Mast Cell-Derived Histamine Regulates Liver Ketogenesis via Oleoylethanolamide Signaling

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Precipitation and predation risk alter the diversity and behavior of pollinators and reduce plant fitness

Biotic and abiotic factors may individually or interactively disrupt plant–pollinator interactions, influencing plant fitness. Although variations in temperature and precipitation are expected to modify the overall impact of predators on plant–pollinator interactions, few empirical studies have assessed if these weather conditions influence anti-predator behaviors and how this context-dependent response may cascade down to plant fitness. To answer this question, we manipulated predation risk (using artificial spiders) in different years to investigate how natural variation in temperature and precipitation may affect diversity (richness and composition) and behavioral (visitation) responses of flower-visiting insects to predation risk, and how these effects influence plant fitness. Our findings indicate that predation risk and an increase in precipitation independently reduced plant fitness (i.e., seed set) by decreasing flower visitation. Predation risk reduced pollinator visitation and richness, and altered species composition of pollinators. Additionally, an increase in precipitation was associated with lower flower visitation and pollinator richness but did not alter pollinator species composition. However, maximum daily temperature did not affect any component of the pollinator assemblage or plant fitness. Our results indicate that biotic and abiotic drivers have different impacts on pollinator behavior and diversity with consequences for plant fitness components. Even small variation in precipitation conditions promotes complex and substantial cascading effects on plants by affecting both pollinator communities and the outcome of plant–pollinator interactions. Tropical communities are expected to be highly susceptible to climatic changes, and these changes may have drastic consequences for biotic interactions in the tropics.     

Evaluation of the WHO classification of dengue disease severity during an epidemic in 2011 in the state of Ceará, Brazil

In 2009, the World Health Organization (WHO) issued a new guideline that stratifies dengue-affected patients into severe (SD) and non-severe dengue (NSD) (with or without warning signs). To evaluate the new recommendations, we completed a retrospective cross-sectional study of the dengue haemorrhagic fever (DHF) cases reported during an outbreak in 2011 in northeastern Brazil. We investigated 84 suspected DHF patients, including 45 (53.6%) males and 39 (46.4%) females. The ages of the patients ranged from five-83 years and the median age was 29. According to the DHF/dengue shock syndrome classification, 53 (63.1%) patients were classified as having dengue fever and 31 (36.9%) as having DHF. According to the 2009 WHO classification, 32 (38.1%) patients were grouped as having NSD [4 (4.8%) without warning signs and 28 (33.3%) with warning signs] and 52 (61.9%) as having SD. A better performance of the revised classification in the detection of severe clinical manifestations allows for an improved detection of patients with SD and may reduce deaths. The revised classification will not only facilitate effective screening and patient management, but will also enable the collection of standardised surveillance data for future epidemiological and clinical studies.     

The mitochondrial genome of Moniliophthora roreri, the frosty pod rot pathogen of cacao

In this study, we report the sequence of the mitochondrial (mt) genome of the Basidiomycete fungus Moniliophthora roreri, which is the etiologic agent of frosty pod rot of cacao (Theobroma cacao L.). We also compare it to the mtDNA from the closely-related species Moniliophthora perniciosa, which causes witches' broom disease of cacao. The 94 Kb mtDNA genome of M. roreri has a circular topology and codes for the typical 14 mt genes involved in oxidative phosphorylation. It also codes for both rRNA genes, a ribosomal protein subunit, 13 intronic open reading frames (ORFs), and a full complement of 27 tRNA genes. The conserved genes of M. roreri mtDNA are completely syntenic with homologous genes of the 109 Kb mtDNA of M. perniciosa. As in M. perniciosa, M. roreri mtDNA contains a high number of hypothetical ORFs (28), a remarkable feature that make Moniliophthoras the largest reservoir of hypothetical ORFs among sequenced fungal mtDNA. Additionally, the mt genome of M. roreri has three free invertron-like linear mt plasmids, one of which is very similar to that previously described as integrated into the main M. perniciosa mtDNA molecule. Moniliophthora roreri mtDNA also has a region of suspected plasmid origin containing 15 hypothetical ORFs distributed in both strands. One of these ORFs is similar to an ORF in the mtDNA gene encoding DNA polymerase in Pleurotus ostreatus. The comparison to M. perniciosa showed that the 15 Kb difference in mtDNA sizes is mainly attributed to a lower abundance of repetitive regions in M. roreri (5.8 Kb vs 20.7 Kb). The most notable differences between M. roreri and M. perniciosa mtDNA are attributed to repeats and regions of plasmid origin. These elements might have contributed to the rapid evolution of mtDNA. Since M. roreri is the second species of the genus Moniliophthora whose mtDNA genome has been sequenced, the data presented here contribute valuable information for understanding the evolution of fungal mt genomes among closely-related species.     

