Characterization of the gut bacterial and viral microbiota in latent autoimmune diabetes in adults.

Latent autoimmune diabetes in adults (LADA) is a heterogeneous disease characterized by autoantibodies against insulin producing pancreatic beta cells and initial lack of need for insulin treatment. The aim of the present study was to investigate if individuals with LADA have an altered gut microbiota relative to non-diabetic control subjects, individuals with type 1 diabetes (T1D), and individuals with type 2 diabetes (T2D). Bacterial community profiling was performed with primers targeting the variable region 4 of the 16S rRNA gene and sequenced. Amplicon sequence variants (ASVs) were generated with DADA2 and annotated to the SILVA database. The gut virome was sequenced, using a viral particle enrichment and metagenomics approach, assembled, and quantified to describe the composition of the viral community. Comparison of the bacterial alpha- and beta-diversity measures revealed that the gut bacteriome of individuals with LADA resembled that of individuals with T2D. Yet, specific genera were found to differ in abundance in individuals with LADA compared with T1D and T2D, indicating that LADA has unique taxonomical features. The virome composition reflected the stability of the most dominant order Caudovirales and the families Siphoviridae, Podoviridae, and Inoviridae, and the dominant family Microviridae. Further studies are needed to confirm these findings.

Red Meat Intake, Indole-3-Acetate, and Dorea longicatena Together Affect Insulin Resistance after Gastric Bypass.

Roux-en-Y Gastric bypass (RYGB) promotes improvement in type 2 diabetes (T2D) shortly after surgery, with metabolic mechanisms yet to be elucidated. This study aimed to investigate the relationship between food intake, tryptophan metabolism, and gut microbiota on the glycemic control of obese T2D women after RYGB surgery. Twenty T2D women who underwent RYGB were evaluated before and three months after surgery. Food intake data were obtained by a seven-day food record and a food frequency questionnaire. Tryptophan metabolites were determined by untargeted metabolomic analysis, and the gut microbiota was determined by 16S rRNA sequencing. The glycemic outcomes were fasting blood glucose, HbA1C, HOMA-IR, and HOMA-beta. Linear regression models were applied to assess the associations between the changes in food intake, tryptophan metabolism, and gut microbiota on glycemic control after RYGB. All variables changed after RYGB (p < 0.05), except for tryptophan intake. Jointly, the variation in red meat intake, plasma indole-3-acetate, and Dorea longicatena was associated with postoperative HOMA-IR {R2 0.80, R2 adj 0.74; p < 0.01}. Red meat intake decreased three months after bariatric surgery while indole-3-acetate and Dorea longicatena increased in the same period. These combined variables were associated with better insulin resistance in T2D women after RYGB.

Immunogenicity, Effectiveness, and Safety of Inactivated Virus (CoronaVac) Vaccine in a Two-Dose Primary Protocol and BNT162b2 Heterologous Booster in Brazil (Immunita-001): A One Year Period Follow Up Phase 4 Study.

Background: Effective and safe vaccines against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are critical to controlling the COVID-19 pandemic and will remain the most important tool in limiting the spread of the virus long after the pandemic is over. Methods: We bring pioneering contributions on the maintenance of the immune response over a year on a real-life basis study in 1,587 individuals (18-90 yrs, median 39 yrs; 1,208 female/379 male) who underwent vaccination with two doses of CoronaVac and BNT162b2 booster after 6-months of primary protocol. Findings: Elevated levels of anti-spike IgG antibodies were detected after CoronaVac vaccination, which significantly decreased after 80 days and remained stable until the introduction of the booster dose. Heterologous booster restored antibody titers up to-1·7-fold, changing overall seropositivity to 96%. Titers of neutralising antibodies to the Omicron variant were lower in all timepoints than those against Delta variant. Individuals presenting neutralising antibodies against Omicron also presented the highest titers against Delta and anti-Spike IgG. Cellular immune response measurement pointed out a mixed immune profile with a robust release of chemokines, cytokines, and growth factors on the first month after CoronaVac vaccination followed by a gradual reduction over time and no increase after the booster dose. A stronger interaction between those mediators was noted over time. Prior exposure to the virus leaded to a more robust cellular immune response and a rise in antibody levels 60 days post CoronaVac than in individuals with no previous COVID-19. Both vaccines were safe and well tolerated among individuals. Interpretation: Our data approach the effectiveness of CoronaVac association with BNT162b2 from the clinical and biological perspectives, aspects that have important implications for informing decisions about vaccine boosters. Funding: Fiocruz, Brazil.

