Influence of wine fermentation temperature on the synthesis of yeast-derived volatile aroma compounds

The yeast Saccharomyces cerevisiae synthesises a variety of volatile aroma compounds during wine fermentation. In this study, the influence of fermentation temperature on (1) the production of yeast-derived aroma compounds and (2) the expression of genes involved in aroma compounds’ metabolism (ADH1, PDC1, BAT1, BAT2, LEU2, ILV2, ATF1, ATF2, EHT1 and IAH1) was assessed, during the fermentation of a defined must at 15 and 28°C. Higher concentrations of compounds related to fresh and fruity aromas were found at 15°C, while higher concentrations of flowery related aroma compounds were found at 28°C. The formation rates of volatile aroma compounds varied according to growth stage. In addition, linear correlations between the increases in concentration of higher alcohol and their corresponding acetates were obtained. Genes presented different expression profiles at both temperatures, except ILV2, and those involved in common pathways were co-expressed (ADH1, PDC1 and BAT2; and ATF1, EHT1 and IAH1). These results demonstrate that the fermentation temperature plays an important role in the wine final aroma profile, and is therefore an important control parameter to fine-tune wine quality during winemaking.     

REML estimation of variance parameters in nonlinear mixed effects models using the SAEM algorithm

Nonlinear mixed effects models are now widely used in biometrical studies, especially in pharmacokinetic research or for the analysis of growth traits for agricultural and laboratory species. Most of these studies, however, are often based on ML estimation procedures, which are known to be biased downwards. A few REML extensions have been proposed, but only for approximated methods. The aim of this paper is to present a REML implementation for nonlinear mixed effects models within an exact estimation scheme, based on an integration of the fixed effects and a stochastic estimation procedure. This method was implemented via a stochastic EM, namely the SAEM algorithm. The simulation study showed that the proposed REML estimation procedure considerably reduced the bias observed with the ML estimation, as well as the residual mean squared error of the variance parameter estimations, especially in the unbalanced cases. ML and REML based estimators of fixed effects were also compared via simulation. Although the two kinds of estimates were very close in terms of bias and mean square error, predictions of individual profiles were clearly improved when using REML vs. ML. An application of this estimation procedure is presented for the modelling of growth in lines of chicken.     

Structural insights into the GTPase domain of Escherichia coli MnmE protein

The Escherichia coli MnmE protein is a 50-kDa multidomain GTPase involved in tRNA modification. Its homologues in eukaryotes are crucial for mitochondrial respiration and, thus, it is thought that the human protein might be involved in mitochondrial diseases. Unlike Ras, MnmE shows a high intrinsic GTPase activity and requires effective GTP hydrolysis, and not simply GTP binding, to be functionally active. The isolated MnmE G-domain (165 residues) conserves the GTPase activity of the entire protein, suggesting that it contains the catalytic residues for GTP hydrolysis. To explore the GTP hydrolysis mechanism of MnmE, we analyzed the effect of low pH on binding and hydrolysis of GTP, as well as on the formation of a MnmE transition state mimic. GTP hydrolysis by MnmE, but not GTP binding or formation of a complex with mant-GDP and aluminium fluoride, is impaired at acidic pH, suggesting that the chemistry of the transition state mimic is different to that of the true transition state, and that some residue(s), critical for GTP hydrolysis, is severely affected by low pH. We use a nuclear magnetic resonance (NMR)-based approach to get insights into the MnmE structure and properties. The combined use of NMR restraints and homology structural information allowed the determination of the MnmE G-domain structure in its free form. Chemical shift structure-based prediction provided a good basis for structure refinement and validation. Our data support that MnmE, unlike other GTPases, does not use an arginine finger to drive catalysis, although Arg252 may play a role in stabilization of the transition state.     

