An Oscillospira decrease coupled to a 2-butanone up-regulation and increases in Ruminococcus and Dorea were identified as gut microbiota signatures of NAFL onset and NAFL-NASH progression, respectively. (Hepatology 2017;65:451-464).

An imbalance in the bacterial species resulting in the loss of intestinal homeostasis has been described in inflammatory bowel diseases (IBD) and irritable bowel syndrome (IBS). In this prospective study, we investigated whether IBD and IBS patients exhibit specific changes in richness and distribution of fecal and mucosal-associated microbiota. Additionally, we assessed potential 16S rRNA gene amplicons biomarkers for IBD, IBS, and controls (CTRLs) by comparison of taxonomic composition. The relative abundance of bacteria, at phylum and genus/species levels, and the bacterial diversity were determined through 16S rRNA sequence-based fecal and mucosal microbiota analysis. Linear discriminant analysis effect size (LEfSe) was used for biomarker discovery associated to IBD and IBS as compared to CTRLs. In fecal and mucosal samples, the microbiota richness was characterized by a microbial diversity reduction, going from CTRLs to IBS to IBD. β-diversity analysis showed a clear separation between IBD and CTRLs and between IBD and IBS with no significant separation between IBS and CTRLs. β-diversity showed a clear separation between mucosa and stool samples in all the groups. In IBD, there was no difference between inflamed and not inflamed mucosa. Based upon the LEfSe data, the Anaerostipes and Ruminococcaceae were identified as the most differentially abundant bacterial taxa in CTRLs. Erysipelotrichi was identified as potential biomarker for IBS, while Gammaproteobacteria, Enterococcus , and Enterococcaceae for IBD. This study provides an overview of the alterations of microbiota and may aid in identifying potential 16S rRNA gene amplicons mucosal biomarkers for IBD and IBS.

Obesity levels, especially in children, have dramatically increased over the last few decades. Recently, several studies highlighted the involvement of gut microbiota in the pathophysiology of obesity. We investigated the composition of gut microbiota in obese adolescents and adults compared to age-matched normal weight (NW) volunteers in order to assemble age- and obesity-related microbiota profiles. The composition of gut microbiota was analyzed by 16S rRNA-based metagenomics. Ecological representations of microbial communities were computed, and univariate, multivariate, and correlation analyses performed on bacterial profiles. The prediction of metagenome functional content from 16S rRNA gene surveys was carried out. Ecological analyses revealed a dissimilarity among the subgroups, and resultant microbiota profiles differed between obese adolescents and adults. Using statistical analyses, we assigned, as microbial markers, Faecalibacterium prausnitzii and Actinomyces to the microbiota of obese adolescents, and Parabacteroides, Rikenellaceae, Bacteroides caccae, Barnesiellaceae, and Oscillospira to the microbiota of NW adolescents. The predicted metabolic profiles resulted different in adolescent groups. Particularly, biosynthesis of primary bile acid and steroid acids, metabolism of fructose, mannose, galactose, butanoate, and pentose phosphate and glycolysis/gluconeogenesis were for the majority associated to obese, while biosynthesis and metabolism of glycan, biosynthesis of secondary bile acid, metabolism of steroid hormone and lipoic acid were associated to NW adolescents. Our study revealed unique features of gut microbiota in terms of ecological patterns, microbial composition and metabolism in obese patients. The assignment of novel obesity bacterial markers may open avenues for the development of patient-tailored treatments dependent on age-related microbiota profiles.

BackgroundCystic fibrosis (CF) is a disorder affecting the respiratory, digestive, reproductive systems and sweat glands. This lethal hereditary disease has known or suspected links to the dysbiosis gut microbiota. High-throughput meta-omics-based approaches may assist in unveiling this complex network of symbiosis modifications.ObjectivesThe aim of this study was to provide a predictive and functional model of the gut microbiota enterophenotype of pediatric patients affected by CF under clinical stability.MethodsThirty-one fecal samples were collected from CF patients and healthy children (HC) (age range, 1–6 years) and analysed using targeted-metagenomics and metabolomics to characterize the ecology and metabolism of CF-linked gut microbiota. The multidimensional data were low fused and processed by chemometric classification analysis.ResultsThe fused metagenomics and metabolomics based gut microbiota profile was characterized by a high abundance of Propionibacterium, Staphylococcus and Clostridiaceae, including Clostridium difficile, and a low abundance of Eggerthella, Eubacterium, Ruminococcus, Dorea, Faecalibacterium prausnitzii, and Lachnospiraceae, associated with overexpression of 4-aminobutyrate (GABA), choline, ethanol, propylbutyrate, and pyridine and low levels of sarcosine, 4-methylphenol, uracil, glucose, acetate, phenol, benzaldehyde, and methylacetate. The CF gut microbiota pattern revealed an enterophenotype intrinsically linked to disease, regardless of age, and with dysbiosis uninduced by reduced pancreatic function and only partially related to oral antibiotic administration or lung colonization/infection.ConclusionsAll together, the results obtained suggest that the gut microbiota enterophenotypes of CF, together with endogenous and bacterial CF biomarkers, are direct expression of functional alterations at the intestinal level. Hence, it’s possible to infer that CFTR impairment causes the gut ecosystem imbalance.This new understanding of CF host-gut microbiota interactions may be helpful to rationalize novel clinical interventions to improve the affected children’s nutritional status and intestinal function.

