André Boorsma

Cell wall construction in Saccharomyces cerevisiae

In this review, we discuss new insights in cell wall architecture and cell wall construction in the ascomycetous yeast Saccharomyces cerevisiae. Transcriptional profiling studies combined with biochemical work have provided ample evidence that the cell wall is a highly adaptable organelle. In particular, the protein population that is anchored to the stress‐bearing polysaccharides of the cell wall, and forms the interface with the outside world, is highly diverse. This diversity is believed to play an important role in adaptation of the cell to environmental conditions, in growth mode and in survival. Cell wall construction is tightly controlled and strictly coordinated with progression of the cell cycle. This is reflected in the usage of specific cell wall proteins during consecutive phases of the cell cycle and in the recent discovery of a cell wall integrity checkpoint. When the cell is challenged with stress conditions that affect the cell wall, a specific transcriptional response is observed that includes the general stress response, the cell wall integrity pathway and the calcineurin pathway. This salvage mechanism includes increased expression of putative cell wall assemblases and some potential cross‐linking cell wall proteins, and crucial changes in cell wall architecture. We discuss some more enzymes involved in cell wall construction and also potential inhibitors of these enzymes. Finally, we use both biochemical and genomic data to infer that the architectural principles used by S. cerevisiae to build its cell wall are also used by many other ascomycetous yeasts and also by some mycelial ascomycetous fungi. Copyright

T-profiler: scoring the activity of predefined groups of genes using gene expression data

One of the key challenges in the analysis of gene expression data is how to relate the expression level of individual genes to the underlying transcriptional programs and cellular state. Here we describe T-profiler, a tool that uses the t-test to score changes in the average activity of predefined groups of genes. The gene groups are defined based on Gene Ontology categorization, ChIP-chip experiments, upstream matches to a consensus transcription factor binding motif or location on the same chromosome. If desired, an iterative procedure can be used to select a single, optimal representative from sets of overlapping gene groups. T-profiler makes it possible to interpret microarray data in a way that is both intuitive and statistically rigorous, without the need to combine experiments or choose parameters. Currently, gene expression data from Saccharomyces cerevisiae and Candida albicans are supported. Users can upload their microarray data for analysis on the web at .

Characterization of the transcriptional response to cell wall stress in Saccharomyces cerevisiae.

The cell wall perturbants Calcofluor white and Zymolyase activate the Pkc1–Rho1‐controlled Slt2p MAP kinase pathway in Saccharomyces cerevisiae. A downstream transcription factor of this pathway, Rlm1p, is known to control expression of about 20 cell wall‐related genes. Global transcript analysis of Calcofluor white and Zymolyase treatment was performed to determine whether cell wall stress affects transcription of these and other genes. Transcript profiles were analysed using two recently developed algorithms, viz. REDUCE, which correlates upstream regulatory motifs with expression, and Quontology, which compares expression of genes from functional groups with overall gene expression. Both methods indicated upregulation of Rlm1p‐controlled cell wall genes and STRE‐controlled genes, and downregulation of ribosomal genes and rRNA genes. Comparison of these expression profiles with the published profiles of two constitutively active upstream activators of the Slt2p–MAP kinase pathway, viz. Pkc1‐R398A and Rho1‐Q68A, revealed significant similarity. In addition, a new putative regulatory motif, CCC(N)10GGC, was found. In Zymolyase ‐treated cells a regulatory site was identified, ATGACGT, which resembles the AFT/CRE binding site. Interestingly, Sko1p, a downstream regulator of the high osmolarity pathway is known to bind to the AFT/CRE binding site, suggesting a possible role for the Hog1 pathway in the response to cell wall stress. Finally, using REDUCE, an improved version of the Rlm1 binding motif, viz. TA(W)4TAGM, was discovered. We propose that this version can be used in combination with REDUCE as a sensitive indicator of cell wall stress. Taken together, our data indicate that cell wall stress results in activation of various signalling pathways including the cell wall integrity pathway. Copyright

Hap4p overexpression in glucose-grown Saccharomyces cerevisiae induces cells to enter a novel metabolic state

