Rsf1p, a protein required for respiratory growth of Saccharomyces cerevisiae

Genome-scale metabolic modelling identifies reactions mediated by SNP-SNP interactions associated with yeast sporulation

Genome-scale metabolic models (GEMs) are powerful tools used to understand the functional effects of genetic variants. However, the impact of single nucleotide polymorphisms (SNPs) in transcription factors and their interactions on metabolic fluxes remains largely unexplored. Using gene expression data from a yeast allele replacement panel grown during sporulation, we constructed co-expression networks and SNP-specific GEMs. Analysis of co-expression networks revealed that during sporulation, SNP-SNP interactions impact the connectivity of metabolic regulators involved in glycolysis, steroid and histidine biosynthesis, and amino acid metabolism. Further, genome-scale differential flux analysis identified reactions within six major metabolic pathways associated with sporulation efficiency variation. Notably, autophagy was predicted to act as a pentose pathway-dependent compensatory mechanism supplying critical precursors like nucleotides and amino acids, enhancing sporulation. Our study highlights how transcription factor polymorphisms interact to shape metabolic pathways in yeast, offering insights into genetic variants associated with metabolic traits in genome-wide association studies.

Glycerol as a substrate for Saccharomyces cerevisiae based bioprocesses - Knowledge gaps regarding the central carbon catabolism of this 'non-fermentable' carbon source

Glycerol is an interesting alternative carbon source in industrial bioprocesses due to its higher degree of reduction per carbon atom compared to sugars. During the last few years, significant progress has been made in improving the well-known industrial platform organism Saccharomyces cerevisiae with regard to its glycerol utilization capability, particularly in synthetic medium. This provided a basis for future metabolic engineering focusing on the production of valuable chemicals from glycerol. However, profound knowledge about the central carbon catabolism in synthetic glycerol medium is a prerequisite for such incentives. As a matter of fact, the current assumptions about the actual in vivo fluxes active on glycerol as the sole carbon source have mainly been based on omics data collected in complex media or were even deduced from studies with other non-fermentable carbon sources, such as ethanol or acetate. A number of uncertainties have been identified which particularly regard the role of the glyoxylate cycle, the subcellular localization of the respective enzymes, the contributions of mitochondrial transporters and the active anaplerotic reactions under these conditions. The review scrutinizes the current knowledge, highlights the necessity to collect novel experimental data using cells growing in synthetic glycerol medium and summarizes the current state of the art with regard to the production of valuable fermentation products from a carbon source that has been considered so far as 'non-fermentable' for the yeast S. cerevisiae.

Proteins involved in wine aroma compounds metabolism by a Saccharomyces cerevisiae flor-velum yeast strain grown in two conditions

A proteomic and exometabolomic study was conducted on Saccharomyces cerevisiae flor yeast strain growing under biofilm formation condition (BFC) with ethanol and glycerol as carbon sources and results were compared with those obtained under no biofilm formation condition (NBFC) containing glucose as carbon source. By using modern techniques, OFFGEL fractionator and LTQ-Orbitrap for proteome and SBSE-TD-GC-MS for metabolite analysis, we quantified 84 proteins including 33 directly involved in the metabolism of glycerol, ethanol and 17 aroma compounds. Contents in acetaldehyde, acetic acid, decanoic acid, 1,1-diethoxyethane, benzaldehyde and 2-phenethyl acetate, changed above their odor thresholds under BFC, and those of decanoic acid, ethyl octanoate, ethyl decanoate and isoamyl acetate under NBFC. Of the twenty proteins involved in the metabolism of ethanol, acetaldehyde, acetoin, 2,3-butanediol, 1,1-diethoxyethane, benzaldehyde, organic acids and ethyl esters, only Adh2p, Ald4p, Cys4p, Fas3p, Met2p and Plb1p were detected under BFC and as many Acs2p, Ald3p, Cem1p, Ilv2p, Ilv6p and Pox1p, only under NBFC. Of the eight proteins involved in glycerol metabolism, Gut2p was detected only under BFC while Pgs1p and Rhr2p were under NBFC. Finally, of the five proteins involved in the metabolism of higher alcohols, Thi3p was present under BFC, and Aro8p and Bat2p were under NBFC.

