Epicoccum nigrum P16, a Sugarcane Endophyte, Produces Antifungal Compounds and Induces Root Growth

Background: Sugarcane is one of the most important crops in Brazil, mainly because of its use in biofuel production. Recent studies have sought to determine the role of sugarcane endophytic microbial diversity in microorganism-plant interactions, and their biotechnological potential. Epicoccum nigrum is an important sugarcane endophytic fungus that has been associated with the biological control of phytopathogens, and the production of secondary metabolites. In spite of several studies carried out to define the better conditions to use E. nigrum in different crops, little is known about the establishment of an endophytic interaction, and its potential effects on plant physiology. Methodology/Principal Findings: We report an approach based on inoculation followed by re-isolation, molecular monitoring, microscopic analysis, plant growth responses to fungal colonization, and antimicrobial activity tests to study the basic aspects of the E. nigrum endophytic interaction with sugarcane, and the effects of colonization on plant physiology. The results indicate that E. nigrum was capable of increasing the root system biomass and producing compounds that inhibit the in vitro growth of sugarcane pathogens Fusarium verticillioides, Colletotrichum falcatum, Ceratocystis paradoxa, and Xanthomomas albilineans. In addition, E. nigrum preferentially colonizes the sugarcane surface and, occasionally, the endophytic environment. Conclusions/Significance: Our work demonstrates that E. nigrum has great potential for sugarcane crop application because it is capable of increasing the root system biomass and controlling pathogens. The study of the basic aspects of the interaction of E. nigrum with sugarcane demonstrated the facultative endophytism of E. nigrum and its preference for the phylloplane environment, which should be considered in future studies of biocontrol using this species. In addition, this work contributes to the knowledge of the interaction of this ubiquitous endophyte with the host plant, and also to a better use of microbial endophytes in agriculture.State of Sao Paulo Research Foundation (FAPESP)FAPESP (State of Sao Paulo Research Foundation) [02/14143-3, 10/08286-2]Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq

Genomics and epidemiology for gastric adenocarcinomas (GE4GAC): a Brazilian initiative to study gastric cancer

Abstract Gastric cancer (GC) is the fifth most common type of cancer worldwide with high incidences in Asia, Central, and South American countries. This patchy distribution means that GC studies are neglected by large research centers from developed countries. The need for further understanding of this complex disease, including the local importance of epidemiological factors and the rich ancestral admixture found in Brazil, stimulated the implementation of the GE4GAC project. GE4GAC aims to embrace epidemiological, clinical, molecular and microbiological data from Brazilian controls and patients with malignant and pre-malignant gastric disease. In this letter, we summarize the main goals of the project, including subject and sample accrual and current findings

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio