Literature DB >> 18424442

Comprehensive transcriptional analysis of the oxidative response in yeast.

María Micaela Molina-Navarro1, Laia Castells-Roca, Gemma Bellí, José García-Martínez, Julia Marín-Navarro, Joaquín Moreno, José E Pérez-Ortín, Enrique Herrero.   

Abstract

The oxidative stress response in Saccharomyces cerevisiae has been analyzed by parallel determination of mRNA levels and transcription rates for the entire genome. A mathematical algorithm has been adapted for a dynamic situation such as the response to stress, to calculate theoretical mRNA decay rates from the experimental data. Yeast genes have been grouped into 25 clusters according to mRNA level and transcription rate kinetics, and average mRNA decay rates have been calculated for each cluster. In most of the genes, changes in one or both experimentally determined parameters occur during the stress response. 24% of the genes are transcriptionally induced without an increase in mRNA levels. The lack of parallelism between the evolution of the mRNA amount and transcription rate predicts changes in mRNA stability during stress. Genes for ribosomal proteins and rRNA processing enzymes are abundant among those whose mRNAs are predicted to destabilize. The number of genes whose mRNAs are predicted to stabilize is lower, although some protein folding or proteasomal genes are among the latter. We have confirmed the mathematical predictions for several genes pertaining to different clusters by experimentally determining mRNA decay rates using the regulatable tetO promoter in transcriptional expression conditions not affected by the oxidative stress. This study indicates that the oxidative stress response in yeast cells is not only conditioned by gene transcription but also by the mRNA decay dynamics and that this complex response may be particularly relevant to explain the temporary down-regulation of protein synthesis occurring during stress.

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Year:  2008        PMID: 18424442     DOI: 10.1074/jbc.M800295200

Source DB:  PubMed          Journal:  J Biol Chem        ISSN: 0021-9258            Impact factor:   5.157


  35 in total

1.  The relative importance of transcription rate, cryptic transcription and mRNA stability on shaping stress responses in yeast.

Authors:  José García-Martínez; Guillermo Ayala; Vicent Pelechano; Sebastián Chávez; Enrique Herrero; José E Pérez-Ortín
Journal:  Transcription       Date:  2012 Jan-Feb

2.  Frataxin depletion in yeast triggers up-regulation of iron transport systems before affecting iron-sulfur enzyme activities.

Authors:  Armando Moreno-Cermeño; Elia Obis; Gemma Bellí; Elisa Cabiscol; Joaquim Ros; Jordi Tamarit
Journal:  J Biol Chem       Date:  2010-10-18       Impact factor: 5.157

3.  Cellular stress induces cytoplasmic RNA granules in fission yeast.

Authors:  Daniel Nilsson; Per Sunnerhagen
Journal:  RNA       Date:  2010-11-22       Impact factor: 4.942

4.  mRNA stability changes precede changes in steady-state mRNA amounts during hyperosmotic stress.

Authors:  Claes Molin; Alexandra Jauhiainen; Jonas Warringer; Olle Nerman; Per Sunnerhagen
Journal:  RNA       Date:  2009-02-17       Impact factor: 4.942

Review 5.  The importance of controlling mRNA turnover during cell proliferation.

Authors:  Sebastián Chávez; José García-Martínez; Lidia Delgado-Ramos; José E Pérez-Ortín
Journal:  Curr Genet       Date:  2016-03-23       Impact factor: 3.886

6.  Comparing transcription rate and mRNA abundance as parameters for biochemical pathway and network analysis.

Authors:  Brewster Hayles; Sailu Yellaboina; Degeng Wang
Journal:  PLoS One       Date:  2010-03-26       Impact factor: 3.240

7.  A genomic approach highlights common and diverse effects and determinants of susceptibility on the yeast Saccharomyces cerevisiae exposed to distinct antimicrobial peptides.

Authors:  Belén López-García; Mónica Gandía; Alberto Muñoz; Lourdes Carmona; Jose F Marcos
Journal:  BMC Microbiol       Date:  2010-11-15       Impact factor: 3.605

8.  A complete set of nascent transcription rates for yeast genes.

Authors:  Vicent Pelechano; Sebastián Chávez; José E Pérez-Ortín
Journal:  PLoS One       Date:  2010-11-16       Impact factor: 3.240

9.  Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses.

Authors:  Gonzalo Guillén-Gosálbez; Albert Sorribas
Journal:  BMC Bioinformatics       Date:  2009-11-24       Impact factor: 3.169

10.  Dissection of a complex transcriptional response using genome-wide transcriptional modelling.

Authors:  Martino Barenco; Daniel Brewer; Efterpi Papouli; Daniela Tomescu; Robin Callard; Jaroslav Stark; Michael Hubank
Journal:  Mol Syst Biol       Date:  2009-11-17       Impact factor: 11.429

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