Single nucleotide variants in transcription factors associate more tightly with phenotype than with gene expression

Mapping the polymorphisms responsible for variation in gene expression, known as Expression Quantitative Trait Loci (eQTL), is a common strategy for investigating the molecular basis of disease. Despite numerous eQTL studies, the relationship between the explanatory power of variants on gene expression versus their power to explain ultimate phenotypes remains to be clarified. We addressed this question using four naturally occurring Quantitative Trait Nucleotides (QTN) in three transcription factors that affect sporulation efficiency in wild strains of the yeast, Saccharomyces cerevisiae. We compared the ability of these QTN to explain the variation in both gene expression and sporulation efficiency. We find that the amount of gene expression variation explained by the sporulation QTN is not predictive of the amount of phenotypic variation explained. The QTN are responsible for 98% of the phenotypic variation in our strains but the median gene expression variation explained is only 49%. The alleles that are responsible for most of the variation in sporulation efficiency do not explain most of the variation in gene expression. The balance between the main effects and gene-gene interactions on gene expression variation is not the same as on sporulation efficiency. Finally, we show that nucleotide variants in the same transcription factor explain the expression variation of different sets of target genes depending on whether the variant alters the level or activity of the transcription factor. Our results suggest that a subset of gene expression changes may be more predictive of ultimate phenotypes than the number of genes affected or the total fraction of variation in gene expression variation explained by causative variants, and that the downstream phenotype is buffered against variation in the gene expression network.

Characterization of GCY1 in Saccharomyces cerevisiae by metabolic profiling

AIMS

The analytical study of intracellular (IC) metabolites has developed with advances in chromatography-linked mass spectrometry and fast sampling procedures. We applied the IC metabolite analysis to characterize the role of GCY1 in the glycerol (GLY) catabolic pathway in Saccharomyces cerevisiae.

METHODS AND RESULTS

Strains with disrupted or overexpressing GLY catabolic genes such as GCY1, DAK1 and DAK2 were constructed. The strains were cultivated under different aeration conditions and quickly quenched using a novel rapid sampling port. IC concentrations of GLY, dihydroxyacetone (DHA), glycerol 3-phosphate and dihydroxyacetone phosphate were analysed in the strains by gas chromatography/mass spectrometry. DHA was not detected in the gcy1 gene-disrupted strain but accumulated 225.91 μmol g DCW(-1) in a DHA kinase gene-deficient strain under micro-aerobic conditions. Additionally, a 16.1% increase in DHA occurred by overexpressing GCY1 in the DHA kinase-deficient strain.

CONCLUSIONS

Metabolic profiling showed that the GCY1 gene product functions as a GLY dehydrogenase in S. cerevisiae, particularly under micro-aerobic conditions.

SIGNIFICANCE AND IMPACT OF THE STUDY

Metabolic profiling of the GLY dissimilation pathway was successfully demonstrated in S. cerevisiae, and the function of GCY1 was explained by the results.

Gene-environment interactions at nucleotide resolution

Interactions among genes and the environment are a common source of phenotypic variation. To characterize the interplay between genetics and the environment at single nucleotide resolution, we quantified the genetic and environmental interactions of four quantitative trait nucleotides (QTN) that govern yeast sporulation efficiency. We first constructed a panel of strains that together carry all 32 possible combinations of the 4 QTN genotypes in 2 distinct genetic backgrounds. We then measured the sporulation efficiencies of these 32 strains across 8 controlled environments. This dataset shows that variation in sporulation efficiency is shaped largely by genetic and environmental interactions. We find clear examples of QTN:environment, QTN: background, and environment:background interactions. However, we find no QTN:QTN interactions that occur consistently across the entire dataset. Instead, interactions between QTN only occur under specific combinations of environment and genetic background. Thus, what might appear to be a QTN:QTN interaction in one background and environment becomes a more complex QTN:QTN:environment:background interaction when we consider the entire dataset as a whole. As a result, the phenotypic impact of a set of QTN alleles cannot be predicted from genotype alone. Our results instead demonstrate that the effects of QTN and their interactions are inextricably linked both to genetic background and to environmental variation.

Phenotypic variation among individuals is caused by naturally occurring genetic differences, or alleles. The relationship between an allele and the phenotype is extremely complex; for example, the effect of an allele often depends upon both the environment and the individual's genetic background. To better understand these complex relationships, we examined the effects of four quantitative trait nucleotides (QTN) in three genes that cause variation in sporulation efficiency between vineyard and oak tree strains of yeast. We measured the effects of the QTN while varying both the genetic makeup of the strains and their growth environments. We found that the effects of each of the four QTN alleles depended upon the genotypes at the other QTN, the growth environment, and whether the strain carried the oak or vineyard parent genome. There were no simple rules that describe the effects of the alleles across all environments; instead, detailed models were needed to account for environmental and genetic variation in order to predict the effects of alleles in specific individuals.

