Yeast toxicogenomics: genome-wide responses to chemical stresses with impact in environmental health, pharmacology, and biotechnology

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.

Keywords: genome-wide approaches; molecular systems biology; predictive toxicology; response to stress; toxicity mechanisms; toxicogenomics; yeast model.

Figure 1

Predicted contribution of Omics approaches applied in the yeast Saccharomyces cerevisiae to obtain toxicological mechanistic insights with application in environmental health, agriculture, drug development, and biotechnology.

Figure 2

Construction and screening of yeast collections. Schematic representation of methodologies and cell libraries available for chemogenomics testing in S. cerevisiae (homozygous or haploid deletion – gene dosage 0%, heterozygous deletion – gene dosage 50%, and overexpression – gene dosage > 100%; see Section “Functional Toxicogenomics using Yeast Gene Deletion Collections”; Auerbach et al., ; Hoon et al., ; Wuster and Madan Babu, ; North and Vulpe, ; Smith et al., 2010). The fitness of strains upon chemical treatment is usually assessed in non-competitive arrays or in competitive bar-coded pools. In the first case, the toxicant can be added to a well plate and each mutant occupies a separate well; the effects are observed directly by comparison with wild-type strain fitness. In the second case, the screen is executed in a pooled format where uniquely tagged (“bar-coded”) strains are grown together in the presence of a toxicant. Fitness is assessed by determining the abundance of the different mutant strains using microarrays coupled with a PCR strategy that amplifies the molecular bar-codes associated with each mutant. Strain depletion in the toxicant-treated pool indicates chemical hypersensitivity.

Figure 3

Proposed model for the action of mancozeb in S. cerevisiae cells. This model results from the integration of yeast chemogenomics (Dias et al., 2010) and proteomics (Santos et al., 2009) approaches. The complex mancozeb-induced expression changes and mancozeb determinants of yeast resistance, were found to be related to oxidative stress, V-ATPase function, protein translation initiation and protein folding, disassembling of protein aggregates and degradation of damaged proteins, lipid and ergosterol biosynthesis, mitochondrial function, cell wall remodeling, and multidrug resistance transporters.

Figure 4

Proposed model for the action of (A) quinine and (B) imatinib in S. cerevisiae cells. These models result from the integration of chemogenomics, transcriptomics and proteomics approaches (dos Santos and Sá-Correia, ; dos Santos et al., ; dos Santos and Sá-Correia, ; dos Santos and Sá-Correia, unpublished results), suggesting new targets and modes of action for quinine and imatinib that possess extensive functional conservation in the organisms of interest, Plasmodium falciparum, and human cells, respectively. The most important results are the identification of PfHT1 as a potential target of quinine, as well as the vacuolar H⁺-ATPase (V-ATPase) as a target of imatinib (see Genome-wide Responses and Determinants of Resistance to Antimalarial Drugs and Genome-wide Responses and Determinants of Resistance to Anticancer Drugs).