No abstract

Yeasts are an important component of insect gut microbial content, playing roles such as degradation of polymers and toxic compounds, biological control, and hormone, vitamin, and digestive enzyme production. The xylophagous beetle gut is a hyperdiverse habitat and a potential source of new species with industrial abilities such as enzyme production, pentose fermentation, and biodetoxification. In this work, samples of Veturius transversus (Passalidae, Coleoptera, and Insecta) were collected from the Central Amazon Rainforest. Their guts were dissected and a total of 20 microbial colonies were isolated using sugarcane bagasse hemicellulosic hydrolysate. They were identified as having 10 distinct biochemical profiles, and genetic analysis allowed identification as three clades in the genera Candida, Williopsis, and Geotrichum. All colonies were able to assimilate D-xylose and 18 were able to produce xylitol, especially a strain of Geotrichum, with a maximum yield of 0.502 g·g−1. These results agree with a previous prediction that the microbial community associated with xylophagous insects is a promising source of species of biotechnological interest.

No abstract

The development of new generation sequencing has significantly boosted the capacity to generate genomic data, thus increasing the demand to automated genomic analysis tools. After genome sequencing and assembly, genomic annotation is performed, a process that allows the extraction of relevant data from generated sequences, highlighting the identification of protein coding genes. In order to facilitate the expansion of offline analysis of genes for resistance to heavy metals of the species Enterobacter cloacae amazonensis, the software Genomic Annotation Analysis Software-GANAS was developed, which visually details the genes and metabolic subsystems annotated using the platform RAST. The annotated genes were analyzed by software comparing the results in several organisms with known resistance to heavy metals. It was found that strain has more resistance genes than the main patterns found in the literature, thus showing the efficiency of using GANAS.