceptor peptide (AP)-tagged ubiquitin. The BirA-directed biotin labeling of AP depends on the proximity of the two fusion proteins in the cell, which leads to preferential labeling of ubiquitinated E3 substrates. In this study, we applied this procedure to RNF8 and identified its substrates.

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Permanent Cell Line Cell, Hela Cell

DISEASE(S): Cervical Adenocarcinoma

SUBMITTER: Rakesh Deshar

LAB HEAD: Jong-Bok Yoon

PROVIDER: PXD006156 | Pride | 2018-11-07

REPOSITORIES: Pride

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RNF8 mediates NONO degradation following UV-induced DNA damage to properly terminate ATR-CHK1 checkpoint signaling.

Deshar Rakesh R Yoo Wonjin W Cho Eun-Bee EB Kim Sungjoo S Yoon Jong-Bok JB

Nucleic acids research 20190101 2

RNF8 plays a critical role in DNA damage response (DDR) to initiate ubiquitination-dependent signaling. To better characterize the role of RNF8 in UV-induced DDR, we searched for novel substrates of RNF8 and identified NONO as one intriguing substrate. We found that: (i) RNF8 ubiquitinates NONO and (ii) UV radiation triggers NONO ubiquitination and its subsequent degradation. Depletion of RNF8 inhibited UV-induced degradation of NONO, suggesting that RNF8 targets NONO for degradation in response ...[more]

PMID: 30445466

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Project description:Proctor2007 - Age related decline of proteolysis, ubiquitin-proteome system This is a stochastic model of the ubiquitin-proteasome system for a generic pool of native proteins (NatP), which have a half-life of about 10 hours under normal conditions. It is assumed that these proteins are only degraded after they have lost their native structure due to a damage event. This is represented in the model by the misfolding reaction which depends on the level of reactive oxygen species (ROS) in the cell. Misfolded proteins (MisP) are first bound by an E3 ubiquitin ligase. Ubiquitin (Ub) is activated by E1 (ubiquitin-activating enzyme) and then passed to E2 (ubiquitin-conjugating enzyme). The E2 enzyme then passes the ubiquitin molecule to the E3/MisP complex with the net effect that the misfolded protein is monoubiquitinated and both E2 and E3 are released. Further ubiquitin molecules are added in a step-wise manner. When the chain of ubiquitin molecules is of length 4 or more, the polyubiquitinated misfolded protein may bind to the proteasome. The model also includes de-ubiquitinating enzymes (DUB) which cleave ubiquitin molecules from the chain in a step-wise manner. They work on chains attached to misfolded proteins both unbound and bound to the proteasomes. Misfolded proteins bound to the proteasome may be degraded releasing ubiquitin. Misfolded proteins including ubiquitinated proteins may also aggregate. Aggregates (AggP) may be sequestered (Seq_AggP) which takes them out of harm's way or they may bind to the proteasome (AggP_Proteasome). Proteasomes bound by aggregates are no longer available for protein degradation. Figure 2 and Figure 3 has been simulated using Gillespie2. This model is described in the article: An in silico model of the ubiquitin-proteasome system that incorporates normal homeostasis and age-related decline. Proctor CJ, Tsirigotis M, Gray DA. BMC Syst Biol 2007; 1: 17 Abstract: BACKGROUND: The ubiquitin-proteasome system is responsible for homeostatic degradation of intact protein substrates as well as the elimination of damaged or misfolded proteins that might otherwise aggregate. During ageing there is a decline in proteasome activity and an increase in aggregated proteins. Many neurodegenerative diseases are characterised by the presence of distinctive ubiquitin-positive inclusion bodies in affected regions of the brain. These inclusions consist of insoluble, unfolded, ubiquitinated polypeptides that fail to be targeted and degraded by the proteasome. We are using a systems biology approach to try and determine the primary event in the decline in proteolytic capacity with age and whether there is in fact a vicious cycle of inhibition, with accumulating aggregates further inhibiting proteolysis, prompting accumulation of aggregates and so on. A stochastic model of the ubiquitin-proteasome system has been developed using the Systems Biology Mark-up Language (SBML). Simulations are carried out on the BASIS (Biology of Ageing e-Science Integration and Simulation) system and the model output is compared to experimental data wherein levels of ubiquitin and ubiquitinated substrates are monitored in cultured cells under various conditions. The model can be used to predict the effects of different experimental procedures such as inhibition of the proteasome or shutting down the enzyme cascade responsible for ubiquitin conjugation. RESULTS: The model output shows good agreement with experimental data under a number of different conditions. However, our model predicts that monomeric ubiquitin pools are always depleted under conditions of proteasome inhibition, whereas experimental data show that monomeric pools were depleted in IMR-90 cells but not in ts20 cells, suggesting that cell lines vary in their ability to replenish ubiquitin pools and there is the need to incorporate ubiquitin turnover into the model. Sensitivity analysis of the model revealed which parameters have an important effect on protein turnover and aggregation kinetics. CONCLUSION: We have developed a model of the ubiquitin-proteasome system using an iterative approach of model building and validation against experimental data. Using SBML to encode the model ensures that it can be easily modified and extended as more data become available. Important aspects to be included in subsequent models are details of ubiquitin turnover, models of autophagy, the inclusion of a pool of short-lived proteins and further details of the aggregation process. This model is hosted on BioModels Database and identified by: BIOMD0000000105. To cite BioModels Database, please use: BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

			Action	DRS
	140912_RNF8_KGG_RK.mgf	Mgf
	140912_RNF8_KGG_RK.pride.mgf.gz	Mgf
	NONO-KGG-MGF.mgf	Mgf
	NONO-KGG-MGF.pride.mgf.gz	Mgf
	NONO-KGG-Mziden.mzid.gz	Mzid