Activity of the pleiotropic drug resistance transcription factors Pdr1p and Pdr3p is modulated by binding site flanking sequences

The transcription factors Pdr1p and Pdr3p regulate pleiotropic drug resistance (PDR) in Saccharomyces cerevisiae via the PDR responsive elements (PDREs) to modulate gene expression. However, the exact mechanisms underlying the differences in their regulons remain unclear. Employing genomic occupancy profiling (CUT&RUN), binding assays, and transcription studies, we characterized the differences in sequence specificity between transcription factors. Findings reveal distinct preferences for core PDRE sequences and the flanking sequences for both proteins. While flanking sequences moderately alter DNA binding affinity, they significantly impact Pdr1/3p transcriptional activity. Notably, both proteins demonstrated the ability to bind half sites, showing potential enhancement of transcription from adjacent PDREs. This insight sheds light on ways Pdr1/3p can differentially regulate PDR.

Unraveling the Half and Full Site Sequence Specificity of the Saccharomyces cerevisiae Pdr1p and Pdr3p Transcription Factors

The transcription factors Pdr1p and Pdr3p regulate pleotropic drug resistance (PDR) in Saccharomyces cerevisiae , via the PDR responsive elements (PDREs) to modulate gene expression. However, the exact mechanisms underlying the differences in their regulons remain unclear. Employing genomic occupancy profiling (CUT&RUN), binding assays, and transcription studies, we characterized the differences in sequence specificity between transcription factors. Findings reveal distinct preferences for core PDRE sequences and the flanking sequences for both proteins. While flanking sequences moderately alter DNA binding affinity, they significantly impact Pdr1/3p transcriptional activity. Notably, both proteins demonstrated the ability to bind half sites, showing potential enhancement of transcription from adjacent PDREs. This insight sheds light on ways Pdr1/3 can differentially regulate PDR.

Sequence-specific dynamics of DNA response elements and their flanking sites regulate the recognition by AP-1 transcription factors

Activator proteins 1 (AP-1) comprise one of the largest families of eukaryotic basic leucine zipper transcription factors. Despite advances in the characterization of AP-1 DNA-binding sites, our ability to predict new binding sites and explain how the proteins achieve different gene expression levels remains limited. Here we address the role of sequence-specific DNA flexibility for stability and specific binding of AP-1 factors, using microsecond-long molecular dynamics simulations. As a model system, we employ yeast AP-1 factor Yap1 binding to three different response elements from two genetic environments. Our data show that Yap1 actively exploits the sequence-specific flexibility of DNA within the response element to form stable protein–DNA complexes. The stability also depends on the four to six flanking nucleotides, adjacent to the response elements. The flanking sequences modulate the conformational adaptability of the response element, making it more shape-efficient to form specific contacts with the protein. Bioinformatics analysis of differential expression of the studied genes supports our conclusions: the stability of Yap1–DNA complexes, modulated by the flanking environment, influences the gene expression levels. Our results provide new insights into mechanisms of protein–DNA recognition and the biological regulation of gene expression levels in eukaryotes.

Assessing regulatory features of the current transcriptional network of Saccharomyces cerevisiae

The capacity of living cells to adapt to different environmental, sometimes adverse, conditions is achieved through differential gene expression, which in turn is controlled by a highly complex transcriptional network. We recovered the full network of transcriptional regulatory associations currently known for Saccharomyces cerevisiae, as gathered in the latest release of the YEASTRACT database. We assessed topological features of this network filtered by the kind of supporting evidence and of previously published networks. It appears that in-degree distribution, as well as motif enrichment evolve as the yeast transcriptional network is being completed. Overall, our analyses challenged some results previously published and confirmed others. These analyses further pointed towards the paucity of experimental evidence to support theories and, more generally, towards the partial knowledge of the complete network.

