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BACKGROUND: Early-onset neonatal sepsis (EONS) remains one of the leading causes of morbidity and mortality related to premature birth, and its diagnosis remains difficult. Our goal was to evaluate the intestinal microbiota of the first meconium of preterm newborns and ascertain whether it is associated with clinical EONS. METHODS: In a controlled, prospective cohort study, samples of the first meconium of premature infants with a gestational age (GA) ≤32 weeks was obtained at Hospital de Clínicas de Porto Alegre and DNA was isolated from the samples. 16S rDNA based microbiota composition of preterm infants with a clinical diagnosis of EONS was compared to that of a control group. RESULTS: 40 (48%) premature infants with clinical diagnosis of EONS and 44 (52%) without EONS were included in the analysis. The most abundant phylum detected in both groups, Proteobacteria, was more prevalent in the sepsis group (p = .034). 14% of variance among bacterial communities (p = .001) correlated with EONS. The genera most strongly associated with EONS were Paenibacillus, Caulobacter, Dialister, Akkermansia, Phenylobacterium, Propionibacterium, Ruminococcus, Bradyrhizobium, and Alloprevotella. A single genus, Flavobacterium, was most strongly associated with the control group. CONCLUSION: These findings suggest that the first-meconium microbiota is different in preterm neonates with and without clinical EONS.

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OBJECTIVE: To determine the differences in preterm infants' stool microbiota considering the use of exclusive own mother's milk and formula in different proportions in the first 28 days of life. METHODS: The study included newborns with GA ≤ 32 weeks divided in 5 group according the feeding regimen: 7 exclusive own mother's milk, 8 exclusive preterm formula, 16 mixed feeding with >70% own mother's milk, 16 mixed feeding with >70% preterm formula, and 15 mixed 50% own mother's milk and preterm formula. Exclusion criteria: congenital infections, congenital malformations and newborns of drug addicted mothers. Stools were collected weekly during the first 28 days. Microbial DNA extraction, 16S rRNA amplification and sequencing were performed. RESULTS: All groups were similar in perinatal and neonatal data. There were significant differences in microbial community among treatments. Approximately 37% of the variation in distance between microbial communities was explained by use of exclusive own mother´s milk only compared to other diets. The diet composed by exclusive own mother´s milk allowed for greater microbial richness (average of 85 OTUs) while diets based on preferably formula, exclusive formula, preferably maternal milk, and mixed of formula and maternal milk presented an average of 9, 29, 23, and 25 OTUs respectively. The mean proportion of the genus Escherichia and Clostridium was always greater in those containing formula than in the those with maternal milk only. CONCLUSIONS: Fecal microbiota in the neonatal period of preterm infants fed with exclusive own mother's milk presented increased richness and differences in microbial composition from those fed with different proportions of formula.

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Moisture and temperature play important roles in the assembly and functioning of prokaryotic communities in soil. However, how moisture and temperature regulate the function of niche- versus neutral-based processes during the assembly of these communities has not been examined considering both the total microbial community and the sole active portion with potential for growth in native subtropical grassland. We set up a well-controlled microcosm-based experiment to investigate the individual and combined effects of moisture and temperature on soil prokaryotic communities by simulating subtropical seasons in grassland. The prokaryotic populations with potential for growth and the total prokaryotic community were assessed by 16S rRNA transcript and 16S rRNA gene analyses, respectively. Moisture was the major factor influencing community diversity and structure, with a considerable effect of this factor on the total community. The prokaryotic populations with potential for growth and the total communities were influenced by the same assembly rules, with the niche-based mechanism being more influential in communities under dry condition. Our results provide new information regarding moisture and temperature in microbial communities of soil and elucidate how coexisting prokaryotic populations, under different physiological statuses, are shaped in native subtropical grassland soil.

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Despite increased efforts, the diverse etiologies of Necrotizing Enterocolitis (NEC) have remained largely elusive. Clinical predictors of NEC remain ill-defined and currently lack sufficient specificity. The development of a thorough understanding of initial gut microbiota colonization pattern in preterm infants might help to improve early detection or prediction of NEC and its associated morbidities. Here we compared the fecal microbiota successions, microbial diversity, abundance and structure of newborns that developed NEC with preterm controls. A 16S rRNA based microbiota analysis was conducted in a total of 132 fecal samples that included the first stool (meconium) up until the 5th week of life or NEC diagnosis from 40 preterm babies (29 controls and 11 NEC cases). A single phylotype matching closest to the Enterobacteriaceae family correlated strongly with NEC. In DNA from the sample with the greatest abundance of this phylotype additional shotgun metagenomic sequencing revealed Citrobacter koseri and Klebsiella pneumoniae as the dominating taxa. These two taxa might represent suitable microbial biomarker targets for early diagnosis of NEC. In NEC cases, we further detected lower microbial diversity and an abnormal succession of the microbial community before NEC diagnosis. Finally, we also detected a disruption in anaerobic microorganisms in the co-occurrence network of meconium samples from NEC cases. Our data suggest that a strong dominance of Citrobacter koseri and/or Klebsiella pneumoniae, low diversity, low abundance of Lactobacillus, as well as an altered microbial-network structure during the first days of life, correlate with NEC risk in preterm infants. Confirmation of these findings in other hospitals might facilitate the development of a microbiota based screening approach for early detection of NEC.

