A dominant suppressor mutation of the met30 cell cycle defect suggests regulation of the Saccharomyces cerevisiae Met4-Cbf1 transcription complex by Met32

Glutathione reductase plays a role in the metabolism of methylmercury degradation in Rhodotorula mucilaginosa

Mercury pollution is a kind of heavy metal pollution with great harm and strong toxicity which exists worldwide. Some microorganisms can convert highly toxic methylmercury into inorganic mercury compounds with significantly reduced toxicity. This is an effective means of methylmercury pollution remediation. As a safe microorganism with great potential in the remediation of heavy metal pollution, Rhodotorula mucilaginosa has not been studied in the remediation of methylmercury. Here, a R. mucilaginosa strain Rm4 with high methylmercury resistance was obtained by wild-strain screening. Its minimal inhibitory concentration and minimum lethal concentration reached 3 and 6 mg/L, respectively. At the same time, Rm4 can also degrade methylmercury. Unlike the traditional microbial methylmercury degradation pathways, R. mucilaginosa's genome does not encode the organomercury lyase gene MerB. However, transcriptomic analysis revealed that the glutathione reductase of R. mucilaginosa responds to the methylmercury degradation process. Structural domain analysis and molecular docking experiments suggest that the glutathione reductase of R. mucilaginosa has the potential to directly or indirectly participate in methylmercury degradation metabolism. Metabolic indicator tests of engineered strains overexpressing the glutathione reductase encoding gene also support this notion.

IMPORTANCE

The remediation of methylmercury pollution is crucial for environmental health. The ability of Rhodotorula mucilaginosa to resist and degrade methylmercury offers a new avenue for bioremediation efforts. Understanding the metabolic pathways involved, particularly the role of glutathione reductase, enhances our knowledge of how Rhodotorula mucilaginosa responds to methylmercury and opens up new possibilities for future research in bioremediation strategies.

Evidence for a hydrogen sulfide-sensing E3 ligase in yeast

In yeast, control of sulfur amino acid metabolism relies upon Met4, a transcription factor that activates the expression of a network of enzymes responsible for the biosynthesis of cysteine and methionine. In times of sulfur abundance, the activity of Met4 is repressed via ubiquitination by the SCFMet30 E3 ubiquitin ligase, but the mechanism by which the F-box protein Met30 senses sulfur status to tune its E3 ligase activity remains unresolved. Herein, we show that Met30 responds to flux through the trans-sulfuration pathway to regulate the MET gene transcriptional program. In particular, Met30 is responsive to the biological gas hydrogen sulfide, which is sufficient to induce ubiquitination of Met4 in vivo. Additionally, we identify important cysteine residues in Met30's WD-40 repeat region that sense the availability of sulfur in the cell. Our findings reveal how SCFMet30 dynamically senses the flow of sulfur metabolites through the trans-sulfuration pathway to regulate the synthesis of these special amino acids.

Overexpression of MET4 Leads to the Upregulation of Stress-Related Genes and Enhanced Sulfite Tolerance in Saccharomyces uvarum

Saccharomyces uvarum is one of the few fermentative species that can be used in winemaking, but its weak sulfite tolerance is the main reason for its further use. Previous studies have shown that the expression of the methionine synthase gene (MET4) is upregulated in FZF1 (a gene encoding a putative zinc finger protein, which is a positive regulator of the transcription of the cytosolic sulfotransferase gene SSU1) overexpression transformant strains, but its exact function is unknown. To gain insight into the function of the MET4 gene, in this study, a MET4 overexpression vector was constructed and transformed into S. uvarum strain A9. The MET4 transformants showed a 20 mM increase in sulfite tolerance compared to the starting strain. Ninety-two differential genes were found in the transcriptome of A9-MET4 compared to the A9 strain, of which 90 were upregulated, and two were downregulated. The results of RT-qPCR analyses confirmed that the expression of the HOMoserine requiring gene (HOM3) in the sulfate assimilation pathway and some fermentation-stress-related genes were upregulated in the transformants. The overexpression of the MET4 gene resulted in a significant increase in sulfite tolerance, the upregulation of fermentation-stress-related gene expression, and significant changes in the transcriptome profile of the S. uvarum strain.

