Genome-wide analysis of the yeast transcriptome upon heat and cold shock

The ABC transporter Pdr18 is required for yeast thermotolerance due to its role in ergosterol transport and plasma membrane properties

Among the mechanisms by which yeast overcomes multiple stresses is the expression of genes encoding ATP-binding cassette (ABC) transporters required for resistance to a wide range of toxic compounds. These substrates may include weak acids, alcohols, agricultural pesticides, polyamines, metal cations, as in the case of Pdr18. This pleotropic drug resistance transporter was previously proposed to transport ergosterol at the plasma membrane (PM) level contributing to the maintenance of PM lipid organization and reduced diffusional permeation induced by lipophilic compounds. The present work reports a novel phenotype associated with the putative drug/xenobiotic-efflux-pump transporter Pdr18: the resistance to heat shock and to long-term growth at supra-optimal temperatures. Cultivation at 40°C was demonstrated to lead to higher PM permeabilization of a pdr18Δ cell population with the PDR18 gene deleted compared with the parental strain population, as indicated by flow cytometry analysis of propidium iodide stained cells. Cells of pdr18Δ grown at 40°C also exhibited increased transcription levels from genes of the ergosterol biosynthetic pathway, compared with parental cells. However, this adaptive response at 40°C was not enough to maintain PM physiological ergosterol levels in the population lacking the Pdr18 transporter and free ergosterol precursors accumulate in the deletion mutant cells.

Differential proteomic analysis by SWATH-MS unravels the most dominant mechanisms underlying yeast adaptation to non-optimal temperatures under anaerobic conditions

Elucidation of temperature tolerance mechanisms in yeast is essential for enhancing cellular robustness of strains, providing more economically and sustainable processes. We investigated the differential responses of three distinct Saccharomyces cerevisiae strains, an industrial wine strain, ADY5, a laboratory strain, CEN.PK113-7D and an industrial bioethanol strain, Ethanol Red, grown at sub- and supra-optimal temperatures under chemostat conditions. We employed anaerobic conditions, mimicking the industrial processes. The proteomic profile of these strains in all conditions was performed by sequential window acquisition of all theoretical spectra-mass spectrometry (SWATH-MS), allowing the quantification of 997 proteins, data available via ProteomeXchange (PXD016567). Our analysis demonstrated that temperature responses differ between the strains; however, we also found some common responsive proteins, revealing that the response to temperature involves general stress and specific mechanisms. Overall, sub-optimal temperature conditions involved a higher remodeling of the proteome. The proteomic data evidenced that the cold response involves strong repression of translation-related proteins as well as induction of amino acid metabolism, together with components related to protein folding and degradation while, the high temperature response mainly recruits amino acid metabolism. Our study provides a global and thorough insight into how growth temperature affects the yeast proteome, which can be a step forward in the comprehension and improvement of yeast thermotolerance.

Heat preadaptation improved the ability of Zygosaccharomyces rouxii to salt stress: a combined physiological and transcriptomic analysis

Zygosaccharomyces rouxii plays important roles in the brewing process of fermented foods such as soy sauce, where salt stress is a frequently encountered condition. In this study, effect of heat preadaptation on salt tolerance of Z. rouxii and the protective mechanisms underlying heat preadaptation were investigated based on physiological and transcriptomic analyses. Results showed that cells subjected to heat preadaptation (37 °C, 90 min) prior to salt stress aroused many physiological responses, including maintaining cell surface smooth and intracellular pH level, increasing Na⁺/K⁺-ATPase activity. Cells subjected to heat preadaptation increased the amounts of unsaturated fatty acids (palmitoleic C16:1, oleic C18:1, linoleic C18:2) and decreased the amounts of saturated fatty acids (palmitic C16:0, stearic C18:0) which caused the unsaturation degree (unsaturated/saturated = U/S ratio) increased by 2.4 times when compared with cells without preadaptation under salt stress. Besides, salt stress led to increase in contents of 5 amino acids (valine, proline, threonine, glycine, and tyrosine) and decrease of 2 amino acids (serine and lysine). When comparing the cells pre-exposed to heat preadaptation followed by challenged with salt stress and the cells without preadaptation under salt stress, the serine, threonine, and lysine contents increased significantly. RNA sequencing revealed that the metabolic level of glycolysis by Z. rouxii was weakened, while the metabolic levels of the pentose phosphate pathway and the riboflavin were enhanced in cells during heat preadaptation. Results presented in this study may contribute to understand the bases of adaptive responses in Z. rouxii and rationalize its exploitation in industrial processes.Key points• Heat preadaptation can improve high salinity tolerance of Z. rouxii.• Combined physiological and transcriptomic analyses of heat preadaptation mechanisms.• Provide theoretical support for the application of Z. rouxii.

