Aspects of Multicellularity in Saccharomyces cerevisiae Yeast: A Review of Evolutionary and Physiological Mechanisms

Gaining insights into the responses of individual yeast cells to ethanol fermentation using Raman tweezers and chemometrics

Saccharomyces cerevisiae is the most common microbe used for the industrial production of bioethanol, and it encounters various stresses that inhibit cell growth and metabolism during fermentation. However, little is currently known about the physiological changes that occur in individual yeast cells during ethanol fermentation. Therefore, in this work, Raman spectroscopy and chemometric techniques were employed to monitor the metabolic changes of individual yeast cells at distinct stages during high gravity ethanol fermentation. Raman tweezers was used to acquire the Raman spectra of individual yeast cells. Multivariate curve resolution-alternating least squares (MCR-ALS) and principal component analysis were employed to analyze the Raman spectra dataset. MCR-ALS extracted the spectra of proteins, phospholipids, and triacylglycerols and their relative contents in individual cells. Changes in intracellular biomolecules showed that yeast cells undergo three distinct physiological stages during fermentation. In addition, heterogeneity among yeast cells significantly increased in the late fermentation period, and different yeast cells may respond to ethanol stress via different mechanisms. Our findings suggest that the combination of Raman tweezers and chemometrics approaches allows for characterizing the dynamics of molecular components within individual cells. This approach can serve as a valuable tool in investigating the resistance mechanism and metabolic heterogeneity of yeast cells during ethanol fermentation.

Optimal trade-off between boosted tolerance and growth fitness during adaptive evolution of yeast to ethanol shocks

BACKGROUND

The selection of Saccharomyces cerevisiae strains with higher alcohol tolerance can potentially increase the industrial production of ethanol fuel. However, the design of selection protocols to obtain bioethanol yeasts with higher alcohol tolerance poses the challenge of improving industrial strains that are already robust to high ethanol levels. Furthermore, yeasts subjected to mutagenesis and selection, or laboratory evolution, often present adaptation trade-offs wherein higher stress tolerance is attained at the expense of growth and fermentation performance. Although these undesirable side effects are often associated with acute selection regimes, the utility of using harsh ethanol treatments to obtain robust ethanologenic yeasts still has not been fully investigated.

RESULTS

We conducted an adaptive laboratory evolution by challenging four populations (P1-P4) of the Brazilian bioethanol yeast, Saccharomyces cerevisiae PE-2_H4, through 68-82 cycles of 2-h ethanol shocks (19-30% v/v) and outgrowths. Colonies isolated from the final evolved populations (P1c-P4c) were subjected to whole-genome sequencing, revealing mutations in genes enriched for the cAMP/PKA and trehalose degradation pathways. Fitness analyses of the isolated clones P1c-P3c and reverse-engineered strains demonstrated that mutations were primarily selected for cell viability under ethanol stress, at the cost of decreased growth rates in cultures with or without ethanol. Under this selection regime for stress survival, the population P4 evolved a protective snowflake phenotype resulting from BUD3 disruption. Despite marked adaptation trade-offs, the combination of reverse-engineered mutations cyr1A1474T/usv1Δ conferred 5.46% higher fitness than the parental PE-2_H4 for propagation in 8% (v/v) ethanol, with only a 1.07% fitness cost in a culture medium without alcohol. The cyr1A1474T/usv1Δ strain and evolved P1c displayed robust fermentations of sugarcane molasses using cell recycling and sulfuric acid treatments, mimicking Brazilian bioethanol production.

CONCLUSIONS

Our study combined genomic, mutational, and fitness analyses to understand the genetic underpinnings of yeast evolution to ethanol shocks. Although fitness analyses revealed that most evolved mutations impose a cost for cell propagation, combination of key mutations cyr1A1474T/usv1Δ endowed yeasts with higher tolerance for growth in the presence of ethanol. Moreover, alleles selected for acute stress survival comprising the P1c genotype conferred stress tolerance and optimal performance under conditions simulating the Brazilian industrial ethanol production.

