Dihydropyrimidinase protects from DNA replication stress caused by cytotoxic metabolites.

Basbous, Jihane; Aze, Antoine; Chaloin, Laurent; Lebdy, Rana; Hodroj, Dana; Ribeyre, Cyril; Larroque, Marion; Shepard, Caitlin; Kim, Baek; Pruvost, Alain; Moreaux, Jérôme; Maiorano, Domenico; Méchali, Marcel; Constantinou, Angelos

doi:10.1101/420893

Cited by 4 publications

(5 citation statements)

References 73 publications

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“…Subsequent base-or nucleotide excision repair can lead to direct or indirect release of these dihydropyrimidines in cells (Venkhataraman et al 2001). Studies on cancer cells and on in vitro DNA replication in Xenopus egg extracts showed that dihydropyrimidines cause DNA-protein crosslinking, interfere with DNA replication and cause transcriptional stress (Basbous et al 2020). In mammalian cells, the zinc metalloprotein dihydropyrimidinase plays a key role in dihydropyrimidine detoxification (Brooks et al 1979;Kikugawa et al 1994).…”

Section: Discussionmentioning

confidence: 99%

Identification of fungal dihydrouracil-oxidase genes by expression in Saccharomyces cerevisiae

Bouwknegt

Vos

Ortiz‐Merino

et al. 2022

Antonie van Leeuwenhoek

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Analysis of predicted fungal proteomes revealed a large family of sequences that showed similarity to the Saccharomyces cerevisiae Class-I dihydroorotate dehydrogenase Ura1, which supports synthesis of pyrimidines under aerobic and anaerobic conditions. However, expression of codon-optimised representatives of this gene family, from the ascomycete Alternaria alternata and the basidiomycete Schizophyllum commune, only supported growth of an S. cerevisiae ura1Δ mutant when synthetic media were supplemented with dihydrouracil. A hypothesis that these genes encode NAD(P)+-dependent dihydrouracil dehydrogenases (EC 1.3.1.1 or 1.3.1.2) was rejected based on absence of complementation in anaerobic cultures. Uracil- and thymine-dependent oxygen consumption and hydrogen-peroxide production by cell extracts of S. cerevisiae strains expressing the A. alternata and S. commune genes showed that, instead, they encode active dihydrouracil oxidases (DHO, EC1.3.3.7). DHO catalyses the reaction dihydrouracil + O2 → uracil + H2O2 and was only reported in the yeast Rhodotorula glutinis (Owaki in J Ferment Technol 64:205–210, 1986). No structural gene for DHO was previously identified. DHO-expressing strains were highly sensitive to 5-fluorodihydrouracil (5F-dhu) and plasmids bearing expression cassettes for DHO were readily lost during growth on 5F-dhu-containing media. These results show the potential applicability of fungal DHO genes as counter-selectable marker genes for genetic modification of S. cerevisiae and other organisms that lack a native DHO. Further research should explore the physiological significance of this enigmatic and apparently widespread fungal enzyme.

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Section: Discussionmentioning

confidence: 99%

Identification of fungal dihydrouracil-oxidase genes by expression in Saccharomyces cerevisiae

Bouwknegt

Vos

Ortiz‐Merino

et al. 2022

Antonie van Leeuwenhoek

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“…DPYS (also known as DHP) is a zinc metalloenzyme, which is highly expressed in tumors compared with the matching normal tissues, whose role is to degrade dihydropyrimidine [27]. Excessive accumulation of dihydropyrimidine will facilitate the constitution of DNA-protein crosslinks, leading to DNA replication and transcriptional stress [27]. Studies have shown that DPYS subtype DPYSL3 was a promising biomarker for GC malignant behavior [28].…”

Section: Discussionmentioning

confidence: 99%

“…Overexpression of NT5E can promote tumor proliferation, migration and invasion [25,26]. DPYS (also known as DHP) is a zinc metalloenzyme, which is highly expressed in tumors compared with the matching normal tissues, whose role is to degrade dihydropyrimidine [27]. Excessive accumulation of dihydropyrimidine will facilitate the constitution of DNA-protein crosslinks, leading to DNA replication and transcriptional stress [27].…”

Section: Discussionmentioning

confidence: 99%

Identification of Crucial Genes of Pyrimidine Metabolism as Biomarkers for Gastric Cancer Prognosis

