The genetic architecture of low-temperature adaptation in the wine yeast Saccharomyces cerevisiae

[Background] Low-temperature growth and fermentation of wine yeast can enhance wine aroma and make them highly desirable traits for the industry. Elucidating response to cold in Saccharomyces cerevisiae is, therefore, of paramount importance to select or genetically improve new wine strains. As most enological traits of industrial importance in yeasts, adaptation to low temperature is a polygenic trait regulated by many interacting loci.[Results] In order to unravel the genetic determinants of low-temperature fermentation, we mapped quantitative trait loci (QTLs) by bulk segregant analyses in the F13 offspring of two Saccharomyces cerevisiae industrial strains with divergent performance at low temperature. We detected four genomic regions involved in the adaptation at low temperature, three of them located in the subtelomeric regions (chromosomes XIII, XV and XVI) and one in the chromosome XIV. The QTL analysis revealed that subtelomeric regions play a key role in defining individual variation, which emphasizes the importance of these regions’ adaptive nature.[Conclusions] The reciprocal hemizygosity analysis (RHA), run to validate the genes involved in low-temperature fermentation, showed that genetic variation in mitochondrial proteins, maintenance of correct asymmetry and distribution of phospholipid in the plasma membrane are key determinants of low-temperature adaptation.This work has been financially supported from the Spanish Government through MINECO and FEDER funds (AGL2013-47300-C3-3-R and PCIN-2015-143 grants) and from Generalitat Valenciana through PROMETEOII/2014/042 grant, awarded to JMG. This study has been carried out in the context of the European Project ERA-IB “YeastTempTation” EGR thanks the Spanish government for an FPI grant BES-2011-044498 and MM also thanks the Generalitat Valenciana for a VALi+d ACIF/2015/194 grant. We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI).Peer reviewe

The Yeast Spore Wall Enables Spores to Survive Passage through the Digestive Tract of Drosophila

In nature, yeasts are subject to predation by flies of the genus Drosophila. In response to nutritional starvation Saccharomyces cerevisiae differentiates into a dormant cell type, termed a spore, which is resistant to many types of environmental stress. The stress resistance of the spore is due primarily to a spore wall that is more elaborate than the vegetative cell wall. We report here that S. cerevisiae spores survive passage through the gut of Drosophila melanogaster. Constituents of the spore wall that distinguish it from the vegetative cell wall are necessary for this resistance. Ascospores of the distantly related yeast Schizosaccharomyces pombe also display resistance to digestion by D. melanogaster. These results suggest that the primary function of the yeast ascospore is as a cell type specialized for dispersion by insect vectors

Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles

Saliva is a readily accessible and informative biofluid, making it ideal for the early detection of a wide range of diseases including cardiovascular, renal, and autoimmune diseases, viral and bacterial infections and, importantly, cancers. Saliva-based diagnostics, particularly those based on metabolomics technology, are emerging and offer a promising clinical strategy, characterizing the association between salivary analytes and a particular disease. Here, we conducted a comprehensive metabolite analysis of saliva samples obtained from 215 individuals (69 oral, 18 pancreatic and 30 breast cancer patients, 11 periodontal disease patients and 87 healthy controls) using capillary electrophoresis time-of-flight mass spectrometry (CE-TOF-MS). We identified 57 principal metabolites that can be used to accurately predict the probability of being affected by each individual disease. Although small but significant correlations were found between the known patient characteristics and the quantified metabolites, the profiles manifested relatively higher concentrations of most of the metabolites detected in all three cancers in comparison with those in people with periodontal disease and control subjects. This suggests that cancer-specific signatures are embedded in saliva metabolites. Multiple logistic regression models yielded high area under the receiver-operating characteristic curves (AUCs) to discriminate healthy controls from each disease. The AUCs were 0.865 for oral cancer, 0.973 for breast cancer, 0.993 for pancreatic cancer, and 0.969 for periodontal diseases. The accuracy of the models was also high, with cross-validation AUCs of 0.810, 0.881, 0.994, and 0.954, respectively. Quantitative information for these 57 metabolites and their combinations enable us to predict disease susceptibility. These metabolites are promising biomarkers for medical screening