Candida glabrata Transcription Factor Rpn4 Mediates Fluconazole Resistance through Regulation of Ergosterol Biosynthesis and Plasma Membrane Permeability

The ability to acquire azole resistance is an emblematic trait of the fungal pathogen Candida glabrata Understanding the molecular basis of azole resistance in this pathogen is crucial for designing more suitable therapeutic strategies. This study shows that the C. glabrata transcription factor (TF) CgRpn4 is a determinant of azole drug resistance. RNA sequencing during fluconazole exposure revealed that CgRpn4 regulates the expression of 212 genes, activating 80 genes and repressing, likely in an indirect fashion, 132 genes. Targets comprise several proteasome and ergosterol biosynthesis genes, including ERG1, ERG2, ERG3, and ERG11 The localization of CgRpn4 to the nucleus increases upon fluconazole stress. Consistent with a role in ergosterol and plasma membrane homeostasis, CgRpn4 is required for the maintenance of ergosterol levels upon fluconazole stress, which is associated with a role in the upkeep of cell permeability and decreased intracellular fluconazole accumulation. We provide evidence that CgRpn4 directly regulates ERG11 expression through the TTGCAAA binding motif, reinforcing the relevance of this regulatory network in azole resistance. In summary, CgRpn4 is a new regulator of the ergosterol biosynthesis pathway in C. glabrata, contributing to plasma membrane homeostasis and, thus, decreasing azole drug accumulation.

Membrane Proteomics Analysis of the Candida glabrata Response to 5-Flucytosine: Unveiling the Role and Regulation of the Drug Efflux Transporters CgFlr1 and CgFlr2

Resistance to 5-flucytosine (5-FC), used as an antifungal drug in combination therapy, compromises its therapeutic action. In this work, the response of the human pathogen Candida glabrata to 5-FC was evaluated at the membrane proteome level, using an iTRAQ-based approach. A total of 32 proteins were found to display significant expression changes in the membrane fraction of cells upon exposure to 5-FC, 50% of which under the control of CgPdr1, the major regulator of azole drug resistance. These proteins cluster into functional groups associated to cell wall assembly, lipid metabolism, amino acid/nucleotide metabolism, ribosome components and translation machinery, mitochondrial function, glucose metabolism, and multidrug resistance transport. Given the obtained indications, the function of the drug:H+ antiporters CgFlr1 (ORF CAGL0H06017g) and CgFlr2 (ORF CAGL0H06039g) was evaluated. The expression of both proteins, localized to the plasma membrane, was found to confer flucytosine resistance. CgFlr2 further confers azole drug resistance. The deletion of CgFLR1 or CgFLR2 was seen to increase the intracellular accumulation of 5-FC, or 5-FC and clotrimazole, suggesting that these transporters play direct roles in drug extrusion. The expression of CgFLR1 and CgFLR2 was found to be controlled by the transcription factors CgPdr1 and CgYap1, major regulator of oxidative stress resistance.

Insight into the Kluyveromyces lactis Pdr1p regulon

The overexpression of efflux pumps is an important mechanism leading to the development of multidrug resistance phenomenon. The transcription factor KlPdr1p, belonging to the Zn₂Cys₆ family, is a central regulator of efflux pump expression in Kluyveromyces lactis. To better understand how KlPDR1-mediated drug resistance is achieved in K. lactis, we used DNA microarrays to identify genes whose expression was affected by deletion or overexpression of the KlPDR1 gene. Eighty-nine targets of the KlPDR1 were identified. From those the transcription of 16 genes was induced in the transformant overexpressing KlPDR1* and simultaneously repressed in the Klpdr1Δ deletion mutant. Almost all of these genes contain putative binding motifs for the AP-1-like transcription factors in their promoters. Furthermore, we studied the possible interplay between KlPdr1p and KlYap1p transcription factors. Our results show that KlYap1p does not significantly contribute to the regulation of KlPDR1 gene expression in the presence of azoles. However, KlPDR1 expression markedly increased in the presence of hydrogen peroxide and hinged upon the presence of KlYap1p. Our results show that although both KlPdr1p and KlYap1p transcription factors are involved in the control of K. lactis multidrug resistance, further studies will be needed to determine their interplay.

MFS multidrug transporters in pathogenic fungi: do they have real clinical impact?

