Yeast Rpn4 Links the Proteasome and DNA Repair via RAD52 Regulation

Environmental and intracellular factors often damage DNA, but multiple DNA repair pathways maintain genome integrity. In yeast, the 26S proteasome and its transcriptional regulator and substrate Rpn4 are involved in DNA damage resistance. Paradoxically, while proteasome dysfunction may induce hyper-resistance to DNA-damaging agents, Rpn4 malfunction sensitizes yeasts to these agents. Previously, we proposed that proteasome inhibition causes Rpn4 stabilization followed by the upregulation of Rpn4-dependent DNA repair genes and pathways. Here, we aimed to elucidate the key Rpn4 targets responsible for DNA damage hyper-resistance in proteasome mutants. We impaired the Rpn4-mediated regulation of candidate genes using the CRISPR/Cas9 system and tested the sensitivity of mutant strains to 4-NQO, MMS and zeocin. We found that the separate or simultaneous deregulation of 19S or 20S proteasome subcomplexes induced MAG1, DDI1, RAD23 and RAD52 in an Rpn4-dependent manner. Deregulation of RAD23, DDI1 and RAD52 sensitized yeast to DNA damage. Genetic, epigenetic or dihydrocoumarin-mediated RAD52 repression restored the sensitivity of the proteasome mutants to DNA damage. Our results suggest that the Rpn4-mediated overexpression of DNA repair genes, especially RAD52, defines the DNA damage hyper-resistant phenotype of proteasome mutants. The developed yeast model is useful for characterizing drugs that reverse the DNA damage hyper-resistance phenotypes of cancers.

Rpn4 and proteasome-mediated yeast resistance to ethanol includes regulation of autophagy

Distilled spirits production using Saccharomyces cerevisiae requires understanding of the mechanisms of yeast cell response to alcohol stress. Reportedly, specific mutations in genes of the ubiquitin-proteasome system, e.g., RPN4, may result in strains exhibiting hyper-resistance to different alcohols. To study the Rpn4-dependent yeast response to short-term ethanol exposure, we performed a comparative analysis of the wild-type (WT) strain, strain with RPN4 gene deletion (rpn4-Δ), and a mutant strain with decreased proteasome activity and consequent Rpn4 accumulation due to PRE1 deregulation (YPL). The stress resistance tests demonstrated an increased sensitivity of mutant strains to ethanol compared with WT. Comparative proteomics analysis revealed significant differences in molecular responses to ethanol between these strains. GO analysis of proteins upregulated in WT showed enrichments represented by oxidative and heat responses, protein folding/unfolding, and protein degradation. Enrichment of at least one of these responses was not observed in the mutant strains. Moreover, activity of autophagy was not increased in the RPN4 deletion strain upon ethanol stress which agrees with changes in mRNA levels of ATG7 and PRB1 genes of the autophagy system. Activity of the autophagic system was clearly induced and accompanied with PRB1 overexpression in the YPL strain upon ethanol stress. We demonstrated that Rpn4 stabilization contributes to the PRB1 upregulation. CRISPR-Cas9-mediated repression of PACE-core Rpn4 binding sites in the PRB1 promoter inhibits PRB1 induction in the YPL strain upon ethanol treatment and results in YPL hypersensitivity to ethanol. Our data suggest that Rpn4 affects the autophagic system activity upon ethanol stress through the PRB1 regulation. These findings can be a basis for creating genetically modified yeast strains resistant to high levels of alcohol, being further used for fermentation in ethanol production.

The ability of transcription factors to differentially regulate gene expression is a crucial component of the mechanism underlying inversion, a frequently observed genetic interaction pattern

Genetic interactions, a phenomenon whereby combinations of mutations lead to unexpected effects, reflect how cellular processes are wired and play an important role in complex genetic diseases. Understanding the molecular basis of genetic interactions is crucial for deciphering pathway organization as well as understanding the relationship between genetic variation and disease. Several hypothetical molecular mechanisms have been linked to different genetic interaction types. However, differences in genetic interaction patterns and their underlying mechanisms have not yet been compared systematically between different functional gene classes. Here, differences in the occurrence and types of genetic interactions are compared for two classes, gene-specific transcription factors (GSTFs) and signaling genes (kinases and phosphatases). Genome-wide gene expression data for 63 single and double deletion mutants in baker's yeast reveals that the two most common genetic interaction patterns are buffering and inversion. Buffering is typically associated with redundancy and is well understood. In inversion, genes show opposite behavior in the double mutant compared to the corresponding single mutants. The underlying mechanism is poorly understood. Although both classes show buffering and inversion patterns, the prevalence of inversion is much stronger in GSTFs. To decipher potential mechanisms, a Petri Net modeling approach was employed, where genes are represented as nodes and relationships between genes as edges. This allowed over 9 million possible three and four node models to be exhaustively enumerated. The models show that a quantitative difference in interaction strength is a strict requirement for obtaining inversion. In addition, this difference is frequently accompanied with a second gene that shows buffering. Taken together, these results provide a mechanistic explanation for inversion. Furthermore, the ability of transcription factors to differentially regulate expression of their targets provides a likely explanation why inversion is more prevalent for GSTFs compared to kinases and phosphatases.

ChiNet uncovers rewired transcription subnetworks in tolerant yeast for advanced biofuels conversion

Analysis of rewired upstream subnetworks impacting downstream differential gene expression aids the delineation of evolving molecular mechanisms. Cumulative statistics based on conventional differential correlation are limited for subnetwork rewiring analysis since rewiring is not necessarily equivalent to change in correlation coefficients. Here we present a computational method ChiNet to quantify subnetwork rewiring by statistical heterogeneity that enables detection of potential genotype changes causing altered transcription regulation in evolving organisms. Given a differentially expressed downstream gene set, ChiNet backtracks a rewired upstream subnetwork from a super-network including gene interactions known to occur under various molecular contexts. We benchmarked ChiNet for its high accuracy in distinguishing rewired artificial subnetworks, in silico yeast transcription-metabolic subnetworks, and rewired transcription subnetworks for Candida albicans versus Saccharomyces cerevisiae, against two differential-correlation based subnetwork rewiring approaches. Then, using transcriptome data from tolerant S. cerevisiae strain NRRL Y-50049 and a wild-type intolerant strain, ChiNet identified 44 metabolic pathways affected by rewired transcription subnetworks anchored to major adaptively activated transcription factor genes YAP1, RPN4, SFP1 and ROX1, in response to toxic chemical challenges involved in lignocellulose-to-biofuels conversion. These findings support the use of ChiNet in rewiring analysis of subnetworks where differential interaction patterns resulting from divergent nonlinear dynamics abound.

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.