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Crude oil extracted from oilfield reservoirs brings together hypersaline produced water. Failure in pipelines transporting this mixture causes contamination of the soil with oil and hypersaline water. Soil salinization is harmful to biological populations, impairing the biodegradation of contaminants. We simulated the contamination of a soil from an oilfield with produced water containing different concentrations of NaCl and crude oil, in order to evaluate the effect of salinity and hydrocarbon concentration on prokaryote community structure and biodegradation activity. Microcosms were incubated in CO 2 -measuring respirometer. After the incubation, residual aliphatic hydrocarbons were quantified and were performed 16S rRNA gene sequencing. An increase in CO 2 emission and hydrocarbon biodegradation was observed with increasing oil concentration up to 100 g kg -1 . Alpha diversity decreased in oil-contaminated soils with an increase in the relative abundance of Actinobacteria and reduction of Bacteroidetes with increasing oil concentration. In the NaCl-contaminated soils, alpha diversity, CO 2 emission, and hydrocarbon biodegradation decreased with increasing NaCl concentration. There was an increase in the relative abundance of Firmicutes and Proteobacteria and a reduction of Actinobacteria with increasing salt concentration. Our results highlight the need to adopt specific bioremediation strategies in soils impacted by mixtures of crude oil and hypersaline produced water.

Sequencing 16S rRNA gene amplicons is the gold standard to uncover the composition of prokaryotic communities. The presence of multiple copies of this gene makes the community abundance data distorted and gene copy normalization (GCN) necessary for correction. Even though GCN of 16S data provided a picture closer to the metagenome before, it should also be compared with communities of known composition due to the fact that library preparation is prone to methodological biases. Here, we process 16S rRNA gene amplicon data from eleven simple mock communities with DADA2 and estimate the impact of GCN. In all cases, the mock community composition derived from the 16S sequencing differs from those expected, and GCN fails to improve the classification for most of the analysed communities. Our approach provides empirical evidence that GCN does not improve the 16S target sequencing analyses in real scenarios. We therefore question the use of GCN for metataxonomic surveys until a more comprehensive catalogue of copy numbers becomes available.

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.

The Brazilian Microbiome Project (BMP) aims to assemble a Brazilian Metagenomic Consortium/Database. At present, many metagenomic projects underway in Brazil are widely known. Our goal in this initiative is to co-ordinate and standardize these together with new projects to come. It is estimated that Brazil hosts approximately 20 % of the entire world's macroorganism biological diversity. It is 1 of the 17 countries that share nearly 70 % of the world's catalogued animal and plant species, and is recognized as one of the most megadiverse countries. At the end of 2012, Brazil has joined GBIF (Global Biodiversity Information Facility), as associated member, to improve the access to the Brazilian biodiversity data in a free and open way. This was an important step toward increasing international collaboration and clearly shows the commitment of the Brazilian government in directing national policies toward sustainable development. Despite its importance, the Brazilian microbial diversity is still considered to be largely unknown, and it is clear that to maintain ecosystem dynamics and to sustainably manage land use, it is crucial to understand the biological and functional diversity of the system. This is the first attempt to collect and collate information about Brazilian microbial genetic and functional diversity in a systematic and holistic manner. The success of the BMP depends on a massive collaborative effort of both the Brazilian and international scientific communities, and therefore, we invite all colleagues to participate in this project.