Transcriptional plasticity through differential assembly of a multiprotein activation complex

Genome-wide patterns of noncoding and protein-coding sequence variation in the major fungal pathogen Aspergillus fumigatus

Aspergillus fumigatus is a deadly fungal pathogen, responsible for >400,000 infections/year and high mortality rates. A. fumigatus strains exhibit variation in infection-relevant traits, including in their virulence. However, most A. fumigatus protein-coding genes, including those that modulate its virulence, are shared between A. fumigatus strains and closely related nonpathogenic relatives. We hypothesized that A. fumigatus genes exhibit substantial genetic variation in the noncoding regions immediately upstream to the start codons of genes, which could reflect differences in gene regulation between strains. To begin testing this hypothesis, we identified 5,812 single-copy orthologs across the genomes of 263 A. fumigatus strains. In general, A. fumigatus noncoding regions showed higher levels of sequence variation compared with their corresponding protein-coding regions. Focusing on 2,482 genes whose protein-coding sequence identity scores ranged between 75 and 99%, we identified 478 total genes with signatures of positive selection only in their noncoding regions and 65 total genes with signatures only in their protein-coding regions. Twenty-eight of the 478 noncoding regions and 5 of the 65 protein-coding regions under selection are associated with genes known to modulate A. fumigatus virulence. Noncoding region variation between A. fumigatus strains included single-nucleotide polymorphisms and insertions or deletions of at least a few nucleotides. These results show that noncoding regions of A. fumigatus genes harbor greater sequence variation than protein-coding regions, raising the hypothesis that this variation may contribute to A. fumigatus phenotypic heterogeneity.

Genome-wide patterns of non-coding sequence variation in the major fungal pathogen Aspergillus fumigatus

A.fumigatus is a deadly fungal pathogen, responsible for >400,000 infections/year and high mortality rates. A. fumigatus strains exhibit variation in infection-relevant traits, including in their virulence. However, most A. fumigatus protein-coding genes, including those that modulate its virulence, are shared between A. fumigatus strains and closely related non-pathogenic relatives. We hypothesized that A. fumigatus genes exhibit substantial genetic variation in the non-coding regions immediately upstream to the start codons of genes, which could reflect differences in gene regulation between strains. To begin testing this hypothesis, we identified 5,812 single-copy orthologs across the genomes of 263 A. fumigatus strains. A. fumigatus non-coding regions showed higher levels of sequence variation compared to their corresponding protein-coding regions. Specifically, we found that 1,274 non-coding regions exhibited <75% nucleotide sequence similarity (compared to 928 protein-coding regions) and 3,721 non-coding regions exhibited between 75% and 99% similarity (compared to 2,482 protein-coding regions) across strains. Only 817 non-coding regions exhibited ≥99% sequence similarity compared to 2,402 protein-coding regions. By examining 2,482 genes whose protein-coding sequence identity scores ranged between 75% and 99%, we identified 478 total genes with signatures of positive selection only in their non-coding regions and 65 total genes with signatures only in their protein-coding regions. 28 of the 478 non-coding regions and 5 of the 65 protein-coding regions under selection are associated with genes known to modulate A. fumigatus virulence. Non-coding region variation between A. fumigatus strains included single nucleotide polymorphisms and insertions or deletions of at least a few nucleotides. These results show that non-coding regions of A. fumigatus genes harbor greater sequence variation than protein-coding regions, raising the hypothesis that this variation may contribute to A. fumigatus phenotypic heterogeneity.

Inferring gene regulatory networks using transcriptional profiles as dynamical attractors

Genetic regulatory networks (GRNs) regulate the flow of genetic information from the genome to expressed messenger RNAs (mRNAs) and thus are critical to controlling the phenotypic characteristics of cells. Numerous methods exist for profiling mRNA transcript levels and identifying protein-DNA binding interactions at the genome-wide scale. These enable researchers to determine the structure and output of transcriptional regulatory networks, but uncovering the complete structure and regulatory logic of GRNs remains a challenge. The field of GRN inference aims to meet this challenge using computational modeling to derive the structure and logic of GRNs from experimental data and to encode this knowledge in Boolean networks, Bayesian networks, ordinary differential equation (ODE) models, or other modeling frameworks. However, most existing models do not incorporate dynamic transcriptional data since it has historically been less widely available in comparison to "static" transcriptional data. We report the development of an evolutionary algorithm-based ODE modeling approach (named EA) that integrates kinetic transcription data and the theory of attractor matching to infer GRN architecture and regulatory logic. Our method outperformed six leading GRN inference methods, none of which incorporate kinetic transcriptional data, in predicting regulatory connections among TFs when applied to a small-scale engineered synthetic GRN in Saccharomyces cerevisiae. Moreover, we demonstrate the potential of our method to predict unknown transcriptional profiles that would be produced upon genetic perturbation of the GRN governing a two-state cellular phenotypic switch in Candida albicans. We established an iterative refinement strategy to facilitate candidate selection for experimentation; the experimental results in turn provide validation or improvement for the model. In this way, our GRN inference approach can expedite the development of a sophisticated mathematical model that can accurately describe the structure and dynamics of the in vivo GRN.

