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

Textile azo dye degradation by Candida rugosa INCQS 71011 isolated from a non-impacted area in Semi-Arid Region of Brazilian Northeast

The yeast Candida rugosa, deposited in the Collection of Reference Microorganisms on Health Surveillance from Oswaldo Cruz Foundation under accession number INCQS 71011, was isolated from a sediment sample from Caldeirão Escuridão, a pristine water reservoir in the surroundings of Serra da Capivara National Park, and was identified based on molecular, physiological and morphological characterization. In addition, it was tested regarding its capacity to degrade three textile azo dyes, namely Reactive Red 198, Reactive Red 141, and Reactive Blue 214 at a concentration of 100 mg l-1 during 7 days of incubation. C. rugosa INCQS 71011 was highly efficient towards two azo dyes tested, Reactive Red 198 and Reactive Red 141, demonstrating potential as a biological treatment agent of textile effluent. These results are pioneers for the yeast C. rugosa, since its degradation capacity of textile azo dyes has not yet been described. In addition, this study provides important evidence that fungi from non-impacted areas can efficiently degrade azo dyes.Key words: Fungi, taxonomic characterization, degradation, textile azo dyes

Arylfurans as potential Trypanosoma cruzi trypanothione reductase inhibitors

The natural lignans veraguensin and grandisin have been reported to be active against Trypanosoma cruzi bloodstream forms. Aiming at the total synthesis of these and related compounds, we prepared three 2-arylfurans and eight 2,5-diarylfurans. They were evaluated for their potential as T. cruzi trypanothione reductase (TR) inhibitors as well against the parasite's intracellular (amastigote) and bloodstream (trypomastigote) forms. Compound 12 was the most effective against TR with an IC50 of 48.5 μM while 7 and 14 were active against amastigotes, inhibiting the parasite development by 60% at 20 μg/ml (59 and 90 μM, respectively). On the other hand, none of the compounds was significantly active against the parasite bloodstream forms even at 250 μg/ml (0.6-1.5 mM)

Description of Dioszegia patagonica sp. nov., a novel carotenogenic yeast isolated from cold environments

During a survey of carotenogenic yeasts from cold and oligotrophic environments in Patagonia, several yeasts of the genus Dioszegia (Tremellales, Agaricomycotina) were detected, including three strains that could not be assigned to any known taxa. Analyses of internal transcribed spacer and D1/D2 regions of the large subunit rRNA gene showed these strains are conspecific with several other strains found in the Italian Alps and in Antarctica soil. Phylogenetic analyses showed that 19 of these strains represent a novel yeast species of the genus Dioszegia. The name Dioszegia patagonica sp. nov. is proposed to accommodate these strains and CRUB 1147T (UFMG 195T=CBMAI 1564T=DBVPG 10618T=CBS 14901T; MycoBank MB 819782) was designated as the type strain. This Dioszegia species accumulates biotechnologically valuable compounds such as carotenoid pigments and mycosporines.Fil: Trochine, Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales. Universidad Nacional del Comahue. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales.; ArgentinaFil: Turchetti, Benedetta. Università Degli Studi Di Perugia;Fil: Vaz, Aline B. M.. Universidade Federal Do Minas Gerais. Instituto de Cs.biologicas; BrasilFil: Brandao, Luciana. Universidade Federal Do Minas Gerais. Instituto de Cs.biologicas; BrasilFil: Rosa, Luiz H.. Universidade Federal Do Minas Gerais. Instituto de Cs.biologicas; BrasilFil: Buzzini, Pietro. Università Degli Studi Di Perugia;Fil: Rosa, Carlos. Universidade Federal do Minas Gerais; BrasilFil: Libkind, Diego. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales. Universidad Nacional del Comahue. Instituto Andino Patagónico de Tecnologías Biológicas y Geoambientales.; Argentin