Atopic dermatitis (AD) has been hypothesised to be associated with gut microbiota (GM) composition. We performed a comparative study of the GM profile of 19 AD children and 18 healthy individuals aimed at identifying bacterial biomarkers associated with the disease. The effect of probiotic intake (Bifidobacterium breve plus Lactobacillus salivarius) on the modulation of GM and the probiotic persistence in the GM were also evaluated. Faecal samples were analysed by real-time PCR and 16S rRNA targeted metagenomics. Although the probiotics, chosen for this study, did not shape the entire GM profile, we observed the ability of these species to pass through the gastrointestinal tract and to persist (only B. breve) in the GM. Moreover, the GM of patients compared to CTRLs showed a dysbiotic status characterised by an increase of Faecalibacterium, Oscillospira, Bacteroides, Parabacteroides and Sutterella and a reduction of short-chain fatty acid (SCFA)-producing bacteria (i.e., Bifidobacterium, Blautia, Coprococcus, Eubacterium and Propionibacterium). Taken togheter these results show an alteration in AD microbiota composition with the depletion or absence of some species, opening the way to future probiotic intervention studies.

The colonization and development of gut microbiota immediately after birth is highly variable and depends on several factors, such as delivery mode and modality of feeding during the first months of life. A cohort of 31 mother and neonate pairs, including 25 at-term caesarean (CS) and 6 vaginally (V) delivered neonates (DNs), were included in this study and 121 meconium/faecal samples were collected at days 1 through 30 following birth. Operational taxonomic units (OTUs) were assessed in 69 stool samples by phylogenetic microarray HITChip and inter- and intra-individual distributions were established by inter-OTUs correlation matrices and OTUs co-occurrence or co-exclusion networks. 1H-NMR metabolites were determined in 70 stool samples, PCA analysis was performed on 55 CS DNs samples, and metabolome/OTUs co-correlations were assessed in 45 CS samples, providing an integrated map of the early microbiota OTUs-metabolome. A microbiota “core” of OTUs was identified that was independent of delivery mode and lactation stage, suggesting highly specialized communities that act as seminal colonizers of microbial networks. Correlations among OTUs, metabolites, and OTUs-metabolites revealed metabolic profiles associated with early microbial ecological dynamics, maturation of milk components, and host physiology.

Pediatric acute-onset neuropsychiatric syndrome (PANS) and pediatric autoimmune neuropsychiatric disorders associated with streptococcal infections syndrome (PANDAS) are conditions that impair brain normal neurologic function, resulting in the sudden onset of tics, obsessive-compulsive disorder, and other behavioral symptoms. Recent studies have emphasized the crosstalk between gut and brain, highlighting how gut composition can influence behavior and brain functions. Thus, the present study investigates the relationship between PANS/PANDAS and gut microbiota ecology. The gut composition of a cohort of 30 patients with PANS/PANDAS was analyzed and compared to control subjects using 16S rRNA-based metagenomics. Data were analyzed for their α- and β-diversity; differences in bacterial distribution were detected by Wilcoxon and LEfSe tests, while metabolic profile was predicted via PICRUSt software. These analyses demonstrate the presence of an altered bacterial community structure in PANS/PANDAS patients with respect to controls. In particular, ecological analysis revealed the presence of two main clusters of subjects based on age range. Thus, to avoid age bias, data from patients and controls were split into two groups: 4–8 years old and >9 years old. The younger PANS/PANDAS group was characterized by a strong increase in Bacteroidetes; in particular, Bacteroides, Odoribacter, and Oscillospira were identified as potential microbial biomarkers of this composition type. Moreover, this group exhibited an increase of several pathways concerning the modulation of the antibody response to inflammation within the gut as well as a decrease in pathways involved in brain function (i.e., SCFA, D-alanine and tyrosine metabolism, and the dopamine pathway). The older group of patients displayed a less uniform bacterial profile, thus impairing the identification of distinct biomarkers. Finally, Pearson’s analysis between bacteria and anti-streptolysin O titer reveled a negative correlation between genera belonging to Firmicutes phylum and anti-streptolysin O while a positive correlation was observed with Odoribacter. In conclusion, this study suggests that streptococcal infections alter gut bacterial communities leading to a pro-inflammatory status through the selection of specific bacterial strains associated with gut inflammation and immune response activation. These findings highlight the possibility of studying bacterial biomarkers associated with this disorder and might led to novel potential therapeutic strategies.

Objective To assess the composition of gut microbiota in Italian and Dutch patients with juvenile idiopathic arthritis ( JIA ) at baseline, with inactive disease, and with persistent activity compared to healthy controls. Methods In a multicenter, prospective, observational cohort study, fecal samples were collected at baseline from 78 Italian and 21 Dutch treatment‐naive JIA patients with <6 months of disease duration and compared to 107 geographically matched samples from healthy children. Forty‐four follow‐up samples from patients with inactive disease and 25 follow‐up samples from patients with persistent activity were analyzed. Gut microbiota composition was determined by 16S ribosomal RNA –based metagenomics. Alpha‐ and β‐diversity were computed, and log ratios of relative abundance were compared between patients and healthy controls using random forest models and logistic regression. Results Baseline samples from Italian patients showed reduced richness compared to healthy controls ( P < 0.001). Random forest models distinguished between Italian patient baseline samples and healthy controls and suggested differences between Dutch patient samples and healthy controls (areas under the curve >0.99 and 0.71, respectively). The operational taxonomic units ( OTU s) of Erysipelotrichaceae (increased in patients) , Allobaculum (decreased in patients), and Faecalibacterium prausnitzii (increased in patients) showed different relative abundance in Italian patient baseline samples compared to controls after controlling for multiple comparisons. Some OTU s differed between Dutch patient samples and healthy controls, but no evidence remained after controlling for multiple comparisons. No differences were found in paired analysis between Italian patient baseline and inactive disease samples. Conclusion Our findings show evidence for dysbiosis in JIA patients. Only patient/control status, age, and geographic origin appear to be drivers of the microbiota profiles, regardless of disease activity stage, inflammation, and markers of autoimmunity.