Time is on our side: the importance of considering a recovery period when assessing flooding tolerance in plants

There is wide consensus about the significance of monitoring plant responses during flooding when evaluating specific tolerance. Nonetheless, plant recovery once water recedes has often been overlooked. This note highlights the importance of registering plant performance during a recovery phase. Two opposite types of plant growth responses, during and after flooding, are discussed. It is shown that an apparently poor performance during flooding does not necessarily involve a reduced tolerance, as plants can prioritize saving energy and carbohydrates for later resumption of vigorous growth during recovery. Conversely, maintenance of positive plant growth during flooding can imply extensive depletion of reserves, consequently constraining future plant growth. Therefore, to accurately estimate real tolerance to this stress, plant performance should be appraised during both flooding and recovery periods.     

Outcrossing potential between 11 important genetically modified crops and the Chilean vascular flora

The potential impact of genetically modified (GM) crops on biodiversity is one of the main concerns in an environmental risk assessment (ERA). The likelihood of outcrossing and pollen‐mediated gene flow from GM crops and non‐GM crops are explained by the same principles and depend primarily on the biology of the species. We conducted a national‐scale study of the likelihood of outcrossing between 11 GM crops and vascular plants in Chile by use of a systematized database that included cultivated, introduced and native plant species in Chile. The database included geographical distributions and key biological and agronomical characteristics for 3505 introduced, 4993 native and 257 cultivated (of which 11 were native and 246 were introduced) plant species. Out of the considered GM crops (cotton, soya bean, maize, grape, wheat, rice, sugar beet, alfalfa, canola, tomato and potato), only potato and tomato presented native relatives (66 species total). Introduced relative species showed that three GM groups were formed having: a) up to one introduced relative (cotton and soya bean), b) up to two (rice, grape, maize and wheat) and c) from two to seven (sugar beet, alfalfa, canola, tomato and potato). In particular, GM crops presenting introduced noncultivated relative species were canola (1 relative species), alfalfa (up to 4), rice (1), tomato (up to 2) and potato (up to 2). The outcrossing potential between species [OP; scaled from ‘very low’ (1) to ‘very high’ (5)] was developed, showing medium OPs (3) for GM–native relative interactions when they occurred, low (2) for GMs and introduced noncultivated and high (4) for the grape‐Vitis vinifera GM–introduced cultivated interaction. This analytical tool might be useful for future ERA for unconfined GM crop release in Chile.     

Beyond missing heritability: prediction of complex traits

Despite rapid advances in genomic technology, our ability to account for phenotypic variation using genetic information remains limited for many traits. This has unfortunately resulted in limited application of genetic data towards preventive and personalized medicine, one of the primary impetuses of genome-wide association studies. Recently, a large proportion of the "missing heritability" for human height was statistically explained by modeling thousands of single nucleotide polymorphisms concurrently. However, it is currently unclear how gains in explained genetic variance will translate to the prediction of yet-to-be observed phenotypes. Using data from the Framingham Heart Study, we explore the genomic prediction of human height in training and validation samples while varying the statistical approach used, the number of SNPs included in the model, the validation scheme, and the number of subjects used to train the model. In our training datasets, we are able to explain a large proportion of the variation in height (h(2) up to 0.83, R(2) up to 0.96). However, the proportion of variance accounted for in validation samples is much smaller (ranging from 0.15 to 0.36 depending on the degree of familial information used in the training dataset). While such R(2) values vastly exceed what has been previously reported using a reduced number of pre-selected markers (<0.10), given the heritability of the trait (～ 0.80), substantial room for improvement remains.     

Non-linear models based on simple topological indices to identify RNase III protein members

Alignment-free classifiers are especially useful in the functional classification of protein classes with variable homology and different domain structures. Thus, the Topological Indices to BioPolymers (TI2BioP) methodology (Agüero-Chapin et al., 2010) inspired in both the TOPS-MODE and the MARCH-INSIDE methodologies allows the calculation of simple topological indices (TIs) as alignment-free classifiers. These indices were derived from the clustering of the amino acids into four classes of hydrophobicity and polarity revealing higher sequence-order information beyond the amino acid composition level. The predictability power of such TIs was evaluated for the first time on the RNase III family, due to the high diversity of its members (primary sequence and domain organization). Three non-linear models were developed for RNase III class prediction: Decision Tree Model (DTM), Artificial Neural Networks (ANN)-model and Hidden Markov Model (HMM). The first two are alignment-free approaches, using TIs as input predictors. Their performances were compared with a non-classical HMM, modified according to our amino acid clustering strategy. The alignment-free models showed similar performances on the training and the test sets reaching values above 90% in the overall classification. The non-classical HMM showed the highest rate in the classification with values above 95% in training and 100% in test. Although the higher accuracy of the HMM, the DTM showed simplicity for the RNase III classification with low computational cost. Such simplicity was evaluated in respect to HMM and ANN models for the functional annotation of a new bacterial RNase III class member, isolated and annotated by our group.