Laboratory germination and sea out-planting of tetraspore progeny from <Emphasis Type="Italic">Kappaphycus striatum</Emphasis> (Rhodophyta) in subtropical waters of Brazil

Tetrasporophyte green strains of Kappaphycus striatum introduced from the Philippines and cultivated in the sea at Ubatuba, São Paulo, Brazil, produced tetraspores in pilot mariculture experiments. In the laboratory, the released tetraspores showed high viability and 79% of germination, producing robust plantlets and large differences in morphology. After 5 months under laboratory culture, some of the plantlets that grew best were attached to ropes, transferred into the sea and monitored for 6 months. The results show the potential of the tetraspore progeny for strain selection and the economic feasibility for mariculture of K. striatum with fast adaptation to the sea and satisfactory growth rates of 6.4±0.4 to 4.3±1.2% day^?1.     

Jasmonoyl isoleucine accumulation is needed for abscisic acid build‐up in roots of Arabidopsis under water stress conditions

Phytohormones are central players in sensing and signalling numerous environmental conditions like drought. In this work, hormone profiling together with gene expression of key enzymes involved in abscisic acid (ABA) and jasmonate biosynthesis were studied in desiccating Arabidopsis roots. Jasmonic acid (JA) content transiently increased after stress imposition whereas progressive and concomitant ABA and Jasmonoyl Isoleucine (JA‐Ile) accumulations were detected. Molecular data suggest that, at least, part of the hormonal regulation takes place at the biosynthetic level. These observations also point to a possible involvement of jasmonates on ABA biosynthesis under stress. To test this hypothesis, mutants impaired in jasmonate biosynthesis (opr3, lox6 and jar1‐1) and in JA‐dependent signalling (coi1) were employed. Results showed that the early JA accumulation leading to JA‐Ile build up was necessary for an ABA increase in roots under two different water stress conditions. Signal transduction between water stress‐induced JA‐Ile accumulation and COI1 is necessary for a full induction of the ABA biosynthesis pathway and subsequent hormone accumulation in roots of Arabidopsis plants. The present work adds a level of interaction between jasmonates and ABA at the biosynthetic level.     

Once a land of big wild rivers: specialism is context‐dependent for riparian snails (Pulmonata: Valloniidae) in central Europe

Specialist species may be perceived as such because of their narrow ecological requirements, but this may be context‐dependent. The genus Vallonia (Gastropoda Pulmonata: Valloniidae) includes widespread generalist species and also two specialists endemic to Central Europe: Vallonia suevica, restricted to warm, wet meadows and riverbanks subject to seasonal flooding; and Vallonia declivis, living only in wet to humid meadows, riverbanks, and reedbeds. Both have experienced dramatic declines; as is the case with many land snails, their global conservation status has been underestimated: these species are Critically Endangered. Other congenerics are probably dispersed by birds. In contrast, the distributions of these meadow specialists appear to be the outcome of their strictly riparian habitat coupled with dispersal by fish. Thus, they have tracked drainage changes through the Pleistocene from their origin in the floodplain uplands of the Danube biodiversity hotspot in the Pliocene. Natural dispersal mechanisms have been disrupted, and riparian and river ecosystems have been destroyed throughout Europe. This has led big‐river specialist molluscs and their associated fishes to the brink of extinction. The notion of specialism thus depends on the ecological context; it is useful to stress their non‐invasive character, current restriction to scarce habitats, and evolution under quite different conditions. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015, ●● , ●●–●●.     

Oligomerization and Membrane-binding Properties of Covalent Adducts Formed by the Interaction of α-Synuclein with the Toxic Dopamine Metabolite 3,4-Dihydroxyphenylacetaldehyde (DOPAL)