Removal of sulfamethazine and Cu2+ by Sakaguchia cladiensis A5: Performance and transcriptome analysis

To reduce the potential risks of contamination of antibiotics and heavy metals to ecological environment and human safety, biological removal of these composite pollutants is the focus of much study. One previously identified isolate, Sakaguchia cladiensis A5, was used to decompose sulfamethazine (SMZ) and adsorb Cu²⁺. The ability of A5 to remove SMZ was enhanced by pre-induced culture, which reached 49.8% on day 9. The removal of SMZ could be also increased to 37.6% on day 3 in the presence of Cu²⁺, but only to 12.2% in the system without Cu²⁺. The biosorption of Cu²⁺ mainly occurred on the cell walls, while the biodegradation of SMZ was inside the cells. By comparative transcriptome analysis for A5, 1270 and 2220 differentially expressed genes (DEGs) were identified after treating single SMZ and SMZ/Cu²⁺, respectively. The Gene expression pattern analysis suggested a suppression of transcriptional changes in A5 responding to SMZ/Cu²⁺ as compared to under the sole stress of SMZ. The DEGs functional enrichment analysis suggested that the antioxidant and sulfate assimilation pathways played a key role on SMZ biodegradation and Cu²⁺ biosorption. The DEGs of proteins CAT, PRDX5, SAT, and CYSC were up-regulated to facilitate the resistance of A5 against oxidative toxicity of Cu²⁺. Moreover, the protein MET30 activated by Cu²⁺ was also overexpressed to promote the transmembrane transport of SMZ, such that A5 could decompose SMZ more effectively in SMZ/Cu²⁺ system. The results of this study would provide new insights into the mechanism of biodegradation and biosorption of SMZ/Cu²⁺.

Impairment of MET transcriptional activators, MET4 and MET31 induced lipid accumulation in Saccharomyces cerevisiae

The genes involved in the methionine pathway are closely associated with phospholipid homeostasis in yeast. The impact of the deletion of methionine (MET) transcriptional activators (MET31, MET32 and MET4) in lipid homeostasis is studied. Our lipid profiling data showed that aberrant phospholipid and neutral lipid accumulation occurred in met31∆ and met4∆ strains with low Met. The expression pattern of phospholipid biosynthetic genes such as CHO2, OPI3 and triacylglycerol (TAG) biosynthetic gene, DGA1 were upregulated in met31∆, and met4∆ strains when compared to wild type (WT). The accumulation of triacylglycerol and sterol esters (SE) content supports the concomitant increase in lipid droplets in met31∆ and met4∆ strains. However, excessive supplies of methionine (1 mM) in the cells lacking the MET transcriptional activators MET31 and MET4 ameliorates the abnormal lipogenesis and causes aberrant lipid accumulation. These findings implicate the methionine accessibility plays a pivotal role in lipid metabolism in the yeast model.

Methionine Dependence of Cancer

Tumorigenesis is accompanied by the reprogramming of cellular metabolism. The shift from oxidative phosphorylation to predominantly glycolytic pathways to support rapid growth is well known and is often referred to as the Warburg effect. However, other metabolic changes and acquired needs that distinguish cancer cells from normal cells have also been discovered. The dependence of cancer cells on exogenous methionine is one of them and is known as methionine dependence or the Hoffman effect. This phenomenon describes the inability of cancer cells to proliferate when methionine is replaced with its metabolic precursor, homocysteine, while proliferation of non-tumor cells is unaffected by these conditions. Surprisingly, cancer cells can readily synthesize methionine from homocysteine, so their dependency on exogenous methionine reflects a general need for altered metabolic flux through pathways linked to methionine. In this review, an overview of the field will be provided and recent discoveries will be discussed.