Mediator dynamics during heat shock in budding yeast

The Mediator complex is central to transcription by RNA polymerase II (Pol II) in eukaryotes. In budding yeast (Saccharomyces cerevisiae), Mediator is recruited by activators and associates with core promoter regions, where it facilitates preinitiation complex (PIC) assembly, only transiently before Pol II escape. Interruption of the transcription cycle by inactivation or depletion of Kin28 inhibits Pol II escape and stabilizes this association. However, Mediator occupancy and dynamics have not been examined on a genome-wide scale in yeast grown in nonstandard conditions. Here we investigate Mediator occupancy following heat shock or CdCl₂ exposure, with and without depletion of Kin28. We find that Pol II occupancy shows similar dependence on Mediator under normal and heat shock conditions. However, although Mediator association increases at many genes upon Kin28 depletion under standard growth conditions, little or no increase is observed at most genes upon heat shock, indicating a more stable association of Mediator after heat shock. Unexpectedly, Mediator remains associated upstream of the core promoter at genes repressed by heat shock or CdCl₂ exposure whether or not Kin28 is depleted, suggesting that Mediator is recruited by activators but is unable to engage PIC components at these repressed targets. This persistent association is strongest at promoters that bind the HMGB family member Hmo1, and is reduced but not eliminated in hmo1Δ yeast. Finally, we show a reduced dependence on PIC components for Mediator occupancy at promoters after heat shock, further supporting altered dynamics or stronger engagement with activators under these conditions.

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.

Glycerol stress in Saccharomyces cerevisiae: Cellular responses and evolved adaptations

Glycerol synthesis is key to central metabolism and stress biology in Saccharomyces cerevisiae, yet the cellular adjustments needed to respond and adapt to glycerol stress are little understood. Here, we determined impacts of acute and chronic exposures to glycerol stress in S. cerevisiae. Glycerol stress can result from an increase of glycerol concentration in the medium due to the S. cerevisiae fermenting activity or other metabolic activities. Acute glycerol-stress led to a 50% decline in growth rate and altered transcription of more than 40% of genes. The increased genetic diversity in S. cerevisiae population, which had evolved in the standard nutrient medium for hundreds of generations, led to an increase in growth rate and altered transcriptome when such population was transferred to stressful media containing a high concentration of glycerol; 0.41 M (0.990 water activity). Evolution of S. cerevisiae populations during a 10-day period in the glycerol-containing medium led to transcriptome changes and readjustments to improve control of glycerol flux across the membrane, regulation of cell cycle, and more robust stress response; and a remarkable increase of growth rate under glycerol stress. Most of the observed regulatory changes arose in duplicated genes. These findings elucidate the physiological mechanisms, which underlie glycerol-stress response, and longer-term adaptations, in S. cerevisiae; they also have implications for enigmatic aspects of the ecology of this otherwise well-characterized yeast.

The Phenotypic Plasticity of Duplicated Genes in Saccharomyces cerevisiae and the Origin of Adaptations

