2019
DOI: 10.1038/s41467-019-12640-5
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Abstract: Accumulation of DNA lesions causing transcription stress is associated with natural and accelerated aging and culminates with profound metabolic alterations. Our understanding of the mechanisms governing metabolic redesign upon genomic instability, however, is highly rudimentary. Using Ercc1-defective mice and Xpg knock-out mice, we demonstrate that combined defects in transcription-coupled DNA repair (TCR) and in nucleotide excision repair (NER) directly affect bioenergetics due to declined transcription, lea… Show more

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Cited by 43 publications
(36 citation statements)
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References 79 publications
(100 reference statements)
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“…Here, we described a mechanism connecting transcription stalling caused by defective DNA repair with augmented intracellular ATP levels, which in turn allosterically inhibit the glycolytic enzyme ATP-dependent 6-phosphofructokinase (Pfk, best known as phosphofructokinase) to reroute glucose through the pentose phosphate pathway (PPP). Potentiation of the PPP is intrinsically associated with increased production of NADPH reducing equivalentswhich are generated in the oxidative branch of the pathwaythat in our experimental system is not paralleled by proportionate production of oxidant species and/or endogenous oxidoreductase activity, and therefore culminates in reductive stress 1 (Figure 1A).…”
mentioning
confidence: 87%
“…Here, we described a mechanism connecting transcription stalling caused by defective DNA repair with augmented intracellular ATP levels, which in turn allosterically inhibit the glycolytic enzyme ATP-dependent 6-phosphofructokinase (Pfk, best known as phosphofructokinase) to reroute glucose through the pentose phosphate pathway (PPP). Potentiation of the PPP is intrinsically associated with increased production of NADPH reducing equivalentswhich are generated in the oxidative branch of the pathwaythat in our experimental system is not paralleled by proportionate production of oxidant species and/or endogenous oxidoreductase activity, and therefore culminates in reductive stress 1 (Figure 1A).…”
mentioning
confidence: 87%
“…Energy Production. In order to facilitate DNA synthesis and repair, the cell requires large ATP pools 52 , and there were several lines of evidence to support ATP generation in HHQ exposed cells. First, an increased relative transcript abundance of enzymes in the tricarboxylic acid (TCA) cycle (i.e., isocitrate dehydrogenase, α-ketoglutarate dehydrogenase, succinate dehydrogenase, fumarase, and malate dehydrogenase) ( Fig.…”
Section: Hhqmentioning
confidence: 99%
“…Given the close relationship between physiological and/or pharmacological external cues and the impact on the systemic metabolic profile, this experimental approach has been extensively used in nutrition, 72,73 agricultural, 74,75 dairy, 76,77 toxicology, 78,79 preclinical, and clinical studies. In life sciences, targeted metabolomics has been mainly employed for the characterization of known metabolites and pathways (i.e., amino acids, glycolysis, Krebs cycle, and pentose phosphate pathway) in in vitro, ex vivo, and in vivo experimental settings 6,80–90 . On the other hand, untargeted metabolomics is mainly used for the identification of biomarkers in biomedical research, for instance, in pathophysiology (i.e., cancer, 91 neurodegenerative diseases, 92,93 and metabolic disorders 94 ) or epidemiology studies 95,96 .…”
Section: Main Applications Of Steady‐state Metabolomicsmentioning
confidence: 99%
“…In life sciences, targeted metabolomics has been mainly employed for the characterization of known metabolites and pathways (i.e., amino acids, glycolysis, Krebs cycle, and pentose phosphate pathway) in in vitro, ex vivo, and in vivo experimental settings. 6,[80][81][82][83][84][85][86][87][88][89][90] On the other hand, untargeted metabolomics is mainly used for the identification of biomarkers in biomedical research, for instance, in pathophysiology (i.e., cancer, 91 neurodegenerative diseases, 92,93 and metabolic disorders 94 ) or epidemiology studies. 95,96 Studies aimed to identify biomarkers can be divided into two main categories.…”
Section: Main Applications Of Steady-state Metabolomicsmentioning
confidence: 99%