Allicin-induced global gene expression profile of Saccharomyces cerevisiae

To understand the response mechanisms of fungus cells upon exposure to the natural fungicide allicin, we performed commercial oligonucleotide microarrays to determine the overall transcriptional response of allicin-treated Saccharomyces cerevisiae strain L1190. Compared with the transcriptional profiles of untreated cultures, 147 genes were significantly upregulated, and 145 genes were significantly downregulated in the allicin-treated cells. We interpreted the microarray data with the hierarchical clustering tool, T-profiler. Major transcriptional responses were induced by allicin and included the following: first, Rpn4p-mediated responses involved in proteasome gene expression; second, the Rsc1p-mediated response involved in iron ion transporter activity; third, the Gcn4p-mediated response, also known as general amino acid control; finally, the Yap1p-, Msn2/4p-, Crz1p-, and Cin5p-mediated multiple stress response. Interestingly, allicin treatment, similar to mycotoxin patulin and artificial fungicide thiuram treatment, was found to induce genes involved in sulfur amino acid metabolism and the defense system for oxidative stress, especially DNA repair, which suggests a potential mutagenicity for allicin. Quantitative real-time reverse transcription-polymerase chain reaction was performed for selected genes to verify the microarray results. To our knowledge, this is the first report of the global transcriptional profiling of allicin-treated S. cerevisiae by microarray.

Comparative analyses of time-course gene expression profiles of the long-lived sch9Delta mutant

In an attempt to elucidate the underlying longevity-promoting mechanisms of mutants lacking SCH9, which live three times as long as wild type chronologically, we measured their time-course gene expression profiles. We interpreted their expression time differences by statistical inferences based on prior biological knowledge, and identified the following significant changes: (i) between 12 and 24 h, stress response genes were up-regulated by larger fold changes and ribosomal RNA (rRNA) processing genes were down-regulated more dramatically; (ii) mitochondrial ribosomal protein genes were not up-regulated between 12 and 60 h as wild type were; (iii) electron transport, oxidative phosphorylation and TCA genes were down-regulated early; (iv) the up-regulation of TCA and electron transport was accompanied by deep down-regulation of rRNA processing over time; and (v) rRNA processing genes were more volatile over time, and three associated cis-regulatory elements [rRNA processing element (rRPE), polymerase A and C (PAC) and glucose response element (GRE)] were identified. Deletion of AZF1, which encodes the transcriptional factor that binds to the GRE element, reversed the lifespan extension of sch9Δ. The significant alterations in these time-dependent expression profiles imply that the lack of SCH9 turns on the longevity programme that extends the lifespan through changes in metabolic pathways and protection mechanisms, particularly, the regulation of aerobic respiration and rRNA processing.

Epistasis in a quantitative trait captured by a molecular model of transcription factor interactions

With technological advances in genetic mapping studies more of the genes and polymorphisms that underlie Quantitative Trait Loci (QTL) are now being identified. As the identities of these genes become known there is a growing need for an analysis framework that incorporates the molecular interactions affected by natural polymorphisms. As a step towards such a framework we present a molecular model of genetic variation in sporulation efficiency between natural isolates of the yeast, Saccharomyces cerevisiae. The model is based on the structure of the regulatory pathway that controls sporulation. The model captures the phenotypic variation between strains carrying different combinations of alleles at known QTL. Compared to a standard linear model the molecular model requires fewer free parameters, and has the advantage of generating quantitative hypotheses about the affinity of specific molecular interactions in different genetic backgrounds. Our analyses provide a concrete example of how the thermodynamic properties of protein-protein and protein-DNA interactions naturally give rise to epistasis, the non-linear relationship between genotype and phenotype. As more causative genes and polymorphisms underlying QTL are identified, thermodynamic analyses of quantitative traits may provide a useful framework for unraveling the complex relationship between genotype and phenotype.

Additions, losses, and rearrangements on the evolutionary route from a reconstructed ancestor to the modern Saccharomyces cerevisiae genome

Comparative genomics can be used to infer the history of genomic rearrangements that occurred during the evolution of a species. We used the principle of parsimony, applied to aligned synteny blocks from 11 yeast species, to infer the gene content and gene order that existed in the genome of an extinct ancestral yeast about 100 Mya, immediately before it underwent whole-genome duplication (WGD). The reconstructed ancestral genome contains 4,703 ordered loci on eight chromosomes. The reconstruction is complete except for the subtelomeric regions. We then inferred the series of rearrangement steps that led from this ancestor to the current Saccharomyces cerevisiae genome; relative to the ancestral genome we observe 73 inversions, 66 reciprocal translocations, and five translocations involving telomeres. Some fragile chromosomal sites were reused as evolutionary breakpoints multiple times. We identified 124 genes that have been gained by S. cerevisiae in the time since the WGD, including one that is derived from a hAT family transposon, and 88 ancestral loci at which S. cerevisiae did not retain either of the gene copies that were formed by WGD. Sites of gene gain and evolutionary breakpoints both tend to be associated with tRNA genes and, to a lesser extent, with origins of replication. Many of the gained genes in S. cerevisiae have functions associated with ethanol production, growth in hypoxic environments, or the uptake of alternative nutrient sources.