The influence of flocculation upon global gene transcription in a yeast CYC8 mutant

The transcriptome from a Saccharomyces cerevisiae tup1 deletion mutant was one of the first comprehensive yeast transcriptomes published. Subsequent transcriptomes from tup1 and cyc8 mutants firmly established the Tup1-Cyc8 complex as predominantly acting as a repressor of gene transcription. However, transcriptomes from tup1/cyc8 gene deletion or conditional mutants would all have been influenced by the striking flocculation phenotypes that these mutants display. In this study, we have separated the impact of flocculation from the transcriptome in a cyc8 conditional mutant to reveal those genes (i) subject solely to Cyc8p-dependent regulation, (ii) regulated by flocculation only and (iii) regulated by Cyc8p and further influenced by flocculation. We reveal a more accurate list of Cyc8p-regulated genes that includes newly identified Cyc8p-regulated genes that were masked by the flocculation phenotype and excludes genes which were indirectly influenced by flocculation and not regulated by Cyc8p. Furthermore, we show evidence that flocculation exerts a complex and potentially dynamic influence upon global gene transcription. These data should be of interest to future studies into the mechanism of action of the Tup1-Cyc8 complex and to studies involved in understanding the development of flocculation and its impact upon cell function.

Food yeasts: occurrence, functions, and stress tolerance in the brewing of fermented foods

With the rapid development of systems biology technology, there is a deeper understanding of the molecular biological mechanisms and physiological characteristics of microorganisms. Yeasts are widely used in the food industry with their excellent fermentation performances. While due to the complex environments of food production, yeasts have to suffer from various stress factors. Thus, elucidating the stress mechanisms of food yeasts and proposing potential strategies to improve tolerance have been widely concerned. This review summarized the recent signs of progress in the variety, functions, and stress tolerance of food yeasts. Firstly, the main food yeasts occurred in fermented foods, and the taxonomy levels are demonstrated. Then, the main functions of yeasts including aroma enhancer, safety performance enhancer, and fermentation period reducer are discussed. Finally, the stress response mechanisms of yeasts and the strategies to improve the stress tolerance of cells are reviewed. Based on sorting out these related recent researches systematically, we hope that this review can provide help and approaches to further exert the functions of food yeasts and improve food production efficiency.

Antifungal bio-coating of endotracheal tube built by overexpressing the MCP1 gene of Saccharomyces boulardii and employing hydrogel as a "house" to antagonize Candida albicans

BACKGROUND

For some ICU patients, an artificial airway must be established with an endotracheal tube, but Candida albicans can easily adhere to the tube surface and form a biofilm, leading to potentially life threatening fungal infections. Therefore, it is urgent to prevent and reduce C. albicans infections introduced by the endotracheal tube. However, there are few antifungal drugs effective against C. albicans, and each of these drugs may have adverse effects on human cells. Saccharomyces boulardii is regarded as an alternative strategy to inhibit the adhesion of C. albicans, but it is affected by environmental stress. We hypothesized that it is feasible to strengthen the antagonistic ability of S. boulardii via encapsulating and genetically modification.

METHODS

In this study, a bioactive material carrying the overexpressed MCP1 gene of Saccharomyces boulardii was constructed based on one-step photo-crosslinking. This material achieved spatial growth control of S. boulardii by encapsulating each S. boulardii cell within a hydrogel pore. The bioactive material was coated on an endotracheal tube and tested for its ability to inhibit the adhesion of C. albicans. Additionally, the material's antagonistic activity towards C. albicans was evaluated by detecting intracellular Adenosine-triphosphate content, reactive oxygen species level and the activity of antioxidative enzymes. Tissue invasion experiment was executed to further evaluate the anti-adhesion ability of S. boulardii bio-coating.

RESULTS

Encapsulating the overexpression of MCP1 by S. boulardii in hydrogel pores enhanced the viability of probiotics in the presence of high salt and oxidation stress. When used as the coating of an endotracheal tube, the S. boulardii bioactive material efficiently inhibited the adhesion of C. albicans by impairing the activities of superoxide dismutase and catalase and disturbing mitochondrial functions. In vivo, the S. boulardii bioactive material coating displayed good biocompatibility and reduced the host tissue invasion and virulence of C. albicans.

CONCLUSIONS

The integration of genetic modification and immobilization model breaks the bottleneck of previous application of microorganisms, and provides a new way to prevent fungal infections introduced by endotracheal tubes.

Antibiofilm Effect of Curcumin on Saccharomyces boulardii during Beer Fermentation and Bottle Aging