Cuminal Inhibits Trichothecium roseum Growth by Triggering Cell Starvation: Transcriptome and Proteome Analysis

Trichothecium roseum is a harmful postharvest fungus causing serious damage, together with the secretion of insidious mycotoxins, on apples, melons, and other important fruits. Cuminal, a predominant component of Cuminum cyminum essential oil has proven to successfully inhibit the growth of T. roseum in vitro and in vivo. Electron microscopic observations revealed cuminal exposure impaired the fungal morphology and ultrastructure, particularly the plasmalemma. Transcriptome and proteome analysis was used to investigate the responses of T. roseum to exposure of cuminal. In total, 2825 differentially expressed transcripts (1516 up and 1309 down) and 225 differentially expressed proteins (90 up and 135 down) were determined. Overall, notable parts of these differentially expressed genes functionally belong to subcellular localities of the membrane system and cytosol, along with ribosomes, mitochondria and peroxisomes. According to the localization analysis and the biological annotation of these genes, carbohydrate and lipids metabolism, redox homeostasis, and asexual reproduction were among the most enriched gene ontology (GO) terms. Biological pathway enrichment analysis showed that lipids and amino acid degradation, ATP-binding cassette transporters, membrane reconstitution, mRNA surveillance pathway and peroxisome were elevated, whereas secondary metabolite biosynthesis, cell cycle, and glycolysis/gluconeogenesis were down regulated. Further integrated omics analysis showed that cuminal exposure first impaired the polarity of the cytoplasmic membrane and then triggered the reconstitution and dysfunction of fungal plasmalemma, resulting in handicapped nutrient procurement of the cells. Consequently, fungal cells showed starvation stress with limited carbohydrate metabolism, resulting a metabolic shift to catabolism of the cell's own components in response to the stress. Additionally, these predicaments brought about oxidative stress, which, in collaboration with the starvation, damaged certain critical organelles such as mitochondria. Such degeneration, accompanied by energy deficiency, suppressed the biosynthesis of essential proteins and inhibited fungal growth.

A Comparative Study of Network Motifs in the Integrated Transcriptional Regulation and Protein Interaction Networks of Shewanella

The Shewanella species shows a remarkable respiratory versatility with a great variety of extracellular electron acceptors (termed Extracellular Electron Transfer, EET). To explore relevant mechanisms from the network motif view, we constructed the integrated networks that combined transcriptional regulation interactions (TRIs) and protein-protein interactions (PPIs) for 13 Shewanella species, identified and compared the network motifs in these integrated networks. We found that the network motifs were evolutionary conserved in these integrated networks. The functional significance of the highly conserved motifs was discussed, especially the important ones that were potentially involved in the Shewanella EET processes. More importantly, we found that: 1) the motif co-regulated PPI took a role in the "standby mode" of protein utilization, which will be helpful for cells to rapidly response to environmental changes; and 2) the type II cofactors, which involved in the motif TRI interacting with a third protein, mainly carried out a signalling role in Shewanella oneidensis MR-1.

YGMD: a repository for yeast cooperative transcription factor sets and their target gene modules

By organizing the genome into gene modules (GMs), a living cell coordinates the activities of a set of genes to properly respond to environmental changes. The transcriptional regulation of the expression of a GM is usually carried out by a cooperative transcription factor set (CoopTFS) consisting of several cooperative transcription factors (TFs). Therefore, a database which provides CoopTFSs and their target GMs is useful for studying the cellular responses to internal or external stimuli. To address this need, here we constructed YGMD (Yeast Gene Module Database) to provide 34120 CoopTFSs, each of which consists of two to five cooperative TFs, and their target GMs. The cooperativity between TFs in a CoopTFS is suggested by physical/genetic interaction evidence or/and predicted by existing algorithms. The target GM regulated by a CoopTFS is defined as the common target genes of all the TFs in that CoopTFS. The regulatory association between any TF in a CoopTFS and any gene in the target GM is supported by experimental evidence in the literature. In YGMD, users can (i) search the GM regulated by a specific CoopTFS of interest or (ii) search all possible CoopTFSs whose target GMs contain a specific gene of interest. The biological relevance of YGMD is shown by a case study which demonstrates that YGMD can provide a GM enriched with genes known to be regulated by the query CoopTFS (Cbf1-Met4-Met32). We believe that YGMD provides a valuable resource for yeast biologists to study the transcriptional regulation of GMs.

