ABSTRACT Ribonucleotide reductases (RNRs) transform RNA building blocks to DNA building blocks by catalyzing the substitution of the 2'OH-group of a ribonucleotide with a hydrogen by a mechanism involving protein radicals. Three classes of RNRs employ different mechanisms for the generation of the protein radical. Recent structural studies of members from each class have led to a deeper understanding of their catalytic mechanism and allosteric regulation by nucleoside triphosphates. The main emphasis of this review is on regulation of RNR at the molecular and cellular level. Conformational transitions induced by nucleotide binding determine the regulation of substrate specificity. An intricate interplay between gene activation, enzyme inhibition, and protein degradation regulates, together with the allosteric effects, enzyme activity and provides the appropriate amount of deoxynucleotides for DNA replication and repair. In spite of large differences in the amino acid sequences, basic structural features are remarkably similar and suggest a common evolutionary origin for the three classes.
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ABSTRACT: Replication stress induced by nucleotide deficiency plays an important role in cancer initiation. Replication stress in primary cells typically activates the cellular senescence tumor-suppression mechanism. Senescence bypass correlates with development of cancer, a disease characterized by metabolic reprogramming. However, the role of metabolic reprogramming in the cellular response to replication stress has been little explored. Here, we report that ataxia telangiectasia mutated (ATM) plays a central role in regulating the cellular response to replication stress by shifting cellular metabolism. ATM inactivation bypasses senescence induced by replication stress triggered by nucleotide deficiency. This was due to restoration of deoxyribonucleotide triphosphate (dNTP) levels through both upregulation of the pentose phosphate pathway via increased glucose-6-phosphate dehydrogenase (G6PD) activity and enhanced glucose and glutamine consumption. These phenotypes were mediated by a coordinated suppression of p53 and upregulation of c-MYC downstream of ATM inactivation. Our data indicate that ATM status couples replication stress and metabolic reprogramming during senescence. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.Cell Reports 04/2015; 11(6). DOI:10.1016/j.celrep.2015.04.014 · 7.21 Impact Factor
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ABSTRACT: The discovery of abundant viruses in the oceans and on land has ushered in a quarter century of groundbreaking advancements in our understanding of viruses within ecosystems. Two types of observations from environmental samples - direct counts of viral particles and viral metagenomic sequences - have been critical to these discoveries. Accurate direct counts have established ecosystem-scale trends in the impacts of viral infection on microbial host populations and have shown that viral communities within aquatic and soil environments respond to both short term and seasonal environmental change. Direct counts have been critical for estimating viral production rate, a measurement essential to quantifying the implications of viral infection for the biogeochemical cycling of nutrients within ecosystems. While direct counts have defined the magnitude of viral processes; shotgun sequences of environmental viral DNA - virome sequences - have enabled researchers to estimate the diversity and composition of natural viral communities. Virome-enabled studies have found the virioplankton to contain thousands of viral genotypes in communities where the most dominant viral population accounts for a small fraction of total abundance followed by a long tail of diverse populations. Detailed examination of long virome sequences has led to new understanding of genotype-to-phenotype connections within marine viruses and revealed that viruses carry metabolic genes that are important to maintaining cellular energy during viral replication. Increased access to long virome sequences will undoubtedly reveal more genetic secrets of viruses and enable us to build a genomics rulebook for predicting key biological and ecological features of unknown viruses.The Journal of Microbiology 03/2015; 53(3):181-92. DOI:10.1007/s12275-015-5068-6 · 1.53 Impact Factor
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ABSTRACT: The highly conserved molecular chaperones Hsp90 and Hsp70 are indispensible for folding and maturation of a significant fraction of the proteome, including many proteins involved in signal transduction and stress response. To examine the dynamics of chaperone-client interactions after DNA damage, we applied quantitative affinity-purification mass spectrometry (AP-MS) proteomics to characterize interactomes of the yeast Hsp70 isoform Ssa1 and Hsp90 isoform Hsp82 before and after exposure to methyl methanesulfonate. Of 256 proteins identified and quantified via (16)O(/18)O labeling and LC-MS/MS, 142 are novel Hsp70/90 interactors. Nearly all interactions remained unchanged or decreased after DNA damage, but 5 proteins increased interactions with Ssa1 and/or Hsp82, including the ribonucleotide reductase (RNR) subunit Rnr4. Inhibiting Hsp70 or 90 chaperone activity destabilized Rnr4 in yeast and its vertebrate homolog hRMM2 in breast cancer cells. In turn, pre-treatment of cancer cells with chaperone inhibitors sensitized cells to the RNR inhibitor gemcitabine, suggesting a novel chemotherapy strategy. All MS data have been deposited in the ProteomeXchange with identifier PXD001284. This study provides the dynamic interactome of the yeast Hsp70 and Hsp90 under DNA damage which suggest key roles for the chaperones in a variety of signaling cascades. Importantly, the cancer drug target ribonucleotide reductase was shown to be a client of Hsp70 and Hsp90 in both yeast and breast cancer cells. As such, this study highlights the potential of a novel cancer therapeutic strategy that exploits the synergy of chaperone and ribonucleotide reductase inhibitors. Copyright © 2014 Elsevier B.V. All rights reserved.Journal of Proteomics 10/2014; 112C:285-300. DOI:10.1016/j.jprot.2014.09.028 · 3.93 Impact Factor