Gene and genome duplication are the major sources of biological innovations in plants and animals. Functional and transcriptional divergence between the copies after gene duplication has been considered the main driver of innovations . However, here we show that increased phenotypic plasticity after duplication plays a more major role than thought before in the origin of adaptations. We perform an exhaustive analysis of the transcriptional alterations of duplicated genes in the unicellular eukaryote Saccharomyces cerevisiae when challenged with five different environmental stresses. Analysis of the transcriptomes of yeast shows that gene duplication increases the transcriptional response to environmental changes, with duplicated genes exhibiting signatures of adaptive transcriptional patterns in response to stress. The mechanism of duplication matters, with whole-genome duplicates being more transcriptionally altered than small-scale duplicates. The predominant transcriptional pattern follows the classic theory of evolution by gene duplication; with one gene copy remaining unaltered under stress, while its sister copy presents large transcriptional plasticity and a prominent role in adaptation. Moreover, we find additional transcriptional profiles that are suggestive of neo- and subfunctionalization of duplicate gene copies. These patterns are strongly correlated with the functional dependencies and sequence divergence profiles of gene copies. We show that, unlike singletons, duplicates respond more specifically to stress, supporting the role of natural selection in the transcriptional plasticity of duplicates. Our results reveal the underlying transcriptional complexity of duplicated genes and its role in the origin of adaptations.

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.

A Minimal Set of Glycolytic Genes Reveals Strong Redundancies in Saccharomyces cerevisiae Central Metabolism

As a result of ancestral whole-genome and small-scale duplication events, the genomes of Saccharomyces cerevisiae and many eukaryotes still contain a substantial fraction of duplicated genes. In all investigated organisms, metabolic pathways, and more particularly glycolysis, are specifically enriched for functionally redundant paralogs. In ancestors of the Saccharomyces lineage, the duplication of glycolytic genes is purported to have played an important role leading to S. cerevisiae's current lifestyle favoring fermentative metabolism even in the presence of oxygen and characterized by a high glycolytic capacity. In modern S. cerevisiae strains, the 12 glycolytic reactions leading to the biochemical conversion from glucose to ethanol are encoded by 27 paralogs. In order to experimentally explore the physiological role of this genetic redundancy, a yeast strain with a minimal set of 14 paralogs was constructed (the "minimal glycolysis" [MG] strain). Remarkably, a combination of a quantitative systems approach and semiquantitative analysis in a wide array of growth environments revealed the absence of a phenotypic response to the cumulative deletion of 13 glycolytic paralogs. This observation indicates that duplication of glycolytic genes is not a prerequisite for achieving the high glycolytic fluxes and fermentative capacities that are characteristic of S. cerevisiae and essential for many of its industrial applications and argues against gene dosage effects as a means of fixing minor glycolytic paralogs in the yeast genome. The MG strain was carefully designed and constructed to provide a robust prototrophic platform for quantitative studies and has been made available to the scientific community.

Mediator, TATA-binding protein, and RNA polymerase II contribute to low histone occupancy at active gene promoters in yeast

Transcription by RNA polymerase II (Pol II) in eukaryotes requires the Mediator complex, and often involves chromatin remodeling and histone eviction at active promoters. Here we address the role of Mediator in recruitment of the Swi/Snf chromatin remodeling complex and its role, along with components of the preinitiation complex (PIC), in histone eviction at inducible and constitutively active promoters in the budding yeast Saccharomyces cerevisiae. We show that recruitment of the Swi/Snf chromatin remodeling complex to the induced CHA1 promoter, as well as its association with several constitutively active promoters, depends on the Mediator complex but is independent of Mediator at the induced MET2 and MET6 genes. Although transcriptional activation and histone eviction at CHA1 depends on Swi/Snf, Swi/Snf recruitment is not sufficient for histone eviction at the induced CHA1 promoter. Loss of Swi/Snf activity does not affect histone occupancy of several constitutively active promoters; in contrast, higher histone occupancy is seen at these promoters in Mediator and PIC component mutants. We propose that an initial activator-dependent, nucleosome remodeling step allows PIC components to outcompete histones for occupancy of promoter sequences. We also observe reduced promoter association of Mediator and TATA-binding protein in a Pol II (rpb1-1) mutant, indicating mutually cooperative binding of these components of the transcription machinery and indicating that it is the PIC as a whole whose binding results in stable histone eviction.