Infections caused by opportunistic fungal pathogens have reached concerning numbers due to the increase of the immunocrompromised human population and to the development of antifungal resistance. This resistance is often attributed to the action of multidrug efflux pumps, belonging to the ATP-binding cassette (ABC) superfamily and the major facilitator superfamily (MFS). Although many studies have focused on the role of ABC multidrug efflux transporters, little is still known on the part played by the Drug:H⁺ Antiporter (DHA) family of the MFS in this context. This review summarizes current knowledge on the role in antifungal drug resistance, mode of action and phylogenetic relations of DHA transporters, from the model yeast S. cerevisiae to pathogenic yeasts and filamentous fungi. Through the compilation of the predicted DHA transporters in the medically relevant Candida albicans, C. glabrata, C. parapsilosis, C. lusitaniae, C. tropicalis, C. guilliermondii, Cryptococcus neoformans, and Aspergillus fumigatus species, the fact that only 5% of the DHA transporters from these organisms have been characterized so far is evidenced. The role of these transporters in antifungal drug resistance and in pathogen-host interaction is described and their clinical relevance discussed. Given the knowledge gathered for these few DHA transporters, the need to carry out a systematic characterization of the DHA multidrug efflux pumps in fungal pathogens, with emphasis on their clinical relevance, is highlighted.

MFS transporters required for multidrug/multixenobiotic (MD/MX) resistance in the model yeast: understanding their physiological function through post-genomic approaches

Multidrug/Multixenobiotic resistance (MDR/MXR) is a widespread phenomenon with clinical, agricultural and biotechnological implications, where MDR/MXR transporters that are presumably able to catalyze the efflux of multiple cytotoxic compounds play a key role in the acquisition of resistance. However, although these proteins have been traditionally considered drug exporters, the physiological function of MDR/MXR transporters and the exact mechanism of their involvement in resistance to cytotoxic compounds are still open to debate. In fact, the wide range of structurally and functionally unrelated substrates that these transporters are presumably able to export has puzzled researchers for years. The discussion has now shifted toward the possibility of at least some MDR/MXR transporters exerting their effect as the result of a natural physiological role in the cell, rather than through the direct export of cytotoxic compounds, while the hypothesis that MDR/MXR transporters may have evolved in nature for other purposes than conferring chemoprotection has been gaining momentum in recent years. This review focuses on the drug transporters of the Major Facilitator Superfamily (MFS; drug:H⁺ antiporters) in the model yeast Saccharomyces cerevisiae. New insights into the natural roles of these transporters are described and discussed, focusing on the knowledge obtained or suggested by post-genomic research. The new information reviewed here provides clues into the unexpectedly complex roles of these transporters, including a proposed indirect regulation of the stress response machinery and control of membrane potential and/or internal pH, with a special emphasis on a genome-wide view of the regulation and evolution of MDR/MXR-MFS transporters.

Candida glabrata drug:H+ antiporter CgQdr2 confers imidazole drug resistance, being activated by transcription factor CgPdr1

The widespread emergence of antifungal drug resistance poses a severe clinical problem. Though predicted to play a role in this phenomenon, the drug:H(+) antiporters (DHA) of the major facilitator superfamily have largely escaped characterization in pathogenic yeasts. This work describes the first DHA from the pathogenic yeast Candida glabrata reported to be involved in antifungal drug resistance, the C. glabrata QDR2 (CgQDR2) gene (ORF CAGL0G08624g). The expression of CgQDR2 in C. glabrata was found to confer resistance to the antifungal drugs miconazole, tioconazole, clotrimazole, and ketoconazole. By use of a green fluorescent protein (GFP) fusion, the CgQdr2 protein was found to be targeted to the plasma membrane in C. glabrata. In agreement with these observations, CgQDR2 expression was found to decrease the intracellular accumulation of radiolabeled clotrimazole in C. glabrata and to play a role in the extrusion of this antifungal from preloaded cells. Interestingly, the functional heterologous expression of CgQDR2 in the model yeast Saccharomyces cerevisiae further confirmed the role of this gene as a multidrug resistance determinant: its expression was able to complement the susceptibility phenotype exhibited by its S. cerevisiae homologue, QDR2, in the presence of imidazoles and of the antimalarial and antiarrhythmic drug quinidine. In contrast to the findings reported for Qdr2, CgQdr2 expression does not contribute to the ability of yeast to grow under K(+)-limiting conditions. Interestingly, CgQDR2 transcript levels were seen to be upregulated in C. glabrata cells challenged with clotrimazole or quinidine. This upregulation was found to depend directly on the transcription factor CgPdr1, the major regulator of multidrug resistance in this pathogenic yeast, which has also been found to be a determinant of quinidine and clotrimazole resistance in C. glabrata.