Evaluating hierarchical machine learning approaches to classify biological databases.

The rate of biological data generation has increased dramatically in recent years, which has driven the importance of databases as a resource to guide innovation and the generation of biological insights. Given the complexity and scale of these databases, automatic data classification is often required. Biological data sets are often hierarchical in nature, with varying degrees of complexity, imposing different challenges to train, test and validate accurate and generalizable classification models. While some approaches to classify hierarchical data have been proposed, no guidelines regarding their utility, applicability and limitations have been explored or implemented. These include 'Local' approaches considering the hierarchy, building models per level or node, and 'Global' hierarchical classification, using a flat classification approach. To fill this gap, here we have systematically contrasted the performance of 'Local per Level' and 'Local per Node' approaches with a 'Global' approach applied to two different hierarchical datasets: BioLip and CATH. The results show how different components of hierarchical data sets, such as variation coefficient and prediction by depth, can guide the choice of appropriate classification schemes. Finally, we provide guidelines to support this process when embarking on a hierarchical classification task, which will help optimize computational resources and predictive performance.

Long COVID-19 syndrome: a 14-months longitudinal study during the two first epidemic peaks in Southeast Brazil.

BACKGROUND: A growing number of long COVID cases after infection have been reported. By definition, long COVID is the condition whereby affected individuals do not recover for several weeks or months following the onset of symptoms suggestive of COVID-19, the profile and timeline of which remains uncertain. METHODS: In this work, in-home, outpatient and hospitalized COVID-19 positive patients were monitored for up to 14 mo to establish the prevalence of long COVID symptoms and their correlation with age, pre-existing comorbidities and course of acute infection. The longitudinal study included 646 positive patients who were monitored once a month. RESULTS: From the whole population, 50.2% presented with long COVID syndrome. Twenty-three different symptoms were reported. Most frequent were fatigue (35.6%), persistent cough (34.0%), dyspnea (26.5%), loss of smell/taste (20.1%) and frequent headaches (17.3%). Mental disorders (20.7%), change in blood pressure (7.4%) and thrombosis (6.2%) were also reported. Most patients presented with 2-3 symptoms at the same time. Long COVID started after mild, moderate and severe infection in 60, 13 and 27% of cases, respectively, and it was not restricted to specific age groups. CONCLUSIONS: Older patients tended to have more severe symptoms, leading to a longer post-COVID-19 period. The presence of seven comorbidities was correlated with the severity of infection, and severity itself was the main factor that determined the duration of symptoms in long COVID cases.

Methotrexate promotes recovery of arthritis-induced alveolar bone loss and modifies the composition of the oral-gut microbiota.

