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

Status de parasitas gastrintestinais em rebanho ovinos, no estado de Rondônia

Objetivou-se verificar o status de parasitas gastrintestinais em um grupo de ovinos, no estado de Rondônia. A pesquisa foi realizada em um rebanho comercial no Município de Vilhena, RO. Foram utilizados ovinos mestiços da raça Santa Inês, de diferentes sexos (machos e fêmeas) e categorias (carneiro, ovelha e cordeiro), dos quais amostras de fezes foram colhidas mensalmente, diretamente da ampola retal e analisadas por meio da contagem de ovos por grama de fezes (OPG) e de oocistos por grama de fezes (OOPG). Procedeu-se ainda a realização da coprocultura desse material para a identificação das espécies de helmintos e protozoários. O ambiente em termos de pluviosidade, umidade relativa do ar e temperatura foi avaliado, ao longo do período de estudo. As variáveis foram analisadas descritivamente. A umidade relativa e pluviosidade aumentou em função dos períodos de avaliação, enquanto que a temperatura do ambiente reduziu. Os ovinos apresentaram-se infectados por helmintos, com maiores contagens nos meses de outubro e novembro. Os gêneros de helmintos identificados nas amostras coletadas foram Haemonchus spp., Strongyloides spp. e  Trichostrongylus spp. Oocistos de Eimeria spp. foram verificados em todos os animais avaliados independente da categoria animal. Houveram diferenças na incidência de helmintos e protozoários em função da categoria animal e com o avançar do período de avaliação  os cordeiros representaram a categoria mais susceptível ao parasitismo

Cinética da degradação ruminal de dietas contendo farelo de casca de pequi

A casca de pequi é um resíduo do processamento do fruto, encontrado em grande volume nas regiões do cerrado brasileiro, que pode constituir uma alternativa para a alimentação de ruminantes. Avaliou-se a cinética da degradação ruminal da matéria seca (MS), proteína bruta (PB) e fibra em detergente neutro (FDN) do farelo da casca de pequi (FCP) e de dietas contendo diferentes níveis do resíduo em substituição ao capim-elefante (CE). Foram utilizados quatro caprinos, machos, portando cânulas ruminais, dispostos em um delineamento experimental de blocos ao acaso com parcela subdividida. Avaliaram-se os parâmetros de degradabilidade do FCP, capim-elefante e de dietas contendo 0, 10, 20 e 30% de FCP em substituição ao CE. Os alimentos foram incubados no rúmen nos tempos de 4, 8, 12, 24, 48, 72 e 96 horas. Os resultados indicaram degradação potencial da MS, PB e FDN do resíduo superiores a 90, 80 e 80%, respectivamente. A adição do FCP em substituição ao CE resultou em maior degradabilidade da matéria seca e fibra em detergente neutro, reflexo da maior fração solúvel e potencialmente degradável da MS do FCP. Para a fração protéica, a adição de FCP correlacionou-se negativamente com a fração solúvel, degradação potencial e efetiva, e positivamente com a fração insolúvel potencialmente degradável. A substituição do capim-elefante por FCP permite melhor aproveitamento da dieta, elevando o aporte de nutrientes ao animal.The pequi hulls is a waste of pequi processing, found in large volume in the Brazilian Cerrado, which may provide an alternative to ruminants' diet. This experiment was developed to evaluate the ruminal degradation kinects of dry matter (DM), crude protein (CP) and neutral detergent fiber (NDF) of pequi hulls bran (PHB) and experimental diets, with different substitution levels of elephant grass (EG) by pequi hulls bran. Four goats castrated with ruminal cannulas were used in a randomized complete block as experimental design. It was evaluated the ruminal degradation of PHB, elephant grass and four diets with 0, 10, 20 e 30% of PHB in substitution to elephant grass. The feeds were incubated in the rumen at times 4, 8, 12, 24, 48, 72 and 96 hours. The results showed that the PHB had high degradation potential DM, CP and NDF, over 90, 80 and 80% respectively. The addition of the PHB, replacing the EG, resulted in a higher degradability of dry matter and neutral detergent fiber, because the pequi waste had higher soluble and potentially degradable fraction of DM than elephant grass. The PHB addition was negatively correlated with the soluble CP and with the potential and effective degradation of the CP, and positively correlated with insoluble potentially digestible CP. The EG substitution for PHB allows better utilization of the diets, increasing the nutrient supplies to the animal

