Gut permeability among Astronauts during Space missions.

The space environment poses substantial challenges to human physiology, including potential disruptions in gastrointestinal health. Gut permeability has only recently become widely acknowledged for its potential to cause adverse effects on a systemic level, rendering it a critical factor to investigate in the context of spaceflight. Here, we propose that astronauts experience the onset of leaky gut during space missions supported by transcriptomic and metagenomic analysis of human and murine samples. A genetic map contributing to intestinal permeability was constructed from a systematic review of current literature. This was referenced against our re-analysis of three independent transcriptomic datasets which revealed significant changes in gene expression patterns associated with the gut barrier. Specifically, in astronauts during flight, we observed a substantial reduction in the expression genes that are crucial for intestinal barrier function, goblet cell development, gut microbiota modulation, and immune responses. Among rodent spaceflight studies, differential expression of cytokines, chemokines, and genes which regulate mucin production and post-translational modifications suggest a similar dysfunction of intestinal permeability. Metagenomic analysis of feces from two murine studies revealed a notable reduction probiotic, short chain fatty acid-producing bacteria and an increase in the Gram-negative pathogens, including Citrobacter rodentium, Enterobacter cloacea, Klebsiella aerogenes, and Proteus hauseri which promote LPS circulation, a recipe for barrier disruption and systemic inflammatory activation. These findings emphasize the critical need to understand the underlying mechanisms and develop interventions to maintain gastrointestinal health in space.

Meta-Analysis Reveals Compositional and Functional Microbial Changes Associated with Osteoporosis.

Over the past decade, the role of the gut microbiota in many disease states has gained a great deal of attention. Mounting evidence from case-control and observational studies has linked changes in the gut microbiota to the pathophysiology of osteoporosis (OP). Nonetheless, the results of these studies contain discrepancies, leaving the literature without a consensus on osteoporosis-associated microbial signatures. Here, we conducted a comprehensive meta-analysis combining and reexamining five publicly available 16S rRNA partial sequence data sets to identify gut bacteria consistently associated with osteoporosis across different cohorts. After adjusting for the batch effect associated with technical variation and heterogeneity of studies, we observed a significant shift in the microbiota composition in the osteoporosis group. An increase in the relative abundance of opportunistic pathogens Clostridium sensu stricto, Bacteroides, and Intestinibacter was observed in the OP group. Moreover, short-chain-fatty-acid (SCFA) producers, including members of the genera Collinsella, Megasphaera, Agathobaculum, Mediterraneibacter, Clostridium XIV, and Dorea, were depleted in the OP group relative to the healthy control (HC) group. Lactic acid-producing bacteria, including Limosilactobacillus, were significantly increased in the OP group. The random forest algorithm further confirmed that these bacteria differentiate the two groups. Furthermore, functional prediction revealed depletion of the SCFA biosynthesis pathway (glycolysis, tricarboxylic acid [TCA] cycle, and Wood-Ljungdahl pathway) and amino acid biosynthesis pathway (methionine, histidine, and arginine) in the OP group relative to the HC group. This study uncovered OP-associated compositional and functional microbial alterations, providing robust insight into OP pathogenesis and aiding the possible development of a therapeutic intervention to manage the disease. IMPORTANCE Osteoporosis is the most common metabolic bone disease associated with aging. Mounting evidence has linked changes in the gut microbiota to the pathophysiology of osteoporosis. However, which microbes are associated with dysbiosis and their impact on bone density and inflammation remain largely unknown due to inconsistent results in the literature. Here, we present a meta-analysis with a standard workflow, robust statistical approaches, and machine learning algorithms to identify notable microbial compositional changes influencing osteoporosis.

Saliva microbiome, dietary, and genetic markers are associated with suicidal ideation in university students.

Here, salivary microbiota and major histocompatibility complex (MHC) human leukocyte antigen (HLA) alleles were compared between 47 (12.6%) young adults with recent suicidal ideation (SI) and 325 (87.4%) controls without recent SI. Several bacterial taxa were correlated with SI after controlling for sleep issues, diet, and genetics. Four MHC class II alleles were protective for SI including DRB1*04, which was absent in every subject with SI while present in 21.7% of controls. Increased incidence of SI was observed with four other MHC class II alleles and two MHC class I alleles. Associations between these HLA alleles and salivary bacteria were also identified. Furthermore, rs10437629, previously associated with attempted suicide, was correlated here with SI and the absence of Alloprevotella rava, a producer of an organic acid known to promote brain energy homeostasis. Hence, microbial-genetic associations may be important players in the diathesis-stress model for suicidal behaviors.

From the bacterial citrus microbiome to the selection of potentially host-beneficial microbes.

Citrus is the most cultivated fruit crop worldwide. The modern citrus industry needs new bioproducts to overcome phytopathological threats, tolerate stresses and increase yield and quality. Mutualistic microbes from roots significantly impact host physiology and health and are a potentially beneficial resource. The bacterial microbiome can be surveyed to select potentially host-beneficial microbes. To achieve this goal, a prevalent "core-citrus" bacterial microbiome was obtained by picking those operational taxonomic units (OTUs) shared among samples within and across two Citrus rootstock genotypes grown in the same soil for more than 20 years. A sub-selection of main OTUs from the defined "core-citrus" microbiome was made based on abundance, host-enriched versus bulk soil, and rhizosphere-indicator species. In parallel, an extensive census of the cultivable microbiota was performed to collect a large number of bacterial citrus isolates. Metataxonomic data were linked to cultured microbes, matching 16S rRNA gene sequences from bacterial isolates with those counterpart OTU reference sequences from the selected bacterial "core-citrus" microbiome. This approach allowed selection of potentially host-beneficial bacteria to mine for agricultural probiotics in future biotechnological applications required for the citrus industry.