Rsf1p is required for an efficient metabolic shift from fermentative to glycerol-based respiratory growth in S. cerevisiae

Previous studies from this laboratory indicated that the product of the RSF1 gene of S. cerevisiae is present in both nucleus and mitochondria, and they suggested that Rsf1p acts as a transcriptional modulator. To investigate this latter question, we performed transcriptome profiling of an rsf1 mutant strain and its wild-type parent during a shift from glucose-based fermentative to glycerol-based respiratory growth to identify genes whose expression is regulated by Rsf1p. Loss of Rsf1p engendered a decrease in transcript levels from many genes encoding components of the electron transport chain and various other mitochondrially-localized products. The earlier studies further showed that rsf1 cells exhibit a growth defect on medium containing glycerol, but not ethanol, as sole carbon source. Importantly, transcriptome profiling of the rsf1 mutant during shift from glucose- to glycerol-based medium revealed that the product of this gene plays a major role in both orchestration of the transition to, and maintenance of, efficient growth on glycerol as sole carbon source. An increase in transcript levels from genes encoding products that function in the stress response, and an imbalance between expression of genes encoding glycerol anabolic and catabolic enzymes, was observed in the rsf1 mutant during steady-state growth on glycerol- but not ethanol-based medium; this suggests the presence of partially separate transcriptional regulatory systems for transition to respiratory growth on each of these two carbon sources. Genes whose expression is affected by loss of Rsf1p, which lacks a known DNA-binding motif, lack a common DNA sequence motif in their upstream regions. These and other data presented here strongly suggest that the transcriptional effects exerted by Rsf1p are mediated via interaction with other transcription factors.

Genetic interactions between transcription factors cause natural variation in yeast

Our understanding of the genetic basis of phenotypic diversity is limited by the paucity of examples in which multiple, interacting loci have been identified. We show that natural variation in the efficiency of sporulation, the program in yeast that initiates the sexual phase of the life cycle, between oak tree and vineyard strains is due to allelic variation between four nucleotide changes in three transcription factors: IME1, RME1, and RSF1. Furthermore, we identified that selection has shaped quantitative variation in yeast sporulation between strains. These results illustrate how genetic interactions between transcription factors are a major source of phenotypic diversity within species.

The YJR127C/ZMS1 gene product is involved in glycerol-based respiratory growth of the yeast Saccharomyces cerevisiae

A putative yeast mitochondrial upstream activating sequence (UAS) was used in a one-hybrid screening procedure that identified the YJR127C ORF on chromosome X. This gene was previously designated ZMS1 and is listed as a transcription factor on the SGD website. Real time RT-PCR assays showed that expression of YJR127C/ZMS1 was glucose-repressible, and a deletion mutant for the gene showed a growth defect on glycerol-based but not on glucose- or ethanol-based medium. Real time RT-PCR analyses identified severely attenuated transcript levels from GUT1 and GUT2 to be the source of that growth defect, the products of GUT1 and GUT2 are required for glycerol utilization. mRNA levels from a large group of mitochondria- and respiration-related nuclear genes also were shown to be attenuated in the deletion mutant. Importantly, transcript levels from the mitochondrial OLI1 gene, which has an associated organellar UAS, were attenuated in the DeltaYJR127C mutant during glycerol-based growth, but those from COX3 (OXI2), which lacks an associated mitochondrial UAS, were not. Transcriptome analysis of the glycerol-grown deletion mutant showed that genes in several metabolic and other categories are affected by loss of this gene product, including protein transport, signal transduction, and others. Thus, the product of YJR127C/ZMS1 is involved in transcriptional control for genes in both cellular genetic compartments, many of which specify products required for glycerol-based growth, respiration, and other functions.

Comparative analysis of promoter regions containing binding sites of the heterodimeric transcription factor Ino2/Ino4 involved in yeast phospholipid biosynthesis

The inositol/choline responsive element (ICRE) functions as a UAS element mediating coordinate expression of structural genes required for yeast phospholipid biosynthesis. However, ICRE motifs could be detected upstream of various genes apparently not involved in lipid metabolism. In this work we investigated the expression pattern of selected genes containing ICRE promoter motifs, as identified by in silico analysis (ARG4, ERG20, FAR8, GPD2, RSF1, URA8, VHT1 and YEL073C). It turned out that the presence of an ICRE upstream of a gene of unknown function indeed allows to conclude for regulation by phospholipid precursors, which is mediated by activators Ino2/Ino4 and the repressor Opi1. We also demonstrated in vitro binding of Ino2/Ino4 heterodimers to promoter regions. Thus, our analysis supports the view that identification of regulatory elements by a database search provides evidence for a specific pattern of gene expression. Activation by pathway-specific regulators may suggest a physiological function for as yet uncharacterized genes.