Evolution of reproductive development in the volvocine algae

The evolution of multicellularity, the separation of germline cells from sterile somatic cells, and the generation of a male–female dichotomy are certainly among the greatest innovations of eukaryotes. Remarkably, phylogenetic analysis suggests that the shift from simple to complex, differentiated multicellularity was not a unique progression in the evolution of life, but in fact a quite frequent event. The spheroidal green alga Volvox and its close relatives, the volvocine algae, span the full range of organizational complexity, from unicellular and colonial genera to multicellular genera with a full germ–soma division of labor and male–female dichotomy; thus, these algae are ideal model organisms for addressing fundamental issues related to the transition to multicellularity and for discovering universal rules that characterize this transition. Of all living species, Volvox carteri represents the simplest version of an immortal germline producing specialized somatic cells. This cellular specialization involved the emergence of mortality and the production of the first dead ancestors in the evolution of this lineage. Volvocine algae therefore exemplify the evolution of cellular cooperation from cellular autonomy. They also serve as a prime example of the evolution of complex traits by a few successive, small steps. Thus, we learn from volvocine algae that the evolutionary transition to complex, multicellular life is probably much easier to achieve than is commonly believed

Gene-expression profiling of peripheral blood mononuclear cells in sepsis

OBJECTIVES:: It has been shown that gene-expression profiling of circulating neutrophils could identify signature genes of sepsis. However, whether similar transcriptional changes occurred in peripheral blood mononuclear cells (PBMC) was not known. Using microarray technology, we performed gene-expression profiling of PBMC to identify signature genes that distinguish sepsis from noninfectious causes of systemic inflammatory response syndrome (SIRS), between Gram-positive and Gram-negative sepsis. DESIGN:: A cross-sectional, observational study. SETTING:: A 20-bed general intensive care unit of a tertiary referral hospital. PATIENTS:: Seventy critically ill patients (46 sepsis and 24 SIRS). INTERVENTIONS:: Intravenous blood was collected for leukocyte separation and RNA extraction. Gene-expression profiling was performed on PBMC using Affymetrix GeneChip microarrays with 54,675 transcripts. Data were divided into a training set (n = 35) and a validation set (n = 35). A molecular signature was developed in the training set using support vector machine and was then validated in the validation set. MEASUREMENTS AND MAIN RESULTS:: We identified a molecular signature of 138 genes that could differentiate between sepsis and SIRS patients with 91% and 80% accuracy in the training and validation sets, respectively. There were no signature genes that could differentiate between Gram-positive and Gram-negative sepsis. The expression of genes involved in inflammatory response and immune function was significantly reduced in septic patients when compared with those with SIRS. Genes involved in apoptosis, on the other hand, were more highly expressed in septic patients. CONCLUSION:: There was evidence of sepsis-related immunosuppression and reduced inflammatory response in mononuclear cells on a transcriptome level. These characteristic transcriptional changes can be used to aid the diagnosis of sepsis. © 2009 by the Society of Critical Care Medicine and Lippincott Williams & Wilkins

Cell cycle sensing of oxidative stress in Saccharomyces cerevisiae by oxidation of a specific cysteine residue in the transcription factor Swi6p

Yeast cells begin to bud and enter S phase when growth conditions are favourable during G1 phase. When subjected to some oxidative stresses, cells delay entry at G1 allowing repair of cellular damage. Hence, oxidative stress sensing is coordinated with the regulation of cell cycle. We identified a novel function of the cell-cycle regulator of Saccharomyces cerevisiae, Swi6p, as a redox sensor through its cysteine residue at position 404. When alanine was substituted at this position, the resultant mutant, C404A, was sensitive to several reactive oxygen species and oxidants including linoleic acid hydroperoxide, the superoxide anion and diamide. This mutant lost the ability to arrest in G1 phase upon treatment with lipid hydroperoxide. The Cys404 residue of Swi6p in wild-type cells was oxidised to a sulfenic acid when cells were subjected to linoleic acid hydroperoxide. Mutation of Cys404 to Ala abolished the down-regulation of expression of the G1 cyclin genes CLN1, CLN2, PCL1 and PCL2 that occurred when cells of the wild type were exposed to the lipid hydroperoxide. In conclusion, oxidative stress signaling for cell-cycle regulation occurs through oxidation of the G1/S-speicific transcription factor Swi6p and consequently leads to suppression of the expression of G1-cyclins and delay in cells entering the cell cycle