Oxidative deamination of dopamine produces the highly toxic aldehyde 3,4-dihydroxyphenylacetaldehyde (DOPAL), enhanced production of which is found in post-mortem brains of Parkinson disease patients. When injected into the substantia nigra of rat brains, DOPAL causes the loss of dopaminergic neurons accompanied by the accumulation of potentially toxic oligomers of the presynaptic protein α-synuclein (aS), potentially explaining the synergistic toxicity described for dopamine metabolism and aS aggregation. In this work, we demonstrate that DOPAL interacts with aS via formation of Schiff-base and Michael-addition adducts with Lys residues, in addition to causing oxidation of Met residues to Met-sulfoxide. DOPAL modification leads to the formation of small aS oligomers that may be cross-linked by DOPAL. Both monomeric and oligomeric DOPAL adducts potently inhibit the formation of mature amyloid fibrils by unmodified aS. The binding of aS to either lipid vesicles or detergent micelles, which results in a gain of α-helix structure in its N-terminal lipid-binding domain, protects the protein against DOPAL adduct formation and, consequently, inhibits DOPAL-induced aS oligomerization. Functionally, aS-DOPAL monomer exhibits a reduced affinity for small unilamellar vesicles with lipid composition similar to synaptic vesicles, in addition to diminished membrane-induced α-helical content in comparison with the unmodified protein. These results suggest that DOPAL could compromise the functionality of aS, even in the absence of protein oligomerization, by affecting the interaction of aS with lipid membranes and hence its role in the regulation of synaptic vesicle traffic in neurons.     

Elastic network models for RNA: a comparative assessment with molecular dynamics and SHAPE experiments

Elastic network models (ENMs) are valuable and efficient tools for characterizing the collective internal dynamics of proteins based on the knowledge of their native structures. The increasing evidence that the biological functionality of RNAs is often linked to their innate internal motions poses the question of whether ENM approaches can be successfully extended to this class of biomolecules. This issue is tackled here by considering various families of elastic networks of increasing complexity applied to a representative set of RNAs. The fluctuations predicted by the alternative ENMs are stringently validated by comparison against extensive molecular dynamics simulations and SHAPE experiments. We find that simulations and experimental data are systematically best reproduced by either an all-atom or a three-beads-per-nucleotide representation (sugar-base-phosphate), with the latter arguably providing the best balance of accuracy and computational complexity.     

An argument for mechanism-based statistical inference in cancer

Cancer is perhaps the prototypical systems disease, and as such has been the focus of extensive study in quantitative systems biology. However, translating these programs into personalized clinical care remains elusive and incomplete. In this perspective, we argue that realizing this agenda—in particular, predicting disease phenotypes, progression and treatment response for individuals—requires going well beyond standard computational and bioinformatics tools and algorithms. It entails designing global mathematical models over network-scale configurations of genomic states and molecular concentrations, and learning the model parameters from limited available samples of high-dimensional and integrative omics data. As such, any plausible design should accommodate: biological mechanism, necessary for both feasible learning and interpretable decision making; stochasticity, to deal with uncertainty and observed variation at many scales; and a capacity for statistical inference at the patient level. This program, which requires a close, sustained collaboration between mathematicians and biologists, is illustrated in several contexts, including learning biomarkers, metabolism, cell signaling, network inference and tumorigenesis.     

A snapshot of cancer in Chile: analytical frameworks for developing a cancer policy

Introduction

The South American country Chile now boasts a life expectancy of over 80 years. As a consequence, Chile now faces the increasing social and economic burden of cancer and must implement political policy to deliver equitable cancer care. Hindering the development of a national cancer policy is the lack of comprehensive analysis of cancer infrastructure and economic impact.

Objectives

Evaluate existing cancer policy, the extent of national investigation and the socio-economic impact of cancer to deliver guidelines for the framing of an equitable national cancer policy.

Methods

Burden, research and care-policy systems were assessed by triangulating objective system metrics – epidemiological, economic, etc. – with political and policy analysis. Analysis of the literature and governmental databases was performed. The oncology community was interviewed and surveyed.

Results

Chile utilizes 1% of its gross domestic product on cancer care and treatment. We estimate that the economic impact as measured in Disability Adjusted Life Years to be US$ 3.5 billion. Persistent inequalities still occur in cancer distribution and treatment. A high quality cancer research community is expanding, however, insufficient funding is directed towards disproportionally prevalent stomach, lung and gallbladder cancers.

Conclusions

Chile has a rapidly ageing population wherein 40% smoke, 67% are overweight and 18% abuse alcohol, and thus the corresponding burden of cancer will have a negative impact on an affordable health care system. We conclude that the Chilean government must develop a national cancer strategy, which the authors outline herein and believe is essential to permit equitable cancer care for the country.