Exploring the microbiome of two uterine sites in cows.

Bacterial communities in the mammalian reproductive system can be rich and diverse, differing in structure and quantity depending on location. In addition, its microbiome is associated with the state of health of this tract and reproductive success. This study evaluated the microbiome composition of the uterine body (UB) and uterine horn mucosa (UH) samples using 16S rRNA sequencing of samples extracted from cows in the Amazon region. It was observed that four main phyla were shared between the uterine sites: Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. Linear discriminant analysis effect size and heat tree analysis showed that members of Lachnospiraceae (NK3A20 group) and Oscillospiraceae were significantly more abundant in the UB than in UH. In addition, there are more unique genera in the UB than in the UH. A higher bacterial load in UB than in UH is expected because of the exposure to external factors of UB. However, comparing the site's communities through beta diversity did not generate well-defined clustering. Thus, it can be attributed to the closeness of the sites, which would make the niches similar ecologically and microbiologically. Therefore, this research provides knowledge to understand biomarkers in the prior reproduction period.

Glycosylation is key for enhancing drug recognition into spike glycoprotein of SARS-CoV-2.

The emergence of COVID-19 caused by SARS-CoV-2 and its spread since 2019 represents the major public health problem worldwide nowadays, which has generated a high number of infections and deaths. The spike protein (S protein) is the most studied protein of SARS-CoV-2, and key to host-cell entry through ACE2 receptor. This protein presents a large pattern of glycosylations with important roles in immunity and infection mechanisms. Therefore, understanding key aspects of the molecular mechanisms of these structures, during drug recognition in SARS-CoV-2, may contribute to therapeutic alternatives. In this work, we explored the impact of glycosylations on the drug recognition on two domains of the S protein, the receptor-binding domain (RBD) and the N-terminal domain (NTD) through molecular dynamics simulations and computational biophysics analysis. Our results show that glycosylations in the S protein induce structural stability and changes in rigidity/flexibility related to the number of glycosylations in the structure. These structural changes are important for its biological activity as well as the correct interaction of ligands in the RBD and NTD regions. Additionally, we evidenced a roto-translation phenomenon in the interaction of the ligand with RBD in the absence of glycosylation, which disappears due to the influence of glycosylation and the convergence of metastable states in RBM. Similarly, glycosylations in NTD promote an induced fit phenomenon, which is not observed in the absence of glycosylations; this process is decisive for the activity of the ligand at the cryptic site. Altogether, these results provide an explanation of glycosylation relevance in biophysical properties and drug recognition to S protein of SARS-CoV-2, which must be considered in the rational drug development and virtual screening targeting S protein.