Rapid Identification of Major QTLS Associated With Near- Freezing Temperature Tolerance in Saccharomyces cerevisiae

Temperatures had a strong effect on many life history traits, including growth, development and reproduction. At near-freezing temperatures (0–4°C), yeast cells could trigger series of biochemical reactions to respond and adapt to the stress, protect them against sever cold and freeze injury. Different Saccharomyces cerevisiae strains vary greatly in their ability to grow at near-freezing temperatures. However, the molecular mechanisms that allow yeast cells to sustain this response are not yet fully understood and the genetic basis of tolerance and sensitivity to near-freeze stress remains unclear. Uncovering the genetic determinants of this trait is, therefore, of is of significant interest. In order to investigate the genetic basis that underlies near-freezing temperature tolerance in S. cerevisiae, we mapped the major quantitative trait loci (QTLs) using bulk segregant analysis (BSA) in the F₂ segregant population of two Chinese indigenous S. cerevisiae strains with divergent tolerance capability at 4°C. By genome-wide comparison of single-nucleotide polymorphism (SNP) profiles between two bulks of segregants with high and low tolerance to near-freezing temperature, a hot region located on chromosome IV was identified tightly associated with the near-freezing temperature tolerance. The Reciprocal hemizygosity analysis (RHA) and gene deletion was used to validate the genes involved in the trait, showed that the gene NAT1 plays a role in the near-freezing temperature tolerance. This study improved our understanding of the genetic basis of the variability of near-freezing temperature tolerance in yeasts. The superior allele identified could be used to genetically improve the near-freezing stress adaptation of industrial yeast strains.

Understanding the Mechanism of Thermotolerance Distinct From Heat Shock Response Through Proteomic Analysis of Industrial Strains of Saccharomyces cerevisiae

Saccharomyces cerevisiae has been intensively studied in responses to different environmental stresses such as heat shock through global omic analysis. However, the S. cerevisiae industrial strains with superior thermotolerance have not been explored in any proteomic studies for elucidating the tolerance mechanism. Recently a new diploid strain was obtained through evolutionary engineering of a parental industrial strain, and it exhibited even higher resistance to prolonged thermal stress. Herein, we performed iTRAQ-based quantitative proteomic analysis on both the parental and evolved industrial strains to further understand the mechanism of thermotolerant adaptation. Out of ∼ 2600 quantifiable proteins from biological quadruplicates, 193 and 204 proteins were differentially regulated in the parental and evolved strains respectively during heat-stressed growth. The proteomic response of the industrial strains cultivated under prolonged thermal stress turned out to be substantially different from that of the laboratory strain exposed to sudden heat shock. Further analysis of transcription factors underlying the proteomic perturbation also indicated the distinct regulatory mechanism of thermotolerance. Finally, a cochaperone Mdj1 and a metabolic enzyme Adh1 were selected to investigate their roles in mediating heat-stressed growth and ethanol production of yeasts. Our proteomic characterization of the industrial strain led to comprehensive understanding of the molecular basis of thermotolerance, which would facilitate future improvement in the industrially important trait of S. cerevisiae by rational engineering.