In a prior study, we elucidated the biofilm formation of Saccharomyces boulardii on glass surfaces during beer bottle aging. Here, we supplemented brewing wort with curcumin at 25 μg/mL concentration to mitigate S. boulardii biofilm and enhance beer's functional and sensory attributes. An assessment encompassing biofilm growth and development, fermentation performance, FLO gene expression, yeast ultrastructure, bioactive content, and consumer acceptance of the beer was conducted throughout fermentation and aging. Crystal violet (CV) and XTT reduction assays unveiled a significant (p < 0.05) reduction in biofilm formation and development. Fluorescent staining (FITC-conA) and imaging with confocal laser scanning microscopy provided visual evidence regarding reduced exopolysaccharide content and biofilm thickness. Transcriptional analyses showed that key adhesins (FLO1, FLO5, FLO9, and FLO10) were downregulated, whereas FLO11 expression remained relatively stable. Although there were initial variations in terms of yeast population and fermentation performance, by day 6, the number of S. boulardii in the test group had almost reached the level of the control group (8.3 log CFU/mL) and remained stable thereafter. The supplementation of brewing wort with curcumin led to a significant (p < 0.05) increase in the beer's total phenolic and flavonoid content. In conclusion, curcumin shows promising potential for use as an additive in beer, offering potential antibiofilm and health benefits without compromising the beer's overall characteristics.

Dynamics of Podospora anserina Genome Evolution in a Long-Term Experiment

The Podospora anserina long-term evolution experiment (PaLTEE) is the only running filamentous fungus study, which is still going on. The aim of our work is to trace the evolutionary dynamics of the accumulation of mutations in the genomes of eight haploid populations of P. anserina. The results of the genome-wide analysis of all of the lineages, performed 8 years after the start of the PaLTEE, are presented. Data analysis detected 312 single nucleotide polymorphisms (SNPs) and 39 short insertion-deletion mutations (indels) in total. There was a clear trend towards a linear increase in the number of SNPs depending on the experiment duration. Among 312 SNPs, 153 were fixed in the coding regions of P. anserina genome. Relatively few synonymous mutations were found, exactly 38; 42 were classified as nonsense mutations; 72 were assigned to missense mutations. In addition, 21 out of 39 indels identified were also localized in coding regions. Here, we also report the detection of parallel evolution at the paralog level in the P. anserina model system. Parallelism in evolution at the level of protein functions also occurs. The latter is especially true for various transcription factors, which may indicate selection leading to optimization of the wide range of cellular processes under experimental conditions.

Metabolic heterogeneity and cross-feeding within isogenic yeast populations captured by DILAC

Genetically identical cells are known to differ in many physiological parameters such as growth rate and drug tolerance. Metabolic specialization is believed to be a cause of such phenotypic heterogeneity, but detection of metabolically divergent subpopulations remains technically challenging. We developed a proteomics-based technology, termed differential isotope labelling by amino acids (DILAC), that can detect producer and consumer subpopulations of a particular amino acid within an isogenic cell population by monitoring peptides with multiple occurrences of the amino acid. We reveal that young, morphologically undifferentiated yeast colonies contain subpopulations of lysine producers and consumers that emerge due to nutrient gradients. Deconvoluting their proteomes using DILAC, we find evidence for in situ cross-feeding where rapidly growing cells ferment and provide the more slowly growing, respiring cells with ethanol. Finally, by combining DILAC with fluorescence-activated cell sorting, we show that the metabolic subpopulations diverge phenotypically, as exemplified by a different tolerance to the antifungal drug amphotericin B. Overall, DILAC captures previously unnoticed metabolic heterogeneity and provides experimental evidence for the role of metabolic specialization and cross-feeding interactions as a source of phenotypic heterogeneity in isogenic cell populations.

Autotoxin-mediated latecomer killing in yeast communities

Cellular adaptation to stressful environments such as starvation is essential to the survival of microbial communities, but the uniform response of the cell community may lead to entire cell death or severe damage to their fitness. Here, we demonstrate an elaborate response of the yeast community against glucose depletion, in which the first adapted cells kill the latecomer cells. During glucose depletion, yeast cells release autotoxins, such as leucic acid and L-2keto-3methylvalerate, which can even kill the clonal cells of the ones producing them. Although these autotoxins were likely to induce mass suicide, some cells differentiated to adapt to the autotoxins without genetic changes. If nondifferentiated latecomers tried to invade the habitat, autotoxins damaged or killed the latecomers, but the differentiated cells could selectively survive. Phylogenetically distant fission and budding yeast shared this behavior using the same autotoxins, suggesting that latecomer killing may be the universal system of intercellular communication, which may be relevant to the evolutional transition from unicellular to multicellular organisms.

