Phosphoproteomic analysis reveals plant <scp>DNA</scp> damage signalling pathways with a functional role for histone H2<scp>AX</scp> phosphorylation in plant growth under genotoxic stress

Waterworth, Wanda M.; Wilson, Michael; Wang, Dapeng; Nühse, Thomas S.; Warward, Stacey; Selley, Julian N.; West, Claudia

doi:10.1111/tpj.14495

Cited by 39 publications

(24 citation statements)

References 70 publications

(117 reference statements)

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“…We identified 933 unique phosphoproteins in phosphopeptide enriched samples from 5-days-old dark-grown seedlings that contain 2884 phosphosites (Table S3 ). These results are similar in number of phosphoproteins and phosphopeptides to other phosphoproteomic experiments [ 18 , 19 ].…”

Section: Resultssupporting

confidence: 89%

A novel strategy to uncover specific GO terms/phosphorylation pathways in phosphoproteomic data in Arabidopsis thaliana

et al. 2021

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Background Proteins are the workforce of the cell and their phosphorylation status tailors specific responses efficiently. One of the main challenges of phosphoproteomic approaches is to deconvolute biological processes that specifically respond to an experimental query from a list of phosphoproteins. Comparison of the frequency distribution of GO (Gene Ontology) terms in a given phosphoproteome set with that observed in the genome reference set (GenRS) is the most widely used tool to infer biological significance. Yet, this comparison assumes that GO term distribution between the phosphoproteome and the genome are identical. However, this hypothesis has not been tested due to the lack of a comprehensive phosphoproteome database. Results In this study, we test this hypothesis by constructing three phosphoproteome databases in Arabidopsis thaliana: one based in experimental data (ExpRS), another based in in silico phosphorylation protein prediction (PredRS) and a third that is the union of both (UnRS). Our results show that the three phosphoproteome reference sets show default enrichment of several GO terms compared to GenRS, indicating that GO term distribution in the phosphoproteomes does not match that of the genome. Moreover, these differences overshadow the identification of GO terms that are specifically enriched in a particular condition. To overcome this limitation, we present an additional comparison of the sample of interest with UnRS to uncover GO terms specifically enriched in a particular phosphoproteome experiment. Using this strategy, we found that mRNA splicing and cytoplasmic microtubule compounds are important processes specifically enriched in the phosphoproteome of dark-grown Arabidopsis seedlings. Conclusions This study provides a novel strategy to uncover GO specific terms in phosphoproteome data of Arabidopsis that could be applied to any other organism. We also highlight the importance of specific phosphorylation pathways that take place during dark-grown Arabidopsis development.

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Section: Resultssupporting

confidence: 89%

A novel strategy to uncover specific GO terms/phosphorylation pathways in phosphoproteomic data in Arabidopsis thaliana

et al. 2021

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“…We identi ed 933 unique phosphoproteins in phosphopeptide enriched samples from 5-days-old dark-grown seedlings that contain 2,884 phosphosites (Additional File 1: Table S3). These results are similar in number of phosphoproteins and phosphopeptides to other phosphoproteomic experiments [18] [19].…”

Section: And Additionalsupporting

confidence: 90%

A Novel Strategy to Uncover Specific Go Terms/phosphorylation Pathways in Phosphoproteomic Data in Arabidopsis Thaliana