Database URL:http://cosbi4.ee.ncku.edu.tw/YGMD/, http://cosbi5.ee.ncku.edu.tw/YGMD/ or http://cosbi.ee.ncku.edu.tw/YGMD/

Functional Analysis of the FZF1 Genes of Saccharomyces uvarum

Being a sister species of Saccharomyces cerevisiae, Saccharomyces uvarum shows great potential regarding the future of the wine industry. The sulfite tolerance of most S. uvarum strains is poor, however. This is a major flaw that limits its utility in the wine industry. In S. cerevisiae, FZF1 plays a positive role in the transcription of SSU1, which encodes a sulfite efflux transport protein that is critical for sulfite tolerance. Although FZF1 has previously been shown to play a role in sulfite tolerance in S. uvarum, there is little information about its action mechanism. To assess the function of FZF1, two over-expression vectors that contained different FZF1 genes, and one FZF1 silencing vector, were constructed and introduced into a sulfite-tolerant S. uvarum strain using electroporation. In addition, an FZF1-deletion strain was constructed. Both of the FZF1-over-expressing strains showed an elevated tolerance to sulfite, and the FZF1-deletion strain showed the opposite effect. Repression of FZF1 transcription failed, however, presumably due to the lack of alleles of DCR1 and AGO. The qRT-PCR analysis was used to examine changes in transcription in the strains. Surprisingly, neither over-expressing strain promoted SSU1 transcription, although MET4 and HAL4 transcripts significantly increased in both sulfite-tolerance increased strains. We conclude that FZF1 plays a different role in the sulfite tolerance of S. uvarum compared to its role in S. cerevisiae.

Network-Based Methods for Identifying Key Active Proteins in the Extracellular Electron Transfer Process in Shewanella oneidensis MR-1

Shewanella oneidensis MR-1 can transfer electrons from the intracellular environment to the extracellular space of the cells to reduce the extracellular insoluble electron acceptors (Extracellular Electron Transfer, EET). Benefiting from this EET capability, Shewanella has been widely used in different areas, such as energy production, wastewater treatment, and bioremediation. Genome-wide proteomics data was used to determine the active proteins involved in activating the EET process. We identified 1012 proteins with decreased expression and 811 proteins with increased expression when the EET process changed from inactivation to activation. We then networked these proteins to construct the active protein networks, and identified the top 20 key active proteins by network centralization analysis, including metabolism- and energy-related proteins, signal and transcriptional regulatory proteins, translation-related proteins, and the EET-related proteins. We also constructed the integrated protein interaction and transcriptional regulatory networks for the active proteins, then found three exclusive active network motifs involved in activating the EET process-Bi-feedforward Loop, Regulatory Cascade with a Feedback, and Feedback with a Protein-Protein Interaction (PPI)-and identified the active proteins involved in these motifs. Both enrichment analysis and comparative analysis to the whole-genome data implicated the multiheme c-type cytochromes and multiple signal processing proteins involved in the process. Furthermore, the interactions of these motif-guided active proteins and the involved functional modules were discussed. Collectively, by using network-based methods, this work reported a proteome-wide search for the key active proteins that potentially activate the EET process.

Flexible model-based clustering of mixed binary and continuous data: application to genetic regulation and cancer

Clustering is used widely in ‘omics’ studies and is often tackled with standard methods, e.g. hierarchical clustering. However, the increasing need for integration of multiple data sets leads to a requirement for clustering methods applicable to mixed data types, where the straightforward application of standard methods is not necessarily the best approach. A particularly common problem involves clustering entities characterized by a mixture of binary data (e.g. presence/absence of mutations, binding, motifs and epigenetic marks) and continuous data (e.g. gene expression, protein abundance, metabolite levels). Here, we present a generic method based on a probabilistic model for clustering this type of data, and illustrate its application to genetic regulation and the clustering of cancer samples. We show that the resulting clusters lead to useful hypotheses: in the case of genetic regulation these concern regulation of groups of genes by specific sets of transcription factors and in the case of cancer samples combinations of gene mutations are related to patterns of gene expression. The clusters have potential mechanistic significance and in the latter case are significantly linked to survival. The method is available as a stand-alone software package (GNU General Public Licence) from http://github.com/BioToolsLeeds/FlexiCoClusteringPackage.git.