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

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.

Characterization of complex regulatory networks and identification of promoter regulatory elements in yeast: "in silico" and "wet-lab" approaches

Transcription is the first step in the flow of biological information from genome to proteome and its tight regulation is a crucial checkpoint in most biological processes occurring in all living organisms. In eukaryotes, one of the most important mechanisms of transcriptional regulation relies on the activity of transcription factors which, upon binding to specific nucleotide motifs (consensus) present in the promoter region of target genes, modulate the activity of RNA polymerase II activating and/or repressing gene transcription. The identification of binding sites for these transcription factors is crucial to the understanding of transcriptional regulation at the molecular level and to the prediction of putative target genes for each transcription factor. However, transcription regulation cannot simply be reduced to transcription factor-gene associations. Frequently, the transcript level of a given gene is determined by a multitude of activators and/or repressors resulting in intertwined and complex regulatory networks. Two case studies dedicated to the study of transcriptional regulation in the experimental model Saccharomyces cerevisiae are presented in this chapter. The computational tools available in YEASTRACT information system are explored in both studies, to identify the regulatory elements that serve as functional DNA-binding sites for a transcription factor (Rim101p), and to characterize the regulatory network underlying the transcriptional regulation of a given yeast gene (FLR1). A set of easily accessible experimental approaches that can be used to confirm the predictions of the bioinformatic analysis is also detailed.

Qualitative modelling and formal verification of the FLR1 gene mancozeb response in Saccharomyces cerevisiae

BACKGROUND

Qualitative models allow understanding the relation between the structure and the dynamics of gene regulatory networks. The dynamical properties of these models can be automatically analysed by means of formal verification methods, like model checking. This facilitates the model-validation process and the test of new hypotheses to reconcile model predictions with the experimental data.

RESULTS

The authors report in this study the qualitative modelling and simulation of the transcriptional regulatory network controlling the response of the model eukaryote Saccharomyces cerevisiae to the agricultural fungicide mancozeb. The model allowed the analysis of the regulation level and activity of the components of the gene mancozeb-induced network controlling the transcriptional activation of the FLR1 gene, which is proposed to confer multidrug resistance through its putative role as a drug eflux pump. Formal verification analysis of the network allowed us to confront model predictions with the experimental data and to assess the model robustness to parameter ordering and gene deletion.

CONCLUSIONS

This analysis enabled us to better understand the mechanisms regulating the FLR1 gene mancozeb response and confirmed the need of a new transcription factor for the full transcriptional activation of YAP1. The result is a computable model of the FLR1 gene response to mancozeb, permitting a quick and cost-effective test of hypotheses prior to experimental validation.

QUANTITATIVE MODELING OF THE SACCHAROMYCES CEREVISIAE FLR1 REGULATORY NETWORK USING AN S-SYSTEM FORMALISM

In this study we address the problem of finding a quantitative mathematical model for the genetic network regulating the stress response of the yeast Saccharomyces cerevisiae to the agricultural fungicide mancozeb. An S-system formalism was used to model the interactions of a five-gene network encoding four transcription factors (Yap1, Yrr1, Rpn4 and Pdr3) regulating the transcriptional activation of the FLR1 gene. Parameter estimation was accomplished by decoupling the resulting system of nonlinear ordinary differential equations into a larger nonlinear algebraic system, and using the Levenberg–Marquardt algorithm to fit the models predictions to experimental data. The introduction of constraints in the model, related to the putative topology of the network, was explored. The results show that forcing the network connectivity to adhere to this topology did not lead to better results than the ones obtained using an unrestricted network topology. Overall, the modeling approach obtained partial success when trained on the nonmutant datasets, although further work is required if one wishes to obtain more accurate prediction of the time courses.

