Transcriptional regulatory networks controlling woolliness in peach in response to preharvest gibberellin application and cold storage

BACKGROUND: Postharvest fruit conservation relies on low temperatures and manipulations of hormone metabolism to maintain sensory properties. Peaches are susceptible to chilling injuries, such as ‘woolliness’ that is caused by juice loss leading to a ‘wooly’ fruit texture. Application of gibberellic acid at the initial stages of pit hardening impairs woolliness incidence, however the mechanisms controlling the response remain unknown. We have employed genome wide transcriptional profiling to investigate the effects of gibberellic acid application and cold storage on harvested peaches. RESULTS: Approximately half of the investigated genes exhibited significant differential expression in response to the treatments. Cellular and developmental process gene ontologies were overrepresented among the differentially regulated genes, whereas sequences in cell death and immune response categories were underrepresented. Gene set enrichment demonstrated a predominant role of cold storage in repressing the transcription of genes associated to cell wall metabolism. In contrast, genes involved in hormone responses exhibited a more complex transcriptional response, indicating an extensive network of crosstalk between hormone signaling and low temperatures. Time course transcriptional analyses demonstrate the large contribution of gene expression regulation on the biochemical changes leading to woolliness in peach. CONCLUSION: Overall, our results provide insights on the mechanisms controlling the complex phenotypes associated to postharvest textural changes in peach and suggest that hormone mediated reprogramming previous to pit hardening affects the onset of chilling injuries. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12870-015-0659-2) contains supplementary material, which is available to authorized users

Using Biotic Interaction Networks for Prediction in Biodiversity and Emerging Diseases

Networks offer a powerful tool for understanding and visualizing inter-species ecological and evolutionary interactions. Previously considered examples, such as trophic networks, are just representations of experimentally observed direct interactions. However, species interactions are so rich and complex it is not feasible to directly observe more than a small fraction. In this paper, using data mining techniques, we show how potential interactions can be inferred from geographic data, rather than by direct observation. An important application area for this methodology is that of emerging diseases, where, often, little is known about inter-species interactions, such as between vectors and reservoirs. Here, we show how using geographic data, biotic interaction networks that model statistical dependencies between species distributions can be used to infer and understand inter-species interactions. Furthermore, we show how such networks can be used to build prediction models. For example, for predicting the most important reservoirs of a disease, or the degree of disease risk associated with a geographical area. We illustrate the general methodology by considering an important emerging disease - Leishmaniasis. This data mining methodology allows for the use of geographic data to construct inferential biotic interaction networks which can then be used to build prediction models with a wide range of applications in ecology, biodiversity and emerging diseases

Antifungal activity of amphotericin B conjugated to nanosized magnetite in the treatment of paracoccidioidomycosis

This study reports on in vitro and in vivo tests that sought to assess the antifungal activity of a newly developed magnetic carrier system comprising amphotericin B loaded onto the surface of pre-coated (with a double-layer of lauric acid) magnetite nanoparticles. The in vitro tests compared two drugs; i.e., this newly developed form and free amphotericin B. We found that this nanocomplex exhibited antifungal activity without cytotoxicity to human urinary cells and with low cytotoxicity to peritoneal macrophages. We also evaluated the efficacy of the nanocomplex in experimental paracoccidioidomycosis. BALB/c mice were intratracheally infected with Paracoccidioides brasiliensis and treated with the compound for 30 or 60 days beginning the day after infection. The newly developed amphotericin B coupled with magnetic nanoparticles was effective against experimental paracoccidioidomycosis, and it did not induce clinical, biochemical or histopathological alterations. The nanocomplex also did not induce genotoxic effects in bone marrow cells. Therefore, it is reasonable to believe that amphotericin B coupled to magnetic nanoparticles and stabilized with bilayer lauric acid is a promising nanotool for the treatment of the experimental paracoccidioidomycosis because it exhibited antifungal activity that was similar to that of free amphotericin B, did not induce adverse effects in therapeutic doses and allowed for a reduction in the number of applications

Current and Future Niche of North and Central American Sand Flies (Diptera: Psychodidae) in Climate Change Scenarios

Ecological niche models are useful tools to infer potential spatial and temporal distributions in vector species and to measure epidemiological risk for infectious diseases such as the Leishmaniases. The ecological niche of 28 North and Central American sand fly species, including those with epidemiological relevance, can be used to analyze the vector’s ecology and its association with transmission risk, and plan integrated regional vector surveillance and control programs. In this study, we model the environmental requirements of the principal North and Central American phlebotomine species and analyze three niche characteristics over future climate change scenarios: i) potential change in niche breadth, ii) direction and magnitude of niche centroid shifts, iii) shifts in elevation range. Niche identity between confirmed or incriminated Leishmania vector sand flies in Mexico, and human cases were analyzed. Niche models were constructed using sand fly occurrence datapoints from Canada, USA, Mexico, Guatemala and Belize. Nine non-correlated bioclimatic and four topographic data layers were used as niche components using GARP in OpenModeller. Both B2 and A2 climate change scenarios were used with two general circulation models for each scenario (CSIRO and HadCM3), for 2020, 2050 and 2080. There was an increase in niche breadth to 2080 in both scenarios for all species with the exception of Lutzomyia vexator. The principal direction of niche centroid displacement was to the northwest (64%), while the elevation range decreased greatest for tropical, and least for broad-range species. Lutzomyia cruciata is the only epidemiologically important species with high niche identity with that of Leishmania spp. in Mexico. Continued landscape modification in future climate change will provide an increased opportunity for the geographic expansion of NCA sand flys’ ENM and human exposure to vectors of Leishmaniases