BackgroundMetabolic and regulatory gene networks generally tend to be stable. However, we have recently shown that overexpression of the transcriptional activator Hap4p in yeast causes cells to move to a state characterized by increased respiratory activity. To understand why overexpression of HAP4 is able to override the signals that normally result in glucose repression of mitochondrial function, we analyzed in detail the changes that occur in these cells.ResultsWhole-genome expression profiling and fingerprinting of the regulatory activity network show that HAP4 overexpression provokes changes that also occur during the diauxic shift. Overexpression of HAP4, however, primarily acts on mitochondrial function and biogenesis. In fact, a number of nuclear genes encoding mitochondrial proteins are induced to a greater extent than in cells that have passed through a normal diauxic shift: in addition to genes required for mitochondrial energy conservation they include genes encoding mitochondrial ribosomal proteins.ConclusionsWe show that overproduction of a single nuclear transcription factor enables cells to move to a novel state that displays features typical of, but clearly not identical to, other derepressed states.

Transcriptome Analysis of Sorbic Acid-Stressed Bacillus subtilis Reveals a Nutrient Limitation Response and Indicates Plasma Membrane Remodeling

The weak organic acid sorbic acid is a commonly used food preservative, as it inhibits the growth of bacteria, yeasts, and molds. We have used genome-wide transcriptional profiling of Bacillus subtilis cells during mild sorbic acid stress to reveal the growth-inhibitory activity of this preservative and to identify potential resistance mechanisms. Our analysis demonstrated that sorbic acid-stressed cells induce responses normally seen upon nutrient limitation. This is indicated by the strong derepression of the CcpA, CodY, and Fur regulon and the induction of tricarboxylic acid cycle genes, SigL- and SigH-mediated genes, and the stringent response. Intriguingly, these conditions did not lead to the activation of sporulation, competence, or the general stress response. The fatty acid biosynthesis (fab) genes and BkdR-regulated genes are upregulated, which may indicate plasma membrane remodeling. This was further supported by the reduced sensitivity toward the fab inhibitor cerulenin upon sorbic acid stress. We are the first to present a comprehensive analysis of the transcriptional response of B. subtilis to sorbic acid stress.

Modulating the distribution of fluxes among respiration and fermentation by overexpression of HAP4 in Saccharomyces cerevisiae

The tendency of Saccharomyces cerevisiae to favor alcoholic fermentation over respiration is a complication in aerobic, biomass-directed applications of this yeast. Overproduction of Hap4p, a positive transcriptional regulator of genes involved in respiratory metabolism, has been reported to positively affect the balance between respiration and fermentation in aerobic glucose-grown batch cultures. In this study, the effects of HAP4 overexpression have been quantified in the prototrophic S. cerevisiae strain CEN.PK 113-7D under a variety of growth conditions. In aerobic glucose-limited chemostat cultures, overexpression of HAP4 increased the specific growth rate at which aerobic fermentation set in by about 10% relative to the isogenic wild-type. Upon relief of glucose-limited conditions, the HAP4-overexpressing strain produced slightly less ethanol than the wild-type strain. The effect of Hap4p overproduction was most drastic in aerobic, glucose-grown chemostat cultures in which ammonium was limiting. In such cultures, the biomass yield on glucose was double that of the wild-type.

Cellular processes and pathways that protect Saccharomyces cerevisiae cells against the plasma membrane-perturbing compound chitosan.

ABSTRACT Global fitness analysis makes use of a genomic library of tagged deletion strains. We used this approach to study the effect of chitosan, which causes plasma membrane stress. The data were analyzed using T-profiler, which was based on determining the sensitivities of groups of deletion strains to chitosan, as defined by Gene Ontology (GO) and by genomic synthetic lethality screens, in combination with t statistics. The chitosan-hypersensitive groups included a group of deletion strains characterized by a defective HOG (high-osmolarity glycerol) signaling pathway, indicating that the HOG pathway is required for counteracting chitosan-induced stress. Consistent with this, activation of this pathway in wild-type cells by hypertonic conditions offered partial protection against chitosan, whereas hypotonic conditions sensitized the cells to chitosan. Other chitosan-hypersensitive groups were defective in RNA synthesis and processing, actin cytoskeleton organization, protein N-glycosylation, ergosterol synthesis, endocytosis, or cell wall formation, predicting that these cellular functions buffer the cell against the deleterious effect of chitosan. These predictions were supported by showing that tunicamycin, miconazole, and staurosporine (which target protein N-glycosylation, ergosterol synthesis, and the cell wall integrity pathway, respectively) sensitized Saccharomyces cerevisiae cells to chitosan. Intriguingly, the GO-defined group of deletion strains belonging to the “cytosolic large ribosomal subunit” was more resistant to chitosan. We propose that global fitness analysis of yeast in combination with T-profiler is a powerful tool to identify specific cellular processes and pathways that are required for survival under stress conditions.