Defining the response of a microorganism to temperatures that span its complete growth temperature range (-2°C to 28°C) using multiplex quantitative proteomics

The growth of all microorganisms is limited to a specific temperature range. However, it has not previously been determined to what extent global protein profiles change in response to temperatures that incrementally span the complete growth temperature range of a microorganism. As a result it has remained unclear to what extent cellular processes (inferred from protein abundance profiles) are affected by growth temperature and which, in particular, constrain growth at upper and lower temperature limits. To evaluate this, 8-plex iTRAQ proteomics was performed on the Antarctic microorganism, Methanococcoides burtonii. Methanococcoides burtonii was chosen due to its importance as a model psychrophilic (cold-adapted) member of the Archaea, and the fact that proteomic methods, including subcellular fractionation procedures, have been well developed. Differential abundance patterns were obtained for cells grown at seven different growth temperatures (-2°C, 1°C, 4°C, 10°C, 16°C, 23°C, 28°C) and a principal component analysis (PCA) was performed to identify trends in protein abundances. The multiplex analysis enabled three largely distinct physiological states to be described: cold stress (-2°C), cold adaptation (1°C, 4°C, 10°C and 16°C), and heat stress (23°C and 28°C). A particular feature of the thermal extremes was the synthesis of heat- and cold-specific stress proteins, reflecting the important, yet distinct ways in which temperature-induced stress manifests in the cell. This is the first quantitative proteomic investigation to simultaneously assess the response of a microorganism to numerous growth temperatures, including the upper and lower growth temperatures limits, and has revealed a new level of understanding about cellular adaptive responses.

Dynamic transcriptional and metabolic responses in yeast adapting to temperature stress

Understanding the response processes in cellular systems to external perturbations is a central goal of large-scale molecular profiling experiments. We investigated the molecular response of yeast to increased and lowered temperatures relative to optimal reference conditions across two levels of molecular organization: the transcriptome using a whole yeast genome microarray and the metabolome applying the gas chromatography/mass spectrometry (GC/MS) technology with in vivo stable-isotope labeling for accurate relative quantification of a total of 50 different metabolites. The molecular adaptation of yeast to increased or lowered temperatures relative control conditions at both the metabolic and transcriptional level is dominated by temperature-inverted differential regulation patterns of transcriptional and metabolite responses and the temporal response observed to be biphasic. The set of previously described general environmental stress response (ESR) genes showed particularly strong temperature-inverted response patterns. Among the metabolites measured, trehalose was detected to respond strongest to the temperature stress and with temperature-inverted up- and downregulation relative to control, midtemperature conditions. Although associated with the same principal environmental parameter, the two different temperature regimes caused very distinct molecular response patterns at both the metabolite and the transcript level. While pairwise correlations between different transcripts and between different metabolites were found generally preserved under the various conditions, substantial differences were also observed indicative of changed underlying network architectures or modified regulatory relationships. Gene and associated gene functions were identified that are differentially regulated specifically under the gradual stress induction applied here compared to abrupt stress exposure investigated in previous studies, including genes of as of yet unidentified function and genes involved in protein synthesis and energy metabolism.

Stability of metabolic correlations under changing environmental conditions in Escherichia coli--a systems approach

BACKGROUND

Biological systems adapt to changing environments by reorganizing their cellular and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underlying metabolic network.

METHODOLOGY/PRINCIPAL FINDINGS

Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic condition-dependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple observations about the changes of metabolic concentrations. The approach was tested with Escherichia coli as a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diauxie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical pathways, and (3) independently of the response scale, based on their importance in the reorganization of the correlation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response.

CONCLUSIONS/SIGNIFICANCE

Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-based approach does not rely on major changes in concentration to identify metabolites important for stress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.

Systematic interpretation of microarray data using experiment annotations

BACKGROUND

Up to now, microarray data are mostly assessed in context with only one or few parameters characterizing the experimental conditions under study. More explicit experiment annotations, however, are highly useful for interpreting microarray data, when available in a statistically accessible format.

RESULTS

We provide means to preprocess these additional data, and to extract relevant traits corresponding to the transcription patterns under study. We found correspondence analysis particularly well-suited for mapping such extracted traits. It visualizes associations both among and between the traits, the hereby annotated experiments, and the genes, revealing how they are all interrelated. Here, we apply our methods to the systematic interpretation of radioactive (single channel) and two-channel data, stemming from model organisms such as yeast and drosophila up to complex human cancer samples. Inclusion of technical parameters allows for identification of artifacts and flaws in experimental design.

CONCLUSION

Biological and clinical traits can act as landmarks in transcription space, systematically mapping the variance of large datasets from the predominant changes down toward intricate details.