Comprehensive Analysis of the SUL1 Promoter of Saccharomyces cerevisiae

In the yeast Saccharomyces cerevisiae, beneficial mutations selected during sulfate-limited growth are typically amplifications of the SUL1 gene, which encodes the high-affinity sulfate transporter, resulting in fitness increases of >35% . Cis-regulatory mutations have not been observed at this locus; however, it is not clear whether this absence is due to a low mutation rate such that these mutations do not arise, or they arise but have limited fitness effects relative to those of amplification. To address this question directly, we assayed the fitness effects of nearly all possible point mutations in a 493-base segment of the gene's promoter through mutagenesis and selection. While most mutations were either neutral or detrimental during sulfate-limited growth, eight mutations increased fitness >5% and as much as 9.4%. Combinations of these beneficial mutations increased fitness only up to 11%. Thus, in the case of SUL1, promoter mutations could not induce a fitness increase similar to that of gene amplification. Using these data, we identified functionally important regions of the SUL1 promoter and analyzed three sites that correspond to potential binding sites for the transcription factors Met32 and Cbf1 Mutations that create new Met32- or Cbf1-binding sites also increased fitness. Some mutations in the untranslated region of the SUL1 transcript decreased fitness, likely due to the formation of inhibitory upstream open reading frames. Our methodology-saturation mutagenesis, chemostat selection, and DNA sequencing to track variants-should be a broadly applicable approach.

Identification of yeast cell cycle regulated genes based on genomic features

Background

Time-course microarray experiments have been widely used to identify cell cycle regulated genes. However, the method is not effective for lowly expressed genes and is sensitive to experimental conditions. To complement microarray experiments, we propose a computational method to predict cell cycle regulated genes based on their genomic features – transcription factor binding and motif profiles.

Results

Through integrating gene-expression data with ChIP-chip binding and putative binding sites of transcription factors, our method shows high accuracy in discriminating yeast cell cycle regulated genes from non-cell cycle regulated ones. We predict 211 novel cell cycle regulated genes. Our model rediscovers the main cell cycle transcription factors and provides new insights into the regulatory mechanisms. The model also reveals a regulatory circuit mediated by a number of key cell cycle regulators.

Conclusions

Our model suggests that the periodical pattern of cell cycle genes is largely coded in their promoter regions, which can be captured by motif and transcription factor binding data. Cell cycle is controlled by a relatively small number of master transcription factors. The concept of genomic feature based method can be readily extended to human cell cycle process and other transcriptionally regulated processes, such as tissue-specific expression.

Regulation of amino acid, nucleotide, and phosphate metabolism in Saccharomyces cerevisiae

Ever since the beginning of biochemical analysis, yeast has been a pioneering model for studying the regulation of eukaryotic metabolism. During the last three decades, the combination of powerful yeast genetics and genome-wide approaches has led to a more integrated view of metabolic regulation. Multiple layers of regulation, from suprapathway control to individual gene responses, have been discovered. Constitutive and dedicated systems that are critical in sensing of the intra- and extracellular environment have been identified, and there is a growing awareness of their involvement in the highly regulated intracellular compartmentalization of proteins and metabolites. This review focuses on recent developments in the field of amino acid, nucleotide, and phosphate metabolism and provides illustrative examples of how yeast cells combine a variety of mechanisms to achieve coordinated regulation of multiple metabolic pathways. Importantly, common schemes have emerged, which reveal mechanisms conserved among various pathways, such as those involved in metabolite sensing and transcriptional regulation by noncoding RNAs or by metabolic intermediates. Thanks to the remarkable sophistication offered by the yeast experimental system, a picture of the intimate connections between the metabolomic and the transcriptome is becoming clear.