Meconium microbiota predicts clinical early-onset neonatal sepsis in preterm neonates.

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.

Genetic risk for autoimmunity is associated with distinct changes in the human gut microbiome.

Susceptibility to many human autoimmune diseases is under strong genetic control by class II human leukocyte antigen (HLA) allele combinations. These genes remain by far the greatest risk factors in the development of type 1 diabetes and celiac disease. Despite this, little is known about HLA influences on the composition of the human gut microbiome, a potential source of environmental influence on disease. Here, using a general population cohort from the All Babies in Southeast Sweden study, we report that genetic risk for developing type 1 diabetes autoimmunity is associated with distinct changes in the gut microbiome. Both the core microbiome and beta diversity differ with HLA risk group and genotype. In addition, protective HLA haplotypes are associated with bacterial genera Intestinibacter and Romboutsia. Thus, general population cohorts are valuable in identifying potential environmental triggers or protective factors for autoimmune diseases that may otherwise be masked by strong genetic control.

Influence of own mother's milk and different proportions of formula on intestinal microbiota of very preterm newborns.

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.

Moisture Is More Important than Temperature for Assembly of Both Potentially Active and Whole Prokaryotic Communities in Subtropical Grassland.

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.

Long-term farming systems modulate multi-trophic responses.

Soil microbiome and multi-trophic relationships are essential for the stability and functioning of agroecosystems. However, little is known about how farming systems and alternative methods for controlling plant pathogens modulate microbial communities, soil mesofauna and plant productivity. In this study, we assessed the composition of eukaryotic microbial groups using a high-throughput sequencing approach (18S rRNA gene marker), the populations of parasitic and free-living nematodes, plant productivity and their inter-relationships in long-term conventional and organic farming systems. The diversity of the fungal community increased in the organic farming system compared to the conventional farming system, whereas the diversity of the protist community was similar between the two farming systems. Compared to conventional farming, organic farming increased the population of free-living nematodes and suppressed plant parasitic nematodes belonging to Meloidogynidae and Pratylenchidae. Fungal diversity and community structure appeared to be related to nematode suppression in the system receiving organic fertilizer, which was characterized by component microbial groups known to be involved in the suppression of soil pathogens. Unraveling the microbiome and multi-trophic interactions in different farming systems may permit the management of the soil environment toward more sustainable control of plant pathogens.

BTW-Bioinformatics Through Windows: an easy-to-install package to analyze marker gene data.

Recent advances in Next-Generation Sequencing (NGS) make comparative analyses of the composition and diversity of whole microbial communities possible at a far greater depth than ever before. This brings new challenges, such as an increased dependence on computation to process these huge datasets. The demand on system resources usually requires migrating from Windows to Linux-based operating systems and prior familiarity with command-line interfaces. To overcome this barrier, we developed a fully automated and easy-to-install package as well as a complete, easy-to-follow pipeline for microbial metataxonomic analysis operating in the Windows Subsystem for Linux (WSL)-Bioinformatics Through Windows (BTW). BTW combines several open-access tools for processing marker gene data, including 16S rRNA, bringing the user from raw sequencing reads to diversity-related conclusions. It includes data quality filtering, clustering, taxonomic assignment and further statistical analyses, directly in WSL, avoiding the prior need of migrating from Windows to Linux. BTW is expected to boost the use of NGS amplicon data by facilitating rapid access to a set of bioinformatics tools for Windows users. Moreover, several Linux command line tools became more reachable, which will enhance bioinformatics accessibility to a wider range of researchers and practitioners in the life sciences and medicine. BTW is available in GitHub (https://github.com/vpylro/BTW). The package is freely available for noncommercial users.

Low Microbial Diversity and Abnormal Microbial Succession Is Associated with Necrotizing Enterocolitis in Preterm Infants.

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.

Draft genome of Nocardia farcinica TRH1, a linear and polycyclic aromatic hydrocarbon-degrading bacterium isolated from the coast of Trindade Island, Brazil.

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.

Lettuce and rhizosphere microbiome responses to growth promoting Pseudomonas species under field conditions.

Plant growth promoting rhizobacteria are well described and recommended for several crops worldwide. However, one of the most common problems in research into them is the difficulty in obtaining reproducible results. Furthermore, few studies have evaluated plant growth promotion and soil microbial community composition resulting from bacterial inoculation under field conditions. Here we evaluated the effect of 54 Pseudomonas strains on lettuce (Lactuca sativa) growth. The 12 most promising strains were phylogenetically and physiologically characterized for plant growth-promoting traits, including phosphate solubilization, hormone production and antagonism to pathogen compounds, and their effect on plant growth under farm field conditions. Additionally, the impact of beneficial strains on the rhizospheric bacterial community was evaluated for inoculated plants. The strains IAC-RBcr4 and IAC-RBru1, with different plant growth promoting traits, improved lettuce plant biomass yields up to 30%. These two strains also impacted rhizosphere bacterial groups including Isosphaera and Pirellula (phylum Planctomycetes) and Acidothermus, Pseudolabrys and Singusphaera (phylum Actinobacteria). This is the first study to demonstrate consistent results for the effects of Pseudomonas strains on lettuce growth promotion for seedlings and plants grown under tropical field conditions.

BMPOS: a Flexible and User-Friendly Tool Sets for Microbiome Studies.

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 .

Draft Genome of Rhodococcus rhodochrous TRN7, Isolated from the Coast of Trindade Island, Brazil.

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.

Low sequencing efforts bias analyses of shared taxa in microbial communities.

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.

Rethinking microbial diversity analysis in the high throughput sequencing era.

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.