Novel insights into the genomic basis of citrus canker based on the genome sequences of two strains of Xanthomonas fuscans subsp. aurantifolii

Background: Citrus canker is a disease that has severe economic impact on the citrus industry worldwide. There are three types of canker, called A, B, and C. The three types have different phenotypes and affect different citrus species. The causative agent for type A is Xanthomonas citri subsp. citri, whose genome sequence was made available in 2002. Xanthomonas fuscans subsp. aurantifolii strain B causes canker B and Xanthomonas fuscans subsp. aurantifolii strain C causes canker C. Results: We have sequenced the genomes of strains B and C to draft status. We have compared their genomic content to X. citri subsp. citri and to other Xanthomonas genomes, with special emphasis on type III secreted effector repertoires. In addition to pthA, already known to be present in all three citrus canker strains, two additional effector genes, xopE3 and xopAI, are also present in all three strains and are both located on the same putative genomic island. These two effector genes, along with one other effector-like gene in the same region, are thus good candidates for being pathogenicity factors on citrus. Numerous gene content differences also exist between the three cankers strains, which can be correlated with their different virulence and host range. Particular attention was placed on the analysis of genes involved in biofilm formation and quorum sensing, type IV secretion, flagellum synthesis and motility, lipopolysacharide synthesis, and on the gene xacPNP, which codes for a natriuretic protein. Conclusion: We have uncovered numerous commonalities and differences in gene content between the genomes of the pathogenic agents causing citrus canker A, B, and C and other Xanthomonas genomes. Molecular genetics can now be employed to determine the role of these genes in plant-microbe interactions. The gained knowledge will be instrumental for improving citrus canker control.Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Conselho Nacional de Desenvolvimento CientIfico e Tecnologico (CNPq)Coordenacao para Aperfeicoamento de Pessoal de Ensino Superior (CAPES)Fundo de Defesa da Citricultura (FUNDECITRUS

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

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

Impact of vaccination on the reproductive performance of multiparous Nellore cows

Two experiments were conducted to evaluate the impact of two vaccines on the reproductive performance of multiparous beef cows in Mato Grosso do Sul, Midwest Brazil. In Experiment 1,765 calved multiparous Nellore cows were subjected to the same fixed-time artificial insemination (FTAI) protocol and rebred. Ultrasound pregnancy diagnosis was performed 30 and 90 days post-FTAI (DPI). Rates of pregnancy and pregnancy loss were determined for three periods: from 30 to 90 DPI, from 30 DPI to calving, and from 90 DPI to calving. The cows were assigned to three groups with different vaccination protocols - namely, Group VACMULT (n=250): vaccine against bovine herpesvirus 1 (BoHV-1), bovine viral diarrhea virus (BVDV), and leptospirosis; Group VACL (n=245): vaccine against leptospirosis alone; Group NOVAC (n=270): no vaccination. Serum antibody titers for BoHV-1, BVDV, and leptospirosis, measured in 57 cows from each group indicated active infection, suggesting circulation of these pathogens in the herd. No differences in pregnancy rates were observed across groups. Pregnancy loss rates did not differ significantly across groups within any of the periods investigated (30 to 90 DPI, 30 DPI to calving, or 90 DPI to calving). In Experiment 2, two vaccination protocols for each vaccine were investigated. Group VACGEST was vaccinated on day zero of FTAI (D0) and again 30 days post-FTAI (30 DPI). Group VACPREV was vaccinated on D0 and again on the day of insemination (D11). No significant difference was observed between groups, or significant gestational loss in the group that received the second vaccine on the day of insemination. The results revealed that neither vaccine interfered with the reproductive performance of multiparous cows. No differences were observed between vaccination carried out on both D0 and D11 and that performed on both D0 and D30. The performance of the IBR/BVDV/Leptospirosis vaccine on the day of the artificial insemination did not cause adverse effects on the reproductive parameters.Foram delineados dois experimentos para avaliar o impacto de duas vacinas no desempenho reprodutivo de vacas multíparas de bovinos de corte em Mato Grosso do Sul, Centro-Oeste do Brasil. No Experimento 1 foram utilizadas 765 vacas multíparas paridas da raça Nelore submetidas ao mesmo protocolo de inseminação artificial em tempo fixo (IATF) e repassadas por touros. O diagnóstico de gestação por ultrassonografia foi realizado aos 30 e 90 dias pós IATF. A prenhez e a taxa de perda de gestação foram determinadas para três períodos: de 30 a 90 DPI, de 30 DPI até para o parto e de 90 DPI até o parto. As vacas foram distribuídas em três grupos: grupo VACMULT (n=250), vacinado com vacina contra herpesvírus bovino tipo 1 (BoHV-1), vírus da diarreia viral bovina (BVDV) e leptospirose; grupo VACL (n=245), vacinado somente contra leptospirose; e grupo NOVAC (n=270), não vacinado. Títulos de anticorpos no soro de 57 vacas de cada grupo evidenciaram infecção por BoHV-1, BVDV e leptospirose, sugerindo circulação desses patógenos no rebanho. No diagnóstico por ultrassonografia, a prenhez não diferiu em nenhum dos três grupos. A taxa de perda de gestação não diferiu significantemente entre os grupos e dentro de qualquer um dos períodos investigados (30 a 90 DPI, 30 DPI até o parto ou 90 DPI até o parto). No Experimento 2 foram testados dois protocolos de vacinação usando as vacinas contra IBR/BVDV/leptospirose e somente contra leptospirose em ambos. No grupo VACGEST as vacas foram vacinas no dia zero (D0) do protocolo da IATF e 30 dias pós- IATF (30 DPI). No grupo VACPREV a primeira dose foi administrada no D0 e a segunda no mesmo dia da IATF (D11). Não houve diferença significativa entre os grupos, nem perda gestacional significativa no grupo que recebeu a segunda vacina no dia da inseminação (VACPREV). Os resultados mostram que as vacinas contra IBR/BVDV/leptospirose e somente contra leptospirose não interferiram no desempenho reprodutivo de vacas multíparas. Não houve diferença significativa entre o protocolo de vacinação empregado em D0 e D11 e aquele utilizado em D0 e 30 DPI. A realização da vacina contra IBR/BVD/leptospirose no dia da inseminação artificial não provocou efeitos adversos nos parâmetros reprodutivos