OBJECTIVES: The impact of rheumatoid arthritis (RA) on the shaping of the oral and gut microbiome raises the question of whether and how RA treatment modifies microbial communities. We examined changes in the oral and gut microbiota in a mouse model of antigen-induced arthritis (AIA) treated or not with methotrexate (MTX). METHODS: Maxillae and stools were evaluated by the MiSeq platform of the V4 region of the 16S rRNA gene. Alveolar bone parameters were analysed by micro-computed tomography. Moreover, arthritis-induced changes in hyperalgesia and oedema were assessed, along with the impact on periodontal bone health. RESULTS: Microbial communities in MTX-treated AIA mice revealed distinct clusters compared to the control and AIA groups. Overall, MTX impacted the richness and variability of microorganisms in the oral-gut axis microbiome at the phylum level. Regarding the oral microbiome, while in the control group the most dominant phylum was Firmicutes, in the AIA group there was a shift towards the predominance of Campilobacteriota and Bacteroidetes associated with the disease. MTX treatment led to greater dominance of the health-associated phylum Proteobacteria. In the gut microbiome, AIA induction resulted in increased abundance of the Verrucomicrobiota phylum, and MTX treatment restored its levels compared to control. Importantly, the MTX-treated AIA animals had significantly less periodontal bone loss, as well as decreased hyperalgesia and joint oedema compared to the AIA animals. CONCLUSION: Data suggest the benefit of MTX treatment in protecting alveolar bone, in addition to providing new insights on the drug-microbiome interaction in the course of RA.

Splenic Transcriptional Responses in Severe Visceral Leishmaniasis: Impaired Leukocyte Chemotaxis and Cell Cycle Arrest.

Structural changes in the spleen have been reported in several infectious diseases. In visceral leishmaniasis (VL), a severe parasitic disease caused by Leishmania spp., the loss of white pulp accompanies a severe clinical presentation. Hamster model reproduces aspects of human VL progression. In the early stages, a transcriptomic signature of leukocyte recruitment was associated with white pulp hyperplasia. Subsequently, impaired leukocyte chemotaxis with loss of T lymphocytes in the periarteriolar lymphoid sheath occurred. This differential gene expression was subsequently corroborated by transcriptomic profiling of spleens in severe human VL. At the latest stage, spleen disorganization was associated with increasing clinical signs of VL. White pulp disruption was accompanied by decreased DLK1 expression. The expression of CXCL13, CCR5, CCL19, CCR6, CCR7 and LTA decreased, likely regulated by CDKN2A overexpression. Our findings enlighten a pathway implying cell cycle arrest and decreased gene expression involved in spleen organization.

Genomic signatures and co-occurrence patterns of the ultra-small Saccharimonadia (phylum CPR/Patescibacteria) suggest a symbiotic lifestyle.

The size of bacterial genomes is often associated with organismal metabolic capabilities determining ecological breadth and lifestyle. The recently proposed Candidate Phyla Radiation (CPR)/Patescibacteria encompasses mostly unculturable bacterial taxa with relatively small genome sizes with potential for co-metabolism interdependencies. As yet, little is known about the ecology and evolution of CPR, particularly with respect to how they might interact with other taxa. Here, we reconstructed two novel genomes (namely, Candidatus Saccharibacter sossegus and Candidatus Chaer renensis) of taxa belonging to the class Saccharimonadia within the CPR/Patescibacteria using metagenomes obtained from acid mine drainage (AMD). By testing the hypothesis of genome streamlining or symbiotic lifestyle, our results revealed clear signatures of gene losses in these genomes, such as those associated with de novo biosynthesis of essential amino acids, nucleotides, fatty acids and cofactors. In addition, co-occurrence analysis provided evidence supporting potential symbioses of these organisms with Hydrotalea sp. in the AMD system. Together, our findings provide a better understanding of the ecology and evolution of CPR/Patescibacteria and highlight the importance of genome reconstruction for studying metabolic interdependencies between unculturable Saccharimonadia representatives.

Staphylococcus epidermidis role in the skin microenvironment.

Wound healing is a complex dynamic physiological process in response to cutaneous destructive stimuli that aims to restore the cutaneous' barrier role. Deciphering the underlying mechanistic details that contribute to wound healing will create novel therapeutic strategies for skin repair. Recently, by using state-of-the-art technologies, it was revealed that the cutaneous microbiota interact with skin immune cells. Strikingly, commensal Staphylococcus epidermidis-induced CD8+ T cells induce re-epithelization of the skin after injury, accelerating wound closure. From a drug development perspective, the microbiota may provide new therapeutic candidate molecules to accelerate skin healing. Here, we summarize and evaluate recent advances in the understanding of the microbiota in the skin microenvironment.