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Here, we report the draft genome sequence and annotation of Nocardia farcinica TRH1, a petroleum hydrocarbons degrading Actinobacteria isolated from the coastal water of Trindade Island, Brazil.(AU)

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Here, we report the draft genome sequence and annotation of Nocardia farcinica TRH1, a petroleum hydrocarbons degrading Actinobacteria isolated from the coastal water of Trindade Island, Brazil.

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Recent advances in science and technology are leading to a revision and re-orientation of methodologies, addressing old and current issues under a new perspective. Advances in next generation sequencing (NGS) are allowing comparative analysis of the abundance and diversity of whole microbial communities, generating a large amount of data and findings at a systems level. The current limitation for biologists has been the increasing demand for computational power and training required for processing of NGS data. Here, we describe the deployment of the Brazilian Microbiome Project Operating System (BMPOS), a flexible and user-friendly Linux distribution dedicated to microbiome studies. The Brazilian Microbiome Project (BMP) has developed data analyses pipelines for metagenomic studies (phylogenetic marker genes), conducted using the two main high-throughput sequencing platforms (Ion Torrent and Illumina MiSeq). The BMPOS is freely available and possesses the entire requirement of bioinformatics packages and databases to perform all the pipelines suggested by the BMP team. The BMPOS may be used as a bootable live USB stick or installed in any computer with at least 1 GHz CPU and 512 MB RAM, independent of the operating system previously installed. The BMPOS has proved to be effective for sequences processing, sequences clustering, alignment, taxonomic annotation, statistical analysis, and plotting of metagenomic data. The BMPOS has been used during several metagenomic analyses courses, being valuable as a tool for training, and an excellent starting point to anyone interested in performing metagenomic studies. The BMPOS and its documentation are available at http://www.brmicrobiome.org .

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Here, we present a draft genome and annotation of Rhodococcus rhodochrous TRN7, isolated from Trindade Island, Brazil, which will provide genetic data to benefit the understanding of its metabolism.

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The potential for comparing microbial community population structures has been greatly enhanced by developments in next generation sequencing methods that can generate hundreds of thousands to millions of reads in a single run. Conversely, many microbial community comparisons have been published with no more than 1,000 sequences per sample. These studies have presented data on levels of shared operational taxonomic units (OTUs) between communities. Due to lack of coverage, that approach might compromise the conclusions about microbial diversity and the degree of difference between environments. In this study, we present data from recent studies that highlight this problem. Also, we analyzed datasets of 16 rRNA sequences with small and high sequence coverage from different environments to demonstrate that the level of sequencing effort used for analyzing microbial communities biases the results. We randomly sampled pyrosequencing-generated 16S rRNA gene libraries with increasing sequence effort. Sequences were used to calculate Good's coverage, the percentage of shared OTUs, and phylogenetic distance measures. Our data showed that simple counts of presence/absence of taxonomic unities do not reflect the real similarity in membership and structure of the bacterial communities and that community comparisons based on phylogenetic tests provide a way to test statistically significant differences between two or more environments without need an exhaustive sampling effort.

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The analysis of amplified and sequenced 16S rRNA genes has become the most important single approach for microbial diversity studies. The new sequencing technologies allow for sequencing thousands of reads in a single run and a cost-effective option is split into a single run across many samples. However for this type of investigation the key question that needs to be answered is how many samples can be sequenced without biasing the results due to lack of sequence representativeness? In this work we demonstrated that the level of sequencing effort used for analyzing soil microbial communities biases the results and determines the most effective type of analysis for small and large datasets. Many simulations were performed with four independent pyrosequencing-generated 16S rRNA gene libraries from different environments. The analysis performed here illustrates the lack of resolution of OTU-based approaches for datasets with low sequence coverage. This analysis should be performed with at least 90% of sequence coverage. Diversity index values increase with sample size making normalization of the number of sequences in all samples crucial. An important finding of this study was the advantage of phylogenetic approaches for examining microbial communities with low sequence coverage. However, if the environments being compared were closely related, a deeper sequencing would be necessary to detect the variation in the microbial composition.

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The bacterial phylogenetic structure of soils from four distinctly different sites in South and North America was analyzed. One hundred and thirty-nine thousand sequences of the V9 region of the small subunit of the bacterial ribosomal RNA gene generated for a previous study were used for this work. Whereas the previous work estimated levels of species richness, this study details the degree of bacterial community overlap between the four soils. Sequences from the four soils were classified and grouped into different phyla and then assigned to operational taxonomic units (OTUs) as defined by 97 or 100% sequence similarity. Pairwise Jaccard and theta similarity indices averaged over all phyla equalled 6 and 12% respectively at the 97% similarity level, and 15% for both at the 100% similarity level. At 100 and 97% sequence similarity, 1.5 and 4.1% of OTUs were found in all four soils respectively, and 87.9 and 74.4%, respectively were a unique particular soil. These analyses, based on the largest soil bacterial sequence retrieval to date, establish the high degree of community structure difference for randomly sampled dissimilar soils and support the idea that wide sampling is important for bioprospecting. The 10 most abundant cultured genera were determined in each soil. These 10 genera comprised a significant proportion of the reads obtained from each soil (31.3-37.4%). Chitinophaga was the most abundant or the second most abundant genus in all four soils with 7.5-13.8% of the total bacterial sequences in these soils. The striking result is that several culturable genera, whose roles in soil are virtually unknown, were found among these dominant sequences.

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