Molecular characterization of the gene profile of Bacillus thuringiensis Berliner isolated from Brazilian ecosystems and showing pathogenic activity against mosquito larvae of medical importance

The occurrence of Aedes aegypti, Culex quinquefasciatus, and mosquitoes of the genus Anopheles potentiate the spread of several diseases, such as dengue, Zika, chikungunya, urban yellow fever, filariasis, and malaria, a situation currently existing in Brazil and in Latin America. Control of the disease vectors is the most effective tool for containing the transmission of the pathogens causing these diseases, and the bacterium Bacillus thuringiensis var. israelensis has been widely used and has shown efficacy over many years. However, new B. thuringiensis (Bt) strains with different gene combinations should be sought for use as an alternative to Bti and to prevent the resistant insects selected. Aiming to identify diversity in the Bt in different Brazilian ecosystems and to assess the pathogenicity of this bacterium to larvae of Ae. aegypti, C. quinquefasciatus, and Anopheles darlingi, Bt strains were obtained from the Amazon, Caatinga (semi-arid region), and Cerrado (Brazilian savanna) biomes and tested in pathogenicity bioassays in third-instar larvae of Ae. aegypti under controlled conditions in the laboratory. The isolates with larvicidal activity to larvae of Ae. aegypti were used in bioassays with the larvae of C. quinquefasciatus and An. darlingi and characterized according to the presence of 14 cry genes (cry1, cry2, cry4, cry10, cry11, cry24, cry32, cry44Aa, cry1Ab, cry4Aa, cry4Ba, cry10Aa, cry11Aa, and cry11Ba), six cyt genes (cyt1, cyt2, cyt1Aa, cyt1Ab, cyt2Aa and cyt2Ba), and the chi gene. Four hundred strains of Bt were isolated: 244 from insects, 85 from Amazon soil, and 71 from the Caatinga biome. These strains, in addition to the 153 strains isolated from Cerrado soil and obtained from the Entomopathogenic Bacillus Bank of Maranhão, were tested in bioassays with Ae. aegypti larvae. A total of 37 (6.7%) strains showed larvicidal activity, with positive amplification of the cry, cyt, and chi genes. The most frequently amplified genes were cry4Aa and cry4Ba, both occurring in 59.4% in these strains, followed by cyt1Aa and cyt2Aa, with 56.7% and 48% occurrence, respectively. Twelve (2.2%) strains that presented 100% mortality within 24 h were used in bioassays to estimate the median lethal concentration (LC50) for Ae. aegypti larvae. Two strains (BtMA-690 and BtMA-1114) showed toxicity equal to that of the Bti standard strain, and the same LC50 value (0.003 mg/L) was recorded for the three bacteria after 48 h of exposure. Detection of the presence of the Bt strains that showed pathogenicity for mosquito larvae in the three biomes studied was possible. Therefore, these strains are promising for the control of insect vectors, particularly the BtMA-1114 strain, which presents a gene profile different from that of Bti but with the same toxic effect. © 2017 Elsevier B.V

