Cocaine Inhibits Dopamine D2 Receptor Signaling via Sigma-1-D2 Receptor Heteromers

Under normal conditions the brain maintains a delicate balance between inputs of reward seeking controlled by neurons containing the D₁-like family of dopamine receptors and inputs of aversion coming from neurons containing the D₂-like family of dopamine receptors. Cocaine is able to subvert these balanced inputs by altering the cell signaling of these two pathways such that D₁ reward seeking pathway dominates. Here, we provide an explanation at the cellular and biochemical level how cocaine may achieve this. Exploring the effect of cocaine on dopamine D₂ receptors function, we present evidence of σ₁ receptor molecular and functional interaction with dopamine D₂ receptors. Using biophysical, biochemical, and cell biology approaches, we discovered that D₂ receptors (the long isoform of the D₂ receptor) can complex with σ₁ receptors, a result that is specific to D₂ receptors, as D₃ and D₄ receptors did not form heteromers. We demonstrate that the σ₁-D₂ receptor heteromers consist of higher order oligomers, are found in mouse striatum and that cocaine, by binding to σ₁ -D₂ receptor heteromers, inhibits downstream signaling in both cultured cells and in mouse striatum. In contrast, in striatum from σ₁ knockout animals these complexes are not found and this inhibition is not seen. Taken together, these data illuminate the mechanism by which the initial exposure to cocaine can inhibit signaling via D₂ receptor containing neurons, destabilizing the delicate signaling balance influencing drug seeking that emanates from the D₁ and D₂ receptor containing neurons in the brain.     

827Spatio-Temporal Quantification of FRET in Living Cells by Fast Time-Domain FLIM: A Comparative Study of Non-Fitting Methods

Förster Resonance Energy Transfer (FRET) measured with Fluorescence Lifetime Imaging Microscopy (FLIM) is a powerful technique to investigate spatio-temporal regulation of protein-protein interactions in living cells. When using standard fitting methods to analyze time domain FLIM, the correct estimation of the FRET parameters requires a high number of photons and therefore long acquisition times which are incompatible with the observation of dynamic protein-protein interactions. Recently, non-fitting strategies have been developed for the analysis of FLIM images: the polar plot or “phasor” and the minimal fraction of interacting donor mf_D. We propose here a novel non-fitting strategy based on the calculation of moments. We then compare the performance of these three methods when shortening the acquisition time: either by reducing the number of counted photons N or the number of temporal channels N_ch, which is particularly adapted for the original fast-FLIM prototype presented in this work that employs the time gated approach. Based on theoretical calculations, Monte Carlo simulations and experimental data, we determine the domain of validity of each method. We thus demonstrate that the polar approach remains accurate for a large range of conditions (low N, N_ch or small fractions of interacting donor f_D). The validity domain of the moments method is more restricted (not applicable when f_D<0.25 or when N_ch = 4) but it is more precise than the polar approach. We also demonstrate that the mf_D is robust in all conditions and it is the most precise strategy; although it does not strictly provide the fraction of interacting donor. We show using the fast-FLIM prototype (with an acquisition rate up to 1 Hz) that these non-fitting strategies are very powerful for on-line analysis on a standard computer and thus for quantifying automatically the spatio-temporal activation of Rac-GTPase in living cells by FRET.     

Metabolic Flux Analysis during the Exponential Growth Phase of Saccharomyces cerevisiae in Wine Fermentations