Tan

Zhuang

et al. 2021

Preprint

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Background Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. Methods Here, we employed DEG analysis to detect the differentially expressed genes (DEGs) in pyrimidine metabolic signaling pathway and used univariate Cox analysis, Lasso-penalizes Cox regression analysis, Kaplan-Meier survival analysis, univariate and multivariate Cox regression analysis to explore their prognostic roles in GC. The DEGs were experimentally validated in GC cells and clinical samples by quantitative real-time PCR. Results Through DEG analysis, we found NT5E, DPYS and UPP1 these three genes are highly expressed in GC. This conclusion has also been verified in GC cells and clinical samples. A prognostic risk model was established according to these three DEGs by Univariate Cox analysis and Lasso-penalizes Cox regression analysis. Kaplan-Meier survival analysis suggested that patient cohorts with high risk score undertook a lower overall survival rate than those with low risk score. Stratified survival analysis, Univariate and multivariate Cox regression analysis of this model confirmed that it is a reliable and independent clinical factor. Therefore, we made nomograms to visually depict the survival rate of GC patients according to some important clinical factors including our risk model. Conclusion In a word, our research found that pyrimidine metabolism is dysregulated in GC and established a prognostic model of GC based on genes differentially expressed in pyrimidine metabolism.

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“…In vitro spectroscopic studies have identified the strikingly high level of the thymine breakdown through the DHT pathway, leading to e.g. breast and lung adenocarcinomas [86][87][88][89]. Thus, it appears as tempting in Fig.…”

Section: Reconstructed Spectramentioning

confidence: 99%

In vitro proton magnetic resonance spectroscopy at 14T for benign and malignant ovary: Part I, signal processing by the nonparametric fast Padé transform

Belkić

2021

J Math Chem

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The present study deals with two different kinds of time signals, encoded by in vitro proton magnetic resonance spectroscopy (MRS) with a high external static magnetic field, 14.1T (Bruker 600 MHz spectrometer). These time signals originate from the specific biofluid samples taken from two patients, one with benign and the other with malignant ovarian cysts. The latter two diagnoses have been made by histopathologic analyses of the samples. Histopathology is the diagnostic gold standard in medicine. The obtained results from signal processing by the nonparametric derivative fast Padé transform (dFPT) show that a number of resonances assignable to known metabolites are considerably more intense in the malignant than in the benign specimens. Such conclusions from the dFPT include the recognized cancer biomarkers, lactic acid and choline-containing compounds. For example, the peak height ratio for the malignant-to-benign samples is about 18 for lactate, Lac. This applies equally to doublet Lac(d) and quartet Lac(q) resonating near 1.41 and 4.36 ppm (parts per million), respectively. For the choline-containing conglomerate (3.19-3.23 ppm), the dFPT with already low-derivative orders (2nd, 3rd) succeeds in clearly separating the three singlet component resonances, free choline Cho(s), phosphocholine PC(s) and glycerophosphocholine GPC(s). These constituents of total choline, tCho, are of critical diagnostic relevance because the increased levels, particularly of PC(s) and GPC(s), are an indicator of a malignant transformation. It is gratifying that signal processing by the dFPT, as a shape estimator, coheres with the mentioned histopathology findings of the two samples. A very large number of resonances is identifiable and quantifiable by the nonparametric dFPT, including those associated with the diagnostically most important low molecular weight metabolites. This is expediently feasible by the automated sequential visualization and quantification that separate and isolate sharp resonances first and subsequently tackle broad macromolecular lineshape profiles. Such a stepwise workflow is not based on subtracting nor annulling any part of the spectrum, in sharp contrast to controversial customary practice in the MRS literature. Rather, sequential estimation exploits the chief derivative feature, which is a faster peak height increase of the thin than of the wide resonances. This is how the dFPT simultaneously improves resolution (linewidth narrowing) and reduces noise (background flattening). Such a twofold achievement makes the dFPT-based proton MRS a high throughput strategy in tumor diagnostics as hundreds of metabolites can be visualized/quantified to offer the opportunity for a possible expansion of the existing list of a handful of cancer biomarkers.

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Dihydropyrimidinase protects from DNA replication stress caused by cytotoxic metabolites.

Cited by 4 publications

References 73 publications

Identification of fungal dihydrouracil-oxidase genes by expression in Saccharomyces cerevisiae

Identification of fungal dihydrouracil-oxidase genes by expression in Saccharomyces cerevisiae

Identification of Crucial Genes of Pyrimidine Metabolism as Biomarkers for Gastric Cancer Prognosis

In vitro proton magnetic resonance spectroscopy at 14T for benign and malignant ovary: Part I, signal processing by the nonparametric fast Padé transform

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