Humans distribute a wide range of microorganisms around building interiors, and some of these are potentially pathogenic. Recent research established that humans are the main drivers of the indoor microbiome and up to now significant literature has been produced about this topic. Here we analyzed differences in bacterial composition between men's and women's restrooms and other common areas within the same public building. Bacterial DNA samples were collected from restrooms and halls of a three-floor building from the Federal University of Pampa, RS, Brazil. The bacterial community was characterized by amplification of the V4 region of the 16S rRNA gene and sequencing. Throughout all samples, the most abundant phylum was Proteobacteria, followed by Actinobacteria, Bacteroidetes and Firmicutes. Beta diversity metrics showed that the structure of the bacterial communities were different among the areas and floors tested, however, only 6-9% of the variation in bacterial communities was explained by the area and floors sampled. A few microorganisms showed significantly differential abundance between men's and women's restrooms, but in general, the bacterial communities from both places were very similar. Finally, significant differences among the microbial community profile from different floors were reported, suggesting that the type of use and occupant demographic within the building may directly influence bacterial dispersion and establishment.

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Ruminal microorganisms play a pivotal role in cattle nutrition. The discovery of the main microbes responsible for enhancing the gain of weight in beef cattle might be used in therapeutic approaches to increase animal performance and cause less environmental damages. Here, we examined differences in bacterial and fungal composition of rumen samples of Braford heifers raised in a natural grassland from Pampa Biome in Brazil. We aimed to detect microbial patterns in the rumen that could be correlated with the gain of weight. 16S and ITS1 genes were amplified from ruminal samples and sequenced to identify the closest microbial relatives within the microbial communities. A predictive model based on microbes responsible for the gain of weight was build and further tested using the entire dataset. The model detected a set of microorganisms associated with animals in the high gain of weight group, including the bacterial taxa RFN20, Prevotella, Anaeroplasma and RF16 and the fungal taxa Aureobasidium, Cryptococcus, Sarocladium, Pleosporales and Tremellales. Most of these organisms have been correlated to the production of substances that improve the ruminal digestion process. These findings provide new insights about cattle nutrition and suggest the use of these microbes to improve beef cattle breeding.