As a consequence of the increase in global average temperature, grapes with the adequate phenolic and aromatic maturity tend to be overripe by the time of harvest, resulting in increased sugar concentrations and imbalanced C/N ratios in fermenting musts. This fact sets obvious additional hurdles in the challenge of obtaining wines with reduced alcohols levels, a new trend in consumer demands. It would therefore be interesting to understand Saccharomyces cerevisiae physiology during the fermentation of must with these altered characteristics. The present study aims to determine the distribution of metabolic fluxes during the yeast exponential growth phase, when both carbon and nitrogen sources are in excess, using continuous cultures. Two different sugar concentrations were studied under two different winemaking temperature conditions. Although consumption and production rates for key metabolites were severely affected by the different experimental conditions studied, the general distribution of fluxes in central carbon metabolism was basically conserved in all cases. It was also observed that temperature and sugar concentration exerted a higher effect on the pentose phosphate pathway and glycerol formation than on glycolysis and ethanol production. Additionally, nitrogen uptake, both quantitatively and qualitatively, was strongly influenced by environmental conditions. This work provides the most complete stoichiometric model used for Metabolic Flux Analysis of S. cerevisiae in wine fermentations employed so far, including the synthesis and release of relevant aroma compounds and could be used in the design of optimal nitrogen supplementation of wine fermentations.     

Polymorphisms in DNA-Repair Genes in a Cohort of Prostate Cancer Patients from Different Areas in Spain: Heterogeneity between Populations as a Confounding Factor in Association Studies

Background

Differences in the distribution of genotypes between individuals of the same ethnicity are an important confounder factor commonly undervalued in typical association studies conducted in radiogenomics.

Objective

To evaluate the genotypic distribution of SNPs in a wide set of Spanish prostate cancer patients for determine the homogeneity of the population and to disclose potential bias.

Design, Setting, and Participants

A total of 601 prostate cancer patients from Andalusia, Basque Country, Canary and Catalonia were genotyped for 10 SNPs located in 6 different genes associated to DNA repair: XRCC1 (rs25487, rs25489, rs1799782), ERCC2 (rs13181), ERCC1 (rs11615), LIG4 (rs1805388, rs1805386), ATM (rs17503908, rs1800057) and P53 (rs1042522). The SNP genotyping was made in a Biotrove OpenArray® NT Cycler.

Outcome Measurements and Statistical Analysis

Comparisons of genotypic and allelic frequencies among populations, as well as haplotype analyses were determined using the web-based environment SNPator. Principal component analysis was made using the SnpMatrix and XSnpMatrix classes and methods implemented as an R package. Non-supervised hierarchical cluster of SNP was made using MultiExperiment Viewer.

Results and Limitations

We observed that genotype distribution of 4 out 10 SNPs was statistically different among the studied populations, showing the greatest differences between Andalusia and Catalonia. These observations were confirmed in cluster analysis, principal component analysis and in the differential distribution of haplotypes among the populations. Because tumor characteristics have not been taken into account, it is possible that some polymorphisms may influence tumor characteristics in the same way that it may pose a risk factor for other disease characteristics.

Conclusion

Differences in distribution of genotypes within different populations of the same ethnicity could be an important confounding factor responsible for the lack of validation of SNPs associated with radiation-induced toxicity, especially when extensive meta-analysis with subjects from different countries are carried out.     

Estimating the success of enzyme bioprospecting through metagenomics: current status and future trends

Recent reports have suggested that the establishment of industrially relevant enzyme collections from environmental genomes has become a routine procedure. Across the studies assessed, a mean number of approximately 44 active clones were obtained in an average size of approximately 53 000 clones tested using naïve screening protocols. This number could be significantly increased in shorter times when novel metagenome enzyme sequences obtained by direct sequencing are selected and subjected to high‐throughput expression for subsequent production and characterization. The pre‐screening of clone libraries by naïve screens followed by the pyrosequencing of the inserts allowed for a 106‐fold increase in the success rate of identifying genes encoding enzymes of interest. However, a much longer time, usually on the order of years, is needed from the time of enzyme identification to the establishment of an industrial process. If the hit frequency for the identification of enzymes performing at high turnover rates under real application conditions could be increased while still covering a high natural diversity, the very expensive and time‐consuming enzyme optimization phase would likely be significantly shortened. At this point, it is important to review the current knowledge about the success of fine‐tuned naïve‐ and sequence‐based screening protocols for enzyme selection and to describe the environments worldwide that have already been subjected to enzyme screen programmes through metagenomic tools. Here, we provide such estimations and suggest the current challenges and future actions needed before environmental enzymes can be successfully introduced into the market.     