Oral microbial dysbiosis linked to worsened periodontal condition in rheumatoid arthritis patients.

Rheumatoid arthritis (RA) is an autoimmune disease characterized by joint inflammation. Individuals with RA have a higher risk of periodontitis and periodontitis has been linked to RA through the production of enzymes by periodontal pathogens that citrullinate proteins. This linkage is supported by findings that periodontitis is associated with increased RA severity and treatment of periodontitis can improve the symptoms of RA. The possible mechanism for this association is through dysbiosis of the oral microbiota triggered by RA-induced systemic inflammation. We examined the RA status of subjects by measuring the number of tender and swollen joints, anti-citrullinated protein antibody and rheumatoid factor. Periodontal disease status and salivary cytokine levels were measured, and dental plaque analyzed by 16S rRNA high throughput sequencing. RA patients had a higher bacterial load, a more diverse microbiota, an increase in bacterial species associated with periodontal disease, more clinical attachment loss, and increased production of inflammatory mediators including IL-17, IL-2, TNF, and IFN-γ. Furthermore, changes in the oral microbiota were linked to worse RA conditions. Our study provides new insights into the bi-directional relationship between periodontitis and RA and suggest that monitoring the periodontal health of RA patients is particularly important.

MicrobiomeDB: a systems biology platform for integrating, mining and analyzing microbiome experiments.

MicrobiomeDB (http://microbiomeDB.org) is a data discovery and analysis platform that empowers researchers to fully leverage experimental variables to interrogate microbiome datasets. MicrobiomeDB was developed in collaboration with the Eukaryotic Pathogens Bioinformatics Resource Center (http://EuPathDB.org) and leverages the infrastructure and user interface of EuPathDB, which allows users to construct in silico experiments using an intuitive graphical 'strategy' approach. The current release of the database integrates microbial census data with sample details for nearly 14 000 samples originating from human, animal and environmental sources, including over 9000 samples from healthy human subjects in the Human Microbiome Project (http://portal.ihmpdcc.org/). Query results can be statistically analyzed and graphically visualized via interactive web applications launched directly in the browser, providing insight into microbial community diversity and allowing users to identify taxa associated with any experimental covariate.

Genomic Comparison among Lethal Invasive Strains of Streptococcus pyogenes Serotype M1.

Streptococcus pyogenes, also known as group A Streptococcus (GAS), is a human pathogen that causes diverse human diseases including streptococcal toxic shock syndrome (STSS). A GAS outbreak occurred in Brasilia, Brazil, during the second half of the year 2011, causing 26 deaths. Whole genome sequencing was performed using Illumina platform. The sequences were assembled and genes were predicted for comparative analysis with emm type 1 strains: MGAS5005 and M1 GAS. Genomics comparison revealed one of the invasive strains that differ from others isolates and from emm 1 reference genomes. Also, the new invasive strain showed differences in the content of virulence factors compared to other isolated in the same outbreak. The evolution of contemporary GAS strains is strongly associated with horizontal gene transfer. This is the first genomic study of a Streptococcal emm 1 outbreak in Brazil, and revealed the rapid bacterial evolution leading to new clones. The emergence of new invasive strains can be a consequence of the injudicious use of antibiotics in Brazil during the past decades.

Enterotype May Drive the Dietary-Associated Cardiometabolic Risk Factors.