Combinatorial control of diverse metabolic and physiological functions by transcriptional regulators of the yeast sulfur assimilation pathway

Methionine abundance affects diverse cellular functions, including cell division, redox homeostasis, survival under starvation, and oxidative stress response. Regulation of the methionine biosynthetic pathway involves three DNA-binding proteins-Met31p, Met32p, and Cbf1p. We hypothesized that there exists a "division of labor" among these proteins that facilitates coordination of methionine biosynthesis with diverse biological processes. To explore combinatorial control in this regulatory circuit, we deleted CBF1, MET31, and MET32 individually and in combination in a strain lacking methionine synthase. We followed genome-wide gene expression as these strains were starved for methionine. Using a combination of bioinformatic methods, we found that these regulators control genes involved in biological processes downstream of sulfur assimilation; many of these processes had not previously been documented as methionine dependent. We also found that the different factors have overlapping but distinct functions. In particular, Met31p and Met32p are important in regulating methionine metabolism, whereas p functions as a "generalist" transcription factor that is not specific to methionine metabolism. In addition, Met31p and Met32p appear to regulate iron-sulfur cluster biogenesis through direct and indirect mechanisms and have distinguishable target specificities. Finally, CBF1 deletion sometimes has the opposite effect on gene expression from MET31 and MET32 deletion.

Characterizing the roles of Met31 and Met32 in coordinating Met4-activated transcription in the absence of Met30

To examine how target gene expression is coordinated among members of a transcription factor family, a simple two-member family (Met31 and Met32) that is essential for regulating sulfur metabolism in budding yeast is examined using both transcriptional and genome-wide binding arrays.

Yeast sulfur metabolism is transcriptionally regulated by the activator Met4. Met4 lacks DNA-binding ability and relies on interactions with Met31 and Met32, paralogous proteins that bind the same cis-regulatory element, to activate its targets. Although Met31 and Met32 are redundant for growth in the absence of methionine, studies indicate that Met32 has a prominent role over Met31 when Met30, a negative regulator of Met4 and Met32, is inactive. To characterize different roles of Met31 and Met32 in coordinating Met4-activated transcription, we examined transcription in strains lacking either Met31 or Met32 upon Met4 induction in the absence of Met30. Microarray analysis revealed that transcripts involved in sulfate assimilation and sulfonate metabolism were dramatically decreased in met32Δ cells compared to its wild-type and met31Δ counterparts. Despite this difference, both met31Δ and met32Δ cells used inorganic sulfur compounds and sulfonates as sole sulfur sources in minimal media when Met30 was present. This discrepancy may be explained by differential binding of Met31 to Cbf1-dependent promoters between these two conditions. In the absence of Met30, genome-wide chromatin immunoprecipitation analyses found that Met32 bound all Met4-bound targets, supporting Met32 as the main platform for Met4 recruitment. Finally, Met31 and Met32 levels were differentially regulated, with Met32 levels mimicking the profile for active Met4. These different properties of Met32 likely contribute to its prominent role in Met4-activated transcription when Met30 is absent.

A transcriptional activator is part of an SCF ubiquitin ligase to control degradation of its cofactors

Multisubunit protein complexes pose a challenge to the coordinated regulation of individual components. We show how the yeast transactivating factor Met4 functions as a component of the SCF(Met30) ubiquitin ligase to synchronize its own activity with cofactor assembly. Cells maintain Met4 in a dormant state by a regulatory ubiquitin chain assembled by SCF(Met30). Nutritional and heavy-metal stress block Met4 ubiquitylation resulting in Met4 activation, which induces a stress-response program including cell-cycle arrest. Met4 relies on assembly with various cofactors for promoter binding. We report here that the stability of these DNA-binding cofactors is regulated by SCF(Met30). Remarkably, the transcriptional activator Met4 functions as a substrate-specificity factor in the context of SCF(Met30/Met4) to coordinate cofactor degradation with its own activity status. Our results establish an additional layer for substrate recruitment by SCF ubiquitin ligases and provide conceptual insight into coordinated regulation of protein complexes.