Transcriptomics Integrated with Metabolomics: Assessing the Central Metabolism of Different Cells after Cell Differentiation in Aureobasidium pullulans NG

When organisms are stimulated by external stresses, oxidative stress is induced, resulting in the production of large amounts of reactive oxygen species (ROS) that inhibit cell growth and accelerate cellular aging until death. Understanding the molecular mechanisms of abiotic stress is important to enhance cellular resistance, and Aureobasidium pullulans, a highly resistant yeast-like fungus, can use cellular differentiation to resist environmental stress. Here, swollen cells (SCs) from two different differentiation periods in Aureobasidium pullulans NG showed significantly higher antioxidant capacity and stress defense capacity than yeast-like cells (YL). The transcriptome and the metabolome of both cells were analyzed, and the results showed that amino acid metabolism, carbohydrate metabolism, and lipid metabolism were significantly enriched in SCs. Glyoxylate metabolism was significantly upregulated in carbohydrate metabolism, replacing the metabolic hub of the citric acid (TCA) cycle, helping to coordinate multiple metabolic pathways and playing an important role in the resistance of Aureobasidium pullulans NG to environmental stress. Finally, we obtained 10 key genes and two key metabolites in SCs, which provide valuable clues for subsequent validation. In conclusion, these results provide valuable information for assessing central metabolism-mediating oxidative stress in Aureobasidium pullulans NG, and also provide new ideas for exploring the pathways of eukaryotic resistance to abiotic stress.

A pluralistic view of holobionts in the context of process ontology

Developing precise definitions and fine categories is an important part of the scientific endeavour, enabling fidelity of transfers of knowledge and the progress of science. Currently, as a result of research on symbiotic microorganisms, science has been flooded with discoveries which appear to undermine many commonly accepted concepts and to introduce new ones that often require updated conceptualisations. One question currently being debated concerns whether or not a holobiont can be considered an organism. Based on which concept, physiology or evolutionary, of the organism is chosen, the verdict differs. We attempt here to show how a change in perspective, from that of substance ontology into that of process ontology, is capable of reconciling opposing positions within the existing discussion and enabling the implementation of conceptual pluralism.

Genome-wide transcriptional regulation in Saccharomyces cerevisiae in response to carbon dioxide

Sugar metabolism by Saccharomyces cerevisiae produces ample amounts of CO2 under both aerobic and anaerobic conditions. High solubility of CO2 in fermentation media, contributing to enjoyable sensory properties of sparkling wine and beers by S. cerevisiae, might affect yeast metabolism. To elucidate the overlooked effects of CO2 on yeast metabolism, we examined glucose fermentation by S. cerevisiae under CO2 as compared to N2 and O2 limited conditions. While both CO2 and N2 conditions are considered anaerobic, less glycerol and acetate but more ethanol were produced under CO2 condition. Transcriptomic analysis revealed that significantly decreased mRNA levels of GPP1 coding for glycerol-3-phosphate phosphatase in glycerol synthesis explained the reduced glycerol production under CO2 condition. Besides, transcriptional regulations in signal transduction, carbohydrate synthesis, heme synthesis, membrane and cell wall metabolism, and respiration were detected in response to CO2. Interestingly, signal transduction was uniquely regulated under CO2 condition, where up-regulated genes (STE3, MSB2, WSC3, STE12 and TEC1) in the signal sensors and transcriptional factors suggested that MAPK signaling pathway plays a critical role in CO2 sensing and CO2-induced metabolisms in yeast. Our study identifies CO2 as an external stimulus for modulating metabolic activities in yeast and a transcriptional effector for diverse applications.

On the Ecological Significance of Phenotypic Heterogeneity in Microbial Populations Undergoing Starvation

To persist in variable environments, populations of microorganisms have to survive periods of starvation and be able to restart cell division in nutrient-rich conditions. Typically, starvation signals initiate a transition to a quiescent state in a fraction of individual cells, while the rest of the cells remain nonquiescent. It is widely believed that, while quiescent (Q) cells help the population to survive long starvation, the nonquiescent (NQ) cells are a side effect of imperfect transition. We analyzed the regrowth of starved monocultures of Q and NQ cells compared to that of mixed, heterogeneous cultures from simple and complex starvation environments. Our experiments, as well as mathematical modeling, demonstrate that Q monocultures benefit from better survival during long starvation and from a shorter lag phase after resupply of rich medium. However, when the starvation period is very short, the NQ monocultures outperform Q and mixed cultures due to their short lag phase. In addition, only NQ monocultures benefit from complex starvation environments, where nutrient recycling is possible. Our study suggests that phenotypic heterogeneity in starved populations could be a form of bet hedging that is adaptive when environmental determinants, such as the length of the starvation period, the length of the regrowth phase, and the complexity of the starvation environment, vary over time.