Integrating Genetic,Neuropsychological and Neuroimaging Data to Model Early-Onset Obsessive Compulsive Disorder Severity

We propose an integrative approach that combines structural magnetic resonance imaging data (MRI), diffusion tensor imaging data (DTI), neuropsychological data, and genetic data to predict early-onset obsessive compulsive disorder (OCD) severity. From a cohort of 87 patients, 56 with complete information were used in the present analysis. First, we performed a multivariate genetic association analysis of OCD severity with 266 genetic polymorphisms. This association analysis was used to select and prioritize the SNPs that would be included in the model. Second, we split the sample into a training set (N = 38) and a validation set (N = 18). Third, entropy-based measures of information gain were used for feature selection with the training subset. Fourth, the selected features were fed into two supervised methods of class prediction based on machine learning, using the leave-one-out procedure with the training set. Finally, the resulting model was validated with the validation set. Nine variables were used for the creation of the OCD severity predictor, including six genetic polymorphisms and three variables from the neuropsychological data. The developed model classified child and adolescent patients with OCD by disease severity with an accuracy of 0.90 in the testing set and 0.70 in the validation sample. Above its clinical applicability, the combination of particular neuropsychological, neuroimaging, and genetic characteristics could enhance our understanding of the neurobiological basis of the disorder.     

Microsatellite Genotyping of Plasmodium vivax Isolates from Pregnant Women in Four Malaria Endemic Countries

Plasmodium vivax is the most widely distributed human parasite and the main cause of human malaria outside the African continent. However, the knowledge about the genetic variability of P. vivax is limited when compared to the information available for P. falciparum. We present the results of a study aimed at characterizing the genetic structure of P. vivax populations obtained from pregnant women from different malaria endemic settings. Between June 2008 and October 2011 nearly 2000 pregnant women were recruited during routine antenatal care at each site and followed up until delivery. A capillary blood sample from the study participants was collected for genotyping at different time points. Seven P. vivax microsatellite markers were used for genotypic characterization on a total of 229 P. vivax isolates obtained from Brazil, Colombia, India and Papua New Guinea. In each population, the number of alleles per locus, the expected heterozygosity and the levels of multilocus linkage disequilibrium were assessed. The extent of genetic differentiation among populations was also estimated. Six microsatellite loci on 137 P. falciparum isolates from three countries were screened for comparison. The mean value of expected heterozygosity per country ranged from 0.839 to 0.874 for P. vivax and from 0.578 to 0.758 for P. falciparum. P. vivax populations were more diverse than those of P. falciparum. In some of the studied countries, the diversity of P. vivax population was very high compared to the respective level of endemicity. The level of inter-population differentiation was moderate to high in all P. vivax and P. falciparum populations studied.     

Habitat structure influences the song characteristics within a population of Great Tits Parus major

Capsule: The structure of Great Tit Parus major songs is shaped by the acoustic properties of the habitat within the breeding territory of individuals.

Aim: To test whether the structure of the habitat influences song structure within a population of Great Tits P. major.

Methods: We recorded Great Tit songs from 42 territories on two different days and measured the habitat structure in each territory. We also trapped the males and estimated the breeding density around each territory, so were able to control the analysis by date, breeding density and male characteristics.

Results: Song pause length was positively affected by the ground cover, while the song rate and the minimum frequency were negatively affected by the shrub cover. Male size negatively affected the peak frequency of the songs, whereas the age of the males affected the frequency range; older males sang with a broader bandwidth.

Conclusion: This study suggests that Great Tits are capable of adjusting their vocalizations in each territory, presumably to enhance transmission owing to vocal plasticity.     

Acoustic sequences in non‐human animals: a tutorial review and prospectus

Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well‐known example of birdsong, other animals such as insects, amphibians, and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise – let alone understand – the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near‐future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning, quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, ‘Analysing vocal sequences in animals’. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field, across taxa and across disciplines. We also provide a tutorial‐style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality.