Adaptation of Saccharomyces cerevisiae Cells to High Ethanol Concentration and Changes in Fatty Acid Composition of Membrane and Cell Size

BACKGROUND: Microorganisms can adapt to perturbations of the surrounding environment to grow. To analyze the adaptation process of the yeast Saccharomyces cerevisiae to a high ethanol concentration, repetitive cultivation was performed with a stepwise increase in the ethanol concentration in the culture medium. METHODOLOGY/PRINCIPAL FINDINGS: First, a laboratory strain of S. cerevisiae was cultivated in medium containing a low ethanol concentration, followed by repetitive cultivations. Then, the strain repeatedly cultivated in the low ethanol concentration was transferred to medium containing a high ethanol concentration and cultivated repeatedly in the same high-ethanol-concentration medium. When subjected to a stepwise increase in ethanol concentration with the repetitive cultivations, the yeast cells adapted to the high ethanol concentration; the specific growth rate of the adapted yeast strain did not decrease during repetitive cultivation in the medium containing the same ethanol concentration, while that of the non-adapted strain decreased during repetitive cultivation. A comparison of the fatty acid composition of the cell membrane showed that the contents in oleic acid (C(18:1)) in ethanol-adapted and non-adapted strains were similar, but the content of palmitic acid (C(16:0)) in the ethanol-adapted strains was lower than that in the non-adapted strain in media containing ethanol. Moreover, microscopic observation showed that the mother cells of the adapted yeast were significantly larger than those of the non-adapted strain. CONCLUSIONS: Our results suggest that activity of cell growth defined by specific growth rate of the yeast cells adapted to stepwise increase in ethanol concentration did not decrease during repetitive cultivation in high-ethanol-concentration medium. Moreover, fatty acid content of cell membrane and the size of ethanol-adapted yeast cells were changed during adaptation process. Those might be the typical phenotypes of yeast cells adapted to high ethanol concentration. In addition, the difference in sizes of the mother cell between the non-adapted and ethanol strains suggests that the cell size, cell cycle and adaptation to ethanol are thought to be closely correlated

G = MAT: Linking Transcription Factor Expression and DNA Binding Data

Transcription factors are proteins that bind to motifs on the DNA and thus affect gene expression regulation. The qualitative description of the corresponding processes is therefore important for a better understanding of essential biological mechanisms. However, wet lab experiments targeted at the discovery of the regulatory interplay between transcription factors and binding sites are expensive. We propose a new, purely computational method for finding putative associations between transcription factors and motifs. This method is based on a linear model that combines sequence information with expression data. We present various methods for model parameter estimation and show, via experiments on simulated data, that these methods are reliable. Finally, we examine the performance of this model on biological data and conclude that it can indeed be used to discover meaningful associations. The developed software is available as a web tool and Scilab source code at http://biit.cs.ut.ee/gmat/

Predicting Cellular Growth from Gene Expression Signatures

Maintaining balanced growth in a changing environment is a fundamental systems-level challenge for cellular physiology, particularly in microorganisms. While the complete set of regulatory and functional pathways supporting growth and cellular proliferation are not yet known, portions of them are well understood. In particular, cellular proliferation is governed by mechanisms that are highly conserved from unicellular to multicellular organisms, and the disruption of these processes in metazoans is a major factor in the development of cancer. In this paper, we develop statistical methodology to identify quantitative aspects of the regulatory mechanisms underlying cellular proliferation in Saccharomyces cerevisiae. We find that the expression levels of a small set of genes can be exploited to predict the instantaneous growth rate of any cellular culture with high accuracy. The predictions obtained in this fashion are robust to changing biological conditions, experimental methods, and technological platforms. The proposed model is also effective in predicting growth rates for the related yeast Saccharomyces bayanus and the highly diverged yeast Schizosaccharomyces pombe, suggesting that the underlying regulatory signature is conserved across a wide range of unicellular evolution. We investigate the biological significance of the gene expression signature that the predictions are based upon from multiple perspectives: by perturbing the regulatory network through the Ras/PKA pathway, observing strong upregulation of growth rate even in the absence of appropriate nutrients, and discovering putative transcription factor binding sites, observing enrichment in growth-correlated genes. More broadly, the proposed methodology enables biological insights about growth at an instantaneous time scale, inaccessible by direct experimental methods. Data and tools enabling others to apply our methods are available at http://function.princeton.edu/growthrate

Stochastic and Regulatory Role of Chromatin Silencing in Genomic Response to Environmental Changes

Phenotypic diversity and fidelity can be balanced by controlling stochastic molecular mechanisms. Epigenetic silencing is one that has a critical role in stress response. Here we show that in yeast, incomplete silencing increases stochastic noise in gene expression, probably owing to unstable chromatin structure. Telomere position effect is suggested as one mechanism. Expression diversity in a population achieved in this way may render a subset of cells to readily respond to various acute stresses. By contrast, strong silencing tends to suppress noisy expression of genes, in particular those involved in life cycle control. In this regime, chromatin may act as a noise filter for precisely regulated responses to environmental signals that induce huge phenotypic changes such as a cell fate transition. These results propose modulation of chromatin stability as an important determinant of environmental adaptation and cellular differentiation

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

Proteomic and Physiological Responses of Kineococcus radiotolerans to Copper

Copper is a highly reactive, toxic metal; consequently, transport of this metal within the cell is tightly regulated. Intriguingly, the actinobacterium Kineococcus radiotolerans has been shown to not only accumulate soluble copper to high levels within the cytoplasm, but the phenotype also correlated with enhanced cell growth during chronic exposure to ionizing radiation. This study offers a first glimpse into the physiological and proteomic responses of K. radiotolerans to copper at increasing concentration and distinct growth phases. Aerobic growth rates and biomass yields were similar over a range of Cu(II) concentrations (0–1.5 mM) in complex medium. Copper uptake coincided with active cell growth and intracellular accumulation was positively correlated with Cu(II) concentration in the growth medium (R2 = 0.7). Approximately 40% of protein coding ORFs on the K. radiotolerans genome were differentially expressed in response to the copper treatments imposed. Copper accumulation coincided with increased abundance of proteins involved in oxidative stress and defense, DNA stabilization and repair, and protein turnover. Interestingly, the specific activity of superoxide dismutase was repressed by low to moderate concentrations of copper during exponential growth, and activity was unresponsive to perturbation with paraquot. The biochemical response pathways invoked by sub-lethal copper concentrations are exceptionally complex; though integral cellular functions are preserved, in part, through the coordination of defense enzymes, chaperones, antioxidants and protective osmolytes that likely help maintain cellular redox. This study extends our understanding of the ecology and physiology of this unique actinobacterium that could potentially inspire new biotechnologies in metal recovery and sequestration, and environmental restoration

Hybridization and adaptive evolution of diverse Saccharomyces species for cellulosic biofuel production

Additional file 15. Summary of whole genome sequencing statistics