Feeding of Arapaima sp.: integrating stomach contents and local ecological knowledge

The giant arapaima (Arapaima sp.) has been described as a fish of change in Amazonia because of its important role in the conservation of floodplains, food security and income generation for rural communities. Nonetheless, despite the cultural, ecological and economic importance of arapaima, data on diet are scarce. Aiming to expand knowledge about arapaima diet in western Amazonia, scientific knowledge was integrated with the knowledge of local dwellers. During the low-water period (September 2018) and the falling-water period (June 2019), arapaima stomachs were collected from 11 floodplain lakes in the middle Juruá River. All fishes were measured [TL (total length)] and sexed. Food items from each stomach were categorized as fishes, invertebrates, plants and bone remains and weighed. Also, in the latter period, experienced local fishers were interviewed about arapaima feeding. This integrated approach revealed that young arapaima eat fish and invertebrates but adult arapaima eat fish of a wide range of species, which were mainly of low and intermediate trophic positions. This study reports the first case of cannibalism for arapaima and also shows that during the low-water period, many individuals had empty stomachs or only some small fish-bone remains and/or plant material. Arapaima sex and TL had no influence on the absence of prey in stomach contents. Overall, it can be concluded that local people had consistent ethnobiological knowledge of arapaima feeding ecology that could be useful within management projects in the region.     

Cutaneous and Mucosal Phaeohyphomycosis Caused by Exophiala spinifera in a Pregnant Patient: Case Report and Literature Review

We report a case of mucocutaneous phaeohyphomycosis caused by Exophiala spinifera. Crusty plaques and nodules were major clinical features. Histological examination revealed brown yeast-like cells and hyphae. Mycological and molecular data identified E. spinifera as etiologic agent. Oral itraconazole was effective, which was in accordance with the results of in vitro susceptibility testing. We speculated that her pregnancy may play a role of risk factor in the infection by E. spinifera.     

MicroRNAs: new players in heart failure

MicroRNAs (miRNAs) are a class of non-coding small RNAs representing one of the most exciting areas of modern medical science. miRNAs modulate a large and complex regulatory network of gene expression of the majority of the protein-coding genes. Currently, evidences suggest that miRNAs play a crucial role in the pathogenesis of heart failure. Some miRNAs as miR-1, miR-133 and miR-208a are highly expressed in the heart and strongly associated with the development of cardiac hypertrophy. Recent data indicate that these miRNAs as well as miR-206 change their expression quickly in response to physical activity. The differential regulation of miRNAs in response to exercise suggests a potential value of circulating miRNAs (c-miRNAs) as biomarkers of physiological mediators of the cardiovascular adaptation induced by exercise. Likewise, serum levels of c-miRNAs such as miR-423-5p have been evaluated as potential biomarkers in the diagnosis and prognosis of heart failure. On the other hand, the manipulation of miRNAs levels using techniques such as ‘miR mimics’ and ‘antagomiRs’ is becoming evident the enormous potential of miRNAs as promising therapeutic strategies in heart failure.     

Colonization of Madagascar periwinkle (Catharanthus roseus), by endophytes encoding gfp marker

This study reports the introduction of gfp marker in two endophytic bacterial strains (Pantoea agglomerans C33.1, isolated from cocoa, and Enterobacter cloacae PR2/7, isolated from citrus) to monitor the colonization in Madagascar perinwinkle (Catharanthus roseus). Stability of the plasmid encoding gfp was confirmed in vitro for at least 72 h of bacterial growth and after the colonization of tissues, under non-selective conditions. The colonization was observed using fluorescence microscopy and enumeration of culturable endophytes in inoculated perinwinkle plants that grew for 10 and 20 days. Gfp-expressing strains were re-isolated from the inner tissues of surface-sterilized roots and stems of inoculated plants, and the survival of the P. agglomerans C33:1gfp in plants 20 days after inoculation, even in the absence of selective pressure, suggests that is good colonizer. These results indicated that both gfp-tagged strains, especially P. agglomerans C33.1, may be useful tools to deliver enzymes or other proteins in plant.     

Diversity of Archaea in Brazilian savanna soils

Although the richness of Bacteria and Fungi in Cerrado’ soils has been reported, here we report, for the first time, the archaeal community in Cerrado’s soils. DNA extracted from soil of two distinct vegetation types, a dense subtype of sensu strict (cerrado denso) and riverbank forest (mata de galeria), was used to amplify Archaea-specific 16S rRNA gene. All of the fragments sequenced were classified as Archaea into the phylum Thaumarchaeota, predominantly affiliated to groups I.1b and I.1c. Sequences affiliated to the group I.1a were found only in the soil from riverbank forest. Soils from ‘cerrado denso’ had greater Archaea richness than those from ‘mata de galeria’ based on the richness indexes and on the rarefaction curve. β-Diversity analysis showed significant differences between the sequences from the two soil areas studied because of their different thaumarchaeal group composition. These results provide information about the third domain of life from Cerrado soils.     

Tight intramolecular regulation of the human Upf1 helicase by its N- and C-terminal domains

The RNA helicase Upf1 is a multifaceted eukaryotic enzyme involved in DNA replication, telomere metabolism and several mRNA degradation pathways. Upf1 plays a central role in nonsense-mediated mRNA decay (NMD), a surveillance process in which it links premature translation termination to mRNA degradation with its conserved partners Upf2 and Upf3. In human, both the ATP-dependent RNA helicase activity and the phosphorylation of Upf1 are essential for NMD. Upf1 activation occurs when Upf2 binds its N-terminal domain, switching the enzyme to the active form. Here, we uncovered that the C-terminal domain of Upf1, conserved in higher eukaryotes and containing several essential phosphorylation sites, also inhibits the flanking helicase domain. With different biochemical approaches we show that this domain, named SQ, directly interacts with the helicase domain to impede ATP hydrolysis and RNA unwinding. The phosphorylation sites in the distal half of the SQ domain are not directly involved in this inhibition. Therefore, in the absence of multiple binding partners, Upf1 is securely maintained in an inactive state by two intramolecular inhibition mechanisms. This study underlines the tight and intricate regulation pathways required to activate multifunctional RNA helicases like Upf1.     

Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques

Multiple sequence alignments (MSAs) have become one of the most studied approaches in bioinformatics to perform other outstanding tasks such as structure prediction, biological function analysis or next-generation sequencing. However, current MSA algorithms do not always provide consistent solutions, since alignments become increasingly difficult when dealing with low similarity sequences. As widely known, these algorithms directly depend on specific features of the sequences, causing relevant influence on the alignment accuracy. Many MSA tools have been recently designed but it is not possible to know in advance which one is the most suitable for a particular set of sequences. In this work, we analyze some of the most used algorithms presented in the bibliography and their dependences on several features. A novel intelligent algorithm based on least square support vector machine is then developed to predict how accurate each alignment could be, depending on its analyzed features. This algorithm is performed with a dataset of 2180 MSAs. The proposed system first estimates the accuracy of possible alignments. The most promising methodologies are then selected in order to align each set of sequences. Since only one selected algorithm is run, the computational time is not excessively increased.