Analyses of typical bacterial clusters in humans named enterotypes may facilitate understanding the host differences in the cardiometabolic profile. It stills unknown whether the three previously described enterotypes were present in populations living below the equator. We examined how the identification of enterotypes could be useful to explain the dietary associations with cardiometabolic risk factors in Brazilian subjects. In this cross-sectional study, a convenience sample of 268 adults (54.2% women) reported their dietary habits and had clinical and biological samples collected. In this study, we analyzed biochemical data and metagenomics of fecal microbiota (16SrRNA sequencing, V4 region). Continuous variables were compared using ANOVA, and categorical variables using chi-square test. Vsearch clustered the operational taxonomic units, and Silva Database provided the taxonomic signatures. Spearman coefficient was used to verify the correlation between bacteria abundances within each enterotype. One hundred subjects were classified as omnivore, 102 lacto-ovo-vegetarians, and 66 strict vegetarians. We found the same structure as the three previously described enterotypes: 111 participants were assigned to Bacteroides, 55 to Prevotella, and 102 to Ruminococcaceae enterotype. The Prevotella cluster contained higher amount of strict vegetarians individuals than the other enterotypes (40.0 vs. 20.7 and 20.6, p = 0.04). Subjects in this enterotype had a similar anthropometric profile but a lower mean LDL-c concentration than the Bacteroides enterotype (96 ± 23 vs. 109 ± 32 mg/dL, p = 0.04). We observed significant correlations between bacterial abundances and cardiometabolic risk factors, but coefficients differed depending on the enterotype. In Prevotella enterotype, Eubacterium ventriosum (r BMI = -0.33, p = 0.03, and r HDL-c = 0.33, p = 0.04), Akkermansia (r 2h glucose = -0.35, p = 0.02), Roseburia (r BMI = -0.36, p = 0.02 and r waist = -0.36, p = 0.02), and Faecalibacterium (r insulin = -0.35, p = 0.02) abundances were associated to better cardiometabolic profile. The three enterotypes previously described are present in Brazilians, supporting that those bacterial clusters are not population-specific. Diet-independent lower LDL-c levels in subjects from Prevotella than in other enterotypes suggest that a protective bacterial cluster in the former should be driving this association. Enterotypes seem to be useful to understand the impact of daily diet exposure on cardiometabolic risk factors. Prospective studies are needed to confirm their utility for predicting phenotypes in humans.

Subgingival microbiota dysbiosis in systemic lupus erythematosus: association with periodontal status.

BACKGROUND: Periodontitis results from the interaction between a subgingival biofilm and host immune response. Changes in biofilm composition are thought to disrupt homeostasis between the host and subgingival bacteria resulting in periodontal damage. Chronic systemic inflammatory disorders have been shown to affect the subgingival microbiota and clinical periodontal status. However, this relationship has not been examined in subjects with systemic lupus erythematosus (SLE). The objective of our study was to investigate the influence of SLE on the subgingival microbiota and its connection with periodontal disease and SLE activity. METHODS: We evaluated 52 patients with SLE compared to 52 subjects without SLE (control group). Subjects were classified as without periodontitis and with periodontitis. Oral microbiota composition was assessed by amplifying the V4 region of 16S rRNA gene from subgingival dental plaque DNA extracts. These amplicons were examined by Illumina MiSeq sequencing. RESULTS: SLE patients exhibited higher prevalence of periodontitis which occurred at a younger age compared to subjects of the control group. More severe forms of periodontitis were found in SLE subjects that had higher bacterial loads and decreased microbial diversity. Bacterial species frequently detected in periodontal disease were observed in higher proportions in SLE patients, even in periodontal healthy sites such as Fretibacterium, Prevotella nigrescens, and Selenomonas. Changes in the oral microbiota were linked to increased local inflammation, as demonstrated by higher concentrations of IL-6, IL-17, and IL-33 in SLE patients with periodontitis. CONCLUSIONS: SLE is associated with differences in the composition of the microbiota, independently of periodontal status.

Gut microbiota interactions with the immunomodulatory role of vitamin D in normal individuals.

