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      Yeast Toxicogenomics: Genome-Wide Responses to Chemical Stresses with Impact in Environmental Health, Pharmacology, and Biotechnology

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          Abstract

          The emerging transdisciplinary field of Toxicogenomics aims to study the cell response to a given toxicant at the genome, transcriptome, proteome, and metabolome levels. This approach is expected to provide earlier and more sensitive biomarkers of toxicological responses and help in the delineation of regulatory risk assessment. The use of model organisms to gather such genomic information, through the exploitation of Omics and Bioinformatics approaches and tools, together with more focused molecular and cellular biology studies are rapidly increasing our understanding and providing an integrative view on how cells interact with their environment. The use of the model eukaryote Saccharomyces cerevisiae in the field of Toxicogenomics is discussed in this review. Despite the limitations intrinsic to the use of such a simple single cell experimental model, S. cerevisiae appears to be very useful as a first screening tool, limiting the use of animal models. Moreover, it is also one of the most interesting systems to obtain a truly global understanding of the toxicological response and resistance mechanisms, being in the frontline of systems biology research and developments. The impact of the knowledge gathered in the yeast model, through the use of Toxicogenomics approaches, is highlighted here by its use in prediction of toxicological outcomes of exposure to pesticides and pharmaceutical drugs, but also by its impact in biotechnology, namely in the development of more robust crops and in the improvement of yeast strains as cell factories.

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          Most cited references162

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          The genetic landscape of a cell.

          A genome-scale genetic interaction map was constructed by examining 5.4 million gene-gene pairs for synthetic genetic interactions, generating quantitative genetic interaction profiles for approximately 75% of all genes in the budding yeast, Saccharomyces cerevisiae. A network based on genetic interaction profiles reveals a functional map of the cell in which genes of similar biological processes cluster together in coherent subsets, and highly correlated profiles delineate specific pathways to define gene function. The global network identifies functional cross-connections between all bioprocesses, mapping a cellular wiring diagram of pleiotropy. Genetic interaction degree correlated with a number of different gene attributes, which may be informative about genetic network hubs in other organisms. We also demonstrate that extensive and unbiased mapping of the genetic landscape provides a key for interpretation of chemical-genetic interactions and drug target identification.
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            Functional discovery via a compendium of expression profiles.

            Ascertaining the impact of uncharacterized perturbations on the cell is a fundamental problem in biology. Here, we describe how a single assay can be used to monitor hundreds of different cellular functions simultaneously. We constructed a reference database or "compendium" of expression profiles corresponding to 300 diverse mutations and chemical treatments in S. cerevisiae, and we show that the cellular pathways affected can be determined by pattern matching, even among very subtle profiles. The utility of this approach is validated by examining profiles caused by deletions of uncharacterized genes: we identify and experimentally confirm that eight uncharacterized open reading frames encode proteins required for sterol metabolism, cell wall function, mitochondrial respiration, or protein synthesis. We also show that the compendium can be used to characterize pharmacological perturbations by identifying a novel target of the commonly used drug dyclonine.
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              Metabonomics: a platform for studying drug toxicity and gene function.

              The later that a molecule or molecular class is lost from the drug development pipeline, the higher the financial cost. Minimizing attrition is therefore one of the most important aims of a pharmaceutical discovery programme. Novel technologies that increase the probability of making the right choice early save resources, and promote safety, efficacy and profitability. Metabonomics is a systems approach for studying in vivo metabolic profiles, which promises to provide information on drug toxicity, disease processes and gene function at several stages in the discovery-and-development process.
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                Author and article information

                Journal
                Front Genet
                Front Genet
                Front. Gene.
                Frontiers in Genetics
                Frontiers Research Foundation
                1664-8021
                09 March 2012
                19 April 2012
                2012
                : 3
                : 63
                Affiliations
                [1] 1simpleInstitute for Biotechnology and Bioengineering, Centre for Biological and Chemical Engineering, Instituto Superior Técnico, Technical University of Lisbon Lisbon, Portugal
                [2] 2simpleDepartment of Bioengineering, Instituto Superior Técnico, Technical University of Lisbon Lisbon, Portugal
                Author notes

                Edited by: Stephen Sturzenbaum, King’s College London, UK

                Reviewed by: Ralph Menzel, Humboldt-Universität zu Berlin, Germany; Barry Panaretou, King’s College London, UK

                *Correspondence: Isabel Sá-Correia, Institute for Biotechnology and Bioengineering, Centre for Biological and Chemical Engineering, Department of Bioengineering, Instituto Superior Técnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal. e-mail: isacorreia@ 123456ist.utl.pt

                This article was submitted to Frontiers in Toxicogenomics, a specialty of Frontiers in Genetics.

                Article
                10.3389/fgene.2012.00063
                3329712
                22529852
                1fb201f7-92be-43ed-9f8e-9483b4ef5707
                Copyright © 2012 dos Santos, Teixeira, Cabrito and Sá-Correia.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non Commercial License, which permits non-commercial use, distribution, and reproduction in other forums, provided the original authors and source are credited.

                History
                : 16 February 2012
                : 03 April 2012
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 176, Pages: 17, Words: 15368
                Categories
                Genetics
                Review Article

                Genetics
                yeast model,molecular systems biology,toxicogenomics,predictive toxicology,toxicity mechanisms,genome-wide approaches,response to stress

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