Congenital Zika syndrome is associated with maternal protein malnutrition

Zika virus (ZIKV) infection during pregnancy is associated with a spectrum of developmental impairments known as congenital Zika syndrome (CZS). The prevalence of this syndrome varies across ZIKV endemic regions, suggesting that its occurrence could depend on cofactors. Here, we evaluate the relevance of protein malnutrition for the emergence of CZS. Epidemiological data from the ZIKV outbreak in the Americas suggest a relationship between undernutrition and cases of microcephaly. To experimentally examine this relationship, we use immunocompetent pregnant mice, which were subjected to protein malnutrition and infected with a Brazilian ZIKV strain. We found that the combination of protein restriction and ZIKV infection leads to severe alterations of placental structure and embryonic body growth, with offspring displaying a reduction in neurogenesis and postnatal brain size. RNA-seq analysis reveals gene expression deregulation required for brain development in infected low-protein progeny. These results suggest that maternal protein malnutrition increases susceptibility to CZS.Fil: Barbeito Andrés, Jimena. Universidade Federal do Rio de Janeiro; Brasil. Universidad Nacional Arturo Jauretche. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos; ArgentinaFil: Pezzuto, Paula. Universidade Federal do Rio de Janeiro; BrasilFil: Higa, Luiza. Universidade Federal do Rio de Janeiro; BrasilFil: Dias, André Alves. Universidade Federal do Rio de Janeiro; BrasilFil: Vasconcelos, Janaina. Universidade Federal do Pará; BrasilFil: Santos, T. M. P.. Universidade Federal do Rio de Janeiro; BrasilFil: Ferreira, Jéssica. Universidade Federal do Rio de Janeiro; BrasilFil: Ferreira, R. O.. Universidade Federal do Rio de Janeiro; BrasilFil: Dutra, F. F.. Universidade Federal do Rio de Janeiro; BrasilFil: Rossi, A. D.. Universidade Federal do Rio de Janeiro; BrasilFil: Barbosa, R. V.. Universidade Federal Do Rio de Janeiro. Centro Nacional de Biologia Estrutural E Bioimagem.; BrasilFil: Amorim, C. K. N.. Evandro Chagas Institute; BrasilFil: de Souza, M. P. C.. Evandro Chagas Institute; BrasilFil: Chimelli, L.. Instituto Estadual do Cérebro Paulo Niemeyer ; BrasilFil: Aguiar, R. S.. Universidade Federal do Rio de Janeiro; BrasilFil: Gonzalez, Paula Natalia. Universidad Nacional Arturo Jauretche. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Provincia de Buenos Aires. Ministerio de Salud. Hospital Alta Complejidad en Red El Cruce Dr. Néstor Carlos Kirchner Samic. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Unidad Ejecutora de Estudios en Neurociencias y Sistemas Complejos; ArgentinaFil: Lara, F. A.. Oswaldo Cruz Institute; BrasilFil: Castro, M.C.. Harvard University. Harvard School of Public Health; Estados UnidosFil: Molnár, Z.. University of Oxford; Reino UnidoFil: Lopes, R. T.. Universidade Federal do Rio de Janeiro; BrasilFil: Bozza, M. T.. Universidade Federal do Rio de Janeiro; BrasilFil: Vianez, J. L. S. G.. Evandro Chagas Institute; BrasilFil: Barbeito, Claudio Gustavo. Universidad Nacional de La Plata. Facultad de Ciencias Veterinarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata; ArgentinaFil: Cuervo, P.. Oswaldo Cruz Institute; BrasilFil: Bellio, M.. Universidade Federal do Rio de Janeiro; BrasilFil: Tanuri, A.. Universidade Federal do Rio de Janeiro; BrasilFil: Garcez, P. P.. Universidade Federal do Rio de Janeiro; Brasi

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

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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities 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 organism 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 neglected 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 lost

A Educação Ambiental na Engenharia: Projeto de Extensão de Reciclagem de Óleo Residual Coletado pelo Projeto de Extensão BioGama

As crescentes importâncias da preservação ambiental e do despertar da conscientização por parte da comunidade sobre os malefícios que o descarte incorreto de resíduos pode acarretar mostram a evidente relevância que a destinação correta do óleo usado para alimentação apresenta. A partir deste resíduo, com pouco investimento podem ser obtidos produtos com maior valor agregado, como biodiesel, sabão e derivados. São necessárias iniciativas para informar a comunidade geral de como descartar corretamente o óleo residual de fritura acarreta ao meio ambiente. Com o intuito de se promover a educação ambiental na cidade do Gama, foi proposto um projeto para que o óleo usado na comunidade do Gama - DF - Brasil seja recolhido e reciclado com fins acadêmicos, ambientais e econômicos. Este artigo demonstra o conhecimento que a comunidade do Gama-DF apresenta com relação a este resíduo, desde a existência de organizações coletoras do óleo de cozinha até os problemas causados ao meio ambiente. Como premissa do projeto BIOGAMA, nome dado para o projeto de reciclagem, alunos do curso de Engenharia de Energia propuseram meios para despertar a conscientização ambiental na comunidade por meio de campanhas educativas e coleta de óleo para que estes possam ser reaproveitados, seja produzindo-se biodiesel, sejam sabões e derivados

Impact of Early Pandemic SARS-CoV-2 Lineages Replacement with the Variant of Concern P.1 (Gamma) in Western Bahia, Brazil

Background: The correct understanding of the epidemiological dynamics of COVID-19, caused by the SARS-CoV-2, is essential for formulating public policies of disease containment. Methods: In this study, we constructed a picture of the epidemiological dynamics of COVID-19 in a Brazilian population of almost 17000 patients in 15 months. We specifically studied the fluctuations of COVID-19 cases and deaths due to COVID-19 over time according to host gender, age, viral load, and genetic variants. Results: As the main results, we observed that the numbers of COVID-19 cases and deaths due to COVID-19 fluctuated over time and that men were the most affected by deaths, as well as those of 60 or more years old. We also observed that individuals between 30- and 44-years old were the most affected by COVID-19 cases. In addition, the viral loads in the patients’ nasopharynx were higher in the early symptomatic period. We found that early pandemic SARS-CoV-2 lineages were replaced by the variant of concern (VOC) P.1 (Gamma) in the second half of the study period, which led to a significant increase in the number of deaths. Conclusions: The results presented in this study are helpful for future formulations of efficient public policies of COVID-19 containment