BACKGROUND: Due to immunomodulatory properties, vitamin D status has been implicated in several diseases beyond the skeletal disorders. There is evidence that its deficiency deteriorates the gut barrier favoring translocation of endotoxins into the circulation and systemic inflammation. Few studies investigated whether the relationship between vitamin D status and metabolic disorders would be mediated by the gut microbiota composition. OBJECTIVE: We examined the association between vitamin D intake and circulating levels of 25(OH)D with gut microbiota composition, inflammatory markers and biochemical profile in healthy individuals. METHODS: In this cross-sectional analysis, 150 young healthy adults were stratified into tertiles of intake and concentrations of vitamin D and their clinical and inflammatory profiles were compared. The DESeq2 was used for comparisons of microbiota composition and the log2 fold changes (log2FC) represented the comparison against the reference level. The association between 25(OH)D and fecal microbiota (16S rRNA sequencing, V4 region) was tested by multiple linear regression. RESULTS: Vitamin D intake was associated with its concentration (r=0.220, p=0.008). There were no significant differences in clinical and inflammatory variables across tertiles of intake. However, lipopolysaccharides increased with the reduction of 25(OH)D (p-trend <0.05). Prevotella was more abundant (log2FC 1.67, p<0.01), while Haemophilus and Veillonella were less abundant (log2FC -2.92 and -1.46, p<0.01, respectively) in the subset with the highest vitamin D intake (reference) than that observed in the other subset (first plus second tertiles). PCR (r=-0.170, p=0.039), E-selectin (r=-0.220, p=0.007) and abundances of Coprococcus (r=-0.215, p=0.008) and Bifdobacterium (r=-0.269, p=0.001) were inversely correlated with 25(OH)D. After adjusting for age, sex, season and BMI, 25(OH)D maintained inversely associated with Coprococcus (ß=-9.414, p=0.045) and Bifdobacterium (ß=-1.881, p=0.051), but significance disappeared following the addition of inflammatory markers in the regression models. CONCLUSION: The role of vitamin D in the maintenance of immune homeostasis seems to occur in part by interacting with the gut microbiota. The attenuation of association of bacterial genera by inflammatory markers suggests that inflammation participate in part in the relationship between the gut microbiota and vitamin D concentration. Studies with appropriate design are necessary to address hypothesis raised in the current study.

Akkermansia muciniphila mediates negative effects of IFNγ on glucose metabolism.

Cross-talk between the gut microbiota and the host immune system regulates host metabolism, and its dysregulation can cause metabolic disease. Here, we show that the gut microbe Akkermansia muciniphila can mediate negative effects of IFNγ on glucose tolerance. In IFNγ-deficient mice, A. muciniphila is significantly increased and restoration of IFNγ levels reduces A. muciniphila abundance. We further show that IFNγ-knockout mice whose microbiota does not contain A. muciniphila do not show improvement in glucose tolerance and adding back A. muciniphila promoted enhanced glucose tolerance. We go on to identify Irgm1 as an IFNγ-regulated gene in the mouse ileum that controls gut A. muciniphila levels. A. muciniphila is also linked to IFNγ-regulated gene expression in the intestine and glucose parameters in humans, suggesting that this trialogue between IFNγ, A. muciniphila and glucose tolerance might be an evolutionally conserved mechanism regulating metabolic health in mice and humans.

HD5 and HBD1 variants' solvation potential energy correlates with their antibacterial activity against Escherichia coli.

The structure-activity relationship of defensins is not clear. It is known that point mutations in HD5 and HBD1 could modify their activities; however, these mutations do not seem to alter their three-dimensional structures. Here, applying molecular dynamics simulations, this relationship was studied in depth. There are modifications in flexibility, solvent accessible surface area and radius of gyration, but these properties are not reflected in the activity. Only alterations in the solvation potential energy were correlated to antibacterial activity against Escherichia coli. Data here reported could lead to a better understanding of structural and functional aspects of α- and ß-defensins.

Exercise induction of gut microbiota modifications in obese, non-obese and hypertensive rats.