Inferring condition-specific modulation of transcription factor activity in yeast through regulon-based analysis of genomewide expression

Background A key goal of systems biology is to understand how genomewide mRNA expression levels are controlled by transcription factors (TFs) in a condition-specific fashion. TF activity is frequently modulated at the post-translational level through ligand binding, covalent modification, or changes in sub-cellular localization. In this paper, we demonstrate how prior information about regulatory network connectivity can be exploited to infer condition-specific TF activity as a hidden variable from the genomewide mRNA expression pattern in the yeast Saccharomyces cerevisiae. Methodology/Principal Findings We first validate experimentally that by scoring differential expression at the level of gene sets or “regulons” comprised of the putative targets of a TF, we can accurately predict modulation of TF activity at the post-translational level. Next, we create an interactive database of inferred activities for a large number of TFs across a large number of experimental conditions in S. cerevisiae. This allows us to perform TF-centric analysis of the yeast regulatory network. Conclusions/Significance We analyze the degree to which the mRNA expression level of each TF is predictive of its regulatory activity. We also organize TFs into “co-modulation networks” based on their inferred activity profile across conditions, and find that this reveals functional and mechanistic relationships. Finally, we present evidence that the PAC and rRPE motifs antagonize TBP-dependent regulation, and function as core promoter elements governed by the transcription regulator NC2. Regulon-based monitoring of TF activity modulation is a powerful tool for analyzing regulatory network function that should be applicable in other organisms. Tools and results are available online at http://bussemakerlab.org/RegulonProfiler/.

Dissecting complex transcriptional responses using pathway-level scores based on prior information

BackgroundThe genomewide pattern of changes in mRNA expression measured using DNA microarrays is typically a complex superposition of the response of multiple regulatory pathways to changes in the environment of the cells. The use of prior information, either about the function of the protein encoded by each gene, or about the physical interactions between regulatory factors and the sequences controlling its expression, has emerged as a powerful approach for dissecting complex transcriptional responses.ResultsWe review two different approaches for combining the noisy expression levels of multiple individual genes into robust pathway-level differential expression scores. The first is based on a comparison between the distribution of expression levels of genes within a predefined gene set and those of all other genes in the genome. The second starts from an estimate of the strength of genomewide regulatory network connectivities based on sequence information or direct measurements of protein-DNA interactions, and uses regression analysis to estimate the activity of gene regulatory pathways. The statistical methods used are explained in detail.ConclusionBy avoiding the thresholding of individual genes, pathway-level analysis of differential expression based on prior information can be considerably more sensitive to subtle changes in gene expression than gene-level analysis. The methods are technically straightforward and yield results that are easily interpretable, both biologically and statistically.

Comparative Analysis of Transcriptome and Fitness Profiles Reveals General and Condition-Specific Cellular Functions Involved in Adaptation to Environmental Change in Saccharomyces cerevisiae

The transcriptional responses of yeast cells to a wide variety of stress conditions have been studied extensively. In addition, deletion mutant collections have been widely used to measure the combined effect of gene loss and stress on growth (fitness). Here we present a comparative analysis of 1,095 publicly available transcription and genome-wide fitness profiles in yeast, from different laboratories and experimental platforms. We analyzed these data, using T-profiler, to describe the correlation in behavior of a priori defined functional groups. Two-mode clustering analysis of the fitness T-profiles revealed that functional groups involved in regulating ribosome biogenesis and translation offer general stress resistance. These groups are closely related to growth rate and nutrient availability. General stress sensitivity was found in deletion mutant groups functioning in intracellular vesicular transport, actin cytoskeleton organization, and cell polarity, indicating that they play an key role in maintaining yeast adaptability. Analysis of the phenotypic and transcriptional variability of our a priori defined functional groups showed that the quantitative effect on fitness of both resistant and sensitive groups is highly condition-dependent. Finally, we discuss the implications of our results for combinatorial drug design.