Novel mutations reveal two important regions in Aspergillus nidulans transcriptional activator MetR

Expression of the sulfur assimilation pathway in Aspergillus nidulans is under control of sulfur metabolite repression, which is composed of scon genes encoding subunits of ubiquitin ligase and the metR gene coding for a transcriptional activator. In this paper we report three dominant suppressors of methionine requirement isolated from a metB3 diploid strain. All three mutations lead to the substitution of phenylalanine 48 by serine or leucine in the conserved N-terminal region of the MetR protein. Strains carrying the dominant suppressor mutations exhibit increased activities of homocysteine synthase and sulfur assimilation enzymes as well as elevated levels of the corresponding transcripts. These changes are observed even under conditions of methionine repression, which suggests that the mutated MetR protein may be resistant to inactivation or degradation mediated by sulfur metabolite repression. We also found that a mutant impaired in sulfite reductase activity, known until now as sG8, has a frameshift which changes 41 C-terminal amino acids. Therefore, it is now designated metR18. This mutant has elevated levels of MetR-regulated transcripts and of activities of sulfur assimilation enzymes (except sulfite reductase), which can be repressed to the wild type level by exogenous methionine. Thus, metR18 and the three dominant suppressors represent new types of mutations affecting different parts of the A. nidulans MetR protein.

Characterizing regulatory path motifs in integrated networks using perturbational data

Pathicular – a Cytoscape plugin for analysing cellular responses to transcription factor perturbations is presented

We introduce Pathicular http://bioinformatics.psb.ugent.be/software/details/Pathicular, a Cytoscape plugin for studying the cellular response to perturbations of transcription factors by integrating perturbational expression data with transcriptional, protein-protein and phosphorylation networks. Pathicular searches for 'regulatory path motifs', short paths in the integrated physical networks which occur significantly more often than expected between transcription factors and their targets in the perturbational data. A case study in Saccharomyces cerevisiae identifies eight regulatory path motifs and demonstrates their biological significance.

Dissection of combinatorial control by the Met4 transcriptional complex

Met4 is the transcriptional activator of the sulfur metabolic network in Saccharomyces cerevisiae. Lacking DNA-binding ability, Met4 must interact with proteins called Met4 cofactors to target promoters for transcription. Two types of DNA-binding cofactors (Cbf1 and Met31/Met32) recruit Met4 to promoters and one cofactor (Met28) stabilizes the DNA-bound Met4 complexes. To dissect this combinatorial system, we systematically deleted each category of cofactor(s) and analyzed Met4-activated transcription on a genome-wide scale. We defined a core regulon for Met4, consisting of 45 target genes. Deletion of both Met31 and Met32 eliminated activation of the core regulon, whereas loss of Met28 or Cbf1 interfered with only a subset of targets that map to distinct sectors of the sulfur metabolic network. These transcriptional dependencies roughly correlated with the presence of Cbf1 promoter motifs. Quantitative analysis of in vivo promoter binding properties indicated varying levels of cooperativity and interdependency exists between members of this combinatorial system. Cbf1 was the only cofactor to remain fully bound to target promoters under all conditions, whereas other factors exhibited different degrees of regulated binding in a promoter-specific fashion. Taken together, Met4 cofactors use a variety of mechanisms to allow differential transcription of target genes in response to various cues.

The emerging regulatory potential of SCFMet30 -mediated polyubiquitination and proteolysis of the Met4 transcriptional activator

The yeast SCF^Met30 ubiquitin ligase plays a critical role in cell division by regulating the Met4 transcriptional activator of genes that control the uptake and assimilation of sulfur into methionine and S-adenosyl-methionine. The initial view on how SCF^Met30 performs its function has been driven by the assumption that SCF^Met30 acts exclusively as Met4 inhibitor when high levels of methionine drive an accumulation of cysteine. We revisit this model in light of the growing evidence that SCF^Met30 can also activate Met4. The notion that Met4 can be inhibited or activated depending on the sulfur metabolite context is not new, but for the first time both aspects have been linked to SCF^Met30, creating an interesting regulatory paradigm in which polyubiquitination and proteolysis of a single transcriptional activator can play different roles depending on context. We discuss the emerging molecular basis and the implications of this new regulatory phenomenon.