TFRank: network-based prioritization of regulatory associations underlying transcriptional responses

MOTIVATION

Uncovering mechanisms underlying gene expression control is crucial to understand complex cellular responses. Studies in gene regulation often aim to identify regulatory players involved in a biological process of interest, either transcription factors coregulating a set of target genes or genes eventually controlled by a set of regulators. These are frequently prioritized with respect to a context-specific relevance score. Current approaches rely on relevance measures accounting exclusively for direct transcription factor-target interactions, namely overrepresentation of binding sites or target ratios. Gene regulation has, however, intricate behavior with overlapping, indirect effect that should not be neglected. In addition, the rapid accumulation of regulatory data already enables the prediction of large-scale networks suitable for higher level exploration by methods based on graph theory. A paradigm shift is thus emerging, where isolated and constrained analyses will likely be replaced by whole-network, systemic-aware strategies.

RESULTS

We present TFRank, a graph-based framework to prioritize regulatory players involved in transcriptional responses within the regulatory network of an organism, whereby every regulatory path containing genes of interest is explored and incorporated into the analysis. TFRank selected important regulators of yeast adaptation to stress induced by quinine and acetic acid, which were missed by a direct effect approach. Notably, they reportedly confer resistance toward the chemicals. In a preliminary study in human, TFRank unveiled regulators involved in breast tumor growth and metastasis when applied to genes whose expression signatures correlated with short interval to metastasis.

Yeast response and tolerance to polyamine toxicity involving the drug : H+ antiporter Qdr3 and the transcription factors Yap1 and Gcn4

The yeast QDR3 gene encodes a plasma membrane drug : H(+) antiporter of the DHA1 family that was described as conferring resistance against the drugs quinidine, cisplatin and bleomycin and the herbicide barban, similar to its close homologue QDR2. In this work, a new physiological role for Qdr3 in polyamine homeostasis is proposed. QDR3 is shown to confer resistance to the polyamines spermine and spermidine, but, unlike Qdr2, also a determinant of resistance to polyamines, Qdr3 has no apparent role in K(+) homeostasis. QDR3 transcription is upregulated in yeast cells exposed to spermine or spermidine dependent on the transcription factors Gcn4, which controls amino acid homeostasis, and Yap1, the main regulator of oxidative stress response. Yap1 was found to be a major determinant of polyamine stress resistance in yeast and is accumulated in the nucleus of yeast cells exposed to spermidine-induced stress. QDR3 transcript levels were also found to increase under nitrogen or amino acid limitation; this regulation is also dependent on Gcn4. Consistent with the concept that Qdr3 plays a role in polyamine homeostasis, QDR3 expression was found to decrease the intracellular accumulation of [(3)H]spermidine, playing a role in the maintenance of the plasma membrane potential in spermidine-stressed cells.

YEASTRACT: providing a programmatic access to curated transcriptional regulatory associations in Saccharomyces cerevisiae through a web services interface

The YEAst Search for Transcriptional Regulators And Consensus Tracking (YEASTRACT) information system (http://www.yeastract.com) was developed to support the analysis of transcription regulatory associations in Saccharomyces cerevisiae. Last updated in June 2010, this database contains over 48 200 regulatory associations between transcription factors (TFs) and target genes, including 298 specific DNA-binding sites for 110 characterized TFs. All regulatory associations stored in the database were revisited and detailed information on the experimental evidences that sustain those associations was added and classified as direct or indirect evidences. The inclusion of this new data, gathered in response to the requests of YEASTRACT users, allows the user to restrict its queries to subsets of the data based on the existence or not of experimental evidences for the direct action of the TFs in the promoter region of their target genes. Another new feature of this release is the availability of all data through a machine readable web-service interface. Users are no longer restricted to the set of available queries made available through the existing web interface, and can use the web service interface to query, retrieve and exploit the YEASTRACT data using their own implementation of additional functionalities. The YEASTRACT information system is further complemented with several computational tools that facilitate the use of the curated data when answering a number of important biological questions. Since its first release in 2006, YEASTRACT has been extensively used by hundreds of researchers from all over the world. We expect that by making the new data and services available, the system will continue to be instrumental for yeast biologists and systems biology researchers.