PGL I expression in live bacteria allows activation of a CD206/PPARγ cross-talk that may contribute to successful Mycobacterium leprae colonization of peripheral nerves.

Mycobacterium leprae, an obligate intracellular bacillus, infects Schwann cells (SCs), leading to peripheral nerve damage, the most severe leprosy symptom. In the present study, we revisited the involvement of phenolic glycolipid I (PGL I), an abundant, private, surface M. leprae molecule, in M. leprae-SC interaction by using a recombinant strain of M. bovis BCG engineered to express this glycolipid. We demonstrate that PGL I is essential for bacterial adhesion and SC internalization. We also show that live mycobacterium-producing PGL I induces the expression of the endocytic mannose receptor (MR/CD206) in infected cells in a peroxisome proliferator-activated receptor gamma (PPARγ)-dependent manner. Of note, blocking mannose recognition decreased bacterial entry and survival, pointing to a role for this alternative recognition pathway in bacterial pathogenesis in the nerve. Moreover, an active crosstalk between CD206 and the nuclear receptor PPARγ was detected that led to the induction of lipid droplets (LDs) formation and prostaglandin E2 (PGE2), previously described as fundamental players in bacterial pathogenesis. Finally, this pathway was shown to induce IL-8 secretion. Altogether, our study provides evidence that the entry of live M. leprae through PGL I recognition modulates the SC phenotype, favoring intracellular bacterial persistence with the concomitant secretion of inflammatory mediators that may ultimately be involved in neuroinflammation

Functional annotation of hypothetical proteins from the <i>Exiguobacterium antarcticum</i> strain B7 reveals proteins involved in adaptation to extreme environments, including high arsenic resistance

<div><p><i>Exiguobacterium antarcticum</i> strain B7 is a psychrophilic Gram-positive bacterium that possesses enzymes that can be used for several biotechnological applications. However, many proteins from its genome are considered hypothetical proteins (HPs). These functionally unknown proteins may indicate important functions regarding the biological role of this bacterium, and the use of bioinformatics tools can assist in the biological understanding of this organism through functional annotation analysis. Thus, our study aimed to assign functions to proteins previously described as HPs, present in the genome of <i>E</i>. <i>antarcticum</i> B7. We used an extensive <i>in silico</i> workflow combining several bioinformatics tools for function annotation, sub-cellular localization and physicochemical characterization, three-dimensional structure determination, and protein-protein interactions. This genome contains 2772 genes, of which 765 CDS were annotated as HPs. The amino acid sequences of all HPs were submitted to our workflow and we successfully attributed function to 132 HPs. We identified 11 proteins that play important roles in the mechanisms of adaptation to adverse environments, such as flagellar biosynthesis, biofilm formation, carotenoids biosynthesis, and others. In addition, three predicted HPs are possibly related to arsenic tolerance. Through an <i>in vitro</i> assay, we verified that <i>E</i>. <i>antarcticum</i> B7 can grow at high concentrations of this metal. The approach used was important to precisely assign function to proteins from diverse classes and to infer relationships with proteins with functions already described in the literature. This approach aims to produce a better understanding of the mechanism by which this bacterium adapts to extreme environments and to the finding of targets with biotechnological interest.</p></div

Workflow used for the annotation of the hypothetical proteins from <i>E</i>. <i>antarcticum</i> B7.

<p>Workflow used for the annotation of the hypothetical proteins from <i>E</i>. <i>antarcticum</i> B7.</p