IMPORTANCE Nongenetic cell heterogeneity is present in glucose-starved yeast populations in the form of quiescent (Q) and nonquiescent (NQ) phenotypes. There is evidence that Q cells help the population survive long starvation. However, the role of the NQ cell type is not known, and it has been speculated that the NQ phenotype is just a side effect of the imperfect transition to the Q phenotype. Here, we show that, in contrast, there are ecological scenarios in which NQ cells perform better than monocultures of Q cells or naturally occurring mixed populations containing both Q and NQ cells. NQ cells benefit when the starvation period is very short and environmental conditions allow nutrient recycling during starvation. Our experimental and mathematical modeling results suggest a novel hypothesis: the presence of both Q and NQ phenotypes within starved yeast populations may reflect a form of bet hedging where different phenotypes provide fitness advantages depending on the environmental conditions.

Prediction of Genetic Groups within Brettanomyces bruxellensis through Cell Morphology Using a Deep Learning Tool

Brettanomyces bruxellensis is described as a wine spoilage yeast with many mainly strain-dependent genetic characteristics, bestowing tolerance against environmental stresses and persistence during the winemaking process. Thus, it is essential to discriminate B. bruxellensis isolates at the strain level in order to predict their stress resistance capacities. Few predictive tools are available to reveal intraspecific diversity within B. bruxellensis species; also, they require expertise and can be expensive. In this study, a Random Amplified Polymorphic DNA (RAPD) adapted PCR method was used with three different primers to discriminate 74 different B. bruxellensis isolates. High correlation between the results of this method using the primer OPA-09 and those of a previous microsatellite analysis was obtained, allowing us to cluster the isolates among four genetic groups more quickly and cheaply than microsatellite analysis. To make analysis even faster, we further investigated the correlation suggested in a previous study between genetic groups and cell polymorphism using the analysis of optical microscopy images via deep learning. A Convolutional Neural Network (CNN) was trained to predict the genetic group of B. bruxellensis isolates with 96.6% accuracy. These methods make intraspecific discrimination among B. bruxellensis species faster, simpler and less costly. These results open up very promising new perspectives in oenology for the study of microbial ecosystems.

A deep learning framework combined with word embedding to identify DNA replication origins

The DNA replication influences the inheritance of genetic information in the DNA life cycle. As the distribution of replication origins (ORIs) is the major determinant to precisely regulate the replication process, the correct identification of ORIs is significant in giving an insightful understanding of DNA replication mechanisms and the regulatory mechanisms of genetic expressions. For eukaryotes in particular, multiple ORIs exist in each of their gene sequences to complete the replication in a reasonable period of time. To simplify the identification process of eukaryote's ORIs, most of existing methods are developed by traditional machine learning algorithms, and target to the gene sequences with a fixed length. Consequently, the identification results are not satisfying, i.e. there is still great room for improvement. To break through the limitations in previous studies, this paper develops sequence segmentation methods, and employs the word embedding technique, 'Word2vec', to convert gene sequences into word vectors, thereby grasping the inner correlations of gene sequences with different lengths. Then, a deep learning framework to perform the ORI identification task is constructed by a convolutional neural network with an embedding layer. On the basis of the analysis of similarity reduction dimensionality diagram, Word2vec can effectively transform the inner relationship among words into numerical feature. For four species in this study, the best models are obtained with the overall accuracy of 0.975, 0.765, 0.885, 0.967, the Matthew's correlation coefficient of 0.940, 0.530, 0.771, 0.934, and the AUC of 0.975, 0.800, 0.888, 0.981, which indicate that the proposed predictor has a stable ability and provide a high confidence coefficient to classify both of ORIs and non-ORIs. Compared with state-of-the-art methods, the proposed predictor can achieve ORI identification with significant improvement. It is therefore reasonable to anticipate that the proposed method will make a useful high throughput tool for genome analysis.

Hypersensitive SSY1 mutations negatively influence transition to quiescence in yeast Saccharomyces cerevisiae

Most cells spend the majority of their life in the non-proliferating, quiescent state. Transition to this state is crucial for microorganisms to survive long starvation periods and restart divisions afterwards. Experimental evolution allowed us to identify several mutation in genes that are presumably important for such transition in yeast cells. Most of these candidate genes belong to the SPS amino acid sensing pathway or to the SIR complex. We assembled these mutations on the ancestral strain background. Analysis of the quiescent/non-quiescent cell ratio of the starved yeast populations confirmed the crucial role of SSY1, the primary receptor component of the SPS sensor, in transition to the Q state. The evolved SSY1 mutations increased yeast sensitivity to amino acid presence in the environment. This resulted in decreased quiescent cell fraction and a 5.14% increase of the total amino acid content in the starved populations. We discuss external amino acid sensing via the SPS pathway as one of the mechanisms influencing transition to quiescence.