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      Global Transcriptome Profile of Cryptococcus neoformans during Exposure to Hydrogen Peroxide Induced Oxidative Stress

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          Abstract

          The ability of the opportunistic fungal pathogen Cryptococcus neoformans to resist oxidative stress is one of its most important virulence related traits. To cope with the deleterious effect of cellular damage caused by the oxidative burst inside the macrophages, C. neoformans has developed multilayered redundant molecular responses to neutralize the stress, to repair the damage and to eventually grow inside the hostile environment of the phagosome. We used microarray analysis of cells treated with hydrogen peroxide (H 2O 2) at multiple time points in a nutrient defined medium to identify a transcriptional signature associated with oxidative stress. We discovered that the composition of the medium in which fungal cells were grown and treated had a profound effect on their capacity to degrade exogenous H 2O 2. We determined the kinetics of H 2O 2 breakdown by growing yeast cells under different conditions and accordingly selected an appropriate media composition and range of time points for isolating RNA for hybridization. Microarray analysis revealed a robust transient transcriptional response and the intensity of the global response was consistent with the kinetics of H 2O 2 breakdown by treated cells. Gene ontology analysis of differentially expressed genes related to oxidation-reduction, metabolic process and protein catabolic processes identified potential roles of mitochondrial function and protein ubiquitination in oxidative stress resistance. Interestingly, the metabolic pathway adaptation of C. neoformans to H 2O 2 treatment was remarkably distinct from the response of other fungal organisms to oxidative stress. We also identified the induction of an antifungal drug resistance response upon the treatment of C. neoformans with H 2O 2. These results highlight the complexity of the oxidative stress response and offer possible new avenues for improving our understanding of mechanisms of oxidative stress resistance in C. neoformans.

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          Most cited references77

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          Genomic expression programs in the response of yeast cells to environmental changes.

          We explored genomic expression patterns in the yeast Saccharomyces cerevisiae responding to diverse environmental transitions. DNA microarrays were used to measure changes in transcript levels over time for almost every yeast gene, as cells responded to temperature shocks, hydrogen peroxide, the superoxide-generating drug menadione, the sulfhydryl-oxidizing agent diamide, the disulfide-reducing agent dithiothreitol, hyper- and hypo-osmotic shock, amino acid starvation, nitrogen source depletion, and progression into stationary phase. A large set of genes (approximately 900) showed a similar drastic response to almost all of these environmental changes. Additional features of the genomic responses were specialized for specific conditions. Promoter analysis and subsequent characterization of the responses of mutant strains implicated the transcription factors Yap1p, as well as Msn2p and Msn4p, in mediating specific features of the transcriptional response, while the identification of novel sequence elements provided clues to novel regulators. Physiological themes in the genomic responses to specific environmental stresses provided insights into the effects of those stresses on the cell.
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            Analysis of variance for gene expression microarray data.

            Spotted cDNA microarrays are emerging as a powerful and cost-effective tool for large-scale analysis of gene expression. Microarrays can be used to measure the relative quantities of specific mRNAs in two or more tissue samples for thousands of genes simultaneously. While the power of this technology has been recognized, many open questions remain about appropriate analysis of microarray data. One question is how to make valid estimates of the relative expression for genes that are not biased by ancillary sources of variation. Recognizing that there is inherent "noise" in microarray data, how does one estimate the error variation associated with an estimated change in expression, i.e., how does one construct the error bars? We demonstrate that ANOVA methods can be used to normalize microarray data and provide estimates of changes in gene expression that are corrected for potential confounding effects. This approach establishes a framework for the general analysis and interpretation of microarray data.
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              Global transcriptional responses of fission yeast to environmental stress.

              We explored transcriptional responses of the fission yeast Schizosaccharomyces pombe to various environmental stresses. DNA microarrays were used to characterize changes in expression profiles of all known and predicted genes in response to five stress conditions: oxidative stress caused by hydrogen peroxide, heavy metal stress caused by cadmium, heat shock caused by temperature increase to 39 degrees C, osmotic stress caused by sorbitol, and DNA damage caused by the alkylating agent methylmethane sulfonate. We define a core environmental stress response (CESR) common to all, or most, stresses. There was a substantial overlap between CESR genes of fission yeast and the genes of budding yeast that are stereotypically regulated during stress. CESR genes were controlled primarily by the stress-activated mitogen-activated protein kinase Sty1p and the transcription factor Atf1p. S. pombe also activated gene expression programs more specialized for a given stress or a subset of stresses. In general, these "stress-specific" responses were less dependent on the Sty1p mitogen-activated protein kinase pathway and may involve specific regulatory factors. Promoter motifs associated with some of the groups of coregulated genes were identified. We compare and contrast global regulation of stress genes in fission and budding yeasts and discuss evolutionary implications.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                28 January 2013
                : 8
                : 1
                : e55110
                Affiliations
                [1 ]Department of Molecular Microbiology, Washington University School of Medicine, Saint Louis, Missouri, United States of America
                [2 ]Edward A. Doisy Department of Biochemistry and Molecular Biology, Saint Louis University School of Medicine, Saint Louis, Missouri, United States of America
                [3 ]Department of Molecular Microbiology and Immunology, Saint Louis University School of Medicine, Saint Louis, Missouri, United States of America
                Stony Brook University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: RU LTC MJD RA JKL. Performed the experiments: RU LTC. Analyzed the data: MJD RA RU. Wrote the paper: RU MJD JKL.

                [¤]

                Current address: School of Molecular Bioscience, University of Sydney, Sydney, New South Wales, Australia

                Article
                PONE-D-12-34578
                10.1371/journal.pone.0055110
                3557267
                23383070
                b3c1d1cc-fe55-4f33-9837-199d0f913d65
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 5 November 2012
                : 18 December 2012
                Page count
                Pages: 15
                Funding
                This work was funded by NIH NIAID R01AI050184 and NIH NHLBI R01HL088905 grants to JKL. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Computational Biology
                Genomics
                Genome Analysis Tools
                Transcriptomes
                Genomics
                Genome Analysis Tools
                Transcriptomes
                Microbiology
                Mycology
                Fungal Biochemistry
                Fungal Physiology
                Model Organisms
                Yeast and Fungal Models
                Molecular Cell Biology
                Cellular Stress Responses
                Medicine
                Infectious Diseases
                Fungal Diseases

                Uncategorized
                Uncategorized

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