Arico

Beati

Wengier

et al. 2021

Preprint

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Background. Proteins are the workforce of the cell and their phosphorylation status tailors specific responses efficiently. One of the main challenges of phosphoproteomic approaches is to deconvolute biological processes that specifically respond to an experimental query from a list of phosphoproteins. Comparison of the frequency distribution of GO (Gene Ontology) terms in a given phosphoproteome set with that observed in the genome reference set (GenRS) is the most widely used tool to infer biological significance. Yet, this comparison assumes that GO term distribution between the phosphoproteome and the genome are identical. However, this hypothesis has not been tested due to the lack of a comprehensive phosphoproteome database.Results. In this study, we test this hypothesis by constructing three phosphoproteome databases in Arabidopsis thaliana: one based in experimental data (ExpRS), another based in in silico phosphorylation protein prediction (PredRS) and a third that is the union of both (UnRS). Our results show that the three phosphoproteome reference sets show default enrichment of several GO terms compared to GenRS, indicating that GO term distribution in the phosphoproteomes does not match that of the genome. Moreover, these differences overshadow the identification of GO terms that are specifically enriched in a particular condition. To overcome this limitation, we present an additional comparison of the sample of interest with UnRS to uncover GO terms specifically enriched in a particular phosphoproteome experiment. Using this strategy, we found that mRNA splicing and cytoplasmic microtubule compounds are important processes specifically enriched in the phosphoproteome of dark-grown Arabidopsis seedlings. Conclusions. This study provides a novel strategy to uncover GO specific terms in phosphoproteome data of Arabidopsis that could be applied to any other organism. We also highlight the importance of specific phosphorylation pathways that take place during dark-grown Arabidopsis development.

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“…With the development of techniques such as mass spectrometry and gene sequencing technology, the ability to quantitatively detect phosphorylation events in the process of IR-induced DNA damage repair can provide new insight for the identification of signaling kinase substrates and molecular mechanisms. Phosphoproteomics has been used not only to identify the targets of DNA damage signaling kinases in mammalian cell lines but also to identify phosphorylation events catalyzed by DNA damage signaling kinases [417][418][419] . Looking ahead, given the large datasets arising from mass spectrometry and high-throughput gene sequencing, statistical analysis methods must be developed for more efficient prediction and analysis.…”

Section: Challenges For Ir-induced Signal Transduction and Targeted Therapymentioning

confidence: 99%

DNA damage response signaling pathways and targets for radiotherapy sensitization in cancer

Huang

Zhou

2020

Sig Transduct Target Ther

539

457

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Radiotherapy is one of the most common countermeasures for treating a wide range of tumors. However, the radioresistance of cancer cells is still a major limitation for radiotherapy applications. Efforts are continuously ongoing to explore sensitizing targets and develop radiosensitizers for improving the outcomes of radiotherapy. DNA double-strand breaks are the most lethal lesions induced by ionizing radiation and can trigger a series of cellular DNA damage responses (DDRs), including those helping cells recover from radiation injuries, such as the activation of DNA damage sensing and early transduction pathways, cell cycle arrest, and DNA repair. Obviously, these protective DDRs confer tumor radioresistance. Targeting DDR signaling pathways has become an attractive strategy for overcoming tumor radioresistance, and some important advances and breakthroughs have already been achieved in recent years. On the basis of comprehensively reviewing the DDR signal pathways, we provide an update on the novel and promising druggable targets emerging from DDR pathways that can be exploited for radiosensitization. We further discuss recent advances identified from preclinical studies, current clinical trials, and clinical application of chemical inhibitors targeting key DDR proteins, including DNA-PKcs (DNA-dependent protein kinase, catalytic subunit), ATM/ATR (ataxia-telangiectasia mutated and Rad3-related), the MRN (MRE11-RAD50-NBS1) complex, the PARP (poly[ADP-ribose] polymerase) family, MDC1, Wee1, LIG4 (ligase IV), CDK1, BRCA1 (BRCA1 C terminal), CHK1, and HIF-1 (hypoxia-inducible factor-1). Challenges for ionizing radiation-induced signal transduction and targeted therapy are also discussed based on recent achievements in the biological field of radiotherapy.

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Phosphoproteomic analysis reveals plant DNA damage signalling pathways with a functional role for histone H2AX phosphorylation in plant growth under genotoxic stress

Cited by 39 publications

References 70 publications

A novel strategy to uncover specific GO terms/phosphorylation pathways in phosphoproteomic data in Arabidopsis thaliana

A novel strategy to uncover specific GO terms/phosphorylation pathways in phosphoproteomic data in Arabidopsis thaliana

A Novel Strategy to Uncover Specific Go Terms/phosphorylation Pathways in Phosphoproteomic Data in Arabidopsis Thaliana

DNA damage response signaling pathways and targets for radiotherapy sensitization in cancer

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