BACKGROUND: Obesity is a multifactor disease associated with cardiovascular disorders such as hypertension. Recently, gut microbiota was linked to obesity pathogenesisand shown to influence the host metabolism. Moreover, several factors such as host-genotype and life-style have been shown to modulate gut microbiota composition. Exercise is a well-known agent used for the treatment of numerous pathologies, such as obesity and hypertension; it has recently been demonstrated to shape gut microbiota consortia. Since exercise-altered microbiota could possibly improve the treatment of diseases related to dysfunctional microbiota, this study aimed to examine the effect of controlled exercise training on gut microbial composition in Obese rats (n = 3), non-obese Wistar rats (n = 3) and Spontaneously Hypertensive rats (n = 3). Pyrosequencing of 16S rRNA genes from fecal samples collected before and after exercise training was used for this purpose. RESULTS: Exercise altered the composition and diversity of gut bacteria at genus level in all rat lineages. Allobaculum (Hypertensive rats), Pseudomonas and Lactobacillus (Obese rats) were shown to be enriched after exercise, while Streptococcus (Wistar rats), Aggregatibacter and Sutturella (Hypertensive rats) were more enhanced before exercise. A significant correlation was seen in the Clostridiaceae and Bacteroidaceae families and Oscillospira and Ruminococcus genera with blood lactate accumulation. Moreover, Wistar and Hypertensive rats were shown to share a similar microbiota composition, as opposed to Obese rats. Finally, Streptococcus alactolyticus, Bifidobacterium animalis, Ruminococcus gnavus, Aggregatibacter pneumotropica and Bifidobacterium pseudolongum were enriched in Obese rats. CONCLUSIONS: These data indicate that non-obese and hypertensive rats harbor a different gut microbiota from obese rats and that exercise training alters gut microbiota from an obese and hypertensive genotype background.

Enterotypes of the human gut microbiome.

Our knowledge of species and functional composition of the human gut microbiome is rapidly increasing, but it is still based on very few cohorts and little is known about variation across the world. By combining 22 newly sequenced faecal metagenomes of individuals from four countries with previously published data sets, here we identify three robust clusters (referred to as enterotypes hereafter) that are not nation or continent specific. We also confirmed the enterotypes in two published, larger cohorts, indicating that intestinal microbiota variation is generally stratified, not continuous. This indicates further the existence of a limited number of well-balanced host-microbial symbiotic states that might respond differently to diet and drug intake. The enterotypes are mostly driven by species composition, but abundant molecular functions are not necessarily provided by abundant species, highlighting the importance of a functional analysis to understand microbial communities. Although individual host properties such as body mass index, age, or gender cannot explain the observed enterotypes, data-driven marker genes or functional modules can be identified for each of these host properties. For example, twelve genes significantly correlate with age and three functional modules with the body mass index, hinting at a diagnostic potential of microbial markers.

Preimplantation development regulatory pathway construction through a text-mining approach.

BACKGROUND: The integration of sequencing and gene interaction data and subsequent generation of pathways and networks contained in databases such as KEGG Pathway is essential for the comprehension of complex biological processes. We noticed the absence of a chart or pathway describing the well-studied preimplantation development stages; furthermore, not all genes involved in the process have entries in KEGG Orthology, important information for knowledge application with relation to other organisms. RESULTS: In this work we sought to develop the regulatory pathway for the preimplantation development stage using text-mining tools such as Medline Ranker and PESCADOR to reveal biointeractions among the genes involved in this process. The genes present in the resulting pathway were also used as seeds for software developed by our group called SeedServer to create clusters of homologous genes. These homologues allowed the determination of the last common ancestor for each gene and revealed that the preimplantation development pathway consists of a conserved ancient core of genes with the addition of modern elements. CONCLUSIONS: The generation of regulatory pathways through text-mining tools allows the integration of data generated by several studies for a more complete visualization of complex biological processes. Using the genes in this pathway as "seeds" for the generation of clusters of homologues, the pathway can be visualized for other organisms. The clustering of homologous genes together with determination of the ancestry leads to a better understanding of the evolution of such process.