Functional analyses of NSF1 in wine yeast using interconnected correlation clustering and molecular analyses

Analyzing time-course expression data captured in microarray datasets is a complex undertaking as the vast and complex data space is represented by a relatively low number of samples as compared to thousands of available genes. Here, we developed the Interdependent Correlation Clustering (ICC) method to analyze relationships that exist among genes conditioned on the expression of a specific target gene in microarray data. Based on Correlation Clustering, the ICC method analyzes a large set of correlation values related to gene expression profiles extracted from given microarray datasets. ICC can be applied to any microarray dataset and any target gene. We applied this method to microarray data generated from wine fermentations and selected NSF1, which encodes a C₂H₂ zinc finger-type transcription factor, as the target gene. The validity of the method was verified by accurate identifications of the previously known functional roles of NSF1. In addition, we identified and verified potential new functions for this gene; specifically, NSF1 is a negative regulator for the expression of sulfur metabolism genes, the nuclear localization of Nsf1 protein (Nsf1p) is controlled in a sulfur-dependent manner, and the transcription of NSF1 is regulated by Met4p, an important transcriptional activator of sulfur metabolism genes. The inter-disciplinary approach adopted here highlighted the accuracy and relevancy of the ICC method in mining for novel gene functions using complex microarray datasets with a limited number of samples.

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.

Perturbation-based analysis and modeling of combinatorial regulation in the yeast sulfur assimilation pathway

Here we establish the utility of a recently described perturbative method to study complex regulatory circuits in vivo. By combining rapid modulation of single TFs under physiological conditions with genome-wide expression analysis, we elucidate several novel regulatory features within the pathways of sulfur assimilation and beyond.

In yeast, the pathways of sulfur assimilation are combinatorially controlled by five transcriptional regulators (three DNA-binding proteins [Met31p, Met32p, and Cbf1p], an activator [Met4p], and a cofactor [Met28p]) and a ubiquitin ligase subunit (Met30p). This regulatory system exerts combinatorial control not only over sulfur assimilation and methionine biosynthesis, but also on many other physiological functions in the cell. Recently we characterized a gene induction system that, upon the addition of an inducer, results in near-immediate transcription of a gene of interest under physiological conditions. We used this to perturb levels of single transcription factors during steady-state growth in chemostats, which facilitated distinction of direct from indirect effects of individual factors dynamically through quantification of the subsequent changes in genome-wide patterns of gene expression. We were able to show directly that Cbf1p acts sometimes as a repressor and sometimes as an activator. We also found circumstances in which Met31p/Met32p function as repressors, as well as those in which they function as activators. We elucidated and numerically modeled feedback relationships among the regulators, notably feedforward regulation of Met32p (but not Met31p) by Met4p that generates dynamic differences in abundance that can account for the differences in function of these two proteins despite their identical binding sites.

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.

Distinct role of Mediator tail module in regulation of SAGA-dependent, TATA-containing genes in yeast

The evolutionarily conserved Mediator complex is required for transcription of nearly all RNA Pol II-dependent promoters, with the tail module serving to recruit Mediator to active promoters in current models. However, transcriptional dependence on tail module subunits varies in a gene-specific manner, and the generality of the tail module requirement for transcriptional activation has not been explored. Here, we show that tail module subunits function redundantly to recruit Mediator to promoters in yeast, and transcriptome analysis shows stronger effects on genome-wide expression in a double-tail subunit deletion mutant than in single-subunit deletion mutants. Unexpectedly, TATA-containing and SAGA-dependent genes were much more affected by impairment of tail module function than were TFIID-dependent genes. Consistent with this finding, Mediator and preinitiation complex association with SAGA-dependent promoters is substantially reduced in gal11/med15Δ med3Δ yeast, whereas association of TBP, Pol II, and other Mediator modules with TFIID-dependent genes is largely independent of the tail module. Thus, we have identified a connection between the Mediator tail module and the division of promoter dependence between TFIID and SAGA.

Biodiversity in sulfur metabolism in hemiascomycetous yeasts

The evolution of the metabolism of sulfur compounds among yeast species was investigated. Differences between species were observed in the cysteine biosynthesis pathway. Most yeast species possess two pathways leading to cysteine production, the transsulfuration pathway and the O-acetyl-serine (OAS) pathway, with the exception of Saccharomyces cerevisiae and Candida glabrata, which only display the transsulfuration pathway, and Schizosaccharomyces pombe, which only have the OAS pathway. An examination of the components of the regulatory network in the different species shows that it is conserved in all the species analyzed, as its central component Met4p was shown to keep its functional domains and its partners were present. The analysis of the presence of genes involved in the catabolic pathway shows that it is evolutionarily conserved in the sulfur metabolism and leads us to propose a role for two gene families which appeared to be highly conserved. This survey has provided ways to understand the diversity of sulfur metabolism products among yeast species through the reconstruction of these pathways. This diversity could account for the difference in metabolic potentialities of the species with a biotechnological interest.